Evidence map›Paper›PMID 38706914›Full record

ArticleJournal of Cancer2024

Clinical Implications of a Six-Protein Signature in Bone Metastasis of Renal Cell Carcinoma.

Zheng Liu, Hanwen Mao, Dinggai Chu, Liang Qin, Jiang Wang

Abstract read
In one paragraph

Article in Journal of Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Zheng LiuDepartment of Oncology, People's Hospital of Dongxihu District, Wuhan, Hubei 430040, P.R. China.
Hanwen MaoDepartment of Oncology, People's Hospital of Dongxihu District, Wuhan, Hubei 430040, P.R. China.
Dinggai ChuDepartment of Oncology, People's Hospital of Dongxihu District, Wuhan, Hubei 430040, P.R. China.
Liang QinDepartment of Orthopedic, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.
Jiang WangDepartment of Orthopedic, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bone metastases is prevalent from renal cell carcinoma (RCC) with poor quality of life and prognosis. Our previous proteomics analysis identified dysregulated proteins in the bone-tropism RCC cells. In this study, we further examined the clinical implications of these proteins using multiple clinical cohorts. We identified 6 proteins with significant upregulation in RCC tumor tissue in comparing to tumor adjacent normal tissue (p<0.05). High expression of these 6 protein-encoding genes significantly correlates with a poor survival in the TCGA-KIRC (Kidney renal clear cell carcinoma) cohort (log-rank test p=2.7e-05), and they all individually had a reverse-correlation with the gene expression of VHL and PBRM1 (p<0.001), and positive-correlation with the expression of VEGFA (p<0.001). Further gene set variation analysis (GSVA) revealed positive correlation with Th17 cells enrichment and negative CD8 T cell infiltration in the RCC tumor microenvironment. High expression of these 6 genes in pretreatment tumors favors longer overall survival (OS)(p=0.027) in anti-PDL1 treated patients (n=428). We treated one humeral metastases RCC patient with the anti-PDL1 antibody drug atezolizumab after examined the elevated expression of the 6 proteins in his nephrectomy tumor tissue, the tumor at the fracture site shrunk remarkably after four courses of treatment. These results altogether suggest a clinical implication of the 6-protein signature in RCC bone metastasis prognosis and response to immune-checkpoint inhibitor treatment.

Indexed as

Bone metastasisclinical omics data cohortsimmune check-point inhibitorkidney renal clear cell carcinoma

Identifiers

PMID38706914
PMCPMC11064255

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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.