| 1. |
- Estupinan, HY, et al.
(författare)
-
BTK gatekeeper residue variation combined with cysteine 481 substitution causes super-resistance to irreversible inhibitors acalabrutinib, ibrutinib and zanubrutinib
- 2021
-
Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 35:85, s. 1317-1329
-
Tidskriftsartikel (refereegranskat)abstract
- Irreversible inhibitors of Bruton tyrosine kinase (BTK), pioneered by ibrutinib, have become breakthrough drugs in the treatment of leukemias and lymphomas. Resistance variants (mutations) occur, but in contrast to those identified for many other tyrosine kinase inhibitors, they affect less frequently the “gatekeeper” residue in the catalytic domain. In this study we carried out variation scanning by creating 11 substitutions at the gatekeeper amino acid, threonine 474 (T474). These variants were subsequently combined with replacement of the cysteine 481 residue to which irreversible inhibitors, such as ibrutinib, acalabrutinib and zanubrutinib, bind. We found that certain double mutants, such as threonine 474 to isoleucine (T474I) or methionine (T474M) combined with catalytically active cysteine 481 to serine (C481S), are insensitive to ≥16-fold the pharmacological serum concentration, and therefore defined as super-resistant to irreversible inhibitors. Conversely, reversible inhibitors showed a variable pattern, from resistance to no resistance, collectively demonstrating the structural constraints for different classes of inhibitors, which may affect their clinical application.
|
|
| 2. |
- Yang, Yang, et al.
(författare)
-
PON-Sol : Prediction of effects of amino acid substitutions on protein solubility
- 2016
-
Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 32:13, s. 2032-2034
-
Tidskriftsartikel (refereegranskat)abstract
- Motivation: Solubility is one of the fundamental protein properties. It is of great interest because of its relevance to protein expression. Reduced solubility and protein aggregation are also associated with many diseases. Results: We collected from literature the largest experimentally verified solubility affecting amino acid substitution (AAS) dataset and used it to train a predictor called PON-Sol. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PONSol has normalized correct prediction ratio of 0.491 on cross-validation and 0.432 for independent test set. The performance of the method was compared both to solubility and aggregation predictors and found to be superior. PON-Sol can be used for the prediction of effects of disease-related substitutions, effects on heterologous recombinant protein expression and enhanced crystallizability. One application is to investigate effects of all possible AASs in a protein to aid protein engineering.
|
|
| 3. |
- Schaafsma, Gerard C. P., et al.
(författare)
-
Genetic Variation in Bruton Tyrosine Kinase
- 2015
-
Ingår i: Agammaglobulinemia. - Cham : Springer International Publishing. - 9783319227146 ; , s. 75-85
-
Bokkapitel (refereegranskat)abstract
- X-linked agammaglobulinemia (XLA) is a hereditary immunodeficiency caused by variations in the gene encoding for Bruton's tyrosine kinase (BTK). Patients with XLA have decreased numbers of mature B cells, lack all immunoglobulin isotypes, and therefore have susceptibility to severe bacterial infections. XLA-causing variations are collected into BTKbase freely available at http://structure.bmc.lu.se/idbase/BTKbase/. Details of the variations are provided at DNA, RNA, and protein levels, using standardized systematic names and a plain English description. In addition, clinical details from the patients are provided when available. BTKbase contains variation entries for 1362 patients from 1198 unrelated families altogether for 742 unique molecular events. The localization of the variations on the gene and protein for BTK can be analyzed by clicking sequences on web pages. The distribution of the variations in the five structural domains is approximately according to the length of the domains, except for the TH and SH3 domains. The most frequently affected sites are CpG dinucleotides. The majority of the amino acid substitutions are structural affecting protein fold or stability. Detailed statistics is provided highlighting variation types, affected domains, exons and introns, as well as structural consequences.
|
|
| 4. |
- Teku, Gabriel N., et al.
