Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome

Progress in understanding role of SPARC protein in gastric cancer

SPARC is a cysteine-rich secretory protein that is highly conservative and shares >70% amino acid sequence homology across all kinds of living organisms. The single-copy gene encoding the SPARC protein is located on human chromosome 5q31.3-q32, consists of 10 exons, and has a full length of 25 900 bp. SPARC protein is mainly expressed in tissue repair-related fibroblasts and endothelial cells, and high expression of SPARC protein has been noted in some aggressive malignant tumors. The incidence and mortality of gastric cancer are high in China, and the high mortality is closely related with tumor invasion and metastasis. SPARC protein is abnormally expressed in gastric carcinoma, and there is still controversy over the role of SPARC in gastric carcinoma. In this paper we review recent progress in understanding the role of SPARC protein in gastric cancer.

Neoplastic and stromal cells contribute to an extracellular matrix gene expression profile defining a breast cancer subtype likely to progress

We recently showed that differential expression of extracellular matrix (ECM) genes delineates four subgroups of breast carcinomas (ECM1, -2, -3- and -4) with different clinical outcome. To further investigate the characteristics of ECM signature and its impact on tumor progression, we conducted unsupervised clustering analyses in 6 additional independent datasets of invasive breast tumors from different platforms for a total of 643 samples. Use of four different clustering algorithms identified ECM3 tumors as an independent group in all datasets tested. ECM3 showed a homogeneous gene pattern, consisting of 58 genes encoding 43 structural ECM proteins. From 26 to 41% of the cases were ECM3-enriched, and analysis of datasets relevant to gene expression in neoplastic or corresponding stromal cells showed that both stromal and breast carcinoma cells can coordinately express ECM3 genes. In in vitro experiments, β-estradiol induced ECM3 gene production in ER-positive breast carcinoma cell lines, whereas TGFβ induced upregulation of the genes leading to ECM3 gene classification, especially in ER-negative breast carcinoma cells and in fibroblasts. Multivariate analysis of distant metastasis-free survival in untreated breast tumor patients revealed a significant interaction between ECM3 and histological grade (p = 0.001). Cox models, estimated separately in grade I-II and grade III tumors, indicated a highly significant association between ECM3 and worse survival probability only in grade III tumors (HR = 3.0, 95% CI = 1.3-7.0, p = 0.0098). Gene Set Enrichment analysis of ECM3 compared to non-ECM3 tumors revealed significant enrichment of epithelial-mesenchymal transition (EMT) genes in both grade I-II and grade III subsets of ECM3 tumors. Thus, ECM3 is a robust cluster that identifies breast carcinomas with EMT features but with accelerated metastatic potential only in the undifferentiated (grade III) phenotype. These findings support the key relevance of neoplastic and stroma interaction in breast cancer progression.

Transcriptional shift identifies a set of genes driving breast cancer chemoresistance

Background

Distant recurrences after antineoplastic treatment remain a serious problem for breast cancer clinical management, which threats patients’ life. Systemic therapy is administered to eradicate cancer cells from the organism, both at the site of the primary tumor and at any other potential location. Despite this intervention, a significant proportion of breast cancer patients relapse even many years after their primary tumor has been successfully treated according to current clinical standards, evidencing the existence of a chemoresistant cell subpopulation originating from the primary tumor.

Methods/Findings

To identify key molecules and signaling pathways which drive breast cancer chemoresistance we performed gene expression analysis before and after anthracycline and taxane-based chemotherapy and compared the results between different histopathological response groups (good-, mid- and bad-response), established according to the Miller & Payne grading system. Two cohorts of 33 and 73 breast cancer patients receiving neoadjuvant chemotherapy were recruited for whole-genome expression analysis and validation assay, respectively. Identified genes were subjected to a bioinformatic analysis in order to ascertain the molecular function of the proteins they encode and the signaling in which they participate. High throughput technologies identified 65 gene sequences which were over-expressed in all groups (P ≤ 0·05 Bonferroni test). Notably we found that, after chemotherapy, a significant proportion of these genes were over-expressed in the good responders group, making their tumors indistinguishable from those of the bad responders in their expression profile (P ≤ 0.05 Benjamini-Hochgerg`s method).

Conclusions

These data identify a set of key molecular pathways selectively up-regulated in post-chemotherapy cancer cells, which may become appropriate targets for the development of future directed therapies against breast cancer.

Profiling of ileal carcinoids

Identification of common molecular mechanisms is needed to facilitate the development of new treatment options for patients with ileal carcinoids.

PURPOSE OF REVIEW

Recent profiling studies on ileal carcinoids were examined to obtain a comprehensive view of risk factors, genetic aberrations, and transcriptional alterations. Special attention was paid to mechanisms that could provide novel targets for therapy.

RESULTS

Genome-wide association studies have shown that single nucleotide polymorphisms (SNPs) at IL12A and DAD1 are associated with an increased risk of ileal carcinoids. Genomic profiling revealed distinct patterns of copy-number alterations in ileal carcinoids. Two groups of carcinoids could be identified by hierarchical clustering. A major group of tumors was characterized by loss on chromosome 18 followed by additional losses on chromosomes 3p, 11q, and 13. Three minimal common regions of deletions were identified at 18q21.1-q21.31, 18q22.1-q22.2, and 18q22.3-q23. A minor group of tumors was characterized by clustered gains on chromosomes 4, 5, 7, 14, and 20. Expression profiling identified three groups of ileal carcinoids by principal component analysis. Tumor progression was associated with changes in gene expression including downregulation of MIR133A. Candidate genes for targeted therapy included ERBB2/HER2, DAD1, PRKCA, RYBP, CASP1, CASP4, CASP5, VMAT1, RET, APLP1, OR51E1, GPR112, SPOCK1, RUNX1, and MIR133A.

CONCLUSION

Profiling of ileal carcinoids has revealed recurrent genetic alterations and distinct patterns of gene expression. Frequent alterations in cellular pathways and genes were identified, suggesting novel targets for therapy. Translational studies are needed to validate suggested molecular targets.

Pro-metastatic tumor–stroma interactions in breast cancer

The vast majority of breast cancer-related deaths are due to metastatic disease. Reciprocal and complex interactions between epithelial tumor cells and the various components of the tumor microenvironment influence tumor progression and metastases although the molecular mechanisms underlying these metastasis-promoting effects are not fully characterized. Identifying and understanding pathways of tumor–stroma cross-talk are likely to lead to the development of novel prognostic biomarkers for metastasis and strategies to prevent metastasis at its earliest stages, resulting in improved patient outcomes.

