Novel prostate cancer biomarkers derived from autoantibody signatures

Protein Modification Employing Non-Canonical Amino Acids to Prepare SUMOylation Detecting Bioconjugates

Protein modification with non-canonical amino acids (ncAAs) represents a useful technology to afford homogenous samples of bioconjugates with site-specific modification. This technique can be directly applied to the detection of aberrant SUMOylation patterns, which are often indicative of disease states. Modified SUMO-trapping proteins, consisting of a catalytically inactive ULP1 fragment (UTAG) fused to the maltose-binding protein MBP, are useful reagents for the binding and labeling of SUMOylated proteins. Mutation of this UTAG fusion protein to facilitate amber suppression technologies for the genetic incorporation of ncAAs was assessed to provide a functional handle for modification. Ultimately, two sites in the maltose-binding protein (MBP) fusion were identified as ideal for incorporation and bioconjugation without perturbation to the SUMO-trapping ability of the UTAG protein. This functionality was then employed to label SUMOylated proteins in HeLa cells and demonstrate their enrichment in the nucleus. This modified UTAG-MBP-ncAA protein has far-reaching applications for both diagnostics and therapeutics.

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Identification of novel autoantibodies in ascites of relapsed paclitaxel-resistant gastric cancer with peritoneal metastasis using immunome protein microarrays and proteomics

BACKGROUND

Gastric cancer (GC) patients with peritoneal metastasis usually have extremely poor prognosis. Intraperitoneal infusion of paclitaxel (PTX) provides an effective treatment, but relapse and PTX-resistance are unavoidable disadvantages, and it is difficult to monitor the occurrence of PTX-resistance.

OBJECTIVE

The aim of this study was to explore novel autoantibodies in the ascites of individuals with relapsed PTX-resistant GC with peritoneal metastasis.

METHODS

Ascites samples were collected before PTX infusion and after the relapse in 3 GC patients. To determine the expression of significantly changed proteins, we performed autoantibody profiling with immunome protein microarrays and tandem mass tag (TMT) quantitative proteomics, and then, the overlapping proteins were selected.

RESULTS

Thirty-eight autoantibodies that were differentially expressed between the ascites in the untreated group and relapsed PTX-resistant group were identified. For confirmation of the results, TMT quantitative proteomics was performed, and 842 dysregulated proteins were identified. Four proteins, TPM3, EFHD2, KRT19 and vimentin, overlapped between these two assays.

CONCLUSIONS

Our results first revealed that TPM3, EFHD2, KRT19 and vimentin were novel autoantibodies in the ascites of relapsed PTX-resistant GC patients. These autoantibodies may be used as potential biomarkers to monitor the occurrence of PTX-resistance.

miRNAs as Therapeutic Tools and Biomarkers for Prostate Cancer

Prostate cancer (PCa) is the fifth cause of tumor-related deaths in man worldwide. Despite the considerable improvement in the clinical management of PCa, several limitations emerged both in the screening for early diagnosis and in the medical treatment. The use of prostate-specific antigen (PSA)-based screening resulted in patients’ overtreatment and the standard therapy of patients suffering from locally advanced/metastatic tumors (e.g., radical prostatectomy, radiotherapy, and androgen deprivation therapy) showed time-limited efficacy with patients undergoing progression toward the lethal metastatic castration-resistant PCa (mCRPC). Although valuable alternative therapeutic options have been recently proposed (e.g., docetaxel, cabazitaxel, abiraterone, enzalutamide, and sipuleucel-T), mCRPC remains incurable. Based on this background, there is an urgent need to identify new and more accurate prostate-specific biomarkers for PCa diagnosis and prognosis and to develop innovative medical approaches to counteract mCRPC. In this context, microRNA (miRNAs) emerged as potential biomarkers in prostate tissues and biological fluids and appeared to be promising therapeutic targets/tools for cancer therapy. Here we overview the recent literature and summarize the achievements of using miRNAs as biomarkers and therapeutic targets/tools for fighting PCa.

