A prognostic gene signature based on focal adhesion related genes for gliomas and identification of the role of RAP1B in glioma progression DOI Creative Commons
Ning Wang, Haoyu Zhou, Tianze Wang

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 18, 2023

Abstract Background The most common malignant primary brain tumor in adults is the gliomas, characterized by extremely variable overall survival (OS) for patients. Although it has been found that focal adhesion genes are associated with clinical prognosis glioma patients, this marker rarely used clinically. Methods We systematically mRNA expression of related gliomas and explored their signature based on 938 samples from TCGA dataset CGGA dataset. Glioma were clustered using an unsupervised clustering method. Subsequently, prognosis-associated genes, gene (FARGS) was constructed least absolute shrinkage selection operator (LASSO) Cox regression. Additionally, multiple bioinformatics methods to examine value FARGS predicting patient outcomes, features, oncogenic pathways, immune microenvironment drug response. Furthermore, vitro vivo experiments conducted validate role RAP1B U87 cells. Results According LASSO regression analysis, a 9-FARG be strongly linked OS high-risk low-risk score pattern. tightly molecular biomarkers, including IDH wild-type, unmethylated MGMTp, non-codeletion 1p19q. group exhibited enrichment biological pathways. Interestingly, results presented strong association therapeutic response immunosuppressive infiltrations M2-type macrophages, MDSCs Tregs, elevated immunosuppressors’ expression. Lastly, cells also functionally confirmed. Conclusions In conclusion, we reported novel promising prediction as well confirmation RAP1B's role.

Language: Английский

Deciphering glycosylation-driven prognostic insights and therapeutic prospects in glioblastoma through a comprehensive regulatory model DOI Creative Commons
Xingyi Jin, Zhuo Chen, Hang Zhao

et al.

Frontiers in Oncology, Journal Year: 2024, Volume and Issue: 14

Published: May 22, 2024

The oncogenesis and development of glioblastoma multiforme have been linked to glycosylation modifications, which are common post-translational protein modifications. Abnormal glycosyltransferase leads irregular patterns, hold clinical significance for GB prognosis. By utilizing both single-cell bulk data, we developed a scoring system assess levels in GB. Moreover, glycosylation-based signature was created predict outcomes therapy responsiveness. study led the an glyco-model incorporating nine key genes. This risk assessment tool effectively stratified patients into two distinct groups. Extensive validation through ROC analysis, RMST, Kaplan-Meier (KM) survival analysis emphasized model’s robust predictive capabilities. Additionally, nomogram constructed rates at specific time intervals. research revealed substantial disparities immune cell infiltration between low-risk high-risk groups, characterized by differences abundance elevated scores. Notably, predicted diverse responses checkpoint inhibitors drug therapies, with groups exhibiting preference demonstrated superior treatments. Furthermore, identified potential targets utilized Connectivity Map pinpoint promising therapeutic agents. Clofarabine YM155 were as potent candidates treatment Our well-crafted discriminates calculating score, accurately predicting outcomes, significantly enhancing prognostic while identifying novel immunotherapeutic chemotherapeutic strategies treatment.

Language: Английский

Citations

1
A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma DOI Creative Commons
Mingjie Lin,

Xiu-Xiao Tang,

G YAO

et al.

Frontiers in Pharmacology, Journal Year: 2023, Volume and Issue: 14

Published: March 20, 2023

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type malignancies, which affected by chemokines. Chemokines can form a local network to regulate movement immune cells and are essential for tumor proliferation metastasis as well interaction between mesenchymal cells. Establishing chemokine genes signature assess prognosis therapy responsiveness in ccRCC goal this effort. Methods: mRNA sequencing data clinicopathological on 526 individuals with were gathered from The Cancer Genome Atlas database investigation (263 training group samples 263 validation samples). Utilizing LASSO algorithm conjunction univariate Cox analysis, gene was constructed. Gene Expression Omnibus (GEO) provided single RNA (scRNA-seq) data, R package “Seurat” applied analyze scRNA-seq data. In addition, enrichment scores 28 microenvironment (TME) calculated using “ssGSEA” algorithm. order develop possible medications patients high-risk ccRCC, “pRRophetic” employed. Results: High-risk had lower overall survival model predicting prognosis, supported cohort. both cohorts, it served an independent prognostic factor. Annotation predicted signature’s biological function revealed that correlated immune-related pathways, riskscore positively infiltration several checkpoints (ICs), including CD47, PDCD1, TIGIT, LAG-3, while negatively TNFRSF14. CXCL2, CXCL12, CX3CL1 shown be significantly expressed monocytes cancer cells, according analysis. Furthermore, high expression CD47 suggested us could promising checkpoint. For who riskscore, we 12 potential medications. Conclusion: Overall, our findings show putative 7-chemokine-gene might predict patient’s reflect disease’s complicated immunological environment. Additionally, offers suggestions how treat precision treatment focused risk assessment.

Language: Английский

Citations

2
Hepatocellular Carcinoma Subtyping and Prognostic Model Construction Based on Chemokine-Related Genes DOI Creative Commons
Qiusheng Guo,

Yangyang Huang,

Xiaoan Zhan

et al.

