Exosomal gene signature in esophageal carcinoma: Insights from single-cell and bulk RNA sequencing.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40816225", "kind": "science-record", "revision": 1, "content_hash": "sha256:d149c814b1b23a77229b2c0ff6cf56977d18605757f91aca9b0d2955114e2403", "created_at": "2026-11-01T10:25:52Z", "updated_at": "2026-11-01T10:25:52Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Exosomal gene signature in esophageal carcinoma: Insights from single-cell and bulk RNA sequencing.", "doi": "10.1016/j.tranon.2025.102490", "pmid": "40816225", "authors": null, "journal": "Translational oncology", "year": 2025, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "quantitative", "state": "complete", "target": {"value": 9.0, "unit": "genes", "tolerance": null, "source": "chars 99-183 of source sha256 313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065"}, "evidence": [{"asset": "source:pmid:40816225", "locator": "chars 99-183 of source sha256 313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065", "quote": "A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data."}]}], "gaps": ["abstract", "authors"]}, "experiment": {"state": "partial", "objective": "the headline numerical result the paper states for its main finding", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate and its interval from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The number a replication must land on, and the sentence it came from.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40816225"], "outputs": ["the published estimate, its unit and its interval"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data behind the published result", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The published result cannot be recomputed without the data the paper analysed.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the analysis programme", "kind": "analysis", "state": "blocked", "blocked_on": "no owned computational capability is bound to this experiment", "description": "Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:40816225", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the registered result"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent", "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:40816225' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40816225", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.tranon.2025.102490", "sha256": "sha256:313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.tranon.2025.102490", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}], "gaps": ["asset:source:pmid:40816225 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:40816225"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40816225"]}, "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": "9fbfe0619d793ef44d7a1148801d660b275e0fecb26d92fd1fc8df2dfe1b3505", "source_hash": "313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065", "raw_response_sha256": "sha256:016b48d83055c8883a203b76d5bfc5928de11357bc31c879eb03ec581aea76fc", "raw_response_chars": 3936}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "13ce42f23b613ccedab54234c43f42d2f3d6f0c540324cca12e4ba78e0200657", "source_hash": "313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065", "raw_response_sha256": "sha256:6833d909c941bd4effa030c131c65517ffde250512b656ba4c1cbccea0c570ff", "raw_response_chars": 52176}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "78c22c0677d78a159bdb222e3621cdf1dd3a993e92443f2121ba1460fa80e4db", "source_hash": "313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065", "raw_response": "{\"parent_value\":9,\"unit\":\"genes\",\"evidence\":\"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\",\"target_result\":\"The study constructed a nine-gene exosomal signature.\",\"number_stated\":true}", "reading": {"parent_value": 9, "unit": "genes", "evidence": "A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.", "target_result": "The study constructed a nine-gene exosomal signature.", "number_stated": true, "source_locator": "chars 99-183 of source sha256 313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065"}, "recorded_at": "2026-10-31T15:29:33.383199+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "b3fe3a2f2f4419f2f84cccc6a8561ef63d77760ac34a69805aaba2edff87972e", "source_hash": "313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065", "raw_response": "<think>We need answer JSON only. Need determine single numerical result replication of registered target main finding. Source headline says \"A nine-gene exosomal signature was constructed...\" Could headline number be nine genes, unit genes? Need exact contiguous quotation containing number. They ask value paper states for registered target, headline numerical result main finding. \"A nine-gene exosomal signature...