Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies.

BACKGROUND: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. RESULTS: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. CONCLUSIONS: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

The multifaceted role of Matricellular Proteins in health and cancer, as biomarkers and therapeutic targets.

The extracellular matrix (ECM) is composed of a mesh of proteins, proteoglycans, growth factors, and other secretory components. It constitutes the tumor microenvironment along with the endothelial cells, cancer-associated fibroblasts, adipocytes, and immune cells. The proteins of ECM can be functionally classified as adhesive proteins and matricellular proteins (MCP). In the tumor milieu, the ECM plays a major role in tumorigenesis and therapeutic resistance. The current review encompasses thrombospondins, osteonectin, osteopontin, tenascin C, periostin, the CCN family, laminin, biglycan, decorin, mimecan, and galectins. The matrix metalloproteinases (MMPs) are also discussed as they are an integral part of the ECM with versatile functions in the tumor stroma. In this review, the role of these proteins in tumor initiation, growth, invasion and metastasis have been highlighted, with emphasis on their contribution to tumor therapeutic resistance. Further, their potential as biomarkers and therapeutic targets based on existing evidence are discussed. Owing to the recent advancements in protein targeting, the possibility of agents to modulate MCPs in cancer as therapeutic options are discussed.

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

Pioglitazone modulates doxorubicin resistance in a in vivo model of drug resistant osteosarcoma xenograft.

Osteosarcoma has been reported with treatment failure in up to 40% of cases. Our laboratory had identified genes involved in the PPARγ pathway to be associated with doxorubicin (DOX) resistance. We hence used PPARγ agonist pioglitazone (PIO) to modulate DOX resistance. DOX-resistant cell line (143B-DOX) was developed by gradient exposure to DOX. The cytotoxicity to PIO and in combination with DOX was assayed in vitro, followed by HPLC to estimate the metabolites of PIO in the presence of microsomes (HLMs). Gene expression studies revealed the mechanism behind the cytotoxicity of PIO. Further, the effects were evaluated in mice bearing 143B-DOX tumors treated either with PIO (20 mg/kg/p.o or 40 mg/kg/p.o Q1D) alone or in combination with DOX (0.5 mg/kg/i.p Q2W). 143B-DOX was 50-fold resistant over parental cells. While PIO did not show any activity on its own, the addition of HLMs to the cells in culture showed over 80% cell kill within 24 h, possibly due to the metabolites of PIO as determined by HPLC. In combination with DOX, PIO had shown synergistic activity. Additionally, cytotoxicity assay in the presence of HLMs revealed that PIO on its own showed promising activity compared to its metabolites-hydroxy pioglitazone and keto pioglitazone. In vivo studies demonstrated that treatment with 40 mg/kg/p.o PIO alone showed significant activity, followed by a combination with DOX. Gene expression studies revealed that PIO could modulate drug resistance by downregulating MDR1 and IL8. Our study suggests that PIO can modulate DOX resistance in osteosarcoma cells.

Economic perspective of cancer treatment in India.

Financial constraints faced by the families play a vital role in cancer treatment refusal, non-adherence, and failure of the prescribed therapy. This review aims to give an insight into the economic perspective of cancer treatment in India, focusing on the accessibility and affordability of oncological drugs, and the move towards generics/biosimilars without compromising on the quality of the treatment. The monthly cost of a set of drugs available in India for the treatment of solid malignancies, approved after 2010 by the US FDA and the Drugs Controller General of India (DCGI) were calculated based on standard patient parameters. The information on the clinical trial, the monthly cost of treatment, and the availability of its equivalent have been compiled. Newer cancer drugs are approved based on surrogate endpoints, with a very modest prolongation of life, but the cost incurred can be unbearable. There is a considerable variation in costs between the innovator and the equivalent drugs, making the latter cost-effective. We have highlighted the importance of generics and biosimilars, as a cost-cutting strategy, in delivering state-of-art health care with a lesser chance of treatment abandonment: this will ensure that all patients have equal access to personalized medicine which are reliable, effective, and affordable for better curative, supportive, and palliative care.

Repurposing Drugs by In Silico Methods to Target BCR Kinase Domain in Chronic Myeloid Leukemia.

