Will Liao

The cellular and molecular origin of tumor-associated macrophages

Long recognized as an evolutionarily ancient cell type involved in tissue homeostasis and immune defense against pathogens, macrophages are being rediscovered as regulators of several diseases, including cancer. Here we show that in mice, mammary tumor growth induces the accumulation of tumor-associated macrophages (TAMs) that are phenotypically and functionally distinct from mammary tissue macrophages (MTMs). TAMs express the adhesion molecule Vcam1 and proliferate upon their differentiation from inflammatory monocytes, but do not exhibit an “alternatively activated” phenotype. TAM terminal differentiation depends on the transcriptional regulator of Notch signaling, RBPJ; and TAM, but not MTM, depletion restores tumor-infiltrating cytotoxic T cell responses and suppresses tumor growth. These findings reveal the ontogeny of TAMs and a discrete tumor-elicited inflammatory response, which may provide new opportunities for cancer immunotherapy. Origins of tumor macrophages To help the immune system fight cancer, it is important to understand the origins and functions of immune cells in tumors and the surrounding tissues. One type of immune cells, macrophages, is present both in tumors and in nearby noncancerous tissue, but the relationship between these two cell populations is unclear. Franklin et al. found that tumor-associated macrophages in mouse mammaries differed in form, function, and origin from macrophages found in nearby noncancerous mammary tissue. Moreover, when they removed macrophages from the tumors but not the other mammary tissue, tumors shrank and cytotoxic T cells—another kind of immune cell that kills tumor cells—infiltrated the tumors. Tumor-associated macrophages may thus be an important therapeutic target. Science, this issue p. 921. The origins of tumor-associated macrophages in a mouse mammary tumor model are revealed. [Also see Perspective by Perdiguero and Geissmann]

Novel Foxo1-dependent transcriptional programs control T reg cell function

Regulatory T (Treg) cells, characterized by expression of the transcription factor forkhead box P3 (Foxp3), maintain immune homeostasis by suppressing self-destructive immune responses. Foxp3 operates as a late-acting differentiation factor controlling Treg cell homeostasis and function, whereas the early Treg-cell-lineage commitment is regulated by the Akt kinase and the forkhead box O (Foxo) family of transcription factors. However, whether Foxo proteins act beyond the Treg-cell-commitment stage to control Treg cell homeostasis and function remains largely unexplored. Here we show that Foxo1 is a pivotal regulator of Treg cell function. Treg cells express high amounts of Foxo1 and display reduced T-cell-receptor-induced Akt activation, Foxo1 phosphorylation and Foxo1 nuclear exclusion. Mice with Treg-cell-specific deletion of Foxo1 develop a fatal inflammatory disorder similar in severity to that seen in Foxp3-deficient mice, but without the loss of Treg cells. Genome-wide analysis of Foxo1 binding sites reveals ∼300 Foxo1-bound target genes, including the pro-inflammatory cytokine Ifng, that do not seem to be directly regulated by Foxp3. These findings show that the evolutionarily ancient Akt–Foxo1 signalling module controls a novel genetic program indispensable for Treg cell function.

The Transcription Factor Foxo1 Controls Central-Memory CD8+ T Cell Responses to Infection

Memory T cells protect hosts from pathogen reinfection, but how these cells emerge from a pool of antigen-experienced T cells is unclear. Here, we show that mice lacking the transcription factor Foxo1 in activated CD8+ T cells have defective secondary, but not primary, responses to Listeria monocytogenes infection. Compared to short-lived effector T cells, memory-precursor T cells expressed higher amounts of Foxo1, which promoted their generation and maintenance. Chromatin immunoprecipitation sequencing revealed the transcription factor Tcf7 and the chemokine receptor Ccr7 as Foxo1-bound target genes, which have critical functions in central-memory T cell differentiation and trafficking. These findings demonstrate that Foxo1 is selectively incorporated into the genetic program that regulates memory CD8+ T cell responses to infection.

The effects of carbon dioxide and temperature on microRNA expression in Arabidopsis development

Elevated levels of CO2 and temperature can both affect plant growth and development, but the signalling pathways regulating these processes are still obscure. MicroRNAs function to silence gene expression, and environmental stresses can alter their expressions. Here we identify, using the small RNA-sequencing method, microRNAs that change significantly in expression by either doubling the atmospheric CO2 concentration or by increasing temperature 3-6 °C. Notably, nearly all CO2-influenced microRNAs are affected inversely by elevated temperature. Using the RNA-sequencing method, we determine strongly correlated expression changes between miR156/157 and miR172, and their target transcription factors under elevated CO2 concentration. Similar correlations are also found for microRNAs acting in auxin-signalling, stress responses and potential cell wall carbohydrate synthesis. Our results demonstrate that both CO2 and temperature alter microRNA expression to affect Arabidopsis growth and development, and miR156/157- and miR172-regulated transcriptional network might underlie the onset of early flowering induced by increasing CO2.

