Functionally altered myeloid cells play an important role in immune suppression in cancer, in angiogenesis, and in tumor cells’ invasion and metastases. Here, we report that inhibition of Notch signaling in hematopoietic progenitor cells (HPC), myeloid-derived suppressor cells (MDSC), and dendritic cells (DC) is directly involved in abnormal myeloid cell differentiation in cancer. Inhibition of Notch signaling was caused by the disruption of the interaction between Notch receptor and transcriptional repressor CSL, which is normally required for efficient transcription of target genes. This disruption was the result of serine phosphorylation of Notch. We demonstrated that increased activity of caseine kinase 2 (CK2) observed in HPC and in MDSC could be responsible for the phosphorylation of Notch and down-regulation of Notch signaling. Inhibition of CK2 by siRNA or by pharmacological inhibitor restored Notch signaling in myeloid cells and substantially improved their differentiation, both in vitro and in vivo. This study demonstrates a novel mechanism regulation of Notch signaling in cancer. This may suggest a new perspective for pharmacological regulation of differentiation of myeloid cells in cancer.
Genetic predisposition is the primary risk factor for familial breast cancer. For the majority of familial breast cancer, however, the genetic predispositions remain unknown. All newly identified predispositions occur rarely in disease population, and the unknown genetic predispositions are estimated to reach up to total thousands. Family unit is the basic structure of genetics. Because it is an autosomal dominant disease, individuals with a history of familial breast cancer must carry the same genetic predisposition across generations. Therefore, focusing on the cases in lineages of familial breast cancer, rather than pooled cases in disease population, is expected to provide high probability to identify the genetic predisposition for each family.
In this study, we tested genetic predispositions by analyzing the family-specific variants in familial breast cancer. Using exome sequencing, we analyzed three families and 22 probands with BRCAx (BRCA-negative) familial breast cancer.
We observed the presence of family-specific, novel, deleterious germline variants in each family. Of the germline variants identified, many were shared between the disease-affected family members of the same family but not found in different families, which have their own specific variants. Certain variants are putative deleterious genetic predispositions damaging functionally important genes involved in DNA replication and damaging repair, tumor suppression, signal transduction, and phosphorylation.
Our study demonstrates that the predispositions for many BRCAx familial breast cancer families can lie in each disease family. The application of a family-focused approach has the potential to detect many new predispositions.
At present, carcinogenic models imply that all individuals in a population are susceptible to cancer. These models either ignore a fall of the cancer incidence rate at old ages, or use some poorly identifiable parameters for its accounting. In this work, a new heuristic model is proposed. The model assumes that, in a population, only a small fraction (pool) of individuals is susceptible to cancer and decomposes the problem of the carcinogenic modeling on two sequentially solvable problems: (i) determination of the age-specific hazard rate in individuals susceptible to cancer (individual hazard rate) from the observed hazard rate in the population (population hazard rate); and (ii) modelling of the individual hazard rate by a chosen “up” of the theoretical hazard function describing cancer occurrence in individuals in time (age). The model considers carcinogenesis as a failure of individuals susceptible to cancer to resist cancer occurrence in aging and uses, as the theoretical hazard function, the three-parameter Weibull hazard function, often utilized in a failure analysis. The parameters of this function, providing the best fit of the modeled and observed individual hazard rates (determined from the population hazard rates), are the outcomes of the modeling. The model was applied to the pancreatic cancer data. It was shown that, in the populations stratified by gender, race and the geographic area of living, the modeled and observed population hazard rates of pancreatic cancer occurrence have similar turnovers at old ages. The sizes of the pools of individuals susceptible to this cancer: (i) depend on gender, race and the geographic area of living; (ii) proportionally influence the corresponding population hazard rates; and (iii) do not influence the individual hazard rates. The model should be further tested using data on other types of cancer and for the populations stratified by different categorical variables.
