bioRxivCancer BiologyPreprint
APC loss promotes intestinal transformation through induction of bistable stem cell states
N Li, RL Myers, Qin ZhuiD, Ye TianiD, Kayla Durning, X Wang, NA Leu, JH Rhoades, Devon Bankler-Jukes, Keara MonaghaniD, Stephanie Adams‐TzivelekidisiD, Oz PompiD, Oscar Pellón-CárdenasiD, Mario Andres BlancoiD, Michael Paul VerziiD, Peter S. KleiniD, Christopher J. LengneriD
Abstract
Colorectal cancer (CRC) is a leading cause of cancer deaths, predominantly initiated by genetic inactivation of the APC tumor suppressor. Current dogma holds that APC inactivation promotes tumorigenesis via hyperactivation of the WNT pathway transcriptional effector, {beta}-CATENIN. Although {beta}-CATENIN activation is required for tumor initiation, activating mutations in {beta}-CATENIN are infrequent. Here, we ask what underlies the selective pressure for APC inactivation by comparing the oncogenic effects of APC loss to {beta}-CATENIN hyperactivation. We find that APC loss activates a {beta}-CATENIN-independent fetal intestinal transcriptional program driven by dysregulation of GSK-3 activity upon the LIM-domain protein AJUBA, a positive regulator of YAP. This results in AJUBA stabilization and downstream transcriptional activation of the YAP-driven fetal intestinal gene expression program. We find that {beta}-CATENIN- and YAP-driven transcriptional states are mutually exclusive, existing in an interchangeable bistable balance among APC-null cells. This results in more robust tumor initiation and metastatic progression downstream of APC loss relative to {beta}-CATENIN activation. Taken together, our findings explain the preferential selection for APC inactivation in CRC development and illuminate how {beta}-CATENIN- and YAP-driven gene expression programs coexist to promote tumorigenesis.
- organism: human
- assay: bulk RNA-seq
- research focus: cell signaling & trafficking
- research focus: cancer & tumor microenvironment
- research focus: gene regulatory network inference
- approach: experimental assay
- approach: statistical model
- Citations
- 1
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