Hydrophobic Proteome Analysis of Triple Negative and Hormone-Receptor-Positive-Her2-Negative Breast Cancer by Mass Spectrometer

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.

Glycoproteomic comparison of clinical triple-negative and luminal breast tumors

Triple-negative (TN) breast cancer accounts for ∼ 15% of breast cancers and is characterized by a high likelihood of relapse and a lack of targeted therapies. In contrast, luminal-type tumors that express the estrogen and progesterone receptors (ER+/PR+) and lack expression of human epidermal growth factor receptor 2 (Her2-) are treated with targeted hormonal therapy and carry a better prognosis. To identify potential targets for the development of future therapeutics aimed specifically at TN breast cancers, we have used a hydrazide-based glycoproteomic workflow to compare protein expression in clinical tumors from nine TN (Her2-/ER-/PR-) and nine luminal (Her2-/ER+/PR+) patients. Using a label-free LC-MS based approach, we identified and quantified 2264 proteins. Of these, 90 proteins were more highly expressed and 86 proteins were underexpressed in the TN tumors relative to the luminal tumors. The expression level of four of these potential targets was verified in the original set of tumors by Western blot and correlated well with our mass-spectrometry-based quantification. Furthermore, 30% of the proteins differentially expressed between luminal and TN tumors were validated in a larger cohort of 406 TN and 469 luminal tumors through corresponding differences in their mRNA expression in publically available microarray data. A group of 29 of these differentially expressed proteins was shown to correctly classify 88% of TN and luminal tumors using microarray data of their associated mRNA levels. Interestingly, even within a group of TN breast cancer patients, the expression levels of these same mRNAs were able to significantly predict patient survival, suggesting that these proteins play a role in the aggressiveness seen in TN tumors. This study provides a comprehensive list of potential targets for the development of diagnostic and therapeutic agents specifically aimed at treating TN breast cancer and demonstrates the utility of using publicly available microarray data to further prioritize potential targets.

Combined phosphoproteomics and bioinformatics strategy in deciphering drug resistant related pathways in triple negative breast cancer

Because of the absence of a clear therapeutic target for triple negative breast cancer (TNBC), conventional chemotherapy is the only available systemic treatment option for these patients. Despite chemotherapy treatment, TNBC patients still have worse prognosis when compared with other breast cancer patients. The study is to investigate unique phosphorylated proteins expressed in chemoresistant TNBC cell lines. In the current study, twelve TNBC cell lines were subjected to drug sensitivity assays against chemotherapy drugs docetaxel, doxorubicin, gemcitabine, and cisplatin. Based on their half maximal inhibitory concentrations, four resistant and two sensitive cell lines were selected for further analysis. The phosphopeptides from these cells were enriched with TiO2 beads and fractionated using strong cation exchange. 1,645 phosphoprotein groups and 9,585 unique phosphopeptides were identified by a high throughput LC-MS/MS system LTQ-Orbitrap. The phosphopeptides were further filtered with Ascore system and 1,340 phosphoprotein groups, 2,760 unique phosphopeptides, and 4,549 unique phosphosites were identified. Our study suggested that differentially phosphorylated Cdk5, PML, AP-1, and HSF-1 might work together to promote vimentin induced epithelial to mesenchymal transition (EMT) in the drug resistant cells. EGFR and HGF were also shown to be involved in this process.

Determination of the Proteomic Response to Lapatinib Treatment using a comprehensive and reproducible ion-current-based proteomics strategy

Lapatinib, a small molecule tyrosine kinase inhibitor is currently used in the treatment of HER2-positive breast cancer. The aim of this study was to further understanding of lapatinib response for the development of novel treatment lapatinib-focussed treatment strategies. HER2-overexpressing SKBR3 breast cancer cells were treated with lapatinib for 12 hours and the resultant proteome analyzed by a comprehensive ion-current-based LC-MS strategy. Among the 1224 unique protein identified from SKBR3 cell lysates, 67 showed a significant change in protein abundance in response to lapatinib. Of these, CENPE a centromeric protein with increased abundance, was chosen for further validation. Knockdown and inhibition of CENPE demonstrated that CENPE enhances SKBR3 cell survival in the presence of lapatinib. Based on this study, CENPE inhibitors may warrant further investigation for use in combination with lapatinib.

A proteomic analysis of human follicular fluid: comparison between fertilized oocytes and non-fertilized oocytes in the same patient

PURPOSE

Human follicular fluid constitutes the microenvironment of follicles and includes various biological active proteins that can affect follicle growth and oocyte fertilization. Conducting proteomic evaluations of human follicular fluid may be helpful for identifying potential biomarkers possibly possessing a predictive value for oocyte quality and the success of in vitro fertilization.

METHOD

We performed proteomic profiling of human follicular fluids containing oocytes that were fertilized and resulted in pregnancy and follicular fluids containing oocytes that were not fertilized in the same patients undergoing intracytoplasmic sperm injection using the LTQ Orbitrap coupled with liquid chromatography-tandem mass spectrometry (LC/MS/MS) analyses.

RESULTS

We identified a total of 503 proteins in human follicular fluids containing fertilized and non-fertilized oocytes obtained from 12 patients. We also found that 53 proteins exhibited significantly different spectral counts between the two groups, including heparan sulfate proteoglycan perlecan, which showed significant upregulation in the follicular fluids containing fertilized oocytes in comparison with that observed in the follicular fluids containing non-fertilized oocytes.

CONCLUSION

Our results suggest a possibility that proteins identified by LC/MS/MS in follicular fluid might not only be involved in folliculogenesis, but also function as biomarkers possessing predictive potential for oocyte maturation and the success of IVF when their expression levels are significantly different between fertilized and non-fertilized oocytes, although no distinctive biomarkers were identified in the current study.

Mass spectrometry (LC-MS/MS) identified proteomic biosignatures of breast cancer in proximal fluid

We have begun an early phase of biomarker discovery in three clinically important types of breast cancer using a panel of human cell lines: HER2 positive, hormone receptor positive and HER2 negative, and triple negative (HER2-, ER-, PR-). We identified and characterized the most abundant secreted, sloughed, or leaked proteins released into serum free media from these breast cancer cell lines using a combination of protein fractionation methods before LC-MS/MS mass spectrometry analysis. A total of 249 proteins were detected in the proximal fluid of 7 breast cancer cell lines. The expression of a selected group of high abundance and/or breast cancer-specific potential biomarkers including thromobospondin 1, galectin-3 binding protein, cathepsin D, vimentin, zinc-α2-glycoprotein, CD44, and EGFR from the breast cancer cell lines and in their culture media were further validated by Western blot analysis. Interestingly, mass spectrometry identified a cathepsin D protein single-nucleotide polymorphism (SNP) by alanine to valine replacement from the MCF-7 breast cancer cell line. Comparison of each cell line media proteome displayed unique and consistent biosignatures regardless of the individual group classifications, demonstrating the potential for stratification of breast cancer. On the basis of the cell line media proteome, predictive Tree software was able to categorize each cell line as HER2 positive, HER2 negative, and hormone receptor positive and triple negative based on only two proteins, muscle fructose 1,6-bisphosphate aldolase and keratin 19. In addition, the predictive Tree software clearly identified MCF-7 cell line overexpresing the HER2 receptor with the SNP cathepsin D biomarker.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

Proteomic-based biosignatures in breast cancer classification and prediction of therapeutic response

Protein-based markers that classify tumor subtypes and predict therapeutic response would be clinically useful in guiding patient treatment. We investigated the LC-MS/MS-identified protein biosignatures in 39 baseline breast cancer specimens including 28 HER2-positive and 11 triple-negative (TNBC) tumors. Twenty proteins were found to correctly classify all HER2 positive and 7 of the 11 TNBC tumors. Among them, galectin-3-binding protein and ALDH1A1 were found preferentially elevated in TNBC, whereas CK19, transferrin, transketolase, and thymosin β4 and β10 were elevated in HER2-positive cancers. In addition, several proteins such as enolase, vimentin, peroxiredoxin 5, Hsp 70, periostin precursor, RhoA, cathepsin D preproprotein, and annexin 1 were found to be associated with the tumor responses to treatment within each subtype. The MS-based proteomic findings appear promising in guiding tumor classification and predicting response. When sufficiently validated, some of these candidate protein markers could have great potential in improving breast cancer treatment.