Identification of ASF1A and HJURP by global H3-H4 histone chaperone analysis as a prognostic two-gene model in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignancy with poor prognosis. Abnormal expression of H3-H4 histone chaperones has been identified in many cancers and holds promise as a biomarker for diagnosis and prognosis. However, systemic analysis of H3-H4 histone chaperones in HCC is still lacking. Here, we investigated the expression of 19 known H3-H4 histone chaperones in HCC. Integrated analysis of multiple public databases indicated that these chaperones are highly expressed in HCC tumor tissues, which was further verified by immunohistochemistry (IHC) staining in offline samples. Additionally, survival analysis suggested that HCC patients with upregulated H3-H4 histone chaperones have poor prognosis. Using LASSO and Cox regression, we constructed a two-gene model (ASF1A, HJURP) that accurately predicts prognosis in ICGC-LIRI and GEO HCC data, which was further validated in HCC tissue microarrays with follow-up information. GSEA revealed that HCCs in the high-risk group were associated with enhanced cell cycle progression and DNA replication. Intriguingly, HCCs in the high-risk group exhibited increased immune infiltration and sensitivity to immune checkpoint therapy (ICT). In summary, H3-H4 histone chaperones play a critical role in HCC progression, and the two-gene (ASF1A, HJURP) risk model is effective for predicting survival outcomes and sensitivity to immunotherapy for HCC patients.

Single-cell transcriptomics reveals ferrimagnetic vortex iron oxide nanoring-mediated mild magnetic hyperthermia exerts antitumor effects by alleviating macrophage suppression in breast cancer.

The potential of Ferrimagnetic vortex iron oxide nanoring-mediated mild magnetic hyperthermia (FVIO-MHT) in solid tumor therapy has been demonstrated. However, the impact of FVIO-MHT on the tumor microenvironment (TME) remains unclear. This study utilized single-cell transcriptome sequencing to examine the alterations in the TME in response to FVIO-MHT in breast cancer. The results revealed the cellular composition within the tumor microenvironment (TME) was primarily modified due to a decrease in tumor cells and an increased infiltration of myeloid cells. Subsequently, an enhancement in active oxygen (ROS) metabolism was observed, indicating oxidative damage to tumor cells. Interestingly, FVIO-MHT reprogrammed the macrophages' phenotypes, as evidenced by alterations in the transcriptome characteristics associated with both classic and alternative activated phenotypes. And an elevated level of ROS generation and oxidative phosphorylation suggested that activated phagocytosis and inflammation occurred in macrophages. Additionally, cell-cell communication analysis revealed that FVIO-MHT attenuated the suppression between tumor cells and macrophages by inhibiting phagocytic checkpoint and macrophage migration inhibitory factor signaling pathways. Inhibition of B2m, an anti-phagocytosis checkpoint, could promote macrophage-mediated phagocytosis and significantly inhibit tumor growth. These data emphasize FVIO-MHT may promote the antitumor capabilities of macrophages by alleviating the suppression between tumor cells and macrophages.

Biomedical Indicators of Patients with Non-Puerperal Mastitis: A Retrospective Study.

