Supplementary Materials

Supplementary Material for:

A Genomics-Based Classification of Human Lung Tumors

The Clinical Lung Cancer Genome Project (CLCGP) and Network Genomic Medicine (NGM)*

*Corresponding authors. E-mail: roman.thomas@uni-koeln.de (R.T.); reinhard.buettner@uk-koeln.de (R.B.); juergen.wolf@uk-koeln.de (J.W.)

Published 30 October 2013, Sci. Transl. Med. 5, 209ra153 (2013)
DOI: 10.1126/scitranslmed.3006802

This PDF file includes:

  • Materials and Methods
  • Fig. S1. Overview of sample processing.
  • Fig. S2. Significantly amplified and deleted regions in lung cancer.
  • Fig. S3. 9p21 is the most frequently deleted region in lung cancer.
  • Fig. S4. Mutation frequencies by histological subtype.
  • Fig. S5. Distribution of mutations within genes.
  • Fig. S6. FGFR alterations in lung tumors.
  • Fig. S7. Frequencies of alterations in genes with known or potential clinical relevance in lung cancer.
  • Fig. S8. Genetic associations in lung cancer.
  • Fig. S9. EGFR mutations and amplifications frequently co-occur in lung AD but not in SQ.
  • Fig. S10. Homozygous and hemizygous deletions of PTEN in EGFR-mutant ADs.
  • Fig. S11. Central pathological review.
  • Fig. S12. Gene expression subtypes of AD according to Wilkerson.
  • Fig. S13. Gene expression subtypes of SQ according to Wilkerson.
  • Fig. S14. Genome-wide comparison of LCNEC and SCLC.
  • Fig. S15. Semisupervised reclassification of lung cancer specimens.
  • Fig. S16. Automated reclassification of AD, SCLC, and SQ.
  • Fig. S17. Prospective testing of genomics-based diagnosis of lung cancer.
  • Fig. S18. BRAF mutations in lung cancer.
  • Fig. S19. Overall survival by stage.
  • Fig. S20. Diagnostic algorithm for lung tumors.
  • Legends for tables S1 to S13
  • References (5562)

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Other Supplementary Material for this manuscript includes the following:

  • Table S1 (Microsoft Excel format). Clinical and genetic features of all CLCGP cases.
  • Table S2 (Microsoft Excel format). Significant copy number alterations in lung cancer for each histological subtype.
  • Table S3 (Microsoft Excel format). Median copy number per patient for chromosome regions with significantly altered copy number.
  • Table S4 (Microsoft Excel format). Annotation of genetic alterations in lung cancer patients.
  • Table S5 (Microsoft Excel format). Statistical results comparing alteration frequencies between histological subtypes.
  • Table S6 (Microsoft Excel format). Gene expression data used for hierarchical clustering.
  • Table S7 (Microsoft Excel format). Reclassification of LCs.
  • Table S8 (Microsoft Excel format). Mutations detected in 15 whole exome–sequenced LCNECs of the lung.
  • Table S9 (Microsoft Excel format). RNAseq-derived gene expression data for 10 LCNECs of the lung.
  • Table S10 (Microsoft Excel format). Results of the unsupervised genetics-based classification of lung tumors.
  • Table S11 (Microsoft Excel format). Automated supervised prediction of lung cancer subtypes based on genetic alterations.
  • Table S12 (Microsoft Excel format). Clinical and genetic features of all NGM cases.
  • Table S13 (Microsoft Excel format). Primer sequences.

[Tables S1 to S13]