Pub Date : 2026-01-01Epub Date: 2025-11-13DOI: 10.1016/j.slast.2025.100365
Boyang Ma , Haiyan Hu , Yu Lin , Zhiheng Wang , Qingyu Song
Although mechanism-to-intervention processes are becoming possible because to the convergence of single-cell technologies with RNA treatment methods, combined host-microbiome analysis with systematic target identification for colorectal adenoma is still fragmented. Here, we created a repeatable computational pipeline that combines MaAsLin2 for host-microbiome association modeling, QIIME2/DADA2 for microbiome processing, and Seurat/Harmony for single-cell analysis. Under strict statistical control (FDR < 0.05), three single-cell RNA sequencing datasets (GSE117875, GSE178341, and GSE144735; totaling 426,425 cells) were combined with parallel microbiome datasets (PRJNA397906, PRJNA541510, and PRJNA672605; 975 samples). In adenoma-associated microbiomes, we measured a 26.8 % decrease in Shannon diversity (4.21→3.08), with a notable enrichment of Fusobacterium nucleatum and a depletion of Faecalibacterium prausnitzii. Immune activation patterns, goblet cell malfunction (MUC2 2.4-fold drop), and stem cell expansion (LGR5 3.2-fold increase) were all identified by single-cell analysis. 847 significant host-microbiome interactions were found by integration analysis, and F. nucleatum showed a substantial correlation with markers of inflammatory signaling (NFKB1: β=0.64, FDR<0.001) and stem cell proliferation (LGR5: β=0.72, FDR<0.001). 25 RNA-targetable candidates were identified by systematic prioritizing, including mRNA restoration targets (MUC2, FOXP3) and ASO/siRNA suppression targets (NFKB1, IL1B). By converting host-microbiome interaction networks into systematic RNA therapeutic options, this technology framework creates a template for the translation of transcriptomics into therapeutics and offers a repeatable pipeline for the creation of precision interventions in colorectal disease.
{"title":"Technology-enabled integration of single-cell transcriptomics and microbiome data identifies RNA-targetable host-microbiota networks in colorectal adenoma","authors":"Boyang Ma , Haiyan Hu , Yu Lin , Zhiheng Wang , Qingyu Song","doi":"10.1016/j.slast.2025.100365","DOIUrl":"10.1016/j.slast.2025.100365","url":null,"abstract":"<div><div>Although mechanism-to-intervention processes are becoming possible because to the convergence of single-cell technologies with RNA treatment methods, combined host-microbiome analysis with systematic target identification for colorectal adenoma is still fragmented. Here, we created a repeatable computational pipeline that combines MaAsLin2 for host-microbiome association modeling, QIIME2/DADA2 for microbiome processing, and Seurat/Harmony for single-cell analysis. Under strict statistical control (FDR < 0.05), three single-cell RNA sequencing datasets (GSE117875, GSE178341, and GSE144735; totaling 426,425 cells) were combined with parallel microbiome datasets (PRJNA397906, PRJNA541510, and PRJNA672605; 975 samples). In adenoma-associated microbiomes, we measured a 26.8 % decrease in Shannon diversity (4.21→3.08), with a notable enrichment of Fusobacterium nucleatum and a depletion of Faecalibacterium prausnitzii. Immune activation patterns, goblet cell malfunction (MUC2 2.4-fold drop), and stem cell expansion (LGR5 3.2-fold increase) were all identified by single-cell analysis. 847 significant host-microbiome interactions were found by integration analysis, and F. nucleatum showed a substantial correlation with markers of inflammatory signaling (NFKB1: β=0.64, FDR<0.001) and stem cell proliferation (LGR5: β=0.72, FDR<0.001). 25 RNA-targetable candidates were identified by systematic prioritizing, including mRNA restoration targets (MUC2, FOXP3) and ASO/siRNA suppression targets (NFKB1, IL1B). By converting host-microbiome interaction networks into systematic RNA therapeutic options, this technology framework creates a template for the translation of transcriptomics into therapeutics and offers a repeatable pipeline for the creation of precision interventions in colorectal disease.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100365"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145530929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-12DOI: 10.1016/j.slast.2025.100387
Chang Liu , Hui Zhang
{"title":"Mass spectrometry applications for high-throughput experimentation in supporting drug discovery","authors":"Chang Liu , Hui Zhang","doi":"10.1016/j.slast.2025.100387","DOIUrl":"10.1016/j.slast.2025.100387","url":null,"abstract":"","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100387"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145757690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-04DOI: 10.1016/j.slast.2025.100381
Min Tang , Rui Liang , Zhenyu Wu , Cheng Chen , Bo He , Ning Zhou , Sujuan Wang , Xinqiang Xiao , Guangdi Li , Yongfang Jiang , Guozhong Gong , Yanwen Zhou
Aims
The transcription factor OCT4A, a well-established master pluripotency factor, exerts regulatory effects on cell fate determination that are closely associated with its protein levels. This study aims to uncover the downstream gene profile features relevant to tumorigenic potential mediated by OCT4A under varying protein abundance in somatic cancer cells (SCCs).
