CGPA: multi-context insights from the cancer gene prognosis atlas.

Cancer transcriptomic data are used extensively to interrogate the prognostic value of targeted genes, yet basic scientists and clinicians have predominantly relied on univariable survival analysis for this purpose. This method often fails to capture the full prognostic potential and contextual relevance of the genes under study, inadvertently omitting a group of genes we term univariable missed-opportunity prognostic (UMOP) genes. Recognizing the complexity of revealing multifaceted prognostic implications, especially when extending the analysis to include various covariates and thresholds, we present the Cancer Gene Prognosis Atlas (CGPA). This platform greatly enhances gene-centric biomarker research across cancer types by offering an interactive and user-friendly interface for highly customized, in-depth prognostic analysis. CGPA notably supports data-driven exploration of gene pairs and gene-hallmark relationships, elucidating key composite biological mechanisms like synthetic lethality and immunosuppression. It further expands its capabilities to assess multi-gene panels using both public and user-provided data, facilitating a seamless mechanism-to-machine analysis. Additionally, CGPA features a designated portal for discovering prognostic gene modules using curated cancer immunotherapy data. Ultimately, CGPA's comprehensive, accessible tools allow cancer researchers, including those without statistical expertise, to precisely investigate the prognostic landscape of genes, customizing the model to fit specific research hypotheses and enhancing biomarker discovery and validation through a synergy of mechanistic and data-driven strategies.

A pan-cancer gamma delta T cell repertoire.

This report presents the largest collection of gamma-delta T cell receptor (γδ TCR) reads in human cancer to date, analyzing about 11,000 patient tumor samples across 33 cancer types using the TRUST4 algorithm. Despite γδ T cells being a small fraction of the T cell population, they play a key role in both innate and adaptive immunity. Our comprehensive analysis reveals their significant presence across all cancer types, specifically highlighting the diverse spectrum and clonality patterns of their γδ receptors. This research highlights the complex roles of γδ T cells in tumor tissues and their potential as prognostic biomarkers. We also demonstrate the utility of T cell receptor gamma (TRG) and delta (TRD) gene expression values from standard RNA-seq data. Ultimately, our work establishes a fundamental resource for future tumor-infiltrating γδ T cell research and may facilitate the development of novel γδ-T-cell-based therapeutic strategies. Together, we demonstrate the strong diversity and prognostic potential of γδ T cells in multiple cancer types.

Licochalcone A mitigates aflatoxin B1-induced immunotoxicity via ferroptosis in bursa of broilers and macrophages.

Aflatoxin B1 (AFB1) is a mycotoxin which is responsible for severe damage to the immune system of humans and livestock. Licochalcone A (Lico A), a polyphenol derived from turmeric, has attracted great attention due to its wonderful antioxidant properties. Ferroptosis, an iron-dependent cell death related to oxidative stress, which plays a crucial role in the resistance of phytochemical to immune-associated injury. Nevertheless, effects of Lico A on the bursa of broilers exposed to AFB1 remain unclear. In this work, broilers were fed diets supplemented with 2 mg/kg of AFB1 and 50 mg/kg of Lico A. Meanwhile, various concentrations of Lico A and AFB1 (15 µM) were used to stimulate macrophages. These results revealed that AFB1 resulted in more severe bursa atrophy and relative weight reduction; the expression of pro-ferroptosis protein ACSL4 and the content of malondialdehyde (MDA) were significantly elevated, while the expression of anti-ferroptosis proteins GPX4, xCT, FSP1 and the content of Glutathione (GSH) was obviously reduced. However, Lico A treatment effectively reversed these effects in the bursa of broilers. Meanwhile, in bursa and macrophages, Lico A mitigated the expression of AFB1-induced apoptosis-associated protein (Caspase-3, Bax, Bcl-2) as well as antioxidant protein (Nrf2, GCLM, HO-1). Importantly, ferroptosis was also observed in macrophages induced by AFB1. Lico A efficaciously alleviated AFB1-induced mitochondrial membrane potential decrease and reactive oxygen species (ROS) production in macrophages; in contrast, Lico A evidently inhibited AFB1-triggered ROS generation and cytotoxicity, which was disabled by the addition of Erastin. Moreover, Liproxstatin-1 significantly inhibited ROS generation induced by AFB1. In summary, the present study elucidates that the main mechanism by which Lico A attenuates AFB1-induced immunotoxicity is through the suppression of ferroptosis, apoptosis, mitochondrial damage and oxidative stress, which is promising for the improvement of immunotoxic effects of AFB1.

