Single-Cell Spatial Transcriptomics Unveils Platelet-Fueled Cycling Macrophages for Kidney Fibrosis.

With the increasing incidence of kidney diseases, there is an urgent need to develop therapeutic strategies to combat post-injury fibrosis. Immune cells, including platelets, play a pivotal role in this repair process, primarily through their released cytokines. However, the specific role of platelets in kidney injury and subsequent repair remains underexplored. Here, the detrimental role of platelets in renal recovery following ischemia/reperfusion injury and its contribution to acute kidney injury  to chronic kidney disease transition is aimed to investigated. In this study, it is shown that depleting platelets accelerates injury resolution and significantly reduces fibrosis. Employing advanced single-cell and spatial transcriptomic techniques, macrophages as the primary mediators modulated by platelet signals is identified. A novel subset of macrophages, termed "cycling M2", which exhibit an M2 phenotype combined with enhanced proliferative activity is uncovered. This subset emerges in the injured kidney during the resolution phase and is modulated by platelet-derived thrombospondin 1 (THBS1) signaling, acquiring profibrotic characteristics. Conversely, targeted inhibition of THBS1 markedly downregulates the cycling M2 macrophage, thereby mitigating fibrotic progression. Overall, this findings highlight the adverse role of platelet THBS1-boosted cycling M2 macrophages in renal injury repair and suggest platelet THBS1 as a promising therapeutic target for alleviating inflammation and kidney fibrosis.

Identification and validation of an immune-derived multiple programmed cell death index for predicting clinical outcomes, molecular subtyping, and drug sensitivity in lung adenocarcinoma.

OBJECTIVES: Comprehensive cross-interaction of multiple programmed cell death (PCD) patterns in the patients with lung adenocarcinoma (LUAD) have not yet been thoroughly investigated. METHODS: Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed an immune-derived multiple programmed cell death index (MPCDI) based on machine learning methods. RESULTS: Using the median MPCDI scores, we categorized the LUAD patients into two groups: low-MPCDI and high-MPCDI. Our analysis of the TCGA-LUAD training cohort and three external GEO cohorts (GSE37745, GSE30219, and GSE68465) revealed that patients with high-MPCDI experienced a more unfavorable prognosis, whereas those with low-MPCDI had a better prognosis. Furthermore, the results of both univariate and multivariate Cox regression analyses further confirmed that MPCDI serves as a novel independent risk factor. By combining clinical characteristics with the MPCDI, we constructed a nomogram that provides an accurate and reliable quantitative tool for personalized clinical management of LUAD patients. The findings obtained from the analysis of C-index and the decision curve revealed that the nomogram outperformed various clinical variables in terms of net clinical benefit. Encouragingly, the low-MPCDI patients are more sensitive to commonly used chemotherapy drugs, which suggests that MPCDI scores have a guiding role in chemotherapy for LUAD patients. CONCLUSION: Therefore, MPCDI can be used as a novel clinical diagnostic classifier, providing valuable insights into the clinical management and clinical decision-making for LUAD patients.

A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer.

Comprehensive action patterns of programmed cell death (PCD) in bladder cancer (BLCA) have not yet been thoroughly investigated. Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed a multiple programmed cell death index (MPCDI) based on a machine learning computational framework. We found that in the TCGA-BLCA training cohort and the independently validated GSE13507 cohort, the patients with high-MPCDI had a worse prognosis, whereas patients with low-MPCDI had a better prognosis. By combining clinical characteristics with the MPCDI, we constructed a nomogram. The C-index demonstrated that the nomogram was significantly more accurate compared to other variables, including MPCDI, age, gender, and clinical stage. The results of the decision curve analysis demonstrated that the nomogram had a better net clinical benefit compared to other clinical variables. Subsequently, we revealed the heterogeneity of BLCA patients, with significant differences in terms of overall immune infiltration abundance, immunotherapeutic response, and drug sensitivity in the two MPCDI groups. Encouragingly, the high-MPCDI patients showed better efficacy for commonly used chemotherapeutic drugs than the low-MPCDI patients, which suggests that MPCDI scores have a guiding role in chemotherapy for BLCA patients. In conclusion, the MPCDI developed and verified in this study is not only an emerging clinical classifier for BLCA patients, but it also serves as a reliable forecaster for both chemotherapy and immunotherapy, which can guide clinical management and clinical decision-making for BLCA patients.

