Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival

ER export via SURF4 uses diverse mechanisms of both client and coat engagement

Protein secretion is an essential process that drives cell growth and communication. Enrichment of soluble secretory proteins into ER-derived transport carriers occurs via transmembrane cargo receptors that connect lumenal cargo to the cytosolic COPII coat. Here, we find that the cargo receptor, SURF4, recruits different SEC24 cargo adaptor paralogs of the COPII coat to export different cargoes. The secreted protease, PCSK9, requires both SURF4 and a co-receptor, TMED10, for export via SEC24A. In contrast, secretion of Cab45 and NUCB1 requires SEC24C/D. We further show that ER export signals of Cab45 and NUCB1 bind co-translationally to SURF4 via a lumenal pocket, contrasting prevailing models of receptor engagement only upon protein folding/maturation. Bioinformatics analyses suggest that strong SURF4-binding motifs are features of proteases, receptor-binding ligands, and Ca2+-binding proteins. We propose that certain classes of proteins are fast-tracked for rapid export to protect the health of the ER lumen.

Transipedia.org: k-mer-based exploration of large RNA sequencing datasets and application to cancer data

Indexing techniques relying on k-mers have proven effective in searching for RNA sequences across thousands of RNA-seq libraries, but without enabling direct RNA quantification. We show here that arbitrary RNA sequences can be quantified in seconds through their decomposition into k-mers, with a precision akin to that of conventional RNA quantification methods. Using an index of the Cancer Cell Line Encyclopedia (CCLE) collection consisting of 1019 RNA-seq samples, we show that k-mer indexing offers a powerful means to reveal non-reference sequences, and variant RNAs induced by specific gene alterations, for instance in splicing factors.

Building a translational cancer dependency map for The Cancer Genome Atlas

Cancer dependency maps have accelerated the discovery of tumor vulnerabilities that can be exploited as drug targets when translatable to patients. The Cancer Genome Atlas (TCGA) is a compendium of 'maps' detailing the genetic, epigenetic and molecular changes that occur during the pathogenesis of cancer, yet it lacks a dependency map to translate gene essentiality in patient tumors. Here, we used machine learning to build translational dependency maps for patient tumors, which identified tumor vulnerabilities that predict drug responses and disease outcomes. A similar approach was used to map gene tolerability in healthy tissues to prioritize tumor vulnerabilities with the best therapeutic windows. A subset of patient-translatable synthetic lethalities were experimentally tested, including PAPSS1/PAPSS12 and CNOT7/CNOT78, which were validated in vitro and in vivo. Notably, PAPSS1 synthetic lethality was driven by collateral deletion of PAPSS2 with PTEN and was correlated with patient survival. Finally, the translational dependency map is provided as a web-based application for exploring tumor vulnerabilities.

Generation of a biliary tract cancer cell line atlas reveals molecular subtypes and therapeutic targets

Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.

Somatic structural variants drive distinct modes of oncogenesis in melanoma

The diversity of structural variants (SVs) in melanoma and how they impact oncogenesis are incompletely known. We performed harmonized analysis of SVs across melanoma histologic and genomic subtypes, and we identified distinct global properties between subtypes. These included the frequency and size of SVs and SV classes, their relation to chromothripsis events, and the impact on cancer-related genes of SVs that alter topologically associated domain (TAD) boundaries. Following our prior identification of double-stranded break repair deficiency in a subset of triple-wild-type cutaneous melanoma, we identified MRE11 and NBN loss-of-function SVs in melanomas with this mutational signature. Experimental knockouts of MRE11 and NBN, followed by olaparib cell viability assays in melanoma cells, indicated that dysregulation of each of these genes may cause sensitivity to PARP inhibitors in cutaneous melanomas. Broadly, harmonized analysis of melanoma SVs revealed distinct global genomic properties and molecular drivers, which may have biological and therapeutic impact.

A novel pipeline for prioritizing cancer type-specific therapeutic vulnerabilities using DepMap identifies PAK2 as a target in head and neck squamous cell carcinomas

There is limited guidance on exploiting the genome-wide loss-of-function CRISPR screens in cancer Dependency Map (DepMap) to identify new targets for individual cancer types. This study integrated multiple tools to filter these data in order to seek new therapeutic targets specific to head and neck squamous cell carcinoma (HNSCC). The resulting pipeline prioritized 143 targetable dependencies that represented both well-studied targets and emerging target classes like mitochondrial carriers and RNA-binding proteins. In total, 14 targets had clinical inhibitors used for other cancers or nonmalignant diseases that hold near-term potential to repurpose for HNSCC therapy. Comparing inhibitor response data that were publicly available for 13 prioritized targets between the cell lines with high vs. low dependency on each target uncovered novel therapeutic potential for the PAK2 serine/threonine kinase. PAK2 gene dependency was found to be associated with wild-type p53, low PAK2 mRNA, and diploid status of the 3q amplicon containing PAK2. These findings establish a generalizable pipeline to prioritize clinically relevant targets for individual cancer types using DepMap. Its application to HNSCC highlights novel relevance for PAK2 inhibition and identifies biomarkers of PAK2 inhibitor response.

