Dermoscopy as a Tool for Identifying Potentially Metastatic Thin Melanoma: A Clinical-Dermoscopic and Histopathological Case-Control Study.

Despite being early-stage tumors, thin cutaneous melanomas contribute significantly to mortality and have a rising incidence. A retrospective case-control study was performed to identify clinical-dermoscopic and histopathological variables linked to local and distant metastases in melanomas ≤0.8 mm. Data from 1 January 2000 to 22 June 2022 were analyzed from two Italian skin cancer referral centers. Sixteen patients with ≤0.8 mm melanomas developing metastases were studied compared to controls without metastases over 5 years. Statistical analysis involved Pearson's chi-squared test or Fisher's exact test. Of the 1396 cases, 1.1% progressed. The median diagnosis age was 49 (range 28-83), with 56.3% men and 43.7% women. The torso was the primary tumor site (43.7%). Clinically, lesions were pigmented (>10 mm diameter: 73.3%, ≥3 colors: 80%). Dermoscopically, the common features were white patches (73.3%), atypical vascular patterns (66.5%), blue-gray areas (60%) and absent pigment networks (60%). Histopathologically, all cases had adverse features like regression (87.4%), dermal mitoses (50%), a vertical growth phase (62.5%) and ulceration (12.5%). These findings were statistically significant compared to controls (p < 0.05). In ≤0.8 mm melanomas, specific clinical-dermoscopic traits might indicate higher metastatic potential when paired with adverse histopathological features.

Perineural invasion score system and clinical outcomes in resected pancreatic cancer patients.

BACKGROUND/OBJECTIVES: Perineural invasion (PNI), classified according to its presence or absence in tumor specimens, is recognized as a poor prognostic factor in pancreatic ductal adenocarcinoma (PDAC) patients. Herein, we identified five histological features of PNI and investigated their impact on survival outcomes of PDAC resected patients. METHODS: Five histopathological features of PNI (diameter, number, site, sheath involvement, and mitotic figures within perineural invasion) were combined in an additional final score (ranging from 0 to 8), and clinical data of PDAC patients were retrospectively analyzed. PNI + patients were stratified in two categories according to the median score value (<6 and ≥ 6, respectively). Impact of PNI on disease-free survival (DFS) and overall survival (OS) were analyzed. RESULTS: Forty-five patients were enrolled, of whom 34 with PNI (PNI+) and 11 without PNI (PNI-). The DFS was 11 months vs. not reached (NR) (p = 0.258), while the OS was 19 months vs. NR (p = 0.040) in PNI+ and PNI- patients, respectively. A ≥6 PNI was identified as an independent predictor of worse OS vs. <6 PNI + patients (29 vs. 11 months, p < 0.001) and <6 PNI+ and PNI- patients (43 vs. 11 months, p < 0.001). PNI ≥6 was an independent negative prognostic factor of DFS vs. <6 PNI+ and PNI- patients (13 vs. 6 months, p = 0.022). CONCLUSIONS: We report a PNI scoring system that stratifies surgically-treated PDAC patients in a graded manner that correlates with patient prognosis better than the current dichotomous (presence/absence) definition. However, further and larger studies are needed to support this PNI scoring system.

Spatial Proximity and Relative Distribution of Tumor-Infiltrating Lymphocytes and Macrophages Predict Survival in Melanoma.

Tumor microenvironment plays a crucial role in primary cutaneous melanoma (CM) progression. Although the role of tumor-infiltrating lymphocyte (TIL) density has been known for a long time, its spatial distribution and impact with or without tumor-associated macrophages (TAMs) remain controversial. Herein, we investigated spatial proximity between tumor cells and immune cells in 113 primary CM and its correlation with disease-free (DFS) and overall survival (OS). The study cohort included clinical stage II (n = 79) and stage III (n = 34) primary CM with a Breslow thickness of >2 mm (with a median age of 64 years, including 72 men and 41 women). In univariate models, patients with SOX10+ melanoma cells with high proximity to CD8+ TILs in a 20 µm radius showed longer DFS (hazard ratio [HR], 0.58; 95% CI, 0.36-0.93; P = .025) and OS (HR, 0.55; 95% CI, 0.32-0.92; P = .023). Furthermore, at multivariate combined analysis, patients with SOX10+ melanoma cells with high proximity to CD8+ TILs or low proximity to CD163+ TAMs in a 20 µm radius showed an increased OS (aHR, 0.37; 95% CI, 0.14-0.96; P = .04) compared with melanoma patients with low proximity to CD8+ TILs or high proximity to CD163+ TAMs. In a subgroup analysis including 92 patients, a significant negative impact on DFS (aHR, 4.49; 95% CI, 1.73-11.64; P = .002) and OS (aHR, 3.97; 95% CI, 1.37-11.49; P = .01) was observed in sentinel lymph node (SLN)-negative patients with a high proximity of CD163+ TAMs to CD8+ TILs. These findings could help identify high-risk patients in the context of thick melanoma and a negative SLN. Our study suggests the importance of quantifying not only the density of immune cells but also the individual and combined relative spatial distributions of tumor cells and immune cells for clinical outcomes in SLN-negative primary CM patients.

