bims-mesote Biomed News
on Mesothelioma
Issue of 2026–04–12
five papers selected by
Laura Mannarino, Humanitas Research



  1. Surg Neurol Int. 2026 ;17 155
       Background: Pleural mesothelioma (PM) is a tumor of the pleural epithelium with a poor prognosis. Asbestos exposure is closely related to its occurrence. To date, there have been 13 reports of PM with intradural invasion.
    Case Description: A 73-year-old male was admitted with rapid progression of back pain and paraparesis. At age 67, he was diagnosed with PM (epithelial type) and underwent chemotherapy and a left thoracotomy for tumor resection. At present, the magnetic resonance newly showed T7-T9 spinal cord compressed due to an intradural tumor. Originating from the left pleura and invading the spinal canal through the intervertebral foramina, the lesion was subtotally resected. Histology confirmed that the intradural tumor lesion was a PM (biphasic type) that had transformed into a malignant tumor. Postoperatively, the patient's paraparesis improved. Despite the administration of adjuvant chemotherapy, the tumor showed regrowth 5 months later; further treatment was purely palliative care.
    Conclusion: In general, patients with PM have a poor prognosis. However, those with some favorable factors (i.e., epithelioid subtype, female sex, and early clinical stage) may survive for up to 5-years.
    Keywords:  Intradural invasion; Late recurrence; Metastatic tumor; Pleural mesothelioma; Thoracic spine
    DOI:  https://doi.org/10.25259/SNI_68_2026
  2. J Thorac Oncol. 2026 Apr 08. pii: S1556-0864(26)00173-5. [Epub ahead of print] 103720
      Diffuse Mesothelioma is typically diagnosed through histopathologic evaluation. Recent advances in therapeutic strategies have heightened the importance of accurate diagnosis and subtyping. In addition to the three well-established histological subtypes of mesothelioma (epithelioid, biphasic and sarcomatoid), the 2021 WHO classification of diffuse pleural mesothelioma [DPM] emphasizes the importance of subtyping patterns and cytological features to improve clinical diagnosis and patient management. Notably, the presence of a solid component or pleomorphic cytological features observed within the epithelioid subtype is associated with a worse prognosis, approaching that of a sarcomatoid mesothelioma. Conversely, cases with abundant myxoid stroma and a solid component comprising less than 50% are associated with an improved survival. In addition, a two-tiered grading system (low vs. high grade) is now recommended for epithelioid mesothelioma. On behalf of IASLC Mesothelioma Sub-Committee of the Rare Tumor Group and Pathology Committee, we herein outline what is new to assist clinicians essential for optimizing the management of patients with mesothelioma. This includes practical questions on immunohistochemical and molecular markers BAP1, MTAP, NF2 and fusion genes, that are relevant to the diagnosis, prognosis and application of emerging therapeutic strategies in DPM. This discussion also addresses frequently asked questions by clinicians regarding sampling modalities aimed at optimizing diagnostic accuracy. The impact of epigenetics, DNA methylation and biomarker discovery is highlighted, with an emphasis on its limitations in distinguishing mesothelioma versus reactive mesothelial proliferations and other neoplastic mimics. The emerging role of Artificial Intelligence in subtyping, grading and prediction of biomarkers for genomic subtyping is also discussed. [251 words].
    DOI:  https://doi.org/10.1016/j.jtho.2026.103720
  3. JTO Clin Res Rep. 2026 Apr;7(4): 100968
       Introduction: Brain metastases (BrMs) are poorly studied and likely underreported in diffuse pleural mesothelioma (DPM), limiting understanding of risk factors associated with their development. We evaluated the genomic, histologic, and clinical landscapes of patients with DPM and BrMs.
    Methods: We retrospectively reviewed all patients with a mesothelioma diagnosis treated at the Memorial Sloan Kettering Cancer Center between January 1, 2010, and May 1, 2025, with cross-sectional brain imaging. Clinicopathologic data and treatment outcomes were annotated for patients with BrMs.
