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Chen M, Ding L, Deng S, Li J, Li X, Jian M, Xu Y, Chen Z, Yan C. Differentiating the Invasiveness of Lung Adenocarcinoma Manifesting as Ground Glass Nodules: Combination of Dual-energy CT Parameters and Quantitative-semantic Features. Acad Radiol 2024; 31:2962-2972. [PMID: 38508939 DOI: 10.1016/j.acra.2024.02.011] [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: 12/20/2023] [Revised: 01/30/2024] [Accepted: 02/07/2024] [Indexed: 03/22/2024]
Abstract
RATIONALE AND OBJECTIVES To evaluate the diagnostic performance of dual-energy CT (DECT) parameters and quantitative-semantic features for differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules (GGNs). MATERIALS AND METHODS Between June 2022 and September 2023, 69 patients with 74 surgically resected GGNs who underwent DECT examinations were included. CT numbers on virtual monochromatic images were calculated at 40-130 keV generated from DECT. Quantitative morphological measurements and semantic features were evaluated on unenhanced CT images and compared between pathologically confirmed adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive lung adenocarcinoma (IAC). Multivariable logistic regression analysis was used to identify independent predictors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test. RESULTS Monochromatic CT numbers at 40-130 keV were significantly higher in IAC than in AIS-MIA (all P < 0.05). Multivariate logistic analysis revealed that CT number of 130 keV (odds ratio [OR] = 1.02, P = 0.013), maximum cross-sectional long diameter (OR =1.40, P = 0.014), deep or moderate lobulation sign (OR =19.88, P = 0.005), and abnormal intranodular vessel morphology (OR = 25.57, P = 0.017) were independent predictors of IAC. The combined prediction model showed a favorable differentiation performance with an AUC of 0.966 (95.2% sensitivity, 94.3% specificity, 94.8% accuracy), which was significantly higher than that for each risk factor (AUC = 0.791-0.822, all P < 0.05). CONCLUSION A multi-parameter combined prediction model integrating monochromatic CT numbers from DECT and quantitative-semantic features is promising for the preoperative discrimination of IAC and AIS-MIA in GGN-predominant lung adenocarcinoma.
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Affiliation(s)
- Mingwang Chen
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Li Ding
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Shuting Deng
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Jingxu Li
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
| | - Xiaomei Li
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Mingjue Jian
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Zhao Chen
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Chenggong Yan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
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Steiner D, Sultan L, Sullivan T, Liu H, Zhang S, LeClerc A, Alekseyev YO, Liu G, Mazzilli SA, Zhang J, Rieger-Christ K, Burks EJ, Beane J, Lenburg ME. Identification of a gene expression signature of vascular invasion and recurrence in stage I lung adenocarcinoma via bulk and spatial transcriptomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.07.597993. [PMID: 38915565 PMCID: PMC11195124 DOI: 10.1101/2024.06.07.597993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Microscopic vascular invasion (VI) is predictive of recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but is difficult to assess in resection specimens and cannot be accurately predicted prior to surgery. Thus, new biomarkers are needed to identify this aggressive subset of stage I LUAD tumors. To assess molecular and microenvironment features associated with angioinvasive LUAD we profiled 162 resected stage I tumors with and without VI by RNA-seq and explored spatial patterns of gene expression in a subset of 15 samples by high-resolution spatial transcriptomics (stRNA-seq). Despite the small size of invaded blood vessels, we identified a gene expression signature of VI from the bulk RNA-seq discovery cohort (n=103) and found that it was associated with VI foci, desmoplastic stroma, and high-grade patterns in our stRNA-seq data. We observed a stronger association with high-grade patterns from VI+ compared with VI- tumors. Using the discovery cohort, we developed a transcriptomic predictor of VI, that in an independent validation cohort (n=60) was associated with VI (AUROC=0.86; p=5.42×10-6) and predictive of recurrence-free survival (HR=1.98; p=0.024), even in VI- LUAD (HR=2.76; p=0.003). To determine our VI predictor's robustness to intra-tumor heterogeneity we used RNA-seq data from multi-region sampling of stage I LUAD cases in TRACERx, where the predictor scores showed high correlation (R=0.87, p<2.2×10-16) between two randomly sampled regions of the same tumor. Our study suggests that VI-associated gene expression changes are detectable beyond the site of intravasation and can be used to predict the presence of VI. This may enable the prediction of angioinvasive LUAD from biopsy specimens, allowing for more tailored medical and surgical management of stage I LUAD.