The objective of this study was to examine the association between
tobacco and alcohol dose and type and the age of onset of pancreatic
Prospective data from the Pancreatic Cancer Collaborative Registry
were used to examine the association between age of onset and variables of
interest including: gender, race, birth country, educational status, family
history of PancCa, diabetes status, and tobacco and alcohol use. Statistical
analysis included logistic and linear regression, Cox proportional hazard
regression, and time-to-event analysis.
The median age to diagnosis for PancCa was 66.3 years (95%
confidence intervals (CIs), 64.5–68.0). Males were more likely than
females to be smokers (77% vs. 69%, P =
0.0002) and heavy alcohol and beer consumers (19% vs. 6%,
34% vs. 19%, P < 0.0001). In
univariate analysis for effects on PancCa presentation age, the following
were significant: gender, alcohol and tobacco use (amount, status and type),
family history of PancCa, and body mass index. Both alcohol and tobacco had
dose-dependent effects. In multivariate analysis, alcohol status and dose
were independently associated with increased risk for earlier PancCa onset
with greatest risk occurring in heavy drinkers (HR 1.62, 95% CI
1.04–2.54). Smoking status had the highest risk for earlier onset
pancreatic cancer with a HR of 2.69 (95% CI, 1.97–3.68) for
active smokers and independent effects for dose (P =
0.019). The deleterious effects for alcohol and tobacco appear to resolve
after 10 years of abstinence.
Alcohol and tobacco use are associated with a dose-related increased
risk for earlier age of onset of PancCa. Although beer drinkers develop
pancreatic cancer at an earlier age than nondrinkers, alcohol type did not
have a significant effect after controlling for alcohol dose.
The 18,352 pancreatic ductal adenocarcinoma (PDAC) cases from the Surveillance Epidemiology and End Results (SEER) database were analyzed using the Kaplan-Meier method for the following variables: race, gender, marital status, year of diagnosis, age at diagnosis, pancreatic subsite, T-stage, N-stage, M-stage, tumor size, tumor grade, performed surgery, and radiation therapy. Because the T-stage variable did not satisfy the proportional hazards assumption, the cases were divided into cases with T1- and T2-stages (localized tumor) and cases with T3- and T4-stages (extended tumor). For estimating survival and conditional survival probabilities in each group, a multivariate Cox regression model adjusted for the remaining covariates was developed. Testing the reproducibility of model parameters and generalizability of these models showed that the models are well calibrated and have concordance indexes equal to 0.702 and 0.712, respectively. Based on these models, a prognostic estimator of survival for patients diagnosed with PDAC was developed and implemented as a computerized web-based tool.
cancer; survival; Cox model; SEER; pancreatic cancer
Modeling of cancer hazards at age t deals with a dichotomous population, a small part of which (the fraction at risk) will get cancer, while the other part will not. Therefore, we conditioned the hazard function, h(t), the probability density function (pdf), f(t), and the survival function, S(t), on frailty α in individuals. Assuming α has the Bernoulli distribution, we obtained equations relating the unconditional (population level) hazard function, hU(t), cumulative hazard function, HU(t), and overall cumulative hazard, H0, with the h(t), f(t), and S(t) for individuals from the fraction at risk. Computing procedures for estimating h(t), f(t), and S(t) were developed and used to fit the pancreatic cancer data collected by SEER9 registries from 1975 through 2004 with the Weibull pdf suggested by the Armitage-Doll model. The parameters of the obtained excellent fit suggest that age of pancreatic cancer presentation has a time shift about 17 years and five mutations are needed for pancreatic cells to become malignant.
cancer incidence; cancer hazard; frailty; Weibull distribution; pancreatic cancer
There is increasing evidence that breast cancer is a heterogeneous disease presented by different phenotypes and that white women have a higher breast cancer incidence rate, whereas black women have a higher mortality rate. It is also well known that white women have lower incidence rates than black women until approximately age 40, when rate curves cross over and white women have higher rates. The goal of this study was to validate the risk of white and black women to breast cancer phenotypes, stratified by statuses of the estrogen (ER) and progesterone (PR) receptors.
