A TGF-ß-dominant chemoresistant phenotype of hepatoblastoma associated with aflatoxin exposure in children.

BACKGROUND AND AIMS: Hepatoblastoma (HB) is the most common liver cancer in children, posing a serious threat to children's health. Chemoresistance is the leading cause of mortality in patients with HB. A more explicit definition of the features of chemotherapy resistance in HB represents a fundamental urgent need. APPROACH AND RESULTS: We performed an integrative analysis including single-cell RNA sequencing, whole-exome sequencing, and bulk RNA sequencing in 180 HB samples, to reveal genomic features, transcriptomic profiles, and the immune microenvironment of HB. Multicolor immunohistochemistry staining and in vitro experiments were performed for validation. Here, we reported four HB transcriptional subtypes primarily defined by differential expression of transcription factors. Among them, the S2A subtype, characterized by strong expression of progenitor ( MYCN , MIXL1 ) and mesenchymal transcription factors ( TWIST1 , TBX5 ), was defined as a new chemoresistant subtype. The S2A subtype showed increased TGF-ß cancer-associated fibroblast and an immunosuppressive microenvironment induced by the upregulated TGF-ß of HB. Interestingly, the S2A subtype enriched SBS24 signature and significantly higher serum aflatoxin B1-albumin (AFB1-ALB) level in comparison with other subtypes. Functional assays indicated that aflatoxin promotes HB to upregulate TGF-ß. Furthermore, clinical prognostic analysis showed that serum AFB1-ALB is a potential indicator of HB chemoresistance and prognosis. CONCLUSIONS: Our studies offer new insights into the relationship between aflatoxin and HB chemoresistance and provide important implications for its diagnosis and treatment.

Hypoxia-driven tumor stromal remodeling and immunosuppressive microenvironment in scirrhous HCC.

BACKGROUND AND AIMS: Scirrhous HCC (SHCC) is one of the unique subtypes of HCC, characterized by abundant fibrous stroma in the tumor microenvironment. However, the molecular traits of SHCC remain unclear, which is essential to develop specialized therapeutic approaches for SHCC. APPROACH AND RESULTS: We presented an integrative analysis containing single-cell RNA-sequencing, whole-exome sequencing, and bulk RNA-sequencing in SHCC and usual HCC samples from 134 patients to delineate genomic features, transcriptomic profiles, and stromal immune microenvironment of SHCC. Multiplexed immunofluorescence staining, flow cytometry, and functional experiments were performed for validation. Here, we identified SHCC presented with less genomic heterogeneity while possessing a unique transcriptomic profile different from usual HCC. Insulin-like growth factor 2 was significantly upregulated in SHCC tumor cells compared to usual HCC, and could serve as a potential diagnostic biomarker for SHCC. Significant tumor stromal remodeling and hypoxia were observed in SHCC with enrichment of matrix cancer-associated fibroblasts and upregulation of hypoxic pathways. Insulin-like growth factor 2 was identified as a key mediator in shaping the hypoxic stromal microenvironment of SHCC. Under this microenvironment, SHCC exhibited an immunosuppressive niche correlated to enhanced VEGFA signaling activity, where CD4 + T cells and CD8 + T cells were dysfunctional. Furthermore, we found that another hypoxic-related molecule SPP1 from SHCC tumor cells suppressed the function of dendritic cells via the SPP1-CD44 axis, which also probably hindered the activation of T cells. CONCLUSION: We uncovered the genomic characteristics of SHCC, and revealed a hypoxia-driven tumor stroma remodeling and immunosuppressive microenvironment in SHCC.

Distinct single-cell immune ecosystems distinguish true and de novo HBV-related hepatocellular carcinoma recurrences.