BACKGROUND: Targeted therapy in the form of highly selective tyrosine kinase inhibitors (TKIs) has transformed the treatment of chronic myeloid leukemia (CML). However, mutations in the kinase domain contribute to drug resistance against TKIs which compromises the treatment response. Our aim is to explore regions outside the BCR-ABL oncoprotein to identify potential therapeutic targets to curb drug resistance by targeting growth factor receptor-bound protein-2 (Grb-2) which binds to BCR-ABL at the phosphorylated tyrosine (Y177) thereby activating the Ras and PI3K/AKT signaling pathway. METHODS: We have used in silico methods to repurpose drugs for identifying their potential to inhibit the binding of Grb-2 with Y177 by occupying the active binding site of the BCR domain. RESULTS: Differentially expressed genes from GEO dataset were found to be associated with hematopoietic cell lineage, NK cell-mediated cytotoxicity, NF-κB and chemokine signaling, cytokine-cytokine receptor interaction, histidine metabolism and transcriptional misregulation in cancer. The fold recognition method of SPARKS-X tool was used to model the BCR domain (Z-score = 8.21). Connectivity Map generated a drug list based on the gene expression profile, which were docked with BCR. Schrodinger XP glide docking identified Diphosphopyridine nucleotide, Hesperidin, Butirosin, Ovoflavin, and Nor-dihydroguaiaretic acid to show strong interaction in close proximity to the active binding pocket containing Y177 of the target protein and was further validated using iGEMDOCK and Parallelized Open Babel and AutoDock suite Pipeline (POAP). CONCLUSION: Our study not only extends our current knowledge about repurposing drugs for newer indications but also provides a route towards combinatorial therapy with standard drugs used for CML treatment. However, the efficacy of these repurposed drugs needs to be further investigated using in vitro and in vivo studies.
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New de novo assembly of the Atlantic bottlenose dolphin (Tursiops truncatus) improves genome completeness and provides haplotype phasing.

High-quality genomes are essential to resolve challenges in breeding, comparative biology, medicine, and conservation planning. New library preparation techniques along with better assembly algorithms result in continued improvements in assemblies for non-model organisms, moving them toward reference-quality genomes. We report on the latest genome assembly of the Atlantic bottlenose dolphin, leveraging Illumina sequencing data coupled with a combination of several library preparation techniques. These include Linked-Reads (Chromium, 10x Genomics), mate pairs (MP), long insert paired ends, and standard paired end. Data were assembled with the commercial DeNovoMAGIC assembly software, resulting in two assemblies, a traditional "haploid" assembly (Tur_tru_Illumina_hap_v1) that is a mosaic of the two parental haplotypes and a phased assembly (Tur_tru_Illumina_phased_v1) where each scaffold has sequence from a single homologous chromosome. We show that Tur_tru_Illumina_hap_v1 is more complete and more accurate compared to the current best reference based on the amount and composition of sequence, the consistency of the MP alignments to the assembled scaffolds, and on the analysis of conserved single-copy mammalian orthologs. The phased de novo assembly Tur_tru_Illumina_phased_v1 is the first publicly available for this species and provides the community with novel and accurate ways to explore the heterozygous nature of the dolphin genome.

Efficient Segmentation of Brain Tumor Using FL-SNM with a Metaheuristic Approach to Optimization.

Nowadays, automatic tumor detection from brain images is extremely significant for many diagnostic as well as therapeutic purposes, due to the unpredictable shape and appearance of tumors. In medical image analysis, the automatic segmentation of tumors from brain using magnetic resonance imaging (MRI) data is the most critical issue. Existing research has some limitations, such as high processing time and lower accuracy, because of the time required for the training process. In this research, a new automatic segmentation process is introduced using machine learning and a swarm intelligence scheme. Here, a fuzzy logic with spiking neuron model (FL-SNM) is proposed for segmenting the brain tumor region in MR images. Initially, input images are preprocessed to remove Gaussian and Poisson noise using a modified Kuan filter (MKF). In the MKF, the optimal selection of the minimum MSE of image pixels is achieved using a random search algorithm (RSA), which improves the peak signal-to-noise ratio (PSNR). Then, the image is smoothed using an anisotropic diffusion filter (ADF) to reduce the over-filtering problem. Afterwards, to extract statistical texture features, Fisher's linear-discriminant analysis (FLDA) is used. Finally, extracted features are transferred to the FL-SNM process and this scheme effectively segments the tumor region. In FL-SNM, the consequent parameters such as weight and bias play an important role in segmenting the region. Therefore, optimizing the weight parameter values using a chicken behavior-based swarm intelligence (CSI) algorithm, is proposed. The proposed (FL-SNM) scheme attained better performance in terms of high accuracy (94.87%), sensitivity (92.07%), specificity (99.34%), precision rate (89.36%), recall rate (88.39%), F-measure (95.06%), G-mean (95.63%), and DSC rate (91.2%), compared to existing convolutional neural networks (CNNs) and hierarchical self-organizing maps (HSOMs).

