Autophagy is a fundamental homeostatic process in which certain cellular components are ingested by double-membrane autophagosomes and then degraded to create energy or to maintain cellular homeostasis and survival. It is typically observed in nutrient-deprived cells as a survival mechanism. However, it has also been identified as a crucial process in maintaining cellular homeostasis and disease progression. Normal cellular metabolism produces reactive oxygen (ROS) and nitrogen species at low levels. However, increased production causes oxidative stress, which can lead to diabetes, cardiovascular diseases, neurological disorders, and cancer. It was recently shown that maintaining redox equilibrium via autophagy is critical for cellular responses to oxidative stress. However, little is understood about the molecular cancer processes that connect to the control of autophagy. In cancer cells, oncogenic mutations, carcinogens, and metabolic reprogramming cause increased ROS generation and oxidative stress. Recent studies have suggested that increased ROS generation activates survival pathways that promote cancer development and metastasis. Moreover, the relationship between metabolic programming and ROS in cancer cells is involved in redox homeostasis and the malignant phenotype. Currently, while the signaling events governing autophagy and how redox homeostasis affects signaling cascades are well understood, very little is known about molecular events related to autophagy. In this review, we focus on current knowledge about autophagy modulation and the role of redox metabolism to further the knowledge of oxidative stress and disease progression in cancer regulation. Therefore, this review focuses on understanding how oxidation/reduction events fine-tune autophagy to help understand how oxidative stress and autophagy govern cancer, either as processes leading to cell death or as survival strategies for maintaining redox homeostasis in cancer.

Type 2 diabetes (T2D) is a chronic metabolic disease defined by insulin insensitivity corresponding to impaired insulin sensitivity, decreased insulin production, and eventually failure of beta cells in the pancreas. There is a 30–40 percent higher risk of developing T2D in active smokers. Moreover, T2D patients with active smoking may gradually develop many complications. However, there is still no significant research conducted to solve the issue. Hence, we have proposed a highthroughput network-based quantitative pipeline employing statistical methods. Transcriptomic and GWAS data were analysed and obtained from type 2 diabetes patients and active smokers. Differentially Expressed Genes (DEGs) resulted by comparing T2D patients’ and smokers’ tissue samples to those of healthy controls of gene expression transcriptomic datasets. We have found 55 dysregulated genes shared in people with type 2 diabetes and those who smoked, 27 of which were upregulated and 28 of which were downregulated. These identified DEGs were functionally annotated to reveal the involvement of cell-associated molecular pathways and GO terms. Moreover, protein–protein interaction analysis was conducted to discover hub proteins in the pathways. We have also identified transcriptional and post-transcriptional regulators associated with T2D and smoking. Moreover, we have analysed GWAS data and found 57 common biomarker genes between T2D and smokers. Then, Transcriptomic and GWAS analyses are compared for more robust outcomes and identified 1 significant common gene, 19 shared significant pathways and 12 shared significant GOs. Finally, we have discovered protein–drug interactions for our identified biomarkers.