Identification of serum biomarkers for pancreatic adenocarcinoma by proteomic analysis

Overexpressed C14orf166 associates with disease progression and poor prognosis in non-small-cell lung cancer

Chromosome 14 ORF 166 (C14orf166), a protein involved in the regulation of RNA transcription and translation, has been reported to possess the potency to promote tumorigenesis; however, the role of C14orf166 in non-small-cell lung cancer (NSCLC) remains unknown. The purpose of the present study was to assess C14orf166 expression and its clinical significance in NSCLC. Immunohistochemical staining, quantitative real-time PCR (qRT-PCR), and Western blotting were used to detect the C14orf166 protein and mRNA expression levels in NSCLC tissues compared with adjacent normal tissues, as well as in NSCLC cells lines compared with normal human bronchial epithelial cells (HBE). Then, the correlations between the C14orf166 expression levels and the clinicopathological features of NSCLC were analyzed. Additionally, the Cox proportional hazard model was used to evaluate the prognostic significance of C14orf166. We found that C14orf166 expression increased in carcinoma tissues compared with their adjacent normal tissues at the protein (P<0.001) and mRNA levels (P<0.001). High expression of C14orf166 was significantly associated with the T stage (P=0.006), lymph node metastasis (P=0.001), advanced TNM stage (P<0.001), and chemotherapy (P<0.001). Moreover, according to the survival analysis, patients with overexpressed C14orf166 were inclined to experience a shorter overall survival and disease-free survival time (P<0.001). Multivariate COX analysis implied that C14orf166 was an independent prognostic biomarker. Taken together, our findings indicate that the overexpression of C14orf166 may contribute to the disease progression of NSCLC, represent a novel prognostic predictor and help high-risk patients make better decisions for subsequent therapy.

Pancreatic Cancer Diagnosis and Management: Has the Time Come to Prick the Bubble?

Pancreatic cancer (PC) is associated with poor prognosis and very dismal survival rates. The most effective possibility of cure is tumor resection, which is only possible in about 15% of patients diagnosed at early stages of disease progression. Recent whole-genome sequencing studies pointed genetic alterations in 12 core signaling pathways in PC. These observations hint at the possibility that the initial mutation in PC might appear nearly 20 years before any symptoms occur, suggesting that a large window of opportunity may exist for early detection. Biomarkers with the potential to identify pre-neoplastic disease or very early stages of cancer are of great promise to improve patient survival. The concept of liquid biopsy refers to a minimally invasive sampling and analysis of liquid biomarkers that can be isolated from body fluids, primarily blood, urine and saliva. A myriad of circulating molecules may be useful as tumor markers, including cell-free DNA (cfDNA), cell-free RNA (cfRNA), circulating tumor cells (CTC), circulating tumor proteins, and extracellular vesicles, more specifically exosomes. In this review, we discuss with more detail the potential role of exosomes in several aspects related to PC, from initiation to tumor progression and its applicability in early detection and treatment. Exosomes are small circulating extracellular vesicles of 50-150 nm in diameter released from the plasma membrane by almost all cells and exhibit some advantages over other biomarkers. Exosomes are central players of intercellular communication and they have been implicated in a series of biological process, including tumorigenesis, migration and metastasis. Several exosomal microRNAs and proteins have been observed to distinguish PC from benign pancreatic diseases and healthy controls. Besides their possible role in diagnosis, understanding exosomes functions in cancer has clarified the importance of microenvironment in PC progression as well as its influence in proliferation, metastasis and resistance to chemotherapy. Increasing knowledge on cancer exosomes provides valuable insights on new therapeutic targets and can potentially open new strategies to treat this disease. Continuous research is needed to ascertain the reliability of using exosomes and their content as potential biomarkers, so that, hopefully, in the near future, they will provide the opportunity for early diagnosis, treatment intervention and increase survival of PC patients.

