Cardiovascular disease and malignant melanoma

Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning

Heart failure (HF) is a complex and prevalent condition, particularly in the elderly, presenting symptoms like chest tightness, shortness of breath, and dyspnea. The study aimed to improve the classification of HF subtypes and identify potential drug targets by exploring the role of Immunogenic Cell Death (ICD), a process known for its role in tumor immunity but underexplored in HF research. Additionally, the study sought to apply deep learning models to enhance HF classification and identify diagnosis-related genes. Various deep learning encoder models were employed to evaluate their effectiveness in clustering HF based on ICD-related genes. Identified HF subtypes were further refined using differentially expressed genes, allowing for the assessment of immune infiltration and functional enrichment. Advanced machine learning techniques were used to identify diagnosis-related genes, and these genes were used to construct nomogram models. The study also explored gene interactions with miRNA and transcription factors. Distinct HF subtypes were identified through clustering based on ICD-related genes. Differentially expressed genes revealed significant variations in immune infiltration and functional enrichment across these subtypes. The diagnostic model showed excellent performance, with an AUC exceeding 0.99 in both internal and external test sets. Diagnosis-related genes were also identified, serving as the foundation for nomogram models and further exploration of their regulatory interactions. This study provides a novel insight into HF by combining the exploration of ICD, the application of deep learning models, and the identification of diagnosis-related genes. These findings contribute to a deeper understanding of HF subtypes and highlight potential therapeutic targets for improving HF classification and treatment.

Association Between Cancer and Cardiovascular Toxicity: A Nationwide Cross-Sectional Study on NHANES 1999-2018

There is a dearth of evidence pertaining to the relationship of cardiovascular disease (CVD) and its subtype with adjudicated cancer, thereby limiting our understanding of the heightened risk of CVD resulting from long-term complications of cancer and its therapies. The aim of this study was to quantify the risks of CVD and its subtypes in adult cancer survivors compared with cancer-free controls in a nationwide cross-sectional study on Continuous National Health and Nutrition Examination Survey (NHANES). We included 44,442 participants ranging in age from 20 to 85 years. Cancer and CVD diagnoses were ascertained via the household questionnaires. The association of cancer status with the risk of CVD and CVD subtype was examined using weighted logistic regression. Stratification analyses were also performed by age, sex, race, marital status, income status, educational level, and hyperlipidemia. The Wald test was used to calculate P-value for interaction. A total of 4178 participants have cancer, while 4829 participants had CVD, respectively. In the multivariable-adjusted model, the cancer was consistently linked to an elevated risk of CVD. Stratification analyses showed that stronger association between cancer status and CVD risk was found in younger adults, non-white, and participants living without a spouse or partner, and without hyperlipidemia. Our study confirmed that cancer participants were strongly linked to living with CVD, independent of traditional cardiovascular risk factors, especially in younger adults, non-white, and participants living without a spouse or partner, and without hyperlipidemia. There exists a pressing requirement to establish effective strategies for the prevention of CVD within this population characterized by a heightened risk.

Obesity and immune-checkpoint inhibitors in advanced melanoma: A meta-analysis of survival outcomes from clinical studies

Obesity is a chronic inflammatory condition that has been associated with different types of cancer. However, its role in melanoma incidence, progression, and response to immune-checkpoint-inhibitors (ICI) is still controversial. On the one hand, increased levels of lipids and adipokines can promote tumor proliferation and several genes associated with fatty acid metabolism have been found to be upregulated in melanomas. On the other hand, immunotherapy seems to be more effective in obese animal models, presumably due to an increase in CD8 + and subsequent decrease in PD-1 + T-cells in the tumor microenvironment. In humans, several studies have investigated the role of BMI (body mass index) and other adiposity-related parameters as potential prognostic markers of survival in advanced melanoma patients treated with ICI. The aim of this research has been to systematically review the scientific literature on studies evaluating the relationship between overweight/obesity and survival outcomes in patients with advanced melanoma treated with ICI and to perform a meta-analysis on those sharing common characteristics. After screening 1070 records identified through a literature search, 18 articles assessing the role of BMI-related exposure in relation to survival outcomes in ICI-treated patients with advanced melanoma were included in our review. In the meta-analysis of the association between overweight (defined as BMI>25 or BMI 25-30), overall survival (OS), and progression free survival (PFS), 7 studies were included, yielding a summary HR of 0.87 (95% CI: 0.74-1.03) and 0.96 (95% CI: 0.86-1.08), respectively. Our results show that, despite few suggestive findings, the use of BMI as a valuable predictor of melanoma patients' survival in terms of PFS and OS should not be currently recommended, due to the limited evidence available.