Biology subjects

Chang, J. T.

Publications and source records attributed to Chang, J. T..

At least 19 recordsLinked to original sources

bioRxiv2024

An annotated biobank of triple negative breast cancer patient-derived xenografts featuring treatment-naive and longitudinal samples throughout neoadjuvant chemotherapy

Triple negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC. To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in the ARTEMIS clinical trial (NCT02276443) at MD Anderson Cancer Center, including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT and from metastatic disease. Models were established from both chemosensitive and chemoresistant tumors, and nearly 30% of PDX models were capable of lung metastasis. Comprehensive molecular profiling demonstrated conservation of genomes and transcriptomes between patient and corresponding PDX tumors, with representation of all major transcriptional subtypes. Transcriptional changes observed in the longitudinal PDX models highlight dysregulation in pathways associated with DNA integrity, extracellular matrix interactions, the ubiquitin-proteasome system, epigenetics, and inflammatory signaling. These alterations reveal a complex network of adaptations associated with chemoresistance. This PDX biobank provides a valuable resource for tackling the most pressing issues facing the clinical management of TNBC, namely chemoresistance and metastasis.

cancer biology↗

bioRxiv2024

TRMT1L-catalyzed m22G27 on tyrosine tRNA is required for efficient mRNA translation and cell survival under oxidative stress.

tRNA modifications are critical for several aspects of their functions, including decoding, folding, and stability. Using a multifaceted approach encompassing eCLIP-seq and Nanopore tRNA-seq, we show that the human tRNA methyltransferase TRMT1L interacts with component of the Rix1 ribosome biogenesis complex and binds to the 28S rRNA, as well as to a subset of tRNAs. Mechanistically, we demonstrate that TRMT1L is responsible for catalyzing m22G solely at position 27 of tRNA-Tyr-GUA. Surprisingly, TRMT1L depletion also impaired the deposition of acp3U and dihydrouridine on tRNA-Tyr-GUA, Cys-GCA, and Ala-CGC. TRMT1L knockout cells have a marked decrease in tRNA-Tyr-GUA levels, coinciding with a reduction in global translation rates and hypersensitivity to oxidative stress. Our results establish TRMT1L as the elusive methyltransferase catalyzing the m22G27 modification on tRNA Tyr, resolving a long-standing gap of knowledge and highlighting its potential role in a tRNA modification circuit crucial for translation regulation and stress response.

molecular biology↗

bioRxiv2024

Functional Diversity of Memory CD8 T Cells is Spatiotemporally Imprinted

Tissue-resident memory CD8 T cells (TRM) kill infected cells and recruit additional immune cells to limit pathogen invasion at barrier sites. Small intestinal (SI) TRM cells consist of distinct subpopulations with higher expression of effector molecules or greater memory potential. We hypothesized that occupancy of diverse anatomical niches imprints these distinct TRM transcriptional programs. We leveraged human samples and a murine model of acute systemic viral infection to profile the location and transcriptome of pathogen-specific TRM cell differentiation at single-transcript resolution. We developed computational approaches to capture cellular locations along three anatomical axes of the small intestine and to visualize the spatiotemporal distribution of cell types and gene expression. TRM populations were spatially segregated: with more effector- and memory-like TRM preferentially localized at the villus tip or crypt, respectively. Modeling ligand-receptor activity revealed patterns of key cellular interactions and cytokine signaling pathways that initiate and maintain TRM differentiation and functional diversity, including different TGF{beta} sources. Alterations in the cellular networks induced by loss of TGF{beta}RII expression revealed a model consistent with TGF{beta} promoting progressive TRM maturation towards the villus tip. Ultimately, we have developed a framework for the study of immune cell interactions with the spectrum of tissue cell types, revealing that T cell location and functional state are fundamentally intertwined.

immunology↗

bioRxiv2023

Selective IL-27 production by intestinal regulatory T cells permits gut-specific regulation of Th17 immunity

Regulatory T (Treg) cells are instrumental in establishing immunological tolerance. However, the precise effector mechanisms by which Treg cells control a specific type of immune response in a given tissue remains unresolved. By simultaneously studying Treg cells from different tissue origins under systemic autoimmunity, here we show that IL-27 is specifically produced by intestinal Treg cells to regulate Th17 immunity. Selectively increased intestinal Th17 responses in mice with Treg cell-specific IL-27 ablation led to exacerbated intestinal inflammation and colitis-associated cancer, but also helped protect against enteric bacterial infection. Furthermore, single-cell transcriptomic analysis has identified a CD83+TCF1+ Treg cell subset that is distinct from previously characterized intestinal Treg cell populations as the main IL-27 producers. Collectively, our study uncovers a novel Treg cell suppression mechanism crucial for controlling a specific type of immune response in a particular tissue, and provides further mechanistic insights into tissue-specific Treg cell-mediated immune regulation.