Differential Protein Expression Marks the Transition From Infection With Opisthorchis viverrini to Cholangiocarcinoma

Parts of Southeast Asia have the highest incidence of intrahepatic cholangiocarcinoma (CCA) in the world because of infection by the liver fluke Opisthorchis viverrini (Ov). Ov-associated CCA is the culmination of chronic Ov-infection, with the persistent production of the growth factors and cytokines associated with persistent inflammation, which can endure for years in Ov-infected individuals prior to transitioning to CCA. Isobaric labeling and tandem mass spectrometry of liver tissue from a hamster model of CCA was used to compare protein expression profiles from inflammed tissue (Ovinfected but not cancerous) versus cancerous tissue (Ov-induced CCA). Immunohistochemistry and immunoblotting were used to verify dysregulated proteins in the animal model and in human tissue. We identified 154 dysregulated proteins that marked the transition from Ov-infection to Ov-induced CCA, i.e. proteins dysregulated during carcinogenesis but not Ov-infection. The verification of dysregulated proteins in resected liver tissue from humans with Ov-associated CCA showed the numerous parallels in protein dysregulation between human and animal models of Ov-induced CCA. To identify potential circulating markers for CCA, dysregulated proteins were compared with proteins isolated from exosomes secreted by a human CCA cell line (KKU055) and 27 proteins were identified as dysregulated in CCA and present in exosomes. These data form the basis of potential diagnostic biomarkers for human Ov-associated CCA. The profile of protein dysregulation observed during chronic Ovinfection and then in Ov-induced CCA provides insight into the etiology of an infection-induced inflammation-related cancer.

Expression and clinical significance of C14orf166 in esophageal squamous cell carcinoma

C14orf166, a 28 kD protein regulating RNA transcription and translation, may serve a critical role in oncogenesis. The aim of the current study was to explore the association between C14orf166 expression and esophageal squamous cell carcinoma (ESCC) and to draw attention to the association between C14orf166 and the initiation, progression and prognosis of ESCC. C14orf166 expression in ESCC and paired normal tissues was detected by immunohistochemical staining, western blotting and reverse transcription-quantitative polymerase chain reaction, and the association between C14orf166 expression and clinicopathological characters of ESCC was analyzed. Survival analysis was used to assess the prognostic significance of C14orf166 and it was observed that C14orf166 expression was higher in the ESCC tissues when compared with adjacent non-cancerous tissues at protein (P<0.001) and mRNA levels (P<0.001). There was a significant difference in T stage, lymph node metastasis and TNM stage in patients categorized according to different C14orf166 expression levels. The overexpression of C14orf166 was associated with a shorter overall survival and disease-free survival, and multivariate analysis indicated that C14orf166 was an independent prognostic indicator. The present study indicates that the expression of C14orf166 is elevated in ESCC, and is potentially a valuable prognostic predictor for ESCC.

C14orf166 overexpression correlates with tumor progression and poor prognosis of breast cancer

BACKGROUND

Chromosome 14 open reading frame 166 (C14orf166) is upregulated in various tumors, but its role in breast cancer has not been reported.

METHODS

Quantitative real-time PCR and western blot were used to determine C14orf166 expression in normal breast epithelial cells (NBEC), breast cancer cells, and four matched pairs of breast cancer tissues and adjacent noncancerous tissues. Using immunohistochemistry, we determined C14orf166 expression in paraffin-embedded tissues from 121 breast cancer patients. Statistical analyses were performed to examine the associations among C14or166 expression, clinicopathological parameters and prognosis outcome of breast cancer. MTT and colony formation assay were used to determine the effect of C14orf166 on cell proliferation by overexpression or knockdown of C14orf166 level.

RESULTS

C14orf166 was upregulated in breast cancer cell lines and tissues compared with the normal cells and adjacent normal breast tissues, high C14orf166 expression was positively with advancing clinical stage. The correlation analysis between C14orf166 expression and clinicopathological characteristics suggested C14orf166 expression was significantly correlated with clinical stages, T classification, N classification and PR expression, Kaplan-Meier curves with log rank tests showed patients with low C14orf166 expression had better survival, Cox-regression analysis suggested C14orf166 was an unfavorable prognostic factor for breast cancer patients. C14orf166 overexpression promoted breast cancer cell proliferation, whereas knockdown of C14orf166 inhibited this effect. Further analysis found C14orf166 overexpression inhibited cell cycle inhibitors P21 and P27 expression, and increased the levels of Cyclin D1 and phosphorylation of Rb, suggesting C14orf166 contributed to cell proliferation by regulating G1/S transition.

CONCLUSION

Our findings suggested C14orf166 could be a novel prognostic biomarker of breast cancer, it also contributes to cell proliferation by regulating G1/S transition.

Exosomes: potential for early detection in pancreatic cancer

Progress in the treatment of patients with pancreatic cancer at earlier stages has motivated research in identifying novel noninvasive or minimally invasive biomarkers for early detection. Exosomes, which contain bioactive molecules (such as proteins, RNAs and lipids), are membrane-structured nanovesicles that are secreted from living cells and are found in human body fluids. As functional mediators, exosomes play key roles in cell-cell communications, regulating diverse biological processes. Here we aim to examine recent findings in the potential diagnostic value of serum exosomes in pancreatic cancer.