Alternative polyadenylation-related genetic variants contribute to bladder cancer risk

Aberrant alternative polyadenylation (APA) events play an important role in cancers, but little is known about whether APA-related genetic variants contribute to the susceptibility to bladder cancer. Previous genome-wide association study performed APA quantitative trait loci (apaQTL) analyses in bladder cancer, and identified 17 955 single nucleotide polymorphisms (SNPs). We found that gene symbols of APA affected by apaQTL-associated SNPs were closely correlated with cancer signaling pathways, high mutational burden, and immune infiltration. Association analysis showed that apaQTL-associated SNPs rs34402449 C>A, rs2683524 C>T, and rs11540872 C>G were significantly associated with susceptibility to bladder cancer (rs34402449: OR = 1.355, 95% confidence interval [CI]: 1.159-1.583, P = 1.33 × 10 -4; rs2683524: OR = 1.378, 95% CI: 1.164-1.632, P = 2.03 × 10 -4; rs11540872: OR = 1.472, 95% CI: 1.193-1.815, P = 3.06 × 10 -4). Cumulative effect analysis showed that the number of risk genotypes and smoking status were significantly associated with an increased risk of bladder cancer ( P trend = 2.87 × 10 -12). We found that PRR13, being demonstrated the most significant effect on cell proliferation in bladder cancer cell lines, was more highly expressed in bladder cancer tissues than in adjacent normal tissues. Moreover, the rs2683524 T allele was correlated with shorter 3' untranslated regions of PRR13 and increased PRR13 expression levels. Collectively, our findings have provided informative apaQTL resources and insights into the regulatory mechanisms linking apaQTL-associated variants to bladder cancer risk.

Functional and regulatory impact of chimeric RNAs in human normal and cancer cells

Fusions of two genes can lead to the generation of chimeric RNAs, which may have a distinct functional role from their original molecules. Chimeric RNAs could encode novel functional proteins or serve as novel long noncoding RNAs (lncRNAs). The appearance of chimeric RNAs in a cell could help to generate new functionality and phenotypic diversity that might facilitate this cell to survive against new environmental stress. Several recent studies have demonstrated the functional roles of various chimeric RNAs in cancer progression and are considered as biomarkers for cancer diagnosis and sometimes even drug targets. Further, the growing evidence demonstrated the potential functional association of chimeric RNAs with cancer heterogeneity and drug resistance cancer evolution. Recent studies highlighted that chimeric RNAs also have functional potentiality in normal physiological processes. Several functionally potential chimeric RNAs were discovered in human cancer and normal cells in the last two decades. This could indicate that chimeric RNAs are the hidden layer of the human transcriptome that should be explored from the functional insights to better understand the functional evolution of the genome and disease development that could facilitate clinical practice improvements. This review summarizes the current knowledge of chimeric RNAs and highlights their functional, regulatory, and evolutionary impact on different cancers and normal physiological processes. Further, we will discuss the potential functional roles of a recently discovered novel class of chimeric RNAs named sense-antisense/cross-strand chimeric RNAs generated by the fusion of the bi-directional transcripts of the same gene. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

IMOPAC: A web server for interactive multiomics and pharmacological analyses of patient-derived cancer cell lines

Large-scale multidimensional cancer genomic and pharmacological profiles have been created by several large consortium projects, including NCI-60, GDSC and DepMap, providing novel opportunities for data mining and further understanding of intrinsic therapeutic response mechanisms. However, it is increasingly challenging for experimental biologists, especially those without a bioinformatic background, to integrate, explore, and analyse these tremendous pharmacogenomics. To address this gap, IMOPAC, an interactive and easy-to-use web-based tool, was introduced to provide rapid visualizations and customizable functionalities on the basis of these three publicly available databases, which may reduce pharmacogenomic profiles from cell lines into readily understandable genetic, epigenetic, transcriptionomic, proteomic, metabolomic, and pharmacological events. The user-friendly query interface together with customized data storage enables users to interactively investigate and visualize multiomics alterations across genes and pathways and to link these alterations with drug responses across cell lines from diverse cancer types. The analyses in our portal include pancancer expression, drug-omics/pathway correlation, cancer subtypes, omics-omics (cis-/trans-regulation) correlation, fusion query analysis, and drug response prediction analysis. The comprehensive multiomics and pharmacogenomic analyses with simple clicking through IMOPAC will significantly benefit cancer precision medicine, contribute to the discoveries of potential biological mechanisms and facilitate pharmacogenomics mining in the identification of clinically actionable biomarkers for both basic researchers and clinical practitioners. IMOPAC is freely available at http://www.hbpding.com/IMOPAC.

