The mutation frequency of HPD related genes in different lung cancer stages.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21006-e21006
Author(s):  
Yanhui Wan ◽  
Fuyuan Fang ◽  
Guodong Wu ◽  
Xing Zhang ◽  
Chao Song ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Mutation Frequency ◽  
Early Stage ◽  
Lung Squamous Cell Carcinoma ◽  
Advanced Lung Cancer ◽  
Advanced Stage ◽  
Related Gene ◽  
Early Stage Lung Cancer ◽  
Advanced Stages ◽  
Stage Lung Cancer

e21006 Background: Clinical detections of hyper-progressive disease (HPD) gene mutations in advanced lung cancer should be considered to avoid the inappropriate immunotherapy, and recently neoadjuvnat and adjuvant immunotherapy also proved to be efficacy in early stage of lung cancer. Nevertheless, it still remains poorly understanding of the distribution of HPD related mutations in early stage lung cancer. Methods: In this study, according to information of patient specimens from public database TCGA, Ⅰ and Ⅱ stages were defined as early stage, Ⅲ and Ⅳ stages were defined as advanced stage. The mutations in HPD related genes were evaluated including CNVs of CCND1, FGF19, FGF3, FGF4, MDM2 and MDM4, and SNVs of DNMT3A. Chi-square test was performed to analyze the differences of HPD related gene mutation frequency in early and advanced stages. Results: Based on the statistics of clinical data from TCGA, we found 399 early stage cases and 110 advanced stage cases in patients with lung adenocarcinoma (LUAD), 402 early stage cases and 91 advanced stage cases in patients with lung squamous cell carcinoma (LUSC). In early stage, we found 76, 76, 76, 75, 89, 201 cases of CNVs of CCND1, FGF19, FGF3, FGF4, MDM2 and MDM4, 10 cases of SNVs of DNMT3A, respectively. In advanced stage, we counted 32, 32, 32, 29, 21, 37 cases of CNVs of CCND1, FGF19, FGF3, FGF4, MDM2 and MDM4, 4 cases of SNVs of DNMT3A, respectively. No significant differences of mutation frequency HPD related gene between early and advanced stages were found via χ2 test. CNVs frequencies of CCND1, FGF19, FGF3, FGF4 and MDM4 in LUAD were significantly lower than them in LUSC. No significant differences of CNVs frequency of MDM2 and SNVs frequency of DNMT3A beween patients with LUAD and patients with LUSC were found. Conclusions: Our analysis indicated that immunotherapy for patients with early stage lung cancer also needed to test these mutations. LUSC patients required paying more attentions on HPD related mutations of which frequencies were significantly higher than LUAD patients. As a retrospective study with a relatively small population, the conclusions of this study needed to be verified with a larger sample.

PD-1 Blockade in Early-Stage Lung Cancer

2019 ◽  
Vol 70 (1) ◽  
pp. 425-435 ◽  
Author(s):  
Samuel Rosner ◽  
Joshua E. Reuss ◽  
Patrick M. Forde
Keyword(s):  
Lung Cancer ◽  
Early Stage ◽  
Immune Checkpoint Blockade ◽  
Advanced Lung Cancer ◽  
Early Stage Lung Cancer ◽  
Early Results ◽  
Stage Disease ◽  
Relapse Rates ◽  
Stage Lung Cancer

Early-stage non–small cell lung cancer is a potentially curable disease, but with relapse rates exceeding 50% with standard treatments, this is a patient population in critical need of therapy innovation. Immunotherapy with immune checkpoint blockade has revolutionized the treatment strategy for advanced lung cancer. However, the role of this therapy in earlier-stage disease is largely unknown. The study of immunotherapy in earlier-stage disease has many advantages, including assessment of pathologic response and incorporation of translational scientific analyses to evaluate antitumor immune responses. Multiple clinical trials are currently under way, with promising early results.

Genome-wide sequencing for early stage lung cancer detection from plasma cell-free DNA (cfDNA): The Circulating Cancer Genome Atlas (CCGA) study.