BACKGROUND: Non-puerperal mastitis (NPM), a recurrent chronic inflammation of non-lactating breast, often proves tremendous difficulty in treatment, and it may give rise to its complicated symptoms and unclear etiology. Furthermore, the clinical morbidity rate of NPM has been increasing in recent years. METHODS: Overall, 284 patients diagnosed with NPM were consecutively recruited as cases in this study, and patients with benign breast disease (n = 1128) were enrolled as control. The clinical, biomedical, and pathological indicators were analyzed. Univariate and multivariate logistic analysis were used to distinguish risks between NPM and benign breast mass patients. Furthermore, according to the pathological characteristics, the patients of NPM were classified into two subgroups: mammary duct ectasia (MDE) and granulomatous lobular mastitis (GLM). The differences of biomedical indicators between MDE and GLM groups were also analyzed. RESULTS: Compared with benign breast mass group, the level of high-density lipoprotein (HDL-C) significantly decreased, while lipoprotein(a) (Lp(a)) and blood glucose (GLU) both increased in NPM group. According to univariate and multivariate logistic analysis, the onset age and HDL-C were generally decreased, while Lp(a) and GLU were increased in NPM group. The onset age, HDL-C, Lp(a), and GLU were modeled to distinguish NPM and benign breast mass. Significant differences were also observed between MDE and GLM patients in biomedical indicators, such as lipoprotein(a) (Lp(a)), lactate dehydrogenase (LDH), creatine kinase (CK), total cholesterol (TC), and so on. CONCLUSIONS: Our results indicated for the first time that biomarkers were associated with NPM. The biomedical indicators involved in lipid metabolism might be important factors in the development and treatment of NPM. In addition, MDE and GLM are two diseases with different inflammatory states of NPM. These findings would be helpful for a better understanding of NPM and give us some insights to develop new diagnostic and therapeutic strategies.

Pharmacokinetics of immediate and sustained-release formulations of paroxetine: Population pharmacokinetic approach to guide paroxetine personalized therapy in chinese psychotic patients.

Paroxetine is one of the most potent selective serotonin reuptake inhibitors (SSRIs) approved for treating depression, panic disorder, and obsessive-compulsive disorder. There is evidence linking genetic polymorphisms and nonlinear metabolism to the Paroxetine's pharmacokinetic (PK) variability. The purpose of the present study was to develop a population PK (PPK) model of paroxetine in Chinese patients, which was used to define the paroxetine's PK parameters and quantify the effect of clinical and baseline demographic factors on these PK characteristics. The study included 184 inpatients with psychosis (103 females and 81 males), with a total of 372 serum concentrations of paroxetine for PPK analyses. The total daily dosage ranged from 20 to 75 mg. One compartment model could fit the PKs characterize of paroxetine. Covariate analysis revealed that dose, formulation, and sex had a significant effect on the PK parameters of paroxetine; however, there was no evident genetic influence of CYP2D6 enzymes on paroxetine concentrations in Chinese patients. The study determined that the population's apparent distribution volume (V/F) and apparent clearance (CL/F), respectively, were 8850 and 21.2 L/h. The CL/F decreased 1-2-fold for each 10 mg dose increase, whereas the different formulations caused a decrease in V/F of 66.6%. Sex was found to affect bioavailability (F), which decreased F by 47.5%. Females had higher F values than males. This PPK model described data from patients with psychosis who received paroxetine immediate-release tablets (IR-T) and/or sustained-release tablets (SR-T). Paroxetine trough concentrations and relative bioavailability were different between formulations and sex. The altered serum concentrations of paroxetine resulting from individual variants and additive effects need to be considered, to optimize the dosage regimen for individual patients.

rs144012689 is a highly specific representative marker of HLA-B*15:02 in the Chinese population.

Objective: To develop an accurate and rapid real-time PCR technique for HLA-B*15:02 genotyping and investigate HLA-B*15:02 allele frequency in four ethnic populations in China. Materials & methods: Based on the highly specific representative markers, a real-time PCR assay was developed for HLA-B*15:02 genotyping, and HLA-B*15:02 allele frequencies were screened in four ethnic populations of China. Sequence-based typing was used to validate the accuracy of the assay. Results: The sensitivity and specificity of the assay were 100%, and the detection limit was 0.2 ng. The frequency of HLA-B*15:02 alleles distributed in the Bouyei population was significantly higher than in the Han group (p < 0.01). Neither the Tibetan nor the Uyghur population carried the HLA-B*15:02 haplotype. Conclusion: The authors developed an accurate HLA-B*15:02 genotyping method for evaluating the risk of adverse drug reactions induced by carbamazepine in various ethnic populations in China.

