Anthocyanins from Lycium ruthenicum Murray attenuates high-fat diet-induced hypercholesterolemia in ApoE-/- mice are related to the modulation of gut microbiota and the ratio of conjugated to unconjugated bile acids in fecal bile acid profile.

Previous findings showed that anthocyanins from Lycium ruthenicum Murray (ACN) reduced HFD-induced hypercholesterolemia by regulating gut microbiota, but the mechanism has not been fully understood. The objective of this research was to know whether the cholesterol-lowering impact of ACN in HFD-induced ApoE-/- mice is related to the gut microbiota-bile acid (BA) metabolism. Twenty-four male ApoE-/- mice were divided into three groups: the Control group, the HFD group, and the HFD + ACN group. Here, we showed that ACN intervention reduced HFD-induced body weight serum concentrations of TC and LDL-C and ameliorated lipid accumulation in the liver and adipose tissues. Besides, ACN altered gut microbiota composition in HFD-fed ApoE-/- mice. Moreover, UHPLC-MS/MS analysis revealed that ACN intervention significantly increased the ratio of conjugated to unconjugated BAs in feces induced by HFD, attributed to the increase in conjugated BAs and decrease in unconjugated BAs. Finally, the correlation analysis indicated that the above changes in fecal BA profile were linked with an increase in Bifidobacterium, Allobaculum and a decrease in Ileibacterium, Helicobacter, Rikenellaceae_RC9_gut_group, Blautia, Odoribacter, and Colidextribacter. In summary, ACN could alleviate HFD-induced hypercholesterolemia in ApoE-/- mice, which was associated with the improvement of gut microbiota and modulation of fecal BA profile.

A cross-disease, pleiotropy-driven approach for therapeutic target prioritization and evaluation.

Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge "W-H-W" (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proof-of-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.

Associations of residential greenness with bone mineral density and osteoporosis: the modifying effect of genetic susceptibility.

OBJECTIVES: To investigate the associations of residential greenness with bone mineral density and incident osteoporosis, and further evaluate the potential modifying effect of genetic susceptibility. METHODS: We used the Normalised Difference Vegetation Index (NDVI) at various buffer distances, including 300 m (NDVI300m), 500 m (NDVI500m), 1000 m (NDVI1000m) and 1500 m (NDVI1500m), to serve as indicators of greenness. We fitted linear regression, logistic regression and Cox proportional hazard models to assess the associations of residential greenness with estimated bone mineral density (eBMD), prevalent osteoporosis and incident osteoporosis, respectively. With the Polygenic Risk Score (PRS) for osteoporosis, we further assessed the joint effects of genetic risk and greenness on the risk of osteoporosis. We conducted causal mediation analyses to explore potential mediators. RESULTS: Each IQR increase in NDVI300m was associated with 0.0007 (95% CI 0.0002 to 0.0013) increase in eBMD, 6% lower risk of prevalent osteoporosis (OR 0.94; 95% CI 0.92 to 0.97) and 5% lower risk of incident osteoporosis (HR 0.95; 95% CI 0.93 to 0.98). The joint effects of greenness and PRS on the risk of osteoporosis displayed a clear dose-response pattern. Compared with individuals exposed to low NDVI levels and high genetic risk, those exposed to high NDVI levels and low genetic risk had a 56% (95% CI 51% to 61%) lower risk of osteoporosis. The primary mediators in the association between greenness and incident osteoporosis were identified as PM2.5 and NO2. CONCLUSIONS: Residential greenness was associated with higher bone mineral density and decreased risk of incident osteoporosis.

Management of KRAS-mutated non-small cell lung cancer.

Kirsten rat sarcoma virus (KRAS) is the most frequently mutated oncogene in human cancers, particularly in non-small cell lung cancer (NSCLC), where mutations are present in 32% of lung adenocarcinoma and 4% of squamous cell lung cancer. The most common KRAS variant is KRAS G12C, which accounts for nearly 40% of all KRAS mutations. Although it is the most common oncogenic driver in NSCLC, KRAS was considered a "nondruggable target" until recently, owing to the lack of any progress in developing targeted therapies for this oncogene. With the recent development and approval of selective KRAS G12C inhibitors such as sotorasib and adagrasib for the treatment of advanced or metastatic NSCLC in the second-line setting and beyond, the standard of care for managing these tumors has undergone a significant change. Mechanisms of resistance to KRAS G12C inhibitors are highly heterogeneous, including both on-target and off-target resistance as well as morphologic switching, thus limiting the activity of these drugs when used as monotherapy. New-generation inhibitors and different combination strategies are being developed in early-phase trials to overcome or delay the onset of resistance as well as to target non-G12C mutations. Owing to the biological heterogeneity of KRAS-mutant NSCLC, treatment will likely need to be individualized based on factors such as co-occurring mutations.

