Identification of novel serum peptides biomarkers for female breast cancer patients in Western China

Clinical Peptidomics: Advances in Instrumentation, Analyses, and Applications

Extensive effort has been devoted to the discovery, development, and validation of biomarkers for early disease diagnosis and prognosis as well as rapid evaluation of the response to therapeutic interventions. Genomic and transcriptomic profiling are well-established means to identify disease-associated biomarkers. However, analysis of disease-associated peptidomes can also identify novel peptide biomarkers or signatures that provide sensitive and specific diagnostic and prognostic information for specific malignant, chronic, and infectious diseases. Growing evidence also suggests that peptidomic changes in liquid biopsies may more effectively detect changes in disease pathophysiology than other molecular methods. Knowledge gained from peptide-based diagnostic, therapeutic, and imaging approaches has led to promising new theranostic applications that can increase their bioavailability in target tissues at reduced doses to decrease side effects and improve treatment responses. However, despite major advances, multiple factors can still affect the utility of peptidomic data. This review summarizes several remaining challenges that affect peptide biomarker discovery and their use as diagnostics, with a focus on technological advances that can improve the detection, identification, and monitoring of peptide biomarkers for personalized medicine.

Bioinformatics and network biology approach to identifying type 2 diabetes genes and pathways that influence the progression of breast cancer

Breast cancer is the second most prevalent malignancy affecting women. Postmenopausal women breast tumor is one of the top causes of death in women, accounting for 23% of cancer cases. Type 2 diabetes, a worldwide pandemic, has been connected to a heightened risk of several malignancies, although its association with breast cancer is still uncertain. In comparison to non-diabetic women, women with T2DM had a 23% elevated likelihood of developing breast cancer. It is difficult to determine causative or genetic susceptibility that connect T2DM and breast cancer. We created a large-scale network-based quantitative approach employing unbiased methods to discover abnormally amplified genes in both T2DM and breast cancer, to solve these issues. We performed transcriptome analysis to uncover identical genetic biomarkers and pathways to clarify the connection between T2DM and breast cancer patients. In this study, two RNA-seq datasets (GSE103001 and GSE86468) from the Gene Expression Omnibus (GEO) are used to identify mutually differentially expressed genes (DEGs) for breast cancer and T2DM, as well as common pathways and prospective medicines. Firstly, 45 shared genes (30 upregulated and 15 downregulated) between T2D and breast cancer were detected. We employed gene ontology and pathway enrichment to characterize prevalent DEGs' molecular processes and signal transduction pathways and observed that T2DM has certain connections to the progression of breast cancer. Using several computational and statistical approaches, we created a protein-protein interactions (PPI) network and revealed hub genes. These hub genes can be potential biomarkers, which may also lead to new therapeutic strategies for investigated diseases. We conducted TF-gene interactions, gene-microRNA interactions, protein-drug interactions, and gene-disease associations to find potential connections between T2DM and breast cancer pathologies. We assume that the potential drugs that emerged from this study could be useful therapeutic values. Researchers, doctors, biotechnologists, and many others may benefit from this research.

Construction of the optimization prognostic model based on differentially expressed immune genes of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common pathology subtype of lung cancer. In recent years, immunotherapy, targeted therapy and chemotherapeutics conferred a certain curative effects. However, the effect and prognosis of LUAD patients are different, and the efficacy of existing LUAD risk prediction models is unsatisfactory.

Methods

The Cancer Genome Atlas (TCGA) LUAD dataset was downloaded. The differentially expressed immune genes (DEIGs) were analyzed with edgeR and DESeq2. The prognostic DEIGs were identified by COX regression. Protein-protein interaction (PPI) network was inferred by STRING using prognostic DEIGs with p value< 0.05. The prognostic model based on DEIGs was established using Lasso regression. Immunohistochemistry was used to assess the expression of FERMT2, FKBP3, SMAD9, GATA2, and ITIH4 in 30 cases of LUAD tissues.

Results

In total,1654 DEIGs were identified, of which 436 genes were prognostic. Gene functional enrichment analysis indicated that the DEIGs were involved in inflammatory pathways. We constructed 4 models using DEIGs. Finally, model 4, which was constructed using the 436 DEIGs performed the best in prognostic predictions, the receiver operating characteristic curve (ROC) was 0.824 for 3 years, 0.838 for 5 years, 0.834 for 10 years. High levels of FERMT2, FKBP3 and low levels of SMAD9, GATA2, ITIH4 expression are related to the poor overall survival in LUAD (p < 0.05). The prognostic model based on DEIGs reflected infiltration by immune cells.

