Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS

Circulating HDL and Non-HDL Associated Apolipoproteins and Breast Cancer Severity

Plasma lipids are carried within lipoproteins with various apolipoprotein content. This study evaluates the interest of measuring the apolipoproteins of circulating lipoproteins in breast cancer. Patients with early-stage breast cancer (n = 140) were included. Tumors differed by the expression of estrogen and progesterone receptor (HR- and HR+ for negative and positive expression) and the proliferation marker Ki-67 (≤20% or ≥30%). Apolipoprotein concentrations were determined in plasma, HDL and non-HDL fractions, and results are given in mg/dL, median (25th-75th). Patients did not differ in their plasma and lipoprotein lipid concentrations. HDL apoC-I and non-HDL apoC-II were reduced (1.34 (1.02-1.80) vs. 1.61 (1.32-2.04), p = 0.04; 0.31 (0.18-0.65) vs. 0.63 (0.39-1.02), p = 0.01; respectively), in RH-/high Ki-67 patients in comparison to RH-/low Ki-67 patients, while plasma apoD and HDL apoD were higher (3.24 (2.99-4.16) vs. 3.07 (2.39-3.51), p = 0.04; 2.74 (2.36-3.35) vs. 2.45 (2.01-2.99), p = 0.04; respectively). When RH+/high Ki-67 patients were compared with RH+/low Ki-67 patients, HDL apoC-I and HDL apoC-III were higher (1.56 (1.20-1.95) vs. 1.35 (1.10-1.62), p = 0.02; 2.80 (2.42-3.64) vs. 2.38 (1.69-2.96), p = 0.02; respectively). The distribution of exchangeable apolipoproteins, such as apoC-I, apoC-II, apoC-III, apoD, between lipoproteins is linked to the severity of breast cancer.

Clinical value of serum biomarkers, squamous cell carcinoma antigen and apolipoprotein C-II in follow-up of patients with locally advanced cervical squamous cell carcinoma treated with radiation: A multicenter prospective cohort study

There are currently no reliable, established serum biomarkers to predict the prognosis of radiotherapy for advanced cervical cancer. We aimed to identify serum biomarkers for survival after radiotherapy for cervical cancer. In this multicenter prospective cohort study, the usefulness of pre- and posttreatment serum protein levels of potential biomarkers, including squamous cell carcinoma antigen (SCC-Ag), apolipoprotein C-II (ApoC-II), matrix metalloproteinase (MMP)1, and MMP2, were evaluated together with clinical factors in 145 cervical cancer patients in order to determine their suitability to predict survival. Progression-free survival (PFS) was the primary endpoint, and overall survival (OS), pelvic PFS (PPFS), and distant metastasis-free survival (DMFS) were the secondary endpoints. Blood samples were collected before and 1 month after radiotherapy to measure serum biomarker levels. ApoC-II was measured using a monoclonal antibody-based enzyme-linked immunosorbent assay, which was developed for this purpose. Kaplan-Meier method, log-rank test, and univariate and multivariate Cox proportional hazards models were used for statistical analyses. In multivariate analysis, larger tumor size was independently associated with shorter PFS, OS, PPFS, and DMFS, while longer overall treatment time was independently associated with shorter PPFS. Higher pretreatment SCC-Ag (P < 0.001) was associated with shorter DMFS. Higher posttreatment SCC-Ag (P = 0.017) was also associated with shorter DMFS. Pretreatment ApoC-II was associated with PPFS in univariate analysis (P = 0.048), but not in multivariate analysis. Patients with pretreatment ApoC-II levels ≤ 25.8 μg/ml had shorter PPFS than those with pretreatment ApoC-II levels > 25.8 μg/ml (P = 0.023, log-rank test). Pre- and posttreatment serum SCC-Ag and pretreatment serum ApoC-II levels may be important biomarkers to predict survival outcomes of patients with cervical cancer after radiotherapy. Pre- and posttreatment SCC-Ag and pretreatment ApoC-II might be useful in clinical settings for screening patients to improve treatment strategies in cervical cancer.

