Biomarkers and Targeted Therapy in Malignant Pleural Mesothelioma

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 1125

Special Issue Editor


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Guest Editor
Medical Oncology Department, Vall d'Hebron Institute of Oncology (VHIO), Vall d’Hebron Hospital Universitari, 08035 Barcelona, Spain
Interests: malignant mesothelioma; target therapy; lung cancer; immunotherapy
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Special Issue Information

Dear Colleagues,

As the Guest Editors of the Special Issue below, I would like to invite you or one of your colleagues to contribute an original research or review article that addresses the topic of “Biomarkers and Targeted Therapy in Malignant Pleural Mesothelioma”.

Malignant pleural mesothelioma is a rare tumor associated with asbestos exposure. Treatment options are limited to date, with a median survival of about 18 months. Treatment with immunotherapy improves survival, but not all patients respond to immunotherapy, and those who do will relapse. Up until now, immunotherapy-predictive biomarkers used in other tumors have not demonstrated a clear predictive role in MPM (TMB, PD-L1). However, histology, in first-line treatment, does seem to have a predictive role in response to treatment.

Moreover, numerous genomic and transcriptomic studies have identified recurrent molecular alterations in MPM (BAP1, CDKN2a, MTAP). Despite this, there are no approved targeted therapies for the most frequent alterations. On the other hand, chromosomal alterations such as chromoptisis seem to play a predictive role in response to immunotherapy.

The aim of this review is to evaluate the possible predictive factors of responses to approved treatments (histology, TMB, PD-L1) and the genomic and transcriptomic alterations that occur in patients with MPM (BAP1, CDKN2a, MTAP...), placing them in the context of possible treatments.

Based on your expertise in this field, we would like to invite you to contribute with a review for a full research paper or an original manuscript for peer review and possible publication in this Special Issue.

I hope that this invitation receives your favorable consideration. We look forward to our future collaboration.

Best wishes,

Dr. Susana Cedrés
Guest Editor

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Keywords

  • malignant mesothelioma
  • target therapy
  • biomarkers

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Published Papers (1 paper)

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Research

18 pages, 3633 KiB  
Article
Radiomics-Based Prediction of Treatment Response to TRuC-T Cell Therapy in Patients with Mesothelioma: A Pilot Study
by Hubert Beaumont, Antoine Iannessi, Alexandre Thinnes, Sebastien Jacques and Alfonso Quintás-Cardama
Cancers 2025, 17(3), 463; https://doi.org/10.3390/cancers17030463 - 29 Jan 2025
Viewed by 858
Abstract
Background/Objectives: T cell receptor fusion constructs (TRuCs), a next generation engineered T cell therapy, hold great promise. To accelerate the clinical development of these therapies, improving patient selection is a crucial pathway forward. Methods: We retrospectively analyzed 23 mesothelioma patients (85 target tumors) [...] Read more.
Background/Objectives: T cell receptor fusion constructs (TRuCs), a next generation engineered T cell therapy, hold great promise. To accelerate the clinical development of these therapies, improving patient selection is a crucial pathway forward. Methods: We retrospectively analyzed 23 mesothelioma patients (85 target tumors) treated in a phase 1/2 single arm clinical trial (NCT03907852). Five imaging sites were involved, the settings for the evaluations were Blinded Independent Central Reviews (BICRs) with double reads. The reproducibility of 3416 radiomics and delta-radiomics (Δradiomics) was assessed. The univariate analysis evaluated correlations at the target tumor level with (1) tumor diameter response; (2) tumor volume response, according to the Quantitative Imaging Biomarker Alliance; and (3) the mean standard uptake value (SUV) response, as defined by the positron emission tomography response criteria in solid tumors (PERCISTs). A random forest model predicted the response of the target pleural tumors. Results: Tumor anatomical distribution was 55.3%, 17.6%, 14.1%, and 10.6% in the pleura, lymph nodes, peritoneum, and soft tissues, respectively. Radiomics/Δradiomics reproducibility differed across tumor localizations. Radiomics were more reproducible than Δradiomics. In the univariate analysis, none of the radiomics/Δradiomics correlated with any response criteria. With an accuracy ranging from 0.75 to 0.9, three radiomics/Δradiomics were able to predict the response of target pleural tumors. Pivotal studies will require a sample size of 250 to 400 tumors. Conclusions: The prediction of responding target pleural tumors can be achieved using a machine learning-based radiomics/Δradiomics analysis. Tumor-specific reproducibility and the average values indicated that using tumor models to create an effective patient model would require combining several target tumor models. Full article
(This article belongs to the Special Issue Biomarkers and Targeted Therapy in Malignant Pleural Mesothelioma)
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