Lung cancer is the most common and one of the most lethal types of cancer. The development of lung cancer therapy depends on the solution of two problems. The first problem is the identification of the driver molecular alterations that govern the tumor growth and progress of disease and the classification of tumors into subtypes based on characteristic combinations of driver alterations. The second challenge is the identification of those tumor subtypes that will be most susceptible to treatment with a particular drug or type of therapy. Methods of quantitative proteomics made it possible to compare tumors by the levels of protein expression and the levels of post-translational modifications at specific protein sites. Thus, researchers were able to identify previously unknown protein landscapes of tumors, identify new disease subtypes, identify new molecular mechanisms of tumor development, nominate new targets for drug design, and identify groups of tumors that are most susceptible to known drugs. In this Special Issue, we will present a collection of articles that highlight the latest findings in proteomic profiling of lung cancer.