1. Lung Cancer Project update Schumacher - Kaiser November 17, 2006

2. DB sample annotations Univariate and multivariate analyses (definition of classes conditions biological interpretation) Preliminary biomedical assessment of transcriptional signatures Dataset integration Project timeline and milestones Ph.D. student – update Next steps... Agenda

3. Novachip platform Biopsies with at least 10% of tumor cells (score>0) Definite diagnoses Squamous cell carcinomas, adenocarcinomas, controls Orthogonal Partial Least Squares Discriminant Analysis Two classes question  OPLS-DA  ranked features Top 500 features  analyses ¬ Pubmed and other NCBI db and tools, Ingenuity Pathway Analysis, Metacore, Medgene, Pathologene, OntoExpress,... Transcriptional assessment of lung biopsies - approach

4. NSCLC: some markers for diagnosis of primary lung adenocarcinomas from Ueno et al (2003) BJC 88:1229  

5. NSCLC: adenocarcinoma – transcriptional signatures  tumor features (1.2) increased levels of pulmonary adenocarcinoma markers (e.g. SFTPA2, SFPTB, SFTPC, SFTPD, NASPA, TTF1) increased cell migration (tumor cells?, endothelial cells,leukocytes??) tumor cell spreading (increased AREG, CLDN4, FN1, HPN, MET, MMP9, PLAU, THBS1, VCAM1) no significant change of APC and other leukocytes‘ markers chemoattraction of mononuclear leukocytes (CCL2, CCL20, CXCL13) – respiratory burst of monocytes? (increased CCL2, FN1, ICAM1, TREM1, VCAM1) increased cell invasiveness – cell extravasation signaling? increased cell attachment (e.g. macrophages: increased FN1, ICAM, VCAM1; tumor cells: increased IGF2, PLAU, THBS1) increased angiogenesis (increased ADAMTS1, FN1, SERPINE1, SPARC, THBS1) increased reactive stroma - myofibroblasts (e.g. SPARC, other) increased tumor growth (increased CCL2, CRABP2, FN1, IGF2, IL6, MET, MMP9, OLR1, PLAU, SPP1, THBS1) increased ECM remodelling – „wound healing“ (increased MMP1, MMP9, MMP11, MMP12, MMP13) decreased redox stress? (decreased GSTA1, GSTA2, GSTM1 - low proliferation? cell cycle?) increased neuritogenesis (increased ABL2, GEM, NFGB, PLAU)

6. NSCLC: adenocarcinoma – transcriptional signatures  tumor features (2.2) tumor progression mechanisms (CTAs (MAGEs, GAGEs), TP63, TP53?) other oncogenes, tumor suppresors relevant markers (MYC, SRC, HER/NEU, HRAS, KRAS2, CCND1; CTNNB1, VEGFC, ERBB1-3) evidence of epigenetics? (HATs, HDACs, DNMTs,...) markers of poor prognosis (e.g. SPARC, more to come...) xenobiotic metabolism (e.g. decreased AKR1C1, GSTs, CYP4B1,...) serum markers? (e.g. IL6, SPP1) relevant molecular pathways: e.g. inflammation-related stem cell –like markers, transient amplifying compartments (KIT, POU5F1, SOXs, SCF, CD33, ABCG2)

7. NSCLC: distinguishing pulmonary small cell carcinoma from poorly differentiated squamous cell carcinoma from Zhang et al (2005) Modern Pathology 18:111 Small cell carcinomaPoorly differentiated squamous carcinoma TTF1 TP63 KRTCDKN2A KRT    (?) 

8. NSCLC: poorly differentiated adenocarcinoma from Zhang et al (2005) Modern Pathology 18:111 TTF1TP63 KRTCDKN2A SFTPBmucins      (?)

9. NSCLC: squamous cell carcinoma – transcriptional signatures  tumor features (1.2) increased levels of epidermal markers (development and differentiation) - relate to carcinogenesis theories: e.g. „wound that never heals“ inflammation, leukocytic infiltration (poor), reactive stroma? increased cell division, proliferation and survival increased invasiveness, ECM remodelling tumor progression mechanisms (MAGE, TP63, TP53?) no major evidence of epigenetics? (HATs, HDACs, DNMTs,...) other oncogenes, tumor suppresors markers of poor prognosis (e.g. MAGEs. GAGE1, SPP1) mechanisms of tumor defense (?) xenobiotic metabolism in smokers, drug treatment, solute transport, CYPs, serum markers? (e.g. IL1A, IL6, SPP1, defensins) relevant molecular pathways (e.g. SHH, polyamines, Ca 2+ signaling) other cancers, transient amplifying compartments, differentiation...

10. from Proksch et al (2006) J Dermatol Sci 43(3):159 NSCLC: squamous cell carcinoma – transcriptional signatures  tumor features (2.2)

11. MAGEs, TP53, epigenetics, TP63

12. Discussion...

13. Datasets integration

14. Proposed project timeline and milestones

15. Next steps...