Anoikis-related PLCB4 is linked to immunotherapy response in osteosarcoma

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 22, 2025

Osteosarcoma, the most common primary bone malignancy, poses significant management challenges due to its aggressiveness and metastatic potential. This study investigates role of anoikis-related genes, particularly phospholipase C beta 4 (PLCB4), as a prognostic biomarker in osteosarcoma. We analyzed transcriptome data from TARGET GSE21257 cohorts using bioinformatics tools, identifying 15 with PLCB4 key marker linked decreased survival. Our findings indicate negative correlation between immune microenvironment scores checkpoint molecules, suggesting impact on immunotherapy responses. Drug sensitivity analyses revealed that high expression correlates lower IC50 values for several chemotherapeutic agents. In vitro experiments showed silencing inhibited cell proliferation reduced PD-L1 expression. underscores critical osteosarcoma progression potential therapeutic target, offering insights into molecular mechanisms biology improving accuracy treatment strategies.

Language: Английский

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Dexmedetomidine attenuates acute stress-impaired learning and memory in mice by maintaining the homeostasis of intestinal flora

European journal of medical research, Journal Year: 2024, Volume and Issue: 29(1)

Published: May 6, 2024

Abstract Dexmedetomidine (Dex) has been used in surgery to improve patients' postoperative cognitive function. However, the role of Dex stress-induced anxiety-like behaviors and impairment is still unclear. In this study, we tested behavior induced by acute restrictive stress analyzed alterations intestinal flora explore possible mechanism. Behavioral tests, including open field test, elevated plus-maze novel object recognition Barnes maze were performed. Intestinal gut Microbe 16S rRNA sequencing was analyzed. We found that intraperitoneal injection significantly improved behavior, recognition, memory impairment. After habituation environment, mice (male, 8 weeks, 18–23 g) randomly divided into a control group (control, N = 10), dexmedetomidine (Dex, AS with normal saline (AS + NS, 10) Dex, 10). By analysis flora, caused disorder mice. intervention changed composition mice, stabilized ecology increased levels Blautia (A genus anaerobic bacteria) Coprobacillus . These findings suggest attenuates stress-impaired learning maintaining homeostasis flora.

Language: Английский

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Artificial Intelligence and Omics in Malignant Gliomas

Physiological Genomics, Journal Year: 2024, Volume and Issue: 56(12), P. 876 - 895

Published: Oct. 22, 2024

Glioblastoma multiforme (GBM) is one of the most common and aggressive type malignant glioma with an average survival time 12–18 mo. Despite utilization extensive surgical resections using cutting-edge neuroimaging, advanced chemotherapy radiotherapy, prognosis remains unfavorable. The heterogeneity GBM presence blood-brain barrier further complicate therapeutic process. It crucial to adopt a multifaceted approach in research understand its biology advance toward effective treatments. In particular, omics research, which primarily includes genomics, transcriptomics, proteomics, epigenomics, helps us how develops, finds biomarkers, discovers new targets. availability large-scale multiomics data requires development computational models infer valuable biological insights for implementation precision medicine. Artificial intelligence (AI) refers host algorithms that becoming major tool capable integrating large databases. Although application AI tools GBM-omics currently early stages, thorough exploration uncover different aspects (subtype classification, prognosis, survival) would have significant impact on both researchers clinicians. Here, we aim review provide database resources AI-based techniques been used study pathogenesis over past decade. We summarize types GBM-related can be develop models. Furthermore, explore various developed either individual or integrated data, highlighting their applications limitations context advancing treatment.

Language: Английский

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From Genomic Exploration to Personalized Treatment: Next-Generation Sequencing in Oncology

Current Issues in Molecular Biology, Journal Year: 2024, Volume and Issue: 46(11), P. 12527 - 12549

Published: Nov. 6, 2024

Next-generation sequencing (NGS) has revolutionized personalized oncology care by providing exceptional insights into the complex genomic landscape. NGS offers comprehensive cancer profiling, which enables clinicians and researchers to better understand molecular basis of tailor treatment strategies accordingly. Targeted therapies based on alterations identified through have shown promise in improving patient outcomes across various types, circumventing resistance mechanisms enhancing efficacy. Moreover, facilitates identification predictive biomarkers prognostic indicators, aiding stratification approaches. By uncovering driver mutations actionable alterations, empowers make informed decisions regarding selection management. However, full potential can only be realized bioinformatics analyses. Bioinformatics plays a crucial role processing raw data, identifying clinically relevant variants, interpreting landscapes. This review investigates diverse techniques, including whole-genome (WGS), whole-exome (WES), single-cell RNA (sc-RNA-Seq), elucidating their roles understanding genomic/transcriptomic landscape cancer. Furthermore, explores integration data with tools facilitate approaches, from tumor heterogeneity predicting therapeutic responses. Challenges future directions NGS-based research are also discussed, underscoring transformative impact these technologies diagnosis, management, strategies.

Language: Английский

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Immune infiltration and clinical significance analyses of the cancer‐associated fibroblast‐related signature in skin cutaneous melanoma

The Journal of Gene Medicine, Journal Year: 2023, Volume and Issue: 26(1)

Published: Oct. 17, 2023

Abstract Background Skin cutaneous melanoma (SKCM) is one of the most aggressive cancers with high mortality rates. Cancer‐associated fibroblasts (CAFs) play essential roles in tumor growth, metastasis and establishment a pro‐tumor microenvironment. This study aimed to establish CAF‐related signature for providing new perspective indicating prognosis guiding therapeutic regimens SKCM patients. Methods In this study, genes were screened out based on melanoma‐associated fibroblast markers identified from single‐cell transcriptome analysis Gene Expression Omnibus (GEO) database module weighted gene co‐expression using The Cancer Genome Atlas (TCGA) dataset. We extracted these expression data samples TCGA constructed prognostic signature. prediction abilities survival prognosis, immune landscape responses chemo‐/immunotherapies evaluated TCGA‐SKCM cohort. Results suggested that CAFs significantly involved clinical outcomes SKCM. A 10‐gene model was constructed, high‐CAF risk group exhibited immunosuppressive features worse prognosis. Patients CAF score more likely not respond checkpoint inhibitors but sensitive some chemotherapeutic agents, suggesting potential approach chemotherapy/anti‐CAF combination treatment improve patient response rate current immunotherapies. Conclusions could serve as robust indicator personal assessment uncover degree immunosuppression provide strategies decision‐making

Language: Английский

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