Priority index for critical Covid-19 identifies clinically actionable targets and drugs.

While genome-wide studies have identified genomic loci in hosts associated with life-threatening Covid-19 (critical Covid-19), the challenge of resolving these loci hinders further identification of clinically actionable targets and drugs. Building upon our previous success, we here present a priority index solution designed to address this challenge, generating the target and drug resource that consists of two indexes: the target index and the drug index. The primary purpose of the target index is to identify clinically actionable targets by prioritising genes associated with Covid-19. We illustrate the validity of the target index by demonstrating its ability to identify pre-existing Covid-19 phase-III drug targets, with the majority of these targets being found at the leading prioritisation (leading targets). These leading targets have their evolutionary origins in Amniota ('four-leg vertebrates') and are predominantly involved in cytokine-cytokine receptor interactions and JAK-STAT signaling. The drug index highlights opportunities for repurposing clinically approved JAK-STAT inhibitors, either individually or in combination. This proposed strategic focus on the JAK-STAT pathway is supported by the active pursuit of therapeutic agents targeting this pathway in ongoing phase-II/III clinical trials for Covid-19.

A novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors.

BACKGROUND: The gangue content in coal seriously affects the calorific value produced by its combustion. In practical applications, gangue in coal needs to be completely separated. The pseudo-dual-energy X-ray method does not have high sorting accuracy. OBJECTIVE: This study aims to propose a novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors to solve the problem of coal and gangue sorting by X-ray. METHODS: This complete algorithm includes five steps: (1) Preferred energy bins, (2) transmittance sorting, (3) one-dimensional R-value sorting, (4) two-dimensional R-value sorting, and (5) three-dimensional R-value sorting. The output range of each step is determined by prior information from 65 groups of coal and gangue. An additional 110 groups of coal and gangue are employed experimentally to validate the algorithm's accuracy. RESULTS: Compared with the 60% sorting accuracy of the Pseudo-dual-energy method, the new algorithm reached a sorting accuracy of 99%. CONCLUSIONS: Study results demonstrate the superiority of this novel algorithm and its feasibility in practical applications. This novel algorithm can guide other two-substance X-ray sorting applications based on photon counting detectors.

Mask and Release Strategy-Enabled Diversity-Oriented Synthesis for DNA-Encoded Library.

An ideal DNA-encoded library (DEL) selection requires the library to consist of diverse core skeletons and cover chemical space as much as possible. However, the lack of efficient on-DNA synthetic approaches toward core skeletons has greatly restricted the diversity of DEL. To mitigate this issue, this work disclosed a "Mask & Release" strategy to streamline the challenging on-DNA core skeleton synthesis. N-phenoxyacetamide is used as a masked phenol and versatile directing group to mediate diversified DNA-compatible C-H functionalization, introducing the 1st-dimensional diversity at a defined site, and simultaneously releasing the phenol functionality, which can facilitate the introduction of the 2nd diversity. This work not only provides a set of efficient syntheses toward DNA-conjugated drug-like core skeletons such as ortho-alkenyl/sulfiliminyl/cyclopropyl phenol, benzofuran, dihydrobenzofuran but also provides a paradigm for on-DNA core skeleton synthetic method development.

Escitalopram-induced QTc prolongation and its relationship with KCNQ1, KCNE1, and KCNH2 gene polymorphisms.