\" Number stated in words nine, but parent_value number perhaps 9, evidence exact quote \"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\" Unit must unit paper prints. \"nine-gene\" is number spelled word, unit gene? Or maybe 9 genes stated in Target prediction: \"the 9 genes included in the risk model.\" The headline numerical result likely nine-gene signature. They say numerical result, exact quote. Could extract 9 and unit \"genes\". Evidence quote maybe \"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\" But requirement evidence exact contiguous quote contains the number. Does \"nine\" count? likely yes. Yet \"unit must be unit paper prints.\" \"nine-gene\" unit is gene perhaps. parent_value 9, unit \"genes\" or \"gene\"? Usually benchmark expected unit from source perhaps \"genes\". Need target_result explain main finding. number_stated true.\n\nBut perhaps there is no actual quantitative performance metric (AUC, HR, p-value); only count of nine-gene signature. They specifically registered target \"the headline numerical result the paper states for its main finding\", likely abstract headline is nine-gene signature. Need quote whole clause as attribution. \"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\" Exact contiguous.\n\nCould quote additionally \"the 9 genes included in the risk model\" to support numeric digit and unit. But single exact contiguous quotation can include both? They ask evidence exact quote contains number. We can quote \"A nine-gene...\" It contains number in words. parent_value numeric 9. Unit \"genes\". Is that unit printed? \"gene\" singular in compound adjective, while \"9 genes\" explicitly printed in another clause. Better evidence could be \"the 9 genes included in the risk model.\" This directly says 9 genes, but target registered main finding and attribution? It refers risk model. Yet perhaps whole sentence: \"In order to identify potential therapeutic options, the enrichR database was utilized to predict small molecule drugs that specifically target the 9 genes included in the risk model.\" This establishes risk model has 9 genes, exact digit and unit. But headline finding is a nine-gene exosomal signature. Could quote that sentence, and perhaps also another contiguous clause? Evidence should be exact contiguous quotation from source, not necessarily only one quote. Could quote two sentences separately? \"A nine-gene...\" and later \"...\" But likely simplest one quote.\n\nNeed target_result string perhaps \"The paper states that a nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\" Should not paraphrase? This field can explain. The instruction says report headline number only, but JSON schema demands target_result. We need concise.\n\nQuestion nuanced: \"find the single numerical result that a replication ... 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.\" There may be a trap: Source text has many numbers, but no performance result. Main headline says \"A nine-gene exosomal signature...\" Thus number 9. It is stated. Unit must paper prints. \"nine-gene\" perhaps unit \"gene\". They might expect \"9 genes\". Evidence exact quote could be \"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\" The number itself is written \"nine\", but exact quote. parent_value 9.\n\nCould parent_value need 9, unit \"genes\". JSON valid. Evidence no ellipsis. Let's ensure exact source punctuation. It is exactly. target_result perhaps \"The headline result is a nine-gene exosomal signature constructed using scRNA-seq and multi-omics data.\" This paraphrases slightly but okay field. number_stated true.\n\n\"unit must be the unit the paper prints.\" The paper prints \"nine-gene\" not \"genes\" in headline. But elsewhere \"9 genes\". Maybe unit should be \"genes\", as semantic unit. They might reject because printed unit \"gene\" in compound. Better quote exact phrase from source \"the 9 genes included in the risk model.\" This explicitly prints \"9 genes\", and is a contiguous exact quotation. But to connect main target, maybe quote full sentence: \"In order to identify potential therapeutic options, the enrichR database was utilized to predict small molecule drugs that specifically target the 9 genes included in the risk model.\" Does that state headline main finding? It confirms 9 genes in risk model. Yet the actual headline sentence is clearer. Could evidence include both exact contiguous quotations separated? Requirement \"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.\" Could quote a longer contiguous passage spanning huge sections? No need. One quote \"A nine-gene...\" contains number. Unit perhaps \"genes\" can be derived, but not calculated. In number extraction tasks, numerical words count. The number is attached to target by wording directly.\n\nMaybe expected no number because \"nine-gene\" is a count describing signature, not a result metric? Registered target says \"headline numerical result the paper states for its main finding\". The source title/abstract-like highlights. \"A nine-gene exosomal signature was constructed...