Faculty Bibliography

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

The Cancer Genome Atlas publication first described the genomic landscape of endometrial cancer and characterized these cancers into four molecular subtypes with different prognoses. The Proactive Molecular Classifier for Endometrial Cancer was developed to more easily and inexpensively classify endometrial cancers into four similar molecular subtypes which are termed POLE, mismatch repair deficient, p53 abnormal and no specific molecular profile. Beyond these four subtypes, other molecular biomarkers may influence clinical behavior and response to targeted therapies and include beta-catenin, Her2 amplification, PI3K/mTOR/AKT alterations, L1CAM, hormone receptor expression, tumor mutational burden, and ARID1A. There are numerous clinical trials exploring treatment escalation and de-escalation within the four molecular subtypes as well as matching targeted therapies to specific mutational or biomarker profiles. All endometrial cancers should undergo basic molecular classification that includes assessment of mismatch repair status. POLE and p53 status are prognostic and may become actionable in the future. Clinicians who treat patients with endometrial cancer should understand the role of molecular classification in guiding treatment. The goal of this practice statement is to guide appropriate testing, interpretation, and application of molecular information in endometrial cancer.

OBJECTIVE:Treatment options and associated biomarkers for advanced and recurrent disease are limited. Endometrial cancers (ECs) with CTNNB1 exon 3 mutations appear to have preferential response to bevacizumab, an anti-angiogenesis treatment, though the mechanism of action is unknown. We aim to identify mediators of bevacizumab-responsive endometrial cancers. METHODS:We analyzed RNA expression from TCGA and protein expression from CPTAC to identify likely targets for β-catenin overactivity. We then transiently and stably overexpressed β-catenin in EC cells to confirm the results suggested by our in silico analysis. We performed corroborative experiments by silencing CTNNB1 in mutated cell lines to demonstrate functional specificity. We implanted transduced cells into xenograft models to study microvessel density. RESULTS:CTNNB1-mutated ECs were associated with increased β-catenin and MMP7 protein abundance (P < 0.001), but not VEGF-A protein abundance. Overexpressing β-catenin in EC cells did not increase VEGF-A abundance but did increase expression and secretion of MMP7 (P < 0.03). Silencing CTNNB1 in CTNNB1-mutated cells decreased MMP7 gene expression in EC (P < 0.0001). Microvessel density was not increased. CONCLUSIONS:These data provide a mechanistic understanding for bevacizumab-response in CTNNB1-mutated ECs demonstrated in GOG-86P. We hypothesize that overexpressed and secreted MMP7 potentially digests VEGFR-1, releasing VEGF-A, and increasing its availability. These activities may drive the formation of permeable vessels, which contributes to tumor progression, metastasis, and immune suppression. This mechanism is unique to EC and advocates for further clinical trials evaluating this treatment-related biomarker.

Transcriptional heterogeneity among malignant cells of a tumor has been studied in individual cancer types and shown to be organized into cancer cell states; however, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Here, we perform a pan-cancer single-cell RNA-sequencing analysis across 15 cancer types and identify a catalog of gene modules whose expression defines recurrent cancer cell states including 'stress', 'interferon response', 'epithelial-mesenchymal transition', 'metal response', 'basal' and 'ciliated'. Spatial transcriptomic analysis linked the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Using mouse models, we further found that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. Our work provides a framework for studying how cancer cell states interact with the tumor microenvironment to form organized systems capable of immune evasion, drug resistance and metastasis.

PURPOSE/OBJECTIVE:-truncating mutations. Conversely, the molecular underpinnings of the rare juvenile granulosa cell tumor (JGCT) have not been well elucidated. To this end, we applied a tumor-only integrated approach to investigate the genomic, transcriptomic, and epigenomic landscape of 31 JGCTs to identify putative oncogenic drivers. EXPERIMENTAL DESIGN/METHODS:Multipronged analyses of 31 JGCTs were performed utilizing a clinically validated next-generation sequencing (NGS)-panel targeting 580 cancer-related genes for genomic interrogation, in addition to targeted RNA NGS for transcriptomic exploration. Genome-wide DNA methylation profiling was conducted using an Infinium Methylation EPIC array targeting 866,562 CpG methylation sites. RESULTS:non-rearranged JGCTs under direct promoter control. Genome-wide DNA methylation rendered a clear delineation between AGCTs and JGCTs at the epigenomic level further supporting its diagnostic utility in distinguishing among these tumors. CONCLUSIONS:rearrangements in a subset of tumors. Our findings further offer insights into possible targeted therapies in a rare entity.