Personalized quantitative evaluation of the quality of radiotherapy plans based on dose prediction / 中华放射医学与防护杂志

Objective:To develop a dose prediction-based quantitative evaluation method of the quality of radiotherapy plans, and to verify the clinical feasibility and clinical value of the method .Methods:The 3D U-Netwas trained using the radiotherapy plans of 45 rectal cancer cases that were formulated by physicists with more than five years of radiotherapy experience. After obtaining 3D dose distribution using 3D U-Net prediction, this study established the plan quality metrics of intensity modulated radiotherapy(IMRT) rectal cancer radiotherapy plans using dose-volume histogram(DVH) indexes of dose prediction. Then, the initial scores of rectal cancer radiotherapy plans were determined.Taking the predicted dose as the optimization goal, the radiotherapy plans were optimized and scored again. The clinical significance of this scoring method was verified by comparing the scores and dosimetric parameters of the 15 rectal cancer cases before and after optimization.Results:The radiotherapy plans before and after optimization all met the clinical dose requirements. The total scores were(77.21±9.74) before optimization, and (88.78±4.92) after optimization. Therefore, the optimized radiotherapy planswon increased scores with a statistically significant difference( t=-4.105, P<0.05). Compared to the plans before optimization, the optimized plans show decreased Dmax of all organs at risk to different extents. Moreover, the Dmax, V107%, and HI of PTV and the Dmax of the bladder decreased in the optimized plans, with statistically significant differences ( t=2.346-5.771, P<0.05). There was no statistically significant difference in other indexes before and after optimization ( P>0.05).The quality of the optimized plans were improved to a certain extent. Conclusions:This study proposed a dose prediction-based quantitative evaluation method of the quality of radiotherapy plans. It can be used for the effective personalized elevation of the quality of radiotherapy plans, which is beneficial to effectively compare and review the quality of clinical plans determined by different physicists and provide personalized dose indicators. Moreover, it can provide great guidance for the formulation of clinical therapy plans.

Research progress on total skin irradiation using helical tomotherapy / 中华放射肿瘤学杂志

Cutaneous T-cell lymphomas are a relatively rare group of mature T-cell lymphomas mainly manifesting in the skin, and its common subtype is mycosis fungoides. Total skin electron irradiation is one of the important conventional treatment methods, but there are many disadvantages, such as uneven dose distribution, poor position repetition, and long treatment time, which affect the clinical efficacy and patient prognosis. With the emergence and gradual popularization of helical tomotherapy in recent years, more and more medical institutions are gradually expanding their applications in total skin irradiation due to their ability to treat ultra-long targets and achieve dose-sculpted distribution, aiming to further explore its good or bad, and confirm whether it can replace the traditional total skin electron irradiation. In this article, research progress on total skin irradiation using helical tomotherapy was reviewed, the development of treatment technology, clinical efficacy and current concerns and controversies were illustrated.

Application of the ArcherQA three-dimensional dose verification system in intensity-modulated radiotherapy plans for nasopharyngeal carcinoma / 中华放射医学与防护杂志

