A serum glycomics approach to breast cancer biomarkers

Because the glycosylation of proteins is known to change in tumor cells during the development of breast cancer, a glycomics approach is used here to find relevant biomarkers of breast cancer. These glycosylation changes are known to correlate with increasing tumor burden and poor prognosis. Current antibody-based immunochemical tests for cancer biomarkers of ovarian (CA125), breast (CA27.29 or CA15-3), pancreatic, gastric, colonic, and carcinoma (CA19-9) target highly glycosylated mucin proteins. However, these tests lack the specificity and sensitivity for use in early detection. This glycomics approach to find glycan biomarkers of breast cancer involves chemically cleaving oligosaccharides (glycans) from glycosylated proteins that are shed or secreted by breast cancer tumor cell lines. The resulting free glycan species are analyzed by MALDI-FT-ICR MS. Further structural analysis of the glycans can be performed in FTMS through the use of tandem mass spectrometry with infrared multiphoton dissociation. Glycan profiles were generated for each cell line and compared. These methods were then used to analyze sera obtained from a mouse model of breast cancer and a small number of serum samples obtained from human patients diagnosed with breast cancer or patients with no known history of breast cancer. In addition to the glycosylation changes detected in mice as mouse mammary tumors developed, glycosylation profiles were found to be sufficiently different to distinguish patients with cancer from those without. Although the small number of patient samples analyzed so far is inadequate to make any legitimate claims at this time, these promising but very preliminary results suggest that glycan profiles may contain distinct glycan biomarkers that may correspond to glycan "signatures of cancer."     

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

Introduction

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

Method

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

Results

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

Conclusions

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.     

Serum metabolomics as a novel diagnostic approach for pancreatic cancer

Pancreatic cancer is one of the leading causes of cancer-related death, and there is currently little hope of a cure because there are no effective biomarkers for its early detection. Therefore, the search for novel biomarkers that would allow the early detection of pancreatic cancer is ongoing. In this study, the differences between the metabolomes of pancreatic cancer patients with Stage III, Stage IVa, or Stage IVb disease (n = 20) and healthy volunteers (n = 9) were evaluated by metabolomics, which is the endpoint of the Omics cascade and therefore the last step in the cascade before the phenotype. In our experimental conditions using gas chromatography mass spectrometry (GC/MS), a total of 60 metabolites were detected in serum, and the levels of 18 of the 60 metabolites were significantly changed in pancreatic cancer patients compared with those in healthy volunteers. Then, Principal Component Analysis (PCA), which is a basic form of Multiple Classification Analysis, was performed, and the PCA scores plots based on the 60 metabolites highlighted the metabolomic differences between the pancreatic cancer patients and healthy volunteers. The differences between different stages of pancreatic cancer were also assessed by Partial Least Squares Discriminant Analysis (PLS-DA), which is one of Multiple Classification Analysis, and we found that it was possible to discriminate among the Stage III, Stage IVa, and Stage IVb groups. In addition, values of the 9 metabolites in 1 Stage I pancreatic cancer patient were similar to those obtained from the Stage III, Stage IVa, and Stage IVb pancreatic cancer patients. Our findings will aid the discovery of novel biomarkers that allow the early detection of pancreatic cancer by metabolomic approaches.     

Cytokeratin19-2g2, a Novel Fragment of Cytokeratin19 in Serum,Indicating a More Invasive Behavior and Worse Prognosis in Breast Cancer Patients

Background

Various studies have been searching for new tumor biomarkers for breast cancer for years. However, so far, few markers have been proved clinically useful except CA153. Based on knowledge that most adenocarcinomas including breast carcinoma expressed Cytokeratin19, the authors studied CK19-2G2,a novel fragment of cytokeratin19 shedding into serum in breast cancer patients.

Patients and Methods

The serum samples of four hundred and seventeen patients including three hundred and three (fifty-four DCIS and two hundred and forty-nine stage I-III) PBC patients and one hundred and fourteen MBC patients, eighty-one healthy controls and twenty-one breast benign disease patients were provided for measurement of CK19-2G2, CEA and CA153.The correlation between clinicopathological characters, prognosis and CK19-2G2 levels was further studied.

