Evidence map›Paper›PMID 34212534›Full record

ArticleThe journal of pathology. Clinical research2021

Integration of NRP1, RGS5, and FOXM1 expression, and tumour necrosis, as a postoperative prognostic classifier based on molecular subtypes of clear cell renal cell carcinoma.

Takashi Yoshida, Chisato Ohe, Junichi Ikeda, Naho Atsumi, Ryoichi Saito, Hisanori Taniguchi, Haruyuki Ohsugi, Motohiko Sugi, Koji Tsuta, Tadashi Matsuda and 1 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in The journal of pathology. Clinical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. 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

11 authors at 1 institution in 1 country.

Takashi YoshidaDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.ORCID 0000-0003-1119-312X
Chisato OheDepartment of Pathology and Laboratory Medicine, Kansai Medical University, Hirakata, Japan.
Junichi IkedaDepartment of Pathology and Laboratory Medicine, Kansai Medical University, Hirakata, Japan.
Naho AtsumiDepartment of Pathology and Laboratory Medicine, Kansai Medical University, Hirakata, Japan.
Ryoichi SaitoDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.
Hisanori TaniguchiDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.
Haruyuki OhsugiDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.
Motohiko SugiDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.
Koji TsutaDepartment of Pathology and Laboratory Medicine, Kansai Medical University, Hirakata, Japan.
Tadashi MatsudaDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.
Hidefumi KinoshitaDepartment of Urology and Andrology, Kansai Medical University, Hirakata, Japan.
Kansai Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular mechanisms of progression of clear cell renal cell carcinoma (ccRCC) have been proven with recent genomic or transcriptional analyses. However, it is still difficult to apply these analyses to daily clinical practice owing to economical and practical issues. Here, we established a pathology-based, postoperative prognostic classification based on the well-validated transcriptional classifier, ClearCode34, in ccRCC. A total of 342 cases with available tissue were identified and randomly allocated into a discovery cohort (n = 138) and a validation cohort (n = 204). Levels of mRNA were quantified using a nCounter Digital Analyzer, and the ccA/ccB subtypes were determined. Histological and immunohistochemistry (IHC) analyses were subsequently performed to establish a pathology-based classification based on the mRNA levels. Finally, the prognostic ability of the new classifier was evaluated in both the discovery and validation cohorts. Of 138 cases in the discovery cohort, 78 (56.5%) and 60 (43.5%) were assigned to the ccA and ccB subtypes, respectively. Proangiogenic genes, neuropilin 1 (NRP1) and regulator of G protein signalling 5 (RGS5), were especially overexpressed in all ccRCC samples and were enriched in ccA-assigned tumours. Histologically, tumour necrosis and the sarcomatoid feature were associated with the ccB subtype. In IHC analyses, expression of NRP1, RGS5, and forkhead box M1 (FOXM1), an epithelial-mesenchymal transition-related factor, significantly correlated with the ccA/ccB subtypes. Combining these three IHC factors and tumour necrosis, we developed the IHC/histology-based classifier, which showed good concordance with the ClearCode34 classifier with an accuracy of 0.80. The established classification significantly stratified relapse-free, cancer-specific, and overall survival rates in both the discovery and validation cohorts. The novel molecular pathology classifier integrating NRP1, RGS5, FOXM1, and tumour necrosis may enable the stratification of oncological outcomes for patients with ccRCC undergoing resection surgery.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorCarcinoma, Renal CellFemaleForkhead Box Protein M1Gene Expression ProfilingHumansImmunohistochemistryKidney NeoplasmsMaleMiddle AgedNecrosisNephrectomyNeuropilin-1Biomarkers, TumorForkhead Box Protein M1FOXM1 protein, humanNeuropilin-1NRP1 protein, humanRGS5 protein, humanRGS Proteinsclear cell renal cell carcinomahistologyimmunohistochemistrymolecular subtypeprognostic classification

Identifiers

PMID34212534
PMCPMC8503898
OpenAlexW3174088378

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.