Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

Características clínicas e histopatológicas de melanoma subungueal en 57 pacientes mexicanos: una cohorte de 5 años / Clinical and Histopathologic Features of Subungual Melanoma in 57 Mexican Patients: A 5-Year Cohort Study

El melanoma subungueal es un tumor poco común, con peor pronóstico comparado con los de otras localizaciones. Corresponde al 1-23% de los melanomas, según la población. El objetivo de este estudio fue describir las características clínicas e histopatológicas del melanoma subungueal en la población mexicana. Se incluyeron 57 pacientes con melanoma subungueal (19% de los 303 melanomas totales), con una mediana de edad de 71 años. La localización predominante fueron los miembros inferiores (52,6% de los melanomas subungueales) y el primer dedo (75,4% de los casos). El subtipo histológico más frecuente fue el acral lentiginoso (50,9%). La mediana de Breslow fue de 3mm. El estadio IA fue el más frecuente (28,1%). Se encontró una tasa de recurrencia del 19,3% y de metástasis del 8,8%. Las características clínico-patológicas fueron semejantes a lo descrito en la literatura. Es importante realizar un diagnóstico y tratamiento tempranos de cara a mejorar su pronóstico.(AU)

Although subungual melanoma is uncommon, it is associated with worse outcomes than melanomas in other locations and accounts for 1% to 23% of all melanomas, depending on the population. The aim of this study was to describe the clinical and histopathologic features of subungual melanoma in a Mexican population. We identified 303 patients with melanoma, and of these, 19% (57 patients with a median age of 71 years) had subungual melanoma. The main sites affected were the lower limbs (52.6%) and the toe (75.4%). The most common histologic subtype was acral lentiginous melanoma (50.9%). Median Breslow thickness was 3 mm, and stage IA tumors were the most common (in 28.1% of patients). Recurrence and metastasis occurred in 19.3% and 8.8% of patients, respectively. The clinical and histopathologic features identified are similar to those described in the literature. Early diagnosis and treatment are crucial for improving prognosis.(AU)

[Translated article] Clinical and Histopathologic Features of Subungual Melanoma in 57 Mexican Patients: A 5-Year Cohort Study / Características clínicas e histopatológicas de melanoma subungueal en 57 pacientes mexicanos: una cohorte de 5 años

El melanoma subungueal es un tumor poco común, con peor pronóstico comparado con los de otras localizaciones. Corresponde al 1-23% de los melanomas, según la población. El objetivo de este estudio fue describir las características clínicas e histopatológicas del melanoma subungueal en la población mexicana. Se incluyeron 57 pacientes con melanoma subungueal (19% de los 303 melanomas totales), con una mediana de edad de 71 años. La localización predominante fueron los miembros inferiores (52,6% de los melanomas subungueales) y el primer dedo (75,4% de los casos). El subtipo histológico más frecuente fue el acral lentiginoso (50,9%). La mediana de Breslow fue de 3mm. El estadio IA fue el más frecuente (28,1%). Se encontró una tasa de recurrencia del 19,3% y de metástasis del 8,8%. Las características clínico-patológicas fueron semejantes a lo descrito en la literatura. Es importante realizar un diagnóstico y tratamiento tempranos de cara a mejorar su pronóstico.(AU)

Although subungual melanoma is uncommon, it is associated with worse outcomes than melanomas in other locations and accounts for 1% to 23% of all melanomas, depending on the population. The aim of this study was to describe the clinical and histopathologic features of subungual melanoma in a Mexican population. We identified 303 patients with melanoma, and of these, 19% (57 patients with a median age of 71 years) had subungual melanoma. The main sites affected were the lower limbs (52.6%) and the toe (75.4%). The most common histologic subtype was acral lentiginous melanoma (50.9%). Median Breslow thickness was 3 mm, and stage IA tumors were the most common (in 28.1% of patients). Recurrence and metastasis occurred in 19.3% and 8.8% of patients, respectively. The clinical and histopathologic features identified are similar to those described in the literature. Early diagnosis and treatment are crucial for improving prognosis.(AU)

Restrospective reappraisal of the prognostic classification of spitzoid melanocytic neoplasms after BRAF and NRAS mutation characterisation: a single institution experience.

