Analysis of the differences of serum protein mass spectrometry in patients with triple negative breast cancer and non-triple negative breast cancer

Exploration of quantitative site-specific serum O-glycoproteomics with isobaric labeling for the discovery of putative O-glycoprotein biomarkers

PURPOSE

Exploration study of site-specific isobaric-TMT-labeling quantitative serum O-glycoproteomics for the discovery of putative O-glycoprotein cancer biomarkers.

EXPERIMENTAL DESIGN

Sera of 10 breast cancer patients was used as the exploration cohort. More abundant N-glycosylation was first removed with PNGase F. After tryptic digestion of de-N-glycosylated serum proteome, the TMT-labeled O-glycopeptides mixture was prepared and analyzed with RPLC-MS/MS. Site-specific qualitative and quantitative database search of O-glycopeptides was carried out with pGlyco 3.0. The same raw datasets were also searched with intact N-glycopeptide search engine GPSeeker to exclude possible interference of N-glycosylation. The final IDs were checked manually with GlcNAc-containing glycosite-determining fragment ions for confirmation.

RESULTS

With the control of spectrum-level FDR ≤ 1% and manual validation, 299 O-glycopeptides corresponding to 83 O-glycosites and 66 O-glycoproteins were identified, and 13 O-glycopeptides were found differentially expressed. Most interestingly, differential O-glycosylation was observed for IgG1 and IgG3, which is an interesting putative biomarker panel.

CONCLUSION AND CLINICAL RELEVANCE

Isobaric-labeling site-specific quantitative O-glycoproteomics is currently a state-of-the-art instrumental platform for discovery of putative seral cancer biomarkers. Differential seral O-glycosylation was observed in the IgG1 and IgG3.

Circulating proteins as predictive and prognostic biomarkers in breast cancer

Breast cancer (BC) is the most common cancer and among the leading causes of cancer death in women. It is a heterogeneous group of tumours with numerous morphological and molecular subtypes, making predictions of disease evolution and patient outcomes difficult. Therefore, biomarkers are needed to help clinicians choose the best treatment for each patient. For the last years, studies have increasingly focused on biomarkers obtainable by liquid biopsy. Circulating proteins (from serum or plasma) can be used for inexpensive and minimally invasive determination of disease risk, early diagnosis, treatment adjusting, prognostication and disease progression monitoring. We provide here a review of the main published studies on serum proteins in breast cancer and elaborate on the potential of circulating proteins to be predictive and/or prognostic biomarkers in breast cancer.

Unraveling the Genomic-Epigenomic Interaction Landscape in Triple Negative and Non-Triple Negative Breast Cancer

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.

Diagnostic and prognostic significance of serum apolipoprotein C-I in triple-negative breast cancer based on mass spectrometry

Women with triple-negative breast cancer (TNBC) have poor prognosis because of the aggressive nature of the tumor, delayed diagnosis and non-specific symptoms in the early stages. Identification of novel specific TNBC serum biomarkers for screening and therapeutic purposes therefore remains an urgent clinical requirement.We obtained serum samples from a total of 380 recruited individuals split into mining and testing sets, with the aim of screening for reliable protein biomarkers from TNBC and non-TNBC (NTNBC) sera. Samples were assessed using mass spectrometry, followed by receiver operating characteristic (ROC), survival and hazard function curve as well as multivariate Cox regression analyses to ascertain the potential of the protein constituents as diagnostic and prognostic biomarkers for TNBC.We identified upregulated apolipoprotein C-I (apoC-I) with a validated positive effect on TNBC tumorigenesis, with confirmation in an independent test set and minimization of systematic bias by pre-analytical parameters. The apoC-I protein had superior diagnostic ability in distinguishing between TNBC and NTNBC cases. Moreover, the protein presented a more robust potential prognostic factor for TNBC than NTNBC. The apoC-I protein identified in this study presents an effective novel diagnostic and prognostic biomarker for TNBC, indicating that measurement of the peak intensity at 7785 Da in serum samples could facilitate improved early detection and estimation of postoperative survival prognosis for TNBC.

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.

Identification of potential serum proteomic biomarkers for clear cell renal cell carcinoma

Objective

To investigate discriminating protein patterns and serum biomarkers between clear cell renal cell carcinoma (ccRCC) patients and healthy controls, as well as between paired pre- and post-operative ccRCC patients.

Methods

We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with ccRCC. A total of 162 serum samples were analyzed in this study, among which there were 58 serum samples from ccRCC patients, 40 from additional paired pre- and post-operative ccRCC patients (n = 20), and 64 from healthy volunteers as healthy controls. ClinProTools software identified several distinct markers between ccRCC patients and healthy controls, as well as between pre- and post-operative patients.

Results

Patients with ccRCC could be identified with a mean sensitivity of 88.38% and a mean specificity of 91.67%. Of 67 m/z peaks that differed among the ccRCC, healthy controls, pre- and post-operative ccRCC patients, 24 were significantly different (P<0.05). Three candidate peaks, which were upregulated in ccRCC group and showed a tendency to return to healthy control values after surgery, were identified as peptide regions of RNA-binding protein 6 (RBP6), tubulin beta chain (TUBB), and zinc finger protein 3 (ZFP3) with the m/z values of 1466.98, 1618.22, and 5905.23, respectively.

Conclusion

MB-MALDI-TOF-MS method could generate serum peptidome profiles of ccRCC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.