Cancer Biomarkers: Surviving the journey from bench to bedside

By: Jeanne M. Rhea   


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Upon completion of this article, the reader will be able to:

  1. list and describe various tumor biomarkers;
  2. describe requirements for approval of clinically useful biomarkers;.
  3. discuss the three-phase theoretical model from identification through implementation of novel biomarkers;
  4. discuss the various aspects of mass spectrometry in the discovery of novel biomarkers.

The Centers for Disease Control and Prevention estimates that one in every four deaths in the United States is due to cancer.1 Worldwide, cancer was estimated to be responsible for 13% of all deaths in 2007.2 In light of these statistics, it may be surprising that approximately one-third of all cancer cases could be prevented if detected at an early enough stage.2 As a heterogeneous disease, cancer evolves via multiple pathways and is a culmination of a variety of genetic, molecular, and clinical events.3 Given that there is significant variation in the risk of developing cancer and that early detection often results in increased survival, developing technologies capable of identifying patients at highest risk and detecting tumors in the earliest stages of development is a pressing need. In addition, the development of molecular-diagnostic tools promises to revolutionize the cancer field through the individualization of cancer treatment.

Biomarkers are defined by the National Institutes of Health as any “characteristic that can be objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.”4 Ideally, biomarkers of diseases, such as cancer, are blood-based molecules that indicate malignant properties, allowing for minimally invasive testing. Over the past decade, the rapid development and improvement of proteomic technologies has resulted in the identification of hundreds of potential protein biomarkers,1 with new disease-associated protein biomarkers described in the scientific literature almost daily. In spite of this, however, relatively few have successfully advanced beyond the discovery phase to become clinical diagnostic biomarkers. In fact, less than two dozen cancer biomarkers are currently approved by the Food and Drug Administration (FDA),5 only nine of which are protein biomarkers identifiable in the blood.6 Other approved protein biomarkers can be identified in urine, such as nuclear matrix protein 22, fibrin-/fibrinogen-degradation products, and bladder-tumor antigen for the monitoring of bladder cancer, or by immunohistochemistry using tumor tissues, such as the estrogen receptor for breast cancer.6 Additional approved cancer biomarkers are DNA based, such as human epidermal growth factor receptor 2, or HER2/neu, for breast cancer, and can be assayed by fluorescent in-situ hybridization (FISH).6

The Holy Grail of the cancer-biomarker field is the development of minimally or non-invasive tests that can be used to diagnose disease at an early stage, to classify tumors so as to better determine the most appropriate course of therapy, to monitor the response to therapy, or to assess disease progression and recurrence.7 While such markers may come in the form of DNA, RNA, miRNA, or carbohydrates,8 the preferred biomolecule remains the protein.9 Given that proteins can directly influence molecular pathways in both normal and transformed cells, it is generally believed that measurement of these molecules can provide a more accurate, real-time indication of the physiological state of individuals. Here, we review protein biomarkers that are currently used to facilitate the clinical management of cancer, and explore additional issues that must be addressed before the promise of such tools comes to fruition.

FDA-approved protein biomarkers for cancer

Currently, there are only nine protein cancer biomarkers that have been approved by the FDA for clinical use (see Table 1).6 These protein markers include a-fetoprotein (AFP) for staging of non-seminomatous testicular cancer and monitoring of hepatocellular carcinoma; cancer antigen-125 (CA-125); and human epididymis protein 4 (HE4) for monitoring of ovarian cancer; thyroglobulin (Tg) for monitoring of thyroid cancer; prostate specific antigen (PSA) for screening and monitoring of prostate cancer, carcinogenic embryonic antigen (CEA) for monitoring of pancreatic cancer; and CA15-3/CA27-29 and HER2/neu for monitoring of breast cancer.6

AFP:This single-chain glycoprotein is produced by the liver and is a major serum protein in the fetus. Following birth, the concentrations of AFP decrease rapidly until only trace amounts are detectable by the second year of life.10 Several studies have shown a direct correlation between elevated AFP levels (>5 U/mL) in non-seminomatous germ-cell tumors (NSGCTs) and disease stage,11 making this protein a useful biomarker in cancer staging. AFP concentrations are also increased in patients with hepatocellular carcinoma (HCC), as persistently elevated levels are indicative of residual disease, while rising levels are suggestive of disease progression or recurrence.12 The sensitivity and specificity of AFP as a biomarker is relatively low; for HCC, sensitivity is 50%, while specificity is 70%.13 In addition to NSGCTs and HCC, however, elevated AFP-serum levels are also associated with pregnancy, primary hepatocellular carcinoma, endodermal sinus tumors, and diseases such as ataxia telangiectasia, acute viral hepatitis, and cirrhosis.

