Molecular, metabolic, and functional CD4 T cell paralysis in the lymph node impedes tumor control.

CD4 T cells are central effectors of anti-cancer immunity and immunotherapy, yet the regulation of CD4 tumor-specific T (TTS) cells is unclear. We demonstrate that CD4 TTS cells are quickly primed and begin to divide following tumor initiation. However, unlike CD8 TTS cells or exhaustion programming, CD4 TTS cell proliferation is rapidly frozen in place by a functional interplay of regulatory T cells and CTLA4. Together these mechanisms paralyze CD4 TTS cell differentiation, redirecting metabolic circuits, and reducing their accumulation in the tumor. The paralyzed state is actively maintained throughout cancer progression and CD4 TTS cells rapidly resume proliferation and functional differentiation when the suppressive constraints are alleviated. Overcoming their paralysis established long-term tumor control, demonstrating the importance of rapidly crippling CD4 TTS cells for tumor progression and their potential restoration as therapeutic targets.

Molecular, metabolic and functional CD4 T cell paralysis impedes tumor control.

CD4 T cells are important effectors of anti-tumor immunity, yet the regulation of CD4 tumor-specific T (T TS ) cells during cancer development is still unclear. We demonstrate that CD4 T TS cells are initially primed in the tumor draining lymph node and begin to divide following tumor initiation. Distinct from CD8 T TS cells and previously defined exhaustion programs, CD4 T TS cell proliferation is rapidly frozen in place and differentiation stunted by a functional interplay of T regulatory cells and both intrinsic and extrinsic CTLA4 signaling. Together these mechanisms paralyze CD4 T TS cell differentiation, redirecting metabolic and cytokine production circuits, and reducing CD4 T TS cell accumulation in the tumor. Paralysis is actively maintained throughout cancer progression and CD4 T TS cells rapidly resume proliferation and functional differentiation when both suppressive reactions are alleviated. Strikingly, Treg depletion alone reciprocally induced CD4 T TS cells to themselves become tumor-specific Tregs, whereas CTLA4 blockade alone failed to promote T helper differentiation. Overcoming their paralysis established long-term tumor control, demonstrating a novel immune evasion mechanism that specifically cripples CD4 T TS cells to favor tumor progression.

Pre-encoded responsiveness to type I interferon in the peripheral immune system defines outcome of PD1 blockade therapy.

Type I interferons (IFN-Is) are central regulators of anti-tumor immunity and responses to immunotherapy, but they also drive the feedback inhibition underlying therapeutic resistance. In the present study, we developed a mass cytometry approach to quantify IFN-I-stimulated protein expression across immune cells and used multi-omics to uncover pre-therapy cellular states encoding responsiveness to inflammation. Analyzing peripheral blood cells from multiple cancer types revealed that differential responsiveness to IFN-Is before anti-programmed cell death protein 1 (PD1) treatment was highly predictive of long-term survival after therapy. Unexpectedly, IFN-I hyporesponsiveness efficiently predicted long-term survival, whereas high responsiveness to IFN-I was strongly associated with treatment failure and diminished survival time. Peripheral IFN-I responsive states were not associated with tumor inflammation, identifying a disconnect between systemic immune potential and 'cold' or 'hot' tumor states. Mechanistically, IFN-I responsiveness was epigenetically imprinted before therapy, poising cells for differential inflammatory responses and dysfunctional T cell effector programs. Thus, we identify physiological cell states with clinical importance that can predict success and long-term survival of PD1-blocking immunotherapy.

Dynamic CD4+ T cell heterogeneity defines subset-specific suppression and PD-L1-blockade-driven functional restoration in chronic infection.

Inhibiting PD-1:PD-L1 signaling has transformed therapeutic immune restoration. CD4+ T cells sustain immunity in chronic infections and cancer, yet little is known about how PD-1 signaling modulates CD4+ helper T (TH) cell responses or the ability to restore CD4+ TH-mediated immunity by checkpoint blockade. We demonstrate that PD-1:PD-L1 specifically suppressed CD4+ TH1 cell amplification, prevents CD4+ TH1 cytokine production and abolishes CD4+ cytotoxic killing capacity during chronic infection in mice. Inhibiting PD-L1 rapidly restored these functions, while simultaneously amplifying and activating TH1-like T regulatory cells, demonstrating a system-wide CD4-TH1 recalibration. This effect coincided with decreased T cell antigen receptor signaling, and re-directed type I interferon (IFN) signaling networks towards dominant IFN-γ-mediated responses. Mechanistically, PD-L1 blockade specifically targeted defined populations with pre-established, but actively suppressed proliferative potential, with limited impact on minimally cycling TCF-1+ follicular helper T cells, despite high PD-1 expression. Thus, CD4+ T cells require unique differentiation and functional states to be targets of PD-L1-directed suppression and therapeutic restoration.

Functional and genetic determinants of mutation rate variability in regulatory elements of cancer genomes.

BACKGROUND: Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mechanisms with functional and genetic determinants remain poorly understood. RESULTS: We characterise the mutational landscape of 1.3 million gene-regulatory and chromatin architectural elements in 2419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We develop RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. Increased mutation frequency in TSSs associates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identify ~ 10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of mutagenesis. We detect site-specific mutational signature enrichments, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. Candidate drivers of localised mutagenesis are also apparent: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutagenesis in pancreatic cancer. CONCLUSIONS: Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver gene discovery. The functional and genetic correlates of mutational processes suggest mechanistic hypotheses for future studies.

