Evidence map›Paper›PMID 36180422›Full record

ArticleNature communications2022

A transcriptional metastatic signature predicts survival in clear cell renal cell carcinoma.

Adele M Alchahin, Shenglin Mei, Ioanna Tsea, Taghreed Hirz, Youmna Kfoury, Douglas Dahl, Chin-Lee Wu, Alexander O Subtelny, Shulin Wu, David T Scadden and 5 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
11.7field-weighted citation impact, top 1% 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

52 citing papers in PubMed, 79 citations in OpenAlex.

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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

15 authors at 2 institutions in 2 countries.

Adele M Alchahin *Childhood Cancer Research unit, Department of Children's and Women's Health, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Shenglin Mei *Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. smei8@mgh.harvard.edu.ORCID 0000-0001-8258-5898
Ioanna TseaChildhood Cancer Research unit, Department of Children's and Women's Health, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Taghreed HirzCenter for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA.
Youmna KfouryCenter for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA.
Douglas DahlDepartment of Urology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Chin-Lee WuDepartment of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Alexander O SubtelnyDepartment of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Shulin WuDepartment of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
David T ScaddenCenter for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA.
John H ShinDepartment of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Philip J Saylor *Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-4849-3695
David B Sykes *Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-9788-0221
Peter V Kharchenko *Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. peter.kharchenko@post.harvard.edu.
Ninib Baryawno *Childhood Cancer Research unit, Department of Children's and Women's Health, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden. n.baryawno@ki.se.ORCID 0000-0001-6054-4163
Harvard University · USKarolinska University Hospital · SE

Funding

Statistical methods for analysis of single-cell variabilityR01HL131768 · NHLBI · HARVARD MEDICAL SCHOOL · PI KHARCHENKO, PETER V · 2015 to 2019
$2.4M
NHLBI NIH HHS R01 HL131768
6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer in adults. When ccRCC is localized to the kidney, surgical resection or ablation of the tumor is often curative. However, in the metastatic setting, ccRCC remains a highly lethal disease. Here we use fresh patient samples that include treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. Single-cell transcriptomic analysis of tumor cells from the primary tumors reveals a distinct transcriptional signature that is predictive of metastatic potential and patient survival. Analysis of supporting stromal cells within the tumor environment demonstrates vascular remodeling within the endothelial cells. An in silico cell-to-cell interaction analysis highlights the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets. Our findings provide biological insights into the interplay between tumor cells and the ccRCC microenvironment.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsAdultEndothelial CellsHumansKidneyTranscriptomeTumor Microenvironment

Identifiers

PMID36180422
PMCPMC9525645
OpenAlexW4298140233

What OpenQuestion holds

Textmetadata
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.