Jun N-terminal kinases or JNKs have been shown to be involved in a wide array of signaling events underlying tumorigenesis and tumor progression. Through its interaction with a diverse set of signaling proteins and adaptors, JNKs regulate cell proliferation, invasive migration, therapy resistance, and programmed cell death. JNKs have been shown to play a role in apoptotic as well as non-apoptotic programmed cell death mechanisms including those of necroptosis, ferroptosis, pyroptosis, and autophagy. Most of the tumorigenic regulatory functions of JNKs can be related to their ability to module cell death via these programmed cell death mechanisms. JNKs stimulate or inhibit cell death in a context-dependent manner by stimulating the expression of specific genes as well as by modulating the activities of pro- and anti-apoptotic proteins through distinct phosphorylation events. This review summarizes our current understanding of the role of JNK in programmed cell death and its impact on cancer growth, progression, and therapy.

The cellular signaling network involves co-ordinated regulation of numerous signaling molecules that aid the maintenance of cellular as well as organismal homeostasis. Aberrant signaling plays a major role in the pathophysiology of many diseases. Recent studies have unraveled the superfamily of long non-coding RNAs (lncRNAs) as critical signaling nodes in diverse signaling networks. Defective signaling by lncRNAs is emerging as a causative factor underlying the pathophysiology of many diseases. LncRNAs have been shown to be involved in the multiplexed regulation of diverse pathways through both genetic and epigenetic mechanisms. They can serve as decoys, guides, scaffolds, and effector molecules to regulate cell signaling. In comparison with the other classes of RNAs, lncRNAs possess unique structural modifications that contribute to their diversity in modes of action within the nucleus and cytoplasm. In this review, we summarize the structure and function of lncRNAs as well as their vivid mechanisms of action. Further, we provide insights into the role of lncRNAs in the pathogenesis of four major disease paradigms, namely cardiovascular diseases, neurological disorders, cancers, and the metabolic disease, diabetes mellitus. This review serves as a succinct treatise that could open windows to investigate the role of lncRNAs as novel therapeutic targets.

Tumor-suppressive effects of resveratrol have been shown in various types of cancer. However, regulation of tumor microenvironment by resveratrol is still unclear. Recent findings suggest resveratrol can potentiate its tumor-suppressive effect through modulation of the signaling pathways of cellular components (fibroblasts, macrophages and T cells). Also, studies have shown that resveratrol can suppress malignant phenotypes of cancer cells acquired in response to stresses of the tumor microenvironment, such as hypoxia, oxidative stress and inflammation. We discuss the effects of resveratrol on cancer cells in stress environment of tumors as well as interactions between cancer cells and non-cancer cells in this review.

Although hypoxia has been shown to reprogram cancer cells toward glycolytic shift, the identity of extrinsic stimuli that induce metabolic reprogramming independent of hypoxia, especially in ovarian cancer, is largely unknown. In this study, we use patient-derived ovarian cancer cells and high-grade serous ovarian cancer cell lines to demonstrate that lysophosphatidic acid (LPA), a lipid growth factor and GPCR ligand whose levels are substantially increased in ovarian cancer patients, triggers glycolytic shift in ovarian cancer cells. Inhibition of the G protein α-subunit Gαi2 disrupted LPA-stimulated aerobic glycolysis. LPA stimulated a pseudohypoxic response via Rac-mediated activation of NADPH oxidase and generation of reactive oxygen species, resulting in activation of HIF1α. HIF1α in turn induced expression of glucose transporter-1 and the glycolytic enzyme hexokinase-2 (HKII). Treatment of mice bearing ovarian cancer xenografts with an HKII inhibitor, 3-bromopyruvate, attenuated tumor growth and conferred a concomitant survival advantage. These studies reveal a critical role for LPA in metabolic reprogramming of ovarian cancer cells and identify this node as a promising therapeutic target in ovarian cancer. Significance: These findings establish LPA as a potential therapeutic target in ovarian cancer, revealing its role in the activation of HIF1α-mediated metabolic reprogramming in this disease. Cancer Res; 78(8); 1923–34. ©2018 AACR.

Cancer represents one of the diseases with the highest mortality rate worldwide. The burden of cancer continues to increase, not only affecting the health-related quality of life of patients but also causing an elevated global financial impact. The complexity and heterogeneity of cancer pose significant challenges in research and clinical practice, contributing to increase the failure rate of clinical trials for antitumoral drugs. This is partially due to the fact that preclinical models still present important limitations in faithfully recapitulating human tumors to serve as reliable indicators of drug effectiveness. Up to now, research and development strategies employ expensive animal models (including the so-called “humanized mice”) that not only raise ethical concerns, but also frequently fail to accurately predict responses to anticancer drugs because they do not faithfully replicate human physiology as well as the patient's tumor microenvironment. On the other side, traditional two-dimensional (2D) cell cultures fail to adequately reproduce the structural organization of tumor and the cellular heterogeneity found in vivo. The growing necessity to develop more accurate cancer models has increasingly emphasized the importance of three-dimensional (3D) in vitro cell cultures, such as cancer-derived spheroids and organoids, as promising alternatives to bridge the gap between 2D and animal models. In this review, we provide a brief overview focusing on 3D in vitro cell cultures as preclinical models capable of properly reproducing the tissue organization, biological composition, and complexity of in vivo tumors in a fine-tuned microenvironment. Despite their limitations, these models collectively enhance our understanding of the mechanisms underlying cancer and may offer the potential for a more reliable assessment of drug efficacy before clinical testing and, consequently, improve therapeutic outcomes for cancer patients.