Long noncoding RNA Regulating ImMune Escape regulates mixed lineage leukaemia protein-1-H3K4me3-mediated immune escape in oesophageal squamous cell carcinoma.

BACKGROUND: Predictive biomarkers for oesophageal squamous cell carcinoma (ESCC) immunotherapy are lacking, and immunotherapy resistance remains to be addressed. The role of long noncoding RNA (lncRNA) in ESCC immune escape and immunotherapy resistance remains to be elucidated. METHODS: The tumour-associated macrophage-upregulated lncRNAs and the exosomal lncRNAs highly expressed in ESCC immunotherapy nonresponders were identified by lncRNA sequencing and polymerase chain reaction assays. CRISPR-Cas9 was used to explore the functional roles of the lncRNA. RNA pull-down, MS2-tagged RNA affinity purification (MS2-TRAP) and RNA-binding protein immunoprecipitation (RIP) were performed to identify lncRNA-associated proteins and related mechanisms. In vivo, the humanized PBMC (hu-PBMC) mouse model was established to assess the therapeutic responses of specific lncRNA inhibitors and their combination with programmed cell death protein 1 (PD-1) monoclonal antibody (mAb). Single-cell sequencing, flow cytometry, and multiplex fluorescent immunohistochemistry were used to analyze immune cells infiltrating the tumour microenvironment. RESULTS: We identified a lncRNA that is involved in tumour immune evasion and immunotherapy resistance. High LINC02096 (RIME) expression in plasma exosomes correlates with a reduced response to PD-1 mAb treatment and poor prognosis. Mechanistically, RIME binds to mixed lineage leukaemia protein-1 (MLL1) and prevents ankyrin repeat and SOCS box containing 2 (ASB2)-mediated MLL1 ubiquitination, improving the stability of MLL1. RIME-MLL1 increases H3K4me3 levels in the promoter regions of programmed death-ligand 1 (PD-L1) and indoleamine 2,3-dioxygenase 1 (IDO-1), constitutively increasing the expression of PD-L1/IDO-1 in tumour cells and inhibiting CD8+ T cells infiltration and activation. RIME depletion in huPBMC-NOG mice significantly represses tumour development and improves the effectiveness of PD-1 mAb treatment by activating T-cell-mediated antitumour immunity. CONCLUSIONS: This study reveals that the RIME-MLL1-H3K4me3 axis plays a critical role in tumour immunosuppression. Moreover, RIME appears to be a potential prognostic biomarker for immunotherapy and developing drugs that target RIME may be a new therapeutic strategy that overcomes immunotherapy resistance and benefits patients with ESCC.

The Single-Cell Landscape of Intratumoral Heterogeneity and The Immunosuppressive Microenvironment in Liver and Brain Metastases of Breast Cancer.

Distant metastasis remains the major cause of morbidity for breast cancer. Individuals with liver or brain metastasis have an extremely poor prognosis and low response rates to anti-PD-1/L1 immune checkpoint therapy compared to those with metastasis at other sites. Therefore, it is urgent to investigate the underlying mechanism of anti-PD-1/L1 resistance and develop more effective immunotherapy strategies for these patients. Using single-cell RNA sequencing, a high-resolution map of the entire tumor ecosystem based on 44 473 cells from breast cancer liver and brain metastases is depicted. Identified by canonical markers and confirmed by multiplex immunofluorescent staining, the metastatic ecosystem features remarkable reprogramming of immunosuppressive cells such as FOXP3+ regulatory T cells, LAMP3+ tolerogenic dendritic cells, CCL18+ M2-like macrophages, RGS5+ cancer-associated fibroblasts, and LGALS1+ microglial cells. In addition, PD-1 and PD-L1/2 are barely expressed in CD8+ T cells and cancer/immune/stromal cells, respectively. Interactions of the immune checkpoint molecules LAG3-LGALS3 and TIGIT-NECTIN2 between CD8+ T cells and cancer/immune/stromal cells are found to play dominant roles in the immune escape. In summary, this study dissects the intratumoral heterogeneity and immunosuppressive microenvironment in liver and brain metastases of breast cancer for the first time, providing insights into the most appropriate immunotherapy strategies for these patients.

The Macrophage-Associated LncRNA MALR Facilitates ILF3 Liquid-Liquid Phase Separation to Promote HIF1α Signaling in Esophageal Cancer.

SIGNIFICANCE: Secretion of TNFα by tumor-associated macrophages stimulates cancer cells to upregulate lncRNA MALR, which induces ILF3 liquid-liquid phase separation and activation of HIF1α signaling to promote cancer progression.

