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Jiang Y, Xie J, Cheng Q, Cai Z, Xu K, Lu W, Wang F, Wu X, Song Y, Lv T, Zhan P. Comprehensive genomic and spatial immune infiltration analysis of survival outliers in extensive-stage small cell lung cancer receiving first-line chemoimmunotherapy. Int Immunopharmacol 2024; 141:112901. [PMID: 39151386 DOI: 10.1016/j.intimp.2024.112901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 07/20/2024] [Accepted: 08/05/2024] [Indexed: 08/19/2024]
Abstract
BACKGROUND A minority of patients with extensive-stage small cell lung cancer (ES-SCLC) exhibit prolonged survival following first-line chemoimmunotherapy, which warrants the use of reliable biomarkers. Here, we investigated the disparities in genomics and immune cell spatial distribution between long- and short-term survival of patients with ES-SCLC. METHODS We retrospectively recruited 11 long-term (>2 years) and 13 short-term (<9 months) ES-SCLC survivors receiving first-line chemoimmunotherapy. The samples were processed using targeted next-generation sequencing (tNGS), programmed death ligand-1 staining, multiplex immunohistochemical staining for immune cells (mIHC), tumor mutation burden (TMB), and chromosomal instability score measurements. The expression of putative genes in SCLC at the bulk and single-cell RNA-sequencing levels, as well as the role of putative genes in pan-cancer immunotherapy cohorts, were analyzed. RESULTS At the genomic level, a greater proportion of the smoking signature and higher TMB (>3.1) were associated with favorable survival. At the single-gene and pathway levels, tNGS revealed that MCL1 and STMN1 amplification and alterations in the apoptosis pathway were more common in short-term survivors, whereas alterations in the DLL3, KMT2B, HGF, EPHA3, ADGRB3, lysine deprivation, and HGF-cMET pathways were observed more frequently in long-term survivors. mIHC analysis of immune cells with different spatial distributions revealed that long-term survivors presented increased numbers of M1-like macrophages in all locations and decreased numbers of CD8+ T cells in the tumor stroma. Bulk transcriptomic analysis demonstrated that high levels of STMN1 and DLL3 represented an immune-suppressive tumor immune microenvironment (TIME), whereas HGF indicated an immune-responsive TIME. The expression levels of our putative genes were comparative in both TP53/RB1 mutant-type and TP53/RB1 wild-type. At the single-cell level, STMN1, MCL1, and DLL3 were highly expressed among all molecular subtypes (SCLC-A, SCLC-N, and SCLC-P), with STMN1 being enriched in cell division and G2M checkpoint pathways. CONCLUSIONS For ES-SCLC patients receiving first-line chemoimmunotherapy, alterations in DLL3, KMT2B, HGF, EPHA3, and ADGRB3 and a greater proportion of M1-like macrophages infiltration in all locations were predictors of favorable survival, while MCL1 and STMN1 amplification, as well as a greater proportion of CD8+ T cells infiltrating the tumor stroma, predicted worse survival.
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Affiliation(s)
- Yuxin Jiang
- School of Medicine, Southeast University, Nanjing 210000, China
| | - Jingyuan Xie
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Qinpei Cheng
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Zijing Cai
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China
| | - Ke Xu
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Wanjun Lu
- Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Fufeng Wang
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Xiaoying Wu
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Yong Song
- School of Medicine, Southeast University, Nanjing 210000, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210002, China.
| | - Tangfeng Lv
- School of Medicine, Southeast University, Nanjing 210000, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210002, China.
| | - Ping Zhan
- School of Medicine, Southeast University, Nanjing 210000, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Nanjing Medical School, Nanjing 210002, China; Department of Respiratory and Critical Care Medicine, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210002, China.
