Breast cancer biomarkers and molecular medicine: part II

Systematic Glycolytic Enzyme Activity Analysis from Human Serum with PEP Technology

A functional proteomics technology was used to systematically monitor metabolic enzyme activities from resolved serum proteins produced by a modified 2-D gel separation and subsequent Protein Elution Plate, a method collectively called PEP. Both qualitative and quantitative differences in the metabolic enzyme activity could be detected between cancer patient and control group, providing excellent biomarker candidates for cancer diagnosis and drug development. This technology has a wide range of applications; it can be used for rapid functional protein purification and characterization as well as drug target identification and validation. The ability for the PEP technology to efficiently separate and recover functional proteins makes it useful for the analysis of any proteins and its variants; this is especially advantageous for enzyme families with large number of enzymes such as protein kinases, phosphatases, proteases, and metabolic enzymes.

A Kelch domain-containing KLHDC7B and a long non-coding RNA ST8SIA6-AS1 act oppositely on breast cancer cell proliferation via the interferon signaling pathway

In our previous study, the Kelch domain-containing 7B (KLHDC7B) was revealed to be hypermethylated at the promoter but upregulated in breast cancer. In this study, we identified a long non-coding RNA, ST8SIA6-AS1 (STAR1), whose expression was significantly associated with KLHDC7B in breast cancer (R2 = 0.3466, P < 0.01). Involvement of the two genes in tumorigenesis was examined via monitoring their effect on cellular as well as molecular events after each gene dysregulation in cultured mammary cell lines. Apoptosis of MCF-7 decreased by 49.5% and increased by 33.1%, while proliferation noted increase and decrease by up- and downregulation of KLHDC7B, respectively, suggesting its oncogenic property. STAR1, however, suppressed cell migration and increased apoptosis. Network analysis identified many target genes that appeared to have similar regulation, especially in relation to the interferon signaling pathway. Concordantly, expression of genes such as IFITs, STATs, and IL-29 in that pathway was affected by KLHDC7B and STAR1. Taken together, KLHDC7B and STAR1 are both overexpressed in breast cancer and significantly associated with gene modulation activity in the interferon signaling pathway during breast tumorigenesis.

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

Molecular genetics complexity impeding research progress in breast and ovarian cancers

Breast and ovarian cancer are heterogeneous diseases. While breast cancer accounts for 25% of cancers worldwide, ovarian cancer accounts for 3.5% of all cancers and it is considered to be the most lethal type of cancer among women. In Oman, breast cancer accounts for 25% and ovarian cancer for 4.5% of all cancer cases. Various risk factors, including variable biological and clinical traits, are involved in the onset of breast and ovarian cancer. Although highly developed diagnostic and therapeutic methods have paved the way for better management, targeted therapy against specific biomarkers has not yet shown any significant improvement, particularly in triple-negative breast cancer and epithelial ovarian cancer, which are associated with high mortality rates. Thus, elucidating the mechanisms underlying the pathology of these diseases is expected to improve their prevention, prognosis and management. The aim of the present study was to provide a comprehensive review and updated information on genomics and proteomics alterations associated with cancer pathogenesis, as reported by several research groups worldwide. Furthermore, molecular research in our laboratory, aimed at identifying new pathways involved in the pathogenesis of breast and ovarian cancer using microarray and chromatin immunoprecipitation (ChIP), is discussed. Relevant candidate genes were found to be either up- or downregulated in a cohort of breast cancer cases. Similarly, ChIP analysis revealed that relevant candidate genes were regulated by the E2F5 transcription factor in ovarian cancer tissue. An ongoing study aims to validate these genes with a putative role as biological markers that may contribute to the development of targeted therapies for breast and ovarian cancer.

Identification of potential serum biomarkers for breast cancer using a functional proteomics technology

BACKGROUND

Cancer is a genetic disease; its development and metastasis depend on the function of many proteins. Human serum contains thousands of proteins; it is a window for the homeostasis of individual's health. Many of the proteins found in the human serum could be potential biomarkers for cancer early detection and drug efficacy evaluation.

METHODS

In this study, a functional proteomics technology was used to systematically monitor metabolic enzyme and protease activities from resolved serum proteins produced by a modified 2-D gel separation and subsequent Protein Elution Plate, a method collectively called PEP. All the experiments were repeated at least twice to ensure the validity of the findings.

