Biology subjects

Chan, T.

Publications and source records attributed to Chan, T..

28 records · Page 2Linked to original sources

bioRxiv2020

IRF8 Governs Tumor-Associated Macrophage Control of T Cell Exhaustion

Tumor progression is associated with overstimulation of cytotoxic T lymphocytes (CTLs), resulting in a dysfunctional state of exhaustion. How T cell exhaustion is elicited in the tumor remains poorly understood. Here we show that tumor-associated macrophages (TAMs) present cancer cell antigen and induce CTL exhaustion through a gene expression program dependent on the transcription factor interferon regulatory factor-8 (IRF8). In a transgenic model of murine breast cancer, CTL priming was supported by IRF8-dependent dendritic cells; yet, CTL exhaustion required TAM expression of IRF8, and its ablation suppressed tumor growth. An analysis of the highly immune-infiltrated human renal cell carcinoma tumors revealed abundant TAMs that expressed IRF8 and were enriched for an IRF8 gene expression signature. The IRF8 signature co-segregated with T cell exhaustion markers and was negatively associated with long-term patient survival. Thus, CTL exhaustion is promoted by TAMs via IRF8, and this crosstalk may be disrupted in TAM-targeted therapies.

immunology↗

bioRxiv2020

Differential RNA editing between epithelial and mesenchymal tumors impacts mRNA abundance in immune response pathways

Recent studies revealed global shifts in RNA editing, the modification of RNA sequences, across many cancers. Besides a few sites implicated in tumorigenesis or metastasis, most tumor-associated sites, predominantly in noncoding regions, have unknown function. Here, we characterize editing profiles between epithelial (E) and mesenchymal (M) phenotypes in seven cancer types, as epithelial-mesenchymal transition (EMT) is a key paradigm for metastasis. We observe distinct editing patterns between E and M tumors and EMT induction upon loss of ADAR enzymes in cultured cells. E-M differential sites are highly enriched in genes involved in immune and viral processes, some of which regulate mRNA abundance of their respective genes. We identify a novel mechanism in which ILF3 preferentially stabilizes edited transcripts. Among editing-dependent ILF3 targets is the transcript encoding PKR, a crucial player in immune response. Our study demonstrates the broad impact of RNA editing in cancer and relevance of editing to cancer-related immune pathways.

cancer biology↗

bioRxiv2020

TGFβ Suppresses Type 2 Immunity to Cancer

The immune system employs two distinct defense strategies against infections: pathogen elimination typified by type 1 immunity, and pathogen containment exemplified by type 2 immunity in association with tissue repair. Akin to infectious diseases, cancer progresses with cancer cell acquisition of microorganism-like behavior propagating at the expense of the host. While immunological mechanisms of cancer cell elimination are well defined, whether immune-mediated cancer cell containment can be induced is poorly understood. Here we show that ablation of transforming growth factor-{beta} receptor II (TGF{beta}RII) in CD4+ T cells promotes tumor tissue healing and halts cancer progression. Notably, the restorative response is dependent on the T helper 2 cytokine IL-4 fortifying vasculature organization that spares only proximal layers of cancer cells from hypoxia, nutrient starvation and death. Thus, type 2 immunity represents an effective cancer defense mechanism, and TGF{beta} signaling in helper T cells may be targeted for novel cancer immunotherapy.

immunology↗

bioRxiv2020

Millipede genomes reveal unique adaptation of genes and microRNAs during myriapod evolution

The Myriapoda including millipedes and centipedes is of major importance in terrestrial ecology and nutrient recycling. Here, we sequenced and assembled two chromosomal-scale genomes of millipedes Helicorthomorpha holstii (182 Mb, N50 18.11 Mb mainly on 8 pseudomolecules) and Trigoniulus corallinus (449 Mb, N50 26.78 Mb mainly on 15 pseudomolecules). Unique defense systems, genomic features, and patterns of gene regulation in millipedes, not observed in other arthropods, are revealed. Millipedes possesses a unique ozadene defensive gland unlike the venomous forcipules in centipedes. Sets of genes associated with anti-microbial activity are identified with proteomics, suggesting that the ozadene gland is not primarily an antipredator adaptation (at least in T. corallinus). Macro-synteny analyses revealed highly conserved genomic blocks between centipede and the two millipedes. Tight Hox and the first loose ecdysozoan ParaHox homeobox clusters are identified, and a myriapod-specific genomic rearrangement including Hox3 is also observed. The Argonaute proteins for loading small RNAs are duplicated in both millipedes, but unlike insects, an argonaute duplicate has become a pseudogene. Evidence of post-transcriptional modification in small RNAs, including species-specific microRNA arm switching that provide differential gene regulation is also obtained. Millipede genomes reveal a series of unique genomic adaptations and microRNA regulation mechanisms have occurred in this major lineage of arthropod diversity. Collectively, the two millipede genomes shed new light on this fascinating but poorly understood branch of life, with a highly unusual body plan and novel adaptations to their environment.

evolutionary biology↗

bioRxiv2020

Genome-wide Functional Characterization of Escherichia coli Promoters and Regulatory Elements Responsible for their Function.

