Deciphering the genomic, epigenomic, and transcriptomic landscapes of pre-invasive lung cancer lesions

Teixeira, Vítor Hugo; Pipinikas, Christodoulos P.; Pennycuick, Adam; Lee-Six, Henry; Chandrasekharan, Deepak; Beane, Jennifer; Morris, Tiffany; Karpathakis, Anna; Feber, Andrew; Breeze, Charles E.; Ntolios, Paschalis; Hynds, Robert E.; Falzon, Mary; Capitanio, Arrigo; Carroll, Bernadette; Durrenberger, Pascal F.; Hardavella, Georgia; Brown, James M.; Lynch, Andy G.; Farmery, Henry; Paul, Dirk S.; Chambers, Rachel C.; McGranahan, Nicholas; Navani, Neal; Thakrar, Ricky; Swanton, Charles; Beck, Stephan; George, Phillip Jeremy; Spira, Avrum; Campbell, Peter J.; Thirlwell, Christina; Janes, Sam M.

doi:10.1038/s41591-018-0323-0

Cited by 187 publications

(156 citation statements)

References 69 publications

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“…Among the most significantly inactivated TFs, we observed FOXA2 , a TF required for alveolarization 53, 54 and that regulates airway epithelial cell differentiation ( Fig.4E ), and NKX2-1 , a master TF of early lung development ( SI fig.S11 ). Both of these TFs have been found to be inactivated in bulk tumor samples, representing lung carcinoma in situ (LCIS) 37, 55 and lung squamous cell carcinoma (LUSC) 37 , consistent with SCIRA’s predictions. Other important TFs predicted by SCIRA to be inactivated included SOX13, which has been broadly implicated in lung morphogenesis 56 , and HIF3A which has been shown to be highly expressed in alveolar epithelial cells and thought to be protective of hypoxia-induced damage 57 ( SI fig.S10 ).…”

Section: Resultssupporting

confidence: 81%

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Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

Wang¹,

Teschendorff

2019

Preprint

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9Inferring the activity of transcription factors in single cells is a key task to improve our 2 0 4 1 relationships function at the single-cell level and therefore their implications can only be truly 4 2 understood at single-cell resolution 3-8 . 4 3 Recent single-cell RNA-sequencing (scRNA-Seq) studies have significantly advanced our 4 4 understanding of cellular development and disease 4, 7, 9-29 , yet how best to infer regulatory 4 5 activity at the single-cell level is still unclear. While a number of methods for inferring 4 6 regulatory activity have appeared 30-32 , all attempt to do so by first inferring the regulatory 4 7interactions from the noisy scRNA-Seq data itself, an approach recently assessed by others to 4 8 be highly suboptimal 33 , mainly because of the relatively high dropout rate of such data 5, 34 . 4 9 7 1 Motivation and rationale for the SCIRA algorithm 7 2

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Section: Resultssupporting

confidence: 81%

“…NKX2-1, FOXA2, FOXJ1 , AHR, HIF3A ) implicate key cancer-pathways (lung differentiation, immune-response, hypoxia-response), and their inactivation likely represents key driver events. Supporting this, epigenetically induced silencing of NKX2-1 has recently been proposed to be a key driver event in the development of lung cancer 55 .…”

Section: Discussionmentioning

confidence: 86%

Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

Wang¹,

Teschendorff

2019

Preprint

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“…This assay can assist CT scans in discriminating between noninvasive and invasive GGNs with a higher diagnostic accuracy (AUC: 0.792, sensitivity: 74.6%, and specificity: 74.4%) compared with current clinical biomarkers, and provide surgeons with complementary information about the pathological changes of GGN. To date, increasing studies have paid attention to the genetic and transcriptomic features of noninvasive lesions [10,62]; however, no serological evidence is available to suggest which kind of GGN should be resected. Our results suggest that an early glycosylation feature of IgG might predict the invasiveness potential with a better performance than current tumor biomarkers in assisting clinical decision making.…”

Section: Discussionmentioning

confidence: 99%

Glycomic Signatures of Plasma IgG Improve Preoperative Prediction of the Invasiveness of Small Lung Nodules

et al. 2019

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Preoperative assessment of tumor invasiveness is essential to avoid overtreatment for patients with small-sized ground-glass nodules (GGNs) of 10 mm or less in diameter. However, it is difficult to determine the pathological state by computed tomography (CT) examination alone. Aberrant glycans has emerged as a tool to identify novel potential disease biomarkers. In this study, we used a lectin microarray-based strategy to investigate whether glycosylation changes in plasma immunoglobulin G (IgG) provide additional information about the invasiveness of small GGNs before surgery. Two independent cohorts (discovery set, n = 92; test set, n = 210) of GGN patients were used. Five of 45 lectins (Sambucus nigra agglutinin, SNA; Datura stramonium agglutinin, DSA; Galanthus nivalis agglutinin, GNA; Euonymus europaeus lectin, EEL; and Vicia villosa agglutinin, VVA) were identified as independent factors associated with pathological invasiveness of small GGNs (p < 0.01). Receiver-operating characteristic (ROC) curve analysis indicated the combination of these five lectins could significantly improve the accuracy of CT in diagnosing invasive GGNs, with an area under the curve (AUC) of 0.792 (p < 0.001), a sensitivity of 74.6%, and specificity of 74.4%, which was superior to current clinical biomarkers. These results suggest that the multilectin assay based on plasma IgG glycosylation may be a useful in vitro complementary test to enhance preoperative determination of the invasiveness of GGNs and guide surgeons to select proper clinical management to avoid overtreatment.

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“…Along the same lines, the progression of LUSC PMLs, also known as carcinoma in situ (CIS), was shown to be predictable using genetic and immune clues. In one report, authors focused on longitudinal CIS biopsies that either progressed to form LUSC or regressed and regained a normal appearance (267). After profiling the genomic, transcriptomic, and epigenomic landscape of those PMLs, the predictive value of specific geneexpression signatures, DNA methylation patterns and copy number alterations was confirmed for specific genes, which could be used to accurately determine the probability of CIS progression (267).…”

Section: Immunogenomics For a Deeper Understanding Of Pmlsmentioning

confidence: 99%

Insights Into Lung Cancer Immune-Based Biology, Prevention, and Treatment

et al. 2020

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Deciphering the genomic, epigenomic, and transcriptomic landscapes of pre-invasive lung cancer lesions

Abstract: Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions.

Cited by 187 publications

References 69 publications

Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

Glycomic Signatures of Plasma IgG Improve Preoperative Prediction of the Invasiveness of Small Lung Nodules

Insights Into Lung Cancer Immune-Based Biology, Prevention, and Treatment

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