BACKGROUND:Endometrioid epithelial ovarian cancer (EEOC) is rare, and its management poorly defined. We examined factors associated with 5-year progression-free survival (PFS) after surgery for EEOC. METHODS:Retrospective study: treatment and outcomes of all EEOC patients undergoing initial surgery at, or presenting to, our institution within 3 months of initial surgery, 1/2002-9/2017. RESULTS:In total, 212 patients were identified. Median follow-up, 63.9 months (range, 0.7-192); median age at diagnosis, 52 years (range, 20-88); disease stage: I, n = 145 (68%); II, n = 47 (22%); III/IV, n = 20 (9%); FIGO grade: 1, 127 (60%); 2, 66 (31%); 3, 17 (8%); unknown, 2 (1%). One hundred twenty-eight (60%) had endometriosis; 75 (35%), synchronous endometrioid endometrial cancer (80%, IA); 101 (48%), complete surgical staging; 8 (5%), positive pelvic lymph nodes (LNs); 6 (4%), positive para-aortic LNs; 176 (97%), complete gross resection; 123 (60%), postoperative chemotherapy; 56(28%), no additional treatment. Five-year PFS, 83% (95% confidence interval [CI]: 76.6%-87.8%); 5-year overall survival (OS), 92.7% (95% CI: 87.7%-95.8%). Age, stage, and surgical staging were associated with improved 5-year PFS, and younger age at diagnosis with improved 5-year OS (p < 0.001). Chemotherapy did not improve 5-year PFS in IA/IB versus observation, but improved survival in IC (hazard ratio [HR]: 1.01, 95% CI: 0.22-4.59, p = 0.99; HR: 0.17, 95% CI: 0.04-0.7, p = 0.006). CONCLUSIONS:Age, stage, and full surgical staging were associated with improved 5-year PFS. Chemotherapy showed no benefit in IA/IB disease.

The determination of endometrial carcinoma histological subtypes, molecular subtypes, and mutation status is critical for the diagnostic process, and directly affects patients' prognosis and treatment. Sequencing, albeit slower and more expensive, can provide additional information on molecular subtypes and mutations that can be used to better select treatments. Here, we implement a customized multi-resolution deep convolutional neural network, Panoptes, that predicts not only the histological subtypes but also the molecular subtypes and 18 common gene mutations based on digitized H&E-stained pathological images. The model achieves high accuracy and generalizes well on independent datasets. Our results suggest that Panoptes, with further refinement, has the potential for clinical application to help pathologists determine molecular subtypes and mutations of endometrial carcinoma without sequencing.

To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targeted massively parallel sequencing of primary ECs between 2014 and 2018 and preoperative CE-CT were included (n = 150). Molecular subtypes of EC were assigned using DNA polymerase epsilon (POLE) hotspot mutations and immunohistochemistry-based p53 and MMR protein expression. TMB was derived from sequencing, with > 15.5 mutations-per-megabase as a cut-point to define TMB-H tumors. After radiomic feature extraction and selection, radiomic features and clinical variables were processed with the recursive feature elimination random forest classifier. Classification models constructed using the training dataset (n = 105) were then validated on the holdout test dataset (n = 45). Integrated radiomic-clinical classification distinguished MMR-D from copy number (CN)-low-like and CN-high-like ECs with an area under the receiver operating characteristic curve (AUROC) of 0.78 (95% CI 0.58-0.91). The model further differentiated TMB-H from TMB-low (TMB-L) tumors with an AUROC of 0.87 (95% CI 0.73-0.95). Peritumoral-rim radiomic features were most relevant to both classifications (p ≤ 0.044). Radiomic analysis achieved moderate accuracy in identifying MMR-D and TMB-H ECs directly from CE-CT. Radiomics may provide an adjunct tool to molecular profiling, especially given its potential advantage in the setting of intratumor heterogeneity.