Objective:To investigate the feasibility of applying the ArcherQA three-dimensional (3D) dosimetric verification system in intensity-modulated radiotherapy (IMRT) plans for nasopharyngeal carcinoma (NPC).Methods:A retrospective analysis was conducted for 105 NPC patients′ IMRT plans developed using the Eclipse treatment planning system (TPS). Dose verification was conducted using the ArcherQA system and through portal dosimetry (PD). Moreover, this study compared γ passing rates (criteria: 3 mm/3%, TH = 10%) between ArcherQA and PD and the doses delivered to the target volume ( Dmean, D90%) and organs at risk (OARs) ( Dmean) between ArcherQA and TPS, and analyzed the 3D γ passing rates of each organ at risk calculated by ArcherQA. Results:The average 3D γ passing rate calculated by ArcherQA was (99.04±1.01)%, and the average 2D γ passing rate measured by PD was (99.49±0.78)%, with statistically significant differences ( t=-3.35, P< 0.05). The dosimetric differences to the target volume between ArcherQA and TPS were as follows: the average difference in Dmean to the gross tumor volume (GTV) was (0.57±0.48)%, and the average difference in D90% was (0.65±0.56)%. For the target volume, the average γ passing rate was (97.67±3.43)% for GTV, (97.80±4.35)% for GTVnd-L, (97.82±4.07)% for GTVnd-R, (97.88±2.44)% for CTV1, and (96.64±4.32)% for CTV2. The mean dose difference of each target volume was CTV1 (0.57±0.46)%, GTVnd-L (0.85±0.55)%, GTVnd-R (0.73±0.55)%, and CTV2 (0.88±0.52)%. For OARs, the mean γ passing rate was (99.93±0.22)% for the brainstem, (99.17±2.82)% for the optic chiasm, (100±0)% for the lens, (99.56±1.05)% for the spinal cord, (99.00±2.06)% for the thyroid, and (87.86±10.42)% for the trachea. Statistically significant differences in the average doses to OARs were observed ( t=-14.62 to 4.82, P<0.05), except for those to the left optic nerve, the right hippocampus, and the right parotid gland. Conclusions:Based on the high-performance GPU platform and the Monte Carlo dose algorithm, ArcherQA can provide accurate 3D dose distribution and 3D γ passing rates inside patients according to CT images and provide the dose volume histogram (DVH) of various regions of interest (ROIs). Therefore, the ArcherQA three-dimensional dose verification system can be applied to IMRT plans for NPC. Moreover, it is inducive to improve the treatment efficiency since it does not occupy the accelerator operation time.

Diverging targets mediate the pathological roleof miR-199a-5p and miR-199a-3p by promoting cardiac hypertrophy and fibrosis.

MicroRNA-199a-5p (miR-199a-5p) and -3p are enriched in the myocardium, but it is unknown whether miR-199a-5p and -3p are co-expressed in cardiac remodeling and what roles they have in cardiac hypertrophy and fibrosis. We show that miR-199a-5p and -3p are co-upregulated in the mouse and human myocardium with cardiac remodeling and in Ang-II-treated neonatal mouse ventricular cardiomyocytes (NMVCs) and cardiac fibroblasts (CFs). miR-199a-5p and -3p could aggravate cardiac hypertrophy and fibrosis in vivo and in vitro. PPAR gamma coactivator 1 alpha (Ppargc1a) and sirtuin 1 (Sirt1) were identified as target genes to mediate miR-199a-5p in promoting both cardiac hypertrophy and fibrosis. However, miR-199a-3p aggravated cardiac hypertrophy and fibrosis through targeting RB transcriptional corepressor 1 (Rb1) and Smad1, respectively. Serum response factor and nuclear factor κB p65 participated in the upregulation of miR-199a-5p and -3p in Ang-II-treated NMVCs and mouse CFs, and could be conversely elevated by miR-199a-5p and -3p. Together, Ppargc1a and Sirt1, Rb1 and Smad1 mediated the pathological effect of miR-199a-5p and -3p by promoting cardiac hypertrophy and fibrosis, respectively. This study suggests a possible new strategy for cardiac remodeling therapy by inhibiting miR-199a-5p and -3p.

