bims-mesote Biomed News
on Mesothelioma
Issue of 2023‒10‒15
four papers selected by
Laura Mannarino, Humanitas Research



  1. Gene Ther. 2023 Oct 13.
      Dry gene powder is a novel non-viral gene-delivery system, which is inhalable with high gene expression. Previously, we showed that the transfection of p16INK4a or TP53 by dry gene powder resulted in growth inhibitions of lung cancer and malignant pleural mesothelioma (MPM) in vitro and in vivo. Here, we report that dry gene powder containing p53- expression-plasmid DNA enhanced the therapeutic effects of cisplatin (CDDP) against MPM even in the presence of endogenous p53. Furthermore, our results indicated that the safe transfection with a higher plasmid DNA (pDNA) concentration suppressed MPM growth independently of chemotherapeutic agents. To develop a new therapeutic alternative for MPM patients without safety concerns over "vector doses", our in vitro data provide basic understandings for dry gene powder.
    DOI:  https://doi.org/10.1038/s41434-023-00424-y
  2. J Environ Pathol Toxicol Oncol. 2024 ;43(1): 31-44
      Malignant pleural mesothelioma (MPM) is rare and aggressive cancer. The most important risk factor for MPM is exposure to asbestos. In this study, we scanned the genomes of individuals MPM and asbestos-induced chronic pleuritis (AICP) to compare and determine copy number alterations (CNAs) between two asbestos-related diseases. We used high-resolution SNP arrays to compare CNA profiles between MPM (n = 55) and AICP (n = 18). DNAs extracted from pleural tissues in both groups. SNP array analysis revealed common losses at 1p, 3p, 6q, 9p, 13q, 14q, 15q, 16q, 22q and frequent gains at chromosomes 1, 3, 5, 7, 8, and 6p, 12q, 15q, 17p, 20q in MPMs (frequencies max 67%-min 30%; these alterations were not detected in AICPs. Besides detecting well-known MPM-associated CNAs, our high -resolution copy number profiling also detected comparatively rare CNAs for MPMs including losses like 9q33.3, 16q and gains of 1p, 1q, 3p, 3q, 6p, 7q, 15q, 12q, 17p, 20q at significant frequencies in the MPM cohort. We also observed Copy Number gains clustered on the NF2 locus in AICPs, whereas this region was commonly deleted in MPMs. According to this distinct genomic profiles between the two groups, AICPs genomes can be clearly distinguished from highly altered MPM genomes. Hence, we can suggest that SNP arrays can be used as a supporting diagnostic tool in terms of discriminating asbestos-related malignant disease such as MPM and benign pleural lesions, which can be challenging in most instances.
    DOI:  https://doi.org/10.1615/JEnvironPatholToxicolOncol.2023047755
  3. Mol Cancer Ther. 2023 Oct 07.
      Few treatment options exist for pleural mesothelioma (PM), which is a progressive malignant tumor. However, the efficacy of molecular-targeted monotherapy is limited, and further therapeutic strategies are warranted to treat PM. Recently, the cancer cell cycle checkpoint inhibitors have attracted attention because they disrupt cell cycle regulation. Here, we aimed to establish a novel combinational therapeutic strategy to inhibit the cell cycle checkpoint kinase, ataxia telangiectasia and Rad3-related protein (ATR) in PM cells. The siRNA screening assay showed that anexelekto (AXL) knockdown enhanced cell growth inhibition when exposed to ATR inhibitors, demonstrating the synergistic effects of the ATR and AXL combination in some PM cells. The AXL and ATR inhibitor combination increased cell apoptosis via the Bim protein and suppressed cell migration when compared to each monotherapy. The combined therapeutic targeting of AXL and ATR significantly delayed regrowth compared with monotherapy. Thus, optimal AXL and ATR inhibition may potentially improve the PM outcome.
    DOI:  https://doi.org/10.1158/1535-7163.MCT-23-0138
  4. Cell Rep Med. 2023 Oct 05. pii: S2666-3791(23)00403-2. [Epub ahead of print] 101226
      Mesothelioma is classified into three histological subtypes, epithelioid, sarcomatoid, and biphasic, according to the relative proportions of epithelioid and sarcomatoid tumor cells present. Current guidelines recommend that the sarcomatoid component of each mesothelioma is quantified, as a higher percentage of sarcomatoid pattern in biphasic mesothelioma shows poorer prognosis. In this work, we develop a dual-task graph neural network (GNN) architecture with ranking loss to learn a model capable of scoring regions of tissue down to cellular resolution. This allows quantitative profiling of a tumor sample according to the aggregate sarcomatoid association score. Tissue is represented by a cell graph with both cell-level morphological and regional features. We use an external multicentric test set from Mesobank, on which we demonstrate the predictive performance of our model. We additionally validate our model predictions through an analysis of the typical morphological features of cells according to their predicted score.
    Keywords:  cancer subtyping; digital pathology; graph neural networks; mesothelioma; multiple instance learning
    DOI:  https://doi.org/10.1016/j.xcrm.2023.101226