Despite decades of intense genetic, biochemical, and evolutionary characterizations of bacterial promoters, we lack the ability to identify or predict transcriptional activities of promoters using primary sequence. Even in simple, well-characterized organisms such as E. coli there is little agreement on the number, location, and strength of promoters. We use a genomically-encoded massively parallel reporter assay to perform the first full characterization of autonomous promoter activity across the E. coli genome. We measure promoter activity of >300,000 sequences spanning the entire genome and map 2,228 promoters active in rich media. Surprisingly, 944 of these promoters were found within intragenic sequences and are associated with conciliatory sequence adaptations by both the protein-coding regions and overlapping RNAP binding sites. Furthermore, we perform a scanning mutagenesis of 2,057 promoters to uncover sequence elements regulating promoter activity, revealing 3,317 novel regulatory elements. Finally, we show that despite these large datasets and modern machine learning algorithms, predicting endogenous promoter activity from primary sequence is still challenging.

microbiology↗

bioRxiv2019

Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via \"mapping\" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

bioinformatics↗

bioRxiv2018

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.

genomics↗

bioRxiv2017

ATRX, DAXX or MEN1 mutant pancreatic neuroendocrine tumors are a distinct alpha-cell signature subgroup

The most commonly mutated genes in pancreatic neuroendocrine tumors (PanNETs) are ATRX, DAXX, and MEN1. Little is known about the cells-of-origin for non-functional neuroendocrine tumors. Here, we genotyped 64 PanNETs for mutations in ATRX, DAXX, and MEN1 and found 37 tumors (58%) carry mutations in these three genes (A-D-M mutant PanNETs) and this correlates with a worse clinical outcome than tumors carrying the wild-type alleles of all three genes (A-D-M WT PanNETs). We performed RNA sequencing and DNA-methylation analysis on 33 randomly selected cases to reveal two distinct subgroups with one group consisting entirely of A-D-M mutant PanNETs. Two biomarkers differentiating A-D-M mutant from A-D-M WT PanNETs were high ARX gene expression and low PDX1 gene expression with PDX1 promoter hyper-methylation in the A-D-M mutant PanNETs. Moreover, A-D-M mutant PanNETs had a gene expression signature related to that of alpha cells (pval < 0.009) of pancreatic islets including increased expression of HNF1A and its transcriptional target genes. This gene expression profile suggests that A-D-M mutant PanNETs originate from or transdifferentiate into a distinct cell type similar to alpha cells.

cancer biology↗

bioRxiv2017

Multi-dimensional genomic analysis of myoepithelial carcinoma identifies prevalent oncogenic gene fusions

Myoepithelial carcinoma (MECA) is an aggressive type of salivary gland cancer with largely unknown molecular features. MECA may arise de novo or result from oncogenic transformation of a pre-existing pleomorphic adenoma (MECA ex-PA). We comprehensively analyzed the molecular alterations in MECA with integrated genomic analyses. We identified a low mutational load (0.5/MB), but a high prevalence of fusion oncogenes (28/40 tumors; 70%). We found FGFR1-PLAG1 in 7 (18%) cases, and the novel TGFBR3-PLAG1 fusion in 6 (15%) cases. TGFBR3-PLAG1 was specific for MECA de novo tumors or the malignant component of MECA ex-PA, was absent in 723 other salivary gland tumors, and promoted a tumorigenic phenotype in vitro. We discovered other novel PLAG1 fusions, including ND4-PLAG1, which is an oncogenic fusion between mitochondrial and nuclear DNA. One tumor harbored an MSN-ALK fusion, which was tumorigenic in vitro, and targetable with ALK inhibitors. Certain gene fusions were predicted to result in neoantigens with high MHC binding affinity. A high number of copy number alterations was associated with poorer prognosis. Our findings indicate that MECA is a fusion-driven disease, nominate TGFBR3-PLAG1 as a hallmark of MECA, and provide a framework for future steps of diagnostic and therapeutic research in this lethal cancer.

cancer biology↗

bioRxiv2017

Software For The Integration Of Multi-Omics Experiments In Bioconductor

Multi-omics experiments are increasingly commonplace in biomedical research, and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multi-omics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide all of the multiple omics data for each cancer tissue in The Cancer Genome Atlas (TCGA) as ready-to-analyze MultiAssayExperiment objects, and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable and reproducible statistical analysis of multi-omics data and enhances data science applications of multiple omics datasets.

bioinformatics↗