Tumor-Infiltrating Lymphocyte Recognition in Primary Melanoma by Deep Learning Convolutional Neural Network.

The presence of tumor-infiltrating lymphocytes (TILs) is associated with a favorable prognosis of primary melanoma (PM). Recently, artificial intelligence (AI)-based approach in digital pathology was proposed for the standardized assessment of TILs on hematoxylin and eosin-stained whole slide images (WSIs). Herein, the study applied a new convolution neural network (CNN) analysis of PM WSIs to automatically assess the infiltration of TILs and extract a TIL score. A CNN was trained and validated in a retrospective cohort of 307 PMs including a training set (237 WSIs, 57,758 patches) and an independent testing set (70 WSIs, 29,533 patches). An AI-based TIL density index (AI-TIL) was identified after the classification of tumor patches by the presence or absence of TILs. The proposed CNN showed high performance in recognizing TILs in PM WSIs, showing 100% specificity and sensitivity on the testing set. The AI-based TIL index correlated with conventional TIL evaluation and clinical outcome. The AI-TIL index was an independent prognostic marker associated directly with a favorable prognosis. A fully automated and standardized AI-TIL appeared to be superior to conventional methods at differentiating the PM clinical outcome. Further studies are required to develop an easy-to-use tool to assist pathologists to assess TILs in the clinical evaluation of solid tumors.

Impact of second opinion pathology review in the diagnosis and management of atypical melanocytic lesions: A prospective study of the Italian Melanoma Intergroup (IMI) and EORTC Melanoma Group.

BACKGROUND: The clinical value of an expert pathological review in patients with an atypical melanocytic lesion diagnosis remains unclear. Herein, we evaluate its impact in a prospective clinical study. METHODS: Patients with newly diagnosed or suspected atypical melanocytic proliferations and challenging skin tumours were reviewed prospectively by a specialised dermatopathologist through the nationwide 'Second Opinion Platform' of the Italian Melanoma Intergroup (IMI) network. The primary aim was the rate of major discrepancies that impacted patient management. Major discrepancies in diagnosis between referral and specialised review were blindly re-analysed by a panel of European Organisation for Research and Treatment (EORTC) Melanoma pathologists. RESULTS: The samples submitted to central review included 254 lesions from 230 patients. The most frequent referral diagnoses were atypical melanocytic nevi of different subtypes (74/254, 29.2%), invasive melanomas (61/254, 24.0%), atypical melanocytic proliferations (37/254, 14.6%), AST (21/254, 8.3%) and in situ melanomas (17/254, 6.7%). There was disagreement between referral diagnosis and expert review in 90/254 cases (35.4%). Most importantly, 60/90 (66.7%) were major discordances with a change to the patient's clinical management. Among the 90 discordant cases, the most frequent new diagnosis occurred in World Health Organisation (WHO) Pathway I, followed by WHO Pathway IV (64/90 and 12/90, respectively). In total, 51/60 cases with major discrepancies were blindly re-evaluated by EORTC Melanoma pathologists with a final interobserver agreement in 90% of cases. CONCLUSION: The study highlights that a second opinion for atypical melanocytic lesions affects clinical management in a minor, but still significant, proportion of cases. A central expert review supports pathologists and clinicians to limit the risk of both over- and under-treatment.

Clinical, histopathological and molecular features of dedifferentiated melanomas: An EORTC Melanoma Group Retrospective Analysis.

