Integration of Single-Cell RNA-Sequencing and Network Analysis to Investigate Mechanisms of Drug Resistance.

Innate resistance and therapeutic-driven development of resistance to anticancer drugs is a common complication of cancer therapy. Understanding mechanisms of drug resistance can lead to development of alternative therapies. One strategy is to subject drug-sensitive and drug-resistant variants to single-cell RNA-seq (scRNA-seq) and to subject the scRNA-seq data to network analysis to identify pathways associated with drug resistance. This protocol describes a computational analysis pipeline to study drug resistance by subjecting scRNA-seq expression data to Passing Attributes between Networks for Data Assimilation (PANDA), an integrative network analysis tool that incorporates protein-protein interactions (PPI) and transcription factor (TF)-binding motifs.

Bone Marrow Macrophages Induce Inflammation by Efferocytosis of Apoptotic Prostate Cancer Cells via HIF-1α Stabilization.

The clearance of apoptotic cancer cells by macrophages, known as efferocytosis, fuels the bone-metastatic growth of prostate cancer cells via pro-inflammatory and immunosuppressive processes. However, the exact molecular mechanisms remain unclear. In this study, single-cell transcriptomics of bone marrow (BM) macrophages undergoing efferocytosis of apoptotic prostate cancer cells revealed a significant enrichment in their cellular response to hypoxia. Here, we show that BM macrophage efferocytosis increased hypoxia inducible factor-1alpha (HIF-1α) and STAT3 phosphorylation (p-STAT3 at Tyr705) under normoxic conditions, while inhibitors of p-STAT3 reduced HIF-1α. Efferocytosis promoted HIF-1α stabilization, reduced its ubiquitination, and induced HIF-1α and p-STAT3 nuclear translocation. HIF-1α stabilization in efferocytic BM macrophages resulted in enhanced expression of pro-inflammatory cytokine MIF, whereas BM macrophages with inactive HIF-1α reduced MIF expression upon efferocytosis. Stabilization of HIF-1α using the HIF-prolyl-hydroxylase inhibitor, Roxadustat, enhanced MIF expression in BM macrophages. Furthermore, BM macrophages treated with recombinant MIF protein activated NF-κB (p65) signaling and increased the expression of pro-inflammatory cytokines. Altogether, these findings suggest that the clearance of apoptotic cancer cells by BM macrophages triggers p-STAT3/HIF-1α/MIF signaling to promote further inflammation in the bone tumor microenvironment where a significant number of apoptotic cancer cells are present.

Transcription factor network analysis based on single cell RNA-seq identifies that Trichostatin-a reverses docetaxel resistance in prostate Cancer.

BACKGROUND: Overcoming drug resistance is critical for increasing the survival rate of prostate cancer (PCa). Docetaxel is the first cytotoxic chemotherapeutical approved for treatment of PCa. However, 99% of PCa patients will develop resistance to docetaxel within 3 years. Understanding how resistance arises is important to increasing PCa survival. METHODS: In this study, we modeled docetaxel resistance using two PCa cell lines: DU145 and PC3. Using the Passing Attributes between Networks for Data Assimilation (PANDA) method to model transcription factor (TF) activity networks in both sensitive and resistant variants of the two cell lines. We identified edges and nodes shared by both PCa cell lines that composed a shared TF network that modeled changes which occur during acquisition of docetaxel resistance in PCa. We subjected the shared TF network to connectivity map analysis (CMAP) to identify potential drugs that could disrupt the resistant networks. We validated the candidate drug in combination with docetaxel to treat docetaxel-resistant PCa in both in vitro and in vivo models. RESULTS: In the final shared TF network, 10 TF nodes were identified as the main nodes for the development of docetaxel resistance. CMAP analysis of the shared TF network identified trichostatin A (TSA) as a candidate adjuvant to reverse docetaxel resistance. In cell lines, the addition of TSA to docetaxel enhanced cytotoxicity of docetaxel resistant PCa cells with an associated reduction of the IC50 of docetaxel on the resistant cells. In the PCa mouse model, combination of TSA and docetaxel reduced tumor growth and final weight greater than either drug alone or vehicle. CONCLUSIONS: We identified a shared TF activity network that drives docetaxel resistance in PCa. We also demonstrated a novel combination therapy to overcome this resistance. This study highlights the usage of novel application of single cell RNA-sequencing and subsequent network analyses that can reveal novel insights which have the potential to improve clinical outcomes.

