Biology subjects

Cheng, J.

Publications and source records attributed to Cheng, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

On the state of protein function prediction: a report on the fourth CAFA challenge

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is a community effort held to understand the field of computational protein function prediction. Every three years, since 2010, the organizers initiate an experiment to collect function predictions on a large set of proteins and then evaluate the performance of predicting methods on a subset of proteins that have accumulated experimental annotations between the submission deadline and the evaluation time. CAFA provides an independent and rigorous assessment of the current state of the art, thus leveling the playing field, highlighting successes, revealing bottlenecks, and offering a forum for the exchange of ideas in protein science. Here, we report the results of the fourth CAFA experiment (CAFA4). ResultsCAFA4 featured the participation of 148 methods from 70 research groups on a total of 46,205 unique proteins over a 5-year annotation accumulation phase, the longest in any CAFA. In a comparison across CAFA2-CAFA4 methods, the prediction of Gene Ontology (GO) terms has clearly improved across all three GO aspects and traditional evaluation settings. While not achieving the first rank, several CAFA2 and CAFA3 methods featured in the top ten methods in many evaluations, suggesting that earlier methods still hold relevance. The performance is weaker in the newly introduced "partial knowledge" evaluation category (proteins with experimental annotations before submission deadline that gained additional annotations in the same GO aspect during the annotation accumulation phase), highlighting the need for a new class of methods. The rankings of the methods were stable over the years in traditional evaluation settings, but less so in the new partial knowledge evaluation. Overall, the field continues to progress with some influx of new participants. Sustained efforts will be necessary to substantially advance it.

bioinformatics↗

bioRxiv2026

GRNPred: A Multimodal Graph Transformer with Masked Gene Expression Pretraining for Gene Regulatory Network Inference

Gene regulatory network (GRN) inference is a fundamental problem in systems biology, aiming to identify transcription factor (TF)-target gene interactions from high-dimensional gene expression data. Accurate GRN reconstruction remains challenging due to limited labeled regulatory data, severe class imbalance, and the complex, nonlinear nature of transcriptional regulation. Here, we introduce GRNPred, a multimodal graph transformer framework for robust GRN inference that integrates gene expression, functional annotations, semantic gene descriptions, regulatory binding motif priors, and gene co-expression network topology. GRNPred follows a two-stage training strategy. In the first self-supervised pretraining phase, a graph transformer encoder is trained on TF-centered gene co-expression subgraphs using masked gene-expression reconstruction, enabling the model to learn transcriptional context from unlabeled data. In the second supervised fine-tuning stage, the pretrained encoder is finetuned for supervised TF-target edge prediction using available regulatory annotations. Transformer-based attention allows GRNPred to capture long-range and context-dependent regulatory interactions that are difficult to model with conventional graph neural networks. Extensive evaluation across 7 benchmark datasets and 3 regulatory network constructions demonstrates that GRNPred consistently outperforms state-of-the-art GRN inference methods, achieving AUROC scores of up to 0.94 and AUPRC scores of up to 0.93, while maintaining strong robustness across diverse biological contexts.

bioinformatics↗

bioRxiv2026

Improving AlphaFold3 by Engineering MSA and Template Inputs

AlphaFold3 introduces a unified framework for predicting the structures and interaction of several biomolecules including single-chain protein monomers, multi-chain protein multimers, and protein-ligand complexes. While it achieves the state-of-the-art performance in most predictions, its prediction accuracy depends on the quality of multiple sequence alignment (MSA) and structural template inputs. There are few works of using customized MSAs and templates to improve AlphaFold3. In this work, we systematically investigate how diverse and carefully engineered MSAs and templates can be leveraged to improve AlphaFold3 predictions. We evaluate our methods on protein monomers, multimers, and protein-ligand complexes, and observe consistent, sizable gains in structure prediction accuracy for monomers (TM-score 0.937 vs 0.882), for multimers (DockQ score 0.550 vs 0.525), and for protein-ligand complexes (ligand RMSD 3.258 [A] vs 4 [A]) compared to the default AlphaFold3. Moreover, for the first time, we demonstrate that AlphaFold3 performs significantly better than AlphaFold2 when both use the same customized MSA and template inputs. The results highlight the importance and effectiveness of using diverse MSAs and templates to improve AlphaFold3.

bioinformatics↗

bioRxiv2026

TomoSwin3D: a Swin3D Transformer for the Identification and Classification of Macromolecules in 3D Cryo-ET Tomograms

