Bone Marrow Transplantation
SEARCH     advanced search my account e-alerts subscribe register
Journal home
Advance online publication
Current issue
Archive
Press releases
For authors
For referees
Contact editorial office
About the journal
For librarians
Subscribe
Advertising
naturereprints
Contact Springer Nature
Customer services
Site features
NPG Subject areas
Access material from all our publications in your subject area:
Biotechnology Biotechnology
Cancer Cancer
Chemistry Chemistry
Dentistry Dentistry
Development Development
Drug Discovery Drug Discovery
Earth Sciences Earth Sciences
Evolution & Ecology Evolution & Ecology
Genetics Genetics
Immunology Immunology
Materials Materials Science
Medical Research Medical Research
Microbiology Microbiology
Molecular Cell Biology Molecular Cell Biology
Neuroscience Neuroscience
Pharmacology Pharmacology
Physics Physics
Browse all publications
 
June (2) 2001, Volume 27, Number 12, Pages 1237-1243
Table of contents    Previous  Article  Next   [PDF]
Progenitor Cell Mobilisation
The CD3-16+56+ NK cell count independently predicts autologous blood stem cell mobilization
D A Stewart1, D Guo2, J Luider3, I Auer3, J Klassen4, D Morris1, C B Brown1, A Chaudhry1, S Glück1 and J A Russell1

1Department of Medicine, Tom Baker Cancer Centre, University of Calgary, and Foothills Hospital, Calgary, Alberta, Canada

2Department of Epidemiology, Tom Baker Cancer Centre, University of Calgary, and Foothills Hospital, Calgary, Alberta, Canada

3Department of Flow Cytometry, Tom Baker Cancer Centre, University of Calgary, and Foothills Hospital, Calgary, Alberta, Canada

4Department of Apheresis, Tom Baker Cancer Centre, University of Calgary, and Foothills Hospital, Calgary, Alberta, Canada

Correspondence to: Dr D Stewart, Tom Baker Cancer Centre, 1331-29th Street, NW, Calgary, AB, Canada T2N 4N2

Abstract

Better predictive factors for autologous blood stem cell mobilization (BSCM) are needed. The purpose of this study was to determine if an independent association exists between lymphocyte or NK cell counts and BSCM. Data were analyzed on 141 consecutive patients aged 19-69 years (median 45) who received combined chemotherapy plus G-CSF for BSCM, and who had measurements of immune cells prior to BSCM. Of the 141 patients, 41% had breast cancer, 14% Hodgkin's disease, 34% non-Hodgkin's lymphoma, and 11% other diagnoses. BSCM involved dose-intensive cyclophosphamide, etoposide, cisplatin (DICEP) plus G-CSF 300 mug (<70 kg) or 480 mug (>70 kg) for 45% of patients, while the remaining 55% received other chemotherapy plus similar doses of G-CSF. Only a single apheresis was performed for 94% of patients. The following factors were analyzed for predictors of BSCM: age, gender, prior chemotherapy, prior radiotherapy, diagnosis, disease status, marrow involvement, mobilization regimen, Hb, WBC, platelet count, B cell, T cell, and NK cell counts. The peripheral blood CD34+ counts on the first day of apheresis (PBCD34) were 6-1783 ´ 106/l (median 150). The PBCD34 count correlated strongly with the number of CD34+ cells collected/l blood apheresed and with the number of CD34+ cells collected/kg. By multivariate analysis using continuous variables, relapsed status (P = 0.0003), not using DICEP mobilization (P = 0.0001), female gender (P = 0.0057), low platelet count (P = 0.051), and low CD3-16+56+ count (P = 0.0158) were associated with low PBCD34 counts. Using categorical variables, the only factors that independently predicted a PBCD34 count <150 ´ 106/l were: >1 prior chemotherapy regimen (odds ratio = 5.12, P = 0.0003), not using DICEP mobilization (odds ratio = 4.94, P = 0.0001), and CD3-16+56+ count <125 ´ 106/l (odds ratio = 2.58, P = 0.0157). In conclusion, the CD3-16+56+ count may be a useful additional predictor of BSCM and warrants further study. Bone Marrow Transplantation (2001) 27, 1237-1243.

