Oscar Alejandro Balbin

Oscar Alejandro Balbin, Ph.D.
14

Ph.D. Program
Investigator III, Bioinformatics
Novartis Institutes for Biomedical Research

Chairs

Dissertation Title

Identifying Novel Targetable Genes and Pathways in Cancer by Integrating Diverse Omics Data

Research Interest

Omics technologies for high-throughput profiling of human genome, transcriptome and proteome are revolutionizing cancer research and driving a paradigm shift in clinical care, from “one size” fits all treatments to molecularly informed therapies. The success of this new precision medicine paradigm will depend on our ability to combine diverse omics-based measurements to distill clinically relevant information that can be acted upon. This thesis developed bioinformatics approaches to integrate multi-omics datasets and applied these approaches in three distinct studies that identified novel actionable genes and pathways in cancer. In the first study, we aim at finding alternative targetable proteins in non-small cell lung cancers (NSCLC) with activating mutations in KRAS, a well-know but undruggable oncogene, by profiling their transcriptome, proteome and phosphoproteome. By reconstructing targetable networks associated with KRAS dependency, we nominate lymphocyte-specific protein tyrosine kinase (LCK) as a critical gene for cell proliferation in these samples, suggesting LCK as a novel druggable protein in KRAS-dependent NSCLC. In the second study, we aim at identifying oncogenic gene fusions in NSCLC patients of unknown driver gene. By characterizing the highly heterogeneous fusion’s landscape in NSCLC, we show that gene fusions incidence is an independent prognostic factor for poor outcome and discover novel Neurorregulin 1 (NRG1) fusions present exclusively in patients of unknown driver; resembling previously reported kinase fusions. This warrants further studies of the therapeutic opportunities for patients with NRG1 rearrangements. Finally in the third study, we aim at characterizing cancer-related genes that overlap and could be regulated by natural antisense transcripts. By determining the extent of antisense gene expression across human cancers and comparing with well-documented sense-antisense pairs, our results raise the possibility that antisense transcripts could modulate the expression of well-known tumor suppressors and oncogenes. This study provides a resource, oncoNATdb, a catalogue of cancer related genes with significant antisense transcription, which will enable researchers to investigate the mechanisms of sense-antisense regulation and their role in cancer. We anticipate that the computational methods developed and the results found in this thesis would assist others with similar tasks and inspire further studies of the therapeutic opportunities provided by these novel targets. 

Current Placement

Novartis Institutes for Biomedical Research