Computed Tomography Features associated With the Eighth Edition TNM Stage Classification for Thymic Epithelial Tumors.

PURPOSE: The eighth edition of the TNM classification of malignant tumors for the first time includes an official staging system for thymic epithelial tumors (TETs) recognized by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). Staging is critical for the management of TETs, and determining stage accurately from imaging has the potential to improve clinical outcomes. We examine preoperative computed tomography (CT) characteristics of TETs associated with AJCC/UICC pathologic TNM stage. MATERIALS AND METHODS: In this retrospective study, patients were included if they met all the following criteria: (1) diagnosis of TET, (2) had primary curative intent surgery performed at Stanford University, and (3) had available preoperative CT imaging for review. Tumor pathology was staged according to the eighth edition TNM classification. Fifteen CT scan features were examined from each patient case according to the International Thymic Malignancy Interest Group standard report terms in a blinded manner. A Lasso-regularized multivariate model was used to produce a weighted scoring system predictive of pathologic TNM stage. RESULTS: Examining the 54 patients included, the following CT characteristics were associated with higher pathologic TNM stage when using the following scoring system: elevated hemidiaphragm (score of 6), vascular endoluminal invasion (score of 6), pleural nodule (score of 2), lobulated contour (score of 2), and heterogeneous internal density (score of 1). Area under the receiver operating characteristic curve was 0.76. CONCLUSIONS: TETs with clearly invasive or metastatic features seen on CT are associated with having higher AJCC/UICC pathologic TNM stage, as expected. However, features of lobulated contour and heterogeneous internal density are also associated with higher stage disease. These findings need to be validated in an independent cohort.

Presence of Even a Small Ground-Glass Component in Lung Adenocarcinoma Predicts Better Survival.

BACKGROUND: While lepidic-predominant lung adenocarcinomas are known to have better outcomes than similarly sized solid tumors, the impact of smaller noninvasive foci within predominantly solid tumors is less clearly characterized. We tested the hypothesis that lung adenocarcinomas with even a small ground-glass opacity (GGO) component have a better prognosis than otherwise similar pure solid (PS) adenocarcinomas. PATIENTS AND METHODS: The maximum total and solid-component diameters were determined by preoperative computed tomography in patients who underwent lobar or sublobar resection of clinical N0 adenocarcinomas without induction therapy between May 2003 and August 2013. Survival between patients with PS tumors (0% GGO) or tumors with a minor ground-glass (MGG) component (1%-25% GGO) was compared by Kaplan-Meier and Cox analyses. RESULTS: A total of 123 patients met the inclusion criteria, comprising 54 PS (44%) and 69 MGG (56%) whose mean ground-glass component was 18 ± 7%. The solid component tumor diameter was not significantly different between the groups (2.3 ± 1.2 cm vs. 2.5 ± 1.3 cm, P = .2). Upstaging to pN1-2 was more common for the PS group (13% [7/54] vs. 3% [2/69], P = .04), but the distribution of pathologic stage was not significantly different between the groups (PS 76% stage I [41/54] vs. MGG 80% stage I [55/69], P = .1). Having a MGG component was associated with markedly better survival in both univariate analysis (MGG 5-year overall survival 86.7% vs. PS 64.5%, P = .001) and multivariable survival analysis (hazard ratio, 0.30, P = .01). CONCLUSION: Patients with resected cN0 lung adenocarcinoma who have even a small GGO component have markedly better survival than patients with PS tumors, which may have implications for both treatment and surveillance strategies.

Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics.

This study investigated the relationship between epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in non-small-cell lung cancer (NSCLC) and quantitative FDG-PET/CT parameters including tumor heterogeneity. 131 patients with NSCLC underwent staging FDG-PET/CT followed by tumor resection and histopathological analysis that included testing for the EGFR and KRAS gene mutations. Patient and lesion characteristics, including smoking habits and FDG uptake parameters, were correlated to each gene mutation. Never-smoker (P < 0.001) or low pack-year smoking history (p = 0.002) and female gender (p = 0.047) were predictive factors for the presence of the EGFR mutations. Being a current or former smoker was a predictive factor for the KRAS mutations (p = 0.018). The maximum standardized uptake value (SUVmax) of FDG uptake in lung lesions was a predictive factor of the EGFR mutations (p = 0.029), while metabolic tumor volume and total lesion glycolysis were not predictive. Amongst several tumor heterogeneity metrics included in our analysis, inverse coefficient of variation (1/COV) was a predictive factor (p < 0.02) of EGFR mutations status, independent of metabolic tumor diameter. Multivariate analysis showed that being a never-smoker was the most significant factor (p < 0.001) for the EGFR mutations in lung cancer overall. The tumor heterogeneity metric 1/COV and SUVmax were both predictive for the EGFR mutations in NSCLC in a univariate analysis. Overall, smoking status was the most significant factor for the presence of the EGFR and KRAS mutations in lung cancer.

Survival and risk factors for progression after resection of the dominant tumor in multifocal, lepidic-type pulmonary adenocarcinoma.

