Recent Developments of Circulating Tumor Cell Analysis for Monitoring Cutaneous Melanoma Patients

The role of micrometastasis in high-risk skin cancers

The propensity to metastasize is the most important prognostic indicator for solid cancers. New insights into the mechanisms of early carcinogenesis have revealed micrometastases are generated far earlier than previously thought. Evidence supports a synergistic relationship between vascular and lymphatic seeding which can occur before there is clinical evidence of a primary tumour. Early vascular seeding prepares distal sites for colonisation while regional lymphatics are co-opted to promote facilitative cancer cell mutations. In response, the host mounts a global inflammatory and immunomodulatory response towards these cells supporting the concept that cancer is a systemic disease. Cancer staging systems should be refined to better reflect cancer cell loads in various tissue compartments while clinical perspectives should be broadened to encompass this view when approaching high-risk cancers. Measured adjunctive therapies implemented earlier for low-volume, in-transit cancer offers the prospect of preventing advanced disease and the need for heroic therapeutic interventions. This review seeks to re-appraise how we view the metastatic process for solid cancers. It will explore in-transit metastasis in the context of high-risk skin cancer and how it dictates disease progression. It will also discuss how these implications will influence our current staging systems and its consequences on management.

Point-of-care optical devices in clinical imaging and screening: A review on the state of the art

Integration of optical technologies in biomedical sciences permitted light manipulation at smaller time-length scales for specific detection and imaging of biological entities. Similarly, advances in consumer electronics and wireless telecommunications strengthened the development of affordable and portable point-of-care (POC) optical devices, circumventing the necessity of conventional clinical analyses by trained personnel. However, many of the POC optical technologies translated from bench to bedside require industrial support for their commercialization and dissemination to the population. This review aims to demonstrate the intriguing progress and challenges of emerging POC devices utilizing optics for clinical imaging (depth-resolved and perfusion imaging) and screening (infections, cancer, cardiac health, and haematologic disorders) with a focus on research studies over the previous 3 years. Special attention is given to POC optical devices that can be utilized in resource-constrained environments.

Metastatic Melanoma: Liquid Biopsy as a New Precision Medicine Approach

Precision medicine has driven a major change in the treatment of many forms of cancer. The discovery that each patient is different and each tumor mass has its own characteristics has shifted the focus of basic and clinical research to the singular individual. Liquid biopsy (LB), in this sense, presents new scenarios in personalized medicine through the study of molecules, factors, and tumor biomarkers in blood such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes and circulating tumor microRNAs (ct-miRNAs). Moreover, its easy application and complete absence of contraindications for the patient make this method applicable in a great many fields. Melanoma, given its highly heterogeneous characteristics, is a cancer form that could significantly benefit from the information linked to liquid biopsy, especially in the treatment management. In this review, we will focus our attention on the latest applications of liquid biopsy in metastatic melanoma and possible developments in the clinical setting.

The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer

Machine learning (ML) can enhance a dermatologist's work, from diagnosis to customized care. The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. This analysis aims to provide dermatologists with a guide that helps demystify the basics of ML and its different applications to identify their possible challenges correctly. This paper surveyed studies on skin cancer detection using deep learning to assess the features and advantages of other techniques. Moreover, this paper also defined the basic requirements for creating a skin cancer detection application, which revolves around two main issues: the full segmentation image and the tracking of the lesion on the skin using deep learning. Most of the techniques found in this survey address these two problems. Some of the methods also categorize the type of cancer too.

Skin Cancer Research Goes Digital: Looking for Biomarkers within the Droplets

Skin cancer, which includes the most frequent malignant non-melanoma carcinomas (basal cell carcinoma, BCC, and squamous cell carcinoma, SCC), along with the difficult to treat cutaneous melanoma (CM), pose important worldwide issues for the health care system. Despite the improved anti-cancer armamentarium and the latest scientific achievements, many skin cancer patients fail to respond to therapies, due to the remarkable heterogeneity of cutaneous tumors, calling for even more sophisticated biomarker discovery and patient monitoring approaches. Droplet digital polymerase chain reaction (ddPCR), a robust method for detecting and quantifying low-abundance nucleic acids, has recently emerged as a powerful technology for skin cancer analysis in tissue and liquid biopsies (LBs). The ddPCR method, being capable of analyzing various biological samples, has proved to be efficient in studying variations in gene sequences, including copy number variations (CNVs) and point mutations, DNA methylation, circulatory miRNome, and transcriptome dynamics. Moreover, ddPCR can be designed as a dynamic platform for individualized cancer detection and monitoring therapy efficacy. Here, we present the latest scientific studies applying ddPCR in dermato-oncology, highlighting the potential of this technology for skin cancer biomarker discovery and validation in the context of personalized medicine. The benefits and challenges associated with ddPCR implementation in the clinical setting, mainly when analyzing LBs, are also discussed.

Urine Cell-Free MicroRNAs in Localized Prostate Cancer Patients

Prostate cancer (PCa) is the most common cancer in men. Prostate-specific antigen screening is recommended for the detection of PCa. However, its specificity is limited. Thus, there is a need to find more reliable biomarkers that allow non-invasive screening for early-stage PCa. This study aims to explore urine microRNAs (miRs) as diagnostic biomarkers for PCa. We assessed cell-free miR (cfmiR) profiles of urine and plasma samples from pre- and post-operative PCa patients (n = 11) and normal healthy donors (16 urine and 24 plasma) using HTG EdgeSeq miRNA Whole Transcriptome Assay based on next-generation sequencing. Furthermore, tumor-related miRs were detected in formalin-fixed paraffin-embedded tumor tissues obtained from patients with localized PCa. Specific cfmiRs signatures were found in urine samples of localized PCa patients using differential expression analysis. Forty-two cfmiRs that were detected were common to urine, plasma, and tumor samples. These urine cfmiRs may have potential utility in diagnosing early-stage PCa and complementing or improving currently available PCa screening assays. Future studies may validate the findings.