Carboxyl graphene modified PEDOT:PSS organic electrochemical transistor for in situ detection of cancer cell morphology.

Circulating tumor cells in human peripheral blood play an important role in cancer metastasis. In addition to the size-based and antibody-based capture and separation of cancer cells, their electrical characterization is important for rare cell detection, which can prove fatal in point-of-care testing. Herein, an organic electrochemical transistor (OECT) biosensor made of solution-gated carboxyl graphene mixed with PEDOT:PSS for the detection of cancer cells in situ is reported. Carboxyl graphene was used in this work to modulate cancer cell morphology, which differs significantly from normal blood cells, to achieve rare cancer cell detection. When the concentration of carboxyl graphene mixed in PEDOT:PSS was increased from 0 to 5 mg mL-1, the cancer cell surface area increased from 218 µm2 to 530 µm2, respectively. A change in cell morphology was also detected by the OECT. Negative charges in the cancer cells induced a positive shift in gate voltage, which was approximately 40 mV for spherical-shaped cells. When the cell surface area increased, transfer curves of transistor revealed a negative shift in gate voltage. Therefore, the sensor can be used for in situ detection of cancer cell morphology during the cell capture process, which can be used to identify whether the captured cells are deformable.

Nonmetastatic Axillary Lymph Nodes Have Distinct Morphology and Immunophenotype in Obese Patients with Breast Cancer at Risk for Metastasis.

Obese patients with breast cancer have worse outcomes than their normal weight counterparts, with a 50% to 80% increased rate of axillary nodal metastasis. Recent studies suggest a link between increased lymph node adipose tissue and breast cancer nodal metastasis. Further investigation into potential mechanisms underlying this link may reveal potential prognostic utility of fat-enlarged lymph nodes in patients with breast cancer. This study used a deep learning model to identify morphologic differences in nonmetastatic axillary nodes between obese, node-positive, and node-negative patients with breast cancer. The model was developed using nested cross-validation on 180 cases and achieved an area under the receiver operator characteristic curve of 0.67 in differentiating patients using hematoxylin and eosin-stained whole slide images. The morphologic analysis of the predictive regions showed an increased average adipocyte size (P = 0.004), increased white space between lymphocytes (P < 0.0001), and increased red blood cells (P < 0.001) in nonmetastatic lymph nodes of node-positive patients. Preliminary immunohistochemistry analysis on a subset of 30 patients showed a trend of decreased CD3 expression and increased leptin expression in fat-replaced axillary lymph nodes of obese, node-positive patients. These findings suggest a novel direction to further investigate the interaction between lymph node adiposity, lymphatic dysfunction, and breast cancer nodal metastases, highlighting a possible prognostic tool for obese patients with breast cancer.

Fabrication of PEDOT:PSS-based solution gated organic electrochemical transistor array for cancer cells detection.

Organic electrochemical transistor (OECT) was applied in chemical and biological sensing. In this work, we developed a simple and repeatable method to fabricate OECT array, which had been successfully used to detect cancer cells. PEDPT:PSS conductive film between source and drain electrodes were patterned through photolithography, which can achieve uniform devices with same electrical characterization. When MCF-7 cancer cells are captured on the PEDOT:PSS surface via specifical antibody, the transfer characteristic of OECT shifts to higher gate electrode voltage due to the electrostatic interaction between cancer cells and device. The effective gate voltage shift can reach about 63 mV when the concentration of cancer cells increased to 5000. The shift of effective gate voltage is related to the cancer cell morphology, which is increased in the first 1 h and decreased when the capture time was larger than 1 h. The device of OECT array can increase the sample flux and make the detection result more accurate. It is expected that OECT array will have promising practical applications in single cancer cell detection in the future.

A molecularly imprinted polypyrrole electrochemiluminescence sensor based on a novel zinc-based metal-organic framework and chitosan for determination of enrofloxacin.