Medical Principles and Practice, Journal Year: 2023, Volume and Issue: 32(6), P. 332 - 342

Published: Jan. 1, 2023

Background: Chemokines not only regulate immune cells but also play significant roles in development and treatment of tumors patient prognoses. However, these effects have been fully explained hepatocellular carcinoma (HCC). Materials Methods: We conducted a clustering analysis chemokine-related genes. then examined the differences survival rates analyzed levels using single-sample Gene Set Enrichment Analysis (ssGSEA) for each subtype. Based on genes different subtypes, we built prognostic model The Cancer Genome Atlas (TCGA) dataset package glmnet validated it Expression Omnibus (GEO) dataset. used univariate multivariate regression analyses to select independent factors R rms draw nomogram reflecting at 1, 3, 5 years. Results: identified two chemokine subtypes and, after screening, found that Cluster1 had higher than Cluster2. In addition, terms evaluation, stromal ESTIMATE abundance, function, expressions various checkpoints, were significantly better those immunophenoscore (IPS) HCC patients was Furthermore, established consisting 9 genes, which correlated with chemokines. Through testing, Riskscore revealed as an factor, could effectively predict patients’ prognoses both TCGA GEO datasets. Conclusion: This study resulted novel related providing new targets theoretical support patients.

Language: Английский

Citations

2
Immune landscape-based machine-learning–assisted subclassification, prognosis, and immunotherapy prediction for glioblastoma DOI Creative Commons

Haiyan Li,

Jian He, Menglong Li

et al.

Frontiers in Immunology, Journal Year: 2022, Volume and Issue: 13

Published: Dec. 1, 2022

As a malignant brain tumor, glioblastoma (GBM) is characterized by intratumor heterogeneity, worse prognosis, and highly invasive, lethal, refractory natures. Immunotherapy has been becoming promising strategy to treat diverse cancers. It known that there are heterogeneous immunosuppressive microenvironments among different GBM molecular subtypes mainly include classical (CL), mesenchymal (MES), proneural (PN), respectively. Therefore, an in-depth understanding of immune landscapes them essential for identifying novel markers GBM.In the present study, based on collecting largest number 109 signatures, we aim achieve precise diagnosis, immunotherapy prediction performing comprehensive immunogenomic analysis. Firstly, machine-learning (ML) methods were proposed evaluate diagnostic values these optimal classifier was constructed accurate recognition three with robust performance. The prognostic signatures then confirmed, risk score established divide all patients into high-, medium-, low-risk groups high predictive accuracy overall survival (OS). complete differential analysis across performed in terms characteristics along clinicopathological features, which indicates MES shows much higher heterogeneity compared CL PN but significantly better responses, although may have microenvironment be more proinflammatory invasive. Finally, subtype proved sensitive 17-AAG, docetaxel, erlotinib using drug sensitivity compounds AS-703026, PD-0325901, MEK1-2-inhibitor might potential therapeutic agents.Overall, findings this research could help enhance our tumor provide new insights improving prognosis patients.

Language: Английский

Citations

4
Anoikis patterns via machine learning strategy and experimental verification exhibit distinct prognostic and immune landscapes in melanoma DOI
Jinfang Liu, Rong Ma, Siyuan Chen

et al.

Clinical & Translational Oncology, Journal Year: 2023, Volume and Issue: 26(5), P. 1170 - 1186

Published: Nov. 21, 2023

Language: Английский

Citations

2
Potent predictive CpG signature for temozolomide response in non-glioma-CpG island methylator phenotype glioblastomas with methylated MGMT promoter DOI
Jiu Wang, Meng Zhang, Yifeng Liu

et al.

Epigenomics, Journal Year: 2022, Volume and Issue: 14(20), P. 1233 - 1247

Published: Oct. 1, 2022

Aim: We aimed to identify potent CpG signatures predicting temozolomide (TMZ) response in glioblastomas (GBMs) that do not have the glioma-CpG island methylator phenotype (G-CIMP) but a methylated promoter of MGMT (meMGMT). Materials & methods: Different datasets non-G-CIMP meMGMT GBMs with molecular and clinical data were analyzed. Results: A panel 77 TMZ efficacy-related CpGs seven-CpG risk signature identified validated for distinguishing differential outcomes radiotherapy plus versus alone GBMs. An integrated classification scheme was also proposed refining MGMT-based TMZ-guiding approach all G-CIMP-GBMs. Conclusion: The may serve as promising predictive biomarker candidates guiding optimal usage GBMs.Glioblastomas gene (meMGMT) show considerable variability their (TMZ). Powerful biomarkers provide information on decision-making can be clinically useful. This study has glioblastomas. is

Language: Английский

Citations

3
Exploring the tumor microenvironment: Chemokine‐related genes and immunotherapy/chemotherapy response in clear‐cell renal cell carcinoma DOI

Yuhao Meng,

Chen Zhang,

Tongfei Fu

et al.

