Comprehensive profiles and diagnostic value of menopausal-specific gut microbiota in premenopausal breast cancer

In Western countries, breast cancer tends to occur in older postmenopausal women. However, in Asian countries, the proportion of younger premenopausal breast cancer patients is increasing. Increasing evidence suggests that the gut microbiota plays a critical role in breast cancer. However, studies on the gut microbiota in the context of breast cancer have mainly focused on postmenopausal breast cancer. Little is known about the gut microbiota in the context of premenopausal breast cancer. This study aimed to comprehensively explore the gut microbial profiles, diagnostic value, and functional pathways in premenopausal breast cancer patients. Here, we analyzed 267 breast cancer patients with different menopausal statuses and age-matched female controls. The α-diversity was significantly reduced in premenopausal breast cancer patients, and the β-diversity differed significantly between breast cancer patients and controls. By performing multiple analyses and classification, 14 microbial markers were identified in the different menopausal statuses of breast cancer. Bacteroides fragilis was specifically found in young women of premenopausal statuses and Klebsiella pneumoniae in older women of postmenopausal statuses. In addition, menopausal-specific microbial markers could exhibit excellent discriminatory ability in distinguishing breast cancer patients from controls. Finally, the functional pathways differed between breast cancer patients and controls. Our findings provide the first evidence that the gut microbiota in premenopausal breast cancer patients differs from that in postmenopausal breast cancer patients and shed light on menopausal-specific microbial markers for diagnosis and investigation, ultimately providing a noninvasive approach for breast cancer detection and a novel strategy for preventing premenopausal breast cancer.Subject terms: Bacterial genetics, Breast cancer     

Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition

The proteins of extracellular vesicles (EVs) that originate from tumors reflect the producer cells’ proteomes and can be detected in biological fluids. Thus, EVs provide proteomic signatures that are of great interest for screening and predictive cancer diagnostics. By applying targeted mass spectrometry with stable isotope-labeled peptide standards, we assessed the levels of 28 EV-associated proteins, including the conventional exosome markers CD9, CD63, CD81, CD82, and HSPA8, in vesicles derived from the lung cancer cell lines NCI-H23 and A549. Furthermore, we evaluated the detectability of these proteins and their abundance in plasma samples from 34 lung cancer patients and 23 healthy volunteers. The abundance of TLN1, TUBA4A, HSPA8, ITGB3, TSG101, and PACSIN2 in the plasma of lung cancer patients was measured using targeted mass spectrometry and compared to that in plasma from healthy volunteers. The most diagnostically potent markers were TLN1 (AUC, 0.95), TUBA4A (AUC, 0.91), and HSPA8 (AUC, 0.88). The obtained EV proteomic signature allowed us to distinguish between the lung adenocarcinoma and squamous cell carcinoma histological types. The proteomic cargo of the extracellular vesicles represents a promising source of potential biomarkers.     

Metabolomic investigation of gastric cancer tissue using gas chromatography/mass spectrometry

Gastric cancer screening or diagnosis is mainly based on endoscopy and biopsy. The aim of this study was to identify the difference of metabolomic profile between normal and malignant gastric tissue, and to further explore tumor biomarkers. Chemical derivatization together with gas chromatography/mass spectrometry (GC/MS) was utilized to obtain the metabolomic information of the malignant and non-malignant tissues of gastric mucosae in 18 gastric cancer patients. Acquired metabolomic data was analyzed using the Wilcoxon rank sum test to find the tissue metabolic biomarkers for gastric cancer. A diagnostic model for gastric cancer was constructed using principal component analysis (PCA), and was assessed with receiver-operating characteristic (ROC) curves. Results showed that 18 metabolites were detected differently between the malignant tissues and the adjacent non-malignant tissues of gastric mucosa. Five metabolites were also detected differently between the non-invasive tumors and the invasive tumors. The diagnostic model could discriminate tumors from normal mucosae with an area under the curve (AUC) value of 0.9629, and another diagnostic model constructed for clinical staging was assessed with an AUC value of 0.969. We conclude that the metabolomic profile of malignant gastric tissue was different from normal, and that the selected tissue metabolites could probably be applied for clinical diagnosis or staging for gastric cancer.     

