A clonal expression biomarker associates with lung cancer mortality

Biswas, Dhruva; Birkbak, Nicolai J.; Rosenthal, Rachel; Hiley, Crispin; Lim, Emilia L.; Papp, Krisztián; Boeing, Stefan; Krzystanek, Marcin; Djureinovic, Dijana; Fleur, Linnéa La; Greco, Maria; Döme, Balázs; Fillinger, János; Brunnström, Hans; Wu, Yin; Moore, David A.; Skrzypski, Marcin; Abbosh, Christopher; Litchfield, Kevin; Bakir, Maise Al; Watkins, Thomas B.K.; Veeriah, Selvaraju; Wilson, Gareth A.; Jamal‐Hanjani, Mariam; Moldvay, Judit; Botling, Johan; Chinnaiyan, Arul M.; Micke, Patrick; Hackshaw, Allan; Bártek, Jiří; Csabai, István; Szállási, Zoltán; Herrero, Javier; McGranahan, Nicholas; Swanton, Charles

doi:10.1038/s41591-019-0595-z

Cited by 88 publications

(79 citation statements)

References 62 publications

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“…Poor genome-wide correlation between expression levels of mRNA and protein has been reported [13,14]. Lack of correlation between PFDN mRNA and PFDN protein levels, due to translational or protein turn-over regulation, may explain why PFDN was not included in any of the expression signatures so far proposed for the prognosis of LC based on transcriptomics (see Biswas et al [15] and the other nine previous signatures cited therein). Other EMT protein markers with high prognostic significance in NSCLC, such as Snail and TWIST1 [16], were also out of published prognostic transcriptomic signatures.…”

Section: Discussionmentioning

confidence: 99%

Overexpression of Canonical Prefoldin Associates with the Risk of Mortality and Metastasis in Non-Small Cell Lung Cancer

Peñate

Praena-Fernández

Pareja

et al. 2020

Cancers

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Canonical prefoldin is a protein cochaperone composed of six different subunits (PFDN1 to 6). PFDN1 overexpression promotes epithelial–mesenchymal transition (EMT) and increases the growth of xenograft lung cancer (LC) cell lines. We investigated whether this putative involvement of canonical PFDN in LC translates into the clinic. First, the mRNA expression of 518 non-small cell LC (NSCLC) cases from The Cancer Genome Atlas (TCGA) database was evaluated. Patients with PFDN1 overexpression had lower overall survival (OS; 45 vs. 86 months; p = 0.034). We then assessed the impact of PFDN expression on outcome in 58 NSCLC patients with available tumor tissue samples. PFDN1, 3, and 5 overexpression were found in 38% (n = 22), 53% (n = 31), and 41% (n = 24) of tumor samples. PFDN1, 3, and 5 overexpression were significantly associated with lower OS, lower disease-free survival (DFS), and lower distant metastasis-free survival (DMFS) for PFDN1 and 3 with a trend for PFDN5. In multivariate analysis, PFDN5 retained significance for OS (hazard ratio (HR) 2.56; p = 0.007) and PFDN1 for DFS (HR 2.53; p = 0.010) and marginally for DMFS (HR 2.32; p = 0.053). Our results indicate that protein response markers, such as PFDN1, 3, and 5, may complement mRNA signatures and be useful for determining the most appropriate therapy for NSCLC patients.

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Section: Discussionmentioning

confidence: 99%

Overexpression of Canonical Prefoldin Associates with the Risk of Mortality and Metastasis in Non-Small Cell Lung Cancer

Peñate

Praena-Fernández

Pareja

et al. 2020

Cancers

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“…Intratumoral heterogeneity provides the seeds for intermetastastic heterogeneity. Intratumoral heterogeneity mediated through chromosome instability is associated with an increased risk of recurrence or death in NSCLC and driven metastasis ( 19 , 20 , 89 ). Chromosome instability is increased in brain metastases and is a driver of metastasis ( 65 , 90 ).…”

Section: Mechanism Of Lung Cancer Driver Genes In Brain Metastasismentioning

confidence: 99%

Advances in Lung Cancer Driver Genes Associated With Brain Metastasis

Kang

Jin

et al. 2021

Front. Oncol.

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Brain metastasis, one of the common complications of lung cancer, is an important cause of death in patients with advanced cancer, despite progress in treatment strategies. Lung cancers with positive driver genes have higher incidence and risk of brain metastases, suggesting that driver events associated with these genes might be biomarkers to detect and prevent disease progression. Common lung cancer driver genes mainly encode receptor tyrosine kinases (RTKs), which are important internal signal molecules that interact with external signals. RTKs and their downstream signal pathways are crucial for tumor cell survival, invasion, and colonization in the brain. In addition, new tumor driver genes, which also encode important molecules closely related to the RTK signaling pathway, have been found to be closely related to the brain metastases of lung cancer. In this article, we reviewed the relationship between lung cancer driver genes and brain metastasis, and summarized the mechanism of driver gene-associated pathways in brain metastasis. By understanding the molecular characteristics during brain metastasis, we can better stratify lung cancer patients and alert those at high risk of brain metastasis, which helps to promote individual therapy for lung cancer.

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“…Careful assessing sensitive and novel biomarkers could monitor the progress and prognosis of carcinoma outcomes [5][6][7][8][9][10][11]. Based on alterations in these molecular or pathways, different assessment of biomarkers that give novel insights into bladder urothelial carcinoma mechanism.…”

Section: Discussionmentioning

confidence: 99%

Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma

Luo

Zhang

2020

BioMed Research International

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Background. Though there are several prognostic models, there is no protein-related prognostic model. The aim of this study is to identify possible prognostic-related proteins in bladder urothelial carcinoma and to try to predict the prognosis of bladder urothelial carcinoma based on these proteins. Methods. Profile data and corresponding clinical traits were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA) expression. Survival-associated protein in bladder urothelial carcinoma patients were estimated with Kaplan-Meier (KM) test and COX regression analysis. The potential molecular mechanisms and properties of these bladder urothelial carcinoma-specific proteins were also explored with the help of computational skills. The risk score model was validated in different clinical traits. Sankey diagram representation is for protein correlation. A new prognostic-related risk model based on proteins was developed by using multivariable COX analysis. Next, the alteration of the corresponding genes to the 6 prognostic-related proteins was analyzed. Finally, the relation between the corresponding genes and the immune infiltration was analyzed using the TIMER. Results. Six proteins were identified to be associated with the prognosis of bladder urothelial carcinoma. A prognostic signature based on proteins (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1, and AXL) performed moderately in prognostic predictions. The alteration of corresponding genes was in 31(24%) sequenced cases. ANXA1, AXL, and EGFR were positively related to CD8+ T cell. Conclusion. Our results screened six proteins of clinical significance. The importance of a personalized protein signature model in the recognition, surveillance. The abnormal expression of six prognostic-related proteins may be caused by corresponding gene alteration. Furthermore, these proteins may affect survival via the immune infiltration.

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A clonal expression biomarker associates with lung cancer mortality

Abstract: for noncommercial research purposes, and access will be granted upon review of a project proposal that will be evaluated by a TRACERx data access committee and entering into an appropriate data access agreement subject to any applicable ethical approvals.

Cited by 88 publications

References 62 publications

Overexpression of Canonical Prefoldin Associates with the Risk of Mortality and Metastasis in Non-Small Cell Lung Cancer

Overexpression of Canonical Prefoldin Associates with the Risk of Mortality and Metastasis in Non-Small Cell Lung Cancer

Advances in Lung Cancer Driver Genes Associated With Brain Metastasis

Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma

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