CD8(high)CD57(+) T-cell population as an independent predictor of response to chemoradiation therapy in extensive-stage small cell lung cancer.

OBJECTIVES: Tangible clinical benefit is achieved in only a relatively small proportion of extensive-stage small cell lung cancer (SCLC) patients receiving current treatment strategies. Therefore, a more personalized use of current and novel treatment approaches is of critical importance. Individualized therapy relies on the identification of specific biomarkers predictive of response to a particular type of cancer treatment. Immune-related parameters emerge as powerful biomarkers among a variety of predictors of clinical response to various types of cancer treatment. PATIENTS AND METHODS: Using multicolor flow cytometry, we evaluated a predictive value of CD8(high)CD57(+) T-cell population and its immunosuppressive (FOXP3(+), NKG2A(+)) and cytotoxic (Perforin(+)) subsets in the peripheral blood of extensive-stage SCLC patients (n=82) treated with either chemotherapy-alone (n=24), or chemoradiation therapy (n=42), or receiving best supportive care (n=16). RESULTS: The low level (<20%) of CD8(high)CD57(+) T cells within the peripheral blood CD8(+) T-cell population and the low level (<3%) of the immunosuppressive FOXP3-positive subset within the CD8(high)CD57(+) T-cell population were independent predictors of a better response to treatment with chemoradiation therapy, but not with chemotherapy alone or best supportive care. Importantly there was no significant survival difference between SCLC patients who were: (i) treated with chemoradiation, but had an unfavourable immune profile (≥20% of CD8(high)CD57(+) T cells and ≥3% of its FOXP3-positive subset), (ii) treated with chemotherapy alone, or (iii) received best supportive care. CONCLUSIONS: We show that only a combination of chemotherapy with radiation therapy offered a considerable survival benefit that was confined to a subset of extensive-stage SCLC patients with a favourable predictive immune profile in the peripheral blood.

Prediction of response in cancer immunotherapy.

This review focuses on the relationship between pre-treatment immune parameter values and outcome of immunotherapy of cancer patients. The evidence presented in this review suggests that there is a relationship between pre-treatment immune parameter values and survival of cancer patients treated with immunotherapy. Tumour-infiltrating immune cells may have a predictive value for immunotherapy, but predictive power might be obtained from peripheral blood leukocytes. Use of peripheral blood may be preferable due to the convenience of collection and analysis compared to using tumour-infiltrating cells. In vivo numbers of cells of the immune system correlate better with clinical outcome than their functional activity ex vivo. This suggests that immunological antitumour mechanisms in vivo are not always related to generally accepted functional parameters of lymphocytes, such as cytotoxicity or cytokine production, ex vivo. The proliferative status of CD8(+) T lymphocytes seems promising for prediction of response in cancer immunotherapy.

A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample.

BACKGROUND: Presently available flow cytometric methods of bromodeoxyuridine (BrdUrd) labelling do not provide information on the cell cycle time (TC) and the growth fraction (GF). In this paper, we describe a novel and simple method to estimate TC and GF from flow cytometric analysis of a single tumour sample after BrdUrd labelling. METHODS: The proposed method is based on two assumptions: (1) the number of labelled cells traversing the cell cycle per unit time is constant and (2) the total number of labelled cells is constant throughout the cycle, provided that cells produced after division are excluded. The total numbers of labelled divided G1 cells, labelled divided S cells, labelled undivided S cells, and labelled undivided G2 cells were obtained for DNA histograms of BrdUrd-positive cells in a collected sample. These cell numbers were used to write equations to determine the durations of cell cycle phases, TC and GF. To illustrate the application of the proposed formulae, cell cycle kinetic parameters were analysed in solid SL2 tumours growing in DBA/2 mice and in human T-leukaemia Jurkat cells in culture. RESULTS: The suitability of the proposed method for estimating durations of the cell cycle phases, TC and GF was demonstrated. TC in SL2 tumours was found to be relatively constant at 4 and 10 days after tumour implantation (20.3 +/- 1.1 h and 21.6 +/- 0.9 h, respectively). GF in tumours at day 10 was lower than GF at day 4 (54.2 +/- 7.7% vs. 79.2 +/- 5.9%, p = 0.0003). Approximate values of TC and GF of cultured Jurkat cells were 23.9 h and 79.3%, respectively. CONCLUSION: The proposed method is relatively simple and permits estimation of the cell cycle parameters, including TC and GF, from a single tumour sample after labelling with BrdUrd. We have shown that this method may be useful in preclinical studies, allowing estimation of changes in GF during growth of murine tumours. Experiments with human Jurkat cells suggest that the proposed method might also prove suitable for measurement of cell kinetics in human tumours. Development of suitable software enabling more objective interpretation of the DNA profile in this method would be desirable.

Predictive value of CD8highCD57+ lymphocyte subset in interferon therapy of patients with renal cell carcinoma.

BACKGROUND: The aim of this retrospective study was to evaluate the significance of pre-treatment levels of peripheral blood lymphocyte subsets for survival of renal cell carcinoma (RCC) patients treated with interferon-a2b (IFN). PATIENTS AND METHODS: CD3+, CD19+, CD16&56+, CD4+, CD8+, CD4+CD45ROhigh and CD8highCD57+ lymphocyte subsets in peripheral blood of 85 advanced RCC patients were determined using flow cytometry. The survival of IFN-treated and non-treated patients was analyzed by gradually testing different cut-off levels of each lymphocyte subset. RESULTS: Advanced RCC patients with > or = 30% CD8highCD57+ lymphocytes in the CD8+ subset had shorter survival compared to patients with < 30% CD8highCD57+ lymphocytes in the CD8+ subset (p = 0.01). Treatment with IFN increased overall survival only in the former subgroup of RCC patients (p = 0.02). CONCLUSION: The present study suggests that the percentage of CD8highCD57+ lymphocytes in the CD8+ subset may have a prognostic significance for advanced RCC patients and may have a predictive value in patient selection for survival benefit due to treatment with IFN.