Materials and methods
CRISPR-Cas9-mediated knockout and doxycycline-inducible OCT4A expression systems were established in cervical (HeLa) and hepatocellular (HepG2, Huh7) cancer cells. Single-cell sequencing, spatial transcriptomic and survival analysis data were used to elucidate the expression pattern of OCT4 in somatic cancer tissues and its prognostic relevance. The plate colony formation assay was performed to assess the tumorigenic capacity of SCCs, and Bulk RNA sequencing coupled with weighted gene co-expression network analysis (WGCNA) identified dose-relevant downstream pathways. Functional enrichment, survival modeling, and RT-qPCR validation were used to construct OCT4A-dose-dependent transcriptional regulatory networks.
Key findings
OCT4 transcript, is heterogeneously present and confined to a small subset of tumor cells within somatic cancer tissues, with a significantly higher proportion of OCT4-positive cells in tumor tissues compared to paired paraneoplastic tissues and is significantly correlated with poor prognosis in SCCs. Endogenous low-level OCT4A positively regulates tumorigenic capacity predominantly through targeting non-coding genes, whereas high-level OCT4A suppresses tumorigenic capacity primarily via protein-coding genes in SCCs. A prognostic model based on high-level OCT4A-regulated protein-coding genes was associated with favorable clinical outcomes, aligning with in vitro phenotypic results.
Significance
Our findings further confirm in SCCs that the functional pleiotropy of OCT4A is closely linked to its protein abundance, and further systematically elucidate the molecular signatures of OCT4A-regulated downstream gene networks associated with tumorigenic phenotypes at differential protein levels, providing novel insights for its translational exploitation in both oncological intervention and regenerative medicine strategies.
{"title":"Deciphering OCT4A-dose-dependent transcriptional profiles associated with tumorigenic potential in somatic cancer cells","authors":"Min Tang , Rui Liang , Zhenyu Wu , Cheng Chen , Bo He , Ning Zhou , Sujuan Wang , Xinqiang Xiao , Guangdi Li , Yongfang Jiang , Guozhong Gong , Yanwen Zhou","doi":"10.1016/j.slast.2025.100381","DOIUrl":"10.1016/j.slast.2025.100381","url":null,"abstract":"<div><h3>Aims</h3><div>The transcription factor OCT4A, a well-established master pluripotency factor, exerts regulatory effects on cell fate determination that are closely associated with its protein levels. This study aims to uncover the downstream gene profile features relevant to tumorigenic potential mediated by OCT4A under varying protein abundance in somatic cancer cells (SCCs).</div></div><div><h3>Materials and methods</h3><div>CRISPR-Cas9-mediated knockout and doxycycline-inducible OCT4A expression systems were established in cervical (HeLa) and hepatocellular (HepG2, Huh7) cancer cells. Single-cell sequencing, spatial transcriptomic and survival analysis data were used to elucidate the expression pattern of OCT4 in somatic cancer tissues and its prognostic relevance. The plate colony formation assay was performed to assess the tumorigenic capacity of SCCs, and Bulk RNA sequencing coupled with weighted gene co-expression network analysis (WGCNA) identified dose-relevant downstream pathways. Functional enrichment, survival modeling, and RT-qPCR validation were used to construct OCT4A-dose-dependent transcriptional regulatory networks.