The Neoantigen Landscape of the Coding and Noncoding Cancer Genome Space.

Tumor mutation burden (TMB) is a measure to predict patient responsiveness to immune checkpoint immunotherapy because with increased mutation frequency, the likelihood of a greater neoantigen burden is increased. Although neoantigen prediction tools exist, tumor neoantigen burden has not been adopted as a measure to predict immunotherapy response. With both measures, current guidelines are limited to the coding regions, but ectopic expression of sequences in the noncoding space may potentially be a source of neoantigens. A pan-cancer cohort of 574 advanced disease stage patients with whole genome and transcriptome sequencing was analyzed to report mutation burden and neoantigen counts within the coding and noncoding regions. The efficacy of tumor neoantigen burden, reported as tumor neoantigen count (TNC), including neoantigens derived from the expression of noncoding regions, compared with TMB as a predictor of response to immunotherapy for 80 patients who had received treatment, was evaluated. TMB was found to be the best predictor of response to immunotherapy, whereas expression-derived TNC from the noncoding regions did not improve prediction of response. Therefore, there is minimal benefit in extending the calculation of TNC to the noncoding space for the purposes of predicting response. However, it is likely that there is a wealth of neoantigens derived from the noncoding space that may impact patient outcomes and treatments.

Use of Treatment-Focused Tumor Sequencing to Screen for Germline Cancer Predisposition.

Next-generation sequencing assays are capable of identifying cancer patients eligible for targeted therapies and can also detect germline variants associated with increased cancer susceptibility. However, these capabilities have yet to be routinely harmonized in a single assay because of challenges with accurately identifying germline variants from tumor-only data. We have developed the Oncology and Hereditary Cancer Program targeted capture panel, which uses tumor tissue to simultaneously screen for both clinically actionable solid tumor variants and germline variants across 45 genes. Validation using 14 tumor specimens, composed of patient samples and cell lines analyzed in triplicate, demonstrated high coverage with sensitive and specific identification of single-nucleotide variants and small insertions and deletions. Average coverage across all targets remained >2000× in 198 additional patient tumor samples. Analysis of 55 formalin-fixed, paraffin-embedded tumor samples for the detection of known germline variants within a subset of cancer-predisposition genes, including one multiexon deletion, yielded a 100% detection rate, demonstrating that germline variants can be reliably detected in tumor samples using a single panel. Combining targetable somatic and actionable germline variants into a single tumor tissue assay represents a streamlined approach that can inform treatment for patients with advanced cancers as well as identify those with potential germline variants who are eligible for confirmatory testing, but would not otherwise have been identified.