Time series analysis of neoadjuvant chemotherapy and bevacizumab-treated breast carcinomas reveals a systemic shift in genomic aberrations.

Background: Chemotherapeutic agents such as anthracyclines and taxanes are commonly used in the neoadjuvant setting. Bevacizumab is an antibody which binds to vascular endothelial growth factor A (VEGFA) and inhibits its receptor interaction, thus obstructing the formation of new blood vessels.

Methods: A phase II randomized clinical trial of 123 patients with Her2-negative breast cancer was conducted, with patients treated with neoadjuvant chemotherapy (fluorouracil (5FU)/epirubicin/cyclophosphamide (FEC) and taxane), with or without bevacizumab.

Data-driven analysis of immune infiltrate in a large cohort of breast cancer and its association with disease progression, ER activity, and genomic complexity.

The tumor microenvironment is now widely recognized for its role in tumor progression, treatment response, and clinical outcome. The intratumoral immunological landscape, in particular, has been shown to exert both pro-tumorigenic and anti-tumorigenic effects. Identifying immunologically active or silent tumors may be an important indication for administration of therapy, and detecting early infiltration patterns may uncover factors that contribute to early risk.

The Longitudinal Transcriptional Response to Neoadjuvant Chemotherapy with and without Bevacizumab in Breast Cancer.

Chemotherapy-induced alterations to gene expression are due to transcriptional reprogramming of tumor cells or subclonal adaptations to treatment. The effect on whole-transcriptome mRNA expression was investigated in a randomized phase II clinical trial to assess the effect of neoadjuvant chemotherapy with the addition of bevacizumab. Tumor biopsies and whole-transcriptome mRNA profiles were obtained at three fixed time points with 66 patients in each arm.

The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes.

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival.

The Sub-Cellular Localization of WRAP53 Has Prognostic Impact in Breast Cancer.

WRAP53 protein controls intracellular trafficking of DNA repair proteins, the telomerase enzyme, and splicing factors. Functional loss of the protein has been linked to carcinogenesis, premature aging and neurodegeneration. The aim of this study was to investigate the prognostic significance of WRAP53 protein expression in breast cancer.

Copy number variations alter methylation and parallel IGF2 overexpression in adrenal tumors.

Overexpression of insulin growth factor 2 (IGF2) is a hallmark of adrenocortical carcinomas and pheochromocytomas. Previous studies investigating the IGF2/H19 locus have mainly focused on a single molecular level such as genomic alterations or altered DNA methylation levels and the causal changes underlying IGF2 overexpression are still not fully established. In the current study, we analyzed 62 tumors of the adrenal gland from patients with Conn's adenoma (CA, n=12), pheochromocytomas (PCC, n=10), adrenocortical benign tumors (ACBT, n=20), and adrenocortical carcinomas (ACC, n=20).

Tumor expression, plasma levels and genetic polymorphisms of the coagulation inhibitor TFPI are associated with clinicopathological parameters and survival in breast cancer, in contrast to the coagulation initiator TF.

Introduction: Hypercoagulability in malignancy increases the risk of thrombosis, but is also involved in cancer progression. Experimental studies suggest that tissue factor (TF) and tissue factor pathway inhibitor (TFPI) are involved in cancer biology as a tumor- promoter and suppressor, respectively, but the clinical significance is less clear. Here, we aimed to investigate the clinical relevance of TF and TFPI genetic and phenotypic diversity in breast cancer.

Integrated analysis reveals microRNA networks coordinately expressed with key proteins in breast cancer.

Background: The role played by microRNAs in the deregulation of protein expression in breast cancer is only partly understood. To gain insight, the combined effect of microRNA and mRNA expression on protein expression was investigated in three independent data sets.

Methods: Protein expression was modeled as a multilinear function of powers of mRNA and microRNA expression.

Increased coagulation activity and genetic polymorphisms in the F5, F10 and EPCR genes are associated with breast cancer: a case-control study.

Background: The procoagulant state in cancer increases the thrombotic risk, but also supports tumor progression. To investigate the molecular mechanisms controlling cancer and hemostasis, we conducted a case-control study of genotypic and phenotypic variables of the tissue factor (TF) pathway of coagulation in breast cancer.

Methods: 366 breast cancer patients and 307 controls were genotyped for SNPs (n = 41) in the F2, F3 (TF), F5, F7, F10, TFPI and EPCR genes, and assayed for plasma coagulation markers (thrombin generation, activated protein C (APC) resistance, D-dimer, antithrombin, protein C, protein S, and TF pathway inhibitor (TFPI)).

Lymphocyte Invasion in IC10/Basal-Like Breast Tumors Is Associated with Wild-Type TP53.

Unlabelled: Lymphocytic infiltration is associated with better prognosis in several epithelial malignancies including breast cancer. The tumor suppressor TP53 is mutated in approximately 30% of breast adenocarcinomas, with varying frequency across molecular subtypes. In this study of 1,420 breast tumors, we tested for interaction between TP53 mutation status and tumor subtype determined by PAM50 and integrative cluster analysis.

A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer.

Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer.

