Identification and clinical detection of genetic alterations of pre-neoplastic lesions Time for the PML ome? David Sidransky MD Johns Hopkins

Transcription

1 Identification and clinical detection of genetic alterations of pre-neoplastic lesions Time for the PML ome? David Sidransky MD Johns Hopkins February 3-5, 2016 Lansdowne Resort, Leesburg, VA

2 Molecular Progression of HNSCC In the old days,there was time to think Precursor lesion 1 9p-(p16) Dysplasia 17p-(p53) CIS 11q-,14q-,8p- Invasive Cancer 3p- Cyclin D1 + 4pq-,13q-

3 Notch 1 mutations are common in Dysplasia 50% of Chinese HNSCC tumors had Notch1 mutations compared to 15% in Caucasians 11% 23% 41.4% 40% 17.3% 17.3% Most mutations are inactivating in US and activating in China

4 Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM _04_ CEL.gz Tumour_GSM _06_ CEL.gz Tumour_GSM _M DA.HNS.053.CEL.gz Tumour_GSM _11_ CEL.gz Tumour_GSM _M DA.HNS.042.CEL.gz Tumour_GSM _M DA.HNS.055.CEL.gz Tumour_GSM _15_ CEL.gz Tumour_GSM _09_ _2nd.CEL.gz Tumour_GSM _14_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM _4_ CEL.gz Tumour_GSM _09_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM _05_ CEL.gz Tumour_GSM _04_ _re run.cel.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM _M DA.HNS.076.CEL.gz Tumour_GSM _M DA.HNS.061.CEL.gz Tumour_GSM _13_ CEL.gz Tumour_GSM _12_ CEL.gz Tumour_GSM _04_ CEL.gz Tumour_GSM _11_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM _06_ CEL.gz Tumour_GSM _05_ CEL.gz Tumour_GSM _01_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM _M DA.HNS.064.CEL.gz Tumour_GSM _M DA.HNS.071.CEL.gz Tumour_GSM CEL.gz Tumour_GSM _M DA.HNS.111.CEL.gz Tumour_GSM _M 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DA.HNS.115.CEL.gz Tumour_GSM CEL.gz Tumour_GSM _15_ CEL.gz Tumour_GSM _03_ CEL.gz Tumour_GSM _M DA.HNS.046.CEL.gz Tumour_GSM _05_ CEL.gz Tumour_GSM _06_ CEL.gz Tumour_GSM _07_ CEL.gz Tumour_GSM _M DA.HNS.090.CEL.gz Tumour_GSM _07_ CEL.gz Tumour_GSM _09_ _2nd.CEL.gz Tumour_GSM _M DA.HNS.084.CEL.gz Tumour_GSM _M DA.HNS.098.CEL.gz Tumour_GSM _07_ CEL.gz Tumour_GSM _06_ CEL.gz Tumour_GSM _M DA.HNS.041.CEL.gz Tumour_GSM _10_ CEL.gz Tumour_GSM _07_ CEL.gz Tumour_GSM _14_ CEL.gz Tumour_GSM _03_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM _02_ CEL.gz Tumour_GSM _M DA.HNS.114.CEL.gz Tumour_GSM _M DA.HNS.029.CEL.gz Tumour_GSM _15_ CEL.gz Tumour_GSM _08_ CEL.gz Tumour_GSM _08_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM _10_ CEL.gz Tumour_GSM _M DA.HNS.062.CEL.gz Tumour_GSM _M DA.HNS.044.CEL.gz Tumour_GSM _01_ CEL.gz Tumour_GSM _04_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM _03_ CEL.gz Tumour_GSM _06_ CEL.gz Tumour_GSM _M DA.HNS.035.CEL.gz Tumour_GSM _2_ CEL.gz Tumour_GSM _M DA.HNS.043.CEL.gz Tumour_GSM _M DA.HNS.103.CEL.gz Tumour_GSM CEL.gz Tumour_GSM _13_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM _M DA.HNS.088.CEL.gz Tumour_GSM _M DA.HNS.107.CEL.gz Tumour_GSM _M DA.HNS.036.CEL.gz Tumour_GSM _M DA.HNS.024.CEL.gz Tumour_GSM _M DA.HNS.057.CEL.gz Tumour_GSM _M DA.HNS.032.CEL.gz Tumour_GSM _M DA.HNS.037.CEL.gz Tumour_GSM _M DA.HNS.105.CEL.gz Tumour_GSM _5_ CEL.gz Tumour_GSM _01_ CEL.gz Tumour_GSM _01_ CEL.gz Tumour_GSM _M DA.HNS.030.CEL.gz Tumour_GSM _3_ CEL.gz Tumour_GSM _03_ CEL.gz Tumour_GSM _05_ CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM _M DA.HNS.081.CEL.gz Tumour_GSM _10_ CEL.gz Tumour_GSM _10_ CEL.gz Tumour_GSM _02_ CEL.gz Tumour_GSM _05_ CEL.gz Tumour_GSM _4_ CEL.gz Tumour_GSM _03_ CEL.gz Tumour_GSM _04_ CEL.gz Tumour_GSM _05_ CEL.gz Tumour_GSM _08_ CEL.gz Tumour_GSM _01_ _2.CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz Tumour_GSM CEL.gz GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM GSM Analysis of the intracellular signaling pathway activation (SPA) based on the transcriptomic data Color Key Value MAPK_Family_Pathway Glucocorticoid_Receptor_Pathway Chemokine_Pathway TGF_beta_Pathway GPCR_Pathway RAS_Pathway Wnt_Pathway STAT3_Pathway IL_6_Pathway JNK_Pathway PAK_Pathway JAK_mStat_Pathway Interferon_Pathway HIF1Alpha_Pathway BRCA1_Pathway TRAF_p_Pathway FLT3_Signaling_Pathway TNF_p_Pathway Transcription_of_mRNA_Pathway ErbB_Family_Pathway EGFR1_Pathway PPAR_Pathway IL_2_Pathway HGF_Pathway TNF_m_Pathway AHR_Pathway Hedgehog_Pathway Nucleotide_excision_repair_ef fect TRAF_m_Pathway Chromatin_Pathway NGF_m_Pathway Circadian_Pathway Cytokine_Network_Pathway Notch_Pathway Hypoxia_induced_EMT_in_cancer_and_fibrosis_3 ATM_Pathway p53_signaling_m_pathway IL_10_Pathway Mismatch_Repair_Pathway CD40_Pathway RANK_Signaling_in_Osteoclast_ Pathway VEGF_Pathway IGF1R_Signaling_Pathway Erythropoeitin_Pathway IP3_Pathway Ubiquitin_Proteasome_Pathway mtor_pathway Estrogen_Pathway Cellular_Anti_Apoptosis_ Pathway CREB_Pathway GSK3_Pathway Androgen_receptor_Pathway camp_pathway SMAD_m_Pathway PTEN_Pathway Mitochondrial_Apopotosis_m_Pathway Caspase_Cascade MAPK_Signaling_Pathway ILK_Pathway Integrin_Signaling_Pathway AKT_Pathway p38_m_signaling_pathway ERK_Signaling_Pathway ILK_Pathway Ubiquitin_Proteasome_Pathway BRCA1_Pathway Caspase_Cascade Mitochondrial_Apopotosis_m_Pathway Transcription_of_mRNA_Pathway Mismatch_Repair_Pathway p53_signaling_m_pathway PTEN_Pathway AHR_Pathway TNF_m_Pathway Chromatin_Pathway ATM_Pathway Interferon_Pathway Cytokine_Network_Pathway TNF_p_Pathway CD40_Pathway Nucleotide_excision_repair_ef fect Circadian_Pathway TRAF_m_Pathway NGF_m_Pathway Hedgehog_Pathway HIF1Alpha_Pathway JAK_mStat_Pathway Hypoxia_induced_EMT_in_cancer_and_f Notch_Pathway Wnt_Pathway TRAF_p_Pathway IL_2_Pathway IP3_Pathway HGF_Pathway ErbB_Family_Pathway FLT3_Signaling_Pathway IL_10_Pathway EGFR1_Pathway Erythropoeitin_Pathway VEGF_Pathway IGF1R_Signaling_Pathway RANK_Signaling_in_Osteoclast_ Pathway Glucocorticoid_Receptor_Pathway IL_6_Pathway STAT3_Pathway Chemokine_Pathway MAPK_Family_Pathway ERK_Signaling_Pathway TGF_beta_Pathway JNK_Pathway AKT_Pathway p38_m_signaling_pathway Integrin_Signaling_Pathway PAK_Pathway MAPK_Signaling_Pathway camp_pathway GSK3_Pathway Androgen_receptor_Pathway CREB_Pathway GPCR_Pathway RAS_Pathway SMAD_m_Pathway Cellular_Anti_Apoptosis_ Pathway PPAR_Pathway Estrogen_Pathway mtor_pathway OSCC (n=459) Leukoplakia (n=85) Alterations involved in early premalignant transition and progression seem to be predominantly loss of function vs established cancers