SEER17 data were fractioned by receptor status into [ER+, PR+], [ER−, PR−], [ER+, PR−], and [ER−, PR+] phenotypes. It was shown that in black women compared to white women, cumulative age-specific incidence rates are: (i) smaller for the [ER+, PR+] phenotype; (ii) larger for the [ER−, PR−] and [ER−, PR+] phenotypes; and (iii) almost equal for the [ER+, PR−] phenotype. Clemmesen's Hook, an undulation unique to women's breast cancer age-specific incidence rate curves, is shown here to exist in both races only for the [ER+, PR+] phenotype. It was also shown that for all phenotypes, rate curves have additional undulations and that age-specific incidence rates are nearly proportional in all age intervals.
For black and white women, risk for the [ER+, PR+], [ER−, PR−] and [ER−, PR+] phenotypes are race dependent, while risk for the [ER+, PR−] phenotype is almost independent of race. The processes of carcinogenesis in aging, leading to the development of each of the considered breast cancer phenotypes, are similar in these racial groups. Undulations exhibited on the curves of age-specific incidence rates of the considered breast cancer phenotypes point to the presence of several subtypes (to be determined) of each of these phenotypes.
The Age–Period–Cohort (APC) analysis is aimed at estimating the following effects on disease incidence: (i) the age of the subject at the time of disease diagnosis; (ii) the time period, when the disease occurred; and (iii) the date of birth of the subject. These effects can help in evaluating the biological events leading to the disease, in estimating the influence of distinct risk factors on disease occurrence, and in the development of new strategies for disease prevention and treatment.
We developed a novel approach for estimating the APC effects on disease incidence rates in the frame of the Log-Linear Age-Period-Cohort (LLAPC) model. Since the APC effects are linearly interdependent and cannot be uniquely estimated, solving this identifiability problem requires setting four redundant parameters within a set of unknown parameters. By setting three parameters (one of the time-period and the birth-cohort effects and the corresponding age effect) to zero, we reduced this problem to the problem of determining one redundant parameter and, used as such, the effect of the time-period adjacent to the anchored time period. By varying this identification parameter, a family of estimates of the APC effects can be obtained. Using a heuristic assumption that the differences between the adjacent birth-cohort effects are small, we developed a numerical method for determining the optimal value of the identification parameter, by which a unique set of all APC effects is determined and the identifiability problem is solved.
We tested this approach while estimating the APC effects on lung cancer occurrence in white men and women using the SEER data, collected during 1975–2004. We showed that the LLAPC models with the corresponding unique sets of the APC effects estimated by the proposed approach fit very well with the observational data.
Cancer immunotherapeutic approaches induce tumor-specific immune responses, in particular CTL responses, in many patients treated. However, such approaches are clinically beneficial to only a few patients. We set out to investigate one possible explanation for the failure of CTLs to eliminate tumors, specifically, the concept that this failure is not dependent on inhibition of T cell function. In a previous study, we found that in mice, myeloid-derived suppressor cells (MDSCs) are a source of the free radical peroxynitrite (PNT). Here, we show that pre-treatment of mouse and human tumor cells with PNT or with MDSCs inhibits binding of processed peptides to tumor cell–associated MHC, and as a result, tumor cells become resistant to antigen-specific CTLs. This effect was abrogated in MDSCs treated with a PNT inhibitor. In a mouse model of tumor-associated inflammation in which the antitumor effects of antigen-specific CTLs are eradicated by expression of IL-1β in the tumor cells, we determined that therapeutic failure was not caused by more profound suppression of CTLs by IL-1β–expressing tumors than tumors not expressing this proinflammatory cytokine. Rather, therapeutic failure was a result of the presence of PNT. Clinical relevance for these data was suggested by the observation that myeloid cells were the predominant source of PNT in human lung, pancreatic, and breast cancer samples. Our data therefore suggest what we believe to be a novel mechanism of MDSC-mediated tumor cell resistance to CTLs.
