bims-mesote Biomed News
on Mesothelioma
Issue of 2023–08–13
eight papers selected by
Laura Mannarino, Humanitas Research
  1. Editorial: Focus on malignant pleural mesothelioma immunology and immunotherapy.
  2. Longitudinal monitoring of response to chemotherapy in patients with malignant pleural mesothelioma by biomarkers.
  3. Predicting Overall Survival for Patients with Malignant Mesothelioma Following Radiotherapy via Interpretable Machine Learning.
  4. Primary and hTERT-Transduced Mesothelioma-Associated Fibroblasts but Not Primary or hTERT-Transduced Mesothelial Cells Stimulate Growth of Human Mesothelioma Cells.
  5. Results of the Meso-ORIGINS feasibility study regarding collection of matched benign-mesothelioma tissue pairs by longitudinal surveillance.
  6. Brief report: Meta-analysis on chemotherapy and PD-(L)1 blockade combination as first-line treatment for unresectable pleural mesothelioma.
  7. The IASLC Pleural Mesothelioma Staging Project: Updated Modeling of Prognostic Factors in Pleural Mesothelioma.
  8. Cancer-Associated Fibroblasts Influence Survival in Pleural Mesothelioma: Digital Gene Expression Analysis and Supervised Machine Learning Model.
  1. Front Immunol. 2023 ;14 1251384
    Editorial: Focus on malignant pleural mesothelioma immunology and immunotherapy.
    Chiara Porta, Didier Jean, Christophe Blanquart.
      
    Keywords:  eosinophils; immune checkpoint inhibitors; mesothelioma; microbiota; oncolytic vaccinia virus; osteopontin; predictive biomarkers; tumor microenvironment
    DOI:  https://doi.org/10.3389/fimmu.2023.1251384
  2. Cancer Biomark. 2023 Jul 17.
    Longitudinal monitoring of response to chemotherapy in patients with malignant pleural mesothelioma by biomarkers.
    Filiz Bogar, Guntulu Ak, Selma Metintas, Adnan Ayhanci, Muzaffer Metintas.
       BACKGROUND: The aim of the study was to longitudinally investigate the serum levels of mesothelin, sestrin1, hyaluronan synthase 2 (HAS2), midkine, and high mobility group box 1 (HMGB1) before and after chemotherapy and at the time of relapse in malignant pleural mesothelioma (MPM) patients treated with chemotherapy and to compare the changes in biomarker levels with radiological treatment outcome.
    METHODS: A total of 64 MPM patients treated with chemotherapy were enrolled in the study and longitudinally followed for changes in biomarker levels in response to treatment. Biomarkers evels were measured in serum using a human ELISA kit. Relative and absolute changes in biomarker levels were compared with the best radiological overall response at each time point.
    RESULTS: Median survival was 20.0 ± 2.4 (15.3-24.7) months in patients with partial and complete response, 17.0 ± 1.0 (15.0-19.0) months in patients with stable disease, and 9.0 ± 1.0 (7.0-11.0) months in patients with progressive disease. A significant decrease in serum levels of mesothelin, midkine, and HMGB1 was observed in patients with radiologically partial and complete responses to chemotherapy (p< 0.001, p= 0.016, and p= 0.039, respectively). In these patients, mesothelin levels decreased by 15%, midkine levels by 7%, and HMGB1 levels by 15%. In addition, HMGB1 serum levels were found to significantly increase by 15% in patients with radiologically progressive responses to chemotherapy compared to pretreatment serum levels (p= 0.035). In patients with partial and complete response to chemotherapy, mesothelin levels increased by 15%, midkine by 12%, and sestrin1 by 8% when the disease recurred (p= 0.004, p= 0.004 and p= 0.044, respectively).
    CONCLUSION: Biomarkers may be useful in the longitudinal monitoring of response to treatment in MPM. However, the results of our study should be validated in larger groups with sufficient case numbers from multicenter institutions.
    Keywords:  HMGB1; Mesothelioma; chemotherapy response; mesothelin; midkine
    DOI:  https://doi.org/10.3233/CBM-220436
  3. Cancers (Basel). 2023 Aug 01. pii: 3916. [Epub ahead of print]15(15):
    Predicting Overall Survival for Patients with Malignant Mesothelioma Following Radiotherapy via Interpretable Machine Learning.
    Zitian Wang, Vincent R Li, Fang-I Chu, Victoria Yu, Alan Lee, Daniel Low, Drew Moghanaki, Percy Lee, X Sharon Qi.
       PURPOSE/OBJECTIVES: Malignant pleural mesothelioma (MPM) is a rare but aggressive cancer arising from the cells of the thoracic pleura with a poor prognosis. We aimed to develop a model, via interpretable machine learning (ML) methods, predicting overall survival for MPM following radiotherapy based on dosimetric metrics as well as patient characteristics.
