Integration of genomics and transcriptomics highlights the crucial role of chromosome 5 open reading frame 34 in various human malignancies DOI Creative Commons
Yilin Li, Yong Zhang, Dan Sun

et al.

Aging, Journal Year: 2023, Volume and Issue: 15(23), P. 14384 - 14410

Published: Dec. 7, 2023

Although some data suggest that chromosome 5 open reading frame 34 (C5orf34) plays a pivotal part in the onset and disease progression of various cancers, there is no pan-cancer investigation C5orf34 at present. This study sought to establish predictive importance variety human malignancies understand its fundamental immunological function. In our research, we applied combination several bioinformatics techniques basic experiments investigate differential expression C5orf34, relationship with prognosis, methylation, single nucleotide variant, clinical characteristics, microsatellite instability, tumor mutational burden, copy number variation, immune cell infiltration cancers from database publicly available aim identifying potential prognostic markers. this found differed significantly among types, according findings. The level markedly increased majority when compared normal tissues, which correlated an unfavorable prognosis patients. Immunohistochemical staining confirmed findings was remarkably up-regulated gynecologic cancers. Moreover, shown be features also expressed genes code for major suppressors, chemokines, activators, chemokine receptors, histocompatibility complex. Finally, shows has employed as biomarker. it might regulate microenvironment malignancies.

Language: Английский

Single-cell RNA sequencing and immune microenvironment analysis reveal PLOD2-driven malignant transformation in cervical cancer DOI Creative Commons
Zhiheng Lin,

Fengxin Wang,

Renwu Yin

et al.

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

Published: Jan. 7, 2025

Cervical cancer is the fourth most common in women globally, and main cause of disease has been found to be ongoing HPV infection. remains primary cancer-related death despite major improvements screening treatment approaches, especially low- middle-income nations. Therefore, it crucial investigate tumor microenvironment advanced cervical order identify possible targets. In better understand malignant epithelial cells (EPCs), this study used bulk RNA-seq data from UCSC conjunction with single-cell RNA sequencing ArrayExpress database. After putting quality control procedures into place, cell type identification clustering analysis using Seurat software were carried out. To clarify functional pathways, enrichment differential gene expression The CIBERSORT ESTIMATE R packages evaluate immune characteristics, univariate multivariate Cox regression analyses extract prognostic features. Furthermore, assessments drug sensitivity Eight types identified, EPCs showing high proliferative stemness Five EPC subpopulations defined, C1 NNMT+ CAEPCs driving differentiation. A NNMT Risk Score (NCRS) model was developed, revealing a correlation between elevated NCRS scores adverse patient outcomes characterized by evasion. vitro experiments validated that PLOD2 significantly enhances proliferation, migration, invasion cells. This investigation delineated eight five cancer, establishing as therapeutic target. demonstrated its capability, indicating higher are associated poorer clinical outcomes. validation highlights potential, underscoring critical need for integrating immunotherapy targeted strategies enhance diagnostic approaches cancer.

Language: Английский

Citations

9

MAZ-mediated tumor progression and immune evasion in hormone receptor-positive breast cancer: Targeting tumor microenvironment and PCLAF+ subtype-specific therapy DOI
Gaofeng Ni,

Yuwei Sun,

Hongling Jia

et al.

Translational Oncology, Journal Year: 2025, Volume and Issue: 52, P. 102280 - 102280

Published: Jan. 13, 2025

Language: Английский

Citations

7

Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance DOI Creative Commons
Hussein Sabit, Borros Arneth, Timothy M. Pawlik

et al.

Pharmaceuticals, Journal Year: 2025, Volume and Issue: 18(1), P. 75 - 75

Published: Jan. 10, 2025

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of tumor microenvironment (TME), leading important advancements toward a much deeper understanding how heterogeneity contributes cancer progression therapeutic resistance. These are able integrate data from molecular genomic, transcriptomic, proteomics, metabolomics studies cells at resolution scale that give rise full cellular complexity TME. Understanding complex sometimes reciprocal relationships among cells, CAFs, immune ECs has led novel insights into their immense functions, which can consequences on behavior. In-depth uncovered evasion mechanisms, including exhaustion T metabolic reprogramming response hypoxia cells. Single-cell also revealed resistance such as stromal cell-secreted factors physical barriers extracellular matrix. Future examining specific pathways targeting approaches reduce TME will likely lead better outcomes with immunotherapies, drug delivery, etc., for treatments. incorporate data, spatial micro-environments, translation personalized therapies. This review emphasizes provide TME, revealing reprogramming, influences. aim guide development targeted therapies, highlighting role diversity shaping behavior treatment outcomes.

Language: Английский

Citations

6

Deciphering Treg cell roles in esophageal squamous cell carcinoma: a comprehensive prognostic and immunotherapeutic analysis DOI Creative Commons
Pengpeng Zhang, Shiyang Dong, Wei Sun

et al.

