Ovarian carcinomas represent a heterogeneous group of neoplasms consisting of separate entities with distinct risk factors, precursor lesions, pathogenesis, patterns of spread, molecular profiles, clinical course, response to chemotherapy, and outcomes. The histologic subtype and the related molecular features are essential for individualized clinical decision-making. The fifth edition of the World Health Organization classification of tumors of the female genital tract divides ovarian carcinomas into at least five main and distinct types of ovarian carcinomas: high-grade serous carcinoma, low-grade serous carcinoma, endometrioid carcinoma, clear cell carcinoma, and mucinous carcinoma. Molecular pathology has improved the knowledge of genomic landscape of ovarian carcinomas identifying peculiar alterations for every histologic subtype. It is well-known that high-grade and low-grade serous carcinomas are separate entities with entirely different morphologic and molecular characteristics. TP53 and BRCA mutations are typical of high-grade serous carcinoma, whereas BRAF and KRAS mutations frequently occur in low-grade serous carcinoma. Endometrioid and clear cell carcinomas are frequently associated with endometriosis. Endometrioid tumors are characterized by β-catenin alterations, microsatellite instability, and PTEN and POLE mutations, while ARID1A mutations occur in both endometrioid and clear cell carcinomas. Mucinous carcinomas are uncommon tumors associated with copy-number loss of CDKN2A and KRAS alterations and metastasis from other sites should always be considered in the differential diagnosis.

Primary pulmonary B-cell lymphomas (PP-BCLs) comprise a group of extranodal non-Hodgkin lymphomas of B-cell origin, which primarily affect the lung without evidence of extrapulmonary disease at the time of diagnosis and up to 3 months afterwards. Primary lymphoid proliferations of the lung are most often of B-cell lineage, and include three major entities with different clinical, morphological, and molecular features: primary pulmonary marginal zone lymphoma of mucosa-associated lymphoid tissue (PP-MZL, or MALT lymphoma), primary pulmonary diffuse large B cell lymphoma (PP-DLBCL), and lymphomatoid granulomatosis (LYG). Less common entities include primary effusion B-cell lymphoma (PEL) and intravascular large B cell lymphoma (IVLBCL). A proper workup requires a multidisciplinary approach, including radiologists, pneumologists, thoracic surgeons, pathologists, hemato-oncologists, and radiation oncologists, in order to achieve a correct diagnosis and risk assessment. Aim of this review is to analyze and outline the clinical and pathological features of the most frequent PP-BCLs, and to critically analyze the major issues in their diagnosis and management.

Bladder cancer (BC) is a heterogeneous disease from a molecular, morphological, and clinical standpoint. HER2 is a known oncogene involved in bladder carcinogenesis. Assessing HER2 overexpression as a result of its molecular changes in a routine pathology practice using immunohistochemistry might be a useful adjunct in several scenarios, namely (1) to correctly identify flat urothelial lesions and inverted urothelial lesions in the diagnostic setting; (2) to provide prognostic hints in both non-muscle invasive (NMI) and muscle invasive (MI) tumors, thus supplementing risk stratification tools, especially when evaluating higher-risk tumors such as those with variant morphology; (3) to improve antibody panels as a surrogate marker of BC molecular subtyping. Furthermore, the potential of HER2 as a therapeutic target has been only partly explored so far, in light of the ongoing development of novel target therapies.

The present review discusses the transformative role of AI in the diagnosis and management of head and neck cancers (HNCs). Methods: It explores how AI technologies, including ML, DL, and CNNs, are applied in various diagnostic tasks, such as medical imaging, molecular profiling, and predictive modeling. Results: This review highlights AI’s ability to improve diagnostic accuracy and efficiency, particularly in analyzing medical images like CT, MRI, and PET scans, where AI sometimes outperforms human radiologists. This paper also emphasizes AI’s application in histopathology, where algorithms assist in whole-slide image (WSI) analysis, tumor-infiltrating lymphocytes (TILs) quantification, and tumor segmentation. AI shows promise in identifying subtle or rare histopathological patterns and enhancing the precision of tumor grading and treatment planning. Furthermore, the integration of AI with molecular and genomic data aids in mutation analysis, prognosis, and personalized treatment strategies. Conclusions: Despite these advancements, the review identifies challenges in AI adoption, such as data standardization and model interpretability, and calls for further research to fully integrate AI into clinical practice for improved patient outcomes.

In prostate cancer (PC), the presence of BRCA somatic and/or germline mutation provides prognostic and predictive information. Meta-analysis aims to estimate the frequency of BRCA mutations in patients with PC (PCp). In November 2022, we reviewed literature searching for all articles testing the proportion of BRCA mutations in PCp, without explicit enrichment for familiar risk. The frequency of germline and somatic BRCA1 and/or BRCA2 mutations was described in three stage disease populations (any/metastatic/metastatic castration-resistant PC, mCRPC). Out of 2253 identified articles, 40 were eligible. Here, 0.73% and 1.20% of any stage PCp, 0.94% and 1.10% of metastatic PCp, and 1.21% and 1.10% of mCRPC patients carried germline and somatic BRCA1 mutation, respectively; 3.25% and 6.29% of any stage PCp, 4.51% and 10.26% of metastatic PCp, and 3.90% and 10.52% of mCRPC patients carried germline and somatic BRCA2 mutation, respectively; and 4.47% and 7.18% of any stage PCp, 5.84% and 10.94% of metastatic PCp, and 5.26% and 11.26% of mCRPC patients carried germline and somatic BRCA1/2 mutation, respectively. Somatic mutations are more common than germline and BRCA2 are more common than BRCA1 mutations; the frequency of mutations is higher in the metastatic setting. Despite that BRCA testing in PC is now standard in clinical practice, several open questions remain.

The term “ovarian carcinoma” encompasses at least five different malignant neoplasms: high-grade serous carcinoma, low-grade serous carcinoma, endometrioid carcinoma, mucinous carcinoma, and clear cell carcinoma. These five histotypes demonstrated distinctive histological, molecular, and clinical features. The rise of novel target therapies and of a tailored oncological approach has demanded an integrated multidisciplinary approach in the setting of ovarian carcinoma. The need to implement a molecular-based classification in the worldwide diagnostic and therapeutic setting of ovarian cancer demanded a search for easy-to-use and cost-effective molecular-surrogate biomarkers, relying particularly on immunohistochemical analysis. The present review focuses on the role of immunohistochemistry as a surrogate of molecular analysis in the everyday diagnostic approach to ovarian carcinomas.