MS4A15 gene expression as a prognostic marker for clinical outcomes in lung adenocarcinoma.

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"PMC11826265", "section_index": 17, "section_title": "Association between MS4A15 expression and clinical features", "row_count": 34, "column_count": 4}, "table": {"label": "Table 1", "caption": "Association between MS4A15 expression and the clinicopathologic features of LUAD patients", "rows": [["Characteristic", "Low expression of MS4A15 (n=267)", "High expression of MS4A15 (n=268)", "P"], ["Gender, n (%)", "", "", "0.002"], ["Female", "124 (23.2)", "162 (30.3)", ""], ["Male", "143 (26.7)", "106 (19.8)", ""], ["Age, n (%)", "", "", "0.02"], ["≤65 years", "142 (27.5)", "113 (21.9)", ""], [">65 years", "118 (22.9)", "143 (27.7)", ""], ["Age, years, median [IQR]", "64 [58.75, 72]", "67 [59, 73]", "0.06"], ["Smoker, n (%)", "", "", "0.008"], ["No", "26 (5.0)", "49 (9.4)", ""], ["Yes", "232 (44.5)", "214 (41.1)", ""], ["T stage, n (%)", "", "", "0.005"], ["T1", "68 (12.8)", "107 (20.1)", ""], ["T2", "160 (30.1)", "129 (24.2)", ""], ["T3", "26 (4.9)", "23 (4.3)", ""], ["T4", "11 (2.1)", "8 (1.5)", ""], ["N stage, n (%)", "", "", "0.09"], ["N0", "166 (32.0)", "182 (35.1)", ""], ["N1", "48 (9.2)", "47 (9.1)", ""], ["N2", "45 (8.7)", "29 (5.6)", ""], ["N3", "2 (0.4)", "0", ""], ["M stage, n (%)", "", "", "0.61"], ["M0", "190 (49.2)", "171 (44.3)", ""], ["M1", "15 (3.9)", "10 (2.6)", ""], ["Pathologic stage, n (%)", "", "", "0.04"], ["Stage I", "137 (26.0)", "157 (29.8)", ""], ["Stage II", "58 (11.0)", "65 (12.3)", ""], ["Stage III", "52 (9.9)", "32 (6.1)", ""], ["Stage IV", "16 (3.0)", "10 (1.9)", ""], ["Primary therapy outcome, n (%)", "", "", "0.005"], ["PD", "47 (10.5)", "24 (5.4)", ""], ["SD", "15 (3.4)", "22 (4.9)", ""], ["PR", "1 (0.2)", "5 (1.1)", ""], ["CR", "156 (35.0)", "176 (39.5)", ""]], "row_count": 34, "column_count": 4, "numeric_cells": 63, "header_rows": 1, "locator": "section[17]/table-wrap[1]#t1"}}, {"id": "asset:table:pmid:39958209:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:a5512366bab8b2da672e75f9d9a4c5f12b7be4e165d1d2850d06a80a399ecd24", "bytes": 989, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[17]/table-wrap[2]#t2", "version": null, "note": "The relationship between the clinicopathological factors of LUAD patients and MS4A15 expression using a logistic analysis", "structure": {"pmcid": "PMC11826265", "section_index": 17, "section_title": "Association between MS4A15 expression and clinical features", "row_count": 10, "column_count": 4}, "table": {"label": "Table 2", "caption": "The relationship between the clinicopathological factors of LUAD patients and MS4A15 expression using a logistic analysis", "rows": [["Characteristics", "Total (N)", "Odds ratio (95% CI)", "P value"], ["Gender (male vs. female)", "535", "0.567 (0.402–0.799)", "0.001"], ["Age (>65 vs. ≤65 years)", "516", "1.523 (1.077–2.158)", "0.02"], ["Smoker (no vs. yes)", "521", "2.043 (1.236–3.446)", "0.006"], ["Race (Black or African American vs. White)", "461", "0.809 (0.457–1.422)", "0.46"], ["Pathologic stage (stage III–IV vs. stage I–II)", "527", "0.543 (0.351–0.831)", "0.005"], ["T stage (T3–4 vs. T1–2)", "532", "0.809 (0.483–1.347)", "0.42"], ["N stage (N2–3 vs. N0–1)", "519", "0.577 (0.347–0.944)", "0.03"], ["M stage (M1 vs. M0)", "386", "0.741 (0.314–1.675)", "0.48"], ["Primary therapy outcome (PD vs. PR & CR)", "409", "0.443 (0.256–0.750)", "0.003"]], "row_count": 10, "column_count": 4, "numeric_cells": 31, "header_rows": 1, "locator": "section[17]/table-wrap[2]#t2"}}], "gaps": ["asset:source:pmid:39958209 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:39958209", "asset:table:pmid:39958209:1", "asset:table:pmid:39958209:2"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:39958209"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "67ea4a752f7c9717331266efa921cda58e0e1366ffa0043b71dcec2deb0d0719", "source_hash": "284b4434737b226836152a23f657b8837623bae555a18bfcdce7be06e7522af4", "raw_response_sha256": "sha256:0be345ef36b38e5479d83ef1e6ea3aa1d7f0adb76cb246f7b1a067c1656e61b9", "raw_response_chars": 