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Ye G, Wu G, Zhang C, Wang M, Liu H, Song E, Zhuang Y, Li K, Qi Y, Liao Y. CT-based quantification of intratumoral heterogeneity for predicting pathologic complete response to neoadjuvant immunochemotherapy in non-small cell lung cancer. Front Immunol 2024; 15:1414954. [PMID: 38933281 PMCID: PMC11199789 DOI: 10.3389/fimmu.2024.1414954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 05/29/2024] [Indexed: 06/28/2024] Open
Abstract
Objectives To investigate the prediction of pathologic complete response (pCR) in patients with non-small cell lung cancer (NSCLC) undergoing neoadjuvant immunochemotherapy (NAIC) using quantification of intratumoral heterogeneity from pre-treatment CT image. Methods This retrospective study included 178 patients with NSCLC who underwent NAIC at 4 different centers. The training set comprised 108 patients from center A, while the external validation set consisted of 70 patients from center B, center C, and center D. The traditional radiomics model was contrasted using radiomics features. The radiomics features of each pixel within the tumor region of interest (ROI) were extracted. The optimal division of tumor subregions was determined using the K-means unsupervised clustering method. The internal tumor heterogeneity habitat model was developed using the habitats features from each tumor sub-region. The LR algorithm was employed in this study to construct a machine learning prediction model. The diagnostic performance of the model was evaluated using criteria such as area under the receiver operating characteristic curve (AUC), accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV). Results In the training cohort, the traditional radiomics model achieved an AUC of 0.778 [95% confidence interval (CI): 0.688-0.868], while the tumor internal heterogeneity habitat model achieved an AUC of 0.861 (95% CI: 0.789-0.932). The tumor internal heterogeneity habitat model exhibits a higher AUC value. It demonstrates an accuracy of 0.815, surpassing the accuracy of 0.685 achieved by traditional radiomics models. In the external validation cohort, the AUC values of the two models were 0.723 (CI: 0.591-0.855) and 0.781 (95% CI: 0.673-0.889), respectively. The habitat model continues to exhibit higher AUC values. In terms of accuracy evaluation, the tumor heterogeneity habitat model outperforms the traditional radiomics model, achieving a score of 0.743 compared to 0.686. Conclusion The quantitative analysis of intratumoral heterogeneity using CT to predict pCR in NSCLC patients undergoing NAIC holds the potential to inform clinical decision-making for resectable NSCLC patients, prevent overtreatment, and enable personalized and precise cancer management.
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Affiliation(s)
- Guanchao Ye
- Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Thoracic Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Guangyao Wu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chunyang Zhang
- Department of Thoracic Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Mingliang Wang
- Department of Thoracic Surgery, Henan Provincial People’s Hospital, Zhengzhou University, Zhengzhou, China
| | - Hong Liu
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Enmin Song
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Yuzhou Zhuang
- School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Kuo Li
- Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Qi
- Department of Thoracic Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China
| | - Yongde Liao
- Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Zhang Y, Hu Q, Pei Y, Luo H, Wang Z, Xu X, Zhang Q, Dai J, Wang Q, Fan Z, Fang Y, Ye M, Li B, Chen M, Xue Q, Zheng Q, Zhang S, Huang M, Zhang T, Gu J, Xiong Z. A patient-specific lung cancer assembloid model with heterogeneous tumor microenvironments. Nat Commun 2024; 15:3382. [PMID: 38643164 PMCID: PMC11032376 DOI: 10.1038/s41467-024-47737-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 04/08/2024] [Indexed: 04/22/2024] Open
Abstract
Cancer models play critical roles in basic cancer research and precision medicine. However, current in vitro cancer models are limited by their inability to mimic the three-dimensional architecture and heterogeneous tumor microenvironments (TME) of in vivo tumors. Here, we develop an innovative patient-specific lung cancer assembloid (LCA) model by using droplet microfluidic technology based on a microinjection strategy. This method enables precise manipulation of clinical microsamples and rapid generation of LCAs with good intra-batch consistency in size and cell composition by evenly encapsulating patient tumor-derived TME cells and lung cancer organoids inside microgels. LCAs recapitulate the inter- and intratumoral heterogeneity, TME cellular diversity, and genomic and transcriptomic landscape of their parental tumors. LCA model could reconstruct the functional heterogeneity of cancer-associated fibroblasts and reflect the influence of TME on drug responses compared to cancer organoids. Notably, LCAs accurately replicate the clinical outcomes of patients, suggesting the potential of the LCA model to predict personalized treatments. Collectively, our studies provide a valuable method for precisely fabricating cancer assembloids and a promising LCA model for cancer research and personalized medicine.
