Cancer

1. PROGNOSIS STUDY OF HIV-RELATED
LYMPHOMA
CHUN CHAO, PH.D.,
DEPARTMENT OF RESEARCH AND EVALUATION
KAISER PERMANENTE SOUTHERN CALIFORNIA
1

2. HIV-INFECTION AND NON-HODGKIN LYMPHOMA (NHL)
• HIV-infected persons are at increased risk of
developing NHL compared to the general
population.
 AIDS defining cancer.
• Use of highly active antiretroviral therapy
(HAART) has significantly decreased the
occurrence of NHL in HIV+ persons.
2

3. HIV INFECTION AND RISK OF NHL (CONT.)
• However, HIV-infected persons are still at
increase risk of NHL in the HAART era.
1
crude rate per 100,000 person-years
2
Rate ratios from Poisson regression models included terms for HIV status, age, sex, calendar period, and
race/ethnicity. Standard multiple imputation methods were used with imputation for missing
race/ethnicity.
Table source: Silverberg et al. AIDS 2009, 23(17): 2337-2345.
3

4. NHL IN HIV-INFECTED PATIENTS
 Not only are HIV+ persons at significantly
elevated risk of NHL, they also tend to have
a more aggressive course of disease.
 Diagnosed at advanced stage
 Extranodal involvement
 CNS lymphoma
 B symptoms
Graph source: http://diseaseminutely.com/diseases/infectious-
diseases/hiv-and-aids/
4

5. CHANGE IN TREATMENT PARADIGM FOR HIV+ NHL
 Before HAART, NHL mortality approaches
100%, and most standard treatment is highly
toxic.
 In the HAART era, CHOP appear to be
tolerably by HIV+ patients diagnosed with
NHL.
 The safety of rituximab use in HIV+ patients
has been controversial.
 Time to evaluate care standard for HIV+
patients with NHL, and to investigate novel
treatment approaches.
5

6. SURVIVAL OF HIV+ NHL PATIENTS IN THE PRE-
AND POST-HAART ERA
Graph source: Lim et al, J Clin Oncol 2005;23:8477-8482.
6

7. SURVIVAL IN NHL PATIENTS
 More than half (59%) of the HIV+ NHL died within 2
years, compared to 29% in HIV-uninfected cases.
2-year overall mortality 2-year lymphoma-specific mortality
7

8. INCREASED MORTALITY IN HIV+ NHL PATIENTS –
MULTIVARIABLE ANALYSES
Table source: Chao et al. AIDS. 2010; 24(11): 1765–1770
8

9. PROGNOSTIC FACTORS IN HIV+ NHL PATIENTS
 In the pre-HAART era, only CD4 cell count,
but not lymphoma characteristics, appeared
to predict survival. In the HAART era,
lymphoma characteristics, such as stage,
have been reported to predict survival in
HIV+ NHL.
 We are interested in identifying tumor
markers that explain the aggressiveness and
heterogeneity of HIV+ lymphoma.
9

10. BACKGROUND – HIV+ DIFFUSE LARGE B-CELL LYMPHOMA
 Diffuse large B-cell lymphoma (DLBCL) is the
most common subtype of HIV+ NHL.
 HIV-related DLBCL is no longer invariably
fatal and is heterogeneous in clinical
outcomes.
 Despite the availability of potentially effective
regimens for DLBCL treatment, more than 50% of
HIV+ patients continue to succumb to the disease.
10

11.  Objective:
 To determine the prognostic significance of novel
viral/molecular markers in HIV-related DLBCL in the HAART
era.
 Rationale:
 Clinical prognostic factors, such as International Prognostic
Index (IPI), do not always accurately predict patient survival.
 A predictive equation combining clinical prognostic markers
and tumor markers may further enhance patient risk
stratification.
 Our results may help to identify new molecular therapeutic
targets for resistant tumors.
11

12. STUDY METHODS
 Study Design:
 Cohort study.
 Study population:
 HIV+ DLBCL cases diagnosed between 1996-2007 at KP Southern
and Northern California.
 Data collection on outcomes and covariates:
 Kaiser Permanente’s electronic medical records.
 Medical chart abstraction.
 Relevant clinical symptoms: e.g., B symptoms.
 Earliest date of known HIV infection.
 Clinical disease progression: e.g., relapse, progression.
12

13. ANALYSIS OF TISSUE SPECIMENS
Pathology review:
 Selection of appropriate tissue specimen.
 Diagnosis confirmation and DLBCL subtyping.
 Two study pathologists independent conducted the assessment.
Discrepancy resolved by consensus.
13

14. ANALYSIS OF TISSUE SPECIMENS (CONT.)
 Archived FFPE tumor blocks.
 Tissue microarray and immunohistochemistry.
 EBV infection was determined by in situ hybridization of EBV-
encoded RNA (EBER).
 Tumor expression of selected B-cell oncogenic markers in the
following categories:
 Viral factor: EBV, HHV8.
 Cell cycle promoters: cyclin D2, cyclin E, cMYC, p27, SKP2.
 B-cell activators: BCL6, FOXP1, PKC-beta 2 and CD21.
 Apoptotic regulators: BCL2, p53, survivin, BAX, GAL3, and BLIMP1.
 Others: CD10, MUM1, Ki-67, CD44, CD30, CD43, LMO2, and
MMP9.
14

