Identifying circulating miRNA biomarkers for early diagnosis and monitoring of lung cancer

Liquid biopsy refers to the sampling, screening, and detecting potential biomarkers in unique liquid samples for clinical use. Lung cancer is one of the most highly frequent cancer subtypes, which is hard to be early diagnosed and monitored by radiological and histopathological evaluation that are the most general and accurate methods. Circulating miRNA is a potential clinical examination index for tumor detection and monitoring tumorigenesis progression using liquid biopsy. However, recognizing and validating the unique clinical values of each candidate circulating miRNA is expensive and time consuming. In this study, we presented a novel computational approach for identifying significant circulating miRNAs that may be applied to early screening, diagnosis, and constant monitoring of lung cancer progression. This approach incorporated several machine learning algorithms and was applied on the expression profiles of circulating miRNAs on lung cancer patients and control samples. In brief, a powerful feature selection method, minimum redundancy maximum relevance, was adopted to evaluate the importance of all features, resulting in a feature list. Then, incremental feature selection incorporating random forest followed to extract key circulating miRNAs. At the same time, an efficient classifier with MCC 0.740 was built. Top five circulating miRNAs, including miR-92a, miR-140-5p, miR-331-3p, miR-223, miR-374a, were analyzed and confirmed that they participated in the pathogenesis of lung cancer, indicating their significant prognosis power in lung cancer.     

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.     

Lamprey immunity protein enables early detection and recurrence monitoring for bladder cancer through recognizing Neu5Gc-modified uromodulin glycoprotein in urine

The clinical management of bladder cancer (BCa) is hindered by the lack of reliable biomarkers. We aimed to investigate the potential of lamprey immunity protein (LIP), a lectin that specifically binds to multi-antennary sialylated N-glycolylneuraminic acid (Neu5Gc) structures on UMOD glycoproteins in the urine of BCa patients. Primary BCa patients had higher levels of LIP-bound Neu5Gc in urine than healthy participants and patients receiving postoperative treatment did. In addition, lectin chip assay and mass spectrometry were used to analyze the glycan chain structure, which can recognize the UMOD glycoprotein decorated with multi-antennary sialylated Neu5Gc structures. Furthermore, compared with urine samples from healthy patients (N = 2821, T/C = 0.12 ± 0.09) or benign patients (N = 360, T/C = 0.11 ± 0.08), the range of the urine T/C ratio detected using LIP test paper was 1.97 ± 0.32 in patients with bladder cancer (N = 518) with significant difference (P < 0.0001). Our results indicate that LIP may be a tool for early BCa identification, diagnosis, and monitoring. Neu5Gc-modified UMOD glycoproteins in urine and Neu5Gc-modified N-glycochains and sialyltransferases may function as potential markers in clinical trials.     

Proteomics approaches in cervical cancer: focus on the discovery of biomarkers for diagnosis and drug treatment monitoring

Introduction: The HPV virus accounts for the majority of cervical cancer cases. Although a diagnostic tool (Pap Test) is widely available, cervical cancer incidence still remains high worldwide, and especially in developing countries, attributed to a large extent to suboptimal sensitivities of the Pap test and unavailability of the test in developing countries.

Areas covered: Proteomics approaches have been used in order to understand the HPV virus correlation to cervical cancer pathology, as well as to discover putative biomarkers for early cervical cancer diagnosis and drug mode of action.

Expert commentary: The present review summarizes the latest in vitro and in vivo proteomic studies for the discovery of putative cervical cancer biomarkers and the evaluation of available drugs and treatments.     

Computerized analysis of cellular features and biomarkers for cytologic diagnosis of early lung cancer

OBJECTIVE: To present a set of novel computerized analysis algorithms to construct a computer-aided cytologic diagnosis (CACD) system to differentiate lung cancer biomarkers and identify cancer cells in the tissue-based specimen images. STUDY DESIGN: Molecular methods, including application of cancer-specific markers, may prove to be complementary to cytology diagnosis, especially when they are combined with CACD system for biomarker assessment. We trained a novel CACD system to recognize expression of the cancer biomarkers histone H2AX in lung cancer cells and then tested the accuracy of this system to distinguish resected lung cancer from preneoplastic and normal tissues. The major characteristics of CACD algorithms is to adapt detection parameters according to cellular image contents. Our newly developed wavelet transform is able to adaptively select different resolution and orientation features based on image content requirements. RESULTS: Visual, statistical and quantitative results as CACD performance evaluation are presented in this paper. CONCLUSION: The presented algorithms and CACD system for cellular feature enhancement, segmentation and classification are very important in distinguishing benign and malignant lesions.     

