This preliminary study aimed to evaluate the feasibility of enhanced terahertz (THz) scattering-type scanning near-field optical microscopy (s-SNOM) for the label-free, nanoscale imaging of ovarian cancer cells. Leveraging an advanced THz s-SNOM platform integrated with zero-intermediate frequency radar detection and atomic force microscopy (AFM), we investigated the morphological and intrinsic dielectric properties of ovarian cancer cells under various preparation protocols. Paraffin-embedded cell sections deposited on silicon dioxide (SiO2) and gold substrates demonstrated clear correlations between AFM-derived topographical maps and THz near-field images, revealing subcellular structures such as distinct nuclear and cytoplasmic domains without the use of exogenous labels. Additionally, imaging of air-dried ES-2 ovarian cancer cell suspensions on gold substrates further improved morphological preservation and contrast resolution compared to paraffin-embedded sections. Our findings indicate that THz s-SNOM enables label-free, nanoscale characterization of cellular architecture and composition, yielding insights into cellular heterogeneity relevant to ovarian cancer research and diagnostics.

Although poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) as monotherapy or in combination with other DNA-damaging agents exhibit promising clinical efficacy, the therapeutic responses are usually transient, with subsequent development of acquired resistance posing a significant challenge. Here, through a small-molecule compound screening, we identify elesclomol, a potent copper ionophore, which sensitizes BRCA-proficient ovarian cancer cells to PARPi by inhibiting activation of the ATR-CHK1 pathway. Mechanistically, we demonstrate that copper directly binds to ATRIP, a critical cofactor of ATR activation, disrupting the ATR-ATRIP interaction, further impairing ATR-mediated DNA damage repair signaling and potentiating PARPi sensitivity. Importantly, we reveal a secondary metabolic vulnerability in PARPi-resistant ovarian cancer associated with de novo pyrimidine synthesis, suggesting that targeting this pathway as an effective strategy to eradicate drug-adaptive residual tumors and resistant patient-derived xenograft models following ATR and PARP co-inhibition. These findings propose de novo pyrimidine synthesis as an adaptive metabolic vulnerability that can be therapeutically targeted to overcome PARPi resistance in BRCA-proficient ovarian cancer.

Background:Cervical cancer remains a major global health burden. Preoperative conization has been proposed to reduce tumor burden and potential intraoperative tumor dissemination, but its survival benefit in patients with stage IB cervical cancer remains uncertain. This study aimed to evaluate the association between preoperative conization and survival outcomes after radical surgery in patients with FIGO 2018 stage IB cervical cancer. Methods:This retrospective study included 1,614 patients with FIGO 2018 stage IB1-IB3 cervical cancer who underwent radical surgery between 2007 and 2016 at a single center. Patients were classified into four groups based on surgical approach and conization status. Progression-free survival (PFS) and overall survival (OS) were analyzed. Inverse probability of treatment weighting (IPTW) based on propensity scores was used to balance baseline characteristics. Survival outcomes were compared using weighted Kaplan-Meier analysis. Results:After IPTW adjustment, baseline covariate balance was substantially improved, although residual imbalances remained for FIGO stage, depth of stromal invasion, neoadjuvant chemotherapy, and tumor differentiation. Weighted survival analysis showed no consistent survival advantage associated with preoperative conization. In pairwise OS comparisons, the laparotomy with conization group appeared to have superior OS compared with the other groups; however, this finding should be interpreted cautiously because no death events occurred in this group, resulting in non-estimable hazard ratios for comparisons involving this group. For PFS, no significant differences were observed between groups, including laparotomy with versus without conization (HR = 2.61, 95% CI: 0.62-11.02, P = 0.54), laparoscopic surgery without conization versus laparotomy without conization (HR = 1.97, 95% CI: 0.98-3.94, P = 0.21), laparoscopic surgery with conization versus laparotomy without conization (HR = 0.84, 95% CI: 0.21-3.49, P = 1.00), laparoscopic surgery without conization versus laparotomy with conization (HR = 0.75, 95% CI: 0.18-3.08, P = 0.98), laparoscopic surgery with conization versus laparotomy with conization (HR = 0.32, 95% CI: 0.05-2.02, P = 0.60), and laparoscopic surgery with versus without conization (HR = 0.43, 95% CI: 0.12-1.59, P = 0.56). Conclusion:Preoperative conization was not associated with improved OS or PFS in patients with FIGO 2018 stage IB cervical cancer undergoing radical surgery. The apparent OS advantage observed in the laparotomy with conization group was based on zero death events and non-estimable hazard ratios, and therefore should not be interpreted as definitive evidence of a survival benefit. Further prospective multicenter studies with larger conization cohorts and longer follow-up are warranted.

