Antonella Chiechi

Excess TGF-β mediates muscle weakness associated with bone metastases in mice

Cancer-associated muscle weakness is a poorly understood phenomenon, and there is no effective treatment. Here we find that seven different mouse models of human osteolytic bone metastases—representing breast, lung and prostate cancers, as well as multiple myeloma—exhibited impaired muscle function, implicating a role for the tumor-bone microenvironment in cancer-associated muscle weakness. We found that transforming growth factor (TGF)-β, released from the bone surface as a result of metastasis-induced bone destruction, upregulated NADPH oxidase 4 (Nox4), resulting in elevated oxidization of skeletal muscle proteins, including the ryanodine receptor and calcium (Ca2+) release channel (RyR1). The oxidized RyR1 channels leaked Ca2+, resulting in lower intracellular signaling, which is required for proper muscle contraction. We found that inhibiting RyR1 leakage, TGF-β signaling, TGF-β release from bone or Nox4 activity improved muscle function in mice with MDA-MB-231 bone metastases. Humans with breast- or lung cancer–associated bone metastases also had oxidized skeletal muscle RyR1 that is not seen in normal muscle. Similarly, skeletal muscle weakness, increased Nox4 binding to RyR1 and oxidation of RyR1 were present in a mouse model of Camurati-Engelmann disease, a nonmalignant metabolic bone disorder associated with increased TGF-β activity. Thus, pathological TGF-β release from bone contributes to muscle weakness by decreasing Ca2+-induced muscle force production.

Retinal pigment epithelium (RPE) exosomes contain signaling phosphoproteins affected by oxidative stress

Age-related macular degeneration (AMD) is a leading cause of vision loss and blindness among the elderly population in the industrialized world. One of the typical features of this pathology is the gradual death of retinal pigment epithelial (RPE) cells, which are essential for maintaining photoreceptor functions and survival. The etiology is multifactorial, and oxidative stress is clearly one of the key factors involved in disease pathogenesis (Plafker, Adv. Exp. Med. Biol. 664 (2010) 447-56; Qin, Drug Dev. Res. 68 (2007) 213-225). Recent work has revealed the presence of phosphorylated signaling proteins in the vitreous humour of patients affected by AMD or other retinal diseases. While the location of these signaling proteins is typically the cell membrane or intracellular compartments, vitreous samples were proven to be cell-free (Davuluri et al., Arch. Ophthalmol. 127 (2009) 613-21). To gain a better understanding of how these proteins can be shed into the vitreous, we used reverse phase protein arrays (RPMA) to analyze the protein and phosphoprotein content of exosomes shed by cultured ARPE-19 cells under oxidative stress conditions. Seventy two proteins were shown to be released by ARPE-19 cells and compartmentalized within exosomes. Forty one of them were selectively detected in their post-translationally modified form (i.e., phosphorylated or cleaved) for the first time in exosomes. Sets of these proteins were linked together reflecting activation of pathway units within exosomes. A subset of (phospho)proteins were altered in exosomes secreted by ARPE-19 cells subjected to oxidative stress, compared to that secreted by control/non stressed cells. Stress-altered exosome proteins were found to be involved in pathways regulating apoptosis/survival (i.e, Bak, Smac/Diablo, PDK1 (S241), Akt (T308), Src (Y416), Elk1 (S383), ERK 1/2 (T202/Y204)) and cell metabolism (i.e., AMPKα1 (S485), acetyl-CoA carboxylase (S79), LDHA). Exosomes may thus represent the conduit through which membrane and intracellular signaling proteins are released into the vitreous. Changes in their (phospho)protein content upon stress conditions suggest their possible role in mediating cell-cell signaling during physio-pathological events; furthermore, exosomes may represent a potential source of biomarkers.

Identification of Potential Biomarkers for Giant Cell Tumor of Bone Using Comparative Proteomics Analysis

Giant cell tumor of bone can be locally aggressive and occasionally can metastasize in the lungs. To identify new markers predictive of aggressive behavior, we analyzed five patients who developed lung metastasis and five who remained disease free for a minimum of 5 years. Using two-dimensional electrophoresis, we detected 28 differentially expressed spots. Fourteen spots were identified using mass spectrometry, including seven up-regulated and seven down-regulated in metastatic samples and classified according to functional categories. We then selected five proteins involved in cell cycle or apoptosis. Thioredoxin peroxidase, allograft inflammatory factor 1, and ubiquitin E2N had more than threefold up-regulation; glutathione peroxidase 1 had 1.9-fold up-regulation; and heat shock protein 27 showed down-regulation in metastatic samples with a very low P value. After validation and analysis of protein levels, evaluation of clinical impact was assessed in a much wider cohort of primary archival specimens. Immunodetection showed a higher frequency of thioredoxin peroxidase, allograft inflammatory factor 1, ubiquitin E2N, and glutathione peroxidase 1 overexpression in primary tumors that developed into lung metastases or that locally relapsed than in the disease-free group, with variable stain intensity and distribution. Kaplan-Meier analysis showed that high expression of glutathione peroxidase 1 was strongly related to local recurrence and metastasis, suggesting that its up-regulation may identify a subset of high-risk patients with giant cell tumor prone to receive diverse clinical management.

