IGF2BP2-related modification patterns in pancreatic cancer: A machine learning-driven approach towards personalized treatment.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38545193", "kind": "science-record", "revision": 3, "content_hash": "sha256:bf0091bd68d77cce6c1b872bb51a10af5a180f8e2865fccaf9f41303e39a87eb", "created_at": "2026-11-01T19:20:29Z", "updated_at": "2026-11-01T22:11:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "IGF2BP2-related modification patterns in pancreatic cancer: A machine learning-driven approach towards personalized treatment.", "doi": "10.1016/j.heliyon.2024.e28243", "pmid": "38545193", "authors": ["Dongjie Chen", "Longjun Zang", "Yanling Zhou", "Yongchao Yang", "Xianlin Zhang", "Zheng Li", "Yufeng Shu", "Wenzhe Gao", "Hongwei Zhu", "Xiao Yu"], "journal": "Heliyon", "year": 2024, "abstract": "Pancreatic cancer (PC) is a malignant digestive system tumor with a very poor prognosis. N6-methyladenosine (m6A) is mediated by a variety of readers and participates in important regulatory roles in PC. Based on TCGA_PAAD, ICGC_AU_PAAD, ICGC_CA_PAAD, GSE28735 and GSE62452 datasets, We mapped the multi-omics changes of m6A readers in PC and found that m6A readers, especially IGF2BP family genes, had specific changes and were significantly associated with poor prognosis. An unsupervised consensus clustering algorithm was used to explore the correlation between specific expression patterns of m6A readers in PC and enrichment pathways, tumor immunity and clinical molecular subtypes. Then, the principal component analysis (PCA) algorithm was used to quantify specific expression patterns and screen core genes. Machine learning algorithms such as Bootstrapping and RSF were used to quantify the expression patterns of core genes and construct a prognostic scoring model for PC patients. What's more, pharmacogenomic databases were used to screen sensitive drug targets and small molecule compounds for high-risk PC patients in an all-around and multi-angle way. Our study has not only provided new insights into personalized prognostication approaches, but also thrown light on integrating tailored risk stratification with precision therapy based on IGF2BP2-mediated m6A modification patterns.", "claims": [{"id": "claim-method", "statement": "Then, RSF analysis based on the minimum depth (MD-RSF) method was used to determine the final prognostic gene markers.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38545193", "locator": "sections[18] \"Development of poor prognostic signatures based on IGF2BP2-mediated modification patterns via machine learning algorithms\" paragraph 2", "quote": "Then, RSF analysis based on the minimum depth (MD-RSF) method was used to determine the final prognostic gene markers."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38545193", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 13 gene sets (FNDC3B, L1CAM, PLXNA1, HMGA2, FAM110B, FAM83A, COX7A1, PMAIP1, KIF20B, SPDL1, SNCG, TGM2 and MUC16) included when C_index reached the maximum (0.7128982) were selected as poor prognostic signatures, defined as PPS associated with IGF2BP2 phenotype.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38545193", "locator": "sections[18] \"Development of poor prognostic signatures based on IGF2BP2-mediated modification patterns via machine learning algorithms\" paragraph 2", "quote": "The 13 gene sets (FNDC3B, L1CAM, PLXNA1, HMGA2, FAM110B, FAM83A, COX7A1, PMAIP1, KIF20B, SPDL1, SNCG, TGM2 and MUC16) included when C_index reached the maximum (0.7128982) were selected as poor prognostic signatures, defined as PPS associated with IGF2BP2 phenotype."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 13 gene sets (FNDC3B, L1CAM, PLXNA1, HMGA2, FAM110B, FAM83A, COX7A1, PMAIP1, KIF20B, SPDL1, SNCG, TGM2 and MUC16) included when C_index reached the maximum (0.7128982) were selected as poor prognostic signatures, defined as PPS associated with IGF2BP2 phenotype.", "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:38545193"], "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:GSE28735"], "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:GSE28735"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38545193", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2024.e28243", "sha256": "sha256:68a85d14caf1efd1914916f0ec01e21613bad3a6c0df3959591df7464ddd5748", "bytes": 78856, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.heliyon.2024.e28243", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10965819", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE28735", "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=GSE28735", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE28735", "version": null, "note": "All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM711904", "GSM711905", "GSM711906", "GSM711907", "GSM711908", "GSM711909", "GSM711910", "GSM711911", "GSM711912", "GSM711913", "GSM711914", "GSM711915", "GSM711916", "GSM711917", "GSM711918", "GSM711919", "GSM711920", "GSM711921", "GSM711922", "GSM711923", "GSM711924", "GSM711925", "GSM711926", "GSM711927", "GSM711928", "GSM711929", "GSM711930", "GSM711931", "GSM711932", "GSM711933", "GSM711934", "GSM711935", "GSM711936", "GSM711937", "GSM711938", "GSM711939", "GSM711940", "GSM711941", "GSM711942", "GSM711943", "GSM711944", "GSM711945", "GSM711946", "GSM711947", "GSM711948", "GSM711949", "GSM711950", "GSM711951", "GSM711952", "GSM711953", "GSM711954", "GSM711955", "GSM711956", "GSM711957", "GSM711958", "GSM711959", "GSM711960", "GSM711961", "GSM711962", "GSM711963", "GSM711964", "GSM711965", "GSM711966", "GSM711967", "GSM711968", "GSM711969", "GSM711970", "GSM711971", "GSM711972", "GSM711973", "GSM711974", "GSM711975", "GSM711976", "GSM711977", "GSM711978", "GSM711979", "GSM711980", "GSM711981", "GSM711982", "GSM711983", "GSM711984", "GSM711985", "GSM711986", "GSM711987", "GSM711988", "GSM711989", "GSM711990", "GSM711991", "GSM711992", "GSM711993"], "sample_count": 