Discovery of YAP1/TAZ pathway inhibitors through phenotypic screening with potent anti-tumor activity via blockade of Rho-GTPase signaling.

This study describes the identification and target deconvolution of small molecule inhibitors of oncogenic Yes-associated protein (YAP1)/TAZ activity with potent anti-tumor activity in vivo. A high-throughput screen (HTS) of 3.8 million compounds was conducted using a cellular YAP1/TAZ reporter assay. Target deconvolution studies identified the geranylgeranyltransferase-I (GGTase-I) complex as the direct target of YAP1/TAZ pathway inhibitors. The small molecule inhibitors block the activation of Rho-GTPases, leading to subsequent inactivation of YAP1/TAZ and inhibition of cancer cell proliferation in vitro. Multi-parameter optimization resulted in BAY-593, an in vivo probe with favorable PK properties, which demonstrated anti-tumor activity and blockade of YAP1/TAZ signaling in vivo.

Prognosis and oncogenomic profiling of patients with tropomyosin receptor kinase fusion cancer in the 100,000 genomes project.

INTRODUCTION: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are oncogenic drivers in various tumor types. Limited data exist on the overall survival (OS) of patients with tumors with NTRK gene fusions and on the co-occurrence of NTRK fusions with other oncogenic drivers. MATERIALS AND METHODS: This retrospective study included patients enrolled in the Genomics England 100,000 Genomes Project who had linked clinical data from UK databases. Patients who had undergone tumor whole genome sequencing between March 2016 and July 2019 were included. Patients with and without NTRK fusions were matched. OS was analyzed along with oncogenic alterations in ALK, BRAF, EGFR, ERBB2, KRAS, and ROS1, and tumor mutation burden (TMB) and microsatellite instability (MSI). RESULTS: Of 15,223 patients analyzed, 38 (0.25%) had NTRK gene fusions in 11 tumor types, the most common were breast cancer, colorectal cancer (CRC), and sarcoma. Median OS was not reached in both the NTRK gene fusion-positive and -negative groups (hazard ratio 1.47, 95% CI 0.39-5.57, P = 0.572). A KRAS mutation was identified in two (5%) patients with NTRK gene fusions, and both had hepatobiliary cancer. High TMB and MSI were both more common in patients with NTRK gene fusions, due to the CRC subset. While there was a higher risk of death in patients with NTRK gene fusions compared to those without, the difference was not statistically significant. CONCLUSION: This study supports the hypothesis that NTRK gene fusions are primary oncogenic drivers and the co-occurrence of NTRK gene fusions with other oncogenic alterations is rare.

ConsensusPathDB 2022: molecular interactions update as a resource for network biology.

Molecular interactions are key drivers of biological function. Providing interaction resources to the research community is important since they allow functional interpretation and network-based analysis of molecular data. ConsensusPathDB (http://consensuspathdb.org) is a meta-database combining interactions of diverse types from 31 public resources for humans, 16 for mice and 14 for yeasts. Using ConsensusPathDB, researchers commonly evaluate lists of genes, proteins and metabolites against sets of molecular interactions defined by pathways, Gene Ontology and network neighborhoods and retrieve complex molecular neighborhoods formed by heterogeneous interaction types. Furthermore, the integrated protein-protein interaction network is used as a basis for propagation methods. Here, we present the 2022 update of ConsensusPathDB, highlighting content growth, additional functionality and improved database stability. For example, the number of human molecular interactions increased to 859 848 connecting 200 499 unique physical entities such as genes/proteins, metabolites and drugs. Furthermore, we integrated regulatory datasets in the form of transcription factor-, microRNA- and enhancer-gene target interactions, thus providing novel functionality in the context of overrepresentation and enrichment analyses. We specifically emphasize the use of the integrated protein-protein interaction network as a scaffold for network inferences, present topological characteristics of the network and discuss strengths and shortcomings of such approaches.

Identification of Small Molecules that Modulate Mutant p53 Condensation.

Structural mutants of p53 induce global p53 protein destabilization and misfolding, followed by p53 protein aggregation. First evidence indicates that p53 can be part of protein condensates and that p53 aggregation potentially transitions through a condensate-like state. We show condensate-like states of fluorescently labeled structural mutant p53 in the nucleus of living cancer cells. We furthermore identified small molecule compounds that interact with the p53 protein and lead to dissolution of p53 structural mutant condensates. The same compounds lead to condensation of a fluorescently tagged p53 DNA-binding mutant, indicating that the identified compounds differentially alter p53 condensation behavior depending on the type of p53 mutation. In contrast to p53 aggregation inhibitors, these compounds are active on p53 condensates and do not lead to mutant p53 reactivation. Taken together our study provides evidence for structural mutant p53 condensation in living cells and tools to modulate this process.