Single-Cell Transcriptomics Analysis Identifies Nuclear Protein 1 as a Regulator of Docetaxel Resistance in Prostate Cancer Cells.

The majority of patients with prostate cancer treated with docetaxel develop resistance to it. To better understand the mechanism behind the acquisition of resistance, we conducted single-cell RNA-sequencing (scRNA-seq) of docetaxel-sensitive and -resistant variants of DU145 and PC3 prostate cancer cell lines. Overall, sensitive and resistant cells clustered separately. Differential gene expression analysis between resistant and sensitive cells revealed 182 differentially expressed genes common to both prostate cancer cell lines. A subset of these genes gave a gene expression profile in the resistant transcriptome-like-sensitive cells similar to the resistant cells. Exploration for functional gene pathways identified 218 common pathways between the two cell lines. Protein ubiquitination was the most differentially regulated pathway and was enriched in the resistant cells. Transcriptional regulator analysis identified 321 potential regulators across both cell lines. One of the top regulators identified was nuclear protein 1 (NUPR1). In contrast to the single-cell analysis, bulk analysis of the cells did not reveal NUPR1 as a promising candidate. Knockdown and overexpression of NUPR1 in the prostate cancer cells demonstrated that NUPR1 confers docetaxel resistance in both cell lines. Collectively, these data demonstrate the utility of scRNA-seq to identify regulators of drug resistance. Furthermore, NUPR1 was identified as a mediator of prostate cancer drug resistance, which provides the rationale to explore NUPR1 and its target genes for reversal of docetaxel resistance. IMPLICATIONS: Using single-cell sequencing of prostate cancer, we show that NUPR1 plays a role in docetaxel resistance.

Rab11b-mediated integrin recycling promotes brain metastatic adaptation and outgrowth.

Breast cancer brain metastases (BCBM) have a 5-20 year latency and account for 30% of mortality; however, mechanisms governing adaptation to the brain microenvironment remain poorly defined. We combine time-course RNA-sequencing of BCBM development with a Drosophila melanogaster genetic screen, and identify Rab11b as a functional mediator of metastatic adaptation. Proteomic analysis reveals that Rab11b controls the cell surface proteome, recycling proteins required for successful interaction with the microenvironment, including integrin ß1. Rab11b-mediated control of integrin ß1 surface expression allows efficient engagement with the brain ECM, activating mechanotransduction signaling to promote survival. Lipophilic statins prevent membrane association and activity of Rab11b, and we provide proof-of principle that these drugs prevent breast cancer adaptation to the brain microenvironment. Our results identify Rab11b-mediated recycling of integrin ß1 as regulating BCBM, and suggest that the recycleome, recycling-based control of the cell surface proteome, is a previously unknown driver of metastatic adaptation and outgrowth.

SNV identification from single-cell RNA sequencing data.

Integrating single-cell RNA sequencing (scRNA-seq) data with genotypes obtained from DNA sequencing studies facilitates the detection of functional genetic variants underlying cell type-specific gene expression variation. Unfortunately, most existing scRNA-seq studies do not come with DNA sequencing data; thus, being able to call single nucleotide variants (SNVs) from scRNA-seq data alone can provide crucial and complementary information, detection of functional SNVs, maximizing the potential of existing scRNA-seq studies. Here, we perform extensive analyses to evaluate the utility of two SNV calling pipelines (GATK and Monovar), originally designed for SNV calling in either bulk or single-cell DNA sequencing data. In both pipelines, we examined various parameter settings to determine the accuracy of the final SNV call set and provide practical recommendations for applied analysts. We found that combining all reads from the single cells and following GATK Best Practices resulted in the highest number of SNVs identified with a high concordance. In individual single cells, Monovar resulted in better quality SNVs even though none of the pipelines analyzed is capable of calling a reasonable number of SNVs with high accuracy. In addition, we found that SNV calling quality varies across different functional genomic regions. Our results open doors for novel ways to leverage the use of scRNA-seq for the future investigation of SNV function.

Death effector domain-containing protein induces vulnerability to cell cycle inhibition in triple-negative breast cancer.

