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• W3041219630 abstract "•First deep proteogenomic landscape of non-smoking lung adenocarcinoma in East Asia•Identified age, sex-related endogenous, and environmental carcinogen mutagenic processes•Proteome-informed classification distinguished clinical features within early stages•Protein networks identified tumorigenesis hallmarks, biomarkers, and druggable targets Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma. Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma. Lung cancer remains the most common malignancy and the leading cause of cancer mortality worldwide (Bray et al., 2018Bray F. Ferlay J. Soerjomataram I. Siegel R.L. Torre L.A. Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin. 2018; 68: 394-424Crossref PubMed Scopus (38104) Google Scholar) and has been mainly attributed to direct tobacco exposure (Bach, 2009Bach P.B. Smoking as a Factor in Causing Lung Cancer.JAMA. 2009; 301: 539-541Crossref PubMed Scopus (15) Google Scholar). However, its incidence in never-smokers remains a significant health problem globally, especially in East Asia and most predominantly among women; the non-smoking-related etiology and carcinogenesis remain poorly understood (Jemal et al., 2018Jemal A. Miller K.D. Ma J. Siegel R.L. Fedewa S.A. Islami F. Devesa S.S. Thun M.J. Higher Lung Cancer Incidence in Young Women Than Young Men in the United States.N. Engl. J. Med. 2018; 378: 1999-2009Crossref PubMed Scopus (134) Google Scholar; Sun et al., 2007Sun S. Schiller J.H. Gazdar A.F. Lung cancer in never smokers–a different disease.Nat. Rev. Cancer. 2007; 7: 778-790Crossref PubMed Scopus (1041) Google Scholar). In Taiwanese population, never-smoker patients are predominant (53%), especially among females (93%) (Tseng et al., 2019Tseng C.H. Tsuang B.J. Chiang C.J. Ku K.C. Tseng J.S. Yang T.Y. Hsu K.H. Chen K.C. Yu S.L. Lee W.C. et al.The Relationship Between Air Pollution and Lung Cancer in Nonsmokers in Taiwan.J. Thorac. Oncol. 2019; 14: 784-792Abstract Full Text Full Text PDF PubMed Scopus (37) Google Scholar). Additionally, early onset is a distinct feature of lung adenocarcinoma (LUAD) in East Asia, particularly among never-smokers (Kawaguchi et al., 2010Kawaguchi T. Matsumura A. Fukai S. Tamura A. Saito R. Zell J.A. Maruyama Y. Ziogas A. Kawahara M. Ignatius Ou S.H. Japanese ethnicity compared with Caucasian ethnicity and never-smoking status are independent favorable prognostic factors for overall survival in non-small cell lung cancer: a collaborative epidemiologic study of the National Hospital Organization Study Group for Lung Cancer (NHSGLC) in Japan and a Southern California Regional Cancer Registry databases.J. Thorac. Oncol. 2010; 5: 1001-1010Abstract Full Text Full Text PDF PubMed Scopus (86) Google Scholar). Genetic factors and exposure to environmental carcinogens may present risk factors contributing to these population differences (Samet et al., 2009Samet J.M. Avila-Tang E. Boffetta P. Hannan L.M. Olivo-Marston S. Thun M.J. Rudin C.M. Lung cancer in never smokers: clinical epidemiology and environmental risk factors.Clin. Cancer Res. 2009; 15: 5626-5645Crossref PubMed Scopus (338) Google Scholar). For instance, in Taiwan, air pollution has been shown to correlate with the incidence of lung cancer in never-smokers (Tseng et al., 2019Tseng C.H. Tsuang B.J. Chiang C.J. Ku K.C. Tseng J.S. Yang T.Y. Hsu K.H. Chen K.C. Yu S.L. Lee W.C. et al.The Relationship Between Air Pollution and Lung Cancer in Nonsmokers in Taiwan.J. Thorac. Oncol. 