Challenges to developing proteomic-based breast cancer diagnostics

Over the past decade, multiple genetic and histological approaches have accelerated development of new breast cancer diagnostics and treatment paradigms. Multiple distinct genetic subtypes of breast cancers have been defined, and this has progressively led toward more personalized medicine in regard to treatment options. There still remains a deficiency in the development of molecular diagnostic assays that can be used for breast cancer detection and pretherapy clinical decisions. In particular, the type of cancer-specific biomarker typified by a serum or tissue-derived protein. Progress in this regard has been minimal, especially in comparison to the rapid advancements in genetic and histological assays for breast cancers. In this review, some potential reasons for this large gap in developing protein biomarkers will be discussed, as well as new strategies for improving these approaches. Improvements in the study design of protein biomarker discovery strategies in relation to the genetic subtypes and histology of breast cancers is also emphasized. The current successes in use of genetic and histological assays for breast cancer diagnostics are summarized, and in that context, the current limitations of the types of breast cancer-related clinical samples available for protein biomarker assay development are discussed. Based on these limitations, research strategies emphasizing identification of glycoprotein biomarkers in blood and MALDI mass spectrometry imaging of tissues are described.     

Using Functional Genetics to Understand Breast Cancer Biology

Genetic screens were for long the prerogative of those that studied model organisms. The discovery in 2001 that gene silencing through RNA interference (RNAi) can also be brought about in mammalian cells paved the way for large scale loss-of-function genetic screens in higher organisms. In this article, we describe how functional genetic studies can help us understand the biology of breast cancer, how it can be used to identify novel targets for breast cancer therapy, and how it can help in the identification of those patients that are most likely to respond to a given therapy.Much remains to be learned regarding the function of mammalian genes. Only some quarter of all human genes have well-described functions. It is likely that quite a few of these currently unannotated genes will turn out to play key parts in cancer biology. For example, a 70-gene gene signature that can discriminate breast tumors of good and poor prognosis contained some 20 genes of currently unknown function (van ‘t Veer et al. 2002). The fact that these genes of unknown function foretell breast cancer prognosis hints at a role for at least some of these genes in breast cancer biology. The unbiased search for genes that contribute to breast cancer development is therefore likely to yield a rich harvest of new insights. RNA interference allows us to suppress genes systematically on a large scale and study the effects of gene suppression on specific cellular processes or signaling pathways. Consequently, RNA interference-based genetic screens have the potential to deepen our understanding of the molecular events that cause breast cancer, to find novel targets for therapy and to find biomarkers of drug responsiveness. In this article, we will describe the technologies available to perform both gain-of-function and loss-of-function genetic screens and will illustrate how such functional genetic screens have been used in the recent past to study a variety of outstanding questions in the biology of breast cancer.     

Epigenetic gene silencing in the Wnt pathway in breast cancer

Breast cancer is one of the most common malignancies in women. Despite advances in treatment of endocrine-dependent tumors, the complete molecular basis of transformation is still unknown. What is clear is that a variety of genetic lesions and epigenetic modifications are present in the neoplasm. Disregulation of several signaling pathways is known to be associated with breast cancer development, among them is the wingless and integration site growth factor (Wnt) pathway. While genetic mutations of certain components of this pathway, such as APC, are significant contributing factors for colorectal cancers, they are typically not the predominate mechanism associated with breast cancer. Instead, it appears that DNA hypermethylation leads to aberrant regulation of the Wnt pathway in breast cancer, and as such, this review focuses on the epigenetic regulation of Wnt pathway components in breast cancer.     

乳腺癌易感基因突变的狭窄分布及其人群差异性

最近10多年来,包括最重要的BRCA1/2在内的多种女性乳腺癌发生发展相关易感基因获得鉴定,并依据其肿瘤风险相关性程度被分别归入高、中和低外显率组别.随后它们的遗传学变异及致病机制研究在世界范围内得以广泛深入地开展,并揭示出其胚系突变具有人群或地域差异性,且局限于仅占10%~20%家族遗传性和早发性乳腺癌的狭窄分布概貌.这些结果转而提示对于大量散发性乳腺癌发病分子机制的研究而言,必须更深入地探讨多重低风险易感多态性复合效应的影响.     

Genetic and epigenetic alterations in breast cancer: what are the perspectives for clinical practice?

