Evidence map›Paper›PMID 30450335›Full record

ReviewFrontiers in oncology2018

The Identification of Immunological Biomarkers in Kidney Cancers.

Antonio Lopez-Beltran, Vanessa Henriques, Alessia Cimadamore, Matteo Santoni, Liang Cheng, Thomas Gevaert, Ana Blanca, Francesco Massari, Marina Scarpelli, Rodolfo Montironi

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
4.6field-weighted citation impact, top 5% 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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 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

10 authors at 8 institutions in 5 countries.

Antonio Lopez-BeltranDepartment of Pathology and Surgery, Faculty of Medicine, Cordoba University, Cordoba, Spain.
Vanessa HenriquesPathology Service, Champalimaud Clinical Center, Lisbon, Portugal.
Alessia CimadamoreSection of Pathological Anatomy, United Hospital, School of Medicine, Polytechnic University of the Marche Region, Ancona, Italy.
Matteo SantoniOncology Unit, Macerata Hospital, Macerata, Italy.
Liang ChengDepartment of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.
Thomas GevaertLaboratory of Experimental Urology, Organ Systems, KU Leuven, Leuven, Belgium.
Ana BlancaInstituto Maimonides de Investigación Biomédica de Córdoba, Córdoba, Spain.
Francesco MassariDivision of Oncology, S. Orsola-Malpighi Hospital, Bologna, Italy.
Marina ScarpelliSection of Pathological Anatomy, United Hospital, School of Medicine, Polytechnic University of the Marche Region, Ancona, Italy.
Rodolfo MontironiSection of Pathological Anatomy, United Hospital, School of Medicine, Polytechnic University of the Marche Region, Ancona, Italy.
Marche Polytechnic University · ITAZ Klina · BEChampalimaud Foundation · PTIndiana University School of MedicineInstituto Maimónides de Investigación Biomédica de Córdoba · ESIRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola · ITOspedale di MacerataUniversity of Córdoba · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent approval of several agents have revolutionized the scenario of therapeutic management of metastatic renal cell carcinoma (RCC) allowing us to reach important clinical end points with extended patients' survival. Actually, every new drug approved has represented an important step forward to the improvement of patient's survival. On the other hand, we now understand that RCC includes a large group of tumor entities, each of them with different genetic and mutational alterations, but also showing different clinical behavior; a reason behind the needs of subtype specific personalized approach to therapy of RCC. Immunotherapy is gradually becoming a key factor in the therapeutic algorithm for patients with locally advanced or metastatic RCC. Due to the combination of potent treatment success and potentially deadly adverse effects from immune checkpoint inhibitors (ICI), gathering prognostic and predictive information about FDA-indicated tumors seems to be prudent. Robust and reliable biomarkers are crucial for patient's selection of treatments with immunomodulatory drugs. PD-L1 expression is a poor prognostic factor and predictive of better responses from both PD-1 and PD-L1 inhibitors in a variety of tumor types including RCC. Each FDA approved PD-1/PD-L1 drug is paired with a PD-L1 Immunohistochemistry (IHC) assay. Thus, there is need for improved knowledge and application of PD-1/PD-L1 IHC biomarkers in daily practice. IHC staining appears in membranous fashion. The atezolizumab approved IHC assay is unique in that only immune cell staining is quantified for the use of this assay in RCC. A single biomarker for patient selection may not be feasible, given that immune responses are dynamic and evolve over time. Biomarker development for ICI drugs will likely require integration of multiple biologic components like PD-L1 expression, TILs and mutational load. New methodological approaches based on digital pathology may be relevant since they will allow recognition of the biomarker and to objectively quantitate its expression, and therefore might produce objective and reproducible cut-off assessment. Multidisciplinary approach is very much needed to fully develop the current and future value of ICI in clinical practice.

Indexed as

immunological biomarkerimmunotherapyPD-L1predictive biomarkerRCC subtypesrenal cell carcinomatumor mutation load

Identifiers

PMID30450335
PMCPMC6225533
OpenAlexW2898662678

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.