scholarly journals Moesin as a prognostic indicator of lung adenocarcinoma improves prognosis by enhancing immune lymphocyte infiltration

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yan-Qi Li ◽  
Zhi Zheng ◽  
Quan-Xing Liu ◽  
Xiao Lu ◽  
Dong Zhou ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Prognostic Indicator ◽  
Pathological Feature ◽  
Lymphocyte Infiltration ◽  
Tissue Samples ◽  
Immune Lymphocytes ◽  
Immune Lymphocyte ◽  
Detailed Statistical Analysis ◽  
Cancer Tissues

Abstract Background Ezrin-radixin-moesin (ERM) have been explored in many cancer processes. Moesin, as its component, has also been found to play an important role in the prognosis of cancer patients, tumor metastasis, drug resistance, and others. Especially in regulating the immunity, but most results came from direct studies on immune cells, there is no clear conclusion on whether moesin has similar effects in tumor cells. And moesin has certain research results in many cancers in other aspects, but there are few about moesin in lung adenocarcinoma (LUAD). Methods We detect the expression of moesin in 82 LUAD and matched normal tissue samples by immunohistochemistry. Besides, for the pathological feature, we did a detailed statistical analysis. And with the help of various databases, we have done in-depth exploration of moesin’s ability to enhance the extent of immune lymphocyte infiltration. Results Moesin is a poor expression in lung cancer tissues than the corresponding normal samples. And this phenomenon had a strongly associated with the prognosis and TNM stage of these LUAD patients. Moesin can enhance the infiltration of multiple immune lymphocytes in lung cancer. And this may be related to the interaction between moesin and various inflammatory molecules. Conclusions Moesin is a newly index for the prognosis of LUAD and improves the prognosis of LUAD patients by regulating a variety of inflammation-related molecules to enhance immune lymphocytes infiltration.

scholarly journals UBE2D1 RNA Expression Was an Independent Unfavorable Prognostic Indicator in Lung Adenocarcinoma, but Not in Lung Squamous Cell Carcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Liyan Hou ◽  
Yingbo Li ◽  
Ying Wang ◽  
Dongqiang Xu ◽  
Hailing Cui ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Survival Data ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Rna Expression

In this study, we investigated the potential prognostic value of ubiquitin-conjugating enzyme E2D1 (UBE2D1) RNA expression in different histological subtypes of non-small-cell lung cancer (NSCLC). A retrospective study was performed by using molecular, clinicopathological, and survival data in the Cancer Genome Atlas (TCGA)—Lung Cancer. Results showed that both lung adenocarcinoma (LUAD) (N=514) and lung squamous cell carcinoma (LUSC) (N=502) tissues had significantly elevated UBE2D1 RNA expression compared to the normal tissues (p<0.001 and p=0.036, respectively). UBE2D1 RNA expression was significantly higher in LUAD than in LUSC tissues. Increased UBE2D1 RNA expression was independently associated with shorter OS (HR: 1.359, 95% CI: 1.031–1.791, p=0.029) and RFS (HR: 1.842, 95% CI: 1.353–2.508, p<0.001) in LUAD patients, but not in LUSC patients. DNA amplification was common in LUAD patients (88/551, 16.0%) and was associated with significantly upregulated UBE2D1 RNA expression. Based on these findings, we infer that UBE2D1 RNA expression might only serve as an independent prognostic indicator of unfavorable OS and RFS in LUAD, but not in LUSC.

Epitope mapping of epidermal growth factor receptor (EGFR) in lung cancer using immunohistochemistry: Fine tuning the protocols

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21162-21162
Author(s):  
J. TIMAR ◽  
K. Derecskei ◽  
B. Dome ◽  
J. Moldvay
Keyword(s):  
Lung Cancer ◽  
Protein Expression ◽  
Ligand Binding ◽  
Lung Adenocarcinoma ◽  
Growth Factor Receptor ◽  
Fine Tuning ◽  
Antigen Retrieval ◽  
Egfr Expression ◽  
Lung Adenocarcinomas ◽  
Cancer Tissues