Nowadays, bacterial resistance caused by the abuse of antibiotics has become a worldwide problem. In this work, a quinolone antibiotic, enrofloxacin (ENR), was rapidly monitored by combining a selective molecular imprinting polymer (MIP) with the electrochemiluminescence (ECL) method. Zn-PTC, a novel zinc-based metal-organic framework (MOF) that has a large specific surface area and ultra-high luminous efficiency, was used as the ECL luminophore. Chitosan (CHIT) was used to contact the specific surface area of molecularly imprinted polymer films and further improved the detection sensitivity. Subsequently, the molecularly imprinted polypyrrole was electropolymerized on the surface of the Zn-PTC and CHIT modified glassy carbon electrode (GCE). The specific sites that could target recombining ENR were shaped on the surface of MIP after extracting the ENR templates. The specific concentrations of ENR could be detected according to the difference in ECL intensity (ΔECL) between the eluting and rebinding of ENR. After optimization, a good linear response of ΔECL and a logarithm of specific ENR concentrations could be obtained in the range of 1.0 × 10-12-1.0 × 10-4 mol L-1, with a detection limit of 9.3 × 10-13 mol L-1 (S/N = 3). Notably, this study provided a rapid, convenient, and cheap method for the detection of ENR in actual samples.

Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms.

OBJECTIVE: Fat-infiltrated axillary lymph nodes (LNs) are unique sites for ectopic fat deposition. Early studies showed a strong correlation between fatty LNs and obesity-related diseases. Confirming this correlation requires large-scale studies, hindered by scarce labeled data. With the long-term goal of developing a rapid and generalizable tool to aid data labeling, we developed an automated deep learning (DL)-based pipeline to classify the status of fatty LNs on screening mammograms. METHODS: Our internal data set included 886 mammograms from a tertiary academic medical institution, with a binary status of the fat-infiltrated LNs based on the size and morphology of the largest visible axillary LN. A two-stage DL model training and fine-tuning pipeline was developed to classify the fat-infiltrated LN status using the internal training and development data set. The model was evaluated on a held-out internal test set and a subset of the Digital Database for Screening Mammography. RESULTS: Our model achieved 0.97 (95% CI: 0.94-0.99) accuracy and 1.00 (95% CI: 1.00-1.00) area under the receiver operator characteristic curve on 264 internal testing mammograms, and 0.82 (95% CI: 0.77-0.86) accuracy and 0.87 (95% CI: 0.82-0.91) area under the receiver operator characteristic curve on 70 external testing mammograms. CONCLUSION: This study confirmed the feasibility of using a DL model for fat-infiltrated LN classification. The model provides a practical tool to identify fatty LNs on mammograms and to allow for future large-scale studies to evaluate the role of fatty LNs as an imaging biomarker of obesity-associated pathologies. ADVANCES IN KNOWLEDGE: Our study is the first to classify fatty LNs using an automated DL approach.

A novel molecularly imprinting polypyrrole electrochemiluminescence sensor based on MIL-101-g-C3N4 for supersensitive determination of ciprofloxacin.

Ciprofloxacin (CIP), a quinolone antibiotic, was rapidly and sensitively detected by integrating the molecularly imprinted polymer (MIP) with an ultra-sensitive electrochemiluminescence (ECL) method. g-C3N4, a typical polymer semiconductor, exhibited outstanding ECL efficiency and excellent ECL stability after combining with an iron-based metal-organic framework (MIL-101). Subsequently, the molecularly imprinted polypyrrole was electropolymerized on the composites of MIL-101-g-C3N4 modified glassy carbon electrode (GCE). The specific sites that could target rebinding the CIP molecules were formed on the surface of MIP after extracting the CIP templates. The determination of specific concentrations of CIP could be realized according to the difference in ECL intensity (△ECL) between the eluting and rebinding of the CIP. Under optimal conditions, a good linear response of △ECL and the logarithm of CIP concentrations was obtained in the range 1.0 × 10-9 ~ 1.0 × 10-5 mol/L, with a detection limit of 4.5 × 10-10 mol/L (S/N = 3) (the working potential was -1.8 ~ 0 V). The RSD of all points in the calibration plot was less than 5.0% and the real samples recovery was between 98.0 and 104%. This paper displays satisfactory selectivity and sensitivity, providing a rapid, convenient, and cheap method for the determination of CIP in real samples.

The Hidden Patient Connections: Predicting Hormonal Therapy Medication Discontinuation Using Hypergraph Neural Network on Clinical Communications.

