Gao, Huanyao

Abstract Background: HER2-positive (HER2+) breast cancer accounts for 20–30% of all breast cancers. Although trastuzumab has significantly improved the survival of patients with HER2+ breast cancer, more than 70% of patients develop drug resistance within one year of treatment. Understanding the molecular mechanisms of trastuzumab resistance and identifying biomarkers that predict early trastuzumab resistance would greatly benefit patients receiving trastuzumab therapy. Methods: Differential-gene-expression analysis of trastuzumab-sensitive and resistant HER2+ breast cancer cell lines from GSE15043 was performed to identify the biomarkers associated with trastuzumab resistance. Differential biomarker expression was confirmed in FFPE tissues collected from clinical HER2+ breast cancer tumor samples that were sensitive or resistant to trastuzumab treatment. The function of the biomarkers associated with trastuzumab resistance was studied using western blotting, immunofluorescence, electron microscopy, and siRNA knockdown and overexpression to elucidate the role and mechanisms of the biomarker in affecting the trastuzumab response. Results: UGT1A7, a member of the uronic acid transferase family, was associated with trastuzumab resistance. UGT1A7 expression was downregulated in trastuzumab-resistant tumor tissues and in a cell line that developed trastuzumab resistance (BT474TR). Overexpressing UGT1A7 in BT474TR restored their sensitivity to trastuzumab treatment, whereas downregulating UGT1A7 expression in parental cells led to trastuzumab resistance. Importantly, UGT1A7 localized to the endoplasmic reticulum and altered stress responses. Furthermore, downregulating UGT1A7 expression promoted epithelial-to-mesenchymal transition (EMT) by affecting TWIST, SNAIL, and GRP78 expression and the AMP-activated protein kinase signaling pathway, thus contributing to trastuzumab resistance. Conclusions: This study demonstrated the important role and novel mechanisms of UGT1A7 in tumor responses to trastuzumab. Low UGT1A7 expression plays an important role in EMT and contributes to trastuzumab resistance. UGT1A7 has the potential to be developed as a biomarker for identifying patients who are resistant to trastuzumab treatment.

AbstractBackgroundAlzheimer’s Disease (AD) has no cure. We showed that partial inhibition of mitochondrial complex I (MCI) with small molecule CP2 induced adaptive stress response activating multiple neuroprotective mechanisms. Chronic treatment reduced inflammation, improved synaptic and mitochondrial functions, and blocked neurodegeneration in symptomatic APP/PS1 mice, a translational model of AD.MethodsAnalysis of mitochondrial morphology and mitochondria‐endoplasmic reticulum (ER) contacts (MERCS) was done in the hippocampal CA1 tissue from APP/PS1 mice treated with CP2 and compared to APP/PS1 and non‐transgenic mice treated with vehicle using serial block‐face scanning electron microscopy (SBFSEM) and three‐dimensional (3D) EM reconstructions combined with western blot analysis and next generation RNA sequencing.ResultsWe demonstrate that CP2 treatment restores mitochondrial morphology and mitochondria‐ ER communication, reducing ER stress in the APP/PS1 mouse brain. Using 3D EM reconstructions, we found that mitochondria in AD dendrites existed primarily as mitochondria‐on‐a‐string (MOAS), a morphological phenotype that is difficult to detect using conventional 2D EM or fluorescence spectroscopy. Compared to other morphological phenotypes, MOAS are extensively enveloped in the ER membranes forming multiple MERCS known to contribute to abnormal lipid and calcium homeostasis, and ER stress in AD. CP2 treatment specifically reduced MOAS formation, consistent with improved energy homeostasis in the brain, with concomitant reduction in MERCS, ER stress, and improved lipid homeostasis.ConclusionsThese data provide novel information on the role MOAS play in AD. Our data demonstrate that in response to energetic stress, mitochondria in dendrites acquire MOAS phenotype with increased interaction with the ER, which may synergistically contribute to the AD development. Since CP2 treatment alleviated the ER stress and improved mitochondrial dynamics and function, these data further support the development of partial MCI inhibitors as disease modifying strategy for AD.

