Reverse Phase Protein Array Data Research Articles

NGMA-3. Use of multi-omics data to initialize and validate a causal model of glioblastoma stem cell signaling

Glioblastomas and glioblastoma stem cells are heterogeneous with respect to mutations, gene expression, and response to drugs. To make predictive responses of individual GBM stem cell lines to drugs, we have constructed a causal model of glioblastoma stem cell signaling. The core model was built starting from pathways identified from TCGA mutation data with the addition of the Jak/STAT, Hedgehog, and Notch pathways. Elements and relations between them were validated and extended using the PCNet interaction database and the INDRA database which includes machine read extractions from the biomedical literature. The result is a high confidence executable model consisting of 209 element and 370 rules of interaction between the elements. Stochastic simulations of the model provide dynamic (quantile) changes in time and responses to perturbations. The output provides activity of individual nodes as well as a cellular output state of cell cycle progression, apoptosis, or differentiation. To simulate the responses of individual cell lines to kinase inhibitors, the model was initialized using DNA sequencing data, RNA-seq, and reverse phase protein array (RPPA) data from each cell line. Comparing the results of the simulations to the drug responses of 11 different kinase targets, the model was 88% accurate in predicting effects on growth and survival. The model was further tested by comparing the effects of Mek inhibition of each of the cell lines in model to the results observed in the RPPA data which overlap by 127 elements. In this case, there was 62% concordance between the model and data when binned into quintiles. Discrepancies between the model predictions and the data are being investigated to determine whether the model logic or extent needs to be revised to improve the model. This modeling approach is a step toward developing algorithms for personalized therapeutics for GBM based on multi-omics data.

Abstract 160: LASSO-based protein signatures for survival prediction in human cancer cohorts

Abstract Background: Large-scale multi-omics data characterizing human tumors are increasingly available and can be leveraged to develop a deeper understanding of biological processes and predict clinical outcomes. Reverse-phase protein array (RPPA) is a high-throughput, antibody-based method that provides a more direct assessment of cellular activity compared to DNA and RNA sequencing, which generate data that do not always correlate with protein expression. Multiple studies have demonstrated the prognostic value of RPPA data. Some of these studies have used pathway-driven approaches, relying on prior knowledge from the literature to group proteins into biological pathways, to develop prognostic signatures or predictors of treatment response. Methods: We obtained normalized RPPA data for up to 258 total, cleaved, acetylated, or phosphorylated protein species from The Cancer Proteome Atlas (TCPA). Starting from a published RPPA-based seven-protein signature of receptor tyrosine kinase (RTK) pathway activity in the form of an unweighted sum of the seven protein measurements, shown to have prognostic value in a 445-patient renal clear cell carcinoma cohort (TCGA-KIRC), we demonstrated that strong stratification of patients into high and low risk groups can be achieved by using a statistical approach—LASSO regression—with no a priori biological knowledge, to select from the 233 proteins and optimally combine their RPPA measurements into a weighted risk score. Method performance was assessed using two unbiased approaches: 1) 10 iterations of 3-fold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan-Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Results: For the first evaluation approach, the median hazard ratio between high and low risk groups across the held-out folds in the cross-validation based on the 7-protein RTK score was 2.4, compared to 3.3 when using the risk score derived by LASSO applied to the training data folds. Furthermore, the median difference in overall survival probability at 5 years based on the LASSO-derived risk score was 32.8%, compared to 25.2% when using the 7-protein RTK score. The permutation test p values were 5.0e-4 for both the RTK pathway-driven and the LASSO data-driven approaches. Finally, we demonstrated the applicability and performance of our approach for overall survival prediction in additional TCGA cohorts; namely, ovarian serous cystadenocarcinoma (TCGA-OVCA), sarcoma (TCGA-SARC), and cutaneous melanoma (TCGA-SKCM). Conclusions: The data-driven nature of our LASSO-based approach makes it versatile and particularly well-suited for the discovery of unexplored protein/disease associations that could aid in therapeutic discovery. Citation Format: Mariam M. Konaté, Ming-Chung Li, Lisa McShane, Yingdong Zhao. LASSO-based protein signatures for survival prediction in human cancer cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 160.

APTO-253 Interaction with G-Quadruplex DNA Is Linked to Inhibition of c-Myc Expression, Induction of DNA Damage, and Generation of Synthetic Lethality in Cells with BRCA1/2 Impairment