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Affiliation(s)
- Dylan Steiner
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Lila Sultan
- Department of Pathology and Laboratory Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Travis Sullivan
- Department of Translational Research, Lahey Hospital and Medical Center, Burlington, MA, USA
| | - Hanqiao Liu
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Sherry Zhang
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Ashley LeClerc
- Boston University Microarray and Sequencing Resource Core Facility, Boston, MA, USA
| | - Yuriy O Alekseyev
- Department of Pathology and Laboratory Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Gang Liu
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Sarah A Mazzilli
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Jiarui Zhang
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Kimberly Rieger-Christ
- Department of Translational Research, Lahey Hospital and Medical Center, Burlington, MA, USA
| | - Eric J Burks
- Department of Pathology and Laboratory Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Jennifer Beane
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Marc E Lenburg
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA, Department of Pathology and Laboratory Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
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Steiner D, Park JA, Singh S, Potter A, Scalera J, Beane J, Suzuki K, Lenburg ME, Burks EJ. A computed tomography-based score indicative of lung cancer aggression (SILA) predicts lung adenocarcinomas with low malignant potential or vascular invasion. Cancer Biomark 2024:CBM230456. [PMID: 39058440 DOI: 10.3233/cbm-230456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2024]
Abstract
BACKGROUND Histologic grading of lung adenocarcinoma (LUAD) is predictive of outcome but is only possible after surgical resection. A radiomic biomarker predictive of grade has the potential to improve preoperative management of early-stage LUAD. OBJECTIVE Validate a prognostic radiomic score indicative of lung cancer aggression (SILA) in surgically resected stage I LUAD (n= 161) histologically graded as indolent low malignant potential (LMP), intermediate, or aggressive vascular invasive (VI) subtypes. METHODS The SILA scores were generated from preoperative CT-scans using the previously validated Computer-Aided Nodule Assessment and Risk Yield (CANARY) software. RESULTS Cox proportional regression showed significant association between the SILA and 7-year recurrence-free survival (RFS) in a univariate (p< 0.05) and multivariate (p< 0.05) model incorporating age, gender, smoking status, pack years, and extent of resection. The SILA was positively correlated with invasive size (spearman r= 0.54, p= 8.0 × 10 - 14) and negatively correlated with percentage of lepidic histology (spearman r=-0.46, p= 7.1 × 10 - 10). The SILA predicted indolent LMP with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.74 and aggressive VI with an AUC of 0.71, the latter remaining significant when invasive size was included as a covariate in a logistic regression model (p< 0.01). CONCLUSIONS The SILA scoring of preoperative CT scans was prognostic and predictive of resected pathologic grade.
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Affiliation(s)
- Dylan Steiner
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
| | - Ju Ae Park
- Thoracic Surgery, Inova Schar Cancer Institute, Fairfax, VA, USA
| | - Sarah Singh
- Department of Radiology, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
| | - Austin Potter
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
| | - Jonathan Scalera
- Department of Radiology, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
| | - Jennifer Beane
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
| | - Kei Suzuki
- Thoracic Surgery, Inova Schar Cancer Institute, Fairfax, VA, USA
| | - Marc E Lenburg
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
- Department of Pathology, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
| | - Eric J Burks
- Department of Pathology, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
- Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA
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Nicotra S, Melan L, Pezzuto F, Bonis A, Silvestrin S, Verzeletti V, Cannone G, Rebusso A, Comacchio GM, Schiavon M, Dell'Amore A, Calabrese F, Rea F. Significance of Spread Through Air Spaces and Vascular Invasion in Early-stage Adenocarcinoma Survival: A Comprehensive Clinicopathologic Study of 427 Patients for Precision Management. Am J Surg Pathol 2024; 48:605-614. [PMID: 38441164 DOI: 10.1097/pas.0000000000002199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/18/2024]
Abstract