Pancreatic Cancer: a Challenge to Cure

Pancreatic ductal adenocarcinoma (PDA) is a challenging disease, as overall survival has not improved over the last several decades. The disease is characterized by late diagnosis, difficult major surgery in resectable patients, and a biologically chemoresistant tumor. Intense research in the field is ongoing to develop biomarkers for early detection and prognostication. Surgery is presently the crux of the management of PDA and has been standardized over the years with high-volume centers reporting <5 % operative mortality. The biggest problem is to overcome the inherent chemoresistance of the tumor that is densely fibrotic and hypoxic and has a tendency to invade surrounding neuronal plexuses. This review attempts to summarize in brief the reasons why PDA is difficult to treat, and provides a glimpse of the ongoing research in the field.

Complement C4a inhibits the secretion of hepatitis B virus screened by surface-enhanced laser desorption ionization time-flight mass spectrometry-based ProteinChip analysis

PURPOSE

Chronic hepatitis B (CHB) is a kind of chronic liver disease caused by persistent hepatitis B virus (HBV) infection. The study aims to seek the factors of host resistance to HBV and investigate their roles.

EXPERIMENTAL DESIGN

Protein profiles of 58 healthy controls and 121 CHB patients were obtained by SELDI-TOF/MS. Predicted protein was validated by ELISA. Protein expression was evaluated by Western blot in the persistently HBV expressing cell line HepG2.2.15 and non-HBV expressing cell line HepG2. The level of HBV DNA was subsequently detected by quantitative real-time PCR in HepG2.2.15 cells with complement C4a treatment.

RESULTS

Significantly altered protein peaks were found through statistical analysis, and m/z 4300 was predicted by databases and successfully matched with the fragment of complement C4a. According to ELISA, serum complement C4a was found to be significantly lower in CHB patients compared with healthy controls (p < 0.001) and the area under receiver operating characteristics curve is 0.78. Furthermore, complement C4a showed lower expression in HepG2.2.5 cells and the secretion of HBV DNA was inhibited by complement C4a.

CONCLUSIONS AND CLINICAL RELEVANCE

The present study implied the important role of complement C4a in inhibiting the HBV DNA secretion in CHB.

C14ORF166 overexpression is associated with pelvic lymph node metastasis and poor prognosis in uterine cervical cancer

C14ORF166 (chromosome 14 open reading frame 166) is a transcriptional repressor related to the regulation of centrosome architecture. However, the role of C14ORF166 in the development and progression of cancer remains largely unknown. The aim of this study was to investigate the expression and clinicopathological significance of C14ORF166 in cervical cancer. C14ORF166 expression was analyzed using quantitative real-time PCR (RT-PCR) and Western blotting in cervical cancer cell lines and eight paired cervical cancer samples and the adjacent normal tissues. Immunohistochemistry was used to analyze C14ORF166 protein expression in 148 clinicopathologically characterized cervical cancer specimens. Statistical analyses were performed to evaluate the relationship between the expression of C14ORF166 and clinicopathologic features and prognosis. C14ORF166 mRNA and protein expression were significantly upregulated in cervical cancer cell lines and tissue samples (P < 0.05). Immunohistochemical analysis revealed a high expression of C14ORF166 was observed in 39.9 % (59/148) of the cervical cancer specimens; the remaining samples expressed low levels or did not express any detectable C14ORF166. The chi-square test indicated that high-level expression of C14ORF166 was significantly associated with International Federation of Gynecology and Obstetrics (FIGO) stage (P < 0.001), vital status (P = 0.026), tumor size (P = 0.034), serum squamous cell carcinoma antigen level (SCC-Ag; P = 0.035), and pelvic lymph node metastasis (P < 0.001). Patients with highly expressed C14ORF166 showed a tendency to receive postoperative chemotherapy (P = 0.005) and postoperative radiation (P = 0.008). Furthermore, high C14ORF166 expression was associated with poorer overall survival compared to low C14ORF166 expression, and C14ORF166 was a significant prognostic factor in univariate and multivariate analysis (P < 0.05). High C14ORF166 expression had prognostic value for poor outcome in cervical cancer. C14ORF166 may represent a biomarker of pelvic lymph node metastasis and enable the identification of high-risk patients along with selection of appropriate treatment strategies.

