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We hope you have enjoyed this limited-length demo
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1. Genetics and management of inherited cancer predisposition 1
- Prof. Joshua Schiffman
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2. Genetics and management of inherited cancer predisposition 2
- Prof. Joshua Schiffman
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3. The cytogenetics of childhood acute leukemia
- Dr. Susana C. Raimondi
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4. Chromosome translocations and cancer
- Prof. Felix Mitelman
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5. Acute myeloid leukemia: genetics, prognosis and treatments
- Prof. Stephen Nimer
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6. Genetic abnormalities in acute lymphoblastic leukemia
- Prof. Ching Hon Pui
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7. Molecular genetics of non-Hodgkin lymphoma
- Prof. Jude Fitzgibbon
-
8. Genetics of breast and ovarian cancer
- Prof. Jeffrey Weitzel
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9. The genetics and genomics of familial renal carcinoma
- Prof. Eamonn Maher
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10. Genomics of lung cancer
- Prof. Ramaswamy Govindan
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11. The genetics of glioblastoma
- Dr. Hai Yan
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12. Genetics of tumor metastasis 1
- Prof. Robert Weinberg
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13. Genetics of tumor metastasis 2
- Prof. Robert Weinberg
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14. CML: genetic paradigm of targeted therapy 1
- Prof. Michael W. Deininger
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15. CML: genetic paradigm of targeted therapy 2
- Prof. Michael W. Deininger
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16. The non-coding RNA revolution in the cancer society
- Prof. George Calin
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17. Role of molecular markers in guiding therapy in cancer
- Prof. Joe Duffy
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18. Functional cancer genomics
- Prof. Roderick Beijersbergen
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19. Pharmacogenomics in cancer therapy
- Prof. Sharon Marsh
Printable Handouts
Navigable Slide Index
- Introduction
- Cancer represents a perfect genetic crime
- Technology has improved
- Tools to profile DNA, mRNA in single experiments
- Different types of sequencing
- Structure of the presentation
- Follicular Lymphoma aka ‘Brill-Symmers’ disease
- Follicular lymphoma (FL) – in a nutshell
- Overall survival is improving
- Sequential biopsies capture FL molecular evolution
- FL the most common small B cell lymphoma
- Precision cancer medicine
- The genetic make up of an individual
- Follicular lymphoma genetics
- Cancer – genetically complex
- Risk of developing FL: few familial cases
- FL outcome linked to non tumour cells in biopsy
- t(14;18) is insufficient for the development of FL
- Existence of a founder population propagating FL
- Current view of FL disease progression
- Longitudinal profiling of paired FL-tFL biopsies
- An epigenetic ‘addiction’ in FL
- Pattern 1: ‘Rich’ CPC with divergent evolution
- Pattern 2: ‘Sparse’ CPC with convergent evolution
- Evolution & diversity: fluctuating profiles
- The genetic landscape and heterogeneity of FL
- Mutations in amino-acid sensing arm of mTORC1
- Precision medicine in lymphoma – EZH2i
- The importance of defining clonality
- Target tumours where mutation present in all cells
- Top ranking mutated genes- targeted sequencing
- Mutation team-sheet in B-cell tumours
- Acknowledgements
Topics Covered
- Indolent B cell follicular lymphoma
- Precision medicine
- Follicular lymphoma genetics
- Risk of developing follicular lymphoma
- Tumour microenvironment
- Mutational landscape
- Evolution
- Precision medicine opportunities
- Tumour profiling tools
Links
Series:
Categories:
Therapeutic Areas:
Talk Citation
Fitzgibbon, J. (2015, November 30). Molecular genetics of non-Hodgkin lymphoma [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 3, 2024, from https://doi.org/10.69645/GRPY1947.Export Citation (RIS)
Publication History
Financial Disclosures
- Prof. Jude Fitzgibbon, Consultant : Epizyme Speaker's Bureau: Gilead, Janssen, Roche Grant/Research Support (Principal Investigator): Epizyme
A selection of talks on Oncology
Transcript
Please wait while the transcript is being prepared...
0:00
My name is Jude Fitzgibbon.
I am a Professor
in Personalized Cancer Medicine
at the Barts Cancer Institute.
It's part of
Queen Mary University of London.
My lecture today
is on the Molecular Genetics
of Non-Hodgkin Lymphoma.
I am going to be using
an indolent B-cell malignancy
called follicular lymphoma
as an example.
0:19
I think it's important to preset
that cancer represents
almost
the perfect genetic disease
where it's radicalized
maybe 10-20 genes
to actually shift
the balance from a normalcy
to a malignant phenotype.
And so we need to think of these
genes as individuals
but also how they kind of
work together to cooperate
to actually drive this change
in phenotype.
And it's helpful
to think of a formula
in relationship to cancer
and indeed B-cell malignancy
in relationship to the genetics
and the microenvironment
working together
to give rise to cancer.
0:55
The technology
has improved fantastically.
When I started my PhD
in the late '80s, you know,
I did my first polymerase
chain reaction,
my first PCRs using
three water baths set
at different temperatures,
a stopwatch, and a tweezers
to actually move the chews
from one place to another.
Now we've got the opportunity
to actually sample all genes,
all DNA in one single experiment
and monitor their expression
at the same time.
1:23
So I think what we should do
is we should try
and get a very clear picture
of what the human genome is.
So if we can imagine
the human genome as a stadium
of 25,000 spectators,
that corresponds
to 25,000 genes.
We know where each spectator,
where each gene lies.
We know the location
and the position,
and then we know exactly
what they look like
because
that's their DNA sequence.
And how they sound
because that's the sequence
of their messenger RNA.
We've now the tools
to define the DNA
and the mRNA profiles
of every cancerous cell
in single experiments
where we can focus
in on the whole genome,
that's the three billion base
pairs of sequence.
If we're just interested
in looking at
the coding sequence,
which is less than 2 percent
of the genome,
we can
focus in on 50 mega bases.
But what's ideal is when we know
the key genes
that we know to be important,
we can focus in on those
using other different
technologies.
Now what's also key is to preset
that we're not just
looking at genes here
because
these are not just genes,
they're genes with clothes on.
So you can see the spectators
have specific clothes on.
And it's that combination
of the gene sequence itself,
but also
the control of gene expression
and gene function
via epigenetics.
That's key in this shift
from normalcy
to the tumor phenotype.