Breast tumor metastasis: analysis via proteomic profiling

The ability to predict the metastatic behavior of a patient’s cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and, to date, they predict individual outcomes poorly. The ongoing development of high-throughput proteomic profiling technologies is opening new avenues for the investigation of cancer and, through application in tissue-based studies and animal models, will facilitate the identification of molecular signatures that are associated with breast tumor cell phenotype. The appropriate use of these approaches has the potential to provide efficient biomarkers, and to improve our knowledge of tumor biology. This, in turn, will enable the development of targeted therapeutics aimed at ameliorating the lethal dissemination of breast cancer. In this review, we focus on the accumulating proteomic signatures of breast tumor progression, particularly those that correlate with the occurrence of distant metastases, and discuss some of the expected future developments in the field.     

Urinary proteomic profiling for diagnostic bladder cancer biomarkers

The ability to detect and monitor bladder cancer in noninvasively obtained urine samples is a major goal. While a number of protein biomarkers have been identified and commercially developed, none have greatly improved the accuracy of sample evaluation over invasive cystoscopy. The ongoing development of high-throughput proteomic profiling technologies will facilitate the identification of molecular signatures that are associated with bladder disease. The appropriate use of these approaches has the potential to provide efficient biomarkers for the early detection and monitoring of recurrent bladder cancer. Identification of disease-associated proteins will also advance our knowledge of tumor biology, which, in turn, will enable development of targeted therapeutics aimed at reducing morbidity from bladder cancer. In this article, we focus on the accumulating proteomic signatures of urine in health and disease, and discuss expected future developments in this field of research.     

Genomic signatures of breast cancer metastasis

Despite significant advances in the treatment of primary cancer, the ability to predict the metastatic behavior of a patient's cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and they predict individual outcomes poorly. However, the recent introduction of high-throughput microarray technology has opened new avenues in genomic investigation of cancer, and through application in tissue-based studies and appropriate animal models, has facilitated the identification of gene expression signatures that are associated with the lethal progression of breast cancer. The use of these approaches has the potential to greatly impact our knowledge of tumor biology, to provide efficient biomarkers, and enable development towards customized prognostication and therapies for the individual.     

Tissue proteomics for cancer biomarker development: laser microdissection and 2D-DIGE

Novel cancer biomarkers are required to achieve early diagnosis and optimized therapy for individual patients. Cancer is a disease of the genome, and tumor tissues are a rich source of cancer biomarkers as they contain the functional translation of the genome, namely the proteome. Investigation of the tumor tissue proteome allows the identification of proteomic signatures corresponding to clinico-pathological parameters, and individual proteins in such signatures will be good biomarker candidates. Tumor tissues are also a rich source for plasma biomarkers, because proteins released from tumor tissues may be more cancer specific than those from non-tumor cells. Two-dimensional difference gel electrophoresis (2D-DIGE) with novel ultra high sensitive fluorescent dyes (CyDye DIGE Fluor satulation dye) enables the efficient protein expression profiling of laser-microdissected tissue samples. The combined use of laser microdissection allows accurate proteomic profiling of specific cells in tumor tissues. To develop clinical applications using the identified biomarkers, collaboration between research scientists, clinicians and diagnostic companies is essential, particularly in the early phases of the biomarker development projects. The proteomics modalities currently available have the potential to lead to the development of clinical applications, and channeling the wealth of produced information towards concrete and specific clinical purposes is urgent.     

Autoantibodies in cancer: prognostic biomarkers and immune activation

The development of proteomic technologies that display a wide variety of antigenic structures has led to the identification of autoantibodies to cancer-derived tumor antigens. These autoantibodies have been detected in sera from patients with multiple cancer types, and are being evaluated as biomarkers for early cancer detection. It is not known whether these antibodies also contribute to active immune surveillance or even tumorigenicity of developing tumors. Here, we review which tumor antigen-specific antibodies are prognostic biomarkers of cancer outcome, and emerging proteomic methods for the isolation and cloning of these antibodies for potential molecular diagnostics and therapeutics.     

Autoantibodies in cancer: prognostic biomarkers and immune activation

The development of proteomic technologies that display a wide variety of antigenic structures has led to the identification of autoantibodies to cancer-derived tumor antigens. These autoantibodies have been detected in sera from patients with multiple cancer types, and are being evaluated as biomarkers for early cancer detection. It is not known whether these antibodies also contribute to active immune surveillance or even tumorigenicity of developing tumors. Here, we review which tumor antigen-specific antibodies are prognostic biomarkers of cancer outcome, and emerging proteomic methods for the isolation and cloning of these antibodies for potential molecular diagnostics and therapeutics.     

Gut microbiota,inflammation, and molecular signatures of host response to infection

Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.     

Application of protein microarrays for multiplexed detection of antibodies to tumor antigens in breast cancer

There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum; may exist in greater concentrations than their cognate antigens; and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies.     

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.     

Development of biosensors for cancer clinical testing

Biosensors are devices that combine a biochemical recognition/binding element (ligand) with a signal conversion unit (transducer). Biosensors are already used for several clinical applications, for example for electrochemical measurement of blood glucose concentrations. Application of biosensors in cancer clinical testing has several potential advantages over other clinical analysis methods including increased assay speed and flexibility, capability for multi-target analyses, automation, reduced costs of diagnostic testing and a potential to bring molecular diagnostic assays to community health care systems and to underserved populations. They have the potential for facilitating Point of Care Testing (POCT), where state-of-the-art molecular analysis is carried out without requiring a state-of-the-art laboratory. However, not many biosensors have been developed for cancer-related testing. One major challenge in harnessing the potential of biosensors is that cancer is a very complex set of diseases. Tumors vary widely in etiology and pathogenesis. Oncologists rely heavily on histological characterization of tumors and a few biomarkers that have demonstrated clinical utility to aid in patient management decisions. New genomic and proteomic molecular tools are being used to profile tumors and produce "molecular signatures." These signatures include genetic and epigenetic signatures, changes in gene expression, protein profiles and post-translational modifications of proteins. These molecular signatures provide new opportunities for utilizing biosensors. Biosensors have enormous potential to deliver the promise of new molecular diagnostic strategies to patients. This article describes some of the basic elements of cancer biology and cancer biomarkers relevant for the development of biosensors for cancer clinical testing, along with the challenges in using this approach.     