NG2 expression predicts the metastasis formation in soft-tissue sarcoma patients

Enhanced expression levels of NG2 proteoglycan in presurgical original lesions of soft‐tissue sarcoma (STS) patients defines with 55% probability the immediate (i.e., within 12 months postsurgery) risk in these individuals to develop postsurgical secondary lesions, independently of any other clinical trait. It, therefore, provides a molecular factor that alone prospects a particularly unfavorable clinical outcome in such patients. Evaluation of the timing of metastasis formation in patients with high and low levels of NG2 in their primitive lesions further stratified the patients in subsets with diverse lag phases in the occurrence of metastatic disease. In our cohort of high‐grade STS cases, transcription of NG2 also showed a 81‐fold amplification in metastatic lesions, when compared to primitive ones, and this gene overexpression was accompanied by an abundant but nonuniform in situ expression of its product. In a similar manner as seen in primitive lesions, patients with higher levels of metastatic NG2 encountered a significantly more dismal clinical course. Multivariate analysis asserted that in these individuals upregulation of NG2 represented an absolute independent prognostic parameter. Therefore, minimally invasive assessment of the transcription levels of the NG2 gene represents a parameter capable of predicting the arising of metastatic disease within a definite postsurgery time interval, and affords in adjunct in the definition of life expectance in STS patients.

Improved data normalization methods for reverse phase protein microarray analysis of complex biological samples

Reverse phase protein microarrays (RPMA) are designed for quantitative, multiplexed analysis of proteins, and their posttranslational modified forms, from a limited amount of sample. To correct for sample to sample variability due to the number of cells in each lysate and the presence of extracellular proteins or red blood cells, a normalization method is required that is independent of these potentially confounding parameters. We adopted a gene microarray algorithm for use with RPMA to optimize the proteomic data normalization process and developed a systematic approach to RPMA processing and analysis, tailored to the study set. Our approach capitalizes on the gene microarray algorithms geNorm and NormFinder to identify the normalization parameter with the lowest variability across a proteomic sample set. Seven analytes (ssDNA, glyceraldehyde 3-phosphate dehydrogenase, α/β-tubulin, mitochondrial ribosomal protein L11, ribosomal protein L13a, β-actin, and total protein) were compared across sample sets including cell lines, tissues subjected to laser capture microdissection, and blood-contaminated tissues. We examined normalization parameters to correct for red blood cell content. We show that single-stranded DNA (ssDNA) is proportional to total non-red blood cell content and is a suitable RPMA normalization parameter. Simple modifications to RPMA processing allow flexibility in using ssDNA-or protein-based normalization molecules.

Role of TGF-β in breast cancer bone metastases

Breast cancer is the most prevalent cancer among females worldwide leading to approximately 350,000 deaths each year. It has long been known that cancers preferentially metastasize to particular organs, and bone metastases occur in ~70% of patients with advanced breast cancer. Breast cancer bone metastases are predominantly osteolytic and accompanied by increased fracture risk, pain, nerve compression and hypercalcemia, causing severe morbidity. In the bone matrix, transforming growth factor-β (TGF-β) is one of the most abundant growth factors, which is released in active form upon tumor-induced osteoclastic bone resorption. TGF-β, in turn, stimulates bone metastatic tumor cells to secrete factors that further drive osteolytic bone destruction adjacent to the tumor. Thus, TGF-β is a crucial factor responsible for driving the feed-forward vicious cycle of cancer growth in bone. Moreover, TGF-β activates epithelial-to-mesenchymal transition, increases tumor cell invasiveness and angiogenesis and induces immunosuppression. Blocking the TGF-β signaling pathway to interrupt this vicious cycle between breast cancer and bone offers a promising target for therapeutic intervention to decrease skeletal metastasis. This review will describe the role of TGF-β in breast cancer and bone metastasis, and pre-clinical and clinical data will be evaluated for the potential use of TGF-β inhibitors in clinical practice to treat breast cancer bone metastases.

Elevated TNFR1 and Serotonin in Bone Metastasis Are Correlated with Poor Survival following Bone Metastasis Diagnosis for Both Carcinoma and Sarcoma Primary Tumors

