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pmid:35047006

Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma.

Shenghua Pan · Tingting Tang · Yanke Wu · Liang Zhang · Zekai Song · Sisi Yu

Frontiers in genetics · 2021 doi:10.3389/fgene.2021.778153

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Experiment

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Data

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2026-11-01T17:36:46Z
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paper object · 10 fields
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title
Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma.
doi
10.3389/fgene.2021.778153
pmid
35047006
authors array · 6 items
[0]
Shenghua Pan
[1]
Tingting Tang
[2]
Yanke Wu
[3]
Liang Zhang
[4]
Zekai Song
[5]
Sisi Yu
journal
Frontiers in genetics
year
2021
abstract
The tumor microenvironment (TME) has been shown to be involved in angiogenesis, tumor metastasis, and immune response, thereby affecting the treatment and prognosis of patients. This study aims to identify genes that are dysregulated in the TME of patients with colon adenocarcinoma (COAD) and to evaluate their prognostic value based on RNA omics data. We obtained 512 COAD samples from the Cancer Genome Atlas (TCGA) database and 579 COAD patients from the independent dataset (GSE39582) in the Gene Expression Omnibus (GEO) database. The immune/stromal/ESTIMATE score of each patient based on their gene expression was calculated using the ESTIMATE algorithm. Kaplan-Meier survival analysis, Cox regression analysis, gene functional enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. We found that immune and stromal scores were significantly correlated with COAD patients' overall survival (log rank p < 0.05). By comparing the high immune/stromal score group with the low score group, we identified 688 intersection differentially expressed genes (DEGs) from the TCGA dataset (663 upregulated and 25 downregulated). The functional enrichment analysis of intersection DEGs showed that they were mainly enriched in the immune process, cell migration, cell motility, Toll-like receptor signaling pathway, and PI3K-Akt signaling pathway. The hub genes were revealed by PPI network analysis. Through Kaplan-Meier and Cox analysis, four TME-related genes that were significantly related to the prognosis of COAD patients were verified in GSE39582. In addition, we uncovered the relationship between the four prognostic genes and immune cells in COAD. In conclusion, based on the RNA expression profiles of 1091 COAD patients, we screened four genes that can predict prognosis from the TME, which may serve as candidate prognostic biomarkers for COAD.
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KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets.
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methodological
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sections[4] "Calculating Immune/Stromal Scores and Survival Analysis" paragraph 2
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KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets.
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Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz.
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sections[13] "Data Availability Statement" paragraph 2
quote
Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz.
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The study found that immune and stromal scores calculated from COAD RNA-expression data were significantly correlated with overall survival.
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We found that immune and stromal scores were significantly correlated with COAD patients’ overall survival (log rank p < 0.05).
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sections[0] "Abstract" paragraph 1
quote
We found that immune and stromal scores were significantly correlated with COAD patients’ overall survival (log rank p < 0.05).
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complete
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The study found that immune and stromal scores calculated from COAD RNA-expression data were significantly correlated with overall survival.
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https://doi.org/10.3389/fgene.2021.778153
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Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz.
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Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz.
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585
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570
taxon
Homo sapiens
title
Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]
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2026-11-01T15:39:54Z
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KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets.
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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.
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Automated Assays Laravel application and simulated adapters
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
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tier
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availability_state
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz.
basis
The paper names GSE39582 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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minimax
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KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35047006", "kind": "science-record", "revision": 5, "content_hash": "sha256:b6584235d6d45537d9c418d8d5df9f947c8a5367dd43fee5cb7d7e28d2bb3b4b", "created_at": "2026-11-01T17:36:46Z", "updated_at": "2026-11-01T22:48:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma.", "doi": "10.3389/fgene.2021.778153", "pmid": "35047006", "authors": ["Shenghua Pan", "Tingting Tang", "Yanke Wu", "Liang Zhang", "Zekai Song", "Sisi Yu"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "The tumor microenvironment (TME) has been shown to be involved in angiogenesis, tumor metastasis, and immune response, thereby affecting the treatment and prognosis of patients. This study aims to identify genes that are dysregulated in the TME of patients with colon adenocarcinoma (COAD) and to evaluate their prognostic value based on RNA omics data. We obtained 512 COAD samples from the Cancer Genome Atlas (TCGA) database and 579 COAD patients from the independent dataset (GSE39582) in the Gene Expression Omnibus (GEO) database. The immune/stromal/ESTIMATE score of each patient based on their gene expression was calculated using the ESTIMATE algorithm. Kaplan-Meier survival analysis, Cox regression analysis, gene functional enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. We found that immune and stromal scores were significantly correlated with COAD patients' overall survival (log rank p < 0.05). By comparing the high immune/stromal score group with the low score group, we identified 688 intersection differentially expressed genes (DEGs) from the TCGA dataset (663 upregulated and 25 downregulated). The functional enrichment analysis of intersection DEGs showed that they were mainly enriched in the immune process, cell migration, cell motility, Toll-like receptor signaling pathway, and PI3K-Akt signaling pathway. The hub genes were revealed by PPI network analysis. Through Kaplan-Meier and Cox analysis, four TME-related genes that were significantly related to the prognosis of COAD patients were verified in GSE39582. In addition, we uncovered the relationship between the four prognostic genes and immune cells in COAD. In conclusion, based on the RNA expression profiles of 1091 COAD patients, we screened four genes that can predict prognosis from the TME, which may serve as candidate prognostic biomarkers for COAD.", "claims": [{"id": "claim-method", "statement": "KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35047006", "locator": "sections[4] \"Calculating Immune/Stromal Scores and Survival Analysis\" paragraph 2", "quote": "KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35047006", "locator": "sections[13] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. The data can be found here. 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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", "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": "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": "KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets."}}, {"id": "method-2", "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-3", "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-4", "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": 0.7, "band": "medium", "quote": "log rank"}}, {"id": "method-5", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "bootstrap_mean_difference", "expected_value": 0.05, "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. 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": ["Publicly available datasets were analyzed in this study. The data can be found here. Publicly available datasets can be found here: https://gdc-hub.s3.us-east-1.amazonaws.com/download/TCGA-COAD.htseq_fpkm-uq.tsv.gz; https://ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39582/matrix/GSE39582_series_matrix.txt.gz."], "basis": "The paper names GSE39582 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:35047006", "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": "2026-11-01T17:16:03Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10899, "completion_tokens": 1683, "cached_tokens": 0}}, "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:35047006", "type": "paper", "label": "pmid:35047006"}, {"id": "source:pmid:35047006", "type": "manuscript", "label": "PMID 35047006 full text"}, {"id": "data:geo:GSE39582", "type": "dataset", "label": "GEO GSE39582"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35047006", "type": "paper", "label": "pmid:35047006"}, {"id": "source:pmid:35047006", "type": "manuscript", "label": "PMID 35047006 full text"}, {"id": "data:geo:GSE39582", "type": "dataset", "label": "GEO GSE39582"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35047006", "type": "extraction", "used": ["source:pmid:35047006"], "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:35047006", "parent_hash": "sha256:3653aa7315437a150c5f4109c4b072b2928ba34e99b29dad9536c0d4f7a93c24", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE39582 licence not read", "asset:data:geo:GSE39582 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "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": ["KM and COX regression analysis were used to further evaluate the relationship between the DEGs and over survival of COAD in the TCGA and GSE39582 datasets."], "order_basis": "analysis_only", "id": "assay:1"}]}