OBJECTIVE: Revealing the single-cell immune ecosystems in true versus de novo hepatocellular carcinoma (HCC) recurrences could help the optimal development of immunotherapies. DESIGN: We performed 5'and VDJ single-cell RNA-sequencing on 34 samples from 20 recurrent HCC patients. Bulk RNA-sequencing, flow cytometry, multiplexed immunofluorescence, and in vitro functional analyses were performed on samples from two validation cohorts. RESULTS: Analyses of mutational profiles and evolutionary trajectories in paired primary and recurrent HCC samples using whole-exome sequencing identified de novo versus true recurrences, some of which occurred before clinical diagnosis. The tumour immune microenvironment (TIME) of truly recurrent HCCs was characterised by an increased abundance in KLRB1+CD8+ T cells with memory phenotype and low cytotoxicity. In contrast, we found an enrichment in cytotoxic and exhausted CD8+ T cells in the TIME of de novo recurrent HCCs. Transcriptomic and interaction analyses showed elevated GDF15 expression on HCC cells in proximity to dendritic cells, which may have dampened antigen presentation and inhibited antitumour immunity in truly recurrent lesions. In contrast, myeloid cells' cross talk with T cells-mediated T cell exhaustion and immunosuppression in the TIME of de novo recurrent HCCs. Consistent with these findings, a phase 2 trial of neoadjuvant anti-PD-1 immunotherapy showed more responses in de novo recurrent HCC patients. CONCLUSION: True and de novo HCC recurrences occur early, have distinct TIME and may require different immunotherapy strategies. Our study provides a source for genomic diagnosis and immune profiling for guiding immunotherapy based on the type of HCC recurrence and the specific TIME.

Identification of DNA methylation signatures for hepatocellular carcinoma detection and microvascular invasion prediction.

BACKGROUND AND AIM: Preoperative evaluation of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) is important for surgical strategy determination. We aimed to develop and establish a preoperative predictive model for MVI status based on DNA methylation markers. METHODS: A total of 35 HCC tissues and the matched peritumoral normal liver tissues as well as 35 corresponding HCC patients' plasma samples and 24 healthy plasma samples were used for genome-wide methylation sequencing and subsequent methylation haplotype block (MHB) analysis. Predictive models were constructed based on selected MHB markers and 3-cross validation was used. RESULTS: We grouped 35 HCC patients into 2 categories, including the MVI- group with 17 tissue and plasma samples, and MVI + group with 18 tissue and plasma samples. We identified a tissue DNA methylation signature with an AUC of 98.0% and a circulating free DNA (cfDNA) methylation signature with an AUC of 96.0% for HCC detection. Furthermore, we established a tissue DNA methylation signature for MVI status prediction, and achieved an AUC of 85.9%. Based on the MVI status predicted by the DNA methylation signature, the recurrence-free survival (RFS) and overall survival (OS) were significantly better in the predicted MVI- group than that in the predicted MVI + group. CONCLUSIONS: In this study, we identified a cfDNA methylation signature for HCC detection and a tissue DNA methylation signature for MVI status prediction with high accuracy.

U1RNP/lncRNA/Transcription Cycle Axis Promotes Tumorigenesis of Hepatocellular Carcinoma.

As a component of the spliceosome, U1 small nuclear ribonucleoproteins (U1RNPs) play critical roles in RNA splicing, and recent studies have shown that U1RNPs could recruit long non-coding RNAs (lncRNAs) to chromatin which are involved in cancer development. However, the interplay of U1 snRNP, lncRNAs and downstream genes and signaling pathways are insufficiently understood in hepatocellular carcinoma (HCC). The expression of U1RNPs was found to be significantly higher in tumors than normal tissues in liver hepatocellular carcinomas of The Cancer Genome Atlas (TCGA-LIHC) dataset. LncRNAs with potential U1-binding sites (termed U1-lncRNAs) were found to be mostly located in the nucleus and their expression was higher in tumor than in normal tissues Bioinformatic analysis indicated that U1-lncRNAs worked with RNA-binding proteins and regulated the transcription cycle in HCC. A U1-lncRNA risk model was constructed using a TCGA dataset, and the AUCs of this risk model to predict 1-, 3- and 5-year overall survival were 0.82, 0.84 and 0.8, respectively. Furthermore, silencing of the small nuclear ribonucleoprotein D2 polypeptide (SNRPD2) resulted in impaired proliferation, G1/M cell cycle arrest and downregulation of transcription-cycle-related genes in HCC cell lines. Taken together, these results indicate that U1RNPs interact with lncRNAs and promote the transcription cycle process in HCC, which suggests that these could be novel biomarkers in the clinical management of HCC.

