Genes noted to be altered in DES9525 after CTNNB1 knockdown as identified by RNA-seq. Fold change is relative to expression in cells treated with scramble control.

Key Clinical MessageAlthough endometriosis is a common condition, both extrapelvic endometriosis and endometriosis associated malignancy (EAM) are rare. We describe the first reported case of a patient with Müllerian‐type carcinosarcoma arising in gastric endometriosis.

Gene set enrichment analysis of pathways altered in desmoid cells after CTNNB1 knockdown

Genes with altered expression in DES9525 cells after treatment with PDGF-BB as compared to untreated cells as determined by RNA-seq.

BACKGROUND:Across surgery, marginalized individuals experience worse postoperative outcomes. These disparities stem from the interplay between multiple factors. METHODS:We introduced a novel framework to assess the role of barriers to access and bias in surgical complications (the uChicago Health Inequity Classification System, CHI-CS) in the setting of morbidity and mortality conference and assessed impact through pre and post implementation surveys. RESULTS:Access and bias were related to surgical complications in 14 ​% of cases. 97 ​% reported enhanced M&M presentations with the grading system, and 47 ​% reported a change in decision-making or practice style. Although post-implementation response rate was low, there were improvements in self-reported confidence and comfort in recognizing and discussing these issues. CONCLUSIONS:Implementation of the CHI-CS framework to discuss bias and access to care positively impacted the way providers view, discuss, and process health inequities.

Gene set enrichment analysis performed on RNA-seq from pre-treatment biopsies taken from patients on the placebo arm of ALLIANCE A091105.

CTNNB1 mutations detected in pre- and post-treatment biopsies from patients on ALLIANCE A091105.

Genes included in HIF1- and angiogenesis-related pathways and used for supervised clustering of desmoid tumors. Pathways in which each gene are included are annotated in the table.

Background: Pancreatic cancer remains highly lethal, and resection represents the only chance for cure. Although patients are counseled regarding short-term (0-3 months) mortality, little is known about mortality 3-6 months (intermediate-term) following surgery. We assessed predictors of intermediate-term mortality, evaluated hospital-level variation, and developed a nomogram to predict intermediate-term mortality risk. Methods: Patients undergoing pancreatic cancer resection were identified from the National Cancer Database (2010-2020). Multivariable logistic regression identified predictors of intermediate-term mortality and assessed differences between short-term and intermediate-term mortality. Multinomial regression grouped by intermediate-term mortality quartiles evaluated hospital-level variation. A neural network model was constructed to predict intermediate-term mortality risk. All statistical tests were 2-sided. Results: Of 45 297 patients, 3974 (8.9%) died within 6 months of surgery of which 2216 (5.1%) were intermediate-term. Intermediate-term mortality was associated with increasing T category, positive nodes, lack of systemic therapy, and positive margins (all P < .05) compared with survival beyond 6 months. Compared with short-term mortality, intermediate-term mortality was associated with treatment at high-volume hospitals, positive nodes, neoadjuvant systemic therapy, adjuvant radiotherapy, and positive margins (all P < .05). Median intermediate-term mortality rate per hospital was 4.5% (interquartile range [IQR] = 2.6-6.5). Highest quartile hospitals had decreased odds of treatment with neoadjuvant systemic therapy, neoadjuvant radiotherapy, and adjuvant radiotherapy (all P < .05). The neural network nomogram was highly accurate (accuracy = 0.9499; area under the receiver operating characteristics curve = 0.7531) in predicting individualized intermediate-term mortality risk. Conclusion: Nearly 10% of patients undergoing pancreatectomy for cancer died within 6 months, of which one-half occurred in the intermediate term. These data have real-world implications to improve shared decision making when discussing curative-intent pancreatectomy.

