An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

Synthesis of Silver Nano Particles Using Myricetin and the In-Vitro Assessment of Anti-Colorectal Cancer Activity: In-Silico Integration

The creation of novel anticancer treatments for a variety of human illnesses, including different malignancies and dangerous microbes, also potentially depends on nanoparticles including silver. Recently, it has been successful to biologically synthesize metal nanoparticles using plant extracts. The natural flavonoid 3,3′, 4′, 5,5′, and 7 hexahydroxyflavon (myricetin) has anticancer properties. There is not much known about the regulatory effects of myricetin on the possible cell fate-determination mechanisms (such as apoptosis/proliferation) in colorectal cancer. Because the majority of investigations related to the anticancer activity of myricetin have dominantly focused on the enhancement of tumor cell uncontrolled growth (i.e., apoptosis). Thus, we have decided to explore the potential myricetin interactors and the associated biological functions by using an in-silico approach. Then, we focused on the main goal of the work which involved the synthesis of silver nanoparticles and the labeling of myricetin with it. The synthesized silver nanoparticles were examined using UV-visible spectroscopy, dynamic light scattering spectroscopy, Fourier transform infrared spectroscopy, and scanning electron microscopy. In this study, we have investigated the effects of myricetin on colorectal cancer where numerous techniques were used to show myricetin’s effect on colon cancer cells. Transmission Electron Microscopy was employed to monitor morphological changes. Furthermore, we have combined the results of the colorectal cancer gene expression dataset with those of the myricetin interactors and pathways. Based on the results, we conclude that myricetin is able to efficiently kill human colorectal cancer cell lines. Since, it shares important biological roles and possible route components and this myricetin may be a promising herbal treatment for colorectal cancer as per an in-silico analysis of the TCGA dataset.

Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer

Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma and furthermore, the TCGA and cBioPortal database have been utilized for clinical relevance understanding. In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.

Gene Expression Profiling of Early Acute Febrile Stage of Dengue Infection and Its Comparative Analysis With Streptococcus pneumoniae Infection

Infectious diseases are the disorders caused by organisms such as bacteria, viruses, fungi, or parasites. Although many of them are permentantly hazardous, a number of them live in and on our bodies and they are normally harmless or even helpful. Under certain circumstances, some organisms may cause diseases and these infectious diseases may be passed directly from person to person or via intermediate vectors including insects and other animals. Dengue virus and Streptococcus pneumoniae are the critical and common sources of infectious diseases. So, it is critical to understand the gene expression profiling and their inferred functions in comparison to the normal and virus infected conditions. Here, we have analyzed the gene expression profiling for dengue hemorrhagic fever, dengue fever, and normal human dataset. Similar to it, streptococcus pneumoniae infectious data were analyzed and both the outcomes were compared. Our study leads to the conclusion that the dengue hemorrhagic fever arises in result to potential change in the gene expression pattern, and the inferred functions obviously belong to the immune system, but also there are some additional potential pathways which are critical signaling pathways. In the case of pneumoniae infection, 19 pathways were enriched, almost all these pathways are associated with the immune system and 17 of the enriched pathways were common with dengue infection except platelet activation and antigen processing and presentation. In terms of the comparative study between dengue virus and Streptococcus pneumoniae infection, we conclude that cell adhesion molecules (CAMs), MAPK signaling pathway, natural killer cell mediated cytotoxicity, regulation of actin cytoskeleton, and cytokine-cytokine receptor interaction are commonly enriched in all the three cases of dengue infection and Streptococcus pneumoniae infection, focal adhesion was enriched between classical dengue fever — dengue hemorrhagic fever, dengue hemorrhagic fever—normal samples, and SP, and antigen processing and presentation and Leukocyte transendothelial migration were enriched in classical dengue fever —normal samples, dengue hemorrhagic fever—normal samples, and Streptococcus pneumoniae infection.

In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity

Type-2 diabetes and obesity are among the leading human diseases and highly complex in terms of diagnostic and therapeutic approaches and are among the most frequent and highly complex and heterogeneous in nature. Based on epidemiological evidence, it is known that the patients suffering from obesity are considered to be at a significantly higher risk of type-2 diabetes. There are several pieces of evidence that support the hypothesis that these diseases interlinked and obesity may aggravate the risk(s) of type-2 diabetes. Multi-level unwanted alterations such as (epi-) genetic alterations, changes at the transcriptional level, and altered signaling pathways (receptor, cytoplasmic, and nuclear level) are the major sources that promote several complex diseases, and such a heterogeneous level of complexity is considered as a major barrier in the development of therapeutics. With so many known challenges, it is critical to understand the relationships and the shared causes between type-2 diabetes and obesity, and these are difficult to unravel and understand. For this purpose, we have selected publicly available datasets of gene expression for obesity and type-2 diabetes, have unraveled the genes and the pathways associated with the immune system, and have also focused on the T-cell signaling pathway and its components. We have applied a simplified computational approach to understanding differential gene expression and patterns and the enriched pathways for obesity and type-2 diabetes. Furthermore, we have also analyzed genes by using network-level understanding. In the analysis, we observe that there are fewer genes that are commonly differentially expressed while a comparatively higher number of pathways are shared between them. There are only 4 pathways that are associated with the immune system in case of obesity and 10 immune-associated pathways in case of type-2 diabetes, and, among them, only 2 pathways are commonly altered. Furthermore, we have presented SPNS1, PTPN6, CD247, FOS, and PIK3R5 as the overexpressed genes, which are the direct components of TCR signaling.

Recent Advances in Integrative Multi-Omics Research in Breast and Ovarian Cancer

The underlying molecular heterogeneity of cancer is responsible for the dynamic clinical landscape of this disease. The combination of genomic and proteomic alterations, including both inherited and acquired mutations, promotes tumor diversity and accounts for variable disease progression, therapeutic response, and clinical outcome. Recent advances in high-throughput proteogenomic profiling of tumor samples have resulted in the identification of novel oncogenic drivers, tumor suppressors, and signaling networks; biomarkers for the prediction of drug sensitivity and disease progression; and have contributed to the development of novel and more effective treatment strategies. In this review, we will focus on the impact of historical and recent advances in single platform and integrative proteogenomic studies in breast and ovarian cancer, which constitute two of the most lethal forms of cancer for women, and discuss the molecular similarities of these diseases, the impact of these findings on our understanding of tumor biology as well as the clinical applicability of these discoveries.

Association of an anaplastic lymphoma kinase pathway signature with cell de-differentiation, neoadjuvant chemotherapy response, and recurrence risk in breast cancer

Background

Aberrant activation of anaplastic lymphoma kinase (ALK) signaling has been found to be involved in the tumorigenesis of multiple types of cancer. The aim of this study was to determine the role of this pathway in the pathogenesis of breast cancer.

Methods

An ALK pathway signature that we generated previously was used to compute the ALK pathway activity in 6381 breast cancer samples from 42 microarray datasets, and the associations between ALK pathway signature score and clinical variables were examined using logistic regression and survival analyses.

