Subunit-specific mass spectrometry method identifies haptoglobin subunit alpha as a diagnostic marker in non-small cell lung cancer

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer

BACKGROUND

Among gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups.

METHODS

Thirty-four patients, categorized into three groups-10 with EC, 12 with Hy, and 12 CO-between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS).

RESULTS

In all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance.

CONCLUSION

The identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery

BACKGROUND

The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.

METHODS

Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.

FINDINGS

A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.

INTERPRETATION

Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.

FUNDING

Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

The hidden potential of glycomarkers: Glycosylation studies in the service of cancer diagnosis and treatment

Changes in the glycosylation process appear early in carcinogenesis and evolve with the growth and spread of cancer. The correlation of the characteristic glycosylation signature with the tumor stage and the appropriate therapy choice is an important issue in translational medicine. Oncologists also pay attention to extracellular vesicles as reservoirs of new cancer glycomarkers that can be potent for cancer diagnosis/prognosis. In this review, we recall glycomarkers used in oncology and show their new glycoforms of improved clinical relevance. We summarize current knowledge on the biological functions of glycoepitopes in cancer-derived extracellular vesicles and their potential use in clinical practice. Is glycomics a future of cancer diagnosis? It may be, but in combination with other omics analyses than alone.

Serum HSP90-Alpha and Oral Squamous Cell Carcinoma : A Prospective Biomarker

AIM

Current study aims to perform differential protein expression analysis of serum samples from Oral squamous cell carcinoma (OSCC) patients and healthy controls in search of potential diagnostic and/or prognostic biomarker(s).

OBJECTIVE

OSCC is diagnosed late, resulting in poor survival and high mortality. Identification of non-invasive prognostic biomarker is of utmost importance for early diagnosis and proper management of the disease; hence we used proteomic approach to identify potential biomarkers from serum.

METHODS

Serum samples (OSCC n=45 and control n=30) were depleted and proteins were separated using 2-D gel electrophoresis followed by identification by mass spectrometric analysis. Gene expression analysis of identified proteins in malignant and normal tissue was also performed to complement proteomics studies.

RESULTS

Among differentially expressed proteins, a noteworthy observation was up regulation of Heat shock protein alpha (HSP90α) from serum of oral cancer patients. We also observed elevated levels of Haptoglobin (HP) along with down regulation of Type II keratin cytoskeletal 1(KRT1) and serum Albumin (ALB) in oral cancer patients. Gene expression studies of identified proteins in malignant and normal tissue revealed a similar pattern with the exception of KRT1. We believe that elevated levels of serum HSP90 alpha might be used as a potential biomarker.

CONCLUSION

Our findings suggest the contribution of HSP90 alpha and other identified proteins in oral pathology as pro/anti apoptotic modulators, thus they are being considered as predictive biomarkers.

Proteomic Profiling for Serum Biomarkers in Mice Exposed to Ionizing Radiation

In response to large-scale radiological incidents, rapid, accurate, and early triage biodosimeters are urgently required. In this study, we investigated candidate radiation-responsive biomarkers using proteomics approaches in mouse models. A total of 452 dysregulated proteins were identified in the serum samples of mice exposed to 0, 2, 5.5, 7, and 8 Gy at 6, 24, and 72 hours postirradiation. Ninety-eight proteins, including 46 at 6 hours, 36 at 24 hours, and 36 at 72 hours, were identified as radiation-responsive proteins (RRPs). Gene Ontology analysis showed the RRPs were involved in proteolysis, extracellular space, hydrolase activity, and carbohydrate binding. Kyoto Encyclopedia of Genes and Genome enrichment showed the RRPs were regulated in "the pentose phosphate pathway," "the proteasome," and "AGE-RAGE signaling in diabetic complications." There were 3 proteins changed and overlapped at all the 3 time points, 8 proteins changed at 6 and 24 hours, 4 proteins changed at 24 and 72hours, and 2 proteins changed at both 6 and 72 hours. Of these proteins, ORM2, HP, SAA1, SAA2, MBL2, COL1A1, and APCS were identified as candidate biomarkers for biodosimeter-based diagnosis through Pearson correlation analysis.

