Cutting Edge Research Plenary

Transcription

1 Cutting Edge Research Plenary Xin Shelley Wang, MD MPH, MD Anderson Cancer Center, Houston, TX, United States Amylou C. Dueck, PhD, Mayo Clinic, Scottsdale, AZ, United States John P. Barile, PhD, Univ. of Hawaii, Honolulu, HI, United States Niels Henrik Hjollund, MD PhD, AmbuFlex, Herning, Denmark

2 Inflammatory Gene SNPs as Predictors of Patient-Reported Symptom Related Functioning in Patients with Multiple Myeloma Xin Shelley Wang, MD, MPH Professor, Department of Symptom Research, The University of Texas MD Anderson Cancer Center ISOQOL 2015

3 Rationale Multiple myeloma (MM) is an incurable disease The disease and its treatment often produce significant functional impairment Inadequate understanding of the mechanisms underlying severe symptoms and poor functioning has limited patient care after aggressive cancer therapy The cytokine response in animal models of sickness behavior demonstrates how increased systemic inflammation induces behaviors that resemble symptoms Gap: No investigation on predictive role of identified inflammatory markers on patient s functioning Hypothesis: we expected that certain regulatory single-nucleotide polymorphisms (SNPs) in inflammation genes are associated with functioning in patients with MM

4 PRO Measurement: Psychometrically Validated Tool, the MD Anderson Symptom Inventory (MDASI)-MM Jones et al. J Hematol Oncol, 2013

5 Serum IL-6 is Associated with Multiple Symptoms in Hematopoietic SCT Wang et al. Cancer, 2008

6 Inflammatory Markers and Development of Symptom Burden in Patients with Multiple Myeloma during Autologous Stem Cell Transplantation (AuSCT) Longitudinal study (N=63) Most-severe symptoms (MDASI): fatigue, poor appetite, pain, distress, disturbed sleep Change in serum IL-6 and other inflammatory markers were temporally related to top 5 symptoms in the acute phase (first 30 days) after AuSCT for MM; models adjusted for quadratic time, age, sex, staging, BMI, baseline mood score, stem cell dose, and bortezomib-based induction regimen Univariate models (327 observations) a Multivariate models (310 observations) b Markers Estimate SE Pr > t Marker Estimate SE Pr > t IL < IL MIP-1α MIP-1α sil-6r sil-1r IL CRP Baseline mood score Wang et al. Clin Cancer Res, 2013

7 Longitudinal Analysis of Patient-Reported Symptoms Post-AuSCT and Their Relationship to Inflammation in Patients with Multiple Myeloma Disease was relatively stable 3 9 months post-ausct Patients were not symptom-free: 35% were in the high-symptom group (trajectory analysis) Most-severe symptoms: fatigue, pain, numbness/tingling, bone aches, and muscle weakness, not related to maintenance therapy and tumor response Controlled for clinical variables, elevated baseline TNF-α predicted high-symptom group membership (p = 0.014), fatigue (p=0.014), muscle weakness (p=0.012), and bone aches (p=0.011) Mean concentrations of inflammatory markers by symptom membership (component score of 5 most-severe symptoms) Low-symptom group (n = 22) High-symptom group (n = 11) p-value* Mean SD Median Min Max Mean SD Median Min Max IL sil-1r sil-2ra TNF-α Wang et al. Leuk Lymphma, 2014

8 Racial/Ethnic Disparities in Inflammatory Gene SNPs as Predictors of Risk for Poor Functioning in Patients with Multiple Myeloma 1 Year Post-Diagnosis Methods: Study design: A cross-sectional study Patients: Patients with MM 1 5 years postdiagnosis Outcome measure: Patients rated symptom-related functional impairment on the 6 interference items of the MD Anderson Symptom Inventory (MDASI) Symptom interference with general activity, work, walking, mood, enjoyment of life, relations with others Rated on a 0 10 scale, with 0 = does not interfere and 10 = interferes completely Recall period: last 24 hours

9 Cytokine SNP Selection Buccal-swab DNA samples. IL-1β -511 C>T (rs16944): the T allele may lead to decreased IL-1β expression TNFα -308G>A (rs ): the G allele is associated with a higher TNF-α and TNF-β expression IL6-174 G>C (rs ): the C allele is associated with a lower IL-6 synthesis IL A>G (rs ): the A allele is associated with a higher serum IL-10 level

10 Statistical Analysis Cluster analysis: all 6 MDASI-MM symptom interference items divided patients into subgroups with good or poor functional status Logistic regression models: examined the relationship between SNPs and poor functioning, adjusted for age, sex, MM stage, performance status (PS), comorbidities, and body mass index Analysis by race: non-hispanic white vs. other (minority), due to the difference in SNP distribution among races on symptom outcomes

11 Study Sample Demographic Characteristics N = 344 Age (yrs) 63.4 ± 9.7 Female 159 (46.2%) Non-Hispanic white 222 (64.5%) Performance status (ECOG PS 1) 254 (73.8%) Stage III or higher 80 (23.3%) Comorbid conditions (44.2%) Underwent stem cell transplant 261 (75.9%) Years of cancer 4.5 ± 3.3 BMI 30.5 ± 7.5