Results

The serum CK19-2G2 levels in breast cancer patients were significantly higher than that in healthy and benign controls. For breast cancer patients, CK19-2G2 levels in MBC were significantly higher than that in PBC patients. The sensitivities of CK19-2G2 for breast carcinoma are as high as CEA and CA153, and up to 71% in MBC patients. Serum CK19-2G2 levels (≥2 mU/mL) were associated with pathological stages, tumor size (≥2 cm), lymph node involvement, and HER2 status. Multivariate analysis revealed that high serum CK19-2G2 level was an independent factor for relapse (P = 0.029) and death (P = 0.040) in breast cancer patients.

Conclusion

Serum CK19-2G2 may be an independent indicator for prognosis and a candidate marker for monitoring metastasis in breast cancer.     

肿瘤标志物联合检测在乳腺癌早期诊断中的应用

目的:探讨肿瘤标志物癌胚抗原(CEA)、糖链抗原19-9(CA19-9)、糖链抗原15-3(CA15-3)联合检测在乳腺癌早期诊断中的应用价值。方法:检测87例乳腺癌患者,55例乳腺良性肿瘤患者和35例健康人血清中CEA、CA19-9、CA153等肿瘤标志物的水平及3种标志物不同组合对乳腺癌的阳性检出率。结果:乳腺癌患者3种肿瘤标志物显著高于正常对照组及乳腺良性肿瘤组(P<0.01)。3项标志物不同组合对不同分期乳腺癌检出的敏感性均高于单项标志物。其中CEA+CA199+CA153组合的检出敏感性较其他组合均高,特别是对早期患者检出率明显提高。结论:CEA+CA199+CA153联合检测能提高乳腺癌的早期诊断率。     

A pilot study of circulating miRNAs as potential biomarkers of early stage breast cancer

Background

To date, there are no highly sensitive and specific minimally invasive biomarkers for detection of breast cancer at an early stage. The occurrence of circulating microRNAs (miRNAs) in blood components (including serum and plasma) has been repeatedly observed in cancer patients as well as healthy controls. Because of the significance of miRNA in carcinogenesis, circulating miRNAs in blood may be unique biomarkers for early and minimally invasive diagnosis of human cancers. The objective of this pilot study was to discover a panel of circulating miRNAs as potential novel breast cancer biomarkers.

Methodology/Principal Findings

Using microarray-based expression profiling followed by Real-Time quantitative Polymerase Cycle Reaction (RT-qPCR) validation, we compared the levels of circulating miRNAs in plasma samples from 20 women with early stage breast cancer (10 Caucasian American (CA) and 10 African American (AA)) and 20 matched healthy controls (10 CAs and 10 AAs). Using the significance level of p<0.05 constrained by at least two-fold expression change as selection criteria, we found that 31 miRNAs were differentially expressed in CA study subjects (17 up and 14 down) and 18 miRNAs were differentially expressed in AA study subjects (9 up and 9 down). Interestingly, only 2 differentially expressed miRNAs overlapped between CA and AA study subjects. Using receiver operational curve (ROC) analysis, we show that not only up-regulated but also down-regulated miRNAs can discriminate patients with breast cancer from healthy controls with reasonable sensitivity and specificity. To further explore the potential roles of these circulating miRNAs in breast carcinogenesis, we applied pathway-based bioinformatics exploratory analysis and predicted a number of significantly enriched pathways which are predicted to be regulated by these circulating miRNAs, most of which are involved in critical cell functions, cancer development and progression.

Conclusions

Our observations from this pilot study suggest that the altered levels of circulating miRNAs might have great potential to serve as novel, noninvasive biomarkers for early detection of breast cancer.     

Serum proteomics of lung adenocarcinomas induced by targeted overexpression of c-raf in alveolar epithelium identifies candidate biomarkers

We previously reported a proteome map of lung adenocarcinomas in serine-threonine kinase of the Raf family (c-raf) transgenic mice. We now extend our initial studies to serum proteins at early stage (1 month) and advanced stages of tumorigenesis (12 months). Notably, serum proteins from wild-type and tumor bearing mice were extracted with a lysis buffer containing 5 mol/L urea, 2 mol/L thiourea, 40 mmol/L Tris, 4% CHAPS, 100 mmol/L DTT, 0.5% BioLyte 3-10, separated by 2-DE and studied by image analysis. On average 400 protein spots per gel were excised and analyzed by MALDI-TOF MS. We identified 45 common and 5 uniquely expressed proteins in wild-type and tumor bearing mice. Apart from uniquely identified proteins we observed for n = 9 proteins differential expression when wild-type and tumor bearing mice were compared. This included serpins and other protease inhibitors, lipocalins, transthyretins, globins, and Igs. Notably, we demonstrate significant regulation of alpha-1-antitrypsin, alpha-2-macroglobulin, hemoglobin subunit alpha, vitamin D-binding protein, major urinary proteins, and transthyretin (up to eight-fold) in serum of lung tumor bearing mice. Disease association of these proteins in human malignancies has been reported. Thus, an identification of regulated serum proteins in this lung cancer disease model provides excellent opportunities for the search of novel biomarkers.     

