Pre-operative Prediction of Ki-67 Expression in Various Histological Subtypes of Lung Adenocarcinoma Based on CT Radiomic Features.

Tumor cell proliferation (Ki-67) expression and its prognostic significance in histological subtypes of lung adenocarcinoma

Objective: To analyze the clinical features and prognostic factors of different histological subtypes of lung adenocarcinoma. Methods: Data from 370 lung adenocarcinoma patients who underwent surgical resection for pathologically supported adenocarcinoma in our hospital between 2000 and 2003 were retro- spectively reviewed. The Kaplan-Meier method was used to estimate patient survival, and Cox’s proportional hazards model was performed for multivariate analysis. Results: The 5-year overall survival rate was 25.26%, and the mean survival time was 3.89 years. In multivariate analysis, histological subtype, incised margin residual, TNM stage, tumor size, and adjuvant chemotherapy were identified as independent survival predictors. The 5-year survival rate in bronchioloalveolar adenocarcinoma (BAC) patients was 41.30%, higher than in patients with other subtypes of lung adenocarcinoma (P=0.002). No significant difference was found in the prognosis among patients with different subtypes of adenocarcinoma without a BAC component. Conclusion: Ade-nocarcinoma with a BAC component is an independent subtype of lung adenocarcinoma. Its prognosis lies between those of BAC and adenocarcinoma without BAC. Histological subtype, incised margin residual, TNM stage, tumor size, and adjuvant chemotherapy are independent survival predictors.

Objective: Solid and micropapillary pattern are highly invasive histologic subtypes in lung adenocarcinoma and are associated with poor prognosis while the biopsy sample is not enough for the accurate histological diagnosis. This study aims to assess the correlation and predictive efficacy between metabolic parameters in (18)F-fluorodeoxy glucose positron emission tomography/computed tomography ((18)F-FDG PET-CT), including the maximum SUV (SUV(max)), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and solid and micropapillary histological subtypes in lung adenocarcinoma. Methods: A total of 145 resected lung adenocarcinomas were included. The clinical data and preoperative (18)F-FDG PET-CT data were retrospectively analyzed. Mann-Whitney U test was used for the comparison of the metabolic parameters between solid and micropapillary subtype group and other subtypes group. Receiver operating characteristic (ROC) curve and areas under curve (AUC) were used for evaluating the prediction efficacy of metabolic parameters for solid or micropapillary patterns. Univariate and multivariate analyses were conducted to determine the prediction factors of the presence of solid or micropapillary subtypes. Results: Median SUV(max) and TLG in solid and papillary predominant subtypes group (15.07 and 34.98, respectively) were significantly higher than those in other subtypes predominant group (6.03 and 10.16, respectively, P<0.05). ROC curve revealed that SUV(max) and TLG had good efficacy for prediction of solid and micropapillary predominant subtypes [AUC=0.811(95% CI: 0.715~0.907) and 0.725(95% CI: 0.610~0.840), P<0.05]. Median SUV(max) and TLG in lung adenocarcinoma with the solid or micropapillary patterns (11.58 and 22.81, respectively) were significantly higher than those in tumors without solid and micropapillary patterns (4.27 and 6.33, respectively, P<0.05). ROC curve revealed that SUV(max) and TLG had good efficacy for predicting the presence of solid or micropapillary patterns [AUC=0.757(95% CI: 0.679~0.834) and 0.681(95% CI: 0.595~0.768), P<0.005]. Multivariate logistic analysis showed that the clinical stage (Stage Ⅲ-Ⅳ), SUV(max) ≥10.27 and TLG≥7.12 were the independent predictive factors of the presence of solid or micropapillary patterns (P<0.05). Conclusions: Preoperative SUV(max) and TLG of lung adenocarcinoma have good prediction efficacy for the presence of solid or micropapillary patterns, especially for the solid and micropapillary predominant subtypes and are independent factors of the presence of solid or micropapillary patterns.

