Genetic and environmental determinants in lung cancer progression and survivorship
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Genetic and Environmental Determinants in Lung Cancer Progression and Survivorship. Ping Yang, M.D., Ph.D. Professor and Consultant Department of Health Sciences Research Department of Medicine Department of Medical Genetics Mayo Comprehensive Cancer Center Mayo Clinic College of Medicine.

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Genetic and environmental determinants in lung cancer progression and survivorship

Genetic and Environmental Determinants in Lung Cancer Progression and Survivorship

Ping Yang, M.D., Ph.D.Professor and Consultant

Department of Health Sciences ResearchDepartment of MedicineDepartment of Medical GeneticsMayo Comprehensive Cancer Center

Mayo Clinic College of Medicine


Outline
Outline

  • Overview of lung cancer prognosis

  • Known determinants of lung cancer survival:environment and genes

  • Identify and validate new predictors for lung cancer survival:ongoing efforts

  • Current research using pharmacogenetic-epidemiologic tools: towardsindividualized medicine

  • Characteristics of long-term survivors:amulti-dimensional approach


Acknowledgement: Survivorship Research Team

Medical OncologyThoracic SurgeryChest Pathology

Alex A. Adjei Mark S. Allen Marie-Christine Aubry

James R. Jett Stephen D. Cassivi

Aminah Jatoi Claude DeschampsBiostatistics

Randolph S. MarksFrancis C. Nichols Sumithra J. Mandrekar

Julian R. MolinaPeter C. PairoleroV. Shane Pankratz

Victor F. TrastekJeff A. Sloan (QoL expert)

Pulmonary Medicine

Eric S. EdellMolecular BiologyPsychology

David E. Midthun Julie M. CunninghamMatthew M. Clark

Wilma L. Lingle

Radiation OncologyWanguo LiuPharmocogenomics

Yolanda I. Garces Stephen N. Thibodeau Richard M. Weinshilboum

BioinformaticsNicotine DependenceChaplain

Zhifu SunJon O. EbbertMary E. Johnson

George Vasmatzis

Oncology NursingEpidemiology

Linda Sarna (UCLA) Ping Yang


Overview an old story with continued challenge carcinoma of the lung and bronchus
Overview: An Old Story with Continued ChallengeCarcinoma of the Lung and Bronchus

  • High incidence rate:

    12-13% cancer diagnosis in U.S.;

    >60% diagnosed at a not-curable stage.

  • High mortality rate:

    5-year survival rate is ~15%.

  • Kills more people than any other cancer:

    ~30% of all cancer deaths in U.S.


  • Known Predictors of Early-stage Lung Cancer Survival

Yang et al., 2004, Modified from Brundage et al. 2002


Background a lung cancer research infrastructure

Quantity

and

Quality

of Life

Background: A Lung Cancer Research Infrastructure

Physical &Psychosocial Status:e.g., symptoms, comorbidity, & supports

Health Related Behaviors: e.g.,diet,smoking, & exercise

Staging, PS, & Treatment: TNM, surgery, chemotherapy, & radiotherapy

Host Factors:e.g.,genetic predisposition anddemo-graphic factors

Tumor: e.g., histologic cell type and differentiation grade, biologic & mechanistic genes

CHEST, 2006


A prospective ly followed patient cohort newly diagnosed lung cancer 1997 ongoing
A ProspectivelyFollowed Patient Cohort: Newly Diagnosed Lung Cancer, 1997-Ongoing

Identification, Baseline data, Blood/Tissue

~1000 patients

each year

6 months

follow-up

1 year

follow-up

Annually after

Progression and Death

Svobodnik A, et al, 2004; Yang P, et al. 2005.


Identifying and Validating NewPrognostic Factors1 of 4 groups

Yang et al., 2004, Modified from Brundage et al. 2002


Example: treatment of recurrent lung cancer and post-recurrence survival



Post-Recurrence Survival by Risk Score Group

RS4

RS: 4-6

RS: 6-8

RS>8

ATS, 2006



Identifying and Validating NewPrognostic Factors2 of 4 groups

Yang et al., 2004, Modified from Brundage et al. 2002


Survival by Years Since Quit Smoking, WomenAdjusted for age, packs per day, years smoked, histology, grade, stage, and treatment

Lung Cancer, 2005


Dietary supplement of vitamins and minerals
Dietary Supplement of Vitamins and Minerals

  • In general population, ~40% take vitamin/ mineral supplements regularly.

  • Approximately 80% of cancer patients do so.

  • Both clinical and laboratory data have shown that certain micronutrients effect the growth of malignant cells:

    i.e., vitamins and minerals appear to bemodulators of tumor growth.

  • Are these supplements helping or hurting lung cancer patients?


Dietary Supplement of Vitamins and Minerals: NSCLC

Multivariable Model-Based Survival Curves

P < 0.01

Lung Cancer, 2005


Identifying and Validating NewPrognostic Factors3 of 4 groups

Yang et al., 2004, Modified from Brundage et al. 2002


Chemotherapy treatment outcome
Chemotherapy & Treatment Outcome

  • For stage III (and IV) NSCLC and limited stage SCLC, combined modality of concurrent chemo- and radiotherapy is considered as the standard of care.