Frontiers in Molecular Biosciences, Journal Year: 2023, Volume and Issue: 10

Published: Sept. 28, 2023

Background: Esophageal squamous cell carcinoma (ESCC) is a prevalent and aggressive form of cancer that poses significant challenges in terms prognosis treatment. Regulatory T cells (Treg cells) have gained attention due to their influential role immune modulation within the tumor microenvironment (TME). Understanding intricate interactions between Treg essential for unraveling mechanisms underlying ESCC progression developing effective prognostic models immunotherapeutic strategies. Methods: A combination single-cell RNA sequencing (scRNA-seq) bulk RNA-seq analysis was utilized explore TME ESCC. The accuracy applicability model were assessed through multi-dimensional evaluations, encompassing an examination model's performance across various dimensions, such as mutation landscape, clinical relevance, enrichment analysis, potential implications immunotherapy Results: pivotal macrophage migration inhibitory factor (MIF) signaling pathway investigated, with focus on its impact other subpopulations. Through comprehensive integration data, Treg-associated signature (TAS) constructed, revealing patients elevated TAS (referred high-TAS individuals) experienced significantly improved prognoses. Heightened infiltration increased expression checkpoint markers observed specimens. validity established IMvigor210 dataset, demonstrating robustness predicting responsiveness immunotherapy. therapeutic benefits immune-based interventions patients. Noteworthy differences patterns emerged high low-TAS cohorts, highlighting avenues exploration. Furthermore, relevance key genes substantiated by analyzing samples from ten paired adjacent tissues, differential levels. Conclusion: study enables accurate prediction patient This achievement holds management ESCC, offering valuable insights informed interventions.

Language: Английский

Citations

25

The integrated single-cell analysis developed an immunogenic cell death signature to predict lung adenocarcinoma prognosis and immunotherapy DOI Creative Commons
Pengpeng Zhang, Haotian Zhang, Junjie Tang

et al.

Aging, Journal Year: 2023, Volume and Issue: 15(19), P. 10305 - 10329

Published: Oct. 4, 2023

Background: Research on immunogenic cell death (ICD) in lung adenocarcinoma (LUAD) has been relatively limited. This study aims to create ICD-related signatures for accurate survival prognosis prediction LUAD patients, addressing the challenge of lacking reliable early prognostic indicators this type cancer. Methods: Using single-cell RNA sequencing (scRNA-seq) analysis, ICD activity cells was calculated by AUCell algorithm, divided into high- and low-ICD groups according median values, key regulatory genes were identified through differential these integrated TCGA data construct using LASSO COX regression multi-dimensional analysis terms prognosis, immunotherapy, tumor microenvironment (TME), mutational landscape. Results: The constructed signature reveals a pronounced disparity between low-risk patients. statistical discrepancies times among patients from both GEO databases further corroborate observation. Additionally, heightened levels immune infiltration expression are evidenced group, suggesting potential benefit immunotherapeutic interventions pivotal risk-associated tissue samples assessed utilizing qRT-PCR, thereby unveiling PITX3 as plausible therapeutic target context LUAD. Conclusions: Our provide help predicting immunotherapy some extent guide clinical treatment

Language: Английский

Citations

23

Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response DOI Creative Commons
Shengshan Xu, Youbin Zheng, Min Ye

et al.

BMC Cancer, Journal Year: 2024, Volume and Issue: 24(1)

Published: Aug. 28, 2024

Recent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking.

Language: Английский

Citations

15

Uncovering the immune microenvironment and molecular subtypes of hepatitis B-related liver cirrhosis and developing stable a diagnostic differential model by machine learning and artificial neural networks DOI Creative Commons

Shengke Zhang,

Cheng‐Lu Jiang, Lai Jiang

et al.

Frontiers in Molecular Biosciences, Journal Year: 2023, Volume and Issue: 10

Published: Sept. 22, 2023

Background: Hepatitis B-related liver cirrhosis (HBV-LC) is a common clinical disease that evolves from chronic hepatitis B (CHB). The development of can be suppressed by pharmacological treatment. When CHB progresses to HBV-LC, the patient's quality life decreases dramatically and drug therapy ineffective. Liver transplantation most effective treatment, but lack donor required for transplantation, high cost procedure post-transplant rejection make this method unsuitable patients. Methods: aim study was find potential diagnostic biomarkers associated with HBV-LC bioinformatics analysis classify into specific subtypes consensus clustering. This will provide new perspective early diagnosis, treatment prevention HCC in Two study-relevant datasets, GSE114783 GSE84044, were retrieved GEO database. We screened feature genes using differential analysis, weighted gene co-expression network (WGCNA), three machine learning algorithms including least absolute shrinkage selection operator (LASSO), support vector recursive elimination (SVM-RFE), random forest (RF) total five methods. After that, we constructed an artificial neural (ANN) model. A cohort consisting GSE123932, GSE121248 GSE119322 used external validation. To better predict risk development, also built nomogram And multiple enrichment analyses samples performed understand biological processes which they significantly enriched. different analyzed Immune infiltration approach. Results: Using data downloaded GEO, developed ANN model based on six genes. clustering classified them two subtypes, C1 C2, it hypothesized patients subtype C2 might have milder symptoms immune analysis. Conclusion: column line graphs showed excellent predictive power, providing diagnosis possible HBV-LC. delineation facilitate future

Language: Английский

Citations

18

Association of the Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) score with immune checkpoint inhibitor efficacy in patients with gastrointestinal and lung cancer DOI Creative Commons
Hao Jiang, Borui Li, Min Wu

et al.