The Breast Cancer Collaborative Registry (BCCR) is a multicenter web-based system that efficiently collects and manages a variety of data on breast cancer (BC) patients and BC survivors. This registry is designed as a multi-tier web application that utilizes Java Servlet/JSP technology and has an Oracle 11g database as a back-end. The BCCR questionnaire has accommodated standards accepted in breast cancer research and healthcare. By harmonizing the controlled vocabulary with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), the BCCR provides a standardized approach to data collection and reporting. The BCCR has been recently certified by the National Cancer Institute’s Center for Biomedical Informatics and Information Technology (NCI CBIIT) as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product.
The BCCR is aimed at facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention, treatment, and survivorship strategies against breast cancer. Currently, seven cancer institutions are participating in the BCCR that contains data on almost 900 subjects (BC patients and survivors, as well as individuals at high risk of getting BC).
biomedical informatics; breast cancer; registry; caBIG® bronze compatible system
The Pancreatic Cancer Collaborative Registry (PCCR) is a multi-institutional web-based system aimed to collect a variety of data on pancreatic cancer patients and high-risk subjects in a standard and efficient way. The PCCR was initiated by a group of experts in medical oncology, gastroenterology, genetics, pathology, epidemiology, nutrition, and computer science with the goal of facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention and treatment strategies against pancreatic cancer. The PCCR is a multi-tier web application that utilizes Java/JSP technology and has Oracle 10 g database as a back-end. The PCCR uses a “confederation model” that encourages participation of any interested center, irrespective of its size or location. The PCCR utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The PCCR controlled vocabulary is harmonized with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT). The PCCR questionnaire has accommodated standards accepted in cancer research and healthcare. Currently, seven cancer centers in the USA, as well as one center in Italy are participating in the PCCR. At present, the PCCR database contains data on more than 2,700 subjects (PC patients and individuals at high risk of getting this disease). The PCCR has been certified by the NCI Center for Biomedical Informatics and Information Technology as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product. The PCCR provides a foundation for collaborative PC research. It has all the necessary prerequisites for subsequent evolution of the developed infrastructure from simply gathering PC-related data into a biomedical computing platform vital for successful PC studies, care and treatment. Studies utilizing data collected in the PCCR may engender new approaches to disease prognosis, risk factor assessment, and therapeutic interventions.
biomedical informatics; pancreatic cancer; registry; caBIG® bronze compatible system
In the frame of the Cox proportional hazard (PH) model, a novel two-step procedure for estimating age-period-cohort (APC) effects on the hazard function of death from cancer was developed. In the first step, the procedure estimates the influence of joint APC effects on the hazard function, using Cox PH regression procedures from a standard software package. In the second step, the coefficients for age at diagnosis, time period and birth cohort effects are estimated. To solve the identifiability problem that arises in estimating these coefficients, an assumption that neighboring birth cohorts almost equally affect the hazard function was utilized. Using an anchoring technique, simple procedures for obtaining estimates of interrelated age at diagnosis, time period and birth cohort effect coefficients were developed.
As a proof-of-concept these procedures were used to analyze survival data, collected in the SEER database, on white men and women diagnosed with LC in 1975–1999 and the age at diagnosis, time period and birth cohort effect coefficients were estimated. The PH assumption was evaluated by a graphical approach using log-log plots. Analysis of trends of these coefficients suggests that the hazard of death from LC for a given time from cancer diagnosis: (i) decreases between 1975 and 1999; (ii) increases with increasing the age at diagnosis; and (iii) depends upon birth cohort effects.
