Driver mutations in oncogenic pathways, rewiring of cellular metabolism and altered ROS homoeostasis are intimately connected hallmarks of cancer. Electrons derived from different metabolic processes are channelled into the mitochondrial electron transport chain (ETC) to fuel the oxidative phosphorylation process. Electrons leaking from the ETC can prematurely react with oxygen, resulting in the generation of reactive oxygen species (ROS). Several signalling pathways are affected by ROS, which act as second messengers controlling cell proliferation and survival. On the other hand, oncogenic pathways hijack the ETC, enhancing its ROS-producing capacity by increasing electron flow or by impinging on the structure and organisation of the ETC. In this review, we focus on the ETC as a source of ROS and its modulation by oncogenic pathways, which generates a vicious cycle that resets ROS levels to a higher homoeostatic set point, sustaining the cancer cell phenotype.

Reactive oxygen species (ROS) are important signaling molecules that act through the oxidation of nucleic acids, proteins, and lipids. Several hallmarks of cancer, including uncontrolled proliferation, angiogenesis, and genomic instability, are promoted by the increased ROS levels commonly found in tumor cells. To counteract excessive ROS accumulation, oxidative stress, and death, cancer cells tightly regulate ROS levels by enhancing scavenging enzymes, which are dependent on the reducing cofactor nicotinamide adenine dinucleotide phosphate (NADPH). This review focuses on mitochondrial ROS homeostasis with a description of six pathways of NADPH production in mitochondria and a discussion of the possible strategies of pharmacological intervention to selectively eliminate cancer cells by increasing their ROS levels.

Inactivating mutations of the tumor suppressor gene Liver Kinase B1 (LKB1) are frequently detected in non-small-cell lung cancer (NSCLC) and cervical carcinoma. Moreover, LKB1 expression is epigenetically regulated in several tumor types. LKB1 has an established function in the control of cell metabolism and oxidative stress. Clinical and preclinical studies support a role of LKB1 as a central modifier of cellular response to different stress-inducing drugs, suggesting LKB1 pathway as a highly promising therapeutic target. Loss of LKB1-AMPK signaling confers sensitivity to energy depletion and to redox homeostasis impairment and has been associated with an improved outcome in advanced NSCLC patients treated with chemotherapy. In this review, we provide an overview of the interplay between LKB1 and its downstream targets in cancer and focus on potential therapeutic strategies whose outcome could depend from LKB1.

The miR-200 family of microRNAs (miRNAs) includes miR-200a, miR-200b, miR-200c, miR-141 and miR-429, five evolutionarily conserved miRNAs that are encoded in two clusters of hairpin precursors located on human chromosome 1 (miR-200b, miR-200a and miR-429) and chromosome 12 (miR-200c and miR-141). The mature -3p products of the precursors are abundantly expressed in epithelial cells, where they contribute to maintaining the epithelial phenotype by repressing expression of factors that favor the process of epithelial-to-mesenchymal transition (EMT), a key hallmark of oncogenic transformation. Extensive studies of the expression and interactions of these miRNAs with cell signaling pathways indicate that they can exert both tumor suppressor- and pro-metastatic functions, and may serve as biomarkers of epithelial cancers. This review provides a summary of the role of miR-200 family members in EMT, factors that regulate their expression, and important targets for miR-200-mediated repression that are involved in EMT. The second part of the review discusses the potential utility of circulating miR-200 family members as diagnostic/prognostic biomarkers for breast, colorectal, lung, ovarian, prostate and bladder cancers.

Anti-VEGF therapy perturbs tumor metabolism, severely impairing oxygen, glucose, and ATP levels. In this study, we investigated the effects of anti-VEGF therapy in multiple experimental tumor models that differ in their glycolytic phenotypes to gain insights into optimal modulation of the metabolic features of this therapy. Prolonged treatments induced vascular regression and necrosis in tumor xenograft models, with highly glycolytic tumors becoming treatment resistant more rapidly than poorly glycolytic tumors. By PET imaging, prolonged treatments yielded an increase in both hypoxic and proliferative regions of tumors. A selection for highly glycolytic cells was noted and this metabolic shift was stable and associated with increased tumor aggressiveness and resistance to VEGF blockade in serially transplanted mice. Our results support the hypothesis that the highly glycolytic phenotype of tumor cells studied in xenograft models, either primary or secondary, is a cell-autonomous trait conferring resistance to VEGF blockade. The finding that metabolic traits of tumors can be selected by antiangiogenic therapy suggests insights into the evolutionary dynamics of tumor metabolism. Cancer Res; 75(1); 120-133. Ó2014 AACR.

