Weinshilboum, Richard M.

Abstract The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a ‘landing pad’ system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.

Abstract Purpose: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS). Experimental Design: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes. Results: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE. Conclusions: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways.

Abstract Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low overall survival rates and high molecular heterogeneity; therefore, few targeted therapies are available. The luminal androgen receptor (LAR) is the most consistently identified TNBC subtype, but the clinical utility has yet to be established. Here, we constructed a novel genomic classifier, LAR-Sig, that distinguishes the LAR subtype from other TNBC subtypes and provide evidence that it is a clinically distinct disease. A meta-analysis of seven TNBC datasets (n = 1086 samples) from neoadjuvant clinical trials demonstrated that LAR patients have significantly reduced response (pCR) rates than non-LAR TNBC patients (odds ratio = 2.11, 95% CI: 1.33, 2.89). Moreover, deconvolution of the tumor microenvironment confirmed an enrichment of luminal epithelium corresponding with a decrease in basal and myoepithelium in LAR TNBC tumors. Increased immunosuppression in LAR patients may lead to a decreased presence of cycling T-cells and plasma cells. While, an increased presence of myofibroblast-like cancer-associated cells may impede drug delivery and treatment. In summary, the lower levels of tumor infiltrating lymphocytes (TILs), reduced immune activity in the micro-environment, and lower pCR rates after NAC, suggest that new therapeutic strategies for the LAR TNBC subtype need to be developed.

e17036 Background: Elevated serum CGA is associated with an intrinsic or treatment-related neuroendocrine differentiation in men with mCRPC. We previously demonstrated that elevated serum CGA was negatively associated with OS in men with mCRPC. Fluctuations in serum CGA during mCRPC therapy is not well known. We analyzed the impact of (i) rising serum CGA and (ii) baseline CGA/PSA ratio during treatment to identify associations with AA therapy. Methods: Between June 2013 and August 2015, 92 men with mCRPC were enrolled in a prospective trial (“PROMOTE”; NCT#01953640) with uniform serum processing performed prior to initiating abiraterone acetate/prednisone (AA/P) and serially after 12 weeks of AA/P treatments. Serum CGA was measured using a homogenous automated immunofluorescent assay. Patients (pts) receiving proton pump inhibitors or with abnormal renal function were excluded due to possible false elevations of serum CGA (n = 21 excluded). All patients underwent a composite response assessment at 12-weeks with imaging/PSA/QOL questionnaires. Kaplan Meier estimates, and Cox Regression models were used to calculate association with time-to-treatment failure (TTF) analyses, defined as time from treatment initiation to AA/P discontinuation based on disease progression (BlueSky Statistics, Chicago, IL, USA). Results: Of the 71 eligible pts, 67/71 had paired baseline and 12-week CGA and 70/71 pts had a baseline and a 12-week PSA available. The median baseline CGA was 83.0ng/ml (range: 53.0 - 127.0 ng/ml), median baseline PSA was 14.4 ng/ml (range: 6.4-40.2 ng/ml), and the median TTF was 10 months (range: 6-25 months). The median CGA after 12 weeks of AA/P was 98.0 ng/ml (58.0 -148.0 ng/ml) and we observed a CGA rise in 41/67 (61.2%) pts. An increase in chromogranin was associated with a lower risk of treatment failure (HR: 0.52, p = 0.0181). The median CGA/PSA ratio was 7.8 (2.6 -16.0). An elevated pretreatment CGA/PSA ratio above the median was associated with a lower risk of treatment failure (HR: 0.54 p value = 0.0185). Conclusions: We show that an increasing chromogranin on AA/P and an elevated baseline CGA/PSA in pts with mCRPC were associated with a favorable response to AA/P. Further studies are needed to assess if rising CGA during therapy reflects neuroendocrine differentiation and may indicate a sign of treatment effect targeting the androgen susceptible cells. Clinical trial information: NCT#01953640.

Abstract Internal validation is the most popular evaluation strategy used for drug–target predictive models. The simple random shuffling in the cross-validation, however, is not always ideal to handle large, diverse and copious datasets as it could potentially introduce bias. Hence, these predictive models cannot be comprehensively evaluated to provide insight into their general performance on a variety of use-cases (e.g. permutations of different levels of connectiveness and categories in drug and target space, as well as validations based on different data sources). In this work, we introduce a benchmark, BETA, that aims to address this gap by (i) providing an extensive multipartite network consisting of 0.97 million biomedical concepts and 8.5 million associations, in addition to 62 million drug–drug and protein–protein similarities and (ii) presenting evaluation strategies that reflect seven cases (i.e. general, screening with different connectivity, target and drug screening based on categories, searching for specific drugs and targets and drug repurposing for specific diseases), a total of seven Tests (consisting of 344 Tasks in total) across multiple sampling and validation strategies. Six state-of-the-art methods covering two broad input data types (chemical structure- and gene sequence-based and network-based) were tested across all the developed Tasks. The best-worst performing cases have been analyzed to demonstrate the ability of the proposed benchmark to identify limitations of the tested methods for running over the benchmark tasks. The results highlight BETA as a benchmark in the selection of computational strategies for drug repurposing and target discovery.