immunology↗

bioRxiv2022

The Cousa objective: a long working distance air objective for multiphoton imaging in vivo

Multiphoton microscopy can resolve fluorescent structures and dynamics deep in scattering tissue, but applying this technique in vivo can be limited by short working distance water-immersion objectives. Here we present an ultra long working distance (20 mm) air objective called the Cousa objective. It is optimized for performance across multiphoton imaging wavelengths, offers a > 4 mm2 field-of-view with submicron lateral resolution, and is compatible with commonly used multiphoton imaging systems. We share the full optical prescription, and report performance including in vivo 2-photon and 3-photon imaging in a range of species and preparations.

neuroscience↗

bioRxiv2022

Phylogenetic inference from single-cell RNA-seq data

Tumors are comprised of subpopulations of cancer cells that harbor distinct genetic profiles and phenotypes that evolve over time and during treatment. By reconstructing the course of cancer evolution, we can understand the acquisition of the malignant properties that drive tumor progression. Unfortunately, recovering the evolutionary relationship of individual cancer cells linked to their phenotypes remains a difficult challenge. To address this issue, we have developed PhylinSic, a method that reconstructs the phylogenetic relationships among cells linked to their gene expression profiles from single cell RNA-sequencing (scRNA-Seq) data, and showed that it was robust to the low read depth, drop-out, and noisiness of scRNA-Seq data. This method called nucleotide bases from scRNA-Seq reads using a probabilistic smoothing approach, and then estimated a phylogenetic tree using a Bayesian modeling algorithm. We evaluated PhylinSic and showed that it identified evolutionary relationships resulting from selective events such as drug selection and metastasis and was sensitive enough to identify subclones from genetic drift. Finally, we applied methods of phylogenetic inference and found that breast tumors resistant to chemotherapies harbored two genetic lineages that independently manifested high predicted activity of K-Ras and {beta}-catenin, potentially acquired by distinct mechanisms through convergent evolution. This suggested that therapeutic strategies may need to target multiple lineages to be durable. Taken together, these results demonstrated that PhylinSic provides a framework to model the evolution and link the genotypes and phenotypes of cells within a tumor or cohort of monophyletic tumors using scRNA-Seq.

bioinformatics↗

bioRxiv2022

Cancer cells communicate with macrophages to prevent T cell activation during development of cell cycle therapy resistance

Cancer cells evolve, acquire resistance to therapy and change their environment. One resistance mechanism involves altering communication with non-malignant cells in the tumor microenvironment (TME). By corrupting the signals for growth and survival, evolving cancer cells can engineer a pro-tumor TME. However, the specific interactions between malignant and non-malignant cells that predispose drug resistance and their changes during treatment remain widely unknown. Here we examine the composition, communication, and phenotypic diversity of tumor-associated cell populations in serial biopsies from early-stage ER+ breast cancers. These patients received either endocrine therapy (letrozole) alone or in combination with a CDK4/6 cell cycle inhibitor ribociclib, and were analyzed using single-cell RNA sequencing (scRNAseq). Our analyses reveal cancer cells from ribociclib resistant tumors stimulate macrophage differentiation towards an immune-suppressive phenotype through upregulation of a broad diversity of cytokines and growth factors. This shift in phenotype leads to reduced macrophage cell IL-15/-18 crosstalk with CD8+ T-cell via IL-2/15RA/18R receptors, resulting in diminished T-cell activation and recruitment. Thus, cancer communication promoting an immune-cold TME predispose tumors to develop CDK4/6 inhibitor resistance, and that the beneficial effects of cell cycle inhibitors through blocking cancer cell proliferation must be balanced against their known inhibitory effect on immune cell division and activation. An optimal treatment strategy will require coupling the prevention of cancer division with activation of an effective cytotoxic T-cell response.

cancer biology↗

bioRxiv2022

Systems-level identification of key transcription factors in immune cell specification

