Cancer Biomarkers

A biomarker is any substance that is measured biologically and associated with an increased risk of diseases. Biomarkers can be present in the serum, or be genetic testing factors, and all are being studied acutely to find out how they can be of more use in cancer screening. Serum biomarkers are produced by body organs or tumors and measure antigens on cell surfaces. When detected in high amounts in blood, they can be suggestive of tumor activity. Serum biomarkers are nonspecific for cancer and can be produced by normal organs as well.  

Biomarker is a measurement which provides insight into the biological process underlying the cancer, and/or gives clinically useful information about an individual malignancy, additional to established clinical parameters such as performance status. This can be:

• Diagnostic —maker specific for the cancer
• Prognostic—marker correlates with extent of disease/natural history
• Predictive—marker correlates with responsiveness/resistance to therapy
• Response assessment—marker correlates with treatment efficacy or development of refractory disease (1). 

A number of biomarkers are well established in oncological practice: 

• Serum alpha-fetoprotein (AFP), human chorionic gonadotrophin (HCG), and lactate dehydrogenase (LDH) are validated prognostic markers for germ-cell malignancies of the testis, and are key to monitoring patients during treatment and on surveillance
• Tumor estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), assessed by immunocytochemistry or fluorescence in situ hybridization (FISH), provide valuable predictors both of response to targeted therapy and prognosis in breast cancers (1).

Commonly used tumor markers: 

• Serum CA125 in ovarian cancer- cancer antigen 125 can be a biomarker of ovarian cancer risk or an indicator of malignancy, but it has low sensitivity and specificity. Levels of this marker can be high in people who have pancreatitis, kidney or liver disease, making its accuracy as a cancer diagnostic tool very limited. However, it can be used to follow the progress of treatment of cancer, and predict a treatment failure when levels rise despite the use of chemotherapeutic agents. Sometimes, a combination of several tumor markers can give risk predictions in someone whose family history for the disease is quite high.

• Serum carcinoembryonic antigen (CEA) in colorectal cancer (but also elevated in e.g. non-small-cell lung cancer (NSCLC) and breast cancer-carcinoembryonic antigen (CEA) is another biomarker that is elevated in patients with colorectal, breast, lung, or pancreatic cancer. As a screening test, it can be elevated by many other factors than cancer; smoking for instance raises CEA levels. Following CEA post-surgery for colon cancer however is an effective way of determining the adequacy of postoperative therapy.

• One of these serum biomarkers in wide use is prostate serum antigen (PSA). PSA is produced by normal prostate cells in small amounts, but the higher the PSA is in the serum, the higher the correlation is toward the existence of prostate cancer. PSA is probably the only serum biomarker currently used consistently in primary care. There are reasons other than cancer that can cause rises in PSA. Infections within the prostate gland (prostatitis), increased exercise with irritation of the affected area, and even vigorous physical examination by a doctor can cause a PSA rise. Factors such as the degree of elevation, the rapidity of increase, and the fraction of free non-bound PSA (higher in benign causes) are all factored in to determine a next step. While no treatment is ever based solely on a PSA, alterations above normal can spur further diagnostic testing to catch the disease at an early stage. While PSA is used in insurance testing to assess the risk of underlying prostate cancer.

• Serum thyroglobulin in follicular and papillary thyroid cancer.
• Serum calcitonin in medullary carcinoma of the thyroid.
• Urinary 5-hydroxyindoleacetic acid (5-HIAA) in carcinoid tumors. 

Development of biomarkers

Progress in the understanding of the molecular biology of cancer has been paralleled by the development of laboratory technology in the fields of genomics and proteomics. Tissue micro-array technology was first described in 1987, and over the last 10 years has been refined so that currently it is possible to quantify the expression of several thousand genes in a single experiment, with only a few days delay between biopsy and automated analysis. Similarly with advances in proteomics, it is estimated that plasma contains greater than 10 000 different proteins, with concentrations varying 10 orders of magnitude. In order to study cancer-specific proteins, techniques have been developed to remove the abundant proteins (albumin, immunoglobulin, fibrinogen, etc), to allow separation and detection of tumor-related proteins, with quantification of not only individual proteins but also their phosphorylation status, which can correlate with activity (1).

