Personalized cancer treatment is a tuned method based on the patient's diagnosis and background. Microfluidic technology offers sensitive detection with higher throughput, as well as reduced time and costs. For personalized cancer treatment, tumor composition and drug sensitivities are very important.
A patient's drug response can be predicted based on the status of biomarkers, or the severity and progression of the disease can be predicted based on the atypical presence of specific cells. Drop-qPCR is a droplet microfluidic technology in which droplets are transported in a reusable capillary and alternately flow through two areas maintained at different constant temperatures and fluorescence detection. It can be efficient with a low contamination risk to detect Her2. A digital droplet‐based PCR method can be used to detect the KRAS mutations with TaqMan probes, to enhance detection of the mutative gene ratio. In addition, accurate prediction of postoperative disease progression in breast or prostate cancer patients is essential for determining post-surgery treatment. A simple microfluidic chamber, coated with a carefully formulated extracellular matrix mixture is used for cells obtained from tumor biopsy after 72 hours of growth and a thorough evaluation of cells by imaging.
Microfluidics is also suitable for circulating tumor cells (CTCs) and non-CTCs liquid biopsy analysis. Beads conjugate to anti‐epithelial cell adhesion molecule (EpCAM) antibodies for positive selection in the CTCs isolation chip (iCHIP). CTCs can also be detected by using the acidification of the tumor microenvironment and the difference in membrane capacitance. CTCs are isolated from blood by a microfluidic device, and are cultured on-chip, which can be a method to capture more biological information in a single analysis. For example, it can be used to test the cell survival rate of 40 different drugs or drug combinations. Tumor‐derived extracellular vesicles can be isolated from urine and detected by an integrated double‐filtration microfluidic device; they also can be isolated from blood and detected by electrochemical sensing method with a two‐level amplification enzymatic assay.
Tumor materials can directly be used for detection through microfluidic devices. To screen primary cells for drugs, it is often necessary to distinguish cancerous cells from non-cancerous cells. A microfluidic chip based on the capacity of cells to pass small constrictions can sort the cell types, metastases. Droplet‐based microfluidic devices have the potential to screen different drugs or combinations of drugs, directly on the primary tumor sample with high accuracy. To improve this strategy, the microfluidic program with a sequential manner of drug cocktails, coupled with fluorescent barcodes, is more efficient. Another advanced strategy is detecting growth rates of single-cell by using suspended microchannel resonators, which can predict drug sensitivities of rare CTCs.
Microfluidics devices also can simulate the tumor microenvironment, to help to test anticancer drugs. Microfluidic devices with 2D or 3D cell cultures can be used to analyze spheroids for different cancer systems (such as lung cancer and ovarian cancer), and are essential for multiple anti-cancer drugs and toxicity tests. This strategy can be improved by increasing the throughput and production of spheroids. For example, one droplet-based microfluidic device for 3D cell culture produces 500 spheroids per chip. These spheroids can be cultured longer in different surroundings to analyze and monitor. The other advanced technology is organs‐on‐a‐chip, and it can be used to simulate several organs to determine the drug metabolism and activity based on vessels mimicking, as well as mimic pH, oxygen... to analyze the relationship between drugs and human organ surroundings.
A recent strategy is single-cell chromatin immunoprecipitation (ChiP)‐Sequencing in droplets, which operates by combining droplet‐based single cell RNA sequencing with DNA‐barcoded antibodies, possibly to explore the tumor heterogeneity by the genotype and phenotype to select the personalized anti-cancer drugs and prevent the cancer relapse.