Ovarian Cancer Tumor Research Articles

CT Findings of Stage IA Ovarian Cancer: Comparison between Borderline Tumor and Stage IC Ovarian Cancer.

Ovarian cancer is a common gynecological malignant tumor in women. Most patients have reached the advanced stage when they visit the hospital. In order to diagnose ovarian cancer at an early stage, treat it at an early stage, and improve the survival rate of patients, this study has used the imaging computed tomography (CT) method to diagnose stage IA ovarian cancer. The purpose of this work was to study CT features of stage IA ovarian cancer, and compare the borderline tumor and stage IC ovarian cancer at the same time so as to improve the CT diagnosis of early ovarian cancer. We retrospectively collected clinical and CT data of patients with stage I ovarian cancer and borderline ovarian tumor admitted to Nantong Tumor Hospital from 2013 to 2021. Altogether, 23 cases of patients (borderline ovarian tumor, 9 cases; stage IA ovarian cancer, 5 cases; stage IC ovarian cancer, 9 cases) were involved. CT characteristics of these patients were analyzed in terms of the tumor diameter, cystic solid structure, solid component, septation, enhancement, peritoneal thickening, ascites, and abdominal lymph nodes. CT features of stage IA ovarian cancer included large tumor size (average diameter: 15 cm), cystic solid structure (4/5; 80%), septation (4/5; 80%), and enhanced cystic wall, septum, or solid components of the tumor on contrast-enhanced CT (5/5; 100%) no peritoneal thickening (0/5; 0%), no ascites (0/5; 0%), and no abdominal lymph node enlargement (0/5; 0%). The tumor structure did not differ significantly between stage IA and IC ovarian cancers (p > 0.05), while intraperitoneal ascites did (χ2 = 0.031; p < 0.05). Stage IA and borderline ovarian tumors did not differ significantly in ovarian tumor structure (p > 0.05). CT features of stage IA ovarian cancer included large tumor size, cystic solid structure, septation, and enhanced cystic wall and solid parts in the tumors. No pelvic or abdominal metastasis was observed.

Fertility and Pregnancy Outcomes after Fertility-Sparing Surgery for Early-Stage Borderline Ovarian Tumors and Epithelial Ovarian Cancer: A Single-Center Study.

This study examined treatment outcomes, including preserved fertility, menstrual regularity, and pregnancy outcomes, in patients with stage I epithelial ovarian cancer (EOC) or borderline ovarian tumors (BOTs) who underwent fertility-sparing surgery (FSS). Patients with stage I EOC and BOTs who were aged 18-45 years and underwent FSS between 2007 and 2022 were retrospectively reviewed. Significant differences between various subgroups in terms of disease recurrence, menstrual irregularity due to the disease, and pregnancy outcomes were analyzed. A total of 71 patients with BOTs and 33 patients with EOC were included. In the BOT group, the median age was 30 (range, 19-44) years. Recurrence occurred in eight patients, with one case exhibiting a malignant transformation into mucinous EOC. Among the 35 married patients with BOTs, 20 successfully conceived, resulting in 23 live births and 3 spontaneous abortions. A higher pregnancy rate was observed in those without prior childbirth (82.4%) than in those who had prior childbirth (33.3%). In the EOC group, the median age was 34 (range, 22-42) years. Recurrence occurred in one patient. Menstrual regularity was maintained in 69.7% of the patients. Among the 14 married patients in this group, 12 achieved a total of 15 pregnancies (including 2 twin pregnancies), 16 live births, and 1 spontaneous abortion. The results of the study confirmed that FSS is a favorable surgical option for young women with early-stage BOTs or EOC who wish to preserve their fertility. However, additional investigations are needed to validate these findings.