2019; 14: 784-792Abstract Full Text Full Text PDF PubMed Scopus (37) Google Scholar). To complement the advances in precision therapy for advanced stage, early detection and prevention may create better clinical and economic benefits for patients and LUAD management. Thus, it is crucial to understand the early processes and progression of oncogenesis, as well as the contributing factors associated with endogenous and environmental mutagens underlying the unique characteristics of non-smoking LUAD in East Asia. Significant unmet clinical needs remain in early stage LUAD. About 20% of stage I patients still relapse after surgical resection worldwide (Sawabata et al., 2010Sawabata N. Asamura H. Goya T. Mori M. Nakanishi Y. Eguchi K. Koshiishi Y. Okumura M. Miyaoka E. Fujii Y. et al.Japanese Lung Cancer Registry Study: first prospective enrollment of a large number of surgical and nonsurgical cases in 2002.J. Thorac. Oncol. 2010; 5: 1369-1375Abstract Full Text Full Text PDF PubMed Scopus (98) Google Scholar). At the molecular level, EGFR activating mutations, comprising mainly L858R mutation and the E746_A750 exon 19 deletion, occur much more frequently in East Asia (>50%, especially in never-smoker females) (Yang et al., 2020Yang C.J. Yang J.C.H. Yang P.C. Precision management of advanced non-small cell lung cancer.Annu. Rev. Med. 2020; 2020: 117-136Crossref Scopus (35) Google Scholar; Shi et al., 2014Shi Y. Au J.S. Thongprasert S. Srinivasan S. Tsai C.M. Khoa M.T. Heeroma K. Itoh Y. Cornelio G. Yang P.C. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER).J. Thorac. Oncol. 2014; 9: 154-162Abstract Full Text Full Text PDF PubMed Scopus (747) Google Scholar). Although patients bearing EGFR mutations benefit from targeted therapies using tyrosine kinase inhibitors, most of them eventually develop resistance (Tomasello et al., 2018Tomasello C. Baldessari C. Napolitano M. Orsi G. Grizzi G. Bertolini F. Barbieri F. Cascinu S. Resistance to EGFR inhibitors in non-small cell lung cancer: Clinical management and future perspectives.Crit. Rev. Oncol. Hematol. 2018; 123: 149-161Crossref PubMed Scopus (32) Google Scholar). Distinctly, patients with EGFR-L858R mutation display shorter overall survival and a higher tendency to develop malignant pleural effusion and cancer metastasis compared to patients with EGFR exon 19 deletion (Kelly et al., 2018Kelly W.J. Shah N.J. Subramaniam D.S. Management of Brain Metastases in Epidermal Growth Factor Receptor Mutant Non-Small-Cell Lung Cancer.Front. Oncol. 2018; 8: 208Crossref PubMed Scopus (37) Google Scholar). A more comprehensive understanding of the molecular remodeling associated with oncogenic EGFR mutations in early stage will help to devise more effective therapeutic approaches. The mutational spectrum of LUAD has been extensively explored by several genomic studies, mostly representing smoking-predominant cohorts (Campbell et al., 2016Campbell J.D. Alexandrov A. Kim J. Wala J. Berger A.H. Pedamallu C.S. Shukla S.A. Guo G. Brooks A.N. Murray B.A. et al.Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas.Nat. Genet. 2016; 48: 607-616Crossref PubMed Scopus (558) Google Scholar; Cancer Genome Atlas Research, 2014Cancer Genome Atlas Research NetworkComprehensive molecular profiling of lung adenocarcinoma.Nature. 2014; 511: 543-550Crossref PubMed Scopus (3022) Google Scholar; Imielinski et al., 2012Imielinski M. Berger A.H. Hammerman P.S. Hernandez B. Pugh T.J. Hodis E. Cho J. Suh J. Capelletti M. Sivachenko A. et al.Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.Cell. 2012; 150: 1107-1120Abstract Full Text Full Text PDF PubMed Scopus (1237) Google Scholar). These studies generated comprehensive catalogs of somatic mutations in Western populations and mutational subtypes associated with smoking. Multi-dimensional “omics” strategies encompassing proteome and phosphoproteome profiling of cancer tissues, in conjunction with genomic analysis, have elucidated new disease subtypes and signaling pathways, as well as potential targets for therapeutic development (Gao et al., 2019Gao Q. Zhu H. Dong L. Shi W. Chen R. Song Z. Huang C. Li J. Dong X. Zhou Y. et al.Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma.Cell. 2019; 179: 561-577.e22Abstract Full Text Full Text PDF PubMed Scopus (165) Google Scholar; Vasaikar et al., 2019Vasaikar S. Huang C. Wang X. Petyuk V.A. Savage S.R. Wen B. Dou Y. Zhang Y. Shi Z. Arshad O.A. et al.Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities.Cell. 2019; 177: 1035-1049.e19Abstract Full Text Full Text PDF PubMed Scopus (193) Google Scholar; Zhang et al., 2016Zhang H. Liu T. Zhang Z. Payne S.H. Zhang B. McDermott J.E. Zhou J.Y. Petyuk V.A. Chen L. Ray D. et al.Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian.Cancer Cell. 2016; 166: 755-765Scopus (468) Google Scholar). Although the genomic profiles of lung cancer in Chinese patients were recently reported (Luo et al., 2018Luo W. Tian P. Wang Y. Xu H. Chen L. Tang C. Shu Y. Zhang S. Wang Z. Zhang J. et al.Characteristics of genomic alterations of lung adenocarcinoma in young never-smokers.Int. J. Cancer. 2018; 143: 1696-1705Crossref PubMed Scopus (27) Google Scholar; Wang et al., 2018aWang C. Yin R. Dai J. Gu Y. Cui S. Ma H. Zhang Z. Huang J. Qin N. Jiang T. et al.Whole-genome sequencing reveals genomic signatures associated with the inflammatory microenvironments in Chinese NSCLC patients.Nat. Commun. 2018; 9: 2054Crossref PubMed Scopus (37) Google Scholar; Zhang et al., 2019Zhang X.C. Wang J. Shao G.G. Wang Q. Qu X. Wang B. Moy C. Fan Y. Albertyn Z. Huang X. et al.Comprehensive genomic and immunological characterization of Chinese non-small cell lung cancer patients.Nat. Commun. 2019; 10: 1772Crossref PubMed Scopus (77) Google Scholar), a comprehensive proteogenomic profiling that can inform on the etiology and unique features of never-smoker and early onset of LUAD in East Asia is currently lacking. In this study, we performed comprehensive genomic, transcriptomic, proteomic, and phosphorylation analysis of patient-matched early stage LUAD tumors, the predominant type of non-small cell lung cancer (NSCLC), and normal adjacent tissues (NATs) obtained from Taiwanese patients representative of the East Asian population. This integrated proteogenomic view revealed the molecular attributes associated with early events and non-smoking-related processes in LUAD, serving as a resource to the cancer community to further delineate the underlying biology and address the unmet clinical needs. Another large, deep scale proteogenomics study of lung adenocarcinoma in a geographically diverse set of patient samples appears in this issue (Gillette et al., 2020Gillette M.A. Satpathy S. Cao S. Dhanasekaran S.M. Vasaikar S.V. Krug K. Petralia F. Li Y. Liang W.-W. Reva B. et al.Proteogenomic characterization reveals therapeutic vulnerabilities in lung adenocarcinoma.Cell. 2020; 183 (this issue): 200-225Abstract Full Text Full Text PDF Scopus (94) Google Scholar). To characterize the proteogenomic landscape of lung adenocarcinoma in East Asia, whole exome sequencing (WES), RNA-seq, proteomics, and phosphoproteomics data were collected from patient-matched tumor and NAT from 103 treatment-naive patients from Taiwan. The clinicopathological characteristics of patients and tumors are summarized in Table S1A. The prospective cohort consisted of 42% male and 58% female patients, 83% non-smokers, and had a median age of 63 years. This cohort (henceforth TW) is distinct from previous lung cancer genomics studies composed of more than 70% of smokers (Campbell et al., 2016Campbell J.D. Alexandrov A. Kim J. Wala J. Berger A.H. Pedamallu C.S. Shukla S.A. Guo G. Brooks A.N. Murray B.A. et al.Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas.Nat. Genet. 2016; 48: 607-616Crossref PubMed Scopus (558) Google Scholar; Cancer Genome Atlas Research, 2014Cancer Genome Atlas Research NetworkComprehensive molecular profiling of lung adenocarcinoma.Nature. 