Pan-cancer analysis for the prognostic and immunological role of CD47: interact with TNFRSF9 inducing CD8 + T cell exhaustion.

PURPOSE: The research endeavors to explore the implications of CD47 in cancer immunotherapy effectiveness. Specifically, there is a gap in comprehending the influence of CD47 on the tumor immune microenvironment, particularly in relation to CD8 + T cells. Our study aims to elucidate the prognostic and immunological relevance of CD47 to enhance insights into its prospective utilities in immunotherapeutic interventions. METHODS: Differential gene expression analysis, prognosis assessment, immunological infiltration evaluation, pathway enrichment analysis, and correlation investigation were performed utilizing a combination of R packages, computational algorithms, diverse datasets, and patient cohorts. Validation of the concept was achieved through the utilization of single-cell sequencing technology. RESULTS: CD47 demonstrated ubiquitous expression across various cancer types and was notably associated with unfavorable prognostic outcomes in pan-cancer assessments. Immunological investigations unveiled a robust correlation between CD47 expression and T-cell infiltration rather than T-cell exclusion across multiple cancer types. Specifically, the CD47-high group exhibited a poorer prognosis for the cytotoxic CD8 + T cell Top group compared to the CD47-low group, suggesting a potential impairment of CD8 + T cell functionality by CD47. The exploration of mechanism identified enrichment of CD47-associated differentially expressed genes in the CD8 + T cell exhausted pathway in multiple cancer contexts. Further analyses focusing on the CD8 TCR Downstream Pathway and gene correlation patterns underscored the significant involvement of TNFRSF9 in mediating these effects. CONCLUSION: A robust association exists between CD47 and the exhaustion of CD8 + T cells, potentially enabling immune evasion by cancer cells and thereby contributing to adverse prognostic outcomes. Consequently, genes such as CD47 and those linked to T-cell exhaustion, notably TNFRSF9, present as promising dual antigenic targets, providing critical insights into the field of immunotherapy.

Pretreatment radiomic biomarker for immunotherapy responder prediction in stage IB-IV NSCLC (LCDigital-IO Study): a multicenter retrospective study.

BACKGROUND: The predictive efficacy of current biomarker of immune checkpoint inhibitors (ICIs) is not sufficient. This study investigated the causality between radiomic biomarkers and immunotherapy response status in patients with stage IB-IV non-small cell lung cancer (NSCLC), including its biological context for ICIs treatment response prediction. METHODS: CT images from 319 patients with pretreatment NSCLC receiving immunotherapy between January 2015 and November 2021 were retrospectively collected and composed a discovery (n=214), independent validation (n=54), and external test cohort (n=51). A set of 851 features was extracted from tumorous and peritumoral volumes of interest (VOIs). The reference standard is the durable clinical benefit (DCB, sustained disease control for more than 6 months assessed via radiological evaluation). The predictive value of combined radiomic signature (CRS) for pathological response was subsequently assessed in another cohort of 98 patients with resectable NSCLC receiving ICIs preoperatively. The association between radiomic features and tumor immune landscape on the online data set (n=60) was also examined. A model combining clinical predictor and radiomic signatures was constructed to improve performance further. RESULTS: CRS discriminated DCB and non-DCB patients well in the training and validation cohorts with an area under the curve (AUC) of 0.82, 95% CI: 0.75 to 0.88, and 0.75, 95% CI: 0.64 to 0.87, respectively. In this study, the predictive value of CRS was better than programmed cell death ligand-1 (PD-L1) expression (AUC of PD-L1 subset: 0.59, 95% CI: 0.50 to 0.69) or clinical model (AUC: 0.66, 95% CI: 0.51 to 0.81). After combining the clinical signature with CRS, the predictive performance improved further with an AUC of 0.837, 0.790 and 0.781 in training, validation and D2 cohorts, respectively. When predicting pathological response, CRS divided patients into a major pathological response (MPR) and non-MPR group (AUC: 0.76, 95% CI: 0.67 to 0.81). Moreover, CRS showed a promising stratification ability on overall survival (HR: 0.49, 95% CI: 0.27 to 0.89; p=0.020) and progression-free survival (HR: 0.43, 95% CI: 0.26 to 0.74; p=0.002). CONCLUSION: By analyzing both tumorous and peritumoral regions of CT images in a radiomic strategy, we developed a non-invasive biomarker for distinguishing responders of ICIs therapy and stratifying their survival outcome efficiently, which may support the clinical decisions on the use of ICIs in advanced as well as patients with resectable NSCLC.

