Identification and Validation of eRNA as a Prognostic Indicator for Cervical Cancer.

The survival of CESC patients is closely related to the expression of enhancer RNA (eRNA). In this work, we downloaded eRNA expression, clinical, and gene expression data from the TCeA and TCGA portals. A total of 7936 differentially expressed eRNAs were discovered by limma analysis, and the relationship between these eRNAs and survival was analyzed by univariate Cox hazard analysis, LASSO regression, and multivariate Cox hazard analysis to obtain an 8-eRNA model. Risk score heat maps, KM curves, ROC analysis, robustness analysis, and nomograms further indicate that this 8-eRNA model is a novel indicator with high prognostic performance independent of clinicopathological classification. The model divided patients into high-risk and low-risk groups, compared pathway diversity between the two groups through GSEA analysis, and provided potential therapeutic agents for high-risk patients.

PvGeneExpDB: An integrative gene expression database for in-depth understanding on the Pacific white shrimp (Litopenaeus vannamei).

The Pacific white shrimp (Litopenaeus vannamei) is a high-valued economic farming species. With the development of high-throughput sequencing technology, cumulative large-scale transcriptomic studies have been revealing molecular landscape of various biological conditions including genetic selection, breeding, evolution, disease landscape, etc. However, no single experiment or databases allow thorough investigations of transcriptomic dynamics for these progressions. Meanwhile, the available datasets are often scattered and lack management. Here, we have established PvGeneExpDB, the first gene expression database for L. vannamei (www.bio-marine-scau.com/pv_ex/), which encompasses gene expression profiles, differential expression, and co-expression analyses under various biological conditions. Based on the analyses of 7 datasets, which include 53 samples with accurate and detailed records, PvGeneExpDB identifies 20,599 novel transcripts, shows expression profiles of a total of 20,817 genes, and implements Gene Ontology (GO) reconstruction of 76.7 % of these genes. Besides, 26 co-expressed groups were first identified by large-scale, cross-sample Weighted Gene Co-expression Network Analysis (WGCNA). By integrating the gene expression data in the database, our goal is to deepen the biological understanding of L. vannamei.

ChArmTelo Enables Large-Scale Chromosome Arm-Level Telomere Analysis across Human Populations and in Cancer Patients.

Telomeres are structures protecting chromosome ends. However, a scalable and cost-effective method to investigate chromosome arm-level (ChArm) telomeres (Telos) in large-scale projects is still lacking, hindering intensive investigation of high-resolution telomeres across cancers and other diseases. Here, ChArmTelo, the first computational toolbox to analyze telomeres at chromosome arm level in human and other animal species, using 10X linked-read and similar technologies, is presented. ChArmTelo currently consists of two algorithms, TeloEM and TeloKnow, for arm-level telomere length (TL) analysis. The algorithms are demonstrated by comprehensive analysis of chromosome arm-level telomere lengths (chArmTLs) in nearly 400 whole genome sequencing samples (WGS) from human populations and animals, including healthy and cancer samples. Notably, considerable performance improvement contributed by using the latest complete telomere-to-telomere reference genome (CHM13v2), compared to hg38, is shown. ChArmTelo reveals population-specific chArmTL differences and liver cancer signatures of chArmTLs and that DNA replication origin disruption may contribute to cancer by affecting TLs. Importantly, ChArmTelo can be readily applied to tens of thousands of cancer and healthy samples with published WGS data.

Sex-biased genome-editing effects of CRISPR-Cas9 across cancer cells dependent on p53 status.

The CRISPR-Cas9 system has emerged as the dominant technology for gene editing and clinical applications. One major concern is its off-target effect after the introduction of exogenous CRISPR-Cas9 into cells. Several previous studies have investigated either Cas9 alone or CRISPR-Cas9 interactions with p53. Here, we reanalyzed previously reported data of p53-associated Cas9 activities and observed large significant sex differences between p53-wildtype and p53-mutant cells. To expand the impact of this finding, we further examined all protein-coding genes for sex-specific dependencies in a large-scale CRISPR-Cas9 screening dataset from the DepMap project. We highlighted the p53-dependent sex bias of gene knockouts (including MYC, PIK3CA, KAT2B, KDM4E, SUV39H1, FANCB, TLR7, and APC2) across cancer types and potential mechanisms (mediated by transcriptional factors, including SOX9, FOXO4, LEF1, and RYBP) underlying this phenomenon. Our results suggest that the p53-dependent sex bias may need to be considered in future clinical applications of CRISPR-Cas9, especially in cancer.

