Surface Adjustment of Reverse Phase Protein Arrays using Positive Control Spots

A protein expression atlas on tissue samples and cell lines from cancer patients provides insights into tumor heterogeneity and dependencies

The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) are foundational resources in cancer research, providing extensive molecular and phenotypic data. However, large-scale proteomic data across various cancer types for these cohorts remain limited. Here, we expand upon our previous work to generate high-quality protein expression data for approximately 8,000 TCGA patient samples and around 900 CCLE cell line samples, covering 447 clinically relevant proteins, using reverse-phase protein arrays. These protein expression profiles offer profound insights into intertumor heterogeneity and cancer dependency and serve as sensitive functional readouts for somatic alterations. We develop a systematic protein-centered strategy for identifying synthetic lethality pairs and experimentally validate an interaction between protein kinase A subunit α and epidermal growth factor receptor. We also identify metastasis-related protein markers with clinical relevance. This dataset represents a valuable resource for advancing our understanding of cancer mechanisms, discovering protein biomarkers and developing innovative therapeutic strategies.

Valosin-containing protein (VCP/p97) is prognostically unfavorable in pediatric AML, and negatively correlates with unfolded protein response proteins IRE1 and GRP78: A report from the Children's Oncology Group

PURPOSE

The endoplasmic reticulum (ER) is the major site of protein synthesis and folding in the cell. ER-associated degradation (ERAD) and unfolded protein response (UPR) are the main mechanisms of ER-mediated cell stress adaptation. Targeting the cell stress response is a promising therapeutic approach in acute myeloid leukemia (AML).

EXPERIMENTAL DESIGN

Protein expression levels of valosin-containing protein (VCP), a chief element of ERAD, were measured in peripheral blood samples from in 483 pediatric AML patients using reverse phase protein array methodology. Patients participated in the Children's Oncology Group AAML1031 phase 3 clinical trial that randomized patients to standard chemotherapy (cytarabine (Ara-C), daunorubicin, and etoposide [ADE]) versus ADE plus bortezomib (ADE+BTZ).

RESULTS

Low-VCP expression was significantly associated with favorable 5-year overall survival (OS) rate compared to middle-high-VCP expression (81% versus 63%, p < 0.001), independent of additional bortezomib treatment. Multivariable Cox regression analysis identified VCP as independent predictor of clinical outcome. UPR proteins IRE1 and GRP78 had significant negative correlation with VCP. Five-year OS in patients characterized by low-VCP, moderately high-IRE1 and high-GRP78 improved after treatment with ADE+BTZ versus ADE (66% versus 88%, p = 0.026).

CONCLUSION AND CLINICAL RELEVANCE

Our findings suggest the potential of the protein VCP as biomarker in prognostication prediction in pediatric AML.

Global proteomic identifies multiple cancer-related signaling pathways altered by a gut pathobiont associated with colorectal cancer

In this work, we investigated the oncogenic role of Streptococcus gallolyticus subsp. gallolyticus (SGG), a gut bacterium associated with colorectal cancer (CRC). We showed that SGG UCN34 accelerates colon tumor development in a chemically induced CRC murine model. Full proteome and phosphoproteome analysis of murine colons chronically colonized by SGG UCN34 revealed that 164 proteins and 725 phosphorylation sites were differentially regulated. Ingenuity Pathway Analysis (IPA) indicates a pro-tumoral shift specifically induced by SGG UCN34, as ~ 90% of proteins and phosphoproteins identified were associated with digestive cancer. Comprehensive analysis of the altered phosphoproteins using ROMA software revealed up-regulation of several cancer hallmark pathways such as MAPK, mTOR and integrin/ILK/actin, affecting epithelial and stromal colonic cells. Importantly, an independent analysis of protein arrays of human colon tumors colonized with SGG showed up-regulation of PI3K/Akt/mTOR and MAPK pathways, providing clinical relevance to our findings. To test SGG's capacity to induce pre-cancerous transformation of the murine colonic epithelium, we grew ex vivo organoids which revealed unusual structures with compact morphology. Taken together, our results demonstrate the oncogenic role of SGG UCN34 in a murine model of CRC associated with activation of multiple cancer-related signaling pathways.

RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data

SUMMARY

Reverse-Phase Protein Array (RPPA) is a robust high-throughput, cost-effective platform for quantitatively measuring proteins in biological specimens. However, converting raw RPPA data into normalized, analysis-ready data remains a challenging task. Here, we present the RPPA SPACE (RPPA Superposition Analysis and Concentration Evaluation) R package, a substantially improved successor to SuperCurve, to meet that challenge. SuperCurve has been used to normalize over 170 000 samples to date. RPPA SPACE allows exclusion of poor-quality samples from the normalization process to improve the quality of the remaining samples. It also features a novel quality-control metric, 'noise', that estimates the level of random errors present in each RPPA slide. The noise metric can help to determine the quality and reliability of the data. In addition, RPPA SPACE has simpler input requirements and is more flexible than SuperCurve, it is much faster with greatly improved error reporting.

