CanCellVar: A database for single-cell variants map in human cancer.

Numerous variants, including both single-nucleotide variants (SNVs) in DNA and A>G RNA edits in mRNA as essential drivers of cellular proliferation and tumorigenesis, are commonly associated with cancer progression and growth. Thus, mining and summarizing single-cell variants will provide a refined and higher-resolution view of cancer and further contribute to precision medicine. Here, we established a database, CanCellVar, which aims to provide and visualize the comprehensive atlas of single-cell variants in tumor microenvironment. The current CanCellVar identified ∼3 million variants (∼1.4 million SNVs and ∼1.4 million A>G RNA edits) involved in 2,754,531 cells of 5 major cell types across 37 cancer types. CanCellVar provides the basic annotation information as well as cellular and molecular function properties of variants. In addition, the clinical relevance of variants can be obtained including tumor grade, treatment, metastasis, and others. Several flexible tools were also developed to aid retrieval and to analyze cell-cell interactions, gene expression, cell-development trajectories, regulation, and molecular structure affected by variants. Collectively, CanCellVar will serve as a valuable resource for investigating the functions and characteristics of single-cell variations and their roles in human tumor evolution and treatment.

CancerProteome: a resource to functionally decipher the proteome landscape in cancer.

Advancements in mass spectrometry (MS)-based proteomics have greatly facilitated the large-scale quantification of proteins and microproteins, thereby revealing altered signalling pathways across many different cancer types. However, specialized and comprehensive resources are lacking for cancer proteomics. Here, we describe CancerProteome (http://bio-bigdata.hrbmu.edu.cn/CancerProteome), which functionally deciphers and visualizes the proteome landscape in cancer. We manually curated and re-analyzed publicly available MS-based quantification and post-translational modification (PTM) proteomes, including 7406 samples from 21 different cancer types, and also examined protein abundances and PTM levels in 31 120 proteins and 4111 microproteins. Six major analytical modules were developed with a view to describe protein contributions to carcinogenesis using proteome analysis, including conventional analyses of quantitative and the PTM proteome, functional enrichment, protein-protein associations by integrating known interactions with co-expression signatures, drug sensitivity and clinical relevance analyses. Moreover, protein abundances, which correlated with corresponding transcript or PTM levels, were evaluated. CancerProteome is convenient as it allows users to access specific proteins/microproteins of interest using quick searches or query options to generate multiple visualization results. In summary, CancerProteome is an important resource, which functionally deciphers the cancer proteome landscape and provides a novel insight for the identification of tumor protein markers in cancer.

SORC: an integrated spatial omics resource in cancer.

The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http://bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.

MicroEpitope: an atlas of immune epitopes derived from cancer microbiomes.

The majority of human cancers harbor molecular evidence of intratumoral microbiota. Microbiota-derived epitopes as molecular mimics of tumor antigens can bind human leukocyte antigen (HLA), thereby modulating host immunity. However, many questions remain regarding the mechanisms underlying the interactions between microbiota and the host's immune system in cancer. Here, MicroEpitope (http://bio-bigdata.hrbmu.edu.cn/MicroEpitope) was developed to provide and analyze the atlas of microbiota-derived epitopes in cancer. We manually collected available mass spectrometry (MS)-based HLA immunopeptidomes of 1190 samples across 24 cancer types. Alignment was performed against an in-house constructed theoretical library of human and intratumor microbiome encoded proteins, including 1298 bacterial and 124 viral species. Currently, MicroEpitope contains 51 497 bacteria and 767 virus-derived epitopes, mainly originating from Bacillus subtilis, Buchnera aphidicola and human cytomegalovirus. The common immunogenic features of epitopes were calculated, as well as their biochemical properties and the clinical relevance of corresponding bacteria and viruses across cancers. MicroEpitope also provides five analytical tools, and multiple visualization methods to facilitate understanding of the roles of microbiota-derived epitopes in cancer immunity. In summary, MicroEpitope represents a vital resource for investigating HLA-presented immunopeptidomes derived from cancer microbiomes, and could further enable rich insight in tumor antigen prioritization strategies.

ImmCluster: an ensemble resource for immunology cell type clustering and annotations in normal and cancerous tissues.