Genomic analyses of flow-sorted Hodgkin Reed-Sternberg cells reveal complementary mechanisms of immune evasion.

Classical Hodgkin lymphoma (cHL) is composed of rare malignant Hodgkin Reed-Sternberg (HRS) cells within an extensive, but ineffective, inflammatory/immune cell infiltrate. HRS cells exhibit near-universal somatic copy gains of chromosome 9p/9p24.1, which increase expression of the programmed cell death protein 1 (PD-1) ligands. To define genetic mechanisms of response and resistance to PD-1 blockade and identify complementary treatment targets, we performed whole-exome sequencing of flow cytometry-sorted HRS cells from 23 excisional biopsies of newly diagnosed cHLs, including 8 Epstein-Barr virus-positive (EBV+) tumors. We identified significantly mutated cancer candidate genes (CCGs) as well as somatic copy number alterations and structural variations and characterized their contribution to disease-defining immune evasion mechanisms and nuclear factor κB (NF-κB), JAK/STAT, and PI3K signaling pathways. EBV- cHLs had a higher prevalence of genetic alterations in the NF-κB and major histocompatibility complex class I antigen presentation pathways. In this young cHL cohort (median age, 26 years), we identified a predominant mutational signature of spontaneous deamination of cytosine- phosphate-guanines ("Aging"), in addition to apolipoprotein B mRNA editing catalytic polypeptide-like, activation-induced cytidine deaminase, and microsatellite instability (MSI)-associated hypermutation. In particular, the mutational burden in EBV- cHLs was among the highest reported, similar to that of carcinogen-induced tumors. Together, the overall high mutational burden, MSI-associated hypermutation, and newly identified genetic alterations represent additional potential bases for the efficacy of PD-1 blockade in cHL. Of note, recurrent cHL alterations, including B2M, TNFAIP3, STAT6, GNA13, and XPO1 mutations and 2p/2p15, 6p21.32, 6q23.3, and 9p/9p24.1 copy number alterations, were also identified in >20% of primary mediastinal B-cell lymphomas, highlighting shared pathogenetic mechanisms in these diseases.

Genomic analyses of PMBL reveal new drivers and mechanisms of sensitivity to PD-1 blockade.

Primary mediastinal large B-cell lymphomas (PMBLs) are aggressive tumors that typically present as large mediastinal masses in young women. PMBLs share clinical, transcriptional, and molecular features with classical Hodgkin lymphoma (cHL), including constitutive activation of nuclear factor κB (NF-κB), JAK/STAT signaling, and programmed cell death protein 1 (PD-1)-mediated immune evasion. The demonstrated efficacy of PD-1 blockade in relapsed/refractory PMBLs led to recent approval by the US Food and Drug Administration and underscored the importance of characterizing targetable genetic vulnerabilities in this disease. Here, we report a comprehensive analysis of recurrent genetic alterations -somatic mutations, somatic copy number alterations, and structural variants-in a cohort of 37 newly diagnosed PMBLs. We identified a median of 9 genetic drivers per PMBL, including known and newly identified components of the JAK/STAT and NF-κB signaling pathways and frequent B2M alterations that limit major histocompatibility complex class I expression, as in cHL. PMBL also exhibited frequent, newly identified driver mutations in ZNF217 and an additional epigenetic modifier, EZH2. The majority of these alterations were clonal, which supports their role as early drivers. In PMBL, we identified several previously uncharacterized molecular features that may increase sensitivity to PD-1 blockade, including high tumor mutational burden, microsatellite instability, and an apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) mutational signature. The shared genetic features between PMBL and cHL provide a framework for analyzing the mechanism of action of PD-1 blockade in these related lymphoid malignancies.

ERCC2 Helicase Domain Mutations Confer Nucleotide Excision Repair Deficiency and Drive Cisplatin Sensitivity in Muscle-Invasive Bladder Cancer.

