STL1267 Inhibits Myofibroblast Differentiation in a TGFß1-Driven Human Lung Fibroblast Model

Pulmonary fibrosis is a progressive interstitial lung disease characterized by excessive fibroblast-to-myofibroblast transition (FMT) and extracellular matrix (ECM) deposition, largely driven by transforming growth factor-beta 1 (TGFß1). Existing therapies offer limited efficacy, particularly in advanced disease. Circadian rhythms have recently emerged as key modulators of lung inflammation and fibrosis. In this study, we developed an in vitro model of chronic fibrotic signaling using adenovirus-mediated TGFß1 overexpression (Ad-TGFß1) or human recombinant protein TGFß1 in primary human lung fibroblasts. Using this model, we investigated the antifibrotic potential of STL1267, a next-generation Rev-erba agonist with improved potency, specificity, and pharmacokinetic properties. RNA sequencing and pathway analysis revealed that STL1267 significantly reversed Ad-TGFß1-induced expression of genes associated with ECM remodeling, collagen biosynthesis, and immune suppression. STL1267 also upregulated pathways related to IL-10, IL-4, and IL-13 signaling, which are known to counteract fibrotic responses. Quantitative PCR and immunoblotting confirmed STL1267's ability to downregulate key pro-fibrotic markers, including COL1A1, aSMA, FN1, and FAP, at both gene and protein levels. Comparative studies with other Rev-erba agonists (GSK4112, SR9009), Saracatinib, and FDA-approved antifibrotic drugs (Pirfenidone, Nintedanib) demonstrated superior efficacy of STL1267 in inhibiting both preventive and post-fibrotic induction models. Moreover, lentiviral overexpression of Rev-erba suppressed TGFß1-induced aSMA expression, supporting a direct antifibrotic role. These findings highlight Rev-erba as a key regulator of myofibroblast differentiation and support both STL1267 and GSK4112 as promising candidates for circadian-based antifibrotic therapy. Future in vivo studies are warranted to evaluate its translational potential in idiopathic pulmonary fibrosis. Overall design: Stranded mRNA sequencing was performed using the Illumina NovaSeq 6000 Sequencing System. Total RNA quality was assessed using the Agilent TapeStation 4200 with the RNA ScreenTape Assay kit (Agilent Technologies, 5067-5576). Library preparation was conducted using the Universal Plus mRNA-Seq with NuQuant stranded mRNA library preparation protocol (Tecan Genomics, 0520-A01), starting with 500 ng of total RNA. The mRNA fraction was enriched via oligo dT bead capture, followed by fragmentation, reverse transcription into cDNA, end repair, ligation of Unique Dual Index (UDI) adaptors, strand selection, and library amplification (12 cycles) using a Bio-Rad S1000 thermal cycler. Library validation was performed using the Agilent TapeStation 4200 with the D1000 ScreenTape Assay kit (Agilent Technologies, 5067-5582). Library concentrations were determined using the NuQuant module of the library prep kit and measured with a Qubit 4 Fluorometer (ThermoFisher/Invitrogen). Libraries were normalized to a final concentration of 1.9 nM, pooled, and quantified in triplicate using the LightCycler 96 (Roche) with FastStart Essential DNA Green Master (Roche, 06402712001) and KAPA Library Quantification DNA Standards 1-6 (KAPA Biosystems, KK4903). The pooled libraries were then denatured with 0.2N NaOH (final concentration: 0.04N), neutralized with 400 mM Tris-HCl (pH 8.0), and diluted to 380 pM for onboard clonal clustering on a patterned flow cell using the NovaSeq 6000 S1 Reagent Kit v1.5 – 200 cycle (Illumina, 20028318). Sequencing was performed using a 2 × 101 cycle format with dual index reads as follows: Read 1 – 101 cycles, Index Read 1 – 8 cycles, Index Read 2 – 8 cycles, and Read 2 – 101 cycles. Following sequencing, raw data was converted from .bcl to fastq format using the bcl2fastq software and demultiplexed into individual sample sequences. Data were distributed via a secure FTP site or Illumina BaseSpace for downstream analysis.

