Topoisomerase 1 Inhibition in MYC-Driven Cancer Promotes Aberrant R-Loop Accumulation to Induce Synthetic Lethality

CRISPR screening reveals topoisomerase 1 as an immediately actionable vulnerability in cancers harboring MYC as a driver oncoprotein that can be targeted with clinically approved inhibitors. MYC is a central regulator of gene transcription and is frequently dysregulated in human cancers. As targeting MYC directly is challenging, an alternative strategy is to identify specific proteins or processes required for MYC to function as a potent cancer driver that can be targeted to result in synthetic lethality. To identify potential targets in MYC-driven cancers, we performed a genome-wide CRISPR knockout screen using an isogenic pair of breast cancer cell lines in which MYC dysregulation is the switch from benign to transformed tumor growth. Proteins that regulate R-loops were identified as a potential class of synthetic lethal targets. Dysregulated MYC elevated global transcription and coincident R-loop accumulation. Topoisomerase 1 (TOP1), a regulator of R-loops by DNA topology, was validated to be a vulnerability in cells with high MYC activity. Genetic knockdown of TOP1 in MYC-transformed cells resulted in reduced colony formation compared with control cells, demonstrating synthetic lethality. Overexpression of RNaseH1, a riboendonuclease that specifically degrades R-loops, rescued the reduction in clonogenicity induced by TOP1 deficiency, demonstrating that this vulnerability is driven by aberrant R-loop accumulation. Genetic and pharmacologic TOP1 inhibition selectively reduced the fitness of MYC-transformed tumors in vivo. Finally, drug response to TOP1 inhibitors (i.e., topotecan) significantly correlated with MYC levels and activity across panels of breast cancer cell lines and patient-derived organoids. Together, these results highlight TOP1 as a promising target for MYC-driven cancers.Significance: CRISPR screening reveals topoisomerase 1 as an immediately actionable vulnerability in cancers harboring MYC as a driver oncoprotein that can be targeted with clinically approved inhibitors

Assessment of Hypoxia in the Stroma of Patient-Derived Pancreatic Tumor Xenografts

The unusually dense stroma of pancreatic cancers is thought to play an important role in their biological aggression. The presence of hypoxia is also considered an adverse prognostic factor. Although it is usually assumed that this is the result of effects of hypoxia on the epithelial component, it is possible that hypoxia exerts indirect effects via the tumor stroma. We therefore measured hypoxia in the stroma of a series of primary pancreatic cancer xenografts. Nine patient-derived pancreatic xenografts representing a range of oxygenation levels were labeled by immunohistochemistry for EF5 and analyzed using semi-automated pattern recognition software. Hypoxia in the tumor and stroma was correlated with tumor growth and metastatic potential. The extent of hypoxia varied from 1%–39% between the different models. EF5 labeling in the stroma ranged from 0–20% between models, and was correlated with the level of hypoxia in the tumor cell area, but not microvessel density. Tumor hypoxia correlated with spontaneous metastasis formation with the exception of one hypoxic model that showed disproportionately low levels of hypoxia in the stroma and was non-metastatic. Our results demonstrate that hypoxia exists in the stroma of primary pancreatic cancer xenografts and suggest that stromal hypoxia impacts the metastatic potential

Assessment of Hypoxia in the Stroma of Patient-Derived Pancreatic Tumor Xenografts

The unusually dense stroma of pancreatic cancers is thought to play an important role in their biological aggression. The presence of hypoxia is also considered an adverse prognostic factor. Although it is usually assumed that this is the result of effects of hypoxia on the epithelial component, it is possible that hypoxia exerts indirect effects via the tumor stroma. We therefore measured hypoxia in the stroma of a series of primary pancreatic cancer xenografts. Nine patient-derived pancreatic xenografts representing a range of oxygenation levels were labeled by immunohistochemistry for EF5 and analyzed using semi-automated pattern recognition software. Hypoxia in the tumor and stroma was correlated with tumor growth and metastatic potential. The extent of hypoxia varied from 1%–39% between the different models. EF5 labeling in the stroma ranged from 0–20% between models, and was correlated with the level of hypoxia in the tumor cell area, but not microvessel density. Tumor hypoxia correlated with spontaneous metastasis formation with the exception of one hypoxic model that showed disproportionately low levels of hypoxia in the stroma and was non-metastatic. Our results demonstrate that hypoxia exists in the stroma of primary pancreatic cancer xenografts and suggest that stromal hypoxia impacts the metastatic potential