Results

Our results indicated that high ALK pathway activity was a significant risk factor for hormone receptor‐negative, high‐grade breast cancer in the 42 datasets. ALK pathway activity was positively associated with pathological complete response (pCR) in 15 datasets annotated with patient's neoadjuvant chemotherapy response information (overall odds ratio = 1.67, P < 0.01), and this association was more significant in HER2‐negative and grade 1&2 tumors than in HER2‐positive and grade 3 tumors. ALK pathway activity was also positively associated with recurrence risk in breast cancer patients from 30 datasets annotated with survival information (overall hazard ratio = 1.21, P < 0.01), particularly in patients with age > 50 years old, with positive lymph nodes, or with residual disease after neoadjuvant chemotherapy.

Conclusions

ALK may be involved in breast cancer tumorigenesis, and ALK pathway signature score may serve as a prognostic biomarker for breast cancer.

Using gene expression data to direct breast cancer therapy: evidence from a preclinical trial

The heterogeneity both within and between breast cancers presents a significant clinical challenge for both diagnosis and therapy. This heterogeneity is present at all levels of analysis in breast cancer, ranging from genomic to metabolomic. A function of this heterogeneity is that numerous signaling networks are activated, and while treatment of one arm may be initially effective, this allows the tumor to be poised to evolve a resistance mechanism. Here we review the classification of breast cancers and discuss therapy of hormone positive, HER2 positive, and triple negative breast cancers. Model systems for breast cancer are examined allowing for a preclinical trial using a personalized medicine approach to be tested. This preclinical trial was based solely on cell signaling pathway activation and effectively and specifically blocked tumor growth in a preclinical model system.

A Phase I Trial of the PI3K Inhibitor Buparlisib Combined With Capecitabine in Patients With Metastatic Breast Cancer

BACKGROUND

Buparlisib is an oral pan-class I phosphotidyinositol-3-kinase (PI3K) inhibitor. The present phase I study evaluated the safety, pharmacokinetics, and efficacy of buparlisib with capecitabine in patients with metastatic breast cancer.

PATIENTS AND METHODS

Patients received buparlisib once daily (range, 50 to 100 mg) for 3 weeks with capecitabine twice daily (range, 1000 to 1250 mg/m²) for 2 weeks with a 1-week break. Dose escalation used a traditional "3 + 3" design with standard definitions of dose-limiting toxicity (DLT) and maximum tolerated dose.

RESULTS

Of the 25 patients enrolled, 23 were evaluable for DLT and 17 were evaluable for response. The maximum tolerated dose of the combination was buparlisib 100 mg daily and capecitabine 1000 mg/m² twice daily. DLTs included grade 3 hyperglycemia and grade 3 confusion. The most common grade 3 toxicities were diarrhea and elevation of aspartate aminotransferase and alanine transaminase. One patient exhibited a complete response to treatment and four had a confirmed partial response. In cohorts 3 and 4, in which the buparlisib dose remained constant but the capecitabine dose was increased, significant increases in the buparlisib plasma concentration were noted.

CONCLUSION

The combination of buparlisib with capecitabine in patients with metastatic breast cancer was generally well-tolerated, with several patients demonstrating prolonged responses. Unexpectedly low rates of PIK3CA mutations (3 of 17) were seen, and only 2 of 7 tumors with subtyping were luminal, making exploration of these putative predictive markers impossible. Further study of the combination is not unreasonable, with expanded pharmacokinetics and sequencing analysis to better elucidate potential drug-drug interactions and more accurate predictive biomarkers of response.

Personalisierte Medizin bei soliden Tumoren

Ein personalisierter Therapieansatz wird in der Behandlung solider Tumore seit Entdeckung der Hormonabhängigkeit von Mammakarzinomen verfolgt. Die verbesserten technischen Möglichkeiten, einen Tumor über die Organzugehörigkeit und den histopathologischen Befund hinaus zu charakterisieren, bringen neue Therapiemöglichkeiten hervor. Im Folgenden werden bereits existierende gezielte Therapieansätze und Resistenzmechanismen beschrieben. Neben einer Erläuterung der praktischen Anwendung der neuen Techniken wie Genexpressionsprofile und die Untersuchung von Tumormaterial auf somatische Mutationen in einer Vielzahl von Genen wird auch der neuen Entwicklung einer Therapie auf der Basis von Keimbahnmutationen in den Genen BRCA1 und BRCA2 mit dem PARP-Inhibitor Olaparib Rechnung getragen und ein Ausblick auf zukünftige Entwicklungen wie Liquid Biopsy erbracht.

Multimodal Assessment of Estrogen Receptor mRNA Profiles to Quantify Estrogen Pathway Activity in Breast Tumors

BACKGROUND

Molecular markers have transformed our understanding of the heterogeneity of breast cancer and have allowed the identification of genomic profiles of estrogen receptor (ER)-α signaling. However, our understanding of the transcriptional profiles of ER signaling remains inadequate. Therefore, we sought to identify the genomic indicators of ER pathway activity that could supplement traditional immunohistochemical (IHC) assessments of ER status to better understand ER signaling in the breast tumors of individual patients.

MATERIALS AND METHODS

We reduced ESR1 (gene encoding the ER-α protein) mRNA levels using small interfering RNA in ER⁺ MCF7 breast cancer cells and assayed for transcriptional changes using Affymetrix HG U133 Plus 2.0 arrays. We also compared 1034 ER⁺ and ER^- breast tumors from publicly available microarray data. The principal components of ER activity generated from these analyses and from other published estrogen signatures were compared with ESR1 expression, ER-α IHC, and patient survival.

RESULTS

Genes differentially expressed in both analyses were associated with ER-α IHC and ESR1 mRNA expression. They were also significantly enriched for estrogen-driven molecular pathways associated with ESR1, cyclin D1 (CCND1), MYC (v-myc avian myelocytomatosis viral oncogene homolog), and NFKB (nuclear factor kappa B). Despite their differing constituent genes, the principal components generated from these new analyses and from previously published ER-associated gene lists were all associated with each other and with the survival of patients with breast cancer treated with endocrine therapies.

CONCLUSION

A biomarker of ER-α pathway activity, generated using ESR1-responsive mRNAs in MCF7 cells, when used alongside ER-α IHC and ESR1 mRNA expression, could provide a method for further stratification of patients and add insight into ER pathway activity in these patients.

Ras Signaling Is a Key Determinant for Metastatic Dissemination and Poor Survival of Luminal Breast Cancer Patients

Breast cancer is associated with alterations in a number of growth factor and hormone-regulated signaling pathways. Mouse models of metastatic breast cancer typically feature mutated oncoproteins that activate PI3K, Stat3, and Ras signaling, but the individual and combined roles of these pathways in breast cancer progression are poorly understood. In this study, we examined the relationship between oncogenic pathway activation and breast cancer subtype by analyzing mouse mammary tumor formation in which each pathway was activated singly or pairwise. All three oncogenes showed cooperation during primary tumor formation, but efficient dissemination was only dependent on Ras. In addition, transcriptional profiling demonstrated that Ras induced adenocarcinomas with molecular characteristics related to human basal-like and HER2(+) tumors. In contrast, Ras combined with PIK3CA(H1047R), an oncogenic mutant linked to ERα(+)/luminal breast cancer in humans, induced metastatic luminal B-like tumors. Consistent with these data, elevated Ras signaling was associated with basal-like and HER2(+) subtype tumors in humans and showed a statistically significant negative association with estrogen receptor (ER) signaling across all breast cancer. Despite this, there are luminal tumors with elevated Ras signaling. Importantly, when considered as a continuous variable, Ras pathway activation was strongly linked to reduced survival of patients with ERα(+) disease independent of PI3K or Stat3 activation. Therefore, our studies suggest that Ras activation is a key determinant for dissemination and poor prognosis of ERα(+)/luminal breast cancer in humans, and hormone therapy supplemented with Ras-targeting agents may be beneficial for treating this aggressive subtype.