CA-125:A member of the glycoprotein family, this protein has been clinically approved for following the response to treatment, predicting prognosis after treatment, and for detecting the recurrence of ovarian cancer. While this protein has been approved as a biomarker for ovarian cancer, it is important to note that increased serum concentrations (>21 U/mL)14 have also been observed in relatively benign conditions, such as endometriosis as well as other malignant cancers — especially those originating in the endometrium, fallopian tubes, lungs, and breast. Thus, utilization of this protein does not demonstrate the clinical sensitivity and specificity required for ovarian-cancer screening.

HE4:As the most recently FDA-approved biomarker, HE4 is recommended for the use of monitoring patients for recurrence of epithelial ovarian cancer. Disease recurrence or progression is often indicated by HE4 levels ³150.1 pM.15 Similar to CA-125, however, elevated levels of HE4 are not solely associated with ovarian cancer, making it non-specific and not suitable for use in diagnosis of or screening for ovarian cancer.

Tg: Tg is a protein produced and used solely by the thyroid gland, and levels in the blood can be measured and used as a tumor marker for monitoring certain types of thyroid cancer. Tg tests are commonly ordered prior to surgical removal of the thyroid gland for cancer to determine whether or not the tumor is producing Tg. Following tumor resection, Tg should be undetectable or very low; measurable levels in the blood may indicate cancerous tissue remaining in the body (incomplete resection) and the need for additional treatment. Tg lab tests can be ordered at regular intervals to monitor for cancer recurrence as rising levels over time following surgery may be indicative of cancer recurrence. In addition to serving as a marker for thyroid cancer, Tg levels are also elevated in persons with Graves’ disease16 and thyroiditis.17

PSA:Serum PSA is typically present at relatively low levels in men, and increased levels of this protein can be indicative of prostate cancer. While the majority of PSA in the blood is bound to serum proteins, a small portion referred to as free PSA is not. Comparison of free PSA to PSA levels is used to assess the risk of cancer, as the ratio of free PSA to PSA in prostate cancer is decreased. Elevated levels of PSA can also be attributed to prostate infection, irritation, benign prostatic hypertrophy, or recent ejaculation. Thus, tests for PSA show neither the specificity nor the sensitivity required for prostate-cancer screening. Nonetheless, despite this controversy, PSA screening continues to be recommended for men over the age of 50 years.

CEA: CEA is a glycoprotein involved in cell adhesion that is normally produced during fetal development. Production of the protein ceases prior to birth and is, therefore, not typically present in the blood of healthy adults. Elevated levels of CEA (>2.5 ng/mL)18 are most commonly used as a biomarker for monitoring of colon cancer following tumor resection and for monitoring the response of metastatic colorectal cancer to systemic therapy. While FDA approved for these applications, elevated CEA levels are also associated with these carcinomas — colorectal, gastric, pancreatic, lung, and breast — making it an unreliable biomarker for cancer diagnosis or early cancer detection.19

CA19-9:This glycoprotein is used to monitor pancreatic-cancer patients’ responses to therapy. While low levels of CA19-9 are detectable in the blood of healthy individuals (37 U/mL),20 significantly elevated levels (>37 U/mL)20 have been observed in patients with pancreatic cancer. Thus, in cases where the cancer is producing elevated levels of CA19-9, routine tests may be ordered as fluctuations in levels can be used to monitor treatment and help detect recurrence. Because elevated levels of CA19-9 have also been correlated with bile duct, gastric, and colon cancers, as well as with non-malignant conditions such as pancreatitis and cystic fibrosis, this tumor marker does not exhibit the specificity to be used for diagnosis or in population screening.

CA15-3/CA27-29:Approved as a biomarker for breast cancer, a high CA15-3 level (>32 U/mL)21 typically indicates advanced breast cancer and a larger tumor burden. CA15-3 is used in combination with diagnostic imaging, patient history, and physical examination during active cancer therapy to monitor metastatis. Due to its lack of sensitivity and specificity, this marker has only been FDA approved for monitoring a patient’s response to breast-cancer treatment and recurrence.

