High-throughput phenotyping of lung cancer somatic mutations [main experiment]
ABSTRACT: Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas using L1000 high-throughput gene-expression assays followed by expression-based variant impact phenotyping (eVIP), a method that uses gene expression changes to distinguish impactful from netural somatic mutations. This series represents the main experiment of the study where 8 replicates of wild-type and mutant ORFs are introduced into A549 cell lines. An ORF library containing wild-type and mutated versions of genes found to be mutated in lung cancer are introduced in A549 cell lines and measurements are made using the L1000 high-throughput gene-expression assay. These are done with 8 replicate experiemnts. The data are processed through a computational system, that converts raw fluorescence intensities into differential gene expression signatures. The data at each stage of the pre-processing are available: (LXB) - raw, unprocessed flow cytometry data from Luminex scanners. One LXB file is generated for each well of a 384-well plate, and each file contains a fluorescence intensity value for every observed analyte in the well. (Q2NORM) - gene expression profiles of directly measured landmark transcripts. Normalized using invariant set scaling followed by quantile normalization. (Z-SCORES) - signatures with differentially expressed genes computed by robust z-scores for each profile relative to control (relative to plate population as control)
Project description:Fresh tumor tissue from primary endometrial tumors. Technology: L1000 is an array based technology that measured 978 landmark genes that are extrapolated using an algorithm to generate a transcription profile of 12,328 genes. Reference L1000 technology: Subramanian A, et al. A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles. Cell. 2017/12/1. 171(6):1437–1452.
Project description:BACKGROUND AND PURPOSE:Targeted therapy and immunotherapy have led to dramatic change in the treatment of lung cancer, however, the overall 5-year survival rate of lung cancer patients is still suboptimal. It is important to exploit new potential of molecularly targeted therapies. High-frequency somatic mutations in KEAP1/NRF2 (27.9%) have been identified in lung squamous cell carcinoma. In this research, we explored the role of KEAP1 somatic mutations in the development of LSCC and whether a nuclear factor erythroid 2-related factor 2(NRF2) inhibitor be potential to target lung cancer carrying KEAP1/NRF2 mutations. METHODS:Lung cancer cell lines A549 and H460 with loss-of-function mutations in KEAP1 stably transfected with wild-type (WT) KEAP1 or somatic mutations in KEAP1 were used to investigate the functions of somatic mutations in KEAP1. Flow cytometry, plate clone formation experiments, and scratch tests were used to examine reactive oxygen species, proliferation, and migration of these cell lines. RESULTS:The expression of NRF2 and its target genes increased, and tumor cell proliferation, migration, and tumor growth were accelerated in A549 and H460 cells stably transfected with KEAP1 mutants compared to control cells with a loss-of-function KEAP1 mutation and stably transfected with WT KEAP1 in both in vitro and in vivo studies. The proliferation of A549 cell line trasfected with the R320Q KEAP1 mutant was inhibited more apparent than that of the A549 cell line trasfected with WT KEAP1 after treatment with NRF2 inhibitor ML385. CONCLUSION:Somatic mutations of KEAP1 identified from patients with LSCC likely promote tumorigenesis mediated by activation of the KEAP1/NRF2 antioxidant stress response pathway. NRF2 inhibition with ML385 could inhibit the proliferation of tumor cells with KEAP1 mutation. Video abstract.
Project description:Somatic mosaicism for DNA copy number alterations (SMC-CNA) is defined as gain or loss of chromosomal segments in mitotic cells within a single organism. As cells harboring SMC-CNA have the potential to undergo clonal expansion, SMC-CNA may be present in a substantial portion of cells in differentiated human tissues and may contribute to the predisposition of these cells to genetic disease including cancer. We characterized gross genomic alterations (>500 kbp) in uninvolved glandular tissue from 59 breast cancer patients and matched samples of primary tumors and lymph node metastases. Array based comparative genomic hybridization experiments showed 10% (6/59) of patients harbored 1 - 359 large SMC-CNA (mean: 1328 kbp; median: 961 kbp) in uninvolved glandular tissue. SMC-CNA were partially recurrent in tumors, albeit with considerable contribution of stochastic SMC-can, indicating genomic destabilization. Therefore, we hypothesized that the observed genomic destabilization is predetermined by mutations in genes related to maintenance of genomic integrity. Targeted resequencing of 301 known predisposition and somatic driver loci revealed mutations in the following genes: BRCA1 (p.Gln1756Profs*74, p.Arg504Cys), BRCA2 (p.Asn3124Ile), NCOR1 (p.Pro1570Glnfs*45), PALB2 (p.Ser500Pro) and TP53 (p.Arg306*). We demonstrated that gross SMC-CNA may be present in a substantial portion of glandular tissue cells, which are distant from that of the tumor cells, and may co-occur with point mutations in crucial cancer predisposing or somatic driver genes. Taken together, this highlights temporal and spatial neoplastic potential of uninvolved glandular tissue from breast cancer patients.
