In this study, novel hyaluronic acid-pH stimuli-responsive lipid membrane mesoporous silica nanoparticles (HA-PL-MSNs) were designed and assembled, with the chemotherapeutic agent doxorubicin (DOX) as the model drug. HA-PL-MSNs exhibited a well-defined mesostructure covered by lipid bilayer and particle size of ~150 nm. The drug loading capacity was up to ~18.2%. DOX release could be effectively retained by the lipid bilayer in pH 7.4 buffer and exhibited a pH-triggered burst release in the acidic condition. Confocal laser scanning microscopy and fluorescence-activated cell sorting showed that HA-PL-MSNs exhibited higher cellular uptake efficiency via CD44 receptor-mediated endocytosis compared with PL-MSNs in HeLa cells. In vitro cytotoxicity studies demonstrated that HA-PL-MSNs could effectively enhance the targeted delivery of DOX and restrain the growth of HeLa cells. This might provide a promising alternative for the development of a targeted anticancer drug delivery system.
mesoporous silica nanoparticles; hyaluronic acid; pH-sensitive lipid membrane; CD44 receptor; HeLa cells
Previous studies have reported that eEF-2 kinase is associated with tumour cell sensitivity to certain therapies. In the present study, we investigated the relationship between eEF-2 kinase and lapatinib, a dual inhibitor of EGFR and HER-2, in nasopharyngeal carcinoma (NPC) cells.
The effect of treatment on the growth and proliferation of NPC cells was measured by three methods: cell counting, crystal violet staining and colony counting. Apoptosis was evaluated by flow cytometry to determine Annexin V-APC/7-AAD and cleaved PARP levels, and the results were further confirmed by Western blot analysis. The expression of eEF-2 kinase and the impacts of different treatments on different signalling pathways were analysed by Western blot analysis.
The expression of eEF-2 kinase was significantly associated with NPC cell sensitivity to lapatinib. Therefore, suppression of this kinase could increase the cytocidal effect of lapatinib, as well as reduce cell viability and colony formation. Furthermore, inhibition of eEF-2 kinase, by either RNA interference (eEF-2 kinase siRNA or shRNA) or pharmacological inhibition (NH125), enhanced lapatinib-induced apoptosis of NPC cells. The results also showed that lapatinib combined with NH125 had a synergistic effect in NPC cells. In addition, mechanistic analyses revealed that downregulation of the ERK1/2 and Src pathways, but not the AKT pathway, was involved in this sensitizing effect.
The results of this study suggest that targeting eEF-2 kinase may improve the efficacy of therapeutic interventions such as lapatinib in NPC cells.
Nasopharyngeal carcinoma; Lapatinib; eEF-2 kinase; Synergistic effect; Src/Erk signalling pathway
Mathematical modeling of drug transport can complement current experimental and clinical investigations to understand drug resistance mechanisms, which eventually will help to develop patient-specific chemotherapy treatments. In this paper, we present a general time- and space-dependent mathematical model based on diffusion theory for predicting chemotherapy outcome. This model has two important parameters: the blood volume fraction and radius of blood vessels divided by drug diffusion penetration length. Model analysis finds that a larger ratio of the radius of blood vessel to diffusion penetration length resulted in to a larger fraction of tumor killed, thereby leading to a better treatment outcome. Clinical translation of the model can help quantify and predict the optimal dosage size and frequency of chemotherapy for individual patients.
Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.
chemotherapy; computer simulation; mathematical modeling; multiscale; tumor growth and invasion; translational research
In an effort to trace the evolution of porcine epidemic diarrhea virus (PEDV), S1 and ORF3 genes of viruses identified in 41 pig farms from seven regions (North, Northeast, Northwest, Central, East, South West, and South, respectively) of China in 2015 were sequenced and analyzed. Sequence analysis revealed that the 41 ORF3 genes and 29 S1 genes identified in our study exhibited nucleotide homologies of 98.2%–100% and 96.6%–100%, respectively; these two genes exhibited low nucleotide sequence similarities with classical CV777 strain and early Chinese strain LZC. Phylogenetic analysis indicated that the identified PEDV strains belonged to global non S-INDEL strains, and exhibited genetic diversity; S1 gene of the HLJ2015/DP1-1 strain harbored an unique deletion of 12 nucleotides (A1130CAACTCCACTG1141); while the Chinese PEDV S-INDEL reference strains included two types of the “CV777” S-INDEL as well as the “US” S-INDEL, and all co-circulated with Chinese non S-INDEL strains. Of 29 identified S1 genes, the SS2 epitope (Y748SNIGVCK755) was highly conserved, while the SS6 epitope (L764QDGQVKI771) and pAPN receptor-binding region (aa 490–615) exhibited amino substitutions. Nine possible recombination events were identified between the 29 identifed S1 genes and the 3 S1 reference genes from early Chinese PEDV strains. The complete S genes of selected Chinese PEDV field strains (2011–2015) showed 5.18%–6.07% nucleotide divergence, which is far higher than the divergence observed in early Chinese PEDV strains (3.1%) (P<0.05). Our data provide evidence that PEDV non S-INDEL strains with genetic diversities and potential recombination circulate in seven regions of China in 2015; Chinese PEDV S-INDEL strains exhibit genetic diversity and co-circulate with non S-INDEL strains.
Asthma is a common worldwide health burden, the prevalence of which is increasing. Recently, the biologically active form of vitamin D3, 1,25-dihydroxyvitamin D3, has been reported to have a protective role in murine asthma; however, the molecular mechanisms by which vitamin D3 attenuates asthma-associated airway injury remain elusive. In the present study, BALB/c mice were sensitized to ovalbumin (OVA) and were administered 100 ng 1,25-dihydroxyvitamin D3 (intraperitoneal injection) 30 min prior to each airway challenge. The inflammatory responses were measured by ELISA, airway damage was analyzed by hematoxylin and eosin staining, airway remodeling was analyzed by Masson staining and periodic acid-Schiff staining, markers of oxidative stress were measured by commercial kits, and the expression levels of α-smooth muscle actin (α-SMA) and the activity of the NF-E2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) and the transforming growth factor-β (TGF-β)/Smad signaling pathways were measured by immunohistochemistry and western blotting. The results demonstrated that OVA-induced airway inflammation and immunoglobulin E overexpression were significantly reduced by vitamin D3 treatment. In addition, treatment with vitamin D3 decreased α-SMA expression, collagen deposition and goblet cell hyperplasia, and inhibited TGF-β/Smad signaling in the asthmatic airway. The upregulated levels of malondialdehyde, and the reduced activities of superoxide dismutase and glutathione in OVA-challenged mice were also markedly restored following vitamin D3 treatment. Furthermore, treatment with vitamin D3 enhanced activation of the Nrf2/HO-1 pathway in the airways of asthmatic mice. In conclusion, these findings suggest that vitamin D3 may protect airways from asthmatic damage via the suppression of TGF-β/Smad signaling and activation of the Nrf2/HO-1 pathway; however, these protective effects were shown to be accompanied by hypercalcemia.
asthma; vitamin D3; inflammation; remodeling; TGF-β/Smad; Nrf2/HO-1
It has been hypothesized that continuously releasing drug molecules into the tumor over an extended period of time may significantly improve the chemotherapeutic efficacy by overcoming physical transport limitations of conventional bolus drug treatment. In this paper, we present a generalized space- and time-dependent mathematical model of drug transport and drug-cell interactions to quantitatively formulate this hypothesis. Model parameters describe: perfusion and tissue architecture (blood volume fraction and blood vessel radius); diffusion penetration distance of drug (i.e., a function of tissue compactness and drug uptake rates by tumor cells); and cell death rates (as function of history of drug uptake). We performed preliminary testing and validation of the mathematical model using in vivo experiments with different drug delivery methods on a breast cancer mouse model. Experimental data demonstrated a 3-fold increase in response using nano-vectored drug vs. free drug delivery, in excellent quantitative agreement with the model predictions. Our model results implicate that therapeutically targeting blood volume fraction, e.g., through vascular normalization, would achieve a better outcome due to enhanced drug delivery.
