Cas13d-mediated isoform-specific RNA knockdown with a unified computational and experimental toolbox.

Alternative splicing is an essential mechanism for diversifying proteins, in which mature RNA isoforms produce proteins with potentially distinct functions. Two major challenges in characterizing the cellular function of isoforms are the lack of experimental methods to specifically and efficiently modulate isoform expression and computational tools for complex experimental design. To address these gaps, we developed and methodically tested a strategy which pairs the RNA-targeting CRISPR/Cas13d system with guide RNAs that span exon-exon junctions in the mature RNA. We performed a high-throughput essentiality screen, quantitative RT-PCR assays, and PacBio long read sequencing to affirm our ability to specifically target and robustly knockdown individual RNA isoforms. In parallel, we provide computational tools for experimental design and screen analysis. Considering all possible splice junctions annotated in GENCODE for multi-isoform genes and our gRNA efficacy predictions, we estimate that our junction-centric strategy can uniquely target up to 89% of human RNA isoforms, including 50,066 protein-coding and 11,415 lncRNA isoforms. Importantly, this specificity spans all splicing and transcriptional events, including exon skipping and inclusion, alternative 5' and 3' splice sites, and alternative starts and ends.

In-depth characterization of intratumoral heterogeneity in refractory B-cell non-Hodgkin lymphoma through the lens of a Research Autopsy Program.

Intratumoral heterogeneity (ITH) provides the substrate for tumor evolution and treatment resistance, yet is remarkably understudied in lymphoma, due to the often limited amount of tissue that gets sampled during the routine diagnostic process, generally from a single nodal or extranodal site. Furthermore, the trajectory of how lymphoma, and especially non-Hodgkin lymphoma, spreads throughout the human body remains poorly understood. Here, we present a detailed characterization of ITH by applying whole-genome sequencing to spatially separated tumor samples harvested at the time of autopsy (n=24) and/or diagnosis (n=3) in three patients presenting with refractory B-cell non-Hodgkin lymphoma. Through deconvolution of bulk samples into clonal mixtures and inference of phylogenetic trees, we found evidence that polyclonal seeding underlies tumor dissemination in lymphoma. We identify mutation signatures associated with ancestral and descendant clones. In our series of patients with highly refractory lymphoma, the determinants of resistance were often harbored by founding clones, although there was also evidence of positive selection of driver mutations, likely under the influence of therapy. Lastly, we show that circulating tumor DNA is suitable for the detection of ancestral mutations but may miss a significant proportion of private mutations that can be detected in tissue. Our study clearly shows the existence of intricate patterns of regional and anatomical evolution that can only be disentangled through multi-regional tumor tissue profiling.

Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas.

Long non-coding RNAs (lncRNAs) are increasingly recognized as functional units in cancer and powerful biomarkers; however, most remain uncharacterized. Here, we analyze 5,592 prognostic lncRNAs in 9,446 cancers of 30 types using machine learning. We identify 166 lncRNAs whose expression correlates with survival and improves the accuracy of common clinical variables, molecular features, and cancer subtypes. Prognostic lncRNAs are often characterized by switch-like expression patterns. In low-grade gliomas, HOXA10-AS activation is a robust marker of poor prognosis that complements IDH1/2 mutations, as validated in another retrospective cohort, and correlates with developmental pathways in tumor transcriptomes. Loss- and gain-of-function studies in patient-derived glioma cells, organoids, and xenograft models identify HOXA10-AS as a potent onco-lncRNA that regulates cell proliferation, contact inhibition, invasion, Hippo signaling, and mitotic and neuro-developmental pathways. Our study underscores the pan-cancer potential of the non-coding transcriptome for identifying biomarkers and regulators of cancer progression.

Combined EZH2 Inhibition and IKAROS Degradation Leads to Enhanced Antitumor Activity in Diffuse Large B-cell Lymphoma.

PURPOSE: The efficacy of EZH2 inhibition has been modest in the initial clinical exploration of diffuse large B-cell lymphoma (DLBCL), yet EZH2 inhibitors are well tolerated. Herein, we aimed to uncover genetic and pharmacologic opportunities to enhance the clinical efficacy of EZH2 inhibitors in DLBCL. EXPERIMENTAL DESIGN: We conducted a genome-wide sensitizing CRISPR/Cas9 screen with tazemetostat, a catalytic inhibitor of EZH2. The sensitizing effect of IKZF1 loss of function was then validated and leveraged for combination treatment with lenalidomide. RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing analyses were performed to elucidate transcriptomic and epigenetic changes underlying synergy. RESULTS: We identified IKZF1 knockout as the top candidate for sensitizing DLBCL cells to tazemetostat. Treating cells with tazemetostat and lenalidomide, an immunomodulatory drug that selectively degrades IKAROS and AIOLOS, phenocopied the effects of the CRISPR/Cas9 screen. The combined drug treatment triggered either cell-cycle arrest or apoptosis in a broad range of DLBCL cell lines, regardless of EZH2 mutational status. Cell-line-based xenografts also showed slower tumor growth and prolonged survival in the combination treatment group. RNA-seq analysis revealed strong upregulation of interferon signaling and antiviral immune response signatures. Gene expression of key immune response factors such as IRF7 and DDX58 were induced in cells treated with lenalidomide and tazemetostat, with a concomitant increase of H3K27 acetylation at their promoters. Furthermore, transcriptome analysis demonstrated derepression of endogenous retroviruses after combination treatment. CONCLUSIONS: Our data underscore the synergistic interplay between IKAROS degradation and EZH2 inhibition on modulating epigenetic changes and ultimately enhancing antitumor effects in DLBCL.

