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Durvalumab after Chemoradiotherapy in Limited-Stage Small-Cell Lung Cancer.局限期小细胞肺癌放化疗后应用度伐利尤单抗。
N Engl J Med. 2024 Oct 10;391(14):1313-1327. doi: 10.1056/NEJMoa2404873. Epub 2024 Sep 13.
2
Key processes in tumor metastasis and therapeutic strategies with nanocarriers: a review.肿瘤转移的关键过程和纳米载体的治疗策略:综述。
Mol Biol Rep. 2024 Jan 25;51(1):197. doi: 10.1007/s11033-023-08910-7.
3
Alleviating hypoxia to improve cancer immunotherapy.缓解缺氧以改善癌症免疫疗法。
Oncogene. 2023 Dec;42(49):3591-3604. doi: 10.1038/s41388-023-02869-2. Epub 2023 Oct 26.
4
TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images.全段分割器:CT图像中104种解剖结构的稳健分割
Radiol Artif Intell. 2023 Jul 5;5(5):e230024. doi: 10.1148/ryai.230024. eCollection 2023 Sep.
5
Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer.免疫细胞微环境的深度计算图像分析揭示了肺癌中特定治疗结果的关联。
NPJ Precis Oncol. 2023 Jun 1;7(1):52. doi: 10.1038/s41698-023-00403-x.
6
A tumor vasculature-based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors.一种基于肿瘤血管系统的成像生物标志物,用于预测接受检查点抑制剂治疗的肺癌患者的反应和生存情况。
Sci Adv. 2022 Nov 25;8(47):eabq4609. doi: 10.1126/sciadv.abq4609.
7
Emerging role of chemokines in small cell lung cancer: Road signs for metastasis, heterogeneity, and immune response.趋化因子在小细胞肺癌中的新兴作用:转移、异质性和免疫反应的路标。
Semin Cancer Biol. 2022 Dec;87:117-126. doi: 10.1016/j.semcancer.2022.11.005. Epub 2022 Nov 9.
8
Progression and metastasis of small cell lung carcinoma: the role of the PI3K/Akt/mTOR pathway and metabolic alterations.小细胞肺癌的进展和转移:PI3K/Akt/mTOR 通路和代谢改变的作用。
Cancer Metastasis Rev. 2021 Dec;40(4):1141-1157. doi: 10.1007/s10555-021-10012-4. Epub 2021 Dec 27.
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An Imaging Biomarker of Tumor-Infiltrating Lymphocytes to Risk-Stratify Patients With HPV-Associated Oropharyngeal Cancer.一种肿瘤浸润淋巴细胞的影像学生物标志物,用于风险分层 HPV 相关口咽癌患者。
J Natl Cancer Inst. 2022 Apr 11;114(4):609-617. doi: 10.1093/jnci/djab215.
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Overcoming Chemotherapy Resistance in SCLC.克服小细胞肺癌的化疗耐药性。
J Thorac Oncol. 2021 Dec;16(12):2002-2015. doi: 10.1016/j.jtho.2021.07.018. Epub 2021 Aug 3.

基于人工智能的放射组学特征预测广泛期小细胞肺癌的预后以及化疗联合免疫疗法相对于单纯化疗的附加益处:一项多机构研究。

AI-based radiomic features predict outcomes and the added benefit of chemoimmunotherapy over chemotherapy in extensive stage small cell lung cancer: A multi-institutional study.

作者信息

Khorrami Mohammadhadi, Mutha Pushkar, Barrera Cristian, Viswanathan Vidya S, Ardeshir-Larijani Fatemeh, Jain Prantesh, Higgins Kristin, Madabhushi Anant

机构信息

Emory University and Georgia Institute of Technology, Atlanta, 30322, Georgia.

Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA.

出版信息

Cancer Lett. 2025 Sep 28;628:217872. doi: 10.1016/j.canlet.2025.217872. Epub 2025 Jun 11.

DOI:10.1016/j.canlet.2025.217872
PMID:40514005
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12276946/
Abstract

Small cell lung cancer (SCLC) is aggressive with poor survival outcomes, and most patients develop resistance to chemotherapy. No predictive biomarkers currently guide therapy. This study evaluates radiomic features to predict PFS and OS in limited-stage SCLC (LS-SCLC) and assesses PFS, OS, and the added benefit of chemoimmunotherapy (CHIO) in extensive-stage SCLC (ES-SCLC). A total of 660 SCLC patients (470 ES-SCLC, 190 LS-SCLC) from three sites were analyzed. LS-SCLC patients received chemotherapy and radiation, while ES-SCLC patients received either chemotherapy alone or CHIO. Radiomic and quantitative vasculature tortuosity features were extracted from CT scans. A LASSO-Cox regression model was used to construct the ES- Risk-Score (ESRS) and LS- Risk-Score (LSRS). ESRS was associated with PFS in training (HR = 1.54, adj. P = .0013) and two independent validation sets (HR = 1.32, adj. P = .0001; HR = 2.4, adj. P = .0073) and with OS in training (HR = 1.37, adj. P = .0054) and validation sets (HR = 1.35, adj. P < .0006; HR = 1.6, adj. P < .0085) in ES-SCLC patients treated with chemotherapy. High-risk patients had improved PFS (HR = 0.68, adj. P < .001) and OS (HR = 0.78, adj. P = .026) with CHIO. LSRS was associated with PFS in training and two independent validation sets (HR = 1.9, adj. P = .007; HR = 1.4, adj. P = .0098; HR = 2.1, adj. P = .028) in LS-SCLC patients receiving chemoradiation. Radiomics is prognostic for PFS and OS and predicts chemoimmunotherapy benefit in high-risk ES-SCLC patients.

摘要

小细胞肺癌(SCLC)侵袭性强,生存预后差,大多数患者会对化疗产生耐药性。目前尚无预测性生物标志物可指导治疗。本研究评估影像组学特征以预测局限期小细胞肺癌(LS-SCLC)的无进展生存期(PFS)和总生存期(OS),并评估广泛期小细胞肺癌(ES-SCLC)的PFS、OS以及化疗联合免疫治疗(CHIO)的附加益处。对来自三个地点的总共660例SCLC患者(470例ES-SCLC,190例LS-SCLC)进行了分析。LS-SCLC患者接受化疗和放疗,而ES-SCLC患者接受单纯化疗或CHIO。从CT扫描中提取影像组学和定量血管迂曲特征。使用套索-考克斯回归模型构建ES-风险评分(ESRS)和LS-风险评分(LSRS)。ESRS与接受化疗的ES-SCLC患者在训练集(风险比[HR]=1.54,校正P=.0013)和两个独立验证集(HR=1.32,校正P=.0001;HR=2.4,校正P=.0073)中的PFS相关,且与训练集(HR=1.37,校正P=.0054)和验证集(HR=1.35,校正P<.0006;HR=1.6,校正P<.0085)中的OS相关。高危患者接受CHIO治疗后PFS(HR=0.68,校正P<.001)和OS(HR=0.78,校正P=.026)得到改善。LSRS与接受放化疗的LS-SCLC患者在训练集和两个独立验证集(HR=1.9,校正P=.007;HR=1.4,校正P=.0098;HR=2.1,校正P=.028)中的PFS相关。影像组学对PFS和OS具有预后价值,并可预测高危ES-SCLC患者从化疗联合免疫治疗中获益。