Association of polymorphisms in TGFB1, XRCC1, XRCC3 genes and CD8 T-lymphocyte apoptosis with adverse effect of radiotherapy for prostate cancer.

The genetic background of each person might affect the severity of radiotherapy (RT)-induced normal tissue toxicity. The aim of study was to evaluate the influence of TGFB1 C-509T and Leu10Pro, XRCC1 Arg280His and XRCC3 Thr241Met polymorphisms as well as the level of radiation-induced CD8 T-lymphocyte apoptosis (RILA) on adverse effects of RT for prostate cancer (PCa). The study included 88 patients with localized or locally advanced PCa who were treated with RT. The polymorphisms were determined by PCR-RFLP analysis on DNA from peripheral blood mononuclear cells. RILA values were measured by flow cytometry. We found that CT genotype of TGFB1 C-509T could be protective biomarker for acute genitourinary (GU) and gastrointestinal (GI) radiotoxicity, while Thr variant of XRCC3 Thr241Met could predict the risk for acute GU radiotoxicity. Correlation between RILA values and toxicity was not detected. Univariate logistic regression analysis showed that Gleason score and risk group were risk factors for late GU, while for late GI radiotoxicity it was diabetes mellitus type 2. However, in multivariate model those were not proven to be significant and independent risk factors. Identification of assays combination predicting individual radiosensitivity is a crucial step towards personalized RT approach.

Treatment time and circadian genotype interact to influence radiotherapy side-effects. A prospective European validation study using the REQUITE cohort.

BACKGROUND: Circadian rhythm impacts broad biological processes, including response to cancer treatment. Evidence conflicts on whether treatment time affects risk of radiotherapy side-effects, likely because of differing time analyses and target tissues. We previously showed interactive effects of time and genotypes of circadian genes on late toxicity after breast radiotherapy and aimed to validate those results in a multi-centre cohort. METHODS: Clinical and genotype data from 1690 REQUITE breast cancer patients were used with erythema (acute; n=340) and breast atrophy (two years post-radiotherapy; n=514) as primary endpoints. Local datetimes per fraction were converted into solar times as predictors. Genetic chronotype markers were included in logistic regressions to identify primary endpoint predictors. FINDINGS: Significant predictors for erythema included BMI, radiation dose and PER3 genotype (OR 1.27(95%CI 1.03-1.56); P < 0.03). Effect of treatment time effect on acute toxicity was inconclusive, with no interaction between time and genotype. For late toxicity (breast atrophy), predictors included BMI, radiation dose, surgery type, treatment time and SNPs in CLOCK (OR 0.62 (95%CI 0.4-0.9); P < 0.01), PER3 (OR 0.65 (95%CI 0.44-0.97); P < 0.04) and RASD1 (OR 0.56 (95%CI 0.35-0.89); P < 0.02). There was a statistically significant interaction between time and genotypes of circadian rhythm genes (CLOCK OR 1.13 (95%CI 1.03-1.23), P < 0.01; PER3 OR 1.1 (95%CI 1.01-1.2), P < 0.04; RASD1 OR 1.15 (95%CI 1.04-1.28), P < 0.008), with peak time for toxicity determined by genotype. INTERPRETATION: Late atrophy can be mitigated by selecting optimal treatment time according to circadian genotypes (e.g. treat PER3 rs2087947C/C genotypes in mornings; T/T in afternoons). We predict triple-homozygous patients (14%) reduce chance of atrophy from 70% to 33% by treating in mornings as opposed to mid-afternoon. Future clinical trials could stratify patients treated at optimal times compared to those scheduled normally. FUNDING: EU-FP7.

Improving Patients' Life Quality after Radiotherapy Treatment by Predicting Late Toxicities.

Personalized treatment and precision medicine have become the new standard of care in oncology and radiotherapy. Because treatment outcomes have considerably improved over the last few years, permanent side-effects are becoming an increasingly significant issue for cancer survivors. Five to ten percent of patients will develop severe late toxicity after radiotherapy. Identifying these patients before treatment start would allow for treatment adaptation to minimize definitive side effects that could impair their long-term quality of life. Over the last decades, several tests and biomarkers have been developed to identify these patients. However, out of these, only the Radiation-Induced Lymphocyte Apoptosis (RILA) assay has been prospectively validated in multi-center cohorts. This test, based on a simple blood draught, has been shown to be correlated with late radiation-induced toxicity in breast, prostate, cervical and head and neck cancer. It could therefore greatly improve decision making in precision radiation oncology. This literature review summarizes the development and bases of this assay, as well as its clinical results and compares its results to the other available assays.

Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity.

