Evidence mapPaperPMID 35359606Full record

ArticleFrontiers in molecular biosciences2022

Gene Expression-Based Signature Can Predict Sorafenib Response in Kidney Cancer.

Alexander Gudkov, Valery Shirokorad, Kirill Kashintsev, Dmitriy Sokov, Daniil Nikitin, Andrey Anisenko, Nicolas Borisov, Marina Sekacheva, Nurshat Gaifullin, Andrew Garazha and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2022. 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
2.3field-weighted citation impact, top 11% 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, 15 citations in OpenAlex.

  1. Article
  2. Observational
  3. Review
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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

14 authors at 5 institutions in 2 countries.

Alexander GudkovI. M. Sechenov First Moscow State Medical University, Moscow, Russia.
Valery ShirokoradMoscow City Oncological Hospital №. 62, Moscow, Russia.
Kirill KashintsevMoscow City Oncological Hospital №. 62, Moscow, Russia.
Dmitriy SokovMoscow City Clinical Oncological Dispensary №. 1, Moscow, Russia.
Daniil NikitinOncobox Ltd., Moscow, Russia.
Andrey AnisenkoOncobox Ltd., Moscow, Russia.
Nicolas BorisovMoscow Institute of Physics and Technology, Moscow, Russia.
Marina SekachevaWorld-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia.
Nurshat GaifullinDepartment of Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow, Russia.
Andrew GarazhaOmicsWay Corp, Walnut, CA, United States.
Maria SuntsovaWorld-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia.
Elena KorolevaMoscow Institute of Physics and Technology, Moscow, Russia.
Anton BuzdinMoscow Institute of Physics and Technology, Moscow, Russia.
Maksim SorokinI. M. Sechenov First Moscow State Medical University, Moscow, Russia.
Sechenov University · RUMoscow City Oncology Hospital №62 · RUMoscow Institute of Physics and Technology · RUEuropean Organisation for Research and Treatment of Cancer · BELomonosov Moscow State University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sorafenib is a tyrosine kinase inhibitory drug with multiple molecular specificities that is approved for clinical use in second-line treatments of metastatic and advanced renal cell carcinomas (RCCs). However, only 10-40% of RCC patients respond on sorafenib-containing therapies, and personalization of its prescription may help in finding an adequate balance of clinical efficiency, cost-effectiveness, and side effects. We investigated whether expression levels of known molecular targets of sorafenib in RCC can serve as prognostic biomarker of treatment response. We used Illumina microarrays to profile RNA expression in pre-treatment formalin-fixed paraffin-embedded (FFPE) samples of 22 metastatic or advanced RCC cases with known responses on next-line sorafenib monotherapy. Among them, nine patients showed partial response (PR), three patients-stable disease (SD), and 10 patients-progressive disease (PD) according to Response Evaluation Criteria In Solid Tumors (RECIST) criteria. We then classified PR + SD patients as "responders" and PD patients as "poor responders". We found that gene signature including eight sorafenib target genes was congruent with the drug response characteristics and enabled high-quality separation of the responders and poor responders [area under a receiver operating characteristic curve (AUC) 0.89]. We validated these findings on another set of 13 experimental annotated FFPE RCC samples (for 2 PR, 1 SD, and 10 PD patients) that were profiled by RNA sequencing and observed AUC 0.97 for 8-gene signature as the response classifier. We further validated these results in a series of qRT-PCR experiments on the third experimental set of 12 annotated RCC biosamples (for 4 PR, 3 SD, and 5 PD patients), where 8-gene signature showed AUC 0.83.

Indexed as

gene signaturekidney cancermicroarray profilingmRNA expressionrenal cell carcinomaRNA sequencingsorafenib responsetyrosine kinase inhibitor

Identifiers

PMID35359606
PMCPMC8963850
OpenAlexW4220940423

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.