Identification of stromal proteins overexpressed in nodular sclerosis Hodgkin lymphoma

Hodgkin lymphoma (HL) represents a category of lymphoid neoplasms with unique features, notably the usual scarcity of tumour cells in involved tissues. The most common subtype of classical HL, nodular sclerosis HL, characteristically comprises abundant fibrous tissue stroma. Little information is available about the protein composition of the stromal environment from HL. Moreover, the identification of valid protein targets, specifically and abundantly expressed in HL, would be of utmost importance for targeted therapies and imaging, yet the biomarkers must necessarily be accessible from the bloodstream. To characterize HL stroma and to identify potentially accessible proteins, we used a chemical proteomic approach, consisting in the labelling of accessible proteins and their subsequent purification and identification by mass spectrometry. We performed an analysis of potentially accessible proteins in lymph node biopsies from HL and reactive lymphoid tissues, and in total, more than 1400 proteins were identified in 7 samples. We have identified several extracellular matrix proteins overexpressed in HL, such as versican, fibulin-1, periostin, and other proteins such as S100-A8. These proteins were validated by immunohistochemistry on a larger series of biopsy samples, and bear the potential to become targets for antibody-based anti-cancer therapies

The 67-kDa laminin receptor originated from a ribosomal protein that acquired a dual function during evolution.

The 67-kDa laminin receptor (67LR) is a nonintegrin cell surface receptor that mediates high-affinity interactions between cells and laminin. Overexpression of this protein in tumor cells has been related to tumor invasion and metastasis. Thus far, only a full-length gene encoding a 37-kDa precursor protein (37LRP) has been isolated. The finding that the cDNA for the 37LRP is virtually identical to a cDNA encoding the ribosomal protein p40 has suggested that 37LRP is actually a component of the translational machinery, with no laminin-binding activity. On the other hand, a peptide of 20 amino acids deduced from the sequence of 37LR/p40 was shown to exhibit high laminin-binding activity. The evolutionary relationship between 23 sequences of 37LRP/p40 proteins was analyzed. This phylogenetic analysis indicated that all of the protein sequences derive from orthologous genes and that the 37LRP is indeed a ribosomal protein that acquired the novel function of laminin receptor during evolution. The evolutionary analysis of the sequence identified as the laminin-binding site in the human protein suggested that the acquisition of the laminin-binding capability is linked to the palindromic sequence LMWWML, which appeared during evolution concomitantly with laminin

Myoferlin controls mitochondrial structure and activity in pancreatic ductal adenocarcinoma, and affects tumor aggressiveness

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death. Therapeutic options remain very limited and are based on classical chemotherapies. Energy metabolism reprogramming appears as an emerging hallmark of cancer and is considered a therapeutic target with considerable potential. Myoferlin, a ferlin family member protein overexpressed in PDAC, is involved in plasma membrane biology and has a tumor-promoting function. In the continuity of our previous studies, we investigated the role of myoferlin in the context of energy metabolism in PDAC. We used selected PDAC tumor samples and PDAC cell lines together with small interfering RNA technology to study the role of myoferlin in energetic metabolism. In PDAC patients, we showed that myoferlin expression is negatively correlated with overall survival and with glycolytic activity evaluated by 18F-deoxyglucose positron emission tomography. We found out that myoferlin is more abundant in lipogenic pancreatic cancer cell lines and is required to maintain a branched mitochondrial structure and a high oxidative phosphorylation activity. The observed mitochondrial fission induced by myoferlin depletion led to a decrease of cell proliferation, ATP production, and autophagy induction, thus indicating an essential role of myoferlin for PDAC cell fitness. The metabolic phenotype switch generated by myoferlin silencing could open up a new perspective in the development of therapeutic strategies, especially in the context of energy metabolism

Methylglyoxal: a novel upstream regulator of DNA methylation.

peer reviewed[en] BACKGROUND: Aerobic glycolysis, also known as the Warburg effect, is predominantly upregulated in a variety of solid tumors, including breast cancer. We have previously reported that methylglyoxal (MG), a very reactive by-product of glycolysis, unexpectedly enhanced the metastatic potential in triple negative breast cancer (TNBC) cells. MG and MG-derived glycation products have been associated with various diseases, such as diabetes, neurodegenerative disorders, and cancer. Glyoxalase 1 (GLO1) exerts an anti-glycation defense by detoxifying MG to D-lactate. METHODS: Here, we used our validated model consisting of stable GLO1 depletion to induce MG stress in TNBC cells. Using genome-scale DNA methylation analysis, we report that this condition resulted in DNA hypermethylation in TNBC cells and xenografts. RESULTS: GLO1-depleted breast cancer cells showed elevated expression of DNMT3B methyltransferase and significant loss of metastasis-related tumor suppressor genes, as assessed using integrated analysis of methylome and transcriptome data. Interestingly, MG scavengers revealed to be as potent as typical DNA demethylating agents at triggering the re-expression of representative silenced genes. Importantly, we delineated an epigenomic MG signature that effectively stratified TNBC patients based on survival. CONCLUSION: This study emphasizes the importance of MG oncometabolite, occurring downstream of the Warburg effect, as a novel epigenetic regulator and proposes MG scavengers to reverse altered patterns of gene expression in TNBC

