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Redefining tumor classification and clinical stratification through a colorectal cancer single-cell atlas

Ateeq M. Khaliq, Zeyneb Kurt, Miles W. Grunvald, Cihat Erdogan, Sultan Sevgi Turgut, Tim Rand, Sonal Khare, Jeffrey A. Borgia, Dana M. Hayden, Sam G. Pappas, Henry R. Govekar, Anuradha R, Bhama, Ajaypal Singh, Richard A. Jacobson, Audery E. Kam, Andrew Zloza, Jochen Reiser, Daniel V. Catenacci, Kiran Turaga, Milan RadovichSheeno Thyparambil, Mia A. Levy, Janakiraman Subramanian, Timothy M. Kuzel, Anguraj Sadanandam, Arif Hussain, Bassel El-Rayes, Ameen Salahudeen, Ashiq Masood*

*Corresponding author for this work

Research output: Working paper › Preprint

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Abstract

Colorectal cancer (CRC), a disease of high incidence and mortality, exhibits a large degree of inter- and intra-tumoral heterogeneity. The cellular etiology of this heterogeneity is poorly understood. Here, we generated and analyzed a single-cell transcriptome atlas of 49,859 CRC cells from 16 patients, validated with an additional 31,383 cells from an independent CRC patient cohort. We describe subclonal transcriptomic heterogeneity of CRC tumor epithelial cells, as well as discrete stromal populations of cancer-associated fibroblasts (CAFs). Within CRC CAFs, we identify the transcriptional signature of specific subtypes that significantly stratifies overall survival in more than 1,500 CRC patients with bulk transcriptomic data. We demonstrate that scRNA analysis of malignant, stromal, and immune cells exhibit a more complex picture than portrayed by bulk transcriptomic-based Consensus Molecular Subtypes (CMS) classification. By demonstrating an abundant degree of heterogeneity amongst these cell types, our work shows that CRC is best represented in a transcriptomic continuum crossing traditional classification systems boundaries. Overall, this CRC cell map provides a framework to re-evaluate CRC tumor biology with implications for clinical trial design and therapeutic development. Competing Interest Statement: The authors have declared no competing interest.
Original languageEnglish
Number of pages40
DOIs
Publication statusSubmitted - 7 Feb 2021

Publication series

NamebioRxiv
PublisherCold Spring Harbor Laboratory Press

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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