APTO-253 is a Phase 1 clinical stage small molecule that selectively kills acute myeloid leukemia (AML) cells in the absence of toxicity to normal peripheral blood mononuclear (PBMCs) and bone marrow cells in various animal species and humans. Previously, APTO-253 was reported to exhibit concentration and time dependent inhibition of c-MYC oncogene expression in AML cells and consequently to induce G0/G1 cell cycle arrest and apoptosis, but not affect normal PBMCs (58th ASH abstract #1716). Current mechanistic studies demonstrated that APTO-253 modulates c-MYC at the transcriptional level by decreasing acetylated H3K27 at its promoters and additionally by destabilizing c-MYC mRNA. In addition, differential gene expression analysis of RNA-seq and reverse phase protein array (RPPA) data highlighted a role for c-MYC in the mechanism of APTO-253 (GO terms - Down regulated by c-MYC p-value 6E-26, Gene promoters bound by c-MYC p-value 4.2 E-10, ChIP targets of c-MYC p-value 3.3E-8). Furthermore, from the RPPA data we observed an increase in p-Chk1, p-Chk2, γH2Ax, and total p53 and E2F1, all of which are indicative of activation of DNA damage response pathways. This was accompanied by elevated levels of XBP1, GRP78, and p-p38 that point towards cellular stress response signaling (GO term Regulation of Cell Stress, p-value 1.89E-8). Subsequent work demonstrated that APTO-253 induced DNA damage as documented by gH2AX foci formation and the neutral COMET assay, and exhibited synthetic lethality in cells with BRCA1/2 mutations that have impaired ability to repair DNA damage by homologous recombination (abstract submitted to 59th ASH annual meeting). This amalgam of data, coupled with structural informatics analyses, suggested a mechanism of action involving the binding and/or stabilization of G-quadruplex (G4) DNA motifs. Intracellular pharmacokinetic studies revealed that APTO-253 converts from a monomer to a ferrous complex. PCR stop and modified FRET assays demonstrated that the APTO-253 ferrous complex Fe(253)3 has activity similar to that of TMPyP4, a well-established G4 ligand, to bind/stabilize G4 structures in telomere sequences (∆T1/2 vs concentration slope 7.7 ±2.7 and 10.67 ±1.23 for Fe(253)3 and TMPyP4, respectively), in MYC promoter sequences (5.07 ±1.56 and 5.62 ±0.75, respectively) and in rRNA sequences (4.6 ±1.1 and 5.6 ±0.88, respectively). Although APTO-253 may participate in multiple mechanistic events, the effect of APTO-253 on c-MYC expression, cell cycle arrest and DNA damage, as well as synthetic lethality in cells with compromised DNA repair mechanisms, can be explained by the action of the Fe(253)3 complex on G-quadruplex DNA motifs. DisclosuresLocal:Aptose Biosciences, Inc.: Employment. Zhang:Aptose Biosciences, Inc.: Employment. Benbatoul:Aptose Biosciences, Inc.: Employment. Folger:Aptose Biosciences, Inc.: Employment. Sheng:Aptose Biosciences, Inc.: Employment. Howell:Aptose Biosciences, Inc.: Membership on an entity's Board of Directors or advisory committees. Rice:Aptose Biosciences, Inc.: Employment, Equity Ownership, Patents & Royalties.

Inhibition of Unc-51 like Autophagy Activating Kinase 1 (ULK1) Is Highly Synergistic with Chemotherapy and Bcl2 Inhibition in Acute Myeloid Leukemia (AML)

IntroductionAcquired resistance to chemotherapy and targeted therapies in AML may be mediated through autophagy. Bcl2 inhibition has also been reported to induce autophagy1. Therapeutic autophagy inhibition has been challenging because of limited druggable targets and pathway redundancy. Our preclinical work confirmed that Atg7 inhibition potentiates chemotherapy effects in AML2. While Atg7 is an E1-like activating enzyme,ULK1 is an apical kinase in the autophagy cascade and the only S/T kinase in the core autophagy pathway that phosphorylates multiple targets (Atg13, Beclin1 and VPS34). ULK1 initiates autophagosome formation and maturation. With the recent development of ULK1 inhibitors we were enabled to investigate the effects of ULK1 inhibition in AML.MethodsFirst we confirmed that chemotherapy (cytarabine, Ara-C) and Bcl2 inhibitor ABT199 induce autophagy in AML cells by LC3 quantification. Next, we studied potential synergy of these agents with ULK1 inhibitor, SBI-0206965 (SBI) in inhibiting cell proliferation and inducing apoptosis. For further insights into the mechanisms of synergy, we conducted large-scale proteomics analyses by reverse phase protein array (RPPA) and mass cytometry (CyTOF).ResultsAs a single agent SBI showed activity against a wide range of AML cell lines (IC50: 250 nM to 3.5 uM) and stem and progenitor cell populations (CD34+/CD38-) in primary AML samples with FLT3-ITD or p53 mutations, while sparing normal CD34+/CD38- cells. Immunoblotting confirmed target inhibition (Fig 1a) and apoptosis induction (Fig 1b).Treatment with Ara-C and ABT199 induced autophagy, which was reversed by SBI (Fig 2). Confirming our hypothesis, SBI showed significant synergy with both Ara-C (CI: 0.52) and ABT199 (CI: 0.16). Additional synergy was seen with FLT3-ITD inhibitor Sorafenib and MEK inhibitor Trametinib.Consistent with previous reports that autophagy deficiency induces DNA damage due to loss of ROS scavenging capacity, downregulation of DNA repair proteins and impaired protein complex formation at the sites of DNA damage3, we found that ULK1 inhibition results in elevated ROS generation which could be reversed by the ROS inhibitor N-acetylcysteine (NAC) (Fig 3a). We also found induction of DNA damage (Fig 3b). Autophagy deficiency has been recently shown to regulate DNA repair via Chk1 downregulation4. Our RPPA data showed significant decrease in cell cycle regulators phosphoS807/811 Rb, CDK1 and Chk1 (Fig 3b). Cell cycle analysis by EdU incorporation assay showed G1 arrest upon treatment with SBI (Fig 3c). In contrast, Bcl2A1 (pro-survival Bcl2 family member) was the most upregulated protein after treatment with SBI; rationalizing our combination studies with ABT199, which exhibits profound synergy (CI: 0.16) associated with increased cleaved Caspase7 and DNA damage (g-H2AX) (Fig 3b).Combinatorial studies with Ara-C also showed increased DNA damage (Fig 4a). Finally, CyTOF confirmed decreased phosphorylation of important signaling molecules like Akt, Erk1/2, MEK1/2, JNK, p38) upon SBI treatment (Fig 4b).We are conducting confirmatory mechanistic studies (changes in DNA damage response, ROS generation, etc.) by genetic silencing of ULK1 as well as studying the effect of drug combinations in the presence or absence of ULK1 inhibition in in vivo models of AML.ConclusionULK1 inhibitor SBI-0206965 effectively reverses therapy induced autophagy and synergizes with chemotherapy and Bcl2 inhibition imparting anti-leukemic effects, thus establishing a therapeutic rationale for ULK1 inhibition in AML. We are pursuing studies to validate the role of ULK1 inhibition in leukemia establishment, engraftment and survival in mice.