Lung adenocarcinoma is histologically diverse but has distinct histologic growth patterns. There is no consensus on the clinical benefit of this histologic model. We aimed to evaluate the differences in the distribution of the preoperative primary tumor positron emission tomography (PET)/computed tomography (CT) standardized uptake values (SUVs) and survival in the lung adenocarcinoma subtypes. We retrospectively evaluated the data of 107 patients with resected lung adenocarcinoma who had preoperative PET/CT between 2005 and 2017 in a single center. Patients had lepidic, acinar, papillary, micropapillary, and solid histologic subtypes. We compared fluorodeoxyglucose SUVs and survival data of histologic subtypes. The median age of the patients was 62 years (40-75), 76.4% were male, the median SUVmax was 9.4 (1-36.7), and the median follow-up time was 29 months (3-135 months). The median overall survival (OS) was 71 months and the median progression-free survival (PFS) was 33 months. SUVmax was significantly different in histologic subtypes: values for papillary, micropapillary, solid, acinar, and lepidic subtypes were 9.7, 8, 12, 9.1, and 3.9, respectively (p = 0.000). Solid predominant adenocarcinoma had significantly higher SUVmax than the other subtypes (p = 0.001). Lepidic predominant adenocarcinoma had significantly lower SUVmax than the other subtypes (p = 0.000). There was no significant difference in OS between histologic subtypes (p = 0.66), but PFS was significantly different between the groups (p = 0.017), and the solid subtype had a shorter PFS than the other histologic subtypes. Lung adenocarcinoma consists of a diverse group of diseases. Different SUVmax values are seen in different histologic subtypes of nonmetastatic lung adenocarcinoma. Solid predominant types have high SUVmax values while lepidic predominant types have lower SUVmax values. The solid subtype had a shorter PFS than the other histologic subtypes.

The histologic heterogeneity of lung adenocarcinoma is well known. Many histologic subtypes have been described, and recently their prognostic and predictive value has emerged. Laser capture microdissection may aid in the isolation of cancer cells from distinct subtypes of lung adenocarcinoma, thus enabling the description of their specific molecular features. Characterization of epidermal growth factor receptor (EGFR) mutations in histologic subtypes of lung adenocarcinoma has become an important issue. The purpose of this study was to analyze EGFR mutations in exons 18-21 in single histologic subtypes of lung adenocarcinoma after laser capture microdissection. A revision and reclassification of a series of 208 non-small cell lung cancers was conducted, and 62 adenocarcinomas with a total of 119 histologic component subtypes were identified. Laser capture microdissection of each subtype was performed. EGFR mutations in exons 18-21 were detected using polymerase chain reaction single-strand conformation polymorphism and direct DNA sequencing. EGFR mutations were detected only in 3 out of the 62 adenocarcinomas analyzed. Two adenocarcinomas harbored EGFR mutations in exon 19 (the E746-T751 deletion VA insertion and the LREAT deletion) and one adenocarcinoma the EGFR exon 21 L858R missense point mutation. EGFR mutations were observed in all component subtypes. This suggests that, in a patient with lung adenocarcinoma, EGFR mutations are not associated with particular component histologic subtypes and probably occur at an early stage of tumorigenesis. Notably, 2 out of the 3 mutated adenocarcinomas had a bronchioloalveolar component, whereas the third mutated adenocarcinoma had a papillary subtype. Although we detected EGFR mutations only in 3 out of 62 adenocarcinomas and EGFR mutations were present in every subtype of each mutated adenocarcinoma, our research might represent a basis for further studies in characterizing molecular profiles of different component subtypes of lung adenocarcinoma.

1552 Background: The frequencies of known driver mutation in lung adenocarcinoma from patients in the United States have been reported by the NCI’s Lung Cancer Mutation Consortium (LCMC), indicating driver mutations were detected in 54% (280/516) of tumors. In this report, mutations found: EGFR 17%, KRAS 22%, HER2 0.6%, PIK3CA 1.2%, BRAF 2%, MET amplification 0.6%, MAP2K1 0.4%, NRAS 0.4%, AKT 0%, ALK rearrangements 7%. However little is known about ethnic difference of driver mutation frequencies and correlations between driver mutations and histological subtypes in lung adenocarcinoma. Methods: Known driver mutations in tumors from 97 Japanese patients with lung adenocarcinoma who underwent surgical resection between 1999 and 2003 in National Cancer Center Hospital East were analyzed by next-generation sequencing and confirmed by Sanger sequencing. Correlations between driver mutations and histological subtypes were also assessed. Results: Driver mutations were detected in 72% of tumors. Mutations found: EGFR 57%, KRAS9%, HER2 2%, PIK3CA 2%, BRAF 1%, MET amplification 1%, MAP2K1 0%, NRAS 0%, AKT 0%. Due to the limitation of rearrangement detection by exon-sequencing, ALK rearrangements were not analyzed. Compared with the report by LCMC, the frequency of EGFR mutations was high and that of KRAS mutations was low in the present study. All mutations were mutually exclusive. The number of predominant histological subtypes of tumors harbored EGFR mutations were papillary 28, acinar 3, solid 5, lepidic 19. That with KRAS mutations showed papillary 2, acinar 2, solid 2, lepidic 3, and HER2 mutations showed papillary 1 and acinar 1. Two tumors harbored PIK3CA mutations showed both histological acinar pattern. Each of BRAF mutation and MET amplification showed lepidic and papillary pattern, respectively. Conclusions: It was suggested that there should be ethnic difference of driver mutation frequencies in lung adenocarcinoma between Asian and non-Asian patients, although the details of ethnic distribution included in LCMC study has not been opened. In addition, each driver mutations did not correspond to specific histological subtypes of lung adenocarcinoma.

