Extend the benchmarking indel set by manual review using the individual cell line sequencing data from the Sequencing Quality Control 2 (SEQC2) project.

Accurate indel calling plays an important role in precision medicine. A benchmarking indel set is essential for thoroughly evaluating the indel calling performance of bioinformatics pipelines. A reference sample with a set of known-positive variants was developed in the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, but the known indels in the known-positive set were limited. This project sought to provide an enriched set of known indels that would be more translationally relevant by focusing on additional cancer related regions. A thorough manual review process completed by 42 reviewers, two advisors, and a judging panel of three researchers significantly enriched the known indel set by an additional 516 indels. The extended benchmarking indel set has a large range of variant allele frequencies (VAFs), with 87% of them having a VAF below 20% in reference Sample A. The reference Sample A and the indel set can be used for comprehensive benchmarking of indel calling across a wider range of VAF values in the lower range. Indel length was also variable, but the majority were under 10 base pairs (bps). Most of the indels were within coding regions, with the remainder in the gene regulatory regions. Although high confidence can be derived from the robust study design and meticulous human review, this extensive indel set has not undergone orthogonal validation. The extended benchmarking indel set, along with the indels in the previously published known-positive set, was the truth set used to benchmark indel calling pipelines in a community challenge hosted on the precisionFDA platform. This benchmarking indel set and reference samples can be utilized for a comprehensive evaluation of indel calling pipelines. Additionally, the insights and solutions obtained during the manual review process can aid in improving the performance of these pipelines.

RAC1 Alterations Induce Acquired Dabrafenib Resistance in Association with Anaplastic Transformation in a Papillary Thyroid Cancer Patient.

BRAF-activating mutations are the most frequent driver mutations in papillary thyroid cancer (PTC). Targeted inhibitors such as dabrafenib have been used in advanced BRAF-mutated PTC; however, acquired resistance to the drug is common and little is known about other effectors that may play integral roles in this resistance. In addition, the induction of PTC dedifferentiation into highly aggressive KRAS-driven anaplastic thyroid cancer (ATC) has been reported. We detected a novel RAC1 (P34R) mutation acquired during dabrafenib treatment in a progressive metastatic lesion with ATC phenotype. To identify a potential functional link between this novel mutation and tumor dedifferentiation, we developed a cell line derived from the metastatic lesion and compared its behavior to isogenic cell lines and primary tumor samples. Our data demonstrated that RAC1 mutations induce changes in cell morphology, reorganization of F-actin almost exclusively at the cell cortex, and changes in cell adhesion properties. We also established that RAC1 amplification, with or without mutation, is sufficient to drive cell proliferation and resistance to BRAF inhibition. Further, we identified polyploidy of chromosome 7, which harbors RAC1, in both the metastatic lesion and its derived cell line. Copy number amplification and overexpression of other genes located on this chromosome, such as TWIST1, EGFR, and MET were also detected, which might also lead to dabrafenib resistance. Our study suggests that polyploidy leading to increased expression of specific genes, particularly those located on chromosome 7, should be considered when analyzing aggressive thyroid tumor samples and in further treatments.

Whole-exome sequencing for ocular adnexal sebaceous carcinoma suggests PCDH15 as a novel mutation associated with metastasis.

Ocular adnexal sebaceous carcinoma (OASeC) is an aggressive eyelid carcinoma. Analysis of molecular-genetic drivers of this disease could reveal new prognostic markers and actionable targets for treatment. To identify somatically acquired genomic mutations in OASeC and explore their associations with metastasis, whole-exome sequencing on DNA extracted from retrospectively collected tumor samples was performed. Thirty-one patients in two orbital oncology centers with OASeC were included. Sequencing results were analyzed to detect mutations and explore their possible association with metastasis. The median patient age was 64 years. A total of 1780 candidate somatic mutations were identified with median mutation rate of 1.0/Mb (range, 0.2-13.6). The five most commonly mutated genes (as determined by MutSig; q value < 0.25) were TP53 (mutated in 22 cases), ZNF750 (13 cases), RB1 (12 cases), NOTCH1 (8 cases), and PCDH15 (5 cases). Mutations in ZNF750 or NOTCH1 pathway genes were present in 24 (77%) of the 31 cases; there was a trend toward mutual exclusivity of ZNF750 and NOTCH1 mutations. All eight tumors with NOTCH1 mutations also had TP53 and/or RB1 mutations. Four of the five PCDH15 mutations and all four PCDH15 missense mutations were identified in patients with metastatic disease, including one patient with distant metastasis and three with nodal metastasis. PCDH15 was significantly associated with metastasis (P = 0.01). We identified the most commonly mutated genes in a series of OASeCs and found a previously unreported mutation in OASeC, PCDH15 mutation, that was significantly associated with metastasis. NOTCH1 mutation is an actionable mutation; clinical trials targeting this mutation are available throughout the US and could be considered for patients with metastatic NOTCH1-mutant OASeC. TP53, ZNF750, RB1, and PCDH15 mutations are most likely loss-of-function mutations and may have diagnostic and prognostic importance.

