Anti-cancer effects of benzimidazole derivative BNZ-111 on paclitaxel-resistant ovarian cancer.

OBJECTIVE: Ovarian cancer, a leading cause of cancer-related deaths in women, remains a formidable challenge, especially in the context of platinum-resistant disease. This study investigated the potential of the benzimidazole derivative BNZ-111 as a novel treatment strategy for platinum-resistant ovarian cancer. METHODS: The human EOC cell lines A2780, HeyA8, SKOV3ip1, A2780-CP20, HeyA8-MDR, and SKOV3-TR were treated with BNZ-111, and cell proliferation, apoptosis, and cell cycle were assessed. RESULTS: It demonstrated strong cytotoxicity in both chemo-sensitive and chemo-resistant epithelial ovarian cancer cell lines, inducing apoptosis and G2/M cell cycle arrest. In vivo experiments using orthotopic and patient-derived xenograft models showed significant tumor growth inhibition without apparent toxicity to vital organs. Unlike paclitaxel, BNZ-111 proved effective in paclitaxel-resistant cells, potentially by bypassing interaction with MDR1 and modulating ß-3 tubulin expression to suppress microtubule dynamics. CONCLUSION: BNZ-111, with favorable drug-like properties, holds promise as a therapeutic option for platinum-resistant ovarian cancer, addressing a critical clinical need in gynecologic oncology.

Evaluating the effect of a mobile-based symptom monitoring system for improving physical function in patients with cancer during chemotherapy: study protocol for a multicentre randomised controlled trial.

INTRODUCTION: Symptoms due to chemotherapy are common in patients with cancer. Cancer-related symptoms are closely associated with the deterioration of physical function which can be associated with decreased quality of life and increased mortality. Thus, timely symptom identification is critical for improving cancer prognosis and survival. Recently, remote symptom monitoring system using digital technology has demonstrated its effects on symptom control or survival. However, few studies examined whether remote monitoring would contribute to retaining physical function among patients with cancer. Therefore, this study aimed to evaluate the effectiveness of mobile-based symptom monitoring in improving physical function among patients with cancer under chemotherapy. METHODS AND ANALYSIS: This study is a multicentre, open-label, parallel-group, randomised controlled trial. We will recruit 372 patients at three tertiary hospitals located in Seoul, South Korea. Study participants will be randomly assigned to either an intervention group receiving the ePRO-CTCAE app and a control group receiving routine clinical practice only. The primary outcome is changes in physical function from commencement to completion of planned chemotherapy. A linear mixed model will be performed under the intention-to-treat principle. The secondary outcomes include physical activity level; changes in pain interference; changes in depressive symptom; unplanned clinical visits; additional medical expenditure for symptom management; completion rate of planned chemotherapy; changes in symptom burden and health-related quality of life; and 1-year overall mortality. ETHICS AND DISSEMINATION: The study has been approved by the institutional review board and ethics committee at the three university hospitals involved in this trial. Written informed consent will be obtained from all the participants. The results of the trial will be submitted for publication in peer-reviewed academic journals and disseminated through relevant literatures. TRIAL REGISTRATION NUMBER: KCT0007220.

Psychometric validation of the Functional Assessment of Cancer Therapy-Endometrial among endometrial cancer patients.

OBJECTIVE: To evaluate a psychometric validation of the endometrial cancer subscales (EnCS) in the Functional Assessment of Cancer Therapy-Endometrial (FACT-EN) among patients with endometrial cancer. METHODS: This cross-sectional study was conducted at a tertiary university-based hospital in South Korea between April and October 2022. Participants completed a survey questionnaire that included the FACT-EN. Exploratory and confirmatory factor analyses (EFA, CFA) and the reliability were measured using the intraclass correlation coefficient (ICC) under a two-way mixed model. Pearson's correlations were used to evaluate the validity. We also tested known-group validity. RESULTS: In total, 240 patients with endometrial cancer participated in the survey. In EFA, we found EnCS included four domains. In CFA, four-factor solution model was good: CFI = 0.659; SRMR = 0.066, and RMSEA = 0.073. The mean (SD) of total score of FACT-EN was 122.84 (23.58). The floor and ceiling effects were 0.4% and 0.4%, respectively. Cronbach's α coefficients for the five scales of the EnCS ranged from 0.78 to 0.91. The ICC of EnCS was 0.76. The convergent and discriminant validity of EnCS was acceptable. In the group analysis, older age and lower ECOG performance scores were associated with higher EnCS scores. The stomach and vaginal domains in EnCS were higher in patients who had completed treatment for more than 1 year compared to those who were still undergoing treatment. CONCLUSIONS: FACT-EN has demonstrated its validity as an assessment tool with significant implications for capturing various symptoms in patients with endometrial cancer.

