We attempted to understand the cervical cancer patient samples through Whole Exome Sequencing. We derived the variants from raw reads via our in-house benchmarked pipeline and validated the variants by IGV. This is the first cervical cancer exome data from the Indian cohort. Background: Cervical cancer (CC) is caused mainly by persistent infections of high-risk HPV, reduced parity, and factors like a decrease in average socioeconomic levels. We keep this because no cervical cancer exome data is available from the Indian cohort. Methods: The CC patient clinical samples were initially subjected to preparation using Qiagen DNA extraction, quantified, and the library preparation using the Agilent target enrichment system. Further, exome capture by Illumina platform (100X), quality check, alignment, and variant calling followed by the downstream analysis and finally visualized by IGV. Results: We observed a large number of SNVs or mutations from an Indian perspective, such as KMT2C, OR4M1, PDPR2P, EPHB1, FAS, OPCML, MGST1, C1QTNF9, HS6ST3, OR4K2, PRPSAP2, KCNJ12, FIGNL1, SFXN1, BAGE2, ARVCF, NAMPT variants of significance, unknown significance and possibly significant are reported. Conclusion: For the first time, KMT2C is observed as a novel potent mutation and pathogenic, showing the variant position at (7:152265091, T>A, SNV 62478356) from the Indian context in CC. Further, we visualized and validated the mutations using the Integrative Genomic Viewer (IGV) browser. Finally, we discuss the inherent challenges through KMT2C mutations.

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with the genetics, genomics, and the environmental influence in causality of PCa, not many studies employing the next generation sequencing (NGS) approaches of PCa have been carried out. In our previous study, we have identified some causal genes and mutations specific to Indian PCa using Whole-Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify DEGs as well as long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened 6 patients who underwent prostatectomy; we performed a whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz. GeneMANIA Stringdb, Cytoscape-Cytohubba, cbioportal to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, HN1L and some other important genes known to be involved in different cancer pathways such as, COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1 etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, and ENST00000647843.1 that need to be characterized further. Deregulation of SOX2OT is observed in various tumors, including lung cancer, gastric cancer, esophageal cancer, breast cancer, hepatocellular carcinoma, ovarian cancer, pancreatic, laryngeal squamous cell carcinoma, osteosarcoma, nasopharyngeal carcinoma, and glioblastoma. It would be interesting to characterize its function in PCa as well. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which have perhaps not been reported. As a pilot study, this has set a precedent for us to validate further experimentally, and we firmly believe this will pave a way towards discovery of biomarkers and development of novel therapies.

In the recent past, there has been a rise in Prostate Cancer (PCa) in Asia, particularly India. Although systematic reviews on PCa have dealt on the genetics, genomics and the environmental influence in causal of PCa, no predictive analytics in comparing the PCa from Caucasian, American to Asian population was attempted. In this review article, we have attempted to elaborate this aspect of PCa and deliberated on challenges related to next generation sequencing methods of PCa’s manifestation when compared to the west.