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BackgroundClinical diagnosis of early melanoma (Breslow thickness less than 0.8 mm) is crucial to disease-free survival. However, it is subjective and can be exceedingly difficult, leading to missed melanomas, or unnecessary excision of benign pigmented skin lesions. An objective technique is needed to improve the diagnosis of early melanoma.MethodsWe have developed a method to improve diagnosis of (thin) melanoma, based on Raman spectroscopy. In an ex vivo study in a tertiary referral (pigmented lesions) centre, high-wavenumber Raman spectra were collected from 174 freshly excised melanocytic lesions suspicious for melanoma. Measurements were performed on multiple locations within the lesions. A diagnostic model was developed and validated on an independent data set of 96 lesions.ResultsApproximately 60% of the melanomas included in this study were melanomas in situ. The invasive melanomas had an average Breslow thickness of 0.89 mm. The diagnostic model correctly classified all melanomas (including in situ) with a specificity of 43.8%, and showed a potential improvement of the number needed to treat from 6.0 to 2.7, at a sensitivity of 100%.ConclusionThis work signifies an important step towards accurate and objective clinical diagnosis of melanoma and in particular melanoma with Breslow thickness <0.8 mm.

Differentiated vulvar intraepithelial neoplasia (dVIN) is a premalignant lesion that is known to progress rapidly to invasive carcinoma. Accurate histological diagnosis is therefore crucial to allow appropriate treatment. To identify reliable diagnostic features, we evaluated the inter-observer agreement in the histological assessment of dVIN, among a bi-national, multi-institutional group of pathologists. Two investigators from Erasmus MC selected 36 hematoxylin-eosin-stained glass slides of dVIN and no-dysplasia, and prepared a list of 15 histological features of dVIN. Nine participating pathologists (i) diagnosed each slide as dVIN or no-dysplasia, (ii) indicated which features they used for the diagnosis, and (iii) rated these features in terms of their diagnostic usefulness. Diagnoses rendered by > 50% participants were taken as the consensus (gold standard). p53-immunohistochemistry (IHC) was performed for all cases, and the expression patterns were correlated with the consensus diagnoses. Kappa (ĸ)-statistics were computed to measure inter-observer agreements, and concordance of the p53-IHC patterns with the consensus diagnoses. For the diagnosis of dVIN, overall agreement was moderate (ĸ = 0.42), and pair-wise agreements ranged from slight (ĸ = 0.10) to substantial (ĸ = 0.73). Based on the levels of agreement and ratings of usefulness, the most helpful diagnostic features were parakeratosis, cobblestone appearance, chromatin abnormality, angulated nuclei, atypia discernable under × 100, and altered cellular alignment. p53-IHC patterns showed substantial concordance (ĸ = 0.67) with the consensus diagnoses. Histological interpretation of dVIN remains challenging with suboptimal inter-observer agreement. We identified the histological features that may facilitate the diagnosis of dVIN. For cases with a histological suspicion of dVIN, consensus-based pathological evaluation may improve the reliability of the diagnosis.

Epidemiology of rare cutaneous malignancies in the general population is poorly documented. This descriptive study aimed to estimate the incidence and trends of all skin malignancies between 1989 and 2005. Data on skin tumors were extracted from the Netherlands Cancer registry (except for basal cell carcinoma (BCC) data—only available from Comprehensive Cancer Centre South) and categorized according to the International Classification of Diseases for Oncology, third edition, codes. Age-standardized incidence rates (European standardized population rate, ESR) per 100,000 person-years were calculated per year and for the period between 2001 and 2005. Estimated annual percentage changes (EAPCs) were estimated by Poisson regression models. A total of 356,620 skin tumors were diagnosed between 1989 and 2005. Excluding BCC, squamous cell carcinoma (SCC), and melanoma, the remaining skin tumors constituted about 2% of all skin malignancies. The incidence of melanoma showed the steepest increase (EAPC, 4.0%), and ESR was close to that observed for SCC (EAPC, 2.3%) between 2001 and 2005 (17.1 versus 19.6). Hematolymphoid tumors (ESR=0.74) were mainly cutaneous T-cell lymphomas (60.8%). No significant increases in incidence were observed for lymphomas, and appendageal, fibromatous, and myomatous carcinomas during 1989–2005. In addition to keratinocytic cancers and melanoma, there is a wide variety of skin tumors that constitute <2% of all skin malignancies. The incidence of UV-related skin tumors increased significantly and more steeply than did those of other skin malignancies.