Pancreatic cancer: diagnosis and treatments

Pancreatic cancer is one of the deadliest cancers, with exceptionally high mortality. Despite the relatively low incidence rate (10th), it is the fourth leading cause of cancer-related deaths in most developed countries. To improve the early diagnosis of pancreatic cancer and strengthen the standardized comprehensive treatment are still the main focus of pancreatic cancer research. Here, we summarized the rapid developments in the diagnosis and treatments of pancreatic cancer. Regarding diagnosis, we reviewed advances in medical imaging technology, tumor markers, molecular biology (e.g., gene mutation), and proteomics. Moreover, great progress has also been made in the treatments of this disease, including surgical resection, chemotherapy, targeted radiotherapy, targeted minimally invasive treatment, and molecular targeted therapy. Therefore, we also recapitulated the development, advantages, and disadvantages of each of the treatment methods in this review.

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results.

SELDI-TOF-MS proteomic profiling of serum, urine, and amniotic fluid in neural tube defects

Neural tube defects (NTDs) are common birth defects, whose specific biomarkers are needed. The purpose of this pilot study is to determine whether protein profiling in NTD-mothers differ from normal controls using SELDI-TOF-MS. ProteinChip Biomarker System was used to evaluate 82 maternal serum samples, 78 urine samples and 76 amniotic fluid samples. The validity of classification tree was then challenged with a blind test set including another 20 NTD-mothers and 18 controls in serum samples, and another 19 NTD-mothers and 17 controls in urine samples, and another 20 NTD-mothers and 17 controls in amniotic fluid samples. Eight proteins detected in serum samples were up-regulated and four proteins were down-regulated in the NTD group. Four proteins detected in urine samples were up-regulated and one protein was down-regulated in the NTD group. Six proteins detected in amniotic fluid samples were up-regulated and one protein was down-regulated in the NTD group. The classification tree for serum samples separated NTDs from healthy individuals, achieving a sensitivity of 91% and a specificity of 97% in the training set, and achieving a sensitivity of 90% and a specificity of 97% and a positive predictive value of 95% in the test set. The classification tree for urine samples separated NTDs from controls, achieving a sensitivity of 95% and a specificity of 94% in the training set, and achieving a sensitivity of 89% and a specificity of 82% and a positive predictive value of 85% in the test set. The classification tree for amniotic fluid samples separated NTDs from controls, achieving a sensitivity of 93% and a specificity of 89% in the training set, and achieving a sensitivity of 90% and a specificity of 88% and a positive predictive value of 90% in the test set. These suggest that SELDI-TOF-MS is an additional method for NTDs pregnancies detection.

Increase of exostosin 1 in plasma as a potential biomarker for opisthorchiasis-associated cholangiocarcinoma

A proteomic-based approach was used to search for potential markers in the plasma of hamsters in which cholangiocarcinoma (CCA) was induced by Opisthorchis viverrini infection and N-nitrosodimethylamine treatment. The plasma proteins of CCA-induced hamsters were resolved by 1-D PAGE, digested by trypsin, and analyzed by LC-MS/MS. From the criteria of protein ID scores >15 and an overexpression of at least three times across all time points, 37 proteins were selected. These overexpressed proteins largely consisted of signal transduction, structural, transport, and transcriptional proteins in the order. Among the most frequently upregulated proteins, exostosin 1 (EXT1) was selected for further validation. By western blot analysis, the EXT1 expression level in the plasma of hamster CCA was significantly higher than that of controls at 1 month and thereafter. Immunohistochemistry revealed that EXT1 was expressed at vascular walls and fibroblasts at 21 days (before tumor onset) and at 2 months (early CCA) posttreatment. Its expression was also observed in bile duct cancer cells during tumor progression at 6 months posttreatment. In the human CCA tissue microarray, EXT1 immunoreactivity was found not only in vascular walls and fibroblasts but also in bile duct cancer cells and was positive in 89.7 % (61/68) of the cases. By ELISA and immunoblotting, plasma EXT1 level was significantly higher in human CCA compared to healthy controls. In conclusion, these results suggest that increased expression of EXT1 level in the plasma might be involved in CCA genesis and might be a potential biomarker of CCA.