AIM: To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi). MATERIALS AND METHODS: Analysis included the REQUITE PCa cohort that received external beam RT and was followed for 2 years. Late toxicity endpoints were: rectal bleeding, urinary frequency, haematuria, nocturia, decreased urinary stream. Among 43 literature-identified SNPs, the 30% most strongly associated with each toxicity were tested. SNP-SNP combinations (named SNP-allele sets) seen in ≥10% of the cohort were condensed into risk (RS) and protection (PS) scores, respectively indicating increased or decreased toxicity risk. Performance of RS and PS was evaluated by logistic regression. RS and PS were then combined into a single PRSi evaluated by area under the receiver operating characteristic curve (AUC). RESULTS: Among 1,387 analysed patients, toxicity rates were 11.7% (rectal bleeding), 4.0% (urinary frequency), 5.5% (haematuria), 7.8% (nocturia) and 17.1% (decreased urinary stream). RS and PS combined 8 to 15 different SNP-allele sets, depending on the toxicity endpoint. Distributions of PRSi differed significantly in patients with/without toxicity with AUCs ranging from 0.61 to 0.78. PRSi was better than the classical summed PRS, particularly for the urinary frequency, haematuria and decreased urinary stream endpoints. CONCLUSIONS: Our method incorporates SNP-SNP interactions when calculating PRS for radiotherapy toxicity. Our approach is better than classical summation in discriminating patients with toxicity and should enable incorporating genetic information to improve normal tissue complication probability models.

Spleen plays a major role in DLL4-driven acute T-cell lymphoblastic leukemia.

The Notch pathway is highly active in almost all patients with T-cell acute lymphoblastic leukemia (T-ALL), but the implication of Notch ligands in T-ALL remains underexplored. Methods: We used a genetic mouse model of Notch ligand delta like 4 (DLL4)-driven T-ALL and performed thymectomies and splenectomies in those animals. We also used several patient-derived T-ALL (PDTALL) models, including one with DLL4 expression on the membrane and we treated PDTALL cells in vitro and in vivo with demcizumab, a blocking antibody against human DLL4 currently being tested in clinical trials in patients with solid cancer. Results: We show that surgical removal of the spleen abrogated T-ALL development in our preclinical DLL4-driven T-ALL mouse model. Mechanistically, we found that the spleen, and not the thymus, promoted the accumulation of circulating CD4+CD8+ T cells before T-ALL onset, suggesting that DLL4-driven T-ALL derives from these cells. Then, we identified a small subset of T-ALL patients showing higher levels of DLL4 expression. Moreover, in mice xenografted with a DLL4-positive PDTALL model, treatment with demcizumab had the same therapeutic effect as global Notch pathway inhibition using the potent γ-secretase inhibitor dibenzazepine. This result demonstrates that, in this PDTALL model, Notch pathway activity depends on DLL4 signaling, thus validating our preclinical mouse model. Conclusion: DLL4 expression in human leukemic cells can be a source of Notch activity in T-ALL, and the spleen plays a major role in a genetic mouse model of DLL4-driven T-ALL.

Consequences of population structure for sex allocation and sexual conflict.

Both sex allocation and sexual conflict can be modulated by spatial structure. However, how the interplay between the type of dispersal and the scale of competition simultaneously affects these traits in sub-divided populations is rarely considered. We investigated sex allocation and sexual conflict evolution in meta-populations of the spider mite Tetranychus urticae evolving under budding (pairing females from the same patch) or random (pairing females from different patches) dispersal and either local (fixed sampling from each subpopulation) or global (sampling as a function of subpopulation productivity) competition. Females evolving under budding dispersal produced less female-biased offspring sex ratios than those from the random dispersal selection regimes, contradicting theoretical predictions. In contrast, the scale of competition did not strongly affect sex allocation. Offspring sex ratio and female fecundity were unaffected by the number of mates, but female fecundity was highest when their mates evolved under budding dispersal, suggesting these males inflict less harm than those evolving under random dispersal. This work highlights that population structure can impact the evolution of sex allocation and sexual conflict. Moreover, selection on either trait may reciprocally affect the evolution of the other, for example via effects on fecundity.

Quantitative proteomic analysis reveals AK2 as potential biomarker for late normal tissue radiotoxicity.