Radiation-sensitive genetic prognostic model identifies individuals at risk for radiation resistance in head and neck squamous cell carcinoma.

BACKGROUND: The advantages of radiotherapy for head and neck squamous cell carcinoma (HNSCC) depend on the radiation sensitivity of the patient. Here, we established and verified radiological factor-related gene signature and built a prognostic risk model to predict whether radiotherapy would be beneficial. METHODS: Data from The Cancer Genome Atlas, Gene Expression Omnibus, and RadAtlas databases were subjected to LASSO regression, univariate COX regression, and multivariate COX regression analyses to integrate genomic and clinical information from patients with HNSCC. HNSCC radiation-related prognostic genes were identified, and patients classified into high- and low-risk groups, based on risk scores. Variations in radiation sensitivity according to immunological microenvironment, functional pathways, and immunotherapy response were investigated. Finally, the expression of HNSCC radiation-related genes was verified by qRT-PCR. RESULTS: We built a clinical risk prediction model comprising a 15-gene signature and used it to divide patients into two groups based on their susceptibility to radiation: radiation-sensitive and radiation-resistant. Overall survival was significantly greater in the radiation-sensitive than the radiation-resistant group. Further, our model was an independent predictor of radiotherapy response, outperforming other clinical parameters, and could be combined with tumor mutational burden, to identify the target population with good predictive value for prognosis at 1, 2, and 3 years. Additionally, the radiation-resistant group was more vulnerable to low levels of immune infiltration, which are significantly associated with DNA damage repair, hypoxia, and cell cycle regulation. Tumor Immune Dysfunction and Exclusion scores also suggested that the resistant group would respond less favorably to immunotherapy. CONCLUSIONS: Our prognostic model based on a radiation-related gene signature has potential for application as a tool for risk stratification of radiation therapy for patients with HNSCC, helping to identify candidates for radiation therapy and overcome radiation resistance.

A homologous and molecular dual-targeted biomimetic nanocarrier for EGFR-related non-small cell lung cancer therapy.

The abnormal activation of epidermal growth factor receptor (EGFR) drives the development of non-small cell lung cancer (NSCLC). The EGFR-targeting tyrosine kinase inhibitor osimertinib is frequently used to clinically treat NSCLC and exhibits marked efficacy in patients with NSCLC who have an EGFR mutation. However, free osimertinib administration exhibits an inadequate response in vivo, with only ∼3% patients demonstrating a complete clinical response. Consequently, we designed a biomimetic nanoparticle (CMNP@Osi) comprising a polymeric nanoparticle core and tumor cell-derived membrane-coated shell that combines membrane-mediated homologous and molecular targeting for targeted drug delivery, thereby supporting a dual-target strategy for enhancing osimertinib efficacy. After intravenous injection, CMNP@Osi accumulates at tumor sites and displays enhanced uptake into cancer cells based on homologous targeting. Osimertinib is subsequently released into the cytoplasm, where it suppresses the phosphorylation of upstream EGFR and the downstream AKT signaling pathway and inhibits the proliferation of NSCLC cells. Thus, this dual-targeting strategy using a biomimetic nanocarrier can enhance molecular-targeted drug delivery and improve clinical efficacy.

Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma.

Background: Autophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated the potential of autophagy-immune-derived biomarkers to predict prognosis and therapeutic response in patients with lung adenocarcinoma. Methods: Patients from the GSE72094 dataset were randomized 7:3 to a training set and an internal validation set. Three independent cohorts, TCGA, GSE31210, and GSE37745, were used for external verification. Unsupervised hierarchical clustering based on autophagy- and immune-associated genes was used to identify autophagy- and immune-associated molecular patterns, respectively. Significantly prognostic autophagy-immune genes were identified by LASSO analysis and by univariate and multivariate Cox regression analyses. Differences in tumor immune microenvironments, functional pathways, and potential therapeutic responses were investigated to differentiate high-risk and low-risk groups. Results: High autophagy status and high immune status were associated with improved overall survival. Autophagy and immune subtypes were merged into a two-dimensional index to characterize the combined prognostic classifier, with 535 genes defined as autophagy-immune-related differentially expressed genes (DEGs). Four genes (C4BPA, CD300LG, CD96, and S100P) were identified to construct an autophagy-immune-related prognostic risk model. Survival and receiver operating characteristic (ROC) curve analyses showed that this model was significantly prognostic of survival. Patterns of autophagy and immune genes differed in low- and high-risk patients. Enrichment of most immune infiltrating cells was greater, and the expression of crucial immune checkpoint molecules was higher, in the low-risk group. TIDE and immunotherapy clinical cohort analysis predicted that the low-risk group had more potential responders to immunotherapy. GO, KEGG, and GSEA function analysis identified immune- and autophagy-related pathways. Autophagy inducers were observed in patients in the low-risk group, whereas the high-risk group was sensitive to autophagy inhibitors. The expression of the four genes was assessed in clinical specimens and cell lines. Conclusions: The autophagy-immune-based gene signature represents a promising tool for risk stratification in patients with lung adenocarcinoma, guiding individualized targeted therapy or immunotherapy.

