RET Alterations Differentiate Molecular Profile of Medullary Thyroid Cancer.

PURPOSE: Medullary thyroid cancer (MTC) is a rare cancer originating from parafollicular C cells of the thyroid gland. Therapeutically relevant alterations in MTC are predominantly reported in RET oncogene, and lower-frequency alterations are reported in KRAS and BRAF. Nevertheless, there is an unmet need existing to analyze the MTC in the Indian cohort by using in-depth sequencing techniques that go beyond the identification of known therapeutic biomarkers. MATERIALS AND METHODS: Here, we characterize MTC using integrative whole-exome and whole-transcriptome sequencing of 32 MTC tissue samples. We performed clinically relevant variant analysis, molecular pathway analysis, tumor immune-microenvironment analysis, and structural characterization of RET novel mutation. RESULTS: Mutational landscape analysis shows expected RET mutations in 50% of the cases. Furthermore, we observed mutations in known cancer genes like KRAS, HRAS, SF3B1, and BRAF to be altered only in the RET-negative cohort. Pathway analysis showed differential enrichment of mutations in transcriptional deregulation genes in the RET-negative cohort. Furthermore, we observed novel RET kinase domain mutation Y900S showing affinity to RET inhibitors accessed via molecular docking and molecular dynamics simulation. CONCLUSION: Altogether, this study provides a detailed genomic characterization of patients with MTC of Indian origin, highlighting the possible utility of targeted therapies in this disease.

Understanding the Impact of Population and Cancer Type on Tumor Mutation Burden Scores: A Comprehensive Whole-Exome Study in Cancer Patients From India.

PURPOSE: The purpose of this study was to understand the impact of population diversity and geographic variation on tumor mutation burden (TMB) scores across cancers and its implication on stratification of patients for immune checkpoint inhibitor (ICI) therapy. MATERIALS AND METHODS: This retrospective study used whole-exome sequencing (WES) to profile 1,233 Indian patients with cancer across 30 different cancer types and to estimate their TMB scores. A WES-based pipeline was adopted, along with an indigenously developed strategy for arriving at true somatic mutations. A robust unsupervised machine learning approach was used to understand the distribution of TMB scores across different populations and within the population. RESULTS: The results of the study showed a biphasic distribution of TMB scores in most cancers, with different threshold scores across cancer types. Patients with cancer in India had higher TMB scores compared with the Caucasian patients. We also observed that the TMB score value at 90th percentile (predicting high efficacy to ICI) was high in four different cancer types (sarcoma, ovary, head and neck, and breast) in the Indian cohort as compared with The Cancer Genome Atlas or public cohort. However, in lung and colorectal cancers, the TMB score distribution was similar between the two population cohorts. CONCLUSION: The findings of this study indicate that it is crucial to benchmark both cancer-specific and population-specific TMB distributions to establish a TMB threshold for each cancer in various populations. Additional prospective studies on much larger population across different cancers are warranted to validate this observation to become the standard of care.

An absolute approach to using whole exome DNA and RNA workflow for cancer biomarker testing.

Introduction: The concept of personalized medicine in cancer has emerged rapidly with the advancement of genome sequencing and the identification of clinically relevant variants that contribute to disease prognosis and facilitates targeted therapy options. In this study, we propose to validate a whole exome-based tumor molecular profiling for DNA and RNA from formalin-fixed paraffin-embedded (FFPE) tumor tissue. Methods: The study included 166 patients across 17 different cancer types. The scope of this study includes the identification of single-nucleotide variants (SNVs), insertions/deletions (INDELS), copy number alterations (CNAs), gene fusions, tumor mutational burden (TMB), and microsatellite instability (MSI). The assay yielded a mean read depth of 200×, with >80% of on-target reads and a mean uniformity of >90%. Clinical maturation of whole exome sequencing (WES) (DNA and RNA)- based assay was achieved by analytical and clinical validations for all the types of genomic alterations in multiple cancers. We here demonstrate a limit of detection (LOD) of 5% for SNVs and 10% for INDELS with 97.5% specificity, 100% sensitivity, and 100% reproducibility. Results: The results were >98% concordant with other orthogonal techniques and appeared to be more robust and comprehensive in detecting all the clinically relevant alterations. Our study demonstrates the clinical utility of the exome-based approach of comprehensive genomic profiling (CGP) for cancer patients at diagnosis and disease progression. Discussion: The assay provides a consolidated picture of tumor heterogeneity and prognostic and predictive biomarkers, thus helping in precision oncology practice. The primary intended use of WES (DNA+RNA) assay would be for patients with rare cancers as well as for patients with unknown primary tumors, and this category constitutes nearly 20-30% of all cancers. The WES approach may also help us understand the clonal evolution during disease progression to precisely plan the treatment in advanced stage disease.