    MATERIALS/METHODS: Sixty MPM (37 right, 23 left) patients treated on a Tomotherapy unit between 2013 and 2018 were retrospectively analyzed. All patients received 45 Gy (25 fractions). The multivariable Cox regression (Cox PH) model and Survival Support Vector Machine (sSVM) were applied to build predictive models of overall survival (OS) based on clinical, dosimetric, and combined variables.
    RESULTS: Significant differences in dosimetric endpoints for critical structures, i.e., the lung, heart, liver, kidney, and stomach, were observed according to target laterality. The OS was found to be insignificantly different (p = 0.18) between MPM patients who tested left- and right-sided, with 1-year OS of 77.3% and 75.0%, respectively. With Cox PH regression, considering dosimetric variables for right-sided patients alone, an increase in PTV_Min, Total_Lung_PTV_Mean, Contra_Lung_Volume, Contra_Lung_V20, Esophagus_Mean, and Heart_Volume had a greater hazard to all-cause death, while an increase in Total_Lung_PTV_V20, Contra_Lung_V5, and Esophagus_Max had a lower hazard to all-cause death. Considering clinical variables alone, males and increases in N stage had greater hazard to all-cause death; considering both clinical and dosimetric variables, increases in N stage, PTV_Mean, PTV_Min, and esophagus_Mean had greater hazard to all-cause death, while increases in T stage and Heart_V30 had lower hazard to all-cause-death. In terms of C-index, the Cox PH model and sSVM performed similarly and fairly well when considering clinical and dosimetric variables independently or jointly.
    CONCLUSIONS: Clinical and dosimetric variables may predict the overall survival of mesothelioma patients, which could guide personalized treatment planning towards a better treatment response. The identified predictors and their impact on survival offered additional value for translational application in clinical practice.
    Keywords:  interpretable machine learning; mesothelioma; outcome prediction and assessment; overall survival; radiation therapy
    DOI:  https://doi.org/10.3390/cancers15153916
  4. Cells. 2023 Aug 05. pii: 2006. [Epub ahead of print]12(15):
    Primary and hTERT-Transduced Mesothelioma-Associated Fibroblasts but Not Primary or hTERT-Transduced Mesothelial Cells Stimulate Growth of Human Mesothelioma Cells.
    Alexander Ries, Astrid Slany, Christine Pirker, Johanna C Mader, Doris Mejri, Thomas Mohr, Karin Schelch, Daniela Flehberger, Nadine Maach, Muhammad Hashim, Mir Alireza Hoda, Balazs Dome, Georg Krupitza, Walter Berger, Christopher Gerner, Klaus Holzmann, Michael Grusch.
      Pleural mesothelioma (PM) is an aggressive malignancy that develops in a unique tumor microenvironment (TME). However, cell models for studying the TME in PM are still limited. Here, we have generated and characterized novel human telomerase reverse transcriptase (hTERT)-transduced mesothelial cell and mesothelioma-associated fibroblast (Meso-CAF) models and investigated their impact on PM cell growth. Pleural mesothelial cells and Meso-CAFs were isolated from tissue of pneumothorax and PM patients, respectively. Stable expression of hTERT was induced by retroviral transduction. Primary and hTERT-transduced cells were compared with respect to doubling times, hTERT expression and activity levels, telomere lengths, proteomes, and the impact of conditioned media (CM) on PM cell growth. All transduced derivatives exhibited elevated hTERT expression and activity, and increased mean telomere lengths. Cell morphology remained unchanged, and the proteomes were similar to the corresponding primary cells. Of note, the CM of primary and hTERT-transduced Meso-CAFs stimulated PM cell growth to the same extent, while CM derived from mesothelial cells had no stimulating effect, irrespective of hTERT expression. In conclusion, all new hTERT-transduced cell models closely resemble their primary counterparts and, hence, represent valuable tools to investigate cellular interactions within the TME of PM.
    Keywords:  conditioned medium; hTERT; human telomerase reverse transcriptase; mesothelioma-associated fibroblasts; pleural mesothelial cells; pleural mesothelioma; tumor microenvironment
    DOI:  https://doi.org/10.3390/cells12152006
  5. BMJ Open. 2023 08 08. 13(8): e067780
    Results of the Meso-ORIGINS feasibility study regarding collection of matched benign-mesothelioma tissue pairs by longitudinal surveillance.
    Katie Ferguson, Matthew Neilson, Rachel Mercer, Jenny King, Kelly Marshall, Hugh Welch, Selina Tsim, Nick A Maskell, Najib M Rahman, Matthew Evison, Kevin G Blyth.
