Tissue biomarkers of breast cancer and their association with conventional pathologic features

Deciphering a proteomic signature for the early detection of breast cancer from breast milk: the role of quantitative proteomics

INTRODUCTION

Breast cancer is one of the most prevalent cancers among women in the United States. Current research regarding breast milk has been focused on the composition and its role in infant growth and development. There is little information about the proteins, immune cells, and epithelial cells present in breast milk which can be indicative of the emergence of BC cells and tumors.

AREAS COVERED

We summarize all breast milk studies previously done in our group using proteomics. These studies include 1D-PAGE and 2D-PAGE analysis of breast milk samples, which include within woman and across woman comparisons to identify dysregulated proteins in breast milk and the roles of these proteins in both the development of BC and its diagnosis. Our projected outlook for the use of milk for cancer detection is also discussed.

EXPERT OPINION

Analyzing the samples by multiple methods allows one to interrogate a set of samples with various biochemical methods that complement each other, thus providing a more comprehensive proteome. Complementing methods like 1D-PAGE, 2D-PAGE, in-solution digestion and proteomics analysis with PTM-omics, peptidomics, degradomics, or interactomics will provide a better understanding of the dysregulated proteins, but also the modifications or interactions between these proteins.

Integrated Proteomics Based on 2D Gel Electrophoresis and Mass Spectrometry with Validations: Identification of a Biomarker Compendium for Oral Submucous Fibrosis—An Indian Study

Oral Submucous Fibrosis (OSMF) is a chronic debilitating disease more frequently found in the South East Asian population. This disease poses a public health priority, as it is grouped under oral potentially malignant disorders, with malignant transformation rates of around 7 to 13%. Hence, early identification of high-risk OSMF patients is of the utmost importance to prevent malignant transformation. Proteomic expression profiling is a promising method for identifying differentially expressed proteins for disease prognosis and risk stratification in OSMF. In this study, overexpressed proteins in OSMF, OSMF transformed into oral squamous cell carcinoma (OSCC) and normal tissues were evaluated by proteomic analysis using two-dimensional electrophoresis (2DE) and mass spectrometry, which revealed 23 upregulated proteins. Validation was done using immunohistochemistry for three secretory proteins, namely 14-3-3ε (n = 130), carbonic anhydrase 1 (CA 1) (n = 125) and heat shock protein 70 (HSP 70) (n = 117), which showed significant overexpression in OSMF, OSCC compared to normal. The present study is the first of its kind in India to the best of our knowledge, assessing the altered expression of proteins in OSMF and OSMF which has undergone malignant transformation, obtaining a better knowledge of the molecular pathways involved in the disease progression. The current study shows that the biomarkers studied can be potentially useful for risk stratification of OSMF to OSCC serving as novel targets for therapeutic intervention. Clinical validation of the targets can further pave way for precision medicine to improve the quality of life in OSMF patients.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

Calcium-Binding Protein S100P Promotes Tumor Progression but Enhances Chemosensitivity in Breast Cancer

BACKGROUND

Chemoresistance remains one of the obstacles to overcome in the treatment of breast cancer. S100 calcium-binding protein P (S100P) has been observed to be overexpressed in several cancers and has been associated with drug resistance, metastasis, and prognosis. However, the role of S100P in chemoresistance in breast cancer has not been thoroughly determined.

METHODS

Immunohistochemistry was used to evaluate the expression level of S100P protein in 22 pairs (pre-chemo and post-chemo) of breast cancer tissue from patients who underwent neoadjuvant chemotherapy. The influence of S100P on the biological behavior and chemosensitivity of breast cancer cells was then investigated.

RESULTS

The protein level of S100P in breast cancer tissue was significantly higher than in benign fibroadenoma (p < 0.001). The S100P expression level was shown to be decreased by 46.55% after neoadjuvant chemotherapy (p = 0.015). Subgroup analysis revealed that S100P reduction (57.58%) was mainly observed in the HER2+ tumors (p = 0.027). Our in vitro experiments showed that the knockdown of S100P suppressed the proliferation, adhesion, migrative and invasive abilities of T47D and SK-BR-3 breast cancer cells. We further demonstrated that this knockdown increased the chemoresistance to paclitaxel and cisplatin in SK-BR-3 cells. We found S100P exerted its function by upregulating NF-κB, CCND1 and Vimentin, but downregulating E-cadherin.

CONCLUSION

S100P promotes the aggressive properties of breast cancer cells and may be considered as a promising therapeutic target. Moreover, S100P can be used to predict the therapeutic effect of chemotherapy in HER2+ breast cancer patients.