Plasmonic Gold Chip for Multiplexed Detection of Ovarian Cancer Biomarker in Urine

Human epididymal protein 4(HE4), carbohydrate antigen 125 (CA125) and osteopontin(OPN) are three key biomarkers in detecting ovarian cancer. To explore the diagnosis value of combined detection of these three biomarkers for ovarian cancer, we developed a multiplexed assay on a plasmonic gold(pGOLD) platform for measuring HE4, CA125 and OPN in urine. The receiver operator characteristic(ROC) curve was drawn, and the diagnosis values of each biomarker alone or in combination for ovarian cancer were evaluated. In the analysis to distinguish ovarian cancer from other gynecological cancers, ovarian cysts and healthy people, the sensitivities of HE4, CA125 and OPN were 72.55%, 52.82% and 68.63%, the specificity values were 95.06%, 87.65% and 90.12%, while the areas under the curve(AUC) were 0.85, 0.75 and 0.77, respectively. The sensitivity and specificity for combination detection of the three markers were 90.20% and 80.25%. The detection methods of HE4, CA125 and OPN based on plasma fluorescence enhanced chip showed good analytic and diagnostic performance, and provided a non-invasive method for the diagnosis of ovarian cancer.     

基于气相色谱-质谱联用和图模型分析的脂代谢异常患者血浆代谢组学研究

利用气相色谱-质谱联用技术(GC-MS)和图模型分析方法,寻找脂代谢异常患者可能的血浆代谢标志物群。采用GC-MS技术对37例脂代谢异常患者和10例健康人的血浆样品进行分析,得到血浆代谢物的表达谱。偏最小二乘-判别分析(Partial least squares-discriminant analysis,PLS-DA)得分图可区分脂代谢异常患者与健康人,运用PLS-DA载荷图及t检验发现有9个代谢物在两组间存在显著性差异。经NIST谱库检索,它们分别为缬氨酸、甘氨酸、丙氨酸、焦谷氨酸、葡萄糖醛酸、半乳糖、甘露糖、亚油酸和甘油。在脂代谢异常患者血浆中,除甘油浓度显著高于健康人外,其余8种代谢物浓度均明显低于健康人。图模型分析结果发现这些代谢物与脂代谢异常临床常用诊断指标之间具有很好的相关性。它们可能是脂代谢异常疾病早期诊断和预后新的特异性代谢标志物群。     

Lysophosphatidylcholine Biomarkers of Lung Cancer Detected by Ultra-performance Liquid Chromatography Coupled with Quadrupole Time-of-flight Mass Spectrometry

Centrifugal ultrafiltration after methanol extraction of whole plasma was used as an optimal condition for the preparation of blood plasma before metabonomic studies. The plasma samples from 102 lung cancer patients and 34 healthy volunteers were prepared with this approach. With ultra-performance liquid chromatography(UPLC) coupled with quadrupole time-of-flight mass spectrometry(Q-TOF MS) analysis, the samples were investigated in order to find potential disease biomarkers. After data acquisition, orthogonal signal correction partial least squares models were built to differentiate the healthy volunteers from lung cancer patients and to identify metabolites that showed significantly different expression between the two groups. Several metabolite ions were identified as potential biomarkers according to the variable importance in the project(VIP) value in both ion modes. Five lysophosphatidylcholines were further identified as specifically lysoPC 16:0, isomer of lysoPC 16:0, lysoPC 18:0, lysoPC 18:1 and lysoPC 18:2. These results suggest that UPLC coupled with Q-TOF MS is an effective technique for the analysis of plasma metabolites in metabonomic studies.     

