Hypoxia is a condition always present in tumor environment owing to the fast growth of tumor cells not supported by adequate blood supply. There is increasing evidence that hypoxia plays an important role in cancer dormancy and cancer metabolism, increasing stemness activity and bringing about cancer initiation and progression . This condition may influence the production of hypoxia inducible factor (HIF) a helix transcription factor which is involved in carcinogenesis and tumor growth through the regulation of genes involved in angiogenesis, glycolytic metabolism and other biological mechanisms. In normoxia condition HIF is inactivated by prolyl hydroxylase enzymes (EGLN 1–3, also known as PHD 1–3) using oxygen as a substrate. Once hydroxilated it binds to a protein called Von Hippel Lindau protein (VHL) for its degradation, whereas in hypoxia condition stabilization and nuclear translocation occur, leading to oncogenes activation. It has got three isoforms HIF-1 HIF-2 and HIF-3. The most studied factor is HIF-1 which is a heterodimer consisting of two forms, the form α is expressed in manner oxygen dependent, the form β is expressed constitutively. Its presence in tumor microenvironment could foster among other the expression of VEGF, HGF, Met protoncogene which induces degradation of the extracellular matrix and TWIST gene, which is in turn involved in a mechanism of cancer cell metastasis called epithelial-mesenchimal transition(EMT). In this review, we summarize the most important findings in HIF action in different types of cancer focusing on its properties to induce tumor cell growth and highlighting its poor prognostic value in different cancers sites.

Non‐small cell lung cancer (NSCLC) is the leading cause of cancer death and in most cases it is often diagnosed at an advanced stage. Many genetic and microenvironmental factors are able to modify the cell cycle inducing carcinogenesis and tumor growth. Among the metabolic and genetic factors that come into play in carcinogenesis and tumor cell differentiation and growth there are two different proteins that should be considered which are glucose transporters (GLUTs) and p16^INK4 The first are glucose transporters which are strongly involved in tumor metabolism, notably accelerating cancer cell metabolism both in aerobic and anaerobic conditions. There are different subtypes of GLUT family factors of which GLUT 1 is the most important and widely expressed. By contrast, p16 is mainly a tumor‐suppressor protein that acts on cyclin‐dependent kinase favoring cell cycle arrest in the G1 phase. Our search focused on the action of the aforementioned factors.

Tobacco smoke contains more than 4000 detectable substances, such as polycyclic aromatic hydrocarbons, nicotine, carbon monoxide and heavy metals, which are considered powerful enzymatic inducers that have notable influence on the efficacy and tolerability of many medications through complex pharmacokinetic and pharmacodynamic interactions. As a result, adjustments of drug dosages are required in smokers, both if they continue to smoke or if they quit after smoking cessation treatment. The purpose of this review is to examine the main drug interactions with tobacco smoke clinically relevant, with a closer look on patients developing oncologic diseases.

Background: Cigarette smoke exposure is the main preventable cause of chronic obstructive pulmonary disease (COPD). Airflow limitation is closely associated with smoking exposure. Smoking could also interfere with lipid metabolism. Aim: To determine the respiratory functional and metabolic changes after smoking cessation in smokers in the short term. Methods: All patients were current smokers. They were assessed by spirometry and questionnaires such as COPD assessment test(CAT), modified Medical Research Council (mMRC) test for dyspnea, Fagestrom’s test for nicotine dependence. Exhaled CO was detected in order to evaluate smoking exposure and smoking cessation (normal value< 7 ppm). A blood sampling was eventually taken for vitamin D and cholesterol assay. All patients underwent therapy with counselling and varenicline as first-line treatment according to its schedule. Detection time: at baseline and one month after smoking cessation. Results: All patients quit smoking during treatment. The mean age was 62 with a prevalence of males. The analysis revealed the following mean values at baseline: CAT mean score was 15, pack-years 35.5, Fagestrom’s Test mean score 5.0. The West’s value was 8.5, whereas Body mass index (BMI) was 25.5.Cigarette daily consumption mean value was 22.5. The comparison before and at follow up one month after smoking cessation about functional and metabolic parameters, show us the following results: FEV 1 was increased by 200 mL (p< 0.02), FEF 25/75 was improved as well as mMRC test. The eCO was dropped to as low as 8 ppM. Interestingly the vitamin D level was increased from 25 to 28 ng/mL without any support therapy. The cholesterol total level was reduced and CAT value and DLCO were also significantly improved. Conclusion: Quit smoking is useful to improve symptoms, respiratory function and metabolic parameters in the short term.