Noninvasive molecular biomarkers for the detection of colorectal cancer

Colorectal cancer (CRC) is the third most common malignancy in the world. Because CRC develops slowly from removable precancerous lesions, detection of the disease at an early stage during regular health examinations can reduce both the incidence and mortality of the disease. Although sigmoidoscopy offers significant improvements in the detection rate of CRC, its diagnostic value is limited by its high costs and inconvenience. Therefore, there is a compelling need for the identification of noninvasive biomarkers that can enable earlier detection of CRC. Accordingly, many validation studies have been conducted to evaluate genetic, epigenetic or protein markers that can be detected in the stool or in serum. Currently, the fecal-occult blood test is the most widely used method of screening for CRC. However, advances in genomics and proteomics combined with developments in other relevant fields will lead to the discovery of novel non invasive biomarkers whose usefulness will be tested in larger validation studies. Here, noninvasive molecular biomarkers that are currently used in clinical settings and have the potential for use as CRC biomarkers are discussed.     

Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects

Background

The aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format—electrochemiluminescence immunoassays—to quantify protein concentrations. The aim was achieved by building and validating a CRC classifier using concentration measures from a large sample set representing a true intent-to-test (ITT) symptomatic population.

Methods

4435 patient samples were drawn from the Endoscopy II sample set. Samples were collected at seven hospitals across Denmark between 2010 and 2012 from subjects with symptoms of colorectal neoplasia. Colonoscopies revealed the presence or absence of CRC. 27 blood plasma proteins were selected as candidate biomarkers based on previous studies. Multiplexed electrochemiluminescence assays were used to measure the concentrations of these 27 proteins in all 4435 samples. 3066 patients were randomly assigned to the Discovery set, in which machine learning was used to build candidate classifiers. Some classifiers were refined by allowing up to a 25% indeterminate score range. The classifier with the best Discovery set performance was successfully validated in the separate Validation set, consisting of 1336 samples.

Results

The final classifier was a logistic regression using ten predictors: eight proteins (A1AG, CEA, CO9, DPPIV, MIF, PKM2, SAA, TFRC), age, and gender. In validation, the indeterminate rate of the new panel was 23.2%, sensitivity/specificity was 0.80/0.83, PPV was 36.5%, and NPV was 97.1%.

Conclusions

The validated classifier serves as the basis of a new blood-based CRC test for symptomatic patients. The improved performance, resulting from robust concentration measures across a large sample set mirroring the ITT population, renders the new test the best available for this population. Results from a test using this classifier can help assess symptomatic patients’ CRC risk, increase their colonoscopy compliance, and manage next steps in their care.

     

Proteomics of post-translational modifications in colorectal cancer: Discovery of new biomarkers

Colorectal cancer (CRC) is one of the costliest health problems and ranks second in cancer-related mortality in developed countries. With the aid of proteomics, many protein biomarkers for the diagnosis, prognosis, and precise management of CRC have been identified. Furthermore, some protein biomarkers exhibit structural diversity after modifications. Post-translational modifications (PTMs), most of which are catalyzed by a variety of enzymes, extensively increase protein diversity and are involved in many complex and dynamic cellular processes through the regulation of protein function. Accumulating evidence suggests that abnormal PTM events are associated with a variety of human diseases, such as CRC, thus highlighting the need for studying PTMs to discover both the molecular mechanisms and therapeutic targets of CRC. In this review, we begin with a brief overview of the importance of protein PTMs, discuss the general strategies for proteomic profiling of several key PTMs (including phosphorylation, acetylation, glycosylation, ubiquitination, methylation, and citrullination), shift the emphasis to describing the specific methods used for delineating the global landscapes of each of these PTMs, and summarize the recent applications of these methods to explore the potential roles of the PTMs in CRC. Finally, we discuss the current status of PTM research on CRC and provide future perspectives on how PTM regulation can play an essential role in translational medicine for early diagnosis, prognosis stratification, and therapeutic intervention in CRC.     