Liposome-Based Carbohydrate Vaccine for Simultaneously Eliciting Humoral and Cellular Antitumor Immunity.

Tumor-associated carbohydrate antigen (TACA)-based cancer vaccines achieved promising results, whereas missing the T cell-mediated cellular immune response is still a crucial problem to be solved. Here, we have developed Tn antigen (GalNAc)-modified liposome-encapsulated TLR9 agonist CpG ODN adjuvant as a cancer vaccine. The glyco-liposome vaccines exhibit strong binding ability with an anti-Tn specific antibody and enhance antigen presentation of both bone marrow-derived dendritic cells (BMDCs) and spleen B cells. In vivo immunogenicity studies have demonstrated that the glyco-liposome vaccines can significantly enhance the generation of high anti-Tn antigen antibody titers and further induce a Th1-dependent cellular immune response, evidenced by IFN-γ secretion in an immune coculture of immunized T cells with Tn-expression 4T1 cancer cells. Collectively, our results highlight a liposome-based carbohydrate vaccine as a promising platform, which can simultaneously elicit both humoral and cellular antitumor immunity.

Development and validation of a preoperative CT-based radiomic nomogram to predict pathology invasiveness in patients with a solitary pulmonary nodule: a machine learning approach, multicenter, diagnostic study.

OBJECTIVES: To develop and validate a preoperative CT-based nomogram combined with radiomic and clinical-radiological signatures to distinguish preinvasive lesions from pulmonary invasive lesions. METHODS: This was a retrospective, diagnostic study conducted from August 1, 2018, to May 1, 2020, at three centers. Patients with a solitary pulmonary nodule were enrolled in the GDPH center and were divided into two groups (7:3) randomly: development (n = 149) and internal validation (n = 54). The SYSMH center and the ZSLC Center formed an external validation cohort of 170 patients. The least absolute shrinkage and selection operator (LASSO) algorithm and logistic regression analysis were used to feature signatures and transform them into models. RESULTS: The study comprised 373 individuals from three independent centers (female: 225/373, 60.3%; median [IQR] age, 57.0 [48.0-65.0] years). The AUCs for the combined radiomic signature selected from the nodular area and the perinodular area were 0.93, 0.91, and 0.90 in the three cohorts. The nomogram combining the clinical and combined radiomic signatures could accurately predict interstitial invasion in patients with a solitary pulmonary nodule (AUC, 0.94, 0.90, 0.92) in the three cohorts, respectively. The radiomic nomogram outperformed any clinical or radiomic signature in terms of clinical predictive abilities, according to a decision curve analysis and the Akaike information criteria. CONCLUSIONS: This study demonstrated that a nomogram constructed by identified clinical-radiological signatures and combined radiomic signatures has the potential to precisely predict pathology invasiveness. KEY POINTS: • The radiomic signature from the perinodular area has the potential to predict pathology invasiveness of the solitary pulmonary nodule. • The new radiomic nomogram was useful in clinical decision-making associated with personalized surgical intervention and therapeutic regimen selection in patients with early-stage non-small-cell lung cancer.

Preoperative CT-based peritumoral and tumoral radiomic features prediction for tumor spread through air spaces in clinical stage I lung adenocarcinoma.

