Journal: Cell reports

Article Title: AKT activation because of PTEN loss upregulates xCT via GSK3β/NRF2, leading to inhibition of ferroptosis in PTEN-mutant tumor cells

doi: 10.1016/j.celrep.2023.112536

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: SuperFi DNA polymerase , ThermoFisher , 12,351,010.

Techniques: Virus, Plasmid Preparation, Recombinant, cDNA Synthesis, Microarray, Gene Expression, Dominant Negative Mutation, Sequencing, CRISPR, Genome Wide, Software, Membrane, Autoradiography, SYBR Green Assay

Journal: Advances in Virus Research

Article Title: Functional Genomic Strategies for Elucidating Human–Virus Interactions

doi: 10.1016/bs.aivir.2015.11.001

Figure Lengend Snippet: Functional Genomic Screens for Elucidating Host–Viral Interactions

Article Snippet: Next, we stably transduced the H1-HeLa-Cas9 cells at a moi of 0.2 with a complex lentiviral pool expressing the human GeCKO v.2 sgRNA library (Addgene #1000000049), which targets 19,052 genes in the human genome with six sgRNAs per gene across two half-libraries (library A and B) ( ).

Techniques: Functional Assay, Virus, Knockdown, Selection, Biomarker Discovery, Suspension, Mutagenesis, Immunofluorescence, Microscopy, TALENs, Flow Cytometry, Comparison, CRISPR, Recombinant, Expressing, Luciferase, Disruption, Infection, Activity Assay, Inhibition, Western Blot, Genome Wide, In Vivo, Construct, Over Expression, Standard Deviation, Membrane, Staining, Viability Assay, In-Cell ELISA, Transfection, Immunoprecipitation, Control, Northern Blot, Fluorescence, Gene Expression, Microarray, Dominant Negative Mutation, Transmission Assay, Electron Microscopy, Transduction, Amplification, Clone Assay, Enzyme-linked Immunosorbent Assay, Modification, Two Hybrid Assay, Plaque Assay, Single Vesicle Fusion Assay, shRNA, Binding Assay, Sequencing, esiRNA, Glycoproteomics, Blocking Assay, Cell Cycle Assay, Ubiquitin Proteomics, Conjugation Assay, Plasmid Preparation, Mass Spectrometry, Reverse Transcription, Polymerase Chain Reaction

Journal: Advances in Virus Research

Article Title: Functional Genomic Strategies for Elucidating Human–Virus Interactions

doi: 10.1016/bs.aivir.2015.11.001

Figure Lengend Snippet: CRISPR/Cas9 screen for HRV host factors. (A) The HRV-HF CRISPR/Cas9 screen workflow showing the generation of the Cas9 expressing H1-HeLa cells containing the sgRNA libraries followed by their subsequent challenge with HRV14 and the assessment of the enriched sgRNAs using next-gen sequencing. (B) HeLa-H1-Cas9 cells were transduced with Moloney Leukemia virus (MLV)-GFP, then supra-transduced with either an empty vector control (parent population) or one expressing a sgRNA against GFP. The cells were selected for puromycin resistance and cultured for 11 days then fixed and imaged for GFP expression. Differential interference contrast (DIC) images are provided below. 4 × magnification. (C) DIC images of cells transduced with either library A or B that survived the HRV14 challenge were expanded and tested for their susceptibility to HRV14’s cytopathic effect over 2 days (bottom row) compared to the unselected parent cell population and the respective uninfected cell populations (top row). (D) Cells from (C) were fixed and immunostained for ICAM1 surface expression by flow cytometry. (E) A chart showing the relative proportion of total sequencing reads for the recovered sgRNAs from the HRV14 CRISPR/Cas9 pooled screen based upon the analysis of genomic DNA from the surviving cells from library A or B. Gene names are provided for each sgRNA with the associated numbers designating their unique identifying library number.