Transcription factors (TFs) are crucial for regulating cell differentiation during the development of the immune system. However, the key TFs for orchestrating the specification of distinct immune cells are not fully understood. Here, we integrated the transcriptomic and epigenomic measurements in 73 mouse and 61 human primary cell types, respectively, that span the immune cell differentiation pathways. We constructed the cell-type-specific transcriptional regulatory network and assessed the global importance of TFs based on the Taiji framework, which is a method we have previously developed that can infer the global impact of TFs using integrated transcriptomic and epigenetic data. Integrative analysis across cell types revealed putative driver TFs in cell lineage-specific differentiation in both mouse and human systems. We have also identified TF combinations that play important roles in specific developmental stages. Furthermore, we validated the functions of predicted novel TFs in murine CD8+ T cell differentiation and showed the importance of Elf1 and Prdm9 in the effector versus memory T cell fate specification and Kdm2b and Tet3 in promoting differentiation of CD8+ tissue resident memory (Trm) cells, validating the approach. Thus, we have developed a bioinformatic approach that provides a global picture of the regulatory mechanisms that govern cellular differentiation in the immune system and aids the discovery of novel mechanisms in cell fate decisions.

systems biology↗

bioRxiv2022

Chromatin-associated lncRNA Malat1 regulates Th17 effector program and promotes intestinal inflammation

Interleukin IL-17 cytokines are central regulators of mucosal homeostasis and disease. In mouse models of colonic tissue injury, IL-17A promotes epithelial barrier functions and restricts local inflammation. Here, we report that IL-17A production by the diverse T lymphocyte subsets is dynamically regulated at different stages of colitis pathogenesis. During the onset and peak of the disease, T{gamma}{delta}17 cells are the major IL-17A producers, while Th17 activity is temporally restricted by long non-coding RNA (lncRNA) Malat1. In response to IL-6 and TGF{beta} signaling, Malat1 is recruited to the Th17-specific cis-regulatory elements, CNS3 and CNS4, of the Il17a locus to fine-tune bivalent super-enhancer activities and repress local transcription. During the resolution phase of inflammation, Malat1 expression is down-regulated to enhance Th17 activities, allowing Th17 cells to emerge as the main producers of IL-17A in the colonic lamina propria. Genetic ablation of Malat1 potentiates IL-17A production in Th17 cells and improves disease outcomes in mouse models of colitis. These findings uncover a surprising role of a chromatin-associated lncRNA in regulating colonic Th17-specific responses to control the timing of inflammation resolution. Significance StatementT cells are critical modulators of mucosal barrier function and inflammation. The function of long-noncoding RNAs (lncRNAs) in T cells and their role in mucosal inflammation remain elusive. Here, we identify an essential role of the lncRNA Malat1 restricting transcription of the Il17a locus in Th17 cells encoding a cytokine implicated in epithelial barrier function post-injury. By controlling the activity of the bivalent super-enhancer at the Il17a locus, Malat1 regulates the timing of inflammation resolution in the intestine. The Malat1-Il17a pathway reveals new targets for combating mucosal diseases. Graphic Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

immunology↗

bioRxiv2021

Development of visual response selectivity in cortical GABAergic interneurons

The visual cortex of carnivores and primates displays a high degree of modular network organization characterized by local clustering and structured long-range correlations of activity and functional properties. Excitatory networks display modular organization before the onset of sensory experience, but the developmental timeline for modular networks of GABAergic interneurons, remains under-explored. Using in vivo calcium imaging of the ferret visual cortex, we find evidence that before visual experience, interneurons display weak orientation tuning and widespread non-specific activation in response to visual stimuli. Modular organization and orientation tuning are evident with as little as one week of visual experience. Furthermore, we find that the development of orientation tuning requires visual experience, while the reduction in widespread network activity does not. Thus, the maturation of inhibitory cortical networks occurs in a delayed, parallel process relative to excitatory neurons.

neuroscience↗

bioRxiv2021

Serine 182 on RORγt regulates T helper 17 and regulatory T cell functions to resolve inflammation

