Autophagic flux restoration enhances the antitumor efficacy of tumor infiltrating lymphocytes

The STING-activating nanofactory relieves T cell exhaustion in Mn-based tumor immunotherapy by regulating mitochondrial dysfunction

Manganese-based STING-activating tumor immunotherapy faces limitations due to T cell exhaustion. Mitochondrial dysfunction is a key factor contributing to T cell exhaustion. Modulating mitochondrial function during manganese-based immunotherapy offers a promising strategy to reverse T cell exhaustion. Spermidine (SPD) enhances mitochondrial function in T cells, making the co-delivery of Mn and SPD a potential therapeutic approach. However, intravenous co-delivery is hindered by the rapid formation of MnO(OH)₂ precipitates. In this study, liposomes were employed as nano-reactors to facilitate the reaction between pre-loaded Mn²⁺ and O₂ in the presence of SPD, forming MnO(OH)₂ precipitates within the liposomes. These liposomes function as nanofactories, further processing MnO(OH)₂ under the regulation of the tumor microenvironment (TME) and delivering Mn, SPD, and O₂. Beyond activating the STING pathway in dendritic cells, L@Mn@SPD alleviates TME hypoxia and effectively reverses CD8⁺ T cell exhaustion. In vivo, L@Mn@SPD achieved a 2.44-fold increase in tumor suppression compared to MnCl₂, along with a 47% rise in CD8⁺ T cell infiltration, a 62.1% reduction in PD-1 expression, and a 110% increase in IFN-γ secretion. This STING-activating nanofactory provides a promising strategy to enhance manganese-based tumor immunotherapy by addressing mitochondrial dysfunction in exhausted T cells.

Emerging dimensions of autophagy in melanoma

Macroautophagy/autophagy has previously been regarded as simply a way for cells to deal with nutrient emergency. But explosive work in the last 15 years has given increasingly new knowledge to our understanding of this process. Many of the functions of autophagy that are unveiled from recent studies, however, cannot be reconciled with this conventional view of cell survival but, instead, point to autophagy being integrally involved at a deeper level of cell biology, playing a critical role in maintaining homeostasis and promoting an integrated stress/immune response. The new appreciation of the role of autophagy in the evolutionary trajectory of cancer and cancer interaction with the immune system provides a mechanistic framework for understanding the clinical benefits of autophagy-based therapies. Here, we examine current knowledge of the mechanisms and functions of autophagy in highly plastic and aggressive melanoma as a model disease of human malignancy, while highlighting emerging dimensions indicating that autophagy is at play beyond its classical face.Abbreviation: AMBRA1: autophagy and beclin 1 regulator 1; AMPK: AMP-activated protein kinase; ATF4: activating transcription factor 4; ATG: autophagy related; BRAF: B-Raf proto-oncogene, serine/threonine kinase; CAFs: cancer-associated fibroblasts; CCL5: C-C motif chemokine ligand 5; CQ: chloroquine; CRISPR: clustered regularly interspaced short palindromic repeats; CTLA4: cytotoxic T-lymphocyte associated protein 4; CTL: cytotoxic T lymphocyte; DAMPs: danger/damage-associated molecular patterns; EGFR: epidermal growth factor receptor; EIF2A/eIF2α: eukaryotic translation initiation factor 2A; EIF2AK3/PERK: eukaryotic translation initiation factor 2 alpha kinase 3; ER: endoplasmic reticulum; FITM2: fat storage inducing transmembrane protein 2; HCQ: hydroxychloroquine; ICB: immune checkpoint blockade; ICD: immunogenic cell death; LDH: lactate dehydrogenase; MAPK: mitogen-activated protein kinase; MTORC1: mechanistic target of rapamycin kinase complex 1; NDP52: nuclear dot protein 52; NFKB/NF-κ B: nuclear factor kappa B; NBR1: the neighbor of BRCA1; NK: natural killer; NRF1: nuclear respiratory factor 1; NSCLC: non-small-cell lung cancer; OPTN: optineurin; PDAC: pancreatic ductal adenocarcinoma; PDCD1/PD-1: programmed cell death 1; PPT1: palmitoyl-protein thioesterase 1; PTEN: phosphatase and tensin homolog; PTK2/FAK1: protein tyrosine kinase 2; RAS: rat sarcoma; SQSTM1/p62: sequestosome 1; STK11/LKB1: serine/threonine kinase 11; TAX1BP1: Tax1 binding protein 1; TFEB: transcription factor EB; TGFB/TGF-β: transforming growth factor beta; TMB: tumor mutational burden; TME: tumor microenvironment; TSC1: TSC complex subunit 1; TSC2: TSC complex subunit 2; ULK1: unc-51 like autophagy activating kinase 1; UVRAG: UV radiation resistance associated.