4270}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "d9683f4534b8befcc6528ccd67263e9b674b0a13a0119247980007722da20930", "source_hash": "284b4434737b226836152a23f657b8837623bae555a18bfcdce7be06e7522af4", "raw_response_sha256": "sha256:83a55e337805b337bab98b783bd13a11ff18cd7132becb25e3240484e3dfe06d", "raw_response_chars": 57368}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "4ed35c5c76744787538a0486af5019f82f16054c8fe8ef08b8836a58fa0cba9a", "source_hash": "284b4434737b226836152a23f657b8837623bae555a18bfcdce7be06e7522af4", "raw_response": "{\"parent_value\":0.863,\"unit\":\"area under the curve\",\"evidence\":\"The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.\",\"target_result\":\"The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.\",\"number_stated\":true}", "reading": {"parent_value": 0.863, "unit": "area under the curve", "evidence": "The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.", "target_result": "The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.", "number_stated": true, "source_locator": "chars 2539-2616 of source sha256 284b4434737b226836152a23f657b8837623bae555a18bfcdce7be06e7522af4"}, "recorded_at": "2026-10-31T15:24:39.083384+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "08ac05d2e0337129330180d03f7124616e3fce1c333bf117936931b8c7b3f01c", "source_hash": "284b4434737b226836152a23f657b8837623bae555a18bfcdce7be06e7522af4", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline numerical result paper states for main finding. Need exact contiguous quote with number, unit printed. Candidates AUC 0.863, perhaps main finding prognostic marker no numeric hazard ratio. Headline numerical result likely 0.863, area under curve. Need unit as paper prints. \"The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.\" Unit perhaps \"area under the curve\" dimensionless. Required unit string. They say unit must be unit paper prints. It prints \"The area under the curve ... was 0.863.\" Could unit be empty? But number stated true likely unit perhaps \"area under the curve\" or \"AUC\"? Need infer desired extraction style.\n\nTarget is generic: headline numerical result paper states for main finding. Source abstract's only headline numerical result is AUC 0.863. Evidence exact contiguous quote. parent_value 0.863. Unit could be \"area under the curve\" perhaps the measured metric, though no physical unit. Maybe \"AUC\" is common unit? Paper doesn't literally use abbreviation AUC in quoted sentence, though earlier \"receiver operating characteristic (ROC)\". It says \"The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.\" The unit perhaps \"area under the curve\" (dimensionless). target_result can say \"The area under the ROC curve for MS4A15 effectiveness was 0.863.\" They demand headline number only perhaps means JSON fields, but target_result likely concise textual result.\n\nNeed exact quotation evidence whole clause. Could quote sentence exactly. Ensure no paraphrase. Unit must be paper prints. \"area under the curve of the ROC curve\" maybe awkward. We can set unit \"area under the curve of the ROC curve\" but unit is not really unit. Maybe unit string \"AUC\" despite source doesn't print acronym. User says unit must be unit paper prints, likely numerical results tasks expect units like years, months, etc. For AUC, dimensionless and no unit. But schema demands string; can use \"\". Yet instruction only says if no number, leave unit and evidence empty. Thus if number stated likely expect unit nonempty? Not necessarily schema only. They say \"unit must be the unit the paper prints.\" If dimensionless metric, perhaps unit \"area under the curve\" as paper wording. Need determine likely benchmark expects unit \"AUC\" perhaps extraction convention.