High Throughput Genomics (HTG) Launches New Product Category: Multiplex Mini-Microarrays (The M3™ Series) Come to Life in Drug Discovery and Research Laboratories Around the World

Introduction

Multiplexed gene expression assays benefit drug discovery by addressing the multi-factorial nature of many disease and drug mechanisms. qNPA ArrayPlate multiplex gene expression improves the precision of data generated from cells, tissue, and fixed tissue (FFPE) samples by removing steps that introduce experimental variation. qNPA technology speeds the research process by enabling accurate and precise time course, dose response, and EC50 values to be determined for multiple genes in hundreds to thousands of samples per day.

The qNPA™ ArrayPlate

HTG’s multiplexed gene expression products are based on the quantitative nuclease protection assay (qNPA™) with a simple, add-only protocol requiring no RNA extraction, amplification, cDNA synthesis, or sample labeling, eliminating many time-consuming manipulations and sources of experimental variation seen in other gene expression technologies. The combination of high sample throughput and data precision makes the qNPA ArrayPlate uniquely suited for discovery applications measuring hundreds to thousands of samples per day.

The qNPA ArrayPlate assay is performed in a flexible microplate format customized by the user to measure any set of 16 genes, the mini-microarray. The protocol is simple, robust, and reproducible in both day-to-day and lab-to-lab testing conditions. HTG’s high throughput OMIX™ II Chemiluminescent Imager collects the data from an entire ArrayPlate in less than 2 minutes. The low cost per data point, reproducibility, and streamlined workflow of the qNPA protocol make it the ideal tool for analyzing gene expression in a highly automated lab setting.

Single-well multiplexing with qNPA enables the measurement of housekeeping genes in the same sample context, providing more reliable normalization than controls performed in separate wells. The ArrayPlate assay delivers average whole assay CVs (reproducibility) of <10%, and reliable gene expression fold-changes of ~20%. These results hold true whether the starting samples are cultured cells, fresh or frozen tissues, fixed tissues (FFPE) or whole organisms. qNPAs practical sensitivity that is similar to that of PCR.

Paradigm shift in Drug Discovery: Getting back to the biology.

In the rush to develop drugs in the post-genomic era, the pharmaceutical industry has been restricted to screening targets with an incomplete understanding of the associated biology. Ten years ago, an average of 100 papers was published on a disease target before screening was performed; today the average is four. Currently, most screens focus on individual genes because they can be easily formatted for a homogeneous assay for subsequent interrogation using a chemical compound library.

This approach is ineffective for many diseases which are known to be the result of dysfunction in multiple genes and gene pathways. For instance, breast cancer genes such as BRACA1, p53, and PTEN have been implicated in the initiation of disease. Different sets of genes are involved in the metastasis, cell escape and migration, immune evasion, implantation, continued replication, and angiogenesis associated with the disease. Producing an assay or panel of assays to monitor all of these events would be a daunting task using traditional, single-gene models of screening in drug discovery.

Using qNPA to quantitatively measure transcriptional profiles in a small molecule, cell based screen greatly simplifies these challenges. By understanding the behavior of a group of genes responsible for a disease and empowering researchers to screen based upon this gene signature, we provide the researcher a deeper insight into the biology of the disease.

qNPA in Drug Discovery

Lead Compound Screening

Gene expression profiles generated with the qNPA ArrayPlate have been used to discover novel molecules that have both the desired drug efficacy and reduced side effects. In a recent collaborative project, lead compounds were developed for treating bipolar disease without the debilitating sedation side-effect many patients experience. By examining overlapping sets of genes from whole-genome microarray experiments and existing drug compounds that had a well defined treatment phenotypes, our collaborator was able to profile the genes responsible for the desirable and undesirable drug effects.

They then narrowed the gene set to 14 relevant transcripts and ran a small molecule screen using the qNPA ArrayPlate to monitor gene expression levels. The research group was able to develop a series of candidate compounds that showed efficacy towards bipolar disease without the adverse side effects in animal models.

A similar second project was initiated for Schizophrenia treatments that showed efficacy without the increased risk of diabetes development seen with many current drugs. Using the same gene signature paradigm, they were able to produce drug candidates that had the desired effects in an animal model.

Toxicology

The power of a cell-based, multiplexed screen is clear – drugs and diseases act in and on organisms, not the purified biochemical assays often used for initial compound screening. Since unwanted drug side effects often become apparent only when the biology of the test system becomes more complicated, starting the discovery process with a cell based approach can provide immediate time and cost savings. Including pre-clinical safety indicators in the primary screen can identify compounds which might fail safety testing fail earlier in the drug discovery continuum, allowing for compound redesign or earlier termination of the project.