OBJECTIVES: This study aims to develop and evaluate preoperative CT-based peritumoral and tumoral radiomic features to predict tumor spread through air space (STAS) status in clinical stage I lung adenocarcinoma (LUAD). MATERIALS AND METHODS: From June 2018 to December 2019, a retrospective diagnostic investigation was done. Patients with pathologically confirmed STAS status (N = 256) were eventually enrolled. The development cohort consisted of 191 patients (74.6%) chosen randomly in a 7:3 ratio, whereas the validation group consisted of 65 patients (25.4%). The performance of models was assessed using receiver operating characteristic analysis, accuracy, sensitivity, specificity, negative predictive values, and positive predictive values. RESULTS: The STAS positive status was found in 85 (33.2%) of the 256 patients (female: 53.2%; median [IQR] age: 62.0, [53.0-79.0] years), while the STAS negative status was found in 171 patients (66.8%) (female:50.6%; median [IQR] age: 62.0, [53.0-87.0] years). The combined TRS and PRS-15 mm model had an AUC of 0.854 (95% CI, 0.799-0.909) in the development cohort and 0.870 (95% CI, 0.781-0.958) in the validation cohort, indicating that the tumor radiomic signature (TRS) model and different peritumoral radiomic signature (PRS) models were used to build the optimal gross radiomic signature (GRS) model. The radiomic nomogram achieves superior discriminatory performance than GRS and clinical and radiological signatures (CRS), with an AUC of 0.871 (95% CI, 0.820-0.922) in the development cohort and AUC of 0.869 (95% CI, 0.776-0.961) in the validation cohort. Based on the Akaike information criterion (AIC) and decision curve analysis (DCA), the radiomic nomogram provided greater clinical predictive capacity than clinical or any radiomic signatures alone. CONCLUSION: In conclusion, we discovered that peritumoral characteristics were substantially related to STAS status. This study revealed the unit of radiomic signature and clinical signatures may have a better performance in STAS status.

Identification of Prognostic Model Based on Immune-Related LncRNAs in Stage I-III Non-Small Cell Lung Cancer.

BACKGROUND: Long non-coding RNAs (lncRNAs) participate in the regulation of immune response and carcinogenesis, shaping tumor immune microenvironment, which could be utilized in the construction of prognostic signatures for non-small cell lung cancer (NSCLC) as supplements. METHODS: Data of patients with stage I-III NSCLC was downloaded from online databases. The least absolute shrinkage and selection operator was used to construct a lncRNA-based prognostic model. Differences in tumor immune microenvironments and pathways were explored for high-risk and low-risk groups, stratified by the model. We explored the potential association between the model and immunotherapy by the tumor immune dysfunction and exclusion algorithm. RESULTS: Our study extracted 15 immune-related lncRNAs to construct a prognostic model. Survival analysis suggested better survival probability in low-risk group in training and validation cohorts. The combination of tumor, node, and metastasis staging systems with immune-related lncRNA signatures presented higher prognostic efficacy than tumor, node, and metastasis staging systems. Single sample gene set enrichment analysis showed higher infiltration abundance in the low-risk group, including B cells (p<0.001), activated CD8+ T cells (p<0.01), CD4+ T cells (p<0.001), activated dendritic cells (p<0.01), and CD56+ Natural killer cells (p<0.01). Low-risk patients had significantly higher immune scores and estimated scores from the ESTIMATE algorithm. The predicted proportion of responders to immunotherapy was higher in the low-risk group. Critical pathways in the model were enriched in immune response and cytoskeleton. CONCLUSIONS: Our immune-related lncRNA model could describe the immune contexture of tumor microenvironments and facilitate clinical therapeutic strategies by improving the prognostic efficacy of traditional tumor staging systems.

KEAP1/NFE2L2 Mutations of Liquid Biopsy as Prognostic Biomarkers in Patients With Advanced Non-Small Cell Lung Cancer: Results From Two Multicenter, Randomized Clinical Trials.

