Although high-risk human papillomaviruses (HPVs) are an important risk factor in the etiopathogenesis of cervical cancer, increasing evidence suggests that the ability to avoid immune surveillance seems to be linked to the transforming potential of HPV and a rapid progression to cancer. In other cancer models, IL-10 contributes to impair anti-tumor immune response either by downregulating human leukocyte antigen Class I (HLA-I) expression or by increasing HLA-G expression. To comprehend how these alterations could contribute to evasion of immune surveillance in cervical cancer, we analyzed HLA-I, HLA-G and IL-10 expressions by immunohistochemistry in 63 biopsies from patients with cervical intraepithelial neoplasia III (CIN-III) and cervical cancer. Immunohistochemistry showed absent or weak HLA-I expression in 50/59 cases. In these cases, a high percentage had loss of heterozygosis. IL-10 and HLA-G expression were observed in 46.6 and 27.6% of cases, respectively. Concurrent upregulation of IL-10 was found in 87.5% of HLA-G positive cases (p = 0.000). Similarly, a significant association between IL-10 expression and HLA-I downregulation was found (p = 0.028). Finally, we observed higher HLA-G expression in patients with HLA-I downregulation than in those with normal HLA-I expression (p = 0.004). Our results suggest that, in cervical cancer, the IL-10 expression may induce an immunosuppressive environment by upregulating HLA-G expression and downregulating HLA class I expression.

Although the immune system provides protection from cancer by means of immunosurveillance, which serves a major function in eliminating cancer cells, it may also lead to cancer immunoediting, molding tumor immunogenicity. Cancer cells exploit several molecular mechanisms to thwart immune-mediated death by disabling cellular components of the immune system associated with tumor recognition and rejection. Human leukocyte antigen (HLA) molecules are mandatory for the immune recognition and subsequent killing of neoplastic cells by the immune system, as tumor antigens must be presented in an HLA-restricted manner to be recognized by T-cell receptors. Impaired HLA-I expression prevents the activation of cytotoxic immune mechanisms, whereas impaired HLA-II expression affects the antigen-presenting capability of antigen presenting cells. Aberrant HLA-G expression by cancer cells favors immune escape by inhibiting the activities of virtually all immune cells. The development of cancer therapies based on T-cell activation must consider these HLA-associated immune evasion mechanisms, as alterations in their expression occur early and frequently in the majority of types of cancer, and have an adverse impact on the clinical response to immunotherapy. Herein, the concept of altered HLA expression as a mechanism exploited by tumors to escape immune control and induce an immunosuppressive environment is reviewed. A number of novel clinical immunotherapeutic approaches used for cancer treatment are also reviewed, and strategies for overcoming the limitations of these immunotherapeutic interventions are proposed.

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Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.