Multiomics analyses reveal pathological mechanisms of HBV infection and integration in liver cancer.

Hepatitis B virus (HBV) infection and integration are important for hepatocellular carcinoma (HCC) initiation and progression, while disease mechanisms are still largely elusive. Here, we combined bulk and single-cell sequencing technologies to tackle the disease mechanisms of HBV-related HCC. We observed high HBV mutation rate and diversity only in tumors without HBV integration. We identified human somatic risk loci for HBV integration (VIMs). Transcription factors (TFs) enriched in VIMs were involved in DNA repair and androgen receptor (AR) signaling. Aberration of AR signaling was further observed by single-cell regulon analysis in HBV-infected hepatocytes, which showed remarkable interactions between AR and the complement system that, together with the X-linked ZXDB regulon that contains albumin (ALB), probably contribute to HCC male predominance. Complement system dysregulation caused by HBV infection was further confirmed by analyses of single-cell copy numbers and cell-cell communications. Finally, HBV infection-associated immune cells presented critical defects, including TXNIP in T cells, TYROBP in NK cells, and the X-linked TIMP1 in monocytes. We further experimentally validated our findings in multiple independent patient cohorts. Collectively, our work shed light on the pathogenesis of HBV-related HCC and other liver diseases that affect billions of people worldwide.

Transmembrane nuclease NUMEN/ENDOD1 regulates DNA repair pathway choice at the nuclear periphery.

Proper repair of DNA damage lesions is essential to maintaining genome integrity and preventing the development of human diseases, including cancer. Increasing evidence suggests the importance of the nuclear envelope in the spatial regulation of DNA repair, although the mechanisms of such regulatory processes remain poorly defined. Through a genome-wide synthetic viability screen for PARP-inhibitor resistance using an inducible CRISPR-Cas9 platform and BRCA1-deficient breast cancer cells, we identified a transmembrane nuclease (renamed NUMEN) that could facilitate compartmentalized and non-homologous end joining-dependent repair of double-stranded DNA breaks at the nuclear periphery. Collectively, our data demonstrate that NUMEN generates short 5' overhangs through its endonuclease and 3'→5' exonuclease activities, promotes the repair of DNA lesions-including heterochromatic lamina-associated domain breaks as well as deprotected telomeres-and functions as a downstream effector of DNA-dependent protein kinase catalytic subunit. These findings underline the role of NUMEN as a key player in DNA repair pathway choice and genome-stability maintenance, and have implications for ongoing research into the development and treatment of genome instability disorders.

Histone mRNA polyadenylation-mediated inflammation underlies various virus infections and cancers.

The mechanistic understanding of virus infection and inflammation in many diseases is incomplete. Normally, messenger RNA (mRNA) tails of replication-dependent histones (RDH) that safeguard naked nuclear DNAs are protected by a specialized stem-loop instead of polyadenylation. Here, we showed that infection by various RNA viruses (including severe acute respiratory syndrome coronavirus 2) induced aberrant polyadenylation of RDH mRNAs (pARDH) that resulted in inflammation or cellular senescence, based on which we constructed a pARDH inflammation score (pARIS). We further investigated pARIS elevation in various disease conditions, including different types of virus infection, cancer, and cellular senescence. Notably, we found that pARIS was positively correlated with coronavirus disease 2019 severity in specific immune cell types. We also detected a subset of HIV-1 elite controllers characterized by pARDH "flipping" potentially mediated by HuR. Importantly, pARIS was positively associated with transcription of endogenous retrovirus but negatively associated with most immune cell infiltration in tumors of various cancer types. Finally, we identified and experimentally verified two pARIS regulators, ADAR1 and ZKSCAN1, which was first linked to inflammation. The ZKSCAN1 was known as a transcription factor but instead was shown to regulate pARIS as a novel RNA binding protein. Both regulators were upregulated under most infection and inflammation conditions. In conclusion, we unraveled a potential antiviral mechanism underlying various types of virus infections and cancers.

