Evidence map›Paper›PMID 34099557›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Single-cell analyses of renal cell cancers reveal insights into tumor microenvironment, cell of origin, and therapy response.

Yuping Zhang, Sathiya P Narayanan, Rahul Mannan, Gregory Raskind, Xiaoming Wang, Pankaj Vats, Fengyun Su, Noshad Hosseini, Xuhong Cao, Chandan Kumar-Sinha and 9 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 245 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
245citing papers in PubMed, 1 pooled it
–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

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

245 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Integrative omics profiling of CRELD2 in ccRCC: a nexus of genetics, prognosis, and tumor microenvironment.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
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  14. Accelerated protein digestion by numbering-up nanochannels, followed by LC-MS analysis.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2026
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185 more citing papers are in PubMed but not listed here.

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

19 authors.

Yuping ZhangMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Sathiya P NarayananMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Rahul MannanMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-6642-0468
Gregory RaskindMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-9940-1984
Xiaoming WangMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0001-9697-5571
Pankaj VatsMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Fengyun SuMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Noshad HosseiniMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Xuhong CaoMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Chandan Kumar-SinhaMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Stephanie J EllisonMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Thomas J GiordanoDepartment of Pathology, University of Michigan, Ann Arbor, MI 48109.
Todd M MorganMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-1140-0603
Sethuramasundaram PitchiayaMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0003-2529-5186
Ajjai AlvaMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-1898-3522
Rohit MehraMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-6955-8884
Marcin CieslikMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Saravana M DhanasekaranMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109.
Arul M ChinnaiyanMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109; arul@umich.edu.

Funding

Exploring Precision Oncology: From Gene Fusions to lncRNAsR35CA231996 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M · 2018 to 2024
$6.4M
University of Michigan Proteogenomics Data Analysis CenterU24CA210967 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M, DHANASEKARAN, SARAVANA M · 2016 to 2020
$4.1M
NCI NIH HHS R35 CA231996NCI NIH HHS U24 CA210967
6 · The paper itself

Abstract

Diverse subtypes of renal cell carcinomas (RCCs) display a wide spectrum of histomorphologies, proteogenomic alterations, immune cell infiltration patterns, and clinical behavior. Delineating the cells of origin for different RCC subtypes will provide mechanistic insights into their diverse pathobiology. Here, we employed single-cell RNA sequencing (scRNA-seq) to develop benign and malignant renal cell atlases. Using a random forest model trained on this cell atlas, we predicted the putative cell of origin for more than 10 RCC subtypes. scRNA-seq also revealed several attributes of the tumor microenvironment in the most common subtype of kidney cancer, clear cell RCC (ccRCC). We elucidated an active role for tumor epithelia in promoting immune cell infiltration, potentially explaining why ccRCC responds to immune checkpoint inhibitors, despite having a low neoantigen burden. In addition, we characterized an association between high endothelial cell types and lack of response to immunotherapy in ccRCC. Taken together, these single-cell analyses of benign kidney and RCC provide insight into the putative cell of origin for RCC subtypes and highlight the important role of the tumor microenvironment in influencing ccRCC biology and response to therapy.

Indexed as

Single-Cell AnalysisCarcinoma, Renal CellCell SurvivalEndothelial CellsEpithelial CellsHumansImmunotherapyKidneyKidney NeoplasmsLymphocytes, Tumor-InfiltratingMyeloid CellsTreatment Outcomecell of originclear cell renal cell carcinomarenal cell carcinomasingle-cell RNA sequencingtumor microenvironment

Identifiers

PMID34099557
PMCPMC8214680

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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.