(författare)
-
Pan-cancer analysis of neoepitopes
- 2018
-
Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1
-
Tidskriftsartikel (refereegranskat)abstract
- Somatic variations are frequent and important drivers in cancers. Amino acid substitutions can yield neoantigens that are detected by the immune system. Neoantigens can lead to immune response and tumor rejection. Although neoantigen load and occurrence have been widely studied, a detailed pan-cancer analysis of the occurrence and characterization of neoepitopes is missing. We investigated the proteome-wide amino acid substitutions in 8-, 9-, 10-, and 11-mer peptides in 30 cancer types with the NetMHC 4.0 software. 11,316,078 (0.24%) of the predicted 8-, 9-, 10-, and 11-mer peptides were highly likely neoepitope candidates and were derived from 95.44% of human proteins. Binding affinity to MHC molecules is just one of the many epitope features. The most likely epitopes are those which are detected by several MHCs and of several peptide lengths. 9-mer peptides are the most common among the high binding neoantigens. 0.17% of all variants yield more than 100 neoepitopes and are considered as the best candidates for any application. Amino acid distributions indicate that variants at all positions in neoepitopes of any length are, on average, more hydrophobic than the wild-type residues. We characterized properties of neoepitopes in 30 cancer types and estimated the likely numbers of tumor-derived epitopes that could induce an immune response. We found that amino acid distributions, at all positions in neoepitopes of all lengths, contain more hydrophobic residues than the wild-type sequences implying that the hydropathy nature of neoepitopes is an important property. The neoepitope characteristics can be employed for various applications including targeted cancer vaccine development for precision medicine.
|
|
| 5. |
- Rivas-Carrillo, Salvador Daniel
(författare)
-
The revolutionary partnership of computation and biology
- 2023
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The organization of living beings is complex. Science uses modeling in order to gain a deeper understanding, and to be able to manipulate the processes of living organisms. To this purpose, I used and developed computational tools to investigate and model different relevant biological phenomena. In paper I, I utilized whole-genome data from wild and domesticated European rabbit (Oryctolagus cuniculus sp.) populations to identify segregating insertions of endogenous retroviruses and compare their variation along the host phylogeny and domestication history. The results from this study highlight the importance of genomic modeling beyond reference organisms and reference individuals, and provide deep insights regarding strategies for variant analyses in host population comparative genomics. In paper IV, I studied the process of exaptation of foreign genetic elements at broad-scale by observing the presence and characteristics of retroviral env gene, syncytin, across vertebrates. I searched a library of more than 150 chromosome-length assemblies covering 17 taxonomical orders for syncytin homologs, where I identified and syntenically aligned over 300 loci insertions, including not previously known insertions. Additionally, three-dimensional structures of the recovered sequences were predicted using AlphaFold2. Phylogenomics analyses suggest a complex dynamic of multiple retroviral insertions at different time points with sequence conservation specific to clades that share a similar histo-physiological placental type.In paper II, I expanded the scope to encompass translational medicine by developing an unsupervised machine learning methodology for detecting anomalies in biomedical signals, MindReader, which I applied primarily to electroencephalogram. In paper III, I developed a hidden Markov model implementation that includes a hypothesis generator for stream time-domain signals, which is used as a dependency for paper II. The work in this thesis substantiates that a combination of biological knowledge, cutting-edge technology, and robust algorithmic design constitute the primordial factors for scientific advancement.
|
|
| 6. |
- Vihinen, Mauno
(författare)
-
Establishment of an international database for genetic variants in esophageal cancer
- 2016
-
Ingår i: Annals of the New York Academy of Sciences. - : Wiley. - 0077-8923. ; 1381:1, s. 45-49
-
Tidskriftsartikel (refereegranskat)abstract
- The establishment of a database has been suggested in order to collect, organize, and distribute genetic information about esophageal cancer. The World Organization for Specialized Studies on Diseases of the Esophagus and the Human Variome Project will be in charge of a central database of information about esophageal cancer–related variations from publications, databases, and laboratories; in addition to genetic details, clinical parameters will also be included. The aim will be to get all the central players in research, clinical, and commercial laboratories to contribute. The database will follow established recommendations and guidelines. The database will require a team of dedicated curators with different backgrounds. Numerous layers of systematics will be applied to facilitate computational analyses. The data items will be extensively integrated with other information sources. The database will be distributed as open access to ensure exchange of the data with other databases. Variations will be reported in relation to reference sequences on three levels––DNA, RNA, and protein—whenever applicable. In the first phase, the database will concentrate on genetic variations including both somatic and germline variations for susceptibility genes. Additional types of information can be integrated at a later stage.