Self-adjustable automatic planning method of intensity modulated radiotherapy based on 3D predicted dose / 中华放射医学与防护杂志

Objective:To develope a self-adjustable automatic planning method of intensity modulated radiotherapy based on predicted dose, in order to enhance the robustness of automatic planning.Methods:After the patients′ dose by 3D U-Res-Net_B network was predicted, the current dose was calculated based on the last iteration result, then the predicted dose was combined to calculate the target dose and optimized. With all iterations completed or exit conditions satisfied, final treatment plannings would be acquired. A total of 30 cases of rectal cancer were tested to verify the effectiveness of the algorithm.Results:The mean value of planning target volumes′ V100% was (95.03±0.91)% for clinical plans, close to (94.67±1.96)% for automatical plans( P>0.05), and better than (92.90±2.13)% for predicted dose with the statisically significant difference ( t=29.0, P<0.05). Automatic planning′s indexes such as V35 of small intestines, V40 of bladders and V20 - V40 of femoral heads were lower than predicted and clinical ones, with the statisically significant difference( t=4.5-118.0, P<0.05). Discrepancy in other indexes of organs at risk was not statistically significantly different( P>0.05). Conclusions:This method made automatic planning processes more robust and more adaptive to difficult clinical situations.

Assessment of biological dose of proton radiotherapy based on different relative biological effect models / 中华放射医学与防护杂志

Objective:To assess proton biological dose with using two kinds of relative biological effect models and to compare them with traditional clinical proton biological dose ( Dose1.1). Methods:Based on Particle simulation tools(TOPAS), physical dose, LET d and LET t were calculated in water phantom and two anthropomorphic phantoms (brain and prostate tumors) respectively. Then DoseLET d and DoseLET t were calculated according to different relative biological effect models, an RBE was 1.1 in traditional clinical proton biological dose calculation. Three kinds of biological doses were compared in the water phantom. To quantify the differences between three method in anthropomorphic phantoms, three points ( D1, D2, D3) were selected according to the physical dose to compare the biological dose. Results:DoseLET d and DoseLET t in water phantom showed the same trend with water depth and both of them were higher than Dose1.1 at the end of proton beam range. The maximal difference between DoseLET d and DoseLET t in the anthropomorphic phantoms was 10.08 cGy, where the relative difference was less than 5%. When DoseLET d and DoseLET t were compared with Dose1.1, the maximal differences in brain tumor target were 71.97 cGy and 61.91 cGy respectively, where the relative differences were less than 25%. The maximal differences in prostate tumor target were 25.95 and 19.96 cGy respectively, where the relative differences were less than 12%. However, the differences outside the target were very small, where the maximal differences in brain and prostate tumors were 5.99 cGy and 9.92 cGy respectively, and the relative differences were less than 5%. Conclusions:Biological doses calculated by two method are of little difference in both water and anthropomorphic phantoms, however, large differences were observed when they were compared with the traditional clinical proton biological dose especially in the high dose area.

Oncogenic action of the exosome cofactor RBM7 by stabilization of CDK1 mRNA in breast cancer.

RNA exosome can target the specific RNAs for their processing/degradation by distinct exosome cofactors. As a key component in exosome cofactors, RNA binding motif protein 7 (RBM7) shows the binding specificity for uridine-rich sequences in mRNAs via its RNA recognition motifs. However, the specific function of RBM7 in human breast cancer remains unclear. In vitro, experiments revealed that knockdown of RBM7 dramatically inhibited breast cancer cell proliferation, while inducing G1 cell cycle arrest; the opposite was true when RBM7 was overexpressed. Meanwhile, experiments in vivo confirmed the oncogenic function of RBM7 in breast cancer. RNA sequencing and the following pathway analysis found that cyclin-dependent kinase1 (CDK1) was one of the main gene regulated by RBM7. Overexpression of RBM7 increased CDK1 expression, while RBM7 knockdown decreased it. RIP assays additionally found that RBM7 bound directly to CDK1 mRNA. It was also showed that RBM7 could directly bind to the AU-rich elements (AREs) in 3'-UTR of CDK1 mRNA, which contributed to the stability of CDK1 mRNA by lengthening its half-life. More importantly, the oncogenic activity reduced by knockdown of RBM7 could be rescued by overexpression of CDK1 both in vitro and in vivo, but mutant CDK1 failed. All the evidences implied RBM7 promoted breast cancer cell proliferation by stabilizing CDK1 mRNA via binding to AREs in its 3'-UTR. As we knew, it was the first attempt to connect the RNA exosome to the tumor development, providing new insights into the mechanisms of RNA exosome-linked diseases.