       OBJECTIVES: To assess key elements of the design for Meso-ORIGINS (Mesothelioma Observational study of RIsk prediction and Generation of paired benign-meso tissue samples, Including a Nested MRI Substudy), an ambitious, UK-wide, prospective study that will collect ≥63 matched benign-mesothelioma tissue pairs through longitudinal surveillance and repeat biopsy of patients with asbestos-associated pleural inflammation (AAPI).
    DESIGN: A multicentre, mixed-methods feasibility study, comprising a prospective observational element, evaluating recruitment feasibility, technical feasibility of repeat local anaesthetic thoracoscopy (LAT) and patient acceptability, and a retrospective cohort study focused on AAPI-mesothelioma evolution rate, informing sample size.
    SETTING: 4 UK pleural disease centres (February 2019-January 2020).
    PARTICIPANTS: Patients with AAPI (history or typical imaging plus appropriate pleural histology) were eligible for both elements. In August 2019, eligibility for the prospective element was broadened, including addition of radiological AAPI for technical feasibility and patient acceptability endpoints only. Retrospective cases required ≥2 years follow-up.
    OUTCOME MEASURES: A prospective recruitment target was set a priori at 27 histological AAPI cases (or 14 in any 6 months). Technical feasibility and patient acceptability were determined at 6-month follow-up by thoracic ultrasound surrogates and questionnaires, respectively. Retrospective malignant pleural mesothelioma evolution rate was defined by proportion (95% CI). Baseline predictors of evolution were identified using logistic regression.
    RESULTS: 296 patients with AAPI (39 prospective, 257 retrospective) were recruited/selected. 21/39 prospective recruits were histologically diagnosed (target n=27). Repeat LAT was technically feasible and acceptable in 13/28 (46%) and 24/36 (67%) cases with complete follow-up data. Mesothelioma evolution was confirmed histologically in 36/257 retrospective cases (14% (95% CI 10.3% to 18.8%)) and associated with malignant CT features (OR 4.78 (95% CI 2.36 to 9.86)) and age (OR 1.06 (95% CI 1.02 to 1.12)).
    CONCLUSIONS: Our initial eligibility criteria were too narrow. Meso-ORIGINS will recruit a broader cohort, including prevalent cases, any biopsy type and patients with malignant CT features. A range of rebiopsy techniques will be allowed, accounting for technical and patient factors. The sample size has been reduced to 500.
    TRIAL REGISTRATION NUMBER: ISRCTN12840870.
    Keywords:  oncology; respiratory medicine (see thoracic medicine); respiratory tract tumours; thoracic medicine
    DOI:  https://doi.org/10.1136/bmjopen-2022-067780
  6. J Thorac Oncol. 2023 Aug 09. pii: S1556-0864(23)00724-4. [Epub ahead of print]
    Brief report: Meta-analysis on chemotherapy and PD-(L)1 blockade combination as first-line treatment for unresectable pleural mesothelioma.
    Marco Tagliamento, Massimo Di Maio, Jordi Remon, Paolo Bironzo, Carlo Genova, Francesco Facchinetti, Mihaela Aldea, Cecile Le Pechoux, Silvia Novello, Fabrice Barlesi, Benjamin Besse, David Planchard.
       BACKGROUND: Dual immune checkpoint blockers (ICBs) regimen represents a standard first-line therapy in unresectable pleural mesothelioma (PM). Novel combination strategies, including ICBs and antiangiogenic drugs, are currently under investigation in this setting. We aimed to assess the efficacy of chemo-immunotherapy combination by reference of literature evidence.
    METHODS: A systematic review and meta-analysis of trials with first-line platinum-based chemotherapy associated with anti-PD(L)1 agents in unresectable PM. We estimated weighted summary proportion of disease response, along with landmark probability of survival outcomes.
    RESULTS: 349 patients with unresectable PM from four trials (DREAM, PrE0505, JME-001, IND.227) were included, 79% (n=274) with epithelioid and 21% (n=75) with non-epithelioid histologic type. In aggregate, objective response rate (ORR) was 59.2% (95%CI: 50.3%-67.9%) and disease control rate (DCR) was 92.2% (95%CI: 89.2%-94.8%). Comparing epithelioid vs. non-epithelioid tumors, the ORR was 64.5% vs. 46.4%, (p<0.001) and the DCR was 92.3% vs. 80.0%, (p=0.043), with on odds ratio of 2.56 (95%CI: 1.51-4.32) for disease response and of 3.37 (95%CI: 0.99-11.47) for disease control. Aggregated estimated probability of progression-free survival was 63% (95%CI: 53%-71%) at 6 months and 25% (95%CI: 21%-31%) at 12 months, whereas 6-, 12- and 24-month overall survival rates were 88% (95%CI: 81%-93%), 71% (95%CI: 61%-79%) and 39% (95%CI: 34%-45%), respectively.
