Comparison of Breast Cancer to Healthy Control Tissue Discovers Novel Markers with Potential for Prognosis and Early Detection

This study was initiated to identify biomarkers with potential value for the early detection of poor-outcome breast cancer. Two sets of well-characterized tissues were utilized: one from breast cancer patients with favorable vs. poor outcome and the other from healthy women undergoing reduction mammaplasty. Over 46 differentially expressed genes were identified from a large list of potential targets by a) mining publicly available expression data (identifying 134 genes for quantitative PCR) and b) utilizing a commercial PCR array. Three genes show elevated expression in cancers with poor outcome and low expression in all other tissues, warranting further investigation as potential blood markers for early detection of cancers with poor outcome. Twelve genes showed lower expression in cancers with poor outcome than in cancers with favorable outcome but no differential expression between aggressive cancers and most healthy controls. These genes are more likely to be useful as prognostic tissue markers than as serum markers for early detection of aggressive disease. As a secondary finding was that, when histologically normal breast tissue was removed from a distant site in a breast with cancer, 7 of 38 specimens displayed a cancer-like expression profile, while the remaining 31 were genetically similar to the reduction mammaplasty control group. This finding suggests that some regions of ipsilateral histologically ‘normal’ breast tissue are predisposed to becoming malignant and that normal-appearing tissue with malignant signature might warrant treatment to prevent new primary tumors.     

Pathway-based classification of cancer subtypes

ABSTRACT: BACKGROUND: Molecular markers based on gene expression profiles have been used in experimental and clinical settings to distinguish cancerous tumors in stage, grade, survival time, metastasis, and drug sensitivity. However, most significant gene markers are unstable (not reproducible) among data sets. We introduce a standardized method for representing cancer markers as 2-level hierarchical feature vectors, with a basic gene level as well as a second level of (more stable) pathway markers, for the purpose of discriminating cancer subtypes. This extends standard gene expression arrays with new pathway-level activation features obtained directly from off-the-shelf gene set enrichment algorithms such as GSEA. Such so-called pathway-based expression arrays are significantly more reproducible across datasets. Such reproducibility will be important for clinical usefulness of genomic markers, and augment currently accepted cancer classification protocols. RESULTS: The present method produced more stable (reproducible) pathway-based markers for discriminating breast cancer metastasis and ovarian cancer survival time. Between two datasets for breast cancer metastasis, the intersection of standard significant gene biomarkers totaled 7.47% of selected genes, compared to 17.65% using pathway-based markers; the corresponding percentages for ovarian cancer datasets were 20.65% and 33.33% respectively. Three pathways, consisting of Type_1_diabetes mellitus, Cytokine-cytokine_receptor_interaction and Hedgehog_signaling (all previously implicated in cancer), are enriched in both the ovarian long survival and breast non-metastasis groups. In addition, integrating pathway and gene information, we identified five (ID4, ANXA4, CXCL9, MYLK, FBXL7) and six (SQLE, E2F1, PTTG1, TSTA3, BUB1B, MAD2L1) known cancer genes significant for ovarian and breast cancer respectively. CONCLUSIONS: Standardizing the analysis of genomic data in the process of cancer staging, classification and analysis is important as it has implications for both pre-clinical as well as clinical studies. The paradigm of diagnosis and prediction using pathway-based biomarkers as features can be an important part of the process of biomarker-based cancer analysis, and the resulting canonical (clinically reproducible) biomarkers can be important in standardizing genomic data. We expect that identification of such canonical biomarkers will improve clinical utility of high-throughput datasets for diagnostic and prognostic applications. Reviewers This article was reviewed by John McDonald (nominated by I. King Jordon), Eugene Koonin, Nathan Bowen (nominated by I, King Jordon), and Ekaterina Kotelnikova (nominated by Mikhail Gelfand).     

A Meta Analysis of Pancreatic Microarray Datasets Yields New Targets as Cancer Genes and Biomarkers

The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC), which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.     