Combination Neoantigen-Based Dendritic Cell Vaccination and Adoptive T-Cell Transfer Induces Antitumor Responses Against Recurrence of Hepatocellular Carcinoma.

A high rate of recurrence after curative therapy is a major challenge for the management of hepatocellular carcinoma (HCC). Currently, no effective adjuvant therapy is available to prevent HCC recurrence. We designed a personalized neoantigen-loaded dendritic cell vaccine and neoantigen-activated T-cell therapy, and used it as adjuvant therapy to treat 10 patients with HCC who had undergone curative resection or radiofrequency ablation in the first stage of a phase II trial (NCT03067493). The primary outcomes were safety and neoantigen-specific immune response. Disease-free survival (DFS) was also evaluated. The immunotherapy was successfully administered to all the patients without unexpected delay and demonstrated a reasonable safety profile with no grade ≥3 treatment-related side effects reported. Seventy percent of patients generated de novo circulating multiclonal neoantigen-specific T-cell responses. Induced neoantigen-specific immunity was maintained over time, and epitope spreading was observed. Patients who generated immune responses to treatment exhibited prolonged DFS compared with nonresponders (P = 0.012), with 71.4% experiencing no relapse for 2 years after curative treatment. High expression of an immune stimulatory signature, enhanced immune-cell infiltration (i.e., CD8+ T cells), and upregulated expression of T-cell inflammatory gene profiles were found in the primary tumors of the responders. In addition, neoantigen depletion (immunoediting) was present in the recurrent tumors compared with the primary tumors (7/9 vs. 1/17, P = 0.014), suggesting that immune evasion occurred under the pressure of immunotherapy. Our study indicates that neoantigen-based combination immunotherapy is feasible, safe, and has the potential to reduce HCC recurrence after curative treatment.

Driver mutations in ADGRL3 are involved in the evolution of ependymoma.

Although there have been recent advances in the molecular pathology of ependymomas, little is known about the underlying molecular evolution during its development. Here, we assessed the clinical, pathological and molecular evolutionary process of ependymoma recurrence in a 9-year-old patient who had seven recurrences of supratentorial ependymoma and died from intracranial multiregional recurrences at the age of 19 years old. Whole-genome sequencing (WGS) of 7 tumor samples (1 primary and 6 subsequent recurrent tumors) was performed to elucidate the mutation landscape and identify potential driver mutations for tumor evolution. The genetic profiles of the seven tumor specimens showed significant heterogeneity and suggested a highly branched evolutionary pattern. The mutational signatures and chromothripsis changed with treatments. Strikingly, adhesion G protein-coupled receptor L3 (ADGRL3, also known as Latrophilins 3, LPNH3) was found to be consistently mutated during the entire disease process. However, Sanger sequencing of other 78 ependymoma patients who underwent surgery at our institution showed no genetic alteration of ADGRL3, as found in the present case. The mRNA levels of ADGRL3 were significantly lower in ependymomas (n = 36), as compared with normal brain tissue (n = 3). Grade III ependymomas had the lowest ADGRL3 expression. Moreover, ependymomas with lower mRNA level of ADGRL3 had shorter overall survival. Our findings, therefore, demonstrate a rare evolutionary process of ependymoma involving ADGRL3.

Multiomic Analysis Reveals Comprehensive Tumor Heterogeneity and Distinct Immune Subtypes in Multifocal Intrahepatic Cholangiocarcinoma.