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Lin Y, Wu W, Lin H, Chen S, Lv H, Chen S, Li C, Wang X, Chen Y. KM04416 suppressed lung adenocarcinoma progression by promoting immune infiltration. J Cardiothorac Surg 2024; 19:465. [PMID: 39054490 PMCID: PMC11270931 DOI: 10.1186/s13019-024-02971-w] [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: 11/15/2023] [Accepted: 07/12/2024] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVES Lung adenocarcinoma (LUAD) is a malignant tumor originating from the bronchial mucosa or glands of the lung, with the fastest increasing morbidity and mortality. Therefore, the prognosis of lung cancer remains poor. Glycerol-3-phosphate dehydrogenase 2 (GPD2) is a widely existing protein pattern sequence in biology and is closely related to tumor progression. The therapy values of GPD2 inhibitor in LUAD were unclear. Therefore, we aimed to analyze the therapy values of GPD2 inhibitor in LUAD. MATERIALS AND METHODS The Cancer Genome Atlas (TCGA)-LUAD database was used to analyze the expression levels of GPD2 in LUAD tissues. The relationship between GPD2 expression and LUAD patient survival was analyzed by Kaplan-Meier method. Moreover, KM04416 as a target inhibitor of GPD2 was used to further investigate the therapy value of GPD2 inhibitor in LUAD cells lines (A549 cell and H1299 cell). The TISIDB website was used to investigate the associations between GPD2 expression and immune cell infiltration in LUAD. RESULTS The results showed that GPD2 is overexpressed in LUAD tissues and significantly associated with poor survival. KM04416 can suppress the progression of LUAD cells by targeting GPD2. Low expression of GPD2 is related to high infiltration of immune cells. CONCLUSIONS In summary, our present study found that targeting inhibition of GPD2 by KM04416 can suppress LUAD progression via adjusting immune cell infiltration.
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Affiliation(s)
- Yalan Lin
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Weijing Wu
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Huihuang Lin
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Shiyuan Chen
- Department of Oncology, Dongguan People 's Hospital, Dongguan, China
| | - Huiying Lv
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Shuchao Chen
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Chuzhao Li
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Xinwen Wang
- Department of Orthopedics, Sanming First Hospital Affiliated to Fujian Medical University, Sanming, Fujian, China.
| | - Yunfeng Chen
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
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Li H, Gong Q, Luo K. Biomarker-driven molecular imaging probes in radiotherapy. Theranostics 2024; 14:4127-4146. [PMID: 38994026 PMCID: PMC11234278 DOI: 10.7150/thno.97768] [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: 04/25/2024] [Accepted: 06/23/2024] [Indexed: 07/13/2024] Open
Abstract
Background: Biomarker-driven molecular imaging has emerged as an integral part of cancer precision radiotherapy. The use of molecular imaging probes, including nanoprobes, have been explored in radiotherapy imaging to precisely and noninvasively monitor spatiotemporal distribution of biomarkers, potentially revealing tumor-killing mechanisms and therapy-induced adverse effects during radiation treatment. Methods: We summarized literature reports from preclinical studies and clinical trials, which cover two main parts: 1) Clinically-investigated and emerging imaging biomarkers associated with radiotherapy, and 2) instrumental roles, functions, and activatable mechanisms of molecular imaging probes in the radiotherapy workflow. In addition, reflection and future perspectives are proposed. Results: Numerous imaging biomarkers have been continuously explored in decades, while few of them have been successfully validated for their correlation with radiotherapeutic outcomes and/or radiation-induced toxicities. Meanwhile, activatable molecular imaging probes towards the emerging biomarkers have exhibited to be promising in animal or small-scale human studies for precision radiotherapy. Conclusion: Biomarker-driven molecular imaging probes are essential for precision radiotherapy. Despite very inspiring preliminary results, validation of imaging biomarkers and rational design strategies of probes await robust and extensive investigations. Especially, the correlation between imaging biomarkers and radiotherapeutic outcomes/toxicities should be established through multi-center collaboration involving a large cohort of patients.