Comparative diagnostic accuracy of the IOTA SRR and LR2 scoring systems for discriminating between malignant and Benign Adnexal masses by junior physicians in Chinese patients: a retrospective observational study

BackgroundThe accuracy of ultrasound in distinguishing benign from malignant adnexal masses is highly correlated with the experience of ultrasound physicians. In China, most of ultrasound differentiation is done by junior physicians.PurposeTo compare the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) Simple Rules Risk (SRR) and IOTA Logistic Regression Model 2 (LR2) scoring systems in Chinese patients with adnexal masses.MethodsRetrospective analysis of ovarian cancer tumor patients who underwent surgery at a hospital in China from January 2016 to December 2021. Screening patients with at least one adnexal mass on inclusion and exclusion criteria. Two trained junior physicians evaluated each mass using the two scoring systems. A receiver operating characteristic curve was used to test the diagnostic performance of each system.ResultsA total of 144 adnexal masses were retrospectively collected. Forty masses were histologically diagnosed as malignant. Compared with premenopausal women, postmenopausal women had a much higher rate of malignant masses. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of the SRR was 97.5% (95% CI: 86.8 -99.9%), 82.7% (95% CI: 74.0 -89.4%), 68.4% (95% CI: 58.7 -76.8%) and 98.9% (95% CI: 92.5 -99.8%). The sensitivity, specificity, PPV, NPV of the LR2 were 90.0% (95% CI: 76.5 -97.2%), 89.4% (95% CI: 81.9 -94.6%), 76.6% (95% CI: 65.0 -85.2%), and 95.9% (95% CI: 90.2 -98.3%). There was good agreement between two scoring systems, with 84.03% total agreement and a kappa value of 0.783 (95% CI: 0.70-0.864). The areas under the curve for predicting malignant tumours using SRR and LR2 were similar for all patients (P > 0.05 ).ConclusionThe two scoring systems can effectively distinguish benign from malignant adnexal masses. Both scoring systems have high diagnostic efficacy, and diagnostic efficacy is stable, which can provide an important reference for clinical decision making.

A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles

Even after debulking surgery combined with chemotherapy or new adjuvant chemotherapy paired with internal surgery, the average year of disease free survival in advanced ovarian cancer was approximately 1.7 years1. The development of a molecular predictor of early recurrence would allow for the identification of ovarian cancer (OC) patients with high risk of relapse. The Ovarian Cancer Disease Free Survival Predictor (ODFSP), a predictive model constructed from a special set of 1580 OC tumors in which gene expression was assessed using both microarray and sequencing platforms, was created by our team. To construct gene expression barcodes that were resistant to biases caused by disparate profiling platforms and batch effects, we employed a meta-analysis methodology that was based on the binary gene pair technique. We demonstrate that ODFSP is a reliable single-sample predictor of early recurrence (1 year or less) using the largest pool of OC transcriptome data sets available to date. The ODFSP model showed significantly high prognostic value for binary recurrence prediction unaffected by clinicopathologic factors, with a meta-estimate of the area under the receiver operating curve of 0.64 (P = 4.6E-05) and a D-index (robust hazard ratio) of 1.67 (P = 9.2E-06), respectively. GO analysis of ODFSP’s 2040 gene pairs (collapsed to 886 distinct genes) revealed the involvement in small molecular catabolic process, sulfur compound metabolic process, organic acid catabolic process, sulfur compound biosynthetic process, glycosaminoglycan metabolic process and aminometabolic process. Kyoto encyclopedia of genes and genomes pathway analysis of ODFSP’s signature genes identified prominent pathways that included cAMP signaling pathway and FoxO signaling pathway. By identifying individuals who might benefit from a more aggressive treatment plan or enrolment in a clinical trial but who will not benefit from standard surgery or chemotherapy, ODFSP could help with treatment decisions.

ARID5B promoted the histone demethylation of SORBS2 and hampered the metastasis of ovarian cancer

