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Quantitative proteomics: closing the gap between biomarker discovery and validation – the rate-limiting step

, 26 August 2020/in Featured Articles /by 3wmedia

Many potential cancer biomarkers have been identified, however, the transfer of these biomarkers from discovery to clinical practice is still a process filled with pitfalls and limitations. To prove clinical utility and performance, these candidate biomarkers need to be reproducible, specific, sensitive, and validated using large sample cohorts, all of which require development of robust and highly sensitive multiplex protein assays.

by Dr G. M. Mustafa, Prof. J. R. Petersen, Prof. L. Denner Prof. F. A. Hussain and Prof. C. Elferink

Background
Although remarkable scientific and technological advances in medicine have been achieved, cancer incidences are still increasing worldwide with the ratio of deaths to new cancer cases remaining relatively unchanged at 49% [1]. The ability of physicians to effectively treat and cure cancer is directly dependent on their ability to detect cancer at an early stage. When cancer develops in an area of the body, such as an organ, as long as it hasn’t spread (metastasized), it may respond well to treatment and in some cases a cure may be possible. Many disease states, especially various types of cancer, can be better diagnosed by the aid of biomarkers, a key element of modern diagnostics and the value of which continuing to increase in modern medicine. As indicators of biological status, biomarkers, whether detected in blood, urine, or tissue, can be useful for the clinical management of various diseases. The changes in biomarker concentration have the potential to guide therapy in disease progression, prognosis and potentially be used to identify the stage of the cancer. Overall, protein biomarkers are needed to help our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers.

Biomarker research
One of the goals of biomarker research is to discover and validate markers that can be used in clinical research applications such as patient stratification, diagnosis and therapeutic monitoring, or in pharmaceutical development to fully characterize the behaviour and efficacy of candidate drugs. The identification of prognostic, predictive or pharmacodynamic biomarkers can be carried out using genomic or proteomic technologies. Proteomic profiling of body fluids, such as serum, has potential as a sensitive diagnostic tool for early cancer detection. Serum provides a rich sample for diagnostic analyses because the expression and release of proteins (potential biomarkers) into the bloodstream occurs in response to specific physiological states. As human plasma has a 1010 dynamic range of proteins [2] with 22 proteins being responsible for 99% of the proteins identified, one of the challenges working with such a complex biological fluid is the difficulty in identifying medium and low abundance proteins. Thus, sample enrichment is a very important step in the discovery phase.

Biomarker validation – the rate-limiting step
Discovery platforms typically result in an extensive hit-list of candidate biomarkers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Over the last several years, many proteins have been proposed as potential biomarkers for various cancers without further evaluation of their clinical utility. The lack of follow-up is due, to a large extent, to the lack of an efficient technology for reproducible and accurate verification of these proteins as biomarkers in a specific disease state. Without proper validation, the identification of biomarkers is of minimal utility. To show clinical utility, biomarkers must be validated using a reliable assay with an independent cohort in a prospective or longitudinal study. A search of the scientific literature clearly indicates that most published biomarkers are inadequate for replacing an existing clinical test or that they are only useful for detecting disease in an advanced stage, where treatment success and/or survival rates are low. Traditionally, validation has been performed with immunoassays which require antibodies that are often unavailable or of poor quality. In addition the immunoassays may not adequately identify or differentiate between post-translational modifications. The process of generating antibodies is also time consuming and costly and is therefore not a practical solution for screening the hit-list of proteins derived from discovery.