Biomarkers in pancreatic cancer: diagnostic, prognostic, and predictive

Pancreatic cancer is the fourth leading cause of cancer-related death in the United States. There has been minimal progress with regard to cancer-specific outcomes in recent decades. Although effective therapies will undoubtedly change the natural history of the disease, effective biomarkers are a promising tool that will likely have a positive impact and will undoubtedly have an important role in the management of patients with pancreatic ductal adenocarcinoma (PDA) in the future. At present, serum CA-19-9 (carbohydrate antigen 19-9) is the only Food and Drug Administration-approved biomarker for PDA, and it has utility as a prognostic marker and as a marker of disease recurrence. There has been a recent explosion in the pancreatic cancer biomarker field with more than 2000 biomarker studies implicating thousands of informative genes as candidate biomarkers. In this review, we summarize the literature on CA-19-9 in PDA and highlight the most promising investigational biomarkers. Distinctions are made between diagnostic biomarkers (detection of disease), prognostic biomarkers (provide information on prognosis and recurrence pattern), and predictive biomarkers (predict treatment response).

Detection of pancreatic cancer using serum protein profiling

BACKGROUND

Currently, no suitable biomarkers for the early detection of pancreatic cancer (PC) are available. Proteins present in the serum could reflect a state of the disease. In this study, these profiles as a diagnostic marker for PC were evaluated.

METHODS

Serum samples were obtained from PC patients (n = 50 calibration set, n = 39 validation set) and healthy volunteers (n = 110 and n = 75 respectively) according to a uniform standardized collection and processing protocol. For peptide and protein isolation, automated solid-phase extraction (SPE) with Weak Cation Exchange (WCX) magnetic beads (MB) was performed using a 96-channel liquid handling platform. Protein profiles were obtained by mass spectrometry (MS) and evaluated by linear discriminant analysis with double cross-validation.

RESULTS

A discriminating profile for PC has been identified, with a sensitivity of 78% and a specificity of 89% in the calibration set with an area under the curve (AUC) of 90%. These results were validated with a sensitivity of 74% and a specificity of 91% (AUC 90%).

CONCLUSION

Serum profiles of healthy controls and PC can be discrimated between. Further research is warranted to evaluate specificity and whether this biosignature can be used for early detection in a high risk population.

Serum proteomics in biomedical research: a systematic review

Proteins that are important indicators of physiological or pathological states may contribute to the early diagnosis of disease, which may provide a basis for identifying the underlying mechanism of disease development. Serum, contains an abundance of proteins, offers an easy and inexpensive approach for disease detection and possesses a high potential to revolutionize the diagnostics. These differentially expressed proteins in serum have become an important role to monitoring the state for disease. Availability of emerging proteomic techniques gives optimism that serum can eventually be placed as a biomedium for clinical diagnostics. Advancements have benefited biomarker research to the point where serum is now recognized as an excellent diagnostic medium for the detection of disease. Comprehensive proteome of human serum fluid with high accuracy and availability has the potential to open new doors for disease biomarker discovery and for disease diagnostics, providing insights useful for future study. Thus, this review presents an overview of the value of serum as a credible diagnostic tool, and we aim to summarize the proteomic technologies currently used for global analysis of serum proteins and to elaborate on the application of serum proteomics to the discovery of disease biomarkers, and discuss some of the critical challenges and perspectives for this emerging field.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

Treatment when prognostic factors do not match St. Gallen recommendations: profiling of prognostic factors among HR(+) and HER2(-) breast cancer patients

BACKGROUND

The St. Gallen consensus provides treatment recommendations for breast cancer based on prognostic factors. Although many patients' prognostic patterns are not easily matched with the prognostic patterns listed in the St. Gallen consensus, there has been no systematic investigation reporting the gap between treatment recommendations and actual postoperative treatment choices in clinical practice.

METHODS

Four hundred seventy-one patients with hormone receptor-positive [HR(+)] and human epidermal growth factor receptor type 2-negative [HER2(-)] breast cancer were analyzed. These patients were classified into either the "crisp treatment group" or "fuzzy treatment group" based on the definitiveness of postoperative treatment selection based on St. Gallen treatment recommendations. The patients in the fuzzy treatment group were further classified into strata in which patients within each stratum shared the same prognostic factor patterns with similar recurrence rates.

RESULTS

A total of 87.3% of HR(+)HER2(-) patients were designated to the fuzzy treatment group. Four prognostic strata were constructed according to the survival tree model, and revealed that patients with poor prognostic profiles tended to receive endocrine therapy with chemotherapy. This suggests that postoperative chemotherapy is useful, although there was no statistical significance.

CONCLUSIONS

We constructed prognostic profiles of patients in the fuzzy treatment group and examined the recurrence rates associated with two treatment regimens within each prognostic profile. These findings are exploratory, but they may be useful for planning prospective studies of the effectiveness of postoperative treatment regimens among patients with a heterogeneous combination of prognostic factors.

