Plasma Lipidomics Profiling to Identify the Biomarkers of Diagnosis and Radiotherapy Response for Advanced Non-Small-Cell Lung Cancer Patients

Background

Advanced lung cancer that contributes to a heavy burden on medical institutions is the leading cause of cancer-related death and is often accompanied by metabolic disorders. In this study, we aimed to explore the biomarkers of diagnosis and radiotherapy response in non-small-cell lung cancer (NSCLC) patients by plasma lipidomics analysis.

Method

Using triple-quadrupole mass spectrometer analysis, our research characterized the plasma lipid metabolomics profile of 25 healthy controls and 31 advanced NSCLC patients in each of three different radiotherapy phases.

Results

The results showed altered lipid elements and concentrations among NSCLC patients with different radiotherapy phases, NSCLC subtypes, and different radiotherapeutic responses. We found that compared to the healthy controls, myelin-associated glycoprotein (MAG), phosphatidylinositol (PI), and phosphatidylserine (PS) were mainly and significantly altered lipid elements (> twofold, and p < 0.05) among NSCLC patients with different radiotherapy phases. Through comparison of lipid elements between bad and good responses of NSCLC patients with radiotherapy, the obviously declined phosphatidylglycerol (PG 18 : 0/14 : 0, 18 : 1/18 : 3, and 18 : 0/20 : 1) or markedly elevated PI (20 : 0/22 : 5 and 18 : 2/22 : 4) and phosphatidic acid (PA 14 : 0/20 : 4, 14 : 0/20 : 3, and 18 : 2/22 : 4) could indicate poor therapeutic response for NSCLC patients. The results of ROC curve analysis suggested that PG (18 : 0/20 : 1 and 18 : 0/14 : 0) could clearly predict the radiotherapeutic response for NSCLC patients, and PS (18 : 0/20 : 0) and cholesterol were the first two lipid components with the most potential for the diagnosis of advanced NSCLC.

Conclusion

Our results indicated that plasma lipidomics profiling might have a vital value to uncover the heterogeneity of lipid metabolism in healthy people and advanced NSCLC patients with different radiotherapy phase, and further to screen out radiotherapeutic response-specific biomarkers.

Alterations of MicroRNA Expression in the Liver, Heart, and Testis of Mice Upon Exposure to Repeated Low-Dose Radiation

MicroRNAs (miRs), which regulate target gene expression at the post-transcriptional level, play a crucial role in inducing biological effects upon high-dose ionizing radiation. Yet, the miR expression profiles in response to repeated low-dose radiation (LDR) in vivo have not been elucidated. This study investigated the response profiles of 11 miRs with functions involved in metabolism, DNA damage and repair, inflammation, and fibrosis in mouse liver, heart, and testis upon repeated LDR exposure for 4 months. The expression profiles were evaluated using stem-loop quantitative reverse transcription polymerase chain reaction immediately and at 2 months after LDR exposure. The expression profiles varied significantly at both time points. At the organ level, the heart was the most affected, followed by the liver and testis, in which significant miR upregulation related to DNA damage response was found. Metabolism-related miRs decreased in the liver and increased in the testis. The current results showed immediate and long-lasting alterations in the miR expression profiles in response to repeated LDR in different organs.

Role of interim 18F-FDG-PET/CT for the early prediction of clinical outcomes of Non-Small Cell Lung Cancer (NSCLC) during radiotherapy or chemo-radiotherapy. A systematic review

BACKGROUND

Non-Small Cell Lung Cancer (NSCLC) is characterized by aggressiveness and includes the majority of thorax malignancies. The possibility of early stratification of patients as responsive and non-responsive to radiotherapy with a non-invasive method is extremely appealing. The distribution of the Fluorodeoxyglucose (¹⁸F-FDG) in tumours, provided by Positron-Emission-Tomography (PET) images, has been proved to be useful to assess the initial staging of the disease, recurrence, and response to chemotherapy and chemo-radiotherapy (CRT).

OBJECTIVES

In the last years, particular efforts have been focused on the possibility of using ad interim ¹⁸F-FDG PET (FDG_int) to evaluate response already in the course of radiotherapy. However, controversial findings have been reported for various malignancies, although several results would support the use of FDG_int for individual therapeutic decisions, at least in some pathologies. The objective of the present review is to assemble comprehensively the literature concerning NSCLC, to evaluate where and whether FDG_int may offer predictive potential.

