Lin Li

Patient-reported symptom burden and circulating cytokines undergoing chemotherapy: a pilot study in patients with ovarian cancer

To analyze the fluctuations of patient-reported outcomes (PROs) and their relationships with cytokines in the peripheral blood of patients undergoing chemotherapy for ovarian cancer (OC). PROs burden was prospectively measured by the M.D. Anderson Symptom Inventory-Ovarian Cancer (MDASI-OC) at baseline before chemotherapy, on a daily basis during and post-chemotherapy days (PCD) 7, 14, and 20. Cytokines were collected at baseline, days prior to hospital discharge and PCD 20. Pearson correlation was used to explore the associations between PROs and cytokines levels in peripheral blood. The top 8 rated symptoms were compared between the neoadjuvant chemotherapy (NACT) group (n=20) and the postoperative adjuvant chemotherapy (PAC) group (n=7). Before chemotherapy, the mean scores of fatigue and lack of appetite in the NACT group were higher than those in the PAC group. After chemotherapy, pain, nausea, vomiting, disturbed sleep, lack of appetite, and constipation increased to peak during PCD 2-6; while, fatigue and numbness or tingling remained at high levels over PCD 2-13. By PCD 20, disturbed sleep and fatigue showed a significant increase in mean scores, particularly in the NACT group; while, other symptom scores decreased and returned to baseline levels. Additionally, the longitudinal fluctuations in pain, fatigue, and lack of appetite were positively associated with circulating levels of interleukin-6 and interferon gamma (p<0.05). MDASI-OC was feasible and adaptable for demonstrating the fluctuations of symptom burden throughout chemotherapy course. Moreover, symptoms changing along with cytokines levels could provide clues for exploring mechanism underlying biochemical etiology.

Mediation Effects of Self-care Self-efficacy and Health-promoting Behaviors on Fear of Cancer Recurrence and Posttraumatic Growth in Postoperative Patients With Cervical Cancer: A Cross-sectional Study

High recurrence risks significantly contribute to poor health outcomes among postoperative cervical cancer patients. This study aimed to determine the impact of fear of cancer recurrence (FCR) on the posttraumatic growth (PTG) in postoperative cervical cancer patients and to investigate the mediating effects of self-care self-efficacy and health-promoting behaviors within this relationship. A total of 334 cervical cancer patients who had undergone surgery in three tertiary hospitals in Liaoning Province, China, were recruited using a convenience sampling method. Data were collected using the general information questionnaire, the Fear of Progression Questionnaire (FCR), the Post-traumatic Growth Inventory (PTG), the Strategies Used by People to Promote Health (self-care self-efficacy), and the Health-Promoting Lifestyle Profile (health-promoting behaviors). Data analysis was performed using descriptive analysis, Pearson's correlations, and multiple linear regression analysis. A structural equation model was conducted using Amos 24.0 software. PTG of cervical cancer patients after surgery was significantly and negatively associated with FCR (r = -.54, p < .001), while positively correlated with self-care self-efficacy (r = .51, p < .001) and health-promoting behaviors (r = .59, p < .001). The mediation model revealed that self-care self-efficacy (Boots 95% CI 0.39 ∼ 0.15) and health-promoting behaviors (Boots 95% CI 0.51 ∼ 0.24) independently served as mediating factors, respectively. Self-care self-efficacy and health-promoting behaviors played a significant chain mediating effect between FCR and PTG (Boots 95% CI 0.19 ∼ 0.07), with an indirect effect of 11.6%. This study demonstrated that self-care self-efficacy and health-promoting behaviors partially mediated the relationship between FCR and PTG in cervical cancer survivors after surgery. Implementing tailored interventions that focus on enhancing self-care self-efficacy and health-promoting behaviors among cervical cancer survivors may help alleviate concerns about cervical cancer recurrence and enhance PTG following surgery.

Intracellular delivery of therapeutic proteins through N-terminal site-specific modification

Adopting orthogonal dual-labeling strategies, a cell-permeable RNase A prodrug was designed for ROS-responsive targeted cancer therapy.

lncRNA SNHG15 Induced by SOX12 Promotes the Tumorigenic Properties and Chemoresistance in Cervical Cancer via the miR‐4735‐3p/HIF1a Pathway

Cervical cancer (CC) is one of the most common malignancies in females, with high prevalence and mortality globally. Despite advances in diagnosis and therapeutic strategies developed in recent years, CC is still a major health burden worldwide. The molecular mechanisms underlying the development of CC need to be understood. In this study, we aimed to demonstrate the role of lncRNA SNHG15 in CC progression. Using qRT‐PCR, we determined that lncRNA SNHG15 is highly expressed in CC tumor tissues and cells. lncRNA SNHG15 knockdown also reduces the tumorigenic properties of CC in vitro, as determined using the MTT, EdU, flow cytometry, and transwell assays. Using bioinformatics analysis, RNA pull‐down, ChIP, and luciferase reporter assays, we verified the molecular mechanisms of lncRNA SNHG15 in CC progression and found that lncRNA SNHG15 expression in CC cells is transcriptionally regulated by SOX12; moreover, lncRNA SNHG15 promotes CC progression via the miR‐4735‐3p/HIF1a axis. This study can provide a potential target for CC diagnosis or therapeutic strategies in the future.

Metabolic signatures of immune checkpoint inhibitor response in gynecologic cancers: Insights from flux balance analysis

Modifiers of immune checkpoint inhibitor (ICI) responses in cancer patients are complex and remain poorly characterized, especially in gynecologic cancers. In this study, we explored fluxomic biomarkers that differentiate responders from non-responders to ICIs in a series of 49 patients with gynecologic cancers, including ovarian, cervical, and endometrial cancers. By applying metabolic enzyme expression as constraints, we utilized an objective-customizable flux balance analysis within a genome-scale metabolic model to predict the metabolic flux differences between responders versus non-responders of ICI treatment. We identified three reactions with consistent differential activity across all ten different optimization objectives: Succinate Dehydrogenase (SUCD1m) in the citric acid cycle, NADH: Guanosine-5-Phosphate Oxidoreductase (r0276) involved in purine catabolism, and Ornithine Transaminase Reversible, Mitochondrial (ORNTArm) in the urea cycle. Additionally, reactions within the folate cycle subsystem, particularly involving MTHFD2, demonstrated significance in distinguishing treatment responses, aligning with previous findings linking MTHFD2 to immune evasion and tumor progression. To further analyze the association between metabolic features and survival outcomes, we implemented machine learning models that integrate multi-omics data. Our model included clinical-pathologic, molecular-genomic features (gene expression, TGF-β score, immune cell abundance from transcriptomic deconvolution), and significant reaction fluxes. Our findings suggest that SUCD1m, MTHFDm and ORNTArm are important metabolic biomarkers that could serve as predictive indicators for ICI response and, if validated in a larger cohort, may guide the development of targeted therapies to enhance treatment efficacy for gynecologic cancer patients. This study highlights the use of genome-scale metabolic modeling to identify clinically relevant biomarkers and improve therapeutic strategies.