Novel insights into the molecular origins and treatment of lung cancer

Lung cancer is the most common and most deadly cancer worldwide. Because of the aggressive and metastatic nature of many forms of the disease, it is frequently diagnosed late and responds poorly to the therapies currently available. Although our understanding of the molecular origins and evolution of lung cancer is still incomplete, recent research has yielded several developments that may offer opportunities for new, targeted and effective therapy. In this review we first discuss the prevalence and origins of lung cancer, with emphasis on non-small-cell lung cancer and adenocarcinoma, together with current treatments and their efficacy. We then look at a selection of recent papers which between them shed new light on possible therapeutic opportunities, including a novel synthetic interaction with the Kras gene and genomic or proteomic profiling studies that may pave the way for personalized treatment for lung cancer based on specific “signatures” of protein and gene expression.Lung cancer remains the foremost cause of cancer deaths worldwide. Despite advances in both detection and treatment, diagnosis is often late and the prognosis for patients poor. Our understanding of the molecular basis and progression of lung cancer remains incomplete, hampering the design and development of more effective diagnostic tools and therapies for this devastating disease. However, the last twelve months have witnessed the publication of several studies that represent significant advances in our knowledge of lung cancer, and may represent important steps on the road to effective new therapies. In this review we aim to summarize these recent developments, and give our perspectives on the therapeutic possibilities they may offer in the future.Key words: lung cancer, adenocarcinoma, egfr, kras, chemotherapy, synthetic lethal, genomic profiling, customized therapy, cancer stem cells, hypoxia-inducible factor     

Primary pulmonary hypertension: molecular basis and potential for therapy

Primary pulmonary hypertension (PPH) is defined clinically by sustained elevation of pulmonary arterial pressure without a demonstrable cause, and is a progressive, often-fatal disease. PPH can be associated with ingestion of appetite suppressants, human immunodeficiency virus infection and certain autoimmune diseases. Familial PPH is known to account for 6% of all cases. Mutations in the gene encoding the bone morphogenetic protein (BMP) type II receptor have been identified in 72% of affected families and 26% of apparently sporadic cases. BMPs are members of the transforming growth factor b superfamily and affect intracellular signalling via Smads and mitogen-activated protein kinases. Evidence supports a 'two-hit' hypothesis in which PPH is triggered by accumulation of genetic and environmental insults in a susceptible individual. Elucidation of the precise molecular and cellular mechanisms underlying PPH will provide a powerful basis for the development of novel therapeutic strategies in the treatment of this devastating condition.     

Single-cell omics: experimental workflow,data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial sc RNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.     

Novel insights into the molecular origins and treatment of lung cancer

Lung cancer remains the foremost cause of cancer deaths worldwide. Despite advances in both detection and treatment, diagnosis is often late and the prognosis for patients poor. Our understanding of the molecular basis and progression of lung cancer remains incomplete, hampering the design and development of more effective diagnostic tools and therapies for this devastating disease. However, the last twelve months have witnessed the publication of several studies that represent significant advances in our knowledge of lung cancer, and may represent important steps on the road to effective new therapies. In this review we aim to summarize these recent developments, and give our perspectives on the therapeutic possibilities they may offer in the future.     

Novel insights through the integration of structural and functional genomics data with protein networks

In recent years, major advances in genomics, proteomics, macromolecular structure determination, and the computational resources capable of processing and disseminating the large volumes of data generated by each have played major roles in advancing a more systems-oriented appreciation of biological organization. One product of systems biology has been the delineation of graph models for describing genome-wide protein-protein interaction networks. The network organization and topology which emerges in such models may be used to address fundamental questions in an array of cellular processes, as well as biological features intrinsic to the constituent proteins (or "nodes") themselves. However, graph models alone constitute an abstraction which neglects the underlying biological and physical reality that the network's nodes and edges are highly heterogeneous entities. Here, we explore some of the advantages of introducing a protein structural dimension to such models, as the marriage of conventional network representations with macromolecular structural data helps to place static node and edge constructs in a biologically more meaningful context. We emphasize that 3D protein structures constitute a valuable conceptual and predictive framework by discussing examples of the insights provided, such as enabling in silico predictions of protein-protein interactions, providing rational and compelling classification schemes for network elements, as well as revealing interesting intrinsic differences between distinct node types, such as disorder and evolutionary features, which may then be rationalized in light of their respective functions within networks.     