Targeted mass spectrometry for multiplexed protein quantitation
A targeted mass-spectrometry-based antibody-free platform for multiplexed protein quantitation fills the well-recognized gap between early biomarker discovery and final clinical assay. Stable-isotope-dilution multiple-reaction-monitoring mass spectrometry (SID-MRM-MS) is a novel technique whereby the quantification of a protein can be calculated from isotopically labelled peptide standards of known concentrations that correspond to the protein of interest [3]. With two to five unique peptides per protein, the concentration of the protein of interest can be accurately determined. Further, the technique can be multiplexed to allow for the simultaneous measurement of many proteins. We have validated this approach using serum samples to identify biomarkers in hepatocellular carcinoma and are confident that it also has the potential for biomarker discovery in other cancers [4]. This powerful workflow opens up new possibilities for biomarker research that may lead to faster, more robust, and improved clinical assays. Targeted proteomics workflows based on SRM and MRM on triple quadruple mass spectrometry platforms show the potential for rapid verification of biomarker candidates in plasma by using heavy isotope-labeled internal standards. This approach has the selectivity, reproducibility, and sensitivity for a range of multiplexed protein assays and has the potential for quantifying protein isoforms in addition to posttranslational modifications for which good quality antibodies often do not exist. The ability to rapidly quantify proteins in a highly multiplexed manner using MRM with internal standard peptides closes the gap between discovery and validation in the biomarker pipeline, which is the rate-limiting step in the biomarker world. Using a triple quadruple mass spectrometer, the first mass analyser (Q1) is set to only transmit the parent weight of a peptide from the target protein, the collision energy is then optimized to produce a diagnostic charged fragment of a peptide fragment in the second mass analyser (Q2), and the third mass analyser (Q3) is set to only transmit and identify this diagnostic peptide fragment (Fig. 1). The key strength of this work flow is that the protein assay development for hundreds of proteins can occur on the order of a month. Once identified, it just takes months to validate the low to sub-ng/ml concentration of candidate biomarkers in hundreds of blood samples. No target-specific reagents, such as antibodies, are needed and only a very small amount of sample (<500ng) is required for quantitation. In addition all potential biomarkers can be quantified in a single assay that is more accurate, rapid, and cost-effective. The capacity of SRM for multiplexed, high-throughput analysis, together with its sensitivity and quantitation, positions SRM as a promising application in medical screening [5, 6]. Summary
The type of clinical proteomics described here has important direct ‘bedside’ applications. We can foresee a future in which the physician will use these proteomic analyses at many points in the management of disease and drug discovery.

References
1. Yeom YI, Kim SY, Lee HG, et al. Cancer biomarkers in ’omics age. Biochip Journal 2008; 2(3): 160–174.
2. Anderson L. Candidate-based proteomics in the search for biomarkers of cardiovascular disease. J Physiol. 2005; 15: 23–60.
3. Lange V, Picotti P, Domon B, Aebersold R. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol. 2008; 4: 222.
4. Mustafa MG, Petersen JR, Ju H, Cicalese L, et al. Biomarker discovery for early detection of hepatocellular carcinoma in hepatitis C-infected patients. Mol Cell Proteomics 2013; 12(12): 3640–3652
5. Keshishian H, Addona TA, Burgess M, et al. Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution. Mol Cell Proteomics (2007); 6(12): 2212–2229
6. Zhao Y, Jia W, Sun W, et al. Combination of improved 18O incorporation and multiple reaction monitoring: a universal strategy for absolute quantitative verification of serum candidate biomarkers of liver cancer. J Proteome Res. (2010); 9(6): 3319–3327

The authors
Gul M. Mustafa*¹ PhD, John R. Petersen²PhD, Larry Denner³ PhD, Feroze A. Hussain⁴ MD, and Cornelis Elferink¹ PhD
¹ Department of Pharmacology, University of Texas Medical Branch, Galveston, Texas, USA
² Victory Lakes Clinical Laboratory, Department of Pathology, University of Texas Medical Branch, Galveston, Texas, USA
³ Department of Internal Medicine, University of Texas Medical Branch, Galveston, Texas, USA
⁴ Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Texas Medical Branch, Galveston, Texas, USA

*Corresponding author
E-mail: gmmustaf@utmb.edu

The role of expressed prostatic secretion biomarkers in prostate cancer screening/surveillance

, 26 August 2020/in Featured Articles /by 3wmedia

Expressed prostatic secretion (EPS) is obtained after prostatic message by milking the urethra and collecting fluid directly from the urethral meatus. Clinicians have previously used this biospecimen primarily for the diagnosis of urinary infections. More recently it has been recognized as a rich source of biomarkers of prostate malignancy. Many of those biomarkers are accessible only in EPS, where it has shown a unique potential in both prostate cancer screening and active surveillance programmes.

by Dr J. Linehan, Dr J. Yamzon, Prof. T. Wilson and Prof. S. Smith

Current risk assessment tools
An estimated 238,590 new cases of prostate cancer will be diagnosed in the United States during 2013. A substantial proportion of these patients are considered ‘low-risk’ for progression and may be best served with conservative management. Yet many will undergo definitive treatment by means of radiotherapy or radical prostatectomy, both of which have risks of life-altering side effects. This huge – and ultimately unsustainable – pattern of over-treatment has incited a shift in practice patterns toward initial conservative management known as Active Surveillance (AS), the premise of which is to minimize unnecessary treatment by performing close monitoring. Should there be signs of tumour progression upon recurring reassessment, then treatment can be offered with curative intent. Currently, our ability to discern one’s risk for harbouring an indolent form of prostate cancer utilizes clinical parameters that lack predictive ability. Serum PSA level, clinical stage determined on digital rectal examination (DRE), and tumour grade determined upon biopsy, known as the Gleason Score (GS), are currently used to stratify the risk of tumour progression, although with only limited accuracy. This is evidenced by studies of men eligible for AS who are found to have more advanced disease upon treatment with radical prostatectomy [1] despite meeting AS criteria using the standard criteria. Tools based on the biology of prostate cancer offer a potential platform for improved risk stratification, and hence allow more appropriate levels of intervention.