Identification of blood protein biomarkers for breast cancer staging by integrative transcriptome and proteome analyses

Breast cancer is the most common malignancy for women. Accurate prediction of breast cancer and its pathological stages is important for treatment decision-making. Although many studies have focused on discovering circulating biomarkers of breast cancer, no such biomarkers have been reported for different stages of this disease. In this study, we identified blood protein biomarkers for each stage of breast cancer by analyzing transcriptome and proteome data from patients. Analysis of the TCGA transcriptome datasets revealed that a large number of genes were differentially expressed in tumor samples of each stage of breast cancer compared with adjacent normal tissues. Blood-secretory proteins encoded by these genes were then predicted by bioinformatics programs. Furthermore, iTRAQ-based proteomic analysis was conducted for plasma samples of breast cancer patients with different stages. A portion of predicted blood-secretory proteins could be detected and verified differentially expressed. Finally, several proteins were chosen as potential blood protein biomarkers for different stages of breast cancer due to their consistent expression patterns at both mRNA and protein levels. Overall, our data provide new insights into diagnosis and classification of breast cancer as well as selection of optimal treatments. SIGNIFICANCE: We identified blood protein biomarkers for each stage of breast cancer by analyzing tissue-based transcriptome and blood-based proteome data from patients. To our knowledge, this is the first time to try to identify blood protein biomarkers for different stages of breast cancer via these integrative analyses. Our data may provide new insights into diagnosis and classification of breast cancer as well as selection of optimal treatment.

Blood-based protein biomarkers in breast cancer

Breast cancer (BCa) is a significant healthcare problem on women worldwide. Thus, early detection is very important to reduce mortality. Furthermore, better BCa prognosis could improve selection of patients eligible for adjuvant therapy. New markers for early diagnosis, accurate prognosis and prediction of response to treatment are necessary to improve BCa care. The present review summarizes important aspects of the potential usefulness of modern technologies, strategies, and scientific findings in proteomic research for discovery of breast cancer-associated blood-based protein biomarkers in the clinic.

Identification of extracellular matrix protein 1 as a potential plasma biomarker of ESCC by proteomic analysis using iTRAQ and 2D-LC-MS/MS

PURPOSE

This study was aimed to conduct a proteomics profiling analysis on plasma obtained from ESCC patients with the goal of identifying appropriate plasma protein biomarkers in the progression of ESCC.

EXPERIMENTAL DESIGN

Plasma from 28 ESCC patients and 28 healthy controls (HC) were analyzed by iTRAQ combined with 2D-LC-MS/MS. ProteinPilot software was used to identify the differentially expressed plasma proteins in ESCC compared to HC. Western blot was performed to verify the expression of selected proteins in 37 independent ESCC patients and 37 HC. Transwell and MTT assays were used to detect the biological function of ECM1 protein in vitro.

RESULTS

Nineteen (four upregulated and fifteen downregulated) proteins were identified as differentially expressed between ESCC and HC (p <0.05). Biological functions of these proteins are involved in cell adhesion, cell apoptosis and metabolic processes, visual perception and immune response. Of these, extracellular matrix 1 (ECM1) and lumican (LUM) were selected further confirmation by Western blot (p <0.05), which were consistent with the iTRAQ results. Furthermore, the migration ability of EC9706 cell line after overexpressing ECM1 was increased significantly (p <0.05). The proliferation ability of HUVEC cell was enhanced when treated with the culture supernatants of EC9706 overexpressed ECM1(p <0.05).

CONCLUSION AND CLINICAL RELEVANCE

This proteome analysis indicate that ECM1 is a potential novel plasma protein biomarker for the detection of primary ESCC and evaluation of neoplasms progression.

