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pmid:35935823

Development and validation of a hypoxia-stemness-based prognostic signature in pancreatic adenocarcinoma.

Xiong Tian · Jing Zheng · Wanlan Mou · Guoguang Lu · Shuaishuai Chen · Juping Du · Yufen Zheng · Shiyong Chen · Bo Shen · Jun Li · Na Wang

Frontiers in pharmacology · 2022 doi:10.3389/fphar.2022.939542

Paper

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Experiment

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title
Development and validation of a hypoxia-stemness-based prognostic signature in pancreatic adenocarcinoma.
doi
10.3389/fphar.2022.939542
pmid
35935823
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[0]
Xiong Tian
[1]
Jing Zheng
[2]
Wanlan Mou
[3]
Guoguang Lu
[4]
Shuaishuai Chen
[5]
Juping Du
[6]
Yufen Zheng
[7]
Shiyong Chen
[8]
Bo Shen
[9]
Jun Li
[10]
Na Wang
journal
Frontiers in pharmacology
year
2022
abstract
Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive and fatal gastrointestinal malignancies with high morbidity and mortality worldwide. Accumulating evidence has revealed the clinical significance of the interaction between the hypoxic microenvironment and cancer stemness in pancreatic cancer progression and therapies. This study aims to identify a hypoxia-stemness index-related gene signature for risk stratification and prognosis prediction in PAAD. Methods: The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm. Univariate Cox regression and LASSO regression analyses were then performed to establish a hypoxia-mRNAsi-related gene signature, and its prognostic performance was verified in both the TCGA-PAAD and GSE62452 corhorts by Kaplan-Meier and receiver operating characteristic (ROC) analyses. Additionally, we further validated the expression levels of signature genes using the TCGA, GTEx and HPA databases as well as qPCR experiments. Moreover, we constructed a prognostic nomogram incorporating the eight-gene signature and traditional clinical factors and analyzed the correlations of the risk score with immune infiltrates and immune checkpoint genes. Results: The mRNAsi values of PAAD samples were significantly higher than those of normal samples (p < 0.001), and PAAD patients with high mRNAsi values exhibited worse overall survival (OS). A novel prognostic risk model was successfully constructed based on the eight-gene signature comprising JMJD6, NDST1, ENO3, LDHA, TES, ANKZF1, CITED, and SIAH2, which could accurately predict the 1-, 3-, and 5-year OS of PAAD patients in both the training and external validation datasets. Additionally, the eight-gene signature could distinguish PAAD samples from normal samples and stratify PAAD patients into low- and high-risk groups with distinct OS. The risk score was closely correlated with immune cell infiltration patterns and immune checkpoint molecules. Moreover, calibration analysis showed the excellent predictive ability of the nomogram incorporating the eight-gene signature and traditional clinical factors. Conclusion: We developed a hypoxia-stemness-related prognostic signature that reliably predicts the OS of PAAD. Our findings may aid in the risk stratification and individual treatment of PAAD patients.
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The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm.
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The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm.
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Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD.
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Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD.
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sections[19] "Internal and external validation of the predictive performance of the eight-gene signature" paragraph 2
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Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD.
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sections[19] "Internal and external validation of the predictive performance of the eight-gene signature" paragraph 2
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Kaplan-Meier survival analysis revealed a notable correlation between high risk scores and the dismal prognosis of PAAD patients in the TCGA dataset (Figure 4A).
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Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35935823", "kind": "science-record", "revision": 3, "content_hash": "sha256:f78a701a11d604d7456756bf9d63ccc589b11e74711705f16696a5f2a9dcef93", "created_at": "2026-11-01T18:15:02Z", "updated_at": "2026-11-01T21:28:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and validation of a hypoxia-stemness-based prognostic signature in pancreatic adenocarcinoma.", "doi": "10.3389/fphar.2022.939542", "pmid": "35935823", "authors": ["Xiong Tian", "Jing Zheng", "Wanlan Mou", "Guoguang Lu", "Shuaishuai Chen", "Juping Du", "Yufen Zheng", "Shiyong Chen", "Bo Shen", "Jun Li", "Na Wang"], "journal": "Frontiers in pharmacology", "year": 2022, "abstract": "Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive and fatal gastrointestinal malignancies with high morbidity and mortality worldwide. Accumulating evidence has revealed the clinical significance of the interaction between the hypoxic microenvironment and cancer stemness in pancreatic cancer progression and therapies. This study aims to identify a hypoxia-stemness index-related gene signature for risk stratification and prognosis prediction in PAAD. Methods: The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm. Univariate Cox regression and LASSO regression analyses were then performed to establish a hypoxia-mRNAsi-related gene signature, and its prognostic performance was verified in both the TCGA-PAAD and GSE62452 corhorts by Kaplan-Meier and receiver operating characteristic (ROC) analyses. Additionally, we further validated the expression levels of signature genes using the TCGA, GTEx and HPA databases as well as qPCR experiments. Moreover, we constructed a prognostic nomogram incorporating the eight-gene signature and traditional clinical factors and analyzed the correlations of the risk score with immune infiltrates and immune checkpoint genes. Results: The mRNAsi values of PAAD samples were significantly higher than those of normal samples (p < 0.001), and PAAD patients with high mRNAsi values exhibited worse overall survival (OS). A novel prognostic risk model was successfully constructed based on the eight-gene signature comprising JMJD6, NDST1, ENO3, LDHA, TES, ANKZF1, CITED, and SIAH2, which could accurately predict the 1-, 3-, and 5-year OS of PAAD patients in both the training and external validation datasets. Additionally, the eight-gene signature could distinguish PAAD samples from normal samples and stratify PAAD patients into low- and high-risk groups with distinct OS. The risk score was closely correlated with immune cell infiltration patterns and immune checkpoint molecules. Moreover, calibration analysis showed the excellent predictive ability of the nomogram incorporating the eight-gene signature and traditional clinical factors. Conclusion: We developed a hypoxia-stemness-related prognostic signature that reliably predicts the OS of PAAD. Our findings may aid in the risk stratification and individual treatment of PAAD patients.", "claims": [{"id": "claim-method", "statement": "The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35935823", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm."}], "state": "complete"}, {"id": "claim-data-access", "statement": "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.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35935823", "locator": "sections[27] \"Data availability statement\" paragraph 2", "quote": "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."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD."}, "evidence": [{"asset": "source:pmid:35935823", "locator": "sections[19] \"Internal and external validation of the predictive performance of the eight-gene signature\" paragraph 2", "quote": "Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD."}, {"asset": "source:pmid:35935823", "locator": "sections[19] \"Internal and external validation of the predictive performance of the eight-gene signature\" paragraph 2", "quote": "Kaplan-Meier survival analysis revealed a notable correlation between high risk scores and the dismal prognosis of PAAD patients in the TCGA dataset (Figure 4A)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Time-dependent ROC analysis suggested that the AUCs for 1-, 3-, and 5-year OS were 0.814 (95% CI: 0.762–0.853), 0.784 (95% CI: 0.709–0.821), and 0.714 (95% CI: 0.685–0.767), respectively (Figure 4D), which confirmed the stability of the eight-gene signature in survival prediction for PAAD.", "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:35935823"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE62452"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE62452"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35935823", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fphar.2022.939542", "sha256": "sha256:79114d1a9ea73283c39bca0877b068408baf7139c9358ba6a53aef63b2a9c4c7", "bytes": 44093, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fphar.2022.939542", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9350896", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE62452", "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=GSE62452", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE62452", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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