Immune Monitoring of Cancer Patients by Multi-color Flow Cytometry

Abstract Introduction There are still substantial morbidity and mortality caused by insufficient immunologic recovery after allo-HSCT. In this context, we attempt to evaluate the clinical relevance of immune monitoring in allo-HSCT recipients. Method Fifty five patients who underwent allo-HSCT between 2008 and 2012 were included. Peripheral blood samples were drawn from recipients before transplant, and on 4, 8, 12, 24, 36 and 48 weeks after transplant. Each blood samples were analyzed by multi-color flow cytometry for determining lymphocyte subsets. MNC were separated from blood specimen, and analyzed for the quantitation of Treg with the use of real-time PCR. We also examined T cell derived IFN-r by using in vitro culture, intracellular staining, and flow cytometry analysis. Results The median age was 43, and AML was the most common reason for transplantation (49.1%). Grade II or more aGVHD occurred in 36.4% of cases, and 49.1% exhibited moderate or severe cGVHD. The differences in the proportion (%) and the absolute number (/uL) of CD4+, CD8+ cells, CD4+ derived IFN-r (%), CD8+ derived IFN-r (%), and Treg (%) between the groups (Gr. II or more aGVHD (+) vs (-); moderate or severe cGVHD (+) vs (-)) were compared by Two sample t-test. Patients with Gr. II or more aGVHD showed decreased CD4+ count at 4, 8 and 12 weeks, but showed rather higher CD8+ count at 8 weeks after transplant. T-cell secretion function assessed by IFN-r (%), and Treg (%) was similar between two groups within 12 weeks after transplant. In case of cGVHD, both CD4+ and CD8+ count tended to be higher in patients with moderate or severe cGVHD, and the trends lasted for up to 48 weeks from allo-HSCT. Treg (%) was almost consistently lower throughout the period in these patients. There were 12 relapses within follow up period (median 36.1 months), and higher slope of post-transplant increase in CD8+ count and CD8 derived IFN-r were identified as protective factors for disease relapse. Conclusion In view of the results so far achieved, slow recovery of CD8 count and function might be associated with disease relapse. However, this is still a preliminary data, and warrants further evaluation. Disclosures: No relevant conflicts of interest to declare.

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Calculation of an immunoscore based on extensive flow cytometry analysis of PBMCs from metastatic breast cancer patients treated with docetaxel alone or in combination with vaccine.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.26_suppl.31 ◽

2013 ◽

Vol 31 (26_suppl) ◽

pp. 31-31 ◽

Cited By ~ 1

Author(s):

Italia Grenga ◽

Renee Nicole Donahue ◽

Peter Sungwhan Kim ◽

Brendan Dempsey ◽

James L. Gulley ◽

...

Keyword(s):

Breast Cancer ◽

Flow Cytometry ◽

Metastatic Breast Cancer ◽

Cancer Patients ◽

Therapeutic Vaccine ◽

Metastatic Breast ◽

Flow Cytometry Analysis ◽

Breast Cancer Patients ◽

Color Flow ◽

Rank Analysis

31 Background: Therapeutic vaccine is emerging as a potentially efficacious and safe treatment for cancer patients. However, markers are not available to identify patients more likely to benefit from this treatment. Aim of this retrospective study was to analyze before treatment immune subsets that correlated with clinical outcome in metastatic breast cancer patients treated with docetaxel alone or in combination with vaccine. Methods: We applied multi-color flow cytometry analysis of PBMCs harvested prior to treatment from patients (n=43) enrolled in a small randomized phase II study of docetaxel alone (n=20) or in combination with PANVAC-V (Vaccinia) and PANVAC-F (Fowlpox) encoding for the tumor-associated antigens CEA and MUC-1, along with a TRIad of COstimulatory Molecules (B7-1, ICAM-1, and LFA-3; called TRICOM) (n=23). Frequency of more than 200 immune sub-populations before treatment was measured by flow cytometry. Each of the resulting subsets was ranked in tertiles. For immune subsets that correlated directly with PFS, 2 points were assigned if the frequency fell in the highest tertile, 1 point if in the middle, and 0 if in the lowest tertile. For subsets that correlated inversely with PFS, the points were assigned in the opposite order. An immunoscore was calculated based on the sum of points assigned to each subset. Log-Rank analysis, with the cutoff based on the median of the immunoscores, was performed to evaluate differences in PFS between patients with a low and high immunoscore. Results: In vaccine plus docetaxel arm, 10 immune subsets from PBMCs before treatment correlated with PFS and were used for the calculation of the immunoscore. Patients with an immunoscore above the median showed a statistically significant longer PFS compared to those with lower score in vaccine plus docetaxel arm (p<0.001, HR=0.1466, 95% CI= 0.0478-0.4375) but not in docetaxel alone arm (p=0.097, HR=0.418, 95% CI=0.147-1.172). Conclusions: Calculation of an immunoscore from PBMCs before treatment based on flow cytometry screening of immune subsets may identify patients that will most likely benefit from vaccine combination immunotherapy.

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