Conclusions

In our study, we built an optimal prognostic signature for LUAD using DEIGs and verified the expression of selected genes in LUAD. Our result suggests immune signature can be harnessed to obtain prognostic insights.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07911-8.

Fibrinogen alpha chain promotes the migration and invasion of human endometrial stromal cells in endometriosis through focal adhesion kinase/protein kinase B/matrix metallopeptidase 2 pathway†

Fibrinogen alpha chain (FGA), a cell adhesion molecule, contains two arginyl-glycyl-aspartic acid (RGD) cell adhesion sequences. Our previous study demonstrated that FGA, as an up-regulated protein in endometriosis (EM), was closely related to disease severity and involved in the development of EM. However, the biological functions and underlying mechanism of FGA in EM have not been fully understood. To explore the roles of FGA in EM, we analyzed the effects of FGA on the biological behaviors of human primary eutopic endometrial stromal cells (EuESC). The results indicated FGA knockdown suppressed the migration and invasion ability of EuESC, which also altered the distribution of cytoskeletal filamentous and cell morphology. Western blot analysis demonstrated that knockdown of FGA attenuated the migration-related protein levels of vimentin and matrix metallopeptidase 2 (MMP-2), but not integrin subunit alpha V (ITGAV) and integrin subunit beta 3 (ITGB3). Meanwhile, integrin-linked transduction pathways were detected. We found FGA knockdown significantly suppressed the expression of focal adhesion kinase (FAK) level and protein kinase B (AKT) phosphorylation, without extracellular-signal-regulated kinase (ERK) dependent pathways. Treatment with the AKT inhibitor MK2206 or RGD antagonist highly decreased the effects of FGA on the migration and invasion of EuESC. RGD antagonist treatment strongly inhibited FAK- and AKT-dependent pathways, but not ERK pathways. Our data indicated that FGA may enhance the migration and invasion of EuESC through RGD sequences binding integrin and activating the FAK/AKT/MMP-2 signaling pathway. This novel finding suggests that FGA may provide a novel potential approach to the treatment of EM, which provides a new way to understand the pathogenesis of EM.

Isoform 1 of Fibrinogen Alpha Chain Precursor is a Potential Biomarker for Steroid-Induced Osteonecrosis of the Femoral Head

PURPOSE

Early diagnosis is crucial to increase the chances of conservation treatment for patients with steroid-induced osteonecrosis of the femoral head (SIONFH). This study aimed to identify serum peptides as potential biomarkers to diagnose SIONFH.

EXPERIMENTAL DESIGN

The serum proteome of 32 SIONFH patients and 24 healthy controls are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS). Next, candidate biomarkers are identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Candidate biomarkers are then validated using ELISA and western blotting.

RESULTS

39 peaks are identified and the expression fold changes of seven peaks in the two groups are greater than 1.5. Three peaks (m/z: 1077.84 Da; m/z: 1061.78 Da; m/z: 1099.56 Da) tend to be upregulated, while four peaks (m/z: 3973.92 Da; m/z: 7766.53 Da; m/z: 3957.31 Da; m/z: 4212.02 Da) tend to be down-regulated in SIONFH patients. The peak for a 1077.84 Da peptide is identified as Isoform 1 of the Fibrinogen alpha chain precursor (FGA). ELISAs and western blot analyses reveal that the expression of FGA is significantly higher in SIONFH patients than healthy controls.

CONCLUSION AND CLINICAL RELEVANCE

FGA is overexpressed in SIONFH patients, and thus, is a novel potential biomarker for SIONFH.

Proteomic Analysis of Cerebrospinal Fluid From Patients With Extranodal NK-/T-Cell Lymphoma of Nasal-Type With Ethmoidal Sinus Metastasis

Objective: Extranodal natural killer /T-cell lymphoma (ENKTL) is an aggressive and unusual subtype of non-Hodgkin lymphoma (NHL) that it is related with the Epstein-Barr virus (EBV). CSF is considered as an ideal source of high-concenrtation disease-related proteins. We aimed at identifying the proteomic markers changes of CSF in ENKTL patients and used such changes to diagnose ENKTL.

Materials and methods: In this study, CSF samples were acquired from hospitalization patients from the Cancer Center of West China Hospital, Chengdu, China. Comparative proteomic profiling are commonly used to do label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). And in this study the same method was used to characterize the variety of proteins in ENKTL patients and none-ENKTL people.

