A key event in the development of CC is the infection by HR-HPVs. Using microarray technology, gene expression profiles in cell lines as well as keratinocytes containing HR-HPVs have been assessed (Chang & Laimins, 2000; Nees *et al.*, 2000; Nees *et al.*, 2001; Duffy *et al.*, 2003; Garner-Hamrick *et al.*, 2004; Lee *et al.*, 2004; Toussaint-Smith *et al.*, 2004). Similarly, the overall effect upon infection of cultured human keratinocytes with low-risk HPVs (LR-HPVs) has been described (Thomas *et al.*, 2001). Interestingly, in contrast to HR-HPVs, LR-HPVs induce the overexpression of a larger number of genes from the family TGF- (Tumor Growth Factor) and apparently, LR-HPVs do not suppress interferoninducible genes (Thomas *et al.*, 2001). This is very interesting as members of the TGF family play a role as tumor suppressor genes (at least at the early development of CC) and interferons are key molecules that counteract viral infections mediated by the immune system. These findings help to explain why the LR-HPVs episomes, conversely to those of

**4. Microarrays and cervical cancer**

molecular mechanisms of CC.

**4.1 Studying carcinogenesis using** *in vitro* **HPV models**

HR-HPVs, are easily eliminated in many cases.

Another important event in the carcinogenesis of CC is the integration of viral genomes into the cellular genome. It is known that upon viral DNA integration into the host genome, the E2 protein expression is usually lost. Since E2 normally represses both E6 and E7, its absence deregulates the latter oncoproteins. Using microarrays, the overall effect upon viral genome integration of HR-HPV type 16, 18, and 33 into cell lines and keratinocytes has been determined (Alazawi *et al.*, 2002; Ruutu *et al.*, 2002; Pett *et al.*, 2006). Notably, these studies found that the integration of the viral genome into the host genome is a critical step because, besides the high chromosomal instability of the infected cells, interferon-inducible genes are accordingly activated, thus eliminating the cells containing mainly viral episomes but promoting the selection of the more unstable cells.

In addition, the overall effect of expressing E2 in some cervical carcinoma cell lines has been also determined (Thierry *et al.*, 2004), inducing in some cases cellular senescence or exit to the G0 cell cycle phase (Wells *et al.*, 2003). Last but not least, the general effect of eliminating the gene E6AP, an important gene involved in the E6-mediated TP53 protein degradation, has been also assessed in multiple CC-derived (HPV+) cell lines (Kelley *et al.*, 2005). All the studies mentioned in this section have identified significant changes in the expression patterns of hundreds of genes including cyclins, kinases, oncogenes, and anti-oncogenes; some known to be involved in CC but other previously unknown, so all these gathered information is essential to systematically study the HPV-mediated CC carcinogenesis.

#### **4.2 Studying carcinogenesis using patient samples**

To identify key genes in the development of CC several strategies have been followed. Some of them had focused on the progress of the lesions while others had compared their origin, i.e. squamous and/or glandular lesions vs normal tissue. In any case, these studies had allowed the identification of gene expression profiles useful for the molecular classification and subclassification of CC.

In the first attempts to classify CC, an expression profile of only 18 differentially expressed genes involved in apoptosis, cell adhesion, and transcription regulation was found between cervical squamous cell carcinoma (SCC) and normal cervical tissue using a microarray of 588 genes (Shim *et al.*, 1998). In another interesting study, employing a 10,000-gene microarray, 40 genes allowed the classification of 34 samples of patients into a normal and a tumoral group (Wong *et al.*, 2003). Moreover, from the 34 samples, 16 could be sub-classified as patients with grade IB and IIB tumors, from which four genes displayed key expression levels in both the previous classification and subclassification, suggesting their role as possible tumor markers (Wong *et al.*, 2003). In a similar analysis but using only 1,276 genes together with 10 samples of SCC and 20 of cervical intraepithelial neoplasia grade 3 (CIN3), a gene expression profile showed that, from all the samples corresponding to CIN3, some correlated with the progression to cancer while others did not, implying the existence of a new subdivision of precancerous lesions histologically indistinguishable (Sopov *et al.*, 2004).

The selection and characterization of tumor samples is critical as this has permitted the establishment of significant gene expression differences between samples from squamous and glandular origin in both normal and pathological conditions (Contag *et al.*, 2004). Obviously, these differences arise by the transcriptional activity of genes particularly expressed in the histological subtypes of CC, but other strategies had also compared the

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 167

classified samples from patients treated with radiation and hyperthermia in two groups: sensitive and tolerant (Harima *et al.*, 2004). Importantly, not only the combined treatment offered a better prognosis than radiotherapy alone, but a long list of genes with a possible

There are other studies where samples of patients with CC were classified in radiotolerant or radiosensitive (Wong *et al.*, 2003), as well as in different radiosensitivity degrees (Tewari *et al.*, 2005). In addition, *in vitro* studies using human keratinocytes (Chen *et al.*, 2002), cervical carcinoma cell lines lacking HPV (Liu *et al.*, 2003) and harboring HPV type either 16 (Liu *et al.*, 2003; Chung *et al.*, 2005) or 18 (Crawford & Piwnica-Worms, 2001; Chaudhry *et al.*, 2003) have been also useful to improve the understanding of the molecular mechanisms that occur when tumor cells are treated with IR. Moreover, high levels of cyclin D1 mRNA (a molecule that promotes the progression of cell cycle) and low mRNA levels of the "Insulinlike Growth Factor-Binding Protein 2" or IGFBP2 (protein that can inhibit or promote tumor growth in many cancers) (Hoeflich *et al.*, 2001) correlate with a radioresistant phenotype in immortalized human keratinocytes and CC cell lines (Chen *et al.*, 2002; Liu *et al.*, 2003; Chung *et al.*, 2005). Other up-regulated genes, primarily involved in the cell cycle, that were detected in patients and radio-resistant cell lines include GAPDH (Kitahara *et al.*, 2002; Harima *et al.*, 2004), E2F3 (Chaudhry *et al.*, 2003; Liu *et al.*, 2003), DDB1 (Chaudhry *et al.*, 2003; Wong *et al.*, 2003) and ICAM5 (Achary *et al.*, 2000; Chung *et al.*, 2005). However, cyclin B1 and D1 have been determined to be overexpressed in immortalized human keratinocytes and several CC-derived radio-resistant cell lines (Chen *et al.*, 2002; Liu *et al.*, 2003), but suppressed in radiosensitive cell lines (Crawford & Piwnica-Worms, 2001; Chaudhry *et al.*,

Unfortunately, is difficult to find a clear correlation of differentially expressed genes between different microarray studies related to radiation therapy because the response is not only different in every patient, but it also depends on the dose, type, time, etc. In spite of this, other radiation-related tumor markers (Haffty & Glazer, 2003) have also been detected including cyclin D1 (CCND1), the factor vascular endothelial growth factor (VEGF) and the proliferating cell nuclear antigen (PCNA), though in isolated studies (Chen *et al.*, 2002;

Similar to radiation, there are several studies but using instead chemical agents. For example, using cell lines derived from CC with and without HPV infection, the effect of anticancer substances that stop cell cycle like lovastatin has been study in a comprehensive manner (Dimitroulakos *et al.*, 2002). Other chemicals have been used like the apoptosisinducing di-indol-methane (Carter *et al.*, 2002), catechin EGCG (found in green tea) (Ahn *et al.*, 2003), arsenic-derived (As2O3 and As4O6) (Ahn *et al.*, 2004b), and platinum-derived compounds (Gatti *et al.*, 2004) as well as the antibiotic zeocin (Hwang *et al.*, 2005). In addition, several effects exerted by chemicals that inhibit the epidermal growth factor receptor (EGFR) oncogene (Woodworth *et al.*, 2005) and phosphatidylinositol kinase (PIK3CA) (Lee *et al.*, 2006) signaling pathways had been also assessed. However, since these compounds are highly toxic, with broad action spectra, similar to those of radiotherapy, only very slight correlations of activated or deactivated genes across all these studies can be observed. For example, the expression of pro-metastatic factor JAG2 is suppressed when CC

role in the molecular mechanisms associated with therapy was obtained.

2003).

Chaudhry *et al.*, 2003; Liu *et al.*, 2003).

**4.3.2 Chemotherapy**

expression profiles between normal and squamous (Cheng *et al.*, 2002b; Chen *et al.*, 2003; Wong *et al.*, 2006) or glandular (Chen *et al.*, 2003; Fujimoto *et al.*, 2004; Chao *et al.*, 2006) tumor samples. Importantly, with a correct histological characterization of the samples, other factors can also be correlated, for example, using more than 40 samples derived from invasive CC (HPV+), it was found that a high burden of viral DNA correlates with high levels of E6 and E7 transcripts, poor prognosis, genomic instability and overexpression of more than 100 genes related to the cell cycle, from which many were identified as oncogenes and at least 50 target genes for the relevant E2F transcription factor family (Rosty *et al.*, 2005). Although the sample description in other studies has remained considerably poor (Ahn *et al.*, 2004a; Guelaguetza Vázquez-Ortíz, 2005; Santin *et al.*, 2005; Vazquez-Ortiz *et al.*, 2005a; Vazquez-Ortiz *et al.*, 2005b), these also had generated long lists of genes possibly important for the molecular study of CC.

Lastly, there are two more examples displaying the great power of microarray technology as these have enriched samples from cytological screening (Papanicolaou). For instance, by obtaining normal and cancerous cells from a cytobrush and from simple exfoliated cells, it was possible to identify known and potential tumor markers in epithelial cells (Hudelist *et al.*, 2005) and CIN3 lesions (Steinau *et al.*, 2005), respectively.

#### **4.3 Treatment**

In the CC treatment, besides surgery there is radiotherapy and chemotherapy. However, it's not possible to predict the individual response of patients. The ability of tumor cells to evade treatments suggests that there are different resistance-induced mechanisms. It is believed that by monitoring the genes involved in the resistance against therapy, will help not only to understand the molecular mechanisms of CC, but also to improve its treatment. Accordingly, depending on the gene expression profiles of tumor samples that indicate sensitivity to radiation or chemotherapy, it could be possible to classify patients, allowing a customized CC treatment (Chin *et al.*, 2005).

#### **4.3.1 Radiation**

The survival of patients diagnosed with cervical cancer has been improved by combining radiotherapy and chemotherapy. However, it has been estimated that about 65% of patients can be cured with radiation alone (Usmani *et al.*, 2005) but such patients have not been identified so far and therefore they suffer the unnecessary and lethal chemotherapy effects. The long-term goal of the first report using microarrays in combination with radiotherapy against CC, was to find a GEP that would help deciding whether a patient would benefit or not with this treatment, avoiding in this way chemotherapy (Achary *et al.*, 2000). Using a microarray of 5,776 genes, 70 identified genes allowed the differentiation of two cell lines derived from a single carcinoma, which had been previously characterized as radiosensitive and radiotolerant. Interestingly, some genes were previously associated with a cellular response against radiation, suggesting a key role in therapy resistance (Achary *et al.*, 2000). Likewise, it was possible to classify 19 samples with 100% accuracy in two groups: sensitive and tolerant to ionizing radiation (IR) by using 62 out of 23.000 (Kitahara *et al.*, 2002). Moreover, from the genes identified in the previous study, it was found that low levels of the gene XRCC5, and its corresponding protein Ku80, correlated with a good prognosis in CC patients (Harima *et al.*, 2003). Thereafter, but using instead 35 genes, the same group classified samples from patients treated with radiation and hyperthermia in two groups: sensitive and tolerant (Harima *et al.*, 2004). Importantly, not only the combined treatment offered a better prognosis than radiotherapy alone, but a long list of genes with a possible role in the molecular mechanisms associated with therapy was obtained.

There are other studies where samples of patients with CC were classified in radiotolerant or radiosensitive (Wong *et al.*, 2003), as well as in different radiosensitivity degrees (Tewari *et al.*, 2005). In addition, *in vitro* studies using human keratinocytes (Chen *et al.*, 2002), cervical carcinoma cell lines lacking HPV (Liu *et al.*, 2003) and harboring HPV type either 16 (Liu *et al.*, 2003; Chung *et al.*, 2005) or 18 (Crawford & Piwnica-Worms, 2001; Chaudhry *et al.*, 2003) have been also useful to improve the understanding of the molecular mechanisms that occur when tumor cells are treated with IR. Moreover, high levels of cyclin D1 mRNA (a molecule that promotes the progression of cell cycle) and low mRNA levels of the "Insulinlike Growth Factor-Binding Protein 2" or IGFBP2 (protein that can inhibit or promote tumor growth in many cancers) (Hoeflich *et al.*, 2001) correlate with a radioresistant phenotype in immortalized human keratinocytes and CC cell lines (Chen *et al.*, 2002; Liu *et al.*, 2003; Chung *et al.*, 2005). Other up-regulated genes, primarily involved in the cell cycle, that were detected in patients and radio-resistant cell lines include GAPDH (Kitahara *et al.*, 2002; Harima *et al.*, 2004), E2F3 (Chaudhry *et al.*, 2003; Liu *et al.*, 2003), DDB1 (Chaudhry *et al.*, 2003; Wong *et al.*, 2003) and ICAM5 (Achary *et al.*, 2000; Chung *et al.*, 2005). However, cyclin B1 and D1 have been determined to be overexpressed in immortalized human keratinocytes and several CC-derived radio-resistant cell lines (Chen *et al.*, 2002; Liu *et al.*, 2003), but suppressed in radiosensitive cell lines (Crawford & Piwnica-Worms, 2001; Chaudhry *et al.*, 2003).

Unfortunately, is difficult to find a clear correlation of differentially expressed genes between different microarray studies related to radiation therapy because the response is not only different in every patient, but it also depends on the dose, type, time, etc. In spite of this, other radiation-related tumor markers (Haffty & Glazer, 2003) have also been detected including cyclin D1 (CCND1), the factor vascular endothelial growth factor (VEGF) and the proliferating cell nuclear antigen (PCNA), though in isolated studies (Chen *et al.*, 2002; Chaudhry *et al.*, 2003; Liu *et al.*, 2003).

#### **4.3.2 Chemotherapy**

166 Topics on Cervical Cancer with an Advocacy for Prevention

expression profiles between normal and squamous (Cheng *et al.*, 2002b; Chen *et al.*, 2003; Wong *et al.*, 2006) or glandular (Chen *et al.*, 2003; Fujimoto *et al.*, 2004; Chao *et al.*, 2006) tumor samples. Importantly, with a correct histological characterization of the samples, other factors can also be correlated, for example, using more than 40 samples derived from invasive CC (HPV+), it was found that a high burden of viral DNA correlates with high levels of E6 and E7 transcripts, poor prognosis, genomic instability and overexpression of more than 100 genes related to the cell cycle, from which many were identified as oncogenes and at least 50 target genes for the relevant E2F transcription factor family (Rosty *et al.*, 2005). Although the sample description in other studies has remained considerably poor (Ahn *et al.*, 2004a; Guelaguetza Vázquez-Ortíz, 2005; Santin *et al.*, 2005; Vazquez-Ortiz *et al.*, 2005a; Vazquez-Ortiz *et al.*, 2005b), these also had generated long lists of genes possibly

Lastly, there are two more examples displaying the great power of microarray technology as these have enriched samples from cytological screening (Papanicolaou). For instance, by obtaining normal and cancerous cells from a cytobrush and from simple exfoliated cells, it was possible to identify known and potential tumor markers in epithelial cells (Hudelist *et*

In the CC treatment, besides surgery there is radiotherapy and chemotherapy. However, it's not possible to predict the individual response of patients. The ability of tumor cells to evade treatments suggests that there are different resistance-induced mechanisms. It is believed that by monitoring the genes involved in the resistance against therapy, will help not only to understand the molecular mechanisms of CC, but also to improve its treatment. Accordingly, depending on the gene expression profiles of tumor samples that indicate sensitivity to radiation or chemotherapy, it could be possible to classify patients, allowing a

The survival of patients diagnosed with cervical cancer has been improved by combining radiotherapy and chemotherapy. However, it has been estimated that about 65% of patients can be cured with radiation alone (Usmani *et al.*, 2005) but such patients have not been identified so far and therefore they suffer the unnecessary and lethal chemotherapy effects. The long-term goal of the first report using microarrays in combination with radiotherapy against CC, was to find a GEP that would help deciding whether a patient would benefit or not with this treatment, avoiding in this way chemotherapy (Achary *et al.*, 2000). Using a microarray of 5,776 genes, 70 identified genes allowed the differentiation of two cell lines derived from a single carcinoma, which had been previously characterized as radiosensitive and radiotolerant. Interestingly, some genes were previously associated with a cellular response against radiation, suggesting a key role in therapy resistance (Achary *et al.*, 2000). Likewise, it was possible to classify 19 samples with 100% accuracy in two groups: sensitive and tolerant to ionizing radiation (IR) by using 62 out of 23.000 (Kitahara *et al.*, 2002). Moreover, from the genes identified in the previous study, it was found that low levels of the gene XRCC5, and its corresponding protein Ku80, correlated with a good prognosis in CC patients (Harima *et al.*, 2003). Thereafter, but using instead 35 genes, the same group

important for the molecular study of CC.

customized CC treatment (Chin *et al.*, 2005).

