tbuckley/cabot-search huggingface dataset:
Vaginal lacerations during laparoscopic hysterectomy for endometrial cancer and local recurrence risk.
Authors: Olivia Nicolais, Mackenzie Cummings, Mitchell Edelson, Lea Moukarzel, Nicholas Cardillo, Elizabeth Burton, Tommy Buchanan, Mark S. Shahin
Journal: Journal of Clinical Oncology (2024)

e17596 Background: Laparoscopic surgery offers equivalent oncologic outcomes as compared to open surgery, while causing lesser morbidity and resulting in a faster recovery. However, vaginal extraction of specimens may cause vaginal or perineal lacerations (VL). To date, no studies have specifically reported the impact of vaginal laceration on local recurrence after surgical treatment for endometrial cancer. The objective of this study is to assess local recurrence rates compared between cases with or without vaginal lacerations (NL). Methods: We identified all patients with endometrial cancer who underwent laparoscopic surgical management between 2014 and 2018. We assessed the rate of local recurrence between patients in VL and NL cohorts. The study included all histologic subtypes and stages. Patients with benign final pathology, cases of synchronous primaries or cases that required laparotomy for extraction were excluded. Results: Among the 540 endometrial cancer MIS cases, 338 were evaluable. There were 40 cases of vaginal laceration during specimen extraction. There was no significant difference in age, race, presence of LVSI, stage, grade, histology or use of vaginal brachytherapy between cohorts. Cases with vaginal lacerations were significantly associated with a higher median BMI of 33.6kg/m 2 (range 18.9-66) in the VL group as compared to 32.3kg/m 2 (range 19.1-66) in the NL group (p=0.03). Uterine size was greater in the laceration group (VL) with a median of 150.5 g (49 - 462g) versus 110g (33 – 573g) in the NL cohort (p &lt;0.01). The VL cohort was more likely to have received adjuvant treatment. Specifically external beam radiation therapy (EBRT) was administered 20% in the VL group versus 8.4% in the NL group (p = 0.02) and chemotherapy was used in 27.5% of the VL group versus 9.7% in the NL group (p &lt; 0.01). In early stage disease, more cases had non-endometrioid histology in the VL group (23% versus 11.5%, p=0.043) and had increased incidence of chemotherapy and radiation use as well (EBRT 5.6% vs 23% and chemotherapy 6.7% versus 23%, both with p= &lt;0.01). There were no cases of isolated vaginal recurrence (0/40) in the VL group as compared to an incidence of 2% (7/298) in the NL group with a relative risk of 0.48 (CI: 0.03-8.36, p=0.62). There were 4 cases of pelvic recurrence (4/40) in the VL group and 2 cases in the NL group (2/298) with a relative risk of 2.13 (CI: 0.46-9.89, p=0.34). Conclusions: In endometrial cancer cases, we did not observe a significantly increased risk of vaginal or pelvic recurrence after a vaginal laceration at the time of specimen removal. This could be attributed to the higher rate of non-endometrioid histology in early stage disease, which resulted in higher rates of adjuvant chemotherapy or radiation treatment.
Suction Thrombectomy and Pulmonary Artery Stenting for Pulmonary Embolism in a Single Lung Transplant
Authors: Jason Katz, Daniel Schimmel, Marysa Leya, Alan Betensley, Mrinalini Subramani, Catherine Myers, Rade Tomic, Chitaru Kurihara, Ambalavanan Arunachalam
Journal: American Journal of Respiratory and Critical Care Medicine (2024)
Identification of prognostic indicators and markers of endometrial carcinoma based on shared metabolism-related genes in gynecological tumors.