As for many solid cancers, laryngeal cancer is treated surgically, and adequate resection margins are critical for survival. Raman spectroscopy has the capacity to accurately differentiate between cancer and non-cancerous tissue based on their molecular composition, which has been proven in previous work. The aim of this study is to investigate whether Raman spectroscopy can be used to discriminate laryngeal cancer from surrounding non-cancerous tissue. Patients surgically treated for laryngeal cancer were included. Raman mapping experiments were performed ex vivo on resection specimens and correlated to histopathology. Water concentration analysis and CH-stretching region analysis were performed in the high wavenumber range of 2500–4000 cm−1. Thirty-four mapping experiments on 22 resection specimens were used for analysis. Both laryngeal cancer and all non-cancerous tissue structures showed high water concentrations of around 75%. Discriminative information was only found to be present in the CH-stretching region of the Raman spectra of the larynx (discriminative power of 0.87). High wavenumber region Raman spectroscopy can discriminate laryngeal cancer from non-cancerous tissue structures. Contrary to the findings for oral cavity cancer, water concentration is not a discriminating factor for laryngeal cancer.

AimsTumour-associated macrophages (TAMs) and regulatory T cells (Tregs) form a special niche supporting tumour progression, and both correlate with worse survival in head and neck cancers. However, the prognostic role of TAM and Tregs in nasopharyngeal carcinoma (NPC) is still unknown. Therefore, we determined differences in TAMs and Tregs in different NPC subtypes, and their prognostic significance.MethodsTissue of 91 NPCs was assessed for TAMs and Tregs by determination of CD68, CD163, CD206 and FOXP3 expression in the tumour microenvironment. Clinicopathological correlations were assessed using Pearson X2 test, Fisher’s exact test, analysis of variance and Mann-Whitney U test. Survival was analysed using Kaplan-Meier curves and Cox regression.ResultsCD68 and FOXP3 counts were higher in Epstein-Barr virus (EBV)-positive NPC, while CD68−/FOXP3−, CD163+/FOXP3− and CD206+/FOXP3− infiltrates were more common in EBV-negative NPC. In the whole NPC group, CD68−/FOXP3− correlated with worse overall survival (OS), and after multivariate analysis high FOXP3 count showed better OS (HR 0.352, 95% CI 0.128 to 0.968). No difference in M2 counts existed between EBV-positive and negative NPC.ConclusionsFOXP3, a Treg marker, seems to be an independent prognostic factor for better OS in the whole NPC group. Therefore, immune-based therapies targeting Tregs should be carefully evaluated. M2 spectrum macrophages are probably more prominent in EBV-negative NPC with also functional differences compared with EBV-positive NPC.

Differentiated vulvar intraepithelial neoplasia (dVIN) is the precursor lesion of HPV-negative vulvar squamous cell carcinoma (VSCC). The histopathological diagnosis of dVIN can be challenging, as it often resembles vulvar non-neoplastic epithelial disorders (NNED), especially lichen sclerosus (LS). We aimed to establish the most specific and reproducible histological features of dVIN and assessed cytokeratin 13 (CK13) and cytokeratin 17 (CK17) immunohistochemistry as a diagnostic aid. Consecutive cases of dVIN (n = 180) and LS (n = 105) from the period 2010 to 2013 were reviewed using a checklist of histological features. Each feature was recorded as ‘present’ or ‘absent’ and statistical comparison (dVIN vs LS) was made. Interobserver agreement between two pairs of pathologists was assessed for a subset of cases of dVIN (n = 31) and LS and other NNED (n = 23). Immunohistochemistry with CK13, CK17, MIB1 and p53 was performed on dVIN, LS, and other NNED cases. Macronucleoli, features of disturbed maturation and angulated nuclei were significantly more common in dVIN than LS (p < 0.001). We found ‘substantial agreement’ for the diagnosis of dVIN (κ = 0.71). Macronucleoli and deep keratinisation had the highest agreement. In dVIN, the mean percentage of cells staining with CK13 was 15 and with CK17, this was 74. For LS, the mean percentage of cells staining with CK13 was 31, and with CK17, this was 41. By plotting receiver operating characteristic curves (ROC), an area under the curve (AUC) of 0.52 was obtained for CK13, and an AUC of 0.87 was obtained for CK17. The most helpful histological features for diagnosing dVIN were macronucleoli, features of disturbed maturation, and angulated nuclei. Increased CK17 expression may have promise for supporting dVIN diagnosis.