Alessandro Vitale and Fabio Farinati equally contributed to this work.Prognosis and designing a treatment modality in patients with hepatocellular carcinoma (HCC) are extremely complex because, in most cases, this neoplasm is accompanied by the cirrhotic liver and other comorbidities. 1 Thus in such cases, tumour stage, the degree of liver function and general conditions of patients are the major deterministic factors. 2,3 A common and promising approach linking prognostic variables with therapeutic choice is to analyse large patient cohorts and, using treatment selection as the main endpoint, identify the fundamental treatment rules. An example of such a data-based approach is the HCC treatment schedule recently proposed by the Hong Kong Liver Cancer (HKLC) group. In this approach, Yau et al 4 applied an algorithm based on classification and regression tree statistical methodology to link the main treatment decision rules with HKLC tumour stages. The main limitation of this approach, however, was that the Key points• Using a large consecutive cohort of patients with hepatocellular carcinoma from Italy (n = 4,867), we showed that a clear therapeutic hierarchy exists irrespective of tumour stage, live function, patient general conditions and treatment period.• This therapeutic hierarchy, in order of survival benefit gain, follows liver transplantation, liver resection, ablation, intra-arterial therapies, systemic therapy and best supportive care.• The results of this study suggest that a personalized approach based on the therapeutic hierarchy concept should be pursued in the context of a multidisciplinary evaluation, for each patient with hepatocellular carcinoma, irrespective of the stage of the disease. AbstractBackground: The Italian Liver Cancer (ITA.LI.CA) prognostic system for patients with hepatocellular carcinoma (HCC) has recently been proposed and validated. We sought to explore the relationship among the ITA.LI.CA prognostic variables (ie tumour stage, functional score based on performance status and Child-Pugh score, and alpha-fetoprotein), treatment selection and survival outcome in HCC patients. Patients and Methods:We analysed 4,867 consecutive HCC patients undergoing six main treatment strategies (liver transplantation, LT; liver resection, LR; ablation, ABL; intra-arterial therapy, IAT; Sorafenib, SOR; and best supportive care, BSC) and enrolled during 2002-2015 in a multicenter Italian database. In order to control pretreatment imbalances in observed variables, a machine learning methodology was used and inverse probability of treatment weights (IPTW) was calculated. An IPTWadjusted multivariate survival model that included ITA.LI.CA prognostic variables, treatment period and treatment strategy was then developed. The survival benefit of HCC treatments was described as a hazard ratio (95% confidence interval), using BSC as a reference value and as predicted median survival.Results: After the IPTW, the six treatment groups became well balanced for most baseline characteristics. In the IPTW-adjust...

LKB1 is a key sensor of metabolic stress, including hypoxia and glucose deprivation, two features of the tumor microenvironment exacerbated by antiangiogenic therapy. We investigated the role of LKB1 as a potential predictive marker of sensitivity to bevacizumab in advanced non-small cell lung cancer (aNSCLC). We retrospectively analyzed LKB1 expression by IHC in 98 samples from 125 patients with aNSCLC, including 59 patients treated with chemotherapy and 39 treated with chemotherapy plus bevacizumab. IHC intensity was recoded in two classes (negative/weak vs. moderate/intense) and correlated with outcome according to treatment arm. Patient-derived tumor xenografts (PDXs) were used to investigate mechanisms involved in preclinical models. In the whole study population (125), median OS and PFS were 11.7 [95% confidence interval (CI), 9.1-15.3] and 6.7 (95% CI, 5.7-7.2) months, respectively. Differential impact of the marker on outcome of the 98 patients was highlighted according to the treatment. Patients with negative/weak LKB1 status did not have a statistically significant benefit from bevacizumab added to chemotherapy (HR for patients treated with bevacizumab: 0.89; 95% CI, 0.51-1.56; = 0.6803), whereas patients expressing moderate/intense LKB1 and receiving bevacizumab had significant lower risk of death compared with those not receiving bevacizumab (HR, 0.26; 95% CI, 0.10-0.64; = 0.0035). Loss of LKB1 was associated with reduced AMPK activation in PDXs and increased tumor necrosis following bevacizumab administration, highlighting impaired control of the metabolic stress caused by this antiangiogenic drug. Our data hint at a possible predictive impact of LKB1 expression in patients with aNSCLC treated with chemotherapy plus bevacizumab. .

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