Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: a multi-center POSH cohort serum proteomics study

Breast cancer in the era of integrating “Omics” approaches

Worldwide, breast cancer is the leading cause of cancer-related deaths in women. Breast cancer is a heterogeneous disease characterized by different clinical outcomes in terms of pathological features, response to therapies, and long-term patient survival. Thus, the heterogeneity found in this cancer led to the concept that breast cancer is not a single disease, being very heterogeneous both at the molecular and clinical level, and rather represents a group of distinct neoplastic diseases of the breast and its cells. Indubitably, in the past decades we witnessed a significant development of innovative therapeutic approaches, including targeted and immunotherapies, leading to impressive results in terms of increased survival for breast cancer patients. However, these multimodal treatments fail to prevent recurrence and metastasis. Therefore, it is urgent to improve our understanding of breast tumor and metastasis biology. Over the past few years, high-throughput “omics” technologies through the identification of novel biomarkers and molecular profiling have shown their great potential in generating new insights in the study of breast cancer, also improving diagnosis, prognosis and prediction of response to treatment. In this review, we discuss how the implementation of “omics” strategies and their integration may lead to a better comprehension of the mechanisms underlying breast cancer. In particular, with the aim to investigate the correlation between different “omics” datasets and to define the new important key pathway and upstream regulators in breast cancer, we applied a new integrative meta-analysis method to combine the results obtained from genomics, proteomics and metabolomics approaches in different revised studies.

Association of circulating leptin, adiponectin, and resistin concentrations with long-term breast cancer prognosis in a German patient cohort

Adipokines including leptin, adiponectin and resistin have been linked to risk of obesity-related cancers potentially through low-grade chronic inflammation pathways. We aimed to assess the role of post-diagnosis circulating adipokines on long-term prognosis in a prospective breast cancer cohort. Adipokines were measured in blood collected at baseline shortly after diagnosis (2002-2005) and at follow-up (2009) from 3112 breast cancer patients enrolled in the population-based MARIE study. Half of the patients had measurements at both time-points. All-cause mortality, breast cancer specific mortality and recurrences were ascertained up to June 2015 (11 years median follow-up). Associations with time-varying adipokine concentrations overall and stratified by estrogen and progesterone receptor (ERPR) were evaluated using adjusted proportional hazard regression. At baseline (n = 2700) and follow-up (n = 2027), median concentrations for leptin, adiponectin and resistin were 4.6 and 2.7 ng/ml, 24.4 and 30.0 mg/l, 15.4 and 26.2 ng/ml, respectively. After adjustment, there was no evidence for associations between adipokines and any outcome overall. In ERPR negative tumors, highest vs. lowest quintile of adiponectin was significantly associated with increased breast cancer specific mortality (HR 2.51, 95%CI 1.07-5.92). Overall, post-diagnosis adipokines were not associated with long-term outcomes after breast cancer. In patients with ERPR negative tumors, higher concentrations of adiponectin may be associated with increased breast cancer specific mortality and warrant further investigation.

Iterative principal component analysis method for improvised classification of breast cancer disease using blood sample analysis

Breast cancer is the most common cancer in women occurring worldwide. Some of the procedures used to diagnose breast cancer are mammogram, breast ultrasound, biopsy, breast magnetic resonance imaging, and blood tests such as complete blood count. Detecting breast cancer at an early stage plays an important role in diagnostic and curative procedures. This paper aims to develop a predictive model for detecting the breast cancer using blood samples data containing age, body mass index (BMI), glucose, insulin, homeostasis model assessment (HOMA), leptin, adiponectin, resistin, and chemokine monocyte chemoattractant protein 1 (MCP-1).The two main challenges encountered in this process are identification of biomarkers and the precision of disease prediction accuracy. The proposed methodology employs principal component analysis in a peculiar approach followed by random forest tree prediction model to discriminate between healthy and breast cancer patients. This approach extracts high communalities, a linear combination of input attributes in a systematic procedure as principal axis elements. The iteratively extracted principal axis elements combined with minimum number of input attributes are able to predict the disease with higher accuracy of classification with increased sensitivity and specificity score. The results proved that the proposed approach generates a higher predictor performance than the previous reported results by opting relevant extracted principal axis elements and attributes that commend the classifier with increased performance measures.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

iTRAQ- and LC-MS/MS-based quantitative proteomics reveals Pqlc2 as a potential regulator of hepatic glucose metabolism and insulin signalling pathway during fasting