With great interest we have read the letter by De Giorgi et al.1 in which they express their disagreement with the conclusions of our study on the potential value of a Raman spectroscopy device in the clinical diagnosis of cutaneous melanoma.2

Molecular diagnostics has revolutionized cancer management, enabling the identification of diagnostic, prognostic, and predictive biomarkers. Despite advancements in technologies such as whole genome sequencing, their translation into clinical practice remains challenging due to insufficiently demonstrated clinical utility. This study identifies unmet clinical needs and requirements for innovative molecular technologies in oncology through interviews ( n = 22) and an online survey ( n = 116), gathering insights from hospital professionals, industry representatives, and health policy and quality assessment experts. Our findings emphasize the increasing importance of liquid biopsies (LBx), particularly plasma‐based assays. Key unmet needs in this area include therapy response monitoring, minimal residual disease detection, and predictive biomarker testing. Additionally, we outline technology requirements tailored to diverse clinical biomarker applications and both centralized and decentralized laboratory settings. A central challenge lies in achieving an optimal balance between multiplexing capacity and turnaround time. By bridging the gap between technology development and real‐world application, this study paves the way for the implementation of new molecular technologies that better meet the needs of the oncology community, ensuring clinical utility and ultimately improving patient care.

Cyclin-dependent kinase 2-associated protein 1 ( CDK2AP1 ; also known as deleted in oral cancer or DOC1 ) is a tumor suppressor gene known to play functional roles in both cell cycle regulation and in the epigenetic control of embryonic stem cell differentiation, the latter as a core subunit of the nucleosome remodeling and histone deacetylation (NuRD) complex. In the vast majority of oral squamous cell carcinomas (OSCC), expression of the CDK2AP1 protein is reduced or lost. Notwithstanding the latter (and the DOC1 acronym), mutations or deletions in its coding sequence are extremely rare. Accordingly, CDK2AP1 protein-deficient oral cancer cell lines express as much CDK2AP1 mRNA as proficient cell lines. Here, by combining in silico and in vitro approaches, and by taking advantage of patient-derived data and tumor material in the analysis of loss of CDK2AP1 expression, we identified a set of microRNAs, namely miR-21-5p, miR-23b-3p, miR-26b-5p, miR-93-5p, and miR-155-5p, which inhibit its translation in both cell lines and patient-derived OSCCs. Of note, no synergistic effects were observed of the different miRs on the CDK2AP1–3-UTR common target. We also developed a novel approach to the combined ISH/IF tissue microarray analysis to study the expression patterns of miRs and their target genes in the context of tumor architecture. Last, we show that CDK2AP1 loss, as the result of miRNA expression, correlates with overall survival, thus highlighting the clinical relevance of these processes for carcinomas of the oral cavity.

The poor prognosis of oral cavity squamous cell carcinoma (OCSCC) patients is associated with residual tumor after surgery. Raman spectroscopy has the potential to provide an objective intra-operative evaluation of the surgical margins. Our aim was to understand the discriminatory basis of Raman spectroscopy at a histological level. In total, 127 pseudo-color Raman images were generated from unstained thin tissue sections of 25 samples (11 OCSCC and 14 healthy) of 10 patients. These images were clearly linked to the histopathological evaluation of the same sections after hematoxylin and eosin-staining. In this way, Raman spectra were annotated as OCSCC or as a surrounding healthy tissue structure (i.e., squamous epithelium, connective tissue (CT), adipose tissue, muscle, gland, or nerve). These annotated spectra were used as input for linear discriminant analysis (LDA) models to discriminate between OCSCC spectra and healthy tissue spectra. A database was acquired with 88 spectra of OCSCC and 632 spectra of healthy tissue. The LDA models could distinguish OCSCC spectra from the spectra of adipose tissue, nerve, muscle, gland, CT, and squamous epithelium in 100%, 100%, 97%, 94%, 93%, and 75% of the cases, respectively. More specifically, the structures that were most often confused with OCSCC were dysplastic epithelium, basal layers of epithelium, inflammation- and capillary-rich CT, and connective and glandular tissue close to OCSCC. Our study shows how well Raman spectroscopy enables discrimination between OCSCC and surrounding healthy tissue structures. This knowledge supports the development of robust and reliable classification algorithms for future implementation of Raman spectroscopy in clinical practice.