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and assessed their performance on multiple clinical cohorts. We demonstrate that deep neural networks outperform the current state in machine learning frameworks. We provide a proof of concept for the use of deep neural network-based frameworks to aid precision oncology strategies.

Upper tract urothelial carcinoma has a luminal-papillary T-cell depleted contexture and activated FGFR3 signaling.

Upper tract urothelial carcinoma (UTUC) is characterized by a distinctly aggressive clinical phenotype. To define the biological features driving this phenotype, we performed an integrated analysis of whole-exome and RNA sequencing of UTUC. Here we report several key insights from our molecular dissection of this disease: 1) Most UTUCs are luminal-papillary; 2) UTUC has a T-cell depleted immune contexture; 3) High FGFR3 expression is enriched in UTUC and correlates with its T-cell depleted immune microenvironment; 4) Sporadic UTUC is characterized by a lower total mutational burden than urothelial carcinoma of the bladder. Our findings lay the foundation for a deeper understanding of UTUC biology and provide a rationale for the development of UTUC-specific treatment strategies.

Comprehensive Genomic Characterization of Upper Tract Urothelial Carcinoma.

BACKGROUND: Upper urinary tract urothelial cancer (UTUC) may have unique etiologic and genomic factors compared to bladder cancer. OBJECTIVE: To characterize the genomic landscape of UTUC and provide insights into its biology using comprehensive integrated genomic analyses. DESIGN, SETTING, AND PARTICIPANTS: We collected 31 untreated snap-frozen UTUC samples from two institutions and carried out whole-exome sequencing (WES) of DNA, RNA sequencing (RNAseq), and protein analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Adjusting for batch effects, consensus mutation calls from independent pipelines identified DNA mutations, gene expression clusters using unsupervised consensus hierarchical clustering (UCHC), and protein expression levels that were correlated with relevant clinical variables, The Cancer Genome Atlas, and other published data. RESULTS AND LIMITATIONS: WES identified mutations in FGFR3 (74.1%; 92% low-grade, 60% high-grade), KMT2D (44.4%), PIK3CA (25.9%), and TP53 (22.2%). APOBEC and CpG were the most common mutational signatures. UCHC of RNAseq data segregated samples into four molecular subtypes with the following characteristics. Cluster 1: no PIK3CA mutations, nonsmokers, high-grade

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

The ZNF304-integrin axis protects against anoikis in cancer.

Ovarian cancer (OC) is a highly metastatic disease, but no effective strategies to target this process are currently available. Here, an integrative computational analysis of the Cancer Genome Atlas OC data set and experimental validation identifies a zinc finger transcription factor ZNF304 associated with OC metastasis. High tumoral ZNF304 expression is associated with poor overall survival in OC patients. Through reverse phase protein array analysis, we demonstrate that ZNF304 promotes multiple proto-oncogenic pathways important for cell survival, migration and invasion. ZNF304 transcriptionally regulates ß1 integrin, which subsequently regulates Src/focal adhesion kinase and paxillin and prevents anoikis. In vivo delivery of ZNF304 siRNA by a dual assembly nanoparticle leads to sustained gene silencing for 14 days, increased anoikis and reduced tumour growth in orthotopic mouse models of OC. Taken together, ZNF304 is a transcriptional regulator of ß1 integrin, promotes cancer cell survival and protects against anoikis in OC.

The Atlastin C-terminal tail is an amphipathic helix that perturbs the bilayer structure during endoplasmic reticulum homotypic fusion.