Glucose homeostasis is tightly controlled by balance between glucose production and uptake in liver tissue upon energy shortage condition. Altered glucose homeostasis contributes to the pathophysiology of metabolic disorders including diabetes and obesity. Here, we aimed to analyse the change of proteomic profile upon prolonged fasting in mice with isobaric tag for relative and absolute quantification (iTRAQ) labelling followed by liquid chromatography-mass spectrometry (LC/MS) technology. Adult male mice were fed or fasted for 16 hours and liver tissues were collected for iTRAQ labelling followed by LC/MS analysis. A total of 322 differentially expressed proteins were identified, including 189 upregulated and 133 downregulated proteins. Bioinformatics analyses, including Gene Ontology analysis (GO), Kyoto encyclopaedia of genes and genomes analysis (KEGG) and protein-protein interaction analysis (PPI) were conducted to understand biological process, cell component, and molecular function of the 322 differentially expressed proteins. Among 322 hepatic proteins differentially expressed between fasting and fed mice, we validated three upregulated proteins (Pqlc2, Ehhadh and Apoa4) and two downregulated proteins (Uba52 and Rpl37) by western-blotting analysis. In cultured HepG2 hepatocellular cells, we found that depletion of Pqlc2 by siRNA-mediated knockdown impaired the insulin-induced glucose uptake, inhibited GLUT2 mRNA level and suppressed the insulin-induced Akt phosphorylation. By contrast, knockdown of Pqlc2 did not affect the cAMP/dexamethasone-induced gluconeogenesis. In conclusion, our study provides important information on protein profile change during prolonged fasting with iTRAQ- and LC-MS/MS-based quantitative proteomics, and identifies Pqlc2 as a potential regulator of hepatic glucose metabolism and insulin signalling pathway in this process.

Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis

BACKGROUNDTuberculosis (TB) kills more people than any other infection, and new diagnostic tests to identify active cases are required. We aimed to discover and verify novel markers for TB in nondepleted plasma.METHODSWe applied an optimized quantitative proteomics discovery methodology based on multidimensional and orthogonal liquid chromatographic separation combined with high-resolution mass spectrometry to study nondepleted plasma of 11 patients with active TB compared with 10 healthy controls. Prioritized candidates were verified in independent UK (n = 118) and South African cohorts (n = 203).RESULTSWe generated the most comprehensive TB plasma proteome to date, profiling 5022 proteins spanning 11 orders-of-magnitude concentration range with diverse biochemical and molecular properties. We analyzed the predominantly low-molecular weight subproteome, identifying 46 proteins with significantly increased and 90 with decreased abundance (peptide FDR ≤ 1%, q ≤ 0.05). Verification was performed for novel candidate biomarkers (CFHR5, ILF2) in 2 independent cohorts. Receiver operating characteristics analyses using a 5-protein panel (CFHR5, LRG1, CRP, LBP, and SAA1) exhibited discriminatory power in distinguishing TB from other respiratory diseases (AUC = 0.81).CONCLUSIONWe report the most comprehensive TB plasma proteome to date, identifying novel markers with verification in 2 independent cohorts, leading to a 5-protein biosignature with potential to improve TB diagnosis. With further development, these biomarkers have potential as a diagnostic triage test.FUNDINGColciencias, Medical Research Council, Innovate UK, NIHR, Academy of Medical Sciences, Program for Advanced Research Capacities for AIDS, Wellcome Centre for Infectious Diseases Research.

Decreased Efficacy of Doxorubicin Corresponds With Modifications in Lipid Metabolism Markers and Fatty Acid Profiles in Breast Tumors From Obese vs. Lean Mice