PURPOSE: The KEAP1-NFE2L2 (Kelch-like ECH-associated protein 1 (KEAP1)-Nuclear factor (erythroid-derived 2)-like 2 (NFE2L2)) mutations are associated with resistance to chemotherapy or immunotherapy in non-small cell lung cancer (NSCLC). Conversely, it has been reported that NFE2L2 mutations potentiate improved clinical outcome with immunotherapy. However, therapeutic benefits for patients with KEAP1/NFE2L2 mutations remain unclear. The purpose of this study was to investigate the association between KEAP1/NFE2L2 and NSCLC prognosis, and to explore whether immunotherapy can improve prognosis in populations with KEAP1/NFE2L2 mutations. EXPERIMENTAL DESIGN: The impact of KEAP1/NFE2L2 mutations on survival outcomes in NSCLC patients received immunotherapy and chemotherapy was verified in the randomized phase II/III POPLAR/OAK trials (blood-based sequencing, bNGS cohort, POPLAR (n = 211) and OAK (n = 642)). The Cancer Genome Atlas (TCGA) NSCLC cohort (n=998) and an in-house Chinese NSCLC cohort (n=733) was used For the analysis of immune-related markers. RESULTS: Compared with KEAP1/NFE2L2 wild-type, patients with KEAP1/NFE2L2 mutations were significantly associated with poorer overall survival (OS, HR = 1.97, 95% CI 1.48-2.63, P < 0.001) on atezolizumab and docetaxel (HR = 1.66, 95% CI 1.28-2.16, P < 0.001). In KEAP1/NFE2L2 mutant group, there was no significant difference in median OS between atezolizumab and docetaxel (HR 0.74, 95% CI 0.53-1.03, P = 0.07). NFE2L2/KEAP1 mutations were significantly associated with higher TMB values and PD-L1 expression in the OAK/POPLAR and in-house Chinese NSCLC cohorts. GSEA revealed that KEAP1/NFE2L2mutant subgroup was associated with deficient infiltration of CD4+ T cells, NK T cells and natural Treg cells, and lower expression of DNA damage response genes in TCGA NSCLC cohort. CONCLUSIONS: Our study revealed that patients with KEAP1/NFE2L2 mutations have a worse prognosis than wild-type patients, both on immunotherapy and chemotherapy. In addition, in patients with KEAP1/NFE2L2 mutations, immunotherapy did not significantly improve prognosis compared to chemotherapy.

A Comprehensive Landscape for Fibril Association Behaviors Encoded Synergistically by Saccharides and Peptides.

Nature provides us a panorama of fibrils with tremendous structural polymorphism from molecular building blocks to hierarchical association behaviors. Despite recent achievements in creating artificial systems with individual building blocks through self-assembly, molecularly encoding the relationship from model building blocks to fibril association, resulting in controlled macroscopic properties, has remained an elusive goal. In this paper, by employing a designed set of glycopeptide building blocks and combining experimental and computational tools, we report a library of controlled fibril polymorphism with elucidation from molecular packing to fibril association and the related macroscopic properties. The growth of the fibril either axially or radially with right- or left-handed twisting is determined by the subtle trade-off of oligosaccharide and oligopeptide components. Meanwhile, visible evidence for the association process of double-strand fibrils has been experimentally and theoretically proposed. Finally the fibril polymorphs demonstrated significant different macroscopic properties on hydrogel formation and cellular migration control.

Homologous recombination repair rathway and RAD54L in early-stage lung adenocarcinoma.

OBJECTIVE: The current study aims to identify the dysregulated pathway involved in carcinogenesis and the essential survival-related dysregulated genes among this pathway in the early stage of lung adenocarcinoma (LUAD). PATIENTS AND METHODS: Data from The Cancer Genome Atlas (TCGA) including 526 tumor tissues of LUAD and 59 healthy lung tissues were analyzed to gain differentially expressed genes (DEGs). Gene ontology (GO) analysis was conducted with DAVID, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs was performed, followed by gene set enrichment analysis (GSEA) methods. Survival analysis was implemented in TCGA dataset and validated in Gene Expression Omnibus (GEO) cohort GSE50081, which includes 127 patients with stage I LUAD. RESULTS: GSEA enrichment analysis suggested that homologous recombination repair (HRR) pathway was significantly enriched. Subsequent KEGG pathway enrichment analysis indicated the significant up-regulation of HRR pathway in patients with T1 stage LUAD. Retrieved in Gene database, RAD54L is involved in HRR pathway and were recognized to be significantly differentially expressed in T1 stage LUAD in our study. The survival analysis indicated that high expression of RAD54L was significantly related to worse overall survival in patients with T1 stage LUAD (TCGA cohort: HR=2.10, 95% CI [1.47-2.98], P = 0.001; GSE50081 validation cohort: HR = 2.61, 95% CI [1.51-4.52], P = 0.002). Multivariate cox regression analysis indicated that RAD54L is an independent prognostic factor in the early-stage LUAD. CONCLUSION: HRR pathway is up-regulated in LUAD, among which the expression of RAD54L was found to be significantly differentially expressed in T1 stage tumor tissue. Patients with high expression of RAD54L were associated with worse overall survival in the TCGA cohort and validation cohort. This study suggests a potential mechanism of lung cancer progression and provide a budding prognostic factor and treatment target in early-stage LUAD.

Dendritic Cell Targeting Peptide-Based Nanovaccines for Enhanced Cancer Immunotherapy.