|
|
| 7. |
- Azevedo, Carla, et al.
(författare)
-
Parkinsons disease and multiple system atrophy patient iPSC-derived oligodendrocytes exhibit alpha-synuclein-induced changes in maturation and immune reactive properties
- 2022
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:12
-
Tidskriftsartikel (refereegranskat)abstract
- Limited evidence has shed light on how aSYN proteins affect the oligodendrocyte phenotype and pathogenesis in synucleinopathies that include Parkinsons disease (PD) and multiple system atrophy (MSA). Here, we investigated early transcriptomic changes within PD and MSA O4(+) oligodendrocyte lineage cells (OLCs) generated from patient-induced pluripotent stem cells (iPSCs). We found impaired maturation of PD and MSA O4(+) OLCs compared to controls. This phenotype was associated with changes in the human leukocyte antigen (HLA) genes, the immunoproteasome subunit PSMB9, and the complement component C4b for aSYN p.A53T and MSA O4(+) OLCs, but not in SNCA(trip) O4(+) OLCs despite high levels of aSYN assembly formation. Moreover, SNCA overexpression resulted in the development of O4(+) OLCs, whereas exogenous treatment with aSYN species led to significant toxicity. Notably, transcriptome profiling of genes encoding proteins forming Lewy bodies and glial cytoplasmic inclusions revealed clustering of PD aSYN p.A53T O4(+) OLCs with MSA O4(+) OLCs. Our work identifies early phenotypic and pathogenic changes within human PD and MSA O4(+) OLCs.
|
|
| 8. |
- Vihinen, Mauno
(författare)
-
How to Define Pathogenicity, Health, and Disease?
- 2017
-
Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 38:2, s. 129-136
-
Tidskriftsartikel (refereegranskat)abstract
- Scientific and clinical communities produce ever increasing amounts of data and details about health and disease. Our ability to understand and utilize this information is limited because of imprecise language and lack of well-defined concepts. This problem involves also the principal concepts of health, disease, and pathogenicity. Here, a systematic model is presented for pathogenicity, as well as for health and disease. It has three components: extent, modulation, and severity, which jointly define the continuum of pathogenicity. The model is population based, and once implemented, it can be used for numerous purposes such as diagnosis, patient stratification, prognosis, finding phenotype–genotype correlations, or explaining adverse drug reactions. The new model has several benefits including health economy by allowing evidence-based personalized/precision medicine.