21162 Background: Until now, immunohistochemistry was not able to become a reliable diagnostic approach for EGFR targeted therapies. The golden standard of the determination of EGFR protein expression in paraffin embedded cancer tissues is the EGFRpharmDXtm kit. Methods: Here we show data based on analysis of 110 lung adenocarcinomas, that the recommended protocol may not be optimal for ideal performance of the immunodetection, since microwave retrieval, extended primary antibody-incubation time and replacement of the developer reagent converted four EGFR-negative tumor into EGFR protein positive out of eight lung adenocarcinoma cases. Protocol modification improved the performance of another widely used EGFR-kit, Ventana's CONFIRM, where replacement of the protease antigen retrieval with microwave cooking converted several EGFR-negative tumors to strongly positive. Meanwhile both EGFR-kits detect EGFR expression (juxtamembrane domain) but do not provide information on the expression of epitopes critical from the point of view of targeted therapy. Results: We have developed two protocols, which can detect the ligand-binding (AB-10, BioMarkers) and C-terminal (AB- 335, Biogenex) cytoplasmic domains of the EGFR protein in paraffin embedded lung cancer tissues. We have shown, based on the analysis of more than 110 lung adenocarcinoma tissues, that the ligand binding domain of EGFR is rarely expressed while the C-terminal domain is ubiquitously expressed in EGFR-PharmDX and CONFIRM-positive cancers. The biological activity of EGFR can be characterized either by autophosphorylation of the receptor or by detection of divers phosphorylated downstream signaling components. We have found that unlike p1086 (detected by a Zymed antibody), the p1173 site of EGFR (identified by a rabbit monoclonal of Epitomics) can be detected 27/110 paraffin embedded lung adenocarcinomas. Conclusions: Using the tested antibody panel we can reliably determine the EGFR protein expression in paraffin embedded (lung)cancer tissues. This work was supported by Ministry of Education (NKFP1a-0024–05). No significant financial relationships to disclose.

Comparison between diameters of the whole nodule and solid area and the proportion of GGO in the tumor shadow on HRCT in predicting less-invasive lung cancer and recurrence after complete resection in patients with clinical N0 NSCLC.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 7021-7021
Author(s):  
Haruhisa Matsuguma ◽  
Rie Nakahara ◽  
Haruko Suzuki ◽  
Takashi Kasai ◽  
Yukari Kamiyama ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Roc Analysis ◽  
Area Under The Curve ◽  
Ground Glass Opacity ◽  
Prognostic Indicator ◽  
Complete Resection ◽  
Less Invasive ◽  
Invasive Lung Adenocarcinoma ◽  
Solid Area

7021 Background: Prediction of less-invasive lung cancer is important in selecting candidates for limited surgical resection. A greater proportion of ground-glass opacity (%GGO) is well-known to be strongly associated with less-invasive lung adenocarcinoma. Recently, the diameter of the solid area (SolidØ) has been reported to also be a simple and better marker for the same purpose compared to the diameter of the whole nodule (NoduleØ). The aim of this study was to confirm that SolidØ can completely replace %GGO in predicting less-invasive lung cancer. Methods: From 1987 to 2009, 433 patients with clinical T1a-2bN0 NSCLC underwent complete resection, and their preoperative HRCT images were preserved in DICOM format. NoduleØ and SolidØ were precisely measured using software. %GGO was calculated using the method we previously published (Eur J Cardiothorac Surg 25:1102-6, 2004). Less-invasive lung cancer was defined as having no vascular, lymphatic, nor pleural invasion. We compared the three parameters with regard to predicting less-invasive lung cancer and recurrence. Results: Among the 433 patients, 220 were male, 367 had an adenocarcinoma histology, and 58 experienced recurrence. Table shows percentages and numbers of non-less-invasive lung cancer cases. Among each category of SolidØ, greater %GGO is associated with less-invasive lung cancer. ROC analysis also showed that the area under the curve of %GGO was the highest (0.859, 95% CI 0.824 – 0.893), followed by SolidØ (0.806, 0.767 – 0.846), and NoduleØ (0.671, 0.620 – 0.721). Regardless of SolidØ, no patient with a greater %GGO (> 50%) experienced recurrence. Conclusions: Although SolidØ is a better prognostic indicator of non-invasiveness compared to NoduleØ, %GGO remains important. [Table: see text]

scholarly journals Non-small cell lung cancer microbiota characterization: Prevalence of enteric and potentially pathogenic bacteria in cancer tissues