Collagen I fiber density increases in lymph node positive breast cancers: pilot study

Collagen I (Col1) fibers are a major structural component in the extracellular matrix of human breast cancers. In a preliminary pilot study, we explored the link between Col1 fiber density in primary human breast cancers and the occurrence of lymph node metastasis. Col1 fibers were detected by second harmonic generation (SHG) microscopy in primary human breast cancers from patients presenting with lymph node metastasis (LN+) versus those without lymph node metastasis (LN-). Col1 fiber density, which was quantified using our in-house SHG image analysis software, was significantly higher in the primary human breast cancers of LN+ (fiber volume=29.22%±4.72%, inter-fiber distance=2.25±0.45  μm) versus LN- (fiber volume=20.33%±5.56%, inter-fiber distance=2.88±1.07  μm) patients. Texture analysis by evaluating the co-occurrence matrix and the Fourier transform of the Col1 fibers proved to be significantly different for the parameters of co-relation and energy, as well as aspect ratio and eccentricity, for LN+ versus LN- cases. We also demonstrated that tissue fixation and paraffin embedding had negligible effect on SHG Col1 fiber detection and quantification. High Col1 fiber density in primary breast tumors is associated with breast cancer metastasis and may serve as an imaging biomarker of metastasis.

Tumor microenvironment and breast cancer progression: a complex scenario

It is now widely accepted that the development and progression of a tumor toward the malignant phenotype is highly dependent on interactions between tumor cells and the tumor microenvironment. Different components of the tumor microenvironment may have stimulatory or inhibitory effects on tumor progression by regulating the gene expression repertoire in tumor cells and stromal cells. This review analyzes novel research findings on breast cancer progression, discussing acquisition of the metastatic phenotype in breast disease in relation to different aspects of cross-talk among components of the tumor microenvironment. Knowledge of the interaction of all of these factors would contribute to elucidating the mechanisms that disrupt regulatory/signaling cascades and downstream effects in breast cancer.

High TWIST1 mRNA expression is associated with poor prognosis in lymph node-negative and estrogen receptor-positive human breast cancer and is co-expressed with stromal as well as ECM related genes

INTRODUCTION

The TWIST homolog 1 (TWIST1) is a transcription factor that induces epithelial to mesenchymal transition (EMT), a key process in metastasis. The purpose of this study was to investigate whether TWIST1 expression predicts disease progression in a large breast cancer cohort with long-term clinical follow-up, and to reveal the biology related to TWIST1 mediated disease progression.

METHODS

TWIST1 mRNA expression level was analyzed by quantitative real-time reverse polymerase chain reaction (RT-PCR) in 1,427 primary breast cancers. In uni- and multivariate analysis using Cox regression, TWIST1 mRNA expression level was associated with metastasis-free survival (MFS), disease-free survival (DFS) and overall survival (OS). Separate analyses in lymph node-negative patients (LNN, n = 778) who did not receive adjuvant systemic therapy, before and after stratification into estrogen receptor (ER)-positive (n = 552) and ER-negative (n = 226) disease, were also performed. The association of TWIST1 mRNA with survival endpoints was assessed using Kaplan-Meier analysis. Using gene expression arrays, genes showing a significant Spearman rank correlation with TWIST1 were used to identify overrepresented Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated biological pathways.

RESULTS

Increased mRNA expression level of TWIST1 analyzed as a continuous variable in both uni- and multivariate analysis was associated with shorter MFS in all patients (hazard ratio (HR): 1.17, 95% confidence interval, (95% CI):1.09 to 1.26; and HR: 1.17, 95% CI: 1.08 to 1.26; respectively), in LNN patients (HR: 1.22, 95% CI: 1.09 to 1.36; and HR: 1.21, 95% CI: 1.07 to 1.36; respectively) and in the ER-positive subgroup of LNN patients (HR: 1.34, 95% CI: 1.17 to 1.53; and HR: 1.32, 95% CI: 1.14 to 1.53; respectively). Similarly, high TWIST1 expression was associated with shorter DFS and OS in all patients and in the LNN/ER-positive subgroup. In contrast, no association of TWIST1 mRNA expression with MFS, DFS or OS was observed in ER-negative patients. Genes highly correlated with TWIST1 were significantly enriched for cell adhesion and ECM-related signaling pathways. Furthermore, TWIST1 mRNA was highly expressed in tumor stroma and positively related to tumor stromal content (P <0.001).

CONCLUSIONS

TWIST1 mRNA expression is an independent prognostic factor for poor prognosis in LNN/ER-positive breast cancer. The biological associations suggest an involvement of the tumor microenvironment in TWIST1's adverse role in breast cancer.

Molecular Classification of Breast Cancer

This article reviews the conceptual and practical implications of the intrinsic subtype classification of breast cancers and the limitations of this approach. It presents the most extensively validated gene expression assays proposed as predictors of clinical outcome and discusses their potential clinical utility and limitations.

Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data--methods and preliminary results

PURPOSE

To identify prognostic imaging biomarkers in non-small cell lung cancer (NSCLC) by means of a radiogenomics strategy that integrates gene expression and medical images in patients for whom survival outcomes are not available by leveraging survival data in public gene expression data sets.

MATERIALS AND METHODS

A radiogenomics strategy for associating image features with clusters of coexpressed genes (metagenes) was defined. First, a radiogenomics correlation map is created for a pairwise association between image features and metagenes. Next, predictive models of metagenes are built in terms of image features by using sparse linear regression. Similarly, predictive models of image features are built in terms of metagenes. Finally, the prognostic significance of the predicted image features are evaluated in a public gene expression data set with survival outcomes. This radiogenomics strategy was applied to a cohort of 26 patients with NSCLC for whom gene expression and 180 image features from computed tomography (CT) and positron emission tomography (PET)/CT were available.

RESULTS

There were 243 statistically significant pairwise correlations between image features and metagenes of NSCLC. Metagenes were predicted in terms of image features with an accuracy of 59%-83%. One hundred fourteen of 180 CT image features and the PET standardized uptake value were predicted in terms of metagenes with an accuracy of 65%-86%. When the predicted image features were mapped to a public gene expression data set with survival outcomes, tumor size, edge shape, and sharpness ranked highest for prognostic significance.

CONCLUSION

This radiogenomics strategy for identifying imaging biomarkers may enable a more rapid evaluation of novel imaging modalities, thereby accelerating their translation to personalized medicine.