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Affiliation(s)
- Haonan Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province and Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, 699 Jinyuan Xi Road, Jimei District, 361021 Xiamen, Fujian, China
| | - Kui Luo
- Department of Radiology, Huaxi MR Research Center (HMRRC), Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province and Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
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Chen K, Wang Y, Li D, Wu R, Wang J, Wei W, Zhu W, Xie W, Feng D, He Y. Biological clock regulation by the PER gene family: a new perspective on tumor development. Front Cell Dev Biol 2024; 12:1332506. [PMID: 38813085 PMCID: PMC11133573 DOI: 10.3389/fcell.2024.1332506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 04/30/2024] [Indexed: 05/31/2024] Open
Abstract
The Period (PER) gene family is one of the core components of the circadian clock, with substantial correlations between the PER genes and cancers identified in extensive researches. Abnormal mutations in PER genes can influence cell function, metabolic activity, immunity, and therapy responses, thereby promoting the initiation and development of cancers. This ultimately results in unequal cancers progression and prognosis in patients. This leads to variable cancer progression and prognosis among patients. In-depth studies on the interactions between the PER genes and cancers can reveal novel strategies for cancer detection and treatment. In this review, we aim to provide a comprehensive overview of the latest research on the role of the PER gene family in cancer.
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Affiliation(s)
- Kai Chen
- Department of Urology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jia Xing, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Yaohui Wang
- Department of Urology, The Third Medical Center of PLA General Hospital, Beijing, China
| | - Dengxiong Li
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Ruicheng Wu
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Jie Wang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Wuran Wei
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Wei Zhu
- Department of Urology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jia Xing, China
| | - Wenhua Xie
- Department of Urology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jia Xing, China
| | - Dechao Feng
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
- Division of Surgery and Interventional Science, University College London, London, United Kingdom
| | - Yi He
- Department of Urology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jia Xing, China
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Bo Z, Song J, He Q, Chen B, Chen Z, Xie X, Shu D, Chen K, Wang Y, Chen G. Application of artificial intelligence radiomics in the diagnosis, treatment, and prognosis of hepatocellular carcinoma. Comput Biol Med 2024; 173:108337. [PMID: 38547656 DOI: 10.1016/j.compbiomed.2024.108337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/04/2024] [Accepted: 03/17/2024] [Indexed: 04/17/2024]
Abstract
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, with an increasing incidence and poor prognosis. In the past decade, artificial intelligence (AI) technology has undergone rapid development in the field of clinical medicine, bringing the advantages of efficient data processing and accurate model construction. Promisingly, AI-based radiomics has played an increasingly important role in the clinical decision-making of HCC patients, providing new technical guarantees for prediction, diagnosis, and prognostication. In this review, we evaluated the current landscape of AI radiomics in the management of HCC, including its diagnosis, individual treatment, and survival prognosis. Furthermore, we discussed remaining challenges and future perspectives regarding the application of AI radiomics in HCC.
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Affiliation(s)
- Zhiyuan Bo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jiatao Song
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Qikuan He
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Bo Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ziyan Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaozai Xie
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Danyang Shu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kaiyu Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
| | - Yi Wang
- Department of Epidemiology and Biostatistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China.