Intestine homeostasis is maintained by the delicate balance of Th17 effector cells and Treg cells. Dysregulation of these cell populations contributes to inflammation, tissue damage, and chronic conditions. ROR{gamma}t is essential for the differentiation of Th17 and a subset of Treg (ROR{gamma}t+ Treg) cells involved in intestinal inflammation. ROR{gamma}t belongs to the nuclear receptor family of transcription factors with hinge regions that are highly flexible for co-activator/co-repressor interactions. Serine 182 at the hinge region of ROR{gamma}t is phosphorylated. This study aims to uncover how S182 on ROR{gamma}t contributes to mucosal homeostasis and diseases. We used CRISRP technology to generate a phosphor-null knock-in mutant mouse line (ROR{gamma}tS182A) to assess its role in intestine physiology. scRNA-seq was performed on WT and ROR{gamma}tS182A cohoused littermates to evaluate colonic T cell heterogeneity under steady state and colitis settings. Single-cell transcriptomics revealed that ROR{gamma}tS182 maintains colonic T cell heterogeneity under steady state, without interfering T cell development and differentiation. In inflamed tissues, ROR{gamma}tS182 simultaneously restricts IL-1{beta}-mediated Th17 activities and promotes anti-inflammatory cytokine IL-10 production in LT-like Treg cells. Phospho-null ROR{gamma}tS182A knock-in mice challenged with DSS induced colitis and EAE experienced delayed recovery and exacerbated pathology. The double switch role of ROR{gamma}tS182 is critical in resolving T cell-mediated inflammation and provides a potential therapeutic target to combat autoimmune diseases.

immunology↗

bioRxiv2021

Simplifying the development of portable, scalable, and reproducible workflows

Command-line software plays a critical role in biology research. However, processes for installing and executing software differ widely. The Common Workflow Language (CWL) is a community standard that addresses this problem. Using CWL, tool developers can formally describe a tools inputs, outputs, and other execution details in a manner that fosters use of shared computational methods and reproducibility of complex analyses. CWL documents can include instructions for executing tools inside software containers--isolated, operating-system environments. Accordingly, CWL tools are portable--they can be executed on diverse computers--including personal workstations, high-performance clusters, or the cloud. This portability enables easier adoption of bioinformatics pipelines. CWL supports workflows, which describe dependencies among tools and using outputs from one tool as inputs to others. To date, CWL has been used primarily for batch processing of large datasets, especially in genomics. But it can also be used for analytical steps of a study. This article explains key concepts about CWL and software containers and provides examples for using CWL in biology research. CWL documents are text-based, so they can be created manually, without computer programming. However, ensuring that these documents confirm to the CWL specification may prevent some users from adopting it. To address this gap, we created ToolJig, a Web application that enables researchers to create CWL documents interactively. ToolJig validates information provided by the user to ensure it is complete and valid. After creating a CWL tool or workflow, the user can create "input-object" files, which store values for a particular invocation of a tool or workflow. In addition, ToolJig provides examples of how to execute the tool or workflow via a workflow engine.

bioinformatics↗

bioRxiv2021

Convergent evolution of resistance pathways during early stage breast cancer treatment with combination cell cycle (CDK) and endocrine inhibitors

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for metastatic estrogen receptor positive (ER+), HER2 negative, breast cancer patients. However, the value of this combination in potentially curable earlier stage patients is not clear. Using single cell transcriptomic profiling, we examined the evolutionary trajectories of early stage breast cancer tumors using serial tumor biopsies from a clinical trial of preoperative endocrine therapy (letrozole) alone or in combination with the cell cycle inhibitor ribociclib. Applying hierarchical regression and Gaussian process mathematical modelling, we classified each tumor by whether it shrinks or persists with therapy and determined cancer phenotypes related to evolution of resistance and cell cycle transcriptional rewiring. We found that all patients tumors undergo subclonal evolution during therapy, irrespective of the clinical response. However, tumors subjected to endocrine therapy alone showed reduced diversity over time, while those facing combination therapy exhibited increased diversity. Despite different subclonal diversity, single nuclei RNA sequencing uncovered common phenotypic changes in tumor cells that persist following treatment. In these tumors, cancer cells with accelerated loss of estrogen signaling have convergent up-regulation of the JNK pathway, while cells that maintain estrogen signaling during therapy show potentiation of CDK4/6 activation consistent with ERBB4 and ERK signaling up-regulation. These convergent phenotypes were associated with growing tumors resistant to combination therapy. Cell cycle reconstruction identified that these tumors can rebound during combination therapy treatment, indicating stronger selection and promotion of a proliferative state. These results indicate that combination therapy in early stage ER+ breast cancers with ER and CDK inhibition drives rapid evolution of resistance via a shift from estrogen signaling to alternative growth factor receptor mediated proliferation and JNK signaling activation, concordant with a bypass in the G1 checkpoint.

