Gut commensal bacteria enhance pathogenesis of a tumorigenic murine retrovirus.

The influence of the microbiota on viral transmission and replication is well appreciated. However, its impact on retroviral pathogenesis outside of transmission/replication control remains unknown. Using murine leukemia virus (MuLV), we found that some commensal bacteria promoted the development of leukemia induced by this retrovirus. The promotion of leukemia development by commensals is due to suppression of the adaptive immune response through upregulation of several negative regulators of immunity. These negative regulators include Serpinb9b and Rnf128, which are associated with a poor prognosis of some spontaneous human cancers. Upregulation of Serpinb9b is mediated by sensing of bacteria by the NOD1/NOD2/RIPK2 pathway. This work describes a mechanism by which the microbiota enhances tumorigenesis within gut-distant organs and points at potential targets for cancer therapy.

Integration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer.

The efficacy of immune checkpoint blockade (ICB) varies greatly among metastatic non-small cell lung cancer (NSCLC) patients. Loss of heterozygosity at the HLA-I locus (HLA-LOH) has been identified as an important immune escape mechanism. However, despite HLA-I disruptions in their tumor, many patients have durable ICB responses. Here we seek to identify HLA-I-independent features associated with ICB response in NSCLC. We use single-cell profiling to identify tumor-infiltrating, clonally expanded CD4+ T cells that express a canonical cytotoxic gene program and NSCLC cells with elevated HLA-II expression. We postulate cytotoxic CD4+ T cells mediate anti-tumor activity via HLA-II on tumor cells and augment HLA-I-dependent cytotoxic CD8+ T cell interactions to drive ICB response in NSCLC. We show that integrating tumor extrinsic cytotoxic gene expression with tumor mutational burden is associated with longer time to progression in a real-world cohort of 123 NSCLC patients treated with ICB regimens, including those with HLA-LOH.

Privacy preserving validation for multiomic prediction models.

Reproducibility of results obtained using ribonucleic acid (RNA) data across labs remains a major hurdle in cancer research. Often, molecular predictors trained on one dataset cannot be applied to another due to differences in RNA library preparation and quantification, which inhibits the validation of predictors across labs. While current RNA correction algorithms reduce these differences, they require simultaneous access to patient-level data from all datasets, which necessitates the sharing of training data for predictors when sharing predictors. Here, we describe SpinAdapt, an unsupervised RNA correction algorithm that enables the transfer of molecular models without requiring access to patient-level data. It computes data corrections only via aggregate statistics of each dataset, thereby maintaining patient data privacy. Despite an inherent trade-off between privacy and performance, SpinAdapt outperforms current correction methods, like Seurat and ComBat, on publicly available cancer studies, including TCGA and ICGC. Furthermore, SpinAdapt can correct new samples, thereby enabling unbiased evaluation on validation cohorts. We expect this novel correction paradigm to enhance research reproducibility and to preserve patient privacy.

Validation of a liquid biopsy assay with molecular and clinical profiling of circulating tumor DNA.

Liquid biopsy is a valuable precision oncology tool that is increasingly used as a non-invasive approach to identify biomarkers, detect resistance mutations, monitor disease burden, and identify early recurrence. The Tempus xF liquid biopsy assay is a 105-gene, hybrid-capture, next-generation sequencing (NGS) assay that detects single-nucleotide variants, insertions/deletions, copy number variants, and chromosomal rearrangements. Here, we present extensive validation studies of the xF assay using reference standards, cell lines, and patient samples that establish high sensitivity, specificity, and accuracy in variant detection. The Tempus xF assay is highly concordant with orthogonal methods, including ddPCR, tumor tissue-based NGS assays, and another commercial plasma-based NGS assay. Using matched samples, we developed a dynamic filtering method to account for germline mutations and clonal hematopoiesis, while significantly decreasing the number of false-positive variants reported. Additionally, we calculated accurate circulating tumor fraction estimates (ctFEs) using the Off-Target Tumor Estimation Routine (OTTER) algorithm for targeted-panel sequencing. In a cohort of 1,000 randomly selected cancer patients who underwent xF testing, we found that ctFEs correlated with disease burden and clinical outcomes. These results highlight the potential of serial testing to monitor treatment efficacy and disease course, providing strong support for incorporating liquid biopsy in the management of patients with advanced disease.

