Lung Cancer, Journal Year: 2024, Volume and Issue: 199, P. 108071 - 108071
Published: Dec. 22, 2024
Recent advances in the subclassification of small cell lung carcinomas (SCLCs) may help to overcome unmet need for targeted therapies and improve survival. However, limited information is available on how expression subtype markers changes during tumour progression. Our study aimed compare these primary brain metastatic SCLCs.
Language: Английский
Advanced Science, Journal Year: 2024, Volume and Issue: 11(31)
Published: June 19, 2024
Abstract Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis susceptible to treatment resistance recurrence. Understanding the intra‐tumoral spatial heterogeneity in SCLC crucial for improving patient outcomes clinically relevant subtyping. In this study, whole transcriptome‐wide analysis of 25 patients at sub‐histological resolution using GeoMx Digital Spatial Profiling technology performed. This deciphered multi‐regional heterogeneity, distinct molecular profiles, biological functions, immune features, subtypes within spatially localized histological regions. Connections between different transcript‐defined phenotypes their impact on survival therapeutic response are also established. Finally, gene signature, termed ITHtyper, based prevalence levels, which enables risk stratification from bulk RNA‐seq profiles identified. The prognostic value ITHtyper rigorously validated independent multicenter cohorts. study introduces preliminary tumor‐centric, regionally targeted transcriptome resource that sheds light previously unexplored SCLC. These findings hold promise improve tumor reclassification facilitate development personalized treatments patients.
Language: Английский
Citations
9
Biomarkers, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 16
Published: Jan. 31, 2025
Background Lung cancer is a primary global health concern, responsible for considerable portion of cancer-related fatalities worldwide. Understanding its molecular complexities crucial identifying potential targets treatment. The goal to slow disease progression and intervene early prevent the development advanced lung cases. Hence, there's an urgent need new biomarkers that can detect in stages. Methods: study conducted RNA-Seq analysis samples from publicly available SRA database (NCBI SRP009408), including both control tumour samples. genes with differential expression between healthy tissues were identified using R Bioconductor. Machine learning (ML) techniques, Random Forest, Lasso, XGBoost, Gradient Boosting, Elastic Net employed pinpoint significant followed by classifiers, Multilayer Perceptron (MLP), Support Vector Machines (SVM), k-Nearest Neighbors (k-NN). Gene ontology pathway analyses performed on differentially expressed (DEGs). top DEG machine combined protein-protein interaction (PPI) analysis, 10 hub essential progression. Results: integrated ML DEGs revealed significance specific samples, five upregulated (COL11A1, TOP2A, SULF1, DIO2, MIR196A2) downregulated (PDK4, FOSB, FLYWCH1, CYB5D2, MIR328), along their associated implicated pathways or co-expression networks identified. Among various algorithms employed, Forest XGBoost proved effective common genes, underscoring pathogenesis. MLP exhibited highest accuracy classifying all genes. Additionally, are pivotal pathogenesis: COL1A1, SOX2, SPP1, THBS2, POSTN, COL5A1, COL11A1, TIMP1, PKP1.
