apostolia m. tsimberidou, md, phd professor cancer...
TRANSCRIPT
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Implementing Precision
Medicine in Oncology:
The IMPACT Clinical
Trials at MD Anderson
Cancer Center
Apostolia M. Tsimberidou, MD,
PhD
Professor
Department of Investigational
Cancer Therapeutics
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Disclosures
Research Funding (my institution): Foundation
Medicine, Immatics, Merck/EMD Serono, Boston
Biomedical, Onyx, Bayer, OBI Pharmaceuticals,
Karus, Tvardi, Parker Institute
Advisory Board: Roche, Europe
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Hypothesis, 2007
▪Selection of therapy based on patients’ tumor molecular analysis
will improve clinical outcomes compared to the standard approach
Methods
▪Patients who exhausted standard treatment options or had
incurable rare cancers were referred to our Phase I program for
treatment.
▪CLIA-certified tumor molecular testing in consecutive patients
referred for treatment.
▪Genes analyzed: 1-50, depending on time of testing
▪Trials available against various targets
▪Treatment: matched targeted therapy, if available; if unavailable,
non-matched.
▪Retrospective analysis, exploratory.
www.clinicaltrials.gov NCT00851032
Initiative for Molecular Profiling in Advanced Cancer Therapy (IMPACT)
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▪Molecular testing: N = 3,743 (2007-2013)
▪ 1,307 (34.9%): ≥1 targetable molecular alteration
▪ 711 (54.4%): matched targeted therapy; 596 (45.6%) non-matched therapy.
▪Median age: 57 yrs (range, 16-86); 39%, men.
▪Median no. of prior therapies, 4 (range, 0-16); previously untreated = 2.8%
▪Cancers: gastrointestinal, 24.2%; gynecological, 19.4%; breast, 13.5%;
melanoma, 11.9%; lung, 8.7%.
Response, evaluable Matched,
N = 697
Non-matched,
N= 571P
Objective response, % 16.2 5.4
Stable disease ≥ 6 months, % 18.7 14.7
Total, % 34.9 20.1 <.001
IMPACT: Results
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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20
40
60
80
100
12 24 36 48 60 72 84 96 108 120 132
Months
No: 596 511 2.8 2.4-3.0
Yes: 711 597 4.0 3.7-4.4
Matched: Total Event Median 95%CI
P < .001HR = .67
Pro
gre
ssio
n-F
ree
Su
rviv
al, %
Progression-Free Survival by Type of Therapy
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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20
40
60
80
100
12 24 36 48 60 72 84 96 108 120 132
Months
No: 596 559 7.3 6.5-8.0
Yes: 711 629 9.3 8.4-10.5Matched: Total Died Median 95% CI
P < .001HR = .72
Overa
ll S
urv
ival, %
Overall Survival by Type of Therapy
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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Risk Factor (vs. other) HR 95% CI P
PAM pathway alterations 1.22 1.08-1.38 .002
Liver metastases 1.46 1.29-1.65 <.001
LDH > ULN 1.66 1.47-1.88 <.001
PS >1 2.15 1.72-2.68 <.001
Albumin < ULN 1.44 1.18-1.76 <.001
PLT > ULN 1.53 1.15-2.04 .003
Age ≥ 60 yrs 1.15 1.03-1.29 .02
CI, confidence interval; HR, hazard ratio; LDH, lactate dehydrogenase; PAM,
PI3K/Akt/mTOR, PLT, platelet count; PS, performance status; ULN, upper limit of normal
Multivariate Analysis, Overall Survival (N = 1,307)
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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Apostolia-Maria Tsimberidou, MD, PhD
20
40
60
80
100
12 24 36 48 60 72 84 96 108 120 132
Months
Score Total Died Median 95% CI
0 204 171 13.7 10.9-17.6
1 420 363 11.0 9.8-12.6
2 403 382 7.4 6.2-8.4
3-4 262 255 4.6 4.2-5.7
5-7 18 18 1.9 1.1-3.4
P < .001
Prognostic Score. Overall Survival (N = 1,307)O
vera
ll S
urv
ival, %
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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Risk Factor (vs. other) HR 95% CI P
Non-Matched therapy 1.30 1.16-1.46 <.001
PAM alterations 1.25 1.10-1.42 <.001
Liver metastases 1.45 1.28-1.64 <.001
LDH > ULN 1.61 1.42-1.83 <.001
PS >1 2.12 1.71-2.64 <.001
Albumin < ULN 1.41 1.15-1.72 .001
PLT > ULN 1.54 1.16-2.04 .003
Age ≥ 60 yrs 1.14 1.02-1.28 .02CI, confidence interval; HR, hazard ratio; LDH, lactate dehydrogenase; PAM, PI3K/Akt/mTOR;
PLT, platelet count; PS, performance status; ULN, upper limit of normal
Multivariate Analysis, Overall Survival Therapy Added (N = 1,307)
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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10
▪ Long-term overall survival was noted in the matched therapy group. The 3-yr
overall survival rate was 15% in the matched group compared to 7% in the
non-matched group. The 10-yr overall survival rate was 6% vs. 1%,
respectively.