AVAILABILITY AND IMPLEMENTATION

The standalone RPPA SPACE R package, tutorials and sample data are available via https://rppa.space/, CRAN (https://cran.r-project.org/web/packages/RPPASPACE/index.html) and GitHub (https://github.com/MD-Anderson-Bioinformatics/RPPASPACE).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The metabolic enzyme hexokinase 2 localizes to the nucleus in AML and normal haematopoietic stem and progenitor cells to maintain stemness

Mitochondrial metabolites regulate leukaemic and normal stem cells by affecting epigenetic marks. How mitochondrial enzymes localize to the nucleus to control stem cell function is less understood. We discovered that the mitochondrial metabolic enzyme hexokinase 2 (HK2) localizes to the nucleus in leukaemic and normal haematopoietic stem cells. Overexpression of nuclear HK2 increases leukaemic stem cell properties and decreases differentiation, whereas selective nuclear HK2 knockdown promotes differentiation and decreases stem cell function. Nuclear HK2 localization is phosphorylation-dependent, requires active import and export, and regulates differentiation independently of its enzymatic activity. HK2 interacts with nuclear proteins regulating chromatin openness, increasing chromatin accessibilities at leukaemic stem cell-positive signature and DNA-repair sites. Nuclear HK2 overexpression decreases double-strand breaks and confers chemoresistance, which may contribute to the mechanism by which leukaemic stem cells resist DNA-damaging agents. Thus, we describe a non-canonical mechanism by which mitochondrial enzymes influence stem cell function independently of their metabolic function.

Thomas, Egan et al. report that hexokinase 2 localizes to the nucleus of leukaemic and normal haematopoietic cells to maintain stemness by interacting with nuclear proteins and modulating chromatin accessibility independently of its kinase activity.

Reverse phase protein arrays in acute leukemia: investigative and methodological challenges

INTRODUCTION

Acute leukemia results from a series of mutational events that alter cell growth and proliferation. Mutations result in protein changes that orchestrate growth alterations characteristic of leukemia. Proteomics is a methodology appropriate for study of protein changes found in leukemia. The high-throughput reverse phase protein array (RPPA) technology is particularly well-suited for the assessment of protein changes in samples derived from clinical trials.

AREAS COVERED

This review discusses the technical, methodological, and analytical issues related to the successful development of acute leukemia RPPAs.

EXPERT COMMENTARY

To obtain representative protein sample lysates, samples should be prepared from freshly collected blood or bone marrow material. Variables such as sample shipment, transit time, and holding temperature only have minimal effects on protein expression. CellSave preservation tubes are preferred for cells collected after exposure to chemotherapy, and incorporation of standardized guidelines for antibody validation is recommended. A more systematic biological approach to analyze protein expression is desired, searching for recurrent patterns of protein expression that allow classification of patients into risk groups, or groups of patients that may be treated similarly. Comparing RPPA protein analysis between cell lines and primary samples shows that cell lines are not representative of patient proteomic patterns.

High-throughput proteomic profiling reveals mechanisms of action of AMG925, a dual FLT3-CDK4/6 kinase inhibitor targeting AML and AML stem/progenitor cells

FLT3 mutations, which are found in a third of patients with acute myeloid leukemia (AML), are associated with poor prognosis. Responses to currently available FLT3 inhibitors in AML patients are typically transient and followed by disease recurrence. Thus, FLT3 inhibitors with new inhibitory mechanisms are needed to improve therapeutic outcomes. AMG925 is a novel, potent, small-molecule dual inhibitor of FLT3 and CDK4/6. In this study. we determined the antileukemic effects and mechanisms of action of AMG925 in AML cell lines and primary samples, in particular AML stem/progenitor cells. AMG925 inhibited cell growth and promoted apoptosis in AML cells with or without FLT3 mutations. Reverse-phase protein array profiling confirmed its on-target effects on FLT3-CDK4/6-regulated pathways and identified unrevealed signaling network alterations in AML blasts and stem/progenitor cells in response to AMG925. Mass cytometry identified pathways that may confer resistance to AMG925 in phenotypically defined AML stem/progenitor cells and demonstrated that combined blockade of FLT3-CDK4/6 and AKT/mTOR signaling facilitated stem cell death. Our findings provide a rationale for the mechanism-based inhibition of FLT3-CDK4/6 and for combinatorial approaches to improve the efficacy of FLT3 inhibition in both FLT3 wild-type and FLT3-mutated AML.

Spatial Bias in Antibody Microarrays May Be an Underappreciated Source of Variability

Antibody microarrays enable multiplexed protein detection with minimal reagent consumption, but they continue to be plagued by lack of reproducibility. Chemically functionalized glass slides are used as substrates, yet antibody binding spatial inhomogeneity across the slide has not been analyzed in antibody microarrays. Here, we characterize spatial bias across five commercial slides patterned with nine overlapping dense arrays (by combining three buffers and three different antibodies), and we measure signal variation for both antibody immobilization and the assay signal, generating 270 heatmaps. Spatial bias varied across models, and the coefficient of variation ranged from 4.6 to 50%, which was unexpectedly large. Next, we evaluated three layouts of spot replicates-local, random, and structured random-for their capacity to predict assay variation. Local replicates are widely used but systematically underestimate the whole-slide variation by up to seven times; structured random replicates gave the most accurate estimation. Our results highlight the risk and consequences of using local replicates: the underappreciation of spatial bias as a source of variability, poor assay reproducibility, and possible overconfidence in assay results. We recommend the detailed characterization of spatial bias for antibody microarrays and the description and use of distributed positive replicates for research and clinical applications.