Cancer treatment efficacy can be significantly enhanced through the elution of drug from nano-carriers that can temporarily stay in the tumor vasculature. Here we present a relatively simple yet powerful mathematical model that accounts for both spatial and temporal heterogeneities of drug dosing to help explain, examine, and prove this concept. We find that the delivery of systemic chemotherapy through a certain form of nano-carriers would have enhanced tumor kill by a factor of 2 to 4 over the standard therapy that the patients actually received. We also find that targeting blood volume fraction (a parameter of the model) through vascular normalization can achieve more effective drug delivery and tumor kill. More importantly, this model only requires a limited number of parameters which can all be readily assessed from standard clinical diagnostic measurements (e.g., histopathology and CT). This addresses an important challenge in current translational research and justifies further development of the model towards clinical translation.
Free radical hypothesis which is one of the most acknowledged aging theories was developed into oxidative stress hypothesis. Protein carbonylation is by far one of the most widely used markers of protein oxidation. We studied the role of age and gender in protein carbonyl content of saliva and plasma among 273 Chinese healthy subjects (137 females and 136 males aged between 20 and 79) and discussed the correlation between protein carbonyl content of saliva and plasma. Protein carbonyl content of saliva and plasma were, respectively, 2.391 ± 0.639 and 0.838 ± 0.274 nmol/mg. Variations of saliva and plasma different age groups all reached significant differences in both male and female (all p < 0.05) while both saliva and plasma protein carbonyls were found to be significantly correlated with age (r = 0.6582 and r = 0.5176, all p < 0.001). Gender was discovered to be unrelated to saliva and plasma protein carbonyl levels (all p > 0.05). Saliva and plasma protein carbonyls were positively related (r = 0.4405, p < 0.001). Surprisingly, saliva and plasma protein carbonyls/ferric reducing ability of plasma (FRAP) ratios were proved to be significantly correlated with age (r = 0.7796 and r = 0.6938, all p < 0.001) while saliva protein carbonyls/FRAP ratio and plasma protein carbonyls/FRAP ratio were also correlated (r = 0.5573, p < 0.001). We concluded that saliva protein carbonyls seem to be an alternative biomarker of aging while the mechanisms of protein carbonylation and oxidative stress and the relationship between saliva protein carbonyls and diseases need to be further investigated.
Saliva; Plasma; Protein carbonylation; Free radicals; Oxidative stress; Aging
Polysaccharides from medicinal plants exert antitumor activity in many cancers. Our previous study demonstrated that polysaccharides extracted from the selenium-enriched Pyracantha fortuneana (Se-PFPs) showed antiproliferative effect in breast cancer cell line. This study aimed to investigate the antitumor effect of Se-PFPs in ovarian cancer cells in vitro and in vivo. Se-PFPs could decrease cell viability, induce apoptosis, and inhibit migratory and invasive potentials in HEY and SKOV3 cells. These findings are supported by reduced expression of cyclin D1, Bcl-2 and MMP-9, enhanced cleavage of PARP and caspase-3, elevated activity of caspase-3 and caspase-9, and EMT (epithelial to mesenchymal transition) inhibition (elevated expression of E-cadherin and cytokeratin 19, and reduced expression of N-cadherin, vimentin, ZEB1 and ZEB2). Moreover, Se-PFPs inhibited xenografted tumor growth through inhibiting cell proliferation and inducing cell apoptosis. More importantly, Se-PFPs significantly reduced cytoplasmic β-catenin particularly nuclear β-catenin expression but increased β-catenin phosphorylation in a GSK-3β-dependent mechanism. Furthermore, β-catenin knockdown exerted similar effects on cell proliferation and invasion as seen in Se-PFPs-treated cells, while β-catenin overexpression neutralized the inhibitory effects of Se-PFPs on cell proliferation and invasion. Take together,Se-PFPs exert antitumor activity through inhibiting cell proliferation, migration, invasion and EMT, and inducing cell apoptosis. These effects are achieved by the inhibition of β-catenin signaling. Thus Se-PFPs can be used as potential therapeutic agents in the prevention and treatment of ovarian cancer.