Single-cell transcriptome has enabled the transcriptional profiling of thousands of immune cells in complex tissues and cancers. However, subtle transcriptomic differences in immune cell subpopulations and the high dimensionality of transcriptomic data make the clustering and annotation of immune cells challenging. Herein, we introduce ImmCluster (http://bio-bigdata.hrbmu.edu.cn/ImmCluster) for immunology cell type clustering and annotation. We manually curated 346 well-known marker genes from 1163 studies. ImmCluster integrates over 420 000 immune cells from nine healthy tissues and over 648 000 cells from different tumour samples of 17 cancer types to generate stable marker-gene sets and develop context-specific immunology references. In addition, ImmCluster provides cell clustering using seven reference-based and four marker gene-based computational methods, and the ensemble method was developed to provide consistent cell clustering than individual methods. Five major analytic modules were provided for interactively exploring the annotations of immune cells, including clustering and annotating immune cell clusters, gene expression of markers, functional assignment in cancer hallmarks, cell states and immune pathways, cell-cell communications and the corresponding ligand-receptor interactions, as well as online tools. ImmCluster generates diverse plots and tables, enabling users to identify significant associations in immune cell clusters simultaneously. ImmCluster is a valuable resource for analysing cellular heterogeneity in cancer microenvironments.

IEAtlas: an atlas of HLA-presented immune epitopes derived from non-coding regions.

Cancer-related epitopes can engage the immune system against tumor cells, thus exploring epitopes derived from non-coding regions is emerging as a fascinating field in cancer immunotherapies. Here, we described a database, IEAtlas (http://bio-bigdata.hrbmu.edu.cn/IEAtlas), which aims to provide and visualize the comprehensive atlas of human leukocyte antigen (HLA)-presented immunogenic epitopes derived from non-coding regions. IEAtlas reanalyzed publicly available mass spectrometry-based HLA immunopeptidome datasets against our integrated benchmarked non-canonical open reading frame information. The current IEAtlas identified 245 870 non-canonical epitopes binding to HLA-I/II allotypes across 15 cancer types and 30 non-cancerous tissues, greatly expanding the cancer immunopeptidome. IEAtlas further evaluates the immunogenicity via several commonly used immunogenic features, including HLA binding affinity, stability and T-cell receptor recognition. In addition, IEAtlas provides the biochemical properties of epitopes as well as the clinical relevance of corresponding genes across major cancer types and normal tissues. Several flexible tools were also developed to aid retrieval and to analyze the epitopes derived from non-coding regions. Overall, IEAtlas will serve as a valuable resource for investigating the immunogenic capacity of non-canonical epitopes and the potential as therapeutic cancer vaccines.

BL-B01D1, a first-in-class EGFR-HER3 bispecific antibody-drug conjugate, in patients with locally advanced or metastatic solid tumours: a first-in-human, open-label, multicentre, phase 1 study.