Mass spectrometric genomic data mining: Novel insights into bioenergetic pathways in Chlamydomonas reinhardtii

A new high-throughput computational strategy was established that improves genomic data mining from MS experiments. The MS/MS data were analyzed by the SEQUEST search algorithm and a combination of de novo amino acid sequencing in conjunction with an error-tolerant database search tool, operating on a 256 processor computer cluster. The error-tolerant search tool, previously established as GenomicPeptideFinder (GPF), enables detection of intron-split and/or alternatively spliced peptides from MS/MS data when deduced from genomic DNA. Isolated thylakoid membranes from the eukaryotic green alga Chlamydomonas reinhardtii were separated by 1-D SDS gel electrophoresis, protein bands were excised from the gel, digested in-gel with trypsin and analyzed by coupling nano-flow LC with MS/MS. The concerted action of SEQUEST and GPF allowed identification of 2622 distinct peptides. In total 448 peptides were identified by GPF analysis alone, including 98 intron-split peptides, resulting in the identification of novel proteins, improved annotation of gene models, and evidence of alternative splicing.     

Novel insights into systemic autoimmune rheumatic diseases using shared molecular signatures and an integrative analysis

We undertook this study to identify DNA methylation signatures of three systemic autoimmune rheumatic diseases (SARDs), namely rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis, compared to healthy controls. Using a careful design to minimize confounding, we restricted our study to subjects with incident disease and performed our analyses on purified CD4⁺ T cells, key effector cells in SARD. We identified differentially methylated (using the Illumina Infinium HumanMethylation450 BeadChip array) and expressed (using the Illumina TruSeq stranded RNA-seq protocol) sites between cases and controls, and investigated the biological significance of this SARD signature using gene annotation databases. We recruited 13 seropositive rheumatoid arthritis, 19 systemic sclerosis, 12 systemic lupus erythematosus subjects, and 8 healthy controls. We identified 33 genes that were both differentially methylated and expressed (26 over- and 7 under-expressed) in SARD cases versus controls. The most highly overexpressed gene was CD1C (log fold change in expression = 1.85, adjusted P value = 0.009). In functional analysis (Ingenuity Pathway Analysis), the top network identified was lipid metabolism, molecular transport, small molecule biochemistry. The top canonical pathways included the mitochondrial L-carnitine shuttle pathway (P = 5E-03) and PTEN signaling (P = 8E-03). The top upstream regulator was HNF4A (P = 3E-05). This novel SARD signature contributes to ongoing work to further our understanding of the molecular mechanisms underlying SARD and provides novel targets of interest.     

Computational prediction of inter-species relationships through omics data analysis and machine learning

Background

Antibiotic resistance and its rapid dissemination around the world threaten the efficacy of currently-used medical treatments and call for novel, innovative approaches to manage multi-drug resistant infections. Phage therapy, i.e., the use of viruses (phages) to specifically infect and kill bacteria during their life cycle, is one of the most promising alternatives to antibiotics. It is based on the correct matching between a target pathogenic bacteria and the therapeutic phage. Nevertheless, correctly matching them is a major challenge. Currently, there is no systematic method to efficiently predict whether phage-bacterium interactions exist and these pairs must be empirically tested in laboratory. Herein, we present our approach for developing a computational model able to predict whether a given phage-bacterium pair can interact based on their genome.

Results

Based on public data from GenBank and phagesDB.org, we collected more than a thousand positive phage-bacterium interactions with their complete genomes. In addition, we generated putative negative (i.e., non-interacting) pairs. We extracted, from the collected genomes, a set of informative features based on the distribution of predictive protein-protein interactions and on their primary structure (e.g. amino-acid frequency, molecular weight and chemical composition of each protein). With these features, we generated multiple candidate datasets to train our algorithms. On this base, we built predictive models exhibiting predictive performance of around 90% in terms of F1-score, sensitivity, specificity, and accuracy, obtained on the test set with 10-fold cross-validation.

Conclusion

These promising results reinforce the hypothesis that machine learning techniques may produce highly-predictive models accelerating the search of interacting phage-bacteria pairs.