Spread through air spaces (STAS) is a novel invasive pattern of lung cancer associated with poor prognosis in non-small cell cancer (NSCLC). We aimed to investigate the incidence of STAS in a surgical series of adenocarcinomas (ADCs) resected in our thoracic surgery unit and to identify the association of STAS with other clinicopathological characteristics. We retrospectively enrolled patients with stage cT1a-cT2b who underwent resection between 2016 and 2022. For each case, a comprehensive pathologic report was accessible which included histotype, mitoses, pleural invasion, fibrosis, tumor infiltrating lymphocytes, necrosis, inflammation, vascular and perineural invasion, as well as STAS. PD-L1 expression was also investigated. A total of 427 patients with ADCs underwent surgery. Regarding overall survival (OS), no significant difference was observed between the STAS positive (STAS+) and STAS negative (STAS-) groups ( P =0.44). However, vascular invasion (VI) was associated with a poorer survival probability ( P =0.018). STAS+/VI+ patients had tendentially worse survival compared with STAS+/VI- ( P =0.089). ADCs with pathologic evidence of immune system (IS) activation (TILs>10% and PD-L1≥1) demonstrated significantly increased OS compared with ADCs with no IS and VI. In terms of recurrence rate, no statistical differences were found between the STAS+ and STAS- samples ( P =0.2). VI was also linked to a significantly elevated risk of recurrence ( P =0.0048). Our study suggests that in resected early-stage ADCs, STAS+ does not seem to influence recurrence or mortality. VI was instead an adverse pathologic prognostic factor for both survival and recurrence, whereas IS seemed to be protective.
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Affiliation(s)
| | | | - Federica Pezzuto
- Pathology Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | | | | | | | | | | | | | | | | | - Fiorella Calabrese
- Pathology Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy
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Jiang MQ, Qian LQ, Shen YJ, Fu YY, Feng W, Ding ZP, Han YC, Fu XL. Who benefit from adjuvant chemotherapy in stage I lung adenocarcinoma? A multi-dimensional model for candidate selection. Neoplasia 2024; 50:100979. [PMID: 38387107 PMCID: PMC10899011 DOI: 10.1016/j.neo.2024.100979] [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: 11/09/2023] [Accepted: 02/14/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND Despite promising overall survival of stage I lung adenocarcinoma (LUAD) patients, 10-25 % of them still went through recurrence after surgery. [1] While it is still disputable whether adjuvant chemotherapy is necessary for stage I patients. [2] IASLC grading system for non-mucinous LUAD shows that minor high-grade patterns are significant indicator of poor prognosis. [3] Other risk factors, such as, pleura invasion, lympho-vascular invasion, STAS, etc. are also related to poor prognosis. [4-6] There still lack evidence whether IASLC grade itself or together with other risk factors can guide the use of adjuvant therapy in stage I patients. In this article, we tried to establish a multi-variable recurrence prediction model for stage I LUAD patients that is able to identify candidates of adjuvant chemotherapy. METHODS We retrospectively collected patients who underwent lung surgery from 2018.8.1 to 2018.12.31 at our institution and diagnosed with lung adenocarcinoma pT1-2aN0M0 (stage I). Clinical data, manifestation on CT scan, pathologic features, driver gene mutations and follow-up information were collected. Cox proportional hazards regression analyses were performed utilizing the non-adjuvant cohort to predict disease free survival (DFS) and a nomogram was constructed and applied to the total cohort. Kaplan-Meier method was used to compare DFS between groups. Statistical analysis was conducted by R version 3.6.3. FINDINGS A total of 913 stage I LUAD patients were included in this study. Median follow-up time is 48.1 months.4-year and 5-year DFS are 92.9 % and 89.6 % for the total cohort. 65 patient experienced recurrence or death. 4-year DFS are 97.0 %,94.6 % and 76.2 %, and 5-year DFS are 95.5 %, 90.0 % and 74.1 % in IASLC Grade1, 2 and 3, respectively(p < 0.0001). High-risk patients defined by single risk factors, such as, IASLC grade 3, pleura invasion, STAS, less LN resected could not benefit from adjuvant therapy. A LASSO-COX regression model was built and patients are divided into high-risk and low-risk groups. In the high-risk group, patients underwent adjuvant chemotherapy have longer DFS than those who did not (p = 0.024), while in the low-risk group, patients underwent adjuvant chemotherapy have inferior DFS than those who did not (p < 0.001). INTERPRETATION IASLC grading is a significant indicator of DFS, however it could not guide adjuvant therapy in our stage I LUAD cohort. Growth patterns and T indicators together with other risk factors could identify high-risk patients that are potential candidate of adjuvant therapy, including some stage IA LUAD patients.
