Emerging molecular biomarkers--blood-based strategies to detect and monitor cancer. Nat Rev Clin Oncol. 2011;8:142-150. [PMID: 21364687 DOI: 10.1038/nrclinonc.2010.220]

Identification of autoantibodies to ECH1 and HNRNPA2B1 as potential biomarkers in the early detection of lung cancer

Identification of biomarkers for early detection of lung cancer (LC) is important, in turn leading to more effective treatment and reduction of mortality. Serological proteome analysis (SERPA) was used to identify proteins around 34 kD as ECH1 and HNRNPA2B1, which had been recognized by serum autoantibody from 25 LC patients. In the validation study, including 90 sera from LC patients and 89 sera from normal individuals, autoantibody to ECH1 achieved an area under the curve (AUC) of 0.799 with sensitivity of 62.2% and specificity of 95.5% in discriminating LC from normal individuals, and showed negative correlation with tumor size (r_s = -0.256, p = 0.023). Autoantibody to HNRNPA2B1 performed an AUC of 0.874 with sensitivity of 72.2% and specificity of 95.5%, and showed negative correlation with lymph node metastasis (r_s = -0.279, p = 0.012). By using longitudinal preclinical samples, autoantibody to ECH1 showed an AUC of 0.763 with sensitivity of 60.0% and specificity of 89.3% in distinguishing early stage LC from matched normal controls, and elevated autoantibody levels could be detected greater than 2 y before LC diagnosis. ECH1 and HNRNPA2B1 are autoantigens that elicit autoimmune responses in LC and their autoantibody can be the potential biomarkers for the early detection of LC.

Electrohydrodynamic-Induced SERS Immunoassay for Extensive Multiplexed Biomarker Sensing

Cancer diagnosis and patient monitoring require sensitive and simultaneous measurement of multiple cancer biomarkers considering that single biomarker analysis present inadequate information on the underlying biological transformations. Thus, development of sensitive and selective assays for multiple biomarker detection might improve clinical diagnosis and expedite the treatment process. Herein, a microfluidic platform for the rapid, sensitive, and parallel detection of multiple cancer-specific protein biomarkers from complex biological samples is presented. This approach utilizes alternating current electrohydrodynamic-induced surface shear forces that provide exquisite control over fluid flow thereby enhancing target-sensor interactions and minimizing non-specific binding. Further, the use of surface-enhanced Raman scattering-based spectral encoding with individual barcodes for different targets enables specific and simultaneous detection of captured protein biomarkers. Using this approach, the specific and sensitive detection of clinically relevant biomarkers including human epidermal growth factor receptor 2 (HER2); Mucin 1, cell surface associated (MUC1); epidermal growth factor receptor; and Mucin 16, cell surface associated (MUC16) at concentrations as low as 10 fg mL^-1 in patient serum is demonstrated. Successful target detection from patient samples further demonstrates the potential of this current approach for the clinical diagnosis, which envisages a clinical translation for a rapid and sensitive appraisal of clinical samples in cancer diagnostics.

Hepatocellular carcinoma suppressor 1 promoter hypermethylation in serum. A diagnostic and prognostic study in hepatitis B

BACKGROUND

Liver cancer ranks as the second leading cause of cancer-related mortality in man worldwide, and hepatocellular carcinoma (HCC) is the most prevalent malignant neoplasm of the liver. The sensitivity of alpha-fetoprotein (AFP) as an HCC diagnostic marker for HCC diagnosis is 39-65%, and one-third patients with HCC are missed using AFP. New biomarkers are needed to diagnose HCC at an earlier stage and to individualize treatment strategies. Hepatocellular carcinoma suppressor 1 (HCCS1) is a newly identified liver tumor suppressor gene.

OBJECTIVE

Our study evaluated the diagnostic value of serum HCCS1 promoter methylation in patients with HCC associated with hepatitis B.

METHODS

We determined the methylation status of serum HCCS1 promoter in 120 patients with HCC, 146 patients with chronic hepatitis B (CHB) and 27 healthy controls (HCs) by methylation-specific polymerase chain reaction (MSP). Evaluation of a cohort with 63 patients with HCC and 44 patients with CHB was set as a validation dataset.

RESULTS

The frequency of HCCS1 promoter methylation in patients with HCC was significantly higher than that in patients with CHB (P<0.001) and HCs (P<0.001), and was associated with tumor node-metastasis (TNM) stage (P=0.01). The sensitivity of serum HCCS1 promoter methylation for discriminating patients with HCC from CHB was 62.5% and that of AFP alone was 55%. Notably, the sensitivity of serum HCCS1 promoter methylation plus AFP level was 81.7%.

CONCLUSION

HCCS1 has potential as a biomarker for diagnosis and prognosis of patients with HCC.

Automated 3D-printed unibody immunoarray for chemiluminescence detection of cancer biomarker proteins

A low cost three-dimensional (3D) printed clear plastic microfluidic device was fabricated for fast, low cost automated protein detection. The unibody device features three reagent reservoirs, an efficient 3D network for passive mixing, and an optically transparent detection chamber housing a glass capture antibody array for measuring chemiluminescence output with a CCD camera. Sandwich type assays were built onto the glass arrays using a multi-labeled detection antibody-polyHRP (HRP = horseradish peroxidase). Total assay time was ∼30 min in a complete automated assay employing a programmable syringe pump so that the protocol required minimal operator intervention. The device was used for multiplexed detection of prostate cancer biomarker proteins prostate specific antigen (PSA) and platelet factor 4 (PF-4). Detection limits of 0.5 pg mL-1 were achieved for these proteins in diluted serum with log dynamic ranges of four orders of magnitude. Good accuracy vs. ELISA was validated by analyzing human serum samples. This prototype device holds good promise for further development as a point-of-care cancer diagnostics tool.

Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer

About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

Ultra-filtration of human serum for improved quantitative analysis of low molecular weight biomarkers using ATR-IR spectroscopy

Monitoring of changes in the concentrations of the low molecular weight constituents enhanced by abundant proteins depletion.