Estudio proteómico 2DE-DIGE en plasma sanguíneo de pacientes en etapa infantil con leucemia linfoblástica aguda

En Colombia, durante la última década la leucemia linfoblástica aguda (LLA) ha sido el cáncer con mayor incidencia, siendo más del 40% de las muertes por cáncer en menores de edad atribuidas a esta enfermedad. Entre los factores que influyen en estas cifras, el diagnóstico tardío es tal vez el factor más sensible que afecta de manera negativa el éxito del tratamiento. Esta investigación se centró en el estudio del proteoma plasmático de niños colombianos diagnosticados con LLA tipo B, dada su alta incidencia, en comparación con controles en la búsqueda de proteínas que podrían tener potencialidad a ser clasificadas como biomarcadores de diagnóstico. Ahora bien, en vista de los avances en las herramientas proteómicas y de espectrometría de masas y sabiendo que son una alternativa para abordar la complejidad molecular de enfermedades como el cáncer, utilizamos una aproximación proteómica basada en una separación por electroforesis bidimensional diferencial (2DE-DIGE) con posterior separación por cromatografía líquida acoplada a espectrometría de masas en tándem. Se encontraron 8 proteínas con expresión diferencial en plasma de pacientes con LLA-B, entre las cuales resaltan la serotransferrina, la Alfa-1-antitripsina, la haptoglobina, la α2-glicoproteína de zinc y la complemento C3.

Inflammatory Markers and MicroRNAs: The Backstage Actors Influencing Prognosis in Colorectal Cancer Patients

BACKGROUND

Colorectal cancer (CRC) remains a deadly disease, afflicting the lives of millions worldwide. The prognosis of CRC patients is best predicted by surgical resection and pathological analysis of specimens. Emerging evidence has attributed a significant role to inflammatory markers and microRNAs (miRNAs) in the prognosis and survival of CRC patients.

AIM

Here, we review the literature on inflammatory markers and miRNAs with an established role on survival rates, response to systemic chemotherapy, and other clinic-pathological parameters in CRC patients.

RESULTS

Our literature review revealed a critical role of inflammatory markers—specifically, the acute-phase proteins, inflammatory cytokines, and blood cell ratios—on prognostic outcomes in CRC patients. MiRNAs, on the other hand, were useful in predicting prognosis and clinical response and accordingly stratifying CRC patients for optimal drug selection.

CONCLUSION

These biomarkers are easily measured in routine blood exams and can be used in adjunct to the tumor-node-metastasis (TNM) staging system to identify high-risk patients and those who are more likely to benefit from chemotherapy and other targeted therapies. However, more prospective studies are needed for the validation of these discussed prognostic and predictive biomarkers.

High serum haptoglobin level is associated with tumor progression and predicts poor prognosis in non-small cell lung cancer

The overall survival time of non-small cell lung cancer (NSCLC) has not improved dramatically in recent decades. An important reason is the lacking of valuable biomarkers. Haptoglobin was reported to have activities of anti-inflammatory, anti-oxidant, autoimmune and tumor angiogenesis. However its potential role as a tumor biomarker was not well recognized. We used an immunoturbidimetry method to measure serum haptoglobin levels in 205 NSCLC patients, and 210 normal healthy controls. We found that serum haptoglobin levels were significantly elevated in NSCLC patients compared with normal healthy controls (1.985±1.039 mg/mLvs. 0.922 ± 0.495 mg/mL, respectively, P < 0.0001). Higher serum haptoglobin levels were associated with advanced TNM stage, lymph node metastasis, and distant metastasis. Area under receiver operating characteristic curve (ROC) for serum haptoglobin was 0.809 (95% CI: 0.767–0.852) at a specificity of 0.881 and sensitivity of 0.639. The optimal cut-off value of haptoglobin was 1.495 mg/mL for discriminating NSCLC from normal healthy controls. Kaplan-Meier log rank analysis revealed that the higher serum haptoglobin levels group had a poorer overall survival compared with lower haptoglobin group (the median survival was 12.0 weeks, 26.0 weeks, respectively, P < 0.01). Further univariate and multivariate Cox regression analysis showed that serum haptoglobin was an independent risk factor of prognosis of NSCLC patients (P < 0.01, P = 0.01, respectively). In conclusion, our study suggests that serum haptoglobin may act as useful clinical serological biomarkers in progression and prognostic evaluation in NSCLC.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Automated Microchromatography Enables Multiplexing of Immunoaffinity Enrichment of Peptides to Greater than 150 for Targeted MS-Based Assays

Immunoaffinity enrichment of peptides coupled with analysis by stable isotope dilution multiple reaction mass spectrometry has been shown to have analytical performance and detection limits suitable for many biomarker verification studies and biological applications. Prior studies have shown that antipeptide antibodies can be multiplexed up to 50 in a single assay without significant loss of performance. Achieving higher multiplex levels is relevant to all studies involving precious biological material as this minimizes the amount of sample that must be consumed to measure a given set of analytes and reduces the assay cost per analyte. Here we developed automated methods employing the Agilent AssayMAP Bravo microchromatography platform and used these methods to characterize the performance of immunoaffinity enrichment of peptides up to multiplex levels of 172. Median capture efficiency for the target peptides remained high (88%) even at levels of 150-plex and declined to 70% at 172-plex compared to antibody performance observed at standard lower multiplex levels (n = 25). Subsequently, we developed and analytically characterized a multiplexed immuno-multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) assay (n = 110) and applied it to measure candidate protein biomarkers of cardiovascular disease in plasma of patients undergoing planned myocardial infarction. The median lower limit of detection of all peptides was 71.5 amol/μL (nM), and the coefficient of variation (CV) was less than 15% at the lower limit of quantification. The results demonstrate that high multiplexed immuno-MRM-MS assays are readily achievable using the optimized sample processing and peptide capture methods described here.

