Class 12 DNA sequencing and cancer DNA pol error rate  per base copied How many errors in a “typical” somatic cell? Most errors don’t have detectable effects But some errors do: oncogenes N – dominant if “activated” tumor suppressor genes N – recessive 2-hit hypothesis in inherited cancer syndromes, BRCA, FAP loss of heterozygosity in tumor DNA Cancer nowadays viewed in molecular-genetic terms

Implications for therapy Can inhibit some overactive oncogenes with small molecule inhibitors (imatinib, etc) often act intracellularly or with antibodies to cell surface receptors (panitumimab, etc) that act in pathways that stimulate intracellular oncogenes But can’t replace function of inactive suppressors

Example of pathway activating oncogenes Extracellular ligand (epidermal growth factor, EGF) binds EGF receptor, which binds another protein, which causes cytoplasmic tail of EGFR to get phosphorylated, which activates other proteins (here including Ras oncogene)…which turn on other genes that stimulate cell growth. Antibody to EGFR may stop process, but if Ras is mutated and constitutively active, Ab to EGFR won’t work because Ras is “downstream” Image from Google search “egfr kras signaling pathway”

Kras mutated and constitutively active in  40% of colon cancers Large effort has gone into whole genome sequencing of tumors and comparison to non-tumor DNA from same patient What are main results? several hundred oncogenes several hundred tumor suppressor genes organized in at least tens of pathways

Tumors are “clonal” but continue to acquire mutations When you sequence a tumor, do you get sequence of majority of cells or of individual cells, with unique mutations? What are “driver” vs. “passenger” mutations? What are some clues to identifying driver mutations? occurrence in multiple tumors mutated in inherited cancer syndromes

Do you think there a more tumor suppressor mutations or oncogene mutations driving tumors? Why? How fast do tumors grow? cell birth rate b (# divisions/day,  1/few days) balanced by cell death rate d cell doubling rate k, N(t)=N 0 2 kt k related to b-d More ways to inactivate a gene (stop codon nearly anywhere) than to make it overactive, so suppressor mutations should exceed activating oncogene mutations, but need to inactivate both copies of a suppressor, so answer not obvious

Types of cancer therapy surgery – curative intent or for palliation radiation chemo to kill rapidly dividing cells -> toxicity from killing normal rapidly dividing cells in gut, bone marrow, skin drugs or antibodies that target oncogenes could be more specific but still often have major side-effects examples – antibody to EGFR (drug names ending in “ab” are antibodies) small drug inhibitors (drug names ending in “ib” are inhibitors) Problem of “development” of resistance to chemo

Roles of DNA sequencing Research – find what genes are involved in cancer big challenge – interpreting changes passenger vs driver mutations are mutations in non-coding regions (98.5% of total) important? which mutations in coding regions are relevant? Patient care which genes are mutated in a specific tumor? is whole genome seq. necessary or would seq. of  hundred known oncogenes and suppressors do?

Patient care – cont’d. diagnostics – circulating tumor DNA akin to pre-natal dx from circ. fetal DNA ? useful for screening or just dx of already ill ? use to follow treatment – ? more sensitive than other biomarkers, e.g. CEA, PSA do genetic assays need to be specific for individual patient’s mutations or are mutations sufficiently common that “generic” tests ok?

“Beaming” assay emulsion pcr for particular oncogenes -> copies single templates on beads break emulsion, hybridize flourescent oligo probes to beads, different colors for oligos matching wt, mutant, and common seq. determine bead color with flow cytometry wiki/Image:Flow_cytometry

pre-opday 3 day 48 day 244 What is plotted? What do #s in quadrants indicate? Beaming assay for Kras mutations from Vogelstein

How sensitive is assay to mutations occurring in fraction of tumor cells as tumors evolve? What fraction of circulating DNA is from tumor? How many beads can you assay? Use of sequence info in therapy possibly to identify unexpected mutations (e.g. uncommon in patient’s tumor type) that might suggest use of different drug – this is hypothetical identify drugs unlikely to be effective – e.g. Ab to EGFR in pts with oncogenic Kras mutations

