Emerging Role of Epigenetic Alterations as Biomarkers and Novel Targets for Treatments in Pancreatic Ductal Adenocarcinoma

The identification of biomarkers for Alzheimer's disease using a systems biology approach based on lncRNA-circRNA-miRNA-mRNA ceRNA networks

In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer's disease.

Epigenetic alterations fuel brain metastasis via regulating inflammatory cascade

Brain metastasis (BrM) is a major threat to the survival of melanoma, breast, and lung cancer patients. Circulating tumor cells (CTCs) cross the blood-brain barrier (BBB) and sustain in the brain microenvironment. Genetic mutations and epigenetic modifications have been found to be critical in controlling key aspects of cancer metastasis. Metastasizing cells confront inflammation and gradually adapt in the unique brain microenvironment. Currently, it is one of the major areas that has gained momentum. Researchers are interested in the factors that modulate neuroinflammation during BrM. We review here various epigenetic factors and mechanisms modulating neuroinflammation and how this helps CTCs to adapt and survive in the brain microenvironment. Since epigenetic changes could be modulated by targeting enzymes such as histone/DNA methyltransferase, deacetylases, acetyltransferases, and demethylases, we also summarize our current understanding of potential drugs targeting various aspects of epigenetic regulation in BrM.

Deoxyribonucleic acid methylation driven aberrations in pancreatic cancer-related pathways

Pancreatic cancer (PanCa) presents a catastrophic disease with poor overall survival at advanced stages, with immediate requirement of new and effective treatment options. Besides genetic mutations, epigenetic dysregulation of signaling pathway-associated enriched genes are considered as novel therapeutic target. Mechanisms beneath the deoxyribonucleic acid methylation and its utility in developing of epi-drugs in PanCa are under trails. Combinations of epigenetic medicines with conventional cytotoxic treatments or targeted therapy are promising options to improving the dismal response and survival rate of PanCa patients. Recent studies have identified potentially valid pathways that support the prediction that future PanCa clinical trials will include vigorous testing of epigenomic therapies. Epigenetics thus promises to generate a significant amount of new knowledge of biological and medical importance. Our review could identify various components of epigenetic mechanisms known to be involved in the initiation and development of pancreatic ductal adenocarcinoma and related precancerous lesions, and novel pharmacological strategies that target these components could potentially lead to breakthroughs. We aim to highlight the possibilities that exist and the potential therapeutic interventions.

Early Diagnosis of Pancreatic Cancer: Clinical Premonitions, Timely Precursor Detection and Increased Curative-Intent Surgery

BACKGROUND

The overall poor prognosis in pancreatic cancer is related to late clinical detection. Early diagnosis remains a considerable challenge in pancreatic cancer. Unfortunately, the onset of clinical symptoms in patients usually indicate advanced disease or presence of metastasis.

ANALYSIS AND RESULTS

Currently, there are no designated diagnostic or screening tests for pancreatic cancer in clinical use. Thus, identifying risk groups, preclinical risk factors or surveillance strategies to facilitate early detection is a target for ongoing research. Hereditary genetic syndromes are a obvious, but small group at risk, and warrants close surveillance as suggested by society guidelines. Screening for pancreatic cancer in asymptomatic individuals is currently associated with the risk of false positive tests and, thus, risk of harms that outweigh benefits. The promise of cancer biomarkers and use of 'omics' technology (genomic, transcriptomics, metabolomics etc.) has yet to see a clinical breakthrough. Several proposed biomarker studies for early cancer detection lack external validation or, when externally validated, have shown considerably lower accuracy than in the original data. Biopsies or tissues are often taken at the time of diagnosis in research studies, hence invalidating the value of a time-dependent lag of the biomarker to detect a pre-clinical, asymptomatic yet operable cancer. New technologies will be essential for early diagnosis, with emerging data from image-based radiomics approaches, artificial intelligence and machine learning suggesting avenues for improved detection.

CONCLUSIONS

Early detection may come from analytics of various body fluids (eg 'liquid biopsies' from blood or urine). In this review we present some the technological platforms that are explored for their ability to detect pancreatic cancer, some of which may eventually change the prospects and outcomes of patients with pancreatic cancer.

NFL-TBS.40-63 Peptide Gold Complex Nanovector: A Novel Therapeutic Approach to Increase Anticancer Activity by Breakdown of Microtubules in Pancreatic Adenocarcinoma (PDAC)

The role of the NFL-TBS.40-63 peptide is to destroy the microtubule network of target glioma cancer cells. Recently, we have conceived a gold-complex biotinylated NFL-TBS.40-63 (BIOT-NFL) to form a hybrid gold nanovector (BIOT-NFL-PEG-AuNPs). This methodology showed, for the first time, the ability of the BIOT-NFL-PEG-AuNPs to target the destruction of pancreatic cancer cells (PDAC) under experimental conditions, as well as detoxification and preclinical therapeutic efficacy regulated by the steric and chemical configuration of the peptide. For this aim, a mouse transplantation tumor model induced by MIA-PACA-2 cells was applied to estimate the therapeutic efficacy of BIOT-NFL-PEG-AuNPs as a nanoformulation. Our relevant results display that BIOT-NFL-PEG-AuNPs slowed the tumor growth and decreased the tumor index without effects on the body weight of mice with an excellent antiangiogenic effect, mediated by the ability of BIOT-NFL-PEG-AuNPs to alter the metabolic profiles of these MIA-PACA-2 cells. The cytokine levels were detected to evaluate the behavior of serum inflammatory factors and the power of BIOT-NFL-PEG-AuNPs to boost the immune system.

Multi-omics analysis of the oncogenic value of copper Metabolism-Related protein COMMD2 in human cancers

BACKGROUND

The copper metabolism MURR1 domain (COMMD) protein family is involved in tumorigenicity of malignant tumors. However, as the member of COMMD, the role of COMMD2 in human tumors remains unknown.

METHODS

We used The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA) database, Cancer Cell Line Encyclopedia (CCLE) platform, univariate Cox regression analysis, Kaplan-Meier curve, cBioPortal, UALCAN database, Sangerbox online platform, GSCA database gene set enrichment analysis (GSEA), and GeneMANIA to analyze the expression of COMMD2, its prognostic values, genomic alteration patterns, and the correlation with tumor stemness, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrates, drug sensitivity, and gene function enrichment in pan-cancer. qRT-PCR, CCK-8, EdU, wound healing, and transwell migration assays were performed to confirm the function of COMMD2.

RESULTS

COMMD2 was strongly expressed in most cancer types. Elevated COMMD2 expression affects the prognosis, clinicopathological stage, and molecular or immune subtypes of various tumors. Moreover, promoter hypomethylation and mutations in the COMMD2 gene may be associated with its high expression and poor survival. Additionally, we discovered that COMMD2 expression was linked to tumor stemness, TMB, MSI, immune cell infiltration, immune-checkpoint inhibitors, and drug sensitivity in pan-cancer. Furthermore, the COMMD2 gene co-expression network is constructed with GSEA analysis, displaying significant interaction of COMMD2 with E2F targets, G2-M checkpoint, and mitotic spindle in bladder cancer (BLCA). Finally, RNA interference data showed suppression of COMMD2 prevented proliferation and migration of BLCA and uterine corpus endometrial carcinoma (UCEC) cells.

CONCLUSION

Our findings shed light on the COMMD2 functions in human cancers and demonstrate that it is a promising prognostic biomarker and therapeutic target in pan-cancer.