\n\nLet's parse task framing. \"Read supplied paper text and find the 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. The evidence must be an exact, contiguous quotation from SOURCE TEXT that contains the number; do not shorten it, do not add an ellipsis and do not paraphrase it. Attribution may be carried by the text's own wording: a number may be attached to the target by a parenthetical list, by the word 'respectively', or by words that name the target directly. When that is how the text links them, quote the whole clause so a reader can check the attribution for themselves. If the text states no number for the registered target, set number_stated to false, leave parent_value at 0, leave unit and evidence empty, and say in target_result what the text does state instead.\"\n\nThis seems general extraction benchmark where target registered perhaps verbal, source may or may not numeric. Here target: headline numerical result paper states for its main finding. Need pick single number. The main numerical finding could 0.863 AUC. Other numbers: 1605 DEGs, 82 pathways, 24 immune cell types, cutoff 50%, thresholds, versions, datasets. Clearly headline result in abstract = AUC 0.863. Unit? The paper prints metric \"area under the curve of the ROC curve for MS4A15 effectiveness\". Could represent unit as \"area under the curve of the ROC curve\". But \"unit\" likely \"AUC\" because that's the measure. Yet paper prints ROC and area under curve, though not acronym AUC. They insist unit must be unit paper prints perhaps don't transform 0.863 to 86.3%. So \"area under the curve of the ROC curve\" or perhaps empty string. We need provide exact unit as source's printed wording maybe \"area under the curve\". Let's think expected schema likely evaluated by LLM or exact fields? parent_value 0.863. unit probably \"area under the curve of the ROC curve\" or \"AUC\". Evidence exact sentence. target_result perhaps \"Area under the ROC curve for MS4A15 effectiveness: 0.863.\" Could they expect no unit since AUC is dimensionless? They ask unit must be unit paper prints. There is no conventional physical unit. In similar tasks, for AUC likely unit \"AUC\" accepted. Need ensure no invented source. \"AUC\" acronym does not appear in source at all? Search source: receiver operating characteristic (ROC), area under curve. No \"AUC\". So if unit must be as paper prints, avoid AUC. Could set unit \"area under the curve of the ROC curve for MS4A15 effectiveness\" exactly as printed. But that's metric descriptor, not unit. Perhaps unit could be \"\" because dimensionless. Yet they specifically require unit field and only tell empty if no number stated, implying for stated number unit should be populated. So likely they consider measurement unit to be \"area under the curve\". Could put \"area under the curve of the ROC curve\". Better exact printed phrase.\n\nNeed \"headline number only\" perhaps target_result should just \"0.863\" and unit separate. But they ask target_result when no number say what text states instead. For stated case, likely target_result textual description. Maybe \"0.863 (area under the ROC curve for MS4A15 effectiveness).\" Yet evidence does attribution. We can make target_result \"Area under the ROC curve for MS4A15 effectiveness was 0.863.\" This repeats.\n\nExact quote:\n\"The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.\"\nYes.\n\nJSON valid. Unit string maybe \"area under the curve of the ROC curve\". Is capitalization relevant? Unit perhaps \"area under the curve of the ROC curve for MS4A15 effectiveness\" exact. Let's formulate.\n\nCould there be concern headline main finding is expression differential but no numeric result, whereas AUC is a secondary metric and not headline? The registered target phrasing explicitly asks \"the headline numerical result the paper states for its main finding\", perhaps the source's abstract has one numerical result. likely 0.863.