Profiling native pulmonary basement membrane stiffness using atomic force microscopy.

Mammalian cells sense and react to the mechanics of their immediate microenvironment. Therefore, the characterization of the biomechanical properties of tissues with high spatial resolution provides valuable insights into a broad variety of developmental, homeostatic and pathological processes within living organisms. The biomechanical properties of the basement membrane (BM), an extracellular matrix (ECM) substructure measuring only ∼100-400 nm across, are, among other things, pivotal to tumor progression and metastasis formation. Although the precise assignment of the Young's modulus E of such a thin ECM substructure especially in between two cell layers is still challenging, biomechanical data of the BM can provide information of eminent diagnostic potential. Here we present a detailed protocol to quantify the elastic modulus of the BM in murine and human lung tissue, which is one of the major organs prone to metastasis. This protocol describes a streamlined workflow to determine the Young's modulus E of the BM between the endothelial and epithelial cell layers shaping the alveolar wall in lung tissues using atomic force microscopy (AFM). Our step-by-step protocol provides instructions for murine and human lung tissue extraction, inflation of these tissues with cryogenic cutting medium, freezing and cryosectioning of the tissue samples, and AFM force-map recording. In addition, it guides the reader through a semi-automatic data analysis procedure to identify the pulmonary BM and extract its Young's modulus E using an in-house tailored user-friendly AFM data analysis software, the Center for Applied Tissue Engineering and Regenerative Medicine processing toolbox, which enables automatic loading of the recorded force maps, conversion of the force versus piezo-extension curves to force versus indentation curves, calculation of Young's moduli and generation of Young's modulus maps, where the pulmonary BM can be identified using a semi-automatic spatial filtering tool. The entire protocol takes 1-2 d.

Basement membrane stiffness determines metastases formation.

The basement membrane (BM) is a special type of extracellular matrix and presents the major barrier cancer cells have to overcome multiple times to form metastases. Here we show that BM stiffness is a major determinant of metastases formation in several tissues and identify netrin-4 (Net4) as a key regulator of BM stiffness. Mechanistically, our biophysical and functional analyses in combination with mathematical simulations show that Net4 softens the mechanical properties of native BMs by opening laminin node complexes, decreasing cancer cell potential to transmigrate this barrier despite creating bigger pores. Our results therefore reveal that BM stiffness is dominant over pore size, and that the mechanical properties of 'normal' BMs determine metastases formation and patient survival independent of cancer-mediated alterations. Thus, identifying individual Net4 protein levels within native BMs in major metastatic organs may have the potential to define patient survival even before tumour formation. The ratio of Net4 to laminin molecules determines BM stiffness, such that the more Net4, the softer the BM, thereby decreasing cancer cell invasion activity.

Retraction Note: Lysyl oxidase is essential for hypoxia-induced metastasis.

A Retraction to this paper has been published and can be accessed via a link at the top of the paper.

Tumor endothelial marker 8 promotes cancer progression and metastasis.

Every year more than 8 million people suffer from cancer-related deaths worldwide [1]. Metastasis, the spread of cancer to distant sites, accounts for 90% of these deaths. A promising target for blocking tumor progression, without causing severe side effects [2], is Tumor Endothelial Marker 8 (TEM8), an integrin-like cell surface protein expressed predominantly in the tumor endothelium and in cancer cells [3, 4]. Here, we have investigated the role of TEM8 in cancer progression, angiogenesis and metastasis in invasive breast cancer, and validated the main findings and important results in colorectal cancer. We show that the loss of TEM8 in cancer cells results in inhibition of cancer progression, reduction in tumor angiogenesis and reduced metastatic burden in breast cancer mouse models. Furthermore, we show that TEM8 regulates cancer progression by affecting the expression levels of cell cycle-related genes. Taken together, our findings may have broad clinical and therapeutic potential for breast and colorectal primary tumor and metastasis treatment by targeting TEM8.

Head and neck cancer subtypes with biological and clinical relevance: Meta-analysis of gene-expression data.

Head and neck squamous cell carcinoma (HNSCC) is a disease with heterogeneous clinical behavior and response to therapies. Despite the introduction of multimodality treatment, 40-50% of patients with advanced disease recur. Therefore, there is an urgent need to improve the classification beyond the current parameters in clinical use to better stratify patients and the therapeutic approaches. Following a meta-analysis approach we built a large training set to whom we applied a Disease-Specific Genomic Analysis (DSGA) to identify the disease component embedded into the tumor data. Eleven independent microarray datasets were used as validation sets. Six different HNSCC subtypes that summarize the aberrant alterations occurring during tumor progression were identified. Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal. Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes. The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes. To conclude, we report a robust molecularly defined subtype classification in HNSCC that can improve patient selection and pave the way to the development of appropriate therapeutic strategies.

Clinical recovery from surgery correlates with single-cell immune signatures.

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.