BACKGROUND: Biomarkers for predicting late normal tissue toxicity to radiotherapy are necessary to personalize treatments and to optimize clinical benefit. Many radiogenomic studies have been published on this topic. Conversely, proteomics approaches are not much developed, despite their advantages. METHODS: We used the isobaric tags for relative and absolute quantitation (iTRAQ) proteomic approach to analyze differences in protein expression levels in ex-vivo irradiated (8 Gy) T lymphocytes from patients with grade ≥ 2 radiation-induced breast fibrosis (grade ≥ 2 bf+) and patients with grade < 2 bf + after curative intent radiotherapy. Patients were selected from two prospective clinical trials (COHORT and PHRC 2005) and were used as discovery and confirmation cohorts. RESULTS: Among the 1979 quantified proteins, 23 fulfilled our stringent biological criteria. Immunoblotting analysis of four of these candidate proteins (adenylate kinase 2, AK2; annexin A1; heat shock cognate 71 kDa protein; and isocitrate dehydrogenase 2) confirmed AK2 overexpression in 8 Gy-irradiated T lymphocytes from patients with grade ≥ 2 bf + compared with patients with grade < 2 bf+. As these candidate proteins are involved in oxidative stress regulation, we also evaluated radiation-induced reactive oxygen species (ROS) production in peripheral blood mononuclear cells from patients with grade ≥ 2 bf + and grade < 2 bf+. Total ROS level, and especially superoxide anion level, increased upon ex-vivo 8 Gy-irradiation in all patients. Analysis of NADPH oxidases (NOXs), a major source of superoxide ion in the cell, showed a significant increase of NOX4 mRNA and protein levels after irradiation in both patient groups. Conversely, only NOX4 mRNA level was significantly different between groups (grade ≥ 2 bf + and grade < 2 bf+). CONCLUSION: These findings identify AK2 as a potential radiosensitivity candidate biomarker. Overall, our proteomic approach highlights the important role of oxidative stress in late radiation-induced toxicity, and paves the way for additional studies on NOXs and superoxide ion metabolism.

Multi-centre technical evaluation of the radiation-induced lymphocyte apoptosis assay as a predictive test for radiotherapy toxicity.

Predicting which patients will develop adverse reactions to radiotherapy is important for personalised treatment. Prediction will require an algorithm or nomogram combining clinical and biological data. The radiation-induced lymphocyte apoptosis (RILA) assay is the leading candidate as a biological predictor of radiotherapy toxicity. In this study we tested the potential of the assay for standardisation and use in multiple testing laboratories. The assay was standardised and reproducibility determined using samples from healthy volunteers assayed concurrently in three laboratories in Leicester (UK), Mannheim (Germany) and Montpellier (France). RILA assays were performed on samples taken prior to radiotherapy from 1319 cancer patients enrolled in the REQUITE project at multiple centres. The patients were being treated for breast (n = 753), prostate (n = 506) or lung (n = 60) cancer. Inter-laboratory comparisons identified several factors affecting results: storage time, incubation periods and type of foetal calf serum. Following standardisation, there was no significant difference in results between the centres. Significant differences were seen in RILA scores between cancer types (prostate > breast > lung), by smoking status (non-smokers > smokers) and co-morbidity with rheumatoid arthritis (arthritics > non-arthritics). An analysis of acute radiotherapy toxicity showed as expected that RILA assay does not predict most end-points, but unexpectedly did predict acute breast pain. This result may elucidate the mechanism by which the RILA assay predicts late radiotherapy toxicity. The work shows clinical trials involving multiple laboratory measurement of the RILA assay are feasible and the need to account for tumour type and other variables when applying to predictive models.

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer.

PURPOSE: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. METHODS: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. RESULTS: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician- (47,025 forms) and patient- (54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade ≥2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). CONCLUSION: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. PATIENT SUMMARY: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short- and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity.

Impact of adjuvant hormonotherapy on radiation-induced breast fibrosis according to the individual radiosensitivity: results of a multicenter prospective French trial.

BACKGROUND: To evaluate risk of severe breast fibrosis occurrence in patients treated by breast-conserving surgery, adjuvant radiotherapy and hormonotherapy (HT) according to individual radiosensitivity (RILA assay). RESULTS: HT- and RILAhigh were the two independent factors associated with improved breast-fibrosis free survival (BFFS). BFFS rate at 36 months was lower in patients with RILAlow and HT+ than in patients with RILAhigh and HT- (75.8% and 100%, respectively; p = 0.004, hazard ratio 5.84 [95% confidence interval (CI) 1.8-19.1]). Conversely, BFFS at 36 months was comparable in patients with RILAhigh and HT+ and in patients with RILAlow and HT- (89.8% and 93.5%, respectively; p = 0.39, hazard ratio 1.7 [95% CI 0.51-5.65]), showing that these two parameters influenced independently the occurrence of severe breast fibrosis. BFFS rate was not affected by the HT type (tamoxifen or aromatase inhibitor) and timing (concomitant or sequential with radiotherapy). CONCLUSIONS: HT and RILA score independently influenced BFFS rate at 36 months. Patients with RILAhigh and HT- presented an excellent BFFS at 36 months (100%). MATERIALS AND METHODS: Breast Fibrosis-Free Survival (BFFS) rate was assessed relative to RILA categories and to adjuvant HT use (HT+ and HT-, respectively) in a prospective multicentre study (NCT00893035) which enrolled 502 breast cancer patients (456 evaluable patients). Breast fibrosis was recorded according to CTCAE v3.0 grading scale; RILA score was defined according to two categories (<12%: RILAlow; ≥12%: RILAhigh).