|
|
| 9. |
- Zhang, Xueli, 1991-
(författare)
-
Biomarkers for Diagnosis, Therapy and Prognosis in Colorectal Cancer : a study from databases, machine learning predictions to laboratory confirmations
- 2020
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Early diagnosis and better therapy response have been believed to be associated with better prognosis. CRC biomarkers are considered as precise indicators for the early diagnosis and better therapy response. It is, therefore, of importance to find out, analyze and evaluate the CRC biomarkers to further provide the more precis evidence for predicting novel potential biomarkers and eventually to improve early diagnosis, personalized therapy and prognosis for CRC.In this study, we started with creating and establishing a CRC biomarker database. (CBD: http://sysbio.suda.edu.cn/CBD/index.html) In the CBD database, there were 870 reported CRC biomarkers collected from the published articles in PubMed. In this version of the CBD, CRC biomarker data was carefully collected, sorted, displayed, and analyzed. The major applications of the CBD are to provide 1) the records of CRC biomarkers (DNA, RNA, protein and others) concerning diagnosis, treatment and prognosis; 2) the basic and clinical research information concerning the CRC biomarkers; 3) the primary results for bioinformatics and biostatics analysis of the CRC biomarkers; 4) downloading/uploading the biomedicine information for CRC biomarkers.Based on our CBD and other public databases, we further analyzed the presented CRC biomarkers (DNAs, RNAs, proteins) and predicted novel potential multiple biomarkers (the combination of single biomarkers) with biological networks and pathways analysis for diagnosis, therapy response and prognosis in CRC. We found several hub biomarkers and key pathways for the diagnosis, treatment and prognosis in CRC. Receiver operating characteristic (ROC) test and survival analysis by microarray data revealed that multiple biomarkers could be better biomarkers than the single biomarkers for the diagnosis and prognosis of CRC.There are 62 diagnosis biomarkers for colon cancer in our CBD. In the previous studies, we found these present biomarkers were not enough to improve significantly the diagnosis of colon cancer. In order to find out novel biomarkers for the colon cancer diagnosis, we have performed /machine learning (ML) techniques such as support vector machine (SVM) and regression tree to predict candidate to discover diagnostic biomarkers for colon cancer. Based on the protein-protein interaction (PPI) network topology features of the identified biomarkers, we found 12 protein biomarkers which were considered as the candidate colon cancer diagnosis biomarkers. Among these protein biomarkers Chromogranin-A (CHGA) was the most powerful biomarker, which showed good performance in bioinformatics test and Immunohistochemistry(IHC). We are now expanding this study to CRC.Expression of CHGA protein in colon cancer was further verified with a novel logistic regressionbased meta-analysis, and convinced as a valuable diagnostic biomarker as compared with the typical diagnostic biomarkers, such as TP53, KRAS and MKI67.microRNAs (miRNAs/miRs) have been considered as potential biomarkers. A novel miRNA-mRNA interaction network-based model was used to predict miRNA biomarkers for CRC and found that miRNA-186-5p, miRNA-10b-5p and miRNA-30e-5p might be the novel biomarkers for CRC diagnosis. In conclusion, we have created a useful CBD database for CRC biomarkers and provided detailed information for how to use the CBD in CRC biomarker investigations. Our studies have been focusing on the biomarkers in diagnosis, therapy and prognosis. Based on our CBD and other powerful cancer associated databases, ML has been used to analyze the characteristics of the CRC biomarkers and predict novel potential CRC biomarkers. The predicted potential biomarkers were further confirmed at biomedical laboratory.
|
|
| 10. |
- Carraro, Marco, et al.
(författare)
-
Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI
- 2017
-
Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1042-1050
-
Tidskriftsartikel (refereegranskat)abstract
- Correct phenotypic interpretation of variants of unknown significance for cancer-associated genes is a diagnostic challenge as genetic screenings gain in popularity in the next-generation sequencing era. The Critical Assessment of Genome Interpretation (CAGI) experiment aims to test and define the state of the art of genotype-phenotype interpretation. Here, we present the assessment of the CAGI p16INK4a challenge. Participants were asked to predict the effect on cellular proliferation of 10 variants for the p16INK4a tumor suppressor, a cyclin-dependent kinase inhibitor encoded by the CDKN2A gene. Twenty-two pathogenicity predictors were assessed with a variety of accuracy measures for reliability in a medical context. Different assessment measures were combined in an overall ranking to provide more robust results. The R scripts used for assessment are publicly available from a GitHub repository for future use in similar assessment exercises. Despite a limited test-set size, our findings show a variety of results, with some methods performing significantly better. Methods combining different strategies frequently outperform simpler approaches. The best predictor, Yang&Zhou lab, uses a machine learning method combining an empirical energy function measuring protein stability with an evolutionary conservation term. The p16INK4a challenge highlights how subtle structural effects can neutralize otherwise deleterious variants.
|
|