Molecular integrity and global gene expression of breast and lung cancer stem cells under long-term storage and recovery

Cryopreservation is a common procedure widely used in biological and clinical sciences. Similar protocols are also applied in preserving cancer stem cells, a field with high promises and challenges. Specific cell surface membrane proteins are considered to be biomarkers of cancer stem cells and they may play a critical role in differentiating stem cells from non stem cells. We have looked at the possible effect of long-term cryopreservation on the molecular integrity of breast MCF7 and lung, A549 and H460, cancer stem cells and to assess if these cells are more sensitive to long-term storage process. We analyzed the expression of CD24 and CD38 as two potent biomarkers of lung cancer stem cells and EpCAM and ALDH that are used as biomarkers of a wide range of cancer stem cells. We also selected three genes essential for the normal functioning of the cells, Fos, MUC1, and HLA. Our results indicate a pattern of down-regulation in the expression of the genes following freezing, in particular among cell surface marker proteins. Global gene expression of the post-thaw breast and lung cancer stem cells also reveals a significant down-regulation in freeze-thaw cells independent from each other. Analyzing the canonical pathways between two populations reveals a significant alteration in the gene expression of the pathways involved in cell cycle, mitosis, and ataxia telangiectasia mutated pathways. Overall, our results indicate that current protocols for long-term storage of lung and breast cancer stem cells may substantially influence the activity and function of genes.     

Standardizing cancer biomarkers criteria: data elements as a foundation for a database. Inflammatory mediator/M-CSF as model marker

The purpose of this position article was to design a set of criteria (data elements) for a wide range of cancer biomarkers (CBs) in an attempt to standardize biomarkers features through a common language as a foundation for a database. Data elements are described as a set of generic criteria, which should characterize nearly all biomarkers introduced in the literature. Data elements were extracted from the review of prominent features that biomarkers represent within various categories. The extracted characteristics of biomarkers produced a short list of shared and unique generic features such as biological nature and history; stage/phase of study; sensitivity and specificity; modes of action; risk assessment; validation status; technology, and recommendation status for diversified biomarkers. To tailor data elements on specific markers, a cytokine, such as macrophage-colony stimulating factor (M-CSF), which has been proposed as a ‹potentially suitable biomarker’ for diagnosis of ovarian, lung, breast, pancreatic, and colorectal cancers, was selected as a Model biomarker. Small scale clinical studies suggested the superior usefulness of M-CSF compared with traditional markers for cancer detection. A key criterion for selecting Model marker and tailoring data elements for detection of cancer was the comparison of data on its specificity and sensitivity with traditional markers. The design of data elements for standardizing CBs criteria is considered a Research Tool and a foundation for developing a comprehensive CBs database useful for oncology researchers for a wide range of biomarkers. Validation, integration and proper packaging, data visualization and recommendation of suitability of CBs, by a panel of experts, for technology development are important challenging next steps toward developing a reliable database, which would allow professionals to effectively retrieve and study integrated information on potentially useful markers; identify important knowledge gaps and limitations of data; and assess state of technologies and commercialization of markers at a point of need. Appropriate use of integrated information on biomarkers in clinical practices would eventually account for more cost-effective characteristics of an individual’s state of health.     

SELDI-TOF serum proteomics and breast cancer: which perspective?

Despite the efforts of recent years, clinicians still lack reliable biomarkers for diagnosis, prognosis and prediction of clinical outcomes in breast cancer patients. Owing to the large number of people potentially involved in the management of this clinical problem, the search for noninvasive and repeatable laboratory assays has been intensive. Recently, the proteomic profiling performed by SELDI-TOF mass spectrometry, has been proposed in order to identify new clusters of serum markers that could be potentially useful in breast cancer management. The purpose of this special report is to review the literature on SELDI-TOF technology applied on serum coming from healthy people and breast cancer patients, in order to verify the clinical applicability of such approach. We conclude that potential new biomarkers, first of all for early diagnosis of breast cancer, need to be validated in larger clinical series.     

