Teresa Davoli

Cumulative Haploinsufficiency and Triplosensitivity Drive Aneuploidy Patterns and Shape the Cancer Genome

Aneuploidy has been recognized as a hallmark of cancer for more than 100 years, yet no general theory to explain the recurring patterns of aneuploidy in cancer has emerged. Here, we develop Tumor Suppressor and Oncogene (TUSON) Explorer, a computational method that analyzes the patterns of mutational signatures in tumors and predicts the likelihood that any individual gene functions as a tumor suppressor (TSG) or oncogene (OG). By analyzing >8,200 tumor-normal pairs, we provide statistical evidence suggesting that many more genes possess cancer driver properties than anticipated, forming a continuum of oncogenic potential. Integrating our driver predictions with information on somatic copy number alterations, we find that the distribution and potency of TSGs (STOP genes), OGs, and essential genes (GO genes) on chromosomes can predict the complex patterns of aneuploidy and copy number variation characteristic of cancer genomes. We propose that the cancer genome is shaped through a process of cumulative haploinsufficiency and triplosensitivity.

Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy

Chromosomal chaos and tumor immunity Cancer immunotherapy produces durable clinical responses in only a subset of patients. Identification of tumor characteristics that correlate with responses could lead to predictive biomarkers and shed light on causal mechanisms. Davoli et al. found that human tumors with extensive aneuploidy—i.e., that display a highly abnormal number of chromosomes and chromosomal segments—express fewer markers of the immune cells responsible for tumor destruction. In a retrospective analysis of clinical trial data, they found that melanoma patients with highly aneuploid tumors were less likely to benefit from immune checkpoint blockade therapy than patients whose tumors had a more normal karyotype. Thus, aneuploidy appears to enhance the ability of tumors to evade the immune system. Science, this issue p. 10.1126/science.aaf8399 Human tumors that display extensive chromosomal aberrations appear to be more resistant to immune attack. INTRODUCTION Aneuploidy, also known as somatic copy number alterations (SCNAs), is widespread in human cancers and has been proposed to drive tumorigenesis. The relationship between SCNAs and the characteristic functional features or “hallmarks” of cancer is not well understood. Among these cancer hallmarks is immune evasion, which is accomplished by neoantigen editing, defects in antigen presentation and inhibition of tumor infiltration, and/or cytotoxic activities of immune cells. Whether and how tumor SCNA levels influence immune evasion is of particular interest as this information could potentially be used to improve the efficacy of immune checkpoint blockade, a therapy that has produced durable responses in a subset of cancer patients. RATIONALE Understanding how SCNAs and mutation load affect tumor evolution, and through what mechanisms, is a key objective in cancer research. To explore the relationships between SCNA levels, tumor mutations, and cancer hallmarks, we examined data from 5255 tumor/normal samples representing 12 cancer types from The Cancer Genome Atlas project. We assigned each tumor an SCNA score and looked for correlations with the number and types of tumor mutations. We also compared the gene expression profiles of tumors with high versus low SCNA levels to identify differences in cellular signaling pathways. RESULTS First, we found that, for most tumors, there was a positive correlation between SCNA levels and the total number of mutations. Second, tumors harboring activating oncogenic mutations in the receptor tyrosine kinase–RAS–phosphatidylinositol 3-kinase pathway showed fewer SCNAs, a finding at odds with the hypothesis of oncogene-driven genomic instability. Third, we found that tumors with high levels of SCNAs showed elevated expression of cell cycle and cell proliferation markers (cell cycle signature) and reduced expression of markers for cytotoxic immune cell infiltrates (immune signature). The increased expression level of the cell cycle signature was primarily predicted by focal SCNAs, with a lesser contribution of arm and whole-chromosome SCNAs. In contrast, the lower expression level of the immune signature was primarily predicted by high levels of arm and whole-chromosome SCNAs. SCNA levels were a stronger predictor of markers of cytotoxic immune cell infiltration than tumor mutational load. Finally, through analysis of data from two published clinical trials of immunotherapy in melanoma patients, we found that high SCNA levels in tumors correlated with poorer survival of patients. The combination of the tumor SCNA score and the tumor mutational load was a better predictor of survival after immunotherapy than either biomarker alone. CONCLUSION We found that two hallmarks of cancer, cell proliferation and immune evasion, are predicted by distinct types of aneuploidy that likely act through distinct mechanisms. Proliferation markers mainly correlated with focal SCNAs, implying a mechanism related to the action of specific genes targeted by these SCNAs. Immune evasion markers mainly correlated with arm- and chromosome-level SCNAs, consistent with a mechanism related to general gene dosage imbalance rather than the action of specific genes. A retrospective analysis of melanoma patients treated with immune checkpoint blockade anti–CTLA-4 (cytotoxic T lymphocyte–associated protein 4) therapy revealed that high SCNA levels were associated with a poorer response, suggesting that tumor aneuploidy might be a useful biomarker for predicting which patients are most likely to benefit from this therapy. Genetic events associated with two cancer hallmarks: cell proliferation and immune evasion. Across several human tumor types, high SCNA levels correlate with increased expression of cell cycle markers and decreased expression of markers of cytotoxic immune cell infiltrates. A high load of tumor neoantigens (reflecting a high level of point mutations) promotes the detection of tumors by the immune system, limiting immune evasion. The relative contribution of focal, arm/chromosome, and neoantigen load to the prediction of proliferation and immune evasion is shown. Immunotherapies based on immune checkpoint blockade are highly effective in a subset of patients. An ongoing challenge is the identification of biomarkers that predict which patients will benefit from these therapies. Aneuploidy, also known as somatic copy number alterations (SCNAs), is widespread in cancer and is posited to drive tumorigenesis. Analyzing 12 human cancer types, we find that, for most, highly aneuploid tumors show reduced expression of markers of cytotoxic infiltrating immune cells, especially CD8+ T cells, and increased expression of cell proliferation markers. Different types of SCNAs predict the proliferation and immune signatures, implying distinct underlying mechanisms. Using published data from two clinical trials of immune checkpoint blockade therapy for metastatic melanoma, we found that tumor aneuploidy inversely correlates with patient survival. Together with other tumor characteristics such as tumor mutational load, aneuploidy may thus help identify patients most likely to respond to immunotherapy.

