Author

P. Selenica

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· 2 Pathology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Assay:clinical cohort / trial· 1 Approach:deep learning· 1

Frequent Co-Authors

B. Weigelt· 3 shared J. S. Reis-Filho· 3 shared F. Pareja· 2 shared A. J. Levine· 1 shared A. Marra· 1 shared A. Nasrazadani· 1 shared A. R. Tannenbaum· 1 shared A. V. Lee· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersCancer Biology

B. Weigelt

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Author profile →

3 papers

Recent·Most cited

Multimodal histopathologic models stratify hormone receptor-positive early breast cancer

K. M. Boehm, O. S. M. El Nahhas, A. Marra, P. Selenica, H. Y. Wen, B. Weigelt, E. D. Paul, P. Cekan, R. Erber, C. M. L. Loeffler, E. Guerini-Rocco, N. Fusco, C. Frascarelli, E. Mane, E. Munzone, , J. N. Kather

This paper develops a multimodal transformer model using H&E images and text reports to predict recurrence scores in hormone receptor-positive breast cancer, achieving high accuracy and generalizability.

bioRxiv · Feb 23, 2024Pathology

Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations

O. S. Shah, A. Nasrazadani, J. Foldi, J. M. Atkinson, C. G. Kleer, P. F. McAuliffe, T. J. Johnston, W. Stallaert, E. M. Da Silva, P. Selenica, H. Dopeso, F. Pareja, D. Mandelker, B. Weigelt, J. S. Reis-Filho, , S. Oesterreich

This study uses spatial molecular profiling to show that mixed invasive ductal-lobular breast cancers have distinct molecular subtypes, oncogenic signatures, and mutations in different tumor regions, leading to prognostic uncertainty and therapeutic challenges.

bioRxiv · Sep 9, 2023Cancer Biology

Geometric Network Analysis Provides Prognostic Information in Patients with High Grade Serous Carcinoma of the Ovary Treated with Immune Checkpoint Inhibitors

R. Elkin, J. H. Oh, Y. L. Liu, P. Selenica, B. Weigelt, J. S. Reis-Filho, D. Zamarin, J. O. Deasy, L. Norton, A. J. Levine, A. R. Tannenbaum

This paper introduces a network curvature-based method to predict prognosis in high-grade serous ovarian cancer patients treated with immune checkpoint inhibitors using copy number alterations.

bioRxiv · Jun 10, 2021Cancer Biology