Time-Lapse Imaging of Neuroblastoma Cells to Determine Cell Fate upon Gene Knockdown

Neuroblastoma is the most common extra-cranial solid tumor of early childhood. Standard therapies are not effective in case of poor prognosis and chemotherapy resistance. To improve drug therapy, it is imperative to discover new targets that play a substantial role in tumorigenesis of neuroblastoma. The mitotic machinery is an attractive target for therapeutic interventions and inhibitors can be developed to target mitotic entry, spindle apparatus, spindle activation checkpoint, and mitotic exit. We present an elaborate analysis pipeline to determine cancer specific therapeutic targets by first performing a focused gene expression analysis to select genes followed by a gene knockdown screening assay of live cells. We interrogated gene expression studies of neuroblastoma tumors and selected 240 genes relevant for tumorigenesis and cell cycle. With these genes we performed time-lapse screening of gene knockdowns in neuroblastoma cells. We classified cellular phenotypes and used the temporal context of the perturbation effect to determine the sequence of events, particularly the mitotic entry preceding cell death. Based upon this phenotype kinetics from the gene knockdown screening, we inferred dynamic gene functions in mitosis and cell proliferation. We identified six genes (DLGAP5, DSCC1, SMO, SNRPD1, SSBP1, and UBE2C) with a vital role in mitosis and these are promising therapeutic targets for neuroblastoma. Images and movies of every time point of all screened genes are available at https://ichip.bioquant.uni-heidelberg.de.

[1]  H. Varmus,et al.  Amplification of N-myc in untreated human neuroblastomas correlates with advanced disease stage. , 1984, Science.

[2]  P. Grambsch,et al.  A Package for Survival Analysis in S , 1994 .

[3]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[4]  T. Kanda,et al.  Histone–GFP fusion protein enables sensitive analysis of chromosome dynamics in living mammalian cells , 1998, Current Biology.

[5]  J. Sedivy,et al.  Mysterious liaisons: the relationship between c-Myc and the cell cycle , 1999, Oncogene.

[6]  M. Kitagawa,et al.  Cell cycle-dependent expression of mammalian E2-C regulated by the anaphase-promoting complex/cyclosome. , 2000, Molecular biology of the cell.

[7]  D. Hanahan,et al.  The Hallmarks of Cancer , 2000, Cell.

[8]  Junjie Chen,et al.  Cloning and Characterization of hCTF18, hCTF8, and hDCC1 , 2003, Journal of Biological Chemistry.

[9]  Chih-Jen Lin,et al.  Probability Estimates for Multi-class Classification by Pairwise Coupling , 2003, J. Mach. Learn. Res..

[10]  J. Tavaré,et al.  A role for glycogen synthase kinase-3 in mitotic spindle dynamics and chromosome alignment , 2003, Journal of Cell Science.

[11]  Bert Gunter,et al.  Improved Statistical Methods for Hit Selection in High-Throughput Screening , 2003, Journal of biomolecular screening.

[12]  G. Brodeur.  Neuroblastoma: biological insights into a clinical enigma , 2003, Nature Reviews Cancer.

[13]  Torsten Hothorn,et al.  On the Exact Distribution of Maximally Selected Rank Statistics , 2002, Comput. Stat. Data Anal..

[14]  B. Doble,et al.  GSK-3: tricks of the trade for a multi-tasking kinase , 2003, Journal of Cell Science.

[15]  T. Nilsen.  The spliceosome: the most complex macromolecular machine in the cell? , 2003, BioEssays : news and reviews in molecular, cellular and developmental biology.

[16]  Marina Pasca di Magliano,et al.  Hedgehog signalling in cancer formation and maintenance , 2003, Nature Reviews Cancer.

[17]  Douglas A. Hosack,et al.  Identifying biological themes within lists of genes with EASE , 2003, Genome Biology.

[18]  E. Rappaport,et al.  Germline PHOX2B mutation in hereditary neuroblastoma. , 2004, American journal of human genetics.