Ovarian cancer (OVCA) is the 4th most common female tumor after breast cancer, cervical cancer, and endometrial cancer, and now is mainly treated with debulking surgery and postoperative cisplatin and paclitaxel-based combination chemotherapy regimens. However, OVCA is insidious in its development and recurrence occurred in some patients after treatment. It is of great significance to study the pathogenesis of ovarian cancer and identify more biomarkers. Recently, the role of histone methyltransferase (HMT) and histone demethylase (HDM) in oncogenesis and development of malignant tumors has raised attention. Unlike other JMJC demethylases that have both JMJC and ARID domains in a single molecule, PHF2 requires assembly into a complex with a DNA-binding subunit (ARID5B) and exerts its enzymatic activity. Therefore, the aim of this manuscript is to investigate the role of histone demethylases ARID5B-PHF2 complex in the metastasis of OVCA. As result, we found ARID5B and PHF2 are both low expressed in OVCA tumor tissues and cell lines and associated with diagnosis and prognosis. Also, ARID5B suppressed rearrangement of the cytoskeleton in the process of EMT in OVCA cell lines. The role of PHF2 as a tumor suppressor was also confirmed both in vivo and in vitro. SORBS2 is low expressed in OVCA tumor tissues and cell lines and associated with diagnosis and prognosis. The expression of SORBS2 is positively corelated with the expression of ARID5B and PHF2. The promoter of SORBS2 is proved combined with ARID5B. The expression of SORBS2 was increased due to ARID5B-PHF2 complex promoted the histone demethylation by mainly binding in site H3K36me2 and therefore promoting the transcription of SORBS2. In conclusion, ARID5B-PHF2 complex promoted the histone demethylation of SORBS2 by mainly bind in site H3K36me2 and therefore promote the transcription of SORBS2 then hampered the process of EMT and tumor generation of OVCA. These results provided a new perspective on the molecular mechanisms of OVCA development and offered a new target of clinical diagnose and treatment of OVCA.

Fertility preservation options in epithelial ovarian cancer and borderline epithelial ovarian tumor

Fertility preservation options in epithelial ovarian cancer and borderline epithelial ovarian tumor

Detection of Ovarian Cancer using Deep Learning: A Survey

The term "ovarian cancer" (OC) refers to the most frequent type of gynecological cancer. The female reproductive system would not function properly without the ovary. Their significance is enhanced by the fact that these small glands produce female sex hormones as well as female gametes. These almond-shaped glandular organs sit directly on either side of the uterus and are connected to it via the ovarian ligament; they do not contain any tubes. There are many potential causes of ovarian cancer, but fortunately there are also many potential methods of diagnosis; one of these is the convolutional neural network. This article summarizes how convolutional neural networks could be used to classify ovarian cancer tumors and what other treatments are out there for the disease. some machine learning algorithms are used in ovarian cancer detection, and throughout the course of this research work, we compared some of them. These algorithms include K-Nearest Neighbors, Support Vector Machine, and Artificial Neural Network. Following a comprehensive analysis of available methods, the Deep Learning Technique was shown to be the most productive in its detection of ovarian cancer.

Combining Mass Cytometry Data by CyTOFmerge Reveals Additional Cell Phenotypes in the Heterogeneous Ovarian Cancer Tumor Microenvironment: A Pilot Study.

The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness.

THU475 Ovarian Tumor-cell Glucocorticoid Receptor Activity Modulates Cytokine Secretion Promoting Recruitment And Activation of Immunosuppressive Cells Into The Tumor Microenvironment

Abstract Disclosure: M. Taya: None. E. LeBlanc: None. L. Bennett: None. S.D. Conzen: None. Elevated levels of immunosuppressive myeloid-derived suppressor cells (MDSCs) circulate in the peripheral blood or infiltrate both tumors and ascites in ovarian cancer patients, however the cause for this observed phenotype is unknown. MDSCs contribute to tumor immune tolerance primarily via inhibition of cytotoxic T-cells or by activation of immunosuppressive T-regulatory cells. We previously showed that high tumor cell glucocorticoid receptor (GR) expression is associated with a relatively poor prognosis in ovarian cancer patients. Additionally, using primary tumor data retrieved from the ovarian cancer TCGA dataset, we show high tumor GR expression is associated with significantly higher expression of Foxp3, a marker of immunosuppressive T-regulatory cells, as well as CD33, a marker of immunosuppressive myeloid cells, further suggesting an immunosuppressive phenotype in ovarian cancer patients. We thus hypothesize that tumor-intrinsic GR activation in ovarian cancer is associated with increased MDSC infiltration into the tumor microenvironment partly due to the modulation of tumor cell cytokine secretion. To determine whether tumor-cell GR activation modulates the cytokine secretome, we previously showed that GR activation in ovarian cancer cells upregulates secretion of immunomodulatory factors including G-CSF, TGFb and CXCL5. Moreover, co-treatment of cells with a selective GR modulator (SGRM) reverses this effect. Preliminary gene expression data indicate GR mediated cytokine secretion and signaling may involve post-transcriptional or post-translational mechanisms. Considering that elevated levels of these cytokines are necessary for the production and recruitment of MDSCs, these data highlight the relevance of this evident glucocorticoid receptor-cytokine circuit in ovarian cancer cells. Furthermore, we show that this tumor-cell cytokine secretome has the capacity to promote differentiation of MDSCs from precursor myeloid cells in healthy PBMCs. Importantly, measuring expression of activation markers such as Arginase-1 and NOS2 illustrated that these MDSCs are in their functional state. To our knowledge, this is the first evidence that a nuclear receptor in ovarian cancer tumor cells is actively driving MDSC differentiation. Finally, employing ovarian cancer xenograft models as well as a syngeneic ID8 tumor model, treatment with SGRMs demonstrated reduced levels of circulating MDSCs in the peripheral blood as well as tumor infiltrated MDSCs. Using neutralizing antibodies for cytokines, we will now identify key mechanisms, specifically, which targetable immunomodulatory factors are contributing to immune suppression. Based on the insight provided by these data, we propose to determine whether targeting ovarian tumor cell-intrinsic GR activation and resulting MDSC infiltration contributes to improved anti-tumor immune response. Presentation: Thursday, June 15, 2023