Tumor markers in breast cancer--evaluation of their clinical usefulness

Breast cancer is the most common neoplasm affecting women in the Western world. Many studies are still conducted with the purpose of finding markers that could be used for early diagnosis and/or serve as possible reliable prognostic or predictive parameters, but with conflicting results. At present, no markers are available for an early diagnosis of breast cancer For surveillance of patients with diagnosed breast cancer the most widely used serum markers are CA 15-3 and CEA which, in combination with other clinical parameters, could have clinical significance. The most useful and clinically important tissue-based markers in breast cancer are estrogen and progesterone receptors, used as a basis for hormonal therapy, and HER-2 receptors, essential in selecting patients for the treatment with Herceptin. New or potentially new markers for breast cancer include BRCA1 and BRCA2 genes for selecting patients at high risk of developing hereditary breast cancer, as well as urokinase plasminogen activator and inhibitor for assessing prognosis in lymph node-negative patients. Results of tumor and patient genetic analyses including their clinical evaluation will enable application of more individualized and personalized approach in diagnosis and therapy of breast cancer patients.     

Proteomic characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery

Clinical cancer proteomics aims at the identification of markers for early detection and predictive purposes, as well as to provide novel targets for drug discovery and therapeutic intervention. Proteomics-based analysis of traditional sources of biomarkers, such as serum, plasma, or tissue lyzates, has resulted in a wealth of information and the finding of several potential tumor biomarkers. However, many of these markers have shown limited usefulness in a clinical setting, underscoring the need for new clinically relevant sources. Here we present a novel and highly promising source of biomarkers, the tumor interstitial fluid (TIF) that perfuses the breast tumor microenvironment. We collected TIFs from small pieces of freshly dissected invasive breast carcinomas and analyzed them by two-dimensional polyacrylamide gel electrophoresis in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Western immunoblotting, as well as by cytokine-specific antibody arrays. This approach provided for the first time a snapshot of the protein components of the TIF, which we show consists of more than one thousand proteins--either secreted, shed by membrane vesicles, or externalized due to cell death--produced by the complex network of cell types that make up the tumor microenvironment. So far, we have identified 267 primary translation products including, but not limited to, proteins involved in cell proliferation, invasion, angiogenesis, metastasis, inflammation, protein synthesis, energy metabolism, oxidative stress, the actin cytoskeleton assembly, protein folding, and transport. As expected, the TIF contained several classical serum proteins. Considering that the protein composition of the TIF reflects the physiological and pathological state of the tissue, it should provide a new and potentially rich resource for diagnostic biomarker discovery and for identifying more selective targets for therapeutic intervention.     

Biomarker discovery using a comparative omics approach in a mouse model developing heterogeneous mammary cancer subtypes

Identification of biomarkers for early breast cancer detection in blood is a challenging task, since breast cancer is a heterogeneous disease with a wide range of tumor subtypes. This is envisioned to result in differences in serum protein levels. The p53(R270H/+) WAPCre mouse model is unique in that these mice spontaneously develop both ER- and ER+ tumors, in proportions comparable to humans. Therefore, these mice provide a well-suited model system to identify human relevant biomarkers for early breast cancer detection that are additionally specific for different tumor subtypes. Mammary gland tumors were obtained from p53(R270H/+) WAPCre mice and cellular origin, ER, and HER2 status were characterized. We compared gene expression profiles for tumors with different characteristics versus control tissue, and determined genes differentially expressed across tumor subtypes. By using literature data (Gene Ontology, UniProt, and Human Plasma Proteome), we further identified protein candidate biomarkers for blood-based detection of breast cancer. Functional overrepresentation analysis (using Gene Ontology, MSigDB, BioGPS, Cancer GeneSigDB, and proteomics literature data) showed enrichment for several processes relevant for human breast cancer. Finally, Human Protein Atlas data were used to obtain a prioritized list of 16 potential biomarkers that should facilitate further studies on blood-based breast cancer detection in humans.     