Results: In the aggregate, 421 non-excrescent and functional proteins were identified among the samples. Of these proteins, 45 proteins quantified match the involved criteria. HRG, TIMP-1, SERPINA3, FGA, FGG, TF, FGB, APP, and AGT were significantly up-regulated.

Discussion: We discovered that some proteins were significantly up-regulated. Also, these proteins themselves or with others proteins may be potential markers to diagnose ENKTL. The changes of proteomics may be a potential method to precisely identify the pathogenesis of the ENKTL.

Fibrinogen alpha chain is up-regulated and affects the pathogenesis of endometriosis

RESEARCH QUESTION

In the group's previous study, fibrinogen alpha chain (FGA) was identified as an up-regulated differential protein that was highly expressed in women with endometriosis. The current study investigated the expression and effects of FGA in endometriosis. It also evaluated the effects of FGA on human endometrial stromal cells and studied the possible mechanism.

DESIGN

This was a cross-sectional analysis of FGA expression in plasma and endometrial tissue of matched eutopic and ectopic samples from women with endometriosis undergoing laparoscopic surgery and samples from women without endometriosis. Forty-four patients with endometriosis and 32 healthy control subjects who donated plasma for FGA analysis, including 26 matched cases of eutopic and ectopic endometria from endometriosis patients and 22 endometria from healthy control subjects, were analysed. The effects of FGA were studied in a human endometrial stromal cell line after transfection with FGA short interfering RNA (siRNA).

RESULTS

FGA concentrations in serum and expression in eutopic and ectopic endometrial tissue were significantly higher in women with endometriosis than controls (P < 0.05 and P < 0.01 respectively), whereas FGA expression was not significantly different in eutopic compared with ectopic endometrial tissues from the same patients. High FGA concentrations in serum were related to disease stage and ovarian involvement, but were not affected by age and menstrual cycle. The knockdown of FGA expression by FGA siRNA inhibited hEM15A cellular adhesion, migration and invasion, and attenuated matrix metalloproteinase-2 (MMP-2) expression.

CONCLUSIONS

High FGA expression in endometriosis was closely related to disease severity and affected cell adhesion, migration and invasion, which might play an important role in the pathogenesis of endometriosis.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.

RNA-Binding Motif Protein 6 is a Candidate Serum Biomarker for Pancreatic Cancer

PURPOSE

Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers.

EXPERIMENTAL DESIGN

The serum proteome of 22 PC patients, 12 pancreatitis patients (PP), and 45 healthy controls (HC) are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Next, a supervised neural network (SNN) algorithm model is established by ClinProTools and the candidate biomarker identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Finally, the candidate biomarker is validated in tissue samples.

RESULTS

The SNN algorithm model discriminates PC from HC with 92.97% sensitivity and 94.55% specificity. Seventy-six differentially expressed peptides are identified, seven of which are significantly different among PC, PP, and HC (p < 0.05). Only one peak (m/z: 1466.99) tends to be upregulated in samples from HC, PP, and PC, which is identified as region of RNA-binding motif protein 6 (RBM6). In subsequent tissue analysis, it is verified that RBM6 expression is significantly higher in PC tissues than paracancerous tissue.

CONCLUSIONS AND CLINICAL RELEVANCE

The results indicate that RBM6 might serve as a candidate diagnostic biomarker for PC.

CLINICAL RELEVANCE

Methods used in this study could generate serum peptidome profiles of PC, PP, and HC, and present an approach to identify potential biomarkers for diagnosis of this malignancy.

Elevated levels of circulating ITIH4 are associated with hepatocellular carcinoma with nonalcoholic fatty liver disease: from pig model to human study

BACKGROUND

Noninvasive biomarkers are urgently needed for optimal management of nonalcoholic fatty liver disease (NAFLD) for the prevention of disease progression into nonalcoholic steatohepatitis (NASH) and hepatocellular carcinoma (HCC). In order to identify the biomarkers, we generated the swine hepatocellular carcinoma (HCC) model associated with NAFLD and performed serum proteomics on the model.

METHODS

Microminipigs were fed a high-fat diet to induce NAFLD and a normal diet as the control. To induce HCC, diethylnitrosamine was intraperitoneally administered. Biopsied liver samples were histopathologically analyzed every 12 weeks. Serum proteins were separated by blue native two-dimensional gel electrophoresis and proteins of interest were subsequently identified by MALDI-TOF MS/MS. Human serum samples were analyzed to validate the candidate protein using antibody-mediated characterization.

