The radical copolymerization kinetics of methyl methacrylate (MMA) and poly-ϵ-caprolactone macrom... more The radical copolymerization kinetics of methyl methacrylate (MMA) and poly-ϵ-caprolactone macromonomer functionalized with a vinyl end group (HEMA-CL(n)) is studied using a pulsed-laser technique. The reactivity ratios for this system are near unity, while a linear relationship between k(p,cop), the copolymer-averaged propagation rate coefficient, and the composition of macromonomer in the feed (0-80 wt% range) is determined. At 50 wt% macromonomer in the feed, a 1.67 ± 0.02 and 1.64 ± 0.06 increase in k(p,cop)/k(p,MMA) is determined for HEMA-CL3 and HEMA-CL2, respectively. These macromonomers are adopted to synthesize nanoparticles (NPs) in the range of 100-150 nm through batch emulsion free radical polymerization (BEP) to produce partially degradable drug delivery carriers. The produced NPs are tested in 4T1 cell line and show excellent characteristics as carriers: they do not affect cell proliferation, and a relevant number of NPs, thousands per cell, are internalized.
ATM ataxia telangiectasia-mutated ATR ATM-related DSBs DNA double-strand breaks DDP cisplatin DXR... more ATM ataxia telangiectasia-mutated ATR ATM-related DSBs DNA double-strand breaks DDP cisplatin DXR doxorubicin BrdUrd 5-bromo-2'-deoxyuridine TUNEL TdT-mediated dUTP nick-end labeling FITC fluorescein isothiocyanate PI propidium iodide ACKNowLedGeMeNts This work is partially supported by MIUR. The generous contribution of the Italian Association for Cancer Research and the Nerina and Mario Mattioli Foundation is gratefully acknowledged.
The antiproliferative response to anticancer treatment is the result of concurrent responses in a... more The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/ after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dosedependence of G 1 , S and G 2 M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario.
We characterize the kinetics of two cancer cell lines: IGROV1 (ovarian carcinoma) and MOLT4 (leuk... more We characterize the kinetics of two cancer cell lines: IGROV1 (ovarian carcinoma) and MOLT4 (leukemia). By means of flow cytometry, we selected two populations from exponentially growing in vitro cell lines, depending on the cells' DNA synthesis activity during a preceding labeling period. For these populations we determined the time course of the percentages of cells in different phases of the cycles, sampling every 3 hr for 60 hr. Initially, semi-synchronous populations quickly converged to a stable age distribution, which is typical of the cell line (at equilibrium); this desynchronization reflects the intercell variability in cell cycle duration. By matching these experimental observations to mathematical modelling, we related the convergence rate toward the asymptotic distribution (R) and the period of the phase-percentage oscillations (T), to the mean cell cycle duration and its coefficient of variation. We give two formulas involving the above-mentioned parameters. Since T and R can be drawn by fitting our data to an asymptotic formula obtained from the model, we can estimate the other two kinetic parameters. IGROV1 cells have a shorter mean cell cycle time, but higher intercell variability than the leukemia line, which takes longer to lose synchrony.
The combination of erlotinib with gemcitabine is one of the most promising therapies for advanced... more The combination of erlotinib with gemcitabine is one of the most promising therapies for advanced pancreatic cancer. Aiming at optimizing this combination, we analyzed in detail the response to sequential treatments with erlotinib → gemcitabine and gemcitabine → erlotinib with an 18 h interval, adopting a previously established experimental/computational approach to quantify the cytostatic and cytotoxic effects at G1, S and G2M checkpoints. This assessment was achieved by contemporary fits of flow cytometric and time-lapse experiments in two human pancreatic cancer cell lines (BxPC-3 and Capan-1) with a mathematical model reproducing the fluxes of cells through the cycle during and after treatment. The S-phase checkpoint contributes in the response to erlotinib, suggesting that the G1 arrest may hamper S-phase cytotoxicity. The response to gemcitabine was driven by the dynamics of the progressive resumption from the S-phase arrest after drug washout. The effects induced by single drugs were used to simulate combined treatments, introducing changes when required. Gemcitabine → erlotinib was more than additive in both cell lines, strengthening the cytostatic effects on cells recovering from the arrest induced by gemcitabine. The interval in the erlotinib → gemcitabine sequence enabled to overcome the antagonist effect of G1 block on gemcitabine efficacy and improved the outcome in Capan-1 cells.