[19]  B. Baguley,et al.  In vitro modelling of human tumour behaviour in drug discovery programmes. , 2004, European journal of cancer.

[20]  C. Conrad,et al.  Automatic identification of subcellular phenotypes on human cell arrays. , 2004, Genome research.

[21]  G. Hampton,et al.  RNAi and HTS: exploring cancer by systematic loss-of-function , 2004, Oncogene.

[22]  Gordon K Smyth,et al.  Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2004, Statistical applications in genetics and molecular biology.

[23]  Patrick Warnat,et al.  Customized oligonucleotide microarray gene expression-based classification of neuroblastoma patients outperforms current clinical risk stratification. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[24]  G. Fang,et al.  HURP controls spindle dynamics to promote proper interkinetochore tension and efficient kinetochore capture , 2006, The Journal of cell biology.

[25]  H. Erfle,et al.  High-throughput RNAi screening by time-lapse imaging of live human cells , 2006, Nature Methods.

[26]  Wolfgang Huber,et al.  Analysis of cell-based RNAi screens , 2006, Genome Biology.

[27]  Thomas Lengauer,et al.  Improved scoring of functional groups from gene expression data by decorrelating GO graph structure , 2006, Bioinform..

[28]  Nathalie Harder,et al.  Automated Analysis of the Mitotic Phases of Human Cells in 3D Fluorescence Microscopy Image Sequences , 2006, MICCAI.

[29]  SaraAntonia Li,et al.  Mitotic kinases: the key to duplication, segregation, and cytokinesis errors, chromosomal instability, and oncogenesis. , 2006, Pharmacology & therapeutics.

[30]  H. Erfle,et al.  Reverse transfection on cell arrays for high content screening microscopy , 2007, Nature Protocols.

[31]  C. Bakal,et al.  Quantitative Morphological Signatures Define Local Signaling Networks Regulating Cell Morphology , 2007, Science.

[32]  Mark J. Murphy,et al.  Glycogen synthase kinase 3 in MLL leukaemia maintenance and targeted therapy , 2008, Nature.

[33]  Amy S. Espeseth,et al.  Genome-scale RNAi screen for host factors required for HIV replication. , 2008, Cell host & microbe.

[34]  B. Zhivotovsky,et al.  Death through a tragedy: mitotic catastrophe , 2008, Cell Death and Differentiation.

[35]  Shunichi Takeda,et al.  Single-stranded DNA-binding protein hSSB1 is critical for genomic stability , 2008, Nature.

[36]  Stephen S. Taylor,et al.  Cancer cells display profound intra- and interline variation following prolonged exposure to antimitotic drugs. , 2008, Cancer cell.

[37]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[38]  R. König,et al.  Global Analysis of Host-Pathogen Interactions that Regulate Early-Stage HIV-1 Replication , 2008, Cell.

[39]  J. Lieberman,et al.  Identification of Host Proteins Required for HIV Infection Through a Functional Genomic Screen , 2007, Science.

[40]  John M. Maris,et al.  Identification of ALK as a major familial neuroblastoma predisposition gene , 2008, Nature.

[41]  S. Pastorino,et al.  Glycogen synthase kinase-3 inhibition induces glioma cell death through c-MYC, nuclear factor-kappaB, and glucose regulation. , 2008, Cancer research.

[42]  Rainer König,et al.  Distinct transcriptional MYCN/c-MYC activities are associated with spontaneous regression or malignant progression in neuroblastomas , 2008, Genome Biology.

[43]  Chang-Young Jang,et al.  Aurora A regulates the activity of HURP by controlling the accessibility of its microtubule-binding domain. , 2008, Molecular biology of the cell.

[44]  A. Merlo,et al.  GSK3β Regulates Differentiation and Growth Arrest in Glioblastoma , 2009, PloS one.

[45]  Avi Ma'ayan,et al.  KEA: kinase enrichment analysis , 2009, Bioinform..