Rapid Autopsy to Define Dendritic Cell Spatial Distribution and T Cell Association in Lung Adenocarcinoma.

Immunotherapy response is associated with the presence of conventional dendritic cells (cDCs). cDC type 1 (cDC1) is critically important for CD8+ T cell activation, cDC type 2 (cDC2) regulates CD4+ T cell responses, and mature regulatory cDCs may dampen T cell responses in the tumor microenvironment (TME). However, we lack a clear understanding of cDC distribution in the human TME, cDC prevalence in metastatic sites, and cDC differences in early- versus late-stage disease. Rapid autopsy specimens of 10 patients with lung adenocarcinoma were evaluated to detect cDCs and immune cells via multiplex immunofluorescence using 18 markers and 42 tumors. First, we found that T cells, cDC1, and cDC2 were confined to stroma, whereas mature regulatory DCs were enriched in tumor, suggesting unique localization-specific functions. Second, lung and lymph node tumors were more enriched in T cells and cDCs than liver tumors, underscoring differences in the TME of metastatic sites. Third, although the proportion of T cells and cDC1 did not differ in different stages, an increase in the proportion of cDC2 and macrophages in late stage suggests potential differences in regulation of T cell responses in different stages. Collectively, these findings provide new, to our knowledge, insights into cDC biology in human cancer that may have important therapeutic implications.

Spotlight on the treatment of non-small cell lung cancer with rare genetic alterations and brain metastasis: Current status and future perspectives.

In patients with non-small cell lung cancer (NSCLC), oncogenic variants present in <5% of cases are considered rare, the predominant of which include human epidermal growth factor receptor 2 (HER2) mutations, mesenchymal-epithelial transition (MET) alterations, c-ros oncogene 1 (ROS1) rearrangements, rearrangement during transfection (RET) fusions, v-raf mouse sarcoma virus oncogene homolog B1 (BRAF) mutations, and neurotrophic troponin receptor kinase (NTRK) fusions. Brain metastases (BMs) occur in approximately 10%-50% of patients with NSCLC harboring rare genetic variants. The recent advent of small-molecule tyrosine kinase inhibitors and macromolecular antibody-drug conjugates (ADCs) has conferred marked survival benefits to patients with NSCLC harboring rare driver alterations. Despite effective brain lesion control for most targeted agents and promising reports of intracranial remission associated with novel ADCs, BM continues to be a major therapeutic challenge. This review discusses the recent advances in the treatment of NSCLC with rare genetic variants and BM, with a particular focus on intracranial efficacy, and explores future perspectives on how best to treat these patients.

GPS-Net: discovering prognostic pathway modules based on network regularized kernel learning.

The search for prognostic biomarkers capable of predicting patient outcomes, by analyzing gene expression in tissue samples and other molecular profiles, remains largely on single-gene-based or global-gene-search approaches. Gene-centric approaches, while foundational, fail to capture the higher-order dependencies that reflect the activities of co-regulated processes, pathway alterations, and regulatory networks, all of which are crucial in determining the patient outcomes in complex diseases like cancer. Here, we introduce GPS-Net, a computational framework that fills the gap in efficiently identifying prognostic modules by incorporating the holistic pathway structures and the network of gene interactions. By innovatively incorporating advanced multiple kernel learning techniques and network-based regularization, the proposed method not only enhances the accuracy of biomarker and pathway identification but also significantly reduces computational complexity, as demonstrated by extensive simulation studies. Applying GPS-Net, we identified key pathways that are predictive of patient outcomes in a cancer immunotherapy study. Overall, our approach provides a novel framework that renders genome-wide pathway-level prognostic analysis both feasible and scalable, synergizing both mechanism-driven and data-driven for precision genomics.