AIMS: The current WHO classification of melanocytic tumours excludes neoplasms showing BRAF or NRAS mutations from the Spitz category. This study aimed to review and reclassify atypical melanocytic tumours with spitzoid morphological features diagnosed between 2009 and 2021 in our hospital after expanding the molecular profile, including BRAF and NRAS mutations in all cases. METHODS AND RESULTS: A total of 71 neoplasms showing spitzoid features (Spitz-like) and atypia were included. The risk of progression of tumours was first studied by integrating the morphology, immunohistochemistry (p16, Ki67, HMB45 and PRAME) and fluorescence in-situ hybridisation (FISH) results (melanoma multiprobe and 9p21). In a second step, after expanding the molecular study, including BRAF and NRAS mutational status, the neoplasms were finally classified into four subgroups: atypical Spitz tumour (AST, n = 45); BRAF-mutated naevus/low-grade melanocytoma with spitzoid morphology (BAMS, n = 2); Spitz melanoma (SM, n = 14); and BRAF or NRAS mutated melanoma with spitzoid features (MSF, n = 10). Follow-up of patients revealed uneventful results for AST and BAMS. Only one SM presented lymph node metastasis after 134 months. Conversely, patients with MSF showed an unfavourable outcome: three developed lymph node metastases after a mean time of 22 months, with one patient presenting distant metastasis and dying of the disease 64 months from diagnosis. The progression-free survival showed significant differences between the four groups of spitzoid tumours (P < 0.001) and between both melanoma subtypes (P = 0.012). CONCLUSIONS: The classification and prognostication of atypical neoplasms with spitzoid features requires the integration of histomorphology with the molecular investigation of tumours, which should include BRAF and NRAS mutational status.

Deep learning data augmentation for Raman spectroscopy cancer tissue classification.

Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular biochemical changes between cancerous vs. normal tissues and cells. In order to design computational approaches for cancer detection, the quality and quantity of tissue samples for RS are important for accurate prediction. In reality, however, obtaining skin cancer samples is difficult and expensive due to privacy and other constraints. With a small number of samples, the training of the classifier is difficult, and often results in overfitting. Therefore, it is important to have more samples to better train classifiers for accurate cancer tissue classification. To overcome these limitations, this paper presents a novel generative adversarial network based skin cancer tissue classification framework. Specifically, we design a data augmentation module that employs a Generative Adversarial Network (GAN) to generate synthetic RS data resembling the training data classes. The original tissue samples and the generated data are concatenated to train classification modules. Experiments on real-world RS data demonstrate that (1) data augmentation can help improve skin cancer tissue classification accuracy, and (2) generative adversarial network can be used to generate reliable synthetic Raman spectroscopic data.

Assessment of a Diagnostic Classification System for Management of Lesions to Exclude Melanoma.