Objective: The aim of this study was to describe the clinical impact of major diagnostic discrepancies in pathology reports of gynecologic malignancies for patients presenting for second opinion to a comprehensive cancer center.
Method(s): All cases of gynecologic malignancy submitted for second opinion review by gynecologic pathologists between 2010 and 2016 were evaluated. Cases with major discrepancies (deemed to have potential clinical impact) with outside diagnoses were self-identified by the specialized gynecologic pathologists. Cases were grouped according to pathologic disagreement with no impact on care and pathologic disagreement with clinical impact. Clinical impact was based on National Comprehensive Cancer Network (NCCN) guidelines and gynecologic oncologist expert opinion.
Result(s): Of the 8,475 gynecologic cases reviewed, 1,265 (15%) discrepancies with outside hospital diagnoses were identified. Of these, 198 (16%) were deemed to be major discrepancies. There were 77 (39%) endometrial cancers, 42 (21%) ovarian cancers, 32 (16%) sarcomas, 30 (15%) cervical cancers, and 18 (9%) other malignancies. Most cases (n = 78, 39%) resulted in change in histology, while 32 (16%) cases noted a different site of origin of disease compared to original diagnosis. Forty-three (22%) cases were downgraded from malignant to benign, and 33 (17%) upgraded from benign to malignant. There were 123 (62%) cases that were deemed to have a pathologic disagreement that had clinical sequelae (change in treatment). Of these, 53 (43%) were surgical (recommend for or against), and 70 (57%) were nonsurgical. Review of uterine sarcoma cases, although considered major discrepancies by expert pathology, had no clinical impact in 60% (n = 18) of cases.
Conclusion(s): Pathologic review of outside cases by specialized gynecologic pathologists identified a group of cases across all gynecologic tumor types that led to changes in clinical management. The impact on patient outcomes should be further explored.
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Adult-type granulosa cell tumor (aGCT) is a rare malignant ovarian sex cord-stromal tumor, harboring recurrent FOXL2 c.C402G/p.C134W hotspot mutations in 97% of cases. These tumors are considered to have a favorable prognosis, however aGCTs have a tendency for local spread and late recurrences, which are associated with poor survival rates. We sought to determine the genetic alterations associated with aGCT disease progression. We subjected primary non-recurrent aGCTs (n = 7), primary aGCTs that subsequently recurred (n = 9) and their matched recurrences (n = 9), and aGCT recurrences without matched primary tumors (n = 10) to targeted massively parallel sequencing of ≥410 cancer-related genes. In addition, three primary non-recurrent aGCTs and nine aGCT recurrences were subjected to FOXL2 and TERT promoter Sanger sequencing analysis. All aGCTs harbored the FOXL2 C134W hotspot mutation. TERT promoter mutations were found to be significantly more frequent in recurrent (18/28, 64%) than primary aGCTs (5/19, 26%, p = 0.017). In addition, mutations affecting TP53, MED12, and TET2 were restricted to aGCT recurrences. Pathway annotation of altered genes demonstrated that aGCT recurrences displayed an enrichment for genetic alterations affecting cell cycle pathway-related genes. Analysis of paired primary and recurrent aGCTs revealed that TERT promoter mutations were either present in both primary tumors and matched recurrences or were restricted to the recurrence and absent in the respective primary aGCT. Clonal composition analysis of these paired samples further revealed that aGCTs display intra-tumor genetic heterogeneity and harbor multiple clones at diagnosis and relapse. We observed that in a subset of cases, recurrences acquired additional genetic alterations not present in primary aGCTs, including TERT, MED12, and TP53 mutations and CDKN2A/B homozygous deletions. Albeit harboring relatively simple genomes, our data provide evidence to suggest that aGCTs are genetically heterogeneous tumors and that TERT promoter mutations and/or genetic alterations affecting other cell cycle-related genes may be associated with disease progression and recurrences.