Keywords

hematopoietic stem cell transplantation; mobilization; CD34+; NK cells

At least 5-8 ´ 106 CD34+ cell/kg are required in autologous stem cell grafts to ensure rapid hematopoietic recovery after myeloablative therapy and autologous stem cell transplantation (ASCT).1 There are currently several different methods of blood stem cell mobilization (BSCM). Many patients mobilize blood stem cells well following treatment with G-CSF 5-10 mug/kg alone or with a combination of moderately dosed chemotherapy plus G-CSF.1,2 The remaining patients often require more expensive methods of BSCM such as higher dose chemotherapy plus G-CSF,3,4 higher G-CSF doses up to 32 mug/kg,5 or combinations of chemotherapy, G-CSF and stem cell factor (Stemgen; Amgen, Thousand Oaks, CA, USA).6,7 Better predictive factors of BSCM are needed to identify the patients who require these potentially more effective, but also more toxic or expensive methods of BSCM.

Factors previously reported to predict poor BSCM include the method of BSCM, marrow infiltration by tumor, prior radiotherapy, number of cycles or duration of prior chemotherapy, repeated cycles of chemotherapy and G-CSF, and the use of certain chemotherapy agents that are especially toxic to stem cells such as BCNU, melphalan, chlorambucil or mitomycin C.2,3 In addition, the platelet count predicts BSCM, possibly because it reflects marrow damage from prior therapy.8 The possible associations between BSCM and lymphocyte or NK cell counts have not been adequately explored. The lymphocyte count, particularly CD3+4+ count, is known to be very sensitive to cytotoxic therapies in adults.9 Therefore, the lymphocyte count may predict BSCM if the impact of the most recent cytotoxic therapy is relevant to BSCM. Conversely, the NK cell count recovers early following cytotoxic therapy, and therefore, may predict BSCM through a possible association with cumulative damage to the stem cells or marrow stroma.10,11,12,13 The purpose of this study was to determine if an independent association exists between B or T lymphocyte or NK cell counts and BSCM.

Patients and methods

Patient characteristics

As a quality assurance project to follow immune recovery after ASCT, we have measured immune cell counts at baseline and at 1 and 3 months post ASCT. Data were analyzed on 141 consecutive patients aged 19-69 years (median 45) who received combined chemotherapy plus G-CSF for BSCM, and who had measurements of immune cells prior to BSCM. Patient characteristics are listed in Table 1. Peripheral blood counts prior to BSCM are listed in Table 2.

Autologous blood stem cell mobilization and collection

Sixty-four patients received dose-intensive cyclophosphamide 5.25 g/m2, etoposide 1050 mg/m2, and cisplatin 105 mg/m2 (DICEP) divided over days 1-3, G-CSF 300 mug (<70 kg) or 480 mug (70 kg) s.c. daily starting on day 14, and had apheresis scheduled for day 19, 20, or 21. DICEP plus G-CSF is our standard BSCM regimen for most patients with multiple myeloma, Hodgkin's and non-Hodgkin's lymphoma. In particular, lymphoma patients with bulky relapsed, primary refractory or marrow positive disease preferentially received DICEP. The remaining 77 patients underwent BSCM with either: (1) cyclophosphamide 2 g/m2 with or without other agents such as doxorubicin 50 mg/m2, 5-fluorouracil 500 mg/m2, or taxotere 100 mg/m2 (n = 62); (2) ICE (ifosfamide 6 g/m2, cisplatin 105 mg/m2, etoposide 450 mg/m2, n = 11); or (3) other chemotherapy (n = 4). The intention for these latter 77 patients was to receive chemotherapy that was disease-specific and dosed to produce short-duration neutropenia and thrombocytopenia that would not require platelet transfusion. Before combining these patients together, we analyzed them by chemotherapy regimen and found no evidence that any one regimen was significantly better or worse at mobilizing blood stem cells. These 77 patients received daily G-CSF 300 mug (<70 kg) or 480 mug (>70 kg) s.c. starting on day 7 or 8, and underwent apheresis on day 13 or 14.