Importance: The proposed MOLEM (Management of Lesion to Exclude Melanoma) schema is more clinically relevant than Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MATH-Dx) for the management classification of melanocytic and nonmelanocytic lesions excised to exclude melanoma. A more standardized way of establishing diagnostic criteria will be crucial in the training of artificial intelligence (AI) algorithms. Objective: To examine pathologists' variability, reliability, and confidence in reporting melanocytic and nonmelanocytic lesions excised to exclude melanoma using the MOLEM schema in a population of higher-risk patients. Design, Setting, and Participants: This cohort study enrolled higher-risk patients referred to a primary care skin clinic in New South Wales, Australia, between April 2019 and December 2019. Baseline demographic characteristics including age, sex, and related clinical details (eg, history of melanoma) were collected. Patients with lesions suspicious for melanoma assessed by a primary care physician underwent clinical evaluation, dermoscopy imaging, and subsequent excision biopsy of the suspected lesion(s). A total of 217 lesions removed and prepared by conventional histologic method and stained with hematoxylin-eosin were reviewed by up to 9 independent pathologists for diagnosis using the MOLEM reporting schema. Pathologists evaluating for MOLEM schema were masked to the original histopathologic diagnosis. Main Outcomes and Measures: Characteristics of the lesions were described and the concordance of cases per MOLEM class was assessed. Interrater agreement and the agreement between pathologists' ratings and the majority MOLEM diagnosis were calculated by Gwet AC1 with quadratic weighting applied. The diagnostic confidence of pathologists was then assessed. Results: A total of 197 patients were included in the study (102 [51.8%] male; 95 [48.2%] female); mean (SD) age was 64.2 (15.8) years (range, 24-93 years). Overall, 217 index lesions were assessed with a total of 1516 histological diagnoses. Of 1516 diagnoses, 677 (44.7%) were classified as MOLEM class I; 120 (7.9%) as MOLEM class II; 564 (37.2%) as MOLEM class III; 114 (7.5%) as MOLEM class IV; and 55 (3.6%) as MOLEM class V. Concordance rates per MOLEM class were 88.6% (class I), 50.8% (class II), 76.2% (class III), 77.2% (class IV), and 74.2% (class V). The quadratic weighted interrater agreement was 91.3%, with a Gwet AC1 coefficient of 0.76 (95% CI, 0.72-0.81). The quadratic weighted agreement between pathologists' ratings and majority MOLEM was 94.7%, with a Gwet AC1 coefficient of 0.86 (95% CI, 0.84-0.88). The confidence in diagnosis data showed a relatively high level of confidence (between 1.0 and 1.5) when diagnosing classes I (mean [SD], 1.3 [0.3]), IV (1.3 [0.3]) and V (1.1 [0.1]); while classes II (1.8 [0.2]) and III (1.5 [0.4]) were diagnosed with a lower level of pathologist confidence (≥1.5). The quadratic weighted interrater confidence rating agreement was 95.2%, with a Gwet AC1 coefficient of 0.92 (95% CI, 0.90-0.94) for the 1314 confidence ratings collected. The confidence agreement for each MOLEM class was 95.0% (class I), 93.5% (class II), 95.3% (class III), 96.5% (class IV), and 97.5% (class V). Conclusions and Relevance: The proposed MOLEM schema better reflects clinical practice than the MPATH-Dx schema in lesions excised to exclude melanoma by combining diagnoses with similar prognostic outcomes for melanocytic and nonmelanocytic lesions into standardized classification categories. Pathologists' level of confidence appeared to follow the MOLEM schema diagnostic concordance trend, ie, atypical naevi and melanoma in situ diagnoses were the least agreed upon and the most challenging for pathologists to confidently diagnose.

Acral Lentiginous Melanoma: A United States Multi-Center Substage Survival Analysis.

BACKGROUND: Acral lentiginous melanoma is associated with worse survival than other subtypes of melanoma. Understanding prognostic factors for survival and recurrence can help better inform follow-up care. OBJECTIVES: To analyze the clinicopathologic features, melanoma-specific survival, and recurrence-free survival by substage in a large, multi-institutional cohort of primary acral lentiginous melanoma patients. METHODS: Retrospective review of the United States Melanoma Consortium database, a multi-center prospectively collected database of acral lentiginous melanoma patients treated between January 2000 and December 2017. RESULTS: Of the 433 primary acral lentiginous melanoma patients identified (median [range] age: 66 [8-97] years; 53% female, 83% white), 66% presented with stage 0-2 disease and the median time of follow-up for the 392 patients included in the survival analysis was 32.5 months (range: 0-259). The 5-year melanoma-specific survivals by stage were 0 = 100%, I = 93.8%, II = 76.2%, III = 63.4%, IIIA = 80.8%, and IV = 0%. Thicker Breslow depth ((HR) = 1.13; 95% CI = 1.05-1.21; P < .001)) and positive nodal status ((HR) = 1.79; 95% CI = 1.00-3.22; P = .050)) were independent prognostic factors for melanoma-specific survival. Breslow depth ((HR = 1.13; 95% CI = 1.07-1.20; P < .001), and positive nodal status (HR = 2.12; 95% CI = 1.38-3.80; P = .001) were also prognostic factors for recurrence-free survival. CONCLUSION: In this cohort of patients, acral lentiginous melanoma was associated with poor outcomes even in early stage disease, consistent with prior reports. Stage IIB and IIC disease were associated with particularly low melanoma-specific and recurrence-free survival. This suggests that studies investigating adjuvant therapies in stage II patients may be especially valuable in acral lentiginous melanoma patients.