表观遗传生物标志物在人类疾病早期诊治中的研究进展

表观遗传修饰异常见于人类的多种疾病(如肿瘤、老年性疾病、发育源性疾病等),影响着这些疾病的发生发展。已有的研究表明,异常表观遗传改变可以作为疾病状态和疾病预测的生物标志物。表观遗传修饰改变的可逆性和可控性也为疾病早期的预防和治疗提供了新策略。本文对DNA甲基化修饰、组蛋白共价修饰、非编码RNA等三种表观遗传方式在肿瘤、老年性疾病和发育源性疾病的研究,以及三者作为表遗传生物标志物在疾病早期诊断和治疗的应用展开介绍,以期为肿瘤、老年性和发育源性相关疾病的诊断与治疗提供借鉴和 参考。     

Current advances in tumor proteomics and candidate biomarkers for hepatic cancer

Tumor proteomics apply proteomics techniques to tumor biological research, mainly by screening candidate biomarkers for early tumor diagnosis, prognosis and treatment. Hepatocellular carcinoma (HCC) is a type of malignant tumor with one of the highest death rates in the world. With the advent of the post-genomic age, tumor biological research developing the technology of proteomics has become a major focus of researchers. The discovery of novel candidate biomarkers is one of crucial problems for the early diagnosis of HCC. In general, there are three distinct types of candidate biomarkers for HCC based on different areas: biochemical biomarkers, antigenic biomarkers and epigenetic biomarkers. This review mainly discusses current advances in the problems and prospects of candidate biomarker for the early diagnosis of HCC, discovered by technologies of tumor proteomics.     

Humoral immunity directed against tumor-associated antigens as potential biomarkers for the early diagnosis of cancer

Over the past decade, it has been demonstrated that cancer is immunogenic, and multiple tumor antigens have been identified in cancer patients. It is now possible to potentially harness the immune response elicited by cancer growth as a potential diagnostic tool. Humoral immunity, or the development of autoantibodies against tumor-associated proteins, may be used as a marker for cancer exposure. Unlike circulating proteins that are shed by bulky tumors, serum autoantibodies are detectable even when antigen expression is minimal. This paper will review the methods used for tumor antigen discovery and overview what is known about autoantibodies targeting common cancer antigens with a focus on breast cancer. Data will be presented modeling the use of tumor antigen associated autoantibodies as a breast cancer diagnostic. The endogenous humoral immune response present in cancer patients may allow the identification of individuals exposed to the malignant transformation of somatic cells.     

Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer

Background

With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types.

Methodology/Principal Findings

In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function.

Conclusion/Significance

The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the ‘omics’ era.     

Methylcap-seq reveals novel DNA methylation markers for the diagnosis and recurrence prediction of bladder cancer in a Chinese population

Purpose

There is a need to supplement or supplant the conventional diagnostic tools, namely, cystoscopy and B-type ultrasound, for bladder cancer (BC). We aimed to identify novel DNA methylation markers for BC through genome-wide profiling of BC cell lines and subsequent methylation-specific PCR (MSP) screening of clinical urine samples.

Experimental Design

The methyl-DNA binding domain (MBD) capture technique, methylCap/seq, was performed to screen for specific hypermethylated CpG islands in two BC cell lines (5637 and T24). The top one hundred hypermethylated targets were sequentially screened by MSP in urine samples to gradually narrow the target number and optimize the composition of the diagnostic panel. The diagnostic performance of the obtained panel was evaluated in different clinical scenarios.

Results

A total of 1,627 hypermethylated promoter targets in the BC cell lines was identified by Illumina sequencing. The top 104 hypermethylated targets were reduced to eight genes (VAX1, KCNV1, ECEL1, TMEM26, TAL1, PROX1, SLC6A20, and LMX1A) after the urine DNA screening in a small sample size of 8 normal control and 18 BC subjects. Validation in an independent sample of 212 BC patients enabled the optimization of five methylation targets, including VAX1, KCNV1, TAL1, PPOX1, and CFTR, which was obtained in our previous study, for BC diagnosis with a sensitivity and specificity of 88.68% and 87.25%, respectively. In addition, the methylation of VAX1 and LMX1A was found to be associated with BC recurrence.

Conclusions

We identified a promising diagnostic marker panel for early non-invasive detection and subsequent BC surveillance.     

Recent advances in the metabolomic study of bladder cancer

Introduction: Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA.

Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA.

Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.     

MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer

Recognition that breast cancer is a heterogeneous disease in which each patient's tumor has specific characteristics has led to a search for biomarkers and combinations of markers (signatures) to improve the diagnosis, prognostic classification and prediction of therapeutic benefit versus toxicity for individual tumors and patients. Many microRNAs (miRNAs) are aberrantly expressed in cancer and seem to influence tumor behavior and progression. miRNAs have great potential to evolve into effective biomarkers in the clinic because of their extreme stability and ease of detection. However, there are several major technical challenges as well as numerous discrepancies among currently reported miRNA signatures. In this review, we discuss the use of miRNA signatures for breast cancer treatment and discuss the challenges in the field.     