The past decade has also heralded in a new era in the understanding of gene regulation in diseases such as cancer. We now appreciate that normal human cells express thousands of non-coding RNAs and that cancer cells misexpress these RNAs. Many of the non-coding RNAs, epitomized by the miRNA, have regulatory functions in normal cells.  The aberrant expression of miRNA promotes tumorigenesis, metastasis, and other features of cancer (1).

The presence of circulating tumor cells (CTCs) in the blood of patients with advanced cancer was noted more than 20 years ago. However it is only in the last few years, again through improved biotechnology, that fast and accurate assay of these have become available. CTCs are particularly abundant in advanced prostate cancer and breast cancer, where: 

• Number of cells predict duration of survival in metastatic disease
• Fall in CTC correlates with response and response duration after chemotherapy
• Change in CTC may be a useful surrogate endpoint for systemic treatment efficacy, superior to current assessment, e.g.. axial imaging
• There is potential value of receptor studies on CTCs to predict subsequent responsiveness to therapies (1).

Sino Biological offers a comprehensive set of tools for cancer biomarker development, including recombinant proteins, antibodies (rabbit mAbs, mouse mAbs, rabbit pAbs), ELISA kits, and ORF cDNA clones. Cancer biomarkers are present in tumor tissues or serum and encompass a wide variety of molecules, including DNA, mRNA, transcription factors, cell surface receptors, and secreted proteins. Cancer biomarkers can be used for prognosis: to predict the natural course of a tumor, indicating whether the outcome for the patient is likely to be good or poor (prognosis). They can also help doctors to decide which patients are likely to respond to a given drug (prediction) and at what dose it might be most effective (pharmacodynamics) (2).

Cancer biomarkers are present in tumor tissues or serum and encompass a wide variety of outcome of tumors, and they guide the decision of whom to treat (or how aggressively to treat). Predictive biomarkers are used to assess the probability that a patient will benefit from a particular treatment. For example, patients with breast cancer in which the gene encoding the estrogen receptor is expressed respond to treatment with tamoxifen, whereas when the gene ERBB2 (also known as HER2) is amplified in the tumor, the patients benefit from treatment with trastuzumab (Herceptin) instead (2). 

Pharmacodynamic biomarkers measure the near-term treatment effects of a drug on the tumor (or on the host) and can, in theory, be used to guide dose selection in the early stages of clinical development of a new anticancer drug. The application of cancer biomarkers is still controversial. An ideal tumor marker should be measured easily, reliably and cost-effectively using an assay with high analytical sensitivity and specificity. In addition, an ideal tumor marker should be present in detectable quantities at early or preclinical stages and the quantitative levels of the tumor marker should reflect tumor burden. Recent technological advances, especially in the fields of genomics and proteomics, have made it easier to identify many biomarkers at once in high-throughput screens. The validation of cancer biomarkers - that is, determination of clinical relevance and applicability - is also quite challenging, and many questions have been raised regarding how new tests will be developed, evaluated, and integrated into clinical practice (2).

Increasingly, attempts are being made to move away from the use of anti-cancer drugs at their maximum tolerable dose, to the optimization of dosage of established and new agents to their pharmacological and biological activity in individuals: 

• Therapeutic drug monitoring- knowledge and measurement of a target plasma level of the drug or its metabolites to allow dose adjustment.
• Direct measurement of biomarker of drug efficacy, e.g. protein phophorylation.
• Use of surrogate endpoints i.e. biological measures which, although independent of tumor cell kill, correlate with this (1).

Signal transduction

Understanding of the cell signaling pathways that control cellular behavior has provided many potential biomarkers for malignant disease. Most of these pathways can be triggered by extracellular factors binding to receptors, either on the cell surface or within the cell. The processes they control include:

• Activation of genes
• Changes in metabolism
• Cellular proliferation
• Cellular death
• Cellular migration

Gene activation can lead to a cascade of effects through production of:

• Proteins with enzyme activity
• Transcription factors which activate one or more genes downstream in the pathway

With the advent of targeted therapies directed at growth factor receptors or their tyrosine kinases, it is becoming increasingly important to identify which components of the signal transduction pathways predominate in individual cancers. For example, most gastrointestinal (GI) stromal tumors are driven by mutation in c-kit which leads to constitutive activation of the kit tyrosine kinase, the target for the tyrosin kinase inhibitor (TKI) imatinib. Clearly when the pathway is disrupted by alteration downstream from the growth factor receptor, agents targeted against the receptor or its specific tyrosin kinases are unlikely to have significant anti-tumor effects. For example, tumors driven by kRAS mutations do not respond to antibody therapy directed against membrane-bound growth factor receptors or to corresponding rececptor TKIs (1).

