BackgroundHigh grade serous ovarian cancer (HGSOC) is the most common subtype of ovarian cancer. Although platinum-based chemotherapy has been the cornerstone for HGSOC treatment, nearly 25% of patients would have less than 6 months of interval since the last platinum chemotherapy, referred to as platinum-resistance. Currently, no precise tools to predict platinum resistance have been developed yet.MethodsNinety-nine HGSOC patients, who have finished cytoreductive surgery and platinum-based chemotherapy in Peking University Third Hospital from 2018 to 2019, were enrolled. Whole-genome sequencing (WGS) and whole-exome sequencing (WES) were performed on the collected tumor tissue samples to establish a platinum-resistance predictor in a discovery cohort of 57 patients, and further validated in another 42 HGSOC patients.ResultsA high prevalence of alterations in DNA damage repair (DDR) pathway, including BRCA1/2, was identified both in the platinum-sensitive and resistant HGSOC patients. Compared with the resistant subgroup, there was a trend of higher prevalence of homologous recombination deficiency (HRD) in the platinum-sensitive subgroup (78.95% vs. 47.37%, p=0.0646). Based on the HRD score, microhomology insertions and deletions (MHID), copy number changes load, duplication load of 1–100 kb, single nucleotide variants load, and eight other mutational signatures, a combined predictor of platinum-resistance, named as DRDscore, was established. DRDscore outperformed in predicting the platinum-sensitivity than the previously reported biomarkers with a predictive accuracy of 0.860 at a threshold of 0.7584. The predictive performance of DRDscore was validated in an independent cohort of 42 HGSOC patients with a sensitivity of 90.9%.ConclusionsA multi-genomic signature-based analysis enabled the prediction of initial platinum resistance in advanced HGSOC patients, which may serve as a novel assessment of platinum resistance, provide therapeutic guidance, and merit further validation.

Objective: DUSP6 is a negative regulator of the ERK signaling pathway and plays an important role in chemotherapy-resistance. Previously we showed that DUSP6 is overexpressed in ovarian cancer side population (SP) cells that possess cancer stem cell-like properties and are quiescent and chemotherapy-resistant. Here, we explore the effects of DUSP6 on chemotherapy-resistance by examining its regulation of the ERK signaling pathway and G0/G1 cell cycle arrest. Methods: mRNA and protein expression of DUSP6 and G0/G1 cell cycle checkpoint regulating proteins (CyclinD1, CyclinD3 and CyclinE2) was evaluated among ovarian cancer cell lines and tissue samples. Ovarian cancer cells were transiently transfected to overexpress DUSP6. After treatment with cisplatin, cell viability was measured by the MTS assay at 48 hours and the half maximal inhibitory concentration (IC50) for each cell line was calculated. Subcellular localization and cell cycle analysis were determined by using immunofluorescence and FACS, respectively. Results: SKOV3 and OVCAR8 SP cells were shown to express higher levels of DUSP6 and lower levels of CyclinD3 compared with non-SP (NSP) cells (P<0.001). Among 39 ovarian cancer tissue samples, expression of DUSP6 in the chemotherapy-resistant group (12 samples) was higher than in the chemotherapy-sensitive group (27 samples) (P<0.05). While a lower level of expression of CyclinD3 was seen in the chemotherapy-resistant group, it was not statistically different from the chemotherapy-sensitive group. HO8910 cells where shown to have higher IC50 to cisplatin than SKOV3 or OVCAR8 cells, and this correlated with higher levels of DUSP6 expression. Overexpression of DUSP6 in SKOV3 cells led to an increase in cisplatin IC50 values (P<0.05), and also markedly reduced the expression levels of phospho-ERK1/2 and CyclinD3 and to the predominance of cells in the G0/G1 phase. Conclusion: Our findings reveal an enhancement of chemotherapy-resistance and a predominance of cells in G1 cell cycle arrest in DUSP6-overexpressing ovarian cancer cells. This suggests that overexpression of DUSP6 promotes chemotherapy-resistance through the negative regulation of the ERK signaling pathway, increasing the G0/G1 phase ratio among ovarian cancer cells, and leading to cellular quiescence.

