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pmid:38546385

A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma.

Qing Lu · Ping Xi · Suling Xu · Zhicheng Zhang · Binbin Gong · Ji Liu · Qiqi Zhu · Ting Sun · Shaoxing Zhu · Ru Chen

Aging · 2024 doi:10.18632/aging.205691

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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title
A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma.
doi
10.18632/aging.205691
pmid
38546385
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[0]
Qing Lu
[1]
Ping Xi
[2]
Suling Xu
[3]
Zhicheng Zhang
[4]
Binbin Gong
[5]
Ji Liu
[6]
Qiqi Zhu
[7]
Ting Sun
[8]
Shaoxing Zhu
[9]
Ru Chen
journal
Aging
year
2024
abstract
BACKGROUND: Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches. MATERIALS AND METHODS: The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model. RESULTS: We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells. CONCLUSIONS: We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.
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A five-gene LLPS-related risk signature, combining CLIC5, MXD3, NUF2, PABPC1L, and PLK1, showed prognostic accuracy for ccRCC in the TCGA-KIRC and E-MTAB-1980 cohorts.
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Results from the TCGA-KIRC and E-MTAB-1980 cohorts consistently demonstrated that our constructed LLPS-related gene risk signature has strong ability and accuracy for prognostic prediction of ccRCC patients.
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A five-gene LLPS-related risk signature, combining CLIC5, MXD3, NUF2, PABPC1L, and PLK1, showed prognostic accuracy for ccRCC in the TCGA-KIRC and E-MTAB-1980 cohorts.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38546385", "kind": "science-record", "revision": 2, "content_hash": "sha256:561f91eb7b5837c22a21b4e5fd32ed21614dfa209ff7f7c0c8650e598456ba9d", "created_at": "2026-11-01T19:20:30Z", "updated_at": "2026-11-01T21:32:48Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma.", "doi": "10.18632/aging.205691", "pmid": "38546385", "authors": ["Qing Lu", "Ping Xi", "Suling Xu", "Zhicheng Zhang", "Binbin Gong", "Ji Liu", "Qiqi Zhu", "Ting Sun", "Shaoxing Zhu", "Ru Chen"], "journal": "Aging", "year": 2024, "abstract": "BACKGROUND: Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches.\nMATERIALS AND METHODS: The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model.\nRESULTS: We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells.\nCONCLUSIONS: We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.", "claims": [{"id": "claim-data-access", "statement": "RNA expression data of ccRCC patients and related clinical data were obtained from the TCGA-KIRC cohort on the TCGA website (https://portal.gdc.cancer.gov/), which contains 541 tumor samples and 72 normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38546385", "locator": "sections[12] \"Data source\" paragraph 2", "quote": "RNA expression data of ccRCC patients and related clinical data were obtained from the TCGA-KIRC cohort on the TCGA website (https://portal.gdc.cancer.gov/), which contains 541 tumor samples and 72 normal samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A five-gene LLPS-related risk signature, combining CLIC5, MXD3, NUF2, PABPC1L, and PLK1, showed prognostic accuracy for ccRCC in the TCGA-KIRC and E-MTAB-1980 cohorts.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38546385", "locator": "sections[3] \"Construction and validation of a prognostic prediction model for LLPS-related genes in ccRCC\" paragraph 4", "quote": "Results from the TCGA-KIRC and E-MTAB-1980 cohorts consistently demonstrated that our constructed LLPS-related gene risk signature has strong ability and accuracy for prognostic prediction of ccRCC patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A five-gene LLPS-related risk signature, combining CLIC5, MXD3, NUF2, PABPC1L, and PLK1, showed prognostic accuracy for ccRCC in the TCGA-KIRC and E-MTAB-1980 cohorts.", "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:38546385"], "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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