selenium-enriched polysaccharides; ovarian cancer; antitumor activity; GSK-3β; β-catenin
Recently, porcine deltacoronavirus (PDCoV) has been proven to be associated with enteric
disease in piglets. Diagnostic tools for serological surveys of PDCoV remain in the
developmental stage when compared with those for other porcine coronaviruses. In our
study, an indirect enzyme-linked immunosorbent assay (ELISA) (rPDCoV-N-ELISA) was
developed to detect antibodies against PDCoV using a histidine-tagged recombinant
nucleocapsid (N) protein as an antigen. The rPDCoV-N-ELISA did not cross-react with
antisera against porcine epidemic diarrhea virus, swine transmissible gastroenteritis
virus, porcine group A rotavirus, classical swine fever virus, porcine circovirus-2,
porcine pseudorabies virus, and porcine reproductive and respiratory syndrome virus; the
receiver operating characteristic (ROC) curve analysis revealed 100% sensitivity and 90.4%
specificity of the rPDCoV-N-ELISA based on samples of known status (n=62). Analyses of
field samples (n=319) using the rPDCoV-N-ELISA indicated that 11.59% of samples were
positive for antibodies against PDCoV. These data demonstrated that the rPDCoV-N-ELISA can
be used for epidemiological investigations of PDCoV and that PDCoV had a low serum
prevalence in pig population in Heilongjiang province, northeast China.
ELISA; porcine deltacoronavirus; serum epidemiology
Previous studies suggested an association between chronic obstructive pulmonary disease (COPD) and cognitive impairment, mostly in developed countries. There is no evidence available on the association between these two common chronic disorders in the elderly people in People’s Republic of China where the population is aging rapidly.
The study population was randomly selected from a nationally representative Disease Surveillance Point System in People’s Republic of China. A standardized questionnaire was administered by trained interviewers during a face-to-face interview in the field survey conducted in 2010–2011. Cognitive function was assessed using the Mini-Mental State Examination. COPD was measured by self-report and the Medical Research Council respiratory questionnaire was used to assess respiratory symptoms. A multivariate logistic regression model was applied to examine the association between COPD and cognitive impairment with adjustment for potential confounding factors.
A total of 16,629 subjects aged over 60 years were included in the study. The prevalence of cognitive impairment was 9.4% (95% confidence interval [CI] 7.7, 11.1). Chronic phlegm was associated with significantly higher prevalence of cognitive impairment in models adjusted for age, sex, marital status, geographic region, urban/rural, education, smoking status, alcohol drinking, and indoor air pollution (odds ratio [OR] 1.46, 95% CI 1.11, 1.93). Chronic respiratory symptoms and self-reported COPD were strongly related to cognitive impairment in urban areas. There were no significant effect modifications for sex, regions, educational level, smoking status, and alcohol drinking.
There was strong association between COPD and cognitive impairment in urban Chinese elderly population.
COPD; cognitive impairment; respiratory symptoms
There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models.