Breast cancer cells modulate lipid and fatty acid metabolism to sustain proliferation. The role of adipocytes in cancer treatment efficacy remains, however, to be fully elucidated. We investigated whether diet-induced obesity (DIO) affects the efficacy of doxorubicin treatment in a breast tumor-bearing mouse model. Female C57BL6 mice were fed a high fat or low fat diet for the full duration of the study (12 weeks). After 8 weeks, mice were inoculated with E0771 triple-negative breast cancer cells in the fourth mammary gland to develop breast tumor allographs. Tumor-bearing mice received either vehicle (Hank's balanced salt solution) or doxorubicin (chemotherapy). Plasma inflammatory markers, tumor, and mammary adipose tissue fatty acid composition, as well as protein expression of lipid metabolism markers were determined. The high fat diet (HFD) attenuated the treatment efficacy of doxorubicin. Both leptin and resistin concentrations were significantly increased in the HFD group treated with doxorubicin. Suppressed lipogenesis (decreased stearoyl CoA-desaturase-1) and lipolysis (decreased hormone-sensitive lipase) were observed in mammary adipose tissue of the DIO animals, whereas increased expression was observed in the tumor tissue of doxorubicin treated HFD mice. Obesogenic conditions induced altered tissue fatty acid (FA) compositions, which reduced doxorubicin's treatment efficacy. In mammary adipose tissue breast cancer cells suppressed the storage of FAs, thereby increasing the availability of free FAs and favored inflammation under obesogenic conditions.

Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach

Why does healthcare of breast cancer (BC) patients, especially in a young population, matter and why are innovative strategies by predictive, preventive, and personalized medicine (PPPM) strongly recommended to replace current reactive medical approach in BC management? Permanent increase in annual numbers of new BC cases with particularly quick growth of premenopausal BC patients, an absence of clearly described risk factors for those patients, as well as established screening tools and programs represent important reasons to focus on BC in young women. Moreover, "young" BC cases are frequently "asymptomatic", difficult to diagnose, and to treat effectively on time. The objective of this article is to update the knowledge on BC in young females, its unique molecular signature, newest concepts in diagnostics and therapy, and to highlight the concepts of predictive, preventive, and personalized medicine with a well-acknowledged potential to advance the overall disease management.

Prognostic value of biomarkers EpCAM and αB-crystallin associated with lymphatic metastasis in breast cancer by iTRAQ analysis

Background

Metastasis is responsible for the majority of deaths in a variety of cancer types, including breast cancer. Although several factors or biomarkers have been identified to predict the outcome of patients with breast cancer, few studies have been conducted to identify metastasis-associated biomarkers.

Methods

Quantitative iTRAQ proteomics analysis was used to detect differentially expressed proteins between lymph node metastases and their paired primary tumor tissues from 23 patients with metastatic breast cancer. Immunohistochemistry was performed to validate the expression of two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins in 190 paraffin-embedded tissue samples. These four proteins were further analyzed for their correlation with clinicopathological features in 190 breast cancer patients.

Results

We identified 637 differentially regulated proteins (397 upregulated and 240 downregulated) in lymph node metastases compared with their paired primary tumor tissues. Data are available via ProteomeXchange with identifier PXD013931. Furthermore, bioinformatics analysis using GEO profiling confirmed the difference in the expression of EpCAM between metastases and primary tumors tissues. Two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins were associated with the progression of breast cancer. Obviously, EpCAM plays a role in the metastasis of breast cancer cells to the lymph node. We further identified αB-crystallin as an independent biomarker to predict lymph node metastasis and the outcome of breast cancer patients.

Conclusion

We have identified that EpCAM plays a role in the metastasis of breast cancer cells to the lymph node. αB-crystallin, a stress-related protein that has recently been shown to be important for cell invasion and survival, was identified as a potential prognostic biomarker to predict the outcome of breast cancer patients.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-6016-3) contains supplementary material, which is available to authorized users.

Association between rs1862513 and rs3745367 Genetic Polymorphisms of Resistin and Risk of Cancer: A Meta-Analysis

The present study aimed to assess any associations between resistin gene (RETN) polymorphisms and cancer susceptibility by conducting a meta-analysis. A comprehensive literature search was performed with PubMed, Web of Science, Scopus and Google Scholar for relevant studies published before April 2018. For the rs1862513 polymorphism, data from 9 studies covering 1,951 cancer patients and 2,295 healthy controls were included in this meta-analysis. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Our meta-analysis revealed that this RETN polymorphism significantly increased the risk of cancer in codominant (OR=1.23, 95% CI= 1.01-1.50, p=0.04, CG vs CC; and OR=1.25, 95% CI= 1.03-1.53, p=0.03, GG vs CC), dominant (OR=1.19, 95% CI= 1.05-1.35, p=0.006, CG+GG vs CC), and allele (OR=1.14, 95% CI= 1.00-1.30, p=0.04, G vs C) inheritance genetic models. Stratification analysis by cancer type revealed that the rs1862513 variant significantly increased the risk of colorectal and breast cancer, and that cancer overall in Caucasians (OR=1.22, 95% CI= 1.04-1.43, p=0.02, CG+GG vs CC; OR=1.18, 95% CI= 1.04-1.34, p=0.01, G vs C). The data revealed no correlation between the rs3745367 polymorphism and cancer risk. Further well-designed studies with larger sample sizes and different ethnicities are warranted to validate the present findings.

