Anti-stress effects of ginseng via down-regulation of tyrosine hydroxylase (TH) and dopamine β-hydroxylase (DBH) gene expression in immobilization-stressed rats and PC12 cells

Catecholamines are among the first molecules that displayed a kind of response to prolonged or repeated stress. It is well established that long-term stress leads to the induction of catecholamine biosynthetic enzymes such as tyrosine hydroxylase (TH) and dopamine β-hydroxylase (DBH) in adrenal medulla. The aim of the present study was to evaluate the effects of ginseng on TH and DBH mRNA expression. Repeated (2 h daily, 14 days) immobilization stress resulted in a significant increase of TH and DBH mRNA levels in rat adrenal medulla. However, ginseng treatment reversed the stress-induced increase of TH and DBH mRNA expression in the immobilization-stressed rats. Nicotine as a ligand of the nicotinic acetylcholine receptor (nAChR) in adrenal medulla stimulates catecholamine secretion and activates TH and DBH gene expression. Nicotine treatment increased mRNA levels of TH and DBH by 3.3- and 3.1-fold in PC12 cells. The ginseng total saponin exhibited a significant reversal in the nicotine-induced increase of TH and DBH mRNA expression, decreasing the mRNA levels of TH and DBH by 57.2% and 48.9%, respectively in PC12 cells. In conclusion, immobilization stress induced catecholamine biosynthetic enzymes gene expression, while ginseng appeared to restore homeostasis via suppression of TH and DBH gene expression. In part, the regulatory activity in the TH and DBH gene expression of ginseng may account for the anti-stress action produced by ginseng

A multi-institutional study of the prevalence of BRCA1 and BRCA2 large genomic rearrangements in familial breast cancer patients

Background: Large genomic rearrangements (LGRs) in the BRCA1/2 genes are frequently observed in breast cancer patients who are negative for BRCA1/2 small mutations. Here, we examined 221 familial breast cancer patients from 37 hospitals to estimate the contribution of LGRs, in a nationwide context, to the development of breast cancer. Methods: Direct sequencing or mutation scanning followed by direct sequencing was performed to screen small mutations. BRCA1/2 small mutation-negative patients were screened for the presence of LGRs using a multiple ligation-dependent probe amplification (MLPA) assay. Results: Using a combined strategy to detect the presence of small mutations and LGRs, we identified BRCA1/2 small mutations in 78 (35.3%) out of 221 familial breast cancer patients and BRCA1 LGRs in 3 (2.1%) out of 143 BRCA1/2 small mutation-negative patients: the deletion of exons 11–13, the deletion of exons 13–15, and whole gene deletion of exons 1-24. The novel deletion of exons 11–13 is thought to result from a non-homologous recombination event mediated by a microhomology sequence comprised of 3 or 4 base pairs: c.3416_4357 + 1863delins187 (NG_005905.2: g.33369_44944delins187). Conclusions: In this study, we showed that LGRs were found in 3.7% (3/81) of the patients who had mutations in BRCA1 or BRCA2, and 7.5% (3/40) of patients with mutations in BRCA1. This suggests that the contribution of LGRs to familial breast cancer in this population might be comparable to that in other ethnic populations. Given these findings, an MLPA to screen for mutations in the BRCA1 gene is recommended as an initial screening test in highly selective settings.Peer Reviewe

Ischemic and Bleeding Events Associated with Thrombocytopenia and Thrombocytosis after Percutaneous Coronary Intervention in Patients with Acute Myocardial Infarction

The early and late ischemic and bleeding clinical outcomes according to baseline platelet count after percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI) remain unclear. Overall, 10,667 patients from the Cardiovascular Risk and identification of potential high-risk population in AMI (COREA-AMI) I and II registries were classified according to the following universal criteria on baseline platelet counts: (1) moderate to severe thrombocytopenia (platelet \u3c 100 K/µL, n = 101), (2) mild thrombocytopenia (platelet = 100~149 K/µL, n = 631), (3) normal reference (platelet = 150~450 K/µL, n = 9832), and (4) thrombocytosis (platelet \u3e 450 K/µL, n = 103). The primary endpoint was the occurrence of major adverse cardiovascular events (MACE). The secondary outcome was Bleeding Academic Research Consortium (BARC) 2, 3, and 5 bleeding. After adjusting for confounders, the moderate to severe thrombocytopenia (HR, 2.03; 95% CI, 1.49–2.78); p \u3c 0.001), mild thrombocytopenia (HR, 1.15; 95% CI, 1.01–1.34; p = 0.045), and thrombocytosis groups (HR, 1.47; 95% CI, 1.07–2.03; p = 0.019) showed higher 5-year MACE rates than the normal reference. In BARC 2, 3, and 5 bleeding outcomes, the bleedings rates were higher than the normal range in the moderate to severe thrombocytopenia (HR, 2.18; 95% CI, 1.36–3.49; p = 0.001) and mild thrombocytopenia (HR, 1.41; 95% CI, 1.12–1.78; p = 0.004) groups. Patients with AMI had higher 5-year MACE rates after PCI if they had lower- or higher-than-normal platelet counts. Thrombocytopenia revealed higher early and late bleeding rates whereas thrombocytosis showed long-term bleeding trends, although these trends were not statistically significant

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fishers exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient usingin vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage (http://www.wang-lab-hkust.com:3838/TMZEP) Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher’s exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs