Longitudinal Brain Changes Associated with Prophylactic Cranial Irradiation in Lung Cancer

Simó, Marta; Vaquero, Lucía; Ripollés, Pablo; Gurtubay-Antolin, Ane; Jové, Josep; Navarro, Arturo; Cardenal, Felipe; Bruna, Jordi; Rodrı́guez-Fornells, Antoni

doi:10.1016/j.jtho.2015.12.110

Cited by 48 publications

(47 citation statements)

References 49 publications

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“…Lung cancer is the most common type of malignant tumor and was the leading cause of cancer-associated death in the USA in 2019 (1). Lung cancer can be categorized into two main histological subtypes, non-small-cell lung cancer (NSCLC) and small-cell lung cancer, accounting for ~85% and ~15% of cases, respectively (2,3). Lung adenocarcinoma (LUAD) is one of the major subtypes of NSCLC with a low 5-year survival rate of ~20% in the USA (4,5).…”

Section: Introductionmentioning

confidence: 99%

Identification of a long non‑coding RNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

Zhang

2020

Oncol Lett

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Long non-coding RNAs (lncRNAs) have a number of functions in various cellular processes and are potential prognostic factors for lung adenocarcinoma (LUAD). A gene risk model could provide novel evidence to improve the prediction of overall outcomes and provide more potential biomarkers. The present study aimed improve a previously published method of gene signature construction to make it more robust and accurate. The lncRNA expression profiles from 594 patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database and samples were divided into high-and low-risk groups based on median risk scores calculated using a prognosis-related risk score formula. Univariate Cox regression, least absolute shrinkage and selection operator algorithm and multivariate Cox regression were performed to construct a gene signature based on the differentially expressed lncRNAs in patients with LUAD. The robustness and accuracy of the present model was assessed using area under the calculated curves (AUC) and Kaplan-Meier (K-M) survival analysis of the high-and low-risk cohorts. Potential biomarkers associated with survival status were then identified using K-M survival analysis and potential biomarker functions were predicted using enrichment analysis of co-expressed mRNAs. The gene signature constructed contained 44 lncRNAs. The AUCs for 3-and 5-year survival with the model were 0.836 and 0.818, respectively, of a time-dependent receiver operator characteristic curve. Moreover, lncRNAs AC124804.1 and MIR34AHG were identified using K-M survival analysis and the potential function of these two lncRNAs was predicted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment. The present lncRNA model provides novel insight which may improve prediction of prognosis for patients with LUAD and identify potentially novel biomarkers for the diagnosis.

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Section: Introductionmentioning

confidence: 99%

Identification of a long non‑coding RNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

Zhang

2020

Oncol Lett

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“…Despite the absolute benefit of PCI in prolonging survival, there is evidence supporting its association in the development of cognitive deficits due to its neurotoxic effects in the brain [ 5 ]. Two recent longitudinal studies by Simó and her colleagues [ 6 , 7 ] showed that neuropsychological deficits in SCLC patients treated with PCI are associated with PCI therapy, possibly in conjunction with platinum-based chemotherapy.…”

Section: Introductionmentioning

confidence: 99%

“…Also, more recent neuroimaging techniques (Magnetic Resonance Imaging (MRI); Diffusion Tensor Imaging (DTI)) have been conducted in order to explore structural alterations related to chemotherapy treatment in cancer populations. Specifically, two studies [ 6 , 11 ] found gray and white matter deficits in SCLC patients. Similar gray and white matter alterations were reported in a recent review of 17 structural MRI and DTI studies focusing on women with breast cancer treated with adjuvant chemotherapy [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Altered Brain Functional Connectivity in Small-Cell Lung Cancer Patients after Chemotherapy Treatment: A Resting-State fMRI Study

Bromis

Gkiatis

Karanasiou

et al. 2017

Computational and Mathematical Methods in Medicine

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Previous studies in small-cell lung cancer (SCLC) patients have mainly focused on exploring neurocognitive deficits associated with prophylactic cranial irradiation (PCI). Little is known about functional brain alterations that might occur due to chemotherapy treatment in this population before PCI is administered. For this reason, we used resting-state functional Magnetic Resonance Imaging (fMRI) to examine potential functional connectivity disruptions in brain networks, including the Default Mode Network (DMN), the Sensorimotor Network, and the Task-Positive Network (TPN). Nineteen SCLC patients after platinum-based chemotherapy treatment and thirteen controls were recruited in the current study. ROI-to-ROI and Seed-to-Voxel analyses were carried out and revealed functional connectivity deficits in patients within all the networks investigated demonstrating the possible negative effect of chemotherapy in cognitive functions in SCLC populations.

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“…Previous studies on CRCI in lung cancer have mainly concentrated on brain structure changes and default mode network disruption (Bromis et al 2017;Simo et al 2015Simo et al , 2016Simo et al , 2018Welzel et al 2008). Bromis et al (2017) found significant FC disruptions within all the rest-state networks of lung cancer patients after chemotherapy compared with the healthy controls.…”

Section: Introductionmentioning

confidence: 88%

Aberrant static and dynamic functional connectivity of the executive control network in lung cancer patients after chemotherapy: a longitudinal fMRI study

Chen

et al. 2020

Brain Imaging and Behavior

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Objective The purpose of the current study was to investigate chemotherapy-related variations in the intrinsic static and dynamic functional connectivity (sFC and dFC, respectively) of the executive control network (ECN) in lung cancer patients. Materials and methods In this study, we evaluated 18 lung cancer patients scanned before and after adjuvant chemotherapy treatment and compared the patients with 21 healthy controls (HCs). All subjects underwent resting-state functional MRI (rs-fMRI). We constructed the sFC and dFC of the bilateral dorsolateral prefrontal cortex (DLPFC) using a sliding-window approach, and the correlations between the changed sFC or dFC and cognitive performance were analyzed. Results Whole-brain sFC analysis showed that the lung cancer patients showed significant FC pattern changes in the bilateral DLPFC, mainly in the bilateral superior frontal gyrus (SFG), bilateral middle frontal gyrus, left superior temporal gyrus, left inferior parietal lobe and the right insula. Furthermore, after chemotherapy, the lung cancer patients showed significantly reduced dFC variability between the right DLPFC and right precuneus compared with HCs. In addition, the decreased dFC between the right DLPFC and left SFG in the lung cancer patients after chemotherapy in state 1 and between the right DLPFC and left insula in the lung cancer patients before chemotherapy in state 2 were negatively correlated with MoCA scores ((r =-0.520, p = 0.039; r =-0.548, p = 0.028, respectively). Conclusions Our results reveal that dynamic connectivity analysis is more effective and sensitive than methods that assume static brain states for linking brain FC patterns and chemotherapy.

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Longitudinal Brain Changes Associated with Prophylactic Cranial Irradiation in Lung Cancer

Cited by 48 publications

References 49 publications

Identification of a long non‑coding RNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

Identification of a long non‑coding RNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

Altered Brain Functional Connectivity in Small-Cell Lung Cancer Patients after Chemotherapy Treatment: A Resting-State fMRI Study

Aberrant static and dynamic functional connectivity of the executive control network in lung cancer patients after chemotherapy: a longitudinal fMRI study

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