Immunological biomarkers predictive of clinical response to chemotherapy and maintenance HAART in HIV + patients with Kaposi sarcoma

Transcription

1 P909 Immunological biomarkers predictive of clinical response to chemotherapy and maintenance HAART in HIV + patients with Kaposi sarcoma Tedeschi R, Bidoli E 2, Bortolin MT, Pratesi C, Basaglia G, Zanussi S, Schioppa O 3, Vaccher E 3 & De Paoli P 4 Microbiology-Immunology and Virology Unit, 2 Epidemiology Unit, 3 Medical Oncology A, 4 Scientific Directorate, Centro di Riferimento Oncologico, IRRCS, Aviano, Italy

2 INTRODUCTION AND PURPOSE In the era of highly active antiretroviral therapy (HAART), Kaposi sarcoma (KS) still represents a common disease, with a wide variation in outcome and survival. Infection with Kaposi sarcoma herpesvirus (KSHV) together with an unregulated immunological state of cytokines, growth factors and angiogenic factors represent the fundamental conditions for the development and/or progression of HIV-related KS. Luminex multiparametric technology, an innovative, high throughput and precise analytical system, allows the simultaneous analysis and quantification of a wide spectrum of biomarkers. Identification of new non invasive laboratory biomarkers, that further support clinical patient s management and help to predict clinical response and outcome, is a very active area of investigation. Our longitudinal study analysed blood levels of selected cytokines and soluble factors involved in inflammation, tumour growth and angiogenesis, in HIV+ KS patients, before and after chemotherapy (CT) and during maintenance (m)-haart. The feasibility of these blood biomarkers for monitoring disease and predicting KS clinical patient response to the therapy was evaluated. In parallel, the predictive significance of KSHV DNA, HIV RNA, CD4 and CD8 cell counts were also assessed.

3 Patients and samples: 27 HIV+ patients with histological confirmed KS; blood samples collected at: T0: before starting chemotherapy (CT); T: the end of chemotherapy (CT); T2: the time of maximum m-haart response; Laboratory Immuno-virological parameters: KSHV DNA, HIV RNA; CD4/CD8 cell counts; Panel : FGF-2, IFN-γ, IFN-α2, IL-RA, IL-β, TNF-α, VEGF, TGF-α, IL-7, IL-2, IL-4, IL-6, IL-7, IL-8, IL-3, IL-2(p40), MIP-α, MIP-β. Panel 2: Angiopoietin-2, BMP-9,Endoglin, Endothelin-, Follistatin, G-CSF, HB-EGF, HGF, leptin, PLGF and EGF. Metalloproteinases:MMP-,MMP-2,MMP-3,MMP-7,MMP-9,MMP-0,MMP-2,MMP-3. Outcomes: CT and m-haart response. Statistical analysis: METHODS Hazard Ratios (HRs) in continuous and corresponding 95% Confidence Intervals (CIs).

4 METHODS KSHV DNA (ORF 65) real time PCR HIV RNA real time PCR (Abbott Molecular) Luminex technology Flowcytometry: CD4/CD8 cell counts

5 RESULTS In the univariate analysis, two angiogenic factors measured at T0 were found to be associated to unfavourable clinical observed response to CT: increasing blood levels of - HB-EGF (p=0.03) - Follistatin (p=0.03) In the univariate analysis, angiogenic factors measured at T0 associated to poor mhaart response were: increasing blood levels of decreasing levels of - MIP-β (p=0.04) - FGF-2 (p=0.04) - IL-RA (p=0.04) - TNF-α (p=0.0) - INF-α2 (p=0.05) - IL-7A (p=0.05) - Endoglin (p=0.0) - MMP-2 (p=0.04) Both high HIV RNA (p=0.04) and KSHV DNA (p=0.04) viral load, measured before starting CT (T0), were associated to poor m-haart response.

6 Baseline KSHV DNA and HIV RNA viral load, CD4 and CD8 cell counts, evaluated in the 27 HIV+ KS patients Median (min-max) KSHV DNA c/ml 50 (0-8247) HIV RNA c/ml 70 ( ) CD4 % 6.9 ( ) CD4 cells/μl 88 (7-036) CD8 % 53.9 ( ) Baseline concentration of the different Metalloproteinases (MMP), evaluated in the 27 HIV+ KS patients Median (min-max) pg/ml MMP ( ) MMP ( ) MMP (2-242) MMP ( ) MMP ( ) MMP ( ) MMP ( ) MMP (62-986) CD8 cells/μl 860 ( )

7 Baseline concentration of the different cytokines, chemokines, growth factors and angiogenesis factors, evaluated in the 27 HIV+ KS patients Median (min-max) pg/ml IFN-γ 9.9 ( ) IL ( ) IL-2(p40) 9.2 ( ) MIP-β 3.3 ( ) IL-β 0.8 ( ) IL ( ) IL ( ) TGF-α 2.2 ( ) FGF ( ) IL-RA 77.4 ( ) IL-7.3 ( ) IL-7A 4.7 ( ) TNF-α 4.4 ( ) IFN-α ( ) IL ( ) Median (min-max) pg/ml IL ( ) MIP-α 4.9 ( ) VEGF 60.7 ( ) PLGF 3.8 (.3-6.2) HB-EGF 28.8 ( ) HGF.3 ( ) Follistatin ( ) Leptin ( ) Endothelin- 2.6 ( ) Endoglin 3.3 ( ) BMP ( ) G-CSF 56.9 ( ) EGF 28.8 ( ) Angiopoietin ( )

8 Hazard Ratios (HR) and corresponding 95% Confidence Intervals (CI) for Chemotherapy (CT) response according to immunological biomarkers found to be statistically significant in 27 HIV+ KS patients Variable Progression /response to CT Median (pg/ml) Min-Max (pg/ml) HR continuous (95%CI) p-value HB-EGF (.-.8) 0.03 Follistatin (.0-2.0) 0.03

9 Variable Progression /response to m-haart Median (pg/ml) Min-Max (pg/ml) HR continuous (95%CI) p-value MIP-β (.0-.4) 0.04 FGF (.0-4.5) 0.04 IL-RA (.0-2.3) 0.04 IL-7A (.0-3.4) 0.05 TNF-α (.2-4.8) 0.0 INF-α (.0-.0) 0.05 Endoglin ( ) 0.0 MMP (.0-.00) 0.04

10 Hazard Ratios (HR) and corresponding 95% Confidence Intervals (CI) for m-haart response according to virological biomarkers found to be statistically significant in 27 HIV+ KS patients Variable Progression /response to m-haart Median (cp/ml) Min-Max (cp/ml) HR continuous (95%CI) p-value KSHV DNA (.0-.7) 0.04 HIV RNA (.0-.0) 0.04

11 CONCLUSIONS Some blood biomarkers, evaluated at baseline in KS patients, were associated to clinical response to chemotherapy and m-haart. In particular: pretreatment plasma levels of HB-EGF and Follistatin were associated to poor clinical response to chemotherapy; pretreatment plasma levels of MIP-β, FGF-2, IL-RA, IL-7A, TNF-α, INF-α2, Endoglin and MMP-2 and high KSHV DNA and HIV RNA viral load were associated to poor clinical response to m-haart; The simultaneous analysis of several biomarkers by Luminex multy-analyte profiling technology may represent an innovative tool in KS clinical monitoring. These non invasive laboratory biomarkers might be useful adjuncts as predictors of patient s prognosis in KS HIV+ follow-up. The identification and measurement of soluble biological markers involved in inflammation, angiogenesis and tumor growth will contribute to shed new insights into KS pathogenesis and to highlight targets for future treatment strategies.