STAT3 contributes to cisplatin resistance, modulating EMT markers, and the mTOR signaling in lung adenocarcinoma.

Lung cancer is the second leading cause of cancer death worldwide and is strongly associated with cisplatin resistance. The transcription factor signal transducer and activator of transcription 3 (STAT3) is constitutively activated in cancer cells and coordinates critical cellular processes as survival, self-renewal, and inflammation. In several types of cancer, STAT3 controls the development, immunogenicity, and malignant behavior of tumor cells while it dictates the responsiveness to radio- and chemotherapy. It is known that STAT3 phosphorylation at Ser727 by mechanistic target of rapamycin (mTOR) is necessary for its maximal activation, but the crosstalk between STAT3 and mTOR signaling in cisplatin resistance remains elusive. In this study, using a proteomic approach, we revealed important targets and signaling pathways altered in cisplatin-resistant A549 lung adenocarcinoma cells. STAT3 had increased expression in a resistance context, which can be associated with a poor prognosis. STAT3 knockout (SKO) resulted in a decreased mesenchymal phenotype in A549 cells, observed by clonogenic potential and by the expression of epithelial-mesenchymal transition markers. Importantly, SKO cells did not acquire the mTOR pathway overactivation induced by cisplatin resistance. Consistently, SKO cells were more responsive to mTOR inhibition by rapamycin and presented impairment of the feedback activation loop in Akt. Therefore, rapamycin was even more potent in inhibiting the clonogenic potential in SKO cells and sensitized to cisplatin treatment. Mechanistically, STAT3 partially coordinated the cisplatin resistance phenotype via the mTOR pathway in non-small cell lung cancer. Thus, our findings reveal important targets and highlight the significance of the crosstalk between STAT3 and mTOR signaling in cisplatin resistance. The synergic inhibition of STAT3 and mTOR potentially unveil a potential mechanism of synthetic lethality to be explored for human lung cancer treatment.

Metformin-induced chemosensitization to cisplatin depends on P53 status and is inhibited by Jarid1b overexpression in non-small cell lung cancer cells.

Metformin has been tested as an anti-cancer therapy with potential to improve conventional chemotherapy. However, in some cases, metformin fails to sensitize tumors to chemotherapy. Here we test if the presence of P53 could predict the activity of metformin as an adjuvant for cisplatin-based therapy in non-small cell lung cancer (NSCLC). A549, HCC 827 (TP53 WT), H1299, and H358 (TP53 null) cell lines were used in this study. A549 cells were pre-treated with a sub-lethal dose of cisplatin to induce chemoresistance. The effects of metformin were tested both in vitro and in vivo and related to the ability of cells to accumulate Jarid1b, a histone demethylase involved in cisplatin resistance in different cancers. Metformin sensitized A549 and HCC 827 cells (but not H1299 and H358 cells) to cisplatin in a P53-dependent manner, changing its subcellular localization to the mitochondria. Treatment with a sub-lethal dose of cisplatin increased Jarid1b expression, yet downregulated P53 levels, protecting A549Res cells from metformin-induced chemosensitization to cisplatin and favored a glycolytic phenotype. Treatment with FL3, a synthetic flavagline, sensitized A549Res cells to cisplatin. In conclusion, metformin could potentially be used as an adjuvant for cisplatin-based therapy in NSCLC cells if wild type P53 is present.

Metformin impairs cisplatin resistance effects in A549 lung cancer cells through mTOR signaling and other metabolic pathways.

Lung cancer is the leading cause of cancer­associated death worldwide and exhibits intrinsic and acquired therapeutic resistance to cisplatin (CIS). The present study investigated the role of mTOR signaling and other signaling pathways after metformin (MET) treatment in control and cisplatin­resistant A549 cells, mapping pathways and possible targets involved in CIS sensitivity. MTT, flow cytometry, clonogenic assay, western blotting, proteomic analysis using the Stable Isotope Labeling by Amino acids in Cell culture (SILAC) approach and reverse transcription­quantitative PCR were performed. The results revealed that CIS treatment induced mTOR signaling pathway overactivation, and the mTOR status was restored by MET. MET and the mTOR inhibitor rapamycin (RAPA) decreased the viability in control and resistant cells, and decreased the cell size increase induced by CIS. In control cells, MET and RAPA decreased colony formation after 72 h and decreased IC50 values, potentiating the effects of CIS. Proteomics analysis revealed important pathways regulated by MET, including transcription, RNA processing and IL­12­mediated signaling. In CIS­resistant cells, MET regulated the apoptotic process, oxidative stress and G2/M transition. Annexin 4 (ANXA4) and superoxide dismutase 2 (SOD2), involved in apoptosis and oxidative stress, respectively, were chosen to validate the SILAC analysis and may represent potential therapeutic targets for lung cancer treatment. In conclusion, the chemosensitizing and antiproliferative effects of MET were associated with mTOR signaling and with potential novel targets, such as ANXA4 and SOD2, in human lung cancer cells.

