Plasma proteomic analysis may identify new markers for radiation-induced lung toxicity in patients with non-small-cell lung cancer

Analyzing the Effect of Vitronectin on Cell Growth and Mesenchymal-Epithelial Transition of Pulmonary Fibroblast Cells

PURPOSE

Vitronectin (VTN), a multifunctional glycoprotein, is involved in various biological and pathological processes. The purpose of this study was to explore the effect of VTN on mesenchymal-epithelial transition (MET) of pulmonary fibroblast cells.

METHODS

Lentivirus encoding for VTN-specific shRNA was constructed and infected into the cultured fibroblast WI-38 cells. Real-time PCR and Western blot were applied to examine the expression of VTN in WI-38 cells. MTT assay was used to assess cell proliferation. Western blot was conducted to examine the expression of MET-related and apoptosis-related proteins.

RESULTS

The knockdown of VTN significantly inhibited the growth of WI-38 cells compared to the control group. Meanwhile, knockdown of VTN remarkably increased the expression of Bax and Caspase 3 compared with the control group. Furthermore, knockdown of VTN significantly promoted the expression of E-cadherin in comparison to control group.

CONCLUSIONS

Knockdown of VTN promoted the expression of apoptosis-related factors, meanwhile, facilitated the MET process of fibroblast cells by regulating the expression of relevant factors. In sum, VTN performed a potential regulator in cell growth and MET of pulmonary fibroblast cells, which can be considered as a potential target for diagnose and therapy of relevant diseases.

The Plasma Levels and Polymorphisms of Vitronectin Predict Radiation Pneumonitis in Patients With Lung Cancer Receiving Thoracic Radiation Therapy

PURPOSE

Our previous findings have identified vitronectin (VTN) as a potential biomarker for radiation pneumonitis (RP) through proteomics and molecular mechanism studies. In a recent study, we further explored associations of plasma level and single nucleotide polymorphisms of VTN with the risk of RP in patients with lung cancer receiving radiation therapy.

METHODS AND MATERIALS

A total of 165 patients with lung cancer were prospectively enrolled with detection of VTN concentration before radiation therapy. VTN reference single nucleotide polymorphisms, rs704 and rs2227721, were genotyped by Taqman probe method. Cox proportional hazard models were performed to identify clinical variables and genotypes associated with the risk of RP on univariate and multivariate analyses, and t tests and analysis of variance were conducted to evaluate the expression level of VTN.

RESULTS

The baseline secretion level of VTN in patients with grade ≥3 RP was significantly higher than that in grade <3 RP patients (P < .0001), and elevated levels were observed in patients having the AA genotype compared with GA/GG genotypes of rs704. The VTN rs704 GA/GG and rs2227721 AA/AC genotypes had a significantly lower risk of RP (hazard ratio [HR], 0.448, P = .005; HR, 0.419, P = .008, respectively). In addition, combining cut-off values of mean lung dose (MLD) and VTN plasma level, grade ≥3 RP risk groupings were as follows: high risk: MLD ≥12 Gy and VTN level ≥132 μg/mL (RP rate, 10 of 16 patients, 62.5%); intermediate risk: MLD ≥12 Gy and VTN level <132 μg/mL or MLD <12 Gy and VTN level ≥132 μg/mL (8 of 70 patients, 11.4%); and low risk: MLD <12 Gy and VTN level <132 μg/mL (1 of 79 patients, 1.3%) (P < .0001).

CONCLUSIONS

Among patients receiving radiation therapy, relatively high plasma levels of VTN before radiation therapy were associated with the higher incidence of RP, and VTN rs704 and rs2227721 each had a significant effect on predicting RP risk. Combining VTN concentration with MLD appeared to facilitate stratification of patients with lung cancer who received radiation therapy into low-, intermediate-, and high-risk RP groups. This study indicated that VTN may serve as a blood biomarker for susceptibility to RP in patients with lung cancer.

