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With high-dimensional data, variable-by-variable statistical testing is often used to select variables whose behavior differs across conditions. Such an approach requires adjustment for multiple testing, which can result in low statistical power. A two-stage approach that first filters variables by a criterion independent of the test statistic, and then only tests variables which pass the filter, can provide higher power. We show that use of some filter/test statistics pairs presented in the literature may, however, lead to loss of type I error control. We describe other pairs which avoid this problem. In an application to microarray data, we found that gene-by-gene filtering by overall variance followed by a t-test increased the number of discoveries by 50%. We also show that this particular statistic pair induces a lower bound on fold-change among the set of discoveries. Independent filtering--using filter/test pairs that are independent under the null hypothesis but correlated under the alternative--is a general approach that can substantially increase the efficiency of experiments.

Profound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE , a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens. Treatment with demethylation agents can reactivate transposable elements. Here in glioblastoma, the authors also show that this is accompanied by de novo presentation of TE-derived peptides on MHC class I molecules.

Meiotic recombination has a central role in the evolution of sexually reproducing organisms. The two recombination outcomes, crossover and non-crossover, increase genetic diversity, but have the potential to homogenize alleles by gene conversion. Whereas crossover rates vary considerably across the genome, non-crossovers and gene conversions have only been identified in a handful of loci. To examine recombination genome wide and at high spatial resolution, we generated maps of crossovers, crossover-associated gene conversion and non-crossover gene conversion using dense genetic marker data collected from all four products of fifty-six yeast (Saccharomyces cerevisiae) meioses. Our maps reveal differences in the distributions of crossovers and non-crossovers, showing more regions where either crossovers or non-crossovers are favoured than expected by chance. Furthermore, we detect evidence for interference between crossovers and non-crossovers, a phenomenon previously only known to occur between crossovers. Up to 1% of the genome of each meiotic product is subject to gene conversion in a single meiosis, with detectable bias towards GC nucleotides. To our knowledge the maps represent the first high-resolution, genome-wide characterization of the multiple outcomes of recombination in any organism. In addition, because non-crossover hotspots create holes of reduced linkage within haplotype blocks, our results stress the need to incorporate non-crossovers into genetic linkage analysis.

Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what controls the spatial distribution of T cells in the tumour microenvironment is not well understood. Here we couple digital pathology and transcriptome analysis on a large ovarian tumour cohort and develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFβ and activated stroma. Furthermore, we identify TGFβ as an important mediator of T cell exclusion. TGFβ reduces MHC-I expression in ovarian cancer cells in vitro. TGFβ also activates fibroblasts and induces extracellular matrix production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFβ might be a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy. The exclusion of T cells from solid tumours is a potentially important mechanism that regulates whether or not cancer patients respond well to checkpoint blocking immunotherapies. Here the authors identify immune phenotypes and mediators of T cell exclusion among ovarian cancer patient samples from the ICON7 phase III trial.

Most colorectal (CRC) tumors are dependent on EGFR/KRAS/BRAF/MAPK signaling activation. ARID1A is an epigenetic regulator mutated in approximately 5% of non-hypermutated CRC tumors. Here we show that anti-EGFR but not anti-VEGF treatment enriches for emerging ARID1A mutations in CRC patients. In addition, we find that patients with ARID1A mutations, at baseline, are associated with worse outcome when treated with cetuximab- but not bevacizumab-containing therapies; thus, this suggests that ARID1A mutations may provide both an acquired and intrinsic mechanism of resistance to anti-EGFR therapies. We find that, ARID1A and EGFR-pathway genetic alterations are mutually exclusive across lung and colorectal cancers, further supporting a functional connection between these pathways. Our results not only suggest that ARID1A could be potentially used as a predictive biomarker for cetuximab treatment decisions but also provide a rationale for exploring therapeutic MAPK inhibition in an unexpected but genetically defined segment of CRC patients. ARID1A is an epigenetic regulator mutated in approximately 5% of non-hypermutated colorectal cancer tumors, however, its relationship with treatment response remains to be explored. Here, the authors suggest that ARID1A mutations may confer intrinsic and acquired resistance to cetuximab treatment.

Based on the success of cancer immunotherapy, personalized cancer vaccines have emerged as a leading oncology treatment. Antigen presentation on MHC class I (MHC-I) is crucial for the adaptive immune response to cancer cells, necessitating highly predictive computational methods to model this phenomenon. Here, we introduce HLApollo, a transformer-based model for peptide-MHC-I (pMHC-I) presentation prediction, leveraging the language of peptides, MHC, and source proteins. HLApollo provides end-to-end treatment of MHC-I sequences and deconvolution of multi-allelic data, using a negative-set switching strategy to mitigate misassigned negatives in unlabelled ligandome data. HLApollo shows a 12.65% increase in average precision (AP) on ligandome data and a 4.1% AP increase on immunogenicity test data compared to next-best models. Incorporating protein features from protein language models yields further gains and reduces the need for gene expression measurements. Guided by clinical use, we demonstrate pan-allelic generalization which effectively captures rare alleles in underrepresented ancestries. Computational methods are used to predict which peptides or antigens are able to bind to MHC in order to activate T cell receptors in neoantigen-directed immunotherapies. Here the authors present an accurate transformer-based method to consider not only the peptide and MHC but also the source antigenic protein to predict peptides which bind to MHC molecules.

