IL-8 Secreted by Gastric Epithelial Cells Infected with Helicobacter pylori CagA Positive Strains Is a Chemoattractant for Epstein-Barr Virus Infected B Lymphocytes.

Helicobacter pylori and EBV are considered the main risk factors in developing gastric cancer. Both pathogens establish life-lasting infections and both are considered carcinogenic in humans. Different lines of evidence support that both pathogens cooperate to damage the gastric mucosa. Helicobacter pylori CagA positive virulent strains induce the gastric epithelial cells to secrete IL-8, which is a potent chemoattractant for neutrophils and one of the most important chemokines for the bacterium-induced chronic gastric inflammation. EBV is a lymphotropic virus that persists in memory B cells. The mechanism by which EBV reaches, infects and persists in the gastric epithelium is not presently understood. In this study, we assessed whether Helicobacter pylori infection would facilitate the chemoattraction of EBV-infected B lymphocytes. We identified IL-8 as a powerful chemoattractant for EBV-infected B lymphocytes, and CXCR2 as the main IL-8 receptor whose expression is induced by the EBV in infected B lymphocytes. The inhibition of expression and/or function of IL-8 and CXCR2 reduced the ERK1/2 and p38 MAPK signaling and the chemoattraction of EBV-infected B lymphocytes. We propose that IL-8 at least partially explains the arrival of EBV-infected B lymphocytes to the gastric mucosa, and that this illustrates a mechanism of interaction between Helicobacter pylori and EBV.

Immunotherapy Options for Acral Melanoma, A fast-growing but Neglected Malignancy.

Melanoma is the deadliest form of skin cancer. It is classified as cutaneous and non-cutaneous, with the former characterized by developing in sun-exposed areas of the skin, UV-light radiation being its most important risk factor and ordinarily affecting fair skin populations. In recent years, the incidence of melanoma has been increasing in populations with darker complexion, for example, Hispanics, in which acral melanoma is highly prevalent. The WHO estimates that the incidence and mortality of melanoma will increase by more than 60% by 2040, particularly in low/medium income countries. Acral melanoma appears in the palms, soles and nails, and because of these occult locations, it is often considered different from other cutaneous melanomas even though it also originates in the skin. Acral melanoma is very rare in Caucasian populations and is often not included from genetic analysis and clinical trials. In this review, we present the worldwide epidemiology of acral melanoma; we summarize its genetic characterization and point out important signaling pathways for targeted therapy. We also discuss how genetic analyses have shown that acral melanoma carries a sufficient mutational load and neoantigen formation to be targeted by the immune system, arguing for a potential benefit with novel immunotherapeutic strategies, alone or combined with targeted therapy. This is important because chemotherapy remains the first-line treatment in non-developed nations despite a disheartening response. In summary, the increased incidence and mortality of acral melanoma in low/medium income countries calls for increasing our knowledge about its nature and therapeutic options and leveling off the asymmetric research conducted primarily on Caucasian populations.

Novel gene signatures for stage classification of the squamous cell carcinoma of the lung.

The squamous cell carcinoma of the lung (SCLC) is one of the most common types of lung cancer. As GLOBOCAN reported in 2018, lung cancer was the first cause of death and new cases by cancer worldwide. Typically, diagnosis is made in the later stages of the disease with few treatment options available. The goal of this work was to find some key components underlying each stage of the disease, to help in the classification of tumor samples, and to increase the available options for experimental assays and molecular targets that could be used in treatment development. We employed two approaches. The first was based in the classic method of differential gene expression analysis, network analysis, and a novel concept known as network gatekeepers. The second approach was using machine learning algorithms. From our combined approach, we identified two sets of genes that could function as a signature to identify each stage of the cancer pathology. We also arrived at a network of 55 nodes, which according to their biological functions, they can be regarded as drivers in this cancer. Although biological experiments are necessary for their validation, we proposed that all these genes could be used for cancer development treatments.

Multivariate Entropy Characterizes the Gene Expression and Protein-Protein Networks in Four Types of Cancer.

There is an important urgency to detect cancer at early stages to treat it, to improve the patients' lifespans, and even to cure it. In this work, we determined the entropic contributions of genes in cancer networks. We detected sudden changes in entropy values in melanoma, hepatocellular carcinoma, pancreatic cancer, and squamous lung cell carcinoma associated to transitions from healthy controls to cancer. We also identified the most relevant genes involved in carcinogenic process of the four types of cancer with the help of entropic changes in local networks. Their corresponding proteins could be used as potential targets for treatments and as biomarkers of cancer.