Significance of liquid-liquid phase separation (LLPS)-related genes in breast cancer: a multi-omics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37338518", "kind": "science-record", "revision": 2, "content_hash": "sha256:9cac53f9b54a6c7e70f2164d0d7e7da481b86324fd655fdc31209df9adcdaff6", "created_at": "2026-11-01T19:02:04Z", "updated_at": "2026-11-01T21:31:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Significance of liquid-liquid phase separation (LLPS)-related genes in breast cancer: a multi-omics analysis.", "doi": "10.18632/aging.204812", "pmid": "37338518", "authors": ["Jiaheng Xie", "Liang Chen", "Dan Wu", "Shengxuan Liu", "Shengbin Pei", "Qikai Tang", "Yue Wang", "Mengmeng Ou", "Zhechen Zhu", "Shujie Ruan", "Ming Wang", "Jingping Shi"], "journal": "Aging", "year": 2023, "abstract": "Currently, the role of liquid-liquid phase separation (LLPS) in cancer has been preliminarily explained. However, the significance of LLPS in breast cancer is unclear. In this study, single cell sequencing datasets GSE188600 and GSE198745 for breast cancer were downloaded from the GEO database. Transcriptome sequencing data for breast cancer were downloaded from UCSC database. We divided breast cancer cells into high-LLPS group and low-LLPS group by down dimension clustering analysis of single-cell sequencing data set, and obtained differentially expressed genes between the two groups. Subsequently, weighted co-expression network analysis (WGCNA) was performed on transcriptome sequencing data, and the module genes most associated with LLPS were obtained. COX regression and Lasso regression were performed and the prognostic model was constructed. Subsequently, survival analysis, principal component analysis, clinical correlation analysis, and nomogram construction were used to evaluate the significance of the prognostic model. Finally, cell experiments were used to verify the function of the model's key gene, PGAM1. We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1. By calculating LLPS-related risk scores, breast cancer patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly worse prognosis. Cell experiments showed that the activity, proliferation, invasion and healing ability of breast cancer cell lines were significantly decreased after knockdown of the key gene PGAM1 in the model. Our study provides a new idea for prognostic stratification of breast cancer and provides a novel marker: PGAM1.", "claims": [{"id": "claim-method", "statement": "Subsequently, univariate COX analysis was performed on the genes mentioned above, and the prognostic genes were preliminarily obtained by setting the domain value p <0.05. Then, further analysis of the Least Absolute Shrinkage and Selection Operator (LASSO) was conducted, with the random seed set as 55555.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37338518", "locator": "sections[8] \"Construction of the prognostic model\" paragraph 2", "quote": "Subsequently, univariate COX analysis was performed on the genes mentioned above, and the prognostic genes were preliminarily obtained by setting the domain value p <0.05. Then, further analysis of the Least Absolute Shrinkage and Selection Operator (LASSO) was conducted, with the random seed set as 55555."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37338518", "locator": "sections[13] \"Data availability statement\" paragraph 2", "quote": "The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37338518", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1.", "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:37338518"], "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:GSE188600"], "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:GSE188600"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37338518", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.204812", "sha256": "sha256:4068e61e07d894cc18c497fcb960720d1647302c22508fe5430db50de07ab9fd", "bytes": 35819, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.18632/aging.204812", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10333080", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE188600", "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=GSE188600", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE188600", "version": null, "note": "The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745].", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM5686673"], "sample_count": 1, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "Single Cell RNA Profiles of a Human Triple Negative Breast Cancer", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE198745", "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=GSE198745", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE198745", "version": null, "note": "The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745].", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM5956093", "GSM5956094", "GSM5956095"], "sample_count": 3, "group_sizes": null, "group_sizes_basis": null, "platform": "24676", "taxon": "Homo sapiens", "title": "Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE188600 not downloaded", "asset:data:geo:GSE188600 licence not read", "asset:data:geo:GSE198745 not downloaded", "asset:data:geo:GSE198745 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": "KM"}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "COX regression"}}, {"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": null, "specific": null, "label": "univariate COX analysis followed by Least Absolute Shrinkage and Selection Operator (LASSO) regression", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Subsequently, univariate COX analysis was performed on the genes mentioned above, and the prognostic genes were preliminarily obtained by setting the domain value p <0.05. Then, further analysis of the Least Absolute Shrinkage and Selection Operator (LASSO) was conducted, with the random seed set as 55555."}}], "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": ["GSE188600", "GSE198745"], "resolved_accessions": ["GSE188600", "GSE198745"], "statements": ["The datasets generated and analysed during the current study are available in the TCGA [https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga] and GEO repository, [GSE188600 and GSE198745]."], "basis": "The paper names GSE188600, GSE198745 in 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:37338518", "data:geo:GSE188600"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE188600"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:44:19Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10031, "completion_tokens": 2769, "cached_tokens": 264}}, "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:37338518", "type": "paper", "label": "pmid:37338518"}, {"id": "source:pmid:37338518", "type": "manuscript", "label": "PMID 37338518 full text"}, {"id": "data:geo:GSE188600", "type": "dataset", "label": "GEO GSE188600"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37338518", "type": "paper", "label": "pmid:37338518"}, {"id": "source:pmid:37338518", "type": "manuscript", "label": "PMID 37338518 full text"}, {"id": "data:geo:GSE188600", "type": "dataset", "label": "GEO GSE188600"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37338518", "type": "extraction", "used": ["source:pmid:37338518"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE188600", "type": "accession_resolution", "used": ["data:geo:GSE188600"], "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:37338518", "parent_hash": "sha256:ce4601f5bff28b7305ab0e4ea070adf4935a7b2bd0d9c4b3b30f1a92f226b090", "fork_of": null, "generation": 1}, "gaps": ["asset:data:geo:GSE188600 licence not read", "asset:data:geo:GSE188600 not downloaded", "asset:data:geo:GSE198745 licence not read", "asset:data:geo:GSE198745 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.83, "evidence": ["ancer were downloaded from the GEO database. Transcriptome sequencing data for breast cancer were downl", "on network analysis (WGCNA) was performed on transcriptome sequencing data, and the module genes most a"], "order_basis": "paper_text_order:361", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["ell lines were significantly decreased after knockdown of the key gene PGAM1 in the model. Our stud"], "order_basis": "paper_text_order:1668", "id": "assay:2"}, {"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": ["KM"], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}