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Simple Summary Despite the importance of vaccination against Coronavirus disease 2019 (COVID-19) in cancer patients, general vaccine uptake rates among cancer patients are known to be low. Here, we tried to investigate the attitude and acceptance rates for COVID-19 vaccine in cancer patients and identify predictive factors for vaccination that could be modified to promote vaccine uptake rates. Between February and April 2021, a total of 1001 cancer patients from five institutions participated in a paper-based survey, consisting of 58 items over six domains. Among the respondents, 61.8% were willing to receive the COVID-19 vaccine. Along with the previously reported predictors for COVID-19 vaccination, including male gender, older age, and influenza vaccination history, we distinctively found that patient’s disease status and health status (absence of cancer recurrence, time since cancer diagnosis over 5 years, and higher EuroQol Visual Analogue Scale scores) were associated with higher acceptance rates of vaccination. Furthermore, physician’s recommendations effectively reduced patient’s vaccine hesitancy. Abstract Considering the high morbidity and mortality of Coronavirus disease 2019 (COVID-19) in patients with malignancy, they are regarded as a priority for COVID-19 vaccination. However, general vaccine uptake rates among cancer patients are known to be lower than in their healthy counterparts. Thus, we aimed to investigate the attitude and acceptance rates for the COVID-19 vaccine in cancer patients and identify predictive factors for vaccination that could be modified to increase vaccine uptake rates, via a paper-based survey (58 items over six domains). A total of 1001 cancer patients participated in this nationwide, multicenter survey between February and April 2021. We observed that 61.8% of respondents were willing to receive the COVID-19 vaccine. Positive predictive factors found to be independently associated with vaccination were male gender, older age, obesity, previous influenza vaccination history, absence of cancer recurrence, time since cancer diagnosis over 5 years, and higher EuroQol Visual Analogue Scale scores. Along with the well-known factors that are positively correlated with vaccination, here, we report that patients’ disease status and current health status were also associated with their acceptance of the COVID-19 vaccination. Moreover, 91.2% of cancer patients were willing to be vaccinated if their attending physicians recommend it, indicating that almost 30% could change their decision upon physicians’ recommendation. Unlike other factors, which are unmodifiable, physicians’ recommendation is the single modifiable factor that could change patients’ behavior. In conclusion, we firstly report that Korean cancer patients’ acceptance rate of the COVID-19 vaccination was 61.8% and associated with disease status and current health status. Physicians should play a major role in aiding cancer patients’ decision-making concerning COVID-19 vaccines.

Simple Summary An increased risk of relapse and death from minimally invasive radical hysterectomy has been reported in some patients with early cervical cancer. Thus, the development of an intuitive and precise decision-aid tool, which estimates recurrence and mortality rates by surgical approach, is necessary. To develop models predicting survival outcomes according to the surgical approach, we collected clinicopathologic and survival data of patients with 2009 FIGO stage IB cervical cancer who underwent a radical hysterectomy. Using only variables that could be obtained preoperatively, we developed various models predicting the probability of 5-year progression-free survival and overall survival. Among them, hybrid ensemble models, combined with logistic regression and multiple machine learning models, achieved the best predictive performance. The developed models are expected to help physicians’ and patients’ decision making related to the surgical approach for primary radical hysterectomy. Abstract We purposed to develop machine learning models predicting survival outcomes according to the surgical approach for radical hysterectomy (RH) in early cervical cancer. In total, 1056 patients with 2009 FIGO stage IB cervical cancer who underwent primary type C RH by either open or laparoscopic surgery were included in this multicenter retrospective study. The whole dataset consisting of patients’ clinicopathologic data was split into training and test sets with a 4:1 ratio. Using the training set, we developed models predicting the probability of 5-year progression-free survival (PFS) and overall survival (OS) with tenfold cross validation. The developed models were validated in the test set. In terms of predictive performance, we measured the area under the receiver operating characteristic curve (AUC) values. The logistic regression models comprised of preoperative variables yielded AUCs of 0.679 and 0.715 for predicting 5-year PFS and OS rates, respectively. Combining both logistic regression and multiple machine learning models, we constructed hybrid ensemble models, and these models showed much improved predictive performance, with 0.741 and 0.759 AUCs for predicting 5-year PFS and OS rates, respectively. We successfully developed models predicting disease recurrence and mortality after primary RH in patients with early cervical cancer. As the predicted value is calculated based on the preoperative factors, such as the surgical approach, these ensemble models would be useful for making decisions when choosing between open or laparoscopic RH.

