Robust Biomarker Screening Using Spares Learning Approach for Liver Cancer Prognosis

Kaushik, Aman Chandra; Mehmood, Aamir; Wei, Dong‐Qing; Dai, Xiaofeng

doi:10.3389/fbioe.2020.00241

Cited by 6 publications

(3 citation statements)

References 23 publications

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“…Compared to the WT, a higher Rg value represents the disassociation of the respective protein. However, the increased number of hydrogen bonds causes the structural unsteadiness 67 , 68 . Hence, consistent fluctuations in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to WT might guide exploring the mechanism by which these missense SNPs alter the structure and function of the native MCM6 protein.…”

Section: Discussionmentioning

confidence: 99%

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Kamal,

Mia,

Faruque

et al. 2024

Sci Rep

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Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

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Section: Discussionmentioning

confidence: 99%

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Kamal,

Mia,

Faruque

et al. 2024

Sci Rep

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“…A potentially unique and practical method for predicting the prognosis of patients with endometrial cancer is the identification of MUC5B mutation through genomic profiling . Based on the expression of this gene in cancers and the importance of missense mutations, we obtained The Cancer Genome Atlas (TCGA) − data showing MUC5B as a frequently mutated gene in CCA, which is considered further for its mutational studies using molecular dynamic simulations , to understand the impact of point substitutions on the protein conformation. Our computational structural biology approach provides a detailed analysis of CCA key mutations, and the results obtained could help further understand the role of MUC5B in cancers and the disease in general.…”

Section: Introductionmentioning

confidence: 99%

Mutational Impacts on the N and C Terminal Domains of the MUC5B Protein: A Transcriptomics and Structural Biology Study

et al. 2023

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Cholangiocarcinoma (CCA) involves various epithelial tumors historically linked with poor prognosis because of its aggressive sickness course, delayed diagnosis, and limited efficacy of typical chemotherapy in its advanced stages. In-depth molecular profiling has exposed a varied scenery of genomic alterations as CCA's oncogenic drivers. Previous studies have mainly focused on commonly occurring TP53 and KRAS alterations, but there is limited research conducted to explore other vital genes involved in CCA. We retrieved data from The Cancer Genome Atlas (TCGA) to hunt for additional CCA targets and plotted a mutational landscape, identifying key genes and their frequently expressed variants. Next, we performed a survival analysis for all of the top genes to shortlist the ones with better significance. Among those genes, we observed that MUC5B has the most significant p-value of 0.0061. Finally, we chose two missense mutations at different positions in the vicinity of MUC5B N and C terminal domains. These mutations were further subjected to molecular dynamics (MD) simulation, which revealed noticeable impacts on the protein structure. Our study not only reveals one of the highly mutated genes with enhanced significance in CCA but also gives insights into the influence of its variants. We believe these findings are a good asset for understanding CCA from genomics and structural biology perspectives.

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“…But, the information about lncRNAs and TNBC is quite limited and the countenance outline, roles and biological machinery regarding lncRNAs in TNBC need to be extensively investigated ( Kapusta and Feschotte, 2014 ; Wang et al, 2017 ). Cancer has had a broad impact on society, it is important to recognize effective and robust tools that could change the impact of cancer ( Kaushik and Sahi, 2017 ; Kaliamurthi et al, 2018 ; Kaushik et al, 2018 , 2019a , b ; Kaushik et al, 2020a , b , c , d ).…”

Section: Introductionmentioning

confidence: 99%

Globally ncRNAs Expression Profiling of TNBC and Screening of Functional lncRNA

Kaushik

Mehmood

Wang

et al. 2021

Front. Bioeng. Biotechnol.

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One of the most well-known cancer subtypes worldwide is triple-negative breast cancer (TNBC) which has reduced prediction due to its antagonistic biotic actions and target’s deficiency for the treatment. The current work aims to discover the countenance outlines and possible roles of lncRNAs in the TNBC via computational approaches. Long non-coding RNAs (lncRNAs) exert profound biological functions and are widely applied as prognostic features in cancer. We aim to identify a prognostic lncRNA signature for the TNBC. First, samples were filtered out with inadequate tumor purity and retrieved the lncRNA expression data stored in the TANRIC catalog. TNBC sufferers were divided into two prognostic classes which were dependent on their survival time (shorter or longer than 3 years). Random forest was utilized to select lncRNA features based on the lncRNAs differential expression between shorter and longer groups. The Stochastic gradient boosting method was used to construct the predictive model. As a whole, 353 lncRNAs were differentially transcribed amongst the shorter and longer groups. Using the recursive feature elimination, two lncRNAs were further selected. Trained by stochastic gradient boosting, we reached the highest accuracy of 69.69% and area under the curve of 0.6475. Our findings showed that the two-lncRNA signs can be proved as potential biomarkers for the prognostic grouping of TNBC’s sufferers. Many lncRNAs remained dysregulated in TNBC, while most of them are likely play a role in cancer biology. Some of these lncRNAs were linked to TNBC’s prediction, which makes them likely to be promising biomarkers.

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Robust Biomarker Screening Using Spares Learning Approach for Liver Cancer Prognosis

Cited by 6 publications

References 23 publications

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Mutational Impacts on the N and C Terminal Domains of the MUC5B Protein: A Transcriptomics and Structural Biology Study

Globally ncRNAs Expression Profiling of TNBC and Screening of Functional lncRNA

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