BACKGROUND: Escitalopram can cause prolongation of the QT interval on the electrocardiogram (ECG). However, only some patients get pathological QTc prolongation in clinic. We investigated the influence of KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors on escitalopram-induced QTc prolongation. METHODS: A total of 713 patients prescribed escitalopram were identified and had at least one ECG recording in this retrospective study. 472 patients with two or more ECG data were divided into QTc prolongation (n = 119) and non-prolongation (n = 353) groups depending on the threshold change in QTc of 30 ms above baseline value (∆QTc ≥ 30 ms). 45 patients in the QTc prolongation group and 90 patients in the QTc non-prolongation group were genotyped for 43 single nucleotide polymorphisms (SNPs) of KCNQ1, KCNE1, and KCNH2 genes. RESULTS: Patients with QTc prolongation (∆QTc ≥ 30 ms) got higher escitalopram dose (10.3 mg) than patients without QTc prolongation (9.4 mg), although no significant relationship was found between QTc interval and escitalopram dose in the linear mixed model. Patients who were older/coronary disease/hypertension or carried with KCNE1 rs1805127 C allele, KCNE1 rs4817668 C allele, KCNH2 rs3807372 AG/GG genotype were significantly at risk for QTc prolongation (∆QTc ≥ 30 ms). Concomitant antipsychotic treatment was associated with a longer QTc interval. LIMITATIONS: A relatively small sample size and lack of the blood concentration of escitalopram restricted the accurate relationship between escitalopram dose and QTc interval. CONCLUSION: Our study revealed that KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors provide a complementary effect in escitalopram-induced QTc prolongation.

Urolithin C alleviates pancreatic ß-cell dysfunction in type 1 diabetes by activating Nrf2 signaling.

AIMS: Type 1 diabetes (T1D) is an autoimmune disorder that destroys insulin-generating pancreatic ß-cells. Preserving pancreatic ß-cell function is important for treating T1D. Our study aims to explore the mechanism underlying urolithin C (UC)-mediated regulation of ß-cell function. METHODS: Non-obese diabetic (NOD) mice were administrated with UC to evaluate UC-mediated protection of T1D. The inflammation of the pancreas islets was examined by hematoxylin and eosin staining. Glucose-stimulated insulin secretion (GSIS) assay and oral glucose tolerance test were applied to evaluate the progression of T1D. MIN6 cells were treated with TNF-α, IL-1ß and IFN-γ in the presence of UC. Cell viability was analyzed by CCK-8. Cell apoptosis, proliferation and DNA fragmentation were examined by Annexin V-FITC and PI staining, EdU incorporation and comet assays. Keap1, Nrf2, HO-1 and NQO1 were examined by western blot. Immunofluorescence staining was applied to detect Nrf2 and insulin. RESULTS: UC administration significantly reduced diabetes incidence, attenuated insulitis, elevated insulin levels and GSIS and reduced blood glucose and AUC in NOD mice. Cytokine treatment suppressed MIN6 cell viability and proliferation but enhanced apoptosis and DNA damage, and these detrimental effects were relieved by UC treatment. Furthermore, UC administration inhibited Keap1 expression and promoted the expression of Nrf2, HO-1 and NQO1 in NOD mice. Nrf2 signaling has been reported to be implicated in preventing the onset of diabetes, and HO-1 and NQO1 are phase II antioxidant enzymes that are regulated by Nrf2 signaling. Cytokine treatment upregulated Keap1 and downregulated Nrf2, HO-1 and NQO1 in MIN6 cells, but it was reversed by UC. The nuclear translocation of Nrf2 was prevented by cytokine treatment, but UC promoted its nuclear translocation. UC-mediated upregulation of Nrf2, HO-1 and NQO1, decreased cell apoptosis and increased proliferation and insulin secretion were abolished by silencing of Nrf2. CONCLUSION: UC improves pancreatic ß-cell function by activating Nrf2 signaling, thereby alleviating T1D progression.

A Nexus between Genetic and Non-Genetic Mechanisms Guides KRAS Inhibitor Resistance in Lung Cancer.

Several studies in the last few years have determined that, in contrast to the prevailing dogma that drug resistance is simply due to Darwinian evolution-the selection of mutant clones in response to drug treatment-non-genetic changes can also lead to drug resistance whereby tolerant, reversible phenotypes are eventually relinquished by resistant, irreversible phenotypes. Here, using KRAS as a paradigm, we illustrate how this nexus between genetic and non-genetic mechanisms enables cancer cells to evade the harmful effects of drug treatment. We discuss how the conformational dynamics of the KRAS molecule, that includes intrinsically disordered regions, is influenced by the binding of the targeted therapies contributing to conformational noise and how this noise impacts the interaction of KRAS with partner proteins to rewire the protein interaction network. Thus, in response to drug treatment, reversible drug-tolerant phenotypes emerge via non-genetic mechanisms that eventually enable the emergence of irreversible resistant clones via genetic mutations. Furthermore, we also discuss the recent data demonstrating how combination therapy can help alleviate KRAS drug resistance in lung cancer, and how new treatment strategies based on evolutionary principles may help minimize or even preclude the emergence of drug resistance.

