Publication Type : Conference Paper
Publisher : IIETA
Source : International Conference on Bio-Neuro Informatics and Algorithms
Campus : Chennai
School : School of Engineering
Department : Computer Science and Engineering
Year : 2022
Abstract : The most prevalent kind of ovarian cancer is high-grade serous ovarian cancer. Drug
resistance is the major issue in this cancer. Transcriptional fusions involving SLC25A40-
ABCB1 is a leading cause of this cancer. To understand the phenotypic consequences,
transcriptional profile was studied using high throughput sequencing technologies. Here we
have used that data to understand co-expressed genes and their functional role in two
different cell types, fusion positive and fusion negative using WGCNA analysis. The major
biological processes which are correlated with fusion positive cells are extracellular
structure organization, external encapsulating structure organization, regulation of cell
migration and axon guidance etc. In addition to these investigations, gene expression data
of a PARPi-sensitive cell line and resistance was analyzed to determine the role and
capabilities of PARP-inhibitors in controlling drug-resistant High-grade serous ovarian
cancer. This investigation also shed light on the possible mechanism of PARPi resistant
cases and concluded that the resistance comes from the dynamics of four biological
processes like regulation of cell junction assembly, cell-cell adhesion, tissue
morphogenesis, neuron projection development and negative regulation of cellular
component organization. Further analysis with different Gene Set Enrichment analysis
illustrates that four processes, negative regulation of lens fiber cell differentiation,
sarcoplasmic reticulum lumen, presynaptic membrane assembly and nitrobenzene
metabolic process are activated in PARPi resistance. These processes are connected to each
other through an important kinase protein ERBB2 which is interpreted as a key protein in
PARPi resistance.
Cite this Research Publication : Sujata Roy, J. Jeyalakshmi, S. Poonkuzhali, M. Michael Gromiha, “Metadata Analysis to Get Insight into Drug Resistant Ovarian Cancer”, 2022 International Conference on Bio-Neuro Informatics and Algorithms (iCBNA 2022), Pune, India 21 – 22 June 2022 , IEEE , pp- 467-471(SCOPUS)