Personalizing Breast Cancer Irradiation Using Biology: From Bench to the Accelerator.

While adjuvant treatments of early breast cancers (BCs) had significantly improved patients' overall survival, some of them will still develop locoregional relapses and/or severe late radio-induced toxicities. Here, we propose to review how to personalize locoregional treatment by identifying patients at high and low risk of locoregional relapse, patients at risk of late radio-induced side effects. We will, therefore, discuss how to enhance BC radiosensitivity. Finally, we will address how personalized radiotherapy could be implemented in prospective clinical trials.

Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era.

The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules to avoid toxicity would be clinically advantageous. Indeed, for the patient at low risk of developing radiation-associated toxicity, use of a hypofractionated protocol could be proposed leading to treatment time reduction and a cost-utility advantage. Conversely, for patients predicted to be at high risk for toxicity, either a more conformal form or a new technique of RT, or a multidisciplinary approach employing surgery could be included in the trial design to avoid or mitigate RT when the potential toxicity risk may be higher than the risk of disease recurrence. In addition, for patients at high risk of recurrence and low risk of toxicity, dose escalation, such as a greater boost dose, or irradiation field extensions could be considered to improve local control without severe toxicities, providing enhanced clinical benefit. In cases of high risk of toxicity, tumor control should be prioritized. In this review, toxicity biomarkers with sufficient evidence for clinical testing are presented. In addition, clinical trial designs and predictive models are described for different clinical situations.

T lymphocytes to predict radiation-induced late effects in normal tissues.

INTRODUCTION: Radiotherapy is one of the main treatments for solid tumors. The total dose that can be delivered to the tumor is limited by the radiation amount received by the surrounding normal tissues, which are at risk of developing acute and late radiation-induced effects. Areas covered: Severe late radiation-induced toxicity occurs in 5% to 10% of patients following radiotherapy. However, the current radiotherapy and radiation protection protocols do not take into account the variations in radiosensitivity among individuals. This review will focus on late radiotherapy-induced side effects and on the different cellular assays (γ-H2AX/53BP1 focus formation, G2 metaphase, G0 micronucleus formation and radio-induced apoptosis in CD8+ T-lymphocytes: level I evidence) that have been developed to predict their occurrence in patients. Expert commentary: The routine prediction of late radiation-induced toxicity in normal tissues in the clinic will allow personalized radiotherapy with better outcome and less side effects. Patients at low risk of late toxicity could receive a higher total dose to the tumor. Conversely, patients at high risk of late toxicity should receive lower radiation doses per fraction, using state-of-the-art treatment techniques, or alternative therapies to avoid radiation-induced side effects.

Microfluidic module for blood cell separation for gene expression radiobiological assays.

Advances in molecular techniques have improved discovery of biomarkers associated with radiation exposure. Gene expression techniques have been demonstrated as effective tools for biodosimetry, and different assay platforms with different chemistries are now available. One of the main challenges is to integrate the sample preparation processing of these assays into microfluidic platforms to be fully automated for point-of-care medical countermeasures in the case of a radiological event. Most of these assays follow the same workflow processing that comprises first the collection of blood samples followed by cellular and molecular sample preparation. The sample preparation is based on the specific reagents of the assay system and depends also on the different subsets of cells population and the type of biomarkers of interest. In this article, the authors present a module for isolation of white blood cells from peripheral blood as a prerequisite for automation of gene expression assays on a microfluidic cartridge. For each sample condition, the gene expression platform can be adapted to suit the requirements of the selected assay chemistry.

Method for validating radiobiological samples using a linear accelerator.

There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed ex-vivo irradiation of human blood samples using the linear accelerator (LINAC). The LINAC was implemented and calibrated for irradiating human whole blood samples. To test the calibration, a 2 Gy test run was successfully performed on a tube filled with water with an accuracy of 3% in dose distribution. To validate our technique the blood samples were ex-vivo irradiated and the results were analyzed using a gene expression assay to follow the effect of the ionizing irradiation by characterizing dose responsive biomarkers from radiobiological assays. The response of 5 genes was monitored resulting in expression increase with the dose of radiation received. The blood samples treated with the LINAC can provide effective irradiated blood samples suitable for molecular profiling to validate radiobiological measurements via the gene-expression based biodosimetry tools.

