Dipongkor Saha

Integrative Transcriptomic and Machine Learning Analysis of ecDNA-Associated Features for Studying Chemotherapy Resistance in TNBC

This study uses transcriptomic analysis and machine learning to identify ecDNA-associated features linked to chemotherapy resistance in TNBC, finding ecDNA burden and prevalence as key predictors of drug resistance.

Molecular Plasticity of T Cells Informs Their Possible Adaptation in 4T1 Tumors

This study tracks T cell transcriptional changes in 4T1 tumors over time, revealing functional decline, reduced TCR diversity, and immunosuppressive shifts in the tumor microenvironment.

Molecular Phenotypic Plasticity Informs Possible Adaptive Change of Triple-Negative Breast Cancer Cells In Vivo

This study examines in vivo gene expression changes in triple-negative breast cancer cells over time, revealing early transcriptional shifts and significant molecular reprogramming linked to ecDNA alterations and immune evasion.