{"id":1858,"date":"2026-04-03T09:29:44","date_gmt":"2026-04-03T06:29:44","guid":{"rendered":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/?p=1858"},"modified":"2026-04-03T11:11:45","modified_gmt":"2026-04-03T08:11:45","slug":"new-publication-lamprou-s-et-al-2026-current-issues-in-molecular-biology","status":"publish","type":"post","link":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/new-publication-lamprou-s-et-al-2026-current-issues-in-molecular-biology\/","title":{"rendered":"New Publication Lamprou S. et al. 2026 Current Issues in Molecular Biology"},"content":{"rendered":"<p>Predicting neoadjuvant chemotherapy response in breast cancer remains critical for optimizing treatment strategies, yet robust predictive biomarkers are lacking. This study implemented an ensemble machine learning approach to identify a gene expression signature predicting pathological complete response (pCR) versus residual disease (RD) using bulk RNA-sequencing data from GSE163882 (138 RD, 80 pCR). We employed TMM normalization with differential expression analysis (250 genes, FDR &lt; 0.05, |log2FC| \u2265 1), ensemble feature selection across five classifiers (Random Forest, Gradient Boosting, SVM, k-NN, and Neural Network) with 10-fold repeated cross-validation, and stacked ensemble development. Consensus selection identified a 17-gene signature consistently ranked across algorithms. <a href=\"https:\/\/doi.org\/10.3390\/cimb48010094\" target=\"_blank\" rel=\"noopener\">Read more<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Predicting neoadjuvant chemotherapy response in breast cancer remains critical for optimizing treatment strategies, yet robust predictive biomarkers are lacking. This study implemented an ensemble machine learning<span class=\"excerpt-hellip\"> [\u2026]<\/span><\/p>\n","protected":false},"author":676,"featured_media":1859,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_lmt_disableupdate":"no","_lmt_disable":"","footnotes":""},"categories":[46],"tags":[],"class_list":["post-1858","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-events"],"modified_by":"kelvege","publishpress_future_action":{"enabled":false,"date":"2026-06-17 04:46:14","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/posts\/1858","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/users\/676"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/comments?post=1858"}],"version-history":[{"count":2,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/posts\/1858\/revisions"}],"predecessor-version":[{"id":1867,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/posts\/1858\/revisions\/1867"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/media\/1859"}],"wp:attachment":[{"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/media?parent=1858"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/categories?post=1858"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ucy.ac.cy\/cancer-biophysics\/wp-json\/wp\/v2\/tags?post=1858"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}