BACKGROUND: Dilated cardiomyopathy (DCM) is a major cause of heart failure and carries a high mortality rate. Myocardial recovery in DCM-related heart failure patients is highly variable, with some patients having little or no response to standard drug therapy. A genome-wide association study may agnostically identify biomarkers and provide novel insight into the biology of myocardial recovery in DCM. METHODS: A genome-wide association study for change in left ventricular ejection fraction was performed in 686 White subjects with recent-onset DCM who received standard pharmacotherapy. Genome-wide association study signals were subsequently functionally validated and studied in relevant cellular models to understand molecular mechanisms that may have contributed to the change in left ventricular ejection fraction. RESULTS: The genome-wide association study identified a highly suggestive locus that mapped to the 5′-flanking region of the CDCP1 (CUB [complement C1r/C1s, Uegf, and Bmp1] domain containing protein 1) gene (rs6773435; P =7.12×10 −7 ). The variant allele was associated with improved cardiac function and decreased CDCP1 transcription. CDCP1 expression was significantly upregulated in human cardiac fibroblasts (HCFs) in response to the PDGF (platelet-derived growth factor) signaling, and knockdown of CDCP1 significantly repressed HCF proliferation and decreased AKT (protein kinase B) phosphorylation. Transcriptomic profiling after CDCP1 knockdown in HCFs supported the conclusion that CDCP1 regulates HCF proliferation and mitosis. In addition, CDCP1 knockdown in HCFs resulted in significantly decreased expression of soluble ST2 (suppression of tumorigenicity-2), a prognostic biomarker for heart failure and inductor of cardiac fibrosis. CONCLUSIONS: CDCP1 may play an important role in myocardial recovery in recent-onset DCM and mediates its effect primarily by attenuating cardiac fibrosis.

Alzheimer’s disease (AD) has no cure. Earlier, we showed that partial inhibition of mitochondrial complex I (MCI) with the small molecule CP2 induces an adaptive stress response, activating multiple neuroprotective mechanisms. Chronic treatment reduced inflammation, Aβ and pTau accumulation, improved synaptic and mitochondrial functions, and blocked neurodegeneration in symptomatic APP/PS1 mice, a translational model of AD. Here, using serial block-face scanning electron microscopy (SBFSEM) and three-dimensional (3D) EM reconstructions combined with Western blot analysis and next-generation RNA sequencing, we demonstrate that CP2 treatment also restores mitochondrial morphology and mitochondria-endoplasmic reticulum (ER) communication, reducing ER and unfolded protein response (UPR) stress in the APP/PS1 mouse brain. Using 3D EM volume reconstructions, we show that in the hippocampus of APP/PS1 mice, dendritic mitochondria primarily exist as mitochondria-on-a-string (MOAS). Compared to other morphological phenotypes, MOAS have extensive interaction with the ER membranes, forming multiple mitochondria-ER contact sites (MERCS) known to facilitate abnormal lipid and calcium homeostasis, accumulation of Aβ and pTau, abnormal mitochondrial dynamics, and apoptosis. CP2 treatment reduced MOAS formation, consistent with improved energy homeostasis in the brain, with concomitant reductions in MERCS, ER/UPR stress, and improved lipid homeostasis. These data provide novel information on the MOAS-ER interaction in AD and additional support for the further development of partial MCI inhibitors as a disease-modifying strategy for AD.

