Theory of cancer evolution (2) Flashcards
biomarker
= biological molecule - sign of disease/condition/abnormal process
personal therapy
not only targeted to type of cancer,
patients own cancer information is used to guide therapy
ideal clinical tool (5)
robust measure of tumour heterogeneity thats:
- rapid
- cost effective
- sampling minimally invasive
- comprehensive tumour smapling (no spatial baises)
- simple proxy biomarkers to assay ITH reliably
tumour heterogeneity
differences between
- tumors of the same type in different patients,
- cancer cells within a single tumor,
- a primary (original) tumor and a secondary tumor.
minimally invasive procedure eg.
liquid biopsy
3 evolutionary therapy strategies
- targeting a clonal mutation
- targeting combined clonal mutations
- adaptive therapy
targeting clonal mutation -
- targets specific clone
- expansion of other clone after therapy, due to loss of competition (& can become insensitive to therapeutic agent)
targeting combined clonal mutations -
(+ a limitation of this)
- targets multiple clones …
- leads to remission
(drugs may interact = really bad side effects, & patients unable to tolerate this treatment)
adaptive therapy -
- target + bring down major clones
- monitor patients progression (with evolutionary biomarkers)
- if previously targeted clone declines too much then interrupt therapy
so competitive clone can restrict growth of resistant clone
TRACERx trials
translational research study aimed at transforming our understanding of cancer evolution
therapy monitoring looks for …
ctDNA and CTCs shed from tumours (if therapy is killing cancer cells –> cellular/genomic material released from apoptotic bodies)
how is chronic lymphocytic Leukemia clinically affectively managed ?
we know mutations in certain genes that lead to resistance,
~5 genes are screened for ~5 mutations (which occur in 99% of resistance cases)
risk stratification
enables providers to identify the right level of care and services for distinct subgroups of patients
understanding the timings of mutations across cancers allows you to determine if intervention is needed or not, how?
mutations can be used to determine between pre-malignant or early invasive lesions
how large data & computational methods help with predicting tumour evolution ?
can classify patients on basis of how their tumour evolved
- this has implications for anticipation of disease progression
key early mutagenic processes associated with tumours (2 e.g.’s)
- Cancer with active APOBEC deaminase activity - treat cells to repeat this signature activity + to link it to a process associated with tumours ..)
- C > T mutations, that occur with age (clock like mechanism)
spontaneous deamination of 5-methylcytosine (5meC) causes …
C to T mutations
barriers to translation of these cancer preventions …
- toxicity (in combination approaches)
- need understanding of complex mechanisms that lead to resistance (eg. fibroblasts protecting cancer cells)
- somatic cells with cancer mutations are not cancers
- predictability is limited, bc of cancer evolution