**4.3 Treatment**

**4.3.1 Radiation**

*al.*, 2005) and CIN3 lesions (Steinau *et al.*, 2005), respectively.

Similar to radiation, there are several studies but using instead chemical agents. For example, using cell lines derived from CC with and without HPV infection, the effect of anticancer substances that stop cell cycle like lovastatin has been study in a comprehensive manner (Dimitroulakos *et al.*, 2002). Other chemicals have been used like the apoptosisinducing di-indol-methane (Carter *et al.*, 2002), catechin EGCG (found in green tea) (Ahn *et al.*, 2003), arsenic-derived (As2O3 and As4O6) (Ahn *et al.*, 2004b), and platinum-derived compounds (Gatti *et al.*, 2004) as well as the antibiotic zeocin (Hwang *et al.*, 2005). In addition, several effects exerted by chemicals that inhibit the epidermal growth factor receptor (EGFR) oncogene (Woodworth *et al.*, 2005) and phosphatidylinositol kinase (PIK3CA) (Lee *et al.*, 2006) signaling pathways had been also assessed. However, since these compounds are highly toxic, with broad action spectra, similar to those of radiotherapy, only very slight correlations of activated or deactivated genes across all these studies can be observed.  Di-indolymethane (Carter *et al.*, 2002) or arsenic compounds (Ahn *et al.*, 2004b), on the other hand, suppressed the transcripts of the proliferation marker PCNA.

It has been likewise reported that the transcription factor E2F4 can be suppressed by the competitive inhibition (in the ATP binding-site) of the EGFR (Woodworth *et al.*, 2005) or simply using zeocin (Hwang *et al.*, 2005). Another gene involved in cell proliferation is CHEK1, which can be suppressed by zeocin (Hwang *et al.*, 2005) and derivatives of arsenic (Ahn *et al.*, 2004b). Lastly, the membrane marker CD83 (antigen involved in immunologic response) has also been down-regulated using arsenic compounds (Ahn *et al.*, 2004b) and EGCG (Ahn *et al.*, 2003). Despite efforts to improve the prognosis of patients through the use of diverse chemotherapy regimens, radiation and their combinations, the quality of life, generally speaking, has not been yet improved significantly (Duenas-Gonzalez *et al.*, 2003). Owed to this, the search for new tumor markers and the development of drugs specifically targeted against these molecules is an important step to control CC.

#### **5. A systematic view on cervical cancer**

Systems biology (SB) seeks to explain biological phenomena through the study of networks that emerge because of the interactions of the cellular and biochemical components of a cell or organism (Kitano, 2002). This can be achieved with the aid of bioinformatics, as it allows the integration of large amounts of information that are generated every day as well as the construction of biology-oriented mathematical models. In fact, not only transcriptional network models for the understanding of cancer have been simulated, but also the integration of microarray-derived data has been a useful tool for identifying gene modules involved in different cancer-altered pathways (Segal *et al.*, 2005). Furthermore, it has been shown that cancer alterations can be better correlated when these are compared to different organisms, suggesting that combining data obtained from both cell lines and various techniques can provide more compelling ideas to understand biological phenomena.

#### **5.1 Systems biology and cervical cancer**

All available information from the cancer transcriptome could be easily correlated if the respective studies would share a universal language e.g. MIAME (Minimal Information About a Microarray Experiment) (Quackenbush, 2004).

Most microarray reports and in particular those in CC, however, contain no standardized data. Using a database and different computational tools (Kent, 2002; Wain *et al.*, 2004; Wheeler *et al.*, 2008) to assign all genes the same nomenclature, it is nonetheless possible to assess their expression levels and correlate them in different scenarios. For example, from all the aforementioned CC microarray studies, when assessing only "on"/"off" expression, we observed genes commonly found between some studies (Table 1).

Many of the genes in Table 1 have been implicated before in CC. Nevertheless, these genes can be related to other high performance techniques, such as the identification of tumor suppressor genes among a big set of genes that increase their expression during loss of tumorigenicity in HeLa cells (Mikheev *et al.*, 2004) or the quantification of transcripts present in samples of CC (Frigessi *et al.*, 2005) or normal cervix (Perez-Plasencia *et al.*, 2005).

cell lines were treated with platinum-containing compounds (Gatti *et al.*, 2004) or diindolymethane (Carter *et al.*, 2002). Di-indolymethane (Carter *et al.*, 2002) or arsenic compounds (Ahn *et al.*, 2004b), on the other hand, suppressed the transcripts of the

It has been likewise reported that the transcription factor E2F4 can be suppressed by the competitive inhibition (in the ATP binding-site) of the EGFR (Woodworth *et al.*, 2005) or simply using zeocin (Hwang *et al.*, 2005). Another gene involved in cell proliferation is CHEK1, which can be suppressed by zeocin (Hwang *et al.*, 2005) and derivatives of arsenic (Ahn *et al.*, 2004b). Lastly, the membrane marker CD83 (antigen involved in immunologic response) has also been down-regulated using arsenic compounds (Ahn *et al.*, 2004b) and EGCG (Ahn *et al.*, 2003). Despite efforts to improve the prognosis of patients through the use of diverse chemotherapy regimens, radiation and their combinations, the quality of life, generally speaking, has not been yet improved significantly (Duenas-Gonzalez *et al.*, 2003). Owed to this, the search for new tumor markers and the development of drugs specifically

Systems biology (SB) seeks to explain biological phenomena through the study of networks that emerge because of the interactions of the cellular and biochemical components of a cell or organism (Kitano, 2002). This can be achieved with the aid of bioinformatics, as it allows the integration of large amounts of information that are generated every day as well as the construction of biology-oriented mathematical models. In fact, not only transcriptional network models for the understanding of cancer have been simulated, but also the integration of microarray-derived data has been a useful tool for identifying gene modules involved in different cancer-altered pathways (Segal *et al.*, 2005). Furthermore, it has been shown that cancer alterations can be better correlated when these are compared to different organisms, suggesting that combining data obtained from both cell lines and various

techniques can provide more compelling ideas to understand biological phenomena.

All available information from the cancer transcriptome could be easily correlated if the respective studies would share a universal language e.g. MIAME (Minimal Information

Most microarray reports and in particular those in CC, however, contain no standardized data. Using a database and different computational tools (Kent, 2002; Wain *et al.*, 2004; Wheeler *et al.*, 2008) to assign all genes the same nomenclature, it is nonetheless possible to assess their expression levels and correlate them in different scenarios. For example, from all the aforementioned CC microarray studies, when assessing only "on"/"off" expression, we

Many of the genes in Table 1 have been implicated before in CC. Nevertheless, these genes can be related to other high performance techniques, such as the identification of tumor suppressor genes among a big set of genes that increase their expression during loss of tumorigenicity in HeLa cells (Mikheev *et al.*, 2004) or the quantification of transcripts present in samples of CC (Frigessi *et al.*, 2005) or normal cervix (Perez-Plasencia *et al.*, 2005).

targeted against these molecules is an important step to control CC.

**5. A systematic view on cervical cancer**

**5.1 Systems biology and cervical cancer**

About a Microarray Experiment) (Quackenbush, 2004).

observed genes commonly found between some studies (Table 1).

proliferation marker PCNA.

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 171

cancerous lesions of squamous and/or glandular origin and ultimately to death. In other words, with this model (Fig. 3) it is not only possible to correlate the up/down regulation of

Fig. 3. Cervix carcinogenesis systematic model. The various nomenclatures employed in the histopathology of cervical cancer are aligned by dashed lines and extended to key cellular and molecular events that occur during the transformation of the epithelium. The solid lines indicate a direct relationship between key events. A key event is the infection of cells in the basal membrane by HR-HPVs. These can turn into episomal bodies, which will be in charge of, on one hand, producing infective virions and, on the other, integrating into the genome of epithelial cells. Upon infection, an average of 2-3 years are necessary to develop cervical intraepithelial neoplasia of low- (CIN1/2) and/or high-grade (CIN3), often characterized by the integration of the viral genome, another key event for the disease progression as this often triggers the deregulation of the oncogenes E6 and E7, mayor chromosomal alterations and cellular immortalization. The immune system plays a key role during carcinogenesis since the majority of HR-HPV infections (80%) as well as most low-grade lesions (80%) regress. Due to this and the long periods of time between viral infection and the progression

to invasive disease, the infection by HR-HPVs is necessary but not sufficient for the

grade squamous intraepithelial lesion.

development of cervical cancer; in addition, the inactivation of anti-oncogenes (besides pRb and p53) and activation of oncogenes are necessary to consequently provoke changes at the (epi-)genomic, transcriptomic and protemic level. *D* = Displasia; L- or HSIL = Low- or High-

Table 1. Genes primarily found to be up- or down-regulated in cervical cancer across different DNA microarray platforms comparing non-pathogenic vs tumor samples and cell lines. The internationally accepted nomenclature for each gene can be found in: http://www.genenames.org/ or http://cgap.nci.nih.gov/Genes/GeneFinder.

Moreover, it is even possible to combine all this information with that derived of techniques of medium- (Nees *et al.*, 1998; Cheng *et al.*, 2002a; Brentani *et al.*, 2003; Ahn *et al.*, 2005; Ranamukhaarachchi *et al.*, 2005; Seo *et al.*, 2005; Sgarlato *et al.*, 2005) and low- (Helliwell, 2001; Keating *et al.*, 2001; Follen *et al.*, 2003; Gray & Herrington, 2004) performance in CC.

In addition, the to-be-integrated information can be further correlated with genes that have been (a) implied as potential markers in several metastatic solid tumors, including some of uterine origin (Ramaswamy *et al.*, 2003); (b) associated with cervical cancer and other kind of cancers whose somatic or germline mutations frequently favor the development of neoplasia (Forbes *et al.*, 2006); or (c) proposed as common tumor proliferation markers overexpressed across microarray reports in very diverse tumor tissues (Whitfield *et al.*, 2006). Last but not least, a more comprehensive systematic analysis of CC can be done by correlating gene upregulation mediated via the transcription factors E2F (Bracken *et al.*, 2004) and TP53 (Wei *et al.*, 2006), being this integration crucial for a general understanding of the transcriptional regulation during CC development because the functions E2F and TP53 are respectively altered by the oncoproteins E7 and E6. The idea of integrating all these additional supporting studies from many sources poses great potential in the diagnosis, prevention, and treatment of cancer as has been shown in liver carcinoma (Thorgeirsson *et al.*, 2006).

#### **5.2 Systematic model of HPV-mediated cervical carcinogenesis**

The invaluable information provided by all the aforementioned microarray-based CC reports can be related to those additional supporting studies through an integrative disease model as the HPV-mediated cervix carcinogenesis develops in a complex multiple-step process (Sherman & Kurman, 1998; Klaes *et al.*, 1999; zur Hausen, 2002; Sherman, 2003; Ahn *et al.*, 2004a; Frazer, 2004; Pett *et al.*, 2006; Snijders *et al.*, 2006). It starts with the HR-HPV infection and episomes formation thereof, followed by the production of virions and/or the integration of the viral genome into the host one that can lead to precancerous and

**Up-regulated genes in cervical cancer Down-regulated genes in cervical cancer**

*et al.*, 2005), (Santin *et al.*, 2005) SMPG (Garner-Hamrick *et al.*, 2004), (Wong *et al.*,

*et al.*, 2006), (Rosty *et al.*, 2005) PPP2R5B (Garner-Hamrick *et al.*, 2004), (Ruutu *et al.*,

*al.*, 2003), (Ahn *et al.*, 2004a) SERPINB2 (Chang & Laimins, 2000), (Ruutu *et al.*, 2002),

2004), (Rosty *et al.*, 2005), (Santin *et al.*, 2005) PI3 (Duffy *et al.*, 2003), (Alazawi *et al.*, 2002),

2003), (Rosty *et al.*, 2005), (Santin *et al.*, 2005) SPRR2B (Duffy *et al.*, 2003), (Wong *et al.*, 2006),

2006), (Santin *et al.*, 2005)

(Santin *et al.*, 2005)

2002), (Santin *et al.*, 2005)

(Santin *et al.*, 2005)

(Santin *et al.*, 2005)

(Wong *et al.*, 2006)

SULT2B1 (Chang & Laimins, 2000), (Duffy *et al.*, 2003),

*Gene References Gene References*

Table 1. Genes primarily found to be up- or down-regulated in cervical cancer across different DNA microarray platforms comparing non-pathogenic vs tumor samples and cell

Moreover, it is even possible to combine all this information with that derived of techniques of medium- (Nees *et al.*, 1998; Cheng *et al.*, 2002a; Brentani *et al.*, 2003; Ahn *et al.*, 2005; Ranamukhaarachchi *et al.*, 2005; Seo *et al.*, 2005; Sgarlato *et al.*, 2005) and low- (Helliwell, 2001; Keating *et al.*, 2001; Follen *et al.*, 2003; Gray & Herrington, 2004) performance in CC.

In addition, the to-be-integrated information can be further correlated with genes that have been (a) implied as potential markers in several metastatic solid tumors, including some of uterine origin (Ramaswamy *et al.*, 2003); (b) associated with cervical cancer and other kind of cancers whose somatic or germline mutations frequently favor the development of neoplasia (Forbes *et al.*, 2006); or (c) proposed as common tumor proliferation markers overexpressed across microarray reports in very diverse tumor tissues (Whitfield *et al.*, 2006). Last but not least, a more comprehensive systematic analysis of CC can be done by correlating gene upregulation mediated via the transcription factors E2F (Bracken *et al.*, 2004) and TP53 (Wei *et al.*, 2006), being this integration crucial for a general understanding of the transcriptional regulation during CC development because the functions E2F and TP53 are respectively altered by the oncoproteins E7 and E6. The idea of integrating all these additional supporting studies from many sources poses great potential in the diagnosis, prevention, and treatment of cancer as has been shown in liver carcinoma (Thorgeirsson *et al.*, 2006).

The invaluable information provided by all the aforementioned microarray-based CC reports can be related to those additional supporting studies through an integrative disease model as the HPV-mediated cervix carcinogenesis develops in a complex multiple-step process (Sherman & Kurman, 1998; Klaes *et al.*, 1999; zur Hausen, 2002; Sherman, 2003; Ahn *et al.*, 2004a; Frazer, 2004; Pett *et al.*, 2006; Snijders *et al.*, 2006). It starts with the HR-HPV infection and episomes formation thereof, followed by the production of virions and/or the integration of the viral genome into the host one that can lead to precancerous and

lines. The internationally accepted nomenclature for each gene can be found in: http://www.genenames.org/ or http://cgap.nci.nih.gov/Genes/GeneFinder.

