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Mwangi, K.

Publications and source records attributed to Mwangi, K..

2 recordsLinked to original sources

Mutational and Expression Profile of ZNF217, ZNF750, ZNF703 Zinc Finger Genes in Kenya Women diagnosed with Breast Cancer

ObjectiveTo characterize the mutational landscape and expression profiles of ZNF217, ZNF703, and ZNF750, and assess their clinical relevance in breast cancer patients from Kenya. MethodsWhole-exome sequencing (WES) and RNA sequencing (RNA-Seq) data from 23 paired tumor-normal samples were analyzed in a Linux-based environment. Somatic mutations were identified using MuTect2 following alignment to the hg38 reference genome and annotation with VEP. Variants were classified by type, coding consequence, and protein position, and mapped to functional domains. Recurrent mutations were identified, and comparisons were made with The Cancer Genome Atlas (TCGA). Gene expression was quantified using STAR and featureCounts, normalized with DESeq2, and analyzed using paired statistical tests with multiple testing correction. Principal component analysis (PCA) and regression analyses were performed to assess expression patterns and clinical associations. ResultsZNF217 and ZNF750 exhibited high mutational burdens, whereas ZNF703 showed a lower mutation frequency. Mutations were predominantly single nucleotide variants, with missense and synonymous variants as the major classes. Variants were distributed across protein sequences, with limited domain enrichment and no clear hotspot clustering. Recurrent mutations were gene-specific and infrequent. Comparison with TCGA data showed concordant mutation prevalence for ZNF217, low frequency for ZNF703, and absence of ZNF750 mutations. All three genes were significantly upregulated in tumors compared to matched normal tissues (ZNF217: p = 0.00068; ZNF703: p = 0.00475; ZNF750: p = 0.00366). Tumor expression exceeded normal expression in 74% of cases for ZNF217, 64% for ZNF703, and 83% for ZNF750. PCA demonstrated partial separation between tumor and normal samples. ZNF703 expression was positively associated with body mass index ({beta} = 0.194, p = 0.025), and ZNF750 expression was higher in estrogen receptor-positive tumors ({beta} = 1.050, p = 0.005). ConclusionZNF217, ZNF703, and ZNF750 display distinct mutation and expression profiles in breast cancer, with evidence of cohort-specific variation. These findings highlight gene-specific mechanisms of dysregulation and emphasize the value of integrating genomic and transcriptomic analyses.

cancer biology↗

Development of a General Purpose Targeted LC-MS Method for Accurate Quantification of the SARS-CoV-2 Spike Protein Expression

The COVID-19 pandemic has catalyzed interest in immuno-multiple reaction monitoring (immuno-MRM) methods, with the detection of peptides unique to the nucleocapsid protein in nasopharyngeal swabs. While current applications predominantly focus on disease biomarkers, the pandemic has unveiled new opportunities, namely for the quantification of antigen expression following mRNA vaccination. Here, we present an optimized immuno-MRM method for quantifying SARS-CoV-2 spike protein fusion peptide, SFIEDLLFNK, for several practical applications. The method is versatile, applicable to multiple biological matrices, including plasma, and can be extended to nasopharyngeal swabs. It also offers a high-precision tool for assessing protein expression following plasmid and mRNA transfection. Moreover, in parallel to enabling accurate antigen quantification, the flow-through can be used to determine the proteome profile of the infected cells, providing insights into the intracellular immune response. This dual capability supports the rapid optimization of mRNA vaccines, thereby driving advancements in vaccine development strategies.

immunology↗