Comprehensive RNA-Seq Analysis Pipeline for Non-Model Organisms and Its Application in Schmidtea mediterranea.

RNA sequencing (RNA-seq) is a high-throughput technology that provides in-depth information on transcriptome. The advancement and dropping costs of RNA sequencing, accompanied by more available reference genomes for different species, make transcriptome analysis in non-model organisms possible. Current obstacles in analyzing RNA-seq data include a lack of functional annotation, which may complicate the process of linking genes to corresponding functions. Here, we provide a one-stop RNA-seq analysis pipeline, PipeOne-NM, for transcriptome functional annotation, non-coding RNA identification, and transcripts alternative splicing analysis of non-model organisms, intended for use with Illumina platform-based RNA-seq data. We performed PipeOne-NM on 237 Schmidtea mediterranea RNA-seq runs and assembled a transcriptome with 84,827 sequences from 49,320 genes, identifying 64,582 mRNA from 35,485 genes, 20,217 lncRNA from 17,084 genes, and 3481 circRNAs from 1103 genes. In addition, we performed a co-expression analysis of lncRNA and mRNA and identified that 1319 lncRNA co-express with at least one mRNA. Further analysis of samples from S. mediterranea sexual and asexual strains revealed the role of sexual reproduction in gene expression profiles. Samples from different parts of asexual S. mediterranea revealed that differential expression profiles of different body parts correlated with the function of conduction of nerve impulses. In conclusion, PipeOne-NM has the potential to provide comprehensive transcriptome information for non-model organisms on a single platform.

Three-dimensional and single-cell sequencing of liver cancer reveals comprehensive host-virus interactions in HBV infection.

Backgrounds: Hepatitis B virus (HBV) infection is a major risk factor for chronic liver diseases and liver cancer (mainly hepatocellular carcinoma, HCC), while the underlying mechanisms and host-virus interactions are still largely elusive. Methods: We applied HiC sequencing to HepG2 (HBV-) and HepG2-2.2.15 (HBV+) cell lines and combined them with public HCC single-cell RNA-seq data, HCC bulk RNA-seq data, and both genomic and epigenomic ChIP-seq data to reveal potential disease mechanisms of HBV infection and host-virus interactions reflected by 3D genome organization. Results: We found that HBV enhanced overall proximal chromatin interactions (CIs) of liver cells and primarily affected regional CIs on chromosomes 13, 14, 17, and 22. Interestingly, HBV altered the boundaries of many topologically associating domains (TADs), and genes nearby these boundaries showed functional enrichment in cell adhesion which may promote cancer metastasis. Moreover, A/B compartment analysis revealed dramatic changes on chromosomes 9, 13 and 21, with more B compartments (inactive or closed) shifting to A compartments (active or open). The A-to-B regions (closing) harbored enhancers enriched in the regulation of inflammatory responses, whereas B-to-A regions (opening) were enriched for transposable elements (TE). Furthermore, we identified large HBV-induced structural variations (SVs) that disrupted tumor suppressors, NLGN4Y and PROS1. Finally, we examined differentially expressed genes and TEs in single hepatocytes with or without HBV infection, by using single-cell RNA-seq data. Consistent with our HiC sequencing findings, two upregulated genes that promote HBV replication, HNF4A and NR5A2, were located in regions with HBV-enhanced CIs, and five TEs were located in HBV-activated regions. Therefore, HBV may promote liver diseases by affecting the human 3D genome structure. Conclusion: Our work promotes mechanistic understanding of HBV infection and host-virus interactions related to liver diseases that affect billions of people worldwide. Our findings may also have implications for novel immunotherapeutic strategies targeting HBV infection.

Deep-learning model AIBISI predicts bacterial infection across cancer types based on pathological images.

