DHCR24 predicts poor clinicopathological features of patients with bladder cancer: A STROBE-compliant study

DHCR24 in Tumor Diagnosis and Treatment: A Comprehensive Review

As an important nutrient in the human body, cholesterol can not only provide structural components for the body's cells, but also can be transformed into a variety of active substances to regulate cell signaling pathways. As an important cholesterol synthase, DHCR24 participates in important regulatory processes in the body. The application of DHCR24 in tumor clinical diagnosis and treatment also attracts much attention. This article reviews the structure and regulatory characteristics of DHCR24, and the research of DHCR24 on tumor progression. We summarize the possible mechanisms of DHCR24 promoting tumor progression through reactive oxygen species (ROS), p53, Ras and PI3K-AKT pathways. Through our review, we hope to provide more research ideas and reference value for the application of DHCR24 in tumor prevention and treatment.

3β-hydroxysteroid-Δ24 reductase dampens anti-viral innate immune responses by targeting K27 ubiquitination of MAVS and STING

IMPORTANCE

The precise regulation of the innate immune response is essential for the maintenance of homeostasis. MAVS and STING play key roles in immune signaling pathways activated by RNA and DNA viruses, respectively. Here, we showed that DHCR24 impaired the antiviral response by targeting MAVS and STING. Notably, DHCR24 interacts with MAVS and STING and inhibits TRIM21-triggered K27-linked ubiquitination of MAVS and AMFR-triggered K27-linked ubiquitination of STING, restraining the activation of MAVS and STING, respectively. Together, this study elucidates how one cholesterol key enzyme orchestrates two antiviral signal transduction pathways.

Clear cell renal cell carcinoma molecular variations in non-Hispanic White and Hispanic patients

BACKGROUND

The United States is becoming increasingly diverse, but few molecular studies have assessed the progression of clear cell renal cell carcinoma (ccRCC) in diverse patient populations. This study examined ccRCC molecular variations in non-Hispanic White (NHW) and Hispanic patients and their effect on the association of gene expression with high-grade (Grade 3 or 4) ccRCC and overall mortality.

METHODS

A total of 156 patients were included in VHL sequencing and/or TempO-Seq analysis. DESeq2 was used to identify the genes associated with high-grade ccRCC. Logistic regression analysis was performed to assess whether race and ethnicity was associated with high/moderate impact VHL somatic mutations and the ccA/ccB subtype. Cox regression analysis was performed to assess association of molecular subtype and gene expression with overall mortality.

RESULTS

NHWs had moderate or high impact mutations in the VHL gene at a higher frequency than Hispanics (40.2% vs. 27.4%), while Hispanics had a higher frequency of the ccA subtype than NHWs (61.9% vs. 45.8%). ccA was more common in patients with BMI≥35 (65.2%) than in those with BMI < 25 (45.0%). There were 11 differentially expressed genes between high- and low-grade tumors. The Haptoglobin (HP) gene was most significantly overexpressed in high- compared to low-grade ccRCC in all samples (p-adj = 1.7 × 10^-12 ). When stratified by subtype, the 11 genes were significantly differentially expressed in the ccB subtype, but none of them were significant after adjusting for multiple testing in ccA. Finally, patients with the ccB subtype had a significantly increased risk of overall mortality (HR 4.87; p = 0.01) compared to patients with ccA, and patients with high HP expression and ccB, had a significantly increased risk of mortality compared to those with low HP expression and ccA (HR 6.45, p = 0.04).

CONCLUSION

This study reports ccRCC molecular variations in Hispanic patients who were previously underrepresented.