2014; 511: 543-550Crossref PubMed Scopus (3022) Google Scholar; Imielinski et al., 2012Imielinski M. Berger A.H. Hammerman P.S. Hernandez B. Pugh T.J. Hodis E. Cho J. Suh J. Capelletti M. Sivachenko A. et al.Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.Cell. 2012; 150: 1107-1120Abstract Full Text Full Text PDF PubMed Scopus (1237) Google Scholar). Histologically, 89% of the tumors were adenocarcinoma, and 80% were at early stages IA and IB (Table S1B). In the adenocarcinoma group (n = 91), a total of 23,145 nonsynonymous somatic single nucleotide variants (SNVs, Table S1C) were identified. At the transcriptional level, a total of 30,155 RNAs were quantified (Table S1D). Using isobaric labeling (Figure S1A), more than 10,000 unique proteins and 20,000 phosphosites were quantified (Figures S1B–S1D; Table S1E–S1G). Two reference samples from a pool of tumor and normal tissues and a pool of late stage tumors that were included in all batches showed a mean correlation of 0.88 and 0.83 for the proteome and phosphoproteome respectively, confirming high technical reproducibility (Figures S1E and S1F). Genomic profiles of genes implicated in cancer according to the Cancer Gene Census (COSMIC) are shown in Figure 1A and Table S1C. EGFR mutations occurred in most patients (85%) as expected, followed by mutations in TP53 (33%) and RBM10 (20%). The overall proportions of SNVs were different between TW and TCGA (the Cancer Genome Atlas) cohorts (p = 0.0005, Figure S1G), with cytosine to thymine (C>T) transition being the most frequent in the TW cohort (Figure 1A, bottom panel) and smoking-related cytosine to adenine (C>A) transversion being the most frequent in the TCGA cohort (Figure 1B). Non-smokers in the two cohorts showed similar proportions of C>T transitions (Table S1H). In contrast, the smoking related C>A transversions are significantly prominent in the TCGA cohort (p = 0.0053, Table S1I), especially in smokers (p < 0.0001). Most interestingly, no significant difference in C>A transversions was observed between smokers and non-smokers in the TW cohort (Table S1I). These observations suggest less significant smoking-related features, implicating other factors contributing to the genomic landscape of TW cohort. Notably, RBM10 and EGFR-L858R mutations were frequent in females, whereas KRAS and APC were often mutated in males (Fisher’s exact test, p < 0.05; Figure 1C, top panel). KRAS and ATM were prominent mutations among patients with smoking history (p < 0.01; Figure 1C, bottom panel). Notably, RBM10 mutations were more prevalent in older females (Figure 1C, middle panel) and coincided with downregulation of both RNA (p = 0.021) and protein (p = 0.036) levels, which was not significant in males (Figure S1H). The frequently mutated genes were tested for mutual exclusivity that may indicate novel synthetic lethality or distinct clonal evolution (Hua et al., 2016Hua X. Hyland P.L. Huang J. Song L. Zhu B. Caporaso N.E. Landi M.T. Chatterjee N. Shi J. MEGSA: A Powerful and Flexible Framework for Analyzing Mutual Exclusivity of Tumor Mutations.Am. J. Hum. Genet. 2016; 98: 442-455Abstract Full Text Full Text PDF PubMed Scopus (22) Google Scholar). In addition to the expected mutual exclusivity between EGFR and KRAS mutations (p < 0.01) (Suda et al., 2010Suda K. Tomizawa K. Mitsudomi T. Biological and clinical significance of KRAS mutations in lung cancer: an oncogenic driver that contrasts with EGFR mutation.Cancer Metastasis Rev. 2010; 29: 49-60Crossref PubMed Scopus (174) Google Scholar), RBM10 mutations were mutually exclusive with TP53, KRAS, XIRP2, and ZNF804B mutations (p < 0.05, Figure 1D). Correlation analysis across studies using mutation frequencies from cBioPortal (Cerami et al., 2012Cerami E. Gao J. Dogrusoz U. Gross B.E. Sumer S.O. Aksoy B.A. Jacobsen A. Byrne C.J. Heuer M.L. Larsson E. et al.The cBiol. cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.Cancer Discov. 