Heat shock factor 1 (HSF1-pSer326) predicts response to bortezomib-containing chemotherapy in pediatric AML: a COG report

Bortezomib (BTZ) was recently evaluated in a randomized phase 3 clinical trial by the Children's Oncology Group (COG) that compared standard chemotherapy (cytarabine, daunorubicin, and etoposide [ADE]) vs standard therapy with BTZ (ADEB) for de novo pediatric acute myeloid leukemia (AML). Although the study concluded that BTZ did not improve outcome overall, we examined patient subgroups benefiting from BTZ-containing chemotherapy using proteomic analyses. The proteasome inhibitor BTZ disrupts protein homeostasis and activates cytoprotective heat shock responses. Total heat shock factor 1 (HSF1) and phosphorylated HSF1 (HSF1-pSer326) were measured in leukemic cells from 483 pediatric patients using reverse phase protein arrays. HSF1-pSer326 phosphorylation was significantly lower in pediatric AML compared with CD34+ nonmalignant cells. We identified a strong correlation between HSF1-pSer326 expression and BTZ sensitivity. BTZ significantly improved outcome of patients with low-HSF1-pSer326 with a 5-year event-free survival of 44% (ADE) vs 67% for low-HSF1-pSer326 treated with ADEB (P = .019). To determine the effect of HSF1 expression on BTZ potency in vitro, cell viability with HSF1 gene variants that mimicked phosphorylated (S326A) and nonphosphorylated (S326E) HSF1-pSer326 were examined. Those with increased HSF1 phosphorylation showed clear resistance to BTZ vs those with wild-type or reduced HSF1-phosphorylation. We hypothesize that HSF1-pSer326 expression could identify patients who benefit from BTZ-containing chemotherapy.

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.

RSK inhibitor BI-D1870 inhibits acute myeloid leukemia cell proliferation by targeting mitotic exit

The 90 kDa Ribosomal S6 Kinase (RSK) drives cell proliferation and survival in cancers, although its oncogenic mechanism has not been well characterized. Phosphorylated level of RSK (T573) was increased in acute myeloid leukemia (AML) patients and associated with poor survival. To examine the role of RSK in AML, we analyzed apoptosis and the cell cycle profile following treatment with BI-D1870, a potent inhibitor of RSK. BI-D1870 treatment increased the G2/M population and induced apoptosis in AML cell lines and patient AML cells. Characterization of mitotic phases showed that the metaphase/anaphase transition was significantly inhibited by BI-D1870. BI-D1870 treatment impeded the association of activator CDC20 with APC/C, but increased binding of inhibitor MAD2 to CDC20, preventing mitotic exit. Moreover, the inactivation of spindle assembly checkpoint or MAD2 knockdown released cells from BI-D1870-induced metaphase arrest. Therefore, we investigated whether BI-D1870 potentiates the anti-leukemic activity of vincristine by targeting mitotic exit. Combination treatment of BI-D1870 and vincristine synergistically increased mitotic arrest and apoptosis in acute leukemia cells. These data show that BI-D1870 induces apoptosis of AML cells alone and in combination with vincristine through blocking mitotic exit, providing a novel approach to overcoming vincristine resistance in AML cells.

Analytical Platforms 1: Use of Cultured Cells and Fluorescent Read-Out Coupled to NormaCurve Normalization in RPPA

The analytic platform described in this chapter uses proteins extracted from cultured cells as an infinite source of material to set up, validate, and quality control an RPPA platform. Readout of the arrays uses near-infrared fluorescence labeling and data normalization is performed using the bioinformatics package NormaCurve.In the first part, we will describe the advantages, drawbacks, and different applications of cell line material for RPPA. In the second part, we will describe how the staining protocol, the method of readout, and the normalization method applied afterward are interconnected and should be considered together. Finally, we will describe the NormaCurve package, which is freely available, and its requirements for implementation.Four protocols are provided in this chapter: (1) Protein lysis of cell lines using a homemade Laemmli buffer, (2) RPPA staining for fluorescent readout including a signal amplification step, (3) total protein staining in the visible spectrum for normalization purposes, and (4) total protein staining in the near-infrared spectrum for normalization purposes.

Proteomic Profiling of Acute Promyelocytic Leukemia Identifies Two Protein Signatures Associated with Relapse

PURPOSE

Acute promyelocytic leukemia (APL) is the most prognostically favorable subtype of Acute myeloid leukemia (AML). Defining the features that allow identification of APL patients likely to relapse after therapy remains challenging.

EXPERIMENTAL DESIGN

Proteomic profiling is performed on 20 newly diagnosed APL, 205 non-APL AML, and 10 normal CD34+ samples using Reverse Phase Protein Arrays probed with 230 antibodies.

RESULTS

Comparison between APL and non-APL AML samples identifies 8.3% of the proteins to be differentially expressed. Proteins higher expressed in APL are involved in the pro-apoptotic pathways or are linked to higher proliferation. The "MetaGalaxy" approach that considers proteins in relation to other assayed proteins stratifies the APL patients into two protein signatures. All of the relapse patients (n = 4/4) are in protein signature 2 (S2). Comparison of proteins between the signatures shows significant differences in relative expression for 38 proteins. Protein expression summary plots suggest less translational activity in combination with a less proliferative character for S2 compared to signature 1.

CONCLUSIONS AND CLINICAL RELEVANCE

This study provides a potential proteomic-based classification of APL patients that may be useful for risk stratification and therapeutic guidance. Validation in a larger independent cohort is required.

