Sieving through the cancer secretome

Cancer is among the most prevalent and serious health problems worldwide. Therefore, there is an urgent need for novel cancer biomarkers with high sensitivity and specificity for early detection and management of the disease. The cancer secretome, encompassing all the proteins that are secreted by cancer cells, is a promising source of biomarkers as the secreted proteins are most likely to enter the blood circulation. Moreover, since secreted proteins are responsible for signaling and communication with the tumor microenvironment, studying the cancer secretome would further the understanding of cancer biology. Latest developments in proteomics technologies have significantly advanced the study of the cancer secretome. In this review, we will present an overview of the secretome sample preparation process and summarize the data from recent secretome studies of six common cancers with high mortality (breast, colorectal, gastric, liver, lung and prostate cancers). In particular, we will focus on the various platforms that were employed and discuss the clinical applicability of the key findings in these studies. This article is part of a Special Issue entitled: An Updated Secretome.     

Volatile organic metabolites identify patients with gastric carcinoma,gastric ulcer,or gastritis and control patients

Background

Gastric cancer ranks 4th among the most common cancers worldwide, and the mortality caused by gastric cancer is 2nd only to lung cancer. Gastric cancer shows a lack of specific symptoms in its early stages. In addition, its clinical symptoms often do not match the corresponding stage. Upper gastrointestinal endoscopy with biopsy is the gold standard for the diagnosis of gastric cancer because of its high accuracy. However, this operation is invasive, patient compliance is poor, and high demands for medical staff and equipment are typical of this procedure. Recent studies have demonstrated a connection between specific breath volatile organic compounds (VOCs) and various forms of cancers.

Methods

We collected expired air from patients with gastric cancer, chronic atrophic gastritis or gastric ulcers as well as from healthy individuals. Solid-phase microextraction, gas chromatography–mass spectrometry and principal component analysis statistics were applied to identify potential biomarkers of gastric cancer among VOCs.

Results

Fourteen differential metabolites were annotated using the NIST 11 database, with a similarity threshold of 70%. Currently, the metabolic origin of VOCs remains unclear; however, several pathways might explain the decreasing or increasing trends that were observed.

Conclusions

The results of this study demonstrate the existence of specific VOC profiles associated with patients with carcinoma. In addition, these metabolites may contribute to the diagnosis and screening of patients with carcinoma.

     

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.     

Cancer Proteomics and the Elusive Diagnostic Biomarkers

Despite progress in genomic and proteomic technology and applications, the validation of cancer biomarkers of use as clinical early detection diagnostics has remained elusive. As described in this brief viewpoint, there are now recognized to be many types of clinical biomarkers and proteomic analyses, particularly when combined with other ‘omic analyses, have been effective in many such biomarker identifications. However, in the area of early diagnosis of cancers, the problems associated with the conversion from identification to diagnostic have largely not been overcome. Notably, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), has been particularly successful in refining the analytical steps needed to tackle this challenging issue and has provided positive insight into how to solve many of the underlying problems. The potential for developing clinical diagnostics for early detection of highly lethal cancers and possible new therapeutic strategies through proteomic analyses, as seen through these CPTAC successes, is more promising than ever.     

Ribonucleic-acid-biomarker candidates for early-phase group detection of common cancers

Cancer is considered as a challenging lethal agent around the world and its detection at early stages would help prevention of the high mortality. Among the widely used biomarkers in clinical diagnosis of cancer, extracellular non-coding RNAs as ribonucleic acid biomarkers serve as state-of-the-art candidates for molecular diagnosis. In that regard, microRNAs are of great priority mainly because of high variety and stability in body fluids. Accordingly, common miRNAs among most prevalent cancers could help us (pre)diagnose cancer with high accuracy in target samples. In this study, common lethal cancers to humans were investigated in case of miRNA profiles to determine the possible common correlation between miRNA up-regulation or down-regulation (as a ribonucleic acid biomarker) and developing the cancers. It was shown that among the investigated miRNAs, five typical extracellular miRNAs (miR-18a, miR-21, miR-155, miR-221, and miR-375) dysregulation are predominant in most cancer varieties comprising breast, colon, lung, prostate, pancreas, gastric, ovarian, esophagus and liver. This could serve as an appropriate target site for developing point-of-care approaches for cancer detection e.g. designing diagnostic biosensor-based microarrays or kits for both quantification and qualification of the biomarkers. Besides, the miRNA candidates could be efficiently applied to cancer therapeutic approaches.     

Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.     

