Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning models into the laboratory information system.

Background: Digital pathology (DP) has revolutionized cancer diagnostics and enabled the development of deep-learning (DL) models aimed at supporting pathologists in their daily work and improving patient care. However, the clinical adoption of such models remains challenging. Here, we describe a proof-of-concept framework that, leveraging Health Level 7 (HL7) standard and open-source DP resources, allows a seamless integration of both publicly available and custom developed DL models in the clinical workflow.

Nanophotonic sensors and AI for a new possible approach for accurate diagnosis of salivary glands tumors: a technical note.

Currently, diagnosing salivary gland tumors in their early stages presents significant challenges. This paper aims to outline a feasibility analysis of a novel approach utilizing advanced nanophotonic sensors and AI to address these diagnostic issues. The proposed approach integrates new nanophotonic sensors to tackle the complexities encountered in the early detection of salivary gland tumors.

Annexin A1 Is Involved in the Antitumor Effects of 5-Azacytidine in Human Oral Squamous Carcinoma Cells.

the treatment of squamous cell carcinomas of the oral cavity (OSCCs) is limited by the lack of reliable diagnostic/prognostic, and predictive markers, as well as by intrinsic tumor cell heterogeneity. 5-azacytidine (5-AZA) offers opportunities for cancer cell reprogramming to develop new target-specific treatments. The protein annexin A1 (ANXA1) is downregulated in head and neck squamous cell carcinoma (HNSCC), correlated with pathological differentiation grade.

Computer-assisted diagnosis to improve diagnostic pathology: A review.

With an increasing demand for accuracy and efficiency in diagnostic pathology, computer-assisted diagnosis (CAD) emerges as a prominent and transformative solution. This review aims to explore the practical applications, implications, strengths, and weaknesses of CAD applied to diagnostic pathology. A comprehensive literature search was conducted to include English-language studies focusing on CAD tools, digital pathology, and Artificial intelligence (AI) applications in pathology.

An Optimized NGS Workflow Defines Genetically Based Prognostic Categories for Patients with Uveal Melanoma.

Background: Despite advances in uveal melanoma (UM) diagnosis and treatment, about 50% of patients develop distant metastases, thereby displaying poor overall survival. Molecular profiling has identified several genetic alterations that can stratify patients with UM into different risk categories. However, these genetic alterations are currently dispersed over multiple studies and several methodologies, emphasizing the need for a defined workflow that will allow standardized and reproducible molecular analyses.

Metformin radiosensitizes OSCC in 2D and 3D models: possible involvement of CAF-1.

Objective: This study investigated metformin as a sensitizer for radiotherapy in oral squamous cell carcinoma (OSCC) to reduce the radiation intensity. It evaluated the drug's effect on Chromatin Assembly Factor-1 (CAF-1) expression, whose high levels correlate with worse prognosis of this cancer.

Methods: The effects of metformin, alone and with radiotherapy, were evaluated on CAL27 (HPV-) and SCC154 (HPV+) OSCC cells.

A Digital Workflow for Automated Assessment of Tumor-Infiltrating Lymphocytes in Oral Squamous Cell Carcinoma Using QuPath and a StarDist-Based Model.

The search for reliable prognostic markers in oral squamous cell carcinoma (OSCC) remains a critical need. Tumor-infiltrating lymphocytes (TILs), particularly T lymphocytes, play a pivotal role in the immune response against tumors and are strongly correlated with favorable prognoses. Computational pathology has proven highly effective for histopathological image analysis, automating tasks such as cell detection, classification, and segmentation.

A machine learning approach to predict HPV positivity of oropharyngeal squamous cell carcinoma.

HPV status is an important prognostic factor in oropharyngeal squamous cell carcinoma (OPSCC), with HPV-positive tumors associated with better overall survival. To determine HPV status, we rely on the immunohistochemical investigation for expression of the P16 protein, which must be associated with molecular investigation for the presence of viral DNA. We aim to define a criterion based on image analysis and machine learning to predict HPV status from hematoxylin/eosin stain.

The oral microbiome and its role in oral squamous cell carcinoma: a systematic review of microbial alterations and potential biomarkers.

Background: Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. Despite advances in diagnosis and treatment, the incidence of OSCC is increasing, and the mortality rate remains high. This systematic review aims to examine the potential association between the composition of the oral microbiota and OSCC.

Leveraging deep learning for identification and segmentation of "CAF-1/p60-positive" nuclei in oral squamous cell carcinoma tissue samples.

In the current study, we introduced a unique method for identifying and segmenting oral squamous cell carcinoma (OSCC) nuclei, concentrating on those predicted to have significant CAF-1/p60 protein expression. Our suggested model uses the StarDist architecture, a deep-learning framework designed for biomedical image segmentation tasks. The training dataset comprises painstakingly annotated masks created from tissue sections previously stained with hematoxylin and eosin (H&E) and then restained with immunohistochemistry (IHC) for p60 protein.

Nutraceuticals in Pregnancy: A Special Focus on Probiotics.

The placenta is crucial to fetal development and performs vital functions such as nutrient exchange, waste removal and hormone regulation. Abnormal placental development can lead to conditions such as fetal growth restriction, pre-eclampsia and stillbirth, affecting both immediate and long-term fetal health. Placental development is a highly complex process involving interactions between maternal and fetal components, imprinted genes, signaling pathways, mitochondria, fetal sexomes and environmental factors such as diet, supplementation and exercise.

Digital odyssey: lessons learnt from a reverse transition from a digital to a manual pathology workflow.