Environmental Toxicology, Journal Year: 2024, Volume and Issue: unknown

Published: March 15, 2024

Abstract Background The treatment of clear‐cell renal cell carcinoma (ccRCC) remains challenge. Chemokines laid impact on the proliferation and metastasis cancer cells. objective was to identify chemokine‐related genes construct a prognostic model for ccRCC. Methods Bulk transcriptomic data ( n = 531), single‐cell RNA sequencing (scRNA‐seq) dataset GSE159115, other validation cohorts were acquired from Cancer Genome Atlas Program (TCGA) GEO databases. All clustering analysis conducted by Seurat R package. Gene set enrichment (GSEA), immune infiltration analysis, single nucleotide variations (SNV) predictive response immunotherapy/chemotherapy conducted. 786‐O A498 lines cultured applied into CCK‐8, Western blot, RT‐qPCR kits. Results Univariate Cox used screen out related survival. ZIC2, SMIM24, COL7A1, IGF2BP3, ITPKA, ADAMTS14, CYP3A7, AURKB identified construction model. High‐risk group had poorer prognosis than low‐risk in each dataset. Memory CD8+ T cells, macrophages, memory B cells higher high‐risk group, while content basophils group. Bortezomib_1191, Dactinomycin_1911, Docetaxel_1007, Daporinad_1248 more sensitive groups groups. Moreover, we found that IGF2BP3 significantly elevated both resistance sunitinib. Knockdown markedly reduced ccRCC migration viability. Conclusion Our study has yielded novel based comprehensive transcriptional atlas patients, shedding light significant tumor microenvironment biology immunotherapy We as pivotal regulator regulating

Language: Английский

Citations

0
Construction and validation of cell cycle-related prognostic genetic model for glioblastoma DOI Creative Commons

Runpeng Zhou,

Kai Zhang, Tingting Dai

et al.

Medicine, Journal Year: 2024, Volume and Issue: 103(40), P. e39205 - e39205

Published: Oct. 4, 2024

Glioblastoma (GBM) is a common primary malignant brain tumor and the prognosis of these patients remains poor. Therefore, further understanding cell cycle-related molecular mechanisms GBM identification appropriate prognostic markers therapeutic targets are key research imperatives. Based on RNA-seq expression datasets from The Cancer Genome Atlas database, prognosis-related biological processes in were screened out. Gene Set Variation Analysis (GSVA), LASSO-COX, univariate multivariate Cox regression analyses, Kaplan–Meier survival analysis, Pearson correlation analysis performed for constructing predictive model. A total 58 genes identified by GSVA differential between control samples. By LASSO 8 as biomarkers GBM. nomogram with superior performance to predict was established regarding risk score, cancer status, recurrence type, mRNAsi. This study revealed value In addition, we constructed reliable model predicting patients. Our findings reinforce relationship cycle may help improve assessment model, based independent factors, enables tailored treatment strategies It particularly useful subgroups uncertain or challenges.

Language: Английский

Citations

0
Biomarkers of immunotherapy in glioblastoma DOI
William Savage, Mitchell D. Yeary, A T'Ang

et al.

Neuro-Oncology Practice, Journal Year: 2024, Volume and Issue: 11(4), P. 383 - 394

Published: April 1, 2024

Abstract Glioblastoma (GBM) is the most common primary brain cancer, comprising half of all malignant tumors. Patients with GBM have a poor prognosis, median survival 14–15 months. Current therapies for GBM, including chemotherapy, radiotherapy, and surgical resection, remain inadequate. Novel are required to extend patient survival. Although immunotherapy has shown promise in other cancers, melanoma non-small lung its efficacy been limited subsets patients. Identifying biomarkers response could help stratify patients, identify new therapeutic targets, develop more effective treatments. This article reviews existing emerging clinical GBM. The scope this review includes immune checkpoint inhibitor antitumoral vaccination approaches, summarizing variety molecular, cellular, computational methodologies that explored setting anti-GBM immunotherapies.

Language: Английский

Citations

0
Prognostic impact of sodium fluorescein-guided microsurgery on cognitive function, neuropeptide dynamics, and short-term outcomes in brain glioma patients DOI Open Access

Yafu Tan

American Journal of Cancer Research, Journal Year: 2024, Volume and Issue: 14(4), P. 1880 - 1891

Published: Jan. 1, 2024

This study conducted a retrospective analysis on 107 brain glioma patients treated from January 2018 to February 2020 assess the impact of sodium fluorescein-guided microsurgery postoperative cognitive function and short-term outcomes. Patients were divided into two groups: control group (n=50 patients) undergoing routine surgery research (n=57 receiving microsurgery. The compared total resection rates, changes in scores, neuropeptide levels cerebrospinal fluid between groups. findings revealed that experienced shorter surgical time hospitalization duration, reduced blood loss, higher rates group. Furthermore, demonstrated improvements scores an increase after surgery. There was no significant difference comparison incidence complications WHO classification preoperative performance independent prognostic factors for evaluation 3-year survival, highlighting clinical significance improving quality life functions without compromising their long-term survival

Language: Английский

Citations

0