Dupuytren\'s contracture (DC) is a fibroproliferative disorder of the palmar fascia characterised by the digits\' flexion contractures and is associated with abnormal build-up of type III collagen. The prevalence of the disease is reported to be highest among Northern European descendants. However, the disease is widespread globally with varying prevalence. DC is a multifactorial disease, having both genetic and environmental factors contributing to the causality of the disease. Over the years, various studies have been conducted to understand the molecular mechanism and genetic aspects of DC but there is a lack of reports on the variants found in the exonic regions. Most reports are backdated making it necessary to re-evaluate the variants to further understand the genetic aetiology of DC. In this review, we first highlight the genetic aspects and previous genetic studies on DC. The report is followed by a discussion on the molecular pathways suggested to be associated with DC and a summary of the genetic variants in the exonic regions found in DC and their connections with the molecular pathways. A total of nine variants were reported originating from six genes comprising three pathways. Most variants reported are involved in the Wnt signalling pathway. Moreover, all variants identified are in European/Caucasian subjects and the variants found in the exonic regions are missense variants. A comparison of these findings with variants from populations of other regions can be conducted to identify the variants with the most occurrence to act as biomarkers or therapeutic targets for DC.

The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies (\"multiomic\" strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual constraints are discussed, along with an exploration of ethical considerations inherent to AI applications for healthcare and research. The ultimate goal is to provide a comprehensive examination of the multifaceted landscape of this innovative field and its clinical implications.

Targeted NGS allows a fast and efficient multi-gene analysis and the detection of key gene aberrations in melanoma. In this study, we aim to describe the genetic alterations in a series of 87 melanoma cases using the oncomine focus assay (OFA), relate these results with the clinicopathological features of the patients, and compare them with our previous study results in which we used a smaller panel, the oncomine solid tumor (OST) DNA kit. Patients diagnosed with advanced melanoma at our center from 2020 to 2022 were included and DNA and RNA were extracted for sequencing. Common mutated genes were BRAF (29%), NRAS (28%), ALK, KIT, and MAP2K1 (5% each). Co-occurring mutations were detected in 29% of the samples, including BRAF with KIT, CTNNB1, EGFR, ALK, HRAS, or MAP2K1. Amplifications and rearrangements were detected in 5% of cases. Only BRAF mutation showed a significant statistical association with sun exposure. For patients with a given genetic profile, the melanoma survival and recurrence-free survival rates were equivalent, but not for stage and LDH values. This expanded knowledge of molecular alterations has helped to more comprehensively characterize our patients and has provided relevant information for deciding the best treatment strategy.

BACKGROUND: Exposure to chemical mixtures inherent in air pollution, has been shown to be associated with the risk of breast and lung cancers. However, studies on the molecular mechanisms of exposure to a mixture of these pollutants, such as hydrocarbons, in the development of breast and lung cancers are scarce. We utilized in silico toxicogenomic analysis to elucidate the molecular pathways linked to both cancers that are influenced by exposure to a mixture of selected hydrocarbons. The Comparative Toxicogenomics Database and Cytoscape software were used for data mining and visualization.
RESULTS: Twenty-five hydrocarbons, common in air pollution with carcinogenicity classification of 1 A/B or 2 (known/presumed or suspected human carcinogen), were divided into three groups: alkanes and alkenes, halogenated hydrocarbons, and polyaromatic hydrocarbons. The in silico data-mining revealed 87 and 44 genes commonly interacted with most of the investigated hydrocarbons are linked to breast and lung cancer, respectively. The dominant interactions among the common genes are co-expression, physical interaction, genetic interaction, co-localization, and interaction in shared protein domains. Among these genes, only 16 are common in the development of both cancers. Benzo(a)pyrene and tetrachlorodibenzodioxin interacted with all 16 genes. The molecular pathways potentially affected by the investigated hydrocarbons include aryl hydrocarbon receptor, chemical carcinogenesis, ferroptosis, fluid shear stress and atherosclerosis, interleukin 17 signaling pathway, lipid and atherosclerosis, NRF2 pathway, and oxidative stress response.
CONCLUSIONS: Within the inherent limitations of in silico toxicogenomics tools, we elucidated the molecular pathways associated with breast and lung cancer development potentially affected by hydrocarbons mixture. Our findings indicate adaptive responses to oxidative stress and inflammatory damages are instrumental in the development of both cancers. Additionally, ferroptosis-a non-apoptotic programmed cell death driven by lipid peroxidation and iron homeostasis-was identified as a new player in these responses. Finally, AHR potential involvement in modulating IL-8, a critical gene that mediates breast cancer invasion and metastasis to the lungs, was also highlighted. A deeper understanding of the interplay between genes associated with these pathways, and other survival signaling pathways identified in this study, will provide invaluable knowledge in assessing the risk of inhalation exposure to hydrocarbons mixture. The findings offer insights into future in vivo and in vitro laboratory investigations that focus on inhalation exposure to the hydrocarbons mixture.

This review systematically examines gender differences in hepatocellular carcinoma (HCC), identifying the influence of sex hormones, genetic variance, and environmental factors on the disease\'s epidemiology and treatment outcomes. Recognizing the liver as a sexually dimorphic organ, we highlight how gender-specific risk factors, such as alcohol consumption and obesity, contribute differently to hepatocarcinogenesis in men and women. We explore molecular mechanisms, including the differential expression of androgen and estrogen receptors, which mediate diverse pathways in tumor biology such as cell proliferation, apoptosis, and DNA repair. Our analysis underscores the critical need for gender-specific research in liver cancer, from molecular studies to clinical trials, to improve diagnostic accuracy and therapeutic effectiveness. By incorporating a gender perspective into all facets of liver cancer research, we advocate for a more precise and personalized approach to cancer treatment that acknowledges gender as a significant factor in both the progression of HCC and its response to treatment. This review aims to foster a deeper understanding of the biological and molecular bases of gender differences in HCC and to promote the development of tailored interventions that enhance outcomes for all patients.