AbstractPurpose: This study sought to identify β-catenin targets that regulate desmoid oncogenesis and determine whether external signaling pathways, particularly those inhibited by sorafenib (e.g., PDGFRβ), affect these targets to alter natural history or treatment response in patients. Experimental Design: In vitro experiments utilized primary desmoid cell lines to examine regulation of β-catenin targets. Relevance of results was assessed in vivo using Alliance trial A091105 correlative biopsies. Results: CTNNB1 knockdown inhibited hypoxia-regulated gene expression in vitro and reduced levels of HIF1α protein. ChIP-seq identified ABL1 as a β-catenin transcriptional target that modulated HIF1α and desmoid cell proliferation. Abrogation of either CTNNB1 or HIF1A inhibited desmoid cell–induced VEGFR2 phosphorylation and tube formation in endothelial cell co-cultures. Sorafenib inhibited this activity directly but also reduced HIF1α protein expression and c-Abl activity while inhibiting PDGFRβ signaling in desmoid cells. Conversely, c-Abl activity and desmoid cell proliferation were positively regulated by PDGF-BB. Reduction in PDGFRβ and c-Abl phosphorylation was commonly observed in biopsy samples from patients after treatment with sorafenib; markers of PDGFRβ/c-Abl pathway activation in baseline samples were associated with tumor progression in patients on the placebo arm and response to sorafenib in patients receiving treatment. Conclusions: The β-catenin transcriptional target ABL1 is necessary for proliferation and maintenance of HIF1α in desmoid cells. Regulation of c-Abl activity by PDGF signaling and targeted therapies modulates desmoid cell proliferation, thereby suggesting a reason for variable biologic behavior between tumors, a mechanism for sorafenib activity in desmoids, and markers predictive of outcome in patients.

Supplemental Methods Tables, Supplemental Methods Figures, Supplemental Figures

Legends to Supplementary Tables S1-S4 and Supplementary Figures S1-S8

Supplementary Tables S1-S4 show primers and gRNAs used in CRISPR/cas9 experiments and differential expression of 14q32 microRNAs in DKO mice and after treatment by 5-Aza-dC.

Background:. Surgeon productivity is measured in relative value units (RVUs). The feasibility of attaining RVU productivity targets requires surgeons to have enough allocated block time to generate RVUs. However, it is unknown how much block time is required for surgeons to attain specific RVU targets. We aimed to estimate the effect of surgeon and practice environment characteristics (SPECs) on block time needed to attain fixed RVU targets. Methods:. We computationally simulated individual surgeons’ annual caseloads under a variety of SPECs in the following way. First, empirical case data were sampled from ACS NSQIP in accordance with surgeon specialty, case-mix complexity, and RVU target. Surgeons’ operating schedules were then constructed according to the block length, turnover time, and scheduling flexibility of the practice environment. These 6 SPECs were concurrently varied over their ranges for a 6-way sensitivity analysis. Results:. Annual operating schedules for 60,000,000 surgeons were simulated. The number of blocks required to attain RVU targets varied significantly with surgeon specialty and increased with increased case-mix complexity, increased turnover time, and decreased scheduling flexibility. Intraspecialty variation in block requirement with variation in environmental characteristics exceeded interspecialty variation with fixed environmental characteristics. Multivariate linear models predicted block utilization across surgical specialties with consideration for the stated factors. An online tool is shared with which to apply these results to one’s particular practice. Conclusions:. Block time required to attain RVU targets varies widely with SPECs; intraspecialty variation exceeds interspecialty variation. The feasibility of attaining RVU targets requires alignment between targets and allocated operating time with consideration for surgical specialty and other practice conditions.

Failure of DNMT 1/3B double-knockout cells to produce liver metastases.

