Slideshow is from the University of Michigan Medical School's M1 Patients and Populations: Medical Genetics Sequence.
View additional course materials on Open.Michigan:
openmi.ch/med-M1PatientsPopulations
Relative fitness contribution of BoLA alleles in T.parva immune cattle: inter...ILRI
Poster prepared by Obara, I., Odongo, D., Kemp, S.J., Seitzer U. and Bishop, R. at the Follow-Up Conference “German-African Cooperation Projects in Infectology”, Bonn, 28–30 June 2012
Slideshow is from the University of Michigan Medical School's M1 Patients and Populations: Medical Genetics Sequence.
View additional course materials on Open.Michigan:
openmi.ch/med-M1PatientsPopulations
Relative fitness contribution of BoLA alleles in T.parva immune cattle: inter...ILRI
Poster prepared by Obara, I., Odongo, D., Kemp, S.J., Seitzer U. and Bishop, R. at the Follow-Up Conference “German-African Cooperation Projects in Infectology”, Bonn, 28–30 June 2012
Development of a next-generation (NGS) assay for pediatric, childhood, and yo...Thermo Fisher Scientific
The study of recurrent somatic alterations associated with pediatric, childhood and young adult cancers has lagged behind those that associated with adult cancers. Whole exome and transcriptome approaches are still being used to support discovery efforts, consequently, due to several initiatives aimed at profiling genomic alterations associated with childhood cancers, a set of recurrent somatic alterations has been defined.
Comparative analysis of gene regulation in mouse rat and humanconstantina mylona
Which is the most suitable model mouse or rat even in the use of the latest gene editing tool-CRISPR/Cas 9 ?
Final Project presentaion on BSc Human Biology
In Search of Better Tools and Capabilities
"We need to do more with less." This is a common theme we hear in our conversations and follow up with Researchers in early phase drug discovery.
To us this translates into better identification and more intense screening of potential therapeutic compounds and targets. Failure is success if it is determined before animal testing.
The foundation being potent, pure and easy to culture primary cells. Then building on the platform with the required media/growth factors, markers, transfection reagents and apoptosis detection kits.
Identification of Rare and Novel Alleles in FFPE Tumor Samples | ESHG 2015 Po...Thermo Fisher Scientific
Tumors are becoming recognized as genetically heterogeneous masses of cells with different clonal histories. Identifying the mutations present in these heterogeneous masses can lead to important insights into the future behavior of the tumor and possible intervention mechanisms. However, the rarity of pathogenic mutations in small subsets of cells can make identification of such alleles difficult. In this study, we demonstrate a complete workflow that facilitates the identification of rare and novel alleles from FFPE tumor sections. We collected small regions with different cellular morphologies from lung tumor samples using laser capture microdissection, extracted both DNA and RNA from these regions, and characterized mutations present and transcript abundances by using Ion AmpliSeq™ targeted sequencing. We show that LCM facilitates the detection of alleles that are not detectable in macrodissected tissue scrapes. We also show that different regions of a tumor have very different patterns of alleles detectable and have a great deal of genetic diversity. Finally, we show that RNA expression patterns are also clearly different in the different regions. Interestingly, dissected regions with similar gross tissue morphologies display differences in alleles present and RNA expression patterns. These results suggest how we may in the future use this method to analyze mutations present in a tumor is to microdissect different subregions of the tumor, and using Ion AmpliSeq™ panels to identify the alleles present in those subregions.
Development of a next-generation (NGS) assay for pediatric, childhood, and yo...Thermo Fisher Scientific
The study of recurrent somatic alterations associated with pediatric, childhood and young adult cancers has lagged behind those that associated with adult cancers. Whole exome and transcriptome approaches are still being used to support discovery efforts, consequently, due to several initiatives aimed at profiling genomic alterations associated with childhood cancers, a set of recurrent somatic alterations has been defined.
Comparative analysis of gene regulation in mouse rat and humanconstantina mylona
Which is the most suitable model mouse or rat even in the use of the latest gene editing tool-CRISPR/Cas 9 ?
Final Project presentaion on BSc Human Biology
In Search of Better Tools and Capabilities
"We need to do more with less." This is a common theme we hear in our conversations and follow up with Researchers in early phase drug discovery.