TriZ-a rotation-tolerant image feature and its application in endoscope-based disease diagnosis

Endoscopy is becoming one of the widely-used technologies to screen the gastric diseases, and it heavily relies on the experiences of the clinical endoscopists. The location, shape, and size are the typical patterns for the endoscopists to make the diagnosis decisions. The contrasting texture patterns also suggest the potential lesions. This study designed a novel rotation-tolerant image feature, TriZ, and demonstrated the effectiveness on both the rotation invariance and the lesion detection of three gastric lesion types, i.e., gastric polyp, gastric ulcer, and gastritis. TriZ achieved 87.0% in the four-class classification problem of the three gastric lesion types and the healthy controls, averaged over the twenty random runs of 10-fold cross-validations. Due to that biomedical imaging technologies may capture the lesion sites from different angles, the symmetric image feature extraction algorithm TriZ may facilitate the biomedical image based disease diagnosis modeling. Compared with the 378,434 features of the HOG algorithm, TriZ achieved a better accuracy using only 126 image features.

1H NMR Metabolomics Reveals Association of High Expression of Inositol 1, 4, 5 Trisphosphate Receptor and Metabolites in Breast Cancer Patients

¹H NMR is used to detect alterations in metabolites and their linkage to metabolic processes in a number of pathological conditions including breast cancer. Inositol 1, 4, 5 trisphosphate (IP₃R) receptor is an intracellular calcium channel known to regulate metabolism and cellular bioenergetics. Its expression is up regulated in a number of cancers. However, its linkage to metabolism in disease conditions has not been evaluated. This study was designed to determine the association if any, of these metabolites with altered expression of IP3R in breast cancer. We used ¹H NMR to identify metabolites in the serum of breast cancer patients (n = 27) and performed Real-time Polymerase Chain Reaction analysis for quantifying the expression of IP₃R type 3 and type 2 in tissues from breast cancer patients (n = 40). Principal Component Analysis (PCA) and Partial Least Square-Discriminant Analysis (PLS-DA) clearly distinguished patients with high/low IP₃R expression from healthy subjects. The present study revealed high expression of IP₃R type 2 and type 3 in human breast tumor tissue compared to adjacent non-tumorous tissue. Moreover, patients with ≥ 2-fold increase in IP₃R (high IP₃R group) had significantly higher concentration of metabolic intermediates compared to those with < 2-fold increase in IP₃R (low IP₃R group). We observed an increase in lipoprotein content and the levels of metabolites like lactate, lysine and alanine and a decrease in the levels of pyruvate and glucose in serum of high IP₃R group patients when compared to those in healthy subjects. Receiver operating characteristic (ROC) curve analysis was performed to show the clinical utility of metabolites. In addition to the human studies, functional relevance of IP₃Rs in causing metabolic disruption was observed in MCF-7 and MDA MB-231 cells. Results from our studies bring forth the importance of metabolic (or metabolomics) profiling of serum by ¹H NMR in conjunction with tissue expression studies for characterizing breast cancer patients. The results from this study provide new insights into relationship of breast cancer metabolites with IP₃R.

The life and works of S100P - from conception to cancer

Since its discovery in 1992, the small, 10.4 kDa calcium-binding protein S100P has gained the attention of researchers from different scientific fields due to its potential roles in both healthy and neoplastic tissues. Although not ubiquitously expressed, in tissues where it is present, S100P is associated with distinct changes in cellular behaviour. In this review we have summarized the evolutionary history of S100P, its expression and involvement in implantation and human embryonic development, as well as important functions in normal tissue and cancer. Finally, we have demonstrated its pivotal role as a potential diagnostic and therapeutic target, which opens promising avenues for further fruitful research on S100P.

Quantitative tissue proteomic investigation of invasive ductal carcinoma of breast with luminal B HER2 positive and HER2 enriched subtypes towards potential diagnostic and therapeutic biomarkers

Worldwide, breast cancer is one of the frequently diagnosed cancers in women with high mortality if not diagnosed at early stage. Although biomarker discoveries through various proteomic approaches have been studied in breast cancer, a limited number of studies have explored the invasive ductal carcinoma with Luminal B HER2 positive (LB) and HER2 enriched (HE) subtypes. The present study employed the complementary quantitative proteomic approaches to find a panel of markers that could discriminate LB and HE subtypes as well as early (ES) and late stages (LS) of these subtypes. A total of 67 and 68 differentially expressed proteins were identified by DIGE for the subtype and stage wise categories, respectively. Multivariate statistical analysis was employed to identify the set of most significant proteins, which could discriminate between these two subtypes and also early and late stages under study. Immunoblotting and MRM based validation in a separate cohort of samples confirmed that panel of biosignatures for LB are APOA1, GELS, HS90B, EF1A1, NHRF1 and PRDX3 and for HE are PRDX1, CATD, CALR, ATPB and CH60. For the diagnosis of early and late stages the potential markers are TPM4, CATD, PRDX3, ANXA3, HSPB1 and CALR, TRFE, GELS, CH60, CAPG, NHRF1, 1433G, GRP78 respectively.

