Machine learning-assisted SERS approach enables the biochemical discrimination in Bcl-2 and Mcl-1 expressing yeast cells treated with ketoconazole and fluconazole antifungals.

Antifungal medications are important due to their potential application in cancer treatment either on their own or with traditional treatments. The mechanisms that prevent the effects of these medications and restrict their usage in cancer treatment are not completely understood. The evaluation and discrimination of the possible protective effects of the anti-apoptotic members of the Bcl-2 family of proteins, critical regulators of mitochondrial apoptosis, against antifungal drug-induced cell death has still scientific uncertainties that must be considered. Novel, simple, and reliable strategies are highly demanded to identify the biochemical signature of this phenomenon. However, the complex nature of cells poses challenges for the analysis of cellular biochemical changes or classification. In this study, for the first time, we investigated the probable protective activities of Bcl-2 and Mcl-1 proteins against cell damage induced by ketoconazole (KET) and fluconazole (FLU) antifungal drugs in a yeast model through surface-enhanced Raman spectroscopy (SERS) approach. The proposed SERS platform created robust Raman spectra with a high signal-to-noise ratio. The analysis of SERS spectral data via advanced unsupervised and supervised machine learning methods enabled unquestionable differentiation (100 %) in samples and biomolecular identification. Various SERS bands related to lipids and proteins observed in the analyses suggest that the expression of these anti-apoptotic proteins reduces oxidative biomolecule damage induced by the antifungals. Also, cell viability assay, Annexin V-FITC/PI double staining, and total oxidant and antioxidant status analyses were performed to support Raman measurements. We strongly believe that the proposed approach paves the way for the evaluation of various biochemical structures/changes in various cells.

S6K2 promises an important therapeutic potential for cancer.

S6K2, the newer member of S6 Kinase family, is a crucial modulator of Akt/mTOR signaling pathway and is a member of AGC kinase family that regulates cellular growth and survival. S6K1 and S6K2 share high sequence similarity; therefore, S6K2 had been underestimated. However, recent studies displayed distinct functions of S6K2. Activated by both Akt/mTOR and Ras/Raf/Mek/Erk signaling pathways, S6K2 regulates cancer cell survival via different routes. Complexation with antiapoptotic proteins BRAF and PKCε avoids non-small-cell lung cancer cells  from apoptosis upon FGF-2 stimulation. Indirect upregulation of the translation of antiapoptotic proteins Bcl-XL and XIAP in HEK293T cells and interference with TNF-induced apoptosis in MCF-7 cells are other routes of cancer cell survival. The aforementioned studies on S6K2 necessitate the development of therapies targeting only on S6K2. Studies targeting S6K2 may help to build important roads for cancer therapy.