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Affiliation(s)
- Yanmei Zhang
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
- Institute of New Materials and Advanced Manufacturing, Beijing Academy of Science and Technology, Beijing, 100089, China
| | - Qifan Hu
- MOE Key Laboratory of Bioinformatics, BNRIST Bioinformatics Division, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Yuquan Pei
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Surgery II, Peking University Cancer Hospital and Institute, Beijing, 100142, China
| | - Hao Luo
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Zixuan Wang
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Xinxin Xu
- Medical School of Chinese PLA, Beijing, 100853, China
| | - Qing Zhang
- Institute of New Materials and Advanced Manufacturing, Beijing Academy of Science and Technology, Beijing, 100089, China
| | - Jianli Dai
- Institute of New Materials and Advanced Manufacturing, Beijing Academy of Science and Technology, Beijing, 100089, China
| | - Qianqian Wang
- Institute of New Materials and Advanced Manufacturing, Beijing Academy of Science and Technology, Beijing, 100089, China
| | - Zilian Fan
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Yongcong Fang
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Min Ye
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Binhan Li
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Mailin Chen
- Department of Radiology, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Qi Xue
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Qingfeng Zheng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Shulin Zhang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Miao Huang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Surgery II, Peking University Cancer Hospital and Institute, Beijing, 100142, China
| | - Ting Zhang
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China
| | - Jin Gu
- MOE Key Laboratory of Bioinformatics, BNRIST Bioinformatics Division, Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Zhuo Xiong
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China.
- Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Beijing, 100084, China.
- Biomanufacturing and Engineering Living Systems Innovation International Talents Base (111 Base), Beijing, 100084, China.
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Yu A, Fu F, Li X, Wu M, Yu M, Zhang W. Perioperative immunotherapy for stage II-III non-small cell lung cancer: a meta-analysis base on randomized controlled trials. Front Oncol 2024; 14:1351359. [PMID: 38454928 PMCID: PMC10917905 DOI: 10.3389/fonc.2024.1351359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/05/2024] [Indexed: 03/09/2024] Open
Abstract
Background In recent years, we have observed the pivotal role of immunotherapy in improving survival for patients with non-small cell lung cancer (NSCLC). However, the effectiveness of immunotherapy in the perioperative (neoadjuvant + adjuvant) treatment of resectable NSCLC remains uncertain. We conducted a comprehensive analysis of its antitumor efficacy and adverse effects (AEs) by pooling data from the KEYNOTE-671, NADIM II, and AEGEAN clinical trials. Methods For eligible studies, we searched seven databases. The randomized controlled trials (RCTs) pertaining to the comparative analysis of combination neoadjuvant platinum-based chemotherapy plus perioperative immunotherapy (PIO) versus perioperative placebo (PP) were included. Primary endpoints were overall survival (OS) and event-free survival (EFS). Secondary endpoints encompassed drug responses, AEs, and surgical outcomes. Results Three RCTs (KEYNOTE-671, NADIM II, and AEGEAN) were included in the final analysis. PIO group (neoadjuvant platinum-based chemotherapy plus perioperative immunotherapy) exhibited superior efficacy in OS (hazard ratio [HR]: 0.63 [0.49-0.81]), EFS (HR: 0.61 [0.52, 0.72]), objective response rate (risk ratio [RR]: 2.21 [1.91, 2.54]), pathological complete response (RR: 4.36 [3.04, 6.25]), major pathological response (RR: 2.79 [2.25, 3.46]), R0 resection rate (RR: 1.13 [1.00, 1.26]) and rate of adjuvant treatment (RR: 1.08 [1.01, 1.15]) compared with PP group (neoadjuvant platinum-based chemotherapy plus perioperative placebo). In the subgroup analysis, EFS tended to favor the PIO group in almost all subgroups. BMI (>25), T stage (IV), N stage (N1-N2) and pathological response (with pathological complete response) were favorable factors in the PIO group. In the safety assessment, the PIO group exhibited higher rates of serious AEs (28.96% vs. 23.51%) and AEs leading to treatment discontinuation (12.84% vs. 5.81%). Meanwhile, although total adverse events, grade 3-5 adverse events, and fatal adverse events tended to favor the PP group, the differences were not statistically significant. Conclusion PIO appears to be superior to PP for resectable stage II-III NSCLC, demonstrating enhanced survival and pathological responses. However, its elevated adverse event (AE) rate warrants careful consideration. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier CRD42023487475.