Proteomic Profiling of Signaling Networks Modulated by G-CSF/Plerixafor/Busulfan-Fludarabine Conditioning in Acute Myeloid Leukemia Patients in Remission or with Active Disease prior to Allogeneic Stem Cell Transplantation

To characterize intracellular signaling in peripheral blood (PB) cells of acute myeloid leukemia (AML) patients undergoing pretransplant conditioning with CXCR4 inhibitor plerixafor, granulocyte colony-stimulating factor (G-CSF), and busulfan plus fludarabine (Bu+Flu) chemotherapy, we profiled 153 proteins in 33 functional groups using reverse phase protein array. CXCR4 inhibition mobilized AML progenitors and clonal AML cells, and this was associated with molecular markers of cell cycle progression. G-CSF/plerixafor and G-CSF/plerixafor/Bu+Flu modulated distinct signaling networks in AML blasts of patients undergoing conditioning with active disease compared to nonleukemic PB cells of patients in remission. We identified AML-specific proteins that remained aberrantly expressed after chemotherapy, representing putative chemoresistance markers in AML.

A quantitative analysis of heterogeneities and hallmarks in acute myelogenous leukaemia

Acute myelogenous leukaemia (AML) is associated with risk factors that are largely unknown and with a heterogeneous response to treatment. Here, we provide a comprehensive quantitative understanding of AML proteomic heterogeneities and hallmarks by using the AML proteome atlas, a proteomics database that we have newly derived from MetaGalaxy analyses, for the proteomic profiling of 205 AML patients and 111 leukaemia cell lines. The analysis of the dataset revealed 154 functional patterns based on common molecular pathways, 11 constellations of correlated functional patterns, and 13 signatures that stratify the patients’ outcomes. We find limited overlap between proteomics data and both cytogenetics and genetic mutations, and also that leukaemia cell lines show limited proteomic similarities with cells from AML patients, suggesting that a deeper focus on patient-derived samples is needed to gain disease-relevant insights. The AML proteome atlas provides a knowledge base for proteomic patterns in AML, a guide to leukaemia cell-line selection, and a broadly applicable computational approach for quantifying the heterogeneities of protein expression and proteomic hallmarks in AML.

Reproducibility and Crossplatform Validation of Reverse-Phase Protein Array Data

Reverse-phase protein array (RPPA) technology is a high-throughput antibody- and microarray-based approach for the rapid profiling of levels of proteins and protein posttranslational modifications in biological specimens. The technology consumes small amounts of samples, can sensitively detect low-abundance proteins and posttranslational modifications, enables measurements of multiple signaling pathways in parallel, has the capacity to analyze large sample numbers, and offers robust interexperimental reproducibility. These features of RPPA experiments have motivated and enabled the use of RPPA technology in various biomedical, translational, and clinical applications, including the delineation of molecular mechanisms of disease, profiling of druggable signaling pathway activation, and search for new prognostic markers. Owing to the complexity of many of these applications, such as developing multiplex protein assays for diagnostic laboratories or integrating posttranslational modification-level data using large-scale proteogenomic approaches, robust and well-validated data are essential. There are many distinct components of an RPPA workflow, and numerous possible technical setups and analysis parameter options exist. The differences between RPPA platform setups around the world offer opportunities to assess and minimize interplatform variation. Crossplatform validation may also aid in the evaluation of robust, platform-independent protein markers of disease and response to therapy.

Mycoplasma contamination of leukemic cell lines alters protein expression determined by reverse phase protein arrays

Mycoplasma contamination is a major problem in cell culturing, potentially altering the results of cell line-based experiments in largely uncharacterized ways. To define the consequences of mycoplasma infection at the level of protein expression we utilized the reverse phase protein array technology to analyze the expression of 235 proteins in mycoplasma infected, uninfected post treatment, and never-infected leukemic cell lines. Overall, protein profiles of cultured cells remained relatively stable after mycoplasma infection. However, paired comparisons for individual proteins identified that 18.7% of the proteins significantly changed between the infected and the never-infected cell line samples, and that 14.0% of the proteins significantly altered between the infected and the post treatment samples. Six percent of the proteins were affected in the post treatment samples compared to the never-infected samples, and 7.2% compared to treated cells that had never had mycoplasma infection before. Proteins that were significantly altered in the infected cells were enriched for apoptotic signaling processes and auto-phosphorylation, suggesting an increased cellular stress and a decreased growth rate. In conclusion, this study shows that mycoplasma infection of leukemic cell lines alters the proteins expression levels, potentially confounding experimental results. This reinforces the need for regular testing of mycoplasma.

