Haematopathology Division, European Institute of Oncology (IEO) Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy.
Nuclear Medicine Division, IEO IRCCS, Milan, Italy.
Blood Adv. 2023 Feb 28;7(4):630-643. doi: 10.1182/bloodadvances.2022007825.
Emerging evidence indicates that chemoresistance is closely related to altered metabolism in cancer. Here, we hypothesized that distinct metabolic gene expression profiling (GEP) signatures might be correlated with outcome and with specific fluorodeoxyglucose positron emission tomography (FDG-PET) radiomic profiles in diffuse large B-cell lymphoma (DLBCL). We retrospectively analyzed a discovery cohort of 48 consecutive patients with DLBCL treated at our center with standard first-line chemoimmunotherapy by performing targeted GEP (T-GEP)- and FDG-PET radiomic analyses on the same target lesions at baseline. T-GEP-based metabolic profiling identified a 6-gene signature independently associated with outcomes in univariate and multivariate analyses. This signature included genes regulating mitochondrial oxidative metabolism (SCL25A1, PDK4, PDPR) that were upregulated and was inversely associated with genes involved in hypoxia and glycolysis (MAP2K1, HIF1A, GBE1) that were downregulated. These data were validated in 2 large publicly available cohorts. By integrating FDG-PET radiomics and T-GEP, we identified a radiometabolic signature (RadSig) including 4 radiomic features (histo kurtosis, histo energy, shape sphericity, and neighboring gray level dependence matrix contrast), significantly associated with the metabolic GEP-based signature (r = 0.43, P = .0027) and with progression-free survival (P = .028). These results were confirmed using different target lesions, an alternative segmentation method, and were validated in an independent cohort of 64 patients. RadSig retained independent prognostic value in relation to the International Prognostic Index score and metabolic tumor volume (MTV). Integration of RadSig and MTV further refined prognostic stratification. This study provides the proof of principle for the use of FDG-PET radiomics as a tool for noninvasive assessment of cancer metabolism and prognostic stratification in DLBCL.
新出现的证据表明，化疗耐药性与癌症中代谢的改变密切相关。在这里，我们假设不同的代谢基因表达谱（GEP）特征可能与结局以及弥漫性大 B 细胞淋巴瘤（DLBCL）的特定氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）放射组学特征相关。我们通过在基线时对相同靶病变进行靶向 GEP（T-GEP）和 FDG-PET 放射组学分析，对在我们中心接受标准一线化疗免疫治疗的 48 例连续 DLBCL 患者的发现队列进行了回顾性分析。基于 T-GEP 的代谢分析确定了一个 6 基因特征，该特征在单变量和多变量分析中与结局独立相关。该特征包括调节线粒体氧化代谢的基因（SCL25A1、PDK4、PDPR），这些基因上调，与缺氧和糖酵解相关的基因（MAP2K1、HIF1A、GBE1）下调呈负相关。这些数据在 2 个大型公开可用队列中得到了验证。通过整合 FDG-PET 放射组学和 T-GEP，我们确定了一个包括 4 个放射组学特征（直方图峰度、直方图能量、形状球形度和相邻灰度依赖矩阵对比度）的放射代谢特征（RadSig），与基于代谢 GEP 的特征显著相关（r=0.43，P=0.0027），与无进展生存期（P=0.028）相关。使用不同的靶病变、替代分割方法验证了这些结果，并在 64 例患者的独立队列中进行了验证。RadSig 与国际预后指数评分和代谢肿瘤体积（MTV）相关，具有独立的预后价值。RadSig 和 MTV 的整合进一步细化了预后分层。这项研究为使用 FDG-PET 放射组学作为非侵入性评估 DLBCL 中癌症代谢和预后分层的工具提供了原理证明。
