Wang, Liewei

Abstract Purpose: TNBC represents an aggressive subtype characterized by earlier relapse and worse survival compared to non-TNBC. Patients with residual TNBC after neoadjuvant chemotherapy (NAC) have a high risk of locoregional recurrence despite aggressive subsequent local therapies, including RT. Thus, new radiosensitizers that address chemoresistant TNBC (i.e residual disease after NAC) are needed. ATR plays a key role in the cellular response to replication stress and DNA damage. TNBC is characterized by G1 checkpoint loss, homologous recombination deficiency (HRD), and other features which increase dependence on ATR pathway signaling. We hypothesized that VX-970, a selective inhibitor of ATR, would effectively radiosensitize TNBC. Methods: Cell lines representing varying subtypes of TNBC (MDA-MB-231, HCC1806, and BT-549) and the normal breast epithelial cell line MCF10a were investigated in clonogenic survival, cell cycle, and DNA damage signaling and repair assays. In addition, Mayo Clinic (MC)TNBC1 and MCTNBC2, patient derived xenograft models (PDXs) generated prospectively from baseline and chemoresistant residual disease surgical specimens after NAC, respectively, of unique patients in the Breast Cancer Genome Guided Therapy Study were analyzed. Tumors were injected into hind-legs of athymic nude mice and animals were randomized to: 1) Vehicle 2) RT 3) VX-970 4) RT + VX-970. RT was delivered in 5 daily fractions of 2 Gy. VX-970 was administered daily 1 hour prior to RT at a dose of 60 mg/kg. Exome sequencing was assessed for germ-line and/or somatic alterations in HR genes and an ex-vivo RAD51 foci formation assay was applied to confirm the functional status of HR in each PDX model. Results: In vitro, VX-970 preferentially inhibited ATR-Chk1-CDC25a signaling, abrogated the RT-induced G2/M checkpoint, delayed resolution of γH2AX and 53BP1 foci and reduced colony formation after RT in MDA-MB-231, HCC1806, and BT-549 relative to MCF10a. In vivo, VX-970 did not exhibit single agent activity at the dose administered but markedly sensitized both MCTNBC1 and MCTNBC2 to RT, suggesting that VX-970 could overcome chemoresistant TNBC biology. For MCTNBC1 and MCTNBC2, the median time to tumor tripling was 26 vs 49 days (p=0.002) and 25 vs 43 days (p=0.006) for the RT and RT + VX-970 groups, respectively. Ex-vivo RAD51 foci formation was robust in MCTNBC1, a PDX without HR gene alterations. In contrast, there was no RT-induced RAD51 foci formation in MCTNBC2, suggesting a BRCA1 mutation in the corresponding human tumor resulted in loss of HR function in that model. Conclusion: VX-970 + RT effectively radiosensitized TNBC PDXs established from both pre-treatment biopsy specimens and chemoresistant residual tumor samples and in both HR deficient and HR proficient settings. ATR inhibition should be investigated in the clinic in combination with RT for patients with residual TNBC after NAC. Citation Format: Robert W. Mutter, Mohamed M. Kahila, Xinyi Tu, Qin Zhou, Jia Yu, Krishna R. Kalari, Liewei Wang, Judy C. Boughey, Matthew P. Goetz, Jann N. Sarkaria, Zhenkun Lou. ATR inhibition is a promising radiosensitizing strategy for chemotherapy-resistant triple negative breast cancer (TNBC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 840.

Abstract Purpose: Although high glucocorticoid receptor (GR) expression in early-stage estrogen receptor (ER)-negative breast cancer is associated with shortened relapse-free survival (RFS), how associated GR transcriptional activity contributes to aggressive breast cancer behavior is not well understood. Using potent GR antagonists and primary tumor gene expression data, we sought to identify a tumor-relevant gene signature based on GR activity that would be more predictive than GR expression alone. Experimental Design: Global gene expression and GR ChIP-sequencing were performed to identify GR-regulated genes inhibited by two chemically distinct GR antagonists, mifepristone and CORT108297. Differentially expressed genes from MDA-MB-231 cells were cross-evaluated with significantly expressed genes in GR-high versus GR-low ER-negative primary breast cancers. The resulting subset of GR-targeted genes was analyzed in two independent ER-negative breast cancer cohorts to derive and then validate the GR activity signature (GRsig). Results: Gene expression pathway analysis of glucocorticoid-regulated genes (inhibited by GR antagonism) revealed cell survival and invasion functions. GR ChIP-seq analysis demonstrated that GR antagonists decreased GR chromatin association for a subset of genes. A GRsig that comprised n = 74 GR activation-associated genes (also reversed by GR antagonists) was derived from an adjuvant chemotherapy-treated Discovery cohort and found to predict probability of relapse in a separate Validation cohort (HR = 1.9; P = 0.012). Conclusions: The GRsig discovered herein identifies high-risk ER-negative/GR-positive breast cancers most likely to relapse despite administration of adjuvant chemotherapy. Because GR antagonism can reverse expression of these genes, we propose that addition of a GR antagonist to chemotherapy may improve outcome for these high-risk patients. Clin Cancer Res; 24(14); 3433–46. ©2018 AACR.