Use of sequence info in therapy relevance to patients – avoid (often severe) toxicity in patients in whom drug won’t work (panitumimab has lots of toxic skin, gut effects) relevance to payors cheaper to gene test everyone to avoid use when predictably ineffective = “companion diagnostics” relevance to pharmaceutical companies – use in resistant patients weakens evidence for efficacy, lack of efficacy is major cause of failure to get FDA approval

Questions from this paper How fast do tumors (cells resistant to chemo) grow? How sensitive are tests for tumor mutations? What is normal mutation rate? What is probability that particular oncogene mutation has occurred? How many mutations -> drug resistance? Do resistance mutations pre-exist in tumors, explaining usual drug failure after few months? Implications for multi-drug therapy

How would you describe the patients in this study? What is progression-free vs. overall survival?

Does prior Kras mutation predict poor response? How long before progression in those w/acquired Kras mutations?

What do panels show? Do mutations or CEA or tumor size assays predict treatment failure sooner? What is doubling rate? patient 1patient 2

If doubling time  is  10d and progression time  is  150 weeks how much has mutant cell # increased in time T? N/N 0 = 2  = 2 15 = 3*10 4

How much circulating DNA? How many cell equivalents in What fraction f is from tumor cells vs. normal cells?

What are these plots? wt mutant

How many dots? What is the lowest % (or number) mutant detectable? Suppose 1 mutant dot is reliable and 10 5 dots -> min fraction of mut. tumor cells detectable = 1/(f*10 5 ) If f = 0.1%, 1% tumor cells is min detectable

How many tumor cells in a 100mm 2 (x-ray) tumor Tumor vol = (area) 3/2 = 1000mm 3 Cell vol  (10  m) 3 => 10 9 tumor cells If 1% are mutant when mutation first detected, how many were there before panatumumab was started? 10 7 /(3*10 4 ) = 3*10 2

Is this consistent with expectation if DNA pol makes 1 base error every generation and you have 10 9 cells => 10 9 genomes copied? ->  1 error in every position If 42 positions confer resistance to panitumumab (their estimate), expect  40 mutant cells to pre-exist; not too far off estimate of 300 given large variance in rates of doubling, etc.

If 40 (or 300) mutant cells are expected to be present, on average, by chance in small tumor, what is probability that a tumor has no such cells? Poisson distribution p i =e -m m i /i! p i = probability of a tumor having i when average number/tumor = m p 0 = e -m = e -40 or e -300 = or

What is chance that at least 1 cell in tumor with 10 9 cells has oncogene mutations conferring resistance to 2 different drugs, if the mutations do not overlap and changes at 40 positions confer resistance to each drug? (40/10 9 ) * (40/10 9 ) * 10 9 cells  Implication – multidrug therapy might avoid outgrowth of resistant mutants

Main ideas Mutations in cancer cells drive growth gain of function = oncogenes loss of function = tumor suppressor genes Some drugs target oncogenes by binding to them or their partners in cell signaling cascades Mutations conferring resistance to individual drugs likely preexist in tumors because they contain large numbers of cells harboring mutations just on basis of DNA pol error rate

Multidrug therapy targeting different oncogenes/ pathways might overcome these resistance mechanisms, but … DNA sequencing has been important for discovery of different mutations driving cancer Often difficult to determine if individual mutations are drivers or passengers Genotyping specific genes in patient tumor DNAs to see if most tumor cells already carry resistance- causing mutations can prevent futile use of expensive toxic drugs

Not clear if routine sequencing of exons or whole tumor genomes is useful clinically at present, as opposed to targeted genotyping or sequencing “Beaming” is nice use of emulsion pcr and flow cytometry to detect not too rare mutations in tumor cells HAPPY THANKSGIVING – work on picking a topic for student presentations beginning 11/30