personalized oncology - intermountainphysician · 2015-11-19 · personalized oncology derrick...
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Cancer Genomics Personalized Oncology
Derrick Haslem, MD Intermountain Southwest
Cancer Center Intermountain Precision
Genomics
Intermountain Southwest Cancer Services
Cancer Experience
Grow into a “tumor” or “neoplasm” Cancer cells spread from there to lymph
nodes and other organs Cancer cells that spread still have same
characteristics of cell of origin • Same properties and characteristics
Staging: Local, Regional, Metastatic
Goals of treatment vary by stage
Local/Regional • Curative treatment
strategy • Treat micro-
metastasis
Metastatic • Palliative treatment
strategy • Buy “quality” time
Treatment options • Surgery • Radiation • Chemotherapy • Targeted therapies
History of Chemotherapy
Chemotherapy
Goal is to reduce cancer burden
Affects ALL cells Since cancer cells
divide rapidly, they are typically more affected
Through trial and error, chemotherapy progressed
Outcome measured: Did patients live longer?
Side Effects of Chemo
Chemo acts on actively dividing cells
Predictable side effects • Nausea • Hair loss • Low blood
counts
Traditional Chemotherapy
• Chemotherapy is not effective in every case
• Non-targeted, toxic resulting in expected side effects
• Large selection of drugs with a low response rate. § Results in high variation, inefficiencies and
increased costs
Cancer Hallmarks Unregulated growth Insensitive to anti-growth
signals Evades apoptosis Multiply indefinitely Stimulate angiogenesis Activation of metastasis and
invasion of tissue
The Human Genome
46 chromosomes
20,000 genes
1 Human Genome
Normal and Aberrant Genes
insu
lin
albu
min
grow
die
KRAS P53* *
grow grow grow
die die die
x
Genome Aberrations
Faulty Genes
1. FGFR1
2. P53
3. MEK1
4. EGFR
5. HER2
Genomic analysis
Cancerous cell
B. Vogelstein, Science. 2013
Number of Mutations in Human Cancers
Precision Genomics Cancer Therapy
mdanderson.org
Clinical Cancer Genomics Program
• Personalized Medicine Clinic
• Genomic Testing
• Molecular Tumor Board
• Drug Procurement
Cancer Genomics Workflow
Day 1
Day 2-5
Day 6
Day 7-8
Day 12-13
Day 13-14
Day 14-18
Molecular Tumor Board
Results and Treatment
Tumor Biopsy or FFPE
Pathology Review
Sample Prep
Analytics
Day 9-11 Molecular
analysis (NGS)
Personalized Medicine Clinic
Molecular Tumor Board
• Multi-institutional participants
• Experts in Cancer Genomics
• Interpretation of Genomics
E-portal for ordering/results delivery:
www.precisioncancer.org
Genomic Testing: Impact on Management
n= 195
Intermountain Precision Medicine Cohort Study
195 assessed for eligibility (had genomic testing)
154 with actionable mutation
75 with actionable mutation,and received targeted trx
36 precision trx match: dx, age, gen,
#prev. trx
Patients received standard trx within Intermountain
36 standard trxmatch: dx, age, gen,
#prev. trx
Assess:-PFS
-Cost of care
Assess:-PFS
-Cost of care
41 without actionable mutation
79 did not received precision trx
39 without match:dx, age, gen, prev. trx
Baseline Characteristics
Targeted ControlCharacteristic No. % No. %Meanage,years 67.8 67Gender
male 22 61.1 22 61.1female 14 38.9 14 38.9
RaceWhite 36 100 30 83.3Black 0 0 1 2.8
Hispanic 0 0 4 11.1Other 0 0 1 2.8
LineofTreatment1stline 0 0 1 2.82ndline 19 52.8 19 52.83rdline 9 25 8 22.24thline 1 2.8 3 8.35thline 2 5.6 1 2.86thline 4 11.1 3 8.37thline 1 2.8 1 2.8Mean 3.1 2.9
TypeofCancerBladder 2 5.6 2 5.6Breast 5 13.9 5 13.9
Cholangio 1 2.8 1 2.8Colon 8 22.2 8 22.2Gastric 1 2.8 1 2.8
HeadandNeck 4 11.1 4 11.1Lung 11 30.6 11 30.6
Melanoma 1 2.8 1 2.8Ovary 1 2.8 1 2.8
Pancreas 2 5.6 2 5.6
Diverse Tumor Types
n n % %
Control Targeted
Primary Outcome: Progression Free Survival
36 precision trx match: dx, age, gen,
#prev. trx
36 standard trxmatch: dx, age, gen,
#prev. trx
Assess:-PFS
-Cost of care
Assess:-PFS
-Cost of care
Clinical Trial: Traditional vs Targeted
Progression Free Survival: Traditional: 12.0 weeks Targeted: 22.9 weeks
HR: 0.53, p<0.002
Progression Free Survival
Secondary Outcome: Cost of Care
Cost of Care:
Standard: $5,011/wk Precision Med: $4,682/wk
p= 0.22
Patient examples
46 female with metastatic melanoma Spread to brain, adrenal glands Not responding to standard treatments
Genomic analysis of the tumor was performed Revealed a KIT mutation
Started Imatinib Safe, oral, well-tolerated drug for CML
…after 2 months of imatinib
Patient Case: Colon Cancer
40s yo man with metastatic colon cancer Progressed through multiple treatments Genomic analysis: HER2 amplification
Patient Case: Colon Cancer (cont’d)
Ø 3 months of drug, tumor shrinking (13 month improvement)
Ø he and his 3 children are thrilled
Chemo TDM-1 2 dosesChemo
TDM-1 3 doses
Patient Case: Lung Cancer
• 79 year old man with metastatic lung cancer (lung)
• Progressed through carbo/gemcitabine, docetaxel
• Genomic analysis: FGFR1 amplification
Patient Case: Lung Cancer
Targeted trx, 3 mo Targeted trx, 6 moChemo
Pt now on treatment >14 months, an oral pill • He reports feeling “very optimistic about life.”
Cancer Genomics is NOT:
NOT a cure May turn it into a chronic disease; ie CML
NOT used to figure out Family Relations Genomic evaluation on the tumor NOT the patient
NOT applicable to every patient/cancer Case by case basis; although changing
NOT guaranteed to work It is new and bugs are still being worked out
Cancer Genomics IS: More options for patients with incurable disease Progress towards a cure or turning cancer into a
chronic disease Exciting technology with clinical application
Opportunity to make life better for patients