STING Agonist-Loaded Nanoparticles Promotes Positive Regulation of Type I Interferon-Dependent Radioimmunotherapy in Rectal Cancer.

Hypoxia-associated radioresistance in rectal cancer (RC) has severely hampered the response to radioimmunotherapy (iRT), necessitating innovative strategies to enhance RC radiosensitivity and improve iRT efficacy. Here, a catalytic radiosensitizer, DMPtNPS, and a STING agonist, cGAMP, are integrated to overcome RC radioresistance and enhance iRT. DMPtNPS promotes efficient X-ray energy transfer to generate reactive oxygen species, while alleviating hypoxia within tumors, thereby increasing radiosensitivity. Mechanistically, the transcriptomic and immunoassay analysis reveal that the combination of DMPtNPS and RT provokes bidirectional regulatory effects on the immune response, which may potentially reduce the antitumor efficacy. To mitigate this, cGAMP is loaded into DMPtNPS to reverse the negative impact of DMPtNPS and RT on the tumor immune microenvironment (TiME) through the type I interferon-dependent pathway, which promotes cancer immunotherapy. In a bilateral tumor model, the combination treatment of RT, DMPtNPS@cGAMP, and αPD-1 demonstrates a durable complete response at the primary site and enhanced abscopal effect at the distant site. This study highlights the critical role of incorporating catalytic radiosensitizers and STING agonists into the iRT approach for RC.

Methylglyoxal from gut microbes boosts radiosensitivity and radioimmunotherapy in rectal cancer by triggering endoplasmic reticulum stress and cGAS-STING activation.

BACKGROUND: Preoperative radiation therapy (preRT) is a fundamental aspect of neoadjuvant treatment for rectal cancer (RC), but the response to this treatment remains unsatisfactory. The combination of radiation therapy (RT) and immunotherapy (iRT) presents a promising approach to cancer treatment, though the underlying mechanisms are not yet fully understood. The gut microbiota may influence the response to RT and immunotherapy. Therefore, we aimed to identify the metabolism of gut microbiota to reverse radioresistance and enhance the efficacy of iRT. METHODS: Fecal and serum samples were prospectively collected from patients with locally advanced rectal cancer (LARC) who had undergone pre-RT treatment. Candidate gut microbiome-derived metabolites linked with radiosensitization were screened using 16s rRNA gene sequencing and ultrahigh-performance liquid chromatography-mass coupled with mass spectrometry. In vitro and in vivo studies were conducted to assess the radiosensitizing effects of the metabolites including the syngeneic CT26 tumor model and HCT116 xenograft tumor model, transcriptomics and immunofluorescence. The CT26 abscopal effect modeling was employed to evaluate the combined effects of metabolites on iRT. RESULTS: We initially discovered the gut microbiota-associated metabolite, methylglyoxal (MG), which accurately predicts the response to preRT (Area Under Curve (AUC) value of 0.856) among patients with LARC. Subsequently, we observed that MG amplifies the RT response in RC by stimulating intracellular reactive oxygen species (ROS) and reducing hypoxia in the tumor in vitro and in vivo. Additionally, our study demonstrated that MG amplifies the RT-induced activation of the cyclic guanosine monophosphate AMP synthase-stimulator of interferon genes pathway by elevating DNA double-strand breaks. Moreover, it facilitates immunogenic cell death generated by ROS-mediated endoplasmic reticulum stress, consequently leading to an increase in CD8+ T and natural killer cells infiltrated in the tumor immune microenvironment. Lastly, we discovered that the combination of anti-programmed cell death protein 1 (anti-PD1) therapy produced long-lasting complete responses in all irradiated tumor sites and half of the non-irradiated ones. CONCLUSIONS: Our research indicates that MG shows promise as a radiosensitizer and immunomodulator for RC. Furthermore, we propose that combining MG with iRT has great potential for clinical practice.

Comprehensive analysis of transient receptor potential channels-related signature for prognosis, tumor immune microenvironment, and treatment response of colorectal cancer.