The Possibility of Using Genotoxicity, Oxidative Stress and Inflammation Blood Biomarkers to Predict the Occurrence of Late Cutaneous Side Effects after Radiotherapy

Despite the progresses performed in the field of radiotherapy, toxicity to the healthy tissues remains a major limiting factor. The aim of this work was to highlight blood biomarkers whose variations could predict the occurrence of late cutaneous side effects. Two groups of nine patients treated for Merkel Cell Carcinoma (MCC) were established according to the grade of late skin toxicity after adjuvant irradiation for MCC: grade 0, 1 or 2 and grade 3 or 4 of RTOG (Radiation Therapy Oncology Group)/EORTC (European Organization for Research and Treatment of Cancer). To try to discriminate these 2 groups, biomarkers of interest were measured on the different blood compartments after ex vivo irradiation. In lymphocytes, cell cycle, apoptosis and genotoxicity were studied. Oxidative stress was evaluated by the determination of the erythrocyte antioxidant capacity (superoxide dismutase, catalase, glutathione peroxidase, reduced and oxidized glutathione) as well as degradation products (protein carbonylation, lipid peroxidation). Inflammation was assessed in the plasma by the measurement of 14 cytokines. The most radiosensitive patients presented a decrease in apoptosis, micronucleus frequency, antioxidant enzyme activities, glutathione and carbonyls; and an increase in TNF-a (Tumor Necrosis Factor a), IL-8 (Interleukin 8) and TGF-β1 (Transforming Growth Factor β1) levels. These findings have to be confirmed on a higher number of patients and before radiotherapy and could allow to predict the occurrence of late skin side effects after radiotherapy.

Mass Spectrometry-Based Analysis of Time-Resolved Proteome Quantification

The aspect of time is essential in biological processes and thus it is important to be able to monitor signaling molecules through time. Proteins are key players in cellular signaling and they respond to many stimuli and change their expression in many time-dependent processes. Mass spectrometry (MS) is an important tool for studying proteins, including their posttranslational modifications and their interaction partners-both in qualitative and quantitative ways. In order to distinguish the different trends over time, proteins, modification sites, and interacting proteins must be compared between different time points, and therefore relative quantification is preferred. In this review, the progress and challenges for MS-based analysis of time-resolved proteome dynamics are discussed. Further, aspects on model systems, technologies, sampling frequencies, and presentation of the dynamic data are discussed.

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.

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1351-8) contains supplementary material, which is available to authorized users.

Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer

PURPOSE

Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypothesized that inflammatory cytokines or the dynamic changes during radiotherapy can improve predictive accuracy for RP2.

EXPERIMENTAL DESIGN

Levels of 30 inflammatory cytokines and clinical information in patients with stages I-III NSCLC treated with radiotherapy were from our prospective studies. Statistical analysis was used to select predictive cytokine candidates and clinical covariates for adjustment. Machine learning algorithm was used to develop the generalized linear model for predicting risk RP2.

RESULTS

A total of 131 patients were eligible and 17 (13.0%) developed RP2. IL8 and CCL2 had significantly (Bonferroni) lower expression levels in patients with RP2 than without RP2. But none of the changes in cytokine levels during radiotherapy was significantly associated with RP2. The final predictive GLM model for RP2 was established, including IL8 and CCL2 at baseline level and two clinical variables. Nomogram was constructed based on the GLM model. The model's predicting ability was validated in the completely independent test set (AUC = 0.863, accuracy = 80.0%, sensitivity = 100%, specificity = 76.5%).

CONCLUSIONS

By machine learning, this study has developed and validated a comprehensive model integrating inflammatory cytokines with clinical variables to predict RP2 before radiotherapy that provides an opportunity to guide clinicians.

