International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling.

BACKGROUND: A common terminology for diagnosis is critically important for clinical communication, education, research and artificial intelligence. Prevailing lexicons are limited in fully representing skin neoplasms. OBJECTIVES: To achieve expert consensus on diagnostic terms for skin neoplasms and their hierarchical mapping. METHODS: Diagnostic terms were extracted from textbooks, publications and extant diagnostic codes. Terms were hierarchically mapped to super-categories (e.g. 'benign') and cellular/tissue-differentiation categories (e.g. 'melanocytic'), and appended with pertinent-modifiers and synonyms. These terms were evaluated using a modified-Delphi consensus approach. Experts from the International-Skin-Imaging-Collaboration (ISIC) were surveyed on agreement with terms and their hierarchical mapping; they could suggest modifying, deleting or adding terms. Consensus threshold was >75% for the initial rounds and >50% for the final round. RESULTS: Eighteen experts completed all Delphi rounds. Of 379 terms, 356 (94%) reached consensus in round one. Eleven of 226 (5%) benign-category terms, 6/140 (4%) malignant-category terms and 6/13 (46%) indeterminate-category terms did not reach initial agreement. Following three rounds, final consensus consisted of 362 terms mapped to 3 super-categories and 41 cellular/tissue-differentiation categories. CONCLUSIONS: We have created, agreed upon, and made public a taxonomy for skin neoplasms and their hierarchical mapping. Further study will be needed to evaluate the utility and completeness of the lexicon.

Plexiform Fibromyxoma in the Stomach: Immunohistochemical Profile and Comprehensive Genetic Characterization.

Plexiform fibromyxoma (PF), also referred to as plexiform angiomyxoid myofibroblast tumor, is an exceedingly rare mesenchymal neoplasm primarily affecting the stomach. Herein, we present a case of PF diagnosed in a 71-year-old male with a history of lung cancer, initially suspected to have a gastrointestinal stromal tumor (GIST) of the stomach, who subsequently underwent subtotal gastrectomy. The histopathological and molecular features of the tumor, including mutations in ABL1, CCND1, CSF1R, FGFR4, KDR, and MALAT1-GLI1 fusion, are elucidated and discussed in the context of diagnostic, prognostic, and therapeutic considerations.

Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment.

PURPOSE: We aimed to assess the efficacy of machine learning and radiomics analysis using magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical setting, to predict tumor budding in liver metastases. METHODS: Patients with MRI in a pre-surgical setting were retrospectively enrolled. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. Balancing was performed and inter- and intraclass correlation coefficients were calculated to assess the between observer and within observer reproducibility of all radiomics extracted features. A Wilcoxon-Mann-Whitney nonparametric test and receiver operating characteristics (ROC) analysis were carried out. Balancing and feature selection procedures were performed. Linear and non-logistic regression models (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. RESULTS: The internal training set included 49 patients and 119 liver metastases. The validation cohort consisted of a total of 28 single lesion patients. The best single predictor to classify tumor budding was original_glcm_Idn obtained in the T1-W VIBE sequence arterial phase with an accuracy of 84%; wavelet_LLH_firstorder_10Percentile was obtained in the T1-W VIBE sequence portal phase with an accuracy of 92%; wavelet_HHL_glcm_MaximumProbability was obtained in the T1-W VIBE sequence hepatobiliary excretion phase with an accuracy of 88%; and wavelet_LLH_glcm_Imc1 was obtained in T2-W SPACE sequences with an accuracy of 88%. Considering the linear regression analysis, a statistically significant increase in accuracy to 96% was obtained using a linear weighted combination of 13 radiomic features extracted from the T1-W VIBE sequence arterial phase. Moreover, the best classifier was a KNN trained with the 13 radiomic features extracted from the arterial phase of the T1-W VIBE sequence, obtaining an accuracy of 95% and an AUC of 0.96. The validation set reached an accuracy of 94%, a sensitivity of 86% and a specificity of 95%. CONCLUSIONS: Machine learning and radiomics analysis are promising tools in predicting tumor budding. Considering the linear regression analysis, there was a statistically significant increase in accuracy to 96% using a weighted linear combination of 13 radiomics features extracted from the arterial phase compared to a single radiomics feature.