Microorganisms play an important role in many physiological functions. Many studies have found that bacteria also regulate cancer susceptibility and tumor progression by affecting some metabolic or immune system signaling pathways. However, current bacterial detection methods are inaccurate or inefficient. Thus, we constructed a deep neural network (AIBISI) based on hematoxylin and eosin (H&E)-stained pathology slides to predict and visualize bacterial infection. Our model performance achieved as high as 0.81 of AUC (area under the ROC curve) within cancer type. We also built a pan-cancer model to predict bacterial infection across cancer types. To facilitate clinical usage, AIBISI visualized image areas affected by possible infection. Importantly, we successfully validated our model (AUC = 0.755) in pathological images from an independent patient cohort of stomach cancer (n = 32). To our best knowledge, this is the first artificial intelligence (AI)-based model to investigate bacterial infection in pathology images and has the potential to enable fast clinical decision related to pathogens in tumors.

Pan-cancer investigation of C-to-U editing reveals its important role in cancer development and new targets for cancer treatment.

RNA editing is prevalent in the transcriptome and is important for multiple cellular processes. C-to-U RNA editing sites (RES) are relatively rare and understudied in humans, compared to A-to-I editing. However, the functional impact of C-to-U editing in human cancers also remains elusive. Here, we conducted the first comprehensive survey of pan-cancer C-to-U RESs. Surprisingly, we found that the same subset of RESs were associated with multiple features, including patient survival, cancer stemness, tumor mutation burden (TMB), and tumor-infiltrated immune cell compositions (ICC), suggesting an RES-mediated close relationship between these features. For example, editing sites for GALM or IFI6 that led to higher expression were linked to lower survival and more cancer stemness. Also, TMB was found to be lower in prostate cancer cases with ICC-associated RESs in CAVIN1 or VWA8 or higher in prostate cancer cases with thymoma. With experimental support, we also found RESs in CST3, TPI1, or TNC that are linked to immune checkpoint blockade by anti-PD1. We also confirmed through experiments that two C-to-U RESs in CSNK2B or RPS14 had different effects on colon cancer cells. Patients with CSNK2B editing, which increased the expression of the oncogene CLDN18, had a lower response to drugs. On the other hand, drugs worked better on people who had RPS14 editing, which greatly increased ribosome production. In summary, our study demonstrated the important roles of C-to-U RESs across cancers and shed light on personalized cancer therapy.

Distinct dosage compensations of ploidy-sensitive and -insensitive X chromosome genes during development and in diseases.

The active X chromosome in mammals is upregulated to balance its dosage to autosomes during evolution. However, it is elusive why the known dosage compensation machinery showed uneven and small influence on X genes. Here, based on >20,000 transcriptomes, we identified two X gene groups (ploidy-sensitive [PSX] and ploidy-insensitive [PIX]), showing distinct but evolutionarily conserved dosage compensations (termed XAR). We demonstrated that XAR-PIX was downregulated whereas XAR-PSX upregulated at both RNA and protein levels across cancer types, in contrast with their trends during stem cell differentiation. XAR-PIX, but not XAR-PSX, was lower and correlated with autoantibodies and inflammation in patients of lupus, suggesting that insufficient dosage of PIX genes contribute to lupus pathogenesis. We further identified and experimentally validated two XAR regulators, TP53 and ATRX. Collectively, we provided insights into X dosage compensation in mammals and demonstrated different regulation of PSX and PIX and their pathophysiological roles in human diseases.

c-Mpl-del, a c-Mpl alternative splicing isoform, promotes AMKL progression and chemoresistance.