Peripheral blood CD34+ (PBCD34+) cell counts were monitored each morning prior to planned apheresis. Apheresis took place when all of the following existed: a PBCD34+ count >10 ´ 106/l, platelet count >50 ´ 109/l, and WBC >5 ´ 109/l. There was always an attempt to target peak PBCD34 for the first day of apheresis. All patients underwent large volume apheresis via a central venous apheresis catheter. The apheresis was monitored by CD34+ counts from the collection bag every 4 litres until target CD34+ yields were obtained. Apheresis was discontinued for: (1) target CD34+ yield (usually 5 ´ 106/kg); (2) platelet counts dropping below 40 ´ 109/l; (3) complications such as bleeding or citrate toxicity; or (4) decreasing CD34+ cell collection per litre apheresis during the procedure to levels deemed unsatisfactory to continue. Apheresis was performed with a continuous flow cell separator (Cobe Spectra, Cobe Canada, Scarborough, Ontario, Canada) processing 5-30 litres of blood/day at flow rates of 50-80 ml/min. If on the first day of apheresis over 20 litres of blood were processed and >3 ´ 106 CD34+ cells/kg were collected, a second apheresis procedure was usually not performed. Since a fixed number or volume of aphereses were not performed, it was not appropriate to use the total number of CD34+ cells/kg collected as the dependent variable in this study. The technique for blood stem cell cryopreservation has been previously described.3

Flow cytometric analysis of CD34+ cells was performed using an EPICS XL flow cytometer (Beckman Coulter, Hialeah, FL, USA). CD45-FITC (J33) and CD34-PE (581) (Beckman Coulter, Brea, CA, USA) antibodies were added to 100 mul of peripheral blood using reverse pipetting technique to ensure accuracy. Samples were incubated for 10 min at room temperature in the dark and then lysed using the Beckman CoulterTQ-Prep system. One hundred mul of Flow Count beads (Beckman Coulter) were added to each tube. Data from four parameters were collected for analysis: forward scatter (FS), log side scatter (LSS), LFL1, and LFL2. Acquisition was halted at 100 000 CD45+ events. Hematopoietic progenitor cells were identified and counted in two histograms (CD45 vs CD34 and FS vs LSS) using ISHAGE criteria: dim CD45+, bright CD34+, and forming a discrete cell cluster with larger FS signal than lymphocytes. The use of a known amount of Flow Count fluorospheres allowed the determination of absolute CD34 count directly from the flow cytometer.

Measurement of lymphocyte subsets and NK cells

Immunophenotyping was performed on whole blood using a three-color flow cytometric method. Approximately 1 ´ 106 white blood cells were added to a test tube with directly conjugated monoclonal antibodies and incubated for 10 min at room temperature. The monoclonal antibodies utilized to investigate T, B and NK cell lymphocyte subsets were CD3-PC5, CD4-PE, CD8-FITC, CD19-PC5, and CD3-FITC+CD16/56-PE (Immunotech, Marseille, France). Erythrocytes were then lysed using the TQ-Prep system (Beckman Coulter) and washed with phosphate-buffered saline (PBS). Cells were resuspended in 0.1% paraformaldehyde-PBS. Lymphocyte subset analysis was performed using an EPICS XL flow cytometer (Beckman Coulter), gating on the lymphocyte population identified in a forward scatter vs side scatter histogram.

Statistics

S-plus 2000-Modern Statistics and Advanced Graphics software (Mathsoft Inc., Seattle, WA, USA) was used for the data analysis. The peripheral blood PBCD34 counts on the first day of apheresis (PBCD34), CD34+ cells collected per litre on the first day of apheresis, and CD34+ cells collected per kg body weight on the first day of apheresis were summarized in conjunction with graphs. The summaries and graphs showed that these three variables were not normally distributed. Therefore we attempted to transform them into normal distribution and we found logarithmic transformation was suitable for all the three variables. A strong correlation between any two of these variables was identified using Pearson's product-moment correlation test (r > 0.9 for all). Based on this and the fact that the PBCD34 count is not affected by apheresis techniques, apheresis duration or patient weights, the PBCD34 count was used as the indicator of BSCM in the model-based analysis. The following factors were analyzed for predictors of BSCM: age, gender, diagnosis, disease status, marrow involvement, prior chemotherapy, prior radiotherapy, mobilization regimen, Hb, WBC, platelet count, B cell (CD19+ cells), T cell (CD3+, CD3+4+, CD3+8+), and NK (CD3-16+56+) cell counts. In univariate analysis, one-way analysis of variance was used for categorical variables, and Spearman's rank correlation was used for continuous variables. The association of B and T lymphocyte and NK cell counts with log PBCD34 was further evaluated using multiple regression analysis with other potential confounding variables being simultaneously controlled. These factors were all added into a linear regression model and removed in a backward stepwise manner for P values greater than 0.05. As an exploratory and complementary analysis, we also divided PBCD34 count and CD3-16+56+ count into two groups respectively by their medians and used logistic regression to assess their relationship while other potential confounding factors were simultaneously controlled.

