Identification of serum proteins as prognostic and predictive markers of colorectal cancer using surface enhanced laser desorption ionization-time of flight mass spectrometry

Circulating Biomarkers in Predicting Pathological Response to Neoadjuvant Therapy for Colorectal Cancer

Circulating biomarkers show promise in the management of many cancers. They have become the novel non-invasive approach to complement the current strategies in colorectal cancer (CRC) management. Their ability in guiding diagnosis, evaluating response to treatment, screening and prognosis is phenomenal, especially when it comes to their minimally invasive nature. These “liquid biopsies,” which show potential for replacing invasive surgical biopsies, provide useful information on the primary and metastatic disease by providing an insight into cancer biology. Analysis of blood and body fluids for circulating tumour DNA (ctDNA), carcinoembryonic antigen (CEA), circulating tumour cells (CTC), or circulating micro RNA (miRNA) shows potential for improving CRC management. Recognizing a predictive model to assess response to neoadjuvant chemotherapy would help in better patient selection. This review was conducted with the aim of outlining the use of circulatory biomarkers in current practice and their effectiveness in the management of patients having CRC with a focus on response to neoadjuvant therapy.

Tryptophan Catabolism and Response to Therapy in Locally Advanced Rectal Cancer (LARC) Patients

In locally advanced rectal cancer patients (LARC), preoperative chemoradiation improves local control and sphincter preservation. The response rate to treatment varies substantially between 20 and 30%, and it is an important prognostic factor. Indeed, nonresponsive patients are subjected to higher rates of local and distant metastases, and worse survival compared to patients with complete response. In the search of predictive biomarkers for response prediction to therapy in LARC patients, we found increased plasma tryptophan levels in nonresponsive patients. On the basis of plasma levels of 5-hydroxy-tryptophan and kynurenine, the activities of tryptophan 5-hydroxylase 1 (TPH1) and indoleamine-2,3-dioxygenases 1 (IDO1)/tryptophan-2,3-dioxygenase (TDO2) have been obtained and data have been correlated with gene expression profiles. We demonstrated that TDO2 overexpression in nonresponsive patients correlates with kynurenine plasma levels. Finally, through the gene expression and targeted metabolomic analysis in paired healthy mucosa-rectal cancer tumor samples, we evaluated the impact of tryptophan catabolism at tissue level in responsive and nonresponsive patients.

Predictive Biomarkers in Metastatic Colorectal Cancer: A Systematic Review

PURPOSE

The development and use of predictive biomarkers to guide treatment decisions are paramount not only for improving survival in patients with metastatic colorectal cancer (mCRC), but also for sparing them from unnecessary toxicity and reducing the economic burden of expensive treatments. We conducted a systematic review of published studies and evaluated the predictive biomarker landscape in the mCRC setting from a molecular and clinical viewpoint.

METHODS

Studies analyzing predictive biomarkers for approved therapies in patients with mCRC were identified systematically using electronic databases. Preclinical studies and those providing no relevant information were excluded.

RESULTS

A total of 173 studies comprising 148 biomarkers were selected for final analysis. Of all the biomarkers analyzed, 1.4% (two of 148) were explored in a prospective manner, whereas 98.6% (146 of 148) were evaluated in retrospective studies. Of the latter group, 78.8% (115 of 146) were not tested in subsequent phases, 9.6% (14 of 146) were tested in other retrospective cohorts, 8.9% (13 of 146) were retrospectively tested in at least one or more randomized cohorts, and only 2.7% (four of 146) were prospectively tested in a clinical trial. Finally, only 1.4% (two of 148) were validated sufficiently and are recognized as biomarkers for guiding treatment decision making in patients with mCRC. These markers were RAS mutational status for anti-EGFR antibodies and microsatellite instability status for anti-programmed cell death-1 drugs.

CONCLUSION

Despite notable efforts to identify predictive biomarkers for various therapies used in the mCRC setting, because of a lack of data beyond retrospective studies and successful biomarker-driven approaches, only two molecular biomarkers have thus far found their translation into the clinic, highlighting the imperative need for implementing novel strategies and additional research in this clinically important field.