Alpha 1-antitrypsin: a novel tumor-associated antigen identified in patients with early-stage breast cancer

Several studies have demonstrated that sera from patients with cancer contain antibodies that recognize a unique group of autologous antigens called tumor-associated antigens (TAA). In the current study, we employed an immunoproteomic approach, combining 2DE, Western blot, and MALDI-MS to identify TAA in the sera of patients diagnosed with infiltrating ductal or in situ carcinoma breast cancer. Sera obtained from 25 newly diagnosed patients with stage II breast cancer and 20 healthy volunteers was evaluated for the presence of novel TAA. Alpha 1-antitrypsin (A1AT) antibodies were detected in 24 of 25 patients with breast cancer (96%) and in 2 of 20 controls (10%). Sensitivity of detection of autoantibodies against A1AT in patients with breast cancer was 96%. Our preliminary results suggest that A1AT and autoantibodies against alpha 1 antitrypsin may be useful serum biomarkers for early-stage breast cancer screening and diagnosis.     

Influence of oxidative injury and monitoring of blood plasma by DSC on breast cancer patients

Damage caused by oxidative stress is involved in many types of diseases, including breast cancer. Our aim was to detect the oxidative stress parameters and blood plasma changes with differential scanning calorimetry (DSC) in breast cancer patients. The study included 40 adult breast cancer women who were grouped according to tumor diameter, regional lymph node metastases, proliferative activity, receptor status and postoperative chemotherapy. To monitor oxidative stress, malondialdehyde, oxygen free radicals (OFRs), activity of myeloperoxidase (MPO), superoxide dismutase (SOD) and catalase (CAT) were measured. Denaturation of plasma components was detected in Setaram Micro DSC-II calorimeter. The total production of OFRs, the MPO activity and lipidperoxidation were significantly increased in each breast cancer patients considering the tumor size, the metastatic lymph nodes, the proliferation activity and receptor status compared with healthy controls (p < 0.05). These pro-oxidants were slightly elevated without chemotherapy, but their values were increased significantly in chemotherapy-receiving group. The activity of SOD and CAT was significantly decreased in all groups, and in regard to the chemotherapy, they were changed significantly parallel to the severity of disease. Regarding to both the increased tumor diameter and the increased number of affected lymph nodes, DSC measurements showed a strong relationship between the maximum excess heat capacity (C_pmax) of the blood plasma and the severity of disease. The study demonstrated that oxidative stress is implicated in breast carcinoma and chemotherapy aggravates these changes which confirmed the plasma DSC measurements also.     

Vitamin D receptor gene polymorphisms in breast cancer

Breast cancer is the leading cause of cancer death among women around the world and its incidence is annually increasing. The vitamin D receptor (VDR) gene is a member of the nuclear receptor superfamily, which is expressed in breast tissue and known to modulate the rate of cell proliferation. Association between the VDR gene polymorphisms and cancer development has been suggested by several studies. However, the relationship between VDR polymorphisms and breast cancer is controversial and has not been confirmed by all studies. The purpose of this study was to investigate the genotype frequencies and association of the VDR Bsm I and Taq I polymorphisms with breast cancer in Turkish patients. In this study, 78 patients with breast cancer and 27 healthy individuals were enrolled. The prevalence of the VDR Taq I and Bsm I alleles and the genotype frequencies in patients with breast cancer was similar to that in the normal population. Our data indicate that no significant differences exist between the patients and control subjects.     

