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pmid:35912224
Necroptosis-Related Genes Signatures Identified Molecular Subtypes and Underlying Mechanisms in Hepatocellular Carcinoma.
Jianguo Wei · Shuqian Hou · Minhua Li · Xiaofei Yao · Li Wang · Zhen Zheng · Haiqian Mo · Yu Chen · Xiaolu Yuan
Frontiers in oncology · 2022 doi:10.3389/fonc.2022.875264
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Experiment
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Complete file
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Next, we used an unsupervised clustering method to assign the samples into phenotype clusters base on 15 necroptosis-related genes. Subsequently, we constructed a NEC score based on NEC phenotype-related prognostic genes to quantify the necroptosis related subtypes of individual patients.\nResults: We divided the samples into the high and low NEC score groups, and the high NEC score showed a poor prognosis. Simultaneously, NEC score is an effective and stable model and had a good performance in predicting the prognosis of HCC patients. A high NEC score was characterized by activation of the stroma and increased levels of immune infiltration. A high NEC score was also related to low expression of immune checkpoint molecules (PD-1/PD-L1). Importantly, the established NEC score would contribute to predicting the response to anti-PD-1/L1 immunotherapy.\nConclusions: Our study provide a comprehensive analysis of necroptosis-related genes in HCC. Stratification based on the NEC score may enable HCC patients to benefit more from immunotherapy and help identify new cancer treatment strategies.", "claims": [{"id": "claim-method", "statement": "The genes with the cut-off criteria of |log FC|≥ 1.0 and adj. P <0.05 were used as DEGs by using limma package (25). Using univariate Cox regression analysis to analyze the correlation between clinical information and necroptosis-related genes expression. Finally, 15 different and prognostic necroptosis related genes were identified.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35912224", "locator": "sections[4] \"Identification of Differential Expression and Prognostic of Necroptosis-Related Genes\" paragraph 2", "quote": "The genes with the cut-off criteria of |log FC|≥ 1.0 and adj. P <0.05 were used as DEGs by using limma package (25). Using univariate Cox regression analysis to analyze the correlation between clinical information and necroptosis-related genes expression. Finally, 15 different and prognostic necroptosis related genes were identified."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35912224", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The NEC score predicted the prognosis of HCC patients in the meta cohort with an ROC AUC of 0.754.", "kind": "quantitative", "target": {"value": 0.001, "unit": "p-value", "tolerance": null, "source": "In addition, patients with high NEC score had a significantly shorter OS than those with low NEC score (P< 0.001; Figure 5C ), and AUC of the ROC was 0.754 ( Figure 5D )."}, "evidence": [{"asset": "source:pmid:35912224", "locator": "sections[17] \"Construction of NEC Score\" paragraph 2", "quote": "In addition, patients with high NEC score had a significantly shorter OS than those with low NEC score (P< 0.001; Figure 5C ), and AUC of the ROC was 0.754 ( Figure 5D )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The NEC score predicted the prognosis of HCC patients in the meta cohort with an ROC AUC of 0.754.", "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:35912224"], "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:GSE140901"], "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:GSE140901"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35912224", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.875264", "sha256": "sha256:5ce708349cc4bf18ad29fc28f2203d1cf7a48b2e01d11ea094560e918a28e9a9", "bytes": 58734, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2022.875264", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9326098", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE140901", "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=GSE140901", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE140901", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . 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P <0.05 were used as DEGs by using limma package (25). Using univariate Cox regression analysis to analyze the correlation between clinical information and necroptosis-related genes expression. Finally, 15 different and prognostic necroptosis related genes were identified."}}, {"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 t-test"}}, {"id": "method-3", "family": "group_comparison", "specific": "mann_whitney", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_mann_whitney"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Mann-Whitney"}}, {"id": "method-4", "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-5", "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-6", "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"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 0.001, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold."}], "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": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "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. 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