Evidence map›Paper›PMID 38482447›Full record

ArticleTranslational cancer research2024

Multiomics combined with single-cell analysis shows that mitophagy-related genes could accurately predict the prognosis of patients with clear cell renal cell carcinoma.

Hang Yin, Yonggui Xiao, Hubo Li, Yong Wang, Liguo Zhang, Anliang Yao, Shaosan Kang, Fenghong Cao

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Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Hang YinSchool of Clinical Medicine, Affiliated Hospital, North China University of Science and Technology, Tangshan, China.
Yonggui XiaoSchool of Clinical Medicine, Affiliated Hospital, North China University of Science and Technology, Tangshan, China.
Hubo LiSchool of Clinical Medicine, Affiliated Hospital, North China University of Science and Technology, Tangshan, China.
Yong WangDepartment of Urology, Affiliated Hospital of North China University of Science and Technology, Tangshan, China.
Liguo ZhangDepartment of Urology, Affiliated Hospital of North China University of Science and Technology, Tangshan, China.
Anliang YaoDepartment of Urology, Affiliated Hospital of North China University of Science and Technology, Tangshan, China.
Shaosan KangDepartment of Urology, Affiliated Hospital of North China University of Science and Technology, Tangshan, China.
Fenghong CaoDepartment of Urology, Affiliated Hospital of North China University of Science and Technology, Tangshan, China.
North China University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor that accounts for a large proportion of kidney cancer, It is prone to recurrence and metastasis, and has a high mortality rate. Although mitophagy is important for metastasis and the recurrence of various tumors, its effect on renal clear cell carcinoma is poorly understood. Methods: Mitophagy-related genes were obtained through the GeneCards database. We normalised the data from different sources by removing the batch effect. Next, we conducted a preliminary screening of mitophagy-related genes and obtained prognosis-related genes from differentially expressed genes. We constructed a prognostic model using least absolute shrinkage and selection operator (LASSO) regression with data from The Cancer Genome Atlas (TCGA) and GSE29609 datasets and validated it internally. International Cancer Genome Consortium (ICGC) and E-MTAB-1980 cohorts also provided double external validation. In addition, we combined multi-omics and single-cell data to comprehensively analyse mitophagy-related gene model signature (MRGMS). Combined with the mitophagy-related gene model (MRGM) score, we constructed a nomogram. Finally, we performed pathway enrichment analysis using a variety of methods. Results: Multiomics and single-cell data analysis showed that the MRGMS is important for patients with ccRCC and is expected to become a new biomarker. The construction of a nomogram was conducive to accurately predicting patient survival. Conclusions: Mitophagy-related genes are important for predicting the prognosis of ccRCC and are conducive to the development of more personalised treatment plans for patients.

Indexed as

Clear cell renal cell carcinoma (ccRCC)computational biologymitophagymultiomicssingle-cell analysis

Identifiers

PMID38482447
PMCPMC10928636
OpenAlexW4392300973

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.