HER2/neu:HER2/neu is encoded by an oncogene, is over expressed in 15% to 20% of invasive breast cancers, and is associated with increased tumor aggressiveness and reduced survival rates.22 Trastuzumab (Herceptin) is a humanized monoclonal antibody that targets HER2/neu and is used in combination with cytotoxic chemotherapy to treat patients with tumors that show over expression of this gene.23 Thus, HER2/neu serves as a predictive biomarker to assess tumor susceptibility to trastuzumab and other HER2/neu-targeted therapies such as lapatinib.24

Additional candidate cancer biomarkers

Although there are only nine FDA-approved blood biomarkers for cancer, the list of potential candidates continues to grow. Vascular endothelial growth factor A (VEGF-A) is a protein having greater than 500 citations in the scientific literature as a potential biomarker,1 and increased serum levels have been associated with melanoma, pituitary, breast, and colorectal carcinomas.1 Calcitonin, a second protein with greater than 500 citations, is a peptide hormone produced by the thyroid that acts to oppose effects of parathyroid hormone (PTH), thereby lowering blood calcium and phosphate levels.1 Levels of calcitonin are often used to aid in the diagnosis of thyroid cancer, to determine cancer- treatment effectiveness, and to monitor patients for recurrence of thyroid tumors.25 Similar to other candidate biomarkers, however, calcitonin lacks the specificity required to be used for diagnosis as elevated levels are also observed in Hashimoto’s thyroiditis.25 Other candidate biomarkers that have >500 citations include gastrin (a hormone associated with gastric and colorectal cancer)26; chromogranin A (CgA), secretory protein associated with neuroendocrine tumors and decreased survival in small cell-lung cancer27; von Willebrand Factor (VWF), coagulation factor showing elevated levels in colorectal cancer patients28; and tumor necrosis factor-a (TNF-a), a pro-inflammatory protein observed in 36.5% of pancreatic-cancer patients.29

Additional blood-based proteins that are well cited in the literature as potential cancer biomarkers include haptoglobin-1 (increased in leukemia patients and associated with poor prognosis in small cell lung cancer); a-2-macroglobulin (a2M), a plasma proteinase inhibitor showing decreased expression in prostate cancer metastases30; and angiopoietin-1 and -2 (Ang-1, Ang-2),  increased levels have been observed in breast cancer.31

Requirements for clinically applicable biomarkers

To be approved as a clinically useful biomarker, several conditions should be considered. First, to be effective for early diagnosis, the potential biomarker must be a molecule that is released into circulation at a detectable concentration by a small asymptomatic tumor.32 Thus far, such molecules have eluded researchers as the majority of biomarkers currently used are only sufficient to detect late-stage tumors, and, therefore, are useful only for disease staging and monitoring. Next, in order to distinguish normal from diseased samples, the biomarker should be highly specific for the tissue of origin, as expression in additional tissues means a high level of expression in normal healthy individuals. In addition, there must be sufficient biomarker released from the diseased tissue to be detectable over other highly expressed background proteins, which likely requires larger tumors.33 An additional caveat to biomarker utility is the need to identify molecules that are not affected in non-cancerous tissue.33 To date, however, no single molecule has been identified that is expressed only by cancer tissue, with the possible exception of those that have variations in post-translational modifications, such as pancreatic ribonuclease in pancreatic adenocarcinoma and kallikrein 6 observed in ovarian cancer.33

Mass spectrometry and the biomarker-discovery pipeline

While there is currently no standardized roadmap for seeing novel biomarkers through from identification to clinical implementation, a three-phase theoretical model has been widely used as a guideline: discovery, verification, and validation (see Figure 1).34 Many discovery-phase platform technologies are available and have been successfully used to identify large numbers of potential biomarkers.9 In the subsequent steps of verification and validation, immunoassays have been the established method of candidate-biomarker confirmation. The antibody reagents required for completion of these assays, however, are not always available, and the high costs associated with generating such tools limits the number of candidates that are pursued past the discovery phase.9 As an alternative to immunoassays, mass spectrometry-(MS-)coupled techniques can be employed to generate a variety of proteomic information, including protein identification. Such methods may include two-dimensional gel electrophoresis (2DGE)-MS, liquid chromatography (LC)-MS, surface laser enhanced desorption and ionization (SELDI)-MS, and matrix-assisted laser desorption ionization (MALDI)-MS, which have been reviewed elsewhere.35 In spite of the available tools and the reports published daily in the scientific literature claiming to have identified another promising marker, proteomics has yet to yield any clinically useful cancer biomarkers.36