Supplemental Figure S1. Comparison of clonogenic survival fractions of various cancer cell lines after treatment with SAR302503 and Ruxolitinib. Supplemental Figure S2. KRAS mutation by treatment sensitivities in NSCLC cell lines. Supplementary Figure S3. The response of NCIH1944 xenografts to ionizing radiation. Supplemental Figure S4. Top-ranked pathways in SAR sensitive NSCLC cell lines. Supplemental Figure S5. Cancer growth and proliferation gene network in SAR-sensitive NSCLC. Supplemental Figure S6. ROC analysis of SAR sensitivity by TSP-IRDS scores. Supplemental Figure S7. Distribution of TSP-IRDS scores in clinical NSCLCs. Supplemental Figure S8. TSP-IRDS predicts survival in clinical NSCLC. Supplemental Figure S9. TSP-IRDS scores predict the benefit of adjuvant cisplatin-based chemotherapy in clinical NSCLC. Supplementary Figure and Table Legends

Importance:Personalized treatment approaches for patients with oligometastatic colorectal liver metastases are critically needed. We previously defined 3 biologically distinct molecular subtypes of colorectal liver metastases: (1) canonical, (2) immune, and (3) stromal. Objective:To independently validate these molecular subtypes in the phase 3 New EPOC randomized clinical trial. Design, Setting, and Participants:This retrospective secondary analysis of the phase 3 New EPOC randomized clinical trial included a bi-institutional discovery cohort and multi-institutional validation cohort. The discovery cohort comprised patients who underwent hepatic resection for limited colorectal liver metastases (98% received perioperative chemotherapy) from May 31, 1994, to August 14, 2012. The validation cohort comprised patients who underwent hepatic resection for liver metastases with perioperative chemotherapy (fluorouracil, oxaliplatin, and irinotecan based) with or without cetuximab from February 26, 2007, to November 1, 2012. Data were analyzed from January 18 to December 10, 2021. Interventions:Resected metastases underwent RNA sequencing and microRNA (miRNA) profiling in the discovery cohort and messenger RNA and miRNA profiling with microarray in the validation cohort. Main Outcomes and Measures:A 31-feature (24 messenger RNAs and 7 miRNAs) neural network classifier was trained to predict molecular subtypes in the discovery cohort and applied to the validation cohort. Integrated clinical-molecular risk groups were designated based on molecular subtypes and the clinical risk score. The unique biological phenotype of each molecular subtype was validated using gene set enrichment analyses and immune deconvolution. The primary clinical end points were progression-free survival (PFS) and overall survival (OS). Results:A total of 240 patients were included (mean [range] age, 63.0 [56.3-68.0] years; 151 [63%] male), with 93 in the discovery cohort and 147 in the validation cohort. In the validation cohort, 73 (50%), 28 (19%), and 46 (31%) patients were classified as having canonical, immune, and stromal metastases, respectively. The biological phenotype of each subtype was concordant with the discovery cohort. The immune subtype (best prognosis) demonstrated 5-year PFS of 43% (95% CI, 25%-60%; hazard ratio [HR], 0.37; 95% CI, 0.20-0.68) and OS of 63% (95% CI, 40%-79%; HR, 0.38; 95% CI, 0.17-0.86), which was statistically significantly higher than the canonical subtype (worst prognosis) at 14% (95% CI, 7%-23%) and 43% (95% CI, 32%-55%), respectively. Adding molecular subtypes to the clinical risk score improved prediction (the Gönen and Heller K for discrimination) from 0.55 (95% CI, 0.49-0.61) to 0.62 (95% CI, 0.57-0.67) for PFS and 0.59 (95% CI, 0.52-0.66) to 0.63 (95% CI, 0.56-0.70) for OS. The low-risk integrated group demonstrated 5-year PFS of 44% (95% CI, 20%-66%; HR, 0.38; 95% CI, 0.19-0.76) and OS of 78% (95% CI, 44%-93%; HR, 0.26; 95% CI, 0.08-0.84), superior to the high-risk group at 16% (95% CI, 10%-24%) and 43% (95% CI, 32%-52%), respectively. Conclusions and Relevance:In this prognostic study, biologically derived colorectal liver metastasis molecular subtypes and integrated clinical-molecular risk groups were highly prognostic. This novel molecular classification warrants further study as a possible predictive biomarker for personalized systemic treatment for colorectal liver metastases. Trial Registration:isrctn.org Identifier: ISRCTN22944367.

Supplemental Figures S5-S6. Distribution of CpG sites, transcription start site and methylation-dependent CTCF binding region in DLK1-MEG9 region.