Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach.

Alzheimer's Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD's pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10-12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.

Intensity standardization methods in magnetic resonance imaging of head and neck cancer.

BACKGROUND AND PURPOSE: Conventional magnetic resonance imaging (MRI) poses challenges in quantitative analysis because voxel intensity values lack physical meaning. While intensity standardization methods exist, their effects on head and neck MRI have not been investigated. We developed a workflow based on healthy tissue region of interest (ROI) analysis to determine intensity consistency within a patient cohort. Through this workflow, we systematically evaluated intensity standardization methods for MRI of head and neck cancer (HNC) patients. MATERIALS AND METHODS: Two HNC cohorts (30 patients total) were retrospectively analyzed. One cohort was imaged with heterogenous acquisition parameters (HET cohort), whereas the other was imaged with homogenous acquisition parameters (HOM cohort). The standard deviation of cohort-level normalized mean intensity (SD NMIc), a metric of intensity consistency, was calculated across ROIs to determine the effect of five intensity standardization methods on T2-weighted images. For each cohort, a Friedman test followed by a post-hoc Bonferroni-corrected Wilcoxon signed-rank test was conducted to compare SD NMIc among methods. RESULTS: Consistency (SD NMIc across ROIs) between unstandardized images was substantially more impaired in the HET cohort (0.29 ± 0.08) than in the HOM cohort (0.15 ± 0.03). Consequently, corrected p-values for intensity standardization methods with lower SD NMIc compared to unstandardized images were significant in the HET cohort (p < 0.05) but not significant in the HOM cohort (p > 0.05). In both cohorts, differences between methods were often minimal and nonsignificant. CONCLUSIONS: Our findings stress the importance of intensity standardization, either through the utilization of uniform acquisition parameters or specific intensity standardization methods, and the need for testing intensity consistency before performing quantitative analysis of HNC MRI.

Genomic and Transcriptomic Characterisation of Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

Standard treatment for locally advanced rectal cancer (LARC) is neoadjuvant chemoradiotherapy (NACRT), followed by surgical resection. However, >70% of patients do not achieve a complete pathological response and have higher rates of relapse and death. There are no validated pre- or on-treatment factors that predict response to NACRT besides tumour stage and size. We characterised the response of 33 LARC patients to NACRT, collected tumour samples from patients prior to, during and after NACRT, and performed whole exome, transcriptome and high-depth targeted sequencing. The pre-treatment LARC genome was not predictive of response to NACRT. However, in line with the increasing recognition of microbial influence in cancer, RNA analysis of pre-treatment tumours suggested a greater abundance of Fusobacteria in intermediate and poor responders. In addition, we investigated tumour heterogeneity and evolution in response to NACRT. While matched pre-treatment, on-treatment and post-treatment tumours revealed minimal genome evolution overall, we identified cases in which microsatellite instability developed or was selected for during NACRT. Recent research has suggested a role for adaptive mutability to targeted therapy in colorectal cancer cells. We provide preliminary evidence of selection for mismatch repair deficiency in response to NACRT. Furthermore, pre-NACRT genomic landscapes do not predict treatment response but pre-NACRT microbiome characteristics may be informative.

Biomarkers of radiation-induced vascular injury.

OBJECTIVE: Cancer survivorship has thrown the spotlight on the incidence of nonmalignant chronic diseases in cancer patients. Endothelial injury is increasingly recognized as a consequence of cancer treatment, particularly after radiation therapy (RT). This review is to provide a current understanding on the pathophysiological mechanisms and predictive biomarkers of radiation-induced vascular injury. RECENT FINDINGS: Radiation directly impacts vasculature by causing endothelial apoptosis and senescence, and alterations in normal homeostasis. This altered milieu at the endothelial surface may contribute to a systemic chronic inflammatory state that is superimposed upon the cascade of normal senescence processes leading to acceleration of age-related disorders, atherosclerosis, and chronic fibrosis. Vasculature imaging, blood-based or cell-component biomarkers, and signatures of genomics, proteomics, metabolomics, and radiomics are potential tools for detection of vascular damage after irradiation. CONCLUSIONS: Development of a valid prediction model by combining an array of imaging tools, blood-based biomarkers, coupled with novel predictors like exosomes and metabolic degradation products can serve to identify RT-induced vascular injury early for subsequent introduction of newer therapeutic approaches to counter radiation morbidity.

Recent advances in radiation therapy of pancreatic cancer.

Pancreatic cancer has a dismal prognosis with an overall survival outcome of just 5% at five years. However, paralleling our improved understanding of the biology of pancreatic cancer, treatment paradigms have also continued to evolve with newer advances in surgical techniques, chemotherapeutic agents, radiation therapy (RT) techniques, and immunotherapy paradigms. RT dose, modality, fraction size, and sequencing are being evaluated actively, and the interplay between RT and immune effects has opened up newer avenues of research. In this review, we will emphasize recent advances in RT for pancreatic cancer, focusing on preoperative chemoradiation, RT dose escalation, sparing of the spleen to reduce lymphopenia, and combination of RT with immunotherapy.