Results

Measures of BSCM

The peripheral blood CD34+ counts on the first day of apheresis (PBCD34) were 6-1783 ´ 106/l (median 150), and CD34+ cell counts on day 1 apheresis were 2-779.5 ´ 106/l blood apheresed (median 61.7 ´ 106/l), and 0.4-103.1 ´ 106/kg (median 11.5 ´ 106/kg). These three measures of BSCM were highly correlated. The Pearson's product-moment correlation coefficient between PBCD34 and CD34+ cell/l apheresed was 0.932, and after log transformation of the two variables the correlation coefficient was 0.960. The Pearson's product-moment correlation coefficient between the PBCD34+ cells and CD34+ cells collected/kg was 0.794, and after log transformation of the two variables the correlation coefficient was 0.910 (see Figure 1). Finally, the correlation coefficient between CD34+ cells/l apheresed and CD34+ cells collected/kg was 0.874, and after log transformation of the two variables the correlation coefficient was 0.955. The PBCD34+ cell count is probably the most direct measure of BSCM because it is not affected by apheresis techniques, apheresis duration, or patient weights. For this reason the PBCD34+ cell count was used as the dependent variable in the remaining analyses.

Univariate analysis of factors potentially associated with BSCM

The analysis of variance for categorical variables is shown in Table 3. In this table, the median values were used as cut-off points for variables such as blood counts and age. Age and blood counts were also analyzed as continuous variables using Spearman's rank correlation. By this latter analysis, platelet count (P = 0.0451) and CD3-16+56+ count (P = 0.0097) were found to correlate with PBCD34+ cell count on the first apheresis day, whereas age (P = 0.6474), hemoglobin (P = 0.0595), WBC (P = 0.1551), lymphocyte count (P = 0.0585), CD3+ count (P = 0.7409), CD3+4+ count (P = 0.7671), CD3+8+ count (P = 0.1913), and CD19+ count (P = 0.6975) did not. The CD19+, CD3+, CD3+4+, and CD3+8+ lymphocyte counts did not correlate with any measure of BSCM. Conversely, the CD3-16+56+ NK cell counts did correlate with BSCM (Figure 2). The CD3-16+56+ counts by quartiles were 8-88, 88-125, 125-215, and 215-654 ´ 106/l. The median PBCD34 for the four CD3-16+56+ quartiles were 121 (6-1613), 127 (7-926), 174 (14-1783), and 198 ´ 106/l (28-1160), respectively (P = 0.011). The CD3-16+56+ count >125 ´ 106/l predicted a PBCD34+ count > the median 150 ´ 106/l with a sensitivity of 61% and specificity of 59%. Likewise, 64% of those who had PBCD34+ cell counts < the first quartile of 60 ´ 106/l had CD3-16+56+ counts <125 ´ 106/l.

Multivariate analysis of factors potentially associated with BSCM

By multivariate analysis using continuous variables, relapsed status (P = 0.0003), not using DICEP mobilization (P = 0.0001), female gender (P = 0.0057), low platelet count (P = 0.051), and low CD3-16+56+ count (P = 0.0158) were associated with low PBCD34 counts.

Using categorical variables, the only factors that independently predicted a PBCD34+ cell count less than the median value of 150 ´ 106/l were: more than one prior chemotherapy regimen (odds ratio = 5.12, P = 0.0003), not using DICEP mobilization (odds ratio = 4.94, P = 0.0001), and a CD3-16+56+ count <125 ´ 106/l (odds ratio = 2.58, P = 0.0157).