We aimed to develop a diagnostic model identifying ovarian cancer (OC) from benign ovarian tumors using metagenomic data from serum microbe-derived extracellular vesicles (EVs). We obtained serum samples from 166 patients with pathologically confirmed OC and 76 patients with benign ovarian tumors. For model construction and validation, samples were randomly divided into training and test sets in the ratio 2:1. Isolation of microbial EVs from serum samples of the patients and 16S rDNA amplicon sequencing were carried out. Metagenomic and clinicopathologic data-based OC diagnostic models were constructed in the training set and then validated in the test set. There were significant differences in the metagenomic profiles between the OC and benign ovarian tumor groups, specifically, genus Acinetobacter was significantly more abundant in the OC group. More importantly, Acinetobacter was the only common genus identified by seven different statistical analysis methods. Among the various metagenomic and clinicopathologic data-based OC diagnostic models, the model consisting of age, serum CA-125 levels, and relative abundance of Acinetobacter showed the best diagnostic performance with the area under the receiver operating characteristic curve of 0.898 and 0.846 in the training and test sets, respectively. Thus, our findings establish a metagenomic analysis of serum microbe-derived EVs as a potential tool for the diagnosis of OC.

Initial identification of biomarkers predicting the exact prognosis of high-grade serous ovarian carcinoma (HGSOC) is important in precision cancer medicine. This study aimed to investigate prognostic biomarkers of HGSOC through proteomic analysis. We conducted label-free liquid chromatography-mass spectrometry using chemotherapy-na&iuml, ve, fresh-frozen primary HGSOC specimens, and compared the results between a favorable prognosis group (progression-free survival (PFS) &ge, 18 months, n = 6) and a poor prognosis group (PFS &lt, 18 months, n = 6). Among 658 differentially expressed proteins, 288 proteins were upregulated in the favorable prognosis group and 370 proteins were upregulated in the poor prognosis group. Using hierarchical clustering, we selected &alpha, 1-antitrypsin (AAT), nuclear factor-&kappa, B (NFKB), phosphomevalonate kinase (PMVK), vascular adhesion protein 1 (VAP1), fatty acid-binding protein 4 (FABP4), platelet factor 4 (PF4), apolipoprotein A1 (APOA1), and &alpha, 1-acid glycoprotein (AGP) for further validation via immunohistochemical (IHC) staining in an independent set of chemotherapy-na&iuml, ve primary HGSOC samples (n = 107). Survival analyses revealed that high expression of AAT, NFKB, and PMVK were independent biomarkers for favorable PFS. Conversely, high expression of VAP1, FABP4, and PF4 were identified as independent biomarkers for poor PFS. Furthermore, we constructed models predicting the 18-month PFS by combining clinical variables and IHC results. Through leave-one-out cross-validation, the optimal model was based on initial serum CA-125, germline BRCA1/2 mutations, residual tumors after surgery, International Federation of Gynecology and Obstetrics (FIGO) stage, and expression levels of the six proteins. The present results elucidate the proteomic landscape of HGSOC and six protein biomarkers to predict the prognosis of HGSOC.

In human epithelial ovarian cancer (EOC), various miRNAs can function as either oncogenes or tumor suppressor genes. We investigated miRNAs known to be involved in EOC progression and analyzed their expression in tissues and serum-derived exosomes from benign serous cystadenoma, borderline serous tumor, low-grade serous ovarian cancer, and high-grade serous ovarian cancer patients (HGSO). The HGSO group was divided based on the platinum-free interval, which is defined as the duration from the completion of platinum-based chemotherapy to recurrence. We also analyzed the mRNA levels of target genes that candidate miRNAs might regulate in patient tissues. miR-214-3p was highly expressed in tissues and exosomes derived from EOC with high malignancy and also found to regulate the expression of LIM homeobox domain 6 (LHX6) mRNA. Serum exosomal levels of miR-214-3p were significantly increased in platinum-resistant HGSO (25.2-fold, p &lt, 0.001) compared to the exosomal expression of benign tumor patients. On transfection of miR-214-3p inhibitor in EOC cells, cell proliferation was inhibited while apoptotic cell death was increased. Collectively, we suggest that miR-214-3p in serum exosomes can be a potential biomarker for the diagnosis and prognosis of ovarian tumor, and its inhibition can be a supportive treatment for EOC.

