Dendritic-cell-targeting virus-like particles as potent mRNA vaccine carriers.

Messenger RNA vaccines lack specificity for dendritic cells (DCs)-the most effective cells at antigen presentation. Here we report the design and performance of a DC-targeting virus-like particle pseudotyped with an engineered Sindbis-virus glycoprotein that recognizes a surface protein on DCs, and packaging mRNA encoding for the Spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or for the glycoproteins B and D of herpes simplex virus 1. Injection of the DC-targeting SARS-CoV-2 mRNA vaccine in the footpad of mice led to substantially higher and durable antigen-specific immunoglobulin-G titres and cellular immune responses than untargeted virus-like particles and lipid-nanoparticle formulations. The vaccines also protected the mice from infection with SARS-CoV-2 or with herpes simplex virus 1. Virus-like particles with preferential uptake by DCs may facilitate the development of potent prophylactic and therapeutic vaccines.

Cooperation between IRTKS and deubiquitinase OTUD4 enhances the SETDB1-mediated H3K9 trimethylation that promotes tumor metastasis via suppressing E-cadherin expression.

Elevated expression and genetic aberration of IRTKS, also named as BAIAP2L1, have been observed in many tumors, especially in tumor progression. however, the molecular and cellular mechanisms involved in the IRTKS-enhanced tumor progression are obscure. Here we show that higher IRTKS level specifically increases histone H3 lysine 9 trimethylation (H3K9me3) by promoting accumulation of the histone methyltransferase SETDB1. Furthermore, we reveal that IRTKS recruits the deubiquitinase OTUD4 to remove Lys48-linked polyubiquitination at K182/K1050 sites of SETDB1, thus blocking SETDB1 degradation via the ubiquitin-proteasome pathway. Interestingly, the enhanced IRTKS-OTUD4-SETDB1-H3K9me3 axis leads to a general decrease in chromatin accessibility, which inhibits transcription of CDH1 encoding E-cadherin, a key molecule essential for maintaining epithelial cell phenotype, and therefore results in epithelial-mesenchymal transition (EMT) and malignant cell metastasis. Clinically, the elevated IRTKS levels in tumor specimens correlate with SETDB1 levels, but negatively associate with survival time. Our data reveal a novel mechanism for the IRTKS-enhanced tumor progression, where IRTKS cooperates with OTUD4 to enhance SETDB1-mediated H3K9 trimethylation that promotes tumor metastasis via suppressing E-cadherin expression. This study also provides a potential approach to reduce the activity and stability of the known therapeutic target SETDB1 possibly through regulating IRTKS or deubiquitinase OTUD4.

Accurate tumor clonal structures require single-cell analysis.

Tumor clonal structure is closely related to future progression, which has been mainly investigated as mutation abundance clustering in bulk samples. With relatively limited studies at single-cell resolution, a systematic comparison of the two approaches is still lacking. Here, using bulk and single-cell mutational data from the liver and colorectal cancers, we checked whether co-mutations determined by single-cell analysis had corresponding bulk variant allele frequency (VAF) peaks. While bulk analysis suggested the absence of subclonal peaks and, possibly, neutral evolution in some cases, the single-cell analysis identified coexisting subclones. The overlaps of bulk VAF ranges for co-mutations from different subclones made it difficult to separate them. Complex subclonal structures and dynamic evolution could be hidden under the seemingly clonal neutral pattern at the bulk level, suggesting single-cell analysis is necessary to avoid underestimation of tumor heterogeneity.

DLK1-directed chimeric antigen receptor T-cell therapy for hepatocellular carcinoma.