</div></div><div><h3>Key findings</h3><div>OCT4 transcript, is heterogeneously present and confined to a small subset of tumor cells within somatic cancer tissues, with a significantly higher proportion of OCT4-positive cells in tumor tissues compared to paired paraneoplastic tissues and is significantly correlated with poor prognosis in SCCs. Endogenous low-level OCT4A positively regulates tumorigenic capacity predominantly through targeting non-coding genes, whereas high-level OCT4A suppresses tumorigenic capacity primarily via protein-coding genes in SCCs. A prognostic model based on high-level OCT4A-regulated protein-coding genes was associated with favorable clinical outcomes, aligning with in vitro phenotypic results.</div></div><div><h3>Significance</h3><div>Our findings further confirm in SCCs that the functional pleiotropy of OCT4A is closely linked to its protein abundance, and further systematically elucidate the molecular signatures of OCT4A-regulated downstream gene networks associated with tumorigenic phenotypes at differential protein levels, providing novel insights for its translational exploitation in both oncological intervention and regenerative medicine strategies.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100381"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145696135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cold tumors, characterized by low cytotoxic T cell infiltration, limit immunotherapy efficacy. Current strategies often depend on tumor-specific antigens or non-specific immune activation, restricting translational potential. Here, we present a peptide-based platform that leverages intratumoral expression of influenza-derived peptides to redirect virus-specific CD8⁺ T cells and remodel the tumor immune microenvironment in an antigen-independent manner.
Methods
In murine 4T1 and CT26 tumor models, the immunodominant influenza A virus peptide NP147–155 was delivered via intratumoral peptide injection or stable lentiviral expression. Immune remodeling was assessed using flow cytometry, cytokine profiling, and transcriptomic profiling. Differential gene expression and pathway analyses identified mechanisms underlying cold-to-hot TME conversion.
Results
Intratumoral NP147–155 expression robustly activated virus-specific CD8⁺ T cells and enhanced IFN-γ secretion. Transcriptomic profiling revealed upregulation of genes associated with cytotoxicity, chemokine signaling, antigen presentation, and the NKG2D-NKG2DL pathway, consistent with increased T cell infiltration and conversion of cold tumors into hot tumors. Tumor growth was significantly suppressed, and durable anti-tumor immunity was established, including in MHC class I-deficient tumors.
Conclusion
This study demonstrates a peptide-based platform to remodel cold tumor immune microenvironments. Integration of transcriptomic profiling provides mechanistic insights and establishes a robust workflow for evaluating immunomodulatory technologies. This tumor-agnostic approach may enhance anti-tumor immunity and improve immunotherapy efficacy in cold tumors.