Authors: Liuqing Zheng, Yanwei Wang, Li Wang, Yiran Meng
Journal: Journal of Clinical Oncology (2024)

e17589 Background: Aberrant metabolism is a major characteristic of cancer and it is important to determine whether there is a common metabolic genetic signature among gynecological cancers. Endometrial cancer, as one of the gynecological tumors, has shown increasing morbidity and mortality rates annually. Investigating shared metabolic molecular markers in gynecological tumors can enhance our understanding of endometrial cancer. Methods: Transcriptome data for gynecological tumors, including ovarian cancer (OV), endometrial cancer (UCEC) and cervical cancer (CESC) were obtained from The Cancer Genome Atlas database. Transcriptome data for normal cervix uteri, uterus and ovary tissues were downloaded from the Genotype-Tissue Expression Project. Metabolism-related gene sets were sourced from the Kyoto Encyclopedia of Genes and Genomes for subsequent analysis (KEGG) for subsequent analysis. Weighted gene co-expression network analysis (WGCNA) was employed to identify gene modules associated with OV, UCEC and CESC. The intersection of three cancer-related modules and metabolism-related gene sets yielded shared SMRGs (Shared Metabolism-Related Genes). UCEC samples were randomly divided into training set and testing set by caret R package in a 5:5 ratio. A risk model based on SMRGs, capable of predicting the overall survival (OS) of UCEC patients, was constructed using LASSO regression and Cox regression analyses. Results: A total of 463 genes were identified as sharing SMRGs through the intersection of modules. And 81 genes associated with OS was further selected by Univariate Cox regression analysis combined with expression and clinical data. Eventually, 8 genes (CYP11B1, SRD5A1, OTC, ACACB, ASS1, ALG3, PLA2G4F and POC1B-GALNT4) were screened out by LASSO regression analysis to construct the prognostic characteristics. The training set was divided into high and low-risk groups based on the computed risk threshold. Kaplan-Meier analysis demonstrated that patients in the low-risk group exhibited better prognosis. Similar differential survival results were observed in the testing and entire sets. Furthermore, analysis of immune and stromal infiltrates indicated increased infiltration of CD8+ T cells in the low-risk group, and PLA2G4F was identified as the core gene. The expression level of PLA2G4F increased with the progression of UCEC and was closely associated with various immune checkpoint factors, including CD48, HAVCR2, CD86, TIGIT, CTLA4 and BTLA. Conclusions: This study established a shared metabolism-related gene prognostic model applicable to gynecological cancers and analyzed its potential role in the treatment and prognosis assessment of endometrial cancer. Additionally, PLA2G4F was identified as a potential immune-related biomarker for UCEC patients.
Demographic factors influencing hysterectomy approaches (with vs. without removal of tubes and/or ovaries): An NCDB review.
Authors: Kristine Au, Caitlyn Voth, Darby Keirns, Peter T. Silberstein
Journal: Journal of Clinical Oncology (2024)

e17578 Background: Endometrial cancer is the most common cancer of the female reproductive organs in the United States, and surgery involving the removal of the uterus, cervix, and ovaries (total hysterectomy) is the most common treatment. However, some women may have their uterus removed with sparing of the ovaries, resulting in the prevention of menopause but an increased incidence of cancer recurrence. Given the pivotal role of surgical outcomes, it is important to examine the variations in treatment approaches – specifically, the choice between total hysterectomy with and without removal of the tubes and/or ovaries – across different demographic groups. Methods: Patients with endometrial cancer were selected from the National Cancer Database (NCDB) and 19,147 patients were identified between 2004 and 2020. We compared the demographic variables of patients who had a total hysterectomy with and without removal of tubes and ovaries. Descriptive statistics, multivariate, and chi-square analyses on SPSS version 28 was used for all analyses; P &lt; 0.05 was considered significant. Results: Black patients with endometrial cancer were 26% less likely to have a total hysterectomy with the removal of tubes and/or ovaries compared to white patients. Conversely, no significant difference was observed in the choice of surgical approach between Hispanic and non-Hispanic patients. A median household income of $74,063 were 97% less likely to have a total hysterectomy with removal of tubes and/ovaries compared to patients with a median household income of less than $46,277. Patients with insurance, including private, Medicaid, Medicare, or other government insurance did not have a significantly different surgical approach than those without insurance. Furthermore, patients living in more educated areas (where &lt;5% of adults lacked a high school degree) were 29% more likely to receive a total hysterectomy with removal of tubes and/or ovaries compared to less educated areas (where &gt;15.3% of adults lacked a high school degree). Conclusions: This study highlights significant determinants that influence the decision to remove the tubes and/or ovaries during a total hysterectomy for endometrial cancer, with emphasis on race, education, and income. Significant implications with removal of ovaries and/or tubes include changes in a woman’s hormonal balance, infertility, and increased risk of further diseases. Understanding and recognizing these determinants within the context of endometrial cancer treatment can contribute to improved patient outcomes, a reduced risk of ovarian cancer and associated complications, and an improvement in overall quality of life. By acknowledging the versatile nature of this decision, healthcare providers can better individualize treatment plans, ultimately striving for favorable long-term health and well-being outcomes for their patients.