Stromal genes add prognostic information to proliferation and histoclinical markers: a basis for the next generation of breast cancer gene signatures

BACKGROUND

First-generation gene signatures that identify breast cancer patients at risk of recurrence are confined to estrogen-positive cases and are driven by genes involved in the cell cycle and proliferation. Previously we induced sets of stromal genes that are prognostic for both estrogen-positive and estrogen-negative samples. Creating risk-management tools that incorporate these stromal signatures, along with existing proliferation-based signatures and established clinicopathological measures such as lymph node status and tumor size, should better identify women at greatest risk for metastasis and death.

METHODOLOGY/PRINCIPAL FINDINGS

To investigate the strength and independence of the stromal and proliferation factors in estrogen-positive and estrogen-negative patients we constructed multivariate Cox proportional hazards models along with tree-based partitions of cancer cases for four breast cancer cohorts. Two sets of stromal genes, one consisting of DCN and FBLN1, and the other containing LAMA2, add substantial prognostic value to the proliferation signal and to clinical measures. For estrogen receptor-positive patients, the stromal-decorin set adds prognostic value independent of proliferation for three of the four datasets. For estrogen receptor-negative patients, the stromal-laminin set significantly adds prognostic value in two datasets, and marginally in a third. The stromal sets are most prognostic for the unselected population studies and may depend on the age distribution of the cohorts.

CONCLUSION

The addition of stromal genes would measurably improve the performance of proliferation-based first-generation gene signatures, especially for older women. Incorporating indicators of the state of stromal cell types would mark a conceptual shift from epithelial-centric risk assessment to assessment based on the multiple cell types in the cancer-altered tissue.

Inactivation of Rb in stromal fibroblasts promotes epithelial cell invasion

Stromal-derived growth factors are required for normal epithelial growth but are also implicated in tumour progression. We have observed inactivation of the retinoblastoma protein (Rb), through phosphorylation, in cancer-associated fibroblasts in oro-pharyngeal cancer specimens. Rb is well known for its cell-autonomous effects on cancer initiation and progression; however, cell non-autonomous functions of Rb are not well described. We have identified a cell non-autonomous role of Rb, using three-dimensional cultures, where depletion of Rb in stromal fibroblasts enhances invasive potential of transformed epithelia. In part, this is mediated by upregulation of keratinocyte growth factor (KGF), which is produced by the depleted fibroblasts. KGF drives invasion of epithelial cells through induction of MMP1 expression in an AKT- and Ets2-dependent manner. Our data identify that stromal fibroblasts can alter the invasive behaviour of the epithelium, and we show that altered expression of KGF can mediate these functions.

Systematic analysis of breast cancer morphology uncovers stromal features associated with survival

The morphological interpretation of histologic sections forms the basis of diagnosis and prognostication for cancer. In the diagnosis of carcinomas, pathologists perform a semiquantitative analysis of a small set of morphological features to determine the cancer's histologic grade. Physicians use histologic grade to inform their assessment of a carcinoma's aggressiveness and a patient's prognosis. Nevertheless, the determination of grade in breast cancer examines only a small set of morphological features of breast cancer epithelial cells, which has been largely unchanged since the 1920s. A comprehensive analysis of automatically quantitated morphological features could identify characteristics of prognostic relevance and provide an accurate and reproducible means for assessing prognosis from microscopic image data. We developed the C-Path (Computational Pathologist) system to measure a rich quantitative feature set from the breast cancer epithelium and stroma (6642 features), including both standard morphometric descriptors of image objects and higher-level contextual, relational, and global image features. These measurements were used to construct a prognostic model. We applied the C-Path system to microscopic images from two independent cohorts of breast cancer patients [from the Netherlands Cancer Institute (NKI) cohort, n = 248, and the Vancouver General Hospital (VGH) cohort, n = 328]. The prognostic model score generated by our system was strongly associated with overall survival in both the NKI and the VGH cohorts (both log-rank P ≤ 0.001). This association was independent of clinical, pathological, and molecular factors. Three stromal features were significantly associated with survival, and this association was stronger than the association of survival with epithelial characteristics in the model. These findings implicate stromal morphologic structure as a previously unrecognized prognostic determinant for breast cancer.

An "elite hacker": breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity

The year 2011 marked the 40 year anniversary of Richard Nixon signing the National Cancer Act, thus declaring the beginning of the "War on Cancer" in the United States. Whereas we have made tremendous progress toward understanding the genetics of tumors in the past four decades, and in developing enabling technology to dissect the molecular underpinnings of cancer at unprecedented resolution, it is only recently that the important role of the stromal microenvironment has been studied in detail. Cancer is a tissue-specific disease, and it is becoming clear that much of what we know about breast cancer progression parallels the biology of the normal breast differentiation, of which there is still much to learn. In particular, the normal breast and breast tumors share molecular, cellular, systemic and microenvironmental influences necessary for their progression. It is therefore enticing to consider a tumor to be a "rogue hacker"--one who exploits the weaknesses of a normal program for personal benefit. Understanding normal mammary gland biology and its "security vulnerabilities" may thus leave us better equipped to target breast cancer. In this review, we will provide a brief overview of the heterotypic cellular and molecular interactions within the microenvironment of the developing mammary gland that are necessary for functional differentiation, provide evidence suggesting that similar biology--albeit imbalanced and exaggerated--is observed in breast cancer progression particularly during the transition from carcinoma in situ to invasive disease. Lastly we will present evidence suggesting that the multigene signatures currently used to model cancer heterogeneity and clinical outcome largely reflect signaling from a heterogeneous microenvironment-a recurring theme that could potentially be exploited therapeutically.

CD99 is a novel prognostic stromal marker in non-small cell lung cancer

The complex interaction between cancer cells and the microenvironment plays an essential role in all stages of tumourigenesis. Despite the significance of this interplay, alterations in protein composition underlying tumour-stroma interactions are largely unknown. The aim of this study was to identify stromal proteins with clinical relevance in non-small cell lung cancer (NSCLC). A list encompassing 203 stromal candidate genes was compiled based on gene expression array data and available literature. The protein expression of these genes in human NSCLC was screened using the Human Protein Atlas. Twelve proteins were selected that showed a differential stromal staining pattern (BGN, CD99, DCN, EMILIN1, FBN1, PDGFRB, PDLIM5, POSTN, SPARC, TAGLN, TNC and VCAN). The corresponding antibodies were applied on tissue microarrays, including 190 NSCLC samples, and stromal staining was correlated with clinical parameters. Higher stromal expression of CD99 was associated with better prognosis in the univariate (p = 0.037) and multivariate (p = 0.039) analysis. The association was independent from the proportion of tumour stroma, the fraction of inflammatory cells and clinical and pathological parameters like stage, performance status and tumour histology. The prognostic impact of stromal CD99 protein expression was confirmed in an independent cohort of 240 NSCLC patients (p = 0.008). Furthermore, double-staining confocal fluorescence microscopy showed that CD99 was expressed in stromal lymphocytes as well as in cancer-associated fibroblasts. Based on a comprehensive screening strategy the membrane protein CD99 was identified as a novel stromal factor with clinical relevance. The results support the concept that stromal properties have an important impact on tumour progression.