The proposed computing procedure can be used for estimating joint APC effects, as well as interrelated age at diagnosis, time period and birth cohort effects in survival analysis of different types of cancer.
cancer survival; age; time period; cohort; hazard function; lung cancer
The MUC1 glycoprotein is considered a tumor antigen due to its over-expression and aberrant glycosylation in cancer tissues. The latter results in appearance of new antigenic tumor-specific glycopeptides not found on normal glycoforms of the mucin. MUC1 glycopeptides can be presented by APCs on MHC class II molecules to activate glycopeptide-specific helper T-cells. No study has yet reported presentation of MUC1 glycopeptides on MHC class I molecules as stimulators of cytotoxic T-cells. In this study we show that human immuno- proteasomes and cathepsin-L can generate octa- to undecameric glycopeptides from the MUC1 repeat domain in vitro. We identified glycosylated fragments of which the decameric glycopeptide SAP10 [SAPDT(GalNAc)RPAPG] containing a single sugar binds with comparable strength to the MHC class I allele HLA-A*0201 as predicted high-score binding epitopes of the tandem repeat. The same sequence glycosylated with the disaccharide Gal-GalNAc does not bind. The glycan on SAP10 is predicted by molecular modeling to either protrude out or point into the MHC groove. SAPDTRPAPG peptide and the respective glycopeptide stimulated cytotoxic T-cells in vitro. Our findings suggest that MUC1 tandem repeat glycopeptides are capable of activating both helper and cytotoxic T-cells and thus represent good candidates for further development as vaccines.
Cancer vaccine; MHC class I; MUC1; immunoproteasome; cathepsin-L
Mathematical modeling of cancer development is aimed at assessing the risk factors leading to cancer. Aging is a common risk factor for all adult cancers. The risk of getting cancer in aging is presented by a hazard function that can be estimated from the observed incidence rates collected in cancer registries. Recent analyses of the SEER database show that the cancer hazard function initially increases with the age, and then it turns over and falls at the end of the lifetime. Such behavior of the hazard function is poorly modeled by the exponential or compound exponential-linear functions mainly utilized for the modeling. In this work, for mathematical modeling of cancer hazards, we proposed to use the Weibull-like function, derived from the Armitage-Doll multistage concept of carcinogenesis and an assumption that number of clones at age t developed from mutated cells follows the Poisson distribution. This function is characterized by three parameters, two of which (r and λ) are the conventional parameters of the Weibull probability distribution function, and an additional parameter (C0) that adjusts the model to the observational data. Biological meanings of these parameters are: r—the number of stages in carcinogenesis, λ—an average number of clones developed from the mutated cells during the first year of carcinogenesis, and C0—a data adjustment parameter that characterizes a fraction of the age-specific population that will get this cancer in their lifetime. To test the validity of the proposed model, the nonlinear regression analysis was performed for the lung cancer (LC) data, collected in the SEER 9 database for white men and women during 1975–2004. Obtained results suggest that: (i) modeling can be improved by the use of another parameter A- the age at the beginning of carcinogenesis; and (ii) in white men and women, the processes of LC carcinogenesis vary by A and C0, while the corresponding values of r and λ are nearly the same. Overall, the proposed Weibull-like model provides an excellent fit of the estimates of the LC hazard function in aging. It is expected that the Weibull-like model can be applicable to fit estimates of hazard functions of other adult cancers as well.
cancer; aging; cancer hazard; Weibull distribution
An efficient computing procedure for estimating the age-specific hazard functions by the log-linear age-period-cohort (LLAPC) model is proposed. This procedure accounts for the influence of time period and birth cohort effects on the distribution of age-specific cancer incidence rates and estimates the hazard function for populations with different exposures to a given categorical risk factor. For these populations, the ratio of the corresponding age-specific hazard functions is proposed for use as a measure of relative hazard. This procedure was used for estimating the risks of lung cancer (LC) for populations living in different geographical areas. For this purpose, the LC incidence rates in white men and women, in three geographical areas (namely: San Francisco-Oakland, Connecticut and Detroit), collected from the SEER 9 database during 1975–2004, were utilized. It was found that in white men the averaged relative hazard (an average of the relative hazards over all ages) of LC in Connecticut vs. San Francisco-Oakland is 1.31 ± 0.02, while in Detroit vs. San Francisco-Oakland this averaged relative hazard is 1.53 ± 0.02. In white women, analogous hazards in Connecticut vs. San Francisco-Oakland and Detroit vs. San Francisco-Oakland are 1.22 ± 0.02 and 1.32 ± 0.02, correspondingly. The proposed computing procedure can be used for assessing hazard functions for other categorical risk factors, such as gender, race, lifestyle, diet, obesity, etc.