Fusion of tubular membranes is required to form three-way junctions found in reticular subdomains of the endoplasmic reticulum. The large GTPase Atlastin has recently been shown to drive endoplasmic reticulum membrane fusion and three-way junction formation. The mechanism of Atlastin-mediated membrane fusion is distinct from SNARE-mediated membrane fusion, and many details remain unclear. In particular, the role of the amphipathic C-terminal tail of Atlastin is still unknown. We found that a peptide corresponding to the Atlastin C-terminal tail binds to membranes as a parallel α helix, induces bilayer thinning, and increases acyl chain disorder. The function of the C-terminal tail is conserved in human Atlastin. Mutations in the C-terminal tail decrease fusion activity in vitro, but not GTPase activity, and impair Atlastin function in vivo. In the context of unstable lipid bilayers, the requirement for the C-terminal tail is abrogated. These data suggest that the C-terminal tail of Atlastin locally destabilizes bilayers to facilitate membrane fusion.

Genome-wide perturbations by miRNAs map onto functional cellular pathways, identifying regulators of chromatin modifiers.

BACKGROUND: Regulation of gene expression by microRNAs (miRNAs) is critical for determining cellular fate and function. Dysregulation of miRNA expression contributes to the development and progression of multiple diseases. miRNA can target multiple mRNAs, making deconvolution of the effects of miRNA challenging and the complexity of regulation of cellular pathways by miRNAs at the functional protein level remains to be elucidated. Therefore, we sought to determine the effects of expression of miRNAs in breast and ovarian cancer cells on cellular pathways by measuring systems-wide miRNA perturbations to protein and phosphoproteins. METHODS: We measure protein level changes by reverse-phase protein array (RPPA) in MDA-MB-231, SKOV3.ip1 and HEYA8 cancer cell lines transfected by a library of 879 human miRNA mimics. RESULTS: The effects of multiple miRNAs-protein networks converged in five broad functional clusters of miRNA, suggesting a broad overlap of miRNA action on cellular pathways. Detailed analysis of miRNA clusters revealed novel miRNA/cell cycle protein networks, which we functionally validated. De novo phosphoprotein network estimation using Gaussian graphical modeling, using no priors, revealed known and novel protein interplay, which we also observed in patient ovarian tumor proteomic data. We identified several miRNAs that have pluripotent activities across multiple cellular pathways. In particular we studied miR-365a whose expression is associated with poor survival across several cancer types and demonstrated that anti-miR-365 significantly reduced tumor formation in animal models. CONCLUSIONS: Mapping of miRNA-induced protein and phosphoprotein changes onto pathways revealed new miRNA-cellular pathway connectivity, paving the way for targeting of dysregulated pathways with potential miRNA-based therapeutics.

A switch in the source of ATP production and a loss in capacity to perform glycolysis are hallmarks of hepatocyte failure in advance liver disease.

BACKGROUND & AIMS: The cause of hepatic failure in the terminal stages of chronic injury is unknown. Cellular metabolic adaptations in response to the microenvironment have been implicated in cellular breakdown. METHODS: To address the role of energy metabolism in this process we studied mitochondrial number, respiration, and functional reserve, as well as cellular adenosine-5'-triphosphate (ATP) production, glycolytic flux, and expression of glycolysis related genes in isolated hepatocytes from early and terminal stages of cirrhosis using a model that produces hepatic failure from irreversible cirrhosis in rats. To study the clinical relevance of energy metabolism in terminal stages of chronic liver failure, we analyzed glycolysis and energy metabolism related gene expression in liver tissue from patients at different stages of chronic liver failure according to Child-Pugh classification. Additionally, to determine whether the expression of these genes in early-stage cirrhosis (Child-Pugh Class A) is related to patient outcome, we performed network analysis of publicly available microarray data obtained from biopsies of 216 patients with hepatitis C-related Child-Pugh A cirrhosis who were prospectively followed up for a median of 10years. RESULTS: In the early phase of cirrhosis, mitochondrial function and ATP generation are maintained by increasing energy production from glycolytic flux as production from oxidative phosphorylation falls. At the terminal stage of hepatic injury, mitochondria respiration and ATP production are significantly compromised, as the hepatocytes are unable to sustain the increased demand for high levels of ATP generation from glycolysis. This impairment corresponds to a decrease in glucose-6-phosphatase catalytic subunit and phosphoglucomutase 1. Similar decreased gene expression was observed in liver tissue from patients at different stages of chronic liver injury. Further, unbiased network analysis of microarray data revealed that expression of these genes was down regulated in the group of patients with poor outcome. CONCLUSIONS: An adaptive metabolic shift, from generating energy predominantly from oxidative phosphorylation to glycolysis, allows maintenance of energy homeostasis during early stages of liver injury, but leads to hepatocyte dysfunction during terminal stages of chronic liver disease because hepatocytes are unable to sustain high levels of energy production from glycolysis.

