Yunqin Chen

Identification of HBV-MLL4 Integration and Its Molecular Basis in Chinese Hepatocellular Carcinoma

To gain molecular insights of HBV integration that may contribute to HCC tumorigenesis, we performed whole transcriptome sequencing and whole genome copy number profiling of hepatocellular carcinoma (HCC) samples from 50 Chinese patients. We identified a total of 33 HBV-human integration sites in 16 of 44 HBV-positive HCC tissues, which were enriched in HBV genotype C-infected patients. In addition, significantly recurrent HBV-MLL4 integration (18%; 8/44) was found in this cohort of patients. Using long-range PCR and Sanger sequencing, we comprehensively characterized gDNA and cDNA sequences that encode for the HBV-MLL4 transcripts, and we revealed that HBV integration into MLL4 exons led to much higher mRNA expression of MLL4 than the integration into MLL4 introns due to an alternative splicing mechanism. Moreover, the HBV-MLL4 integration occurred almost exclusively in CTNNB1 and TP53 wild-type patients. The integration was also associated with a distinct gene expression profile. In conclusion, this is the first report on the molecular basis of the MLL4 integration driving MLL4 over-expression. HBV-MLL4 integration occurred frequently in Chinese HCC patients, representing a unique molecular segment for HCC with HBV infection.

Identification of Pathogen Signatures in Prostate Cancer Using RNA-seq.

Infections of the prostate by bacteria, human papillomaviruses, polyomaviruses, xenotropic murine leukemia virus (MLV)-related gammaretroviruses, human cytomegaloviruses and other members of the herpesvirus family have been widely researched. However, many studies have yielded conflicting and controversial results. In this study, we systematically investigated the transcriptomes of human prostate samples for the unique genomic signatures of these pathogens using RNA-seq data from both western and Chinese patients. Human and nonhuman RNA-seq reads were mapped onto human and pathogen reference genomes respectively using alignment tools Bowtie and BLAT. Pathogen infections and integrations were analyzed in adherence with the standards from published studies. Among the nine pathogens (Propionibacterium acnes, HPV, HCMV, XMRV, BKV, JCV, SV40, EBV, and HBV) we analyzed, Propionibacterium acnes genes were detected in all prostate tumor samples and all adjacent samples, but not in prostate samples from healthy individuals. SV40, HCMV, EBV and low-risk HPVs transcripts were detected in one tumor sample and two adjacent samples from Chinese prostate cancer patients, but not in any samples of western prostate cancer patients; XMRV, BKV and JCV sequences were not identified in our work; HBV, as a negative control, was absent from any samples. Moreover, no pathogen integration was identified in our study. While further validation is required, our analysis provides evidence of Propionibacterium acnes infections in human prostate tumors. Noted differences in viral infections across ethnicity remain to be confirmed with other large prostate cancer data sets. The effects of bacterial and viral infections and their contributions to prostate cancer pathogenesis will require continuous research on associated pathogens.

Epidemiology and Outcomes of Complicated Skin and Soft Tissue Infections among Inpatients in Southern China from 2008 to 2013

Complicated skin and soft tissue infections (cSSTI) are some of the most commonly treated infections in hospitals, and place heavy economic burdens on patients and society. Here we report the findings from an analysis of cSSTI based on a retrospective study which was conducted within the Chinese inpatient population. We focused our research on the analysis of the patient population, antibiotic treatment, clinical outcome and economic burden. The study population comprised 527 selected patients hospitalized between 2008 and 2013. Among the hospitalizations with microbiological diagnoses, 61.41% (n = 113) were diagnosed as infected with Gram-positive bacteria, while 46.20% (n = 85) were infected with Gram-negative bacteria. The most commonly found Gram-positive bacteria was Staphylococcus aureus (40.76%, n = 75), and the most common Gram-negative bacteria was Escherichia coli (14.13%, n = 26). About 20% of the Staphylococcus aureus were methicillin-resistant. The resistance rate of isolated Staphylococcus aureus or Escherichia coli to penicillin was around 90%; in contrast, the resistance rate to vancomycin, linezolid or imipenem was low (<20%). A large percentage of patients were treated with cephalosporins and fluoroquinolones, while vancomycin and imipenem were also included to treat drug-resistant pathogens. Over half of the hospitalizations (58.43%, n = 336) experienced treatment modifications. The cost to patients with antibiotic modifications was relatively higher than to those without. In conclusion, our study offers an analysis of the disease characteristics, microbiological diagnoses, treatment patterns and clinical outcomes of cSSTI in four hospitals in Guangdong Province, and sheds lights on the current clinical management of cSSTI in China.