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Affiliation(s)
- Meng-Qi Jiang
- Department of Radiation Oncology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li-Qiang Qian
- Department of Thoracic Surgery, Shanghai Lung Cancer Center, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yu-Jia Shen
- Department of Radiation Oncology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yuan-Yuan Fu
- Department of Radiation Oncology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wen Feng
- Department of Radiation Oncology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zheng-Ping Ding
- Department of Thoracic Surgery, Shanghai Lung Cancer Center, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yu-Chen Han
- Department of Pathology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Xiao-Long Fu
- Department of Radiation Oncology, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
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Kim PJ, Hwang HS, Choi G, Sung HJ, Ahn B, Uh JS, Yoon S, Kim D, Chun SM, Jang SJ, Go H. A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma. Sci Rep 2024; 14:6366. [PMID: 38493247 PMCID: PMC10944489 DOI: 10.1038/s41598-024-56867-9] [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: 04/18/2023] [Accepted: 03/12/2024] [Indexed: 03/18/2024] Open
Abstract
This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung adenocarcinoma (LUAD) based on its histopathological features. Clinicopathological data and whole slide images from 164 LUAD cases were collected and used to train DL models with an ImageNet pre-trained efficientnet-b2 architecture, densenet201, and resnet152. The models were trained to classify each image patch into high-risk or low-risk groups, and the case-level result was determined by multiple instance learning with final FC layer's features from a model from all patches. Analysis of the clinicopathological and genetic characteristics of the model-based risk group was performed. For predicting recurrence, the model had an area under the curve score of 0.763 with 0.750, 0.633 and 0.680 of sensitivity, specificity, and accuracy in the test set, respectively. High-risk cases for recurrence predicted by the model (HR group) were significantly associated with shorter recurrence-free survival and a higher stage (both, p < 0.001). The HR group was associated with specific histopathological features such as poorly differentiated components, complex glandular pattern components, tumor spread through air spaces, and a higher grade. In the HR group, pleural invasion, necrosis, and lymphatic invasion were more frequent, and the size of the invasion was larger (all, p < 0.001). Several genetic mutations, including TP53 (p = 0.007) mutations, were more frequently found in the HR group. The results of stages I-II were similar to those of the general cohort. DL-based model can predict the recurrence risk of LUAD and identify the presence of the TP53 gene mutation by analyzing histopathologic features.
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Affiliation(s)
- Pil-Jong Kim
- School of Dentistry and Dental Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Hee Sang Hwang
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Gyuheon Choi
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Hyun-Jung Sung
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Bokyung Ahn
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Ji-Su Uh
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Shinkyo Yoon
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Deokhoon Kim
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sung-Min Chun
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Se Jin Jang
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Heounjeong Go
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
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Deng L, Tang HZ, Luo YW, Feng F, Wu JY, Li Q, Qiang JW. Preoperative CT Radiomics Nomogram for Predicting Microvascular Invasion in Stage I Non-Small Cell Lung Cancer. Acad Radiol 2024; 31:46-57. [PMID: 37331866 DOI: 10.1016/j.acra.2023.05.015] [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: 03/03/2023] [Revised: 05/08/2023] [Accepted: 05/15/2023] [Indexed: 06/20/2023]
Abstract
RATIONALE AND OBJECTIVES: This study aims to develop and validate a nomogram integrating clinical-CT and radiomic features for preoperative prediction of microvascular invasion (MVI) in patients with stage I non‑small cell lung cancer (NSCLC). MATERIALS AND METHODS This retrospective study analyzed 188 cases of stage I NSCLC (63 MVI positives and 125 negatives), which were randomly assigned to training (n = 133) and validation cohorts (n = 55) at a ratio of 7:3. Preoperative non-contrast and contrast-enhanced CT (CECT) images were used to analyze computed tomography (CT) features and extract radiomics features. The student's t-test, the Mann-Whitney-U test, the Pearson correlation, the least absolute shrinkage and selection operator, and multivariable logistic analysis were used to select the significant CT and radiomics features. Multivariable logistic regression analysis was performed to build the clinical-CT, radiomics, and integrated models. The predictive performances were evaluated through the receiver operating characteristic curve and compared with the DeLong test. The integrated nomogram was analyzed regarding discrimination, calibration, and clinical significance. RESULTS The rad-score was developed with one shape and four textural features. The integrated nomogram incorporating radiomics score, spiculation, and the number of tumor-related vessels (TVN) demonstrated better predictive efficacy than the radiomics and clinical-CT models in the training cohort (area under the curve [AUC], 0.893 vs 0.853 and 0.828, and p = 0.043 and 0.027, respectively) and validation cohort (AUC, 0.887 vs 0.878 and 0.786, and p = 0.761 and 0.043, respectively). The nomogram also demonstrated good calibration and clinical usefulness. CONCLUSION The radiomics nomogram integrating the radiomics with clinical-CT features demonstrated good performance in predicting MVI status in stage I NSCLC. The nomogram may be a useful tool for physicians in improving personalized management of stage I NSCLC.
