asco research community forum 2017 annual meeting

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Monica M. Bertagnolli, MDASCO President‐Elect

Dana‐Farber/Brigham & Women’s Cancer Center

ASCO Research Community ForumADVANCING CANCER CARE THROUGH

RESEARCH PARTNERSHIPS “For the loved ones we've all lost, for the family we can still save, let's make America the country that cures cancer once and for all.”

“Imagine if you all worked together. I’m not kidding.”

Beau Biden Cancer Moonshot

• Establish a network for direct patient involvement

• Create a translational science network devoted exclusivelyto immunotherapy

• Develop ways to overcome cancer’s resistance to therapy

• Build a national cancer data ecosystem

• Intensify research on the major drivers of childhood cancers

ASCO Research Community Forum2017 Annual Meeting

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• Expand use of proven cancer prevention and early detection strategies

• Mine past patient data to predict future patient outcomes

• Minimize cancer treatment’s debilitating side effects

• Develop a 3‐D cancer atlas

• Develop new cancer technologies

CANCER DATA COOPERATIVES: A REQUIREMENT FOR PROGRESS IN ONCOLOGY


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Response of RCC to Everolimus

EverolimusPlacebo

Progression-free survival(months)

Frequent Activation of the PI(3)K Pathway inClear Cell Renal Carcinoma

Motzer et al Lancet 372:449 (2008)

Hakimi et al Nat Gen 45:849 (2013)

Sato et al Nat Gen 45:860 (2013)

TCGA Nature 499:45 (2013)

mTOR mutations 73 year old with metastatic bladder cancer. Complete response to everolimus (mTORC1 inhibitor) on

MSKCC protocol 08-123. The patient remains on drug with no evidence of disease 24

months after starting treatment. This patient was one of only 2 who responded to drug (of 45

patients). The drug did not achieve it’s pre-trial statistical endpoint (>70% of patients progression free at 2 months).

Pre-Treatment 6 month 18 month3 month

Iyer et al. Science 338(6104):221 (2012)

Frameshift mutationin TSC1

Frameshift mutationin TSC1

Everolimus

Whole Genome Sequencing Reveals Molecular Basis forExceptional Response to Everolimus in Bladder Cancer

Metastatic anaplastic lymphoma kinase (ALK)-rearranged lung cancer

ALK C1156Y mutation Resistant to crizotinib

Response to lorlatinib (PF-06463922)

Relapse: C1156Y mutation and ALK L1198F mutation

Response to crizotinib

ALK C1156Y ALK L1198F

Shaw et al NEJM 2015;371:54


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The Challenge of Trials for Genomically-Defined Populations

• Phase 2 study in advanced BRAF V600E NSCLC• >2,000 subjects screened to enroll 23 patients

• Randomized Phase 3 trial• >15,000 subjects to identify 300 eligible patients• ~14 years projected to complete study

Under a master protocol, patients are screened for various biomarkers and assigned to trials (arms) for drugs that are most likely to be effective

• Patients may have more clinical trial options as there is more efficient use of small biopsy specimens by centrally performing many at the same time

• Patients are enrolled from a large, centrally screened pool, doing away with the need for patients to undergomultiple screenings to enter different trials

Maximize success of the trial by studying subtypes of disease for which targeted therapies should provide dramatic benefit

ASCO Research Community Forum 2017 Annual Meeting

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NCI-MATCH

Arm Variant Prevalence Rate % Drug OpenedAccrualGoal

I PIK3CA 3.47 Taselisib Feb ‘16 70 Full

W FGFR 2.86 AZD4547 May ’16 70

Z1I BRCA1 or BRCA2 2.79 AZD1775 Mar ‘17 35

P PTEN loss 1.93 GSK2636771 Feb ‘16 35 Full

Z1A NRAS 1.90 Binimetinib May ’16 70

S1 NF1 1.77 Mekinist™ Feb ‘16 70

N PTEN 1.75 GSK2636771 Feb ‘16 35 Closed

Z1D dMMR status 1.51 Opdivo® May ‘16 70

Q HER2 amplif. 1.49 Kadcyla® Aug ‘15 70 Closed

J HER2 amplif. 1.49 Herceptin® Perjeta® Mar ‘17 35

Z1C CDK4 or CDK6 1.36 Ibrance® Mar ‘17 35

M TSC1 or TSC2 1.11 TAK‐228 Mar ‘17 35

B HER2 activating 1.04 Gilotrif® Aug ‘15 70

Z1B CCND1/2/3 0.84 Ibrance® May ‘16 70

R BRAF fusions 0.80 Mekinist™ Aug ‘15 35


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• Trial is open and enrolling in every state, DC, and Puerto Rico• 50% of the 1100 sites have enrolled at least one patient for

screening

In patients tested so far, the tumor gene variants we are studying are

less common than expected,

from 3.47 percent to zero

The discovery that prevalence rates for tumor gene abnormalities being studied in the trial are lower than expected sheds light on the fact that for several of the treatment arms to reach their 35‐patient goal, we really need to look at tens of thousands of patients

