Spatially resolved multiomics: data analysis from monoomics to multiomics DOI Creative Commons
Changxiang Huan, Jinze Li, Yingxue Li

et al.

BME Frontiers, Journal Year: 2024, Volume and Issue: 6

Published: Jan. 13, 2024

Spatial monoomics has been recognized as a powerful tool for exploring life sciences. Recently, spatial multiomics advanced considerably, which could contribute to clarifying many biological issues. techniques in epigenomics, genomics, transcriptomics, proteomics, and metabolomics can enhance our understanding of functions cellular identities by simultaneously measuring tissue structures biomolecule levels. technology evolved from multiomics. Moreover, the resolution, high-throughput detection capability, capture efficiency, compatibility with various sample types omics have considerably advanced. Despite technological advances this field, data analysis frameworks stagnated. Current challenges include incomplete pipeline, overly complex tasks, few established strategies. In review, we systematically summarize recent developments improvements related pipeline. On basis technology, propose integration strategy cross-platform, cross-slice, cross-modality. We potential applications aiming provide researchers clinicians better how such is expected substantially impact biology precision medicine through measurements extraction biomolecular features.

Language: Английский

Integrating multi-omics and machine learning methods reveals the metabolism of amino acids and derivatives-related signature in colorectal cancer DOI Creative Commons
Jian Yue, Huiying Fang,

Qian Yang

et al.

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 26, 2025

Objective The metabolism of amino acids and derivatives (MAAD) is closely related to the occurrence development colorectal cancer (CRC), but specific regulatory mechanisms are not yet clear. This study aims explore role MAAD in progression ultimately identify key molecules that may become potential therapeutic targets for CRC. Methods integrates bulk transcriptome single-cell analyze MAAD-related genes from multiple levels. Subsequently, numerous machine learning methods were incorporated construct prognostic models, infiltration immune cells, tumor heterogeneity, mutation burden, pathway changes under different modes analyzed. Finally, identified experimental validation. Results We successfully constructed models Nomograms based on molecules. There was a notable survival benefit observed low-risk patients when contrasted with their high-risk counterparts. In addition, group had poorer response immunotherapy stronger heterogeneity compared group. Further research found by knocking down gene. LSM8, malignant characteristics cell lines significantly alleviated, suggesting LSM8 target. Conclusion gene likely involved CRC could be hopeful target intervention.

Language: Английский

Citations

0
Role and Validation of Lactylation-Related Gene Markers in Postmenopausal Osteoporosis DOI
Fengwei Tan,

Xiaohong Cui,

Shuang Ren

et al.

Applied Biochemistry and Biotechnology, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Language: Английский

Citations

0
BRD4 as the key lactylation related gene in heart failure identified through bioinformatics analysis DOI Creative Commons
Kaiyuan Li, Lingyu Han,

Xiaowen Wang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 1, 2025

Lactylation modification is postulated to influence the progression of heart failure (HF) through diverse pathways, albeit underlying mechanisms remain elusive. Methods In this study, bioinformatics approaches were employed analyze HF dataset (GSE5406) retrieved from Gene Expression Omnibus, with objective identifying lactylation-related genes (LRGs). Key LRGs implicated in selected using Least Absolute Shrinkage and Selection Operator (LASSO) Weighted Co-Expression Network Analysis (WGCNA). The diagnostic efficacy biological significance these evaluated receiver operating characteristic (ROC) curve analysis, Set Enrichment Analysis, immune cell infiltration analysis. Furthermore, findings validated single-cell sequencing datasets (GSE161470) vitro models ascertain expression patterns functional roles identified key LRGs. A total 276 dataset. Initial screening utilizing two analysis methods pinpointed BRD4 as a potential pivotal LRG influencing progression. ROC revealed high accuracy for BRD4, an Area Under Curve score 0.877. Immune data analyses indicated that exhibits strong association cells, including mast T macrophages, demonstrates significantly elevated cells well cardiomyocytes. Both mRNA protein levels found be upregulated compared control groups. This study represents first utilize multiple identify HF, thereby establishing foundation future investigations into acylation-related HF.

Language: Английский

Citations

0
Construction of a novel prognostic model based on lncRNAs-related to DNA damage repair for predicting the prognosis of clear cell renal cell carcinoma DOI Creative Commons
Peng Chen, Jian Li, Renli Tian

et al.

Annals of Medicine, Journal Year: 2025, Volume and Issue: 57(1)

Published: April 2, 2025

CcRCC has the characteristics of high aggression, metastasis, mortality, wide tumour heterogeneity and variable clinical course. The purpose this study was to explore potential value lncRNAs-related DNA damage repair (DDR) in predicting prognosis ccRCC by construction verification a novel prognostic model. RNA-seq data were downloaded from public databases. Subsequently, Pearson correlation analysis differential expression performed identify DElncRNAs-related DDR. Then, through univariate Cox LASSO analysis, DDR associated with screened for risk score In addition, functional annotation, mutation burden, immune drug sensitivity analyses based on assess patients different groups. Based four best selected. model these DElncRNAs constructed LASSO. Multivariate showed that age independent factors (p < 0.05). Functional enrichment DDR-related biological processes mainly enriched group. highly mutated genes low groups same (VHL, PBRM1 TTN), but they also had their own unique genes. significantly 0.05) positively correlated infiltration degree CD8 T cells evaluated six algorithms. it found sensitivities drugs Etoposide, Imatinib, Sorafenib, Bosutinib Sunitinib. A satisfactory accuracy survival patients.

Language: Английский

Citations

0
Lactylation in cancer progression and drug resistance DOI
Yuxiu Sun, He Wang,

Zhe Cui

et al.