The transcriptional landscape of Shh medulloblastoma.

Sonic hedgehog medulloblastoma encompasses a clinically and molecularly diverse group of cancers of the developing central nervous system. Here, we use unbiased sequencing of the transcriptome across a large cohort of 250 tumors to reveal differences among molecular subtypes of the disease, and demonstrate the previously unappreciated importance of non-coding RNA transcripts. We identify alterations within the cAMP dependent pathway (GNAS, PRKAR1A) which converge on GLI2 activity and show that 18% of tumors have a genetic event that directly targets the abundance and/or stability of MYCN. Furthermore, we discover an extensive network of fusions in focally amplified regions encompassing GLI2, and several loss-of-function fusions in tumor suppressor genes PTCH1, SUFU and NCOR1. Molecular convergence on a subset of genes by nucleotide variants, copy number aberrations, and gene fusions highlight the key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma and open up opportunities for therapeutic intervention.

Integrative pathway enrichment analysis of multivariate omics data.

Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.

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.

Changes of Cell Biochemical States Are Revealed in Protein Homomeric Complex Dynamics.

We report here a simple and global strategy to map out gene functions and target pathways of drugs, toxins, or other small molecules based on "homomer dynamics" protein-fragment complementation assays (hdPCA). hdPCA measures changes in self-association (homomerization) of over 3,500 yeast proteins in yeast grown under different conditions. hdPCA complements genetic interaction measurements while eliminating the confounding effects of gene ablation. We demonstrate that hdPCA accurately predicts the effects of two longevity and health span-affecting drugs, the immunosuppressant rapamycin and the type 2 diabetes drug metformin, on cellular pathways. We also discovered an unsuspected global cellular response to metformin that resembles iron deficiency and includes a change in protein-bound iron levels. This discovery opens a new avenue to investigate molecular mechanisms for the prevention or treatment of diabetes, cancers, and other chronic diseases of aging.

Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast.

BACKGROUND: Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted. RESULTS: We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package ( https://cran.r-project.org/web/packages/VertexSort/index.html ). CONCLUSIONS: The KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes in general.

Combining the Optimized Yeast Cytosine Deaminase Protein Fragment Complementation Assay and an In Vitro Cdk1 Targeting Assay to Study the Regulation of the γ-Tubulin Complex.

Cdk1 is the essential cyclin-dependent kinase in the budding yeast Saccharomyces cerevisiae. Cdk1 orchestrates cell cycle control by phosphorylating target proteins with extraordinary temporal and spatial specificity by complexing with one of the nine cyclin regulatory subunits. The identification of the cyclin required for targeting Cdk1 to a substrate can help to place the regulation of that protein at a specific time point during the cell cycle and reveal information needed to elucidate the biological significance of the regulation. Here, we describe a combination of strategies to identify interaction partners of Cdk1, and associate these complexes to the appropriate cyclins using a cell-based protein-fragment complementation assay. Validation of the specific reliance of the OyCD interaction between Cdk1 and budding yeast γ-tubulin on the Clb3 cyclin, relative to the mitotic Clb2 cyclin, was performed by an in vitro kinase assay using the γ-tubulin complex as a substrate.

Extracting insight from noisy cellular networks.

Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched.

Dissection of Cdk1-cyclin complexes in vivo.

Cyclin-dependent kinases (Cdks) are regulatory enzymes with temporal and spatial selectivity for their protein substrates that are governed by cell cycle-regulated cyclin subunits. Specific cyclin-Cdk complexes bind to and phosphorylate target proteins, coupling their activity to cell cycle states. The identification of specific cyclin-Cdk substrates is challenging and so far, has largely been achieved through indirect correlation or use of in vitro techniques. Here, we use a protein-fragment complementation assay based on the optimized yeast cytosine deaminase to systematically identify candidate substrates of budding yeast Saccharomyces cerevisiae Cdk1 and show dependency on one or more regulatory cyclins. We identified known and candidate cyclin dependencies for many predicted protein kinase Cdk1 targets and showed elusory Clb3-Cdk1-specific phosphorylation of γ-tubulin, thus establishing the timing of this event in controlling assembly of the mitotic spindle. Our strategy can be generally applied to identify substrates and accessory subunits of multisubunit protein complexes.

Allelic transcripts dosage effect in morphologically normal ovarian cells from heterozygous carriers of a BRCA1/2 French Canadian founder mutation.

We hypothesized that the transcriptome of primary cultures of morphologically normal ovarian surface epithelial cells could be altered by the presence of a heterozygous BRCA1 or BRCA2 mutation. We aimed to discover early events associated with ovarian carcinogenesis, which could represent putative targets for preventive strategies of this silent killer tumor. We identified the first molecular signature associated with French Canadian BRCA1 or BRCA2 founder mutations in morphologically normal ovarian epithelial cells. We discovered that wild-type and mutated BRCA2 allelic transcripts were expressed not only in morphologically normal but also in tumor cells from BRCA2-8765delAG carriers. Further analysis of morphologically normal ovarian and tumor cells from BRCA1-4446C>T carriers lead to the same observation. Our data support the idea that one single hit in BRCA1 or BRCA2 is sufficient to alter the transcriptome of phenotypically normal ovarian epithelial cells. The highest level of BRCA2-mutated allele transcript expression was measured in cells originating from the most aggressive ovarian tumor. The penetrance of the mutation and the aggressiveness of the related tumor could depend on a dosage effect of the mutated allele transcript.