Diagnostic value of apolipoprotein C-I, transthyretin and apolipoprotein C-III in gastric cancer

Diagnostic value of apolipoprotein C-I (ApoC-I), transthyretin (TTR) and ApoC-III in gastric cancer were evaluated. Retrospective analysis methods were used to collect 60 patients with gastric cancer first diagnosed in The First Affiliated Hospital of Jiaxing University. There were 60 patients with chronic atrophic gastritis in the benign lesion group and 60 healthy individuals in the control group. The expression levels of serum ApoC-I, TTR and ApoC-III was detected by enzyme-linked immunosorbent assay. Differences existed in the expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group, benign lesion group and control group (P<0.001), with the expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group being lower than that of the benign lesion group (P<0.05), and the expression levels of ApoC-I, TTR and ApoC-III in the benign lesion group being lower than that of the control group (P<0.05). The expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group were to a certain degree correlated with the clinical stage, lymph node metastasis and differentiation of patients in the gastric cancer group (P<0.05). The specificity and negative predictive value of combined detection were proven to be higher than the separate detection of the three factors (P<0.05). The detection of serum ApoC-I, TTR and ApoC-III was of great significance in the diagnosis of gastric cancer and the estimation of its severity. The method of combined detection is worth a further in-depth study as it could improve the specificity of diagnosis and have a higher negative predictive value.

Clinical predictive circulating peptides in rectal cancer patients treated with neoadjuvant chemoradiotherapy

Preoperative chemoradiotherapy is worldwide accepted as a standard treatment for locally advanced rectal cancer. Current standard of treatment includes administration of ionizing radiation for 45-50.4 Gy in 25-28 fractions associated with 5-fluorouracil administration during radiation therapy. Unfortunately, 40% of patients have a poor or absent response and novel predictive biomarkers are demanding. For the first time, we apply a novel peptidomic methodology and analysis in rectal cancer patients treated with preoperative chemoradiotherapy. Circulating peptides (Molecular Weight <3 kDa) have been harvested from patients' plasma (n = 33) using nanoporous silica chip and analyzed by Matrix-Assisted Laser Desorption/Ionization-Time of Flight mass spectrometer. Peptides fingerprint has been compared between responders and non-responders. Random Forest classification selected three peptides at m/z 1082.552, 1098.537, and 1104.538 that were able to correctly discriminate between responders (n = 16) and non-responders (n = 17) before therapy (T0) providing an overall accuracy of 86% and an area under the receiver operating characteristic (ROC) curve of 0.92. In conclusion, the nanoporous silica chip coupled to mass spectrometry method was found to be a realistic method for plasma-based peptide analysis and we provide the first list of predictive circulating biomarker peptides in rectal cancer patients underwent preoperative chemoradiotherapy.

Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies

INTRODUCTION

Treatment selection tools are needed to enhance the efficacy of targeted treatment in patients with solid malignancies. Providing a readout of aberrant signaling pathways and proteolytic events, mass spectrometry-based (MS-based) peptidomics enables identification of predictive biomarkers, whereas the serum or plasma peptidome may provide easily accessible signatures associated with response to treatment. In this systematic review, we evaluate MS-based peptide profiling in blood for prompt clinical implementation.

METHODS

PubMed and Embase were searched for studies using a syntax based on the following hierarchy: (a) blood-based matrix-assisted or surface-enhanced laser desorption/ionization time-of-flight MS peptide profiling (b) in patients with solid malignancies (c) prior to initiation of any treatment modality, (d) with availability of outcome data.

RESULTS

Thirty-eight studies were eligible for review; the majority were performed in patients with non-small cell lung cancer (NSCLC). Median classification prediction accuracy was 80% (range: 66%-93%) in 11 models from 14 studies reporting an MS-based classification model. A pooled analysis of 9 NSCLC studies revealed clinically significant median progression-free survival in patients classified as "poor outcome" and "good outcome" of 2.0 ± 1.06 months and 4.6 ± 1.60 months, respectively; median overall survival was also clinically significant at 4.01 ± 1.60 months and 10.52 ± 3.49 months, respectively.

CONCLUSION

Pretreatment MS-based serum and plasma peptidomics have shown promising results for prediction of treatment outcome in patients with solid tumors. Limited sample sizes and absence of signature validation in many studies have prohibited clinical implementation thus far. Our pooled analysis and recent results from the PROSE study indicate that this profiling approach enables treatment selection, but additional prospective studies are warranted.

SELDI-TOF-MS proteomic profiling of serum, urine, and amniotic fluid in neural tube defects