BackgroundAccording to the International Multidisciplinary Classification of Lung Adenocarcinoma (LAD) by International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) in 2011, the diagnosis of LAD is changing from simple morphology into a comprehensive multidisciplinary classification. The aim of this study is to detect the expression of Notch-1 and analyze its clinicopathological or prognostic significance in different histological subtypes of Lung Adenocarcinomas (LADs).MethodsWestern blot and Semi-quantitative Reverse transcription-polymerase chain reaction (RT-PCR) assays, as well as immunohisitochemistry, were performed to detect the expression of Notch-1 in LAD cells and tissue samples. Kaplan-Meier and multivariate Cox regression analyses were performed to evaluate the correlation of Notch-1 expression with clinicopathological factors and prognosis of LAD patients.ResultsThe expression level of Notch-1 protein in LAD cell lines or tissues was significantly lower than that in normal human bronchial epithelial cell line (16HBE) or nontumor tissues (P < 0.05). By statistical analyses, it was observed that negative Notch-1 expression was significantly associated with advanced clinical stage (P = 0.001) and lymph node metastasis (P = 0.026) in LAD patients. Also, the recurrence rate of Notch-1-positive group was higher than the Notch-1-negative group (P = 0.001), and patients with positive Notch-1 expression have a prolonged progression of overall survival (P = 0.033). More interestingly, the expression of Notch-1 protein was often observed to be negative in solid predominant adenocarcinoma (SPA) tissues, but highly expressed in papillary predominant adenocarcinoma (PPA) and micropapillary predominant adenocarcinoma (MPA) tissues. Kaplan-Meier survival analysis showed that patients with positive Notch-1 expression had a prolonged progression of overall survival compared with those with negative Notch-1 expression (P = 0.033). The median survival time of Notch-1-positive or negative patients was 64.6 months (95% CI: 31.497-97.703 months) or 36.0 months (95% CI: 12.132-59.868 months).ConclusionsNotch-1 could be used as a predictable biomarker to be detected in different pathological and histological subtypes in LAD for diagnosis or prognosis.

The Underlying Tumor Genomics of Predominant Histologic Subtypes in Lung Adenocarcinoma.

Adenocarcinoma is the most common type of lung cancer, and pre-operative biopsy plays an important role to determine its major subtypes. As proposed by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) in 2011, the predominant histological subtype of adenocarcinoma is an indicator of outcomes and recurrence rate. However, the value of CT-guided core biopsy in predicting the predominant subtype and detecting the presence of an aggressive subtype of adenocarcinoma, peripheral sub-solid nodule, has less been discussed. We retrospectively reviewed 318 consecutive peripheral sub-solid nodules that underwent percutaneous CT-guided lung biopsy and surgical resection, between October 2015 and December 2018 and were diagnosed as adenocarcinoma with histological subtype. The subtyping results from biopsy and surgical pathology were compared to evaluate the concordance rate. The overall concordance rate between biopsy and surgical pathology in determining the predominant histological subtype was 64%. Better concordance was found in small tumors (≤ 2cm), in predicting either predominant histology (χ2 = 7.091, P = 0.008) or high grade adenocarcinoma, micropapillary and/or solid subtype, MIP-SOL (χ2 = 22.301, P < 0.001). The analysis of ground glass opacity (GGO) component (C/T ratio) obtained significantly higher accuracy in the pure GGO group than in the other two groups in predicting predominant histology or high grade adenocarcinoma (χ2 = 17.560, P < 0.001 and χ2 = 61.938, P < 0.001, respectively). CT-guided core biopsies provide additional value in predicting the histological subtype of lung adenocarcinoma after surgical resection, especially in small tumors (≤ 2cm) or an initially pure GGO group.