{"title":"Viral peptides remodel the tumor immune microenvironment of cold tumors with RNA-seq insights","authors":"Zhengqi Peng , Qian Chen , Pengkhun Nov , Mohsin Farid Sulehri , Yujing Liu , Hexi Zhu , Wulikaixi Yagufu , Yiteng Chen , Haipeng Tang , Linlang Guo , Mengchuan Wang","doi":"10.1016/j.slast.2025.100379","DOIUrl":"10.1016/j.slast.2025.100379","url":null,"abstract":"<div><h3>Background</h3><div>Cold tumors, characterized by low cytotoxic T cell infiltration, limit immunotherapy efficacy. Current strategies often depend on tumor-specific antigens or non-specific immune activation, restricting translational potential. Here, we present a peptide-based platform that leverages intratumoral expression of influenza-derived peptides to redirect virus-specific CD8⁺ T cells and remodel the tumor immune microenvironment in an antigen-independent manner.</div></div><div><h3>Methods</h3><div>In murine 4T1 and CT26 tumor models, the immunodominant influenza A virus peptide NP<sub>147–155</sub> was delivered via intratumoral peptide injection or stable lentiviral expression. Immune remodeling was assessed using flow cytometry, cytokine profiling, and transcriptomic profiling. Differential gene expression and pathway analyses identified mechanisms underlying cold-to-hot TME conversion.</div></div><div><h3>Results</h3><div>Intratumoral NP<sub>147–155</sub> expression robustly activated virus-specific CD8⁺ T cells and enhanced IFN-γ secretion. Transcriptomic profiling revealed upregulation of genes associated with cytotoxicity, chemokine signaling, antigen presentation, and the NKG2D-NKG2DL pathway, consistent with increased T cell infiltration and conversion of cold tumors into hot tumors. Tumor growth was significantly suppressed, and durable anti-tumor immunity was established, including in MHC class I-deficient tumors.</div></div><div><h3>Conclusion</h3><div>This study demonstrates a peptide-based platform to remodel cold tumor immune microenvironments. Integration of transcriptomic profiling provides mechanistic insights and establishes a robust workflow for evaluating immunomodulatory technologies. This tumor-agnostic approach may enhance anti-tumor immunity and improve immunotherapy efficacy in cold tumors.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100379"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145696199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-05DOI: 10.1016/j.slast.2025.100382
Nathaniel G. Hentz , John Thomas Bradshaw
The need to measure volume is an important component of any liquid-based assay, because the final result is often based upon the concentration of some analyte within the assay. Volume measurements can be used to determine the actual amount of sample throughout an assay. They can also be used to calibrate, routinely verify performance of, or optimize liquid classes for liquid handling platforms or other automated or manual pipetting devices. This review surveys current liquid volume measurement methods and technologies available for use in life science laboratories. Volumes considered in this review range from picoliters to a few milliliters, which are typical for life science assays. While the need for volume measurement extends across many different industries, the focus here is on applications in biopharmaceutical and clinical life science laboratories. This review evaluates key measurable attributes, including the addressable volume range, as well as the attainable precision and accuracy of the method or technology. Several important features are also considered such as the ability to measure actual samples, commercial availability, regulatory compliance, sample type, workflow integration, suitability for in-line use, and relative ease of use.
{"title":"Guide to liquid volume measurements: A review of methods and technologies","authors":"Nathaniel G. Hentz , John Thomas Bradshaw","doi":"10.1016/j.slast.2025.100382","DOIUrl":"10.1016/j.slast.2025.100382","url":null,"abstract":"<div><div>The need to measure volume is an important component of any liquid-based assay, because the final result is often based upon the concentration of some analyte within the assay. Volume measurements can be used to determine the actual amount of sample throughout an assay. They can also be used to calibrate, routinely verify performance of, or optimize liquid classes for liquid handling platforms or other automated or manual pipetting devices. This review surveys current liquid volume measurement methods and technologies available for use in life science laboratories. Volumes considered in this review range from picoliters to a few milliliters, which are typical for life science assays. While the need for volume measurement extends across many different industries, the focus here is on applications in biopharmaceutical and clinical life science laboratories. This review evaluates key measurable attributes, including the addressable volume range, as well as the attainable precision and accuracy of the method or technology. Several important features are also considered such as the ability to measure actual samples, commercial availability, regulatory compliance, sample type, workflow integration, suitability for in-line use, and relative ease of use.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100382"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145702913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-04DOI: 10.1016/j.slast.2025.100380
Ferdinand Lange, Tessa Habich, Sascha Beutel
Laboratory digitalization is a complex field that includes many aspects to consider, such as device control, data management, and data evaluation. This article presents a potential laboratory digitalization process, including the use of open-source software and hardware components from laboratory equipment to data evaluation. It shows what is required and how it can be used. In this example, a SiLA-based continuous chromatography system is used as a model device to demonstrate the possible purification of GFP from crude cell lysate. The current version of the Gateway Module is a translation unit for driver protocols used for device control. It uses SiLA-based drivers within a Docker environment to communicate with the server infrastructure. The Gateway Module software was managed and rolled out with the mkbox-project. Finally, the recorded laboratory data are stored in a data management system and made available for later analysis. The article also discusses how software and hardware are maintained in the background, as well as the update strategy used.