Discussion

Now that several alternative methods of BSCM exist, it has become increasingly important to predict when a patient will have difficulty mobilizing blood stem cells. Similar to previous studies,1,2,3,4,5,6,7,8 we found that the mobilization regimen and factors associated with cumulative marrow damage from cytotoxic therapy correlate with BSCM. The present study confirms previous reports that DICEP mobilizes stem cells more effectively than less intensive chemotherapy.3,4 All our patients received similar doses of G-CSF (4-7 mug/kg) and did not receive stem cell factor. The impact of cytokine choice or dose could, therefore, not be assessed.

We did find that low platelet counts and relapsed disease status were associated with poor BSCM when the data were analyzed using continuous variables, whereas more than one prior chemotherapy regimen was associated with BSCM when the data were analyzed in a categorical manner. These factors probably relate to cumulative marrow damage from prior cytotoxic therapy. Patients with primary refractory disease and those in first remission received less chemotherapy prior to BSCM than did relapsed patients. Previous studies have also found low blood counts predict poor BSCM.8,14 Due to missing data, we could not analyze other factors that may have affected BSCM such as the use of repetitive cycles of G-CSF with recent chemotherapy, interval from most recent chemotherapy to BSCM, cumulative duration of uninterrupted chemotherapy prior to BSCM, and marrow cellularity pre-BSCM.15,16,17,18

Of most interest, the present study suggests that peripheral blood CD3-16+56+ cell counts may independently predict BSCM. The surface immunophenotype of NK cells consists of CD16 and CD56 expression. Other markers associated with mature NK cells are CD2, CD7, CD8, CD11a, CD11b, CD45, and CD69.19 These additional markers were not measured in this study. We measured the CD3-16+56+ population to be certain that this population was different to the T cell population. The CD3-16+56+ cell population is known to possess properties of NK cells including the ability to lyse autologous or allogeneic tumor cells lines and virus-infected cells without prior sensitization.19

We speculate that the NK cell count correlates with BSCM by reflecting the health of the marrow stem cells and stroma. Marrow damage by prior chemotherapy unquestionably affects BSCM.2 The effects of chemotherapy on NK cell numbers have not been extensively studied.15 In some studies, there appeared to be only a transient decrease in the number of CD16+56+ cells after different chemotherapy regimens, and this decrease recovered by the beginning of the next cycle of treatment.10,11 In some studies, no decrease at all was found in CD16+ cells after chemotherapy.12 In contrast Brenner and colleagues20 found that the cytolytic NK cell progenitor pool was reduced but the ability of individual NK cells to lyse target cells was unaltered. Another study demonstrated that chemotherapy may transiently suppress NK cell activity, but the activity returns to pre-treatment levels within 3 weeks.11 It is possible that NK cells recover quickly after drug-induced pancytopenia so that the body's immune system is rapidly capable of fighting infections that may have occurred during neutropenia. NK cells recover approximately 3-4 days earlier than neutrophils and monocytes after autologous or allogeneic peripheral blood stem cell transplantation.21,22 Recovery of NK cell numbers after transplantation of CD34-selected BM or PBSC is also rapid.23 Collectively, these studies suggest that the differentiation of NK cells from BM progenitor cells occurs rapidly without restriction of thymic involvement.24,25 It is understandable, therefore, that the numbers of NK cells correlate with numbers of CD34+ cells, and in turn predict BSCM.

It is also possible that NK cell numbers indirectly predict BSCM because they reflect the health of marrow stroma. Miller and colleagues26 have demonstrated that NK cells can be derived from primitive human marrow progenitors in a modified long-term stroma-dependent culture system. They found that commitment to the NK lineage from primitive marrow progenitors required an adequate marrow stroma microenvironment.13 Conversely, other studies have shown that direct contact with stroma is not required for early differentiation of other myeloid cells from primitive progenitors.27 The stroma may in turn be associated with BSCM because it produces cytokines required for proliferation and release of stem cells from the marrow.28,29

A final possible explanation for the correlation between CD3-16+56+ counts and BSCM is the fact that NK cells themselves may directly play a role in BSCM through the production of cytokines such as IL-12 that stimulates BSCM, or through the production of proteolytic enzymes that cleave VCAM-1 and release stem cells from marrow stroma. Against this hypothesis, however, is the fact that IL-2 plus G-CSF decreases BSCM relative to G-CSF alone.30 This is despite an increase in NK cells and mononuclear cell cytotoxicity in the stem cell products mobilized with IL-2.30 Therefore, simply increasing NK cell numbers does not seem to improve BSCM. All of these possible explanations are simply conjecture and need to be evaluated in appropriate studies.

