Preclinical-to-clinical Anti-cancer Drug Response Prediction and Biomarker Identification Using TINDL

Prediction of the response of cancer patients to different treatments and identification of biomarkers of drug response are two major goals of individualized medicine. Here, we developed a deep learning framework called TINDL, completely trained on preclinical cancer cell lines (CCLs), to predict the response of cancer patients to different treatments. TINDL utilizes a tissue-informed normalization to account for the tissue type and cancer type of the tumors and to reduce the statistical discrepancies between CCLs and patient tumors. Moreover, by making the deep learning black box interpretable, this model identifies a small set of genes whose expression levels are predictive of drug response in the trained model, enabling identification of biomarkers of drug response. Using data from two large databases of CCLs and cancer tumors, we showed that this model can distinguish between sensitive and resistant tumors for 10 (out of 14) drugs, outperforming various other machine learning models. In addition, our small interfering RNA (siRNA) knockdown experiments on 10 genes identified by this model for one of the drugs (tamoxifen) confirmed that tamoxifen sensitivity is substantially influenced by all of these genes in MCF7 cells, and seven of these genes in T47D cells. Furthermore, genes implicated for multiple drugs pointed to shared mechanism of action among drugs and suggested several important signaling pathways. In summary, this study provides a powerful deep learning framework for prediction of drug response and identification of biomarkers of drug response in cancer. The code can be accessed at https://github.com/ddhostallero/tindl.

Association of whole blood mRNA expression and overall survival (OS) in metastatic castrate resistant prostate cancer (mCRPC)

201

Background: Previous studies have evaluated peripheral whole blood mRNA to identify prognostic biomarkers in metastatic prostate cancer, with no consistent genes of prognostic significance between studies and sample collection done at various points of therapy. We aim to identify the prognostic value of 20 previously identified genes in patients mCRPC from a prospective clinical trial. Methods: Between June 2013 and August 2015, whole blood was prospectively collected in PAXgene RNA tubes from 92 men with mCRPC (NCT01953640). Gene expression from samples with RIN > 4.0 were quantified using a customized NanoString CodeSet of 20 candidate genes (C1QA, MCM2, STOM, GABARAPL2, R10K3, HMBS, TFDP1, CDKN1A, ITGAL, TMCC2, TERF2IP, MMP9, SNCA, TIMP1, SLC4A1, SELENBP1, TMEM66, SEMA4D, PROS1, CD22). The raw data from the nCounter Analysis system were normalized to the positive controls and log2 transformed. Univariable Cox proportional hazards models were performed on each target gene sufficiently above negative control (5 times the maximum value of the negative control) to evaluate associations with overall survival (OS). For each gene we considered a linear, quadratic, or categorical model with quantile cutpoints. Categorical models with cutpoints at the 25th percentile for the genes CD22, GABARAPL2, R10K3, and STOM were used as there was a nonlinear relationship between gene expression and death hazard. The remaining genes were modeled with a linear model. Findings were considered statistically significant based on p-values adjusted using the Holm-Bonferroni correction. Results: 18/20 genes were identified and passed quality control (QC) measures, which excluded C1QA and MCM2. 72/92 men had an evaluable pretreatment specimen that passed QC. The median age was 72 years. The study cohort was evenly balanced in terms of Gleason score ( < = 7 v. > 7) and 60% had high volume disease. The median follow-up time was 5.73 years (IQR: 5.39, 6.49) and 58 patients had died. Of the 18 genes evaluated, STOM (Stomatin) [hazard ratio (HR) 3.00, adjusted p = 0.007] and GABARAPL2 (GABA Type A Receptor Associated Protein Like 2) [HR 2.62, adjusted p = 0.033] were significantly associated with overall survival in univariate analysis. In multivariate analysis, after adjusting for volume of metastatic disease and Gleason score, STOM [HR 2.89, adjusted p = 0.014] was significantly associated with overall survival. Conclusions: Elevated whole blood mRNA expression of STOM is adversely associated with OS in mCRPC. Further studies investigating elucidating the molecular significance of STOM in mCRPC are planned. Clinical trial information: NCT01953640 .

Testis- specific Y-encoded- like protein 1 and cholesterol metabolism: Regulation of CYP1B1 expression through Wnt signaling

The cytochromes P450 (CYPs) represent a large gene superfamily that plays an important role in the metabolism of both exogenous and endogenous compounds. We have reported that the testis-specific Y-encoded-like proteins (TSPYLs) are novel CYP gene transcriptional regulators. However, little is known of mechanism(s) by which TSPYLs regulate CYP expression or the functional consequences of that regulation. The TSPYL gene family includes six members, TSPYL1 to TSPYL6. However, TSPYL3 is a pseudogene, TSPYL5 is only known to regulates the expression of CYP19A1, and TSPYL6 is expressed exclusively in the testis. Therefore, TSPYL 1, 2 and 4 were included in the present study. To better understand how TSPYL1, 2, and 4 might influence CYP expression, we performed a series of pull-downs and mass spectrometric analyses. Panther pathway analysis of the 2272 pulled down proteins for all 3 TSPYL isoforms showed that the top five pathways were the Wnt signaling pathway, the Integrin signaling pathway, the Gonadotropin releasing hormone receptor pathway, the Angiogenesis pathway and Inflammation mediated by chemokines and cytokines. Specifically, we observed that 177 Wnt signaling pathway proteins were pulled down with the TSPYLs. Subsequent luciferase assays showed that TSPYL1 knockdown had a greater effect on the activation of Wnt signaling than did TSPYL2 or TSPYL4 knockdown. Therefore, in subsequent experiments, we focused our attention on TSPYL1. HepaRG cell qRT-PCR showed that TSPYL1 regulated the expression of CYPs involved in cholesterol-metabolism such as CYP1B1 and CYP7A1. Furthermore, TSPYL1 and β-catenin regulated CYP1B1 expression in opposite directions and TSPYL1 appeared to regulate CYP1B1 expression by blocking β-catenin binding to the TCF7L2 transcription factor on the CYP1B1 promoter. In β-catenin and TSPYL1 double knockdown cells, CYP1B1 expression and the generation of CYP1B1 downstream metabolites such as 20-HETE could be restored. Finally, we observed that TSPYL1 expression was associated with plasma cholesterol levels and BMI during previous clinical studies of obesity. In conclusion, this series of experiments has revealed a novel mechanism for regulation of the expression of cholesterol-metabolizing CYPs, particularly CYP1B1, by TSPYL1 via Wnt/β-catenin signaling, raising the possibility that TSPYL1 might represent a molecular target for influencing cholesterol homeostasis.

Association of malnutrition with in-hospital and long-term outcomes among ST-elevation myocardial infarction patients receiving primary PCI

Background

The impact of malnutrition on outcomes in a contemporary ST-segment-elevation myocardial infarction (STEMI) population is unclear. We hypothesized that malnutrition severity amongst STEMI patients undergoing primary percutaneous coronary intervention (pPCI) is associated with worse long-term outcomes.

Purpose

The aim of this study was 2-fold: 1) to establish the prevalence of malnutrition among STEMI patients undergoing pPCI; 2) to determine the association of malnutrition severity on in-hospital and 1-year outcomes in STEMI patients receiving pPCI

Methods

We retrospectively identified 1,169 STEMI patients of age ≥65 years who had received pPCI (2013–2020). Patients who had presented with out-of-hospital cardiac arrest or those who received fibrinolytic therapy were excluded. The Controlling Nutritional Status (CONUT) score, based on serum albumin, total cholesterol and lymphocyte count, was used as a tool to assess the nutritional status of included patients. Malnourished patients were defined as those with a CONUT score of 5 to 12. To account for the impact of frailty, a frailty index (FI) was determined using the health deficit accumulation model (Table 1). The primary outcome was 1-year all-cause mortality. The secondary outcome was a composite of in-hospital heart failure, cardiogenic shock, re-infarction, major bleeding, stroke, and all-cause mortality. A multivariable model adjusting for baseline covariates, including frailty index score, was performed (Figure 1).

