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The RNA Revolution a Guide to RNA As a Biomarker and Its Detection

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The RNA Revolution a Guide to RNA As a Biomarker and Its Detection WHITEPAPER The RNA Revolution A Guide to RNA as a Biomarker and its Detection www.acdbio.com/whitepapers Whitepaper: The RNA Revolution TABLE OF CONTENTS Introduction 5 1. What is a biomarker? 5 2. The value of RNA biomarkers 6 3. The concept of alternative biomarkers 7 3.1 Protein-based biomarker detection 7 3.2 DNA-based biomarkers 7 4. Selecting the right RNA biomarker detection method 9 4.1 In-solution methods 9 4.1.1 Real-time PCR 9 4.1.2 Nuclease protection assays 9 4.1.3 Nanostring® Counter® technology 9 4.1.4 Summary 9 4.2 In situ methods 9 4.2.1 Conventional RNA ISH methods 10 4.2.2 Direct detection RNA ISH 10 4.2.3 RNAscope® ISH 10 5. Summary 14 References 15 © Advanced Cell Diagnostics Inc. 3 www.acdbio.com/whitepapers Whitepaper: The RNA Revolution EXPLORING BIOMARKERS WITH THE NEW CENTRAL DOGMA When is it best to measure DNA, RNA or protein? DNA + Single copy in situ detection possible – Does not indicate expression level: limited information Useful when: • Measuring large genomic alterations e.g. HER2 amplifi cation mRNA RNA ncRNA + Many biomarkers discovered from + Many biomarkers discovered from transcriptomic studies transcriptomic studies – In situ measurement techniques previously – In situ measurement techniques previously unsuitable for routine use unsuitable for routine use Useful when: Useful when: • Differential RNA expression • Transcriptomic discovery identifi ed as biomarker phase identifi es biomarker: • Protein measurement not ncRNA must be measured possible directly, as no protein counterparts • Limited correlation with protein levels: direct RNA measurement is desirable Protein + In situ detection for routine use available – Limited antibody performance or availability – Unsuitable as surrogate for RNA Useful when: • Differential protein expression and/or localization identifi ed as biomarkers • Quality antibodies available Figure 1: Exploring biomarkers with the new central dogma. It can be a daunting decision for scientists to know when to focus on DNA, messenger RNA (mRNA), non-coding RNA (ncRNA) or protein biomarkers for routine clinical use, with each exhibiting its own strengths and limitations. © Advanced Cell Diagnostics Inc. 4 www.acdbio.com/whitepapers Whitepaper: The RNA Revolution INTRODUCTION One of the biggest surprises of the human genome project and visualize DNA and proteins in their native context was that the number of protein coding genes found in our within single cells, until now the best routine measurement genome was unexpectedly small: a mere 20,000 versus tools for RNA analysis have been those that detect and the anticipated 100,000 or more. This presented a real quantify RNA in solution. However, these methods only conundrum for the research community – how does our provide an “average” measurement in a cell population, incredible level of phenotypic complexity and diversity masking the incredible level of cell-to-cell variation in arise from such a modest set of genes? Discovering the RNA expression. With its central role in cell physiology, world of non-coding RNAs revealed the answer, thanks to protein has been the more popular biomarker traditionally, new transcriptomic technologies such as microarrays and providing functional insights into disease states while also next generation sequencing (NGS) enabling new avenues lending itself to well-established detection techniques. The in RNA research. Today, new classes of RNAs are being lack of effective RNA in situ detection methods has often discovered on a regular basis that do not code for proteins, resulted in the use of DNA and protein as surrogates for but instead have a hand in genetic regulatory control and those RNA biomarkers initially discovered, however this a wide range of cellular activities. Amazingly diverse and can be problematic. Changes in RNA expression may not changeable, these transcripts have the potential to produce result from DNA alterations and may not correlate with any number of splice variants, and in the latest catalog protein levels – or there may be no protein counterparts compiled by the ENCODE project, [1] we now know that at all in the case of non-coding RNAs. The bottom line is, there are approximately 60,000 genes and ~200,000 RNA when utilizing RNA biomarkers initially discovered during species. This RNA revolution has created a fundamental microarray or RNA-seq programs, the best approach is shift in how researchers now view “the central dogma”, direct RNA measurement in situ, since the use of a DNA challenging the traditional idea that DNA is the master and or protein surrogate, or solution-based RNA analysis, RNA merely the messenger. The revelation of RNA’s vast inevitably