Ensuring sample quality for blood biomarker studies in clinical trials: a multicenter international study for plasma and serum sample preparation

Background

Sample quality is critical for biomarker detection in oncology, and platelet degradation and contamination in plasma have a remarkable impact on the ability to accurately quantify many blood-based biomarkers. Platelet factor 4 (PF4) can be used as an indicator to monitor sample quality. This multicenter study aimed to determine the impact of critical components of the blood sample handling process on platelet degradation/contamination and to establish an optimal method for collecting platelet-poor plasma samples.

Methods

At each of six participating centers, blood samples were drawn from 12-13 healthy volunteers. Serum and plasma samples were prepared from whole blood samples using nine different methods that have been commonly used in ongoing multicenter trials. PF4 levels in the prepared samples were measured by enzyme-linked immunosorbent assay (ELISA). Paired t-tests were used for statistical analysis.

Results

Blood samples were collected from 74 subjects enrolled in six centers. PF4 levels were significantly higher in serum samples than in plasma samples (P<0.001), in plasma samples from blood that sat at room temperature for 5 minutes (P=0.021), in plasma samples prepared at an insufficient centrifugal force (P<0.001), and in plasma samples prepared from blood that sat for longer than 4 hours on ice (P=0.001). For each method, the PF4 levels did not differ significantly among the centers or between Chinese and American subjects. The methods that resulted in normal levels of PF4 involved keeping blood samples on ice for 30 minutes to <4 hours and centrifugation at 2,500-3,000 ×g for 30 min.

Conclusions

This multicenter study evaluated multiple blood sample handling conditions for minimizing platelet degradation during plasma serum preparation and determined an optimal method for preparing platelet-poor plasma. The findings of this study can be applied in future blood biomarker studies.

Blood-based biomarkers for precision medicine in lung cancer: precision radiation therapy

Both tumors and patients are complex and models that determine survival and toxicity of radiotherapy or any other treatment ideally must take into account this variability as well as its dynamic state. The genetic features of the tumor and the host, and increasingly also the epi-genetic and proteomic characteristics, are being unraveled. Multiple techniques, including histological examination, blood sampling, measurement of circulating tumor cells (CTCs), and functional and molecular imaging, can be used for this purpose. However, the effects of radiation on the tumor and on organs at risk (OARs) are also influenced by the applied dose and volume of irradiated tissues. Combining all these biological, clinical, imaging, and dosimetric parameters in a validated prognostic or predictive model poses a major challenge. Here we aimed to provide an objective review of the potential of blood markers to guide high precision radiation therapy. A combined biological-mathematical approach opens new doors beyond prognostication of patients, as it allows truly precise oncological treatment. Indeed, the core for individualized and precision medicine is not only selection of patients, but even more the optimization of the therapeutic window on an individual basis. A holistic model will allow for determination of an individual dose-response relationship for each organ at risk for each tumor in each individual patient for the complete oncological treatment package. This includes, but is not limited to, radiotherapy alone. Individualized dose-response curves will allow for consideration of different doses of radiation and combinations with other drugs to plan for both optimal toxicity and complete response. Insights into the interactions between a multitude of parameters will lead to the discovery of new pathways and networks that will fuel new biological research on target discovery.

Identification of extracellular matrix protein 1 as a potential plasma biomarker of ESCC by proteomic analysis using iTRAQ and 2D-LC-MS/MS

PURPOSE

This study was aimed to conduct a proteomics profiling analysis on plasma obtained from ESCC patients with the goal of identifying appropriate plasma protein biomarkers in the progression of ESCC.

EXPERIMENTAL DESIGN

Plasma from 28 ESCC patients and 28 healthy controls (HC) were analyzed by iTRAQ combined with 2D-LC-MS/MS. ProteinPilot software was used to identify the differentially expressed plasma proteins in ESCC compared to HC. Western blot was performed to verify the expression of selected proteins in 37 independent ESCC patients and 37 HC. Transwell and MTT assays were used to detect the biological function of ECM1 protein in vitro.

