Chromosome 7 to the rescue: overcoming chromosome 10 loss in gliomas.

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers, a phenomenon that has been investigated without resolution since the late 1980s. Expanding beyond previous gene-centric studies, we investigate the co-occurrence in a genome-wide manner taking an evolutionary perspective. First, by mining large tumor aneuploidy data, we predict that the more likely order is 10 loss followed by 7 gain. Second, by analyzing extensive genomic and transcriptomic data from both patients and cell lines, we find that this co-occurrence can be explained by functional rescue interactions that are highly enriched on 7, which can possibly compensate for any detrimental consequences arising from the loss of 10. Finally, by analyzing transcriptomic data from normal, non-cancerous, human brain tissues, we provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues.

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to target tissues is challenging. To address this, we assessed whether primary and metastatic tumors resemble their tissue of origin or target tissue in terms of gene expression. We analyzed gene expression profiles from various cancer types, including single-cell and bulk RNA-seq data, in both paired and unpaired primary and metastatic patient cohorts. We quantified the transcriptomic distances between tumor samples and their normal tissues, revealing that primary tumors are more similar to their tissue of origin, while metastases shift towards the target tissue. Pathway-level analysis highlighted critical transcriptomic changes during metastasis. Notably, primary cancers exhibited higher activity in cancer hallmarks, including Activating Invasion and Metastasis , compared to metastatic cancers. This comprehensive landscape analysis provides insight into how cancer tumors adapt to their metastatic environments, providing a transcriptome-wide view of the processes involved.

Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations.

Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores-the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)-to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs.

MYC Induces Immunotherapy and IFNγ Resistance Through Downregulation of JAK2.

Immunotherapy has revolutionized the treatment of advanced melanoma. Because the pathways mediating resistance to immunotherapy are largely unknown, we conducted transcriptome profiling of preimmunotherapy tumor biopsies from patients with melanoma that received PD-1 blockade or adoptive cell therapy with tumor-infiltrating lymphocytes. We identified two melanoma-intrinsic, mutually exclusive gene programs, which were controlled by IFNγ and MYC, and the association with immunotherapy outcome. MYC-overexpressing melanoma cells exhibited lower IFNγ responsiveness, which was linked with JAK2 downregulation. Luciferase activity assays, under the control of JAK2 promoter, demonstrated reduced activity in MYC-overexpressing cells, which was partly reversible upon mutagenesis of a MYC E-box binding site in the JAK2 promoter. Moreover, silencing of MYC or its cofactor MAX with siRNA increased JAK2 expression and IFNγ responsiveness of melanomas, while concomitantly enhancing the effector functions of T cells coincubated with MYC-overexpressing cells. Thus, we propose that MYC plays a pivotal role in immunotherapy resistance through downregulation of JAK2.

Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome.

BACKGROUND: Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. METHODS: We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient's response to a variety of therapies in multiple cancer types without training on previous treatment response data. We study ENLIGHT in two translationally oriented scenarios: personalized oncology (PO), aimed at prioritizing treatments for a single patient, and clinical trial design (CTD), selecting the most likely responders in a patient cohort. FINDINGS: Evaluating ENLIGHT's performance on 21 blinded clinical trial datasets in the PO setting, we show that it can effectively predict a patient's treatment response across multiple therapies and cancer types. Its prediction accuracy is better than previously published transcriptomics-based signatures and is comparable with that of supervised predictors developed for specific indications and drugs. In combination with the interferon-γ signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, ENLIGHT can potentially enhance clinical trial success for immunotherapies and other monoclonal antibodies by excluding non-responders while overall achieving more than 90% of the response rate attainable under an optimal exclusion strategy. CONCLUSIONS: ENLIGHT demonstrably enhances the ability to predict therapeutic response across multiple cancer types from the bulk tumor transcriptome. FUNDING: This research was supported in part by the Intramural Research Program, NIH and by the Israeli Innovation Authority.

Alternative cleavage and polyadenylation generates downstream uncapped RNA isoforms with translation potential.

The use of alternative promoters, splicing, and cleavage and polyadenylation (APA) generates mRNA isoforms that expand the diversity and complexity of the transcriptome. Here, we uncovered thousands of previously undescribed 5' uncapped and polyadenylated transcripts (5' UPTs). We show that these transcripts resist exonucleases due to a highly structured RNA and N6-methyladenosine modification at their 5' termini. 5' UPTs appear downstream of APA sites within their host genes and are induced upon APA activation. Strong enrichment in polysomal RNA fractions indicates 5' UPT translational potential. Indeed, APA promotes downstream translation initiation, non-canonical protein output, and consistent changes to peptide presentation at the cell surface. Lastly, we demonstrate the biological importance of 5' UPTs using Bcl2, a prominent anti-apoptotic gene whose entire coding sequence is a 5' UPT generated from 5' UTR-embedded APA sites. Thus, APA is not only accountable for terminating transcripts, but also for generating downstream uncapped RNAs with translation potential and biological impact.

A cell-type-specific atlas of the inner ear transcriptional response to acoustic trauma.