RESULTS

In the NAFLD pigs, hepatic histology of nonalcoholic steatohepatitis (NASH) was observed at 36 weeks, and HCC developed at 60 weeks. Among serum proteins identified with MALDI-TOF MS/MS, serum inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4), an acute response protein which is secreted primarily by liver, was identified as the most characteristic protein corresponding with NAFLD progression and HCC development in the NAFLD pigs. With immunoassay, serum ITIH4 levels in the NAFLD pigs were chronologically increased in comparison with those in control animal. Furthermore, immunohistochemistry showed ITIH4 expression in hepatocytes also increased in both the cancer lesions and parenchyma as NAFLD progressed. Human study is also consistent with this observation because serum ITIH4 levels were significantly higher in HCC-NAFLD patients than in the simple steatosis, NASH, and virus-related HCC patients. Of note, HCC-NAFLD patients who had higher serum ITIH4 levels exhibited poorer prognosis after hepatectomy.

CONCLUSIONS

We established an HCC pig model associated with NAFLD. Serum proteomics on the swine HCC with NAFLD model implicated ITIH4 as a non-invasive biomarker reflecting NAFLD progression as well as subsequent HCC development. Most importantly, the results in the swine study have been validated in human cohort studies. Dissecting speciation of serum ITIH4 promises to have clinical utility in monitoring the disease.

Plasma Peptidome Pattern of Breast Cancer Using Magnetic Beads-Based Plasma Fractionation and MALDI-TOF MS: A Case Control Study in Egypt

Objective: The present study aimed to determine peptidome patterns in breast cancer (BC). Methods: We analyzed the plasma proteomic profiling of 80 BC patients and 50 healthy controls, using hydrophobic interaction chromatography magnetic beads (MB-HIC8) separation followed by Matrix assisted laser desorption ionization/ time of flight mass spectrometry (MALDI-TOF MS). Results: ClinProTools software identified 92 peaks that differed among the analyzed groups, 33 peaks were significantly different (P < 0.05). Of those, 22 peaks were up-regulated while 11 peaks were down-regulated in BC patients compared with the healthy controls. Three peptide ion signatures (m/z 1,570.31, 1,897.4 and 2,568.17) were provided by the Quick Classifier model to discriminate BC patients from healthy control subjects with 96.4% accuracy. External validation was performed by an independent group and this achieved a sensitivity of 100% and a specificity of 76.9%. Conclusion: MALDI-TOF MS has good analytical performance in distinguishing BC patients from healthy controls.

Proteomic Screening for Serum Biomarkers for Cervical Cancer and Their Clinical Significance

Background

The present study aimed to determine serum markers for cervical cancer (CC) and to provide valuable references for clinical diagnosis and treatment.

Material/Methods

Serum samples were collected from age-matched healthy control women, and from female CC patients before and after surgery. Serum biomarkers were selected by comparing serum peptides profiles among the 3 groups by magnetic bead-based weak cation – exchange chromatography fractionation combined with matrix-assisted laser desorption/ionization-time of flight mass spectrometry. Probable serum biomarkers for cervical cancer were then further identified by liquid chromatography-electrospray ionization-tandem mass spectrometry system and the identified proteins were verified by enzyme-linked immunosorbent assay (ELISA).

Results

Three peptide biomarkers were identified for distinguishing CC patients from normal individuals, and distinguishing preoperative CC patients from postoperative CC patients. Of these 3 identified protein peptide regions, 2 peptide regions – TKT (Peak 2, 2435.63 m/z, 499–524) and FGA (Peak 4, 2761.79 m/z, 603–629) – were identified as upregulated markers, and peptide region of APOA1 (Peak 9, 2575.3 m/z, 245–260) was identified as a downregulated biomarker in preoperative CC patients compared with healthy women.

Conclusions

The present study provides a new method for identifying potential serum biomarkers for CC patients.

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.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.

Histone-lysine N-methyltransferase SETD7 is a potential serum biomarker for colorectal cancer patients

Background

There is an urgent need for the identification of new, clinically useful biomarkers of CRC to enhance diagnostic and prognostic capabilities.

