A Novel Hypoxia-Immune Signature for Gastric Cancer Prognosis and Immunotherapy: Insights from Bulk and Single-Cell RNA-Seq.

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Relationship Between Gene Signature and Clinicopathological Parameters", "row_count": 14, "column_count": 7}, "table": {"label": "Table 1", "caption": "Cox Regression Analysis of Clinicopathological Features and Risk Score Impact on OS in TCGA-STAD and GSE84437 Cohorts.", "rows": [["Factors", "Univariate Analysis", "Multivariate Analysis"], ["HR", "95%CI", "p-Value", "HR", "95%CI", "p-Value"], ["TCGA cohort"], ["Age", "1.52", "1.094–2.113", "0.0125 *", "1.773", "1.2707–2.475", "0.000754 ***"], ["Gender (male vs. female)", "1.232", "0.8774–1.73", "0.228", "1.201", "0.8532–1.689", "0.294109"], ["T stage", "1.306", "1.072–1.591", "0.00797 **", "1.238", "1.0004–1.533", "0.049602 *"], ["N stage", "1.379", "1.196–1.59", "9.78 × 10−6 ***", "1.312", "1.1312–1.521", "0.000328 ***"], ["Risk score (high vs. low)", "1.818", "1.314–2.514", "0.000305 ***", "1.854", "1.3381–2.569", "0.000208 ***"], ["GSE84437 cohort"], ["Age", "1.02", "1.007–1.032", "0.00225 **", "1.023", "1.0108–1.036", "0.000244 ***"], ["Gender (male vs. female)", "1.256", "0.9275–1.7", "0.141", "1.184", "0.8726–1.606", "0.278218"], ["T stage", "1.74", "1.378–2.198", "3.31 × 10−6 ***", "1.583", "1.2385–2.024", "0.000246 ***"], ["N stage", "1.676", "1.429–1.967", "2.42 × 10−10 ***", "1.515", "1.2871–1.782", "5.72 × 10−7 ***"], ["Risk score (high vs. low)", "1.589", "1.206–2.094", "0.00101 **", "1.395", "1.0562–1.843", "0.019045 *"]], "row_count": 14, "column_count": 7, "numeric_cells": 63, "header_rows": 2, "locator": "section[12]/table-wrap[1]#cimb-47-00552-t001"}}, {"id": "asset:table:pmid:40729021:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:b3376c7a09b84936dffd7f0cdc295b89bfb976107acceceb8107543e406ea448", "bytes": 1563, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[2]#cimb-47-00552-t002", "version": null, "note": "The correlation between clinicopathological factors and the risk score.", "structure": {"pmcid": "PMC12293835", "section_index": 12, "section_title": "3.2. Relationship Between Gene Signature and Clinicopathological Parameters", "row_count": 18, "column_count": 9}, "table": {"label": "Table 2", "caption": "The correlation between clinicopathological factors and the risk score.", "rows": [["", "TCGA Cohort", "GSE84437 Cohort"], ["Total(N = 404)", "LowRisk (N = 202)", "High Risk (N = 202)", "p-Value", "Total(N = 433)", "High Risk (N = 216)", "Low Risk (N = 217)", "p-Value"], ["Gender"], ["Male", "261 (64.6%)", "134 (66.3%)", "127 (62.9%)", "0.5325", "296 (68.4%)", "147 (68.1%)", "149 (68.7%)", "0.892"], ["Female", "143 (35.4%)", "68 (33.7%)", "75 (37.1%)", "137 (31.6%)", "69 (31.9%)", "68 (31.3%)"], ["Age"], ["<55", "67 (16.6%)", "30 (14.9%)", "37 (18.2%)", "0.4222", "129 (28.9%)", "69 (31.9%)", "60 (27.6%)", "0.329"], ["≥55", "337 (83.4%)", "172 (85.1%)", "165 (81.7%)", "304 (70.2%)", "147 (68.1%)", "157 (72.4%)"], ["N stage"], ["N0", "125 (30.9%)", "66 (32.7%)", "59 (29.2%)", "0.4545", "80 (18.5%)", "39 (18.1%)", "41 (18.9%)", "0.011 *"], ["N1", "114 (28.2%)", "59 (29.2%)", "55 (27.2%)", "188 (43.4%)", "80 (37%)", "108 (49.8%)"], ["N2", "82 (20.3%)", "42 (20.8%)", "40 (19.8%)", "132 (30.5%)", "81 (37.5%)", "51 (23.5%)"], ["N3", "83 (20.5%)", "35 (17.3%)", "48 (23.8%)", "33 (7.6%)", "16 (7.4%)", "17 (7.8%)"], ["T stage"], ["T1", "22 (5.4%)", "16 (7.9%)", "6 (3%)", "0.0222 *", "11 (2.5%)", "1 (0.5%)", "10 (4.6%)", "0.001 ***"], ["T2", "90 (22.3%)", "41 (20.3%)", "49 (24.3%)", "38 (8.8%)", "13 (6.0%)", "25 (11.5%)"], ["T3", "182 (45%)", "99 (49%)", "83 (41.1%)", "92 (21.2%)", "40 (18.5%)", "52 (24%)"], ["T4", "110 (27.2%)", "46 (22.8%)", "64 (31.7%)", "292 (67.4%)", "162 (75%)", "130 (59.9%)"]], "row_count": 18, "column_count": 9, "numeric_cells": 89, "header_rows": 2, "locator": "section[12]/table-wrap[2]#cimb-47-00552-t002"}}], "gaps": ["asset:source:pmid:40729021 not verified"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "targets"]}, "capability": {"state": "absent", "requirements": [], "gaps": ["capability"]}, "readiness": {"state": "partial", "tier": null, "blocking_axis": null, "blocked_on": null, "axes": {}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:40729021", "asset:table:pmid:40729021:1", "asset:table:pmid:40729021:2"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40729021"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "passed", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "857b522bc2584cc30d7a23706e561ec2aa23a664b042625e534e980dc3ddbfc9", "source_hash": "3b458d73984e2680c36c030909b3a6d65905451d9d1ef800ce2e914bbdc1e0f7", "raw_response_sha256": "sha256:50122462bf053c4d99adf09eaab847f258186f97d5a12213401d2a9e4645b952", "raw_response_chars": 