A shock flash breaking out of a dusty red supergiant.

Shock-breakout emission is light that arises when a shockwave, generated by the core-collapse explosion of a massive star, passes through its outer envelope. Hitherto, the earliest detection of such a signal was at several hours after the explosion1, although a few others had been reported2-7. The temporal evolution of early light curves should provide insights into the shock propagation, including explosion asymmetry and environment in the vicinity, but this has been hampered by the lack of multiwavelength observations. Here we report the instant multiband observations of a type II supernova (SN 2023ixf) in the galaxy M101 (at a distance of 6.85 ± 0.15 Mpc; ref. 8), beginning at about 1.4 h after the explosion. The exploding star was a red supergiant with a radius of about 440 solar radii. The light curves evolved rapidly, on timescales of 1-2 h, and appeared unusually fainter and redder than predicted by the models9-11 within the first few hours, which we attribute to an optically thick dust shell before it was disrupted by the shockwave. We infer that the breakout and perhaps the distribution of the surrounding dust were not spherically symmetric.

Autophagy of OTUD5 destabilizes GPX4 to confer ferroptosis-dependent kidney injury.

Ferroptosis is an iron-dependent programmed cell death associated with severe kidney diseases, linked to decreased glutathione peroxidase 4 (GPX4). However, the spatial distribution of renal GPX4-mediated ferroptosis and the molecular events causing GPX4 reduction during ischemia-reperfusion (I/R) remain largely unknown. Using spatial transcriptomics, we identify that GPX4 is situated at the interface of the inner cortex and outer medulla, a hyperactive ferroptosis site post-I/R injury. We further discover OTU deubiquitinase 5 (OTUD5) as a GPX4-binding protein that confers ferroptosis resistance by stabilizing GPX4. During I/R, ferroptosis is induced by mTORC1-mediated autophagy, causing OTUD5 degradation and subsequent GPX4 decay. Functionally, OTUD5 deletion intensifies renal tubular cell ferroptosis and exacerbates acute kidney injury, while AAV-mediated OTUD5 delivery mitigates ferroptosis and promotes renal function recovery from I/R injury. Overall, this study highlights a new autophagy-dependent ferroptosis module: hypoxia/ischemia-induced OTUD5 autophagy triggers GPX4 degradation, offering a potential therapeutic avenue for I/R-related kidney diseases.

Identification of a miRNA-mRNA regulatory network for post-stroke depression: a machine-learning approach.

Objective: The study aimed to explore the miRNA and mRNA biomarkers in post-stroke depression (PSD) and to develop a miRNA-mRNA regulatory network to reveal its potential pathogenesis. Methods: The transcriptomic expression profile was obtained from the GEO database using the accession numbers GSE117064 (miRNAs, stroke vs. control) and GSE76826 [mRNAs, late-onset major depressive disorder (MDD) vs. control]. Differentially expressed miRNAs (DE-miRNAs) were identified in blood samples collected from stroke patients vs. control using the Linear Models for Microarray Data (LIMMA) package, while the weighted correlation network analysis (WGCNA) revealed co-expressed gene modules correlated with the subject group. The intersection between DE-miRNAs and miRNAs identified by WGCNA was defined as stroke-related miRNAs, whose target mRNAs were stroke-related genes with the prediction based on three databases (miRDB, miRTarBase, and TargetScan). Using the GSE76826 dataset, the differentially expressed genes (DEGs) were identified. Overlapped DEGs between stroke-related genes and DEGs in late-onset MDD were retrieved, and these were potential mRNA biomarkers in PSD. With the overlapped DEGs, three machine-learning methods were employed to identify gene signatures for PSD, which were established with the intersection of gene sets identified by each algorithm. Based on the gene signatures, the upstream miRNAs were predicted, and a miRNA-mRNA network was constructed. Results: Using the GSE117064 dataset, we retrieved a total of 667 DE-miRNAs, which included 420 upregulated and 247 downregulated ones. Meanwhile, WGCNA identified two modules (blue and brown) that were significantly correlated with the subject group. A total of 117 stroke-related miRNAs were identified with the intersection of DE-miRNAs and WGCNA-related ones. Based on the miRNA-mRNA databases, we identified a list of 2,387 stroke-related genes, among which 99 DEGs in MDD were also embedded. Based on the 99 overlapped DEGs, we identified three gene signatures (SPATA2, ZNF208, and YTHDC1) using three machine-learning classifiers. Predictions of the three mRNAs highlight four miRNAs as follows: miR-6883-5p, miR-6873-3p, miR-4776-3p, and miR-6738-3p. Subsequently, a miRNA-mRNA network was developed. Conclusion: The study highlighted gene signatures for PSD with three genes (SPATA2, ZNF208, and YTHDC1) and four upstream miRNAs (miR-6883-5p, miR-6873-3p, miR-4776-3p, and miR-6738-3p). These biomarkers could further our understanding of the pathogenesis of PSD.

