RESUMEN
BACKGROUND: Cholesteryl ester (CE) accumulation in intracellular lipid droplets (LDs) is an essential signature of clear cell renal cell carcinoma (ccRCC), but its molecular mechanism and pathological significance remain elusive. METHODS: Enabled by the label-free Raman spectromicroscopy, which integrated stimulated Raman scattering microscopy with confocal Raman spectroscopy on the same platform, we quantitatively analyzed LD distribution and composition at the single cell level in intact ccRCC cell and tissue specimens in situ without any processing or exogenous labeling. Since we found that commonly used ccRCC cell lines actually did not show the CE-rich signature, primary cancer cells were isolated from human tissues to retain the lipid signature of ccRCC with CE level as high as the original tissue, which offers a preferable cell model for the study of cholesterol metabolism in ccRCC. Moreover, we established a patient-derived xenograft (PDX) mouse model that retained the CE-rich phenotype of human ccRCC. FINDINGS: Surprisingly, our results revealed that CE accumulation was induced by tumor suppressor VHL mutation, the most common mutation of ccRCC. Moreover, VHL mutation was found to promote CE accumulation by upregulating HIFα and subsequent PI3K/AKT/mTOR/SREBPs pathway. Inspiringly, inhibition of cholesterol esterification remarkably suppressed ccRCC aggressiveness in vitro and in vivo with negligible toxicity, through the reduced membrane cholesterol-mediated downregulations of integrin and MAPK signaling pathways. INTERPRETATION: Collectively, our study improves current understanding of the role of CE accumulation in ccRCC and opens up new opportunities for treatment. FUNDING: This work was supported by National Natural Science Foundation of China (No. U23B2046 and No. 62027824), National Key R&D Program of China (No. 2023YFC2415500), Fundamental Research Funds for the Central Universities (No. YWF-22-L-547), PKU-Baidu Fund (No. 2020BD033), Peking University First Hospital Scientific and Technological Achievement Transformation Incubation Guidance Fund (No. 2022CX02), and Beijing Municipal Health Commission (No. 2020-2Z-40713).
Asunto(s)
Carcinoma de Células Renales , Ésteres del Colesterol , Neoplasias Renales , Mutación , Fosfatidilinositol 3-Quinasas , Proteínas Proto-Oncogénicas c-akt , Transducción de Señal , Proteína Supresora de Tumores del Síndrome de Von Hippel-Lindau , Animales , Humanos , Ratones , Carcinoma de Células Renales/genética , Carcinoma de Células Renales/metabolismo , Carcinoma de Células Renales/patología , Línea Celular Tumoral , Ésteres del Colesterol/metabolismo , Modelos Animales de Enfermedad , Progresión de la Enfermedad , Neoplasias Renales/metabolismo , Neoplasias Renales/genética , Neoplasias Renales/patología , Fosfatidilinositol 3-Quinasas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Proteína Supresora de Tumores del Síndrome de Von Hippel-Lindau/genética , Proteína Supresora de Tumores del Síndrome de Von Hippel-Lindau/metabolismoRESUMEN
BACKGROUND: Viruses are critical for the regulation of cancer development and for therapy. Human adenovirus C (HadVC) has been detected in central nervous system and glioma tissue. The objective of the present study was the development of a robust prognostic model based on HadVC infection (HadVCi)-relevant genes. METHODS: The genome, transcriptome, and virome were systemically analyzed using The Cancer Genome Atlas dataset for training and 2 cohorts from the Chinese Glioma Genome Atlas and an immunotherapy trial cohort with 17 patients receiving anti-PD-1 treatment for validation. HadVCi-relevant gene selection from differentially expressed genes between HadVC-infected and non-HadVC-infected glioma patients using least absolute shrinkage and selection operator regression was followed by Cox regression modeling to establish a prognostic HadVCi score. Kaplan-Meier and receiver operating characteristic curve analyses were performed to estimate the predictive capacity of the HadVCi score. The χ2, Spearman, and Mann-Whitney U tests were used to identify the correlation with the clinicopathological parameters, treatment responsiveness, and immune landscape. Temozolomide-resistant glioma cells were established and analyzed at the transcriptional level using RNA sequencing data. RESULTS: The HadVCi score was (-0.2526673∗TRPC6) + (-0.2244276∗RNF207) + (-0.0894468∗SEC31B) + (-0.0190214∗ZCRB1) + (-0.017122∗DNPH1) + (0.0495818∗CCDC34) + (0.1196349∗PURG) + (0.1778997∗LILRA5). The score possesses a strong ability to predict overall survival. Further analysis revealed a higher HadVCi score correlated with a malignant phenotype and poorer treatment responsiveness to temozolomide-based chemotherapy and combined therapies. Additionally, transcriptomic analysis showed malignancy-, stemness-, and radioresistant-related gene activation in the HadVCi group, which characterized the poor outcomes and limited sensitivity to standard therapy. CONCLUSIONS: The HadVCi score could be an effective tool for survival prediction and treatment guidance for patients with glioma.