5780}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "875f65cbf3355dbd88efaad3ee82e2cc04d331c7293c534dd874fcb5b10f8d72", "source_hash": "3b458d73984e2680c36c030909b3a6d65905451d9d1ef800ce2e914bbdc1e0f7", "raw_response_sha256": "sha256:1aef0ed746a0fe620298f68c060eec584b10e2573be3b665a5ccbbd5de0f2919", "raw_response_chars": 63261}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "7758688910659033c799282248fd59d0490f28d2fdb6a3bca912d947ecbe86c7", "source_hash": "3b458d73984e2680c36c030909b3a6d65905451d9d1ef800ce2e914bbdc1e0f7", "raw_response": "{\"parent_value\":5,\"unit\":\"genes\",\"evidence\":\"Results: Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\",\"target_result\":\"The study identified a five-gene signature.\",\"number_stated\":true}", "reading": {"parent_value": 5, "unit": "genes", "evidence": "Results: Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.", "target_result": "The study identified a five-gene signature.", "number_stated": true, "source_locator": "chars 932-1004 of source sha256 3b458d73984e2680c36c030909b3a6d65905451d9d1ef800ce2e914bbdc1e0f7"}, "recorded_at": "2026-10-31T15:23:28.270945+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "fb890e3242902672f5d81c28e50e2b056b22690d74aeebc55859974d8405eb11", "source_hash": "3b458d73984e2680c36c030909b3a6d65905451d9d1ef800ce2e914bbdc1e0f7", "raw_response": "<think>We need produce JSON object according schema extracting single numerical result headline main finding from source. Need carefully interpret no number for main headline. Source abstract results five genes named, risk score stratifies, no hazard ratio numeric, no survival metric. Methods mention 22 immune cell types, 9 major cell types, p <0.05, 3 scRNA datasets, R version; but not headline numerical result. Registered target headline numerical result paper states for main finding. Likely false because paper text no numerical value attached to main finding (five genes perhaps number \"Five\" but unit genes; is that headline numerical result?). Need decide. We have explicit source \"Results: Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\" That is a numerical result for main finding, unit \"genes\", parent_value 5. User asks \"single numerical result that a replication of the registered target has to reproduce. Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed. The unit must be the unit the paper prints. Evidence exact contiguous quotation contains the number; ... Attribution may be carried ... when text links them, quote whole clause.\" Target \"the headline numerical result the paper states for its main finding\". Five genes is likely headline number in abstract. We must analyze expected desired behavior. They deliberately source has no HR number, but counts 5 signature genes. They might intend no number because headline main finding? Let's inspect formulation. Registered target specified abstractly \"the headline numerical result the paper states for its main finding\". We need extract number only if explicit. Abstract Results: \"Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\" This is explicit numerical result for main finding of novel hypoxia-immune signature. Replication must reproduce 5 genes. Unit \"genes\". Number written \"Five\" not numeric? parent_value number 5, evidence exact includes Five. They say \"Report headline number only: value paper itself states ... not value you calculated, converted, averaged or reconstructed.\" Converting \"Five\" to 5 is natural, allowed presumably. The unit paper prints no \"genes\" unit printed yes. Could also be \"22 different types\" etc but not main. \"9 major cell types\" not main. \"p-value threshold of less than 0.05\" not main. \"Five genes\" likely expected. Need consider target semantic ambiguity. Might be instruction \"if text states no number for registered target set false\" a guard against picking arbitrary methods counts. The source has many incidental numbers and one abstract main result count. The intended is likely 5 genes. We should extract exactly \"Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\" This is whole clause, contiguous, number. number_stated true, parent_value 5, unit \"genes\", target_result describe five-gene signature in abstract. Evidence whole clause. No need include \"Results:\" but can include as exact contiguous. Could evidence \"Results: Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\" meets attribution. Target_result \"The paper reports five genes identified for its prognostic hypoxia- and immune-related gene signature.