RESULTS

Nineteen (four upregulated and fifteen downregulated) proteins were identified as differentially expressed between ESCC and HC (p <0.05). Biological functions of these proteins are involved in cell adhesion, cell apoptosis and metabolic processes, visual perception and immune response. Of these, extracellular matrix 1 (ECM1) and lumican (LUM) were selected further confirmation by Western blot (p <0.05), which were consistent with the iTRAQ results. Furthermore, the migration ability of EC9706 cell line after overexpressing ECM1 was increased significantly (p <0.05). The proliferation ability of HUVEC cell was enhanced when treated with the culture supernatants of EC9706 overexpressed ECM1(p <0.05).

CONCLUSION AND CLINICAL RELEVANCE

This proteome analysis indicate that ECM1 is a potential novel plasma protein biomarker for the detection of primary ESCC and evaluation of neoplasms progression.

Systemic effects of ionizing radiation at the proteome and metabolome levels in the blood of cancer patients treated with radiotherapy: the influence of inflammation and radiation toxicity

PURPOSE

Blood is the most common replacement tissue used to study systemic responses of organisms to different types of pathological conditions and environmental insults. Local irradiation during cancer radiotherapy induces whole body responses that can be observed at the blood proteome and metabolome levels. Hence, comparative blood proteomics and metabolomics are emerging approaches used in the discovery of radiation biomarkers. These techniques enable the simultaneous measurement of hundreds of molecules and the identification of sets of components that can discriminate different physiological states of the human body. Radiation-induced changes are affected by the dose and volume of irradiated tissues; hence, the molecular composition of blood is a hypothetical source of biomarkers for dose assessment and the prediction and monitoring of systemic responses to radiation. This review aims to provide a comprehensive overview on the available evidence regarding molecular responses to ionizing radiation detected at the level of the human blood proteome and metabolome. It focuses on patients exposed to radiation during cancer radiotherapy and emphasizes effects related to radiation-induced toxicity and inflammation.

CONCLUSIONS

Systemic responses to radiation detected at the blood proteome and metabolome levels are primarily related to the intensity of radiation-induced toxicity, including inflammatory responses. Thus, several inflammation-associated molecules can be used to monitor or even predict radiation-induced toxicity. However, these abundant molecular features have a rather limited applicability as universal biomarkers for dose assessment, reflecting the individual predisposition of the immune system and tissue-specific mechanisms involved in radiation-induced damage.

Transition from identity to bioactivity-guided proteomics for biomarker discovery with focus on the PF2D platform

Proteomic strategies provide a valuable tool kit to identify proteins involved in diseases. With recent progress in MS technology, high throughput proteomics has accelerated protein identification for potential biomarkers. Numerous biomarker candidates have been identified in several diseases, and many are common among pathologies. An overall strategy that could complement and strengthen the search for biomarkers is combining protein identity with biological outcomes. This review describes an emerging framework of bridging bioactivity to protein identity, exploring the possibility that some biomarkers will have a mechanistic role in the disease process. A review of pulmonary, cardiovascular, and CNS biomarkers will be discussed to demonstrate the utility of combining bioactivity with identification as a means to not only find meaningful biomarkers, but also to uncover functional mediators of disease.

[Radiomics: Definition and clinical development]

The ultimate goal in radiation oncology is to offer a personalized treatment to all patients indicated for radiotherapy. Radiomics is a tool that reinforces a deep analysis of tumors at the molecular aspect taking into account intrinsic susceptibility in a long-term follow-up. Radiomics allow qualitative and quantitative performance analyses with high throughput extraction of numeric radiologic data to obtain predictive or prognostic information from patients treated for cancer. A second approach is to define biological or constitutional that could change the practice. This technique included normal tissue individual susceptibility but also potential response of tumors under ionizing radiation treatment. These "omics" are biological and technical techniques leading to simultaneous novel identification and exploration a set of genes, lipids, proteins.

