Salto‐Tellez, Manuel

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe 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.

AbstractThe WHO Classification of Tumours provides the international standards for the classification and diagnosis of tumours. It enables direct comparisons to be made between different countries. In the new fifth edition, the series has gone digital with the launch of a website as well as a series of books, known widely as the WHO Blue Books. The first volume to be produced is on the classification of Digestive System tumours, replacing the successful 2010 version. It has been rewritten and updated accordingly. This article summarises the major diagnostic innovations that have occurred over the last decade and that have now been incorporated in the classification. As an example, it incorporates the recently proposed classification of neuroendocrine tumours, based on the recognition that neuroendocrine tumours and carcinomas differ substantially in the genetic abnormalities that drive their growth, findings relevant to treatment selection and outcome prediction. Several themes have emerged during the production process. One is the importance of the progression from hyperplasia to dysplasia to carcinoma in the evolution of the malignant process. Advances in imaging techniques and endoscopy have resulted in enhanced access to precancerous lesions in the gastrointestinal and biliary tract, necessitating both changes in classification schema and clinical practice. Diagnosis of tumours is no longer the sole purview of pathologists, and some patients now receive treatment before tissue is obtained, based on clinical, radiological and liquid biopsy results. This makes the classification relevant to many disciplines involved in the care of patients with tumours of the digestive system.

TPS11120 Background: Currently there is no biomarker to predict specific benefit from DNA-damaging anthracycline and cyclophosphamide-based chemotherapy in the clinic. Loss of the Fanconi anemia/BRCA (FA/BRCA) DNA-damage response pathway occurs in approximately 25% of breast cancer and results in sensitivity to DNA-damaging agents. We therefore developed an assay to detect loss of the FA/BRCA pathway, for the purpose of predicting benefit from chemotherapy. Methods: 21 FA patient samples were analyzed to identify genetic processes associated with loss of the FA/BRCA pathway. Unsupervised hierarchical clustering was then performed using 60 BRCA1/2 mutant and 47 sporadic tumor samples and a molecular subgroup was identified that was defined by the molecular processes representing loss of the FA/BRCA pathway. A 44-gene DNA Damage response deficient (DDRD) assay was developed that could identify this subgroup from formalin fixed, paraffin embedded (FFPE) samples in the clinic. Results: In a publicly available independent cohort of 204 patients, the assay predicted response to neoadjuvant DNA-damaging chemotherapy (5-fluorouracil, anthracycline and cyclophosphamide) with an odds ratio of 4.01, (95% Cl:1.69-9.54). We also analysed samples from an independent cohort of 114 node-negative breast cancer patients treated with adjuvant 5-fluorouracil, epirubicin and cyclophosphamide treatment at the Northern Ireland Cancer Centre. The DDRD assay significantly predicted 5-year relapse free survival with a hazard ratio of 0.27 (95% Cl:0.10-0.83). The assay was not predictive of survival in patients who did not receive chemotherapy. Conclusions: An FFPE tissue-based assay that detects loss of the FA/BRCA pathway has been developed and independently validated as a predictor of response and prognosis following DNA damaging anthracycline/cyclophosphamide-based chemotherapy in the neoadjuvant and adjuvant settings.