Developing machine learning–based prognostic models for gestational choriocarcinoma: Insights into treatment efficacy and patient survival.
Authors: Mustafa Alshwayyat, Sakhr Abdulsalam Alshwayyat, Haya Kamal, Tala Abdulsalam Alshwayyat, Abdalwahab Alenezy
Journal: Journal of Clinical Oncology (2024)

e17607 Background: Gestational Choriocarcinoma (GCC) is a highly aggressive tumor derived from syncytiotrophoblasts. There is currently controversy surrounding the initiation of chemotherapy for patients with GCC. We aimed to investigate the influence of chemotherapy on survival rates and develop machine-learning-based prognostic models for GCC patients to improve treatment decisions and personalized medicine. Methods: Data were obtained from the Surveillance, Epidemiology, and End Results database (2000–2020). Patients who met any of the following criteria were excluded: diagnosis not confirmed by histology, previous history of cancer or with other concurrent malignancies, and unknown data. To identify prognostic variables, we conducted Cox regression analysis and constructed prognostic models using machine learning (ML) algorithms to predict the 5-year survival. Patient records were randomly divided into training (70 %) and validation (30 %) sets. A validation method incorporating the area under the curve (AUC) of the receiver operating characteristic curve was used to validate the accuracy and reliability of the ML models. We also investigated the role of multiple therapeutic options using Kaplan-Meier survival analysis. Results: This study included 732 patients, of whom 283 received chemotherapy, 116 underwent surgery alone, and 333 underwent both surgery and chemotherapy. Most patients (54.5%) were aged 30 years or older, with a median age of 32 years. The largest racial group was white, comprising 66.4% of cases, followed by black (16.7 %). Furthermore, most cases were localized (n=262), and only 13% presented with stage IV disease and 44.3% with metastasis. Survival analysis showed no significant differences in survival between the treatment modalities. Multivariate Cox regression analysis identified older age, unmarried status, and AJCC stage II as significant prognostic factors. The random forest classifier (RFC) and K-Nearest Neighbors (KNN) were the most accurate ML models, with the AJCC stage, race, and SEER stage as key factors. Performance metrics for all ML algorithms are summarized in the Table. Conclusions: Our study provides a novel and practical tool for GCC prognosis and management. Although our tool offers a valuable resource for personalized clinical decisions, further research is needed to better understand the role of chemotherapy in GCC treatment and its impact on patient outcomes. [Table: see text]
Species delimitation 4.0: integrative taxonomy meets artificial intelligence
Authors: Kevin Karbstein, Lara Kösters, Ladislav Hodač, Martin Hofmann, Elvira Hörandl, Salvatore Tomasello, Natascha D. Wagner, Brent C. Emerson, Dirk C. Albach, Stefan Scheu, Sven Bradler, Jan de Vries, Iker Irisarri, He Li, Pamela Soltis, Patrick Mäder, Jana Wäldchen
Journal: Trends in Ecology & Evolution (2024)

Although species are central units for biological research, recent findings in genomics are raising awareness that what we call species can be ill-founded entities due to solely morphology-based, regional species descriptions. This particularly applies to groups characterized by intricate evolutionary processes such as hybridization, polyploidy, or asexuality. Here, challenges of current integrative taxonomy (genetics/genomics + morphology + ecology, etc.) become apparent: different favored species concepts, lack of universal characters/markers, missing appropriate analytical tools for intricate evolutionary processes, and highly subjective ranking and fusion of datasets. Now, integrative taxonomy combined with artificial intelligence under a unified species concept can enable automated feature learning and data integration, and thus reduce subjectivity in species delimitation. This approach will likely accelerate revising and unraveling eukaryotic biodiversity.
