scholarly journals P2.17-14 Impaired Immune Defense in Tumor Micro-Environment Is Associated with Risk of Recurrence in Early Stage Lung Adenocarcinoma

2019 ◽  
Vol 14 (10) ◽  
pp. S889
Author(s):  
Y. Lou ◽  
A. Khoor ◽  
M. Thomas ◽  
J. Kachergus ◽  
Y. Ma ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Immune Defense ◽  
Risk Of Recurrence

scholarly journals TERT Mutation was Associated with the Risk of Recurrence in Lung Adenocarcinoma with A Micropapillary Pattern

2020 ◽  
Author(s):  
Fenfang Wang ◽  
Lu Xu ◽  
Qing Hao ◽  
Chenghui Li ◽  
Qihuan Wu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
High Risk ◽  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Growth Factor Receptor ◽  
Egfr Mutations ◽  
Molecular Characteristics ◽  
Risk Of Recurrence ◽  
Tert Mutation ◽  
Micropapillary Pattern

Abstract Background: Lung adenocarcinoma with a micropapillary pattern (MPPAC) is the histological subtype of lung cancer. It has attracted increasing attention, especially regarding its association with poor prognosis, including the predisposition towards recurrence and metastasis. Although MPPAC has been described in early-stage cases, only a few studies have reported the correlation between disease-specific prognosis and gene mutation of MPPAC. This study aimed to clarify the common genetic mutations and the prognostic characteristics in MPPAC patients.Methods: A total of 17 patients whose surgical pathology was defined as MPPAC were followed up, the molecular characteristics were elucidated by next-generation sequencing, and the prognostic characteristics were analyzed. Results: Epidermal growth factor receptor (EGFR) mutations were identified in 11/17 (65%) of patients. TP53 alterations were identified in 10/17 (59%). Other common mutations include ATM (18%), KRAS (18%), SDHA (18%), and TERT (18%). MPPAC patients harboring EGFR and TERT mutations were at a high risk of tumor recurrence, while TP53 might be associated with a low risk of recurrence. Conclusions: TERT mutation was more frequently harbored in MPPAC patients than in the other histological type of lung cancer, and such patients were at a high risk of recurrence. So TERT mutation might be associated with adverse prognosis in MPPAC patients.

Integration of mRNA and microRNA profiles as prognostic and predictive markers in lung adenocarcinoma

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 7522-7522
Author(s):  
J. H. Strickler ◽  
W. Mostertz ◽  
W. Kim ◽  
K. Walters ◽  
M. Stevenson ◽  
...  
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Cell Lines ◽  
Cisplatin Resistance ◽  
Early Stage ◽  
Gene Signature ◽  
Discovery Cohort ◽  
Risk Of Recurrence ◽  
Increased Risk

7522 Background: Lung adenocarcinoma (ADC) is a distinct biologic entity with unique gene amplifications (Weir B, Nature 2008). Yet, comprehensive transcriptomic analysis, including microRNAs, specific to lung ADC are lacking. Methods: Using mRNA expression data from a discovery cohort of 154 patients with histologically proven early stage (I and II) lung ADC, signatures of oncogenic pathway and tumor microenvironment status were applied and further organized by hierarchical clustering to develop a metagene model. Further, using in vitro assays in a large cohort of lung ADC cell lines (n = 42) with corresponding mRNA and microRNA data, novel microRNAs associated with a poor prognosis and their relationship to cisplatin resistance was elucidated. Results: In the discovery cohort of 154 patients with early stage disease, activation of oncogenic pathways associated with wound healing (angiogenesis), chromosomal instability, and STAT signaling were associated with an increased risk of recurrence (p<0.001). Utilizing the extremes of survival to identify cohorts of patients as high and low risk phenotypes, using bayesian regression, a 100 gene signature (‘metagene') that captured the diversity of signaling pathways unique to patients at increased risk of recurrence was identified and validated in an independent cohort (n = 364) of lung ADC samples with 78.3% accuracy. Kaplan Meier survival analysis and multivariate analysis further confirmed the independent prognostic value of the 100 gene signature (p= 0.007). Using in vitro cell proliferation assays, predicted high risk lung ADC cell lines were identified as being more resistant to cisplatin therapy than those predicted to be low risk (p=0.001). In a novel manner, we also identified several microRNAs (miR-215, miR-98, miR- 643, let-7b, miR-665, miR-629) associated with a high risk of recurrence and more importantly cisplatin resistance. Conclusions: mRNA and microRNA profiles reflect unique aspects of individual tumors and may characterize histology-specific tumor heterogeneity in lung ADC, providing an opportunity to better characterize the oncogenic process and refine therapeutic options. No significant financial relationships to disclose.