▪ Matched therapy was an independent factor predicting longer survival in
multivariate analysis.
▪ PI3K/Akt/mTOR pathway abnormalities were associated with inferior
outcomes compared to other alterations.
▪ We developed a prognostic score for overall survival including molecular
pathway abnormalities.
IMPACT 1: Conclusions
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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▪ Precision Medicine uses targeted therapy, immunotherapy, and other
strategies to target specific biological abnormalities causing
carcinogenesis in individual patients.
▪ Precision Medicine in cancer requires:
1. Complete understanding of tumor biology, including immune
features, that drives carcinogenesis
2. Use of effective drugs and therapeutic strategies that inhibit
carcinogenesis (rigorous definition)
3. Access to testing and effective drugs for all patients starting at
diagnosis and during the course of their disease
Implementation of Precision Medicine
ASCO 2018, Press Briefing Presentation AM Tsimberidou, MD, PhD
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Precision Medicine in a Patient with Salivary
Cancer (BRAF V600E Mutation, Vemurafenib)
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•The MD Anderson program pooled 1,144 patients in a phase I study after profiling their tumors for mutations that might be targets of the tested drugs.
•Apostolia Tsimberidou, the researcher who led the study, reported that 40% had mutations in 10 molecular pathways that were targeted by the experimental compounds.
•Tumors in 27% of those given agents that targeted their mutations responded to treatment compared to 5% for those with unmatched therapies.
THE WALL STREET JOURNAL June 6, 2011
Major Shift in War on Cancer
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THE ECONOMIST June 9, 2011
Taking aim sooner
If personalized medicine is to achieve its full
potential, it should be used earlier on in clinical trials
Many scientists … believe that matching volunteers'
genetic profiles to the drugs being tested will not only
be better for the volunteers, but may also speed up the
trials, and save millions of dollars in the process.
One such is Apostolia-Maria Tsimberidou of the
University of Texas's MD Anderson Cancer Center, in
Houston. And her preliminary results, presented at a
meeting of the American Society of Clinical Oncology in Chicago, suggest she is right.
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Challenges: Current Barriers
Actual Goal
Biopsy for molecular profile Not standard Standard of care
Tumor biology, markers Limited Complete
Bioinformatics Limited Optimized
Tumor heterogeneity Tumor/blood Validated cell-free DNA analysis
Drug discovery Limited More and effective drugs
Time to analysis 10-60 days 1-3 days
Clinical trial, drug available 5-30% of patients All patients
Timing (course of disease) Advanced, metastatic Starting at diagnosis
“Targeted drug” definition Imprecise Precise
Selection of optimal therapy Subjective Evidence-based, tumor board,
artificial intelligence
Adaptive learning, “N of 1” <10% 100%
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Primary Objective
To determine whether patients treated with a targeted
therapy selected on the basis of mutational analysis of the
tumor have longer progression-free survival from the time of
randomization than those whose treatment is not selected
based on alteration analysis
PI: Tsimberidou, AM
www.clinicaltrials.gov NCT02152254
Supported in part by a research grant from Foundation Medicine
Randomized Study Evaluating Molecular Profiling and
Targeted Agents in Metastatic Cancer (IMPACT 2)
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IMPACT 2. Study Design (I)
Metastatic disease
Tumor biopsy for molecular profiling, 100%
Targetable molecular aberrations (≥1 aberration)
Yes, 50% No, 50%
FDA-approved drugs within labeled indication
Yes, 30% No, 70%
Excluded; patient
followed for
progression but
not randomized
Is there a clinical trial
or commercially
available targeted
therapy?
Yes, 70%
Randomize
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IMPACT 2. Study Design (II)
Targeted
therapy
Treatment
not selected
based on
molecular
analysis
1
1
CrossoverIf:
•Progressive disease
•Toxicity
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0
50
100
150
200
250
300
350
400
450
PATIENTS ENROLLED IN IMPACT2
Cumulative plot of patients enrolled in IMPACT2
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0
10
20
30
40
50
60
70
PATIENTS RANDOMIZED IN IMPACT2
Cumulative plot of patients randomized in IMPACT2
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Genomic Alterations
FGF19 amplification
FGF4 amplification
FGF23 amplification
FGF3 amplification
FGF6 amplification
CCND1 amplification
CCND2 amplification
CDKN2A/B loss
CHD2 D213N
CREBBP R1392*
EMSY amplification
KDM5A amplification
KRAS amplification
MYC duplication exons 2-3
TP53 E204*
Head and Neck Squamous Cell Carcinoma with FGF Amplifications: CR to FGFR Inhibitor
Dumbrava I, … Tsimberidou, AM, JCO Precision Oncology – In Press
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A C
DB
Head and Neck Squamous Cell Carcinoma with FGFAmplifications: CR to FGFR Inhibitor
Dumbrava I, … Tsimberidou, AM, JCO Precision Oncology – In Press
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Mutation in Potentially
Actionable Gene
Underwent Genomic Testing
N = 2000
Genotype-matched trial after
genomic testing?