Comprehensive Identification of Host Modulators of HIV-1 Replication using Multiple Orthologous RNAi Reagents

SUMMARY RNAi screens have implicated hundreds of host proteins as HIV-1 dependency factors (HDFs). While informative, these early studies overlap poorly due to false positives and false negatives. To ameliorate these issues, we combined information from the existing HDF screens together with new screens performed with multiple orthologous RNAi reagents (MORR). In addition to being traditionally validated, the MORR screens and the historical HDF screens were quantitatively integrated by the adaptation of an established analysis program, RIGER, for the collective interpretation of each gene’s phenotypic significance. False positives were addressed by the removal of poorly expressed candidates through gene expression filtering, as well as with GESS, which identifies off-target effects. This workflow produced a quantitatively integrated network of genes that modulate HIV-1 replication. We further investigated the roles of GOLGI49, SEC13, and COG in HIV-1 replication. Collectively, the MORR-RIGER method minimized the caveats of RNAi screening and improved our understanding of HIV-1–host cell interactions.

A genetic interaction analysis identifies cancer drivers that modify EGFR dependency

A large number of cancer drivers have been identified through tumor sequencing efforts, but how they interact and the degree to which they can substitute for each other have not been systematically explored. To comprehensively investigate how cancer drivers genetically interact, we searched for modifiers of epidermal growth factor receptor (EGFR) dependency by performing CRISPR, shRNA, and expression screens in a non-small cell lung cancer (NSCLC) model. We elucidated a broad spectrum of tumor suppressor genes (TSGs) and oncogenes (OGs) that can genetically modify proliferation and survival of cancer cells when EGFR signaling is altered. These include genes already known to mediate EGFR inhibitor resistance as well as many TSGs not previously connected to EGFR and whose biological functions in tumorigenesis are not well understood. We show that mutation of PBRM1, a subunit of the SWI/SNF complex, attenuates the effects of EGFR inhibition in part by sustaining AKT signaling. We also show that mutation of Capicua (CIC), a transcriptional repressor, suppresses the effects of EGFR inhibition by partially restoring the EGFR-promoted gene expression program, including the sustained expression of Ets transcription factors such as ETV1 Together, our data provide strong support for the hypothesis that many cancer drivers can substitute for each other in certain contexts and broaden our understanding of EGFR regulation.