Abstract Background: Cancer is usually treated with a combination of drugs rather than a single agent. Treating cancer with a drug combination decreases the likelihood of the cancer acquiring resistance to therapy. It also allows for lower dosages of individual drugs, which reduces the occurrence and severity of side effects. Using public datasets, we investigated potential anti-cancer drug combinations using a novel framework, ReCorDE (Recurrent Correlation of Drugs with Enrichment), which identifies correlated drug response patterns for drugs with different primary mechanisms of action. Methods: 250 drugs from CTRPv2, GDSCv2, and PRISM datasets were examined using normalized logIC50 or AUC measurements. ReCorDE consists of a correlation and an enrichment step. For each dataset, we constructed pairwise drug-drug relationships using Spearman’s correlation. Combinations significant (p < 0.05) in less than two datasets after Benjamini-Hochberg (BH) correction were pruned. To turn each drug combination into a drug class combination, all drugs were mapped to their corresponding fourth-level Anatomical Therapeutic Chemical (ATC) codes. Then, using a hypergeometric test, for each class combination in the subset of significant drug combinations (the “inside” set), we tested for enrichment of that class combination in the inside set compared to the class combination universe, the distribution of class combinations for all unique pairwise drug-drug associations (250 unique drugs; 31,125 distinct drug combinations mapped to 1596 distinct class combinations). Multiple testing during enrichment was corrected using the BH method with a significance cutoff of p< 0.05. Results: We found 2764 pairs to be significant at a = 0.05 using the AUC measure. With a correlation coefficient of 0.77, vincristine and YK-4-279, an EWS-FLI1/RNA Helicase A inhibitor, had the lowest computed p-value of of 1.39 × 10−120 Adjusted p-values for >15% of these combinations had p-values < 5 × 10−6. Class combination enrichment on the same set showed 132 class pairs were enriched in the inside set compared to the class combination universe after BH correction. Taxanes/Plk1 inhibitors (OR = 69.5, adjusted p = 5.6 × 10−11); Aurora Kinase inhibitors/histone modifying agents (OR=9.2, adjusted p = 6.13 × 10−11); and pyrimidine analogues/CDK inhibitors (OR=3.43, adjusted p = 0.02) are a few notable enriched class combinations. The enrichment of these class combinations in the inside set suggests that combinations of drugs from these classes may be particularly effective in treating cancer compared to other drug combinations. Conclusions: Our framework, ReCorDE, demonstrates that finding potential drug combinations and characterizing novel, frequently perturbed pathways outside of a drug's primary mechanisms of action can be accomplished by identifying correlated drug-drug pairs from large, publicly accessible databases. Citation Format: Emily T. Ghose, August John, Huanyao Gao, Krishna R. Kalari, Liewei Wang. ReCorDE: A novel computational framework to discover potential combinations of anti-cancer drugs. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4290.

Abstract Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying molecular mechanisms is needed to identify effective targets to overcome resistance. Given the complexity of the transcriptional dynamics in cells, differential gene expression analysis of bulk transcriptomics data cannot provide sufficient detailed insights into resistance mechanisms. Incorporating network structures could overcome this limitation to provide a global and functional perspective of Abi resistance in mCRPC. Here, we developed TraRe, a computational method using sparse Bayesian models to examine phenotypically driven transcriptional mechanistic differences at three distinct levels: transcriptional networks, specific regulons, and individual transcription factors (TF). TraRe was applied to transcriptomic data from 46 patients with mCRPC with Abi-response clinical data and uncovered abrogated immune response transcriptional modules that showed strong differential regulation in Abi-responsive compared with Abi-resistant patients. These modules were replicated in an independent mCRPC study. Furthermore, key rewiring predictions and their associated TFs were experimentally validated in two prostate cancer cell lines with different Abi-resistance features. Among them, ELK3, MXD1, and MYB played a differential role in cell survival in Abi-sensitive and Abi-resistant cells. Moreover, ELK3 regulated cell migration capacity, which could have a direct impact on mCRPC. Collectively, these findings shed light on the underlying transcriptional mechanisms driving Abi response, demonstrating that TraRe is a promising tool for generating novel hypotheses based on identified transcriptional network disruptions. Significance: The computational method TraRe built on Bayesian machine learning models for investigating transcriptional network structures shows that disruption of ELK3, MXD1, and MYB signaling cascades impacts abiraterone resistance in prostate cancer.

Abstract Androgen receptor (AR) is expressed in 80% to 90% of estrogen receptor α–positive (ER+) breast cancers. Accumulated evidence has shown that AR is a tumor suppressor and that its expression is associated with improved prognosis in ER+ breast cancer. However, both a selective AR agonist (RAD140) and an AR inhibitor (enzalutamide, ENZ) have shown a therapeutic effect on ER+ breast cancer, so the potential for clinical application of AR-targeting therapy for ER+ breast cancer is still in dispute. In this study, we evaluated the efficacy of ENZ and RAD140 in vivo and in vitro in AR+/ER+ breast cancer models, characterizing the relationship of AR and ER levels to response to AR-targeting drugs and investigating the alterations of global gene expression and chromatin binding of AR and ERα after ENZ treatment. In the AR-low setting, ENZ directly functioned as an ERα antagonist. Cell growth inhibition by ENZ in breast cancer with low AR expression was independent of AR and instead dependent on ER. In AR-high breast cancer models, AR repressed ERα signaling and ENZ promoted ERα signaling by antagonizing AR. In contrast, RAD140 activated AR signaling and suppressed AR-high tumor growth by deregulating ERα expression and blocking ERα function. Overall, analysis of the dynamic efficacies and outcomes of AR agonist, and antagonist in the presence of different AR and ERα levels reveals regulators of response and supports the clinical investigation of ENZ in selected ER+ tumors with a low AR/ER ratio and AR agonists in tumors with a high AR/ER ratio. Significance: The ratio of androgen receptor to estrogen receptor in breast cancer dictates the response to AR-targeted therapies, providing guidelines for developing AR-directed treatment strategies for patients with breast cancer.