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Affiliation(s)
- Lin Deng
- Department of Radiology, Jinshan Hospital & Shanghai Medical College, Fudan University, Shanghai, China (L.D., H.Z.T., J.Y.W., J.W.Q.)
| | - Han Zhou Tang
- Department of Radiology, Jinshan Hospital & Shanghai Medical College, Fudan University, Shanghai, China (L.D., H.Z.T., J.Y.W., J.W.Q.)
| | - Ying Wei Luo
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center/Cancer Hospital, Guangzhou, China (Y.W.L., Q.L.)
| | - Feng Feng
- Department of Radiology, Affiliated Tumor Hospital of Nantong University, Nantong, China (F.F.)
| | - Jing Yan Wu
- Department of Radiology, Jinshan Hospital & Shanghai Medical College, Fudan University, Shanghai, China (L.D., H.Z.T., J.Y.W., J.W.Q.)
| | - Qiong Li
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center/Cancer Hospital, Guangzhou, China (Y.W.L., Q.L.)
| | - Jin Wei Qiang
- Department of Radiology, Jinshan Hospital & Shanghai Medical College, Fudan University, Shanghai, China (L.D., H.Z.T., J.Y.W., J.W.Q.).
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Xue W, Kong L, Zhang X, Xin Z, Zhao Q, He J, Wu W, Duan G. Tumor blood vessel in 3D reconstruction CT imaging as an risk indicator for growth of pulmonary nodule with ground-glass opacity. J Cardiothorac Surg 2023; 18:333. [PMID: 37968739 PMCID: PMC10647107 DOI: 10.1186/s13019-023-02423-x] [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: 02/06/2023] [Accepted: 11/03/2023] [Indexed: 11/17/2023] Open
Abstract
OBJECTIVE Despite the vital role of blood perfusion in tumor progression, in patients with persistent pulmonary nodule with ground-glass opacity (GGO) is still unclear. This study aims to investigate the relationship between tumor blood vessel and the growth of persistent malignant pulmonary nodules with ground-glass opacity (GGO). METHODS We collected 116 cases with persistent malignant pulmonary nodules, including 62 patients as stable versus 54 patients in the growth group, from 2017 to 2021. Three statistical methods of logistic regression model, Kaplan-Meier analysis regression analysis were used to explore the potential risk factors for growth of malignant pulmonary nodules with GGO. RESULTS Multivariate variables logistic regression analysis and Kaplan-Meier analysis identified that tumor blood vessel diameter (p = 0.013) was an significant risk factor in the growth of nodules and Cut-off value of tumor blood vessel diameter was 0.9 mm with its specificity 82.3% and sensitivity 66.7%.While in subgroup analysis, for the GGO CTR < 0.5[C(the maximum diameter of consolidation in tumor)/T(the maximum diameter of the whole tumor including GGO) ratio], tumor blood vessel diameter (p = 0.027) was important during the growing processes of nodules. CONCLUSIONS The tumor blood vessel diameter of GGO lesion was closely associated with the growth of malignant pulmonary nodules. The results of this study would provide evidence for effective follow-up strategies for pulmonary nodule screening.
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Affiliation(s)
- Wenfei Xue
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
| | - Lingxin Kong
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
- Graduate School, Hebei Medical University, Shijiazhuang, 050000, China
| | - Xiaopeng Zhang
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
| | - Zhifei Xin
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
| | - Qingtao Zhao
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
| | - Jie He
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
| | - Wenbo Wu
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China
| | - Guochen Duan
- Department of Thoracic Surgery, Hebei Province General Hospital, No. 348, Heping Road West, Xinhua District, Shijiazhuang, 050000, China.