Diagnostic, prognostic, and predictive biomarkers in pancreatic cancer

Serum CA 19-9 is the only FDA approved biomarker recommended for use in the routine management of pancreatic ductal adenocarcinoma (PDA). Over 2,000 biomarker studies related to pancreatic cancer appear in the literature, highlighting the need to discover and develop improved tests. Diagnostic biomarkers have implications for early detection of PDA, prognostic markers predict patient survival and recurrence patterns, and predictive markers can help personalize treatment regimens.

Seven-signal proteomic signature for detection of operable pancreatic ductal adenocarcinoma and their discrimination from autoimmune pancreatitis

There is urgent need for biomarkers that provide early detection of pancreatic ductal adenocarcinoma (PDAC) as well as discrimination of autoimmune pancreatitis, as current clinical approaches are not suitably accurate for precise diagnosis. We used mass spectrometry to analyze protein profiles of more than 300 plasma specimens obtained from PDAC, noncancerous pancreatic diseases including autoimmune pancreatitis patients and healthy subjects. We obtained 1063 proteomic signals from 160 plasma samples in the training cohort. A proteomic signature consisting of 7 mass spectrometry signals was used for construction of a proteomic model for detection of PDAC patients. Using the test cohort, we confirmed that this proteomic model had discrimination power equal to that observed with the training cohort. The overall sensitivity and specificity for detection of cancer patients were 82.6% and 90.9%, respectively. Notably, 62.5% of the stage I and II cases were detected by our proteomic model. We also found that 100% of autoimmune pancreatitis patients were correctly assigned as noncancerous individuals. In the present paper, we developed a proteomic model that was shown able to detect early-stage PDAC patients. In addition, our model appeared capable of discriminating patients with autoimmune pancreatitis from those with PDAC.

Discovery of diagnostic biomarkers for pancreatic cancer in immunodepleted serum by SELDI-TOF MS

MOTIVATION

Reports of serum pancreatic cancer (PC) biomarkers using SELDI-TOF MS have been inconsistent because different chip surfaces and interference with high-abundant proteins. This study examines the influence of these factors on the detection of discriminating diagnostic biomarkers.

METHODS

Serum from fourteen from patients with PC, disease controls (DC, n = 14) and healthy volunteers (HV, n = 14) were evaluated by SELDI using H50, IMAC, Q10 and CM10 chips. A further evaluation was undertaken after depletion of seven high-abundant proteins using spin cartridges.

RESULTS

More protein peaks were detected in whole serum than in depleted serum for IMAC, H50 and Q10 chips: 60 vs 39, 56 vs 48 and 69 vs 65, respectively, while the CM10 found less peaks in serum (27 vs 47 peaks). However, there were more differentially expressed peaks in the depleted serum samples for PC vs DC and PC vs HV samples using the H50, Q10 and CM10 ProteinChip arrays, whereas for IMAC arrays, more discriminating peaks were seen in non-depleted serum. The highly significant peaks observed on Q10, CM10 and H50 are consistent with the previous finding of ApoA-I (m/z 27,910-28000) and ApoA-II (m/z 8758 and 17,240). In addition, a number of new discriminating protein peaks were found on different ProteinChip arrays, notably peaks at m/z 4280 and 7763 on IMAC arrays.

CONCLUSION

This study confirms the diagnostic value of ApoA-I&II and identifies further potential diagnostic biomarkers for pancreatic cancer when multiple chip surfaces are used with depletion of the most highly-abundant proteins.

Purification, identification and profiling of serum amyloid A proteins from sera of advanced-stage cancer patients

Surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) is a powerful tool for screening potential biomarkers of various pathological conditions. However, low resolution and mass accuracy of SELDI-TOF-MS remain a major obstacle for determination of biological identities of potential protein biomarkers. We report here a refined workflow that combines ZipTip desalting, acetonitrile precipitation, high-performance liquid chromatography (HPLC) separation and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) analysis for the profiling, purification and identification of the targeted serum proteins found by SELDI-TOF-MS. By using this workflow, we purified ten targeted proteins from the sera of patients with various types of advanced stage (stage III–IV) cancers. These proteins were identified as isoforms of the human serum amyloid protein A (SAA) family with or without truncations at their N-terminals. This was confirmed by Western blot analysis. Different SAA expression patterns were observed by MALDI-TOF-MS profiling. SAA has long been reported as a biomarker for various cancer types such as lung cancer, ovarian cancer, and breast cancer. However, in this study we found increased SAA expression in the sera of advanced-stage cancer patients with different cancer types. Our results suggest that maybe SAA should not be used alone as a biomarker for any specific cancer type.

