Biology subjects

Ganguli, P.

Publications and source records attributed to Ganguli, P..

3 recordsLinked to original sources

bioRxiv2024

Context-dependent effects of CDKN2A and other 9p21 gene losses during the evolution of oesophageal cancer

CDKN2A is a tumour suppressor located in chromosome 9p21 and frequently lost in Barretts oesophagus (BO) and oesophageal adenocarcinoma (OAC). How CDKN2A and other 9p21 gene co-deletions affect OAC evolution remains understudied. We explored the effects of 9p21 loss in OACs and cancer progressor and non-progressor BOs with matched genomic, transcriptomic, and clinical data. Despite its cancer driver role, CDKN2A loss in BO prevents OAC initiation by counter-selecting subsequent TP53 alterations. 9p21 gene co-deletions predict poor patient survival in OAC but not BO through context-dependent effects on cell cycle, oxidative phosphorylation, and interferon response. Immune quantifications using bulk transcriptome, RNAscope and high-dimensional tissue imaging showed that IFNE loss reduces immune infiltration in BO but not OAC. Mechanistically, CDKN2A loss suppresses the maintenance of squamous epithelium, contributing to a more aggressive phenotype. Our study demonstrates context-dependent roles of cancer genes during disease evolution, with consequences for cancer detection and patient management.

cancer biology↗

bioRxiv2022

PRESGENE: A web server for PRediction of ESsential GENE using integrative machine learning strategies

Study of essential genes in disease-causing organisms has wide application in the prediction of therapeutic targets and exploring different clinical strategies. Predicting gene essentiality for large set of genes in non-model, less explored organisms is challenging. Computational methods that use machine learning (ML)-based strategies are popularly adopted for essential gene prediction as they provide key advantage of considering diverse biological features. Previous works from our group have demonstrated two ML-based pipelines for predicting essential genes with high accuracy that mitigates the problems of sufficient labeled imbalanced dataset and limited labeled datasets of essential genes. Here we present PRESGENE at https://presgene.ncl.res.in, a ML-based web server for prediction of essential genes in unexplored eukaryotic and prokaryotic organisms. Our algorithms mitigate the problems of training dataset imbalance and limited availability of experimentally labeled data for essential genes. PRESGENE with its user-friendly web interface and high accuracy will prove to be a seamless experience for biologists looking for an accurate essential gene prediction server with limited labeled data for novel organisms.

bioinformatics↗

bioRxiv2020

A study of conventional histological parameters in excision specimens of breast cancer over a 7 year period and association with immunohistochemical categories

Background Along with conventional histological examination, immunohistochemistry (IHC) is a useful adjunct to assessment of a breast cancer excision specimen. Previous studies have shown differences in behavior of neoplasms depending on their histopathological as well as immunohistochemical categories; in particular, triple negative breast cancers (on IHC) show the worst prognosis.Objectives To find association, if any, within conventional histopathological characteristics (size, grade, stage, mitotic count, desmoplasia, dense inflammatory infiltrate, lymphovascular invasion) and between the conventional parameters and immunohistochemical categories of breast cancer, in both primary and post neo adjuvant chemotherapy (NACT) specimens.Methods 177 breast cancer excision specimens examined over last 7 years were assessed retrospectively, their histopathological parameters were recorded. In cases where immunohistochemistry was performed (N=108) the specimen was placed in one of the immunohistochemical categories: Luminal A, Luminal B, Her2 and Triple negative cancers. The data was then analysed by standard statistical methods.Results No statistically significant association was found between the histopathological parameters and IHC category was. However, a strong correlation was seen between lymphovascular invasion within the primary tumor and increasing lymph node involvement. There was also a reduction in ER and PR expression in neoplasms post NACT, while HER2 expression remained largely unchanged.Conclusion There might be additional genetic subtypes underlying the immunohistochemical phenotypes which determine the morphological characteristics of the neoplasm.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