2271P Development of an oncolytic virus for the treatment of high grade serous ovarian cancer and other stromal rich tumours

2271P Development of an oncolytic virus for the treatment of high grade serous ovarian cancer and other stromal rich tumours

Transcriptome analyses reveal new insights on key determinants of perineural invasion in high-grade serous ovarian cancer.

Perineural invasion (PNI) is a pathological feature of many cancers associated with poor outcomes, metastases, and recurrence. In relation to ovarian cancer (OC), there is no information about PNI's role and mechanisms. Our study found that patients with PNI-positive symptoms had significantly shorter overall survival (OS) time than patients with PNI-negative symptoms. Multivariate analyses demonstrated that PNI represented a substantial independent prognostic factor in OC patients. At the transcriptome level, it is noteworthy that PNI positivity was negatively correlated with the degree of infiltration of immune killer cells in OC tumor tissues, including macrophage, central memory CD4 T-cell, natural killer cells, monocyte, and central memory CD4 T-cell. The results of this study revealed that TAS2Rs proteins were markedly upregulated in PNI-positive OC tissues and predicted poor prognoses. Moreover, Immunohistochemical analysis demonstrated that the TAS2R10 protein was associated with poor prognoses and PNI in OC. Consequently, we found for the first time that PNI was a powerful predictor of poor prognosis in OC and analyzed its expression pattern and some preliminary biochemical characterization, providing new clues for guiding clinical prevention and treatment of OC.

Profiling ovarian cancer tumor and microenvironment during disease progression for cell-based immunotherapy design

Ovarian cancer (OC) is highly lethal due to late detection and frequent recurrence. Initial treatments, comprising surgery and chemotherapy, lead to disease remission but are invariably associated with subsequent relapse. The identification of novel therapies and an improved understanding of the molecular and cellular characteristics of OC are urgently needed. Here, we conducted a comprehensive analysis of primary tumor cells and their microenvironment from 16 chemonaive and 10 recurrent OC patient samples. Profiling OC tumor biomarkers allowed for the identification of potential molecular targets for developing immunotherapies, while profiling the microenvironment yielded insights into its cellular composition and property changes between chemonaive and recurrent samples. Notably, we identified CD1d as a biomarker of the OC microenvironment and demonstrated its targeting by invariant natural killer T (iNKT) cells. Overall, our study presents a comprehensive immuno-profiling of OC tumor and microenvironment during disease progression, guiding the development of immunotherapies for OC treatment, especially for recurrent disease.

Diagnostic value of CA125, HE4, and systemic immune-inflammation index in the preoperative investigation of ovarian masses.