Purpose: Up to 50% of Asian patients with NSCLC have EGFR gene mutations, indicating that selecting eligible patients for EGFR-TKIs treatments is clinically important. The aim of the study is to develop and validate radiomics-based nomograms, integrating radiomics, CT features and clinical characteristics, to non-invasively predict EGFR mutation status and subtypes.Materials and Methods: We included 637 patients with lung adenocarcinomas, who performed the EGFR mutations analysis in the current study. The whole dataset was randomly split into a training dataset (n = 322) and validation dataset (n = 315). A sub-dataset of EGFR-mutant lesions (EGFR mutation in exon 19 and in exon 21) was used to explore the capability of radiomic features for predicting EGFR mutation subtypes. Four hundred seventy-five radiomic features were extracted and a radiomics sore (R-score) was constructed by using the least absolute shrinkage and selection operator (LASSO) regression in the training dataset. A radiomics-based nomogram, incorporating clinical characteristics, CT features and R-score was developed in the training dataset and evaluated in the validation dataset.Results: The constructed R-scores achieved promising performance on predicting EGFR mutation status and subtypes, with AUCs of 0.694 and 0.708 in two validation datasets, respectively. Moreover, the constructed radiomics-based nomograms excelled the R-scores, clinical, CT features alone in terms of predicting EGFR mutation status and subtypes, with AUCs of 0.734 and 0.757 in two validation datasets, respectively.Conclusions: Radiomics-based nomogram, incorporating clinical characteristics, CT features and radiomic features, can non-invasively and efficiently predict the EGFR mutation status and thus potentially fulfill the ultimate purpose of precision medicine. The methodology is a possible promising strategy to predict EGFR mutation subtypes, providing the support of clinical treatment scenario.

Background The volume doubling time (VDT) is a key parameter in the differentiation of aggressive tumors from slow-growing tumors. How different histologic subtypes of primary lung adenocarcinomas vary in their VDT and the prognostic value of this measurement is unknown. Purpose To investigate differences in VDT between the predominant histologic subtypes of primary lung adenocarcinomas and to assess the correlation between VDT and prognosis. Materials and Methods This retrospective study included patients who underwent at least two serial CT examinations before undergoing operation between July 2010 and December 2018. Three-dimensional tumor segmentation was performed on two CT images and VDTs were calculated. VDTs were compared between predominant histologic subtypes and lesion types by using Kruskal-Wallis tests. Disease-free survival (DFS) was obtained in patients undergoing surgical procedures before July 2017. Univariable and multivariable Cox proportional hazards regression analyses were performed to determine predictors of DFS. Results Among 268 patients (mean age, 64 years ± 8 [standard deviation]; 143 men), there were 30 lepidic, 87 acinar, 109 papillary, and 42 solid or micropapillary predominant subtypes. The median VDT was 529 days (interquartile range, 278-872 days) for lung adenocarcinomas. VDTs differed across subtypes (P < .001) and were shortest in solid or micropapillary subtypes (229 days; interquartile range, 77-530 days). Solid lesions (VDT, 248 days) had shorter VDTs than subsolid lesions (part-solid lesions, 665 days; nonsolid lesions, 648 days) (P < .001). In the 148 patients (mean age, 64 years ± 8; 89 men) included in the survival analysis, 35 patients had disease recurrence and 17 patients died. VDT (<400 days) was an independent risk factor for poor DFS (hazard ratio, 2.6; P = .01) and higher TNM stage. Adding VDT to TNM stage improved model performance (C-index, 0.69 for TNM stage vs 0.77 for combined VDT class and TNM stage; P = .002). Conclusion Volume doubling times varied significantly according to the predominant histologic subtypes of lung adenocarcinoma and had additional prognostic value for disease-free survival. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Ko in this issue.