To us this translates into better identification and more intense screening of potential therapeutic compounds and targets. Failure is success if it is determined before animal testing.
The foundation being potent, pure and easy to culture primary cells. Then building on the platform with the required media/growth factors, markers, transfection reagents and apoptosis detection kits.
Identification of Rare and Novel Alleles in FFPE Tumor Samples | ESHG 2015 Po...Thermo Fisher Scientific
Tumors are becoming recognized as genetically heterogeneous masses of cells with different clonal histories. Identifying the mutations present in these heterogeneous masses can lead to important insights into the future behavior of the tumor and possible intervention mechanisms. However, the rarity of pathogenic mutations in small subsets of cells can make identification of such alleles difficult. In this study, we demonstrate a complete workflow that facilitates the identification of rare and novel alleles from FFPE tumor sections. We collected small regions with different cellular morphologies from lung tumor samples using laser capture microdissection, extracted both DNA and RNA from these regions, and characterized mutations present and transcript abundances by using Ion AmpliSeq™ targeted sequencing. We show that LCM facilitates the detection of alleles that are not detectable in macrodissected tissue scrapes. We also show that different regions of a tumor have very different patterns of alleles detectable and have a great deal of genetic diversity. Finally, we show that RNA expression patterns are also clearly different in the different regions. Interestingly, dissected regions with similar gross tissue morphologies display differences in alleles present and RNA expression patterns. These results suggest how we may in the future use this method to analyze mutations present in a tumor is to microdissect different subregions of the tumor, and using Ion AmpliSeq™ panels to identify the alleles present in those subregions.
Tumor Mutational Load assessment of FFPE samples using an NGS based assayThermo Fisher Scientific
Understanding the molecular determinants of response to immune checkpoint blockade inhibitors is a critical unmet need for translational oncology research. Research tools to characterize the mutational landscape of cancers may potentially help identify predictive biomarkers for immuno-therapy that can be tested in future studies. Herein, we describe a targeted Ion AmpliSeq assay to determine the mutational load and signature of cancer research samples.
Hotspot mutation and fusion transcript detection from the same non-small cell...Thermo Fisher Scientific
The presence of certain chromosomal Header
rearrangements and the subsequent fusion
gene derived from translocations has been
implicated in a number of cancers. Hundreds of
translocations have been described in the
literature recently but the need to efficiently
detect and further characterize these
chromosomal translocations is growing
exponentially. The two main methods to identify
and monitor translocations, fluorescent in situ
hybridization (FISH) and comparative genomic
hybridization (CGH) are challenging, labor
intensive, the information obtained is limited,
and sensitivity is rather low. Common sample
types for these analyses are biopsies or small
tumors, which are very limited in material
making the downstream measurement of more
than one analyte rather difficult; obtaining
another biopsy, using a different section or
splitting the sample can raise issues of tumor
heterogeneity. The ability to study mutation
status as well as measuring fusion transcript
expression from the same sample is powerful
because you’re maximizing the information
obtained from a single precious sample and
eliminating any sample to sample variation.
Here we describe the efficient isolation of two
valuable analytes, RNA and DNA, from the
same starting sample without splitting, followed
by versatile and informative downstream
analysis. This methodology has been applied to
FFPE and degraded samples as well as fresh
tissues, cells and blood. DNA and RNA were
recovered from the same non-small cell lung
adenocarcinoma sample and both mutation
analysis, as well as fusion transcript detection
was performed using the Ion Torrent PGM™
platform on the same Ion 318™ chip. Using
10ng of DNA and 10ng of RNA input, we
applied the Ion AmpliSeq™ Colon and Lung
Cancer panel to analyze over 500 COSMIC
mutations in 22 genes and the Ion AmpliSeq™
RNA Lung Fusion panel to detect 40 different
fusion transcripts.
PROKARYOTIC TRANSCRIPTOMICS AND METAGENOMICSLubna MRL
After billions of years of evolution, prokaryotes have developed a huge diversity of regulatory mechanisms, many of which are probably uncharacterized. Now that the powerful tool of whole-transcriptome analysis can be used to study the RNA of bacteria and archaea, a new set of un expected RNA-based regulatory strategies might be revealed.