Invasive and non-invasive testing
Current efforts in biomarker discovery and validation stand to complement the existing tools that gauge eligibility for AS. Several tools, such as Oncotype DX-Prostate® (Genomic Health) and Prolaris® (Myriad Genetics), are commercially available and generate risk scores for harbouring more advanced disease. These rely on extraction of RNA from tumour tissue, most commonly taken from the biopsy specimen that may not contain the sufficient amounts of cancer tissue needed to perform these proprietary tests. AS protocols require periodic repeat biopsies of the tumour, which may have potential complications of bleeding, infection, and pain. Thus, a less invasive method of assessment is ideal. Tools reliant on serum and urine specimens are attractive in that they are more readily obtained. Serum tests, such as free-to-total PSA ratios, the 4K Score (OPKO Health), and the Prostate Health Index (Beckman-Coulter), show promise in refining prostate cancer diagnosis, but these rely on proteins shed from the tumour into circulation. Urine based tests like PCA3 (Gen-Probe) or DNA based tests like ConfirmMDx (MDxHealth) rely on proteins shed into the urine after prostate massage, or DNA extracted from biopsy specimens. These latter tests are utilized in the clinical scenario where prostate cancer remains undiagnosed despite high suspicion by standard parameters.

The biological function of the prostate gland is the production of seminal fluid critical to reproduction. It contains DNA, RNA, proteins and metabolites that have the potential to serve as biomarkers useful in prostate cancer diagnosis and risk assessment. Its contents can be retrieved by two non-invasive methods. The first, variously called a post-DRE urine or post-massage urine, is obtained as a urine sample collected immediately after an attentive DRE. The second, termed prostatic fluid or expressed prostatic secretion (EPS) is obtained after prostatic massage by milking the urethra and collecting fluid directly from the urethral meatus. Neither specimen requires invasive techniques and both contain significant numbers of prostate cancer cells and prostate cancer biomarkers [2–5]. Each has advantages and disadvantages. Post-DRE urine is relatively straightforward to collect; however, the urine volume, and cell lysis that occurs in urine, can significantly dilute the informative cellular material and hinder the recovery of the informative components of the fluid. EPS specimens require more effort to collect but are undiluted and do not promote cell lysis or block activity measurements. Most clinicians would prefer to collect post-DRE urine samples, but the extra effort required to collect EPS could be justified because a number of useful biomarkers cannot be assessed in post-DRE urine. Patient acceptance of both biopsy and EPS collection are improved dramatically by the administration of valium prior to biopsy. Moreover, EPS collection prior to biopsy can be performed in a single clinical visit.

Both EPS and post-DRE urine specimens have proven successful in prostate cancer detection using gene expression biomarkers, where PCA3 and TMPRSS2:ERG fusions have proven effective. Here, sufficient quantities of RNA are present in either specimen, permitting roughly equivalent improvements in performance in the prediction of biopsy outcome (Table 1). The moderate improvement in test performance seen in EPS compared to post-DRE urine appears to be attributable to the need for normalization to PSA messenger RNA measured in the same specimen [6]. This requirement is unique to post-DRE urine as a specimen since urine volume collection is not constant, making it necessary to gauge the informative RNA signals against a fixed RNA signal. The choice of PSA messenger RNA in this application tends to suppress the informative signals since more of it is released into the urine from regions of prostate cancer where the basement membrane is compromised. Moreover it is not possible to measure the volume of the prostatic fluid after it is diluted by the variable urine catch.

DNA methylation is much more difficult to quantify, since DNA is present in much lower concentration in cells, and the required chemical treatments of the isolated DNA results in a severe reduction of the DNA available for quantitative PCR amplification. It has only been reported to be effective in the prediction of biopsy outcome in EPS [4], where the combination of hypermethylation at RARß, RASSF1 and GSTP1performed as well as PCA3 as a single marker.