Abstract Motivation RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study, we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data. Results We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16 562 isoform-pairs from 4929 genes. Among those, 26% of the discovered patterns were significant (P<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. Finally, the effects of drop-out events and expression levels of isoforms on ISOP's performances were investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoform-level preference, commitment and heterogeneity in single-cell RNA-sequencing data. Availability and implementation The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license. Supplementary information Supplementary data are available at Bioinformatics online.

Biomedical research is undergoing rapid change, with the development of a series of analytical omics techniques that are capable of generating Biomedical Big Data. These developments provide an unprecedented opportunity to gain novel insight into disease pathophysiology and mechanisms of drug action and response—but they also present significant challenges. Pharmacogenomics is a discipline within Clinical Pharmacology that has been at the forefront in defining, taking advantage of, and dealing with the opportunities and challenges of this aspect of the Post‐Genome Project world. This overview will describe the evolution of germline pharmacogenomic research strategies as we have moved from an era of candidate genes to agnostic genome‐wide association studies (GWAS) coupled with the functional and mechanistic pursuit of GWAS signals. Germline pharmacogenomic studies of breast cancer endocrine therapy will be used to illustrate research strategies that are being applied broadly to omics studies of drug response phenotypes.

The testis‐specific Y‐encoded‐like protein (TSPYL) gene family includes TSPYL1 to TSPYL6. We previously reported that TSPYL5 regulates cytochrome P450 (CYP) 19A1 expression. Here we show that TSPYLs, especially TSPYL 1, 2, and 4, can regulate the expression of many CYP genes, including CYP17A1, a key enzyme in androgen biosynthesis, and CYP3A4, an enzyme that catalyzes the metabolism of abiraterone, a CYP17 inhibitor. Furthermore, a common TSPYL1 single nucleotide polymorphism (SNP), rs3828743 (G/A) (Pro62Ser), abolishes TSPYL1's ability to suppress CYP3A4 expression, resulting in reduced abiraterone concentrations and increased cell proliferation. Data from a prospective clinical trial of 87 metastatic castration‐resistant prostate cancer patients treated with abiraterone acetate/prednisone showed that the variant SNP genotype (A) was significantly associated with worse response and progression‐free survival. In summary, TSPYL genes are novel CYP gene transcription regulators, and genetic alteration within these genes significantly influences response to drug therapy through transcriptional regulation of CYP450 genes.