Multicellular systems are currently studied both in vitro and in vivo using different platforms, ... more Multicellular systems are currently studied both in vitro and in vivo using different platforms, providing high throughput data of different types. Mathematical modelling is now called to interpret this reality and has to face more and more with quantitative data. This requires a connection between the basic theoretical model and the data structures, taking account of the processes of measure. Working on the response to anticancer treatment, we considered the data provided by flow cytometry (FC) and time-lapse live cell imaging (TL) in time-course experiments in vitro with untreated and treated cell populations. We created a flexible cell cycle simulator including subsequent cell generations to achieve a full reconstruction in silico of the cell cycle progression under a variety of treatment effects. Unperturbed growth was modelled taking into account intercellular variability of G1,S and G2M transit times, quiescent cells and natural cell loss. The effect of treatment was modelled by “perturbation modules” associated to each cell cycle phase and cell generation, containing a submodel of the checkpoint activity in that phase. Upon input of a set of parameters associated to unperturbed growth and perturbation modules, the program reproduced the time course of cell cycling through subsequent generations, providing outputs comparable with both TL and FC measures. The challenges to fit the data of specific experiments were discussed, indicating a feasible procedure for model building and identification. This lead to a dynamic rendering of proliferation midway between the macroscopic data level and the underlying molecular processes.
We have previously developed experimental and data analysis procedures to measure the antiprolife... more We have previously developed experimental and data analysis procedures to measure the antiproliferative activity of drugs in continuously proliferating cancer cell lines using carboxyfluorescein diacetate succinimidyl ester (CFSE). The method was applied here to analyze the role of p53 in the effect of the anticancer drug cisplatin, distinguishing events occurring in the first generation of cells from those in the second and subsequent generations. A CFSE-loaded colon carcinoma cell line expressing functional wild-type p53 was treated for 1 with cisplatin in parallel with its p53-deficient counterpart, collecting frequency distributions of DNA and CFSE content up to 72 h after treatment. At a sublethal cisplatin concentration proliferation was temporarily inhibited but then the block was overcome and most cells were able to divide several times. The initial block was stronger in HCTp53-/- cells, resulting in a larger proportion of undivided cells at 24 h. This was confirmed and amplified at a higher, lethal concentration, where undivided G(2)M-blocked p53-deficient cells eventually died by non-apoptotic mechanisms, while p53-proficient cells avoided this with a less stringent block. This gave p53-proficient cells more time to repair and eventually decide on survival or apoptotic death before traversing the cycle into their second generation.
in this work the cytotoxicity of PMMA-based nanoparticles against mouse mammary cancer cells (4T1... more in this work the cytotoxicity of PMMA-based nanoparticles against mouse mammary cancer cells (4T1) has been investigated. NPs have been synthesized using either monomer starved semi-batch emulsion polymerization (MSSEP) or standard batch emulsion polymerization (BEP) processes adopting potassium persulfate (KPS) as initiator and two different emulsifiers: sodium dodecyl sulfate (SDS) and Tween 80. The toxicity of NPs produced using SDS has been confirmed in in vitro experiments while it has been found that NPs stabilized with Tween 80 show a good biocompatibility. Moreover, the absence of toxicity of NPs in which the SDS is substituted with Tween 80 adopting ion exchange resins (IER) has been proved. Finally the biocompatibility of the sulfate chain end groups coming from the adopted initiator has been assessed.