\" clearly headline numerical result. They might define target deliberately broad to select this. There is also 78 immune genes, 32 cancer types, 9 genes. Main finding headline = nine-gene. So yes.\n\nNeed only JSON, no markdown. Let's formulate:\n{\n \"parent_value\": 9,\n \"unit\": \"genes\",\n \"evidence\": \"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\",\n \"target_result\": \"The paper states that a nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\",\n \"number_stated\": true\n}\nWould \"unit paper prints\" perhaps \"gene\" not \"genes\"? Usually unit field should be \"genes\" because 9 genes. Evidence exact. Another option evidence sentence with explicit 9 genes: \"In order to identify potential therapeutic options, the enrichR database was utilized to predict small molecule drugs that specifically target the 9 genes included in the risk model.\" Then unit exact \"genes\". But target_result says main finding. Is evidence attribution sufficient? It says \"risk model\", not \"exosomal signature\". Meanwhile headline quote directly names exosomal signature. The unit printed there is compound \"nine-gene\". Unit can still be \"genes.\" User says \"unit must be the unit the paper prints\", likely means don't transform %, etc. Maybe they expect \"genes\". Explicit occurrence helps.\n\nCould evidence be:\n\"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data. The risk score correlates strongly with prognosis in esophageal carcinoma patients.\"\nNo explicit 9 digit. Not needed.\n\nCould quote exact contiguous region from target prediction and mention risk model. But maybe \"registered target\" is the headline numerical result, and evidence should directly support target. Best quote is headline. If evaluator checks number substring perhaps \"nine\" recognized, likely.\n\n\"Report the headline number only\" means target_result maybe just \"9 genes\" perhaps not explanatory.</think>\n\n{\"parent_value\":9,\"unit\":\"genes\",\"evidence\":\"A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\",\"target_result\":\"The paper states that a nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.\",\"number_stated\":true}", "reading": {"parent_value": 9, "unit": "genes", "evidence": "A nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.", "target_result": "The paper states that a nine-gene exosomal signature was constructed using scRNA-seq and multi-omics data.", "number_stated": true, "source_locator": "chars 99-183 of source sha256 313192d582eb1d576797a59fa371aca21d8dec7ff6b0b084cb88e38bb0905065"}, "recorded_at": "2026-10-31T15:29:42.516788+00:00"}], "agreement": true, "disagreements": {"analysis_methods": {"minimax": ["Seurat single-cell RNA-seq analysis", "quality control filtering", "t-SNE dimensionality reduction", "marker-gene identification", "log₂(TPM + 1) normalization", "ComBat batch-effect correction", "Seurat SCTransform-based integration", "principal component analysis", "AUCell exosome gene scoring", "differential gene expression analysis", "intersection analysis", "Gene Ontology pathway enrichment analysis", "clusterProfiler", "enrichR target prediction", "Gene Set Variation Analysis (GSVA)", "pan-cancer analysis"], "minimax_alt": ["Single-cell RNA sequencing analysis with Seurat", "Quality-control filtering", "t-SNE dimensionality reduction", "Marker-gene identification", "log₂(TPM + 1) normalization", "ComBat batch-effect correction using sva (v3.36.0)", "Seurat SCTransform-based integration using FindIntegrationAnchors and IntegrateData", "Principal component analysis", "AUCell exosome gene scoring", "Differential gene expression analysis", "Intersection analysis of differential and known exosome-related genes", "Gene Ontology pathway enrichment analysis using clusterProfiler", "Mutation analysis using TCGAbiolinks and maftools", "enrichR small-molecule target prediction", "Gene Set Variation Analysis (GSVA)", "Immunotherapy-cohort analysis", "Pan-cancer analysis"], "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:8ca158d65fe01932bf2a1be3a643b016e803c579a6eeb450fea0627d79d0b0d0", "type": "sep_package", "label": "SEP v1 package for pmid:40816225"}], "activities": [{"id": "activity:conversion:pmid:40816225", "type": "conversion", "used": ["package:8ca158d65fe01932bf2a1be3a643b016e803c579a6eeb450fea0627d79d0b0d0"], "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": "97b028fa-732e-4aba-9fc5-8f1244089b36", "parent_hash": "8ca158d65fe01932bf2a1be3a643b016e803c579a6eeb450fea0627d79d0b0d0", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40816225 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:accession_absent", "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:40816225' does not resolve to a declared asset", "targets"]}