Drug Resistance Updates, Journal Year: 2025, Volume and Issue: unknown, P. 101248 - 101248

Published: April 1, 2025

Language: Английский

Citations

0
Machine learning algorithms integrate bulk and single-cell RNA data to reveal the crosstalk and heterogeneity of Glycolysis and Lactylation activity following Pulmonary Arterial Hypertension DOI
Qiuhong Chen,

Qin Zheng,

Yang Hong

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 25, 2025

Abstract Background: Glycolysis and lactylation activity significantly impact the pathogenesis of Pulmonary Arterial Hypertension (PAH); however, studies exploring their heterogeneity potential correlation at single-cell level are still lacking. Identifying feature genes that commonly regulated by both glycolysis could enhance our understanding PAH. Methods: We employed RNA sequencing (scRNA-seq) to investigate across various cellular tiers following PAH, aiming acquire comprehensive biological insights into We Utilized AUCell, Ucell, singscore, ssGSEA, AddModuleScore algorithms identify common positive negative in PAH level. Furthermore, we three machine learning algorithms, Boruta, Random Forest, SVM-RFE optimal related BulkRNA-seq further leveraged CellChat pseudotime analysis delve regulatory mechanisms characteristic genes. used qPCR detect expression ACTR2, CCDC88A, MRC1 rat model pulmonary hypertension. Results: For first time level, discovered activities exhibit different cell layers However, show remarkable consistency, being highly active macrophages, fibroblasts, monocytes, epithelial cells, while displaying lower lymphatic endothelial cells. This indicates a between these two pathways Consequently, defined set co-regulate Using identified key predictive for namely MRC1. verify excessive Conclusions: Following might simultaneously upregulating macrophages monocytes contribute progression. Clinical trial Not applicable.

Language: Английский

Citations

0
A Novel Signature Composed of Hypoxia, Glycolysis, Lactylation Related Genes to Predict Prognosis and Immunotherapy in Hepatocellular Carcinoma DOI Creative Commons

Yi Feng,

Shichao Long,

Yuanbing Yao

et al.

Frontiers in Bioscience-Landmark, Journal Year: 2025, Volume and Issue: 30(4)

Published: April 21, 2025

Background: Hepatocellular carcinoma (HCC) is one of the leading causes cancer death worldwide. The hypoxic microenvironment in HCC enhances glycolysis and co-directed lactate accumulation, which leads to increased lactylation. However, exact biological pattern remains be elucidated. Therefore, we sought identify hypoxia-glycolysis-lactylation (HGL) prognosis-related signatures validate this vitro. Methods: Transcriptomic data patients with were collected from Cancer Genome Atlas (TCGA), International Consortium (ICGC), Gene Expression Omnibus (GEO) databases. Differentially expressed HGL genes between normal tissues obtained by DEseq2. consensus clustering algorithm was employed stratify into two distinct clusters. Subsequently, single sample Set Enrichment Analysis (ssGSEA), Tumor Immune Estimation Resource (TIMER) Dysfunction Exclusion (TIDE) algorithms utilized assess immune infiltration evasion. Least Absolute Shrinkage Selection Operator (LASSO) COX regression analysis used an signature. Based on spatial transcriptome histological data, analyzed expression these explored function Homer Scaffold Protein 1 (HOMER1) cells. Results: We identified 72 differentially Cluster2, better survival (p < 0.001), significantly enriched metabolic-related pathways. signature exhibited great predictive efficacy for TCGA, ICGC, GSE148355 databases (3-year area under curve (AUC) = 0.822, 0.738, 0.707, respectively). elevated HOMER1 revealed combination data. Knocking down inhibited malignant progression Conclusions: a discovered gene, HOMER1, that influences potential become novel therapeutic target.

Language: Английский

Citations

0
New insights into the roles of lactylation in cancer DOI Creative Commons

Yajun Emily Zhu,

Wenhui Liu, Zhiying Luo

et al.

Frontiers in Pharmacology, Journal Year: 2024, Volume and Issue: 15

Published: Oct. 22, 2024

Lactylation, a novel discovered posttranslational modification, is vital component of lactate function and prevalent in wide range cells, interacting with both histone non-histone proteins. Recent studies have confirmed that lactylation as new contributor to epigenetic landscape involved multiple pathological processes. Accumulating evidence reveals exists different pathophysiological states leads inflammation cancer; however, few mechanisms been elaborated. This review summarizes the biological processes roles cancer, well discusses relevant potential therapeutic targets, aiming provide insights for targeted cancer therapy.

Language: Английский

Citations

3
Exploring the molecular landscape of osteosarcoma through PTTG family genes using a detailed multi-level methodology DOI Creative Commons
Yulin Lu,

Danjun Wang,

Gengshuo Chen

et al.

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: July 30, 2024

Osteosarcoma (OS) poses a significant clinical challenge, necessitating comprehensive exploration of its molecular underpinnings.

Language: Английский

Citations

2
Lactate and lactylation in gastrointestinal cancer: Current progress and perspectives (Review) DOI Creative Commons

Yufen He,

Yanbin Huang, Peng Peng

et al.

Oncology Reports, Journal Year: 2024, Volume and Issue: 53(1)

Published: Nov. 8, 2024

Gastrointestinal (GI) cancers, which have notable incidence and mortality, are impacted by metabolic reprogramming, especially the increased production accumulation of lactate. Lactylation, a post‑translational modification driven lactate, is crucial regulator gene expression cellular function in GI cancer. The present review aimed to examine advancements understanding lactate lactylation mechanisms production, its influence on tumor microenvironment clinical implications levels as potential biomarkers were explored. Furthermore, was investigated, including biochemical foundation, primary targets functional outcomes. underscored therapeutic strategies targeting metabolism lactylation. Challenges future directions emphasize innovative cancer improve

Language: Английский

Citations

0