In silico study of cancer stage-specific DNA methylation pattern in White breast cancer patients based on TCGA dataset

BackgroundBreast cancer is one of the most common types of cancer among women. As current breast cancer treatments are still ineffective, we assess the methylation pattern of White breast cancer patients across cancer stage based on The Cancer Genome Atlas (TCGA) dataset. Significant hypermethylation and hypomethylation can regulate the gene expression, thus becoming potential biomarkers in breast cancer tumorigenesis.MethodsDNA methylation data was downloaded using TCGA Assembler 2 based on race-specific metadata of TCGA - Breast Invasive Carcinoma (TCGA-BRCA) project from Genomic Data Commons (GDC) Data Portal. After the data was divided into each cancer stage, duplicated data of each patient was removed using OMICSBind, while differentially-expressed probes were identified using edgeR. The resulting probes were validated based on correlation and regression analysis with the gene expression, ANOVA between cancer stages, ROC curve per stage, as well as databases.ResultsBased on the White dataset, we found 66 significant hypermethylated genes with logFC > 1.8 between Stage I-III. From this number, three epigenetic-regulated, stage-specific genes are proposed to be the detection biomarkers of breast cancer due to significant aberrant gene expression and/or low mutation ratio among breast cancer patients: ABCC9 (Stage III), SHISA3 (Stage II), and POU4F1 (Stage I-II).ConclusionsOur study shows that ABCC9, SHISA3, and POU4F1 are potential stage-specific detection biomarkers of breast cancer for White individuals, whereas their roles in other races need to be studied further.     

Reversed phase UHPLC/ESI-MS determination of oxylipins in human plasma: a case study of female breast cancer

The ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC/MS) method was optimized and validated for the determination of oxylipins in human plasma using the targeted approach with selected reaction monitoring (SRM) in the negative-ion electrospray ionization (ESI) mode. Reversed phase UHPLC separation on an octadecylsilica column enabled the analysis of 63 oxylipins including numerous isomeric species within 12-min run time. The method was validated (calibration curve, linearity, limit of detection, limit of quantification, carry-over, precision, accuracy, recovery rate, and matrix effect) and applied to 40 human female plasma samples from breast cancer patients and age-matched healthy volunteers (control). Thirty-six oxylipins were detected in human plasma with concentrations above the limit of detection, and 21 of them were quantified with concentrations above the limit of quantitation. The concentrations determined in healthy controls are in a good agreement with previously reported data on human plasma. Quantitative data were statistically evaluated by multivariate data analysis (MDA) methods including principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA). S-plot and box plots showed that 13-HODE, 9-HODE, 13-HOTrE, 9-HOTrE, and 12-HHTrE were the most upregulated oxylipin species in plasma of breast cancer patients.

     

超声参数联合血清OPN、IL-1β对乳腺癌的临床诊断价值研究

选取我院收治的乳腺癌(BC)患者82例设为研究组,同期乳腺良性肿瘤患者82例设为对照组,探讨了超声参数联合血清骨桥蛋白(OPN)、白细胞介素-1β(IL-1β)对BC的诊断价值.结果显示,研究组患者病灶处的RI值、PI值和血清OPN、IL-1β水平均高于对照组(P＜0.05);PI值、RI值、血清OPN、IL-1β水平...     

A Magnetically Driven Tandem Chip Enables Rapid Isolation and Multiplexed Profiling of Extracellular Vesicles

The protein phenotypes of extracellular vesicles (EVs) have emerged as promising biomarkers for cancer diagnosis and treatment monitoring. However, the technical challenges in rapid isolation and multiplexed molecular detection of EVs have limited their clinical practice. Herein, we developed a magnetically driven tandem chip to achieve streamlined rapid isolation and multiplexed profiling of surface protein biomarkers of EVs. Driven by magnetic force, the magnetic nanomixers not only act as tiny stir bars to promote mass transfer and enhance reaction efficiency of EVs, but also transport on communicating vessels of the tandem chip continuously and expedite the assay workflow. We designed cyclic surface enhancement of Raman scattering (SERS) tags to bind with target EVs and then release them by exonuclease I, eliminating steric hindrance and amplifying the SERS signal of multiple protein biomarkers on EVs. Due to the excellent assay performance, six breast cancer biomarkers were detected simultaneously on EVs using only 10 μL plasma within 1.5 h. The unweighted SUM signature offers great accuracy in discriminating breast cancer patients from healthy donors. Overall, the dynamic magnetic driving tandem chip offers a new avenue to advance the clinical application of EV-based liquid biopsy.     

