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Recently it has become clear that only a small percentage (7%) of disease-associated single nucleotide polymorphisms (SNPs) are located in protein-coding regions, while the remaining 93% are located in gene regulatory regions or in intergenic regions. Thus, the understanding of how genetic variations control the expression of non-coding RNAs (in a tissue-dependent manner) has far-reaching implications. We tested the association of SNPs with expression levels (eQTLs) of large intergenic non-coding RNAs (lincRNAs), using genome-wide gene expression and genotype data from five different tissues. We identified 112 cis-regulated lincRNAs, of which 45% could be replicated in an independent dataset. We observed that 75% of the SNPs affecting lincRNA expression (lincRNA cis-eQTLs) were specific to lincRNA alone and did not affect the expression of neighboring protein-coding genes. We show that this specific genotype-lincRNA expression correlation is tissue-dependent and that many of these lincRNA cis-eQTL SNPs are also associated with complex traits and diseases.

Loss of BRCA2 affects genome stability and is deleterious for cellular survival. Using a genome-wide genetic screen in near-haploid KBM-7 cells, we show that tumor necrosis factor-alpha (TNFα) signaling is a determinant of cell survival upon BRCA2 inactivation. Specifically, inactivation of the TNF receptor (TNFR1) or its downstream effector SAM68 rescues cell death induced by BRCA2 inactivation. BRCA2 inactivation leads to pro-inflammatory cytokine production, including TNFα, and increases sensitivity to TNFα. Enhanced TNFα sensitivity is not restricted to BRCA2 inactivation, as BRCA1 or FANCD2 inactivation, or hydroxyurea treatment also sensitizes cells to TNFα. Mechanistically, BRCA2 inactivation leads to cGAS-positive micronuclei and results in a cell-intrinsic interferon response, as assessed by quantitative mass-spectrometry and gene expression profiling, and requires ASK1 and JNK signaling. Combined, our data reveals that micronuclei induced by loss of BRCA2 instigate a cGAS/STING-mediated interferon response, which encompasses re-wired TNFα signaling and enhances TNFα sensitivity. The loss of homologous recombination (HR) genes such as BRCA1 and BRCA2 is deleterious to the survival of normal cells, yet it is tolerated in cancer cells. Here the authors identify TNFα signaling as a determinant of viability in BRCA2 - inactivated cancer cells.

The composition of the gut microbiome has been associated with clinical responses to immune checkpoint inhibitor (ICI) treatment, but there is limited consensus on the specific microbiome characteristics linked to the clinical benefits of ICIs. We performed shotgun metagenomic sequencing of stool samples collected before ICI initiation from five observational cohorts recruiting ICI-naive patients with advanced cutaneous melanoma ( n  = 165). Integrating the dataset with 147 metagenomic samples from previously published studies, we found that the gut microbiome has a relevant, but cohort-dependent, association with the response to ICIs. A machine learning analysis confirmed the link between the microbiome and overall response rates (ORRs) and progression-free survival (PFS) with ICIs but also revealed limited reproducibility of microbiome-based signatures across cohorts. Accordingly, a panel of species, including Bifidobacterium pseudocatenulatum , Roseburia spp. and Akkermansia muciniphila , associated with responders was identified, but no single species could be regarded as a fully consistent biomarker across studies. Overall, the role of the human gut microbiome in ICI response appears more complex than previously thought, extending beyond differing microbial species simply present or absent in responders and nonresponders. Future studies should adopt larger sample sizes and take into account the complex interplay of clinical factors with the gut microbiome over the treatment course. An analysis of metagenomic sequencing of stool samples from multiple cohorts of patients with melanoma treated with immune checkpoint blockade uncovers microbiome correlates of response to therapy and also reveals widespread variability across populations.