Metagenomics, together with in vitro evolution and high-throughput screening technologies, provides industry with an unprecedented chance to bring biomolecules into industrial application.
The Main Advantage
The main advantages of flow cytometry over histology and IHC is the possibility to precisely measure the quantities of antigens and the possibility to stain each cell with multiple antibodies-fluorophores, in current laboratories around 10 antibodies can be bound to each cell. This is much less than mass cytometer where up to 40 can be currently measured, but at a higher and slower pace.
Aquatic research
In aquatic systems, flow cytometry is used for the analysis of autofluorescing cells or cells that are fluorescently-labeled with added stains.
This research started in 1981 when Clarice Yentsch used flow cytometry to measure the fluorescence in a red tide producing dinoflagellates
Marine scientists use the sorting ability of flow cytometers to make discrete measurements of cellular activity and diversity, to conduct investigations into the mutualistic relationships between microorganisms that live in close proximity,and to measure biogeochemical rates of multiple processes in the ocean
Cell Proliferation assay
Cell proliferation is the major function in the immune system. Often it is required to analyse the proliferative nature of the cells in order to make some conclusions. One such assay to determine the cell proliferation is the tracking dye carboxyfluorescein diacetate succinimidyl ester (CFSE). It helps to monitor proliferative cells. This assay gives quantitative as well as qualitative data during time-series experiments
Cell counting
Cell sorting
Determining cell characteristics and function
Detecting microorganisms
Biomarker detection
Protein engineering detection
Diagnosis of health disorders such as blood cancers
Flow cytometry can be used for cell cycle analysis to estimate the percentages of a cell population in the different phases of the cell cycle, or it can be used with other reagents to analyze just the S phase.
Why flow cytometry is ideal for cell cycle analysis
Live-cell cycle analysis stains—Vybrant DyeCycle stains
Classic DNA cell cycle stains such as Hoechst 33342 and DRAQ5 for cell cycle analysis, but most of these have limitations that have to be considered when using them in an experiment which is why the Invitrogen Vybrant DyeCycle stains for live-cell cycle analysis were developed.
Fixed-cell cycle analysis stains FxCycle reagents
We offer classic DNA cell cycle stains such as DAPI, PI, and 7-AAD for fixed cell cycle analysis, but these reagents do not cover the full spectrum of laser excitation available.
The FxCycle reagents offer options for the 405 nm (violet) and 633 nm (red) laser thereby increasing the ability to multiplex by freeing up the 488 nm and 633 nm lasers for other cellular analyses such as immunophenotyping, apoptosis analysis, and dead cell discrimination.
Precise—Accurate cell cycle analysis in living cells
Safe—Low cytotoxicity for combining with additional live cell experiments
Cell sort compatible—Easily sort cells based on phase of the cell cycle
1. Profiles of Contributing genes to sensitive/resistant PhenotyPe of 11 Different
onCology theraPeutiC agents aCross 240 Cell lines.
O’Day, C., Ovechkina, Y., Marcoe, K.F., Keyser, R., Yoshino, K., Nguyen, P., Hnilo, J., Shively, R., Mulligan, J., Bernards, K., Chesnut-Speelman, J., Lin, T., and Wang, S.
Ricerca Biosciences LLC – Bothell, WA, USA
PurPose Figure 2. CVs in the nuclear channel were low. The CV of control wells was averaged over 3 independent
experiments. Overall, 91% of cell lines had a CV of less than 20% and only 11 non-adherent cells had
Figure 4: Sensitive and resistant cell lines to Erlotinib with genetic biomarkers. Figure 7: Sensitive and resistant cell lines to VX-680 with genetic biomarkers.
