Exploration of an Prognostic Signature Related to Endoplasmic Reticulum Stress in Colorectal Adenocarcinoma and Their Response Targeting Immunotherapy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37920989", "kind": "science-record", "revision": 3, "content_hash": "sha256:988a313b27527647fd6dadf2555ca03f13515441c20334af135b5b96269a6959", "created_at": "2026-11-01T19:02:48Z", "updated_at": "2026-11-01T22:10:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of an Prognostic Signature Related to Endoplasmic Reticulum Stress in Colorectal Adenocarcinoma and Their Response Targeting Immunotherapy.", "doi": "10.1177/15330338231212073", "pmid": "37920989", "authors": ["Yu Xu", "Yang-Mei Xie", "Wen-Sha Sun", "Rong Zi", "Hong-Qiao Lu", "Le Xiao", "Kun-Mei Gong", "Shi-Kui Guo"], "journal": "Technology in cancer research & treatment", "year": 2023, "abstract": "Background: Endoplasmic reticulum (ER) stress plays a pro-apoptotic role in colorectal adenocarcinoma (COAD). This study aimed to develop a novel ER-stress-related prognostic risk model for COAD and provide support for COAD cohorts with different risk score responses to immune checkpoint inhibitor therapies. Methods: TCGA-COAD and GSE39582 were included in this prospective study. Univariate and multivariate Cox analyses were performed to identify prognostic ER stress-related genes (ERSGs). Accordingly, the immune infiltration landscape and immunotherapy response in different risk groups were assessed. Finally, the expression of prognostic genes in 10 normal and 10 COAD tissue samples was verified using reverse transcription-quantitative polymerase chain reaction. Results: Eight prognostic genes were selected to establish an ERSG-based signature in the training set of the TCGA-COAD cohort. The accuracy of this was confirmed using a testing set of TCGA-COAD and GSE39582 cohorts. Gene set variation analysis indicated that differential functionality in high-low-risk groups was related to immune-related pathways. Corresponding to this, CD36, TIMP1, and PTGIS were significantly associated with 19 immune cells with distinct proportions between the different risk groups, such as central memory CD4T cells and central memory CD8T cells. Moreover, the risk score was considered effective for predicting the clinical response to immunotherapy, and the immunotherapy response was significantly and negatively correlated with the risk score of individuals with COAD. Furthermore, the immune checkpoint inhibitor treatment was less effective in the high-risk group, where the expression levels of PD-L1 and tumor immune dysfunction and exclusion scores in the high-risk group were significantly increased. Finally, the experimental results demonstrated that the expression trends of prognostic genes in clinical samples were consistent with the results from public databases. Conclusion: Our study established a novel risk signature to predict the COAD prognosis of patients and provide theoretical support for the clinical treatment of COAD.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate Cox analyses were performed to identify prognostic ER stress-related genes (ERSGs).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37920989", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Univariate and multivariate Cox analyses were performed to identify prognostic ER stress-related genes (ERSGs)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Availability of Data and Materials: The GSE39582 cohort used in our study can be found in the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE39582), and the TCGA-COAD cohort (https://portal.gdc.cancer.gov/) is available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37920989", "locator": "sections[27] \"Footnotes\" paragraph 2", "quote": "Availability of Data and Materials: The GSE39582 cohort used in our study can be found in the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE39582), and the TCGA-COAD cohort (https://portal.gdc.cancer.gov/) is available."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "", "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:37920989"], "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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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:37920989", "data:geo:GSE39582"], "steps": []}, "must_build": {"dsl_operations": [{"operation": "student_t", "unlocks_papers": null, "priority": null}], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE39582"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:58:14Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 18325, "completion_tokens": 1270, "cached_tokens": 256}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:37920989", "type": "paper", "label": "pmid:37920989"}, {"id": "source:pmid:37920989", "type": "manuscript", "label": "PMID 37920989 full text"}, {"id": "data:geo:GSE39582", "type": "dataset", "label": "GEO GSE39582"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37920989", "type": "paper", "label": "pmid:37920989"}, {"id": "source:pmid:37920989", "type": "manuscript", "label": "PMID 37920989 full text"}, {"id": "data:geo:GSE39582", "type": "dataset", "label": "GEO GSE39582"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37920989", "type": "extraction", "used": ["source:pmid:37920989"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE39582", "type": "accession_resolution", "used": ["data:geo:GSE39582"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:37920989", "parent_hash": "sha256:b78a82d651752aa7653e0d253b2d5da8ba8104333087ea3c4c97bc60e6b98e8b", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE39582 licence not read", "asset:data:geo:GSE39582 not downloaded", "execution.not_run", "method.reader_named_unmapped", "method.student_t", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:run_analysis blocked on method:student_t"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["adjacent normal tissue samples and performed RT-qPCR. As shown in Figure 10, KPNA2, SHH, TRAP1, a", "ed at low levels. The statistical results of RT-qPCR are shown in Table 2. The mRNA expression pa", "and adjacent normal samples was confirmed by RT-qPCR (n = 10). (A) KPNA2 (P = .0151, t = 2.685),", "*** P < .001, **** P < .0001.Abbreviations: RT-qPCR, real-time quantitative reverse transcriptio"], "order_basis": "paper_text_order:2586", "id": "assay:1"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Student's t-test"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}