Long, Beverly

Abstract Introduction: Acquired resistance to platinum remains a major clinical problem in ovarian cancer since systemic therapies have limited efficacy in this setting. There is growing evidence that the tumor microenvironment (TME) contributes to such resistance, as well as the pathogenesis of the disease. The study of the TME is limited by technical challenges of separating the epithelial from the stromal component. To overcome this limitation, we performed RNA sequencing (RNA-Seq) for three pairs of sensitive and induced resistant patient-derived xenograft models since the epithelial transcripts originate from human tissue and the stroma component is murine. Methods: To determine which TME genes might be contributing to chemotherapy resistance, three platinum-sensitive ovarian cancer PDX lines were treated repeatedly with carboplatin/paclitaxel until resistance occurred. Primary platinum-sensitive and induced platinum resistant tumors were characterized histologically by H&E and Masson Trichrome staining. The three pairs of sensitive and resistant PDX models were then subjected to RNA-Seq. Raw sequencing data were processed through Xenome to classify the reads into epithelial carcinoma (human) or TME (mouse) through Mayo Clinic’s internal RNA-Seq pipeline for transcriptome quantification. Differential expression analysis between induced resistant and sensitive models was carried out for both carcinoma and TME components using edgeR paired analysis. Gene set enrichment analysis was used to identify overrepresented biologic functions for differentially expressed genes between the pairs. Top significantly varied, differentially expressed genes between the pairs were validated using species-specific qPCR. Results: Histologic analysis of the matched sensitive/resistant pairs revealed a marked increase of the stromal component in the resistant tumors evident by H&E and Masson trichrome staining. A total number of 95 and 312 genes were differentially expressed in the epithelial and TME component, respectively (FDR<0.05; absolute log2 fold-change >1.5). The stemness marker SOX2 was significantly upregulated in the human component of the resistant tumors as confirmed by qPCR. Genes involved in stroma remodeling were upregulated in the “murine” component of the resistant tumors, and upregulation was confirmed by qPCR (normalized to a murine housekeeper gene). Gene set enrichment analysis showed that the upregulated genes in TME of resistant models were enriched for cytoskeleton related functions, while the downregulated genes were enriched for extracellular matrix-related functions. Conclusion: A bioinformatics strategy able to map human and murine reads separately may identify resistance mechanisms attributed to the two tumor subcompartments and could lead to strategies to potentially target each separately or concurrently. Citation Format: Valentina Zanfagnin, Yuanhang Liu, Pritha Chanana, Xiaonan Pritha, Beverly Long, Joe Pathoulas, Brad Evans, Jaime Davila, Chen Wang, Saravut John Weroha. Transcriptional profiling of tumor stroma using ovarian cancer PDX models with induced platinum-resistance [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B18.

Abstract Background: Endometrial cancer is highly curable when detected early, but clinical symptoms are often missed. Most cancers arise in women with abnormal postmenopausal bleeding (PMB). However, PMB is not specific for endometrial cancers. In previous reports, the prevalence of endometrial cancer in women with PMB was reported to range from 3-25%. Because of the importance for guiding clinical management and endometrial cancer risk prediction, we conducted a systematic review and meta-analysis to obtain precise prevalence estimates of endometrial cancer in women with PMB. Methods: A systematic review and meta-analysis summarized all peer-reviewed studies reporting endometrial cancer prevalence in women with PMB, published before Sept. 1, 2016. We calculated a pooled prevalence estimate and 95% confidence interval (CI) using a random-effects model, and quantified heterogeneity across studies using the I2 statistic. Subgroup meta-analyses were performed to investigate sources of variability according to selection criteria for endometrial thickness (ET) and hormone replacement therapy (HRT). We also stratified by study location to determine whether prevalence estimates varied by country or region if ≤5 studies included per country. Results: 105 studies were included, contributing data for 37,000 women with PMB and 3,028 with cancer from 34 countries. Overall, the pooled prevalence of endometrial cancer in women with PMB was 11% (95% CI 10-12%), with I2 =94.3%. Among studies that selected women with a minimum ET (≥ 4mm; n=14), the pooled prevalence of endometrial cancer was 17% (95% CI 14-20%) compared with studies that did not select for ET (10%, 95% CI 9-11%). In studies that excluded women using HRT (n=34), the pooled prevalence of endometrial cancer was 15% (95% CI 12-17%) compared with studies that did not exclude women using HRT (9%, 95% CI 8-10%). Stratification by study location revealed variation in prevalence estimates. For example, in the United States (n=9) and the United Kingdom (n=16), prevalence of endometrial cancer was 4% (95% CI 2-7%) and 5% (95% CI 4-6%), respectively, whereas in Italy (n=14), the prevalence was 11% (95% 8-14%). Regional differences were also observed, ranging from 8% (95% CI 3-14%) in South Central Asia (n=5) to 18% (95% CI 12-23%) in Southern Europe (n=11). Conclusions: The overall prevalence of endometrial cancer among unselected women with PMB is approximately 10% with substantial heterogeneity across studies. Marked geographic differences in the prevalence endometrial cancer were observed. Factors related to selection for ET and/or HRT use may partially contribute to this variability. Risk prediction models depend on precise prevalence estimates for accurate prediction and utility in clinical management. More research is needed to test the applicability of endometrial cancer risk prediction models in high-risk subgroups and in study populations from diverse geographic regions. Citation Format: Megan A. Clarke, Beverly J. Long, Arena Del Mar Morillo, Jamie N. Bakkum-Gamez, Nicolas Wentzensen. The prevalence of endometrial cancer in women with postmenopausal bleeding: a systematic review and meta-analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 275. doi:10.1158/1538-7445.AM2017-275