RESULTS

For the first time, significant differences were found between breast cancer patient serum and normal serum in two families of enzymes known to be involved in cancer development and metastasis: metabolic enzymes and proteases. Multiple enzyme species were identified in the serum assayed directly or after enrichment. Both qualitative and quantitative differences in the metabolic enzyme and protease activity were detected between breast cancer patient and control group, providing excellent biomarker candidates for breast cancer diagnosis and drug development.

CONCLUSIONS

This study identified several potential functional protein biomarkers from breast cancer patient serum. It also demonstrated that the functional proteomics technology, PEP, can be applied to the analysis of any functional proteins in human serum which contains thousands of proteins. The study indicated that the functional domain of the human serum could be unlocked with the PEP technology, pointing to a novel alternative for the development of diagnosis biomarkers for breast cancer and other diseases.

Overexpression of ANLN contributed to poor prognosis of anthracycline-based chemotherapy in breast cancer patients

PURPOSE

To investigate the associations of ANLN expression with prognosis of breast cancer and clinical outcome of anthracycline-based chemotherapy.

METHODS

This study enrolled 308 breast cancer patients in which 264 of them received anthracycline-based chemotherapy. Immunohistochemistry was used to detect ANLN expression level of the patients. Clinical characteristics of the patients were collected, and associations of ANLN expression with prognosis were analyzed.

RESULTS

Our results showed that ANLN expression was associated with survival of breast cancer patients, and it was also related to clinical outcome of patients received anthracycline-based chemotherapy. Breast cancer patients with high expression of ANLN would have poor prognosis and poor clinical outcome to anthracycline-based chemotherapy.

CONCLUSION

ANLN could be an independent prognosis predictor for breast cancer, and its expression might be used to predict the anthracycline-based chemotherapy clinical outcome in breast cancer patients.

Positive correlation between expression level of mitochondrial serine hydroxymethyltransferase and breast cancer grade

Metabolic reprogramming plays an essential role in supporting the survival and proliferation of cancer cells. Serine hydroxymethyltransferase (SHMT) directs serine to the metabolism of one-carbon unit and the synthesis of thymidilate as a key factor in this metabolic shift. Although the mitochondrial isoform of SHMT (SHMT2) has been proven to be a crucial factor in the serine/glycine metabolism in several cancer cell types, the expression pattern of SHMT2 and the correlation of expression level of SHMT2 and other clinicopathological parameters in clinical breast cancer remain to be explored. In this research, 76 breast cancer patients who underwent modified radical mastectomy were enrolled for immunohistochemical analysis of the expression level of SHMT2 in their cancerous breast tissues for comparison with that in matching, distant noncancerous tissues. The results showed that SHMT2 was not expressed in the distant noncancerous cells. In contrast, SHMT2 protein could be stained in all breast cancer samples at varying degrees. Higher level of SHMT2 was expressed in grade III breast cancer cells than that those in grade I–II (P<0.05). In conclusion, SHMT2 was highly expressed in breast cancer cells, and the expression level of SHMT2 was positively correlated with breast cancer grade, suggesting that SHMT2 could be a target for anticancer therapies.

Neogenin expression is inversely associated with breast cancer grade in ex vivo

BACKGROUND

Neogenin is closely related to the human tumor suppressor gene deleted in colorectal cancer and plays a role in mammary morphogenesis. This study aimed to assess neogenin expression in breast cancer for any clinically significant association.

METHODS

A total of 54 breast cancer patients who underwent modified radical mastectomy were enrolled for immunohistochemical and quantitative real-time PCR analysis of neogenin expression in their cancerous breast tissues in comparison to matching distant non-cancerous tissues.

RESULTS

The data showed that the neogenin protein was either strongly or moderately expressed in the cytoplasm of the distant non-cancerous cells. In contrast, neogenin protein was either weakly or not expressed in the cytoplasm of 51/54 (94.4%) breast cancer cells, among which 13 breast cancer cases did not express neogenin protein at all (13/54, 24.1%). Similarly, levels of neogenin mRNA were significantly lower in breast cancer tissues than that of the matched distant non-cancerous tissues (51/54, 94.4%). Neogenin expression was inversely associated with breast cancer grade; that is, grade III breast cancer expressed much less neogenin than grade I-II (P<0.05).

CONCLUSIONS

This study indicates that neogenin expression in breast cancer tissues is inversely associated with tumor grade.