Genome-wide analyses of LATERAL ORGAN BOUNDARIES in cassava reveal the role of LBD47 in defence against bacterial blight.

The Arabidopsis thaliana ASYMMETRIC LEAVES2 (AS2) gene is responsible for the development of flat, symmetric, and extended leaf laminae and their veins. The AS2 gene belongs to the plant-specific AS2-LIKE/LATERAL ORGAN BOUNDARIES (LOB)-domain (ASL/LBD), which consists of 42 proteins in Arabidopsis with a conserved amino-terminal domain known as the AS2/LOB domain, and a variable carboxyl-terminal region. AS2/LOB domain consists of an amino-terminal (N-terminal) that contains a cysteine repeat (the C-motif), a conserved glycine residue, and a leucine-zipper-like. AS2/LOB domain has been characterised in plants such as A. thaliana, Zea mays, and Oryza sativum. Nevertheless, it remains uncharacterised in cassava (Manihot esculenta). Characterisation and identification of cassava ASL/LBD genes using the computational algorithms, hidden Markov model profiles (PF03195), determined 55 ASL/LBD genes (MeASLBD1 to MeASLBD55). The gene structure and motif composition were conserved in MeASLBDs, while the expression profiles of these genes were highly diverse, implying that they are associated with diverse functions. Weighted gene co-expression network analysis (WGCNA) of target genes and promoter analysis suggest that these MeASLBDs may be involved in hormone and stress responses. Furthermore, the analysis of cis-regulatory elements in promoter regions suggested that MeASLBDs may be involved in the plant phytohormone signal response. The transcriptome data of cassava under biotic and abiotic stresses revealed that MeASLBD46 and MeASLBD47 greatly respond to disease and drought. The MeASLBD47 gene was selected for functional analysis. The result indicated that MeASLBD47 significantly mitigated the virulence of cassava bacterial blight (XamCHN11) through Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) and Virus-induced gene silencing (VIGS). These findings provided a comprehensive analysis of ASL/LBD genes and laid the groundwork for future research to understand ASL/LBD genes.

[Bioinformatics analysis and validation of key genes in transformation of idiopathic membranous nephropathy to end-stage renal disease and traditional Chinese medicines for prevention and treatment].

This study used bioinformatics analysis to screen out key genes involved in the transformation of idiopathic membranous nephropathy to end-stage renal disease and to predict targeted Chinese herbs and medicines and active ingredients with preventive and curative effects. The GSE108113 microarray of idiopathic membranous nephropathy and GSE37171 microarray of were downloaded from the comprehensive gene expression database, and 8 homozygous differentially expressed genes for the transformation of idiopathic membranous nephropathy into end-stage renal disease of were screened out by R software. GraphPad Prism was used to verify the expression of homozygous differentially expressed genes in GSE115857 microarray of idiopathic membranous nephropathy and GSE66494 microarray of chronic kidney disease, and 7 key genes(FOS, OGT, CLK1, TIA1, TTC14, CHORDC1, and ANKRD36B) were finally obtained. The Gene Ontology(GO) analysis was performed. There were 209 functions of encoded proteins, mainly involved in regulation of RNA splicing, cytoplasmic stress granule, poly(A) binding, etc. Thirteen traditional Chinese medicines with the effect of preventing the transformation of idiopathic membranous nephropathy to end-stage renal disease were screened out from Coremine Medical database, including Ginseng Radix et Rhizoma, Lycopi Herba, and Gardeniae Fructus, which were included in the Chinese Pharmacopoeia(2020 edition). The active ingredient quercetin mined from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) had ability to dock with the key gene FOS-encoded protein molecule, which provided targets and research ideas for the development of new traditional Chinese medicines.

