Refining colorectal cancer classification and clinical stratification through a single-cell atlas.
dc.contributor.author | Khaliq, Ateeq M | |
dc.contributor.author | Erdogan, Cihat | |
dc.contributor.author | Kurt, Zeyneb | |
dc.contributor.author | Turgut, Sultan Sevgi | |
dc.contributor.author | Grunvald, Miles W | |
dc.contributor.author | Rand, Tim | |
dc.contributor.author | Khare, Sonal | |
dc.contributor.author | Borgia, Jeffrey A | |
dc.contributor.author | Hayden, Dana M | |
dc.contributor.author | Pappas, Sam G | |
dc.contributor.author | Govekar, Henry R | |
dc.contributor.author | Kam, Audrey E | |
dc.contributor.author | Reiser, Jochen | |
dc.contributor.author | Turaga, Kiran | |
dc.contributor.author | Radovich, Milan | |
dc.contributor.author | Zang, Yong | |
dc.contributor.author | Qiu, Yingjie | |
dc.contributor.author | Liu, Yunlong | |
dc.contributor.author | Fishel, Melissa L | |
dc.contributor.author | Turk, Anita | |
dc.contributor.author | Gupta, Vineet | |
dc.contributor.author | Al-Sabti, Ram | |
dc.contributor.author | Subramanian, Janakiraman | |
dc.contributor.author | Kuzel, Timothy M | |
dc.contributor.author | Sadanandam, Anguraj | |
dc.contributor.author | Waldron, Levi | |
dc.contributor.author | Hussain, Arif | |
dc.contributor.author | Saleem, Mohammad | |
dc.contributor.author | El-Rayes, Bassel | |
dc.contributor.author | Salahudeen, Ameen A | |
dc.contributor.author | Masood, Ashiq | |
dc.date.accessioned | 2022-05-17T13:43:55Z | |
dc.date.available | 2022-05-17T13:43:55Z | |
dc.date.issued | 2022-05-11 | |
dc.identifier.uri | http://hdl.handle.net/10713/18879 | |
dc.description | Following publication of the original article [1], the authors noticed an error in Additional file 1. The incorrect Figure S5 was published. The corrected Additional file 1 is published in the correction and the original article [1] has been updated. See in https://doi.org/10.1186/s13059-022-02724-9. | |
dc.description.abstract | Background: Colorectal cancer (CRC) consensus molecular subtypes (CMS) have different immunological, stromal cell, and clinicopathological characteristics. Single-cell characterization of CMS subtype tumor microenvironments is required to elucidate mechanisms of tumor and stroma cell contributions to pathogenesis which may advance subtype-specific therapeutic development. We interrogate racially diverse human CRC samples and analyze multiple independent external cohorts for a total of 487,829 single cells enabling high-resolution depiction of the cellular diversity and heterogeneity within the tumor and microenvironmental cells. Results: Tumor cells recapitulate individual CMS subgroups yet exhibit significant intratumoral CMS heterogeneity. Both CMS1 microsatellite instability (MSI-H) CRCs and microsatellite stable (MSS) CRC demonstrate similar pathway activations at the tumor epithelial level. However, CD8+ cytotoxic T cell phenotype infiltration in MSI-H CRCs may explain why these tumors respond to immune checkpoint inhibitors. Cellular transcriptomic profiles in CRC exist in a tumor immune stromal continuum in contrast to discrete subtypes proposed by studies utilizing bulk transcriptomics. We note a dichotomy in tumor microenvironments across CMS subgroups exists by which patients with high cancer-associated fibroblasts (CAFs) and C1Q+TAM content exhibit poor outcomes, providing a higher level of personalization and precision than would distinct subtypes. Additionally, we discover CAF subtypes known to be associated with immunotherapy resistance. Conclusions: Distinct CAFs and C1Q+ TAMs are sufficient to explain CMS predictive ability and a simpler signature based on these cellular phenotypes could stratify CRC patient prognosis with greater precision. Therapeutically targeting specific CAF subtypes and C1Q + TAMs may promote immunotherapy responses in CRC patients. | en_US |
dc.description.uri | https://doi.org/10.1186/s13059-022-02677-z | en_US |
dc.description.uri | https://doi.org/10.1186/s13059-022-02724-9 | |
dc.language.iso | en | en_US |
dc.publisher | Springer Nature | en_US |
dc.relation | Processed scRNA-seq and metadata are available in the NCBI Gene Expression Omnibus (GEO) database under the accession code GSE200997 [113]. Additionally, Seurat objects, matrix files are available on GitHub [43]. It is also been deposited to Zenodo (https://zenodo.org/) with assigned DOI: 10.5281/zenodo.6466249 [114]. Public datasets used in our analysis were downloaded from GEO under accession numbers GSE39582 [45], GSE17536 [48], GSE132465 [18], GSE144735 [18], and GSE178341 [19]; raw counts were directly obtained from the author [19], and scRNA-seq data from Kieffer et al. [28] was downloaded from Bioturing platform [21]. Due to privacy concerns for human patients, the raw FASTQ data used in this study will be made available upon request for scientific research. | en_US |
dc.relation.ispartof | Genome Biology | en_US |
dc.rights | © 2022. The Author(s). | en_US |
dc.subject | CMS classification | en_US |
dc.subject | Cancer-associated fibroblast | en_US |
dc.subject | Colorectal cancer | en_US |
dc.subject | Immunotherapy | en_US |
dc.subject | Single-cell analysis | en_US |
dc.subject | Stromal signatures | en_US |
dc.title | Refining colorectal cancer classification and clinical stratification through a single-cell atlas. | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1186/s13059-022-02677-z | |
dc.identifier.pmid | 35538548 | |
dc.source.journaltitle | Genome biology | |
dc.source.volume | 23 | |
dc.source.issue | 1 | |
dc.source.beginpage | 113 | |
dc.source.endpage | ||
dc.source.country | England |