Partial-Body Irradiation in Patients with Prostate Cancer Treated with IMRT Has Little Effect on the Composition of Serum Proteome

Partial body irradiation during cancer radiotherapy (RT) induces a response of irradiated tissues that could be observed at the level of serum proteome. Here we aimed to characterize the response to RT in group of patients treated because of prostate cancer. Five consecutive blood samples were collected before, during, and after the end of RT in a group of 126 patients who received definitive treatment with a maximum dose of 76 Gy. Serum peptidome, which was profiled in the 2000–16,000 Da range using MALDI-MS. Serum proteins were identified and quantified using the shotgun LC-MS/MS approach. The majority of changes in serum peptidome were detected between pre-treatment samples and samples collected after 3–4 weeks of RT (~25% of registered peptides changed their abundances significantly), yet the intensity of observed changes was not correlated significantly with the degree of acute radiation toxicity or the volume of irradiated tissues. Furthermore, there were a few serum proteins identified, the abundances of which were different in pre-RT and post-RT samples, including immunity and inflammation-related factors. Observed effects were apparently weaker than in comparable groups of head and neck cancer patients in spite of similar radiation doses and volumes of irradiated tissues in both groups. We concluded that changes observed at the level of serum proteome were low for this cohort of prostate cancer patients, although the specific components involved are associated with immunity and inflammation, and reflect the characteristic acute response of the human body to radiation.

Nondosimetric risk factors for radiation-induced lung toxicity

The decision to administer a radical course of radiotherapy (RT) is largely influenced by the dose-volume metrics of the treatment plan, but what are the patient-related and other factors that may independently increase the risk of radiation lung toxicity? Poor pulmonary function has been regarded as a risk factor and a relative contraindication for patients undergoing radical RT, but recent evidence suggests that patients with poor spirometry results may tolerate conventional or high-dose RT as well as, if not better than, patients with normal function. However, caution may need to be exercised in patients with underlying interstitial pulmonary fibrosis. Furthermore, there is emerging evidence of molecular markers of increased risk of toxicity. This review discusses patient-related risk factors other than dosimetry for radiation lung toxicity.

Profiling of low molecular weight proteins in plasma from locally irradiated individuals

In studies reported in the 1960s and since, blood plasma from radiation-exposed individuals has been shown to induce chromosome damage when transferred into lymphocyte cultures of non-irradiated persons. This effect has been described to occur via clastogenic factors, whose nature is still mostly unknown. We have previously examined clastogenic factors from irradiated individuals by looking at plasma-induced DNA damage in reporter cells. Plasma was tested from ca. 30 locally exposed clinical patients receiving fractionated radiation treatment, as well as from three radiological accident victims exposed in 1994, albeit sampled 14 years post-accident. In the current work, proteome changes in the plasma from all subjects were examined with 2D gel electrophoresis-based proteomics techniques, in order to evaluate the level of protein expression with respect to the findings of a clastogenic factor effect. No differences were observed in protein expression due to local radiation exposure (pre- vs post-exposure). In contrast, plasma from the radiation accident victims showed alterations in the expression of 18 protein spots (in comparison with plasma from the control group). Among these, proteins such as haptoglobin, serotransferrin/transferrin, fibrinogen and ubiquitin-60S ribosomal protein L40 were observed, none of them likely to be clastogenic factors. In conclusion, the proteomics techniques applied were unable to identify changes in the proteome of the locally irradiated patients, whereas such differences were observed for the accident victims. However, association with the clastogenic effect or any specific clastogenic factor remains unresolved and thus further studies with more sensitive techniques are warranted.

[Intrinsic radiosensitivity: predictive assays that will change daily practice]

The impact of curative radiotherapy depends mainly on the total dose delivered homogenously in the targeted volume. Nevertheless, the dose delivered to the surrounding healthy tissues may reduce the therapeutic ratio of many radiation treatments. In a same population treated in one center with the same technique, it appears that individual radiosensitivity clearly exists, namely in terms of late side effects that are in principle non-reversible. This review details the different radiobiological approaches that have been developed to better understand the mechanisms of radiation-induced late effects. We also present the possibilities of clinical use of predictive assays in the close future.

