6.5 Prognostics

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What are prognostic tools for cancer? 

 

At their core, prognostic tools are standards to predict patient survival in cancer. Traditionally, prognostic factors have been defined as “factors that predict disease outcome in the absence of systemic adjuvant therapy.” Systemic adjuvant therapy refers to additional treatments given after the main treatment. However, with the increasing number of patients that relapse after therapy, the definition of prognostic tools has been redefined to mean “a factor that predicts outcome in the absence of systemic therapy or predicts an outcome different from that of patients without the marker, despite empiric therapy” (1). In other words, prognostic tools must specifically predict patient survival that is independent of treatment and at a distinct molecular level.

 

 

Types of prognostic tools

 

Many prognostic tools exist. A previous standard was the tumour, node, metastasis (TNM)-staging system (2), where doctors evaluate a patient’s condition by monitoring the behavior and appearance of a tumour. Despite being used for over a decade, this method is limited, because many times, the physical characteristics of the tumour fail to correlate with actual disease complications.

 

Recently, with developments in genome sequencing, targeted therapies, and molecular diagnostics, prognostic tools strive to be personalized on the molecular level (1). This is made possible by the identification of biomarkers: molecular entities (DNA, RNA, and protein) that specifically correlate with patient outcomes. Biomarkers are collected and isolated from patient serum and tissue samples. 

 

 

1) Serum-based markers

 

Blood collected from cancer patients can be screened for serum-based markers. These markers tend to be soluble proteins or nucleic acid deposited by the tumor cells through extracellular release. Assays used to screen for these markers include microarrays for the nucleic acids of interest, or immunoassays for the secreted proteins. Prostate-specific antigen (PSA) is a common serum-based biomarker for prostate cancer while various miRNAs serve as prognostic biomarkers for breast cancer (4). 

Collecting serum-based markers is advantageous because they are easy to obtain and and the process is relatively non-invasive. Quantitatively measuring these markers in the blood is powerful as it enables doctors to rapidly diagnose patients, even at early stages of tumor development, and effectively monitor tumor progression through changing levels of the biomarkers.

 

 

2) Tissue-based markers

 

Biopsies from patients (surgically removed tumor samples) are screened for tissue-based biomarkers, which are typically extracellular receptors. One example is the human epidermal growth factor receptor-2 (HER-2) for breast cancer. A plethora of disruptions have been identified in HER-2, including gene amplification and protein overexpression, which are specific to tumor cells and associated with poor outcomes (3). 

Identifying the type of disruption to tissue-based biomarkers is vital for risk evaluations and stratifying patients for treatment. For instance, HER-2 is currently being used to identify patients that will respond favourably to specific anti-HER-2 therapies like trastuzumab (Herceptin).

 

Another prognostic tool that is used to predict patient survival is the presence or absence of circulating tumour cells (CTCs). It has been found that the presence of >5 CTCs in 7.5 mL of peripheral blood is associated with unfavourable outcomes (poor overall survival) in metastatic breast, colorectal, and prostate cancer (5). Circulating tumour cells are associated with the epithelial-mesenchymal transition (EMT) that occurs during metastasis. They can be isolated and enumerated using the CellSearch System (5).

 

 

Prognostic Tools and Adverse Drug Reactions (ADR)

 

Prognostic tools are currently being used to minimize adverse drug reactions (ADR). Currently, there are two markers available for recognising ADRs in cancer therapy. The first is an enzyme that we discussed in the previous section, thiopurine methyltransferase (TMPT). Recall that this protein marker predicts toxicity from thiopurines during treatment of acute lymphoblastic leukemia (ALL). The other marker is uridine diphosphate glucuronyltransferase 1A1 (UDP-UGT1A1) used in the treatment of colorectal cancer, which it predicts toxicity to the drug called irinotecan.

 

As mentioned previously, genotyping is used to determine a patient's risk for ADR. Knowing a patient's genetic TMPT status from genotyping results allows doctors to evaluate whether that patient can tolerate and respond appropriately to the standard dose thiopurine treatments or if they need to have their treatment tailored (1).

 

 

Challenges and Goals of Biomarker Discovery

 

Despite progress, biomarkers are difficult to evaluate. Many of the current markers don’t correlate specifically with patient survival, but are associated with other factors including age, sex, and smoking status.

 

Biomarkers must correctly differentiate patients with a less severe disease from those with more aggressive forms in order to separate patients that can receive treatment and respond favourably and those that will experience harmful consequences if they receive the standard treatment.  These consequences include failed treatment due to chemotherapeutic resistance or life-threatening side effects such as ADR (1). The ultimate goal of biomarker discovery is to find the right treatment for the right patients at the right time.  