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Chen Z, Yue Z, Yang K, Shen C, Cheng Z, Zhou X, Li S. Four Ounces Can Move a Thousand Pounds: The Enormous Value of Nanomaterials in Tumor Immunotherapy. Adv Healthc Mater 2023; 12:e2300882. [PMID: 37539730 DOI: 10.1002/adhm.202300882] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 07/17/2023] [Indexed: 08/05/2023]
Abstract
The application of nanomaterials in healthcare has emerged as a promising strategy due to their unique structural diversity, surface properties, and compositional diversity. In particular, nanomaterials have found a significant role in improving drug delivery and inhibiting the growth and metastasis of tumor cells. Moreover, recent studies have highlighted their potential in modulating the tumor microenvironment (TME) and enhancing the activity of immune cells to improve tumor therapy efficacy. Various types of nanomaterials are currently utilized as drug carriers, immunosuppressants, immune activators, immunoassay reagents, and more for tumor immunotherapy. Necessarily, nanomaterials used for tumor immunotherapy can be grouped into two categories: organic and inorganic nanomaterials. Though both have shown the ability to achieve the purpose of tumor immunotherapy, their composition and structural properties result in differences in their mechanisms and modes of action. Organic nanomaterials can be further divided into organic polymers, cell membranes, nanoemulsion-modified, and hydrogel forms. At the same time, inorganic nanomaterials can be broadly classified as nonmetallic and metallic nanomaterials. The current work aims to explore the mechanisms of action of these different types of nanomaterials and their prospects for promoting tumor immunotherapy.
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Affiliation(s)
- Ziyin Chen
- Department of Urology, China-Japan Friendship Hospital, 100029, Beijing, P. R. China
| | - Ziqi Yue
- Department of Forensic Medicine, Harbin Medical University, 150001, Harbin, P. R. China
| | - Kaiqi Yang
- Clinical Medicine, Harbin Medical University, 150001, Harbin, P. R. China
| | - Congrong Shen
- Department of Urology, China-Japan Friendship Hospital, 100029, Beijing, P. R. China
| | - Zhe Cheng
- Department of Forensic Medicine, Harbin Medical University, 150001, Harbin, P. R. China
| | - Xiaofeng Zhou
- Department of Urology, China-Japan Friendship Hospital, 100029, Beijing, P. R. China
| | - Shenglong Li
- Second Ward of Bone and Soft Tissue Tumor Surgery, Cancer Hospital of Dalian University of Technology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, 110042, Shenyang, P. R. China
- The Liaoning Provincial Key Laboratory of Interdisciplinary Research on Gastrointestinal Tumor Combining Medicine with Engineering, Shenyang, 110042, China
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10
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Zhang Y, Hu Y, Zhang S, Zhu M, Lu J, Hu B, Guo X, Zhang Y. Effects of pre-operative biopsy on recurrence and survival in stage I lung adenocarcinoma patients in China. ERJ Open Res 2023; 9:00675-2022. [PMID: 37583968 PMCID: PMC10423981 DOI: 10.1183/23120541.00675-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 05/04/2023] [Indexed: 08/17/2023] Open
Abstract
Background Whether pre-operative biopsy affects post-operative recurrence and metastasis of lung cancer patients is still controversial. Methods In order to clarify these disputes, we collected relevant literature to conduct a meta-analysis. To validate the results of the meta-analysis, we retrospectively analysed 575 patients with stage I lung adenocarcinoma who underwent surgical resection at our centre from 2010 to 2018 using propensity score matching and competing risk models. Results 5509 lung cancer patients from 11 articles were included in the meta-analysis. Summary analysis showed that the total recurrence rate of the biopsy group was higher than that of the nonbiopsy group (risk ratio 1.690, 95% CI 1.220-2.330; p=0.001). After propensity score matching, we found that there was no significant correlation between biopsy and total recurrence (risk ratio 1.070, 95% CI 0.540-2.120; p=0.850). In our cohort, of 575 stage I lung adenocarcinomas, 113 (19.7%) patients underwent pre-operative biopsy. During a median (interquartile range) follow-up of 71 (57-93) months, multivariable analyses showed pre-operative biopsy in the overall observation cohort (subdistribution hazard ratio (SHR) 1.522, 95% CI 0.997-2.320; p=0.051) and in the propensity score-matched cohort (SHR 1.134, 95% CI 0.709-1.810; p=0.600) was not significantly correlated with the risk of recurrence and metastasis. Moreover, the pre-operative biopsy did not affect disease-free survival (SHR 0.853, 95% CI 0.572-1.273; p=0.438) or overall survival (SHR 0.647, 95% CI 0.352-1.189; p=0.161). Conclusion Pre-operative biopsy might not increase the risk of recurrence and metastasis, suggesting that these procedures might be safe for patients with stage I lung adenocarcinoma whose diagnosis is difficult to determine before surgery.
