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Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps
Open accessAbstract
Abstract Most colorectal cancers (CRCs) develop from either adenomas (ADs) or sessile serrated lesions (SSLs). The origins and molecular landscapes of these histologically distinct pre-cancerous polyps remain incompletely understood. Here, we present an atlas at single-cell resolution of sporadic conventional tubular/tubulovillous ADs, SSLs, hyperplastic polyps (HPs), microsatellite stable (MSS) and unstable (MSI-H) CRC, and normal colonic mucosa. Using single-cell transcriptomics and multiplex imaging, we studied 69 datasets from 33 participants. We also examined separate sets of 66 and 274 polyps for RNA and targeted gene sequencing, respectively. We performed multiplex imaging on a tissue microarray of 14 ADs and 15 CRCs, and we integrated pre-cancer polyp data with published single-cell and The Cancer Genome Atlas (TCGA) bulk CRC data to establish potential polyp-cancer relationships. Striking differences were observed between ADs and SSLs that extended to MSS and MSI-H CRCs, respectively, reflecting their distinct origins and trajectories. ADs arose from WNT pathway dysregulation in stem cells, which aberrantly expanded and expressed a Hippo and ASCL2 regenerative program. In marked contrast, SSLs were depleted of stem cell-like populations and instead exhibited a program of gastric metaplasia in the setting of elevated cytotoxic inflammation. Using subtype-specific gene regulatory networks and shared genetic variant analysis, we implicated serrated polyps, including some HPs conventionally considered benign, as arising from a metaplastic program in committed absorptive cells. ADs and SSLs displayed distinct patterns of immune cell infiltration that may influence their natural history. Our multi-omic atlas provides novel insights into the malignant potential of colorectal polyps and serves as a framework for precision surveillance and prevention of sporadic CRC.
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R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430
lmerTest Package: Tests in Linear Mixed Effects Models
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017) · Journal of Statistical Software · doi:10.18637/jss.v082.i13 · Cited by 24,346
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., et al. (2020) · Nature · doi:10.1038/s41586-020-2649-2 · Cited by 23,826
Siegel, R. L., Miller, K. D., & Jemal, A. (2019) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21551 · Cited by 20,160
Harris, C., Millman, K., van der Walt, S., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N., et al. (2020) · RePEc: Research Papers in Economics · Cited by 17,844
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Hallmarks of transcriptional intratumour heterogeneity across a thousand tumours
Gavish, A., Tyler, M., Greenwald, A. C., Hoefflin, R., Simkin, D., Tschernichovsky, R., Galili Darnell, N., Somech, E., Barbolin, C., Antman, T., et al. (2023) · Nature · doi:10.1038/s41586-023-06130-4 · Cited by 556
Joanito, I., Wirapati, P., Zhao, N., Nawaz, Z., Yeo, G., Lee, F., Eng, C. L. P., Macalinao, D. C., Kahraman, M., Srinivasan, H., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01100-4 · Cited by 434
Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets
Zhang, S., Xiao, X., Yi, Y., Wang, X., Zhu, L., Shen, Y., Lin, D., & Wu, C. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01848-7 · Cited by 399
Valdeolivas, A., Amberg, B., Giroud, N., Richardson, M., Gálvez, E. J. C., Badillo, S., Julien-Laferrière, A., Túrós, D., Voith von Voithenberg, L., Wells, I., et al. (2024) · npj Precision Oncology · doi:10.1038/s41698-023-00488-4 · Cited by 130
Borràs, D. M., Verbandt, S., Ausserhofer, M., Sturm, G., Lim, J., Verge, G. A., Vanmeerbeek, I., Laureano, R. S., Govaerts, J., Sprooten, J., et al. (2023) · Cell Discovery · doi:10.1038/s41421-023-00605-4 · Cited by 67
Metadata
- Authors
- Chen, B., Scurrah, C. R., McKinley, E. T., Simmons, A. J., Ramirez-Solano, M. A., Zhu, X., Markham, N. O., Heiser, C. N., Vega, P. N., Rolong, A., Kim, H., Sheng, Q., Drewes, J. L., Zhou, Y., Southard-Smith, A. N., Xu, Y., Ro, J., Jones, A. L., Revetta, F., Berry, L. D., Niitsu, H., Islam, M., Pelka, K., Hofree, M., Chen, J. H., Sarkizova, S., Ng, K., Giannakis, M., Boland, G. M., Aguirre, A. J., Anderson, A. C., Rozenblatt-Rosen, O., Regev, A., Hacohen, N., Kawasaki, K., Sato, T., Goettel, J. A., Grady, W. M., Zheng, W., Washington, M. K., Cai, Q., Sears, C. L., Goldenring, J. R., Franklin, J. L., Su, T., Huh, W. J., Vandekar, S., Roland, J. T., Liu, Q., Coffey, R. J., Shrubsole, M. J., & Lau, K. S.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 184
- Issue
- 26
- Pages
- 6262-6280.e26
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W4200259443
- Cited by
- 325
- References
- 188
- FWCI
- 25.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Chen, B., Scurrah, C. R., McKinley, E. T., Simmons, A. J., Ramirez-Solano, M. A., Zhu, X., Markham, N. O., Heiser, C. N., Vega, P. N., Rolong, A., Kim, H., Sheng, Q., Drewes, J. L., Zhou, Y., Southard-Smith, A. N., Xu, Y., Ro, J., Jones, A. L., Revetta, F., . . . Lau, K. S. (2021). Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps. Cell. https://doi.org/10.1016/j.cell.2021.11.031
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