Abstract 2261: Identification of MEIS-associated networks and gene sets involved in prostate cancer progression
Authors: Calvin VanOpstall, Raj Bhanvadia, Hannah Brechka, Marc Gillard, Wen-Ching Chan, Jorge Andrade, Donald J. Vander Griend
Journal: Cancer Research (2018)

Abstract Introduction: MEIS1/2 transcription factors, known for their role as HOX cofactors in development, have previously been shown to have prognostic value in patients with intermediate Gleason grade prostate cancer (PrCa). Patients with low expression of MEIS1/2 were shown to have decreased overall survival and time to biochemical recurrence. However, an understanding of the MEIS-associated transcriptional networks driving this tumor suppression has remained unknown. Methods: Using an RNA-seq dataset composed of 25 primary prostate tumors and 51 annotated metastases obtained from dbGAP, we normalized transcript expression across samples before stratifying by MEIS1/2 expression levels. Primary tumor (PT) samples with MEIS1/2 expression levels in the lowest tertile were classified as the MEISLOW group, while PT samples with MEIS1/2 expression in the highest tertile were classified as the MEISHIGH group. Differentially expressed genes (DEGs) were detected using Cuffquant-Cuffnorm-Cuffdiff suite featureCounts, DESeq2, edgeR, or limma. Transcripts were further filtered by fold change ≥ 1.5, and genes detected by at least more than one method were collected into a list of high-confidence differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA), and Ingenuity Pathways Analysis (IPA) (Ingenuity Systems) were then used to identify functional categories or pathways that were significantly enriched or different. Results: Pair-wise analyses identified 1804 DEGs between the MEISHIGH and MEISLOW prostate primary tumor groups, which also demonstrated similar and non-significant expression between the MEISLOW and metastatic samples. These genes thus have similar expression between more aggressive MEISLOW tumors and metastasis, yet significantly distinct expression in the more indolent MEISLOW tumors. IPA analysis of this DEG list identified several networks involved in cellular proliferation and survival, as well as inflammatory response and cellular movement. GSEA results also demonstrate a positive enrichment in MEISHIGH tumors for gene sets involved in cell fate commitment, cell-cell adhesion, negative regulation of proliferation, and cell morphogenesis and differentiation, and a negative enrichment in expression of cMYC targets and genes involved in G1-S transition. Conclusions: Together these data provide a list of key MEIS-associated target genes in PrCa progression, and support a model whereby primary prostate tumors expressing high levels of MEIS1/2 are less proliferative, more differentiated, and have increased cell-cell adhesion, thereby promoting a more indolent tumor phenotype. These data are in direct support of previous studies revealing improved prognosis in tumors with higher expression of MEIS1/2, and decreased expression of MEIS2 in castration-resistant prostate cancer cells. Citation Format: Calvin VanOpstall, Raj Bhanvadia, Hannah Brechka, Marc Gillard, Wen-Ching Chan, Jorge Andrade, Donald J. Vander Griend. Identification of MEIS-associated networks and gene sets involved in prostate cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2261.