PURPOSE: Targeted therapy and immunotherapy are transforming the treatment approach for intrahepatic cholangiocarcinoma (ICC). However, little is known about the intertumor heterogeneity (ITH) of multifocal ICC and its impacts on patient response to these treatments. We aimed to characterize the immunogenomic and epigenomic heterogeneity of multifocal ICC to guide treatment decision making. EXPERIMENTAL DESIGN: We obtained 66 tumor samples from 16 patients with multifocal ICC and characterized the tumor and immune heterogeneity using whole-exome sequencing, bulk and single-cell RNA sequencing, methylation microarray, and multiplex immunostaining. Patients were divided into high- or low-ITH groups according to the median ITH index. Two independent cohorts were used to validate findings. Responses to anti-PD-1 therapy were assessed. RESULTS: Multifocal ICC presented considerable intertumor genomic, transcriptional, and epigenomic heterogeneity within a patient in high ITH group. The immune profile among multiple tumors within a patient was relatively less heterogeneous in high- or low-ITH group, and consistent responses of multiple tumors to anti-PD-1 immunotherapy were observed. Unsupervised clustering of immune markers identified one low and one high immune subtype, with higher immune cell infiltration, closer tumor-immune cell interactions, and upregulated IFN-signature expression in high-immune subtype. Determining expression levels of CD8B and ICOS facilitated this immune classification and prediction of patient prognosis. Finally, promoter DNA methylation contributed to different immune profiles of two subtypes by regulating immune-gene expression. CONCLUSIONS: There is comprehensive heterogeneity in the genome, transcriptome, and epigenome of multifocal ICC. On the basis of the less heterogeneous immune profile of ICC, we suggest an immune classification that stratifies patients' prognosis and may support personalized immunotherapy.

BBCancer: an expression atlas of blood-based biomarkers in the early diagnosis of cancers.

The early detection of cancer holds the key to combat and control the increasing global burden of cancer morbidity and mortality. Blood-based screenings using circulating DNAs (ctDNAs), circulating RNA (ctRNAs), circulating tumor cells (CTCs) and extracellular vesicles (EVs) have shown promising prospects in the early detection of cancer. Recent high-throughput gene expression profiling of blood samples from cancer patients has provided a valuable resource for developing new biomarkers for the early detection of cancer. However, a well-organized online repository for these blood-based high-throughput gene expression data is still not available. Here, we present BBCancer (http://bbcancer.renlab.org/), a web-accessible and comprehensive open resource for providing the expression landscape of six types of RNAs, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), microRNAs (miRNAs), circular RNAs (circRNAs), tRNA-derived fragments (tRFRNAs) and Piwi-interacting RNAs (piRNAs) in blood samples, including plasma, CTCs and EVs, from cancer patients with various cancer types. Currently, BBCancer contains expression data of the six RNA types from 5040 normal and tumor blood samples across 15 cancer types. We believe this database will serve as a powerful platform for developing blood biomarkers.

lnCAR: A Comprehensive Resource for lncRNAs from Cancer Arrays.

Long noncoding RNAs (lncRNA) have emerged as promising biomarkers in cancer diagnosis, treatment, and prognosis. Recent studies suggest that a large number of coding gene expression microarray probes could be reannotated as lncRNAs. Microarray, once the most cutting-edge high-throughput gene expression technology, has been used for thousands of cancer studies and has brought invaluable resources for studying the functions of lncRNA in cancer development. However, a comprehensive lncRNA resource based on microarray data is still lacking. Here, we present lnCAR (lncRNAs from cancer arrays), a comprehensive open resource for providing expression profiles and prognostic landscape of lncRNAs derived from reannotation of public microarray data. Currently, lnCAR contains 52,300 samples for differential expression analysis and 12,883 samples for survival analysis from 10 cancer types. lnCAR allows users to interactively explore any annotated or novel lncRNAs. We believe lnCAR will serve as a valuable resource for the community focused on lncRNA research in cancer. SIGNIFICANCE: lnCAR, a new interactive tool of reannotated public cancer-related microarray data, provides expression profiles and prognostic landscapes of lncRNAs across thousands of samples and multiple cancer types.