Identification of a prognostic model based on immune and hypoxia-related gene expressions in cervical cancer.

BACKGROUND: Tumour immune microenvironment (TIME) has long been a key direction of tumour research. Understanding the occurrence, metastasis and other processes of cervical cancer (CC) is of great significance in the diagnosis and prognosis of tumours. METHODS: Here, this study applied the univariate Cox regression model to determine the prognostic association of immune and hypoxia signature genes in CC, and used Least Absolute Shrinkage and Selection Operator (LASSO) Cox method to build immune and hypoxia related risk score model to uncover the immune signature of the TIME of CC. Moreover, we used in vitro experiment to validate the expression level of signature genes. Notably, we assessed the predictive effect of anti-PD1/PDL1 immunotherapy using risk score model. RESULTS: Through the LASSO Cox regression model, we obtained 12 characteristic genes associated with the prognosis of CC, and also associated with immunity and hypoxia. Interestingly, the high-risk group had the properties of high hypoxia and low immunity, while the low-risk group had the properties of low hypoxia and high immunity. In the low-risk group, patients lived longer and had a significant therapeutic advantage of anti-PD-1 immunotherapy. CONCLUSIONS: Established risk scores model can help predict response to anti-PD-1 immunotherapy of CC.

The survival rate of cervical cancer (CC) is still low. A prognostic model for CC is urgently needed to improve the prognosis and survival. This study constructed a risk scoring models based on 12 characteristic gene related to hypoxia and immunity, including CX3CL1, CXCL3, GHSR, DLL4, FGFR2, PDF, KLRK1, MAP3K14, RETNLB, PRDX2, P4HA1 and PGK1, which can help predict the prognosis of PD-1 immunotherapy in CC patients. The high-risk group may have the properties of high hypoxia and low immunity, while the low-risk group patients live longer and have obvious therapeutic advantages in anti-PD-1 immunotherapy. Our findings suggest a potential link between hypoxia, immunity, prognosis, tumour immune microenvironment and response to immunotherapy in CC patients.

Alteration of vaginal microbiota in patients with recurrent miscarriage.

The aim of this study was to characterise the structure of vaginal microbiota in unexplained recurrent miscarriage (RM). The vaginal bacterial communities of 16 patients with RM and 20 healthy volunteers were sampled. Then, the microbiomes of bacterial profiles of RM patients and healthy volunteers were compared by sequencing the V3-V4 regions of the bacterial 16S ribosomal RNA gene using the Illumina MiSeq platform (Illumina, San Diego, CA). Taxonomic analysis demonstrated that abundance of Lactobacillus and Gardnerella were significantly different between the RM and control groups. Furthermore, at the genus level, Lactobacillus was the most dominant genus in the two groups. Statistically significant differences were observed in three genera between RM and control groups. In the control group, two bacterial taxa were significantly more abundant (Lactobacillus and Gardnerella), while only one taxon was overrepresented in the RM group (Atopobium). These present findings provide experimental evidence supporting vaginal microbiota dysbiosis in women with RM.Impact statementWhat is already known on this subject? Currently, bacterial vaginosis is thought to be mainly due to the vaginal dysbacteriosis, which can induce unexplained recurrent miscarriage, premature rupture of membranes, low birth weight premature birth, premature birth, chorioamnionitis and series of diseases.What do the results of this study add? The current study demonstrated that Lactobacillus and Gardnerella were significantly decreased in RM patients compared to healthy control, while Atopobium was overrepresented in the RM group.What are the implications of these findings for clinical practice and/or further research? Clinically, women with RM might benefit from vaginal microbiota treatment, adjuvant therapy with Lactobacillus-based live biotherapeutics.