Strategies for Isolation and Molecular Profiling of Circulating Tumor Cells

Cancer is the leading cause of death by disease worldwide, and metastasis is responsible for more than 90% of the mortality of cancer patients. Metastasis occurs when tumor cells leave the primary tumor, travel through the blood stream as circulating tumor cells (CTCs), and then colonize secondary tumors at sites distant from the primary tumor. The capture, identification, and analysis of CTCs offer both scientific and clinical benefits. On the scientific side, the analysis of CTCs could help elucidate possible genetic alterations and signaling pathway aberrations during cancer progression, which could then be used to find new methods to stop cancer progression. On the clinical side, non-invasive testing of a patient's blood for CTCs can be used for patient diagnosis and prognosis, as well as subsequent monitoring of treatment efficacy in routine clinical practice. Additionally, investigation of CTCs early in the progression of cancer may reveal targets for initial cancer detection and for anti-cancer treatment. This chapter will evaluate strategies and devices used for the isolation and identification of CTCs directly from clinical samples of blood. Recent progress in the understanding of the significance of both single CTCs and circulating tumor microemboli will be discussed. Also, advancements in the use of CTC-based liquid biopsy in clinical diagnosis and the potential of CTC-based molecular characterization for use in clinical applications will be summarized.

Molecular profiling of single circulating tumor cells from lung cancer patients

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.

AAgAtlas 1.0: a human autoantigen database

Autoantibodies refer to antibodies that target self-antigens, which can play pivotal roles in maintaining homeostasis, distinguishing normal from tumor tissue and trigger autoimmune diseases. In the last three decades, tremendous efforts have been devoted to elucidate the generation, evolution and functions of autoantibodies, as well as their target autoantigens. However, reports of these countless previously identified autoantigens are randomly dispersed in the literature. Here, we constructed an AAgAtlas database 1.0 using text-mining and manual curation. We extracted 45 830 autoantigen-related abstracts and 94 313 sentences from PubMed using the keywords of either ‘autoantigen’ or ‘autoantibody’ or their lexical variants, which were further refined to 25 520 abstracts, 43 253 sentences and 3984 candidates by our bio-entity recognizer based on the Protein Ontology. Finally, we identified 1126 genes as human autoantigens and 1071 related human diseases, with which we constructed a human autoantigen database (AAgAtlas database 1.0). The database provides a user-friendly interface to conveniently browse, retrieve and download human autoantigens as well as their associated diseases. The database is freely accessible at http://biokb.ncpsb.org/aagatlas/. We believe this database will be a valuable resource to track and understand human autoantigens as well as to investigate their functions in basic and translational research.

Plasmonic ELISA based on the controlled growth of silver nanoparticles

Herein, we demonstrate a plasmonic ELISA based on the alkaline phosphatase (ALP)-mediated growth of silver nanoparticles (AgNPs) for the sensitive, rapid, and naked-eye detection of cancer biomarkers in clinical serum samples. This approach was used to measure the low-abundance alpha fetal protein (AFP) in clinical sera, which demonstrates its great capability in the differentiation of cancers and evaluation of therapeutic responses. Impressively, the readout of the plasmonic assay depends on the rapid formation of Ag colloidal solutions with various degrees of yellow color, which can be distinguished by the naked eye, without the need for sophisticated platforms. The limit of detection of the plasmonic ELISA for alpha fetal protein (AFP) can be as low as 0.23 ng mL^-1, which is approximately 10 folds lower than that of conventional ELISA. This plasmonic ELISA opens a new avenue for the early detection of cancers and monitoring of cancer reoccurrence especially in resource-poor regions where convenient diagnostic tools are highly desirable.

Screening the low molecular weight fraction of human serum using ATR-IR spectroscopy

Vibrational spectroscopic techniques can detect small variations in molecular content, linked with disease, showing promise for screening and early diagnosis. Biological fluids, particularly blood serum, are potentially valuable for diagnosis purposes. The so-called Low Molecular Weight Fraction (LMWF) contains the associated peptidome and metabolome and has been identified as potentially the most relevant molecular population for disease-associated biomarker research. Although vibrational spectroscopy can deliver a specific chemical fingerprint of the samples, the High Molecular Weight Fraction (HMWF), composed of the most abundant serum proteins, strongly dominates the response and ultimately makes the detection of minor spectral variations a challenging task. Spectroscopic detection of potential serum biomarkers present at relatively low concentrations can be improved using pre-analytical depletion of the HMWF. In the present study, human serum fractionation by centrifugal filtration was used prior to analysis by Attenuated Total Reflection infrared spectroscopy. Using a model sample based on glycine spiked serum, it is demonstrated that the screening of the LMWF can be applied to quantify blinded concentrations up to 50 times lower. Moreover, the approach is easily transferable to different bodily fluids which would support the development of more efficient and suitable clinical protocols exploring vibrational spectroscopy based ex-vivo diagnostic tools. Revealing serum LMWF for spectral serological diagnostic applications.

High-Throughput Electrochemical Microfluidic Immunoarray for Multiplexed Detection of Cancer Biomarker Proteins

Microchip-based microfluidic electrochemical arrays hold great promise for fast, high-throughput multiplexed detection of cancer biomarker proteins at low cost per assay using relatively simple instrumentation. Here we describe an inexpensive high-throughput electrochemical array featuring 32 individually addressable microelectrodes that is further multiplexed with an 8-port manifold to provide 256 sensors. The gold electrode arrays were fabricated by wet-etching commercial gold compact discs (CD-R) followed by patterned insulation. A print-and-peel method was used to create sub-microliter hydrophobic wells surrounding each sensor to eliminate cross contamination during immobilization of capture antibodies. High-throughput analyses were realized using eight 32-sensor immunoarrays connected to the miniaturized 8-port manifold, allowing 256 measurements in <1 h. This system was used to determine prostate cancer biomarker proteins prostate specific antigen (PSA), prostate specific membrane antigen (PSMA), interleukin-6 (IL-6), and platelet factor-4 (PF-4) in serum. Clinically relevant detection limits (0.05 to 2 pg mL^-1) and 5-decade dynamic ranges (sub pg mL^-1 to well above ng mL^-1) were achieved for these proteins utilizing precapture of analyte proteins on magnetic nanoparticles decorated with enzyme labels and antibodies.

