scholarly journals Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0205003 ◽  
Author(s):  
Constance A. Owens ◽  
Christine B. Peterson ◽  
Chad Tang ◽  
Eugene J. Koay ◽  
Wen Yu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Lung Tumor ◽  
Small Cell ◽  
Tumor Segmentation ◽  
Small Cell Lung ◽  
Segmentation Methods

Prognostic impact of c-Met/phospho-Met, and topoisomerase I in small cell lung cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e17540-e17540
Author(s):  
Hideko Ikeda ◽  
Hayato Koba ◽  
Koji Kurokawa ◽  
Shingo Nishikawa ◽  
Tomoyuki Araya ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factor ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Lung Tumor ◽  
Small Cell ◽  
Independent Prognostic Factor ◽  
High Expression ◽  
Prognostic Impact ◽  
Small Cell Lung

e17540 Background: The hepatocyte growth factor/MET pathway has been shown to cause tumor progression in several types of carcinomas. We reported that c-Met up-regulated topoisomease I (Topo I) in non-small cell lung cancer cell lines (submitted for publication). The aims of this study were 1) to examine the prognostic influence of c-MET/phospho-MET (p-Met), or Topo I expression and 2) to elucidate correlation between c-Met/p-Met expression and Topo I expression in small cell lung cancer (SCLC). Methods: This retrospective study included 72 SCLC patients (pts) with available tumor tissue from primary lung tumor or metastatic lesions and clinical data including survival. We performed immunohistochemistry to detect c-MET/phospho-MET and Topo I expression. Results: Tumor tissues were obtained from 72 SCLC pts. Sixty-six pts, (51 male, 15 female, median age 67.5 range 43-91, LD/ED 38/28, PS0,1/2,3,4 57/9) were evaluated. c-Met overexpression was seen in 40.9%, p-Met in 74.2%, and Topo I expression in 59.1%, respectively. High expression of Topo I associated with lower response rate (RR) (96.7% in low group vs 78.4% in high group, p=0.029) and shorter progression-free survival (PFS) (65W vs 39W, p=0.040) but did not correlate with overall survival (OS). Phosphorylation of Met protein did not correlate with RR, PFS or OS. Interestingly, intensity of p-Met significantly correlated with Topo I expression (p=0.048). High expression of c-Met protein did not associated with RR or PFS but significantly associated with shorter OS (high 53W, low 95W, p=0.018). Multivariate analysis which included c-Met, stage, PS, and age resulted that c-Met was an independent prognostic factor for OS of pts with SCLC (HR; 2.144, 95% confidence interval 1.162-3.956, p=0.015). Conclusions: This study suggested c-Met high expression was an independent prognostic factor, and Topo I was up-regulated by Met in SCLC.

Significance of EGFR and KRAS gene mutation in small cell lung cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e18564-e18564 ◽  
Author(s):  
Koji Kurokawa ◽  
Tomoharu Matsui ◽  
Hideko Ikeda ◽  
Shingo Nishikawa ◽  
Takashi Sone ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Kras Mutation ◽  
Egfr Mutation ◽  
Kinase Inhibitor ◽  
Lung Tumor ◽  
Small Cell ◽  
Driver Mutations ◽  
Small Cell Lung

e18564 Background: In non-small cell lung cancer, epidermal growth factor receptor (EGFR) and KRAS are known as driver mutations. However the association between these gene alteration and small cell lung cancer (SCLC) has been unclear. The aim of this study is to investigate the gene status of EGFR and Kras in SCLC. Methods: This retrospective study included 66 SCLC patients with available tumor tissue from primary lung tumor or metastatic and clinical data including survival. We evaluated for the presence of EGFR and KRAS mutation those patients using Scorpion-ARMS method. This study was approved by IRB. Results: Sixty-six patients (52 male,14 female median age 68 range 49-89, LD/ED 34/32, PS0-1/2-3 57/9, smoker/never smoker 64/2) were evaluated. Their median overall survival (OS) were 484 days, progression-free survival (PFS) were 217 days. Sixty-six samples were evaluated EGFR mutation test and 61 were evaluated KRAS mutation test by Scorpion-ARMs methods. SCLC patients with EGFR mutation were the only one patients (1.5%,1/66). KRAS mutation were also the only one patients (1.6%,1/61). A 54 years-old nevere-smoker female was already treated with EGFR tyrosine kinase inhibitor for non-small cell lung cancer, the patients with EGFR mutation had a transformation into SCLC. The KRAS mutation patient was combined SCLC with adenocarcinoma. Conclusions: This study suggested that EGFR and KRAS patients associated with SCLC is poor, these driver mutation is unnecessary for common SCLC.