Identification and Confirmation of Differentially Expressed Fucosylated Glycoproteins in the Serum of Ovarian Cancer Patients Using a Lectin Array and LC-MS/MS

In order to discover potential glycoprotein biomarkers in ovarian cancer, we applied a lectin array and Exactag labeling based quantitative glycoproteomics approach. A lectin array strategy was used to detect overall lectin-specific glycosylation changes in serum proteins from patients with ovarian cancer and those with benign conditions. Lectins, which showed significant differential response for fucosylation, were used to extract glycoproteins that had been labeled using isobaric chemical tags. The glycoproteins were then identified and quantified by LC-MS/MS, and five glycoproteins were found to be differentially expressed in the serum of ovarian cancer patients compared to benign diseases. The differentially expressed glycoproteins were further confirmed by lectin-ELISA and ELISA assay. Corticosteroid-binding globulin (CBG), serum amyloid p component (SAP), complement factor B (CFAB), and histidine-rich glycoprotein (HRG) were identified as potential markers for differentiating ovarian cancer from benign diseases or healthy controls. A combination of CBG and HRG (AUC = 0.825) showed comparable performance to CA125 (AUC = 0.829) in differentiating early stage ovarian cancer from healthy controls. The combination of CBG, SAP, and CA125 showed improved performance for distinguishing stage III ovarian cancer from benign diseases compared to CA125 alone. The ability of CBG, SAP, HRG, and CFAB to differentiate the serum of ovarian cancer patients from that of controls was tested using an independent set of samples. Our findings suggest that glycoprotein modifications may be a means to identify novel diagnostic markers for detection of ovarian cancer.     

A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

     

AGR3 in Breast Cancer: Prognostic Impact and Suitable Serum-Based Biomarker for Early Cancer Detection

Blood-based early detection of breast cancer has recently gained novel momentum, as liquid biopsy diagnostics is a fast emerging field. In this study, we aimed to identify secreted proteins which are up-regulated both in tumour tissue and serum samples of breast cancer patients compared to normal tissue and sera. Based on two independent tissue cohorts (n = 75 and n = 229) and one serum cohort (n = 80) of human breast cancer and healthy serum samples, we characterised AGR3 as a novel potential biomarker both for breast cancer prognosis and early breast cancer detection from blood. AGR3 expression in breast tumours is significantly associated with oestrogen receptor α (P<0.001) and lower tumour grade (P<0.01). Interestingly, AGR3 protein expression correlates with unfavourable outcome in low (G1) and intermediate (G2) grade breast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, P<0.05) indicating an independent prognostic impact. In sera analysed by ELISA technique, AGR3 protein concentration was significantly (P<0.001) elevated in samples from breast cancer patients (n = 40, mainly low stage tumours) compared to healthy controls (n = 40). To develop a suitable biomarker panel for early breast cancer detection, we measured AGR2 protein in human serum samples in parallel. The combined AGR3/AGR2 biomarker panel achieved a sensitivity of 64.5% and a specificity of 89.5% as shown by receiver operating characteristic (ROC) curve statistics. Thus our data clearly show the potential usability of AGR3 and AGR2 as biomarkers for blood-based early detection of human breast cancer.     

