Biology subjects

Tian, L.

Publications and source records attributed to Tian, L..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Dynorphin modulates motivation through a pallido-amygdala cholinergic circuit

The endogenous opioid peptide dynorphin and its receptor {kappa}-opioid receptor (KOR) have been implicated in divergent behaviors, but the underlying mechanisms remain elusive. Here we show that dynorphin released from nucleus accumbens dynorphinergic neurons exerts powerful modulation over a ventral pallidum (VP) disinhibitory circuit, thereby controlling cholinergic transmission to the amygdala and motivational drive in mice. On one hand, dynorphin acts postsynaptically via KORs on local GABAergic neurons in the VP to promote disinhibition of cholinergic neurons, which release acetylcholine into the amygdala to invigorate reward-seeking behaviors. On the other hand, dynorphin also acts presynaptically via KORs on dynorphinergic terminals to limit its own release. Such autoinhibition keeps cholinergic neurons from prolonged activation and release of acetylcholine, and prevents perseverant reward seeking. Our study reveals how dynorphin exquisitely modulate motivation through cholinergic system, and provides an explanation for why these neuromodulators are involved in motivational disorders, including depression and addiction.

neuroscience↗

bioRxiv2024

Aging trajectories of memory CD8+ T cells differ by their antigen specificity

Memory T cells are a highly dynamic and heterogeneous population that is maintained by cytokine-driven homeostatic proliferation interspersed with episodes of antigen-mediated expansion and contraction which affect their functional state and their durability. This heterogeneity complicates studies on the impact of aging on global human memory cells, specifically, it is unclear how aging drives memory T cell dysfunction. Here, we used chronic infection with Epstein-Barr virus (EBV) to assess the influence of age on memory states at the level of antigen-specific CD8+ T cells. We find that in young adults (<40 years), EBV-specific CD8+ T cells assume preferred differentiation states depending on their peptide specificity. By age >65-years, different T cell specificities had undergone largely distinct aging trajectories, which had in common a loss in adaptive and a gain in innate immunity signatures. No evidence was seen for cellular senescence or exhaustion. While naive/stem-like EBV-specific T cells disappeared with age, T cell diversity of EBV-specific memory cells did not change or even increased. In summary, by controlling for antigen specificity we uncover age-associated shifts in gene expression and TCR diversity that have implications for optimizing vaccination strategies and adoptive T cell therapy.

immunology↗

bioRxiv2024

A nuclear RNA degradation code for eukaryotic transcriptome surveillance

The RNA exosome plays critical roles in eukaryotic RNA degradation, but it remains unclear how the exosome specifically recognizes its targets. The PAXT connection is an adaptor that recruits the exosome to polyadenylated RNAs in the nucleus, especially transcripts polyadenylated at intronic poly(A) sites. Here we show that PAXT-mediated RNA degradation is induced by the combination of a 5' splice site and a poly(A) junction, but not by either sequence alone. These sequences are bound by U1 snRNP and cleavage/polyadenylation factors, which in turn cooperatively recruit PAXT. As the 5' splice site-poly(A) junction combination is typically not found on correctly processed full-length RNAs, we propose that it functions as a "nuclear RNA degradation code" (NRDC). Importantly, disease-associated single nucleotide polymorphisms that create novel 5' splice sites in 3' untranslated regions can induce aberrant mRNA degradation via the NRDC mechanism. Together our study identified the first NRDC, revealed its recognition mechanism, and characterized its role in human diseases.

molecular biology↗

bioRxiv2024

Fast-scBatch: Batch Effect Correction Using Neural Network-Driven Distance Matrix Adjustment

Batch effect is a frequent challenge in deep sequencing data analysis that can lead to misleading conclusions. Existing methods do not correct batch effects satisfactorily, especially with single-cell RNA sequencing (scRNA-seq) data. To address this challenge, we introduce fast-scBatch, a novel and efficient two-phase algorithm for batch-effect correction in scRNA-seq data, designed to handle non-linear and complex batch effects. Specifically, this method utilizes the inherent correlation structure of the data for batch effect correction and employs a neural network to expedite the process. It outputs a corrected expression matrix, facilitating downstream analyses. We validated fast-scBatch through simulation studies and on two scRNA-seq datasets, demonstrating its superior performance in batch-effect correction compared to current methods, as evidenced by visualization using UMAP plots, and metrics including Adjusted Rand Index (ARI) and Adjusted Mutual Information (AMI).