Simple Summary Hexokinase II (HKII) is a key glycolysis enzyme associated with tumorigenesis, but its molecular mechanism and pathophysiological role in chemoresistant ovarian cancer remain elusive. In this study, we delineate the novel mechanism showing that activated phosphorylated-p53 (P-p53 Ser15) is required for the regulation of HKII intracellular trafficking and metabolic regulation in chemosensitive ovarian cancer, but not in chemoresistant ovarian cancer harboring p53 mutation. We have observed that increased nuclear HKII-P-p53 (Ser15) interaction is likely associated with chemosensitivity and better survival outcomes in epithelial ovarian cell lines, human primary epithelial ovarian cancer cells, and tumor sections. Nuclear HKII-P-p53 (Ser15) interaction may function as a promising prognostic biomarker, enabling prediction of patients with poor prognosis for deciding better clinical strategies. Abstract In epithelial ovarian cancer (EOC), carboplatin/cisplatin-induced chemoresistance is a major hurdle to successful treatment. Aerobic glycolysis is a common characteristic of cancer. However, the role of glycolytic metabolism in chemoresistance and its impact on clinical outcomes in EOC are not clear. Here, we show a functional interaction between the key glycolytic enzyme hexokinase II (HKII) and activated P-p53 (Ser15) in the regulation of bioenergetics and chemosensitivity. Using translational approaches with proximity ligation assessment in cancer cells and human EOC tumor sections, we showed that nuclear HKII-P-p53 (Ser15) interaction is increased after chemotherapy, and functions as a determinant of chemoresponsiveness as a prognostic biomarker. We also demonstrated that p53 is required for the intracellular nuclear HKII trafficking in the control of glycolysis in EOC, associated with chemosensitivity. Mechanistically, cisplatin-induced P-p53 (Ser15) recruits HKII and apoptosis-inducing factor (AIF) in chemosensitive EOC cells, enabling their translocation from the mitochondria to the nucleus, eliciting AIF-induced apoptosis. Conversely, in p53-defective chemoresistant EOC cells, HKII and AIF are strongly bound in the mitochondria and, therefore, apoptosis is suppressed. Collectively, our findings implicate nuclear HKII-P-p53(Ser15) interaction in chemosensitivity and could provide an effective clinical strategy as a promising biomarker during platinum-based therapy.

This study aimed to investigate the impact of sarcopenia and body composition on survival outcomes in Korean patients with advanced-stage high-grade serous ovarian carcinoma (HGSOC). We retrospectively identified patients diagnosed with and treated for International Federation of Gynecology and Obstetrics stage III-IV HGSOC. Skeletal muscle index (SMI) was measured using pre-treatment computed tomography scans at the third lumbar vertebra. Sarcopenia was defined as SMI &lt, 39.0 cm2/m2. Patients&rsquo, clinicopathologic characteristics and survival outcomes were compared according to sarcopenia presence. For subgroup analysis, we also measured the total fat area from the same image. In total, 76 and 103 patients were assigned to the sarcopenia and control groups, respectively. Comorbidities, stage, serum CA-125 levels, and size of residual tumor after surgery were similar between both groups. After a median follow up of 42.7 months, both groups showed similar progression-free survival (PFS) and overall survival (OS). In subgroup analysis confined to the sarcopenia group, patients with high fat-to-muscle ratio (FMR, &ge, 2.1, n = 38) showed significantly worse OS than those with low FMR (&lt, 2.1, n = 38) (5-year survival rate, 44.7% vs. 80.0%, p = 0.046), whereas PFS was not different (p = 0.365). Multivariate analyses identified high FMR as an independent poor prognostic factor for OS in this group (adjusted hazard ratio, 3.377, 95% confidence interval, 1.1709.752, p = 0.024). In conclusion, sarcopenia did not influence recurrence rates and survival in Korean patients with advanced-stage HGSOC. However, among the patients with sarcopenia, high FMR was associated with decreased OS.