Noise-induced hearing loss (NIHL) results from a complex interplay of damage to the sensory cells of the inner ear, dysfunction of its lateral wall, axonal retraction of type 1C spiral ganglion neurons, and activation of the immune response. We use RiboTag and single-cell RNA sequencing to survey the cell-type-specific molecular landscape of the mouse inner ear before and after noise trauma. We identify induction of the transcription factors STAT3 and IRF7 and immune-related genes across all cell-types. Yet, cell-type-specific transcriptomic changes dominate the response. The ATF3/ATF4 stress-response pathway is robustly induced in the type 1A noise-resilient neurons, potassium transport genes are downregulated in the lateral wall, mRNA metabolism genes are downregulated in outer hair cells, and deafness-associated genes are downregulated in most cell types. This transcriptomic resource is available via the Gene Expression Analysis Resource (gEAR; https://umgear.org/NIHL) and provides a blueprint for the rational development of drugs to prevent and treat NIHL.

Genetic mapping of developmental trajectories for complex traits and diseases.

Genome-wide association studies (GWAS) have identified numerous common genetic variants associated with complex human traits and diseases. However, the translation of GWAS discoveries into biological and clinical insights is highly challenging. In this study, we present a novel bioinformatics approach for enhancing the functional interpretation of GWAS signals, based on their integration with single-cell (sc)RNA-seq datasets that examine developmental processes. Our approach performs three tasks: (1) Identification of links between cell differentiation trajectories and traits; (2) Elucidation of biological processes and molecular pathways that underlie such trajectory-trait links; and (3) Prioritization of target genes that carry the links between trajectories, pathways and traits. We applied our method to a set of 11 traits of various pathologies, and 12 scRNA-seq datasets of diverse developmental processes, and it readily detected well-established biological connections, including those between the maturation of cortical inhibitory interneurons and schizophrenia, hepatocytes and cholesterol levels, and pancreatic beta-islet cells and type-2 diabetes. For each of these associations, our method pinpointed top candidate genes that are strongly associated with both the kinetics of the differentiation trajectory and the disease's genetic risk. By the identification of trajectory-disease links, molecular pathways that underlie them and prioritizing candidate risk genes, our method improves the understanding of the etiology of complex diseases, and thus holds promise for enhancing rational drug development that is aimed at targeting specific biological processes that mediate the genetic predisposition to diseases.

Systematic identification of functional SNPs interrupting 3'UTR polyadenylation signals.

Alternative polyadenylation (APA) is emerging as a widespread regulatory layer since the majority of human protein-coding genes contain several polyadenylation (p(A)) sites in their 3'UTRs. By generating isoforms with different 3'UTR length, APA potentially affects mRNA stability, translation efficiency, nuclear export, and cellular localization. Polyadenylation sites are regulated by adjacent RNA cis-regulatory elements, the principals among them are the polyadenylation signal (PAS) AAUAAA and its main variant AUUAAA, typically located ~20-nt upstream of the p(A) site. Mutations in PAS and other auxiliary poly(A) cis-elements in the 3'UTR of several genes have been shown to cause human Mendelian diseases, and to date, only a few common SNPs that regulate APA were associated with complex diseases. Here, we systematically searched for SNPs that affect gene expression and human traits by modulation of 3'UTR APA. First, focusing on the variants most likely to exert the strongest effect, we identified 2,305 SNPs that interrupt the canonical PAS or its main variant. Implementing pA-QTL tests using GTEx RNA-seq data, we identified 330 PAS SNPs (called PAS pA-QTLs) that were significantly associated with the usage of their p(A) site. As expected, PAS-interrupting alleles were mostly linked with decreased cleavage at their p(A) site and the consequential 3'UTR lengthening. However, interestingly, in ~10% of the cases, the PAS-interrupting allele was associated with increased usage of an upstream p(A) site and 3'UTR shortening. As an indication of the functional effects of these PAS pA-QTLs on gene expression and complex human traits, we observed for few dozens of them marked colocalization with eQTL and/or GWAS signals. The PAS-interrupting alleles linked with 3'UTR lengthening were also strongly associated with decreased gene expression, indicating that shorter isoforms generated by APA are generally more stable than longer ones. Last, we carried out an extended, genome-wide analysis of 3'UTR variants and detected thousands of additional pA-QTLs having weaker effects compared to the PAS pA-QTLs.

Cell-type-specific analysis of alternative polyadenylation using single-cell transcriptomics data.

Alternative polyadenylation (APA) is emerging as an important layer of gene regulation because the majority of mammalian protein-coding genes contain multiple polyadenylation (pA) sites in their 3' UTR. By alteration of 3' UTR length, APA can considerably affect post-transcriptional gene regulation. Yet, our understanding of APA remains rudimentary. Novel single-cell RNA sequencing (scRNA-seq) techniques allow molecular characterization of different cell types to an unprecedented degree. Notably, the most popular scRNA-seq protocols specifically sequence the 3' end of transcripts. Building on this property, we implemented a method for analysing patterns of APA regulation from such data. Analyzing multiple datasets from diverse tissues, we identified widespread modulation of APA in different cell types resulting in global 3' UTR shortening/lengthening and enhanced cleavage at intronic pA sites. Our results provide a proof-of-concept demonstration that the huge volume of scRNA-seq data that accumulates in the public domain offers a unique resource for the exploration of APA based on a very broad collection of cell types and biological conditions.