Assessing the risk of uterine serous carcinoma in survivors of triple-negative breast cancer: Is BRCA1 the link?
Authors: William Manning, Siguo Li, Amy Bregar, Allison Ann Gockley, Mark C. Clapp, Roni Nitecki Wilke, Shayan Dioun, Jose Alejandro Rauh-Hain, Alexander Melamed
Journal: Journal of Clinical Oncology (2024)

5602 Background: Uterine serous carcinoma (USC) is a rare and deadly form of endometrial cancer. It is unclear whether BRCA1 pathogenic variants (PV) are associated with an increased risk of USC. Because patients with triple-negative breast cancer (TNBC) have a high prevalence of BRCA1 PV, we hypothesize that if BRCA1 PV are causally related to the development of USC, survivors of TNBC would be at an increased risk of subsequent USC. This cohort study compares USC incidence rates in TNBC survivors with population-based controls. We estimate the magnitude of the association between BRCA1PV and USC that must exist if the excess risk of USC among TNBC survivors is attributable to differences in the prevalence of BRCA1 PV between TNBC survivors and controls. Methods: Using the Surveillance, Epidemiology, and End Results 17 registry data, we identified patients with TNBC diagnosed between Jan 2010 and Dec 2020 and population-based controls. Due to limited data on BRCA1 PV prevalence among non-white TNBC survivors, we restricted this analysis to White women. We estimated the probability of having a BRCA1 PV based on reported age-based prevalence for the general population and cohorts of patients with TNBC. We fit Poisson regression models to estimate age-specific incidence rates and age-adjusted relative risk of USC among TNBC survivors compared with controls and to estimate the relative risk of USC among BRCA1 PV carriers. Results: We identified 48,082 patients with TNBC accounting for 202,074 person-years. The median age at diagnosis was 61 years. The control population contributed 215,813,524 person-years of follow-up. There were 19 incident diagnoses of USC among TNBC survivors and 8,056 among controls, corresponding to crude rates of 9.4 and 3.7 cases per 100,000 person-years, respectively (Figure). After adjusting for age, TNBC survivors had a 59% increase in rate of developing USC (incidence rate ratio 1.59; 95% CI 1.02 to 2.50) compared to controls. We attributed the excess risk of USC among TNBC survivors to differences in BRCA1 PV prevalence. Given this, we estimated that BRCA1 PV was associated with an approximately 30-fold increase in the incidence of TNBC (95% CI 1.1 to 790). Conclusions: Survivors of TNBC, a population with a high prevalence of BRCA1 mutations, are at increased risk of USC compared with population-matched controls. This observation is concordant with an association between pathologic BRCA1 mutations and USC.
Prognostic value of PORTEC-3 molecular markers by disease risk in a real-world early endometrial cancer cohort.