Identification and validation of colorectal neoplasia-specific methylation markers for accurate classification of disease

Aberrant DNA methylation occurs early in oncogenesis, is stable, and can be assayed in tissues and body fluids. Therefore, genes with aberrant methylation can provide clues for understanding tumor pathways and are attractive candidates for detection of early neoplastic events. Identification of sequences that optimally discriminate cancer from other diseased and healthy tissues is needed to advance both approaches. Using well-characterized specimens, genome-wide methylation techniques were used to identify candidate markers specific for colorectal neoplasia. To further validate 30 of these candidates from genome-wide analysis and 13 literature-derived genes, including genes involved in cancer and others with unknown functions, a high-throughput methylation-specific oligonucleotide microarray was used. The arrays were probed with bisulfite-converted DNA from 89 colorectal adenocarcinomas, 55 colorectal polyps, 31 inflammatory bowel disease, 115 extracolonic cancers, and 67 healthy tissues. The 20 most discriminating markers were highly methylated in colorectal neoplasia (area under the receiver operating characteristic curve > 0.8; P < 0.0001). Normal epithelium and extracolonic cancers revealed significantly lower methylation. Real-time PCR assays developed for 11 markers were tested on an independent set of 149 samples from colorectal adenocarcinomas, other diseases, and healthy tissues. Microarray results could be reproduced for 10 of 11 marker assays, including eight of the most discriminating markers (area under the receiver operating characteristic curve > 0.72; P < 0.009). The markers with high specificity for colorectal cancer have potential as blood-based screening markers whereas markers that are specific for multiple cancers could potentially be used as prognostic indicators, as biomarkers for therapeutic response monitoring or other diagnostic applications, compelling further investigation into their use in clinical testing and overall roles in tumorigenesis.     

Integrated gene networks in breast cancer development

Breast cancer is a complex and heterogenous disease. Classical molecular medical approaches cannot fully understand and comprehend its pathogenesis. In this review, the development of new biological markers for the early detection and creation of guided and specific therapy of breast cancer are discussed in light of the rapid advances in the “omics”. Results of cancer research in combination with large-scale methods that examine the expression status of genes and proteins have identified a large number of new biomarkers as well as confirmed the human growth hormone as an important player in the pathogenesis of this disease through its autocrine regulation where it influences the activation of Pax5 and HOXA1 gene networks.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

Introduction

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

Method

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

Results

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

Conclusions

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.     

Search of potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry

Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1–17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.     

A pilot study of circulating miRNAs as potential biomarkers of early stage breast cancer

Background

To date, there are no highly sensitive and specific minimally invasive biomarkers for detection of breast cancer at an early stage. The occurrence of circulating microRNAs (miRNAs) in blood components (including serum and plasma) has been repeatedly observed in cancer patients as well as healthy controls. Because of the significance of miRNA in carcinogenesis, circulating miRNAs in blood may be unique biomarkers for early and minimally invasive diagnosis of human cancers. The objective of this pilot study was to discover a panel of circulating miRNAs as potential novel breast cancer biomarkers.