A pan-cancer organoid platform for precision medicine.

Patient-derived tumor organoids (TOs) are emerging as high-fidelity models to study cancer biology and develop novel precision medicine therapeutics. However, utilizing TOs for systems-biology-based approaches has been limited by a lack of scalable and reproducible methods to develop and profile these models. We describe a robust pan-cancer TO platform with chemically defined media optimized on cultures acquired from over 1,000 patients. Crucially, we demonstrate tumor genetic and transcriptomic concordance utilizing this approach and further optimize defined minimal media for organoid initiation and propagation. Additionally, we demonstrate a neural-network-based high-throughput approach for label-free, light-microscopy-based drug assays capable of predicting patient-specific heterogeneity in drug responses with applicability across solid cancers. The pan-cancer platform, molecular data, and neural-network-based drug assay serve as resources to accelerate the broad implementation of organoid models in precision medicine research and personalized therapeutic profiling programs.

Human Hepatitis B Viral Infection Outcomes Are Linked to Naturally Occurring Variants of HLA-DOA That Have Altered Function.

HLA molecules of the MHC class II (MHCII) bind and present pathogen-derived peptides for CD4 T cell activation. Peptide loading of MHCII in the endosomes of cells is controlled by the interplay of the nonclassical MHCII molecules, HLA-DM (DM) and HLA-DO (DO). DM catalyzes peptide loading, whereas DO, an MHCII substrate mimic, prevents DM from interacting with MHCII, resulting in an altered MHCII-peptide repertoire and increased MHCII-CLIP. Although the two genes encoding DO (DOA and DOB) are considered nonpolymorphic, there are rare natural variants. Our previous work identified DOB variants that altered DO function. In this study, we show that natural variation in the DOA gene also impacts DO function. Using the 1000 Genomes Project database, we show that ∼98% of individuals express the canonical DOA*0101 allele, and the remaining individuals mostly express DOA*0102, which we found was a gain-of-function allele. Analysis of 25 natural occurring DOα variants, which included the common alleles, identified three null variants and one variant with reduced and nine with increased ability to modulate DM activity. Unexpectedly, several of the variants produced reduced DO protein levels yet efficiently inhibited DM activity. Finally, analysis of associated single-nucleotide polymorphisms genetically linked the DOA*0102 common allele, a gain-of-function variant, with human hepatitis B viral persistence. In contrast, we found that the DOα F114L null allele was linked with viral clearance. Collectively, these studies show that natural variation occurring in the human DOA gene impacts DO function and can be linked to specific outcomes of viral infections.

Integrated genomic profiling expands clinical options for patients with cancer.

Genomic analysis of paired tumor-normal samples and clinical data can be used to match patients to cancer therapies or clinical trials. We analyzed 500 patient samples across diverse tumor types using the Tempus xT platform by DNA-seq, RNA-seq and immunological biomarkers. The use of a tumor and germline dataset led to substantial improvements in mutation identification and a reduction in false-positive rates. RNA-seq enhanced gene fusion detection and cancer type classifications. With DNA-seq alone, 29.6% of patients matched to precision therapies supported by high levels of evidence or by well-powered studies. This proportion increased to 43.4% with the addition of RNA-seq and immunotherapy biomarker results. Combining these data with clinical criteria, 76.8% of patients were matched to at least one relevant clinical trial on the basis of biomarkers measured by the xT assay. These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor-normal plus transcriptome sequencing outperforms tumor-only DNA panel testing.

RNA Sequencing of the Tumor Microenvironment in Precision Cancer Immunotherapy.

RNA sequencing (RNA-seq) provides an efficient high-throughput technique to robustly characterize the tumor immune microenvironment (TME). The increasing use of RNA-seq in clinical and basic science settings provides a powerful opportunity to access novel therapeutic biomarkers in the TME. Advanced computational methods are making it possible to resolve the composition of the tumor immune infiltrate, infer the immunological phenotypes of those cells, and assess the immune receptor repertoire in RNA-seq data. These immunological characterizations have increasingly important implications for guiding immunotherapy use. Here, we highlight recent studies that demonstrate the potential utility of RNA-seq in clinical settings, review key computational methods used for characterizing the TME for precision cancer immunotherapy, and discuss important considerations in data interpretation and current technological limitations.