Nested case control study of proteomic biomarkers for interstitial lung disease in Japanese patients with non-small-cell lung cancer treated with erlotinib: a multicenter phase IV study (JO21661)

BACKGROUND

Interstitial lung disease (ILD) is a serious adverse drug reaction associated with epidermal growth factor receptor tyrosine-kinase inhibitors (EGFR TKIs). Its risk factors are yet to be fully elucidated. We sought to identify proteomic biomarkers associated with ILD development in erlotinib-treated Japanese patients with non-small-cell lung cancer (NSCLC) to build predictive models.

PATIENTS AND METHODS

We conducted a nested case-control study. The participants were patients with NSCLC enrolled in a phase IV study of erlotinib in whom ILD developed within 120 days after erlotinib administration. The controls were randomly selected patients without ILD from the overall study cohort who were also treated with erlotinib. Serum samples were obtained before the first administration of erlotinib and were assayed by liquid chromatography-mass spectroscopy/mass spectroscopy (LC-MS/MS). Logistic regression analysis was performed to identify the peptide and proteins associated with ILD.

RESULTS

A total of 645 patients were enrolled in the cohort; 15 case patients and 64 controls were analyzed. When multiplicity was taken into account, we were unable to statistically verify any genuine association between individual markers and ILD. Investigation of the predictive power based on leave-one-out cross-validation (LOOCV) showed that the area under the receiver operating characteristic curve was 0.73 at a maximum. Additional analysis suggested that 3 proteins (C3, C4A/C4B, and APOA1) have a stronger association with ILD than do the other proteins tested.

CONCLUSION

We were unable to demonstrate predictive serum protein markers for ILD development. However, C3, C4A/C4B, and APOA1 are worthy of further investigation.

Serum and plasma proteomics and its possible use as detector and predictor of radiation diseases

All tissues can be damaged by ionizing radiation. Early biomarkers of radiation injury are critical for triage, treatment and follow-up of large numbers of people exposed to ionizing radiation after terrorist attacks or radiological accident, and for prediction of normal tissue toxicity before, during and after a treatment by radiotherapy. The comparative proteomic approach is a promising and powerful tool for the discovery of new radiation biomarkers. In association with multivariate statistics, proteomics enables measurement of the level of hundreds or thousands of proteins at the same time and identifies set of proteins that can discriminate between different groups of individuals. Human serum and plasma are the preferred samples for the study of normal and disease-associated proteins. Extreme complexity, extensive dynamic range, genetic and physiological variations, protein modifications and incompleteness of sampling by two-dimensional electrophoresis and mass spectrometry represent key challenges to reproducible, high-resolution, and high-throughput analyses of serum and plasma proteomes. The future of radiation research will possibly lie in molecular networks that link genome, transcriptome, proteome and metabolome variations to radiation pathophysiology and serve as sensors of radiation disease. This chapter reviews recent advances in proteome analysis of serum and plasma as well as its applications to radiation biology and radiation biomarker discovery for both radiation exposure and radiation tissue toxicity.

Genetic deficiency in complement component 4b does not alter radiation-induced lung disease in mice

Previous investigations have shown altered levels of complement components to be associated with radiation-induced lung disease. In this study we aimed to determine whether a deficiency in complement component 4b alters the lung response to irradiation of C57BL/6 mice. The pulmonary phenotype of C57BL/6 C4b(-/-) mice and their wild-type littermates was assessed following an 18 Gy single dose to the thoracic cavity. The assessed end points included, survival time postirradiation, bronchoalveolar lavage cell differential, hydroxyproline measures and histological evidence of alveolitis and fibrosis. The lung phenotype of C4b-deficient mice did not differ from that of wild-type mice in terms of survival time postirradiation, tissue hydroxyproline levels or by histological evidence of alveolitis or fibrosis. No differences in bronchoalveolar cell differential counts were evident among the irradiated mice grouped by C4b genotype. We concluded that a deficiency in C4b does not alter radiation-induced lung disease in the C57BL/6 mouse model.

