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pmid:32236130

Transcriptome analysis reveals gender-specific differences in overall metabolic response of male and female patients in lung adenocarcinoma.

Ya Li · Cheng-Lu He · Wen-Xing Li · Rui-Xian Zhang · Yong Duan

PloS one · 2020 doi:10.1371/journal.pone.0230796

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pmid:32236130
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title
Transcriptome analysis reveals gender-specific differences in overall metabolic response of male and female patients in lung adenocarcinoma.
doi
10.1371/journal.pone.0230796
pmid
32236130
authors array · 5 items
[0]
Ya Li
[1]
Cheng-Lu He
[2]
Wen-Xing Li
[3]
Rui-Xian Zhang
[4]
Yong Duan
journal
PloS one
year
2020
abstract
BACKGROUND: Evidence from multiple studies suggests metabolic abnormalities play an important role in lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. The present study aimed to explore differences in the global metabolic response between male and female patients in LUAD and to identify the metabolic genes associated with lung cancer susceptibility. METHODS: Transcriptome and clinical LUAD data were acquired from The Cancer Genome Atlas (TCGA) database. Information on metabolic genes and metabolic subsystems were collected from the Recon3D human metabolic model. Two validation datasets (GSE68465 and GSE72094) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis, gene set enrichment analysis and protein-protein interaction networks were used to identified key metabolic pathways and genes. Functional experiments were used to verify the effects of genes on proliferation, migration, and invasion in lung cancer cells in vitro. RESULTS: Samples of tumors and adjacent non-tumor tissue from both male and female patients exhibited distinct global patterns of gene expression. In addition, we found large differences in methionine and cysteine metabolism, pyruvate metabolism, cholesterol metabolism, nicotinamide adenine dinucleotide (NAD) metabolism, and nuclear transport between male and female LUAD patients. We identified 34 metabolic genes associated with lung cancer susceptibility in males and 15 in females. Most of the metabolic cancer-susceptibility genes had high prediction accuracy for lung cancer (AUC > 0.9). Furthermore, both bioinformatics analysis and experimental results showed that TAOK2 was down-regulated and ASAH1 was up-regulated in male tumor tissue and female tumor tissue in LUAD. Functional experiments showed that inhibiting ASAH1 suppressed the proliferation, migration, and invasion of lung cancer cells. CONCLUSIONS: Metabolic cancer-susceptibility genes may be used alone or in combination as diagnostic markers for LUAD. Further studies are required to elucidate the functions of these genes in LUAD.
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). Kaplan-Meier survival curves were used to express differences between high and low expression levels of each metabolic gene among groups in relation to the prognosis of the patient.
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sections[3] "Lung adenocarcinoma data collection" paragraph 2
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/).
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sections[6] "Comparison of clinical variables and prognosis analysis of deregulated metabolic genes" paragraph 2
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Kaplan-Meier survival curves were used to express differences between high and low expression levels of each metabolic gene among groups in relation to the prognosis of the patient.
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.
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sections[3] "Lung adenocarcinoma data collection" paragraph 2
quote
The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.
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caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study
resolution_checked_at
2026-11-01T15:39:55Z
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.
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KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma
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2026-11-01T15:39:55Z
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Descriptive statistics of the clinical characteristics of LUAD patients stratified by gender.
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Overall differences in metabolic gene expression and clinical features grouped by gender
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Descriptive statistics of the clinical characteristics of LUAD patients stratified by gender.
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). Kaplan-Meier survival curves were used to express differences between high and low expression levels of each metabolic gene among groups in relation to the prognosis of the patient.
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.
basis
The paper names GSE68465, GSE72094 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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SAH1 expression or low TAOK2 expression were transfected with knockdown plasmid (siASAH1#1 and siASAH
[1]
liferation ability of A549 and XWLC-05 cells transfected with knockdown plasmid (siASAH1#1 and siASAH
[2]
e invasion ability of A549 and XWLC-05 cells transfected with knockdown plasmid was lower than that o
[3]
bility of A549 and XWLC-05 cells. Cells were transfected with knockdown plasmid (siASAH1#1 and siASAH
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University, A549 and XWLC-05 cells were all cultured in RPMI-1640 medium (Hyclone, USA) supplemented
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CC and cultured following standard protocol. A549 and XWLC-05 lung adenocarcinoma cancer cell
[2]
linical Cancer, Kunming Medicine University, A549 and XWLC-05 cells were all cultured in RPMI-
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in lung cancer cells was evaluated. Briefly, A549 and XWLC-05 cells with high ASAH1 expression
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ank vector (siCtrl or exCtrl), respectively. CCK-8 assay and invasion assay were performed to i
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adenocarcinoma cancer cells in vitro.(A) The CCK-8 assay results showing the proliferation abil