Potential role of microRNA-126 in the diagnosis of cancers: A systematic review and meta-analysis

BACKGROUND

Cancer has become a major public concern all over the world and early diagnosis of cancer is of great benefit for treatment and prognosis. Several studies have investigated the association between abnormal circulating microRNA-126 (miR-126) expression and the risk of various cancers, but the results are inconsistent. Therefore, this meta-analysis was carried out to assess the potential diagnostic value of miR-126 for cancer.

METHODS

Relevant studies were searched from PubMed, Embase, and Web of Science and we calculated the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the summary receiver operator characteristic curve (AUC) to assess the diagnostic value of miR-126 for cancer detection.

RESULTS

A total of 745 cancer patients and 749 controls from 11 studies of 7 papers were included in this meta-analysis. The summary estimates revealed that the pooled sensitivity was 68% (95% confidence interval [CI]: 60-75%), the specificity was 76% (95% CI: 65-85%), the PLR was 2.87 (95% CI: 1.96-4.21), the NLR was 0.42 (95% CI: 0.35-0.52), the DOR was 7 (95% CI: 4-11), and the AUC was 0.77 (95%CI: 0.73-0.80). Moreover, the sample type, cancer type, sample size, and quality score might be sources of heterogeneity.

CONCLUSION

This systematic review and meta-analysis suggests that miR-126 has great potential to be a noninvasive biomarker in the diagnosis of cancer. However, more well-designed studies with larger sample size on the diagnostic value of miR-126 for cancer are needed in the future.

Combined Biomarker and Computed Tomography Screening Strategies for Lung Cancer: Projections of Health and Economic Tradeoffs in the US Population

Background: Lung cancer screening with computed tomography (CT) of individuals who meet certain age and smoking history criteria is the current standard-of-care. Methods: Using a published simulation model, we compared outcomes associated with seven biomarker + CT screening strategies to CT screening alone using Centers for Medicare & Medicaid Services eligibility criteria. We assumed that the biomarker had conditionally independent performance; was used for first-line screening in some, or all, individuals screened; and could be extended to Centers for Medicare & Medicaid Services–ineligible smokers. Strategies differed by inclusion criteria (e.g., pack-years) and proportion of individuals for whom CT remained the first-line test. Each model run simulated a combined cohort of one million men and one million women born in 1950. Primary outcomes were cancer-specific mortality reduction and screening costs; biomarker costs were measured relative to CT. Efficiency frontiers identified optimal health and economic tradeoffs. Sensitivity analysis evaluated the stability of results. Results: Standard-of-care screening yielded an 8.3% cancer-specific mortality reduction in the simulated US population (screened + unscreened individuals). For a biomarker test with 75% sensitivity and 95% specificity, mortality reductions across biomarker + CT strategies ranged from 7.0% to 23.9%. If the biomarker’s cost was >0.86× that of CT, standard-of-care screening remained on the efficiency frontier, indicating that health and economic tradeoffs were equally (or more) efficient relative to all biomarker + CT strategies. Biomarker + CT strategy costs were principally driven by biomarker specificity; mortality reduction was driven by sensitivity. Conclusion: Combined biomarker + CT strategies have the potential to improve future lung cancer screening effectiveness in the United States and achieve economic efficiency that is greater than the current standard-of-care.

HOTAIRM1 as a potential biomarker for diagnosis of colorectal cancer functions the role in the tumour suppressor

Recent studies have revealed many different long noncoding RNAs (lncRNA), however, the investigation for their function and clinical value as tumour biomarkers has scarcely begun. Here, we found that expression of HOTAIRM1 was reduced in colorectal cancer (CRC) tissues compared with matched normal tissues, and plasma HOTAIRM1 levels in CRC patients were less than in controls. The cut-off point was chosen as 0.003 with a sensitivity of 64.00% and a specificity of 76.50% in the validation set. The performance of HOTAIRM1 was highly comparable to carcinoembryonic antigen (CEA), and better than CA19-9 and CA125. The combined assay of HOTAIRM1 and CEA raised the sensitivity and specificity to 84.00%. HOTAIRM1 knockdown resulted in obvious changes in expression of the cell proliferation related to genes and promoted cell proliferation. HOTAIRM1 plays a role of tumour suppressor in CRC; Down-regulation of HOTAIRM1 can serve as a biomarker for CRC, and combined HOTAIRM1 and CEA assay might provide a promising diagnosis for CRC.

Noninvasive strategies for breast cancer early detection

Breast cancer screening and presurgical diagnosis are currently based on mammography, ultrasound and more sensitive imaging technologies; however, noninvasive biomarkers represent both a challenge and an opportunity for early detection of cancer. An extensive number of potential breast cancer biomarkers have been discovered by microarray hybridization or sequencing of circulating DNA, noncoding RNA and blood cell RNA; multiplex analysis of immune-related molecules and mass spectrometry-based approaches for high-throughput detection of protein, endogenous peptides, circulating and volatile metabolites. However, their medical relevance and their translation to clinics remain to be exploited. Once they will be fully validated, cancer biomarkers, used in combination with the current and emerging imaging technologies, represent an avenue to a personalized breast cancer diagnosis.

An integrated cell line-based discovery strategy identified follistatin and kallikrein 6 as serum biomarker candidates of breast carcinoma

Secreted proteins constitute a relevant source of putative cancer biomarkers. Here, we compared the secretome of a series of four genetically-related breast cancer cell lines as a model of aggressiveness using quantitative mass spectrometry. 537 proteins (59.5% of the total identified proteins) predicted to be released or shed from cells were identified. Using a scoring system based on i) iTRAQ value, ii) breast cancer tissue mRNA expression levels, and iii) immunohistochemical staining (public database), a short list of 10 candidate proteins was selected. Using specific ELISA assays, the expression level of the top five proteins was measured in a verification set of 56 patients. The four significantly differentially expressed proteins were then validated in a second independent set of 353 patients. Finally, follistatin (FST) and kallikrein 6 (KLK6) in serum were significantly higher (p-value < 0.0001) in invasive breast cancer patients compared with non-cancerous controls. Using specific cut-off values, FST distinguished breast cancer samples from healthy controls with a sensitivity of 65% and an accuracy of 68%, whereas KLK6 achieved a sensitivity of 55% and an accuracy of 61%. Therefore, we concluded that FST and KLK6 may have significance in breast cancer detection.