Project description:A Cartes d'Identite des Tumeurs (CIT) project from the french Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net: Anaplastic oligodendrogliomas (AOs) are rare primary brain tumors which are generally incurable with few treatment targets identified. Most oligodendrogliomas have chromosome 1p/19q co-deletion and IDH mutation. We analyzed 51 AOs by whole-exome and/or transcriptome sequencing identifying previously reported frequent somatic mutations in CIC and FUBP1 genes. We also identified recurrent mutations in TCF12 (11% of IDHmut-codel) which encodes basic helix-loop-helix (bHLFH) transcription factor 12 which is an oligodendrocyte-related transcription factor in IDHmut-codel tumors. Strikingly, the somatic mutations (encoding E548R and R602M substitutions) have not been reported previously in cancer but are identical to germline mutations causing craniosynostosis. Incorporating TCGA data on 43 AO tumors also implicates functional mutation of SMARCA4, NOTCH1, NOTCH2, SETD2, RBPJ and ARID1A/1B. These data are compatible with the combined deregulation of metabolism, chromatin organization/remodeling and Notch-pathway genes in AO oncogenesis. Our analysis provides further insights into the unique and shared pathways driving AO and new targets for therapeutic intervention.
Project description:Inactivation of the tumor suppressor protein Merlin leads to the development of benign nervous system tumors in neurofibromatosis type2 (NF2). Documented causes of Merlin inactivation include deleterious mutations in the encoding neurofibromin2 gene (NF2) and aberrant Merlin phosphorylation leading to proteasomal degradation. Rare somatic NF2 mutations have also been detected in common human malignancies not associated with NF2, including colorectal and lung cancer. Furthermore, tumors without NF2 mutations and with unaltered NF2 transcript levels, but with low Merlin expression, have been reported. The present study demonstrated that NF2 is also regulated by microRNAs (miRNAs) through direct interaction with evolutionarily conserved miRNA response elements (MREs) within its 3'?untranslated region (3'UTR). Dual?Luciferase assays in human colorectal carcinoma (HCT116) and lung adenocarcinoma (A549) cells revealed downregulation of NF2 by miR?92a?3p via its wild?type 3'UTR, but not NF2?3'UTR with mutated miR?92a?3p MRE. HCT116 cells overexpressing miR?92a?3p exhibited significant downregulation of endogenous NF2 mRNA and protein levels, which was rescued by co?transfection of a target protector oligonucleotide specific for the miR?92a?3p binding site within NF2?3'UTR. miR?92a?3p overexpression in HCT116 and A549 cells promoted migration, proliferation and resistance to apoptosis, as well as altered F?actin organization compared with controls. Knockdown of NF2 by siRNA phenocopied the oncogenic effects of miR?92a overexpression on HCT116 and A549 cells. Collectively, the findings of the present study provide functional proof of the unappreciated role of miRNAs in NF2 regulation and tumor progression, leading to enhanced oncogenicity.