**5.2 Systematic model of HPV-mediated cervical carcinogenesis**

MYBL2 (Thierry *et al.*, 2004), (Chen *et al.*, 2003), (Rosty

PRIM1 (Nees *et al.*, 2001), (Garner-Hamrick *et al.*,

RRM2 (Nees *et al.*, 2001), (Thierry *et al.*, 2004), (Wong

SPARC (Nees *et al.*, 2001), (Duffy *et al.*, 2003), (Chen *et*

TTK (Garner-Hamrick *et al.*, 2004), (Wells *et al.*,

(Garner-Hamrick *et al.*, 2004), (Toussaint-Smith *et al.*, 2004), (Wong *et al.*, 2006), (Vazquez-Ortiz *et al.*, 2005a)

VEGF

cancerous lesions of squamous and/or glandular origin and ultimately to death. In other words, with this model (Fig. 3) it is not only possible to correlate the up/down regulation of

Fig. 3. Cervix carcinogenesis systematic model. The various nomenclatures employed in the histopathology of cervical cancer are aligned by dashed lines and extended to key cellular and molecular events that occur during the transformation of the epithelium. The solid lines indicate a direct relationship between key events. A key event is the infection of cells in the basal membrane by HR-HPVs. These can turn into episomal bodies, which will be in charge of, on one hand, producing infective virions and, on the other, integrating into the genome of epithelial cells. Upon infection, an average of 2-3 years are necessary to develop cervical intraepithelial neoplasia of low- (CIN1/2) and/or high-grade (CIN3), often characterized by the integration of the viral genome, another key event for the disease progression as this often triggers the deregulation of the oncogenes E6 and E7, mayor chromosomal alterations and cellular immortalization. The immune system plays a key role during carcinogenesis since the majority of HR-HPV infections (80%) as well as most low-grade lesions (80%) regress. Due to this and the long periods of time between viral infection and the progression to invasive disease, the infection by HR-HPVs is necessary but not sufficient for the development of cervical cancer; in addition, the inactivation of anti-oncogenes (besides pRb and p53) and activation of oncogenes are necessary to consequently provoke changes at the (epi-)genomic, transcriptomic and protemic level. *D* = Displasia; L- or HSIL = Low- or Highgrade squamous intraepithelial lesion.

Depending on the study, however, the gene correlation has to be carefully done, for example, the processes of cell differentiation and senescence (Nees *et al.*, 2000; Wells *et al.*, 2003; Ranamukhaarachchi *et al.*, 2005) have been considered as anti-cell proliferation molecular events (Gandarillas, 2000). Similarly, an indirect correlation could be observed for gene activation mediated by LR-HPVs (Thomas *et al.*, 2001) but not HR-HPVs or E6 and E7 oncogene suppression (Wells *et al.*, 2003; Thierry *et al.*, 2004; Kelley *et al.*, 2005) by E2 (Dowhanick *et al.*, 1995) or RNA interference (Novina & Sharp, 2004). More importantly, nonetheless, as will be discussed in the coming subsections, this model allows the comparison of candidate tumor markers to data obtained from other CC studies at the genomic (Lazo, 1999; Wilting *et al.*, 2006), transcriptomic (Martin *et al.*, 2006), proteomic (Bae *et al.*, 2005; Choi *et al.*, 2005; Yim & Park, 2006) and epigenomic (Duenas-Gonzalez *et al.*, 2005; Sova *et al.*, 2006) level.

#### **5.3 Up-regulated candidate tumor markers**

Although many genes frequently activated in CC have been reported using microarrays, other techniques and analyses strongly suggest that these are tumor markers. This can be illustrated with the inhibitor of cyclin-dependent kinases (CDKs) *p16INK4a* or *CDKN2A*, which is involved in cell cycle and has been categorized as a tumor marker in the development of CC (Keating *et al.*, 2001). Overexpression of *p16INK4a* at both the transcript and protein level can be detected in samples of cervical dysplasia, squamous and glandular HR-HPV positive and negative lesions when compared with normal cervix by lowthroughput techniques (Martin *et al.*, 2006). As summarized in Table 2, *p16INK4a* up-regulation has been also found using medium- (Brentani *et al.*, 2003) and high-performance methods when the oncoprotein E7 is expressed in cell lines *in vitro* (Nees *et al.*, 2001; Garner-Hamrick *et al.*, 2004), in patient samples *in vivo* (Rosty *et al.*, 2005) and when comparing tumors vs normal tissue (Hudelist *et al.*, 2005; Rosty *et al.*, 2005; Santin *et al.*, 2005; Wong *et al.*, 2006).

Interestingly, *p16INK4a* is one of the genes that can display somatic mutations in CC; an abnormal status that has been linked to the development of cervical squamous cell cancer (SCC) (Forbes *et al.*, 2006). Dozens of references in the literature demonstrate that the overexpression of *p16INK4a* is useful as a CC tumor marker; however, using patient samples, others have determined transcript inactivation due to strong hypermethylation on its promoter region (Duenas-Gonzalez *et al.*, 2005). Although these findings are contradictory at first glance, some subpopulations of dysplastic cervical cells can also display epigenetic silencing of *p16INK4a* and associated low protein levels (Nuovo *et al.*, 1999). This suggests that the expression of *p16INK4a* is inhibited in some cells within the tumor, whereas its overexpression can be abundant in other cells, most probably expressing the oncoprotein E7. In spite of this, the detection of *p16INK4a* is very useful in the cytological diagnosis of CC and, furthermore, recent evidence suggests that the determination of the *p16INK4a* protein may be even more useful than the already-established HR-HPVs detection in the cytological diagnosis (Nieh *et al.*, 2005).

Another important up-regulated gene is "survivin" or *BIRC5* (Table 2). Although surviving expression is undetectable in normal adult tissues, its expression can be detected normally

specific genes upon presence/absence of HR-HPVs episomes or genome integration as well as that of the oncoproteins E6 and/or E7, but also to identify specific carcinogenesis targets. Depending on the study, however, the gene correlation has to be carefully done, for example, the processes of cell differentiation and senescence (Nees *et al.*, 2000; Wells *et al.*, 2003; Ranamukhaarachchi *et al.*, 2005) have been considered as anti-cell proliferation molecular events (Gandarillas, 2000). Similarly, an indirect correlation could be observed for gene activation mediated by LR-HPVs (Thomas *et al.*, 2001) but not HR-HPVs or E6 and E7 oncogene suppression (Wells *et al.*, 2003; Thierry *et al.*, 2004; Kelley *et al.*, 2005) by E2 (Dowhanick *et al.*, 1995) or RNA interference (Novina & Sharp, 2004). More importantly, nonetheless, as will be discussed in the coming subsections, this model allows the comparison of candidate tumor markers to data obtained from other CC studies at the genomic (Lazo, 1999; Wilting *et al.*, 2006), transcriptomic (Martin *et al.*, 2006), proteomic (Bae *et al.*, 2005; Choi *et al.*, 2005; Yim & Park, 2006) and epigenomic (Duenas-Gonzalez *et al.*,

Although many genes frequently activated in CC have been reported using microarrays, other techniques and analyses strongly suggest that these are tumor markers. This can be illustrated with the inhibitor of cyclin-dependent kinases (CDKs) *p16INK4a* or *CDKN2A*, which is involved in cell cycle and has been categorized as a tumor marker in the development of CC (Keating *et al.*, 2001). Overexpression of *p16INK4a* at both the transcript and protein level can be detected in samples of cervical dysplasia, squamous and glandular HR-HPV positive and negative lesions when compared with normal cervix by lowthroughput techniques (Martin *et al.*, 2006). As summarized in Table 2, *p16INK4a* up-regulation has been also found using medium- (Brentani *et al.*, 2003) and high-performance methods when the oncoprotein E7 is expressed in cell lines *in vitro* (Nees *et al.*, 2001; Garner-Hamrick *et al.*, 2004), in patient samples *in vivo* (Rosty *et al.*, 2005) and when comparing tumors vs normal tissue (Hudelist *et al.*, 2005; Rosty *et al.*, 2005; Santin *et al.*, 2005; Wong *et al.*, 2006).

Interestingly, *p16INK4a* is one of the genes that can display somatic mutations in CC; an abnormal status that has been linked to the development of cervical squamous cell cancer (SCC) (Forbes *et al.*, 2006). Dozens of references in the literature demonstrate that the overexpression of *p16INK4a* is useful as a CC tumor marker; however, using patient samples, others have determined transcript inactivation due to strong hypermethylation on its promoter region (Duenas-Gonzalez *et al.*, 2005). Although these findings are contradictory at first glance, some subpopulations of dysplastic cervical cells can also display epigenetic silencing of *p16INK4a* and associated low protein levels (Nuovo *et al.*, 1999). This suggests that the expression of *p16INK4a* is inhibited in some cells within the tumor, whereas its overexpression can be abundant in other cells, most probably expressing the oncoprotein E7. In spite of this, the detection of *p16INK4a* is very useful in the cytological diagnosis of CC and, furthermore, recent evidence suggests that the determination of the *p16INK4a* protein may be even more useful than the already-established HR-HPVs detection in the cytological

Another important up-regulated gene is "survivin" or *BIRC5* (Table 2). Although surviving expression is undetectable in normal adult tissues, its expression can be detected normally

2005; Sova *et al.*, 2006) level.

diagnosis (Nieh *et al.*, 2005).

**5.3 Up-regulated candidate tumor markers**

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 175

and particularly in CC (Branca *et al.*, 2005), opening promising therapeutic strategies (Altieri, 2006). Other emergent useful target genes are the members 2 and 4 from the "minichromosome maintenance deficient" complex or *MCM* found, genes primary involved in DNA replication that have been considered useful for cancer diagnosis and therapy (Rosty et al., 2005; Santin et al., 2005). Similarly, other up-regulated genes that could be specifically targeted are the 2 topoisomerase or *TOP2A* (Whitfield *et al.*, 2006), cyclin B1 or *CCNB1* (Yuan *et al.*, 2004), the kinase 1 polo type or *PLK1* (Strebhardt & Ullrich, 2006) and keratin 19 or *KRT19* (Chang *et al.*, 2005). The transcripts of the latter gene have been abundantly estimated not only in CC-derived samples (Frigessi *et al.*, 2005), but also determined as overexpressed at both the messenger (Alazawi *et al.*, 2002; Brentani *et al.*, 2003; Garner-Hamrick *et al.*, 2004; Wong *et al.*, 2006), and protein (Bae *et al.*, 2005) level in cervical neoplasia compared to normal tissue. As *KRT19*, a protein part of the intermediate filaments of epithelial cells, *KRT18* (Table

It should be noted that several genes reported in Table 2 only have been linked to CC using high and average performance techniques, such as the gene involved in the structural maintenance of chromosomes *"SMC4L1"*. As far as we known, a single report correlated the expression levels of this gene to esophageal squamous cancer (Yen *et al.*, 2005), but a genomic analysis showed that chromosomal gains in the region 3q12.1- 28 (where *SMC4L1* lies) are most common in SCC (Wilting *et al.*, 2006). This gene might be activated by E2F (Bracken *et al.*, 2004), but it is desirable to check the expression levels of SMC4L1 with lowyield techniques to determine its relevance in CC as well as for potential metastatic markers

Using microarrays and other techniques it has been possible to find genes frequently downregulated in CC, suggesting that these may play a role as tumor markers e.g. the tumor suppressor gene *p21WAF1/CIP1* or *CDKN1A*, which regulates the cell cycle via CDKs inhibition, senescence as well as TP53-dependent and -independent apoptosis (Table 3). Upon degradation or inactivation of the nuclear phosphoprotein TP53 by E6 or PLK1, respectively, the transcription of *p21WAF1/CIP1* is reduced as observed in several types of cancer (Gartel & Radhakrishnan, 2005) and particularly in CC samples using DNA microarrays (Chang & Laimins, 2000; Nees *et al.*, 2000; Nees *et al.*, 2001; Duffy *et al.*, 2003; Wells *et al.*, 2003; Thierry *et al.*, 2004; Kelley *et al.*, 2005). In addition, it has been suggested that low *p21WAF1/CIP1* expression correlates with poor prognosis in cervical adenocarcinoma (AC) (Lu *et al.*, 1998). Moreover, in samples derived from CC it has been observed a decrease in cell growth and induction of *p21WAF1/CIP1* by platinum-based chemotherapy (Gatti *et al.*, 2004) as well as

Other down-regulated genes in CC include the gene desmoglein 1 or *DSG1*, which encodes a protein involved in the homeostasis of cell-cell epithelial junctions and belongs to the family of "cadherins", proteins whose expression decreases as it progresses in many kinds of cancers, such as cervical cancer (de Boer *et al.*, 1999). It has been determined that the expression of *DSG1* increases in presence of LR-HPVs episomal bodies in human keratinocytes, but its expression levels highly decrease when HR-HPV episomes are present in cell lines and SCC samples. Moreover, DSG1 importantly lies in an area that often presents chromosomal losses during CC (Table 3) and has been assigned as a pro-apoptotic

2) could likewise play an important role in the molecular diagnosis of cancer.

like LMNB1 or proliferation ones like MAD2L1 gene (Table 2).

radioimmunotherapy directed against KRT19 (Chang *et al.*, 2005).

factor mediated by the caspase 3 in keratinocytes (Dusek *et al.*, 2006).

**5.4 Down-regulated candidate tumor markers**

Table 2. Genes frequently reported as up-regulated in cervical cancer (CC). A) For each biological process, genes are listed in descending order by the mayor number of reports related to CC e.g. the gene MKI67 has been reported at least 190 times in CC. Genes in bold have been used as therapeutic targets in cancer, whereas genes in italics are not so known in CC. The chromosomal localization of the gene is shown in brackets. B) Techniques of highthroughput are DNA microarrays; medium- DD, RDA and ESTs; and low- are tumor markers previously defined in CC. C) Genes proposed as metastasis markers (in solid tumors), tumoral cancer markers (due to frequent mutations) and proliferation markers (large number of cancers). D) Transcription factor (TF) that might regulate the corresponding gene. E) The analysis of the genome refers to the most common chromosomal gains in CC (1q, 3q, 5p, 8q, 20q and Xq); transcriptome to the importance of genes in CC; proteome to overexpressed proteins in CC and; epigenome to genes whose promoter has been found methylated in samples derived from CC. For gene nomenclature see Table 1.

in embryogenesis and abnormally in cancer (mainly inhibiting apoptosis). Due to this, survivin has been generally proposed as a proliferation tumor marker in cancer (Whitfield *et al.*, 2006)

(Brentani *et al.*, 2003) (Sgarlato *et al.*, 2005)

(Brentani *et al.*,

(Brentani *et al.*, 2003) (Sgarlato *et al.*, 2005)

(Brentani *et al.*,

(Brentani *et al.*,

Table 2. Genes frequently reported as up-regulated in cervical cancer (CC). A) For each biological process, genes are listed in descending order by the mayor number of reports related to CC e.g. the gene MKI67 has been reported at least 190 times in CC. Genes in bold have been used as therapeutic targets in cancer, whereas genes in italics are not so known in CC. The chromosomal localization of the gene is shown in brackets. B) Techniques of highthroughput are DNA microarrays; medium- DD, RDA and ESTs; and low- are tumor markers previously defined in CC. C) Genes proposed as metastasis markers (in solid tumors), tumoral cancer markers (due to frequent mutations) and proliferation markers

(large number of cancers). D) Transcription factor (TF) that might regulate the

corresponding gene. E) The analysis of the genome refers to the most common chromosomal gains in CC (1q, 3q, 5p, 8q, 20q and Xq); transcriptome to the importance of genes in CC; proteome to overexpressed proteins in CC and; epigenome to genes whose promoter has been found methylated in samples derived from CC. For gene nomenclature see Table 1.

in embryogenesis and abnormally in cancer (mainly inhibiting apoptosis).  Other emergent useful target genes are the members 2 and 4 from the "minichromosome maintenance deficient" complex or *MCM* found, genes primary involved in DNA replication that have been considered useful for cancer diagnosis and therapy (Rosty et al., 2005; Santin et al., 2005). Similarly, other up-regulated genes that could be specifically targeted are the 2 topoisomerase or *TOP2A* (Whitfield *et al.*, 2006), cyclin B1 or *CCNB1* (Yuan *et al.*, 2004), the kinase 1 polo type or *PLK1* (Strebhardt & Ullrich, 2006) and keratin 19 or *KRT19* (Chang *et al.*, 2005). The transcripts of the latter gene have been abundantly estimated not only in CC-derived samples (Frigessi *et al.*, 2005), but also determined as overexpressed at both the messenger (Alazawi *et al.*, 2002; Brentani *et al.*, 2003; Garner-Hamrick *et al.*, 2004; Wong *et al.*, 2006), and protein (Bae *et al.*, 2005) level in cervical neoplasia compared to normal tissue. As *KRT19*, a protein part of the intermediate filaments of epithelial cells, *KRT18* (Table 2) could likewise play an important role in the molecular diagnosis of cancer.