     

Leukemia gene atlas--a public platform for integrative exploration of genome-wide molecular data

Leukemias are exceptionally well studied at the molecular level and a wealth of high-throughput data has been published. But further utilization of these data by researchers is severely hampered by the lack of accessible integrative tools for viewing and analysis. We developed the Leukemia Gene Atlas (LGA) as a public platform designed to support research and analysis of diverse genomic data published in the field of leukemia. With respect to leukemia research, the LGA is a unique resource with comprehensive search and browse functions. It provides extensive analysis and visualization tools for various types of molecular data. Currently, its database contains data from more than 5,800 leukemia and hematopoiesis samples generated by microarray gene expression, DNA methylation, SNP and next generation sequencing analyses. The LGA allows easy retrieval of large published data sets and thus helps to avoid redundant investigations. It is accessible at www.leukemia-gene-atlas.org.     

Nitric oxide and pulmonary arterial pressures in pulmonary hypertension

Decreased production of vasodilator substances such as nitric oxide (NO) has been proposed as important in development of pulmonary arterial hypertension (PAH). We hypothesize that NO measured over time serves as a non invasive marker of severity of PAH and response to therapy. We prospectively and serially measured exhaled NO and carbon monoxide (CO), a vasodilator and anti-inflammatory product of heme oxygenases, in 17 PAH patients in conjunction with hemodynamic parameters over 2 years. Although pulmonary artery pressures and NO were similar in all patients at entry to the study, NO increased in the 12 individuals who survived to complete the study, and correlated with change in pulmonary artery pressures. In contrast, CO did not change or correlate with hemodynamic parameters. Investigation of NO-oxidant reaction products in PAH in comparison to controls suggests that NO synthesis is impaired in the lung and that reactive oxygen species may be involved in the pathophysiology of pulmonary hypertension. Endogenous NO is inversely related to pulmonary artery pressure in PAH, with successful therapy of PAH associated with increase in NO.     

BMPR2 haploinsufficiency as the inherited molecular mechanism for primary pulmonary hypertension

Primary pulmonary hypertension (PPH) is a potentially lethal disorder, because the elevation of the pulmonary arterial pressure may result in right-heart failure. Histologically, the disorder is characterized by proliferation of pulmonary-artery smooth muscle and endothelial cells, by intimal hyperplasia, and by in situ thrombus formation. Heterozygous mutations within the bone morphogenetic protein type II receptor (BMPR-II) gene (BMPR2), of the transforming growth factor beta (TGF-beta) cell-signaling superfamily, have been identified in familial and sporadic cases of PPH. We report the molecular spectrum of BMPR2 mutations in 47 additional families with PPH and in three patients with sporadic PPH. Among the cohort of patients, we have identified 22 novel mutations, including 4 partial deletions, distributed throughout the BMPR2 gene. The majority (58%) of mutations are predicted to lead to a premature termination codon. We have also investigated the functional impact and genotype-phenotype relationships, to elucidate the mechanisms contributing to pathogenesis of this important vascular disease. In vitro expression analysis demonstrated loss of BMPR-II function for a number of the identified mutations. These data support the suggestion that haploinsufficiency represents the common molecular mechanism in PPH. Marked variability of the age at onset of disease was observed both within and between families. Taken together, these studies illustrate the considerable heterogeneity of BMPR2 mutations that cause PPH, and they strongly suggest that additional factors, genetic and/or environmental, may be required for the development of the clinical phenotype.     

Anxiety and depression disorders in patients with pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension

Background

The objective of this prospective study was to assess the prevalence of anxiety and depression disorders and their association with quality of life (QoL), clinical parameters and survival in patients with pulmonary hypertension (PH).

Methods

We prospectively assessed 158 patients invasively diagnosed with pulmonary arterial hypertension (n = 138) and inoperable chronic thromboembolic PH (n = 20) by clinical measures including quality of life (QoL, SF-36 questionnaire), cardiopulmonary exercise testing and six minute walking distance and by questionnaires for depression (PHQ-9) and anxiety (GAD-7). According to the results of the clinical examination and the questionnaires for mental disorders (MD) patients were classified into two groups, 1) with moderate to severe MD (n = 36, 22,8%), and 2) with mild or no MD (n = 122). Patients were followed for a median of 2.7 years. Investigators of QoL, SF-36 were blinded to the clinical data.

Results

At baseline the 2 groups did not differ in their severity of PH or exercise capacity. Patients with moderate to severe MD (group 1) had a significantly lower QoL shown in all subscales of SF-36 (p < 0.002). QoL impairment significantly correlated with the severity of depression (p < 0.001) and anxiety (p < 0.05). During follow-up period 32 patients died and 3 were lost to follow-up. There was no significant difference between groups regarding survival. Only 8% of the patients with MD received psychopharmacological treatment.