cancer incidence; temporal trend; cohort effect; hazard function; lung cancer
The structural organization of the amyloidogenic β-protein containing 40 amino acid residues (Aβ40) was studied by the high temperature molecular dynamics simulations in the acidic (pH ∼ 3) and basic (pH ∼ 8) pH regions. The obtained data suggest that the central Ala21-Gly29 segment of Aβ40 can adopt folded and partially unfolded structures. At the basic pH, this segment forms folded structures stabilized by electrostatic interactions and hydrogen bonds. At the acidic pH, it forms partially unfolded structures. Two other segments flanking to the central segment exhibit the propensity to adopt unstable interconverting α-helical, 310-helical and turn-like structures. One of these segments is comprised of the Ala30-Val36 residues at both of the considered pHs. The second segment is comprised of the Glu11-Phe20 at the basic pH and of the Glu11-Val24 residues at the acidic pHs. The revealed pH-dependent structuration of the Aβ40 allowed us to suggest a possible scenario for initial Aβ aggregation. According to this scenario, the occurrence of the partially unfolded states of the Ala21-Gly29 segment plays main role in the Aβ oligomerization process.
amyloid-β protein; Alzheimer disease; oligomerization; fibril; electrostatic interactions; molecular dynamics simulations
A simple, computationally efficient procedure for analyses of the time period and birth cohort effects on the distribution of the age-specific incidence rates of cancers is proposed. Assuming that cohort effects for neighboring cohorts are almost equal and using the Log-Linear Age-Period-Cohort Model, this procedure allows one to evaluate temporal trends and birth cohort variations of any type of cancer without prior knowledge of the hazard function. This procedure was used to estimate the influence of time period and birth cohort effects on the distribution of the age-specific incidence rates of first primary, microscopically confirmed lung cancer (LC) cases from the SEER9 database. It was shown that since 1975, the time period effect coefficients for men increase up to 1980 and then decrease until 2004. For women, these coefficients increase from 1975 up to 1990 and then remain nearly constant. The LC birth cohort effect coefficients for men and women increase from the cohort of 1890–94 until the cohort of 1925–29, then decrease until the cohort of 1950–54 and then remain almost unchanged. Overall, LC incidence rates, adjusted by period and cohort effects, increase up to the age of about 72–75, turn over, and then fall after the age of 75–78. The peak of the adjusted rates in men is around the age of 77–78, while in women, it is around the age of 72–73. Therefore, these results suggest that the age distribution of the incidence rates in men and women fall at old ages.
identifiability problem; temporal trend; cohort effect; cancer incidence; lung cancer
The relationships between cancer incidence rates and the age of patients at cancer diagnosis are a quantitative basis for modeling age distributions of cancer. The obtained model parameters are needed to build rigorous statistical and biological models of cancer development. In this work, a new mathematical model, called the Generalized Beta (GB) model is proposed. Confidence intervals for parameters of this model are derived from a regression analysis. The GB model was used to approximate the incidence rates of the first primary, microscopically confirmed cases of pancreatic cancer (PC) and kidney cancer (KC) that served as a test bed for the proposed approach. The use of the GB model allowed us to determine analytical functions that provide an excellent fit for the observed incidence rates for PC and KC in white males and females. We make the case that the cancer incidence rates can be characterized by a unique set of model parameters (such as an overall cancer rate, and the degree of increase and decrease of cancer incidence rates). Our results suggest that the proposed approach significantly expands possibilities and improves the performance of existing mathematical models and will be very useful for modeling carcinogenic processes characteristic of cancers. To better understand the biological plausibility behind the aforementioned model parameters, detailed molecular, cellular, and tissue-specific mechanisms underlying the development of each type of cancer require further investigation. The model parameters that can be assessed by the proposed approach will complement and challenge future biomedical and epidemiological studies.