The substantial heterogeneity exhibited by head and neck cancer (HNC), encompassing diverse cellular origins, anatomical locations, and etiological contributors, combined with the prevalent late-stage diagnosis, poses significant challenges for clinical management. Genomic sequencing endeavors have revealed extensive alterations in key signaling pathways that regulate cellular proliferation and survival. Initiatives to engineer therapies targeting these dysregulated pathways are underway, with several candidate molecules progressing to clinical evaluation phases, including FDA approval for agents like the EGFR-targeting monoclonal antibody cetuximab for K-RAS wild-type, EGFR-mutant HNSCC treatment. Non-coding RNAs (ncRNAs), owing to their enhanced stability in biological fluids and their important roles in intracellular and intercellular signaling within HNC contexts, are now recognized as potent biomarkers for disease management, catalyzing further refined diagnostic and therapeutic strategies, edging closer to the personalized medicine desideratum. Enhanced comprehension of the genomic and immunological landscapes characteristic of HNC is anticipated to facilitate a more rigorous assessment of targeted therapies benefits and limitations, optimize their clinical deployment, and foster innovative advancements in treatment approaches. This review presents an update on the molecular mechanisms and mutational spectrum of HNC driving the oncogenesis of head and neck malignancies and explores their implications for advancing diagnostic methodologies and precision therapeutics.

The ability of pathogenic bacteria to evade antibiotic treatment is an intricate and multifaceted phenomenon. Over the years, treatment failure among patients due to determinants of antimicrobial resistance (AMR) has been the focal point for the research and development of new therapeutic agents. However, the survival of bacteria by persisting under antibiotic stress has largely been overlooked. Bacterial persisters are a subpopulation of sensitive bacterial cells exhibiting a noninheritable drug-tolerant phenotype. They are linked to the recalcitrance of infections in healthcare settings, in turn giving rise to AMR variants. The importance of bacterial persistence in recurring infections has been firmly recognized. Fundamental work over the past decade has highlighted numerous unique tolerance factors contributing to the persister phenotype in many clinically relevant pathogens. This review summarizes contributing factors that could aid in developing new strategies against bacterial antibiotic persisters.

Combining immune checkpoint inhibitors, specifically nivolumab (anti-PD-1) and ipilimumab (anti-CTLA-4), holds substantial promise in revolutionizing cancer treatment. This review explores the transformative impact of these combinations, emphasizing their potential for enhancing therapeutic outcomes across various cancers. Immune checkpoint proteins, such as PD1 and CTLA4, play a pivotal role in modulating immune responses. Blocking these checkpoints unleashes anticancer activity, and the synergy observed when combining multiple checkpoint inhibitors underscores their potential for enhanced efficacy. Nivolumab and ipilimumab harness the host\'s immune system to target cancer cells, presenting a powerful approach to prevent tumor development. Despite their efficacy, immune checkpoint inhibitors are accompanied by a distinct set of adverse effects, particularly immune-related adverse effects affecting various organs. Understanding these challenges is crucial for optimizing treatment strategies and ensuring patient well-being. Ongoing clinical trials are actively exploring the combination of checkpoint inhibitory therapies, aiming to decipher their synergistic effects and efficacy against diverse cancer types. This review discusses the mechanisms, adverse effects, and various clinical trials involving nivolumab and ipilimumab across different cancers, emphasizing their transformative impact on cancer treatment.

The process of identification and management of neurological disorder conditions faces challenges, prompting the investigation of novel methods in order to improve diagnostic accuracy. In this study, we conducted a systematic literature review to identify the significance of genetics- and molecular-pathway-based machine learning (ML) models in treating neurological disorder conditions. According to the study\'s objectives, search strategies were developed to extract the research studies using digital libraries. We followed rigorous study selection criteria. A total of 24 studies met the inclusion criteria and were included in the review. We classified the studies based on neurological disorders. The included studies highlighted multiple methodologies and exceptional results in treating neurological disorders. The study findings underscore the potential of the existing models, presenting personalized interventions based on the individual\'s conditions. The findings offer better-performing approaches that handle genetics and molecular data to generate effective outcomes. Moreover, we discuss the future research directions and challenges, emphasizing the demand for generalizing existing models in real-world clinical settings. This study contributes to advancing knowledge in the field of diagnosis and management of neurological disorders.

Medulloblastoma is the most frequently encountered malignant brain tumor in the pediatric population. The standard of care currently consists of surgical resection, craniospinal irradiation, and multi-agent chemotherapy. However, despite this combination of multiple aggressive modalities, recurrence of the disease remains a substantial concern, and treatment resistance is a rising issue. The development of this resistance results from the interplay of a myriad of anatomical properties, cellular processes, molecular pathways, and genetic and epigenetic alterations. In fact, several efforts have been directed towards this domain and characterizing the major contributors to this resistance. Herein, this review highlights the different mechanisms that drive relapse and are implicated in the occurrence of treatment resistance and discusses them in the context of the latest molecular-based classification of medulloblastoma. These mechanisms include the impermeability of the blood-brain barrier to drugs, the overactivation of specific molecular pathways, the resistant and multipotent nature of cancer stem cells, intratumoral and intertumoral heterogeneity, and metabolic plasticity. Subsequently, we build on that to explore potential strategies and targeted agents that can abrogate these mechanisms, undermine the development of treatment resistance, and augment medulloblastoma\'s response to therapeutic modalities.