The highly quantitative nature of qNPA allows it to be used to determine precise gene-based EC50s by performing dose response curves. This approach substitutes gene expression levels for biochemical activity typically measured in EC50s. QSAR studies can be quickly and reliably done to promote a hits-to-leads program based upon qNPA ArrayPlate results.

Retrospective studies from archived tissues (FFPE)

Biomarker and prognostic discovery

Pharmaceutical companies and medical schools possess large archives of clinical samples with highly annotated medical information. These specimens are typically formalin fixed-paraffin embedded (FFPE) tissue that has limited utility with most modern molecular gene expression methods due to poor RNA quality. The qNPA approach does not require the RNA to be intact or soluble, and is therefore uniquely suited to measure gene expression in these difficult samples.

A recently published paper in Lab Investigations using the qNPA ArrayPlate demonstrated that an FFPE sample archived over 18 years ago yielded identical results to a matched frozen sample that was freshly fixed. In the study, HTG along with the Fred Hutchinson Cancer Center and the Arizona Cancer Center began a retrospective examination of Diffuse Large B-cell Lymphoma (DLBCL) tumors.

Non-overlapping gene signatures for prognostic staging of the disease have been reported in several publications. The consortium assembled three gene signature arrays that contained minimal gene overlaps and undertook a forty sample study to determine the efficiency with which these genes correctly assigned disease stage.

The results of the initial study suggested that the qNPA ArrayPlate approach could determine disease stage by matching the gene signature of the blinded sample to that of a reference specimen. A larger study recently published in the journal Blood tested an additional 200 samples and provided corroborating results for the earlier tests. Most of the samples used in this study were FFPE tumors ranging from 6 to 18 years old – all samples provided excellent results.

Reexamination of Failed Drug Candidates

Historically, the research value of archived samples declines as they age due to degradation of the RNA contained within them. This reduces their utility for research because they are not able to be matched with prognostic or diagnostic gene signatures consisting of newly discovered genes and biomarkers. A qNPA approach can, however, turn back the clock on these specimens and unlock decades of gene expression data in otherwise inaccessible, unusable samples.

Among the possibilities is the reexamination of drug candidates that failed during late phase clinical trials due to insufficient or incomplete efficacy. With a fuller understanding of the genes responsible for the disease, a drug can be retested to determine if a more suitable clinical study cohort can be designed and the drug targeted specifically towards a subset of disease sufferers. Failed drugs may be powerful treatments for different forms of disease which are not readily differentiated using histopathology or other traditional diagnostic methods.

Summary: Enabling Power of a Multiplexed Assay

Multiplexed gene expression assays permit simultaneous rather than sequential measurement of biological processes, increasing productivity, providing higher content data, and generating data in a more biologically relevant context. The necessity to select a single drug target for intensive screening is eliminated, reducing hypothesis failure risk and potentially eliminating years of experiments needed to select the single target.

Pursuing drug discovery programs through multiplex gene expression instead of single target screens provides advantages by:

• Eliminating the time needed to identify the protein or biochemical targets and develop the required screening assays. Research efforts can be spent on drug compound development instead of assay development.

• Opening high throughput screening at the level of whole cells, tissues, and whole organisms. qNPA overcomes many of the issues that cause in vivo data to be far less reproducible than in vitro data.

• Providing a molecular profile of the disease and treatment phenotype instead of a single gene response data point. This profile provides more biological context for the screening result.

• Permitting potential side effects to be discovered earlier in the discovery and optimization process, leading to earlier failure or redesign of lead compounds.

Companion diagnostics: qNPA in the Clinic

In the future, companion diagnostics based on quantitative multiplexed diagnostic gene expression assays like qNPA are expected to provide a fuller, more accurate understanding of a patient’s disease state, stage, and subtype. Related diagnostics could also be used to monitor drug efficacy during drug therapies to guide more effective, personalized therapies. qNPA-based diagnostics have the ability to bring the promise of personalized medicine into mainstream clinical practice.

With its extremely low CVs, qNPA is uniquely suited to analyze subtle, yet biologically important changes in gene expression that can affect the patient’s response to a treatment. qNPA can deliver a level of data precision that other multiplexed diagnostic platforms, such a RT-qPCR, cannot. In the future, disease diagnosis and proper treatment course may be determined with a single qNPA-based test, instead of the complex, iterative approach used in the clinic today.

Conclusion

High throughput multiplexed gene expression analysis offers researchers a powerful new tool for drug discovery. Interrogating multiple genes in the same sample improves the precision of the data and provides a broader, more in-depth view of the underlying biology. The qNPA ArrayPlate provides a simple, precise, and cost effective means to study the complex biology of many diseases challenging drug development programs today and holds the promise of better prognostic and diagnostics in the future.