[46]  M. Harrison,et al.  Beyond taxanes: a review of novel agents that target mitotic tubulin and microtubules, kinases, and kinesins. , 2009, Clinical advances in hematology & oncology : H&O.

[47]  Aideen Long,et al.  Statistical methods for analysis of high-throughput RNA interference screens , 2009, Nature Methods.

[48]  C. Rudin,et al.  Smoothened Mutation Confers Resistance to a Hedgehog Pathway Inhibitor in Medulloblastoma , 2009, Science.

[49]  Amy S. Espeseth,et al.  Host Cell Factors in HIV Replication: Meta-Analysis of Genome-Wide Studies , 2009, PLoS pathogens.

[50]  Hui Gao,et al.  Smoothened as a new therapeutic target for human osteosarcoma , 2010, Molecular Cancer.

[51]  A. Fersht,et al.  Physical and functional interactions between human mitochondrial single-stranded DNA-binding protein and tumour suppressor p53 , 2008, Nucleic acids research.

[52]  Cheng-guang Huang,et al.  Knockdown of ubiquitin-conjugating enzyme E2C/UbcH10 expression by RNA interference inhibits glioma cell proliferation and enhances cell apoptosis in vitro , 2010, Journal of Cancer Research and Clinical Oncology.

[53]  P. Jallepalli,et al.  Cohesin acetylation speeds the replication fork , 2009, Nature.

[54]  William J. Godinez,et al.  Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time. , 2009, Genome research.

[55]  Florian Markowetz,et al.  How to Understand the Cell by Breaking It: Network Analysis of Gene Perturbation Screens , 2009, PLoS Comput. Biol..

[56]  Jan Koster,et al.  NF1 Is a Tumor Suppressor in Neuroblastoma that Determines Retinoic Acid Response and Disease Outcome , 2010, Cell.

[57]  R Eils,et al.  Comparison of performance of one-color and two-color gene-expression analyses in predicting clinical endpoints of neuroblastoma patients , 2010, The Pharmacogenomics Journal.

[58]  D. Hallahan,et al.  LABORATORY INVESTIGATION – HUMAN/ANIMAL TISSUE GSK-3b inhibition promotes cell death, apoptosis, and in vivo , 2022 .

[59]  Maria Kavallaris,et al.  Microtubules and resistance to tubulin-binding agents , 2010, Nature Reviews Cancer.

[60]  M. Boutros,et al.  Clustering phenotype populations by genome-wide RNAi and multiparametric imaging , 2010, Molecular systems biology.

[61]  Samuel Bernard,et al.  Tumor Growth Rate Determines the Timing of Optimal Chronomodulated Treatment Schedules , 2010, PLoS Comput. Biol..

[62]  I. Keklikoglou,et al.  Time-Resolved Human Kinome RNAi Screen Identifies a Network Regulating Mitotic-Events as Early Regulators of Cell Proliferation , 2011, PloS one.

[63]  K. Rohr,et al.  LARGE-SCALE TRACKING FOR CELL MIGRATION AND PROLIFERATION ANALYSIS AND EXPERIMENTAL OPTIMIZATION OF HIGH-THROUGHPUT SCREENS , 2011 .

[64]  Cynthia Winter,et al.  RNAi screen of the protein kinome identifies checkpoint kinase 1 (CHK1) as a therapeutic target in neuroblastoma , 2011, Proceedings of the National Academy of Sciences.

[65]  E. Attiyeh,et al.  Advances in the understanding of constitutional and somatic genomic alterations in neuroblastoma. , 2011, Cancer genetics.

[66]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[67]  N. Gray,et al.  Systematic Kinome shRNA Screening Identifies CDK11 (PITSLRE) Kinase Expression Is Critical for Osteosarcoma Cell Growth and Proliferation , 2012, Clinical Cancer Research.

[68]  M. Malumbres,et al.  Killing cells by targeting mitosis , 2012, Cell Death and Differentiation.