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Affiliation(s)
- Yuan Zhang
- Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing Institute of Respiratory Medicine, Beijing, China
- These authors contributed equally
| | - Yi Hu
- Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing Institute of Respiratory Medicine, Beijing, China
- These authors contributed equally
| | - Shu Zhang
- Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing Institute of Respiratory Medicine, Beijing, China
| | - Min Zhu
- Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing Institute of Respiratory Medicine, Beijing, China
| | - Jun Lu
- Department of Pathology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Bin Hu
- Department of Thoracic Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Xiaojuan Guo
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Yuhui Zhang
- Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing Institute of Respiratory Medicine, Beijing, China
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11
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Vascular Invasion Predicts Recurrence in Stage IA2-IB Lung Adenocarcinoma but not Squamous Cell Carcinoma. Clin Lung Cancer 2022; 24:e126-e133. [PMID: 36631388 DOI: 10.1016/j.cllc.2022.12.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/02/2022] [Accepted: 12/20/2022] [Indexed: 12/26/2022]
Abstract
BACKGROUND Lymphovascular invasion (LVI) is an adverse prognostic feature in resected stage I non-small cell lung cancer (NSCLC); however, it is unclear if the prognostic significance applies to both lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). MATERIALS AND METHODS A retrospective review of H&E-stained slides from surgically resected AJCC 8th ed. stage IA2-IB LUAD (n = 344) and LUSC (n = 102) from two institutions was performed. LVI was defined as either lymphatic (LI) or vascular (VI) invasion. Outcomes were assessed by 5-year recurrence-free survival (RFS) estimates using the Kaplan-Meier method. RESULTS The cohorts of LUAD and LUSC showed no significant differences in 5-year RFS (81% each), stage, age, race, or surgical procedure. The presence of LVI, VI, and LI was predictive of 5-year RFS for LUAD (LVI + 71% vs. LVI - 92%, P < 0.001; VI + 64% vs. VI - 90%, P < 0.001; LI + 75% vs. LI - 84%, P = 0.030) but not LUSC (LVI + 84% vs. LVI - 79%, P = 0.740; VI + 83% vs. VI- 80%, P = 0.852; LI + 84% vs. LI - 81%, P = 0.757). Among LUAD with LVI, VI was a stronger predictor of 5-year RFS than the remaining subset of VI-LI + tumors (64% vs. 87%, P = 004). Subset analysis of LI among LUAD stratified by VI showed no significant prognostic advantage to adding LI for risk stratification (VI-LI + 87% vs. VI-LI - 92%, P = 0.347 & VI+LI + 62% vs. VI + LI- 66%, P = 0.422). VI was present in 36% of LUAD. CONCLUSION Vascular invasion is a strong predictor of recurrence in stage IA2-IB LUAD but not in LUSC. Adjuvant therapy trials should be directed at this subgroup.