A Prognostic Model of Seven Immune Genes to Predict Overall Survival in Childhood Acute Myeloid Leukemia

Background. Acute myeloid leukemia (AML) is one of the most common hematological malignancies and accounts for about 20% of childhood leukemias. Currently, immunotherapy is one of the recommended treatment schemes for recurrent AML patients to improve their survival rates. Nonetheless, low remission and high mortality rates are observed in recurrent AML and challenge the prognosis of AML patients. To address this problem, we aimed to establish and verify a reliable prognostic risk model using immune-related genes to improve the prognostic evaluation and recommendation for personalized treatment of AML. Methods. Transcriptome data and clinical data were acquired from the TARGET database while immune genes were sourced from InnateDB and ImmPort Shared databases. The mRNA expression profile matrix of immune genes from 62 normal samples and 1408 AML cases was extracted from the transcriptome data and subjected to differential expression (DE) analysis. The entire cohort of DE immune genes was randomly divided into the test group and training group. The prognostic model associated with immune genes was constructed using the training group. The test group and entire cohort were employed for model validation. Lastly, we analyzed the potential clinical application of the model and its association with immune cell infiltration. Results. In total, 751 DE immune genes were differentially regulated, including 552 upregulated and 199 downregulated. Based on these DE genes, we developed and validated a prognostic risk model composed of seven immune genes, GDF1, TPM2, IL1R1, PSMD4, IL5RA, DHCR24, and IL12RB2. This model is able to predict the 5-year survival rate more accurately compared with age, gender, and risk stratification. Further analysis showed that CD8+ T-cell contents and neutrophil infiltration decreased but macrophage infiltration increased as the risk score increased. Conclusions. A seven-immune gene model of AML was developed and validated. We propose this model as an independent prognostic variable able to estimate the 5-year survival rate. In addition, the model can also reflect the immune microenvironment of AML patients.

Combination treatment of docetaxel with caffeic acid phenethyl ester suppresses the survival and the proliferation of docetaxel-resistant prostate cancer cells via induction of apoptosis and metabolism interference

BACKGROUND

Docetaxel has been approved by USFDA as a first-line treatment for castration-resistant prostate cancer (CRPC) patients. Patients receiving androgen deprivation therapy along with docetaxel result in superior survival, lower serum prostate specific antigen (PSA) level, and better quality of life. However, a significant proportion of these patients ultimately develop resistance to docetaxel within months. Caffeic acid phenethyl ester (CAPE), one of the main bioactive components extracted from the propolis, has been reported to be effective for repressing the tumor growth, the migration and invasion of prostate cancer (PCa) cells, as well as the downstream signaling and stability of androgen receptor (AR). We hence determined if combination treatment of docetaxel with CAPE can suppress the proliferation and the survival of docetaxel-resistant PCa cells.

METHODS

We established docetaxel-resistant PC/DX25 and DU/DX50 CRPC cell lines from PC-3 and DU-145 human PCa cells, respectively. Proliferation assay, MTT assay, flow cytometry with Annexin V staining, Comet Assay, and nude mice xenograft model were applied to determine the effects of combination treatment on cell proliferation and survival of the docetaxel-resistant PCa cells. Micro-Western Array (MWA) and qRT-PCR were used to investigate the molecular mechanism lying underneath.

RESULTS

Combination treatment effectively suppressed the proliferation, survival and tumor growth of docetaxel-resistant PCa cells both in vitro and in nude mice. Comet assay and flow cytometry indicated that combination treatment induced apoptosis in docetaxel-resistant PCa cells. MWA and Western blotting assay revealed that combination treatment suppressed protein expression of Bcl-2, AKT2, c-Myc, apoptosis and caspase activation inhibitor (AVEN), pyruvate kinase M2 (PKM2) but increased protein expression of Bax, caspase 3, cytochrome c, glucose-6-phosphate dehydrogenase (G6PD) and acylglycerol kinase (AGK). Overexpression of Bcl-2 in the docetaxel-resistant PCa cells enhanced cell proliferation of docetaxel-resistant PCa cells under combination treatment. Analysis with qRT-PCR suggested that combination treatment decreased cholesterol biosynthesis genes DHCR24 (24-dehydrocholesterol reductase) and LSS (lanosterol synthase) but increased genes involved in glycolysis and TCA cycle.