The use of Bayesian hierarchical models for adaptive randomization in biomarker-driven phase II studies

The role of biomarkers has increased in cancer clinical trials such that novel designs are needed to efficiently answer questions of both drug effects and biomarker performance. We advocate Bayesian hierarchical models for response-adaptive randomized phase II studies integrating single or multiple biomarkers. Prior selection allows one to control a gradual and seamless transition from randomized-blocks to marker-enrichment during the trial. Adaptive randomization is an efficient design for evaluating treatment efficacy within biomarker subgroups, with less variable final sample sizes when compared to nested staged designs. Inference based on the Bayesian hierarchical model also has improved performance in identifying the sub-population where therapeutics are effective over independent analyses done within each biomarker subgroup.

p38γ MAPK Is a Therapeutic Target for Triple-Negative Breast Cancer by Stimulation of Cancer Stem-Like Cell Expansion

Triple-negative breast cancer (TNBC) is highly progressive and lacks established therapeutic targets. p38γ mitogen-activated protein kinase (MAPK) (gene name: MAPK12) is overexpressed in TNBC but how overexpressed p38γ contributes to TNBC remains unknown. Here, we show that p38γ activation promotes TNBC development and progression by stimulating cancer stem-like cell (CSC) expansion and may serve as a novel therapeutic target. p38γ silencing in TNBC cells reduces mammosphere formation and decreases expression levels of CSC drivers including Nanog, Oct3/4, and Sox2. Moreover, p38γ MAPK-forced expression alone is sufficient to stimulate CSC expansion and to induce epithelial cell transformation in vitro and in vivo. Furthermore, p38γ depends on its activity to stimulate CSC expansion and breast cancer progression, indicating a therapeutic opportunity by application of its pharmacological inhibitor. Indeed, the non-toxic p38γ specific pharmacological inhibitor pirfenidone selectively inhibits TNBC growth in vitro and/or in vivo and significantly decreases the CSC population. Mechanistically, p38γ stimulates Nanog transcription through c-Jun/AP-1 via a multi-protein complex formation. These results together demonstrate that p38γ can drive TNBC development and progression and may be a novel therapeutic target for TNBC by stimulating CSC expansion. Inhibiting p38γ activity with pirfenidone may be a novel strategy for the treatment of TNBC.

Neural networks and Fuzzy clustering methods for assessing the efficacy of microarray based intrinsic gene signatures in breast cancer classification and the character and relations of identified subtypes

In the classification of breast cancer subtypes using microarray data, hierarchical clustering is commonly used. Although this form of clustering shows basic cluster patterns, more needs to be done to investigate the accuracy of clusters as well as to extract meaningful cluster characteristics and their relations to increase our confidence in their use in a clinical setting. In this study, an in-depth investigation of the efficacy of three reported gene subsets in distinguishing breast cancer subtypes was performed using four advanced computational intelligence methods-Self-Organizing Maps (SOM), Emergent Self-Organizing Maps (ESOM), Fuzzy Clustering by Local Approximation of Memberships (FLAME), and Fuzzy C-means (FCM)-each differing in the way they view data in terms of distance measures and fuzzy or crisp clustering. The gene subsets consisted of 71, 93, and 71 genes reported in the literature from three comprehensive experimental studies for distinguishing Luminal (A and B), Basal, Normal breast-like, and HER2 subtypes. Given the costly procedures involved in clinical studies, the proposed 93-gene set can be used for preliminary classification of breast cancer. Then, as a decision aid, SOM can be used to map the gene signature of a new patient to locate them with respect to all subtypes to get a comprehensive view of the classification. These can be followed by a deeper investigation in the light of the observations made in this study regarding overlapping subtypes. Results from the study could be used as the base for further refining the gene signatures from later experiments and from new experiments designed to separate overlapping clusters as well as to maximally separate all clusters.

An integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer

Elucidating the molecular drivers of human breast cancers requires a strategy capable of integrating multiple forms of data and an ability to interpret the functional consequences of a given genetic aberration. Here we present an integrated genomic strategy based on the use of gene expression signatures of oncogenic pathway activity (n=52) as a framework to analyze DNA copy number alterations in combination with data from a genome-wide RNAi screen. We identify specific DNA amplifications, and importantly, essential genes within these amplicons representing key genetic drivers, including known and novel regulators of oncogenesis. The genes identified include eight that are essential for cell proliferation (FGD5, METTL6, CPT1A, DTX3, MRPS23, EIF2S2, EIF6 and SLC2A10) and are uniquely amplified in patients with highly proliferative luminal breast tumors, a clinical subset of patients for which few therapeutic options are effective. Our results demonstrate that this general strategy has the potential to identify putative therapeutic targets within amplicons through an integrated use of genetic, genomic, and genome-wide RNAi data sets.

Breast cancer classification: linking molecular mechanisms to disease prognosis

Breast cancer was traditionally perceived as a single disease; however, recent advances in gene expression and genomic profiling have revealed that breast cancer is in fact a collection of diseases exhibiting distinct anatomical features, responses to treatment and survival outcomes. Consequently, a number of schemes have been proposed for subtyping of breast cancer to bring out the biological and clinically relevant characteristics of the subtypes. Although some of these schemes capture underlying molecular differences, others predict variations in response to treatment and survival patterns. However, despite this diversity in the approaches, it is clear that molecular mechanisms drive clinical outcomes, and therefore an effective scheme should integrate molecular as well as clinical parameters to enable deeper understanding of cancer mechanisms and allow better decision making in the clinic. Here, using a large cohort of ∼550 breast tumours from The Cancer Genome Atlas, we systematically evaluate a number of expression-based schemes including at least eight molecular pathways implicated in breast cancer and three prognostic signatures, across a variety of classification scenarios covering molecular characteristics, biomarker status, tumour stages and survival patterns. We observe that a careful combination of these schemes yields better classification results compared with using them individually, thus confirming that molecular mechanisms and clinical outcomes are related and that an effective scheme should therefore integrate both these parameters to enable a deeper understanding of the cancer.

An integrated genomic approach identifies persistent tumor suppressive effects of transforming growth factor-β in human breast cancer

INTRODUCTION

Transforming growth factor-βs (TGF-βs) play a dual role in breast cancer, with context-dependent tumor-suppressive or pro-oncogenic effects. TGF-β antagonists are showing promise in early-phase clinical oncology trials to neutralize the pro-oncogenic effects. However, there is currently no way to determine whether the tumor-suppressive effects of TGF-β are still active in human breast tumors at the time of surgery and treatment, a situation that could lead to adverse therapeutic responses.

METHODS

Using a breast cancer progression model that exemplifies the dual role of TGF-β, promoter-wide chromatin immunoprecipitation and transcriptomic approaches were applied to identify a core set of TGF-β-regulated genes that specifically reflect only the tumor-suppressor arm of the pathway. The clinical significance of this signature and the underlying biology were investigated using bioinformatic analyses in clinical breast cancer datasets, and knockdown validation approaches in tumor xenografts.

