Effectiveness of a healthcare-based mobile intervention on sedentary patterns, physical activity, mental well-being and clinical and productivity outcomes in office employees with type 2 diabetes: study protocol for a randomized controlled trial

Background: Prolonged sedentary time is associated with an increased incidence of chronic disease including type 2 diabetes mellitus (DM2). Given that occupational sedentary time contributes signifcantly to the total amount of daily sedentariness, incorporating programmes to reduce occupational sedentary time in patients with chronic disease would allow for physical, mental and productivity benefts. The aim of this study is to evaluate the short-, medium- and long-term efectiveness of a mHealth programme for sitting less and moving more at work on habitual and occupational sedentary behaviour and physical activity in ofce staf with DM2. Secondary aims. To evaluate the efectiveness on glycaemic control and lipid profle at 6- and 12-month follow-up; anthropometric profle, blood pres‑ sure, mental well-being and work-related post-intervention outcomes at 3, 6 and 12months. Methods: Multicentre randomized controlled trial. A sample size of 220 patients will be randomly allocated into a control (n=110) or intervention group (n=110), with post-intervention follow-ups at 6 and 12months. Health professionals from Spanish Primary Health Care units will randomly invite patients (18–65 years of age) diagnosed with DM2, who have sedentary ofce desk-based jobs. The control group will receive usual healthcare and information on the health benefts of sitting less and moving more. The intervention group will receive, through a smartphone app and website, strategies and real-time feedback for 13weeks to change occupational sedentary behaviour. Variables: (1) Subjective and objective habitual and occupational sedentary behaviour and physical activity (Workforce Sit‑ ting Questionnaire, Brief Physical Activity Assessment Tool, activPAL3TM); 2) Glucose, HbA1c; 3) Weight, height, waist circumference; 4) Total, HDL and LDL cholesterol, triglycerides; (5) Systolic, diastolic blood pressure; (6) Mental well being (Warwick-Edinburgh Mental Well-being); (7) Presenteeism (Work Limitations Questionnaire); (8) Impact of work on employees´ health, sickness absence (6th European Working Conditions Survey); (9) Job-related mental strain (Job Content Questionnaire). Diferences between groups pre- and post- intervention on the average value of the vari‑ ables will be analysed. Discussion: If the mHealth intervention is efective in reducing sedentary time and increasing physical activity in ofce employees with DM2, health professionals would have a low-cost tool for the control of patients with chronic disease.The study was funded by Fondo de Investigación Sanitaria, Instituto de Salud Carlos III (PI17/01788) and the predoctoral research grant Isabel Fernández 2020 from the Spanish Society of Family and Community Medicine (semFYC). The funders had no role in the design, analysis, data interpretation or writing of the manuscript

MYC activation impairs cell-intrinsic IFNγ signaling and confers resistance to anti-PD1/PD-L1 therapy in lung cancer

Elucidating the adaptive mechanisms that prevent host immune response in cancer will help predict efficacy of anti-programmed death-1 (PD1)/L1 therapies. Here, we study the cell-intrinsic response of lung cancer (LC) to interferon-y (IFNy), a cytokine that promotes immunoresponse and modulates programmed death-ligand 1 (PD-L1) levels. We report complete refractoriness to IFNy in a subset of LCs as a result of JAK2 or IFNGR1 inactivation. A submaximal response affects another subset that shows constitutive low levels of IFNy-stimulated genes (IySGs) coupled with decreased H3K27ac (histone 3 acetylation at lysine 27) depo-sition and promoter hypermethylation and reduced IFN regulatory factor 1 (IRF1) recruitment to the DNA on IFNy stimulation. Most of these are neuroendocrine small cell LCs (SCLCs) with oncogenic MYC/MYCL1/ MYCN. The oncogenic activation of MYC in SCLC cells downregulates JAK2 and impairs IySGs stimulation by IFNy. MYC amplification tends to associate with a worse response to anti-PD1/L1 therapies. Hence alterations affecting the JAK/STAT pathway and MYC activation prevent stimulation by IFNy and may predict anti-PD1/L1 efficacy in LC

Genome-wide profiling of non-smoking-related lung cancer cells reveals common RB1 rearrangements associated with histopathologic transformation in EGFR-mutant tumors.

