In search of the altering salivary proteome in metastatic breast and ovarian cancers

Development and validation of a model and nomogram for breast cancer diagnosis based on quantitative analysis of serum disease-specific haptoglobin N-glycosylation

BACKGROUND

A better diagnostic marker is in need to distinguish breast cancer from suspicious breast lesions. The abnormal glycosylation of haptoglobin has been documented to assist cancer diagnosis. This study aims to evaluate disease-specific haptoglobin (DSHp)-β N-glycosylation as a potential biomarker for breast cancer diagnosis.

METHODS

DSHp-β chains of 497 patients with suspicious breast lesions who underwent breast surgery were separated from serum immunoinflammatory-related protein complexes. DSHp-β N-glycosylation was quantified by mass spectrometric analysis. After missing data imputation and propensity score matching, patients were randomly assigned to the training set (n = 269) and validation set (n = 113). Logistic regression analysis was employed in model and nomogram construction. The diagnostic performance was analyzed with receiver operating characteristic and calibration curves.

RESULTS

95 N-glycopeptides at glycosylation sites N207/N211, N241, and N184 were identified in 235 patients with benign breast diseases and 262 patients with breast cancer. DSHp-β N-tetrafucosyl and hexafucosyl were significantly increased in breast cancer compared with benign diseases (p < 0.001 and p = 0.001, respectively). The new diagnostic model and nomogram included GN2F2, G6N3F6, GN2FS at N184, G-N&G2S2, G2&G3NFS, G2N3F, GN3 at N207/N211, CEA, CA153, and could reliably distinguish breast cancer from benign diseases. For the training set, validation set, and training and validation sets, the area under the curves (AUCs) were 0.80 (95% CI: 0.75-0.86, specificity: 87%, sensitivity: 62%), 0.77 (95% CI:0.69-0.86, specificity: 75%, sensitivity: 69%), and 0.80 (95% CI:0.76-0.84, specificity: 77%, sensitivity: 68%), respectively. CEA, CA153, and their combination yielded AUCs of 0.62 (95% CI: 0.56-0.67, specificity: 29%, sensitivity: 90%), 0.65 (95% CI: 0.60-0.71, specificity: 74%, sensitivity: 51%), and 0.67 (95% CI: 0.62-0.73, specificity: 60%, sensitivity: 68%), respectively.

CONCLUSIONS

The combination of DSHp-β N-glycopeptides, CEA, and CA153 might be a better serologic marker to differentiate between breast cancer and benign breast diseases. The dysregulated N-glycosylation of serum DSHp-β could provide insights into breast tumorigenesis.

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.

Targeted proteomics using parallel reaction monitoring confirms salivary proteins indicative of metastatic triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype due to the absence of hormonal receptors. Our study aimed to identify and determine the effectiveness of salivary proteins as candidate markers for metastatic TNBC subtype using parallel reaction monitoring mass spectrometry (PRM-MS). Three salivary proteins (lipocalin-1, SMR3B, and plastin-2) that showed significant differential expression in label-free quantitation (LFQ) between TNBC (N = 6) and health subjects (HS; N = 6) were selected for further validation. The developed PRM assay was used to quantify peptides GLST and NNLE (lipocalin-1), VYAL and MINL (Plastin-2) and GPYP, and IPPP (SMR3B) on a different cohort of TNBC patients (N = 20) and HS (N = 20) for evaluating their discriminating performances. Quantitative validation using PRM correlated well with the LFQ results, and 5 peptides from three proteins showed a similar up-or down-regulation. Subsequently, these proteins were validated by Western blot analysis. Compared to one protein's performance as an individual marker, the five-signature panel with salivary GLST, VYAL, MINL, GPYP, and IPPP achieved better performance in differentiating aggressive TNBC and HS with sensitivity (80%) and specificity (95%). Targeted proteomic analysis of the prioritized proteins highlights a peptide-based signature in saliva as the potential predictor to distinguish between TNBC and HS. SIGNIFICANCE OF THE STUDY: This study was designed to identify and quantify potential markers in saliva from the triple-negative breast cancer (TNBC) patients using parallel reaction monitoring assay. Three salivary proteins, Lipocalin-1 (LCN-1), Submaxillary androgen-regulated protein 3B (SMR3B), and Plastin-2 (LCP-1) selected in the discovery-phase were further quantified by targeted proteomics and Western blots. The salivary proteins successfully differentiated TNBC patients from healthy subjects with a sensitivity (80%) and specificity (95%).