RESULTS

TGF-β-driven tumor suppression was highly dependent on Smad3, and Smad3 target genes that were specifically enriched for involvement in tumor suppression were identified. Patterns of Smad3 binding reflected the preexisting active chromatin landscape, and target genes were frequently regulated in opposite directions in vitro and in vivo, highlighting the strong contextuality of TGF-β action. An in vivo-weighted TGF-β/Smad3 tumor-suppressor signature was associated with good outcome in estrogen receptor-positive breast cancer cohorts. TGF-β/Smad3 effects on cell proliferation, differentiation and ephrin signaling contributed to the observed tumor suppression.

CONCLUSIONS

Tumor-suppressive effects of TGF-β persist in some breast cancer patients at the time of surgery and affect clinical outcome. Carefully tailored in vitro/in vivo genomic approaches can identify such patients for exclusion from treatment with TGF-β antagonists.

[Personalized medicine and breast cancer: anticipatory medicine, prognostic evaluation and therapeutic targeting]

Breast cancer is now considered as a large collection of distinct biological entities, the management of which is increasingly personalized. Personalized medicine - defined as a medicine, which uses molecular profiles, notably genetic profiles, from patients and/or tumors to tailor therapeutic decisions - is now introduced in the management of breast cancer at any stages: screening and prevention of hereditary forms, prognostic and predictive evaluation of early breast cancer, and, more recently, novel clinical trials in advanced breast cancer, where genetic characterization of tumor tissue based on genomics, including next-generation sequencing tools, is used to drive specific therapeutic targeting.

Treatment of triple-negative breast cancer using anti-EGFR-directed radioimmunotherapy combined with radiosensitizing chemotherapy and PARP inhibitor

Triple-negative breast cancer (TNBC) is associated with poor survival. Chemotherapy is the only standard treatment for TNBC. The prevalence of BRCA1 inactivation in TNBC has rationalized clinical trials of poly(adenosine diphosphate ribose) polymerase (PARP) inhibitors. Similarly, the overexpression of epidermal growth factor receptor (EGFR) rationalized anti-EGFR therapies in this disease. However, clinical trials using these 2 strategies have not reached their promise. In this study, we used EGFR as a target for radioimmunotherapy and hypothesized that EGFR-directed radioimmunotherapy can deliver a continuous lethal radiation dose to residual tumors that are radiosensitized by PARP inhibitors and chemotherapy.

METHODS

We analyzed EGFR messenger RNA in published gene expression array studies and investigated EGFR protein expression by immunohistochemistry in a cohort of breast cancer patients to confirm EGFR as a target in TNBC. Preclinically, using orthotopic and metastatic xenograft models of EGFR-positive TNBC, we investigated the effect of the novel combination of (177)Lu-labeled anti-EGFR monoclonal antibody, chemotherapy, and PARP inhibitors on cell death and the survival of breast cancer stem cells.

RESULTS

In this first preclinical study of anti-EGFR radioimmunotherapy in breast cancer, we found that anti-EGFR radioimmunotherapy is safe and that TNBC orthotopic tumors and established metastases were eradicated in mice treated with anti-EGFR radioimmunotherapy combined with chemotherapy and PARP inhibitors. We showed that the superior response to this triple-agent combination therapy was associated with apoptosis and eradication of putative breast cancer stem cells.

CONCLUSION

Our data support further preclinical investigations toward the development of combination therapies using systemic anti-EGFR radioimmunotherapy for the treatment of recurrent and metastatic TNBC.

Treatment algorithms for hormone receptor-positive advanced breast cancer: going forward in endocrine therapy—overcoming resistance and introducing new agents

Overcoming de novo or acquired endocrine resistance remains critical to further enhancing the benefit of existing endocrine therapies. Recent progress has been made in understanding the molecular biology associated with acquired endocrine resistance, including adaptive "cross-talk" between ER and various growth factor receptor and cell-signaling pathways. Strategies that combine endocrine therapy with targeted inhibitors of growth factor receptors or cell-survival pathways to further enhance first-line response have largely been disappointing, suggesting that any attempts to prevent endocrine resistance by blocking specific pathways from the outset will be futile. In contrast, success has been seen by selecting patients with acquired endocrine resistance and enhancing response to further endocrine therapy by the addition of mTOR antagonists. Numerous other therapeutics are being evaluated in combination with endocrine therapies based on varying levels of preclinical science to support their use, including inhibitors of PI3K, HDAC, Src, IGFR-1, and CDK4/6. Enriching trial recruitment by molecular profiling of different ER+ subtypes will become increasingly important to maximize any additional benefit that these new agents may bring to current endocrine therapies for breast cancer.

Chemotherapy (CT) and hormonotherapy (HT) as neoadjuvant treatment in luminal breast cancer patients: results from the GEICAM/2006-03, a multicenter, randomized, phase-II study

BACKGROUND

Luminal breast cancer is a highly endocrine responsive disease. However, the therapeutic benefit of chemotherapy (CT) in this population is not fully characterized. This study investigates the value of CT and hormone therapy (HT) in luminal breast cancer patients in the neoadjuvant setting.

PATIENTS AND METHODS

Patients with operable breast cancer and immunophenotypically defined luminal disease (ER+/PR+/HER2-/cytokeratin 8/18+) were recruited. Patients were randomized to CT (epirubicin 90 mg/m(2) plus cyclophosphamide 600 mg/m(2) 4 cycles followed by docetaxel 100 mg/m(2 )4 cycles [EC-T]) or HT (exemestane 25 mg daily 24 weeks [combined with goserelin in premenopausal patients]). The primary end point was the clinical response measured by magnetic resonance imaging.

RESULTS

Ninety-five patients were randomized (47 CT, 48 HT). The clinical response rate was 66% for CT and 48% for HT (P = 0.075). We performed an unplanned analysis based on Ki67 levels (cut-off of 10%). Similar clinical response was seen between arms in patients with low Ki67 (CT: 63%, HT: 58%; P = 0.74); patients with high Ki67 had a better response with CT (67 versus 42%; P = 0.075). Grade 3/4 toxicity was more frequent with CT.

CONCLUSIONS

Luminal immunophenotype is not enough to identify patients who do not benefit from neoadjuvant CT. Luminal patients with low proliferation index could potentially avoid CT.

Adhesion-mediated cytoskeletal remodeling is controlled by the direct scaffolding of Src from FAK complexes to lipid rafts by SSeCKS/AKAP12

Metastatic cell migration and invasion are regulated by altered adhesion-mediated signaling to the actin-based cytoskeleton via activated Src-FAK complexes. SSeCKS (the rodent orthologue of human Gravin/AKAP12), whose expression is downregulated by oncogenic Src and in many human cancers, antagonizes oncogenic Src pathways including those driving neovascularization at metastatic sites, metastatic cell motility and invasiveness. This is likely manifested through its function as a scaffolder of F-actin and signaling proteins such as cyclins, calmodulin, protein kinase (PK) C and PKA. Here, we show that in contrast to its ability to inhibit haptotaxis, SSeCKS increased prostate cancer cell adhesion to fibronectin (FN) and type I collagen in a FAK-dependent manner, correlating with a relative increase in FAK^poY397 levels. In contrast, SSeCKS suppressed adhesion-induced Src activation (Src^poY416) and phosphorylation of FAK at Y925, a known Src substrate site. SSeCKS also induced increased cell spreading, cell flattening, integrin β1 clustering and formation of mature focal adhesion plaques. An in silico analysis identified a Src-binding domain on SSeCKS (a.a.153–166) that is homologous to the Src binding domain of Caveolin-1, and this region is required for SSeCKS-Src interaction, for SSeCKS-enhanced Src activity and sequestration to lipid rafts, and for SSeCKS-enhanced adhesion of MAT-LyLu and CWR22Rv1 prostate cancer cells. Our data suggest a model in which SSeCKS suppresses oncogenic motility by sequestering Src to caveolin-rich lipid rafts, thereby disengaging Src from FAK-associated adhesion and signaling complexes.