a CV greater than 25%. The log of the difference from the average IC50 value was plotted against the 240 cell lines. Kras mutations correlated The log of the difference from the average EC50 is plotted against the various cell lines. CTTNB1 mutations predominate
A number of targeted therapies have been shown to be effective in the treatment of cancer, such as Imatinib for
with resistance. Genetic analysis of mRNA data was not complete, but the few known cell lines that overexpress EGFR in the most sensitive cells lines and tended to be of colon/GI origin. Those cell lines with CTTNB1 mutations that were
treating chronic myelogenous leukemia, Erlotinib for non-small-cell lung cancers and Sorefinib for metastatic lung
All cells were grouped according to morphology and the CVs of the control wells were averaged and binned according were identified as sensitive. Cell lines with EGFR mutations that were not sensitive also had mutations in the Ras/Raf resistant were not of colon origin. APC mutations tended to be intermediate/resistant with no APC mutations in the 50
cancer. The sporadic sensitivity to these therapeutic agents has launched an investigation of correlation between
to the range of CVs: a) adherent cells; b) semi-adherent cells; c) non-adherent cells. pathway. most sensitive cell lines.
cancer phenotype and genotype. We have developed an in vitro cellular assay to evaluate the relationship between
tumor genotypes (Affymetrix SNP and gene expression chips and Sanger mutation data) and cancer cell sensitivity a) b) c)
for over 240 human tumor cell lines. A panel of targeted therapeutics was used to show the usefulness of this in vitro
approach for developing anticancer drugs. Data for nine of the eleven evaluated therapeutics is shown below. Data
was not shown for Staurosporine, Paclitaxel or Doxorubicin in the interest of space. Stomach
Lung Liver Endocrine
and colon
MethoDs
Growth and assay conditions were established for all 240 cell lines. Compounds were added in half-log dilutions for 10
concentrations using tipless acoustic transfer with an Echo 550. An additional “time zero” (T0) plate also was seeded
at the same density and analyzed for cell number on day one to determine the number of doublings. Seventy-two Table 2: Panel of mutations generated from Sanger Database
hours after compound addition, the cells were fixed and stained with antibodies for activated caspase-3 and phospho-
histone H3. Nuclei were stained with DAPI. Cells were imaged with a 4X objective on an IN Cell Image Analyzer and All cell lines were analyzed for:
analyzed with the Developer software tool. Data was plotted with in-house Math IQ graphing software using nonlinear 1. Mutation data (Available on most cell lines. Twenty two % of the cell lines did
regression analysis. Data was analyzed for cell count (% of control), fold induction of apoptosis (% of control) and fold not have mutation data.)
induction or decrease in G2 (% of control). All data was normalized to control wells. Reference compound data was 2. SNP analysis (Affymetrix SNP 500K array)
analyzed and pooled. Cell lines were binned to sensitive and resistant lines based on acceptable in vivo dosage levels
3. Gene expression data (Affymetrix U133 plus 2.0 array) Figure 5: Sensitive and resistant cell lines to CL-1040 with genetic biomarkers.
or a marked delineation of sensitivity. Sensitive and resistant cell lines were then correlated to mutation spectrums to
determine genes underlying the corresponding phenotype (Fig.1). Mutation data was used to analyze these cell lines.
Table 3: Colon/GI cancers with CTNNB1 mutations
are sensitive to Aurora inhibition.
ConClusions
Genetic data was generated in house, through the CABIG site and the Sanger site. All data
Analysis of expression and SNP data is currently underway. was normalized through RMA normalization Gene copy number and mRNA expression data. The log of the difference from the average EC50 value was plotted against the various cell lines. Ras/Raf mutations CTNNB1 mutations made up 4 of the 5 most sensitive cell
predominated in the sensitive cells and RB mutations conferred resistance. The one Braf mutation that was not sensitive, Summary of Erlotinib
https://cabig.nci.nih.gov/caArray_GSKdata/ lines in the 32 colon/GI cancers shown below. B-catenin
Figure 1: Assay Workflow harbored a G464V mutation rather than the activating V600E mutation. • Kras mutations confer resistance to treatment
50+ Gene Mutation data mRNA levels are being examined for over-expression.