A novel role of ADGRF1 (GPR110) in promoting cellular quiescence and chemoresistance in human epidermal growth factor receptor 2‐positive breast cancer

Purpose Adhesion G protein coupled receptors (aGPCRs) remains least explored GPCRs family for their role in health and disease. The aGPCR, ADGRF1 (GPR110), is overexpressed and predicts poor survival in various cancer types. However, ADGRF1's coupling to G proteins and downstream pathways remain unknown in cancer. We have reported that ADGRF1 is overexpressed in tumorigenic population and in anti-HER2 therapy-resistant derivatives of various HER2+ breast cancer (BC) cell line models. Further, we have reported that ADGRF1 knockdown reduces tumorigenesis and metastasis in HER2+ BC cells. In this study, we evaluated the effects of ADGRF1 overexpression (OE) on tumorigenesis, signaling pathways, and outcomes in HER2+ BC. Methods Stable clones of 2 HER2+ BC cell lines, BT474 and SKBR3, were generated to overexpress ADGRF1 construct in doxycycline-inducible manner. The effect of ADGRF1 on tumorigenesis was evaluated in vitro using soft agar assays, mammosphere assay, and Aldefluor assay. The effect on the HER pathway was evaluated by assessing expression of phospho- and total-HER1 and -HER2 and potency of anti-HER2 drugs. G protein coupling of ADGRF1 was determined by co-immunoprecipitation of Gαs and Gαq and detecting second messengers, cAMP and IP1, in presence/absence of synaptamide, an ADGRF1 agonist. Downstream pathways of ADGRF1 were explored by RNAseq and Reverse Phase Protein Arrays (RPPA) and functional assays. ADGRF1 expression was assessed in BC patients from The Cancer Genome Atlas. ADGRF1 OE effects on survival was evaluated using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Results ADGRF1 OE enhanced the number of colonies and mammospheres and increased Aldefluor+ tumorigenic cell population, suggesting a role in tumorigenesis. ADGRF1 OE did not alter the expression total- or phospho-HER1/-HER2 proteins or efficacy of anti-HER2 drugs. Overexpressed ADGRF1 co-immunoprecipitated with Gαs and Gαq proteins and increased cAMP and IP1. However, inhibition of only the Gαs pathway by SQ22536 reversed the pro-tumorigenic effects of ADGRF1 OE, suggesting pro-tumorigenic effects of the ADGRF1-Gαs pathway. Synaptamide, did not alter cAMP or IP1 with/without ADGRF1 OE or the number of mammospheres. Integration of RNA-Seq and RPPA data showed that ADGRF1 OE inhibited cell cycle. We detected G0/1 arrest by cell cycle analysis with ADGRF1 OE. The protein level of the proliferation marker Ki67 was reduced upon ADGRF1 OE. Also, ADGRF1 OE led to a 10-fold reduction in potency of docetaxel, a chemotherapy drug used in HER2+ BC. ADGRF1 was overexpressed and amplified in basal and HER2 compared to luminal A and B BCs. High ADGRF1 expression predicted poor survival in HER2 subtype, but not in basal BC. Conclusions: ADGRF1 represents a novel drug target in HER2+ BC, warranting discovery of novel ADGRF1 antagonists.

The Marine Natural Product Furospinulosin 1 Induces Apoptosis in MDA-MB-231 Triple Negative Breast Cancer Cell Spheroids, But Not in Cells Grown Traditionally with Longer Treatment

Cancer cells grown in spheroid conditions interact with each other and the extracellular matrix, providing a better representation of the in vivo environment than two-dimensional cultures and are a more clinically relevant model. A discrete screening of genetically diverse marine samples in the spheroid assay led to the identification of a novel activity for the known compound furospinulosin 1. This compound shows activity against MDA-MB-231 triple negative breast cancer cells grown as spheroids and treated for 24 or 48 h. No cytotoxicity was seen in traditional two-dimensional adherent cultures treated for a longer time (72 h). A reverse phase protein array (RPPA) confirmed the limited activity of the compound in cells grown traditionally and revealed changes in protein expression when cells are grown as spheroids that are associated with better clinical prognosis. Analysis of the RPPA data through the Broad institute’s connectivity map suggested the hypothesis that furospinulosin 1 functions as an MEK inhibitor. Analysis of the RPPA data through STRING supports the apoptosis observed. The selectivity exhibited by furospinulosin 1 for triple negative breast cancer cells only when grown as spheroids makes it an interesting compound with strong therapeutic potential that merits further study.

Abstract PD9-04: Identification of biomarkers associated with therapeutic resistance: Quantitative protein/phosphoprotein analysis of ~750 patients across 8 arms of the neoadjuvant I-SPY 2 TRIAL for high-risk early stage breast cancer