Article Snippet: Next, we stably transduced the H1-HeLa-Cas9 cells at a moi of 0.2 with a complex lentiviral pool expressing the human GeCKO v.2 sgRNA library (Addgene #1000000049), which targets 19,052 genes in the human genome with six sgRNAs per gene across two half-libraries (library A and B) ( ).

Techniques: CRISPR, Expressing, Sequencing, Transduction, Virus, Plasmid Preparation, Control, Cell Culture, Flow Cytometry

Journal: Cell reports

Article Title: AKT activation because of PTEN loss upregulates xCT via GSK3β/NRF2, leading to inhibition of ferroptosis in PTEN-mutant tumor cells

doi: 10.1016/j.celrep.2023.112536

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: GPX4 , abcam , ab125066; RRID:AB_10973901.

Techniques: Virus, Plasmid Preparation, Recombinant, cDNA Synthesis, Microarray, Gene Expression, Dominant Negative Mutation, Sequencing, CRISPR, Genome Wide, Software, Membrane, Autoradiography, SYBR Green Assay

Journal: Cell Reports Methods

Article Title: Applications of deep learning in understanding gene regulation

doi: 10.1016/j.crmeth.2022.100384

Figure Lengend Snippet: Genomic-level deep-learning applications

Article Snippet: DeepSEA , 2015 , ✓ , ✓ , ✓ , ✓ , , , • ENCODE o 125 DHS profiles o 690 TF binding profiles of 160 TFs • Roadmap Epigenomics o 104 histone modification profiles • HGMD (non-coding regulatory mutations) • GRASP (non-coding eQTLs) , • CNN (1 kb input) • multi-task learning , human , multiple.

Techniques: Variant Assay, Functional Assay, Binding Assay, Modification, Expressing, Transformation Assay, Gene Expression, Sequencing

Journal: Cell Reports Methods

Article Title: Applications of deep learning in understanding gene regulation

doi: 10.1016/j.crmeth.2022.100384

Figure Lengend Snippet: Proteomic- and phenotype-level deep-learning applications

Article Snippet: DeepSEA , 2015 , ✓ , ✓ , ✓ , ✓ , , , • ENCODE o 125 DHS profiles o 690 TF binding profiles of 160 TFs • Roadmap Epigenomics o 104 histone modification profiles • HGMD (non-coding regulatory mutations) • GRASP (non-coding eQTLs) , • CNN (1 kb input) • multi-task learning , human , multiple.

Techniques: Modification, Phospho-proteomics, Ubiquitin Proteomics, Sequencing, Binding Assay, Genome Wide, Microarray, Functional Assay, Selection

Journal: Cancer Cell International

Article Title: Prostate cancer in omics era

doi: 10.1186/s12935-022-02691-y

Figure Lengend Snippet: several of the ground-breaking PCa multi-omics research

Article Snippet: ICGC [ ] , Projects, including ICGC, TCGA, Johns Hopkins University, and the Tumor Sequencing Project, covering somatic mutations, CNV, structural rearrangements, gene expression, microRNAs, and DNA methylation data , Uses a web-based graphical user interface to provide researchers with a variety of options for searching and analyzing data, and to help them create complex searches across multiple data sets , http://dcc.icgc.org.

Techniques: Biomarker Discovery, Microarray, Next-Generation Sequencing, Functional Assay, Gene Expression, Sequencing, DNA Methylation Assay, Quantitative Proteomics, Mutagenesis, Genome Wide, Drug discovery, Clinical Proteomics

Journal: Blood Cancer Journal

Article Title: Lymphoid clonal hematopoiesis: implications for malignancy, immunity, and treatment

doi: 10.1038/s41408-022-00773-8

Figure Lengend Snippet: Summary of major studies associating L-CH with lymphoid malignancy.

Article Snippet: Terao et al. (2020) , Detection of mCAs in blood from one or more Infinium Human SNP Arrays , 179,417 individuals from the Biobank Japan cohort , Common mutational precursors of CLL (trisomy 12, 13q deletion, and 13q LOH) were less frequent in Japanese individuals compared to the UK Biobank cohort. Selective pressure for specific mCAs varies with genetic background, consistent with the lower rates of CLL and higher rates of T-cell leukemia in the Japanese. , [ ] .