\n\nMaybe the headline result in paper title/main claim is MS4A15 downregulated, and no exact number stated for expression change. But instruction asks single numerical result replication target has to reproduce. They might expect AUC because only reported headline metric. The text says \"The area under the curve ... 0.863.\" likely selected target. Yes.\n\nUnit: AUC dimensionless. Could label \"area under the curve (AUC)\" but AUC not printed, though expansion printed. They say \"unit must be the unit the paper prints\", likely okay to use phrase exactly. Let's use \"area under the curve of the ROC curve\" exact contiguous phrase. target_result perhaps \"The ROC area under the curve for MS4A15 effectiveness was 0.863.\" No need exact quote there.\n\nNeed output only JSON.</think>\n\n{\"parent_value\":0.863,\"unit\":\"area under the curve of the ROC curve\",\"evidence\":\"The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.\",\"target_result\":\"The area under the ROC curve for MS4A15 effectiveness was 0.863.\",\"number_stated\":true}", "reading": {"parent_value": 0.863, "unit": "area under the curve of the ROC curve", "evidence": "The area under the curve of the ROC curve for MS4A15 effectiveness was 0.863.", "target_result": "The area under the ROC curve for MS4A15 effectiveness was 0.863.", "number_stated": true, "source_locator": "chars 2539-2616 of source sha256 284b4434737b226836152a23f657b8837623bae555a18bfcdce7be06e7522af4"}, "recorded_at": "2026-10-31T15:24:58.167781+00:00"}], "agreement": false, "disagreements": {"physical_methods": {"minimax": ["Real-time quantitative polymerase chain reaction (RT-qPCR) was performed to validate the messenger RNA transcription level in vitro."], "minimax_alt": ["Cell culture of A549 and NHBE cells", "Real-time quantitative polymerase chain reaction (RT-qPCR)"], "decisive": false}, "analysis_methods": {"minimax": ["Differential Expression analysis of Sequencing data version 2 (DESeq2)", "ClusteProfiler package for Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses", "Gene set variation analysis (GSVA)", "Wilcoxon rank-sum test", "Logistic regression analysis", "Receiver operating characteristic (ROC) curve analysis", "Kaplan-Meier analysis", "Spearman correlation analysis", "Real-time quantitative polymerase chain reaction (RT-qPCR)"], "minimax_alt": ["Differential Expression analysis of Sequencing data version 2 (DESeq2)", "Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using ClusteProfiler", "Gene set enrichment analysis using ClusteProfiler", "Gene set variation analysis (GSVA) using single-sample gene set enrichment analysis (ssGSEA)", "Spearman correlation", "Wilcoxon rank-sum test", "Logistic regression", "Receiver operating characteristic (ROC) curve analysis", "Kaplan-Meier analysis"], "decisive": false}, "unit": {"minimax": "area under the curve", "minimax_alt": "area under the curve of the ROC curve", "decisive": true}}, "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": "blocked", "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.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:05ef46f68ee8df57e10912dbf40911ef8eb04cb9425a81e199ee07a623b12a90", "type": "sep_package", "label": "SEP v1 package for pmid:39958209"}], "activities": [{"id": "activity:conversion:pmid:39958209", "type": "conversion", "used": ["package:05ef46f68ee8df57e10912dbf40911ef8eb04cb9425a81e199ee07a623b12a90"], "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:39958209", "parent_hash": "sha256:23c78823e4ee50b535e567d0d851af1fb95e708768a60bf0fc1ab3c281e4a492", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:39958209 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "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:39958209' does not resolve to a declared asset", "targets"]}