A prognostic signature of defective p53-dependent G1 checkpoint function in melanoma cell lines

Melanoma cell lines and normal human melanocytes (NHM) were assayed for p53-dependent G1 checkpoint response to ionizing radiation (IR)-induced DNA damage. Sixty-six percent of melanoma cell lines displayed a defective G1 checkpoint. Checkpoint function was correlated with sensitivity to IR with checkpoint-defective lines being radio-resistant. Microarray analysis identified 316 probes whose expression was correlated with G1 checkpoint function in melanoma lines (P≤0.007) including p53 transactivation targets CDKN1A, DDB2, and RRM2B. The 316 probe list predicted G1 checkpoint function of the melanoma lines with 86% accuracy using a binary analysis and 91% accuracy using a continuous analysis. When applied to microarray data from primary melanomas, the 316 probe list was prognostic of 4-yr distant metastasis-free survival. Thus, p53 function, radio-sensitivity, and metastatic spread may be estimated in melanomas from a signature of gene expression.

Activation-induced cytidine deaminase (AID) linking immunity, chronic inflammation, and cancer

Activation-induced cytidine deaminase (AID) is critically involved in class switch recombination and somatic hypermutation of Ig loci resulting in diversification of antibodies repertoire and production of high-affinity antibodies and as such represents a physiological tool to introduce DNA alterations. These processes take place within germinal centers of secondary lymphoid organs. Under physiological conditions, AID is expressed predominantly in activated B lymphocytes. Because of the mutagenic and recombinogenic potential of AID, its expression and activity is tightly regulated on different levels to minimize the risk of unwanted DNA damage. However, chronic inflammation and, probably, combination of other not-yet-identified factors are able to create a microenvironment sufficient for triggering an aberrant AID expression in B cells and, importantly, in non-B-cell background. Under these circumstances, AID may target also non-Ig genes, including cancer-related genes as oncogenes, tumor suppressor genes, and genomic stability genes, and modulate both genetic and epigenetic information. Despite ongoing progress, the complete understanding of fundamental aspects is still lacking as (1) what are the crucial factors triggering an aberrant AID expression/activity including the impact of Th2-driven inflammation and (2) to what extent may aberrant AID in human non-B cells lead to abnormal cell state associated with an increased rate of genomic alterations as point mutations, small insertions or deletions, and/or recurrent chromosomal translocations during solid tumor development and progression.

[Genomics and clinical research for breast cancer]

Genomics of breast cancer is paving the way towards more and more tailored treatments. The number of molecularly targeted therapies under development is increasing. In parallel, the high-throughput analyses revealed the molecular heterogeneity of disease, and identified several very different molecular subtypes, numerous and sometimes very scarce molecular alterations, and multigenic signatures predictive for clinical outcome, some of which are being tested in prospective clinical trials. This molecular segmentation of breast cancer and the multitude of new drugs to be tested (alone and in combination) lead to develop clinical trials based on the molecular profile of tumors to guide the patient towards the most suitable drug.

Pumilio facilitates miRNA regulation of the E2F3 oncogene

E2F transcription factors are important regulators of cell proliferation and are frequently dysregulated in human malignancies. To identify novel regulators of E2F function, we used Drosophila as a model system to screen for mutations that modify phenotypes caused by reduced levels of dE2F1. This screen identified components of the Pumilio translational repressor complex (Pumilio, Nanos, and Brain tumor) as suppressors of dE2F1-RNAi phenotypes. Subsequent experiments provided evidence that Pumilio complexes repress dE2F1 levels and that this mechanism of post-transcriptional regulation is conserved in human cells. The human Pumilio homologs Pum 1 and Pum 2 repress the translation of E2F3 by binding to the E2F3 3' untranslated region (UTR) and also enhance the activity of multiple E2F3 targeting microRNAs (miRNAs). E2F3 is an oncogene with strong proliferative potential and is regularly dysregulated or overexpressed in cancer. Interestingly, Pumilio/miRNA-mediated regulation of E2F3 is circumvented in cancer cells in several different ways. Bladder carcinomas selectively down-regulate miRNAs that cooperate with Pumilio to target E2F3, and multiple tumor cell lines shorten the 3' end of the E2F3 mRNA, removing the Pumilio regulatory elements. These studies suggest that Pumilio-miRNA repression of E2F3 translation provides an important level of E2F regulation that is frequently abrogated in cancer cells.

Triple-negative subtype predicts poor overall survival and high locoregional relapse in inflammatory breast cancer

BACKGROUND

Numerous studies have demonstrated that expression of estrogen/progesterone receptor (ER/PR) and human epidermal growth factor receptor (HER)-2 is important for predicting overall survival (OS), distant relapse (DR), and locoregional relapse (LRR) in early and advanced breast cancer patients. However, these findings have not been confirmed for inflammatory breast cancer (IBC), which has different biological features than non-IBC.

METHODS

We retrospectively analyzed the records of 316 women who presented to MD Anderson Cancer Center in 1989-2008 with newly diagnosed IBC without distant metastases. Most patients received neoadjuvant chemotherapy, mastectomy, and postmastectomy radiation. Patients were grouped according to receptor status: ER(+) (ER(+)/PR(+) and HER-2-; n = 105), ER(+)HER-2(+) (ER(+)/PR(+) and HER-2(+); n = 37), HER-2(+) (ER(-)/PR(-) and HER-2(+); n = 83), or triple-negative (TN) (ER(-)PR(-)HER-2(-); n = 91). Kaplan-Meier and Cox proportional hazards methods were used to assess LRR, DR, and OS rates and their associations with prognostic factors.

RESULTS

The median age was 50 years (range, 24-83 years). The median follow-up time and median OS time for all patients were both 33 months. The 5-year actuarial OS rates were 58.7% for the entire cohort, 69.7% for ER(+) patients, 73.5% for ER(+)HER-2(+) patients, 54.0% for HER=2(+) patients, and 42.7% for TN patients (p < .0001); 5-year LRR rates were 20.3%, 8.0%, 12.6%, 22.6%, and 38.6%, respectively, for the four subgroups (p < .0001); and 5-year DR rates were 45.5%, 28.8%, 50.1%, 52.1%, and 56.7%, respectively (p < .001). OS and LRR rates were worse for TN patients than for any other subgroup (p < .0001-.03).

CONCLUSIONS

TN disease is associated with worse OS, DR, and LRR outcomes in IBC patients, indicating the need for developing new locoregional and systemic treatment strategies for patients with this aggressive subtype.