scholarly journals Multiomic Characterization of Stage I Lung Adenocarcinoma Reveals Distinct Genetic and Immunologic Features of Recurrent Disease

2021 ◽  
Author(s):  
Johannes R Kratz ◽  
Jack Z Li ◽  
Jessica Tsui ◽  
Jen C Lee ◽  
Vivianne W Ding ◽  
...  
Keyword(s):  
Lung Cancer ◽  
High Risk ◽  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Stage I ◽  
Early Stage Lung Cancer ◽  
Risk Of Recurrence ◽  
Adaptive Immune ◽  
Mutation Burden ◽  
Lung Adenocarcinomas

Background: Recurrence after surgery for early-stage lung cancer is common, occurring between 30-50% of the time. Despite the popularization of prognostic gene signatures in early-stage lung cancer that allow us to better predict which patients may recur, why patients recur after surgery remains unclear. Methods: Using a large cohort of lung adenocarcinoma patients with complete genetic, genomic, epigenetic and clinical profiling, a recurrence classifier was developed which identifies patients at highest risk of recurrence. The genetic, genomic, and epigenetic profiles of stage I patients with low- vs. high-risk of recurrence were compared. To characterize the tumor immune microenvironment of recurrent stage I tumors, single cell RNA-seq was performed on fresh tissue samples undergoing lung adenocarcinoma resection at UCSF to identify unique immune population markers and applied to the large stage I lung adenocarcinoma cohort using digital cytometry. Results: Recurrence high-risk stage I lung adenocarcinomas demonstrated a higher mutation burden than low-risk tumors, however, none of the known canonical lung cancer driver mutations were more prevalent in high-risk tumors. Transcriptomic analysis revealed widespread activation of known cancer and cell cycle pathways with simultaneous downregulation of immune response pathways including antigen presentation and Th1/Th2 activation. Tumors at high-risk of recurrence displayed depleted adaptive immune populations, and depletion of adaptive immune populations was independently prognostic of recurrence in stage I lung adenocarcinomas. Conclusion: Recurrent stage I lung adenocarcinomas display distinct features of genomic and genetic instability including increased tumor mutation burden, neoantigen load, activation of numerous mitotic and cell cycle genes, and decreased genome-wide methylation burden. Relative depletion of infiltrating adaptive immune populations may allow these tumors to escape immunosurveillance and recur after surgery.

scholarly journals P3.02-090 Hypoxia-Induced Modifications of the Small Non-Coding RNA Transcriptome Delineates Risk of Recurrence in Early-Stage Lung Adenocarcinoma

2017 ◽  
Vol 12 (11) ◽  
pp. S2270
Author(s):  
V. Martinez ◽  
E. Marshall ◽  
N. Firmino ◽  
B. Minatel ◽  
K. Bennewith ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Risk Of Recurrence ◽  
Non Coding Rna

scholarly journals DeepRePath: Identifying the Prognostic Features of Early-Stage Lung Adenocarcinoma Using Multi-Scale Pathology Images and Deep Convolutional Neural Networks