Cryo-electron tomography (cryo-ET) enables in situ three-dimensional visualization of many protein complexes and other macromolecular assemblies such as ribosomes in cells, yet automated macromolecule particle identification in 3D cryo-ET tomograms remains a major bottleneck due to dose-limited low signal-to-noise ratios, missing-wedge artifacts, and densely crowded cellular backgrounds. We present TomoSwin3D, an end-to-end three-dimensional (3D) macromolecule particle identification and classification pipeline centered on a Swin Transformer-based U-Net that performs particle identification and classification and outputs particle centroid coordinates. TomoSwin3D leverages a multi-channel input representation that augments raw tomogram densities with complementary 3D feature maps capturing edge strength (Sobel gradients), local contrast enhancement (morphological top-hat), and multiscale blob responses (Difference-of-Gaussians), improving detectability of small and low-contrast targets. To better preserve particle geometry and avoid hand-crafted shape assumptions, it adopts occupancy-preserving supervision that directly uses available 3D instance masks rather than heuristic Gaussian/spherical labels and applies scalable patch-wise inference followed by lightweight post-processing (connected-component analysis, size filtering, centroid extraction) for robust centroid coordinate extraction. Across diverse simulated and experimental cryo-ET tomogram benchmarks including SHREC 2021 and 2020 test datasets, EMPIAR dataset, and Cryo-ET data portal dataset, TomoSwin3D achieves strong and consistent performance in detecting proteins and other particles, outperforming existing methods, with a pronounced advantage in picking hard, small protein particles. These results establish TomoSwin3D as a scalable and accurate solution for high-throughput cryo-ET macromolecule particle picking and downstream subtomogram averaging.

biochemistry↗

bioRxiv2026

TFBindFormer:A Cross-Attention Transformer for Transcription Factor--DNA Binding Prediction

Transcription factors (TFs) are central regulators of gene expression, and their selective recognition of genomic DNA underlies various biological processes. Experimental profiling of TF-DNA interactions using chromatin immunoprecipitation followed by sequencing (ChIP-seq) provides high-resolution maps of in vivo TF-DNA binding but remains costly, labor-intensive, and inherently low-throughput, limiting their scalability across different transcription factors, cell types, and regulatory conditions. Computational modeling therefore plays an essential role in inferring TF-DNA interactions at genome scale. However, most existing computational models rely solely on DNA sequence and chromatin features to predict TF-DNA binding, neglecting TF-specific protein information. This omission limits their ability to capture protein-dependent binding specificity. Here, we present TFBindFormer, a hybrid cross-attention transformer that explicitly integrates genomic DNA features with TF-specific representations derived from protein sequences and structures. By modeling protein-conditioned, position-specific TF-DNA interactions, TFBindFormer enables direct learning of molecular determinants underlying DNA recognition. Evaluated across hundreds of cell-type-specific TFs and hundreds of millions of genome-wide DNA bins, TFBindFormer consistently outperforms DNA-only baselines, achieving substantial gains in both area under precision-recall curve (AUPRC) and area under receiver operating characteristic curve (AUROC). Together, these results demonstrate that integrating TF and DNA features via cross-attention enables TFBindFormer to serve as an effective and scalable framework for large-scale TF-DNA binding prediction.

bioinformatics↗

bioRxiv2026

FoTO1 is an epoxide isomerase in paclitaxel biosynthesis

Paclitaxel biosynthesis is limited by the instability of taxadiene-4(5)-epoxide, which readily diverts to the non-productive byproduct 5(12)-oxa-3(11)-cyclotaxane (OCT) instead of rearranging to taxadiene-5-ol. Although FoTO1 suppresses OCT accumulation, its molecular function has been unclear. Here we identify FoTO1 as a dedicated epoxide isomerase that directs productive rearrangement. Biochemical characterization, site-directed mutagenesis, and QM/MM calculations reveal a pre-organized D68-D149 dyad that electrostatically activates epoxide ring opening and stereospecific rearrangement. Modular dissection of the C-terminal extension further reveals a functional partition between catalytic integrity and productive coupling with T5OH, mediated by specific hydrophobic contacts that enforce precise geometric complementarity at the binary complex interface. These results demonstrate how electrostatic activation and enzyme association cooperate to control the fate of a highly reactive intermediate in paclitaxel biosynthesis.