{"title":"Implementation of a modular digital laboratory infrastructure for SiLA 2 based devices","authors":"Ferdinand Lange, Tessa Habich, Sascha Beutel","doi":"10.1016/j.slast.2025.100380","DOIUrl":"10.1016/j.slast.2025.100380","url":null,"abstract":"<div><div>Laboratory digitalization is a complex field that includes many aspects to consider, such as device control, data management, and data evaluation. This article presents a potential laboratory digitalization process, including the use of open-source software and hardware components from laboratory equipment to data evaluation. It shows what is required and how it can be used. In this example, a SiLA-based continuous chromatography system is used as a model device to demonstrate the possible purification of GFP from crude cell lysate. The current version of the Gateway Module is a translation unit for driver protocols used for device control. It uses SiLA-based drivers within a Docker environment to communicate with the server infrastructure. The Gateway Module software was managed and rolled out with the mkbox-project. Finally, the recorded laboratory data are stored in a data management system and made available for later analysis. The article also discusses how software and hardware are maintained in the background, as well as the update strategy used.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100380"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145696148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-05DOI: 10.1016/j.slast.2025.100384
Ping Wu , Matthew Moore , Peter Cieszewski, Kayla Beam, Sivamani Elumalai, Stephen B. Rigoulot
This report outlines the development and implementation of a Computer Numerical Control (CNC) based Automated Media Dispensing System (AMDS) in a plant biotechnology research laboratory. The AMDS, a dual-channel liquid dispensing system, underwent comprehensive testing and refinement over a two-year period. Designed to serve the production demand for a commercial transformation pipeline, the system represents an initial automation step to replace manual media dispensing operations. Performance evaluation demonstrates that this iteration surpasses manual dispensing metrics, achieving a process capability index (Cpk) of 2.28 compared to 1.43 for manual operations, while maintaining comparable time per tray efficiency. The system delivers significant ergonomic benefits by reducing prolonged standing periods associated with manual dispensing tasks. Building upon established automated dispensing principles, the custom-built AMDS achieves core functionality while reducing the barrier to entry, with an estimated material cost of approximately one-fiftieth that of more comprehensive market solutions. The system's modular architecture facilitates future modifications and adaptations, positioning it as a valuable tool for addressing evolving research needs in plant biotechnology while enabling broader adoption of automated dispensing technology.
{"title":"Low-Cost CNC-Based media dispensing system for biotechnology laboratories","authors":"Ping Wu , Matthew Moore , Peter Cieszewski, Kayla Beam, Sivamani Elumalai, Stephen B. Rigoulot","doi":"10.1016/j.slast.2025.100384","DOIUrl":"10.1016/j.slast.2025.100384","url":null,"abstract":"<div><div>This report outlines the development and implementation of a Computer Numerical Control (CNC) based Automated Media Dispensing System (AMDS) in a plant biotechnology research laboratory. The AMDS, a dual-channel liquid dispensing system, underwent comprehensive testing and refinement over a two-year period. Designed to serve the production demand for a commercial transformation pipeline, the system represents an initial automation step to replace manual media dispensing operations. Performance evaluation demonstrates that this iteration surpasses manual dispensing metrics, achieving a process capability index (Cpk) of 2.28 compared to 1.43 for manual operations, while maintaining comparable time per tray efficiency. The system delivers significant ergonomic benefits by reducing prolonged standing periods associated with manual dispensing tasks. Building upon established automated dispensing principles, the custom-built AMDS achieves core functionality while reducing the barrier to entry, with an estimated material cost of approximately one-fiftieth that of more comprehensive market solutions. The system's modular architecture facilitates future modifications and adaptations, positioning it as a valuable tool for addressing evolving research needs in plant biotechnology while enabling broader adoption of automated dispensing technology.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100384"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145702911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-12DOI: 10.1016/j.slast.2025.100386
XingYu Yang , Qin Qiu , Yu Tang , WeiDi Sun , XiFang Wu , XiaoJiang Li , YanXin Ren
Purpose
The PBRM1 (PB1) gene, which encodes BAF180, a specific subunit of the PBAF SWI / SNF complex, is extensively studied in some other cancers, yet its effects and related mechanisms in NPC remains inadequately understood. Aerobic glycolysis is one of the hallmarks of cancer, and whether PBRM1 is involved in this metabolic metastasis in NPC remains unclear.
