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pmid:37180113

A novel prognostic signatures based on metastasis- and immune-related gene pairs for colorectal cancer.

Bei Pan · Yanzhe Yue · Wenbo Ding · Li Sun · Mu Xu · Shukui Wang

Frontiers in immunology · 2023 doi:10.3389/fimmu.2023.1161382

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

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title
A novel prognostic signatures based on metastasis- and immune-related gene pairs for colorectal cancer.
doi
10.3389/fimmu.2023.1161382
pmid
37180113
authors array · 6 items
[0]
Bei Pan
[1]
Yanzhe Yue
[2]
Wenbo Ding
[3]
Li Sun
[4]
Mu Xu
[5]
Shukui Wang
journal
Frontiers in immunology
year
2023
abstract
Background: Metastasis remains the leading cause of mortality in patients diagnosed with colorectal cancer (CRC). The pivotal contribution of the immune microenvironment in the initiation and progression of CRC metastasis has gained significant attention. Methods: A total of 453 CRC patients from The Cancer Genome Atlas (TCGA) were included as the training set, and GSE39582, GSE17536, GSE29621, GSE71187 were included as the validation set. The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package. CTSW and FABP4-knockout CRC cells were constructed via CRISPR-Cas9 system. Western-blot and Transwell assay were utilized to explore the role of fatty acid binding protein 4 (FABP4) / cathepsin W (CTSW) in CRC metastasis and immunity. Results: Based on the normal/tumor, high-/low-immune cell infiltration, and metastatic/non-metastatic group, we identified 161 differentially expressed genes. After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts. According to this model, we clustered patients and found that the high-risk group was associated with stage, T and M stage. In addition, the high-risk group also shown higher immune infiltration and high sensitivity to PARP inhibitors. Further, FABP4 and CTSW derived from the constitutive model were identified to be involved in metastasis and immunity of CRC. Conclusion: In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment.
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The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package.
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quote
The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
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sections[20] "Data availability statement" paragraph 2
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
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A validated three-gene-pair prognostic model for colorectal cancer was constructed, and CTSW and FABP4 were identified as potential therapeutic targets.
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sections[0] "Abstract" paragraph 3
quote
After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts.
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In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment.
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A validated three-gene-pair prognostic model for colorectal cancer was constructed, and CTSW and FABP4 were identified as potential therapeutic targets.
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[170]
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[171]
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[172]
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[173]
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[179]
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[180]
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[186]
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[187]
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[188]
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[189]
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[190]
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[191]
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[192]
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[193]
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[194]
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[195]
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[196]
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[197]
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[198]
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[199]
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[200]
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[201]
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[202]
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[203]
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[204]
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[205]
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[206]
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[207]
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[208]
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[209]
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[210]
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[211]
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[212]
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[213]
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[214]
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[220]
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[221]
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[222]
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[223]
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[228]
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[229]
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[230]
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[232]
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[233]
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[234]
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[235]
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[236]
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[238]
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[239]
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[240]
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[242]
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[243]
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[249]
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[250]
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[251]
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[252]
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[253]
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[254]
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[255]
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[256]
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[257]
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[258]
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[259]
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[260]
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[262]
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[264]
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[265]
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[266]
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[267]
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[268]
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[269]
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[270]
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[271]
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[272]
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[273]
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[274]
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[275]
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[276]
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[277]
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[278]
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[279]
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[280]
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[281]
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[282]
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[283]
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[284]
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[285]
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[286]
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[287]
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[288]
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[289]
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[290]
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[291]
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[292]
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[293]
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[294]
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[295]
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[296]
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[297]
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[298]
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[299]
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[300]
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[301]
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[302]
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[303]
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[304]
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[306]
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[307]
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[308]
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[309]
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[310]
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[311]
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[312]
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[313]
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[314]
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[315]
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[316]
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[317]
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[318]
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[319]
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[320]
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[321]
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[322]
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[323]
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[324]
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[325]
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[326]
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[327]
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[328]
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[329]
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[330]
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[331]
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[332]
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[333]
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[334]
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[335]