Combining biomarkers to detect disease with application to prostate cancer

In early detection of disease, combinations of biomarkers promise improved discrimination over diagnostic tests based on single markers. An example of this is in prostate cancer screening, where additional markers have been sought to improve the specificity of the conventional Prostate-Specific Antigen (PSA) test. A marker of particular interest is the percent free PSA. Studies evaluating the benefits of percent free PSA reflect the need for a methodological approach that is statistically valid and useful in the clinical setting. This article presents methods that address this need. We focus on and-or combinations of biomarker results that we call logic rules and present novel definitions for the ROC curve and the area under the curve (AUC) that are applicable to this class of combination tests. Our estimates of the ROC and AUC are amenable to statistical inference including comparisons of tests and regression analysis. The methods are applied to data on free and total PSA levels among prostate cancer cases and matched controls enrolled in the Physicians' Health Study.     

结直肠腺瘤及结直肠癌患者肠道中梭杆菌属与产丁酸菌的定量研究

【目的】通过观察梭杆菌属(Fusobacterium spp.)和两株产丁酸菌(Eubacterium rectale、Faecalibacterium prausnitzii)在结直肠癌患者及结直肠腺瘤患者粪便样品中的丰度差异,研究梭杆菌属和产丁酸菌数量变化在结直肠腺瘤和结直肠癌发生发展中的作用和意义。【方法】收集结直肠癌患者(n=19)、结直肠腺瘤患者(n=12)及健康人(n=19)3组粪便样品,提取细菌基因组DNA,利用实时荧光定量PCR技术定量检测3组样品中梭杆菌属(Fusobacterium spp.)、直肠真杆菌(Eubacterium rectale)、普拉梭菌(Faecalibacterium prausnitzii)以及总菌的16S rRNA基因的拷贝数,然后利用秩和检验两两比较3组样品中目标菌群的数量和丰度差异。【结果】结直肠癌组的梭杆菌属丰度显著高于结直肠腺瘤组(P=0.013)和健康组(P=0.000),结直肠腺瘤组的梭杆菌属丰度显著高于健康组(P=0.002);结直肠腺瘤组普拉梭菌的丰度显著低于健康组(P=0.033);结直肠腺瘤组的总菌16S rRNA基因拷贝数也显著低于健康组(P=0.002);直肠真杆菌的水平在3组样品间没有显著差异。【结论】与健康人的粪便样品相比,结直肠腺瘤病人的粪便中产丁酸菌普拉梭菌数量下降,而结直肠腺瘤和结直肠癌病人的粪便样品中梭杆菌属数量增加;梭杆菌属和产丁酸菌数量上的变化提示它们可能与结直肠腺瘤和结直肠癌的发生密切相关。     

Discovery of urine biomarkers for bladder cancer via global metabolomics

Bladder cancer (BC) is latent in its early stage and lethal in its late stage. Therefore, early diagnosis and intervention are essential for successful BC treatment. Considering the limitations of current diagnostic tools, noninvasive biomarkers that are both highly sensitive and specific are needed to improve the overall survival and quality of life of patients. With the advent of systems biology, “-omics” technologies have been developed over the past few decades. As a promising member, global metabolomics has increasingly been found to have clear potential for biomarker discovery. However, urinary metabolomics studies related to BC have lagged behind those of other urinary cancers, and major findings have not been systematically reported. The objective of this review is to comprehensively list the currently identified potential urinary metabolite biomarkers for BC.     

