A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

     

Metabolomics approach for predicting response to neoadjuvant chemotherapy for colorectal cancer

Introduction

Colorectal cancer (CRC) is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. Only some CRC patients will benefit from neoadjuvant chemotherapy (NACT).

Objectives

An accurate prediction of response to NACT in CRC patients would greatly facilitate optimal personalized management, which could improve their long-term survival and clinical outcomes.

Methods

In this study, plasma metabolite profiling was performed to identify potential biomarker candidates that can predict response to NACT for CRC. Metabolic profiles of plasma from non-response (n?=?30) and response (n?=?27) patients to NACT were studied using UHPLC–quadruple time-of-flight)/mass spectrometry analyses and statistical analysis methods.

Results

The concentrations of nine metabolites were significantly different when comparing response to NACT. The area under the receiver operating characteristic curve value of the potential biomarkers was up to 0.83 discriminating the non-response and response group to NACT, superior to the clinical parameters (carcinoembryonic antigen and carbohydrate antigen 199).

Conclusion

These results show promise for larger studies that could result in more personalized treatment protocols for CRC patients.

     

Best serum biomarker combination for ovarian cancer classification

Background

Screening test using CA-125 is the most common test for detecting ovarian cancer. However, the level of CA-125 is diverse by variable condition other than ovarian cancer. It has led to misdiagnosis of ovarian cancer.

Methods

In this paper, we explore the 16 serum biomarker for finding alternative biomarker combination to reduce misdiagnosis. For experiment, we use the serum samples that contain 101 cancer and 92 healthy samples. We perform two major tasks: Marker selection and Classification. For optimal marker selection, we use genetic algorithm, random forest, T-test and logistic regression. For classification, we compare linear discriminative analysis, K-nearest neighbor and logistic regression.

Results

The final results show that the logistic regression gives high performance for both tasks, and HE4-ELISA, PDGF-AA, Prolactin, TTR is the best biomarker combination for detecting ovarian cancer.

Conclusions

We find the combination which contains TTR and Prolactin gives high performance for cancer detection. Early detection of ovarian cancer can reduce high mortality rates. Finding a combination of multiple biomarkers for diagnostic tests with high sensitivity and specificity is very important.

     

Associations of branched-chain amino acids with parameters of energy balance and survival in colorectal cancer patients: results from the ColoCare study

Background

Branched-chain amino acids (BCAA) have been previously linked to survival in colorectal cancer (CRC) patients. It is unclear whether BCAAs are prognostic biomarkers or surrogate markers for energy balance.

Objectives

We aimed to determine correlations of BCAAs with markers of energy balance over time and to investigate prognostic significance of BCAAs in CRC.

Methods

We used urinary samples from newly diagnosed CRC patients [n?=?163; (stage I–IV)] from the ColoCare study in Heidelberg, Germany, collected at surgery (n?=?163), 6 (n?=?83) and 12 months follow-up (n?=?54). Isoleucine, leucine, valine, (2Z)-3-methylglutaconic acid (3HM), 2-ethylhydracrylic acid (2EA), 2-methyl-3-hydroxybutyrate (2M3H) were detected using gas-chromatography mass-spectrometry and proton-nuclear-magnetic-resonance spectroscopy. Partial correlation coefficients between BCAAs with body mass index, physical activity (metabolic equivalent) and muscle area were computed and adjusted for sex and age at diagnosis. We used Cox proportional hazard models to investigate overall survival (OS) after 24 months of follow-up.

Results

We did not observe significant correlations between BCAAs and parameters of energy balance at all time points (correlation ranges: BMI: r?=???0.13 to ??0.01; METs: r?=???0.14 to 0.02; dorsal muscle: r?=???0.03 to 0.10). BCAAs were not associated with risk of death in stage I–III (e.g., valine: HR_log2?=?1.62, p?=?0.25) or in stage IV tumors. Elevated concentrations of 2EA and 2M3H were significantly associated with OS, independent of stage (2EA: stage I–III: HR_log2?=?0.42, p?=?0.04; stage IV: HR_log2?=?0.51, p?=?0.01).

Conclusion

Our study suggests that BCAAs in colorectal cancer patients do not reflect parameters of energy balance and may be independently associated with overall survival.

