Background: The tumor microenvironment (TME) consists of heterogeneous cell populations, including malignant cells and nonmalignant cells that support tumor proliferation, invasion, and metastasis through extensive cross talk. The intra-tumor immune landscape is a critical factor influencing patient survival and response to immunotherapy. Methods: Gene expression data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Immune cell infiltration was determined by single-sample Gene Set Enrichment Analysis (ssGSEA) depending on the integrated immune gene sets from published studies. Univariate analysis was used to determine the prognostic value of the infiltrated immune cells. Least absolute shrinkage and selection operator (LASSO) regression was performed to screen for the most survival-relevant immune cells. An immune-cell characteristic score (ICCS) model was constructed by using multivariate Cox regression analysis. Results: The immune cell infiltration patterns across 32 cancer types were identified, and patients in the high immune cell infiltration cluster had worse overall survival (OS) but better progression-free interval (PFI) compared to the low immune cell infiltration cluster. However, immune cell infiltration showed inconsistent prognostic value depending on the cancer type. High immune cell infiltration (High CI) indicated a worse prognosis in brain lower grade glioma (LGG), glioblastoma multiforme (GBM), and uveal melanoma (UVM), and favorable prognosis in adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), sarcoma (SARC), and skin cutaneous melanoma (SKCM). LUAD prognosis was significantly influenced by the infiltration of 13 immune cell types, with high infiltration of all but Type 2 T helper (Th2) cells correlating with a favorable prognosis. The ICCS model based on six most survival-relevant immune cell populations was generated that classified patients into low- and high-ICCS groups with good and poor prognoses, respectively. The multivariate and stratified analyses further revealed that the ICCS was an independent prognostic factor for LUAD. Conclusions: The infiltration of immune cells in 32 cancer types was quantified, and considerable heterogeneity was observed in the prognostic relevance of these cells in different cancer types. An ICCS model was constructed for LUAD with competent prognostic performance, which can further deepen our understanding of the TME of LUAD and can have implications for immunotherapy.

The codependency of cholesterol metabolism sustains the malignant progression of glioblastoma (GBM) and effective therapeutics remain scarce. In orthotopic GBM models in male mice, we identify that codependent cholesterol metabolism in tumors induces phagocytic dysfunction in monocyte-derived tumor-associated macrophages (TAMs), resulting in disease progression. Manipulating cholesterol efflux with apolipoprotein A1 (ApoA1), a cholesterol reverse transporter, restores TAM phagocytosis and reactivates TAM-T cell antitumor immunity. Cholesterol metabolomics analysis of in vivo-sorted TAMs further reveals that ApoA1 mediates lipid-related metabolic remodeling and lowers 7-ketocholesterol levels, which directly inhibits tumor necrosis factor signaling in TAMs through mitochondrial translation inhibition. An ApoA1-armed oncolytic adenovirus is also developed, which restores antitumor immunity and elicits long-term tumor-specific immune surveillance. Our findings provide insight into the mechanisms by which cholesterol metabolism impairs antitumor immunity in GBM and offer an immunometabolic approach to target cholesterol disturbances in GBM.

Resistance remains an obstacle to anti-programmed cell death protein 1 (PD-1) therapy in human cancer. One critical resistance mechanism is the lack of T cell chemotaxis in the tumor microenvironment (TME). CXCL10-CXCR3 signaling is required for T cell tumor infiltration and tumor immunotherapy. Oncolytic viruses (OVs), including oncolytic adenoviruses (AdVs), induce effective T cell immunity and tumor infiltration. Thus, arming OV with CXCL10 would be an attractive strategy to overcome resistance to anti-PD1 therapy. Here, we successfully constructed a novel recombinant oncolytic adenovirus encoding murine CXCL10, named Adv-CXCL10. Through intratumoural injection, the continuous expression of the functional chemokine CXCL10 in the TME is realized to recruit more CXCR3⁺ T cells into the TME to kill tumor cells, and the recombinant adenovirus shows great power to ‘fire up’ the TME and enhance the antitumour efficiency of PD-1 antibodies.