Background: Transient receptor potential channels (TRPC) play critical regulatory functions in cancer occurrence and progression. However, knowledge on its role in colorectal cancer (CRC) is limited. In addition, neoadjuvant treatment and immune checkpoint inhibitors (ICIs) have increasing roles in CRC management, but not all patients benefit from them. In this study, a TRPC related signature (TRPCRS) was constructed for prognosis, tumor immune microenvironment (TIME), and treatment response of CRC. Methods: Data on CRC gene expression and clinical features were retrospectively collected from TCGA and GEO databases. Twenty-eight TRPC regulators (TRPCR) were retrieved using gene set enrichment analysis. Different TRPCR expression patterns were identified using non-negative matrix factorization for consensus clustering, and a TRPCRS was established using LASSO. The potential value of TRPCRS was assessed using functional enrichment analysis, tumor immune analysis, tumor somatic mutation analysis, and response to preoperative chemoradiotherapy or ICIs. Moreover, an external validation was conducted using rectal cancer samples that received preoperative chemoradiotherapy at Fujian Cancer Hospital (FJCH) via qRT-PCR. Results: Among 834 CRC samples in the TCGA and meta-GEO cohorts, two TRPCR expression patterns were identified, which were associated with various immune infiltrations. In addition, 266 intersected genes from 5564 differentially expressed genes (DEGs) between two TRPC subtypes, 4605 DEGs between tumor tissue and adjacent non-tumor tissue (all FDR< 0.05, adjusted P< 0.001), and 1329 prognostic related genes (P< 0.05) were identified to establish the TRPCRS, which was confirmed in the TCGA cohort, two cohorts from GEO, and one qRT-PCR cohort from FJCH. According to the current signature, the high-TRPC score group had higher expressions of PD-1, PD-L1, and CTLA4, lower TIDE score, and improved response to anti-PD-1 treatment with better predictive ability. Compared to the high-TRPC score group, the low-TRPC score group comprised an immunosuppressive phenotype with increased infiltration of neutrophils and activated MAPK signaling pathway, but was more sensitive to preoperative chemoradiotherapy and associated with improved prognosis. Conclusions: The current TRPCRS predicted the prognosis of CRC, evaluated the TIME in CRC, and anticipated the response to immune therapy and neoadjuvant treatment.

Identification of chromatin organization-related gene signature for hepatocellular carcinoma prognosis and predicting immunotherapy response.

BACKGROUND: Chromatin organization is associated with tumorigenesis; however, information on its role in hepatocellular carcinoma (HCC) is limited. Moreover, although immune checkpoint inhibitors (ICIs) have proven effective against HCC, the optimal index remains unknown. In this study, we aimed to construct a chromatin organization-related gene signature (CORGS) for prognosis and predicting response to ICIs in HCC. METHODS: HCC-related data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Construction (ICGC). Chromatin organization-related genes (CORGs) were retrieved from Gene Set Enrichment Analysis. Differentially expressed genes (DEGs) and prognostic genes were then applied to select candidate genes using advanced statistical methods, including learning vector quantization, random forest, and lasso regression. Subsequently, the CORGS was established based on chromatin organization-related hub genes using multivariate Cox regression analysis, evaluated with Kaplan-Meier survival curves, and verified in 64 samples of HCC patients from Fujian Provincial Hospital (FPH) via quantitative PCR. Subsequently, functional enrichment analysis, tumor somatic mutation analysis, and tumor immune analysis were performed to evaluate the potential value of the CORGS. RESULTS: Three hundred and thirty-nine CORGs were identified as DEGs, and 186 were associated with HCC prognosis (all P < 0.05). Four intersection genes were selected to establish the CORGS using TCGA cohort, which was found to serve as an independent risk factor for HCC patients. CORGS was then validated in an ICGC cohort. In addition, CORGS reliability was verified in 64 samples from HCC patients and 26 adjacent non-tumorous tissues, collected from the FPH. The CORGS was also associated with tumor immune microenvironment characteristics and ICI response. Moreover, data from "IMvigor 210" revealed that more patients in the low CORGS group responded to atezolizumab compared to high CORGS patients (P < 0.05). Finally, a nomogram of tumor characteristics and the CORGS was established, exhibiting superior discrimination and calibration compared to the current staging system and published models. CONCLUSIONS: CORGS may serve as an effective predictive biomarker for HCC as well as a potential index of the tumor immune microenvironment and ICI response.