The worldwide incidence of breast cancer affects 1.2 million women each year. In contrast to the high occurrence of this malady, a decline in mortality is reported among industrialized countries. In this respect, both awareness campaigns and substantial progress achieved in therapy and diagnosis allowed for the enhancement of the survival rate in patients with breast cancer. Undoubtedly, oncology research programs played a relevant role in the improvement of therapeutics and diagnostics for breast cancer. Major strides were reported, especially over the last decade and a half, in better understanding molecular and cellular biology events involved in breast cancer pathogenesis and progression of the disease. However, therapeutic approaches for the treatment of patients with breast cancer need further improvement. Therapeutic interventions can chronically compromise both the state of health and quality of life of breast cancer survivors. In addition, current therapeutic approaches have not significantly improved the survival rate in patients with metastatic disease. On these grounds, it is necessary to develop more efficient therapeutics and diagnostic tools, which can improve the health and quality of life of breast cancer survivors and increase the survival rate in patients with metastatic disease. In this respect, the field of cancer research has placed a particular emphasis on the elucidation of genetic and epigenetic alterations that may lead to the pathogenesis of breast cancer and contribute to its progression.     

Computational Screening and Molecular Dynamic Simulation of Breast Cancer Associated Deleterious Non-Synonymous Single Nucleotide Polymorphisms in TP53 Gene

Breast cancer is one of the most common cancers among the women around the world. Several genes are known to be responsible for conferring the susceptibility to breast cancer. Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types. TP53 mutations in breast cancer are known to be related to a poor prognosis and chemo resistance. This renders them as a promising molecular target for the treatment of breast cancer. In this study, we present a computational based screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53. We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB. We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein. Results from our simulations revealed a detailed consequence of the mutations on the p53 DNA-binding core domain that may provide insight for therapeutic approaches in breast cancer.     

Evaluation and treatment of BRCA-positive patients

The recent discovery of the breast cancer-associated genes BRCA1 and BRCA2 has now made it possible to identify individuals who are at a very high risk for the future development of breast cancer. To some extent, however, society has fallen victim to its molecular genetic technology. The significance of these discoveries to the detection, treatment, and prevention of breast cancer cannot be overstated. Nevertheless, the appropriate administration and interpretation of BRCA genetic testing and the treatment of BRCA-positive patients remain controversial issues. Complexities of BRCA testing require that such genetic screening be restricted to selected high-risk patients and that test results be interpreted by a knowledgeable molecular geneticist. Although no medical prophylaxis has been demonstrated to be of benefit in BRCA-positive patients, recent evidence suggests that a prophylactic mastectomy, with or without reconstruction, is a reasonable treatment option that substantially reduces cancer risk.     

Using sufficient direction factor model to analyze latent activities associated with breast cancer survival

High-dimensional gene expression data often exhibit intricate correlation patterns as the result of coordinated genetic regulation. In practice, however, it is difficult to directly measure these coordinated underlying activities. Analysis of breast cancer survival data with gene expressions motivates us to use a two-stage latent factor approach to estimate these unobserved coordinated biological processes. Compared to existing approaches, our proposed procedure has several unique characteristics. In the first stage, an important distinction is that our procedure incorporates prior biological knowledge about gene-pathway membership into the analysis and explicitly model the effects of genetic pathways on the latent factors. Second, to characterize the molecular heterogeneity of breast cancer, our approach provides estimates specific to each cancer subtype. Finally, our proposed framework incorporates sparsity condition due to the fact that genetic networks are often sparse. In the second stage, we investigate the relationship between latent factor activity levels and survival time with censoring using a general dimension reduction model in the survival analysis context. Combining the factor model and sufficient direction model provides an efficient way of analyzing high-dimensional data and reveals some interesting relations in the breast cancer gene expression data.     

Deconstructing the molecular portrait of basal-like breast cancer

Gene-expression profiling has revealed several molecular subtypes of breast cancer, which differ in their pathobiology and clinical outcomes. Basal-like tumors are a newly recognized subtype of breast cancer, which express genes that are characteristic of basal epithelial cells, such as the basal cytokeratins, and are associated with poor relapse-free and overall survival. However, the genetic and epigenetic alterations that are responsible for the biologically aggressive phenotype of these estrogen receptor-negative and HER2/ErbB2-negative tumors are not well understood, thereby hindering efforts to develop targeted therapies. Here, we focus on new insights into the molecular pathogenesis of basal-like breast cancer and explore how these discoveries might impact the treatment of these poor-prognosis tumors.     