Hormonal therapy is an important adjuvant treatment for breast cancer patients, but medication discontinuation of such therapy is not uncommon. The goal of this paper is to conduct research on the modeling of clinic communications, which have shown value in understanding medication discontinuation, to predict the discontinuation of hormonal therapy medications. Notably, we leveraged the Hypergraph Neural Network to capture the hidden connections of patients that were inferred from clinical communications. Combining the content of clinical communications as well as the demographics, insurance, and cancer stage information, our model achieved an AUC of 67.9%, which significantly outperformed other baselines such as Graph Convolutional Network (65.3%), Random Forest (62.7%), and Support Vector Machine (62.8%). Our study suggested that incorporating the hidden patient connections encoded in clinical communications into prediction models could boost their performance. Future research would consider combining structured medical records and clinical communications to better predict medication discontinuation.

Non-Metastatic Axillary Lymph Nodes Have Distinct Morphology and Immunophenotype in Obese Breast Cancer patients at Risk for Metastasis.

Obese patients have worse breast cancer outcomes than normal weight women including a 50% to 80% increased rate of axillary nodal metastasis. Recent studies have shown a potential link between increased lymph node adipose tissue and breast cancer nodal metastasis. Further investigation into potential mechanisms underlying this link may reveal potential prognostic utility of fat-enlarged lymph nodes in breast cancer patients. In this study, a deep learning framework was developed to identify morphological differences of non-metastatic axillary nodes between node-positive and node-negative obese breast cancer patients. Pathology review of the model-selected patches found an increase in the average size of adipocytes (p-value=0.004), an increased amount of white space between lymphocytes (p-value<0.0001), and an increased amount of red blood cells (p-value<0.001) in non-metastatic lymph nodes of node-positive breast cancer patients. Our downstream immunohistology (IHC) analysis showed a decrease of CD3 expression and increase of leptin expression in fat-replaced axillary lymph nodes in obese node-positive patients. In summary, our findings suggest a novel direction to further investigate the crosstalk between lymph node adiposity, lymphatic dysfunction, and breast cancer nodal metastases.

CT characterization of retractor related liver injuries after pancreaticoduodenectomy: Retrospective analysis of a single institution experience.

PURPOSE: Retractor related liver injuries (RRLI) are reported after upper gastrointestinal tract surgeries; most commonly laparoscopic cholecystectomy and gastric surgeries. The aim of this study was to characterize the incidence, identification, type, severity, clinical features and risk factors for RRLI after open and robotic pancreaticoduodenectomy. METHODS: A 6-year retrospective study of 230 patients was performed. Clinical data was extracted from the electronic medical record. Post-operative imaging was reviewed and graded using the American Association for the Surgery of Trauma (AAST) liver injury scale. RESULTS: 109 patients met eligibility criteria. RRLI occurred in 23/109 (21.1%), with a higher incidence in the robotic/combinedapproach (4/9) compared with open (19/100). Most common injury was an intraparenchymal hematoma (56.5%), grade II (78.3%), located in segments II/III (77%). 39.1% of injuries were not reported on the CT interpretation. There was a statistically significant elevation of postoperative AST/ALT in the RRLI group [median AST 219.5 vs. 72.0 (p < 0.001), ALT 203.0 vs. 69.0 (p < 0.001)]. Trends toward lower preoperative platelet counts and longer operations were observed in the RRLI group. No significant difference in hospital length of stay or post-operative pain scores were noted. CONCLUSION: RRLI occurred frequently after pancreaticoduodenectomy, however most injuries were low grade and the only clinical significance was a transient increase in transaminases. A trend toward higher injury rates was observed in robotic cases. In this population, RRLI was often unrecognized on postoperative imaging.

Development and Validation of the Veterans Affairs Eosinophilic Esophagitis Cohort.

