Detection of Immunotherapeutic Response in a Transgenic Mouse Model of Pancreatic Ductal Adenocarcinoma Using Multiparametric MRI Radiomics: A Preliminary Investigation.

使用多参数 MRI 放射组学检测胰腺导管腺癌转基因小鼠模型的免疫治疗反应: 初步研究。

  • 影响因子:2.00
  • DOI:10.1016/j.acra.2020.04.026
  • 作者列表:"Eresen A","Yang J","Shangguan J","Benson AB","Yaghmai V","Zhang Z
  • 发表时间:2020-06-01

RATIONALE AND OBJECTIVES:To develop classification and regression models interpreting tumor characteristics obtained from structural (T1w and T2w) magnetic resonance imaging (MRI) data for early detection of dendritic cell (DC) vaccine treatment effects and prediction of long-term outcomes for LSL-KrasG12D; LSL-Trp53R172H; Pdx-1-Cre (KPC) transgenic mice model of pancreatic ductal adenocarcinoma. MATERIALS AND METHODS:Eight mice were treated with DC vaccine for 3 weeks while eight KPC mice were used as untreated control subjects. The reproducibility of the computed 264 features was evaluated using the intraclass correlation coefficient. Key variables were determined using a three-step feature selection approach. Support vector machines classifiers were generated to differentiate treatment-related changes on tumor tissue following first- and third weeks of the DC vaccine therapy. The multivariable regression models were generated to predict overall survival (OS) and histological tumor markers of KPC mice using quantitative features. RESULTS:The quantitative features computed from T1w MRI data have better reproducibility than T2w MRI features. The KPC mice in treatment and control groups were differentiated with a longitudinally increasing accuracy (first- and third weeks: 87.5% and 93.75%). The linear regression model generated with five features of T1w MRI data predicted OS with a root-mean-squared error (RMSE) <6 days. The proposed multivariate regression models predicted histological tumor markers with relative error <2.5% for fibrosis percentage (RMSE: 0.414), CK19+ area (RMSE: 0.027), and Ki67+ cells (RMSE: 0.190). CONCLUSION:Our results demonstrated that proposed models generated with quantitative MRI features can be used to detect early treatment-related changes in tumor tissue and predict OS of KPC mice following DC vaccination.


原理和目的: 开发分类和回归模型,解释从结构 (T1w 和 T2w) 磁共振成像 (MRI) 数据获得的肿瘤特征,用于树突状细胞 (DC) 的早期检测 LSL-KrasG12D 疫苗治疗效果及远期疗效预测; LSL-Trp53R172H; Pdx-1-Cre (KPC) 转基因小鼠胰腺导管腺癌模型。 材料和方法: 8 只小鼠用 DC 疫苗治疗 3 周,8 只 KPC 小鼠作为未治疗对照。使用组内相关系数评价计算的 264 特征的再现性。使用三步特征选择方法确定关键变量。生成支持向量机分类器,以区分 DC 疫苗治疗第一周和第三周后肿瘤组织上的治疗相关变化。生成多变量回归模型,使用定量特征预测 KPC 小鼠的总生存期 (OS) 和组织学肿瘤标志物。 结果: T1w MRI 数据计算的定量特征具有比 T2w MRI 特征更好的再现性。治疗组和对照组中的 KPC 小鼠以纵向增加的准确性进行分化 (第一周和第三周: 87.5% 和 93.75%)。使用 T1w MRI 数据的 5 个特征生成的线性回归模型预测了 OS,均方根误差 (RMSE) <6 天。提出的多元回归模型预测纤维化百分比 (RMSE: 2.5%) 、 CK19 + 面积 (RMSE: 0.414) 和 Ki67 + 细胞 (RMSE: 0.027) 的相对误差 <的组织学肿瘤标志物 0.190)。 结论: 我们的结果证明,用定量 MRI 特征生成的建议模型可用于检测肿瘤组织的早期治疗相关变化,并预测 KPC 小鼠接种 DC 后的 OS。



作者列表:["Akula SM","Ruvolo PP","McCubrey JA"]