cancer; incidence rates; aging; histopathology
Polymer therapeutics has emerged as a new clinical option for the treatment of human diseases. However, little is known about pharmacogenetic responses to drugs formulated with polymers. In this study, we demonstrate that a formulation containing the block copolymer Pluronic P85 and antineoplastic drug, doxorubicin (Dox), prevents the development of multidrug resistance in the human breast carcinoma cell line, MCF7. Specifically, MCF7 cells cultured in the presence of Pluronic were unable to stably grow in concentrations of Dox that exceeded 10ng Dox/ml of culture media. In sharp contrast, MCF7 cells cultured in the absence of the block copolymer resulted in the selection and stable growth of cells that tolerated 1000 times higher concentration of the drug (10,000ng Dox/ml culture media). Detailed characterization of the isolated sublines demonstrated that those cells selected in the polymer-drug formulation did not show amplification of the MDR1 gene, likely resulting in their high sensitivity to the drug. Conversely, cells selected with Dox alone showed an elevated level in the expression of the MDR1 gene along with a corresponding increase in the expression level of the drug efflux transporter, Pgp, and likely contributing to the high resistance of the cells to Dox. Global analysis of the expression profiles of 20K genes by DNA microarray revealed that the use of Pluronic in combination with Dox drastically changed the direction and magnitude of the genetic response of the tumor cells to Dox and may potentially enhance therapeutic outcomes. Overall, this study reinforces the need for a thorough assessment of pharmacogenomic effects of polymer therapeutics.
multidrug resistance; P-glycoprotein; Pluronic; poloxamer; polymer genomics
Antigen-specific CD8+ T-cell tolerance is one of the major mechanisms of tumor escape. Recent studies have shown that this tolerance was induced by myeloid-derived suppressor cells (MDSC). Using in vivo models we have found that MDSC directly disrupted the binding of the specific peptide-MHC (pMHC) dimers to CD8+ T cells via nitration of tyrosines within TCR/CD8 complex, which resulted in the inability of CD8+ T cells to bind pMHC and respond to the specific peptide. These cells retained their ability to respond to non-specific stimulation. Nitration of TCR/CD8 was induced by MDSC via hyperproduction of reactive oxygen species (ROS) and peroxynitrite during direct cell-cell contact. Molecular modeling suggested specific sites of nitration that could affect conformational flexibility of TCR/CD8 and its interaction with pMHC. This data demonstrates novel mechanisms of T-cell tolerance in cancer that also can be pertinent to many pathological conditions associated with accumulation of MDSC.
Misfolding and aggregation of proteins is a common thread linking a number of important human health problems. The misfolded and aggregated proteins are inducers of cellular stress and activators of immunity in neurodegenerative diseases. They might posses clear cytotoxic properties, being responsible for the dysfunction and loss of cells in the affected organs. Despite the crucial importance of protein misfolding and abnormal interactions, very little is currently known about the molecular mechanism underlying these processes. Factors that lead to protein misfolding and aggregation in vitro are poorly understood, not to mention the complexities involved in the formation of protein nanoparticles with different morphologies (e.g. the nanopores) in vivo. A better understanding of the molecular mechanisms of misfolding and aggregation might facilitate development of the rational approaches to prevent pathologies mediated by protein misfolding. The conventional tools currently available to researchers can only provide an averaged picture of a living system, whereas much of the subtle or short-lived information is lost. We believe that the existing and emerging nanotools might help solving these problems by opening the entirely novel pathways for the development of early diagnostic and therapeutic approaches. This article summarizes recent advances of the nanoscience in detection and characterization of misfolded protein conformations. Based on these findings we outline our view on the nanoscience development towards identification intracellular nanomachines and/or multicomponent complexes critically involved in protein misfolding.
