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pmid:37180655

Bioinformatics identification of prognostic genes and potential interaction analysis in renal cell carcinoma.

Yimin Yuan · Jingzi Wang · Liqu Huang · Yunfei Guo

Translational cancer research · 2023 doi:10.21037/tcr-22-2242

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:37180655
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2026-11-01T19:01:51Z
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2026-11-01T22:09:27Z
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title
Bioinformatics identification of prognostic genes and potential interaction analysis in renal cell carcinoma.
doi
10.21037/tcr-22-2242
pmid
37180655
authors array · 4 items
[0]
Yimin Yuan
[1]
Jingzi Wang
[2]
Liqu Huang
[3]
Yunfei Guo
journal
Translational cancer research
year
2023
abstract
Background: Renal cell carcinoma (RCC) is one of the ten most prevalent cancers in the world and its incidence has been rising over the past decade. However, effective biomarkers to predict the prognosis of patients remains absent, and the exact molecular mechanism of the disease remains unclear. Therefore, the identification of key genes and their biological pathways are of great significance to identify the differential expressed genes associated with the prognosis for patients with RCC, and to further explore their potential protein-protein interactions (PPIs) in tumorigenesis. Methods: The gene expression microarray data for GSE15641 and GSE40435 were extracted from the Gene Expression Omnibus (GEO) database, including 150 primary tumors and their matched adjacent non-tumor tissues. Afterwards, gene expression for fold changes (FCs) and P value for tumor and non-tumor tissues were analyzed using online tool GEO2R. Gene expression with logFCs of greater than two combined with P value of lower than 0.01 were considered as candidate targets for treatment of RCC. The survival analysis of candidate genes was performed by online software OncoLnc. The PPI network was implemented with Search Tool for the Retrieval of Interacting Genes (STRING). Results: In total, there were 625 differentially expressed genes (DEGs) in GSE15641, including 415 increased and 210 decreased genes. A total of 343 DEGs were identified in the GSE40435 with 101 upregulated and 242 downregulated genes, the 20 genes with highest FC in high or low expression in each database were summarized. Five candidate genes were overlapped genes in the two GEO datasets. However, aldolase, fructose-bisphosphate B (ALDOB) was found to be the only gene affecting the prognosis. A number of critical genes were identified behind the mechanism, of which they interacted with ALDOB. Among them, phosphofructokinase, platelet (PFKP), phosphofructokinase, muscle (PFKM), pyruvate kinase L/R (PKLR), and fructose-bisphosphatase 1 (FBP1) showed a better prognosis, whereas only glyceraldehyde-3-phosphate dehydrogenase (GAPDH) rendered a bleak outcome. Conclusions: Five genes were found to be overlappingly expressed in the top 20 greatest FC in two human GEO datasets. This is of great value in the treatment and prognosis of RCC.
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Student’s t-test was used to test the statistical significance of differential expression of genes.
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Student’s t-test was used to test the statistical significance of differential expression of genes.
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sections[4] "Microarray data" paragraph 2
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The expression array for GSE15641 consisted of a messenger RNA (mRNA) expression profile of 49 RCC tumors, and 23 normal kidney samples. Transcriptional profiling with oligonucleotide microarrays (22,283 genes, GPL96) was performed on all samples.
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ALDOB was the only overlapping differentially expressed candidate gene associated with prognosis in RCC patients.
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However, aldolase, fructose-bisphosphate B (ALDOB) was found to be the only gene affecting the prognosis.
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ALDOB was the only overlapping differentially expressed candidate gene associated with prognosis in RCC patients.
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Gene signatures of progression and metastasis in renal cell cancer
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data:geo:GSE15641
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GEO GSE15641
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activity-reading-sci-2026-11-01
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classification
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pmid:37180655
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pmid:37180655
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PMID 37180655 full text
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GEO GSE15641
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agent:corpus-assay-engine
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agent:corpus-assay-engine
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[0]
asset:data:geo:GSE15641 licence not read
[1]
asset:data:geo:GSE15641 not downloaded
[2]
asset:data:geo:GSE40435 licence not read
[3]
asset:data:geo:GSE40435 not downloaded
[4]
execution.not_run
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review.human_critique
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review.independent_reader
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review.machine_critique
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[0] object · 11 fields
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99e1195c7d6f
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99e1195c7d6f
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tumorigenesis. Methods: The gene expression microarray data for GSE15641 and GSE40435 were extracte
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id
assay:1
[1] object · 11 fields
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transfection
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99e1195c7d6f
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99e1195c7d6f
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[0]
of proliferation was increased in the ALDOB knockdown cells (Figure S2). To sum up, these findings
[1]
LR, and FBP1 were downregulated in the ALDOB knockdown cell lines (Figure S3). Supplementary Materi
[2]
of ALDOB expression in ccRCC cells, we used shRNA to knock down ALDOB in Caki-1 cell. We detec
order_basis
paper_text_order:4903
id
assay:2
