Evidence map›Paper›PMID 32903369›Full record

ReviewFrontiers in oncology2020

Predictive Biomarkers of Response to Immunotherapy in Metastatic Renal Cell Cancer.

Alessandra Raimondi, Pierangela Sepe, Emma Zattarin, Alessia Mennitto, Marco Stellato, Melanie Claps, Valentina Guadalupi, Elena Verzoni, Filippo de Braud, Giuseppe Procopio

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
4.9field-weighted citation impact, top 4% 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

42 citing papers in PubMed, 77 citations in OpenAlex.

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  12. Management of Renal Cell Carcinoma: Promising Biomarkers and the Challenges to Reach the Clinic.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    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

10 authors at 1 institution in 1 country.

Alessandra RaimondiDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Pierangela SepeDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Emma ZattarinDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Alessia MennittoDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Marco StellatoDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Melanie ClapsDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Valentina GuadalupiDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Elena VerzoniDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Filippo de BraudDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Giuseppe ProcopioDepartment of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Fondazione IRCCS Istituto Nazionale dei Tumori · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn the last decades, the therapeutic decision-making approach to metastatic renal cell cancer (mRCC) has dramatically changed thanks to the introduction in the treatment scenario of, first, anti-angiogenic agents and, afterward, immune-checkpoint inhibitors (ICIs). Immunotherapy is now the standard of care in pretreated mRCC patients and has recently entered even the first line setting. Nevertheless, in mRCC as well as in other tumor settings, a durable and clinically meaningful benefit from treatment with ICIs is not obtained for all patients treated. Therefore, the necessity to identify and validate predictive biomarkers of response to immunotherapy has emerged, in order to design the optimal treatment strategy for mRCC patients. DISCUSSION: In this review, we present and discuss the most promising predictive biomarkers of response to ICIs in mRCC with the recent data available. In details, the first marker that was investigated is the immunohistochemical expression of programmed death receptor ligand 1 (PD-L1), showing a negative prognostic role in mRCC, but the debate about its potential predictive value is still open. Additionally, the high heterogeneity in PD-L1 determination methods adds complexity to this issue. Second, the tumor mutational or neoantigen burden is an emerging biomarker of increased response to immunotherapy, hypothesizing that the higher the TMB, the higher is the production of neoantigens, and thus the stimulation of anti-tumor immune response, even though controversial results have been obtained. Third, the tumor microenvironment, namely the different populations of the immune infiltrate, plays a key role in tumor progression and in the response to immunotherapy. Finally, several studies have collected evidence on the potential association of the occurrence of immune-related adverse events (irAEs) with the benefit from ICIs, first in non-small cell lung cancer (NSCLC) and melanoma, and recently even in mRCC.

conclusionSeveral promising biomarkers of response to immunotherapy with ICIs have been identified, though without conclusive results upon their potential predictive value in mRCC. Therefore, the results of the exploratory analyses of the recently presented first-line trials and hopefully of future prospective, biomarker-driven studies could provide useful tools to be applied in the everyday clinical practice.

Indexed as

biomarkerimmunotherapymetastasesPD-L1renal cell carcinomatumor mutational burden

Identifiers

PMID32903369
PMCPMC7434861
OpenAlexW3048690183

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.