Eosinophilic pneumonia associated with concomitant cigarette and marijuana smoking.

A 29-year-old Caucasian man presented for the evaluation of a new onset of shortness of breath associated with cough and wheeze for 1 day. The history was significant for a recent travel of 20 h duration to Houston, a new onset of cigarette smoking for 2 weeks and marijuana smoking. The patient was afebrile and did not have any leg swelling; initial diagnosis of community-acquired pneumonia was made and the patient was started on antibiotics. Despite being on antibiotics, his medical condition continued to deteriorate and extensive diagnostic workup for infectious and autoimmune aetiology including bronchoalveolar lavage was completed and was inconclusive. Ultimately, the patient underwent video-assisted thoracoscopic lung biopsy which led to the diagnosis of acute eosinophilic pneumonia. Steroids were started with a good treatment response. The patient was discharged on a tapering dose of steroids; a follow-up chest x ray at 6 weeks was within normal limits.

May-thurner syndrome: a case report and review of the literature.

May-Thurner syndrome (MTS) has been recognized as a clinical entity for almost six decades. The true incidence rate of MTS is unknown and perhaps ranges from 22 to 32% according to the autopsy studies in the early twentieth century. However, MTS related deep venous thrombosis (DVT) accounts for only 2%-3% of all lower limb DVTS. In MTS, the left common iliac vein is compressed against the fifth lumbar vertebrae by the right common iliac artery, as it crosses in front of the vein. Chronic pulsation of the artery is thought to cause elastin, collagen deposition, and intimal fibrosis leading to formation of venous spur and venous thrombosis. MTS can present as acute or chronic DVT leading to pulmonary embolism (PE), chronic leg pain, chronic ulcers, or skin pigmentation changes. In this case report we have described an interesting case of a 28-year-old Caucasian female who presented for evaluation of shortness of breath (SOB) associated with cough for one week. SOB was found to be secondary to massive bilateral pulmonary embolism resulting from extensive MTS related DVT of the left lower extremity. Patient underwent pharmacomechanical treatment with local thrombolysis, thrombectomy, and venoplasty along with stent placement that extended to inferior vena caval junction. Subsequently patient was discharged on coumadin. MTS should be considered in differentials when faced with a case of unilateral DVT particularly in younger age group.

A case of multiple myeloma coexisting with primary hyperparathyroidism and review of the literature.

Hypercalcemia is a common medical problem with an estimated prevalence of 15% among hospitalized patients. Multiple myeloma (MM) and primary hyperparathyroidism (PHPT) are among the most common causes of hypercalcemia but coexistence of both pathologic processes in a patient is an extremely rare phenomenon. In this paper we have discussed a patient presenting with this rare phenomenon. We have also provided a comprehensive review of the scientific literature published on codiagnosis of MM and PHPT.

Baseline characteristics of patients with chronic kidney disease stage 3 and stage 4 in Spain: the MERENA observational cohort study.

BACKGROUND: To obtain information on cardiovascular morbidity, hypertension control, anemia and mineral metabolism based on the analysis of the baseline characteristics of a large cohort of Spanish patients enrolled in an ongoing prospective, observational, multicenter study of patients with stages 3 and 4 chronic kidney diseases (CKD). METHODS: Multicenter study from Spanish government hospital-based Nephrology outpatient clinics involving 1129 patients with CKD stages 3 (n = 434) and 4 (n = 695) defined by GFR calculated by the MDRD formula. Additional analysis was performed with GFR calculated using the CKD-EPI and Cockcroft-Gault formula. RESULTS: In the cohort as a whole, median age 70.9 years, morbidity from all cardiovascular disease (CVD) was very high (39.1%). In CKD stage 4, CVD prevalence was higher than in stage 3 (42.2 vs 35.6% p < 0.024). Subdividing stage 3 in 3a and 3b and after adjusting for age, CVD increased with declining GFR with the hierarchy (stage 3a < stage 3b < stage 4) when calculated by CKD-EPI (31.8, 35.4, 42.1%, p 0.039) and Cockcroft-Gault formula (30.9, 35.6, 43.4%, p 0.010) and MDRD formula (32.5, 36.2, 42.2%,) but with the latter, it did not reach statistical significance (p 0.882). Hypertension was almost universal among those with stages 3 and 4 CKD (91.2% and 94.1%, respectively) despite the use of more than 3 anti-hypertensive agents including widespread use of RAS blockers. Proteinuria (> 300 mg/day) was present in more than 60% of patients and there was no significant differences between stages 3 and 4 CKD (1.2 ± 1.8 and 1.3 ± 1.8 g/day, respectively). A majority of the patients had hemoglobin levels greater than 11 g/dL (91.1 and 85.5% in stages 3 and 4 CKD respectively p < 0.001) while the use of erythropoiesis-stimulating agents (ESA) was limited to 16 and 34.1% in stages 3 and 4 CKD respectively. Intact parathyroid hormone (i-PTH) was elevated in stage 3 and stage 4 CKD patients (121 ± 99 and 166 ± 125 pg/mL p 0.001) despite good control of calcium-phosphorus levels. CONCLUSION: This study provides an overview of key clinical parameters in patients with CKD Stages 3 and 4 where delivery or care was largely by nephrologists working in a network of hospital-based clinics of the Spanish National Healthcare System.