BACKGROUND & AIMS: Gaps remain in understanding the epidemiology of eosinophilic esophagitis (EoE). Our aim was to identify and validate a national cohort of individuals with EoE using Veterans Health Administration (VHA) data. METHODS: We used 2 validation strategies to develop algorithms that identified adults with EoE between 1999 and 2020. The first validation strategy applied International Classification of Diseases (ICD) code algorithms to a base cohort of individuals who underwent esophagogastroduodenoscopy with esophageal biopsy specimens. The second applied ICD code algorithms to a base cohort of all individuals in the VHA. For each ICD algorithm applied, a random sample of candidate EoE cases and non-EoE controls were selected and the charts were reviewed manually by a blinded reviewer. Each algorithm was modified iteratively until the prespecified diagnostic accuracy end point (95% confidence lower bound for a positive predictive value [PPV], >88%) was achieved. We compiled individuals from each strategy's maximum performance algorithm to construct the Veterans Affairs Eosinophilic Esophagitis Cohort. RESULTS: The maximum performance algorithm from the first validation strategy included 2 or more ICD code encounters for EoE separated by more than 30 days and achieved a 93.3% PPV (lower bound, 88.1%) for identifying true EoE cases. The maximum performance algorithm from the second validation strategy included 4 or more ICD code encounters for EoE in which 2 codes were separated by at least 30 days, and similarly achieved a 93.3% PPV (lower bound, 88.1%). Combining both strategies yielded 6637 individuals, which comprised the Veterans Affairs Eosinophilic Esophagitis Cohort. CONCLUSIONS: We developed and validated 2 highly accurate coding algorithms for EoE and established a nationwide VHA cohort of adults with EoE for future studies.

Hydrogen Sulfide Enhances Browning Repression and Quality Maintenance in Fresh-Cut Peaches via Modulating Phenolic and Amino Acids Metabolisms.

Effects of hydrogen sulfide (H2S) on the browning and quality maintenance of fresh-cut peach fruit were studied. The results showed that H2S treatment repressed the development of surface browning, suppressed the increase in respiration rate and weight loss, and delayed the decline of firmness while soluble solids content (SSC) and microbial growth were unaffected during storage. H2S treatment maintained higher contents of phenolic compounds, especially neo-chlorogenic acid, catechin, and quercetin, and delayed the degradation of phenolic compounds by enhancing the activities of phenolic biosynthesis-related enzymes and inhibiting the oxidative activities of polyphenol oxidase (PPO) in comparison with control. Moreover, H2S stimulated the accumulation of amino acids and their derivatives including proline, γ-aminobutyric acid (GABA), and polyamines (PAs) via enhancing biosynthesis and repressing degradation compared to control. These results suggested that H2S treatment enhanced the accumulation of phenolic, amino acids, and their derivatives by modulating phenolic and amino acids metabolisms, which contributed to the higher antioxidant activity and membrane integrity maintenance, ultimately repressing browning development and maintaining the quality. Therefore, the current study speculated that H2S might be a promising approach for browning inhibition and quality maintenance in fresh-cut peach fruit.

Association between fat-infiltrated axillary lymph nodes on screening mammography and cardiometabolic disease.

Objective: Ectopic fat deposition within and around organs is a stronger predictor of cardiometabolic disease status than body mass index (BMI). Fat deposition within the lymphatic system is poorly understood. This study examined the association between the prevalence of cardiometabolic disease and ectopic fat deposition within axillary lymph nodes (LNs) visualized on screening mammograms. Methods: A cross-sectional study was conducted on 834 women presenting for full-field digital screening mammography. The status of fat-infiltrated LNs was assessed based on the size and morphology of axillary LNs from screening mammograms. The prevalence of cardiometabolic disease was retrieved from the electronic medical records, including type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, high blood glucose, cardiovascular disease, stroke, and non-alcoholic fatty liver disease. Results: Fat-infiltrated axillary LNs were associated with a high prevalence of T2DM among all women (adjusted odds ratio: 3.92, 95% CI: [2.40, 6.60], p-value < 0.001) and in subgroups of women with and without obesity. Utilizing the status of fatty LNs improved the classification of T2DM status in addition to age and BMI (1.4% improvement in the area under the receiver operating characteristic curve). Conclusion: Fat-infiltrated axillary LNs visualized on screening mammograms were associated with the prevalence of T2DM. If further validated, fat-infiltrated axillary LNs may represent a novel imaging biomarker of T2DM in women undergoing screening mammography.

Bladder cancer prognosis using deep neural networks and histopathology images.

