Yan Hou

Discrimination between malignant and benign ovarian tumors by plasma metabolomic profiling using ultra performance liquid chromatography/mass spectrometry

BACKGROUND Discrimination between epithelial ovarian cancer (EOC) and benign ovarian tumor (BOT) has always been difficult in clinical practice. We investigated the application of metabolomics in distinguishing EOC and BOT and tried to discover valuable biomarkers. METHODS Plasma metabolomic profiling was performed using ultra-performance liquid chromatography mass spectrometry (UPLC/MS). Partial least-squares discriminant analysis was employed to classify EOC and BOT, and reveal their metabolic differences. The area under the receiver-operating characteristic curve (AUC) was utilized to evaluate the predictive performance of the metabolic profiles for external validation set. RESULTS The metabolomic profiles consisting of 535 metabolites revealed a clear separation between EOC and BOT, with AUC of 0.86 for the external validation set. 6 metabolic biomarkers were identified, and the plasma concentrations of the 4 ascertained biomarkers (L-tryptophan, LysoPC(18:3), LysoPC(14:0), and 2-Piperidinone) were lower in EOC patients than those in BOT patients. Among them, tryptophan and LysoPC have been suspected to participate in cancer progression, and 2-Piperidinone might be a novel biomarker for EOC. CONCLUSIONS Metabolomics could be used to discriminate EOC from BOT in clinical practice, and the identified metabolic biomarkers might be important on investigating the biological mechanisms of EOC.

The long-term efficacy of neoadjuvant chemotherapy followed by radical hysterectomy compared with radical surgery alone or concurrent chemoradiotherapy on locally advanced-stage cervical cancer.

Objectives: The purpose of this study was to compare the long-term survival of patients with locally advanced cervical cancer (stages IB2-IIB) treated with neoadjuvant chemotherapy followed by radical hysterectomy (hysterectomy plus pelvic lymph node dissection) (NACT + RS) with the survival of those treated with radical surgery (hysterectomy plus pelvic lymph node dissection) (RS) or concurrent chemoradiotherapy (CCRT). Methods: A retrospective study was performed. Patients were followed up for 54 to 114 months (median, 82.8 months). All risk factors that may have affected the disease-free survival (DFS) and overall survival (OS) were assessed. Results: From January 2000 to December 2005, 476 eligible patients were followed up. The 5-year DFS rates of the NACT + RS, RS, and CCRT groups were 85.00%, 77.44%, and 52.94%, respectively (P < 0.0001), whereas the 5-year OS rates were 88.67%, 80.21% and 64.37%, respectively (P < 0.0001). The NACT + RS group had significantly higher survival rates than both the RS (DFS: hazard ratio = 1.870, P = 0.0031; OS: hazard ratio = 1.813, P = 0.0175) and CCRT (DFS: hazard ratio = 3.535, P < 0.0001; OS: hazard ratio = 3.157, P < 0.0001) groups, while adjusting for the pathological type, clinical stage, tumor size (initial), and age. The 5-year DFS rate for patients receiving TP (paclitaxel and cisplatin) was 90.55%, and 71.70% for patients receiving PVB (cisplatin, vincristine, and bleomycin); the 5-year OS rates were 96.75% for TP and 70.09% for PVB, respectively. Patients receiving TP had a statistically significant improvement in both 5-year DFS and OS rates (P < 0.001). Conclusions: Neoadjuvant NACT + RS improves the long-term DFS and OS of patients with locally advanced cervical cancer stage IB2-IIB compared with RS alone and especially compared with CCRT. In the NACT + RS group, NACT with TP improves the long-term DFS and OS of patients compared with patients who had PVB chemotherapy regimen. These results may provide some useful information for clinicians to treat patients with locally advanced cervical carcinoma.

Identification of metabolic biomarkers to diagnose epithelial ovarian cancer using a UPLC/QTOF/MS platform

Abstract Background. Currently available tests are insufficient to distinguish patients with epithelial ovarian cancer (EOC) from normal individuals. Metabolomics, a study of metabolic processes in biologic systems, has emerged as a key technology in the measurements of small molecular metabolites in tissues or biofluids. Material and methods. To investigate the application of metabolomics on selecting EOC-associated biomarkers, 173 plasma specimens (80 newly diagnosed EOC patients and 93 normal individuals) were analyzed using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC/QTOF/MS). A two-step strategy was performed to select EOC-associated biomarkers. The first step was to select potential biomarkers in distinguishing 42 cancer patients from 58 normal controls through partial least-squares discriminant analysis (PLS-DA) and database searching, and the second step was to validate the discrimination performance of these biomarkers in a dataset contained 38 EOCs and 35 controls. Results. Eight candidate biomarkers were selected. The combination of these biomarkers resulted in the area of receiver operating characteristic curve (AUC) of 0.941, a sensitivity of 0.921, and a specificity of 0.886 at the best cut-off point for detecting EOC. Discussion. Our findings suggested that sharp differences in metabolic profiles exist between EOC patients and normal controls. The identified eight metabolites associated with EOC may be served as novel biomarkers for diagnosis.

