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Human-specific elimination of epithelial Siglec-XII suppresses the risk of inflammation-driven colorectal cancers
Hector A. Cuello, Saptarshi Sinha, Andrea L. Verhagen, Nissi Varki, Ajit Varki, Pradipta Ghosh
Hector A. Cuello, Saptarshi Sinha, Andrea L. Verhagen, Nissi Varki, Ajit Varki, Pradipta Ghosh
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Research Article Inflammation Oncology

Human-specific elimination of epithelial Siglec-XII suppresses the risk of inflammation-driven colorectal cancers

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Abstract

Carcinomas are common in humans but rare among closely related “great apes.” Plausible explanations, including human-specific genomic alterations affecting the biology of sialic acids, are proposed, but causality remains unproven. Here, an integrated evolutionary genetics-phenome-transcriptome approach studied the role of SIGLEC12 gene (encoding Siglec-XII) in epithelial transformation and cancer. Exogenous expression of the protein in cell lines and genetically engineered mice recapitulated approximately 30% of the human population in whom the protein is expressed in a form that cannot bind ligand because of a fixed, homozygous, human-universal missense mutation. Siglec-XII–null cells/mice recapitulated the remaining approximately 70% of the human population in whom an additional polymorphic frameshift mutation eliminates the entire protein. Siglec-XII expression drove several pro-oncogenic phenotypes in cell lines and increased tumor burden in mice challenged with chemical carcinogen and inflammation. Transcriptomic studies yielded a 29-gene signature of Siglec-XII–positive disease and when used as a computational tool for navigating human data sets, pinpointed with surprising precision that SIGLEC12 expression (model) recapitulates a very specific type of colorectal carcinomas (disease) that is associated with mismatch-repair defects and inflammation, disproportionately affects European Americans, and carries a favorable prognosis. They revealed a hitherto-unknown evolutionary genetic mechanism for an ethnic/environmental predisposition of carcinogenesis.

Authors

Hector A. Cuello, Saptarshi Sinha, Andrea L. Verhagen, Nissi Varki, Ajit Varki, Pradipta Ghosh

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Figure 6

Computational Siglec-XII–positive CRCs.

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Computational Siglec-XII–positive CRCs.
(A) Expression of Siglec-XII in ...
(A) Expression of Siglec-XII in human colorectal tumors was evaluated by immunohistochemistry. Representative images of tumors that were scored as negative (specimen 69) or positive (specimen 84) are shown. Scale bar: 100 μm. (B) Multivariate analysis of Siglec-XII positivity as a linear combination of all variables in the tumors used in this study. The coefficient of each variable (at the center) with their upper and lower bounds of 95% confidence interval (as error bars) and the P values from t tests are illustrated in the bar plot. The P value for each term tests the null hypothesis that the coefficient is equal to 0 (no effect). Asterisk = significant covariate. *P = 0.018. See also Supplemental Table 1 for source data. (C) Schematic summarizes the transcriptomics-based computational approach to find a match between model (Siglec-XII murine tumors) versus disease (human CRCs). (D) Violin plots display the StepMiner normalized composite scores of the DEGs (in Figure 5) in tumor and matched adjacent normal colon tissues in 15 African American (AA) and 9 European American (EA) patients. (E and F) Kaplan-Meier curves for overall and progression-free survival (Supplemental Figure 5, A and B) in patients with all CRCs (E) or just the MSI-high subset (F), stratified based on high versus low mean expression values of the DEGs in B. (G and H) Violin plots of the StepMiner normalized composite scores of key immune (G) and mismatch repair (H) genes that were found to be differentially expressed between the 2 ethnic groups in GSE146009 (left) and in the control (C) versus Siglec-XII (S) mouse tumors (right) (ref. 37). See also Supplemental Figure 5, C–F, for the patterns of expression of the individual genes displayed as heatmaps. Statistics: P values in each violin plot (D, G, and H) are based on 2-tailed Welch’s t test between comparator groups. P values for survival plots were determined by log-rank test.

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