Resistin effects on pancreatic cancer progression and chemoresistance are mediated through its receptors CAP1 and TLR4

Resistin, secreted by macrophages in tumor microenvironment, has never been investigated in pancreatic cancer models, despite a vibrant tumor microenvironment around pancreatic tumors. We evaluated serum resistin levels in healthy individuals versus pancreatic cancer patients representing different tumor grades. In vitro mechanistic analysis involved MiaPaCa-2 and SW1990 cells. Resistin signaling depends on binding of resistin to its cognitive receptors. Therefore, we silenced adenylyl cyclase-associated protein 1 (CAP1) and toll-like receptor 4 (TLR4), its two known receptors, individually as well as in combination, by short hairpin RNA (shRNA). Effect of resistin on cell proliferation, migration, invasion, cell cycle, and sensitivity to gemcitabine was studied without or with silencing of resistin receptors CAP1 and/or TLR4. The results were also confirmed in vivo in mice xenografted with MiaPaCa-2 cells without or with receptor silencing. We report high resistin levels in pancreatic cancer patients which correlate positively with tumor grades. We observed a marked reduction in the resistin-induced proliferation, migration, invasion, and cell cycle of pancreatic cancer cells MiaPaCa-2 and SW1990 when the receptors were silenced. The results were confirmed in vivo wherein resistin effects were significantly attenuated in MiaPaCa-2 xenografts with silenced receptors. The combined silencing of CAP1 and TLR4 was found to be most effective in vitro and in vivo. We found activation of STAT3 by resistin in vivo and in vitro which was dependent on the presence of CAP1 and TLR4. Further, resistin was found to induce resistance to gemcitabine through its receptors. Our results describe novel functional roles of resistin with implications toward a better understanding of pancreatic tumor microenvironment.

Adipocytes and Obesity-Related Conditions Jointly Promote Breast Cancer Cell Growth and Motility: Associations With CAP1 for Prognosis

The global increase in overweight and obesity rates represent pressing public health concerns associated with severe comorbidities, amongst a rising incidence and impaired outcome of breast cancer. Yet, biological explanations for how obesity affects breast cancer are incompletely mapped. Herein, the joint impact by differentiated 3T3-L1 adipocytes and obesity-related metabolic conditions on breast cancer cells was evaluated in vitro and adipocyte-derived mediators assessed. Adipokine receptor expression was explored among breast cancer cell lines (n = 47) and primary breast tumors (n = 1,881), where associations with survival outcomes were investigated. Adipocytes and metabolic complications jointly stimulated breast cancer cell proliferation and motility, with phenotype-specific differences. Resistin was among the top modulated adipokines secreted by 3T3-L1 adipocytes under obesity-associated metabolic conditions compared with normal physiology. The newly identified resistin receptor, CAP1, was expressed across a large panel of breast cancer cell lines and primary breast tumors. CAP1 was associated with poor tumor characteristics with higher CAP1 expression among estrogen receptor (ER)-negative tumors, relative to ER-positive tumors (P = 0.025), and higher histological grades (P = 0.016). High CAP1 tumor expression was associated with shorter overall survival (adjusted hazard ratio [HR_adj] 1.54; 95% confidence interval [CI], 1.11-2.13) and relapse-free survival (HR_adj 1.47; 95% CI, 1.10-1.96), compared with low or intermediate CAP1 expression, particularly among ER-positive tumors or lymph node positive tumors. Together, these translational data demonstrate that the adipocyte secretome promote breast cancer cell proliferation and motility and highlight a potential role of CAP1 regarding breast cancer outcome-results that warrant further investigation to elucidate the obesity-breast cancer link in human pathology.