https://m2.mtmt.hu/ hun 2026-10-24 04:18 BookChapter 35054097 APPROVED true 0 false 2026-08-04T10:00:56.891+0000 2024-07-31T13:31:09.912+0000 2024-06-18T08:42:36.963+0000 true 10087400 Nemes Kolos /api/author/10087400 Author true 2024-07-31T13:31:10.185+0000 2024-07-31T13:31:10.185+0000 true false true 31 31 /api/publicationtype/31 PublicationType 4 true 31 BookChapter true 10000175 Abstract true 31 31 /api/publicationtype/31 PublicationType 4 true 31 BookChapter /api/subtype/10000175 Absztrakt / Kivonat SubType 453 true 10000175 true 1 /api/category/1 Category true 1 Kolos, Nemes PREDICTIVE INSIGHTS INTO DRUG RESPONSE: INTEGRATING PROTEOMICS AND GENE EXPRESSION WITH MACHINE LEARNING IN SMALL CELL LUNG CANCER 185 185 185 1 2024 Introduction: Small Cell Lung Cancer (SCLC) is characterized by aggressive behavior and limited treatment efficacy. The integration of proteomics and gene expression data offers new avenues for predicting drug responses. This study utilizes dimension reduction and clustering techniques to identify distinct sample clusters within SCLC cell lines, aiming to discover variable drug responses and enhance personalized treatment strategies. Methods and Results: Proteomic and gene expression data from SCLC cell lines were subjected to dimension reduction techniques (tSNE, UMAP, PCA) and clustering methods (DynamicTreeCut, HDBSCAN, k-means) to form distinct sample clusters. Drug response data, in terms of IC50 values, were obtained from databases such as NCI, GDSC, CCLE, and UTSW. Within each sample cluster, drug responses were analyzed to identify patterns of sensitivity or resistance. Additionally, ssGSEA was employed to derive enrichment scores from gene clusters, which were then correlated with the drug response data to pinpoint biomarkers predictive of treatment outcomes. This dual approach of clustering samples and correlating gene cluster enrichment scores with drug responses enabled the identification of distinct phenotypic profiles with specific drug susceptibilities. Conclusion: By clustering SCLC cell lines based on proteomic and transcriptomic data and correlating gene expression signatures with drug responses, our study delineates a comprehensive method to discern and exploit therapeutic vulnerabilities in SCLC. This strategy enhances the precision of drug response p true 2024 false true false true false NONE 2026-08-04 false 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 false false false false 2024-09-16T08:42:37.375+0000 HCEMM Cancer Genomics and Epigenetcis Core Group (HCEMM); Interdiszciplináris Orvostudományok Doktori Iskola (SZTE / DI) 6 33 2 6 0 true 217 true 10002 English /api/language/10002 Angol Language true 2 false true 26764493 IDENTICAL /api/publicationidentifier/26764493 https://huphar.org/huphar2024/wp-content/uploads/2024/06/HUPHAR2024-Programfuzet-4.pdf https://huphar.org/huphar2024/wp-content/uploads/2024/06/HUPHAR2024-Programfuzet-4.pdf PublicationIdentifier true 39 Full text @@@ /api/publicationsource/39 Teljes dokumentum PlainSource true true 10006 /api/publicationsourcetype/10006 PublicationSourceType true true 39 true false /api/publication/35000600 true true 32 32 /api/publicationtype/32 PublicationType 6 true 32 Book Conference on Pharmacology, Pharmacokinetics & Innovation (HUPHAR 2024) false 35000600 false false true true false Book 2024 true 1 /api/category/1 Category true 1 false Language 10002 /api/language/10002 Angol English true 2 true PersonAuthorship 117948067 /api/authorship/117948067 1 0.2 true false Author 10087400 /api/author/10087400 Nemes Kolos true true Kolos Nemes true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 117948068 /api/authorship/117948068 2 0.2 false false Author 10089737 /api/author/10089737 Benő Alexandra Ágnes true true Alexandra Benő true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 117948069 /api/authorship/117948069 3 0.2 false false Author 10060864 /api/author/10060864 Mihalekné Fűr Gabriella true 10060864 true Mihalekné Fűr Gabriella true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 117948070 /api/authorship/117948070 4 0.2 false false Author 10093937 /api/author/10093937 Magó Éva true true Éva Magó true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 117948071 /api/authorship/117948071 5 0.2 false false Author 10093938 /api/author/10093938 Goór-Topolcsányi Petronella true true Petronella Topolcsányi true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 117948506 /api/authorship/117948506 6 0.0 false true Author 