The surface-enhanced Raman spectroscopy (SERS) technique combined with chemometry can be a potential tool for early discrimination of small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) from plasma and, as well as from the lung tissue samples. Based on the acquired spectra and the applied algorithm, it is possible to distinguish between the two types of SCLC and NSCLC associated with smoking and also to differentiate between subtypes of NSCLC in a very fast mode in comparison to standard histopathology. The applied chemometry in the form of the partial least squares regression (PLSR) and the partial least squares discriminant analysis (PLS-DA) method allows, for the first time, to discriminate against tumor samples and determine between SCLC, NSCLC, and NSCLC types. The presented data clearly indicate that plasma samples are enough to discriminate between SCLC and NSCLC samples and NSCLC subtypes efficiently, which significantly facilitates the cancer diagnosis in terms of time and costs of analysis. Moreover, the fast and proper identification of LCC samples, especially in the case of a very aggressive SCLC-like type of cancer, has a substantial impact on the patient's treatments and thus may significantly impact the patient's life.