Role of biomarkers in the early diagnosis of Alzheimer's disease

Alheimer's disease is the most frequent cause of cognitive decline and behavioral abnormalities in adults. Diagnosis is currently made in the advanced phases. An an early diagnosis in the prodromal phase (or earlier if possible) is required for the prevention of this disease, its early management and the development of potential therapies that could alter its natural course. The syndromic concept of mild cognitive impairment (the presence of detectable and quantifiable deterioration in one of the cognitive domains but without affecting -or without substantially affecting- autonomic performance of instrumental function) and its variants has aided understanding of the predementia stages of Alheimer's disease, even though its etiology may involve multiple factors. The use of biomarkers such as determination of the proteins involved in the disease in cerebrospinal fluid (Aβ??-amyloid, total and phosphorylated tau) and measurement of the hippocampus and entorhinal cortex with magnetic resonance imaging and positron emission tomography (both glucose and amyloid measurements), alone or combined, could allow early and etiologic diagnosis. Patients with Alzheimer's disease show reduced Aβ??-amyloid levels and increased total and phosphorylated tau levels in cerebrospinal fluid.     

Biomarkers for the lung cancer diagnosis and their advances in proteomics

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.     

Evaluation of serum exosomal LncRNA‐based biomarker panel for diagnosis and recurrence prediction of bladder cancer

Exosomes are small membrane vesicles released by many cells. These vesicles can mediate cellular communications by transmitting active molecules including long non‐coding RNAs (lncRNAs). In this study, our aim was to identify a panel of lncRNAs in serum exosomes for the diagnosis and recurrence prediction of bladder cancer (BC). The expressions of 11 candidate lncRNAs in exosome were investigated in training set (n = 200) and an independent validation set (n = 320) via quantitative real‐time PCR. A three‐lncRNA panel (PCAT‐1, UBC1 and SNHG16) was finally identified by multivariate logistic regression model to provide high diagnostic accuracy for BC with an area under the receiver‐operating characteristic curve (AUC) of 0.857 and 0.826 in training set and validation set, respectively, which was significantly higher than that of urine cytology. The corresponding AUCs of this panel for patients with Ta, T1 and T2‐T4 were 0.760, 0.827 and 0.878, respectively. In addition, Kaplan‐Meier analysis showed that non‐muscle‐invasive BC (NMIBC) patients with high UBC1 expression had significantly lower recurrence‐free survival (P = 0.01). Multivariate Cox analysis demonstrated that UBC1 was independently associated with tumour recurrence of NMIBC (P = 0.018). Our study suggested that lncRNAs in serum exosomes may serve as considerable diagnostic and prognostic biomarkers of BC.     

The agony of choice: how to find a suitable CPP for cargo delivery

Successful and effective cellular delivery remains a main obstacles in the medical field. The use of cell‐penetrating peptides (CPPs) has become one of the most important tools for the internalisation of a wide range of molecules including pharmaceuticals. It is still difficult to choose one CPP for one biological application because there is no ubiquitous CPP meeting the diverse requirements. In our case, we are looking for a suitable CPP to deliver the pro‐apoptotic KLA peptide (KLAKLAKKLAKLAK) by a simple co‐incubation strategy. For that reason, we selected three different cell lines (fibroblastic, cancerous and macrophagic cells) and studied the uptake and subcellular localisation of six different CPPs alone as well as mixed with the KLA peptide. Furthermore, we used the CPPs with a carboxyamidated or a carboxylated C‐terminus and analysed the impact of the C‐termini on internalisation and cargo delivery. We could clearly showed that the cellular CPP uptake is not only dependent on the used CPP and cell line but also highly affected by its chemical nature of the C‐terminus (uptake: carboxyamidated CPPs > carboxylated CPPs) and can influence its cellular localisation. We successfully delivered the KLA peptide in the three cell lines and learned that here as well, the C‐terminus is crucial for an effective peptide delivery. Finally, we induced apoptosis in mouse leukaemic monocyte macrophage (RAW 264.7) and in human breast adenocarcinoma (MCF‐7) cells using the mixture of amidated MPG peptide : KLA and in african green monkey kidney fibroblast (Cos‐7) cells using carboxylated integrin peptide : KLA. Copyright © 2012 European Peptide Society and John Wiley & Sons, Ltd.     

MicroRNAs: Potential biomarkers for cancer diagnosis,prognosis and targets for therapy

MicroRNAs have a revolutionary impact on cancer research over recent years. They emerge as important players in tumorigenesis, leading to a paradigm shift in oncology. The widespread and comprehensive use of microRNA microarrays has enabled the identification of a number of microRNAs as potential biomarkers for cancer. It is encouraging to report that microRNAs have remarkable stability in both formalin-fixed tissue and blood. Many microRNAs have been identified to act as oncogenes, tumor suppressors, or even modulators of cancer stem cells and metastasis. Some studies not only reported the identified microRNA biomarkers, but also deciphered their target genes and the underlying mechanisms. The rapid discovery of many microRNA targets and their relevant pathways has contributed to the development of microRNA-based therapeutics, but the developing progress of antisense or siRNA drugs has been hampered by stability, specificity and delivery problems. This review summarizes the most significant and latest findings of original researches on microRNAs involvement in cancer, focusing on the potential of cancer-related microRNAs as biomarkers for diagnosis, prognosis and targets for therapy.