2012; 2: 401-404Crossref PubMed Scopus (7663) Google Scholar) further reflects the distinct profile of our cohort (Figure 1E). The EGFR and RBM10, as well as two cell-cycle-related genes (CDC27 and RB1) have much higher mutation frequency in our cohort, whereas somatic mutations in TP53, KRAS, and KEAP1 were more prevalent in the other three studies (Figure 1F). Even comparing non-smokers in the TW and TCGA LUAD cohorts, several genes had significantly different mutation frequencies (Table S1J). For example, top-ranking genes EGFR, RBM10, and RNF213 have significantly higher frequencies (3.7- to 5.9-fold) in TW cohort, while KRAS mutation occurs more frequently (4.5-fold) in TCGA cohort. Somatic mutations on ATP2B3 and TET2 also occur more frequently in TW cohort. The results indicate differences of cancer genomes for the never-smokers between TW and TCGA LUAD. RNA-seq, proteomics, and phosphoproteomics data were integrated to devise a multi-omics taxonomy. Principal-component analysis (PCA) using row-mean scaled data (log2-transformed) showed a clear separation of the tumor and normal tissues at both the RNA and protein levels, as well as distinct clusters of the reference samples, confirming the absence of batch effects and revealing the higher variation of tumor compared to NAT (Figure 2A). The RNA-to-protein correlation using log2T/N (tumor/normal) values was moderate to low with sample-wise and gene-wise median Spearman correlations of 0.31 and 0.14, respectively (Figures 2B and 2C; Table S2A). Only 22% proteins displayed significant positive correlations with the cognate RNA (Spearman, Benj. Hoch. false discovery rate [FDR] < 0.05; Figure 2C). Enrichment analysis showed a pathway-dependent RNA-to-protein correlation, with basic cellular functions poorly corresponding to RNA (Figure 2D; Table S2B). Additionally, pathway enrichment analysis using the protein median log2T/N values across patients revealed the overall regulation trends (Figure 2E; Table S2C). Taken together, these analyses indicate transcriptionally modulated upregulation of DNA replication, glycolysis, glutathione metabolism, and immune-related pathways, while upregulation of DNA repair, protein processing and transport pathways, and downregulation of cell-adhesion-related pathways were more apparent at protein level. Focusing on the NSCLC pathway, most proteins and their phosphorylation sites were differentially regulated. Though protein expression of EGFR, ERBB2, Ras, and PKC were downregulated, many of their downstream signaling protein nodes such as JAK3, STATs, PI3K, AKT, MEK, EML4, PLCG2, and STK4 were consistently upregulated, likely mediated by phosphorylation of these kinases and known oncogenes (Figure 2F; Table S2D). The phosphorylation sites on the Raf/MEK/ERK axis displayed high inter-patient variation based on the standard deviation of the regressed phosphorylation values across patients, indicating patient-specific regulation of the MAPK pathway (Figure 2F; Table S2E). To elucidate the molecular dynamics of tumor progression, we classified patients into three groups; IA, IB, and ≥II stages; and performed differential expression analysis at both protein and RNA levels using ANOVA. Differentially expressed proteins and RNAs (p < 0.05) were further divided into two clusters by k-means clustering, and enrichment analysis of biological terms and Gene Ontology biological process (GO-BP) was performed for the clusters with progressive up- or downregulation across stages (Figures 2G and 2H). Several key processes and terms such as DNA replication, canonical glycolysis, proteasome, antibacterial humoral response, glycosyltransferase, and actin filament organization were common between the two molecular levels (Figures 2I and 2J). Proteins that function in cell-to-cell communication, signaling, and plasma