Unraveling the potential mechanisms of the anti-osteoporotic effects of the Achyranthes bidentata-Dipsacus asper herb pair: a network pharmacology and experimental study.

Background: Osteoporosis is a prevalent bone metabolism disease characterized by a reduction in bone density, leading to several complications that significantly affect patients' quality of life. The Achyranthes bidentata-Dipsacus asper (AB-DA) herb pair is commonly used in Traditional Chinese Medicine (TCM) to treat osteoporosis. This study aimed to investigate the therapeutic compounds and potential mechanisms of AB-DA using network pharmacology, molecular docking, molecular dynamics simulation, and experimental verification. Methods: Identified compounds of AB-DA were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicine Information Database (TCM-ID), TCM@Taiwan Database, BATMAN-TCM, and relevant literature. The main bioactive ingredients were screened based on the criteria of "OB (oral bioavailability) ≥ 30, DL (drug-likeness) ≥ 0.18." Potential targets were predicted using the PharmMapper and SwissTargetPrediction websites, while disease (osteoporosis)-related targets were obtained from the GeneCards, DisGeNET, and OMIM databases. The PPI network and KEGG/GO enrichment analysis were utilized for core targets and pathway screening in the STRING and Metascape databases, respectively. A drug-compound-target-pathway-disease network was constructed using Cytoscape software to display core regulatory mechanisms. Molecular docking and dynamics simulation techniques explored the binding reliability and stability between core compounds and targets. In vitro and in vivo validation experiments were utilized to explore the anti-osteoporosis efficiency and mechanism of sitogluside. Results: A total of 31 compounds with 83 potential targets for AB-DA against osteoporosis were obtained. The PPI analysis revealed several hub targets, including AKT1, CASP3, EGFR, IGF1, MAPK1, MAPK8, and MAPK14. GO/KEGG analysis indicated that the MAPK cascade (ERK/JNK/p38) is the main pathway involved in treating osteoporosis. The D-C-T-P-T network demonstrated therapeutic compounds that mainly consisted of iridoids, steroids, and flavonoids, such as sitogluside, loganic acid, and ß-ecdysterone. Molecular docking and dynamics simulation analyses confirmed strong binding affinity and stability between core compounds and targets. Additionally, the validation experiments showed preliminary evidence of antiosteoporosis effects. Conclusion: This study identified iridoids, steroids, and flavonoids as the main therapeutic compounds of AB-DA in treating osteoporosis. The underlying mechanisms may involve targeting core MAPK cascade (ERK/JNK/p38) targets, such as MAPK1, MAPK8, and MAPK14. In vivo experiments preliminarily validated the anti-osteoporosis effect of sitogluside. Further in-depth experimental studies are required to validate the therapeutic value of AB-DA for treating osteoporosis in clinical practice.

Non-inferiority of intermittent theta burst stimulation over the left V1 vs. classical target for depression: A randomized, double-blind trial.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) targeting the visual cortex (VC) has shown antidepressant effects for major depressive disorder (MDD) in sham-controlled trials, but comparisons with rTMS targeting the left dorsolateral prefrontal cortex (DLPFC) are lacking. We aimed to determine the non-inferiority of intermittent theta-burst stimulation (iTBS) over VC vs DLPFC for MDD. METHODS: Participants randomly received navigated iTBS over the left V1 or the left DLPFC twice daily for 14 days with a 3-month follow-up. The primary outcome was change in Hamilton Depression Rating Scale (HAMD-17) score from baseline to treatment end, with 2.5 points as the non-inferiority margin. Secondary outcomes included: improvement in Montgomery-Asberg Depression Rating Scale (MADRS), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA); response and remission rates; suicidal ideation and adverse events. RESULTS: Of 75 randomized patients, 67 completed full treatment, including 52 first-episode patients and 15 relapsers. The primary outcome indicated the non-inferiority of VC (adjusted difference 1.14, lower 97.5 % CI -1.24; p = .002), confirmed by improvements in objective cognitive task and protein levels, as did most secondary outcomes. Reduced suicidal ideation after treatment, incidence of eye discomfort and pain score were lower in the VC group. CONCLUSIONS: Left VC iTBS has the potential to be non-inferior to DLPFC iTBS in most first-episode MDD in improving depressive symptoms and cognitive function, with less suicidal ideation and adverse events. LIMITATIONS: Given the limited sample size, the lack of a sham control and the use of antidepressants, the findings should be interpreted with caution.