SmartImpute: A Targeted Imputation Framework for Single-cell Transcriptome Data.

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and tissue transcriptomic complexity. However, the high frequency of dropout events in scRNA-seq data complicates downstream analyses such as cell type identification and trajectory inference. Existing imputation methods address the dropout problem but face limitations such as high computational cost and risk of over-imputation. We present SmartImpute, a novel computational framework designed for targeted imputation of scRNA-seq data. SmartImpute focuses on a predefined set of marker genes, enhancing the biological relevance and computational efficiency of the imputation process while minimizing the risk of model misspecification. Utilizing a modified Generative Adversarial Imputation Network architecture, SmartImpute accurately imputes the missing gene expression and distinguishes between true biological zeros and missing values, preventing overfitting and preserving biologically relevant zeros. To ensure reproducibility, we also provide a function based on the GPT4 model to create target gene panels depending on the tissue types and research context. Our results, based on scRNA-seq data from head and neck squamous cell carcinoma and human bone marrow, demonstrate that SmartImpute significantly enhances cell type annotation and clustering accuracy while reducing computational burden. Benchmarking against other imputation methods highlights SmartImpute's superior performance in terms of both accuracy and efficiency. Overall, SmartImpute provides a lightweight, efficient, and biologically relevant solution for addressing dropout events in scRNA-seq data, facilitating deeper insights into cellular heterogeneity and disease progression. Furthermore, SmartImpute's targeted approach can be extended to spatial omics data, which also contain many missing values.

spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis.

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

A novel efficient strategy to generate liver sinusoidal endothelial cells from human pluripotent stem cells.

Liver sinusoidal endothelial cells (LSECs) are highly specialized endothelial cells (ECs) that play an important role in liver development and regeneration. Additionally, it is involved in various pathological processes, including steatosis, inflammation, fibrosis and hepatocellular carcinoma. However, the rapid dedifferentiation of LSECs after culture greatly limits their use in vitro modeling for biomedical applications. In this study, we developed a highly efficient protocol to induce LSEC-like cells from human induced pluripotent stem cells (hiPSCs) in only 8 days. Using single-cell transcriptomic analysis, we identified several novel LSEC-specific markers, such as EPAS1, LIFR, and NID1, as well as several previously revealed markers, such as CLEC4M, CLEC1B, CRHBP and FCN3. These LSEC markers are specifically expressed in our LSEC-like cells. Furthermore, hiPSC-derived cells expressed LSEC-specific proteins and exhibited LSEC-related functions, such as the uptake of acetylated low density lipoprotein (ac-LDL) and immune complex endocytosis. Overall, this study confirmed that our novel protocol allowed hiPSCs to rapidly acquire an LSEC-like phenotype and function in vitro. The ability to generate LSECs efficiently and rapidly may help to more precisely mimic liver development and disease progression in a liver-specific multicellular microenvironment, offering new insights into the development of novel therapeutic strategies.

Targeting antioxidant factor Nrf2 by raffinose ameliorates lipid dysmetabolism-induced pyroptosis, inflammation and fibrosis in NAFLD.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a persistent liver condition that affects both human health and animal productive efficiency on a global scale. A number of naturally occurring compounds activate nuclear factor erythroid 2-related factor 2 (Nrf2) as a transcription factor with important protective effects against many liver diseases, including NAFLD. Raffinose (Ra), an oligosaccharide extracted from several plants, exhibits diverse biological functions. However, the uncertainty lies in determining whether the activation of Nrf2 by Ra can provide a preventive effect on liver lipotoxicity. PURPOSE: The aim of this study was to shed light on the molecular pathways by which Ra possesses its protective benefits against NAFLD. METHODS: Experimental protocols were established using WT and Nrf2-null (Nrf2-/-) mice. Liver samples from each group were collected for Western blot, RT-qPCR, H & E, Sirius red and Oil red O staining. Additionally, serums were processed for ELISA. ALM12 cells were gathered for Western blot and immunofluorescence. Moreover, to elucidate the molecular mechanism of Ra, molecular docking was performed. RESULTS: Our results indicated that Ra remarkably alleviated liver lipotoxic in vivo and in vitro. Ra treatment effectively corrected hepatic steatosis, the release of AST, ALT, TG, and TC, as well as the depletion of HDL and LDL. Meanwhile, Ra efficiently prevented inflammation by inhibiting the TLR4-MyD88-NF-κB pathway and pyroptosis. Additionally, these findings implied that Ra reduced the production of fibrosis-related proteins, which enhanced collagen deposition. Molecular docking revealed that Ra possessed the ability to bind specific regions of Nrf2, resulting in the enhancement of Nrf2 activation and nuclear translocation. Ra treatment restored serum redox factors and antioxidant enzymes to normal levels; however, these alterations were clearly reversed in Nrf2-/- mice. CONCLUSION: This study reveals novel information on Ra's protective benefits against liver injury caused by abnormal lipid metabolism; these effects are mostly mediated by Nrf2 activation, suggesting a potential new medicine or treatment strategy for NAFLD.