  • The goal of such treatment is to improve loco-regional tumor control and minimize metastases without increasing morbidity.

  • Overall, there is a significant benefit in survival, but only in a subset of 25-30% among all treated. Who and why?


Chemotherapy agents in used at mayo clinic during the past eight years 1997 2004
Chemotherapy Agents (in %) Used at Mayo Clinic During the Past Eight Years (1997-2004)

All Chemotherapy First-Line Subsequent Chemotherapy Chemotherapy

Drug Groups

Stage III/IV Stage III&IV Stage III&IV NSCLC SCLC NSCLC SCLC NSCLC SCLC

Total Count (denominator) 1093 247 1093 247 463 107

Platinum-containing Agents (P) 90.1 94.7 85.7 91.5 51.8 61.7

Taxane-containing agents (T) 76.2 30.8 66.1 10.5 45.8 52.3

Gemcitabine (G) 32.0 4.9 13.0 0 47.5 11.2

EGFR inhibitor (E) 8.0 0 2.7 0 12.5 0

Either P or T 91.7 97.2 88.2 96.4 64.4 84.1

Both P and T 74.7 28.3 63.7 5.7 33.3 29.9

Either P or G 94.0 94.7 91.1 91.5 76.9 68.2

Both P and G 28.2 4.9 7.6 0 22.5 4.7

Either P or E 92.2 94.7 88.2 91.5 59.6 61.7

Both P and E 5.9 0 0.3 0 4.8 0

Either T or G 85.3 31.2 78.0 10.5 77.8 56.1

Both T and G 23.0 4.5 1.1 0 15.6 7.5

Either T or E 79.2 30.8 68.6 10.5 54.0 52.3

Both T and E 4.9 0 0.3 0 4.3 0

Either G or E 35.9 4.9 15.6 0 54.0 11.2

Both G and I 4.1 0 0.1 0 6.0 0

None of the above 3.1 2.8 4.6 3.6 9.7 14.0


A BRIEF BACKGROUND Past Eight Years (1997-2004)

  • Platinum-based drugs are commonly used in lung cancer chemotherapy.

  • The glutathione metabolic pathway is directly involved in the inactivation of platinum compounds.


The glutathione pathway and its role in drug detoxification yang et al 2006 jco
The Glutathione Pathway and Its Role Past Eight Years (1997-2004)in Drug Detoxification – Yang et al., 2006; JCO

Glutathione


Gclc g ene platinum based drugs lung cancer survival
GCLC Past Eight Years (1997-2004)Gene, Platinum-based Drugs, & Lung Cancer Survival

Yang et al., 2005


Clinical implications
Clinical Past Eight Years (1997-2004)Implications

  • Genotypes of glutathione-related enzymes may be used as host factors in predicting patients’ survival after treatment with platinum-based drugs.

  • The distribution of GCLC repeats marker:

    GCLC-77: 19% - not use platinum drugs?

    GCLC-7_: 50% - balancing benefit vs. harm?

    GCLC-other: 31% - suitable for platinum-drugs?

Yang et al., 2005


Many shortcomings
Many Shortcomings Past Eight Years (1997-2004)

Much needed to be done…

Other pathways

Paradoxical “toxicities”

Accurate follow-up data


Identifying and Past Eight Years (1997-2004)Validating NewPrognostic Factors- 4 -

Yang et al., 2004, Modified from Brundage et al. 2002


Jtcvs 2006
JTCVS., 2006 Past Eight Years (1997-2004)


Biological markers promises and challenges
Biological Markers: Past Eight Years (1997-2004)Promises and Challenges

  • Treatment response is generally poor.

  • Limited markers to predict prognosis and apply to individualized management.

  • Gene expression profiling, “microarray”, has been widely used to search for answers at molecular level for differed lung cancer survival

  • (Note: DNA microarray measures tens of thousands expressed genes via mRNA simultaneously in tissue or cells)


Emerging evidence shows that the accuracy of expression-based outcome prediction varies greatly among studies.

Converging questions have been raised from researchers and clinicians:

  • Why does gene-based prediction vary?

  • Can DNA expression profiles provide more accurate prediction than conventional predictors?

  • Are gene panels or molecular signatures independent predictors or merely surrogates of conventional factors?


Three pioneer studies larger samples in top tier journals
Three Pioneer Studies: expression-based outcome prediction varies greatly among studies. Larger Samples in “Top-Tier” Journals

  • Stanford group (PNAS 2001;98(24):13784-9):56 cases of lung cancer - 41 AD, 16 SCC, 5 LCLC, 5 SCLC

  • Harvard group (PNAS 2001;98(24):13790-5):186 cases of lung cancer - 127 AD, 21 SCC, 20 carcinoid, 6 SCLC

  • Michigan group (Nat Med 2002;8:816-24): - 86 cases of lung adenocarcinoma




Comparison of survival predictions by a 50-gene signature and combination of clinical and pathologic variables

Sun &Yang, 2006;15:2063-8


Outline1
Outline and combination of clinical and pathologic variables

  • Overview of lung cancer prognosis

  • Known determinants of lung cancer survival:genes and environment

  • Identify and validate new predictors for lung cancer survival:ongoing efforts

  • Current research using pharmacogenetic-epidemiologic tools: towardsindividualized medicine

  • Characteristics of long-term survivors:amulti-dimensional approach


A brief background
A Brief Background and combination of clinical and pathologic variables

  • Individuals who are alive over 5 years after a lung cancer diagnosis are referred to as long-term lung cancer (LTLC) survivors.