| | - Gang Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Zhejiang-Germany Interdisciplinary Joint Laboratory of Hepatobiliary-Pancreatic Tumor and Bioengineering, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
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Gan J, Liu M, Liu F, Wen J, Fu W, Jia J. Synchronous double primary small cell lung cancer and invasive ductal breast carcinoma: a case report. BMC Pulm Med 2024; 24:93. [PMID: 38388422 PMCID: PMC10885399 DOI: 10.1186/s12890-024-02897-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 02/04/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Although lung and breast cancers are common malignancies, the occurrence of primary synchronous neoplasms involving these organs has been rarely reported in literature. CASE PRESENTATION A 75-year-old female patient presented at a local hospital with a ten-day history of dizziness and slurred speech. A CT contrast-enhanced scan revealed a 4.2 cm mass in the lower lobe of the right lung and a 3.8 cm space-occupying lesion in the right breast. Subsequent breast ultrasound identified a hypoechoic lesion measuring5.41 × 4.75 × 3.06 cm in the right breast, and an ultrasound-guided biopsy confirmed the presence of infiltrating ductal carcinoma of the right breast. The immunohistochemistry analysis of the breast mass revealed positive staining for ER, PR, HER-2, AR and Ki67 in the tumor cells, while negative staining was observed for P63, Calponin, CK5/6 and CK14. MR imaging of the head detected abnormal signals in the right frontal lobe (3.6 cm×2.9 cm in size), left cerebellar hemisphere, and punctate enhancement in the left temporal lobe, indicating potential metastasis. Pathological examination of a lung biopsy specimen confirmed the presence of small cell lung cancer (SCLC). Furthermore, immunohistochemistry analysis of the lung lesions demonstrated positive staining for TTF-1, CK-Pan, Syn, CgA, CD56, P53 (90%) and Ki67 (70%), and negative staining for NapsinA and P40 in the tumor cells. The patient's diagnosis of SCLC with stage cT2bN0M1c IVB and brain metastases (BM), as well as invasive ductal breast carcinoma (IDC), was confirmed based on the aforementioned results. Whereupon we proposed a treatment plan consisting of whole-brain radiation (40 Gy/20fractions), focal radiotherapy (60 Gy/20fractions), and adjuvant concurrent chemotherapy with oral etoposide (50 mg on days 1 to 20). CONCLUSIONS To the best of our knowledge, the present case is the first of its kind to describe the synchronous double cancer, consisting of primary SCLC and IDC.
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Affiliation(s)
- Junqing Gan
- Department of Chemoradiation, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China
| | - Meiyue Liu
- Department of Chemoradiation, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China
| | - Fei Liu
- Department of Radiotherapy, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China
| | - Junxiu Wen
- Department of Pathology, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China
| | - Wenjuan Fu
- Department of Chemoradiation, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China
| | - Jinghao Jia
- Department of Chemoradiation, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China.
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Zhang X, Zhang G, Qiu X, Yin J, Tan W, Yin X, Yang H, Wang H, Zhang Y. Non-invasive decision support for clinical treatment of non-small cell lung cancer using a multiscale radiomics approach. Radiother Oncol 2024; 191:110082. [PMID: 38195018 DOI: 10.1016/j.radonc.2024.110082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 12/01/2023] [Accepted: 01/02/2024] [Indexed: 01/11/2024]
Abstract
BACKGROUND Selecting therapeutic strategies for cancer patients is typically based on key target-molecule biomarkers that play an important role in cancer onset, progression, and prognosis. Thus, there is a pressing need for novel biomarkers that can be utilized longitudinally to guide treatment selection. METHODS Using data from 508 non-small cell lung cancer (NSCLC) patients across three institutions, we developed and validated a comprehensive predictive biomarker that distinguishes six genotypes and infiltrative immune phenotypes. These features were analyzed to establish the association between radiological phenotypes and tumor genotypes/immune phenotypes and to create a radiological interpretation of molecular features. In addition, we assessed the sensitivity of the models by evaluating their performance at five different voxel intervals, resulting in improved generalizability of the proposed approach. FINDINGS The radiomics model we developed, which integrates clinical factors and multi-regional features, outperformed the conventional model that only uses clinical and intratumoral features. Our combined model showed significant performance for EGFR, KRAS, ALK, TP53, PIK3CA, and ROS1 mutation status with AUCs of 0.866, 0.874, 0.902, 0.850, 0.860, and 0.900, respectively. Additionally, the predictive performance for PD-1/PD-L1 was 0.852. Although the performance of all models decreased to different degrees at five different voxel space resolutions, the performance advantage of the combined model did not change. CONCLUSIONS We validated multiscale radiomic signatures across tumor genotypes and immunophenotypes in a multi-institutional cohort. This imaging-based biomarker offers a non-invasive approach to select patients with NSCLC who are sensitive to targeted therapies or immunotherapy, which is promising for developing personalized treatment strategies during therapy.