biochemistry↗

bioRxiv2026

Identification of a somatic H3K23me3 methyltransferase SET-19 in C. elegans

Histone methylation plays essential roles in modulating chromatin organization and gene expression. H3K23 methylation is a conserved histone modification, yet its biological roles and the enzymes responsible for its deposition remain poorly understood. Here, we show that the loss of set-19 leads to a pronounced reduction in H3K23 methylation in C. elegans, as revealed by quantitative mass spectrometry, western blotting, and immunofluorescence staining. In vitro biochemical assays show that recombinant SET-19 proteins purified from E. coli directly catalyze H3K23 methylation. Genome-wide chromatin immunoprecipitation assays reveal that H3K23me3 is enriched at heterochromatic regions and that loss of set-19 alters H3K23me3 levels, accompanied by derepression of gene expression. Genetic analyses indicate that SET-19 is dispensable for both germline and somatic RNAi as well as transgenerational epigenetic inheritance of RNAi. SET-19 is predominantly expressed in somatic cells and specifically mediates H3K23me3 deposition in somatic tissues. The loss of set-19 causes a developmental delay without affecting fertility. Together, our results identify SET-19 as a somatic H3K23 methyltransferase and link H3K23me3 to gene repression in C. elegans.

genetics↗

bioRxiv2026

Paternal behavior is controlled by preoptic Trpc5 neurons

Male parenting behavior is highly conserved and activated only after offspring are born. Here we show that the behavioral switch from infanticide in virgin male mice to caregiving in wild-type sires is associated with enhanced expression and activation of Transient receptor potential channel 5 (Trpc5) in estrogen receptor (Esr1)-expressing neurons in the hypothalamic medial preoptic area (MPOA). While selective deletion of Trpc5 from Esr1MPOA neurons diminishes paternal behavior in sires, overexpression of Trpc5 in these neurons converts the otherwise infanticidal virgin males to exhibit care to pups. Mechanistically, Trpc5-dependent changes in neuronal excitability underlie fatherhood-associated Esr1MPOA neuron plasticity. Notably, Trpc5 overexpression also enhances escape behavior and elicits exploratory diving behavior, suggesting that these neurons control a broader adaptive parenting response in males. These findings establish a Trpc5-dependent MPOA neural signal as a critical regulator of paternal behavior.

neuroscience↗

bioRxiv2026

Impact of Censoring on the Quality of Cortical Parcellations and Personalized TMS Targets

Head motion systematically biases functional connectivity (FC) estimates in resting-state functional MRI (rs-fMRI). A common mitigation strategy is to censor high-motion volumes and discard high-motion runs. However, overly stringent censoring risks discarding signal alongside noise, potentially degrading FC estimates. Here, we test the efficacy of various censoring strategies on individual-specific cortical parcellations and personalized transcranial magnetic stimulation (TMS) target selection. Using precision-fMRI datasets comprising 50 individuals, we define individualized "ground-truth" references from [≥]1 hour of low-motion data per participant. We then simulate 10-min or 20-min rs-fMRI sessions with varying motion levels from the remaining data, yielding final samples of 22 and 19 participants, respectively. Higher motion produces parcellations and TMS targets that deviate further from the ground-truth references. However, at any given motion level, lenient censoring produces higher quality parcellations and personalized TMS targets than strict censoring. The improvement is comparable to doubling scan duration from 20 to 40 min under strict censoring. With personalized connectome-guided TMS, a common dilemma is whether to re-scan patients with only high-motion runs. A mixed-motion session with one low-motion run and one high-motion run may often be considered usable after discarding the high-motion run and strict censoring. We find that lenient censoring of high-motion-only sessions yields TMS targets comparable to - or even better than - those derived from strictly censored mixed-motion sessions. Therefore, within the motion range and parcellation/TMS targeting frameworks evaluated here, patients may not need to be re-scanned solely because all runs exceed strict censoring criteria.

neuroscience↗

bioRxiv2026

Heat stress-induced condensation of G3BP1 in perinuclear P-bodies in C. elegans' germline