Proteomics analysis of human breast milk by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) coupled with mass spectrometry to assess breast cancer risk

Breast cancer (BC) is one of the most common cancers and one of the most common causes for cancer-related mortality. Discovery of protein biomarkers associated with cancer is considered important for early diagnosis and prediction of the cancer risk. Protein biomarkers could be investigated by large-scale protein investigation or proteomics, using mass spectrometry (MS)-based techniques. Our group applies MS-based proteomics to study the protein pattern in human breast milk from women with BC and controls and investigates the alterations and dysregulations of breast milk proteins in comparison pairs of BC versus control. These dysregulated proteins might be considered potential future biomarkers of BC. Identification of potential biomarkers in breast milk may benefit young women without BC, but who could collect the milk for future assessment of BC risk. Previously we identified several dysregulated proteins in different sets of human breast milk samples from BC patients and controls using gel-based protein separation coupled with MS. Here, we performed 2D-PAGE coupled with nano-liquid chromatography–tandem MS (nanoLC-MS/MS) in a small-scale study on a set of six human breast milk pairs (three BC samples vs. three controls) and we identified several dysregulated proteins that have potential roles in cancer progression and might be considered potential BC biomarkers in the future.     

A proteomic approach to investigate potential biomarkers directed against membrane-associated breast cancer proteins

The identification of specific protein markers for breast cancer would provide the basis for early diagnosis. Particularly, membrane and membrane-associated proteins are rich in targets for antibodies that may constitute suitable biomarkers of carcinogenesis. However, membrane proteins separation using 2-DE remains difficult. In this work, the breast cancer cell line MCF7 was used as source of proteins for the screening of potential cell membrane-associated antigens recognized by autoantibodies in patients with breast cancer and healthy volunteers. The protein extract obtained using trifluoroethanol (TFE) as cosolvent was compared to a total cell lysate protein extract prepared by a current technique. After 2-DE separation of the two extracts, their protein patterns clearly differed. About 63% of the proteins identified in the TFE-extract were predicted to possess at least one transmembrane domain. 2-D blots probed with sera from cancer patients or from healthy volunteers showed that, as expected, additional antigens were provided in the TFE-extract. Thus, the method described here appeared well suited for proteomic investigation of potential biomarkers undetected by current techniques.     

Methylenetetrahydrofolate reductase polymorphism, diet, and breast cancer in Korean women

To evaluate the interactive effect of methylenetetrahydrofolate reductase (MTHFR) genotype and dietary factors on the development of breast cancer, a hospital based case-control study was conducted in South Korean study population consisting of 189 histologically confirmed incident breast cancer cases and their 189 age-matched controls without present or previous history of cancer. A PCR-RFLP method was used for the genotyping of MTHFR (C677T) and statistical evaluations were performed by unconditional logistic regression analysis. Consumption of some dietary factors, such as green vegetables (OR = 0.3, 95% CI: 0.2-0.6), white vegetables (OR = 0.3, 95% CI: 0.1-0.7) mushrooms (OR = 0.4, 95% CI: 0.3-0.7), and meats (OR = 1.7, 95% CI: 1.1-2.8) significantly decreased or increased the risk of breast cancer. Although the breast cancer risk was 1.7-fold (95% CI: 0.8-3.2) increased in women with MTHFR TT genotype, the association was not statistically significant. Women with MTHFR TT genotype and low green vegetable intake increased 5.6-fold (95% CI: 1.2-26.3) risk of breast cancer compared to high green vegetable intake group containing MTHFR CC/CT genotype. However, the interaction was not significant (p for interaction = 0.96). Our findings suggest that MTHFR polymorphism did not influence individual susceptibility to breast cancer. However MTHFR (C667T) genotype and green vegetable intakes appeared to have the interactive effect in breast cancer development.     