Combined scRNAseq and Bulk RNAseq Analysis to Reveal the Dual Roles of Oxidative Stress-Related Genes in Acute Myeloid Leukemia.

Background: Oxidative stress (OS) can either lead to leukemogenesis or induce tumor cell death by inflammation and immune response accompanying the process of OS through chemotherapy. However, previous studies mainly focus on the level of OS state and the salient factors leading to tumorigenesis and progression of acute myeloid leukemia (AML), and nothing has been done to distinguish the OS-related genes with different functions. Method: First, we downloaded single-cell RNA sequencing (scRNAseq) and bulk RNA sequencing (RNAseq) data from public databases and evaluated the oxidative stress functions between leukemia cells and normal cells by the ssGSEA algorithm. Then, we used machine learning methods to screen out OS gene set A related to the occurrence and prognosis of AML and OS gene set B related to treatment in leukemia stem cells (LSCs) like population (HSC-like). Furthermore, we screened out the hub genes in the above two gene sets and used them to identify molecular subclasses and construct a model for predicting therapy response. Results: Leukemia cells have different OS functions compared to normal cells and significant OS functional changes before and after chemotherapy. Two different clusters in gene set A were identified, which showed different biological properties and clinical relevance. The sensitive model for predicting therapy response based on gene set B demonstrated predictive accuracy by ROC and internal validation. Conclusion: We combined scRNAseq and bulk RNAseq data to construct two different transcriptomic profiles to reveal the different roles of OS-related genes involved in AML oncogenesis and chemotherapy resistance, which might provide important insights into the mechanism of OS-related genes in the pathogenesis and drug resistance of AML.

Glutathione metabolism rewiring protects renal tubule cells against cisplatin-induced apoptosis and ferroptosis.

Renal proximal tubular cells are highly vulnerable to different types of assaults during filtration and reabsorption, leading to acute renal dysfunction and eventual chronic kidney diseases (CKD). The chemotherapeutic drug cisplatin elicits cytotoxicity causing renal tubular cell death, but its executing mechanisms of action are versatile and elusive. Here, we show that cisplatin induces renal tubular cell apoptosis and ferroptosis by disrupting glutathione (GSH) metabolism. Upon cisplatin treatment, GSH metabolism is impaired leading to GSH depletion as well as the execution of mitochondria-mediated apoptosis and lipid oxidation-related ferroptosis through activating IL6/JAK/STAT3 signaling. Inhibition of JAK/STAT3 signaling reversed cell apoptosis and ferroptosis in response to cisplatin induction. Using a cisplatin-induced acute kidney injury (CAKI) mouse model, we found that inhibition of JAK/STAT3 significantly mitigates cisplatin nephrotoxicity with a reduced level of serum BUN and creatinine as well as proximal tubular distortion. In addition, the GSH booster baicalein also reclaims cisplatin-induced renal tubular cell apoptosis and ferroptosis as well as the in vivo nephrotoxicity. In conclusion, cisplatin disrupts glutathione metabolism, leading to renal tubular cell apoptosis and ferroptosis. Rewiring glutathione metabolism represents a promising strategy for combating cisplatin nephrotoxicity.

Controllable Image Synthesis With Attribute-Decomposed GAN.

This paper proposes Attribute-Decomposed GAN (ADGAN) and its enhanced version (ADGAN++) for controllable image synthesis, which can produce realistic images with desired attributes provided in various source inputs. The core ideas of the proposed ADGAN and ADGAN++ are both to embed component attributes into the latent space as independent codes and thus achieve flexible and continuous control of attributes via mixing and interpolation operations in explicit style representations. The major difference between them is that ADGAN processes all component attributes simultaneously while ADGAN++ utilizes a serial encoding strategy. More specifically, ADGAN consists of two encoding pathways with style block connections and is capable of decomposing the original hard mapping into multiple more accessible subtasks. In the source pathway, component layouts are extracted via a semantic parser and the segmented components are fed into a shared global texture encoder to obtain decomposed latent codes. This strategy allows for the synthesis of more realistic output images and the automatic separation of un-annotated component attributes. Although the original ADGAN works in a delicate and efficient manner, intrinsically it fails to handle the semantic image synthesizing task when the number of attribute categories is huge. To address this problem, ADGAN++ employs the serial encoding of different component attributes to synthesize each part of the target real-world image, and adopts several residual blocks with segmentation guided instance normalization to assemble the synthesized component images and refine the original synthesis result. The two-stage ADGAN++ is designed to alleviate the massive computational costs required when synthesizing real-world images with numerous attributes while maintaining the disentanglement of different attributes to enable flexible control of arbitrary component attributes of the synthesized images. Experimental results demonstrate the proposed methods' superiority over the state of the art in pose transfer, face style transfer, and semantic image synthesis, as well as their effectiveness in the task of component attribute transfer. Our code and data are publicly available at https://github.com/menyifang/ADGAN.