[Radiosensitivity assays of normal tissues]

Radiotherapy allows locoregional control with systemic impact in some indications. Technologic advances decrease the dose received by normal tissues leading to a low crude number of late side effects near to 5%. Intrinsic radiosensitivity are still of interest in this context of high level of technology and optimized treatments. Assays of radiosensitivity are detailed in this article arguing the negative results but also the perspectives.

Baseline plasma proteomic analysis to identify biomarkers that predict radiation-induced lung toxicity in patients receiving radiation for non-small cell lung cancer

PURPOSE

To identify new plasma proteomic markers before radiotherapy start to predict later grade ≥2 radiation-induced lung toxicity (RILT2).

METHODS

Fifty-seven patients with non-small cell lung cancer received radiotherapy (RT) were eligible. Forty-eight patients with minimum follow-up of 1 year, nine with RILT2 with tumor stage matched to 39 without RILT2, were enrolled for this analysis. Platelet-poor plasma was obtained within 2 weeks before radiotherapy. The plasma proteomes were compared using a multiplexed quantitative proteomics approach involving ExacTag labeling, reverse-phase high-performance liquid chromatography, and nano liquid chromatography electrospray ionization tandem mass spectrometry. Z scores and Bonferroni-adjusted p values for the two-sample mean comparison were used to identify the differential protein expression between patients with and without RILT2.

RESULTS

More than 200 proteins were identified and quantified. After excluding proteins that were not detected in at least 40% of the 48 patient samples, C4b-binding protein alpha chain and vitronectin had significantly higher (p < 0.001 and p = 0.02) expression levels in patients with RILT2 compared with patients without RILT2. These two proteins were validated by Western blot. Ingenuity pathway analysis revealed that they both play important roles in the inflammatory response and are associated with the known pathways of radiation-induced lung damage.

CONCLUSIONS

This proteomic approach demonstrates new plasma protein biomarkers before treatment for future studies on RILT2 prediction.

[Interest of blood markers in predicting radiation-induced toxicity]

The oncologic outcome and the total dose are highly correlated with the treatment by ionizing radiation. The dose increase (total or per fraction) may provoke late-side effects that are potentially irreversible. The radiation-induced CD8 lymphocyte apoptotic value and the molecular modifications within the lymphocyte are capable of predicting the level of risk of developing late-side effects after curative intent radiotherapy. In this review, we present the different blood assays in this setting and discuss the current possibilities of researches, namely those involving the proteomic process.

Global expression study in colorectal cancer on proteins with alkaline isoelectric point by two-dimensional difference gel electrophoresis

Colorectal cancer is one of the leading causes of cancer death worldwide. To identify candidates for biomarkers and therapeutic targets, we investigated the proteome of colorectal cancer tissues. Using 2D-DIGE in combination with our original large format electrophoresis apparatus, we compared surgically resected normal and tumor tissues from 53 patients with colorectal cancer. We focused on proteins with an alkaline pI using IPG gels for the alkaline range. We observed 1687 protein spots, and found 100 spots with statistical (p<0.01) and significant (>2-fold) differences between the normal and the tumor tissue groups. Among these 100 protein spots, five showed a different intensity between tumor tissues from the stage-II and the stage-III patients. MS experiments revealed that these 100 protein spots corresponded to 58 unique proteins. These included six proteins which had not been previously reported to be associated with colorectal cancer. Among these proteins, five were not reported in any type of malignancy. IEF/western blotting confirmed the differences in protein expression between the normal and the tumor tissues. These results may provide an insight for biomarker development and drug target discovery in colorectal cancer.