Methods
We established NPC cell lines with knockdown of PBRM1 and performed functional analysis to understand the impact of their production. Based on the RNA-seq data, we mainly analyzed the activity of the AKT-mTOR signaling pathway and examined the expression levels of some key glycolytic genes including HIF 1α, PFKP, ENO 1, PKM and LDHA. Using in vivo experiments, we verified the effect of PBRM1 on the proliferation of NPC.
Results
Our findings indicate that PBRM1 deficiency enhances proliferation, migration, and invasion in both CNE1 and CNE2 cells. Notably, PBRM1 downregulate activates the AKT-mTOR pathway, upregulating glycolytic enzymes and lactate production. Subcutaneous tumor formation assay in nude mice also showed that knockdown of PBRM1 promoted NPC cells growth.
Conclusion
This study illuminates PBRM1′s tumor suppressor role, highlighting the AKT-mTOR pathway and aerobic glycolysis as potential therapeutic targets in NPC.
{"title":"Elucidating the role of PBRM1 in NPC via RNA-seq transcriptomic sequencing","authors":"XingYu Yang , Qin Qiu , Yu Tang , WeiDi Sun , XiFang Wu , XiaoJiang Li , YanXin Ren","doi":"10.1016/j.slast.2025.100386","DOIUrl":"10.1016/j.slast.2025.100386","url":null,"abstract":"<div><h3>Purpose</h3><div>The PBRM1 (PB1) gene, which encodes BAF180, a specific subunit of the PBAF SWI / SNF complex, is extensively studied in some other cancers, yet its effects and related mechanisms in NPC remains inadequately understood. Aerobic glycolysis is one of the hallmarks of cancer, and whether PBRM1 is involved in this metabolic metastasis in NPC remains unclear.</div></div><div><h3>Methods</h3><div>We established NPC cell lines with knockdown of PBRM1 and performed functional analysis to understand the impact of their production. Based on the RNA-seq data, we mainly analyzed the activity of the AKT-mTOR signaling pathway and examined the expression levels of some key glycolytic genes including HIF 1α, PFKP, ENO 1, PKM and LDHA. Using in vivo experiments, we verified the effect of PBRM1 on the proliferation of NPC.</div></div><div><h3>Results</h3><div>Our findings indicate that PBRM1 deficiency enhances proliferation, migration, and invasion in both CNE1 and CNE2 cells. Notably, PBRM1 downregulate activates the AKT-mTOR pathway, upregulating glycolytic enzymes and lactate production. Subcutaneous tumor formation assay in nude mice also showed that knockdown of PBRM1 promoted NPC cells growth.</div></div><div><h3>Conclusion</h3><div>This study illuminates PBRM1′s tumor suppressor role, highlighting the AKT-mTOR pathway and aerobic glycolysis as potential therapeutic targets in NPC.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100386"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145757713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-11-29DOI: 10.1016/j.slast.2025.100372
Yirui Niu , Quan Dai , Min Li
Skeletal Class II malocclusion is a common dentofacial deformity often associated with dysregulation in the growth and remodeling of periodontal tissues. Understanding the cellular heterogeneity and molecular pathways of periodontal ligament (PDL) cells is crucial for identifying novel therapeutic targets. However, traditional bulk sequencing methods lack the resolution to distinguish cell-type-specific gene expression and epigenetic regulation, limiting insights into the pathogenesis of this condition. To address these limitations, we propose an integrated framework utilizing 5200 high-quality PDL Single-Cell RNA combined with Assay for Transposase-Accessible Chromatin using sequencing (scRNA-ATAC-seq) to perform a multi-omics dissection of PDL cells in Class II malocclusion. This approach enables the simultaneous profiling of transcriptomic and chromatin accessibility landscapes at single-cell resolution, uncovering cell-specific regulatory networks. Using this scRNA-ATAC-seq method, we successfully identified 12 distinct PDL cell subpopulations and revealed key transcription factors and signaling pathways involved in aberrant skeletal development. Data integration achieved a 0.94 accuracy score, enabling confident regulatory mapping. The findings provide critical insights into the gene regulatory architecture underlying Class II malocclusion and highlight potential cell-specific therapeutic targets for clinical intervention.
