Monica Nicolau

Lysyl oxidase is essential for hypoxia-induced metastasis

Metastasis is a multistep process responsible for most cancer deaths, and it can be influenced by both the immediate microenvironment (cell–cell or cell–matrix interactions) and the extended tumour microenvironment (for example vascularization). Hypoxia (low oxygen) is clinically associated with metastasis and poor patient outcome, although the underlying processes remain unclear. Microarray studies have shown the expression of lysyl oxidase (LOX) to be elevated in hypoxic human tumour cells. Paradoxically, LOX expression is associated with both tumour suppression and tumour progression, and its role in tumorigenesis seems dependent on cellular location, cell type and transformation status. Here we show that LOX expression is regulated by hypoxia-inducible factor (HIF) and is associated with hypoxia in human breast and head and neck tumours. Patients with high LOX-expressing tumours have poor distant metastasis-free and overall survivals. Inhibition of LOX eliminates metastasis in mice with orthotopically grown breast cancer tumours. Mechanistically, secreted LOX is responsible for the invasive properties of hypoxic human cancer cells through focal adhesion kinase activity and cell to matrix adhesion. Furthermore, LOX may be required to create a niche permissive for metastatic growth. Our findings indicate that LOX is essential for hypoxia-induced metastasis and is a good therapeutic target for preventing and treating metastases.

A streamlined platform for high-content functional proteomics of primary human specimens

Achieving information content of satisfactory breadth and depth remains a formidable challenge for proteomics. This problem is particularly relevant to the study of primary human specimens, such as tumor biopsies, which are heterogeneous and of finite quantity. Here we present a functional proteomics strategy that unites the activity-based protein profiling and multidimensional protein identification technologies (ABPP-MudPIT) for the streamlined analysis of human samples. This convergent platform involves a rapid initial phase, in which enzyme activity signatures are generated for functional classification of samples, followed by in-depth analysis of representative members from each class. Using this two-tiered approach, we identified more than 50 enzyme activities in human breast tumors, nearly a third of which represent previously uncharacterized proteins. Comparison with cDNA microarrays revealed enzymes whose activity, but not mRNA expression, depicted tumor class, underscoring the power of ABPP-MudPIT for the discovery of new markers of human disease that may evade detection by other molecular profiling methods.

Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival

High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER+) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER+ breast cancers. We denote the group as c-MYB+ breast cancer.

Clinical recovery from surgery correlates with single-cell immune signatures

Single-cell mass cytometry revealed immune correlates of patient-associated variability in surgical recovery. Signaling Surgical Recovery The speed and ease of recovery after surgery differ for every patient, and determining the mechanisms that drive recovery could lead to patient-specific recovery protocols. Gaudilliere et al. used mass cytometry to characterize postsurgical immunological insult at a single-cell level and found a surgical immune signature that correlated with clinical recovery across patients. Specifically, cell signaling responses, but not cell frequency, were linked to recovery. Moreover, the correlated signaling responses occurred most notably in CD14+ monocytes, suggesting that these cells may play a predominant role in surgical recovery. The consistency of this signature across patients suggests a tightly regulated immune response to surgical trauma, which, if validated, may form the basis of a diagnostic guideline for personalized postsurgical care. Delayed recovery from surgery causes personal suffering and substantial societal and economic costs. Whether immune mechanisms determine recovery after surgical trauma remains ill-defined. Single-cell mass cytometry was applied to serial whole-blood samples from 32 patients undergoing hip replacement to comprehensively characterize the phenotypic and functional immune response to surgical trauma. The simultaneous analysis of 14,000 phosphorylation events in precisely phenotyped immune cell subsets revealed uniform signaling responses among patients, demarcating a surgical immune signature. When regressed against clinical parameters of surgical recovery, including functional impairment and pain, strong correlations were found with STAT3 (signal transducer and activator of transcription), CREB (adenosine 3′,5′-monophosphate response element–binding protein), and NF-κB (nuclear factor κB) signaling responses in subsets of CD14+ monocytes (R = 0.7 to 0.8, false discovery rate <0.01). These sentinel results demonstrate the capacity of mass cytometry to survey the human immune system in a relevant clinical context. The mechanistically derived immune correlates point to diagnostic signatures, and potential therapeutic targets, that could postoperatively improve patient recovery.

LOXL2-mediated matrix remodeling in metastasis and mammary gland involution

More than 90% of cancer patient mortality is attributed to metastasis. In this study, we investigated a role for the lysyl oxidase-related enzyme lysyl oxidase-like 2 (LOXL2) in breast cancer metastasis, in both patient samples and in vivo models. Analysis of a published microarray data set revealed that LOXL2 expression is correlated with metastasis and decreased survival in patients with aggressive breast cancer. In immunocompetent or immunocompromised orthotopic and transgenic breast cancer models we showed that genetic, chemical or antibody-mediated inhibition of LOXL2 resulted in decreased metastasis. Mechanistic investigations revealed that LOXL2 promotes invasion by regulating the expression and activity of the extracellular proteins tissue inhibitor of metalloproteinase-1 (TIMP1) and matrix metalloproteinase-9 (MMP9). We found that LOXL2, TIMP1, and MMP9 are coexpressed during mammary gland involution, suggesting they function together in glandular remodeling after weaning. Finally, we found that LOXL2 is highly expressed in the basal/myoepithelial mammary cell lineage, like many other genes that are upregulated in basal-like breast cancers. Our findings highlight the importance of LOXL2 in breast cancer progression and support the development of anti-LOXL2 therapeutics for the treatment of metastatic breast cancer.