The etiology and the molecular basis of lung adenocarcinomas (LuADs) in nonsmokers are currently unknown. Furthermore, the scarcity of available primary cultures continues to hamper our biological understanding of non-smoking-related lung adenocarcinomas (NSK-LuADs). We established patient-derived cancer cell (PDC) cultures from metastatic NSK-LuADs, including two pairs of matched EGFR-mutant PDCs before and after resistance to tyrosine kinase inhibitors (TKIs), and then performed whole-exome and RNA sequencing to delineate their genomic architecture. For validation, we analyzed independent cohorts of primary LuADs. In addition to known non-smoker-associated alterations (e.g. RET, ALK, EGFR, and ERBB2), we discovered novel fusions and recurrently mutated genes, including ATF7IP, a regulator of gene expression, that was inactivated in 5% of primary LuAD cases. We also found germline mutations at dominant familiar-cancer genes, highlighting the importance of genetic predisposition in the origin of a subset of NSK-LuADs. Furthermore, there was an over-representation of inactivating alterations at RB1, mostly through complex intragenic rearrangements, in treatment-naive EGFR-mutant LuADs. Three EGFR-mutant and one EGFR-wild-type tumors acquired resistance to EGFR-TKIs and chemotherapy, respectively, and histology on re-biopsies revealed the development of small-cell lung cancer/squamous cell carcinoma (SCLC/LuSCC) transformation. These features were consistent with RB1 inactivation and acquired EGFR-T790M mutation or FGFR3-TACC3 fusion in EGFR-mutant tumors. We found recurrent alterations in LuADs that deserve further exploration. Our work also demonstrates that a subset of NSK-LuADs arises within cancer-predisposition syndromes. The preferential occurrence of RB1 inactivation, via complex rearrangements, found in EGFR-mutant tumors appears to favor SCLC/LuSCC transformation under growth-inhibition pressures. Thus RB1 inactivation may predict the risk of LuAD transformation to a more aggressive type of lung cancer, and may need to be considered as a part of the clinical management of NSK-LuADs patients.This work was supported by the Fundacion Cientifica Asociacion Española Contra el Cancer-AECC (grant number GCB14142170MONT) to LMM, MS-C, and EF; the Spanish Ministry of Economy and Competitivity-MINECO (grant number SAF-2017-82186R to MS-C; Rio Hortega-CM17/00180 to MS; PROYBAR17005NADA to EN); the Health Institute Carlos III-ISCIII, Fondo Europeo de Desarrollo Regional-FEDER (grant Number PT13/0001/0044, PT17/0009/0019, PI16 01821); the Government of Navarra (grant number DIANA project); and the Ramon Areces Foundation (no grant number is applicable) to LMM and RP.S

MYC activation impairs cell-intrinsic IFNγ signaling and confers resistance to anti-PD1/PD-L1 therapy in lung cancer

Elucidating the adaptive mechanisms that prevent host immune response in cancer will help predict efficacy of anti-programmed death-1 (PD1)/L1 therapies. Here, we study the cell-intrinsic response of lung cancer (LC) to interferon-γ (IFNγ), a cytokine that promotes immunoresponse and modulates programmed death-ligand 1 (PD-L1) levels. We report complete refractoriness to IFNγ in a subset of LCs as a result of JAK2 or IFNGR1 inactivation. A submaximal response affects another subset that shows constitutive low levels of IFNγ-stimulated genes (IγSGs) coupled with decreased H3K27ac (histone 3 acetylation at lysine 27) deposition and promoter hypermethylation and reduced IFN regulatory factor 1 (IRF1) recruitment to the DNA on IFNγ stimulation. Most of these are neuroendocrine small cell LCs (SCLCs) with oncogenic MYC/MYCL1/MYCN. The oncogenic activation of MYC in SCLC cells downregulates JAK2 and impairs IγSGs stimulation by IFNγ. MYC amplification tends to associate with a worse response to anti-PD1/L1 therapies. Hence alterations affecting the JAK/STAT pathway and MYC activation prevent stimulation by IFNγ and may predict anti-PD1/L1 efficacy in LC

A novel epigenetic signature for early diagnosis in lung cancer

Purpose: lung cancer remains as the leading cause of cancer-related death worldwide, mainly due to late diagnosis. Cytology is the gold-standard method for lung cancer diagnosis in minimally invasive respiratory samples, despite its low sensitivity. We aimed to identify epigenetic biomarkers with clinical utility for cancer diagnosis in minimally/noninvasive specimens to improve accuracy of current technologies. Experimental design: the identification of novel epigenetic biomarkers in stage I lung tumors was accomplished using an integrative genome-wide restrictive analysis of two different large public databases. DNA methylation levels for the selected biomarkers were validated by pyrosequencing in paraffin-embedded tissues and minimally invasive and noninvasive respiratory samples in independent cohorts. Results: we identified nine cancer-specific hypermethylated genes in early-stage lung primary tumors. Four of these genes presented consistent CpG island hypermethylation compared with nonmalignant lung and were associated with transcriptional silencing. A diagnostic signature was built using multivariate logistic regression model based on the combination of four genes: BCAT1, CDO1, TRIM58, and ZNF177. Clinical diagnostic value was also validated in multiple independent cohorts and yielded a remarkable diagnostic accuracy in all cohorts tested. Calibrated and cross-validated epigenetic model predicts with high accuracy the probability to detect cancer in minimally and noninvasive samples. We demonstrated that this epigenetic signature achieved higher diagnostic efficacy in bronchial fluids as compared with conventional cytology for lung cancer diagnosis. Conclusions: minimally invasive epigenetic biomarkers have emerged as promising tools for cancer diagnosis. The herein obtained epigenetic model in combination with current diagnostic protocols may improve early diagnosis and outcome of lung cancer patients