Abstract Background: The goal of I-SPY 2 is to rapidly test novel therapies in addition to standard of care in high-risk breast cancer patients. It has resulted in increasing response rates, where pCR rates in TNBC and HR-HER2+ subsets have reached ~60% and ~75%, respectively. Yet, there remains a sizeable subset of non-responders, especially among HR+ patients. Identification of ‘universal’ resistance mechanisms may guide rational selection of agents to improve these patient's outcomes. Thus, we analyzed reverse phase protein array (RPPA) based quantitative protein/phosphoprotein data across arms to assess whether there are common mechanisms rendering these cancers resistant to all agent classes tested to date. Methods: 736 patients (260 HR+HER2-, 252 TN, 142 HR+HER2-, and 82 HR-HER2+; over 8 arms: 194 Ctr, 105 neratinib (N), 63 veliparib/carboplatin (VC), 128 AMG386 (anti-ANG1/2), 87 MK2206 (anti-AKT), 43 TH/pertuzumab (P), 49 TDM1/P, and 67 pembrolizumab (Pembro)) with pCR and RPPA data at the pre-treatment time point were considered for this analysis. 141 RPPA endpoints representing key cancer pathways were assessed for association with pCR using logistic regression modeling, with HR, HER2 and treatment arm as covariates (likelihood ratio test; p<0.05). Analysis was also performed in HR/HER2 subsets and within treatment arms. Markers were analyzed individually; multiple comparison correction (Benjamini-Hochberg) was applied to p-values. Our analysis is exploratory, and does not adjust for other biomarkers outside this study. Results: Prior to FDR correction, high levels of Cyclin D1, a cell cycle protein implicated in estrogen-mediated DNA damage repair, associate with non-pCR in the population as a whole and within all subtypes except for the HR-HER2+ subset; an association that retains significance after FDR correction overall as well as in HER2- and HR+HER2- subsets. Within individual arms, high Cyclin D1 predicted non-response in VC, control, and AMG386; and trends toward association in Pembro and N. In addition, high quantitative ER and phospho-androgen receptor (pAR; S650) associate with non-pCR in the population as a whole and in the HR+HER2- subset. For both ER and pAR the strongest association with non-pCR was in the Pembro arm. Candidates for universal sensitivity signals include immune proteins JAK-STAT (pSTAT5 (Y694) and pSTAT1 (Y701)) overall; and pERBB2/pEGFR for HER2+ patients. Conclusions: High levels of Cyclin D1, but not other cell cycle proteins, predict non-response to chemo-/targeted-therapy across arms and subtypes, suggesting that agents specifically targeting Cyclin D1 may increase chemo-sensitivity. ER/phospho-AR as global resistance signals suggest inclusion of anti-AR agents in combination therapy, and the need for new endocrine-based approaches. Citation Format: Julia Wulfkuhle, Denise Wolf, Christina Yau, Lamorna Brown-Swigart, Rosa I Gallagher, Gillian Hirst, Laura Sit, Smita Asare, I-SPY 2 TRIAL Investigators, Nola Hylton, Angela DeMichele, Douglas Yee, Jo Chien, Hope Rugo, John Park, Kathy Albain, Rita Nanda, Debu Tripathy, Richard Schwab, Don Berry, Laura Esserman, Laura van t' Veer, Emanual Petricoin, III. Identification of biomarkers associated with therapeutic resistance: Quantitative protein/phosphoprotein analysis of ~750 patients across 8 arms of the neoadjuvant I-SPY 2 TRIAL for high-risk early stage breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD9-04.

Reverse Phase Protein Array Reveals Correlation of Retinoic Acid Metabolism With Cardiomyopathy in Friedreich's Ataxia

Identifying biomarkers is important for assessment of disease progression, prediction of symptom development, and determination of treatment effectiveness. While unbiased analyses of differential gene expression using next-generation sequencing methods are now routinely conducted, proteomics studies are more challenging because of traditional methods predominantly being low throughput and offering a limited dynamic range for simultaneous detection of hundreds of proteins that drastically differ in their intracellular abundance. We utilized a sensitive and high-throughput proteomic technique, reverse phase protein array (RPPA), to attain protein expression profiles of primary fibroblasts obtained from patients with Friedreich's ataxia (FRDA) and unaffected controls (CTRLs). The RPPA was designed to detect 217 proteins or phosphorylated proteins by individual antibody, and the specificity of each antibody was validated prior to the experiment. Among 62 fibroblast samples (44 FRDA and 18 CTRLs) analyzed, 30 proteins/phosphoproteins were significantly changed in FRDA fibroblasts compared with CTRL cells (p < 0.05), mostly representing signaling molecules and metabolic enzymes. As expected, frataxin was significantly downregulated in FRDA samples, thus serving as an internal CTRL for assay integrity. Extensive bioinformatics analyses were conducted to correlate differentially expressed proteins with critical disease parameters (e.g., selected symptoms, age of onset, guanine–adenine–adenine sizes, frataxin levels, and Functional Assessment Rating Scale scores). Members of the integrin family of proteins specifically associated with hearing loss in FRDA. Also, RPPA data, combined with results of transcriptome profiling, uncovered defects in the retinoic acid metabolism pathway in FRDA samples. Moreover, expression of aldehyde dehydrogenase family 1 member A3 differed significantly between cardiomyopathy-positive and cardiomyopathy-negative FRDA cohorts, demonstrating that metabolites such as retinol, retinal, or retinoic acid could become potential predictive biomarkers of cardiac presentation in FRDA.

Intratumor Heterogeneity Correlates With Reduced Immune Activity and Worse Survival in Melanoma Patients.

BackgroundHuman malignant melanoma is a highly aggressive, heterogeneous and drug-resistant cancer. Due to a high number of clones, harboring various mutations that affect key pathways, there is an exceptional level of phenotypic variation and intratumor heterogeneity (ITH) in melanoma. This poses a significant challenge to personalized cancer medicine. Hitherto, it remains unclear to what extent the heterogeneity of melanoma affects the immune microenvironment. Herein, we explore the interaction between the tumor heterogeneity and the host immune response in a melanoma cohort utilizing The Cancer Genome Atlas (TCGA).MethodsClonal Heterogeneity Analysis Tool (CHAT) was used to estimate intratumor heterogeneity, and immune cell composition was estimated using CIBERSORT. The Overall Survival (OS) among groups was analyzed using Kaplan–Meier curves with the log-rank test and multivariate cox regression. RNA-seq data were evaluated to identify differentially expressed immunomodulatory genes. The reverse phase protein array (RPPA) data platform was used to validate immune responses at protein level.ResultsTumors with high heterogeneity were associated with decreased overall survival (p = 0.027). High CHAT tumors were correlated with less infiltration by anti-tumor CD8 T cells (p = 0.0049), T follicular cells (p = 0.00091), and M1 macrophages (p = 0.0028), whereas tumor-promoting M2 macrophages were increased (p = 0.02). High CHAT tumors correlated with a reduced expression of immunomodulatory genes, particularly Programmed Cell Death 1 (PD1) and its ligand PD-L1. In addition, high CHAT tumors exhibited lower immune Cytotoxic T lymphocytes (CTLs)-mediated toxicity pathway score (p = 2.9E−07) and cytotoxic pathway score (p = 2.9E−08). High CHAT tumors were also associated with a lower protein level of immune-regulatory kinases, such as lymphocyte-specific protein tyrosine kinase (LCK) (p = 3.4e−5) and spleen tyrosine kinase (SYK) (p = 0.0011).ConclusionsHighly heterogeneous melanoma tumors are associated with reduced immune cell infiltration and immune response activation as well as decreased survival. Our results reveal that intratumor heterogeneity is an indicative factor for patient survival due to its impact on anti-tumor immune response.