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.

Expression Profiles of ASIC1/2 and TRPV1/4 in Common Skin Tumors.

The acid-sensing ion channels ASIC1 and ASIC2, as well as the transient receptor potential vanilloid channels TRPV1 and TRPV4, are proton-gated cation channels that can be activated by low extracellular pH (pHe), which is a hallmark of the tumor microenvironment in solid tumors. However, the role of these channels in the development of skin tumors is still unclear. In this study, we investigated the expression profiles of ASIC1, ASIC2, TRPV1 and TRPV4 in malignant melanoma (MM), squamous cell carcinoma (SCC), basal cell carcinoma (BCC) and in nevus cell nevi (NCN). We conducted immunohistochemistry using paraffin-embedded tissue samples from patients and found that most skin tumors express ASIC1/2 and TRPV1/4. Striking results were that BCCs are often negative for ASIC2, while nearly all SCCs express this marker. Epidermal MM sometimes seem to lack ASIC1 in contrast to NCN. Dermal portions of MM show strong expression of TRPV1 more frequently than dermal NCN portions. Some NCN show a decreasing ASIC1/2 expression in deeper dermal tumor tissue, while MM seem to not lose ASIC1/2 in deeper dermal portions. ASIC1, ASIC2, TRPV1 and TRPV4 in skin tumors might be involved in tumor progression, thus being potential diagnostic and therapeutic targets.

An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm.

Skin cancer is the most common cancer of the body. It is estimated that more than one million people worldwide develop skin cancer each year. Early detection of this cancer has a high effect on the disease treatment. In this paper, a new optimal and automatic pipeline approach has been proposed for the diagnosis of this disease from dermoscopy images. The proposed method includes a noise reduction process before processing for eliminating the noises. Then, the Otsu method as one of the widely used thresholding method is used to characterize the region of interest. Afterward, 20 different features are extracted from the image. To reduce the method complexity, a new modified version of the Thermal Exchange Optimization Algorithm is performed to the features. This improves the method precision and consistency. To validate the proposed method's efficiency, it is implemented to the American Cancer Society database, its results are compared with some state-of-the-art methods, and the final results showed the superiority of the proposed method against the others.

A Transcriptome-Wide Isoform Landscape of Melanocytic Nevi and Primary Melanomas Identifies Gene Isoforms Associated with Malignancy.

Genetic splice variants have become of central interest in recent years, as they play an important role in different cancers. Little is known about splice variants in melanoma. Here, we analyzed a genome-wide transcriptomic dataset of benign melanocytic nevi and primary melanomas (n = 80) for the expression of specific splice variants. Using kallisto, a map for differentially expressed splice variants in melanoma vs. benign melanocytic nevi was generated. Among the top genes with differentially expressed splice variants were Ras-related in brain 6B (RAB6B), a member of the RAS family of GTPases, Macrophage Scavenger Receptor 1 (MSR1), Collagen Type XI Alpha 2 Chain (COLL11A2), and LY6/PLAUR Domain Containing 1 (LYPD1). The Gene Ontology terms of differentially expressed splice variants showed no enrichment for functional gene sets of melanoma vs. nevus lesions, but between type 1 (pigmentation type) and type 2 (immune response type) melanocytic lesions. A number of genes such as Checkpoint Kinase 1 (CHEK1) showed an association of mutational patterns and occurrence of splice variants in melanoma. Moreover, mutations in genes of the splicing machinery were common in both benign nevi and melanomas, suggesting a common mechanism starting early in melanoma development. Mutations in some of these genes of the splicing machinery, such as Serine and Arginine Rich Splicing Factor A3 and B3 (SF3A3, SF3B3), were significantly enriched in melanomas as compared to benign nevi. Taken together, a map of splice variants in melanoma is presented that shows a multitude of differentially expressed splice genes between benign nevi and primary melanomas. The underlying mechanisms may involve mutations in genes of the splicing machinery.

