Improving diagnosis and prognostication in mesothelioma and malignant pleural disease

Abstract

Introduction

Pleural mesothelioma (PM) is a primary malignancy of the lung lining caused by asbestos. Patients face uncertainty at several points in their disease journey, which causes stress and anxiety[1]. These include delays in diagnosis and difficulty predicting individual disease trajectory and prognosis[2]. Accurately monitoring disease with Computed tomography (CT) scans carries its own challenges[3]. This research addressed these key areas, aiming to reduce the uncertainty faced at each stage.

Methods

Patient data and biopsy samples from the TARGET randomised controlled trial (RCT) were used to evaluate the role of the panel of immunohistochemical (IHC)
markers, BAP1 and MTAP, in PM diagnosis. Biopsy samples from two prospective cohort studies were used to investigate the IHC stain ki67 alongside nuclear grade in risk stratifying patients with epithelioid PM. Blood samples from the same studies were tested for cytomegalovirus (CMV) antibodies to investigate whether previous viral infection predicted disease outcomes. Finally, a prospective cohort study was conducted to determine the role of serum mesothelin (SM) in predicting disease status in PM.

Results

The ancillary diagnostic tests BAP1 and MTAP IHC diagnosed PM in fewer biopsies, with a shorter time to diagnosis and reduced healthcare costs. Ki67 was validated as a surrogate marker of nuclear grade and further stratified patients into prognostic groups. Previous CMV infection was not predictive of disease outcome. Finally, serial SM measurement was predictive of disease status when compared to the current gold standard.

Discussion

This thesis shows that the addition of simple tests can reduce diagnostic delays and add valuable prognostic information. Performing interval blood testing could complement CT scanning for monitoring PM. This body of work shows that additional tests could benefit patients at all stages of their disease journey.

Date of Award	20 Jan 2026
Original language	English
Awarding Institution	University of Bristol
Supervisor	Nick A Maskell (Supervisor) & Anna C Bibby (Supervisor)