Abstract Understanding the function of non-coding genomic sequence variants represents a challenge for biomedicine. Many diseases are products of gene-by-environment interactions with complex mechanisms. This study addresses these themes by mechanistic characterization of non-coding variants that influence gene expression only after drug or hormone exposure. Using glucocorticoid signaling as a model system, we integrated genomic, transcriptomic, and epigenomic approaches to unravel mechanisms by which variant function could be revealed by hormones or drugs. Specifically, we identified cis-regulatory elements and 3D interactions underlying ligand-dependent associations between variants and gene expression. One-quarter of the glucocorticoid-modulated variants that we identified had already been associated with clinical phenotypes. However, their affected genes were ‘unmasked’ only after glucocorticoid exposure and often with function relevant to the disease phenotypes. These diseases involved glucocorticoids as risk factors or therapeutic agents and included autoimmunity, metabolic and mood disorders, osteoporosis and cancer. For example, we identified a novel breast cancer risk gene, MAST4, with expression that was repressed by glucocorticoids in cells carrying the risk genotype, repression that correlated with MAST4 expression in breast cancer and treatment outcomes. These observations provide a mechanistic framework for understanding non-coding genetic variant-chemical environment interactions and their role in disease risk and drug response.

AbstractAlternative polyadenylation (APA) is a common genetic regulatory mechanism that generates distinct 3′ ends for RNA transcripts. Changes in APA have been associated with multiple biological processes and disease phenotypes. However, the role of hormones and their drug analogs in APA remains largely unknown. In this study, we investigated transcriptome‐wide the impact of glucocorticoids on APA in 30 human B‐lymphoblastoid cell lines. We found that glucocorticoids could regulate APA for a subset of genes, possibly by changing the expression of 142 RNA‐binding proteins, some with known APA‐regulating properties. Interestingly, genes with glucocorticoid‐mediated APA were enriched in viral translation‐related pathways, while genes with glucocorticoid‐mediated expression were enriched in interferon and interleukin pathways, suggesting that glucocorticoid‐mediated APA might result in functional consequences distinct from gene expression. For example, glucocorticoids, a pharmacotherapy for severe COVID‐19, were found to change the APA but not the expression of LY6E, an important antiviral inhibitor in coronavirus diseases. Glucocorticoid‐mediated APA was also cell‐type‐specific, suggesting an action of glucocorticoids that may be unique to immune regulation. We also observed evidence for genotype‐dependent glucocorticoid‐mediated APA (referred to as pharmacogenomic‐alterative polyadenylation quantitative trait loci), providing potential functional mechanisms for a series of common genetic variants that had previously been associated with immune disorders, but without a clear mechanism. In summary, this study reports a series of observations regarding the impact of glucocorticoids on APA, raising the possibility that this mechanism might have implications for both disease pathophysiology and drug therapy.

Approximately one‐third of patients with metastatic castration‐resistant prostate cancer (CRPC) exhibited primary abiraterone resistance. To identify alternative treatment for abiraterone nonresponders, we performed drug discovery analyses using the L1000 database using differentially expressed genes identified in tumor biopsies and patient‐derived xenograft (PDX) tumors between abiraterone responders and nonresponders enrolled in PROMOTE trial. This approach identified 3 drugs, including topoisomerase II (TOP2) inhibitor mitoxantrone, CDK4/6 inhibitor palbociclib, and pan‐CDK inhibitor PHA‐793887. These drugs significantly suppressed the growth of abiraterone‐resistant cell lines and PDX models. Moreover, we identified 11 genes targeted by all 3 drugs that were associated with worse outcomes in both the PROMOTE and Stand Up To Cancer cohorts. This 11‐gene panel might also function as biomarkers to select the 3 alternative therapies for this subgroup of patients with CRPC, warranting further clinical investigation.