Integrative analyses of prognosis, tumor immunity, and ceRNA network of the ferroptosis-associated gene FANCD2 in hepatocellular carcinoma.

Extensive evidence has revealed that ferroptosis plays a vital role in HCC development and progression. Fanconi anemia complementation group D2 (FANCD2) has been reported to serve as a ferroptosis-associated gene and has a close relationship with tumorigenesis and drug resistance. However, the impact of the FANCD2-related immune response and its mechanisms in HCC remains incompletely understood. In the current research, we evaluated the prognostic significance and immune-associated mechanism of FANCD2 based on multiple bioinformatics methods and databases. The results demonstrated that FANCD2 was commonly upregulated in 15/33 tumors, and only the high expression of FANCD2 in HCC was closely correlated with worse clinical outcomes by OS and DFS analyses. Moreover, ncRNAs, including two major types, miRNAs and lncRNAs, were closely involved in mediating FANCD2 upregulation in HCC and were established in a ceRNA network by performing various in silico analyses. The DUXAP8-miR-29c-FANCD2 and LINC00511-miR-29c-FANCD2 axes were identified as the most likely ncRNA-associated upstream regulatory axis of FANCD2 in HCC. Finally, FANCD2 expression was confirmed to be positively related to HCC immune cell infiltration, immune checkpoints, and IPS analysis, and GSEA results also revealed that this ferroptosis-associated gene was primarily involved in cancer-associated pathways in HCC. In conclusion, our investigations indicate that ncRNA-related modulatory overexpression of FANCD2 might act as a promising prognostic and immunotherapeutic target against HCC.

ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation.

The competing endogenous RNA (ceRNA) network is a newly discovered post-transcriptional regulation that controls both physiological and pathological progresses. Increasing research studies have been pivoted on this theory to explore the function of novel non-coding RNAs, pseudogenes, circular RNAs, and messenger RNAs. Although there are several R packages or computational tools to analyze ceRNA networks, an urgent need for easy-to-use computational tools still remains to identify ceRNA regulation. Besides, the conventional tools were mainly devoted to investigating ceRNAs in malignancies instead of those in neurodegenerative diseases. To fill this gap, we developed ceRNAshiny, an interactive R/Shiny application, which integrates widely used computational methods and databases to provide and visualize the construction and analysis of the ceRNA network, including differential gene analysis and functional annotation. In addition, demo data in ceRNAshiny could provide ceRNA network analyses about neurodegenerative diseases such as Parkinson's disease. Overall, ceRNAshiny is a user-friendly application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying ceRNA networks.

Transcriptomic profiling suggests candidate molecular responses to waterlogging in cassava.

Owing to climate change impacts, waterlogging is a serious abiotic stress that affects crops, resulting in stunted growth and loss of productivity. Cassava (Manihot esculenta Grantz) is usually grown in areas that experience high amounts of rainfall; however, little research has been done on the waterlogging tolerance mechanism of this species. Therefore, we investigated the physiological responses of cassava plants to waterlogging stress and analyzed global gene transcription responses in the leaves and roots of waterlogged cassava plants. The results showed that waterlogging stress significantly decreased the leaf chlorophyll content, caused premature senescence, and increased the activities of superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) in the leaves and roots. In total, 2538 differentially expressed genes (DEGs) were detected in the leaves and 13364 in the roots, with 1523 genes shared between the two tissues. Comparative analysis revealed that the DEGs were related mainly to photosynthesis, amino metabolism, RNA transport and degradation. We also summarized the functions of the pathways that respond to waterlogging and are involved in photosynthesis, glycolysis and galactose metabolism. Additionally, many transcription factors (TFs), such as MYBs, AP2/ERFs, WRKYs and NACs, were identified, suggesting that they potentially function in the waterlogging response in cassava. The expression of 12 randomly selected genes evaluated via both quantitative real-time PCR (qRT-PCR) and RNA sequencing (RNA-seq) was highly correlated (R2 = 0.9077), validating the reliability of the RNA-seq results. The potential waterlogging stress-related transcripts identified in this study are representatives of candidate genes and molecular resources for further understanding the molecular mechanisms underlying the waterlogging response in cassava.