Stochastic model of contact inhibition and the proliferation of melanoma in situ.

Contact inhibition is a central feature orchestrating cell proliferation in culture experiments; its loss is associated with malignant transformation and tumorigenesis. We performed a co-culture experiment with human metastatic melanoma cell line (SKMEL- 147) and immortalized keratinocyte cells (HaCaT). After 8 days a spatial pattern was detected, characterized by the formation of clusters of melanoma cells surrounded by keratinocytes constraining their proliferation. In addition, we observed that the proportion of melanoma cells within the total population has increased. To explain our results we propose a spatial stochastic model (following a philosophy of the Widom-Rowlinson model from Statistical Physics and Molecular Chemistry) which considers cell proliferation, death, migration, and cell-to-cell interaction through contact inhibition. Our numerical simulations demonstrate that loss of contact inhibition is a sufficient mechanism, appropriate for an explanation of the increase in the proportion of tumor cells and generation of spatial patterns established in the conducted experiments.

Accumulation of prohibitin is a common cellular response to different stressing stimuli and protects melanoma cells from ER stress and chemotherapy-induced cell death.

Melanoma is responsible for most deaths among skin cancers and conventional and palliative care chemotherapy are limited due to the development of chemoresistance. We used proteomic analysis to identify cellular responses that lead to chemoresistance of human melanoma cell lines to cisplatin. A systems approach to the proteomic data indicated the participation of specific cellular processes such as oxidative phosphorylation, mitochondrial organization and homeostasis, as well as the unfolded protein response (UPR) to be required for the survival of cells treated with cisplatin. Prohibitin (PHB) was among the proteins consistently accumulated, interacting with the functional clusters associated with resistance to cisplatin. We showed PHB accumulated at different levels in melanoma cell lines under stressing stimuli, such as (i) treatment with temozolomide (TMZ), dacarbazine (DTIC) and cisplatin; (ii) serum deprivation; (iii) tunicamycin, an UPR inducer. Prohibitin accumulated in the mitochondria of melanoma cells after cisplatin and tunicamycin treatment and its de novo accumulation led to chemoresistance melanoma cell lines. In contrast, PHB knock-down sensitized melanoma cells to cisplatin and tunicamycin treatment. We conclude that PHB participates in the survival of cells exposed to different stress stimuli, and can therefore serve as a target for the sensitization of melanoma cells to chemotherapy.

Docosahexaenoic Acid Modulates a HER2-Associated Lipogenic Phenotype, Induces Apoptosis, and Increases Trastuzumab Action in HER2-Overexpressing Breast Carcinoma Cells.

In breast cancer, lipid metabolic alterations have been recognized as potential oncogenic stimuli that may promote malignancy. To investigate whether the oncogenic nature of lipogenesis closely depends on the overexpression of HER2 protooncogene, the normal breast cell line, HB4a, was transfected with HER2 cDNA to obtain HER2-overexpressing HB4aC5.2 cells. Both cell lines were treated with trastuzumab and docosahexaenoic acid. HER2 overexpression was accompanied by an increase in the expression of lipogenic genes involved in uptake (CD36), transport (FABP4), and storage (DGAT) of exogenous fatty acids (FA), as well as increased activation of "de novo" FA synthesis (FASN). We further investigate whether this lipogenesis reprogramming might be regulated by mTOR/PPARγ pathway. Inhibition of the mTORC1 pathway markers, p70S6 K1, SREBP1, and LIPIN1, as well as an increase in DEPTOR expression (the main inhibitor of the mTOR) was detected in HB4aC5.2. Based on these results, a PPARγ selective antagonist, GW9662, was used to treat both cells lines, and the lipogenic genes remained overexpressed in the HB4aC5.2 but not HB4a cells. DHA treatment inhibited all lipogenic genes (except for FABP4) in both cell lines yet only induced death in the HB4aC5.2 cells, mainly when associated with trastuzumab. Neither trastuzumab nor GW9662 alone was able to induce cell death. In conclusion, oncogenic transformation of breast cells by HER2 overexpression may require a reprogramming of lipogenic genetic that is independent of mTORC1 pathway and PPARγ activity. This reprogramming was inhibited by DHA.

Emerging targets for combination therapy in melanomas.

Cutaneous melanomas are often difficult to treat when diagnosed in advanced stages. Melanoma cells adapt to survive in extreme environmental conditions and are among the tumors with larger genomic instability. Here we discuss some intrinsic and extrinsic mechanisms of resistance of melanoma cells to both conventional and target therapies, such as autophagy, adaptation to endoplasmic reticulum stress, metabolic reprogramming, mechanisms of tumor repopulation and the role of extracellular vesicles in this later phenomenon. These biological processes are potentially targetable and thus provide a platform for research and discovery of new drugs for combination therapy to manage melanoma patient treatment.