Correction to: The RNA binding protein RBMS3 inhibits the metastasis of breast cancer by regulating Twist1 expression.

In the original publication of this article [1], the molecular weight of RBMS3 was incorrectly noted as 38 KDa within Fig 1A, Fig 2A and Fig 2B. The figures have been updated to list the correct molecular weight of RBMS3 as 41 KDa.

Circular RNA circRNA_000203 aggravates cardiac hypertrophy via suppressing miR-26b-5p and miR-140-3p binding to Gata4.

AIMS: Circular RNAs (circRNAs) are involved in gene regulation in a variety of physiological and pathological processes. The present study aimed to investigate the effect of circRNA_000203 on cardiac hypertrophy and the potential mechanisms involved. METHODS AND RESULTS: CircRNA_000203 was found to be up-regulated in the myocardium of Ang-II-infused mice and in the cytoplasma of Ang-II-treated neonatal mouse ventricular cardiomyocytes (NMVCs). Enforced expression of circRNA_000203 enhances cell size and expression of atrial natriuretic peptide and ß-myosin heavy chain in NMVCs. In vivo, heart function was impaired and cardiac hypertrophy was aggravated in Ang-II-infused myocardium-specific circRNA_000203 transgenic mice (Tg-circ203). Mechanistically, we found that circRNA_000203 could specifically sponge miR-26b-5p, -140-3p in NMVCs. Further, dual-luciferase reporter assay showed that miR-26b-5p, -140-3p could interact with 3'-UTRs of Gata4 gene, and circRNA_000203 could block the above interactions. In addition, Gata4 expression is transcriptionally inhibited by miR-26b-5p, -140-3p mimic in NMVCs but enhanced by over-expression of circRNA_000203 in vitro and in vivo. Functionally, miR-26b-5p, -140-3p, and Gata4 siRNA, could reverse the hypertrophic growth in Ang-II-induced NMVCs, as well as eliminate the pro-hypertrophic effect of circRNA_000203 in NMVCs. Furthermore, we demonstrated that NF-κB signalling mediates the up-regulation of circRNA_000203 in NMVCs exposed to Ang-II treatment. CONCLUSIONS: Our data demonstrated that circRNA_000203 exacerbates cardiac hypertrophy via suppressing miR-26b-5p and miR-140-3p leading to enhanced Gata4 levels.

Dose distributions prediction for intensity-modulated radiotherapy of postoperative rectal cancer based on deep learning / 中华放射医学与防护杂志

Objective:To develop a deep learning model for predicting three-dimensional (3D) voxel-wise dose distributions for intensity-modulated radiotherapy (IMRT).Methods:A total of 110 postoperative rectal cancer cases treated by IMRT were considered in the study, of which 90 cases were randomly selected as the training-validating set and the remaining as the testing set. A 3D deep learning model named 3D U-Res-Net was constructed to predict 3D dose distributions. Three types of 3D matrices from CT images, structure sets and beam configurations were fed into the independent input channel, respectively, and the 3D matrix of IMRT dose distributions was taken as the output to train the 3D model. The obtained 3D model was used to predict new 3D dose distributions. The predicted accuracy was evaluated in two aspects: the average dose prediction bias and mean absolute errors (MAEs)of all voxels within the body, the dice similarity coefficients (DSCs), Hausdorff distance(HD 95) and mean surface distance (MSD) of different isodose surfaces were used to address the spatial correspondence between predicted and clinical delivered 3D dose distributions; the dosimetric index (DI) including homogeneity index, conformity index, V50, V45 for PTV and OARs between predicted and clinical truth were statistically analyzed with the paired-samples t test. Results:For the 20 testing cases, the average prediction bias ranged from -2.12% to 2.88%, and the MAEs varied from 2.55% to 5.75%. The DSCs value was above 0.9 for all isodose surfaces, the average MSD ranged from 0.21 cm to 0.45 cm, and the average HD 95 varied from 0.61 cm to 1.54 cm. There was no statistically significant difference for all DIs, except for bladder Dmean. Conclusions:This study developed a deep learning model based on 3D U-Res-Net by considering beam configurations input and achieved an accurate 3D voxel-wise dose prediction for rectal cancer treated by IMRT.