A novel epigenetic signature for early diagnosis in lung cancer

Purpose: lung cancer remains as the leading cause of cancer-related death worldwide, mainly due to late diagnosis. Cytology is the gold-standard method for lung cancer diagnosis in minimally invasive respiratory samples, despite its low sensitivity. We aimed to identify epigenetic biomarkers with clinical utility for cancer diagnosis in minimally/noninvasive specimens to improve accuracy of current technologies. Experimental design: the identification of novel epigenetic biomarkers in stage I lung tumors was accomplished using an integrative genome-wide restrictive analysis of two different large public databases. DNA methylation levels for the selected biomarkers were validated by pyrosequencing in paraffin-embedded tissues and minimally invasive and noninvasive respiratory samples in independent cohorts. Results: we identified nine cancer-specific hypermethylated genes in early-stage lung primary tumors. Four of these genes presented consistent CpG island hypermethylation compared with nonmalignant lung and were associated with transcriptional silencing. A diagnostic signature was built using multivariate logistic regression model based on the combination of four genes: BCAT1, CDO1, TRIM58, and ZNF177. Clinical diagnostic value was also validated in multiple independent cohorts and yielded a remarkable diagnostic accuracy in all cohorts tested. Calibrated and cross-validated epigenetic model predicts with high accuracy the probability to detect cancer in minimally and noninvasive samples. We demonstrated that this epigenetic signature achieved higher diagnostic efficacy in bronchial fluids as compared with conventional cytology for lung cancer diagnosis. Conclusions: minimally invasive epigenetic biomarkers have emerged as promising tools for cancer diagnosis. The herein obtained epigenetic model in combination with current diagnostic protocols may improve early diagnosis and outcome of lung cancer patients

A novel epigenetic signature for early diagnosis in lung cancer

Purpose: lung cancer remains as the leading cause of cancer-related death worldwide, mainly due to late diagnosis. Cytology is the gold-standard method for lung cancer diagnosis in minimally invasive respiratory samples, despite its low sensitivity. We aimed to identify epigenetic biomarkers with clinical utility for cancer diagnosis in minimally/noninvasive specimens to improve accuracy of current technologies. Experimental design: the identification of novel epigenetic biomarkers in stage I lung tumors was accomplished using an integrative genome-wide restrictive analysis of two different large public databases. DNA methylation levels for the selected biomarkers were validated by pyrosequencing in paraffin-embedded tissues and minimally invasive and noninvasive respiratory samples in independent cohorts. Results: we identified nine cancer-specific hypermethylated genes in early-stage lung primary tumors. Four of these genes presented consistent CpG island hypermethylation compared with nonmalignant lung and were associated with transcriptional silencing. A diagnostic signature was built using multivariate logistic regression model based on the combination of four genes: BCAT1, CDO1, TRIM58, and ZNF177. Clinical diagnostic value was also validated in multiple independent cohorts and yielded a remarkable diagnostic accuracy in all cohorts tested. Calibrated and cross-validated epigenetic model predicts with high accuracy the probability to detect cancer in minimally and noninvasive samples. We demonstrated that this epigenetic signature achieved higher diagnostic efficacy in bronchial fluids as compared with conventional cytology for lung cancer diagnosis. Conclusions: minimally invasive epigenetic biomarkers have emerged as promising tools for cancer diagnosis. The herein obtained epigenetic model in combination with current diagnostic protocols may improve early diagnosis and outcome of lung cancer patients

Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data.

There is a lack of useful diagnostic tools to identify EGFR mutated NSCLC patients with long-term survival. This study develops a prognostic model using real world data to assist clinicians to predict survival beyond 24 months. EGFR mutated stage IIIB and IV NSCLC patients diagnosed between January 2009 and December 2017 included in the Spanish Lung Cancer Group (SLCG) thoracic tumor registry. Long-term survival was defined as being alive 24 months after diagnosis. A multivariable prognostic model was carried out using binary logistic regression and internal validation through bootstrapping. A nomogram was developed to facilitate the interpretation and applicability of the model. 505 of the 961 EGFR mutated patients identified in the registry were included, with a median survival of 27.73 months. Factors associated with overall survival longer than 24 months were: being a woman (OR 1.78); absence of the exon 20 insertion mutation (OR 2.77); functional status (ECOG 0-1) (OR 4.92); absence of central nervous system metastases (OR 2.22), absence of liver metastases (OR 1.90) or adrenal involvement (OR 2.35) and low number of metastatic sites (OR 1.22). The model had a good internal validation with a calibration slope equal to 0.781 and discrimination (optimism corrected C-index 0.680). Survival greater than 24 months can be predicted from six pre-treatment clinicopathological variables. The model has a good discrimination ability. We hypothesized that this model could help the selection of the best treatment sequence in EGFR mutation NSCLC patients