Evidence map›Paper›PMID 34200770›Full record

ArticleCancers2021

Integrative Transcriptomic Analysis Reveals Distinctive Molecular Traits and Novel Subtypes of Collecting Duct Carcinoma.

Chiara Gargiuli, Pierangela Sepe, Anna Tessari, Tyler Sheetz, Maurizio Colecchia, Filippo Guglielmo Maria de Braud, Giuseppe Procopio, Marialuisa Sensi, Elena Verzoni, Matteo Dugo

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06302569 (Activity of Pembrolizumab Plus Enfortumab Vedotin in Collecting Duct and Renal Medullary Carcinoma), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 15% 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.

NCT06302569 phase2recruitingnot on this mapstarted 2025, after this paper: background citation

Activity of Pembrolizumab Plus Enfortumab Vedotin in Collecting Duct and Renal Medullary Carcinoma

TypeinterventionalSponsorGiuseppe ProcopioRan2025 to 2029Enrolled23ConditionsBellini Carcinoma, Collecting Duct Carcinoma, Renal Medullary CarcinomaArmsPembrolizumab + Enfortumab Vedotin
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

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

10 authors at 4 institutions in 2 countries.

Chiara GargiuliPlatform of Integrated Biology, Department of Applied Research and Technology Development, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.ORCID 0000-0002-6973-9634
Pierangela SepeDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Anna TessariDepartment of Cancer Biology and Genetics, College of Medicine and Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.
Tyler SheetzDepartment of Cancer Biology and Genetics, College of Medicine and Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0002-4440-1477
Maurizio ColecchiaDepartment of Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Filippo Guglielmo Maria de BraudDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Giuseppe ProcopioDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Marialuisa SensiPlatform of Integrated Biology, Department of Applied Research and Technology Development, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Elena VerzoniDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Matteo DugoPlatform of Integrated Biology, Department of Applied Research and Technology Development, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.ORCID 0000-0001-9786-2763
Fondazione IRCCS Istituto Nazionale dei Tumori · ITThe Ohio State University · USThe Ohio State University Wexner Medical Center · USUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Collecting duct carcinoma (CDC) is a rare and highly aggressive kidney cancer subtype with poor prognosis and no standard treatments. To date, only a few studies have examined the transcriptomic portrait of CDC. Through integration of multiple datasets, we compared CDC to normal tissue, upper-tract urothelial carcinomas, and other renal cancers, including clear cell, papillary, and chromophobe histologies. Association between CDC gene expression signatures and in vitro drug sensitivity data was evaluated using the Cancer Therapeutic Response Portal, Genomics of Drug Sensitivity in Cancer datasets, and connectivity map. We identified a CDC-specific gene signature that predicted in vitro sensitivity to different targeted agents and was associated to worse outcome in clear cell renal cell carcinoma. We showed that CDC are transcriptionally related to the principal cells of the collecting ducts providing evidence that this tumor originates from this normal kidney cell type. Finally, we proved that CDC is a molecularly heterogeneous disease composed of at least two subtypes distinguished by cell signaling, metabolic and immune-related alterations. Our findings elucidate the molecular features of CDC providing novel biological and clinical insights. The identification of distinct CDC subtypes and their transcriptomic traits provides the rationale for patient stratification and alternative therapeutic approaches.

Indexed as

collecting duct carcinomagene expressionhistological classificationkidney cancermolecular subtypesprognostic/predictive biomarkersrenal cell carcinomastranscriptomic

Identifiers

PMID34200770
PMCPMC8230422
OpenAlexW3170861594

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.