TCDD-Inducible Poly-ADP-Ribose Polymerase (TIPARP), A Novel Therapeutic Target Of Breast Cancer.

BACKGROUND: TIPARP (TCDD-inducible poly-ADP-ribose polymerase), a mono-ADP-ribosyltransferase and a transcriptional repressor of aryl hydrocarbon receptor (AHR), was one of the potential therapeutic targets for human cancers identified by CRISPR-Cas9 screens recently. Studies about TIPARP on cancers are scarce till now, most of which just focus on expressions, while the functions have not been widely reported yet. Moreover, the TIPARP prognostic significance and therapeutic value of breast cancer is also uncertain. METHODS: The present study was performed to comprehensively analyze the expression pattern, prognostic effect, potential therapeutic function of TIPARP in breast cancer by pooling all currently available databases online including Oncomine, UALCAN, bc-GenExMiner, Kaplan-Meier Plotter, COSMIC, UCSC Xena, STRING, DAVID and Comparative Toxicogenomics Database. Further, we also performed several cell biology experiments including RT-qPCR, Western blot and CCK-8 in cellular and clinical sample levels to confirm the conclusions from bioinformatics analysis. RESULTS: TIPARP was expressed lower in tumor tissues comparing with normal tissues. Meanwhile, several clinical parameters of breast cancer patients were correlated with TIPARP expression. Further, higher TIPARP expression was related to preferable survival. Moreover, the mutations and DNA methylation of TIPARP might contribute to TIPARP dysregulation in breast cancer. Interactors with TIPARP were significantly enriched in telomere maintenance, telomere organization and mainly participated in pathways in cancer. Finally, several common drugs including metformin were observed to up-regulate the expression of TIPARP. CONCLUSION: TIPARP might act as a preferable prognostic marker of breast cancer through multiple biological processes such as DNA methylation, mutation as well as pathway related to telomere and so on. TIPARP could be considered as a potential therapeutic target for breast cancer. However, large-scale and comprehensive research is needed to clarify our results.

Effects of Comedication and Genetic Factors on the Population Pharmacokinetics of Lamotrigine: A Prospective Analysis in Chinese Patients With Epilepsy.

Lamotrigine (LTG) is a second-generation anti-epileptic drug widely used for focal and generalized seizures in adults and children, and as a first-line medication in pregnant women and women of childbearing age. However, LTG pharmacokinetics shows high inter-individual variability, thus potentially leading to therapeutic failure or side effects in patients. This prospective study aimed to establish a population pharmacokinetics model for LTG in Chinese patients with epilepsy and to investigate the effects of genetic variants in uridine diphosphate glucuronosyltransferase (UGT) 1A4, UGT2B7, MDR1, ABCG2, ABCC2, and SLC22A1, as well as non-genetic factors, on LTG pharmacokinetics. The study population consisted of 89 patients with epilepsy, with 419 concentrations of LTG. A nonlinear mixed effects model was implemented in NONMEM software. A one-compartment model with first-order input and first-order elimination was found to adequately characterize LTG concentration. The population estimates of the apparent volume of distribution (V/F) and apparent clearance (CL/F) were 12.7 L and 1.12 L/h, respectively. The use of valproic acid decreased CL/F by 38.5%, whereas the co-administration of rifampicin caused an increase in CL/F of 64.7%. The CL/F decreased by 52.5% in SLC22A1-1222AA carriers. Patients with the ABCG2-34AA genotype had a 42.0% decrease in V/F, whereas patients with the MDR1-2677TT and C3435TT genotypes had a 136% increase in V/F. No obvious genetic effect of UGT enzymes was found relative to the concentrations of LTG in Chinese patients. Recommended dose regimens for patients with different gene polymorphisms and comedications were estimated on the basis of Monte Carlo simulations and the established model. These findings should be valuable for developing individualized dosage regimens in adult and adolescent Chinese patients 13-65 years of age.

