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Are we making any progress in the molecular taxonomy of CRC? Marcello Maugeri-Saccà, MD, PhD Istituto Nazionale Tumori “Regina Elena”

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Presentation on theme: "Are we making any progress in the molecular taxonomy of CRC? Marcello Maugeri-Saccà, MD, PhD Istituto Nazionale Tumori “Regina Elena”"— Presentation transcript:

1 Are we making any progress in the molecular taxonomy of CRC? Marcello Maugeri-Saccà, MD, PhD Istituto Nazionale Tumori “Regina Elena”

2 Various ways of classifying CRC: first-generation classifier

3 Second-generation classifier: genome instability-based classification Simons et al., Ann Oncol 2013 Defective MMR due to MLH1methylation or germline mutations in MMR genes Transcriptional silencing of tumor suppressor and DNA repair genes (MLH1, BRAF-mut.) Chromosomal gains and losses and structural rearrangements: LOH at APC, TP53, SMAD4, etc chromosomal instable microsatellite instable CpG island methylator phenotype

4 Third generation classifiers: Gene expression profiling-based classification A B C: mixed classification

5 Cell of origin-based classification: salient characteristics of the six CRC subtypes and correlation with colon-crypt location and Wnt signaling Sadanandam et al., Nat Med 2013 two published gene expression data sets (core data sets, n = 445)

6 Cell of origin-based classification: Sadanandam et al., Nat Med 2013 transit-amplifying subtype was a heterogeneous collection of samples with variable expression of stem cell and Wnt-target genes.

7 CRC subtypes and treatment response Khambata-Ford dataset (n:110, cetux monotherapy)

8 Prognosis-derived classification De Sousa E Melo, Nat Med 2013 AMC-AJCCII-90 dataset, stage II

9 The prognosis-based classifiers are represented in cell lines and xenografts

10 TMA-based miniclassifier using IHC for four gene products (FRMD6, ZEB1, HTR2B and CDX2) selected on the basis of validated reliable staining and high differential expression between CCS1 and CCS3 in multiple data sets CCS1 (CIN 18q loss, 20q gain ) CCS2 (MSI/CIMP+/Braf-mut CCS3 (heterogenous) Prognosis-derived classification: subtype-specific molecular alterations and reproducibility in the clinical setting

11 Different published prognostic signatures show very limited overlap

12 Gene sets specific for serrated- or FAP-associated adenomas (APC germline mutation/tumor development via the CIN pathway)showed association with CCS3 or CCS1-CIN tumors

13 Third generation classifiers: Gene expression profiling-based classification - cell of origin+ genomic instability + prognosis - Marisa L, Plos Med patients with stage II–III

14 Summary of the main characteristics of the six subtypes. Marisa L, Plos Med 2013

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17 filtering biologically relevant mutations 1)MutSig: Frequency 2) Paradigm Shift: Data integration (mutations, gene expression profile, etc) 3) MEMo: Mutual exclusivity module analysis

18 1)MutSig: Frequency (False positive) threshold is chosen to control for the False Discovery Rate (FDR), and genes exceeding this threshold are reported as significantly mutated.

19 Paradigm Shift: Data integration NFE2L2 /KEAP1 pathway

20 MEMo: Mutual exclusivity module analysis

21 The Cancer Genome Atlas (TCGA)

22 Diversity and frequency of genetic changes leading to deregulation of signalling pathways in CRC

23 Module 1 Module 2 Module 3 Module 4 Druggable vs Undruggable

24 The origin of cancer heterogeneity Maugeri-Saccà M. Targeted Therapies in Oncology (in press)

25 Biomarker frequencies of discordance between primary tumours and metastases Bedard et al., Nature 2013

26 Variable Clonal Repopulation Dynamics in CRC Kreso et al., Science 2013 The progeny of single CRC cells was followed by carrying out clonal tracking experiments through lentiviral integration site mapping by Southern blotting Persistent clones Short-term clones Transient clones Resting clones Fluctuating Clones - nongenetic mechanisms of heterogeneity - Oxa treatment altered repopulation dynamics Clonal behavior (proliferative potential and tumor re-generation potency is classified across multiple recipients

27 Take-home message - Novel prognostic classifiers need validation and head-to- head comparisons - Think beyond superstar pathways: back to the lab to set up novel strategies for targeting the untargetable -Investigations of tumor heterogeneity in the clinical setting (e.g. single cell analisys)

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29 Prognosis-based classification and therapy efficacy

30 Poor-prognosis CRC develops from serrated precursor lesions

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32 Common Cancer Stem Cell Gene Variants Predict Colon Cancer Recurrence Gerger et al., CCR 2011

33 Circulating Cancer Stem-Like Cells and Prognosis in Patients With Dukes’ Stage B and C Colorectal Cancer (Training Set) Iinuma et al., JCO 2011

34 Circulating Cancer Stem-Like Cells and Prognosis in Patients With Dukes’ Stage B and C Colorectal Cancer (Validation Set)

35 CD133 expression and the prognosis of colorectal cancer Flowchart of selection of studies for inclusion in meta-analysis CD133 expression and 5-year OS rate CD133 expression and 5-year DFS rate Chen et al., Plos One 2013

36 CSCs and chemoresistance Maugeri-Saccà M.et al. Clin Cancer Res 2011 A-B-C: CSC-intrinsic mechanisms D: CSC-extrinsic mechanisms

37 Drugging the undruggable Chan et al., Nature Reviews Drug Discovery 2011

38 The principle of high-throughput loss-of-function genetic screens for biomarker- driven clinical trials Maugeri-Saccà M., et al. Current Pharmaceutical Design. In press

39 Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR Prahallad et al., Nature 2012

40 CRC subtypes and treatment response

41 Variable Clonal Repopulation Dynamics Influence Chemotherapy Response proportion of clone types generated by reinjecting Ctrl and OX-treated tumors Post-chemo enriched population


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