Evaluating deep learning-based melanoma classification using immunohistochemistry and routine histology: A three center study.

Pathologists routinely use immunohistochemical (IHC)-stained tissue slides against MelanA in addition to hematoxylin and eosin (H&E)-stained slides to improve their accuracy in diagnosing melanomas. The use of diagnostic Deep Learning (DL)-based support systems for automated examination of tissue morphology and cellular composition has been well studied in standard H&E-stained tissue slides. In contrast, there are few studies that analyze IHC slides using DL. Therefore, we investigated the separate and joint performance of ResNets trained on MelanA and corresponding H&E-stained slides. The MelanA classifier achieved an area under receiver operating characteristics curve (AUROC) of 0.82 and 0.74 on out of distribution (OOD)-datasets, similar to the H&E-based benchmark classification of 0.81 and 0.75, respectively. A combined classifier using MelanA and H&E achieved AUROCs of 0.85 and 0.81 on the OOD datasets. DL MelanA-based assistance systems show the same performance as the benchmark H&E classification and may be improved by multi stain classification to assist pathologists in their clinical routine.

Endocrine nuclear receptors and long non­coding RNAs reciprocal regulation in cancer (Review).

Nuclear receptors (NRs) are transcriptional regulators involved in different aspects of normal cell physiology. Their deregulation is associated with aberrant expression, gene mutations and/or epigenetic alterations that can be related to the pathogenesis of various human diseases, and especially in cancer. In particular, a complex genomic network involved in the development and progression of NR­mediated cancer has been highlighted. Advanced genomic technologies have made it possible to understand that the expression of any particular NR in a given cancer subtype is only one component of a larger transcriptional machinery that is controlled by multiple associated NRs and transcription factors. Additionally, their ability to regulate and to be regulated by molecules of non­coding RNAs, microRNAs as well as long non­coding RNAs, is opening new scenarios for understanding the role of NRs in cancer initiation and progression. In the present review, the authors aimed to outline the reciprocal interactions that exist between the main NRs and long non­coding RNAs in different tumor diseases, to suggest new diagnostic biomarkers as well as therapeutic strategies for these tumors.

A Retrospective Multicenter Italian Analysis of Epidemiological, Clinical and Histopathological Features in a Sample of Patients with Acinic Cell Carcinoma of the Parotid Gland.

BACKGROUND: The acinic cell carcinoma (AciCC) of the parotid gland is a rare tumor with an indolent behavior; however, a subgroup of this tumor presents an aggressive behavior with a tendency to recur. The aim of this multicenter study was to identify and stratify those patients with AciCC at high risk of tumor recurrence. METHODS: A retrospective study was carried out involving 77 patients treated with surgery between January 2000 and September 2022, in different Italian referral centers. Data about tumor characteristics and its recurrence were collected. The histological specimens and slides were independently reviewed by a senior pathologist coordinator (L.C.) and the institution's local head and neck pathologist. RESULTS: The patients' age average was 53.6 years, with a female prevalence in the group. The mean follow-up was 67.4 months (1-258, SD 59.39). The five-year overall survival (OS) was 83.2%. The 5-year disease-free survival (DFS) was 60% (95% CI 58.2-61.7). A high incidence of necrosis, extraglandular spread, lymphovascular invasion (LVI), atypical mitosis, and cellular pleomorphism was observed in the high-risk tumors compared to the low-risk ones. CONCLUSION: AciCC generally had an indolent behavior, optimal OS, DFS with few cervical node metastases, and rare distant relapses. This multicenter retrospective case series provides evidence of the need for clinical-epidemiological-histological stratification for patients at risk of poor outcomes. Our results suggest that the correct definition of high-risk AciCC should include tumor size, the presence of necrosis, extraglandular spread, LVI, atypical mitosis, and cellular pleomorphism.

Oligo-metastatic neoPlasms from the gastro-intestinal tract: iDentIfiCaTIon of cliNical and molecular drivers: the PREDICTION study.

