In the era of the rapid development of cancer immunotherapy, there is a high level of interest in the application of cell-released small vesicles that stimulate the immune system. As cell-derived nanovesicles, exosomes show great promise in cancer immunotherapy because of their immunogenicity and molecular transfer function. The cargoes carried on exosomes have been recently identified with improved technological advances and play functional roles in the regulation of immune responses. In particular, exosomes derived from tumor cells and immune cells exhibit unique composition profiles that are directly involved in anticancer immunotherapy. More importantly, exosomes can deliver their cargoes to targeted cells and thus influence the phenotype and immune-regulation functions of targeted cells. Accumulating evidence over the last decade has further revealed that exosomes can participate in multiple cellular processes contributing to cancer development and therapeutic effects, showing the dual characteristics of promoting and suppressing cancer. The potential of exosomes in the field of cancer immunotherapy is huge, and exosomes may become the most effective cancer vaccines, as well as targeted antigen/drug carriers. Understanding how exosomes can be utilized in immune therapy is important for controlling cancer progression; additionally, exosomes have implications for diagnostics and the development of novel therapeutic strategies. This review discusses the role of exosomes in immunotherapy as carriers to stimulate an anti-cancer immune response and as predictive markers for immune activation; furthermore, it summarizes the mechanism and clinical application prospects of exosome-based immunotherapy in human cancer.

Temozolomide (TMZ), an alkylating agent, is widely used for treating primary and recurrent high-grade gliomas. However, the efficacy of TMZ is often limited by the development of resistance. Recently, studies have found that TMZ treatment could induce autophagy, which contributes to therapy resistance in glioma. To enhance the benefit of TMZ in the treatment of glioblastomas, effective combination strategies are needed to sensitize glioblastoma cells to TMZ. In this regard, as autophagy could promote cell survival or autophagic cell death, modulating autophagy using a pharmacological inhibitor, such as chloroquine, or an inducer, such as rapamycin, has received considerably more attention. To understand the effectiveness of regulating autophagy in glioblastoma treatment, this review summarizes reports on glioblastoma treatments with TMZ and autophagic modulators from in vitro and in vivo studies, as well as clinical trials. Additionally, we discuss the possibility of using autophagy regulatory compounds that can sensitive TMZ treatment as a chemotherapy for glioma treatment.

Ferroptosis is an iron-dependent cell death process that plays important regulatory roles in the occurrence and development of cancers, including hepatocellular carcinoma (HCC). Moreover, the molecular events surrounding aberrantly expressed long non-coding RNAs (lncRNAs) that drive HCC initiation and progression have attracted increasing attention. However, research on ferroptosis-related lncRNA prognostic signature in patients with HCC is still lacking. In this study, the association between differentially expressed lncRNAs and ferroptosis-related genes, in 374 HCC and 50 normal hepatic samples obtained from The Cancer Genome Atlas (TCGA), was evaluated using Pearson’s test, thereby identifying 24 ferroptosis-related differentially expressed lncRNAs. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model were used to construct and validate a prognostic risk score model from both TCGA training dataset and GEO testing dataset (GSE40144). A nine-lncRNA-based signature (CTD-2033A16.3, CTD-2116N20.1, CTD-2510F5.4, DDX11-AS1, LINC00942, LINC01224, LINC01231, LINC01508, and ZFPM2-AS1) was identified as the ferroptosis-related prognostic model for HCC, independent of multiple clinicopathological parameters. In addition, the HCC patients were divided into high-risk and low-risk groups according to the nine-lncRNA prognostic signature. The gene set enrichment analysis enrichment analysis revealed that the lncRNA-based signature might regulate the HCC immune microenvironment by interfering with tumor necrosis factor α/nuclear factor kappa-B, interleukin 2/signal transducers and activators of transcription 5, and cytokine/cytokine receptor signaling pathways. The infiltrating immune cell subtypes, such as resting memory CD4(+) T cells, follicular helper T cells, regulatory T cells, and M0 macrophages, were all significantly different between the high-risk group and the low-risk group as indicated in Spearman’s correlation analysis. Moreover, a substantial increase in the expression of B7H3 immune checkpoint molecule was found in the high-risk group. Our findings provided a promising insight into ferroptosis-related lncRNAs in HCC and a personalized prediction tool for prognosis and immune responses in patients.