Results

Among 1,169 STEMI patients receiving pPCI, 315 (26.9%) were classified as malnourished. Malnourished patients were older (mean 77.4 vs. 76.0 years, p=0.009) and had a higher comorbidity burden. After multivariable adjustment, worsening malnutrition was associated with increased 1-year all-cause mortality (odds ratio [OR] = 1.29, p&lt;0.001). Worsening malnutrition was also associated with a higher incidence of the in-hospital composite adverse outcome (OR = 1.12, p=0.003) and increased in-hospital all-cause mortality (OR=1.41, p&lt;0.001).

Conclusion

Among STEMI patients receiving pPCI, 1 in 4 were malnourished. Malnutrition was associated with increased rate of in-hospital composite adverse outcome and worse long-term outcomes, even when accounting for frailty. Efforts to routinely identify malnourished STEMI patients and to implement best practices to reduce the risk of adverse events in this vulnerable population are warranted.

Funding Acknowledgement

Type of funding sources: None.

Anastrozole Regulates Fatty Acid Synthase in Breast Cancer

Our previous matched case-control study of postmenopausal women with resected early-stage breast cancer revealed that only anastrozole, but not exemestane or letrozole, showed a significant association between the 6-month estrogen concentrations and risk of breast cancer. Anastrozole, but not exemestane or letrozole, is a ligand for estrogen receptor α. The mechanisms of endocrine resistance are heterogenous and with the new mechanism of anastrozole, we have found that treatment of anastrozole maintains fatty acid synthase (FASN) protein level by limiting the ubiquitin-mediated FASN degradation, leading to increased breast cancer cell growth. Mechanistically, anastrozole decreases the guided entry of tail-anchored proteins factor 4 (GET4) expression, resulting in decreased BCL2-associated athanogene cochaperone 6 (BAG6) complex activity, which in turn, prevents RNF126-mediated degradation of FASN. Increased FASN protein level can induce a negative feedback loop mediated by the MAPK pathway. High levels of FASN are associated with poor outcome only in patients with anastrozole-treated breast cancer, but not in patients treated with exemestane or letrozole. Repressing FASN causes regression of breast cancer cell growth. The anastrozole-FASN signaling pathway is eminently targetable in endocrine-resistant breast cancer.

TOTAL risk score for predicting safe very early discharge in patients with ST-elevation myocardial infarction (STEMI)

Background/Introduction

Previously validated risk scores for identifying low-risk patients after ST-segment elevation myocardial infarction (STEMI) have led to acceptance of the safety and feasibility of discharge after 48–72 hours of hospitalization, reducing hospital length of stay and costs. With ongoing improvements in outcomes, it may be possible to select patients who are safe to discharge very early (24–48 hours) but this has never been evaluated.

Purpose

We sought to develop and validate a novel risk score for identifying low-risk patients suitable for very early discharge (≤48 hours of hospitalization) post-STEMI.

Methods

We derived a novel risk score using data from patients enrolled in the Trial of Routine Aspiration Thrombectomy with PCI versus PCI alone in Patients with STEMI (TOTAL). The TOTAL database was randomly divided into a derivation cohort with 2/3 of the composite events and non-events and remaining 1/3 as the internal validation cohort. Using the derivation cohort, we identified risk factors for cardiovascular death (CV) or non-fatal cardiac arrest by performing a univariate and multivariable stepwise regression analysis of baseline clinical and angiographic characteristics. Each co-variate was assigned an integer score based on regression coefficients and the novel TOTAL risk score was developed by adding points from each risk factor profile. We externally validated the TOTAL score using data from the Radial versus Femoral Access for Coronary Intervention (RIVAL) trial.

Results

The TOTAL derivation cohort included 6331 participants with 287 events (CV death/cardiac arrest). Twelve independent risk-factors associated with risk of CV death and non-fatal cardiac arrest at 1 year were selected and weighted for the TOTAL risk score (Table 1). In the TOTAL validation cohort (n=3166), patients with a TOTAL score of 0–4 points (n=779 (24.6%)) were categorized as very low risk with only a 0.1% risk of CV death/cardiac arrest observed within 24 hours of hospitalization, and no further events observed between 24 hours and 30 days post-STEMI. In the RIVAL validation dataset (n=1451), patients with a TOTAL score of 0–4 points (n=737 (50.7%)) had a 0.3% risk of CV death/cardiac arrest within 24 hours, with no further events observed between 24 hours and 72 hours of hospitalization.

Conclusion

The TOTAL risk score identified a very low risk subset of patients for whom early discharge, 24–48 hours post-STEMI, is likely safe. These findings have the potential to change practice and support early discharge after STEMI.

Funding Acknowledgement

Type of funding sources: None.

Interaction Between SNP Genotype and Efficacy of Anastrozole and Exemestane in Early-Stage Breast Cancer

Aromatase inhibitors (AIs) are the treatment of choice for hormone receptor-positive early breast cancer in postmenopausal women. None of the third-generation AIs are superior to the others in terms of efficacy. We attempted to identify genetic factors that could differentiate between the effectiveness of adjuvant anastrozole and exemestane by examining single-nucleotide polymorphism (SNP)-treatment interaction in 4,465 patients. A group of SNPs were found to be differentially associated between anastrozole and exemestane regarding outcomes. However, they showed no association with outcome in the combined analysis. We followed up common SNPs near LY75 and GPR160 that could differentiate anastrozole from exemestane efficacy. LY75 and GPR160 participate in epithelial-to-mesenchymal transition and growth pathways, in both cases with SNP-dependent variation in regulation. Collectively, these studies identified SNPs that differentiate the efficacy of anastrozole and exemestane and they suggest additional genetic biomarkers for possible use in selecting an AI for a given patient.

Single-nucleotide polymorphism biomarkers of adjuvant anastrozole-induced estrogen suppression in early breast cancer

OBJECTIVES

Based on our previous findings that postmenopausal women with estrone (E1) and estradiol (E2) concentrations at or above 1.3 pg/ml and 0.5 pg/ml, respectively, after 6 months of adjuvant anastrozole therapy had a three-fold risk of recurrence, we aimed to identify a single-nucleotide polymorphism (SNP)-based model that would predict elevated E1 and E2 and then validate it in an independent dataset.

PATIENTS AND METHODS

The test set consisted of 322 women from the M3 study and the validation set consisted of 152 patients from MA.27. All patients were treated with adjuvant anastrozole, had on-anastrozole E1 and E2 concentrations and genome-wide genotyping.

RESULTS

SNPs were identified from the M3 genome-wide association study. The best model to predict the E1-E2 phenotype with high balanced accuracy was a support vector machine model using clinical factors plus 46 SNPs. We did not have an independent cohort that is similar to the M3 study with clinical, E1-E2 phenotypes and genotype data to test our model. Hence, we chose a nested matched case-control cohort (MA.27 study) for testing. Our E1-E2 model was not validated but we found the MA.27 validation cohort was both clinically and genomically different.

CONCLUSIONS

We identified a SNP-based model that had excellent performance characteristics for predicting the phenotype of elevated E1 and E2 in women treated with anastrozole. This model was not validated in an independent dataset but that dataset was clinically and genomically substantially different. The model will need validation in a prospective study.

CDC25B partners with PP2A to induce AMPK activation and tumor suppression in triple negative breast cancer

Cell division cycle 25 (CDC25) dual specificity phosphatases positively regulate the cell cycle by activating cyclin-dependent kinase/cyclin complexes. Here, we demonstrate that in addition to its role in cell cycle regulation, CDC25B functions as a regulator of protein phosphatase 2A (PP2A), a major cellular Ser/Thr phosphatase, through its direct interaction with PP2A catalytic subunit. Importantly, CDC25B alters the regulation of AMP-activated protein kinase signaling (AMPK) by PP2A, increasing AMPK activity by inhibiting PP2A to dephosphorylate AMPK. CDC25B depletion leads to metformin resistance by inhibiting metformin-induced AMPK activation. Furthermore, dual inhibition of CDC25B and PP2A further inhibits growth of 3D organoids isolated from patient derived xenograft model of breast cancer compared to CDC25B inhibition alone. Our study identifies CDC25B as a regulator of PP2A, and uncovers a mechanism of controlling the activity of a key energy metabolism marker, AMPK.