Clinical implications and utility of field cancerization

Cancer begins with multiple cumulative epigenetic and genetic alterations that sequencially transform a cell, or a group of cells in a particular organ. The early genetic events might lead to clonal expansion of pre-neoplastic daughter cells in a particular tumor field. Subsequent genomic changes in some of these cells drive them towards the malignant phenotype. These transformed cells are diagnosed histopathologically as cancers owing to changes in cell morphology. Conceivably, a population of daughter cells with early genetic changes (without histopathology) remain in the organ, demonstrating the concept of field cancerization. With present technological advancement, including laser capture microdisection and high-throughput genomic technologies, carefully designed studies using appropriate control tissue will enable identification of important molecular signatures in these genetically transformed but histologically normal cells. Such tumor-specific biomarkers should have excellent clinical utility. This review examines the concept of field cancerization in several cancers and its possible utility in four areas of oncology; risk assessment, early cancer detection, monitoring of tumor progression and definition of tumor margins.     

Meta-analysis of microRNA-183 family expression in human cancer studies comparing cancer tissues with noncancerous tissues

MicroRNA-183 (miR-183) family is proposed as promising biomarkers for early cancer detection and accurate prognosis as well as targets for more efficient treatment. The results of their expression feature in cancer tissues are inconsistent and controversy still exists in identifying them as new biomarkers of cancers. Therefore, to systemically evaluate the most frequently reported cancers in which miR-183 family members were up- or down-regulated is critical for further investigation on physiological impact of its aberrant regulation in specific cancers. The published studies that compared the level of miR-183 family expression in cancer tissues with those in noncancerous tissues were reviewed by the meta-analysis with a vote-counting strategy. Among the 49 included studies, a total of 18 cancers were reported, with 11 cancers reported in at least two studies. In the panel of miR-183 family members' expression analysis, colorectal cancer and prostate cancer ranked at the top among consistently reported cancer types with up-regulated feature. Bladder cancer, lung cancer and hepatocellular carcinoma were the third most frequently reported cancer types with significant over-expression of miR-96, miR-182 and miR-183 respectively. Breast cancer and gastric cancer were presented with inconsistent regulations and the members of this family had their own distinct regulated features in other different cancers. MiR-183 family, either individually or as a cluster, may be useful prognostic markers and/or therapeutic targets in several cancers. Further studies and repeat efforts are still required to determine the role of miR-183 family in various cancer progressions.     

Defining a mutational signature for endometrial cancer screening and early detection

IntroductionThe current availability of genomic information represents an opportunity to develop new strategies for early detection of cancer. New molecular tests for endometrial cancer may improve performance and failure rates of histological aspirate-based diagnosis, and provide promising perspectives for a potential screening scenario. However, the selection of relevant biomarkers to develop efficient strategies can be a challenge.Materials and methodsWe developed an algorithm to identify the largest number of patients with endometrial cancer using the minimum number of somatic mutations based on The Cancer Genome Atlas (TCGA) dataset.ResultsThe algorithm provided the number of subjects with mutations (sensitivity) for a given number of biomarkers included in the signature. For instance, by evaluating the 50 most representative point mutations, up to 81.9% of endometrial cancers can be identified in the TCGA dataset. At gene level, a 92.9% sensitivity can be obtained by interrogating five genes.DiscussionWe developed a computational method to aid in the selection of relevant genomic biomarkers in endometrial cancer that can be adapted to other cancer types or diseases.     

Integrated Analysis Reveals together miR-182, miR-200c and miR-221 Can Help in the Diagnosis of Prostate Cancer

Research has shown that microRNAs are promising biomarkers that can be used to promote a more accurate diagnosis of cancer. In this study, we developed an integrated multi-step selection process to analyze available high-throughput datasets to obtain information on microRNAs as cancer biomarkers. Applying this approach to the microRNA expression profiles of prostate cancer and the datasets in The Cancer Genome Atlas Data Portal, we identified miRNA-182, miRNA-200c and miRNA-221 as possible biomarkers for prostate cancer. The associations between the expressions of these three microRNAs with clinical parameters as well as their diagnostic capability were studied. Several online databases were used to predict the target genes of these three microRNAs, and the results were confirmed by significant statistical correlations. Comparing with the other 18 types of cancers listed in The Cancer Genome Atlas Data Portal, we found that the combination of both miRNA-182 and miRNA-200c being up-regulated and miRNA-221 being down-regulated only happens in prostate cancer. This provides a unique biological characteristic for prostate cancer that can potentially be used for diagnosis based on tissue testing. In addition, our study also revealed that these three microRNAs are associated with the pathological status of prostate cancer.     

Cancer prevention in primary care. Current trends and some prospects for the future--II.

