Background: Colorectal cancer (CRC) has been divided into 4 consensus molecular subtypes (CMSs), of which CMS4 has the mesenchymal identity and the highest relapse rate. Our goal is to develop a prognostic signature by integrating the immune system and mesenchymal modalities involved in CMS4.
Methods: The gene expression profiles collected from 5 public datasets were applied to this study, including 1280 samples totally. Network analysis was applied to integrate the mesenchymal modalities and immune signature to establish an immune-based prognostic signature for CRC (IPSCRC).
Results: We identified 6 immune genes as key factors of CMS4 and established the IPSCRC. The IPSCRC could significantly divide patients into high- and low- risk groups in terms of relapse-free survival (RFS) and overall survival (OS) and in discovery (RFS: P < .0001) and 4 independent validation sets (RFS range: P = .01 to <.0001; OS range: P = .02-.0004). After stage stratification, the IPSCRC could still distinguish poor prognosis patients in discovery (RFS: P = .04) and validation cohorts (RFS range: P = .04-.007) within stage II in terms of RFS. Further, in multivariate analysis, the IPSCRC remained an independent predictor of prognosis. Moreover, Macrophage M2 was significantly enriched in the high-risk group, while plasma cells enriched in the low-risk group.
Conclusion: We propose an immune-based signature identified by network analysis, which is a promising prognostic biomarker and help for the selection of CRC patients who might benefit from more rigorous therapies. Further prospective studies are warranted to test and validate its efficiency for clinical application.
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http://dx.doi.org/10.1097/MD.0000000000020617 | DOI Listing |
Cancer Med
January 2025
Department of Pharmacology, College of Pharmacy, Jinan University, Guangzhou, China.
Background: Distinctive heterogeneity characterizes diffuse large B-cell lymphoma (DLBCL), one of the most frequent types of non-Hodgkin's lymphoma. Mitochondria have been demonstrated to be closely involved in tumorigenesis and progression, particularly in DLBCL.
Objective: The purposes of this study were to identify the prognostic mitochondria-related genes (MRGs) in DLBCL, and to develop a risk model based on MRGs and machine learning algorithms.
Heliyon
January 2025
Department of Orthopedics Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background: T cell receptor (TCR) signaling pathway is closely related to tumor progress and immunotherapy. This study aimed to explore the clinical significance, prognosis, immune infiltration and chemotherapy sensitivity of TCR in osteosarcoma (OS).
Material And Methods: OS data were obtained from TARGET and GEO database.
EJIFCC
December 2024
Department of Radiotherapy, All India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, 273008, India.
The article provides a thorough and up-to-date analysis of the role that microRNAs (miRNAs) within the realm of cancer therapy, paying specific attention to their diagnostic, prognostic as well as therapeutic capabilities. The miRNAs (small non-coding RNAs) are the current major genes that regulate gene expression. They are a key factor in the genesis of cancer.
View Article and Find Full Text PDFClin Transl Med
January 2025
Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Thyroid cancer is one of the most common endocrine tumors worldwide, especially among women and the metastatic mechanism of papillary thyroid carcinoma remains poorly understood.
Methods: Thyroid cancer tissue samples were obtained for single-cell RNA-sequencing and spatial transcriptomics, aiming to intratumoral and antimetastatic heterogeneity of advanced PTC. The functions of APOE in PTC cell proliferation and invasion were confirmed through in vivo and in vitro assays.
Cancer Cell Int
January 2025
Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510080, China.
Background: Patients with lung adenocarcinoma (LUAD) receiving drug treatment often have an unpredictive response and there is a lack of effective methods to predict treatment outcome for patients. Dendritic cells (DCs) play a significant role in the tumor microenvironment and the DCs-related gene signature may be used to predict treatment outcome. Here, we screened for DC-related genes to construct a prognostic signature to predict prognosis and response to immunotherapy in LUAD patients.
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