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.

Background The treatment of depression in children and adolescents is a substantial public health challenge. This study examined artificial intelligence tools for the prediction of early outcomes in depressed children and adolescents treated with fluoxetine, duloxetine, or placebo. Methods The study samples included training datasets ( N = 271) from patients with major depressive disorder (MDD) treated with fluoxetine and testing datasets from patients with MDD treated with duloxetine ( N = 255) or placebo ( N = 265). Treatment trajectories were generated using probabilistic graphical models (PGMs). Unsupervised machine learning identified specific depressive symptom profiles and related thresholds of improvement during acute treatment. Results Variation in six depressive symptoms (difficulty having fun, social withdrawal, excessive fatigue, irritability, low self‐esteem, and depressed feelings) assessed with the Children’s Depression Rating Scale‐Revised at 4–6 weeks predicted treatment outcomes with fluoxetine at 10–12 weeks with an average accuracy of 73% in the training dataset. The same six symptoms predicted 10–12 week outcomes at 4–6 weeks in (a) duloxetine testing datasets with an average accuracy of 76% and (b) placebo‐treated patients with accuracies of 67%. In placebo‐treated patients, the accuracies of predicting response and remission were similar to antidepressants. Accuracies for predicting nonresponse to placebo treatment were significantly lower than antidepressants. Conclusions PGMs provided clinically meaningful predictions in samples of depressed children and adolescents treated with fluoxetine or duloxetine. Future work should augment PGMs with biological data for refined predictions to guide the selection of pharmacological and psychotherapeutic treatment in children and adolescents with depression.

Abstract Background: Androgen receptor (AR) is widely expressed in ER+ breast cancers. Accumulated evidence showed that AR is a tumor suppressor in ERα+ breast cancers. Enzalutamide (ENZ), an AR antagonist, blocks AR signalling, and was reported to inhibit estrogen-driven tumor growth as effectively as tamoxifen. Hence, this study was performed to further examine the mechanism of action of ENZ in ERα+ breast cancers. Methods: The AR gene was knocked out using the CRISPR-Cas9 system. Four crRNAs targeting AR and trans-activating crRNA were co-transfected to Cas9-positive MCF7 and T47D cells, two ERα+ breast cancer cell lines with relatively low AR levels based on RNA seq. ESR1 knock down was performed using a lentivirus system. MCF7 and T47D cells were infected with the ESR1-shRNA lentivirus and selected by puromycin for 2 weeks. Single clones of knockdown or knockout cells were tested using western blot. MCF7 and T47D cells were collected for RNA-seq and ChIP-seq after treated with DMSO or 10µM ENZ for 6 hours in complete medium. All sequences were aligned to the Human Reference Genome (hg38, UCSC). Differential gene expression was performed using limma package and upstream analysis was done in Ingenuity Pathway Analysis software. ChIP peaks were called using MACS2 and overlapping was analyzed using ChIPpeakAnno package in R. Tritium labeled ENZ or estradiol were incubated with ERα overnight. The bound radioactivity was measured using a Beckmann LS 6500 liquidscintillation counter. Results: We found the cell growth inhibition effect of ENZ was little impaired by AR gene knock out in MCF7 and T47D cells as was expected. As ENZ has been shown to inhibit estrogen-driven tumor growth, we performed studies to understand the mechanism of ENZ.We performed RNA-seq and identified 193 differential expressed genes (76 up and 117 down) between DMSO and ENZ-treated MCF7 cells (FC>2 or <0.5, FDR<0.05). Upstream analysis showed that ESR1 might be the upstream regulator of those differentially expressed genes and ESR1 signaling was predicted to be inhibited after ENZ treatment (P=1.69×10-10). To examine the alteration of ERα genomic binding, we performed global ERα ChIP-seq and found 39.58% (8,681/21,933) of ERα-bound sites were abolished by ENZ and the binding intensity was significantly decreased upon ENZ treatment in 12,868 shared peaks. Moreover, radiolabled binding assays showed that ENZ displaced estrogen binding to ERα and directly bound to ERα with a KD= 399.60nM. We further observed a reduction of proliferation inhibition of ENZ in ESR1-KD cells compared with control cells. This suggests that ENZ inhibits ER+ cell growth by displacing E2 from ERα binding sites and subsequently diminishes ERα genomic binding and blocks ERα signaling in ER+ cancers. Conclusion: We found that enzalutamide inhibits cell growth not through AR but by antagonizing ERα activity in MCF7 and T47D ER+ cells. These results reveal ER is the main factor affecting enzalutamide efficacy in these two ERα+ breast cancer cell lines. Further clinical trials are needed to investigate AR antagonists in ERα+ breast cancers. Citation Format: Lixuan Wei, Jia Yu, Huanyao Gao, Huan Zhang, Thanh Nguyen, Yayun Gu, Richard M. Weinshilboum, James N. Ingle, Liewei Wang. Estrogen receptor is a target of enzalutamide in ER+ breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD1-03.