Cancer control encompasses the whole spectrum from prevention and early diagnosis to treatment and palliation. The key to the future of cancer control will be to establish multidisciplinary approaches to each type of cancer across this spectrum. For primary prevention this requires some understanding of the causes of each cancer. Although understanding of the aetiology of cancer has greatly improved, prospects for the primary prevention of many common cancers remain remote. Other approaches currently under evaluation include chemoprevention and the use of biomarkers (discussed last week). The identification of predisposing genes for some of the common cancers may have a considerable impact on the ability to recognise those at risk. Overall, however, mortality trends indicate that reduction of smoking remains the main priority for cancer prevention in the United Kingdom. For primary care teams, brief interventions to reduce smoking are likely to achieve the greatest benefit. This should be seen as part of broader policies aimed at achieving change in the whole population. The government must acknowledge its major responsibility to cancer prevention by banning all forms of advertising and promotion of tobacco.     

Cancer prevention in primary care. Current trends and some prospects for the future--1.

Cancer control encompasses the whole spectrum from prevention and early diagnosis to treatment and palliation. The key to the future of cancer control will be to establish multidisciplinary approaches to each type of cancer across this spectrum. For primary prevention this requires some understanding of the causes of each cancer. Although understanding of the aetiology of cancer has greatly improved, prospects for the primary prevention of many common cancers remain remote. Other approaches currently under evaluation include chemoprevention and the use of biomarkers. The identification of predisposing genes for some of the common cancers may have a considerable impact on the ability to recognise those at risk. Overall, however, mortality trends indicate that reduction of smoking remains the main priority for cancer prevention in the United Kingdom. For primary care teams, brief interventions to reduce smoking are likely to achieve the greatest benefit. This should be seen as part of broader policies aimed at achieving change in the whole population. The government must acknowledge its major responsibility to cancer prevention by banning all forms of advertising and promotion of tobacco.     

Preclinical strategies to define predictive biomarkers for therapeutically relevant cancer subtypes

Defining key driver mutations in cancer, the resulting aberrations in molecular mechanisms and the subsequent phenotype underpins the development and implementation of novel personalized medicine strategies. The literature is replete with biomarkers of prognosis and therapeutic responsiveness identified in single cohorts of patients that have not been independently validated and as a consequence, not developed. Integrating companion biomarker discovery with therapeutic development at the preclinical stage creates the opportunity to identify candidate biomarkers early, which would significantly facilitate both biomarker and therapeutic development. Advances in “-omic” technologies have led to large-scale efforts in characterizing and cataloguing the full range of aberrations in cancer. These include the International Cancer Genome Consortium and The Cancer Genome Atlas, which aim to comprehensively catalogue the range of genomic aberrations for large numbers of cancers for a progressively increasing range of cancer types and subtypes. The technical challenges associated with achieving these goals in some instances have required the generation of primary xenografts and cell lines. These extensively characterized model systems will provide an unprecedented resource for the discovery of biomarkers of therapeutic responsiveness for established therapies, and the development of companion biomarkers linked with preclinical novel therapeutic development in the future.     

Advances in theranostic biomarkers for tumor immunotherapy

Cancer treatment has known a revolution with the emergence of immune checkpoint inhibitors. However, accurate theranostic biomarkers are lacking. In this review, we discuss different types of biomarkers currently under investigation. First, we focus on tissue biomarkers including PD-L1 expression by immunohistochemistry—the first Food and Drug Administration—approved biomarker—despite conflicting results. In addition, we report on novel biomarkers, including protein-based, molecular (tumor mutational load, immune signature…), circulating (neutrophil-to-lymphocyte ratio, serum cytokines…), and imaging-based biomarkers (radiomic signatures and positron-emission tomography using radiolabeled antibodies). We highlight the limitations of each candidate biomarker and finally discuss combinatorial approaches for their use and the opportunity to switch from a predictive strategy of biomarker research to an adaptive one in the field of cancer immunotherapy.     

