Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression.

BACKGROUND: Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications. METHODS: We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan-Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression. RESULTS: We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion. CONCLUSIONS: Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.

Cytoplasmic Localization Isoform of Cyclin Y Enhanced the Metastatic Ability of Lung Cancer via Regulating Tropomyosin 4.

Cyclin Y (CCNY) is a novel cyclin and highly conserved in metazoan species. Previous studies from our and other laboratory indicate that CCNY play a crucial role in tumor progression. There are two CCNY isoform which has different subcellular distributions, with cytoplasmic isoform (CCNYc) and membrane distribution isoform (CCNYm). However, the expression and function of CCNY isoforms is still unclear. We firstly found CCNYc was expressed in natural lung cancer tissue and cells through the subcellular distribution. Co-IP and immunofluorescence showed that both CCNYm and CCNYc could interact with PFTK1. Further studies illustrated that CCNYc but not CCNYm enhanced cell migration and invasion activity both in vivo and vitro. The function of CCNYc could be inhibited by suppression of PFTK1 expression. In addition, our data indicated that tropomyosin 4 (TPM4), a kind of actin-binding proteins, was down-regulated by suppression of CCNY. F-actin assembly could be controlled by CCNYc as well as PFTK1 and TPM4. As a result, CCNY was mainly expressed in lung cancer. CCNYc could promote cell motility and invasion. It indicated that CCNYc/PFTK1 complex could promote cell metastasis by regulating the formation of F-actin via TPM4.

Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis.

BACKGROUND: Epithelial ovarian cancer (EOC), as a lethal malignancy in women, is often diagnosed as advanced stages. In contrast, intermediating between benign and malignant tumors, ovarian low malignant potential (LMP) tumors show a good prognosis. However, the differential diagnosis of the two diseases is not ideal, resulting in delays or unnecessary therapies. Therefore, unveiling the molecular differences between LMP and EOC may contribute to differential diagnosis and novel therapeutic and preventive policies development for EOC. METHODS: In this study, three microarray data (GSE9899, GSE57477 and GSE27651) were used to explore the differentially expressed genes (DEGs) between LMP and EOC samples. Then, 5 genes were screened by protein-protein interaction (PPI) network, receiver operating characteristic (ROC), survival and Pearson correlation analysis. Meanwhile, chemical-core gene network construction was performed to identify the potential drugs or risk factors for EOC based on 5 core genes. Finally, we also identified the potential function of the 5 genes for EOC through pathway analysis. RESULTS: Two hundred thirty-four DEGs were successfully screened, including 81 up-regulated genes and 153 down-regulated genes. Then, 5 core genes (CCNB1, KIF20A, ASPM, AURKA, and KIF23) were identified through PPI network analysis, ROC analysis, survival and Pearson correlation analysis, which show better diagnostic efficiency and higher prognostic value for EOC. Furthermore, NetworkAnalyst was used to identify top 15 chemicals that link with the 5 core genes. Among them, 11 chemicals were potential drugs and 4 chemicals were risk factors for EOC. Finally, we found that all 5 core genes mainly regulate EOC development via the cell cycle pathway by the bioinformatic analysis. CONCLUSION: Based on an integrated bioinformatic analysis, we identified potential biomarkers, risk factors and drugs for EOC, which may help to provide new ideas for EOC diagnosis, condition appraisal, prevention and treatment in future.

International trends in ovarian cancer incidence from 1973 to 2012.

PURPOSE: Ovarian cancer is the 7th leading cancer diagnosis and the 8th leading cause of cancer death in women worldwide. We conducted this study to investigate the incidence of ovarian cancer internationally. METHODS: The trends in ovarian cancer incidence were analyzed through the latest data of CI5 over the 40-year period from 21 populations in 4 continents using Joinpoint analysis, ASRs and proportions of different histological subtypes in those populations were also analyzed using volume XI of CI5. RESULTS: ASRs of ovarian cancer were from 7.0 to 11.6 per 100,000 in non-Asia populations during 2008-2012. In Asia, the ASR in Israel (Jews) were the highest, up to 8.1 per 100,000 in the same period. The international trends from 1973 to 2012 showed that ASRs of ovarian cancer were decreasing in 8 of 21 selected populations, whereas ASRs in Slovakia, Spain (Navarra) and China (Shanghai) were increasing. Meanwhile, there are certain differences in the main pathological classification patterns within different regions. In Asia, China (Hong Kong) and Japan both have a higher ASRs and proportions for clear cell and endometrioid carcinomas, while Japan has the highest ASRs and proportions for mucinous carcinomas. CONCLUSION: Although the reasons for those trends were not entirely clear, environmental, reproductive and genetic factors were likely to have led to these patterns. Meanwhile, more attention and further study should be given to the etiological factors of histology-specific ovarian cancer.

Non-invasive detection of hepatocellular carcinoma serum metabolic profile through surface-enhanced Raman spectroscopy.

The present study aims to identify distinctive Raman spectrum metabolic peaks to predict hepatocellular carcinoma (HCC). We performed a label-free, non-invasive surface-enhanced Raman spectroscopy (SERS) test on 230 serum samples including 47 HCC, 60 normal controls (NC), 68 breast cancer (BC) and 55 lung cancer (LC) by mixing Au@AgNRs with serum directly. Based on the observed SERS spectra, discriminative metabolites including tryptophan, phenylalanine, and etc. were found in HCC, when compared with BC, LC, and NC (P<0.05 in all). Common metabolites-proline, valine, adenine and thymine were found in HCC, BC and LC with compared to NC group (P<0.05). Importantly, Raman spectra of HCC serum biomarker AFP were firstly detected to analyze the HCC prominent peak. Orthogonal partial least squares discriminant analysis was adopted to assess the diagnostic accuracy; area under curve value of HCC is 0.991. This study provides new insights into the HCC metabolites detection through Raman spectroscopy.

Vitronectin: a promising breast cancer serum biomarker for early diagnosis of breast cancer in patients.

Breast cancer is the most common cancer in women worldwide, identification of new biomarkers for early diagnosis and detection will improve the clinical outcome of breast cancer patients. In the present study, we determined serum levels of vitronectin (VN) in 93 breast cancer patients, 30 benign breast lesions, 9 precancerous lesions, and 30 healthy individuals by enzyme-linked immunosorbent assays. Serum VN level was significantly higher in patients with stage 0-I primary breast cancer than in healthy individuals, patients with benign breast lesion or precancerous lesions, as well as those with breast cancer of higher stages. Serum VN level was significantly and negatively correlated with tumor size, lymph node status, and clinical stage (p < 0.05 in all cases). In addition, VN displayed higher area under curve (AUC) value (0.73, 95 % confidence interval (CI) [0.62-0.84]) than carcinoembryonic antigen (CEA) (0.64, 95 % CI [0.52-0.77]) and cancer antigen 15-3 (CA 15-3) (0.69, 95 % CI [0.58-0.81]) when used to distinguish stage 0-I cancer and normal control. Importantly, the combined use of three biomarkers yielded an improvement in receiver operating characteristic curve with an AUC of 0.83, 95 % CI [0.74-0.92]. Taken together, our current study showed for the first time that serum VN is a promising biomarker for early diagnosis of breast cancer when combined with CEA and CA15-3.