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249832
Author(s):  
Nathan Dumont-Leblond ◽  
Marc Veillette ◽  
Christine Racine ◽  
Philippe Joubert ◽  
Caroline Duchaine
Keyword(s):  
Lung Cancer ◽  
Pathogenic Bacteria ◽  
Amplicon Sequencing ◽  
Healthy Tissue ◽  
Cancer Tissue ◽  
Rrna Gene ◽  
Variable Degree ◽  
Tissue Samples ◽  
Small Cancer ◽  
Cancer Tissues

Following recent findings linking the human gut microbiota to gastrointestinal cancer and its treatment, the plausible relationship between lung microbiota and pulmonary cancer is explored. This study aims at characterizing the intratumoral and adjacent healthy tissue microbiota by applying a 16S rRNA gene amplicon sequencing protocol to tissue samples of 29 non-small cancer patients. Emphasis was put on contaminant management and a comprehensive comparison of bacterial composition between cancerous and healthy adjacent tissues of lung adenocarcinoma and squamous cell carcinoma is provided. A variable degree of similarity between the two tissues of a same patient was observed. Each patient seems to possess its own bacterial signature. The two types of cancer tissue do not have a distinct bacterial profile that is shared by every patient. In addition, enteric, potentially pathogenic and pro-inflammatory bacteria were more frequently found in cancer than healthy tissue. This work brings insights into the dynamic of bacterial communities in lung cancer and provides prospective data for more targeted studies.

scholarly journals FAM83A-AS1 Promotes Tumor Progression Through MET Signaling in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Shengbin Bai ◽  
Huijie Zhao ◽  
Xaofei Zeng ◽  
Baoyue Lin ◽  
Yinghan Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Migration And Invasion ◽  
Functional Studies ◽  
Cycle Arrest ◽  
Elevated Expression ◽  
Lung Cancer Therapy ◽  
Prognosis Marker ◽  
Cancer Tissues

Abstract Background Studies demonstrate that long non-coding RNAs (lncRNAs) play critical roles in the occurrence and development of cancer. However, many of the molecular mechanisms underlying lncRNAs role in this process remains unclear. Methods Here, we analyzed lncRNA expression in lung cancer tissues based on RNA-Seq analysis and found that lncRNA FAM83A-AS1 was one of the top up-regulated lncRNAs in lung adenocarcinoma and elevated expression of FAM83A-AS1 was significantly associated with poor patient survival. We validated these results using RT-PCR and an independent cohort of lung cancer. Results Functional studies indicated that knockdown of FAM83A-AS1 decreased cell proliferation, colony formation, migration and invasion in H1299 and H838 lung cancer cells. Knockdown of FAM83A-AS1 induced the autophagy and cell cycle arrest at G2. Mechanistically, we found that MET, p62 and phosphor S6K proteins were decreased upon FAM83A-AS1 knockdown. Conclusion In conclusion, FAM83A-AS1 may have potential as a diagnosis/prognosis marker and its oncogenic role could lead to potential targeting for lung cancer therapy.

scholarly journals Sphingomyelin(d35:1) as a novel predictor for lung adenocarcinoma recurrence after a radical surgery: a case-control study

2020 ◽  
Author(s):  
Yusuke Takanashi ◽  
Kazuhito Funai ◽  
Shumpei Sato ◽  
Akikazu Kawase ◽  
Hong Tao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Radical Surgery ◽  
Tissue Samples ◽  
Recurrent Group ◽  
Recurrence Prediction ◽  
Lipid Species ◽  
Frozen Tissue ◽  
Candidate Predictor ◽  
Lung Adenocarcinomas