Comparison of RNA-Seq and microarray in the prediction of protein expression and survival prediction.

Gene expression profiling using RNA-sequencing (RNA-seq) and microarray technologies is widely used in cancer research to identify biomarkers for clinical endpoint prediction. We compared the performance of these two methods in predicting protein expression and clinical endpoints using The Cancer Genome Atlas (TCGA) datasets of lung cancer, colorectal cancer, renal cancer, breast cancer, endometrial cancer, and ovarian cancer. We calculated the correlation coefficients between gene expression measured by RNA-seq or microarray and protein expression measured by reverse phase protein array (RPPA). In addition, after selecting the top 103 survival-related genes, we compared the random forest survival prediction model performance across test platforms and cancer types. Both RNA-seq and microarray data were retrieved from TCGA dataset. Most genes showed similar correlation coefficients between RNA-seq and microarray, but 16 genes exhibited significant differences between the two methods. The BAX gene was recurrently found in colorectal cancer, renal cancer, and ovarian cancer, and the PIK3CA gene belonged to renal cancer and breast cancer. Furthermore, the survival prediction model using microarray was better than the RNA-seq model in colorectal cancer, renal cancer, and lung cancer, but the RNA-seq model was better in ovarian and endometrial cancer. Our results showed good correlation between mRNA levels and protein measured by RPPA. While RNA-seq and microarray performance were similar, some genes showed differences, and further clinical significance should be evaluated. Additionally, our survival prediction model results were controversial.

Depleting myeloid-biased haematopoietic stem cells rejuvenates aged immunity.

Ageing of the immune system is characterized by decreased lymphopoiesis and adaptive immunity, and increased inflammation and myeloid pathologies1,2. Age-related changes in populations of self-renewing haematopoietic stem cells (HSCs) are thought to underlie these phenomena3. During youth, HSCs with balanced output of lymphoid and myeloid cells (bal-HSCs) predominate over HSCs with myeloid-biased output (my-HSCs), thereby promoting the lymphopoiesis required for initiating adaptive immune responses, while limiting the production of myeloid cells, which can be pro-inflammatory4. Ageing is associated with increased proportions of my-HSCs, resulting in decreased lymphopoiesis and increased myelopoiesis3,5,6. Transfer of bal-HSCs results in abundant lymphoid and myeloid cells, a stable phenotype that is retained after secondary transfer; my-HSCs also retain their patterns of production after secondary transfer5. The origin and potential interconversion of these two subsets is still unclear. If they are separate subsets postnatally, it might be possible to reverse the ageing phenotype by eliminating my-HSCs in aged mice. Here we demonstrate that antibody-mediated depletion of my-HSCs in aged mice restores characteristic features of a more youthful immune system, including increasing common lymphocyte progenitors, naive T cells and B cells, while decreasing age-related markers of immune decline. Depletion of my-HSCs in aged mice improves primary and secondary adaptive immune responses to viral infection. These findings may have relevance to the understanding and intervention of diseases exacerbated or caused by dominance of the haematopoietic system by my-HSCs.

Major clinical research advances in gynecologic cancer in 2023: a tumultuous year for endometrial cancer.

In the 2023 series, we summarized the major clinical research advances in gynecologic oncology based on communications at the conference of Asian Society of Gynecologic Oncology Review Course. The review consisted of 1) Endometrial cancer: immune checkpoint inhibitor, antibody drug conjugates (ADCs), selective inhibitor of nuclear export, CDK4/6 inhibitors WEE1 inhibitor, poly (ADP-ribose) polymerase (PARP) inhibitors. 2) Cervical cancer: surgery in low-risk early-stage cervical cancer, therapy for locally advanced stage and advanced, metastatic, or recurrent setting; and 3) Ovarian cancer: immunotherapy, triplet therapies using immune checkpoint inhibitors along with antiangiogenic agents and PARP inhibitors, and ADCs. In 2023, the field of endometrial cancer treatment witnessed a landmark year, marked by several practice-changing outcomes with immune checkpoint inhibitors and the reliable efficacy of PARP inhibitors and ADCs.

Initial experience with the enhanced recovery after surgery (ERAS) protocols in gynecologic surgery at an urban academic tertiary medical center.