The Pan-Cancer Multi-Omics Landscape of FOXO Family Relevant to Clinical Outcome and Drug Resistance.

The forkhead box O (FOXO) transcription factors (TFs) family are frequently mutated, deleted, or amplified in various human cancers, making them attractive candidates for therapy. However, their roles in pan-cancer remain unclear. Here, we evaluated the expression, prognostic value, mutation, methylation, and clinical features of four FOXO family genes (FOXO1, FOXO3, FOXO4, and FOXO6) in 33 types of cancers based on the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases. We used a single sample gene set enrichment analysis (ssGSEA) algorithm to establish a novel index called "FOXOs score". Moreover, we investigated the association between the FOXOs score and tumor microenvironment (TME), the responses to multiple treatments, along with drug resistance. We found that the FOXO family genes participated in tumor progression and were related to the prognosis in various types of cancer. We calculated the FOXOs score and found that it was significantly correlated with multiple malignant pathways in pan-cancer, including Wnt/beta-catenin signaling, TGF-beta signaling, and hedgehog signaling. In addition, the FOXOs score was also associated with multiple immune-related characteristics. Furthermore, the FOXOs score was sensitive for predicting the efficacy of diverse treatments in multiple cancers, especially immunotherapy. In conclusion, FOXO family genes were vital in pan-cancer and were strongly correlated with the TME. A high FOXOs score indicated an excellent immune-activated TME and sensitivity to multiple treatments. Hence, the FOXOs score might potentially be used as a biomarker in patients with a tumor.

Leveraging diverse cell-death patterns to predict the prognosis and drug sensitivity of triple-negative breast cancer patients after surgery.

BACKGROUND: Postoperative progression and chemotherapy resistance is the major cause of treatment failure in patients with triple-negative breast cancer (TNBC). Currently, there is a lack of an ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients. Diverse programmed cell death (PCD) patterns play an important role in tumor progression, which has the potential to be a prognostic and drug sensitivity indicator for TNBC after surgery. MATERIALS AND METHODS: Twelve PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis) were analyzed for model construction. Bulk transcriptome, single-cell transcriptome, genomics, and clinical information were collected from TCGA-BRCA, METABRIC, GSE58812, GSE21653, GSE176078, GSE75688, and KM-plotter cohorts to validate the model. RESULTS: The machine learning algorithm established a cell death index (CDI) with a 12-gene signature. Validated in five independent datasets, TNBC patients with high CDI had a worse prognosis after surgery. Two molecular subtypes of TNBC with distinct vital biological processes were identified by an unsupervised clustering model. A nomogram with high predictive performance was constructed by incorporating CDI with clinical features. Furthermore, CDI was associated with immune checkpoint genes and key tumor microenvironment components by integrated analysis of bulk and single-cell transcriptome. TNBC patients with high CDI are resistant to standard adjuvant chemotherapy regimens (docetaxel, oxaliplatin, etc.); however, they might be sensitive to palbociclib (an FDA-approved drug for luminal breast cancer). CONCLUSION: Generally, we established a novel CDI model by comprehensively analyzing diverse cell death patterns, which can accurately predict clinical prognosis and drug sensitivity of TNBC after surgery. A user-friendly website was created to facilitate the application of this prediction model (https://tnbc.shinyapps.io/CDI_Model/).

Turning up a new pattern: Identification of cancer-associated fibroblast-related clusters in TNBC.

Growing evidence indicates a connection between cancer-associated fibroblasts (CAFs) and tumor microenvironment (TME) remodeling and tumor progression. Nevertheless, how patterns of CAFs impact TME and immunotherapy responsiveness in triple-negative breast cancer (TNBC) remains unclear. Here, we systematically investigate the relationship between TNBC progression and patterns of CAFs. By using unsupervised clustering methods in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, we identified two distinct CAF-associated clusters that were related to clinical features, characteristics of TME, and prognosis of patients. Then, we established a CAF-related prognosis index (CPI) by the least absolute shrinkage and selection operator (LASSO)-Cox regression method. CPI showed prognostic accuracy in both training and validation cohorts (METABRIC, GSE96058, and GSE21653). Consequently, we constructed a nomogram with great predictive performance. Moreover, the CPI was verified to be correlated with the responsiveness of immunotherapy in three independent cohorts (GSE91061, GSE165252, and GSE173839). Taken together, the CPI might help us improve our recognition of the TME of TNBC, predict the prognosis of TNBC patients, and offer more immunotherapy strategies in the future.