15. IMAGE OF TMA CORES
15

16. STUDY METHODS (CONT.)
 Outcome of interest:
 Overall survival and progression-free survival.
 Follow-up:
 Up to 5 years after DLBCL diagnosis (minimum 3 yrs).
 Statistical analysis:
 Multivariable Cox model.
 Propensity score used for adjusting for potential confounding.
 Bootstrapping for validation.
16

17. STUDY POPULATION
17

18. STUDY POPULATION FOR TUMOR MARKER ANALYSIS
 Of 194 HIV+ DLBCL cases identified; 80 had
sufficient tissue for study inclusion.
 We compared the demographic, HIV disease
factors, DLBCL characteristics, and co-
morbidity history among those who did vs. did
not have an adequate tumor specimen.
 No important difference was found between those who
were included vs. those who were not.
18

19. BASELINE CHARACTERISTICS KP Northern KP Southern
California California
Total
(N=131) (N=63) (N=194)
Mean (SD)/Percent
Age, yr 47 (10) 48 (10) 47 (10)
Male gender 97% 90% 95%
White Race 66% 49% 60%
Stage
I (Localized) 26% 19% 24%
II (Regional) 17% 16% 16%
III (Distant) 54% 49% 53%
Extranodal involvement
Stage I: 10, 11, 12 27% 22% 25%
Stage II: 20, 21, 22, 23 16% 14% 15%
Stage III: 30, 31, 32, 33 15% 16% 15%
Stage IV: 88 Disseminated 40% 44% 42%
B symptoms
No B symptoms 47% 46% 47%
Any B symptoms 32% 43% 36%
Unknown 21% 10% 17%
HIV risk group
Heterosexual 11% 22% 15%
IDU 8% 0% 5%
MSM 61% 30% 51%
OTH/UNK 20% 48% 29%
Prior AIDS diagnosis 42% 63% 49%
Prior use of HAART 59% 71% 63%
CD4 cell count at DLBCL dx
204.3 (181.08) 187.4 (159.82) 198.5 (173.84)
19
Mean (SD), cells/mm 3

20. FINDINGS OF TUMOR MARKER EXPRESSION
 We found that Ki-67, PKC-beta 2, CD44, and
survivin were expressed (i.e., 2+) in the
majority of these HIV-related DLBCL cases.
 On the other hand, expression of HHV8,
CD21, cyclin D2, SKP2, and BLMIP1 was
uncommon.
 31% of cases were positive for EBV; 4%
positive for HHV8.
 We did not find universal CD20 expression in
these cases, suggesting that CD20 might be
lost in some HIV+ DLBCL.
20

21. CLUSTER EXAMINATION OF TUMOR MARKERS
 We examined the pair-wise Pearson’s
correlation coefficient between the
expressions of all markers.
 The correlation coefficient was generally low
(i.e., <0.25).
 Notably, EBV and HHV8 infection status was
associated with the expression of several
markers.
21

22. MARKER EXPRESSION & HAZARD RATIO (HR)
OF MARKER POSITIVITY ON 2-YEAR MORTALITY
Adjusted HR adjusted for stage, presence of B symptom, Germinal Center phenotype, prior AIDS
and CD4 cell count.
22

23. HIV+ DLBCL PROGNOSTIC TUMOR MARKERS
 In the crude analysis, cMYC, EBV and BLIMP1 positivity
was associated with greater 2-yr overall mortality.
Red : cMYC+, Blue: cMYC - Red : EBV+, Blue: EBV -
23

24. 2-YEAR OVERALL SURVIVAL BY CD4 AND MARKER LEVELS
Red: high CD4/low marker; Blue: high CD4/high marker
Green: low CD4/low marker; Black: low CD4/high marker
24

25. SUMMARY OF IMMUNODECIFENCY AND
PROGNOSTIC TUMOR MARKER ANALYSIS
 Cases with low CD4 and high levels of EBV or
cMYC had worse survival.
 Risk stratification may consider both CD4
and tumor marker expression, although
confirmation is needed in larger studies.
25

26. FUTURE STEPS
 Future analysis will incorporate
 Progression-free survival.
 Validation using bootstrapping.
 Examination of trend in treatment pattern for HIV+ DLBCL.
 Effects of antiretroviral medication discontinuation on
lymphoma outcome.
 Tumor marker expression comparison by HIV infection
status.
26

27. ACKNOWLEDGEMENTS
HIV-related DLBCL study investigator team:
Kaiser Permanente Southern California: Drs. Chun Chao
(PI), Reina Haque, and Daniel H Zha.
Kaiser Permanente Northern California: Drs. Michael
Silverberg (site PI) and Laurel Habel.
University of California, Los Angeles: Drs. Jonathan Said
(Site PI) and Otoniel Martínez-Maza.
University of California, San Francisco: Dr. Donald
Abrams (Site PI).
Funding: R01CA134234-01 from the NCI (Chao),
K01AI071725 from the NIAID (Silverberg).
27

28. THANK YOU FOR YOUR ATTENTION
Questions?
28