Ovarian cancer was the eighth most frequently diagnosed cancer among women in 2022. The global age-standardized incidence rate of ovarian cancer decreased from 7.22/100,000 to 6.71/100,000 from 1990 to 2021. However, incidence trends varied across countries. Declining ovarian cancer incidence rates were reported in high-income countries, such as the United States, Austria, the Netherlands, and Norway, while there were increasing incidence rates in Africa and parts of Asia, including Japan and India. The global age-standardized mortality rate of ovarian cancer decreased from 4.73/100,000 to 4.06/100,000 between 1999 and 2021 with varying trends among countries. Moreover, the age-standardized 5-year net ovarian cancer survival rate in most countries remained < 50%. Several specific factors related to ovarian cancer risk have been identified, including reproductive factors, use of oral contraceptives, anti-inflammatory diets, endometriosis, pelvic inflammatory disease, obesity, diabetes, and occupational asbestos exposure. No screening or prevention strategy has been proven effective in downstaging or reducing mortality from ovarian cancer in an average-risk population without a family cancer history or pathogenic variants. Indeed, risk-reducing salpingo-oophorectomy remains the gold standard for lowering the risk of ovarian cancer in high-risk individuals with hereditary mutations. This review provides a comprehensive overview of the epidemiology, risk factors, screening, and prevention of ovarian cancer, aiming to offer a global perspective on public health strategies for addressing the disease.

Cryoablation simulation based on Finite Element Method (FEM) can facilitate preoperative planning for liver tumors. However, it has limited application in clinical practice due to its time-consuming process and improvable accuracy. We aimed to propose a FEM-based simulation model for rapid and accurate prediction of the iceball size during the hepatic cryofreezing cycle. A 3D simulation model was presented to predict the iceball size (frozen isotherm boundaries) in biological liver tissues undergoing cryofreezing based on the Pennes bioheat equation. The simulated results for three cryoprobe types were evaluated in the ex vivo porcine livers and clinical data. In ex vivo experiments, CT-based measurements of iceball size were fitted as growth curves and compared to the simulated results. Eight patient cases of CT-guided percutaneous hepatic cryoablation procedures were retrospectively collected for clinical validation. The Dice Score Coefficient (DSC) and Hausdorff distance (HD) were used to measure the similarity between simulation and ground truth segmentation. The measurements in the ex vivo experiments showed a close similarity between the simulated and experimental iceball growth curves for three cryoprobe models, with all mean absolute error<2.9 mm and coefficient of determination>0.85. In the clinical validation, the simulation model achieved high accuracy with a DSC of 0.87 ± 0.03 and an HD of 2.0 ± 0.4 mm. The average computational time was 23.2 s for all simulations. Our simulation model achieves accurate iceball size predictions within a short time during hepatic cryoablation and potentially allows for the implementation of the preoperative cryoablation planning system.