Stress granules (SGs) are essential subcellular assemblies that enable cells to adapt to environmental stress, and their dynamic assembly and disassembly are critical for maintaining cellular homeostasis and reproductive capacity. However, the function and regulation of stress granules in germline cells remain mysterious. In this study, we characterized the function of GTBP-1, the homolog of human G3BP1, in response to heat stress in Caenorhabditis elegans and elucidated its regulation in stress granule dynamics. gtbp-1 mutants exhibit pronounced temperature-dependent biodirectional reproductive characteristics. At lower temperatures, their brood size is higher than that of wild-type animals, whereas at 25 {degrees}C they are completely sterile. GTBP-1 is diffusely distributed at normal culturing temperatures but forms perinuclear stress granules upon heat shock in the germline. While the NTF2 domain is essential for germline stress granule formation, other domains, including the IDR, RRM and RGG, are required for the recovery phase after heat shock. GTBP-1 stress granules colocalize with the P-bodies, but not with other germ granules. The depletion of P-bodies prohibited the perinuclear GTBP-1 stress granule formation. A combination of forward genetic screening together with RNAi-based candidate screening identified the P body components, the RNA helicase LAF-1, the SUMO protein SMO-1, and the mTOR pathway effector RSKS-1(S6K) as key regulators of GTBP-1 germline stress granule formation. Together, this work revealed that germline stress granules may be subjected to multiple layers of regulations and GTBP-1 may safeguards reproductive homeostasis under temperature stress by coordinating germline stress granule condensation. Author SummaryReproduction is particularly vulnerable to environmental stress, yet germ cells must remain functional to ensure fertility. How germ cells protect themselves under stressful conditions is still not well understood. In this study, we used the nematode Caenorhabditis elegans to examine how germ cells respond to heat stress, focusing on GTBP-1, a conserved protein involved in stress granule formation. We found that GTBP-1 plays contrasting roles depending on temperature: under normal conditions it restrains reproduction, whereas under heat stress it becomes essential for maintaining fertility. When animals are exposed to elevated temperature, GTBP-1 rapidly forms granules around the nuclei of germ cells, these granules assemble at sites occupied by processing bodies, another type of RNA-containing structure, revealing a close spatial relationship between two stress-responsive compartments. We also found that this process is regulated by conserved factors involved in RNA regulation and nutrient-responsive signaling. Together, our findings show how germ cells reorganize RNA-protein assemblies to preserve reproductive capacity under stressful conditions.

genetics↗

bioRxiv2026

RankMap: Rank-based reference mapping for fast and robust cell type annotation in spatial and single-cell transcriptomics

Accurate cell type annotation is essential for the analysis of single-cell and spatial transcriptomics data. While reference-based annotation methods have been widely adopted, many existing approaches rely on full-transcriptome profiles and incur substantial computational cost, limiting their applicability to large-scale spatial datasets and platforms with partial gene panels. Here, we present RankMap (https://github.com/jinming-cheng/RankMap), an efficient and flexible R package for reference-based cell type annotation across both single-cell and spatial transcriptomics. RankMap transforms gene expression profiles into rank-based representations using the top expressed genes per cell, improving robustness to platform-specific biases and expression scale differences. A multinomial regression model trained with elastic net regularization is then used to predict cell types and associated confidence scores. We benchmarked RankMap on five spatial transcriptomics datasets, including Xenium, MERFISH, and Stereo-seq, as well as two single-cell datasets, and compared it with established methods such as SingleR, Azimuth, and RCTD. RankMap achieved competitive or superior annotation accuracy while consistently reducing runtime compared to existing methods, particularly for large spatial datasets. These results demonstrate that RankMap provides a scalable and robust solution for reference-based cell type annotation in modern single-cell and spatial transcriptomics studies.

bioinformatics↗

bioRxiv2026

jazzPanda: A hybrid approach to find spatial markergenes in imaging-based spatial transcriptomics data

MotivationSpatial transcriptomics resolves the organisation of tissues and their cellular neigh-bourhoods, where cell type identification depends on reliable marker gene detection. Existing marker methods were developed for single-cell RNA sequencing and ignore the spatial coordinates of cells and transcripts, a particular problem for imaging-based platforms where transcript counts per gene per cell are extremely sparse. ResultsWe present jazzPanda, a method for detecting spatially informative marker genes in imaging-based spatial transcriptomics. Transcript and cell coordinates are aggregated into one-dimensional vectors by spatial binning, and gene vectors can be built directly from transcript coordinates without cell segmentation. Markers are identified either by permutation-based rank correlation for single-sample data, or by a lasso-regularised generalised linear model that accommo-dates multiple samples and platform-specific background signal from negative-control probes. To our knowledge, jazzPanda is the only marker detection method to account jointly for spatial distri-bution, replication across samples, and platform background. Benchmarked against the Wilcoxon rank sum test and t-tests on public Xenium and CosMx data, jazzPanda recovers markers with stronger spatial concordance and greater specificity, yielding smaller, more interpretable marker sets. The same vector framework also extends to cluster- and gene-level co-location analysis. Availability and implementationjazzPanda is implemented as an open-source R/Bioconductor package, freely available at https://bioconductor.org/packages/jazzPanda. Analysis code for this article is at https://github.com/phipsonlab/jazzPanda_paper, with an accompanying analysis website at https://phipsonlab.github.io/jazzPanda_workflowr/. Datasets and scripts are deposited at https://zenodo.org/records/18149456. Contactphipson.b@wehi.edu.au

bioinformatics↗

bioRxiv2026

The long noncoding RNA Malat1 contains an internal ribosome entry site mediating micropeptide translation