BACKGROUND: Antibody-drug conjugates have promising clinical activity in the treatment of solid tumours. BL-B01D1 is a first-in-class EGFR-HER3 bispecific antibody-drug conjugate. We aimed to assess the safety and preliminary antitumour activity of BL-B01D1 in patients with locally advanced or metastatic solid tumours. METHODS: This first-in-human, open-label, multicentre, dose-escalation and dose-expansion phase 1 trial was conducted in seven hospitals in China, enrolling patients aged 18-75 years (dose escalation; phase 1a) or older than 18 years (dose expansion; phase 1b), with a life expectancy of at least 3 months, an Eastern Cooperative Oncology Group performance status of 0-1, and histologically or cytologically confirmed locally advanced or metastatic solid tumours that had progressed on current standard treatment. In the phase 1a i3+3 design, patients received intravenous BL-B01D1 at three different schedules: 0·27 mg/kg, 1·5 mg/kg, and 3·0 mg/kg weekly; 2·5 mg/kg, 3·0 mg/kg, and 3·5 mg/kg on days 1 and 8 of each cycle every 3 weeks; or 5·0 mg/kg and 6·0 mg/kg on day 1 of each cycle every 3 weeks. The primary objectives of phase 1a were to identify the safety, maximum tolerated dose, and dose-limiting toxicity. In phase 1b, patients were treated in two schedules: 2·5 and 3·0 mg/kg on days 1 and 8 every 3 weeks, or 4·5, 5·0, and 6·0 mg/kg on day 1 every 3 weeks. The primary objectives of phase 1b were to assess the safety and recommended phase 2 dose of BL-B01D1, and objective response rate was a key secondary endpoint. Safety was analysed in all patients with safety records who received at least one dose of BL-B01D1. Antitumour activity was assessed in the activity analysis set which included all patients who received at least one dose of BL-B01D1 every 3 weeks. This trial is registered with China Drug Trials, CTR20212923, and ClinicalTrials.gov, NCT05194982, and recruitment is ongoing. FINDINGS: Between Dec 8, 2021, and March 13, 2023, 195 patients (133 [65%] men and 62 [32%] women; 25 in phase 1a and 170 in phase 1b) were consecutively enrolled, including 113 with non-small-cell lung cancer, 42 with nasopharyngeal carcinomas, 13 with small-cell lung cancer, 25 with head and neck squamous cell carcinoma, one with thymic squamous cell carcinoma, and one with submandibular lymphoepithelioma-like carcinoma. In phase 1a, four dose-limiting toxicities were observed (two at 3·0 mg/kg weekly and two at 3·5 mg/kg on days 1 and 8 every 3 weeks; all were febrile neutropenia), thus the maximum tolerated dose was reached at 3·0 mg/kg on days 1 and 8 every 3 weeks and 6·0 mg/kg on day 1 every 3 weeks. Grade 3 or worse treatment-related adverse events occurred in 139 (71%) of 195 patients; the most common of which were neutropenia (91 [47%]), anaemia (76 [39%]), leukopenia (76 [39%]), and thrombocytopenia (63 [32%]). 52 (27%) patients had a dose reduction and five (3%) patients discontinued treatment due to treatment-related adverse events. One patient was reported as having interstitial lung disease. Treatment-related deaths occurred in three (2%) patients (one due to pneumonia, one due to septic shock, and one due to myelosuppression). In 174 patients evaluated for activity, median follow-up was 6·9 months (IQR 4·5-8·9) and 60 (34%; 95% CI 27-42) patients had an objective response. INTERPRETATION: Our results suggest that BL-B01D1 has preliminary antitumour activity in extensively and heavily treated advanced solid tumours with an acceptable safety profile. Based on the safety and antitumour activity data from both phase 1a and 1b, 2·5 mg/kg on days 1 and 8 every 3 weeks was selected as the recommended phase 2 dose in Chinese patients. FUNDING: Sichuan Baili Pharmaceutical. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Active Molecular Gripper as a Macrocycle Synthesizer.

A confined space preorganizes substrates, which substantially changes their chemical reactivity and selectivity; however, the performance as a reaction vessel is hampered by insensitivity to environmental changes. Here, we show a dynamic confined space formed by substrate grasping of an amphiphilic host with branched aromatic arms as an active molecular gripper capable of performing substrate grasping, macrocyclization, and product release acting as a macrocycle synthesizer. The confined reaction space is formed by the substrate grasping of the molecular gripper, which is further stabilized by gel formation. Confining a linear substrate in the closed form of the gripper triggers a spontaneous ring-forming reaction to release a macrocycle product by opening. The consecutive open-closed switching enables repetitive tasks to be performed with remarkable working efficiency.

Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective.

Metabolic reprogramming drives the development of an immunosuppressive tumor microenvironment (TME) through various pathways, contributing to cancer progression and reducing the effectiveness of anticancer immunotherapy. However, our understanding of the metabolic landscape within the tumor-immune context has been limited by conventional metabolic measurements, which have not provided comprehensive insights into the spatiotemporal heterogeneity of metabolism within TME. The emergence of single-cell, spatial, and in vivo metabolomic technologies has now enabled detailed and unbiased analysis, revealing unprecedented spatiotemporal heterogeneity that is particularly valuable in the field of cancer immunology. This review summarizes the methodologies of metabolomics and metabolic regulomics that can be applied to the study of cancer-immunity across single-cell, spatial, and in vivo dimensions, and systematically assesses their benefits and limitations.