BIOLOGICAL SIGNIFICANCE

Discovery of new serum biomarkers that exhibit increased sensitivity and specificity compared to current biomarkers appears to be an essential field of research in cancer. Most biological markers show insufficient diagnostic sensitivity for early breast cancer detection and, for the majority of them, their concentrations are elevated only in metastatic forms of the disease. It is therefore essential to identify clinically reliable biomarkers and develop effective approaches for cancer diagnosis. One promising approach in this field is the study of secreted proteins through proteomic analysis of in vitro progression breast cancer models. Here we have shown that FST and KLK6 are elevated in breast cancer patient serum compared to healthy controls. We expect that our discovery strategy will help to identify cancer-specific and body-fluid-accessible biomarkers.

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Lactose-Functionalized Gold Nanorods for Sensitive and Rapid Serological Diagnosis of Cancer

Timely and accurate diagnosis of cancer is crucial to cancer treatment. However, serological diagnosis of cancer still faces great challenge because the conventional methodology based on the enzyme-linked immune sorbent assay (ELISA) is costly, time-consuming, and complicated, involving multiple steps. Herein, lactose-functionalized gold nanorods (Lac-GNRs) are fabricated as efficient biosensors to detect cancerous conditions based on the unique surface plasmon resonance properties of GNRs and high specificity of lactose to the galectin-1 cancer biomarker. A trace concentration of galectin-1 as small as 10(-13) M can be detected by Lac-GNRs. The comparative study among BSA, galectin-3, and galectin-1 demonstrates the good specificity of Lac-GNRs to galectin-1 either in aqueous solutions or in the complex and heterogeneous serum specimens. Clinical tests show that the Lac-GNRs biosensors can readily distinguish the serums of cancer patients from those of healthy persons simply by using a microplate reader or even direct visual observation. The Lac-GNRs biosensing platform is highly efficient and easy to use and have great potential in rapid screening of cancer patients.

Deciphering the complexity of the cancer proteome for diagnostic applications

The proteome is the most functional component encoded in the genome, yet most features of the proteome that are deregulated in cancer cannot be predicted from genomic analysis alone. These include post-translational modifications (PTMs), sub-cellular localization, networks and circuitry, formation of complexes, and functional activity, all of which could play a role or be affected as part of tumorigenesis. Thus, there is a substantial opportunity to elucidate protein alterations in cancer and to translate knowledge into diagnostics and therapeutics. The progress made in mining the cancer proteome for diagnostic applications and the path forward are herein reviewed.

Comparative Study of Autoantibody Responses between Lung Adenocarcinoma and Benign Pulmonary Nodules

INTRODUCTION

The reduction in lung cancer mortality associated with computed tomography (CT) screening has led to its increased use and a concomitant increase in the detection of benign pulmonary nodules. Many individuals found to have benign nodules undergo unnecessary, costly, and invasive procedures. Therefore, there is a need for companion diagnostics that stratify individuals with pulmonary nodules into high-risk or low-risk groups. Lung cancers can trigger host immune responses and elicit antibodies against tumor antigens. The identification of these autoantibodies (AAbs) and their corresponding antigens may expand our knowledge of cancer immunity, leading to early diagnosis or even benefiting immunotherapy. Previous studies were performed mostly in the context of comparing cancers and healthy (smoker) controls. We have performed one of the first studies to understand humoral immune response in patients with cancer, patients with benign nodules, and healthy smokers.

METHODS

We first profiled seroreactivity to 10,000 full-length human proteins in 40 patients with early-stage lung cancer and 40 smoker controls by using nucleic acid programmable protein arrays to identify candidate cancer-specific AAbs. Enzyme-linked immunosorbent assays of promising candidates were performed on 137 patients with lung cancer and 127 smoker controls, as well as on 170 subjects with benign pulmonary nodules.

RESULTS

From protein microarray screening experiments using a discovery set of 40 patients and 40 smoker controls, 17 antigens showing higher reactivity in lung cancer cases relative to the controls were subsequently selected for evaluation in a large sample set (n = 264) by using enzyme-linked immunosorbent assay. A five-AAb classifier (tetratricopeptide repeat domain 14 [TTC14], B-Raf proto-oncogene, serine/threonine kinase [BRAF], actin like 6B [ACTL6B], MORC family CW-type zinc finger 2 [MORC2], and cancer/testis antigen 1B [CTAG1B]) that can differentiate lung cancers from smoker controls with a sensitivity of 30% at 89% specificity was developed. We further tested AAb responses in subjects with CT-positive benign nodules (n = 170), and developed a five-AAb panel (keratin 8, type II, TTC14, Kruppel-like factor 8, BRAF, and tousled like kinase 1) with a sensitivity of 30% at 88% specificity. Interestingly, messenger RNA levels of six AAb targets (TTC14, BRAF, MORC family CW-type zinc finger 2, cancer/testis antigen 1B, keratin 8, type II, and tousled like kinase 1) were also found to increase in lung adenocarcinoma tissues based on The Cancer Genome Atlas data set.

CONCLUSION

We discovered AAbs associated with lung adenocaricnoma that have the potential to differentiate cancer from CT-positive benign diseases. We believe that these antibodies warrant future validation using a larger sample set and/or longitudinal samples individually or as a panel. They could potentially be part of companion molecular diagnostic modalities that will benefit subjects undergoing CT screening for lung cancer.

Evaluation of Plasma miR-21 and miR-152 as Diagnostic Biomarkers for Common Types of Human Cancers

Stable blood based miRNA species have allowed for the differentiation of patients with various types of cancer. Therefore, specific blood-based miRNA might be considered as a methodology which could be informative of the presence of cancer potentially from multiple distinct organ sites. Recently, miR-21 has been identified as an “oncomir” in various tumors while miR-152 as a tumor suppressor. In this study, we investigated whether circulating miR-21 and miR-152 can be used for early detection of lung cancer (LuCa), colorectal carcinoma (CRC), breast cancer (BrCa) and prostate cancer (PCa), with distinguishing cancer from various benign lesions on these organ sites. We measured the two miRNA levels by using real-time RT-PCR in plasma samples from a total of 204 cancer patients, 159 various benign lesions, and 228 normal subjects. We observed significantly elevated expression of miR-21 and miR-152 in LuCa, CRC, and BrCa when compared with normal controls. We also found upregulation of plasma miR-21 and miR-152 levels in patients with benign lesions of lung and breast, as compared to normal controls, respectively. No significant expression variation of the two miRNAs was observed in PCa or prostatic benign lesions as compared to healthy controls. Receiver operating characteristic (ROC) analyses revealed that miR-21 and/or miR-152 can discriminate LuCa, CRC and BrCa from normal controls. Our results suggest that plasma miR-21 and miR-152 may serve as non-specific noninvasive biomarkers for early screening of LuCa, CRC, and BrCa, but not PCa.

