Assessment of Early Therapy Response with 18F-FLT PET in Glioblastoma Multiforme

2014 ◽  
Vol 39 (10) ◽  
pp. e431-e432 ◽  
Author(s):  
Matthew J. Oborski ◽  
Emre Demirci ◽  
Charles M. Laymon ◽  
Frank S. Lieberman ◽  
James M. Mountz
2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xiao Bao ◽  
Ming-Wei Wang ◽  
Yong-Ping Zhang ◽  
Ying-Jian Zhang

Aim. It was aimed to monitor early treatment response of Sunitinib in U87MG models mimicking glioblastoma multiforme by longitudinal18F-FLT microPET/CT imaging in this study.Methods. U87MG tumor mice were intragastrically injected with Sunitinib at a dose of 80 mg/kg for consecutive 7 days.18F-FLT microPET/CT scans were acquired on days 0, 1, 3, 7, and 13 after therapy. Tumor sizes and body weight were measured. Tumor samples were collected for immunohistochemical analysis of proliferation and microvessel density (MVD) with anti-Ki67 and anti-CD31, respectively.Results. The uptake ratios of tumor to the contralateral muscle (T/M) of18F-FLT in the Sunitinib group decreased from baseline to day 3 (T/M0= 2.98 ± 0.33; T/M3= 2.23 ± 0.36;P<0.001), reached the bottom on day 7 (T/M7= 1.96 ± 0.35;P<0.001), and then recovered on day 13. The T/M of18F-FLT uptake in the control group remained around 3.0. There was no difference for the tumor size between both groups until day 11.18F-FLT uptakes of tumor were correlated with Ki67 staining index and MVD.Conclusion. Early therapy response to Sunitinib could be predicted via18F-FLT PET, which will contribute to monitoring antiangiogenesis treatment.


Author(s):  
David Brasse ◽  
Hélène Burckel ◽  
Patrice Marchand ◽  
Marc Rousseau ◽  
Ali Ouadi ◽  
...  

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2381-2381 ◽  
Author(s):  
Paul Brent Ferrell ◽  
Kirsten E. Diggins ◽  
Hannah G. Polikowsky ◽  
Jonathan M. Irish

Abstract Introduction: The plasticity and stemness of acute myeloid leukemia (AML) cells are thought to be driving factors in disease aggressiveness and poor patient survival. These factors also contribute to the challenge of designing analytical cytometry panels to study AML over time during treatment. A high content single cell approach was designed to pinpoint rare populations of AML cells present prior to treatment that emerge and dominate following therapy resistance or disease relapse. Twenty-seven diagnostic and differentiation markers were measured on AML cells in order to track rare cell subsets pre- and post- treatment, measure kinetics of early therapy response, and identify any novel leukemic cell populations. Methods: AML patients undergoing induction chemotherapy were identified and consented for this study according to a local Institutional Review Board-approved protocol. Samples of peripheral blood and bone marrow were collected and cryopreserved after mononuclear cell separation. Thawed samples were stained with a mass cytometry panel to quantify 27 AML biomarkers on every cell. From each patient, up to 12 samples of blood and marrow were obtained before, during, and after induction chemotherapy (n = 46 total samples; 14 marrow and 32 blood from 5 individual donors). Stained cells were analyzed by mass cytometry (CyTOF). Dimensionality reduction and visualization was performed using viSNE. Leukemic cell subsets and differentiated cells from healthy donors were characterized in terms of abundance in each sample, 27-marker expression phenotype, heterogeneity of marker expression within the subset, and differentiation status in each sample. A stem/progenitor index was created to quantify the phenotypic distance of cells in a population from the CD34+stem/progenitor cells. Results: In unsupervised viSNE analysis of 27-marker cellular phenotype, leukemic blasts formed phenotypically distinct groups of cells, were CD45lo, and had an expression profile that closely matched the diagnostic fluorescent flow cytometry immunophenotype. The 27-marker panel grouped cells into 11 major populations: CD34+ hematopoietic stem/progenitor cells (HSPCs), 5 differentiated non-malignant populations (myeloid, CD4+ T, CD8+ T, B, and NK cells), and 3 major populations of leukemia cells. Remission was apparent on viSNE when no more than 5% of leukemic blasts remained. The remaining cells were instead part of the non-malignant populations. In poor outcome cases, at-diagnosis bone marrow leukemia cells were initially close in 27-dimenional phenotype to the non-malignant stem/progenitor cells (i.e. higher stem/progenitor index). In a case of primary refractory disease, six therapy resistant cell (TRC) populations became dominant within the leukemic blast area. These same TRC populations were present but initially rare and constituted only 0.6% to 2% of total pre-treatment AML blasts at diagnosis. TRC populations displayed increased per-cell expression of markers associated with stemness and leukemia initiating ability, including CD34, CD38, and CXCR4/CD184 (respective increases of 0.7, 0.9, and 0.6 fold on the log-like asinh15 scale). In contrast, expression of CD34, CD38, and major cell type identity markers (e.g. HLA-DR, CD4, CD19) did not significantly change over time on non-AML cells (all <0.2 fold). Conclusion: These results demonstrate the ability of high-dimensional mass cytometry to reveal, characterize, and compare rare and highly plastic cell populations over time in primary human tissue samples. Use of 27 markers meant that cells that dramatically changed expression of a few markers could still be matched to phenotypically similar cells using the other 20+ markers. Such phenotypic similarities were captured well by viSNE computational analysis. This approach offers greatly expanded longitudinal monitoring of AML while 1) effectively capturing differentiation along with cellular abundance, 2) identifying biomarkers of therapy resistance for cell sorting and targeting, and 3) enabling the single cell analysis of signaling networks in concert with critical markers of cell identity. Disclosures Irish: Cytobank, Inc. : Employment, Equity Ownership.