 

Tumor exosomes as diagnostic and prognostic tools for cancer

 

Exosomes are one mechanism by which normal cells transfer messages between each other [6]. Essentially, exosomes are a key method of cell signaling [6]. They are nanosized membrane vesicles that have been found to contain various RNA molecules (including miRNA, mRNA and long non-protein coding RNA) as well as protein effectors [6].

 

It has been shown that a number of cancer cell types secrete elevated levels of exosomes [7]. Elevated exosome levels were shown in a variety of tumor types including breast, colorectum, brain, ovarian, prostate, lung and bladder cancer [7]. Currently, there are multiple hypotheses as to why tumor cells have increased exosomal secretion. It has been speculated that tumor exosomes contain pro-angiogenic factors, that when taken up by recipient cells promote the growth of blood vessels within the tumor [8]. In addition, it is thought that tumors control protein expression in various recipient cell types that internalize the exosomes as well as immune cells in order to regulate their microenvironment. One proposed mechanism for such a phenomenon is that miRNAs present in the exosomes silence the expression of specific genes in the recipient [7,9].

 

Aberrant miRNA expression is common to most tumor cell types [9]. MiRNAs are thus common constituents of tumor exosomes [9]. After the secretion of miRNA-containing exosomes by the tumor cell, the exosomes are taken up by recipient cells [7,9]. These recipient cells may be in the form of immune cells such as T cells, B cells, macrophages, neutrophils and dendritic cells. Upon release of the exosomal constituents into the recipient cytoplasm, miRNAs play various modulatory roles within the recipient cell [9]. They associate with multiple host cell factors to form the RNA-induced silencing complex (RISC) which acts to degrade specific host cell mRNAs [7]. By employing this mechanism, tumor cells can regulate the expression of various genes within the many different cell types in our body [9]. It has been recently shown that tumor-derived miRNAs can bind to Toll-like receptors and induce a prometastatic inflammatory response, thereby facilitating their own metastasis [9].

 

Tumors have been shown to secrete exosomes containing pro-angiogenic factors in large quantities [8]. Generally, the rate-limiting step in the growth of a solid tumor is the activation of myofibroblast formation and the development of blood vessels within the tumor [8]. In order to overcome this challenge, tumor cells secrete massive amounts of exosomes containing various effectors responsible for the stimulation of angiogenic growth [8]. For example, the secretion of exosomes containing pro-angiogenic proteins such as VEGF and TGFb have been shown to induce myofibroblast-rich interstitial stromal formation in prostate cancer [8].

 

Since exosomes consist of characteristic protein and RNA signatures of their host cells, a high throughput analysis of exosomal contents across in a wide variety of cancers can be implemented to generate data for the production of a non-invasive diagnostic and prognostic tool for cancer [10]. Many scientists believe that by surveying the contents of tumor exosomes in various stages of cancer, clinical prognostic and diagnostic tools can be developed to determine the stage of the disease. Essentially, tumor exosomes can be used as biomarkers for disease progression due to the specificity of their contents at each step of disease progression [10]. This theory is made potentially feasible due to the fact that exosomes can be easily isolated from a patient’s blood (among other bodily fluids) with minimum invasiveness [10].

 

References

  1. Duffy, M. J., & Crown, J. (2008). A personalized approach to cancer treatment: how biomarkers can help. Clinical chemistry54(11), 1770-1779.
  2. Garman, K. S., Nevins, J. R., & Potti, A. (2007). Genomic strategies for personalized cancer therapy. Human molecular genetics16(R2), R226-R232.
  3. Xu, C. Molecular and Genetics Testing For Personalized Cancer Treatment. 8It just keeps working.=, 29.
  4. Tessari, A., Palmieri, D. & Di Cosimo, S. (2014). Overview of diagnostic/targeted treatment combinations in personalized medicine for breast cancer patients. Pharmgenomic Pers Med, 7: 1-19.
  5. Miller, M.C., Doyle, G.V., Terstappen, L.W.M.M. (2009). Significance of circulating tumor cells detected by the CellSearch System in patients with metastatic breat colorectal and prostate cancer. Journal of Oncology. 2010, 617421: 1-8
  6.  Asfar S. Azmi, Bin Bao, Fazlul H. Sarkar. (2013). Exosomes in cancer development, metastasis and drug resistance: a comprehensive review. Cancer Metastasis Review. 32:623-642.
  7.  Jenjaroenpun P, et al. (2013). Characterization of RNA in exosomes secreted by human breast cancer cell lines using next-generation sequencing. PeerJ.
  8.  Webber JP, et al. (2014) Differntiation of tumor-promoting stromal myofibroblasts by cancer exosomes. Oncogene.
  9. Gajos-Michnieqicz A, Duechler M, Czyz M. (2014). MiRNA in melanoma-derived exosomes. Cancer Letters.
  10.  Duijvesz D, et al. Exosomes as biomarker treasure chests for prostate cancer. European Urology. 59:823-831.