A model of pulse formation in flow cytometers is presented that demonstrates the proportionality ... more A model of pulse formation in flow cytometers is presented that demonstrates the proportionality between the area (or the peak height) of the fluorescence signal produced by the photomultiplier and the number of fluorochrome molecules present in the cell that cause the signal. The model clarifies the possible instrumental origins of inaccuracy in this linearity that results in a broadening of the histograms obtained. A comprehensive formula for the coefficient of variation of the unimodular histograms of an homogeneous population is presented that clearly discriminates among the different contributions of staining, possible inhomogeneity of the examined population, photon statistics, and instrumental instabilities.Finally, some experimental data are presented that show the agreement with the proposed formula.
Figure S2 Immunohistochemistry with anti-CD-31 antibody. The panel shows that the treatment with ... more Figure S2 Immunohistochemistry with anti-CD-31 antibody. The panel shows that the treatment with trabectedin and pioglitazone causes both in the sensitive (ML017) and the innate resistant (ML006) tumors a strong decrease of vascular supply. The effect was less evident in ML017/ET tumors with acquired resistance against trabectedin.
, ML006, ML017 and ML017/ET. Control level values are subtracted. ET, trabectedin; PIO, pioglitaz... more , ML006, ML017 and ML017/ET. Control level values are subtracted. ET, trabectedin; PIO, pioglitazone; ET-PIO trabectedin plus pioglitazone. Gene expression data confirmed that the main genes implicated in adipogenesis process are activated in the ML017 after trabectedin treatment and in the ML006 and ML017/ET models in combination with pioglitazone. ADIPOQ seems to be the most up-regulated one.
Purpose:This study was aimed at investigating whether the PPARγ agonist pioglitazone—given in com... more Purpose:This study was aimed at investigating whether the PPARγ agonist pioglitazone—given in combination with trabectedin—is able to reactivate adipocytic differentiation in myxoid liposarcoma (MLS) patient-derived xenografts, overcoming resistance to trabectedin.Experimental Design:The antitumor and biological effects of trabectedin, pioglitazone, and the combination of the two drugs were investigated in nude mice bearing well-characterized MLS xenografts representative of innate or acquired resistance against trabectedin. Pioglitazone and trabectedin were given by daily oral and weekly i.v. administrations, respectively. Molecular studies were performed by using microarrays approach, real-time PCR, and Western blotting.Results:We found that the resistance of MLS against trabectedin is associated with the lack of activation of adipogenesis. The PPARγ agonist pioglitazone reactivated adipogenesis, assessed by histologic and gene pathway analyses. Pioglitazone was well tolerated and did not increase the toxicity of trabectedin. The ability of pioglitazone to reactivate adipocytic differentiation was observed by morphologic examination, and it is consistent with the increased expression of genes such as ADIPOQ implicated in the adipogenesis process. The determination of adiponectin by Western blotting constitutes a good and reliable biomarker related to MLS adipocytic differentiation.Conclusions:The finding that the combination of pioglitazone and trabectedin induces terminal adipocytic differentiation of some MLSs with the complete pathologic response and cure of tumor-bearing mice provides a strong rationale to test the combination of trabectedin and pioglitazone in patients with MLS.
Computer Methods and Programs in Biomedicine, Mar 1, 1990
A program has been implemented on a VAX computer that simulates the progression of cells through ... more A program has been implemented on a VAX computer that simulates the progression of cells through the cell cycle and generates data similar to those obtained in flow cytometry with different techniques. Features of the program are general applicability and flexibility, options including consideration of (a) mean duration of cell cycle phases, (b) their inter-cell distribution, (c) a first order commitment from GO into G1 phase, and (d) a total or partial block of the output from any phase. Examples are given of simulated flow cytometric experiments of drug-induced cell cycle perturbation and of bromodeoxyuridine pulse labeling. This program should help to acquire a correct understanding of the relationship between kinetic features and flow cytometric data.
