Lung cancer is one of the most frequent tumors that metastasize to the brain. Brain metastasis (BM) is common in advanced cases, being the major cause of patient morbidity and mortality. BMs are thought to arise via the seeding of circulating tumor cells into the brain microvasculature. In brain tissue, the interaction with immune cells promotes a microenvironment favorable to the growth of cancer cells. Despite multimodal treatments and advances in systemic therapies, lung cancer patients still have poor prognoses. Therefore, there is an urgent need to identify the molecular drivers of BM and clinically applicable biomarkers in order to improve disease outcomes and patient survival. The goal of this review is to summarize the current state of knowledge on the mechanisms of the metastatic spread of lung cancer to the brain and how the metastatic spread is influenced by the brain microenvironment, and to elucidate the molecular determinants of brain metastasis regarding the role of genomic and transcriptomic changes, including coding and non-coding RNAs. We also present an overview of the current therapeutics and novel treatment strategies for patients diagnosed with BM from NSCLC.

Prognostic biomarkers for recurrence of Oral Squamous Cell Carcinoma (OSCC) are urgently needed. We aimed to independently validate a 4-gene expression signature (MMP1, COL4A1, P4HA2, THBS2) predictive of OSCC recurrence risk. Gene expression was measured using Nanostring nCounter ® in 245 histologically normal surgical resection margins from 62 patients. Association between risk scores for individual patients and recurrence was assessed by Kaplan-Meier analysis. Signature performance was quantified by concordance index (CI), hazard ratio (HR) and the area under receiver operating characteristics (AUC). Risk scores for recurrence were significantly higher than recurrence-free patients (p = 9.58e-7, Welch's t-test). A solid performance of the 4-gene signature was determined: CI = 0.64, HR = 3.38 (p = 1.4E-4; log-rank test), AUC = 0.71. We showed that three margins per patient are sufficient to preserve predictive performance (CI = 0.65; HR = 2.92; p = 2.94e-3; AUC = 0.71). Association between the predicted risk scores and recurrence was assessed and showed HR = 2.44 (p = 9.6E-3; logrank test, N = 62). Signature performance analysis was repeated using an optimized threshold (70 th percentile of risks), resulting in HR = 3.38 (p = 1.4E-4; log-rank test, N = 62). The 4-gene signature was validated as predictive of recurrence risk in an independent cohort of patients with resected OSCC and histologically negative margins, and is potentially applicable for clinical decision making on adjuvant treatment and disease monitoring. Oral Squamous Cell Carcinoma (OSCC) is the most common head and neck cancer, and the 8 th most frequent cancer 1 , accounting for >300,000 new cases and >145,000 deaths every year, worldwide 2. Conventional treatment for OSCC includes surgery, radiotherapy and chemotherapy. However, patients often exhibit poor response to treatment and high rates of recurrence, typically between 20-40% 3 , reducing the five-year survival to 50% 4 .

Metabolomics based on untargeted flow infusion electrospray ionization high-resolution mass spectrometry (FIE-HRMS) can provide a snap-shot of metabolism in living cells. Lung Squamous Cell Carcinoma (SCC) is one of the predominant subtypes of Non-Small Cell Lung Cancers (NSCLCs), which usually shows a poor prognosis. We analysed lung SCC samples and matched histologically normal lung tissues from eight patients. Metabolites were profiled by FIE-HRMS and assessed using t-test and principal component analysis (PCA). Differentially accumulating metabolites were mapped to pathways using the mummichog algorithm in R, and biologically meaningful patterns were indicated by Metabolite Set Enrichment Analysis (MSEA). We identified metabolic rewiring networks, including the suppression of the oxidative pentose pathway and found that the normal tricarboxylic acid (TCA) cycle were decoupled from increases in glycolysis and glutamine reductive carboxylation. Well-established associated effects on nucleotide, amino acid and thiol metabolism were also seen. Novel aspects in SCC tissue were increased in Vitamin B complex cofactors, serotonin and a reduction of γ-aminobutyric acid (GABA). Our results show the value of FIE-HRMS as a high throughput screening method that could be exploited in clinical contexts.

Introduction: Tobacco smoke is associated with oxidative and inflammatory pathways, increasing the risk of chronic-degenerative diseases. Our goal was to evaluate the effects of acute “Pera” and “Moro” orange juice consumption on inflammatory processes and oxidative stress in microRNA (miRNA) expression in plasma from healthy smokers.Methods: This was a randomized crossover study that included healthy smokers over 18 years old. Blood samples were collected before and 11 h after beverage ingestion. Participants were instructed to drink 400 mL of Pera orange juice (Citrus sinensis), Moro orange juice (Citrus sinensis L. Osbeck), or water. Each subject drank the beverages in a 3-way crossover study design. Inflammatory and oxidative stress biomarkers and circulating miRNA expression profiles were determined. The subjects maintained their usual tobacco exposure during the experiment.Results: We included 18 individuals (12 men and 6 women), with 37.0 ± 12.0 years old. All subjects received the 3 interventions. Increased expression of circulating miRNAs (miR-150-5p, miR-25-3p, and miR-451a) was verified after cigarette smoking, which were attenuated after intake of both types of orange juice. There was no difference regarding serum levels of TNF-α, IL-6, MMP-9, and C-reactive protein. Despite the increased activity of serum superoxide dismutase and glutathione peroxidase after “Pera” or “Moro” orange juice intake, respectively, no changes in lipid hydroperoxide levels were detected.Conclusion: Tobaccos smokers showed increased expression of miR-150-5p, miR-25-3p, and miR-451a was noted, and attenuated by orange juice intake. miRNAs were predicted to regulate 244 target genes with roles in oxidative stress, PI3K-Akt, and MAPK signaling, which are pathways frequently involved in smoking-related cardiovascular diseases and cancer.