Clinical observation of next-generation photodynamic therapy (NGPDT) for advanced non-small cell lung cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e19028-e19028
Author(s):  
Li Jun Li
Keyword(s):  
Lung Cancer ◽  
Photodynamic Therapy ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Clinical Observation ◽  
Lung Tumor ◽  
Remission Rate ◽  
Small Cell ◽  
Next Generation ◽  
Small Cell Lung

e19028 Background: Clinical observation of next-generation photodynamic therapy (NGPDT) for advanced non-small cell lung cancer (NSCLC). Methods: Through pathology or cytology diagnosis, 66 cases of advanced non-small cell lung cancer patients were selected and randomly divided into two groups. The Next Generation Photodynamic Therapy (NGPDT) group had 32 patients. Photosensitizer was administered on a dosage of 2 mg per kilogram of body weight, wherein two-thirds via ultrasonic atomization inhalation and one-third via oral intake. After the irradiation target(s) were determined, optical fiber for laser treatment purposes was guided into lung tumor(s) via interstitial procedure, percutaneous puncture under precious laser navigation, irradiation light intensity was 200 J/cm2, irradiation power was 1,000 mw, activation was then started and lasted for eight to ten minutes, laser irradiation into tumor was two to five centimeters in length, irradiation could be performed phase by phase (sub-paragraph treatment) based on tumor size or irradiations could be performed repeatedly. While in the mean time in the chemotherapy/radiotherapy group (external beam radiotherapy + whole body chemotherapy) 34 cases were observed, 15 MV X ray radiation therapy irradiation field covers primary lung tumor lesion(s) and mediastinal lymphatic drainage area, dosage was 65-70 Gy, on every first day in a week of radiotherapy, 20 mg cisplatin was administered via intravenous application. Results: In the NGPDT group and simultaneous radiotherapy/chemotherapy group, one and two years survival rate were 93.75%, 70.60% and 68.75, 32.35% respectively (P <0.05). The complete remission rate and partial remission rate were 56.20% and 21.30%, rate of the NGPDT group was significantly higher than that of the corresponding radiotherapy and chemotherapy group, the difference was statistically significant (P <0.05). Conclusions: NGPDT can prolong survival in patients with advanced NSCLC, improving their quality of life; it is one of the most effective measures for advanced non-small cell lung cancer treatment.

Comparative T-cell oligoclonality in lung, tumor and lymph nodes in human non-small cell lung cancer

2005 ◽  
Author(s):  
Sophie Derniame ◽  
Jean-Michel Vignaud ◽  
Gilbert Faure ◽  
Marie Béné ◽  
Frédéric Massin
Keyword(s):  
Lung Cancer ◽  
T Cell ◽  
Lymph Nodes ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Lung Tumor ◽  
Small Cell ◽  
Small Cell Lung

The heterogeneity of circulating lung tumor cells from non-small cell lung cancer patients

2016 ◽  
Vol 61 ◽  
pp. S80
Author(s):  
S.L. Kong ◽  
S.J. Tan ◽  
T.K.H. Lim ◽  
H.M. Poh ◽  
T.Z.X. Yeo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Patients ◽  
Tumor Cells ◽  
Cell Lung Cancer ◽  
Lung Tumor ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Patients

scholarly journals Deep segmentation networks predict survival of non-small cell lung cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Stephen Baek ◽  
Yusen He ◽  
Bryan G. Allen ◽  
John M. Buatti ◽  
Brian J. Smith ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Prognostic Value ◽  
Predictive Power ◽  
Ct Images ◽  
Small Cell ◽  
Tumor Segmentation ◽  
Small Cell Lung ◽  
Pet Ct