JARID1B is a luminal lineage-driving oncogene in breast cancer.

Recurrent mutations in histone-modifying enzymes imply key roles in tumorigenesis, yet their functional relevance is largely unknown. Here, we show that JARID1B, encoding a histone H3 lysine 4 (H3K4) demethylase, is frequently amplified and overexpressed in luminal breast tumors and a somatic mutation in a basal-like breast cancer results in the gain of unique chromatin binding and luminal expression and splicing patterns. Downregulation of JARID1B in luminal cells induces basal genes expression and growth arrest, which is rescued by TGFβ pathway inhibitors.

TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance.

Purpose: In breast cancer, the TP53 gene is frequently mutated and the mutations have been associated with poor prognosis. The prognostic impact of the different types of TP53 mutations across the different molecular subtypes is still poorly understood. Here, we characterize the spectrum and prognostic significance of TP53 mutations with respect to the PAM50 subtypes and integrative clusters (IC).

Systematic assessment of prognostic gene signatures for breast cancer shows distinct influence of time and ER status.

Background: The aim was to assess and compare prognostic power of nine breast cancer gene signatures (Intrinsic, PAM50, 70-gene, 76-gene, Genomic-Grade-Index, 21-gene-Recurrence-Score, EndoPredict, Wound-Response and Hypoxia) in relation to ER status and follow-up time.

Methods: A gene expression dataset from 947 breast tumors was used to evaluate the signatures for prediction of Distant Metastasis Free Survival (DMFS). A total of 912 patients had available DMFS status.

The 5p12 breast cancer susceptibility locus affects MRPS30 expression in estrogen-receptor positive tumors.

Genome-wide association studies have identified numerous loci linked to breast cancer susceptibility, but the mechanism by which variations at these loci influence susceptibility is usually unknown. Some variants are only associated with particular clinical subtypes of breast cancer. Understanding how and why these variants influence subtype-specific cancer risk contributes to our understanding of cancer etiology.

Triple-negative breast cancer and the need for new therapeutic targets.

Triple-negative breast cancers (TNBCs) are a diverse and heterogeneous group of tumors that by definition lack estrogen and progesterone receptors and amplification of the HER2 gene. The majority of the tumors classified as TNBCs are highly malignant, and only a subgroup responds to conventional chemotherapy with a favorable prognosis. Results from decades of research have identified important molecular characteristics that can subdivide this group of breast cancers further.

Improving breast cancer survival analysis through competition-based multidimensional modeling.

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease.

Systematic analysis of challenge-driven improvements in molecular prognostic models for breast cancer.

Although molecular prognostics in breast cancer are among the most successful examples of translating genomic analysis to clinical applications, optimal approaches to breast cancer clinical risk prediction remain controversial. The Sage Bionetworks-DREAM Breast Cancer Prognosis Challenge (BCC) is a crowdsourced research study for breast cancer prognostic modeling using genome-scale data. The BCC provided a community of data analysts with a common platform for data access and blinded evaluation of model accuracy in predicting breast cancer survival on the basis of gene expression data, copy number data, and clinical covariates.

Copynumber: Efficient algorithms for single- and multi-track copy number segmentation.

Background: Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number.

The HER2 amplicon includes several genes required for the growth and survival of HER2 positive breast cancer cells.

About 20% of breast cancers are characterized by amplification and overexpression of the HER2 oncogene. Although significant progress has been achieved for treating such patients with HER2 inhibitor trastuzumab, more than half of the patients respond poorly or become resistant to the treatment. Since the HER2 amplicon at 17q12 contains multiple genes, we have systematically explored the role of the HER2 co-amplified genes in breast cancer cell growth and their relation to trastuzumab resistance.

Analyzing cancer samples with SNP arrays.

Single nucleotide polymorphism (SNP) arrays are powerful tools to delineate genomic aberrations in cancer genomes. However, the analysis of these SNP array data of cancer samples is complicated by three phenomena: (a) aneuploidy: due to massive aberrations, the total DNA content of a cancer cell can differ significantly from its normal two copies; (b) nonaberrant cell admixture: samples from solid tumors do not exclusively contain aberrant tumor cells, but always contain some portion of nonaberrant cells; (c) intratumor heterogeneity: different cells in the tumor sample may have different aberrations. We describe here how these phenomena impact the SNP array profile, and how these can be accounted for in the analysis.

The breast cancer genome--a key for better oncology.

Molecular classification has added important knowledge to breast cancer biology, but has yet to be implemented as a clinical standard. Full sequencing of breast cancer genomes could potentially refine classification and give a more complete picture of the mutational profile of cancer and thus aid therapy decisions. Future treatment guidelines must be based on the knowledge derived from histopathological sub-classification of tumors, but with added information from genomic signatures when properly clinically validated.

Ischemia caused by time to freezing induces systematic microRNA and mRNA responses in cancer tissue.

Time to freezing tumor tissue for RNA expression analysis will always vary to some extent. To evaluate the effect of ischemia time, tumor tissue from ten breast cancer patients was collected and aliquots of tissue were snap frozen at different time points after surgery (0, 0.5, 1, 3 and 6 h).