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pmid:35464857

Exploration of Reduced Mitochondrial Content-Associated Gene Signature and Immunocyte Infiltration in Colon Adenocarcinoma by an Integrated Bioinformatic Analysis.

Jinlin Kang · Na Li · Fen Wang · Yan Wei · Yangyang Zeng · Qifan Luo · Xuehua Sun · Hui Xu · Jin Peng · Fuxiang Zhou

Frontiers in genetics · 2022 doi:10.3389/fgene.2022.832331

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Experiment

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Data

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pmid:35464857
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title
Exploration of Reduced Mitochondrial Content-Associated Gene Signature and Immunocyte Infiltration in Colon Adenocarcinoma by an Integrated Bioinformatic Analysis.
doi
10.3389/fgene.2022.832331
pmid
35464857
authors array · 10 items
[0]
Jinlin Kang
[1]
Na Li
[2]
Fen Wang
[3]
Yan Wei
[4]
Yangyang Zeng
[5]
Qifan Luo
[6]
Xuehua Sun
[7]
Hui Xu
[8]
Jin Peng
[9]
Fuxiang Zhou
journal
Frontiers in genetics
year
2022
abstract
Purpose: Mitochondrial dysfunction refers to cancer immune evasion. A novel 7-gene prognostic signature related to the mitochondrial DNA copy number was utilized to evaluate the immunocyte infiltration in colon cancer according to the risk scores and to predict the survival for colon cancer. Experimental design: We performed an integrated bioinformatic analysis to analyze transcriptome profiling of the EB-treated mitochondrial DNA-defected NCM460 cell line with differentially expressed genes between tumor and normal tissues of COAD in TCGA. The LASSO analysis was utilized to establish a prognostic signature. ESTIMATE and CIBERSORT validated the differences of immunocyte infiltration between colon cancer patients with high- and low-risk scores. Results: Our study identified a 7-gene prognostic signature (LRRN2, ANKLE1, GPRASP1, PRAME, TCF7L1, RAB6B, and CALB2). Patients with colon cancer were split into the high- and low-risk group by the risk scores in TCGA (training cohort: HR = 2.50 p < 0.0001) and GSE39582 (validation cohort: HR = 1.43 p < 0.05). ESTIMATE and CIBERSORT revealed diverseness of immune infiltration in the two groups, especially downregulated T-cell infiltration in the patients with high-risk scores. Finally, we validated the colon patients with a low expression of the mitochondrial number biomarker TFAM had less CD3+ and CD8+ T-cell infiltration in clinical specimens. Conclusion: An mtDNA copy number-related 7-gene prognostic signature was investigated and evaluated, which may help to predict the prognosis of colon cancer patients and to guide clinical immunotherapy via immunocyte infiltration evaluation.
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The Kaplan–Meier survival analysis was performed to assess the correlation between the patient survival probability and different groups, which were characterized by the risk score related to the 7-gene feature expression in TCGA calculated by LASSO.
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sections[10] "Survival Analysis" paragraph 2
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The Kaplan–Meier survival analysis was performed to assess the correlation between the patient survival probability and different groups, which were characterized by the risk score related to the 7-gene feature expression in TCGA calculated by LASSO.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
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sections[22] "Data Availability Statement" paragraph 2
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
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sample_count
585
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]
resolution_checked_at
2026-11-01T15:39:54Z
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The Kaplan–Meier survival analysis was performed to assess the correlation between the patient survival probability and different groups, which were characterized by the risk score related to the 7-gene feature expression in TCGA calculated by LASSO.
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
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tier
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true
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[0]
GSE39582
statements array · 1 item
[0]
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
basis
The paper names GSE39582 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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partial
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minimax
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minimax
read_at
2026-11-01T17:43:28Z
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GEO GSE39582
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classification
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pmid:35464857
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manuscript
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PMID 35464857 full text
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dataset
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GEO GSE39582
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agent:corpus-assay-engine
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activity-read-35464857
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extraction
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agent:minimax-reader
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activity-resolve-GSE39582
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[0]
integrated bioinformatic analysis to analyze transcriptome profiling of the EB-treated mitochondrial DN
