Cuproplasia characterization in colon cancer assists to predict prognosis and immunotherapeutic response.

Introduction: Colon cancer is the 3rd most prevalent cancer worldwide, with more than 900,000 deaths annually. Chemotherapy, targeted treatment, and immunotherapeutic treatment are the three cornerstones of colon cancer treatment; however, the occurrence of immune therapy resistance is the most pressing problem to solve. Copper is a mineral nutrient that is both beneficial and potentially toxic to cells and is increasingly implicated in cell proliferation and death pathways. Cuproplasia is characterized by copper-dependent cell growth and proliferation. This term encompasses both neoplasia and hyperplasia and describes the primary and secondary effects of copper. The connection between copper and cancer has been noted for decades. However, the relationship between cuproplasia and colon cancer prognosis remains unclear. Method: In this study, we applied bioinformatics approaches including WGCNA, GSEA and etc. to delineate cuproplasia characterization of colon cancer, set up a robust Cu_riskScore model based on cuproplasia-relevant genes and found its relevant biological processes use qRT-pCR to validate our results on our cohort. Result: The Cu_riskScore is found to be relevant to Stage and MSI-H subtype, and some biological processes including MYOGENESIS and MYC TARGETS. The Cu_riskScore high and low groups also showed different immune infiltration pattern and genomic traits. Finally, the result of our cohort showed the Cu_riskScore gene RNF113A has a marked effect in predicting immunotherapy response. Discussion: In conclusion, we identified a cuproplasia-related gene expression signature consisting of six genes and studied the landscape of the clinical and biological characterization of this model in Colon Cancer. Furthermore, the Cu_riskScore was demonstrated to be a robust prognostic indicator and predictive factor for the benefits of immunotherapy.

Exploring biomarkers for prognosis and neoadjuvant chemosensitivity in rectal cancer: Multi-omics and ctDNA sequencing collaboration.

Introduction: This study aimed to identified the key genes and sequencing metrics for predicting prognosis and efficacy of neoadjuvant chemotherapy (nCT) in rectal cancer (RC) based on genomic DNA sequencing in samples with different origin and multi-omics association database. Methods: We collected 16 RC patients and obtained DNA sequencing data from cancer tissues and plasma cell-free DNA before and after nCT. Various gene variations were analyzed, including single nucleotide variants (SNV), copy number variation (CNV), tumor mutation burden (TMB), copy number instability (CNI) and mutant-allele tumor heterogeneity (MATH). We also identified genes by which CNV level can differentiate the response to nCT. The Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database were used to further evaluate the specific role of therapeutic relevant genes and screen out the key genes in multi-omics levels. After the intersection of the screened genes from differential expression analysis, survival analysis and principal components analysis dimensionality reduction cluster analysis, the key genes were finally identified. Results: The genes CNV level of principal component genes in baseline blood and cancer tissues could significantly distinguish the two groups of patients. The CNV of HSP90AA1, EGFR, SRC, MTOR, etc. were relatively gained in the better group compared with the poor group in baseline blood. The CNI and TMB was significantly different between the two groups. The increased expression of HSP90AA1, EGFR, and SRC was associated with increased sensitivity to multiple chemotherapeutic drugs. The nCT predictive score obtained by therapeutic relevant genes could be a potential prognostic indicator, and the combination with TMB could further refine prognostic prediction for patients. After a series of analysis in multi-omics association database, EGFR and HSP90AA1 with significant differences in multiple aspects were identified as the key predictive genes related to prognosis and the sensitivity of nCT. Discussion: This work revealed that effective combined application and analysis in multi-omics data are critical to search for predictive biomarkers. The key genes EGFR and HSP90AA1 could serve as an effective biomarker to predict prognose and neoadjuvant chemosensitivity.

Left ventricular global longitudinal strain predicts mortality and heart failure admissions in African American patients.

BACKGROUND: Several studies have demonstrated the importance of left ventricular (LV) global longitudinal strain (GLS) as a reliable prognostic indicator in patients with heart failure (HF). These studies have included few African American (AA) patients, despite the growing prevalence and severity of HF in this patient population. HYPOTHESIS: LV GLS predicts long-term HF admission and all-cause mortality in AA patients with chronic HF on optimal guideline-directed medical therapy (GDMT). METHODS: We enrolled 207 AA adults, age 56 ± 14.5 years, with New York Heart Association (NYHA) class I through III HF on optimal GDMT from the University of Illinois HF clinic between November 2001 and February 2014. LV GLS was assessed by velocity vector imaging using 2-, 3-, and 4-chamber views. Patients were followed for HF admissions and death for 3 ± 3.0 years. LV GLS value of -7.95 was used as the optimal cutoff point that maximizes sensitivity and specificity RESULTS: LV GLS < -7.95% was significantly associated with higher all-cause mortality and HF admissions in Kaplan-Meier survival curves (log-rank P < 0.001). After incorporation in multivariate Cox proportional hazard models, GLS < -7.95% was found to be an independent predictor of all-cause mortality (hazard ratio [HR] = 4.04; 95% confidence interval [CI]: 1.07-15.32; P = 0.04] and HF admissions (HR = 3.86; 95% CI: 1.38-10.77; P = 0.010). CONCLUSIONS: In AA patients with chronic stable HF on GDMT, more impaired LV GLS (< -7.95%) is a strong and independent predictor of long-term all-cause mortality and HF admissions.

Gene therapy for bone regeneration.

Efficacious bone regeneration could revolutionize the clinical management of many bone and musculoskeletal disorders. Bone has the unique ability to regenerate and continuously remodel itself throughout life. However, clinical situations arise when bone is unable to heal itself, as with segmental bone loss, fracture non-union, and failed spinal fusion. This leads to significant morbidity and mortality. Current attempts at improved bone healing have been met with limited success, fueling the development of improved techniques. Gene therapy in many ways represents an ideal approach for augmenting bone regeneration. Gene therapy allows specific gene products to be delivered to a precise anatomic location. In addition, the level of transgene expression as well as the duration of expression can be regulated with current techniques. For bone regeneration, the gene of interest should be delivered to the fracture site, expressed at appropriate levels, and then deactivated once the fracture has healed. Delivery of biological factors, mostly bone morphogenetic proteins (BMPs), has yielded promising results both in animal and clinical studies. There has also been tremendous work on discovering new growth factors and exploring previously defined ones. Finally, significant advances are being made in the delivery systems of the genes, ranging from viral and non-viral vectors to tissue engineering scaffolds. Despite some public hesitation to gene therapy, its use has great potential to expand our ability to treat a variety of human bone and musculoskeletal disorders. It is conceivable that in the near future gene therapy can be utilized to induce bone formation in virtually any region of the body in a minimally invasive manner. As bone biology and gene therapy research progresses, the goal of successful human gene transfer for augmentation of bone regeneration draws nearer.