A novel truncated form of S100P predicts disease-free survival in patients with lymph node positive breast cancer

The calcium-binding protein S100P is overexpressed in various cancers and may contribute to the oncogenic phenotype. This study used mass spectrometry to characterize a novel 9.2-kDa C-terminally truncated form of S100P (t-S100P), and to investigate its potential prognostic value in breast cancer. Univariate analysis demonstrated the association between breast tissue t-S100P levels (n = 148) and conventional pathological markers. Across all tumor samples, high t-S100P was strongly prognostic for poor disease-free survival (P = 0.005), its efficacy confined to lymph node-positive tumors (n = 74, P = 0.007). Matrix-assisted laser desorption/ionization imaging mass spectrometry confirmed differential t-S100P abundance between breast cancer and unaffected adjacent tissue. t-S100P was exclusively located in the cell nucleus of breast cancer tissue, and full-length S100P was essentially undetectable by mass spectrometry. We conclude that t-S100P is the predominant form of S100P in breast cancer tissue and is strongly prognostic for disease-free survival in women with lymph node-positive disease.

Molecular mechanism of cell death induced by king cobra (Ophiophagus hannah) venom l-amino acid oxidase

Snake venom LAAOs have been reported to exhibit a wide range of pharmacological activities, including cytotoxic, edema-inducing, platelet aggregation-inducing/platelet aggregation-inhibiting, bactericidal and antiviral activities. A heat-stable form of l-amino acid oxidase isolated from king cobra (Ophiophagus hannah) venom (OH-LAAO) has been shown to exhibit very potent cytotoxicity against human tumorigenic cells but not in their non-tumorigenic counterparts, and the cytotoxicity was due to the apoptosis-inducing effect of the enzyme. In this work, the molecular mechanism of cell death induced by OH-LAAO was investigated. The enzyme exerts its apoptosis-inducing effect presumably via both intrinsic and extrinsic pathways as suggested by the increase in caspase-8 and -9 activities. Oligonucleotide microarray analysis showed that the expression of a total of 178 genes was significantly altered as a result of oxidative stress induced by the hydrogen peroxide generated by the enzyme. Of the 178 genes, at least 27 genes are involved in apoptosis and cell death. These alterations of gene expression was presumably caused by the direct cytotoxic effect of H2O2 generated during the enzymatic reaction, as well as the non-specific oxidative modifications of signaling molecules that eventually lead to apoptosis and cell death. The very substantial up-regulation of cytochrome P450 genes may also contribute to the potent cytotoxic action of OH-LAAO by producing excessive reactive oxygen species (ROS). In conclusion, the potent apoptosis inducing activity of OH-LAAO was likely due to the direct cytotoxic effect of H2O2 generated during the enzymatic reaction, as well as the non-specific oxidation of signalling molecules.

Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

Introduction

Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.

Methods

Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.

Results

From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.

Conclusions

Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.

A novel highly reactive Fab antibody for breast cancer tissue diagnostics and staging also discriminates a subset of good prognostic triple-negative breast cancers

The discovery of novel markers for breast cancer (BC) has been recently relied on antibody combinatorial libraries and selection through phage display. We constructed a recombinant Fab library, and after selections against BC tissues, the FabC4 clone was thoroughly investigated by immunohistochemistry in 232 patients with long-term follow-up. The FabC4 ligand was determined by mass spectrometry. The FabC4 expression was associated with younger age, lack of progesterone receptor, higher histological grades and non-luminal subtypes, and it also identified a subset of good prognostic triple-negative BCs, possibly targeting a conformational epitope of Cytokeratin-10 (CK10). This new CK10-epitope specific antibody may open new possibilities in diagnostic and therapeutic strategies.

Mass spectrometry for the detection of potential psychiatric biomarkers

The search for molecules that can act as potential biomarkers is increasing in the scientific community, including in the field of psychiatry. The field of proteomics is evolving and its indispensability for identifying biomarkers is clear. Among proteomic tools, mass spectrometry is the core technique for qualitative and quantitative identification of protein markers. While significant progress has been made in the understanding of biomarkers for neurodegenerative diseases such as Alzheimer's disease, multiple sclerosis and Parkinson's disease, psychiatric disorders have not been as extensively investigated. Recent and successful applications of mass spectrometry-based proteomics in fields such as cardiovascular disease, cancer, infectious diseases and neurodegenerative disorders suggest a similar path for psychiatric disorders. In this brief review, we describe mass spectrometry and its use in psychiatric biomarker research and highlight some of the possible challenges of undertaking this type of work. Further, specific examples of candidate biomarkers are highlighted. A short comparison of proteomic with genomic methods for biomarker discovery research is presented. In summary, mass spectrometry-based techniques may greatly facilitate ongoing efforts to understand molecular mechanisms of psychiatric disorders.

Breast cancer biomarkers: proteomic discovery and translation to clinically relevant assays

Although the molecular classification and prognostic assessment of breast tumors based on gene expression profiling is well established, a number of proteomic studies that propose potential breast cancer biomarkers has not yet led to any new diagnostic, prognostic or predictive test in wide clinical use. This review examines the current status of breast cancer biomarkers, discusses sample types (including plasma, tumor tissue, nipple aspirate and ductal lavage, as well as cell culture models) and different electrophoretic and mass spectrometry methods that have been widely used for the discovery of proteomic biomarkers in breast cancer, and also considers several approaches to biomarker validation. The pathway leading from the initial proteomic discovery and validation process to translation into a clinically useful test is also discussed.