Language: Английский
Citations
1
Indian Journal of Surgical Oncology, Journal Year: 2024, Volume and Issue: 16(1), P. 257 - 278
Published: Sept. 5, 2024
Language: Английский
Citations
7
The Journal of Pathology Clinical Research, Journal Year: 2025, Volume and Issue: 11(2)
Published: Feb. 25, 2025
Abstract Papillary thyroid carcinoma (PTC) is one of the most common endocrine malignancies, with varying levels risk and clinical behavior. A better understanding molecular characteristics could improve diagnosis assessment. In this study, we performed whole transcriptomic sequencing on 113 PTC cases, including 70 high‐risk 43 low‐risk Chinese patients. Comparative transcriptional profiling analysis revealed two functionally distinct patterns gene dysregulation between subtypes. Low‐risk PTCs showed significant upregulation immune‐related genes increased immune cell infiltration, whereas presented extensive alterations in expression activation oncogenic signaling pathways. Additionally, developed a 31‐gene signature (PTCrisk) for differentiating from PTCs, which was validated across both in‐house external multicenter cohorts. PTCrisk scores were positively correlated key clinicopathological features, tumor size, lymph node metastasis, TNM stage, BRAF mutation status. Overall, our study provides further insights into stratification may contribute to development personalized therapeutic strategies
Language: Английский
Citations
0
Research, Journal Year: 2025, Volume and Issue: 8
Published: Jan. 1, 2025
High-grade lung neuroendocrine carcinomas (Lu-NECs) are clinically refractory malignancies with poor prognosis and limited therapeutic advances. The biological molecular features underlying the histological heterogeneity of Lu-NECs not fully understood. In this study, we present a multi-omics integration whole-exome sequencing deep proteomic profiling in 93 Chinese to establish first comprehensive proteogenomic atlas disease spectrum. Our analyses revealed high degree mutational concordance among subtypes at genomic level; however, distinct profiles enabled clear differentiation subtypes, unveiling subtype-specific related tumor metabolism, immunity, proliferation. Furthermore, RB1 mutations confer divergent prognostic effects through cis- trans- regulation. addition, identified potential protein biomarkers for subtype classification risk stratification, which were validated by immunohistochemistry an independent cohort. This study provides valuable resource insight into Lu-NEC heterogeneity.
Language: Английский
Citations
0
Molecules, Journal Year: 2025, Volume and Issue: 30(8), P. 1731 - 1731
Published: April 12, 2025
Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid progression, early metastasis, and high recurrence rates. Historically considered homogeneous disease, recent multi-omic studies have revealed distinct molecular subtypes driven lineage-defining transcription factors, including ASCL1, NEUROD1, POU2F3, YAP1, as well an inflamed subtype (SCLC-I). These exhibit unique therapeutic vulnerabilities, thereby paving the way for precision medicine targeted therapies. Despite advances in classification, tumor heterogeneity, plasticity, therapy resistance continue to hinder clinical success treating SCLC patients. To this end, novel strategies are being explored, BCL2 inhibitors, DLL3-targeting agents, Aurora kinase PARP epigenetic modulators. Additionally, immune checkpoint inhibitors (ICIs) show promise, particularly immune-enriched of Hence, deeper understanding characteristics, evolution, regulatory mechanisms subtype-specific factors crucial rationally optimizing therapy. This knowledge not only facilitates identification targets, but also provides foundation overcoming developing personalized combination treatment strategies. In future, integration data, dynamic monitoring, approaches expected further advance translation therapies, ultimately improving patient survival outcomes.
Language: Английский
Citations
0
MedComm, Journal Year: 2024, Volume and Issue: 5(10)
Published: Oct. 1, 2024
The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed last few years. However, harnessing power biology streamlining an array ST tools to achieve designated research goals are fundamental require real-world experiences. We present a review by updating technical scope across different principal basis timeline manner hinting on generally adopted techniques used within community. also current progress bioinformatic propose pipelined workflow toolbox available for data exploration. With particular interests tumor microenvironment where is broadly utilized, we summarize up-to-date made via ST-based technologies narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) multiple cancer types their ways deploying through ST. updated offers guidance forward-looking viewpoints endorsed many high-resolution utilized disentangle biological questions that may lead clinical significance future.
Language: Английский
Citations
2
Current Opinion in Oncology, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 4, 2024
This review aims to provide an overview of recent advances in immunotherapy for small cell lung cancer (SCLC), with a focus on the current status immune checkpoint inhibitors (ICIs), novel combination strategies, and key biomarkers.
Language: Английский
Citations
2
Lung Cancer, Journal Year: 2024, Volume and Issue: 199, P. 108071 - 108071
Published: Dec. 22, 2024
Recent advances in the subclassification of small cell lung carcinomas (SCLCs) may help to overcome unmet need for targeted therapies and improve survival. However, limited information is available on how expression subtype markers changes during tumour progression. Our study aimed compare these primary brain metastatic SCLCs.
Language: Английский
Citations
0