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ALDOB in Caki-1 cell by cell counting kit-8 (CCK-8), which showed that the capacity of prolifer
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paper_text_order:5030
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assay:3
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37180655", "kind": "science-record", "revision": 3, "content_hash": "sha256:9e522bd59580996a8ef055fbb0f151d68bd690d3e2a942970bb64b3e9c1dd0ec", "created_at": "2026-11-01T19:01:51Z", "updated_at": "2026-11-01T22:09:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics identification of prognostic genes and potential interaction analysis in renal cell carcinoma.", "doi": "10.21037/tcr-22-2242", "pmid": "37180655", "authors": ["Yimin Yuan", "Jingzi Wang", "Liqu Huang", "Yunfei Guo"], "journal": "Translational cancer research", "year": 2023, "abstract": "Background: Renal cell carcinoma (RCC) is one of the ten most prevalent cancers in the world and its incidence has been rising over the past decade. However, effective biomarkers to predict the prognosis of patients remains absent, and the exact molecular mechanism of the disease remains unclear. Therefore, the identification of key genes and their biological pathways are of great significance to identify the differential expressed genes associated with the prognosis for patients with RCC, and to further explore their potential protein-protein interactions (PPIs) in tumorigenesis.\nMethods: The gene expression microarray data for GSE15641 and GSE40435 were extracted from the Gene Expression Omnibus (GEO) database, including 150 primary tumors and their matched adjacent non-tumor tissues. Afterwards, gene expression for fold changes (FCs) and P value for tumor and non-tumor tissues were analyzed using online tool GEO2R. Gene expression with logFCs of greater than two combined with P value of lower than 0.01 were considered as candidate targets for treatment of RCC. The survival analysis of candidate genes was performed by online software OncoLnc. The PPI network was implemented with Search Tool for the Retrieval of Interacting Genes (STRING).\nResults: In total, there were 625 differentially expressed genes (DEGs) in GSE15641, including 415 increased and 210 decreased genes. A total of 343 DEGs were identified in the GSE40435 with 101 upregulated and 242 downregulated genes, the 20 genes with highest FC in high or low expression in each database were summarized. Five candidate genes were overlapped genes in the two GEO datasets. However, aldolase, fructose-bisphosphate B (ALDOB) was found to be the only gene affecting the prognosis. A number of critical genes were identified behind the mechanism, of which they interacted with ALDOB. Among them, phosphofructokinase, platelet (PFKP), phosphofructokinase, muscle (PFKM), pyruvate kinase L/R (PKLR), and fructose-bisphosphatase 1 (FBP1) showed a better prognosis, whereas only glyceraldehyde-3-phosphate dehydrogenase (GAPDH) rendered a bleak outcome.\nConclusions: Five genes were found to be overlappingly expressed in the top 20 greatest FC in two human GEO datasets. This is of great value in the treatment and prognosis of RCC.", "claims": [{"id": "claim-method", "statement": "Student’s t-test was used to test the statistical significance of differential expression of genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37180655", "locator": "sections[5] \"Identification of DEGs\" paragraph 2", "quote": "Student’s t-test was used to test the statistical significance of differential expression of genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The expression array for GSE15641 consisted of a messenger RNA (mRNA) expression profile of 49 RCC tumors, and 23 normal kidney samples. 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Transcriptional profiling with oligonucleotide microarrays (22,283 genes, GPL96) was performed on all samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ALDOB was the only overlapping differentially expressed candidate gene associated with prognosis in RCC patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37180655", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "However, aldolase, fructose-bisphosphate B (ALDOB) was found to be the only gene affecting the prognosis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ALDOB was the only overlapping differentially expressed candidate gene associated with prognosis in RCC patients.", "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:37180655"], "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:GSE15641"], "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:GSE15641"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37180655", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-22-2242", "sha256": "sha256:5a8d666ced1718cd630a2a601bf3087a727bfb82692d020778629194b858370a", "bytes": 37276, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tcr-22-2242", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10174992", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE15641", "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=GSE15641", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE15641", "version": null, "note": "The expression array for GSE15641 consisted of a messenger RNA (mRNA) expression profile of 49 RCC tumors, and 23 normal kidney samples. 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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": ["GSE15641", "GSE40435"], "resolved_accessions": ["GSE15641", "GSE40435"], "statements": ["The expression array for GSE15641 consisted of a messenger RNA (mRNA) expression profile of 49 RCC tumors, and 23 normal kidney samples. Transcriptional profiling with oligonucleotide microarrays (22,283 genes, GPL96) was performed on all samples."], "basis": "The paper names GSE15641, GSE40435 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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Methods: The gene expression microarray data for GSE15641 and GSE40435 were extracte"], "order_basis": "paper_text_order:683", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["of proliferation was increased in the ALDOB knockdown cells (Figure S2). To sum up, these findings", "LR, and FBP1 were downregulated in the ALDOB knockdown cell lines (Figure S3). Supplementary Materi", "of ALDOB expression in ccRCC cells, we used shRNA to knock down ALDOB in Caki-1 cell. We detec"], "order_basis": "paper_text_order:4903", "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": 0.93, "evidence": ["ALDOB in Caki-1 cell by cell counting kit-8 (CCK-8), which showed that the capacity of prolifer"], "order_basis": "paper_text_order:5030", "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": 0.8, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}