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[336]
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[337]
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[338]
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[339]
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[340]
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[341]
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[342]
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[343]
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[344]
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[345]
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[346]
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[347]
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[348]
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[349]
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[350]
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[351]
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[352]
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[353]
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[354]
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[355]
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[356]
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[357]
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[358]
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[359]
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[360]
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[361]
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[362]
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[363]
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[364]
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[365]
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[366]
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[367]
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[368]
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[369]
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[370]
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[371]
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[372]
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[373]
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[374]
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[375]
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[376]
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[377]
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[378]
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[379]
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[380]
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[381]
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[382]
GSM972320
[383]
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[384]
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[385]
GSM972323
[386]
GSM972324
[387]
GSM972325
[388]
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[389]
GSM972327
[390]
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[391]
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[392]
GSM972330
[393]
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[394]
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[395]
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[396]
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[397]
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[398]
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[399]
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[400]
GSM972338
[401]
GSM972339
[402]
GSM972340
[403]
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[404]
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[405]
GSM972343
[406]
GSM972344
[407]
GSM972345
[408]
GSM972346
[409]
GSM972347
[410]
GSM972348
[411]
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[412]
GSM972350
[413]
GSM972351
[414]
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[415]
GSM972353
[416]
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[417]
GSM972355
[418]
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[419]
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[420]
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[421]
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[422]
GSM972360
[423]
GSM972361
[424]
GSM972362
[425]
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[426]
GSM972364
[427]
GSM972365
[428]
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[429]
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[430]
GSM972368
[431]
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[432]
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[433]
GSM972371
[434]
GSM972372
[435]
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[436]
GSM972374
[437]
GSM972375
[438]
GSM972376
[439]
GSM972377
[440]
GSM972378
[441]
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[442]
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[443]
GSM972381
[444]
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[445]
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[446]
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[447]
GSM972385
[448]
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[449]
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[450]
GSM972388
[451]
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[452]
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[453]
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[454]
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[455]
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[456]
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[457]
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[458]
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[459]
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[460]
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[461]
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[462]
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[463]
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[464]
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[465]
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[466]
GSM972404
[467]
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[468]
GSM972406
[469]
GSM972407
[470]
GSM972408
[471]
GSM972409
[472]
GSM972410
[473]
GSM972411
[474]
GSM972412
[475]
GSM972413
[476]
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[477]
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[478]
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[479]
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[480]
GSM972418
[481]
GSM972419
[482]
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[483]
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[484]
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[485]
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[486]
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[487]
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[488]
GSM972426
[489]
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[490]
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[491]
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[492]
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[493]
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[494]
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[495]
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[496]
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[497]
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[498]
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[499]
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[500]
GSM972438
[501]
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[502]
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[503]
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[504]
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[505]
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[506]
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[507]
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[508]
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[509]
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[510]
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[511]
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[512]
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[513]
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[514]
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[515]
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[516]
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[517]
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[518]
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[519]
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[520]
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[521]
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[522]
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[523]
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[524]
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[525]
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[526]
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[527]
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[528]
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[529]
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[530]
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[531]
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[532]
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[533]
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[534]
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[535]
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[536]
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[537]
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[538]
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[539]
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[540]
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[541]
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[542]
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[543]
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[544]
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[545]
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[546]
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[547]
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[548]
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[549]
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[550]
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[551]
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[552]
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[553]
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[554]
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[555]
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[556]
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[557]
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[558]
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[559]
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[560]
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[561]
