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  • Review
  • Open Access

7 November 2026

19 Pages

Mapping the Epigenetic Regulatory Landscape and Core Transcriptional Axes Across Cell Cycle Phases in Lung Cancer

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1
Semillero de Investigación—Biología Molecular del Cáncer, Facultad de Medicina, Fundación Universitaria Sanitas, Bogotá 110131, Colombia
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Dirección Académica, Universidad Nacional de Colombia, Sede de La Paz, La Paz 111016, Colombia
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Grupo de Investigación INPAC, Specialized Laboratory, Clinica Universitaria Colombia, Clínica Colsanitas S.A., Bogotá 111321, Colombia
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Grupo de Investigación INPAC, Department of Internal Medicine, Clinica Universitaria Colombia, Clínica Colsanitas S.A., Bogotá 111321, Colombia

Abstract

Lung-cancer cell-cycle progression is shaped by interacting checkpoint, transcriptional, chromatin, and non-coding RNA regulatory layers rather than by isolated molecular alterations. This integrative review uses SMARCB1, NOC2L, CDCA4, and CHEK1 as four complementary anchor regulators representing SWI/SNF-dependent chromatin remodeling, inhibition of histone acetyltransferase activity, E2F-linked transcriptional modulation, and checkpoint signaling, respectively. We critically map their literature-supported relationships across G1, S, G2, and M and integrate DNA and histone methylation, acetylation, chromatin remodeling, phosphorylation, ubiquitination, hydroxylation, and non-coding RNA regulation. Importantly, lung-cancer-specific evidence is distinguished from evidence extrapolated from other tumor models, and experimentally established mechanisms are separated from contextual or hypothesis-generating phase assignments. The strongest lung-specific evidence concerns CHEK1 dependence, replication stress, and chromatin-state plasticity, whereas several proposed phase-specific functions of NOC2L, CDCA4, and SMARCB1 remain incompletely validated in lung cancer. Recent 2026 studies further emphasize subtype-specific CHEK1 biology, therapy-associated chromatin reprogramming, and long non-coding RNA control. This framework identifies testable regulatory hypotheses while avoiding interpretation of network association as direct causality.

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