     

<Superscript>1</Superscript>H NMR metabolic profiling of gastric cancer patients with lymph node metastasis

Introduction

Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.

Objectives

We performed ¹H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.

Methods

¹H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).

Results

There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.

Conclusion

To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.

     

Candidate serum metabolite biomarkers for differentiating gastroesophageal reflux disease,Barrett’s esophagus,and high-grade dysplasia/esophageal adenocarcinoma

Introduction/objectives

Incidence of esophageal adenocarcinoma (EA), an often fatal cancer, has increased sharply over recent decades. Several important risk factors (reflux, obesity, smoking) have been identified for EA and its precursor, Barrett’s esophagus (BE), but a key challenge remains in identifying individuals at highest risk, since most with reflux do not develop BE, and most with BE do not progress to cancer. Metabolomics represents an emerging approach for identifying novel biomarkers associated with cancer development.

Methods

We used targeted liquid chromatography-mass spectrometry (LC-MS) to profile 57 metabolites in 322 serum specimens derived from individuals with gastroesophageal reflux disease (GERD), BE, high-grade dysplasia (HGD), or EA, drawn from two well-annotated epidemiologic parent studies.

Results

Multiple metabolites differed significantly (P?<?0.05) between BE versus GERD (n?=?9), and between HGD/EA versus BE (n?=?4). Several top candidates (FDR q?≤?0.15), including urate, homocysteine, and 3-nitrotyrosine, are linked to inflammatory processes, which may contribute to BE/EA pathogenesis. Multivariate modeling achieved moderate discrimination between HGD/EA and BE (AUC?=?0.75), with less pronounced separation for BE versus GERD (AUC?=?0.64).

Conclusion

Serum metabolite differences can be detected between individuals with GERD versus BE, and between those with BE versus HGD/EA, and may help differentiate patients at different stages of progression to EA.

     

Polycystic ovary syndrome in Indian women: a mass spectrometry based serum metabolomics approach

Introduction

Polycystic ovary syndrome (PCOS) is a complex, heterogeneous endocrinological disorder with uncertain pathogenesis and is very common in women of reproductive age. There are few reports of utilizing metabolomics approach to understand the complex pathophysiology of PCOS. However, excluding one previous NMR-based metabolomics study, none of the study was conducted in Indian population.

Objective

The study aims to compare the serum metabolomic profile of PCOS women with controls from the Eastern region of India.

Methods

PCOS women (n?=?35) and healthy control women (n?=?30) undergoing tubal ligation were recruited for this study. Serum metabolic profiles were generated using liquid chromatography–tandem mass spectrometry (LC-MS/MS) and gas chromatography–mass spectrometry (GC-MS). Multivariate statistical analysis was applied to spectral data obtained from both the LC-MS/MS and GC/MS.

Results

Nine metabolites were identified to be most significantly dysregulated in sera of PCOS women; however, few other identified metabolites were also altered but with lesser significance. Amongst these metabolites, riboflavin, sucrose, adenine and N-acetyl glycine, phosphoric acid and cortisol were down-regulated, whereas, thymine, cystathionine, and phenylalanine were up-regulated in PCOS when compared with controls. The observed changes in metabolite expression suggested alterations in aminoacyl-tRNA biosynthesis, metabolism of nitrogen, alanine-aspartate-glutamate, galactose, glycine-serine-threonine, and pyrimidine-purine among several metabolic pathways possibly implicated in these PCOS women.

Conclusion

The altered metabolites identified in PCOS women of Eastern Indian population, provide insight into current perceptive of the disease pathology, metabolic involvements, and may be considered as putative markers of PCOS.

     

Metabolomic characterization of experimental ovarian cancer ascitic fluid

Introduction

Malignant ascites (MA) is a major cause of morbidity that occurs in 37% of ovarian cancer patients. The accumulation of MA in the peritoneal cavity due to cancer results in debilitating symptoms and extremely poor quality of life. There is an urgent unmet need to expand the understanding of MA to design effective treatment strategies, and to improve MA diagnosis.

Objective

Our purpose here is to contribute to a better characterization of MA metabolic composition in ovarian cancer.