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3308
Author(s):  
Won Sang Shim ◽  
Kwangil Yim ◽  
Tae-Jung Kim ◽  
Yeoun Eun Sung ◽  
Gyeongyun Lee ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Early Stage ◽  
External Validation ◽  
Area Under The Curve ◽  
The Cancer Genome Atlas ◽  
Deep Convolutional Neural Networks ◽  
Prognostic Features ◽  
Multi Scale ◽  
Model Based ◽  
Number Of Patients

The prognosis of patients with lung adenocarcinoma (LUAD), especially early-stage LUAD, is dependent on clinicopathological features. However, its predictive utility is limited. In this study, we developed and trained a DeepRePath model based on a deep convolutional neural network (CNN) using multi-scale pathology images to predict the prognosis of patients with early-stage LUAD. DeepRePath was pre-trained with 1067 hematoxylin and eosin-stained whole-slide images of LUAD from the Cancer Genome Atlas. DeepRePath was further trained and validated using two separate CNNs and multi-scale pathology images of 393 resected lung cancer specimens from patients with stage I and II LUAD. Of the 393 patients, 95 patients developed recurrence after surgical resection. The DeepRePath model showed average area under the curve (AUC) scores of 0.77 and 0.76 in cohort I and cohort II (external validation set), respectively. Owing to low performance, DeepRePath cannot be used as an automated tool in a clinical setting. When gradient-weighted class activation mapping was used, DeepRePath indicated the association between atypical nuclei, discohesive tumor cells, and tumor necrosis in pathology images showing recurrence. Despite the limitations associated with a relatively small number of patients, the DeepRePath model based on CNNs with transfer learning could predict recurrence after the curative resection of early-stage LUAD using multi-scale pathology images.

scholarly journals A circular RNAs dataset landscape reveals potential signatures for the detection and prognosis of early-stage lung adenocarcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhiying Chen ◽  
Jiahui Wei ◽  
Min Li ◽  
Yongjuan Zhao
Keyword(s):  
Functional Analysis ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Target Genes ◽  
Interaction Analysis ◽  
Early Stage ◽  
Gene Interaction ◽  
Gene Expression Omnibus ◽  
Circular Rnas ◽  
Cerna Network

Abstract Background This study aimed to identify potential circular ribonucleic acid (circRNA) signatures involved in the pathogenesis of early-stage lung adenocarcinoma (LAC). Methods The circRNA sequencing dataset of early-stage LAC was downloaded from the Gene Expression Omnibus database. First, the differentially expressed circRNAs (DEcircRNAs) between tumour and non-tumour tissues were screened. Then, the corresponding miRNAs and their target genes were predicted. In addition, prognosis-related genes were identified using survival analysis and further used to build a network of competitive endogenous RNAs (ceRNAs; DEcircRNA–miRNA–mRNA). Finally, the functional analysis and drug–gene interaction analysis of mRNAs in the ceRNA network was performed. Results A total of 35 DEcircRNAs (30 up-regulated and 5 down-regulated circRNAs) were identified. Moreover, 135 DEcircRNA–miRNA and 674 miRNA–mRNA pairs were predicted. The survival analysis of these target mRNAs revealed that 60 genes were significantly associated with survival outcomes in early-stage LAC. Of these, high levels of PSMA 5 and low levels of NAMPT, CPT 2 and TNFSF11 exhibited favourable prognoses. In addition, the DEcircRNA–miRNA–mRNA network was constructed, containing 5 miRNA–circRNA (hsa_circ_0092283/hsa-miR-762/hsa-miR-4685-5p; hsa_circ_0070610/hsa-let-7a-2-3p/hsa-miR-3622a-3p; hsa_circ_0062682/hsa-miR-4268) and 60 miRNA–mRNA pairs. Functional analysis of the genes in the ceRNA network showed that they were primarily enriched in the Wnt signalling pathway. Moreover, PSMA 5, NAMPT, CPT 2 and TNFSF11 had strong correlations with different drugs. Conclusion Three circRNAs (hsa_circ_0062682, hsa_circ_0092283 and hsa_circ_0070610) might be potential novel targets for the diagnosis of early-stage LAC.

Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma

2021 ◽  
Author(s):  
Lin Huang ◽  
Kun Qian
Keyword(s):  
Machine Learning ◽  
Lung Adenocarcinoma ◽  
Cancer Detection ◽  
High Performance ◽  
Large Scale ◽  
Early Cancer ◽  
Early Stage ◽  
Early Cancer Detection ◽  
Ionization Mass ◽  
Efficient Test

Abstract Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 second using only 50 nL of serum. We define a metabolic range of 100-400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70-90% and specificity~90-93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls (p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.

Osimertinib as neoadjuvant treatment for resectable stage II-IIIB EGFR mutant lung adenocarcinoma (NEOS).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 8524-8524
Author(s):  
Chao Lyu ◽  
Wentao Fang ◽  
Haitao Ma ◽  
Jia Wang ◽  
Wenjie Jiao ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Surgical Resection ◽  
Interim Analysis ◽  
Kinase Inhibitors ◽  
Response Rate ◽  
Early Stage ◽  
Neoadjuvant Treatment ◽  
Complete Response ◽  
Stage Ii ◽  
Meaningful Improvement

8524 Background: Neoadjuvant treatment has demonstrated efficacy in several types of cancer and is increasingly used for the treatment of early-stage cancers with the potential of cancer downstaging to enhance complete surgical resection and to improve clinical outcomes. Recent evidences have demonstrated that the neoadjuvant use of first/second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) may provide clinically meaningful improvement in EGFRm non-small cell lung cancer (NSCLC) patients, however, limited data were reported on osimertinib, the third-generation EGFR-TKI, in the neoadjuvant setting. Here we present an interim analysis of osimertinib as neoadjuvant treatment for resectable EGFRm NSCLC. Methods: NEOS is a prospective, multi-center, single-arm study to evaluate the efficacy and safety of osimertinib as neoadjuvant treatment in resectable EGFRm (19del/L858R) lung adenocarcinoma. Eligible patients were treated with osimertinib 80 mg orally per day for six weeks followed by surgery. Assessment of response to neoadjuvant therapy was performed according to RECIST 1.1. The primary endpoint was response rate. Secondary endpoints included safety, R0 surgical resection rate, quality of life, major pathologic response (MPR) rate, pathological complete response (pCR) rate, and N2 downstaging rate. Results: As of Dec. 17, 2020, 18 eligible patients (median age 61 [range 46-73], 27.8% male, 22.2% ECOG PS 1) have been enrolled. Patients with clinical stages IIa, IIb, and IIIa (8th AJCC) accounted for 16.7%, 22.2% and 61.1%, respectively. Half (9/18) of the patients had EGFR exon 21 L858R mutations and the other half (9/18) had EGFR exon 19del mutations. Amongst all 15 patients who completed efficacy assessment after neoadjuvant osimertinib, the response rate (RR) was 73.3% (11/15) and the disease control rate (DCR) was 100% (15/15). R0 surgical resection was performed in 93.3% (14/15) patients. Pathological downstaging occurred in 53.3% (8/15) patients. 42.9% (3/7) of the patients with confirmed N2 lymph nodes experienced downstaging to N0 disease after receiving neoadjuvant osimertinib. One patient was identified with a pCR. Adverse events (AEs) were reported in 66.7% (12/18) of patients, with the most common AE being rash (8/18, 44.4%), oral ulceration (8/18, 44.4%), and diarrhea (5/18, 27.8%). No grade 3-5 AEs or serious AEs were reported. Conclusions: Interim analysis from this study indicated neoadjuvant osimertinib as an effective and feasible treatment in patients with resectable stage II-IIIB EGFRm NSCLC. The trial is ongoing and the final results will be provided in the future. Clinical trial information: ChiCTR1800016948.

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