Discovery and validation of breast cancer subtypes

BackgroundPrevious studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+.ResultsBased upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability.ConclusionAs a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.

DNA copy number alterations and expression of relevant genes in triple-negative breast cancer

Triple‐negative breast cancer (TNBC) is defined by a lack of expression of estrogen, progesterone, and HER2 receptors, and genetically most of them fall into the basal subgroup of breast cancer. The important issue of TNBC is poorer clinical outcome and absence of effective targeted therapy. In this study, we sought to identify DNA copy number alterations and expression of relevant genes characteristic of TNBC to discover potential therapeutic targets. Frozen tissues from 114 breast cancers were analyzed using high‐resolution array comparative genomic hybridization. The classification into subtype was determined by estrogen and progesterone receptor expression, and by the presence or absence of gain on the ERBB2 containing clone. The ACE algorithm was used for calling gain and loss of clones. Twenty‐eight cases (25%) were classified as TNBC. Recurrent gains (≥25%) unique to TNBC were 9p24‐p21, 10p15‐p13, 12p13, 13q31‐q34, 18q12, 18q21‐q23, and 21q22. Two published gene expression array data sets comparing basal subtype versus other subtype breast cancers were used for searching candidate genes. Of the genes upregulated in the basal subtype, 45 of 686 genes in one data set and 59 of 1,428 in the second data set were found to be located in the gained regions. Of these candidate genes, gain of NFIB (9p24.1) was specific for TNBC in a validation set by real‐time PCR. In conclusion, we have identified recurrently gained regions characteristic of TNBC, and found that NFIB copy number and expression is increased in TNBC across the data sets. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045‐2257/suppmat.

Deficiency in Mammalian Histone H2B Ubiquitin Ligase Bre1 (Rnf20/Rnf40) Leads to Replication Stress and Chromosomal Instability

Mammalian Bre1 complexes (BRE1A/B (RNF20/40) in humans and Bre1a/b (Rnf20/40) in mice) function similarly to their yeast homolog Bre1 as ubiquitin ligases in monoubiquitination of histone H2B. This ubiquitination facilitates methylation of histone H3 at K4 and K79, and accounts for the roles of Bre1 and its homologs in transcriptional regulation. Recent studies by others suggested that Bre1 acts as a tumor suppressor, augmenting expression of select tumor suppressor genes and suppressing select oncogenes. In this study, we present an additional mechanism of tumor suppression by Bre1 through maintenance of genomic stability. We track the evolution of genomic instability in Bre1-deficient cells from replication-associated double-strand breaks (DSB) to specific genomic rearrangements that explain a rapid increase in DNA content and trigger breakage-fusion-bridge cycles. We show that aberrant RNA-DNA structures (R-loops) constitute a significant source of DSBs in Bre1-deficient cells. Combined with a previously reported defect in homologous recombination, generation of R-loops is a likely initiator of replication stress and genomic instability in Bre1-deficient cells. We propose that genomic instability triggered by Bre1 deficiency may be an important early step that precedes acquisition of an invasive phenotype, as we find decreased levels of BRE1A/B and dimethylated H3K79 in testicular seminoma and in the premalignant lesion in situ carcinoma.

Disease-specific genomic analysis

MOTIVATION Genomic high-throughput technology generates massive data, providing opportunities to understand countless facets of the functioning genome. It also raises profound issues in identifying data relevant to the biology being studied. RESULTS We introduce a method for the analysis of pathologic biology that unravels the disease characteristics of high dimensional data. The method, disease-specific genomic analysis (DSGA), is intended to precede standard techniques like clustering or class prediction, and enhance their performance and ability to detect disease. DSGA measures the extent to which the disease deviates from a continuous range of normal phenotypes, and isolates the aberrant component of data. In several microarray cancer datasets, we show that DSGA outperforms standard methods. We then use DSGA to highlight a novel subdivision of an important class of genes in breast cancer, the estrogen receptor (ER) cluster. We also identify new markers distinguishing ductal and lobular breast cancers. Although our examples focus on microarrays, DSGA generalizes to any high dimensional genomic/proteomic data.

Oxidative stress pathways highlighted in tumor cell immortalization : association with breast cancer outcome

An improved understanding of cell immortalization and its manifestation in clinical tumors could facilitate novel therapeutic approaches. However, only rare tumor cells, which maintain telomerase expression in vitro, immortalize spontaneously. By expression-profiling analyses of limited-life primary breast tumor cultures pre- and post-hTERT transduction, and spontaneously immortalized breast cancer cell lines, we identified a common signature characteristic of tumor cell immortalization. A predominant feature of this immortalization signature (ImmSig) was the significant overexpression of oxidoreductase genes. In contrast to epithelial cells derived from low histologic grade primary tumors, which required hTERT transduction for the acquisition of ImmSig, spontaneously immortalizing high-grade tumor cultures displayed similar molecular changes independent of exogenous hTERT. Silencing the hTERT gene reversed ImmSig expression, increased cellular reactive oxygen species levels, altered mitochondrial membrane potential and induced apoptotic and proliferation changes in immortalized cells. In clinical breast cancer samples, cell-proliferation-pathway genes were significantly associated with ImmSig. In these cases, ImmSig expression itself was inversely correlated with patient survival (P=0), and was particularly relevant to the outcome of estrogen receptor-positive tumors. Our data support the notion that ImmSig assists in surmounting normal barriers related to oxidative and replicative stress response. Targeting a subset of aggressive breast cancers by reversing ImmSig components could be a practical therapeutic strategy.