cancer biology↗

bioRxiv2020

RNA adenosine deaminase ADAR2 modulates T helper 17 cell effector function

ADAR1 and ADAR2 catalyze adenosine-to-inosine (A-to-I) editing, the most common post-transcriptional modification in RNA. While ADAR1 is ubiquitously expressed and plays a critical role in preventing activation of the host immune system, ADAR2 exhibits tissue-specific and inducible expression patterns, and its function in the immune system is not known. Here, we identify an intragenic super-enhancer involved in the dramatic induction of ADAR2 when naive helper T cells differentiate toward the Th17 lineage. By editing the inverted repeat sequences at the 3 untranslated region (UTR) of Malt1, which encodes a component of the NF-{kappa}B activation complex, ADAR2 promotes MALT1 expression and Th17 effector function. Interference with the ADAR2-MALT1 pathway dampens the production of Th17 cytokines and promotes T cell-mediated colitis. This study expands our understanding of RNA editing in adaptive immunity and identifies the ADAR2-MALT1-IL-17A axis as a potential therapeutic target for inflammatory conditions in the intestine.

immunology↗

bioRxiv2020

Delineation of a molecularly distinct terminally differentiated memory CD8 T cell population

Memory CD8 T cells provide durable protection against diverse intracellular pathogens and can be broadly segregated into distinct circulating and tissue-resident populations. Paradigmatic studies have demonstrated circulating memory cells can be further divided into effector memory (TO_SCPLOWEMC_SCPLOW) and central memory (TO_SCPLOWCMC_SCPLOW) populations based on discrete functional characteristics. Following resolution of infection, we identified a persisting antigen-specific CD8 T cell population that was simultaneously terminally-fated with potent effector function but maintained memory T cell qualities and conferred robust protection against reinfection. Notably, this terminally-differentiated effector memory CD8 T cell population (terminal-TO_SCPLOWEMC_SCPLOW) was conflated within the conventional TO_SCPLOWEMC_SCPLOW population, prompting redefinition of the classical characteristics of TO_SCPLOWEMC_SCPLOW cells. Murine terminal-TO_SCPLOWEMC_SCPLOW were transcriptionally, functionally, and developmentally unique compared to TO_SCPLOWEMC_SCPLOW cells. Through mass cytometry and single-cell RNAseq analyses of human peripheral blood from healthy individuals, we also identified an analogous terminal-TO_SCPLOWEMC_SCPLOW population of CD8 T cells that was transcriptionally distinct from TO_SCPLOWEMC_SCPLOW and TO_SCPLOWCMC_SCPLOW. A key finding of this study was that parsing of terminal-TO_SCPLOWEMC_SCPLOW from conventionally defined TO_SCPLOWEMC_SCPLOW challenges classical characteristics of TO_SCPLOWEMC_SCPLOW biology, including enhanced presence in lymphoid tissues, robust IL-2 production and recall potential, greater than expected homeostatic fitness, refined transcription factor dependencies, and a distinct molecular phenotype. Classification of terminal-TO_SCPLOWEMC_SCPLOW and clarification of TO_SCPLOWEMC_SCPLOW biology hold broad implications for understanding the molecular regulation of memory cell states and harnessing immunological memory to improve immunotherapies.

immunology↗

bioRxiv2020

Circulating immune cell phenotype dynamics reflect the strength of tumor-immune cell interactions in patients during immunotherapy

