The emerging roles of NGS in clinical oncology and personalized medicine

Hussen, Bashdar Mahmud; Abdullah, Sara Tharwat; Salihi, Abbas; Sabir, Dana Khdr; Sidiq, Karzan R.; Rasul, Mohammed Fatih; Hidayat, Hazha Jamal; Ghafouri‐Fard, Soudeh; Taheri, Mohammad; Jamali, Elena

doi:10.1016/j.prp.2022.153760

Cited by 42 publications

(24 citation statements)

References 190 publications

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“…In recent years, bioinformatic databases have provided abundant transcriptomic and clinical data (8,9), which are convenient for the analysis of relevant markers with potential significance (10)(11)(12). In this study, we explored several databases for molecular markers of HCC and investigated their expression levels in clinical specimens.…”

Section: Introductionmentioning

confidence: 99%

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

Cui

Wang²,

Chen³

et al. 2023

Front. Oncol.

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BackgroundPatients with hepatocellular carcinoma (HCC) have poor prognosis, especially in advanced stages. Targeted therapy is the main treatment for advanced HCC patients, but the optimal targets for HCC remain poorly understood. The main purpose of this study was to identify potential novel prognostic markers and therapeutic targets.MethodsFirstly, differentially expressed genes (DEGs) in HCC were identified from the Gene Expression Omnibus (GEO) database. The expression, significance in prognosis, and potential mechanisms of DEGs were analyzed using GEPIA, TIMER, HPA, Kaplan Meier Plotter, CBioPortal, miRWalk, TargetScan, and ENCORI databases. Immunohistochemical staining was used to determine the protein expression levels of potential candidate genes.ResultsThe mRNA levels of MND1, STXBP6, and CLGN were significantly increased in HCC (p< 0.01). HCC patients with elevated CLGN mRNA levels had poorer overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and disease-specific survival (DSS) (p < 0.05). Higher MND1 mRNA levels significantly correlated with poorer DFS in HCC patients (p< 0.05). However, there was no significant correlation between STXBP6 expression and prognosis of HCC (p> 0.05). Further analysis revealed that patients with elevated CLGN mRNA expression in advanced pathology stages had poorer prognosis (p< 0.01). In addition, CLGN protein levels were elevated in HCC compared to their levels in normal tissues. The mRNA levels of CLGN had no significant correlation with the abundance of six common tumor infiltrating lymphocytes in HCC (COR < 0.5). Moreover, the mutation rate of CLGN was less than 1% in HCC patients (10/1089). Finally, the expression level of hsa-miR-194-3p in HCC was significantly lower than that in normal tissues (p < 0.05), and prognosis of HCC with low expression of hsa-miR-194 was poor (p < 0.05).ConclusionThe upregulation of CLGN in HCC is significantly associated with poor patient prognosis, especially in the advanced stages, and may be regulated by hsa-miR-194-3p. These findings suggest that CLGN may be closely related to the progression of HCC, and is a potential therapeutic target and prognostic indicator for patients with advanced HCC.

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Section: Introductionmentioning

confidence: 99%

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

Cui

Wang²,

Chen³

et al. 2023

Front. Oncol.

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“…Genomic profiling has assumed an increasing role in the clinical management of cancer patients, thanks to the approval of numerous drugs showing demonstrated activity in patients with specific genomic alterations [ 1 , 2 , 3 , 4 ]. The need to identify an increasing number of complex genomic biomarkers led to the introduction of next-generation sequencing (NGS) technologies in clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

et al. 2022

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The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

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“…High-throughput data analysis has assumed an increasingly important role in the clinical management of cancer patients, and the need to identify an increasing number of complex biomarkers has led to the introduction of next-generation sequencing (NGS) technologies in clinical practice ( Hussen et al, 2022 ). RNA-sequencing based on NGS has provided new therapeutic modalities for TNBC by identifying cancer-driving variants and molecular subtypes of TNBC ( Hu et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of immune-related signature for the prognosis and benefit of immunotherapy in triple-negative breast cancer

Sun

Zhang

2022

Front. Genet.

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Background: There is a lack of biomarkers for predicting the efficacy of immunotherapy in triple-negative breast cancer (TNBC). Hence, we constructed an immune risk score (IRS) model to predict the prognosis of patients with TNBC and evaluate those who are sensitive to immunotherapy.Methods: The ribonucleic acid (RNA) sequencing data, mutation data, and clinical information of TNBC patients were obtained from The Cancer Genome Atlas database. Data of immune-related genes were obtained from the Import and InnateDB databases. The IRS model was constructed using univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, and the predictive ability of the prognostic model was evaluated. Further external validation was performed using the Gene Expression Omnibus (GEO) databases GSE58812 and GSE135565. Data on the clinical characteristics, immune landscape, and immune checkpoint inhibitors used in different risk groups were analyzed. Finally, the drug sensitivity of the patients in the high- and low-risk groups was predicted.Results: The prognostic risk score model comprised six genes: HSPA6, LCN1, ARTN, IL36G, BCL2A1, and CASP12. The area under the curve values at 1 year, 3 years, and 5 years were 0.835, 0.852, and 0.843, respectively, indicating that the model has a good potential for predicting the long-term survival of TNBC patients, which is consistent with the results of the GEO cohort. Compared with the high-risk group, the low-risk group had a better prognosis; more abundant immune-activated cell infiltrates, such as CD8+ T cells and CD4 memory-activated T cells, and a higher enrichment of immune-related signaling pathways, such as the cytokine receptor interaction, nucleotide oligomerization domain-like receptor signal pathway, T-cell receptor signal pathway, and B-cell receptor signaling pathway, were observed. In addition, the immune checkpoint encoding genes, such as CD274, CTLA4, PDCD1, and PDCD1LG2 were highly expressed in the low-risk group, which showed that this group was more likely to benefit from immunotherapy.Conclusion: A new IRS gene feature was established to predict the patients’ prognosis and guide immunotherapy. Moreover, it was revealed that several potential therapeutic drugs can be used in high-risk patients who are unresponsive to immunotherapy.

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The emerging roles of NGS in clinical oncology and personalized medicine

Cited by 42 publications

References 190 publications

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

Identification of immune-related signature for the prognosis and benefit of immunotherapy in triple-negative breast cancer

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