{"title":"Single cell and multi omics dissection of periodontal ligament cells identifies regulatory networks and therapeutic targets in skeletal class II malocclusion","authors":"Yirui Niu , Quan Dai , Min Li","doi":"10.1016/j.slast.2025.100372","DOIUrl":"10.1016/j.slast.2025.100372","url":null,"abstract":"<div><div>Skeletal Class II malocclusion is a common dentofacial deformity often associated with dysregulation in the growth and remodeling of periodontal tissues. Understanding the cellular heterogeneity and molecular pathways of periodontal ligament (PDL) cells is crucial for identifying novel therapeutic targets. However, traditional bulk sequencing methods lack the resolution to distinguish cell-type-specific gene expression and epigenetic regulation, limiting insights into the pathogenesis of this condition. To address these limitations, we propose an integrated framework utilizing 5200 high-quality PDL Single-Cell RNA combined with Assay for Transposase-Accessible Chromatin using sequencing (scRNA-ATAC-seq) to perform a multi-omics dissection of PDL cells in Class II malocclusion. This approach enables the simultaneous profiling of transcriptomic and chromatin accessibility landscapes at single-cell resolution, uncovering cell-specific regulatory networks. Using this scRNA-ATAC-seq method, we successfully identified 12 distinct PDL cell subpopulations and revealed key transcription factors and signaling pathways involved in aberrant skeletal development. Data integration achieved a 0.94 accuracy score, enabling confident regulatory mapping. The findings provide critical insights into the gene regulatory architecture underlying Class II malocclusion and highlight potential cell-specific therapeutic targets for clinical intervention.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100372"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145650051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-12DOI: 10.1016/j.slast.2025.100385
Yixian Liu , Xin Lan , Xiaoyi Zhang , Xinyi Ren , Hongmin Duan , Yanrong Dan , Dong Duan , Ganghua Lu
<div><h3>Background</h3><div>Ovarian cancer (OC) is the deadliest malignant tumor among gynecological tumors. The current treatment measures for OC remain not optimistic, so it is important to determine reliable prognostic biomarkers to prolong OC patients' survival.</div></div><div><h3>Methods</h3><div>The OC-related transcriptome data were downloaded from the University of California Santa Cruz (UCSC) and we obtained the Differentially Expressed Genes (DEGs) between OC and normal samples. The Nectins and Nectin-like (Necl) scores of OC patients were calculated by single-sample Gene Set Enrichment Analysis (ssGSEA), the correlation between these scores and the prognosis of OC patients was explored using the Kaplan-Meier survival curve. DEGs were overlapped with Nectins and Necls-related genes selected by Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the differentially expressed Nectins and Necls-related genes (DENNGs). Next, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were carried out on DENNGs. The Protein-Protein Interaction (PPI) network of DENNGs was constructed and hub genes were screened. In addition, univariate and multivariate Cox regression analysis were used to obtain the prognosis-related genes of OC patients and construct a prognostic model. Gene Set Variation Analysis (GSVA) was performed on the genes of high and low risk groups. SsGSEA algorithm was used to calculate the immune cell scores and the correlation between different immune cells and prognosis-related genes was explored.</div></div><div><h3>Results</h3><div>We obtained 583 DENNGs by crossing 6778 DEGs in OC and 584 Nectin- and Necl-related genes. The scores of Nectins and Necls in the OC group increased significantly, together with the poor prognosis. KEGG and GO analyses showed that DENNGs were mainly associated with cell proliferation, aging, canceration, and virus infection. Univariate and multivariate Cox analyses screened six prognosis-related genes (PTTG1, MELK, CENPF, PLK1, KIF20A, TOP2A) and modeled prognosis risks. Furthermore, a nomogram that integrated the risk model and patient age accurately predicted OC prognosis. The results of GSVA showed