BACKGROUND:Ovarian cancer (OV) continues to be the most lethal type of gynecological cancer with a poor prognosis. During tumorigenesis and cancer advancement, mitochondria are key players in energy metabolism. This study focuses on exploring the mitochondria-related genes for the prognosis of OV. METHODS:RNA expression profiles and single-cell data were acquired from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus databases for screening and validating mitochondria-related differentially expressed genes (DEGs). After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. Functional enrichment analysis was performed on this prognostic gene set. Immune infiltration analysis was performed between MS groups. Validation for the prognostic model gene OAT was performed to identify the prognostic significance, combined with in vitro experiments to explore its expressions in OV cells. qRT-PCR assay was performed to examine the expression of OAT in human ovarian cancer cell samples and normal ovarian epithelial cells. RESULTS:A total of 21 prognostic mitochondria-related DEGs were identified for reliably constructing the model MS with excellent prognostic performance in OV. GO and KEGG analysis confirmed these genes were enriched in the generation of precursor metabolites and energy. It illustrated more lymphocyte infiltration in the high MS group than low MS group. OAT served as a novel biomarker for OV patients, showing poor survival in OV patients with high expression of OAT. qPCR assays confirmed its significantly high expression in human ovary cancer cell lines. CONCLUSIONS:The MS offers tailored risk evaluations and immunotherapy treatments for each OV patient. MS model gene OAT has been recognized as a new oncogene for OV linked to immune escape.

Recent research has demonstrated that activating the cGAS-STING pathway can enhance interferon production and the activation of T cells. A manganese complex, called TPA-Mn, was developed in this context. The reactive oxygen species (ROS)-sensitive nanoparticles (NPMn) loaded with TPA-Mn are developed. NPMn activates the cGAS-STING pathway via cGAS activation (i.e., 1.6-fold enhancement of P-STING), which in turn increases the secretion of pro-inflammatory cytokines (e.g., TNF-α, IL-6, and IL-2). This promotes dendritic cell maturation, enhances the infiltration of cytotoxic T lymphocytes, and reduces the percentage of immunosuppressive regulatory T cells. In addition, it is crucial to emphasize that cisplatin-induced DNA damage can potentially trigger activation of the cGAS-STING pathway. NPMn, in combination with low-dose NPPt, a carrier of a Cis(IV) prodrug capable of causing DNA damage, augments the cGAS-STING pathway activation and significantly activates the tumor immune microenvironment (TIME). Furthermore, combined with anti-PD-1 antibody, NPPt+NPMn shows synergistic efficacy in both ovarian cancer peritoneal metastases and recurrence models. It not only effectively eliminates tumors but also induces a strong immune memory response, providing a promising strategy for the clinical management of ovarian cancer. This work offers a design of manganese-based nanoparticles for immunotherapy.

Background Pulmonary adenocarcinoma, a predominant form of lung cancer, is characterized by diverse histopathological subtypes, including ground-glass nodules (GGNs), which may represent different degrees of malignancy. The accurate differentiation between invasive and non-invasive GGNs is paramount, as it significantly influences clinical management and treatment strategies. Objective To evaluate the clinical efficacy of spectral CT combined with targeted scanning in diagnosing invasive GGNs in pulmonary adenocarcinoma. Methods A retrospective analysis of 120 patients with GGNs, who underwent spectral CT and targeted scanning at the Second Affiliated Hospital of Qiqihar Medical College (Nov 2021 - Dec 2022), was conducted. Patients were categorized based on postoperative pathology into non-invasive (66) and invasive (54) groups. Imaging features and values of various indicators including water concentration (WC), spectral curve slope (k value), and iodine concentration across different phases were analyzed and compared. Key independent factors for invasive GGN and the predictive value of the combined imaging technique were explored. Results The invasive lesion group showed a higher incidence of fissure sign, spiculation sign, and bronchial inflation sign, along with increased values of WC, WCAP, and WCVP across phases ( p < 0.05). These factors were identified as main influencers of invasive GGN, with OR values >1. The combined imaging parameters achieved an AUC of 0.914, sensitivity of 0.925, and specificity of 0.880, significantly outperforming individual indicators. Conclusion Fissure sign, spiculation sign, bronchial inflation sign, WC, WCAP, and WCVP effectively predict invasive GGNs in pulmonary adenocarcinoma. Their combined application enhances predictive accuracy.