The extent that immune cell phenotypes in the peripheral blood reflect within-tumor immune activity prior to and early in cancer therapy is unclear. To address this question, we studied the population dynamics of tumor and immune cells, and immune phenotypic changes, using clinical tumor and immune cell measurements and single cell genomic analyses. These samples were serially obtained from a cohort of advanced gastrointestinal cancer patients enrolled on a trial with chemotherapy and immunotherapy. Using an ecological population model, fitted to clinical tumor burden and immune cell abundance data from each patient, we find evidence of a strong tumor-circulating immune cell interaction in responder patients, but not those patients that progress on treatment. Upon initiation of therapy, immune cell abundance increased rapidly in responsive patients, and once the peak level is reached, tumor burden decreases, similar to models of predator-prey interactions; these dynamic patterns were absent in non-responder patients. To interrogate phenotype dynamics of circulating immune cells, we performed single cell RNA sequencing at serial time points during treatment. These data show that peripheral immune cell phenotypes were linked to the increased strength of patients tumor-immune cell interaction, including increased cytotoxic differentiation and strong activation of interferon signaling in peripheral T-cells in responder patients. Joint modeling of clinical and genomic data highlights the interactions between tumor and immune cell populations and reveals how variation in patient responsiveness can be explained by differences in peripheral immune cell signaling and differentiation soon after the initiation of immunotherapy. One sentence summaryPeripheral immune cell differentiation and signaling, upon initiation of immunotherapy, reflects tumor attacking ability and patient response. Significance statementThe evolution of peripheral immune cell abundance and signaling over time, as well as how these immune cells interact with the tumor, may impact a cancer patients response to therapy. By developing an ecological population model, we provide evidence of a dynamic predator-prey like relationship between circulating immune cell abundance and tumor size in patients that respond to immunotherapy. This relationship is not found either in patients that are non-responsive to immunotherapy or during chemotherapy. Single cell RNA-sequencing (scRNAseq) of serial peripheral blood samples from patients show that the strength of tumor-immune cell interactions is reflected in T-cells interferon activation and differentiation early in treatment. Thus, circulating immune cell dynamics reflect a tumors response to immunotherapy.

cancer biology↗

bioRxiv2020

Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data with ImmClassifier

Single-cell RNA sequencing is an emerging strategy for characterizing the immune cell population in diverse environments including blood, tumor or healthy tissues. While this has traditionally been done with flow or mass cytometry targeting protein expression, scRNA-Seq has several established and potential advantages in that it can profile immune cells and non-immune cells (e.g. cancer cells) in the same sample, identify cell types that lack precise markers for flow cytometry, or identify a potentially larger number of immune cell types and activation states than is achievable in a single flow assay. However, scRNA-Seq is currently limited due to the need to identify the types of each immune cell from its transcriptional profile, which is not only time-consuming but also requires a significant knowledge of immunology. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells vs macrophages), making fine distinctions has turned out to be a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that ImmClassifier outperforms other tools (+20% recall, +14% precision) in distinguishing fine-grained cell types (e.g. CD8+ effector memory T cells) with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.

bioinformatics↗

bioRxiv2020

A 'one-two punch' therapy strategy to target chemoresistance in ER+ breast cancer

BackgroundCancer cell phenotypes evolve over the course of a tumors treatment. The phenotypes that emerge and disappear over time will be specific to each drug regimen and type of cancer. Chemotherapy remains one of the most common and effective treatments for metastatic breast cancer patients; however, resistance to chemotherapy inevitably emerges. Cancer chemotherapy treatment regimens are not designed to target emerging chemo-resistance, despite its clear importance in progressive cancer. This study focuses on finding sequential treatment strategies that target acquired chemo-resistant states and optimize response to chemotherapy. MethodsIn this study, we used heterogeneous tumor samples from patients to identify subclones resistant to chemotherapy. Using flow cytometry for stem cell markers and DNA sequencing to define subclonal population changes, we measured the enrichment of cancer stem cell-like (CSL) phenotypes in subclones that survive chemotherapy. We then analyzed breast cancer patient tumor organoids and cell line acquisition of CSL traits following chemotherapy, as well as the ability of different drugs to reverse acquired resistance, using flow cytometry, mammosphere assays, and single cell RNA-sequencing analysis. ResultsWe show that in progressive estrogen receptor positive (ER+) metastatic breast cancer patients, resistant tumor subclones that emerge following chemotherapy have increased CSL abundance. Further, in vitro organoid growth of ER+ patient cancer cells also shows that chemotherapy treatment leads to increased abundance of ALDH+/CD44+ CSL cells. Chemotherapy induced CSL abundance is blocked by treatment with a pan-HDAC inhibitor, belinostat. Further, belinostat treatment diminished both mammosphere formation and size following chemotherapy, also indicating a decrease in progenitor CSL traits. HDAC inhibitors specific to class IIa (HDAC4, HDAC5) and IIb (HDAC6) were shown to primarily reverse the chemo-resistant CSL state. Single-cell RNA sequencing analysis with patient samples showed that HDAC targets and MYC signaling were promoted by chemotherapy and inhibited upon HDAC inhibitor treatment. ConclusionThese findings indicate that HDAC inhibition can block chemotherapy-induced drug resistant phenotypes with one-two punch strategy in refractory breast cancer cells.

cancer biology↗