The field defect and prostate function
Prostate functionality becomes an important diagnostic tool when one considers the extensive field defect that characterizes the disease [8]. Field defects are best defined as functional aberrations that extend beyond the morphologically recognizable tumour in otherwise histologically normal tissue. The concept dates to the early 1950s and has been shown to involve altered DNA methylation patterns extending several millimeters from the prostate tumour. In prostate tumorigenesis it has recently been documented that extensive chromosome rearrangements occur in single steps involving chromothripsis and chromoplexy [9, 10]. In this view the field defect represents clonal progeny of an earlier stage in tumour evolution from which additional chromothripsis and chromoplexy events generate the malignancy. Since most reports of hypermethyled loci fall at or extremely near fragile sites [11], DNA methylation alterations may be linked to chromoplexy and chromothripsis, making it possible to detect cancer by looking for early alterations DNA methylation patterning. Mitochondrial DNA aberrations also appear to track prostate tumour evolution and the field defect includes mitochondrial DNA deletions [12].

Each of these findings suggests that capacity of the prostate gland to produce functional prostatic fluid will be regionally compromised. Genome wide aberrations in DNA methylation coupled with the aberrant expression of transcription factors, such as ERG, could indicate wholesale aberrations in gene expression, while the mitochondrial deletions may underlie alterations in the unique metabolic pathways present in the normal gland. The field defect around larger or more highly evolved tumours could in fact affect the entire gland and can be expected to significantly alter not only the nature but also the amount of prostatic fluid that the gland can produce.

Anecdotally, surgeons collecting EPS by the non-invasive procedure prior to prostatectomy or by squeezing the excised gland just after prostatectomy note that a prostate with a larger tumour burden yields less fluid than a gland bearing small tumour foci, suggesting that the measured volume of the recoverable fluid should be an effective biomarker for prostate cancer. This was demonstrated in recent studies with patients who are eligible for active surveillance by various criteria but were treated with robot assisted radical prostatectomy instead.

For these studies, we used a biomarker set that measures the secretion capacity of the prostate gland. This set includes recovered EPS volume in microlitres and total recovered RNA in nanograms. It is measured along with pre-operative serum PSA value as baseline in multivariate logistic regression analysis (Fig. 1).

Future directions
Given the utility of EPS biomarkers in predicting the presence of occult extracapsular extension in an AS cohort, we believe that the advantages of EPS in assessing the functionality of the gland make it uniquely suited for initial risk stratification in determining eligibility for AS and also in monitoring the disease during surveillance. One of the most perplexing issues in this area is detecting misclassification. In preliminary work in this area (Wittig et al. in prepartion) we noted that more than 40% of patients initially scored as GS 6 in an NCCN cohort can be occult GS 7 comprising largely GS 3+4 patterns with relatively fewer pattern 4+3 GS 7s. Although GS 7 patients are referred for definitive treatment this data suggests that many have not progressed during AS. None of the available biomarkers that we have tested in EPS thus far (TMPRSS2:ERG, PCA3, Secretion Capacity, TXNRD1 or PSA-mRNA) reliably detect this relatively subtle change in the GS. Misclassification recognized at repeat biopsy is generally accepted as an error of initial biopsy undersampling. One can question the clinical significance of such a subtle nuance and its affect on the grander outcomes of disease metastasis and prostate cancer death. Biopsy misclassification is yet another example of the under-performance of standard parameters (like the GS) and the need for biomarker based determinations of disease aggressiveness.

Several new biomarkers are evaluable exclusively in EPS. One example is PSA activity. PSA is a proteolytic enzyme that cannot be assayed in urine specimens, although the assay may function in urine sediment. It is active in EPS and has been shown to be inversely proportional to tumour aggressiveness [13] . Another biomarker with potential in EPS is citrate, which has been shown to be an indicator of prostate cancer in seminal fluid. This marker [14] reflects the overall health of the gland, since the unique metabolism of the normal prostate is designed to secrete citrate into the prostatic fluid. A third biomarker approachable only in EPS is zinc [15]. This ion is taken up preferentially in normal prostate where it blocks the degradation of citrate by inhibiting aconitase in the citric acid cycle thus contributing to the normal function of the gland in citrate secretion.
In summary, the suboptimal performance of the current clinicopatholigic parameters utilized in prostate cancer diagnosis and risk stratification drive the need for additional tools. Biomarkers examined in EPS offer the additional dimension of prostate-function assessment through a non-invasive platform that has great potential to improve prostate cancer diagnosis, risk stratification, and AS.