Integrative DNA methylome analysis of pan-cancer biomarkers in cancer discordant monozygotic twin-pairs

Background

A key focus in cancer research is the discovery of biomarkers that accurately diagnose early lesions in non-invasive tissues. Several studies have identified malignancy-associated DNA methylation changes in blood, yet no general cancer biomarker has been identified to date. Here, we explore the potential of blood DNA methylation as a biomarker of pan-cancer (cancer of multiple different origins) in 41 female cancer discordant monozygotic (MZ) twin-pairs sampled before or after diagnosis using the Illumina HumanMethylation450 BeadChip.

Results

We analysed epigenome-wide DNA methylation profiles in 41 cancer discordant MZ twin-pairs with affected individuals diagnosed with tumours at different single primary sites: the breast, cervix, colon, endometrium, thyroid gland, skin (melanoma), ovary, and pancreas. No significant global differences in whole blood DNA methylation profiles were observed. Epigenome-wide analyses identified one novel pan-cancer differentially methylated position at false discovery rate (FDR) threshold of 10 % (cg02444695, P = 1.8 × 10⁻⁷) in an intergenic region 70 kb upstream of the SASH1 tumour suppressor gene, and three suggestive signals in COL11A2, AXL, and LINC00340. Replication of the four top-ranked signals in an independent sample of nine cancer-discordant MZ twin-pairs showed a similar direction of association at COL11A2, AXL, and LINC00340, and significantly greater methylation discordance at AXL compared to 480 healthy concordant MZ twin-pairs. The effects at cg02444695 (near SASH1), COL11A2, and LINC00340 were the most promising in biomarker potential because the DNA methylation differences were found to pre-exist in samples obtained prior to diagnosis and were limited to a 5-year period before diagnosis. Gene expression follow-up at the top-ranked signals in 283 healthy individuals showed correlation between blood methylation and gene expression in lymphoblastoid cell lines at PRL, and in the skin tissue at AXL. A significant enrichment of differential DNA methylation was observed in enhancer regions (P = 0.03).

Conclusions

We identified DNA methylation signatures in blood associated with pan-cancer, at or near SASH1, COL11A2, AXL, and LINC00340. Three of these signals were present up to 5 years prior to cancer diagnosis, highlighting the potential clinical utility of whole blood DNA methylation analysis in cancer surveillance.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-016-0172-y) contains supplementary material, which is available to authorized users.

Circulating miRNAs with prognostic value in metastatic breast cancer and for early detection of metastasis

Metastasis is the principal cause of high morbidity and mortality among breast cancer (BC) patients. Identification of markers that can be routinely monitored to predict onset of metastasis in BC patients and prognosis of metastatic breast cancer (MBC) patients would increase their median survival. In this study, plasma miRNAs of 40 MBC patients were profiled by TaqMan low density arrays and miRNAs with prognostic capacity were identified. The candidates were validated initially in the samples of 237 MBC patients and subsequently in 335 samples from an independent study cohort of BC patients. Sixteen miRNAs were established to be significantly associated with overall survival, and were termed as prognostic miRNA panel template (PROMPT). These included miR-141, miR-144, miR-193b, miR-200a, miR-200b, miR-200c, miR-203, miR-210, miR-215, miR-365, miR-375, miR-429, miR-486-5p, miR-801, miR-1260 and miR-1274a. Additionally, 11 of these miRNAs were also associated with progression-free survival. Their prognostic significance was further confirmed in samples from a second study cohort of BC patients. In addition, miR-200a, miR-200b, miR-200c, miR-210, miR-215 and miR-486-5p were found to be significantly associated with onset of metastasis up to 2 years prior to clinical diagnosis in BC patients. We have thus identified panels of miRNAs, which include metastasis promoting miR-200 family and miR-203, as well as oncogenic and tumor-suppressive miRNAs, that can serve as prognostic markers for MBC, and early detection markers of metastasis in BC.

Engineered Hybrid Nanoparticles for On-Demand Diagnostics and Therapeutics

Together with the simultaneous development of nanomaterials and molecular biology, the bionano interface brings about various applications of hybrid nanoparticles in nanomedicine. The hybrid nanoparticles not only present properties of the individual components but also show synergistic effects for specialized applications. Thus, the development of advanced hybrid nanoparticles for targeted and on-demand diagnostics and therapeutics of diseases has rapidly become a hot research topic in nanomedicine. The research focus is to fabricate novel classes of programmable hybrid nanoparticles that are precisely engineered to maximize drug concentrations in diseased cells, leading to enhanced efficacy and reduced side effects of chemotherapy for the disease treatment. In particular, the hybrid nanoparticle platforms can simultaneously target diseased cells, enable the location to be imaged by optical methods, and release therapeutic drugs to the diseased cells by command. This Account specially discusses the rational fabrication of integrated hybrid nanoparticles and their applications in diagnostics and therapeutics. For diagnostics applications, hybrid nanoparticles can be utilized as imaging agents that enable detailed visualization at the molecular level. By the use of suitable targeting ligands incorporated on the nanoparticles, targeted optical imaging may be feasible with improved performance. Novel imaging techniques such as multiphoton excitation and photoacoustic imaging using near-infrared light have been developed using the intrinsic properties of particular nanoparticles. The use of longer-wavelength excitation sources allows deeper penetration into the human body for disease diagnostics and at the same time reduces the adverse effects on normal tissues. Furthermore, multimodal imaging techniques have been achieved by combining several types of components in nanoparticles, offering higher accuracy and better spatial views, with the aim of detecting life-threatening diseases before symptoms appear. For therapeutics applications, various nanoparticle-based treatment methods such as photodynamic therapy, drug delivery, and gene delivery have been developed. The intrinsic ability of organic nanoparticles to generate reactive oxygen species has been utilized for photodynamic therapy, and mesoporous silica nanoparticles have been widely used for drug loading and controlled delivery. Herein, the development of controlled-release systems that can specifically deliver drug molecules to target cells and release then upon triggering is highlighted. By control of the release of loaded drug molecules at precise sites (e.g., cancer cells or malignant tumors), side effects of the drugs are minimized. This approach provides better control and higher efficacy of drugs in the human body. Future personalized medicine is also feasible through gene delivery methods. Specific DNA/RNA-carrying nanoparticles are able to deliver them to target cells to obtain desired properties. This development may create an evolution in current medicine, leading to more personalized healthcare systems that can reduce the population screening process and also the duration of drug evaluation. Furthermore, nanoparticles can be incorporated with various components that can be used for simultaneous diagnostics and therapeutics. These multifunctional theranostic nanoparticles enable real-time monitoring of treatment process for more efficient therapy.

