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Context.--Recently, a new type of antibody-drug conjugate, trastuzumab-deruxtecan (T-DXd), has been approved for the treatment of metastatic breast cancer with low level of human epidermal growth factor receptor 2 (HER2) gene expression. Thereby, eligibility relies on an accurate diagnosis of HER2-low status defined by immunohistochemistry IHC 1+/2+ with no gene amplification. Objective.--To assess pathologists' accuracy and training efficacy in the diagnosis of HER2-low. Design.--Agreement rates of HER2-low scoring in breast cancer tissue were assessed between expert consensus and real-world pathologists (n = 77 from 14 countries) before and after a specific 4-hour training for HER2-low detection. Two assays were evaluated, the Ventana Pathway 4B5 CDx and the Dako HercepTest (polyclonal). Concordance of the pathologists with consensus score and efficacy of training were measured by Cohen k, overall rater agreement, and receiver operating characteristic (ROC) curve statistics. Results.--In the Ventana 4B5 HER2-low category, baseline agreement rates were >80% but Conclusions.--The ability of pathologists to achieve acceptable diagnostic accuracy in identifying patients with HER2-low breast cancer could be enhanced by short-term training. Potential routes to improve the quality of HER2-low scoring in clinical practice have been identified. doi: 10.5858/arpa.2024-0052OA, During the past 20 years, diagnosis of human epidermal growth factor receptor 2 (HER2) status has been essential in determining eligibility of breast cancer patients for HER2-targeted therapies. (1,2) Although [...]

Simple Summary: Personalised cancer treatment improves outcome for patients but requires that each individual tumour is classified using molecular tools. Extensive genomic studies for each individual patients are out of reach for the majority of the population, therefore, pathologists need to apply readily available tests to achieve molecular classification for all cancer patients. This paper describes how gastric cancer can be classified using on slide tests already used by histopathologists. Using this classification, oncologists can select more effective treatment for each patient. Background and Objectives: Gastric cancer (GC) is one of the most commonly diagnosed cancers and the fourth cause of cancer death worldwide. Personalised treatment improves GC outcomes. A molecular classification is needed to choose the appropriate therapy. A classification that uses on-slide biomarkers and formalin-fixed and paraffin-embedded (FFPE) tissue is preferable to comprehensive genomic analysis. In 2016, Setia and colleagues proposed an on-slide classification; however, this is not in widespread use. We propose a modification of this classification that has six subgroups: GC associated with Epstein–Barr virus (GC EBV+), GC with mismatch-repair deficiency (GC dMMR), GC with epithelial–mesenchymal transformation (GC EMT), GC with chromosomal instability (GC CIN), CG that is genomically stable (GC GS) and GC not otherwise specified (GC NOS). This classification also has a provision for biomarkers for current or emerging targeted therapies (Her2, PD-L1 and Claudin18.2). Here, we assess the implementation and feasibility of this inclusive working classification. Materials and Methods: We constructed a tissue microarray library from a cohort of 79 resection cases from FFPE tissue archives. We used a restricted panel of on-slide markers (EBER, MMR, E-cadherin, beta-catenin and p53), defined their interpretation algorithms and assigned each case to a specific molecular subtype. Results: GC EBV(+) cases were 6%, GC dMMR cases were 20%, GC EMT cases were 14%, GC CIN cases were 23%, GC GS cases were 29%, and GC NOS cases were 8%. Conclusions: This working classification uses markers that are widely available in histopathology and are easy to interpret. A diagnostic subgroup is obtained for 92% of the cases. The proportion of cases in each subgroup is in keeping with other published series. Widescale implementation appears feasible. A study using endoscopic biopsies is warranted. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) accounts for approximately 12% to 17% of all breast cancers and has an aggressive clinical behavior. Increased tumor-infiltrating lymphocyte counts are prognostic for survival in TNBC, making this disease a potential target for cancer immunotherapy. Research on immunophenotyping of tumor-infiltrating lymphocytes is revealing molecular and structural organization in the tumor microenvironment that may predict patient prognosis. The anti-programmed death-ligand 1 (PD-L1) antibody atezolizumab plus nab-paclitaxel was the first cancer immunotherapy combination to demonstrate progression-free survival benefit and clinically meaningful overall survival benefit in the first-line treatment of metastatic TNBC (mTNBC) in patients with PD-L1-expressing tumor-infiltrating immune cells in 1% or more of the tumor area. This led to its United States and European Union approval for mTNBC and US approval of the VENTANA PD-L1 (SP142) assay as a companion diagnostic immunohistochemistry assay. Subsequently, the anti-programmed death-1 (PD-1 ) antibody pembrolizumab plus chemotherapy was approved by the US Food and Drug Administration for mTNBC based on progression-free survival benefit in patients with a combined positive score of at least 10 by its concurrently approved 22C3 companion diagnostic assay. Treatment guidelines now recommend PD-L1 testing for patients with mTNBC, and the testing landscape will likely become increasingly complex as new anti-PD-L1 and anti-PD-1 agents and diagnostics are approved for TNBC. Integrating PD-L1 testing into current diagnostic workflows for mTNBC may provide more treatment options for these patients. Therefore, it is critical for medical oncologists and pathologists to understand the available assays and their relevance to therapeutic options to develop an appropriate workflow for immunohistochemistry testing. [ABSTRACT FROM AUTHOR]

Abstract Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ‘Immunoscore’ into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).