Out of 130 ovarian cancer patients the DNA index of cells from ovarian carcinoma was studied in 5... more Out of 130 ovarian cancer patients the DNA index of cells from ovarian carcinoma was studied in 56 cases in which cytospin preparations showed the presence of atypical cells. In 24 patients the population had a diploid DNA index (1.0) and in the others the DNA index ranged from 1.2 to 2.0 (tetraploid). No hypodiploid or hypertetraploid populations were detected. Repeated samples from the same patients did not show any significant differences and primary culture did not alter the DNA index. In contrast, cell cycle phase distribution differed greatly from sample to sample, as also the ratio between DNA diploid and DNA aneuploid populations. Primary culture was successful in 57% of the tumours, with a higher percentage of success in DNA aneuploid tumours. After primary culture the ratio between DNA aneuploid cells and DNA diploid cells increased. In relation to the histological gradings of malignancy, DNA aneuploid cells clustered in the highest grade of malignancy. The mean S-phase for tumours with a DNA index of 1.0 was 3.5 and 14.1% for those with DNA index >1. Ovarian carcinomas show a large difference in DNA index between patients even after primary culture.
Different antiangiogenic approaches have been proposed in cancer treatment where therapeutic effi... more Different antiangiogenic approaches have been proposed in cancer treatment where therapeutic efficacy has been shown with the addition of cytotoxic agents. Here, we used SU6668, a small-molecule receptor tyrosine kinase inhibitor, to investigate the combinatorial effect with paclitaxel on the cellular populations of the developing vasculature. Experimental Design: The effect of this combination was evaluated in vitro in a 72-hour proliferation assay on human umbilical vein endothelial cells (HUVEC) and human microvascular endothelial cells derived from lungs, endothelial cells, aortic smooth muscle cells, and human ovarian carcinoma cells sensitive (1A9) and resistant (1A9-PTX22) to paclitaxel. Combination data were assessed by isobologram analysis. Cell survival was determined by terminal deoxyribonucleotide transferase^mediated nick-end labeling and Annexin V staining. The activity of the combination in vivo was evaluated in fibroblast growth factor-2^induced angiogenesis in Matrigel plugs s.c. implanted in mice. The 1A9-PTX22, paclitaxel-resistant xenograft model was used to evaluate tumor response. Results: Combination index values and isobologram analysis showed synergy in inhibition of proliferation of HUVEC, human microvascular endothelial cells derived from lungs, and aortic smooth muscle cells. The combination induced greater apoptosis in HUVEC than the single agents. The addition of paclitaxel to the treatment with SU6668 significantly decreased the hemoglobin content and the number of CD31-positive vessels in Matrigel plugs in vivo. The combination of the drugs was more active than either single agent against 1A9-PTX22 xenografts; the tumor growth delay was accompanied by a significant reduction of vascular density. Conclusions: These findings show that the activity of angiogenesis inhibitors on vascular cells could be potentiated when administered in combination with chemotherapeutic agents that themselves have vascular targeting properties.
Various prognostic indexes have been proposed to improve physicians' ability to predict survival ... more Various prognostic indexes have been proposed to improve physicians' ability to predict survival time in advanced cancer patients admitted to palliative care (PC), but no optimal score has still been identi ed. The study therefore aims to develop and externally validate a new multivariable predictive model in this setting. Methods We developed the model on 1020 cancer patients prospectively enrolled to home care palliative care at VIDAS Milan, Italy, between May 2018 and February 2020 and followed-up to June 2020. The model was then validated among two separate samples of 544 home care and 247 hospice patients. Overall survival was considered as the primary outcome to develop and validate the model; Cox and exible parametric Royston-Parmar regression models were used. Results Through a four-step modelling process, among 68 clinical factors considered, ve predictors were included in the predictive model, i.e., rattle, heart rate, anorexia, liver failure, and the Karnofsky performance status. Patient's survival probability at various time points was estimated. The predictive model showed a good calibration and moderate discrimination (area under the receiver operating characteristic curve between 0.72 and 0.79) in the home care validation set, but model calibration was suboptimal in hospice patients. Conclusions The new multivariable predictive model for palliative cancer patients' survival (PACS model) includes clinical parameters routinely at patient's admission to PC and can be easily used to facilitate immediate and appropriate clinical decisions for PC cancer patients in the home setting.