BACKGROUND: Metastatic disease in tumors originating from the gastrointestinal tract can exhibit varying degrees of tumor burden at presentation. Some patients follow a less aggressive disease course, characterized by a limited number of metastatic sites, referred to as "oligo-metastatic disease" (OMD). The precise biological characteristics that define the oligometastatic behavior remain uncertain. In this study, we present a protocol designed to prospectively identify OMD, with the aim of proposing novel therapeutic approaches and monitoring strategies. METHODS: The PREDICTION study is a monocentric, prospective, observational investigation. Enrolled patients will receive standard treatment, while translational activities will involve analysis of the tumor microenvironment and genomic profiling using immunohistochemistry and next-generation sequencing, respectively. The first primary objective (descriptive) is to determine the prevalence of biological characteristics in OMD derived from gastrointestinal tract neoplasms, including high genetic concordance between primary tumors and metastases, a significant infiltration of T lymphocytes, and the absence of clonal evolution favoring specific driver genes (KRAS and PIK3CA). The second co-primary objective (analytic) is to identify a prognostic score for true OMD, with a primary focus on metastatic colorectal cancer. The score will comprise genetic concordance (> 80%), high T-lymphocyte infiltration, and the absence of clonal evolution favoring driver genes. It is hypothesized that patients with true OMD (score 3+) will have a lower rate of progression/recurrence within one year (20%) compared to those with false OMD (80%). The endpoint of the co-primary objective is the rate of recurrence/progression at one year. Considering a reasonable probability (60%) of the three factors occurring simultaneously in true OMD (score 3+), using a significance level of α = 0.05 and a test power of 90%, the study requires a minimum enrollment of 32 patients. DISCUSSION: Few studies have explored the precise genetic and biological features of OMD thus far. In clinical settings, the diagnosis of OMD is typically made retrospectively, as some patients who undergo intensive treatment for oligometastases develop polymetastatic diseases within a year, while others do not experience disease progression (true OMD). In the coming years, the identification of true OMD will allow us to employ more personalized and comprehensive strategies in cancer treatment. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT05806151.

A 3-dimensional histology computer model of malignant melanoma and its implications for digital pathology.

BACKGROUND: Historically, cancer diagnoses have been made by pathologists using two-dimensional histological slides. However, with the advent of digital pathology and artificial intelligence, slides are being digitised, providing new opportunities to integrate their information. Since nature is 3-dimensional (3D), it seems intuitive to digitally reassemble the 3D structure for diagnosis. OBJECTIVE: To develop the first human-3D-melanoma-histology-model with full data and code availability. Further, to evaluate the 3D-simulation together with experienced pathologists in the field and discuss the implications of digital 3D-models for the future of digital pathology. METHODS: A malignant melanoma of the skin was digitised via 3 µm cuts by a slide scanner; an open-source software was then leveraged to construct the 3D model. A total of nine pathologists from four different countries with at least 10 years of experience in the histologic diagnosis of melanoma tested the model and discussed their experiences as well as implications for future pathology. RESULTS: We successfully constructed and tested the first 3D-model of human melanoma. Based on testing, 88.9% of pathologists believe that the technology is likely to enter routine pathology within the next 10 years; advantages include a better reflectance of anatomy, 3D assessment of symmetry and the opportunity to simultaneously evaluate different tissue levels at the same time; limitations include the high consumption of tissue and a yet inferior resolution due to computational limitations. CONCLUSIONS: 3D-histology-models are promising for digital pathology of cancer and melanoma specifically, however, there are yet limitations which need to be carefully addressed.

Advancing the PD-L1 CPS test in metastatic TNBC: Insights from pathologists and findings from a nationwide survey.