The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells.

Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network-based computational analysis of global gene expression data from matched sensitive and acquired drug-resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2-positive breast cancer patients. Further, forcing drug-sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.

GTP-dependent packing of a three-helix bundle is required for atlastin-mediated fusion.

The mechanisms governing atlastin-mediated membrane fusion are unknown. Here we demonstrate that a three-helix bundle (3HB) within the middle domain is required for oligomerization. Mutation of core hydrophobic residues within these helices inactivates atlastin function by preventing membrane tethering and the subsequent fusion. GTP binding induces a conformational change that reorients the GTPase domain relative to the 3HB to permit self-association, but the ability to hydrolyze GTP is required for full fusion, indicating that nucleotide binding and hydrolysis play distinct roles. Oligomerization of atlastin stimulates its ability to hydrolyze GTP, and the energy released drives lipid bilayer merger. Mutations that prevent atlastin self-association also abolish oligomerization-dependent stimulation of GTPase activity. Furthermore, increasing the distance of atlastin complex formation from the membrane inhibits fusion, suggesting that this distance is crucial for atlastin to promote fusion.

Membrane fusion by the GTPase atlastin requires a conserved C-terminal cytoplasmic tail and dimerization through the middle domain.

The biogenesis and maintenance of the endoplasmic reticulum (ER) requires membrane fusion. ER homotypic fusion is driven by the large GTPase atlastin. Domain analysis of atlastin shows that a conserved region of the C-terminal cytoplasmic tail is absolutely required for fusion activity. Atlastin in adjacent membranes must associate to bring the ER membranes into molecular contact. Drosophila atlastin dimerizes in the presence of GTPγS but is monomeric with GDP or without nucleotide. Oligomerization requires the juxtamembrane middle domain three-helix bundle, as does efficient GTPase activity. A soluble version of the N-terminal cytoplasmic domain that contains the GTPase domain and the middle domain three-helix bundle serves as a potent, concentration-dependent inhibitor of membrane fusion both in vitro and in vivo. However, atlastin domains lacking the middle domain are without effect. GTP-dependent dimerization of atlastin generates an enzymatically active protein that drives membrane fusion after nucleotide hydrolysis and conformational reorganization.

Fusing a lasting relationship between ER tubules.

Atlastin is an integral membrane GTPase localized to the endoplasmic reticulum (ER). In vitro and in vivo analyses indicate that atlastin is a membrane fusogen capable of driving membrane fusion, suggesting a role in ER structure and maintenance. Interestingly, mutations in the human atlastin-1 gene, SPG3A, cause a form of autosomal dominant hereditary spastic paraplegia (HSP). The etiology of HSP is unclear, but two predominant forms of the disorder are caused by mutant proteins that affect ER structure, formation and maintenance in motor neurons. In this review, we describe the current knowledge about the molecular mechanism of atlastin function and its potential role in HSP. Greater understanding of the function of atlastin and associated proteins should provide important insight into normal ER biogenesis and maintenance, as well as the pathology of disease.

Homotypic fusion of ER membranes requires the dynamin-like GTPase atlastin.

Establishment and maintenance of proper architecture is essential for endoplasmic reticulum (ER) function. Homotypic membrane fusion is required for ER biogenesis and maintenance, and has been shown to depend on GTP hydrolysis. Here we demonstrate that Drosophila Atlastin--the fly homologue of the mammalian GTPase atlastin 1 involved in hereditary spastic paraplegia--localizes on ER membranes and that its loss causes ER fragmentation. Drosophila Atlastin embedded in distinct membranes has the ability to form trans-oligomeric complexes and its overexpression induces enlargement of ER profiles, consistent with excessive fusion of ER membranes. In vitro experiments confirm that Atlastin autonomously drives membrane fusion in a GTP-dependent fashion. In contrast, GTPase-deficient Atlastin is inactive, unable to form trans-oligomeric complexes owing to failure to self-associate, and incapable of promoting fusion in vitro. These results demonstrate that Atlastin mediates membrane tethering and fusion and strongly suggest that it is the GTPase activity that is required for ER homotypic fusion.