Tobacco use is associated with low peripheral beta-arrestin 1 levels in major depression: A preliminary report.

BACKGROUND: Understanding mechanisms associated with depressed smokers is a relevant question given that tobacco use disorder with comorbid major depressive disorder (MDD) has worse outcomes. The beta-arrestin 1 (ARRB1) pathway is a suggested biomarker for major depressive disorder and is involved in both antidepressant mechanism of action and tobacco addiction. We aimed to assess the association between smoking and peripheral ARRB1 expression in participants who exhibited MDD with current major depressive episode (MDE). BASIC PROCEDURES: 61 participants who exhibited MDD with current MDE with a score above 17 on the Hamilton Depression Rating Scale (HDRS), and who were free from antidepressant drug treatment for at least one month before inclusion, were assessed for tobacco use and cigarettes/day. Peripheral ARRB1 expression was assessed by sandwich ELISA from peripheral blood mononuclear cells (PBMC). FINDINGS: In participants who exhibited MDD with current MDE, peripheral ARRB1 expression was lower in tobacco users (n = 20, mean (SD) 4.795 (1.04) ng/mg of total protein) compared to non-tobacco users (n = 41, mean (SD) 6.19 (1.56) ng/mg; FDR p-value= 0.0044). Higher daily tobacco consumption was associated with lower peripheral ARRB1 expression (r = -0.314; FDR p-value=0.037). CONCLUSIONS: Tobacco consumption should be considered in studies of ARRB1 in participants who exhibit MDD. ARRB1 signaling is a new target of interest with a potential clinical implication for people with MDD and tobacco use disorder.

Identification of beta-arrestin-1 as a diagnostic biomarker in lung cancer.

BACKGROUND: Distinguishing lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) has a tremendous therapeutic implication. Sometimes, the commonly used immunohistochemistry (IHC) markers fail to discriminate between them, urging for the identification of new diagnostic biomarkers. METHODS: We performed IHC on tissue microarrays from two cohorts of lung cancer patients to analyse the expression of beta-arrestin-1, beta-arrestin-2 and clinically used diagnostic markers in ADC and SCC samples. Logistic regression models were applied for tumour subtype prediction. Parallel reaction monitoring (PRM)-based mass spectrometry was used to quantify beta-arrestin-1 in plasma from cancer patients and healthy donors. RESULTS: Beta-arrestin-1 expression was significantly higher in ADC versus SCC samples. Beta-arrestin-1 displayed high sensitivity, specificity and negative predictive value. Its usefulness in an IHC panel was also shown. Plasma beta-arrestin-1 levels were considerably higher in lung cancer patients than in healthy donors and were higher in patients who later experienced a progressive disease than in patients showing complete/partial response following EGFR inhibitor therapy. CONCLUSIONS: Our data identify beta-arrestin-1 as a diagnostic marker to differentiate ADC from SCC and indicate its potential as a plasma biomarker for non-invasive diagnosis of lung cancer. Its utility to predict response to EGFR inhibitors is yet to be confirmed.