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35464857", "kind": "science-record", "revision": 4, "content_hash": "sha256:d5079b98d10b9c7a0578a5158e6527a63e448acf644c43d74cbfd896346fcaf5", "created_at": "2026-11-01T18:14:20Z", "updated_at": "2026-11-01T22:06:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of Reduced Mitochondrial Content-Associated Gene Signature and Immunocyte Infiltration in Colon Adenocarcinoma by an Integrated Bioinformatic Analysis.", "doi": "10.3389/fgene.2022.832331", "pmid": "35464857", "authors": ["Jinlin Kang", "Na Li", "Fen Wang", "Yan Wei", "Yangyang Zeng", "Qifan Luo", "Xuehua Sun", "Hui Xu", "Jin Peng", "Fuxiang Zhou"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Purpose: Mitochondrial dysfunction refers to cancer immune evasion. A novel 7-gene prognostic signature related to the mitochondrial DNA copy number was utilized to evaluate the immunocyte infiltration in colon cancer according to the risk scores and to predict the survival for colon cancer. Experimental design: We performed an integrated bioinformatic analysis to analyze transcriptome profiling of the EB-treated mitochondrial DNA-defected NCM460 cell line with differentially expressed genes between tumor and normal tissues of COAD in TCGA. The LASSO analysis was utilized to establish a prognostic signature. ESTIMATE and CIBERSORT validated the differences of immunocyte infiltration between colon cancer patients with high- and low-risk scores. Results: Our study identified a 7-gene prognostic signature (LRRN2, ANKLE1, GPRASP1, PRAME, TCF7L1, RAB6B, and CALB2). Patients with colon cancer were split into the high- and low-risk group by the risk scores in TCGA (training cohort: HR = 2.50 p < 0.0001) and GSE39582 (validation cohort: HR = 1.43 p < 0.05). ESTIMATE and CIBERSORT revealed diverseness of immune infiltration in the two groups, especially downregulated T-cell infiltration in the patients with high-risk scores. Finally, we validated the colon patients with a low expression of the mitochondrial number biomarker TFAM had less CD3+ and CD8+ T-cell infiltration in clinical specimens. Conclusion: An mtDNA copy number-related 7-gene prognostic signature was investigated and evaluated, which may help to predict the prognosis of colon cancer patients and to guide clinical immunotherapy via immunocyte infiltration evaluation.", "claims": [{"id": "claim-method", "statement": "The Kaplan–Meier survival analysis was performed to assess the correlation between the patient survival probability and different groups, which were characterized by the risk score related to the 7-gene feature expression in TCGA calculated by LASSO.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35464857", "locator": "sections[10] \"Survival Analysis\" paragraph 2", "quote": "The Kaplan–Meier survival analysis was performed to assess the correlation between the patient survival probability and different groups, which were characterized by the risk score related to the 7-gene feature expression in TCGA calculated by LASSO."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35464857", "locator": "sections[22] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE39582"], "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:GSE39582"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35464857", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.832331", "sha256": "sha256:3f662e83532696200c483da40c1aaa4023a5ba9827a4b248d40f4f320665846a", "bytes": 34415, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2022.832331", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9024084", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE39582", "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=GSE39582", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE39582", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE39582 not downloaded", "asset:data:geo:GSE39582 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "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-2", "family": null, "specific": null, "label": "Kaplan–Meier survival analysis", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The Kaplan–Meier survival analysis was performed to assess the correlation between the patient survival probability and different groups, which were characterized by the risk score related to the 7-gene feature expression in TCGA calculated by LASSO."}}], "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": 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE39582"], "resolved_accessions": ["GSE39582"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."], "basis": "The paper names GSE39582 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:35464857", "data:geo:GSE39582"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE39582"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:43:28Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10320, "completion_tokens": 1168, "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:35464857", "type": "paper", "label": "pmid:35464857"}, {"id": "source:pmid:35464857", "type": "manuscript", "label": "PMID 35464857 full text"}, {"id": "data:geo:GSE39582", "type": "dataset", "label": "GEO GSE39582"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35464857", "type": "paper", "label": "pmid:35464857"}, {"id": "source:pmid:35464857", "type": "manuscript", "label": "PMID 35464857 full text"}, {"id": "data:geo:GSE39582", "type": "dataset", "label": "GEO GSE39582"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35464857", "type": "extraction", "used": ["source:pmid:35464857"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE39582", "type": "accession_resolution", "used": ["data:geo:GSE39582"], "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:35464857", "parent_hash": "sha256:d0921ffc8711131eec945178ebc8db97a13ee5db0ad5c78e3789e78596266bc3", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE39582 licence not read", "asset:data:geo:GSE39582 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": 0.69, "evidence": ["integrated bioinformatic analysis to analyze transcriptome profiling of the EB-treated mitochondrial DN"], "order_basis": "paper_text_order:494", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["limma"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}