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12
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Yambayev I, Sullivan TB, Rieger-Christ KM, Servais EL, Stock CT, Quadri SM, Sands JM, Suzuki K, Burks EJ. Vascular invasion identifies the most aggressive histologic subset of stage I lung adenocarcinoma: Implications for adjuvant therapy. Lung Cancer 2022; 171:82-89. [DOI: 10.1016/j.lungcan.2022.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 07/08/2022] [Accepted: 07/21/2022] [Indexed: 11/15/2022]
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13
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Ahn B, Yoon S, Kim D, Chun SM, Lee G, Kim HR, Jin Jang S, Sang Hwang H. Clinicopathologic and genomic features of high-grade pattern and their subclasses in lung adenocarcinoma. Lung Cancer 2022; 170:176-184. [PMID: 35820357 DOI: 10.1016/j.lungcan.2022.07.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 06/28/2022] [Accepted: 07/04/2022] [Indexed: 10/17/2022]
Abstract
INTRODUCTION Recent lung adenocarcinoma (LUAD) grading system proposed by the International Association for the Study of Lung Cancer (IASLC) has emphasized the proportion of high-grade patterns (HGPs). We aimed to evaluate the clinicopathologic and genomic characteristics associated with HGP which has not yet been fully investigated. METHODS Tissue samples from 174 patients who underwent surgical resection of LUAD from January to December 2015 were histologically evaluated. Proportions of HGPs, including solid, micropapillary, cribriform, and complex glandular patterns, were individually quantified. Prognostic implications of HGP proportion, both as a continuous variable and as subclasses divided by cutoffs of 20%, 50%, and 90% (low-intermediate grade [LIG], HGP <20%; high grade 1 [HG1], 20-<50%, HG2, 50-<90%; HG3, ≥90%) were evaluated. Different clinicopathologic factors and genomic alterations according to the HGP subclasses were assessed. RESULTS Relative hazards of the HGP gradually elevated as its proportion increased over 20%, the cut-off value established by the IASLC grading system, and the cancer-specific overall survival (OS) of HG1 subclass was not significantly decreased compared to the LIG subclass on univariate analysis. However, further subgrouping showed significantly increased frequencies of male, advanced stage tumors, lymphovascular invasion, and spread through alveolar space in higher HGP subclasses. Also, common LUAD driver mutations, particularly EGFR mutations, were less frequent, whereas alterations in TP53 and cell cycle pathway-related genes were more frequent. Higher HGP subclasses and TP53 gene alteration were associated with shorter cancer-specific OS and RFS in multivariate survival analysis. CONCLUSIONS HGP subclasses of LUAD displayed distinct clinicopathological characteristics and genomic alterations, including TP53 and cell cycle pathway, emphasizing the clinical value of these subclasses in LUAD. Higher HGP subclass and alteration in TP53 may be markers of poor post-operative survival.
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Affiliation(s)
- Bokyung Ahn
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Shinkyo Yoon
- Department of Oncology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Deokhoon Kim
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Sung-Min Chun
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Goeun Lee
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Hyeong-Ryul Kim
- Department of Thoracic and Cardiovascular Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Se Jin Jang
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Hee Sang Hwang
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
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Lymph but Not Blood Vessel Invasion Is Independent Prognostic in Lung Cancer Patients Treated by VATS-Lobectomy and Might Represent a Future Upstaging Factor for Early Stages. Cancers (Basel) 2022; 14:cancers14081893. [PMID: 35454799 PMCID: PMC9031652 DOI: 10.3390/cancers14081893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 04/02/2022] [Accepted: 04/06/2022] [Indexed: 12/04/2022] Open
Abstract
Lung cancer is the most frequent cause of cancer-related death worldwide. The patient’s outcome depends on tumor size, lymph node involvement and metastatic spread at the time of diagnosis. The prognostic value of lymph and blood vessel invasion, however, is still insufficiently investigated. We retrospectively examined the invasion of lymph vessels and blood vessels separately as two possible prognostic factors in 160 patients who underwent a video-assisted thoracoscopic lobectomy for non-small-cell lung cancer at our institution between 2014 and 2019. Lymph vessel invasion was significantly associated with the UICC stage, lymph node involvement, tumor dedifferentiation, blood vessel invasion and recurrence. Blood vessel invasion tended to be negative prognostic, but missed the level of significance (p = 0.108). Lymph vessel invasion, on the other hand, proved to be a prognostic factor for both histological subtypes, adenocarcinoma (p < 0.001) as well as squamous cell carcinoma (p = 0.018). After multivariate analysis apart from the UICC stage, only lymph vessel invasion remained independently prognostic (p = 0.018). Remarkably, we found analogue survival curve progressions of patients with stage I, with lymph vessel invasion, compared to stage II non-small-cell lung cancer. After further validation in prospective studies, lymph vessel invasion might be considered as an upstaging factor in resectable lung cancer. Especially in the early-stage of the disease, it might represent an additional risk factor to consider adjuvant therapy after surgical resection.
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