2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 7532-7532
Author(s):  
M. Schmuecking ◽  
C. P. Schneider ◽  
N. Presselt ◽  
R. P. Baum ◽  
J. Leonhardi ◽  
...  

7532 Background: A randomized multicenter phase III trial was designed to assess if timing of chemoradiation may alter treatment outcome for patients (pts) with stage III NSCLC in a multimodality treatment approach. Additionally, the role of F-18 FDG PET within clinical trials is evaluated for staging, therapy management, molecular radiation treatment planning (MRTP) and early therapy response and its effect on survival as compared to regression grade (RG). Methods: Inclusion criteria: histologically confirmed NSCLC stage IIIA/IIIB. ECOG PS 0–1. Primary end points: OS, DFS. Secondary end points: TTP, QoL, RR. Neoadjuvant treatment: 2–3 cycles of paclitaxel/carboplatin and a block of chemoradiation (45 Gy, 1.5 Gy b.i.d., concomitant paclitaxel/carboplatin) followed by surgery. Randomization: late (Arm1) vs. early (Arm2) chemoradiation. Staging: PET in addition to CT and/or MRI after randomization, second PET after completion of neoadjuvant therapy. Assessment of standardized uptake values (SUV) in primary tumor (PT) and all metastatic lymph nodes (LN). Documentation of involved LN as detected by PET and LN sampling during surgery according to Naruke/ATS-LCSG classification. Evaluation of RG and correlation with PET for PT and each LN. MRTP using fused PET/CT data. Intent to treat analyses using Kaplan-Meier estimates, log rank tests, Cox multivariate models. Results: 210 eligible pts were enrolled (Arm1: 106, Arm2: 104, well-balanced on all factors). Paraoperative lethality 4.3%. Treatment-related deaths in Arm1: 8.3%, in Arm2: 5.9%. Up-staging in 26/210 pts due to distant metastases, down-staging in 5/210 pts resulting in 15% stage migration. Actuarial tumor specific survival after 60 months: complete vs. incomplete metabolic remission: 56% vs. 24% (p =0.005), RG III/IIb (no/less than 10% of vital tumor cells) vs. RG IIa/I (more than 10% vital tumor cells): 61% vs. 25% (p <0.001). Late vs. early chemoradiation: 30% vs. 45% (p =0.313). Multivariate Cox regression for initial SUV: p >0.05. Conclusions: Long-term survivors with early chemoradiation have a trend to better survival being not statistically significant. Metabolic remission correlates well with RG and may predict therapeutic outcome. No significant financial relationships to disclose.


2012 ◽  
Vol 12 (1) ◽  
pp. 212-224
Author(s):  
M.W. Huellner ◽  
T.P. Hennedige ◽  
R. Winterhalder ◽  
T. Zander ◽  
S.K. Venkatesh ◽  
...  

Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1055 ◽  
Author(s):  
Thomas M. Deutsch ◽  
Stefan Stefanovic ◽  
Manuel Feisst ◽  
Chiara Fischer ◽  
Fabian Riedel ◽  
...  

Detection of circulating tumor cells (CTC) can distinguish between aggressive and indolent metastatic disease in breast cancer patients and is thus considered an independent, negative prognostic factor. A clear decline in CTCs is observed in patients who respond to systemic therapy. Nevertheless, CTCs can decrease in patients experiencing disease progression during systemic therapy, too. This study aims to determine the differences between CTC decline in patients responding to therapy and those in whom disease is progressing. Therefore, CTC values were compared at the start and after one cycle of a new line of systemic therapy. In all, 108 initially CTC-positive patients (with ≥5 intact CTCs in 7.5 mL blood) were enrolled in this study and intact and apoptotic CTCs were measured via the CellSearch® system. A cut-off analysis was performed using Youden’s J statistics to differentiate between CTC change in the two groups. Here, 64 (59.3%) patients showed stable disease or partial response vs. 44 (40.7%) presenting disease progression. Median overall survival was 23 (range: 4–92) vs. 7 (2–43) months (p < 0.001). Median intact CTC count at enrollment was 15.0 (5–2760) vs. 30.5 (5–200000) cells (p = 0.39) and 2.5 (0–420) vs. 8.5 (0–15000) cells after one cycle of systemic therapy (p = 0.001). Median apoptotic CTC count at enrollment was 10.5 (0–1500) vs. 9 (0–800) cells (p = 0.475) and 1 (0–200) vs. 3 (0–250) cells after one cycle of systemic therapy (p = 0.01). A 50% reduction in baseline apoptotic CTC count represents the optimal cut-off to differentiate between therapy response and disease progression. An apoptotic CTC reduction of ≤10% is 74% specific for early disease progression.


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