No abstract

Over the past decades, several advances in cancer cell biology have led to relevant details about a phenomenon called "Warburg effect". Currently, it has been accepted that Warburg effect is not anymore compatible with all cancer cells, and thus the process of aerobic glycolysis is now challenged by the knowledge of a large number of cells presenting mitochondrial function. The energy metabolism of cancer cells is focused in the bioenergetic and biosynthetic pathways to meet the requirements of rapid proliferation. Changes in the metabolism of carbohydrate, amino acids and lipids have already been reported in cancer cells and might play relevant roles for cancer progression. To the best of our knowledge, mostly of these changes are established, mainly due to genetic reprogramming that leads to the transformation of a healthy into a cancerous cell. Indeed, several enzymes of high relevance for the energy are targets of oncogenes (ex. PI3K, HIF1 and Myc) and tumor suppressor proteins (ex. p53). As a consequence of the extensive study on cancer cell metabolism, some new therapeutic strategies have appeared that aim to interrupt the aberrant metabolism, as well as the influence of genetic reprogramming in cancer cells. In this perspective, we briefly review the cancer cell metabolism (carbohydrate, amino acid and lipid), and also describe oncogenes and tumor suppressors that affect cancer cell metabolism. We also discuss some potential candidates for target therapy to disrupt the main driven-force for cancer cell metabolism and proliferation.

Based on these results, we found that compound 12a promote ROS production, interfering with energy metabolism, cell viability and proliferation, and thus promoting an whole cell damage.

Photosensitizers (PS) are compounds that can generate reactive oxygen species under irradiation of appropriate light and are widely used in photodynamic therapy (PDT). Currently, topical PDT is an effective treatment for several skin diseases, including bacterial infections, fungal mycoses and psoriasis. In addition, PDT is also used to treat nonmelanoma skin cancer and can be a potential tool for melanoma, associated with other treatments. In this work, we evaluated the antitumor photoactivity of a new pyrene‐based PS (TPPy) by using the murine melanoma cell line (B16F10). The in vitro permeation/retention tests in porcine ear skin were also performed in order to evaluate the potential application of the PS for topical use in skin cancer. Moreover, to determine the toxicity in vivo, we used the Galleria mellonella as an alternative animal model of study. The results showed that TPPy is a promising PS for application in PDT, with potential antitumor photoactivity (IC50 6.5 μmol L‐1), absence of toxicity in the G. mellonella model at higher concentration (70.0 mmol L−1) and the accumulation tendency in the epidermis plus dermis sites (165.20 ± 4.12 ng cm−2).

Melanoma is one of the most dangerous skin cancers in the world. It accounts for 55% of all deaths associated with skin cancer. Researchers believe that skin cancer increases the risk of other cancers if not diagnosed early. Therefore, prompt and timely diagnosis of this disease is very important for the successful treatment of the patient. This system can detect melanoma lethal carcinoma from other skin lesions without the need for surgery, with a low cost, accuracy of about 98.88% and specificity 99%. In this article, a new, intelligent and accurate software (Delphi) system has been used to diagnose melanoma skin cancer. To detect malignant melanoma, the ABCDT rule, asymmetry (A), boundary (B), color (C), diameter (D) and textural variation (T) of the lesion are calculated and finally, an artificial neural network (ANN) is used to obtain an accurate result. The ANN with Multi-Layer Perceptron (MLP) contains the five extraction Characteristics (ABCDT) of lesions is used as inputs, two hidden layers, and two outputs. Very good results were obtained using this method. It was observed that for a dataset of 180 dermoscopic lesion images including 80 malignant melanomas, 20 benign melanomas and 80 nevus lesions. Due to its automatic recognition and ability to be installed on a computer, this system can be very useful for dermatologists as well as the general public.