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Affiliation(s)
- Xingping Zhang
- School of Medical Information Engineering, Gannan Medical University, 341000, Ganzhou, China; Cyberspace Institute of Advanced Technology, Guangzhou University, 510006 Guangzhou, China; Institute for Sustainable Industries and Liveable Cities, Victoria University, 3011, Melbourne, Australia; Department of New Networks, Peng Cheng Laboratory, 518000, Shenzhen, China
| | - Guijuan Zhang
- Department of Respiratory and Critical Care, First Affiliated Hospital of Gannan Medical University, 341000, Ganzhou, China
| | - Xingting Qiu
- Department of Radiology, First Affiliated Hospital of Gannan Medical University, 341000, Ganzhou, China
| | - Jiao Yin
- Institute for Sustainable Industries and Liveable Cities, Victoria University, 3011, Melbourne, Australia
| | - Wenjun Tan
- Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, 110189, Shenyang, China
| | - Xiaoxia Yin
- Cyberspace Institute of Advanced Technology, Guangzhou University, 510006 Guangzhou, China
| | - Hong Yang
- Cyberspace Institute of Advanced Technology, Guangzhou University, 510006 Guangzhou, China
| | - Hua Wang
- Institute for Sustainable Industries and Liveable Cities, Victoria University, 3011, Melbourne, Australia.
| | - Yanchun Zhang
- Institute for Sustainable Industries and Liveable Cities, Victoria University, 3011, Melbourne, Australia; School of Computer Science and Technology, Zhejiang Normal University, 321000, Jinhua, China; Department of New Networks, Peng Cheng Laboratory, 518000, Shenzhen, China.
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Lv X, Li Y, Xu X, Zheng Z, Li F, Fang K, Wang Y, Wang B, Hou D. Multisequence MRI-based radiomics nomogram for early prediction of osimertinib resistance in patients with non-small cell lung cancer brain metastases. Eur J Radiol Open 2023; 11:100521. [PMID: 37692549 PMCID: PMC10485591 DOI: 10.1016/j.ejro.2023.100521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 08/09/2023] [Accepted: 08/31/2023] [Indexed: 09/12/2023] Open
Abstract
Background Osimertinib resistance is a major problem in the course of targeted therapy for non-small cell lung cancer (NSCLC) patients. To develop and validate a multisequence MRI-based radiomics nomogram for early prediction of osimertinib resistance in NSCLC with brain metastases (BM). Methods Pretreatment brain MRI of 251 NSCLC patients proven with BM were retrospectively enrolled from two centers (training cohort: 196 patients; testing cohort: 55 patients). According to the gene test result of osimertinib resistance, patients were labeled as resistance and non-resistance groups (training cohort: 65 versus 131 patients; testing cohort: 25 versus 30 patients). Radiomics features were extracted from T2WI, T2 fluid-attenuated inversion recovery (T2-FLAIR), diffusion weighted imaging (DWI) and contrast-enhanced T1-weighted imaging (T1-CE) sequences separately and radiomics score (rad-score) were built from the four sequences. Then a multisequence MRI-based nomogram was developed and the predictive ability was evaluated by ROC curves and calibration curves. Results The rad-scores of the four sequences has significant differences between resistance and non-resistance groups in both training and testing cohorts. The nomogram achieved the highest predictive ability with area under the curve (AUC) of 0.989 (95 % confidence interval, 0.976-1.000) and 0.923 (95 % confidence interval, 0.851-0.995) in the training and testing cohort respectively. The calibration curves showed excellent concordance between the predicted and actual probability of osimertinib resistance using the radiomics nomogram. Conclusions The multisequence MRI-based radiomics nomogram can be used as a noninvasive auxiliary tool to identify candidates who were resistant to osimertinib, which could guide clinical therapy for NSCLC patients with BM.