bioinformatics↗

bioRxiv2024

Dietary protein restriction diminishes sucrose reward and reduces sucrose-evoked mesolimbic dopamine signaling

ObjectiveA growing literature suggests manipulating dietary protein status decreases sweet consumption in rodents and in humans. Underlying neurocircuit mechanisms have not yet been determined, but previous work points towards hedonic rather than homeostatic pathways. Here we hypothesized that a history of protein restriction reduces sucrose seeking by altering mesolimbic dopamine signaling. MethodsWe tested this hypothesis using established behavioral tests of palatability and motivation, including the palatability contrast and conditioned place preference (CPP) tests. We used modern optical sensors for measuring real-time nucleus accumbens (NAc) dopamine dynamics during sucrose consumption, via fiber photometry, in male C57/Bl6J mice maintained on low-protein high-carbohydrate (LPHC) or control (CON) diet for [~]5 weeks. ResultsA history of protein restriction decreased the consumption of a sucrose dessert in sated mice by [~]50% compared to controls [T-test, p< 0.05]. The dopamine release in NAc during sucrose consumption was reduced, also by [~]50%, in LPHC-fed mice compared to CON [T-test, p< 0.01]. Furthermore, LPHC-feeding blocked the sucrose-conditioned place preference we observed in CON-fed mice [paired T-test, p< 0.05], indicating reduced motivation. This was accompanied by a 33% decrease in neuronal activation of the NAc core, as measured by c-Fos immunolabeling from brains collected directly after the CPP test. ConclusionsDespite ongoing efforts to promote healthier dietary habits, adherence to recommendations aimed at reducing the intake of added sugars and processed sweets remains challenging. This study highlights chronic dietary protein restriction as a nutritional intervention that suppresses the motivation for sucrose intake, via blunted sucrose-evoke dopamine release in NAc.

physiology↗

bioRxiv2024

LAIR1 prevents excess inflammatory tissue damage in S. aureus skin infection and Cutaneous T-cell Lymphoma

Patients with cutaneous T cell lymphoma (CTCL) experience high morbidity and mortality due to S. aureus skin infections and sepsis, but the causative immune defect is unclear. We previously identified high levels of LAIR2, a decoy protein for the inhibitory receptor LAIR1, in advanced CTCL. Mice do not have a LAIR2 homolog, so we used Lair1 knock-out (KO) mice to model LAIR2 overexpression. In a model of subcutaneous S. aureus skin infection, Lair1 KO mice had significantly larger abscesses and areas of dermonecrosis compared to WT. Lair1 KO exhibited a pattern of increased inflammatory responses in infection and sterile immune stimulation, including increased production of proinflammatory cytokines and myeloid chemokines, neutrophil ROS, and collagen/ECM remodeling pathways. Notably, Lair1 KO infected skin had a similar bacterial burden and neutrophils and monocytes had equivalent S. aureus phagocytosis compared to WT. These findings support a model in which lack of LAIR1 signaling causes an excessive inflammatory response that does not improve infection control. CTCL skin lesions harbored similar patterns of increased expression in cytokine and collagen/ECM remodeling pathways, suggesting that high levels of LAIR2 in CTCL recapitulates Lair1 KO, causing inflammatory tissue damage and compromising host defense against S. aureus infection.

immunology↗

bioRxiv2024

At the onset of active whisking, the input layer of barrel cortex exhibits a 24 h window of increased excitability that depends on prior experience.