Activation-induced cytidine deaminase (AID)-associated multigene signature to assess impact of AID in etiology of diseases with inflammatory component

Activation-induced cytidine deaminase (AID) is expressed in B cells within germinal centers and is critically involved in class switch recombination and somatic hypermutation of immunoglobulin loci. Functionally active AID can additionally be detected within ectopic follicular structures developed at sites of chronic inflammation. Furthermore, AID may target non-Ig genes in B- and non-B-cell background. Therefore, AID-associated effects are of increasing interest in disease areas such as allergy, inflammation, autoimmunity, and cancer.Pathway- or disease-relevant multigene signatures have attracted substantial attention for therapeutic target proposal, diagnostic tools, and monitoring of therapy response. To delineate the impact of AID in etiology of multifactorial diseases, we designed the AID-associated 25-gene signature. Chronic rhinosinusitis with nasal polyps was used as an inflammation-driven airway disease model; high levels of IgE have been previously shown to be present within polyp tissue. Expression levels of 16 genes were found to be modulated in polyps including AID, IgG and IgE mature transcripts which reflect AID activity; clustering algorithm revealed an AID-specific gene signature for the disease state with nasal polyp. Complementary, AID-positive ectopic lymphoid structures were detected within polyp tissues by in situ immunostaining. Our data demonstrate the class switch recombination and somatic hypermutation events likely taking place locally in the airways and in addition to the previously highlighted markers and/or targets as IL5 and IgE suggest novel candidate genes to be considered for treatment of nasal polyposis including among others IL13 and CD23. Thus, the algorithm presented herein including the multigene signature approach, analysis of co-regularities and creation of AID-associated functional network gives an integrated view of biological processes and might be further applied to assess role of altered AID expression in etiology of other diseases, in particular, aberrant immunity and cancer.

A phase 2 trial of dasatinib in patients with advanced HER2-positive and/or hormone receptor-positive breast cancer

PURPOSE

SRC-family kinases (SFK) are involved in numerous oncogenic signaling pathways. A phase 2 trial of dasatinib, a potent oral tyrosine kinase inhibitor of SFKs, was carried out in patients with human epidermal growth factor receptor 2-positive (HER2+) and/or hormone receptor-positive (HR+) advanced breast cancer.

EXPERIMENTAL DESIGN

Patients with measurable tumors and progression after chemotherapy and HER2 and/or HR-targeted agents in adjuvant or metastatic settings (maximum of two prior metastatic setting regimens) received twice daily dasatinib. Primary endpoint was Response Evaluation Criteria in Solid Tumors-defined response rate. Secondary endpoints included toxicity and limited pharmacokinetics.

RESULTS

Seventy patients (55 years median age) were treated, 83% of HER2+ patients had received prior HER2-directed therapy, and 61% of HR+ patients had received prior endocrine therapy in the advanced setting. Dasatinib starting dose was reduced from 100 to 70 mg twice daily to limit toxicity. Median therapy duration was 1.8 months in both dose groups and most discontinuations were due to progression. Of 69 evaluable patients, three had confirmed partial responses and six had stable disease for 16 weeks or more (disease control rate = 13.0%); all nine of these tumors were HR+ (two were also HER2+). The most common drug-related toxicities were gastrointestinal complaints, headache, asthenia, and pleural effusion. Grade 3-4 toxicity occurred in 37% of patients and was comparable between doses; drug-related serious adverse events were less frequent with 70 mg twice daily than 100 mg twice daily.

CONCLUSION

Limited single-agent activity was observed with dasatinib in patients with advanced HR+ breast cancer.

Clinical implementation of RNA signatures for pharmacogenomic decision-making

RNA profiling is increasingly used to predict drug response, dose, or toxicity based on analysis of drug pharmacokinetic or pharmacodynamic pathways. Before implementing multiplexed RNA arrays in clinical practice, validation studies are carried out to demonstrate sufficient evidence of analytic and clinical performance, and to establish an assay protocol with quality assurance measures. Pathologists assure quality by selecting input tissue and by interpreting results in the context of the input tissue as well as the technologies that were used and the clinical setting in which the test was ordered. A strength of RNA profiling is the array-based measurement of tens to thousands of RNAs at once, including redundant tests for critical analytes or pathways to promote confidence in test results. Instrument and reagent manufacturers are crucial for supplying reliable components of the test system. Strategies for quality assurance include careful attention to RNA preservation and quality checks at pertinent steps in the assay protocol, beginning with specimen collection and proceeding through the various phases of transport, processing, storage, analysis, interpretation, and reporting. Specimen quality is checked by probing housekeeping transcripts, while spiked and exogenous controls serve as a check on analytic performance of the test system. Software is required to manipulate abundant array data and present it for interpretation by a laboratory physician who reports results in a manner facilitating therapeutic decision-making. Maintenance of the assay requires periodic documentation of personnel competency and laboratory proficiency. These strategies are shepherding genomic arrays into clinical settings to provide added value to patients and to the larger health care system.

Glutamine synthetase is a genetic determinant of cell type-specific glutamine independence in breast epithelia

Although significant variations in the metabolic profiles exist among different cells, little is understood in terms of genetic regulations of such cell type-specific metabolic phenotypes and nutrient requirements. While many cancer cells depend on exogenous glutamine for survival to justify the therapeutic targeting of glutamine metabolism, the mechanisms of glutamine dependence and likely response and resistance of such glutamine-targeting strategies among cancers are largely unknown. In this study, we have found a systematic variation in the glutamine dependence among breast tumor subtypes associated with mammary differentiation: basal- but not luminal-type breast cells are more glutamine-dependent and may be susceptible to glutamine-targeting therapeutics. Glutamine independence of luminal-type cells is associated mechanistically with lineage-specific expression of glutamine synthetase (GS). Luminal cells can also rescue basal cells in co-culture without glutamine, indicating a potential for glutamine symbiosis within breast ducts. The luminal-specific expression of GS is directly induced by GATA3 and represses glutaminase expression. Such distinct glutamine dependency and metabolic symbiosis is coupled with the acquisition of the GS and glutamine independence during the mammary differentiation program. Understanding the genetic circuitry governing distinct metabolic patterns is relevant to many symbiotic relationships among different cells and organisms. In addition, the ability of GS to predict patterns of glutamine metabolism and dependency among tumors is also crucial in the rational design and application of glutamine and other metabolic pathway targeted therapies.

Linear and non-linear dependencies between copy number aberrations and mRNA expression reveal distinct molecular pathways in breast cancer

Background

Elucidating the exact relationship between gene copy number and expression would enable identification of regulatory mechanisms of abnormal gene expression and biological pathways of regulation. Most current approaches either depend on linear correlation or on nonparametric tests of association that are insensitive to the exact shape of the relationship. Based on knowledge of enzyme kinetics and gene regulation, we would expect the functional shape of the relationship to be gene dependent and to be related to the gene regulatory mechanisms involved. Here, we propose a statistical approach to investigate and distinguish between linear and nonlinear dependences between DNA copy number alteration and mRNA expression.

Results

We applied the proposed method to DNA copy numbers derived from Illumina 109 K SNP-CGH arrays (using the log R values) and expression data from Agilent 44 K mRNA arrays, focusing on commonly aberrated genomic loci in a collection of 102 breast tumors. Regression analysis was used to identify the type of relationship (linear or nonlinear), and subsequent pathway analysis revealed that genes displaying a linear relationship were overall associated with substantially different biological processes than genes displaying a nonlinear relationship. In the group of genes with a linear relationship, we found significant association to canonical pathways, including purine and pyrimidine metabolism (for both deletions and amplifications) as well as estrogen metabolism (linear amplification) and BRCA-related response to damage (linear deletion). In the group of genes displaying a nonlinear relationship, the top canonical pathways were specific pathways like PTEN and PI13K/AKT (nonlinear amplification) and Wnt(B) and IL-2 signalling (nonlinear deletion). Both amplifications and deletions pointed to the same affected pathways and identified cancer as the top significant disease and cell cycle, cell signaling and cellular development as significant networks.