Pharmacogenomics of aromatase inhibitors in postmenopausal breast cancer and additional mechanisms of anastrozole action

Aromatase inhibitors (AIs) reduce breast cancer recurrence and prolong survival, but up to 30% of patients exhibit recurrence. Using a genome-wide association study of patients entered on MA.27, a phase III randomized trial of anastrozole versus exemestane, we identified a single nucleotide polymorphism (SNP) in CUB And Sushi multiple domains 1 (CSMD1) associated with breast cancer–free interval, with the variant allele associated with fewer distant recurrences. Mechanistically, CSMD1 regulates CYP19 expression in an SNP- and drug-dependent fashion, and this regulation is different among 3 AIs: anastrozole, exemestane, and letrozole. Overexpression of CSMD1 sensitized AI-resistant cells to anastrozole but not to the other 2 AIs. The SNP in CSMD1 that was associated with increased CSMD1 and CYP19 expression levels increased anastrozole sensitivity, but not letrozole or exemestane sensitivity. Anastrozole degrades estrogen receptor α (ERα), especially in the presence of estradiol (E2). ER⁺ breast cancer organoids and AI- or fulvestrant-resistant breast cancer cells were more sensitive to anastrozole plus E2 than to AI alone. Our findings suggest that the CSMD1 SNP might help to predict AI response, and anastrozole plus E2 serves as a potential new therapeutic strategy for patients with AI- or fulvestrant-resistant breast cancers.

A germline variation within the CSMD1 gene predicts aromatase inhibitor response in breast cancer.

Abstract LB-103: The interaction between SNP genotype and aromatase inhibitor treatment response in early breast cancer

Purpose: To determine genetic variants that could differentiate aromatase inhibitors (AIs) efficacy in early stage breast cancer. Experimental Design: We performed a stratified cox-proportional hazards analysis utilizing stratification factors and other covariates examining Breast Cancer Free Interval (BCFI) SNP-treatment interaction in Caucasian patients entered on the MA.27 trial. This analysis involved 4465 patients (2226 on anastrozole and 2239 on exemestane arm) including 245 (121 on anastrozole and 124 events on exemestane arm) with a breast event. Preclinical laboratory studies included luciferase activity, chromatin immunoprecipitation (ChIP) assay, and cell migration assays. Results: We identified 887 SNPs with a p-value &lt;1E-4 that could differentiate anastrozole from exemestane efficacy. We next used GTEx databases to determine whether these SNPs might be cis-eQTLs with nearby genes, and found that 95 SNPs were eQTL with 14 genes. Functional validation of SNP effect in these 14 genes on response to anastrozole and exemestane revealed that 3 SNPs showed genotype-dependent differences between anastrozole and exemestane. Two of the three SNPs, rs1877193 and rs6735923 located upstream of LY75 gene, were associated with higher LY75 gene expression. Our drug-SNP interaction GWAS showed that both SNPs were associated with better BCFI for exemestane compared to anastrozole (HR= 0.447, 0.458). The SNP rs62293499 located downstream of the GPR160 gene was also associated with better BCFI for exemestane compared to anastrozole (HR=0.433). Interestingly, all 3 SNPs were associated with worse outcome (shorter BCFI) in anastrozole treated patients (HR=1.39~1.58), but with longer BCFI in the exemestane treated patients (HR=0.58~0.71) based on our GWAS results in MA.27 trial. However, all 3 SNPs showed no association with BCFI if the two treatment arms, anastrozole and exemestane, were combined (HR=0.92~1.08). Consistently, cells with Ly75 or GPR160 SNP variant genotypes were more sensitive to exemestane compared to anastrozole. Mechanistically, the 3 SNPs regulated estrogen receptor-dependant LY75 and GPR160 expression. LY75 suppression induced epithelial-to-mesenchymal transition (EMT) in breast cancer cell lines, accompanied by increased migratory capacity in vitro. LY75 knockdown also resulted in predominant downregulation of functional pathways such as cell proliferation, while pathways associated with mesenchymal stimulation were generally increased. GPR160 knockdown also resulted in downregulation of cell proliferation pathways. Conclusions: This SNP genotype and AI treatment interaction clinical study revealed unique genetic variants that differentiate anastrozole and exemestane efficacy. The signals were lost in the GWAS analysis when anastrozole and exemestane were combined. Preclinical laboratory studies revealed novel functions of LY75 and GPR160 in breast cancer. These findings represent potential steps towards individualized AI therapy.

Citation Format: Junmei Cairns, James N. Ingle, Krishna R. Kalari, Lois E. Shepherd, Matthew J. Ellis, Paul E. Goss, Poulami Barman, Erin E. Carlson, Matthew P. Goetz, Richard M. Weinshilboum, Liewei Wang. The interaction between SNP genotype and aromatase inhibitor treatment response in early breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-103.

Anastrozole has an Association between Degree of Estrogen Suppression and Outcomes in Early Breast Cancer and is a Ligand for Estrogen Receptor α

PURPOSE

To determine if the degree of estrogen suppression with aromatase inhibitors (AI: anastrozole, exemestane, letrozole) is associated with efficacy in early-stage breast cancer, and to examine for differences in the mechanism of action between the three AIs.

EXPERIMENTAL DESIGN

Matched case-control studies [247 matched sets from MA.27 (anastrozole vs. exemestane) and PreFace (letrozole) trials] were undertaken to assess whether estrone (E1) or estradiol (E2) concentrations after 6 months of adjuvant therapy were associated with risk of an early breast cancer event (EBCE). Preclinical laboratory studies included luciferase activity, cell proliferation, radio-labeled ligand estrogen receptor binding, surface plasmon resonance ligand receptor binding, and nuclear magnetic resonance assays.

RESULTS

Women with E1 ≥1.3 pg/mL and E2 ≥0.5 pg/mL after 6 months of AI treatment had a 2.2-fold increase in risk (P = 0.0005) of an EBCE, and in the anastrozole subgroup, the increase in risk of an EBCE was 3.0-fold (P = 0.001). Preclinical laboratory studies examined mechanisms of action in addition to aromatase inhibition and showed that only anastrozole could directly bind to estrogen receptor α (ERα), activate estrogen response element-dependent transcription, and stimulate growth of an aromatase-deficient CYP19A1^-/- T47D breast cancer cell line.

CONCLUSIONS

This matched case-control clinical study revealed that levels of estrone and estradiol above identified thresholds after 6 months of adjuvant anastrozole treatment were associated with increased risk of an EBCE. Preclinical laboratory studies revealed that anastrozole, but not exemestane or letrozole, is a ligand for ERα. These findings represent potential steps towards individualized anastrozole therapy.

4071Early changes in quality of life after transcatheter aortic valve replacement: One-year results from the 3M TAVR Study

Background

In patients with severe calcific aortic stenosis, transcatheter aortic valve replacement (TAVR) has been shown to significantly improve quality of life (QOL). However, changes in QOL at early follow-up (<1 month), and following next-day discharge are poorly understood.

Methods

A total of 411 patients at 13 centers were enrolled in the Multimodality, Multidisciplinary but Minimalist TAVR (3M TAVR) study in 2015–2017. QOL was evaluated using the Kansas City Cardiomyopathy Questionnaire (KCCQ-12) in participants with a baseline score and at least one score at 2 weeks, 30 days and 1 year. Study endpoints were change in (1) KCCQ-Overall Summary Score (KCCQ-OS) and (2) minimal clinically important differences (MCID). Mixed effects models were used to explore patterns of change from baseline, with fixed terms for time, status at 1-year and their interaction terms, and a random intercept for subject to account for within subject correlation. Descriptive statistics were used to report MCID.

