P35.23 Integrated Analysis of Genomic and Immunological Features in Lung Adenocarcinoma with Micropapillary Component

BackgroundMicropapillary adenocarcinoma is one of the most aggressive histologic subtypes of lung adenocarcinoma (LADC), and even a minor proportion of micropapillary component (MPC) within the LADC could contribute to poor prognosis. Comprehensive analysis of genetic and immunological features of LADC with different percentages of MPC would help better understand cancer biology of this LADC subtype and direct future treatments.MethodsWe performed next-generation sequencing (NGS) for a discovery cohort of 43 LADC patients whose tumors were micro-dissected to separate MPC and non-MPC lesions and a reference cohort of 113 LADC patients. MPC-enriched genetic alterations that were detected in the discovery cohort were then confirmed using a validation cohort of 183 LADC patients. Immunological staining was also conducted on the MPC-containing samples in the discovery cohort.ResultsTumors with a higher percentage of MPC tended to harbor more tumor mutation burdens (TMBs) and chromosome instability (CIN). Some rare genetic events may serve as the genetic landscape to drive micropapillary tumor progression. Specifically, alterations in transcription termination factor 1 (TTF1), brain-specific angiogenesis inhibitor 3 (BAI3), mammalian target of rapamycin (MTOR), and cyclin-dependent kinase inhibitor 2A (CDKN2A) were cross-validated to be enriched in MPC-contained LADC. Additionally, tumors with a higher percentage of MPC were associated with a higher percentage of CD4+, CD8+, and PD-L1+ staining, and some genetic changes that were enriched in MPC, including MET amplification and MTOR mutation, were correlated with increased PD-L1 expression.ConclusionWe identified multiple novel MPC-enriched genetic changes that could help us understand the nature of this aggressive cancer subtype. High MPC tumors tended to have elevated levels of TMBs, T cell infiltration, and immunosuppression than low MPC tumors, implying the potential link between MPC content and sensitivity to immunotherapy.

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Integrated analysis reveals key genes with prognostic value in lung adenocarcinoma

Cancer Management and Research ◽

10.2147/cmar.s168636 ◽

2018 ◽

Vol Volume 10 ◽

pp. 6097-6108 ◽

Cited By ~ 11

Author(s):

Ying-Jian Song ◽

Juan Tan ◽

Xin-Huai Gao ◽

Li-Xin Wang

Keyword(s):

Lung Adenocarcinoma ◽

Prognostic Value ◽

Integrated Analysis ◽

Key Genes

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A Comprehensive Investigation of Molecular Features and Prognosis of Lung Adenocarcinoma with Micropapillary Component

Journal of Thoracic Oncology ◽

10.1097/jto.0000000000000341 ◽

2014 ◽

Vol 9 (12) ◽

pp. 1772-1778 ◽

Cited By ~ 37

Author(s):

Yang Zhang ◽

Rui Wang ◽

Deng Cai ◽

Yuan Li ◽

Yunjian Pan ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Comprehensive Investigation ◽

Molecular Features ◽

Micropapillary Component

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Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma

Journal of Oncology ◽

10.1155/2020/5310793 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Xiaolin Yu ◽

Xiaomei Zhang ◽

Yanxia Zhang

Keyword(s):

Tumor Microenvironment ◽

Confidence Interval ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

External Validation ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Integrated Analysis ◽

Lasso Regression ◽

The Status

Lung adenocarcinoma (LUAD) is a common subtype of lung cancer with a depressing survival rate. The reprogramming of tumor metabolism was identified as a new hallmark of cancer in tumor microenvironment (TME), and we made a comprehensive exploration to reveal the prognostic role of the metabolic-related genes. Transcriptome profiling data of LUAD were, respectively, downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Based on the extracted metabolic-related genes, a novel 5-gene metabolic prognostic signature (including GNPNAT1, LPGAT1, TYMS, LDHA, and PTGES) was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. This signature confirmed its robustness and accuracy by external validation in multiple databases. It could be an independent risk factor for LUAD, and the nomograms possessed moderately accurate performance with the C-index of 0.755 (95% confidence interval: 0.706–0.804) and 0.691 (95% confidence interval: 0.636–0.746) in training set and testing set. This signature could reveal the metabolic features according to the results of gene set enrichment analysis (GSEA) and meanwhile monitor the status of TME through ESTIMATE scores and the infiltration levels of immune cells. In conclusion, this gene signature is a cost-effective tool which could indicate the status of TME to provide more clues in the exploration of new diagnostic and therapeutic strategy.

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