BACKGROUND:Sentinel lymph node (SLN) mapping is crucial in cervical cancer, helping to assess lymph node status while reducing unnecessary systemic lymph node dissection. However, bilateral SLN mapping fails in 5 %-20 % of cases, with various contributing factors. This meta-analysis aims to identify predictive factors associated with SLN mapping failure in cervical cancer. METHODS:A comprehensive literature search was conducted across Cochrane, MEDLINE, Embase, PubMed, Web of Science, CBM, CNKI, WFDB, and VIP from inception to July 2024. Additional data were obtained from SRCTN, Physicians Data Query, ClinicalTrials, and the International Clinical Trials Registry Platform. Two independent researchers screened studies, assessed quality, and extracted data. The associations between predictive factors and SLN mapping failure were evaluated using odds ratios (ORs) with 95 % confidence intervals (CIs). RESULTS:A total of 27 observational studies comprising 4059 patients were included. Significant predictive factors for SLN mapping failure included tumor size ≥2 cm [OR = 1.35, 95 % CI (1.05, 1.74), P = 0.018], age ≥50 years [OR = 2.71, 95 % CI (1.85, 3.97), P ≤ 0.001], FIGO stages II-IV [OR = 2.11, 95 % CI (1.20, 3.72), P = 0.009], pelvic lymph node metastasis [OR = 2.15, 95 % CI (1.10, 4.20), P = 0.025], and neoadjuvant chemotherapy (NACT) [OR = 1.44, 95 % CI (1.09, 1.90), P = 0.010]. Other factors including obesity, surgical approach, cervical conization, tumor differentiation, lymphovascular space invasion (LVSI), and histologic type were not associated with SLN mapping failure. CONCLUSIONS:Larger tumor, older age, advanced FIGO stage, pelvic lymph node metastasis, and NACT are predictive factors for SLN mapping failure. These findings highlight the importance of preoperative assessment before SLN mapping.

Ovarian cancer (OV) is the most lethal gynecological malignancy in the world. At present, the effect of m7G modification-related genes on the development of ovarian cancer remains unclear. We performed consensus clustering of ovarian cancer samples based on the expression of 24 m7G modification-related genes, and obtained 2 subtypes. There were some differences in immune cell infiltration between the two subtypes. Furthermore, enrichment analysis showed that differential genes were mainly enriched in several pathways and biological processes, including positive translation regulation and TRAPP complex. Multivariate cox regression analysis confirmed two genes (DCP2 and NUDT16) related to prognosis for the construction of risk score prediction models. The risk map of survival status showed that the high-risk samples had a shorter survival time (p<0.05). Risk score was an independent prognostic factor for OV and correlated with immunotherapy response. We also performed network analysis for DCP2 and NUDT16. We further explored the effects of the genes on cellular function and prognosis. In conclusion, this study provided a new perspective for the development mechanism of ovarian cancer.

Ovarian cancer, especially the drug-resistant subtype, has a treatment response rate of less than 30 %, primarily due to enhanced DNA damage repair mechanisms that reduce the efficacy of chemotherapy. Moreover, the low level of immune cell infiltration in ovarian tumors limits the therapeutic response to immune checkpoint inhibitors (ICIs). Addressing both chemoresistance and immune activation is essential to improve outcomes. DNAdependent protein kinase catalytic subunit (DNA-PKcs), a critical component of the DNA damage repair pathway, plays a key role in the repair of DNA double-strand breaks (DSBs). Inhibition of DNA-PKcs not only sensitizes tumors to chemotherapy but also activates the cGAS-STING innate immunity pathway. Herein, we developed a glutathione (GSH)-responsive nanoparticle (NP2), self-assembled from a GSH-sensitive doxorubicin prodrug (PHHM-SS-DOX) and a DNA-PKcs inhibitor (AZD7648). NP2 responds to elevated GSH levels in cancer cells and releases DOX and AZD7648. AZD7648 inhibits DNA-PKcs phosphorylation, suppressing the non-homologous end joining (NHEJ) pathway and exacerbating doxorubicin-induced DSBs. Then sustained accumulation of dsDNA further activates the cGAS-STING pathway. In vivo, NP2 demonstrated significant tumor growth inhibition and modulation of antitumor immunity. It activated the cGAS-STING pathway and enhanced the release of inflammatory cytokines, maturation of dendritic cells, infiltration of CD8+ T cells, and polarization of tumor-associated macrophages toward the pro-inflammatory M1 phenotype. These effects reprogrammed the ovarian cancer microenvironment into an "immune-hot" tumor, significantly improving the response to ICIs. This strategy provides a novel therapeutic avenue to overcome chemoresistance and enhance the efficacy of immunotherapy in ovarian cancer.