OncoSearch: cancer gene search engine with literature evidence

In order to identify genes that are involved in oncogenesis and to understand how such genes affect cancers, abnormal gene expressions in cancers are actively studied. For an efficient access to the results of such studies that are reported in biomedical literature, the relevant information is accumulated via text-mining tools and made available through the Web. However, current Web tools are not yet tailored enough to allow queries that specify how a cancer changes along with the change in gene expression level, which is an important piece of information to understand an involved gene's role in cancer progression or regression. OncoSearch is a Web-based engine that searches Medline abstracts for sentences that mention gene expression changes in cancers, with queries that specify (i) whether a gene expression level is up-regulated or down-regulated, (ii) whether a certain type of cancer progresses or regresses along with such gene expression change and (iii) the expected role of the gene in the cancer. OncoSearch is available through http://oncosearch.biopathway.org.

Molecular imaging of EGFR/HER2 cancer biomarkers by protein MRI contrast agents

Epidermal growth factor receptor (EGFR) and HER2 are major prognosis biomarkers and drug targets overexpressed in various types of cancer cells. There is a pressing need to develop MRI contrast agents capable of enhancing the contrast between normal tissues and tumors with high relaxivity, capable of targeting tumors, and with high intratumoral distribution and minimal toxicity. In this review, we first discuss EGFR signaling and its role in tumor progression as a major drug target. We then report our progress in the development of protein contrast agents with significant improvement of both r1 and r2 relaxivities, pharmacokinetics, in vivo retention time, and in vivo dose efficiency. Finally, we report our effort in the development of EGFR-targeted protein contrast agents with the capability to cross the endothelial boundary and with good tissue distribution across the entire tumor mass. The noninvasive capability of MRI to visualize spatially and temporally the intratumoral distribution as well as quantify the levels of EGFR and HER2 would greatly improve our ability to track changes of the biomarkers during tumor progression, monitor treatment efficacy, aid in patient selection, and further develop novel targeted therapies for clinical application.

Breast and ovarian cancers: a survey and possible roles for the cell surface heparan sulfate proteoglycans

Tumor markers are widely used in pathology not only for diagnostic purposes but also to assess the prognosis and to predict the treatment of the tumor. Because tumor marker levels may change over time, it is important to get a better understanding of the molecular changes during tumor progression. Occurrence of breast and ovarian cancer is high in older women. Common known risk factors of developing these cancers in addition to age are not having children or having children at a later age, the use of hormone replacement therapy, and mutations in certain genes. In addition, women with a history of breast cancer may also develop ovarian cancer. Here, the authors review the different tumor markers of breast and ovarian carcinoma and discuss the expression, mutations, and possible roles of cell surface heparan sulfate proteoglycans during tumorigenesis of these carcinomas. The focus is on two groups of proteoglycans, the transmembrane syndecans and the lipid-anchored glypicans. Both families of proteoglycans have been implicated in cellular responses to growth factors and morphogens, including many now associated with tumor progression.

The efficacy and safety of neoadjuvant chemotherapy +/- letrozole in postmenopausal women with locally advanced breast cancer: a randomized phase III clinical trial

This two-arm randomized clinical study aimed to evaluate the efficacy and safety of neoadjuvant concurrent chemotherapy and letrozole in postmenopausal women with locally advanced breast carcinoma. One hundred and one postmenopausal women aged 50-83 years with pathologically proven locally advanced (clinical stage T3, T4 and/or N2, N3) breast cancer were randomly assigned to receive neoadjuvant chemotherapy alone (control arm, n = 51) or neoadjuvant chemotherapy concurrent with letrozole 2.5 mg (study arm, n = 50). Chemotherapy consisted of a median 4 (range 3-5) cycles of intravenous 5-fluorouracil 600 mg/m(2), doxorubicin 60 mg/m(2), and cyclophosphamide 600 mg/m(2), every three weeks. All patients subsequently underwent modified radical mastectomy approximately two weeks after the last cycle of chemotherapy. Pathologic complete response rates were 25.5% and 10.2% in the study and the control group, respectively (P = 0.049). Similarly, clinical complete response rates were 27.6% and 10.2% in the study and the control group, respectively (P = 0.037). In the subgroup analysis of hormone receptor-positive cases, the complete response rates were more prominent in study group compared with control group. Common treatment-related side effects such as nausea, vomiting, bone marrow suppression, and mucositis were similar in both groups, but hot flush was more prevalent in study group compared with control group (P = 0.023). The addition of letrozole concurrently with neoadjuvant chemotherapy provides a higher clinical and pathologic response rates with acceptable toxicity compared with chemotherapy alone in postmenopausal women with locally advanced sensitive breast cancer.