Large‐scale profiling of metabolic dysregulation in ovarian cancer

Ovarian cancer is the leading cause of death in gynecologic malignancies. Profiling of endogenous metabolites has potential to identify changes caused by cancer and provide inspiring insights into cancer metabolism. To systematically investigate ovarian cancer metabolism, we performed metabolic profiling of 448 plasma samples related to epithelial ovarian cancer (EOC) based on ultra‐performance liquid chromatography mass spectrometry in both positive and negative modes. These unbiased metabolomic profiles could well distinguish EOC from benign ovarian tumor (BOT) and uterine fibroid (UF). Fifty‐three metabolites were identified as specific biomarkers for EOC, and this is the first report of piperine, 3‐indolepropionic acid, 5‐hydroxyindoleacetaldehyde and hydroxyphenyllactate as metabolic biomarkers of EOC. The AUC values of these metabolites for discriminating EOC from BOT/UF and early‐stage EOC from BOT/UF were 0.9100/0.9428 and 0.8385/0.8624, respectively. Meanwhile, our metabolites were able to distinguish early‐stage EOC from late‐stage EOC with an AUC of 0.8801. Importantly, analysis of dysregulated metabolic pathways extends our current understanding of EOC metabolism. Metabolic pathways in EOC patients are mainly characterized by abnormal phospholipid metabolism, altered l‐tryptophan catabolism, aggressive fatty acid β‐oxidation and aberrant metabolism of piperidine derivatives. Together, these metabolic pathways provide a foundation to support cancer development and progression. In conclusion, our large‐scale plasma metabolomics study yielded fundamental insights into dysregulated metabolism in ovarian cancer, which could facilitate clinical diagnosis, therapy, prognosis and shed new lights on ovarian cancer pathogenesis.

LAPTM4B overexpression is a novel predictor of epithelial ovarian carcinoma metastasis

LAPTM4B is a novel tumor‐associated gene. To date, there have been no published data regarding the role of LAPTM4B expression in epithelial ovarian carcinoma metastasis. Therefore, this study was performed to determine whether LAPTM4B overexpression is a new predictor of epithelial ovarian carcinoma metastasis. LAPTM4B expression was evaluated in 22 normal ovarian specimens and 139 ovarian carcinomas by western blotting analyses and immunohistochemistry. Univariate and multivariate analyses were used to determine the association between LAPTM4B expression and epithelial ovarian carcinoma metastasis. Western blotting analysis demonstrated that LAPTM4B was overexpressed in metastatic tissues from patients with ovarian cancers, and immunohistochemistry results revealed that among 59 patients with LAPTM4B overexpression, 57 (96.6%) presented intraperitoneal metastasis and 31 (52.5%) had lymph node metastasis. The results of the univariate and multivariate analyses demonstrated that LAPTM4B overexpression correlated with metastasis. The odds ratio of high‐to‐low expression for intraperitoneal metastasis was 11.410 (95% CI: 2.357, 55.239) and that for lymph node metastasis was 6.332 (95% CI: 2.533, 15.831). For intraperitoneal metastasis, the sensitivity and specificity of LAPTM4B overexpression were 48.7% and 90.9%; for lymph node metastasis, they were 73.8%% and 71.1%, respectively. LAPTM4B overexpression is a new predictor of epithelial ovarian carcinoma metastasis and an important potential biomarker for the early diagnosis of ovarian carcinoma.

Reciprocal Changes of Circulating Long Non-Coding RNAs ZFAS1 and CDR1AS Predict Acute Myocardial Infarction

This study sought to evaluate the potential of circulating long non-coding RNAs (lncRNAs) as biomarkers for acute myocardial infarction (AMI). We measured the circulating levels of 15 individual lncRNAs, known to be relevant to cardiovascular disease, using the whole blood samples collected from 103 AMI patients, 149 non-AMI subjects, and 95 healthy volunteers. We found that only two of them, Zinc finger antisense 1 (ZFAS1) and Cdr1 antisense (CDR1AS), showed significant differential expression between AMI patients and control subjects. Circulating level of ZFAS1 was significantly lower in AMI (0.74 ± 0.07) than in non-AMI subjects (1.0 ± 0.05, P < 0.0001), whereas CDR1AS showed the opposite changes with its blood level markedly higher in AMI (2.18 ± 0.24) than in non-AMI subjects (1.0 ± 0.05, P < 0.0001). When comparison was made between AMI and non-AMI, the area under ROC curve was 0.664 for ZFAS1 alone or 0.671 for CDR1AS alone, and 0.691 for ZFAS1 and CDR1AS combination. Univariate and multivariate analyses identified these two lncRNAs as independent predictors for AMI. Similar changes of circulating ZFAS1 and CDR1AS were consistently observed in an AMI mouse model. Reciprocal changes of circulating ZFAS1 and CDR1AS independently predict AMI and may be considered novel biomarkers of AMI.