Prognostic variables in patients with thick melanomas. Analysis of 362 cases.

BACKGROUND: Melanoma epidemiological and prognostic studies are based on Caucasian populations, in whom the predominant subtype is superficially-spreading melanoma and in whom thin melanomas (Breslow < 3 mm) predominate. Mexican patients show a predominance of thick melanomas (Breslow ≥ 3 mm), and the acral subtype is the most common. There are no publications on prognostic factors in thick melanomas. We hypothesize that we will identify factors that determine the prognosis in this group of patients. OBJECTIVE: To identify clinical-pathological factors associated with the prognosis of patients with thick melanomas in the Mexican population. MATERIAL AND METHODS: Data on melanomas with Breslow > 3 mm were collected from 2010 to 2015. The prognostic influence of various clinical-pathological factors was analyzed. RESULTS: The most common subtypes were acral melanoma in 271 patients (74.9 %) and nodular melanoma in 49 (13.5 %). Median Breslow thickness was 7 mm. 56.6 % of the patients had lymph node metastases (clinical stage [CS] III), 269 (74.3 %) had ulceration, and surgical margins were positive in 15 (4.1 %). Elevated neutrophil: lymphocyte ratio (≥ 2) was found in 188 (51.9 %). The variables associated with lower overall survival were CS (p < 0.001), Breslow thickness (p = 0.044), ulceration (p = 0.004), mitotic activity (p < 0.001), < 2-cm margin (p < 0.001) and an increased neutrophil: lymphocyte ratio (p = 0.037). In the multivariate analysis, the factors associated with overall survival were CS, mitotic activity, and surgical margin. CONCLUSIONS: In patients with thick melanomas, overall survival is influenced by mitotic activity, a positive margin, and clinical stage.

ANTECEDENTES: Los estudios sobre factores pronóstico de melanoma están basados en poblaciones cau­cásicas, con predominio de melanomas delgados (Breslow < 3 mm). Los pacientes mexicanos muestran predominio de melanomas gruesos (Breslow ≥ 3 mm). OBJETIVO: Identificar factores asocia­dos al pronóstico de pacientes con melanomas gruesos. MATERIAL Y MÉTODOS: Se analizó la influencia pronóstica de factores clinico­patológicos en 362 melanomas gruesos. RESULTADOS: La mediana de Breslow fue de 7 mm, 271 (74.9 %) pacientes tuvieron melanoma acral y 49 (13.5 %) melanoma nodular. El 56.6 % de los pacientes se encontró en etapa clínica [EC] III), 269 (74.3 %) tenía ulceración y 15 (4.1 %) márgenes positivos. Las variables asociadas con menor supervivencia global [SG] fueron la EC (p < 0.001), Breslow (p = 0.044), ulceración (p = 0.004), mitosis (p < 0.001) y margen < 2 cm (p < 0.001) . En el análisis multivariante los factores que influyen en SG fueron la EC, mitosis y el margen quirúrgico. CONCLUSIONES: En pacientes con melanomas gruesos la SG es influida por un margen positive, mitosis y EC.

From Melanocytes to Melanoma Cells: Characterization of the Malignant Transformation by Four Distinctly Different Melanin Fluorescence Spectra (Review).