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis

BACKGROUND

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

METHODS

We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

RESULTS

Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

CONCLUSION

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Oxygen and metabolic reprogramming in the tumor microenvironment influences metastasis homing

Tumor metastasis is the leading cause of cancer mortality, often characterized by abnormal cell growth and invasion to distant organs. The cancer invasion due to epithelial to mesenchymal transition is affected by metabolic and oxygen availability in the tumor-associated micro-environment. A precise alteration in oxygen and metabolic signaling between healthy and metastatic cells is a substantial probe for understanding tumor progression and metastasis. Molecular heterogeneity in the tumor microenvironment help to sustain the metastatic cell growth during their survival shift from low to high metabolic-oxygen-rich sites and reinforces the metastatic events. This review highlighted the crucial role of oxygen and metabolites in metastatic progression and exemplified the role of metabolic rewiring and oxygen availability in cancer cell adaptation. Furthermore, we have also addressed potential applications of altered oxygen and metabolic networking with tumor type that could be a signature pattern to assess tumor growth and chemotherapeutics efficacy in managing cancer metastasis.

Clinical Proteomics of Biofluids in Haematological Malignancies

Since the emergence of high-throughput proteomic techniques and advances in clinical technologies, there has been a steady rise in the number of cancer-associated diagnostic, prognostic, and predictive biomarkers being identified and translated into clinical use. The characterisation of biofluids has become a core objective for many proteomic researchers in order to detect disease-associated protein biomarkers in a minimally invasive manner. The proteomes of biofluids, including serum, saliva, cerebrospinal fluid, and urine, are highly dynamic with protein abundance fluctuating depending on the physiological and/or pathophysiological context. Improvements in mass-spectrometric technologies have facilitated the in-depth characterisation of biofluid proteomes which are now considered hosts of a wide array of clinically relevant biomarkers. Promising efforts are being made in the field of biomarker diagnostics for haematologic malignancies. Several serum and urine-based biomarkers such as free light chains, β-microglobulin, and lactate dehydrogenase are quantified as part of the clinical assessment of haematological malignancies. However, novel, minimally invasive proteomic markers are required to aid diagnosis and prognosis and to monitor therapeutic response and minimal residual disease. This review focuses on biofluids as a promising source of proteomic biomarkers in haematologic malignancies and a key component of future diagnostic, prognostic, and disease-monitoring applications.

The development and clinical applications of proteomics: an Indian perspective

INTRODUCTION

Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic.

AREAS COVERED

This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed.

EXPERT OPINION

The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

Changes in Serum and Salivary Proteins in Canine Mammary Tumors

The aim of this study was to evaluate changes in serum and saliva proteomes in canine mammary tumors (CMT) using a high-throughput quantitative proteomic analysis in order to potentially discover possible biomarkers of this disease. Proteomes of paired serum and saliva samples from healthy controls (HC group, n = 5) and bitches with CMT (CMT group, n = 5) were analysed using a Tandem Mass Tags-based approach. Twenty-five dogs were used to validate serum albumin as a candidate biomarker in an independent sample set. The proteomic analysis quantified 379 and 730 proteins in serum and saliva, respectively. Of those, 35 proteins in serum and 49 in saliva were differentially represented. The verification of albumin in serum was in concordance with the proteomic data, showing lower levels in CMT when compared to the HC group. Some of the modulated proteins found in the present study such as haptoglobin or S100A4 have been related to CMT or human breast cancer previously, while others such as kallikrein-1 and immunoglobulin gamma-heavy chains A and D are described here for the first time. Our results indicate that saliva and serum proteomes can reflect physiopathological changes that occur in CMT in dogs and can be a potential source of biomarkers of the disease.