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Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma.

ABSTRACT: Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were segmented semi-automatically. Segmented tumor regions were further subdivided into core and boundary sub-regions, to quantify intensity variations across the tumor. Reproducibility of the features was evaluated in an independent test-retest dataset of 32 patients. The proposed metrics showed high degree of reproducibility in a repeated experiment (concordance, CCC≥0.897; dynamic range, DR≥0.92). Association with overall survival was evaluated by Cox proportional hazard regression, Kaplan-Meier survival curves, and the log-rank test. Both features were associated with overall survival (convexity: p = 0.008; entropy ratio: p = 0.04) in Cohort 1 but not in Cohort 2 (convexity: p = 0.7; entropy ratio: p = 0.8). In both cohorts, these features were found to be descriptive and demonstrated the link between imaging characteristics and patient survival in lung adenocarcinoma.

SUBMITTER: Grove O

PROVIDER: S-EPMC4349806 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma.

Grove Olya O Berglund Anders E AE Schabath Matthew B MB Aerts Hugo J W L HJ Dekker Andre A Wang Hua H Velazquez Emmanuel Rios ER Lambin Philippe P Gu Yuhua Y Balagurunathan Yoganand Y Eikman Edward E Gatenby Robert A RA Eschrich Steven S Gillies Robert J RJ

PloS one 20150304 3

Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were s ...[more]

PMID: 25739030

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Project description:BackgroundColon adenocarcinoma (COAD) is a frequent malignancy of the digestive system with a poor prognosis and high mortality rate worldwide. Intratumor heterogeneity (ITH) is associated with tumor progression, poor prognosis, immunosuppression, and therapy resistance. However, the relationship between ITH and prognosis, the immune microenvironment, and the chemotherapy response in COAD patients remains unknown, and this knowledge is urgently needed.MethodsWe obtained clinical information and gene expression data for COAD patients from The Cancer Genome Atlas (TCGA) database. The DEPTH2 algorithm was utilized to evaluate the ITH score. X-tile software was used to determine the optimal cutoff value of the ITH score. The COAD patients were divided into high- and low-ITH groups based on the cutoff value. We analyzed prognosis, tumor mutation burden (TMB), gene mutations, and immune checkpoint expression between the high- and low-ITH groups. Differentially expressed genes (DEGs) in the high- and low-ITH groups were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. We performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to screen the prognosis-related genes for the construction of an ITH-related prognostic signature. The nomogram was used to predict the overall survival (OS) of COAD patients. The protein-protein interaction (PPI) network was constructed by using the GeneMANIA database. Principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were employed to explore the differences in biological pathway activation status between the high- and low-risk groups. The proportion and type of tumor-infiltrating immune cells were evaluated by the CIBERSORT and ESTIMATE algorithms. Additionally, we assessed the chemotherapy response and predicted small-molecule drugs for treatment. Finally, the expression of the prognosis-related genes was validated by using the UALCAN database and Human Protein Atlas (HPA) database.ResultsThe OS of the high-ITH group was worse than that of the low-ITH group. A positive correlation between ITH and TMB was identified. In subgroups stratified by age, gender, and tumor stage, the OS of the low-ITH group remained better than that of the high-ITH group. There were dramatic differences in the mutated genes, single nucleotide variant classes, variant types, immune checkpoints and cooccurring and mutually exclusive mutations of the DEGs between the high- and low-ITH groups. Based on the DEGs between the high- and low-ITH groups, we constructed a five-gene signature consisting of CEACAM5, ENO2, GABBR1, MC1R, and SLC44A4. The COAD patients were divided into high- and low-risk groups according to the median risk score. The OS of the high-risk group was worse than that of the low-risk group. The nomogram was used to accurately predict the 1-, 3- and 5-year OS of COAD patients and showed good calibration and moderate discrimination ability. The stromal score, immune score, and ESTIMATE score of the high-risk group were significantly higher than those of the low-risk group, whereas tumor purity showed the opposite trend. The patients classified by the risk score had distinguishable sensitivity to chemotherapeutic drugs. Finally, two public databases confirmed that CEACAM5 and SLC44A4 were upregulated in normal tissues compared with COAD tissues, and ENO2, GABBR1, and MC1R were upregulated in COAD tissues compared with normal tissues.ConclusionOverall, we identified an ITH-related prognostic signature for COAD that was closely related to the tumor microenvironment and chemotherapy response. This signature may help clinicians make more personalized and precise treatment decisions for COAD patients.

Project description:Pancreatic ductal adenocarcinoma (PDAC) tumor interpatient heterogeneity has been well described with two major prognostic subtypes (classical and basal-like). An important intrapatient heterogeneity has been reported but has not yet been studied extensively due to the lack of standardized, reproducible, and easily accessible high-throughput methods. We built an immunohistochemical (IHC) tool capable of differentiating RNA-defined classical and basal-like tumors by selecting relevant antibodies using a multistep process. The successive stages of (i) an in silico selection from a literature review and a bulk transcriptome analysis of 309 PDACs, (ii) a tumor-specific selection from 30 patient-derived xenografts and single-cell data, followed by (iii) the validation on tissue microarrays in 50 PDAC were conducted. We used our final IHC panel on two independent cohorts of resected PDAC (n = 95, whole-slide, n = 148, tissue microarrays) for external validation. After digitization and registration of pathology slides, we performed a tile-based analysis in tumor areas to identify relevant marker combinations. Sequential marker selection led to the following panel: GATA6, CLDN18, TFF1, MUC16, S100A2, KRT17, PanBasal. Four different phenotypes were identified: one classical, one intermediate (KRT17+), and two basal-like (MUC16+ versus S100A2+) with specific biological properties. The presence of a minor basal contingent drastically reduced overall survival [hazard ratio (HR) = 1.90, p = 0.03], even in classical predominant PDACs. Analysis of preneoplastic lesions suggested that pancreatic carcinogenesis might follow a progressive evolution from classical toward a basal through an early intermediate phenotype. In conclusion, our IHC panel redefined and easily assessed the high degree of intra- and intertumoral heterogeneity of PDAC. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Dataset Information

Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma.

Publications

Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma.

Similar Datasets

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