DYNLL1 accelerates cell cycle via ILF2/CDK4 axis to promote hepatocellular carcinoma development and palbociclib sensitivity.

BACKGROUND: Disorder of cell cycle represents as a major driver of hepatocarcinogenesis and constitutes an attractive therapeutic target. However, identifying key genes that respond to cell cycle-dependent treatments still facing critical challenges in hepatocellular carcinoma (HCC). Increasing evidence indicates that dynein light chain 1 (DYNLL1) is closely related to cell cycle progression and plays a critical role in tumorigenesis. In this study, we explored the role of DYNLL1 in the regulation of cell cycle progression in HCC. METHODS: We analysed clinical specimens to assess the expression and predictive value of DYNLL1 in HCC. The oncogenic role of DYNLL1 was determined by gain or loss-of-function experiments in vitro, and xenograft tumour, liver orthotopic, and DEN/CCl4-induced mouse models in vivo. Mass spectrometry analysis, RNA sequencing, co-immunoprecipitation assays, and forward and reverse experiments were performed to clarify the mechanism by which DYNLL1 activates the interleukin-2 enhancer-binding factor 2 (ILF2)/CDK4 signalling axis. Finally, the sensitivity of HCC cells to palbociclib and sorafenib was assessed by apoptosis, cell counting kit-8, and colony formation assays in vitro, and xenograft tumour models and liver orthotopic models in vivo. RESULTS: DYNLL1 was significantly higher in HCC tissues than that in normal liver tissues and closely related to the clinicopathological features and prognosis of patients with HCC. Importantly, DYNLL1 was identified as a novel hepatocarcinogenesis gene from both in vitro and in vivo evidence. Mechanistically, DYNLL1 could interact with ILF2 and facilitate the expression of ILF2, then ILF2 could interact with CDK4 mRNA and delay its degradation, which in turn activates downstream G1/S cell cycle target genes CDK4. Furthermore, palbociclib, a selective CDK4/6 inhibitor, represents as a promising therapeutic strategy for DYNLL1-overexpressed HCC, alone or particularly in combination with sorafenib. CONCLUSIONS: Our work uncovers a novel function of DYNLL1 in orchestrating cell cycle to promote HCC development and suggests a potential synergy of CDK4/6 inhibitor and sorafenib for the treatment of HCC patients, especially those with increased DYNLL1.

Polyphenol-Based Bicontinuous Porous Spheres Via Amine-Mediated Polymerization-Induced Fusion Assembly.

Bicontinuous porous materials, which possess 3D interconnected network and pore channels facilitating the mass diffusion to the interior of materials, have demonstrated their promising potentials in a large variety of research fields. However, facile construction of such complex and delicate structures is still challenging. Here, an amine-mediated polymerization-induced fusion assembly strategy is reported for synthesizing polyphenol-based bicontinuous porous spheres with various pore structures. Specifically, the fusion of pore-generating template observed by TEM promotes the development of bicontinuous porous networks that are confirmed by 3D reconstruction. Furthermore, the resultant bicontinuous porous carbon particles after pyrolysis, with a diameter of ≈600 nm, a high accessible surface area of 359 m2 g-1, and a large pore size of 40-150 nm manifest enhanced performance toward the catalytic degradation of sulfamethazine in water decontamination. The present study expands the toolbox of interfacial tension-solvent-dependent porous spheres while providing new insight into their structure-property relationships.

Shedding light on the hidden human proteome expands immunopeptidome in cancer.

Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.

PRES: a webserver for decoding the functional perturbations of RNA editing sites.

Rapid progresses in RNA-Seq and computational methods have assisted in quantifying A-to-I RNA editing and altered RNA editing sites have been widely observed in various diseases. Nevertheless, functional characterization of the altered RNA editing sites still remains a challenge. Here, we developed perturbations of RNA editing sites (PRES; http://bio-bigdata.hrbmu.edu.cn/PRES/) as the webserver for decoding functional perturbations of RNA editing sites based on editome profiling. After uploading an editome profile among samples of different groups, PRES will first annotate the editing sites to various genomic elements and detect differential editing sites under the user-selected method and thresholds. Next, the downstream functional perturbations of differential editing sites will be characterized from gain or loss miRNA/RNA binding protein regulation, RNA and protein structure changes, and the perturbed biological pathways. A prioritization module was developed to rank genes based on their functional consequences of RNA editing events. PRES provides user-friendly functionalities, ultra-efficient calculation, intuitive table and figure visualization interface to display the annotated RNA editing events, filtering options and elaborate application notebooks. We anticipate PRES will provide an opportunity for better understanding the regulatory mechanisms of RNA editing in human complex diseases.

Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia.

BACKGROUND: Numerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies. METHODS: We utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein-protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets. RESULTS: We found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data. CONCLUSIONS: Our study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.

Fibroblast growth factor receptor 4 deficiency in macrophages aggravates experimental colitis by promoting M1-polarization.

OBJECTIVE AND DESIGN: Compelling evidence indicates that dysregulated macrophages may play a key role in driving inflammation in inflammatory bowel disease (IBD). Fibroblast growth factor (FGF)-19, which is secreted by ileal enterocytes in response to bile acids, has been found to be significantly lower in IBD patients compared to healthy individuals, and is negatively correlated with the severity of diarrhea. This study aims to explore the potential impact of FGF19 signaling on macrophage polarization and its involvement in the pathogenesis of IBD. METHODS: The dextran sulfate sodium (DSS)-induced mouse colitis model was utilized to replicate the pathology of human IBD. Mice were created with a conditional knockout of FGFR4 (a specific receptor of FGF19) in myeloid cells, as well as mice that overexpressing FGF19 specifically in the liver. The severity of colitis was measured using the disease activity index (DAI) and histopathological staining. Various techniques such as Western Blotting, quantitative PCR, flow cytometry, and ELISA were employed to assess polarization and the expression of inflammatory genes. RESULTS: Myeloid-specific FGFR4 deficiency exacerbated colitis in the DSS mouse model. Deletion or inhibition of FGFR4 in bone marrow-derived macrophages (BMDMs) skewed macrophages towards M1 polarization. Analysis of transcriptome sequencing data revealed that FGFR4 deletion in macrophages significantly increased the activity of the complement pathway, leading to an enhanced inflammatory response triggered by LPS. Mechanistically, FGFR4-knockout in macrophages promoted complement activation and inflammatory response by upregulating the nuclear factor-κB (NF-κB)-pentraxin3 (PTX3) pathway. Additionally, FGF19 suppressed these pathways and reduced inflammatory response by activating FGFR4 in inflammatory macrophages. Liver-specific overexpression of FGF19 also mitigated inflammatory responses induced by DSS in vivo. CONCLUSION: Our study highlights the significance of FGF19-FGFR4 signaling in macrophage polarization and the pathogenesis of IBD, offering a potential new therapeutic target for IBD.

Asymmetric Synthesis of Tertiary α-Hydroxylation-Cyclopentanones via Synergetic Catalysis of Chiral-at-Metal Rhodium(III) Complexes/Pyrrolidine.

Catalytic and asymmetric domino Michael/aldol reaction of 1,2-dicarbonyl compounds with α,ß-unsaturated ketones under the synergetic catalysis of chiral-at-metal rhodium complexes and pyrrolidine to deliver tertiary α-hydroxylation-cyclopentanones (45-89% yields with 81-99% ee and up to >20:1 dr) bearing three contiguous stereogenic centers had been established. Moreover, the scalability and practical utility of this protocol were well demonstrated by employing a gram-scale reaction and some representative transformations.

Retention time prediction and MRM validation reinforce the biomarker identification of LC-MS based phospholipidomics.