BACKGROUND: Delta-like homologue 1 (DLK1), a transmembrane protein, is highly expressed in hepatocellular carcinoma (HCC). We explored whether DLK1-directed chimeric antigen receptor (CAR) T cells can specifically eliminate DLK1-positive HCC cells and serve as a therapeutic strategy for HCC immunotherapy. METHODS: We first characterized a homemade anti-human DLK1 monoclonal antibody, sequenced the single-chain Fragment variable (scFv) and integrated it into the second-generation CAR lentiviral vector, and then developed the DLK1-directed CAR-T cells. The cytotoxic activities of DLK1-directed CAR-T cells against different HCC cells were evaluated in vitro and in vivo. RESULTS: The genetically modified human T cells with the DLK1-directed CARs produced cytotoxic activity against DLK1-positive HCC cells. Additionally, the DLK1-directed CARs enhanced T cell proliferation and activation in a DLK1-dependent manner. Interestingly, the DLK1-targeted CAR-T cells significantly inhibited both subcutaneous and peritoneal xenograft tumours derived from human liver cancer cell lines HepG2 or Huh-7. CONCLUSION: DLK1-directed CAR-T cells specifically suppresses DLK1-positive HCC cells in vitro and in vivo. This study provides a novel transmembrane antigen DLK1 as a potential therapeutic target appropriate for CAR-T cell therapy, which may be further developed as a clinical therapeutic strategy for HCC immunotherapy.

Inhibition of Arid1a increases stem/progenitor cell-like properties of liver cancer.

ARID1A, a key subunit of the SWI/SNF chromatin remodeling complex, exhibits recurrent mutations in various types of human cancers, including liver cancer. However, the function of ARID1A in the pathogenesis of liver cancer remains controversial. Here, we demonstrate that Arid1a knockout may result in states of different cell differentiation, as indicated by single-cell RNA sequencing (scRNA-seq) analysis. Bulk RNA-seq also revealed that Arid1a deficiency upregulated these genes related to cell stemness and differentiation, but downregulated genes related to the hepatic functions. Furthermore, we confirmed that deficiency of Arid1a increased the expression of hepatic stem/progenitor cell markers, such as Cd133 and Epcam, and enhanced the self-renewal ability of cells. Mechanistic studies revealed that Arid1a loss remodeled the chromatin accessibility of some genes related to liver functions. Thus, Arid1a deficiency might contribute to cancer development by increasing the number of stem/progenitor-like cells through dysregulating the expression of these genes related to cell stemness, differentiation and liver functions.

Exposure to aristolochic acid I is associated with poor prognosis of liver cancer patients.

The aristolochic acids (AAs), derived from Aristolochia and Asarum species used widely in herbal medicines, are closely associated with liver cancer. The major AA derivatives are aristolochic acid I (AAI) and II (AAII), which can bind DNA covalently to form AA-DNA adducts after metabolic activation in vivo. Among all these AA-DNA adducts, 7-(deoxyadenosine-N6-yl) aristolactam I (dA-AL-I) is the most abundant and persistent DNA lesion in patients. However, the direct evidence indicating AA exposure in human liver cancer is still missing. Here, we analyzed dA-AL-I adduct, the direct biomarker of AAI exposure, by ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-TQ/MS) in 209 liver cancer patients. Also, DNA samples from mice treated with/without AAI were used as positive and negative controls. dA-AL-I adduct was present in 110 of 209 (52.6%) patients, indicating that these patients were exposed to AAI prior to their clinical investigations and also had a worse prognosis. The relative high AA exposure rate and worse prognosis in our cohort of patients emphasize the significance to increase public awareness to avoid the use of herbal medicine containing AAs or their derivatives.

BRD4 inhibition induces synthetic lethality in ARID2-deficient hepatocellular carcinoma by increasing DNA damage.

