Desmoplastic stromal signatures predict patient outcomes in pancreatic ductal adenocarcinoma.
Desmoplastic stromal signatures predict patient outcomes in pancreatic ductal adenocarcinoma.
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促结缔组织增生性间质特征可预测胰腺导管腺癌患者的预后。
DOI：
10.1016/j.xcrm.2023.101248
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发表时间：
2023-11-21
影响因子：
14.3
通讯作者：
Longaker, Michael T.
中科院分区：
文献类型：
--
作者：
Mascharak, Shamik;Guo, Jason L.;Foster, Deshka S.;Khan, Anum;Davitt, Michael F.;Nguyen, Alan T.;Burcham, Austin R.;Chinta, Malini S.;Guardino, Nicholas J.;Griffin, Michelle;Lopez, David M.;Miller, Elisabeth;Januszyk, Michael;Raghavan, Shyam S.;Longacre, Teri A.;Delitto, Daniel J.;Norton, Jeffrey A.;Longaker, Michael T.
胰腺导管腺癌（PDAC）预计将成为癌症相关死亡的第二大原因。特征包括结缔组织增生与可变的细胞外基质（ECM）结构和复杂的微环境与空间定义的肿瘤，间质和免疫群体。然而，促结缔组织增生的空间组织在患者/肿瘤变异性中的作用仍有待研究，我们使用两种技术来阐明这一点。首先，我们量化了437例患者的ECM模式，揭示了与无病生存和总生存相关的结构。其次，我们空间配置文件的细胞环境的78个标本使用codetection索引，确定轴的促炎细胞相互作用预测较差的结果。我们发现，临床特征，包括新辅助化疗状态，肿瘤分期和ECM结构，与不同的基质免疫组织，包括成纤维细胞亚型与不同的壁龛。最后，我们定义了预测生存率的统一特征，受试者工作特征曲线下面积（AUC）为0.872-0.903，生存率差异为655天。总的来说，我们的研究结果建立了与较差结局相关的纤维化基质超微结构和细胞组织。促炎细胞空间相互作用进一步区分结果临床特征与不同的基质免疫细胞组织相关一个统一的，基于机器学习的签名预测PDAC患者生存Mascharak和Guo et al.阐明促结缔组织增生的空间组织在PDAC患者预后中的作用。他们的空间分析揭示了与总体和无病生存相关的全球矩阵架构，与较差结果相关的促炎细胞-细胞相互作用，以及一个统一的基于机器学习的特征，该特征预测了独立队列中的患者结果。
Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second leading cause of cancer-related death. Hallmarks include desmoplasia with variable extracellular matrix (ECM) architecture and a complex microenvironment with spatially defined tumor, stromal, and immune populations. Nevertheless, the role of desmoplastic spatial organization in patient/tumor variability remains underexplored, which we elucidate using two technologies. First, we quantify ECM patterning in 437 patients, revealing architectures associated with disease-free and overall survival. Second, we spatially profile the cellular milieu of 78 specimens using codetection by indexing, identifying an axis of pro-inflammatory cell interactions predictive of poorer outcomes. We discover that clinical characteristics, including neoadjuvant chemotherapy status, tumor stage, and ECM architecture, correlate with differential stromal-immune organization, including fibroblast subtypes with distinct niches. Lastly, we define unified signatures that predict survival with areas under the receiver operating characteristic curve (AUCs) of 0.872–0.903, differentiating survivorship by 655 days. Overall, our findings establish matrix ultrastructural and cellular organizations of fibrosis linked to poorer outcomes. Matrix architecture of desmoplasia correlates with overall and disease-free survival Pro-inflammatory cell spatial interactions further differentiate outcomes Clinical characteristics correlate with distinct stromal-immune cell organization A unified, machine-learning-based signature predicts PDAC patient survival Mascharak and Guo et al. elucidate the role of desmoplastic spatial organization in PDAC patient outcomes. Their spatial analysis uncovers global matrix architectures associated with overall and disease-free survival, pro-inflammatory cell-cell interactions correlated with poorer outcomes, and a unified, machine-learning-based signature that predicts patient outcomes in an independent cohort.
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影响因子：
64.5
作者：
Goltsev Y;Samusik N;Kennedy-Darling J;Bhate S;Hale M;Vazquez G;Black S;Nolan GP
通讯作者：
Nolan GP
影响因子：
3.7
作者：
Bolm, Louisa;Zghurskyi, Petro;Wellner, Ulrich F.
通讯作者：
Wellner, Ulrich F.
影响因子：
50.3
作者：
Foster, Deshka S.;Januszyk, Michael;Delitto, Daniel;Yost, Kathryn E.;Griffin, Michelle;Guo, Jason;Guardino, Nicholas;Delitto, Andrea E.;Chinta, Malini;Burcham, Austin R.;Nguyen, Alan T.;Bauer-Rowe, Khristian E.;Titan, Ashley L.;Salhotra, Ankit;Jones, R. Ellen;da Silva, Oscar;Lindsay, Hunter G.;Berry, Charlotte E.;Chen, Kellen;Henn, Dominic;Mascharak, Shamik;Talbott, Heather E.;Kim, Alexia;Nosrati, Fatemeh;Sivaraj, Dharshan;Ransom, R. Chase;Matthews, Michael;Khan, Anum;Wagh, Dhananjay;Coller, John;Gurtner, Geoffrey C.;Wan, Derrick C.;Wapnir, Irene L.;Chang, Howard Y.;Norton, Jeffrey A.;Longaker, Michael T.
通讯作者：
Longaker, Michael T.
影响因子：
--
作者：
Drifka CR;Loeffler AG;Mathewson K;Keikhosravi A;Eickhoff JC;Liu Y;Weber SM;Kao WJ;Eliceiri KW
通讯作者：
Eliceiri KW
影响因子：
3.8
作者：
Kaissis, Georgios;Ziegelmayer, Sebastian;Braren, Rickmer
通讯作者：
Braren, Rickmer