Cancer is a leading cause of death worldwide. Cancer biomarkers are the key to positive and long-lasting outcomes; they can reduce the suffering and cost to society associated with the disease. The high burden of malignancy worldwide underscores the unmet potential of biomarkers for cancer diagnosis, prognosis and prediction of treatment response. There is a pressing need for novel strategies to discover cancer biomarkers and translate molecular diagnostics from the bench to the bedside Citation[1,2].
Recent technological advances in biomedical research have made it easier to identify many molecular biomarkers that may potentially improve cancer screening and detection, advance the drug development process, and enhance the effectiveness and safety of cancer care by allowing physicians to tailor treatment for individual patients Citation[3]. Proteomics is a promising technology for the identification of biomarkers and novel therapeutic targets for cancers. Rapid progress in oncoproteomics has opened new avenues for tumor-associated biomarker discovery Citation[4].
Diagnostic or early-detection biomarkers
Early detection of cancer is a way to improve the overall survival in the cancer epidemic. Identified by MALDI-TOF/TOF, serum vimentin was found to be significantly overexpressed in the small-size (≤2 cm) hepatocellular carcinoma (HCC) tumors compared with the non-neoplastic controls. It is further confirmed to be a potential surrogate marker for the detection of small HCCs, either alone or in combination with α-fetoprotein Citation[5]. Performing comparative proteomics analysis based on 2D gel electrophoresis of HCC tissues, the downregulation of phenol sulfotransferase (SULT1A1) was demonstrated to be closely associated with an advanced International Union Against Cancer stage and high levels of serum α-fetoprotein. SULT1A1 may be a useful biomarker for the detection of early HCC and it may help to predict the clinical outcome of HCC patients Citation[6].
Employing standard immunoproteomic methods and a Luminex-based direct-capture immunobead assay, a multiplexed tumor-associated autoantibody (including annexin I, annexin II, heat-shock protein 70-9B, inosine-5-monophosphate dehydrogenase, phosphoglycerate mutase and ubiquillin)-based blood test has been developed for the detection of early-stage non-small cell lung cancer (NSCLC) in high-risk populations. The misclassification rate of this six-biomarker panel is only 7% Citation[7]. On the other hand, the isobaric tag for relative and absolute quantitation-based quantitative profile of urine samples from bladder cancer patients with different stages has identified apolipoprotein A-I (APOA1) as a potential bladder cancer biomarker for early detection. Sensitivity and specificity were 84 and 94%, respectively Citation[8].
Recently, the US FDA approval of an ovarian tumor triage test OVA1™ marked a milestone achievement for the development of protein markers from the laboratory to the clinic. When combined with clinical assessment such as imaging and physical examination, this immunoassay-based assay (including 2-microglobulin, APOA1, CA125, transferrin and transthyretin) has a positive predictive value in women with a higher likelihood of malignancy. The OVA1 score can assist physicians in determining whether a patient would benefit from referral to a gynecologic oncologist because of a high likelihood of malignancy Citation[9].
Prognostic or metastasis biomarkers
Prognostic or metastasis biomarkers help to stratify cancer patients for treatment by identifying individuals with different risks of outcome. A number of biomarkers have recently been identified that offer important prognostic information. In the comparative analysis of whole proteomes between ovarian serous borderline tumor and serous carcinoma, overexpression of peroxiredoxin 1 (PRDX1) was significantly correlated with poor overall survival in serous carcinomas. On a multivariate Cox analysis, the relative risk of death was 8.74 in patients with serous carcinomas showing more than 50% of PRDX1-positive cancer cells. These results suggested that PRDX1 might be a useful prognostic biomarker in ovarian serous carcinoma Citation[10]. Comparing the benign bladder urothelium and urothelial carcinomas, it has been reported that increased expression of bladder cancer-associated protein confers an adverse patient outcome, suggesting that categorization of staining patterns for this protein may have prognostic value. Furthermore, the combination of bladder cancer-associated protein and adipocyte-type fatty acid-binding protein correlated more closely with grade and/or stage of disease than the individual markers Citation[11].
Using laser microdissection, accurate mass and time tag proteomics, differential proteins were reported conforming to a variety of potential tumorigenic pathways in intrahepatic cholangiocarcinoma (ICC). Explored by tissue microarray analysis, an increased abundance of vimentin was detected in 70% of ICC cases and in none of the controls. These results suggested that vimentin might play a role in the aggressiveness of ICC and it provided a basis for the serious outcome of this cancer Citation[12]. SELDI-TOF mass spectrometry (MS) analysis of meningioma tissues was carried out to discover new markers of tissue invasion/infiltration. An increased phosphorylation of vimentin appeared to be a discriminative marker for clustering infiltrative and noninfiltrative meningiomas. Sensitivity and specificity were 86.7 and 100%, respectively Citation[13].
For NSCLC, serum amyloid A (SAA) was detected by SELDI-TOF MS to be significantly elevated in lung cancer patients with survival time of less than 5 years when compared with patients with a survival time of 5 years or more. Elevated SAA level may be a noninvasive biomarker useful for the prediction of NSCLC prognosis Citation[14]. Also screened by SELDI-TOF MS, apolipoprotein A-II and SAA were identified as independent factors for survival of metastatic renal cell cancer patients. Combining these two proteins with lactate dehydrogenase, performance status and the number of metastasis sites, a novel prognostic survival model was generated. This protein-based model may improve prediction of overall survival over the commonly used Memorial Sloan-Kettering Cancer Center risk model Citation[15].