membrane such as integrins, G-protein coupled receptors, ion channels, adaptive immunity, and antigen presentation presented an overall negative regulation trend during progression (Figure 2I). In contrast, proteins in glycolysis, DNA replication, stress response, and protein processing, turnover, and trafficking processes were upregulated in the later stages. The upregulation of DNA replication and repair processes, as well as the loss of cilium assembly genes, were most prominent at the RNA level (Figure 2J). Lung cancer is a very heterogeneous disease at a cellular and histological level. Thus, it is noted that tumor heterogeneity may partially contribute to these differences. Nevertheless, these results highlight the importance of multi-omics integration to identify dysregulation of molecular homeostasis during tumor progression. In summary, our results reveal a demographically distinct genomic landscape with different driver alteration frequencies. Its proteogenomic characterization shows that cellular transformation toward a more advanced cancer stage is characterized by an overall RNA-to-protein activation of replication with a parallel negative regulation of the proteome components involved in plasma membrane signaling and communication. Furthermore, the identified proteomic and RNA signatures represent the hallmarks of biological process remodeling that occurs during tumor progression. Next, we delineated the direct and indirect consequences of genomic aberrations in our cohort at the transcriptome and proteome levels. Using customized protein databases incorporating somatic mutations of individual patients, 337 mutated peptides corresponding to 319 proteins were identified (q-value < 0.01, FDR < 1%). Among these, variant isoforms of 15 cancer driver genes were identified, such as TP53BP1 D358E, RNF213 E1272Q, and D1331G, and KRAS G12C mutations in the top-ranking genes (Figure S2; Table S2F). Truncating mutations in RBM10 showed a systematic negative effect on both RNA and protein levels, whereas missense mutations in KRAS, LABM1, and PIK3CA were associated with increased protein expression only, possibly through increased stability (centered log2T/N values, t test p < 0.003; Figure 3A; Tables S3A and S3B). Elevated phosphorylation of EGFR S1064 and Y1197 has been reported in response to EGF in lung cancer cells (Zhang et al., 2015Zhang X. Belkina N. Jacob H.K. Maity T. Biswas R. Venugopalan A. Shaw P.G. Kim M.S. Chaerkady R. Pandey A. et al.Identifying novel targets of oncogenic EGF receptor signaling in lung cancer through global phosphoproteomics.Proteomics. 2015; 15: 340-355Crossref PubMed Scopus (34) Google Scholar). Although the impact of mutations in EGFR protein abundance was not conclusive, EGFR activating mutations (L858R and Del19) correlated with increased phosphorylation of S1064 and Y1197 (Figure 3B) (Tam et al., 2009Tam I.Y. Leung E.L. Tin V.P. Chua D.T. Sihoe A.D. Cheng L.C. Chung L.P. Wong M.P. Double EGFR mutants containing rare EGFR mutant types show reduced in vitro response to gefitinib compared with common activating missense mutations.Mol. Cancer Ther. 2009; 8: 2142-2151Crossref PubMed Scopus (53) Google Scholar), reflecting the activation of mutated EGFR in the patients. We also performed phospho-correlation analysis using the phosphorylation log2T/N values normalized to the corresponding protein log2T/N by linear regression and filtered by Spearman’s p values. Downstream activation of the MAPK signaling can be evidenced by the positive correlation of EGFR-pY1197 with MAP2K2-pT394 (Koch et al., 2016Koch H. Wilhelm M. Ruprecht B. Beck S. Frejno M. Klaeger S. Kuster B. Phosphoproteome Profiling Reveals Molecular Mechanisms of Growth-Factor-Mediated Kinase Inhibitor Resistance in EGFR-Overexpressing Cancer Cells.J. Proteome Res. 2016; 15: 4490-4504Crossref PubMed Scopus (12) Google