COVIDpro: Database for Mining Protein Dysregulation in Patients with COVID-19.

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 still has limited treatment options. Our understanding of the molecular dysregulations that occur in response to infection remains incomplete. We developed a web application COVIDpro (https://www.guomics.com/covidPro/) that includes proteomics data obtained from 41 original studies conducted in 32 hospitals worldwide, involving 3077 patients and covering 19 types of clinical specimens, predominantly plasma and serum. The data set encompasses 53 protein expression matrices, comprising a total of 5434 samples and 14,403 unique proteins. We identified a panel of proteins that exhibit significant dysregulation, enabling the classification of COVID-19 patients into severe and non-severe disease categories. The proteomic signatures achieved promising results in distinguishing severe cases, with a mean area under the curve of 0.87 and accuracy of 0.80 across five independent test sets. COVIDpro serves as a valuable resource for testing hypotheses and exploring potential targets for novel treatments in COVID-19 patients.

Clinical Network Systems Biology: Traversing the Cancer Multiverse.

In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has revealed that cancer, beyond its genomic heterogeneity, is a complex system of microenvironments, sub-clonal tumor populations, and a variety of other cell types that impinge on the genetic and non-genetic mechanisms underlying the disease. Thus, a systems approach to cancer biology has become instrumental in identifying the key components of tumor initiation, progression, and the eventual emergence of drug resistance. Through the union of clinical medicine and basic sciences, there has been a revolution in the development and approval of cancer therapeutic drug options including tyrosine kinase inhibitors, antibody-drug conjugates, and immunotherapy. This 'Team Medicine' approach within the cancer systems biology framework can be further improved upon through the development of high-throughput clinical trial models that utilize machine learning models, rapid sample processing to grow patient tumor cell cultures, test multiple therapeutic options and assign appropriate therapy to individual patients quickly and efficiently. The integration of systems biology into the clinical network would allow for rapid advances in personalized medicine that are often hindered by a lack of drug development and drug testing.

Correlation of Q223R and K109R polymorphisms in leptin receptor gene with susceptibility of breast cancer: A systematic review and meta-analysis.

BACKGROUND: Increasing evidence has suggested a strong association of Q223R (rs1137101) and K109R (rs1137100) polymorphisms in leptin receptor (LEPR) gene with susceptibility of breast cancer (BC), but inconsistent results were obtained. To provide a quantitative assessment of this association, a systematic review and meta-analysis was performed. METHODS: A literature search of PubMed, EMBASE, Google Scholar, and the Chinese National Knowledge Infrastructure was collected. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. RESULTS: A total of 20 case-control studies for Q223R polymorphism and 8 case-control studies for K109R polymorphism were included. Significant association between Q223R polymorphism and BC risk was not found in total, Asian or Caucasian population, but in African population: allelic model, OR = 0.72, 95% CI = 0.60-0.86, p < 0.001; recessive model, OR = 0.67, 95%CI = 0.52-0.87, P = 0.003; dominant model, OR = 1.58, 95% CI = 1.15-2.17, p = 0.004; homozygous model, OR = 0.51, 95% CI = 0.36-0.78, p < 0.001. Significant association between K109R polymorphism and BC risk was not found in total or Caucasian population, but in Asian population: dominant model, OR = 0.24, 95% CI = 0.07-0.84, p = 0.03; heterozygous model, OR = 1.87, 95% CI = 1.07-3.26, p = 0.03. CONCLUSION: The available evidence suggests that Q223R polymorphism may be significantly associated with BC risk in African population. K109R polymorphism may be significantly associated with BC risk in Asian population.

A Closer Look at EGFR Inhibitor Resistance in Non-Small Cell Lung Cancer through the Lens of Precision Medicine.