Results

Data were available for 358 (87.1%) participants. 216 (60.3%) were men with a median age 84.0 and STS 5.0 There was significant increase in QOL 2 weeks after TAVR (p≤0.01), and further significant improvement at the 1-month timepoint (p<0.01) for participants who were alive at 1 year. Sex, age category, and STS score category did not have a significant effect on the change in QOL (p>0.05). In the first 2 weeks, moderate (10–20 points) and large (>20 points) improvements were observed in 19.9% and 49.0% of the surviving patients, respectively; at 1-year, similar MCID were seen in 14.6% and 64.0% respectively.

Figure 1

Conclusion

This is the first study to report significant increase in QOL 2 weeks after TAVR, with sustained improvement during the first year in patients treated with the Vancouver TAVR Clinical Pathway with a goal of next-day discharge. Further studies are necessary to determine whether alternative TAVR clinical pathways yield similar findings.

Acknowledgement/Funding

Investigator-initiated unrestricted research grant, Edwards

5 Effect of feeding time on behavioral and stress responses in gestation sows under isocaloric conditions

Investigated the effect of feeding time on behavior and stress responses in pregnant sows under isocaloric conditions. Eighteen sows (Landrace × Yorkshire); BW 248.6 ± 2.8 kg; parity 3.30 ± 0.39); were blocked by parity and randomly assigned to 1 of 3 feeding times. Corn-soybean meal-based diet was fed once at: 0730 (Control, T1), 1130 (T2), and 1530 h (T3). On average, sows received 7190 kcal ME d−1 during gestation from 2.25 kg of diet formulated to contain SID Lys/ME of 1.71 g/Mcal. Saliva samples were collected every 2 h for 12 h in stalls on d 52 of pregnancy and assayed for cortisol using ELISA technique. Behavior data were collected 24 h for 7 d from d 53 of gestation by affixing a Remote Insights ear tag to each sow after 21 d adaptation period. Each sow had 120,960 data points categorized into: “Active,” “Feed” or “Dormant”. Data were analyzed using GLIMMIX procedure of SAS 9.4. Statistical significance was set at P ≤ 0.05, and a trend as 0.05 < P ≤ 0.10. Sow was the experimental unit. A 24 h area under the curve (AUC) was estimated by trapezoidal summation method. Adjustment for multiple comparisons was based on Tukey Kramer’s method. Sows fed daily at 0730 had both lower feeding and total activity compared with sows fed at 1130 h (P < 0.02) but similar to sows fed at 1530 h (P > 0.05). Feeding sows at 1130 h daily resulted in reduced cortisol AUC compared with 1530 h fed sows (P < 0.04) but similar to sows fed at 0730 h (P > 0.05). In conclusion, feeding sows daily at 1130 resulted in increased feed and total activity but reduced cortisol concentration, suggesting that elevated sow activity might not necessary indicate activation of hypothalamic-pituitary-adrenal (HPA) axis.

9 Behavioral and stress responses to feeding frequency in pregnant sows under isocaloric conditions

The objective of this study was to investigate behavioral and stress responses to feeding frequency in pregnant sows under isocaloric conditions. Eighteen sows (Landrace × Yorkshire); BW 226.10 ± 1.29 kg; parity 3.1 ± 0.42); were blocked by parity and randomly assigned to 1 of 3 feeding frequency regimes. Sows were fed corn-soybean meal-based diet 1× [0730 (Control, T1), 2× “[half ration at 0730 and 1530 h (T2)]” and then “[one-third portion at 0730, 1130, and 1530 h (T3)]”. On average, sows received 7190 kcal ME d−1 during gestation from 2.25 kg of diet formulated to contain SID Lys/ME of 1.71 g/Mcal. Saliva samples were collected from 0630 to 1830 h, 2 hrs apart and assayed for cortisol using ELISA technique. Behavior data were collected for 7 d from d 53 of gestation by affixing a Remote Insights ear tag to each sow. Each sow had 120,960 data points categorized into: “Active,” “Feed” or “Dormant”. The data were analyzed using GLIMMIX procedure of SAS 9.4 with treatment as fixed effect and sow as random effect. Results were considered statistically significant when P < 0·05 and were considered as trends when P ≤ 0·10. Sow was the experimental unit. A 24 h area under the curve (AUC) was calculated by trapezoidal method. The P-values were adjusted for multiplicity based on Tukey Kramer’s method. A 24 h total activity and total feeding activity AUC were reduced in sows fed 2× daily compared with sows fed 1× and 3× daily (P < 0.01). A 12 h cortisol AUC was lower for sows fed 2× daily relative to treatment groups fed 1× and 3× daily (P < 0.02). In conclusion, feeding pregnant sows twice daily may improve sow welfare by reducing feeding activity, total activity, and the activation of hypothalamic-pituitary-adrenal (HPA) axis.

The lncRNA MIR2052HG regulates ERα levels and aromatase inhibitor resistance through LMTK3 by recruiting EGR1

Background

Our previous genome-wide association study using the MA.27 aromatase inhibitors adjuvant trial identified SNPs in the long noncoding RNA MIR2052HG associated with breast cancer-free interval. MIR2052HG maintained ERα both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated ERα degradation. Our goal was to further elucidate MIR2052HG’s mechanism of action.

Methods

RNA-binding protein immunoprecipitation assays were performed to demonstrate that the transcription factor, early growth response protein 1 (EGR1), worked together with MIR2052HG to regulate that lemur tyrosine kinase-3 (LMTK3) transcription in MCF7/AC1 and CAMA-1 cells. The location of EGR1 on the LMTK3 gene locus was mapped using chromatin immunoprecipitation assays. The co-localization of MIR2052HG RNA and the LMTK3 gene locus was determined using RNA-DNA dual fluorescent in situ hybridization. Single-nucleotide polymorphisms (SNP) effects were evaluated using a panel of human lymphoblastoid cell lines.

Results

MIR2052HG depletion in breast cancer cells results in a decrease in LMTK3 expression and cell growth. Mechanistically, MIR2052HG interacts with EGR1 and facilitates its recruitment to the LMTK3 promoter. LMTK3 sustains ERα levels by reducing protein kinase C (PKC) activity, resulting in increased ESR1 transcription mediated through AKT/FOXO3 and reduced ERα degradation mediated by the PKC/MEK/ERK/RSK1 pathway. MIR2052HG regulated LMTK3 in a SNP- and aromatase inhibitor-dependent fashion: the variant SNP increased EGR1 binding to LMTK3 promoter in response to androstenedione, relative to wild-type genotype, a pattern that can be reversed by aromatase inhibitor treatment. Finally, LMTK3 overexpression abolished the effect of MIR2052HG on PKC activity and ERα levels.

Conclusions

Our findings support a model in which the MIR2052HG regulates LMTK3 via EGR1, and LMTK3 regulates ERα stability via the PKC/MEK/ERK/RSK1 axis. These results reveal a direct role of MIR2052HG in LMTK3 regulation and raise the possibilities of targeting MIR2052HG or LMTK3 in ERα-positive breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1130-3) contains supplementary material, which is available to authorized users.

Anastrozole Aromatase Inhibitor Plasma Drug Concentration Genome-Wide Association Study: Functional Epistatic Interaction Between SLC38A7 and ALPPL2

Anastrozole is a widely prescribed aromatase inhibitor for the therapy of estrogen receptor positive (ER+) breast cancer. We performed a genome‐wide association study (GWAS) for plasma anastrozole concentrations in 687 postmenopausal women with ER+ breast cancer. The top single‐nucleotide polymorphism (SNP) signal mapped across SLC38A7 (rs11648166, P = 2.3E‐08), which we showed to encode an anastrozole influx transporter. The second most significant signal (rs28845026, P = 5.4E‐08) mapped near ALPPL2 and displayed epistasis with the SLC38A7 signal. Both of these SNPs were cis expression quantitative trait loci (eQTL)s for these genes, and patients homozygous for variant genotypes for both SNPs had the highest drug concentrations, the highest SLC38A7 expression, and the lowest ALPPL2 expression. In summary, our GWAS identified a novel gene encoding an anastrozole transporter, SLC38A7, as well as epistatic interaction between SNPs in that gene and SNPs near ALPPL2 that influenced both the expression of the transporter and anastrozole plasma concentrations.

Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer

This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among the 23,398 genes of the human genome to experiment on in the laboratory to establish new drug mechanisms. As a case study, this paper uses MDA-MB-231 breast cancer single-cells treated with the antidiabetic drug metformin. We show that mixture-model-based unsupervised methods with validation from hierarchical clustering can identify single-cell subpopulations (clusters). These clusters are characterized by a small set of genes (1% of the genome) that have significant differential expression across the clusters and are also highly correlated with pathways with anticancer effects driven by metformin. Among the identified small set of genes associated with reduced breast cancer incidence, laboratory experiments on one of the genes, CDC42, showed that its downregulation by metformin inhibited cancer cell migration and proliferation, thus validating the ability of machine learning approaches to identify biologically relevant candidates for laboratory experiments. Given the large size of the human genome and limitations in cost and skilled resources, the broader impact of this work in identifying a small set of differentially expressed genes after drug treatment lies in augmenting the drug-disease knowledge of pharmacogenomics experts in laboratory investigations, which could help establish novel biological mechanisms associated with drug response in diseases beyond breast cancer.

Principled multi-omic analysis reveals gene regulatory mechanisms of phenotype variation

Recent studies have analyzed large-scale data sets of gene expression to identify genes associated with interindividual variation in phenotypes ranging from cancer subtypes to drug sensitivity, promising new avenues of research in personalized medicine. However, gene expression data alone is limited in its ability to reveal cis-regulatory mechanisms underlying phenotypic differences. In this study, we develop a new probabilistic model, called pGENMi, that integrates multi-omic data to investigate the transcriptional regulatory mechanisms underlying interindividual variation of a specific phenotype—that of cell line response to cytotoxic treatment. In particular, pGENMi simultaneously analyzes genotype, DNA methylation, gene expression, and transcription factor (TF)-DNA binding data, along with phenotypic measurements, to identify TFs regulating the phenotype. It does so by combining statistical information about expression quantitative trait loci (eQTLs) and expression-correlated methylation marks (eQTMs) located within TF binding sites, as well as observed correlations between gene expression and phenotype variation. Application of pGENMi to data from a panel of lymphoblastoid cell lines treated with 24 drugs, in conjunction with ENCODE TF ChIP data, yielded a number of known as well as novel (TF, Drug) associations. Experimental validations by TF knockdown confirmed 41% of the predicted and tested associations, compared to a 12% confirmation rate of tested nonassociations (controls). An extensive literature survey also corroborated 62% of the predicted associations above a stringent threshold. Moreover, associations predicted only when combining eQTL and eQTM data showed higher precision compared to an eQTL-only or eQTM-only analysis using pGENMi, further demonstrating the value of multi-omic integrative analysis.

Abstract P5-07-01: LncRNA MIR2052HG regulates ERα level and endocrine resistance through LMTK3 by recruiting early growth response protein 1

BACKGROUND: A GWAS for the MA.27 aromatase inhibitors (AIs) adjuvant trial (4,406 controls and 252 cases) identified variant (V) SNPs in a long noncoding (lnc) RNA, MIR2052HG, that were associated with longer breast cancer free interval (HR= 0.37, P= 2.15E-07). V SNPs (MAF= 0.32 to 0.42) were associated with lower MIR2052HG and ERα expression in the presence of AIs. MIR2052HG maintained ERα both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated ERα degradation. (Cancer Res 76:7012-23, 2016). Our goal was to further elucidate MIR2052HG's mechanism of action.

METHODS: RNA-Binding Protein Immunoprecipitation (RBPI) assays were performed to demonstrate that the transcription factor, early growth response protein 1 (EGR1), worked together with MIR2052HG to regulate lemur tyrosine kinase-3 (LMTK3) transcription in MCF7/AC1 and CAMA-1 cells. The location of EGR1 on the LMTK3 gene locus was mapped using chromatin immunoprecipitation (ChIP) assays. The co-localization of MIR2052HG RNA and the LMTK3 gene locus was determined using RNA-DNA dual fluorescent in situ hybridization (FISH). SNP effects were evaluated using a panel of human lymphoblastoid cell lines.

RESULTS: TCGA analysis revealed LMTK3 and MIR2052HG expression were highly correlated in ERα-positive breast cancer patients. We found that the MIR2052HG transcript was located in the LMTK3 gene locus by RNA-DNA FISH. Among all of the 12 potential LMTK3 transcription factors identified in the Encode database that were examined by RBPI, only EGR1 showed an interaction with MIR2052HG. CHIP assays confirmed EGR1 binding to the two putative EGR1 binding sites in LMTK3 gene.Depletion of MIR2052HG reduced the binding of EGR1 to the LMTK3 promoter and decreased LMTK3 expression, suggesting that it might function as a scaffold. Mechanistically, decreased LMTK3 levels further increased protein kinase C (PKC) activity and downstream AKT activity, leading to reduced ESR1 mRNA levels via increased pFOXO3. At the protein level, in MIR2052HG depleted cells, increased PKC activity increased the phosphorylation of MEK, ERK, and RSK1, leading to increased ERα phosphorylation at Ser167 and increased ERα degradation. Conversely, overexpression of LMTK3 in MIR2052HG depleted cells reversed these phenotypes. MIR2052HG regulated LMTK3 and ERα expression in a SNP- dependent fashion: the MIR2052HG V SNP, relative to wild-type (WT) genotype, increased LMTK3/ERα expression in response to androstenedione due to increased binding between EGR1 and the LMTK3 promoter in LCLs. However, AI treatment reduced this binding in MIR2052HG variant cells but increased binding in WT cells, resulting in decreased LMTK3/ERα in V cells and increased expression in WT cells.

CONCLUSIONS: Our findings support a model in which the protective MIR2052HG variant genotype regulates LMTK3 via MIR2052HG/EGR1, and LMTK3 regulates ERα stability via the PKC/MEK/ERK/RSK1 axis. This regulation may explain the effect of the MIR2052HG variant genotype on cell proliferation and response to AIs in MA.27. These findings provide new insight into the mechanism of action of MIR2052HG and suggest that LMTK3 may be a new therapeutic target in ERα-positive breast cancer patients treated with AIs.

Citation Format: Cairns J, Ingle JN, Shepherd LE, Kubo M, Goetz MP, Weinshilboum RM, Kalari KR, Wang L. LncRNA MIR2052HG regulates ERα level and endocrine resistance through LMTK3 by recruiting early growth response protein 1 [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-07-01.

Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines

Metformin is currently considered as a promising anticancer agent in addition to its anti-diabetic effect. To better individualize metformin therapy and explore novel molecular mechanisms in cancer treatment, we conducted a pharmacogenomic study using 266 lymphoblastoid cell lines (LCLs). Metformin cytotoxicity assay was performed using the MTS assay. Genome-wide association (GWA) analyses were performed in LCLs using 1.3 million SNPs, 485k DNA methylation probes, 54k mRNA expression probe sets, and metformin cytotoxicity (IC50s). Top candidate genes were functionally validated using siRNA screening, followed by MTS assay in breast cancer cell lines. Further study of one top candidate, STUB1, was performed to elucidate the mechanisms by which STUB1 might contribute to metformin action. GWA analyses in LCLs identified 198 mRNA expression probe sets, 12 SNP loci, and 5 DNA methylation loci associated with metformin IC50 with P-values <10−4 or <10−5. Integrated SNP/methylation loci-expression-IC50 analyses found 3 SNP loci or 5 DNA methylation loci associated with metformin IC50 through trans-regulation of expression of 11 or 26 genes with P-value <10−4. Functional validation of top 61 candidate genes in 4 IPA networks indicated down regulation of 14 genes significantly altered metformin sensitivity in two breast cancer cell lines. Mechanistic studies revealed that the E3 ubiquitin ligase, STUB1, could influence metformin response by facilitating proteasome-mediated degradation of cyclin A. GWAS using a genomic data-enriched LCL model system, together with functional and mechanistic studies using cancer cell lines, help us to identify novel genetic and epigenetic biomarkers involved in metformin anticancer response.

