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

Emerging and novel functions of complement protein C1q

Copyright: © 2015 Kouser, Madhukaran, Shastri, Saraon, Ferluga, Al-Mozaini and Kishore. Complement protein C1q, the recognition molecule of the classical pathway, performs a diverse range of complement and non-complement functions. It can bind various ligands derived from self, non-self, and altered self and modulate the functions of immune and non-immune cells including dendritic cells and microglia. C1q involvement in the clearance of apoptotic cells and subsequent B cell tolerance is more established now. Recent evidence appears to suggest that C1q plays an important role in pregnancy where its deficiency and dysregulation can have adverse effects, leading to preeclampsia, missed abortion, miscarriage or spontaneous loss, and various infections. C1q is also produced locally in the central nervous system, and has a protective role against pathogens and possible inflammatory functions while interacting with aggregated proteins leading to neurodegenerative diseases. C1q role in synaptic pruning, and thus CNS development, its anti-cancer effects as an immune surveillance molecule, and possibly in aging are currently areas of extensive research

Missed Opportunities in Identifying Cardiomyopathy Aetiology Prior to Advanced Heart Failure Therapy

BACKGROUND: Specific aetiologies of cardiomyopathy can significantly impact treatment options as well as appropriateness and prioritisation for advanced heart failure therapies such as ventricular assist device (VAD) or orthotopic heart transplantation (OHT). We reviewed the tissue diagnoses of patients who underwent advanced therapies for heart failure (HF) to identify diagnostic discrepancies. METHODS: This study presents a retrospective cohort of the aetiology of cardiomyopathy in 118 patients receiving either durable VAD or OHT. Discrepancies between the preoperative aetiological diagnosis of cardiomyopathy with the pathological diagnosis were recorded. Echocardiographic and haemodynamic data were reviewed to examine differences in patients with differing aetiological diagnoses. RESULTS: Twelve (12) of 118 (12/118) (10.2%) had a pathological diagnosis that was discordant with pre-surgical diagnosis. The most common missed diagnoses were infiltrative cardiomyopathy (5) and hypertrophic cardiomyopathy (3). Patients with misidentified aetiology of cardiomyopathy had smaller left ventricular (LV) dimensions on echocardiography than patients with dilated cardiomyopathy (5.8±0.9 vs 6.7±1.1 respectively p=0.01). CONCLUSIONS: Most HF patients undergoing VAD and OHT had a correct diagnosis for their heart failure prior to treatment, but a missed diagnosis at time of intervention (VAD or OHT) was not uncommon. Smaller LV dimension on echocardiogram in a patient with a non-ischaemic cardiomyopathy warrants further workup for a more specific aetiology

Hierarchical HotNet: identifying hierarchies of altered subnetworks

MotivationThe analysis of high-dimensional 'omics data is often informed by the use of biological interaction networks. For example, protein-protein interaction networks have been used to analyze gene expression data, to prioritize germline variants, and to identify somatic driver mutations in cancer. In these and other applications, the underlying computational problem is to identify altered subnetworks containing genes that are both highly altered in an 'omics dataset and are topologically close (e.g. connected) on an interaction network.ResultsWe introduce Hierarchical HotNet, an algorithm that finds a hierarchy of altered subnetworks. Hierarchical HotNet assesses the statistical significance of the resulting subnetworks over a range of biological scales and explicitly controls for ascertainment bias in the network. We evaluate the performance of Hierarchical HotNet and several other algorithms that identify altered subnetworks on the problem of predicting cancer genes and significantly mutated subnetworks. On somatic mutation data from The Cancer Genome Atlas, Hierarchical HotNet outperforms other methods and identifies significantly mutated subnetworks containing both well-known cancer genes and candidate cancer genes that are rarely mutated in the cohort. Hierarchical HotNet is a robust algorithm for identifying altered subnetworks across different 'omics datasets.Availability and implementationhttp://github.com/raphael-group/hierarchical-hotnet.Supplementary informationSupplementary material are available at Bioinformatics online

A drug discovery platform to identify compounds that inhibit EGFR triple mutants.

Receptor tyrosine kinases (RTKs) are transmembrane receptors of great clinical interest due to their role in disease. Historically, therapeutics targeting RTKs have been identified using in vitro kinase assays. Due to frequent development of drug resistance, however, there is a need to identify more diverse compounds that inhibit mutated but not wild-type RTKs. Here, we describe MaMTH-DS (mammalian membrane two-hybrid drug screening), a live-cell platform for high-throughput identification of small molecules targeting functional protein-protein interactions of RTKs. We applied MaMTH-DS to an oncogenic epidermal growth factor receptor (EGFR) mutant resistant to the latest generation of clinically approved tyrosine kinase inhibitors (TKIs). We identified four mutant-specific compounds, including two that would not have been detected by conventional in vitro kinase assays. One of these targets mutant EGFR via a new mechanism of action, distinct from classical TKI inhibition. Our results demonstrate how MaMTH-DS is a powerful complement to traditional drug screening approaches