Stable isotope labeling of amino acids in cell culture followed by liquid chromatography (LC)-MS/MS analysis has identified mitochondrial import inner membrane translocase subunit Tim17-A (TIMM17A) as a prognostic marker for breast cancer. The expression level of TIMM17A was directly correlated with tumor progression and survival. Overexpression and siRNA knockdown experiments indicated oncogenic activity of TIMM17A in breast cancer Citation[16]. A LC-MS/MS-based label-free quantitative proteomics approach was applied to compare the differential secretome of primary colorectal cancer (CRC) and its lymph node metastatic cells. Immunohistochemical analysis demonstrated that the overexpressions of growth differentiation factor 15 or trefoil factor 3 in CRC were associated with lymph node metastasis. They may serve as potential biomarkers for the prediction of CRC metastasis Citation[17].
Analyzing the nasopharyngeal carcinoma (NPC) cell secretome and tissue transcriptome, a higher pretreated serum level of cystatin A was found to be associated with a higher nodal stage and poorer prognosis of NPC patients. Cystatin A could modulate the migration and invasion of NPC cells in vitroCitation[18]. It has been detected that NPC patients with higher eukaryotic translation initiation factor 4 γ1 (EIF4G1) expression had shorter overall survival. Using shRNA to knock down the expression of EIF4G1 not only markedly inhibited cell cycle progression, proliferation, migration, invasion and colony formation, but also dramatically suppressed in vivo xenograft tumor growth Citation[19].
Biomarkers predictive of therapeutic benefit
Another important aspect of cancer biomarkers is the predictive ability they provide for the use of a more targeted approach in treatment. Proteomics analysis demonstrated that the downregulation of 14-3-3σ and maspin, as well as the upregulation of GRP78 and Mn-SOD, were significantly correlated with NPC radioresistance. A combination of the four proteins achieved a sensitivity and specificity of 90 and 88%, respectively, in discriminating radiosensitive from radioresistant NPC. Furthermore, resistance to ionizing radiation can be partially reversed by overexpressed 14-3-3σ in radioresistant cells Citation[20]. Proteomics and immunohistochemical analyses on pretreatment biopsies revealed that the immune signaling molecule α-defensin was overexpressed in tumors from breast cancer patients with a pathologic complete response to neoadjuvant radiation or paclitaxel treatment. Analysis of a larger panel of tumors from patients receiving presurgical taxane-based treatment demonstrated that α-defensins were statistically associated with response to therapy at the time of surgery Citation[21].
Measured by reverse-phase protein array, EGF receptor (EGFR) and two TGF-β pathway proteins (c-jun-NH2-kinase and Smad3) demonstrated significant associations with normalization of CA125 in post-chemotherapy patients with advanced serous ovarian cancer. TGF-β pathway signaling may play an important role as a marker of chemoresistance in advanced serous ovarian cancer Citation[22].
A Phase I dose-escalation study assessed biomarkers for cetuximab efficacy in plasma and tissue samples collected from metastatic CRC patients Citation[23]. Pharmacoproteomics and pharmacogenomics analyses demonstrated that responses were seen only in patients with KRAS wild-type tumors, and progression-free survival was longer for patients with KRAS wild-type compared with KRAS mutant tumors. These results confirmed that patients with KRAS wild-type metastatic CRC were those most likely to benefit from cetuximab treatment Citation[23]. Tumor EGFR ligand RNA levels were also significantly associated with survival classification predicted by the VeriStrat signatures (serum MALDI classifier based on eight distinct m/z features provided by Biodesix, [Broomfield, CA, USA]) in CRC patients treated with cetuximab or EGFR-tyrosine kinase inhibitors, and combined KRAS mutation status provided improved survival classification. This combination of biomarkers may provide a clinically practical way to identify patients with diverse cancer types who are most likely to benefit from treatment with EGFR inhibitors Citation[24]. Biospecimens from a Phase II study of erlotinib in first-line advanced lung cancer were analyzed by the VeriStrat®. Significant correlations between VeriStrat status and EGFR mutations with survival were found, but such correlations were not found with KRAS mutations. VeriStrat was confirmed to be a significant predictor of survival after first-line treatment with erlotinib in patients with wild-type EGFR, independent of mutations in KRASCitation[25].
Challenges & perspectives
Although the discovery of molecular biomarkers has increased tremendously in recent decades, translation of these biomarkers to more effective patient care and better outcomes remains a challenge. There are still many obstacles to develop clinically useful cancer biomarkers, including technical challenges associated with pre-analytical variables and validating potential cancer biomarkers, as well as challenges associated with developing, evaluating and incorporating the screening or diagnostic tests that make use of those cancer biomarkers into clinical practice Citation[3].
The emerging omics technologies are being increasingly used for cancer research and biomarker discovery Citation[26]. Recent advances in high-throughput proteomics technologies have provided new opportunities in the molecular analysis of human cancer at an unprecedented speed. Oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as invasion, metastasis and resistance to therapy Citation[4]. With the advent of new and improved protein chip technologies, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management Citation[27]. It is foreseeable that the future of the use of protein markers would have to go through miniaturized and automatic techniques. Multiple biomarkers will probably be used together to develop more accurate assays. Combinations of existing biomarkers with novel molecular markers will probably be an emerging trend in developing theranostic tests for cancer management. Molecular cancer biomarkers are moving forward in translational medicine, but there is still a long way to success.
Financial & competing interests disclosure
The author has 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.
Related Research Data
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