10045334 /api/author/10045334 Pongor Lőrinc true 10045334 true Lőrinc Pongor true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true /api/publication/35054097 <div class="BookChapter Publication long-list"> <div class="authors"> <img title="Forrásközlemény" style="float: left" src="/frontend/resources/grid/publication-core-icon.png"> <div class="autype autype0"> <span class="author-name" mtid="10087400"><a href="/gui2/?type=authors&mode=browse&sel=10087400" target="_blank">Kolos Nemes (<span class="authorship-author-name">Nemes Kolos</span> <span class="authorAux-mtmt"> bioinformatika</span>) </a> </span> <span class="author-affil"><span title="Szegedi Tudományegyetem">SZTE</span>/<span title="Doktori Iskolák">DI</span>/Interdiszciplináris Orvostudományok Doktori Iskola; <span title="Magyar Molekuláris Medicina Kiválósági Központ (HCEMM) Nonprofit Kft.">HCEMM</span>/HCEMM Cancer Genomics and Epigenetcis Core Group</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10089737"><a href="/gui2/?type=authors&mode=browse&sel=10089737" target="_blank">Alexandra Benő (<span class="authorship-author-name">Benő Alexandra Ágnes</span> <span class="authorAux-mtmt"> Cancer Genomics and Epigenetics</span>) </a> </span> <span class="author-affil"><span title="Magyar Molekuláris Medicina Kiválósági Központ (HCEMM) Nonprofit Kft.">HCEMM</span>/HCEMM Cancer Genomics and Epigenetcis Core Group</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10060864"><a href="/gui2/?type=authors&mode=browse&sel=10060864" target="_blank">Mihalekné Fűr Gabriella (<span class="authorship-author-name">Mihalekné Fűr Gabriella</span> <span class="authorAux-mtmt"> Biológia, SCLC, Pankreatológia</span>) </a> </span> <span class="author-affil"><span title="Magyar Molekuláris Medicina Kiválósági Központ (HCEMM) Nonprofit Kft.">HCEMM</span>/HCEMM Cancer Genomics and Epigenetcis Core Group</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10093937"><a href="/gui2/?type=authors&mode=browse&sel=10093937" target="_blank">Éva Magó (<span class="authorship-author-name">Magó Éva</span> <span class="authorAux-mtmt"> biológia</span>) </a> </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10093938"><a href="/gui2/?type=authors&mode=browse&sel=10093938" target="_blank">Petronella Topolcsányi (<span class="authorship-author-name">Goór-Topolcsányi Petronella</span> <span class="authorAux-mtmt"> SCLC, biológia</span>) </a> </span> <span class="author-affil"><span title="Magyar Molekuláris Medicina Kiválósági Központ (HCEMM) Nonprofit Kft.">HCEMM</span>/HCEMM Cancer Genomics and Epigenetcis Core Group</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10045334"><a href="/gui2/?type=authors&mode=browse&sel=10045334" target="_blank">Lőrinc Pongor (<span class="authorship-author-name">Pongor Lőrinc</span> <span class="authorAux-mtmt"> Bioinformatika</span>) </a> </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;35054097" target="_blank">PREDICTIVE INSIGHTS INTO DRUG RESPONSE: INTEGRATING PROTEOMICS AND GENE EXPRESSION WITH MACHINE LEARNING IN SMALL CELL LUNG CANCER</a></div> <div class="InBook"><div class="chapter-in">In:</div> <div class="authors"> </div> <div class="booktitle"><a href="/gui2/?mode=browse&params=publication;35000600" target="_blank">Conference on Pharmacology, Pharmacokinetics & Innovation (HUPHAR 2024) : Oral & Poster Abstracts </a></div> <div class="conference"> Konferencia helye, ideje: <span class="location">Mátraháza, Magyarország <span class="conference-date">2024.06.05. - 2024.06.07.</span> </div> : <span class="page"> pp 185-185 </span> <span class="year">(2024)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> </span> <span class="bookchapter-ids">Befoglaló link(ek):</span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="https://huphar.org/huphar2024/wp-content/uploads/2024/06/HUPHAR2024-Programfuzet-4.pdf" target="_blank" href="https://huphar.org/huphar2024/wp-content/uploads/2024/06/HUPHAR2024-Programfuzet-4.pdf"> Teljes dokumentum </a> </span> </span> <div class="mtid"><span class="long-pub-mtid">Közlemény: 35054097</span> | <span class="status-data status-APPROVED"> Nyilvános </span> <span class="long-book-mtid">Befoglaló: 35000600</span> Forrás | <span class="type-subtype">Egyéb konferenciaközlemény ( Absztrakt / Kivonat ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">kézi felvitel</span> </div> <div class="lastModified">Utolsó módosítás: 2024.07.31. 15:31 Mihalekné Fűr Gabriella (Biológia, SCLC, Pankreatológia) </div> </div> </div>