\" Might be headline number \"Five\". No other numerical result for main finding? They might expect no number for risk score due HR absent. But the target is broad \"headline numerical result ... main finding\". Five genes qualifies. We must not overthink but reason further.\n\nThis task pattern likely generated benchmark with target descriptions and source chunks. They ask to find numerical result. Source text an abstract plus methods. The registered target \"the headline numerical result the paper states for its main finding\" may be an intentionally underspecified target because paper absent actual quantitative values. User expects false if no number for registered target. We need decide intended test via wording. They often ask \"REGISTERED TARGET: the main numerical result reported in the abstract\" and source has e.g. median overall survival 35 months. Here target \"headline numerical result the paper states for its main finding\". Abstract contains \"Five genes\" which is numerical but arguably headline count main finding. Thus true seems plausible.\n\nLook at paper title \"A Novel Hypoxia-Immune Signature for Gastric Cancer Prognosis and Immunotherapy: Insights from Bulk and Single-Cell RNA-Seq\". Abstract says five genes were identified, risk score etc. No numeric performance. A replication must reproduce five-gene signature and prognostic performance. The only clear numeric headline count is 5. Unit must unit paper prints: \"genes\". The user asks \"single numerical result that a replication of the registered target has to reproduce.\" \"the headline numerical result the paper states for its main finding\" = gene signature comprised 5 genes. It says \"Five genes ... were identified.\" Exactly.\n\nNeed ensure evidence exact contiguous quotation with no modification. Use \"Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\" Exactly text. Could include Results prefix but no need; whole clause good. parent_value 5 unit \"genes\". target_result not necessarily just number? They request \"Report the headline number only\" might mean output only headline numeric value in parent_value, and target_result string perhaps \"Five genes ...\". Can describe identification of five genes. JSON only. No markdown.\n\nCould set evidence \"Results: Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\" This includes complete contiguous source. Need unit singular? Source \"Five genes\". Unit \"genes\". Good.\n\nFinal JSON.</think>\n\n{\"parent_value\":5,\"unit\":\"genes\",\"evidence\":\"Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.\",\"target_result\":\"The paper identifies five genes for the hypoxia- and immune-related prognostic signature.\",\"number_stated\":true}", "reading": {"parent_value": 5, "unit": "genes", "evidence": "Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified.", "target_result": "The paper identifies five genes for the hypoxia- and immune-related prognostic signature.", "number_stated": true, "source_locator": "chars 941-1004 of source sha256 3b458d73984e2680c36c030909b3a6d65905451d9d1ef800ce2e914bbdc1e0f7"}, "recorded_at": "2026-10-31T15:23:52.669891+00:00"}], "agreement": true, "disagreements": {"analysis_methods": {"minimax": ["Cox regression analysis", "Kaplan–Meier analysis", "log-rank test", "t-tests", "chi-square tests", "single-sample Gene Set Enrichment Analysis (ssGSEA)", "Principal Component Analysis (PCA)", "Z-score methods", "CIBERSORT", "Harmony algorithm", "Seurat pipeline", "SingleR"], "minimax_alt": ["Cox regression analyses", "Kaplan–Meier analysis", "log-rank test", "t-tests", "chi-square tests", "CIBERSORT", "single-sample Gene Set Enrichment Analysis (ssGSEA)", "Principal Component Analysis (PCA)", "Z-score methods", "Harmony algorithm", "Seurat pipeline", "SingleR"], "decisive": false}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "passed", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.passed"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:834280a8bc2d7efe75c5f27fa4d56d2a2b0b9a3d2f0dc2d63ea1019b69c99e4f", "type": "sep_package", "label": "SEP v1 package for pmid:40729021"}], "activities": [{"id": "activity:conversion:pmid:40729021", "type": "conversion", "used": ["package:834280a8bc2d7efe75c5f27fa4d56d2a2b0b9a3d2f0dc2d63ea1019b69c99e4f"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:40729021", "parent_hash": "sha256:60b89ea7886bafabe525edf17becbb284d6f5376adb1e522f7eacf6306946608", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:40729021 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.passed", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40729021' does not resolve to a declared asset", "targets"]}