We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.

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Upon entering the cerebral cortex sensory information spreads through six different horizontal neuronal layers that are interconnected by vertical axonal projections. It is believed that through these projections layers can influence each other’s response to sensory stimuli, yet the specific role played by each layer in cortical processing is still poorly understood. Here we show that layer 6 in the primary visual cortex of the mouse plays a crucial role in controlling the gain of visually evoked activity in neurons of the upper layers without, however, changing their tuning to orientation. This gain modulation results from the coordinated action of layer 6 projections to superficial layers and deep projections to the thalamus, with a substantial role of the former circuit. This study thus establishes L6 as a major mediator of cortical gain modulation and suggests it could be a node through which convergent inputs from several brain areas can regulate the earliest steps of cortical visual processing.

Summary The molecular mechanisms controlling the termination of cortical interneuron migration are unknown. Here we demonstrate that prior to synaptogenesis, migrating interneurons change their responsiveness to ambient GABA from a motogenic to a stop signal. We found that during migration into the cortex, ambient GABA and glutamate initially stimulate the motility of interneurons through both GABAA and AMPA/NMDA receptor activation. Once in the cortex, up-regulation of the potassium-chloride co-transporter KCC2 is both necessary and sufficient to reduce interneuron motility through its ability to reduce membrane potential upon GABAA receptor activation which decrease the frequency of spontaneous intracellular calcium transients initiated by L-type Voltage-Sensitive Calcium Channels (VSCC) activation. Our results suggest a novel mechanism whereby migrating interneurons determine the relative density of surrounding interneurons and principal cells through their ability to sense the combined extracellular levels of ambient glutamate and GABA once GABAA receptor activation becomes hyperpolarizing.

Summary In layer 6 (L6), a principal output layer of the mammalian cerebral cortex, a population of excitatory neurons defined by the NTSR1-Cre mouse line inhibit cortical responses to visual stimuli. Here we show that of the two major types of excitatory neurons existing in L6, the NTSR1-Cre line selectively targets those whose axon innervate both cortex and thalamus and not those whose axons remain within the cortex. These cortico-thalamic neurons mediate widespread inhibition across all cortical layers by recruiting fast-spiking inhibitory neurons whose cell-body resides in deep cortical layers yet whose axons arborize throughout all layers. This study reveals a circuit by which L6 modulates cortical activity and identifies an inhibitory neuron able to regulate the strength of cortical responses throughout cortical depth.

The molecular mechanisms specifying the dendritic morphology of different neuronal subtypes are poorly understood. Here we demonstrate that the bHLH transcription factor Neurogenin2 (Ngn2) is both necessary and sufficient for specifying the dendritic morphology of pyramidal neurons in vivo by specifying the polarity of its leading process during the initiation of radial migration. The ability of Ngn2 to promote a polarized leading process outgrowth requires the phosphorylation of a single tyrosine residue at position 241, an event that is neither involved in Ngn2 direct transactivation properties nor its proneural function. Interestingly, the migration defect observed in the Ngn2 knockout mouse and in progenitors expressing the Ngn2(Y241F) mutation can be rescued by inhibiting the activity of the small-GTPase RhoA in cortical progenitors. Our results demonstrate that Ngn2 coordinates the acquisition of the radial migration properties and the unipolar dendritic morphology characterizing pyramidal neurons through molecular mechanisms distinct from those mediating its proneural activity.

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I-like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer-positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.

T-cell responses to minor histocompatibility antigens (mHAs) mediate both antitumor immunity (graft-versus-leukemia [GVL]) and graft-versus-host disease (GVHD) in allogeneic stem cell transplant. Identifying mHAs with high allele frequency, tight binding affinity to common HLA molecules, and narrow tissue restriction could enhance immunotherapy against leukemia. Genotyping and HLA allele data from 101 HLA-matched donor-recipient pairs (DRPs) were computationally analyzed to predict both class I and class II mHAs likely to induce either GVL or GVHD. Roughly twice as many mHAs were predicted in HLA-matched unrelated donor (MUD) stem cell transplantation (SCT) compared with HLA-matched related transplants, an expected result given greater genetic disparity in MUD SCT. Computational analysis predicted 14 of 18 previously identified mHAs, with 2 minor antigen mismatches not being contained in the patient cohort, 1 missed mHA resulting from a noncanonical translation of the peptide antigen, and 1 case of poor binding prediction. A predicted peptide epitope derived from GRK4, a protein expressed in acute myeloid leukemia and testis, was confirmed by targeted differential ion mobility spectrometry-tandem mass spectrometry. T cells specific to UNC-GRK4-V were identified by tetramer analysis both in DRPs where a minor antigen mismatch was predicted and in DRPs where the donor contained the allele encoding UNC-GRK4-V, suggesting that this antigen could be both an mHA and a cancer-testis antigen. Computational analysis of genomic and transcriptomic data can reliably predict leukemia-associated mHA and can be used to guide targeted mHA discovery.