This study aimed to ascertain the diagnostic accuracy of CA125, HE4, systemic immune-inflammation index (SII), fibrinogen-to-albumin ratio (FAR), prognostic nutritional index (PNI), and their combination for ovarian cancer (OC) to discover an optimal combined diagnostic index for early diagnosis of OC. A thorough investigation was conducted to ascertain the correlation between these markers and the pathological characteristics of OC, thereby providing a foundation for early identification and treatment of this disorder. One hundred seventy patients with documented OC and benign ovarian tumors (BOTs) treated at Hebei General Hospital between January 2019 and December 2022 were included in this retrospective study. Data analysis was conducted using IBM SPSS Statistics version V26.0, MedCalc Statistical Software version 19.4.0, and the R Environment for Statistical Computing software (R Foundation for Statistical Computing). Isolated CA125 showed the best application value for differentiating benign ovarian tumors from OC when the defined variables were compared separately. The combination of CA125, HE4, FAR, SII, and PNI displayed a greater area under the operating characteristic curve curve than any one of them or other combinations of the 5 variables. Compared to CA125 alone, the combination of CA125, HE4, FAR, SII, and PNI showed a slight gain in sensitivity (83.91%), negative predictive value (83.91%), accuracy (85.88%), and a decrease in negative likelihood ratio (0.180%). Higher preoperative CA125, HE4, SII, and FAR levels, and lower PNI levels predicted a higher probability of advanced OC progression and lymph node metastasis. FAR has better application value than other inflammation-related markers (PNI and SII). This study suggests that preoperative serum SII, PNI, and FAR may be clinically valuable markers in patients with OC. FAR has better application value than other inflammation-related markers (PNI and SII). As we delve deeper into the inflammatory mechanisms associated with tumors, we may discover more effective combinations of tumor and inflammatory biomarkers.

Usefulness of COL11A1 as a Prognostic Marker of Tumor Infiltration.

Determining the infiltration of carcinomas is essential for the proper follow-up and treatment of cancer patients. However, it continues to be a diagnostic challenge for pathologists in multiple types of tumors. In previous studies (carried out in surgical specimens), the protein COL11A1 has been postulated as an infiltration marker mainly expressed in the extracellular matrix (ECM). We hypothesized that a differential expression of COL11A1 may exist in the peritumoral stroma of tumors that have acquired infiltrating properties and that it may be detected in the small biopsies usually available in normal clinical practice. In our study, we performed immunohistochemical staining in more than 350 invasive and noninvasive small samples obtained via core needle biopsy (CNB), colonoscopy, or transurethral resection of bladder tumor (TURBT) of breast, colorectal, bladder, and ovarian cancer. Our results revealed that COL11A1 immunostaining had a sensitivity to classify the samples into infiltrative vs. noninfiltrative tumors of 94% (breast), 97% (colorectal), >90% (bladder), and 74% (ovarian); and a specificity of 97% (breast), 100% (colorectal), and >90% (bladder). In ovarian cancer, the negative predictive value (0.59) did not present improvement over the usual histopathological markers. In all samples tested, the cumulative sensitivity was 86% and the specificity 96% (p < 0.0001). COL11A1-positive immunostaining in small biopsies of breast, colon, bladder and ovarian cancer is an accurate predictive marker of tumor infiltration that can be easily implemented in daily clinical practice.

Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications

MotivationOvarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer.MethodsA functional module-based approach was utilized to identify key gene expression pathways that distinguish different stages of ovarian cancer (OC) within a tissue biopsy cohort. This cohort consisted of control samples (n = 79), stage I/II samples (n = 280), and stage III/IV samples (n = 1016). To further explore these altered molecular pathways, minimal spanning tree (MST) analysis was applied, leading to the formulation of metabolic biomarker hypotheses for OC liquid biopsy. To validate, a multiple reaction monitoring (MRM) based quantitative LCMS/MS method was developed. This method allowed for the precise quantification of targeted metabolite biomarkers using an OC blood cohort comprising control samples (n = 464), benign samples (n = 3), and OC samples (n = 13).ResultsEleven functional modules were identified as significant differentiators (false discovery rate, FDR < 0.05) between normal and early-stage, or early-stage and late-stage ovarian cancer (OC) tumor tissues. MST analysis revealed that the metabolic L-arginine/nitric oxide (L-ARG/NO) pathway was reprogrammed, and the modules related to "DNA replication" and "DNA repair and recombination" served as anchor modules connecting the other nine modules. Based on this analysis, symmetric dimethylarginine (SDMA) and arginine were proposed as potential liquid biopsy biomarkers for OC assessment. Our quantitative LCMS/MS analysis on our OC blood cohort provided direct evidence supporting the use of the SDMA-to-arginine ratio as a liquid biopsy panel to distinguish between normal and OC samples, with an area under the ROC curve (AUC) of 98.3%.ConclusionOur comprehensive analysis of tissue genomics and blood quantitative LC/MSMS metabolic data shed light on the metabolic reprogramming underlying OC pathophysiology. These findings offer new insights into the potential diagnostic utility of the SDMA-to-arginine ratio for OC assessment. Further validation studies using adequately powered OC cohorts are warranted to fully establish the clinical effectiveness of this diagnostic test.