Serological proteome analysis of dogs with breast cancer unveils common serum biomarkers with human counterparts

Canine mammary tumor is being touted as a model for investigating the human breast cancer. Breast cancer of the both species has similar biological behavior, histopathologic characteristics, and metastatic pattern. In this study, we used the serological proteome analysis to detect autoantigens that elicit a humoral response in dogs with mammary tumor in order to identify serum biomarkers with potential usefulness as diagnostic markers and to better understand molecular mechanisms underlying canine breast cancer development. Protein extract from a cell line was subject to 2DE followed by Western blotting using sera from 15 dogs with mammary tumor and sera from 15 healthy control dogs. Immunoreactive autoantigens were subsequently identified by the MALDI‐TOF MS. Four autoantigens, including manganese‐superoxide dismutase, triose phosphate isomerase, alpha‐enolase, and phosphoglycerate mutase1, with significantly higher immunoreactivity in the tumor samples than in the normal samples were identified as biomarker candidates. Immunohistochemistry and Western blotting revealed higher expression of these biomarkers in the malignant tumors than in the normal or benign tumors. The autoantigens found in this study have been reported to elicit autoantibody response in the human breast cancer, indicating the similarity of breast cancer proteome profile in dogs with that in human beings.     

CDFI鉴别男性乳腺良恶性肿瘤价值及与CXCL1、Gab2、MVD的相关性探究

本研究选取18例男性乳腺恶性肿瘤患者作为研究组,纳入同期41例男性良性乳腺肿瘤及50例健康体检男性分别作为良性对照组和健康对照组,通过对比分析发现,研究组CDFI参数[搏动指数(PI)、阻力指数(RI)、血流速度(PSV)]高于良性对照组和健康对照组(P＜O.05);PI、RI、PSV联合诊断男性乳腺恶性肿瘤的AUC高...     

Association of the XRCC1 gene polymorphisms with cancer risk in Turkish breast cancer patients

The X-ray repair cross-complementing group 1 (XRCC1) gene is believed to play an important role in base excision repair and displays genetic polymorphisms. Data on the role of XRCC1 polymorphisms in cancer susceptibility is inconsistent. In the present study, we investigated the effect of two XRCC1 polymorphisms, Arg194Trp and Arg399Gln, on breast cancer risk in a case- control study involving Turkish breast cancer patients and healthy women. Both alleles exhibited a similar distribution among cases and controls leading to lack of any significant association between the XRCC1 polymorphisms and breast cancer risk, either in homozygotes and heterozygotes or combined. The allele frequency of the codon 194 variant was very low in cases and healthy individuals (5.3 and 3.9%, respectively) compared to that of the variant 399Gln allele (39.7 and 37.4%). Our results do not support evidence for a role of the XRCC1 polymorphism in developing breast cancer.     

Expanded metabolomics approach to profiling endogenous carbohydrates in the serum of ovarian cancer patients

We applied hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry to the quantitative analysis of serum from 58 women, including ovarian cancer patients, ovarian benign tumor patients, and healthy controls. All of these ovarian cancer and ovarian benign tumor patients have elevated cancer antigen 125, which makes them clinically difficult to differentiate the malignant from the benign. All of the 16 endogenous carbohydrates were quantitatively detected in the human sera, of which, eight endogenous carbohydrates were significantly different (P‐value < 0.05) between the ovarian cancer and healthy control. According to the receiver operating characteristic curve analysis, arabitol was the most potentially specific biomarker for discriminating ovarian cancer from healthy control, having an area under the curve of 0.911. A panel of metabolite markers composed of maltose, maltotriose, raffinose, and mannitol was selected, which was able to discriminate the ovarian cancer from the benign ovarian tumor counterparts, with an area under concentration‐time curve value of 0.832. Endogenous carbohydrates in the expanded metabolomics approach after the global metabolic profiling are characterized and are potential biomarkers for the early diagnosis of ovarian cancer.