Purpose: There is an urgent need for therapies that will reduce the mortality of patients with bone metastasis. In this study, we profiled the protein signal pathway networks of the human bone metastasis microenvironment. The goal was to identify sets of interacting proteins that correlate with survival time following the first diagnosis of bone metastasis. Experimental Design: Using Reverse Phase Protein Microarray technology, we measured the expression of 88 end points in the bone microenvironment of 159 bone metastasis tissue samples derived from patients with primary carcinomas and sarcomas. Results: Metastases originating from different primary tumors showed similar levels of cell signaling across tissue types for the majority of proteins analyzed, suggesting that the bone microenvironment strongly influences the metastatic tumor signaling profiles. In a training set (72 samples), TNF receptor 1, alone (P = 0.0013) or combined with serotonin (P = 0.0004), TNFα (P = 0.0214), and RANK (P = 0.0226), was associated with poor survival, regardless of the primary tumor of origin. Results were confirmed by (i) analysis of an independent validation set (71 samples) and (ii) independent bioinformatic analysis using a support vector machine learning model. Spearman rho analysis revealed a highly significant number of interactions intersecting with ERα S118, serotonin, TNFα, RANKL, and matrix metalloproteinase in the bone metastasis signaling network, regardless of the primary tumor. The interaction network pattern was significantly different in the short versus long survivors. Conclusions: TNF receptor 1 and neuroendocrine-regulated protein signal pathways seem to play an important role in bone metastasis and may constitute a novel drug-targetable mechanism of seed-soil cross talk in bone metastasis. Clin Cancer Res; 19(9); 2473–85. ©2013 AACR.

Mapping protein signal pathway interaction in sarcoma bone metastasis: linkage between rank, metalloproteinases turnover and growth factor signaling pathways.

We applied reverse phase protein microarrays technology to map signal pathway interactions in a discovery set of 34 soft tissue sarcoma (STS) bone metastases compared to healthy bone. Proteins associated with matrix remodeling (MMP), adhesion (FAK Y576/577, Syndecan-1), and growth/survival (IGF1R Y1135/1136, PI3K, EGFR) were elevated in metastasis compared to normal bone. Linkage between Syndecan-1, FAK Y576/577, Shc Y317, and EGFR, IGF Y1135/1136, PI3K/AKT was a prominent feature of STS bone metastasis. Elevated linkage between RANKL and 4EBP1 T37/46, EGFR, IGF1R Y1135/1136, Src Y41, Shc Y317, PI3Kp110γ was associated with short survival. Finally, we tested the hypothesis that signal pathway proteins augmented in the STS bone metastasis may provide clues to understand the subset of primary STS that metastasize. The most representative molecules identified in the discovery set were validated on an independent series of 82 primary STS by immunohistochemistry applied to a tissue microarray. The goal was to correlate the molecular profile in the primary tumors with a higher likelihood of metastasis. Elevation of activated kinase substrate endpoints IRS1 S612, 4EBP1 T37/46, FAK Y576/577 and loss of Fibronectin, were associated with a higher likelihood of metastases. These data indicate that the linkage between matrix remodeling, adhesion, and growth signaling may drive STS metastasis and can be the basis for prognostic and therapeutic strategies.

Proteomic Analysis Reveals Autophagy as Pro-Survival Pathway Elicited by Long-Term Exposure with 5-Azacitidine in High-Risk Myelodysplasia

Azacytidine (5-AZA) is the standard first-choice treatment for high-risk myelodysplasia (MDS) patients. However, the clinical outcome for those patients who interrupt treatment or whose disease failed to respond is very poor. In order to identify the cellular pathways that are modified by long-term exposure to 5-AZA, we evaluated key proteins associated with the autophagy pathway by reverse-phase microarray (RPPA). Comparing bone marrow mononucleated cells (BMMCs) obtained from 20 newly-diagnosed patients and after four 5-AZA cycles we found an increased autophagy signaling. We then evaluated ex-vivo the effect of the combination of 5-AZA with autophagy inhibitors chloroquine (CQ) and leupeptin. Since 5-AZA and CQ showed synergism due to an increase of basal autophagy after 5-AZA exposure, we adopted a sequential treatment treating BMMCs with 5 μM 5-AZA for 72 h followed by 10 μM CQ for 24 h and found increased apoptosis, associated to a reduction of G2M phase and increase in G0-G1 phase. Long-term exposure to 5-AZA induced the reduction of the autophagic marker SQSTM1/p62, reversible by CQ or leupeptin exposure. In conclusion, we identified autophagy as a compensatory pathway occurring in MDS-BM after long-term exposure to 5-AZA and we provided evidences that a sequential treatment of 5-AZA followed by CQ could improve 5-AZA efficacy, providing novel insight for tailored therapy in MDS patients progressing after 5-AZA therapy.

Normalization of Reverse Phase Protein Microarray Data: Choosing the Best Normalization Analyte

Reverse phase protein microarray (RPMA) are a relatively recent but widely used approach to measure a large number of proteins, in their original and posttranslational modified forms, in a small clinical sample. Data normalization is fundamental for this technology, to correct for the sample-to-sample variability in the many possible confounding factors: extracellular proteins, red blood cells, different number of cells in the sample. To address this need, we adopted gene microarray algorithms to tailor the RPMA processing and analysis to the specific study set. Using geNorm and NormFinder algorithms, we screened seven normalization analytes (ssDNA, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), α/β-tubulin, mitochondrial ribosomal protein L11 (MRPL11), ribosomal protein L13a (RPL13a), β-actin, and total protein) across different sample sets, including cell lines, blood contaminated tissues, and tissues subjected to laser capture microdissection (LCM), to identify the analyte with the lowest variability. Specific normalization analytes were found to be advantageous for different classes of samples, with ssDNA being the optimal analyte to normalize blood contaminated samples.