Abstract Background: To improve the postoperative prognosis of patients with lung cancer, predicting the recurrence high-risk patients is needed for the efficient application of adjuvant chemotherapy. However, predicting lung cancer recurrence after a radical surgery is difficult even with conventional histopathological prognostic factors, thereby a novel predictor should be identified. As lipid metabolism alterations are known to contribute to cancer progression, we hypothesized that lung adenocarcinomas with high recurrence risk contain candidate lipid predictors. This study aimed to identify candidate lipid predictors for the recurrence of lung adenocarcinoma after a radical surgery.Methods: Frozen tissue samples of primary lung adenocarcinoma obtained from patients who underwent a radical surgery were retrospectively reviewed. Recurrent and non-recurrent cases were assigned to recurrent (n = 10) and non-recurrent (n = 10) groups, respectively. Extracted lipids from frozen tissue samples were subjected to liquid chromatography-tandem mass spectrometry analysis. The average total lipid levels of the non-recurrent and recurrent groups were compared. Candidate predictors were screened by comparing the folding change and P-value of t-test in each lipid species between the recurrent and non-recurrent groups.Results: The average total lipid level of the recurrent group was 1.65 times higher than that of the non-recurrent group (P < 0.05). A total of 203 lipid species were increased (folding change, ≥2; P < 0.05) and 4 lipid species were decreased (folding change, ≤0.5; P < 0.05) in the recurrent group. Among these candidates, increased sphingomyelin (SM)(d35:1) in the recurrent group was the most prominent candidate predictor, showing high performance of recurrence prediction (AUC, 9.1; sensitivity, 1.0; specificity, 0.8; accuracy, 0.9).Conclusion: We propose SM(d35:1) as a novel candidate predictor for lung adenocarcinoma recurrence. Our finding can contribute to precise recurrence prediction and qualified postoperative therapeutic strategy for lung adenocarcinomas.Abbreviations: AUC, area under the ROC curve; ROC, receiver operating characteristic. This retrospective study was registered at the UMIN Clinical Trial Registry (UMIN000039202) on 21st January 2020.

scholarly journals Characteristics of Microbiome in Lung Adenocarcinoma Tissue from Patients in Southwestern China

2020 ◽  
Author(s):  
Sinuo Zhu ◽  
Yunping Zhao ◽  
Yanan Bao ◽  
Yue Cui ◽  
Xingming Zhu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Beta Diversity ◽  
Clinical Stage ◽  
Alpha Diversity ◽  
Southwestern China ◽  
Cancer Tissue ◽  
16S Rna ◽  
Significant Difference ◽  
Cancer Tissues

Abstract Background:Increasing evidences have unveiled the connection between microbiome and lung cancer. This study aims to identify the characteristics of microbial communities in the lung cancer tissues from patients in southwestern China, and to compare the distinct microbial genes at different clinical stages of lung cancer for uncovering potential immunotherapy targets.Methods:Forty samples of primary lung adenocarcinoma tissue were performed by 16S rRNA gene sequencing. The subjects were grouped according to TNM stages (T and N group), clinical stage and smoke status. To identify the taxa composition of each sample, Operational Taxonomic Units (OTUs) were classified on the Effective Tags with 97% identity. The linear discriminant analysis effect size (LEfSe) method was utilized to compare relative abundances of all bacterial taxa between non-metastasis group and metastasis group. The Shannon index of the 97% identity OTUs was calculated to evaluate alpha diversity. Beta diversity measurement was calculated using Principal Co-ordinates Analysis (PCoA).Results:A total of 951 OTUs were identified in the cancer tissues, including 224 overlapping genera. No significant difference has been found in the alpha diversity within all the groups. Beta diversity was significantly different in N group, T group and clinical stage group. By LEfSe analysis, nine differential species were identified in the N group, of which the relative abundance of genus Bifidobacterium was 10.78%±11.59% in the N0 group and 20.15%±13.44% in the N+ group (p<0.05). In the T1 and T2 group, the LEfSe result identified 4 phylum and 10 genera. The differential genera were Moraxella, Dolosigranulum, Corynebacteriaceae and Citrobacter in the T2 group and Bifidobacterium, Alistipes, Akkermansia, Blautia, Lactobacillus as well as Facelibacterium in the T1 group. Differential bacterial composition and abundance were also observed in the clinical stage group.Conclusions:In conclusion, by 16S RNA sequencing, we identified dominant species of lung cancer tissue in different groups of AD patients. Bifidobacterium plays important role both in lymph node metastasis and tumor progression, which could provide specific immunotherapy strategy for lung cancer.

