Author

Angeliki Karatza

NYU Langone HealthORCID 0009-0004-9271-4576Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:mouse· 2 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1

Frequent Co-Authors

Itai YanaiiD· 2 shared Kwok‐Kin WongiD· 2 shared Maayan PouriD· 2 shared Metamia CiampricottiiD· 2 shared Alfonso LopeziD· 1 shared Alvaro Quintanal Villalonga· 1 shared Àlvaro Quintanal-VillalongaiD· 1 shared Amanda W. LundiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersCancer Biology

Itai YanaiORCID

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3 papers

Recent·Most cited

Cancer cell adaptations along a proliferation-robustness axis drive TME pro-tumor phenotypes

Maayan Pour, Guisheng Zhao, Angeliki Karatza, Gustavo S. França, Linda Procell, Anjali N. Rao, Deborah Corcoran, Ayushi S. Patel, Cristina H Hajdu, Kwok‐Kin Wong, Amanda W. Lund, Edna Cukierman, Itai Yanai

The paper shows cancer cells adapt along a proliferation-robustness axis in response to TME components, leading to pro-tumor phenotypes.

bioRxiv · Oct 29, 2026 · PreprintCancer Biology

Cross-species analysis identifies genotype-driven vulnerabilities in lung adenocarcinoma

Angeliki Karatza, Maayan Pour, Jaylen M Powell, Yuan Hao, Dimitris Nasias, Yi Jer Tan, Alfonso Lopez, Metamia Ciampricotti, Chengwei Peng, Àlvaro Quintanal-Villalonga, Yeuan Ting Lee, Rüveyda Ayasun, Muhammad Elnaggar, Priyanka Sahu, Igor Dolgalev, , Kwok‐Kin Wong

This study identifies genotype-specific immune and metabolic vulnerabilities in lung adenocarcinoma through cross-species analysis of human and mouse tumors.

bioRxiv · Aug 24, 2025 · PreprintCancer Biology

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF)

Charles S. Comiter, Xingjian Chen, Eeshit Dhaval Vaishnav, Koseki J. Kobayashi-Kirschvink, Metamia Ciampricotti, Ke Zhang, Jason Murray, Francesco Monticolo, Jianhuan Qi, Ryota Tanaka, Sonia E. Brodowska, Bo Li, Yiming Yang, Scott J. Rodig, Angeliki Karatza, , Aviv Regev

SCHAF generates spatially resolved single-cell transcriptomes from H&E histology images using vision transformers and adversarial learning, showing good agreement with ground-truth data.

bioRxiv · Mar 21, 2023 · PreprintBioinformatics