Accumulation of mutant proteins in cells can induce proteinopathies and cause functional damage to organs.Recently,the Cingulin(CGN)protein has been shown to maintain the morphology of cuticular plates of inner ear ha...Accumulation of mutant proteins in cells can induce proteinopathies and cause functional damage to organs.Recently,the Cingulin(CGN)protein has been shown to maintain the morphology of cuticular plates of inner ear hair cells and a frameshift mutation in CGN causes autosomal dominant non-syndromic hearing loss.Here,we find that the mutant CGN proteins form insoluble aggregates which accumulate intracellularly and lead to cell death.Expression of the mutant CGN in the inner ear results in severe hair cell death and hearing loss in mice,resembling the auditory phenotype in human patients.Interestingly,a human-specific residue(V1112)in the neopeptide generated by the frameshift mutation is critical for the aggregation and cytotoxicity of the mutant human CGN.Moreover,the expression of heat shock factor 1(HSF1)decreases the accumulation of insoluble mutant CGN aggregates and rescues cell death.In summary,these findings identify mutant-specific toxic polypeptides as a disease-causing mechanism of the deafness mutation in CGN,which can be targeted by the expression of the cell chaperone response regulator HSF1.展开更多
Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells.Some of these molecules can induce an immune response,and therefore,their use in immunotherapeutic s...Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells.Some of these molecules can induce an immune response,and therefore,their use in immunotherapeutic strategies based on cancer vaccines has been extensively explored.Studies based on these approaches have been triggered by the current high-throughput DNA sequencing technologies.However,there is no universal nor straightforward bioinformatic protocol to discover neoan-tigens using DNA sequencing data.Thus,we propose a bioinformatic protocol to detect tumor-specific antigens associated with single nucleotide variants(SNVs)or“mutations”in tumoral tissues.For this purpose,we used publicly available data to build our model,including exome sequencing data from colorectal cancer and healthy cells obtained from a single case,as well as frequent human leukocyte antigen(HLA)class I alleles in a specific population.HLA data from Costa Rican Central Valley population was selected as an example.The strategy included three main steps:(1)pre-processing of sequencing data;(2)variant calling analysis to detect tumor-specific SNVs in comparison with healthy tissue;and(3)prediction and characterization of peptides(protein fragments,the tumor-specific antigens)derived from the variants,in the context of their affinity with frequent alleles of the selected population.In our model data,we found 28 non-silent SNVs,present in 17 genes in chromosome one.The protocol yielded 23 strong binders peptides derived from the SNVs for frequent HLA class I alleles for the Costa Rican population.Although the analyses were performed as an example to implement the pipeline,to our knowledge,this is the first study of an in silico cancer vaccine using DNA sequencing data in the context of the HLA alleles.It is concluded that the standardized protocol was not only able to identify neoantigens in a specific but also provides a complete pipeline for the eventual design of cancer vaccines using the best bioinformatic practices.展开更多
基金supported by the National Natural Science Foundation of China(82171136 and 92368110 to G.W.,82201291 to G.-J.Z.,82171145 to X.Q.,81870721 to J.C.,and 81970884 and 82192862 to X.G.)Natural Science Foundation of Jiangsu Province(BK20220189to G.-J.Z.and BK20220188 to Q.L.)+1 种基金Special Foundation for Health Science and Technology Development of Nanjing(YKK21109 to G.-J.Z.)the Clinical Research Foundation of Drum Tower Hospital affiliated to Nanjing University Medical School(2021-LCYJ-PY-04 to G.-J.Z.)。
文摘Accumulation of mutant proteins in cells can induce proteinopathies and cause functional damage to organs.Recently,the Cingulin(CGN)protein has been shown to maintain the morphology of cuticular plates of inner ear hair cells and a frameshift mutation in CGN causes autosomal dominant non-syndromic hearing loss.Here,we find that the mutant CGN proteins form insoluble aggregates which accumulate intracellularly and lead to cell death.Expression of the mutant CGN in the inner ear results in severe hair cell death and hearing loss in mice,resembling the auditory phenotype in human patients.Interestingly,a human-specific residue(V1112)in the neopeptide generated by the frameshift mutation is critical for the aggregation and cytotoxicity of the mutant human CGN.Moreover,the expression of heat shock factor 1(HSF1)decreases the accumulation of insoluble mutant CGN aggregates and rescues cell death.In summary,these findings identify mutant-specific toxic polypeptides as a disease-causing mechanism of the deafness mutation in CGN,which can be targeted by the expression of the cell chaperone response regulator HSF1.
基金funded by Vicerrectoría de Investigación—Universidad de Costa Rica,with the Project“C1163 proNGS 2.0:Protocolos operativos estandarizados de análisis de datos moleculares obtenidos por NGS o afines y de algoritmos de inteligencia artificial en modelos biológicos(2021–2023)”.
文摘Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells.Some of these molecules can induce an immune response,and therefore,their use in immunotherapeutic strategies based on cancer vaccines has been extensively explored.Studies based on these approaches have been triggered by the current high-throughput DNA sequencing technologies.However,there is no universal nor straightforward bioinformatic protocol to discover neoan-tigens using DNA sequencing data.Thus,we propose a bioinformatic protocol to detect tumor-specific antigens associated with single nucleotide variants(SNVs)or“mutations”in tumoral tissues.For this purpose,we used publicly available data to build our model,including exome sequencing data from colorectal cancer and healthy cells obtained from a single case,as well as frequent human leukocyte antigen(HLA)class I alleles in a specific population.HLA data from Costa Rican Central Valley population was selected as an example.The strategy included three main steps:(1)pre-processing of sequencing data;(2)variant calling analysis to detect tumor-specific SNVs in comparison with healthy tissue;and(3)prediction and characterization of peptides(protein fragments,the tumor-specific antigens)derived from the variants,in the context of their affinity with frequent alleles of the selected population.In our model data,we found 28 non-silent SNVs,present in 17 genes in chromosome one.The protocol yielded 23 strong binders peptides derived from the SNVs for frequent HLA class I alleles for the Costa Rican population.Although the analyses were performed as an example to implement the pipeline,to our knowledge,this is the first study of an in silico cancer vaccine using DNA sequencing data in the context of the HLA alleles.It is concluded that the standardized protocol was not only able to identify neoantigens in a specific but also provides a complete pipeline for the eventual design of cancer vaccines using the best bioinformatic practices.