Progress and challenges in screening for early detection of ovarian cancer

Ovarian cancer is characterize by few early symptoms, presentation at an advanced stage, and poor survival. As a result, it is the most frequent cause of death from gynecological cancer. During the last decade, a research effort has been directed toward improving outcomes for ovarian cancer by screening for preclinical, early stage disease using both imaging techniques and serum markers. Numerous biomarkers have shown potential in samples from clinically diagnosed ovarian cancer patients, but few have been thoroughly assessed in preclinical disease and screening. The most thoroughly investigated biomarker in ovarian cancer screening is CA125. Prospective studies have demonstrated that both CA125 and transvaginal ultrasound can detect a significant proportion of preclinical ovarian cancers, and refinements in interpretation of results have improved sensitivity and reduced the false-positive rate of screening. There is preliminary evidence that screening can improve survival, but the impact of screening on mortality from ovarian cancer is still unclear. Prospective studies of screening are in progress in both the general population and high-risk population, including the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), a randomized trial involving 200,000 postmenopausal women designed to document the impact of screening on mortality. Recent advances in technology for the study of the serum proteome offer exciting opportunities for the identification of novel biomarkers or patterns of markers that will have greater sensitivity and lead time for preclinical disease than CA125. Considerable interest and controversy has been generated by initial results utilizing surface-enhanced laser desorption/ionization (SELDI) in ovarian cancer. There are challenging issues related to the design of studies to evaluate SELDI and other proteomic technology, as well as the reproducibility, sensitivity, and specificity of this new technology. Large serum banks such as that assembled in UKCTOCS, which contain preclinical samples from patients who later developed ovarian cancer and other disorders, provide a unique resource for carefully designed studies of proteomic technology. There is a sound basis for optimism that further developments in serum proteomic analysis will provide powerful methods for screening in ovarian cancer and many other diseases.     

Circulating tumor cells in the early detection of human cancers

Cancer is a severe disease with high morbidity and mortality globally. Thus, early detection is emerging as an important topic in modern oncology. Although the strategies for early detection have developed rapidly in recent decades, they remain challenging due to the subtle symptoms in the initial stage of the primary tumor. Currently, tumor biomarkers, imaging, and specific screening tests are widely used in various cancer types; however, each method has limitations. The harms are even overweight against the benefits in some cases. Therefore, early detection approaches should be improved urgently. Liquid biopsy, for now, is a convenient and non-invasive way compared to the traditional tissue biopsy in screening and early diagnosis. Circulating tumor cells (CTCs) are vital in liquid biopsy and play a central role in tumor dissemination and metastases. They have promising potential as cancer biomarkers in early detection. This review updates the knowledge of the biology of CTC; it also highlights the CTC enrichment technologies and their applications in the early detection of several human cancers.     

Clinical proteomics of breast cancer

Despite the lifetimes that increased in breast cancers due to the the early screening programs and new therapeutic strategies, many cases still are being lost due to the metastatic relapses. For this reason, new approaches such as the proteomic techniques have currently become the prime objectives of breast cancer researches. Various omic-based techniques have been applied with increasing success to the molecular characterisation of breast tumours, which have resulted in a more detailed classification scheme and have produced clinical diagnostic tests that have been applied to both the prognosis and the prediction of outcome to the treatment. Implementation of the proteomics-based techniques is also seen as crucial if we are to develop a systems biology approach in the discovery of biomarkers of the early diagnosis, prognosis and prediction of the outcome of the breast cancer therapies. In this review, we discuss the studies that have been conducted thus far, for the discovery of diagnostic, prognostic and predictive biomarkers, and evaluate the potential of the discriminating proteins identified in this research for clinical use as breast cancer biomarkers.     

The evolution of molecular diagnosis using digital polymerase chain reaction to detect cancer via cell‐free DNA and circulating tumor cells

Cancer is one of the most important causes of death worldwide. The onset of cancer may be initiated due to a variety of factors such as environment, genetics or even due to personal lifestyle choices. To counteract this tremendous increase, the demand for a new technology has risen. By this means, the use of digital polymerase chain reaction (dPCR) has been shown to be a promising methodology in the early detection of many types of cancers. Furthermore, several researchers confirmed that the use of tumor cell‐free DNA (cfDNA) and circulating tumor cells (CTC) in peripheral blood is essential in revealing an early prognosis of such diseases. Besides this, it was established that dPCR might be used in a much more efficient, accurate, and reliable manner to amplify a variety of genetic material up to the identification of mutations in hematological diseases. Therefore, this article demonstrates the differences between conventional PCR and dPCR as a molecular technique to detect the early onset of cancer. Furthermore, CTC and cfDNA were officially approved by the Food and Drug Administration as new biological biomarkers in cancer development and monitoring.     

Biomarkers in molecular medicine: cancer detection and diagnosis

In spite of advances in diagnostics and therapeutics, cancer remains the second leading cause of death in the U.S. Successful cancer treatment depends not only on better therapies but also on improved methods to assess an individual's risk of developing cancer and to detect cancers at early stages when they can be more effectively treated. Current cancer diagnostic imaging methods are labor-intensive and expensive, especially for screening large asymptomatic populations. Effective screening strategies depend on methods that are noninvasive and detect cancers in their early stages of development. There is increasing interest and enthusiasm in molecular markers as tools for cancer detection and prognosis. It is hoped that newly discovered cancer biomarkers and advances in high-throughput technologies would revolutionize cancer therapies by improving cancer risk assessment, early detection, diagnosis, prognosis, and monitoring therapeutic response. These biomarkers will be used either as stand-alone tests or to complement existing imaging methods.