The major importance of our finding regarding CD3-16+56+ cells is the potential usefulness of having a baseline blood test that predicts BSCM. Although the CD3-16+56+ count was more strongly associated with BSCM than any other blood count in our analysis, we feel that it cannot be used for clinical decision-making at this time. We only studied 77 patients who underwent mobilization with moderate-dose chemotherapy and G-CSF. Perhaps a larger study could better identify predictors for low CD3-16+56+ counts, and identify certain subgroups where the CD3-16+56+ count would have particular relevance for predicting BSCM. No such subgroup could be identified in this study.

Other than the baseline platelet count, the only other blood marker that has been reported to possibly predict BSCM is the baseline peripheral blood CD34+ (PBCD34) count. Fruehauf and colleagues31 recently reported a small series of 40 healthy allogeneic donors who received G-CSF for BSCM. They reported mean baseline CD34+ cell counts of 1.34 and 0.523 ´ 106/l in two groups of patients. The group with the higher CD34+ cell count received G-CSF 10 mug/kg/day while the other group received G-CSF 20 mug/kg/day. Both groups went on to mobilize equally well (PBCD34+ of 78 cell counts ´ 106/l in both groups). The authors inferred from these results that it is beneficial to measure baseline PBCD34+ cell counts and use higher G-CSF doses for BSCM if the PBCD34+ cell count is low. Unfortunately, the sample size was small and another explanation of these results is that PBCD34+ cell counts do not predict BSCM. In terms of other candidate markers of BSCM, a low CD4+ count is associated with poor BSCM in the setting of HIV-1 positive patients.32 However, such an association has not been reported for HIV-1 negative patients. Finally, a bone marrow CD34+/CD71- content of 30/mul was associated with CD34+ cell yield (3.12 vs 2.19 ´ 106/kg, P = 0.013) in 34 breast cancer patients.33 Quantitating CD34+ cells on bone marrow aspirates is complicated, however, by variability in volume of aspirate and contamination with peripheral blood. Such a report, therefore, needs to be reproduced after standardization of sampling and testing methods.

There are several limitations to the present study. Of most importance is the fact that the patients were heterogeneous in terms of diagnosis, prior therapy and BSCM regimen. This heterogeneity, however, allowed linear regression analysis to identify factors that had the strongest independent correlation with BSCM. In addition, we analyzed several blood cell types for association with BSCM. The study results therefore, may be criticized because of multiple comparisons, and the association between CD3-16+56+ NK cell counts and BSCM may arguably have been due to chance. The ability of NK cell counts to predict BSCM definitely needs confirmation prospectively by other centers in more homogeneous patient populations. The univariate analysis was conducted mainly to help in selection of variables used in model-based analysis and the P values were presented for descriptive purposes only. With this consideration, no multiple comparison adjustments were made. In our multivariate analysis, we evaluated further the association identified in univariate analysis between NK cell counts and PBCD34+ cells with other potential confounding variables being simultaneously controlled. It seems that no factors clearly confounded this relationship between NK cell counts and PBCD34+ cells. For the analysis using categorical data, we arbitrarily chose cut-offs based on the median values. This analysis, therefore, is somewhat less reliable than the regression analysis using continuous variables. The analysis using categorical data is included because it demonstrates the same association between CD3-16+56+ count and BSCM as the regression analysis, and the hazard ratio gives some idea as to the magnitude of the association. Nevertheless, it is understandable that the other variables may be slightly different than the regression analysis due to the arbitrary cut-offs chosen.

In conclusion, the CD3-16+56+ cell count was found independently to predict BSCM in this heterogeneous group of patients. It may be a useful predictor of BSCM in addition to measures of the extent of prior cytotoxic therapy and warrants further study to determine if it can help better to target patient groups who require more or less intensive regimens for BSCM.

Acknowledgements

We thank Jan McLaughlin for data collection and management. Research support was by Alberta Cancer Foundation Grant No. 2350003.