Method

We determined the metabolic composition of ascitic fluids resulting from orthotopic growth of two ovarian cancer cell lines, the mouse ID8- vascular endothelial growth factor (VEGF)-Defb29 cell line and the human OVCAR3 cell line using high-resolution ¹H MRS. ID8-VEGF-Defb29 tumors induce large volumes of ascites, while OVCAR3 tumors induce ascites less frequently and at smaller volumes. To better understand the factors driving the metabolic composition of the fluid, we characterized the metabolism of these ovarian cancer cells in culture by analyzing cell lysates and conditioned culture media with ¹H NMR.

Results

Distinct metabolite patterns were detected in ascitic fluid collected from OVCAR3 and ID8-VEGF-Defb29 tumor bearing mice that were not reflected in the corresponding cell culture or conditioned medium.

Conclusion

High-resolution ¹H NMR metabolic markers of MA can be used to improve characterization and diagnosis of MA. Metabolic characterization of MA can provide new insights into how MA fluid supports cancer cell growth and resistance to treatment, and has the potential to identify metabolic targeting strategies to reduce or eliminate the formation of MA.

     

Comprehensive quantitative lipidomic approach to investigate serum phospholipid alterations in breast cancer

Introduction

Globally, breast cancer is the most common cancer in women and ranks second most common cause of cancer related mortality. Although efforts are made by researchers in molecular characterization of breast cancer using “-OMIC’S” approaches, limited work has explored to understand the phospholipid alterations in breast cancer.

Objectives

This study aims to explore five classes of serum phospholipid alterations in breast cancer towards discrimination of breast cancer from benign and healthy controls.

Methods

Twenty eight each of breast cancer patients and age-matched benign and healthy control serum samples were used to identify alterations of phospholipids using liquid chromatography-multiple reaction monitoring-mass spectrometry. Both multivariate and univariate statistical analyses were applied to investigate breast cancer associated phospholipid alterations. Differentially expressed phospholipid species were further confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Results

Among the identified and quantified 200 phospholipids, 25 phospholipids were found to be statistically significant (VIP > 1.4 and ANOVA p < 0.05) in the serum of women with breast cancer when compared with benign and healthy controls. Comparison of serum phospholipids of breast cancer patients and healthy controls revealed 12 phospholipids were found to be differentially expressed in which six were up-regulated and six were down-regulated. While comparative analysis of breast cancer serum against benign showed an increased concentration of six phospholipids in breast cancer samples. Further, significantly altered phospholipids were structurally characterized by enhanced product ion scanning.

Conclusion

Our results demonstrate that some of the differentially regulated phospholipids identified in our study such as PE (14:1/16:0), PC (18:0/18:0), LPE 14:0, PE (20:0/22:2) could be a panel of potential signature which can discriminate breast cancer from benign and healthy controls. These findings also provide insight into lipidomic information that can be used for monitoring of breast cancer progression.

     

Benign mixed epithelial stromal tumor of the renal pelvis with exophytic growth: case report

Background

Mixed epithelial and stromal tumor (MEST) is a distinctive benign composite neoplasm of the kidney predominantly seen in females mostly in the perimenopausal period. Although these tumors are known to arise from renal pelvis, our case was distinct in that it had no intrapelvic component growing in exophytic fashion.

Case report

A 35 year old female patient presented to us with vague abdominal pain. She had undergone excision of bilateral ovarian cystic masses for cystic teratoma twelve years earlier. A computed tomography scan of abdomen and pelvis showed a 9 × 7 cm uniformly solid mass with poor contrast enhancement situated in the inferomedial aspect of the left kidney. On exploration, the mass was arising from the inferior and anterior aspect of left renal pelvis, and was attached to it with a narrow pedicle. There was no adherence or attachment to the renal parenchyma. The mass was excised preserving the kidney. Microscopically, the tumor was composed of large collagenized areas containing bundles of spindle cells and several 'microcysts' lined by cuboidal epithelium suggestive of a benign mixed epithelial stromal tumor.

Discussion

Mixed epithelial tumors usually present in perimenopausal women as a partially cystic mass. Tumors are composed of irregular mixtures of cystic and solid areas, glands with variable complexity and distribution and the stromal component is characterized by a spindle cell proliferation. Commonly, it arises from the renal parenchyma and pelvis and nephrectomy is advocated to manage these tumors.

Conclusion

MEST is a distinctive benign tumor of the kidney that should be distinguished from other renal neoplasms. MEST arising from the renal pelvis and growing exophytically is a rare entity. The overall prognosis is favorable.

