Can a simple proteomics urine test assist in the early diagnosis of early-stage cancer?

Keywords::

• cancer biomarkers
• human urine
• mass spectrometry
• proteomics

Each year, more than 10 million people are diagnosed with cancer worldwide, while almost 8 million die from cancer or cancer-associated diseases and 12% of all deaths globally are due to tumors [1]. The total number of cancer cases is on the rise globally, the most prevalent being lung, breast, bowel and stomach cancers. Owing to improved clinical procedures as well as higher detection rates at earlier stages in tumor progression, many prevalent cancers such as breast cancer have a favorable outcome with an almost 80% 5-year survival rate. However, the 5-year survival rates fall below 15% for upper gastrointestinal cancer cases, of which pancreatic cancer has the poorest outcome of 2–3%. Low survival rates can be attributed to diagnosis at an advanced stage of disease, where the possibility of a noninvasive intervention in tumor progression is greatly reduced. It is therefore of great importance to devise new, or adapt known, methodologies not only to pharmacologically treat but also to diagnose cancers at an early stage through the discovery of biomarkers as diagnostic tools. The identification of such biomarkers would allow the elucidation of signal transduction pathways and druggable targets for a curative approach.

Many of the technologies used to identify cancerous tissue growth rely on biopsies of the tissue itself and can potentially emphasize the molecular changes due to the uncontrolled growth of the cancer. In many cases, important targets that could be useful in diagnostics are joining the ranks of the many hundreds, if not thousands, of protein or gene changes happening at the same time and might ultimately get lost in the general noise. Furthermore, using biopsies as a diagnostic tool is generally impractical, if not impossible, in the clinical setting. There is a clear need to simplify the source to be screened, avoiding genetic variations and population heterogeneity, in order to define reliable disease markers. This is especially true when proteomic methods are used. Proteomic methodologies, which have advanced substantially over the last couple of decades, are mainly centered on mass spectrometry (MS), and are an invaluable tool in defining and characterizing proteins, their modifications and, more recently, in assessing the quantity of a protein in a biological environment. These advances have led to a surge of developments in the fields of systems biology as well as bioinformatics. However, there are clear limitations to the use of MS techniques, such as detection limits and peak densities, where a complex system, such as the entire proteome of a cell, needs to be subfractionated before any meaningful analysis can be attempted, unless the aim is to only study the most abundant proteins in the first place. Another limitation is the actual sample itself, where obtainable quantities can be too small to embark on a screen for a potential cancer biomarker. A logical approach that would avoid such bottlenecks is to use another medium such as blood components, which are much easier to collect in suitable amounts, or to use a substantially less complex system, such as urine, which contains approximately 3000 proteins and is an ideal source to screen for protein or peptide biomarkers. Urine analysis has a number of advantages, including a completely noninvasive sampling for patients, the ease of sampling and the availability of suitably large quantities. Urine itself is also relatively stable in terms of protein and peptide composition and fragmentation state compared with other body fluids such as serum, where proteolytic degradation has been shown to occur during or after sample collection, which can skew a proteomic screen in a nondesirable manner.

Urine was successfully used in the discovery of small chemical components in the stratification of cancer samples [2], and the associated MS-based emerging area of metabolomics has shown promising advances in lead marker discoveries [3]. Even the application of molecular biology techniques such as PCR and quantitative PCR, which are unsurpassed in detecting miniscule quantities of target material, have been used successfully in the study of cancer-related urinary changes in hypermethylation of gene promoters [4]. A novel approach using predictive proteomics, which is based on prior knowledge of proteins found in urine and bioinformatic analysis of gene array data from diseased tissue, has shown some potential in predicting potential cancer-associated markers in urine [5]. Exploration of other potential cancer-driven changes in the makeup of the urinary proteome has shown that post-translational modifications of proteins can also be used as indicators of the disease, where altered glycosylation patterns were clearly associated with pancreatic cancer [6].

Several specific potential cancer biomarkers have already been mentioned in the literature, all of which appear to be connected to the early onset of the disease. Early-onset prostate cancer results in an altered urinary expression pattern of engrailed-2 (EN2) [7], while both apolipoprotein A1 (APOA1) [8] and uroplakin 3A (UPK3A) [9] are potential urinary biomarkers for the early detection of bladder cancer, and changes in the expression pattern of aquaporin 1 (AQP1) and adipophilin (ADFP) have been shown to be associated with early stages in kidney cancer progression [10]. In addition, this list of potential early-onset cancer markers is joined by putative markers that show altered expression patterns in cancers originating from several distinct tissues. One such ‘global’ marker is calcyclin (S100A6), which has been shown to be a biomarker for breast [11], upper GI tract [12], gastric [13] and pancreatic cancer, as well as metastasis [14], osteosarcoma [15] and others.

It is also apparent from the published literature that the distinction between cancer-specific markers and those associated with systemic inflammation can sometimes be difficult (e.g., interleukins, C-reactive protein and TGFs [16]), which could be interpreted that there is no clear division between those two disease states. Assuming this is true means that any attempt to identify cancer-specific markers would be futile. However, there is a vast amount of published work that indicates that inflammation might be associated with, but is distinct from, tumor growth. In order to avoid any future confusion and data misinterpretation, there is a clear need to harmonize the various methods used in urinary biomarker discovery, from study design to sample handling and data analysis. Recent efforts were made to put forward general guidelines in urine proteomics for clinical marker discovery and evaluation [17]. Another hurdle to overcome is the application of the findings in a clinical setting. The complexity of the detection method makes MS-based approaches difficult or unsuitable to implement in the clinical environment and a translation of proteomic results to alternative methods such as antibody-based and/or dipstick techniques might be preferable. The commonly used ELISA assays to detect and measure levels of various proteins in urine could be the way forward following the initial identification of useful markers.

Another question, which currently remains unanswered, is whether the proposed markers are a true indication of an early-stage cancer. There is currently no absolute proof that any of the postulated markers, whether or not they appear at an early stage of the disease, are clinically useful in a large population. There is a clear need for longitudinal studies of initially healthy people in order to observe proteomic changes that can be attributed to disease processes and cancer growth over an extended period. Using animal models as an alternative is of limited benefit, as induced cancers might not reflect what might be happening in humans over a prolonged period of time. Furthermore, using the currently postulated potential urinary markers to assess human tumor growth, without the disease being diagnosed using different independent methods such as PET and CT scans, also raises ethical questions. It would certainly be beneficial for true-positive cases, but detrimental for patients with false-positive identifications. An approach to this problem would be to monitor not just one but several potential markers simultaneously, and there is a current trend aimed at improving the reliability of the diagnostic tests by the use of more than one biomarker. This has been taken to the extreme in one report, where an 810 differential antibody-based array was employed to define cancer patterns in urine [18].

Ultimately, is there scope in finding early biomarkers for cancer in urine or are the molecules found so far an indication that tumor growth has progressed too far to be classified as early-onset cancer? There is no simple answer to these questions. It is obvious that the elucidation of any high-confidence marker in urine for a specific cancer type is more than valuable, as this has direct implications in diagnostics, disease assessment and the instigation of a curative approach, either through surgery, adjuvant therapy or both, as well as pin-pointing the diseased tissue. However, if any such markers can be found at a very early onset of tumor growth, as research suggests might be possible, then a whole new chapter in cancer discovery, treatment and prevention will open. Only time will tell.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.