Liquid Biopsy Potential Biomarkers in Prostate Cancer

Prostate cancer (PCa) is the second most common cancer in men worldwide with an incidence of 14.8% and a mortality of 6.6%. Shortcomings in comprehensive medical check-ups in low- and middle-income countries lead to delayed detection of PCa and are causative of high numbers of advanced PCa cases at first diagnosis. The performance of available biomarkers is still insufficient and limited applicability, including logistical and financial burdens, impedes comprehensive implementation into health care systems. There is broad agreement on the need of new biomarkers to improve (i) early detection of PCa, (ii) risk stratification, (iii) prognosis, and (iv) treatment monitoring. This review focuses on liquid biopsy tests distinguishing high-grade significant (Gleason score (GS) ≥ 7) from low-grade indolent PCa. Available biomarkers still lack performance in risk stratification of biopsy naïve patients. However, biomarkers with highly negative predictive values may help to reduce unnecessary biopsies. Risk calculators using integrative scoring systems clearly improve decision-making for invasive prostate biopsy. Emerging biomarkers have the potential to substitute PSA and improve the overall performance of risk calculators. Until then, PSA should be used and may be replaced whenever enough evidence has accumulated for better performance of a new biomarker.

Autoantibodies against oncogenic ERG protein in prostate cancer: potential use in diagnosis and prognosis in a panel with C-MYC, AMACR and HERV-K Gag

Overdiagnosis and overtreatment of prostate cancer (CaP) is attributable to widespread reliance on PSA screening in the US. This has prompted us and others to search for improved biomarkers for CaP, to facilitate early detection and disease stratification. In this regard, autoantibodies (AAbs) against tumor antigens could serve as potential candidates for diagnosis and prognosis of CaP. Towards this, our goals were: i) To investigate whether AAbs against ERG oncoprotein (overexpressed in 25-50% of Caucasian American and African American CaP) are present in the sera of CaP patients; ii) To evaluate an AAb panel to enhance CaP detection. The results using an enzyme-linked immunosorbent assay (ELISA) showed that anti-ERG AAbs are present in a significantly higher proportion in the sera of CaP patients compared to healthy controls (p = 0.0001). Furthermore, a panel of AAbs against ERG, AMACR and human endogenous retrovirus-K Gag successfully differentiated CaP patient sera from healthy controls (AUC = 0.791). These results demonstrate for the first time that anti-ERG AAbs are present in the sera of CaP patients. In addition, the data also suggest that AAbs against ERG together with AMACR and HERV-K Gag may be a useful panel of biomarkers for diagnosis and prognosis of CaP.

The Use of Biomarkers in Prostate Cancer Screening and Treatment

Prostate cancer screening and diagnosis has been guided by prostate-specific antigen levels for the past 25 years, but with the most recent US Preventive Services Task Force screening recommendations, as well as concerns regarding overdiagnosis and overtreatment, a new wave of prostate cancer biomarkers has recently emerged. These assays allow the testing of urine, serum, or prostate tissue for molecular signs of prostate cancer, and provide information regarding both diagnosis and prognosis. In this review, we discuss 12 commercially available biomarker assays approved for the diagnosis and treatment of prostate cancer. The results of clinical validation studies and clinical decision-making studies are presented. This information is designed to assist urologists in making clinical decisions with respect to ordering and interpreting these tests for different patients. There are numerous fluid and biopsy-based genomic tests available for prostate cancer patients that provide the physician and patient with different information about risk of future disease and treatment outcomes. It is important that providers be able to recommend the appropriate test for each individual patient; this decision is based on tissue availability and prognostic information desired. Future studies will continue to emphasize the important role of genomic biomarkers in making individualized treatment decisions for prostate cancer patients.