Prognostic value of matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9) and aminopeptidase N/CD13 in breast cancer patients

The aim of this study was to analyse the expression of matrix metalloproteinase-2(MMP-2), matrix metalloproteinase-9 (MMP-9) and aminopeptidase APN/CD13 in breast carcinoma samples, and their possible prognostic value in breast cancer patients. The expression of MMP-2, MMP-9 and APN/CD13 in tumor cells was analysed in 138 breast carcinomas by immunohistochemical staining of tumor cells using the semiquantitative method for the detection of cytoplasmic and membrane reaction in tumor cells as well as stromal cells positivity. MMP-2 was positive in tumor cells of 52.9% patients and in stromal cells of 74.6% patients, while MMP-9 positive tumor and stromal cells were found in 84.8 and 63.8% patients, respectively. Tumor cell APN/CD13 expression was found in 36.2% patients. Stromal cell MMP-2 expression correlated significantly with tumor size and neoangiogenesis. A positive correlation was also observed between tumor cell MMP-9 expression and hormone receptor status. Stromal cell coexpression of MMP-2/MMP-9 correlated significantly with tumor size. APN/CD13 expression in tumor cells significantly correlated with tumor type and neoangiogenesis. Overall survival was significantly shorter in patients with MMP-2, MMP-2/MMP-9 positive tumor cells, and tended to be shorter in patients with APN/CD13 positive tumor cells. Coexpression of MMP-2/MMP-9 in tumor cells was an independent risk factor for patient survival (OD = 13.9). Our results suggest that MMP-2, MMP-9, APN/CD13 expression and MMP-2/MMP-9 coexpression in combination with other standard prognostic factors can serve as a poor prognostic factor in the evaluation of breast cancer prognosis.

Biomarkers for Basal-like Breast Cancer

Initially recognized through microarray-based gene expression profiling, basal-like breast cancer, for which we lack effective targeted therapies, is an aggressive form of carcinoma with a predilection for younger women. With some success, immunohistochemical studies have attempted to reproduce the expression profile classification of breast cancer through identification of subtype-specific biomarkers. This review aims to present an in depth summary and analysis of the current status of basal-like breast cancer biomarker research. While a number of biomarkers show promise for future clinical application, the next logical step is a comprehensive investigation of all biomarkers against a gene expression profile gold standard for breast cancer subtype assignment.

Automated quantitative assessment of HER-2/neu immunohistochemical expression in breast cancer

The expression of the HER-2/neu (HER2) gene, a member of the epidermal growth factor receptor family, has been shown to be a valuable prognostic indicator for breast cancer. However, interobserver variability has been reported in the evaluation of HER2 with immunohistochemistry. It has been suggested that automated computer-based evaluation can provide a consistent and objective evaluation of HER2 expression. In this manuscript, we present an automated method for the quantitative assessment of HER2 using digital microscopy. The method processes microscopy images from tissue slides with a multistage algorithm, including steps of color pixel classification, nuclei segmentation, and cell membrane modeling, and extracts quantitative, continuous measures of cell membrane staining intensity and completeness. A minimum cluster distance classifier merges the features to classify the slides into HER2 categories. An evaluation based on agreement analysis with pathologist-derived HER2 scores, showed good agreement with the provided truth. Agreement varied within the different classes with highest agreement (up to 90%) for positive (3+) slides, and lowest agreement (72%-78%) for equivocal (2+) slides which contained ambiguous scoring. The developed automated method has the potential to be used as a computer aid for the immunohistochemical evaluation of HER2 expression with the objective of increasing observer reproducibility.

An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer

Background

The most common application of microarray technology in disease research is to identify genes differentially expressed in disease versus normal tissues. However, it is known that, in complex diseases, phenotypes are determined not only by genes, but also by the underlying structure of genetic networks. Often, it is the interaction of many genes that causes phenotypic variations.

Results

In this work, using cancer as an example, we develop graph-based methods to integrate multiple microarray datasets to discover disease-related co-expression network modules. We propose an unsupervised method that take into account both co-expression dynamics and network topological information to simultaneously infer network modules and phenotype conditions in which they are activated or de-activated. Using our method, we have discovered network modules specific to cancer or subtypes of cancers. Many of these modules are consistent with or supported by their functional annotations or their previously known involvement in cancer. In particular, we identified a module that is predominately activated in breast cancer and is involved in tumor suppression. While individual components of this module have been suggested to be associated with tumor suppression, their coordinated function has never been elucidated. Here by adopting a network perspective, we have identified their interrelationships and, particularly, a hub gene PDGFRL that may play an important role in this tumor suppressor network.