Neural tube defects (NTDs) are common birth defects, whose specific biomarkers are needed. The purpose of this pilot study is to determine whether protein profiling in NTD-mothers differ from normal controls using SELDI-TOF-MS. ProteinChip Biomarker System was used to evaluate 82 maternal serum samples, 78 urine samples and 76 amniotic fluid samples. The validity of classification tree was then challenged with a blind test set including another 20 NTD-mothers and 18 controls in serum samples, and another 19 NTD-mothers and 17 controls in urine samples, and another 20 NTD-mothers and 17 controls in amniotic fluid samples. Eight proteins detected in serum samples were up-regulated and four proteins were down-regulated in the NTD group. Four proteins detected in urine samples were up-regulated and one protein was down-regulated in the NTD group. Six proteins detected in amniotic fluid samples were up-regulated and one protein was down-regulated in the NTD group. The classification tree for serum samples separated NTDs from healthy individuals, achieving a sensitivity of 91% and a specificity of 97% in the training set, and achieving a sensitivity of 90% and a specificity of 97% and a positive predictive value of 95% in the test set. The classification tree for urine samples separated NTDs from controls, achieving a sensitivity of 95% and a specificity of 94% in the training set, and achieving a sensitivity of 89% and a specificity of 82% and a positive predictive value of 85% in the test set. The classification tree for amniotic fluid samples separated NTDs from controls, achieving a sensitivity of 93% and a specificity of 89% in the training set, and achieving a sensitivity of 90% and a specificity of 88% and a positive predictive value of 90% in the test set. These suggest that SELDI-TOF-MS is an additional method for NTDs pregnancies detection.

[Preliminary study of MALDI-TOF mass spectrometry-based screening of patients with the NSCLC serum-specific peptides]

背景与目的

早期诊断是提高肺癌生存率的关键，传统的肺癌诊断技术仍存在一定局限性。鉴于近年来以质谱为核心技术的肿瘤蛋白组学在癌症诊断方面的初步研究，本研究探索性应用基质辅助激光解析电离飞行时间质谱（matrix assisted laser desorption ionization-time of flight-mass spectrometry, MALDI-TOF-MS）分析非小细胞肺癌（non-small cell lung cancer, NSCLC）患者和健康人群的血清差异多肽，以建立NSCLC的血清分类模型。

方法

将年龄和性别匹配的133例NSCLC患者和132例健康者血清标本按照3:1的比例随机分为两组：训练组由100例NSCLC患者和100例健康者血清标本组成，用以建立分类模型；测试组由33例NSCLC患者和32例健康者血清标本组成，用以验证模型。采用铜离子鳌合纳米磁珠提取血清多肽、MALDI-TOF-MS技术检测得到质谱图。ClinProTools^TM统计软件分析训练组NSCLC患者与健康者之间的多肽图谱，从中筛选出一组差异多肽并建立分类模型，最后用测试组对模型进行盲样验证。

结果

在训练组中观察到血清质荷比（m/z）在1, 000 Da-10, 000 Da范围内有131个差异多肽信号峰，在此范围内共得到14个有统计学意义的差异多肽峰（P < 0.000, 001; AUC≥0.9），其中NSCLC患者与健康者相比，表达上调的多肽有2个，表达下调的有12个，由统计软件筛选出3个多肽峰（7, 478.59 Da、2, 271.44 Da、4, 468.38 Da）建立分类模型，然后对测试组进行验证，其盲样验证敏感性100%，特异性96.9%，准确率98.5%。

结论

本组研究显示NSCLC患者与健康人群的血清多肽存在差异，应用MALDI-TOF-MS技术可建立NSCLC的血清多肽分类模型且小规模验证具有较好的敏感性和特异性，希望大规模验证模型，并与传统诊断方法对照或结合，进而尝试建立一种新的NSCLC早期诊断模式。

Proteomics for discovery of candidate colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Proteomics, genomics and transcriptomics: their emerging roles in the discovery and validation of colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cancer in females and the third in males. Since CRC is often diagnosed at an advanced stage when prognosis is poor, identification of biomarkers for early diagnosis is urgently required. Recent advances in proteomics, genomics and transcriptomics have facilitated high-throughput profiling of data generated from CRC-related genes and proteins, providing a window of information for biomarker discovery and validation. However, transfer of candidate biomarkers from bench to bedside remains a dilemma. In this review, we will discuss emerging proteomic technologies and highlight various sample types utilized for proteomics-based identification of CRC biomarkers. Moreover, recent breakthroughs in genomics and transcriptomics for the identification of CRC biomarkers, with particular emphasis on the merits of emerging methylomic and miRNAomic strategies, will be discussed. Integration of proteomics, genomics and transcriptomics will facilitate the discovery and validation of CRC biomarkers leading to the emergence of personalized medicine.

Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics

Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies.

Combining proteomics, serum biomarkers and bioinformatics to discriminate between esophageal squamous cell carcinoma and pre-cancerous lesion

OBJECTIVE

Biomarker assay is a noninvasive method for the early detection of esophageal squamous cell carcinoma (ESCC). Searching for new biomarkers with high specificity and sensitivity is very important for the early detection of ESCC. Serum surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) is a high throughput technology for identifying cancer biomarkers using drops of sera.

METHODS

In this study, 185 serum samples were taken from ESCC patients in a high incidence area and screened by SELDI. A support vector machine (SVM) algorithm was adopted to analyze the samples.

