Lina Ma

Multi-omics integrative analysis is pivotal for elucidating complex molecular mechanisms and biological processes, yet remains challenging due to the high dimensionality and heterogeneity of multi-omics data. Here we present MIA, a machine learning framework for accurate sample clustering and feature discovery from multi-omics data. Unlike existing algorithms that primarily rely on two-dimensional representations, MIA models multi-omics data as a three-dimensional tensor and integrates tensor decomposition, fuzzy c-means, and an enhanced random forest model within a unified framework. Benchmarking on simulated and empirical datasets demonstrates that MIA consistently outperforms representative state-of-the-art algorithms in both clustering and feature identification. Application to multiple TCGA cancer types further shows its ability to stratify samples and identify molecular features associated with clinically relevant outcomes. Specifically, in glioblastoma, MIA reveals three previously uncharacterized subtypes with distinct prognostic profiles and uncovers feature genes strongly associated with subtype identity. These genes are further linked to therapeutic response and retain discriminative power across major glioblastoma cellular populations at single-cell resolution. Collectively, our results establish MIA as a generalizable computational framework for multi-omics integrative analysis, enabling systematic molecular stratification and interpretable feature discovery across diverse biological systems.

LncExpDB is a comprehensive expression database of human long non-coding RNAs (lncRNAs) across diverse biological contexts. Here, we present LncExpDB 2.0 (https://ngdc.cncb.ac.cn/lncexpdb/) with significant updates and enhancements as detailed below: (i) expansion of biological contexts from 9 to 15 by integrating immunotherapy, aging, metabolic diseases, neurodegenerative diseases, reproduction, and wound healing; (ii) identification of 44 752 highly expressed genes, 39 253 featured genes with function-linked expression patterns, and 35.19 million lncRNA–mRNA co-expression pairs; (iii) in-depth functional analyses of featured genes, such as correlation with tumor microenvironment, age-related expression profiles, and functional enrichment; (iv) deployment of new tools for exploring complex lncRNA–mRNA interactions and lncRNA–immune checkpoint correlation; and (v) development of a pipeline module with documented workflow and command-line instructions for reproducible expression profiling. Collectively, LncExpDB 2.0 provides a multi-context landscape of lncRNA expression and serves as a critical resource for functional exploration of the “dark matter” in the human genome.

An accurate assessment of p53’s functional status is critical for cancer genomic medicine. However, there is a significant challenge in identifying tumors with non-mutational p53 inactivations that are not detectable through DNA sequencing. These undetected cases are often misclassified as p53-normal, leading to inaccurate prognosis and downstream association analyses. To address this issue, we built the support vector machine (SVM) models to systematically reassess p53’s functional status in TP53 wild-type (TP53 ^WT) tumors from multiple The Cancer Genome Atlas (TCGA) cohorts. Cross-validation demonstrated the good performance of the SVM models with a mean area under curve (AUC) of 0.9822, precision of 0.9747, and recall of 0.9784. Our study revealed that a significant proportion (87%–99%) of TP53 ^WT tumors actually have compromised p53 function. Additional analyses uncovered that these genetically intact but functionally impaired (termed as predictively reduced function of p53 or TP53 ^WT-pRF) tumors exhibited genomic and pathophysiologic features akin to TP53 mutant tumors: heightened genomic instability and elevated levels of hypoxia. Clinically, patients with TP53 ^WT-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53 (TP53 ^WT-pN) tumors, and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

Protists, a highly diverse group of microscopic eukaryotic organisms distinct from fungi, animals and plants, exert crucial roles within the earth's biosphere. However, the genomes of only a small fraction of known protist species have been published and made publicly accessible. To address this constraint, the Protist 10 000 Genomes Project (P10K) was initiated, implementing a specialized pipeline for single-cell genome/transcriptome assembly, decontamination and annotation of protists. The resultant P10K database (https://ngdc.cncb.ac.cn/p10k/) serves as a comprehensive platform, collating and disseminating genome sequences and annotations from diverse protist groups. Currently, the P10K database has incorporated 2959 genomes and transcriptomes, including 1101 newly sequenced datasets by P10K and 1858 publicly available datasets. Notably, it covers 45% of the protist orders, with a significant representation (53% coverage) of ciliates, featuring nearly a thousand genomes/transcriptomes. Intriguingly, analysis of the unique codon table usage among ciliates has revealed differences compared to the NCBI taxonomy system, suggesting a need to revise the codon tables used for these species. Collectively, the P10K database serves as a valuable repository of genetic resources for protist research and aims to expand its collection by incorporating more sequenced data and advanced analysis tools to benefit protist studies worldwide.