PURPOSE: Dedifferentiated melanoma (DedM) poses significant diagnostic challenges. We aimed to investigate the clinical, histopathological and molecular features of DedM. Methylation signature (MS) and copy number profiling (CNP) were carried out in a subgroup of cases. PATIENTS AND METHODS: A retrospective series of 78 DedM tissue samples from 61 patients retrieved from EORTC (European Organisation for Research and Treatment of Cancer) Melanoma Group centres were centrally reviewed. Clinical and histopathological features were retrieved. In a subgroup of patients, genotyping through Infinium Methylation microarray and CNP analysis was carried out. RESULTS: Most patients (60/61) had a metastatic DedM showing most frequently an unclassified pleomorphic, spindle cell, or small round cell morphology akin to undifferentiated soft tissue sarcoma, rarely associated with heterologous elements. Overall, among 20 successfully analysed tissue samples from 16 patients, we found retained melanoma-like MS in only 7 tissue samples while a non-melanoma-like MS was observed in 13 tissue samples. In two patients from whom multiple specimens were analysed, some of the samples had a preserved cutaneous melanoma MS while other specimens exhibited an epigenetic shift towards a mesenchymal/sarcoma-like profile, matching the histological features. In these two patients, CNP was largely identical across all analysed specimens, in line with their common clonal origin, despite significant modification of their epigenome. CONCLUSIONS: Our study further highlights that DedM represents a real diagnostic challenge. While MS and genomic CNP may help pathologists to diagnose DedM, we provide proof-of-concept that dedifferentiation in melanoma is frequently associated with epigenetic modifications.

Digital Quantification of Intratumoral CD8+ T-Cells Predicts Relapse and Unfavorable Outcome in Uveal Melanoma.

Although it is a disease that occurs mainly in the Caucasian population, uveal melanoma (UM) is the most common primary intraocular tumor in adults. Here, we used digital pathology and image analysis for the diagnosis of UM and the prediction of the prognosis. Our retrospective study included a total of 404 histopathological slides from 101 patients. A digital image acquisition and quantitative analysis of tissue immune biomarkers (CD4, CD8, CD68, CD163) were performed. A negative impact of the intratumoral CD8 positive cell density higher than 13.3 cells/mm2 was detected for both RFS (HR 2.08, 95% Cl 1.09 to 3.99, p = 0.027) and OS (HR 3.30, 95% CI 1.58 to 6.88, p = 0.001). Moreover, we confirmed that older age and stage III were independent negative prognostic factors for both RFS and OS. Our results suggest that a specific distribution profile of CD8 in UM might predict the risk of relapse and death, with potential implications for determining which subgroups of UMs are amenable to specific pharmacological treatment regimens.

Bright-Field Multiplex Immunohistochemistry Assay for Tumor Microenvironment Evaluation in Melanoma Tissues.

The tumor microenvironment (TME) plays a crucial role in melanoma development, progression and response to treatment. As many of the most relevant TME cell phenotypes are defined by the simultaneous detection of more than two markers, the bright-field (BF) multiplex immunohistochemistry (IHC) technique has been introduced for the quantitative assessment and evaluation of the relative spatial distances between immune cells and melanoma cells. In the current study, we aimed to validate BF multiplex IHC techniques in the Ventana Discovery Ultra Immunostainer to be applied to the evaluation of the TME in variably pigmented melanoma tissues. The BF multiplex IHC staining was performed using different combinations of six immune-cell markers-CD3, CD4, CD8, CD20, CD68 and CD163-and the melanoma cell marker SOX10. Our results show that the BF double IHC Yellow/Purple protocol guarantees the maximum contrast in all the cell populations tested and the combination SOX10 (Green), CD8 (Yellow) and CD163 (Purple) of the BF triple IHC protocol ensures the best contrast and discrimination between the three stained cell populations. Furthermore, the labeled cells were clearly distinct and easily identifiable using the image analysis software. Our standardized BF IHC multiplex protocols can be used to better assess the immune contexts of melanoma patients with potential applications to drive therapeutic decisions within clinical trials.

Overexpression of helper T cell type 2-related molecules in the skin of patients with eosinophilic dermatosis of hematologic malignancy.

BACKGROUND: Eosinophilic dermatosis of hematologic malignancy (EDHM) is a rare dermatosis associated with blood tumors. OBJECTIVE: To characterize the expression of T-cell and B-cell markers and pruritogenic mediators in EDHM skin. METHODS: Immunohistochemical and immunofluorescence analysis were performed in 12 skin samples of EDHM, 11 samples of bullous pemphigoid (BP), and 5 samples from healthy controls (HC). Serum levels of interleukin (IL) 4 were analyzed in 11 patients with EDHM, 11 BP patients, and 5 HC by enzyme-linked immunosorbent assay. RESULTS: T-cell markers, including clusters of differentiation (CD) 3, CD4, CD8, and CD5 were significantly overexpressed in EDHM and BP skin compared to HC. A predominance of CD4+ over CD8+ cells and GATA3+ (helper T cell type 2 [Th2] marker) over T-bet+ (Th1 marker) cells were observed. FOXP3 expression was increased but the FOXP3/CD4 ratio was low. B-cell markers were under-represented, without significant differences between the 3 groups. IL-4 and IL-31 were significantly overexpressed in EDHM and BP compared to HC and colocalized with the Th2-associated marker GATA3. Eotaxin-1 was significantly overexpressed in EDHM compared to BP and HC. IL-4 serum concentration was significantly increased in EDHM and BP compared to HC. LIMITATIONS: Small sample size; retrospective design. CONCLUSIONS: Targeting Th2-related molecules, in particular IL-4, holds promise for EDHM management.