Integrating RNA expression and visual features for immune infiltrate prediction.

Patient responses to cancer immunotherapy are shaped by their unique genomic landscape and tumor microenvironment. Clinical advances in immunotherapy are changing the treatment landscape by enhancing a patient's immune response to eliminate cancer cells. While this provides potentially beneficial treatment options for many patients, only a minority of these patients respond to immunotherapy. In this work, we examined RNA-seq data and digital pathology images from individual patient tumors to more accurately characterize the tumor-immune microenvironment. Several studies implicate an inflamed microenvironment and increased percentage of tumor infiltrating immune cells with better response to specific immunotherapies in certain cancer types. We developed NEXT (Neural-based models for integrating gene EXpression and visual Texture features) to more accurately model immune infiltration in solid tumors. To demonstrate the utility of the NEXT framework, we predicted immune infiltrates across four different cancer types and evaluated our predictions against expert pathology review. Our analyses demonstrate that integration of imaging features improves prediction of the immune infiltrate. Of note, this effect was preferentially observed for B cells and CD8 T cells. In sum, our work effectively integrates both RNA-seq and imaging data in a clinical setting and provides a more reliable and accurate prediction of the immune composition in individual patient tumors.

Neutralizing Antibody Responses to Viral Infections Are Linked to the Non-classical MHC Class II Gene H2-Ob.

Select humans and animals control persistent viral infections via adaptive immune responses that include production of neutralizing antibodies. The precise genetic basis for the control remains enigmatic. Here, we report positional cloning of the gene responsible for production of retrovirus-neutralizing antibodies in mice of the I/LnJ strain. It encodes the beta subunit of the non-classical major histocompatibility complex class II (MHC-II)-like molecule H2-O, a negative regulator of antigen presentation. The recessive and functionally null I/LnJ H2-Ob allele supported the production of virus-neutralizing antibodies independently of the classical MHC haplotype. Subsequent bioinformatics and functional analyses of the human H2-Ob homolog, HLA-DOB, revealed both loss- and gain-of-function alleles, which could affect the ability of their carriers to control infections with human hepatitis B (HBV) and C (HCV) viruses. Thus, understanding of the previously unappreciated role of H2-O (HLA-DO) in immunity to infections may suggest new approaches in achieving neutralizing immunity to viruses.

Gene regulatory networks in the immune system.

We describe examples of genomic control circuits that underlie developmental transitions and cellular activation states within the immune system. The architectures of simple gene regulatory networks (GRNs) are highlighted to emphasize conservation of regulatory motifs. The regulatory logic and the cell fate dynamics of each simple GRN, the latter revealed by mathematical and computational modeling, are elaborated. This framework is being expanded to enable the assembly and analysis of complex GRNs using genomic, computational, and high-throughput experimental methodologies. The paradigm will provide new insights into immune cell development and function, and into the pathophysiology of autoimmune and inflammatory disorders, as well as immune malignancies.

Gender bias in autoimmunity is influenced by microbiota.

Gender bias and the role of sex hormones in autoimmune diseases are well established. In specific pathogen-free nonobese diabetic (NOD) mice, females have 1.3-4.4 times higher incidence of type 1 diabetes (T1D). Germ-free (GF) mice lost the gender bias (female-to-male ratio 1.1-1.2). Gut microbiota differed in males and females, a trend reversed by male castration, confirming that androgens influence gut microbiota. Colonization of GF NOD mice with defined microbiota revealed that some, but not all, lineages overrepresented in male mice supported a gender bias in T1D. Although protection of males did not correlate with blood androgen concentration, hormone-supported expansion of selected microbial lineages may work as a positive-feedback mechanism contributing to the sexual dimorphism of autoimmune diseases. Gene-expression analysis suggested pathways involved in protection of males from T1D by microbiota. Our results favor a two-signal model of gender bias, in which hormones and microbes together trigger protective pathways.

Inferring transcriptional and microRNA-mediated regulatory programs in glioblastoma.