Conclusions

This paper presents a novel approach to assessing the validity of the dependence of expression data on copy number data, and this approach may help in identifying the drivers of carcinogenesis.

bc-GenExMiner: an easy-to-use online platform for gene prognostic analyses in breast cancer

Gene prognostic meta-analyses should benefit from breast tumour genomic data obtained during the last decade. The aim was to develop a user-friendly, web-based application, based on DNA microarrays results, called "breast cancer Gene-Expression Miner" (bc-GenExMiner) to improve gene prognostic analysis performance by using the same bioinformatics process. bc-GenExMiner was developed as a web-based tool including a MySQL relational database. Survival analyses are performed with R statistical software and packages. Molecular subtyping was performed by means of three single sample predictors (SSPs) and three subtype clustering models (SCMs). Twenty-one public data sets have been included. Among the 3,414 recovered breast cancer patients, 1,209 experienced a pejorative event. Molecular subtyping by means of three SSPs and three SCMs was performed for 3,063 patients. Furthermore, three robust lists of stable subtyped patients were built to maximize reliability of molecular assignment. Gene prognostic analyses are done by means of univariate Cox proportional hazards model and may be conducted on cohorts split by nodal (N), oestrogen receptor (ER), or molecular subtype status. To evaluate independent prognostic impact of genes relative to Nottingham Prognostic Index and Adjuvant! Online, adjusted Cox proportional hazards models are performed. bc-GenExMiner allows researchers without specific computation skills to easily and quickly evaluate the in vivo prognostic role of genes in breast cancer by means of Cox proportional hazards model on large pooled cohorts, which may be split according to different prognostic parameters: N, ER, and molecular subtype. Prognostic analyses by molecular subtype may also be performed in three robust molecular subtype classifications.

A 3'-untranslated region KRAS variant and triple-negative breast cancer: a case-control and genetic analysis

BACKGROUND

We previously identified a functional variant in a let-7 microRNA (miRNA) complementary site in the 3'-untranslated region of the KRAS oncogene (rs61764370) which is associated with cancer. We aimed to investigate the association of this KRAS variant with breast cancer and tumour biology.

METHODS

We assessed frequency distributions of the KRAS variant in 415 patients with histologically confirmed breast cancer and 457 controls from Connecticut, USA (study group 1) and association of this variant with breast-cancer subtypes in 690 Irish women with known oestrogen receptor (ER), progesterone receptor (PR), and HER2 statuses, and 360 controls (study group 2). We pooled data for study groups 1 and 2 with a cohort of 140 women with triple-negative breast cancer and 113 controls to assess the association of the KRAS variant with triple-negative breast cancer risk, and genome-wide mRNA and specific miRNA expression in patients with triple-negative breast cancer.

FINDINGS

Although frequency distributions of the KRAS variant in study group 1 did not differ between all genotyped individuals, eight (33%) of 24 premenopausal women with ER/PR-negative cancer had the KRAS variant, compared with 27 (13%) of 201 premenopausal controls (p=0.015). In study group 2, the KRAS variant was significantly enriched in women with triple-negative breast cancer (19 [21%] of 90 cases) compared with 64 (13%) of 478 for luminal A, 13 (15%) of 87 for luminal B, and two (6%) of 35 for HER2-positive subgroups (p=0.044). Multivariate analysis in the pooled study groups showed that the KRAS variant was associated with triple-negative breast cancer in premenopausal women (odds ratio 2.307, 95% CI 1.261-4.219, p=0.0067). Gene-expression analysis of triple-negative breast-cancer tumours suggested that KRAS-variant positive tumours have significantly altered gene expression, and are enriched for the luminal progenitor and BRCA1 deficiency signatures. miRNA analysis suggested reduced levels of let-7 miRNA species in KRAS-variant tumours.

INTERPRETATION

The KRAS variant might be a genetic marker for development of triple-negative breast cancer in premenopausal women, and altered gene and miRNA expression signatures should enable molecular and biological stratification of patients with this subgroup of breast cancer.

FUNDING

US National Institutes of Health.

Hunk is required for HER2/neu-induced mammary tumorigenesis

Understanding the molecular pathways that contribute to the aggressive behavior of human cancers is a critical research priority. The SNF1/AMPK-related protein kinase Hunk is overexpressed in aggressive subsets of human breast, ovarian, and colon cancers. Analysis of Hunk(–/–) mice revealed that this kinase is required for metastasis of c-myc–induced mammary tumors but not c-myc–induced primary tumor formation. Similar to c-myc, amplification of the proto-oncogene HER2/neu occurs in 10%–30% of breast cancers and is associated with aggressive tumor behavior. By crossing Hunk(–/–) mice with transgenic mouse models for HER2/neu-induced mammary tumorigenesis, we report that Hunk is required for primary tumor formation induced by HER2/neu. Knockdown and reconstitution experiments in mouse and human breast cancer cell lines demonstrated that Hunk is required for maintenance of the tumorigenic phenotype in HER2/neu-transformed cells. This requirement is kinase dependent and resulted from the ability of Hunk to suppress apoptosis in association with downregulation of the tumor suppressor p27(kip1). Additionally, we find that Hunk is rapidly upregulated following HER2/neu activation in vivo and in vitro. These findings provide what we believe is the first evidence for a role for Hunk in primary tumorigenesis and cell survival and identify this kinase as an essential effector of the HER2/neu oncogenic pathway.

Assessment of kidney organ quality and prediction of outcome at time of transplantation

The critical importance of donor organ quality, i.e., number of surviving nephrons, ability to withstand injury, and capacity for repair in determining short- and long-term outcomes is becoming increasingly clear. This review provides an overview of studies to assess donor kidney quality and subsequent transplant outcomes based on clinical pathology and transcriptome-based variables available at time of transplantation. Prediction scores using clinical variables function when applied to large data sets but perform poorly for the individual patient. Histopathology findings in pre-implantation or post-reperfusion biopsies help to assess structural integrity of the donor kidney, provide information on pre-existing donor disease, and can serve as a baseline for tracking changes over time. However, more validated approaches of analysis and prospective studies are needed to reduce the number of discarded organs, improve allocation, and allow prediction of outcomes. Molecular profiling detects changes not seen by morphology or captured by clinical markers. In particular, molecular profiles provide a quantitative measurement of inflammatory burden or immune activation and reflect coordinated changes in pathways associated with injury and repair. However, description of transcriptome patterns is not an end in itself. The identification of predictive gene sets and the application to an individualized patient management needs the integration of clinical and pathology-based variables, as well as more objective reference markers of transplant function, post-transplant events, and long-term outcomes.

Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

Background

Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ("model signatures") constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer.

Methods

Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways.

Results

We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that simultaneous high MYC and RAS activity confers significantly worse prognosis than either high MYC or high RAS activity alone. We further validate these novel prognostic classifications in independent sets of 173 ER- and 567 ER+ breast cancers.