The development of motor control over sensory organs is a critical milestone, enabling active explo-ration and shaping of the sensory environment. Whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we confirm and exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we describe a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, immediately following the onset of active whisking around on postnatal days 13 and 14. This increase in neuronal gain is specific to layer IV, independent of changes in synaptic strength, and requires prior sensory experience. Further, these effects are not expressed in inhibitory in-terneurons in barrel cortex. The transient increase in excitability is not evident in layer II/III of barrel cortex or in the visual cortex upon eye opening, suggesting a unique interaction between the development of active sensing and the thalamocortical input layer in the somatosensory iso-cortex. Predictive modeling indicates that, immediately following the onset of active whisking, changes in active membrane conductances alone can reliably distinguish neurons in control but not whisker-deprived hemispheres. Our findings demonstrate an experience-dependent, lamina-specific refinement of neuronal excitability tightly linked to the emergence of active whisking. This tran-sient increase in the gain of the thalamic input layer coincides with a critical period for synaptic plasticity in downstream layers, suggesting a role in cortical maturation and sensory processing.

neuroscience↗

bioRxiv2024

Spatiotemporally resolved transcriptome atlas of developing mouse placenta reveals mechanisms of embryonic lethality.

Proper placentation is fundamental to the growth and viability of the maturing embryo. However, a thorough grasp of the spatial organization of cell types, their interactions, and gene expression patterns along the maternal-fetal function during placental development remains incomplete. Here, we utilized Stereo-seq to construct the spatiotemporal transcriptomic atlas of the mouse placenta (STAMP) spanning embryonic (E) days 9.5 to 18.5 at single cell resolution (https://db.cngb.org/stomics/stamp/). This resource delineates spatially resolved cellular dynamics and gene expression patterns across placental and maternal compartments. We identified distinct glycogen trophoblast cell (GC) subclusters, mapped their developmental trajectories, and uncovered transcriptional transitions accompanying their migration from the junctional zone to the maternal decidua from E12.5 onward. In a defective placentation model with perinatal lethality, GCs abnormally persisted at E18.5 with excessive glycogen and reduced degradation metabolites in placenta and fetal liver, indicating impaired glycogen breakdown. Maternal glucose supplementation restored glucose levels and rescued fetal survival, underscoring GC-mediated metabolic support as critical for viability. Together, this study provides a comprehensive spatiotemporal placental atlas and demonstrates that GC-mediated glycogen metabolism is essential for sustaining fetal viability.

developmental biology↗

bioRxiv2024

Endogenous opioid dynamics in the dorsal striatum sculpt neural activity to control goal-directed action

Endogenous neuropeptides are uniquely poised to regulate neuronal activity and behavior across multiple timescales. Traditional studies ascribing neuropeptide contributions to behavior lack spatiotemporal precision. The endogenous opioid dynorphin is highly enriched in the dorsal striatum, known to be critical for regulating goal-directed behavior. However, the locus, the precise timescale, or functional role of endogenous dyn-KOR signaling on goal-directed behavior is unknown. Here, we report that local, time-locked dynorphin release from the dorsomedial striatum is necessary and sufficient for goal-directed behavior using a suite of high resolution modern approaches including in vivo two-photon imaging, neuropeptide biosensor detection, conditional deletions and time-locked optogenetic manipulations. We discovered that glutamatergic axon terminals from the basolateral amygdala evoke striatal dynorphin release, resulting in retrograde presynaptic GPCR inhibition during behavior. Collectively, our findings isolate a causal role for endogenous neuropeptide release at rapid timescales, and subsequent GPCR activity for tuning and promoting fundamental goal-directed behaviors.

neuroscience↗

bioRxiv2024

DeepVID v2: Self-Supervised Denoising with Decoupled Spatiotemporal Enhancement for Low-Photon Voltage Imaging