12 MDASI Symptom Interference in the High- and Low-Interfernce Groups Mean Score of MDASI- Interference Item Low- Interference Group (N= 237) High- Interference Group (N= 107), 31% Mean SD Mean SD Effect Size (Cohen s d) Component score of MDASI- Interference Activity Mood Work Relations Walking Enjoy Life WAW REM

13 Cytokine Genotypes Distributed Differently among Racial Groups White (n=222) Black (n=75) Hispanic (n=32) Other (n=15) P (χ 2 test) IL1β -511 CC 90 (40.5%) 13 (17.3%) 9 (28.1%) 2 (13.3%) <.0001 CT 110 (49.5%) 39 (52.0%) 15 (46.9%) 7 (46.7%) TT 22 (9.9%) 23 (30.7%) 8 (25.0%) 6 (40.0%) TNFα -308 AA 38 (17.1%) 10 (13.3%) 4 (12.5%) 3 (20.0%) GA 113 (50.9%) 41 (54.7%) 19 (59.4%) 8 (53.3%) GG 71 (32.0%) 24 (32.0%) 9 (28.1%) 4 (26.7%) IL AA 20 (9.0%) 8 (10.7%) 7 (21.9%) 2 (13.3%) AG 37 (16.7%) 21 (28.0%) 6 (18.8%) 8 (53.3%) GG 165 (74.3%) 46 (61.35%) 19 (59.4%) 5 (33.3%) IL6-174 CC 26 (11.7%) 1 (1.3%) 1 (3.1%) 0 <.0001 GC 119 (53.6%) 14 (18.7%) 10 (31.3%) 2 (13.3%) GG 77 (34.7%) 60 (80.0%) 21 (65.6%) 13 (86.7%)

14 Cytokine Genotype Distributions by Tumor Response Genotype Response (n=134) Stable Disease (n=137) Disease Progressing/Relapse (n=73) 21% IL-6 174, n (%) CC 12(8.96) 9(6.57) 7(9.59) GC 57(42.54) 60(43.80) 28(38.36) GG 65(48.51) 68(49.64) 38(52.05) IL-1β 511, n (%) CC 43(32.09) 45(32.85) 26(35.62) CT 71(52.99) 64(46.72) 36(49.32) TT 20(14.93) 28(20.44) 11(15.07) TNF-a 308, n (%) GG 42(31.34) 45(32.85) 21(28.77) GA 71(52.99) 68(49.64) 42(57.53) AA 21(15.67) 24(17.52) 10(13.70) IL , n (%) AA 11(8.21) 15(10.95) 11(15.07) AG 27(20.15) 30(21.90) 15(20.55) GG 96(71.64) 92(67.15) 47(64.38) P

15 Risk Factors for being in a High Interference Group Membership of High Overall Interference Non-Hispanic White Other OR (95% CI) P OR (95% CI) P Age 0.95( ) Stage3 2.89( ) ECOG PS, _1 vs ( ) ( ) BMI 1.05( ) PT_Radiation 2.38( ) Anemia 2.75( ) IL-1β 511, CC vs CT/TT 1.98( )

16 Risk Factors for a Rating of 4 10 on Single Interference Items MDASI- Interference Item Non-Hispanic White Other OR (95% CI) P OR (95% CI) P Activity Staging 3.26( ) ECOG PS, 1-3 vs ( ) ( ) BMI 1.11( ) <.0001 Anemia 2.31( ) Walking ECOG PS, 1-3 vs ( ) ( ) BMI 1.09( ) Anemia 3.28( ) IL 6-174, GG vs GC/CC 4.66( ) Staging 3.86( ) Gender (F vs. M) 2.40( ) Enjoy Life Age 0.95( ) ECOG PS, 1-3 vs ( ) Years of MM 0.87( ) TuR3 1.85( ) IL1β -511, CC vs CT/TT 1.92( )

17 Discussion Perceived or self-rated physical health or functioning: among top 5 outcomes of GeneQol Consortium activities (Sprangers et al, 2009) We found that symptoms were interfering with physical and affective functioning in one-third of patients with MM, based on patient-rated MDASI interference scores Our results supports growing evidence of the inflammation hypothesis in human study Racial/ethnic factors Contribute to the role of expression-regulating polymorphisms in cytokine genes Predict functional status in patients with MM; group with consistently high symptom burden Further study should include both inflammatory genes/pathways and other candidates Health care implication: Screening for predisposition to deficits provides evidence for allocating care to individuals with the greatest need

18 Acknowledgements MD Anderson Cancer Center This work was supported by NCI P01 CA124767; PI: Dr. Charles S. Cleeland Department of Symptom Research Drs. Qiuling Shi, Lori Williams, Tito Mendoza, Charles Cleeland Research team Department of Head & Neck Surgery: Dr. Guojun Li for SNP work Department of Lymphoma and Myeloma Drs. Robert Orlowski, Nina Shah contributed patients

19 Cutting Edge Research Plenary Thank you to our sponsor: Abacus International