Unveiling tumor immune evasion mechanisms: abnormal expression of transporters on immune cells in the tumor microenvironment

Metabolic gatekeepers: harnessing tumor-derived metabolites to optimize T cell-based immunotherapy efficacy in the tumor microenvironment

The tumor microenvironment (TME) orchestrates a complex interplay between tumor cells and immune cells, crucially modulating the immune response. This review delves into the pivotal role of metabolic reprogramming in the TME, highlighting how tumor-derived metabolites influence T lymphocyte functionality and the efficacy of cancer immunotherapies. Focusing on the diverse roles of these metabolites, we examine how lactate, lipids, amino acids, and other biochemical signals act not only as metabolic byproducts but as regulatory agents that can suppress or potentiate T cell-mediated immunity. By integrating recent findings, we underscore the dual impact of these metabolites on enhancing tumor progression and inhibiting immune surveillance. Furthermore, we propose innovative therapeutic strategies that target metabolic pathways to restore immune function within the TME. The insights provided in this review pave the way for the development of metabolic interventions aimed at enhancing the success of immunotherapies in oncology, offering new hope for precision medicine in the treatment of cancer.

A co-culture model to study modulators of tumor immune evasion through scalable arrayed CRISPR-interference screens

Cancer cells effectively evade immune surveillance, not only through the well-known PD-1/PD-L1 pathway but also via alternative mechanisms that impair patient response to immune checkpoint inhibitors. We present a novel co-culture model that pairs a reporter T-cell line with different melanoma cell lines that have varying immune evasion characteristics. We developed a scalable high-throughput lentiviral arrayed CRISPR interference (CRISPRi) screening protocol to conduct gene perturbations in both T-cells and melanoma cells, enabling the identification of genes that modulate tumor immune evasion. Our study functionally validates the co-culture model system and demonstrates the performance of the CRISPRi-screening protocol by modulating the expression of known regulators of tumor immunity. Together, our work provides a robust framework for future research aimed at systematically exploring mechanisms of tumor immune evasion.

Lung cancer cell-derived exosomes: progress on pivotal role and its application in diagnostic and therapeutic potential

Lung cancer is frequently detected in an advanced stage and has an unfavourable prognosis. Conventional therapies are ineffective for the treatment of metastatic lung cancer. While certain molecular targets have been identified as having a positive response, the absence of appropriate drug carriers prevents their effective utilization. Lung cancer cell-derived exosomes (LCCDEs) have gained attention for their involvement in the development of cancer, as well as their potential for use in diagnosing, treating, and predicting the outcome of lung cancer. This is due to their biological roles and their inherent ability to transport biomolecules from the donor cells. Lung cancer-associated cell-derived extracellular vesicles (LCCDEVs) have the ability to enhance cell proliferation and metastasis, influence angiogenesis, regulate immune responses against tumours during the development of lung cancer, control drug resistance in lung cancer treatment, and are increasingly recognised as a crucial element in liquid biopsy evaluations for the detection of lung cancer. Therapeutic exosomes, which possess inherent intercellular communication capabilities, are increasingly recognised as effective vehicles for targeted drug delivery in precision medicine for tumours. This is due to their exceptional biocompatibility, minimal immunogenicity, low toxicity, prolonged circulation in the bloodstream, biodegradability, and ability to traverse different biological barriers. Currently, multiple studies are being conducted to create new means of diagnosing and predicting outcomes using LCCDEs, as well as to develop techniques for utilizing exosomes as effective carriers for medication delivery. This paper provides an overview of the current state of lung cancer and the wide range of applications of LCCDEs. The encouraging findings and technologies suggest that the utilization of LCCDEs holds promise for the clinical treatment of lung cancer patients.

The Role of the Large T Antigen in the Molecular Pathogenesis of Merkel Cell Carcinoma

The large T antigen (LT) of the Merkel cell polyomavirus (MCPyV) is crucial for Merkel cell carcinoma (MCC), a rare but very aggressive form of neuroendocrine skin cancer. The clonal integration of MCPyV DNA into the host genome is a signature event of this malignancy. The resulting expression of oncogenes, including the small T (sT) antigen and a truncated form of the LT (truncLT), directly contribute to carcinogenesis. The truncation of the C-terminus of LT prevents the virus from replicating due to the loss of the origin binding domain (OBD) and the helicase domain. This precludes cytopathic effects that would lead to DNA damage and ultimately cell death. At the same time, the LxCxE motif in the N-terminus is retained, allowing truncLT to bind the retinoblastoma protein (pRb), a cellular tumor suppressor. The continuously inactivated pRb promotes cell proliferation and tumor development. truncLT exerts several classical functions of an oncogene: altering the host cell cycle, suppressing innate immune responses to viral DNA, causing immune escape, and shifting metabolism in favor of cancer cells. Given its central role in MCC, the LT is a major target for therapeutic interventions with novel approaches, such as immune checkpoint inhibition, T cell-based immunotherapy, and cancer vaccines.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma

BACKGROUND

Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers.

METHODS

10 machine-learning algorithms and their combinations were applied in this work. A stable Tstr-related score (TCs) was constructed to predict the outcomes and PD-1 blockade treatment response in ccRCC patients. A nomogram based on TCs for personalized prediction of patient prognosis was constructed. Functional enrichment analysis and TimiGP algorithm were used to explore the underlying role of Tstr in ccRCC. The key TCs-related gene was identified by comprehensive analysis, and the bioinformatics results were verified by immunohistochemistry using a tissue microarray.

RESULTS

A robust TCs was constructed and validated in four independent cohorts. TCs accurately predicted the prognosis and PD-1 blockade treatment response in ccRCC patients. The novel nomogram was able to precisely predict the outcomes of ccRCC patients. The underlying biological process of Tstr was related to acute inflammatory response and acute-phase response. Mast cells were identified to be involved in the role of Tstr as a protective factor in ccRCC. TNFS13B was shown to be the key TCs-related gene, which was an independent predictor of unfavorable prognosis. The protein expression analysis of TNFSF13B was consistent with the mRNA analysis results. High expression of TNFSF13B was associated with poor response to PD-1 blockade treatment.

CONCLUSIONS

This study provides a Tstr cell-related score for predicting outcomes and PD-1 blockade therapy response in ccRCC. Tstr cells may exert their pro-tumoral role in ccRCC, acting against mast cells, in the acute inflammatory tumor microenvironment. TNFSF13B could serve as a key biomarker related to TCs.