Biodosimetry on small blood volume using gene expression assay.

This paper reports the development of a biodosimetry device suitable for rapidly measuring expression levels of a low-density gene set that can define radiation exposure, dose and injury in a public health emergency. The platform comprises a set of 14 genes selected on the basis of their abundance and differential expression level in response to radiation from an expression profiling series measuring 41,000 transcripts. Gene expression is analyzed through direct signal amplification using a quantitative Nuclease Protection Assay (qNPA). This assay can be configured as either a high-throughput microplate assay or as a handheld detection device for individual point-of-care assays. Recently, we were able to successfully develop the qNPA platform to measure gene expression levels directly from human whole blood samples. The assay can be performed with volumes as small as 30 microL of whole blood, which is compatible with collection from a fingerstick. We analyzed in vitro irradiated blood samples with qNPA. The results revealed statistically significant discrimination between irradiated and non-irradiated samples. These results indicate that the qNPA platform combined with a gene profile based on a small number of genes is a valid test to measure biological radiation exposure. The scalability characteristics of the assay make it appropriate for population triage. This biodosimetry platform could also be used for personalized monitoring of radiotherapy treatments received by patients.

Optimization of a Microfluidic Mixing Process for Gene Expression-Based Bio-dosimetry.

In recent decades advances in radiation imaging and radiation therapy have led to a dramatic increase in the number of people exposed to radiation. Consequently, there is a clear need for personalized biodosimetry diagnostics in order to monitor the dose of radiation received and adapt it to each patient depending on their sensitivity to radiation exposure (Hall E.J. and Brenner D. J., 2008). Similarly, after a large-scale radiological event such as a dirty bomb attack, there will be a major need to assess, within a few days the radiation doses received by tens of thousands of individuals. Current high throughput devices can handle only a few hundred individuals per day. Hence there is a great need for a very fast self-contained non-invasive biodosimetric device based on a rapid blood test.This paper presents a case study where regression methods and designed experiments are used to arrive at the optimal settings for various factors that impact the kinetics in a biodosimetric device. We use ridge regression to initially identify a set of potentially important variables in the mixing process which is one of the critical sub systems of the device. This was followed by a series of designed experiments to arrive at the optimal setting of the significant microfluidic cartridge and piezoelectric disk (PZT) (D. Sadler, F. Zenhausern, U.S. Patent 6,986,601; Lee, S. Y., Ko, B., Yang, W., 2005) related factors. This statistical approach has been utilized to study the microfluidic mixing to mix water and dye mixtures of 70 µl volume. The outcome of the statistical design, experimentation and analysis was then exploited for optimizing the design, fabrication and assembly of the microfluidic devices. As a result of the experiments that were performed, the system was fine tuned and the mixing time was reduced from 5.5 minutes to 2 minutes.

Accumulation of polyadenylated mRNA, Pab1p, eIF4E, and eIF4G with P-bodies in Saccharomyces cerevisiae.

Recent experiments have shown that mRNAs can move between polysomes and P-bodies, which are aggregates of nontranslating mRNAs associated with translational repressors and the mRNA decapping machinery. The transitions between polysomes and P-bodies and how the poly(A) tail and the associated poly(A) binding protein 1 (Pab1p) may affect this process are unknown. Herein, we provide evidence that poly(A)(+) mRNAs can enter P-bodies in yeast. First, we show that both poly(A)(-) and poly(A)(+) mRNA become translationally repressed during glucose deprivation, where mRNAs accumulate in P-bodies. In addition, both poly(A)(+) transcripts and/or Pab1p can be detected in P-bodies during glucose deprivation and in stationary phase. Cells lacking Pab1p have enlarged P-bodies, suggesting that Pab1p plays a direct or indirect role in shifting the equilibrium of mRNAs away from P-bodies and into translation, perhaps by aiding in the assembly of a type of mRNP within P-bodies that is poised to reenter translation. Consistent with this latter possibility, we observed the translation initiation factors (eIF)4E and eIF4G in P-bodies at a low level during glucose deprivation and at high levels in stationary phase. Moreover, Pab1p exited P-bodies much faster than Dcp2p when stationary phase cells were given fresh nutrients. Together, these results suggest that polyadenylated mRNAs can enter P-bodies, and an mRNP complex including poly(A)(+) mRNA, Pab1p, eIF4E, and eIF4G2 may represent a transition state during the process of mRNAs exchanging between P-bodies and translation.