Glucose metabolism inhibitor PFK-015 combined with immune checkpoint inhibitor is an effective treatment regimen in cancer.

Metabolic inhibition via PFKFB3 inhibition has demonstrated considerable tumor inhibitory effects in various studies; however, PFKFB3 inhibition did not show satisfactory tumor inhibition when used in clinical trials. PFKFB3 is a crucial metabolic enzyme that is highly upregulated in cancer cells and directly affects tumor glycolysis. Here, we showed that PFKFB3 inhibition suppresses tumors in vitro and in vivo in immune-deficient xenografts. However, this inhibition induces the upregulation of PD-L1 levels, which inactivated cocultured T-cells in vitro, compromises anti-tumor immunity in vivo, and reduced anti-tumor efficacy in an immune-competent mouse model. Functionally, PD-1 mAb treatment enhances the efficacy of PFKFB3 inhibition in immunocompetent and hu-PBMC NOG mouse models. Mechanistically, PFKFB3 inhibition increases phosphorylation of PFKFB3 at residue Ser461, which increases interaction with HIF-1α, and their colocalization into the nucleus, where HIF-1α transcriptionally upregulate PD-L1 expression and causes subsequent tumor immune evasion. Higher phos-PFKFB3 correlated with higher PD-L1 expression, lower CD8 and GRZMB levels, and shorter survival time in ESCC patients.

Long noncoding RNA AGPG regulates PFKFB3-mediated tumor glycolytic reprogramming.

Tumor cells often reprogram their metabolism for rapid proliferation. The roles of long noncoding RNAs (lncRNAs) in metabolism remodeling and the underlying mechanisms remain elusive. Through screening, we found that the lncRNA Actin Gamma 1 Pseudogene (AGPG) is required for increased glycolysis activity and cell proliferation in esophageal squamous cell carcinoma (ESCC). Mechanistically, AGPG binds to and stabilizes 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3). By preventing APC/C-mediated ubiquitination, AGPG protects PFKFB3 from proteasomal degradation, leading to the accumulation of PFKFB3 in cancer cells, which subsequently activates glycolytic flux and promotes cell cycle progression. AGPG is also a transcriptional target of p53; loss or mutation of TP53 triggers the marked upregulation of AGPG. Notably, inhibiting AGPG dramatically impaired tumor growth in patient-derived xenograft (PDX) models. Clinically, AGPG is highly expressed in many cancers, and high AGPG expression levels are correlated with poor prognosis, suggesting that AGPG is a potential biomarker and cancer therapeutic target.

Effect of Induction Time on the Proliferation and Differentiation of Induced Schwann-Like Cells from Adipose-Derived Stem Cells.

To compare how different induction time takes effect on the proliferation and secretion ability of adipose-derived stem cell (ADSC)-induced Schwann-like cells (iSCs), ADSCs were isolated from healthy adult female rats. Flow cytometry (FCM) was performed to detect the ADSC-positive markers CD29, CD44, and CD90 and the negative marker CD45. iSC induction medium was used to culture the ADSCs. S-100, GFAP, MBP, and P75 were detected by immunofluorescence staining to identify iSC differentiation. Cell morphological changes were observed by an inverted microscope after induction. An MTS assay was used to evaluate the cell proliferation ability. Western blot analyses of caspase-3/cleaved caspase-3 and FCM were applied to assess cell apoptosis. Co-culture system of PC12 and ADSCs or iSCs was established to analyse the biological function of iSCs. Among the examined proteins, S-100, GFAP, MBP, and P75 were expressed in iSCs. After day 7, the cell proliferation rate was significantly lower than that before induction, and on day 19, the proliferation rate of iSCs was lower than 50% of the proliferation rate before induction (OD value = 0.016 ± 0.003 vs. 0.400 ± 0.004, p < 0.01). Starting from day 19, P21, P53, Apoj, S100, Gdnf, and Mbp all consistently showed a trend toward increased expression. Secretion of NGF, MBP, and BDNF was more enhanced at 19 days than that at 7 days. In co-culture system, the induction effect of iSCs was more pronounced at 19 days than that at 7 days, and the difference was statistically significant (55.40 ± 4.50 µm vs 37.15 ± 3.75 µm, p < 0.01). In conclusion, the proliferation ability of ADSC-derived iSCs was negatively correlated with the induction time, while the expression of SC marker proteins was positively correlated. Therefore, iSCs are suitable for use at 19 days after induction.