The Capacity of the Ovarian Cancer Tumor Microenvironment to Integrate Inflammation Signaling Conveys a Shorter Disease-free Interval.

Ovarian cancer has one of the highest deaths to incidence ratios across all cancers. Initial chemotherapy is effective, but most patients develop chemoresistant disease. Mechanisms driving clinical chemo-response or -resistance are not well-understood. However, achieving optimal surgical cytoreduction improves survival, and cytoreduction is improved by neoadjuvant chemotherapy (NACT). NACT offers a window to profile pre- versus post-NACT tumors, which we used to identify chemotherapy-induced changes to the tumor microenvironment. We obtained matched pre- and post-NACT archival tumor tissues from patients with high-grade serous ovarian cancer (patient, n = 6). We measured mRNA levels of 770 genes (756 genes/14 housekeeping genes, NanoString Technologies), and performed reverse phase protein array (RPPA) on a subset of matched tumors. We examined cytokine levels in pre-NACT ascites samples (n = 39) by ELISAs. A tissue microarray with 128 annotated ovarian tumors expanded the transcriptional, RPPA, and cytokine data by multispectral IHC. The most upregulated gene post-NACT was IL6 (16.79-fold). RPPA data were concordant with mRNA, consistent with elevated immune infiltration. Elevated IL6 in pre-NACT ascites specimens correlated with a shorter time to recurrence. Integrating NanoString (n = 12), RPPA (n = 4), and cytokine (n = 39) studies identified an activated inflammatory signaling network and induced IL6 and IER3 (immediate early response 3) post-NACT, associated with poor chemo-response and time to recurrence. Multiomics profiling of ovarian tumor samples pre- and post-NACT provides unique insight into chemo-induced changes to the tumor microenvironment. We identified a novel IL6/IER3 signaling axis that may drive chemoresistance and disease recurrence.

Integrative analysis of multi-platform reverse-phase protein array data for the pharmacodynamic assessment of response to targeted therapies

Reverse-phase protein array (RPPA) technology uses panels of high-specificity antibodies to measure proteins and protein post-translational modifications in cells and tissues. The approach offers sensitive and precise quantification of large numbers of samples and has thus found applications in the analysis of clinical and pre-clinical samples. For effective integration into drug development and clinical practice, robust assays with consistent results are essential. Leveraging a collaborative RPPA model, we set out to assess the variability between three different RPPA platforms using distinct instrument set-ups and workflows. Employing multiple RPPA-based approaches operated across distinct laboratories, we characterised a range of human breast cancer cells and their protein-level responses to two clinically relevant cancer drugs. We integrated multi-platform RPPA data and used unsupervised learning to identify protein expression and phosphorylation signatures that were not dependent on RPPA platform and analysis workflow. Our findings indicate that proteomic analyses of cancer cell lines using different RPPA platforms can identify concordant profiles of response to pharmacological inhibition, including when using different antibodies to measure the same target antigens. These results highlight the robustness and the reproducibility of RPPA technology and its capacity to identify protein markers of disease or response to therapy.

Photoreceptor Degeneration in Pro23His Transgenic Rats (Line 3) Involves Autophagic and Necroptotic Mechanisms.

Photoreceptor death contributes to 50% of irreversible vision loss in the western world. Pro23His (P23H) transgenic albino rat strains are widely used models for the most common rhodopsin gene mutation associated with the autosomal dominant form of retinitis pigmentosa. However, the mechanism(s) by which photoreceptor death occurs are not well understood and were the principal aim of this study. We first used electroretinogram recording and optical coherence tomography to confirm the time course of functional and structural loss. Electroretinogram analyses revealed significantly decreased rod photoreceptor (a-wave), bipolar cell (b-wave) and amacrine cell responses (oscillatory potentials) from P30 onward. The cone-mediated b-wave was also decreased from P30. TUNEL analysis showed extensive cell death at P18, with continued labeling detected until P30. Focused gene expression arrays indicated activation of, apoptosis, autophagy and necroptosis in whole retina from P14-18. However, analysis of mitochondrial permeability changes (ΔΨm) using JC-1 dye, combined with immunofluorescence markers for caspase-dependent (cleaved caspase-3) and caspase-independent (AIF) cell death pathways, indicated mitochondrial-mediated cell death was not a major contributor to photoreceptor death. By contrast, reverse-phase protein array data combined with RIPK3 and phospho-MLKL immunofluorescence indicated widespread necroptosis as the predominant mechanism of photoreceptor death. These findings highlight the complexity of mechanisms involved in photoreceptor death in the Pro23His rat model of degeneration and suggest therapies that target necroptosis should be considered for their potential to reduce photoreceptor death.

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.

Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With increasing mortality figures, the accurate prediction of prognosis has become essential. In recent years, multi-omics analysis has emerged as a useful survival prediction tool. However, the methodology relevant to multi-omics analysis has not yet been fully established and further improvements are required for clinical applications. In this study, we developed a novel method to accurately predict the survival of patients with lung cancer using multi-omics data. With unsupervised learning techniques, survival-associated subtypes in non-small cell lung cancer were first detected using the multi-omics datasets from six categories in The Cancer Genome Atlas (TCGA). The new subtypes, referred to as integration survival subtypes, clearly divided patients into longer and shorter-surviving groups (log-rank test: p = 0.003) and we confirmed that this is independent of histopathological classification (Chi-square test of independence: p = 0.94). Next, an attempt was made to detect the integration survival subtypes using only one categorical dataset. Our machine learning model that was only trained on the reverse phase protein array (RPPA) could accurately predict the integration survival subtypes (AUC = 0.99). The predicted subtypes could also distinguish between high and low risk patients (log-rank test: p = 0.012). Overall, this study explores novel potentials of multi-omics analysis to accurately predict the prognosis of patients with lung cancer.