Discovery of biomarkers for gastric cancer: a proteomics approach

Gastric cancer is the second leading cause of cancer-related deaths worldwide. Although many treatment options exist for patients with gastric tumors, the incidence and mortality rate of gastric cancer are on the rise. The early stages of gastric cancer are non-symptomatic, and the treatment response is unpredictable. This situation is further aggravated by a lack of diagnostic biomarkers that can aid in the early detection and prognosis of gastric cancer and in the prediction of chemoresistance. Moreover, clinical surgical specimens are rarely obtained, and traditional biomarkers of gastric cancer are not very effective. Many studies in the field of proteomics have contributed to the discovery and establishment of powerful diagnostic tools (e.g., ProteinChip array) in the management of cancer. The evolution in proteomic technologies has not only enabled the screening of a large number of samples but also enabled the identification of pathologically significant proteins, such as phosphoproteins, and the quantitation of difference in protein expression under different conditions. Multiplexed assays are used widely to accurately fractionate various complex samples such as blood, tissue, cells, and Helicobacter pylori-infected specimens to identify differentially expressed proteins. Biomarker detection studies have substantially contributed to the areas of secretome, metabolome, and phosphoproteome. Here, we review the development of potential biomarkers in the natural history of gastric cancer, with specific emphasis on the characteristics of target protein convergence.     

Predictive and prognostic biomarkers in colorectal cancer

Colorectal cancer is the third most common cancer and the second leading cause of cancer-related death in the United States.Three quarters of patients diagnosed with colorectal cancer will have early s...     

Identification of biomarkers for colorectal cancer through proteomics-based approaches

The early detection of colorectal cancer is one of the great challenges in the battle against this disease. However, owing to its heterogeneous character, single markers are not likely to provide sufficient diagnostic power to be used in colorectal cancer population screens. This review provides an overview of recent studies aimed at the discovery of new diagnostic protein markers through proteomics-based approaches. It indicates that studies that start with the proteomic analysis of tumor tissue or tumor cell lines (near the source) have a high potential to yield novel and colorectal cancer-specific biomarkers. In the next step, the diagnostic accuracy of these candidate markers can be assessed by a targeted ELISA assay using serum from colorectal cancer patients and healthy controls. Instead, direct proteomic analysis of serum yields predominantly secondary markers composed of fragments of abundant serum proteins that may be associated with tumor-associated protease activity, and alternatively, immunoproteomic analysis of the serum antibody repertoire provides a valuable tool to identify the molecular imprint of colorectal cancer-associated antigens directly from patient serum samples. The latter approach also allows a relatively easy translation into targeted assays. Eventually, multimarker assays should be developed to reach a diagnostic accuracy that meets the stringent criteria for colorectal cancer screening at the population level.     

Development and preliminary validation of the cancer family impact scale for colorectal cancer

AIM: The aim of our study was to develop a measure of how a family history of colorectal cancer (CRC) affects families from the viewpoint of unaffected family members. METHOD: Using data from 1,285 participants (637 families) in the Johns Hopkins Colon Cancer Genetic Testing study, we developed and validated The Cancer Family Impact Scale (CFIS), an instrument for use in studies investigating relationships among family factors and CRC prevention behaviors when family history is a risk factor. RESULTS: Through exploratory factor analysis (EFA) using a 50% random sample of participants, we identified 5 latent constructs among 18 items: (1) NEGATIVE: negative effects of cancer on the family; (2) POSITIVE: positive effects of cancer on the family; (3) COMMUNICATE: how families communicate about cancer; (4) FLOW: how information about cancer is conveyed in families; and (5) NORM: how individuals react to family norms about cancer. Confirmatory factor analysis (CFA) on the same sample showed the CFIS to have a reasonably good fit (chi(2) = 389.97, degree of freedom (df ) = 122, root mean square error of approximation = 0.06 [0.05-0.07], comparative fit index = 0.90, Tucker-Lewis index = 0.88, goodness of fit index = 0.94), and findings were cross-validated on the remaining 50% of the participants. The reliability of the scale was alpha = 0.65. CONCLUSIONS: The CFIS could be used to clarify the role that family factors play in the association between CRC family history and CRC prevention behaviors, and also aid in the development and evaluation of family-based cancer prevention interventions.     