Metabolic phenotyping for monitoring ovarian cancer patients

Epithelial ovarian cancer (EOC) is the most deadly of the gynecological cancers. New approaches and better tools for monitoring treatment efficacy and disease progression of EOC are required. In this study, metabolomics using rapid resolution liquid chromatography mass spectrometry was applied to a systematic investigation of metabolic changes in response to advanced EOC, surgery and recurrence. The results revealed considerable metabolic differences between groups. Moreover, 37, 30, and 26 metabolites were identified as potential biomarkers for primary, surgical and recurrent EOC, respectively. Primary EOC was characterized by abnormal lipid metabolism and energy disorders. Oxidative stress and surgical efficacy were clear in the post-operative EOC patients. Recurrent EOC patients showed increased amino acid and lipid metabolism compared with primary EOC patients. After cytoreductive surgery, eight metabolites (e.g. l-kynurenine, retinol, hydroxyphenyllactic acid, 2-octenoic acid) corrected towards levels of the control group, and four (e.g. hydroxyphenyllactic acid, 2-octenoic acid) went back again to primary EOC levels after disease relapse. In conclusion, this study delineated metabolic changes in response to advanced EOC, surgery and recurrence, and identified biomarkers that could facilitate both understanding and monitoring of EOC development and progression.

Identification of biomarkers for unstable angina by plasma metabolomic profiling

Unstable angina (UA) is one of the most dangerous types of coronary heart disease and has high mortality and morbidity rates worldwide. However, the diagnostic accuracy for UA is unsatisfactory in clinical practice. In this study, we investigated the application of plasma metabolomics in discovering potential biomarkers for the diagnosis of UA. Plasma samples from 45 UA and 43 atherosclerosis (AS) in-patients were collected and analyzed using rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometry (RRLC-QTOF/MS) in both positive and negative ion modes. Good separations were observed between the UA patients and AS controls. Tandem mass spectrometry experiments were carried out to identify biomarker candidates that contributed most to the discrimination (VIP > 1.2 and p < 0.05). Sixteen potential endogenous biomarkers for UA were identified, and those could perform a satisfactory diagnostic accuracy for discrimination between UA and AS patients (AUC = 0.9143). In the UA patients compared to the AS controls, the plasma concentrations of 12 metabolites were higher while the concentrations of four metabolites were lower. In conclusion, our study demonstrated that plasma metabolomics analyzed by RRLC-QTOF/MS had great potential in biomarker discovery for UA. These biomarkers could not only be helpful for the diagnosis of patients with UA, but also provide more information for further understanding of the metabolic processes of UA.

Long non-coding RNA ZFAS1 interacts with miR-150-5p to regulate Sp1 expression and ovarian cancer cell malignancy

We reported that long non-coding RNA ZFAS1 was upregulated in epithelial ovarian cancer tissues, and was negatively correlated to the overall survival rate of patients with epithelial ovarian cancer in this study. While depletion of ZFAS1 inhibited proliferation, migration, and development of chemoresistance, overexpression of ZFAS1 exhibited an even higher proliferation rate, migration activity, and chemoresistance in epithelial ovarian cancer cell lines. We further found miR-150-5p was a potential target of ZFAS1, which was downregulated in epithelial ovarian cancer tissue. MiR-150-5p subsequently inhibited expression of transcription factor Sp1, as evidence by luciferase assays. Inhibition of miR-150-5p rescued the suppressed proliferation and migration induced by depletion of ZFAS1 in epithelial ovarian cancer cells, at least in part. Taken together, our findings revealed a critical role of ZFAS1/miR-150-5p/Sp1 axis in promoting proliferation rate, migration activity, and development of chemoresistance in epithelial ovarian cancer. And ZFAS1/miR-150-5p may serve as novel markers and therapeutic targets of epithelial ovarian cancer.

Identification of a six-lncRNA signature associated with recurrence of ovarian cancer

Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA expression data were extracted from GSE9891 and GSE30161. LASSO (least absolute shrinkage and selection operator) penalized regression was used to identify an lncRNA-based signature using the GSE9891 training cohort. The signature was then validated in GSE9891 internal and GSE30161 external validation cohorts. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to explore the possible functions of identified lncRNAs. A six-lncRNA signature (RUNX1-IT1, MALAT1, H19, HOTAIRM1, LOC100190986 and AL132709.8) was identified in the training cohort and validated in internal and external validation cohorts using the LASSO method (P < 0.05). This signature was also independent of other clinical factors according to multivariate and sub-group analyses. The identified lncRNAs are involved in cancer-related biological processes and pathways. We selected a highly reliable signature based on six lncRNAs associated with OvCa recurrence. This six-lncRNA signature is a promising method to personalize ovarian cancer therapy and may improve patient quality of life quality according to patients’ condition in the future.