Proteomic Identification of Transgelin as a Prognostic and Therapeutic Biomarker of Kidney Fibrosis = 단백체학을 통해 발견한 신장 섬유화 예후 예측 및 치료 표적으로서의 Transgelin의 역할 규명

다국어 초록 (Multilingual Abstract)

The progression of chronic kidney disease is closely dissociated with tubulointerstitial fibrosis, marked by excessive accumulation of extracellular matrix. However, current diagnostic biomarkers have limitations in accurately reflecting the extent of kidney fibrosis. To discover potential biomarkers for kidney fibrosis, mass spectrometry-based proteomic profiling using human kidney tubular epithelial cells and kidney tissue from a 5/6 nephrectomy rat model was performed.
Mass spectrometry-based proteomic analysis was performed on transforming growth factor β-induced human-derived tubular epithelial cells and kidney tissue from a 5/6 nephrectomy (5/6 Nx) rat model. Integrative analysis across cellular and animal renal fibrosis models identified 351 differentially expressed proteins showing concurrent changes were identified. Among these, 69 proteins associated with the extracellular matrix, aging, and mitochondria were selected for gene set enrichment analysis. After then, network analysis highlighted five key proteins (transgelin, acyl-CoA dehydrogenase medium chain, G elongation factor mitochondrial 1, secreted protein acidic and rich incysteine, and translation elongation factor mitochondrial), among which transgelin stood out due to its interactions with known fibrosis-related proteins.
The utility of transgelin as a novel biomarker for kidney fibrosis was further validated. Transgelin gene expression was elevated in kidney tissue from the 5/6 nephrectomy model. Consistently, transgelin expression in kidney tissue progressively increased from intermediate to advanced stages of fibrosis in both the 5/6 nephrectomy rat model and the unilateral ureteral obstruction mouse model. Validation using kidney tissue and urine samples from chronic kidney disease patients confirmed transgelin upregulation, particularly in advanced disease stages. Furthermore, inhibition of transgelin in cellular models alleviated fibrosis and reduced reactive oxygen species levels.
In conclusion, the current approach identified transgelin as a promising noninvasive biomarker and therapeutic target for kidney fibrosis, implicating its role in mitochondrial dysfunction and oxidative stress regulation.

국문 초록 (Abstract)

만성 콩팥병의 진행은 과도한 세포외기질 축적을 특징으로 하는 신장 섬유화와 밀접하게 관련되어 있다. 신장 섬유화의 잠재적 바이오마커를 발굴하기 위해, 인간 유래 신장 세뇨관 상피세포와 5/6 신장 절제 랫드 모델의 신장 조직을 대상으로 질량분석 기반 단백질체학 분석을 시행했다.
세포 및 동물 신장 섬유화 모델을 통합 분석한 결과, 동시에 변화하는 351개의 차등 발현 단백질이 확인되었다. 유전자 집합 풍부도 분석을 이용하여 그 중 세포외기질, 노화, 미토콘드리아와 관련된 69개의 단백질을 일차 선별하였다. 이후 네트워크 분석을 통해 5개(transgelin, acyl-CoA dehydrogenase medium chain, G elongation factor mitochondrial 1, secreted protein acidic and rich incysteine, and translation elongation factor mitochondrial)의 핵심 단백질 도출되었으며, 이 중 transgelin은 기존 보고된 섬유화 관련 단백질들과 상호작용이 많아 후보 단백질로 주목받았다.
Transgelin의 신장 섬유화 바이오마커로서의 유용성을 추가 검증 실험을 하였다. 5/6 신장절제 모델의 신장 조직에서 transgelin 유전자 발현이 증가하였다. 5/6 신장절제 랫드 모델과 일측 요관 폐쇄 마우스 모델의 신장 조직 모두에서 섬유화가 중등도에서 고도 단계로 진행됨에 따라 transgelin 발현이 점진적으로 증가하였다. 만성 콩팥병 환자의 신장 조직 및 소변 샘플을 통한 검증에서도 만성 콩팥병 진행에 따라 transgelin 발현 증가가 확인되었다. 또한, 세포 모델에서 transgelin을 억제했을 때 섬유화가 완화되고 활성산소 수준이 감소하는 효과도 관찰되었다.
결론적으로, 본 연구는 transgelin을 만성 콩팥병에서 발생하는 신장 섬유화의 유망한 비침습적 바이오마커이자 치료 표적으로 제시하며, transgelin이 미토콘드리아 기능 장애 및 산화 스트레스 조절에 관여할 가능성을 제시한다.

목차 (Table of Contents)

• List of Tables 6
• List of Figures 7
• Chapter 1. Introduction 8
• Chapter 2. Materials and Methods 11
• 2.1 Overview of the experimental workflow 11
• 2.2 Cellular model: human primary tubular epithelial cells 13
• 2.3 Animal model: 5/6 nephrectomy rat model 14
• 2.4 Animal model: unilateral obstruction mouse model 15
• 2.5 Human kidney biopsy and urine samples 18
• 2.6 Proteomics sample preparation and analysis 20
• 2.7 Molecular analysis techniques 22
• 2.8 Statistical analysis 27
• Chapter 3. Results 28
• 3.1 Differentially expressed proteins in cellular model 28
• 3.2 Differentially expressed proteins in animal model 31
• 3.3 Integrated analysis of differentially expressed proteins between cellular and animal models 34
• 3.4 Network analysis of key proteins associated with kidney fibrosis 37
• 3.5 Validation of mRNA expression for selected fibrosis-associated proteins from proteomics 40
• 3.6 Elevated TAGLN expression in kidney tissue of 5/6 Nx rat model and UUO model 43
• 3.7 TAGLN expression in kidney biopsy tissue and urine of patients with CKD 44
• 3.8 Therapeutic potential of TAGLN inhibition in fibrosis and oxidative stress in hTECs 49
• Chapter 4. Discussion 50
• Bibliography 50
• Abstract in Korean 64