CONCLUSIONS

Combination treatment of docetaxel with CAPE effectively suppressed the proliferation and survival of docetaxel-resistant PCa cells via inhibition of Bcl-2 and c-Myc as well as induction of metabolism interference. Combination treatment can be beneficial for patients with docetaxel-resistant PCa.

Enzymes in the Cholesterol Synthesis Pathway: Interactomics in the Cancer Context

A global protein interactome ensures the maintenance of regulatory, signaling and structural processes in cells, but at the same time, aberrations in the repertoire of protein-protein interactions usually cause a disease onset. Many metabolic enzymes catalyze multistage transformation of cholesterol precursors in the cholesterol biosynthesis pathway. Cancer-associated deregulation of these enzymes through various molecular mechanisms results in pathological cholesterol accumulation (its precursors) which can be disease risk factors. This work is aimed at systematization and bioinformatic analysis of the available interactomics data on seventeen enzymes in the cholesterol pathway, encoded by HMGCR, MVK, PMVK, MVD, FDPS, FDFT1, SQLE, LSS, DHCR24, CYP51A1, TM7SF2, MSMO1, NSDHL, HSD17B7, EBP, SC5D, DHCR7 genes. The spectrum of 165 unique and 21 common protein partners that physically interact with target enzymes was selected from several interatomic resources. Among them there were 47 modifying proteins from different protein kinases/phosphatases and ubiquitin-protein ligases/deubiquitinases families. A literature search, enrichment and gene co-expression analysis showed that about a quarter of the identified protein partners was associated with cancer hallmarks and over-represented in cancer pathways. Our results allow to update the current fundamental view on protein-protein interactions and regulatory aspects of the cholesterol synthesis enzymes and annotate of their sub-interactomes in term of possible involvement in cancers that will contribute to prioritization of protein targets for future drug development.

Targeting SREBP-2-Regulated Mevalonate Metabolism for Cancer Therapy

Recently, targeting metabolic reprogramming has emerged as a potential therapeutic approach for fighting cancer. Sterol regulatory element binding protein-2 (SREBP-2), a basic helix-loop-helix leucine zipper transcription factor, mainly regulates genes involved in cholesterol biosynthesis and homeostasis. SREBP-2 binds to the sterol regulatory elements (SREs) in the promoters of its target genes and activates the transcription of mevalonate pathway genes, such as HMG-CoA reductase (HMGCR), mevalonate kinase and other key enzymes. In this review, we first summarized the structure of SREBP-2 and its activation and regulation by multiple signaling pathways. We then found that SREBP-2 and its regulated enzymes, including HMGCR, FPPS, SQS, and DHCR4 from the mevalonate pathway, participate in the progression of various cancers, including prostate, breast, lung, and hepatocellular cancer, as potential targets. Importantly, preclinical and clinical research demonstrated that fatostatin, statins, and N-BPs targeting SREBP-2, HMGCR, and FPPS, respectively, alone or in combination with other drugs, have been used for the treatment of different cancers. This review summarizes new insights into the critical role of the SREBP-2-regulated mevalonate pathway for cancer and its potential for targeted cancer therapy.

3β-Hydroxysteroid-Δ24 Reductase (DHCR24) Protects Pancreatic β Cells from Endoplasmic Reticulum Stress-Induced Apoptosis by Scavenging Excessive Intracellular Reactive Oxygen Species

There is accumulating evidence showing that apoptosis induced by endoplasmic reticulum (ER) stress plays a key role in pancreatic β cell dysfunction and insulin resistance. 3β-Hydroxysteroid-Δ24 Reductase (DHCR24) is a multifunctional enzyme located in the endoplasmic reticulum (ER), which has been previously shown to protect neuronal cells from ER stress-induced apoptosis. However, the role of DHCR24 in type 2 diabetes is only incompletely understood so far. In the present study, we induced ER stress by tunicamycin (TM) treatment and showed that infection of MIN6 cells with Ad-DHCR24-myc rendered these cells resistant to caspase-3-mediated apoptosis induced by TM, while cells transfected with siRNAs targeting DHCR24 were more sensitive to TM. Western blot analysis showed that TM treatment induced upregulation of Bip protein levels in both cells infected with Ad-LacZ (the control group) and Ad-DHCR24-myc, indicating substantial ER stress. Cells infected with Ad-LacZ exhibited a rapid and strong activation of ATF6 and p38, peaking at 3 h after TM exposure. Conversely, cells infected with Ad-DHCR24-myc showed a higher and more sustained activation of ATF6 and Bip than control cells. DHCR24 overexpression also inhibited the generation of intracellular reactive oxygen species (ROS) induced by ER stress and protected cells from apoptosis caused by treatment with both cholesterol and hydrogen peroxide. In summary, these data demonstrate, for the first time, that DHCR24 protects pancreatic β cells from apoptosis induced by ER stress.

