15-LOX-1 has diverse roles in the resensitization of resistant cancer cell lines to doxorubicin.

Lipoxygenases (LOXs) are a family of enzymes that can oxygenate polyunsaturated fatty acids. As a member of the family, 15-lipoxygenase-1 (15-LOX-1) specifically metabolizes arachidonic acid and linoleic acid. 15-LOX-1 can affect physiological and pathophysiological events via regulation of the protein-lipid interactome, alterations in intracellular redox state and production of lipid metabolites that are involved in the induction and resolution of inflammation. Although several studies have shown that 15-LOX-1 has an antitumorigenic role in many different cancer models, including breast cancer, the role of the protein in cancer drug resistance has not been established yet. In this study, we, for the first time, aimed to show the potential role of 15-LOX-1 in acquired doxorubicin (DOX) resistance in MCF7 and HeLa cancer cell lines. Our results show that ALOX15 was transcriptionally downregulated in DOX-resistant cells compared with their drug-sensitive counterparts. Moreover, overexpression of ALOX15 in the drug-resistant cells resulted in resensitization of those cells to DOX in a cell-dependent manner. 15-LOX-1 expression could induce apoptosis by activating PPARγ and enhance the accumulation of DOX in drug-resistant MCF7 cells by altering cellular motility properties, and membrane dynamics. However, HeLa DOX cells did not show any of these effects but were susceptible to cell death when treated with 13(S)-HODE. These results underline the role and importance of 15-LOX-1 in cancer drug resistance, and points to novel mechanisms as a therapeutic approach to overcome cancer drug resistance.

Differential synergistic effects of palbociclib and doxorubicin on doxorubicin-resistant cancer cells with diverse tumor origins.

Palbociclib is a dual inhibitor of cyclin-dependent kinases 4 and 6 (CDK4/6). Palbociclib has frequently been studied in breast cancer cells and has also been linked to function of P-glycoprotein (P-gp), main protein responsible for cancer drug resistance. However, the effect of Palbociclib on cancer drug resistance and specifically doxorubicin-resistant cells overexpressing P-gp have limitedly been studied in the literature. Here, we aimed to decipher the possible synergistic effects of Palbociclib and Doxorubicin combination treatment in doxorubicin-resistant not only breast cancer, which has restrictedly been studied previously, but leukemia and cervical cancer cell lines in the presence of sensitive counterparts to totally explore the mechanistic properties of the Palbociclib in cancer drug resistance. Our results underlined that Palbociclib differentially displayed synergistic effect with doxorubicin in a cell type-specific manner and increased the efficacy of Doxorubicin in Doxorubicin-resistant cells. As a monotherapy, palbociclib has been shown to decrease the expression of MDR-1 in doxorubicin-resistant cells, and when used in combination with doxorubicin, it has been shown to increase the accumulation of doxorubicin in the cell and consequently induce apoptosis. This is the first report that proposes the Palbociclib as a candidate for combination therapy to limit the Doxorubicin resistance in different cancer origins in clinics.

Investigation of evolutionary dynamics for drug resistance in 3D spheroid model system using cellular barcoding technology.

Complex evolutionary dynamics governing the drug resistance is one of the major challenges in cancer treatment. Understanding these mechanisms requires a sequencing technology with higher resolution to delineate whether pre-existing or de novo drug mechanisms are behind the drug resistance. Combining this technology with clinically very relevant model system, namely 3D spheroids, better mimicking tumorigenesis and drug resistance have so far been lacking. Thus, we sought to establish dabrafenib and irinotecan resistant derivatives of barcoded 3D spheroids with the ultimate aim to quantify the selection-induced clonal dynamics and identify the genomic determinants in this model system. We found that dabrafenib and irinotecan induced drug resistance in 3D-HT-29 and 3D-HCT-116 spheroids are mediated by pre-existing and de novo resistant barcodes, indicating the presence of polyclonal drug resistance in this system. Moreover, whole-exome sequencing analysis found chromosomal gains and mutations associated with dabrafenib and irinotecan resistance in 3D-HT-29 and 3D-HCT-116 spheroids. Last, we show that dabrafenib and irinotecan resistance are also mediated by multiple drug resistance by detection of upregulation of the drug efflux pumps, ABCB1 and ABCG2, in our spheroid model system. Overall, we present the quantification of drug resistance and evolutionary dynamics in spheroids for the first time using cellular barcoding technology and the underlying genomic determinants of the drug resistance in our model system.

Systems Biology and Experimental Model Systems of Cancer.

Over the past decade, we have witnessed an increasing number of large-scale studies that have provided multi-omics data by high-throughput sequencing approaches. This has particularly helped with identifying key (epi)genetic alterations in cancers. Importantly, aberrations that lead to the activation of signaling networks through the disruption of normal cellular homeostasis is seen both in cancer cells and also in the neighboring tumor microenvironment. Cancer systems biology approaches have enabled the efficient integration of experimental data with computational algorithms and the implementation of actionable targeted therapies, as the exceptions, for the treatment of cancer. Comprehensive multi-omics data obtained through the sequencing of tumor samples and experimental model systems will be important in implementing novel cancer systems biology approaches and increasing their efficacy for tailoring novel personalized treatment modalities in cancer. In this review, we discuss emerging cancer systems biology approaches based on multi-omics data derived from bulk and single-cell genomics studies in addition to existing experimental model systems that play a critical role in understanding (epi)genetic heterogeneity and therapy resistance in cancer.