High copy number endometrial cancers (HCNEC) are dominated by excessive duplications scattered across the genome, termed here as the HyperDuplication GenomoPhenotype (HDGP). Although correlated with cancer progression, its biological significance and implications for therapy have not yet been established. We identified locations and sizes of duplications in 171 endometrial cancer cases and designated 71 HCNEC cases as HDGP. We also investigated the response to the pan-ERBB inhibitor afatinib in a subset of HDGP-EC cases with ERBB2/ERBB3 duplications using a patient-derived three-dimensional culture model. Our analysis demonstrates that beyond tandem duplications there is a more general pattern involving coordinated duplication of multiple distant regions of the genome, demonstrating preferential selectivity to over-expressed potential oncogenes within a broad network. This suggests that HDGP increases tumor fitness and resistance to therapy by perturbing important gene networks in concert rather than only driver genes, suggesting a mechanistic basis for the ineffectiveness of targeted drugs in these patients and highlighting the need for combination therapies in these highly aggressive cases.
Abstract Repeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects regression models were used to perform statistical modeling of tumor growth data. Biologically plausible structures for the covariation between repeated tumor burden measurements are explained. Graphical, tabular, and information criteria tools useful for choosing the mean model functional form and covariation structure are demonstrated in a Case Study of five PDX models comparing cancer treatments. Power calculations were performed via simulation. Linear mixed effects regression models applied to the natural log scale were shown to describe the observed data well. A straight growth function fit well for two PDX models. Three PDX models required quadratic or cubic polynomial (time squared or cubed) terms to describe delayed tumor regression or initial tumor growth followed by regression. Spatial(power), spatial(power) + RE, and RE covariance structures were found to be reasonable. Statistical power is shown as a function of sample size for different levels of variation. Linear mixed effects regression models provide a unified and flexible framework for analysis of PDX repeated measures data, use all available data, and allow estimation of tumor doubling time.
Targeting glutamine metabolism has emerged as a novel therapeutic strategy for several human cancers, including ovarian cancer. The primary target of this approach is the kidney isoform of glutaminase, glutaminase 1 (GLS1), a key enzyme in glutamine metabolism that is overexpressed in several human cancers. A first-in-class inhibitor of GLS1, called CB839 (Telaglenastat), has been investigated in several clinical trials, with promising results. The first clinical trial of CB839 in platinum-resistant patients with ovarian cancer is forthcoming. ARID1A-mutated ovarian clear cell carcinoma (OCCC) is a relatively indolent and chemoresistant ovarian cancer histotype. In OCCC-derived cells ARID1A simultaneously drives GLS1 expression and metabolism reprograming. In ARID1A-mutated OCCC-derived mouse models, loss of ARID1A corresponds to GLS1 upregulation and increases sensitivity to GLS1 inhibition. Thus, targeting of GLS1 with CB839 has been suggested as a targeted approach for patients with OCCC with tumors harboring ARID1A mutations. Here, we investigated whether GLS1 is differentially expressed between patients with OCCC whose tumors are ARID1A positive and patients whose tumors are ARID1A negative. In clinical specimens of OCCC, we found that GLS1 overexpression was not correlated with ARID1A loss. In addition, GLS1 overexpression was associated with better clinical outcomes. Our findings have implications for human trials using experimental therapeutics targeting GLS1. Significance: GLS1 differential expression in patients with OCCC with or without ARID1A mutations is significant because a clinical trial with a GLS1 inhibitor is forthcoming. Tumors without ARID1A have low levels of GLS1 and GLS1 expression is associated to better outcome. Thus, blockade of GLS1 could be counterproductive for patients with OCCC.
To identify high-risk disease in clinicopathologic low-risk endometrial cancer (EC) with high microsatellite instability (MSI-H) or no specific molecular profile (NSMP) and therapeutic insensitivity in clinicopathologic high-risk MSI-H/NSMP EC.We searched The Cancer Genome Atlas for DNA sequencing, RNA expression, and surveillance data regarding MSI-H/NSMP EC. We used a molecular classification system of E2F1 and CCNA2 expression and sequence variations in POLE, PPP2R1A, or FBXW7 (ECPPF) to prognostically stratify MSI-H/NSMP ECs. Clinical outcomes were annotated after integrating ECPPF and sequence variations in homologous recombination (HR) genes.Data were available for 239 patients with EC, which included 58 MSI-H and 89 NSMP cases. ECPPF effectively stratified MSI-H/NSMP EC into distinct molecular groups with prognostic implications: molecular low risk (MLR), with low CCNA2 and E2F1 expression, and molecular high risk (MHR), with high CCNA2 and E2F1 expression and/or PPP2R1A and/or FBXW7 variants. The 3-year disease-free survival (DFS) rate was 43.8% in the MHR group with clinicopathologic low-risk indicators and 93.9% in the MLR group (P<.001). In the MHR group, wild-type HR genes were present in 28% of cases but in 81% of documented recurrences. The 3-year DFS rate in patients with MSI-H/NSMP EC with clinicopathologic high-risk indicators was significantly higher in the MLR (94.1%) and MHR/HR variant gene (88.9%) groups than in the MHR/HR wild-type gene group (50.3%, P<.001).ECPPF may resolve prognostic challenges for MSI-H/NSMP EC by identifying occult high-risk disease in EC with clinicopathologic low-risk indicators and therapeutic insensitivity in EC with clinicopathologic high-risk indicators.
The goal of this study was to evaluate the depth of myometrial invasion as a predictor of distant recurrence in patients with node-negative stage IB endometrioid endometrial cancer.
During the past decade, the age-adjusted mortality rate for endometrial cancer (EC) increased 1.9% annually with TP53 mutant ( TP53 -mu) EC disproportionally represented in advanced disease and deaths. Therefore, we aimed to assess pivotal molecular parameters that differentiate clinical outcomes in high- and low-risk EC. Using the Cancer Genome Atlas, we analyzed EC specimens with available DNA sequences and quantitative gene-specific RNA expression data. After polymerase ɛ ( POLE )-mutant specimens were excluded, differential gene-specific mutations and mRNA expressions were annotated and integrated. Consequent to TP53 -mu failure to induce p21, derepression of multiple oncogenes harboring promoter p21 repressive sites was observed, including CCNA2 and FOXM1 ( P < .001 compared with TP53 wild type [ TP53 -wt]). TP53 -wt EC with high CCNA2 expression ( CCNA2 -H) had a targeted transcriptomic profile similar to that of TP53 -mu EC, suggesting CCNA2 is a seminal determinant for both TP53 -wt and TP53 -mu EC. CCNA2 enhances E2F1 function, upregulating FOXM1 and CIP2A , as observed in TP53 -mu and CCNA2 -H TP53 -wt EC ( P < .001). CIP2A inhibits protein phosphatase 2A, leading to AKT inactivation of GSK3β and restricted oncoprotein degradation; PPP2R1A and FBXW7 mutations yield similar results. Upregulation of FOXM1 and failed degradation of FOXM1 is evidenced by marked upregulation of multiple homologous recombination genes ( P < .001). Integrating these molecular aberrations generated a molecular biomarker panel with significant prognostic discrimination ( P = 5.8×10 −7 ); adjusting for age, histology, grade, myometrial invasion, TP53 status, and stage, only CCNA2 -H/ E2F1 -H ( P = .0003), FBXW7 -mu/ PPP2R1A -mu ( P = .0002), and stage ( P = .017) were significant. The generated prognostic molecular classification system identifies dissimilar signaling aberrations potentially amenable to targetable therapeutic options.
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