No (1211)
Genotype-Selected
Trial N = 54
Genotype-Relevant
Trial N = 29
Yes (789)
No (706)Yes (83)
Enrollment on Genotype-Matched Trials
11% of pts with mutations
in actionable genes went
on genotype-matched trials
Meric-Bernstam et al, JCO, 2015
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Workflow: Development of Personalized Cancer Therapy Gene Data
Kurnit et al. Cancer Res 2017
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1. Molecular profile is ordered as:
▪ Standard of care or
▪ For clinical trials: i.e. IMPACT2, NCI-MATCH, MPACT
▪ Interpretation of molecular profile:
▪ Precision Oncology Decision Support team
▪ Expert oncologists in precision medicine
▪ Selection and treatment on clinical trials is based on:
▪ Recommendation of tumor molecular board
▪ Clinical trial availability
▪ Patient preference and eligibility
▪ Study sponsor and insurance approval
2. Stringent regulatory CRC/IRB/DSMB review and trial
prioritization
Clinical Practice: Phase I Program, MD Anderson
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ASCO’s Targeted Agent and Profiling Utilization Registry (TAPUR)
➢ To describe the anti-tumor activity and toxicity of commercially available, targeted therapy of patients with advanced cancer whose tumor harbors a genomic variant known to be a drug target.
➢ To learn from the real world practice of prescribing targeted therapies and to educate oncologists about implementation of precision medicine in clinical practice
Richard Schilsky, CMO and VP ASCO
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Intra-tumor Heterogeneity: How to Resolve it?
Circulating free tumor DNA
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Targeted Therapy and Immunotherapy
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• Unresectable/metastatic, MSI-H or mismatch repair deficient
(dMMR) solid tumors that have progressed following prior
treatment or with MSI-H or dMMR colorectal cancer that has
progressed following treatment with a fluoropyrimidine,
oxaliplatin, and irinotecan.
• PD-L1–positive recurrent or advanced gastric or
gastroesophageal junction (GEJ) adenocarcinoma with ≥ 2
lines of chemotherapy, including fluoropyrimidine- and
platinum-containing chemotherapy, and, if appropriate,
HER2/neu-targeted therapy: KEYNOTE-059 study: 143 of
259 patients had PD–L1-positive tumors (combined positive
score ≥1), non-MSI high; ORR: 13.3% (CR 1.4%; PR 11.9%);
Duration of response: 2.8+ to 19.4+ months
Pembrolizumab: FDA Approval Based on Tumor Markers
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Depth of response
Nivolumab in Mismatch-Repair Deficient Non-Colorectal Cancers: NCI-MATCH Trial:N= 34: PR, 24%; SD ≥ 2 months, 32%
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Mutational Burden and ORR to PD1/PDL1
Inhibitors in Selected Tumor Types
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Slide 4
Study of Immuno-Markers That Predict Response to Immunotherapy
Presented By Lisa Butterfield at 2016 ASCO Annual Meeting
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Presented By Mary Disis at 2018 ASCO-SITC Clinical Immuno-Oncology Symposium
Hot and Cold Tumors
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Screening Production phase Treatment/Observation Follow-up
NCT02876510, Immatics PI, AM Tsimberidou; Co-PI, Borje Andersson
ACTolog: Endogenous CD8+ T cells in Advanced Cancer
HLA phenotype HLA-A*02:01
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Precision Medicine 2018
▪ Multiple alterations, complex molecular networks,
immune mechanisms, transcriptomic, proteomic and
epigenetic changes can be identified in individual
patients
▪ These markers should be integrated into clinical practice
to select optimal therapy
▪ Complexity of biomarkers is increasing
▪ Development of infrastructure is needed to use artificial
intelligence to integrate all available patient data to
perform algorithm analysis in decision making for
optimal drug selection, for More Effective Drugs, For
More Patients, Faster.
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Acknowledgements
MD Anderson or WIN Leadership
• Dr. John Mendelsohn
• Dr. Razelle Kurzrock
• Dr. Richard Schilsky
• Dr. Patrick Hwu
Investigational Cancer Therapeutics
• Dr. Funda Meric, Chair
• Dr. David Hong
• Dr. Filip Janku
• Dr. Aung Naing
• Dr. Siqing Fu
• Dr. Sarina Piha-Paul
• Dr. Vivek Subbiah
• Dr. Jordi Rodon
• Dr. Timothy Yap
• Dr. Jennifer Wheler (former faculty)
• Dr. Gerald Falchook (former faculty)
Pathology
•Dr. Stanley Hamilton
•Dr. Russell Broaddus
Biostatistics
•Dr. Donald Berry (IMPACT 2)
•Dr. Jack Lee (IMPACT 1)
•Graciela Nogueras (IMPACT 1)
Institute for Personalized Cancer Therapy
Funding
•Donors: Alberto Barretto Alberto
Barretto, Jamie Hope, and Mr. and Mrs.
Zane W. Arrott (IMPACT 1)
•Foundation Medicine (IMPACT 2)
•Multiple pharmaceutical Companies
(individual clinical trials)
Patients and Families
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Department of Investigational Cancer Therapeutics