Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study

The Lancet Digital Health - Tập 3 - Trang e371-e382 - 2021
Yuming Jiang1, Xiaokun Liang1,2,3, Zhen Han4,5, Wei Wang6, Sujuan Xi7, Tuanjie Li4,5, Chuanli Chen8, Qingyu Yuan8, Na Li2,3, Jiang Yu4,5, Yaoqin Xie2,3, Yikai Xu8, Zhiwei Zhou6, George A Poultsides9, Guoxin Li4,6, Ruijiang Li1
1Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
2Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
3Shenzhen Colleges of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
4Department of General Surgery, Nanfang Hospital, Southern medical University, Guangzhou, China
5Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Guangzhou, China
6Department of Gastric Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
7The Reproductive Medical Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
8Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
9Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA

Tài liệu tham khảo

Bray, 2018, Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries, CA Cancer J Clin, 68, 394, 10.3322/caac.21492 Paoletti, 2010, Benefit of adjuvant chemotherapy for resectable gastric cancer: a meta-analysis, JAMA, 303, 1729, 10.1001/jama.2010.534 Noh, 2014, Adjuvant capecitabine plus oxaliplatin for gastric cancer after D2 gastrectomy (CLASSIC): 5-year follow-up of an open-label, randomised phase 3 trial, Lancet Oncol, 15, 1389, 10.1016/S1470-2045(14)70473-5 Jiang, 2017, Association of adjuvant chemotherapy with survival in patients with stage II or III gastric cancer, JAMA Surg, 152, 10.1001/jamasurg.2017.1087 Cheong, 2018, Predictive test for chemotherapy response in resectable gastric cancer: a multi-cohort, retrospective analysis, Lancet Oncol, 19, 629, 10.1016/S1470-2045(18)30108-6 Valkenburg, 2018, Targeting the tumour stroma to improve cancer therapy, Nat Rev Clin Oncol, 15, 366, 10.1038/s41571-018-0007-1 Kobayashi, 2019, Cancer-associated fibroblasts in gastrointestinal cancer, Nat Rev Gastroenterol Hepatol, 16, 282, 10.1038/s41575-019-0115-0 Quail, 2013, Microenvironmental regulation of tumor progression and metastasis, Nat Med, 19, 1423, 10.1038/nm.3394 Pietras, 2010, Hallmarks of cancer: interactions with the tumor stroma, Exp Cell Res, 316, 1324, 10.1016/j.yexcr.2010.02.045 Ligorio, 2019, Stromal microenvironment shapes the intratumoral architecture of pancreatic cancer, Cell, 178, 160, 10.1016/j.cell.2019.05.012 Torres, 2013, Proteome profiling of cancer-associated fibroblasts identifies novel proinflammatory signatures and prognostic markers for colorectal cancer, Clin Cancer Res, 19, 6006, 10.1158/1078-0432.CCR-13-1130 Huijbers, 2013, The proportion of tumor-stroma as a strong prognosticator for stage II and III colon cancer patients: validation in the VICTOR trial, Ann Oncol, 24, 179, 10.1093/annonc/mds246 Moffitt, 2015, Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma, Nat Genet, 47, 1168, 10.1038/ng.3398 Calon, 2015, Stromal gene expression defines poor-prognosis subtypes in colorectal cancer, Nat Genet, 47, 320, 10.1038/ng.3225 Mahajan, 2018, Immune Cell and stromal signature associated with progression-free survival of patients with resected pancreatic ductal adenocarcinoma, Gastroenterology, 155, 1625, 10.1053/j.gastro.2018.08.009 Friedman, 2020, Cancer-associated fibroblast compositions change with breast cancer progression linking the ratio of S100A4+ and PDPN+ CAFs to clinical outcome, Nat Can, 1, 692, 10.1038/s43018-020-0082-y Zhi, 2010, Cancer-associated fibroblasts are positively correlated with metastatic potential of human gastric cancers, J Exp Clin Cancer Res, 29, 66, 10.1186/1756-9966-29-66 Wu, 2013, Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer, Gut, 62, 1100, 10.1136/gutjnl-2011-301373 Uhlik, 2016, Stromal-based signatures for the classification of gastric cancer, Cancer Res, 76, 2573, 10.1158/0008-5472.CAN-16-0022 Zhang, 2020, CAF secreted miR-522 suppresses ferroptosis and promotes acquired chemo-resistance in gastric cancer, Mol Cancer, 19, 43, 10.1186/s12943-020-01168-8 Li, 2020, Natural killer cell and stroma abundance are independently prognostic and predict gastric cancer chemotherapy benefit, JCI Insight, 5, 10.1172/jci.insight.136570 Grunberg, 2021, Cancer-associated fibroblasts promote aggressive gastric cancer phenotypes via heat shock factor 1-mediated secretion of extracellular vesicles, Cancer Res, 10.1158/0008-5472.CAN-20-2756 Zhong, 2019, Overexpression of periostin is positively associated with gastric cancer metastasis through promoting tumor metastasis and invasion, J Cell Biochem, 120, 9927, 10.1002/jcb.28275 Yuan, 2016, Spatial Heterogeneity in the tumor microenvironment, Cold Spring Harb Perspect Med, 6, 10.1101/cshperspect.a026583 Josson, 2010, Tumor-stroma co-evolution in prostate cancer progression and metastasis, Semin Cell Dev Biol, 21, 26, 10.1016/j.semcdb.2009.11.016 Sun, 2018, A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study, Lancet Oncol, 19, 1180, 10.1016/S1470-2045(18)30413-3 Jiang, 2020, Noninvasive imaging evaluation of tumor immune microenvironment to predict outcomes in gastric cancer, Ann Oncol, 