Functional Signaling Profiles (FSP) reveal information regarding signal transduction networks, including pathway activation and feedback loops that predict patient response to targeted drug therapy. Enabled by the SnapPathTMplatform, FSPs are algorithm based tests that compare stimulated/inhibited patient samples to unstimulated, Basel samples. FSPs utilize phosphoprotein-based ex vivo biomarkers to yield functional information beyond what can be achieved with traditional static DNA/RNA biomarkers in dead tissue. The figure below represents the unique patient stratification and clinical potential of a SnapPath™ FSP (3).

Biomarker Strategies is developing a pipeline of unique ex vivo biomarker tests to inform targeted drug treatment selection, including combination therapies, for cancer patients with melanoma, breast, colon, lung, pancreatic and other solid tumors. Given the recent success of BRAF inhibition in melanoma, the technology of author's is uniquely suited to assess the functional bypass mechanisms of BRAF inhibition and facilitate novel therapeutic strategies for BRAF inhibitor resistance (3).

Ex vivo biomarkers are dynamic molecular markers, such as phosphoproteins, that are evoked from live tumor cells after being removed from a patient. Unlike static biomarkers detected from FFPE-based tumor samples, ex vivo biomarkers enable true functional tests of cancer cells and reveal important elements of tumor cell biology, including signal transduction circuitry. SnapPath™ is an enabling platform for this new class of biomarkers in solid tumors, including ex vivo-based companion diagnostics. Much of the early work in ex vivo biomarkers was pioneered in leukemia and lymphoma. Biomarker Strategies has extended this work to solid tumors using the SnapPath™ live tumor testing platform. (3).

Researchers from Virginia Commonwealth University Massey Cancer Center have discovered a new biomarker related to the body's immune system that can predict a breast cancer patients' risk of cancer recurrence. This breakthrough may lead to new genetic testing that further personalizes breast cancer care. The study, published in the journal Breast Cancer Research and Treatment, is the first to use tumor infiltrating immune cells located at the site of the tumor to predict cancer recurrence. Using tissue samples from breast cancer patients, researchers found that a specific, five-gene signature related to tumor infiltrating immune cells can accurately predict relapse-free survival. Currently, there are two main tests used to predict the risk of relapse in breast cancer patients, the Oncotype DX panel and the MammaPrint panel. Both of these tests focus on genes that are mainly expressed by tumor cells. Masoud Manjili, D.V.M., Ph.D. assistant professor of microbiology and immunology at VCU Massey said that the body initiates an immune response when it detects cancer, and immune system cells are usually present at the site of the tumor. Their test differs from currently used tests by looking for a biological response to the presence of cancer, and not relying on genes expressed by the actual cancer cells. Tissue specimens were collected from female breast cancer patients and maintained in the VCU Massey Cancer Center Tissue & Data Acquisition and Analysis Core (TDAAC) over the past seven years. They studied data from 17 patients. Of these patients, they had eight that relapsed within five years and nine that have remained cancer-free up to seven years. The five-gene signature was found to predict relapse in these patients with over 85 percent accuracy. Manjili and his team wanted to test their findings in a long-term study of breast cancer patients undergoing treatment. Manjili reported that their findings could lead to clinical trials that test whether using immunotherapy prior to conventional treatments in breast cancer patients with a high risk of relapse could prime the patients' immune system, much like a vaccine, to prevent the likelihood of relapse (4).