that TGF-β-mediated epithelial-mesenchymal transition, tumor cell invasion and metastasis were activated in the high-risk group, while pathways related to tumor cell invasiveness, such as hedgehog (Hh) mediated by hypoxia, were activated in the low-risk group. Finally, we found five immune cells (activated CD4+ <em>T</em> cells, central memory CD4+ <em>T</em> cells, central memory CD8+ <em>T</em> cells, T follicular helper cells (tTFH), and type II helper T cells(Th2)) different between OC and normal samples, and prognosis-related genes were positively correlated with activated CD4+ cells and Th2 of immune cells but negatively correlated with tTFH.</div></div><div><h3>Conclusion</h3><div>We identified six prognosis-related genes and constructed a prognostic mo
{"title":"A novel prognostic model in ovarian cancer based on the Nectin family and Necl-like molecules related transcriptomics","authors":"Yixian Liu , Xin Lan , Xiaoyi Zhang , Xinyi Ren , Hongmin Duan , Yanrong Dan , Dong Duan , Ganghua Lu","doi":"10.1016/j.slast.2025.100385","DOIUrl":"10.1016/j.slast.2025.100385","url":null,"abstract":"<div><h3>Background</h3><div>Ovarian cancer (OC) is the deadliest malignant tumor among gynecological tumors. The current treatment measures for OC remain not optimistic, so it is important to determine reliable prognostic biomarkers to prolong OC patients' survival.</div></div><div><h3>Methods</h3><div>The OC-related transcriptome data were downloaded from the University of California Santa Cruz (UCSC) and we obtained the Differentially Expressed Genes (DEGs) between OC and normal samples. The Nectins and Nectin-like (Necl) scores of OC patients were calculated by single-sample Gene Set Enrichment Analysis (ssGSEA), the correlation between these scores and the prognosis of OC patients was explored using the Kaplan-Meier survival curve. DEGs were overlapped with Nectins and Necls-related genes selected by Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the differentially expressed Nectins and Necls-related genes (DENNGs). Next, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were carried out on DENNGs. The Protein-Protein Interaction (PPI) network of DENNGs was constructed and hub genes were screened. In addition, univariate and multivariate Cox regression analysis were used to obtain the prognosis-related genes of OC patients and construct a prognostic model. Gene Set Variation Analysis (GSVA) was performed on the genes of high and low risk groups. SsGSEA algorithm was used to calculate the immune cell scores and the correlation between different immune cells and prognosis-related genes was explored.</div></div><div><h3>Results</h3><div>We obtained 583 DENNGs by crossing 6778 DEGs in OC and 584 Nectin- and Necl-related genes. The scores of Nectins and Necls in the OC group increased significantly, together with the poor prognosis. KEGG and GO analyses showed that DENNGs were mainly associated with cell proliferation, aging, canceration, and virus infection. Univariate and multivariate Cox analyses screened six prognosis-related genes (PTTG1, MELK, CENPF, PLK1, KIF20A, TOP2A) and modeled prognosis risks. Furthermore, a nomogram that integrated the risk model and patient age accurately predicted OC prognosis. The results of GSVA showed that TGF-β-mediated epithelial-mesenchymal transition, tumor cell invasion and metastasis were activated in the high-risk group, while pathways related to tumor cell invasiveness, such as hedgehog (Hh) mediated by hypoxia, were activated in the low-risk group. Finally, we found five immune cells (activated CD4+ <em>T</em> cells, central memory CD4+ <em>T</em> cells, central memory CD8+ <em>T</em> cells, T follicular helper cells (tTFH), and type II helper T cells(Th2)) different between OC and normal samples, and prognosis-related genes were positively correlated with activated CD4+ cells and Th2 of immune cells but negatively correlated with tTFH.</div></div><div><h3>Conclusion</h3><div>We identified six prognosis-related genes and constructed a prognostic mo","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"36 ","pages":"Article 100385"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145758442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号