The Anti-Tumor Effect of HDAC Inhibition in a Human Pancreas Cancer Model Is Significantly Improved by the Simultaneous Inhibition of Cyclooxygenase 2

Pancreatic ductal adenocarcinoma is the fourth leading cause of cancer death worldwide, with no satisfactory treatment to date. In this study, we tested whether the combined inhibition of cyclooxygenase-2 (COX-2) and class I histone deacetylase (HDAC) may results in a better control of pancreatic ductal adenocarcinoma. The impact of the concomitant HDAC and COX-2 inhibition on cell growth, apoptosis and cell cycle was assessed first in vitro on human pancreas BxPC-3, PANC-1 or CFPAC-1 cells treated with chemical inhibitors (SAHA, MS-275 and celecoxib) or HDAC1/2/3/7 siRNA. To test the potential antitumoral activity of this combination in vivo, we have developed and characterized, a refined chick chorioallantoic membrane tumor model that histologically and proteomically mimics human pancreatic ductal adenocarcinoma. The combination of HDAC1/3 and COX-2 inhibition significantly impaired proliferation of BxPC-3 cells in vitro and stalled entirely the BxPC-3 cells tumor growth onto the chorioallantoic membrane in vivo. The combination was more effective than either drug used alone. Consistently, we showed that both HDAC1 and HDAC3 inhibition induced the expression of COX-2 via the NF-kB pathway. Our data demonstrate, for the first time in a Pancreatic Ductal Adenocarcinoma (PDAC) model, a significant action of HDAC and COX-2 inhibitors on cancer cell growth, which sets the basis for the development of potentially effective new combinatory therapies for pancreatic ductal adenocarcinoma patients.Peer reviewe

A new murine model of osteoblastic/osteolytic lesions from human androgen-resistant prostate cancer

BACKGROUND: Up to 80% of patients dying from prostate carcinoma have developed bone metastases that are incurable. Castration is commonly used to treat prostate cancer. Although the disease initially responds to androgen blockade strategies, it often becomes castration-resistant (CRPC for Castration Resistant Prostate Cancer). Most of the murine models of mixed lesions derived from prostate cancer cells are androgen sensitive. Thus, we established a new model of CRPC (androgen receptor (AR) negative) that causes mixed lesions in bone. METHODS: PC3 and its derived new cell clone PC3c cells were directly injected into the tibiae of SCID male mice. Tumor growth was analyzed by radiography and histology. Direct effects of conditioned medium of both cell lines were tested on osteoclasts, osteoblasts and osteocytes. RESULTS: We found that PC3c cells induced mixed lesions 10 weeks after intratibial injection. In vitro, PC3c conditioned medium was able to stimulate tartrate resistant acid phosphatase (TRAP)-positive osteoclasts. Osteoprotegerin (OPG) and endothelin-1 (ET1) were highly expressed by PC3c while dikkopf-1 (DKK1) expression was decreased. Finally, PC3c highly expressed bone associated markers osteopontin (OPN), Runx2, alkaline phosphatase (ALP), bone sialoprotein (BSP) and produced mineralized matrix in vitro in osteogenic conditions. CONCLUSIONS: We have established a new CRPC cell line as a useful system for modeling human metastatic prostate cancer which presents the mixed phenotype of bone metastases that is commonly observed in prostate cancer patients with advanced disease. This model will help to understand androgen-independent mechanisms involved in the progression of prostate cancer in bone and provides a preclinical model for testing the effects of new treatments for bone metastases

Approximate Bayes Optimal Policy Search using Neural Networks

peer reviewedBayesian Reinforcement Learning (BRL) agents aim to maximise the expected collected rewards obtained when interacting with an unknown Markov Decision Process (MDP) while using some prior knowledge. State-of-the-art BRL agents rely on frequent updates of the belief on the MDP, as new observations of the environment are made. This offers theoretical guarantees to converge to an optimum, but is computationally intractable, even on small-scale problems. In this paper, we present a method that circumvents this issue by training a parametric policy able to recommend an action directly from raw observations. Artificial Neural Networks (ANNs) are used to represent this policy, and are trained on the trajectories sampled from the prior. The trained model is then used online, and is able to act on the real MDP at a very low computational cost. Our new algorithm shows strong empirical performance, on a wide range of test problems, and is robust to inaccuracies of the prior distribution

Detection of DNaseI-hypersensitive sites in the human gene coding for the 37 kD laminin receptor precursor/p40 ribosomal associated protein

info:eu-repo/semantics/publishe