computer simulation; mathematical modeling; signaling pathway; tumor growth and invasion; drug discovery; translational research
To trace the evolution of canine coronavirus (CCoV), 201 stool samples from diarrheic dogs in northeast China were subjected to reverse transcription-polymerase chain reactions (RT-PCRs) targeting the partial M and S genes of CCoV, followed by an epidemiological analysis. M gene RT-PCRs showed that 28.36% (57/201) of the samples were positive for CCoV; of the 57 positive samples, CCoV-I and CCoV-II accounted for 15.79% (9/57) and 84.21% (48/57), respectively. A sequence comparison of the partial M gene revealed nucleotide homologies of 88.4%–100% among the 57 CCoV strains, and 88.7%–96.2% identity between the 57 CCoV strains and the Chinese reference strain HF3. The CCoV-I and CCoV-II strains exhibited genetic diversity when compared with reference strains from China and other countries. The 57 CCoV strains exhibited high co-infection rates with canine kobuvirus (CaKV) (33.33%) and canine parvovirus-2 (CPV-2) (31.58%). The CCoV prevalence in diarrheic dogs differed significantly with immunization status, regions, seasons, and ages. Moreover, 28 S genes were amplified from the 57 CCoV-positive samples, including 26 CCoV-IIa strains, one CCoV-IIb strain, and one CCoV-I strain. A sequence comparison of the partial S gene revealed 86.3%–100% nucleotide identity among the 26 CCoV-IIa strains, and 89.6%–92.2% identity between the 26 CCoV-IIa strains and the Chinese reference strain V1. The 26 CCoV-IIa strains showed genetic diversity when compared with reference strains from China and other countries. Our data provide evidence that CCoV-I, CCoV-IIa, and CCoV-IIb strains co-circulate in the diarrhoetic dogs in northeast China, high co-infection rates with CaKV and CPV-2 were observed, and the CCoV-II strains exhibited high prevalence and genetic diversity.
Canine kobuviruses (CaKVs) are newly recognized picornaviruses that have been recently
detected in dogs in the U.S.A., Italy, U.K., the Republic of Korea and Tanzania. To trace
the evolution of CaKV strains, a total of 201 fecal samples from rectal swabs of diarrheic
dogs, which were obtained from May 2014 to April 2015 in northeast China, were detected by
reverse transcription-PCR targeting a partial (504 bp) fragment of the 3D gene.
Furthermore, a phylogenetic analysis of the CaKV strains identified in northeast China was
conducted based on the partial 3D gene sequence. The results indicated that 36 fecal
samples (17.91%, 36/201) were positive for CaKV, in which the co-infection rates of canine
coronavirus, canine parvovirus-2 and canine bocavirus were 58.33%, 41.67%, and 11.11%,
respectively. Sequence comparison of the partial 3D gene revealed nucleotide homologies of
94.4–100%, 95.6–98.6%, 94.3–97.6%, 94.4–96.3% and 93.3–95.1% within the 36 Chinese CaKV
strains, and between the 36 Chinese CaKV strains and four CaKV reference strains from
South Korea, Italy, U.S.A. and Tanzania, respectively. A phylogenetic tree revealed that
the 36 Chinese CaKV strains formed one specific CaKV lineage with CaKVs that have recently
been identified in other countries. The 36 Chinese CaKV strains were closely related to
CaKV reference strains from Asia and Europe, but differed genetically from CaKV reference
strains from North America and Africa. This study provides evidence that CaKVs circulate
in diarrhoetic dogs in China and that they exhibit substantial genetic diversity and high
co-infection rates with other enteric viruses.
canine kobuvirus; epidemiology; genetic diversity; kobuvirus
Plant bZIP proteins characteristically harbor a highly conserved bZIP domain with two structural features: a DNA-binding basic region and a leucine (Leu) zipper dimerization region. They have been shown to be diverse transcriptional regulators, playing crucial roles in plant development, physiological processes, and biotic/abiotic stress responses. Despite the availability of six completely sequenced legume genomes, a comprehensive investigation of bZIP family members in legumes has yet to be presented.
In this study, we identified 428 bZIP genes encoding 585 distinct proteins in six legumes, Glycine max, Medicago truncatula, Phaseolus vulgaris, Cicer arietinum, Cajanus cajan, and Lotus japonicus. The legume bZIP genes were categorized into 11 groups according to their phylogenetic relationships with genes from Arabidopsis. Four kinds of intron patterns (a–d) within the basic and hinge regions were defined and additional conserved motifs were identified, both presenting high group specificity and supporting the group classification. We predicted the DNA-binding patterns and the dimerization properties, based on the characteristic features in the basic and hinge regions and the Leu zipper, respectively, which indicated that some highly conserved amino acid residues existed across each major group. The chromosome distribution and analysis for WGD-derived duplicated blocks revealed that the legume bZIP genes have expanded mainly by segmental duplication rather than tandem duplication. Expression data further revealed that the legume bZIP genes were expressed constitutively or in an organ-specific, development-dependent manner playing roles in multiple seed developmental stages and tissues. We also detected several key legume bZIP genes involved in drought- and salt-responses by comparing fold changes of expression values in drought-stressed or salt-stressed roots and leaves.