2018 ◽  
Vol 36 (18_suppl) ◽  
pp. LBA8501-LBA8501 ◽  
Author(s):  
Geoffrey R. Oxnard ◽  
Tara Maddala ◽  
Earl Hubbell ◽  
Alex Aravanis ◽  
Nan Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Detection ◽  
Early Stage ◽  
Classification Model ◽  
Advanced Lung Cancer ◽  
Whole Genome ◽  
Early Stage Lung Cancer ◽  
Genome Wide ◽  
Lung Cancer Detection ◽  
Stage Lung Cancer

LBA8501 Background: Plasma cfDNA genomic analysis is used widely for the care of advanced lung cancer, but its suitability for early stage lung cancer detection is not well established. CCGA (NCT02889978) is a prospective, multi-center, observational study launched for the development of a noninvasive assay for cancer detection. Methods: Blood was prospectively collected (N = 1627) from 749 controls (no cancer diagnosis) and 878 participants (pts) with newly-diagnosed untreated cancer in this preplanned substudy, including 127 pts with lung cancer. Three prototype sequencing assays were performed: paired cfDNA and white blood cell (WBC) targeted sequencing (507 genes, 60,000X) for single nucleotide variants/indels; paired cfDNA and WBC whole genome sequencing (WGS) for copy number variation (30X); and cfDNA whole genome bisulfite sequencing (WGBS) for methylation (30X). For each assay, a classification model using 10-fold cross-validation was developed for all pts with cancer, then evaluated in the pts with lung cancer; sensitivity was estimated at 95% specificity. Results: We evaluated pts with lung cancer (127) and a subset of controls (580) with similar ages (mean±SD yrs: 67±9, 60±13), 85% and 43% were ever-smokers, and 46% and 22% were men, respectively. Of 3055 nonsynonymous mutations detected across 122 evaluable pts with lung cancer, > 50% were detected in WBC consistent with clonal hematopoiesis (CH). Accounting for CH, sensitivity in 63 stage I-IIIA pts evaluable across all 3 assays was 48% (35-61, targeted), 54% (41-67, WGS), and 56% (43-68, WGBS); in 54 stage IIIB-IV pts it was 85% (73-93, targeted), 91% (80-97, WGS), and 93% (82-98, WGBS) . Similar sensitivities were observed across histological subtypes (adenocarcinoma, squamous cell, small cell). Comparison to tumor WGS and multi-assay classification will be reported. Conclusions: Early stage lung cancers are detectable in cfDNA using a genome-wide sequencing approach. For lung cancer detection using targeted assays, CH must be accounted for to minimize false positives. Assay optimization is ongoing to allow further clinical development in the intended use population. Clinical trial information: NCT02889978.

scholarly journals P04.10 Relapsed or Metastatic Organotropism in Early Stage Lung Cancer after Radical Surgery

2021 ◽  
Vol 16 (3) ◽  
pp. S264-S265
Author(s):  
F. Xu ◽  
L. Yang ◽  
C. Liu ◽  
J. Ying ◽  
Y. Wang
Keyword(s):  
Lung Cancer ◽  
Radical Surgery ◽  
Early Stage ◽  
Early Stage Lung Cancer ◽  
Stage Lung Cancer

scholarly journals Structural and functional radiomics for lung cancer

2021 ◽  
Author(s):  
Guangyao Wu ◽  
Arthur Jochems ◽  
Turkey Refaee ◽  
Abdalla Ibrahim ◽  
Chenggong Yan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Treatment Strategy ◽  
Early Stage ◽  
Quality Data ◽  
Clinical Implementation ◽  
Early Stage Lung Cancer ◽  
Treatment Response Evaluation ◽  
Advanced Stage Lung Cancer ◽  
Stage Lung Cancer

Abstract Introduction Lung cancer ranks second in new cancer cases and first in cancer-related deaths worldwide. Precision medicine is working on altering treatment approaches and improving outcomes in this patient population. Radiological images are a powerful non-invasive tool in the screening and diagnosis of early-stage lung cancer, treatment strategy support, prognosis assessment, and follow-up for advanced-stage lung cancer. Recently, radiological features have evolved from solely semantic to include (handcrafted and deep) radiomic features. Radiomics entails the extraction and analysis of quantitative features from medical images using mathematical and machine learning methods to explore possible ties with biology and clinical outcomes. Methods Here, we outline the latest applications of both structural and functional radiomics in detection, diagnosis, and prediction of pathology, gene mutation, treatment strategy, follow-up, treatment response evaluation, and prognosis in the field of lung cancer. Conclusion The major drawbacks of radiomics are the lack of large datasets with high-quality data, standardization of methodology, the black-box nature of deep learning, and reproducibility. The prerequisite for the clinical implementation of radiomics is that these limitations are addressed. Future directions include a safer and more efficient model-training mode, merge multi-modality images, and combined multi-discipline or multi-omics to form “Medomics.”

scholarly journals The impact of emphysema on surgical outcomes of early-stage lung cancer: a retrospective study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Seijiro Sato ◽  
Masaya Nakamura ◽  
Yuki Shimizu ◽  
Tatsuya Goto ◽  
Terumoto Koike ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Retrospective Study ◽  
Surgical Outcomes ◽  
Early Stage ◽  
Early Stage Lung Cancer ◽  
The Impact ◽  
Stage Lung Cancer
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