From Detection to Cure - Emerging Roles for Urinary Tumor DNA (utDNA) in Bladder Cancer.

PURPOSE OF REVIEW: This review sought to define the emerging roles of urinary tumor DNA (utDNA) for diagnosis, monitoring, and treatment of bladder cancer. Building from early landmark studies the focus is on recent studies, highlighting how utDNA could aid personalized care. RECENT FINDINGS: Recent research underscores the potential for utDNA to be the premiere biomarker in bladder cancer due to the constant interface between urine and tumor. Many studies find utDNA to be more informative than other biomarkers in bladder cancer, especially in early stages of disease. Points of emphasis include superior sensitivity over traditional urine cytology, broad genomic and epigenetic insights, and the potential for non-invasive, real-time analysis of tumor biology. utDNA shows promise for improving all phases of bladder cancer care, paving the way for personalized treatment strategies. Building from current research, future comprehensive clinical trials will validate utDNA's clinical utility, potentially revolutionizing bladder cancer management.

Liver epigenomic signature associated with chronic oxidative stress in a mouse model of glutathione deficiency.

Oxidative stress is intimately involved in the pathogenesis of fatty liver disease (FLD). A major factor contributing to oxidative stress is the depletion of the ubiquitous antioxidant glutathione (GSH). Unexpectedly, chronic GSH deficiency renders glutamate-cysteine ligase modifier subunit (Gclm)-null mice protected from fatty liver injuries. Epigenetic regulation serves as an important cellular mechanism in modulating gene expression and disease outcome in FLD, although it is not well understood how systemic redox imbalance modifies the liver epigenome. In the current study, utilizing the Gclm-null mouse model, we aimed to elucidate redox-associated epigenomic changes and their implications in liver stress response. We performed high-throughput array-based DNA methylation profiling (MeDIP array) in 22,327 gene promoter regions (from -1300 bp to +500 bp of the Transcription Start Sites) in the liver and peripheral blood cells. Results from the MeDIP array demonstrate that, although global methylation enrichment in gene promoters did not change, low GSH resulted in prevalent demethylation at the individual promoter level. Such an effect likely attributed to a declined availability of the methyl donor S-adenosyl methionine (SAM) in Gclm-null liver. Functional enrichment analysis of liver target genes is suggestive of a potential role of epigenetic mechanisms in promoting cellular survival and lipid homeostasis in Gclm-null liver. In comparison with the liver tissue, MeDIP array in peripheral blood cells revealed a panel of 19 gene promoters that are candidate circulating biomarkers for hepatic epigenomic changes associated with chronic GSH deficiency. Collectively, our results provided new insights into the in vivo interplay between liver redox state and DNA methylation status. The current study laid the groundwork for future epigenetic/epigenomic investigations in experimental settings or human populations under conditions of liver oxidative stress induced by environmental or dietary challenges.

Differential gene expression analysis of spatial transcriptomic experiments using spatial mixed models.