NTRK Gene Fusion Detection in Atypical Spitz Tumors.

Atypical Spitz tumors (AST) deviate from stereotypical Spitz nevi for one or more atypical features and are now regarded as an intermediate category of melanocytic tumors with uncertain malignant potential. Activating NTRK1/NTRK3 fusions elicit oncogenic events in Spitz lesions and are targetable with kinase inhibitors. However, their prevalence among ASTs and the optimal approach for their detection is yet to be determined. A series of 180 ASTs were screened with pan-TRK immunohistochemistry and the presence of NTRK fusions was confirmed using FISH, two different RNA-based NGS panels for solid tumors, and a specific real time RT-PCR panel. Overall, 26 ASTs showed pan-TRK immunostaining. NTRK1 fusions were detected in 15 of these cases showing cytoplasmic immunoreaction, whereas NTRK3 was detected in one case showing nuclear immunoreaction. Molecular tests resulted all positive in only two ASTs (included the NTRK3 translocated), RNA-based NGS and real time RT-PCR were both positive in three cases, and FISH and real time RT-PCR in another two cases. In seven ASTs NTRK1 fusions were detected only by FISH and in two cases only by real time RT-PCR. The frequency of NTRK fusions in ASTs is 9%, with a clear prevalence of NTRK1 compared to NTRK3 alterations. Pan-TRK immunohistochemistry is an excellent screening test. Confirmation of NTRK fusions may require the use of different molecular techniques.

NGS-Based Analysis of Atypical Deep Penetrating Nevi.

Deep penetrating nevi (DPNs) are rare melanocytic neoplasms consisting of pigmented spindled or epithelioid melanocytes with a distinctive wedge-shaped configuration showing activation of the WNT pathway, with unusual cyto-architectural features. It is unclear whether they show a distinct genomic profile associated with a diverse metastatic potential. We describe herein a cohort of 21 atypical DPNs analyzed by next-generation sequencing using the Ion AmpliSeq™ Comprehensive Cancer Panel. We found that ß-catenin exon 3 was mutated in 95% and MAP kinase pathway genes in 71% of the cases. Less frequent mutations were observed in HRAS (19%) and MAP2K1 (24%). Isocitrate dehydrogenases 1 (IDH1) mutations, including R132C, V178I, and S278L, were identified in 38% of cases and co-existed with BRAF/HRAS mutations. The only case with progressive nodal disease carried alterations in the ß-catenin pathway and mutations in IDH1 and NRAS (codon 61). By a comprehensive mutation analysis, we found low genetic heterogeneity and a lack of significant associations between specific gene mutations and histopathological features, despite atypical features. Whether the acquisition of an NRAS or IDH1 mutation in an atypical DPN may represent a molecular evolution implying a pathway to melanoma progression should be confirmed in a larger series.

Digital Immunophenotyping Predicts Disease Free and Overall Survival in Early Stage Melanoma Patients.

