Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), infects one third of the world's population. Among these infections, clinical isolates belonging to the W-Beijing appear to be emerging, representing about 50% of Mtb isolates in East Asia, and about 13% of all Mtb isolates worldwide. In animal models, infection with W-Beijing strain, Mtb HN878, is considered “hypervirulent” as it results in increased mortality and causes exacerbated immunopathology in infected animals. We had previously shown the Interleukin (IL) -17 pathway is dispensable for primary immunity against infection with the lab adapted Mtb H37Rv strain. However, it is not known whether IL-17 has any role to play in protective immunity against infection with clinical Mtb isolates. We report here that lab adapted Mtb strains, such as H37Rv, or less virulent Mtb clinical isolates, such as Mtb CDC1551, do not require IL-17 for protective immunity against infection while infection with Mtb HN878 requires IL-17 for early protective immunity. Unexpectedly, Mtb HN878 induces robust production of IL-1β through a TLR-2-dependent mechanism, which supports potent IL-17 responses. We also show that the role for IL-17 in mediating protective immunity against Mtb HN878 is through IL-17 Receptor signaling in non-hematopoietic cells, mediating the induction of the chemokine, CXCL-13, which is required for localization of T cells within lung lymphoid follicles. Correct T cell localization within lymphoid follicles in the lung is required for maximal macrophage activation and Mtb control. Since IL-17 has a critical role in vaccine-induced immunity against TB, our results have far reaching implications for the design of vaccines and therapies to prevent and treat emerging Mtb strains. In addition, our data changes the existing paradigm that IL-17 is dispensable for primary immunity against Mtb infection, and instead suggests a differential role for IL-17 in early protective immunity against emerging Mtb strains.

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Transcriptional and epigenetic embryonic programs can be reactivated in cancer cells. As result, a specific subset of undifferentiated cells with stem-cells properties emerges and drives tumorigenesis. Recent findings have shown that ectoderm- and endoderm-derived tissues continue expressing stem-cells related transcription factors of the SOX-family of proteins such as SOX2 and SOX9 which have been implicated in the presence of cancer stem-like cells (CSCs) in tumors. Currently, there is enough evidence suggesting an oncogenic role for SOX9 in different types of human cancers. This review provides a summary of the current knowledge about the involvement of SOX9 in development and progression of cancer. Understanding the functional roles of SOX9 and clinical relevance is crucial for developing novel treatments targeting CSCs in cancer.

Breast cancer is the neoplasm with the highest number of deaths in women. Although the molecular mechanisms associated with the development of this tumor have been widely described, metastatic disease has a high mortality rate. In recent years, several studies show that microRNAs or miRNAs regulate complex processes in different biological systems including cancer. In the present work, we describe a group of 61 miRNAs consistently over-expressed in breast cancer (BC) samples that regulate the breast cancer transcriptome. By means of data mining from TCGA, miRNA and mRNA sequencing data corresponding to 1091 BC patients and 110 normal adjacent tissues were downloaded and a miRNA–mRNA network was inferred. Calculations of their oncogenic activity demonstrated that they were involved in the regulation of classical cancer pathways such as cell cycle, PI3K–AKT, DNA repair, and k-Ras signaling. Using univariate and multivariate analysis, we found that five of these miRNAs could be used as biomarkers for the prognosis of overall survival. Furthermore, we confirmed the over-expression of two of them in 56 locally advanced BC samples obtained from the histopathological archive of the National Cancer Institute of Mexico, showing concordance with our previous bioinformatic analysis.