Development and Validation of the B Cell-Associated Fc Receptor-like Molecule-Based Prognostic Signature in Skin Cutaneous Melanoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32908921", "kind": "science-record", "revision": 8, "content_hash": "sha256:860c98f31806162b9f22aca74320c105a55a9e9658b01417f91436afc26874a2", "created_at": "2026-11-01T15:41:10Z", "updated_at": "2026-11-01T22:45:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and Validation of the B Cell-Associated Fc Receptor-like Molecule-Based Prognostic Signature in Skin Cutaneous Melanoma.", "doi": "10.1155/2020/8509805", "pmid": "32908921", "authors": ["Yu Liu", "Yiding Chen", "Xianyu Hu", "Jialin Meng", "Xiaojing Li"], "journal": "BioMed research international", "year": 2020, "abstract": "METHODS: 461 patients with CM from The Cancer Genome Atlast- (TCGA-) CM cohort and 290 pateints from the GSE65904 cohort were enrolled. Student's t-test was used to compare the differences, and Pearson's correlation coefficient was employed to evaluate associations. The Kaplan-Meier (K-M) survival analysis was used to evaluate overall survival (OS). The multivariate Cox regression was conducted to generate the FCRL prognostic signature. GSEA analysis and TIMER were employed to study the potential mechanisms.\nRESULT: Patients with Breslow's depth high or equal to 3 cm had the lower expression of FCRL1-6 (all, P < 0.05), which indicates poor OS, as well as age, stage, and Breslow's depth subgroups (all, P < 0.001). The overall FCRL1-6 prognostic signature was generated in the TCGA cohort (K-M, P < 0.001; area under the curve (AUC), 0.649 for 3-year OS) and validated in the GSE65904 cohort (K-M, P < 0.001; AUC, 0.659 for 3-year OS). The GSEA results revealed that high expression of FCRLs indicated activated immune-associated pathways, and FCRLs are positively associated with the infiltration of B cells.\nCONCLUSION: Highly expressed FCRLs were observed associated with a favourable OS of CM. FCRL1-6-based prediction signature could act as a biomarker to predict the prognosis of patients with CM.", "claims": [{"id": "claim-method", "statement": "Student's t-test was used to compare the differences between unpaired values, while the Pearson's product-moment correlation coefficient was employed to evaluate the association between CpG sites and mRNA expression of FCRLs. The Kaplan-Meier (K-M) survival analysis of patient subgroups with high and low levels of FCRLs and clinicopathological characteristics was also performed. To evaluate the overall prognostic value of FCRLs, we generated the FCRLs prognostic signature based on the results of the multivariate Cox regression with the TCGA-CM cohort, and each patient obtained a risk score from the signature. Next, the time-dependent receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC) for 1-year, 3-year, and 5-year OS and disease-free survival, and to determine the prediction accuracy of our model using the “survivalROC” package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32908921", "locator": "sections[4] \"2.2. Statistical Methods\" paragraph 2", "quote": "Student's t-test was used to compare the differences between unpaired values, while the Pearson's product-moment correlation coefficient was employed to evaluate the association between CpG sites and mRNA expression of FCRLs."}, {"asset": "source:pmid:32908921", "locator": "sections[4] \"2.2. Statistical Methods\" paragraph 2", "quote": "The Kaplan-Meier (K-M) survival analysis of patient subgroups with high and low levels of FCRLs and clinicopathological characteristics was also performed."}, {"asset": "source:pmid:32908921", "locator": "sections[5] \"2.3. Establishment and Validation of the Prognostic Signature\" paragraph 2", "quote": "To evaluate the overall prognostic value of FCRLs, we generated the FCRLs prognostic signature based on the results of the multivariate Cox regression with the TCGA-CM cohort, and each patient obtained a risk score from the signature."}, {"asset": "source:pmid:32908921", "locator": "sections[5] \"2.3. Establishment and Validation of the Prognostic Signature\" paragraph 2", "quote": "Next, the time-dependent receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC) for 1-year, 3-year, and 5-year OS and disease-free survival, and to determine the prediction accuracy of our model using the “survivalROC” package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are included within the article. The gene expression data can be accessed on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32908921", "locator": "sections[17] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are included within the article. The gene expression data can be accessed on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "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:32908921"], "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:GSE65904"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:student_t", "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:GSE65904"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:student_t"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32908921", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2020/8509805", "sha256": "sha256:8c4f2c475f9860107e201a90baf4381ea86d9f4a651edf13df4db9738272e979", "bytes": 29737, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2020/8509805", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7463385", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE65904", "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=GSE65904", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE65904", "version": null, "note": "The data used to support the findings of this study are included within the article. 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Next, the time-dependent receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC) for 1-year, 3-year, and 5-year OS and disease-free survival, and to determine the prediction accuracy of our model using the “survivalROC” package."}}, {"id": "method-2", "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"}}, {"id": "method-3", "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-4", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.7, "band": "medium", "quote": "Pearson's correlation"}}], "targets": [], "gaps": ["method.student_t"]}, "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": false, "required_operations": [], "missing_operations": ["student_t"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: student_t_test."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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