• 3 EGFR mutations were present in the 240 cell lines. One was sensitive
http://www.sanger.ac.uk/genetics/CGP/Celllines APC mutations predominate in the resistant cells but and the two others were intermediate/resistant because of Ras/Raf
“The mutation data was obtained from the Sanger Institute Catalogue Of Somatic Mutations In
G464V
APC mutations are thought to be mutually exclusive mutations
Cancer web site, http://www.sanger.ac.uk/cosmic Bamford et al (2004) The COSMIC (Catalogue of CTNNB1 mutations. Other genes found through
of Somatic Mutations in Cancer) database and website. Br J Cancer, 91,355-358.”
expression analysis might give a more complete picture Summary of CL-1040
of this sensitivity. Braf mutations clearly predominate in the sensitive cell lines
Figure 3: Distribution plot of sensitive and resistant cell lines. • 15 of the 30 most sensitive cell lines had Braf mutations
• None of the 30 most resistant cell lines had Braf mutations
• One somewhat resistant Braf mutation was a G464V rather than the
EC50 values were plotted against IC50 values for many of the 240 cell lines. For some agents that generated typical V600E mutation
incomplete growth inhibition (GI), GI50 values or max % growth inhibition was plotted against the EC50 values (Fig. Ras mutations had a positive correlation with sensitive cells but weaker
3a. and i). Sensitive cell lines were selected by a clear demarcation from the others such as in figures 3b, c, e, f, and Sensitive than Braf
g. For Geldanamycin (Fig. 3d) all cell lines responded over a small range but a few were resistant. For Dasatinib • All of the 30 most sensitive cell lines contained Braf or Ras mutations
(Fig. 3c) CML lines were most sensitive. However, a subset of the cell lines did not demonstrate good growth • 1 out of the 30 most resistant cell lines had a Ras mutation
Rb mutations appear exclusively in the resistant cell lines
inhibition when results were adjusted for the number of cells plated. Similarly, with Everolimus (Fig 3a) two groups
• 8 of the 30 most resistant cell lines had a Rb mutation
of sensitive and resistant cells were apparent but of the sensitive lines, some showed poor growth inhibition when
• 0 of the 30 most sensitive cell lines had a Rb mutation
results were adjusted for the number of cells plated. CL-1040 did not show a clear demarcation between sensitive
• Rb protein intersects the Ras/Raf pathway at CDK-cyclin control of S
and resistant and thus cutoff was made based on in vivo dosage levels. phase transcription
Summary of VX-680
Figure 6: RB mutations and Ras/Raf activation are competing processes. CTNNB1 mutations predominate in the sensitive cell lines
Intermediate
• 4 out of the 33 colon/GI cell lines have a CTTNB1 mutation and these
Figure 1: Cells are plated in 384 wells and treated with inhibitor Cells harboring a Ras/Raf activating mutation, activate CDK cyclin and ERK, which phosphorylate RB. Phosphorylated mutations are 4 of the 5 most sensitive cell lines to VX-680
(staurosporine) for 72 hours. Cells were fixed and stained with RB dissociates from the transcription complex and E2F is able to transcribe RNA and translate proteins needed for • 5 of the 8 CTNNB1 mutations occur in the sensitive cell lines determined
anti-activated caspase 3 (green), anti-phospho-histone H3 (red) to have a GI50 of 0.005 to 0.025; One CTNNB1 mutated cell line is in
entry to S phase. However, if RB is mutated, E2F is constitutively activated and MEK inhibition is not able to inhibit the resistant category
and DAPI for cell number (blue). All data is normalized to vehicle transcription. Hence, Rb mutations confer resistance to CL-1040. • 4 of the 4 colon cancers with CTTNB1 mutations are sensitive
control wells and reported as % of control (nuclear count) or fold
APC mutations do not exist in the sensitive lines but predominate in the
induction (apoptosis and cell cycle). Data is binned into sensitive intermediate/resistant cell lines
and resistant cell lines and analyzed for genetic correlations. • 0 of the 30 most sensitive cell lines have APC mutations.
• 2 of the 30 most resistant cell lines have APC mutations. APC
mutations may be in the resistant/intermediate cell lines because they
are exclusive of CTNNB1 mutation
Table 1. Multiplexed cytotoxicity assay parameters are robust. Intra-assay variability in EC50 of Staurosporine
on HCT-116 over 10 independent experiments. Data will be further validated by correlating genes from
Resistant expression analysis and gene copy number. Analysis
Cell line HCT-116 was propagated and plated in 10 different experiments. Reference compound controls were added of this data is currently in progress.
in accord with our standard assay. Data was collected, analyzed, and averaged with standard deviations. Results are
reported above.