Recurrent Patterns of Protein Expression Signatures in Pediatric Acute Lymphoblastic Leukemia: Recognition and Therapeutic Guidance

Pediatric acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy, and the second leading cause of pediatric cancer-related death in developed countries. While the cure rate for newly diagnosed ALL is excellent, the genetic heterogeneity and chemoresistance of leukemia cells at relapse makes individualized curative treatment plans difficult. We hypothesize that genetic events would coalesce into a finite number of protein signatures that could guide the design of individualized therapy. Custom reverse-phase protein arrays were produced from pediatric ALL (n = 73) and normal CD34⁺ (n = 10) samples with 194 validated antibodies. Proteins were allocated into 31 protein functional groups (PFG) to analyze them in the context of other proteins, based on known associations from the literature. The optimal number of protein clusters was determined for each PFG. Protein networks showed distinct transition states, revealing "normal-like" and "leukemia-specific" protein patterns. Block clustering identified strong correlation between various protein clusters that formed 10 protein constellations. Patients that expressed similar recurrent combinations of constellations comprised 7 distinct signatures, correlating with risk stratification, cytogenetics, and laboratory features. Most constellations and signatures were specific for T-cell ALL or pre-B-cell ALL; however, some constellations showed significant overlap. Several signatures were associated with Hispanic ethnicity, suggesting that ethnic pathophysiologic differences likely exist. In addition, some constellations were enriched for "normal-like" protein clusters, whereas others had exclusively "leukemia-specific" patterns.Implications: Recognition of proteins that have universally altered expression, together with proteins that are specific for a given signature, suggests targets for directed combinatorial inhibition or replacement to enable personalized therapy. Mol Cancer Res; 16(8); 1263-74. ©2018 AACRSee related article by Hoff et al., p. 1275.

Recognition of Recurrent Protein Expression Patterns in Pediatric Acute Myeloid Leukemia Identified New Therapeutic Targets

Heterogeneity in the genetic landscape of pediatric acute myeloid leukemia (AML) makes personalized medicine challenging. As genetic events are mediated by the expression and function of proteins, recognition of recurrent protein patterns could enable classification of pediatric AML patients and could reveal crucial protein dependencies. This could help to rationally select combinations of therapeutic targets. To determine whether protein expression levels could be clustered into functionally relevant groups, custom reverse-phase protein arrays were performed on pediatric AML (n = 95) and CD34⁺ normal bone marrow (n = 10) clinical specimens using 194 validated antibodies. To analyze proteins in the context of other proteins, all proteins were assembled into 31 protein functional groups (PFG). For each PFG, an optimal number of protein clusters was defined that represented distinct transition states. Block clustering analysis revealed strong correlations between various protein clusters and identified the existence of 12 protein constellations stratifying patients into 8 protein signatures. Signatures were correlated with therapeutic outcome, as well as certain laboratory and demographic characteristics. Comparison of acute lymphoblastic leukemia specimens from the same array and AML pediatric patient specimens demonstrated disease-specific signatures, but also identified the existence of shared constellations, suggesting joint protein deregulation between the diseases.Implication: Recognition of altered proteins in particular signatures suggests rational combinations of targets that could facilitate stratified targeted therapy. Mol Cancer Res; 16(8); 1275-86. ©2018 AACRSee related article by Hoff et al., p. 1263.

High-throughput profiling of signaling networks identifies mechanism-based combination therapy to eliminate microenvironmental resistance in acute myeloid leukemia

The bone marrow microenvironment is known to provide a survival advantage to residual acute myeloid leukemia cells, possibly contributing to disease recurrence. The mechanisms by which stroma in the microenvironment regulates leukemia survival remain largely unknown. Using reverse-phase protein array technology, we profiled 53 key protein molecules in 11 signaling pathways in 20 primary acute myeloid leukemia samples and two cell lines, aiming to understand stroma-mediated signaling modulation in response to the targeted agents temsirolimus (MTOR), ABT737 (BCL2/BCL-XL), and Nutlin-3a (MDM2), and to identify the effective combination therapy targeting acute myeloid leukemia in the context of the leukemia microenvironment. Stroma reprogrammed signaling networks and modified the sensitivity of acute myeloid leukemia samples to all three targeted inhibitors. Stroma activated AKT at Ser473 in the majority of samples treated with single-agent ABT737 or Nutlin-3a. This survival mechanism was partially abrogated by concomitant treatment with temsirolimus plus ABT737 or Nutlin-3a. Mapping the signaling networks revealed that combinations of two inhibitors increased the number of affected proteins in the targeted pathways and in multiple parallel signaling, translating into facilitated cell death. These results demonstrated that a mechanism-based selection of combined inhibitors can be used to guide clinical drug selection and tailor treatment regimens to eliminate microenvironment-mediated resistance in acute myeloid leukemia.

AXL Inhibition Suppresses the DNA Damage Response and Sensitizes Cells to PARP Inhibition in Multiple Cancers

Epithelial to mesenchymal transition (EMT) is associated with a wide range of changes in cancer cells, including stemness, chemo- and radio-resistance, and metastasis. The mechanistic role of upstream mediators of EMT has not yet been well characterized. Recently, we showed that non-small cell lung cancers (NSCLC) that have undergone EMT overexpress AXL, a receptor tyrosine kinase. AXL is also overexpressed in a subset of triple-negative breast cancers (TNBC) and head and neck squamous cell carcinomas (HNSCC), and its overexpression has been associated with more aggressive tumor behavior and linked to resistance to chemotherapy, radiotherapy, and targeted therapy. Because the DNA repair pathway is also altered in patient tumor specimens overexpressing AXL, it is hypothesized that modulation of AXL in cells that have undergone EMT will sensitize them to agents targeting the DNA repair pathway. Downregulation or inhibition of AXL directly reversed the EMT phenotype, led to decreased expression of DNA repair genes, and diminished efficiency of homologous recombination (HR) and RAD51 foci formation. As a result, AXL inhibition caused a state of HR deficiency in the cells, making them sensitive to inhibition of the DNA repair protein, PARP1. AXL inhibition synergized with PARP inhibition, leading to apoptotic cell death. AXL expression also associated positively with markers of DNA repair across TNBC, HNSCC, and NSCLC patient cohorts.