Exploring the classification of cancer cell lines from multiple omic views.

BackgroundCancer classification is of great importance to understanding its pathogenesis, making diagnosis and developing treatment. The accumulation of extensive omics data of abundant cancer cell line provide basis for large scale classification of cancer with low cost. However, the reliability of cell lines as in vitro models of cancer has been controversial.MethodsIn this study, we explore the classification on pan-cancer cell line with single and integrated multiple omics data from the Cancer Cell Line Encyclopedia (CCLE) database. The representative omics data of cancer, mRNA data, miRNA data, copy number variation data, DNA methylation data and reverse-phase protein array data were taken into the analysis. TumorMap web tool was used to illustrate the landscape of molecular classification.The molecular classification of patient samples was compared with cancer cell lines.ResultsEighteen molecular clusters were identified using integrated multiple omics clustering. Three pan-cancer clusters were found in integrated multiple omics clustering. By comparing with single omics clustering, we found that integrated clustering could capture both shared and complementary information from each omics data. Omics contribution analysis for clustering indicated that, although all the five omics data were of value, mRNA and proteomics data were particular important. While the classifications were generally consistent, samples from cancer patients were more diverse than cancer cell lines.ConclusionsThe clustering analysis based on integrated omics data provides a novel multi-dimensional map of cancer cell lines that can reflect the extent to pan-cancer cell lines represent primary tumors, and an approach to evaluate the importance of omic features in cancer classification.

Abstract 1505: Platelet derived growth factor receptor alpha oncogene dependency in glioblastoma

Abstract Platelet-derived growth factor receptor alpha (PDGFRA) is a ligand-activated receptor tyrosine kinase (RTK) involved in neurodevelopment. In pediatric and adult glioblastoma (GBM), PDGFRA downstream signaling promotes tumor cell proliferation, stemness and survival. Deregulated oncogenic PDGFRA signaling in these tumors occurs by gene amplification (15% of cases), often times as extrachromosomal elements (ecDNA), or by mutations and transcriptional upregulation. Lack of biomarker-based patient selection has contributed to failure of PDGFRA inhibitors in clinical trials. To provide experimental evidence for selection of patients that can benefit from PDGFRA targeted therapy, we have investigated the mode of PDGFRA deregulation in patient-derived GBM models, which we hypothesize determines the degree of dependency on PDGFRA signaling. PDGFRA copy number and mRNA levels in a panel of 13 GBM tumors, derived cancer stem cells (CSC) and xenografts (PDX) were determined by DNA and RNA seq, respectively. EcDNA location of PDGFRA-amplified CSCs was determined by FISH. Levels of total PDGFRA and activated (phospho-PDGFRA Y754) protein were determined by IHC and reverse phase protein array (RPPA). PDGFRA mRNA overexpression was observed for 3 GBM tumors and their derived models: one GBM carrying PDGFRA ecDNA amplification (HF3253), and two non-amplified GBMs (Tukey p=0.60, 0.37). Messenger RNA correlated to total protein levels for all cases, but corresponding PDGFRA activation was observed only for HF3253. High levels of PDGFRA activation in HF3253 PDX was retained in recurrent tumors after temozolomide treatment. Exploiting intra-tumoral heterogeneity, we have isolated 2 single cell clones from HF3253 CSCs which do not carry PDGFRA ecDNA(-) and tested their self-renewal and tumorigenic potential against the parental ecDNA(+) cells. Reduced self-renewal in both ecDNA(-) clones was observed (p=1e-03, p=0.01). Tumor growth in mouse orthotopic xenografts, measured by symptom-free survival, was extraordinarily reduced in the two ecDNA(-) clones (log-rank, p=1e-03, 2e-04). In contrast to parental HF3253, ecDNA(-) tumors demonstrated diffuse tumor morphology and weak PDGFRA activation. Using RPPA data from four in vitro media conditions (normal growth, minus EGF/FGF, 2% and 10% FBS) in eight GBM CSC models, the effect of growth conditions on PDGFRA activation was significant and strongest under growth factor-depleted conditions (p=5e-04, 2-way ANOVA). In conclusion, we demonstrated the dependency on PDGFRA signaling in a patient-derived GBM model carrying ecDNA PDGFRA amplification. PDGFRA over-expression was observed for 2 GBMs in absence of gene amplification, but it did not result in protein activation, which our data suggest is a determinant of oncogene dependency. PDGFRA activity is preserved by endogenous stressors (removal of growth factors) and exogenous stressors (TMZ). Our data validates PDGFRA as a therapeutic target in a subset of GBM patients and demonstrates that detection of ecDNA-amplified PDGFRA has the potential to be a predictive biomarker of future PDGFRA targeted therapies. Citation Format: Artem D. Berezovsky, Susan M. Irtenkauf, Andrea D. Transou, Laura A. Hasselbach, Tom Mikkelsen, Ana C. deCarvalho. Platelet derived growth factor receptor alpha oncogene dependency in glioblastoma [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 1505.