Extracellular heat shock proteins and cancer: New perspectives

Heat shock proteins (HSPs) are a large family of molecular chaperones aberrantly expressed in cancer. The expression of HSPs in tumor cells has been shown to be implicated in the regulation of apoptosis, immune responses, angiogenesis and metastasis. Given that extracellular vesicles (EVs) can serve as potential source for the discovery of clinically useful biomarkers and therapeutic targets, it is of particular interest to study proteomic profiling of HSPs in EVs derived from various biological fluids of cancer patients. Furthermore, a divergent expression of circulating microRNAs (miRNAs) in patient samples has opened new opportunities in exploiting miRNAs as diagnostic tools. Herein, we address the current literature on the expression of extracellular HSPs with particular interest in HSPs in EVs derived from various biological fluids of cancer patients and different types of immune cells as promising targets for identification of clinical biomarkers of cancer. We also discuss the emerging role of miRNAs in HSP regulation for the discovery of blood-based biomarkers of cancer. We outline the importance of understanding relationships between various HSP networks and co-chaperones and propose the model for identification of HSP signatures in cancer. Elucidating the role of HSPs in EVs from the proteomic and miRNAs perspectives may provide new opportunities for the discovery of novel biomarkers of cancer.     

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.     

microRNAs in breast cancer: regulatory roles governing the hallmarks of cancer

A large number of etiological factors and the complexity of breast cancers present challenges for prevention and treatment. Recently, the emergence of microRNAs (miRNAs) as cancer biomarkers has added an extra dimension to the ‘molecular signatures’ of breast cancer. Bioinformatic analyses indicate that each miRNA can regulate hundreds of target genes and could serve functionally as ‘oncogenes’ or ‘tumour suppressor’ genes, and co‐ordinate multiple cellular processes relevant to cancer progression. A number of studies have shown that miRNAs play important roles in breast tumorigenesis, metastasis, proliferation and differentiation of breast cancer cells. This review provides a comprehensive overview of miRNAs with established functional relevance in breast cancer, their established target genes and resulting cellular phenotype. The role and application of circulating miRNAs in breast cancer is also discussed. Furthermore, we summarize the role of miRNAs in the hallmarks of breast cancer, as well as the possibility of using miRNAs as potential biomarkers for detection of breast cancer.     

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.     

Advanced proteomic technologies for cancer biomarker discovery

Proteomic technologies have experienced major improvements in recent years. Such advances have facilitated the discovery of potential tumor markers with improved sensitivities and specificities for the diagnosis, prognosis and treatment monitoring of cancer patients. This review will focus on four state-of-the-art proteomic technologies, namely 2D difference gel electrophoresis, MALDI imaging mass spectrometry, electron transfer dissociation mass spectrometry and reverse-phase protein array. The major advancements these techniques have brought about and examples of their applications in cancer biomarker discovery will be presented in this review, so that readers can appreciate the immense progress in proteomic technologies from 1997 to 2008. Finally, a summary will be presented that discusses current hurdles faced by proteomic researchers, such as the wide dynamic range of protein abundance, standardization of protocols and validation of cancer biomarkers, and a 5-year view of potential solutions to such problems will be provided.     

Cancer proteomics

Conclusion The future of cancer diagnostics will be based on a panel of proteomic biomarkers. They could be used to detect cancer at an early stage, to predict and to direct therapies. Enzymes and related proteins are important biological molecules, which could serve as cancer biomarkers. These biomarkers could be intact or fragments of proteins. The challenge is to be able to find and validate these potential biomarkers as clinical diagnostics. With the advances in proteomic technologies, we are closer than ever to find these “new” enzyme molecules or fragments. The translation of newly discovered biomarkers could provide an opportunity to revolutionize the era of personalized medicine.     

Specific 50'CpG island methylation signatures of FHIT and p16 genes and their potential diagnostic relevance in Indian breast cancer patients

Even after tremendous molecular studies, early detection,more accurate and sensitive diagnosis, and prognosis of breast cancer appear to be a riddle so far. To stab the enigma, this study is designed to envisage DNA methylation signatures as cancer-specific and stage-specific biomarkers in Indian patients. Rigorous review of scattered scientific reports on aberrant DNA methylation helped us to select and analyze a potential tumor suppressor gene pair (FHIT and p16 genes) in breast cancer patients. Methylation signatures from 232 primary sporadic breast cancer patients were pinpointed by methylation-specific PCR (MSP). To increase the sensitivity, we combined both MSP and expression studies (RT-PCR and Northern blotting) in a reproducible manner. Statistical analysis illustrated that hypermethylation of FHIT gene ( p < 0.0001) and p16 gene ( p=0.04) may be used as a potential diagnostic marker to diagnose the early and locally advanced stages of breast cancer. Additionally, the study authenticates the dependency of methylation and expressional loss of p16 gene on FHIT gene silencing. This observation not only describes the severity of disease when both genes are silenced but also drives to speculate the molecular cross talk between two genes or genetic pathways dictated by them separately.