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Affiliation(s)
- Anping Yu
- Department of Oncology, Fengcheng People’s Hospital, Yichun, China
- Department of Oncology, The Affiliated Fengcheng Hospital of Yichun University, Yichun, China
| | - Feng Fu
- Department of Oncology, Shangrao People’s Hospital, Shangrao, China
| | - Xiongying Li
- Department of Oncology, Fengcheng People’s Hospital, Yichun, China
- Department of Oncology, The Affiliated Fengcheng Hospital of Yichun University, Yichun, China
| | - Mengxin Wu
- Department of Oncology, Shangrao People’s Hospital, Shangrao, China
| | - Meijian Yu
- Department of Oncology, Shangrao People’s Hospital, Shangrao, China
| | - Wenxiong Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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Lu S, Zhang W, Wu L, Wang W, Zhang P. Perioperative Toripalimab Plus Chemotherapy for Patients With Resectable Non-Small Cell Lung Cancer: The Neotorch Randomized Clinical Trial. JAMA 2024; 331:201-211. [PMID: 38227033 PMCID: PMC10792477 DOI: 10.1001/jama.2023.24735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 11/09/2023] [Indexed: 01/17/2024]
Abstract
Importance Adjuvant and neoadjuvant immunotherapy have improved clinical outcomes for patients with early-stage non-small cell lung cancer (NSCLC). However, the optimal combination of checkpoint inhibition with chemotherapy remains unknown. Objective To determine whether toripalimab in combination with platinum-based chemotherapy will improve event-free survival and major pathological response in patients with stage II or III resectable NSCLC compared with chemotherapy alone. Design, Setting, and Participants This randomized clinical trial enrolled patients with stage II or III resectable NSCLC (without EGFR or ALK alterations for nonsquamous NSCLC) from March 12, 2020, to June 19, 2023, at 50 participating hospitals in China. The data cutoff date for this interim analysis was November 30, 2022. Interventions Patients were randomized in a 1:1 ratio to receive 240 mg of toripalimab or placebo once every 3 weeks combined with platinum-based chemotherapy for 3 cycles before surgery and 1 cycle after surgery, followed by toripalimab only (240 mg) or placebo once every 3 weeks for up to 13 cycles. Main Outcomes and Measures The primary outcomes were event-free survival (assessed by the investigators) and the major pathological response rate (assessed by blinded, independent pathological review). The secondary outcomes included the pathological complete response rate (assessed by blinded, independent pathological review) and adverse events. Results Of the 501 patients randomized, 404 had stage III NSCLC (202 in the toripalimab + chemotherapy group and 202 in the placebo + chemotherapy group) and 97 had stage II NSCLC and were excluded from this interim analysis. The median age was 62 years (IQR, 56-65 years), 92% of patients were male, and the median follow-up was 18.3 months (IQR, 12.7-22.5 months). For the primary outcome of event-free survival, the median length was not estimable (95% CI, 24.4 months-not estimable) in the toripalimab group compared with 15.1 months (95% CI, 10.6-21.9 months) in the placebo group (hazard ratio, 0.40 [95% CI, 0.28-0.57], P < .001). The major pathological response rate (another primary outcome) was 48.5% (95% CI, 41.4%-55.6%) in the toripalimab group compared with 8.4% (95% CI, 5.0%-13.1%) in the placebo group (between-group difference, 40.2% [95% CI, 32.2%-48.1%], P < .001). The pathological complete response rate (secondary outcome) was 24.8% (95% CI, 19.0%-31.3%) in the toripalimab group compared with 1.0% (95% CI, 0.1%-3.5%) in the placebo group (between-group difference, 23.7% [95% CI, 17.6%-29.8%]). The incidence of immune-related adverse events occurred more frequently in the toripalimab group. No unexpected treatment-related toxic effects were identified. The incidence of grade 3 or higher adverse events, fatal adverse events, and adverse events leading to discontinuation of treatment were comparable between the groups. Conclusions and Relevance The addition of toripalimab to perioperative chemotherapy led to a significant improvement in event-free survival for patients with resectable stage III NSCLC and this treatment strategy had a manageable safety profile. Trial Registration ClinicalTrials.gov Identifier: NCT04158440.
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Affiliation(s)
- Shun Lu
- Department of Medical Oncology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Zhang
- First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Lin Wu
- Department of Thoracic Medical Oncology, Hunan Cancer Hospital, Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Wenxiang Wang
- Second Department of Thoracic Surgery, Hunan Cancer Hospital, Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Peng Zhang
- Shanghai Pulmonary Hospital, Tong Ji University, Shanghai, China
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