Proteomics analysis of human serum of patients with non-small-cell lung cancer reveals proteins as diagnostic biomarker candidates

Non-small-cell lung carcinomas (NSCLC) is the most common type of lung cancer and it has a poor prognosis, because overall survival after 5 years is 20–25% for all stages. Thus, it is extremely important to increase the survival rate in the early stages NSCLC by focusing on novel screening tests of cancer identifying specific biomarkers expression associated with a more accurate tumor staging and patient prognosis. In this study, we focused our attention on quantitative proteomics of three heavily glycosylated serum proteins: AMBP, α2 macroglobulin, and SERPINA1. In particular, we analyzed serum samples from 20 NSCLC lung adenocarcinoma cancer patients in early and advanced stages, and 10 healthy donors to obtain a relative quantification through the MRM analysis of these proteins that have shown to be markers of cancer development and progression. AMBP, α2 macroglobulin, and SERPINA1 were chosen because all of them possess endopeptidase inhibitor activity and play key roles in cancer. We observe a variation in the expression of these proteins linked to the stage of the disease. Therefore, we believe that proteins like α2 macroglobulin, αmicroglobulin/bikunin, and SERPINA1 could be useful biomarkers for early detection of lung cancer and in monitoring its evolution.     

肿瘤标志物联合检测在乳腺癌早期诊断中的应用

目的：探讨肿瘤标志物癌胚抗原（CEA）、糖链抗原19-9（CA19-9）、糖链抗原15-3（CA15-3）联合检测在乳腺癌早期诊断中的应用价值。方法：检测87例乳腺癌患者,55例乳腺良性肿瘤患者和35例健康人血清中CEA、CA19-9、CA153等肿瘤标志物的水平及3种标志物不同组合对乳腺癌的阳性检出率。结果：乳腺癌患者3种肿瘤标志物显著高于正常对照组及乳腺良性肿瘤组（P〈0.01）。3项标志物不同组合对不同分期乳腺癌检出的敏感性均高于单项标志物。其中CEA＋CA199＋CA153组合的检出敏感性较其他组合均高,特别是对早期患者检出率明显提高。结论：CEA＋CA199＋CA153联合检测能提高乳腺癌的早期诊断率。     

Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer

Cancer patients spontaneously generate autoantibodies (AAb) to tumor-derived proteins. To detect AAb, we have probed novel high-density custom protein microarrays (NAPPA) expressing 4988 candidate tumor antigens with sera from patients with early stage breast cancer (IBC), and bound IgG was measured. We used a three-phase serial screening approach. First, a prescreen was performed to eliminate uninformative antigens. Sera from stage I-III IBC (n = 53) and healthy women (n = 53) were screened for AAb to all 4988 protein antigens. Antigens were selected if the 95th percentile of signal of cases and controls were significantly different (p < 0.05) and if the number of cases with signals above the 95th percentile of controls was significant (p < 0.05). These 761 antigens were screened using an independent set of IBC sera (n = 51) and sera from women with benign breast disease (BBD) (n = 39). From these, 119 antigens had a partial area under the ROC curve (p < 0.05), with sensitivities ranging from 9-40% at >91% specificity. Twenty-eight of these antigens were confirmed using an independent serum cohort (n = 51 cases/38 controls, p < 0.05). Using all 28 AAb, a classifier was identified with a sensitivity of 80.8% and a specificity of 61.6% (AUC = 0.756). These are potential biomarkers for the early detection of breast cancer.     

A proton nuclear magnetic resonance metabonomics approach for biomarker discovery in nonalcoholic fatty liver disease

This study was undertaken to discover novel biomarkers for the noninvasive early diagnosis of nonalcoholic fatty liver disease (NAFLD). A methionine and choline deficient (MCD) diet was used to represent different stages of NAFLD in male C57BL/6 mice. (1)H NMR spectroscopy and principal components analysis (PCA) were used to investigate the time-related biochemical changes in mice sera induced by the MCD diet. Many serum metabolites' concentrations changed between control and MCD-fed mice. Hierarchical cluster analysis (HCA) and artificial neural networks (ANNs) were used to select the least number of metabolites to be used for the noninvasive diagnosis of various stages of NAFLD; four potential biomarkers, serum glucose, lactate, glutamate/glutamine, and taurine were selected. To verify the diagnostic accuracy of these selected metabolites, their serum concentrations were measured in healthy controls (n = 28), NAFLD patients with steatosis (n = 15), steatosis patients with necro-inflammatory disease (n = 11), and NASH patients (n = 6). On the basis of results from MCD-fed mice model, clinical tests, and previous reports, we propose using the levels of the four metabolites for diagnosing NAFLD at various stages. Furthermore, the probability of developing NAFLD at a particular stage was assessed by multinomial logistic regression (MLR) based on the clinical results of the four serum metabolites.     