Association between radiomics features of DCE-MRI and CD8+ and CD4+ TILs in advanced gastric cancer

Objective: The aim of this investigation was to explore the correlation between the levels of tumor-infiltrating CD8⁺ and CD4⁺ T cells and the quantitative pharmacokinetic parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with advanced gastric cancer. Methods: We retrospectively analyzed the data of 103 patients with histopathologically confirmed advanced gastric cancer (AGC). Three pharmacokinetic parameters, K_ep, K^trans, and V_e, and their radiomics characteristics were obtained by Omni Kinetics software. Immunohistochemical staining was used to determine CD4⁺ and CD8⁺ TILs. Statistical analysis was subsequently performed to assess the correlation between radiomics characteristics and CD4⁺ and CD8⁺ TIL density. Results: All patients included in this study were finally divided into either a CD8⁺ TILs low-density group (n = 51) (CD8⁺ TILs < 138) or a high-density group (n = 52) (CD8⁺ TILs ≥ 138), and a CD4⁺ TILs low-density group (n = 51) (CD4⁺ TILs < 87) or a high-density group (n = 52) (CD4⁺ TILs ≥ 87). ClusterShade and Skewness based on K_ep and Skewness based on K^trans both showed moderate negative correlation with CD8⁺ TIL levels (r = 0.630-0.349, p < 0.001), with ClusterShade based on K_ep having the highest negative correlation (r = -0.630, p < 0.001). Inertia-based K_ep showed a moderate positive correlation with the CD4⁺ TIL level (r = 0.549, p < 0.001), and the Correlation based on K_ep showed a moderate negative correlation with the CD4⁺ TIL level, which also had the highest correlation coefficient (r = -0.616, p < 0.001). The diagnostic efficacy of the above features was assessed by ROC curves. For CD8⁺ TILs, ClusterShade of K_ep had the highest mean area under the curve (AUC) (0.863). For CD4⁺ TILs, the Correlation of K_ep had the highest mean AUC (0.856). Conclusion: The radiomics features of DCE-MRI are associated with the expression of tumor-infiltrating CD8⁺ and CD4⁺ T cells in AGC, which have the potential to noninvasively evaluate the expression of CD8⁺ and CD4⁺ TILs in AGC patients.

Autoimmunity and Carcinogenesis: Their Relationship under the Umbrella of Autophagy

The immune system and autophagy share a functional relationship. Both innate and adaptive immune responses involve autophagy and, depending on the disease's origin and pathophysiology, it may have a detrimental or positive role on autoimmune disorders. As a "double-edged sword" in tumors, autophagy can either facilitate or impede tumor growth. The autophagy regulatory network that influences tumor progression and treatment resistance is dependent on cell and tissue types and tumor stages. The connection between autoimmunity and carcinogenesis has not been sufficiently explored in past studies. As a crucial mechanism between the two phenomena, autophagy may play a substantial role, though the specifics remain unclear. Several autophagy modifiers have demonstrated beneficial effects in models of autoimmune disease, emphasizing their therapeutic potential as treatments for autoimmune disorders. The function of autophagy in the tumor microenvironment and immune cells is the subject of intensive study. The objective of this review is to investigate the role of autophagy in the simultaneous genesis of autoimmunity and malignancy, shedding light on both sides of the issue. We believe our work will assist in the organization of current understanding in the field and promote additional research on this urgent and crucial topic.