Background: In addition to directly lysing tumors, oncolytic viruses also induce antitumor immunity by recruiting and activating immune cells in the local tumor microenvironment. However, the activation of the immune cells induced by oncolytic viruses is always accompanied by high-level expression of immune checkpoints in these cells, which may reduce the efficacy of the oncolytic viruses. The aim of this study is to arm the oncolytic vaccinia virus (VV) with immune checkpoint blockade to enhance its antitumor efficacy. Methods: Through homologous recombination with the parental VV, an engineered VV-scFv-TIGIT was produced, which encodes a single-chain variable fragment (scFv) targeting T-cell immunoglobulin and ITIM domain (TIGIT). The antitumor efficacy of the VV-scFv-TIGIT was explored in several subcutaneous and ascites tumor models. The antitumor efficacy of VV-scFv-TIGIT combined with programmed cell death 1 (PD-1) or lymphocyte-activation gene 3 (LAG-3) blockade was also investigated. Results: The VV-scFv-TIGIT effectively replicated in tumor cells and lysed them, and prompt the infected tumor cells to secret the functional scFv-TIGIT. Compared with control VV, intratumoral injection of VV-scFv-TIGIT in several mouse subcutaneous tumor models showed superior antitumor efficacy, accompanied by more T cell infiltration and a higher degree of CD8⁺ T cells activation. Intraperitoneal injection of VV-scFv-TIGIT in a mouse model of malignant ascites also significantly improved T cell infiltration and CD8⁺ T cell activation, resulting in more than 90% of the tumor-bearing mice being cured. Furthermore, the antitumor immune response induced by VV-scFv-TIGIT was dependent on CD8⁺ T cells which mediated a long-term immunological memory and a systemic antitumor immunity against the same tumor. Finally, the additional combination of PD-1 or LAG-3 blockade further enhanced the antitumor efficacy of VV-scFv-TIGIT, increasing the complete response rate of tumor-bearing mice. Conclusions: Oncolytic virotherapy using engineered VV-scFv-TIGIT was an effective strategy for cancer immunotherapy. Administration of VV-scFv-TIGIT caused a profound reshaping of the suppressive tumor microenvironment from ‘cold’ to ‘hot’ status. VV-scFv-TIGIT also synergized with PD-1 or LAG-3 blockade to achieve a complete response to tumors with poor response to VV or immune checkpoint blockade monotherapy.

The high mortality of patients with non-small cell lung cancer (NSCLC) emphasizes the necessity of identifying a robust and reliable prognostic signature for NSCLC patients. This study aimed to identify and validate a prognostic signature for the prediction of both disease-free survival (DFS) and overall survival (OS) of NSCLC patients by integrating multiple datasets. We firstly downloaded three independent datasets under the accessing number of GSE31210, GSE37745 and GSE50081, and then performed an univariate regression analysis to identify the candidate prognostic genes from each dataset, and identified the gene signature by overlapping the candidates. Then, we built a prognostic model to predict DFS and OS using a risk score method. Kaplan–Meier curve with log-rank test was used to determine the prognostic significance. Univariate and multivariate Cox proportional hazard regression models were implemented to evaluate the influences of various variables on DFS and OS. The robustness of the prognostic gene signature was evaluated by re-sampling tests based on the combined GEO dataset (GSE31210, GSE37745 and GSE50081). Furthermore, a The Cancer Genome Atlas (TCGA)-NSCLC cohort was utilized to validate the prediction power of the gene signature. Finally, the correlation of the risk score of the gene signature and the Gene set variation analysis (GSVA) score of cancer hallmark gene sets was investigated. We identified and validated a six-gene prognostic signature in this study. This prognostic signature stratified NSCLC patients into the low-risk and high-risk groups. Multivariate regression and stratification analyses demonstrated that the six-gene signature was an independent predictive factor for both DFS and OS when adjusting for other clinical factors. Re-sampling analysis implicated that this six-gene signature for predicting prognosis of NSCLC patients is robust. Moreover, the risk score of the gene signature is correlated with the GSVA score of 7 cancer hallmark gene sets. This study provided a robust and reliable gene signature that had significant implications in the prediction of both DFS and OS of NSCLC patients, and may provide more effective treatment strategies and personalized therapies.

We investigated the expression and proinflammatory activity of interleukin (IL)-36 in patients with systemic lupus erythematosus (SLE). The expression level of IL-36, its putative receptors and the frequency of CD19⁺CD24^highCD27⁺ regulatory B (Breg) lymphocytes of peripheral blood from 43 SLE patients and 16 normal control (NC) subjects were studied using ELISA and flow cytometry. Plasma cytokines/chemokines and ex vivo productions of cytokine/chemokine from peripheral blood mononuclear cells (PBMC) stimulated with recombinant IL-36 were determined by Luminex multiplex assay. Plasma concentrations of IL-36α, IL-36γ and the proportions of circulating IL-36R-positive CD19⁺ B lymphocytes in total B lymphocytes and PBMC were significantly increased in active SLE patients compared with NC (all p < 0.05). Plasma IL-36α and IL-36γ correlated positively with SLE disease activity and elevated plasma IL-10 concentration (all p < 0.05). The frequencies of circulating Breg lymphocytes in total B lymphocytes and PBMC were significantly decreased in both inactive and active SLE patients compared with NC (all p < 0.01). The frequency of Breg lymphocytes in total B lymphocytes correlated negatively with the proportion of IL-36R-positive B lymphocytes (p < 0.05). IL-36α exerted substantial proinflammatory effect in PBMC from SLE patients by inducing the production of IL-6 and CXCL8. Upon stimulation with IL-36α and IL-36γ, ex vivo productions of IL-6 and CXCL8 were significantly increased in SLE patients compared with NC (all p < 0.05). This cross-sectional study demonstrated that over expression of circulating IL-36α may exert a proinflammatory effect as observed in human SLE.