{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T15:29:29Z","timestamp":1788881369758,"version":"build-2803163510"},"reference-count":27,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T00:00:00Z","timestamp":1784678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Syst. Biol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Carcinogenesis involves two major phases: somatic evolution of normal tissue toward tumor formation, followed by tumor progression toward malignancy. Standard differential expression analysis cannot assign genes specifically to either phase. We introduce N- and T-genes with exclusive expression intervals for normal tissue and tumors, respectively, as markers that could potentially map these dynamics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Using TCGA RNA-Seq data from prostate adenocarcinoma (PRAD), lung adenocarcinoma (LUAD) and liver hepatocellular carcinoma (LIHC), we identify N- and T-genes through statistically significant expression intervals exclusive to normal or tumor samples, respectively. We discretize expression into three states (\n                      <jats:italic>e<\/jats:italic>\n                      = \u22121, 0, +1) and count the number of active N-genes in normal samples and active T-genes in tumor samples. Under an ergodic assumption, these counts correlates with pseudo-temporal coordinates for somatic evolution and tumor progression, respectively. We construct complete gene panels (100% sensitive and 100% specific within the training set) using a previously defined algorithm, and perform a molecular taxonomy of normal and tumor samples based on these panels.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Across different cancer types, normal and tumor samples occupy two well-separated attractors in gene-expression space, giving rise to large sets of N- and T-genes. The number of active N-genes decreases continuously as samples move away from the normal attractor, whereas the number of active T-genes increases as samples progress towards the tumor attractor. Large blocks of N-genes are observed, suggesting coordinated multi-gene deactivation events. The combination of staging through the number of active genes with the molecular taxonomy based on panel genes provides a complete description of the somatic evolution of a normal tissue and the progression towards malignancy of tumors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The N- and T-gene framework provides a natural decomposition of carcinogenesis into somatic evolution (loss of N-gene activity) and tumor progression (gain of T-gene activity). Active N- and T-gene counts can be interpreted as tally marks of somatic evolution and tumor progression, respectively, while complete gene panels enable a taxonomy of samples and helps identifying the biological programs active in each sample. The framework is general and applicable across cancer types, although quantitative results depend on the underlying dataset.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fsysb.2026.1845582","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T04:39:25Z","timestamp":1784695165000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Mapping cancer dynamics from normal tissue to malignancy using N- and T-gene expression markers"],"prefix":"10.3389","volume":"6","author":[{"given":"Gabriel","family":"Gil","sequence":"first","affiliation":[{"name":"Institute of Cybernetics, Mathematics and Physics","place":["Havana, Cuba"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rolando","family":"Perez","sequence":"additional","affiliation":[{"name":"Center for Molecular Immunology","place":["Havana, Cuba"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Augusto","family":"Gonzalez","sequence":"additional","affiliation":[{"name":"Institute of Cybernetics, Mathematics and Physics","place":["Havana, Cuba"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,22]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1088\/0034-4885\/50\/7\/001","article-title":"Theory of first-order phase transitions","volume":"50","author":"Binder","year":"1987","journal-title":"Rep. 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