Abstract 5880: Pan-cancer gene expression analysis of tissue microarray using EdgeSeq Oncology Biomarker Panel and a cross-comparison with ERBB3 immunohistochemical analysis

Abstract Background: Antibody-drug conjugate (ADC) is one of the recent break-through approaches of targeting tumors, in which chemotherapeutic agents are attached via linkers to antibodies recognizing membrane proteins on tumor cells and the agents are delivered directly into tumor cells. In ADC drug development, it is important to determine the antibody-target gene expression levels in tumor cells as well as normal tissues. Methods: We characterized an established pan-cancer tissue microarray set by gene expression analysis using HTG EdgeSeq Oncology Biomarker Panel (2,867 genes for 2,376 samples including 17 solid cancer types and 25 normal tissues) and compared it with immunohistochemistry (IHC) result of ERBB3, which is a target of anti-ERBB3 ADC, U3-1402, being investigated in clinical trials. Furthermore, these data were compared with RNA-seq and Reverse-Phase Protein Array (RPPA) publicly available data sets from The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). Results: Gene signature analyses indicated a similarity of cancer type characteristics between the tissue microarray cohort and TCGA data, such as richness of cancer-associated fibroblast and immune cell infiltrate. As expected, ERBB3 mRNA expression results by EdgeSeq were similar to TCGA RNA-seq data, suggesting an epithelial-biased expression pattern. The result of IHC for ERBB3 showed overall correlation with EdgeSeq mRNA data, such as high IHC scores in melanoma. Interestingly several cancer types and subtypes showed low IHC signals relatively to EdgeSeq data, such as low IHC signals in hepatocellular carcinoma despite of a certain mRNA expression levels. RNA-seq and RPPA data of CCLE did not show such discordance between mRNA and protein levels, which could be a result of the regulation due to in vivo environmental factors. In breast cancer, ERBB3 IHC score levels were generally lower in triple negative breast cancer (TNBC), while TNBC-Mesenchymal subtype showed relatively high IHC score levels comparable to non-TNBC tumor types. In stomach cancer, intestinal subtype showed higher IHC score levels than diffuse subtype despite similar mRNA expression levels. These subtype-specific protein-level regulations were also observed in TCGA RNA-seq and RPPA data comparison. Conclusion: These results suggested a unique protein-level regulation of ERBB3 in tumor cells. It would be important to investigate the significance of protein-level antibody-target expressions on tumor samples, such as IHC on tissue microarray, for antibody-based drug development. Citation Format: Koichiro Inaki, Naoyuki Maeda, Tomoko Shibutani, Serenella Eppenberger-Castori, Stefan Nicolet, Kumiko Koyama, Yui Tanaka, Yuki Kaneda, Kenichi Wakita, Yoshinobu Shiose, Masato Murakami. Pan-cancer gene expression analysis of tissue microarray using EdgeSeq Oncology Biomarker Panel and a cross-comparison with ERBB3 immunohistochemical analysis [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 5880.

Abstract 5321: Novel imipridone ONC206 inhibits cell proliferation and induces apoptosis in uterine serous cancer through altering MAPK/AKT signaling network and metabolic reprogramming

Abstract Uterine serous carcinoma (USC) is the most aggressive subtype of endometrial cancer. Patients with advanced stage USC have poor survival rates and new treatment regimens are lacking. ONC201 is the first clinical bitopic antagonist of dopamine receptor D2 (DRD2), that is well tolerated and currently being investigated in several clinical trials for oncology. ONC206 is a chemical derivative of ONC201 with the same impridone core structure, which is also a DRD2 antagonist that exhibits distinct receptor pharmacology and nanomolar potency in various preclinical cancer models. However, the effects of ONC206 on USC progression and the mechanism of action have not been thoroughly explored. Using both in vitro and in vivo models, and multiple USC cell lines, the effects of ONC206 on cell proliferation and apoptosis were determined. Reverse phase protein arrays (RPPAs) and Western blot analyses were used to determine the effect of ONC206 on the expression of key proteins in various signaling networks in ONC206 treated USC cells. The results showed that ONC206 suppressed USC cell proliferation and induces apoptosis in a dose-dependent manner. Luciferase labeled USC cell ARK1-bearing mice treated with 100mg/kg ONC206 had significantly lower chemiluminescent signals than those treated with the control buffer. RPPA data showed that ONC206 treated USC cells had markedly lower expression signals in p38MAPK, p-AKT, p-S6, and multiple mitochondrial proteins associated with mitochondrial ATP synthesis including MTCO1, and TFAM than the control cells did. Significantly lower ATP levels and cytochrome c oxidase activities in ONC206 treated USC cells than in control cells were demonstrated by luminescent ATP detection assay kit and the cytochrome c oxidase assay kit. These data suggest that ONC206 suppresses USC progression through inhibiting MAPK/AKT network, which subsequently leads to metabolic reprogramming and increased apoptosis. Moreover, by knocking-out DRD2, USC cells became more resistant to ONC206 treatment. This suggested that the effect of ONC206 is likely mediated through its binding to DRD2. ONC206 also showed a synergistic effect with paclitaxel in vitro. Further studies which demonstrate the optimal dosage and the efficacy of treatment of USC using ONC206 are warranted. Citation Format: Chi Lam Au Yeung, Wen Hu, Li Zhang, Sammy Ferri-Borgogno, Rohinton S. Tarapore, Joshua E. Allen, Karen H. Lu, Samuel C. Mok. Novel imipridone ONC206 inhibits cell proliferation and induces apoptosis in uterine serous cancer through altering MAPK/AKT signaling network and metabolic reprogramming [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 5321.

Enhanced immortalization, HUWE1 mutations and other biological drivers of breast invasive carcinoma in Black/African American patients.