P10.08.B PI3K INHIBITION FOR SENSITIZING CANCER CELLS TO TUMOR TREATING FIELDS (TTFIELDS)

Abstract BACKGROUND Tumor Treating Fields (TTFields) are electric fields that disrupt cellular processes critical for cancer cell viability and tumor progression, ultimately leading to cell death. TTFields therapy is approved for treatment of adult patients with glioblastoma (GBM) or unresectable pleural mesothelioma. Clinical trials are underway in other solid tumors, including ovarian cancer and non-small cell lung carcinoma (NSCLC). The objective of this study is to identify possible mechanisms involved in reduced sensitivity of cancer cell to TTFields, and explore strategies to circumvent them. MATERIAL AND METHODS GBM U-87 MG, ovarian cancer A2780, and NSCLC H1299 cells were treated with continuous long-term application of TTFields (1.7 V/cm RMS, 200 or 150 kHz, 6 or 13 days, specific conditions depending on cell line). Changes in signaling pathways were examined for cells following 3 days of treatment with Luminex multiplex assay, followed by Western blot validation for specific pathway markers. In vivo validation was performed in ovarian cancer (MOSE-L), hepatocellular carcinoma (N1-S1), and NSCLC (LL/2) tumor sections from animals treated with TTFields utilizing immunohistochemistry. Next, efficacy of TTFields concomitant with relevant inhibitors was evaluated in vitro and in mice inoculated orthotopically with ovarian cancer cells (MOSE-L). Tumor volume was measured at study end by luciferin signal detection using the In Vivo Imaging System (IVIS). RESULTS TTFields inflicted a cytotoxic effect on the cancer cells that increased over time, though with moderately reduced sensitivity following prolonged treatment application. PI3K/AKT signaling pathway was shown to be activated in treated cells, with the amplitude of AKT phosphorylation increasing over time. AKT phosphorylation was also demonstrated in tumor sections of animals treated with TTFields. Experiments performed with concomitant PI3K/AKT pathway inhibitors sensitized the cells to TTFields, enhancing cytotoxicity in vitro and treatment efficacy in vivo. CONCLUSION PI3K/AKT signaling pathway is involved in cancer cell reduced sensitivity to TTFields, and inhibition of this pathway sensitizes cancer cells to TTFields.

Ligand-based adoptive T cell targeting CA125 in ovarian cancer

BackgroundOvarian cancer (OC) is a highly aggressive gynecological malignancy prevalent worldwide. Most OC cases are typically diagnosed at advanced stages, which has led to a 5-year overall survival rate of less than 35% following conventional treatment. Furthermore, immune checkpoint inhibitor therapy has shown limited efficacy in the treatment of patients with OC, and CAR-T therapy has also demonstrated modest results owing to inadequate T cell infiltration. Therefore, novel strategies must be developed to enhance T cell persistence and trafficking within the OC tumor microenvironment.MethodsIn this study, we developed a novel adoptive T-cell therapy for ovarian cancer based on a chimeric antigen receptor structure. We used a ligand-receptor binding motif to enhance the therapeutic effect of targeting CA125. Since mesothelin can naturally bind to CA125 with high affinity, we concatenated the core-binding fragment of mesothelin with the 4-1BB and CD3ζ signal fragments to assemble a novel CA125-targeting chimeric receptor (CR). The CAR structure targeting CA125 derived from the 4H11 antibody was also constructed. CR- and CAR-encoding RNA were electroporated into T cells to evaluate their antitumor activity both in vitro and in vivo.ResultsWhile CR-T or CAR-T cells exhibited moderate activity against two ovarian cancer cell lines, T cells co-expressing CR and CAR exhibited a superior killing effect compared to T cells expressing either CR or CAR alone. Furthermore, upon interaction with ovarian tumors, the ability of CR and CAR T cells to release activation markers and functional cytokines increased significantly. Similarly, CR and CAR co-expressing T cells persistently controlled the growth of transplanted ovarian cancer tumors in NSG mice and significantly prolonged the overall survival of tumor-challenged mice. Transcriptome sequencing revealed that the survival and cytotoxicity of T cells co-expressing CR and CAR were significantly altered compared with those of T cells expressing either CR or CAR.ConclusionOur findings demonstrate that CA125 targeting CR and CAR can synergistically kill ovarian cancer cells, indicating that CA125 targeting by the two binding motifs simultaneously in tumors may improve the therapeutic outcomes of ovarian cancer treatment.

