Dclk1 Defines Quiescent Pancreatic Progenitors that Promote Injury-Induced Regeneration and Tumorigenesis

The existence of adult pancreatic progenitor cells has been debated. While some favor the concept of facultative progenitors involved in homeostasis and repair, neither a location nor markers for such cells have been defined. Using genetic lineage tracing, we show that Doublecortin-like kinase-1 (Dclk1) labels a rare population of long-lived, quiescent pancreatic cells. In vitro, Dclk1+ cells proliferate readily and sustain pancreatic organoid growth. In vivo, Dclk1+ cells are necessary for pancreatic regeneration following injury and chronic inflammation. Accordingly, their loss has detrimental effects after cerulein-induced pancreatitis. Expression of mutant Kras in Dclk1+ cells does not affect their quiescence or longevity. However, experimental pancreatitis converts Kras mutant Dclk1+ cells into potent cancer-initiating cells. As a potential effector of Kras, Dclk1 contributes functionally to the pathogenesis of pancreatic cancer. Taken together, these observations indicate that Dclk1 marks quiescent pancreatic progenitors that are candidates for the origin of pancreatic cancer

Analysis of Oncogenic Signal Transduction with Application to KRAS Signaling Pathways

The discovery of novel members of tumorigenic pathways remains a critical step to fully dissect the molecular biology of cancer. Indeed, because a number of cancer drivers are themselves undruggable, elucidating the signaling apparatuses in which they participate is essential for discovering novel therapeutic targets that will allow the treatment of aggressive neoplastic growth. In the context of oncoproteins and tumor suppressors, novel participants may be upstream regulators, downstream effectors, or physical cognate binding partners. In this work, we develop in silico approaches to more fully elucidate the tumorigenic signaling machinery used by tumor suppressors and oncoproteins. We first report applications of machine-learning algorithms to integrate diverse networkbased information to generate testable hypotheses of proteins involved in canonical oncogenic pathways. We develop the OncoSig algorithm to elucidate novel members of protein-centric maps to elucidate upstream modulators, cognate binding partners, and downstream effectors for any tumor suppressor or oncogene in a tumor-specific fashion. We specifically apply OncoSig to elucidate the oncogenic KRAS regulatory map in Lung adenocarcinoma (LUAD). Oncogenic KRAS is a key driver of aggressive tumor growth in many LUAD patients, yet has no FDA-approved drugs targeting it. Thus, elucidating members of the KRAS protein-centric map is critical for discovering synthetic lethal interactions that may be subject to therapeutic targeting. Critically, 18/22 of novel predicted KRAS interactors elicited synthetic lethality in LUAD organoid cultures that harbored an activating KRAS mutation. We then extend the OncoSig algorithm to 10 oncogenic/tumor suppressor pathways (such as TP53, EGFR, and PI3K), and show that OncoSig is able to recover known regulators and downstream effectors of these critical mediators of tumorigenesis. We then focus specifically on dissecting KRAS’s physical protein-protein interactions. Many cognate binding partners bind to KRAS via a structurally conserved RAS-Binding Domain (RBD), thus propagating KRAS signal transduction. Thus, for example, CRAF, PI3K, and RALGDS, all bind to KRAS via an RBD. To elucidate novel KRAS protein-protein interactors, we use structural and sequence based approaches to discover biophysical properties of known RBDs. We apply the PrePPI algorithm, which predicts novel protein-protein interactions based on structural similarity, and find that PrePPI successfully recovers known RBDs while discriminating from domains structurally similar to the RBD that do not bind to KRAS. Using this information, we develop biophysical features to computationally predict novel KRAS binding partners. Finally, we report computational and experimental work addressing whether KRAS forms a homodimer. The precise mechanism for how KRAS propagates signal transduction after binding to the RBD remains elusive, and KRAS homo-dimerization, for example, may play a key role in KRAS induced tumorigenesis. Using Analytical Utracentrifugation to measure binding affinity, we find that KRAS forms either a weak dimer or a large non-specific multimer. Furthermore, analysis of KRAS protein structures deposited in the Protein Data Bank reveals key regions that have a propensity to form homodimer contacts in the crystal complexes, and may mediate KRAS homo-dimerization in a biological setting as well. These results provide mechanistic insight into how KRAS dimerization may facilitate cellular signal transduction

UHRF1 is a mediator of KRAS driven oncogenesis in lung adenocarcinoma.