Acute megakaryocytic leukemia (AMKL) is a clinically heterogeneous subtype of acute myeloid leukemia characterized by unrestricted megakaryoblast proliferation and poor prognosis. Thrombopoietin receptor c-Mpl is a primary regulator of megakaryopoeisis and a potent mitogenic receptor. Aberrant c-Mpl signaling has been implicated in a myriad of myeloid proliferative disorders, some of which can lead to AMKL, however, the role of c-Mpl in AMKL progression remains largely unexplored. Here, we identified increased expression of a c-Mpl alternative splicing isoform, c-Mpl-del, in AMKL patients. We found that c-Mpl-del expression was associated with enhanced AMKL cell proliferation and chemoresistance, and decreased survival in xenografted mice, while c-Mpl-del knockdown attenuated proliferation and restored apoptosis. Interestingly, we observed that c-Mpl-del exhibits preferential utilization of phosphorylated c-Mpl-del C-terminus Y607 and biased activation of PI3K/AKT pathway, which culminated in upregulation of GATA1 and downregulation of DDIT3-related apoptotic responses conducive to AMKL chemoresistance and proliferation. Thus, this study elucidates the critical roles of c-Mpl alternative splicing in AMKL progression and drug resistance, which may have important diagnostic and therapeutic implications for leukemia accelerated by c-Mpl-del overexpression.

APOBEC Alteration Contributes to Tumor Growth and Immune Escape in Pan-Cancer.

The accumulating evidence demonstrates that the apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC), DNA-editing protein plays an important role in the molecular pathogenesis of cancer. In particular, the APOBEC3 family was shown to induce tumor mutations by an aberrant DNA editing mechanism. However, knowledge regarding the reconstitution of the APOBEC family genes across cancer types is still lacking. Here, we systematically analyzed the molecular alterations, immuno-oncological features, and clinical relevance of the APOBEC family in pan-cancer. We found that APOBEC genes were widely and significantly differentially expressed between normal and cancer samples in 16 cancer types, and that their expression levels are significantly correlated with the prognostic value in 17 cancer types. Moreover, two patterns of APOBEC-mediated stratification with distinct immune characteristics were identified in different cancer types, respectively. In ACC, for example, the first pattern of APOBEC-mediated stratification was closely correlated with the phenotype of immune activation, which was characterized by a high immune score, increased infiltration of CD8 T cells, and higher survival. The other pattern of APOBEC-mediated stratification was closely correlated with the low-infiltration immune phenotype, which was characterized by a low immune score, lack of effective immune infiltration, and poorer survival. Further, we found the APOBEC-mediated pattern with low-infiltration immune was also highly associated with the advanced tumor subtype and the CIMP-high tumor subtype (CpG island hypermethylation). Patients with the APOBEC-mediated pattern with immune activation were more likely to have therapeutic advantages in ICB (immunological checkpoint blockade) treatment. Overall, our results provide a valuable resource that will be useful in guiding oncologic and therapeutic analyses of the role of APOBEC family in cancer.

REIA: A database for cancer A-to-I RNA editing with interactive analysis.

Epitranscriptomic changes caused by adenosine-to-inosine (A-to-I) RNA editing contribute to the pathogenesis of human cancers; however, only a small fraction of the millions editing sites detected so far has clear functionality. To facilitate more in-depth studies on the editing, this paper offers REIA (http://bioinfo-sysu.com/reia), an interactive web server that analyses and visualizes the association between human cancers and A-to-I RNA editing sites (RESs). As a comprehensive database, REIA curates not only 8,447,588 RESs from 9,895 patients across 34 cancers, where 33 are from TCGA and 1 from GEO, but also 13 different types of multi-omic data for the cancers. As an interactive server, REIA provides various options for the user to specify the interested sites, to browse their annotation/editing level/profile in cancer, and to compare the difference in multi-omic features between editing and non-editing groups. From the editing profiles, REIA further detects 658 peptides that are supported by mass spectrum data but not yet covered in any prior works.

Field cancerization profile-based prognosis signatures lead to more robust risk evaluation in hepatocellular carcinoma.

The development of reliable biomarkers has been an urgent issue as well as a hot spot of research on the diagnosis, treatment, and prognostic evaluation of hepatocellular carcinoma (HCC). Here, we established and validated two field cancerization profile-based prognostic signatures (gene expression score [GES] and immune score [IS]) for HCC. Our study confirmed that field cancerization profile-based models outperform conventional models on risk evaluation, offering insights for further studies on prognostic model construction. The nomogram constructed by combining GES, IS, and TNM stage was proved effective in improving the individualized prediction of the overall risk of patients. Distinct peritumoral characteristics were observed in several immune cells (e.g., CD8 T cells and dendritic cells), which might explain the diversified prognosis and clinical benefit of immunotherapy. Moreover, a series of drug targets, prognosis-associated genes, and pathways were identified, which may contribute to molecular mechanism studies as well as therapeutic target development of HCC.