Biophysical control of invasive tumor cell behavior by extracellular matrix microarchitecture

Fibrillar collagen gels, which are used extensively in vitro to study tumor-microenvironment interactions, are composed of a cell-instructive network of interconnected fibers and pores whose organization is sensitive to polymerization conditions such as bulk concentration, pH, and temperature. Using confocal reflectance microscopy and image autocorrelation analysis to quantitatively assess gel microarchitecture, we show that additional polymerization parameters including culture media formulation and gel thickness significantly affect the dimensions and organization of fibers and pores in collagen gels. These findings enabled the development of a three-dimensional culture system in which cell-scale gel microarchitecture was decoupled from bulk gel collagen concentration. Interestingly, morphology and migration characteristics of embedded MDA-MB-231 cells were sensitive to gel microarchitecture independently of collagen gel concentration. Cells adopted a polarized, motile phenotype in gels with larger fibers and pores and a rounded or stellate, less motile phenotype in gels with small fibers and pores regardless of bulk gel density. Conversely, cell proliferation was sensitive to gel concentration but not microarchitecture. These results indicate that cell-scale gel microarchitecture may trump bulk-scale gel density in controlling specific cell behaviors, underscoring the biophysical role of gel microarchitecture in influencing cell behavior.

Microenvironment-centred dynamics in aggressive B-cell lymphomas

Aggressive B-cell lymphomas share high proliferative and invasive attitudes and dismal prognosis despite heterogeneous biological features. In the interchained sequence of events leading to cancer progression, neoplastic clone-intrinsic molecular events play a major role. Nevertheless, microenvironment-related cues have progressively come into focus as true determinants for this process. The cancer-associated microenvironment is a complex network of nonneoplastic immune and stromal cells embedded in extracellular components, giving rise to a multifarious crosstalk with neoplastic cells towards the induction of a supportive milieu. The immunological and stromal microenvironments have been classically regarded as essential partners of indolent lymphomas, while considered mainly negligible in the setting of aggressive B-cell lymphomas that, by their nature, are less reliant on external stimuli. By this paper we try to delineate the cardinal microenvironment-centred dynamics exerting an influence over lymphoid clone progression in aggressive B-cell lymphomas.

Secreted protein acidic and rich in cysteine (SPARC) is associated with nasopharyngeal carcinoma metastasis and poor prognosis

Background

The aim of the present study was to analyse the expression of Secreted protein acidic and rich in cysteine (SPARC) in nasopharyngeal carcinoma (NPC) specimens, and to evaluate its correlation with clinicopathologic features, including survival of patients with NPC

Methods

NPC tissue microarrays (TMAs) were constructed from Sun Yat-sen University Cancer Center (SYSUCC), another three centers on mainland China, Singapore and Hong Kong. Using quantitative RT-PCR and Western-blotting techniques, we detected mRNA and protein expression of SPARC in NPC cell lines and immortalized nasopharyngeal epithelial cells (NPECs) induced by Bmi-1 (NPEC2 Bmi-1). The difference of SPARC expression in the cell lines was tested using a t-test method. The relationship between the SPARC expression and clinicopathological data was assessed by chi-square. Survival analysis was estimated using the Kaplan-Meier approach with log-rank test. Univariate and multivariate analyses of clinical variables were performed using Cox proportional hazards regression models.

Results

The expression levels of SPARC mRNA and protein were markedly higher in NPC cell lines than in NPEC2 Bmi-1. Especially, the expression levels of SPARC mRNA and protein were much lower in the 6-10B than in the 5-8 F (P = 0.002, P = 0.001). SPARC immunostaining revealed cytoplasmic localization in NPC cells and no staining in the stroma and epithelium.

In addition, high level of SPARC positively correlated with the status of distant metastasis (P = 0.001) and WHO histological classification (P = 0.023). NPC patients with high SPARC expression also had a significantly poorer prognosis than patients with low SPARC expression (log-rank test, P < 0.001), especially patients with advanced stage disease (log-rank, P < 0.001). Multivariate analysis suggested that the level of SPARC expression was an independent prognostic indicator for the overall survival of patients with NPC (P < 0.001).

Conclusions

SPARC expression is common in NPC patients. Our data shows that elevated SPARC expression is a potential unfavorable prognostic factor for patients with NPC.

Molecular classification of estrogen receptor-positive/luminal breast cancers

Estrogen receptor (ER)-positive breast cancer is the most prevalent subtype of invasive breast cancers. Patients with ER-positive breast cancers have variable clinical outcomes and responses to endocrine therapy and chemotherapy. With the advent of microarray-based gene expression profiling, unsupervised analysis methods have resulted in a classification of ER-positive disease into subtypes with different outcomes (ie, luminal A and luminal B); subsequent studies have demonstrated that these subtypes have different patterns of genetic aberrations and outcome. Studies based on supervised methods of microarray analysis have led to the development of prognostic gene signatures that identify a subgroup of ER-positive breast cancer patients with excellent outcome, who could forego chemotherapy. Despite the excitement with these approaches, several lines of evidence have demonstrated that the subclassification of ER-positive cancers and the prognostic value of gene signatures is largely driven by the expression levels of proliferation-related genes and that proliferation markers, such as Ki67, may provide equivalent prognostic information to that provided by gene signatures. In this review, we discuss the contribution of gene expression profiling to the classification of ER-positive breast cancer, the role of prognostic and predictive signatures, and the potential stratification of ER-positive disease according to their dependency on the phosphatidylinositol 3-kinase pathway.

Circulating tumor cells measurements in hepatocellular carcinoma

Liver cancer is the fifth most common cancer in men and the seventh in women. During the past 20 years, the incidence of HCC has tripled while the 5-year survival rate has remained below 12%. The presence of circulating tumor cells (CTC) reflects the aggressiveness nature of a tumor. Many attempts have been made to develop assays that reliably detect and enumerate the CTC during the development of the HCC. In this case, the challenges are (1) there are few markers specific to the HCC (tumor cells versus nontumor cells) and (2) they can be used to quantify the number of CTC in the bloodstream. Another technical challenge consists of finding few CTC mixed with million leukocytes and billion erythrocytes. CTC detection and identification can be used to estimate prognosis and may serve as an early marker to assess antitumor activity of treatment. CTC can also be used to predict progression-free survival and overall survival. CTC are an interesting source of biological information in order to understand dissemination, drug resistance, and treatment-induced cell death. Our aim is to review and analyze the different new methods existing to detect, enumerate, and characterize the CTC in the peripheral circulation of patients with HCC.