  • In the U.S., approximately 26,000 individuals become LTLC survivors annually.

  • A paucity of information regarding the quality of life (QoL) among LTLC survivors.


Longitudinal evaluation of quality of life in long term lung cancer survivors a short story

Longitudinal Evaluation of Quality of Life in Long-Term Lung Cancer SurvivorsA Short story

Overall QoL change between two time periods: under 3years and over5years post diagnosis


Multi dimension follow up measures
Multi-dimension Follow-up Measures Cancer Survivors

Besides medical records, multiple tools:

  • SF-8 Health Survey

  • ECOG* Performance Status Score (*Eastern Cooperative Oncology Group)

  • Lung Cancer Symptom Scale (LCSS)

  • Linear Analogue Self-assessment (LASA)(modified for lung cancer patients)

  • Baecke Questionnaire for Habitual Activities

  • FACT-SP Spiritual Well Being Assessment

  • Other tools (diet, sleep, cognitive function, etc)


Qol assessment
QoL Assessment Cancer Survivors

  • Overall QoL was assessed using LCSS-9:

    - scores 0 (worst) to 100 points (best)

    - as continuous variable: distance in cm on a VAS

    a raw score of the total 100 points

    - as a binary variable

    a poor QoL defined as <50 points(Sloan, 2004)

  • Declining QoL was definedas:

    a 10-point or more decrease between

    the two time periods


A prospective lung cancer cohort long term survivors 2002 2004
A Prospective Lung Cancer Cohort: Cancer SurvivorsLong-term Survivors, 2002-2004

N = 2837

N = 448, 15.8%

Patients diagnosed

1997-1999

5-year

follow-up

Annually after


Declining overall qol over time higher proportion with poor overall qol
Declining Overall QoL Over Time: Cancer SurvivorsHigher Proportion with Poor Overall QoL

Yang et al., 2005


Factors influencing overall qol in long term lung cancer survivors
Factors Influencing Overall QoL in Long-term Lung Cancer Survivors

Poor QoL at

Characteristics<3 year>5 year

Age > 75 years

Education < 16 years 

TNM staging- Stage I

Histology-Poorly/un-differentiated 

Lung cancer treatment

Chemotherapy – Yes 

Radiation therapy – Yes 

Comorbid conditions

COPD 

Heart failure 

Recurrent/subsequent

lung cancer 


Implications
Implications Survivors

  • Our preliminary results show: among the LTLC survivors, the mean overall QoL declined significantly between the two time periods.

    This is in a sharp contrast to long-term survivors of other cancers, e.g., breast cancer, whose overall QoL are compatibleto their age-matched controls.

  • We found substantial differences in factors contributing to their poor QoL ateach time period.


Future directions
Future Directions Survivors

  • Long-term lung cancer survivors may need additional help to improve their QoL.

  • Further research efforts are needed. The next step is to identify factors that are associatedwith a declined vs. an improved QoL over time: environmental, genetic, biological, behavioral, psychosocial.

  • Ultimately, we aim to define modifiable factors and improve QoL of “at risk” survivors.


Acknowledgement: Survivorship Research Team Survivors

Alex A. Adjei Mark S. Allen Marie-Christine Aubry

William R. Bamlet Aaron O. Bungum Stephen D. Cassivi

Jean M. Chovan Matthew M. Clark Claude Deschamps

Julie M Cunningham Jon O. Ebbert Eric S. Edell

Chiaki Endo Susan M. Ernst Erin E. Finke

Yolanda I. Garces Debra L. Hare Shauna L. Hillman

Aminah Jatoi James R. Jett Ruoxiang Jiang

Mary E. Johnson Thomas D. Knowlton Farhad Kosari

Wilma L. Lingle Wanguo Liu Sumithra J. Mandrekar

Randolph S. MarksSheila R. McNallan Rebecca L. Meyer

David E. MidthunJulian R. Molina Francis C. Nichols

Paul J. NovotnyJanice R. Offord Scott H. Okuno

Peter C. PairoleroV Shane Pankratz Jeff A. Sloan

Shawn M. StoddardHiroshi Sugimura Zhifu Sun

William R. TaylorStephen N. Thibodeau Victor F. Trastek

Jason A. Wampfler Richard M. Weihshilboum

Diane K. Wilke Brent A. Williams Joel B. Worra

George Vasmatzis Anthony L. Visbal Xinghua Zhao

ALL STUDY PARTICIPANTS AND SUPPORTERS

THANK YOU!


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