Melica Nourmoussavi Brodeur

Interferon response and epigenetic modulation by SMARCA4 mutations drive ovarian tumor immunogenicity

Cell-intrinsic mechanisms of immunogenicity in ovarian cancer (OC) are not well understood. Damaging mutations in the SWI/SNF chromatin remodeling complex, such as SMARCA4 (BRG1), are associated with improved response to immune checkpoint blockade; however, the mechanism by which this occurs is unclear. We found that SMARCA4 loss in OC models resulted in increased cancer cell–intrinsic immunogenicity, characterized by up-regulation of long-terminal RNA repeats, increased expression of interferon-stimulated genes, and up-regulation of antigen presentation machinery. Notably, this response was dependent on STING, MAVS, and IRF3 signaling but was independent of the type I interferon receptor. Mouse ovarian and melanoma tumors with SMARCA4 loss demonstrated increased infiltration and activation of cytotoxic T cells, NK cells, and myeloid cells in the tumor microenvironment. These results were recapitulated in BRG1 inhibitor–treated SMARCA4- proficient tumor models, suggesting that modulation of chromatin remodeling through targeting SMARCA4 may serve as a strategy to overcome cancer immune evasion.

Machine learning for prediction of concurrent endometrial carcinoma in patients diagnosed with endometrial intraepithelial neoplasia

To identify predictive clinico-pathologic factors for concurrent endometrial carcinoma (EC) among patients with endometrial intraepithelial neoplasia (EIN) using machine learning. a retrospective analysis of 160 patients with a biopsy proven EIN. We analyzed the performance of multiple machine learning models (n = 48) with different parameters to predict the diagnosis of postoperative EC. The prediction variables included: parity, gestations, sampling method, endometrial thickness, age, body mass index, diabetes, hypertension, serum CA-125, preoperative histology and preoperative hormonal therapy. Python 'sklearn' library was used to train and test the models. The model performance was evaluated by sensitivity, specificity, PPV, NPV and AUC. Five iterations of internal cross-validation were performed, and the mean values were used to compare between the models. Of the 160 women with a preoperative diagnosis of EIN, 37.5% (60) had a post-op diagnosis of EC. In univariable analysis, there were no significant predictors of EIN. For the five best machine learning models, all the models had a high specificity (71%-88%) and a low sensitivity (23%-51%). Logistic regression model had the highest specificity 88%, XG Boost had the highest sensitivity 51%, and the highest positive predictive value 62% and negative predictive value 73%. The highest area under the curve was achieved by the random forest model 0.646. Even using the most elaborate AI algorithms, it is not possible currently to predict concurrent EC in women with a preoperative diagnosis of EIN. As women with EIN have a high risk of concurrent EC, there may be a value of surgical staging including sentinel lymph node evaluation, to more precisely direct adjuvant treatment in the event EC is identified on final pathology.

Neoadjuvant radiotherapy and brachytherapy in endometrial cancer with gross cervical involvement: a CHIRENDO research group study

Historically, radical hysterectomy followed by adjuvant radiotherapy has been offered to patients with endometrial cancer who have gross cervical involvement; however, this approach is known to carry considerable morbidity. Neoadjuvant radiotherapy followed by extra-fascial hysterectomy has been proposed as an alternative treatment but has been poorly studied to date. To evaluate the locoregional control rate associated with neoadjuvant radiotherapy followed by extra-fascial hysterectomy. A retrospective cohort study of 30 patients with endometrial cancer with gross cervical involvement treated between May 2006 and January 2016 was performed. Eligible patients were those aged The median age was 60 (range 37-82) and median body mass index was 32 kg/m Neoadjuvant radiotherapy followed by extra-fascial hysterectomy offers good locoregional control with low treatment-related morbidity in patients with endometrial cancer with overt cervical involvement.