Evidence map›Paper›PMID 36776840›Full record

ReviewFrontiers in immunology2023

Immunotherapy with immune checkpoint inhibitors and predictive biomarkers in malignant mesothelioma: Work still in progress.

Matteo Perrino, Fabio De Vincenzo, Nadia Cordua, Federica Borea, Marta Aliprandi, Armando Santoro, Paolo Andrea Zucali

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

24 citing papers in PubMed, 26 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Dual-time-point [EJNMMI research · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Immunotherapy advances in pleural mesothelioma.Therapeutic advances in medical oncology · 2026
    Review
  10. Article
  11. Review
  12. CDKN2A deletion is associated with immune desertification in diffuse pleural mesothelioma.Journal of experimental & clinical cancer research : CR · 2025
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
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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

7 authors at 3 institutions in 1 country.

Matteo PerrinoDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
Fabio De VincenzoDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
Nadia CorduaDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
Federica BoreaDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
Marta AliprandiDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
Armando SantoroDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
Paolo Andrea ZucaliDepartment of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Milan, Italy.
IRCCS Humanitas Research Hospital · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITHumanitas University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Malignant mesothelioma (MM) is a rare and aggressive neoplasm, usually associated with a poor prognosis (5 years survival rate <10%). For unresectable disease, platinum and pemetrexed chemotherapy has been the only standard of care in first line for more than two decades, while no standard treatments have been approved in subsequent lines. Recently, immunotherapy has revolutionized the therapeutic landscape of MM. In fact, the combination of ipilimumab plus nivolumab has been approved in first line setting. Moreover, immune checkpoint inhibitors (ICIs) showed promising results also in second-third line setting after platinum-based chemotherapy. Unfortunately, approximately 20% of patients are primary refractory to ICIs and there is an urgent need for reliable biomarkers to improve patient's selection. Several biological and molecular features have been studied for this goal. In particular, histological subtype (recognized as prognostic factor for MM and predictive factor for chemotherapy response), programmed death ligand 1 (PD-L1) expression, and tumor mutational burden (widely hypothesized as predictive biomarkers for ICIs in several solid tumors) have been evaluated, but with unconclusive results. On the other hand, the deep analysis of tumor infiltrating microenvironment and the improvement in genomic profiling techniques has led to a better knowledge of several mechanisms underlying the MM biology and a greater or poorer immune activation. Consequentially, several potential biomarkers predictive of response to immunotherapy in patients with MM have been identified, also if all these elements need to be further investigated and prospectively validated. In this paper, the main evidences about clinical efficacy of ICIs in MM and the literature data about the most promising predictive biomarkers to immunotherapy are reviewed.

Indexed as

Lung NeoplasmsMesothelioma, MalignantBiomarkers, TumorHumansImmune Checkpoint InhibitorsImmunotherapyNivolumabTumor MicroenvironmentBiomarkers, TumorImmune Checkpoint InhibitorsNivolumabbiomarkersimmune checkpoint inhibitorsimmunotherapymalignant mesotheliomapredictive of response

Identifiers

PMID36776840
PMCPMC9911663
OpenAlexW4318200601

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.