AbstractNon-small-cell lung cancer (NSCLC) represents approximately 80–85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography/computed tomography (PET/CT) images have predictive power for NSCLC outcomes. To this end, easily calculated functional features such as the maximum and the mean of standard uptake value (SUV) and total lesion glycolysis (TLG) are most commonly used for NSCLC prognostication, but their prognostic value remains controversial. Meanwhile, convolutional neural networks (CNN) are rapidly emerging as a new method for cancer image analysis, with significantly enhanced predictive power compared to hand-crafted radiomics features. Here we show that CNNs trained to perform the tumor segmentation task, with no other information than physician contours, identify a rich set of survival-related image features with remarkable prognostic value. In a retrospective study on pre-treatment PET-CT images of 96 NSCLC patients before stereotactic-body radiotherapy (SBRT), we found that the CNN segmentation algorithm (U-Net) trained for tumor segmentation in PET and CT images, contained features having strong correlation with 2- and 5-year overall and disease-specific survivals. The U-Net algorithm has not seen any other clinical information (e.g. survival, age, smoking history, etc.) than the images and the corresponding tumor contours provided by physicians. In addition, we observed the same trend by validating the U-Net features against an extramural data set provided by Stanford Cancer Institute. Furthermore, through visualization of the U-Net, we also found convincing evidence that the regions of metastasis and recurrence appear to match with the regions where the U-Net features identified patterns that predicted higher likelihoods of death. We anticipate our findings will be a starting point for more sophisticated non-intrusive patient specific cancer prognosis determination. For example, the deep learned PET/CT features can not only predict survival but also visualize high-risk regions within or adjacent to the primary tumor and hence potentially impact therapeutic outcomes by optimal selection of therapeutic strategy or first-line therapy adjustment.

scholarly journals Statistical and bioinformatic analysis of hemimethylation patterns in non-small cell lung cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shuying Sun ◽  
Austin Zane ◽  
Carolyn Fulton ◽  
Jasmine Philipoom
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Lung Tumor ◽  
Small Cell ◽  
Rank Test ◽  
Small Cell Lung ◽  
Cpg Sites ◽  
Cpg Site ◽  
Dna Strands

Abstract Background DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns. Methods In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools. Results In this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. Several genes that are known to be associated with cancer are hemimethylated differently between the cancerous and normal samples. Furthermore, highly hemimethylated genes exhibit many different interactions with other genes that may be associated with cancer. Hemimethylation has diverse patterns and frequencies that are comparable between normal and tumorous cells. Therefore, hemimethylation may be related to both normal and tumor cell development. Conclusions Our research has identified CpG clusters and genes that are hemimethylated in normal and lung tumor samples. Due to the potential impact of hemimethylation on gene expression and cell function, these clusters and genes may be important to advance our understanding of the development and progression of non-small cell lung cancer.

scholarly journals MRTF-A-NF-κB/p65 axis-mediated PDL1 transcription and expression contributes to immune evasion of non-small-cell lung cancer via TGF-β

2021 ◽  
Author(s):  
Fu Du ◽  
Xin Qi ◽  
Aotong Zhang ◽  
Fanfan Sui ◽  
Xuemin Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Signaling Pathway ◽  
Cell Lung Cancer ◽  
Anticancer Agents ◽  
Immune Escape ◽  
Lung Tumor ◽  
Small Cell ◽  
Small Cell Lung

AbstractPD-L1 is abnormally regulated in many cancers and is critical for immune escape. Fully understanding the regulation of PD-L1 expression is vital for improving the clinical efficacy of relevant anticancer agents. TGF-β plays an important role in the low reactivity of PD-1/PD-L1 antibody immunotherapy. However, it is not very clear whether and how TGF-β affects PD-L1 expression. In the present study, we show that TGF-β upregulates the expression of the transcriptional coactivator MRTF-A in non-small-cell lung cancer cells, which subsequently interacts with NF-κB/p65 rather than SRF to facilitate the binding of NF-κB/p65 to the PDL1 promoter, thereby activating the transcription and expression of PD-L1. This leads to the immune escape of NSCLC cells. This process is dependent on the activation of the TGF-β signaling pathway. In vivo, inhibition of MRTF-A effectively suppresses the growth of lung tumor syngrafts with enrichment of NK and T cells in tumor tissue. Our study defines a new signaling pathway that regulates the transcription and expression of PD-L1 upon TGF-β treatment, which may have a significant impact on research into the application of immunotherapy in treating lung cancer.

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