An Unfolded Protein Response-Related mRNA Signature Predicting the Survival and Therapeutic Effect of Hepatocellular Carcinoma.

BACKGROUND: Tumorigenesis, metastasis, and treatment response of hepatocellular carcinoma (HCC) are regulated by unfolded protein responses (UPR) signaling pathways, including IRE1a, PERK, and ATF6, but little is known about UPR related genes with HCC prognosis and therapeutic indicators. OBJECTIVE: We aimed to identify a UPR related prognostic signature (UPRRPS) for HCC and explore the potential effect of the current signature on the existing molecular targeted agents and immune checkpoint inhibitors (ICIs). METHODS: We used The Cancer Genome Atlas (TCGA) database to screen candidate UPR genes (UPRGs), which are expressed differentially between hepatocellular carcinoma and normal liver tissue and associated with prognosis. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, which was validated using data from the International Cancer Genome Consortium (ICGC) database and evaluated by the C-index. Then immune and molecular characteristics stratified by the current UPRRPS were analyzed, and the corresponding drug sensitivity was conducted. RESULTS: Initially, 42 UPRGs from the TCGA database were screened as differentially expressed genes, which were also associated with HCC prognosis. Using the LASSO regression analysis, nine UPRGs (EXTL3, PPP2R5B, ZBTB17, EIF2S2, EIF2S3, HDGF, SRPRB, EXTL2, and TPP1) were used to develop a UPRRPS to predict the OS of HCC patients in the TCGA set with the Cindex of 0.763. The current UPRRPS was also well-validated in the ICGC set with the C-index of 0.700. Multivariate Cox regression analyses also confirmed that the risk score was an independent risk factor for HCC in both the TCGA and ICGC sets (both P<0.05). Functional analyses showed that low-risk score was associated with increased natural killer cells, T helpers, tumor immune dysfunction and exclusion score, microsatellite instability expression, and more benefit from ICIs; the high-risk score was associated with increased active dendritic cells, Tregs, T-cell exclusion score, and less benefit from ICIs. Gene set enrichment analyses showed that the signaling pathways of VEGF, MAPK, and mTOR were enriched in high UPRRPS, and the drug sensitivities of the corresponding inhibitors were all significantly higher in the high UPRRPS subgroup (all P<0.001). CONCLUSION: With the current findings, UPRRPS was a promising biomarker for predicting the prognosis of HCC patients. UPRRPS might also be taken as a potential indicator to guide the management of immune checkpoint inhibitors and molecular targeted agents.

Identification of Aging-Related Genes Associated With Clinical and Prognostic Features of Hepatocellular Carcinoma.

Background: Aging is a well-studied concept, but no studies have comprehensively analyzed the association between aging-related genes (AGs) and hepatocellular carcinoma (HCC) prognosis. Methods: Gene candidates were selected from differentially expressed genes and prognostic genes in The Cancer Genome Atlas (TCGA) database. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, and this was validated using data from the International Cancer Genome Consortium (ICGC) database. Functional analysis was conducted using gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis, and immune microenvironment and tumor stemness analyses. Results: Initially, 72 AGs from the TCGA database were screened as differentially expressed between normal and tumor tissues and as genes associated with HCC prognosis. Then, seven AGs (POLA1, CDK1, SOCS2, HDAC1, MAPT, RAE1, and EEF1E1) were identified using the LASSO regression analysis. The seven AGs were used to develop a risk score in the training set, and the risk was validated to have a significant prognostic value in the ICGC set (p < 0.05). Patients with high risk scores had lower tumor differentiation, higher stage, and worse prognosis (all p < 0.05). Multivariate Cox regression analyses also confirmed that the risk score was an independent prognostic factor for HCC in both the TCGA and ICGC sets (all p < 0.05). Further analysis showed that a high risk score was correlated with the downregulation of metabolism and tumor immunity. Conclusion: The risk score predicts HCC prognosis and could thus be used as a biomarker not only for predicting HCC prognosis but also for deciding on treatment.