Spatial transcriptomics (ST) assays represent a revolution in how the architecture of tissues is studied by allowing for the exploration of cells in their spatial context. A common element in the analysis is delineating tissue domains or "niches" followed by detecting differentially expressed genes to infer the biological identity of the tissue domains or cell types. However, many studies approach differential expression analysis by using statistical approaches often applied in the analysis of non-spatial scRNA data (e.g., two-sample t-tests, Wilcoxon's rank sum test), hence neglecting the spatial dependency observed in ST data. In this study, we show that applying linear mixed models with spatial correlation structures using spatial random effects effectively accounts for the spatial autocorrelation and reduces inflation of type-I error rate observed in non-spatial based differential expression testing. We also show that spatial linear models with an exponential correlation structure provide a better fit to the ST data as compared to non-spatial models, particularly for spatially resolved technologies that quantify expression at finer scales (i.e., single-cell resolution).

Trisomy 8 Defines a Distinct Subtype of Myeloproliferative Neoplasms Driven by the MYC-Alarmin Axis.

Despite advances in understanding the genetic abnormalities in myeloproliferative neoplasms (MPN) and the development of JAK2 inhibitors, there is an urgent need to devise new treatment strategies, particularly for patients with triple-negative (TN) myelofibrosis (MF) who lack mutations in the JAK2 kinase pathway and have very poor clinical outcomes. Here we report that MYC copy number gain and increased MYC expression frequently occur in TN-MF and that MYC-directed activation of S100A9, an alarmin protein that plays pivotal roles in inflammation and innate immunity, is necessary and sufficient to drive development and progression of MF. Notably, the MYC-S100A9 circuit provokes a complex network of inflammatory signaling that involves numerous hematopoietic cell types in the bone marrow microenvironment. Accordingly, genetic ablation of S100A9 or treatment with small molecules targeting the MYC-S100A9 pathway effectively ameliorates MF phenotypes, highlighting the MYC-alarmin axis as a novel therapeutic vulnerability for this subgroup of MPNs. Significance: This study establishes that MYC expression is increased in TN-MPNs via trisomy 8, that a MYC-S100A9 circuit manifest in these cases is sufficient to provoke myelofibrosis and inflammation in diverse hematopoietic cell types in the BM niche, and that the MYC-S100A9 circuit is targetable in TN-MPNs.

Glucose-driven histone lactylation promotes the immunosuppressive activity of monocyte-derived macrophages in glioblastoma.

Immunosuppressive macrophages restrict anti-cancer immunity in glioblastoma (GBM). Here, we studied the contribution of microglia (MGs) and monocyte-derived macrophages (MDMs) to immunosuppression and mechanisms underlying their regulatory function. MDMs outnumbered MGs at late tumor stages and suppressed T cell activity. Molecular and functional analysis identified a population of glycolytic MDM expressing GLUT1 with potent immunosuppressive activity. GBM-derived factors promoted high glycolysis, lactate, and interleukin-10 (IL-10) production in MDMs. Inhibition of glycolysis or lactate production in MDMs impaired IL-10 expression and T cell suppression. Mechanistically, intracellular lactate-driven histone lactylation promoted IL-10 expression, which was required to suppress T cell activity. GLUT1 expression on MDMs was induced downstream of tumor-derived factors that activated the PERK-ATF4 axis. PERK deletion in MDM abrogated histone lactylation, led to the accumulation of intratumoral T cells and tumor growth delay, and, in combination with immunotherapy, blocked GBM progression. Thus, PERK-driven glucose metabolism promotes MDM immunosuppressive activity via histone lactylation.

A pyroptosis-related lncRNA-based prognostic index for hepatocellular carcinoma by relative expression orderings.