Nuclear proteome analysis reveals a role of Vav1 in modulating RNA processing during maturation of tumoral promyelocytes

Vav1 is a key molecule in the ATRA-induced acquisition of a mature phenotype by tumoral myeloid precursors. Since ATRA acts throughout events that require extensive changes of nuclear architecture and activity and considering that Vav1 accumulates inside the nuclear compartment of differentiating APL-derived cells, the possible role of this protein in modulating the nuclear proteome was investigated. Membrane-depleted nuclei purified from NB4 cells induced to differentiate with ATRA in the presence of forcedly down-modulated Vav1 were subjected to 2D-DIGE followed by mass spectra analysis. The obtained data demonstrated that, in NB4 cells treated with ATRA, Vav1 is involved in determining the nuclear amount of proteins involved in molecular complexes with DNA and may participate to RNA processing by carrying in the nucleus molecules involved in modulating mRNA production and stability, like hnRNPs and SR proteins. Our results provide the first evidence that, at least in maturation of tumoral myeloid precursors, Vav1 is part of interconnected networks of functionally related proteins ended to regulate different aspects of gene expression. Since defects in mRNA processing are common in tumor development, our data suggest that Vav1 is a potential target molecule for developing new anti-cancer strategies.

Data mining reveals complex interactions of risk factors and clinical feature profiling associated with the staging of non-hepatitis B virus/non-hepatitis C virus-related hepatocellular carcinoma

AIM

  Non-hepatitis B virus/non-hepatitis C virus-related hepatocellular carcinoma (NBNC-HCC) is often detected at an advanced stage, and the pathology associated with the staging of NBNC-HCC remains unclear. Data mining is a set of statistical techniques which uncovers interactions and meaningful patterns of factors from a large data collection. The aims of this study were to reveal complex interactions of the risk factors and clinical feature profiling associated with the staging of NBNC-HCC using data mining techniques.

METHODS

  A database was created from 663 patients with NBNC-HCC at 20 institutions. The Milan criteria were used as staging of HCC. Complex associations of variables and clinical feature profiling with the Milan criteria were analyzed by graphical modeling and decision tree algorithm methods, respectively.

RESULTS

  Graphical modeling identified six factors independently associated with the Milan criteria: diagnostic year of HCC; diagnosis of liver cirrhosis; serum aspartate aminotransferase (AST); alanine aminotransferase (ALT); α-fetoprotein (AFP); and des-γ-carboxy prothrombin (DCP) levels. The decision trees were created with five variables to classify six groups of patients. Sixty-nine percent of the patients were within the Milan criteria, when patients showed an AFP level of 200 ng/mL or less, diagnosis of liver cirrhosis and an AST level of less than 93 IU/mL. On the other hand, 18% of the patients were within the Milan criteria, when patients showed an AFP level of more than 200 ng/mL and ALT level of 20 IU/mL or more.

CONCLUSION

  Data mining disclosed complex interactions of the risk factors and clinical feature profiling associated with the staging of NBNC-HCC.

Secretome-based identification of ULBP2 as a novel serum marker for pancreatic cancer detection

Background

To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues.

Methods

ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9).

Results

Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls.

Conclusions

Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening.

Reproducibility of SELDI Spectra Across Time and Laboratories

This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.

The reproducibility of mass spectrometry (MS) data collected using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) has been questioned. This investigation was designed to test the reproducibility of SELDI data collected over time by multiple users and instruments. Five laboratories prepared arrays once every week for six weeks. Spectra were collected on separate instruments in the individual laboratories. Additionally, all of the arrays produced each week were rescanned on a single instrument in one laboratory. Lab-to-lab and array-to-array variability in alignment parameters were larger than the variability attributable to running samples during different weeks. The coefficient of variance (CV) in spectrum intensity ranged from 25% at baseline, to 80% in the matrix noise region, to about 50% during the exponential drop from the maximum matrix noise. Before normalization, the median CV of the peak heights was 72% and reduced to about 20% after normalization. Additionally, for the spectra from a common instrument, the CV ranged from 5% at baseline, to 50% in the matrix noise region, to 20% during the drop from the maximum matrix noise. Normalization reduced the variability in peak heights to about 18%. With proper processing methods, SELDI instruments produce spectra containing large numbers of reproducibly located peaks, with consistent heights.