Semiparametric estimation for joint modeling of colorectal cancer risk and functional biomarkers measured with errors

This research is motivated by a pilot colorectal adenoma study, where the outcome of interest is the presence of colorectal adenoma representing risk for colorectal cancer, and the predictors of interest are protein biomarkers that are repeatedly measured with errors along the length of a microscopic structure in the human colon, the colon crypt. Biomarkers of this type are referred to as functional biomarkers. The investigators are interested in identifying features of functional biomarkers that are associated with risk for colorectal cancer. In this paper, we investigate a joint modeling approach, where the binary clinical outcome is modeled using a logistic regression model with the unobserved true functional biomarkers as the predictors. Most existing methods are developed either for linear models or for functional biomarkers measured without errors and cannot be directly applied to our data. The applicable methods include a two-step method and a maximum likelihood method, which have some limitations. We propose a robust semiparametric method to overcome the limitations of the existing methods. We study the properties of the proposed method, and show in simulations that it compares favorably with other methods and also offers significant savings in CPU time. We analyze the pilot colorectal adenoma data and show that expression levels of AFC, a tumor suppressor gene, in the transitional area from the proliferation zone to the differentiation zone of colon crypts are likely to be associated with risk for colorectal cancer. Given the relatively small sample size in the pilot study, our results need to be validated in the future full-scale studies.     

Plasma choline-containing phospholipids: potential biomarkers for colorectal cancer progression

Colorectal cancer (CRC) is believed to progress through the adenoma–carcinoma sequence. The adenoma–carcinoma transition is an important window for early detection and intervention of CRC. In the present study, plasma samples from patients with CRC (n = 120), patients with adenomatous polyps (AP) (n = 120), and healthy controls (n = 120) were collected. Plasma phospholipid levels were analyzed with liquid chromatography–tandem mass spectrometry. It was found that the plasma levels of major lysophosphatidylcholine (LPC) species were gradationally decreased from healthy controls, AP to CRC subjects. A formula including total saturated LPCs, 18:2 LPC and sphingosylphosphorylcholine (SPC) yielded a sensitivity and specificity of 88.3 and 80 % for separating CRC from healthy controls. An optimized model with total saturated LPCs, 20:4 LPC and sphingomyelins (SM) as markers yielded a sensitivity and specificity of 89 and 80 % for separating AP from the healthy controls. Moreover, with SM, SPC and saturated LPCs as markers, a model was made to separate CRC from AP with the sensitivity and specificity of 90 and 92.5 %, respectively. These data indicate that the plasma choline-containing phospholipid levels represent potential biomarkers to distinguish between healthy controls, AP and CRC cases, implying their clinical usage in CRC and/or AP-CRC progression detection.     

Epigenetic biomarkers in colorectal cancer: premises and prospects

Context: Colorectal cancer is one of the most common cancers worldwide. Epigenetic alterations play an important role in the pathogenesis of the colorectal cancer.

Objective: This review has focused on the most recent investigations, which has suggested potential epigenetic biomarkers in colorectal cancer.

Methods: Evidences were achieved by searching online medical databases including Google scholar, Pubmed, Scopus and Science Direct.

Results: Extensive studies have indicated that aberrant epigenetic modifications could serve as potential biomarkers for diagnosis, prognosis and prediction of colorectal cancer.

Conclusion: Advances in aberrant epigenetic modifications can open new avenues for exploration of reliable and robust biomarkers to improve the management of CRC patients.     

Novel molecular classification of colorectal cancer and correlation with survival

IntroductionColorectal cancer (CRC) is one of the most common cancers worldwide. This study was designed to evaluate biological patterns, explore molecular classification and correlate with survival outcome in treatment naïve CRC patients.MethodsOver 11 years consecutive series of 435 CRC patients were operated on as primary surgical therapy. A total of 201 CRC patients were included, whose complete set of clinical information was available, and their good quality tumour blocks were retrieved. Immunohistochemistry was used for tumour analysis, and partitional clustering was performed using R software for cluster analysis.ResultsThe median age was 43 (range 10–85) years; adenocarcinoma was the most commonly seen histological type. The great majority had positive CK20, CEA, E-Cadherin, Ki67, CDX2, and p53 expression. There were four distinct molecular classes found, whereas Ki67, CDX2, and p53 play the main role in partitioning. Younger age negatively impacted survival; overall and disease-specific survival was 26 months only with 50 months’ longest survival.ConclusionColorectal cancer is a biologically heterogeneous disease with at least four distinct molecular patterns, where cell proliferation and gene repair mechanisms appear to play the key role.     

