Melanoma secretion of transforming growth factor-β2 leads to loss of epidermal AMBRA1 threatening epidermal integrity and facilitating tumour ulceration

Porcine-derived collagen peptides promote re-epithelialisation through activation of integrin signalling

Chronic non-healing cutaneous wounds represent a major burden to patients and healthcare providers worldwide, emphasising the continued unmet need for credible and efficacious therapeutic approaches for wound healing. We have recently shown the potential for collagen peptides to promote proliferation and migration during cutaneous wound healing. In the present study, we demonstrate that the application of porcine-derived collagen peptides significantly increases keratinocyte and dermal fibroblast expression of integrin α2β1 and activation of an extracellular signal-related kinase (ERK)-focal adhesion kinase (FAK) signalling cascade during wound closure in vitro. SiRNA-mediated knockdown of integrin β1 impaired porcine-derived collagen peptide-induced wound closure and activation of ERK-FAK signalling in keratinocytes but did not impair ERK or FAK signalling in dermal fibroblasts, implying the activation of differing downstream signalling pathways. Studies in ex vivo human 3D skin equivalents subjected to punch biopsy-induced wounding confirmed the ability of porcine-derived collagen peptides to promote wound closure by enhancing re-epithelialisation. Collectively, these data highlight the translational and clinical potential for porcine-derived collagen peptides as a viable therapeutic approach to promote re-epithelialisation of superficial cutaneous wounds.

AMBRA1 levels predict resistance to MAPK inhibitors in melanoma

Intrinsic and acquired resistance to mitogen-activated protein kinase inhibitors (MAPKi) in melanoma remains a major therapeutic challenge. Here, we show that the clinical development of resistance to MAPKi is associated with reduced tumor expression of the melanoma suppressor Autophagy and Beclin 1 Regulator 1 (AMBRA1) and that lower expression levels of AMBRA1 predict a poor response to MAPKi treatment. Functional analyses show that loss of AMBRA1 induces phenotype switching and orchestrates an extracellular signal-regulated kinase (ERK)-independent resistance mechanism by activating focal adhesion kinase 1 (FAK1). In both in vitro and in vivo settings, melanomas with low AMBRA1 expression exhibit intrinsic resistance to MAPKi therapy but higher sensitivity to FAK1 inhibition. Finally, we show that the rapid development of resistance in initially MAPKi-sensitive melanomas can be attributed to preexisting subclones characterized by low AMBRA1 expression and that cotreatment with MAPKi and FAK1 inhibitors (FAKi) effectively prevents the development of resistance in these tumors. In summary, our findings underscore the value of AMBRA1 expression for predicting melanoma response to MAPKi and supporting the therapeutic efficacy of FAKi to overcome MAPKi-induced resistance.

The combined immunohistochemical expression of AMBRA1 and SQSTM1 identifies patients with poorly differentiated cutaneous squamous cell carcinoma at risk of metastasis: A proof of concept study

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) incidence continues to increase globally with, as of yet, an unmet need for reliable prognostic biomarkers to identify patients at increased risk of metastasis. The aim of the present study was to test the prognostic potential of the combined immunohistochemical expression of the autophagy regulatory biomarkers, AMBRA1 and SQSTM1, to identify high-risk patient subsets.

METHODS

A retrospective cohort of 68 formalin-fixed paraffin-embedded primary cSCCs with known 5-year metastatic outcomes were subjected to automated immunohistochemical staining for AMBRA1 and SQSTM1. Digital images of stained slides were annotated to define four regions of interest: the normal and peritumoral epidermis, the tumor mass, and the tumor growth front. H-score analysis was used to semi-quantify AMBRA1 or SQSTM1 expression in each region of interest using Aperio ImageScope software, with receiver operator characteristics and Kaplan-Meier analysis used to assess prognostic potential.

RESULTS

The combined loss of expression of AMBRA1 in the tumor growth front and SQSTM1 in the peritumoral epidermis identified patients with poorly differentiated cSCCs at risk of metastasis (*p < 0.05).

CONCLUSIONS

Collectively, these proof of concept data suggest loss of the combined expression of AMBRA1 in the cSCC growth front and SQSTM1 in the peritumoral epidermis as a putative prognostic biomarker for poorly differentiated cSCC.

Validation of epidermal AMBRA1 and loricrin (AMBLor) as a prognostic biomarker for nonulcerated American Joint Committee on Cancer stage I/II cutaneous melanoma

BACKGROUND

Combined expression of the autophagy-regulatory protein AMBRA1 (activating molecule in Beclin1-regulated autophagy) and the terminal differentiation marker loricrin in the peritumoral epidermis of stage I melanomas can identify tumour subsets at low risk of -metastasis.