Conclusion

Using a network-based approach, our method provides new insights into the complex cellular mechanisms that characterize cancer and cancer subtypes. By incorporating co-expression dynamics information, our approach can not only extract more functionally homogeneous modules than those based solely on network topology, but also reveal pathway coordination beyond co-expression.

Quantitative multiplex methylation-specific PCR analysis doubles detection of tumor cells in breast ductal fluid

PURPOSE

The challenges of cytology for accurate diagnosis of breast cancer are well recognized. We previously showed that normal and tumor tissue can be distinguished using a technique called quantitative multiplex methylation-specific PCR (QM-MSP). We hypothesized that quantitative analysis of methylated genes will provide enhanced detection of cancer cells present in cytologic specimens.

EXPERIMENTAL DESIGN

QM-MSP was done on ductal lavage cells from a set of 37 ductal lavage samples from women undergoing mastectomy (27 with cancer and 3 without). Duct histology information was available for each lavaged duct. QM-MSP data was assessed by measuring cumulative methylation index and by receiver operating characteristic threshold analysis. To determine the baseline level of methylation for each gene in this population, cells from 60 ducts of women at high risk of developing breast cancer were analyzed.

RESULTS

QM-MSP findings on a panel of nine genes were correlated to duct histology and ductal lavage cytology. Cytology detected cancer in 33% (7 of 21 ducts) with a specificity of 99% (92 of 93). QM-MSP detected cancer as calculated by cumulative methylation index with a sensitivity of 62% (13 of 21) and specificity of 82% (62 of 76) and by receiver operating characteristic threshold analysis with a sensitivity of 71% (15 of 21) and specificity of 83% (63 of 76).

CONCLUSIONS

Compared with cytology, QM-MSP doubled the sensitivity of detection of cancer. This study provides proof of principle by showing the advantages of using methylation analyses to query cytologic specimens and indicates its potential use in diagnosis and in stratifying risk.

The role of osteopontin in tumor progression and metastasis in breast cancer

The use of cancer biomarkers to anticipate the outlines of disease has been an emerging issue, especially as cancer treatment has made such positive steps in the last few years. Progress in the development of consistent malignancy markers is imminent because advances in genomics and bioinformatics have allowed the examination of immense amounts of data. Osteopontin is a phosphorylated glycoprotein secreted by activated macrophages, leukocytes, and activated T lymphocytes, and is present in extracellular fluids, at sites of inflammation, and in the extracellular matrix of mineralized tissues. Several physiologic roles have been attributed to osteopontin, i.e., in inflammation and immune function, in mineralized tissues, in vascular tissue, and in kidney. Osteopontin interacts with a variety of cell surface receptors, including several integrins and CD44. Binding of osteopontin to these cell surface receptors stimulates cell adhesion, migration, and specific signaling functions. Overexpression of osteopontin has been found in a variety of cancers, including breast cancer, lung cancer, colorectal cancer, stomach cancer, ovarian cancer, and melanoma. Moreover, osteopontin is present in elevated levels in the blood and plasma of some patients with metastatic cancers. Therefore, suppression of the action of osteopontin may confer significant therapeutic activity, and several strategies for bringing about this suppression have been identified. This review looks at the recent advances in understanding the possible mechanisms by which osteopontin may contribute functionally to malignancy, particularly in breast cancer. Furthermore, the measurement of osteopontin in the blood or tumors of patients with cancer, as a way of providing valuable prognostic information, will be discussed based on emerging clinical data.

Identification of Cripto-1 as a Novel Serologic Marker for Breast and Colon Cancer

PURPOSE

Human Cripto-1 (CR-1), a cell membrane glycosylphosphatidylinositol-anchored glycoprotein that can also be cleaved from the membrane, is expressed at high levels in several different types of human tumors. We evaluated whether CR-1 is present in the plasma of patients with breast and colon cancer, and if it can represent a new biomarker for these malignancies.

EXPERIMENTAL DESIGN

We determined CR-1 plasma levels using a sandwich-type ELISA in 21 healthy volunteers, 54 patients with breast cancer, 33 patients with colon carcinoma, and 21 patients with benign breast lesions. Immunohistochemical analysis was also used to assess CR-1 expression in cancerous tissues.