Is there a real risk of radiation-induced breast cancer for postmenopausal women?

The risk of radiation-induced breast cancer decreases with increasing age at exposure. Thus, for calculating the individual risk for a patient undergoing mammography, age-related risk coefficients need to be used. In this report, the results of epidemiological studies on risks of radiation-induced breast cancer are reviewed indicating that the available data do not show the risk to be enhanced for women exposed at the age of 55 years or older. This lack of evidence is reflected by the fact that the risk coefficients recommended by national and international advisory bodies differ by a factor of 10 or more for age at exposure of 50–60 years or older. A hypothesis is proposed indicating that the risk of radiation-induced breast cancer might decrease considerably at the time of menopause. The hypothesis is based on the following line of arguments: (1) evidence has accumulated from molecular genetic studies indicating that the development of colorectal cancer requires a cascade of subsequent mutations consisting of at least seven genetic events. (2) For colorectal cancer, the annual rates of incidence and mortality increase with age to the power of 5–6. Thus, the number of mutation steps (minus 1) is approximately reflected by the power of age dependence. (3) For western populations, the incidence and mortality of breast cancer up to the age of about 50 years increase with age to the power of about 6, indicating that a similar number of genetic events might be involved in development of breast cancer as has been identified for colorectal cancer. (4) For women aged 50 years or older, breast cancer occurs at an annual rate that is about proportional to age or age squared. This may mean that after menopause, the processes in the multistep mutation cascade leading to breast cancer are slowed down by a factor of about 4 or more. (5) The constant relative risk model of radiation carcinogenesis implies for solid cancers that radiation acts by inducing additional mutations in the earlier steps of the multistep cascade. It is suggested that the break-point in the age-specific annual rate of breast cancer incidence at menopause is associated with a corresponding drop in radiation sensitivity with respect to induction of breast cancer. Received: 8 January 2001 / Accepted: 20 March 2001     

Establishing a molecular continuum in breast cancer DNA microarrays and benign breast disease.

Although the risk of breast cancer for women in the United States is approximately 1 in 9, identification of risk factors and translation of that knowledge into strategies for prevention have been inhibited by poor understanding of disease pathogenesis. A few benign breast proliferations are associated with higher risks of breast cancer, but definition of a preneoplastic morphologic continuum is lacking. If progression from a premalignant state to malignancy is accompanied by genetic changes, then identification in benign breast disease lesions (BBD) of alterations similar to those found in breast cancer should strengthen the perception of BBD as a premalignant condition. Current testing for hereditary breast cancer susceptibility presumes that only women with invasive breast or ovarian cancer are gene carriers. Therefore, neither in situ breast cancer nor atypical hyperplasias are considered clinically as evidence of a breast-ovarian syndrome, nor are these diagnoses used to predict carrier status within at-risk families. This reflects lack of evidence that breast cancer develops along a recognized morphologic continuum from precursor lesions. New mutation screening procedures such as DNA microarrays can provide sensitivity, specificity, and high throughput that circumvent limitations imposed on the scope of molecular marker analyses applied to archival resources. We have studied a BRCA1-mutant individual with loss of the wild type BRCA1 allele in benign breast proliferations. Both her benign and malignant lesions showed molecularly identical TP53 mutations, indicating that significant genetic alterations can occur in BBD and supporting the clonal evolution from BBD to malignancy.     

Breast cancer prevention strategies for the twentieth century

The incidence of breast cancer has reached epidemic proportions in most Western developed countries. The breast cancer rate is three times higher than in developing countries. In the USA alone, one in eight women will develop breast cancer during her lifetime. Molecular medicine has allowed us to make great advances in understanding disease susceptibility and pathogenesis. It has also let us forge inroads into the genetic screening of women who have a family history of breast cancer. However, women who have been classified as members of the high-risk groups have expectations of effective prevention or prophylactic therapy that cannot, as yet, be delivered. It is time to give serious consideration to the emerging prophylactic strategies that take advantage of the advances in molecular techniques in order to address this deficit.     