Discovery:Both tissue-based and blood-based biomarkers have the potential to reveal important information regarding the natural history of a disease. While the latter are most desirable, the identification of blood biomarkers is complicated by the fact that the 20 most highly abundant proteins comprise 99% of the total protein mass in blood.37 Thus, the discovery of rare, lowly expressed cancer-specific proteins by MS is nearly impossible without the aid of biochemical techniques to reduce sample complexity.38 Such techniques, however, result in significant pre-analytical variation and hinder the reproducibility of blood-based biomarker discovery. Nonetheless, circulating cancer biomarkers can be discovered indirectly by analyzing fluids collected from the area surrounding the tumor, or by analyzing the tumor itself via an MS-based approach.39-41 Use of such specimens greatly enhance the ability to identify candidate biomarkers as many potential protein markers are secreted or shed directly into the bloodstream, thus concentrations are increased in these samples.

The initial discovery phase can result in lists consisting of up to several thousand proteins that show differential expression patterns between healthy control tissues and diseased tissues, and often contain many false-positives. These lists can be narrowed to approximately 50 to 100 proteins by comparing the lists to proteins identified in the literature as disease-specific by other means such as transcriptional profiling and by using additional criteria set forth by individual laboratories.34 While such criteria are often arbitrary, four additional concepts should be considered when determining which biomarkers to carry through to the next phase.42 From a clinical perspective, assays for novel biomarkers introduced for clinical use should be able to be performed on existing instrumentation, thereby limiting economic impact (e.g., purchase of specialized equipment and the training of technical staff).42 Next, a novel biomarker should have the capacity to provide additional information about the disease that can be used by clinicians in the care of patients.42 This information should also be available in a timely and efficient manner,42 as biomarker assays requiring extended periods to yield pertinent information are not clinically viable in disease management. Finally, because economic concerns increasingly influence medical decisions, parameters — such as cost of the biomarker assay and its ability to be used to avoid costly and ineffective therapy — are important considerations when deciding on the clinical utility of a potential biomarker.42

Verification:The main goal of the verification phase is the affirmation of candidate sensitivity and assessment of its specificity.34 Specimens used in the completion of this phase are collected from a broader range of cases and controls than those used in the discovery phase in order to capture the variation that exists in populations due to genetic, environmental, and biological differences.34 Consequently, the candidate protein list is reduced to two to five biomarkers by quantitatively assessing their ability to identify cancerous tissues from healthy control tissues in a moderate number of samples.34 In this phase of the pipeline, targeted MS approaches — such as accurate inclusion mass screening (AIMS)43-45 and multiple reaction monitoring (MRM)-MS — can be used to confirm that the candidate biomarker is detectable in the blood and that the biomarker is elevated in cancer versus healthy control samples. These methods exploit the hypothesis-based approach to biomarker discovery by taking advantage of the known amino-acid sequence of candidate proteins and using it to predict peptides produced from tryptic digests and their resulting mass-to-charge ratios (m/z). Using this information, MS instruments can be programmed to detect these predicted peptides exclusively, essentially increasing sensitivity for the detection of low-abundance proteins.

Following experiments demonstrating the ability to detect the candidate protein biomarker in blood, additional studies are required to show differential expression of the protein in disease versus healthy individuals. To date, immunoassays — such as enzyme-linked immunosorbent assays (ELISAs) — have been the preferred approach,38 and, with good quality antibodies, can detect proteins in the ng/mL range.9 The availability of the highly specific and sensitive antibodies required for these assays is limited, making the cost of validating a candidate by this method cost and time prohibitive. MRM-MS provides an alternative to ELISAs, and is a well-established technology used in clinical reference laboratories to quantify drug metabolites and metabolites that accumulate in inborn errors of metabolism.46,47 Without using biochemical techniques to enrich for the target proteins, MRM-MS has the ability to detect proteins in the 100 ng/mL to 1,000 ng/mL concentration range from relatively small volumes of serum (1 µL to 10 µL).48 Additional techniques, such as stable isotope standards and capture by antipeptide antibodies (SISCAPA),49-51 which utilizes antipeptide antibodies to enrich target peptides from samples prior to analysis, can be used to effectively increase the functional sensitivity of MRM-MS down to the 100 pg/mL range.52 The ability to multiplex reactions using MRM-MS provides an additional advantage over traditional immunoassays as numerous proteins can be simultaneously quantified in parallel.9

During this phase, it is imperative to determine whether patient characteristics (e.g., patient age, sex, ethnicity, lifestyle, diet, or exercise) or sample collection and/or storage can affect the levels of detectable biomarkers. Another biomarker characteristic that must be determined is half-life — because those that are quickly cleared from circulation by the kidneys or liver, or are degraded by serum proteases — are not viable candidates for clinical application.32