Circulating MicroRNAs as Biomarkers and Mediators of Cell-Cell Communication in Cancer

The realization of personalized medicine for cancer will rely not only on the development of new therapies, but on biomarkers that direct these therapies to the right patient. MicroRNA expression profiles in the primary tumor have been shown to differ between cancer patients and healthy individuals, suggesting they might make useful biomarkers. However, examination of microRNA expression in the primary tumor requires an invasive biopsy procedure. More recently, microRNAs have been shown to be released from the primary tumor into the circulation where they can be utilized as non-invasive biomarkers to diagnose patients, predict prognosis, or indicate therapeutic response. This review provides an overview of the current use of circulating microRNAs as biomarkers as well as recent findings on their role in regulating cell signaling interactions in the tumor microenvironment.

Piezometric biosensors for anti-apoptotic protein survivin based on buried positive-potential barrier and immobilized monoclonal antibodies

The anti-apoptotic protein survivin (Sur) plays an important role in the regulation of cell division and inducing the chemotherapeutic drug resistance. The Sur protein and its mRNA have recently been studied as cancer biomarkers and potential targets for cancer therapy. In this work, we have focused on the design of immunosensors for the detection of Sur based on buried positive-potential barrier layer structure and anti-survivin antibody. The modification of solid AuQC piezoelectrodes was monitored by recording the resonance frequency shift and electrochemical measurements during each step of the sensor preparation. Our results indicate that the immunosensor with covalently bound monoclonal anti-survivin antibody can detect Sur with the limit of detection, LOD=1.7nM (S/N=3σ). The immunosensor applicability for the analysis of real samples was assessed by testing samples of cell lysate solutions obtained from human astrocytoma (glioblastoma) U-87MG cell line, with the experiments performed using the standard addition method. The good linearity of the calibration curves for PBS and lysate solutions at low Sur concentrations confirm the high specificity of the proposed biosensor and good discrimination against nonspecific interactions with lysate components. The calculations indicate that there is still room to increase the Sur capture capacity for Sur while miniaturizing the sensor. The important advantage of the sensor is that it can be reused by a simple regeneration procedure.

An optical nanoruler based on a conjugated polymer-silver nanoprism pair for label-free protein detection

An optical nanoruler system based on a conjugated polyelectrolyte-silver nanoprism pair is developed for label-free protein detection by taking advantage of the metal-enhanced fluorescence effect of silver nanostructures. Antibody-antigen interactions induce a change in the metal-fluorophore distance, followed by the response of a fluorescent signal of the conjugated polyelectrolyte. The system is used to detect target antigens sensitively and selectively.

Exogenous marker-engineered mesenchymal stem cells detect cancer and metastases in a simple blood assay

Introduction

Mesenchymal stem cells (MSCs) are adult multipotent stem cells that possess regenerative and immunomodulatory properties. They have been widely investigated as therapeutic agents for a variety of disease conditions, including tissue repair, inflammation, autoimmunity, and organ transplantation. Importantly, systemically infused MSCs selectively home to primary and metastatic tumors, though the molecular mechanisms of tumor tropism of MSCs remain incompletely understood. We have exploited the active and selective MSCs homing to cancer microenvironments to develop a rapid and selective blood test for the presence of cancer.

Methods

We tested the concept of using transplanted MSCs as the basis for a simple cancer blood test. MSCs were engineered to express humanized Gaussia luciferase (hGluc). In a minimally invasive fashion, hGluc secreted by MSCs into circulation as a reporter for cancer presence, was assayed to probe whether MSCs co-localize with and persist in cancerous tissue.

Results

In vitro, hGluc secreted by engineered MSCs was detected stably over a period of days in the presence of serum. In vivo imaging showed that MSCs homed to breast cancer lung metastases and persisted longer in tumor-bearing mice than in tumor-free mice (P < 0.05). hGluc activity in blood of tumor-bearing mice was significantly higher than in their tumor-free counterparts (P < 0.05).

Conclusions

Both in vitro and in vivo data show that MSCs expressing hGluc can identify and report small tumors or metastases in a simple blood test format. Our novel and simple stem cell-based blood test can potentially be used to screen, detect, and monitor cancer and metastasis at early stages and during treatment.

Electronic supplementary material

The online version of this article (doi:10.1186/s13287-015-0151-9) contains supplementary material, which is available to authorized users.

Potential Role of MicroRNA-210 as Biomarker in Human Cancers Detection: A Meta-Analysis

We conducted this meta-analysis aimed to evaluate diagnostic accuracy of miR-210 in human cancers. A total of 673 cancer patients and 606 cancer-free individuals from 13 studies were contained in this meta-analysis. The overall diagnostic results in our study showed that the pooled sensitivity was 0.70, specificity was 0.76, and the AUC was 0.80. In addition, the PLR and NLR were 2.9 and 0.39, with DOR of 8. After the outliner exclusion detected by sensitivity analysis, these parameters had minimal change, which confirmed the stability of our work. The results in our studies showed that the miR-210 assay yielded relatively moderate accuracy in cancer patients and cancer-free individual differentiation. More basic researches are needed to highlight its role as supplement in clinical treatment.