Sources of Error in Mammalian Genetic Screens

Genetic screens are invaluable tools for dissection of biological phenomena. Optimization of such screens to enhance discovery of candidate genes and minimize false positives is thus a critical aim. Here, we report several sources of error common to pooled genetic screening techniques used in mammalian cell culture systems, and demonstrate methods to eliminate these errors. We find that reverse transcriptase-mediated recombination during retroviral replication can lead to uncoupling of molecular tags, such as DNA barcodes (BCs), from their associated library elements, leading to chimeric proviral genomes in which BCs are paired to incorrect ORFs, shRNAs, etc. This effect depends on the length of homologous sequence between unique elements, and can be minimized with careful vector design. Furthermore, we report that residual plasmid DNA from viral packaging procedures can contaminate transduced cells. These plasmids serve as additional copies of the PCR template during library amplification, resulting in substantial inaccuracies in measurement of initial reference populations for screen normalization. The overabundance of template in some samples causes an imbalance between PCR cycles of contaminated and uncontaminated samples, which results in a systematic artifactual depletion of GC-rich library elements. Elimination of contaminating plasmid DNA using the bacterial endonuclease Benzonase can restore faithful measurements of template abundance and minimize GC bias.

A primary melanoma and its asynchronous metastasis highlight the role of BRAF, CDKN2A, and TERT

Alterations in pathways including BRAF, CDKN2A, and TERT contribute to the development of melanoma, but the sequence in which the genetic alterations occur and their prognostic significance remains unclear. To clarify the role of these pathways, we analyzed a primary melanoma and its metastasis.

STOP gene Phactr4 is a tumor suppressor

Significance Cell proliferation control is central to tumor suppression. We previously identified hundreds of suppressors of tumorigenesis and/or proliferation (STOP) genes that restrain normal cell proliferation. Here we show that one such STOP gene, phosphatase and actin regulator 4 (PHACTR4), acts to prevent tumorigenesis. Phactr4 suppresses proliferation and transformation in vitro and tumorigenesis in vivo. PHACTR4 is significantly mutated or downregulated in several cancers, and reintroduction of Phactr4 limits proliferation and tumor growth in cells from these cancers. Thus, our studies provide strong evidence that PHACTR4 is a tumor suppressor. Cancer develops through genetic and epigenetic alterations that allow unrestrained proliferation and increased survival. Using a genetic RNAi screen, we previously identified hundreds of suppressors of tumorigenesis and/or proliferation (STOP) genes that restrain normal cell proliferation. Our STOP gene set was significantly enriched for known and putative tumor suppressor genes. Here, we report a tumor-suppressive role for one STOP gene, phosphatase and actin regulator 4 (PHACTR4). Phactr4 is one of four members of the largely uncharacterized Phactr family of protein phosphatase 1 (PP1)- and actin-binding proteins. Our work suggests that Phactr4 restrains normal cell proliferation and transformation. Depletion of Phactr4 with multiple shRNAs leads to increased proliferation and soft agar colony formation. Phactr4 acts, in part, through an Rb-dependent pathway, because Rb phosphorylation is maintained upon growth factor withdrawal in Phactr4-depleted cells. Examination of tumor copy number analysis and sequencing revealed that PHACTR4 is significantly deleted and mutant in many tumor subtypes. Furthermore, cancer cell lines with reduced Phactr4 expression exhibit tumor suppressor hypersensitivity upon Phactr4 complementation, leading to reduced proliferation, transformation, and tumor formation. Thus, Phactr4 acts as a tumor suppressor that is deleted and mutant in several cancers.

