Genetics, Molecular Profiling &

Epidemiology of Early Stage MelanomaWinship Cancer Institute

2016 Melanoma Conference

Atlanta, GA, Feb. 27, 2016

Sancy Leachman, M.D., Ph.D.

Disclosures & Conflicts

• Myriad Genetics Laboratory – MSAB (honorarium), Early Access

Program for myPath & myRisk (limited number of free tests)

• Castle Biosciences – MSAB (honorarium)

• Apple Support – Research Kit Tools, Thought Leader Meeting, &

Marketing

• NOTE: Mole Mapper is free, open source, and no revenue is

being generated from sponsorships.

Overview: Early Detection through Genetic & Epidemiologic

Tools

• Genetic tools: Identifying patients at-risk

• Epidemiologic Tools

– War on Melanoma Community Registry

– Mole Mapper iPhone App

Melanoma Genetics & Genetic Testing

Germline – Blood tests that tell you how much risk the patient has of

developing a melanoma (predisposition testing)

Somatic – Tests that tell you how likely your patient’s tumor has of being a

melanoma (diagnostic testing)

Somatic – Tests that tell you how likely your patient’s melanoma

has of metastasizing (being a lethal melanoma—prognostic

testing)

Context: Germline Testing of Highest Risk Patients for Early

Identification & Screening

Vulnerable Phenotype

Light skin, eyes, hair, family history

Freckles, Sunburns, immunosuppression

High-Risk

Red hair (MC1R homozygote); > 100 nevi;

>5 dysplastic nevi; personal hx MM; AKs,

BCCs, SCCs (genes & environment)

Highest/Syndromic

“Rule of Threes” and Other Cancers

CDKN2A (p16, ARF), CDK4, TERT,

POT1, XP, BAP1, PTEN

Risk Level

(relative to

Gen. Pop.)

30+X

4-8X

2X

Proportion of

Melanoma Population

0.2-2.0%

≈15-30%

Almost

everybody

else!?

Almost

everybody

else!?

≥3 invasive melanomas

in blood relatives≥3 melanomas in an individual

≥3 melanoma + pancreatic

OR astrocytoma (*2) in FDRs

OR unusual associations:

Uveal melanoma, lung

adenocarcinoma,

mesothelioma,

paraganglioma, clear cell

renal carcinoma

Identifying Hereditary Melanoma: Consider the “Rule of Twos & Threes”

*Only 1 criteria needs to be met. Consideration should be

given to age at diagnosis, UV exposure, skin type, and

ethnicity, as there may be exceptions to the “Rule of Twos

& Threes.” Leachman, et al. JAAD 2009

Germline genetic testing: Single genes, panels of genes, or exomeNGS, test sequencing?

• Single gene – when phenotype suggests a particular mutation

• Gene panel – perhaps better, if cost is no object

• Exome/Genome sequencing – interpretation difficult

• Testing order: based on phenotype, history, cost

Navigating the Genetic Testing Options for

Hereditary Patients

Only Melanoma

+/- Pancreatic OR

+/- Astrocytoma

Melanoma

+ Uveal Melanoma OR

+ Lung Adenocarcinoma OR

+ Paraganglioma OR

+ Mesothelioma OR

+ Clear Cell Renal Carcinoma

Melanoma in special context

Multiple other cancers/signs

including:

• SCC/BCC

• Breast, Thyroid, Endometrial

• Prostate

• Renal

• Colon

CDKN2A

If Negative

CDK4If Negative

BAP1

If Negative

PANEL TEST

Work with Genetic Counseling

Assure Genes Associated with Observed Cancers

Are Contained in the Panel

Other Syndrome?

• Xeroderma pigmentosum

• Cowden

• Tumor-specific (e.g.

Breast or Colon)

FAMMM

Cutaneous Cancer SyndromeBAP-1 Pattern

The Testing Process

Identify Candidates Using

“Rule of Twos & Threes”

Refer for Genetic

Counseling

Mutation

Does NOT

Desire

Testing

Desires Testing

Mutation of

Uncertain

Significance

No

Mutation

Manage Based on Family

History

• Add Other CA

Screening

• Test 1st Degree

• Select Family

Member with

Melanoma

• Preauthorize

• Send to a CLIA Lab

Genetic Diagnostic Testing for Melanoma

• Fundamentally different than predisposition testing

– Purpose is to determine if a lesion is melanoma, not if the

individual is at risk for melanoma

– Performed on tissue, not blood

– Provides adjunctive measure to complement histology in

ambiguous cases

Fluorescent In-Situ Hybridization (FISH)

• Two clinically available assays based on gene copy number

• Most studies on unambiguous lesions

– Sensitivity 87-94%; specificity 95-98%

• Less sensitivity in ambiguous lesions (43%)

• Subjective, requires specialized expertise

• Chromosomes: 6p25 (RREB1), 8q24 (MYC), 9p21

(CDKN2A/p16), 11q13 (CCND1), centromere (CEN9)

Comparative Genomic Hybridization (CGH)

• Also detects chromosomal gains and losses

• Comparison between tumor DNA & control DNA to

evaluate entire genome

• Sensitivity & specificity not as well-characterized

• Most studies done on unambiguous cases

• Some subjectivity, but less than FISH

Gene Expression Profiling (GEP): Quantitative Reverse

Transcription Polymerase Chain

Reaction

• Evaluates expression of RNA rather than mutations in

DNA

• Panel of 23 genes used

• Expression algorithm used to generate a score that falls

into a benign or malignant range

• Objective and quantitative

Comparison of Diagnostic Genetic Tests for Melanoma

FISH CGH qRT-PCR

Advantages Minimal tissue

required; single-cell

resolution; can detect

translocations

Can assess all 23

chromosomes; no

proficiency in

fluorescent

microscopy required

Provides additional

diagnostic value in

discriminating benign

vs malignant lesions

Limitations Visualizes tiny

fraction of genome;

expertise

requirement

Can’t assess

intratumoral

heterogeneity;

dilution by stroma

New test,

publications in

progress; no

correlation with

outcome

Genetic Prognostic Testing for Melanoma

• Fundamentally different than predisposition or diagnostic

testing

– Purpose is to determine if a lesion is a potentially deadly

melanoma

– Performed on tissue, not blood

– Provides adjunctive measure to complement histologic (e.g.,

Breslow depth) and other prognostic (e.g., sentinel node

biopsy) data

• Evaluates risk of recurrence for cutaneous melanoma patients

• Separates tumors into Class 1 (less risk) and Class 2 (more risk)

• High positive predictive value for Class 2

• High negative predictive value for Class 1

• Allows improved risk stratification that supports consideration of

heightened follow-up (maybe adjuvant therapy in future)

Hodi, et al. 2010; Joseph, et al. 2014; Lyle, et al. 2014; Menzies, et al. 2014; Nishino, et al. 2014; Steinman,

et al. 2014; Del Vecchio, et al. 2015; Kaufman, et al. 2015; Tsai, et al. 2015

Gene Expression Profiling (GEP): Quantitative Reverse

Transcription Polymerase Chain

Reaction

5-yr DMFS

Class 1 = 100%

Class 2 = 58%

Gerami, et al. Clin Cancer Res. 2015;21(1),175-183.

Distant Metastasis Free Survival

Class 1

(n=76)

Class 2

(n=141)

Events 14 71

5-yr DMFS 82% 46%

Class 1

Class 2

% fre

e o

f m

eta

sta

sis

100%

75%

50%

25%

0%

n=217

p<0.0001

Time (years)

1086420

Gerami, et al. J Am Acad Dermatol. 2015;72(5):780-5.e3.

Gene Expression Profiling (GEP): Class 1 and 2

Discriminates Risk of Recurrence

Putting it all together: An integrated approach to “choice points”

in melanoma patients

Patient calls

with concern

Expedited

Appointment

Yes

Routine

Appointment

New

∆ing

Hx?No

History

Physical

• Risk assess

• FBSE

• Dermoscopy

Low/Moderate Risk

Education &

Appropriate F/U

High/Extreme Risk

Photography?

Biopsy?

Referral?

Photography?

• Total body

• Select nevi

• Combination

Biopsy? Referral?

Additional Imaging

• Confocal

• OCT

• Hyperspectral

Reassured

(Monitor)Benign or Equivocal Malignant

Consider 2nd Opinion

Consider Molecular Dx

*Excise

*Guidelines

*Multidisciplinary

Genetic

Counselor

Genetic

Testing?

Consider

Mol. Prog.

Epidemiologic Tools: War on Melanoma Community Registry

• Walsh Family $$

• 25,000 Living Patients

• Patients, Family, Friends

• IRB-Approved

• Collaborative

• >4800 total

• >3500 Patients

Early Detection: Oregon vs Schleswig-Holstein

Similar Populations, Different Health Care System

The War Plan: A Statewide Population

Sciences Experiment!