    Results: Among 194 patients with mesothelioma and brain imaging, 16 (8%) had BrMs. Half (n = 8) had tumors of epithelioid histology, 44% (n = 7) biphasic, and 6% (n = 1) sarcomatoid. Compared with our DPM cohort regardless of BrMs (n = 194) or a DPM cohort from The Cancer Genome Atlas (n = 74), patients with DPM and BrMs had a higher prevalence of LATS2 alterations (46% versus 7% versus 12%, respectively [p < 0.00001]). BrMs were typically (88%, n = 14) diagnosed after neurologic symptoms prompting imaging. Among patients with BrMs, the median overall survival from initial mesothelioma diagnosis was 35.4 (95% confidence interval, 19.3-not reached) months and 3.7 (95% confidence interval, 3.5-not reached) months from BrM diagnosis.
    Conclusions: Our findings suggest that BrM develops relatively late in DPM, is more common than previously reported, and may be enriched in patients with LATS2 alterations. Prospective, multi-institutional studies with standardized brain imaging are needed to further characterize the incidence of BrMs in DPM and associated risk factors. Routine brain surveillance at diagnosis and with symptoms should be considered for patients with DPM.
    Keywords:  Brain metastases; Diffuse pleural mesothelioma; Genomics; Mesothelioma
    DOI:  https://doi.org/10.1016/j.jtocrr.2026.100968
  4. Cell Death Dis. 2026 Apr 10.
      Pleural Mesothelioma (PM) is an aggressive neoplasm of the lung pleura with poor survival rates, highlighting the urgent need for novel therapeutic options. The CDK4/6 inhibitors abemaciclib and palbociclib have demonstrated promising results in patient-derived xenograft models of PM. In this study, we observed that palbociclib reduced proliferation, leading to increased cell size, enhanced SA-β-galactosidase activity, and elevated secretion of IL-6 and IL-8 (SASP), all of which are hallmarks of senescence. However, upon drug removal, the cells regrew. To enhance therapeutic efficacy, we attempted to induce cell death in palbociclib-pretreated PM cells with conventional senolytics, such as BH3 mimetics. While some cells showed sensitivity to Bcl-xL inhibitors, neither navitoclax nor the specific Bcl-xL inhibitor A-1331852, nor other BH3 mimetics targeting Bcl-2 (venetoclax) or Mcl-1 (S63845) increased cell death when combined with palbociclib. We explored the activity of signalling pathways after treatment with palbociclib and identified higher Src and STAT3 phosphorylation, as well as activation of the mTORC1 axis. Therefore, we employed inhibitors of these pathways, such as dasatinib, momelotinib or Torin-1, which did not synergise with palbociclib to kill the cells. In contrast, we found that the chemotherapeutic drug cisplatin induces permanent cell cycle arrest and complete senescence in PM cells. While both drugs increased the phosphorylation of γH2AX, the effects of cisplatin were stronger and more consistent across cell lines. The differential effects of palbociclib and cisplatin on permanent growth arrest were verified by sorting PM cells based on size and β-galactosidase activity. Our findings underscore the importance of understanding the nature of therapy-induced senescence when assessing the effectiveness of senolytics in different tumour models.
    DOI:  https://doi.org/10.1038/s41419-026-08696-z
  5. Pathologica. 2026 Feb;118(1): 12-19
       Objective: To develop and validate a deep learning model trained on reticulin-stained whole slide images (MesoRet) to accurately identify transitional features and assist in the histologic subtyping of diffuse mesothelioma.
    Methods: A total of 115 cases of diffuse mesothelioma were collected from two institutions and reviewed by expert thoracic pathologists. Reticulin-stained whole-slide images were used to train a supervised deep learning model on the Aiforia Create platform to distinguish epithelioid, sarcomatoid, and transitional patterns. Model performance was validated on independent slides and compared with expert pathologists' assessments.
    Results: MesoRet accurately identified reticulin patterns across mesothelioma histotypes achieving 96.32% precision and 99.06% sensitivity, excluding artifacts and non-tumour tissue. It outperformed pathologists in identifying transitional patterns, reducing diagnostic time and minimising errors.
    Conclusions: MesoRet provides an accurate and objective approach for detecting reticulin patterns in mesothelioma, supporting histological subtyping and contributing to more consistent diagnoses. Although further validation is required, it represents a promising model to improve diagnostic precision and guide therapeutic decision-making.
    Keywords:  computational pathology.; deep learning; diffuse mesothelioma; reticulin stain; transitional mesothelioma
    DOI:  https://doi.org/10.32074/1591-951X-1583