Abstract Prostate cancer is the most frequently diagnosed male cancer. For prostate cancer that has progressed to an advanced or metastatic stage, androgen deprivation therapy (ADT) is the standard of care. ADT inhibits activity of the androgen receptor (AR), a master regulator transcription factor in normal and cancerous prostate cells. The major limitation of ADT is the development of castration-resistant prostate cancer (CRPC), which is almost invariably due to transcriptional re-activation of the AR. One mechanism of AR transcriptional re-activation is expression of AR-V7, a truncated, constitutively active AR variant (AR-V) arising from alternative AR pre-mRNA splicing. Noteworthy, AR-V7 is being developed as a predictive biomarker of primary resistance to androgen receptor (AR)-targeted therapies in CRPC. Multiple additional AR-V species are expressed in clinical CRPC, but the extent to which these may be co-expressed with AR-V7 or predict resistance is not known. Here we utilized long read sequencing to identify and quantify AR isoforms expressed in CRPC. To unambiguously characterize all AR isoforms, we prepared Iso-Seq™ libraries via 3’ rapid amplification of cDNA ends (RACE) with RNA isolated from prostate cancer cell lines and xenograft tissues using a forward primer anchored in AR exon 1. 3’RACE reactions were subjected to single molecule, real-time (SMRT®) long-read sequencing with a Pacific Biosciences RSII System. Our work identified AR-V9 as a truncated isoform that is frequently co-expressed with AR-V7 in CRPC. Mechanistically, our work re-annotated AR-V7 and AR-V9 mRNAs, showing these two species shared a common 3’ terminal exon containing separate splice acceptor sites. Taking into account this new information, novel siRNAs and antibodies which could distinguish between AR-V7 and AR-V9 were designed, validated and used to measure the relative expression of these two AR isoforms in CRPC cells with a view to determining the potential of AR-V9 as a predictive biomarker of primary resistance to AR-targeted therapies. Citation Format: Manish Kohli, Yeung Ho, David W. Hillman, Jamie L. Van Etten, Christine Henzler, Rendong Yang, Yingming Li, Elizabeth Tseng, Ting Hon, Tyson A. Clark, Liguo Wang, Kevin Silverstein, Liewei Wang, Scott M. Dehm. SMRT® Sequencing of full-length androgen receptor isoforms in prostate cancer reveals previously hidden drug resistant variants [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 425. doi:10.1158/1538-7445.AM2017-425

Abstract Background: Circulating cell-free DNA (cfDNA) analysis is emerging as a less invasive approach to assessing tumor genomic alterations in cancer patients. Although high concordance has been reported between tumor tissue NGS and cfDNA in studies investigating specific genetic alterations, the fidelity of cfDNA to tumor tissue DNA in the global genomic scale is largely unknown. In a correlative study of a prospective clinical trial (NCT# 01953640) conducted in mCRPC stage patients treated with abiraterone acetate/prednisone (A/P), we evaluated correlation of genomic CNA in tumor DNA obtained from biopsy of metastatic lesions and matched plasma cfDNA. Methods: mCRPC patients (pts) underwent two image-guided core biopsies of metastases prior to initiation of A/P (visit 1, V1) and 12 weeks after treatment (visit 2, V2). At both time points plasma was obtained at the time of the core biopsies and cfDNA was extracted using DNA Blood Mini Kit (Qiagen, Valencia, CA). High coverage (for tumor tissue) and low coverage (for cfDNA) whole genome sequencing reads were first mapped to the human genome hg19. Read counts (RC) from the mapped sequence files were then binned into 1Mb windows. The RC ratio in each genomic bin was calculated by comparing tumor tissue DNA to lymphocyte gDNA derived from the same patient, and was further log2 transformed, corrected for GC content, and normalized by CGHnormaliter. The fully normalized log2 ratios data was subjected to segmentation using DNAcopy algorithm. Results: Between 05/2013 and 09/2015, 92 patients (pts) were enrolled of which tissue and plasma NGS data both visits was available for 18 pts. The correlation of CNAs between tumor tissue and its cfDNA counterpart ranges from 0.013 to 0.83 for V1 samples, and -0.05 to 0.9 for V2 samples. The decreased correlation in some pairs of samples is largely due to low tumor content and heterogeneity in the cfDNA. Although there is a wide range of correlation, commonly shared CNAs were identified in multiple chromosomal regions, including loss in 8p, gain in 8q and chromosome 5 and X. On the other hand, several genomic regions show inconsistent CNAs between tumor tissue and cfDNA among 15 pairs of samples in which cfDNA have large tumor content. These include: loss in 6q, 1p, 2p, 9q, 11q, 13p, 15p, 20p and gain in 8q and 10p in cfDNA but not in tumor tissue; marked loss in chromosome 22 and gain in p arm of X chromosome in tumor tissue but much less evident in cfDNA. Conclusion: High concordance of CNAs between cfDNA and tumor tissue DNA can be achieved given sufficient tumor content of cfDNA. However, more CNAs can be identified in cfDNA than its tumor tissue counterpart. Our result suggests that cfDNA NGS is a useful tool to investigate clonal evolution associated with cancer progression. Citation Format: Chiang-Ching Huang, Meijun Du, Liguo Wang, Yen-chen Lin, Hua Huang, Liewei Wang, Liang Wang, Manish Kohli. Comparison of copy number aberrations (CNAs) between plasma cell free DNA (cfDNA) and tissue DNA in metastatic castrate resistant prostate cancer (mCRPC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2733. doi:10.1158/1538-7445.AM2017-2733