Pembrolizumab has received approval as a first-line treatment for unresectable/metastatic triple-negative breast cancer (mTNBC) with a PD-L1 combined positive score (CPS) of ≥ 10. However, assessing CPS in mTNBC poses challenges. Firstly, it represents a novel analysis for breast pathologists. Secondly, the heterogeneity of PD-L1 expression in mTNBC further complicates the assessment. Lastly, the lack of standardized assays and staining platforms adds to the complexity. In KEYNOTE trials, PD-L1 expression was evaluated using the IHC 22C3 pharmDx kit as a companion diagnostic test. However, both the 22C3 pharmDx and VENTANA PD-L1 (SP263) assays are validated for CPS assessment. Consequently, assay-platform choice, staining conditions, and scoring methods can significantly impact the testing outcomes. This consensus paper aims to discuss the intricacies of PD-L1 CPS testing in mTNBC and provide practical recommendations for pathologists. Additionally, we present findings from a nationwide Italian survey elucidating the state-of-the-art in PD-L1 CPS testing in mTNBC.

Oligo-Metastatic Cancers: Putative Biomarkers, Emerging Challenges and New Perspectives.

Some cancer patients display a less aggressive form of metastatic disease, characterized by a low tumor burden and involving a smaller number of sites, which is referred to as "oligometastatic disease" (OMD). This review discusses new biomarkers, as well as methodological challenges and perspectives characterizing OMD. Recent studies have revealed that specific microRNA profiles, chromosome patterns, driver gene mutations (ERBB2, PBRM1, SETD2, KRAS, PIK3CA, SMAD4), polymorphisms (TCF7L2), and levels of immune cell infiltration into metastases, depending on the tumor type, are associated with an oligometastatic behavior. This suggests that OMD could be a distinct disease with specific biological and molecular characteristics. Therefore, the heterogeneity of initial tumor burden and inclusion of OMD patients in clinical trials pose a crucial methodological question that requires responses in the near future. Additionally, a solid understanding of the molecular and biological features of OMD will be necessary to support and complete the clinical staging systems, enabling a better distinction of metastatic behavior and tailored treatments.

Neoadjuvant plus adjuvant combined or sequenced vemurafenib, cobimetinib and atezolizumab in patients with high-risk, resectable BRAF-mutated and wild-type melanoma: NEO-TIM, a phase II randomized non-comparative study.

Background: Following the increased survival of patients with metastatic melanoma thanks to immunotherapy and targeted therapy, neoadjuvant approaches are being investigated to address the unmet needs of unresponsive and intolerant patients. We aim to investigate the efficacy of neoadjuvant plus adjuvant combined or sequenced vemurafenib, cobimetinib and atezolizumab in patients with high-risk, resectable BRAF-mutated and wild-type melanoma. Methods: The study is a phase II, open-label, randomized non-comparative trial in patients with stage IIIB/C/D surgically resectable, BRAF-mutated and wild-type melanoma, with three possible treatments: (1) vemurafenib 960 mg twice daily from day 1 to 42; (2) vemurafenib 720 mg twice daily from day 1 to 42; (3) cobimetinib 60 mg once daily from day 1 to 21 and from day 29 to 42; and (4) atezolizumab 840 mg for two cycles (day 22 and day 43).Patients will be randomized to three different arms: A) BRAF-mutated patients will receive over 6 weeks (1) + (3); B) BRAF-mutated patients will receive over 6 weeks (2) + (3) + (4); C) BRAF wild-type patients will receive over 6 weeks (3) + (4). All patients will also receive atezolizumab 1200 mg every 3 weeks for 17 cycles after surgery and after a second screening period (up to 6 weeks). Discussion: Neoadjuvant therapy for regional metastases may improve operability and outcomes and facilitate the identification of biomarkers that can guide further lines of treatment. Patients with clinical stage III melanoma may especially benefit from neoadjuvant treatment, as the outcomes of surgery alone are very poor. It is expected that the combination of neoadjuvant and adjuvant treatment may reduce the incidence of relapse and improve survival. Clinical trial registration: eudract.ema.europa.eu/protocol.htm, identifier 2018-004841-17.

IL-6 as new prognostic factor in patients with advanced cutaneous squamous cell carcinoma treated with cemiplimab.