Hepatocellular carcinoma (HCC) has emerged as the third cause of cancer-related death owing to lacking effective systemic therapies. Genomic DNA sequencing revealed the high frequency of loss-of-function mutations in ARID2, which encodes a subunit of SWI/SNF chromatin remodeling complex, however, the therapeutic strategy for the HCC patients with ARID2 mutations is still completely unclear. In this study, we first performed a high-throughput screening approach using a compound library consisting of 2 180 FDA-approved drugs and other compounds, to elicit the potential drugs for synthetic lethality to target ARID2-deficient HCC cells. Interestingly, JQ1, a selective inhibitor of bromodomain protein BRD4, uniquely suppressed the growth of ARID2- deficient HCC cells. Next JQ1 is further confirmed to predominantly induce cell lethality upon ARID2 depletion through exacerbating DNA damage, especially double strand breaks (DSBs). Functional assays demonstrated that both BRD4 inhibition and ARID2 deficiency synergistically impede two main DNA damage repair pathways, homologous recombination (HR) and non-homologous end-joining (NHEJ), through attenuating the transcription of BRCA1, RAD51, and 53BP1, which encode the core molecules responsible for DSB repair. Mechanistically, both ARID2 and BRD4 exert a synergistic effect for maintaining transcriptional enhancer-promoter loops of these genes within chromatin conformation. However, as both ARID2 and BRD4 are disrupted, the expression of these DNA repair-related genes in response to DNA damage are hindered, resulting in DSB accumulation and cell apoptosis. Taken together, this study discloses that BRD4 inhibition may induce synthetic lethality in ARID2-deficient HCC cells, which might provide a potential therapeutic strategy for HCC patients with ARID2 mutations.

Cinobufagin Is a Selective Anti-Cancer Agent against Tumors with EGFR Amplification and PTEN Deletion.

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor, and almost half of the patients carrying EGFR-driven tumor with PTEN deficiency are resistant to EGFR-targeted therapy. EGFR amplification and/or mutation is reported in various epithelial tumors. This series of studies aimed to identify a potent compound against EGFR-driven tumor. We screened a chemical library containing over 600 individual compounds purified from Traditional Chinese Medicine against GBM cells with EGFR amplification and found that cinobufagin, the major active ingredient of Chansu, inhibited the proliferation of EGFR amplified GBM cells and PTEN deficiency enhanced its anti-proliferation effects. Cinobufagin also strongly inhibited the proliferation of carcinoma cell lines with wild-type or mutant EGFR expression. In contrast, the compound only weakly inhibited the proliferation of cancer cells with low or without EGFR expression. Cinobufagin blocked EGFR phosphorylation and its downstream signaling, which additionally induced apoptosis and cytotoxicity in EGFR amplified cancer cells. In vivo, cinobufagin blocked EGFR signaling, inhibited cell proliferation, and elicited apoptosis, thereby suppressing tumor growth in both subcutaneous and intracranial U87MG-EGFR xenograft mouse models and increasing the median survival of nude mice bearing intracranial U87MG-EGFR tumors. Cinobufagin is a potential therapeutic agent for treating malignant glioma and other human cancers expressing EGFR.

ARID1A deficiency weakens BRG1-RAD21 interaction that jeopardizes chromatin compactness and drives liver cancer cell metastasis.

ARID1A, encoding a subunit of SWI/SNF chromatin remodeling complex, is widely recognized as a tumor suppressor gene in multiple tumor types including liver cancer. Previous studies have demonstrated that ARID1A deficiency can cause liver cancer metastasis, possibly due to the altered chromatin organization, however the underlying mechanisms remain poorly understood. To address the effect of Arid1a deficiency on chromatin organization, we generated chromatin interaction matrices, and exploited the conformation changes upon Arid1a depletion in hepatocytes. Our results demonstrated that Arid1a deficiency induced A/B compartment switching, topologically associated domain (TAD) remodeling, and decrease of chromatin loops. Further mechanism studies revealed that ATPase BRG1 of SWI/SNF complex could physically interact with RAD21, a structural subunit of chromatin architectural element cohesin; whereas ARID1A deficiency significantly diminished the coupled BRG1-RAD21. Interestingly, the tumor-associated genes within the switched compartments were differentially expressed depending upon Arid1a depletion or not. As a consequence of ARID1A deficiency-induced conformational alteration, the dysregulation of some genes such as PMP22 and GSC, promoted the invasion capacity of liver cancer cells. This study provides an insight into liver cancer tumorigenesis and progression related to ARID1A mutations.