SignificanceVoltage imaging is a powerful tool for studying the dynamics of neuronal activities in the brain. However, voltage imaging data are fundamentally corrupted by severe Poisson noise in the low-photon regime, which hinders the accurate extraction of neuronal activities. Self-supervised deep learning denoising methods have shown great potential in addressing the challenges in low-photon voltage imaging without the need for ground truth, but usually suffer from the tradeoff between spatial and temporal performance. AimWe present DeepVID v2, a novel self-supervised denoising framework with decoupled spatial and temporal enhancement capability to significantly augment low-photon voltage imaging. ApproachDeepVID v2 is built on our original DeepVID framework,1,2 which performs frame-based denoising by utilizing a sequence of frames around the central frame targeted for denoising to leverage temporal information and ensure consistency. The network further integrates multiple blind pixels in the central frame to enrich the learning of local spatial information. Additionally, DeepVID v2 introduces a new edge extraction branch to capture fine structural details in order to learn high spatial resolution information. ResultsWe demonstrate that DeepVID v2 is able to overcome the tradeoff between spatial and temporal performance, and achieve superior denoising capability in resolving both high-resolution spatial structures and rapid temporal neuronal activities. We further show that DeepVID v2 is able to generalize to different imaging conditions, including time-series measurements with various signal-to-noise ratios (SNRs) and in extreme low-photon conditions. ConclusionsOur results underscore DeepVID v2 as a promising tool for enhancing voltage imaging. This framework has the potential to generalize to other low-photon imaging modalities and greatly facilitate the study of neuronal activities in the brain.

neuroscience↗

bioRxiv2024

An empirical evaluation of simulated gastrointestinal digestion platforms for use in plant breeding, using common bean (Phaseolus vulgaris L.) as a model

There remains a disconnect in plant breeding between increasing nutrient levels in crops at time of harvest and increasing bioaccessible levels of those nutrients during digestion. This study aims to develop and compare simulated digestion models for use in plant breeding and examine bioaccessible nutrient levels in common bean samples with differing seed coat coloration and patterning. The highest trait values (starch and protein hydrolysis, total phenolics, and antioxidant power) were observed from more dynamic digestion models, but even simple dynamic models showed higher trait values than a commonly used static digestion model. The use of these models provided insight on nutrient bioaccessibility; e.g., differences were observed during digestion between common bean genotypes for protein hydrolysis and between growing environments for both total phenolics and protein hydrolysis. Together, these results inform potential future pathways for applying simulated digestion models in plant breeding to improve bioaccessible nutrient levels in crops.

plant biology↗

bioRxiv2024

Availability of an inflammatory macrophage niche drives phenotypic and functional alterations in Kupffer cells

Inflammatory signals lead to recruitment of circulating monocytes and induce their differentiation into disease-associated macrophages1-3. Therefore, whether blocking inflammatory monocytes can mitigate disease progression is being actively evaluated4. Here, we employed multiple lineage tracing models and confirmed that monocyte-derived macrophages (mo-macs) are the major population of liver metastasis-associated macrophages (LMAMs), while the population of Kupffer cells (KCs), liver-resident macrophages, is diminished in liver metastatic nodules. Paradoxically, genetic ablation of mo-macs resulted in only a marginal decrease in LMAMs. Using a proliferation recording system and a KC tracing model in a monocyte-deficient background, we found that LMAMs can be replenished either via increased local macrophage proliferation or by promoting KC infiltration. After occupying macrophage niches left vacant by monocyte depletion, KCs exhibit substantial phenotypic and functional alterations through epigenetic reprogramming. These data suggest that dual blockade of monocytes and macrophages could be used to effectively target immunosuppressive myelopoiesis and to reprogram the microenvironment towards an immunostimulatory state.

immunology↗

bioRxiv2024

A Robust Statistical Approach for Finding Informative Spatially Associated Pathways

Spatial transcriptomics offers insights into functional localization of cells by mapping gene expression to spatial locations. Traditional focus on selecting spatially variable genes often misses the complexity of biological pathways and biological network dynamics. We introduce a novel framework that shifts the focus towards identifying functional pathways associated with spatial variability, by adapting the Brownian distance covariance test to explore the heterogeneity of biological functions over space. The statistical approach is free of parameter selection. It allows for a deeper understanding of how cells coordinate their activities across different spatial domains through biological processes. By analyzing real human and mouse datasets, the method found significant pathways that were associated with spatial variation, as well as different pathway patterns among inner- and edge-cancer regions. This innovative framework offers a new perspective on analyzing spatial transcriptomic data, contributing to our understanding of tissue architecture and disease pathology.

bioinformatics↗

bioRxiv2024

Global invasion history and genomic signatures of adaptation of a highly invasive lace bug

