What is cancer genomic testing?
How does cancer genomic testing work?
Utility of cancer genomic testing
References
Further reading
Cancer genome testing has revolutionized the field of cancer care by easing the development of personalized medicine.
The development of targeted therapies through individual-level cancer genome analysis is considered the most promising approach for better cancer management.
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What is cancer genomic testing?
Cancer is a highly heterogeneous disease, with different cancer cells showing distinct morphologic, genetic, and phenotypic profiles. Even a single type of cancer can have distinct profiles in two patients, making it harder for physicians to choose optimal treatments for each patient.
Cancer genomic assays have been designed to identify DNA mutations, mutational load, and tumor-specific antigens that are triggering the development and progression of a specific cancer.
Characterization of somatic and germline defects in individual tumor samples by genomic assays can help physicians select appropriate medicines for each patient, thus paving the way toward personalized medicine.
While germline genomic analysis helps identify future cancer risks among patients and their family members, somatic and germline genomic analyses are associated with identifying personalized medicine, personalized prognosis, and cancer monitoring.
How does cancer genomic testing work?
Cancer genomic testing works by sampling the patient's blood, plasma, or other biological fluids and isolating cancer cell-derived circulating DNA from the liquid biopsy samples.
The circulating tumor DNA (ctDNA) is subjected to next-generation sequencing to identify driver mutations and monitor treatment response and the emergence of treatment resistance.
Liquid biopsy next-generation sequencing is emerging as an effective alternative to conventional tissue biopsy. Liquid biopsy is less invasive and has higher potency to identify cancer-specific biomarkers and a faster turnaround time than a tissue biopsy. Liquid biopsy can detect somatic mutations in ctDNA during treatment and follow-up.
This information can be compared with the findings of baseline tissue biopsy conducted after cancer diagnosis and before tumor resection. Liquid biopsy findings can also be compared with conventional imaging-based results to monitor tumor recurrence or the emergence of treatment resistance.
Despite promising clinical outcomes in cancer diagnosis and treatment, the widespread application of liquid biopsy to screen asymptomatic populations has been restricted by certain shortcomings. Asymptomatic patients with early-stage cancers release lower levels of ctDNA, making liquid biopsy challenging.
What is Personalized Medicine?
Utility of cancer genomic testing
Cancer genomic testing through next-generation sequencing of cancer samples provides enormous information about the cancer genome, including sequence mutations, insertion/deletion mutations, altered copy number, structural rearrangement, and loss of heterozygosity (genetic diversity) in DNA.
The RNA samples isolated from tumors can be subjected to next-generation sequencing to identify differentially expressed genes, gene fusion, small RNAs, aberrantly spliced isoforms, and allele-specific expression patterns.
Targeted molecular therapies can clinically inhibit driver mutations identified through next-generation sequencing. Trastuzumab and imatinib were the first targeted medicines approved for treating patients with HER2-amplified metastatic breast cancer and BCR–ABL-fusion-positive chronic myelogenous leukemia, respectively. Various clinically-approved targeted therapies are available to treat non-small-cell lung cancer, melanoma, and colorectal cancer.
Tumor DNA, non-tumor genomic DNA, and tumor RNA samples isolated from the same patient can be subjected to next-generation sequencing to identify somatic variants that have the potential to alter amino acid sequences in the resulting protein. These predictions of somatic variations are parsed into the resulting novel peptides, which a neoantigen predictor then evaluates to generate a final neoantigen prediction list.
Neoantigens generated by computational predictions with the highest affinity to class I or class II Human Leukocyte Antigen (HLA) molecules can be used to design personalized anticancer vaccines based on RNA, DNA, or protein.
Genetic signatures generated by genomic testing can be utilized for cancer classification. Four new subtypes of endometrial cancer have been identified through genetic analysis of patient-derived tumor samples. This analysis further helps identify which subtype is more aggressive and requires more rigorous treatment.
Similarly, genetic analysis of breast cancer has made it possible to detect distinct genetic signatures that can accurately identify patients who can get maximum benefits from estrogen-lowering drugs.
Genomic testing can facilitate the repurposing of anticancer drugs by identifying genetically similar cancers. Studies have identified similar genetic profiles between endometrial cancers, a lethal subtype of ovarian cancer, and basal-like breast cancer. Moreover, studies have identified novel genetic mutations in breast cancer patients, which have already been identified in patients with leukemia, prostate, colorectal, lung, or skin cancers.
Thus, patients with these novel mutations can be treated with drugs already clinically approved for treating genetically similar cancers.
Methylation sequencing is a promising approach to detecting altered DNA methylation patterns and other epigenetic changes in cancer. DNA methylation is an epigenetic modification that can change gene expression without altering DNA code.
Similar to genetic mutations, epigenetic changes can trigger tumorigenesis and impact the emergence of treatment resistance. Some epigenetic inhibitors, including azacytidine, developed in recent years have shown promising outcomes in modulating the efficacy of immunotherapies and preventing drug resistance.
Recently developed targeted methylation sequencing has shown promising outcomes in detecting cancer at an early stage. This technique has been found to detect more than 50 types of cancers, across all stages, with more than 99% specificity.
Cancer genomic testing can provide opportunities for shared decision-making. Actionable genomic information can be used to educate cancer patients about their susceptibility, risk, and disease prognosis.
This information can also be used to increase awareness about cancer risks among patients' family members and encourage them to cancer screening and adopt preventive strategies.
References
Further reading
Breakthrough study unravels molecular subtypes of breast cancer