Scholar), which further correlates with its substrate MAPK3-pT198/pT202 (Figure 3C), in turn with pMAPK1 and other downstream phosphoproteins (RSK2, cPLA2, and STMN1, Figure S3A). Using their median relative abundance as a signature of MAPK pathway activity, patients were ranked from high to low MAPK signaling (Figure 3D). This indicated that the MAPK signaling pathway is commonly activated among both EGFR-WT (wild-type) and mutated patients with different degrees of activation. Patients without EGFR activating mutations frequently coincided with low MAPK signaling. Three of four EGFR-WT cases with higher MAPK activity harbored KRAS mutations (Figure 3D). It is noted that low MAPK signaling was observed for most tumors with EGFR mutations that also harbor TP53 mutations (Figure 3D). Variation of MAPK pathway activity was observed within never-smokers with different EGFR activating mutations and is also influenced by TP53 mutations (Figure S3B). Anti-correlation between TP53 mutation and MAPK pathway activity has been observed in the TCGA cohort (Cancer Genome Atlas Research, 2014Cancer Genome Atlas Research NetworkComprehensive molecular profiling of lung adenocarcinoma.Nature. 2014; 511: 543-550Crossref PubMed Scopus (3022) Google Scholar). Additionally, late stage tumors with lymph node metastasis showed lower MAPK activity (Figure 3D). Further studies are required to determine whether this dynamic MAPK pathway profile is associated with different clinical outcomes of these patients with EGFR activating mutation.Figure 3Impact of Mutations on the Proteome and Phosphoproteome of LUADShow full caption(A) Heatmaps showing the direct effect of mutations on their encoded RNA and protein expression levels (centered log2T/N).(B) Boxplots illustrating the effect of EGFR activating mutations on EGFR phosphorylation (t-test, p < 0.05).(C) Scatterplots of co-phosphorylation within the EGFR-MEK-ERK axis (Spearman’s rank, p < 0.05).(D) Ranked co-phosphorylation signature of the MAPK cascade aligned with clinical features.(E) Two-dimensinal plot representing eQTLs and pQTLs with variants (x axis) and associated genes (y axis). The size of the points is increasing with the confidence of the association.(F) Heatmap of the relative abundance of cell-cycle-related proteins (top panel) and KIT protein (bottom panel) that were significantly associated with TP53 mutations.(G) Scatterplot of the MAPK pathway score and KIT relative abundance across patients (Spearman’s rank, p = 0.00078).(H) Heatmap of phosphosites related to DNA condensation, recombination, and DNA damage response proteins positively associated with TP53 mutations (t-test, p < 0.05).(I) Summary of key TP53 mutation associations.See also Figure S3.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure S3Impact of Genomic Alterations in the Proteome and Phosphoproteome of Lung Adenocarcinoma, Related to Figure 3Show full caption(A) Correlation between phospho-MAPK3 and its downstream phosphoproteins. (B) Ranked co-phosphorylation signature of the MAPK cascade of nonsmokers with different EGFR mutation status. (C) Manhattan plots of the most confident non-redundant association tests in eQTL and pQTL analysis. (D) Heatmap of cell cycle related genes associated with TP53 mutations at the RNA level. (E) Drug response of lung cancer cell lines with TP53 mutation from TCGA and COSMIC hotspot (Wilcoxon rank-sum test, p = 0.021).View Large Image Figure ViewerDownload Hi-res image Download (PPT) (A) Heatmaps showing the direct effect of mutations on their encod" @default.
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• W3041219630 date "2020-07-01" @default.
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• W3041219630 title "Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression" @default.
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