MD reviews results of genomic test performed in CLIA certified/CAP accredited lab

MD determines if drug match exists in protocol

Patient enrolled on study

Matched therapy administered; safety and efficacy outcomes recorded

Data monitoring committee regularly reviews RR of tumor-variant-drug groups

Results released when protocol-specified endpoints met

No match, Rx at MD discretion


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Validated Biomarkers Diagnostic Prognostic Predictive

Effective Therapeutics

High efficacy

Low toxicity

Good: Genotyping Early drug discovery Discovery science

Not So Good: Translational science Data analysis Clinical validation

Challenges in acquiring the evidence: Clinical trials designs Utilizing real world data


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Validated Biomarkers Diagnostic Prognostic Predictive

A Learning Healthcare System

Effective Therapeutics

High efficacy

Low toxicity

Public‐Private Partnership for Health Care Research and Delivery

DATA SHARING

Retrospective Cohort Studies

Electronic Health RecordsAdministrative DataClaims DataHealth SurveysPatient/Disease Registries

Treatment OutcomeAdverse EventsEnvironmental ExposuresQuality of Life

BiomarkersProtein expressionGenomic profilingImaging

Randomized Clinical TrialsProspective Observational Trials

2011: Diagnosed withmetastatic diseaseCore biopsies breast & liver

2015: gluteal mass biopsy

Tamoxifen/Lupron Fulvestrant Ganetespib

Letrozole BYL719

Capecitabine Eribulin Palbociclib / Bazedoxefine

2011: Mastectomy & lymph node dissection

ER- / PR- / HER2-ESR1 single-copy deletionRB1 nonsense + LOHPTEN homozygous deletionCDH1 nonsense + LOH

ER+ / PR+ / HER2-ESR1 WTRB1 WTPTEN WTCDH1 nonsense + LOH

Are designed, organized, and conducted by sponsors according to the general data sharing and biorepository use rules of the Metastatic Breast Cancer Initiative and the MBC Characterization Protocol

utilize the MBC Characterization Protocol as a means of studying tumor biology at the individual patient level, developing biomarkers, and/or identifying patients for study eligibility

Allow accumulation of longitudinal data

Trials affiliated with the Metastatic Breast Cancer Initiative:


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MBC CHARACTERIZATION PROTOCOL AND BIOREPOSITORY:

Biomarker determination from metastatic tumor biopsies

Metastatic tumor biopsy & blood

sample

MBC-Affiliated Clinical Trials of Novel Agents and Combinations Specific to Identified Disease

Progression Mechanisms

Cell CycleMediated

HER2-Mediated

ESR1Mediated

Novel Resistance Mechanisms

Additional Targetable Alterations

Enrollment in Longitudinal Database

Biorepository

Determination of Study Eligibility

Trial #1 (CDKi combo)

Trial #2 (e.g. ER+ neratinib)

Trial #3 (e.g. novel SERD)

Future Trials (to be developed)

Basket Trials(e.g. BRAF, MTOR)

• Established in 2003• Patient‐level data from >33,000 individuals• 25 adjuvant trials• Completed studies:

•Efficacy of adjuvant chemotherapy•DFS as a surrogate for OS•Survival following recurrence•Benefit and adverse events inyoung vs. older patients•Outcomes in black patients•Relationship between BMI and OS

“…we are not here to decide if we publish clinical-trial data, but how!”

Dr. Guido Rasi, EMA Executive DirectorNovember, 2012

• Policy final in October 2014, took effect January 1, 2015

• Clinical Study Reports available upon decisionconcerning the application

• Updated policy in 2017 clarified data sharing


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US National Academies of Science, Institute of Medicine

Leads to improved understanding of disease natural history

Improves trial design

Integrates complementary data sources (observational, biomarker, “real world”)

Reduces duplication

Increases transparency

Enables creation of data standards

Permits pooling for meta‐analysis

Protecting academic credit

Patient confidentiality concerns

Concerns over quality of analyses

Fear of conflicting results

Data sharing is difficult, expensive, and time‐consuming


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Data Access: One Size Does Not Fit All


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DAVE: Data Analysis, Visualization, and Exploration


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2017:>100,000 patients

Understudied populations Age 15‐19 and > 65 Underrepresented minorities Residents of rural communities Patients with co‐morbid conditions Uninsured patients

• Only 3% of cancer patients participate inclinical trials


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Rare tumors

“Personalized” medicine approaches

Longitudinal analyses of multiple sequential therapies


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Improving quality for Patients, Providers, Researchers

So many questions, so few patients in clinical trials!

Making the most of every opportunity Trial designs to test biology‐driven hypotheses Learning how to learn from clinical care

Sharing is an obligation The power of the many: many patients, crowd‐sourced analyses


asco research community forum 2017 annual meeting

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