KRAS is a frequent driver in lung cancer. To identify KRAS-specific vulnerabilities in lung cancer, we performed RNAi screens in primary spheroids derived from a Kras mutant mouse lung cancer model and discovered an epigenetic regulator Ubiquitin-like containing PHD and RING finger domains 1 (UHRF1). In human lung cancer models UHRF1 knock-out selectively impaired growth and induced apoptosis only in KRAS mutant cells. Genome-wide methylation and gene expression analysis of UHRF1-depleted KRAS mutant cells revealed global DNA hypomethylation leading to upregulation of tumor suppressor genes (TSGs). A focused CRISPR/Cas9 screen validated several of these TSGs as mediators of UHRF1-driven tumorigenesis. In vivo, UHRF1 knock-out inhibited tumor growth of KRAS-driven mouse lung cancer models. Finally, in lung cancer patients high UHRF1 expression is anti-correlated with TSG expression and predicts worse outcomes for patients with KRAS mutant tumors. These results nominate UHRF1 as a KRAS-specific vulnerability and potential target for therapeutic intervention

UHRF1 is a mediator of KRAS driven oncogenesis in lung adenocarcinoma

Abstract KRAS is a frequent driver in lung cancer. To identify KRAS-specific vulnerabilities in lung cancer, we performed RNAi screens in primary spheroids derived from a Kras mutant mouse lung cancer model and discovered an epigenetic regulator Ubiquitin-like containing PHD and RING finger domains 1 (UHRF1). In human lung cancer models UHRF1 knock-out selectively impaired growth and induced apoptosis only in KRAS mutant cells. Genome-wide methylation and gene expression analysis of UHRF1-depleted KRAS mutant cells revealed global DNA hypomethylation leading to upregulation of tumor suppressor genes (TSGs). A focused CRISPR/Cas9 screen validated several of these TSGs as mediators of UHRF1-driven tumorigenesis. In vivo, UHRF1 knock-out inhibited tumor growth of KRAS-driven mouse lung cancer models. Finally, in lung cancer patients high UHRF1 expression is anti-correlated with TSG expression and predicts worse outcomes for patients with KRAS mutant tumors. These results nominate UHRF1 as a KRAS-specific vulnerability and potential target for therapeutic intervention

Oncoprotein-specific molecular interaction maps (SigMaps) for cancer network analyses

Tumor-specific elucidation of physical and functional oncoprotein interactions could improve tumorigenic mechanism characterization and therapeutic response prediction. Current interaction models and pathways, however, lack context specificity and are not oncoprotein specific. We introduce SigMaps as context-specific networks, comprising modulators, effectors and cognate binding-partners of a specific oncoprotein. SigMaps are reconstructed de novo by integrating diverse evidence sources-including protein structure, gene expression and mutational profiles-via the OncoSig machine learning framework. We first generated a KRAS-specific SigMap for lung adenocarcinoma, which recapitulated published KRAS biology, identified novel synthetic lethal proteins that were experimentally validated in three-dimensional spheroid models and established uncharacterized crosstalk with RAB/RHO. To show that OncoSig is generalizable, we first inferred SigMaps for the ten most mutated human oncoproteins and then for the full repertoire of 715 proteins in the COSMIC Cancer Gene Census. Taken together, these SigMaps show that the cell's regulatory and signaling architecture is highly tissue specific

Asymmetric Binding to NS5A by Daclatasvir (BMS-790052) and Analogs Suggests Two Novel Modes of HCV Inhibition

Symmetric, dimeric daclatasvir (BMS-790052) is the clinical lead for a class of picomolar inhibitors of HCV replication. While specific, resistance-bearing mutations at positions 31 and 93 of domain I strongly suggest the viral NS5A as target, structural mechanism(s) for the drugs’ activities and resistance remains unclear. Several previous models suggested symmetric binding modes relative to the homodimeric target; however, none can fully explain SAR details for this class. We present semiautomated workflows to model potential receptor conformations for docking. Surprisingly, ranking docked hits with our library-derived 3D-pharmacophore revealed two distinct asymmetric binding modes, at a conserved poly-proline region between 31 and 93, consistent with SAR. Interfering with protein–protein interactions at this membrane interface can explain potent inhibition of replication–complex formation, resistance, effects on lipid droplet distribution, and virion release. These detailed interaction models and proposed mechanisms of action will allow structure-based design of new NS5A directed compounds with higher barriers to HCV resistance