    CONCLUSION: According to our analysis, first-line chemo-immunotherapy shows promise as a potential novel treatment approach for PM, exhibiting encouraging survival outcomes and an enhanced response rate, including for the epithelioid subtype. Ongoing studies are necessary to establish its precise placement within the treatment algorithm.
    DOI:  https://doi.org/10.1016/j.jtho.2023.08.004
  7. J Thorac Oncol. 2023 Aug 09. pii: S1556-0864(23)00725-6. [Epub ahead of print]
    The IASLC Pleural Mesothelioma Staging Project: Updated Modeling of Prognostic Factors in Pleural Mesothelioma.
    Members of the IASLC Staging and Prognostic Factors Committee and Advisory Board and Participating Institutions
       INTRODUCTION: The International Association for the Study of Lung Cancer (IASLC) developed an international pleural mesothelioma database to improve staging. Data entered from 1995-2009 (training dataset) were analyzed previously to evaluate supplemental prognostic factors. We evaluated these factors with new clinical data to determine if the previous models could be improved.
    METHODS: Patients entered into the database from 2009-2019 (validation cohort) were assessed for association between prior prognosticators and overall survival using Cox proportional hazards regression with bidirectional stepwise selection. Additional variables were analyzed and models were compared using Harrell's C-index.
    RESULTS: The training dataset included 3,101 patients and the validation cohort 1,733 patients. For the multivariable pathologic staging model applied to the training cohort, C-index was 0.68 (95% CI: 0.656-0.705). For the validation dataset (n = 497), C-index was 0.650 (95% CI: 0.614, 0.685), and pathologic stage, histology, sex, adjuvant therapy, and platelet count were independently associated with survival. Adding anemia to the model increased the C-index to 0.652 (95% CI: 0.618, 0.686). A basic presentation model including all parameters prior to staging yielded a C-index of 0.668 (0.641, 0.695). For comparison, the European Organization for Research and Treatment of Cancer (EORTC) model yielded C-indices of 0.550 (95% CI: 0.511, 0.589) and 0.577 (95% CI: 0.550, 0.604) for pathologic staging and presentation models, respectively.
    CONCLUSIONS: Although significant predictors differed slightly, the IASLC training model performed well in the validation set and better than the EORTC model. International collaboration is critical to improve outcomes in this rare disease.
    Keywords:  Mesothelioma; extrapleural pneumonectomy; pleurectomy/decortication; prognostic factors; staging
    DOI:  https://doi.org/10.1016/j.jtho.2023.08.005
  8. Int J Mol Sci. 2023 Aug 04. pii: 12426. [Epub ahead of print]24(15):
    Cancer-Associated Fibroblasts Influence Survival in Pleural Mesothelioma: Digital Gene Expression Analysis and Supervised Machine Learning Model.
    Sabrina Borchert, Alexander Mathilakathu, Alina Nath, Michael Wessolly, Elena Mairinger, Daniel Kreidt, Julia Steinborn, Robert F H Walter, Daniel C Christoph, Jens Kollmeier, Jeremias Wohlschlaeger, Thomas Mairinger, Luka Brcic, Fabian D Mairinger.
      The exact mechanism of desmoplastic stromal reaction (DSR) formation is still unclear. The interaction between cancer cells and cancer-associated fibroblasts (CAFs) has an important role in tumor progression, while stromal changes are a poor prognostic factor in pleural mesothelioma (PM). We aimed to assess the impact of CAFs paracrine signaling within the tumor microenvironment and the DSR presence on survival, in a cohort of 77 PM patients. DSR formation was evaluated morphologically and by immunohistochemistry for Fibroblast activation protein alpha (FAP). Digital gene expression was analyzed using a custom-designed CodeSet (NanoString). Decision-tree-based analysis using the "conditional inference tree" (CIT) machine learning algorithm was performed on the obtained results. A significant association between FAP gene expression levels and the appearance of DSR was found (p = 0.025). DSR-high samples demonstrated a statistically significant prolonged median survival time. The elevated expression of MYT1, KDR, PIK3R1, PIK3R4, and SOS1 was associated with shortened OS, whereas the upregulation of VEGFC, FAP, and CDK4 was associated with prolonged OS. CIT revealed a three-tier system based on FAP, NF1, and RPTOR expressions. We could outline the prognostic value of CAFs-induced PI3K signaling pathway activation together with FAP-dependent CDK4 mediated cell cycle progression in PM, where prognostic and predictive biomarkers are urgently needed to introduce new therapeutic strategies.
    Keywords:  cancer-associated fibroblasts; digital gene expression; machine learning; pleural mesothelioma; survival
    DOI:  https://doi.org/10.3390/ijms241512426
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