BACKGROUND: It remains unclear whether a dominant lung adenocarcinoma that presents with multifocal ground glass opacities (GGOs) should be treated by local therapy. We sought to address survival in this setting and to identify risk factors for progression of unresected GGOs. METHODS: Retrospective review of 70 patients who underwent resection of a pN0, lepidic adenocarcinoma, who harbored at least 1 additional GGO. Features associated with GGO progression were determined using logistic regression and survival was evaluated using the Kaplan-Meier method. RESULTS: Subjects harbored 1 to 7 GGOs beyond their dominant tumor (DT). Mean follow-up was 4.1 ± 2.8 years. At least 1 GGO progressed after DT resection in 21 patients (30%). In 11 patients (15.7%), this progression prompted resection (n = 5) or stereotactic radiotherapy (n = 6) at mean 2.8 ± 2.3 years. Several measures of the overall tumor burden were associated with GGO progression (all P values < .03) and with progression prompting intervention (all P values < .01). In logistic regression, greater DT size (odds ratio, 1.07; 95% confidence interval, 1.01-1.14) and an initial GGO > 1 cm (odds ratio, 4.98; 95% confidence interval, 1.15-21.28) were the only factors independently associated with GGO progression. Survival was not negatively influenced by GGO progression (100% with vs 80.7% without; P = .1) or by progression-prompting intervention (P = .4). CONCLUSIONS: At 4.1-year mean follow-up, 15.7% of patients with unresected GGOs after resection of a pN0 DT underwent subsequent intervention for a progressing GGO. Some features correlated with GGO growth, but neither growth, nor need for an intervention, negatively influenced survival. Thus, even those at highest risk for GGO progression should not be denied resection of a DT.

Predictive radiogenomics modeling of EGFR mutation status in lung cancer.

Molecular analysis of the mutation status for EGFR and KRAS are now routine in the management of non-small cell lung cancer. Radiogenomics, the linking of medical images with the genomic properties of human tumors, provides exciting opportunities for non-invasive diagnostics and prognostics. We investigated whether EGFR and KRAS mutation status can be predicted using imaging data. To accomplish this, we studied 186 cases of NSCLC with preoperative thin-slice CT scans. A thoracic radiologist annotated 89 semantic image features of each patient's tumor. Next, we built a decision tree to predict the presence of EGFR and KRAS mutations. We found a statistically significant model for predicting EGFR but not for KRAS mutations. The test set area under the ROC curve for predicting EGFR mutation status was 0.89. The final decision tree used four variables: emphysema, airway abnormality, the percentage of ground glass component and the type of tumor margin. The presence of either of the first two features predicts a wild type status for EGFR while the presence of any ground glass component indicates EGFR mutations. These results show the potential of quantitative imaging to predict molecular properties in a non-invasive manner, as CT imaging is more readily available than biopsies.

The prognostic landscape of genes and infiltrating immune cells across human cancers.

Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing data sets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies. By using this resource, we identified a forkhead box MI (FOXM1) regulatory network as a major predictor of adverse outcomes, and we found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and facilitate the discovery of biomarkers and therapeutic targets.

mTORC1 promotes denervation-induced muscle atrophy through a mechanism involving the activation of FoxO and E3 ubiquitin ligases.

Skeletal muscle mass and function are regulated by motor innervation, and denervation results in muscle atrophy. The activity of mammalian target of rapamycin complex 1 (mTORC1) is substantially increased in denervated muscle, but its regulatory role in denervation-induced atrophy remains unclear. At early stages after denervation of skeletal muscle, a pathway involving class II histone deacetylases and the transcription factor myogenin mediates denervation-induced muscle atrophy. We found that at later stages after denervation of fast-twitch muscle, activation of mTORC1 contributed to atrophy and that denervation-induced atrophy was mitigated by inhibition of mTORC1 with rapamycin. Activation of mTORC1 through genetic deletion of its inhibitor TSC1 (tuberous sclerosis complex 1) sensitized mice to denervation-induced muscle atrophy and suppressed the kinase activity of Akt, leading to activation of FoxO transcription factors and increasing the expression of genes encoding E3 ubiquitin ligases atrogin [also known as MAFbx (muscle atrophy F-box protein)] and MuRF1 (muscle-specific ring finger 1). Rapamycin treatment of mice restored Akt activity, suggesting that the denervation-induced increase in mTORC1 activity was producing feedback inhibition of Akt. Genetic deletion of the three FoxO isoforms in skeletal muscle induced muscle hypertrophy and abolished the late-stage induction of E3 ubiquitin ligases after denervation, thereby preventing denervation-induced atrophy. These data revealed that mTORC1, which is generally considered to be an important component of anabolism, is central to muscle catabolism and atrophy after denervation. This mTORC1-FoxO axis represents a potential therapeutic target in neurogenic muscle atrophy.

Diaphragm muscle atrophy in the mouse after long-term mechanical ventilation.

INTRODUCTION: Mechanical ventilation (MV) is a life-saving measure, but full ventilator support causes ventilator-induced diaphragm atrophy (VIDA). Previous studies of VIDA have relied on human biopsies or a rat model. If MV can induce diaphragm atrophy in mice, then mechanistic study of VIDA could be explored via genetic manipulation. RESULTS: We show that 18 hours of MV in mice results in a 15% loss of diaphragm weight and a 17% reduction in fiber cross-sectional area. Important catabolic cascades are activated in this mouse model: transcription of the ubiquitin ligases, atrogin and MuRF1, and the apoptotic marker, Bim, are increased; the marker of autophagy, LC3, is induced at the protein level and shows a punctate distribution in diaphragm muscle fibers. CONCLUSIONS: This mouse model recapitulates the key pathophysiological findings of other models of VIDA, and it will enable the genetic manipulation required to fully explore the mechanisms underlying this important process.