The melanin fluorescence emitted by pigment cells of the human skin has been a central research topic for decades, because melanin, on the one hand, protects against (solar) radiation in the near-UV range, whereas on the other hand, melanocytes are the starting point for the malignant transformation into melanoma. Until recently, however, melanin fluorescence was not accessible in the context of conventional spectroscopy, because it is ultraweak and is overshadowed by the more intense so-called autofluorescence of endogenous fluorophores. The advent of a new method of laser spectroscopy has made this melanin fluorescence measurable in vivo. A stepwise two-photon absorption with 800 nm photons is used, which more selectively excites melanin (dermatofluoroscopy). Our review summarizes the experimental results on melanin fluorescence of the four types of cutaneous pigment cells from healthy and malignant tissues. Outstanding is the finding that different types of melanocytes (i.e., melanocytes of common nevi, versus dysplastic nevi or versus melanoma cells) show characteristically different fluorescence spectra. The possibilities of using this melanin fluorescence for melanoma diagnosis are shown. Moreover, the uniform fluorescence spectra emitted by different melanoma subtypes are essential. Conclusions are drawn about the molecular processes in the melanosomes that determine fluorescence. Finally, experimental suggestions for further investigations are given.

Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification.

BACKGROUND: Clinicians and pathologists traditionally use patient data in addition to clinical examination to support their diagnoses. OBJECTIVES: We investigated whether a combination of histologic whole slides image (WSI) analysis based on convolutional neural networks (CNNs) and commonly available patient data (age, sex and anatomical site of the lesion) in a binary melanoma/nevus classification task could increase the performance compared with CNNs alone. METHODS: We used 431 WSIs from two different laboratories and analysed the performance of classifiers that used the image or patient data individually or three common fusion techniques. Furthermore, we tested a naive combination of patient data and an image classifier: for cases interpreted as 'uncertain' (CNN output score <0.7), the decision of the CNN was replaced by the decision of the patient data classifier. RESULTS: The CNN on its own achieved the best performance (mean ± standard deviation of five individual runs) with AUROC of 92.30% ± 0.23% and balanced accuracy of 83.17% ± 0.38%. While the classification performance was not significantly improved in general by any of the tested fusions, naive strategy of replacing the image classifier with the patient data classifier on slides with low output scores improved balanced accuracy to 86.72% ± 0.36%. CONCLUSION: In most cases, the CNN on its own was so accurate that patient data integration did not provide any benefit. However, incorporating patient data for lesions that were classified by the CNN with low 'confidence' improved balanced accuracy.

Variables pronósticas de pacientes con melanomas gruesos. Análisis de 362 casos / Prognostic variables in patients with thick melanomas. Analysis of 362 cases

Resumen Antecedentes: Los estudios sobre factores pronóstico de melanoma están basados en poblaciones caucásicas, con predominio de melanomas delgados (Breslow < 3 mm). Los pacientes mexicanos muestran predominio de melanomas gruesos (Breslow ≥ 3 mm). Objetivo: Identificar factores asociados al pronóstico de pacientes con melanomas gruesos. Material y métodos: Se analizó la influencia pronóstica de factores clinicopatológicos en 362 melanomas gruesos. Resultados: La mediana de Breslow fue de 7 mm, 271 (74.9 %) pacientes tuvieron melanoma acral y 49 (13.5 %) melanoma nodular. El 56.6 % de los pacientes se encontró en etapa clínica [EC] III), 269 (74.3 %) tenía ulceración y 15 (4.1 %) márgenes positivos. Las variables asociadas con menor supervivencia global [SG] fueron la EC (p < 0.001), Breslow (p = 0.044), ulceración (p = 0.004), mitosis (p < 0.001) y margen < 2 cm (p < 0.001) . En el análisis multivariante los factores que influyen en SG fueron la EC, mitosis y el margen quirúrgico. Conclusiones: En pacientes con melanomas gruesos la SG es influida por un margen positive, mitosis y EC.