It should be noted that several genes reported in Table 2 only have been linked to CC using high and average performance techniques, such as the gene involved in the structural maintenance of chromosomes *"SMC4L1"*. As far as we known, a single report correlated the expression levels of this gene to esophageal squamous cancer (Yen *et al.*, 2005), but a genomic analysis showed that chromosomal gains in the region 3q12.1- 28 (where *SMC4L1* lies) are most common in SCC (Wilting *et al.*, 2006). This gene might be activated by E2F (Bracken *et al.*, 2004), but it is desirable to check the expression levels of SMC4L1 with lowyield techniques to determine its relevance in CC as well as for potential metastatic markers like LMNB1 or proliferation ones like MAD2L1 gene (Table 2).

#### **5.4 Down-regulated candidate tumor markers**

Using microarrays and other techniques it has been possible to find genes frequently downregulated in CC, suggesting that these may play a role as tumor markers e.g. the tumor suppressor gene *p21WAF1/CIP1* or *CDKN1A*, which regulates the cell cycle via CDKs inhibition, senescence as well as TP53-dependent and -independent apoptosis (Table 3). Upon degradation or inactivation of the nuclear phosphoprotein TP53 by E6 or PLK1, respectively, the transcription of *p21WAF1/CIP1* is reduced as observed in several types of cancer (Gartel & Radhakrishnan, 2005) and particularly in CC samples using DNA microarrays (Chang & Laimins, 2000; Nees *et al.*, 2000; Nees *et al.*, 2001; Duffy *et al.*, 2003; Wells *et al.*, 2003; Thierry *et al.*, 2004; Kelley *et al.*, 2005). In addition, it has been suggested that low *p21WAF1/CIP1* expression correlates with poor prognosis in cervical adenocarcinoma (AC) (Lu *et al.*, 1998). Moreover, in samples derived from CC it has been observed a decrease in cell growth and induction of *p21WAF1/CIP1* by platinum-based chemotherapy (Gatti *et al.*, 2004) as well as radioimmunotherapy directed against KRT19 (Chang *et al.*, 2005).

Other down-regulated genes in CC include the gene desmoglein 1 or *DSG1*, which encodes a protein involved in the homeostasis of cell-cell epithelial junctions and belongs to the family of "cadherins", proteins whose expression decreases as it progresses in many kinds of cancers, such as cervical cancer (de Boer *et al.*, 1999). It has been determined that the expression of *DSG1* increases in presence of LR-HPVs episomal bodies in human keratinocytes, but its expression levels highly decrease when HR-HPV episomes are present in cell lines and SCC samples. Moreover, DSG1 importantly lies in an area that often presents chromosomal losses during CC (Table 3) and has been assigned as a pro-apoptotic factor mediated by the caspase 3 in keratinocytes (Dusek *et al.*, 2006).

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 177

(Seo *et al.*,

2004), (Wong *et al.*, 2006) - - (Ramaswamy

(Brentani *et*

represent increased expression levels upon different schemes of radio and/or chemotherapy, whereas genes in *italics* are not so known in CC. The chromosomal

Table 3. Genes frequently reported as down-regulated in cervical cancer (CC). A) For each biological process, genes are listed in descending order by the mayor number of reports related to CC e.g. the gene *CDKN1A* has been reported at least 70 times in CC. Genes in bold

localization of the gene is shown in brackets. B) Techniques of high-throughput are mainly DNA microarrays; medium- DD, and ESTs; and low- are tumor markers previously defined in CC. C) Genes proposed as metastasis markers (in solid tumors) and tumoral cancer markers (due to frequent mutations). D) Transcription factor (TF) that might regulate the corresponding gene. E) The analysis of the genome refers to the most common chromosomal alterations in CC (2q, 3p, 4p, 5p, 5q, 6p, 6q, 11q, 13q, 18q and 19q). For gene nomenclature

Another gene that could be of interest in CC is *SERPINB2*. The gene product is an inhibitor of the serine-type proteases like the plasminogen activator (also known as *PLAU*). On one hand, *SERPINB2* suppression has been determined using both microarrays as well as genomic studies in CC (Table 3); but on the other, its expression in HeLa cells can stabilize the expression levels of the Rb protein and suppress the oncoproteins E6 and E7 of HPV18 (Darnell *et al.*, 2005). This suggests that low levels of *SERPINB2* promote CC development,

Of genes not known in CC there are several examples, being the gene *TRIM22* or "tripartite motif-containing 22", which has been found down-regulated in at least 6

2005) - - - - -

*et al.*, 2003)

*al.*, 2003) - - - - -

(Forbes *et al.*, 2006)

(Forbes *et al.*, 2006)

(Nees *et al.*, 2000) -

2006)

2006)

*SPRR1A*  (1q21-22)

*INPP5D*  (2q36-37)

*IGFBP6*  (12q13)

*PPP2R5B*  (11q12)

MPG (16p13.3)

*DDB2*  (11p12-11)

*RUNX1*  (21q22.3)

> *LCN2*  (9q34)

*Signal Transduction*

*DNA*

*DNA*

*Cellular*

*Transport*

see Table 1.

 Genes frequently reported as down-regulated in cervical cancer (CC). A) For each biological process, genes are listed in descending order by the mayor number of reports related to CC e.g. the gene *CDKN1A* has been reported at least 70 times in CC. Genes in bold represent increased expression levels upon different schemes of radio and/or chemotherapy, whereas genes in *italics* are not so known in CC. The chromosomal localization of the gene is shown in brackets. B) Techniques of high-throughput are mainly DNA microarrays; medium- DD, and ESTs; and low- are tumor markers previously defined in CC. C) Genes proposed as metastasis markers (in solid tumors) and tumoral cancer markers (due to frequent mutations). D) Transcription factor (TF) that might regulate the corresponding gene. E) The analysis of the genome refers to the most common chromosomal alterations in CC (2q, 3p, 4p, 5p, 5q, 6p, 6q, 11q, 13q, 18q and 19q). For gene nomenclature see Table 1.

Another gene that could be of interest in CC is *SERPINB2*. The gene product is an inhibitor of the serine-type proteases like the plasminogen activator (also known as *PLAU*). On one hand, *SERPINB2* suppression has been determined using both microarrays as well as genomic studies in CC (Table 3); but on the other, its expression in HeLa cells can stabilize the expression levels of the Rb protein and suppress the oncoproteins E6 and E7 of HPV18 (Darnell *et al.*, 2005). This suggests that low levels of *SERPINB2* promote CC development, being this a potentially good molecular marker.

Of genes not known in CC there are several examples, being the gene *TRIM22* or "tripartite motif-containing 22", which has been found down-regulated in at least 6

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 179

Furthermore, high levels of the corresponding proteins served by themselves as poor prognostic factors in patients with AC compared with SCC (Chao *et al.*, 2006). Other genes

1. *CRABP2* (belongs to the EDC and encodes the retinoic acid binding protein 2) has been identified as up-regulated in SSC compared to normal tissue (Shim *et al.*, 1998; Seo *et al.*,

2. *NDRG1* (N-myc Downstream Regulated Gene 1) is involved in cell growth and differentiation and was found overexpressed in SCC compared to AC (Chao *et al.*, 2006)

3. Other members of the "Carcinoembryonic antigen-related cell adhesion molecule" family such as the *CEACAM-1*, *-5*, *-6*, and *-7*, are shown as up-regulated in AC

4. *MSLN* or mesothelin encodes a membrane glycoprotein involved in cell adhesion whose transcripts are detectable in normal tissue but abundant in tumors of glandular origin or HeLa cells. In CC, *MSLN* is overexpressed in AC compared to SCC (Chao *et al.*, 2006) and in HPV-18-derived samples of SCC/AC compared to normal tissue (Rosty *et al.*, 2005). It is worth noting that *MSLN* is a therapeutic target in various malignancies

5. Finally, high expression levels of *FOLR1* (folate receptor) have been associated with an AC phenotype (Fujimoto *et al.*, 2004) and tumorigenicity in cell lines derived from AC (Mikheev *et al.*, 2004). However, further studies are required to demonstrate the relevance of this receptor in both AC and SCC because it is known that via FOLR1 and folic acid, its ligand, some drugs can be bound and directed into over-expressing high

The aforementioned "tumoral markers" could be potentially important for the diagnosis, prevention, and treatment of CC because these were identified using cell lines from various sources as well as samples of SCC and/or AC for comparative studies with normal tissues. Last but not least, a recent and interesting CC review not only proposed a similar systematic model of HPV infection highlighting the current debate on the viral status as hallmark of disease progression (episomal vs integrated forms where HPV-18 genome integration seems to prevail in women with advance disease in contrast to HPV-16), but also provided overlapping and additional tumor markers at some of those analyzed herein (Woodman *et al.*, 2007). Along these lines, it would be worth saying that cancer, including its hundred subtypes, is such a complex phenomenon (Vogelstein & Kinzler, 2004), which should be rather seen as an average of key molecular events displaying often specific hallmarks

Thanks to the comparison of the cervix in normal and abnormal conditions via transcriptomics in general and particularly using DNA microarrays, it is possible to identify known and unknown clinically relevant genes for the disease progression. The next goal is to identify and validate specific tumor markers for profiling histo- and pathological subtypes. This will allow not only a molecular subclassification and more understanding of CC, but also choosing the right treatment for each patient according to its gene expression signature if there is prior knowledge about the most likely response

levels of *FOLR1,* as suggested in several types of cancer (Kelemen, 2006).

for potential use as markers in CC that have been found with microarrays are:

2005) and AC (Chao *et al.*, 2006).

(Hassan *et al.*, 2004).

**6. Conclusions**

and normal cervical tissue (Sgarlato *et al.*, 2005).

(Hanahan & Weinberg, 2000) of disease progression.

compared to SCC (Fujimoto *et al.*, 2004; Chao *et al.*, 2006).

microarray studies (Table 3). *TRIM22* belongs to a conserved family of antiviral proteins, where the member 22 has been implicated in inhibiting the replication of the human immunodeficiency virus 1 (HIV1) (Nisole *et al.*, 2005). This suggests that TRIM22 may be relevant in the immune response HR-HPVs and that these viruses may be responsible for its inhibition.

Table 3 also lists genes from the epidermal differentiation complex (EDC, located in the band 21 of the long arm of chromosome 1), for instance, using SAGE, abundant transcripts of *SPRR3* have been found in normal cervical tissue, but a low *SPRR3* expression has been determined in tumor tissue using microarrays (Table 3). This suggests that *SPRR3* and perhaps *SPRR1A,* which also belongs to the EDC, may be useful tumor markers in CC. Last, other suppressed genes in CC are *IGFBP6* and *RUNX1* (Table 3). While the first one is responsible for inactivating a potent growth factor similar to insulin (IGF2), a gene in turn required by IGFBP6 to reduce metastatic characteristics in tumors from different origin (Bach, 2005), the second gene belongs to a family of transcription factors that can inhibit angiogenesis (Sakakura *et al.*, 2005).

#### **5.5 Candidate tumor markers in cervical cancer subtypes**

Although HPV-16-infections are more frequently detected than HPV-18 ones in squamous cell carcinoma (SCC), the latter ones are more often associated to adenocarcinoma of the cervix (AC), whose incidence is growing at the same time as SCC incidence. Interestingly, several genes with a clinically usefulness for the molecular differentiation between the two major histological subtypes of CC have been found using DNA microarrays (Table 4). The genes *TACSTD1* and *CEACAM5,* which encode transmembrane proteins that transmit signals for development, motility and cell growth, for example, were found to be upregulated in AC compared to SCC (Chao *et al.*, 2006).

Table 4. Genes with a possible clinical utility for the molecular differentiation between squamous cell carcinoma (SCC) and adenocarcinoma (AC) in cervical cancer. The internationally accepted nomenclature for each gene can be found in: http://www.genenames.org/ or http://cgap.nci.nih.gov/Genes/GeneFinder.

Furthermore, high levels of the corresponding proteins served by themselves as poor prognostic factors in patients with AC compared with SCC (Chao *et al.*, 2006). Other genes for potential use as markers in CC that have been found with microarrays are:

The aforementioned "tumoral markers" could be potentially important for the diagnosis, prevention, and treatment of CC because these were identified using cell lines from various sources as well as samples of SCC and/or AC for comparative studies with normal tissues. Last but not least, a recent and interesting CC review not only proposed a similar systematic model of HPV infection highlighting the current debate on the viral status as hallmark of disease progression (episomal vs integrated forms where HPV-18 genome integration seems to prevail in women with advance disease in contrast to HPV-16), but also provided overlapping and additional tumor markers at some of those analyzed herein (Woodman *et al.*, 2007). Along these lines, it would be worth saying that cancer, including its hundred subtypes, is such a complex phenomenon (Vogelstein & Kinzler, 2004), which should be rather seen as an average of key molecular events displaying often specific hallmarks (Hanahan & Weinberg, 2000) of disease progression.

#### **6. Conclusions**

178 Topics on Cervical Cancer with an Advocacy for Prevention

microarray studies (Table 3). *TRIM22* belongs to a conserved family of antiviral proteins, where the member 22 has been implicated in inhibiting the replication of the human immunodeficiency virus 1 (HIV1) (Nisole *et al.*, 2005). This suggests that TRIM22 may be relevant in the immune response HR-HPVs and that these viruses may be responsible for

Table 3 also lists genes from the epidermal differentiation complex (EDC, located in the band 21 of the long arm of chromosome 1), for instance, using SAGE, abundant transcripts of *SPRR3* have been found in normal cervical tissue, but a low *SPRR3* expression has been determined in tumor tissue using microarrays (Table 3). This suggests that *SPRR3* and perhaps *SPRR1A,* which also belongs to the EDC, may be useful tumor markers in CC. Last, other suppressed genes in CC are *IGFBP6* and *RUNX1* (Table 3). While the first one is responsible for inactivating a potent growth factor similar to insulin (IGF2), a gene in turn required by IGFBP6 to reduce metastatic characteristics in tumors from different origin (Bach, 2005), the second gene belongs to a family of transcription factors that can inhibit

Although HPV-16-infections are more frequently detected than HPV-18 ones in squamous cell carcinoma (SCC), the latter ones are more often associated to adenocarcinoma of the cervix (AC), whose incidence is growing at the same time as SCC incidence. Interestingly, several genes with a clinically usefulness for the molecular differentiation between the two major histological subtypes of CC have been found using DNA microarrays (Table 4). The genes *TACSTD1* and *CEACAM5,* which encode transmembrane proteins that transmit signals for development, motility and cell growth, for example, were found to be

*Gene Reference Gene Reference*  CRABP2 (Chao *et al.*, 2006) BIRC3 (Fujimoto *et al.*, 2004) NDRG1 (Chao *et al.*, 2006) CEACAM1 (Fujimoto *et al.*, 2004) CDH13 (Fujimoto *et al.*, 2004) CEACAM5-7 (Chao *et al.*, 2006) KRT13 (Chao *et al.*, 2006) FOLR1 (Fujimoto *et al.*, 2004) KRT15 (Chao *et al.*, 2006) MSLN (Chao *et al.*, 2006) PTHLH (Fujimoto *et al.*, 2004) S100P (Chao *et al.*, 2006) S100A9 (Chao *et al.*, 2006) TACSTD1 (Chao *et al.*, 2006) SPRR1B (Chao *et al.*, 2006) TSPAN3 (Chao *et al.*, 2006)

Table 4. Genes with a possible clinical utility for the molecular differentiation between squamous cell carcinoma (SCC) and adenocarcinoma (AC) in cervical cancer. The

internationally accepted nomenclature for each gene can be found in:

http://www.genenames.org/ or http://cgap.nci.nih.gov/Genes/GeneFinder.