Techniques: Genome Wide, Sequencing, Mutagenesis, Clone Assay, Biomarker Discovery, Microarray, DNA Sequencing, Clinical Proteomics

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: ( A ) TaqMan quantitative real-time PCR of APOBEC3B in ACCs in our cohort of adrenocortical tissue samples. Normal, n = 21; Benign, n = 69; ACC, n = 38. ( B ) APOBEC3B expression in publicly available microarray data from the GEO database, GSE10927. Normal, n = 10; ACA, n = 22; ACC, n = 33. The data were analyzed through GEO2R online software tool and all the data points were shown in Box-whiskers plots ( C ) APOBEC3B expression in another publicly available data from EMBL-EBI, E-TABM-311. Normal n = 4; ACA, n = 58; ACC, n = 34. * P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001. The author submitted normalized expression data were collected directly and all the data points were shown in Box-whiskers plots ( D ) Representative immunofluorescent staining images for APOBEC3B expression in adrenocortical tissues. DAPI is used to stain the cell nuclei for reference (magnification, 40×). TaqMan gene expression ( E ) and protein expression ( F ) of APOBEC3B in three adrenocortical carcinoma cell lines, BD140A, H295R, SW13, and normal human embryonic kidney cell line, HEK293. We used H295R and BD140 adrenocortical carcinoma cell lines for subsequent experiments as they are more representative of adrenocortical carcinomas.

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Real-time Polymerase Chain Reaction, Expressing, Microarray, Software, Staining, Gene Expression

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: Knockdown of APOBEC3B gene expression over time using two siRNAs targeting (A3Bsi1, A3Bsi2) both isoforms in BD140A ( A ) and H295R ( B ) cell lines by TaqMan quantitative real-time PCR. Percentage expression has been normalized to scrambled siRNA which was used as a negative control. The cell proliferation growth curve after transient transfection of two siRNAs in BD140A ( C ) and H295R ( D ) cell lines as measured by CyQuant assay. * P < 0.05; *** P < 0.001. Cell cycle analysis in BD140A ( E ) and H295R ( F ) cell lines after transient knockdown of APOBEC3B for 72 hours. The proportion of cells in each phase is represented as a percentage next to their corresponding peaks.

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Knockdown, Gene Expression, Real-time Polymerase Chain Reaction, Expressing, Negative Control, Transfection, CyQUANT Assay, Cell Cycle Assay

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: ( A ) Representative co-immunofluorescent staining images of APOBEC3B and γH2AX in normal, benign adrenocortical tumors and adrenocortical carcinoma. DAPI was used to stain the cell nuclei as a reference. (magnification, 40×) ( B ) The table represents the list and type of mutations within the TP53 gene that was screened in adrenocortical tumors using Sanger DNA sequencing. ( C ) The adrenocortical tumors were stratified into two groups (high and low expression levels) based on the median gene expression level of APOBEC3B and the average number of observed TP53 mutations in each patient was represented. The y-axis represents the sequencing data obtained from both forward and reverse strands for a given mutation. Error bar represents the standard error mean (SEM).

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Staining, DNA Sequencing, Expressing, Gene Expression, Sequencing, Mutagenesis

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: ( A ) Genome-wide CGH array representing cumulative copy number gain or loss for all chromosomes in adrenocortical carcinoma samples were dichotomized by the median gene expression level of APOBEC3B in the tumor samples. Red indicates the copy number loss while blue represents the copy number gain in a given chromosome. The columns represent each chromosome. Overall patient survival dichotomized based on the median gene expression level of APOBEC3B from two publicly available datasets; E-TABM-311 ( B ), GSE19776, ( C ) our cohort, ( D ) and the TCGA adrenocortical cancer data ( E ).