Biological and clinical implications of FGFR aberrations in paediatric and young adult cancers

Rare but recurrent mutations in the fibroblast growth factor receptor (FGFR) pathways, most commonly in one of the four FGFR receptor tyrosine kinase genes, can potentially be targeted with broad-spectrum multi-kinase or FGFR selective inhibitors. The complete spectrum of these mutations in paediatric cancers is emerging as precision medicine programs perform comprehensive sequencing of individual tumours. Identification of patients most likely to benefit from FGFR inhibition currently rests on identifying activating FGFR mutations, gene fusions, or gene amplification events. However, the expanding use of transcriptome sequencing (RNAseq) has identified that many tumours overexpress FGFRs, in the absence of any genomic aberration. The challenge now presented is to determine when this indicates true FGFR oncogenic activity. Under-appreciated mechanisms of FGFR pathway activation, including alternate FGFR transcript expression and concomitant FGFR and FGF ligand expression, may mark those tumours where FGFR overexpression is indicative of a dependence on FGFR signalling. In this review, we provide a comprehensive and mechanistic overview of FGFR pathway aberrations and their functional consequences in paediatric cancer. We explore how FGFR over expression might be associated with true receptor activation. Further, we discuss the therapeutic implications of these aberrations in the paediatric setting and outline current and emerging therapeutic strategies to treat paediatric patients with FGFR-driven cancers.

Analysis of Cancer Genomic Amplifications Identifies Druggable Collateral Dependencies within the Amplicon

The identification of novel therapeutic targets for specific cancer molecular subtypes is crucial for the development of precision oncology. In the last few years, CRISPR/Cas9 screens have accelerated the discovery and validation of new targets associated with different tumor types, mutations, and fusions. However, there are still many cancer vulnerabilities associated with specific molecular features that remain to be explored. Here, we used data from CRISPR/Cas9 screens in 954 cancer cell lines to identify gene dependencies associated with 16 common cancer genomic amplifications. We found that high-copy-number genomic amplifications generate multiple collateral dependencies within the amplified region in most cases. Further, to prioritize candidate targets for each chromosomal region amplified, we integrated gene dependency parameters with both druggability data and subcellular location. Finally, analysis of the relationship between gene expression and gene dependency led to the identification of genes, the expression of which may constitute predictive biomarkers of dependency. In conclusion, our study provides a set of druggable targets specific for each amplification, opening the possibility to specifically target amplified tumors on this basis.

VRK1 Is a Synthetic-Lethal Target in VRK2-Deficient Glioblastoma

Synthetic lethality is a genetic interaction that results in cell death when two genetic deficiencies co-occur but not when either deficiency occurs alone, which can be co-opted for cancer therapeutics. Pairs of paralog genes are among the most straightforward potential synthetic-lethal interactions by virtue of their redundant functions. Here, we demonstrate a paralog-based synthetic lethality by targeting vaccinia-related kinase 1 (VRK1) in glioblastoma (GBM) deficient of VRK2, which is silenced by promoter methylation in approximately two thirds of GBM. Genetic knockdown of VRK1 in VRK2-null or VRK2-methylated cells resulted in decreased activity of the downstream substrate barrier to autointegration factor (BAF), a regulator of post-mitotic nuclear envelope formation. Reduced BAF activity following VRK1 knockdown caused nuclear lobulation, blebbing, and micronucleation, which subsequently resulted in G2-M arrest and DNA damage. The VRK1-VRK2 synthetic-lethal interaction was dependent on VRK1 kinase activity and was rescued by ectopic expression of VRK2. In VRK2-methylated GBM cell line-derived xenograft and patient-derived xenograft models, knockdown of VRK1 led to robust tumor growth inhibition. These results indicate that inhibiting VRK1 kinase activity could be a viable therapeutic strategy in VRK2-methylated GBM.

SIGNIFICANCE

A paralog synthetic-lethal interaction between VRK1 and VRK2 sensitizes VRK2-methylated glioblastoma to perturbation of VRK1 kinase activity, supporting VRK1 as a drug discovery target in this disease.