Clonal evolution in liver cancer at single-cell and single-variant resolution.

Genetic heterogeneity of tumor is closely related to its clonal evolution, phenotypic diversity and treatment resistance, and such heterogeneity has only been characterized at single-cell sub-chromosomal scale in liver cancer. Here we reconstructed the single-variant resolution clonal evolution in human liver cancer based on single-cell mutational profiles. The results indicated that key genetic events occurred early during tumorigenesis, and an early metastasis followed by independent evolution was observed in primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. By parallel single-cell RNA-Seq, the transcriptomic phenotype of HCC was found to be related with genetic heterogeneity. For the first time we reconstructed the single-cell and single-variant clonal evolution in human liver cancer, and dissection of both genetic and phenotypic heterogeneity will facilitate better understanding of their relationship.

LZP is required for hepatic triacylglycerol transportation through maintaining apolipoprotein B stability.

The conserved zona pellucida (ZP) domain is found in hundreds of extracellular proteins that are expressed in various organs and play a variety of roles as structural components, receptors and tumor suppressors. A liver-specific zona pellucida domain-containing protein (LZP), also named OIT3, has been shown to be mainly expressed in human and mouse hepatocytes; however, the physiological function of LZP in the liver remains unclear. Here, we show that Lzp deletion inhibited very low-density lipoprotein (VLDL) secretion, leading to hepatic TG accumulation and lower serum TG levels in mice. The apolipoprotein B (apoB) levels were significantly decreased in the liver, serum, and VLDL particles of LZP-deficient mice. In the presence of LZP, which is localized to the endoplasmic reticulum (ER) and Golgi apparatus, the ER-associated degradation (ERAD) of apoB was attenuated; in contrast, in the absence of LZP, apoB was ubiquitinated by AMFR, a known E3 ubiquitin ligase specific for apoB, and was subsequently degraded, leading to lower hepatic apoB levels and inhibited VLDL secretion. Interestingly, hepatic LZP levels were elevated in mice challenged with a high-fat diet and humans with simple hepatic steatosis, suggesting that LZP contributes to the physiological regulation of hepatic TG homeostasis. In general, our data establish an essential role for LZP in hepatic TG transportation and VLDL secretion by preventing the AMFR-mediated ubiquitination and degradation of apoB and therefore provide insight into the molecular function of LZP in hepatic lipid metabolism.

A novel neoantigen discovery approach based on chromatin high order conformation.

BACKGROUND: High-throughput sequencing technology has yielded reliable and ultra-fast sequencing for DNA and RNA. For tumor cells of cancer patients, when combining the results of DNA and RNA sequencing, one can identify potential neoantigens that stimulate the immune response of the T cell. However, when the somatic mutations are abundant, it is computationally challenging to efficiently prioritize the identified neoantigen candidates according to their ability of activating the T cell immuno-response. METHODS: Numerous prioritization or prediction approaches have been proposed to address this issue but none of them considers the original DNA loci of the neoantigens from the perspective of 3D genome. Based on our previous discoveries, we propose to investigate the distribution of neoantigens with different immunogenicity abilities in 3D genome and propose to adopt this important information into neoantigen prediction. RESULTS: We retrospect the DNA origins of the immuno-positive and immuno-negative neoantigens in the context of 3D genome and discovered that DNA loci of the immuno-positive neoantigens and immuno-negative neoantigens have very different distribution pattern. Specifically, comparing to the background 3D genome, DNA loci of the immuno-positive neoantigens tend to locate at specific regions in the 3D genome. We thus used this information into neoantigen prediction and demonstrated the effectiveness of this approach. CONCLUSION: We believe that the 3D genome information will help to increase the precision of neoantigen prioritization and discovery and eventually benefit precision and personalized medicine in cancer immunotherapy.