The radical copolymerization kinetics of methyl methacrylate (MMA) and poly-ϵ-caprolactone macrom... more The radical copolymerization kinetics of methyl methacrylate (MMA) and poly-ϵ-caprolactone macromonomer functionalized with a vinyl end group (HEMA-CL(n)) is studied using a pulsed-laser technique. The reactivity ratios for this system are near unity, while a linear relationship between k(p,cop), the copolymer-averaged propagation rate coefficient, and the composition of macromonomer in the feed (0-80 wt% range) is determined. At 50 wt% macromonomer in the feed, a 1.67 ± 0.02 and 1.64 ± 0.06 increase in k(p,cop)/k(p,MMA) is determined for HEMA-CL3 and HEMA-CL2, respectively. These macromonomers are adopted to synthesize nanoparticles (NPs) in the range of 100-150 nm through batch emulsion free radical polymerization (BEP) to produce partially degradable drug delivery carriers. The produced NPs are tested in 4T1 cell line and show excellent characteristics as carriers: they do not affect cell proliferation, and a relevant number of NPs, thousands per cell, are internalized.
ATM ataxia telangiectasia-mutated ATR ATM-related DSBs DNA double-strand breaks DDP cisplatin DXR... more ATM ataxia telangiectasia-mutated ATR ATM-related DSBs DNA double-strand breaks DDP cisplatin DXR doxorubicin BrdUrd 5-bromo-2'-deoxyuridine TUNEL TdT-mediated dUTP nick-end labeling FITC fluorescein isothiocyanate PI propidium iodide ACKNowLedGeMeNts This work is partially supported by MIUR. The generous contribution of the Italian Association for Cancer Research and the Nerina and Mario Mattioli Foundation is gratefully acknowledged.
The antiproliferative response to anticancer treatment is the result of concurrent responses in a... more The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/ after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dosedependence of G 1 , S and G 2 M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario.
We characterize the kinetics of two cancer cell lines: IGROV1 (ovarian carcinoma) and MOLT4 (leuk... more We characterize the kinetics of two cancer cell lines: IGROV1 (ovarian carcinoma) and MOLT4 (leukemia). By means of flow cytometry, we selected two populations from exponentially growing in vitro cell lines, depending on the cells' DNA synthesis activity during a preceding labeling period. For these populations we determined the time course of the percentages of cells in different phases of the cycles, sampling every 3 hr for 60 hr. Initially, semi-synchronous populations quickly converged to a stable age distribution, which is typical of the cell line (at equilibrium); this desynchronization reflects the intercell variability in cell cycle duration. By matching these experimental observations to mathematical modelling, we related the convergence rate toward the asymptotic distribution (R) and the period of the phase-percentage oscillations (T), to the mean cell cycle duration and its coefficient of variation. We give two formulas involving the above-mentioned parameters. Since T and R can be drawn by fitting our data to an asymptotic formula obtained from the model, we can estimate the other two kinetic parameters. IGROV1 cells have a shorter mean cell cycle time, but higher intercell variability than the leukemia line, which takes longer to lose synchrony.
The combination of erlotinib with gemcitabine is one of the most promising therapies for advanced... more The combination of erlotinib with gemcitabine is one of the most promising therapies for advanced pancreatic cancer. Aiming at optimizing this combination, we analyzed in detail the response to sequential treatments with erlotinib → gemcitabine and gemcitabine → erlotinib with an 18 h interval, adopting a previously established experimental/computational approach to quantify the cytostatic and cytotoxic effects at G1, S and G2M checkpoints. This assessment was achieved by contemporary fits of flow cytometric and time-lapse experiments in two human pancreatic cancer cell lines (BxPC-3 and Capan-1) with a mathematical model reproducing the fluxes of cells through the cycle during and after treatment. The S-phase checkpoint contributes in the response to erlotinib, suggesting that the G1 arrest may hamper S-phase cytotoxicity. The response to gemcitabine was driven by the dynamics of the progressive resumption from the S-phase arrest after drug washout. The effects induced by single drugs were used to simulate combined treatments, introducing changes when required. Gemcitabine → erlotinib was more than additive in both cell lines, strengthening the cytostatic effects on cells recovering from the arrest induced by gemcitabine. The interval in the erlotinib → gemcitabine sequence enabled to overcome the antagonist effect of G1 block on gemcitabine efficacy and improved the outcome in Capan-1 cells.
