Therapeutic Landscape of Human Cancers
Genomics is poised to transform the clinical practise in oncology. However, utilization of genomics in regular practise has been deterrent for many due to the lack of appropriate infrastructure, resources and technical expertise requirement. As an attempt to circumvent the problem and help the wider community to tap the knowledge present in vast genomic data, my research work focuses on following three functional aspects of the cancer genome:

1) Discovery and validation of therapeutically relevant alterations in human cancers using the hypothesis driven approach. I have discovered novel oncogenic and small molecule sensitive FGFR3 alterations in lung adenocarcinoma (PMID: 27998968). Furthermore, I am collaborating with other researchers to identify additional therapeutically relevant alterations in lung cancers, head & neck cancers, gall-bladder cancers, cervical cancer and breast cancer.

2) Development of integrated genomics strategy for deriving biological interpretation. This data driven approach takes advantage of whole genome sequencing (WGS), whole transcriptome sequencing (WTS), targeted DNA sequencing (TDS), small RNA sequencing (sRNA-seq), long non-coding RNA expression and others to enhance signal-to-noise ratio in datasets, enabling the discovery of true biological alteration. I have played pivotal role in development of integrative genomics analysis strategy leading to the discovery of NRBP1 in head & neck cancer (PMID: 26572163) and miRNA -- Progesterone receptor -- SGK1 network in breast cancer (PMID: 28876975, 30337371). Furthermore, I am expanding the depth of integrative genomics analysis by utilizing the machine learning and artificial intelligence to make novel discoveries from complex genomics data.

3) Development of computational biology methods/tools for biological and clinical interpretation of next-generation sequencing (NGS) data. I have developed HPVDetector (PMID: 25973533), a simple yet precise and robust tool for detecting HPV from tumour samples using variety of NGS platforms. In collaboration with other researchers, we are now expanding the tool (now called Cancer Pathogen Detector, CPD) to detect and analyse more than 1,000 odd cancer related pathogens. Additionally, I am developing ClinOme (short for clinical genome) -- a user friendly computational tool to generate automated clinical reports from raw NGS data.

Links: Pubmed , Google Scholar