METHODS

Several searches were completed on Medline and the Embase database, combining different keywords. Original papers published in the English language from 2005 to 2016 with studies involving FDG_int in patients affected by NSCLC and treated with radiation therapy or chemo-radiotherapy only were chosen.

RESULTS

Twenty-one studies out of 970 in Pubmed and 1256 in Embase were selected, reporting on 627 patients.

CONCLUSION

Certainly, the lack of univocal PET parameters was identified as a major drawback, while standardization would be required for best practice. In any case, all these papers denoted FDG_int as promising and a challenging examination for early assessment of outcomes during CRT, sustaining its predictivity in lung cancer.

A radiobiological model of radiotherapy response and its correlation with prognostic imaging variables

Radiobiological models of tumour control probability (TCP) can be personalized using imaging data. We propose an extension to a voxel-level radiobiological TCP model in order to describe patient-specific differences and intra-tumour heterogeneity. In the proposed model, tumour shrinkage is described by means of a novel kinetic Monte Carlo method for inter-voxel cell migration and tumour deformation. The model captures the spatiotemporal evolution of the tumour at the voxel level, and is designed to take imaging data as input. To test the performance of the model, three image-derived variables found to be predictive of outcome in the literature have been identified and calculated using the model's own parameters. Simulating multiple tumours with different initial conditions makes it possible to perform an in silico study of the correlation of these variables with the dose for 50% tumour control ([Formula: see text]) calculated by the model. We find that the three simulated variables correlate with the calculated [Formula: see text]. In addition, we find that different variables have different levels of sensitivity to the spatial distribution of hypoxia within the tumour, as well as to the dynamics of the migration mechanism. Finally, based on our results, we observe that an adequate combination of the variables may potentially result in higher predictive power.

MeDiA: Mean Distance Association and Its Applications in Nonlinear Gene Set Analysis

Probabilistic association discovery aims at identifying the association between random vectors, regardless of number of variables involved or linear/nonlinear functional forms. Recently, applications in high-dimensional data have generated rising interest in probabilistic association discovery. We developed a framework based on functions on the observation graph, named MeDiA (Mean Distance Association). We generalize its property to a group of functions on the observation graph. The group of functions encapsulates major existing methods in association discovery, e.g. mutual information and Brownian Covariance, and can be expanded to more complicated forms. We conducted numerical comparison of the statistical power of related methods under multiple scenarios. We further demonstrated the application of MeDiA as a method of gene set analysis that captures a broader range of responses than traditional gene set analysis methods.

Low dose irradiation profoundly affects transcriptome and microRNAme in rat mammary gland tissues

Ionizing radiation has been successfully used in medical tests and treatment therapies for a variety of medical conditions. However, patients and health-care workers are greatly concerned about overexposure to medical ionizing radiation and possible cancer induction due to frequent mammographies and/or CT scans. Diagnostic imaging involves the use of low doses of ionizing radiation, and its potential carcinogenic role creates a cancer risk concern for exposed individuals. In this study, the effects of X-ray exposure of different doses on the gene expression patterns and the micro-RNA expression patterns in normal breast tissue were investigated in rats. Our results revealed the activation of immune response pathways upon low dose of radiation exposure. These included natural killer mediated cytotoxicity pathways, antigen processing and presentation pathways, chemokine signaling pathways, and T- and B-cell receptor signaling pathways. Both high and low doses of radiation led to miRNA expression alterations. Increased expression of miR-34a may be linked to cell cycle arrest and apoptosis. Up-regulation of miR-34a was correlated with down-regulation of its target E2F3 and up-regulation of p53. This data suggests that ionizing radiation at specific high and low doses leads to cell cycle arrest and a possible initiation of apoptosis.