     

Quantification of angiogenesis in estrogen receptor-positive and negative breast carcinoma

Background

The objective of this study was to evaluate angiogenesis according to CD34 antigen expression in estrogen receptor (ER)-positive and negative breast carcinomas.

Methods

This study comprised 64 cases of infiltrating ductal carcinoma in postmenopausal women divided into two groups: Group A: ER-positive, n = 35; and Group B: ER-negative, n = 29. The anti-CD34 monoclonal antibody was used as a marker for endothelial cells. Microvessel count was carried out in 10 fields per slide using a 40× objective lens (magnification 400×). Statistical analysis of the data was performed using Student's t-test (p < 0.05).

Results

The mean number of vessels stained with the anti-CD34 antibody in the estrogen receptor-positive and negative tumors was 23.51 ± 1.15 and 40.24 ± 0.42, respectively. The number of microvessels was significantly greater in the estrogen receptor-negative tumors (p < 0.001).

Conclusion

ER-negative tumors have significantly greater CD34 antigen expression compared to ER-positive tumors.

     

Discrimination of pancreatic cancer and pancreatitis by LC-MS metabolomics

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is the fifth most common cause of cancer-related death in Europe with a 5-year survival rate of <5%. Chronic pancreatitis (CP) is a risk factor for PDAC development, but in the majority of cases malignancy is discovered too late for curative treatment. There is at present no reliable diagnostic marker for PDAC available.

Objectives

The aim of the study was to identify single blood-based metabolites or a panel of metabolites discriminating PDAC and CP using liquid chromatography-mass spectrometry (LC-MS).

Methods

A discovery cohort comprising PDAC (n?=?44) and CP (n?=?23) samples was analyzed by LC-MS followed by univariate (Student’s t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Discriminative metabolite features were subject to raw data examination and identification to ensure high feature quality. Their discriminatory power was then confirmed in an independent validation cohort including PDAC (n?=?20) and CP (n?=?31) samples.

Results

Glycocholic acid, N-palmitoyl glutamic acid and hexanoylcarnitine were identified as single markers discriminating PDAC and CP by univariate analysis. OPLS-DA resulted in a panel of five metabolites including the aforementioned three metabolites as well as phenylacetylglutamine (PAGN) and chenodeoxyglycocholate.

Conclusion

Using LC-MS-based metabolomics we identified three single metabolites and a five-metabolite panel discriminating PDAC and CP in two independent cohorts. Although further study is needed in larger cohorts, the metabolites identified are potentially of use in PDAC diagnostics.

     

Intratumoral anti-HuD immunotoxin therapy for small cell lung cancer and neuroblastoma

Background

Most patients with small cell lung cancer (SCLC) or neuroblastoma (NB) already show clinically detectable metastases at diagnosis and have an extremely poor prognosis even when treated with combined modalities. The HuD-antigen is a neuronal RNA-binding protein that is expressed in 100% of SCLC tumor cells and over 50% of neuroblastoma cells. The correlation between high titers of circulating anti-HuD antibodies in patients and spontaneous tumor remission suggests that the HuD-antigen might be a potential molecular target for immunotherapy.

Methods

We have constructed a new antibody-toxin compound (called BW-2) by assembling a mouse anti-human-HuD monoclonal antibody onto streptavidin/saporin complexes.

Results

We found that the immunotoxin BW-2 specifically killed HuD-positive human SCLC and NB cancer cells at very low concentrations in vitro. Moreover, intratumoral immunotoxin therapy in a nude mouse model of human SCLC (n?=?6) significantly reduced local tumor progression without causing toxicity. When the same intratumoral immunotoxin protocol was applied to an immunocompetent A/J mouse model of NB, significant inhibition of local tumor growth was also observed. In neuroblastoma allografted A/J mice (n?=?5) treated twice with intratumoral immunotoxin, significant tumor regression occurred in over 80% of the animals and their duration of tumor response was significantly prolonged.

Conclusions

Our study suggests that anti-HuD based immunotoxin therapy may prove to be an effective alternative treatment for patients with SCLC and NB.