protein misfolding; protein aggregation; conformational disease; nanomedicine; atomic force microscopy; force spectroscopy; single molecule analyses
The neuropathology of Parkinson's disease (PD) includes loss of dopaminergic neurons in the substantia nigra, nitrated α-synuclein (N-α-Syn) enriched intraneuronal inclusions or Lewy bodies and neuroinflammation. While the contribution of innate microglial inflammatory activities to disease are known, evidence for how adaptive immune mechanisms may affect the course of PD remains obscure. We reasoned that PD-associated oxidative protein modifications create novel antigenic epitopes capable of peripheral adaptive T cell responses that could affect nigrostriatal degeneration.
Methods and Findings
Nitrotyrosine (NT)-modified α-Syn was detected readily in cervical lymph nodes (CLN) from 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) intoxicated mice. Antigen-presenting cells within the CLN showed increased surface expression of major histocompatibility complex class II, initiating the molecular machinery necessary for efficient antigen presentation. MPTP-treated mice produced antibodies to native and nitrated α-Syn. Mice immunized with the NT-modified C-terminal tail fragment of α-Syn, but not native protein, generated robust T cell proliferative and pro-inflammatory secretory responses specific only for the modified antigen. T cells generated against the nitrated epitope do not respond to the unmodified protein. Mice deficient in T and B lymphocytes were resistant to MPTP-induced neurodegeneration. Transfer of T cells from mice immunized with N-α-Syn led to a robust neuroinflammatory response with accelerated dopaminergic cell loss.
These data show that NT modifications within α-Syn, can bypass or break immunological tolerance and activate peripheral leukocytes in draining lymphoid tissue. A novel mechanism for disease is made in that NT modifications in α-Syn induce adaptive immune responses that exacerbate PD pathobiology. These results have implications for both the pathogenesis and treatment of this disabling neurodegenerative disease.
There are three major B-cell compartments in peripheral lymphoid organs: the germinal center (GC), the mantle zone (MNZ) and the marginal zone (MGZ). Unique sets of B-cells reside in these compartments, and they have specific functional roles in humoral immune response. MNZ B cells are naïve cells in a quiescent state and may participate in GC reactions upon proper stimulation. The adult splenic MGZ contains mostly memory B cells and is also known to provide a rapid response to particulate antigens. The GC B-cells proliferate rapidly and undergo selection and affinity maturation. The B-cell maturational process is accompanied by changes in the expression of cell-surface and intracellular proteins and requires signals from the specialized microenvironments.
We performed laser microdissection of the three compartments for gene expression profiling by cDNA microarray. The transcriptional program of the GC was dominated by upregulation of genes associated with proliferation and DNA repair or recombination. The MNZ and MGZ showed increased expression of genes promoting cellular quiescence. The three compartments also revealed distinct repertoires of apoptosis-associated genes, chemokines and chemokine receptors. The MNZ and GC showed upregulation of CCL20 and CCL18 respectively. The MGZ was characterized by high expression of many chemokines genes e.g. CXCL12, CCL3, CCL14 and IFN-associated genes, consistent with its role in rapid response to infections. A stromal signature was identified including genes associated with macrophages or with synthesis of extracellular matrix and genes that influenced lymphocyte migration and survival. Differentially expressed genes that did not belong to the above categories include the well characterized BCL6 and CD10 and many others whose function is not known.
Transcriptional profiling of B-cell compartments has identified groups of genes involved in critical molecular and cellular events that affect proliferation, survival migration, and differentiation of the cells. The gene expression study of normal B-cell compartments may additionally contribute to our understanding of the molecular abnormalities of the corresponding lymphoid tumors.