Conclusion

We have proposed a novel method for pathway activity estimation in tumours and have shown that pathway modules antagonize or synergize to delineate novel prognostic subtypes. Specifically, our results suggest that simultaneous modulation of T-helper differentiation and TGF-beta pathways may improve clinical outcome of hormone insensitive breast cancers over treatments that target only one of these pathways.

Identification of predictive markers of response to the MEK1/2 inhibitor selumetinib (AZD6244) in K-ras-mutated colorectal cancer

Mutant K-ras activity leads to the activation of the RAS/RAF/MEK/ERK pathway in approximately 44% of colorectal cancer (CRC) tumors. Accordingly, several inhibitors of the MEK pathway are under clinical evaluation in several malignancies including CRC. The aim of this study was to develop and characterize predictive biomarkers of response to the MEK1/2 inhibitor AZD6244 in CRC in order to maximize the clinical utility of this agent. Twenty-seven human CRC cell lines were exposed to AZD6244 and classified according to the IC(50) value as sensitive (≤ 0.1 μmol/L) or resistant (>1 μmol/L). All cell lines were subjected to immunoblotting for effector proteins, K-ras/BRAF mutation status, and baseline gene array analysis. Further testing was done in cell line xenografts and K-ras mutant CRC human explants models to develop a predictive genomic classifier for AZD6244. The most sensitive and resistant cell lines were subjected to differential gene array and pathway analyses. Members of the Wnt signaling pathway were highly overexpressed in cell lines resistant to AZD6244 and seem to be functionally involved in mediating resistance by shRNA knockdown studies. Baseline gene array data from CRC cell lines and xenografts were used to develop a k-top scoring pair (k-TSP) classifier, which predicted with 71% accuracy which of a test set of patient-derived K-ras mutant CRC explants would respond to AZD6244, providing the basis for a patient-selective clinical trial. These results also indicate that resistance to AZD6244 may be mediated, in part, by the upregulation of the Wnt pathway, suggesting potential rational combination partners for AZD6244 in CRC.

Through a glass darkly: advances in understanding breast cancer biology, 2000-2010

Our understanding of breast cancer as a clinical and biologic entity has been gaining granularity for several decades; in particular, the importance of hormone receptors and HER2 were realized long ago and have served as the impetus for therapeutic agents that have improved the cure rate of estrogen receptor-positive and HER2-positive breast cancer and the lives of thousands of women. The past decade brought even more understanding of the complexity of breast cancer biology through the development and clinical applications of array-based technologies for discovery and prognostication. We now realize that there are at least 5 intrinsic subtypes within breast cancer, at least one of which-the basal-like-currently lacks targeted therapies and is the most pressing therapeutic challenge for the next decade. We have several validated prognostic profiles that allow increased thoughtfulness in adjuvant decision making. With this understanding also comes the recognition that if breast cancer represents several biologically distinct entities, then breast cancer risk assessment and treatment must take this heterogeneity into account, which complicates trial design and interpretation. Despite therapeutic advances and the development of a number of targeted agents against hormone receptor signaling, HER2, and angiogenesis, we have significant challenges to overcome. These include the need for more tissue-based studies to allow us to understand the mechanisms of sensitivity and resistance within and across subtypes, and the need to revisit risk and prevention by subtype.

Triple-negative breast cancer: present challenges and new perspectives

Triple-negative breast cancers (TNBC), characterized by absence of estrogen receptor (ER), progesterone receptor (PR) and lack of overexpression of human epidermal growth factor receptor 2 (HER2), are typically associated with poor prognosis, due to aggressive tumor phenotype(s), only partial response to chemotherapy and present lack of clinically established targeted therapies. Advances in the design of individualized strategies for treatment of TNBC patients require further elucidation, by combined 'omics' approaches, of the molecular mechanisms underlying TNBC phenotypic heterogeneity, and the still poorly understood association of TNBC with BRCA1 mutations. An overview is here presented on TNBC profiling in terms of expression signatures, within the functional genomic breast tumor classification, and ongoing efforts toward identification of new therapy targets and bioimaging markers. Due to the complexity of aberrant molecular patterns involved in expression, pathological progression and biological/clinical heterogeneity, the search for novel TNBC biomarkers and therapy targets requires collection of multi-dimensional data sets, use of robust multivariate data analysis techniques and development of innovative systems biology approaches.

Claudin 1 in breast tumorigenesis: revelation of a possible novel "claudin high" subset of breast cancers

Claudins are the major component of the tight junctions in epithelial cells and as such play a key role in the polarized location of ion channels, receptors, and enzymes to the different membrane domains. In that regard, claudins are necessary for the harmonious development of a functional epithelium. Moreover, defective tight junctions have been associated with the development of neoplastic phenotype in epithelial cells. Breakdown of cell-cell interactions and deregulation of the expression of junctional proteins are therefore believed to be key steps in invasion and metastasis. Several studies suggest that the claudins are major participants in breast tumorigenesis. In this paper, we discuss recent advances in our understanding of the potential role of claudin 1 in breast cancer. We also discuss the significance of a subset of estrogen receptor negative breast cancers which express “high” levels of the claudin 1 protein. We propose that claudin 1 functions both as a tumor suppressor as well as a tumor enhancer/facilitator in breast cancer.

A pathway-based classification of human breast cancer

The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somatic mutations acquired during oncogenesis. An ability to dissect this heterogeneity, to identify subgroups that represent common mechanisms of disease, will be critical to understanding the complexities of genetic alterations and to provide a framework to develop rational therapeutic strategies. Here, we describe a classification scheme for human breast cancer making use of patterns of pathway activity to build on previous subtype characterizations using intrinsic gene expression signatures, to provide a functional interpretation of the gene expression data that can be linked to therapeutic options. We show that the identified subgroups provide a robust mechanism for classifying independent samples, identifying tumors that share patterns of pathway activity and exhibit similar clinical and biological properties, including distinct patterns of chromosomal alterations that were not evident in the heterogeneous total population of tumors. We propose that this classification scheme provides a basis for understanding the complex mechanisms of oncogenesis that give rise to these tumors and to identify rational opportunities for combination therapies.

New strategies in estrogen receptor-positive breast cancer

Endocrine therapy has led to a significant improvement in outcomes for women with estrogen receptor-positive (ER+) breast cancer. Current questions in the adjuvant setting include the optimal duration of endocrine therapy, and the accurate molecular prediction of endocrine responsiveness using gene array-based assays compared with ER expression itself. In advanced disease, novel selective estrogen receptor antagonists (SERM) have failed to make an impact, although the pure ER antagonist fulvestrant may have a role, albeit optimal dose and sequence remain unclear. Overcoming de novo or acquired endocrine resistance remains critical to enhancing further the benefit of existing endocrine therapies. Recent progress has been made in understanding the molecular biology associated with acquired endocrine resistance, including adaptive "cross-talk" between ER and peptide growth factor receptor pathways such as epidermal growth factor receptor (EGFR)/human epidermal growth factor receptor 2 (HER2). Future strategies that are being evaluated include combining endocrine therapy with inhibitors of growth factor receptors or downstream signaling pathways, to treat or prevent critical resistance pathways that become operative in ER+ tumors. Preclinical experiments have provided great promise for this approach, although clinical data remain mixed. Enriching trial recruitment by molecular profiling of different ER+ subtypes will become increasingly important to maximize additional benefit that new agents may bring to current endocrine therapies for breast cancer.