Lacking targetable molecular drivers, triple-negative breast cancer (TNBC) is the most clinically challenging subtype of breast cancer. In this study, we reveal that Death Effector Domain-containing DNA-binding protein (DEDD), which is overexpressed in > 60% of TNBCs, drives a mitogen-independent G1/S cell cycle transition through cytoplasm localization. The gain of cytosolic DEDD enhances cyclin D1 expression by interacting with heat shock 71 kDa protein 8 (HSC70). Concurrently, DEDD interacts with Rb family proteins and promotes their proteasome-mediated degradation. DEDD overexpression renders TNBCs vulnerable to cell cycle inhibition. Patients with TNBC have been excluded from CDK 4/6 inhibitor clinical trials due to the perceived high frequency of Rb-loss in TNBCs. Interestingly, our study demonstrated that, irrespective of Rb status, TNBCs with DEDD overexpression exhibit a DEDD-dependent vulnerability to combinatorial treatment with CDK4/6 inhibitor and EGFR inhibitor in vitro and in vivo. Thus, our study provided a rationale for the clinical application of CDK4/6 inhibitor combinatorial regimens for patients with TNBC.

GAD1 Upregulation Programs Aggressive Features of Cancer Cell Metabolism in the Brain Metastatic Microenvironment.

The impact of altered amino acid metabolism on cancer progression is not fully understood. We hypothesized that a metabolic transcriptome shift during metastatic evolution is crucial for brain metastasis. Here, we report a powerful impact in this setting caused by epigenetic upregulation of glutamate decarboxylase 1 (GAD1), a regulator of the GABA neurotransmitter metabolic pathway. In cell-based culture and brain metastasis models, we found that downregulation of the DNA methyltransferase DNMT1 induced by the brain microenvironment-derived clusterin resulted in decreased GAD1 promoter methylation and subsequent upregulation of GAD1 expression in brain metastatic tumor cells. In a system to dynamically visualize cellular metabolic responses mediated by GAD1, we monitored the cytosolic NADH:NAD+ equilibrium in tumor cells. Reducing GAD1 in metastatic cells by primary glia cell coculture abolished the capacity of metastatic cells to utilize extracellular glutamine, leading to cytosolic accumulation of NADH and increased oxidative status. Similarly, genetic or pharmacologic disruption of the GABA metabolic pathway decreased the incidence of brain metastasis in vivo Taken together, our results show how epigenetic changes in GAD1 expression alter local glutamate metabolism in the brain metastatic microenvironment, contributing to a metabolic adaption that facilitates metastasis outgrowth in that setting. Cancer Res; 77(11); 2844-56. ©2017 AACR.

Tumor-induced Stromal STAT1 Accelerates Breast Cancer via Deregulating Tissue Homeostasis.

The tumor microenvironment (TME), the dynamic tissue space in which the tumor exists, plays a significant role in tumor initiation, and is a key contributor in cancer progression; however, little is known about tumor-induced changes in the adjacent tissue stroma. Herein, tumor-induced changes in the TME were explored at the morphologic and molecular level to further understand cancer progression. Tumor-adjacent mammary glands (TAG) displayed altered branching morphology, expansion of myofibroblasts, and increased mammosphere formation, broadly suggesting a tumor-induced field effect. FACS analysis of TAGs demonstrated an increased number of Lin-CD24+/CD49+ enriched mammary gland stem cells (MaSC), suggesting deregulated tissue homeostasis in TAGs. Comparative transcriptome analysis of TAGs and contralateral control glands coupled with meta-analysis on differentially expressed genes with two breast cancer stromal patient microarray datasets identified shared upregulation of STAT1. Knockdown of STAT1 in cancer-associated fibroblast (CAF) cocultured with human breast cancer cells altered cancer cell proliferation, indicating a role for STAT1 as a stromal contributor of tumorigenesis. Furthermore, depletion of STAT1 in CAFs significantly reduced periductal reactive fibrosis and delayed early breast cancer progression in vivo Finally, cotreatment with fludarabine, a FDA-approved STAT1 activation inhibitor and DNA synthesis inhibitor, in combination with doxorubicin, showed enhanced therapeutic efficacy in treating mouse mammary gland tumors. Taken together, these results demonstrate that stromal STAT1 expression promotes tumor progression and is a potential therapeutic target for breast cancer.Implications: Tumors induce stromal STAT1-dependent cytokine secretion that promotes tumor cell proliferation and can be targeted using clinically-approved inhibitors of STAT1. Mol Cancer Res; 15(5); 585-97. ©2017 AACR.