Ovarian Carcinosarcoma: Effects of Cytoreductive Status and Platinum-Based Chemotherapy on Survival

Objective. To define survival patterns of women with ovarian carcinosarcoma based on patient, tumor, and treatment characteristics. Methods/Materials. A single-institution, retrospective analysis of women diagnosed with ovarian carcinosarcoma from February 1993 to May 2009 was performed. Survival was analyzed with Cox proportional hazards ratios and Kaplan Meier tests. Results. Forty-seven cases of primary ovarian carcinosarcoma were identified. Age conveyed an HR 3.28 (95% CI 1.51–7.11, P=0.003) for death. Compared to Stages I-II, Stage III carried an HR for death of 4.75 (95% CI 1.16–19.4, P=0.03) and Stage IV disease an HR of 9.13 (95% CI 1.76–47.45, P=0.009). Compared to those with microscopic residual, women with >1 cm diameter of residual disease after primary cytoreductive surgery had an HR for death of 4.71 (95% CI 1.84–12.09, P=0.001). At analysis, 59.1% of those who received platinum-based chemotherapy were alive, compared to 23.1% of those who received nonplatinum-based chemotherapy (P=0.08). Conclusions. Age, stage, and cytoreduction to no gross residual disease are associated with improved survival in women with ovarian carcinosarcoma. Complete surgical cytoreduction should be the goal of surgical management when possible, but the ideal adjuvant treatment regimen remains unclear

Discontinuation of hydroxychloroquine in older patients with systemic lupus erythematosus: a multicenter retrospective study

Background Although hydroxychloroquine (HCQ) is a mainstay of treatment for patients with systemic lupus erythematosus (SLE), ocular toxicity can result from accumulated exposure. As the longevity of patients with SLE improves, data are needed to balance the risk of ocular toxicity and the risk of disease flare, especially in older patients with quiescent disease. Accordingly, this study was initiated to examine the safety of HCQ withdrawal in older SLE patients. Methods Data were obtained by retrospective chart review at three major lupus centers in New York City. Twenty-six patients who discontinued HCQ and thirty-two patients on HCQ matched for gender, race/ethnicity, and age were included in this study. The primary outcome was the occurrence of a lupus flare classified by the revised version of the Safety of Estrogens in Lupus Erythematosus: National Assessment version of the Systemic Lupus Erythematosus Disease Activity Index (SELENA-SLEDAI) Flare composite index, within 1 year of HCQ withdrawal or matched time of continuation. Results Five patients (19.2%) in the HCQ withdrawal group compared to five (15.6%) in the HCQ continuation group experienced a flare of any severity (odds ratio [OR] = 1.28; 95% CI 0.31, 5.30; p = 0.73). There were no severe flares in either group. The results were similar after adjusting for length of SLE, number of American College of Rheumatology criteria, low complement levels, and SELENA-SLEDAI score, and in a propensity score analysis (OR = 1.18; 95% CI 0.23, 6.16; p = 0.84). The analysis of time to any flare revealed a non-significant earlier time to flare in the HCQ withdrawal group (log-rank p = 0.67). Most flares were in the cutaneous and musculoskeletal systems, but one patient in the continuation group developed pericarditis. The most common reason for HCQ withdrawal was retinal toxicity (42.3%), followed by patient’s preference (34.6%), other confirmed or suspected adverse effects (15.4%), ophthalmologist recommendation for macular degeneration (3.8%), and rheumatologist recommendation for quiescent SLE (3.8%). Conclusions In this retrospective study of older stable patients with SLE on long-term HCQ, withdrawal did not significantly increase the risk of flares

Integrated Molecular Characterization of Uterine Carcinosarcoma

SummaryWe performed genomic, epigenomic, transcriptomic, and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy-number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest among all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy-number alterations in genes that are therapeutic targets were identified

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

33 UPLIFT (ENGOT-ov67/GOG-3048) a pivotal cohort of upifitamab rilsodotin (XMT-1536; UpRi), a NaPi2b-directed antibody drug conjugate (ADC) in platinum-resistant ovarian cancer

Upifitamab rilsodotin (UpRi), is a first-in-class antibody drug conjugate targeting NaPi2b, a sodium-dependent phosphate transporter protein broadly expressed in solid tumors including high-grade serous epithelial ovarian, fallopian tube and primary peritoneal cancers (OC), and limited expression in healthy tissues. Preliminary antitumor activity from the Phase 1b expansion cohort of heavily pretreated patients with OC has been reported (Richardson et al., SGO 2022). Data through June 2021 demonstrated clinically meaningful activity in patients with recurrent ovarian cancer, with notable activity in patients with NaPi2b-high tumors (TPS ≥75) treated at the optimized dose of 36 mg/m2. Effective and well-tolerated treatments for platinum-resistant ovarian cancer (PROC) remain a substantial unmet medical need. Single agent chemotherapy, which is the standard of care, has limited efficacy (response rate ≤12%) and short duration of response. Based on the encouraging anti-tumor activity of UpRi, UPLIFT was designed to be a single-arm Phase 2 registrational trial for UpRi in PROC. The UPLIFT cohort is enrolling patients with platinum-resistant high grade serous ovarian, fallopian tube and primary peritoneal cancer with up to 4 prior lines of therapy. Prior bevacizumab is required for patients with 1 or 2 prior lines of therapy but is not required for patients with 3–4 prior lines of therapy. Patients may enroll regardless of NaPi2b expression; ≤ Grade 2 peripheral neuropathy is permitted. Primary platinum refractory patients are excluded. UPLIFT will enroll approximately 180 patients globally, including approximately 100 patients with high NaPi2b expression. UpRi will be dosed intravenously at 36 mg/ m2 up to a maximum dose of ~80 mg every 4 weeks. Baseline tumor samples (fresh or archived) will be collected for central analysis of NaPi2b expression. The primary endpoint is ORR in patients with high NaPi2b expression. The cut-off for high NaPi2b expression is Tumor Proportion Score (TPS) ≥75, which was based on data from the Phase 1 expansion cohort. Secondary endpoints include ORR in the overall population, duration of response, and safety. This study is being conducted in collaboration with ENGOT (ENGOT-ov67) and GOG (GOG-3048). Patients will be enrolled globally. NCT03319628 This is a Trial in Progress; therefore, we do not have results/conclusions at this time. This is a Trial in Progress; therefore, we do not have results/conclusions at this time