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Genome Wide, Gene Expression

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: ( A ) APOBEC3B gene expression (log2 fold change) analyzed in a functional screen of 92 cancer-associated transcription factors. ( B ) Independent validation of four candidates by TaqMan gene expression in H295R cells. Luciferase reporter assay under the control of APOBEC3B gene promoter after transient knockdown of GATA3 transcription factor with two different siRNAs in BD140A ( C ) and H295R ( D ) cell lines. ( E ) Overall patient survival dichotomized based on the median gene expression level of GATA3 from the TCGA adrenocortical cancer dataset.

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Gene Expression, Functional Assay, Biomarker Discovery, Luciferase, Reporter Assay, Control, Knockdown

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: APOBEC3B TCGA OS multivariate analysis

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques:

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: ( A ) Schematic representation of the GATA3 binding sites on the APOBEC3B promoter region. Arrows indicate the primer probes used for ChiP-PCR; TSS, transcription start site. ( B ) Agarose gel electrophoresis of SYBR green PCR products produced from site A and site B specific primer probes of APOBEC3B promoter region after chromatin immunoprecipitation (ChIP) with GATA3 antibody. Primers were also designed for Exon 5 of APOBEC3B where there are no putative binding sites for GATA3 as a negative control. RNApolII was used as a positive control for ChiP and housekeeping gene GAPDH was used for validation. Previously published GATA3 binding target, GCMB gene specific primers was used as a positive control for GATA3 ChiP antibody . A reaction mixture without template was used as a negative control for PCR. Fold enrichment of GATA3 binding sites A and B after ChIP with GATA3 antibody relative to immunoglobulin (IgG) antibody in BD140A ( C ) and H295R ( D ) cell lines. Luciferase reporter assay after transiently transfecting BD140A ( E ) and H295R ( F ) cell lines with wild-type, site A (G644C) and site B (C910G) mutants in the APOBEC3B promoter region.

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Binding Assay, Agarose Gel Electrophoresis, SYBR Green Assay, Produced, Chromatin Immunoprecipitation, Negative Control, Positive Control, Biomarker Discovery, Luciferase, Reporter Assay

Journal: Oncotarget

Article Title: GATA3 and APOBEC3B are prognostic markers in adrenocortical carcinoma and APOBEC3B is directly transcriptionally regulated by GATA3

doi: 10.18632/oncotarget.27703

Figure Lengend Snippet: ( A ) APOBEC3B protein expression in H295R cells stably transfected with four different shRNAs targeting APOBEC3B. shRNA 2 and shRNA 4 were selected for in vivo experiments based on the efficiency. ( B ) Tumor growth curve in NOD scid gamma (NSG) mice that received a vector control, APOBEC3B shRNA2, and 4 stably transfected H295R cells flanks on either side. A total of eight mice per each group were used for this study. Three of the control mice died in the first week after injection for unrelated reasons. The error bars represent the standard error mean (SEM). * Indicates p < 0.05. ( C ) The tumor weight of each group at the time of sacrifice (8 weeks after xenograft). ( D ) The isolated tumors from each group at the time of sacrifice.

Article Snippet: The mutations in the APOBEC3B promoter constructs were generated by site-directed mutagenesis of a wild-type (WT) human APOBEC3B promoter clone obtained from Switchgear genomics using QuickChange Site-directed mutagenesis kit from Stratagene (Santa Clara, CA, USA).

Techniques: Expressing, Stable Transfection, Transfection, shRNA, In Vivo, Plasmid Preparation, Control, Injection, Isolation

Journal: Blood Cancer Journal

Article Title: Lymphoid clonal hematopoiesis: implications for malignancy, immunity, and treatment

doi: 10.1038/s41408-022-00773-8

Figure Lengend Snippet: Summary of major studies associating L-CH with lymphoid malignancy.

