Correction: 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 (T(C)) and the growth fraction (GF). In this paper, we describe a novel and simple method to estimate T(C )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 G(1 )cells, labelled divided S cells, labelled undivided S cells, and labelled undivided G(2 )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, T(C )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, T(C )and GF was demonstrated. T(C )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 T(C )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 T(C )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

Platinum sensitivity of ovarian cancer cells does not influence their ability to induce M2-type macrophage polarization

ProblemDevelopment of platinum resistance in ovarian cancer is mediated by both cancer cells and tumor microenvironment. Activation of epithelial-mesenchymal transition program in cancer cells may lead to enrichment for resistant clones. These processes can be affected by tumor-associated macrophages, a highly plastic population of cells that participate in tumor progression and response to treatment by shaping the microenvironment. We aimed to study how platinum resistance influences the crosstalk between macrophages and ovarian cancer cells.Method of studyUsing cisplatin-sensitive ovarian cancer cell line A2780, we developed and characterized cisplatin-resistant A2780Cis and cisplatin and doxorubicin co-resistant A2780Dox cell lines. Next, we set up an indirect coculture system with THP-1 cell line-derived M0-type-, M1-type- and M2-type-like polarized macrophages. We monitored the expression of genes associated with cellular stemness, multidrug resistance, and epithelial-mesenchymal transition in cancer cells, and expression profile of M1/M2 markers in macrophages.ResultsDevelopment of drug resistance in ovarian cancer cell lines was accompanied by increased migration, clonogenicity, and upregulated expression of transcription factors, associated with cellular stemness and epithelial-mesenchymal transition. Upon coculture, we noted that the most relevant changes in gene expression profile occurred in A2780 cells. Moreover, M0- and M1-type macrophages, but not M2-type macrophages, showed significant transcriptional alterations.ConclusionOur results provide the evidence for bidirectional interplay between cancer cells and macrophages. Independent of platinum resistance status, ovarian cancer cells polarize macrophages toward M2-like type, whereas macrophages induce epithelial-mesenchymal transition and stemness-related gene expression profile in cisplatin-sensitive, but not cisplatin-resistant cancer cells

Chemokine profiling in serum from patients with ovarian cancer reveals candidate biomarkers for recurrence and immune infiltration

The management of advanced ovarian cancer is challenging due to the high frequency of recurrence, often associated with the development of resistance to platinum-based chemotherapy. Molecular analyses revealed the complexity of ovarian cancer with particular emphasis on the immune system, which may contribute to disease progression and response to treatment. Cytokines and chemokines mediate the cross-talk between cancer and immune cells, and therefore, present as potential biomarkers, reflecting the tumor microenvironment. A panel of circulating C-C motif chemokine ligand (CCL) and C-X-C motif chemokine ligand (CXCL) chemokines were examined in the serum of 40 high-grade patients with ovarian cancer prior to primary surgery. The level of immune infiltration in tumors was also analyzed. The preoperative levels of chemokines differ between patients. Elevated levels of circulating CXCL4 + CCL20 + CXCL1 combination can discriminate patients with shorter recurrence-free survival and overall survival. The presence of tumor-infiltrating T lymphocytes was detected in half of the patients. The mRNA expression analysis suggests the presence of antitumoral and immunosuppressive elements in the tumor microenvironment. The combination of circulating CXCL9 + CXCL10 can distinguish immune-infiltrated tumors that will lead to shorter recurrence-free survival. The results suggest that preoperative profiling of circulating chemokines in patients with ovarian cancer may provide valuable information regarding tumor recurrence and immune infiltration. The findings demonstrate that combinations have better prognostic utility than single chemokines, and may serve as patient stratification tools

A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample-2

<p><b>Copyright information:</b></p><p>Taken from "A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample"</p><p>BMC Cancer 2005;5():122-122.</p><p>Published online 22 Sep 2005</p><p>PMCID:PMC1261259.</p><p>Copyright © 2005 Eidukevicius et al; licensee BioMed Central Ltd.</p>values obtained with the proposed method and with the RM (cubic) method. C. Correlation between values obtained with the proposed method and with the RM (cubic) method

A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample-0

<p><b>Copyright information:</b></p><p>Taken from "A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample"</p><p>BMC Cancer 2005;5():122-122.</p><p>Published online 22 Sep 2005</p><p>PMCID:PMC1261259.</p><p>Copyright © 2005 Eidukevicius et al; licensee BioMed Central Ltd.</p>t < T. , Tand are durations of G, S and Gphases of the cell cycle, respectively. Horizontal lines dividing Gand Sbars indicate that half of the labelled divided cells are excluded from calculations

A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample-4

<p><b>Copyright information:</b></p><p>Taken from "A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample"</p><p>BMC Cancer 2005;5():122-122.</p><p>Published online 22 Sep 2005</p><p>PMCID:PMC1261259.</p><p>Copyright © 2005 Eidukevicius et al; licensee BioMed Central Ltd.</p> Labelled cells have not yet entered the Scompartment. B. Labelled cells start entering the Scompartment. C. Considerable proportions of labelled cells are present both in the Sand in the Scompartment. D. Labelled cells are leaving the Scompartment. The optimal time for measurement of cell kinetics in Jurkat cells with the proposed method appears to be 12 h

A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample-3

<p><b>Copyright information:</b></p><p>Taken from "A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample"</p><p>BMC Cancer 2005;5():122-122.</p><p>Published online 22 Sep 2005</p><p>PMCID:PMC1261259.</p><p>Copyright © 2005 Eidukevicius et al; licensee BioMed Central Ltd.</p

A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample-1

<p><b>Copyright information:</b></p><p>Taken from "A method to estimate cell cycle time and growth fraction using bromodeoxyuridine-flow cytometry data from a single sample"</p><p>BMC Cancer 2005;5():122-122.</p><p>Published online 22 Sep 2005</p><p>PMCID:PMC1261259.</p><p>Copyright © 2005 Eidukevicius et al; licensee BioMed Central Ltd.</p>orescence) with a gate set for BrdUrd positive cells. B. DNA histogram analysis of BrdUrd positive cells; M1 indicates labelled divided Gcells (G); M2 indicates labelled divided S cells (S); M3 indicates labelled undivided S cells (S); M4 indicates labelled undivided Gcells (G). C. The same DNA histogram as in B, shown at higher magnification; Scompartment is separated from Scompartment by the channel corresponding to the lowest number of events (indicated by dotted vertical line). Total number of cells within each of these markers is obtained using statistics option of WinMDI 2.8 software

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

<p>Abstract</p> <p>Background</p> <p>Presently available flow cytometric methods of bromodeoxyuridine (BrdUrd) labelling do not provide information on the cell cycle time (T_C) and the growth fraction (GF). In this paper, we describe a novel and simple method to estimate T_Cand GF from flow cytometric analysis of a single tumour sample after BrdUrd labelling.</p> <p>Methods</p> <p>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 G₁cells, labelled divided S cells, labelled undivided S cells, and labelled undivided G₂cells 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, T_Cand 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.</p> <p>Results</p> <p>The suitability of the proposed method for estimating durations of the cell cycle phases, T_Cand GF was demonstrated. T_Cin 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 T_Cand GF of cultured Jurkat cells were 23.9 h and 79.3%, respectively.</p> <p>Conclusion</p> <p>The proposed method is relatively simple and permits estimation of the cell cycle parameters, including T_Cand 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.</p