Evidence map›Paper›PMID 36275614›Full record

ArticleFrontiers in molecular biosciences2022

Cuproptosis patterns in papillary renal cell carcinoma are characterized by distinct tumor microenvironment infiltration landscapes.

Chiyu Zhang, Ruizhen Huang, Xiaoqing Xi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Review
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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

3 authors at 2 institutions in 1 country.

Chiyu ZhangDepartment of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Ruizhen HuangDepartment of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Xiaoqing XiDepartment of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Nanchang University · CNSecond Affiliated Hospital of Nanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cuproptosis is a novel kind of programmed cell death that has been linked to tumor development, prognosis, and responsiveness to therapy. Nevertheless, the precise function of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) remains unknown. We characterized the genetic and transcriptional changes of CRGs in papillary renal cell carcinoma (PRCC) samples and analyzed the expression patterns in two separate cohorts. We observed that two unique cuproptosis-related subgroups and three separate gene subgroups were connected with clinicopathological, prognostic, and TME features of patients. Then, a risk score for predicting overall survival (OS) was created and validated in patients with PRCC. To make the risk score more clinically useful, we created a nomogram that was very accurate. A lower risk score, which was associated with higher tumor mutation burden, and immune activity, suggested a better prognosis for OS. Additionally, the risk score was shown to be substantially linked with the drug's susceptibility to chemotherapeutic agents. Our extensive research of CRGs in PRCC identified possible roles for them in the TME, clinicopathological features, and overall survival. These findings may help advance our knowledge of CRGs in PRCC and pave the way for improved prognosis and the creation of more effective immunotherapy therapies.

Indexed as

cuproptosisdrug sensitivitypapillary renal cell carcinomaprognostic modeltumor microenvironment

Identifiers

PMID36275614
PMCPMC9579370
OpenAlexW4301401167

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.