BACKGROUND: Prognostic factors for initial response of advanced cutaneous squamous cell carcinoma to cemiplimab treatment are lacking. Il-6 has been found to affect immune cell populations which impact tumor development. The aim was to investigate the prognostic significance of IL-6 serum levels before and during treatment. METHODS: Serum levels of IL-6 were correlated with clinical outcomes in a retrospective study. RESULTS: Overall, 39 patients were enrolled. High serum levels of IL-6 (> 5.6 pg/ml) were associated with poorer survival (45.1% vs 0 deaths; OS: 16.1 ± 1.5 vs 20.8 ± 0 months, 95% CI 13,046 to 19,184) and shorter PFS (10.3 ± 1.9 vs 18.9 ± 1.5 months; 95% CI 3433 to 10,133) in patients with advanced CSCC treated with cemiplimab. In addition, patients whose IL-6 level increased after treatment with cemiplimab, independently of the basal level, had a poorer response to treatment than patients whose level was reduced or stable after immunotherapy. CONCLUSIONS: Serum levels of IL-6 at baseline and changes after cemiplimab immunotherapy may have a prognostic significance in patients with advanced cutaneous squamous cell carcinoma.

Clinicopathologic and Dermoscopic Features of 20 Cases of Spark's Nevus, a Dermoscopic Simulator of Melanoma.

ABSTRACT: Spark's nevus is a particular type of melanocytic nevus, with histology that shows features of both Spitz and Clark nevus. Detailed dermoscopic features in a series of Spark nevi have not been described yet. We performed a monocentric retrospective observational study on 20 lesions of Spark nevus excised from 19 patients (M:F = 10:9; mean age: 37,6 years), reviewed by 5 experts in dermoscopy and 2 dermatopathologists. A histologic review confirmed that Spark nevi were mostly symmetric (80%), well circumscribed (100%), mainly compound (65%) melanocytic lesions with either epithelioid (55%) or spitzoid (45%) cell morphology and bridging of the nests (100%). Spark nevi were more frequently found on the trunk (85%) in patients with a history of sunburns in childhood (84%), with skin phototype III (79%), and with high nevus count (>100 nevi, 7 patients (36%)). On dermoscopy, we observed different general patterns: multicomponent (40%), reticular-globular-homogeneous (15%), globular homogeneous (15%), reticular (15%), reticular-globular (5%), homogeneous (5%), and globular (5%). Spark nevi showed frequently dermoscopic asymmetry (63%), brown color (90%) with areas of central hyperpigmentation (41%) and peripheral hypopigmentation (28%), atypical pigment network (48%), irregular globules (42%), irregular dots (31%), irregular blotches (16%), blue-whitish veil (13%), peripheral island (25%), irregular hyperpigmented areas (12%), and regression (33%). BRAF mutation was present in 7 of the 10 analyzed cases (70%); all these cases presented a history of evolution. In conclusion, Spark nevi occur on the trunk of young adults with high nevus count and history of sunburns; dermoscopic features are protean, often atypical and suspicious of melanoma.

Early-Stage Oral Tongue Squamous Cell Carcinoma and a Positive Sentinel Lymph Node Biopsy: Description of a Prognostic Correlation between Pre-Treatment Inflammatory Biomarkers, the Depth of Invasion and the Worst Pattern of Invasion.

The aim of this study was to investigate the correlation between pre-treatment inflammatory biomarkers and the post-operative depth of invasion (DOI) and worst pattern of invasion (WPOI) in early-stage oral tongue squamous cell carcinoma (OTSCC) by means of positive sentinel lymph node biopsy (SLNB). A retrospective analysis of patients affected by cN0 T1-T2 OTSCC who had undergone an SLNB at the National Cancer Institute of Naples was performed. The patients were studied using an evaluation of the pre-treatment neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), and a histopathological analysis of the DOI and WPOI. The statistical analysis showed that among the prognostic biomarkers, the NLR was a significant predictor of high WPOI values (p = 0.002). The cut-off NLR value was 2.52 with a probability of developing a positive sentinel lymph node biopsy (SLNB) of 30.3%. In contrast, the DOI value was 5.20 with a probability of developing a positive SLNB of 31.82%. Regarding the WPOI, increasing the WPOI class increased the likelihood of a positive SLNB occurrence, and a positive significant correlation was found between the WPOI and SLNB (Csp = 0.342; p < 0.001). Pre-treatment NLR, together with post-surgical DOI and WPOI, can be a reliable predictor of occult neck metastasis in patients affected by early-stage OTSCC with a clinically negative neck. Further prospective studies with a larger series will be needed to confirm the results obtained and to better define the NLR, WPOI and DOI cut-off values in order for elective neck dissection to be recommended in relation to a clinically negative neck.