NcRNA-regulated CAPZA1 associated with prognostic and immunological effects across lung adenocarcinoma.

Recent discoveries have suggested that the F-actin capping protein α1 subunit (CAPZA1) in various human tumors could play a significantly important role in regulating cell proliferation, metastasis, and epithelial-mesenchymal transition. However, the immune-regulating role of CAPZA1 in the initiation and development of lung adenocarcinoma (LUAD) remains unclear. In our research, we first found that CAPZA1 serves as an oncogene in pan-cancers from the TCGA data and higher CAPZA1 expression process unfavorably prognostic value in LUAD based on starBase database, PrognoScan, and LOGpc database. Then, in our analyses, lncRNAs AC026356.1 in LUAD acted as a competitive endogenous RNA (ceRNA) of miR-30d-5p, which might be the possible regulatory miRNA of CAPZA1 based on the starBase database. Finally, we confirmed that CAPZA1 expression had a tightly positive correlation with immune infiltration cells, immune infiltration markers, TMB, MSI, immune score, stromal score, and immune checkpoints, indicating that CAPZA1 was a markedly reliable therapeutic target for immunological antitumor strategies. In conclusion, our investigations revealed that CAPZA1 might function as an immune-associated biomarker in the development and treatment of LUAD, thereby acting as a promising prognostic and therapeutic target against LUAD.

Benefit of adjuvant chemotherapy for patients with stage IB non-small cell lung cancer: a systematic review and meta-analysis.

BACKGROUND: Adjuvant chemotherapy (ACT) is routinely the recommended treatment for patients with advanced non-small cell lung cancer (NSCLC) but remains a controversial option in stage IB patients. We therefore pooled the current evidence to determine the prognostic impact of ACT in stage IB NSCLC patients in the context of the eighth tumor, node, metastasis (TNM) staging system. METHODS: Five electronic databases were searched for eligible studies up to December 2020 without language restrictions. The primary and secondary outcomes were overall survival (OS) and disease-free survival (DFS). Search results were filtered by a set of eligibility criteria and analyzed in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The risk of bias was assessed independently using a modified set. Stata 16.0 was used for general data analysis and meta-analysis, and subgroup analyses were performed to investigate the source of interstudy heterogeneity. RESULTS: In all, 12 eligible studies were identified and 15,678 patients included. Our results demonstrated that ACT was associated with improved OS [n=11; hazard ratio (HR) =0.65; 95% confidence interval (CI): 0.60-0.70; P<0.001; I2=33.4%, P=0.131] and DFS (n=9; HR =0.73; 95% CI: 0.63-0.83; P<0.001; I2=66.7%, P=0.002) in stage IB NSCLC patients. Subgroup analysis by histology indicated that administration of ACT conferred more favorable survival to both stage IB squamous cell carcinoma (n=1; HR =0.56; 95% CI: 0.28-0.84; P<0.001) and adenocarcinoma (n=6; HR =0.59; 95% CI: 0.47-0.71; P<0.001; I2=31.0%, P=0.203). Meanwhile, both platinum-based ACT (n=7; HR =0.62; 95% CI: 0.51-0.74; P<0.001; I2=44.8%, P=0.093) and other regimens (n=2; HR =0.66; 95% CI: 0.61-0.72; P<0.001; I2=0.7%, P=0.316) could benefit patients with stage IB disease. DISCUSSION: ACT might provide survival benefits to patients with stage IB NSCLC irrespective of histology or regimens. Patient selection and time trend biases were inevitable due to the limitation of retrospective studies. More prospective studies should be initiated to investigate the optimal ACT regimens in different histologic types in stage IB NSCLC patients.