In most cells, Malat1 long noncoding RNA localizes to the nucleus where it affects splicing and chromatin function. In neurons Malat1 is exported to the cytoplasm where it is translated to generate the M1 micropeptide. Here we characterize an internal ribosome entry site (IRES) required for Malat1 translation. Although preceded by a long Malat1 5' RNA segment this element induces translation at the M1 AUG. In vivo chemical probing and structural modeling identified a 135 nt RNA secondary structure consisting of three stem loops that is sufficient for IRES activity. Using this minimal element for affinity purification from cell extracts, the IRES RNA selectively binds ribosomal subunits and translation factors. Depletion of the binding proteins Rack1 and hnRNP A2/B1 inhibits downstream IRES-dependent translation without affecting translation of an upstream ORF. Our study identifies an unexpected functional unit hidden within a widely studied long noncoding RNA.

molecular biology↗

bioRxiv2026

Temperature and intrinsic Ca2+ reshape TRPM4 pharmacology

Proteins operate in dynamic environments where ions, lipids, and temperature collectively define their properties, yet most studies rely on simplified conditions that overlook these intrinsic variables. Here, we show two such factors--temperature and Ca2+-- remodel the function and pharmacology of TRPM4, an ion channel implicated in cardiac conduction, immune regulation, cancer, and intestinal fluid homeostasis. At physiological temperature and Ca2+, TPPO--previously considered a selective TRPM5 inhibitor inactive toward TRPM4--potently activates TRPM4, revealing strong synergy among temperature, Ca2+, and ligand binding. In contrast, Necrocide-1, a necroptotic activator targeting the same binding pocket, defies this logic: it opens TRPM4 without Ca2+ but is antagonized by Ca2+. Meanwhile, the inhibitors NBA and CBA engage a nearby pocket, locking the channel in a non-conductive pre-open state. Our findings highlight that even rigid binding pockets can exhibit temperature-dependent ligand recognition, revealing hidden pharmacology and informing selective, environment-aware therapeutic strategies.

biophysics↗

bioRxiv2026

Identification a Compact Promoter using a New Promoter Selection Strategy and Engineering Hybrid Pol II/III Enable Efficient Genome Editing in Human Retinal Ganglion Cells

Promoters and vectors are critical components of gene therapy, enabling the delivery and expression of therapeutic genes to correct both loss- and gain-of-function mutations. Adeno-associated virus (AAV) vectors are the leading platform for in vivo gene delivery; however, the widely used Streptococcus pyogenes Cas9 (SpCas9, 4.1 kb) approaches the AAV packaging limit of 4.7 kb. This constraint often necessitates dual-vector systems, which reduce therapeutic efficiency, or the use of smaller nucleases such as SaCas9 (3.2 kb) and AacCas12b (3.4 kb), which have lower PAM site frequencies. To enhance promoter selection for gene therapy applications, we developed a strategy to identify compact, cell-preferred RNA polymerase II (Pol II) promoters. Analysis of approximately 300 compact Pol II promoters revealed that exogenous expression levels in one cell type correlate more strongly with those in other cell types than with endogenous expression, underscoring the importance of exogenous expression efficiency in promoter selection. Using this approach, we identified a compact Pol II promoter #2 (Pro2, 133 bp) that drives robust transgene expression in human retinal ganglion cells (RGCs). To enable single-AAV delivery of SpCas9, we analyzed three commonly used Pol III promoters (H1, 7SK and U6) and determined their minimal functional lengths using a CRISPR/Cas9 reporter assay. We further engineered three compact hybrid Pol II/III promoters which combined pro2 with minimal H1, 7SK and U6 (276, 294, and 323 bp) capable of co-expressing SpCas9 and gRNA, enabling efficient genome editing in both transfected HEK293 cells (approaching 100%) and human RGCs (up to 55.9%) from human stem cell-derived retinal ganglion cells (RGCs). Together, these findings establish a framework for developing single-AAV CRISPR-based gene therapy strategies. Authors contributionsPWZ and DJZ conceived the study, designed the experiments, performed data analysis and interpretation, and were the primary contributors to manuscript writing. STZ played a key role in data collection and correlation analysis. YYC, SL, LF, CJK, YD, CAB, JC, and DW contributed to the execution of essential experiments and subsequent data analysis. All authors have read and approved the final manuscript. Declaration of interestsThe authors declare no conflicts of interest.

