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RNA and Oncology

RNA and Oncology

In the previous post, we ran through a number of cellular processes where significant changes in gene expression profile are seen. Those processes set the stage for higher-order physiological events, such as chronic inflammation and tumorigenesis. RNA-seq can be used to diagnose many of these diseases once the underlying gene expression patterns have been established. Here, we will look more closely at oncology, a field where the use of RNA profiling is becoming extremely important for developing targeted treatment regimes.

RNA as a biomarker

The ability to identify and categorize a tumor at the genetic and molecular level is one of the most significant advances in oncology over the past decade plus, even though the biomarker field is still in its infancy. In an ideal situation, molecular diagnostics provide information about the specific tumor subtype and, by extension, its responsiveness to specific therapies and patient prognosis. Furthermore, biomarkers can indicate the presence of cancerous cells even before traditional pathology might come into play. As a result, discovery and validation of biomarkers is currently a high priority for cancer researchers.

RNA has turned out to be a promising biomarker for numerous cancers. MicroRNA (miRNA), short fragments of functional but non-coding RNA that often operate as regulators of gene expression, are a popular target of investigation. Specific changes in miRNA levels are indicative of disease. These changes may be the over- or under-expression of a miRNA relative to normal levels, as well as changes in the ratio between two miRNAs.

Research in the past several years has demonstrated that RNAs of many types are released from cells and enter systemic circulation. And unlike many cellular proteins, RNAs are relatively stable in circulation and easy to identify at low levels with current technology. Because of these features, isolating and characterizing RNA biomarkers is often a non-invasive procedure requiring only a blood draw (liquid biopsy).

Specific miRNAs have been identified as biomarkers of gastric, prostate, breast/ovarian, bladder, and squamous cell carcinoma, among others. In the latter instance, according to a 2011 review by Etheridge et al, it is a decrease in two miRNAs that indicate a problem. By contrast, bladder cancer appears to be highlighted by a change in the ratio of two miRNAs. A cancer’s miRNA profile may be useful for the purposes of clinical intervention, as well as diagnosis. For example, the presence of miR-221 in breast/ovarian cancer is indicative of chemoresistance, so clinicians may need to take a different approach to treatment in these patients.

 

Packaging of RNA

RNA can show up floating free in systemic circulation. However, a rapidly growing body of work shows that RNA is often loaded into tiny, membrane bound packages that are released from cells. These packages, called exosomes or microvesicles, are an important part of intercellular communication and other processes. Cells – both healthy and transformed – actively load certain miRNAs into microvesicles for release and transport to its neighbors. This gives clinicians concentrated packages of pathologically relevant biomarkers that can be isolated and characterized.

RNA can also be isolated from circulating tumor cells (CTC). These cells are released from the primary tumor and enter systemic circulation, often through a process of epithelial-to-mesenchymal transition followed by intravasation. Because these cells are in fact part of the tumor itself, they are by definition representative of the tumor’s genetic profile. RNA isolated from these cells is useful for RNA-seq to characterize the primary tumor. However, the first challenge is finding CTCs, which make up a tiny proportion of the total cell population in peripheral blood. A common approach is to isolate them by coating beads or other resins with antibodies against proteins known to be over-expressed by CTCs. From there, assays like Cofactor’s picoRNA can take the tiny quantities of isolated RNA and sequence it for clinically useful information.

 

Clinical applications of gene expression profiling

As noted above, gene signatures derived from RNA-seq are useful for characterizing a tumor’s molecular subtype. In addition, the genetic signature of a cancer cell can identify the tumor’s origin. Primary tumors and distal metastases often have different profiles, so distinguishing one from another can help in the tracking of disease progression and, potentially, the appropriate clinical intervention.

Related to this latter point is the issue of gene expression and drug sensitivity. Even in the early 2000s, researchers were using genetic profiling to build predictions of various cancers towards sensitivity or resistance to therapeutic intervention. For example, a paper from 2005 by Györffy et al treated 30 different cancer cell lines (in culture, not from fresh tumors)with 11 different cancer drugs. the group then used microarray to compare gene expression profiles of resistant and sensitive cell lines for each drug. Similar work has been ongoing, and is a significant part of the Precision Medicine Initiative. For more on this topic, see “Genomics driven-oncology: challenges and perspectives” by Normanno and Cree.

Finally, we will touch briefly on another related topic, that of gene expression and clinical outcome. Traditional pathology remains an important part of characterizing tumors, and physical characteristics are used for prognosis. Without a molecular component, though, these older methods can only go so far. As Stuart Schnitt puts it in his 2010 review:

Although these risk categories [built on traditional pathology] have been of great value for assessing prognosis and risk in groups of patients, their role in determining prognosis and evaluating risk in an individual patient with breast cancer is more limited, as patients with similar combinations of features may have very different clinical outcomes” (emphasis added).

This is where gene expression profiling comes in. Starting with microarray and now utilizing RNA-seq, clinicians have both the technology and the bioinformatics tools to define prognosis for cancer patients. A paper published in 2002 used microarray to develop a pool of roughly 5,000 cancer-related genes in breast cancer patients (representing about 1/5 of all protein-coding genes in humans). Even this early study concluded that “this gene expression profile will outperform all currently used clinical parameters in predicting disease outcome.” Genetic analysis can indicate many cellular characteristics, such as the likelihood of metastasis. Lung cancer, for example, is notorious for devastating metastases. Elucidating the genes involved in this process has helped with diagnosis, but is also useful for identifying candidate targets for future drugs.

All told, as the technology has advanced so has the predictive value, moving the field of oncology towards a point where diagnosis, prognosis and treatment regime are all part of an integrated and personalized process. As more cancer biomarkers and gene expression profiles are elucidated and validated, and as more anti-cancer therapeutics are developed, the importance of RNA-seq and other tools for gene expression analysis will continue to grow. Cofactor is now a CAP-CLIA certified lab. Additionally, we are developing Pinnacle, the RNA-based biomarker panel for cancer. For questions about this product, contact us to request more information.

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