Massive Public Education CampaignProviders Skin Care Services Lay Public

Grass Roots AND Top-Down

Discovery of Suspicious Lesions

Screening & Biopsy If Needed

Early Stage Removal If Needed

Expansion To Other States

Experimental Design

Baseline Measures:

• Obstacles

• Tumor Depth/Stage

• Cost

• Comparison to controls

Repeated MeasuresSuccessful

Unsu

cce

ssfu

l

Refine & Repeat

A Massive Campaign Requires A Massive Army

Melanoma Community RegistryPatients Family Friends

Education:

• Symposia

• Curriculum

• Outreach

Activism:

• Legislation

• Community Events

• Fundraising

Research:

• Questionnaires

• Imaging

• Phone Apps

• New Tests

Novel Application Of Volunteerism Tools

Over 800 Participants

• 126 Volunteers

• 21 Providers

• 18 from registry

Pilot Experiment: Skin Cancer Research Expo and Sun Safety

Event, May 30, 2015

Melanoma Community Registry

• 127 New Registrants Enrolled

• 244 Risk & Phenotype Question-

naires Completed

Skin Cancer Research Expo and Sun Safety Event

May 30, 2015

Knight BioLibrary

• 162 blood draws

• 810 - 26 ml vials

• 2,400 aliquots

Skin Cancer Research Expo and Sun Safety Event

May 30, 2015

Skin Checks and

Sun safety

• 247 screened

• 55 recommended

biopsies

• 4 possible melanoma

• 5 possible SCC

• 13 possible basal

cells

• 55 toured DermSpectra

Skin Cancer Research Expo and Sun Safety Event

May 30, 2015

Research Demos/Info

• Knight Clinical Trials – 50

ppl

• Tan Meter – 175 ppl

• Mole Mapper – 20

downloaded app

• OCTRI – 65 healthy

controls

Skin Cancer Research Expo and Sun Safety Event

May 30, 2015

Social Media

- 45 social posts on

Facebook, Twitter, &

LinkedIn

- Reached 105,608

users across all

Platforms

- 15,000 saw our top Post

- 1500 “re-engagements” (re-tweets,

comments, shares, etc.)

- 1400 clicks to our registry & sites

- 600 YouTube views

Skin Cancer Research Expo and Sun Safety Event

May 30, 2015

Preliminary Data: The Registry Wants to

Participate

Opportunities to Participate:

I want to attend educational

conferences

I want to attend focus groups to

provide my opinion about

questionnaire development or

other documents for participants.

I want to attend melanoma-

centric events

Preliminary Data: The Registry Will Participate

In Research

Where do the patients come from?

Oregon Health & Science University (OHSU)

31%

Providence Health & Systems20%

Kaiser Permanente11%

Legacy Health9%

Other22%

Veterans Administration2%

I prefer not to provide access to this information

electronically, but I will provide records as hard-

copy2%

I prefer not to privide access to this information

3%

Other7%

Q19: HEALTH CARE SYSTEMS THAT HAVE MY ELECTRONIC MEDIAL RECORDS INCLUDE:

War on Melanoma Community Registry: Representative

Participants for Research

62%

24%

3%

1%3%

7%

Q26: What was your Stage of Melanoma (n=1162)

In Situ Stage I or II Stage III Stage III In transit Stage IV Don't know

• Representative categories of

patients

• Controls included

• Eager to participate

• A tool to better understand

melanoma at every level

Mole Mapper: A tool within a tool

• Dream: To make this app OUR app, to facilitate mole

tracking and collaboration worldwide!

FAQ’s:Cannot diagnose melanoma or make

recommendations for care

Can measure & track nevi

Available in iTunes Store (NOT PLUS)

Part of Apple’s ResearchKit Suite of

Apps

Android version in development

For “The People:” Provide a free, quantitative

mole-tracking tool

Short-Term Goals for the Mole Mapper App

For Providers

& Patients:

Facilitate

productive clinic

visits

Participant

Clinician Researcher

For Researchers:

Conduct a large-

scale,

crowdsourced,

research study

Design: Current Work Flow

Mole Map

Keep Data

On Phone

No back-up

Sage

Bio-

network

OHSU War

on

Melanoma

Cohort

Consent

to Share

Data

Strip Identifiers

De-Identified

Data

PHILinkers Image Analysis

& Challenges

Human Research

Citizen Science

Optimization

Challenges for the Development of a Melanoma Research App:

Legal & Regulatory

Bureau of Consumer

Protectionhttps://www.ftc.gov/news-

events/press-releases/2015/02/ftc-

cracks-down-marketers-

melanoma-detection-apps

Challenges: Clinical Research App Development is Complex

App

Launch

OHSU

Developer

Dan Webster

Sage

Bionetworks

ResearchKit

Thought

Leaders

Team Effort:

• OHSU Leadership

• Knight Leadership

• Clinical Trials/CTSA

• Dermatology

• Strategic Communications

• Social Media

• IRB

• Contracts

• Legal Affairs

• ITG Security

• Technology Transfer

• Outside consultants

• Funding

• Modification for ResearchKit

• Specifications

• Testing

• Pre-launch Meetings

• Guidance

• Prioritization

• Publicity

• Essential

Collaborator

• Back-end

• Big-data

Oct. 15!