scholarly journals The effectiveness of afatinib in patients with lung adenocarcinoma harboring complex epidermal growth factor receptor mutation

2020 ◽  
Vol 12 ◽  
pp. 175883592094615
Author(s):  
Shang-Gin Wu ◽  
Chong-Jen Yu ◽  
James Chih-Hsin Yang ◽  
Jin-Yuan Shih
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Growth Factor Receptor ◽  
Egfr Mutations ◽  
Line Treatment ◽  
First Line ◽  
Tissue Samples ◽  
Epidermal Growth ◽  
Egfr Tkis ◽  
First Line Treatment

Background and aims: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) are effective against classical EGFR mutations in lung cancer. However, their effectiveness and the prognosis of lung cancer patients with complex EGFR mutations are not well delineated. Therefore, we aimed to investigate the treatment effectiveness of different EGFR TKIs in patients with complex EGFR mutations. Patients and methods: From 2005 to 2020, we collected lung adenocarcinoma tissue samples for EGFR mutation analysis using direct Sanger sequencing. Patients with EGFR mutations treated with EGFR TKIs as first-line treatment were enrolled. Clinical characteristics, EGFR mutation status, treatment response, progression-free survival (PFS), and overall survival (OS) were analyzed. Results: Among 2675 patients with EGFR mutations, 239 (8.9%) had complex EGFR mutations, of whom 125 received EGFR TKI treatment as first-line treatment. Multivariate analysis revealed that afatinib was a more favorable factor for PFS than gefitinib [hazard ratio (HR), 2.01; 95% confidence interval (CI), 1.11–3.62] and erlotinib (HR, 2.61; 95% CI, 1.31–5.22), especially in patients with uncommon mutation patterns. Afatinib treatment as first-line treatment was also associated with longer OS compared with erlotinib (HR, 2.48; 95% CI, 1.20–5.12). Classical mutation pattern was associated with longer PFS ( p = 0.001) and OS ( p = 0.020). Secondary T790M was detected in 22 of 52 (42.3%) patients who had re-biopsied tissue samples after acquiring resistance to EGFR TKIs. There was no significant difference in secondary T790M formation after acquired resistance to the three EGFR TKIs ( p = 0.261). Furthermore, three (5.8%) patients had small-cell lung cancer transformation. Conclusion: Afatinib is an effective first-line treatment for patients with lung adenocarcinoma harboring complex EGFR mutations, especially those with uncommon mutation patterns.

scholarly journals Sphingomyelin(d35:1) as a novel predictor for lung adenocarcinoma recurrence after a radical surgery: a case-control study

2020 ◽  
Author(s):  
Yusuke Takanashi ◽  
Kazuhito Funai ◽  
Shumpei Sato ◽  
Akikazu Kawase ◽  
Hong Tao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Total Lipid ◽  
Radical Surgery ◽  
Tissue Samples ◽  
Recurrent Group ◽  
Recurrence Prediction ◽  
Lipid Species ◽  
Frozen Tissue ◽  
Candidate Predictor