Differential roles of ERRFI1 in EGFR and AKT pathway regulation affect cancer proliferation

AKT signaling is modulated by a complex network of regulatory proteins and is commonly deregulated in cancer. Here, we present a dual mechanism of AKT regulation by the ERBB receptor feedback inhibitor 1 (ERRFI1). We show that in cells expressing high levels of EGFR, ERRF1 inhibits growth and enhances responses to chemotherapy. This is mediated in part through the negative regulation of AKT signaling by direct ERRFI1-dependent inhibition of EGFR In cells expressing low levels of EGFR, ERRFI1 positively modulates AKT signaling by interfering with the interaction of the inactivating phosphatase PHLPP with AKT, thereby promoting cell growth and chemotherapy desensitization. These observations broaden our understanding of chemotherapy response and have important implications for the selection of targeted therapies in a cell context-dependent manner. EGFR inhibition can only sensitize EGFR-high cells for chemotherapy, while AKT inhibition increases chemosensitivity in EGFR-low cells. By understanding these mechanisms, we can take advantage of the cellular context to individualize antineoplastic therapy. Finally, our data also suggest targeting of EFFRI1 in EGFR-low cancer as a promising therapeutic approach.

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure

With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches. However, considerations for application in clinical metabolic profiling remain to be evaluated. Particularly, regarding the robustness of AutoML to identify and adjust for common clinical confounders. In this study, we present a focused case study regarding AutoML considerations for using the Tree-Based Optimization Tool (TPOT) in metabolic profiling of exposure to metformin in a biobank cohort. First, we propose a tandem rank-accuracy measure to guide agnostic feature selection and corresponding threshold determination in clinical metabolic profiling endeavors. Second, while AutoML, using default parameters, demonstrated potential to lack sensitivity to low-effect confounding clinical covariates, we demonstrated residual training and adjustment of metabolite features as an easily applicable approach to ensure AutoML adjustment for potential confounding characteristics. Finally, we present increased homocysteine with long-term exposure to metformin as a potentially novel, non-replicated metabolite association suggested by TPOT; an association not identified in parallel clinical metabolic profiling endeavors. While warranting independent replication, our tandem rank-accuracy measure suggests homocysteine to be the metabolite feature with largest effect, and corresponding priority for further translational clinical research. Residual training and adjustment for a potential confounding effect by BMI only slightly modified the suggested association. Increased homocysteine is thought to be associated with vitamin B12 deficiency - evaluation for potential clinical relevance is suggested. While considerations for clinical metabolic profiling are recommended, including adjustment approaches for clinical confounders, AutoML presents an exciting tool to enhance clinical metabolic profiling and advance translational research endeavors.

Therapy response testing of breast cancer in a 3D high-throughput perfused microfluidic platform

BACKGROUND

Breast cancer is the most common invasive cancer among women. Currently, there are only a few models used for therapy selection, and they are often poor predictors of therapeutic response or take months to set up and assay. In this report, we introduce a microfluidic OrganoPlate® platform for extracellular matrix (ECM) embedded tumor culture under perfusion as an initial study designed to investigate the feasibility of adapting this technology for therapy selection.

METHODS

The triple negative breast cancer cell lines MDA-MB-453, MDA-MB-231 and HCC1937 were selected based on their different BRCA1 and P53 status, and were seeded in the platform. We evaluate seeding densities, ECM composition (Matrigel®, BME2rgf, collagen I) and biomechanical (perfusion vs static) conditions. We then exposed the cells to a series of anti-cancer drugs (paclitaxel, olaparib, cisplatin) and compared their responses to those in 2D cultures. Finally, we generated cisplatin dose responses in 3D cultures of breast cancer cells derived from 2 PDX models.

RESULTS

The microfluidic platform allows the simultaneous culture of 96 perfused micro tissues, using limited amounts of material, enabling drug screening of patient-derived material. 3D cell culture viability is improved by constant perfusion of the medium. Furthermore, the drug response of these triple negative breast cancer cells was attenuated by culture in 3D and differed from that observed in 2D substrates.

CONCLUSIONS

We have investigated the use of a high-throughput organ-on-a-chip platform to select therapies. Our results have raised the possibility to use this technology in personalized medicine to support selection of appropriate drugs and to predict response to therapy in a real time fashion.

SNPs near the cysteine proteinase cathepsin O gene (CTSO) determine tamoxifen sensitivity in ERα-positive breast cancer through regulation of BRCA1

Tamoxifen is one of the most commonly employed endocrine therapies for patients with estrogen receptor α (ERα)-positive breast cancer. Unfortunately the clinical benefit is limited due to intrinsic and acquired drug resistance. We previously reported a genome-wide association study that identified common SNPs near the CTSO gene and in ZNF423 associated with development of breast cancer during tamoxifen therapy in the NSABP P-1 and P-2 breast cancer prevention trials. Here, we have investigated their roles in ERα-positive breast cancer growth and tamoxifen response, focusing on the mechanism of CTSO. We performed in vitro studies including luciferase assays, cell proliferation, and mass spectrometry-based assays using ERα-positive breast cancer cells and a panel of genomic data-rich lymphoblastoid cell lines. We report that CTSO reduces the protein levels of BRCA1 and ZNF423 through cysteine proteinase-mediated degradation. We also have identified a series of transcription factors of BRCA1 that are regulated by CTSO at the protein level. Importantly, the variant CTSO SNP genotypes are associated with increased CTSO and decreased BRCA1 protein levels that confer resistance to tamoxifen. Characterization of the effect of both CTSO SNPs and ZNF423 SNPs on tamoxifen response revealed that cells with different combinations of CTSO and ZNF423 genotypes respond differently to Tamoxifen, PARP inhibitors or the combination of the two drugs due to SNP dependent differential regulation of BRCA1 levels. Therefore, these genotypes might be biomarkers for selection of individual drug to achieve the best efficacy.

Many studies have demonstrated that germline genetic variation can contribute to both breast cancer disease risk and treatment response. However, the underlying mechanisms associated with these biomarkers often remains understudied. As part of functional genomic studies following up a case-control genome-wide association study (GWAS) performed with the large and influential National Surgical Adjuvant Breast and Bowel Project P-1 and P-2 SERM breast cancer prevention trials, we investigated the top GWAS SNPs in CTSO gene on chromosome 4 and mechanisms of CTSO involvement in the regulation of BRCA1 and response to therapy. We showed that, based on individual’s genotype, CTSO contributes differentially to tamoxifen response in ERα-positive (ER+) breast cancer cells by regulating ZNF423 and BRCA1levels and that PARP inhibitors can effectively restore tamoxifen sensitivity in subjects with unfavorable genotypes of CTSO and ZNF423 associated with tamoxifen resistance. Our work highlights the potential value of a new biomarker signature involving CTSO and ZNF423-related SNPs for selection of tamoxifen or PARP inhibitors.

Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance

BACKGROUND

Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance.

RESULTS

We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group.

CONCLUSIONS

Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.

