Malignant peritoneal mesothelioma (MPM) is a very rare malignancy of the peritoneum and has a poor prognosis. Of all mesotheliomas, pleural mesothelioma is more common than MPM. In comparison to pleural mesothelioma, the link with asbestos exposure is weaker (33–50% vs. >80%), but it is still the best-defined risk factor. MPM spreads predominantly expansive rather than infiltrative and symptoms are related to tumor spread within the abdominal cavity. Often, MPM is encountered incidentally by diagnostic imaging or by surgery. Computed tomography scan is widely accepted as a first line modality in diagnostic imaging. In diagnostic histopathology, MPM presents some challenges. Firstly, adequate clinical information is of utmost importance to consider the possibility of the diagnosis of MPM. Furthermore, a few morphological subtypes and variants exist. The most sensitive immunohistochemical markers are calretinin (100%), WT1 (94%) and CK5/6 (89%). The malignant character of immunohistochemically demonstrated mesothelial cells is not always obvious. This paradigm somewhat changed with the advent of immunohistochemical demonstration of BAP1 (BRCA-1 associated protein 1). Loss of BAP1 expression supports a diagnosis of malignancy. The gold standard in treatment remains cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC). Targetable molecular pathways in MPM are being identified. An exciting finding was the demonstration of ALK rearrangements in a small subset of patients with MPM and it is hoped for that at least this small subgroup of patients could benefit from treatment with ALK inhibitors. First-generation tyrosine kinase inhibitors against epidermal growth factor receptor (EGFR) did not show any significant activity in MPM. In contrast, nintedanib, an angiokinase inhibitor, improved progression-free survival and bevacizumab, a humanized anti-VEGF antibody increased overall survival in patients with MPM, when administered in combination with cisplatin and pemetrexed. Ongoing immunotherapy trials will offer a possible new treatment.

The clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Introduction: Inflammatory breast cancer (IBC) is a rare but aggressive form of breast cancer (BC) in which the (prognostic) role of stromal tumour-infiltrating lymphocytes (sTIL) and the peripheral circulating immune cells in patients with residual disease (RD) after neo-adjuvant chemotherapy (NACT) is not clearly established. Methodology: To describe the evolution of sTIL and some peripheral inflammation markers (Neutrophil-to-lymphocyte ratio, Platelet-to-lymphocyte ratio and Lymphocyte-to-monocyte ratio) after NACT in IBC, we retrospectively collected clinicopathological variables for 125 stage III IBC patients. sTILs were scored by three different researchers on an H&E slide of the mastectomy specimen. A cohort of subtype-matched non-IBC breast cancer patients (nIBC) treated with NACT was included for comparison. Results: There was no significant difference in the pre- and posttreatment sTIL scores between IBC and nIBC and in both groups the number of sTIL was significantly lower after NACT. However, the IBC phenotype did correlate with a stronger decrease of sTIL after NACT (OR: 0.25, 95% CI: 0.073–0.76, p = 0.018). The change in the peripheral immune markers was not significantly different between IBC and nIBC. After NACT, 75 patients had residual disease. In this group, a high number of sTIL before NACT (HR: 0.23, 95% CI: 0.05–1.02, p = 0.05) was prognostic for a longer OS, while a low number of sTIL after NACT (HR: 0.33, 95% CI: 0.11–0.98, p = 0.046) and a low residual cancer cellularity (HR: 0.20, 95% CI: 0.08–0.52, p < 0.001) was associated with a longer DFS. Conclusions: IBC is associated with a significantly stronger decrease of sTIL after NACT compared to nIBC. Furthermore, a high number of sTIL after NACT was associated with a worse prognosis in IBC.