The cellularity assessment in bone marrow biopsies (BMBs) for the diagnosis of Philadelphia chromosome (Ph)-negative myeloproliferative neoplasms (MPNs) is a key diagnostic feature and is usually performed by the human eyes through an optical microscope with consequent inter-observer and intra-observer variability. Thus, the use of an automated tool may reduce variability, improving the uniformity of the evaluation. The aim of this work is to develop an accurate AI-based tool for the automated quantification of cellularity in BMB histology. A total of 55 BMB histological slides, diagnosed as Ph- MPN between January 2018 and June 2023 from the archives of the Pathology Unit of University “Luigi Vanvitelli” in Naples (Italy), were scanned on Ventana DP200 or Epredia P1000 and exported as whole-slide images (WSIs). Fifteen BMBs were randomly selected to obtain a training set of AI-based tools. An expert pathologist and a trained resident performed annotations of hematopoietic tissue and adipose tissue, and annotations were exported as .tiff images and .png labels with two colors (black for hematopoietic tissue and yellow for adipose tissue). Subsequently, we developed a semantic segmentation model for hematopoietic tissue and adipose tissue. The remaining 40 BMBs were used for model verification. The performance of our model was compared with an evaluation of the cellularity of five expert hematopathologists and three trainees; we obtained an optimal concordance between our model and the expert pathologists’ evaluation, with poorer concordance for trainees. There were no significant differences in cellularity assessments between two different scanners.

Methylthioadenosine phosphorylase (MTAP) loss is an emerging biomarker in several human malignancies, mainly due to its frequent co-deletion with CDKN2A on chromosome 9p21. Beyond its diagnostic value, MTAP deficiency has important biological consequences, including metabolic reprogramming, immune microenvironment modulation, and increased dependency on PRMT5-related pathways. This review summarizes the current evidence on MTAP alterations across different tumor types. The role of MTAP immunohistochemistry as a practical surrogate for CDKN2A homozygous deletion is discussed, together with its advantages and interpretative limitations. In addition, the potential predictive relevance of MTAP loss for immunotherapy, antifolate-based treatments, and novel PRMT5-targeted strategies is explored. Overall, MTAP assessment represents a promising tool in modern diagnostic pathology and precision oncology, bridging morphology, molecular alterations, and therapeutic decision-making.