Article Snippet: Niroula et al. (2021) , Detection of SNVs/indels in WES data at 56 M-CH related genes and 235 genes recurrently mutated in lymphoid malignancy (VAF > 2%). mCAs were previously detected in a prior study. CH and mCAs were excluded if they were detected less than 6 months before a hematologic malignancy diagnosis. , 420,969 individuals with SNP microarray data and 55,383 individuals with WES from the UK Biobank and Mass General Brigham Biobank , CHIP occurs at both M-CHIP/M-mCA and L-CHIP/L-mCA loci and increases with age. M-CH and L-CH loci clearly segregate on the incidence myeloid and lymphoid malignancy. M-CHIP is dominated by DNMT3A, TET2, and ASXL1 somatic mutants, while L-CHIP is spread more evenly across a large number of genes. CLL was the dominant lymphoid malignancy occurring subsequent to L-CH. , [ ] .

Techniques: Genome Wide, Sequencing, Mutagenesis, Clone Assay, Biomarker Discovery, Microarray, DNA Sequencing, Clinical Proteomics

Journal: Leukemia & lymphoma

Article Title: OVERCOMING MULTIPLE MYELOMA DRUG RESISTANCE IN THE ERA OF CANCER “OMICS”

doi: 10.1080/10428194.2017.1337115

Figure Lengend Snippet: “Omics” technologies used in preclinical and clinical studies

Article Snippet: By using molecular profiles to understand disease mechanisms, predict drug response and patient relapse, “omics” data can be used to guide pre-clinical drug development and tailor personalized treatments for each individual patient and disease. table ft1 table-wrap mode="anchored" t5 Table 1. caption a7 Omics Approach Omics Technology Source Material Readout Application Preclinical Clinical WGS, WES Genomics Genomic DNA (Germline) WGS: Sequence of entire chromosomal and mitochondrial DNA WES: Sequence of all exomes in genome Discover new mechanisms of drug resistance, biomarker discovery Patient risk stratification, predict response to therapy, guide therapeutic decisions Cancer genome sequencing Genomic DNA (Tumour) Mutational profile of cancer SNP array, CNV microarray Genomic DNA (Germline or Tumour) Unbiased association of genotype and phenotype Identification of genetic variation associated with response and/or adverse events to treatment RNA Seq, RNA microarray Transcriptomics mRNA (cDNA) Gene expression profile, disease associated genes, chemoresistance- associated genes Monitor changes in mutational landscape of cancer, predict response to therapy, guide therapeutic decisions Protein analysis by LC-MS/MS, SILAC-MS, ITRAQ-MS Proteomics Proteins Protein maps and predicted networks, disease-associated proteins, chemoresistance-associated proteins Predict treatment response, guide therapeutic decisions, monitor treatment response and relapse Metabolome analysis by LC-MS/MS, NMR, ion-mobility spectrometry, Raman spectroscopy Metabolomics Metabolites Metabolite profiles in cancer, tissues, and body fluids Genome-wide DNA methylation assays, miRNA array, Histone modification assays Epigenomics DNA, proteins DNA methylation, miRNAs, histone modifications High-throughput screen (knockdown/knockout shRNA/CRISPR-Cas9 screens, overexpression screens, drug screens) Genomics, Multi-omics Cells, proteins, embryo Phenotype (i.e. survival, proliferation, chemoresistance), biochemical, etc... NA Open in a separate window WGS: whole genome sequencing; WES: whole exome sequencing; SNP: single nucleotide polymorphism; CNV: copy number variant; LC-MS/MS: liquid chromatography-tandem mass spectrometry; miRNA: microRNA; NMR: nuclear magnetic resonance; shRNA: short hairpin RNA; CRISPR: clustered regularly interspaced short palindromic repeats “Omics” technologies used in preclinical and clinical studies Indeed, recent advances in high-throughput “omics” techniques afford us an unprecedented opportunity to understand drug resistance at the genomic, transcriptomic, and proteomic level.

Techniques: Sequencing, Biomarker Discovery, Microarray, RNA Sequencing, Gene Expression, Multiplex sample analysis, Ion-Mobility Spectrometry, Raman Spectroscopy, Genome Wide, DNA Methylation Assay, Modification, Knockdown, shRNA, Over Expression