Background: Hepatocellular carcinoma (HCC) is an invasive malignant tumor, and pyroptosis makes an important contribution to the pathology and progression of liver cancer. Many prognostic models have been proposed for HCC based on the quantitative expression level of candidate genes, which are unsuitable for clinical application due to their vulnerability against experimental batch effects. The aim of this study was to develop a novel pyroptosis-related long non-coding RNA (lncRNA)-based prognostic index (PLPI) for HCC based on relative expression orderings (REOs). Methods: Firstly, the pyroptosis-related lncRNAs were identified through the Wilcoxon rank-sum test and gene co-expression analyses. Then, the novel prognostic model PLPI was constructed by pyroptosis-related lncRNA pairs, which were identified by multiple machine learning algorithms. Gene set enrichment, somatic mutation, and drug sensitivity analyses were conducted to measure the differences between high- and low-risk patients. Multiple immune analyses were used to explore the association between PLPI and the immunological microenvironment. Results: In this study, a novel prognostic model PLPI based on 10 pyroptosis-related lncRNA pairs was constructed, which was proven to be an independent prognostic risk factor. The receiver operating characteristic (ROC) curves showed that the model had a good prognostic ability in the training, testing, and external set, respectively [5-year area under the curve (AUC) =0.73, 5-year AUC =0.81, 4-year AUC =0.79]. The results of survival, somatic mutation, and immune analyses showed that the patients in the low-risk group had a better prognosis, lower rates of somatic mutation, and better immune cell infiltration. Personalized chemotherapeutic drugs were also identified for the patients with HCC. Conclusions: The novel PLPI not only greatly predicted the prognosis of patients with HCC but could also offer novel ideas and approaches for the therapeutic management of HCC.

The functional role of L-fucose on dendritic cell function and polarization.

Despite significant advances in the development and refinement of immunotherapies administered to combat cancer over the past decades, a number of barriers continue to limit their efficacy. One significant clinical barrier is the inability to mount initial immune responses towards the tumor. As dendritic cells are central initiators of immune responses in the body, the elucidation of mechanisms that can be therapeutically leveraged to enhance their functions to drive anti-tumor immune responses is urgently needed. Here, we report that the dietary sugar L-fucose can be used to enhance the immunostimulatory activity of dendritic cells (DCs). L-fucose polarizes immature myeloid cells towards specific DC subsets, specifically cDC1 and moDC subsets. In vitro, L-fucose treatment enhances antigen uptake and processing of DCs. Furthermore, our data suggests that L-fucose-treated DCs increase stimulation of T cell populations. Consistent with our functional assays, single-cell RNA sequencing of intratumoral DCs from melanoma- and breast tumor-bearing mice confirmed transcriptional regulation and antigen processing as pathways that are significantly altered by dietary L-fucose. Together, this study provides the first evidence of the ability of L-fucose to bolster DC functionality and provides rational to further investigate how L-fucose can be used to leverage DC function in order to enhance current immunotherapy.

Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer.

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

High-quality acrylic fibers from waste textiles.

The objective of this work is to develop a closed-loop recycling method specifically tailored for acrylic fibers. Recycling waste acrylic is essential, given the vast volumes of acrylic-containing textiles produced yearly and the strong capability of acrylics to generate toxic microplastics. However, none of the available closed-loop recycling, mechanical recycling, chemical recycling, and direct extrusion technologies work for acrylics. Acrylic fibers are always blended with other textile fibers, making fiber separation via mechanical recycling almost impossible. Polyacrylonitrile, an addition-polymerized thermoplastic material, cannot be depolymerized into its original monomer. Direct extrusion of waste acrylics faces issues of uncontrollable colors on fibers and pollution of spinning lines due to the influence of existing colorants. In our method, acrylic fibers were extracted from waste textiles using a novel approach involving maximized acrylic swelling and dissolution with dimethyl sulfoxide and butanediol. Cationic dyes were effectively removed through cost-effective recycling technology. This work demonstrates that cationic dyes seriously affect the acrylic dissolution, color consistency, and dyeability of regenerated fibers via direct wet extrusion. Such negative impacts of dyes have been eliminated by our cost-effective and closed-loop acrylic recycling technology, which enables the efficient separation of non-acrylic fibers and dyes from acrylic fibers. Our recycling system achieved zero discharges through recycling solvents, dyes, and acrylics. The regenerated acrylic fibers exhibited mechanical properties and dyeability comparable to virgin acrylic fibers. The material and energy costs to produce pure acrylic from waste textiles were only 40 % of those from fossils. This study successfully introduces a closed-loop recycling method for acrylic fibers from waste textiles, addressing key challenges in acrylic fiber recycling. Further research and implementation of this technology are recommended to advance its commercial viability and widespread adoption.