**carcinoma Up-regulated genes in adenocarcinoma**

its inhibition.

angiogenesis (Sakakura *et al.*, 2005).

**5.5 Candidate tumor markers in cervical cancer subtypes**

upregulated in AC compared to SCC (Chao *et al.*, 2006).

**Up-regulated genes in squamous cell**

Thanks to the comparison of the cervix in normal and abnormal conditions via transcriptomics in general and particularly using DNA microarrays, it is possible to identify known and unknown clinically relevant genes for the disease progression. The next goal is to identify and validate specific tumor markers for profiling histo- and pathological subtypes. This will allow not only a molecular subclassification and more understanding of CC, but also choosing the right treatment for each patient according to its gene expression signature if there is prior knowledge about the most likely response

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 181

Ahn WS, Seo MJ, Bae SM, Lee JM, Namkoong SE, Kim CK & Kim YW (2005) Cellular

Alazawi W, Pett M, Arch B, Scott L, Freeman T, Stanley MA & Coleman N (2002) Changes in

Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H,

Altieri DC (2006) Targeted therapy by disabling crossroad signaling networks: the survivin

Alwine JC, Kemp DJ & Stark GR (1977) Method for detection of specific RNAs in agarose

Bach LA (2005) IGFBP-6 five years on; not so 'forgotten'? *Growth hormone & IGF research* 15,

Bae SM, Lee CH, Cho YL, Nam KH, Kim YW, Kim CK, Han BD, Lee YJ, Chun HJ & Ahn WS

Bartlett JM (2002) Approaches to the analysis of gene expression using mRNA: a technical

Berk AJ & Sharp PA (1977) Sizing and mapping of early adenovirus mRNAs by gel electrophoresis of S1 endonuclease-digested hybrids. *Cell* 12, 721-732. Bracken AP, Ciro M, Cocito A & Helin K (2004) E2F target genes: unraveling the biology.

Branca M, Giorgi C, Santini D, Di Bonito L, Ciotti M, Costa S, Benedetto A, Casolati EA,

Brentani H, Caballero OL, Camargo AA, da Silva AM, da Silva WA, Jr., Dias Neto E, Grivet

Favalli C, Paba P, Di Bonito P, Mariani L, Syrjanen S, Bonifacio D, Accardi L, Zanconati F & Syrjanen K (2005) Survivin as a marker of cervical intraepithelial neoplasia and high-risk human papillomavirus and a predictor of virus clearance and prognosis in cervical cancer. *American journal of clinical pathology* 124, 113-121. Brenner S, Johnson M, Bridgham J, Golda G, Lloyd DH, Johnson D, Luo SJ, McCurdy S, Foy

M, Ewan M, Roth R, George D, Eletr S, Albrecht G, Vermaas E, Williams SR, Moon K, Burcham T, Pallas M, DuBridge RB, Kirchner J, Fearon K, Mao J & Corcoran K (2000) Gene expression analysis by massively parallel signature sequencing (MPSS)

M, Gruber A, Guimaraes PE, Hide W, Iseli C, Jongeneel CV, Kelso J, Nagai MA, Ojopi EP, Osorio EC, Reis EM, Riggins GJ, Simpson AJ, de Souza S, Stevenson BJ, Strausberg RL, Tajara EH, Verjovski-Almeida S, Acencio ML, Bengtson MH,

*of the International Gynecological Cancer Society* 15, 94-106.

papillomavirus 16. *Cancer research* 62, 6959-6965.

paradigm. *Molecular cancer therapeutics* 5, 478-482.

cervical cancer patients. *Gynecologic oncology* 99, 26-35.

on microbead arrays. *Nature Biotechnology* 18, 630-634.

overview. *Molecular biotechnology* 21, 149-160.

*Trends in Biochemical Sciences* 29, 409-417.

expression profiling. *Nature* 403, 503-511.

74, 5350-5354.

185-192.

*DNA and cell biology* 22, 217-224.

line, CaSki cells, through apoptosis, G(1) arrest, and regulation of gene expression.

process classification of human papillomavirus-16-positive SiHa cervical carcinoma cell using Gene Ontology. *International journal of gynecological cancer: official journal*

cervical keratinocyte gene expression associated with integration of human

Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J, Jr., Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO & Staudt LM (2000) Distinct types of diffuse large B-cell lymphoma identified by gene

gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes. *Proceedings of the National Academy of Sciences of the United States of America*

(2005) Two-dimensional gel analysis of protein expression profile in squamous

she would have. This is the only way to fully understand more about this complex disease.

The intention of this manuscript is to provide the reader a broad view of the transcriptome, an area that is developing rapidly, especially in cancer. It is worthwhile reemphasize that the transcriptome also consists of non-coding RNAs regulating the transcription of many genes and likewise acting as oncogenes or tumor suppressor genes. With such complexity, the best tackling to cancer will rely on predictive hypothesis, so it is important to take into account systems biology, which will allow us to better understand transcriptional networks and identify specific therapy targets for a tailored therapy.

Although there are improved programs for the early diagnosis of CC as well as very effective prophylactic vaccines against HR-HPVs, the high mortality rates triggered by CC will not diminish soon, not even in the medium-term after optimizing CC monitoring programs and broadly executing vaccination schemes. An alternative for CC patients is therefore to look at those tumor markers that could aid in the stratification of the disease and therapy. Unfortunately, genomics and all its derivatives are exacerbating global inequalities in terms of scientific research and health between developed and developing countries since the first cause of death of women in the former countries is breast cancer whereas in the latter ones CC kills every 2 hours, on average, a Mexican woman in productive age.

#### **7. Acknowledgments**

We thank the library at the MPI of Coal Research for financial support.

#### **8. References**

she would have. This is the only way to fully understand more about this complex

The intention of this manuscript is to provide the reader a broad view of the transcriptome, an area that is developing rapidly, especially in cancer. It is worthwhile reemphasize that the transcriptome also consists of non-coding RNAs regulating the transcription of many genes and likewise acting as oncogenes or tumor suppressor genes. With such complexity, the best tackling to cancer will rely on predictive hypothesis, so it is important to take into account systems biology, which will allow us to better understand transcriptional networks

Although there are improved programs for the early diagnosis of CC as well as very effective prophylactic vaccines against HR-HPVs, the high mortality rates triggered by CC will not diminish soon, not even in the medium-term after optimizing CC monitoring programs and broadly executing vaccination schemes. An alternative for CC patients is therefore to look at those tumor markers that could aid in the stratification of the disease and therapy. Unfortunately, genomics and all its derivatives are exacerbating global inequalities in terms of scientific research and health between developed and developing countries since the first cause of death of women in the former countries is breast cancer whereas in the latter ones CC kills every 2 hours, on average, a Mexican woman in

Acevedo Rocha CG, Alvarez E, Zafra de la Rosa G, Alvarez Navarro M & Gariglio P (2007)

Achary MP, Jaggernauth W, Gross E, Alfieri A, Klinger HP & Vikram B (2000) Cell lines

Adams MD, Kelley JM, Gocayne JD, Dubnick M, Polymeropoulos MH, Xiao H, Merril CR,

expressed sequence tags and human genome project. *Science* 252, 1651-1656. Ahn WS, Bae SM, Lee JM, Namkoong SE, Han SJ, Cho YL, Nam GH, Seo JS, Kim CK & Kim

Ahn WS, Bae SM, Lee KH, Kim YW, Lee JM, Namkoong SE, Lee IP, Kim CK, Seo JS & Sin JI

Ahn WS, Huh SW, Bae SM, Lee IP, Lee JM, Namkoong SE, Kim CK & Sin JI (2003) A major

[Cervical cancer and DNA microarrays: tumour marker identification]. *Ginecologia*

from the same cervical carcinoma but with different radiosensitivities exhibit different cDNA microarray patterns of gene expression. *Cytogenetics and cell genetics*

Wu A, Olde B, Moreno RF & et al. (1991) Complementary DNA sequencing:

YW (2004a) Searching for pathogenic gene functions to cervical cancer. *Gynecologic*

(2004b) Comparison of effects of As2O3 and As4O6 on cell growth inhibition and gene expression profiles by cDNA microarray analysis in SiHa cells. *Oncology*

constituent of green tea, EGCG, inhibits the growth of a human cervical cancer cell

and identify specific therapy targets for a tailored therapy.

We thank the library at the MPI of Coal Research for financial support.

*y Obstetricia de Mexico* 75, 205-213.

disease.

productive age.

**8. References**

**7. Acknowledgments**

91, 39-43.

*oncology* 93, 41-48.

*reports* 12, 573-580.

line, CaSki cells, through apoptosis, G(1) arrest, and regulation of gene expression. *DNA and cell biology* 22, 217-224.

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 183

Chao A, Wang TH, Lee YS, Hsueh S, Chao AS, Chang TC, Kung WH, Huang SL, Chao FY,

Chaudhry MA, Chodosh LA, McKenna WG & Muschel RJ (2003) Gene expression profile of

Chen X, Shen B, Xia L, Khaletzkiy A, Chu D, Wong JY & Li JJ (2002) Activation of nuclear

Chen Y, Miller C, Mosher R, Zhao X, Deeds J, Morrissey M, Bryant B, Yang D, Meyer R,

Cheng Q, Lau WM, Chew SH, Ho TH, Tay SK & Hui KM (2002a) Identification of molecular

Cheng Q, Lau WM, Tay SK, Chew SH, Ho TH & Hui KM (2002b) Identification and

Chin KV, Alabanza L, Fujii K, Kudoh K, Kita T, Kikuchi Y, Selvanayagam ZE, Wong YF, Lin

response in cancer. *Annals of the New York Academy of Sciences* 1058, 186-195. Choi YP, Kang S, Hong S, Xie X & Cho NH (2005) Proteomic analysis of progressive factors

Chung YM, Kim BG, Park CS, Huh SJ, Kim J, Park JK, Cho SM, Kim BS, Kim JS, Yoo YD &

Clarke PA, te Poele R & Workman P (2004) Gene expression microarray technologies in the development of new therapeutic agents. *European journal of cancer* 40, 2560-2591. Collins FS, Green ED, Guttmacher AE & Guyer MS (2003) A vision for the future of

Contag SA, Gostout BS, Clayton AC, Dixon MH, McGovern RM & Calhoun ES (2004)

Coulton G (2004) Are histochemistry and cytochemistry 'Omics'? *Journal of molecular*

Couzin J (2003) Medicine. Tracing the steps of metastasis, cancer's menacing ballet. *Science*

Crawford DF & Piwnica-Worms H (2001) The G(2) DNA damage checkpoint delays

expression of genes encoding mitotic regulators. *The Journal of biological chemistry*

Comparison of gene expression in squamous cell carcinoma and adenocarcinoma

resistance in cervical cancer. *International journal of cancer* 117, 194-201. Ciro M, Bracken AP & Helin K (2003) Profiling cancer. *Current opinion in cell biology* 15, 213-

cervical carcinoma. *International journal of cancer* 98, 419-426.

in uterine cervical cancer. *Proteomics* 5, 1481-1493.

genomics research. *Nature* 422, 835-847.

*histology* 35, 603-613.

299, 1002-1006.

276, 37166-37177.

of the uterine cervix. *Gynecologic oncology* 95, 610-617. Costa FF (2010) Non-coding RNAs: Meet thy masters. *Bioessays* 32, 599-608.

Crick F (1970) Central dogma of molecular biology. *Nature* 227, 561-563.

expression. *International journal of cancer* 119, 91-98.

cervix. *British journal of cancer* 86, 274-281.

*research* 62, 1213-1221.

1935.

220.

Wei ML & Lai CH (2006) Molecular characterization of adenocarcinoma and squamous carcinoma of the uterine cervix using microarray analysis of gene

human cells irradiated in G1 and G2 phases of cell cycle. *Cancer letters* 195, 221-233.

factor kappaB in radioresistance of TP53-inactive human keratinocytes. *Cancer*

Cronin F, Gostout BS, Smith-McCune K & Schlegel R (2003) Identification of cervical cancer markers by cDNA and tissue microarrays. *Cancer research* 63, 1927-

markers for the early detection of human squamous cell carcinoma of the uterine

characterization of genes involved in the carcinogenesis of human squamous cell

Y & Shih WC (2005) Application of expression genomics for predicting treatment

Bae DS (2005) Increased expression of ICAM-3 is associated with radiation

Bettoni F, Bodmer WF, Briones MR, Camargo LP, Cavenee W, Cerutti JM, Coelho Andrade LE, Costa dos Santos PC, Ramos Costa MC, da Silva IT, Estecio MR, Sa Ferreira K, Furnari FB, Faria M, Jr., Galante PA, Guimaraes GS, Holanda AJ, Kimura ET, Leerkes MR, Lu X, Maciel RM, Martins EA, Massirer KB, Melo AS, Mestriner CA, Miracca EC, Miranda LL, Nobrega FG, Oliveira PS, Paquola AC, Pandolfi JR, Campos Pardini MI, Passetti F, Quackenbush J, Schnabel B, Sogayar MC, Souza JE, Valentini SR, Zaiats AC, Amaral EJ, Arnaldi LA, de Araujo AG, de Bessa SA, Bicknell DC, Ribeiro de Camaro ME, Carraro DM, Carrer H, Carvalho AF, Colin C, Costa F, Curcio C, Guerreiro da Silva ID, Pereira da Silva N, Dellamano M, El-Dorry H, Espreafico EM, Scattone Ferreira AJ, Ayres Ferreira C, Fortes MA, Gama AH, Giannella-Neto D, Giannella ML, Giorgi RR, Goldman GH, Goldman MH, Hackel C, Ho PL, Kimura EM, Kowalski LP, Krieger JE, Leite LC, Lopes A, Luna AM, Mackay A, Mari SK, Marques AA, Martins WK, Montagnini A, Mourao Neto M, Nascimento AL, Neville AM, Nobrega MP, O'Hare MJ, Otsuka AY, Ruas de Melo AI, Paco-Larson ML, Guimaraes Pereira G, Pesquero JB, Pessoa JG, Rahal P, Rainho CA, Rodrigues V, Rogatto SR, Romano CM, Romeiro JG, Rossi BM, Rusticci M, Guerra de Sa R, Sant' Anna SC, Sarmazo ML, Silva TC, Soares FA, Sonati Mde F, de Freitas Sousa J, Queiroz D, Valente V, Vettore AL, Villanova FE, Zago MA & Zalcberg H (2003) The generation and utilization of a cancer-oriented representation of the human transcriptome by using expressed sequence tags. *Proceedings of the National Academy of Sciences of the United States of America* 100, 13418-13423.

Bueno-de-Mesquita JM, Linn SC, Keijzer R, Wesseling J, Nuyten DS, van Krimpen C, Meijers

Bustamante C, Cheng W & Mejia YX (2011) Revisiting the central dogma one molecule at a

Bustin SA (2000) Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. *Journal of molecular endocrinology* 25, 169-193. Buyse M, Loi S, van't Veer L, Viale G, Delorenzi M, Glas AM, d'Assignies MS, Bergh J,

Carter TH, Liu K, Ralph W, Jr., Chen D, Qi M, Fan S, Yuan F, Rosen EM & Auborn KJ (2002)

Chang CH, Tsai LC, Chen ST, Yuan CC, Hung MW, Hsieh BT, Chao PL, Tsai TH & Lee TW

Chang YE & Laimins LA (2000) Microarray analysis identifies interferon-inducible genes

cancer. *Journal of the National Cancer Institute* 98, 1183-1192.