Model-based unsupervised learning informs metformin-induced cell-migration inhibition through an AMPK-independent mechanism in breast cancer

We demonstrate that model-based unsupervised learning can uniquely discriminate single-cell subpopulations by their gene expression distributions, which in turn allow us to identify specific genes for focused functional studies. This method was applied to MDA-MB-231 breast cancer cells treated with the antidiabetic drug metformin, which is being repurposed for treatment of triple-negative breast cancer. Unsupervised learning identified a cluster of metformin-treated cells characterized by a significant suppression of 230 genes (p-value < 2E-16). This analysis corroborates known studies of metformin action: a) pathway analysis indicated known mechanisms related to metformin action, including the citric acid (TCA) cycle, oxidative phosphorylation, and mitochondrial dysfunction (p-value < 1E-9); b) 70% of these 230 genes were functionally implicated in metformin response; c) among remaining lesser functionally-studied genes for metformin-response was CDC42, down-regulated in breast cancer treated with metformin. However, CDC42's mechanisms in metformin response remained unclear. Our functional studies showed that CDC42 was involved in metformin-induced inhibition of cell proliferation and cell migration mediated through an AMPK-independent mechanism. Our results points to 230 genes that might serve as metformin response signatures, which needs to be tested in patients treated with metformin and, further investigation of CDC42 and AMPK-independence's role in metformin's anticancer mechanisms.

Cerebellar contribution to higher and lower order rule learning and cognitive flexibility in mice

Cognitive flexibility has traditionally been considered a frontal lobe function. However, converging evidence suggests involvement of a larger brain circuit which includes the cerebellum. Reciprocal pathways connecting the cerebellum to the prefrontal cortex provide a biological substrate through which the cerebellum may modulate higher cognitive functions, and it has been observed that cognitive inflexibility and cerebellar pathology co-occur in psychiatric disorders (e.g., autism, schizophrenia, addiction). However, the degree to which the cerebellum contributes to distinct forms of cognitive flexibility and rule learning is unknown. We tested lurcher↔wildtype aggregation chimeras which lose 0-100% of cerebellar Purkinje cells during development on a touchscreen-mediated attentional set-shifting task to assess the contribution of the cerebellum to higher and lower order rule learning and cognitive flexibility. Purkinje cells, the sole output of the cerebellar cortex, ranged from 0 to 108,390 in tested mice. Reversal learning and extradimensional set-shifting were impaired in mice with⩾95% Purkinje cell loss. Cognitive deficits were unrelated to motor deficits in ataxic mice. Acquisition of a simple visual discrimination and an attentional-set were unrelated to Purkinje cells. A positive relationship was observed between Purkinje cells and errors when exemplars from a novel, non-relevant dimension were introduced. Collectively, these data suggest that the cerebellum contributes to higher order cognitive flexibility, lower order cognitive flexibility, and attention to novel stimuli, but not the acquisition of higher and lower order rules. These data indicate that the cerebellar pathology observed in psychiatric disorders may underlie deficits involving cognitive flexibility and attention to novel stimuli.

Abstract PD1-04: CSMD1 SNPs selectively affect anastrozole response in postmenopausal breast cancer patients

BACKGROUND: Based on prospective clinical trials, there is no evidence for differences in efficacy between the 3 aromatase inhibitors (AIs) anastrozole, exemestane, and letrozole. The purpose of this study was to identify germline genetic variants associated with response to AIs and to help identify novel mechanisms associated with drug disease efficacy.

METHODS: A genome-wide association study (GWAS) was performed for 624 patients (Steroids 2015;99:32-38) to identify SNPs associated with estrogen level change in women with estrogen receptor (ER) positive breast cancer treated with anastrozole. Replication of associated SNPs was performed in a GWAS from the MA.27 trial that compared adjuvant anastrozole and exemestane treatment of post-menopausal women with ER+ breast cancer. Functional studies were subsequently performed to determine SNP effects and underlying mechanisms.

RESULTS: Our initial GWAS identified SNPs within CSMD1 that were associated with changes in estrogen levels during anastrozole therapy. An additional SNP in CSMD1 was also associated with breast cancer events in CCTG MA.27. Functionally, we showed that CSMD1 regulates CYP19 expression in a SNP-, and in an anastrozole- dependent fashion. These phenomena were not observed for either letrozole or exemestane. In MA.27, an anastrozole- specific effect was also seen with the minor allele having a protective effect on time to distant metastasis (HR=0.49, p=0.00259), but this was not the case for exemestane (HR=0.71, p=0.111). Our in vitro functional studies indicated that overexpression of CSMD1 sensitized anastrozole or letrozole resistant cells to anastrozole but not to the other two AIs. The SNP in CSMD1 that was associated with increased CSMD1 and CYP19 expression levels increased anastrozole sensitivity, but not letrozole or exemestane in lymphoblastoid cell lines (LCLs) homozygous for either WT or variant CSMD1 SNP genotypes. Based on these observations, we explored whether anastrozole has additional mechanisms beyond its function as a CYP19 inhibitor. Utilizing an estrogen response element (ERE) luciferase reporter assay in a CYP19 CRISPR knockout breast cancer T47D cell line and a surface plasmon resonance (SPR) assay, we found that anastrozole can also function as an ERα agonist, and can bind to, and result in, proteasome dependent ERα degradation, especially in the presence of E2. Treatment of these CYP19 CRISPR knockout cells with anastrozole in the presence of increasing concentrations of E2 results in greater sensitivity compared with anastrozole alone, while the addition of E2, as expected, does not improve letrozole or exemestane sensitivity. These same observations were also seen in letrozole and anastrazole resistant cells.

CONCLUSIONS: Our findings suggest that anastrozole might be more effective than letrozole or exemestane in patients with the CSMD1 SNP. Furthermore, anastrozole can function as an ERα agonist, binding to ERα and resulting in its degradation, especially in the presence of E2. These findings should help to make it possible to develop precision endocrine therapies for women who are candidates for AIs.

Citation Format: Cairns J, Ingle J, Dudenkov T, Kalari K, Buzdar A, Kubo M, Robson M, Ellis M, Goss P, Shepherd L, Goetz M, Weinshilboum R, Wang L. CSMD1 SNPs selectively affect anastrozole response in postmenopausal breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD1-04.

A comprehensive approach for evaluating telemedicine-delivered multidisciplinary breast cancer meetings in southern Scotland

Multidisciplinary team (MDT) meetings for decisions on cancer management are a cornerstone of UK cancer policy. We have proposed a comprehensive methodology to assess the clinical and economic effectiveness of telemedicine in this setting, which is being tested in a randomized breast cancer trial. Pre- and post-telemedicine assessment includes attitudes to and expectations of telemedicine, based on semistructured interviews. The communication content of videotapes of the MDT meeting is being scored using Borgatta's revised Interaction Process Analysis System. The technical performance of the telemedicine equipment is reported on a standardized pro forma. A short questionnaire captures key elements of professional satisfaction for each patient discussion (consensus on future management, confidence in and sharing of decision), added value of linkage, group atmosphere, overall conduct of the meeting and compliance with SIGN guidelines. A cost-minimization analysis will be used for economic assessment.

A network-based phenotype mapping approach to identify genes that modulate drug response phenotypes

To better address the problem of drug resistance during cancer chemotherapy and explore the possibility of manipulating drug response phenotypes, we developed a network-based phenotype mapping approach (P-Map) to identify gene candidates that upon perturbed can alter sensitivity to drugs. We used basal transcriptomics data from a panel of human lymphoblastoid cell lines (LCL) to infer drug response networks (DRNs) that are responsible for conferring response phenotypes for anthracycline and taxane, two common anticancer agents use in clinics. We further tested selected gene candidates that interact with phenotypic differentially expressed genes (PDEGs), which are up-regulated genes in LCL for a given class of drug response phenotype in triple-negative breast cancer (TNBC) cells. Our results indicate that it is possible to manipulate a drug response phenotype, from resistant to sensitive or vice versa, by perturbing gene candidates in DRNs and suggest plausible mechanisms regulating directionality of drug response sensitivity. More important, the current work highlights a new way to formulate systems-based therapeutic design: supplementing therapeutics that aim to target disease culprits with phenotypic modulators capable of altering DRN properties with the goal to re-sensitize resistant phenotypes.