31, 760, 10.1016/j.annonc.2020.03.295 Vaidya, 2020, CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multi-cohort study for outcome prediction, Lancet Digit Health, 2, e116, 10.1016/S2589-7500(20)30002-9 Gulshan, 2016, Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs, JAMA, 316, 2402, 10.1001/jama.2016.17216 Esteva, 2017, Dermatologist-level classification of skin cancer with deep neural networks, Nature, 542, 115, 10.1038/nature21056 Ehteshami Bejnordi, 2017, Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer, JAMA, 318, 2199, 10.1001/jama.2017.14585 Chilamkurthy, 2018, Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study, Lancet, 392, 2388, 10.1016/S0140-6736(18)31645-3 Coudray, 2018, Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning, Nat Med, 24, 1559, 10.1038/s41591-018-0177-5 Ardila, 2019, End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography, Nat Med, 25, 954, 10.1038/s41591-019-0447-x Kikuchi, 2014, The niche component periostin is produced by cancer-associated fibroblasts, supporting growth of gastric cancer through ERK activation, Am J Pathol, 184, 859, 10.1016/j.ajpath.2013.11.012 Zhou, 2015, Periostin secreted by glioblastoma stem cells recruits M2 tumour-associated macrophages and promotes malignant growth, Nat Cell Biol, 17, 170, 10.1038/ncb3090 Ryner, 2015, Upregulation of periostin and reactive stroma is associated with primary chemoresistance and predicts clinical outcomes in epithelial ovarian cancer, Clin Cancer Res, 21, 2941, 10.1158/1078-0432.CCR-14-3111 Oh, 2017, Overexpression of POSTN in tumor stroma is a poor prognostic indicator of colorectal cancer, J Pathol Transl Med, 51, 306, 10.4132/jptm.2017.01.19 Yang, 2020, Prognostic value of periostin in multiple solid cancers: a systematic review with meta-analysis, J Cell Physiol, 235, 2800, 10.1002/jcp.29184 Li, 2013, Upregulation of periostin prevents P53-mediated apoptosis in SGC-7901 gastric cancer cells, Mol Biol Rep, 40, 1677, 10.1007/s11033-012-2218-3 Yu, 2019, Effect of laparoscopic vs open distal gastrectomy on 3-year disease-free survival in patients with locally advanced gastric cancer: the CLASS-01 randomized clinical trial, JAMA, 321, 1983, 10.1001/jama.2019.5359 2011, Japanese gastric cancer treatment guidelines 2010 (ver. 3), Gastric Cancer, 14, 113, 10.1007/s10120-011-0042-4 Haejin, 2017, Validation of the 8th edition of the AJCC TNM staging system for gastric cancer using the national cancer database, Ann Surg Oncol, 24, 3683, 10.1245/s10434-017-6078-x Jiang, 2018, ImmunoScore signature: a prognostic and predictive tool in gastric cancer, Ann Surg, 267, 504, 10.1097/SLA.0000000000002116 Jiang, 2018, Immunomarker support vector machine classifier for prediction of gastric cancer survival and adjuvant chemotherapeutic benefit, Clin Cancer Res, 24, 5574, 10.1158/1078-0432.CCR-18-0848 He KM, Zhang XY, Ren SQ, Sun J. Deep residual learning for image recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition; Las Vegas NV; June 26–July 1, 2016: 770–78. Russakovsky, 2015, ImageNet large scale visual recognition challenge, Int J Comput Vis, 115, 211, 10.1007/s11263-015-0816-y Selvaraju, 2020, Grad-CAM: visual explanations from deep networks via gradient-based localization, Int J Comput Vis, 128, 336, 10.1007/s11263-019-01228-7 Tsujino, 2007, Stromal myofibroblasts predict disease recurrence for colorectal cancer, Clin Cancer Res, 13, 2082, 10.1158/1078-0432.CCR-06-2191 Segal, 2007, Decoding global gene expression programs in liver cancer by noninvasive imaging, Nat Biotechnol, 25, 675, 10.1038/nbt1306 Wu, 2018, Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer, Breast Cancer Res, 20, 101, 10.1186/s13058-018-1039-2 Tang, 2018, Development of an immune-pathology informed radiomics model for non-small cell lung cancer, Sci Rep, 8 Sun, 2020, Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated signature of CD8 cells, J Immunother Cancer, 8, 10.1136/jitc-2020-001429 Zinn, 2018, A coclinical radiogenomic validation study: conserved magnetic resonance radiomic appearance of periostin-expressing glioblastoma in patients and xenograft models, Clin Cancer Res, 24, 6288, 10.1158/1078-0432.CCR-17-3420 Mu, 2020, Non-invasive decision support for NSCLC treatment using PET/CT radiomics, Nat Commun, 11, 10.1038/s41467-020-19116-x Lou, 2019, An image-based deep learning framework for individualising radiotherapy dose: a retrospective analysis of outcome prediction, Lancet Digit Health, 1, e136, 10.1016/S2589-7500(19)30058-5 Shitara, 2020, Efficacy and safety of pembrolizumab or pembrolizumab plus chemotherapy vs chemotherapy alone for patients with first-line, advanced gastric cancer: the KEYNOTE-062 phase 3 randomized clinical trial, JAMA Oncol, 6, 1571, 10.1001/jamaoncol.2020.3370 Cunningham, 2006, Perioperative chemotherapy versus surgery alone for resectable gastroesophageal cancer, N Engl J Med, 355, 11, 10.1056/NEJMoa055531 Tauriello, 2018, TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis, Nature, 554, 538, 10.1038/nature25492 Mariathasan, 2018, TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells, Nature, 554, 544, 10.1038/nature25501