A Resource Aware MapReduce Based Parallel SVM for Large Scale Image Classifications

Machine learning techniques have facilitated image retrieval by automatically classifying and annotating images with keywords. Among them support vector machines (SVMs) are used extensively due to their generalization properties. However, SVM training is notably a computationally intensive process especially when the training dataset is large. This paper presents RASMO, a resource aware MapReduce based parallel SVM algorithm for large scale image classifications which partitions the training data set into smaller subsets and optimizes SVM training in parallel using a cluster of computers. A genetic algorithm based load balancing scheme is designed to optimize the performance of RASMO in heterogeneous computing environments. RASMO is evaluated in both experimental and simulation environments. The results show that the parallel SVM algorithm reduces the training time significantly compared with the sequential SMO algorithm while maintaining a high level of accuracy in classifications.National Basic Research Program (973) of China under Grant 2014CB34040

Detailed Molecular and Immune Marker Profiling of Archival Prostate Cancer Samples Reveals an Inverse Association between TMPRSS2:ERG Fusion Status and Immune Cell Infiltration

Prostate cancer is a significant global health issue and limitations to current patient management pathways often result in over- or under-treatment. New ways to stratify patients are urgently needed. We conducted a feasibility study of such novel assessments looking for associations between genomic changes and lymphocyte infiltration. An innovative workflow utilizing an in-house targeted sequencing panel, immune cell profiling using an image analysis pipeline, RNA-Seq, and exome sequencing in select cases was tested. Gene fusions were profiled by RNA-seq in 27/27 cases and a significantly higher TIL count was noted in tumors without a TMPRSS2:ERG fusion compared to those with the fusion (P = 0.01). Although this finding was not replicated in a larger validation set (n=436) of The Cancer Genome Atlas images, there was a trend in the same direction. Differential expression analysis of TIL-High and TIL-Low tumors revealed the enrichment of both innate and adaptive immune response pathways. Mutations in mismatch repair genes (MLH1 and MSH6 mutations in 1/27 cases) were identified. We describe a potential immune escape mechanism in TMPRSS2:ERG fusion positive tumors. Detailed profiling, as shown here, can provide novel insights into tumor biology. Likely differences with findings with other cohorts are related to methods used to define region of interest, but this warrants further study in a larger cohort

Cone photoreceptor phosphodiesterase PDE6H inhibition regulates cancer cell growth and metabolism, replicating the dark retina response

Abstract Background PDE6H encodes PDE6γ′, the inhibitory subunit of the cGMP-specific phosphodiesterase 6 in cone photoreceptors. Inhibition of PDE6, which has been widely studied for its role in light transduction, increases cGMP levels. The purpose of this study is to characterise the role of PDE6H in cancer cell growth. Methods From an siRNA screen for 487 genes involved in metabolism, PDE6H was identified as a controller of cell cycle progression in HCT116 cells. Role of PDE6H in cancer cell growth and metabolism was studied through the effects of its depletion on levels of cell cycle controllers, mTOR effectors, metabolite levels, and metabolic energy assays. Effect of PDE6H deletion on tumour growth was also studied in a xenograft model. Results PDE6H knockout resulted in an increase of intracellular cGMP levels, as well as changes to the levels of nucleotides and key energy metabolism intermediates. PDE6H knockdown induced G1 cell cycle arrest and cell death and reduced mTORC1 signalling in cancer cell lines. Both knockdown and knockout of PDE6H resulted in the suppression of mitochondrial function. HCT116 xenografts revealed that PDE6H deletion, as well as treatment with the PDE5/6 inhibitor sildenafil, slowed down tumour growth and improved survival, while sildenafil treatment did not have an additive effect on slowing the growth of PDE6γ′-deficient tumours. Conclusions Our results indicate that the changes in cGMP and purine pools, as well as mitochondrial function which is observed upon PDE6γ′ depletion, are independent of the PKG pathway. We show that in HCT116, PDE6H deletion replicates many effects of the dark retina response and identify PDE6H as a new target in preventing cancer cell proliferation and tumour growth