Somatic mutations affect key pathways in lung adenocarcinoma

Authors

Ding L

Getz G

Wheeler DA

Mardis ER

McLellan MD

Cibulskis K

Sougnez C

Greulich H

Muzny DM

Morgan MB

Fulton L

Fulton RS

Zhang Q

Wendl MC

Lawrence MS

Larson DE

Chen K

Dooling DJ

Sabo A

Hawes AC

Shen H

Jhangiani SN

Lewis LR

Hall O

Zhu Y

Mathew T

Ren Y

Yao J

Scherer SE

Clerc K

Metcalf GA

Ng B

Milosavljevic A

Gonzalez-Garay ML

Osborne JR

Meyer R

Shi X

Tang Y

Koboldt DC

Lin L

Abbott R

Miner TL

Pohl C

Fewell G

Haipek C

Schmidt H

Dunford-Shore BH

Kraja A

Crosby SD

Sawyer CS

Vickery T

Sander S

Robinson J

Winckler W

Baldwin J

Chirieac LR

Dutt A

Fennell T

Hanna M

Johnson BE

Onofrio RC

Thomas RK

Tonon G

Weir BA

Zhao X

Ziaugra L

Zody MC

Giordano T

Orringer MB

Roth JA

Spitz MR

Wistuba II

Ozenberger B

Good PJ

Chang AC

Beer DG

Watson MA

Ladanyi M

Broderick S

Yoshizawa A

Travis WD

Pao W

Province MA

Weinstock GM

Varmus HE

Gabriel SB

Lander ES

Gibbs RA

Meyerson M

Wilson RK

Doi

10.1038/nature07423

PMID: 18948947 · DOI: 10.1038/nature07423 · Journal: Nature (2008)

TL;DR

The Tumour Sequencing Project (TSP) sequenced 623 candidate cancer genes across 188 primary lung adenocarcinomas, identifying 1,013 non-synonymous somatic mutations and 26 significantly mutated genes. Beyond the five genes previously known to be frequently mutated in LUAD (TP53, KRAS, STK11, EGFR, CDKN2A), the study discovered recurrent mutations in tumour suppressors NF1, ATM, RB1, and APC, and in tyrosine kinases ERBB4, EPHA3, KDR, and NTRK family members. Integrated analysis with SNP arrays and expression arrays revealed convergence on MAPK, p53, Wnt, cell cycle, and mTOR signalling pathways.

Cohort & data

  • 188 primary LUAD tumours (minimum 70% tumour content), with matched normals.
  • Dataset: luad_tsp (dbGaP phs000144.v1.p1; GEO GSE12667 for expression).
  • Targeted DNA sequencing of 623 candidate cancer genes (all coding exons and splice sites); 247 Mb of tumour DNA analysed.
  • SNP array (Affymetrix 250K StyI) on 383 tumours for copy number; gene expression (Affymetrix U133Plus2) on 75 tumours.
  • Samples contributed by Dana-Farber, MD Anderson, Memorial Sloan-Kettering, University of Michigan, and Washington University.

Key findings

  • 1,013 non-synonymous somatic mutations identified in 163 of 188 tumours: 915 point mutations, 12 dinucleotide mutations, 29 insertions, 57 deletions.
  • 26 genes identified as significantly mutated; 17 were significant by at least two independent statistical methods.
  • EGFR and KRAS mutations are mutually exclusive (P < 1e-7); no sample harboured mutations in both.
  • EGFR mutations negatively correlate with STK11 mutations (P = 7e-6).
  • ATM and TP53 mutations show strong mutual exclusivity (P = 9.5e-5), suggesting either suffices for loss of cell-cycle checkpoint control.
  • PRKDC mutations associate with hypermutation: tumours with PRKDC mutations average 24.3 mutations vs 4.7 without (P = 3.52e-59).
  • Smokers have significantly more mutations than never-smokers (P = 0.021); EGFR correlates with never-smoker status (P = 0.0046), KRAS with smoker status (P = 0.021).
  • 132 of 188 tumours (70%) have at least one mutation in the MAPK pathway.
  • mTOR pathway components mutated in 17 genes and >30% of tumours (excluding KRAS-mutant tumours).
  • TP53 mutation frequency increases with tumour grade (13%, 24%, 52% for grades 1, 2, 3; P = 7.8e-6).