Abstract Background: Cyclin dependent 4/6 kinase inhibitors (CDK4/6i) and endocrine therapy (ET) have improved progression-free survival (PFS) and overall survival in HR+ MBC, but progression of disease ultimately occurs. Apart from HR+ status, there are no clinically available biomarkers that enable oncologists to determine prognosis and predict response to CDK4/6i. An emerging biomarker is serum thymidine kinase 1 (TK1), a secreted marker of proliferation that is prognostic in pts with HR+ HER2- MBC. High levels of TKa are associated with inferior PFS, whereas pts with low TKa levels pretreatment, or TKa levels that decrease on ET and a CDK4/6i, have superior PFS. Notably, TKa levels rebound ≥ 5 days off Pb, with resumption of cell cycling. PROMISE (NCT0281902) is a prospective study that enrolled women with HR+ MBC starting Pb + letrozole (L) in the 1st line [FL] or Pb + fulvestrant in the 2nd line [SL] setting. The trial includes a comprehensive “omic” assessment of blood, tumor, urine and the fecal microbiome to identify novel genomic variants and pathways associated with an early decline in TKa (measured after 2 months or end of cycle [C]2) and PFS. Here, we report the association between i) pre-treatment TKa (pre-TKa) levels and PFS (i.e. from registration to the 1st disease event) and ii) TKa levels at the end of C2 (C2-TKa) and PFS-2 (i.e. from the start of C3 to the 1st disease event).Methods: TKa testing was performed using the DiviTum assay (Biovica). TKa+ disease was defined as ≥ 200 Du/L and TKa- disease as below limit of detection to 200 Du/L. Log-rank test and univariate Cox modeling were used to assess the association between pre-TKa levels and PFS and between end of C2-TKa levels and PFS-2. The database was locked on June 28, 2021. Results: Of 68 pts enrolled, 4 were ineligible and pre-TKa data was unavailable for 4. Of the remaining 60 pts (45 FL, 15 SL), the percentage of pts with pre-TKa+ disease was 33.3% in FL (15/45, 95% CI: 20.0-49.0%), and 46.7% (7/15, 95% CI: 21.4-71.9%) in the SL. The median follow-up time for pts on study was 24 months (range: 2-42 months). There were 22 disease events (13 in FL, 9 in SL). In the FL setting, PFS was significantly shorter for preTKa+ pts compared to preTKa- pts (HR: 4.15, 95% CI:1.35-12.74; p=0.007), but not for SL pts (HR: 1.11, 95% CI: 0.30-4.18, p=0.875). End of C2 TKa data was obtained for pts while on Pb (n=5), or after stopping Pb as follows: 1-4 days (n=9), 5-8 days (n=28) and 9-36 days (n=11). PFS-2 was not associated with C2-TKa in the FL (p=0.834) or SL (p=0.454) settings. An analysis of TKa levels by metastatic site will be presented at the meeting.Conclusions: A secreted biomarker of proliferation (TK1) obtained prior to initiating CDK4/6i and ET for the treatment of HR+ MBC is associated with PFS in pts receiving 1st line Pb + L, but not in those receiving 2nd line Pb + fulvestrant. While the end of C2 TKa levels were not associated with PFS, the interpretability of these data are limited, given treatment delays (0-36 days) prior to starting C3 that may result in TKa rebound. Future studies evaluating the predictive nature of TKa and Pb response should focus on earlier timepoints while on drug. Citation Format: Ciara C O'Sullivan, Jun He, Jason Sinnwell, Vera J Suman, Krishna R Kalari, Peter T Vedell, Ann M Moyer, Xiaojia Tang, Kevin J Thompson, Abe Eyman Casey, Alvaro Moreno-Aspitia, Donald W Northfelt, Minetta C Liu, Tufia C Haddad, Saranya Chumsri, Brendan McMenomy, Prema Peethambaram, Kathryn J Ruddy, Karthik V Giridhar, Roberto A Leon-Ferre, Mattias Bergqvist, Adrian Nordmark, Richard M Weinshilboum, Liewei Wang, Matthew P Goetz. Serum thymidine kinase 1 activity (TKa) levels and progression-free survival (PFS) in patients (pts) with hormone receptor positive (HR+) HER2-negative metastatic breast cancer (MBC) on palbociclib (Pb) and endocrine therapy (ET) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-22.