Dysfunctional lipid metabolism plays a crucial role in the development and progression of various diseases. Accurate measurement of lipidomes can help uncover the complex interactions between genes, proteins, and lipids in health and diseases. The prediction of retention time (RT) has become increasingly important in both targeted and untargeted metabolomics. However, the potential impact of RT prediction on targeted LC-MS based lipidomics is still not fully understood. Herein, we propose a simplified workflow for predicting RT in phospholipidomics. Our approach involves utilizing the fatty acyl chain length or carbon-carbon double bond (DB) number in combination with multiple reaction monitoring (MRM) validation. We found that our model's predictive capacity for RT was comparable to that of a publicly accessible program (QSRR Automator). Additionally, MRM validation helped in further mitigating the interference in signal recognition. Using this developed workflow, we conducted phospholipidomics of sorafenib resistant hepatocellular carcinoma (HCC) cell lines, namely MHCC97H and Hep3B. Our findings revealed an abundance of monounsaturated fatty acyl (MUFA) or polyunsaturated fatty acyl (PUFA) phospholipids in these cell lines after developing drug resistance. In both cell lines, a total of 29 lipids were found to be co-upregulated and 5 lipids were co-downregulated. Further validation was conducted on seven of the upregulated lipids using an independent dataset, which demonstrates the potential for translation of the established workflow or the lipid biomarkers.

Increased OIT3 in macrophages promotes PD-L1 expression and hepatocellular carcinogenesis via NF-κB signaling.

Oncoprotein-induced transcript 3 (OIT3) facilitates macrophage M2 polarization and hepatocellular carcinoma (HCC) progression, however, whether OIT3 regulates tumor immunity remains largely unknown. Here we found that OIT3 was upregulated in HCC-associated macrophages, which inhibited CD4+ and CD8+ T-cell infiltration in the tumor microenvironment (TME). Mechanistically, OIT3 increased the expression of PD-L1 on tumor-associated macrophages (TAMs) by activating NF-κB signaling, blockade of NF-κB reversed the immunosuppressive activity of TAMs and dampens HCC tumorigenesis. Our findings provide the molecular basis for OIT3 enhancing tumor immunosuppression and highlighted a potential therapeutic strategy for targeting the TAMs of HCC.

Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes.

Large-scale cancer genome sequencing has enabled the catalogs of somatic mutations; however, the mutational impact on intrinsically disordered protein regions (IDRs) has not been systematically investigated to date. Here, we comprehensively characterized the mutational landscapes of IDRs and found that IDRs have higher mutation frequencies across diverse cancers. We thus developed a computational method, ROI-Driver, to identify putative driver genes enriching IDR and domain hotspots in cancer. Numerous well-known cancer-related oncogenes or tumor suppressors that play important roles in cancer signaling regulation, development and immune response were identified at a higher resolution. In particular, the incorporation of IDR structures helps in the identification of novel potential driver genes that play central roles in human protein-protein interaction networks. Interestingly, we found that the putative driver genes with IDR hotspots were significantly enriched with predicted phase separation propensities, suggesting that IDR mutations disrupt phase separation in key cellular pathways. We also identified an appreciable number of clinically relevant genes enriching IDR mutational hotspots that exhibited differential expression patterns and are associated with cancer patient survival. In summary, combinations of mutational effects on IDRs significantly increase the sensitivity of driver detection and are likely to open new therapeutic avenues for various cancers.

TransLnc: a comprehensive resource for translatable lncRNAs extends immunopeptidome.

LncRNAs are not only well-known as non-coding elements, but also serve as templates for peptide translation, playing important roles in fundamental cellular processes and diseases. Here, we describe a database, TransLnc (http://bio-bigdata.hrbmu.edu.cn/TransLnc/), which aims to provide comprehensive experimentally supported and predicted lncRNA peptides in multiple species. TransLnc currently documents approximate 583 840 peptides encoded by 33 094 lncRNAs. Six types of direct and indirect evidences supporting the coding potential of lncRNAs were integrated, and 65.28% peptides entries were with at least one type of evidence. Considering the strong tissue-specific expression of lncRNAs, TransLnc allows users to access lncRNA peptides in any of the 34 tissues involved in. In addition, both the unique characteristic and homology relationship were also predicted and provided. Importantly, TransLnc provides computationally predicted tumour neoantigens from peptides encoded by lncRNAs, which would provide novel insights into cancer immunotherapy. There were 220 791 and 237 915 candidate neoantigens binding by major histocompatibility complex (MHC) class I or II molecules, respectively. Several flexible tools were developed to aid retrieve and analyse, particularly lncRNAs tissue expression patterns, clinical relevance across cancer types. TransLnc will serve as a valuable resource for investigating the translation capacity of lncRNAs and greatly extends the cancer immunopeptidome.