Artificial intelligence (AI) is a general term that refers to the use of a machine to imitate intelligent behavior for performing complex tasks with minimal human intervention, such as machine learning; this technology is revolutionizing and reshaping medicine. AI has considerable potential to perfect health-care systems in areas such as diagnostics, risk analysis, health information administration, lifestyle supervision, and virtual health assistance. In terms of immunotherapy, AI has been applied to the prediction of immunotherapy responses based on immune signatures, medical imaging and histological analysis. These features could also be highly useful in the management of cancer immunotherapy given their ever-increasing performance in improving diagnostic accuracy, optimizing treatment planning, predicting outcomes of care and reducing human resource costs. In this review, we present the details of AI and the current progression and state of the art in employing AI for cancer immunotherapy. Furthermore, we discuss the challenges, opportunities and corresponding strategies in applying the technology for widespread clinical deployment. Finally, we summarize the impact of AI on cancer immunotherapy and provide our perspectives about underlying applications of AI in the future.

Cancer-associated fibroblasts (CAFs) plays an essential role in cancer cell growth, metabolism and immunoreaction. Autophagy is an intracellular self-degradative process that balances cell energy source and regulates tissue homeostasis. Targeting autophagy has gained interest with multiple preclinical and clinical trials, such as the pharmacological inhibitor chloroquine or the inducer rapamycin, especially in exploiting its ability to modulate the secretory capability of CAFs to enhance drug delivery or inhibit it to prevent its influence on cancer cell chemoresistance. In this review, we summarize the reports on autophagy in cancer-associated fibroblasts by detailing the mechanism and role of autophagy in CAFs, including the hypoxic-autophagy positive feedback cycle, the metabolic cross-talk between CAFs and tumors induced by autophagy, CAFs secreted cytokines promote cancer survival by secretory autophagy, CAFs autophagy-induced EMT, stemness, senescence and treatment sensitivity, as well as the research of antitumor chemicals, miRNAs and lncRNAs. Additionally, we discuss the evidence of molecules in CAFs that are relevant to autophagy and the contribution to sensitive treatments as a potential target for cancer treatment.

Background: LncRNAs have been shown to play essential roles in cancer therapeutic response. However, the detailed mechanism of lncRNAs in temozolomide (TMZ) resistance in glioblastoma (GBM) remain to be elucidated. Methods: To elucidate the mechanism maintaining TMZ resistance, we constructed two TMZ-resistant GBM cell lines (T98G-R/U118-R). LncRNAs from four public datasets were reanalyzed, and the candidate lncRNA ADAMTS9-AS2 was evaluated in TMZ-treated GBM patients and in vitro cell lines. Results: Reanalysis of lncRNA expression profiles identified ADAMTS9-AS2 as significantly overexpressed in TMZ-resistant GBM cells and as positively associated with the IC₅₀ of TMZ in GBM cells. Overexpression of ADAMTS9-AS2 was also significantly associated with poor TMZ response and shorter progression-free survival (PFS) in TMZ-treated GBM patients. Knockdown of ADAMTS9-AS2 inhibited proliferation and attenuated the IC₅₀ of TMZ, as well as mitigating invasion and migration in TMZ-resistant GBM cells. Subsequent investigations indicated that reduced expression of ADAMTS9-AS2 significantly suppressed expression of the FUS protein, which was predicted as a direct substrate of ADAMTS9-AS2. Expression trends of FUS were directly correlated with those of ADAMTS9-AS2, as shown by increasing concentrations and prolonged treatment with TMZ. RNA pull-down and RIP assays indicated that both endogenous and exogenous ADAMTS9-AS2 directly binds to the RRM and Znf_RanBP2 domains of FUS, consequently increasing FUS protein expression. Knockdown of ADAMTS9-AS2 reduced the half-life of FUS and decreased FUS protein stability via K48 ubiquitin degradation. Moreover, the E3 ubiquitin-protein ligase MDM2 interacts with and down regulates FUS, while the RRM and Znf_RanBP2 domains of FUS facilitate its binding with MDM2. ADAMTS9-AS2 decreased the interaction between MDM2 and FUS, which mediates FUS K48 ubiquitination. Additionally, knockdown of the ADAMTS9-AS2/FUS signaling axis significantly alleviated progression and metastasis in TMZ-resistant cells. Conclusion: ADAMTS9-AS2 possessed a novel function that promotes TMZ resistance via upregulating the FUS/MDM2 axis in GBM cells. The RRM or Znf_RanBP2 domains of FUS facilitate the combination of ADAMTS9-AS2 and FUS, competitively inhibiting MDM2-dependent FUS K48 ubiquitination and resulting in enhanced FUS stability and TMZ resistance. Our results suggest that the ADAMTS9-AS2/FUS/MDM2 axis may represent a suitable prognostic biomarker and a potential target in TMZ-resistant GBM therapy.