PURPOSE: DNA-damaging agents comprise the backbone of systemic treatment for many tumor types; however, few reliable predictive biomarkers are available to guide use of these agents. In muscle-invasive bladder cancer (MIBC), cisplatin-based chemotherapy improves survival, yet response varies widely among patients. Here, we sought to define the role of the nucleotide excision repair (NER) gene ERCC2 as a biomarker predictive of response to cisplatin in MIBC. EXPERIMENTAL DESIGN: Somatic missense mutations in ERCC2 are associated with improved response to cisplatin-based chemotherapy; however, clinically identified ERCC2 mutations are distributed throughout the gene, and the impact of individual ERCC2 variants on NER capacity and cisplatin sensitivity is unknown. We developed a microscopy-based NER assay to profile ERCC2 mutations observed retrospectively in prior studies and prospectively within the context of an institution-wide tumor profiling initiative. In addition, we created the first ERCC2-deficient bladder cancer preclinical model for studying the impact of ERCC2 loss of function. RESULTS: We used our functional assay to test the NER capacity of clinically observed ERCC2 mutations and found that most ERCC2 helicase domain mutations cannot support NER. Furthermore, we show that introducing an ERCC2 mutation into a bladder cancer cell line abrogates NER activity and is sufficient to drive cisplatin sensitivity in an orthotopic xenograft model. CONCLUSIONS: Our data support a direct role for ERCC2 mutations in driving cisplatin response, define the functional landscape of ERCC2 mutations in bladder cancer, and provide an opportunity to apply combined genomic and functional approaches to prospectively guide therapy decisions in bladder cancer.See related commentary by Grivas, p. 907.

Preclinical Efficacy of the Novel Monocarboxylate Transporter 1 Inhibitor BAY-8002 and Associated Markers of Resistance.

The lactate transporter SLC16A1/monocarboxylate transporter 1 (MCT1) plays a central role in tumor cell energy homeostasis. In a cell-based screen, we identified a novel class of MCT1 inhibitors, including BAY-8002, which potently suppress bidirectional lactate transport. We investigated the antiproliferative activity of BAY-8002 in a panel of 246 cancer cell lines and show that hematopoietic tumor cells, in particular diffuse large B-cell lymphoma cell lines, and subsets of solid tumor models are particularly sensitive to MCT1 inhibition. Associated markers of sensitivity were, among others, lack of MCT4 expression, low pleckstrin homology like domain family A member 2, and high pellino E3 ubiquitin protein ligase 1 expression. The antitumor effect of MCT1 inhibition was less pronounced on tumor xenografts, with tumor stasis being the maximal response. BAY-8002 significantly increased intratumor lactate levels and transiently modulated pyruvate levels. In order to address potential acquired resistance mechanisms to MCT1 inhibition, we generated MCT1 inhibitor-resistant cell lines and show that resistance can occur by upregulation of MCT4 even in the presence of sufficient oxygen, as well as by shifting energy generation toward oxidative phosphorylation. These findings provide insight into novel aspects of tumor response to MCT1 modulation and offer further rationale for patient selection in the clinical development of MCT1 inhibitors. Mol Cancer Ther; 17(11); 2285-96. ©2018 AACR.

Author Correction: Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

In the version of this article originally published, an asterisk was omitted from Fig. 1a. The asterisk has been added to the figure. Additionally, a "NOTCH2" label was erroneously included in Fig. 4a. The label has been removed. The errors have been corrected in the PDF and HTML versions of this article.

Publisher Correction: Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

In the version of this article originally published, some text above the "Tri-nucleotide sequence motifs" label in Fig. 2a appeared incorrectly. The text was garbled and should have appeared as nucleotide codes.Additionally, the labels on the bars in Fig. 2c were not italicized in the original publication. These are gene symbols, and they should have been italicized.The colored labels above the graphs in Fig. 4b were also erroneously not italicized. These labels represent gene names and loci, and they should have been italicized.

Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.

NetSig: network-based discovery from cancer genomes.

Methods that integrate molecular network information and tumor genome data could complement gene-based statistical tests to identify likely new cancer genes; but such approaches are challenging to validate at scale, and their predictive value remains unclear. We developed a robust statistic (NetSig) that integrates protein interaction networks with data from 4,742 tumor exomes. NetSig can accurately classify known driver genes in 60% of tested tumor types and predicts 62 new driver candidates. Using a quantitative experimental framework to determine in vivo tumorigenic potential in mice, we found that NetSig candidates induce tumors at rates that are comparable to those of known oncogenes and are ten-fold higher than those of random genes. By reanalyzing nine tumor-inducing NetSig candidates in 242 patients with oncogene-negative lung adenocarcinomas, we find that two (AKT2 and TFDP2) are significantly amplified. Our study presents a scalable integrated computational and experimental workflow to expand discovery from cancer genomes.

Analysis of somatic microsatellite indels identifies driver events in human tumors.

Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3).

A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer.