Proteomics in pediatric cystic craniopharyngioma

Adamantinomatous craniopharyngioma (ACP) is still often burdened by a poor prognosis in children as far as the risk of recurrence and the quality of life are concerned. Therefore, many efforts are now dedicated to investigate the molecular characteristics of this tumor aiming at finding new therapeutic options. ACP is prevalently a cystic lesion so that an increasing number of researches are focused on the analysis of its cystic content. In the present article, the main results of the current proteomic analysis (PA) on the ACP fluid are summarized. Both "bottom-up" and "top-down" approaches have been utilized. In the bottom-up approach, proteins and peptides are enzymatically or chemically digested prior to liquid chromatography and mass spectrometry analyses. The bottom-up approach pointed out several proteins of the inflammation (namely, α2-HS-glycoprotein, α1-antichymotrypsin and apolipoproteins) as possibly involved in the genesis and growth of the cystic component of ACP. The top-down strategy analyzes proteins and peptides in the intact state, making it particularly suitable for the identification of peptides and low molecular weight proteins and for the characterization of their possible isoforms and post-translational modifications. The top-down approach disclosed the presence of the thymosin β family. Thymosin β4, in particular, which is involved in the cytoskeleton organization and migration of several tumors, could play a role in the progression of ACP. Finally, PA was utilized to investigate alterations in cyst fluid character after treatment with interferon-α. The analyzed samples showed a progressive reduction of the levels of α-defensins (proteins involved in the inflammatory-mediated response) after the intracystic injection of interferon-α, thus reinforcing the hypothesis that inflammation contributes to ACP cyst pathogenesis. Additional studies on the solid component of ACP are still necessary to further validate the previous results and to identify possible markers for targeted therapy.

Proteomic analysis of plasma identifies the Toll-like receptor agonists S100A8/A9 as a novel possible marker for systemic sclerosis phenotype

BACKGROUND

Systemic sclerosis (SSc) is an autoimmune disease characterised by fibrosis of the skin and the internal organs. Except for anticentromere, antitopoisomerase I and antipolymerase III antibodies, there are no reliable circulating markers predicting susceptibility and internal organ complications. This study has exploited a proteome-wide profiling method with the aim to identify new markers to identify SSc phenotype.

METHOD

40 SSc patients were included for proteomic identification. Patients were stratified as having diffuse cutaneous SSc (dcSSc) (n=19) or limited cutaneous SSc (lcSSc) (n=21) according to the extent of skin involvement. As controls 19 healthy donors were included. Blood was drawn and plasma was stored before analysing with the SELDI-TOF-MS. For replication in serum, the cohort was extended with 60 SSc patients.

RESULTS

Proteomic analysis revealed a list of 25 masspeaks that were differentially expressed between SSc patients and healthy controls. One of the peaks was suggestive for S100A8, a masspeak we previously found in supernatant of plasmacytoid dendritic cells from SSc patients. Increased expression of S100A8/A9 in SSc patients was confirmed in replication cohort compared with controls. Intriguingly, S100A8/A9 was highest in patients with limited cutaneous SSc having lung fibrosis.

CONCLUSIONS

S100A8/A9 was robustly found to be elevated in the circulation of SSc patients, suggesting its use as a biomarker for SSc lung disease and the need to further explore the role of TLR in SSc.

Early diagnostic protein biomarkers for breast cancer: how far have we come?

Many studies have used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to search for blood-based proteins that are related to the presence of breast cancer. We review the biomarkers discovered or targeted measured by these methods and discuss the strengths and weaknesses of these studies. We highlight two proteins that were most often related to breast cancer: C3a des-arginine anaphylatoxin (C3adesArg) (molecular weight: 8,938 Da) and fragments of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4). In addition, we elaborate on three important methodological aspects related to these studies: protein identification, specificity of the markers, and disease heterogeneity. Finally, we propose some points to be addressed in future studies. These include the use of other analytical measurement techniques, need of protein identification, the importance of identical sample handling protocols for cases and controls, and the stratification of the results according to molecular subtypes and stages of breast cancer. Ultimately this may lead to the discovery of new and valid breast cancer specific biomarkers.