Defining the Profile of Patients with Primary Merkel Cell Carcinoma in Central Italy: A Retrospective Analysis.

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer that usually occurs in elderly people on sun-exposed areas, with a predisposition to local recurrence. Evidence suggests a growing incidence over the past decade; however, robust epidemiologic data are still lacking. We describe the MCC population in clinical practice in a retrospective analysis of demographic, clinical, and tumor characteristics from medical records of primary MCC patients, between 2015 and 2020, at six dermatology clinics in Central Italy. Ninety-four patients were included (57.4% male; mean age 78.2 ± 10.1 years, range 47-99 years). The estimated incidence rate of MCC was 0.93 per 100,000 inhabitants/year. Lower limbs were the most frequently affected site (31.5%), and 54% of patients for whom information was available were immunosuppressed. Lymph node involvement was reported in 42.5% of patients, and distant metastases in almost 20%. Most patients underwent surgery for tumor excision and were mainly referred to specialized dermatology clinics by dermatologists (47.9%) and general surgeons (28.7%). Apart from the relatively balanced prevalence of MCC in men and women, the predominant location on lower limbs, and the higher incidence rate compared with previous reports in Italy, this population is, overall, similar to the populations described in other observational studies. MCC management requires the involvement of several specialties. Increased awareness of MCC and standardization of its management are urgently needed.

"Concomitant" Cutaneous and Nodal Spitz Nevus/Tumor: A New Scenario for an Old Problem.

ABSTRACT: Spitz tumors are notoriously characterized by a high propensity to nodal involvement with a morphologically malignant (intraparenchymal) pattern but with little or no tendency toward further spread. We describe a case of spindle cell Spitz neoplasm removed from the thigh in a 34-year-old woman and initially diagnosed as "Spitzoid melanoma;" the sentinel node was characterized by a morphologically benign pattern of nodal involvement, with prevailingly capsular and septal aggregated of melanocytes showing the same cytomorphological features as the cutaneous tumor. Both the cutaneous and the nodal tumor were strongly ROS1-positive on immunohistochemistry; rearrangement of the ROS1 gene was confirmed with fluorescence in situ hybridization on the cutaneous tumor. The clonal relationship between the cutaneous and the nodal capsular/trabecular tumor, as established by their morphological and immunophenotypical resemblance, underlines the existence of a morphologically benign pattern of spread of Spitz neoplasms, as also suggested by the occurrence of eruptive Spitz nevi.

Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinicopathological practice. OBJECTIVE: The objective of the study was to systematically analyse the current state of research on reader studies involving melanoma and to assess their potential clinical relevance by evaluating three main aspects: test set characteristics (holdout/out-of-distribution data set, composition), test setting (experimental/clinical, inclusion of metadata) and representativeness of participating clinicians. METHODS: PubMed, Medline and ScienceDirect were screened for peer-reviewed studies published between 2017 and 2021 and dealing with AI-based skin cancer classification involving melanoma. The search terms skin cancer classification, deep learning, convolutional neural network (CNN), melanoma (detection), digital biomarkers, histopathology and whole slide imaging were combined. Based on the search results, only studies that considered direct comparison of AI results with clinicians and had a diagnostic classification as their main objective were included. RESULTS: A total of 19 reader studies fulfilled the inclusion criteria. Of these, 11 CNN-based approaches addressed the classification of dermoscopic images; 6 concentrated on the classification of clinical images, whereas 2 dermatopathological studies utilised digitised histopathological whole slide images. CONCLUSIONS: All 19 included studies demonstrated superior or at least equivalent performance of CNN-based classifiers compared with clinicians. However, almost all studies were conducted in highly artificial settings based exclusively on single images of the suspicious lesions. Moreover, test sets mainly consisted of holdout images and did not represent the full range of patient populations and melanoma subtypes encountered in clinical practice.