Dynamic Trajectory of a Patient-Reported Outcome and Its Associated Factors for Patients with Chronic Heart Failure: A Growth Mixture Model Approach.

Purpose: This study aimed to identify subgroups of chronic heart failure (CHF) patients with distinct trajectories of quality of life (QOL) and to identify baseline characteristics associated with the trajectories. Patients and methods: Two-year, prospective, cohort study including 315 patients with CHF was conducted from July 2017. Information on QOL assessed by CHF-patient-reported outcomes measure (CHF-PROM) was collected at baseline, 6, 12, 18, and 24 months. Demographic and clinical variables were recorded at baseline. Growth mixture model was used to identify distinct trajectories of CHF-PROM and its physical, psychological, social, and therapeutic domains. Single factor analysis was employed to assess the factors associated with development of CHF-PROM over time. Results: Two classes of overall score of CHF-PROM were identified: poorer (14.0%) and better (86.0%). Poorer class tended to be aged, have low diastolic blood pressure, have concomitant atrial fibrillation, diabetes, chronic obstructive pulmonary disease, cancers, and central nervous system diseases, and used nitrates. Three classes of physical scores were identified: unstable-poorer (5.2%), stable-poorer (29.4%) and better (65.4%). Age, NYHA grade, chronic obstructive pulmonary disease, combined with cancers and central nervous system diseases were related to the grouping. Poorer (8.6%) and better (91.4%) classes of psychological scores were identified. Poorer class tended to be female and had concomitant atrial fibrillation. Degenerate class (34.6%) and meliorate class (65.4%) of therapeutic scores were identified. Degenerate class tended to have concomitant chronic obstructive pulmonary disease and use less angiotensin converting enzyme inhibitors. Conclusion: We identified different classes with distinct trajectories of QOL that may help proper evaluate QOL and further improve its status for patients CHF.

HOXA5: A crucial transcriptional factor in cancer and a potential therapeutic target.

HOX genes occupy a significant role in embryogenesis, hematopoiesis, and oncogenesis. HOXA5, a member of the A cluster of HOX genes, is essential for establishing the skeleton and normal organogenesis. As previously reported, aberrant HOXA5 expression contributes to anomalies and dysfunction of various organs, as well as affecting proliferation, differentiation, invasion, apoptosis, and other biological processes of tumor cells. Different cancers showed both downregulated and upregulated HOXA5 expression. The most common strategy for controlling HOXA5 downregulated expression may be CpG island hypermethylation. Additionally, current research demonstrated the regulatory network of HOXA5 and its connection with cancer stem cell progression and the immune microenvironment. Epigenetic modulators and upstream regulators, such as DNMTi and retinoic acid, may be beneficial for anti-tumor effects targeting HOXA5. Here, we summarize current knowledge about the HOXA5 gene, its role in various cancers, and its potential therapeutic value.

HOXA5 Is Recognized as a Prognostic-Related Biomarker and Promotes Glioma Progression Through Affecting Cell Cycle.

Glioma is malignant tumor derives from glial cells in the central nervous system. High-grade glioma shows aggressive growth pattern, and conventional treatments, such as surgical removal and chemo-radiotherapy, archive limitation in the interference of this process. In this work, HOXA5, from the HOX family, was identified as a glioma cell proliferation-associated factor by investigating its feature in the TCGA and CGGA data set. High HOXA5 expression samples contain unfavorable clinical features of glioma, including IDH wild type, un-methylated MGMT status, non-codeletion 1p19q status, malignant molecular subtype. Survival analysis indicates that high HOXA5 expression samples are associated with worse clinical outcome. The CNVs and SNPs profile difference further confirmed the enrichment of glioma aggressive related biomarkers. In the meantime, the activation of DNA damage repair-related pathways and TP53-related pathways is also related to HOXA5 expression. In cell lines, U87MG and U251, by interfering HOXA5 expression significantly inhibit glioma progression and apoptosis, and cell cycle is arrested at the G2/M phase. Collectively, increased HOXA5 expression can promote glioma progression via affecting glioma cell proliferation.

A comprehensive prognostic signature for glioblastoma patients based on transcriptomics and single cell sequencing.

PURPOSE: Glioblastoma (GBM) is the most common and deadly brain tumor. We aimed to reveal potential prognostic GBM marker genes, elaborate their functions, and build an effective a prognostic model for GBM patients. METHODS: Through data mining of The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), we screened for significantly differentially expressed genes (DEGs) to calculate risk scores for individual patients. Published data of somatic mutation and copy number variation profiles were analyzed for distinct genomic alterations associated with risk scores. In addition, single-cell sequencing was used to explore the biological functions of the identified prognostic marker genes. By combining risk scores and other clinical features, we built a comprehensive prognostic GBM model. RESULTS: Seven DEGs (CLEC5A, HOXC6, HOXA5, CCL2, GPRASP1, BSCL2 and PTX3) were identified as being prognostic for GBM. Expression of these genes was confirmed in different GBM cell lines using real-time PCR. Risk scores calculated from the seven DEGs revealed prognostic value irrespective of other clinical factors, including IDH mutation status, and were negatively correlated with TP53 expression. The prognostic genes were found to be associated with tumor proliferation and progression based on pseudo-time analysis in neoplastic cells. A final prognostic model was developed and validated with a good performance, especially in geriatric GBM patients. CONCLUSIONS: Using genetic profiles, age, IDH mutation status, and chemotherapy and radiotherapy, we constructed a comprehensive prognostic model for GBM patients. The model has a good performance, especially in geriatric GBM patients.