In summary, this genome-wide identification, characterization and expression analysis of legume bZIP genes provides valuable information for understanding the molecular functions and evolution of the legume bZIP transcription factor family, and highlights potential legume bZIP genes involved in regulating tissue development and abiotic stress responses.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-2258-x) contains supplementary material, which is available to authorized users.
bZIP gene family; Legume genomes; Evolution; Expression analysis
There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used.
Agent-based modeling; analysis of variance; multiscale; non-small cell lung cancer; parameter ranking
Sudden deaths associated with the use of electroconvulsive therapy are rare. In this case report
a 58-year-old male with a 20-year history of bipolar disorder and no history or signs of cardiac illness died
from cardiac arrest within one hour of receiving an initial session of modified electroconvulsive therapy
(MECT) to treat a recurrent episode of non-psychotic mania. The patient regained consciousness and was
medically stable immediately after the MECT session (which did not produce a convulsion) but deteriorated
rapidly after transfer to the recovery room. It was not possible to conduct an autopsy, but the authors
surmise that the most probable cause was that the use of haloperidol 17 hours prior to MECT exacerbated
the cardiac effects of nonconvulsive MECT. The case highlights the need for a thorough cardiac work-up on
patients being considered for MECT (possibly including assessment of cardiac enzymes in older individuals)
and careful consideration of the concurrent use of antipsychotic medications and MECT.
electroconvulsive therapy; sudden death; antipsychotic medication; bipolar disorder; China
To trace evolution of canine parvovirus-2 (CPV-2), a total of 201 stool samples were collected from dogs with diarrhea in Heilongjiang province of northeast China from May 2014 to April 2015. The presence of CPV-2 in the samples was determined by PCR amplification of the VP2 gene (568 bp) of CPV-2. The results revealed that 95 samples (47.26%) were positive for CPV-2, and they showed 98.8%–100% nucleotide identity and 97.6%–100% amino acid identity. Of 95 CPV-2-positive samples, types new2a (Ser297Ala), new2b (Ser297Ala), and 2c accounted for 64.21%, 21.05%, and 14.74%, respectively. The positive rate of CPV-2 and the distribution of the new2a, new2b and 2c types exhibited differences among regions, seasons, and ages. Immunized dogs accounted for 48.42% of 95 CPV-2-positive samples. Coinfections with canine coronavirus, canine kobuvirus, and canine bocavirus were identified. Phylogenetic analysis revealed that the identified new2a, new2b, and CPV-2c strains in our study exhibited a close relationship with most of the CPV-2 strains from China; type new2a strains exhibited high variability, forming three subgroups; type new2b and CPV-2c strains formed one group with reference strains from China. Of 95 CPV-2 strains, Tyr324Ile and Thr440Ala substitutions accounted for 100% and 64.21%, respectively; all type new2b strains exhibited the Thr440Ala substitution, while the unique Gln370Arg substitution was found in all type 2c strains. Recombination analysis using entire VP2 gene indicated possible recombination events between the identified CPV-2 strains and reference strains from China. Our data revealed the co-circulation of new CPV-2a, new CPV-2b, and rare CPV-2c, as well as potential recombination events among Chinese CPV-2 strains.