Post-Launch Challenges: A Three-Year Plan for Success

• Intensive & ongoing needs analysis, team building

• Optimized data flow

• Nurturing the cohort

• De-bugging, improved usability

• Evolving/Adding “new features” functionality

• Development & release process, including Android

• Serving outside collaborators

• Obtaining preliminary data

• Writing grants/proposals

• Business plan for sustainability

Progress: What does the App do now?

• Map Measure Monitor Monthly

“Map, Measure, and Monitor Moles Monthly”

Monitor Monthly

Informed Consent Is Required Before Data Release Occurs:

Novel Process

Go through formal consent on app

Pass test to demonstrate understanding

of risks and benefits

(Courtesy of John Wilbanks &

Sage Bionetworks)

Data: Includes Baseline Demographic and Risk Questions

Data: How much interest has been generated for

Mole Mapper?

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

10/23 11/3 11/9 11/16 11/24 12/7 1/7 2/4 2/19

Mole Mapper Stats

App Store Views Downloads Registrants Moles Measured

Data: Building a Cohort of Thousands in Months (4 months)

8,019 App Downloads

2,204 Consented Participants

2,787 Mole Measurements & Mole Photos

~13% of participants are melanoma

patients/survivors, ~27% with family history

Data: Mole Size Is Consistent with Clinical Experience

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

11.5

12.0

12.5

13.0

13.5

14.0

14.5

15.0

0

25

50

75

100

125

150

175

200

225

Mole Diameter (mm)

Num

ber

of M

ole

Mea

sure

men

ts

Mole Measurement Distribution

Average Mole Size: 3.83mm

1 std. deviation larger:

5.97mm

in keeping with 6mm “eraser”

recommendation for vigilance

Data: User Comments

The dashboard helped me discover my

statistically significant “Ugly Duckling”:

7.1 mm fried-egg on my back

Citizen Science: Patient-Driven Improvements

“Sometimes it’s hard

to take pictures and

keep the reference

next to the mole”

Participant

Clinician Researcher

“I don’t always have

a coin on me for

measuring”

Provide a free, melanoma triage tool - maybe

a diagnostic tool?

Opportunities: Long-Term Goals for the Mole Mapper App

Reduce

unnecessary

patient visits

and detect

melanoma

earlier

Participant

Clinician Researcher

Optimize and

automate image

analysis for diagnostic

purposes?

Incorporate advanced

imaging tools and

algorithms?

Opportunities: Data will be “open-sourced” to qualified

researchers worldwide

48

Participant

Clinician Researcher

Opportunities: Cohort will be “crowd-sourced” to contribute

data worldwide

Participant

Clinician Researcher

Chemoprevention Trial?

Summary: Germline Genetic Testing to Identify Patients at

Highest Risk for Screening

• Identify the highest risk individuals

• Unlikely you will find many of these patients

• Likely the tests will have changed between now and the

time you identify them

• Identify a genetic counselor in your area and refer, work

with them to assure appropriate follow-up

• Refer to a registry: leachmas@ohsu.edu

• Diagnostic genetic testing to assess likelihood that a

lesion is malignant

– FISH, CGH, qRT-PCR available

– Little outcome data on any

– Little data on ambiguous lesions

– Can help to guide surgical removal & treatment

• Prognostic genetic testing to assess likelihood that a

lesion is deadly

– qRT-PCR available

– Growing data to support (David Lawson)

– Can help to guide follow-up

Summary: Diagnostic & Prognostic Genetic Testing to Identify

Patients Needing Additional

Care

• The next era of cancer care will emphasize prevention and

early detection

• Engaging patients through a registry/app is powerful

• It takes a village

• To Join/refer: “War on Melanoma”

• Try the App: www.molemapper.org and provide feedback

• Contact me: leachmas@ohsu.edu

• Together we can make this happen!

Summary: Epidemiologic and Technologic Tools Can

Contribute Directly to Research Efforts

Acknowledgements!

Dan & Courtney Webster

Stephen Friend

Andrew Trister

Divya Nag

Jeff Williams

Lisa Domenico

Berwick Baker Edelson Guild

Norris

Edison Eberting

Gershenwald

Olbricht Rigel

Kashani Tumeh

Kirkwood Swetter

Kean

Zone Halpern

Geller

Weinstock

Thought

Leaders