Graded Foxo1 activity in Treg cells differentiates tumour immunity from spontaneous autoimmunity

Regulatory T (Treg) cells expressing the transcription factor Foxp3 have a pivotal role in maintaining immunological self-tolerance; yet, excessive Treg cell activities suppress anti-tumour immune responses. Compared to the resting Treg (rTreg) cell phenotype in secondary lymphoid organs, Treg cells in non-lymphoid tissues exhibit an activated Treg (aTreg) cell phenotype. However, the function of aTreg cells and whether their generation can be manipulated are largely unexplored. Here we show that the transcription factor Foxo1, previously demonstrated to promote Treg cell suppression of lymphoproliferative diseases, has an unexpected function in inhibiting aTreg-cell-mediated immune tolerance in mice. We find that aTreg cells turned over at a slower rate than rTreg cells, but were not locally maintained in tissues. aTreg cell differentiation was associated with repression of Foxo1-dependent gene transcription, concomitant with reduced Foxo1 expression, cytoplasmic localization and enhanced phosphorylation at the Akt sites. Treg-cell-specific expression of an Akt-insensitive Foxo1 mutant prevented downregulation of lymphoid organ homing molecules, and impeded Treg cell homing to non-lymphoid organs, causing CD8+ T-cell-mediated autoimmune diseases. Compared to Treg cells from healthy tissues, tumour-infiltrating Treg cells downregulated Foxo1 target genes more substantially. Expression of the Foxo1 mutant at a lower dose was sufficient to deplete tumour-associated Treg cells, activate effector CD8+ T cells, and inhibit tumour growth without inflicting autoimmunity. Thus, Foxo1 inactivation is essential for the migration of aTreg cells that have a crucial function in suppressing CD8+ T-cell responses; and the Foxo signalling pathway in Treg cells can be titrated to break tumour immune tolerance preferentially.

Genome-wide localization of protein-DNA binding and histone modification by a bayesian change-point method with ChIP-seq data

Next-generation sequencing (NGS) technologies have matured considerably since their introduction and a focus has been placed on developing sophisticated analytical tools to deal with the amassing volumes of data. Chromatin immunoprecipitation sequencing (ChIP-seq), a major application of NGS, is a widely adopted technique for examining protein-DNA interactions and is commonly used to investigate epigenetic signatures of diffuse histone marks. These datasets have notoriously high variance and subtle levels of enrichment across large expanses, making them exceedingly difficult to define. Windows-based, heuristic models and finite-state hidden Markov models (HMMs) have been used with some success in analyzing ChIP-seq data but with lingering limitations. To improve the ability to detect broad regions of enrichment, we developed a stochastic Bayesian Change-Point (BCP) method, which addresses some of these unresolved issues. BCP makes use of recent advances in infinite-state HMMs by obtaining explicit formulas for posterior means of read densities. These posterior means can be used to categorize the genome into enriched and unenriched segments, as is customarily done, or examined for more detailed relationships since the underlying subpeaks are preserved rather than simplified into a binary classification. BCP performs a near exhaustive search of all possible change points between different posterior means at high-resolution to minimize the subjectivity of window sizes and is computationally efficient, due to a speed-up algorithm and the explicit formulas it employs. In the absence of a well-established “gold standard” for diffuse histone mark enrichment, we corroborated BCPs island detection accuracy and reproducibility using various forms of empirical evidence. We show that BCP is especially suited for analysis of diffuse histone ChIP-seq data but also effective in analyzing punctate transcription factor ChIP datasets, making it widely applicable for numerous experiment types.

ATRX is a regulator of therapy induced senescence in human cells

Senescence is a state of stable cell cycle exit with important implications for development and disease. Here, we demonstrate that the chromatin remodeling enzyme ATRX is required for therapy-induced senescence. ATRX accumulates in nuclear foci and is required for therapy-induced senescence in multiple types of transformed cells exposed to either DNA damaging agents or CDK4 inhibitors. Mobilization into foci depends on the ability of ATRX to interact with H3K9me3 histone and HP1. Foci form soon after cells exit the cell cycle, before other hallmarks of senescence appear. Eliminating ATRX in senescent cells destabilizes the senescence-associated heterochromatic foci. Additionally, ATRX binds to and suppresses expression from the HRAS locus; repression of HRAS is sufficient to promote the transition of quiescent cells into senescence and preventing repression blocks progression into senescence. Thus ATRX is a critical regulator of therapy-induced senescence and acts in multiple ways to drive cells into this state.Therapy induced senescence (TIS) is a growth suppressive program activated by cytostatic agents in some cancer cells. Here the authors show that the chromatin remodeling enzyme ATRX is a regulator of TIS and drives cells into this state via multiple mechanisms.