Background: The enhanced recovery after surgery (ERAS) protocols have been consistently associated with improved patient experience and surgical outcomes. Despite the release of ERAS Society guidelines specific to gynecologic oncology, the adoption of ERAS in gynecology on global level has been disappointingly low and some centers have shown minimal improvement in clinical outcomes after adopting ERAS. The aim of this study is to describe the development and early experience of ERAS protocols in gynecologic surgery at an urban academic tertiary medical center. Methods: This was an observational prospective cohort study. The target patient population included those with low comorbidities who were scheduled to undergo various types of gynecologic surgeries for both benign and malignant diseases between October 2020 and February 2021. Two attending surgeons implemented the protocols for their patients (ERAS cohort) while three attending surgeons maintained the conventional perioperative care for their patients (non-ERAS cohort). Baseline characteristics, surgical outcomes and patients' answers to a 12-question survey were compared. A case-matched comparative analysis was also performed between the ERAS cohort and the historical non-ERAS cohort (those who received the same types of surgical procedures from the two ERAS attending surgeons prior to the implementation of the protocols). Results: A total of 244 patients were evaluated (122 in the ERAS cohort vs. 122 in the non-ERAS cohort). The number of vials of opioid analgesia used during the first two postoperative days was significantly lower whereas the use of nonsteroidal anti-inflammatory drugs (NSAIDs) and acetaminophen was more frequent in the ERAS cohort group. The patients in the ERAS group reported less postoperative pain, feelings of hunger and thirst, and greater amount of exercise postoperatively. These benefits of the ERAS cohort were more pronounced in the patients who underwent laparotomic surgeries than those who underwent laparoscopic surgeries. The case-matched comparative analysis also showed similar results. The length of hospital stay did not differ between those who underwent the ERAS protocols and those who did not. Conclusions: The results of the study demonstrated the safety, clinical feasibility and benefits of the ERAS protocols for patients undergoing gynecologic surgeries for both benign and malignant indications.

Combined radiomics-clinical model to predict platinum-sensitivity in advanced high-grade serous ovarian carcinoma using multimodal MRI.

Introduction: We aimed to predict platinum sensitivity using routine baseline multimodal magnetic resonance imaging (MRI) and established clinical data in a radiomics framework. Methods: We evaluated 96 patients with ovarian cancer who underwent multimodal MRI and routine laboratory tests between January 2016 and December 2020. The patients underwent diffusion-weighted, contrast-enhanced T1-weighted, and T2-weighted MRI. Subsequently, 293 radiomic features were extracted by manually identifying tumor regions of interest. The features were subjected to the least absolute shrinkage and selection operators, leaving only a few selected features. We built the first prediction model with a tree-based classifier using selected radiomics features. A second prediction model was built by combining the selected radiomic features with four established clinical factors: age, disease stage, initial tumor marker level, and treatment course. Both models were built and tested using a five-fold cross-validation. Results: Our radiomics model predicted platinum sensitivity with an AUC of 0.65 using a few radiomics features related to heterogeneity. The second combined model had an AUC of 0.77, confirming the incremental benefits of the radiomics model in addition to models using established clinical factors. Conclusion: Our combined radiomics-clinical data model was effective in predicting platinum sensitivity in patients with advanced ovarian cancer.

Practice guidelines for management of uterine corpus cancer in Korea: a Korean Society of Gynecologic Oncology consensus statement.

The Korean Society of Gynecologic Oncology (KSGO) had been making an effort to standardize and enhance the quality of domestic uterine corpus cancer treatment by developing updated clinical practice guidelines in 2021. The KSGO revised the guidelines based on a literature search using 4 key elements: Population, Intervention, Comparison, and Outcome framework. These elements include the evaluation of the efficacy and safety of immune checkpoint inhibitor treatment in recurrent/advanced endometrial cancer patients who have failed platinum-based chemotherapy, as well as the effect of combined treatment with trastuzumab in patients with HER2/neu-positive endometrial cancer. Additionally, the guideline assessed the efficacy and safety of omitting lymph node dissection in low-risk endometrial cancer patients, investigated the effect of sentinel lymph node mapping in early-stage endometrial cancer surgery, addressed the outcome of chemoradiation therapy as a postoperative treatment in patients with advanced (stage III-IVA) endometrial cancer, and explored the impact of initial treatment with immune checkpoint inhibitors on survival in patients with advanced or recurrent endometrial cancer patients.

How accurately can one predict drug binding modes using AlphaFold models?

Computational prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine-learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here, we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G-protein-coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand-binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery.