Identification of potential serum biomarkers for breast cancer using a functional proteomics technology

LncRNA T376626 is a promising serum biomarker and promotes proliferation, migration, and invasion via binding to LAMC2 in triple-negative breast cancer

PURPOSE

Circulating long noncoding RNAs (lncRNAs) have been reported to serve as biomarkers for cancer diagnosis. Here, we identified the clinical diagnostic value and biological function of lncRNA T376626 in triple-negative breast cancer (TNBC).

METHOD

A genome-wide lncRNA microarray was used to screen promising serum-based lncRNA biomarkers. The expression of candidate serum lncRNAs was validated in 282 breast cancer (BC) patients and 78 healthy subjects. The diagnostic value of serum lncRNA T376626 was determined by receiver operating characteristic (ROC) curve. RNA fluorescent in situ hybridization (FISH) and RNAScope ISH assays were conducted to examine the expression and localization of lncRNA T376626 in TNBC cells and BC tissues. Kaplan-Meier analysis was conducted to evaluate the relationship between lncRNA T376626 and BC patients' overall survival (OS) rate. CCK-8, colony-forming, wound healing and Transwell assays were performed to investigate the biological function of lncRNA T376626 on cell proliferation, migration, and invasion in two TNBC cell lines. Cell apoptosis-, cell cycle- and epithelial-mesenchymal transition (EMT)-related biomarkers were quantified by western blots. The lncRNA T376626 binding proteins were screened and identified by RNA pulldown.

RESULTS

LncRNA T376626 level was significantly higher in TNBC serums and tissues. Higher levels of lncRNA T376626 were positively associated with a higher pathological differentiation stage, more aggressive molecular subtype, and poor prognosis in BC and TNBC patients. The area under the curve (AUC) of serum lncRNA T376626 was 0.842. Overexpression (Knockdown) of lncRNA T376626 significantly promoted (inhibited) TNBC cell proliferation, migration, and invasion, possibly by regulating several cell cycle, cell apoptosis and EMT biomarkers. LAMC2 were identified as lncRNA T376626-binding proteins. LAMC2 facilitated TNBC proliferation and metastasis through lncRNA T376626.

CONCLUSIONS

LncRNA T376626 may serve as a TNBC serum-based diagnostic and prognostic biomarker and play an oncogenic role in TNBC progression through binding to LAMC2.

Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70–80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of “6P” medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC–MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein–protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with “proteome point sampling” methods that allow for proteomic profiling by in vivo “proteome point characterization”, or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC–MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.

Liquid Biopsies, Novel Approaches and Future Directions

Cancer is among the leading causes of death worldwide. Early diagnosis and prognosis are vital to improve patients' outcomes. The gold standard of tumor characterization leading to tumor diagnosis and prognosis is tissue biopsy. Amongst the constraints of tissue biopsy collection is the sampling frequency and the incomplete representation of the entire tumor bulk. Liquid biopsy approaches, including the analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), circulating miRNAs, and tumor-derived extracellular vesicles (EVs), as well as certain protein signatures that are released in the circulation from primary tumors and their metastatic sites, present a promising and more potent candidate for patient diagnosis and follow up monitoring. The minimally invasive nature of liquid biopsies, allowing frequent collection, can be used in the monitoring of therapy response in real time, allowing the development of novel approaches in the therapeutic management of cancer patients. In this review we will describe recent advances in the field of liquid biopsy markers focusing on their advantages and disadvantages.

Non-invasive optical characterization and detection of CA 15-3 breast cancer biomarker in blood serum using monoclonal antibody-conjugated gold nanourchin and surface-enhanced Raman scattering

A proof-of-concept of colloidal surface-enhanced Raman scattering (SERS) substrate for rapid selective detection of overexpressed CA 15-3 biomarker in breast cancer serum (BCS) is suggested using PEGylated gold nanourchins (GNUs) conjugated with anti-CA 15-3 monoclonal antibody (mAb). UV-vis spectroscopy provided conformational information about mAb where the initial aromatic amino acid peak was red-shifted from 271 to 291 nm. The fluorescence peak of tyrosine in mAb was reduced by ≈ 77%, and red-shifted by ≈ 3 nm after incubation in BCS. Fourier transform near-infrared spectroscopy and SERS were used to study the composition and the molecular structure of the mAb and BCS. Some of the most dominant Raman shifts after GNU-PEG-mAb interaction with BCS are 498, 736, 818, 1397, 1484, 2028, 2271, and 3227 cm-1 mainly corresponding to C-N-C in amines, vibrational modes of amino acids, C-H out-of-plane bend, C-O stretching carboxylic acid, the vibrational mode in phospholipids, NH3+ amine salt, C≡N stretching in nitriles, and O-H stretching. The intensity of SERS signals varied per trial due to the statistical behavior of GNU in BCS, agglomeration, laser power, and the heating effect. Despite very small amount of plasmonic heating, the result of the ANOVA test demonstrated that under our experimental conditions, the heating effect on signal variation is negligible and that the differences in the laser power are insignificant for all SERS observations (p > 0.6); thus, other parameters are responsible. The absorbance of mAb-conjugated GNU was decreased after five minutes of irradiation at 8 mW in the BCS.

Comparative proteomic analysis of mustard lung as a complicated disease using systems biology approach

During Iraq-Iran conflict, chemical weapons, particularly SM gas, were used numerous times, whose aftereffects are still present. This study aimed to compare serum proteome in the chronic ML (n = 10) and HC (n = 10). TMT label-based quantitative proteomics was used to examine serums from two groups. Among total significant proteins, 14 proteins were upregulated (log₂ ≥ FC 0.5, p 0.05), and 6 proteins were downregulated (log₂ ≤ FC - 0.5, p 0.05). By helping PPI network, and EA, 11 main pathways connected to significantly different protein expression levels were discovered, including inflammatory and cell adhesion signaling pathways. It may be deduced that the wounded organs of exposed individuals experience poor repair cycles of cell degeneration and regeneration because certain repair signals were elevated while other structural and adhesion molecules were downregulated. The systems biology approach can help enhance our basic knowledge of biological processes, and contribute to a deeper understanding of pathophysiological mechanisms, as well as the identification of potential biomarkers of disease.

Serum semaphorin 4C as a diagnostic biomarker in breast cancer: A multicenter retrospective study

Background

To date, there is no approved blood‐based biomarker for breast cancer detection. Herein, we aimed to assess semaphorin 4C (SEMA4C), a pivotal protein involved in breast cancer progression, as a serum diagnostic biomarker.

Methods

We included 6,213 consecutive inpatients from Tongji Hospital, Qilu Hospital, and Hubei Cancer Hospital. Training cohort and two validation cohorts were introduced for diagnostic exploration and validation. A pan‐cancer cohort was used to independently explore the diagnostic potential of SEMA4C among solid tumors. Breast cancer patients who underwent mass excision prior to modified radical mastectomy were also analyzed. We hypothesized that increased pre‐treatment serum SEMA4C levels, measured using optimized in‐house enzyme‐linked immunosorbent assay kits, could detect breast cancer. The endpoints were diagnostic performance, including area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Post‐surgery pathological diagnosis was the reference standard and breast cancer staging followed the TNM classification. There was no restriction on disease stage for eligibilities.

Results

We included 2667 inpatients with breast lesions, 2378 patients with other solid tumors, and 1168 healthy participants. Specifically, 118 patients with breast cancer were diagnosed with stage 0 (5.71%), 620 with stage I (30.00%), 966 with stage II (46.73%), 217 with stage III (10.50%), and 8 with stage IV (0.39%). Patients with breast cancer had significantly higher serum SEMA4C levels than benign breast tumor patients and normal controls (P < 0.001). Elevated serum SEMA4C levels had AUC of 0.920 (95% confidence interval [CI]: 0.900–0.941) and 0.932 (95%CI: 0.911–0.953) for breast cancer detection in the two validation cohorts. The AUCs for detecting early‐stage breast cancer (n = 366) and ductal carcinoma in situ (n = 85) were 0.931 (95%CI: 0.916–0.946) and 0.879 (95%CI: 0.832–0.925), respectively. Serum SEMA4C levels significantly decreased after surgery, and the reduction was more striking after modified radical mastectomy, compared with mass excision (P < 0.001). The positive rate of enhanced serum SEMA4C levels was 84.77% for breast cancer and below 20.75% for the other 14 solid tumors.

Conclusions

Serum SEMA4C demonstrated promising potential as a candidate biomarker for breast cancer diagnosis. However, validation in prospective settings and by other study groups is warranted.

Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Identification of a Profile of Neutrophil-Derived Granule Proteins in the Surface of Gold Nanoparticles after Their Interaction with Human Breast Cancer Sera

It is well known that the interaction of a nanomaterial with a biological fluid leads to the formation of a protein corona (PC) surrounding the nanomaterial. Using standard blood analyses, alterations in protein patterns are difficult to detect. PC acts as a “nano-concentrator” of serum proteins with affinity for nanoparticles’ surface. Consequently, characterization of PC could allow detection of otherwise undetectable changes in protein concentration at an early stage of a disease, such as breast cancer (BC). Here, we employed gold nanoparticles (AuNPs_diameter: 10.02 ± 0.91 nm) as an enrichment platform to analyze the human serum proteome of BC patients (n = 42) and healthy controls (n = 42). Importantly, the analysis of the PC formed around AuNPs after their interaction with serum samples of BC patients showed a profile of proteins that could differentiate breast cancer patients from healthy controls. These proteins developed a significant role in the immune and/or innate immune system, some of them being neutrophil-derived granule proteins. The analysis of the PC also revealed serum proteome alterations at the subtype level.

Design of a New Peptide Substrate Probe of the Putative Biomarker Legumain with Potential Application in Prostate Cancer Diagnosis Ex Vivo

The lysosomal endoprotease legumain (asparaginyl endoprotease) has been proposed as a putative biomarker in prostate tumours, in which the enzyme is markedly overexpressed. Overexpression, coupled with highly selective specificity for cleavage of substrates at the C-terminus of asparagine (Asn) residues, make legumain an attractive biochemical target for potential diagnosis, prognosis and treatment. We report the design, synthesis, characterisation and preliminary evaluation of a new rhodamine-B (Rho-B)-labelled legumain peptide substrate probe5[Rho-Pro-Ala-Asn-PEG-AQ(4-OH)] and its selective targeting to lysosomes in PC3 prostate cancer cells. Probe5was efficiently activated by recombinant human legumain to afford the high quantum yield reporter fluorophore tripeptide4b(Rho-Pro-Ala-Asn-OH) with concomitant release of intense fluorescence. Furthermore, probe5was activated upon incubation with homogenates derived from fresh-frozen tissue material of prostatectomy specimens. Probe5represents a new viable biochemical tool for probing the activity of legumain with the potential to be used in ex vivo diagnostics in the cancer pathology laboratory.

Systematic Glycolytic Enzyme Activity Analysis from Human Serum with PEP Technology

A functional proteomics technology was used to systematically monitor metabolic enzyme activities from resolved serum proteins produced by a modified 2-D gel separation and subsequent Protein Elution Plate, a method collectively called PEP. Both qualitative and quantitative differences in the metabolic enzyme activity could be detected between cancer patient and control group, providing excellent biomarker candidates for cancer diagnosis and drug development. This technology has a wide range of applications; it can be used for rapid functional protein purification and characterization as well as drug target identification and validation. The ability for the PEP technology to efficiently separate and recover functional proteins makes it useful for the analysis of any proteins and its variants; this is especially advantageous for enzyme families with large number of enzymes such as protein kinases, phosphatases, proteases, and metabolic enzymes.

Blood-based protein biomarkers in breast cancer

Breast cancer (BCa) is a significant healthcare problem on women worldwide. Thus, early detection is very important to reduce mortality. Furthermore, better BCa prognosis could improve selection of patients eligible for adjuvant therapy. New markers for early diagnosis, accurate prognosis and prediction of response to treatment are necessary to improve BCa care. The present review summarizes important aspects of the potential usefulness of modern technologies, strategies, and scientific findings in proteomic research for discovery of breast cancer-associated blood-based protein biomarkers in the clinic.

Biomarker and Drug Target Discovery Using Quantitative Proteomics Post-Intracerebral Hemorrhage Stroke in the Rat Brain

The pathological mechanisms of acute intracerebral hemorrhage (ICH) remain unknown and unverified. In the present study, we used quantitative proteomics to elucidate the pathological mechanisms and to identify novel biomarker and therapeutic target candidates via tissue proteome in a rat model of acute ICH. Rats were experimentally induced with ICH (n = 6) or Sham (n = 6), and their brain tissue was obtained by 24 h. The TMT-LC–MS/MS-based proteomics approach was used to quantify the differential proteomes across brain tissue, and the results were further analyzed by ingenuity pathway analysis to explore canonical pathways and the relationship involved in the uploaded data. Upon quantification, we found that 96 secreted proteins that were identified in the ICH 24-h group were significantly different those in the control group (P < 0.05); among these proteins, 57 increased and 39 decreased in abundance. Bioinformatic analyses of differentially expressed proteins demonstrated that the protein localization and ERK1 and ERK2 cascade were the top two biological processes with the highest concentrations of differentially proteins. The top protein-protein action network with high confidence levels of protein was the albumin and ERK signaling pathways. Albumin, ERK, and p-ERK were assessed in brain tissue by western blot analysis, and higher expression levels of albumin and p-ERK were observed in the ICH group. Our proteomic results highlight important change in the biological processes of ERK1 and ERK2 cascade, which are possible targets for future interventions of ICH. To our knowledge, this study provides in-depth analysis of ICH in brain tissue, and we propose 96 new biomarker candidates for ICH, including albumin and ERK.