RESULTS

Very low levels of CR-1 (mean+/-SD) were detected in the plasma of healthy volunteers (0.32+/-0.19 ng/mL). A statistically significant increase in the levels of plasma CR-1 was found in patients with colon carcinoma (4.68+/-3.5 ng/mL) and in patients with breast carcinoma (2.97+/-1.48 ng/mL; P<0.001). Although moderate levels of plasma CR-1 were found in women with benign lesions of the breast (1.7+/-0.99 ng/mL), these levels were significantly lower than in patients with breast cancer (P<0.001). Finally, immunohistochemical analysis and real-time reverse transcription-PCR confirmed strong positivity for CR-1 in colon and/or breast tumor tissues.

CONCLUSION

This study suggests that plasma CR-1 might represent a novel biomarker for the detection of breast and colon carcinomas.

Clinical trials design and treatment tailoring: General principles applied to breast cancer research

Nowadays tailored therapy tends to replace standard cancer treatment approaches. Tailoring treatment is possible thanks to clinical trials results that identified subgroups of patients benefiting most from some treatments. Treatment can be tailored on the basis of specific clinical characteristics of the population or on the basis of predictive or prognostic markers. Finally treatment can be tailored for specific molecular targets. This evolution in cancer treatment has triggered the development of innovative trial designs to validate these new hypotheses. The real challenge of the next coming years resides in recruiting large number of patients from specific subgroups to validate tailored therapies.

Proteome profile of the MCF7 cancer cell line: a mass spectrometric evaluation

The development of novel proteomic technologies that will enable the discovery of disease specific biomarkers is essential in the clinical setting to facilitate early diagnosis and increase survivability rates. We are reporting a shotgun two-dimensional (2D) strong cationic exchange/reversed-phase liquid chromatography/electrospray ionization tandem mass spectrometry (SCX/RPLC/ESI-MS/MS) protocol for the analysis of proteomic constituents in cancerous cells. The MCF7 breast cancer cell line was chosen as a model system. A series of optimization steps were performed to improve the LC/MS experimental setup, sample preparation, data acquisition and database search protocols, and a data filtering strategy was developed to enable confident identification of a large number of proteins and potential biomarkers. This research has resulted in the identification of >2000 proteins using multiple filtering and p-value sorting. Approximately 1600-1900 proteins had p < 0.001, and, of these, approximately 60% were matched by >or=2 unique peptides. Alternatively, >99% of the proteins identified by >or=2 unique peptides had p < 0.001. When searching the data against a reversed database of proteins, the rate of false positive identifications was 0.1% at the peptide level and 0.4% at the protein level. The typical reproducibility in detecting overlapping proteins across replicate runs exceeded 90% for proteins matched by >or=2 unique peptides. According to their biological function, approximately 200 proteins were involved in cancer-relevant cellular processes, and over 25 proteins were previously described in the literature as putative cancer biomarkers, as they were found to be differentially expressed between normal and cancerous cell states. Among these, biomarkers such PCNA, cathepsin D, E-cadherin, 14-3-3-sigma, antigen Ki-67, TP53RK, and calreticulin were identified. These data were generated by subjecting to MS analysis approximately 42 microg of sample, analyzing 16 SCX peptide fractions, and interpreting approximately 55,000 MS2 spectra. Total MS time required for analysis was 40 h.

Integrative epidemiology: from risk assessment to outcome prediction

In this paper, we advance the concept of integrative epidemiology. Our unifying premise is that the same genes that are implicated in cancer risk may also be involved in a person's propensity to carcinogenic exposure and/or to modulation of therapeutic outcome. In the coming years, molecular epidemiology will play an increasingly prominent role in early detection of cancer and in identifying genetically high-risk subgroups that might benefit disproportionately from more intensive screening or chemoprevention interventions. Molecular epidemiology is also integral to pharmacogenetic research, by constructing genetic profiles that could be used to individualize therapy and to understand the functional consequences of chemoprevention, chemotherapy, or radiotherapy response. At the level of risk assessment, the focus might be on germline polymorphisms in candidate genes; for early detection, epigenetic events in these same or other genes may be relevant; and tumor tissue expression levels, loss of heterozygosity, genomic amplification, rearrangements, or somatic mutations in the same classes of genes may determine outcome. We will provide examples of how changes in the function of a single gene can contribute to susceptibility to carcinogenic exposure, predisposition to cancer development, patient prognosis, and prediction of outcome.