Computational construction of TME-related lncRNAs signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35808868", "kind": "science-record", "revision": 4, "content_hash": "sha256:884b12203ac771c7c18eef94ca7290c540cc406d741fe5f6d1e1d4be8886424c", "created_at": "2026-11-01T18:14:51Z", "updated_at": "2026-11-01T22:06:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Computational construction of TME-related lncRNAs signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.", "doi": "10.1002/jcla.24582", "pmid": "35808868", "authors": ["Libin Zhou", "Hualong Fang", "Fei Guo", "Min Yin", "Huimin Long", "Guobin Weng"], "journal": "Journal of clinical laboratory analysis", "year": 2022, "abstract": "BACKGROUND: The tumor microenvironment (TME) is closely related to clear cell renal cell carcinoma (ccRCC) prognosis, and immunotherapy response. In current study, comprehensive bio-informative analysis was adopted to construct a TME-related lncRNA signature for immune checkpoint inhibitors (ICIs) and targeted drug responses in ccRCC patients.\nMETHODS: The TME mRNAs were screened following the immune and stromal scores with the data from GSE15641, GSE29609, GSE36895, GSE46699, GSE53757, and The Cancer Genome Atlas (TCGA)-kidney renal clear cell carcinoma (KIRC). And the TME-related lncRNAs were recognized using correlation analysis. The TME-related lncRNAs prognostic model was constructed using the training dataset. Kaplan-Meier analysis, principal-component analysis, and time-dependent receiver operating characteristic were used to evaluate the risk model. The immune cell infiltration in TME was evaluated using the single-sample gene set enrichment analysis (ssGSEA), ESTIMATE, and microenvironment cell populations counter algorithm. The immunophenoscore (IPS) was used to assess the response to immunotherapy with the constructed model.\nRESULTS: In the current study, 364 TME-related lncRNAs were selected based on the integrated bioinformatical analysis. Six TME-related lncRNAs (LINC00460, LINC01094, AC008870.2, AC068792.1, and AC007637.1) were identified as the prognostic signature in the training dataset and subsequently verified in the testing and entire datasets. Patients in the high-risk group exhibited poor overall survival and disease-free survival than those in the low-risk group. The 1-, 3-, and 5-year areas under the curves of the prognostic signature in the entire dataset were 0.704, 0.683, and 0.750, respectively. The risk score independently predicted ccRCC survival based on univariate and multivariate Cox regression. GSEA analysis suggested that the high-risk group was concentrated on immune-related pathways. The high-risk group were characterized by high immune cell infiltration, high TMB and somatic mutation counters, high IPS-PD-1 + CTLA4 scores, and immune checkpoints expression upregulation, reflecting the higher ICIs response. The half inhibitory concentrations of sunitinib, temsirolimus, and rapamycin were low in the high-risk group.\nCONCLUSION: The TME-related lncRNAs signature constructed could reliably predict the prognosis and immunotherapy response and targeted ccRCC patients' therapy.", "claims": [{"id": "claim-method", "statement": "The prognostic TME‐related lncRNAs in the training data were detected by univariate Cox regression. The slightly contributory TME‐related lncRNAs were deleted by least absolute shrinkage and selection operator (LASSO) analysis. Finally, an optimal prognostic signature was developed using multivariate Cox regression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35808868", "locator": "sections[7] \"Risk model construction and verification for KIRC\" paragraph 2", "quote": "The prognostic TME‐related lncRNAs in the training data were detected by univariate Cox regression. The slightly contributory TME‐related lncRNAs were deleted by least absolute shrinkage and selection operator (LASSO) analysis. Finally, an optimal prognostic signature was developed using multivariate Cox regression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35808868", "locator": "sections[30] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "The data that support the findings of this study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The AUCs of 1, 3, and 5 years were 0.704, 0.683, and 0.750 in the testing dataset and 0.704, 0.683, and 0.750 in the entire dataset.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35808868", "locator": "sections[19] \"Validating the performance of the risk model\" paragraph 2", "quote": "The AUCs of 1, 3, and 5 years were 0.637, 0.724, and 0.736 in the testing dataset and 0.704, 0.683, and 0.750 in the entire dataset (Figure 3K,L)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The AUCs of 1, 3, and 5 years were 0.704, 0.683, and 0.750 in the testing dataset and 0.704, 0.683, and 0.750 in the entire dataset.", "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:35808868"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35808868", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/jcla.24582", "sha256": "sha256:5e9ee10ab8008c7773112d6a63ee99ff0b3545487a2b0dcb1b7135508cddcb0e", "bytes": 37957, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1002/jcla.24582", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9396193", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "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": 1.0, "band": "verbatim", "quote": "The prognostic TME‐related lncRNAs in the training data were detected by univariate Cox regression. The slightly contributory TME‐related lncRNAs were deleted by least absolute shrinkage and selection operator (LASSO) analysis. Finally, an optimal prognostic signature was developed using multivariate Cox regression."}}, {"id": "method-2", "family": "group_comparison", "specific": "student_t_test", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["student_t"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Student's t test"}}, {"id": "method-3", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-4", "family": "group_comparison", "specific": "anova", "label": "Group comparison", "dsl_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "ANOVA"}}, {"id": "method-5", "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": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["The data that support the findings of this study are available from the corresponding author upon reasonable request."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:35808868"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:54:57Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 11011, "completion_tokens": 3183, "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:35808868", "type": "paper", "label": "pmid:35808868"}, {"id": "source:pmid:35808868", "type": "manuscript", "label": "PMID 35808868 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35808868", "type": "paper", "label": "pmid:35808868"}, {"id": "source:pmid:35808868", "type": "manuscript", "label": "PMID 35808868 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35808868", "type": "extraction", "used": ["source:pmid:35808868"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "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:35808868", "parent_hash": "sha256:74a05ea1ecdf8de88df320f9d3f773d6724f63274aa8df8d828758d11e33f55a", "fork_of": null, "generation": 3}, "gaps": ["execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The prognostic TME‐related lncRNAs in the training data were detected by univariate Cox regression. The slightly contributory TME‐related lncRNAs were deleted by least absolute shrinkage and selection operator (LASSO) analysis. Finally, an optimal prognostic signature was developed using multivariate Cox regression."], "order_basis": "analysis_only", "id": "assay:1"}]}