Gene expression profiling in breast cancer: classification, prognostication, and prediction

Microarray-based gene expression profiling has had a major effect on our understanding of breast cancer. Breast cancer is now perceived as a heterogeneous group of different diseases characterised by distinct molecular aberrations, rather than one disease with varying histological features and clinical behaviour. Gene expression profiling studies have shown that oestrogen-receptor (ER)-positive and ER-negative breast cancers are distinct diseases at the transcriptomic level, that additional molecular subtypes might exist within these groups, and that the prognosis of patients with ER-positive disease is largely determined by the expression of proliferation-related genes. On the basis of these principles, a molecular classification system and prognostic multigene classifiers based on microarrays or derivative technologies have been developed and are being tested in randomised clinical trials and incorporated into clinical practice. In this review, we focus on the conceptual effect and potential clinical use of the molecular classification of breast cancer, and discuss prognostic and predictive multigene predictors.

The microenvironment in breast cancer progression: biology and implications for treatment

Breast cancer comprises a heterogeneous group of malignancies derived from the ductal epithelium. The microenvironment of these cancers is now recognized as a critical participant in tumor progression and therapeutic responses. Recent data demonstrate significant gene expression and epigenetic alterations in cells composing the microenvironment during disease progression, which can be explored as biomarkers and targets for therapy. Indeed, gene expression signatures derived from tumor stroma have been linked to clinical outcomes. There is increasing interest in translating our current understanding of the tumor microenvironment to the development of novel therapies.

Bromodomain-Containing Protein 4: A Dynamic Regulator of Breast Cancer Metastasis through Modulation of the Extracellular Matrix

Metastasis is an extremely complex process that accounts for most cancer-related deaths. Malignant primary tumors can be removed surgically, but the cells that migrate, invade, and proliferate at distant organs are often the cells that prove most difficult to target therapeutically. There is growing evidence that host factors outside of the primary tumors are of major importance in the development of metastasis. Recently, we have shown that the bromodomain-containing protein 4 or bromodomain 4 (Brd4) functions as an inherited susceptibility gene for breast cancer progression and metastasis. In this paper, we will discuss that host genetic background on which a tumor arises can significantly alter the biology of the subsequent metastatic disease, and we will focus on the role of Brd4 in regulating metastasis susceptibility.

The impact of the ovarian microenvironment on the anti-tumor effect of SPARC on ovarian cancer

A lack of host-derived SPARC promotes disease progression in an intraperitoneal (IP) ID8 mouse model of epithelial ovarian cancer (EOC). Since orthotopic injection (OT) of ID8 cells better recapitulates high-grade serous cancer, we examined the impact of host-derived SPARC following OT injection. Sparc(-/-) and wild-type (WT) mice were injected with ID8 cells either OT or IP and tumors were analyzed at the moribund stage. Sparc(-/-) mice had reduced survival and fewer well-defined abdominal lesions compared with WT controls after IP injection, whereas no differences were observed in survival or abdominal lesions between Sparc(-/-) and WT mice after OT injection. No differences in mass or collagen content were observed in ovarian tumors between OT-injected Sparc(-/-) and WT mice. The abdominal wall of the IP-injected Sparc(-/-) mice exhibited immature and less abundant collagen fibrils compared with WT mice both in injected and non-injected controls. In contrast to human EOC, SPARC was expressed by the tumor cells but was absent in reactive stroma of WT mice. Exposure to the ovarian microenvironment through OT injections alters the metastatic behaviour of ID8 cells, which is not affected by the absence of host-derived SPARC.

Insight into the heterogeneity of breast cancer through next-generation sequencing

Rapid and sophisticated improvements in molecular analysis have allowed us to sequence whole human genomes as well as cancer genomes, and the findings suggest that we may be approaching the ability to individualize the diagnosis and treatment of cancer. This paradigmatic shift in approach will require clinicians and researchers to overcome several challenges including the huge spectrum of tumor types within a given cancer, as well as the cell-to-cell variations observed within tumors. This review discusses how next-generation sequencing of breast cancer genomes already reveals insight into tumor heterogeneity and how it can contribute to future breast cancer classification and management.

The tumor microenvironment modulates tamoxifen resistance in breast cancer: a role for soluble stromal factors and fibronectin through β1 integrin

Tamoxifen resistance has been largely attributed to genetic alterations in the epithelial tumor cells themselves, such as overexpression of HER-2/Neu. However, in the clinic, only about 15-20% of cases of HER-2/Neu amplification has actually been correlated to the acquisition of endocrine resistance, suggesting that other mechanisms must be involved as well. Using the epithelial LM05-E and the fibroblastic LM05-F cell lines, derived from the estrogen dependent spontaneous M05 mouse mammary tumor, as well as MCF-7 cells, we analyzed whether soluble stromal factors or extracellular matrix components protected against tamoxifen induced cell death. Involvement of signaling pathways was determined by using specific inhibitors and western blot, and phosphorylation of the estrogen receptor alpha by western blot and immunofluorescence. Soluble factors produced by the fibroblastic cells protect the epithelial tumor cells from tamoxifen-induced cell death through a mechanism that involves EGFR and matrix metalloproteinases upstream of PI3K/AKT. Exogenous fibronectin by itself confers endocrine resistance through interaction with β1 integrin and activation of PI3K/AKT and MAPK/ERK 1/2 pathways. The conferred resistance is reversed by blocking β1 integrin. We show also that treatment with both conditioned medium and fibronectin leads to the phosphorylation of the estrogen receptor at serine-118, suggesting stromal factors as modulators of ER activity. Our results show that the tumor microenvironment can modulate tamoxifen resistance, providing an alternative explanation for why patients become refractory to hormone-therapy.

Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling

We use an integrated approach to understand breast cancer heterogeneity by modeling mRNA, copy number alterations, microRNAs, and methylation in a pathway context utilizing the pathway recognition algorithm using data integration on genomic models (PARADIGM). We demonstrate that combining mRNA expression and DNA copy number classified the patients in groups that provide the best predictive value with respect to prognosis and identified key molecular and stromal signatures. A chronic inflammatory signature, which promotes the development and/or progression of various epithelial tumors, is uniformly present in all breast cancers. We further demonstrate that within the adaptive immune lineage, the strongest predictor of good outcome is the acquisition of a gene signature that favors a high T-helper 1 (Th1)/cytotoxic T-lymphocyte response at the expense of Th2-driven humoral immunity. Patients who have breast cancer with a basal HER2-negative molecular profile (PDGM2) are characterized by high expression of protumorigenic Th2/humoral-related genes (24-38%) and a low Th1/Th2 ratio. The luminal molecular subtypes are again differentiated by low or high FOXM1 and ERBB4 signaling. We show that the interleukin signaling profiles observed in invasive cancers are absent or weakly expressed in healthy tissue but already prominent in ductal carcinoma in situ, together with ECM and cell-cell adhesion regulating pathways. The most prominent difference between low and high mammographic density in healthy breast tissue by PARADIGM was that of STAT4 signaling. In conclusion, by means of a pathway-based modeling methodology (PARADIGM) integrating different layers of molecular data from whole-tumor samples, we demonstrate that we can stratify immune signatures that predict patient survival.

The process of macrophage migration promotes matrix metalloproteinase-independent invasion by tumor cells

Tumor-associated macrophages are known to amplify the malignant potential of tumors by secreting a variety of cytokines and proteases involved in tumor cell invasion and metastasis, but how these macrophages infiltrate tumors and whether the macrophage migration process facilitates tumor cell invasion remain poorly documented. To address these questions, we used cell spheroids of breast carcinoma SUM159PT cells as an in vitro model of solid tumors. We found that macrophages used both the mesenchymal mode requiring matrix metalloproteinases (MMPs) and the amoeboid migration mode to infiltrate tumor cell spheroids. Whereas individual SUM159PT cells invaded Matrigel using an MMP-dependent mesenchymal mode, when they were grown as spheroids, tumor cells were unable to invade the Matrigel surrounding spheroids. When spheroids were infiltrated or in contact with macrophages, tumor cell invasiveness was restored. It was dependent on the capacity of macrophages to remodel the matrix and migrate in an MMP-independent mesenchymal mode. This effect of macrophages was much reduced when spheroids were infiltrated by Matrigel migration-defective Hck(-/-) macrophages. In the presence of macrophages, SUM159PT migrated into Matrigel in the proximity of macrophages and switched from an MMP-dependent mesenchymal migration to an amoeboid mode resistant to protease inhibitors.Thus, in addition to the well-described paracrine loop between macrophages and tumor cells, macrophages can also contribute to the invasiveness of tumor cells by remodeling the extracellular matrix and by opening the way to exit the tumor and colonize the surrounding tissues in an MMP-dispensable manner.

The Role of Proteomics in the Diagnosis and Treatment of Women's Cancers: Current Trends in Technology and Future Opportunities

Technological and scientific innovations over the last decade have greatly contributed to improved diagnostics, predictive models, and prognosis among cancers affecting women. In fact, an explosion of information in these areas has almost assured future generations that outcomes in cancer will continue to improve. Herein we discuss the current status of breast, cervical, and ovarian cancers as it relates to screening, disease diagnosis, and treatment options. Among the differences in these cancers, it is striking that breast cancer has multiple predictive tests based upon tumor biomarkers and sophisticated, individualized options for prescription therapeutics while ovarian cancer lacks these tools. In addition, cervical cancer leads the way in innovative, cancer-preventative vaccines and multiple screening options to prevent disease progression. For each of these malignancies, emerging proteomic technologies based upon mass spectrometry, stable isotope labeling with amino acids, high-throughput ELISA, tissue or protein microarray techniques, and click chemistry in the pursuit of activity-based profiling can pioneer the next generation of discovery. We will discuss six of the latest techniques to understand proteomics in cancer and highlight research utilizing these techniques with the goal of improvement in the management of women's cancers.

Matrix metalloproteinases and their inhibitors in canine mammary tumors

Background

Malignant canine mammary tumors represent 50% of all neoplasms in female dogs. Matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) are thought to be involved in tumor progression, and they are also associated with the reactive stroma, which provides structural and vascular support for tumor growth.

Results

MMP-2, MMP-9 and MT1-MMP were expressed at both the mRNA and protein levels in tumor samples. MMP-2 and MMP-9 immunohistochemical reactions were evident both in the epithelial tumor cells and in the stromal compartment to varying degrees; in particular, the intensity of the MMP-2 staining was stronger in the stromal fibroblasts close to epithelial tumor cells in simple carcinomas than in adenomas. These data were supported by gelatin-zymography; bands for the active form of MMP-2 were found in 94% of carcinoma samples, compared with 17% of benign tumor samples. The gene expression and immunohistochemical results for MT1-MMP were comparable to those for MMP-2. The immunoreactivity for MMP-13 and TIMP-2 was lower in carcinomas than in adenomas, confirming the mRNA data for MMP-13 and the other MMP inhibitors that were evaluated. The active form of MMP-9, but not the active form of MMP-2, was identified in the plasma of all of the tested dogs.

Conclusions

Our findings suggest that MMP-9, MMP-2 and MT1-MMP, which are synthesized by epithelial cancer cells and cancer-associated fibroblasts, play an important role in malignant canine mammary tumors. The reduction of MMP-13 and TIMP-2 could also be a significant step in malignant transformation. MMP-2 and MT1-MMP could be further evaluated as future biomarkers for predicting the progression and prognosis of canine mammary tumors.

Elevated expression of stromal palladin predicts poor clinical outcome in renal cell carcinoma

The role that stromal renal cell carcinoma (RCC) plays in support of tumor progression is unclear. Here we sought to determine the predictive value on patient survival of several markers of stromal activation and the feasibility of a fibroblast-derived extracellular matrix (ECM) based three-dimensional (3D) culture stemming from clinical specimens to recapitulate stromal behavior in vitro. The clinical relevance of selected stromal markers was assessed using a well annotated tumor microarray where stromal-marker levels of expression were evaluated and compared to patient outcomes. Also, an in vitro 3D system derived from fibroblasts harvested from patient matched normal kidney, primary RCC and metastatic tumors was employed to evaluate levels and localizations of known stromal markers such as the actin binding proteins palladin, alpha-smooth muscle actin (α-SMA), fibronectin and its spliced form EDA. Results suggested that RCCs exhibiting high levels of stromal palladin correlate with a poor prognosis, as demonstrated by overall survival time. Conversely, cases of RCCs where stroma presents low levels of palladin expression indicate increased survival times and, hence, better outcomes. Fibroblast-derived 3D cultures, which facilitate the categorization of stromal RCCs into discrete progressive stromal stages, also show increased levels of expression and stress fiber localization of α-SMA and palladin, as well as topographical organization of fibronectin and its splice variant EDA. These observations are concordant with expression levels of these markers in vivo. The study proposes that palladin constitutes a useful marker of poor prognosis in non-metastatic RCCs, while in vitro 3D cultures accurately represent the specific patient's tumor-associated stromal compartment. Our observations support the belief that stromal palladin assessments have clinical relevance thus validating the use of these 3D cultures to study both progressive RCC-associated stroma and stroma-dependent mechanisms affecting tumorigenesis. The clinical value of assessing RCC stromal activation merits further study.

Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

Breast cancer comprises a collection of diseases with distinctive clinical, histopathological, and molecular features. Importantly, tumors with similar histological features may display disparate clinical behaviors. Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies. The use of these prognostic and predictive signatures in routine clinical decision-making remains controversial. Here, we review the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management.

The application of gene co-expression network reconstruction based on CNVs and gene expression microarray data in breast cancer

Copy number variations (CNVs) are one type of the human genetic variations and are pervasive in the human genome. It has been confirmed that they can play a causal role in complex diseases. Previous studies of CNVs focused more on identifying the disease-specific CNV regions or candidate genes on these CNV regions, but less on the synergistic actions between genes on CNV regions and other genes. Our research combined the CNVs with related gene co-expression to reconstruct gene co-expression network by using single nucleotide polymorphism microarray datasets and gene microarray datasets of breast cancer, and then extracted the modules which connected densely inside and analyzed the functions of modules. Interestingly, all of these modules' functions were related to breast cancer according to our enrichment analysis, and most of the genes in these modules have been reported to be involved in breast cancer. Our findings suggested that integrating CNVs and gene co-expressed relations was an available way to analyze the roles of CNV genes and their synergistic genes in breast cancer, and provided a novel insight into the pathological mechanism of breast cancer.

Expression of Toll-like receptor 4 and beta 1 integrin in breast cancer

Toll-like receptor (TLR) 4 signaling pathway has been shown to support tumor cell growth in vitro and in vivo. Its stimulation on breast cancer cell lines induces β1 integrin and promotes tumor invasiveness. However, its role in predicting clinical behavior of tumor is not yet clarified. Therefore, we investigated TLR4 and β1 integrin expression on 133 primary breast cancer samples by immunohistochemistry and correlated it with overall survival and disease-free survival of patients as well as with clinicopathological characteristics of the tumor. We found higher β1 integrin expression in invasive lobular cancer in comparison with other tumor types. No significant association of TLR4 and β1 integrin expression with overall survival or disease-free survival was seen. Therefore, we conclude that expression of these markers is of biological interest but appears to be of little additional use as predictive clinical marker.

miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors

Introduction

Few studies have performed expression profiling of both miRNA and mRNA from the same primary breast carcinomas. In this study we present and analyze data derived from expression profiling of 799 miRNAs in 101 primary human breast tumors, along with genome-wide mRNA profiles and extensive clinical information.

Methods

We investigate the relationship between these molecular components, in terms of their correlation with each other and with clinical characteristics. We use a systems biology approach to examine the correlative relationship between miRNA and mRNAs using statistical enrichment methods.

Results

We identify statistical significant differential expression of miRNAs between molecular intrinsic subtypes, and between samples with different levels of proliferation. Specifically, we point to miRNAs significantly associated with TP53 and ER status. We also show that several cellular processes, such as proliferation, cell adhesion and immune response, are strongly associated with certain miRNAs. We validate the role of miRNAs in regulating proliferation using high-throughput lysate-microarrays on cell lines and point to potential drivers of this process.

Conclusion

This study provides a comprehensive dataset as well as methods and system-level results that jointly form a basis for further work on understanding the role of miRNA in primary breast cancer.

Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

Background

Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes.

Methods

Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR) to neoadjuvant chemotherapy were also built using this approach.

Results

We identified statistically significant prognostic models for relapse-free survival (RFS) at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR) predictions for the entire population.

Conclusions

Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA copy number changes, will be needed to build robust prognostic models for ER-negative breast cancer patients. This combined clinical and genomics model approach can also be used to build predictors of therapy responsiveness, and could ultimately be applied to other tumor types.

Microenvironmental influences that drive progression from benign breast disease to invasive breast cancer

Invasive breast cancer represents the endpoint of a developmental process that originates in the terminal duct lobular units and is believed to progress through stages of increasing proliferation, atypical hyperplasia, and carcinoma in situ before the cancer acquires invasive and metastatic capabilities. By comparison with invasive breast cancer, which has been studied extensively, the preceding stages of benign breast disease are more poorly understood. Much less is known about the molecular changes underlying benign breast disease development and progression, as well as the transition from in situ into invasive disease. Even less focus has been given to the specific role of stroma in this progression. The reasons for lack of knowledge about these lesions often come from their small size and limited sample availability. More challenges are posed by limitations of the models used to investigate the lesions preceding invasive breast cancer. However, recent studies have identified alterations in stromal cell function that may be critical for disease progression from benign disease to invasive cancer: key functions of myoepithelial cells that maintain tissue structure are lost, while tissue fibroblasts become activated to produce proteases that degrade the extracellular matrix and trigger the invasive cellular phenotype. Gene expression profiling of stromal alterations associated with disease progression has also identified key transcriptional changes that occur early in disease development. In this review, we will summarize recent studies showing how stromal factors can facilitate progression of ductal carcinoma in situ to invasive disease. We also suggest approaches to identify processes that control earlier stages of disease progression.

Endogenous versus tumor-specific host response to breast carcinoma: a study of stromal response in synchronous breast primaries and biopsy site changes

PURPOSE

We recently described two types of stromal response in breast cancer derived from gene expression studies of tenosynovial giant cell tumors and fibromatosis. The purpose of this study is to elucidate the basis of this stromal response--whether they are elicited by individual tumors or whether they represent an endogenous host reaction produced by the patient.

EXPERIMENTAL DESIGN

Stromal signatures from patients with synchronous dual primaries were analyzed by immunohistochemistry on a tissue microarray (n = 26 pairs) to evaluate the similarity of stromal responses in different tumors within the same patient. We also characterized the extent to which the stromal signatures were conserved between stromal response to injury compared to the stromal response to carcinoma using gene expression profiling and tissue microarray immunohistochemistry.

RESULTS

The two stromal response signatures showed divergent associations in synchronous primaries: the DTF fibroblast response is more likely to be similar in a patient with multiple breast primaries (permutation analysis P = 0.0027), whereas CSF1 macrophage response shows no significant concordance in separate tumors within a given patient. The DTF fibroblast signature showed more concordance across normal, cancer, and biopsy site samples from within a patient, than across normal, cancer, and biopsy site samples from a random group of patients, whereas the CSF1 macrophage response did not.