BMC Cancer, Journal Year: 2024, Volume and Issue: 24(1)

Published: April 8, 2024

Abstract Objective This study aimed to conduct a comprehensive analysis, evaluating the prognostic significance of baseline Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) Score in patients undergoing immune checkpoint inhibitor (ICI) therapy. Methods A search was performed across various databases, including PubMed, Cochrane Library, EMBASE, Google Scholar, until October 21, 2023, compile relevant articles for analysis. The investigation encompassed diverse clinical outcomes, overall survival (OS) progression-free (PFS). Results analysis included total 15 articles, comprising 19 studies involving 3335 patients. Among studies, nine focused on NSCLC, six were conducted HCC. Pooled results revealed that with elevated ALI levels experienced prolonged OS (HR: 0.51, 95% CI: 0.37–0.70, p < 0.001) extended PFS 0.61, 0.52–0.72, 0.001). Furthermore, GRIm score > 1 associated reduced 2.07, 1.47–2.92, diminished 1.78, 1.35–2.34, cancer receiving ICIs. Subgroup indicated cutoff values 18 exhibited enhanced predictive potential. Additionally, HCC patients, those HCC-GRIm 2 showed substantially decreased risk mortality compared individuals ≤ 2.63, 1.89–3.65, Conclusion served as dependable indicators ICI therapy context treatment.

Language: Английский

Citations

4

Characterization of NOD-like receptor-based molecular heterogeneity in glioma and its association with immune micro-environment and metabolism reprogramming DOI Creative Commons

Chun-Lin Lu,

Haochuan Ma, Jie Wang

et al.

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

Published: Jan. 15, 2025

The characteristics and role of NOD-like receptor (NLR) signaling pathway in high-grade gliomas were still unclear. This study aimed to reveal the association NLR with clinical heterogeneity glioblastoma (GBM) patients, explore hub genes occurrence development GBM. Transcriptomic data from 496 GBM patients complete prognostic information obtained TCGA, GEO, CGGA databases. Using NMF clustering algorithm expression profiles genes, these classified into different subtypes. activity immune micro-environment then compared between A novel accurate profile-based marker for was developed using LASSO COX regression analysis. Based on gene profile, accurately divided two subtypes (C1 C2) outcomes. groups showed microenvironment metabolic characteristics, which might be potential reason difference prognosis. Differential enrichment analyzes revealed intrinsic signature differences C1 C2 differential C2, molecular markers related developed. AUC value 3-year ROC curve ranged 0.601 0.846, suggesting its significance. Single-cell sequencing analysis that mainly active myeloid cells within random forest identified crucial TRIP6 pathway. Molecular biology experiments confirmed abnormally overexpressed Knockdown can significantly inhibit proliferation migration ability cells. plays a critical regulating metabolism reprogramming is affects malignant biological behavior

Language: Английский

Citations

0

Molecular characteristics and prognostic significances of lysosomal-dependent cell death in kidney renal clear cell carcinoma DOI Creative Commons

Shunliang He,

Jiaao Sun,

Hewen Guan

et al.

Aging, Journal Year: 2024, Volume and Issue: unknown

Published: March 7, 2024

Lysosomal-dependent cell death (LDCD) has an excellent therapeutic effect on apoptosis-resistant and drug-resistant tumors; however, the important role of LDCD-related genes (LDCD-RGs) in kidney renal clear carcinoma (KIRC) not been reported. Initially, single-cell atlas LDCD signal KIRC was comprehensively depicted. We also emphasized molecular characteristics LDCD-RGs various human neoplasms. Predicated upon expressive quotients LDCD-RGs, we stratified patients into tripartite cohorts denoted as C1, C2, C3. Those allocated to ambit C1 evinced most sanguine prognosis within cohort, underscored by acme scores. This further confirms significant that play both pathophysiological foundation clinical implications KIRC. In culmination, virtue employing LASSO-Cox analytical modality, have ushered innovative avant-garde prognostic framework tailored for KIRC, predicated bedrock LDCD-RGs. The assemblage instances arbitrarily apportioned constituents inclusive a didactic internally wielded validation cadre, externally administered cohort. Concurrently, were dichotomized strata connoting elevated jeopardy synonymous with adverse trajectories, conversely, diminished risk tantamount favorable prognoses, contingent calibrated expressions Succinctly, our investigative findings serve underscore cardinal capacity harbored milieu, concurrently birthing pioneering schema intrinsically linked trajectory its attendant prognoses.

Language: Английский

Citations

2