Conclusion

Anxiety and depression were frequently diagnosed in our patients and significantly correlated with quality of life, but not with long term survival. Further prospective studies are needed to confirm the results.     

Novel molecular insights into RhoA GTPase-induced resistance to aqueous humor outflow through the trabecular meshwork

Impaired drainage of aqueous humor through the trabecular meshwork (TM) culminating in increased intraocular pressure is a major risk factor for glaucoma, a leading cause of blindness worldwide. Regulation of aqueous humor drainage through the TM, however, is poorly understood. The role of RhoA GTPase-mediated actomyosin organization, cell adhesive interactions, and gene expression in regulation of aqueous humor outflow was investigated using adenoviral vector-driven expression of constitutively active mutant of RhoA (RhoAV14). Organ-cultured anterior segments from porcine eyes expressing RhoAV14 exhibited significant reduction of aqueous humor outflow. Cultured TM cells expressing RhoAV14 exhibited a pronounced contractile morphology, increased actin stress fibers, and focal adhesions and increased levels of phosphorylated myosin light chain (MLC), collagen IV, fibronectin, and laminin. cDNA microarray analysis of RNA extracted from RhoAV14-expressing human TM cells revealed a significant increase in the expression of genes encoding extracellular matrix (ECM) proteins, cytokines, integrins, cytoskeletal proteins, and signaling proteins. Conversely, various ECM proteins stimulated robust increases in phosphorylation of MLC, paxillin, and focal adhesion kinase and activated Rho GTPase and actin stress fiber formation in TM cells, indicating a potential regulatory feedback interaction between ECM-induced mechanical strain and Rho GTPase-induced isometric tension in TM cells. Collectively, these data demonstrate that sustained activation of Rho GTPase signaling in the aqueous humor outflow pathway increases resistance to aqueous humor outflow through the trabecular pathway by influencing the actomyosin assembly, cell adhesive interactions, and the expression of ECM proteins and cytokines in TM cells.     

Novel missense mutations in gidB gene associated with streptomycin resistance in Mycobacterium tuberculosis: insights from molecular dynamics

Streptomycin was the first antibiotic used for the treatment of tuberculosis by inhibiting translational proof reading. Point mutation in gidB gene encoding S-adenosyl methionine (SAM)-dependent 7-methylguanosine (m7G) methyltransferase required for methylation of 16S rRNA confers streptomycin resistance. As there was no structural substantiation experimentally, gidB protein model was built by threading algorithm. In this work, molecular dynamics (MD) simulations coupled with binding free energy calculations were performed to outline the mechanism underlying high-level streptomycin resistance associated with three novel missense mutants including S70R, T146M, and R187M. Results from dynamics analyses suggested that the structure distortion in the binding pocket of gidB mutants modulate SAM binding affinity. At the structural level, these conformational changes bring substantial decrease in the number of residues involved in hydrogen bonding and dramatically reduce thermodynamic stability of mutant gidB–SAM complexes. The outcome of comparative analysis of the MD simulation trajectories revealed lower conformational stability associated with higher flexibility in mutants relative to the wild-type, turns to be major factor driving the emergence of drug resistance toward antibiotic. This study will pave way toward design and development of resistant defiant gidB inhibitors as potent anti-TB agents.     

Differential protein expression in human gliomas and molecular insights

Gliomas are the most common of the primary intracranial tumors with astrocytomas constituting about 40%. Using clinically and histologically assessed astrocytomas, we have studied their protein profiles using a two-dimensional gel electrophoresis-mass spectrometry approach and identified differentially expressed proteins which may be useful molecular indicators to understand these tumors. Examination of the protein profiles of 27 astrocytoma samples of different grades revealed 72 distinct, differentially expressed proteins belonging to various functional groups such as cytoskeleton and intermediate filament proteins, heat shock proteins (HSPs), enzymes and regulatory proteins. Based on the consistency of their differential expression, 29 distinct proteins could be short-listed and may have a role in the pathology of astrocytomas. Some were found to be differentially expressed in both Grade III and IV astrocytomas while others were associated with a particular grade. A notable observation was underexpression of Prohibitin, a potential tumor suppressor protein, Rho-GDP dissociation inhibitor, Rho-GDI, a regulator of Rho GTPases and HSPs as well as destabilization of glial fibrillary acidic protein, GFAP, major protein of the glial filaments, in Grade III malignant tumors. We attempt to explain glioma malignancy and progression in terms of their combined role.