Tissue microarrays for testing molecular biomarkers of cervical intraepithelial neoplasia: feasibility study

OBJECTIVE: To test the possibility of creating tissue microarrays of pre-malignant lesions of the cervix. STUDY DESIGN Paraffin-embedded blocks of 240 cervical tissue specimens were sampled. Lesions from benign squamous and glandular epithelium through various grades of cervical intraepithelial neoplasia (CIN) to frank carcinoma of squamous and glandular origin were cored with a 0.6-mm needle and arrayed in 4 tissue blocks. Sections of these blocks were stained with hematoxylineosin (H-E) and evaluated as to adequacy of tissue cores, representativity of the material and correspondence to the original diagnosis. Immunohistochemical staining with p16 and a novel marker C4.8(4/2/#1) was performed. RESULTS: In > 80% of cases sufficient material from the lesion could be obtained. No or inadequate material was seen in 6% of cases. The core sample did not correspond to the original diagnosis in 12% of cases. The reason was mainly a discrepancy in the grade of the CIN. Discrepancies in diagnoses occurred in only premalignant lesions. Immunohistochemical staining could reliably be performed and evaluated on all tissue cores. CONCLUSION: Tissue microarrays of cervical intraepithelial lesions are technically feasible and can be created reliably. The key to success is a careful and repeated comparison of the tissue block with the corresponding H-E section. Tissue microarrays of preinvasive cervical lesions may allow high throughput analysis of emerging molecular biomarkers in cervical carcinogenesis.     

Low penetrance genetic polymorphisms as potential biomarkers for colorectal cancer predisposition

Colorectal cancer is a leading form of cancer in both males and females. Early detection of individuals at risk of colorectal cancer allows proper treatment and management of the disease to be implemented, which can potentially reduce the burden of colorectal cancer incidence, morbidity and mortality. In recent years, the role of genetic susceptibility factors in mediating predisposition to colorectal cancer has become more and more apparent. Identification of high‐frequency, low‐penetrance genetic polymorphisms associated with the cancer has therefore emerged as an important approach which can potentially aid prediction of colorectal cancer risk. However, the overwhelming amount of genetic epidemiology data generated over the past decades has made it difficult for one to assimilate the information and determine the exact genetic polymorphisms that can potentially be used as biomarkers for colorectal cancer. This review comprehensively consolidates, based primarily on results from meta‐analyses, the recent progresses in the search of colorectal cancer‐associated genetic polymorphisms, and discusses the possible mechanisms involved.     

Faecal microbial biomarkers in early diagnosis of colorectal cancer

Colorectal cancer (CRC) is ranked as the second most common cause of cancer deaths and the third most common cancer globally. It has been described as a ‘silent disease’ which is often easily treatable if detected early—before progression to carcinoma. Colonoscopy, which is the gold standard for diagnosis is not only expensive but is also an invasive diagnostic procedure, thus, effective and non-invasive diagnostic methods are urgently needed. Unfortunately, the current methods are not sensitive and specific enough in detecting adenomas and early colorectal neoplasia, hampering treatment and consequently, survival rates. Studies have shown that imbalances in such a relationship which renders the gut microbiota in a dysbiotic state are implicated in the development of adenomas ultimately resulting in CRC. The differences found in the makeup and diversity of the gut microbiota of healthy individuals relative to CRC patients have in recent times gained attention as potential biomarkers in early non-invasive diagnosis of CRC, with promising sensitivity, specificity and even cost-effectiveness. This review summarizes recent studies in the application of these microbiota biomarkers in early CRC diagnosis, limitations encountered in the area of the faecal microbiota studies as biomarkers for CRC, and future research exploits that address these limitations.