BACKGROUND: the prognostic significance of tumor infiltrating lymphocytes (TILs) in intermediate/thick primary cutaneous melanoma (PCM) remains controversial, partially because conventional evaluation is not reliable, due to inter-observer variability and diverse scoring methods. We aimed to assess the prognostic impact of the density and spatial distribution of immune cells in early stage intermediate/thick PCM. MATERIALS AND METHODS: digital image acquisition and quantitative analysis of tissue immune biomarkers (CD3, CD4, CD8, CD68, PD-L1, CD163, FOX-P3, and PD-1) was carried out in a training cohort, which included patients with primary PCM ≥ 2 mm diagnosed, treated, and followed-up prospectively in three Italian centers. Results were validated in an independent Italian cohort. RESULTS: in the training cohort, 100 Stage II-III melanoma patients were valuable. At multivariable analysis, a longer disease free survival (DFS) was statistically associated with higher levels of CD4+ intratumoral T-cells (aHR [100 cell/mm2 increase] 0.98, 95%CI 0.95-1.00, p = 0.041) and CD163+ inner peritumoral (aHR [high vs. low] 0.56, 95%CI 0.32-0.99, p = 0.047). A statistically significant longer DFS (aHR [high-high vs. low-low] 0.52, 95%CI 0.28-0.99, p = 0.047) and overall survival (OS) (aHR [high-high vs. low-low] 0.39, 95%CI 0.18-0.85, p = 0.018) was found in patients with a high density of both intratumoral CD8+ T-cells and CD68+ macrophages as compared to those with low density of both intratumoral CD8+ T-cells and CD68+ macrophages. Consistently, in the validation cohort, patients with high density of both intratumoral CD8+ and CD3+ T-cells were associated to a statistically better DFS (aHR[high-high vs. low-low] 0.24, 95%CI 0.10-0.56, p < 0.001) and those with high density of both intratumoral CD8+ and CD68+ were associated to a statistically longer OS (aHR[high-high vs. low-low] 0.28, 95%CI 0.09-0.86, p = 0.025). CONCLUSION: our findings suggest that a specific preexisting profile of T cells and macrophages distribution in melanomas may predict the risk of recurrence and death with potential implications for the stratification of stage II-III melanoma patients.

Recognition of Cutaneous Melanoma on Digitized Histopathological Slides via Artificial Intelligence Algorithm.

Increasing incidence of skin cancer combined with a shortage of dermatopathologists has increased the workload of pathology departments worldwide. In addition, the high intraobserver and interobserver variability in the assessment of melanocytic skin lesions can result in underestimated or overestimated diagnosis of melanoma. Thus, the development of new techniques for skin tumor diagnosis is essential to assist pathologists to standardize diagnoses and plan accurate patient treatment. Here, we describe the development of an artificial intelligence (AI) system that recognizes cutaneous melanoma from histopathological digitalized slides with clinically acceptable accuracy. Whole-slide digital images from 100 formalin-fixed paraffin-embedded primary cutaneous melanoma were used to train a convolutional neural network (CNN) based on a pretrained Inception-ResNet-v2 to accurately and automatically differentiate tumoral areas from healthy tissue. The CNN was trained by using 60 digital slides in which regions of interest (ROIs) of tumoral and healthy tissue were extracted by experienced dermatopathologists, while the other 40 slides were used as test datasets. A total of 1377 patches of healthy tissue and 2141 patches of melanoma were assessed in the training/validation set, while 791 patches of healthy tissue and 1122 patches of pathological tissue were evaluated in the test dataset. Considering the classification by expert dermatopathologists as reference, the trained deep net showed high accuracy (96.5%), sensitivity (95.7%), specificity (97.7%), F1 score (96.5%), and a Cohen's kappa of 0.929. Our data show that a deep learning system can be trained to recognize melanoma samples, achieving accuracies comparable to experienced dermatopathologists. Such an approach can offer a valuable aid in improving diagnostic efficiency when expert consultation is not available, as well as reducing interobserver variability. Further studies in larger data sets are necessary to verify whether the deep learning algorithm allows subclassification of different melanoma subtypes.

TRPA1 Expression in Synovial Sarcoma May Support Neural Origin.

Synovial sarcoma (SS) is a malignant mesenchymal soft tissue neoplasm. Despite its name, the cells of origin are not synovial cells, but rather neural, myogenic, or multipotent mesenchymal stem cells have been proposed as possible cells originators. Unlike other sarcomas, an unusual presentation of long-term pain at the tumor site has been documented, but the exact mechanisms have not been fully clarified yet. The transient receptor potential ankyrin 1 (TRPA1) is a nonselective cation channel mainly expressed in primary sensory neurons, where it functions as a pain sensor. TRPA1 have also been described in multiple non-excitable cells, including those derived from neural crest stem cells such as glial cells and, in particular, Schwann cell oligodendrocytes and astrocytes. We evaluated TRPA1 expression in SS. We selected a cohort of 41 SSs, and by immunohistochemistry, we studied TRPA1 expression. TRPA1 was found in 92.6% of cases. Triple TRPA1/pS100/SOX10 and TRPA1/SLUG/SNAIL staining strongly supports a neural origin of SS. TRPA1 positivity was also observed in a subset of cases negative with pS100, SOX10 and/or SLUG/SNAIL, and these divergent phenotypes may reflect a process of tumor plasticity and dedifferentiation of neural-derived SSs. Given the functional diversity of TRPA1 and its expression in neuronal and non-neuronal multipotent neural crest stem cells, it remains to be determined whether TRPA1 expression in SSs neoplastic cells plays a role in the molecular mechanism associated with premonitory pain symptoms and tumor progression.