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The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). Kaplan-Meier survival curves were used to express differences between high and low expression levels of each metabolic gene among groups in relation to the prognosis of the patient.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32236130", "kind": "science-record", "revision": 8, "content_hash": "sha256:5e642c9b8fdc3dbc747d362db7049a890cad56b4c7e81f15a41643cadfb0174f", "created_at": "2026-11-01T15:40:58Z", "updated_at": "2026-11-01T22:01:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptome analysis reveals gender-specific differences in overall metabolic response of male and female patients in lung adenocarcinoma.", "doi": "10.1371/journal.pone.0230796", "pmid": "32236130", "authors": ["Ya Li", "Cheng-Lu He", "Wen-Xing Li", "Rui-Xian Zhang", "Yong Duan"], "journal": "PloS one", "year": 2020, "abstract": "BACKGROUND: Evidence from multiple studies suggests metabolic abnormalities play an important role in lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. The present study aimed to explore differences in the global metabolic response between male and female patients in LUAD and to identify the metabolic genes associated with lung cancer susceptibility.\nMETHODS: Transcriptome and clinical LUAD data were acquired from The Cancer Genome Atlas (TCGA) database. Information on metabolic genes and metabolic subsystems were collected from the Recon3D human metabolic model. Two validation datasets (GSE68465 and GSE72094) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis, gene set enrichment analysis and protein-protein interaction networks were used to identified key metabolic pathways and genes. Functional experiments were used to verify the effects of genes on proliferation, migration, and invasion in lung cancer cells in vitro.\nRESULTS: Samples of tumors and adjacent non-tumor tissue from both male and female patients exhibited distinct global patterns of gene expression. In addition, we found large differences in methionine and cysteine metabolism, pyruvate metabolism, cholesterol metabolism, nicotinamide adenine dinucleotide (NAD) metabolism, and nuclear transport between male and female LUAD patients. We identified 34 metabolic genes associated with lung cancer susceptibility in males and 15 in females. Most of the metabolic cancer-susceptibility genes had high prediction accuracy for lung cancer (AUC > 0.9). Furthermore, both bioinformatics analysis and experimental results showed that TAOK2 was down-regulated and ASAH1 was up-regulated in male tumor tissue and female tumor tissue in LUAD. Functional experiments showed that inhibiting ASAH1 suppressed the proliferation, migration, and invasion of lung cancer cells.\nCONCLUSIONS: Metabolic cancer-susceptibility genes may be used alone or in combination as diagnostic markers for LUAD. Further studies are required to elucidate the functions of these genes in LUAD.", "claims": [{"id": "claim-method", "statement": "The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). 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The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32236130", "locator": "sections[3] \"Lung adenocarcinoma data collection\" paragraph 2", "quote": "The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The complete transcriptome and clinical data for 513 tumor samples and 57 adjacent non-tumor samples were obtained, including 237 tumor samples and 23 adjacent non-tumor samples in males and 276 tumor samples and 34 adjacent non-tumor samples in females."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "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:32236130"], "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:GSE68465"], "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:GSE68465"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32236130", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1371/journal.pone.0230796", "sha256": "sha256:0427c834e82f65a8377173b68d134d39b9ab75f48d0ed9069cbfd011f14e0b9e", "bytes": 41695, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1371/journal.pone.0230796", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7112214", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE68465", "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=GSE68465", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE68465", "version": null, "note": "The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). 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Kaplan-Meier survival curves were used to express differences between high and low expression levels of each metabolic gene among groups in relation to the prognosis of the patient."}}, {"id": "method-2", "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-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": 0.8, "band": "high", "quote": "Cox proportional hazards"}}, {"id": "method-4", "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"}}, {"id": "method-5", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "χ2"}}], "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": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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Cells were transfected with knockdown plasmid (siASAH1#1 and siASAH"], "order_basis": "paper_text_order:5599", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["University, A549 and XWLC-05 cells were all cultured in RPMI-1640 medium (Hyclone, USA) supplemented", "CC and cultured following standard protocol. A549 and XWLC-05 lung adenocarcinoma cancer cell", "linical Cancer, Kunming Medicine University, A549 and XWLC-05 cells were all cultured in RPMI-", "in lung cancer cells was evaluated. Briefly, A549 and XWLC-05 cells with high ASAH1 expression"], "order_basis": "paper_text_order:5993", "id": "assay:2"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ank vector (siCtrl or exCtrl), respectively. CCK-8 assay and invasion assay were performed to i", "adenocarcinoma cancer cells in vitro.(A) The CCK-8 assay results showing the proliferation abil"], "order_basis": "paper_text_order:7198", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The LUAD transcriptomes and clinical data were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). Kaplan-Meier survival curves were used to express differences between high and low expression levels of each metabolic gene among groups in relation to the prognosis of the patient."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}