Modelling non-homogeneous stochastic reaction-diffusion systems: the case study of gemcitabine-treated non-small cell lung cancer growth

Background

Reaction-diffusion based models have been widely used in the literature for modeling the growth of solid tumors. Many of the current models treat both diffusion/consumption of nutrients and cell proliferation. The majority of these models use classical transport/mass conservation equations for describing the distribution of molecular species in tumor spheroids, and the Fick's law for describing the flux of uncharged molecules (i.e oxygen, glucose). Commonly, the equations for the cell movement and proliferation are first order differential equations describing the rate of change of the velocity of the cells with respect to the spatial coordinates as a function of the nutrient's gradient. Several modifications of these equations have been developed in the last decade to explicitly indicate that the tumor includes cells, interstitial fluids and extracellular matrix: these variants provided a model of tumor as a multiphase material with these as the different phases. Most of the current reaction-diffusion tumor models are deterministic and do not model the diffusion as a local state-dependent process in a non-homogeneous medium at the micro- and meso-scale of the intra- and inter-cellular processes, respectively. Furthermore, a stochastic reaction-diffusion model in which diffusive transport of the molecular species of nutrients and chemotherapy drugs as well as the interactions of the tumor cells with these species is a novel approach. The application of this approach to he scase of non-small cell lung cancer treated with gemcitabine is also novel.

Methods

We present a stochastic reaction-diffusion model of non-small cell lung cancer growth in the specification formalism of the tool Redi, we recently developed for simulating reaction-diffusion systems. We also describe how a spatial gradient of nutrients and oncological drugs affects the tumor progression. Our model is based on a generalization of the Fick's first diffusion law that allows to model diffusive transport in non-homogeneous media. The diffusion coefficient is explicitly expressed as a function depending on the local conditions of the medium, such as the concentration of molecular species, the viscosity of the medium and the temperature. We incorporated this generalized law in a reaction-based stochastic simulation framework implementing an efficient version of Gillespie algorithm for modeling the dynamics of the interactions between tumor cell, nutrients and gemcitabine in a spatial domain expressing a nutrient and drug concentration gradient.

Results

Using the mathematical framework of model we simulated the spatial growth of a 2D spheroidal tumor model in response to a treatment with gemcitabine and a dynamic gradient of oxygen and glucose. The parameters of the model have been taken from recet literature and also inferred from real tumor shrinkage curves measured in patients suffering from non-small cell lung cancer. The simulations qualitatively reproduce the time evolution of the morphologies of these tumors as well as the morphological patterns follow the growth curves observed in patients.

Conclusions

s This model is able to reproduce the observed increment/decrement of tumor size in response to the pharmacological treatment with gemcitabine. The formal specification of the model in Redi can be easily extended in an incremental way to include other relevant biophysical processes, such as local extracellular matrix remodelling, active cell migration and traction, and reshaping of host tissue vasculature, in order to be even more relevant to support the experimental investigation of cancer.

¹⁸F-FDG PET-CT during chemo-radiotherapy in patients with non-small cell lung cancer: the early metabolic response correlates with the delivered radiation dose

Background

To evaluate the metabolic changes on ¹⁸ F-fluoro-2-deoxyglucose positron emission tomography integrated with computed tomography (¹⁸ F-FDG PET-CT) performed before, during and after concurrent chemo-radiotherapy in patients with locally advanced non-small cell lung cancer (NSCLC); to correlate the metabolic response with the delivered radiation dose and with the clinical outcome.

Methods

Twenty-five NSCLC patients candidates for concurrent chemo-radiotherapy underwent ¹⁸ F-FDG PET-CT before treatment (pre-RT PET-CT), during the third week (during-RT PET-CT) of chemo-radiotherapy, and 4 weeks from the end of chemo-radiotherapy (post-RT PET-CT). The parameters evaluated were: the maximum standardized uptake value (SUVmax) of the primary tumor, the SUVmax of the lymph nodes, and the Metabolic Tumor Volume (MTV).

Results

SUVmax of the tumor and MTV significantly (p=0.0001, p=0.002, respectively) decreased earlier during the third week of chemo-radiotherapy, with a further reduction 4 weeks from the end of treatment (p<0.0000, p<0.0002, respectively). SUVmax of lymph nodes showed a trend towards a reduction during chemo-radiotherapy (p=0.06) and decreased significantly (p=0.0006) at the end of treatment. There was a significant correlation (r=0.53, p=0.001) between SUVmax of the tumor measured at during-RT PET-CT and the total dose of radiotherapy reached at the moment of the scan. Disease progression free survival was significantly (p=0.01) longer in patients with complete metabolic response measured at post-RT PET-CT.