Multicellular systems are currently studied both in vitro and in vivo using different platforms, ... more Multicellular systems are currently studied both in vitro and in vivo using different platforms, providing high throughput data of different types. Mathematical modelling is now called to interpret this reality and has to face more and more with quantitative data. This requires a connection between the basic theoretical model and the data structures, taking account of the processes of measure. Working on the response to anticancer treatment, we considered the data provided by flow cytometry (FC) and time-lapse live cell imaging (TL) in time-course experiments in vitro with untreated and treated cell populations. We created a flexible cell cycle simulator including subsequent cell generations to achieve a full reconstruction in silico of the cell cycle progression under a variety of treatment effects. Unperturbed growth was modelled taking into account intercellular variability of G1,S and G2M transit times, quiescent cells and natural cell loss. The effect of treatment was modelled by “perturbation modules” associated to each cell cycle phase and cell generation, containing a submodel of the checkpoint activity in that phase. Upon input of a set of parameters associated to unperturbed growth and perturbation modules, the program reproduced the time course of cell cycling through subsequent generations, providing outputs comparable with both TL and FC measures. The challenges to fit the data of specific experiments were discussed, indicating a feasible procedure for model building and identification. This lead to a dynamic rendering of proliferation midway between the macroscopic data level and the underlying molecular processes.
We have previously developed experimental and data analysis procedures to measure the antiprolife... more We have previously developed experimental and data analysis procedures to measure the antiproliferative activity of drugs in continuously proliferating cancer cell lines using carboxyfluorescein diacetate succinimidyl ester (CFSE). The method was applied here to analyze the role of p53 in the effect of the anticancer drug cisplatin, distinguishing events occurring in the first generation of cells from those in the second and subsequent generations. A CFSE-loaded colon carcinoma cell line expressing functional wild-type p53 was treated for 1 with cisplatin in parallel with its p53-deficient counterpart, collecting frequency distributions of DNA and CFSE content up to 72 h after treatment. At a sublethal cisplatin concentration proliferation was temporarily inhibited but then the block was overcome and most cells were able to divide several times. The initial block was stronger in HCTp53-/- cells, resulting in a larger proportion of undivided cells at 24 h. This was confirmed and amplified at a higher, lethal concentration, where undivided G(2)M-blocked p53-deficient cells eventually died by non-apoptotic mechanisms, while p53-proficient cells avoided this with a less stringent block. This gave p53-proficient cells more time to repair and eventually decide on survival or apoptotic death before traversing the cycle into their second generation.
in this work the cytotoxicity of PMMA-based nanoparticles against mouse mammary cancer cells (4T1... more in this work the cytotoxicity of PMMA-based nanoparticles against mouse mammary cancer cells (4T1) has been investigated. NPs have been synthesized using either monomer starved semi-batch emulsion polymerization (MSSEP) or standard batch emulsion polymerization (BEP) processes adopting potassium persulfate (KPS) as initiator and two different emulsifiers: sodium dodecyl sulfate (SDS) and Tween 80. The toxicity of NPs produced using SDS has been confirmed in in vitro experiments while it has been found that NPs stabilized with Tween 80 show a good biocompatibility. Moreover, the absence of toxicity of NPs in which the SDS is substituted with Tween 80 adopting ion exchange resins (IER) has been proved. Finally the biocompatibility of the sulfate chain end groups coming from the adopted initiator has been assessed.