leads to information loss, compromising the full number and diverse role in gene regulation has brought to diagnostic utility of the RNA biomarker. light the many possibilities for using RNA as an indicator The discovery of the “new world” of RNA has sparked an of biological states: the biomarker. unprecedented drive towards better tools to characterize Indeed, the widespread use of transcriptomic profiling the complexity of RNA – in terms of quantity, function and in cancer research over recent years has proven that, spatial distribution. Presenting a vital piece of the puzzle like protein, RNA is a rich source of clinically valuable in elucidating the role played by RNA in disease states, biomarkers for diagnosis, prognosis and predicting pinpointing the localization of specific RNAs within cells therapeutic response. [2, 3] Although such transcriptomic and tissue architecture is an important factor in realizing profiling may identify many potential biomarkers, translating its true potential as a biomarker. Here we examine the these discoveries into the clinic for routine RNA biomarker utility of RNA as a biomarker, and how this is profoundly measurement presents challenges in terms of established linked to the developing technologies now available for its analytical technologies. While it is commonplace to detect detection, localization and validation. 1. WHAT IS A BIOMARKER? The term biomarker is currently defined as ‘a characteristic components of the cell: DNA, RNA or protein. As we will that is objectively measured and evaluated as an indicator explain in more depth, while DNA biomarkers provide a of normal biological processes, pathogenic processes, or static view of the cells and protein biomarkers suffer from pharmacologic responses to a therapeutic intervention or variable detection success (albeit through well-established other health care intervention’. [4] Biomarkers have long techniques), RNA biomarkers are both functionally been used for diagnostic testing and the identification of significant and now benefit from new robust tools for potential therapeutic targets, and are growing exponentially detection (Figure 1). in their importance in the era of personalized medicine. Of course, a biomarker is only as good as its routine A valuable biomarker is capable of uncovering a specific analysis methodology – which demands the capabilities biological trait or measurable change directly associated highlighted in Box 1. with a physiological condition or disease status, [5] and they therefore tend to be one of the three main functional © Advanced Cell Diagnostics Inc. 5 www.acdbio.com/whitepapers Whitepaper: The RNA Revolution Box 1: The optimal biomarker method Detection Localization • Accurate and precise biomarker analysis requires • Since differential expression across cell populations sensitivity to detect even the most scarce molecules, forms the basis for multicellular physiology, and specificity to differentiate between multiple analyzing a biomarker in its morphological related molecular species. context presents an especially powerful tool. Visualizing such expression in situ, within intact Quantification tissue morphology also opens many doors for researchers, particularly in the area of cell-to-cell • While measuring biomarker levels at a continuous communication. For example, examining autocrine scale provides more accurate information than and paracrine networks, and communication within detection alone, levels can vary significantly even tumors or between tumor and stroma. between individual cells. An average measurement over a population of cells may therefore obscure significant events, while single-cell analysis can reveal important intercellular heterogeneity, yielding more insightful data. 2. THE VALUE OF RNA BIOMARKERS Our understanding of RNA is constantly evolving, with discoveries over the last few decades including alternative splicing and the catalytic activity of some RNAs, along with the identification of many small non-coding and long non-coding RNAs (lncRNAs). [6] It has become increasingly clear that RNA is a key player in a myriad of both normal and disease-related cellular activities, and genetic regulatory control. For this reason, RNA has become a molecule of great interest and value across the research, diagnostic and pharmaceutical arenas, and since RNA expression reflects the state of a biological system, it presents an ideal choice of biomarker. RNA expression levels are highly dynamic and integrate both genetic and epigenetic mechanisms of gene regulation, serving as an excellent molecular phenotypic readout of Figure 2: Revealing the RNA expression signature of individual the functional state of the cell. In order to utilize the full cells within the tissue architecture. Human breast cancer potential of these biomarkers, there is an unprecedented FFPE
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