Authors: Jessica Dow, Sahiti Kolli, Brad Karalius, Jessica Shami, Sajan Khosla, David Roy, Ingrid A. Mayer, Sara Dempster
Journal: Journal of Clinical Oncology (2024)

5604 Background: Molecular classification of endometrial cancer (EC) proposed by The Cancer Genome Atlas in 2013 has improved prognostic assessment of patients. PORTEC-3 assessed these molecular markers in early-stage high risk patients. We examine the prognostic value of these markers in a real-world data (RWD) cohort of early-stage high risk patients and extend the analysis to intermediate and low risk patients to inform treatment decisions across disease risk levels. Methods: We performed a retrospective study (2016-2022) of EC patients from the Tempus de-identified, multimodal RW database. Stage I-III patients who received total hysterectomy with bilateral salpingo-oophorectomy and next generation sequencing (NGS) Tempus xT assays were stratified into high, intermediate, and low risk disease levels based on tumor characterization and categorized into POLE mutated (POLEm), mismatch repair-deficient (dMMR), p53-abnormal (p53abn), or no specific molecular profile (NSMP) PORTEC-3 subtypes. Recurrence-free survival (RFS), defined as time from surgery to earliest disease recurrence, progression, metastasis or death, was assessed using Kaplan-Meier methods for the combination of risk level and molecular subtype. We compared RFS trends across molecular subtypes at 5-years in PORTEC-3 and 18-months in RWD due to limited follow-up. Results: Of the 740 eligible RWD patients, 546 (74%), 110 (15%) and 84 (11%) were high, intermediate, and low risk and 286 (39%), 250 (34%), 180 (24%) and 24 (3%) were P53abn, NSMP, dMMR and POLEm, respectively. Similar to RFS trends at 5 years in PORTEC-3, the p53abn subtype consistently had the lowest 18-month RFS, although the degree of separation from other subtypes varied across risk levels. NSMP and dMMR subtypes had 18-month RFS within 4% of each other for high and low risk levels, consistent with PORTEC-3. The POLEm subtype had 100% 18-month RFS across risk levels, but low prevalence. Conclusions: Marker prognostic ranking was consistent between the PORTEC-3 high risk cohort and all risk levels in RWD despite absolute RFS differences likely due to differences in baseline characteristics and outcome assessments. The consistent poor prognosis of p53abn patients, good prognosis of POLEm albeit with limited power, and moderate prognosis of NSMP and dMMR patients in RWD support use of these markers to inform treatment decisions across disease risk levels in an early EC setting. [Table: see text]
Cadonilimab plus lenvatinib in patients with advanced endometrial cancer: A multicenter, single-arm, phase II trial.
Authors: Chunyan Lan, Xielan Yang, Jing Zhao, Min Zheng, Fan Yang, Zhiwen Xie, Xiaoliu Wu, Hongying Yang, Wenyan Wang, Xin Huang
Journal: Journal of Clinical Oncology (2024)

5600 Background: Lenvatinib plus pembrolizumab is the standard treatment for patients with advanced endometrial cancer with mismatch repair-proficient (pMMR) disease who had disease progression after the receipt of prior systemic platinum-based therapy. Cadonilimab is a PD-1/CTLA-4 bi-specific antibody. We aimed to assess the combination of cadonilimab and lenvatinib in patients with advanced endometrial cancer who had previously received at least one platinum-based chemotherapy. Methods: In this phase II study with a safety-run in, eligible patients were aged 18 years or older with advanced endometrial cancer of any histologic subtype, except sarcoma, progressed after at least one prior platinum-based chemotherapy, had an Eastern Cooperative Oncology Group performance status of 0 or 1. In the safety run-in period, a 3+3 dose de-escalation design was used to determine the maximum tolerated dose (MTD) and recommended phase II dose (RP2D) of lenvatinib (16 mg or 12 mg once daily) combined with cadonilimab 10 mg/kg every 3 weeks. After the completion of safety run-in period, the phase II cohort at the RP2D will open. Approximately 29 patients are planned to receive treatment at the RP2D. The primary endpoint was objective response rate (ORR) at the RP2D. Key secondary endpoints included disease control rate (DCR), duration of response (DOR), progression-free survival (PFS), overall survival (OS), and safety. Results: Between 8 May 2023 and 18 December 2023, 24 patients were enrolled. As of 31 December 2023, enrollment was ongoing. No DLTs were observed during the safety run-in period. The RP2D of lenvatinib is 16 mg once daily. Among 21 efficacy-evaluable patients, the ORR was 52.4% (95% CI: 29.1–75.7), and the DCR was 90.5% (95% CI: 69.6–98.8). The Medians for DOR, PFS, and OS were not reached. Grade 3–4 treatment-related adverse events included increased ALT (2 [8.3%]), increased AST (1 [4.2%]), increased creatine phosphokinase (1 [4.2%]), hypertension (1 [4.2%]), and intestinal perforation (1 [4.2%]). Conclusions: Cadonilimab plus lenvatinib showed promising antitumor activity in patients with advanced endometrial cancer who have experienced disease progression after prior systemic platinum-based therapy. The combination therapy had a favorable and manageable safety profile. Clinical trial information: NCT05824481 . [Table: see text]