A model of pulse formation in flow cytometers is presented that demonstrates the proportionality ... more A model of pulse formation in flow cytometers is presented that demonstrates the proportionality between the area (or the peak height) of the fluorescence signal produced by the photomultiplier and the number of fluorochrome molecules present in the cell that cause the signal. The model clarifies the possible instrumental origins of inaccuracy in this linearity that results in a broadening of the histograms obtained. A comprehensive formula for the coefficient of variation of the unimodular histograms of an homogeneous population is presented that clearly discriminates among the different contributions of staining, possible inhomogeneity of the examined population, photon statistics, and instrumental instabilities.Finally, some experimental data are presented that show the agreement with the proposed formula.
Figure S2 Immunohistochemistry with anti-CD-31 antibody. The panel shows that the treatment with ... more Figure S2 Immunohistochemistry with anti-CD-31 antibody. The panel shows that the treatment with trabectedin and pioglitazone causes both in the sensitive (ML017) and the innate resistant (ML006) tumors a strong decrease of vascular supply. The effect was less evident in ML017/ET tumors with acquired resistance against trabectedin.
, ML006, ML017 and ML017/ET. Control level values are subtracted. ET, trabectedin; PIO, pioglitaz... more , ML006, ML017 and ML017/ET. Control level values are subtracted. ET, trabectedin; PIO, pioglitazone; ET-PIO trabectedin plus pioglitazone. Gene expression data confirmed that the main genes implicated in adipogenesis process are activated in the ML017 after trabectedin treatment and in the ML006 and ML017/ET models in combination with pioglitazone. ADIPOQ seems to be the most up-regulated one.
Purpose:This study was aimed at investigating whether the PPARγ agonist pioglitazone—given in com... more Purpose:This study was aimed at investigating whether the PPARγ agonist pioglitazone—given in combination with trabectedin—is able to reactivate adipocytic differentiation in myxoid liposarcoma (MLS) patient-derived xenografts, overcoming resistance to trabectedin.Experimental Design:The antitumor and biological effects of trabectedin, pioglitazone, and the combination of the two drugs were investigated in nude mice bearing well-characterized MLS xenografts representative of innate or acquired resistance against trabectedin. Pioglitazone and trabectedin were given by daily oral and weekly i.v. administrations, respectively. Molecular studies were performed by using microarrays approach, real-time PCR, and Western blotting.Results:We found that the resistance of MLS against trabectedin is associated with the lack of activation of adipogenesis. The PPARγ agonist pioglitazone reactivated adipogenesis, assessed by histologic and gene pathway analyses. Pioglitazone was well tolerated and did not increase the toxicity of trabectedin. The ability of pioglitazone to reactivate adipocytic differentiation was observed by morphologic examination, and it is consistent with the increased expression of genes such as ADIPOQ implicated in the adipogenesis process. The determination of adiponectin by Western blotting constitutes a good and reliable biomarker related to MLS adipocytic differentiation.Conclusions:The finding that the combination of pioglitazone and trabectedin induces terminal adipocytic differentiation of some MLSs with the complete pathologic response and cure of tumor-bearing mice provides a strong rationale to test the combination of trabectedin and pioglitazone in patients with MLS.
Computer Methods and Programs in Biomedicine, Mar 1, 1990
A program has been implemented on a VAX computer that simulates the progression of cells through ... more A program has been implemented on a VAX computer that simulates the progression of cells through the cell cycle and generates data similar to those obtained in flow cytometry with different techniques. Features of the program are general applicability and flexibility, options including consideration of (a) mean duration of cell cycle phases, (b) their inter-cell distribution, (c) a first order commitment from GO into G1 phase, and (d) a total or partial block of the output from any phase. Examples are given of simulated flow cytometric experiments of drug-induced cell cycle perturbation and of bromodeoxyuridine pulse labeling. This program should help to acquire a correct understanding of the relationship between kinetic features and flow cytometric data.