The Resource for Coronavirus 2019 (RCoV19) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19. The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.

The Resource for Coronavirus 2019 (RCoV19, https://ngdc.cncb.ac.cn/ncov/ ) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19.

Biological databases serve as a global fundamental infrastructure for the worldwide scientific community, which dramatically aid the transformation of big data into knowledge discovery and drive significant innovations in a wide range of research fields. Given the rapid data production, biological databases continue to increase in size and importance. To build a catalog of worldwide biological databases, we curate a total of 5825 biological databases from 8931 publications, which are geographically distributed in 72 countries/regions and developed by 1975 institutions (as of September 20, 2022). We further devise a z-index, a novel index to characterize the scientific impact of a database, and rank all these biological databases as well as their hosting institutions and countries in terms of citation and z-index. Consequently, we present a series of statistics and trends of worldwide biological databases, yielding a global perspective to better understand their status and impact for life and health sciences. An up-to-date catalog of worldwide biological databases, as well as their curated meta-information and derived statistics, is publicly available at Database Commons (https://ngdc.cncb.ac.cn/databasecommons/).

Background Metastatic castration-resistant prostate cancer (mCRPC) remains an incurable disease. Bispecific T cell engagers (TCEs) targeting prostate-specific membrane antigen (PSMA) and CD3 on T cells showed great clinical potential for the treatment of mCRPC. However, cytokine release syndrome (CRS) and poor pharmacokinetic (PK) profile hinder their further development. To overcome these challenges, Janux has developed JANX007, a tumor-activated T cell engager (TRACTr) with enhanced safety and PK properties. JANX007 is a humanized trispecific protein that contains PSMA- and CD3-binding domains, an albumin binding domain to extend circulating half-life, and a CD3 inhibitory peptide mask fused to the molecule through tumor protease cleavable linker. Only when tumor-resident proteases cleave the TRACTr and enable mask separation can the resulting active molecule bind CD3. This cleavage-dependent CD3 agonism can potentially limit systemic toxicity associated with broad T cell activation. Methods Peptide masks against the CD3 binding domain were identified via phage display. Mask efficiency was evaluated using human CD3 ELISAs. Masking and cleavable linker stability was characterized in human (healthy and mCRPC donor) and cynomolgus monkey serum. JANX007-induced cleavage-dependent activation of T cells was evaluated in human PBMC/prostate tumor cell in vitro co-culture assays. The pharmacokinetic and safety profile of JANX007 was evaluated in non-human primate (NHP) studies. Results Engagement of CD3 target by JANX007 was shown to be cleavage dependent where masking reduced CD3 binding by >600x. In vitro, JANX007 exhibited a ~500x decrease in potency to activate T cells and induce T cell-mediated tumor cell killing relative to non-masked TCE. JANX007 was highly stable in healthy and mCRPC human donor serum, with ≤1% cleavage per day. While proteolytic cleavage of JANX007 in the tumor microenvironment is expected to drive anti-tumor activity, the maintenance of masking in the blood compartment is expected to mitigate the safety risks associated with potential off-tumor toxicity and CRS. JANX007 was found to be highly stable in NHPs with minimally detectable cleavage. The lack of TCE accumulation in NHPs mitigated on-target healthy tissue toxicities and minimized CRS. Clinical chemistry, hematology, and pathology data package support No-Observed-Adverse-Effect-Level (NOAEL) ≥1.5 mg/kg/dose. Finally, the cleavable albumin-binding domain extended the circulating half-life of JANX007 to ~120h in NHPs, relative to the 2h half-life of non-masked TCE, supporting its projected once-weekly clinical dosing. Conclusions Cleavage-dependent activity, half-life extended PK, the potential for superior safety and manufacturability properties of JANX007 support its further development as an attractive mCRPC therapeutic. Acknowledgements We acknowledge Marque Todd for providing insightful comments and help with the interpretation of NHP safety studies. Ethics Approval All animal experiments were approved by the Institutional Animal Use and Care Committee of the institutions conducting the studies and in compliance with the Animal Welfare Act, the Guide for the Care and Use of Laboratory Animals, and the Office of Laboratory Animal Welfare.