C, de Graaf PW, Bos MM, Hart AA, Rutgers EJ, Peterse JL, Halfwerk H, de Groot R, Pronk A, Floore AN, Glas AM, Van't Veer LJ & van de Vijver MJ (2009) Validation of 70-gene prognosis signature in node-negative breast cancer. *Breast cancer research*

Lidereau R, Ellis P, Harris A, Bogaerts J, Therasse P, Floore A, Amakrane M, Piette F, Rutgers E, Sotiriou C, Cardoso F & Piccart MJ (2006) Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast

Diindolylmethane alters gene expression in human keratinocytes in vitro. *The*

(2005) Radioimmunotherapy and apoptotic induction on CK19-overexpressing human cervical carcinoma cells with Re-188-mAbCx-99. *Anticancer research* 25,

and Stat-1 as major transcriptional targets of human papillomavirus type 31. *Journal*

13418-13423.

2719-2728.

*of virology* 74, 4174-4182.

*and treatment* 117, 483-495.

*Journal of nutrition* 132, 3314-3324.

time. *Cell* 144, 480-497.

Bettoni F, Bodmer WF, Briones MR, Camargo LP, Cavenee W, Cerutti JM, Coelho Andrade LE, Costa dos Santos PC, Ramos Costa MC, da Silva IT, Estecio MR, Sa Ferreira K, Furnari FB, Faria M, Jr., Galante PA, Guimaraes GS, Holanda AJ, Kimura ET, Leerkes MR, Lu X, Maciel RM, Martins EA, Massirer KB, Melo AS, Mestriner CA, Miracca EC, Miranda LL, Nobrega FG, Oliveira PS, Paquola AC, Pandolfi JR, Campos Pardini MI, Passetti F, Quackenbush J, Schnabel B, Sogayar MC, Souza JE, Valentini SR, Zaiats AC, Amaral EJ, Arnaldi LA, de Araujo AG, de Bessa SA, Bicknell DC, Ribeiro de Camaro ME, Carraro DM, Carrer H, Carvalho AF, Colin C, Costa F, Curcio C, Guerreiro da Silva ID, Pereira da Silva N, Dellamano M, El-Dorry H, Espreafico EM, Scattone Ferreira AJ, Ayres Ferreira C, Fortes MA, Gama AH, Giannella-Neto D, Giannella ML, Giorgi RR, Goldman GH, Goldman MH, Hackel C, Ho PL, Kimura EM, Kowalski LP, Krieger JE, Leite LC, Lopes A, Luna AM, Mackay A, Mari SK, Marques AA, Martins WK, Montagnini A, Mourao Neto M, Nascimento AL, Neville AM, Nobrega MP, O'Hare MJ, Otsuka AY, Ruas de Melo AI, Paco-Larson ML, Guimaraes Pereira G, Pesquero JB, Pessoa JG, Rahal P, Rainho CA, Rodrigues V, Rogatto SR, Romano CM, Romeiro JG, Rossi BM, Rusticci M, Guerra de Sa R, Sant' Anna SC, Sarmazo ML, Silva TC, Soares FA, Sonati Mde F, de Freitas Sousa J, Queiroz D, Valente V, Vettore AL, Villanova FE, Zago MA & Zalcberg H (2003) The generation and utilization of a cancer-oriented representation of the human transcriptome by using expressed sequence tags. *Proceedings of the National Academy of Sciences of the United States of America* 100,

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 185

Frigessi A, van de Wiel MA, Holden M, Svendsrud DH, Glad IK & Lyng H (2005) Genome-

Frith MC, Pheasant M & Mattick JS (2005) The amazing complexity of the human transcriptome. *European journal of human genetics : EJHG* 13, 894-897. Fujimoto T, Nishikawa A, Iwasaki M, Akutagawa N, Teramoto M & Kudo R (2004) Gene

Fuller AP, Palmer-Toy D, Erlander MG & Sgroi DC (2003) Laser capture microdissection

Gandarillas A (2000) Epidermal differentiation, apoptosis, and senescence: common

Garner-Hamrick PA, Fostel JM, Chien WM, Banerjee NS, Chow LT, Broker TR & Fisher C

Gartel AL & Radhakrishnan SK (2005) Lost in transcription: p21 repression, mechanisms,

Gatherer D (2010) So what do we really mean when we say that systems biology is holistic?

Gatti L, Beretta GL, Carenini N, Corna E, Zunino F & Perego P (2004) Gene expression

Gibb EA, Brown CJ & Lam WL (2011) The functional role of long non-coding RNA in

Glas AM, Floore A, Delahaye LJ, Witteveen AT, Pover RC, Bakx N, Lahti-Domenici JS,

Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML,

Gray LJ & Herrington CS (2004) Molecular markers for the prediction of progression of CIN

Guelaguetza Vázquez-Ortíz ea (2005) Análisis de expresión global del cáncer cérvico

Haffty BG & Glazer PM (2003) Molecular markers in clinical radiation oncology. *Oncogene*

Hanson JC, Tangrea MA, Kim S, Armani MD, Pohida TJ, Bonner RF, Rodriguez-Canales J &

lesions. *International journal of gynecological pathology* 23, 95-96.

Hanahan D & Weinberg RA (2000) The hallmarks of cancer. *Cell* 100, 57-70.

dissection instruments. *Nature protocols* 6, 457-467.

keratinocyte culture system. *Journal of virology* 78, 9041-9050.

*Nucleic Acids Research* 33, e143.

*Gynecologic oncology* 93, 446-453.

*biology and neoplasia* 8, 335-345.

*BMC systems biology* 4, 22.

test. *BMC Genomics* 7, 278.

monitoring. *Science* 286, 531-537.

human carcinomas. *Mol Cancer* 10, 38.

*Sci* 61, 973-981.

434-441.

22, 5915-5925.

pathways? *Experimental gerontology* 35, 53-62.

and consequences. *Cancer research* 65, 3980-3985.

wide estimation of transcript concentrations from spotted cDNA microarray data.

expression profiling in two morphologically different uterine cervical carcinoma cell lines derived from a single donor using a human cancer cDNA array.

and advanced molecular analysis of human breast cancer. *Journal of mammary gland*

(2004) Global effects of human papillomavirus type 18 E6/E7 in an organotypic

profiles in the cellular response to a multinuclear platinum complex. *Cell Mol Life*

Bruinsma TJ, Warmoes MO, Bernards R, Wessels LF & Van't Veer LJ (2006) Converting a breast cancer microarray signature into a high-throughput diagnostic

Downing JR, Caligiuri MA, Bloomfield CD & Lander ES (1999) Molecular classification of cancer: class discovery and class prediction by gene expression

uterino: rutas metabólicas y genes alterados. *Revista de Investigaciones Clinicas* 57

Emmert-Buck MR (2011) Expression microdissection adapted to commercial laser

Darnell GA, Antalis TM, Rose BR & Suhrbier A (2005) Silencing of integrated human

de Boer CJ, van Dorst E, van Krieken H, Jansen-van Rhijn CM, Warnaar SO, Fleuren GJ &

Dias Neto E, Correa RG, Verjovski-Almeida S, Briones MR, Nagai MA, da Silva W, Jr., Zago

Dimitroulakos J, Marhin WH, Tokunaga J, Irish J, Gullane P, Penn LZ & Kamel-Reid S (2002)

Domazet B, Maclennan GT, Lopez-Beltran A, Montironi R & Cheng L (2008) Laser capture

cancer. *International journal of clinical and experimental pathology* 1, 475-488. Dowhanick JJ, McBride AA & Howley PM (1995) Suppression of cellular proliferation by the

Duenas-Gonzalez A, Cetina L, Mariscal I & de la Garza J (2003) Modern management of locally advanced cervical carcinoma. *Cancer treatment reviews* 29, 389-399. Duenas-Gonzalez A, Lizano M, Candelaria M, Cetina L, Arce C & Cervera E (2005)

Duffy CL, Phillips SL & Klingelhutz AJ (2003) Microarray analysis identifies differentiation-

Dusek RL, Getsios S, Chen F, Park JK, Amargo EV, Cryns VL & Green KJ (2006) The

Follen M, Meyskens FL, Jr., Alvarez RD, Walker JL, Bell MC, Storthz KA, Sastry J, Roy K,

Forbes S, Clements J, Dawson E, Bamford S, Webb T, Dogan A, Flanagan A, Teague J,

Forrest ARR, Taylor DF, Crowe ML, Chalk AM, Waddell NJ, Kolle G, Faulkner GJ, Rimantas

Frazer IH (2004) Prevention of cervical cancer through papillomavirus vaccination. *Nature*

vaccines, and surrogate endpoint biomarkers. *Cancer* 98, 2044-2051.

kinases and phosphatases. *Genome Biology* 7, R5.

*Reviews Immunology* 4, 46-54.

papillomavirus E2 protein. *Journal of virology* 69, 7791-7799.

*of virology* 79, 4246-4256.

*pathology* 155, 505-515.

cell carcinomas. *Neoplasia* 4, 337-346.

3496.

*cancer* 4, 38.

281, 3614-3624.

94, 318-322.

205.

papillomavirus type 18 oncogene transcription in cells expressing SerpinB2. *Journal*

Litvinov SV (1999) Changing roles of cadherins and catenins during progression of squamous intraepithelial lesions in the uterine cervix. *The American journal of*

MA, Bordin S, Costa FF, Goldman GH, Carvalho AF, Matsukuma A, Baia GS, Simpson DH, Brunstein A, de Oliveira PS, Bucher P, Jongeneel CV, O'Hare MJ, Soares F, Brentani RR, Reis LF, de Souza SJ & Simpson AJ (2000) Shotgun sequencing of the human transcriptome with ORF expressed sequence tags. *Proceedings of the National Academy of Sciences of the United States of America* 97, 3491-

Microarray and biochemical analysis of lovastatin-induced apoptosis of squamous

microdissection in the genomic and proteomic era: targeting the genetic basis of

Epigenetics of cervical cancer. An overview and therapeutic perspectives. *Molecular*

associated genes regulated by human papillomavirus type 16 E6. *Virology* 314, 196-

differentiation-dependent desmosomal cadherin desmoglein 1 is a novel caspase-3 target that regulates apoptosis in keratinocytes. *The Journal of biological chemistry*

Richards-Kortum R & Cornelison TL (2003) Cervical cancer chemoprevention,

Wooster R, Futreal PA & Stratton MR (2006) Cosmic 2005. *British journal of cancer*

K, Katayama S, Wells C, Kai C, Kawai J, Carninci P, Hayashizaki Y & Grimmond SM (2006) Genome-wide review of transcriptional complexity in mouse protein

Hanahan D & Weinberg RA (2000) The hallmarks of cancer. *Cell* 100, 57-70.

Hanson JC, Tangrea MA, Kim S, Armani MD, Pohida TJ, Bonner RF, Rodriguez-Canales J & Emmert-Buck MR (2011) Expression microdissection adapted to commercial laser dissection instruments. *Nature protocols* 6, 457-467.

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 187

Kalantari M, Garcia-Carranca A, Morales-Vazquez CD, Zuna R, Montiel DP, Calleja-Macias

Kelley ML, Keiger KE, Lee CJ & Huibregtse JM (2005) The global transcriptional effects of

Kitahara O, Katagiri T, Tsunoda T, Harima Y & Nakamura Y (2002) Classification of

Klaes R, Woerner SM, Ridder R, Wentzensen N, Duerst M, Schneider A, Lotz B, Melsheimer

Klee EW, Erdogan S, Tillmans L, Kosari F, Sun Z, Wigle DA, Yang P, Aubry MC &

Lander ES & Weinberg RA (2000) Genomics: journey to the center of biology. *Science* 287,

Lazo PA (1999) The molecular genetics of cervical carcinoma. *British journal of cancer* 80,

Lee CM, Fuhrman CB, Planelles V, Peltier MR, Gaffney DK, Soisson AP, Dodson MK, Tolley

Lee KA, Shim JH, Kho CW, Park SG, Park BC, Kim JW, Lim JS, Choe YK, Paik SG & Yoon

Li J, Yen C, Liaw D, Podsypanina K, Bose S, Wang SI, Puc J, Miliaresis C, Rodgers L,

mutated in human brain, breast, and prostate cancer. *Science* 275, 1943-1947.

Current state and future direction. *Molecular & cellular proteomics*.

integrated papillomavirus oncogenes. *Cancer research* 59, 6132-6136.

sampling versus bulk tissue-sampling. *BMC medical genomics* 2, 13.

by the E6AP ubiquitin ligase. *Journal of virology* 79, 3737-3747. Kent WJ (2002) BLAT--the BLAST-like alignment tool. *Genome research* 12, 656-664.

Kitano H (2002) Systems biology: a brief overview. *Science* 295, 1662-1664.

119, 243-250.

295-303.

1777-1782.

2008-2018.

250-256.

IE, Johansson B, Andersson S & Bernard HU (2009) Laser capture microdissection of cervical human papillomavirus infections: copy number of the virus in cancerous and normal tissue and heterogeneous DNA methylation. *Virology* 390, 261-267. Keating JT, Ince T & Crum CP (2001) Surrogate biomarkers of HPV infection in cervical neoplasia screening and diagnosis. *Advances in anatomic pathology* 8, 83-92. Kelemen LE (2006) The role of folate receptor alpha in cancer development, progression and

treatment: cause, consequence or innocent bystander? *International journal of cancer*

the human papillomavirus E6 protein in cervical carcinoma cell lines are mediated

sensitivity or resistance of cervical cancers to ionizing radiation according to expression profiles of 62 genes selected by cDNA microarray analysis. *Neoplasia* 4,

P & von Knebel Doeberitz M (1999) Detection of high-risk cervical intraepithelial neoplasia and cervical cancer by amplification of transcripts derived from

Vasmatzis G (2009) Impact of sample acquisition and linear amplification on gene expression profiling of lung adenocarcinoma: laser capture micro-dissection cell-

HD, Green CL & Zempolich KA (2006) Phosphatidylinositol 3-kinase inhibition by LY294002 radiosensitizes human cervical cancer cell lines. *Clinical cancer research* 12,

DY (2004) Protein profiling and identification of modulators regulated by the E7 oncogene in the C33A cell line by proteomics and genomics. *Proteomics* 4, 839-848. Legrain P, Aebersold R, Archakov A, Bairoch A, Bala K, Beretta L, Bergeron J, Borchers C,

Corthals GL, Costello CE, Deutsch EW, Domon B, Hancock W, He F, Hochstrasser D, Marko-Varga G, Salekdeh GH, Sechi S, Snyder M, Srivastava S, Uhlen M, Hu CH, Yamamoto T, Paik YK & Omenn GS (2011) The human proteome project:

McCombie R, Bigner SH, Giovanella BC, Ittmann M, Tycko B, Hibshoosh H, Wigler MH & Parsons R (1997) PTEN, a putative protein tyrosine phosphatase gene

Harima Y, Sawada S, Miyazaki Y, Kin K, Ishihara H, Imamura M, Sougawa M, Shikata N &

radiotherapy and survival. *American journal of clinical oncology* 26, e80-85. Harima Y, Togashi A, Horikoshi K, Imamura M, Sougawa M, Sawada S, Tsunoda T,

Harrell JC, Dye WW, Harvell DM, Sartorius CA & Horwitz KB (2008) Contaminating cells

Harrison PR, Conkie D, Paul J & Jones K (1973) Localisation of cellular globin messenger RNA by in situ hybridisation to complementary DNA. *FEBS letters* 32, 109-112. Hassan R, Bera T & Pastan I (2004) Mesothelin: a new target for immunotherapy. *Clinical*

Helliwell TR (2001) Molecular markers of metastasis in squamous carcinomas. *The Journal of*

Hipp J, Cheng J, Hanson JC, Yan W, Taylor P, Hu N, Rodriguez-Canales J, Tangrea MA,

Hollestelle A & Schutte M (2005) Representational difference analysis as a tool in the search for new tumor suppressor genes. *Methods in molecular medicine* 103, 143-159. Hubank M & Schatz DG (1994) Identifying differences in mRNA expression by representational difference analysis of cDNA. *Nucleic Acids Research* 22, 5640-5648. Hudelist G, Czerwenka K, Singer C, Pischinger K, Kubista E & Manavi M (2005) cDNA

Hughes TR, Mao M, Jones AR, Burchard J, Marton MJ, Shannon KW, Lefkowitz SM, Ziman

Human Genome Sequencing C (2004) Finishing the euchromatic sequence of the human

Hwang J, Kim YY, Huh S, Shim J, Park C, Kimm K, Choi DK, Park TK & Kim S (2005) The

time-dependent serial gene response to Zeocin treatment involves caspasedependent apoptosis in HeLa cells. *Microbiology and immunology* 49, 331-342. Ishitobi M, Goranova TE, Komoike Y, Motomura K, Koyama H, Glas AM, van Lienen E,

Inaji H, Van't Veer LJ & Kato K (2010) Clinical utility of the 70-gene MammaPrint profile in a Japanese population. *Japanese journal of clinical oncology* 40, 508-512.

a feasibility study. *Cancer genetics and cytogenetics* 158, 35-42.

