Diagnostic accuracy of uterine fluid lactate dehydrogenase isoenzyme activity profile and vaginal ultrasound in detecting endometrial cancer in women with postmenopausal bleeding

A novel alternative splicing-based prediction model for uteri corpus endometrial carcinoma

Alternative splicing (AS) is crucial a mechanism by which the complexity of mammalian and viral proteom increased overwhelmingly. There lacks systematic and comprehensive analysis of the prognostic significance of AS profiling landscape for uteri corpus endometrial carcinoma (UCEC). In this study, univariate and multivariate Cox regression analyses were conducted to identify candidate survival-associated AS events curated from SpliceSeq for the construction of prognostic index (PI) models. A correlation network between splicing factor-related AS events and significant survival-associated AS events were constructed using Cytoscape 3.5. As consequence, 28281 AS events from 8137 genes were detected from 506 UCEC patients, including 2630 survival-associated AS events. Kaplan Meier survival analysis revealed that six of the seven PI models (AD, AP, AT, ME, RI and ALL) exhibited good performance in stratifying the prognosis of low risk and high risk group (P<0.05). Among the six PI models, PI-AT performed best with an area under curves (AUC) value of 0.758 from time-dependent receiver operating characteristic. Correlation network implicated potential regulatory mechanism of AS events in UCEC. PI models based on survival-associated AS events for UCEC in this study showed preferable prognosis-predicting ability and may be promising prognostic indicators for UCEC patients.

Summary: This is the first study to systematically investigate the prognostic value of AS in UCEC. Findings in the presents study supported the clinical potential of AS for UCEC and shed light on the potential AS-associated molecular basis of UCEC.

Advances in endometrial cancer protein biomarkers for use in the clinic

INTRODUCTION

Endometrial cancer (EC) is the fourth most common cancer in women in developed countries. The identification of sensitive and specific biomarkers to improve early detection of EC is crucial for an appropriate management of this disease, in which 30% of patients are diagnosed only at advanced stages, which is associated with high levels of morbidity and mortality. Despite major efforts and investments made to identify EC biomarkers, no protein has yet reached the stage of clinical application. Areas covered: This review gathers the numerous candidate biomarkers for EC diagnosis proposed in proteomic studies published from 1978 to 2017. Additionally, we summarize limitations associated with the proteomic technologies and study designs employed in those articles. Finally, we address new perspectives in EC biomarker research, including the comprehensive knowledge of previously suggested candidate biomarkers in conjunction with novel mass spectrometry-based proteomic technologies with enhanced sensitivity and specificity not yet applied to EC studies and a directed clinical perspective in the study design. Expert commentary: These ingredients could be the recipe to accelerate the application of protein biomarkers in the clinic.

Cancer-Related Triplets of mRNA-lncRNA-miRNA Revealed by Integrative Network in Uterine Corpus Endometrial Carcinoma

The regulation of transcriptome expression level is a complex process involving multiple-level interactions among molecules such as protein coding RNA (mRNA), long noncoding RNA (lncRNA), and microRNA (miRNA), which are essential for the transcriptome stability and maintenance and regulation of body homeostasis. The availability of multilevel expression data enables a comprehensive view of the regulatory network. In this study, we analyzed the coding and noncoding gene expression profiles of 301 patients with uterine corpus endometrial carcinoma (UCEC). A new method was proposed to construct a genome-wide integrative network based on variance inflation factor (VIF) regression method. The cross-regulation relations of mRNA, lncRNA, and miRNA were then selected based on clique-searching algorithm from the network, when any two molecules of the three were shown as interacting according to the integrative network. Such relation, which we call the mRNA-lncRNA-miRNA triplet, demonstrated the complexity in transcriptome regulation process. Finally, six UCEC-related triplets were selected in which the mRNA participates in endometrial carcinoma pathway, such as CDH1 and TP53. The multi-type RNAs are proved to be cross-regulated as to each of the six triplets according to literature. All the triplets demonstrated the association with the initiation and progression of UCEC. Our method provides a comprehensive strategy for the investigation of transcriptome regulation mechanism.

Endometrial/uterine corporeal volume ratio (EV/UCV) as predictor of malignancy in women with postmenopausal bleeding

OBJECTIVE

To evaluate the role of endometrial/uterine corporeal volume ratio for the prediction of endometrial malignancy in cases of postmenopausal bleeding.

METHODS

Endometrial volumes and uterine body volumes excluding cervices measured by VOCAL (virtual organ computer-aided analysis) were estimated in 160 women with postmenopausal bleeding. Endometrial/uterine corporeal volume ratios were calculated for all. Endometrial biopsies and histopathological results were obtained for all. One hundred normal postmenopausal women were included as controls.

RESULTS

Histopathological results of the 160 women with postmenopausal bleeding revealed 53 atypia, 27 endometrial cancer and 80 benign conditions. An endometrial/uterine volume (EV/UCV) ratio of a cutoff value >0.017 was predictive of malignancy. Endometrial/uterine volume ratio was more sensitive than endometrial volume and endometrial thickness for prediction of endometrial cancer.

CONCLUSION

An endometrial/uterine volume ratio (EV/UCV) >0.017 is predictive of malignancy. (EV/UCV) was more accurate in the prediction of malignancy than endometrial thickness and endometrial volume.