Immunoseroproteomic Profiling in African American Men with Prostate Cancer: Evidence for an Autoantibody Response to Glycolysis and Plasminogen-Associated Proteins

African American (AA) men suffer from a disproportionately high incidence and mortality of prostate cancer (PCa) compared with other racial/ethnic groups. Despite these disparities, African American men are underrepresented in clinical trials and in studies on PCa biology and biomarker discovery. We used immunoseroproteomics to profile antitumor autoantibody responses in AA and European American (EA) men with PCa, and explored differences in these responses. This minimally invasive approach detects autoantibodies to tumor-associated antigens that could serve as clinical biomarkers and immunotherapeutic agents. Sera from AA and EA men with PCa were probed by immunoblotting against PC3 cell proteins, with AA sera showing stronger immunoreactivity. Mass spectrometry analysis of immunoreactive protein spots revealed that several AA sera contained autoantibodies to a number of proteins associated with both the glycolysis and plasminogen pathways, particularly to alpha-enolase (ENO1). The proteomic data is deposited in ProteomeXchange with identifier PXD003968. Analysis of sera from 340 racially diverse men by enzyme-linked immunosorbent assays (ELISA) showed higher frequency of anti-ENO1 autoantibodies in PCa sera compared with control sera. We observed differences between AA-PCa and EA-PCa patients in their immunoreactivity against ENO1. Although EA-PCa sera reacted with higher frequency against purified ENO1 in ELISA and recognized by immunoblotting the endogenous cellular ENO1 across a panel of prostate cell lines, AA-PCa sera reacted weakly against this protein by ELISA but recognized it by immunoblotting preferentially in metastatic cell lines. These race-related differences in immunoreactivity to ENO1 could not be accounted by differential autoantibody recognition of phosphoepitopes within this antigen. Proteomic analysis revealed differences in the posttranslational modification profiles of ENO1 variants differentially recognized by AA-PCa and EA-PCa sera. These intriguing results suggest the possibility of race-related differences in the antitumor autoantibody response in PCa, and have implications for defining novel biological determinants of PCa health disparities.

Developing a model for forecasting Gleason score ≥7 in potential prostate cancer patients to reduce unnecessary prostate biopsies

PURPOSE

The diagnosis of Gleason score (GS) ≥7 with distinction from GS < 7 remains a difficult problem instructing clinical decisions. Moreover, the present wide application of prostate biopsy to increase prostate cancer detection rate might cause unnecessary and excessive examination or treatment. Therefore, a risk assessment model for forecasting GS ≥ 7 in potential prostate cancer patients was established to reduce unnecessary prostate biopsies.

METHODS

Patients (n = 981; September 2009 to January 2013) who underwent trans-rectal ultrasound (TRUS)-guided core prostate biopsy were retrospectively evaluated in the first stage of the study. Age, prostate-specific antigen (PSA), free PSA (fPSA), the free/total PSA ratio (f/t), prostate volume (PV), PSA density (PSAD), digital rectal examination (DRE) findings (texture, nodules) and B-ultrasound detection results (normal or abnormal, presence of hypoechoic mass or microcalcification) were considered as potential predictive factors. After multiple logistic regression analysis, independent variables used to build a nomogram were selected using a backward elimination selection procedure. Then, a model to forecast GS ≥ 7 was designed for potential prostate cancer patients. In the second stage of the study, 410 cases (January 2013 to March 2015) were subsequently evaluated using our model for prostate biopsies, and the outcomes of biopsies were compared between the two stages.

RESULTS

PSA, DRE texture, DRE nodules and B-ultrasound results were finally brought into our nomogram; a obviously greater area under the receiver operating characteristic (ROC) curve was obtained for the model than utilizing PSA, fPSA or PSAD alone (0.831 vs. 0.803, 0.770, 0.780 separately). We thereafter sought the best cutoff value in the ROC curve at 0.87, which provided sensitivity as high as 90%. Meanwhile, the specificity was 45.8%, which was much higher than the specificity of PSA, fPSA and PSAD at the same sensitivity level (37.7, 24.6 and 35.2%, respectively). In the first stage, the detection rate of GS ≥ 7 in the high-risk group was significantly higher than in the low-risk group (80.3 vs. 35.0%, p < 0.001). Furthermore, in the second stage, with the application of the new model associated with our former models, the rate of GS ≥ 7 was improved from 71.0 (697/981) to 79.2% (267/337) (p = 0.003).

CONCLUSIONS

The model for forecasting GS ≥ 7 is effective, which could reduce unnecessary prostate biopsies without delaying patients' diagnoses and treatments.