Development of a model to predict breast cancer survival using data from the National Cancer Data Base

BACKGROUND

With the large amounts of data on patient, tumor, and treatment factors available to clinicians, it has become critically important to harness this information to guide clinicians in discussing a patient's prognosis. However, no widely accepted survival calculator is available that uses national data and includes multiple prognostic factors. Our objective was to develop a model for predicting survival among patients diagnosed with breast cancer using the National Cancer Data Base (NCDB) to serve as a prototype for the Commission on Cancer's "Cancer Survival Prognostic Calculator."

PATIENTS AND METHODS

A retrospective cohort of patients diagnosed with breast cancer (2003-2006) in the NCDB was included. A multivariable Cox proportional hazards regression model to predict overall survival was developed. Model discrimination by 10-fold internal cross-validation and calibration was assessed.

RESULTS

There were 296,284 patients for model development and internal validation. The c-index for the 10-fold cross-validation ranged from 0.779 to 0.788 after inclusion of all available pertinent prognostic factors. A plot of the observed versus predicted 5 year overall survival showed minimal deviation from the reference line.

CONCLUSION

This breast cancer survival prognostic model to be used as a prototype for building the Commission on Cancer's "Cancer Survival Prognostic Calculator" will offer patients and clinicians an objective opportunity to estimate personalized long-term survival based on patient demographic characteristics, tumor factors, and treatment delivered.

Proteomics in cancer research: Are we ready for clinical practice?

Although genomics has delivered major advances in cancer prognostics, treatment and diagnostics, it still only provides a static image of the situation. To study more dynamic molecular entities, proteomics has been introduced into the cancer research field more than a decade ago. Currently, however, the impact of clinical proteomics on patient management and clinical decision-making is low and the implementations of scientific results in the clinic appear to be scarce. The search for cancer-related biomarkers with proteomics however, has major potential to improve risk assessment, early detection, diagnosis, prognosis, treatment selection and monitoring. In this review, we provide an overview of the transition of oncoproteomics towards translational oncology. We describe which lessons are learned from currently approved protein biomarkers and previous proteomic studies, what the pitfalls and challenges are in clinical proteomics applications, and how proteomic research can be successfully translated into medical practice.

Branched zinc oxide nanorods arrays modified paper electrode for electrochemical immunosensing by combining biocatalytic precipitation reaction and competitive immunoassay mode

Branched zinc oxide nanorods (BZR) arrays, an array with high charge carries collection efficiency and specific surface area, are grown on the reduced graphene oxide-paper working electrode for the first time to construct a paper-based electrochemical (EC) immunosensor. Typically, the BZR are fabricated via a simple hydrothermal process, which can provide abundant sites for antibodies loading. By combining the large surface area of porous zinc oxide (PZS) and good biocompatibility of gold nanoparticles (AuNPs), PZS-AuNPs (PZS@Au) nanocomposites are designed to label horseradish peroxide (HRP) and antigens. After a competitive reaction between antigens and PZS@Au nanocomposites labeled antigens, the signal labels are introduced into the immunosensor, in which, HRP participate in biocatalytic precipitation process. The produced precipitate reduces the electrode surface area and hinders the electron transfer. With the increase of concentration of antigens, the signal labels introduced into the sensor decrease, thus, a signal-on immunoassay for α-fetoprotein detection is constructed. The proposed paper-based EC immunosensor combines enzymatic biocatalytic precipitation reaction and competitive immunoassay mode for the first time, and possesses a wide linear range from 0.2 pg mL(-1) to 500 ng mL(-1) with a detection limit of 0.08 pg mL(-1). In addition, the proposed method is simple, sensitive and specific and can be a promising platform for other protein detection.

Real-time in vivo cancer diagnosis using Raman spectroscopy

Raman spectroscopy has becoming a practical tool for rapid in vivo tissue diagnosis. This paper provides an overview on the latest development of real-time in vivo Raman systems for cancer detection. Instrumentation, data handling, as well as oncology applications of Raman techniques were covered. Optic fiber probes designs for Raman spectroscopy were discussed. Spectral data pre-processing, feature extraction, and classification between normal/benign and malignant tissues were surveyed. Applications of Raman techniques for clinical diagnosis for different types of cancers, including skin cancer, lung cancer, stomach cancer, oesophageal cancer, colorectal cancer, cervical cancer, and breast cancer, were summarized. Schematic of a real-time Raman spectrometer for skin cancer detection. Without correction, the image captured on CCD camera for a straight entrance slit has a curvature. By arranging the optic fiber array in reverse orientation, the curvature could be effectively corrected.

Plasma Autoantibodies Associated with Basal-like Breast Cancers

BACKGROUND

Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detecting and managing this deadly disease.

METHODS

Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed.

RESULTS

We identified 13 AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (P = 0.009) in BLBC patients. In addition, MN1 and TP53 AAbs were associated with worse survival [MN1 AAb marker HR = 2.25, 95% confidence interval (CI), 1.03-4.91; P = 0.04; TP53, HR = 2.02, 95% CI, 1.06-3.85; P = 0.03]. We found limited evidence that AAb levels differed by demographic characteristics.

CONCLUSIONS

These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection.

IMPACT

Our study identifies 13 AAb markers associated specifically with BLBC and may improve detection or management of this deadly disease.

Validation of a multiprotein plasma classifier to identify benign lung nodules

INTRODUCTION

Indeterminate pulmonary nodules (IPNs) lack clinical or radiographic features of benign etiologies and often undergo invasive procedures unnecessarily, suggesting potential roles for diagnostic adjuncts using molecular biomarkers. The primary objective was to validate a multivariate classifier that identifies likely benign lung nodules by assaying plasma protein expression levels, yielding a range of probability estimates based on high negative predictive values (NPVs) for patients with 8 to 30 mm IPNs.

METHODS

A retrospective, multicenter, case-control study was performed using multiple reaction monitoring mass spectrometry, a classifier comprising five diagnostic and six normalization proteins, and blinded analysis of an independent validation set of plasma samples.