Abstract Background: Studies on prognostic factors in melanoma are based on Caucasian populations, with a predominance of thin melanomas (Breslow <3 mm). Mexican patients show a predominance of thick melanomas (Breslow ≥ 3 mm). Objective: To identify factors associated with the prognosis of patients with thick melanomas. Material and methods: The prognostic influence of clinicopathological factors was analyzed in 362 thick melanomas. Results: The Breslow median was 7 mm, 271 (74.9 %) patients had acral melanoma and 49 (13.5 %) nodular melanoma. The 56.6 % of patients were found in clinical stage [CS] III), 269 (74.3 %) had ulceration, and 15 (4.1 %) had positive margins. The variables associated with lower overall survival [OS] were CS (p < 0.001), Breslow (p = 0.044), ulceration (p = 0.004), mitosis (p < 0.001) and margin < 2 cm (p < 0.001). In the multivariate analysis, the factors influencing OS were CD, mitosis, and the surgical margin. Conclusions: In patients with thick melanomas, OS is influenced by a positive margin, mitosis and CS.

The utility of PRAME immunohistochemistry in the evaluation of challenging melanocytic tumors.

BACKGROUND: PRAME (PReferentially expressed Antigen in Melanoma) immunohistochemistry has demonstrated high specificity for unequivocal melanomas; however, its utility in ambiguous melanocytic neoplasms has yet to be fully elucidated. METHODS: Cases of challenging melanocytic neoplasms were subclassified into one of three categories: challenging, favor benign (FB), challenging, cannot be subclassified (CCS), or challenging, favor malignant (FM). Using a previously published system, whereby cases with diffuse staining (>75%) were considered positive, scoring of PRAME was performed. Additionally, tumors with hotspot staining were also considered positive. RESULTS: Sixteen out of 85 tumors showed positive staining representing 5% of FB tumors, 24% of CCS tumors, and 47% of FM. In FB and CCS tumors, positive staining was mainly encountered in atypical intraepidermal melanocytic proliferations and spitzoid neoplasms. The specificity of positive PRAME staining was 95% and its concordance with the final diagnostic interpretation was 75%. CONCLUSIONS: PRAME positivity is more common in neoplasms favored to be malignant by histopathologic evaluation. Its clinical utility may include early diagnosis of incipient melanoma in situ. Rarely, benign melanocytic neoplasms could show diffuse expression of PRAME, and additional studies are needed to determine optimal utilization. Lastly, hotspot staining may increase its sensitivity without much compromise in specificity.

Biology of Melanoma.

Melanoma skin cancer is derived from skin melanocytes and has a high risk of metastatic spread. The era of molecular genetics and next-generation sequencing has uncovered the role of oncogenic BRAFV600E mutations in many melanomas, validated the role of ultraviolet-induced DNA mutations in melanoma formation, and uncovered many of the molecular events that occur during melanoma development. Targeted therapies and immunotherapy have dramatically improved outcomes and provided an increased rate of cure for metastatic melanoma. This article reviews the formation of melanoma, the molecular events involved in melanoma growth and metastasis, and the biology underlying resistance to melanoma therapies.

Distribution and clinical role of KIT gene mutations in melanoma according to subtype: a study of 492 Spanish patients.

BACKGROUND: KIT mutations are primarily associated with acral and mucosal melanoma, and have been reported to show higher prevalence in chronic sun-damaged (CSD) than non-CSD melanomas. OBJECTIVES: To investigate the prevalence of KIT mutations in melanoma according to subtype, and determine the clinical role of such mutations. MATERIALS & METHODS: We present results from a study of a Spanish population of 492 melanomas, classified according to the latest World Health Organization (WHO) guidelines. We analysed the mutational status of KIT and correlated with different clinical variables related to sun exposure and family history. RESULTS: KIT mutations were significantly more frequent in acral (3/36; 8.3%) and mucosal (4/8; 50%) melanomas than non-acral cutaneous melanomas. No significant difference was observed in KIT mutational status between CSD and non-CSD melanomas. CONCLUSION: Our results suggest that KIT mutations in melanoma tumours are unrelated to the development of nevi or chronic sun damage, but their presence is associated with aggressive melanomas which show ulceration, vascular invasiveness, and increased Breslow thickness. These findings are consistent with those reported by The Cancer Genome Atlas network.