A risk model for relapsed/refractory aggressive NHL integrating clinical risk factors and pretransplant Deauville score.

There are limited data regarding the combined value of the pretransplant Deauville score (DS) from a positron emission tomography scan and clinical risk factors in patients with relapsed/refractory aggressive non-Hodgkin lymphoma (NHL). We performed a retrospective analysis to assess the prognostic role of pretransplant DS in patients with relapsed/refractory aggressive NHL who underwent salvage chemotherapy and autologous stem cell transplantation (ASCT). We identified 174 eligible patients between January 2013 and March 2019. In multivariable analysis, pretransplant DS, B symptoms, and secondary International Prognostic Index (sIPI) were independent risk factors for event-free survival (EFS). These variables were used to derive an integrated risk score that categorized 166 patients with available information for all risk factors into 3 groups: low (n = 92; 55.4%), intermediate (n = 48; 28.9%), and high (n = 26; 15.7%). The new prognostic index showed a strong association with EFS (low-risk vs intermediate-risk hazard ratio [HR], 3.94; 95% confidence interval [CI], 2.16-7.17; P < .001; low-risk vs high-risk HR, 10.83; 95% CI, 5.81-20.19; P < .001) and outperformed models based on clinical risk factors or DS alone. These results were validated in 60 patients from an independent external cohort (low-risk vs intermediate-risk HR, 4.04; 95% CI, 1.51-10.82; P = .005; low-risk vs high-risk HR, 10.49; 95% CI, 4.11-26.73; P < .001). We propose and validate a new prognostic index that risk-stratifies patients undergoing salvage chemotherapy followed by ASCT, thereby identifying patients at high risk for posttransplant treatment failure.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks.

A comprehensive catalog of cancer driver mutations is essential for understanding tumorigenesis and developing therapies. Exome-sequencing studies have mapped many protein-coding drivers, yet few non-coding drivers are known because genome-wide discovery is challenging. We developed a driver discovery method, ActiveDriverWGS, and analyzed 120,788 cis-regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project. We found 30 CRMs with enriched SNVs and indels (FDR < 0.05). These frequently mutated regulatory elements (FMREs) were ubiquitously active in human tissues, showed long-range chromatin interactions and mRNA abundance associations with target genes, and were enriched in motif-rewiring mutations and structural variants. Genomic deletion of one FMRE in human cells caused proliferative deficiencies and transcriptional deregulation of cancer genes CCNB1IP1, CDH1, and CDKN2B, validating observations in FMRE-mutated tumors. Pathway analysis revealed further sub-significant FMREs at cancer genes and processes, indicating an unexplored landscape of infrequent driver mutations in the non-coding genome.

ID1 Is Critical for Tumorigenesis and Regulates Chemoresistance in Glioblastoma.

Glioblastoma is the most common primary brain tumor in adults. While the introduction of temozolomide chemotherapy has increased long-term survivorship, treatment failure and rapid tumor recurrence remains universal. The transcriptional regulatory protein, inhibitor of DNA-binding-1 (ID1), is a key regulator of cell phenotype in cancer. We show that CRISPR-mediated knockout of ID1 in glioblastoma cells, breast adenocarcinoma cells, and melanoma cells dramatically reduced tumor progression in all three cancer systems through transcriptional downregulation of EGF, which resulted in decreased EGFR phosphorylation. Moreover, ID1-positive cells were enriched by chemotherapy and drove tumor recurrence in glioblastoma. Addition of the neuroleptic drug pimozide to inhibit ID1 expression enhanced the cytotoxic effects of temozolomide therapy on glioma cells and significantly prolonged time to tumor recurrence. Conclusively, these data suggest ID1 could be a promising therapeutic target in patients with glioblastoma. SIGNIFICANCE: These findings show that the transcriptional regulator ID1 is critical for glioblastoma initiation and chemoresistance and that inhibition of ID1 enhances the effect of temozolomide, delays tumor recurrence, and prolongs survival.

Intertumoral Heterogeneity within Medulloblastoma Subgroups.

While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of medulloblastoma. Integrative analysis using SNF further delineates group 3 from group 4 medulloblastoma, which is not as readily apparent through analyses of individual data types. Two clear subtypes of infants with Sonic Hedgehog medulloblastoma with disparate outcomes and biology are identified. Medulloblastoma subtypes identified through integrative clustering have important implications for stratification of future clinical trials.

Noncoding RNA for personalized prostate cancer treatment: utilizing the 'dark matters' of the genome.

Prostate cancer is the most commonly diagnosed cancer in men in western countries, with significant health impact. Clinically, it is complicated with the lack of biomarkers and effective treatments for aggressive disease, particularly castration-resistant prostate cancer. Although we have gained much insight into the biology of prostate cancer through studying protein-coding genes, they represent only a small fraction of our genome. Therefore, it is essential for us to investigate noncoding RNAs, which comprise the majority of our transcriptome, in order to achieve a better understanding of prostate cancer and move toward personalized medicine. In this article, we will address recent advancements in our knowledge of noncoding RNAs, and discuss the clinical potentials and challenges of different types of noncoding RNAs in prostate cancer.