Conclusions

In patients with locally advanced NSCLC, ¹⁸ F-FDG PET-CT performed during and after treatment allows early metabolic modifications to be detected, and for this SUVmax is the more sensitive parameter. Further studies are needed to investigate the correlation between the metabolic modifications during therapy and the clinical outcome in order to optimize the therapeutic strategy. Since the metabolic activity during chemo-radiotherapy correlates with the cumulative dose of fractionated radiotherapy delivered at the moment of the scan, special attention should be paid to methodological aspects, such as the radiation dose reached at the time of PET.

Cigarette smoke induces MUC5AC protein expression through the activation of Sp1

Cigarette smoke (CS) exposure is associated with increased mucus production and chronic obstructive pulmonary disease (COPD). MUC5AC is the major inducible mucus gene in the airway. The purpose of this investigation was to elucidate the mechanisms of CS-induced activation of MUC5AC gene transcription. We observed that the region -3724/-3224 of the MUC5AC promoter is critical for CS-induced gene transcriptional activity and that this region contains two Sp1 binding sites. Using a lung-relevant model, we observed that CS increased nuclear Sp1 protein expression. Consequently, CS exposure resulted in enhanced Sp1-DNA binding activity and Sp1 trans-activation. Co-transfection of the MUC5AC-luc reporter with Sp1 expression plasmids resulted in significantly increased MUC5AC-luc activity, whereas co-treatment with mithramycin A, a Sp1 inhibitor, abolished CS-induced MUC5AC promoter activity. Using mobility shift assay and chromatin immunoprecipitation, we demonstrated that two Sp1 binding sites in the MUC5AC promoter are functional and responsive to CS exposure. A mutation of either Sp1 binding site in the MUC5AC promoter significantly decreased CS-induced promoter activity. Together, these data indicate that CS induces MUC5AC gene transcription predominantly through increased Sp1 nuclear protein levels and increased Sp1 binding to its promoter region.

Early FDG PET at 10 or 20 Gy under chemoradiotherapy is prognostic for locoregional control and overall survival in patients with head and neck cancer

PURPOSE

Our study aimed to explore the optimal timing as well as the most appropriate prognostic parameter of (18)F-fluorodeoxyglucose positron emission tomography (FDG PET) during chemoradiotherapy (CRT) for an early prediction of outcome for patients with head and neck squamous cell carcinoma (HNSCC).

METHODS

Serial PET data (before and three times during CRT) of 37 patients with advanced stage HNSCC, receiving combined CRT between 2005 and 2009, were evaluated. The maximum standardized uptake value (SUV(max)), the average SUV (SUV(mean)) and the gross tumour volume determined by FDG PET (GTV PET), based on a source to background algorithm, were analysed. Stratified actuarial analysis was performed for overall survival (OS), disease-free survival (DFS) and locoregional control (LRC). The median follow-up time was 26 months (range 8-50).

RESULTS

For all patients, OS was 51%, DFS 44% and LRC 55% after 2 years. The 2-year OS (88%) and 2-year LRC (88%) were higher for patients whose SUV(max) of the primary tumour decreased 50% or more from the beginning (0 Gy) to week 1 or 2 (10 or 20 Gy) of CRT (ΔSUV(max10/20) ≥ 50%) than for patients with ΔSUV(max20) < 50% (2-year OS = 38%; p = 0.02; 2-year LRC 40%; p = 0.06). A pretreatment GTV PET below the median of 10.2 ml predicted a better 2-year OS (34% for GTV PET ≥ 10.2 ml vs 83% for GTV PET < 10.2 ml; p = 0.02).

CONCLUSION

The decrease of SUV(max) from before (0 Gy) to week 1 or 2 (10 or 20 Gy) of CRT is a potential prognostic marker for patients with HNSCC. Because GTV PET depends on the applied method of analysis, we suggest the use of SUV(max), especially ΔSUV(max10/20), for an early estimation of therapy outcome. Confirmatory studies are warranted.