Effect of Hypoxia in the Transcriptomic Profile of Lung Fibroblasts from Idiopathic Pulmonary Fibrosis (vol 11, 3014, 2022)
Por:
Romero, Y, Balderas-Martínez, YI, Vargas-Morales, MA, Castillejos-López, M, Vázquez-Pérez, JA, Calyeca, J, Torres-Espíndola, LM, Patiño, N, Camarena, A, Carlos-Reyes, A, Flores-Soto, E, León-Reyes, G, Sierra-Vargas, MP, Herrera, I, Luis-García, ER, Ruiz, V, Velázquez-Cruz, R, Aquino-Gálvez, A
Publicada:
1 jul 2026
Resumen:
© 2026 by the authors.An error occurred in the original publication [1] due to incorrect identification of the hypoxia and normoxia samples, resulting from an erroneous assignment of experimental conditions in our bioinformatics process. Since all subsequent steps—differential expression analysis, expression change estimation (log2), and metabolic pathway enrichment—depended on this metadata, the underlying read counts and statistical significance for each gene are correct, but the two conditions were systematically interchanged. Consequently, it was necessary to swap the terms “upregulated” and “downregulated” in the affected passages of the corrected version. We sincerely regret this error and offer our deepest apologies for any confusion or inconvenience it may have caused our readers and the scientific community. We remain firmly committed to maintaining the accuracy of the scientific record. To ensure clarity, the specific corrections are detailed below. Abstract: Idiopathic pulmonary fibrosis (IPF) is an aging-associated disease characterized by exacerbated extracellular matrix deposition that disrupts oxygen exchange. Hypoxia and its transcription factors (HIF-1a and 2a) influence numerous circuits that could perpetuate fibrosis by increasing myofibroblast differentiation and by promoting extracellular matrix accumulation. Therefore, this work aimed to elucidate the signature of hypoxia in the transcriptomic circuitry of IPF-derived fibroblasts. To determine this transcriptomic signature, a gene expression analysis with six lines of lung fibroblasts under normoxia or hypoxia was performed; three cell lines were derived from patients with IPF, and three were from healthy donors, obtaining a total of 36 replicates. We used the Clariom D platform, which allows us to evaluate a huge number of transcripts, to analyze the response to hypoxia in both controls and IPF. The controls’ response is greater by the number of genes and complexity. In the search for specific genes responsible for the IPF fibroblast phenotype, nineteen dysregulated genes were found in lung fibroblasts from IPF patients in hypoxia (nine down-regulated and ten up-regulated). In this sense, the signaling pathways revealed to be affected in the pulmonary fibroblasts of patients with IPF may represent an adaptation to chronic hypoxia. Network analysis using Ingenuity Pathway Software (IPA) shows a transcriptomic landscape in normal fibroblasts during hypoxia revealing metabolic changes regulated by HIF-1a (Figure 3A,B). These changes showed a central role of HIF-1a in YTH N6-Methyladenosine RNA Binding Protein 2 (YTHDF2)-mediated cell cycle regulation which promotes mRNA decay during the cell cycle in somatic reprogramming (Figure 3A). Consistent with that, TP53, a master cell cycle regulator implicated in aging, senescence, and fibrosis, was down-regulated (Figure 3C). The radial diagram of TP53 and its targets reveals its central role in the regulation of autophagy-related processes (ATG4a and ATG4b), topological stress (TOP2B), glycolysis (TIGAR), and insulin-like growth factor regulation (IGF) and transport and uptake by insulin-like growth factor binding proteins (PAPPA). In summary, controls have a complex network involving more genes in the hypoxia adaptation and antagonistic mechanisms such as autophagy regulation. IPA also identified alterations in the AKT signaling in IPF; AKT can negatively regulate autophagy in the opposite direction to controls (Figure 3D). A third Venn diagram was constructed to identify the transcriptional signature with dysregulated genes shared between the controls and IPF (Figure 7A). Of the three groups of genes analyzed, the first group contained genes that belong to the adaptation hypoxia response in controls (311); the analysis coincides with those that were made as a whole by condition and cell line. As these pathways are not found in IPF fibroblasts, they provide us with information that could help elucidate the mechanisms of IPF pathogenesis since, for some reason, they have been lost or blocked. In the second group, only 35 genes were found altered in both; these genes are involved in hypoxia and mesenchymal pathways. Finally, the genes that are induced by hypoxia are shared in different cell lines from IPF. Tables 2 and 3 show the 19 DEGs, divided into up- and down-regulated; there are some similarities in the four up-regulated genes in our study because previous studies in IPF report them up-regulated, and this is the case with Coagulation factor III (F3), Hedgehog interacting protein (HHIP), Interleukin 6 (IL-6), and Stanniocalcin 1 (STC1) (Table 2). Five genes were identified to be up-regulated, that have not been studied in IPF, which are Cyclin G2 (CCNG2), Potassium Channel Tetramerization Domain Containing 16 (KCTD16), Basic helix-loop-helix family member e41 (BHLHE41), Syntaxin binding protein 6 (STXBP6), and Serpin family B member 7 (SERPINB7) (Table 2). Nine genes were found down-regulated, of which four genes have been previously related to IPF: Endothelial PAS domain protein 1 (EPAS1), Transferrin receptor (TFRC), Endothelin receptor type A (EDNRA) and Periostin (POSTN). The other five genes have not been associated with IPF: the Alcohol dehydrogenase 1B (ADH1B), Protocadherin 18 (PCDH18), Homeobox A5 (HOXA5), Solute carrier family 14-member 1 (SLC14A1), and Ubiquitin specific peptidase 18 (USP18) (Table 3). Pathways in IPF fibroblasts that are not shared with healthy cells are pathways that could help us begin to guide potential therapeutic targets. In the case of fibroblasts from patients with IPF, low levels of EPAS (HIF-2a) suggest that it plays an essential role in this chronic adaptation to hypoxia. In the original publication, there was a mistake in Figure 2A–D, as published. As up or down regulation is inverted. The corrected Figure 2 appears below. We revised the Figure 2 legend in response to the Academic Editor’s comments. As part of this revision and fo
Filiaciones:
Univ Nacl Autonoma Mexico, Fac Ciencias, Mexico City 04510, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Lab Biol Computac, Mexico City 14080, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Lab Biol Mol, Dept Fibrosis Pulm, Mexico City 14080, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Dept Epidemiol & Estadist, Mexico City 14080, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Lab Biol Mol Enfermedades Emergentes & EPOC, Mexico City 14080, Mexico
Ohio State Univ, Davis Heart & Lung Res Inst, Dept Internal Med, Div Pulm Crit Care & Sleep Med, Columbus, OH 43210 USA
Inst Nacl Pediat INP, Lab Farmacol, Mexico City 04530, Mexico
Inst Nacl Med Genomica INMEGEN, Undad Citometria Flujo UCiF, Mexico City 14610, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Lab HLA, Mexico City 14080, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Lab Onco Inmunobiol, Dept Enfermedades Cron Degenerat, Mexico City 14080, Mexico
Univ Nacl Autonoma Mexico, Fac Med, Dept Farmacol, Mexico City 04510, Mexico
Inst Nacl Med Genomica INMEGEN, Lab Genom Metab Oseo, Mexico City 14610, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Dept Invest Toxicol & Med Ambiental, Mexico City 14080, Mexico
Inst Nacl Enfermedades Resp Ismael Cosio Villegas, Lab Biol Celular, Dept Fibrosis Pulm, Mexico City 14080, Mexico
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