Computational discovery of transcription factors associated with drug response

This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulatory contexts associated with cytotoxicity. The method, GENMi (Gene Expression iN the Middle), postulates that single-nucleotide polymorphisms within TF-binding sites putatively modulate its regulatory activity, and the resulting variation in gene expression leads to variation in drug response. Analysis of 161 TFs and 24 treatments revealed 334 significantly associated TF-treatment pairs. Investigation of 20 selected pairs yielded literature support for 13 of these associations, often from studies where perturbation of the TF expression changes drug response. Experimental validation of significant GENMi associations in taxanes and anthracyclines across two triple-negative breast cancer cell lines corroborates our findings. The method is shown to be more sensitive than an alternative, genome-wide association study-based approach that does not use gene expression. These results demonstrate the utility of GENMi in identifying TFs that influence drug response and provide a number of candidates for further testing.

CHILDSPLA: a collaboration between children and researchers to design and animate health states

AIM

The children's health state preferences learnt from animation (CHILDSPLA) project developed an interactive application presented on a touch screen device using an animated character to collect information from children about their health.

BACKGROUND

The underlying hypothesis was that health information could be directly collected from children as young as 4 years old by the use of animated characters. This paper describes in detail how children were involved in the development of the application, and recounts both the challenges and benefits of that process. A child psychologist and an animation filmmaker worked closely with children to design a character and to animate it to represent different health states. Children were recruited from a local primary school (n = 38) and a paediatric specialist hospital (n = 36). Diverse interactive activities were organized to help children give feedback and guide the design process. The activities for each session were adjusted to the children's needs, based on the experience of previous sessions.

RESULTS

The character and the animations were modified according to the feedback provided by the children.

CONCLUSIONS

Developing the CHILDSPLA app in collaboration with children was a worthwhile and enriching experience, despite the required iteration and extension of the design process, as it enabled us to adjust the tool to the children's needs.

Bora downregulation results in radioresistance by promoting repair of double strand breaks

Following DNA double-strand breaks cells activate several DNA-damage response protein kinases, which then trigger histone H2AX phosphorylation and the accumulation of proteins such as MDC1, p53-binding protein 1, and breast cancer gene 1 at the damage site to promote DNA double-strand breaks repair. We identified a novel biomarker, Bora (previously called C13orf34), that is associated with radiosensitivity. In the current study, we set out to investigate how Bora might be involved in response to irradiation. We found a novel function of Bora in DNA damage repair response. Bora down-regulation increased colony formation in cells exposed to irradiation. This increased resistance to irradiation in Bora-deficient cells is likely due to a faster rate of double-strand breaks repair. After irradiation, Bora-knockdown cells displayed increased G2-M cell cycle arrest and increased Chk2 phosphorylation. Furthermore, Bora specifically interacted with the tandem breast cancer gene 1 C-terminal domain of MDC1 in a phosphorylation dependent manner, and overexpression of Bora could abolish irradiation induced MDC1 foci formation. In summary, Bora may play a significant role in radiosensitivity through the regulation of MDC1 and DNA repair.

Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize

BACKGROUND

Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement.

RESULTS

We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield.

CONCLUSION

This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.

The CRASH-2 trial: a randomised controlled trial and economic evaluation of the effects of tranexamic acid on death, vascular occlusive events and transfusion requirement in bleeding trauma patients

BACKGROUND

Among trauma patients who survive to reach hospital, exsanguination is a common cause of death. A widely practicable treatment that reduces blood loss after trauma could prevent thousands of premature deaths each year. The CRASH-2 trial aimed to determine the effect of the early administration of tranexamic acid on death and transfusion requirement in bleeding trauma patients. In addition, the effort of tranexamic acid on the risk of vascular occlusive events was assessed.

OBJECTIVE

Tranexamic acid (TXA) reduces bleeding in patients undergoing elective surgery. We assessed the effects and cost-effectiveness of the early administration of a short course of TXA on death, vascular occlusive events and the receipt of blood transfusion in trauma patients.

DESIGN

Randomised placebo-controlled trial and economic evaluation. Randomisation was balanced by centre, with an allocation sequence based on a block size of eight, generated with a computer random number generator. Both participants and study staff (site investigators and trial co-ordinating centre staff) were masked to treatment allocation. All analyses were by intention to treat. A Markov model was used to assess cost-effectiveness. The health outcome was the number of life-years (LYs) gained. Cost data were obtained from hospitals, the World Health Organization database and UK reference costs. Cost-effectiveness was measured in international dollars ($) per LY. Deterministic and probabilistic sensitivity analyses were performed to test the robustness of the results to model assumptions.

SETTING

Two hundred and seventy-four hospitals in 40 countries.

PARTICIPANTS

Adult trauma patients (n = 20,211) with, or at risk of, significant bleeding who were within 8 hours of injury.

INTERVENTIONS

Tranexamic acid (loading dose 1 g over 10 minutes then infusion of 1 g over 8 hours) or matching placebo.

MAIN OUTCOME MEASURES

The primary outcome was death in hospital within 4 weeks of injury, and was described with the following categories: bleeding, vascular occlusion (myocardial infarction, stroke and pulmonary embolism), multiorgan failure, head injury and other.

RESULTS

Patients were allocated to TXA (n = 10,096) and to placebo (n = 10,115), of whom 10,060 and 10,067 patients, respectively, were analysed. All-cause mortality at 28 days was significantly reduced by TXA [1463 patients (14.5%) in the TXA group vs 1613 patients (16.0%) in the placebo group; relative risk (RR) 0.91; 95% confidence interval (CI) 0.85 to 0.97; p = 0.0035]. The risk of death due to bleeding was significantly reduced [489 patients (4.9%) died in the TXA group vs 574 patients (5.7%) in the placebo group; RR 0.85; 95% CI 0.76 to 0.96; p = 0.0077]. We recorded strong evidence that the effect of TXA on death due to bleeding varied according to the time from injury to treatment (test for interaction p < 0.0001). Early treatment (≤ 1 hour from injury) significantly reduced the risk of death due to bleeding [198 out of 3747 patients (5.3%) died in the TXA group vs 286 out of 3704 patients (7.7%) in the placebo group; RR 0.68; 95% CI 0.57 to 0.82; p < 0.0001]. Treatment given between 1 and 3 hours also reduced the risk of death due to bleeding [147 out of 3037 patients (4.8%) died in the TXA group vs 184 out of 2996 patients (6.1%) in the placebo group; RR 0.79; 95% CI 0.64 to 0.97; p = 0.03]. Treatment given after 3 hours seemed to increase the risk of death due to bleeding [144 out of 3272 patients (4.4%) died in the TXA group vs 103 out of 3362 patients (3.1%) in the placebo group; RR 1.44; 95% CI1.12 to 1.84; p = 0.004]. We recorded no evidence that the effect of TXA on death due to bleeding varied by systolic blood pressure, Glasgow Coma Scale score or type of injury. Administering TXA to bleeding trauma patients within 3 hours of injury saved an estimated 755 LYs per 1000 trauma patients in the UK. The cost of giving TXA to 1000 patients was estimated at $30,830. The incremental cost of giving TXA compared with not giving TXA was $48,002. The incremental cost per LY gained of administering TXA was $64.

CONCLUSIONS

Early administration of TXA safely reduced the risk of death in bleeding trauma patients and is highly cost-effective. Treatment beyond 3 hours of injury is unlikely to be effective. Future work [the Clinical Randomisation of an Antifibrinolytic in Significant Head injury-3 (CRASH-3) trial] will evaluate the effectiveness and safety of TXA in the treatments of isolated traumatic brain injury (http://crash3.lshtm.ac.uk/).

TRIAL REGISTRATION

Current Controlled Trials ISRCTN86750102, ClinicalTrials.gov NCT00375258 and South African Clinical Trial Register DOH-27-0607-1919.

FUNDING

The project was funded by the Bupa Foundation, the J P Moulton Charitable Foundation and the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 17, No. 10. See HTA programme website for further project information.