CONCLUSIONS

The results suggest that the DTF fibroblast response is host-specific, whereas the CSF1 response may be tumor-elicited. Our findings provide further insight into stromal response and may facilitate the development of therapeutic strategies to target particular stromal subtypes.

Jekyll and Hyde: the role of the microenvironment on the progression of cancer

It is now recognized that the host microenvironment undergoes extensive change during the evolution and progression of cancer. This involves the generation of cancer-associated fibroblasts (CAFs), which, through release of growth factors and cytokines, lead to enhanced angiogenesis, increased tumour growth and invasion. It has also been demonstrated that CAFs may modulate the cancer stem cell (CSC) phenotype, which has therapeutic implications. The altered fibroblast phenotype also contributes to the development of an altered extracellular matrix (ECM), with synthesis of ECM isoforms rarely found in normal tissues, including tenascin-C isoforms and the fibronectin EDA isoform. There is also emerging evidence of how the tensile strength of the tumour-associated ECM may be modified and lead to altered signalling in tumour cells. The hypoxic environment of the tumour stimulates angiogenesis and also impacts on other aspects of cell signalling, including the c-met pathway and lysyl oxidase-mediated signalling, which can directly promote tumour cell invasion. The inflammatory infiltrate associated with many solid tumours also modulates tumour function, having both anti- and pro-tumour effects. All of these components of the microenvironment provide potential targets for therapeutic attack, with a number of molecules already in clinical trials. It is also becoming evident that characterizing the tumour microenvironment can provide important prognostic and predictive information about tumours, independent of the tumour cell phenotype.

Cell-matrix interactions in mammary gland development and breast cancer

The mammary gland is an organ that at once gives life to the young, but at the same time poses one of the greatest threats to the mother. Understanding how the tissue develops and functions is of pressing importance in determining how its control mechanisms break down in breast cancer. Here we argue that the interactions between mammary epithelial cells and their extracellular matrix (ECM) are crucial in the development and function of the tissue. Current strategies for treating breast cancer take advantage of our knowledge of the endocrine regulation of breast development, and the emerging role of stromal-epithelial interactions (Fig. 1). Focusing, in addition, on the microenvironmental influences that arise from cell-matrix interactions will open new opportunities for therapeutic intervention. We suggest that ultimately a three-pronged approach targeting endocrine, growth factor, and cell-matrix interactions will provide the best chance of curing the disease.

Molecular anatomy of breast cancer stroma and its prognostic value in estrogen receptor-positive and -negative cancers

PURPOSE

The purpose of this study was to identify genes enriched in breast cancer stroma, assess the stromal gene expression differences between estrogen receptor (ER) -positive and -negative cancers, and separately determine their prognostic value in these two subtypes of breast cancers.

METHODS

We compared gene expression profiles of pairs of fine-needle (stroma-poor) and core-needle (stroma-rich) biopsies from 37 cancers to identify stroma-associated genes. We defined stromal metagenes and tested their prognostic values in 684 node-negative patients who received no systemic adjuvant therapy and 259 tamoxifen-treated patients.

RESULTS

We identified 293 probe sets overexpressed in core biopsies; these included five highly coexpressed gene clusters (metagenes) corresponding to immune functions and extracellular matrix components. These genes showed quantitative and qualitative differences between ER-positive and ER-negative cancers. A B-cell/plasma cell metagene showed strong prognostic value in ER-positive highly proliferative cancers, a lesser prognostic value in ER-negative cancers, and no prognostic value in ER-positive cancers with low proliferation. The hazard ratio for distant relapse in the lowest compared with the highest tertile of the pooled prognostic data set was 4.29 (95% CI, 2.04 to 9.01; P = .001) in ER-positive cancers and 3.34 (95% CI, 1.60 to 6.97; P = .001) in ER-negative cancers. This remained significant in multivariate analysis including routine variables and other genomic prognostic scores. As a result of quantitative differences in this metagene between ER-positive and ER-negative cancers, different thresholds apply in the two subgroups. Other stromal metagenes had inconsistent prognostic value.

CONCLUSION

Among ER-negative and ER-positive highly proliferative cancers, a subset of tumors with high expression of a B-cell/plasma cell metagene carries a favorable prognosis.

Tumors as organs: complex tissues that interface with the entire organism

Solid tumors are not simply clones of cancer cells. Instead, they are abnormal organs composed of multiple cell types and extracellular matrix. Some aspects of tumor development resemble processes seen in developing organs, whereas others are more akin to tissue remodeling. Some microenvironments, particularly those associated with tissue injury, are favorable for progression of mutant cells, whereas others restrict it. Cancer cells can also instruct surrounding tissues to undergo changes that promote malignancy. Understanding the complex ways in which cancer cells interact with their surroundings, both locally in the tumor organ and systemically in the body as a whole, has implications for effective cancer prevention and therapy.

Prediction and prognosis: impact of gene expression profiling in personalized treatment of breast cancer patients

Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.

Brg-1 mediates the constitutive and fenretinide-induced expression of SPARC in mammary carcinoma cells via its interaction with transcription factor Sp1

Background

Secreted protein, acidic and rich in cysteine (SPARC) is a matricellular protein that mediates cell-matrix interactions. It has been shown, depending on the type of cancer, to possess either pro- or anti-tumorigenic properties. The transcriptional regulation of the SPARC gene expression has not been fully elucidated and the effects of anti-cancer drugs on this process have not been explored.

Results

In the present study, we demonstrated that chromatin remodeling factor Brg-1 is recruited to the proximal SPARC promoter region (-130/-56) through an interaction with transcription factor Sp1. We identified Brg-1 as a critical regulator for the constitutive expression levels of SPARC mRNA and protein in mammary carcinoma cell lines and for SPARC secretion into culture media. Furthermore, we found that Brg-1 cooperates with Sp1 to enhance SPARC promoter activity. Interestingly, fenretinide [N-4(hydroxyphenyl) retinamide, 4-HPR], a synthetic retinoid with anti-cancer properties, was found to up-regulate the transcription, expression and secretion of SPARC via induction of the Brg-1 in a dose-dependent manner. Finally, our results demonstrated that fenretinide-induced expression of SPARC contributes significantly to a decreased invasion of mammary carcinoma cells.

Conclusions

Overall, our results reveal a novel cooperative role of Brg-1 and Sp1 in mediating the constitutive and fenretinide-induced expression of SPARC, and provide new insights for the understanding of the anti-cancer effects of fenretinide.