Biallelic inactivation of BRCA1 or BRCA2 is associated with a pattern of genome-wide mutations known as signature 3. By analyzing ∼1,000 breast cancer samples, we confirmed this association and established that germline nonsense and frameshift variants in PALB2, but not in ATM or CHEK2, can also give rise to the same signature. We were able to accurately classify missense BRCA1 or BRCA2 variants known to impair homologous recombination (HR) on the basis of this signature. Finally, we show that epigenetic silencing of RAD51C and BRCA1 by promoter methylation is strongly associated with signature 3 and, in our data set, was highly enriched in basal-like breast cancers in young individuals of African descent.

Comparison of algorithms for the detection of cancer drivers at subgene resolution.

Understanding genetic events that lead to cancer initiation and progression remains one of the biggest challenges in cancer biology. Traditionally, most algorithms for cancer-driver identification look for genes that have more mutations than expected from the average background mutation rate. However, there is now a wide variety of methods that look for nonrandom distribution of mutations within proteins as a signal for the driving role of mutations in cancer. Here we classify and review such subgene-resolution algorithms, compare their findings on four distinct cancer data sets from The Cancer Genome Atlas and discuss how predictions from these algorithms can be interpreted in the emerging paradigms that challenge the simple dichotomy between driver and passenger genes.

Phenotypic Characterization of a Comprehensive Set of MAPK1/ERK2 Missense Mutants.

Tumor-specific genomic information has the potential to guide therapeutic strategies and revolutionize patient treatment. Currently, this approach is limited by an abundance of disease-associated mutants whose biological functions and impacts on therapeutic response are uncharacterized. To begin to address this limitation, we functionally characterized nearly all (99.84%) missense mutants of MAPK1/ERK2, an essential effector of oncogenic RAS and RAF. Using this approach, we discovered rare gain- and loss-of-function ERK2 mutants found in human tumors, revealing that, in the context of this assay, mutational frequency alone cannot identify all functionally impactful mutants. Gain-of-function ERK2 mutants induced variable responses to RAF-, MEK-, and ERK-directed therapies, providing a reference for future treatment decisions. Tumor-associated mutations spatially clustered in two ERK2 effector-recruitment domains yet produced mutants with opposite phenotypes. This approach articulates an allele-characterization framework that can be scaled to meet the goals of genome-guided oncology.

Analyzing and interpreting genome data at the network level with ConsensusPathDB.

ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq. The tool reports interaction network modules, biochemical pathways and functional information that are significantly enriched by the user's input, applying computational methods for statistical over-representation, enrichment and graph analysis. The results of this protocol can be observed within a few minutes, even with genome-wide data. The resulting network associations can be used to interpret high-throughput data mechanistically, to characterize and prioritize biomarkers, to integrate different omics levels, to design follow-up functional assay experiments and to generate topology for kinetic models at different scales.

High-throughput Phenotyping of Lung Cancer Somatic Mutations.

Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas. We present an expression-based variant-impact phenotyping (eVIP) method that uses gene expression changes to distinguish impactful from neutral somatic mutations. eVIP identified 69% of mutations analyzed as impactful and 31% as functionally neutral. A subset of the impactful mutations induces xenograft tumor formation in mice and/or confers resistance to cellular EGFR inhibition. Among these impactful variants are rare somatic, clinically actionable variants including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and multiple BRAF variants, demonstrating that rare mutations can be functionally important in cancer.

Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles.

UNLABELLED: Cancer genome characterization efforts now provide an initial view of the somatic alterations in primary tumors. However, most point mutations occur at low frequency, and the function of these alleles remains undefined. We have developed a scalable systematic approach to interrogate the function of cancer-associated gene variants. We subjected 474 mutant alleles curated from 5,338 tumors to pooled in vivo tumor formation assays and gene expression profiling. We identified 12 transforming alleles, including two in genes (PIK3CB, POT1) that have not been shown to be tumorigenic. One rare KRAS allele, D33E, displayed tumorigenicity and constitutive activation of known RAS effector pathways. By comparing gene expression changes induced upon expression of wild-type and mutant alleles, we inferred the activity of specific alleles. Because alleles found to be mutated only once in 5,338 tumors rendered cells tumorigenic, these observations underscore the value of integrating genomic information with functional studies. SIGNIFICANCE: Experimentally inferring the functional status of cancer-associated mutations facilitates the interpretation of genomic information in cancer. Pooled in vivo screen and gene expression profiling identified functional variants and demonstrated that expression of rare variants induced tumorigenesis. Variant phenotyping through functional studies will facilitate defining key somatic events in cancer. Cancer Discov; 6(7); 714-26. ©2016 AACR.See related commentary by Cho and Collisson, p. 694This article is highlighted in the In This Issue feature, p. 681.