[A method for reliable detection of genomic point mutations based on single-cell target-sequencing].

The analysis of genomic point mutations is one of the research strategies to explore the clonal evolution of tumor cells. At present, clonal evolution of tumor cells is mainly determined by bulk sampling and sequencing of different sections of the tumor. Since this approach analyzes a mixture of different cell types, it may not accurately represent the clonal evolution of specific tumor cell populations and likely miss low frequency mutations, especially when the sequencing depths are not sufficient. To address this issue, we have developed a strategy to analyze genomic point mutations from prostate basal cell carcinoma (BCC) tissues at single-cell resolution. Firstly, we optimized the single-cell whole genome amplification procedure with HepG2 cells. Then the single cells from BCC tissue were captured by a microfluidic chip of Fluidigm and processed for whole-genome amplification. Both SCUBE3 and MST1L genomic mutations were obtained by whole exome sequencing. Finally, we examined the genomic mutations through single-cell targeted amplification and Sanger sequencing. The established method successfully reconfirmed the mutations of SCUBE3 and MST1L in BCC at single cell level. The strategy established in this study could provide a useful tool for determining the clonal evolution of tumor cells based on genomic mutations at single-cell resolution.

Investigating higher-order interactions in single-cell data with scHOT.

Single-cell genomics has transformed our ability to examine cell fate choice. Examining cells along a computationally ordered 'pseudotime' offers the potential to unpick subtle changes in variability and covariation among key genes. We describe an approach, scHOT-single-cell higher-order testing-which provides a flexible and statistically robust framework for identifying changes in higher-order interactions among genes. scHOT can be applied for cells along a continuous trajectory or across space and accommodates various higher-order measurements including variability or correlation. We demonstrate the use of scHOT by studying coordinated changes in higher-order interactions during embryonic development of the mouse liver. Additionally, scHOT identifies subtle changes in gene-gene correlations across space using spatially resolved transcriptomics data from the mouse olfactory bulb. scHOT meaningfully adds to first-order differential expression testing and provides a framework for interrogating higher-order interactions using single-cell data.

DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning.

MOTIVATION: The mutations of cancers can encode the seeds of their own destruction, in the form of T-cell recognizable immunogenic peptides, also known as neoantigens. It is computationally challenging, however, to accurately prioritize the potential neoantigen candidates according to their ability of activating the T-cell immunoresponse, especially when the somatic mutations are abundant. Although a few neoantigen prioritization methods have been proposed to address this issue, advanced machine learning model that is specifically designed to tackle this problem is still lacking. Moreover, none of the existing methods considers the original DNA loci of the neoantigens in the perspective of 3D genome which may provide key information for inferring neoantigens' immunogenicity. RESULTS: In this study, we discovered that DNA loci of the immunopositive and immunonegative MHC-I neoantigens have distinct spatial distribution patterns across the genome. We therefore used the 3D genome information along with an ensemble pMHC-I coding strategy, and developed a group feature selection-based deep sparse neural network model (DNN-GFS) that is optimized for neoantigen prioritization. DNN-GFS demonstrated increased neoantigen prioritization power comparing to existing sequence-based approaches. We also developed a webserver named deepAntigen (http://yishi.sjtu.edu.cn/deepAntigen) that implements the DNN-GFS as well as other machine learning methods. We believe that this work provides a new perspective toward more accurate neoantigen prediction which eventually contribute to personalized cancer immunotherapy. AVAILABILITY AND IMPLEMENTATION: Data and implementation are available on webserver: http://yishi.sjtu.edu.cn/deepAntigen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutational and transcriptomic landscapes of a rare human prostate basal cell carcinoma.