A new technology that enables the detection of antibodies in the blood that target abnormal glycoproteins produced by cancer cells may make it possible to use these antibodies as biomarkers for the early detection of cancer. Cancer cells can express molecules on their surfaces which are not usually found on the surface of normal cells. Sometimes, the immune system will recognize these molecules as being "foreign" and produce antibodies against them as a defense mechanism. Because the targeted molecules are on a person's own cells, the antibodies are called "autoantibodies." Autoantibodies alone are rarely sufficient to kill cancer cells, but they may prove useful as biomarkers to detect cancer early.

In this study, the researchers identified and analyzed autoantibodies directed against abnormal forms of the protein MUC-1, which is a member of a family of proteins called mucins. Mucins are found in the plasma membrane (outer membrane) of epithelial cells and, during their production, are modified by the addition of carbohydrate (sugar) molecules in a process known as glycosylation. Previous research had shown that MUC-1 is produced in larger amounts by many types of cancer cells and that it is abnormally glycosylated by those cells. To detect autoantibodies against aberrantly glycosylated forms of MUC-1, the researchers had to develop a new technology in which they used enzymes to attach sugar molecules to MUC-1 peptides (fragments) in the laboratory. This process yielded a diverse "library" of molecules called glycopeptides that included molecules containing the abnormal carbohydrates previously found on cancer cells. Next, the researchers attached the members of this glycopeptide library to a special type of slide to create "microarrays," which they subsequently used to screen the blood (serum) of newly diagnosed patients with breast, ovarian, or prostate cancer, as well as serum from normal control subjects, for the presence of antibodies against abnormal forms of MUC-1.

The scientists found that the serum from cancer patients contained immunoglobulin G (IgG) antibodies that reacted with members of the glycopeptide library. From patient to patient, these antibodies were present in differing amounts and specificities. In contrast, IgG antibodies in the serum of healthy control subjects did not react with members of the glycopeptide library (5).

According to the researchers, this study should be viewed as a proof-of-concept study, and much more work is required before a clinically useful assay, or assays, based on their findings can be developed.

Moreover, although many common cancer types overproduce MUC-1, many do not. Therefore, extending this approach to other cancer types will require the identification of additional glycoproteins that are aberrantly expressed in cancer. Nevertheless, it is hoped that refinements of this technology will lead to disease-specific assays that can be used to diagnose many cancers earlier, when they may be most treatable (5).

Imaging biomarkers

Oncology requires comparison of imaging-based measurements to define the response of disease.  CT scan or MRI is mainly used for solid tumor masses. 3D volumetric tumor assessment is currently being investigated. Dynamic contrast-enhanced CT and MRI allow the assessment of anti-angiogenic effects on tumor perfusion. Positron Emission Tomography (PET) scan can quantitatively measure tumor perfusion (15O-labelled H2O). VEGFR-2 is an example of PET imaging of molecular pathway receptors. Tumor cell proliferation can be measured by 18F-fluorothymidine.

Multiple somatically acquired chromosomal rearrangements, such as focal amplification of the MYCN oncogene or deletions at chromosome arms 1p or 11q, are each associated with an aggressive neuroblastoma phenotype (6). Although these somatically acquired genomic alterations are of clinical use as prognostic biomarkers, until recently little was known about the constitutional genetic events that initiate tumorigenesis. Highly penetrant gain-of-function mutations in the anaplastic lymphoma kinase (ALK) tyrosine kinase domain were recently identified as the major cause of familial neuroblastoma, and somatic mutations in this gene implicate it as a target for therapeutic intervention (7).

Eventually, the researchers hope to create different biomarkers for clinical applications and pharmacological development. While these developments provide great hope for the individualization of cancer therapies. The expansion in understanding of the molecular changes of biomarkers giving rise to cancer is now leading to the rational development of therapies specifically targeted against the type of cancer.

References:

1. Edited by Cassidy,J et al. In: Oxford Handbook of Oncology, Oxford University Press, 3rd ed, (2010).
2. http://www.sinobiological.com/Cancer-Biomarker-a-835.html
3. http://www.biomarkerstrategies.com/fsp.html
4. http://www.sciencedaily.com/releases/2011/05/110516131538.html
5. Wandall, H.H et al., Cancer Research, 70(4):1306-1313 (2010)
6. Maris, J.M., Hogarty,M.D et al. Lancet, 369:2106-2120 (2007).
7. Mosse, Y.P, et al. Nature, 455: 930-935 (2008).