Black/African-American (B/AA) breast cancer patients tend to have more aggressive tumor biology compared to White/Caucasians. In this study, a variety of breast tumor molecular expression profiles of patients derived from the two racial groupings were investigated. Breast invasive carcinoma sample data (RNASeq version 2, Reverse Phase Protein Array, mutation, and miRSeq data) from the Cancer Genome Atlas were examined. The results affirm that B/AA patients are more likely than Caucasian patients to harbor the aggressive basal-like or the poor prognosis-associated HER2-enriched molecular subtypes of breast cancer. There is also a higher incidence of the triple-negative breast cancer (TNBC) among B/AA patients than the general population, a fact reflected in the mutation patterns of genes such as PIK3CA and TP53. Furthermore, an immortalization signature gene set, is enriched in samples from B/AA patients. Among stage III patients, TERT, DRAP1, and PQBP1, all members of the immortalization gene signature set, are among master-regulators with increased activity in B/AA patients. Master-regulators driving differences in expression profiles between the two groups include immortalization markers, senescence markers, and immune response and redox gene products. Differences in expression, between B/AA and Caucasian patients, of RB1, hsa-let-7a, E2F1, c-MYC, TERT, and other biomolecules appear to cooperate to enhance entry into the S-phase of the cell cycle in B/AA patients. Higher expression of miR-221, an oncomiR that facilitates entry into the cell cycle S-phase, is regulated by c-MYC, which is expressed more in breast cancer samples from B/AA patients. Furthermore, the cell migration- and invasion-promoting miRNA, miR-135b, has increased relative expression in B/AA patients. Knock down of the immortalization marker TERT inhibited triple-negative breast cancer cell lines (MDA-MB-231 and MDA-MB-468) cell viability and decreased expression of TERT, MYC and WNT11. For those patients with available survival data, prognosis of stage II patients 50 years of age or younger at diagnosis, was distinctly poorer in B/AA patients. Also associated with this subset of B/AA patients are missense mutations in HUWE1 and PTEN expression loss. Relative to Caucasian non-responders to endocrine therapy, B/AA non-responders show suppressed expression of a signature gene set on which biological processes including signaling by interleukins, circadian clock, regulation of lipid metabolism by PPARα, FOXO-mediated transcription, and regulation of TP53 degradation are over-represented. Thus, we identify molecular expression patterns suggesting diminished response to oxidative stress, changes in regulation of tumor suppressors/facilitators, and enhanced immortalization in B/AA patients are likely important in defining the more aggressive molecular tumor phenotype reported in B/AA patients.

Hippo pathway interacts with Wnt pathway to regulate the neural crest cells

The neural crest (NC) cells are migratory multipotent cells during embryogenesis, which differentiate into various derivatives and contribute significantly to tissues and organs. The Hippo pathway is a conserved anti‐growth fundamental pathway, yet its role in NC remains poorly understood. We found that Hippo pathway plays pivotal roles in NC cells proliferation, migration and differentiation, based on data obtained from comprehensive studies using in vivo NC conditional knock‐out mouse models and in vitro NC cells. Deficiency of Hippo effectors Yap and Taz caused defects in NC‐derived structures in mice such as vascular and cranial bone defects, as well as failure of NC cells to proliferate, migrate and differentiate. Notably, our motif analysis of ATAC‐seq (assay for transposase‐accessible chromatin with high‐throughput sequencing) data in mouse craniofacial tissues and human NC cells indicated that genome‐wide, 38.9% genes have enriched Tead (Yap/Taz cofactor) motifs are also enriched in Tcf/Lef (β‐catenin cofactors) motifs, suggesting that Hippo interacts with Wnt to coordinately regulate gene expression in NC cells. Wnt‐β‐catenin pathway, another fundamental pathway, has been shown to play a key role in NC cells. Our co‐IP data uncovered a direct interaction between Yap/Taz and β‐catenin in NC cells. Furthermore, our RNA‐seq data in mouse craniofacial tissues and Reverse Phase Protein Array (RPPA) data in mouse NC cells indicated that many known Wnt target genes important for cell migration and fate determination were also regulated by Yap/Taz. In addition, Yap/Taz‐Tead and Tcf/Lef‐β‐catenin complexes coordinately and directly regulate the expression of these genes. Together, our findings uncover novel roles of hippo‐Yap pathway in regulating NC cells, which partially functions through interaction with Wnt‐β‐catenin pathway.Support or Funding InformationThis work was supported by grants from the National Institutes of Health (R56HL142704, R03DE025873, K01DE026561 to J.W.).

Protein Expression of Cyclin B1, Transferrin Receptor, and Fibronectin Is Correlated with the Prognosis of Adrenal Cortical Carcinoma.

BackgroundAdrenal cortical carcinoma (ACC) is a rare cancer with a variable prognosis. Several prognostic factors of ACC have been previously reported, but a proteomic analysis has not yet been performed. This study aimed to investigate prognostic biomarkers for ACC using a proteomic approach.MethodsWe used reverse-phase protein array data from The Cancer Proteome Atlas, and identified differentially expressed proteins in metastatic ACCs. Multivariate Cox regression analysis adjusted by age and staging was used for survival analysis, and the C-index and category-free net reclassification improvement (cfNRI) were utilized to evaluate additive prognostic value.ResultsIn 46 patients with ACC, cyclin B1, transferrin receptor (TfR1), and fibronectin were significantly overexpressed in patients with distant metastasis. In multivariate models, high expression of cyclin B1 and TfR1 was significantly associated with mortality (hazard ratio [HR], 6.13; 95% confidence interval [CI], 1.02 to 36.7; and HR, 6.59; 95% CI, 1.14 to 38.2; respectively), whereas high fibronectin expression was not (HR, 3.92; 95% CI, 0.75 to 20.4). Combinations of high cyclin B1/high TfR1, high cyclin B1/high fibronectin, and high TfR1/high fibronectin were strongly associated with mortality ([HR, 13.72; 95% CI, 1.89 to 99.66], [HR, 9.22; 95% CI, 1.34 to 63.55], and [HR, 18.59; 95% CI, 2.54 to 135.88], respectively). In reclassification analyses, cyclin B1, TfR1, fibronectin, and combinations thereof improved the prognostic performance (C-index, 0.78 to 0.82–0.86; cfNRI, all P values <0.05).ConclusionIn ACC patients, the overexpression of cyclin B1, TfR1, and fibronectin and combinations thereof were associated with poor prognosis.