Emmert-Buck MR & Balis U (2011) SIVQ-aided laser capture microdissection: A tool for high-throughput expression profiling. *Journal of pathology informatics* 2, 19. Hoeflich A, Reisinger R, Lahm H, Kiess W, Blum WF, Kolb HJ, Weber MM & Wolf E (2001)

Insulin-like growth factor-binding protein 2 in tumorigenesis: protector or

array analysis of cytobrush-collected normal and malignant cervical epithelial cells:

M, Schelter JM, Meyer MR, Kobayashi S, Davis C, Dai HY, He YDD, Stephaniants SB, Cavet G, Walker WL, West A, Coffey E, Shoemaker DD, Stoughton R, Blanchard AP, Friend SH & Linsley PS (2001) Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. *Nature*

60, 237-248.

*Clinical & experimental metastasis* 25, 81-88.

promoter? *Cancer research* 61, 8601-8610.

*cancer research* 10, 3937-3942.

*pathology* 194, 289-293.

*Biotechnology* 19, 342-347.

genome. *Nature* 431, 931-945.

Ohnishi T (2003) Expression of Ku80 in cervical cancer correlates with response to

Nakamura Y & Katagiri T (2004) Prediction of outcome of advanced cervical cancer to thermoradiotherapy according to expression profiles of 35 genes selected by cDNA microarray analysis. *International journal of radiation oncology, biology, physics*

alter gene signatures in whole organ versus laser capture microdissected tumors: a comparison of experimental breast cancers and their lymph node metastases.

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 189

Nisole S, Stoye JP & Saib A (2005) TRIM family proteins: retroviral restriction and antiviral

Nuovo GJ, Plaia TW, Belinsky SA, Baylin SB & Herman JG (1999) In situ detection of the

Okamoto K & Beach D (1994) Cyclin-G Is a Transcriptional Target of the P53 Tumor-

Orlando V (2000) Mapping chromosomal proteins in vivo by formaldehyde-crosslinkedchromatin immunoprecipitation. *Trends in Biochemical Sciences* 25, 99-104. Perez-Plasencia C, Riggins G, Vazquez-Ortiz G, Moreno J, Arreola H, Hidalgo A, Pina-

Pett MR, Herdman MT, Palmer RD, Yeo GS, Shivji MK, Stanley MA & Coleman N (2006)

Polyak K & Riggins GJ (2001) Gene discovery using the serial analysis of gene expression

Ranamukhaarachchi DG, Unger ER, Vernon SD, Lee D & Rajeevan MS (2005) Gene

Rappolee DA, Mark D, Banda MJ & Werb Z (1988) Wound macrophages express TGF-alpha

Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J,

wide location and function of DNA binding proteins. *Science* 290, 2306-+. Rhodes DR & Chinnaiyan AM (2005) Integrative analysis of the cancer transcriptome. *Nature*

Rosenwald A, Wright G, Chan WC, Connors JM, Campo E, Fisher RI, Gascoyne RD, Muller-

Quackenbush J (2004) Data standards for 'omic' science. *Nature Biotechnology* 22, 613-614. Ramaswamy S, Ross KN, Lander ES & Golub TR (2003) A molecular signature of metastasis

*Academy of Sciences of the United States of America* 103, 3822-3827.

in primary solid tumors. *Nature Genetics* 33, 49-54.

harboring human papillomavirus 16. *Genomics* 85, 727-738.

*Gynecologic oncology* 97, 35-40.

*America* 96, 12754-12759.

*BMC Genomics* 6, 130.

2958.

712.

*Genetics* 37, S31-S37.

defence. *Nature Reviews Microbiology* 3, 799-808.

Novina CD & Sharp PA (2004) The RNAi revolution. *Nature* 430, 161-164.

Suppressor Protein. *The EMBO Journal* 13, 4816-4822.

squamous cells of undetermined significance-categorized Pap smear? A comparative analysis using abnormal cervical smears with follow-up biopsies.

hypermethylation-induced inactivation of the p16 gene as an early event in oncogenesis. *Proceedings of the National Academy of Sciences of the United States of*

Sanchez P & Salcedo M (2005) Characterization of the global profile of genes expressed in cervical epithelium by Serial Analysis of Gene Expression (SAGE).

Selection of cervical keratinocytes containing integrated HPV16 associates with episome loss and an endogenous antiviral response. *Proceedings of the National*

technique: Implications for cancer research. *Journal of Clinical Oncology* 19, 2948-

expression profiling of dysplastic differentiation in cervical epithelial cells

and other growth factors in vivo: analysis by mRNA phenotyping. *Science* 241, 708-

Hannett N, Kanin E, Volkert TL, Wilson CJ, Bell SP & Young RA (2000) Genome-

Hermelink HK, Smeland EB, Giltnane JM, Hurt EM, Zhao H, Averett L, Yang L, Wilson WH, Jaffe ES, Simon R, Klausner RD, Powell J, Duffey PL, Longo DL, Greiner TC, Weisenburger DD, Sanger WG, Dave BJ, Lynch JC, Vose J, Armitage JO, Montserrat E, Lopez-Guillermo A, Grogan TM, Miller TP, LeBlanc M, Ott G, Kvaloy S, Delabie J, Holte H, Krajci P, Stokke T & Staudt LM (2002) The use of

Liang P & Pardee AB (1992) Differential display of eukaryotic messenger RNA by means of

Liang P & Pardee AB (2003) Analysing differential gene expression in cancer. *Nature Reviews*

Lin J & Li M (2008) Molecular profiling in the age of cancer genomics. *Expert review of*

Liu SS, Cheung AN & Ngan HY (2003) Differential gene expression in cervical cancer cell

Lockhart DJ, Dong HL, Byrne MC, Follettie MT, Gallo MV, Chee MS, Mittmann M, Wang

Lu X, Toki T, Konishi I, Nikaido T & Fujii S (1998) Expression of p21WAF1/CIP1 in

Macoska JA (2002) The progressing clinical utility of DNA microarrays. *CA Cancer J Clin* 52,

Martin CM, Astbury K & O'Leary JJ (2006) Molecular profiling of cervical neoplasia. *Expert*

Mendes Soares LM & Valcarcel J (2006) The expanding transcriptome: the genome as the

Mikheev AM, Mikheeva SA, Liu B, Cohen P & Zarbl H (2004) A functional genomics

Mook S, Schmidt MK, Viale G, Pruneri G, Eekhout I, Floore A, Glas AM, Bogaerts J, Cardoso

Nees M, Geoghegan JM, Hyman T, Frank S, Miller L & Woodworth CD (2001)

responsive genes in cervical keratinocytes. *Journal of virology* 75, 4283-4296. Nees M, Geoghegan JM, Munson P, Prabhu V, Liu Y, Androphy E & Woodworth CD (2000)

Nees M, van Wijngaarden E, Bakos E, Schneider A & Durst M (1998) Identification of novel

Ng P, Wei CL, Sung WK, Chiu KP, Lipovich L, Ang CC, Gupta S, Shahab A, Ridwan A,

suppressor of HeLa cell transformation. *Carcinogenesis* 25, 47-59.

approach for the identification of putative tumor suppressor genes: Dickkopf-1 as

F, Piccart-Gebhart MJ, Rutgers ET & Van't Veer LJ (2009) The 70-gene prognosissignature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study. *Breast cancer research and*

Papillomavirus type 16 oncogenes downregulate expression of interferonresponsive genes and upregulate proliferation-associated and NF-kappaB-

Human papillomavirus type 16 E6 and E7 proteins inhibit differentiationdependent expression of transforming growth factor-beta2 in cervical

molecular markers which correlate with HPV-induced tumor progression.

Wong CH, Liu ET & Ruan Y (2005) Gene identification signature (GIS) analysis for transcriptome characterization and genome annotation. *Nature Methods* 2, 105-111. Nieh S, Chen SF, Chu TY, Lai HC, Lin YS, Fu E & Gau CH (2005) Is p16(INK4A) expression

more useful than human papillomavirus test to determine the outcome of atypical

lines before and after ionizing radiation. *International journal of oncology* 22, 1091-

CW, Kobayashi M, Horton H & Brown EL (1996) Expression monitoring by hybridization to high-density oligonucleotide arrays. *Nature Biotechnology* 14, 1675-

adenocarcinoma of the uterine cervix: a possible immunohistochemical marker of a

the polymerase chain reaction. *Science* 257, 967-971.

*Cancer* 3, 869-876.

1099.

1680.

50-59.

*molecular diagnostics* 8, 263-276.

favorable prognosis. *Cancer* 82, 2409-2417.

*review of molecular diagnostics* 6, 217-229.

*treatment* 116, 295-302.

*Oncogene* 16, 2447-2458.

'Book of Sand'. *The EMBO Journal* 25, 923-931.

keratinocytes. *Cancer research* 60, 4289-4298.

squamous cells of undetermined significance-categorized Pap smear? A comparative analysis using abnormal cervical smears with follow-up biopsies. *Gynecologic oncology* 97, 35-40.

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 191

Silvestri A, Colombatti A, Calvert VS, Deng J, Mammano E, Belluco C, De Marchi F, Nitti D,

Slodkowska EA & Ross JS (2009) MammaPrint 70-gene signature: another milestone in

Snijders PJ, Steenbergen RD, Heideman DA & Meijer CJ (2006) HPV-mediated cervical

Sopov I, Sorensen T, Magbagbeolu M, Jansen L, Beer K, Kuhne-Heid R, Kirchmayr R,

Southan C (2004) Has the yo-yo stopped? An assessment of human protein-coding gene

Sova P, Feng Q, Geiss G, Wood T, Strauss R, Rudolf V, Lieber A & Kiviat N (2006) Discovery

Steinau M, Lee DR, Rajeevan MS, Vernon SD, Ruffin MT & Unger ER (2005) Gene

Strausberg RL, Feingold EA, Grouse LH, Derge JG, Klausner RD, Collins FS, Wagner L,

Strebhardt K & Ullrich A (2006) Targeting polo-like kinase 1 for cancer therapy. *Nature*

Tangrea MA, Chuaqui RF, Gillespie JW, Ahram M, Gannot G, Wallis BS, Best CJ, Linehan

WM, Liotta LA, Pohida TJ, Bonner RF & Emmert-Buck MR (2004) Expression microdissection: operator-independent retrieval of cells for molecular profiling.

in severe cervical neoplasia. *International journal of cancer* 112, 33-43.

Stein LD (2004) Human genome: end of the beginning. *Nature* 431, 915-916.

*Sciences of the United States of America* 99, 16899-16903.

*Diagnostic molecular pathology* 13, 207-212.

*Reviews Cancer* 6, 321-330.

micromirror array. *Nature Biotechnology* 17, 974-978.

*diagnostics* 9, 417-422.

number. *Proteomics* 4, 1712-1726.

biomarker discovery. *BMC Genomics* 6, 64.

164.

Liotta LA, Petricoin EF & Pierobon M (2010) Protein pathway biomarker analysis of human cancer reveals requirement for upfront cellular-enrichment processing. *Laboratory investigation; a journal of technical methods and pathology* 90, 787-796.  *Expert review of molecular*

carcinogenesis: concepts and clinical implications. *The Journal of pathology* 208, 152-

Schneider A & Durst M (2004) Detection of cancer-related gene expression profiles

of novel methylation biomarkers in cervical carcinoma by global demethylation and microarray analysis. *Cancer epidemiology, biomarkers & prevention* 15, 114-123.

expression profile of cervical tissue compared to exfoliated cells: impact on

Shenmen CM, Schuler GD, Altschul SF, Zeeberg B, Buetow KH, Schaefer CF, Bhat NK, Hopkins RF, Jordan H, Moore T, Max SI, Wang J, Hsieh F, Diatchenko L, Marusina K, Farmer AA, Rubin GM, Hong L, Stapleton M, Soares MB, Bonaldo MF, Casavant TL, Scheetz TE, Brownstein MJ, Usdin TB, Toshiyuki S, Carninci P, Prange C, Raha SS, Loquellano NA, Peters GJ, Abramson RD, Mullahy SJ, Bosak SA, McEwan PJ, McKernan KJ, Malek JA, Gunaratne PH, Richards S, Worley KC, Hale S, Garcia AM, Gay LJ, Hulyk SW, Villalon DK, Muzny DM, Sodergren EJ, Lu X, Gibbs RA, Fahey J, Helton E, Ketteman M, Madan A, Rodrigues S, Sanchez A, Whiting M, Young AC, Shevchenko Y, Bouffard GG, Blakesley RW, Touchman JW, Green ED, Dickson MC, Rodriguez AC, Grimwood J, Schmutz J, Myers RM, Butterfield YS, Krzywinski MI, Skalska U, Smailus DE, Schnerch A, Schein JE, Jones SJ & Marra MA (2002) Generation and initial analysis of more than 15,000 fulllength human and mouse cDNA sequences. *Proceedings of the National Academy of*

molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. *The New England journal of medicine* 346, 1937-1947.

Rosty C, Sheffer M, Tsafrir D, Stransky N, Tsafrir I, Peter M, de Cremoux P, de La

Ruutu M, Peitsaro P, Johansson B & Syrjanen S (2002) Transcriptional profiling of a human

Sakakura C, Hagiwara A, Miyagawa K, Nakashima S, Yoshikawa T, Kin S, Nakase Y, Ito K,

Santin AD, Zhan F, Bignotti E, Siegel ER, Cane S, Bellone S, Palmieri M, Anfossi S, Thomas

Schena M, Shalon D, Davis RW & Brown PO (1995) Quantitative Monitoring of Gene-

Segal E, Friedman N, Kaminski N, Regev A & Koller D (2005) From signatures to models: understanding cancer using microarrays. *Nature Genetics* 37 Suppl, S38-45. Seo MJ, Bae SM, Kim YW, Hur SY, Ro DY, Lee JM, Namkoong SE, Kim CK & Ahn WS (2005)

cervical carcinoma by gene ontology. *Gynecologic oncology* 96, 621-629. Sgarlato GD, Eastman CL & Sussman HH (2005) Panel of genes transcriptionally up-

quantitative reverse transcription-PCR. *Clinical chemistry* 51, 27-34.

Shapiro JA (2009) Revisiting the central dogma in the 21st century. *Annals of the New York*

Sherman ME (2003) Chapter 11: Future directions in cervical pathology. *Journal of the*

Sherman ME & Kurman RJ (1998) Intraepithelial carcinoma of the cervix: reflections on half

Shim C, Zhang W, Rhee CH & Lee JH (1998) Profiling of differentially expressed genes in

Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RC, Gaasenbeek M, Angelo M,

human primary cervical cancer by complementary DNA expression array. *Clinical*

Reich M, Pinkus GS, Ray TS, Koval MA, Last KW, Norton A, Lister TA, Mesirov J, Neuberg DS, Lander ES, Aster JC & Golub TR (2002) Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning.

lymphoma. *The New England journal of medicine* 346, 1937-1947.

gastric cancer. *International journal of cancer* 113, 221-228.

carcinoma. *Oncogene* 24, 7094-7104.

*Virology* 331, 269-291.

*Academy of Sciences* 1178, 6-28.

*cancer research* 4, 3045-3050.

*Nature medicine* 8, 68-74.