BACKGROUND:Gynecological malignancies, particularly ovarian cancer, pose a formidable challenge to women's wellbeing, as evidenced by the global incidence and mortality rates, emphasizing the pressing need for advanced diagnostic and treatment modalities. The heterogeneity of ovarian cancer poses challenges for traditional therapeutic approaches, necessitating the exploration of novel, precision medicine techniques. METHODS:This study leveraged multi-dataset analysis to construct and validate an Artificial Intelligence-Derived Prognostic Index (AIDPI) for ovarian cancer. Transcriptome data from the TCGA, ICGC, and GEO databases were utilized, encompassing bulk and single-cell RNA sequencing. The AIDPI model was developed and refined using univariate Cox regression analysis and an ensemble of machine learning algorithms. Functional analysis, immunoprofiling, and the role of the MFAP4 gene were investigated to elucidate the biological mechanisms underlying the model. RESULTS:The AIDPI model demonstrated superior accuracy in predicting ovarian cancer prognosis compared to existing models. It correlated with clinical treatment outcomes, including chemotherapy responsiveness, and was integrated into a nomogram for improved prognostic stratification. Functional analysis revealed the influence of AIDPI genes on tumor immune infiltration and cell cycle regulation. Single-cell analysis exposed cell type-specific expression patterns, and the MFAP4 gene was identified as a potential therapeutic target due to its association with patient prognosis and modulation of cellular behavior. In clinical samples of ovarian cancer patients, MFAP4 is highly expressed in metastatic lesions and is associated with poor prognosis. In vitro and in vivo experiments, knockdown of MFAP4 reduces the metastasis of ovarian cancer cells. CONCLUSION:The AIDPI model offers a highly accurate tool for ovarian cancer prognosis and treatment decision-making, underscored by the integration of multi-omics data and artificial intelligence. The model's performance and biological insights provide a foundation for advancing precision medicine in ovarian cancer. MFAP4's functionality and the influence of DNA methylation present opportunities for prospective research endeavors and potential therapeutic interventions.

Overcoming the immunosuppressive tumor microenvironment and therapeutic resistance remains a significant challenge in ovarian cancer treatment. In this study, a glutathione-responsive polymeric nanoparticle platform for the co-delivery of the USP1 inhibitor SJB3-019A and the PARP inhibitor Niraparib is developed. This system synergistically enhances DNA damage accumulation, suppresses homologous recombination repair, and robustly activate the STING signaling pathway, leading to enhanced type I interferon responses and mitigation of immune evasion. Mechanistically, USP1 inhibition significantly impairs DNA repair, amplifying the synthetic lethality of PARP inhibition and promoting immunogenic cell death. In vivo studies demonstrated precise, glutathione-responsive drug release and substantial tumor accumulation of the nanoparticles, resulting in remarkable antitumor efficacy in murine ovarian cancer models. Importantly, this combinational approach effectively remodels the tumor microenvironment by increasing CD8⁺ T cell infiltration and enhancing tumor sensitivity to immune checkpoint blockade therapies. This innovative strategy targeting DNA damage responses presents a promising platform for precise and effective ovarian cancer immunotherapy.