Methodology/Principal Findings

Using microarray-based expression profiling followed by Real-Time quantitative Polymerase Cycle Reaction (RT-qPCR) validation, we compared the levels of circulating miRNAs in plasma samples from 20 women with early stage breast cancer (10 Caucasian American (CA) and 10 African American (AA)) and 20 matched healthy controls (10 CAs and 10 AAs). Using the significance level of p<0.05 constrained by at least two-fold expression change as selection criteria, we found that 31 miRNAs were differentially expressed in CA study subjects (17 up and 14 down) and 18 miRNAs were differentially expressed in AA study subjects (9 up and 9 down). Interestingly, only 2 differentially expressed miRNAs overlapped between CA and AA study subjects. Using receiver operational curve (ROC) analysis, we show that not only up-regulated but also down-regulated miRNAs can discriminate patients with breast cancer from healthy controls with reasonable sensitivity and specificity. To further explore the potential roles of these circulating miRNAs in breast carcinogenesis, we applied pathway-based bioinformatics exploratory analysis and predicted a number of significantly enriched pathways which are predicted to be regulated by these circulating miRNAs, most of which are involved in critical cell functions, cancer development and progression.

Conclusions

Our observations from this pilot study suggest that the altered levels of circulating miRNAs might have great potential to serve as novel, noninvasive biomarkers for early detection of breast cancer.     

分子诊断技术在乳腺癌检测中的最新进展

乳腺癌是一种严重危害女性健康的恶性肿瘤,对其致病基因的检测有助于肿瘤早期诊断、精准治疗及预后评估.本文总结了近年来乳腺癌相关的热点基因,并对相关基因的分子诊断技术、检测方法及应用进行了综述.首次评述了数字PCR方法用于乳腺癌分子检测的进展.全面对比不同分子诊断技术的差别与优缺点,为乳腺癌关键基因的检测提供指导建议与理论支持,并对未来发展趋势做出展望.     

Molecular diagnostics of non-small cell lung cancer using mediastinal lymph nodes sampled by endoscopic ultrasound-guided needle aspiration

Non-small cell lung cancer is a common cancer with significant mortality. Accurate and early staging of this cancer has a significant impact on outcome. Endoscopic ultrasound-guided fine needle aspiration of involved mediastinal lymph nodes is critical for staging. Several molecular markers have been identified recently in association with non-small cell carcinoma of the lung that are promising to make early detection of metastatic disease more reliable.     

Biomarkers for early detection of breast cancer: what, when, and where?

Early detection of breast cancer reduces the suffering and cost to society associated with the disease. A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. The earlier and more accurate the diagnostic biomarker can predict disease onset, the more valuable it becomes. Here, a brief review of existing and emerging approaches for breast cancer biomarker identification and analysis is presented. Those biomarkers found in biological fluids, blood in particular, apparently hold the best promise for fast development of screening assays. Autoantibodies and abnormal tumor-specific DNA methylation found in cell-free plasma DNA may provide the best opportunity for constructing multiplexed and highly redundant tests, which will be sufficiently specific and sensitive for early detection of breast cancer. It is expected that technologies developed for breast cancer detection will be useful for other types of cancer.     

Human small breast epithelial mucin: the promise of a new breast tumor biomarker

Breast cancer remains one of the most frequently diagnosed cancers today. In developed countries, one in eight women is expected to present with breast cancer within her lifetime and an estimated 1,000,000 cases are detected each year worldwide (Canadian Cancer Statistics, http://www.cancer.ca/vgn/images/ portal/cit_86751114/14/33/1959864 11niw_stats2004_en.pdf). For women with recurrent disease, the median time of survival is about 2 years. Despite optimal surgery, adjuvant irradiation, hormonal treatment, and chemotherapy, approximately 30% of patients with localized breast cancer finally develop distant metastases. Early detection, which enables intervention at a localized and potentially curable stage, remains a central goal in breast cancer treatment. Indeed, the 5-year survival rate for women with breast cancer has been shown to increase dramatically when the disease is diagnosed at an early stage: from less than 25% in women with disseminated cancer to about 75% in patients with regional disease and over 95% in women with a localized tumor (Breast Cancer Facts and Figures, 2001-2002, http://www.cancer.org/downloads/STT/BrCaFF 2001.pdf). Unfortunately, only 60% of all breast cancers are diagnosed at a local stage. Any improvement in early detection through identification of tumor biomarkers would have a significant impact on reducing overall breast cancer mortality.