Project description:Retinoblastoma (RB, OMIM:180200) is the most common malignant childhood tumor of the eye with an estimated incidence between 1 in 16,000 and 1 in 18,000 live births [1,2]. RB is the first disease for which a genetic etiology of cancer has been described  being caused by mutations in the first tumor suppressor gene identified (RB1, Genbank accession # L11910). Mutations in both alleles of the RB1 gene are required for the development of this neoplasm , and, depending on the germ-line or somatic origin of the defect, a heritable or sporadic form can be distinguished. RB is unilateral in 60% of cases and only 15% of these are heritable ; in contrast, 40% of retinoblastomas are bilateral with risk of transmission to the offspring. Heritable retinoblastoma constitutes a cancer predisposition syndrome . RB1 is located on chromosome 13 at band q14 and can be affected by a heterogeneous spectrum of genetic abnormalities, including chromosome translocation/deletion, genomic rearrangements, ranging from whole gene microdeletion to intragenic exons loss or duplication, and more than 900 different point mutations . Mutational analysis is performed to search for the predisposing RB1 gene mutation in peripheral blood of patients with RB, but the molecular diagnosis requires several technical approaches to cover the entire field of oncogenic RB1 defects, frequently resulting in numerous, expensive and time consuming procedures. In particular, cytogenetic tools, such as classical chromosome investigations and Fluorescent In Situ Hybridization (FISH), in addition to Multiplex Ligation-dependent Probe Amplification (MLPA) technique, may account for detection of about 16% of RB1 abnormalities , while the remaining large amount of point mutations need to be investigated using sequencing analysis. Since the 1970s, Sanger sequencing has been recognized as the gold standard for mutation analysis in molecular diagnostics; however, its low-throughput, long turnaround time and overall cost  have called for new paradigms. Next Generation Sequencing (NGS) can massively sequence millions of DNA segments, promising low costs, increased workflow speed and enhanced sensitivity in mutation detection [9,10,11] On the other hand, conventional and molecular cytogenetic analysis, have been replaced by modern high-throughput investigations, such as array Comparative Genomic Hybridization (aCGH), that can reveal and measure cryptic genomic imbalances. In addition, aCGH can be focused on specific DNA segments or genes maximizing the resolution via a customized process. Based on these observations, we have recruited a cohort of retinoblastoma patients we previously investigated with conventional cytogenetics and MLPA. Patients diagnosed with RB but negative to the above standard screening have been tested with NGS to assess its ability in identifying RB causative mutations. On the other hand, patients positive to standard screening have been further investigated with RB1-custom array CGH analysis to characterize the genomic rearrangements with a better resolution compared to the conventional techniques. The complementary aCGH data set related to this study has also been deposited at ArrayExpress, under accession number E-MTAB-3492: https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3492/
Project description:Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with prognosis and clinical outcomes. Next-generation sequencing was used to reveal the mitochondrial genomes of tumor and conditionally normal adjacent tissues from 61 Stage 1 LUADs. Mitochondrial somatic mutations and clinical outcomes including relapse-free survival (RFS) were analyzed. Patients with somatic mutations in the D-loop region had longer RFS (adjusted hazard ratio, adjHR = 0.18, p = 0.027), whereas somatic mutations in mitochondrial Complex IV and Complex V genes were associated with shorter RFS (adjHR = 3.69, p = 0.012, and adjHR = 6.63, p = 0.002, respectively). The risk scores derived from mitochondrial somatic mutations were predictive of RFS (adjHR = 9.10, 95%CI: 2.93-28.32, p < 0.001). Our findings demonstrated the vulnerability of the mitochondrial genome to mutations and the potential prediction ability of somatic mutations. This research may contribute to improving molecular guidance for patient treatment in precision medicine.
Project description:BACKGROUND:Most methods that integrate network and mutation data to study cancer focus on the effects of genes/proteins, quantifying the effect of mutations or differential expression of a gene and its neighbors, or identifying groups of genes that are significantly up- or down-regulated. However, several mutations are known to disrupt specific protein-protein interactions, and network dynamics are often ignored by such methods. Here we introduce a method that allows for predicting the disruption of specific interactions in cancer patients using somatic mutation data and protein interaction networks. METHODS:We extend standard network smoothing techniques to assign scores to the edges in a protein interaction network in addition to nodes. We use somatic mutations as input to our modified network smoothing method, producing scores that quantify the proximity of each edge to somatic mutations in individual samples. RESULTS:Using breast cancer mutation data, we show that predicted edges are significantly associated with patient survival and known ligand binding site mutations. In-silico analysis of protein binding further supports the ability of the method to infer novel disrupted interactions and provides a mechanistic explanation for the impact of mutations on key pathways. CONCLUSIONS:Our results show the utility of our method both in identifying disruptions of protein interactions from known ligand binding site mutations, and in selecting novel clinically significant interactions. Supporting website with software and data: https://www.cs.cmu.edu/~mruffalo/mut-edge-disrupt/ .
Project description:Single cells from ML-DS sample 186-2 (bone marrow) were analysed to determine whether mutations in JAK2 and CSF2RB ocurred in the same or different cells in this patient. Single live, CD19neg, CD3neg, CD45mid and CD117 positive cells were sorted into 96-well plates on the BD Fusion with antibodies as described above. Cord blood single cells were sorted similarly to serve as a control for the single cell Sequencing.