Serum haptoglobin as a novel molecular biomarker predicting colorectal cancer hepatic metastasis

Early detection of liver metastasis is important for improving colorectal cancer (CRC) patient survival. Our previous studies showed haptoglobin was highly expressed in primary CRC tissues, especially in heterochronous metastatic cases. Here, we assessed the potential of serum haptoglobin (sHP) as a biomarker for early detection of CRC liver metastasis by evaluating the sHP in 475 CRC patients and 152 healthy volunteers. In the training set (250 cases), sHP level in CRC-M1 (1773.18 ± 690.25 ng/mL) were significantly increased as compared to in CRC-M0 (1544.37 ± 1497.65 ng/mL) or healthy (917.76 ± 571.59 ng/mL). And the high sHP level was correlated with poor survival. Logistic regression analysis revealed that sHP, serum carcinoembryonic antigen (sCEA) and serum carbohydrate antigen 19.9 (sCA19.9) level were the significant parameters for detecting liver metastasis. In leave-one-out-cross-validation, these three markers resulted in 89.1% sensitivity and 85.8% specificity for hepatic metastasis detection. In an independent test set (225 cases), receiver operating characteristic curve analysis of sHP in CRC liver metastasis showed an area under the curve of 0.735, with a sensitivity of 87.2% and a specificity of 59.9%. Combination of sHP, sCEA and sCA19.9 improved diagnostic accuracy to 0.880, with a sensitivity of 88.5% and a specificity of 87.8%. Silencing of HP by specific shRNA significantly inhibited the LOVO and SW620 cell invasion, and suppressed xenograft tumor invasive growth. In summary, these results demonstrate that sHP is associated with poor prognosis of CRC patients and that HP promotes colorectal cancer cell invasion. sHP combining with sCA19.9 and sCEA may be used as accurate predictors of CRC liver metastasis.

Targeted proteomics of solid cancers: from quantification of known biomarkers towards reading the digital proteome maps

The concept of personalized medicine includes novel protein biomarkers that are expected to improve the early detection, diagnosis and therapy monitoring of malignant diseases. Tissues, biofluids, cell lines and xenograft models are the common sources of biomarker candidates that require verification of clinical value in independent patient cohorts. Targeted proteomics - based on selected reaction monitoring, or data extraction from data-independent acquisition based digital maps - now represents a promising mass spectrometry alternative to immunochemical methods. To date, it has been successfully used in a high number of studies answering clinical questions on solid malignancies: breast, colorectal, prostate, ovarian, endometrial, pancreatic, hepatocellular, lung, bladder and others. It plays an important role in functional proteomic experiments that include studying the role of post-translational modifications in cancer progression. This review summarizes verified biomarker candidates successfully quantified by targeted proteomics in this field and directs the readers who plan to design their own hypothesis-driven experiments to appropriate sources of methods and knowledge.

[Research Progress of Biomakers Proteomics-based in Lung Cancer]

蛋白组学技术可以应用于癌症研究来检测差异蛋白质表达以发现癌症生物标志物。肺癌的生物标志物在肺癌早期诊断、指导治疗和预后监测方面起着关键作用。因此，迫切需要确定新的早期诊断和预后指标以开辟新的治疗途径。本文简要介绍了基于蛋白质组学的肺癌生物标志物的最新研究报告。他包括作为诊断、预后和预测性的生物标志物，以及基于最近发表文献的基础上和我们所做的相关工作的总结。

Modeling discrete survival time using genomic feature data

Researchers have recently shown that penalized models perform well when applied to high-throughput genomic data. Previous researchers introduced the generalized monotone incremental forward stagewise (GMIFS) method for fitting overparameterized logistic regression models. The GMIFS method was subsequently extended by others for fitting several different logit link ordinal response models to high-throughput genomic data. In this study, we further extended the GMIFS method for ordinal response modeling using a complementary log-log link, which allows one to model discrete survival data. We applied our extension to a publicly available microarray gene expression dataset (GSE53733) with a discrete survival outcome. The dataset included 70 primary glioblastoma samples from patients of the German Glioma Network with long-, intermediate-, and short-term overall survival. We tested the performance of our method by examining the prediction accuracy of the fitted model. The method has been implemented as an addition to the ordinalgmifs package in the R programming environment.

Lung Cancer Biomarkers

Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.