Invasive species cause enormous economic and ecological damage. Climate change has resulted in an unprecedented increase in the number and impact of invaders. The mechanisms underlying invasions, however, are largely unclear. The sycamore lace bug, Corythucha ciliata, is a highly invasive species that originated in North America. Its population has expanded over the Northern Hemisphere since the 1960s. In this study, we assemble the lace bugs genome using high-coverage PacBio, Illumina, and Hi-C sequencing. We identify 15,278 protein-coding genes and expansion of gene families with oxidoreductase and metabolic activities. In-depth resequencing of 402 samples collected from native and nine invasive countries across three continents identified 2.74 million single nucleotide polymorphisms. We resolve two major invasion routes of this lace bug from North America through both Europe and Japan, forming a contact zone in East Asia. Genomic signatures of selection associated with invasion and long-term balancing selection in native ranges are identified. These genomic signatures overlap with each other and the expanded genes, suggesting an improvement in the oxidative stress and thermal tolerance of this species. Our findings offer valuable insights into the genomic architecture and adaptive evolution underlying the invasive capabilities of species in the face of rapid environmental changes.

evolutionary biology↗

bioRxiv2024

Single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) to reliably detect isoform usage and coding mutations in targeted genes at a single-cell level

Single-cell long-read sequencing has transformed our understanding of isoform usage and the mutation heterogeneity between cells. Despite unbiased in-depth analysis, the low sequencing throughput often results in insufficient read coverage thereby limiting our ability to perform mutation calling for specific genes. Here, we developed a single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) method that demonstrated high specificity and efficiency in capturing targeted transcripts using long-read sequencing, allowing an in-depth analysis of mutation status and transcript usage for genes of interest. The method includes creating a probe panel for transcript capture, using barcoded primers for pooling and efficient sequencing via Oxford Nanopore Technologies platforms. scRaCH-seq is applicable to stored and indexed single-cell cDNA which allows analysis to be combined with existing short-read RNA-seq datasets. In our investigation of BTK and SF3B1 genes in samples from patients with chronic lymphocytic leukaemia (CLL), we detected SF3B1 isoforms and mutations with high sensitivity. Integration with short-read scRNA-seq data revealed significant gene expression differences in SF3B1-mutated CLL cells, though it did not impact the sensitivity of the anti-cancer drug venetoclax. scRaCH-seqs capability to study long-read transcripts of multiple genes makes it a powerful tool for single-cell genomics.

molecular biology↗

bioRxiv2024

Deciphering the Molecular Mechanism of Post-Acute Sequelae of COVID-19 through Comorbidity Network Analysis

