About Us

Protein extracts obtained from cultured cells or tissues are serially diluted, spotted onto nitrocellulose-coated microscope slides and probed for a specific protein or protein modification via antibodies that have been validated for RPPA use. Probing for protein modifications of samples enables functional proteomics studies applicable to systems biology analyses. Probed signals are scanned to obtain digital images of the slides; spot densities from the digital images are quantified via software to determine relative levels of the protein for all samples on the slide. Software is also used to determine staining quality of each slide. Each slide is probed with one antibody; replicate slides are printed to probe for approximately 500 different antibodies to produce a functional proteomic profile of each sample. 

Advantages of RPPA and Functional Proteomics

Studies of complex diseases such as cancer have shown that genetic alterations do not account for all causes of the disease. Changes in protein levels and structure have also been shown to play critical roles in tumor development and progression. In cancers, several genetic and epigenetic changes are often required for development of the disease. Studying large-scale epigenetic changes such as protein phosphorylation or cleavage will greatly aid in understanding the causes and determining effective treatment of cancers and other complex diseases.

Advantages of the RPPA platform include the following: 

• Cost effective: A high throughput approach concurrently tests and quantifies over 1000 samples on a signal slide.
• Sensitive: Applicable to very small sample sizes (ng of protein lysates, detecting attomoles of a specific protein), less than 10 cell equivalents. It detects and quantifies hundreds of different proteins at their expression levels and modification status in 80 µl of cell lysates.
• Quantitative: Serially diluted samples enable detection of proteins in their linear range to reliably determine relative protein levels of all samples.
• Simple: Does not require direct labeling of the sample; samples can be submitted without additional modification
• Versatile: An antibody-based platform can probe for various protein-associated effects including modification of basal protein expression levels, growth factor‐ or ligand‐induced effects, and time resolved responses appropriate for systems biology analyses. It provides information to integrate the consequence of genetic aberrations in cancer, validate therapeutic targets, demonstrate on‐ and off‐target activity of drugs, and evaluate drug pharmacodynamics.

Our Unique Platform

UT MD Anderson's RPPA Core maintains and improves upon its high quality output by continuously validating and performing quality control checks on all aspects of its RPPA Pipeline, including the following: 

• Serial dilutions of each sample to capture the linear antibody-antigen reaction for accurate data analysis
• A continuously developing and highly stringent antibody validation process to select and maintain only the most qualified antibodies for RPPA analysis
• 48 unique cell lysates printed on every slide for quality controls of data generation and analysis as well as for replicates-based normalization to merge RPPA data across different slides
• A combination of various additional quality control processes developed, implemented, and optimized for our RPPA data analysis to provide reliable data to customers: algorithms of spatial correction, quality control of antibody probing, protein loading correction, replicates-based normalization, and quality determination of antibody batches
• An automated program for RPPA Pipeline processes implemented to reduce manual labor, human error, and customer turnaround time 

The RPPA Process

The RPPA Core analyzes expression and modification of proteins in cultured cells (human and animal) and tissues, including blood cells (excluding erythrocytes) and patient derived xenografts.

Cell Lines 

• Characterize cell signaling networks under different culture conditions
• Determine drug selectivity
• Identify therapeutic targets
• Define regulatory mechanisms in signaling networks, including forward and feedback loops and crosstalks
• Analyze up to 1000 conditions concurrently such as for detailed concentration and time course studies for systems biology approaches  

Patient Samples 

• Classify patient tumors
• Correlate DNA, RNA and protein
• Determine prognosis
• Predict responses to targeted therapies
• Provide pharmacodynamics and biologically relevant dose
• Determine appropriate handling procedures for clinical samples (based on antigen stability analysis) 
  

We currently do not accept FFPE samples for RPPA processing due to the lack of quality and analyzable protein present within this sample type. 

Rationale

Molecular therapeutics is designed to capitalize on tumor cells that arise from the rewiring of functional networks due to genomic and epigenetic changes in tumor or their effects on the tumor environment. Although DNA and RNA analysis have been used extensively to identify novel targets and to define patients likely to benefit from targeted therapies, they provide only indirect measurements of the functions of most therapeutic targets. Therefore, assessing changes on the levels of protein expression and function is the most efficient way to evaluate the mechanisms underlying sensitivity and resistance to targeted therapy.

Reverse phase protein array (RPPA), an antibody-based assay, has emerged as a robust, sensitive, and cost-effective approach to analyze large numbers of samples for quantitative assessment of key protein molecules in functional pathways. The RPPA platform is a powerful measurement to identify and validate targets, classify tumor subsets, assess pharmacodynamics, and define prognostic and predictive markers, adaptive responses and rational drug combinations in model systems as well as in patient samples. Its greatest utility is through integration with other analytic platforms such as DNA sequencing, translational profiling, epigenomics and metabolomics.