TNF superfamily death ligands are expressed on the surface of immune cells and can trigger apoptosis in susceptible cancer cells by engaging cognate death receptors. A recombinant soluble protein comprising the ectodomain of Apo2 ligand/TNF-related apoptosis-inducing ligand (Apo2L/TRAIL) has shown remarkable preclinical anticancer activity but lacked broad efficacy in patients, possibly owing to insufficient exposure or potency. We observed that antibody cross-linking substantially enhanced cytotoxicity of soluble Apo2L/TRAIL against diverse cancer cell lines. Presentation of the ligand on glass-supported lipid bilayers enhanced its ability to drive receptor microclustering and apoptotic signaling. Furthermore, covalent surface attachment of Apo2L/TRAIL onto liposomes—synthetic lipid-bilayer nanospheres—similarly augmented activity. In vivo, liposome-displayed Apo2L/TRAIL achieved markedly better exposure and antitumor activity. Thus, covalent synthetic-membrane attachment of a cell-surface ligand enhances efficacy, increasing therapeutic potential. These findings have translational implications for liposomal approaches as well as for Apo2L/TRAIL and other clinically relevant TNF ligands. Significance A recombinant soluble version of the transmembrane death ligand Apo2L/TRAIL has shown compelling preclinical results as a potential cancer therapeutic, but studies in cancer patients have demonstrated little efficacy. Supported membrane display of Apo2L/TRAIL, to mimic the endogenous ligand more faithfully, markedly augments receptor clustering and apoptosis stimulation in cancer cells. Covalent attachment of Apo2L/TRAIL to the surface of liposomes offers a therapeutically tractable approach to membrane display that substantially increases tumor exposure, caspase activation, and antitumor potency. These findings open new avenues for clinical investigation of Apo2L/TRAIL as a cancer therapeutic and may apply to other members of the TNF superfamily, such as FasL and CD70, which are expressed on immune-cell surfaces and are important candidates for cancer immunotherapy.

Polycomb (PcG) regulation has been thought to produce stable long-term gene silencing. Genomic analyses in Drosophila and mammals, however, have shown that it targets many genes, which can switch state during development. Genetic evidence indicates that critical for the active state of PcG target genes are the histone methyltransferases Trithorax (TRX) and ASH1. Here we analyze the repertoire of alternative states in which PcG target genes are found in different Drosophila cell lines and the role of PcG proteins TRX and ASH1 in controlling these states. Using extensive genome-wide chromatin immunoprecipitation analysis, RNAi knockdowns, and quantitative RT-PCR, we show that, in addition to the known repressed state, PcG targets can reside in a transcriptionally active state characterized by formation of an extended domain enriched in ASH1, the N-terminal, but not C-terminal moiety of TRX and H3K27ac. ASH1/TRX N-ter domains and transcription are not incompatible with repressive marks, sometimes resulting in a \"balanced\" state modulated by both repressors and activators. Often however, loss of PcG repression results instead in a \"void\" state, lacking transcription, H3K27ac, or binding of TRX or ASH1. We conclude that PcG repression is dynamic, not static, and that the propensity of a target gene to switch states depends on relative levels of PcG, TRX, and activators. N-ter TRX plays a remarkable role that antagonizes PcG repression and preempts H3K27 methylation by acetylation. This role is distinct from that usually attributed to TRX/MLL proteins at the promoter. These results have important implications for Polycomb gene regulation, the \"bivalent\" chromatin state of embryonic stem cells, and gene expression in development.

Polycomb group (PcG) complexes are multiprotein assemblages that bind to chromatin and establish chromatin states leading to epigenetic silencing 1 , 2 . PcG proteins regulate homeotic genes in flies and vertebrates, but little is known about other PcG targets and the role of the PcG in development, differentiation and disease. Here, we determined the distribution of the PcG proteins PC, E(Z) and PSC and of trimethylation of histone H3 Lys27 (me3K27) in the D. melanogaster genome. At more than 200 PcG target genes, binding sites for the three PcG proteins colocalize to presumptive Polycomb response elements (PREs). In contrast, H3 me3K27 forms broad domains including the entire transcription unit and regulatory regions. PcG targets are highly enriched in genes encoding transcription factors, but they also include genes coding for receptors, signaling proteins, morphogens and regulators representing all major developmental pathways.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths, with a 5% 5-year survival rate for metastatic disease, yet with limited therapeutic advancements due to insufficient understanding of and inability to accurately capture high-risk CRC patients who are most likely to recur. We aimed to improve high-risk classification by identifying biological pathways associated with outcome in adjuvant stage II/III CRC. We included 1062 patients with stage III or high-risk stage II colon carcinoma from the prospective three-arm randomized phase 3 AVANT trial, and performed expression profiling to identify a prognostic signature. Data from validation cohort GSE39582, The Cancer Genome Atlas, and cell lines were used to further validate the prognostic biology. Our retrospective analysis of the adjuvant AVANT trial uncovered a prognostic signature capturing three biological functions-stromal, proliferative and immune-that outperformed the Consensus Molecular Subtypes (CMS) and recurrence prediction signatures like Oncotype Dx in an independent cohort. Importantly, within the immune component, high granzyme B (GZMB) expression had a significant prognostic impact while other individual T-effector genes were less or not prognostic. In addition, we found GZMB to be endogenously expressed in CMS2 tumor cells and to be prognostic in a T cell independent fashion. A limitation of our study is that these results, although robust and derived from a large dataset, still need to be clinically validated in a prospective study. This work furthers our understanding of the underlying biology that propagates stage II/III CRC disease progression and provides scientific rationale for future high-risk stratification and targeted treatment evaluation in biomarker defined subpopulations of resectable high-risk CRC. Our results also shed light on an alternative GZMB source with context-specific implications on the disease's unique biology.