| 1. |
- Salomonsson, A., et al.
(författare)
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A Nation-Wide Population-Based Mapping of Targetable Alterations in Smoking-Independent Lung Cancer
- 2018
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Ingår i: Journal of Thoracic Oncology. - : Elsevier. - 1556-0864 .- 1556-1380. ; 13:10, s. S431-S432
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Smoking is by far the most important cause of lung cancer. However, lung cancer among never-smokers is common and increasing [1]. A smoking-independent subgroup of lung adenocarcinoma with certain molecular and clinical features exists [2-3]. Therefore, as 1st project within the Swedish Molecular Initiative against Lung cancer (SMIL) we aim to characterize never-smoking lung cancer for etiological, diagnostic and therapeutic purposes.Method: Through the Swedish National Lung Cancer Registry [1], we identified all individuals who underwent surgery for lung cancer in Sweden 2005-2014 and who were registered as never-smokers (n=540). At each study site (n=6), clinical data were reviewed by a thoracic oncologist/pulmonologist through patients' medical charts and archived tumor tissues were retrieved and reviewed by a thoracic pathologist. For subsequent studies, we extracted DNA and RNA (using the Qiagen AllPrep kit for FFPE tissue) and constructed tissue microarrays. As a first pre-planned analysis, we performed fusion gene mapping using an RNA-based NanoString nCounter Elements assay, as previously described [4].Result: In the first 212 (out of 540) analyzed samples, we detected 17 fusions involving ALK, 8 involving RET, and 2 involving NRG1. In addition, MET exon 14 skipping was found in 17 samples. In total, these findings involved 21% of analyzed cases. Additional results from further studies on the cohort will be presented.Conclusion: SMIL is an ongoing nation-wide molecular research collaboration on lung cancer where we currently collect one of the largest never-smoking lung tumor cohorts worldwide. From the first pre-planned analyses, we conclude that, in a population-based cohort of early stage lung cancer from never-smokers, druggable oncogenic fusions are frequent.
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| 2. |
- Midttun, Øivind, et al.
(författare)
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A cross-sectional study of inflammatory markers as determinants of circulating kynurenines in the Lung Cancer Cohort Consortium
- 2023
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Circulating concentrations of metabolites (collectively called kynurenines) in the kynurenine pathway of tryptophan metabolism increase during inflammation, particularly in response to interferon-gamma (IFN-γ). Neopterin and the kynurenine/tryptophan ratio (KTR) are IFN-γ induced inflammatory markers, and together with C-reactive protein (CRP) and kynurenines they are associated with various diseases, but comprehensive data on the strength of associations of inflammatory markers with circulating concentrations of kynurenines are lacking. We measured circulating concentrations of neopterin, CRP, tryptophan and seven kynurenines in 5314 controls from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). The associations of neopterin, KTR and CRP with kynurenines were investigated using regression models. In mixed models, one standard deviation (SD) higher KTR was associated with a 0.46 SD higher quinolinic acid (QA), and 0.31 SD higher 3-hydroxykynurenine (HK). One SD higher neopterin was associated with 0.48, 0.44, 0.36 and 0.28 SD higher KTR, QA, kynurenine and HK, respectively. KTR and neopterin respectively explained 24.1% and 16.7% of the variation in QA, and 11.4% and 7.5% of HK. CRP was only weakly associated with kynurenines in regression models. In summary, QA was the metabolite that was most strongly associated with the inflammatory markers. In general, the inflammatory markers were most strongly related to metabolites located along the tryptophan-NAD axis, which may support suggestions of increased production of NAD from tryptophan during inflammation.
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| 3. |
- Wang, Xinan, et al.
(författare)
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Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification
- 2024
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Ingår i: Genome Medicine. - : BioMed Central (BMC). - 1756-994X. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.Methods: Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.Results: Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12–3.50, P-value = 4.13 × 10−15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99–2.49, P-value = 5.70 × 10−46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72–0.74). Conclusions: Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.
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| 4. |
- Zhang, Ruyang, et al.
(författare)
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A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians
- 2022
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Ingår i: Journal of Thoracic Oncology. - : Elsevier. - 1556-0864 .- 1556-1380. ; 17:8, s. 974-990
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).Methods: Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.Results: With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10−13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10−13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10−13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10−13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10−4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.Conclusions: Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.
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