molecular biology↗

bioRxiv2026

THIK-1 channel mediates microglial glucose sensing and modulates AgRP neurons

Microglia play essential roles in maintaining energy homeostasis, and their dysfunction contributes to metabolic disease. Although high-fat diet (HFD) exposure induces microglial activation, the underlying mechanisms remain poorly defined. Here, we identified a previously unrecognized role for THIK-1 channel in mediating glucose sensing of microglia in arcuate nucleus of the hypothalamus (ARH), during HFD-induced obesity. Pharmacological inhibition of THIK-1 channel with tetrapentylammonium (TPA) suppresses feeding and attenuates body-weight gain in diet induced obese mice. Mechanistically, inhibition of agouti-related peptide (AgRP) neurons is indispensable for TPA-induced hypophagia. Moreover, THIK-1 inhibition promotes microglial phagocytosis of perineuronal nets (PNNs), leading to reduced AgRP neuronal activity and feeding suppression. Together, these findings establish THIK-1 as a critical glucose sensor in hypothalamic microglia and uncover a microglia-dependent pathway through which overnutrition modulates AgRP neuronal activity via PNN remodeling to regulate energy balance, highlighting THIK-1 as a potential therapeutic target for treatment of diet-induced obesity.

neuroscience↗

bioRxiv2026

A Hybrid Gag Lattice as a Structural Intermediate in HIV-1 Maturation

HIV-1 maturation converts the spherical immature Gag lattice into the conical mature capsid required for infectivity, yet the structural route linking these two lattice endpoints remains unclear. Using single-particle cryo-electron microscopy and cryo-electron tomography on reconstituted assemblies and virus-like particles (VLPs), we identify a distinct hybrid lattice in which the capsid protein (CA) N-terminal domain adopts a mature-like conformation, whereas the CA C-terminal domain-SP1 layer remains immature. This architecture is observed in native, enveloped VLPs produced in human cells, demonstrating formation under physiologically relevant conditions. The hybrid lattice engages three myo-inositol hexakisphosphate (IP6) molecules per CA-SP1 hexamer, underscoring IP6-dependent stabilization; accordingly, excess IP6 enriches the hybrid population. Tomographic mapping shows that hybrid regions coexist with the immature lattice within the same particle and are enriched near lattice discontinuities, consistent with edge-localized remodeling that can accommodate conformational rearrangements and partial disassembly and reassembly. Disrupting a hybrid-specific inter-hexamer contact preserves immature lattice assembly and particle release but abrogates infectivity, compromises core integrity, and prevents mature lattice formation, implicating the hybrid architecture as an on-pathway intermediate. Molecular dynamics simulations further support coordinated rearrangements that bias the system away from the immature configuration toward hybrid and then mature organizations. Together, these results support a maturation model in which localized displacive remodeling and partial disassembly/reassembly act in concert, with IP6 tuning the balance among lattice states. This study provides new insight into HIV-1 maturation and identifies the hybrid lattice as a potential therapeutic target.

biochemistry↗

bioRxiv2026

TSTScope Unifies Single-Cell Multi-Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Immune checkpoint blockade (ICB) can produce durable responses in cancer, but reliable predictors of benefit are still lacking. CD8 tumor-specific T cells are essential for ICB efficacy, yet it remains unclear which functional states of these cells determine therapeutic success. To address this, we developed TSTScope, an interpretable deep learning framework that integrates single-cell transcriptomic and T-cell receptor sequencing data to generate unified representations of CD8 T-cell identity. By applying TSTScope to non-small cell lung cancer (NSCLC) datasets, we characterized the gene programs defining tumor specificity and computationally inferred a population of potential TSTs. Crucially, we demonstrate that clinical response is not a product of TST abundance, but is instead governed by their functional state. We derived the MPR score, a metric capturing this functional potential, which proved to be a robust predictor of treatment outcomes. In an independent validation cohort, the MPR score significantly outperformed established biomarkers. Collectively, TSTScope identifies a distinct functional state of tumor-specific T cells as a primary determinant of ICB efficacy, providing both a mechanistic framework and a potent tool for precision immunotherapy.

bioinformatics↗