Author

P. Pandya

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 4 Cell Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Organism:mouse· 3 Assay:bulk RNA-seq· 2 Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Research Focus:host-pathogen & immune response· 2 Organism:human· 2 Assay:imaging· 2

Frequent Co-Authors

A. Geraldes· 2 shared C. Bass· 2 shared C. J. Bakkenist· 2 shared D. Mehrotra· 2 shared F. P. Vendetti· 2 shared J. H. Beumer· 2 shared J. Hense· 2 shared J. J. Deppas· 2 shared

Activity by Year

2021-2024 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersCancer Biology

A. Geraldes

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Author profile →

5 papers

Recent·Most cited

Deoxyuridine-rich cytoplasmic DNA antagonizes STING-dependent innate immune responses and sensitizes resistant tumors to anti-PD-L1 therapy

P. Pandya, F. P. Vendetti, J. A. El-Ghoubaira, S. Pathak, J. J. Deppas, R. E. Jones, A. V. Columbus, Y. Zhang, D. Ivanov, Z. Huang, K. M. MacDonald, S. M. Harding, R. Buj, K. M. Aird, J. H. Beumer, , C. J. Bakkenist

The paper shows that dU-rich cytoplasmic DNA inhibits STING-dependent immune responses and enhances anti-PD-L1 therapy efficacy in tumors.

bioRxiv · Apr 4, 2024 · PreprintCancer Biology

Thymidine rescues ATR kinase inhibition induced deoxyuridine contamination in genomic DNA, cell death, and Type 1 interferon expression

N. Sugitani, F. P. Vendetti, A. J. Cipriano, P. Pandya, J. J. Deppas, T. N. Moiseeva, S. Schamus-Haynes, Y. Wang, D. Palmer, H. U. Osmanbeyoglu, A. Bostwick, N. W. Snyder, Y.-N. Gong, K. M. Aird, G. M. Delgoffe, , C. J. Bakkenist

This study shows that thymidine rescues ATR kinase inhibitor-induced deoxyuridine contamination, cell death, and Type 1 interferon expression in CD8+ T cells.

bioRxiv · Feb 24, 2022 · PreprintCancer Biology

Deep learning can predict multi-omic biomarkers from routine pathology images: A systematic large-scale study

S. Arslan, D. Mehrotra, J. Schmidt, A. Geraldes, S. Singhal, J. Hense, X. Li, C. Bass, J. N. Kather, P. Pandya, P. Raharja-Liu

This study shows deep learning can predict multi-omic biomarkers from H&E-stained cancer slides, with 50% of models achieving AUC > 0.633 across 32 cancer types.

bioRxiv · Jan 21, 2022 · PreprintCancer Biology

Evaluation of a predictive method for the H&E-based molecular profiling of breast cancer with deep learning

S. Arslan, X. Li, J. Schmidt, J. Hense, A. Geraldes, C. Bass, K. Brown, A. Marcia, T. Dewhirst, P. Pandya, S. Singhal, D. Mehrotra, P. Raharja-Liu

The paper validates a deep learning method that predicts breast cancer biomarkers from H&E slides with high accuracy in a clinical setting.

bioRxiv · Jan 4, 2022 · PreprintCancer Biology

Distinct Hypoxia-induced Translational Profiles of Embryonic and Adult-derived Macrophages

N. S. Wilcox, T. O. Yarovinsky, P. Pandya, V. S. Ramgolam, A. Moro, Y. Wu, S. Nicoli, K. K. Hirschi, J. R. Bender

The paper compares hypoxia-induced translational profiles of embryonic and adult-derived macrophages using TRAP and RNA-seq, identifying distinct gene expression patterns and HuR-dependent transcripts.

bioRxiv · Mar 18, 2021Cell Biology