*National Cancer Institute. Monographs*, 72-79.

a century of progress. *Cancer* 83, 2243-2246.

molecular profiling to predict survival after chemotherapy for diffuse large-B-cell

Rochefordiere A, Salmon R, Dorval T, Thiery JP, Couturier J, Radvanyi F, Domany E & Sastre-Garau X (2005) Identification of a proliferation gene cluster associated with HPV E6/E7 expression level and viral DNA load in invasive cervical

papillomavirus 33-positive squamous epithelial cell line which acquired a selective growth advantage after viral integration. *International journal of cancer* 100, 318-326.

Yamagishi H, Yazumi S, Chiba T & Ito Y (2005) Frequent downregulation of the runt domain transcription factors RUNX1, RUNX3 and their cofactor CBFB in

M, Burnett A, Kay HH, Roman JJ, O'Brien TJ, Tian E, Cannon MJ, Shaughnessy J, Jr. & Pecorelli S (2005) Gene expression profiles of primary HPV16- and HPV18 infected early stage cervical cancers and normal cervical epithelium: identification of novel candidate molecular markers for cervical cancer diagnosis and therapy.

Expression Patterns with a Complementary-DNA Microarray. *Science* 270, 467-470.

New approaches to pathogenic gene function discovery with human squamous cell

regulated in squamous cell carcinoma of the cervix identified by representational difference analysis, confirmed by macroarray, and validated by real-time

A Transcriptome- and Marker-Based Systemic Analysis of Cervical Cancer 193

Wei CL, Wu Q, Vega VB, Chiu KP, Ng P, Zhang T, Shahab A, Yong HC, Fu YT, Weng ZP,

Wells SI, Aronow BJ, Wise TM, Williams SS, Couget JA & Howley PM (2003) Transcriptome

Wheeler DL, Barrett T, Benson DA, Bryant SH, Canese K, Chetvernin V, Church DM,

Whitfield ML, George LK, Grant GD & Perou CM (2006) Common markers of proliferation.

Wilting SM, Snijders PJ, Meijer GA, Ylstra B, van den Ijssel PR, Snijders AM, Albertson DG,

Wong YF, Cheung TH, Tsao GS, Lo KW, Yim SF, Wang VW, Heung MM, Chan SC, Chan

oligonucleotide microarray. *International journal of cancer* 118, 2461-2469. Wong YF, Selvanayagam ZE, Wei N, Porter J, Vittal R, Hu R, Lin Y, Liao J, Shih JW, Cheung

Woodman CBJ, Collins SI & Young LS (2007) The natural history of cervical HPV infection:

Woodworth CD, Michael E, Marker D, Allen S, Smith L & Nees M (2005) Inhibition of the

Yamashita T, Honda M & Kaneko S (2008) Application of Serial Analysis of Gene Expression

Yen CC, Chen YJ, Pan CC, Lu KH, Chen PC, Hsia JY, Chen JT, Wu YC, Hsu WH, Wang LS,

Yim EK & Park JS (2006) Role of proteomics in translational research in cervical cancer.

in cancer research. *Current pharmaceutical biotechnology* 9, 375-382.

progressed. *World journal of gastroenterology : WJG* 11, 1267-1272.

by DNA microarray. *Clinical cancer research* 9, 5486-5492.

unresolved issues. *Nature Reviews Cancer* 7, 11-22.

*Expert review of proteomics* 3, 21-36.

Coffa J, Schouten JP, van de Wiel MA, Meijer CJ & Steenbergen RD (2006) Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. *The Journal of pathology* 209, 220-230.

LK, Ho TW, Wong KW, Li C, Guo Y, Chung TK & Smith DI (2006) Genome-wide gene expression profiling of cervical cancer in Hong Kong women by

TH, Lo KW, Yim SF, Yip SK, Ngong DT, Siu N, Chan LK, Chan CS, Kong T, Kutlina E, McKinnon RD, Denhardt DT, Chin KV & Chung TK (2003) Expression genomics of cervical cancer: molecular classification and prediction of radiotherapy response

epidermal growth factor receptor increases expression of genes that stimulate inflammation, apoptosis, and cell attachment. *Molecular cancer therapeutics* 4, 650-

Huang MH, Huang BS, Hu CP, Chen PM & Lin CH (2005) Copy number changes of target genes in chromosome 3q25.3-qter of esophageal squamous cell carcinoma: TP63 is amplified in early carcinogenesis but down-regulated as disease

binding sites in the human genome. *Cell* 124, 207-219.

*America* 100, 7093-7098.

*Acids Research* 36, D13-21.

658.

*Nature Reviews Cancer* 6, 99-106.

Liu JJ, Zhao XD, Chew JL, Lee YL, Kuznetsov VA, Sung WK, Miller LD, Lim B, Liu ET, Yu Q, Ng HH & Ruan YJ (2006) A global map of p53 transcription-factor

signature of irreversible senescence in human papillomavirus-positive cervical cancer cells. *Proceedings of the National Academy of Sciences of the United States of*

Dicuccio M, Edgar R, Federhen S, Feolo M, Geer LY, Helmberg W, Kapustin Y, Khovayko O, Landsman D, Lipman DJ, Madden TL, Maglott DR, Miller V, Ostell J, Pruitt KD, Schuler GD, Shumway M, Sequeira E, Sherry ST, Sirotkin K, Souvorov A, Starchenko G, Tatusov RL, Tatusova TA, Wagner L & Yaschenko E (2008) Database resources of the National Center for Biotechnology Information. *Nucleic*

Tewari D, Monk BJ, Al-Ghazi MS, Parker R, Heck JD, Burger RA & Fruehauf JP (2005) Gene

Thierry F, Benotmane MA, Demeret C, Mori M, Teissier S & Desaintes C (2004) A genomic

Thomas JT, Oh ST, Terhune SS & Laimins LA (2001) Cellular changes induced by low-risk

Thorgeirsson SS, Lee JS & Grisham JW (2006) Functional genomics of hepatocellular

Tian S, Roepman P, Van't Veer LJ, Bernards R, de Snoo F & Glas AM (2010) Biological

Toussaint-Smith E, Donner DB & Roman A (2004) Expression of human papillomavirus type

Usmani N, Foroudi F, Du J, Zakos C, Campbell H, Bryson P & Mackillop WJ (2005) An

van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy

van de Vijver MJ, He YD, van't Veer LJ, Dai H, Hart AA, Voskuil DW, Schreiber GJ, Peterse

Vazquez-Ortiz G, Ciudad CJ, Pina P, Vazquez K, Hidalgo A, Alatorre B, Garcia JA,

Vazquez-Ortiz G, Pina-Sanchez P, Vazquez K, Duenas A, Taja L, Mendoza P, Garcia JA &

Velculescu VE, Zhang L, Vogelstein B & Kinzler KW (1995) Serial Analysis of Gene-

Vogelstein B & Kinzler KW (2004) Cancer genes and the pathways they control. *Nature*

Wadlow R & Ramaswamy S (2005) DNA microarrays in clinical cancer research. *Current*

Wain HM, Lush MJ, Ducluzeau F, Khodiyar VK & Povey S (2004) Genew: the Human Gene Nomenclature Database, 2004 updates. *Nucleic Acids Research* 32, D255-257.

feasibility study. *Gynecologic oncology* 99, 84-91.

hallmarks of cancer. *Biomark Insights* 5, 129-138.

expression of angiogenic factors. *Oncogene* 23, 2988-2995.

*research* 64, 895-903.

827.

*Journal of virology* 75, 7564-7571.

carcinoma. *Hepatology* 43, S145-150.

of breast cancer. *Nature* 415, 530-536.

*research* 36, 448-458.

*medicine* 10, 789-799.

*New England journal of medicine* 347, 1999-2009.

12 in cervical cancer. *BMC Cancer* 5, 68.

Expression. *Science* 270, 484-487.

*molecular medicine* 5, 111-120.

expression profiling of in vitro radiation resistance in cervical carcinoma: a

approach reveals a novel mitotic pathway in papillomavirus carcinogenesis. *Cancer*

human papillomavirus type 11 in keratinocytes that stably maintain viral episomes.

functions of the genes in the mammaprint breast cancer profile reflect the

16 E6 and E7 oncoproteins in primary foreskin keratinocytes is sufficient to alter the

evidence-based estimate of the appropriate rate of utilization of radiotherapy for cancer of the cervix. *International journal of radiation oncology, biology, physics* 63, 812-

K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R & Friend SH (2002) Gene expression profiling predicts clinical outcome

JL, Roberts C, Marton MJ, Parrish M, Atsma D, Witteveen A, Glas A, Delahaye L, van der Velde T, Bartelink H, Rodenhuis S, Rutgers ET, Friend SH & Bernards R (2002) A gene-expression signature as a predictor of survival in breast cancer. *The*

Salamanca F, Peralta-Rodriguez R, Rangel A & Salcedo M (2005a) Gene identification by cDNA arrays in HPV-positive cervical cancer. *Archives of medical*

Salcedo M (2005b) Overexpression of cathepsin F, matrix metalloproteinases 11 and

**12**

*Morocco*

**Evaluation of p53, p16INK4a and**

**for Cervical Cancer Diagnosis**

*1Unité de Biologie et Recherche Médicale, Centre National de l'Energie, des Sciences et Techniques Nucléaires (CNESTEN), Rabat*

*3Laboratoire Virologie Hygiène and Microbiologie, Faculté des Sciences et Techniques Mohammédia*

**E-Cadherin Status as Biomarkers**

M. El Mzibri1,\*, M. Attaleb1, R. Ameziane El Hassani1, M. Khyatti2, L. Benbacer1, M. M. Ennaji3 and M. Amrani4

*2Laboratoire d'Onco-Virologie, Institut Pasteur du Maroc, Casablanca*

*4Service d'Anatomie Pathologique, Institut National d'Oncologie, Rabat*

Worldwide, carcinoma of the uterine cervix is one of the most common malignancies among women. Incidence rates of this disease vary from about 5 cases per 100 000 women per year in many industrialized countries to more than 50 per 100 000 in some developing nations. Approximately 80% of all cases occur in less-developed countries, because prevention programs are either non-existent or poorly conducted (WHO, 2009). Furthermore, in the less developed areas of the world, cervical cancer begins to strike significantly among women as young as 25-30 years of age, clearly identifying this disease

Clinical epidemiology have clearly identified that the association between infection with high-risk types of human papillomavirus (HPV) and high-grade cervical cancer precursors as well as cervical cancer is very strong (Wright Jr., 2006). However, even highrisk HPV infection are widespread in the world, the majority of HPV-associated lesions such as cervical intraepithelial neoplasia (CIN) will remain stable or spontaneously regress over time (zur Hausen, 2000; Ferenczy, 2001; Holowaty, 1999; Syrjanen, 1996), suggesting that other genetic and epigenetic events are likely to be involved in cervical carcinogenesis. Indeed, genomic alterations leading to tumor suppressor gene inactivation and/or oncogene activation are the critical pathways in the development and progression of cervical cancer as well as the other types of cancer. In this field, p53, p16 and Ecadherin are important proteins that play critical role in the development and the

**1.

Corresponding Author

 \*

## **Evaluation of p53, p16INK4a and E-Cadherin Status as Biomarkers for Cervical Cancer Diagnosis**

M. El Mzibri1,\*, M. Attaleb1, R. Ameziane El Hassani1, M. Khyatti2, L. Benbacer1, M. M. Ennaji3 and M. Amrani4 *1Unité de Biologie et Recherche Médicale, Centre National de l'Energie, des Sciences et Techniques Nucléaires (CNESTEN), Rabat 2Laboratoire d'Onco-Virologie, Institut Pasteur du Maroc, Casablanca 3Laboratoire Virologie Hygiène and Microbiologie, Faculté des Sciences et Techniques Mohammédia 4Service d'Anatomie Pathologique, Institut National d'Oncologie, Rabat Morocco*

#### **1. Introduction**

194 Topics on Cervical Cancer with an Advocacy for Prevention

Yuan J, Yan R, Kramer A, Eckerdt F, Roller M, Kaufmann M & Strebhardt K (2004) Cyclin B1

Zimmermann CR, Orr WC, Leclerc RF, Barnard EC & Timberlake WE (1980) Molecular

zur Hausen H (2002) Papillomaviruses and cancer: from basic studies to clinical application.

zur Hausen H (2009) The search for infectious causes of human cancers: Where and why (Nobel lecutre). *Angewandte Chemie International Edition* 48, 5798-5808.

*Oncogene* 23, 5843-5852.

*Nature Reviews Cancer* 2, 342-350.

715.

depletion inhibits proliferation and induces apoptosis in human tumor cells.

cloning and selection of genes regulated in Aspergillus development. *Cell* 21, 709-

Worldwide, carcinoma of the uterine cervix is one of the most common malignancies among women. Incidence rates of this disease vary from about 5 cases per 100 000 women per year in many industrialized countries to more than 50 per 100 000 in some developing nations. Approximately 80% of all cases occur in less-developed countries, because prevention programs are either non-existent or poorly conducted (WHO, 2009). Furthermore, in the less developed areas of the world, cervical cancer begins to strike significantly among women as young as 25-30 years of age, clearly identifying this disease as the cancer priority in women.

Clinical epidemiology have clearly identified that the association between infection with high-risk types of human papillomavirus (HPV) and high-grade cervical cancer precursors as well as cervical cancer is very strong (Wright Jr., 2006). However, even highrisk HPV infection are widespread in the world, the majority of HPV-associated lesions such as cervical intraepithelial neoplasia (CIN) will remain stable or spontaneously regress over time (zur Hausen, 2000; Ferenczy, 2001; Holowaty, 1999; Syrjanen, 1996), suggesting that other genetic and epigenetic events are likely to be involved in cervical carcinogenesis. Indeed, genomic alterations leading to tumor suppressor gene inactivation and/or oncogene activation are the critical pathways in the development and progression of cervical cancer as well as the other types of cancer. In this field, p53, p16 and Ecadherin are important proteins that play critical role in the development and the progression of cervical cancer.

<sup>\*</sup> Corresponding Author

Evaluation of p53, p16INK4a and E-Cadherin

1988).

(Filippova, 2004).

Hausen, 2009).

Status as Biomarkers for Cervical Cancer Diagnosis 197

E5 expression enhances oncogenic potential (Stoppler, 1996; Maufort, 2010) but the exact function of E5 remains poorly understood. E6 and E7 expression is essential for maintenance of the transformed state and malignant progression (Bosch, 1990; von Knebel Doeberitz,

The implication of E6 and E7 proteins in cervical cancer progression is mainly due through their interactions with hTERT, p53 and Retinoblastoma protein (pRB). hTERT is a catalytic subunit of Telomerase that acts to synthesise telomere ends of linear chromosomes during DNA replication. p53 is a transcription factor that regulates cell cycle arrest, apoptosis, senescence, DNA repair and cell metabolism; p53 activity is inhibited by ubiquitin ligase which also ubiquitinates p53 to initiate p53 degradation (Figure 1). In addition to inducing the rapid degradation of p53, E6 also binds to and degrades FADD, preventing the transmission of apoptotic signals via the Fas pathway

pRB is a tumour suppressor protein and interacts with transcription factor E2F to repress the transcription of genes required for the S phase of the cell cycle (Figure 1). E7 can also bind to

Currently vaccination based strategy is an alternative method showed to be amore effective and practical approach than the implementation of regular and periodic cytological screening. Today it is very well established that intervention with vaccines permits already the statement that essential precursor lesions of this cancer are efficiently prevented (Zur

other connected proteins such as p107 and p130 (Raybould, 2011).

Fig. 1. Schematic representation of E6 and E7 activities in cervical cells

### **2. Human papillomavirus and cervical cancer**

Association between HPV and cervical lesions and cancer has started in 1970s' years after the hypothesis that cervical cancer may arise from infections with the virus found in condylomata acuminata (zur Hausen, 1975; 1976). Then epidemiological and clinical studies have clearly demonstrated that HPV are the major etiologic agents of neoplasia of the cutaneous and mucosal epithelia; HPV positivity in cervical cancer is estimated to be between 90% and 95% (zur Hausen, 1991; Munoz, 2003). Currently, there is compelling evidence to indicate that the development of human cervical cancer without involvement of the specific HPV is exceptional.