The RNA binding protein RBMS3 inhibits the metastasis of breast cancer by regulating Twist1 expression.

BACKGROUND: Metastasis remains the biggest obstacle for breast cancer treatment. Therefore, identification of specific biomarker of metastasis is very necessary. The RNA binding protein 3 (RBMS3) acts as a tumor suppressor in various cancers. Whereas, its role and underlying molecular mechanism in breast cancer is far from elucidated. METHODS: Quantitative real-time PCR and western blots were carried out to determine the expression of RBMS3 in breast cancer cells and tissues. Transwell and in vivo metastasis assay were conducted to investigate the effects of RBMS3 on migration, invasion and metastasis of breast cancer cells. Transcriptome sequencing was applied to screen out the differential gene expression affected by RBMS3. RNA immunoprecipitation assay combined with luciferase reporter assay were performed to explore the direct correlation between RBMS3 and Twist1 mRNA. RESULTS: RBMS3 was downregulated in breast cancer and ectopic expression of RBMS3 contributed to inhibition of cell migration, invasion in vitro and lung metastasis in vivo. Furthermore, RBMS3 negatively regulated Twsit1 expression via directly binding to 3'-UTR of Twist1 mRNA, and thereby decreased Twist1-induced expression of matrix metalloproteinase 2 (MMP2). Additionally, Twist1-induced cell migration, invasion and lung metastasis could be reversed by the upregulation of RBMS3. CONCLUSIONS: In summary, our study revealed a novel mechanism of the RBMS3/Twsit1/MMP2 axis in the regulation of invasion and metastasis of breast cancer, which may become a potential molecular marker for breast cancer treatment.

The study of automatic treatment planning of prostate cancer based on DVH prediction models of organs at risk / 中华放射肿瘤学杂志

Objective To evaluate the feasibility of utilizing dose-volume histogram (DVH) prediction models of organs at risk (OARs) to deliver automatic treatment planning of prostate cancer.Methods The training set included 30 cases randomly selected from a database of 42 cases of prostate cancer receiving treatment planning.The bladder and rectum were divided into sub-volumes (Ai) of 3 mm in layer thickness according to the spatial distance from the boundary of planning target volume (PTV).A skewed normal Gaussian function was adopted to fit the differential DVH of Ai,and a precise mathematical model was built after optimization.Using the embedded C++ subroutine of Pinnacle scripa,ahe volume of each Ai of the remaining validation set for 12 patients was obtained to predict the DVH parameters of these OARa,ahich were used as the objective functions to create personalized Pinnacle script.Finalla,automatic plans were generated using the script.The dosimetric differences among the original clinical plannina,aredicted value and the automatic treatment planning were statistically compared with paired t-test.Results DVH residual analysis demonstrated that predictive volume fraction of the bladder and rectum above 6 000 cGy were lower than those of the original clinical planning.The automatic treatment planning significantly reduced the V70,V60,V50 of the bladder and the V70 and V60 of the rectum than the original clinical planning (all P＜0.05),the coverage and conformal index (CI) of PTV remained unchangea,and the homogeneity index (HI) was slightly decreased with no statistical significance (P＞ 0.05).Conclusion The automatic treatment planning of the prostate cancer based on the DVH prediction models can reduce the irradiation dose of OARs and improve the treatment planning efficiency.