Genome wide mapping of Foxo1 binding-sites in murine T lymphocytes

The Forkhead box O (Foxo) family of transcription factors has a critical role in controlling the development, differentiation, and function of T cells. However, the direct target genes of Foxo transcription factors in T cells have not been well characterized. In this study, we focused on mapping the genome wide Foxo1-binding sites in naïve CD4+ T cells, CD8+ T cells, and Foxp3+ regulatory T (Treg) cells. By using chromatin immunoprecipitation coupled with deep sequencing (ChIP-Seq), we identified Foxo1 binding sites that were shared among or specific to the three T cell populations. Here we describe the experiments, quality controls, as well as the deep sequencing data. Part of the data analysis has been published by Ouyang W et al. in Nature 2012 [1] and Kim MV et al. in Immunity 2013 [2], and the associated data set were uploaded to NCBI Gene Expression Omnibus.

Abstract 4497: NYGC glioblastoma clinical outcomes pilot study: Discovering therapeutic potential in glioblastoma through integrative genomics

Current adjuvant therapeutic options for the treatment of Glioblastoma (GBM) are often determined by limited histological information. Additionally, most GBM clinical trials for targeted chemotherapeutic agents do not distinguish the genetic mutational tumor profiles of the patients recruited and have failed to reach successful treatment endpoints. The New York Genome Center (NYGC) has undertaken a glioblastoma clinical sequencing outcome pilot study to better determine personal treatment options for patients with GBM using integrated genomic data. During the initial phase of this study for 2015 NYGC has performed whole genome sequencing (WGS) on 10 primary GBM tumor-normal pairs, analyzed each patient9s tumor for single nucleotide variants, structural variants and copy number alterations. In addition RNA sequencing and a DNA methylation assay were also performed on several of the patients. The patient9s genomic profile was then compared to a database of known targeted therapeutic approaches. A final tumor board composed of NYGC scientists, GBM consortium scientists and treating oncologists then reviewed all data prior to identifying a final therapeutic strategy. Data from the first 10 patients revealed RB1 variants to be predominant in half of the patients. SNV9s in NF1 or PIK3R1 were also discovered in 4 out of 10 samples. Remaining lower frequency variants occurred in TP53, PDGFRA, PTEN, PIK3CA, ERBB3, SMO, STAG2, ACVR1, NFKB1 and JAK3. Analysis of copy number alterations resulted in 8 of 10 patients containing the characteristic chromosome 7 amplification combined with chromosome 10 deletion, affecting EGFR and PTEN, respectively. Extreme amplification with potential double minute structural variation of EGFR containing the A289V mutation was observed in 2 of 10 samples. Two samples contained a potentially targetable over-amplification of the PDGFRA/KIT/KDR chromosome 4 locus. Predominant deletions resided in CDKN2A, ESR2, PTEN and FLT3. Hemizygous deletions of RB1 combined with RB1 nonsense or missense variants were observed in 4 samples. To date, RNA sequencing was performed on 5 patient samples. Most strikingly the combination of DNA and RNA sequencing revealed the presence of a putative activating MET exon skipping event in the extracellular domain. This MET variant was considered as a potential targetable variant. Therapeutic options resulting from WGS genomic profiles were the PI3K inhibitor BKM120 (60%), half of these had an additional aberration in MET and were recommended for the combinatorial trial NCT01870726. Drug recommendations for the treatment of GBM based on specific N = 1 patient genomic profiles were also made for nilotinib, vismodegib and palbociclib. Here, we present the first phase of the NYGC GBM clinical outcome study demonstrating how patient WGS information can provide more precise therapeutic options in the treatment of glioblastoma. Citation Format: Kazimierz O. Wrzeszczynski, Nicolas Robine, Vladimir Vacic, Anne-Katrin Emde, Bo-Juen Chen, Will Liao, Kanika Arora, Minita Shah, Ewa A. Grabowska, Vanessa Felice, Esra Dikoglu, Catherine Reeves, Mayu Frank, Vaidehi Jobanputra, Michael C. Zody, Toby Bloom, Robert B. Darnell. NYGC glioblastoma clinical outcomes pilot study: Discovering therapeutic potential in glioblastoma through integrative genomics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4497.

A Stochastic Segmentation Model for the Indentification of Histone Modification and DNase I Hypersensitive Sites in Chromatin

Focal alterations in chromatin structure are essential for the proper functioning of various classes of transcriptional regulatory elements in the human genome. These changes can be detected through an increased sensitivity to DNase I and other nucleases due to an open and accessible chromatin conformation. Currently, quantitative analysis approaches use heuristic procedures to identify regions enriched for histone modifications and DNase I hypersensitivity. We here develop a stochastic segmentation model and associate inference framework to characterize the categorical and continuous features of hierarchical structures hidden in sequences. The proposed model has attractive statistical and computational properties and yields explicit formulas for posterior distribution of hidden states with a hierarchical structure. We propose an approximation method whose computational complexity is only linear in sequence length. We demonstrate the performance of the model via extensive simulations. We further use our model to identify DNase I sensitivity and DNase I hypersentitive sites over the Encyclopedia of DNA Elements (ENCODE) regions in human lymphoblastoid cells.