RESULTS

The classifier achieved validation on 141 lung nodule-associated plasma samples based on predefined statistical goals to optimize sensitivity. Using a population based nonsmall-cell lung cancer prevalence estimate of 23% for 8 to 30 mm IPNs, the classifier identified likely benign lung nodules with 90% negative predictive value and 26% positive predictive value, as shown in our prior work, at 92% sensitivity and 20% specificity, with the lower bound of the classifier's performance at 70% sensitivity and 48% specificity. Classifier scores for the overall cohort were statistically independent of patient age, tobacco use, nodule size, and chronic obstructive pulmonary disease diagnosis. The classifier also demonstrated incremental diagnostic performance in combination with a four-parameter clinical model.

CONCLUSIONS

This proteomic classifier provides a range of probability estimates for the likelihood of a benign etiology that may serve as a noninvasive, diagnostic adjunct for clinical assessments of patients with IPNs.

Assessment of immune status using blood transcriptomics and potential implications for global health

The immune system plays a key role in health maintenance and pathogenesis of a wide range of diseases. Leukocytes that are present in the blood convey valuable information about the status of the immune system. Blood transcriptomics, which consists in profiling blood transcript abundance on genome-wide scales, has gained in popularity over the past several years. Indeed, practicality and simplicity largely makes up for what this approach may lack in terms of cell population-level resolution. An extensive survey of the literature reveals increasingly widespread use across virtually all fields of medicine as well as across a number of different animal species, including model organisms but also animals of economical importance. Dissemination across such a wide range of disciplines holds the promise of adding a new perspective, breadth or context, to the considerable depth afforded by whole genome profiling of blood transcript abundance. Indeed, it is only through such contextualization that a truly global perspective will be gained from the use of systems approaches. Also discussed are opportunities that may arise for the fields of immunology and medicine from using blood transcriptomics as a common denominator for developing interactions and cooperation across fields of research that have traditionally been and largely remain compartmentalized. Finally, an argument is made for building immunology research capacity using blood transcriptomics platforms in low-resource and high-disease burden settings.

Insights into the application of let-7 family as promising biomarker in cancer screening

Cancer is a leading cause of death worldwide with its low 5-year survival rate. Studies on the accuracy of let-7 family for human cancers have inconsistent conclusions, leading us to conduct this meta-analysis. This meta-analysis comprised of 11 studies from eight articles involving 805 cancer patients and 483 controls. The pooled parameters were as follows: sensitivity, 77 % (95 % confidence interval (CI) 73-81 %); specificity, 80 % (95 % CI 68-88 %); positive likelihood ratio (PLR), 3.8; negative likelihood ratio (NLR), 0.29; and diagnostic odds ratio (DOR) 13.0. In addition, we plotted the SROC and calculated the area under the curve (AUC) of 0.81 (95 % CI 0.78-0.84), which indicated a relatively high descriptive accuracy. In summary, our data suggested that let-7 family might be applied in noninvasive screening tests for human cancers, which needed to be validated in further large-scale studies.

Sox17 promoter methylation in plasma DNA is associated with poor survival and can be used as a prognostic factor in breast cancer

Aberrant DNA methylation that leads to the inactivation of tumor suppressor genes is known to play an important role in the development and progression of breast cancer. Methylation status of cancer-related genes is considered to be a promising biomarker for the early diagnosis and prognosis of tumors. This study investigated the methylation status of the Sox17 gene in breast cancer tissue and its corresponding plasma DNA to evaluate the association of methylation levels with clinicopathological parameters and prognosis.The methylation status of the Sox17 gene promoter was evaluated with methylation-specific polymerase chain reaction (MSP) in 155 paired breast cancer tissue and plasma samples and in 60 paired normal breast tissue and plasma samples. Association of Sox17 methylation status with clinicopathological parameters was analyzed by χ tests. Overall and disease-free survival (DFS) curves were calculated using Kaplan-Meier analysis, and the differences between curves were analyzed by log-rank tests.The frequency of Sox17 gene methylation was 72.9% (113/155) in breast cancer tissues and 58.1% (90/155) in plasma DNA. Sox17 gene methylation was not found in normal breast tissues or in their paired plasma DNA. There was a significant correlation of Sox17 methylation between corresponding tumor tissues and paired plasma DNA (r = 0.688, P < 0.001). Aberrant Sox17 methylation in cancer tissues and in plasma DNA was significantly associated with the tumor node metastasis stage (P = 0.035 and P = 0.001, respectively) and with lymph node metastasis (P < 0.001 and P = 0.001, respectively). Kaplan-Meier survival curves showed that aberrant Sox17 promoter methylation in cancer tissues and plasma DNA was associated with poor DFS (P < 0.005) and overall survival (OS) (P < 0.005). Multivariate analysis showed that Sox17 methylation in plasma DNA was an independent prognostic factor in breast cancer for both DFS (P = 0.020; hazard ratio [HR] = 2.142; 95% confidence interval [CI]: 1.128-4.067) and for OS (P = 0.001; HR = 4.737; 95% CI: 2.088-10.747).Sox17 gene promoter methylation may play an important role in breast cancer progression and could be used as a prognostic biomarker to identify patients at risk of developing metastasis or recurrence after mastectomy.

Implementation of proteomics for cancer research: past, present, and future

Cancer is the leading cause of the death, accounts for about 13% of all annual deaths worldwide. Many different fields of science are collaborating together studying cancer to improve our knowledge of this lethal disease, and find better solutions for diagnosis and treatment. Proteomics is one of the most recent and rapidly growing areas in molecular biology that helps understanding cancer from an omics data analysis point of view. The human proteome project was officially initiated in 2008. Proteomics enables the scientists to interrogate a variety of biospecimens for their protein contents and measure the concentrations of these proteins. Current necessary equipment and technologies for cancer proteomics are mass spectrometry, protein microarrays, nanotechnology and bioinformatics. In this paper, we provide a brief review on proteomics and its application in cancer research. After a brief introduction including its definition, we summarize the history of major previous work conducted by researchers, followed by an overview on the role of proteomics in cancer studies. We also provide a list of different utilities in cancer proteomics and investigate their advantages and shortcomings from theoretical and practical angles. Finally, we explore some of the main challenges and conclude the paper with future directions in this field.