IMPLICATIONS

The novel role for AXL in DNA repair, linking it to EMT, suggests that AXL can be an effective therapeutic target in combination with targeted therapy such as PARP inhibitors in several different malignancies. Mol Cancer Res; 15(1); 45-58. ©2016 AACR.

A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis

Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response.

Essential role for cyclic-AMP responsive element binding protein 1 (CREB) in the survival of acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) relapse remains a leading cause of cancer related death in children, therefore, new therapeutic options are needed. Recently, we showed that a peptide derived from Cyclic-AMP Responsive Element Binding Protein (CREB) was highly phosphorylated in pediatric leukemias.

In this study, we determined CREB phosphorylation and mRNA levels showing that CREB expression was significantly higher in ALL compared to normal bone marrow (phosphorylation: P < 0.0001, mRNA: P = 0.004). High CREB and phospho-CREB expression was correlated with a lower median overall survival in a cohort of 140 adult ALL patients. ShRNA mediated knockdown of CREB in ALL cell lines blocked leukemic cell growth by inducing cell cycle arrest and apoptosis. Gene expression array analysis showed downregulation of CREB target genes regulating cell proliferation and glucose metabolism and upregulation of apoptosis inducing genes. Similar to CREB knockdown, the CREB inhibitor KG-501 decreased leukemic cell viability and induced apoptosis in ALL cell lines, as well as primary T-ALL samples, with cases showing high phospho-CREB levels being more sensitive than those with lower phospho-CREB levels.

Together, these in vitro findings support an important role for CREB in the survival of ALL cells and identify this transcription factor as a potential target for treatment.

Activation of the PI3K/mTOR Pathway following PARP Inhibition in Small Cell Lung Cancer

Small cell lung cancer (SCLC) is an aggressive malignancy with limited treatment options. We previously found that PARP is overexpressed in SCLC and that targeting PARP reduces cell line and tumor growth in preclinical models. However, SCLC cell lines with PI3K/mTOR pathway activation were relatively less sensitive to PARP inhibition. In this study, we investigated the proteomic changes in PI3K/mTOR and other pathways that occur following PAPR inhibition and/or knockdown in vitro and in vivo. Using reverse-phase protein array, we found the proteins most significantly upregulated following treatment with the PARP inhibitors olaparib and rucaparib were in the PI3K/mTOR pathway (p-mTOR, p-AKT, and pS6) (p≤0.02). Furthermore, amongst the most significantly down-regulated proteins were LKB1 and its targets AMPK and TSC, which negatively regulate the PI3K pathway (p≤0.042). Following PARP knockdown in cell lines, phosphorylated mTOR, AKT and S6 were elevated and LKB1 signaling was diminished. Global ATP concentrations increased following PARP inhibition (p≤0.02) leading us to hypothesize that the observed increased PI3K/mTOR pathway activation following PARP inhibition results from decreased ATP usage and a subsequent decrease in stress response signaling via LKB1. Based on these results, we then investigated whether co-targeting with a PARP and PI3K inhibitor (BKM-120) would work better than either single agent alone. A majority of SCLC cell lines were sensitive to BKM-120 at clinically achievable doses, and cMYC expression was the strongest biomarker of response. At clinically achievable doses of talazoparib (the most potent PARP inhibitor in SCLC clinical testing) and BKM-120, an additive effect was observed in vitro. When tested in two SCLC animal models, a greater than additive interaction was seen (p≤0.008). The data presented here suggest that combining PARP and PI3K inhibitors enhances the effect of either agent alone in preclinical models of SCLC, warranting further investigation of such combinations in SCLC patients.

Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA) were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

M, Mills GB, Heymach JV, Wistuba II, Wang J, Byers. LA. An Integrated Molecular Analysis of Lung Adenocarcinomas Identifies Potential Therapeutic Targets among TTF1-Negative Tumors, Including DNA Repair Proteins and Nrf2

PURPOSE

Thyroid transcription factor-1 (TTF1) immunohistochemistry (IHC) is used clinically to differentiate primary lung adenocarcinomas (LUAD) from squamous lung cancers and metastatic adenocarcinomas from other primary sites. However, a subset of LUAD (15%-20%) does not express TTF1, and TTF1-negative patients have worse clinical outcomes. As there are no established targeted agents with activity in TTF1-negative LUAD, we performed an integrated molecular analysis to identify potential therapeutic targets.

EXPERIMENTAL DESIGN

Using two clinical LUAD cohorts (274 tumors), one from our institution (PROSPECT) and The Cancer Genome Atlas, we interrogated proteomic profiles (by reverse phase protein array, RPPA), gene expression, and mutational data. Drug response data from 74 cell lines were used to validate potential therapeutic agents.

RESULTS

Strong correlations were observed between TTF1 IHC and TTF1 measurements by RPPA (Rho = 0.57, P < 0.001) and gene expression (NKX2-1, Rho = 0.61, P < 0.001). Established driver mutations (e.g., BRAF and EGFR) were associated with high TTF1 expression. In contrast, TTF1-negative LUAD had a higher frequency of inactivating KEAP1 mutations (P = 0.001). Proteomic profiling identified increased expression of DNA repair proteins (e.g., Chk1 and the DNA repair score) and suppressed PI3k/mTOR signaling among TTF1-negative tumors, with differences in total proteins confirmed at the mRNA level. Cell line analysis showed drugs targeting DNA repair to be more active in TTF1-low cell lines.

