Mutational and Transcriptional Characterization Establishes Prognostic Models for Resectable Lung Squamous Cell Carcinoma

Liu, Yinqiang; Duan, Jian; Zhang, Fujun; Liu, Fanghao; Luo, Xiaoyu; Shi, Yunfei; Lei, Youming

doi:10.2147/cmar.s384918

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…The relationship between TENM3 and neuroblastoma has been reported by Hiwatari et al (Hiwatari et al, 2022), who suggested that TENM3 acts as a novel ALK partner in young adults at high risk for stage 4 neuroblastoma. However, few research has been conducted on this gene in LC, the only studies found that the mutation Frontiers in Pharmacology frontiersin.org frequency of TENM3 increased significantly in patients with stage III (Liu et al, 2023). Our results can provide clues for future basic and clinical research related to LUAD treatment.…”

Section: Figurementioning

confidence: 67%

Function and prognostic value of basement membrane -related genes in lung adenocarcinoma

Zhang

Liu

et al. 2023

Front. Pharmacol.

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Background: Lung adenocarcinoma (LUAD) has become a common cause of cancer-related death. Many studies have shown that the basement membrane (BM) is associated with the development of cancer. However, BM-related gene expression and its relationship to LUAD prognosis remains unclear.Methods: BM-related genes from previous studies were used. Clinical and mRNA expression information were obtained from TCGA database. Cox, minimum absolute contraction, and selection operator regression were applied to analyze the selected genes affecting LUAD prognosis. A prognostic-risk model was then established. Furthermore, this study applied Kaplan-Meier analysis to assess the outcomes of high- and low-risk groups, then explored their differences in drug sensitivity. The DSigDB database was used to screen for therapeutic small-molecule drugs.Results: Fourteen prognostic models based on BM-related genes were successfully constructed and validated in patients with LUAD. We also found that independence was a prognostic factor in all 14 BM-based models. Functional analysis showed that the enrichment of BM-related genes mainly originated from signaling pathways related to cancer. The BM-based model also suggested that immune cell infiltration is associated with checkpoints. The low-risk patients may benefit from cyclopamine and docetaxel treatments.Conclusion: This study identified a reliable biomarker to predict survival in patients with LUAD and offered new insights into the function of BM-related genes in LUAD.

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Section: Figurementioning

confidence: 67%

Function and prognostic value of basement membrane -related genes in lung adenocarcinoma

Zhang

Liu

et al. 2023

Front. Pharmacol.

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“…A large number of somatic and germinal mutations (EGFR (20%), TP53 (54.6-64.6%), KRAS (43.7%), BRAF (3.2%), ERBB2 (1.3%), MET (9.4%), STK11 (16.2%), and PIK3CA (9−12.4%)), gene amplifications (EGFR, ERBB2, MET (17.68%), PIK3CA, and NKX2), deletions (DOK2), rearrangements (ALK (13.3%), ROS1 (3.9%), and RET (5.2%)), and fusions (ALK/EML4) [31], which increase the risk of developing lung cancer in certain populations, have been identified but have not led to the development of effective treatments since global mortality rates have not significantly decreased [9]. TP53 (78%), TTN (68%), CSMD3 (39%), MUT16 (36%), and RYR2 (36%) have the highest mutational frequency, and BRINP3, COL11A1, GRIN2B, MUC5B, NLRP3, and TENM3 have shown significantly higher mutational frequency in stage III of lung squamous cell carcinoma [32], while TP53, EGFR, KRAS, ALK, BRAF, MET, RET, and ROS1 are the most frequent mutation genes in lung adenocarcinoma [33]. KRAS mutations appear in less than 40% of NSCLC patients, with a higher prevalence in LUAD (32%) than in LUSC (4%), in Western (26%) than in Asian (11%) patients, in smokers (30%) than in non-smokers (10%), and almost never in SCLC [34].…”

Section: Lung Cancermentioning

confidence: 99%

Host Transcriptional Regulatory Genes and Microbiome Networks Crosstalk through Immune Receptors Establishing Normal and Tumor Multiomics Metafirm of the Oral-Gut-Lung Axis

Otálora-Otálora,

López-Rivera,

Aristizábal-Guzmán

et al. 2023

IJMS

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The microbiome has shown a correlation with the diet and lifestyle of each population in health and disease, the ability to communicate at the cellular level with the host through innate and adaptative immune receptors, and therefore an important role in modulating inflammatory process related to the establishment and progression of cancer. The oral cavity is one of the most important interaction windows between the human body and the environment, allowing the entry of an important number of microorganisms and their passage across the gastrointestinal tract and lungs. In this review, the contribution of the microbiome network to the establishment of systemic diseases like cancer is analyzed through their synergistic interactions and bidirectional crosstalk in the oral-gut-lung axis as well as its communication with the host cells. Moreover, the impact of the characteristic microbiota of each population in the formation of the multiomics molecular metafirm of the oral-gut-lung axis is also analyzed through state-of-the-art sequencing techniques, which allow a global study of the molecular processes involved of the flow of the microbiota environmental signals through cancer-related cells and its relationship with the establishment of the transcription factor network responsible for the control of regulatory processes involved with tumorigenesis.

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Survival prediction and molecular subtyping of squamous cell lung cancer based on network embedding

Guo,

Chen,

Wang

et al. 2024

Sci Rep

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Squamous cell lung cancer (SQCLC), which is fatal to humans, is heterogeneous with different genetic and histological features. We used SBMOI, a multi-omics data integration method from previous study, to integrate clinical, gene expression, and somatic mutation data of SQCLC to construct new patient features. Next, random survival forest (RSF) model and SimpleMKL model were constructed to predict the survival of SQCLC patients, and K-means model was constructed to perform molecular subtyping. The results of the RSF model showed that when the dimension of the patient features were 11 × 364 and the hard threshold was 0.2, we obtained the best results, and the AUC value of the 1-year time-dependent ROC curve was 0.706. The SimpleMKL model, constructed using the same patient features, performed exceptionally well, with 1-year, 5-year, and 10-year survival prediction AUC values of 0.944, 0.947 and 0.950, respectively. We used K-means analysis to identify three SQCLC molecular subtypes with significant survival differences. The patient features constructed by SBMOI were used to effectively predict the survival and molecular subtyping of SQCLC patients. In addition, our study further confirmed the effectiveness in multi-omics data integration task and broad applicability of SBMOI. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-81199-z.

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Mutational and Transcriptional Characterization Establishes Prognostic Models for Resectable Lung Squamous Cell Carcinoma

Cited by 3 publications

References 49 publications

Function and prognostic value of basement membrane -related genes in lung adenocarcinoma

Function and prognostic value of basement membrane -related genes in lung adenocarcinoma

Host Transcriptional Regulatory Genes and Microbiome Networks Crosstalk through Immune Receptors Establishing Normal and Tumor Multiomics Metafirm of the Oral-Gut-Lung Axis

Survival prediction and molecular subtyping of squamous cell lung cancer based on network embedding

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