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Affiliation(s)
- Xinna Lv
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Ye Li
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Xiaoyue Xu
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Ziwei Zheng
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Fang Li
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Kun Fang
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Yue Wang
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Bing Wang
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Dailun Hou
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
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Megyesfalvi Z, Gay CM, Popper H, Pirker R, Ostoros G, Heeke S, Lang C, Hoetzenecker K, Schwendenwein A, Boettiger K, Bunn PA, Renyi-Vamos F, Schelch K, Prosch H, Byers LA, Hirsch FR, Dome B. Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions. CA Cancer J Clin 2023; 73:620-652. [PMID: 37329269 DOI: 10.3322/caac.21785] [Citation(s) in RCA: 52] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/30/2023] [Accepted: 04/04/2023] [Indexed: 06/19/2023] Open
Abstract
Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative-intent lung resection, and these individuals require adjuvant platinum-etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum-etoposide chemotherapy. Patients with metastatic (extensive-stage) disease are treated with a combination of platinum-etoposide chemotherapy plus immunotherapy with an anti-programmed death-ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum-based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.
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Affiliation(s)
- Zsolt Megyesfalvi
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
- National Koranyi Institute of Pulmonology, Budapest, Hungary
| | - Carl M Gay
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Helmut Popper
- Diagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Robert Pirker
- Department of Medicine I, Medical University of Vienna, Vienna, Austria
| | - Gyula Ostoros
- National Koranyi Institute of Pulmonology, Budapest, Hungary
| | - Simon Heeke
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Christian Lang
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Division of Pulmonology, Department of Medicine II, Medical University of Vienna, Vienna, Austria
| | - Konrad Hoetzenecker
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Anna Schwendenwein
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Kristiina Boettiger
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Paul A Bunn
- University of Colorado School of Medicine, Aurora, CO, USA
| | - Ferenc Renyi-Vamos
- Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
- National Koranyi Institute of Pulmonology, Budapest, Hungary
| | - Karin Schelch
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Center for Cancer Research, Medical University of Vienna, Vienna, Austria
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna General Hospital, Vienna, Austria
| | - Lauren A Byers
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fred R Hirsch
- Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Tisch Cancer Institute, Center for Thoracic Oncology, Mount Sinai Health System, New York, NY, USA
| | - Balazs Dome
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
- National Koranyi Institute of Pulmonology, Budapest, Hungary
- Department of Translational Medicine, Lund University, Lund, Sweden
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10
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Wang J, Zhong F, Xiao F, Dong X, Long Y, Gan T, Li T, Liao M. CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma. Front Oncol 2023; 13:1157891. [PMID: 37020864 PMCID: PMC10069670 DOI: 10.3389/fonc.2023.1157891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/06/2023] [Indexed: 04/07/2023] Open
Abstract
Purpose Exploring a non-invasive method to accurately differentiate peripheral small cell lung cancer (PSCLC) and peripheral lung adenocarcinoma (PADC) could improve clinical decision-making and prognosis. Methods This retrospective study reviewed the clinicopathological and imaging data of lung cancer patients between October 2017 and March 2022. A total of 240 patients were enrolled in this study, including 80 cases diagnosed with PSCLC and 160 with PADC. All patients were randomized in a seven-to-three ratio into the training and validation datasets (170 vs. 70, respectively). The least absolute shrinkage and selection operator regression was employed to generate radiomics features and univariate analysis, followed by multivariate logistic regression to select significant clinical and radiographic factors to generate four models: clinical, radiomics, clinical-radiographic, and clinical-radiographic-radiomics (comprehensive). The Delong test was to compare areas under the receiver operating characteristic curves (AUCs) in the models. Results Five clinical-radiographic features and twenty-three selected radiomics features differed significantly in the identification of PSCLC and PADC. The clinical, radiomics, clinical-radiographic and comprehensive models demonstrated AUCs of 0.8960, 0.8356, 0.9396, and 0.9671 in the validation set, with the comprehensive model having better discernment than the clinical model (P=0.036), the radiomics model (P=0.006) and the clinical-radiographic model (P=0.049). Conclusions The proposed model combining clinical data, radiographic characteristics and radiomics features could accurately distinguish PSCLC from PADC, thus providing a potential non-invasive method to help clinicians improve treatment decisions.
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Affiliation(s)
- Jingting Wang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Feiyang Zhong
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Feng Xiao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinyang Dong
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yun Long
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Tian Gan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ting Li
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Meiyan Liao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Meiyan Liao,
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