Ranking novel cancer driving synthetic lethal gene pairs using TCGA data

Synthetic lethality (SL) has emerged as a promising approach to cancer therapy. In contrast to the costly and labour-intensive genome-wide siRNA or CRISPR-based human cell line screening approaches, computational approaches to prioritize potential synthetic lethality pairs for further experimental validation represent an attractive alternative. In this study, we propose an efficient and comprehensive in-silico pipeline to rank novel SL gene pairs by mining vast amounts of accumulated tumor high-throughput sequencing data in The Cancer Genome Atlas (TCGA), coupled with other protein interaction networks and cell line information. Our pipeline integrates three significant features, including mutation coverage in TCGA, driver mutation probability and the quantified cancer network information centrality, into a ranking model for SL gene pair identification, which is presented as the first learning-based method for SL identification. As a result, 107 potential SL gene pairs were obtained from the top 10 results covering 11 cancers. Functional analysis of these genes indicated that several promising pathways were identified, including the DNA repair related Fanconi Anemia pathway and HIF-1 signaling pathway. In addition, 4 SL pairs, mTOR-TP53, VEGFR2-TP53, EGFR-TP53, ATM-PRKCA, were validated using drug sensitivity information in the cancer cell line databases CCLE or NCI60. Interestingly, significant differences in the cell growth of mTOR siRNA or EGFR siRNA knock-down were detected between cancer cells with wild type TP53 and mutant TP53. Our study indicates that the pre-screening of potential SL gene pairs based on the large genomics data repertoire of tumor tissues and cancer cell lines could substantially expedite the identification of synthetic lethal gene pairs for cancer therapy.

Genomic and transcriptome profiling identified both human and HBV genetic variations and their interactions in Chinese hepatocellular carcinoma.

Interaction between HBV and host genome integrations in hepatocellular carcinoma (HCC) development is a complex process and the mechanism is still unclear. Here we described in details the quality controls and data mining of aCGH and transcriptome sequencing data on 50 HCC samples from the Chinese patients, published by Dong et al. (2015) (GEO#: GSE65486). In additional to the HBV-MLL4 integration discovered, we also investigated the genetic aberrations of HBV and host genes as well as their genetic interactions. We reported human genome copy number changes and frequent transcriptome variations (e.g. TP53, CTNNB1 mutation, especially MLL family mutations) in this cohort of the patients. For HBV genotype C, we identified a novel linkage disequilibrium region covering HBV replication regulatory elements, including basal core promoter, DR1, epsilon and poly-A regions, which is associated with HBV core antigen over-expression and almost exclusive to HBV-MLL4 integration.

Treatment and survival patterns of Chinese patients diagnosed with breast cancer between 2005 and 2009 in Southwest China: An observational, population-based cohort study.

AbstractBreast cancer is a significant health issue both globally and within China. Here, we present epidemiological data for female patients diagnosed with breast cancer and treated at West China Hospital, Sichuan University, between 2005 and 2009. Patients who were diagnosed with breast cancer between 2005 and 2009 were enrolled. Data cut-off in this analysis was October 2013, allowing a minimum of 3 years’ follow-up, or follow-up until death. Data were collected and subject to statistical analyses to assess relationships between patient and cancer characteristics, treatment patterns and long-term outcomes. A total of 2252 women with breast cancer were included in the analyses. Luminal B was the most common subtype of breast cancer and human epidermal growth factor 2 (HER2)-positive (nonluminal) was the least common. Most patients had early-stage disease (stage ⩽IIIa) at diagnosis. Patients with luminal A appeared to have the best overall survival (OS), compared with other subtypes. Hormone-receptor positivity was associated with improved prognosis, compared with negativity (OS hazard ratio [HR] 0.5). Late-stage compared with early-stage disease at diagnosis was associated with much poorer OS across all patients and tumor subtypes. Clear differences were apparent between breast cancer subtypes and the response to treatment. The interaction of breast cancer subtypes, treatments and disease stage is complex. One of the most important factors for improved prognosis is diagnosis and treatment at an early-stage of disease. With breast cancer becoming an increasingly important health concern, this highlights the importance of establishing systems and protocols to identify and treat patients with breast cancer as early as possible.

Clinical characteristics and antimicrobial patterns in complicated intra-abdominal infections: a 6-year epidemiological study in southern China.

Complicated intra-abdominal infection (cIAIs) are a common and important cause of morbidity worldwide. In this study, the clinical features, microbiological profiles, antimicrobial patterns and treatments of 3233 cIAI patients (mean age, 47.6 years; 54.7% male) with 3531 hospitalisations from 2008-2013 were retrospectively investigated. The most commonly isolated bacteria were Escherichia coli (47.6%), Klebsiella pneumoniae (16.9%), Enterococcus faecalis (10.4%) and Pseudomonas aeruginosa (8.8%). Ciprofloxacin, aminoglycoside (gentamicin), piperacillin/tazobactam and carbapenems exhibited activity against 53%, 76%, 88% and 100% of extended-spectrum β-lactamase (ESBL)-positive Enterobacteriaceae isolates, respectively. Pseudomonas aeruginosa isolates exhibited 100%, 95%, 88%, 71% and 76% susceptibility to aminoglycoside (gentamicin), ciprofloxacin, meropenem, imipenem and ceftazidime, respectively, and Enterococcus remained 100% susceptible to vancomycin and linezolid. β-Lactam antibacterials other than penicillin (specifically third-generation cephalosporins) and imidazole derivatives (ornidazole and metronidazole) were the most common first-line treatments. Patients subjected to regimen change after initial antibiotic treatment had predisposing conditions (e.g. older age, more severe co-morbidities) and a higher incidence of P. aeruginosa infection; in addition, these patients encountered a higher average cost of care and worse clinical outcomes compared with those without medication modification. Taken together, these findings indicate the importance of appropriate initial empirical therapy and suggest the use of combination therapy comprising cephalosporins and metronidazole.