Abstract Background: To improve the postoperative prognosis of patients with lung cancer, predicting the recurrence high-risk patients is needed for the efficient application of adjuvant chemotherapy. However, predicting lung cancer recurrence after a radical surgery is difficult even with conventional histopathological prognostic factors, thereby a novel predictor should be identified. As lipid metabolism alterations are known to contribute to cancer progression, we hypothesized that lung adenocarcinomas with high recurrence risk contain candidate lipid predictors. This study aimed to identify candidate lipid predictors for the recurrence of lung adenocarcinoma after a radical surgery.Methods: Frozen tissue samples of primary lung adenocarcinoma obtained from patients who underwent a radical surgery were retrospectively reviewed. Recurrent and non-recurrent cases were assigned to recurrent (n = 10) and non-recurrent (n = 10) groups, respectively. Extracted lipids from frozen tissue samples were subjected to liquid chromatography-tandem mass spectrometry analysis. The average total lipid levels of the non-recurrent and recurrent groups were compared. Candidate predictors were screened by comparing the folding change and P-value of t-test in each lipid species between the recurrent and non-recurrent groups.Results: The average total lipid level of the recurrent group was 1.65 times higher than that of the non-recurrent group (P < 0.05). A total of 203 lipid species were increased (folding change, ≥2; P < 0.05) and 4 lipid species were decreased (folding change, ≤0.5; P < 0.05) in the recurrent group. Among these candidates, increased sphingomyelin (SM)(d35:1) in the recurrent group was the most prominent candidate predictor, showing high performance of recurrence prediction (AUC, 9.1; sensitivity, 1.0; specificity, 0.8; accuracy, 0.9).Conclusion: We propose SM(d35:1) as a novel candidate predictor for lung adenocarcinoma recurrence. Our finding can contribute to precise recurrence prediction and qualified postoperative therapeutic strategy for lung adenocarcinomas.Abbreviations: AUC, area under the ROC curve; ROC, receiver operating characteristic.

scholarly journals Sphingomyelin(d35:1) as a novel predictor for lung adenocarcinoma recurrence after a radical surgery: a case control study

2020 ◽  
Author(s):  
Yusuke Takanashi ◽  
Kazuhito Funai ◽  
Shumpei Sato ◽  
Akikazu Kawase ◽  
Hong Tao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Radical Surgery ◽  
Tissue Samples ◽  
Recurrent Group ◽  
Recurrence Prediction ◽  
Lipid Species ◽  
Frozen Tissue ◽  
Candidate Predictor ◽  
Lung Adenocarcinomas

Abstract Background To improve the postoperative prognosis of patients with lung cancer, predicting the recurrence high-risk patients is needed for the efficient application of adjuvant chemotherapy. However, predicting lung cancer recurrence after a radical surgery is difficult even with conventional histopathological prognostic factors, thereby a novel predictor should be identified. As lipid metabolism alterations are known to contribute to cancer progression, we hypothesized that lung adenocarcinomas with high recurrence risk contain candidate lipid predictors. This study aimed to identify candidate lipid predictors for the recurrence of lung adenocarcinoma after a radical surgery. Methods Frozen tissue samples of primary lung adenocarcinoma obtained from patients who underwent a radical surgery were retrospectively reviewed. Recurrent and non-recurrent cases were assigned to recurrent (n = 10) and non-recurrent (n = 10) groups, respectively. Extracted lipids from frozen tissue samples were subjected to liquid chromatography-tandem mass spectrometry analysis. The average total lipid levels of the non-recurrent and recurrent groups were compared. Candidate predictors were screened by comparing the folding change and P-value of t-test in each lipid species between the recurrent and non-recurrent groups. Results The average total lipid level of the recurrent group was 1.65 times higher than that of the non-recurrent group (P < 0.05). A total of 203 lipid species were increased (folding change, ≥ 2; P < 0.05) and 4 lipid species were decreased (folding change, ≤ 0.5; P < 0.05) in the recurrent group. Among these candidates, increased sphingomyelin (SM)(d35:1) in the recurrent group was the most prominent candidate predictor, showing high performance of recurrence prediction (AUC, 9.1; sensitivity, 1.0; specificity, 0.8; accuracy, 0.9). Conclusion We propose SM(d35:1) as a novel candidate predictor for lung adenocarcinoma recurrence. Our finding can contribute to precise recurrence prediction and qualified postoperative therapeutic strategy for lung adenocarcinomas.

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