Copy number alterations (CNAs) can promote tumor progression by altering gene expression levels. Due to transcriptional adaptive mechanisms, however, CNAs do not always translate proportionally into altered expression levels. By reanalyzing >34,000 gene expression profiles, we reveal the degree of transcriptional adaptation to CNAs in a genome-wide fashion, which strongly associate with distinct biological processes. We then develop a platform-independent method—transcriptional adaptation to CNA profiling (TACNA profiling)—that extracts the transcriptional effects of CNAs from gene expression profiles without requiring paired CNA profiles. By applying TACNA profiling to >28,000 patient-derived tumor samples we define the landscape of transcriptional effects of CNAs. The utility of this landscape is demonstrated by the identification of four genes that are predicted to be involved in tumor immune evasion when transcriptionally affected by CNAs. In conclusion, we provide a novel tool to gain insight into how CNAs drive tumor behavior via altered expression levels. Copy number alterations (CNAs) can drive tumor progression in cancer by altering gene expression levels, but transcriptional adaption can skew CNA impact. Here, the authors present transcriptional adaptation to CNA (TACNA) profiling; a tool to extract the transcriptional effect of CNAs from expression data without requiring paired CNA profiles.

Multiple clinical trials targeting the gut microbiome are being conducted to optimize treatment outcomes for immune checkpoint blockade (ICB). To improve the success of these interventions, understanding gut microbiome changes during ICB is urgently needed. Here through longitudinal microbiome profiling of 175 patients treated with ICB for advanced melanoma, we show that several microbial species-level genome bins (SGBs) and pathways exhibit distinct patterns from baseline in patients achieving progression-free survival (PFS) of 12 months or longer (PFS ≥12) versus patients with PFS shorter than 12 months (PFS <12). Out of 99 SGBs that could discriminate between these two groups, 20 were differentially abundant only at baseline, while 42 were differentially abundant only after treatment initiation. We identify five and four SGBs that had consistently higher abundances in patients with PFS ≥12 and <12 months, respectively. Constructing a log ratio of these SGBs, we find an association with overall survival. Finally, we find different microbial dynamics in different clinical contexts including the type of ICB regimen, development of immune-related adverse events and concomitant medication use. Insights into the longitudinal dynamics of the gut microbiome in association with host factors and treatment regimens will be critical for guiding rational microbiome-targeted therapies aimed at enhancing ICB efficacy. Understanding the dynamics of the gut microbiota over the course of cancer treatment regimens and their associated adverse events can help identify microbial features that associate with response to immune checkpoint blockade.

Immune checkpoint inhibitors (ICIs), by reinvigorating CD8 + T cell mediated immunity, have revolutionized cancer therapy. Yet, the systemic CD8 + T cell distribution, a potential biomarker of ICI response, remains poorly characterized. We assessed safety, imaging dose and timing, pharmacokinetics and immunogenicity of zirconium-89-labeled, CD8-specific, one-armed antibody positron emission tomography tracer 89 ZED88082A in patients with solid tumors before and ~30 days after starting ICI therapy (NCT04029181). No tracer-related side effects occurred. Positron emission tomography imaging with 10 mg antibody revealed 89 ZED88082A uptake in normal lymphoid tissues, and tumor lesions across the body varying within and between patients two days after tracer injection ( n  = 38, median patient maximum standard uptake value (SUV max ) 5.2, IQI 4.0–7.4). Higher SUV max was associated with mismatch repair deficiency and longer overall survival. Uptake was higher in lesions with stromal/inflamed than desert immunophenotype. Tissue radioactivity was localized to areas with immunohistochemically confirmed CD8 expression. Re-imaging patients on treatment showed no change in average (geometric mean) tumor tracer uptake compared to baseline, but individual lesions showed diverse changes independent of tumor response. The imaging data suggest enormous heterogeneity in CD8 + T cell distribution and pharmacodynamics within and between patients. In conclusion, 89 ZED88082A can characterize the complex dynamics of CD8 + T cells in the context of ICIs, and may inform immunotherapeutic treatments. A CD8-specific, one-armed antibody positron emission tomography tracer enables the visualization of the immune response in patients with solid tumors before and after starting immunotherapy.