Comparative Genomics Reveals Evolutionary Drivers of Sessile Life and Left-right Shell Asymmetry in Bivalves.

Bivalves are species-rich mollusks with prominent protective roles in coastal ecosystems. Across these ancient lineages, colony-founding larvae anchor themselves either by byssus production or by cemented attachment. The latter mode of sessile life is strongly molded by left-right shell asymmetry during larval development of Ostreoida oysters such as Crassostrea hongkongensis. Here, we sequenced the genome of C. hongkongensis in high resolution and compared it to reference bivalve genomes to unveil genomic determinants driving cemented attachment and shell asymmetry. Importantly, loss of the homeobox gene Antennapedia (Antp) and broad expansion of lineage-specific extracellular gene families are implicated in a shift from byssal to cemented attachment in bivalves. Comparative transcriptomic analysis shows a conspicuous divergence between left-right asymmetrical C. hongkongensis and symmetrical Pinctada fucata in their expression profiles. Especially, a couple of orthologous transcription factor genes and lineage-specific shell-related gene families including that encoding tyrosinases are elevated, and may cooperatively govern asymmetrical shell formation in Ostreoida oysters.

FPIA: A database for gene fusion profiling and interactive analyses.

As one of the hallmarks of cancer, gene fusions play an important role in tumorigenesis, and have been established as biomarkers and therapeutic targets. Although recent years have witnessed the development of gene fusion databases, a tool with interactive analytic functions remains lacking. Here, we introduce fusion profiling interactive analysis (FPIA), a web server to perform interactive and customizable analysis on fusion genes. With this platform, researchers can easily explore fusion-associated biological and molecular differences including gene expression, tumor purity and ploidy, mutation, copy number variations, protein expression, immune cell infiltration, stemness, telomere length, microsatellite instability, survival and novel peptides based on 33 cancer types from The Cancer Genome Atlas (TCGA) data. Currently, it contains 31 633 fusion events from 6910 patients. FPIA complements the existing gene fusion annotation databases with its multiomics analytic capacity, integrated analysis features, customized analysis selection and user-friendly design. The comprehensive data analyses by FPIA will greatly facilitate data mining, hypothesis generation and therapeutic target discovery. FPIA is available at http://bioinfo-sysu.com/fpia.

Enhancer RNA-based modeling of adverse events and objective responses of cancer immunotherapy reveals associated key enhancers and target genes.

Immune checkpoint inhibitors (ICI) targeting PD-1/PD-L1 or CTLA-4 are emerging and effective immunotherapy strategies. However, ICI-treated patients present heterogeneous responses and adverse events, thus demanding effective ways to assess benefit over risk before treatment. Here, by integrating pan-cancer clinical and molecular data, we tried to predict immune-related adverse events (irAEs, risk) and objective response rates (ORRs, benefit) based on enhancer RNAs (eRNAs) expression among patients receiving anti-PD-1/PD-L1 therapies. We built two tri-variate (eRNAs) regression models, one (with ENSR00000326714, ENSR00000148786, and ENSR00000005553) explaining 71% variance (R=0.84) of irAEs and the other (with ENSR00000164478, ENSR00000035913, and ENSR00000167231) explaining 79% (R=0.89) of ORRs. Interestingly, target genes of irAE-related enhancers, including upstream regulators of MYC, were involved in metabolism, inflammation, and immune activation, while ORR-related enhancers target PAK2 and DLG1 which participate in T cell activation. More importantly, we found that ENSR00000148786 probably enhanced TMEM43/LUMA expression mainly in B cells to induce irAEs in ICI-treated patients. Our study provides references for the identification of immunotherapy-related biomarkers and potential therapeutic targets during immunotherapy.