Methods

We performed proteomic profiling on serum samples from paired pre- and post-operative CRC patients, colorectal polyps patients and healthy controls using an approach combining magnetic bead-based weak cation exchange and matrix-assisted laser desorption ionization-time of flight mass spectrometry. We next performed liquid chromatography-electrospray ionization-tandem mass spectrometry to identify the proteins and selected potential biomarker based on bioinformatics analysis of the TCGA and GEO dataset. We examined SETD7 expression in serum and tissue samples by ELISA and immunohistochemistry respectively and explored the biological function of SETD7 in vitro.

Findings

85 differentially expressed peptides were identified. Five peptides showing the most significant changes in abundance across paired pre- and post-operation CRC patients, colorectal polyps patients and healthy controls were identified as peptide regions of FGA, MUC5AC and SETD7. Bioinformatics analysis suggested that the up-regulation of SETD7 in CRC is relatively specific. Validation studies showed that SETD7 expression increased from healthy controls to those with colorectal polyps and finally CRC patients, and decreased after surgery. The sensitivity and specificity of SETD7 were 92.17% and 81.08%, with a high diagnostic value (AUC = 0.9477). In addition, SETD7 expression was significantly correlated with tumor stage and microsatellite instability. Knockdown of SETD7 inhibited cancer cell proliferation, induced G1/S cell cycle arrest and increased apoptosis.

Interpretation

Our data indicate that SETD7 could serve as a potential diagnostic and prognostic biomarker for CRC.

Identification of serum proteins AHSG, FGA and APOA-I as diagnostic biomarkers for gastric cancer

Background

The development of clinically accessible biomarkers is critical for the early diagnosis of gastric cancer (GC) in patients. High-throughput proteomics techniques could not only effectively generate a serum peptide profile but also provide a new approach to identify potentially diagnostic and prognostic biomarkers for cancer patients.

Methods

In this study, we aim to identify potentially discriminating serum biomarkers for GC. In the discovery cohort, we screened potential biomarkers using magnetic-bead-based purification and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in 64 samples from 32 GC patients that were taken both pre- and post-operatively and 30 healthy volunteers that served as controls. In the validation cohort, the expression patterns and diagnostic values of serum FGA, AHSG and APOA-I were further confirmed by ELISA in 42 paired GC patients (pre- and post-operative samples from 16 patients with pathologic stage I/II and 26 with stage III/IV), 30 colorectal cancer patients, 30 hepatocellular carcinoma patients, and 28 healthy volunteers.

Results

ClinProTools software was used and annotated 107 peptides, 12 of which were differentially expressed among three groups (P < 0.0001, fold > 1.5). These 12 peptide peaks were further identified as FGA, AHSG, APOA-I, HBB, TXNRD1, GSPT2 and CAKP5. ELISA data suggested that the serum levels of FGA, AHSG and APOA-I in GC patients were significantly different compared with healthy controls and had favorable diagnostic values for GC patients. Moreover, we found that the serum levels of these three proteins were associated with TNM stages and could reflect tumor burden.

Conclusion

Our findings suggested that FGA, AHSG and APOA-I might be potential serum biomarkers for GC diagnosis.

Salivary Glycopatterns as Potential Biomarkers for Screening of Early-Stage Breast Cancer

OBJECTIVE

We systematically investigated and assessed the alterations of salivary glycopatterns and possibility as biomarkers for diagnosis of early-stage breast cancer.

DESIGN

Alterations of salivary glycopatterns were probed using lectin microarrays and blotting analysis from 337 patients with breast benign cyst or tumor (BB) or breast cancer (I/II stage) and 110 healthy humans. Their diagnostic models were constructed by a logistic stepwise regression in the retrospective cohort. Then, the performance of the diagnostic models were assessed by ROC analysis in the validation cohort. Finally, a double-blind cohort was tested to confirm the application potential of the diagnostic models.

RESULTS

The diagnostic models were constructed based on 9 candidate lectins (e.g., PHA-E+L, BS-I, and NPA) that exhibited significant alterations of salivary glycopatterns, which achieved better diagnostic powers with an AUC value >0.750 (p<0.001) for the diagnosis of BB (AUC: 0.752, sensitivity: 0.600, and specificity: 0.835) and I stage breast cancer (AUC: 0.755, sensitivity: 0.733, and specificity: 0.742) in the validation cohort. The diagnostic model of I stage breast cancer exhibited a high accuracy of 0.902 in double-blind cohort.

CONCLUSIONS

This study could contribute to the screening for patients with early-stage breast cancer based on precise alterations of salivary glycopatterns.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.