Diagnosis and treatment pattern among rural and urban breast cancer patients in Southwest China from 2005 to 2009

The incidence of all cancers in China is generally higher in urban areas; however, the mortality risk for affected patients is considerably higher in rural areas. We present a subanalysis investigating the differences in patient and disease characteristics, treatment patterns, and outcomes between rural and urban patients who were diagnosed with breast cancer at West China Hospital between 2005–2009. Baseline patient and disease characteristics were recorded, and patients were followed up for a minimum of 3 years, or until death. For this subanalysis, patients were stratified by their residential status (rural or urban). Of the 2252 patients in the cohort, 76.3% were from urban areas and 22.1% were from rural areas. Significant differences were observed in the prevalence of luminal A and human epidermal growth factor receptor 2-positive breast cancers among rural and urban patients. Estrogen receptor (ER)-positive patients were less likely to receive anti-ER therapy if they were from rural areas compared with urban areas; the use of aromatase inhibitors was also significantly lower for rural patients than urban patients. Univariate, multivariate, and Kaplan–Meier analyses all demonstrated that overall survival and progression-free survival were significantly lower for rural patients than urban patients.

Epidemiology, microbiology, and treatment patterns of pediatric patients hospitalized with pneumonia at two hospitals in China: a patient chart review study

Background The etiology, epidemiology, treatment patterns, and clinical outcomes of neonatal and pediatric pneumonia patients in China are not well reported. This retrospective chart review study aimed to describe such information among neonatal (0 to 27 days) and pediatric (28 days to <18 years) pneumonia patients in two regions of China. Methods Electronic medical records of pneumonia hospitalizations (aged <18 years) admitted between 2008 and 2013 from four hospitals under Guangdong Provincial Hospital of Chinese Medicine (Southern China) and between 2010 and 2014 at Peking University People’s Hospital (Beijing, Northern China) were reviewed. Results The average age of neonatal hospitalizations in Beijing (n=92) was 3.5 days. The mean length of hospital stay was 11.2 days, and no deaths occurred. Staphylococcus epidermidis was the most common bacteria found in Beijing patients, whereas Mycoplasma pneumoniae was the most common bacteria found in Guangdong patients. The average age of pediatric hospitalizations was 3.3 (±3.1) and 6.5 (±5.6) years in Guangdong (n=3,046) and Beijing (n=222), respectively. The mean length of hospital stay was 17.4 and 5.8 days, and overall mortality rates were 0.2% and 0.5%. Conclusion The findings revealed a low level of bacterial isolation and hence microbiological diagnoses. There was a low level of in-hospital mortality due to pneumonia, and the majority of hospitalizations were discharged from hospital, suggesting that current practice was generally effective. Neonatal hospitalizations were greater than pediatric hospitalizations in Beijing along with disparity in bacterial profile when compared with Guangdong, intending a need to improve neonatal pneumonia prophylaxis and selection of appropriate treatment.

Dynamic Text Categorization of Search Results for Medical Class Recognition in Real World Evidence Studies in the Chinese Language

Classifying clinical terms from electronic medical record (EMR) systems is critical for real world evidence (RWE) research. Yet the task is challenging, especially in languages other than English. Clinical research institutes require a cost-effective method to address this challenge. We proposed a software pipeline with two components: a feature generator that gathers descriptive words of the terms by text-segmenting the search results from two search engines and a learning mechanism that utilizes machine learning algorithms for classification. Models are trained with training sets of different sizes to determine effectiveness. Models were compared using 10-fold cross validation or another supplied testing set. We applied our pipeline to a Chinese medication term set extracted from a clinical system, and also to a data set of standard medications names. A term-vs.-word frequency matrix was generated based on the Google search results of the term sets. Most models tasked with classifying whether a medication belonged to Western or Chinese medicine achieved high accuracy, especially with radial basis functions (RBF) network. The performance of models trained with training sets of different sizes was not significantly different. When the same approach was applied to the information gathered from another Chinese language search engine (Baidu), better performance was achieved. The results of the other experiments conducted on the medication name set also demonstrates a significant improvement from baseline. Dynamic text categorization with machine learning can be applied to classify clinical terms based on information retrieved from search engines in RWE studies.