METHODS::Pancreatic ductal adenocarcinoma (PDAC) is a disease of aging. The TP53 gene product regulates cell growth, aging, and cancer. To determine the important targets of TP53 in PDAC, we examined the expression of 440 proteins on a reverse phase protein array (RPPA) in PDAC-derived MIA-PaCa-2 cells which either had WT-TP53 or lacked WT-TP53. MIA-PaCa-2 cells have a TP53 mutation as well as mutant KRAS and represent a good in vitro model to study PDAC. RPPA analysis demonstrated expression of tumor promoting proteins in cells that lacked WT-TP53; and this feature could be reversed significantly when the cells were transfected with vector encoding WT-TP53 or treated with berberine or a modified berberine (BBR). Expression of miR-34a-associated signaling was elevated in cells expressing WT-TP53 compared to cells expressing mTP53. Results from in vivo studies using human PDAC specimens confirmed the in vitro results as the expression of miR-34a and associated signaling was significantly decreased in PDAC specimens compared to non-cancerous tissues. This study determined SERPINE1 as a miR-34a target with relevance to the biology of PDAC. Thus, we have identified a key target (SERPINE1) of the TP53/miR-34a axis that may serve as a potential biomarker for early detection of pancreatic cancer.

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作者列表:["Kou L","Huang H","Lin X","Jiang X","Bao S","Luo Q","Sun J","Yao Q","Ganapathy V","Chen R"]

METHODS::Background: SLC6A14 (ATB0,+), a Na+/Cl-coupled transporter for neutral/cationic amino acids, is overexpressed in many cancers; It has been investigated as a target for improved liposomal drug delivery to treat liver cancer.Research design and methods: Here we explored the mechanism of ATB0,+-mediated entry of such liposomes. As ATB0,+ is highly-expressed in pancreatic cancer, we also examined the therapeutic utility of ATB0,+-targeted liposomal drug delivery to treat this cancer.Results: The uptake of lysine-conjugated liposomes (LYS-LPs) was greater in ATB0,+-positive MCF7 cells. The uptake process consisted of two steps: binding and internalization. The binding of LYS-LPs to MCF7 cells was higher than that of bare liposomes, and the process was dependent on Na+ and Cl-, and inhibitable by ATB0,+ substrates or blocker. In contrast, the internalization step was independent of lysine. The cellular entry of LYS-LPs facilitated by ATB0,+ occurred via endocytosis with transient endosomal degradation of ATB0,+ protein with subsequent recovery. Moreover, LYS-LPs also enhanced the uptake and cytotoxicity of gemcitabine in these cells in an ATB0,+-dependent manner.Conclusions: We conclude that ATB0,+ could be exploited for targeted drug delivery in the form of lysine-conjugated liposomes and that the approach represents a novel strategy for enhanced pancreatic cancer therapy.

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作者列表:["Okada KI","Kawai M","Hirono S","Kojima F","Tanioka K","Terada M","Miyazawa M","Kitahata Y","Iwahashi Y","Ueno M","Hayami S","Murata SI","Shimokawa T","Yamaue H"]

METHODS:PURPOSE:Pre-operative prediction of histological response to neoadjuvant therapy aids decisions regarding surgical management of borderline resectable pancreatic cancer (BRPC). We elucidate correlation between pre-/post-treatment whole-tumor apparent diffusion coefficient (ADC) value and rate of tumor cell destruction. We newly verify whether post-treatment ADC value at the site of vascular contact predicts R0 resectability of BRPC. METHODS:We prospectively reviewed 28 patients with BRPC who underwent diffusion-weighted magnetic resonance imaging before neoadjuvant chemotherapy and surgery. Correlation between the percentage of tumor cell destruction and various parameters was analyzed. Strong parameters were assessed for their ability to predict therapeutic histological response and R0 resectability. RESULTS:Pre-/post-treatment whole-tumor ADC value correlated with tumor cell destruction rate by all parameters (R = 0.630/0.714, P  50% was determined at 1.40 × 10-3 mm2/s. It predicts histological response with 100% sensitivity, 81% specificity, and 89% accuracy. It predicts R0 with 88% sensitivity, 70% specificity, and 75% accuracy. CONCLUSIONS:Post-treatment whole-tumor ADC value may be a predictor of R0 resectability in patients with BRPC. Tumor cell destruction rate is indicated by the difference between pre-/post-treatment ADC values. This difference is strongly affected by the pre-treatment ADC value. The cutoff value of ADC at the site of vascular contact could not discriminate R0 resectability.

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