(1) Background: Biomarkers might play a significant role in predicting the clinical outcomes of patients with ovarian cancer. By analyzing lipid metabolism genes, future perspectives may be uncovered; (2) Methods: RNA-seq data for serous ovarian cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The non-negative matrix factorization package in programming language R was used to classify molecular subtypes of lipid metabolism genes and the limma package in R was performed for functional enrichment analysis. Through lasso regression, we constructed a multi-gene prognosis model; (3) Results: Two molecular subtypes were obtained and an 11-gene signature was constructed (PI3, RGS, ADORA3, CH25H, CCDC80, PTGER3, MATK, KLRB1, CCL19, CXCL9 and CXCL10). Our prognostic model shows a good independent prognostic ability in ovarian cancer. In a nomogram, the predictive efficiency was notably superior to that of traditional clinical features. Related to known models in ovarian cancer with a comparable amount of genes, ours has the highest concordance index; (4) Conclusions: We propose an 11-gene signature prognosis prediction model based on lipid metabolism genes in serous ovarian cancer.

Respiratory distress syndrome (RDS) is the most frequent pulmonary complication in preterm infants. RDS incidence differs between genders, which has been called the male disadvantage. Besides maturation of the surfactant system, Na⁺ transport driven alveolar fluid clearance is crucial for the prevention of RDS. Na⁺ transport is mediated by the epithelial Na⁺ channel (ENaC) and the Na,K-ATPase, therefore potential differences in their expression or activity possibly contribute to the gender imbalance observed in RDS. Fetal distal lung epithelial (FDLE) cells of rat fetuses were separated by sex and analyzed regarding expression and activity of the Na⁺ transporters. Ussing chamber experiments showed a higher baseline short-circuit current (I_SC) and amiloride-sensitive ΔI_SC in FDLE cells of female origin. In addition, maximal amiloride-sensitive ΔI_SC and maximal ouabain-sensitive ΔI_SC of female cells were higher when measured in the presence of a permeabilized basolateral or apical membrane, respectively. The number of FDLE cells per fetus recoverable during cell isolation was also significantly higher in females. In addition, lung wet-to-dry weight ratio was lower in fetal and newborn female pups. Female derived FDLE cells had higher mRNA levels of the ENaC- and Na,K-ATPase subunits. Furthermore, estrogen (ER) and progesterone receptor (PR) mRNA levels were higher in female cells, which might render female cells more responsive, while concentrations of placenta-derived sex steroids do not differ between both genders during fetal life. Inhibition of ER-β abolished the sex differences in Na⁺ transport and female cells were more responsive to estradiol stimulation. In conclusion, a higher alveolar Na⁺ transport, possibly attributable to a higher expression of hormone receptors in female FDLE cells, provides an explanation for the well known sex-related difference in RDS occurrence and outcome.

(1) Background: The tumor microenvironment is involved in the growth and proliferation of malignant tumors and in the process of resistance towards systemic and targeted therapies. A correlation between the gene expression profile of the tumor microenvironment and the prognosis of ovarian cancer patients is already known. (2) Methods: Based on data from The Cancer Genome Atlas (379 RNA sequencing samples), we constructed a prognostic 11-gene signature (SNRPA1, CCL19, CXCL11, CDC5L, APCDD1, LPAR2, PI3, PLEKHF1, CCDC80, CPXM1 and CTAG2) for Fédération Internationale de Gynécologie et d’Obstétrique stage III and IV serous ovarian cancer through lasso regression. (3) Results: The established risk score was able to predict the 1-, 3- and 5-year prognoses more accurately than previously known models. (4) Conclusions: We were able to confirm the predictive power of this model when we applied it to cervical and urothelial cancer, supporting its pan-cancer usability. We found that immune checkpoint genes correlate negatively with a higher risk score. Based on this information, we used our risk score to predict the biological response of cancer samples to an anti-programmed death ligand 1 immunotherapy, which could be useful for future clinical studies on immunotherapy in ovarian cancer.

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.

The side effects of systemic cancer therapy and the lack of clinical data on safety and efficacy of COVID-19 vaccination in cancer patients cause uncertainty among the patients about whether to get vaccinated or not. Here, we evaluated attitude towards and effects of COVID-19 vaccination in patients with breast and gynecological cancer undergoing systemic cancer therapy. Since March 15th, 2021, cancer patients who received one of the approved COVID-19 vaccines were routinely interviewed about immediate and late side effects. Clinical parameters such as current therapy, time interval between therapy administration and vaccination, and changes in the therapy schedule due to vaccination were documented. The collected data were analyzed de-identified as a part of routine quality assurance. By July 27th, 2021, 218 patients (74.3% breast cancer patients) had received one of two COVID-19 vaccine doses, and 112 patients had received both doses: 77.5% received Conmirnaty (BioNTech/Pfizer), 16.1% Vaxzevria (Astra Zeneca) and 5.9% COVID-19 Vaccine Moderna. The COVID-19 vaccines had an acceptable safety profile with self-limiting local and systemic adverse events, which rarely lasted >48 h post vaccination. Symptoms occurred predominantly after the second dose of the vaccine and less frequently in older patients >55 years. No vaccine-related serious adverse events were reported, and only limited effects of vaccination on the therapy schedule were observed. Breast and gynecologic cancer patients tolerate the COVID-19 vaccination while undergoing systemic cancer therapy without any additional side effects beyond those reported in the general population.

Purpose: With the beginning of 2021, the world has been suffering from the COVID-19 pandemic for more than 1 year. More and more, we are able to evaluate side effects of the pandemic in the healthcare sector. A negative impact on cancer diagnoses is one of them. Careful observation of trends in an academic gyneco-oncological context appears important to identify potential negative developments. Methods: We analyzed the case number of gynecologic and breast cancer diagnoses in the period from January to June 2020 compared to 2019 and during the period of the first general German lockdown (March 22nd until May 5th 2020). Patients were characterized by age, tumor type, FIGO or TNM stage and presence of symptoms at initial hospital presentation. Results: The frequency of newly diagnosed gynecologic and breast cancer cases from beginning of January until end of June changed by − 10% and by − 12% during the lockdown in 2020 compared to 2019. In both periods, reduction of breast cancer cases was relatively larger than decrease of gynecologic cancers. Moreover, median patient age decreased. For the first half of 2020, we found a shift towards higher tumor stages (N+/M1 or FIGO III–IV). During the lockdown period, the appearance of tumor-associated symptoms at diagnosis increased by about 12%. Conclusion: This analysis illustrates the anticipated general decrease in diagnoses of primary cancers during the lockdown periods in 2020 due to COVID-19 pandemic for gynecologic and breast cancer cases.