To discover novel therapeutic targets for triple-negative breast cancer (TNBC) and cancer stem cells (CSCs), we screened long non-coding RNAs (lncRNAs) most enriched in TNBCs for high expression in CSCs defined by high Aldefluor activity and associated with worse patient outcomes. This led to the identification of non-coding RNA in the aldehyde dehydrogenase 1 A pathway (NRAD1), also known as LINC00284. Targeting NRAD1 in TNBC tumors using antisense oligonucleotides reduced cell survival, tumor growth, and the number of cells with CSC characteristics. Expression of NRAD1 is regulated by an enzyme that causes Aldefluor activity in CSCs, aldehyde dehydrogenase 1A3 (ALDH1A3) and its product retinoic acid. Cellular fractionation revealed that NRAD1 is primarily nuclear localized, which suggested a potential function in gene regulation. This was confirmed by transcriptome profiling and chromatin isolation by RNA purification, followed by sequencing (ChIRP-seq), which demonstrated that NRAD1 has enriched chromatin interactions among the genes it regulates. Gene Ontology enrichment analysis revealed that NRAD1 regulates expression of genes involved in differentiation and catabolic processes. NRAD1 also contributes to gene expression changes induced by ALDH1A3; thereby, the induction of NRAD1 is a novel mechanism through which ALDH1A3 regulates gene expression. Together, these data identify lncRNA NRAD1 as a downstream effector of ALDH1A3, and a target for TNBCs and CSCs, with functions in cell survival and regulation of gene expression.

Acute promyelocytic leukemia (APL) is characterized by arrested differentiation of promyelocytes. Patients treated with all-trans retinoic acid (ATRA) alone experience relapse, while patients treated with ATRA and arsenic trioxide (ATO) are often relapse-free. This suggests sustained changes have been elicited by the combination therapy. To understand the lasting effects of the combination therapy, we compared the effects of ATRA and ATO on NB4 and ATRA-resistant NB4-MR2 APL cells during treatment versus post treatment termination. After treatment termination, NB4 cells treated with ATRA or ATO reverted to non-differentiated cells, while combination-treated cells remained terminally differentiated. This effect was diminished in NB4-MR2 cells. This suggests combination treatment induced more permanent changes. Combination treatment induced higher expression of target genes (e.g., transglutaminase 2 and retinoic acid receptor beta), which in NB4 cells was sustained post treatment termination. To determine whether sustained epigenetic changes were responsible, we quantified the enrichment of histone modifications by chromatin immunoprecipitation, and CpG methylation by bisulfite-pyrosequencing. While ATRA and combination treatment induced similar histone acetylation enrichment, combination treatment induced greater demethylation of target genes, which was sustained. Therefore, sustained demethylation of target genes by ATRA and ATO combination treatment is associated with lasting differentiation and gene expression changes.

Avoiding detection and destruction by immune cells is key for tumor initiation and progression. The important role of cancer stem cells (CSCs) in tumor initiation has been well established, yet their ability to evade immune detection and targeting is only partly understood. To investigate the ability of breast CSCs to evade immune detection, we identified a highly tumorigenic population in a spontaneous murine mammary tumor based on increased aldehyde dehydrogenase activity. We performed tumor growth studies in immunocompetent and immunocompromised mice. In immunocompetent mice, growth of the spontaneous mammary tumor was restricted; however, the Aldefluor population was expanded, suggesting inherent resistance mechanisms. Gene expression analysis of the sorted tumor cells revealed that the Aldefluor tumor cells has decreased expression of transporter associated with antigen processing (TAP) genes and co-stimulatory molecule CD80, which would decrease susceptibility to T cells. Similarly, the Aldefluor population of patient tumors and 4T1 murine mammary cells had decreased expression of TAP and co-stimulatory molecule genes. In contrast, breast CSCs identified by CD44 CD24 do not have decreased expression of these genes, but do have increased expression of C-X-C chemokine receptor type 4. Decitabine treatment and bisulfite pyrosequencing suggests that DNA hypermethylation contributes to decreased TAP gene expression in Aldefluor CSCs. TAP1 knockdown resulted in increased tumor growth of 4T1 cells in immunocompetent mice. Together, this suggests immune evasion mechanisms in breast CSCs are marker specific and epigenetic silencing of TAP1 in Aldefluor breast CSCs contributes to their enhanced survival under immune pressure. Stem Cells 2018;36:641-654.

