Integrative Functional Genomics Analysis of Kaposi Sarcoma Cohorts

Area of Science:

• Oncology
• Virology
• Bioinformatics

Background:

• Kaposi sarcoma (KS) is an AIDS-defining cancer caused by KS-associated herpesvirus (KSHV), posing a global health challenge.
• Next-generation sequencing (NGS) has been underutilized for profiling KS lesions compared to other cancers.

Purpose of the Study:

• To compile and harmonize a comprehensive dataset of KS and non-tumor cutaneous samples.
• To analyze gene expression profiles, pathway activities, and immune infiltrates across diverse patient cohorts.
• To facilitate biological insights and biomarker discovery for Kaposi sarcoma.

Main Methods:

• RNA-sequencing (RNA-seq) data from 9 Argentinian KS lesions were generated.
• Data were integrated with publicly available datasets from USA and Sub-Saharan African cohorts.
• Unsupervised analysis was performed on 131 KS-related samples.

Main Results:

• Four distinct KS clusters were identified based on host and KSHV gene expression, immune infiltrate, and pathway activity.
• A compiled RNA-seq profile was created, integrating data from Argentina, USA, and Sub-Saharan Africa.
• The dataset is publicly available via the UCSC Xena browser for research.

Conclusions:

• The harmonized KS dataset provides a valuable resource for exploring host-viral interactions and identifying potential biomarkers.
• Accessible data visualization and analysis tools can empower researchers without extensive bioinformatics expertise.
• This resource has the potential to advance our understanding of Kaposi sarcoma pathogenesis and treatment strategies.