Abbreviations
AS, active surveillance
AUC, area under curve
DRE, digital rectal examination
EPS, expressed prostatic secretion
GS, Gleason Score
PSA, prostate-specific antigen
ROC, receiver operating characteristic

References
1. Conti SL, Dall’era M, Fradet V, Cowan JE, Simko J, Carroll PR. Pathological outcomes of candidates for active surveillance of prostate cancer. J Urol. 2009; 181: 1628–1633 (Discussion pp. 1624–1633).
2. Groskopf J, Aubin SM, Deras IL, Blase A, Bodrug S, Clark C. APTIMA PCA3 molecular urine test: development of a method to aid in the diagnosis of prostate cancer. Clin Chem. 2006; 52: 1089–1095.
3. Crocitto LE, Korns D, Kretzner L, Shevchuk T, Blair SL, Wilson TG, Ramin, SA, Kawachi MH, Smith SS. Prostate cancer molecular markers GSTP1 and hTERT in expressed prostatic secretions as predictors of biopsy results. Urology 2004; 64: 821–825.
4. Clark JP, Munson KW, Gu JW, Lamparska-Kupsik K, Chan KG, Yoshida JS, Kawachi MH, Crocitto LE, Wilson TG, et al. Performance of a single assay for both type III and type VI TMPRSS2:ERG fusions in non-invasive prediction of prostate biopsy outcome. Clin Chem. 2008; 54: 2007–2017.
5. Laxman B, Tomlins SA, Mehra R, Morris DS, Wang L, Helgeson BE, Shah RB, Rubin MA, Wei JT, Chinnaiyan AM. Noninvasive detection of TMPRSS2:ERG fusion transcripts in the urine of men with prostate cancer. Neoplasia 2006; 8: 885–888.
6. Whelan C, Crocitto L, Kawachi M, Chan K, Smith D, Wilson T, Smith S. The influence of PSA-RNA yield on the analysis of expressed prostatic secretions (EPS) for prostate cancer diagnosis. Can J Urol. 2013; 20: 6597–6602.
7. Tomlins SA, Aubin SM, Siddiqui J, Lonigro RJ, Sefton-Miller L, Miick S, Williamsen S, Hodge P, Meinke J, et al. Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA. Sci Transl Med. 2011; 3: 94ra72.
8. Mehrotra J, Varde S, Wang H, Chiu H, Vargo J, Gray K, Nagle RB, Neri JR, Mazumder A. Quantitative, spatial resolution of the epigenetic field effect in prostate cancer. Prostate 2008; 68: 152–160.
9. Crasta K, Ganem NJ, Dagher R, Lantermann AB, Ivanova EV, Pan Y, Nezi L, Protopopov A, Chowdhury D, Pellman D. DNA breaks and chromosome pulverization from errors in mitosis. Nature 2012; 482: 53–58.
10. Baca SC, Prandi D, Lawrence MS, Mosquera JM, Romanel A, Drier Y, Park K, Kitabayashi N, MacDonald TY, et al. Punctuated evolution of prostate cancer genomes. Cell 2013; 153: 666–677.
11. Smith SS. Maintaining the unmethylated state. Clin Epigenetics 2013; 5: 17.
12. Maki J, Robinson K, Reguly B, Alexander J, Wittock R, Aguirre A, Diamandis EP, Escott N, Skehan A, et al. Mitochondrial genome deletion aids in the identification of false- and true-negative prostate needle core biopsy specimens. Am J Clin Pathol. 2008; 129: 57–66.
13. Ahrens MJ, Bertin PA, Vonesh EF, Meade TJ, Catalona WJ, Georganopoulou D. PSA enzymatic activity: A new biomarker for assessing prostate cancer aggressiveness. Prostate 2013; 73: 1731–1737.
14. Kline EE, Treat EG, Averna TA, Davis MS, Smith AY, Sillerud LO. Citrate concentrations in human seminal fluid and expressed prostatic fluid determined via 1H nuclear magnetic resonance spectroscopy outperform prostate specific antigen in prostate cancer detection. J Urol. 2006; 176: 2274–2279.
15. Zaichick V, Sviridova TV, Zaichick SV. Zinc in the human prostate gland: normal, hyperplastic and cancerous. Int Urol Nephrol. 1997; 29: 565–574.

The authors
Jennifer Linehan MD, Jonathan Yamzon MD, Timothy Wilson MD, and Steven Smith* PhD
NanoLab, Division of Urology, City of Hope, Duarte, California, USA

*Corresponding author
E-mail: ssmith@coh.org

Performance evaluation of tumour markers assay on Mindray CL-2000i chemiluminescence immunoassay system

, 26 August 2020/in Featured Articles, Tumour Markers /by 3wmedia

by Minjie Wang, Binbin Han, Xuexiang Li, Jun Qi Tumour markers play an important role in the detection and management of cancer. It is critical to evaluate new assay systems for precise measurement of commonly used tumour markers in the clinical setting. The goal of this study is to evaluate the performance of […]