Cholesterol and 27-hydroxycholesterol promote thyroid carcinoma aggressiveness

Cholesterol mediates its proliferative and metastatic effects via the metabolite 27-hydroxycholesterol (27-HC), at least in breast and endometrial cancer. We determined the serum lipoprotein profile, intratumoral cholesterol and 27-HC levels in a cohort of patients with well-differentiated papillary thyroid carcinoma (PTC; low/intermediate and high risk), advanced thyroid cancers (poorly differentiated, PDTC and anaplastic thyroid carcinoma, ATC) and benign thyroid tumors, as well as the expression of genes involved in cholesterol metabolism. We investigated the gene expression profile, cellular proliferation, and migration in Nthy-ori 3.1 and CAL-62 cell lines loaded with human low-density lipoprotein (LDL). Patients with more aggressive tumors (high-risk PTC and PDTC/ATC) showed a decrease in blood LDL cholesterol and apolipoprotein B. These changes were associated with an increase in the expression of the thyroid’s LDL receptor, whereas 3-hydroxy-3-methylglutaryl-CoA reductase and 25-hydroxycholesterol 7-alpha-hydroxylase were downregulated, with an intratumoral increase of the 27-HC metabolite. Furthermore, LDL promoted proliferation in both the Nthy-ori 3.1 and CAL-62 thyroid cellular models, but only in ATC cells was its cellular migration increased significantly. We conclude that cholesterol and intratumoral accumulation of 27-HC promote the aggressive behavior process of PTC. Targeting cholesterol metabolism could be a new therapeutic strategy in thyroid tumors with poor prognosis.

Predicting prognosis of endometrioid endometrial adenocarcinoma on the basis of gene expression and clinical features using Random Forest

Traditional clinical features are not sufficient to accurately judge the prognosis of endometrioid endometrial adenocarcinoma (EEA). Molecular biological characteristics and traditional clinical features are particularly important in the prognosis of EEA. The aim of the present study was to establish a predictive model that considers genes and clinical features for the prognosis of EEA. The clinical and RNA sequencing expression data of EEA were derived from samples from The Cancer Genome Atlas (TCGA) and Peking University People's Hospital (PKUPH; Beijing, China). Samples from TCGA were used as the training set, and samples from the PKUPH were used as the testing set. Variable selection using Random Forests (VSURF) was used to select the genes and clinical features on the basis of TCGA samples. The RF classification method was used to establish the prediction model. Kaplan-Meier curves were tested with the log-rank test. The results from this study demonstrated that on the basis of TCGA samples, 11 genes and the grade were selected as the input features. In the training set, the out-of-bag (OOB) error of RF model-1, which was established using the '11 genes', was 0.15; the OOB error of RF model-2, which was established using the 'grade', was 0.39; and the OOB error of RF model-3, established using the '11 genes and grade', was 0.15. In the testing set, the classification accuracy of RF model-1, model-2 and model-3 was 71.43, 66.67 and 80.95%, respectively. In conclusion, to the best of our knowledge, the VSURF was used to select features relevant to EEA prognosis, and an EEA predictive model combining genes and traditional features was established for the first time in the present study. The prediction accuracy of the RF model on the basis of the 11 genes and grade was markedly higher than that of the RF models established by either the 11 genes or grade alone.