Out of 130 ovarian cancer patients the DNA index of cells from ovarian carcinoma was studied in 5... more Out of 130 ovarian cancer patients the DNA index of cells from ovarian carcinoma was studied in 56 cases in which cytospin preparations showed the presence of atypical cells. In 24 patients the population had a diploid DNA index (1.0) and in the others the DNA index ranged from 1.2 to 2.0 (tetraploid). No hypodiploid or hypertetraploid populations were detected. Repeated samples from the same patients did not show any significant differences and primary culture did not alter the DNA index. In contrast, cell cycle phase distribution differed greatly from sample to sample, as also the ratio between DNA diploid and DNA aneuploid populations. Primary culture was successful in 57% of the tumours, with a higher percentage of success in DNA aneuploid tumours. After primary culture the ratio between DNA aneuploid cells and DNA diploid cells increased. In relation to the histological gradings of malignancy, DNA aneuploid cells clustered in the highest grade of malignancy. The mean S-phase for tumours with a DNA index of 1.0 was 3.5 and 14.1% for those with DNA index >1. Ovarian carcinomas show a large difference in DNA index between patients even after primary culture.
Different antiangiogenic approaches have been proposed in cancer treatment where therapeutic effi... more Different antiangiogenic approaches have been proposed in cancer treatment where therapeutic efficacy has been shown with the addition of cytotoxic agents. Here, we used SU6668, a small-molecule receptor tyrosine kinase inhibitor, to investigate the combinatorial effect with paclitaxel on the cellular populations of the developing vasculature. Experimental Design: The effect of this combination was evaluated in vitro in a 72-hour proliferation assay on human umbilical vein endothelial cells (HUVEC) and human microvascular endothelial cells derived from lungs, endothelial cells, aortic smooth muscle cells, and human ovarian carcinoma cells sensitive (1A9) and resistant (1A9-PTX22) to paclitaxel. Combination data were assessed by isobologram analysis. Cell survival was determined by terminal deoxyribonucleotide transferase^mediated nick-end labeling and Annexin V staining. The activity of the combination in vivo was evaluated in fibroblast growth factor-2^induced angiogenesis in Matrigel plugs s.c. implanted in mice. The 1A9-PTX22, paclitaxel-resistant xenograft model was used to evaluate tumor response. Results: Combination index values and isobologram analysis showed synergy in inhibition of proliferation of HUVEC, human microvascular endothelial cells derived from lungs, and aortic smooth muscle cells. The combination induced greater apoptosis in HUVEC than the single agents. The addition of paclitaxel to the treatment with SU6668 significantly decreased the hemoglobin content and the number of CD31-positive vessels in Matrigel plugs in vivo. The combination of the drugs was more active than either single agent against 1A9-PTX22 xenografts; the tumor growth delay was accompanied by a significant reduction of vascular density. Conclusions: These findings show that the activity of angiogenesis inhibitors on vascular cells could be potentiated when administered in combination with chemotherapeutic agents that themselves have vascular targeting properties.
Various prognostic indexes have been proposed to improve physicians' ability to predict survival ... more Various prognostic indexes have been proposed to improve physicians' ability to predict survival time in advanced cancer patients admitted to palliative care (PC), but no optimal score has still been identi ed. The study therefore aims to develop and externally validate a new multivariable predictive model in this setting. Methods We developed the model on 1020 cancer patients prospectively enrolled to home care palliative care at VIDAS Milan, Italy, between May 2018 and February 2020 and followed-up to June 2020. The model was then validated among two separate samples of 544 home care and 247 hospice patients. Overall survival was considered as the primary outcome to develop and validate the model; Cox and exible parametric Royston-Parmar regression models were used. Results Through a four-step modelling process, among 68 clinical factors considered, ve predictors were included in the predictive model, i.e., rattle, heart rate, anorexia, liver failure, and the Karnofsky performance status. Patient's survival probability at various time points was estimated. The predictive model showed a good calibration and moderate discrimination (area under the receiver operating characteristic curve between 0.72 and 0.79) in the home care validation set, but model calibration was suboptimal in hospice patients. Conclusions The new multivariable predictive model for palliative cancer patients' survival (PACS model) includes clinical parameters routinely at patient's admission to PC and can be easily used to facilitate immediate and appropriate clinical decisions for PC cancer patients in the home setting.
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Papers by Paolo Ubezio