BACKGROUND: As a rare subtype of prostate carcinoma, basal cell carcinoma (BCC) has not been studied extensively and thus lacks systematic molecular characterization. METHODS: Here, we applied single-cell genomic amplification and RNA-Seq to a specimen of human prostate BCC (CK34ßE12+ /P63+ /PAP- /PSA- ). The mutational landscape was obtained via whole exome sequencing of the amplification mixture of 49 single cells, and the transcriptomes of 69 single cells were also obtained. RESULTS: The five putative driver genes mutated in BCC are CASC5, NUTM1, PTPRC, KMT2C, and TBX3, and the top three nucleotide substitutions are C>T, T>C, and C>A, similar to common prostate cancer. The distribution of the variant allele frequency values indicated that these single cells are from the same tumor clone. The 69 single cells were clustered into tumor, stromal, and immune cells based on their global transcriptomic profiles. The tumor cells specifically express basal cell markers like KRT5, KRT14, and KRT23 and epithelial markers EPCAM, CDH1, and CD24. The transcription factor covariance network analysis showed that the BCC tumor cells have distinct regulatory networks. By comparison with current prostate cancer datasets, we found that some of the bulk samples exhibit basal cell signatures. Interestingly, at single-cell resolution the gene expression patterns of prostate BCC tumor cells show uniqueness compared with that of common prostate cancer-derived circulating tumor cells. CONCLUSIONS: This study, for the first time, discloses the comprehensive mutational and transcriptomic landscapes of prostate BCC, which lays a foundation for the understanding of its tumorigenesis mechanism and provides new insights into prostate cancers in general.

The Mutational Features of Aristolochic Acid-Induced Mouse and Human Liver Cancers.

BACKGROUND AND AIMS: Aristolochic acid (AA) exposure has been statistically associated with human liver cancers. However, direct evidence of AA exposure-induced liver cancer is absent. This study aims to establish a direct causal relationship between AA exposure and liver cancers based on a mouse model and then explores the AA-mediated genomic alterations that could be implicated in human cancers with AA-associated mutational signature. APPROACH AND RESULTS: We subjected mice, including phosphatase and tensin homolog (Pten)-deficient ones, to aristolochic acid I (AAI) alone or a combination of AAI and CCl4 . Significantly, AAI exposure induced mouse liver cancers, including hepatocellular carcinoma (HCC) and combined HCC and intrahepatic cholangiocarcinoma, in a dose-dependent manner. Moreover, AAI exposure also enhanced tumorigenesis in these CCl4 -treated or Pten-deficient mice. AAI led to DNA damage and AAI-DNA adduct that could initiate liver cancers through characteristic adenine-to-thymine transversions, as indicated by comprehensive genomic analysis, which revealed recurrent mutations in Harvey rat sarcoma virus oncogene. Interestingly, an AA-associated mutational signature was mainly implicated in human liver cancers, especially from China. Moreover, we detected the AAI-DNA adduct in 25.8% (16/62) of paratumor liver tissues from randomly selected Chinese patients with HCC. Furthermore, based on phylogenetic analysis, the characteristic mutations were found in the initiating malignant clones in the AA-implicated mouse and human liver cancers where the mutations of tumor protein p53 and Janus kinase 1 were prone to be significantly enriched in the AA-affected human tumors. CONCLUSIONS: This study provides evidence for AA-induced liver cancer with the featured mutational processes during malignant clonal evolution, laying a solid foundation for the prevention and diagnosis of AA-associated human cancers, especially liver cancers.

scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets.

Concerted examination of multiple collections of single-cell RNA sequencing (RNA-seq) data promises further biological insights that cannot be uncovered with individual datasets. Here we present scMerge, an algorithm that integrates multiple single-cell RNA-seq datasets using factor analysis of stably expressed genes and pseudoreplicates across datasets. Using a large collection of public datasets, we benchmark scMerge against published methods and demonstrate that it consistently provides improved cell type separation by removing unwanted factors; scMerge can also enhance biological discovery through robust data integration, which we show through the inference of development trajectory in a liver dataset collection.