Biomarker Research最新文献

Gene therapy utilizes nucleic acid drugs to treat diseases, encompassing gene supplementation, gene replacement, gene silencing, and gene editing. It represents a distinct therapeutic approach from traditional medications and introduces novel strategies for genetic disorders. Over the past two decades, significant advancements have been made in the field of gene therapy, leading to the approval of various gene therapy drugs. Gene therapy was initially employed for treating genetic diseases and cancers, particularly monogenic conditions classified as orphan diseases due to their low prevalence rates; however, polygenic or complex diseases exhibit higher incidence rates within populations. Extensive research on the etiology of polygenic diseases has unveiled new therapeutic targets that offer fresh opportunities for their treatment. Building upon the progress achieved in gene therapy for monogenic diseases and cancers, extending its application to polygenic or complex diseases would enable targeting a broader range of patient populations. This review aims to discuss the strategies of gene therapy, methods of gene editing (mainly CRISPR-CAS9), and carriers utilized in gene therapy, and highlight the applications of gene therapy in polygenic or complex diseases focused on applications that have either entered clinical stages or are currently undergoing clinical trials.

Radiotherapy (RT) controls local lesions, meantime it has the capability to induce systemic response to inhibit distant, metastatic, non-radiated tumors, which is referred to as the "abscopal effect". It is widely recognized that radiotherapy can stimulate systemic immune response. This provides a compelling theoretical basis for the combination of immune therapy combined with radiotherapy(iRT). Indeed, this phenomenon has also been observed in clinical treatment, bringing significant clinical benefits to patients, and a series of basic studies are underway to amplify this effect. However, the molecular mechanisms of immune response induced by RT, determination of the optimal treatment regimen for iRT, and how to amplify the abscopal effect. In order to amplify and utilize this effect in clinical management, these key issues require to be well addressed; In this review, we comprehensively summarize the growing consensus and emphasize the emerging limitations of enhancing the abscopal effect with radiotherapy or immunotherapy. Finally, we discuss the prospects and barriers to the current clinical translational applications.

Immunotherapy has shown promising anti-tumor effects across various tumors, yet it encounters challenges from the inhibitory tumor immune microenvironment (TIME). Infiltrating regulatory T cells (Tregs) are important contributors to immunosuppressive TIME, limiting tumor immunosurveillance and blocking effective anti-tumor immune responses. Although depletion or inhibition of systemic Tregs enhances the anti-tumor immunity, autoimmune sequelae have diminished expectations for the approach. Herein, we summarize emerging strategies, specifically targeting tumor-infiltrating (TI)-Tregs, that elevate the capacity of organisms to resist tumors by reprogramming their phenotype. The regulatory mechanisms of Treg reprogramming are also discussed as well as how this knowledge could be utilized to develop novel and effective cancer immunotherapies.

Tumor cells possess complex immune evasion mechanisms to evade immune system attacks, primarily through metabolic reprogramming, which significantly alters the tumor microenvironment (TME) to modulate immune cell functions. When a tumor is sufficiently immunogenic, it can activate cytotoxic T-cells to target and destroy it. However, tumors adapt by manipulating their metabolic pathways, particularly glucose, amino acid, and lipid metabolism, to create an immunosuppressive TME that promotes immune escape. These metabolic alterations impact the function and differentiation of non-tumor cells within the TME, such as inhibiting effector T-cell activity while expanding regulatory T-cells and myeloid-derived suppressor cells. Additionally, these changes lead to an imbalance in cytokine and chemokine secretion, further enhancing the immunosuppressive landscape. Emerging research is increasingly focusing on the regulatory roles of non-tumor cells within the TME, evaluating how their reprogrammed glucose, amino acid, and lipid metabolism influence their functional changes and ultimately aid in tumor immune evasion. Despite our incomplete understanding of the intricate metabolic interactions between tumor and non-tumor cells, the connection between these elements presents significant challenges for cancer immunotherapy. This review highlights the impact of altered glucose, amino acid, and lipid metabolism in the TME on the metabolism and function of non-tumor cells, providing new insights that could facilitate the development of novel cancer immunotherapies.

Immunotherapy has emerged as a pivotal modality in cancer treatment, with immune checkpoint inhibitors effectively combating malignancies by impeding crucial pathways within the immune system and stimulating patients' immune responses. Soluble forms of immune checkpoints exhibit a remarkable diversity and can be readily tracked in circulation, holding immense potential as biomarkers for cancer treatment. An increasing number of studies focused on soluble immune checkpoints in cancer have emerged thanks to technological advancements. In this systematic review, we comprehensively summarized the recent studies on soluble immune checkpoints in human cancer risk prediction, outcome prediction, therapeutic applications, and potential molecular mechanisms, which demonstrated the promising future of soluble immune checkpoints in clinical applications. The clinical relevance of soluble immune checkpoints has been recognized in multiple cancers, yet the therapeutic applications and mechanisms remain obscure. Interpreting the impacts and mechanisms of soluble immune checkpoints could shed a light on the novel strategies of cancer screening, treatments, and outcome prediction.