RESULTS

The SVM patterns successfully distinguished ESCC from pre-cancerous lesions (PCLs). Also, types of PCL, including dysplasia (DYS) and basal cell hyperplasia (BCH), and healthy controls (HC) were distinguished with an accuracy of 95.2% (DYS), 96.6% (BCH), and 93.8% (HC), respectively. A marker of 25.1 kDa was identified in the ESCC patterns whose peak intensity was observed to increase significantly during the development of esophageal carcinogenesis, and to decrease obviously after surgery.

CONCLUSIONS

We selected five ESCC biomarkers to form a diagnostic pattern which can discriminate among the different stages of esophageal carcinogenesis. This pattern can significantly improve the detection of ESCC.

Identification of MXRA5 as a novel biomarker in colorectal cancer

In our previous study, significantly high expression levels of matrix-remodeling associated 5 (MXRA5) were identified in fresh-cultured colorectal cancer (CRC) tissues compared with their normal adjacent mucosa by differential secretome analysis. Whether MXRA5 is a potential serum biomarker of CRC has not been evaluated. The aim of this study was to investigate the association between MXRA5 expression and clinicopathological characteristics of CRC patients. The MXRA5 expression levels were determined by quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) in 20 colorectal adenoma tissues, 156 CRC tissues and their corresponding adjacent normal mucosa. Relative quantity (RQ) value and immunoreactive score (IRS) were used for quantitative assessment. The staining for MXRA5 protein was mainly located in the cytoplasm of CRC cells. All CRC tissues were positively stained, with a higher expression rate (IRS>4) of 67% (105/156), and a lower expression rate (IRS≤4) of 33% (51/156). Meanwhile, their corresponding normal tissues exhibited little positive staining; the higher expression rate was 0% (0/156) and the lower expression rate was 25% (16/156). Additionally, more than half of the adenoma tissues were positively stained; the higher expression rate was 15% (3/20) and the lower expression rate was 50% (10/20). The MXRA5 protein positive staining rates were significantly correlated with the lesion sites (colon vs. rectum, 76 vs. 59%), TNM staging (I+II vs. III+IV, 56 vs. 73%) and metastasis (present vs. absent; 76 vs. 61%) with the most high positive staining rate observable in omental metastasis (82%). However, MXRA5 mRNA expression levels showed no significant differences between CRC tissues and their corresponding normal tissues, and no significant correlation between IRS and corresponding RQ value was observed. In this study, we present the first evaluation of MXRA5 protein expression in CRC tissue. Our results revealed that MXRA5 protein is aberrantly expressed in CRC tissues, and has potential value in early detection of CRC and prediction of omental metastasis.

New serum biomarkers for detection of tuberculosis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND

New technologies for the early detection of tuberculosis (TB) are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. The aim of the present study was to screen for the potential protein biomarkers in serum for the diagnosis of TB using proteomic fingerprint technology.

METHODS

Proteomic fingerprint technology combining protein chips with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to profile the serum proteins from 50 patients with TB, 25 patients with lung disease other than TB, and 25 healthy volunteers. The protein fingerprint expression of all the serum samples and the resulting profiles between TB and control groups were analyzed with the Biomarker Wizard system.

RESULTS

A total of 30 discriminating m/z peaks were detected that were related to TB (p<0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the three biomarkers (2024, 8007, and 8598 Da) generated excellent separation between the TB and control groups. The sensitivity was 84.0% and the specificity was 86.0%. Blind test data indicated a sensitivity of 80.0% and a specificity of 84.2%.

CONCLUSIONS

The data suggested a potential application of SELDI-TOF MS as an effective technology to profile serum proteome, and with pattern analysis, a diagnostic model comprising three potential biomarkers was indicated to differentiate people with TB and healthy controls rapidly and precisely.

Mass spectrometry-based proteomics in biomedical research: emerging technologies and future strategies

In recent years, the technology and methods widely available for mass spectrometry (MS)-based proteomics have increased in power and potential, allowing the study of protein-level processes occurring in biological systems. Although these methods remain an active area of research, established techniques are already helping answer biological questions. Here, this recent evolution of MS-based proteomics and its applications are reviewed, including standard methods for protein and peptide separation, biochemical fractionation, quantitation, targeted MS approaches such as selected reaction monitoring, data analysis and bioinformatics. Recent research in many of these areas reveals that proteomics has moved beyond simply cataloguing proteins in biological systems and is finally living up to its initial potential – as an essential tool to aid related disciplines, notably health research. From here, there is great potential for MS-based proteomics to move beyond basic research, into clinical research and diagnostics.