Large-scale cancer genomics projects are profiling hundreds of tumors at multiple molecular layers, including copy number, mRNA and miRNA expression, but the mechanistic relationships between these layers are often excluded from computational models. We developed a supervised learning framework for integrating molecular profiles with regulatory sequence information to reveal regulatory programs in cancer, including miRNA-mediated regulation. We applied our approach to 320 glioblastoma profiles and identified key miRNAs and transcription factors as common or subtype-specific drivers of expression changes. We confirmed that predicted gene expression signatures for proneural subtype regulators were consistent with in vivo expression changes in a PDGF-driven mouse model. We tested two predicted proneural drivers, miR-124 and miR-132, both underexpressed in proneural tumors, by overexpression in neurospheres and observed a partial reversal of corresponding tumor expression changes. Computationally dissecting the role of miRNAs in cancer may ultimately lead to small RNA therapeutics tailored to subtype or individual.

A cooperative microRNA-tumor suppressor gene network in acute T-cell lymphoblastic leukemia (T-ALL).

The importance of individual microRNAs (miRNAs) has been established in specific cancers. However, a comprehensive analysis of the contribution of miRNAs to the pathogenesis of any specific cancer is lacking. Here we show that in T-cell acute lymphoblastic leukemia (T-ALL), a small set of miRNAs is responsible for the cooperative suppression of several tumor suppressor genes. Cross-comparison of miRNA expression profiles in human T-ALL with the results of an unbiased miRNA library screen allowed us to identify five miRNAs (miR-19b, miR-20a, miR-26a, miR-92 and miR-223) that are capable of promoting T-ALL development in a mouse model and which account for the majority of miRNA expression in human T-ALL. Moreover, these miRNAs produce overlapping and cooperative effects on tumor suppressor genes implicated in the pathogenesis of T-ALL, including IKAROS (also known as IKZF1), PTEN, BIM, PHF6, NF1 and FBXW7. Thus, a comprehensive and unbiased analysis of miRNA action in T-ALL reveals a striking pattern of miRNA-tumor suppressor gene interactions in this cancer.

Genome-wide RNA-mediated interference screen identifies miR-19 targets in Notch-induced T-cell acute lymphoblastic leukaemia.

MicroRNAs (miRNAs) have emerged as novel cancer genes. In particular, the miR-17-92 cluster, containing six individual miRNAs, is highly expressed in haematopoietic cancers and promotes lymphomagenesis in vivo. Clinical use of these findings hinges on isolating the oncogenic activity within the 17-92 cluster and defining its relevant target genes. Here we show that miR-19 is sufficient to promote leukaemogenesis in Notch1-induced T-cell acute lymphoblastic leukaemia (T-ALL) in vivo. In concord with the pathogenic importance of this interaction in T-ALL, we report a novel translocation that targets the 17-92 cluster and coincides with a second rearrangement that activates Notch1. To identify the miR-19 targets responsible for its oncogenic action, we conducted a large-scale short hairpin RNA screen for genes whose knockdown can phenocopy miR-19. Strikingly, the results of this screen were enriched for miR-19 target genes, and include Bim (Bcl2L11), AMP-activated kinase (Prkaa1) and the phosphatases Pten and PP2A (Ppp2r5e). Hence, an unbiased, functional genomics approach reveals a coordinate clampdown on several regulators of phosphatidylinositol-3-OH kinase-related survival signals by the leukaemogenic miR-19.

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs.

Transfection of small RNAs (such as small interfering RNAs (siRNAs) and microRNAs (miRNAs)) into cells typically lowers expression of many genes. Unexpectedly, increased expression of genes also occurs. We investigated whether this upregulation results from a saturation effect--that is, competition among the transfected small RNAs and the endogenous pool of miRNAs for the intracellular machinery that processes small RNAs. To test this hypothesis, we analyzed genome-wide transcript responses from 151 published transfection experiments in seven different human cell types. We show that targets of endogenous miRNAs are expressed at significantly higher levels after transfection, consistent with impaired effectiveness of endogenous miRNA repression. This effect exhibited concentration and temporal dependence. Notably, the profile of endogenous miRNAs can be largely inferred by correlating miRNA sites with gene expression changes after transfections. The competition and saturation effects have practical implications for miRNA target prediction, the design of siRNA and short hairpin RNA (shRNA) genomic screens and siRNA therapeutics.