BackgroundTo investigate whether quantitative radiomic features extracted from digital breast tomosynthesis (DBT) are associated with Ki-67 expression of breast cancer.Materials and methodsThis is a prospective ethically approved study of 70 women diagnosed with invasive breast cancer in 2018, including 40 low Ki-67 expression (Ki-67 proliferation index <14%) cases and 30 high Ki-67 expression (Ki-67 proliferation index ≥ 14%) cases. A set of 106 quantitative radiomic features, including morphological, grey/scale statistics, and texture features, were extracted from DBT images. After applying least absolute shrinkage and selection operator (LASSO) method to select the most predictive features set for the classifiers, low versus high Ki-67 expression was evaluated by the area under the curve (AUC) at receiver operating characteristic analysis. Correlation coefficient was calculated for the most significant features.ResultsA combination of five features yielded AUC of up to 0.698. The five most predictive features (sphericity, autocorrelation, interquartile range, robust mean absolute deviation, and short-run high grey-level emphasis) showed a statistical significance (p ≤ 0.001) in the classification. Thirty-four features were significantly (p ≤ 0.001) correlated with Ki-67, and five of these had a correlation coefficient of > 0.5.ConclusionThe present study showed that quantitative radiomic imaging features of breast tumour extracted from DBT images are associated with breast cancer Ki-67 expression. Larger studies are needed in order to further evaluate these findings.

P3.01-061 Prognostic Significance of Stem Cell-Related Marker Expression and Its Correlation with Histologic Subtypes in Lung Adenocarcinoma: Topic: Stem Cells in Lung Cancer

To determine whether different subtypes of lung adenocarcinoma (AC) have distinct microRNA (miRNA) expression profiles, and to identify miRNAs associated with aggressive subgroups of resected lung AC. miRNA expression profile analysis was performed in 91 resected lung AC and 10 matched nonmalignant lung tissues using a PCR-based array. An independent cohort of 60 lung ACs was used for validating by quantitative PCR the top 3 prognostic miRNAs. Gene-expression data from 51 miRNA profiled tumors was used for determining transcript-specific miRNA correlations and gene-enrichment pathway analysis. Unsupervised hierarchical clustering of 356 miRNAs identified 3 major clusters of lung AC correlated with stage (P = 0.023), tumor differentiation (P < 0.003), and IASLC histologic subtype of lung AC (P < 0.005). Patients classified in cluster 3 had worse survival as compared with the other clusters. Eleven of 22 miRNAs associated with poor survival were encoded in a large miRNA cluster at 14q32. The top 3 prognostic 14q32 miRNAs (miR-411, miR-370, and miR-376a) were validated in an independent cohort of 60 lung AC. A significant association with cell migration and cell adhesion was found by integrating gene-expression data with miR-411, miR-370, and miR-376a expression. miR-411 knockdown significantly reduced cell migration in lung AC cell lines and this miRNA was overexpressed in tumors from patients who relapsed systemically. Different morphologic subtypes of lung AC have distinct miRNA expression profiles, and 3 miRNAs encoded at 14q32 (miR-411, miR-370, and miR-376a) were associated with poor survival after lung AC resection.

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; To determine whether different subtypes of lung adenocarcinoma (AC) have distinct microRNA (miRNA) expression profiles, and to identify miRNAs associated with aggressive subgroups of resected lung AC.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; miRNA expression profile analysis was performed in 91 resected lung AC and 10 matched nonmalignant lung tissues using a PCR-based array. An independent cohort of 60 lung ACs was used for validating by quantitative PCR the top 3 prognostic miRNAs. Gene-expression data from 51 miRNA profiled tumors was used for determining transcript-specific miRNA correlations and gene-enrichment pathway analysis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; Unsupervised hierarchical clustering of 356 miRNAs identified 3 major clusters of lung AC correlated with stage (&lt;i&gt;P&lt;/i&gt; = 0.023), tumor differentiation (&lt;i&gt;P&lt;/i&gt; &lt; 0.003), and IASLC histologic subtype of lung AC (&lt;i&gt;P&lt;/i&gt; &lt; 0.005). Patients classified in cluster 3 had worse survival as compared with the other clusters. Eleven of 22 miRNAs associated with poor survival were encoded in a large miRNA cluster at 14q32. The top 3 prognostic 14q32 miRNAs (miR-411, miR-370, and miR-376a) were validated in an independent cohort of 60 lung AC. A significant association with cell migration and cell adhesion was found by integrating gene-expression data with miR-411, miR-370, and miR-376a expression. miR-411 knockdown significantly reduced cell migration in lung AC cell lines and this miRNA was overexpressed in tumors from patients who relapsed systemically.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; Different morphologic subtypes of lung AC have distinct miRNA expression profiles, and 3 miRNAs encoded at 14q32 (miR-411, miR-370, and miR-376a) were associated with poor survival after lung AC resection. &lt;i&gt;Clin Cancer Res; 20(12); 3107–17. ©2014 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;