We combine mathematical modeling with experiments in living mice to quantify the relative roles of intrinsic cellular vs. tissue-scale physiological contributors to chemotherapy drug resistance, which are difficult to understand solely through experimentation. Experiments in cell culture and in mice with drug-sensitive (Eµ-myc/Arf-/-) and drug-resistant (Eµ-myc/p53-/-) lymphoma cell lines were conducted to calibrate and validate a mechanistic mathematical model. Inputs to inform the model include tumor drug transport characteristics, such as blood volume fraction, average geometric mean blood vessel radius, drug diffusion penetration distance, and drug response in cell culture. Model results show that the drug response in mice, represented by the fraction of dead tumor volume, can be reliably predicted from these inputs. Hence, a proof-of-principle for predictive quantification of lymphoma drug therapy was established based on both cellular and tissue-scale physiological contributions. We further demonstrate that, if the in vitro cytotoxic response of a specific cancer cell line under chemotherapy is known, the model is then able to predict the treatment efficacy in vivo. Lastly, tissue blood volume fraction was determined to be the most sensitive model parameter and a primary contributor to drug resistance.
Chemotherapy is mainstay of treatment for the majority of patients with breast cancer, but results in only 26% of patients with distant metastasis living 5 years past treatment in the United States, largely due to drug resistance. The complexity of drug resistance calls for an integrated approach of mathematical modeling and experimental investigation to develop quantitative tools that reveal insights into drug resistance mechanisms, predict chemotherapy efficacy, and identify novel treatment approaches. This paper reviews recent modeling work for understanding cancer drug resistance through the use of computer simulations of molecular signaling networks and cancerous tissues, with a particular focus on breast cancer. These mathematical models are developed by drawing on current advances in molecular biology, physical characterization of tumors, and emerging drug delivery methods (e.g., nanotherapeutics). We focus our discussion on representative modeling works that have provided quantitative insight into chemotherapy resistance in breast cancer and how drug resistance can be overcome or minimized to optimize chemotherapy treatment. We also discuss future directions of mathematical modeling in understanding drug resistance.
computer simulation; mathematical modeling; molecular signaling network; physical property; tumor growth and invasion; translational research
Cyclin B1-CDK1 complex plays an important role in the regulation of cell cycle. Activation of Cyclin B1 and CDK1 and the formation of the complex in G2/M are under multiple regulations involving many regulators such as isoforms of 14-3-3 and CDC25 and Wee1. Abnormal expression of Cyclin B1 and CDK1 has been detected in various tumors. However, to our knowledge no previous study has investigated Cyclin B1 and CDK1 in vulvar cancer. Therefore, we evaluated the statuses of CDK1Tyr15, pCDK1Thr161, Cyclin B1 (total) and pCyclin B1Ser126 in 297 cases of vulvar squamous cell carcinomas by immunohistochemistry. Statistical analyses were performed to explore their clinicopathological and prognostic values. In at least 25% of tumor cases high expression of CDK1Tyr15, pCDK1Thr161, Cyclin B1 (total) and pCyclin B1Ser126 was observed, compared to the low levels in normal vulvar squamous epithelium. Elevated levels of CDK1Tyr15, pCDK1Thr161, Cyclin B1 (total) and pCyclin B1Ser126 were correlated with advanced tumor behaviors and aggressive features. Although CDK1Tyr15, pCDK1Thr161, Cyclin B1 (total) and pCyclin B1Ser126 could not be identified as prognostic factors, combinations of (pCDK1Thr161 C+N + 14-3-3σN), (pCDK1Thr161 C+N + 14-3-3ηC), (pCDK1Thr161 C+N + Wee1C) and (pCDK1Thr161 C+N + 14-3-3σN + 14-3-3ηC + Wee1C) were correlated with disease-specific survival (p = 0.036, p = 0.029, p = 0.042 and p = 0.007, respectively) in univariate analysis. The independent prognostic significance of (pCDK1Thr161 C+N + 14-3-3σN + 14-3-3ηC + Wee1C) was confirmed by multivariate analysis. In conclusion, CDK1Tyr15, pCDK1Thr161, Cyclin B1 (total) and pCyclin B1Ser126 may be involved in progression of vulvar squamous cell carcinoma. The combination of pCDK1Thr161, 14-3-3σ, 14-3-3η and Wee1 was a statistically independent prognostic factor.
