Somatic variant calling is the computational process used to identify genetic changes that occur in diseased tissue, such as a tumor, but are not inherited from a parent. This analysis provides the molecular blueprint of an individual’s cancer. By pinpointing the exact genetic alterations that drive malignant growth, this specialized analysis shifts the focus from general disease mechanisms to a patient-specific understanding of cancer. This information is foundational for advancing personalized medicine and developing targeted therapeutic strategies.
Defining Somatic Versus Germline Variants
The distinction between somatic and germline variants is the central concept in cancer genomics. Germline variants are inherited from parents and are present in every cell of the body, including healthy tissue. These variants represent an individual’s constitutional genetic makeup. While some may predispose a person to cancer, they are not the acquired mutations that drive the tumor itself.
Somatic variants are acquired mutations that arise during a person’s lifetime, typically due to errors in DNA replication or environmental factors. These changes are confined to specific cells, such as those within a tumor, and are not passed on to offspring. The primary goal of somatic variant calling is to isolate these acquired tumor-specific variants from the tens of thousands of harmless germline variants found throughout the genome.
The Necessity of Paired Sample Comparison
Identifying somatic mutations requires a differential analysis, which is why sequencing tumor DNA alone is insufficient for accurate results. A single tumor sample contains both acquired somatic variants and the patient’s complete set of inherited germline variants. To isolate these somatic variants, the industry standard is to employ a paired tumor-normal sequencing strategy.
This approach involves collecting two samples from the same patient: a tumor sample (the case) and a corresponding normal sample (the control), which is often healthy tissue like peripheral blood or adjacent non-cancerous tissue. Both samples undergo next-generation sequencing to generate raw genetic data. The computational variant calling pipeline then performs a direct comparison of the two sequenced genomes at every single position.
Any genetic change present in the tumor sample but absent in the matched normal sample is classified as a somatic variant. Conversely, any variant found in both samples at comparable frequencies is filtered out as a germline variant. This comparative subtraction is performed by specialized software tools, which use statistical models to distinguish true biological signals from sequencing errors. The matched normal sample acts as the patient’s unique genetic reference.
Categories of Somatic Variants Identified
Somatic variant calling pipelines are designed to detect a spectrum of genetic alterations.
Single Nucleotide Variants (SNVs)
The smallest and most common type is the Single Nucleotide Variant (SNV), which involves the substitution of a single DNA base pair for another. If an SNV occurs within a protein-coding region, it can change a single amino acid in the resulting protein, potentially altering its function to become oncogenic.
Insertions and Deletions (Indels)
Indels involve the addition or removal of a few DNA base pairs, generally less than 50 base pairs. If an Indel occurs within the coding sequence of a gene, especially one that is not a multiple of three, it can cause a frameshift. This frameshift completely changes the downstream amino acid sequence, often leading to a premature stop codon and a non-functional protein product.
Structural Variants (SVs)
Larger-scale changes are classified as Structural Variants (SVs), which are greater than 50 base pairs and dramatically rearrange genomic architecture. These include Copy Number Variations (CNVs), where entire segments of DNA are deleted or duplicated, resulting in an abnormal number of gene copies. Gene amplifications can lead to the overproduction of a cancer-driving protein, such as the ERBB2 gene in breast cancer. Other SVs involve inversions or translocations, potentially creating oncogenic fusion genes.
Real-World Applications in Cancer Genomics
The successful identification of somatic variants has transformed the clinical management of cancer, moving beyond broad treatment protocols to personalized care. One of the most direct applications is guiding therapeutic selection, where specific somatic mutations are matched with targeted drugs. For instance, the detection of a BRAF V600E mutation in melanoma or colorectal cancer indicates a patient is likely to respond to a BRAF inhibitor drug.
Somatic variant profiles also provide information for predicting patient outcomes and monitoring disease progression. Quantification of the Tumor Mutational Burden (TMB)—the total number of somatic mutations in a tumor—is a predictive biomarker for response to immunotherapy in several cancer types. A high TMB suggests the tumor cells have produced many abnormal proteins, making them more visible and vulnerable to attack by the patient’s immune system.
Analyzing somatic variants allows researchers to track the evolution of a tumor over time and understand the mechanisms of drug resistance. By comparing the somatic variants in a primary tumor to those in a recurring or metastatic lesion, scientists can identify new mutations that arose during treatment. This information is then used to adjust treatment strategies.