Evidence map›Paper›PMID 36557227›Full record

ArticleMetabolites2022

Metabolomic Analysis of Renal Cell Carcinoma in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.

Kathleen M McClain, Joshua N Sampson, Jessica L Petrick, Kaitlyn M Mazzilli, Robert E Gerszten, Clary B Clish, Mark P Purdue, Loren Lipworth, Steven C Moore

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
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

9 authors at 5 institutions in 1 country.

Kathleen M McClainDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.ORCID 0000-0001-5520-2097
Joshua N SampsonDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Jessica L PetrickSlone Epidemiology Center at Boston University, Boston, MA 02118, USA.
Kaitlyn M MazzilliDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Robert E GersztenDivision of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA.
Clary B ClishBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Mark P PurdueDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Loren LipworthDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
Steven C MooreDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.ORCID 0000-0002-8169-1661
National Cancer Institute · USBeth Israel Deaconess Medical Center · USBoston University · USBroad Institute · USVanderbilt University Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In the US in 2021, 76,080 kidney cancers are expected and >80% are renal cell carcinomas (RCCs). Along with excess fat, metabolic dysfunction is implicated in RCC etiology. To identify RCC-associated metabolites, we conducted a 1:1 matched case−control study nested within the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Methods: We measured 522 serum metabolites in 267 cases/control pairs. Cases were followed for a median 7.1 years from blood draw to diagnosis. Using conditional logistic regression, we computed adjusted odds ratios (ORs) and 95% confidence intervals (CIs) comparing risk between 90th and 10th percentiles of log metabolite intensity, with the significance threshold at a false discovery rate <0.20. Results: Four metabolites were inversely associated with risk of RCC during follow-up—C38:4 PI, C34:0 PC, C14:0 SM, and C16:1 SM (ORs ranging from 0.33−0.44). Two were positively associated with RCC risk—C3-DC-CH3 carnitine and C5 carnitine (ORs = 2.84 and 2.83, respectively). These results were robust when further adjusted for metabolic risk factors (body mass index (BMI), physical activity, diabetes/hypertension history). Metabolites associated with RCC had weak correlations (|r| < 0.2) with risk factors of BMI, physical activity, smoking, alcohol, and diabetes/hypertension history. In mutually adjusted models, three metabolites (C38:4 PI, C14:0 SM, and C3-DC-CH3 carnitine) were independently associated with RCC risk. Conclusions: Serum concentrations of six metabolites were associated with RCC risk, and three of these had independent associations from the mutually adjusted model. These metabolites may point toward new biological pathways of relevance to this malignancy.

Indexed as

kidney cancermetabolomicsrenal cell carcinoma

Identifiers

PMID36557227
PMCPMC9785244
OpenAlexW4311002458

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.