A quantitative understanding of the advantages of nanoparticle-based drug delivery vis-à-vis conventional free drug chemotherapy has yet to be established for cancer or other disease despite numerous investigations. Here, we employ first-principles cell biophysics, drug pharmaco-kinetics and drug pharmaco-dynamics to model the delivery of doxorubicin (DOX) to hepatocellular carcinoma (HCC) tumor cells and predict the resultant experimental cytotoxicity data. The fundamental, mechanistic hypothesis of our mathematical model is that the integrated history of drug uptake by the cells over time of exposure, which sets the cell death rate parameter, and the uptake rate are the sole determinants of dose response relationship. A universal solution of the model equations is capable of predicting the entire, nonlinear dose response of the cells to any drug concentration based on just two separate measurements of these cellular parameters. This analysis reveals that nanocarrier-mediated delivery overcomes resistance to free drug because of improved cellular uptake rates, and that dose response curves to nanocarrier mediated drug delivery are equivalent to those for free-drug, but “shifted to the left,” i.e., lower amounts of drug achieve the same cell kill. We then demonstrate the model’s general applicability to different tumor and drug types, and cell-exposure time courses by investigating HCC cells exposed to cisplatin and 5-fluorouracil, breast cancer MCF-7 cells exposed to DOX, and pancreatic adenocarcinoma PANC-1 cells exposed to gemcitabine. The model will help in the optimal design of nanocarriers for clinical applications and improve the current, largely empirical understanding of in vivo drug transport and tumor response.
Drug delivery; mathematical modeling; mesoporous silica nanoparticle; pharmacokinetics-pharmacodynamics model; protocells
Multiscale models are commonplace in cancer modeling, where individual models acting on different biological scales are combined within a single, cohesive modeling framework. However, model composition gives rise to challenges in understanding interfaces and interactions between them. Based on specific domain expertise, typically these computational models are developed by separate research groups using different methodologies, programming languages, and parameters. This paper introduces a graph-based model for semantically linking computational cancer models via domain graphs that can help us better understand and explore combinations of models spanning multiple biological scales. We take the data model encoded by TumorML, an XML-based markup language for storing cancer models in online repositories, and transpose its model description elements into a graph-based representation. By taking such an approach, we can link domain models, such as controlled vocabularies, taxonomic schemes, and ontologies, with cancer model descriptions to better understand and explore relationships between models. The union of these graphs creates a connected property graph that links cancer models by categorizations, by computational compatibility, and by semantic interoperability, yielding a framework in which opportunities for exploration and discovery of combinations of models become possible.
tumor modeling; in silico oncology; model exploration; property graphs; neo4j
Long-living Ames dwarf (df/df) mice are homozygous for a mutation of the Prop1df gene. As a result, mice are deficient in growth hormone (GH), prolactin (PRL) and thyrotropin (TSH). In spite of the hormonal deficiencies, df/df mice live significantly longer and healthier lives compared to their wild type siblings. We studied the effects of calorie restriction (CR) on the expression of insulin signaling genes in skeletal muscle and adipose tissue of normal and df/df mice. The analysis of genes expression showed that CR differentially affects the insulin signaling pathway in these insulin target organs. Moreover, results obtained in both normal and Ames dwarf mice indicate more direct effects of CR on insulin signaling genes in adipose tissue than in skeletal muscle. Interestingly, CR reduced the protein levels of adiponectin in the epididymal adipose tissue of normal and Ames dwarf mice, while elevating adiponectin levels in skeletal muscle and plasma of normal mice only.
In conclusion, our findings suggest that both skeletal muscle and adipose tissue are important mediators of insulin effects on longevity. Additionally, the results revealed divergent effects of CR on expression of genes in the insulin signaling pathway of normal and Ames dwarf mice.
Ames dwarf; insulin; adipose tissue; skeletal muscle; adiponectin; obesity