Role of E542 and E545 missense mutations of PIK3CA in breast cancer: a comparative computational approach

Recent statistics describe breast cancer as the leading cause of death among women across the world with varied causes and reasons. Lifestyle, diet, genetic and environmental factors introduce their generous contributions towards breast cancer, among which genetic factors have lately become one of the most important aspects in understanding the mechanism. Although various genes have already been reported in causing breast cancer, PIK3CA stands second on the list. Mutations observed in this gene have the ability to trigger the different activities of the cell, thereby bypassing the regular cellular cycle. Among the mutations in PIK3CA, three hotspot mutations were commonly reported, one in the catalytic domain (position HIS1047) and other two in the helical domain (position GLU542 and GLU545). In the helical domain of PIK3CA, the lysine substitution at 542–545 positions was significantly studied in causing breast cancer. To compare the deleterious effect of these mutations, in silico prediction tools along with molecular dynamics simulations and molecular docking approach was initiated to analyse the change in binding landscape upon mutation. In this comparative analysis, we report that the mere existence of mutant E545K can trigger the function of the protein but may not be as harmful as H1047R. Among the two mutations E542K and E545K, the latter shows the most deleterious effect that correlates with the previous reported experimental studies. We assume the results observed in this combinatorial computational study might further pave a better way for providing better treatment procedures.     

RB in Breast Cancer: The Crossroads of Tumorigenesis and Treatment

Cancer is a highly heterogeneous disease, wherein specific determinants modulate disease severity and therapeutic outcomes. In breast cancer, significant effort has been channeled into defining critical genetic effectors of disease behavior. One key molecular determinant is the retinoblastoma tumor suppressor (RB), which is functionally inactivated in the majority of human cancers, and aberrant in nearly half of breast cancers. Deficiency in RB function compromises cell cycle checkpoints, contributes to aggressive tumor proliferation, and is associated with advanced disease. Recent investigation indicates that RB-deficiency has dramatic and disparate effects on the response to therapeutic modalities utilized in the treatment of breast cancer. Loss of RB function promotes inappropriate cell cycle progression during therapeutic challenge. In the context of cytotoxic therapies, this lack of checkpoint function leads to increased sensitivity to the agent. However, RB-deficiency efficiently bypasses the anti-mitogenic function of hormonal therapies and is associated with early disease recurrence following tamoxifen therapy. Thus, RB-pathway status has powerful effects on both tumorigenic proliferation and therapeutic response, and may represent a critical basis for informing breast cancer therapy.     

乳腺癌靶向治疗的分子基础

近年来,乳腺癌靶向治疗的研究取得了显著进展。分子靶向药物通过作用于乳腺癌细胞相关细胞的分子信号传导途径,特异性针对异常环节进行干预,控制细胞基因的表达,从而抑制或杀死肿瘤细胞,以此达到治疗乳腺癌的目的。本文将对乳腺癌靶向治疗的分子基础研究进展做一综述。     

Breast cancer in the personal genomics era

Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The "standard of care" approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer.     

Exome Analysis Reveals Differentially Mutated Gene Signatures of Stage,Grade and Subtype in Breast Cancers

Breast cancers exhibit highly heterogeneous molecular profiles. Although gene expression profiles have been used to predict the risks and prognostic outcomes of breast cancers, the high variability of gene expression limits its clinical application. In contrast, genetic mutation profiles would be more advantageous than gene expression profiles because genetic mutations can be stably detected and the mutational heterogeneity widely exists in breast cancer genomes. We analyzed 98 breast cancer whole exome samples that were sorted into three subtypes, two grades and two stages. The sum deleterious effect of all mutations in each gene was scored to identify differentially mutated genes (DMGs) for this case-control study. DMGs were corroborated using extensive published knowledge. Functional consequences of deleterious SNVs on protein structure and function were also investigated. Genes such as ERBB2, ESP8, PPP2R4, KIAA0922, SP4, CENPJ, PRCP and SELP that have been experimentally or clinically verified to be tightly associated with breast cancer prognosis are among the DMGs identified in this study. We also identified some genes such as ARL6IP5, RAET1E, and ANO7 that could be crucial for breast cancer development and prognosis. Further, SNVs such as rs1058808, rs2480452, rs61751507, rs79167802, rs11540666, and rs2229437 that potentially influence protein functions are observed at significantly different frequencies in different comparison groups. Protein structure modeling revealed that many non-synonymous SNVs have a deleterious effect on protein stability, structure and function. Mutational profiling at gene- and SNV-level revealed differential patterns within each breast cancer comparison group, and the gene signatures correlate with expected prognostic characteristics of breast cancer classes. Some of the genes and SNVs identified in this study show high promise and are worthy of further investigation by experimental studies.