CONCLUSIONS

Combined genomic and proteomic analyses demonstrated infrequent alteration of validated lung cancer targets (including the absence of BRAF mutations in TTF1-negative LUAD), but identified novel potential targets for TTF1-negative LUAD, including KEAP1/Nrf2 and DNA repair pathways.

Microarray R-based analysis of complex lysate experiments with MIRACLE

Motivation: Reverse-phase protein arrays (RPPAs) allow sensitive quantification of relative protein abundance in thousands of samples in parallel. Typical challenges involved in this technology are antibody selection, sample preparation and optimization of staining conditions. The issue of combining effective sample management and data analysis, however, has been widely neglected.

Results: This motivated us to develop MIRACLE, a comprehensive and user-friendly web application bridging the gap between spotting and array analysis by conveniently keeping track of sample information. Data processing includes correction of staining bias, estimation of protein concentration from response curves, normalization for total protein amount per sample and statistical evaluation. Established analysis methods have been integrated with MIRACLE, offering experimental scientists an end-to-end solution for sample management and for carrying out data analysis. In addition, experienced users have the possibility to export data to R for more complex analyses. MIRACLE thus has the potential to further spread utilization of RPPAs as an emerging technology for high-throughput protein analysis.

Availability: Project URL: http://www.nanocan.org/miracle/

Contact: mlist@health.sdu.dk

Supplementary information:Supplementary data are available at Bioinformatics online.

Spatial normalization of reverse phase protein array data

Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.

A comprehensive comparison of normalization methods for loading control and variance stabilization of reverse-phase protein array data

Loading control (LC) and variance stabilization of reverse-phase protein array (RPPA) data have been challenging mainly due to the small number of proteins in an experiment and the lack of reliable inherent control markers. In this study, we compare eight different normalization methods for LC and variance stabilization. The invariant marker set concept was first applied to the normalization of high-throughput gene expression data. A set of “invariant” markers are selected to create a virtual reference sample. Then all the samples are normalized to the virtual reference. We propose a variant of this method in the context of RPPA data normalization and compare it with seven other normalization methods previously reported in the literature. The invariant marker set method performs well with respect to LC, variance stabilization and association with the immunohistochemistry/florescence in situ hybridization data for three key markers in breast tumor samples, while the other methods have inferior performance. The proposed method is a promising approach for improving the quality of RPPA data.

Loss of TRIM62 expression is an independent adverse prognostic factor in acute myeloid leukemia

BACKGROUND

Tripartite motif (TRIM)-62 is a putative tumor suppressor gene whose role in leukemia is unknown.

MATERIALS AND METHODS

We evaluated the effect of TRIM62 protein expression in patients with acute myeloid leukemia (AML). We used reverse-phase protein array methodology to determine TRIM62 levels in leukemia-enriched protein samples from 511 patients newly diagnosed with AML.

RESULTS

TRIM62 levels in AML cells were significantly lower than in normal CD34-positive cells, suggesting that TRIM62 loss might be involved in leukemogenesis, but was not associated with specific karyotypic abnormalities or Nucleophosmin (NPM1), Fms-like Tyrosine Kinase-3 (FLT3), or rat sarcoma viral oncogene (RAS) mutational status. Low TRIM62 levels were associated with shorter complete remission duration and significantly shorter event-free and overall survival rates, particularly among patients with intermediate-risk cytogenetics. In that AML subgroup, age and TRIM62 levels were the most powerful independent prognostic factors for survival. TRIM62 protein levels further refined the risk associated with NPM1 and FLT3 mutational status. TRIM62 loss was associated with altered expression of proteins involved in leukemia stem cell homeostasis (β-catenin and Notch), cell motility, and adhesion (integrin-β3, ras-related C3 botulinum toxin substrate [RAC], and fibronectin), hypoxia (Hypoxia-inducible factor 1-alpha [HIF1α], egl-9 family hypoxia-inducible factor 1 [Egln1], and glucose-regulated protein, 78 kDa [GRP78]), and apoptosis (B-cell lymphoma-extra large (BclXL) and caspase 9).

CONCLUSION

Low TRIM62 levels, consistent with a tumor suppressor role, represent an independent adverse prognostic factor in AML.

Realizing the promise of reverse phase protein arrays for clinical, translational, and basic research: a workshop report: the RPPA (Reverse Phase Protein Array) society