Objective Emerging studies have demonstrated the promising clinical value of circulating tumor cells (CTCs) for diagnosis, disease assessment, treatment monitoring and prognosis in epithelial ovarian cancer. However, the clinical application of CTC remains restricted due to diverse detection techniques with variable sensitivity and specificity and a lack of common standards. Methods We enrolled 160 patients with epithelial ovarian cancer as the experimental group, and 90 patients including 50 patients with benign ovarian tumor and 40 healthy females as the control group. We enriched CTCs with immunomagnetic beads targeting two epithelial cell surface antigens (EpCAM and MUC1), and used multiple reverse transcription-polymerase chain reaction (RT-PCR) detecting three markers (EpCAM, MUC1 and WT1) for quantification. And then we used a binary logistic regression analysis and focused on EpCAM, MUC1 and WT1 to establish an optimized CTC detection model. Results The sensitivity and specificity of the optimized model is 79.4% and 92.2%, respectively. The specificity of the CTC detection model is significantly higher than CA125 (92.2% vs . 82.2%, P=0.044), and the detection rate of CTCs was higher than the positive rate of CA125 (74.5% vs. 58.2%, P=0.069) in early-stage patients (stage I and II). The detection rate of CTCs was significantly higher in patients with ascitic volume ≥500 mL, suboptimal cytoreductive surgery and elevated serum CA125 level after 2 courses of chemotherapy (P<0.05). The detection rate of CTC EpCAM + and CTC MUC1+ was significantly higher in chemo-resistant patients (26.3% vs . 11.9%; 26.4% vs . 13.4%, P<0.05). The median progression-free survival time for CTC MUC1+ patients trended to be longer than CTC MUC1− patients, and overall survival was shorter in CTC MUC1+ patients (P=0.043). Conclusions Our study presents an optimized detection model for CTCs, which consists of the expression levels of three markers (EpCAM, MUC1 and WT1). In comparison with CA125, our model has high specificity and demonstrates better diagnostic values, especially for early-stage ovarian cancer. Detection of CTC EpCAM+ and CTC MUC1+ had predictive value for chemotherapy resistance, and the detection of CTC MUC1+ suggested poor prognosis.

Changes in glacier resources and their meltwater runoff contributions in Xinjiang are significant to the hydrological processes and water resources utilization. This study used the first and second Chinese Glacier Inventory, geomorphological and meteorological data. GIS spatial analysis technology was used to explore the characteristics of glacier change and its response to topography and climate change in Xinjiang in the last 50 years. The results show that there are currently 20,695 glaciers in Xinjiang with a total area of 22,742.55 km2 and ice reserves of about 2229.17 km3. Glaciers in Xinjiang are concentrated at 5100–6000 m. The Tianshan mountains have the largest number of glaciers. However, the Kunlun mountains have the largest glaciers and ice reserves. The scale of glaciers is significantly larger in the south than that in the north. The changes in glaciers in Xinjiang during the last 50 years are mainly receding and splitting, and their number, area, and ice reserves have decreased by 13,597,080.12 km2 and 482.65 km3, respectively. Small glaciers are more sensitive to climate change. Glaciers are basically unchanged in regions above 6000 m. The glaciers on the south slope of mountains are more susceptible to climate change. The phenomenon of an increase in the number of glaciers but decreasing total area in the southern mountains is related to glacier extinction and splitting. Glacier development and formation are determined by the combination of topography and hydrothermal material conditions. The change of glacier areas in Xinjiang is jointly affected by climatic conditions (53.45%) and topographic conditions (46.55%), among which climatic conditions are more prominent.

Research on the spatio-temporal correlation between the intensity of human activities and the temperature of earth surfaces is of great significance in many aspects, including fully understanding the causes and mechanisms of climate change, actively adapting to climate change, pursuing rational development, and protecting the ecological environment. Taking the north slope of Tianshan Mountains, located in the arid area of northwestern China and extremely sensitive to climate change, as the research area, this study retrieves the surface temperature of the mountain based on MODIS data, while characterizing the intensity of human activities thereby data on the night light, population distribution and land use. The evolution characteristics of human activity intensity and surface temperature in the study area from 2000 to 2018 were analyzed, and the spatio-temporal correlation between them was further explored. It is found that: (1) The average human activity intensity (0.11) in the research area has kept relatively low since this century, and the overall trend has been slowly rising in a stepwise manner (0.0024•a -1 ); in addition, the increase in human activity intensity has lagged behind that in construction land and population by 1-2 years. (2) The annual average surface temperature in the area is 7.18 ℃ with a pronounced growth. The rate of change (0.02 ℃•a -1 ) is about 2.33 times that of the world. The striking boost in spring (0.068 ℃•a -1 ) contributes the most to the overall warming trend. Spatially, the surface temperature is low in the south and high in the north, due to the prominent influence of the underlying surface characteristics, such as elevation and vegetation coverage. (3) The intensity of human activity and the surface temperature are remarkably positively correlated in the human activity areas there, showing a strong distribution in the east section and a weak one in the west section. The expression of its spatial differentiation and correlation is comprehensively affected by such factors as scopes of human activities, manifestations, and