OBJECTIVES

To validate the combined expression of peritumoral AMBRA1 and loricrin (AMBLor) as a prognostic biomarker able to identify both stage I and II melanomas at low risk of tumour recurrence.

METHODS

Automated immunohistochemistry was used to analyse peritumoral AMBRA1 and loricrin expression in geographically distinct discovery (n = 540) and validation (n = 300) cohorts of nonulcerated American Joint Committee on Cancer (AJCC) stage I and II melanomas. AMBLor status was correlated with clinical outcomes in the discovery and validation cohorts separately and combined.

RESULTS

Analysis of AMBLor in the discovery cohort revealed a recurrence-free survival (RFS) rate of 95.5% in the AMBLor low-risk group vs. 81.7% in the AMBLor at-risk group (multivariate log-rank, P < 0.001) and a negative predictive value (NPV) of 96.0%. In the validation cohort, AMBLor analysis revealed a RFS rate of 97.6% in the AMBLor low-risk group vs. 78.3% in the at-risk group (multivariate log-rank, P < 0.001) and a NPV of 97.6%. In a multivariate model considering AMBLor, Breslow thickness, age and sex, analysis of the combined discovery and validation cohorts showed that the estimated effect of AMBLor was statistically significant, with a hazard ratio of 3.469 (95% confidence interval 1.403-8.580, P = 0.007) and an overall NPV of 96.5%.

CONCLUSIONS

These data provide further evidence validating AMBLor as a prognostic biomarker to identify nonulcerated AJCC stage I and II melanoma tumours at low risk of disease recurrence.

TCF12 Activates TGFB2 Expression to Promote the Malignant Progression of Melanoma

As one of the most common malignant tumors, melanoma is a serious threat to human health. More than half of melanoma patients have a BRAF mutation, and 90% of them have a BRAF(V600E) mutation. There is a targeted therapy for patients using a BRAF(V600E) inhibitor. However, no response to treatment is generally inevitable due to the heterogeneity of melanoma. Coupled with its high metastatic character, melanoma ultimately leads to poor overall survival. This study aimed to explore the possible mechanisms of melanoma metastasis and identify a more effective method for the treatment of melanoma. In this paper, we report that TCF12 expression is higher in melanoma, especially in metastatic tumors, through analyzing data from TCGA. Then, cell proliferation, colony formation, and transwell assays show that the upregulated expression of TCF12 can promote proliferation and metastasis of melanoma cells in vitro. The same result is confirmed in the subcutaneous tumor formation assay. Moreover, TGFB2 is identified as a direct downstream target of TCF12 by RNA-seq, qPCR, immunoblotting, ChIP, and a dual luciferase reporting assay. Interestingly, depletion of TCF12 can sensitize melanoma to BRAF inhibition both in vitro and in vivo. Overall, our results demonstrate that TCF12 promotes melanoma progression and can be a potential tumor therapeutic target.

Melanoma-derived mediators can foster the premetastatic niche: crossroad to lymphatic metastasis

The natural history of advanced malignant melanoma demonstrates that, in most cases, widespread tumor dissemination is preceded by regional metastases involving tumor-draining lymph nodes [sentinel lymph nodes (SLNs)]. Under physiological conditions, LNs play a central role in immunosurveillance to non-self-antigens to which they are exposed via afferent lymph. The dysfunctional immunity in SLNs is mediated by tumor secretory factors that allow the survival of metastatic melanoma cells within the LN by creating a premetastatic niche (PMN). Recent studies outline the altered microenvironment of LNs shaped by melanoma mediators. Here, we discuss tumor secretory factors involved in subverting tumor immunity and remodeling LNs and highlight emerging therapeutic strategies to reinvigorate antitumoral immunity in SLNs.

Diagnostic and Prognostic Deep Learning Applications for Histological Assessment of Cutaneous Melanoma

Melanoma is among the most devastating human malignancies. Accurate diagnosis and prognosis are essential to offer optimal treatment. Histopathology is the gold standard for establishing melanoma diagnosis and prognostic features. However, discrepancies often exist between pathologists, and analysis is costly and time-consuming. Deep-learning algorithms are deployed to improve melanoma diagnosis and prognostication from histological images of melanoma. In recent years, the development of these machine-learning tools has accelerated, and machine learning is poised to become a clinical tool to aid melanoma histology. Nevertheless, a review of the advances in machine learning in melanoma histology was lacking. We performed a comprehensive literature search to provide a complete overview of the recent advances in machine learning in the assessment of melanoma based on hematoxylin eosin digital pathology images. In our work, we review 37 recent publications, compare the methods and performance of the reviewed studies, and highlight the variety of promising machine-learning applications in melanoma histology.