Background:Ablation is an effective alternative treatment option for early-stage non-small cell lung cancer (NSCLC) patients who are not candidates for surgery or who refuse surgery. Microwave ablation (MWA) and cryoablation (CA) are both minimally invasive treatment techniques widely used in NSCLC patients, and their safety and efficacy have been verified. This study aimed to compare the safety and efficacy of co-ablation (Co-A) and MWA in the treatment of subpleural stage I NSCLC. Methods:From December 2023 to December 2024, a retrospective analysis was conducted on 87 eligible patients (40 males, 47 females; mean age ± standard deviation: 72.03±9.07 years; age range, 31-88 years). Patients were divided into two groups based on the treatment method: a Co-A group and an MWA group. Recurrence-free survival (RFS) rates and complication rates were compared between the two groups. Results:Co-A had a significantly longer mean operative time compared to MWA (28.26±7.56 vs. 6.37±2.01 min, P<0.001). Postoperative analgesic intervention was significantly lower in the Co-A group (30.4% vs. 45.4%, P=0.03). Mean follow-up time was similar between groups (7.04±2.01 vs. 7.27±2.49 months, P=0.69). RFS rates at study end were 95.7% in Co-A and 100.0% in MWA (P=0.26). Common complications-pneumothorax, transient hemoptysis, and pleural effusion-showed no significant differences in incidence between the two groups (P>0.05). However, pneumothorax requiring chest tube drainage was significantly higher in the Co-A group (34.8% vs. 7.8%, P=0.008). Conclusions:Compared with MWA, Co-A demonstrates no significant difference in efficacy or safety for treating patients with subpleural stage I NSCLC, but is associated with reduced perioperative pain and a longer operative duration.

ABSTRACT Purpose As microwave ablation continues to be used in patients with inoperable stage I non‐small cell lung cancer (NSCLC), it is particularly important to monitor efficacy. Whether plasma ctDNA detection can predict its efficacy should be illustrated. Methods We recruited 43 patients with inoperative stage I NSCLC, all of whom underwent biopsy‐synchronous microwave ablation (MWA). Peripheral blood samples were collected at baseline (n = 43), within 1 h post‐MWA (n = 28), and at the landmark time point (n = 26) for MRD detection. Clinical outcomes were analyzed using Kaplan–Meier survival analysis. Results Patients with undetectable ctDNA at baseline (p = 0.042) and within 1 h after MWA (p = 0.023) had better clinical outcomes. In particular, patients with undetectable ctDNA at the 1‐h post‐MWA time point did not experience recurrence. Detection of ctDNA at the landmark time point is considered an independent risk factor for prognosis and is strongly correlated with clinical outcomes (p = 0.001), the median time to recurrence indicated by ctDNA was 4.9 months earlier compared to imaging. The clinical outcomes of patients with ctDNA clearance were similar to those with no ctDNA (p = 0.570). Risk stratification indicated that patients with persistent ctDNA had worse clinical outcomes compared to those who never had detectable ctDNA (p = 0.004). Conclusion Our findings suggest that ctDNA monitoring can assist in predicting clinical outcomes in stage I NSCLC treated with microwave ablation. Patients with undetectable ctDNA within 1 h after MWA are determined to be clinically cured. Risk stratification based on ctDNA test results helps to differentiate high‐risk patients.