RPPA determines levels of protein expression and modifications such as phosphorylation, cleavage, and fatty acid alteration. RPPA allows concordant interrogation of multiple signaling molecules along their functional status. We utilized RPPA to profile and validate signaling networks in human cancer cell lines and tumor tissue.

Each sample is analyzed for cell cycle progression, apoptosis, functional proteomics, and signaling network activity. The results will be classified and compared with disease patterns to generate a gmolecular signature. The integrated information will display potential therapeutic targets or biomarkers to accurately predict or rapidly define intracellular signaling networks and functional outcomes affected by therapeutics, providing an expanding repertoire for clinical evaluation.

Availability of key reagents required for execution of the high throughput RPPA project

We have extensively validated about 500 different monospecific antibodies to signaling molecules that are useful for the RPPA approach. These antibodies are assessed for specificity, quantification and sensitivity (dynamic range) using protein extracts from cultured cells or tumor tissue. These antibodies specifically recognize proteins acting on multiple signaling pathways, including receptor tyrosine kinases, PI3K-AKT and MAPK cascades, LKB1-AMPK and TGFƒÀ cascades, as well as DNA repair, cell cycle and apoptosis/autophagy regulators. We are currently validating a group of antibodies for monitoring immune responses to cancer development and to cancer therapy. We update our antibody list routinely and post it publicly on our website to the proteomics community around the world. 

We have also established QC processes to improve the quality and accuracy of RPPA data sets. A set of cell lysates has been defined, prepared in large quantities and designated as "Control Lysates." Technical replicates of these Control Lysates are placed on each RPPA slide at different locations to assess assay sensitivity, stability, and reproducibility. These Control Lysates also serve as a standard for batch variation adjustment. Additionally, a large quantity of "Mixed Lysates" has been prepared from 32 different cell lines. Serial dilutions of Mixed Lysates are printed for 96 technical replicates on each slide at different locations as a standard for spatial correction and quality control in data analysis to determine relative protein concentration. The QC score from quality control samples indicate good (above 0.8) or poor (below 0.8) antibody staining. Poor QC slides are excluded from further data analysis and in most cases, are repeated for staining with different antibody concentrations.

We have full access to an Integra Assist Plus pipetting robot for serial dilution of cell lysates and sample transfer, two Quanterix 2470 arrayers for printing up to 100 slides per run with several automated runs continuing for several days, and three Agilent Link 48 autostainers that probe each slide with a different antibody. Each autostainer is capable of staining up to 48 slides per day under conditions that are specific for each individual antibody.

Approach

Currently, we perform RPPA on samples prepared from frozen tissue or from cultured cell lines.

For tumor tissue, we extract proteins from about 15 mg of snap frozen tissue by homogenizer or ceramic beads. Protein concentration will be determined and adjusted to 2.g/.l.

For cell lines, we prefer a 6-well format to obtain enough protein for the entire procedure. Briefly, we select cell lines based on a specific disease model. Cells are seeded in 6-well plates and treated according to experimental design. Cells are lysed in 6-well plates and protein concentration adjusted to 1.5.g/.l.

Proteins extracted from frozen tissue or cultured cells are denatured by 1% SDS + B-Me followed by serial dilution (to detect the antigen-antibody reaction in a linear range for accurate quantification). Serially diluted cellular proteins are arrayed on nitrocellulose-coated slides and probed with validated antibodies that recognize signaling molecules in their functional state. Signals are captured by tyramide dye deposition and a DAB colorimetric reaction. Data is collected and quantitative analysis is performed using custom spot finding and curve fitting software developed for this purpose. Features include automated spot identification, background correction, controlling for location, serial dilution-signal intensity curve construction, and concentration determination. The values derived from the slope and intercept of the "supercurve" construction are expressed relative to standard control cell lysates or control peptides on the array. These values indicate the levels of protein expression and modification (phosphorylation or cleavage based on antibody specificity).

We analyze the data for the presence of clusters, based on differential protein expression by using available methods with the R statistical software package. We will use a variety of unsupervised clustering methods (including hierarchical clustering, K-means, independent component analysis, mutual information, and gene shaving) to classify the samples into statistically similar groups. We will evaluate the robustness and statistical significance of these groups using bootstrap resampling of the data. By plotting the data under each condition or each disease pattern independently, we will be able to evaluate linked events and create a database for pathways and networks. Alterations in important signaling molecules in multiple pathways will be correlated to the data from cell survival assay or patient outcomes and integrated to allow rapid assessment of functional proteomics studies.