Functional genomics reveals that tumors with activating phosphoinositide 3-kinase mutations are dependent on accelerated protein turnover

Activating mutations in the phosphoinositide 3-kinase (PI3K) signaling pathway are frequently identified in cancer. To identify pathways that support PI3K oncogenesis, we performed a genome-wide RNAi screen in isogenic cell lines harboring wild-type or mutant PIK3CA to search for PI3K synthetic-lethal (SL) genes. A combined analysis of these results with a meta-analysis of two other large-scale RNAi screening data sets in PI3K mutant cancer cell lines converged on ribosomal protein translation and proteasomal protein degradation as critical nononcogene dependencies for PI3K-driven tumors. Genetic or pharmacologic inhibition of either pathway alone, but not together, selectively killed PI3K mutant tumor cells in an mTOR-dependent manner. The expression of ribosomal and proteasomal components was significantly up-regulated in primary human colorectal tumors harboring PI3K pathway activation. Importantly, a PI3K SL gene signature containing the top hits of the SL genes identified in our meta-analysis robustly predicted overall patient survival in colorectal cancer, especially among patients with tumors with an activated PI3K pathway. These results suggest that disruption of protein turnover homeostasis via ribosome or proteasome inhibition may be a novel treatment strategy for PI3K mutant human tumors.

Abstract SY10-01: How aneuploidy drives cancer

Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA Aneuploidy has been recognized as a hallmark of cancer for over 100 years, yet no general theory to explain the recurring patterns of aneuploidy in cancer has emerged. We developed Tumor Suppressor and Oncogene (TUSON) Explorer, a computational method that analyzes the patterns of mutational signatures in tumors and predicts the likelihood that any individual gene functions as a tumor suppressor (TSG) or oncogene (OG). By analyzing >8200 tumor-normal pairs we provide statistical evidence suggesting many more genes possess cancer driver properties than anticipated, forming a continuum of oncogenic potential. These genes represent the vast majority of cancer drivers and the genetic networks they drive are a focus of future cancer system biological approaches to cancer research. Integrating our driver predictions with information on somatic copy number alterations, we find that the distribution and the potency of TSGs (STOP genes), OGs and essential genes (GO genes) on chromosomes can predict the complex patterns of aneuploidy and copy number variation characteristic of cancer genomes. We propose that the cancer genome is shaped through a process of cumulative haploinsufficiency and triplosensitivity. We are now assessing how aneuploidy drives cancer and the potency with which it does so. We have found that aneuploidy predicts survival better than mutational drivers and as well as existing clinical parameters in many cases. We have also discovered that different classes of aneuploidy drive transcriptional programs for two hallmarks of cancer and will present data supporting these observations and their implications. Citation Format: Teresa Davoli, Hajima Uno, Andrew Xu, Kristen Mengwasser, Laura Sack, Peter J. Park, Stephen J. Elledge. How aneuploidy drives cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr SY10-01.

Abstract SY36-03: How aneuploidy drives tumorigenesis

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Aneuploidy has been recognized as a hallmark of cancer for over 100 years, yet no general theory to explain the recurring patterns of aneuploidy in cancer has emerged. Here we describe the development of Tumor Suppressor and Oncogene (TUSON) Explorer, a computational method that analyzes the patterns of mutational signatures in tumors and predicts the likelihood that any individual gene functions as a tumor suppressor (TSG) or oncogene (OG). By analyzing >8200 tumor-normal pairs we provide statistical evidence suggesting many more genes possess cancer driver properties than anticipated, forming a continuum of oncogenic potential. Integrating our driver predictions with information on somatic copy number alterations, we find that the distribution and the potency of TSGs (STOP genes), OGs and essential genes (GO genes) on chromosomes can predict the complex patterns of aneuploidy and copy number variation characteristic of cancer genomes. We propose that the cancer genome is shaped through a process of cumulative haploinsufficiency and triplosensitivity. Citation Format: Teresa Davoli, Wei Xu, Peter Park, Stephen J. Elledge. How aneuploidy drives tumorigenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr SY36-03. doi:10.1158/1538-7445.AM2014-SY36-03