90, "group_sizes": null, "group_sizes_basis": null, "platform": "6244", "taxon": "Homo sapiens", "title": "Microarray gene-expression profiles of 45 matching pairs of pancreatic tumor and adjacent non-tumor tissues from 45 patients with pancreatic ductal adenocarcinoma", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"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": "All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1527105", "GSM1527106", "GSM1527107", "GSM1527108", "GSM1527109", "GSM1527110", "GSM1527111", "GSM1527112", "GSM1527113", "GSM1527114", "GSM1527115", "GSM1527116", "GSM1527117", "GSM1527118", "GSM1527119", "GSM1527120", "GSM1527121", "GSM1527122", "GSM1527123", "GSM1527124", "GSM1527125", "GSM1527126", "GSM1527127", "GSM1527128", "GSM1527129", "GSM1527130", "GSM1527131", "GSM1527132", "GSM1527133", "GSM1527134", "GSM1527135", "GSM1527136", "GSM1527137", "GSM1527138", "GSM1527139", "GSM1527140", "GSM1527141", "GSM1527142", "GSM1527143", "GSM1527144", "GSM1527145", "GSM1527146", "GSM1527147", "GSM1527148", "GSM1527149", "GSM1527150", "GSM1527151", "GSM1527152", "GSM1527153", "GSM1527154", "GSM1527155", "GSM1527156", "GSM1527157", "GSM1527158", "GSM1527159", "GSM1527160", "GSM1527161", "GSM1527162", "GSM1527163", "GSM1527164", "GSM1527165", "GSM1527166", "GSM1527167", "GSM1527168", "GSM1527169", "GSM1527170", "GSM1527171", "GSM1527172", "GSM1527173", "GSM1527174", "GSM1527175", "GSM1527176", "GSM1527177", "GSM1527178", "GSM1527179", "GSM1527180", "GSM1527181", "GSM1527182", "GSM1527183", "GSM1527184", "GSM1527185", "GSM1527186", "GSM1527187", "GSM1527188", "GSM1527189", "GSM1527190", "GSM1527191", "GSM1527192", "GSM1527193", "GSM1527194", "GSM1527195", "GSM1527196", "GSM1527197", "GSM1527198", "GSM1527199", "GSM1527200", "GSM1527201", "GSM1527202", "GSM1527203", "GSM1527204", "GSM1527205", "GSM1527206", "GSM1527207", "GSM1527208", "GSM1527209", "GSM1527210", "GSM1527211", "GSM1527212", "GSM1527213", "GSM1527214", "GSM1527215", "GSM1527216", "GSM1527217", "GSM1527218", "GSM1527219", "GSM1527220", "GSM1527221", "GSM1527222", "GSM1527223", "GSM1527224", "GSM1527225", "GSM1527226", "GSM1527227", "GSM1527228", "GSM1527229", "GSM1527230", "GSM1527231", "GSM1527232", "GSM1527233", "GSM1527234"], "sample_count": 130, "group_sizes": null, "group_sizes_basis": null, "platform": "6244", "taxon": "Homo sapiens", "title": "Microarray gene-expression profiles of 69 pancreatic tumors and 61 adjacent non-tumor tissue from patients with pancreatic ductal adenocarcinoma", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE28735 not downloaded", "asset:data:geo:GSE28735 licence not read", "asset:data:geo:GSE62452 not downloaded", "asset:data:geo:GSE62452 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-3", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "principal component analysis"}}, {"id": "method-4", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.8, "band": "high", "quote": "limma"}}, {"id": "method-5", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "random forest"}}, {"id": "method-6", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "Chi-square"}}, {"id": "method-7", "family": null, "specific": null, "label": "Random survival forest analysis based on the minimum depth (MD-RSF) method", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Then, RSF analysis based on the minimum depth (MD-RSF) method was used to determine the final prognostic gene markers."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE62452", "GSE28735"], "resolved_accessions": ["GSE62452", "GSE28735"], "statements": ["All data used in this study are publicly available. The materials that support the conclusion of this article have been included within the Materials and Methods section “Data acquisition and preprocessing”."], "basis": "The paper names GSE62452, GSE28735 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:38545193", "data:geo:GSE28735"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE28735"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:13:47Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 20813, "completion_tokens": 3967, "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:38545193", "type": "paper", "label": "pmid:38545193"}, {"id": "source:pmid:38545193", "type": "manuscript", "label": "PMID 38545193 full text"}, {"id": "data:geo:GSE28735", "type": "dataset", "label": "GEO GSE28735"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38545193", "type": "paper", "label": "pmid:38545193"}, {"id": "source:pmid:38545193", "type": "manuscript", "label": "PMID 38545193 full text"}, {"id": "data:geo:GSE28735", "type": "dataset", "label": "GEO GSE28735"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38545193", "type": "extraction", "used": ["source:pmid:38545193"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE28735", "type": "accession_resolution", "used": ["data:geo:GSE28735"], "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:38545193", "parent_hash": "sha256:0fd952f18cb3d5bacce6f44fc77983ad91a7f2e80be3135cecc49451e1705ec0", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE28735 licence not read", "asset:data:geo:GSE28735 not downloaded", "asset:data:geo:GSE62452 licence not read", "asset:data:geo:GSE62452 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Kaplan-Meier"], "order_basis": "analysis_only", "id": "assay:1"}]}