References

1 Siena S, Schiavo R, Pedrazzoli P, Carlo-Stella C. Therapeutic relevance of CD34 cell dose in blood cell transplantation for cancer therapy. J Clin Oncol 2000; 18: 1360-1377, MEDLINE

2 To LB, Haylock DN, Simmons PJ, Juttner CA. The biology and clinical uses of blood stem cells. Blood 1997; 89: 2233-2258, MEDLINE

3 Stewart DA, Guo D, Morris D et al. Superior autologous blood stem cell mobilization from dose-intensive cyclophosphamide, etoposide, cisplatin plus G-CSF than from less intensive chemotherapy regimens. Bone Marrow Transplant 1999; 23: 111-117, MEDLINE

4 Gajewski JL, Donato M, Anderlini P et al. Intensive chemotherapy with G-CSF mobilization yields improved peripheral blood progenitor cell (PBPC) collection, quicker recovery after high dose chemotherapy and reduces progression risk compared to G-CSF alone for mobilization. Blood 1999; 94: (Suppl. 1) 665a (Abstr. 2953),

5 Gazitt Y, Freytes CO, Callander N et al. Successful PBSC mobilization with high dose G-CSF for patients failing a first round of mobilization. J Hematother 1999; 8: 173-183, MEDLINE

6 Facon T, Harousseau JL, Maloisel F et al. Stem cell factor in combination with filgrastim after chemotherapy improves peripheral blood progenitor cell yield and reduces apheresis requirements in multiple myeloma patients: a randomized, controlled trial. Blood 1999; 94: 1218-1225, MEDLINE

7 Stiff PJ. Management strategies for the hard-to-mobilize patient. Bone Marrow Transplant 1999; 23: (Suppl. 2) S29-S33, MEDLINE

8 Weaver CH, Schwartzberg LS, Birch R et al. Collection of peripheral blood progenitor cells after the administration of cyclophosphamide, etoposide, and granulocyte-colony-stimulating factor: an analysis of 497 patients. Transfusion 1997; 37: 896-903, MEDLINE

9 Mackall CL, Fleisher TA, Brown MR et al. Age, thymopoiesis, and CD4+ T-lymphocyte regeneration after intensive chemotherapy. New Engl J Med 1995; 332: 143-149, MEDLINE

10 Sewell HF, Halbert CF, Robins RA et al. Chemotherapy-induced differential changes in lymphocyte subsets and natural killer cell function in patients with advanced breast cancer. Int J Cancer 1993; 55: 735-738, MEDLINE

11 Brittenden J, Heys SD, Ross J et al. Natural cytotoxicity in breast cancer patients receiving neoadjuvant chemotherapy: effects of L-arginine supplementation. Eur J Surg Oncol 1994; 20: 467-472, MEDLINE

12 Bonilla A, Alvvarez-Mon M, Merino F et al. Natural killer activity in patients with breast cancer. Eur J Gynaecol Oncol 1990; 11: 103-109, MEDLINE

13 Miller JS, Alley KA, McGlave P. Differentiation of natural killer (NK) cells from human primitive marrow progenitors in a stroma-based long-term culture system: identification of a CD34+7+ NK progenitor. Blood 1994; 83: 2594-2601, MEDLINE

14 Kulkarni S, Powles R, Cunningham D et al. Factors predicting failure to mobilize adequate CD34 positive cells (2 ´ 106/kg) after priming with growth factors. Blood 2000; 96: 519a (Abstr. 2233),

15 Perry AR, Watts MJ, Peniket AJ et al. Progenitor cell yields are frequently poor in patients with histologically indolent lymphomas especially when mobilized within 6 months of previous chemotherapy. Bone Marrow Transplant 1998; 21: 1201-1205, MEDLINE

16 Olavarria E, Kanfer EJ. Selection and use of chemotherapy with hematopoietic growth factors for mobilization of peripheral blood progenitor cells. Curr Opin Hematol 2000; 7: 191-196, MEDLINE

17 Ketterer N, Salles G, Tremisi P et al. Analysis of factors influencing 300 peripheral blood progenitor cell (PBPC) collections in 273 patients treated for lymphoproliferative diseases. Blood 1997; 90: (Suppl. 1) 213a (Abstr. 939),

18 Bensinger W, Appelbaum F, Rowley S et al. Factors that influence collection and engraftment of autologous peripheral blood stem cells. J Clin Oncol 1995; 13: 2547-2555, MEDLINE