肺纤维化（Pulmonary fibrosis）是一种进行性间质性肺病（interstitial lung disease），特征为成纤维细胞向肌成纤维细胞转化（fibroblast-to-myofibroblast transition, FMT）过度以及细胞外基质（extracellular matrix, ECM）沉积，其主要驱动因素为转化生长因子-β1（transforming growth factor-beta 1, TGF-β1）。现有治疗手段的疗效有限，尤其在疾病晚期阶段。近年来，昼夜节律（circadian rhythms）被证实是肺部炎症与纤维化的关键调控因子。本研究通过腺病毒介导的TGF-β1过表达（adenovirus-mediated TGF-β1 overexpression, Ad-TGF-β1）或使用人重组TGF-β1蛋白处理原代人肺成纤维细胞（primary human lung fibroblasts），构建了慢性纤维化信号通路的体外模型。利用该模型，本研究探究了新一代Rev-erbα激动剂STL1267的抗纤维化潜力，该化合物的效能、特异性及药代动力学特性均得到优化。RNA测序（RNA sequencing）与通路分析（pathway analysis）结果显示，STL1267可显著逆转Ad-TGF-β1诱导的、与细胞外基质重塑、胶原蛋白生物合成及免疫抑制相关的基因表达。STL1267还可上调与IL-10、IL-4及IL-13信号通路相关的基因集，而上述通路已知可拮抗纤维化反应。实时定量PCR（quantitative PCR, qPCR）与免疫印迹（immunoblotting）实验证实，STL1267可在基因与蛋白水平下调COL1A1、αSMA、FN1及FAP等关键促纤维化标志物。与其他Rev-erbα激动剂（GSK4112、SR9009）、萨拉卡替尼（Saracatinib）以及美国FDA获批的抗纤维化药物吡非尼酮（Pirfenidone）、尼达尼布（Nintedanib）的对比研究表明，STL1267在预防性及治疗性纤维化诱导模型中均表现出更优的疗效。此外，慢病毒（lentiviral）介导的Rev-erbα过表达可抑制TGF-β1诱导的αSMA表达，进一步证实了Rev-erbα发挥直接抗纤维化作用。上述研究结果凸显Rev-erbα是肌成纤维细胞分化的关键调控因子，并支持STL1267与GSK4112均可作为基于昼夜节律的抗纤维化治疗的潜在候选药物。后续需开展体内实验以评估其在特发性肺纤维化（idiopathic pulmonary fibrosis, IPF）中的转化应用潜力。整体实验设计：采用Illumina NovaSeq 6000测序系统完成链特异性mRNA测序（stranded mRNA sequencing）。总RNA质量通过Agilent TapeStation 4200与RNA ScreenTape检测试剂盒（Agilent Technologies, 5067-5576）进行评估。文库制备采用Universal Plus mRNA-Seq带NuQuant链特异性mRNA文库制备流程（Tecan Genomics, 0520-A01），起始总RNA用量为500 ng。通过寡聚dT磁珠（oligo dT bead）富集mRNA组分，随后依次进行片段化、反转录为cDNA、末端修复、连接唯一双索引（Unique Dual Index, UDI）接头、链选择，以及使用Bio-Rad S1000热循环仪完成12个循环的文库扩增。文库验证采用Agilent TapeStation 4200与D1000 ScreenTape检测试剂盒（Agilent Technologies, 5067-5582）。文库浓度通过文库制备试剂盒的NuQuant模块测定，并使用Qubit 4荧光计（ThermoFisher/Invitrogen）完成定量。将文库归一化至终浓度1.9 nM后混合，采用LightCycler 96（Roche）结合FastStart Essential DNA Green Master（Roche, 06402712001）与KAPA文库定量DNA标准品1-6（KAPA Biosystems, KK4903）进行三次重复定量。混合文库经0.2N NaOH变性（终浓度为0.04N）后，用400 mM Tris-HCl（pH 8.0）中和，并稀释至380 pM，使用NovaSeq 6000 S1 Reagent Kit v1.5 – 200 cycle（Illumina, 20028318）在patterned flow cell（图案化流动池）上完成上机克隆聚类。测序采用2×101循环双索引模式，具体参数如下：Read 1 – 101循环，Index Read 1 – 8循环，Index Read 2 – 8循环，Read 2 – 101循环。测序完成后，使用bcl2fastq软件将原始数据从.bcl格式转换为fastq格式，并进行双端拆分得到各样本的独立序列。数据通过安全FTP站点或Illumina BaseSpace分发至下游分析环节。