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INTEGRATIVE FUNCTIONAL GENOMICS ANALYSIS OF KAPOSI'S SARCOMA COHORTS
  • +11
  • Ezequiel Lacunza,
  • Valeria Fink,
  • Julian Naipauer,
  • María E. Salas,
  • Ana M. Gun,
  • Mary J. Goldman,
  • Jingchun Zhu,
  • Sion Williams,
  • María Inés Figueroa,
  • Pedro Cahn,
  • Omar Coso,
  • Ethel Cesarman,
  • Juan C. Ramos,
  • Martin C. Abba
Ezequiel Lacunza
CINiBA
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Valeria Fink
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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Julian Naipauer
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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María E. Salas
CINiBA
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Ana M. Gun
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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Mary J. Goldman
University of California
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Jingchun Zhu
University of California
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Sion Williams
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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María Inés Figueroa
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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Pedro Cahn
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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Omar Coso
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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Ethel Cesarman
Weill Cornell Medicine Department of Pathology and Laboratory Medicine
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Juan C. Ramos
UM-CFAR/SCCC Argentina Consortium for Research and Training in Virally Induced AIDS-Malignancies
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Martin C. Abba
CINiBA

Corresponding Author:mcabba@gmail.com

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Abstract

Kaposi’s sarcoma (KS) is an AIDS-defining cancer and a significant global health challenge caused by Kaposi’s sarcoma-associated herpesvirus (KSHV). NGS-based approaches have profiled KS lesions in a minimal number of studies compared with other neoplastic diseases. Here we present a compiled and harmonized dataset of 131 KS and non-tumor cutaneous samples in the context of their predicted pathway activities, immune infiltrate, KSHV and HIV gene expression profiles, and their associated clinical data representing patient populations from Argentina, United States (USA), and Sub-Saharan Africa cohorts. RNA-seq data from 9 Argentinian KS lesions were generated and integrated with previously published datasets derived from the USA and sub-Saharan African cohorts from Tanzania, Zambia, and Uganda. Unsupervised analysis of 131 KS-related samples allowed us to identify four KS clusters based on their host and KSHV gene expression profiles, immune infiltrate, and the activity of specific signaling pathways. The compiled RNA-seq profile is shared with the research community through the UCSC Xena browser for further visualization, download, and analysis ([https://kaposi.xenahubs.net/](https://kaposi.xenahubs.net/)). These resources will allow biologists without bioinformatics knowledge to explore and correlate the host and viral transcriptome in a curated dataset of different KS RNA-seq-based cohorts, which can lead to novel biological insights and biomarker discovery.
07 Nov 2024Submitted to Journal of Medical Virology
08 Nov 2024Submission Checks Completed
08 Nov 2024Assigned to Editor
08 Nov 2024Review(s) Completed, Editorial Evaluation Pending
09 Nov 2024Reviewer(s) Assigned
28 Nov 2024Editorial Decision: Revise Major