Proteomics in pancreatic cancer research

In this review, we give an overview of the actual role of proteomic technologies in the study of pancreatic cancers (PCs). We describe PC proteomics on the basis of sample origins, i.e. tissues, body fluids, and PC cell lines. As regards PC tissues, we report the identification of a number of candidate biomarkers of precursor lesions that may allow early diagnosis of this neoplasia. Moreover, we describe cytoskeletal and hypoxia-regulated proteins that confirm the involvement of cytoskeleton modifications and metabolism adaptations in carcinogenesis. We also discuss the most important biomarkers identified by proteomic analysis involved in local invasion and distant metastasis, and in the cross-talk between pancreatic tumor and the surrounding stroma. Furthermore, we report novel candidate biomarkers identified in serum, plasma, and pancreatic juice of cancer patients compared with cancer-free controls. Proteomic alterations in PC cell line models as compared to normal controls and studies on cell lines treated with drugs or new agents to understand their mechanism of pharmacological action or the onset of drug resistance are also presented. Finally, we discuss the recent improvements obtained in classical 2-DE and high-throughput proteomic strategies able to allow the overcoming of relevant proteomic drawbacks.

Discovery of serum biomarkers for pancreatic adenocarcinoma using proteomic analysis

Background and aims:

The serum/plasma proteome was explored for biomarkers to improve the diagnostic ability of CA19-9 in pancreatic adenocarcinoma (PC).

Methods:

A Training Set of serum samples from 20 resectable and 18 stage IV PC patients, 54 disease controls (DCs) and 68 healthy volunteers (HVs) were analysed by surface-enhanced laser desorption and ionisation time-of-flight mass spectrometry (SELDI-TOF MS). The resulting protein panel was validated on 40 resectable PC, 21 DC and 19 HV plasma samples (Validation-1 Set) and further by ELISA on 33 resectable PC, 28 DC and 18 HV serum samples (Validation-2 Set). Diagnostic panels were derived using binary logistic regression incorporating internal cross-validation followed by receiver operating characteristic (ROC) analysis.

Results:

A seven-protein panel from the training set PC vs DC and from PC vs HV samples gave the ROC area under the curve (AUC) of 0.90 and 0.90 compared with 0.87 and 0.91 for CA19-9. The AUC was greater (0.97 and 0.99, P<0.05) when CA19-9 was added to the panels and confirmed on the validation-1 samples. A simplified panel of apolipoprotein C-I (ApoC-I), apolipoprotein A-II (ApoA-II) and CA19-9 was tested on the validation-2 set by ELISA, in which the ROC AUC was greater than that of CA19-9 alone for PC vs DC (0.90 vs 0.84) and for PC vs HV (0.96 vs 0.90).

Conclusions:

A simplified diagnostic panel of CA19-9, ApoC-I and ApoA-II improves the diagnostic ability of CA19-9 alone and may have clinical utility.

Serum tumor markers in pancreatic cancer-recent discoveries

The low prevalence of pancreatic cancer remains an obstacle to the development of effective screening tools in an asymptomatic population. However, development of effective serologic markers still offers the potential for improvement of diagnostic capabilities, especially for subpopulations of patients with high risk for pancreatic cancer. The accurate identification of patients with pancreatic cancer and the exclusion of disease in those with benign disorders remain important goals. While clinical experience largely dismissed many candidate markers as useful markers of pancreatic cancer, CA19-9 continues to show promise. The present review highlights the development and the properties of different tumor markers in pancreatic cancer and their impact on the diagnostic and treatment of this aggressive disease.

Comparison of three methods for fractionation and enrichment of low molecular weight proteins for SELDI-TOF-MS differential analysis

In most diseases, the clinical need for serum/plasma markers has never been so crucial, not only for diagnosis, but also for the selection of the most efficient therapies, as well as exclusion of ineffective or toxic treatment. Due to the high sample complexity, prefractionation is essential for exploring the deep proteome and finding specific markers. In this study, three different sample preparation methods (i.e., highly abundant protein precipitation, restricted access materials (RAM) combined with IMAC chromatography and peptide ligand affinity beads) were investigated in order to select the best fractionation step for further differential proteomic experiments focusing on the LMW proteome (MW inferior to 40,000 Da). Indeed, the aim was not to cover the entire plasma/serum proteome, but to enrich potentially interesting tissue leakage proteins. These three methods were evaluated on their reproducibility, on the SELDI-TOF-MS peptide/protein peaks generated after fractionation and on the information supplied. The studied methods appeared to give complementary information and presented good reproducibility (below 20%). Peptide ligand affinity beads were found to provide efficient depletion of HMW proteins and peak enrichment in protein/peptide profiles.