In the fully digital Caltagirone pathology laboratory, a reverse shift from a digital to a manual workflow occurred due to a server outage in September 2023. Here, insights gained from this unplanned transition are explored. Surveying the affected pathologists and technicians revealed unanimous preferences for the time-saving and error-reducing capabilities of the digital methodology.

A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma.

Anatomical pathology is undergoing its third revolution, transitioning from analogical to digital pathology and incorporating new artificial intelligence technologies into clinical practice. Aside from classification, detection, and segmentation models, predictive models are gaining traction since they can impact diagnostic processes and laboratory activity, lowering consumable usage and turnaround time. Our research aimed to create a deep-learning model to generate synthetic Ki-67 immunohistochemistry from Haematoxylin and Eosin (H&E) stained images.

The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board.

Objective: The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered.

Histopathological Image Deep Feature Representation for CBIR in Smart PACS.

Pathological Anatomy is moving toward computerizing processes mainly due to the extensive digitization of histology slides that resulted in the availability of many Whole Slide Images (WSIs). Their use is essential, especially in cancer diagnosis and research, and raises the pressing need for increasingly influential information archiving and retrieval systems. Picture Archiving and Communication Systems (PACSs) represent an actual possibility to archive and organize this growing amount of data.

Immunohistochemical expression of PRAME is a marker of poor prognosis in uveal melanoma: A clinico-pathologic and immunohistochemical study on a series of 85 cases.

PReferentially expressed Antigen in Melanoma (PRAME) is a cancer testis antigen, first isolated in tumor-reactive T-cell clones from a metastatic melanoma patient. It has been widely studied in skin pathology as an immunohistochemical marker capable of distinguishing between benign nevi and malignant melanomas. PRAME has been found to be also expressed in non-melanocytic tumors, including lung, breast, kidney and ovarian cancer.

The disruption of the CCDC6 - PP4 axis induces a BRCAness like phenotype and sensitivity to PARP inhibitors in high-grade serous ovarian carcinoma.

Background: Treatment with PARP inhibitors (PARPi) is primarily effective against high-grade serous ovarian cancers (HGSOC) with BRCA1/2 mutations or other deficiencies in homologous recombination (HR) repair mechanisms. However, resistance to PARPi frequently develops, mostly as a result of BRCA1/2 reversion mutations. The tumour suppressor CCDC6 is involved in HR repair by regulating the PP4c phosphatase activity on γH2AX.

The tumour suppressor CCDC6 is involved in ROS tolerance and neoplastic transformation by evading ferroptosis.

Coiled-coil domain containing 6 (CCDC6) is a tumour suppressor gene involved in apoptosis and DNA damage response. CCDC6 is known to be functionally impaired upon gene fusions, somatic mutations, and altered protein turnover in several tumours. Testicular germ cell tumours are among the most common malignancies in young males.

Neuropilin-1 Expression Associates with Poor Prognosis in HNSCC and Elicits EGFR Activation upon CDDP-Induced Cytotoxic Stress.

Head and neck squamous cell carcinoma (HNSCC) includes a group of aggressive malignancies characterized by the overexpression of the epidermal growth factor receptor (EGFR) in 90% of cases. Neuropilin-1 (NRP-1) acts as an EGFR co-receptor, enhancing, upon ligand stimulation, EGFR signaling in several cellular models. However, NRP-1 remains poorly characterized in HNSCC.

Detection of CAF-1/p60 in peripheral blood as a potential biomarker of HNSCC tumors.

To date, a very small number of serum biomarkers have been identified for clinical use in squamous carcinomas of the head and neck region. Chromatin Assembly Factor-1 (CAF-1) heterotrimeric complex subunit CAF1/p60 expression levels have been reported to be of prognostic value in Oral Squamous Cell Carcinoma (OSCC), as well as in other human solid tumors. Here our aim was to detect and quantify CAF1/p60 in the peripheral blood of Head and Neck Squamous Cell Carcinoma (HNSCC) patients, and to investigate the possible associations between serum concentration of CAF-1/p60 and HNSCC tumors.

Tissue Expression of Carbonic Anhydrase IX Correlates to More Aggressive Phenotype of Basal Cell Carcinoma.

Basal cell carcinoma (BCC) is the most common cancer in the white-skinned population accounting for about 15% of all neoplasms. Its incidence is increasing worldwide, at a rate of about 10% per year. BCC, although infrequently metastasizing, very often causes extensive tissue losses, due to the high propensity toward stromal infiltration, particularly in its dedifferentiated forms, with disfiguring and debilitating results.

Low-Grade Intraductal Carcinoma of the Parotid Gland: A Case Report and Literature Review.

Low-grade intraductal carcinoma is a rare neoplasia with an excellent prognosis, previously classified as low-grade cribriform cystadenocarcinoma and low-grade salivary duct carcinoma. The tumor mainly occurs in the parotid gland and presents a ductal phenotype and an intraductal/intracystic growth pattern. It resembles intraductal breast lesions such as atypical ductal hyperplasia, papillary and cribriform ductal carcinoma in situ.

Expression of P16INK4a in Uveal Melanoma: New Perspectives.

Uveal melanoma (UM) is the most common intraocular tumor in adults. Despite sharing the name and similar morphological features with cutaneous melanoma (CM), it is an entirely different neoplasia with a particular genetic background and clinical behavior. CDKN2A is a gene located at chromosome 9p21, encoding for P16INK4a and P14(ARF) proteins, whose role as a tumor suppressor has been clearly defined in many malignant tumors.