Background: Recent studies indicate that bladder cancer is among the top 10 most common cancers in the world (Saginala et al. 2022). Bladder cancer frequently reoccurs, and prognostic judgments may vary among clinicians. As a favorable prognosis may help to inform less aggressive treatment plans, classification of histopathology slides is essential for the accurate prognosis and effective treatment of bladder cancer patients. Developing automated and accurate histopathology image analysis methods can help pathologists determine the prognosis of patients with bladder cancer. Materials and methods: In this study, we introduced Bladder4Net, a deep learning pipeline, to classify whole-slide histopathology images of bladder cancer into two classes: low-risk (combination of PUNLMP and low-grade tumors) and high-risk (combination of high-grade and invasive tumors). This pipeline consists of four convolutional neural network (CNN)-based classifiers to address the difficulties of identifying PUNLMP and invasive classes. We evaluated our pipeline on 182 independent whole-slide images from the New Hampshire Bladder Cancer Study (NHBCS) (Karagas et al., 1998; Sverrisson et al., 2014; Sverrisson et al., 2014) collected from 1994 to 2004 and 378 external digitized slides from The Cancer Genome Atlas (TCGA) database (https://www.cancer.gov/tcga). Results: The weighted average F1-score of our approach was 0.91 (95% confidence interval (CI): 0.86-0.94) on the NHBCS dataset and 0.99 (95% CI: 0.97-1.00) on the TCGA dataset. Additionally, we computed Kaplan-Meier survival curves for patients who were predicted as high risk versus those predicted as low risk. For the NHBCS test set, patients predicted as high risk had worse overall survival than those predicted as low risk, with a log-rank p-value of 0.004. Conclusions: If validated through prospective trials, our model could be used in clinical settings to improve patient care.

A novel three-dimensional molecularly imprinted polypyrrole electrochemical sensor based on MOF derived porous carbon and nitrogen doped graphene for ultrasensitive determination of dopamine.

Herein, a novel molecular imprinting polypyrrole electrochemical sensor was fabricated based on a zirconia and carbon core-shell structure (ZrO2@C) and a nitrogen-doped graphene (NPG) modified glassy carbon electrode (GCE) for ultrasensitive recognition of dopamine (DA). The NPG was prepared by a sacrificial-template-assisted pyrolysis method and ZrO2@C was synthesized via annealing treatment of a zirconium-based metal-organic framework (UiO-66). A convenient electropolymerization method was used to prepare the pyrrole (Py) conductive molecularly imprinted polymer (MIP) in the presence of DA. The elution process of DA was performed by a simple overoxidation process under alkaline conditions. Differential pulse voltammetry (DPV) was used to assess the electrochemical performance of the sensors. The MIP-based electrochemical sensor with specific binding sites could be used for selective recognition of DA. Under the optimal conditions, the linear range of such a sensor was 5.0 × 10-9-1.0 × 10-4 mol L-1 and the detection limit was 3.3 × 10-10 mol L-1 (S/N = 3). This sensor exhibited suitable selectivity, stability, and reproducibility, which suggested that it could be a promising candidate for rapid diagnostic methods in dopamine investigations.

Fat-enlarged axillary lymph nodes are associated with node-positive breast cancer in obese patients.

PURPOSE: Obesity associated fat infiltration of organ systems is accompanied by organ dysfunction and poor cancer outcomes. Obese women demonstrate variable degrees of fat infiltration of axillary lymph nodes (LNs), and they are at increased risk for node-positive breast cancer. However, the relationship between enlarged axillary nodes and axillary metastases has not been investigated. The purpose of this study is to evaluate the association between axillary metastases and fat-enlarged axillary nodes visualized on mammograms and breast MRI in obese women with a diagnosis of invasive breast cancer. METHODS: This retrospective case-control study included 431 patients with histologically confirmed invasive breast cancer. The primary analysis of this study included 306 patients with pre-treatment and pre-operative breast MRI and body mass index (BMI) > 30 (201 node-positive cases and 105 randomly selected node-negative controls) diagnosed with invasive breast cancer between April 1, 2011, and March 1, 2020. The largest visible LN was measured in the axilla contralateral to the known breast cancer on breast MRI. Multivariate logistic regression models were used to assess the association between node-positive status and LN size adjusting for age, BMI, tumor size, tumor grade, tumor subtype, and lymphovascular invasion. RESULTS: A strong likelihood of node-positive breast cancer was observed among obese women with fat-expanded lymph nodes (adjusted OR for the 4th vs. 1st quartile for contralateral LN size on MRI: 9.70; 95% CI 4.26, 23.50; p < 0.001). The receiver operating characteristic curve for size of fat-enlarged nodes in the contralateral axilla identified on breast MRI had an area under the curve of 0.72 for predicting axillary metastasis, and this increased to 0.77 when combined with patient and tumor characteristics. CONCLUSION: Fat expansion of axillary lymph nodes was associated with a high likelihood of axillary metastases in obese women with invasive breast cancer independent of BMI and tumor characteristics.