Eggerthella lenta bacteremia in a Crohn's disease patient after ileocecal resection.

Eggerthella lenta is an anaerobic, nonspore-forming Gram-positive rod and is a common gut commensal. Bacteremia from this organism is rare but when present is always clinically significant. Gastrointestinal disease and malignancy are the most common causes for bacteremia from this organism. Eggerthella species have been isolated in feces from patients with inflammatory bowel disease, but bacteremia has not been reported to the best of our knowledge. Here we report the case of a young African-American female with Crohn's disease who developed Eggerthella lenta bacteremia after ileocaecal resection.

The nematode resistance allele at the rhg1 locus alters the proteome and primary metabolism of soybean roots.

Heterodera glycines, the soybean cyst nematode (SCN), causes the most damaging chronic disease of soybean (Glycine max). Host resistance requires the resistance allele at rhg1. Resistance destroys the giant cells created in the plant's roots by the nematodes about 24 to 48 h after commencement of feeding. In addition, 4 to 8 d later, a systemic acquired resistance develops that discourages later infestations. The molecular mechanisms that control the rhg1-mediated resistance response appear to be multigenic and complex, as judged by transcript abundance changes, even in near isogenic lines (NILs). This study aimed to focus on key posttranscriptional changes by identifying proteins and metabolites that were increased in abundance in both resistant and susceptible NILs. Comparisons were made among NILs 10 d after SCN infestation and without SCN infestation. Two-dimensional gel electrophoresis resolved more than 1,000 protein spots on each gel. Only 30 protein spots with a significant (P < 0.05) difference in abundance of 1.5-fold or more were found among the four treatments. The proteins in these spots were picked, trypsin digested, and analyzed using quadrupole time-of-flight tandem mass spectrometry. Protein identifications could be made for 24 of the 30 spots. Four spots contained two proteins, so that 28 distinct proteins were identified. The proteins were grouped into six functional categories. Metabolite analysis by gas chromatography-mass spectrometry identified 131 metabolites, among which 58 were altered by one or more treatment; 28 were involved in primary metabolism. Taken together, the data showed that 17 pathways were altered by the rhg1 alleles. Pathways altered were associated with systemic acquired resistance-like responses, including xenobiotic, phytoalexin, ascorbate, and inositol metabolism, as well as primary metabolisms like amino acid synthesis and glycolysis. The pathways impacted by the rhg1 allelic state and SCN infestation agreed with transcript abundance analyses but identified a smaller set of key proteins. Six of the proteins lay within the same small region of the interactome identifying a key set of 159 interacting proteins involved in transcriptional control, nuclear localization, and protein degradation. Finally, two proteins (glucose-6-phosphate isomerase [EC 5.3.1.9] and isoflavone reductase [EC 1.3.1.45]) and two metabolites (maltose and an unknown) differed in resistant and susceptible NILs without SCN infestation and may form the basis of a new assay for the selection of resistance to SCN in soybean.

The interactions of the largest subunit of RNA polymerase II with other cellular proteins: a bioinformatic approach.

The function of a protein is governed by its interaction with other proteins inside a cell. Therefore, it is important to identify the interacting partners of a particular protein to decipher its function. The protein interaction networks are generally determined by bioinformatic as well as experimental methodologies such as yeast two hybrid, mass spectrometry, immunoprecipitation, and fluorescence resonance energy transfer assays. Here, we have analyzed bioinformatically the interactions of Rpb1p (the largest subunit of RNA Polymerase II) with other proteins in yeast, using Cytoscape software and Biogrid/Biomart database. We find that Rpb1p interacts with a large number of proteins involved in mRNA synthesis, processing, export, and other cellular processes. These results validate the application of such bioinformatic approach to determine the interactome for other cellular proteins.