Struma ovarii (SO) represents a rare subset of ovarian germ cell tumors, with approximately 5% transforming into malignant SO (MSO). This study retrospectively analyzed clinical data from 23 SO patients treated at the Cancer Hospital of the Chinese Academy of Medical Sciences between January 2013 and December 2023, including 17 benign SO and 6 MSO cases. Additionally, a systematic review of 164 cases of MSO confined to the ovary, reported in the literature from 1946 to 2024, was conducted. Data on pathological type, treatment, and prognosis were extracted, and univariate and multivariate Cox regression analyses were performed to identify risk factors for recurrence in stage I MSO. The median age at diagnosis was higher for benign SO compared to MSO (58 vs. 42.5 years), with 70.6% of patients being postmenopausal. Benign SO commonly presented with abdominal distension or mass, with more than half having ascites, while MSO patients were asymptomatic and lacked ascites. Cox regression analyses revealed that ovarian cystectomy was adversely associated with recurrence risk in stage I MSO, likely due to surgically induced capsular rent and potential tumor spillage. Significantly lower recurrence risks were observed in patients who underwent unilateral or bilateral salpingo-oophorectomy (HR = 0.36, P = 0.019; HR = 0.19, P = 0.004, respectively). This study highlights the importance of the surgical approach in the management of stage I MSO. A thorough preoperative discussion of the benefits and risks of different surgical approaches is recommended for patients desiring fertility preservation. Postoperative adjuvant therapy has not been shown to have a significant impact on prognosis. For the treatment of recurrent MSO, selecting appropriate surgical and adjuvant therapeutic strategies is essential to improve the long-term prognosis of MSO patients.

Platinum resistance cause therapeutic failure and poor prognosis in ovarian cancer, and evasion of apoptosis is a critical factor in chemoresistance. A limited number of FDA-approved anticancer drugs directly target apoptotic pathways. Here, we discovered that MCL1, a critical anti-apoptotic protein, is amplified and associated with platinum resistance and survival in ovarian cancer, assisting in personalized treatment. We further identified S63845 through drug-based screening, the most potent MCL1 inhibitor, which efficiently enhanced carboplatin (CBP) sensitivity in various ovarian cancer models, including primary ovarian cancer cells, orthotopic ovarian cancer, peritoneal metastasis, and human patient-derived xenograft (PDX) models. Mechanistically, S63845 competitively binds to MCL1, disrupts the binding of apoptosis effector (BAK and BAX) or pro-apoptotic BH3 protein (BIM) to MCL1 respectively, and eventually enhances CBP-induced apoptosis.To promote the clinical transformation of S63845, we developed follicle-stimulating hormone-modified liposome nanoparticles (S63845@Lipo-FSH) to enhance stability, membrane penetration, and tumor-targeting capabilities. S63845@Lipo-FSH exhibits a superior therapeutic efficacy and tumor targeting compared to free S63845, even when the dose of S63845 is reduced to one-fifth. Overall, targeting MCL1 by S63845@Lipo-FSH enhances CBP efficiency in ovarian cancer, with safety and efficacy, suggesting that this strategy is effective and promising for clinical application.

Ovarian clear cell carcinoma (OCCC) is a subtype of ovarian cancer with a poor prognosis that often shows resistance to chemotherapy. This study retrospectively analyzed 247 patients with OCCC who were admitted to the Cancer Hospital of the Chinese Academy of Medical Sciences (CAMS) between August 2007 and August 2023. Univariate and multivariate Cox regression analyses were used to identify clinicopathological factors associated with OCCC, and a nomogram prediction model was developed to predict OCCC patient survival outcomes. Kaplan‒Meier survival analysis was used to compare survival outcomes among patients with recurrent disease. Compared with systemic therapy, secondary debulking surgery significantly improved the postrecurrence survival (PRS) rate (P = 0.006). Subgroup analysis revealed that the survival benefit was more pronounced in patients with recurrence and satisfactory tumor shrinkage (PPRS = 0.01, PPFS2 = 0.047). The multivariate analysis revealed that positive preoperative ascites, incomplete remission following initial treatment, and undergoing more than six cycles of postoperative chemotherapy were independent prognostic factors affecting overall survival (OS). Additionally, patients with a positive PD-L1 test who received immunotherapy did not experience relapse during the follow-up period. In conclusion, the secondary clearance procedure offers significant benefits for patients with recurrent OCCC, and patients may experience a survival benefit from supplemental immune or targeted therapy at the end of chemotherapy. The development of a personalized treatment plan can help achieve precise treatment, improve prognosis, and enhance patients' quality of life.