Immunotherapy emerges as an effective avenue for tumor elimination and has many advantages compared with traditional surgery, radiotherapy, and chemotherapy. Tumor vaccines play an important role in cancer immunotherapy, while the application of tumor vaccines in clinical usage is limited because only limited response can be induced by primary tumor antigens. Accordingly, it is a key point to activate T-cell response with some novel tumor vaccines. Here, we applied phage display biopanning and screened a peptide (TY) that could combine with bone-marrow-derived-dendritic-cells (BMDCs) specifically and spleenic DCs. Then we developed mesoporous silica nanoparticles (MSN-TY/OVA/CpG), with peptide TY and OVA/CpG to target and activate DCs, respectively. Our results showed that the nanoparticles (NPs) could be specifically absorbed by DC in vitro, which enhanced the maturation and activation of DCs in vitro and in vivo. The in vitro study demonstrated the efficiency of nanoparticles in antigen uptake by BMDCs and in the activation of antigen-specific cytotoxic CD8+ T cells. Moreover, MSN-TY/OVA/CpG could activate antigen-specific CD8+ T cells and elicited the cytotoxic T lymphocyte (CTL) priming in naive C57BL/6J mice. Therapeutic application of MSN-TY/OVA/CpG enhanced the activation of DCs and the introducing of CD8+ T cell-mediated immune response to promote tumor elimination, prolong survival of tumor-bearing mice, and cause less systemic toxicity. All these results showed that the targeted nanovaccines could deliver antigen into DCs and activate cancer immunotherapy.

LncTIC1 interacts with ß-catenin to drive liver TIC self-renewal and liver tumorigenesis.

Liver tumor-initiating cells (TICs) are drivers of liver tumorigenesis, and Wnt/ß-catenin activation plays a principal role in the self-renewal of liver TICs. Despite a deep understanding of Wnt/ß-catenin regulation, the roles of long noncoding RNAs (lncRNAs) in Wnt/ß-catenin activation and liver TIC self-renewal are largely unknown. Here, we performed unbiased screening of lncRNAs in liver tumorigenesis and found lncTIC1 was highly expressed with liver tumorigenesis. LncTIC1 was also highly expressed in liver TICs and required for the self-renewal of liver TICs. LncTIC1 drove liver TIC self-renewal through Wnt/ß-catenin signaling. LncTIC1 interacted with the N terminal of ß-catenin and inhibited the phosphorylation of ß-catenin, finally maintaining the stability of ß-catenin to drive the activation of Wnt/ß-catenin signaling. Through ß-catenin maintenance and Wnt/ß-catenin regulation, lncTIC1 participated in liver TIC self-renewal, liver tumorigenesis and tumor propagation. Moreover, blockade of lncTIC1 signaling greatly inhibited the propagation of liver cancer and liver TICs.

LncFZD6 initiates Wnt/ß-catenin and liver TIC self-renewal through BRG1-mediated FZD6 transcriptional activation.

Liver tumor-initiating cells (TICs), the drivers for liver tumorigenesis, accounts for liver tumor initiation, metastasis, drug resistance and relapse. Wnt/ß-catenin signaling pathway emerges as a critical modulator in liver TIC self-renewal. However, the molecular mechanism of Wnt/ß-catenin initiation in liver tumorigenesis and liver TICs is still elusive. Here, we examined the expression pattern of 10 Wnt receptors (FZD1-FZD10), and found only FZD6 is overexpressed along with liver tumorigenesis. What's more, a divergent lncRNA of FZD6, termed lncFZD6, is also highly expressed in liver cancer and liver TICs. LncFZD6 drives liver TIC self-renewal and tumor initiation capacity through FZD6-dependent manner. LncFZD6 interacts with BRG1-embedded SWI/SNF complex and recruits it to FZD6 promoter, and thus drives the transcriptional initiation of FZD6 by chromatin remodeling. WNT5A, a ligand of FZD6, is highly expressed in liver non-TICs and drives the self-renewal of liver TICs through lncFZD6-BRG1-FZD6-dependent manner. Through FZD6 transcriptional regulation in cis, lncFZD6 activates Wnt/ß-catenin signaling in liver TICs. LncFZD6-BRG1-Wnt5A/ß-catenin pathway can serve as a target for liver TIC elimination. Altogether, lncFZD6 promotes Wnt/ß-catenin activation and liver TIC self-renewal through BRG1-dependent FZD6 expression.