Abstract Background: Cyclin-dependent 4/6 kinase inhibitors (CDK4/6i) and endocrine therapy (ET) have improved progression-free survival (PFS) and overall survival in hormone-receptor-positive (HR+) metastatic breast cancer (MBC), but endocrine resistance is a major challenge. PROMISE [NCT0281902; n=63] is a multicenter study that enrolled women with HR+ HER2- MBC commencing palbociclib (Pb) with letrozole (1st line [1L]) or fulvestrant (2nd line [2L]), and was designed to perform a comprehensive “omic” assessment of prospectively collected biospecimens (pre-treatment (M1), at 2 months (M2), and at disease progression). The goal is to identify novel genomic variants and pathways associated with resistance to CDK4/6i and ET and PFS outcomes. Here we report the association between the proteomic, metabolomics, and lipidomics data generated from pre-Pb and 2-month serum samples and PFS. Methods: Untargeted mass spectrometry data was generated from Metabolon, assaying 1308 metabolites and 831 lipids. Additionally, 1436 proteins were assayed on the Olink platform. Cox proportional hazard models were used to evaluate the univariate hazard ratio (HR) for all features with respect to PFS. The analyses were performed on samples from 45 patients (N=33 1Lwith 9 progression events and 12 2L with 8 progression events), obtained from M1 and M2 timepoints on Pb + ET. Enrichment analysis p-values are calculated using Fisher’s exact test. Results: Proteomics: In the M1 timepoint, 93 and 43 proteins were associated with PFS in the 1L and 2L settings, respectively; inflammation genes were enriched among the 1L setting (p= 0.034); 33 proteins presented HRs ranging between 0.026 and 0.56. The FABP9 protein (HR of 1.98, 95% CI 1.02-3.83) was associated with worse PFS. Conversely, inflammation genes were not observed to be enriched in 2L. In the M2 timepoint, we observed 60 and 21 proteins significantly associated with PFS, but no biological function was enriched in 1L and 2L. Metabolites: In the M1 timepoint, metabolism of the sulfur-containing amino acids (methionine, cysteine, SAM and taurine) were enriched in the 1L setting (p= 0.035, HR range 0.15-0.33); and the branched-chain amino acids (leucine, isoleucine, and valine) were significantly associated with PFS in the 2L setting (p= 0.028, HR range 0.013-0.33). At the M2 timepoint, the amino acids were no longer enriched, but fatty acid metabolism was significantly enriched for both 1L and 2L (p= 0.048 and 0.067, respectively). Pathways involving lipids, amino acids, and xenobiotics were enriched in metabolites related to PFS (p <0.05) for both treatment lines at M1 and M2. Lipidomics: In the M1 timepoint, 10 and 19 lipids were associated with PFS for 1L and 2L, respectively. The most notable lipid associated with worse PFS in the 1L was an 18 carbon phosphatidylinositol, PI(18:1/18:2), (HR 7.34 (CI 1.27-42.50); 8 triglycerides were associated with improved PFS (HR range 0.39 and 0.55). In 2L, the 19 lipids associated with PFS included 12 phosphatidylcholines (enrichment p = 5.6X10-8). In the M2 timepoint, 15 and 8 lipids were significantly associated with PFS for 1L and 2L. An enrichment of phosphatidylinositols was observed in 1L (p= 1.2X10-5); none were observed in the 2L.Future Directions: Networks are being constructed using the proximity scores of the proteins, lipids, and metabolites associated with PFS in M1 and M2 for 1L and 2L. Network similarities and analyses will be conducted.Conclusion: Distinct multi-omic changes identified in serum samples obtained from PROMISE participants M1 and M2 on Pb correlate with disease progression in both 1L and 2L settings. Additionally, validation studies will determine the significance of these findings. Citation Format: Krishna R. Kalari, Kevin J. Thompson, Jason Sinnwell, Xiaojia Tang, Vera J. Suman, Jun He, Seul Kee Byeon, Akhilesh Pandey, Abe Eyman Casey, Peter T. Vedell, Ann M. Moyer, Alvaro Moreno-Aspitia, Donald W. Northfelt, Minetta C. Liu, Tufia C. Haddad, Saranya Chumsri, Prema Peethambaram, Kathryn J. Ruddy, Karthik V. Giridhar, Roberto A. Leon-Ferre, Richard M. Weinshilboum, Liewei Wang, Ciara C. O’ Sullivan, Matthew P. Goetz. Multiomics data reveal novel biomarkers for CDK4/6 resistance [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-01-03.