The role of OIP5 in the carcinogenesis and progression of ovarian cancer

BackgroundOpa interacting protein 5 (OIP5), which is a cancer/testis-specific gene, plays a cancer-promoting role in various types of human cancer. However, the role of OIP5 in the carcinogenesis and progression of ovarian cancer remains unknown.MethodsWe first analyzed the expression of OIP5 in ovarian cancer and various human tumors with the Sangerbox online analysis tool. GSE12470, GSE14407 and GSE54388 were downloaded from the Gene Expression Omnibus (GEO) database, and GEO2R was used to screen differentially expressed genes in ovarian cancer tissues. Gene Ontology (GO) enrichment analysis was used to explore the related biological processes. Receiver operating characteristic (ROC) curve was generated to evaluate the predictive ability of OIP5 for ovarian cancer. Next, RT–PCR, immunohistochemistry and Western blotting were utilized to evaluate the expression of OIP5 in ovarian cancer. CCK8, EdU proliferation assays and colony formation assays were used to measure cell proliferation, cell cycle progression was examined by PI staining and flow cytometry, and cell apoptosis was examined by Caspase3/7 activity assays. The effect of OIP5 on the migration and invasion of ovarian cancer cells was analyzed with Transwell assays.ResultsWe found that OIP5 is highly expressed in ovarian cancer through bioinformatics analysis, and importantly, OIP5 may be an important biomarker for the prognosis and diagnosis of ovarian cancer. RT–PCR assays, immunohistochemistry and Western blotting were also used to confirm the high expression of OIP5 in ovarian cancer. Subsequently, we demonstrated that the proliferation and migration of the ovarian cancer cell line A2780 were significantly inhibited after OIP5 gene silencing, apoptosis was increased and cell cycle progression was arrested at the G1 phase.ConclusionThis study indicated that OIP5 was highly expressed in ovarian cancer and that downregulation of OIP5 inhibited the proliferation, migration and invasion of ovarian cancer cells, induced cell cycle arrest and promoted cell apoptosis. Therefore, OIP5 may be an important biomarker for the early diagnosis and potential target for treatment of ovarian cancer.

The anti-tumor potential of sinomenine: a narrative review.

Currently, chemotherapy is the main treatment for most tumors. However, drug resistance and many adverse reactions associated with chemotherapy greatly limit its use. Therefore, an increasing number of researchers have shifted the research focus the anti-tumor activity of traditional Chinese medicine. The objective of this article is to review the anti-tumor mechanism of sinomenine and its derivatives to provide a reference for further study and clinical transformation. In this study, we searched for relevant articles on the anti-tumor mechanism of Sinomenium using databases such as PubMed and Medline. Sinomenine is a monomer alkaloid component extracted from the rhizome of Sinomenium acuturn. A number of basic studies have proven that sinomenine and its derivatives show significant anti-tumor activity in breast cancer, lung cancer, liver cancer, stomach cancer, ovarian cancer, osteosarcoma and other tumors. They can induce apoptosis and autophagic death of tumor cells, inhibit proliferation, migration and invasion of tumor cells, increase the sensitivity of tumor cells to radiotherapy and chemotherapy, and reverse the drug resistance through various molecular mechanisms. In addition, sinomenine can effectively relieve osteolysis and bone pain in tumor patients. At present, anti-tumor research on sinomenine remains in the basic experimental stage. Sinomenine and its derivatives are rich in substances with high anti-tumor potential. This analysis provides a review of the anti-tumor effects and mechanisms of sinomenine, with the hope of further exploring the medical value of sinomenine in anti-tumor treatments.

Activin levels correlate with lymphocytic infiltration in epithelial ovarian cancer tumors (2304)

Activin levels correlate with lymphocytic infiltration in epithelial ovarian cancer tumors (2304)