     

Metabolomic prediction of endometrial cancer

Introduction

Endometrial cancer (EC) is associated with metabolic disturbances including obesity, diabetes and metabolic syndrome. Identifying metabolite biomarkers for EC detection has a crucial role in reducing morbidity and mortality.

Objective

To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC.

Methods

We performed NMR and mass spectrometry based metabolomic analyses of serum in EC cases versus controls. A total of 46 early-stage (FIGO stages I–II) and 10 late-stage (FIGO stages III–IV) EC cases constituted the study group. A total of 60 unaffected control samples were used. Patients and controls were divided randomly into a discovery group (n?=?69) and an independent validation group (n?=?47). Predictive algorithms based on biomarkers and demographic characteristics were generated using logistic regression analysis.

Results

A total of 181 metabolites were evaluated. Extensive changes in metabolite levels were noted in the EC versus the control group. The combination of C14:2, phosphatidylcholine with acyl-alkyl residue sum C38:1 (PCae C38:1) and 3-hydroxybutyric acid had an area under the receiver operating characteristics curve (AUC) (95% CI)?=?0.826 (0.706–0.946) and a sensitivity?=?82.6%, and specificity?=?70.8% for EC overall. For early EC prediction: BMI, C14:2 and PC ae C40:1 had an AUC (95% CI)?=?0.819 (0.689–0.95) and a sensitivity?=?72.2% and specificity?=?79.2% in the validation group.

Conclusions

EC is characterized by significant perturbations in important cellular metabolites. Metabolites accurately detected early-stage EC cases and EC overall which could lead to the development of non-invasive biomarkers for earlier detection of EC and for monitoring disease recurrence.

     

Altered metabolite levels and correlations in patients with colorectal cancer and polyps detected using seemingly unrelated regression analysis

Introduction

Metabolomics technologies enable the identification of putative biomarkers for numerous diseases; however, the influence of confounding factors on metabolite levels poses a major challenge in moving forward with such metabolites for pre-clinical or clinical applications.

Objectives

To address this challenge, we analyzed metabolomics data from a colorectal cancer (CRC) study, and used seemingly unrelated regression (SUR) to account for the effects of confounding factors including gender, BMI, age, alcohol use, and smoking.

Methods

A SUR model based on 113 serum metabolites quantified using targeted mass spectrometry, identified 20 metabolites that differentiated CRC patients (n?=?36), patients with polyp (n?=?39), and healthy subjects (n?=?83). Models built using different groups of biologically related metabolites achieved improved differentiation and were significant for 26 out of 29 groups. Furthermore, the networks of correlated metabolites constructed for all groups of metabolites using the ParCorA algorithm, before or after application of the SUR model, showed significant alterations for CRC and polyp patients relative to healthy controls.

Results

The results showed that demographic covariates, such as gender, BMI, BMI², and smoking status, exhibit significant confounding effects on metabolite levels, which can be modeled effectively.

Conclusion

These results not only provide new insights into addressing the major issue of confounding effects in metabolomics analysis, but also shed light on issues related to establishing reliable biomarkers and the biological connections between them in a complex disease.

     

Magnetic resonance imaging features for differentiating breast papilloma with high-risk or malignant lesions from benign papilloma: a retrospective study on 158 patients

Background

Benign breast papilloma is currently managed with conservative management with close observation. In contrast, papilloma with high-risk or malignant lesions warrants surgical excision. The purpose of our study was to investigate magnetic resonance imaging (MRI) features of breast papilloma and to identify imaging diagnostic indicators for papilloma with high-risk or malignant lesions.

Methods

MRI features of 175 surgically confirmed papillomas on 158 patients were retrospectively reviewed. The 175 cases included 132 cases of benign papilloma and 43 cases of papilloma with high-risk or malignant lesions. The MRI features of these lesions were classified into three types: mass, non-mass enhancement (NME), and occult lesion. The occult lesion was defined as the presence of only ductal dilation without any enhanced lesions on MRI. For a mass lesion, the mixed mass-NME lesion was considered if linear, segmental or regional enhanced lesion was found adjacent to the mass. Clinical and MRI features were compared by univariate and multivariate analysis between the benign papilloma and the papilloma with high-risk or malignant lesions.