Paclitaxel is a common breast cancer drug; however, some tumors are resistant. The identification of biomarkers for paclitaxel resistance or sensitivity would enable the development of strategies to improve treatment efficacy. A genome-wide in vivo shRNA screen was performed on paclitaxel-treated mice with MDA-MB-231 tumors to identify genes associated with paclitaxel sensitivity or resistance. Gene expression of the top screen hits was associated with tumor response (resistance or sensitivity) among patients who received neoadjuvant chemotherapy containing paclitaxel. We focused our validation on screen hit B-cell lymphoma 6 (BCL6), which is a therapeutic target in cancer but for which no effects on drug response have been reported. Knockdown of BCL6 resulted in increased tumor regression in mice treated with paclitaxel. Similarly, inhibiting BCL6 using a small molecule inhibitor enhanced paclitaxel treatment efficacy both in vitro and in vivo in breast cancer models. Mechanism studies revealed that reduced BCL6 enhances the efficacy of paclitaxel by inducing sustained G1/S arrest, concurrent with increased apoptosis and expression of target gene cyclindependent kinase inhibitor 1A. In summary, the genome-wide shRNA knockdown screen has identified BCL6 as a potential targetable resistance biomarker of paclitaxel response in breast cancer.

Treatment decisions for breast cancer are based upon stage, tumor grade and hormone receptor status, and can include surgical resection, hormone receptor antagonists, radiation, and chemotherapy (e.g. paclitaxel). Breast cancer treatment success depends upon avoidance of chemotherapy resistance (i.e. achieving complete response) and prevention of both over- and under-treatment. Increased understanding of the genes which cause resistance and sensitivity to currently used drugs would lead to development of more effective therapeutic strategies that are specifically tailored to patient groups based on molecular profiling of their tumors (i.e. personalized medicine). Being able to identify the genes which when expressed in a tumor predict sensitivity or resistance to treatment prior to administration of paclitaxel would improve treatment efficacy and patient survival. We performed an in vivo shRNA genome-wide screen with MDA-MB-231 tumors treated with paclitaxel for the purpose of identifying genes which determine breast cancer response to paclitaxel. Completion of 6 replicates of the in vivo screen identified 26 putative paclitaxel sensitivity genes and 14 putative paclitaxel resistance genes (e.g. BCL6) for breast cancer. Screen-identified putative paclitaxel resistance were verified by individual knockdown clone generation and comparison of their sensitivity to paclitaxel-induced decreased cell proliferation, cell-cycle arrest, and apoptosis to a shRNA scramble control clone. Upon individual knockdown of the putative resistance genes (e.g. BCL6), MDA-MB-231 cells were more sensitive to paclitaxel and demonstrated increased apoptosis and decreased paclitaxel IC50 concentrations. Finally, expression of a preliminary gene signature generated from the screen-identified hits was tested for its ability to predict response to paclitaxel in two archived patient data sets. The preliminary gene signature predicted response to paclitaxel in the datasets with an accuracy ranging from 70 to 100%. Further confirmation experiments of the remaining potential resistance and sensitivity genes will help to generate a more robust genetic profile which can be used to identify candidate breast cancer patients who would most benefit from paclitaxel treatment as opposed to treatment with other drugs. Citation Format: Mohammad Sultan, Thomas Tan Huynh, Margaret Lois Thomas, Krysta Mila Coyle, Carman A. Giacomantonio, Paola Marcato. Identification of genes that predict response to paclitaxel in breast cancer using an in vivo genome-wide knockdown screen. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr B26.