IntroductionThe post-acute sequelae of COVID-19 presents a significant health challenge in the post-pandemic world. Our study aims to analyze longitudinal electronic health records to determine the impact of COVID-19 on disease progression, provide molecular insights into these mechanisms, and identify associated biomarkers. MethodWe included 58,710 patients with COVID-19 records from 01/01/2020 to 31/08/2022 and at least one hospital admission before and after the acute phase of COVID-19 (28 days) as the treatment group. A healthy control group of 174,071 individuals was established for comparison using propensity score matching based on pre-existing diseases (before COVID-19). We built a comorbidity network using Pearson correlation coefficient differences between pairs of pre-existing disease and post-infection disease in both groups. Disease-protein mapping and protein-protein interaction network analysis revealed the impact of COVID-19 on disease trajectories through protein interactions in the human body. ResultsThe disparity in the weight of prevalent disease comorbidity patterns between the treatment and control groups highlights the impact of COVID-19. Certain specific comorbidity patterns show a more pronounced influence by COVID-19. For each comorbidity pattern, overlapping proteins directly associated with pre-existing diseases, post-infection diseases, and COVID-19 help to elucidate the biological mechanism of COVID-19s impact on each comorbidity pattern. Proteins essential for explaining the biological mechanism can be identified based on their weights. ConclusionDisease comorbidity associations influenced by COVID-19, as identified through longitudinal electronic health records and disease-protein mapping, can help elucidate the biological mechanisms of COVID-19, discover intervention methods, and decode the molecular basis of comorbidity associations. This analysis can also yield potential biomarkers and corresponding treatments for specific disease patterns. Ethical approvalEthical approval for this study was granted by the Institutional Review Board of the University of Hong Kong/HA HK West Cluster (UW20-556, UW21-149 and UW21-138). RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for research articles up to Nov 30, 2022, with no language restrictions, using the terms "Post-Acute Sequelae of COVID-19" OR "PASC" OR "Long COVID" AND "comorbidity" OR "multimorbidity" OR "co-morbidity" OR "multi-morbidity". We found most related papers focus on the comorbidity or multimorbidity patterns among PASC. Some papers focus on the associations between specific diseases and PASC. However, no study investigated the biological mechanism of PASC from the perspective of comorbidity network. Added value of this studyThis study investigated the biological mechanism of PASC based on the comorbidity network including the impact of pre-existing diseases (diseases diagnosed within 730 days before COVID-19) on the development of PASC. We classified pairs of pre-existing disease and post-infection disease (new diseases diagnosed in 28 days to 180 days after COVID-19) as comorbidity associations. Through a comparison of the frequency of comorbidity associations in health people group and patients with COVID-19 infection group, we identified comorbidity patterns that are significantly influenced by COVID-19 infection and constructed a comorbidity network comprising of 117 nodes (representing diseases) and 271 edges (representing comorbidity patterns). These comorbidity patterns suggest COVID-19 patients with these pre-existing diseases have higher risk for post-infection diseases. Through the analysis of the Protein-Protein interaction (PPI) network and associations between diseases and proteins, we identified key proteins in the topological distance of each comorbidity pattern and important biological pathways by GO enrichment analysis. These proteins and biological pathways provide insights into the underlying biological mechanism of PASC. Implications of all the available evidenceThe identification of elevated-risk comorbidity patterns associated with COVID-19 infection is crucial for the effective allocation of medical resources, ensuring prompt care for those in greatest need. Furthermore, it facilitates the recovery process of patients from COVID-19, offering a roadmap for their path back to health. The key proteins identified in our study have the potential to serve as biomarkers and targets for therapeutic intervention, thereby establishing a foundation for the development of new drugs and the repurposing of existing ones. Further research should focus on drug discovery and the development of drug recommendations for patients with COVID-19 infections.

pathology↗

bioRxiv2024

Prefrontal cortical dynorphin peptidergic transmission constrains threat-driven behavioral and network states

Prefrontal cortical (PFC) circuits provide top-down control of threat reactivity. This includes ventromedial PFC (vmPFC) circuitry, which plays a role in suppressing fear-related behavioral states. Dynorphin (Dyn) has been implicated in mediating negative affect and mal-adaptive behaviors induced by severe threats and is expressed in limbic circuits, including the vmPFC. However, there is a critical knowledge gap in our understanding of how vmPFC Dyn-expressing neurons and Dyn transmission detect threats and regulate expression of defensive behaviors. Here, we demonstrate that Dyn cells are broadly activated by threats and release Dyn locally in the vmPFC to limit passive defensive behaviors. We further demonstrate that vmPFC Dyn-mediated signaling promotes a switch of vmPFC networks to a fear-related state. In conclusion, we reveal a previously unknown role of vmPFC Dyn neurons and Dyn neuropeptidergic transmission in suppressing defensive behaviors in response to threats via state-driven changes in vmPFC networks. Highlights[bullet] vmPFCDyn neurons are activated by threats and threat-predictive cues [bullet]Characterization of a genetically-encoded kappa-opioid receptor sensor [bullet]vmPFCDyn neurons rapidly release Dyn in response to threats and their predictors [bullet]vmPFCDyn signaling opposes threat-induced passive defensive behaviors [bullet]Dyn signaling promotes threat-evoked state transitions in vmPFC networks

neuroscience↗

bioRxiv2023

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types

As the most abundant mRNA modification in mRNA, N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the function and role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A-seq and RNA-seq samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A- regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A for cancer precision medicine for patients with different cancer types.

bioinformatics↗