The apoptosis repressor with a CARD domain (ARC) gene is a direct hypoxia-inducible factor 1 target gene and promotes survival and proliferation of VHL-deficient renal cancer cells.

The induction of hypoxia-inducible factors (HIFs) is essential for the adaptation of tumor cells to a low-oxygen environment. We found that the expression of the apoptosis inhibitor ARC (apoptosis repressor with a CARD domain) was induced by hypoxia in a variety of cancer cell types, and its induction is primarily HIF1 dependent. Chromatin immunoprecipitation (ChIP) and reporter assays also indicate that the ARC gene is regulated by direct binding of HIF1 to a hypoxia response element (HRE) located at bp -190 upstream of the transcription start site. HIFs play an essential role in the pathogenesis of renal cell carcinoma (RCC) under normoxic conditions, through the loss of the Von Hippel-Lindau gene (VHL). Accordingly, our results show that ARC is not expressed in normal renal tissue but is highly expressed in 65% of RCC tumors, which also express high levels of carbonic anhydrase IX (CAIX), a HIF1-dependent protein. Compared to controls, ARC-deficient RCCs exhibited decreased colony formation and increased apoptosis in vitro. In addition, loss of ARC resulted in a dramatic reduction of RCC tumor growth in SCID mice in vivo. Thus, HIF-mediated increased expression of ARC in RCC can explain how loss of VHL can promote survival early in tumor formation.

LOXL2 induces aberrant acinar morphogenesis via ErbB2 signaling.

INTRODUCTION: Lysyl oxidase-like 2 (LOXL2) is a matrix-remodeling enzyme that has been shown to play a key role in invasion and metastasis of breast carcinoma cells. However, very little is known about its role in normal tissue homeostasis. Here, we investigated the effects of LOXL2 expression in normal mammary epithelial cells to gain insight into how LOXL2 mediates cancer progression. METHODS: LOXL2 was expressed in MCF10A normal human mammary epithelial cells. The 3D acinar morphogenesis of these cells was assessed, as well as the ability of the cells to form branching structures on extracellular matrix (ECM)-coated surfaces. Transwell-invasion assays were used to assess the invasive properties of the cells. Clinically relevant inhibitors of ErbB2, lapatinib and Herceptin (traztuzumab), were used to investigate the role of ErbB2 signaling in this model. A retrospective study on a previously published breast cancer patient dataset was carried out by using Disease Specific Genomic Analysis (DSGA) to investigate the correlation of LOXL2 mRNA expression level with metastasis and survival of ErbB2-positive breast cancer patients. RESULTS: Fluorescence staining of the acini revealed increased proliferation, decreased apoptosis, and disrupted polarity, leading to abnormal lumen formation in response to LOXL2 expression in MCF10A cells. When plated onto ECM, the LOXL2-expressing cells formed branching structures and displayed increased invasion. We noted that LOXL2 induced ErbB2 activation through reactive oxygen species (ROS) production, and ErbB2 inhibition by using Herceptin or lapatinib abrogated the effects of LOXL2 on MCF10A cells. Finally, we found LOXL2 expression to be correlated with decreased overall survival and metastasis-free survival in breast cancer patients with ErbB2-positive tumors. CONCLUSIONS: These findings suggest that LOXL2 expression in normal epithelial cells can induce abnormal changes that resemble oncogenic transformation and cancer progression, and that these effects are driven by LOXL2-mediated activation of ErbB2. LOXL2 may also be a beneficial marker for breast cancer patients that could benefit most from anti-ErbB2 therapy.

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.

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.

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.

Characterization of molecular subtypes of Korean breast cancer: an ethnically and clinically distinct population.

We aimed to investigate the molecular characteristics of Korean breast cancer. A cDNA microarray study (>42k clones) was performed on 69 breast cancers and three normal breast tissues. The subjects had a high percentage of HER-2 expression, hormone receptor negativity, and young onset. Molecular subtypes according to gene expression profiles were determined and their correlations to the clinicopathologic characteristics and patients outcome were analyzed. The tumors were subdivided into luminal-, normal breast-like, ERBB2+, and basal-like subtypes according to the correlations to the previously described intrinsic genes and five centroids. Only a few tumors were highly correlated to the luminal B and normal-like centroids. The high grade tumors with high p53 and Ki-67 were found more commonly in non-luminal tumors. Distant recurrence-free survival was worse in ERBB2+ and basal-like subgroups than luminal tumors. In an unsupervised clustering with 864 genes, many interesting gene clusters were observed, some of which had not been previously described. Although the Korean breast cancers showed generally similar molecular phenotypes as Western studies, some distinct gene expression patterns and their association to clinical outcomes were observed.

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 (> or =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.

Disease-specific genomic analysis: identifying the signature of pathologic biology.

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.

Discovery and validation of breast cancer subtypes.

BACKGROUND: Previous 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+. RESULTS: Based 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. CONCLUSION: As 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.

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.