Results

Multivariate logistic regression analysis demonstrated that clinical characteristics including being or older than 50?years (odds ratio [OR]?=?4.506), having bloody nipple discharge (OR?=?4.499), and concurrent breast cancer (OR?=?5.083) were significant indicators for papilloma with high-risk or malignant lesions. On MRI, most papillomas presented as mass (n?=?135, 77.1%), and fewer as NME (n?=?37, 21.1%) and occult lesion (n?=?3, 1.7%). For the mass lesion, the logistic regression analysis demonstrated that a mass size exceeding 10?mm (OR?=?2.956) and mixed mass-NME lesion (OR?=?4.143) were independent risk indicators for a papilloma with high-risk or malignant lesions. For the NME lesion, the segmental or regional distribution was more commonly observed in the papilloma with high-risk or malignant lesions (61.5%) than the benign papilloma (12.5%) (P?=?0.006). All the cases of occult lesions were benign papillomas.

Conclusions

MRI features including a mass size exceeding 10?mm, mixed mass-NME lesion, and NMEs with segmental or regional distribution indicate a papilloma with high-risk or malignant lesions.

     

Comparisons of gene coexpression network modules in breast cancer and ovarian cancer

Background

Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules of both cancers, so as to infer the potential cancer-related modules.

Methods

We applied the eigen-decomposition to the matrix that integrates the gene coexpression networks of both breast cancer and ovarian cancer. With hierarchical clustering of the related eigenvectors, we obtained the network modules of both cancers simultaneously. Enrichment analysis on Gene Ontology (GO), KEGG pathway, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA) in the identified modules was performed.

Results

We identified 43 modules that are enriched by at least one of the four types of enrichments. 31, 25, and 18 modules are enriched by GO terms, KEGG pathways, and DO terms, respectively. The structure of 29 modules in both cancers is significantly different with p-values less than 0.05, of which 25 modules have larger densities in ovarian cancer. One module was found to be significantly enriched by the terms related to breast cancer from GO, KEGG and DO enrichment. One module was found to be significantly enriched by ovarian cancer related terms.

Conclusion

Breast cancer and ovarian cancer share some common properties on the module level. Integration of both cancers helps identifying the potential cancer associated modules.

     

Autophagy regulated by lncRNA HOTAIR contributes to the cisplatin-induced resistance in endometrial cancer cells

Objectives

To identify whether lncRNAs (long non-coding RNA) participate in the regulation of cisplatin-resistant induced autophagy in endometrial cancer cells.

Results

Autophagy activity was significantly boosted in cisplatin-resistant Ishikawa cells, a human endometrial cancer cell line, compared with that in parental Ishikawa cells. After analyzing the overall long noncoding RNA (lncRNA) profiling, a meaningful lncRNA, HOTAIR, was identified. It was down-regulated simultaneously in cisplatin-resistant Ishikawa cells and parental Ishikawa cells treated with cisplatin. RNA interference of HOTAIR reduced the proliferation of cisplatin-resistant Ishikawa cells and enhanced the autophagy activity of cisplatin-resistant Ishikawa cells with or without cisplatin treatment, in addition, beclin-1, multidrug resistance (MDR), and P-glycoprotein (P-gp) were mediated by lncRNA HOTAIR.

Conclusions

It is clear that lncRNAs, specifically HOTAIR, can regulate the cisplatin-resistance ability of human endometrial cancer cells through the regulation of autophagy by influencing Beclin-1, MDR, and P-gp expression.

     

Epithelial-myoepithelial carcinoma of the parotid gland,unusual malignancy radiologically simulating a benign lesion: case report

Background

Ultrasound (US), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are widely used in the clinical diagnosis of parotid gland tumors and their efficacy in identifying benign lesions is well documented. However, problems arise when facing some malignant lesions. Only few cases of salivary gland low grade malignant tumors have been previously reported in the literature complete with the radiological features.

Case presentation

We here describe a case of epithelial-myoepithelial carcinoma (EMC) of the parotid gland, a low grade malignant tumor, with spread to an intraparotid lymph node and with CT and MRI findings mimicking a benign lesion.

Conclusion

All the images revealed sharply outlined profiles and a homogeneous enhancement of the nodule, suggesting a benign tumor and demonstrating that a radiological evaluation of the lesion alone may be unsatisfactory and misleading in the diagnosis of salivary gland tumours, especially in the case of low grade malignant tumors, such as EMC.