19 Brittenden J, Heys SD, Ross J, Eremin O. Natural killer cells and cancer. Cancer 1996; 77: 1226-1243, MEDLINE

20 Brenner BG, Gryllis C, Gornitsky M et al. Differential effects of chemotherapy-induced and HIV-1-induced immunocompromise on NK and LAK cell activities using breast cancer and HIV-1 seropositive patient populations. Anticancer Res 1991; 11: 969-974, MEDLINE

21 Talmadge J, Reed E, Ino K et al. Rapid immunologic reconstitution following transplantation with mobilized peripheral blood stem cells as compared to bone marrow. Bone Marrow Transplant 1997; 19: 161-172, MEDLINE

22 Roberts M, To L, Gillis D et al. Immune reconstitution following peripheral blood stem cell transplantation autologous marrow transplantation and allogeneic bone marrow transplantation. Bone Marrow Transplant 1993; 12: 469-475, MEDLINE

23 Bomberger C, Singh-Jairam M, Rodey G et al. Lymphoid reconstitution after autologous PBSC transplantation with FACS-sorted CD34+ hematopoietic progenitors. Blood 1998; 91: 2588-2600, MEDLINE

24 Lotzova E, Savary C, Champlin R. Genesis of human oncolytic natural killer cells from primitive CD34+33- bone marrow progenitors. J Immunol 1993; 150: 5263-5269, MEDLINE

25 Klingemann H-G. Relevance and potential of natural killer cells in stem cell transplantation. Biol Blood Marrow Transplant 2000; 6: 90-99, MEDLINE

26 Miller JS, Verfaillie C, McGlave P. The generation of human natural killer cells from CD34+/DR- primitive progenitors in long-term bone marrow culture. Blood 1992; 80: 2182-2187, MEDLINE

27 Verfaillie CM. Direct contact between human primitive hematopoietic progenitors and bone marrow stroma is not required for long-term in vitro hematopoiesis. Blood 1992; 79: 2821-2826, MEDLINE

28 Bautz F, Rafii S, Kanz L, Mohle R. Expression and secretion of vascular endothelial growth factor-A by cytokine-stimulated hematopoietic progenitor cells. Possible role in the hematopoietic microenvironment. Exp Hematol 2000; 28: 700-706, MEDLINE

29 Papayannopoulou T. Hematopoietic stem/progenitor cell mobilization. A continuing quest for etiologic mechanisms. Ann NY Acad Sci 1999; 872: 187-197, MEDLINE

30 Burns LJ, Weisdorf DJ, DeFor TE et al. Enhancement of the anti-tumor activity of a peripheral blood progenitor cell graft by mobilization with interleukin 2 plus granulocyte colony-stimulating factor in patients with advanced breast cancer. Exp Hematol 2000; 28: 96-103, MEDLINE

31 Fruehauf S, Wilmes A, Weber-Nordt R et al. G-CSF dose-dependent progenitor cell mobilization in healthy donors: results of a randomized study using baseline CD34+ cell counts. Blood 2000; 96: 179a (Abstr. 771),

32 Schooley RT, Mladenovic J, Sevin A et al. Reduced mobilization of CD34+ stem cells in advanced human immunodeficiency virus type 1 disease. J Infect Dis 2000; 181: 148-157, MEDLINE

33 Osma MM, Ortuno F, de Arriba F et al. Bone marrow steady-state CD34+/CD71- cell content is a predictive value of rG-CSF-mobilized CD34+ cells. Bone Marrow Transplant 1998; 21: 983-985, MEDLINE

Figures

Figure 1 Relationship between PBCD34 and CD34+ cells collected/kg body weight.

Figure 2 Relationship between CD3-16+56+ cell counts and peripheral blood CD34+ counts on the morning of apheresis.

Tables

Table 1 Patient characteristics

Table 2 Peripheral blood counts prior to BSCM

Table 3 Univariate analysis of factors predicting blood stem cell mobilization (PBCD34 count on first apheresis day)

Received 24 January 2001; accepted 4 April 2001
June (2) 2001, Volume 27, Number 12, Pages 1237-1243
Table of contents    Previous  Article  Next    [PDF]