Reverse phase protein array (RPPA) technology introduced a miniaturized "antigen-down" or "dot-blot" immunoassay suitable for quantifying the relative, semi-quantitative or quantitative (if a well-accepted reference standard exists) abundance of total protein levels and post-translational modifications across a variety of biological samples including cultured cells, tissues, and body fluids. The recent evolution of RPPA combined with more sophisticated sample handling, optical detection, quality control, and better quality affinity reagents provides exquisite sensitivity and high sample throughput at a reasonable cost per sample. This facilitates large-scale multiplex analysis of multiple post-translational markers across samples from in vitro, preclinical, or clinical samples. The technical power of RPPA is stimulating the application and widespread adoption of RPPA methods within academic, clinical, and industrial research laboratories. Advances in RPPA technology now offer scientists the opportunity to quantify protein analytes with high precision, sensitivity, throughput, and robustness. As a result, adopters of RPPA technology have recognized critical success factors for useful and maximum exploitation of RPPA technologies, including the following: preservation and optimization of pre-analytical sample quality, application of validated high-affinity and specific antibody (or other protein affinity) detection reagents, dedicated informatics solutions to ensure accurate and robust quantification of protein analytes, and quality-assured procedures and data analysis workflows compatible with application within regulated clinical environments. In 2011, 2012, and 2013, the first three Global RPPA workshops were held in the United States, Europe, and Japan, respectively. These workshops provided an opportunity for RPPA laboratories, vendors, and users to share and discuss results, the latest technology platforms, best practices, and future challenges and opportunities. The outcomes of the workshops included a number of key opportunities to advance the RPPA field and provide added benefit to existing and future participants in the RPPA research community. The purpose of this report is to share and disseminate, as a community, current knowledge and future directions of the RPPA technology.

CDKN2D-WDFY2 is a cancer-specific fusion gene recurrent in high-grade serous ovarian carcinoma

Ovarian cancer is the fifth leading cause of cancer death in women. Almost 70% of ovarian cancer deaths are due to the high-grade serous subtype, which is typically detected only after it has metastasized. Characterization of high-grade serous cancer is further complicated by the significant heterogeneity and genome instability displayed by this cancer. Other than mutations in TP53, which is common to many cancers, highly recurrent recombinant events specific to this cancer have yet to be identified. Using high-throughput transcriptome sequencing of seven patient samples combined with experimental validation at DNA, RNA and protein levels, we identified a cancer-specific and inter-chromosomal fusion gene CDKN2D-WDFY2 that occurs at a frequency of 20% among sixty high-grade serous cancer samples but is absent in non-cancerous ovary and fallopian tube samples. This is the most frequent recombinant event identified so far in high-grade serous cancer implying a major cellular lineage in this highly heterogeneous cancer. In addition, the same fusion transcript was also detected in OV-90, an established high-grade serous type cell line. The genomic breakpoint was identified in intron 1 of CDKN2D and intron 2 of WDFY2 in patient tumor, providing direct evidence that this is a fusion gene. The parental gene, CDKN2D, is a cell-cycle modulator that is also involved in DNA repair, while WDFY2 is known to modulate AKT interactions with its substrates. Transfection of cloned fusion construct led to loss of wildtype CDKN2D and wildtype WDFY2 protein expression, and a gain of a short WDFY2 protein isoform that is presumably under the control of the CDKN2D promoter. The expression of short WDFY2 protein in transfected cells appears to alter the PI3K/AKT pathway that is known to play a role in oncogenesis. CDKN2D-WDFY2 fusion could be an important molecular signature for understanding and classifying sub-lineages among heterogeneous high-grade serous ovarian carcinomas.

High-grade serous carcinoma (HG-SC) is the most common subtype of ovarian cancer observed in women. This subtype of ovarian cancer is typically detected at advanced stages due to lack of effective early screening tools. Recurrent cancer-specific gene fusions resulting from chromosomal translocations have the potential to serve as effective screening tools as well as therapeutic targets. Here we identified CDKN2D-WDFY2 as a cancer-specific fusion gene present in 20% of HG-SC tumors, by far the most frequent gene recombinant event found in this highly heterogeneous disease. We also presented evidence that the expression of this fusion may affect the PI3K/AKT pathway that is important for cancer progression. Thus CDKN2D-WDFY2 could very well represent a major cellular lineage important for detecting and classifying heterogeneous ovarian carcinomas, and could provide insight into the underlying mechanism of this deadly disease. This is critical, given that ovarian cancer kills 140,200 women worldwide each year, and few ovarian cancer-specific molecular alterations are currently available for targeting and screening.

Proteomic profiling identifies distinct protein patterns in acute myelogenous leukemia CD34+CD38- stem-like cells

Acute myeloid leukemia (AML) is believed to arise from leukemic stem-like cells (LSC) making understanding the biological differences between LSC and normal stem cells (HSC) or common myeloid progenitors (CMP) crucial to understanding AML biology. To determine if protein expression patterns were different in LSC compared to other AML and CD34+ populations, we measured the expression of 121 proteins by Reverse Phase Protein Arrays (RPPA) in 5 purified fractions from AML marrow and blood samples: Bulk (CD3/CD19 depleted), CD34-, CD34+(CMP), CD34+CD38+ and CD34+CD38-(LSC). LSC protein expression differed markedly from Bulk (n=31 cases, 93/121 proteins) and CD34+ cells (n= 30 cases, 88/121 proteins) with 54 proteins being significantly different (31 higher, 23 lower) in LSC than in either Bulk or CD34+ cells. Sixty-seven proteins differed significantly between CD34+ and Bulk blasts (n=69 cases). Protein expression patterns in LSC and CD34+ differed markedly from normal CD34+ cells. LSC were distinct from CD34+ and Bulk cells by principal component and by protein signaling network analysis which confirmed individual protein analysis. Potential targetable submodules in LSC included the proteins PU.1(SP1), P27, Mcl1, HIF1α, cMET, P53, Yap, and phospho-Stats 1, 5 and 6. Protein expression and activation in LSC differs markedly from other blast populations suggesting that studies of AML biology should be performed in LSC.