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. Identifying which genes and pathways explain genetic associations is challenging. Here, the authors present DEPICT, a tool for gene prioritization, pathway analysis and tissue/cell-type enrichment analysis that can be used to generate testable hypotheses from genetic association studies.

Rudolf Fehrmann, Lude Franke and colleagues report a method for capturing the variation present within mammalian transcriptomes in a limited number of 'transcriptional components' and demonstrate widespread correlation between gene copy number and expression levels. The method allows for the inference of candidate gene function and the identification of potential therapeutic targets in cancer. Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gene expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying this method to 16,172 patient-derived tumor samples, we replicated many loci with aberrant copy numbers and identified recurrently disrupted genes in genomically unstable cancers.

Oncogene-induced replication stress characterizes many aggressive cancers. Several treatments are being developed that target replication stress, however, identification of tumors with high levels of replication stress remains challenging. We describe a gene expression signature of oncogene-induced replication stress. A panel of triple-negative breast cancer (TNBC) and non-transformed cell lines were engineered to overexpress CDC25A , CCNE1 or MYC , which resulted in slower replication kinetics. RNA sequencing analysis revealed a set of 52 commonly upregulated genes. In parallel, mRNA expression analysis of patient-derived tumor samples (TCGA, n  = 10,592) also revealed differential gene expression in tumors with amplification of oncogenes that trigger replication stress ( CDC25A , CCNE1 , MYC , CCND1 , MYB , MOS , KRAS , ERBB2 , and E2F1 ). Upon integration, we identified a six-gene signature of oncogene-induced replication stress ( NAT10 , DDX27 , ZNF48 , C8ORF33 , MOCS3 , and MPP6) . Immunohistochemical analysis of NAT10 in breast cancer samples (n = 330) showed strong correlation with expression of phospho-RPA ( R  = 0.451, p  = 1.82 × 10 −20 ) and γH2AX ( R  = 0.304, p  = 2.95 × 10 −9 ). Finally, we applied our oncogene-induced replication stress signature to patient samples from TCGA ( n  = 8,862) and GEO ( n  = 13,912) to define the levels of replication stress across 27 tumor subtypes, identifying diffuse large B cell lymphoma, ovarian cancer, TNBC and colorectal carcinoma as cancer subtypes with high levels of oncogene-induced replication stress.

Chemotherapy-related endothelial damage contributes to the early development of cardiovascular morbidity in testicular cancer patients. We aimed to identify relevant mechanisms of and search for candidate biomarkers for this endothelial damage. Human micro-vascular endothelial cells (HMEC-1) were exposed to bleomycin or cisplatin with untreated samples as control. 18k cDNA microarrays were used. Gene expression differences were analysed at single gene level and in gene sets clustered in biological pathways and validated by qRT-PCR. Protein levels of a candidate biomarker were measured in testicular cancer patient plasma before, during and after bleomycin-etoposide-cisplatin chemotherapy, and related to endothelial damage biomarkers (von Willebrand Factor (vWF), high-sensitivity C-Reactive Protein (hsCRP)). Microarray data identified several genes with highly differential expression; e.g. Growth Differentiation Factor 15 (GDF-15), Activating Transcription Factor 3 (ATF3) and Amphiregulin (AREG). Pathway analysis revealed strong associations with 'p53' and 'Diabetes Mellitus' gene sets. Based on known function, we measured GDF-15 protein levels in 41 testicular patients during clinical follow-up. Pre-chemotherapy GDF-15 levels equalled controls. Throughout chemotherapy GDF-15, vWF and hsCRP levels increased, and were correlated at different time-points. An unbiased approach in a preclinical model revealed genes related to chemotherapy-induced endothelial damage, like GDF-15. The increases in plasma GDF-15 levels in testicular cancer patients during chemotherapy and its association with vWF and hsCRP suggest that GDF-15 is a potentially useful biomarker related to endothelial damage.