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[563]
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[564]
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[565]
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[566]
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[567]
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[568]
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[569]
GSM972507
[570]
GSM972508
[571]
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[572]
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[573]
GSM972511
[574]
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[575]
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[576]
GSM972514
[577]
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[578]
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[579]
GSM972517
[580]
GSM972518
[581]
GSM972519
[582]
GSM972520
[583]
GSM972521
[584]
GSM972522
sample_count
585
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE71187
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71187
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE71187
version
null
note
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .
access_statement_kind
data_availability_statement
sample_accessions array · 189 items
[0]
GSM1829199
[1]
GSM1829200
[2]
GSM1829201
[3]
GSM1829202
[4]
GSM1829203
[5]
GSM1829204
[6]
GSM1829205
[7]
GSM1829206
[8]
GSM1829207
[9]
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[10]
GSM1829209
[11]
GSM1829210
[12]
GSM1829211
[13]
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[14]
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[15]
GSM1829214
[16]
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[17]
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[18]
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[19]
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[20]
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[21]
GSM1829220
[22]
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[23]
GSM1829222
[24]
GSM1829223
[25]
GSM1829224
[26]
GSM1829225
[27]
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[28]
GSM1829227
[29]
GSM1829228
[30]
GSM1829229
[31]
GSM1829230
[32]
GSM1829231
[33]
GSM1829232
[34]
GSM1829233
[35]
GSM1829234
[36]
GSM1829235
[37]
GSM1829236
[38]
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[39]
GSM1829238
[40]
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[41]
GSM1829240
[42]
GSM1829241
[43]
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[44]
GSM1829243
[45]
GSM1829244
[46]
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[47]
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[48]
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[49]
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[50]
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[51]
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[52]
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[53]
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[54]
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[55]
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[56]
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[57]
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[58]
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[59]
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[60]
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[61]
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[62]
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[63]
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[64]
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[65]
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[66]
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[67]
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[68]
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[69]
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[70]
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[71]
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[72]
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[73]
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[74]
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[75]
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[76]
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[77]
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[78]
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[79]
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[80]
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[81]
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[82]
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[83]
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[84]
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[85]
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[86]
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[88]
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[89]
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[90]
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[91]
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[92]
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[93]
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[94]
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[95]
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[96]
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[98]
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[99]
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[100]
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[101]
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[102]
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[103]
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[104]
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[105]
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[106]
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[108]
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[109]
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[112]
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[113]
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[114]
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[115]
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[116]
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[119]
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[120]
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[122]
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[123]
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[125]
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[126]
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[185]
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[187]
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[188]
GSM1829387
sample_count
189
group_sizes
null
group_sizes_basis
null
platform
6480
taxon
Homo sapiens
title
Development of colorectal cancer gene expression signatures from expression profiles of embryonic development, precancer progression and cancer samples
resolution_checked_at
2026-11-01T18:46:34Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE17536 not downloaded
[1]
asset:data:geo:GSE17536 licence not read
[2]
asset:data:geo:GSE29621 not downloaded
[3]
asset:data:geo:GSE29621 licence not read
[4]
asset:data:geo:GSE39582 not downloaded
[5]
asset:data:geo:GSE39582 licence not read
[6]
asset:data:geo:GSE71187 not downloaded
[7]
asset:data:geo:GSE71187 licence not read
analysis object · 4 fields
state
complete
methods array · 2 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
band
verbatim
quote
The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package.
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ABP4-knockout CRC cells were constructed via CRISPR-Cas9 system. Western-blot and Transwell assa
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The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37180113", "kind": "science-record", "revision": 2, "content_hash": "sha256:efa83a8908c46ec3d6348b5a858d46837f1a9d7a2956527ad78c52816dbe6146", "created_at": "2026-11-01T19:01:51Z", "updated_at": "2026-11-01T21:30:44Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel prognostic signatures based on metastasis- and immune-related gene pairs for colorectal cancer.", "doi": "10.3389/fimmu.2023.1161382", "pmid": "37180113", "authors": ["Bei Pan", "Yanzhe Yue", "Wenbo Ding", "Li Sun", "Mu Xu", "Shukui Wang"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Background: Metastasis remains the leading cause of mortality in patients diagnosed with colorectal cancer (CRC). The pivotal contribution of the immune microenvironment in the initiation and progression of CRC metastasis has gained significant attention.\nMethods: A total of 453 CRC patients from The Cancer Genome Atlas (TCGA) were included as the training set, and GSE39582, GSE17536, GSE29621, GSE71187 were included as the validation set. The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package. CTSW and FABP4-knockout CRC cells were constructed via CRISPR-Cas9 system. Western-blot and Transwell assay were utilized to explore the role of fatty acid binding protein 4 (FABP4) / cathepsin W (CTSW) in CRC metastasis and immunity.\nResults: Based on the normal/tumor, high-/low-immune cell infiltration, and metastatic/non-metastatic group, we identified 161 differentially expressed genes. After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts. According to this model, we clustered patients and found that the high-risk group was associated with stage, T and M stage. In addition, the high-risk group also shown higher immune infiltration and high sensitivity to PARP inhibitors. Further, FABP4 and CTSW derived from the constitutive model were identified to be involved in metastasis and immunity of CRC.\nConclusion: In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment.", "claims": [{"id": "claim-method", "statement": "The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37180113", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. 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The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A validated three-gene-pair prognostic model for colorectal cancer was constructed, and CTSW and FABP4 were identified as potential therapeutic targets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37180113", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts."}, {"asset": "source:pmid:37180113", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A validated three-gene-pair prognostic model for colorectal cancer was constructed, and CTSW and FABP4 were identified as potential therapeutic targets.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37180113"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE39582", "GSE17536", "GSE29621", "GSE71187"], "resolved_accessions": ["GSE39582", "GSE17536", "GSE29621", "GSE71187"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."], "basis": "The paper names GSE39582, GSE17536, GSE29621, GSE71187 in GSE39582 and the accession resolves in the repository. 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