Validation: The final phase of the biomarker pipeline involves testing of several thousand clinically relevant samples to characterize test sensitivity and specificity, and to ensure that measurement biases or artifacts do not influence biomarker detection.34 Given that the scientific literature is bursting with reports of novel protein markers, it may be surprising that relatively few of these are pursued through the validation phase. It is this step in the biomarker pipeline where the bottleneck arises as validation requires the analysis of hundreds, if not thousands, of samples using a higher stringency than that for marker identification. During the discovery phase, high precision and accuracy in quantitating protein differences between samples are sacrificed for throughput, with the understanding that markers identified in these studies will undergo a rigorous validation process.53 Because such measurements should be absolute, MS represents an ideal platform for biomarker validation.53 Once standardized methods of sample collection, processing, and analysis have been agreed upon, data generated using this technology can be compared across sample cohorts and laboratories.53

One of the most important hurdles facing biomarker implementation is the lack of adequately preserved biological specimens for validation studies. The establishment of comprehensive tissue-tumor banks by laboratories performing biomarker discovery through the characterization of cancerous and healthy tissues using high-throughput proteomic approaches could help to alleviate this issue. The preservation of such samples should be standardized so as to reduce variation in the resulting data.

Variation in MS discovery of novel biomarkers:Each step in the biomarker-discovery process must be well thought out and carefully designed to reduce variability and the possibility of identifying candidate proteins showing changes in expression unrelated to the disease state of the individual.54 Since 1998, new protein targets across all diseases have been approved by regulatory agencies at a rate of one per year. The reasons behind such a slow rate of approval — despite the number of reported candidate biomarkers — are manifold and represent gaps in the current biomarker pipeline. For example, the discovery phase of novel biomarkers is often considered the most exciting, and is well funded by both government and academic research.55 Funding for what is arguably the most critical phase of this pipeline — the winnowing of the list of potential candidates down to those that show the most promise to carry into the validation phase — is lacking.55 Moreover, a lack of standardization in sample collection, processing, and storage has been shown to affect results obtained by MS.56 Multiple freeze/thaw cycles of clinical samples often used in biomarker discovery may also contribute to a lack of reproducibility during the validation phase.56 Another important consideration when collecting clinical specimens for disease-specific protein discovery is the need to ensure that not all disease samples come from one institution while all healthy samples come from another. Guarding against such situations prevents systematic bias that is typically identified during validation studies that also include hospital-specific makers. Other sources of variation can be operator-dependant, instrument-dependant, and/or reagent lot-dependant (i.e., differences in trypsin lots). One way to minimize such effects is through the randomization and blinding of samples as they are received by research laboratories.

In summary, the abundance of reported candidate-biomarker proteins in the scientific literature compared to the lack of those reaching clinical use indicates that the aforementioned pipeline bottleneck falls in either the verification or validation phases. To stress this point, Polanski and Anderson compiled a list of 1,261 proteins that have been cited in the literature as being differentially expressed in human cancers.1 Of the 1,261 proteins, 22% are reported to be present in the blood and should be detectable given a sensitive enough assay. Interestingly, only 5% of these candidates have been thoroughly investigated as biomarkers (greater than 500 citations),1 with 41 (~3%) actually being used in some clinical capacity. The reason behind so few biomarkers reaching the clinic can largely be explained by the inability of current technologies to consistently and quantitatively verify the presence of the candidates in patient samples and the failure, thus far, to identify biomarkers with high specificity for a particular disease.9 As noted above, none of the nine FDA-approved cancer biomarkers demonstrate the specificity required for diagnosis when used alone. Thus, the development of panels of proteins, such as the FDA-approved OVA1 test,57 may be crucial to achieve the specificity required for early cancer diagnosis, and is interesting to speculate that members of such panels are likely to have already been identified but not yet implemented.58

Jeanne M. Rhea, PhD, is a post-doctoral Fellow working with Ross J. Molinaro, MT(ASCP), PhD, D(ABCC), F(ACB) within the Department of Pathology and Laboratory Medicine at Emory University School of Medicine in Atlanta, GA.



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Cancer Biomarkers: Surviving the journey from bench to bedside
PhD, is a Post-Doctoral Fellow working within the Department of Pathology and Laboratory Medicine at Emory University School of Medicine in Atlanta, GA.