Alterations in mucosa-associated microbiota in the stomach of patients with gastric cancer.

PURPOSE: The purpose of this study was to characterize alterations in mucosa-associated microbiota in different anatomical locations of the stomach during gastric cancer progression and to identify associations between Helicobacter pylori infection and gastric microbial changes in patients with gastric cancer. METHODS: Twenty-five H. pylori negative subjects with chronic gastritis and thirty-four subjects with gastric cancer were recruited, including H. pylori negative and positive patients with tumors in the antrum and the corpus. Gastric mucosa-associated microbiota were determined by 16S ribosomal RNA gene sequencing using a 454 sequencing platform. RESULTS: We found that individuals with chronic gastritis from three different anatomical sites exhibited different microbiota compositions, although the microbial alpha diversity, richness and beta diversity were similar. Compared to patients with chronic gastritis, the gastric microbiota compositions were significantly different at the order level in the antrum and the corpus of patients with gastric cancer, which was dependent on the H. pylori infection status. Microbial alpha diversity and species richness, however, were similar between chronic gastritis and gastric cancer cases and independent of H. pylori status. The microbial community structure in patients with gastric cancer was distinct from that in patients with chronic gastritis. In addition, we found that the presence of H. pylori markedly altered the structure in gastric corpus cancer, but only mildly affected the antrum. CONCLUSION: Our data revealed distinct niche-specific microbiota alterations during the progression from gastritis to gastric cancer. These alterations may reflect adaptions of the microbiota to the diverse specific environmental habitats in the stomach, and may play an important, as yet undetermined, role in gastric carcinogenesis.

A Machine Learning Approach for Long-Term Prognosis of Bladder Cancer based on Clinical and Molecular Features.

Improving the consistency and reproducibility of bladder cancer prognoses necessitates the development of accurate, predictive prognostic models. Current methods of determining the prognosis of bladder cancer patients rely on manual decision-making, including factors with high intra- and inter-observer variability, such as tumor grade. To advance the long-term prediction of bladder cancer prognoses, we developed and tested a computational model to predict the 10-year overall survival outcome using population-based bladder cancer data, without considering tumor grade classification. The resulted predictive model demonstrated promising performance using a combination of clinical and molecular features, and was also strongly related to patient overall survival in Cox models. Our study suggests that machine learning methods can provide reliable long-term prognoses for bladder cancer patients, without relying on the less consistent tumor grade. If validated in clinical trials, this automated approach could guide and improve personalized management and treatment for bladder cancer patients.

Loss of breast cancer metastasis suppressor 1 promotes ovarian cancer cell metastasis by increasing chemokine receptor 4 expression.

Breast cancer metastasis suppressor 1 (BRMS1) is a predominantly nuclear protein that differentially regulates the expression of multiple genes, leading to suppression of metastasis without affecting orthotopic tumor growth. It has been demonstrated that BRMS1 may be correlated with advanced ovarian cancer. The aim of this study was to investi-gate the mechanisms of BRMS1 involvement in ovarian cancer metastasis. We constructed a plasmid containing a short hairpin RNA (shRNA) against BRMS1 and transfected it into the ovarian cancer cell line OVCAR3. Real-time reverse transcription polymerase chain reaction (real-time PCR) and Western blot analyses demonstrated that BRMS1 expression was efficiently downregulated. Stable suppression of BRMS1 significantly enhanced cell adhesion, migration, invasion and angiogenesis. We also found that chemokine receptor 4 (CXCR4) was upregulated at both the mRNA and protein levels. When approaching for the mechanism, we discovered that activation of the nuclear factor-κB (NF-κB) signaling pathway mediated CXCR4 upregulation, as demonstrated by the electrophoretic mobility shift assay (EMSA). Collectively, these results suggest that attenuation of BRMS1 may play a critical role in promoting migration, invasion and angiogenesis of ovarian cancer cells and BRMS1 may regulate the metastatic potential at least in part through upregulation of CXCR4 via NF-κB activation. Restoration of BRMS1 function is thus a potential new strategy for treating human ovarian cancer.