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-to-segment images such as of neurons and organoids. Here we describe a comprehensive shallow-learning framework for automated quantitative phenotyping of three-dimensional (3D) image data using unsupervised data-driven voxel-based feature learning, which enables computationally facile classification, clustering and advanced data visualization. We demonstrate the analysis potential on complex 3D images by investigating the phenotypic alterations of: neurons in response to apoptosis-inducing treatments and morphogenesis for oncogene-expressing human mammary gland acinar organoids. Our novel implementation of image analysis algorithms called Phindr3D allowed rapid implementation of data-driven voxel-based feature learning into 3D high content analysis (HCA) operations and constitutes a major practical advance as the computed assignments represent the biology while preserving the heterogeneity of the underlying data. Phindr3D is provided as Matlab code and as a stand-alone program (https://github.com/DWALab/Phindr3D)

Assessment of Hypoxia in the Stroma of Patient-Derived Pancreatic Tumor Xenografts

The unusually dense stroma of pancreatic cancers is thought to play an important role in their biological aggression. The presence of hypoxia is also considered an adverse prognostic factor. Although it is usually assumed that this is the result of effects of hypoxia on the epithelial component, it is possible that hypoxia exerts indirect effects via the tumor stroma. We therefore measured hypoxia in the stroma of a series of primary pancreatic cancer xenografts. Nine patient-derived pancreatic xenografts representing a range of oxygenation levels were labeled by immunohistochemistry for EF5 and analyzed using semi-automated pattern recognition software. Hypoxia in the tumor and stroma was correlated with tumor growth and metastatic potential. The extent of hypoxia varied from 1%–39% between the different models. EF5 labeling in the stroma ranged from 0–20% between models, and was correlated with the level of hypoxia in the tumor cell area, but not microvessel density. Tumor hypoxia correlated with spontaneous metastasis formation with the exception of one hypoxic model that showed disproportionately low levels of hypoxia in the stroma and was non-metastatic. Our results demonstrate that hypoxia exists in the stroma of primary pancreatic cancer xenografts and suggest that stromal hypoxia impacts the metastatic potential

Modelling the MYC-driven normal-to-tumour switch in breast cancer.

The potent MYC oncoprotein is deregulated in many human cancers, including breast carcinoma, and is associated with aggressive disease. To understand the mechanisms and vulnerabilities of MYC-driven breast cancer, we have generated an in vivo model that mimics human disease in response to MYC deregulation. MCF10A cells ectopically expressing a common breast cancer mutation in the phosphoinositide 3 kinase pathway (PIK3CAH1047R) led to the development of organised acinar structures in mice. Expressing both PIK3CAH1047R and deregulated MYC led to the development of invasive ductal carcinoma. Therefore, the deregulation of MYC expression in this setting creates a MYC-dependent normal-to-tumour switch that can be measured in vivo These MYC-driven tumours exhibit classic hallmarks of human breast cancer at both the pathological and molecular level. Moreover, tumour growth is dependent upon sustained deregulated MYC expression, further demonstrating addiction to this potent oncogene and regulator of gene transcription. We therefore provide a MYC-dependent model of breast cancer, which can be used to assay in vivo tumour signalling pathways, proliferation and transformation from normal breast acini to invasive breast carcinoma. We anticipate that this novel MYC-driven transformation model will be a useful research tool to better understand the oncogenic function of MYC and for the identification of therapeutic vulnerabilities

MYC Deregulation in Primary Human Cancers

MYC regulates a complex biological program by transcriptionally activating and repressing its numerous target genes. As such, MYC is a master regulator of many processes, including cell cycle entry, ribosome biogenesis, and metabolism. In cancer, the activity of the MYC transcriptional network is frequently deregulated, contributing to the initiation and maintenance of disease. Deregulation often leads to constitutive overexpression of MYC, which can be achieved through gross genetic abnormalities, including copy number alterations, chromosomal translocations, increased enhancer activity, or through aberrant signal transduction leading to increased MYC transcription or increased MYC mRNA and protein stability. Herein, we summarize the frequency and modes of MYC deregulation and describe both well-established and more recent findings in a variety of cancer types. Notably, these studies have highlighted that with an increased appreciation for the basic mechanisms deregulating MYC in cancer, new therapeutic vulnerabilities can be discovered and potentially exploited for the inhibition of this potent oncogene in cancer