Genes & alterations

  • TP53 — 66 mutations; frequency increases with grade; copy number loss and reduced expression in mutant tumours.
  • KRAS — frequent mutations correlating with smoking; copy number gain and increased expression in mutant tumours.
  • EGFR — mutations in never-smokers; associated with lower overall mutation rate, copy number gain, and higher expression.
  • STK11 — >30 mutations; LOH in 17 tumours; correlates with smoker status (P = 0.044).
  • NF1 — 16 mutations in 13 patients (4 nonsense, 5 splice-site, 1 frameshift); homozygous deletion in one tumour; newly implicated in LUAD.
  • ATM — 14 mutations in 13 tumours (1 nonsense, 1 splice-site, 2 frameshift); first demonstration of significant ATM mutation frequency in LUAD.
  • RB1 — 7 mutations; 5 co-occur with TP53, 2 with ATM mutations.
  • APC — 13 mutations in 11 tumours; first report in lung adenocarcinoma (previously known only in squamous and small-cell).
  • ERBB4 — 9 mutations; 2 in kinase domain, 5 in receptor ligand binding domain.
  • EPHA3 — 11 mutations; first statistically significant demonstration in LUAD; K761N in kinase domain at conserved “molecular brake” position.
  • KDR — significantly mutated; 4 kinase domain mutations; rare amplifications suggesting proto-oncogene role.
  • NTRK1/NTRK2/NTRK3 — 20 mutations total; 7 in kinase domains.
  • CDKN2A — 9 mutations plus frequent focal deletions.
  • LRP1B — 17 mutations; positive correlation with solid subtype (P = 2.29e-5) and higher tumour grade (P = 0.013).
  • PTPRD — frequently mutated and previously shown deleted; co-mutates with PIK3C3.
  • PTEN — mutations correlated with copy number loss; associated with lower mutation rates.
  • FGFR4 — 3 kinase domain mutations; co-occurrence with NTRK2 and PDGFRA mutations.
  • NRAS — rare amplification observed.
  • ERBB2 — 4 mutations plus amplification.
  • MDM2 — amplification in p53 pathway context.

Clinical implications

  • Mutual exclusivity of EGFR and KRAS mutations supports independent treatment stratification for tyrosine kinase inhibitors (gefitinib, erlotinib) vs other approaches.
  • NF1 mutations suggest MEK inhibitor sensitivity in a subset of LUAD patients.
  • KDR mutations suggest potential benefit from VEGFR inhibitors such as sorafenib or sunitinib.
  • mTOR pathway mutations in >30% of tumours support testing rapamycin analogues in LUAD.
  • PRKDC mutations as a marker of hypermutation phenotype, potentially relevant to immunotherapy response (not tested in this study).
  • Smoking-associated mutation burden differences suggest distinct biology for never-smoker LUAD.

Limitations & open questions

  • Only 623 genes sequenced (not whole-exome or whole-genome); additional driver genes likely missed.
  • Cohort size (n=188) insufficient to fully power detection of lower-frequency drivers (e.g., AKT1, BRAF, PTEN fell below significance).
  • No functional validation of newly discovered mutations; oncogenic vs passenger status requires experimental confirmation.
  • Expression data available for only 75 of 188 tumours, limiting integrative analyses.
  • Stromal contamination may have reduced mutation detection sensitivity in 16 of 25 tumours with no discovered mutations.
  • Study predates next-generation sequencing; Sanger-based approach has lower sensitivity for subclonal mutations.
  • No metastatic or treated samples; applicability to drug resistance contexts unknown.

Citations from this paper used in the wiki

  • “We have identified 1,013 non-synonymous somatic mutations in 163 of the 188 tumours” (Abstract/Results).
  • “We identified a total of 26 significantly mutated genes, among them 17 genes are designated as significant by at least two approaches” (Results).
  • “132 of the 188 tumours sequenced have at least one mutation in the MAPK pathway” (Pathway analysis section).
  • “The average of 24.3 mutations in tumours having PRKDC mutations is significantly higher than the average of 4.7 mutations in tumours without PRKDC mutations (P = 3.52 x 10-59)” (Results).
  • “mTOR pathway components are mutated in 17 genes and in more than 30% of tumours sequenced” (Results).
  • “EGFR mutations correlate with the status of patients who have never smoked (P=0.0046), whereas KRAS mutations correlate with smoker status (P=0.021)” (Clinical features section).

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