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pmid:33083148

CKS2 and RMI2 are two prognostic biomarkers of lung adenocarcinoma.

Dayong Xiao · Siyuan Dong · Shize Yang · Zhenghua Liu

PeerJ · 2020 doi:10.7717/peerj.10126

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Experiment

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title
CKS2 and RMI2 are two prognostic biomarkers of lung adenocarcinoma.
doi
10.7717/peerj.10126
pmid
33083148
authors array · 4 items
[0]
Dayong Xiao
[1]
Siyuan Dong
[2]
Shize Yang
[3]
Zhenghua Liu
journal
PeerJ
year
2020
abstract
BACKGROUND: Lung adenocarcinoma (ACA) is the most common subtype of non-small-cell lung cancer. About 70%-80% patients are diagnosed at an advanced stage; therefore, the survival rate is poor. It is urgent to discover accurate markers that can differentiate the late stages of lung ACA from the early stages. With the development of biochips, researchers are able to efficiently screen large amounts of biological analytes for multiple purposes. METHODS: Our team downloaded GSE75037 and GSE32863 from the Gene Expression Omnibus (GEO) database. Next, we utilized GEO's online tool, GEO2R, to analyze the differentially expressed genes (DEGs) between stage I and stage II-IV lung ACA. The using the Cytoscape software was used to analyze the DEGs and the protein-protein interaction (PPI) network was further constructed. The function of the DEGs were further analyzed by cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) online tools. We validated these results in 72 pairs human samples. RESULTS: We identified 109 co-DEGs, most of which were involved in either proliferation, S phase of mitotic cell cycle, regulation of exit from mitosis, DNA replication initiation, DNA replication, and chromosome segregation. Utilizing cBioPortal and University of California Santa Cruz databases, we further confirmed 35 hub genes. Two of these genes, encoding CDC28 protein kinase regulatory subunit 2 (CKS2) and RecQ-mediated genome instability 2 (RMI2), were upregulated in lung ACA compared with adjacent normal tissues. The Kaplan-Meier curves revealed upregulation of CKS2 and RMI2 are associated with worse survival. Using CMap analysis, we discovered 10 small molecular compounds that reversed the altered DEGs, the top five are phenoxybenzamine, adiphenine, resveratrol, and trifluoperazine. We also evaluated 72 pairs resected samples, results revealed that upregulation of CKS2 and RMI2 in lung ACA were associated with larger tumor size. Our results allow the deeper recognizing of the mechanisms of the progression of lung ACA, and may indicate potential therapeutic strategies for the therapy of lung ACA.
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Gene expression analysis of lung adenocarcinoma and matched adjacent non-tumor lung tissue
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The raw measurements are available in the Supplementary Files.
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The paper names GSE75037, GSE32863 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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C. GEPIA is an online tool that provides the RNA sequencing expression data (Tang et al., 2017). The GEP
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CKS2 and RMI2 expression was detected using qPCR. We used TRIzol reagent (Invitrogen, Carlsba
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adjacent normal tissue. The results from the qPCR aligned with our bioinformatic results, sugg
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33083148", "kind": "science-record", "revision": 7, "content_hash": "sha256:885d986b275605a61c549fca07a74a6275adb09e1a2d3f47b86221832ab3b637", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:02:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CKS2 and RMI2 are two prognostic biomarkers of lung adenocarcinoma.", "doi": "10.7717/peerj.10126", "pmid": "33083148", "authors": ["Dayong Xiao", "Siyuan Dong", "Shize Yang", "Zhenghua Liu"], "journal": "PeerJ", "year": 2020, "abstract": "BACKGROUND: Lung adenocarcinoma (ACA) is the most common subtype of non-small-cell lung cancer. About 70%-80% patients are diagnosed at an advanced stage; therefore, the survival rate is poor. It is urgent to discover accurate markers that can differentiate the late stages of lung ACA from the early stages. With the development of biochips, researchers are able to efficiently screen large amounts of biological analytes for multiple purposes.\nMETHODS: Our team downloaded GSE75037 and GSE32863 from the Gene Expression Omnibus (GEO) database. Next, we utilized GEO's online tool, GEO2R, to analyze the differentially expressed genes (DEGs) between stage I and stage II-IV lung ACA. The using the Cytoscape software was used to analyze the DEGs and the protein-protein interaction (PPI) network was further constructed. The function of the DEGs were further analyzed by cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) online tools. We validated these results in 72 pairs human samples.\nRESULTS: We identified 109 co-DEGs, most of which were involved in either proliferation, S phase of mitotic cell cycle, regulation of exit from mitosis, DNA replication initiation, DNA replication, and chromosome segregation. Utilizing cBioPortal and University of California Santa Cruz databases, we further confirmed 35 hub genes. Two of these genes, encoding CDC28 protein kinase regulatory subunit 2 (CKS2) and RecQ-mediated genome instability 2 (RMI2), were upregulated in lung ACA compared with adjacent normal tissues. The Kaplan-Meier curves revealed upregulation of CKS2 and RMI2 are associated with worse survival. Using CMap analysis, we discovered 10 small molecular compounds that reversed the altered DEGs, the top five are phenoxybenzamine, adiphenine, resveratrol, and trifluoperazine. We also evaluated 72 pairs resected samples, results revealed that upregulation of CKS2 and RMI2 in lung ACA were associated with larger tumor size. Our results allow the deeper recognizing of the mechanisms of the progression of lung ACA, and may indicate potential therapeutic strategies for the therapy of lung ACA.", "claims": [{"id": "claim-method", "statement": "The GEO DataSets provide GEO2R, an online tool which can identify DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083148", "locator": "sections[4] \"Identification of DEGs\" paragraph 2", "quote": "The GEO DataSets provide GEO2R, an online tool which can identify DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw measurements are available in the Supplementary Files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083148", "locator": "sections[21] \"Additional Information and Declarations\" paragraph 5", "quote": "The raw measurements are available in the Supplementary Files."}], "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:33083148"], "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. 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