The development of EGFR small-molecule inhibitors has provided significant benefit for the affected patient population. Unfortunately, current inhibitors are no curative therapy, and their development has been driven by on-target mutations that interfere with binding and thus inhibitory activity. Genomic studies have revealed that, in addition to these on-target mutations, there are also multiple off-target mechanisms of EGFR inhibitor resistance and novel therapeutics that can overcome these challenges are sought. Resistance to competitive 1st-generation and covalent 2nd- and 3rd-generation EGFR inhibitors is overall more complex than initially thought, and novel 4th-generation allosteric inhibitors are expected to suffer from a similar fate. Additional nongenetic mechanisms of resistance are significant and can include up to 50% of the escape pathways. These potential targets have gained recent interest and are usually not part of cancer panels that look for alterations in resistant patient specimen. We discuss the duality between genetic and nongenetic EGFR inhibitor drug resistance and summarize current team medicine approaches, wherein clinical developments, hand in hand with drug development research, drive potential opportunities for combination therapy.

Correlation of DEPDC5 rs1012068 and rs5998152 Polymorphisms with Risk of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.

Background: Emerging evidence has shown that two common genetic polymorphisms within the pleckstrin domain-containing protein 5 (DEPDC5), rs1012068 and rs5998152, may be associated with the risk of hepatocellular carcinoma (HCC), especially in those individuals chronically infected with the hepatitis C virus (HCV) or the hepatitis B virus (HBV). However, these findings have not been consistently replicated in the literature due to limited sample sizes or different etiologies of HCC. Thus, the present systematic review and meta-analysis were performed to resolve this inconsistency. Methods: The databases PubMed, Embase, Web of Science, the China National Knowledge Infrastructure, and Scopus were searched up to December 12, 2022. Data from relevant studies were pooled, and odds ratios and 95% confidence intervals were calculated. Results: A total of 11 case-control studies encompassing 2,609 cases and 8,171 controls on rs1012068 and three encompassing 411 cases and 1,448 controls on rs5998152 were included. Results indicated that the DEPDC5 rs1012068 polymorphism did not significantly increase HCC risk in the total population (allelic model (OR = 1.32, 95% CI = 1.04-1.67, P = 0.02); the recessive model (OR = 1.42, 95% CI = 0.96-2.10, P = 0.08); the dominant model (OR = 1.43, 95% CI = 1.09-1.87, P = 0.01); the homozygous model (OR = 1.61, 95% CI = 1.01-2.57, P = 0.05); the heterozygous model (OR = 1.39, 95% CI = 1.09-1.79, P = 0.009)). Subgroup analyses based on ethnicity and etiology revealed that the rs1012068 polymorphism, under all five genetic models, was associated with increased HCC risk in Asians or in individuals with chronic HBV infection but not in individuals with chronic HCV infection. A significant association was also observed between rs5998152 and HCV-related HCC risk in Asians chronically infected with HCV under allelic, dominant, and heterozygous models. Conclusion: Our study suggests that the DEPDC5 rs1012068 polymorphism increases HCC risk, especially in Asians with chronic HBV infection, while the rs5998152 polymorphism increases HCC risk in Asians with chronic HCV infection.

Overexpression of POU3F2 promotes radioresistance in triple-negative breast cancer via Akt pathway activation.

PURPOSE: POU3F2 is associated with malignant behaviors and poor prognosis in cancer. However, the function and mechanism of POU3F2 in breast cancer remain to be elucidated. Our study aimed to explore the role of POU3F2 in triple-negative breast cancer and radiotherapy. METHODS: POU3F2 expression was examined by RT-PCR and Western blot. The proliferation of cancer cells was measured by MTT assay. Migration of cancer cells was determined by Transwell assay and wound healing assay. To determine which protein interacts with POU3F2, Co-IP was performed. Survival analysis was performed based on the online database GEPIA. DNA damage after radiation was examined by Comet Assay. Radiosensitivity was evaluated with clonogenic survival assays. A tumor xenograft model was established with MDA-MB-231 breast cancer cells in BALB/c nude mice to explore the effect of POU3F2 in vivo. RESULTS: We found that the expression of POU3F2 was significantly elevated in breast cancer cells, especially in TNBC, and higher POU3F2 expression was related to poor prognosis of patients with breast cancer. Functional assays revealed that POU3F2 promoted proliferation, migration, and invasion of triple-negative breast cancer (TNBC) cells in vitro and in vivo. In addition, the knockdown of POU3F2 decreased the radioresistance of TNBC cells in vitro. Furthermore, POU3F2 could enhance the activation of the Akt pathway by interacting with ARNT2, thereby promoting proliferation and radioresistance in TNBC cells. CONCLUSIONS: Our results provide evidence that high expression of POU3F2 promotes radioresistance in triple-negative breast cancer via Akt pathway activation by interacting with ARNT2.