Transforming growth factor beta 1 serum levels in patients with preinvasive and invasive lesions of the breast

Transforming growth factor beta (TGF-beta)1 is thought to be involved in breast carcinogenesis. TGF-beta1 acts in an antiproliferative manner in the early stages of breast carcinogenesis, but promotes tumor progression and metastases in the advanced stages of the disease. No data have been published on serum TGF-beta1 in breast cancer. We investigated TGF-beta1 serum levels in patients with breast cancer (n=135), ductal carcinoma in situ (DCIS) I to III (n=67) or fibroadenoma (n=35), and in healthy women (n=40) to determine its value as a differentiation marker between malignant, pre-invasive and benign diseases and as a predictive marker for metastatic spread. Median (range) TGF-beta1 serum levels in patients with breast cancer, DCIS I-III or benign breast lesions and in healthy women were 48.8 (18-82.4) pg/mL, 45.3 (26.9-58.3) pg/mL, 47.2 (17.2-80.5) pg/mL and 51.6 (30.9-65.1) pg/mL, respectively (p=0.2). In breast cancer patients TGF-beta1 serum levels showed no statistically significant correlation with tumor stage, lymph node involvement, histological grade, estrogen receptor status and progesterone receptor status. Our data fail to indicate any correlation between serum TGF-beta1 levels and clinicopathological parameters of breast diseases. Serum TGF-beta1 levels do not provide clinical information in addition to established tumor markers.     

Definitive Characterization of CA 19-9 in Resectable Pancreatic Cancer Using a Reference Set of Serum and Plasma Specimens

The validation of candidate biomarkers often is hampered by the lack of a reliable means of assessing and comparing performance. We present here a reference set of serum and plasma samples to facilitate the validation of biomarkers for resectable pancreatic cancer. The reference set includes a large cohort of stage I-II pancreatic cancer patients, recruited from 5 different institutions, and relevant control groups. We characterized the performance of the current best serological biomarker for pancreatic cancer, CA 19–9, using plasma samples from the reference set to provide a benchmark for future biomarker studies and to further our knowledge of CA 19–9 in early-stage pancreatic cancer and the control groups. CA 19–9 distinguished pancreatic cancers from the healthy and chronic pancreatitis groups with an average sensitivity and specificity of 70–74%, similar to previous studies using all stages of pancreatic cancer. Chronic pancreatitis patients did not show CA 19–9 elevations, but patients with benign biliary obstruction had elevations nearly as high as the cancer patients. We gained additional information about the biomarker by comparing two distinct assays. The two CA 9–9 assays agreed well in overall performance but diverged in measurements of individual samples, potentially due to subtle differences in antibody specificity as revealed by glycan array analysis. Thus, the reference set promises be a valuable resource for biomarker validation and comparison, and the CA 19–9 data presented here will be useful for benchmarking and for exploring relationships to CA 19–9.     

Crucial considerations for pipelines to validate circulating biomarkers for breast cancer

Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.     

乳腺癌改良根治术患者术后复发转移的危险因素及血清CA125、COX-2、sTNFR-P55的预测价值研究

摘要 目的：探讨乳腺癌改良根治术患者术后复发转移的危险因素及血清糖类抗原125（CA125）、环加氧酶-2（COX-2）、可溶性肿瘤坏死因子受体P55（sTNFR-P55）的预测价值。方法：对2014年1月至2016年12月新疆医科大学第一附属医院收治的109例行乳腺癌改良根治术的乳腺癌患者进行前瞻性研究,所有患者术后均随访5年,其中2例失访,107例完成随访。根据5年内患者复发转移情况将其分为复发转移组（n=31）和未复发转移组（n=76）。收集患者入院时的临床病理资料,采用电化学发光法检测术前血清CA125,采用酶联免疫吸附法检测术前血清COX-2、sTNFR-P55。采用logistic回归模型分析患者术后复发转移的影响因素,绘制受试者工作特征（ROC）曲线评估血清CA125、COX-2、sTNFR-P55对术后复发转移的预测价值。结果：复发转移组肿瘤直径＞5 cm、浸润性非特殊癌、脉管癌栓、雌激素受体（ER）/孕激素受体（PR）阴性、无内分泌治疗构成比、TNM分期IIIA期、腋窝淋巴结转移数量4~9个构成比高于未复发转移组（P<0.05）。复发转移组血清CA125、COX-2、sTNFR-P55水平高于未复发转移组（P<0.05）。多因素logistic回归分析结果显示,肿瘤直径＞5 cm、浸润性非特殊癌、TNM分期IIIA期、脉管癌栓、腋窝淋巴结转移数量4~9个、CA125升高、COX-2升高、sTNFR-P55升高是乳腺癌改良根治术患者术后5年内复发转移的独立危险因素（OR=1.318、1.213、1.223、1.137、1.257、1.241、1.313、1.351,P<0.05）。血清CA125、COX-2、sTNFR-P55均可有效预测乳腺癌术后复发转移,曲线下面积（AUC）分别为0.803、0.749、0.761,三指标联合预测术后复发转移的AUC为0.915,灵敏度和特异度分别为0.94、0.83。结论：肿瘤直径、浸润性非特殊癌、TNM分期、脉管癌栓、腋窝淋巴结转移数量以及术前血清CA125、COX-2、sTNFR-P55异常升高是乳腺癌改良根治术患者术后5年内复发转移的危险因素,术前血清CA125、COX-2、sTNFR-P55联合检测可预测乳腺癌改良根治术后的复发转移风险。     

Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets

A "bottom-up" proteomics approach and a two-dimensional (strong cation exchange followed by reversed-phase) LC-MS/MS strategy on a linear ion trap (LTQ) were utilized to identify and compare expressions of extracellular and membrane-bound proteins in the conditioned media of three breast cell lines (MCF-10A, BT474, and MDA-MB-468). Proteomics analysis of the media identified in excess of 600, 500, and 700 proteins in MCF-10A, BT474, and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6, and 10 (ranging in concentration from 2 to 50 microg/liter) in MDA-MB-468 conditioned medium as validated by ELISA and confidently identified Her-2/neu in BT474 cells. Subcellular localization was determined based on Genome Ontology terms for all the 1,139 proteins of which 34% were classified as extracellular and membrane-bound. Proteomics analysis of MDA-MB-468 cell lysate demonstrated that only 5% of all identified proteins were extracellular. This confirmed our hypothesis that examining the CM of cell lines, as opposed to the cell lysates, leads to a significant enrichment in secreted proteins. Tissue specificity, functional classifications, and spectral counting were performed. Elafin, a protease inhibitor, identified in the conditioned media of BT474 and MDA-MB-468 and the three kallikreins (KLK5, KLK6, and KLK10) were validated using an immunoassay on various serum and biological samples. Some of the secreted proteins identified have established roles in breast cancer development (cell growth, differentiation, and metastasis) and/or are linked to early onset breast cancer. Our approach to mining for low abundance molecules could identify proteins in various stages of breast cancer development. Many of the identified proteins are potentially useful to investigate as circulating serum breast cancer biomarkers.     

Development of multiplexed bead-based immunoassays for the detection of early stage ovarian cancer using a combination of serum biomarkers

CA125 as a biomarker of ovarian cancer is ineffective for the general population. The aim of this study was to evaluate multiplexed bead-based immunoassay of multiple ovarian cancer-associated biomarkers such as transthyretin and apolipoprotein A1, together with CA125, to improve the identification and evaluation of prognosis of ovarian cancer. We measured the serum levels of CA125, transthyretin, and apolipoprotein A1 from the serum of 61 healthy individuals, 84 patients with benign ovarian disease, and 118 patients with ovarian cancer using a multiplex liquid assay system, Luminex 100. The results were then analyzed according to healthy and/or benign versus ovarian cancer subjects. When CA125 was combined with the other biomarkers, the overall sensitivity and specificity were significantly improved in the ROC curve, which showed 95% and 97% sensitivity and specificity, respectively. At 95% specificity for all stages the sensitivity increased to 95.5% compared to 67% for CA125 alone. For stage I+II, the sensitivity increased from 30% for CA125 alone to 93.9%. For stage III+IV, the corresponding values were 96.5% and 91.6%, respectively. Also, the three biomarkers were sufficient for maximum separation between noncancer (healthy plus benign group) and stage I+II or all stages (I-IV) of disease. The new combination of transthyretin, and apolipoprotein A1 with CA125 improved both the sensitivity and the specificity of ovarian cancer diagnosis compared with those of individual biomarkers. These findings suggest the benefit of the combination of these markers for the diagnosis of ovarian cancer.