5 TSG Promoter Hypermethylation may be as/more important than mutation (frequency)

6 A. B. We performed targeted next generation sequencing on DNA isolated from multifocal AAHs and from different zones of histologic progression within AISs and MIAs Neoplasia AAH (6 patients) 3-5 AAH lesions Primary each tumor AIS (5 patients) Zone 1 Zone 3 Zone 2 MIA (5 patients) Zone 1 Zone 4 Zone 2 Zone 3 * Control Lymph Node * Patients had not been treated with chemotherapy or radiation before tumor biopsy Atypical Adenomatous Hyperplasia Normal lung AAH Adenocarcinoma In Situ Zone 1 Zone 2 Zone 3 Minimally Invasive Adenocarcinoma Zone 1 Zone 2 Zone 3 Zone 4 Invasive cancer

7 Wildly heterogeneous Landscape of Genetic Alterations in AAH Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Recurrent mutations in AAH lesions and matched primary adenocarcinoma Patient 1 AAH3 AAH4 Primary tumor EGFR - in frame del 2% 2% 9% KRAS p TP53 p.279g>e 3% 17% 20% Patient 1 Patient 3 AAH3 AAH4 Primary tumor AAH2 AAH3 AAH4 Primary tumor EGFR - in frame del 2% 2% 9% KRAS p.12g>c 6% 8% 8% 13% TP53 p.279g>e 3% 17% 20% * In all three cases we saw a consecutive increase in mutations fractional abundance from AAH to primary tumor, suggesting a spatial expansion of these clones as they progressed histologically.

8 Mutational landscape varies between the stages of tumor progression AAH AIS MIA NF1 TP53 TP53 KIT GNAS TP53 EGFR ABL1 EGFR PTEN CTNNB1 BRCA2 TSC2 EZH2 BRAF AKT1 RET MET PTPN11 ATM ROS1 GATA2 GATA1 AKT1 MYC FGFR3 HRAS MET IGF1R IGF1R CREBBP EGFR ARID1A ATRX FGFR4 IGF1R PDGFRA ERBB2 NOTCH1 ERBB2 ABL1 ARID1B NOTCH1 MED12 DNMT3A FGFR2 ERBB4 CCND1 APC ERBB4 ATM APC NOTCH3 CCND1 KRAS TSC2 RUNX1 KRAS ARID1A NOTCH4 ARID1B MAML1 MED12 ALK PTCH1 MLL GNAQ FLT3 TNFAIP3 FBXW7 IKZF1 ASXL1 HNF1A GNA11 PBRM1 TET2 IDH2 SF3B1 MSH6 ATRX ASXL1 BRAF FGFR2 MPL TET2 Genes mutated in 1AAH lesion Genes mutated in 2AAH lesions Genes mutated in 3AAH lesions in more than 1 patient Genes mutated in 4AAH lesions Genes mutated in 1 patient Genes mutated in 2 patients Genes mutated in 3 patients Genes mutated in 4 patients Genes mutated in 1 patient Genes mutated in 2 patients Genes mutated in 3 patients Genes mutated in 4 patients AAH has the most mutations in genes without annotated interactions (13 as compared with 6 in both AIS and MIA) suggestive of higher diversity in potentially affected molecular pathways in pre-neoplastic lesions.

9 Harbingers of malignant transition Significant increase in mutation fractional abundance of EGFR, TP53 and other cancer driving genes was seen in MIA patients, compared to AAH and AIS. Suggesting clonal expansion of these events. Intratumor heterogeneity and emergence of driver mutations 1. 81% (AIS) and 83% (MIA) of all somatic mutations were not detectable across every focus of a given lesion. Dead ends. 2. Mutations present in all zones within the same lesion were limited to a handful of well-known cancer-driving genes, such as EGFR, TP53, KRAS and ATRX.

10 Detection of mutant DNA from from lung milli lesions in plasma and sputum Even 0.1% of the mutant DNA can be detected in a wild-type background Of 13 mutations tested, 10 were detected in plasma and 7 were detected in the sputum samples * Low prevalence BRAF p.469g>a mutation that was identified by NGS in DNA extracted from AAH lesion, was detected by ddpcr in the associated body fluids. * This mutation was not detected in the matched primary invasive tumor using ddpcr. We detected mutated genes in plasma DNA of the 3MIA patient even though these mutations were identified by deep sequencing in only one of four zones selectively sampled from the primary tumor of this

11 Summary 1. Mutations landscape varies significantly between the AAH, AIS and MIA lesions. 2. There is no single predominant pattern of lung cancerogenesis. 3. KRAS mutations or simultaneous loss of TP53 activity and EGFR activation is a harbinger of malignant transition. 4. In some cases AAH and the associated cancer are clonally related but not in many cases 5. Clonal expansion is an early event of tumor progression. 6. There are many clonal dead ends not represented in TCGA 7. Utilizing an ultra-sensitive digital droplet PCR approach, genetic alterations in early glandular neoplasms (e.g. AAH) could be detected in paired circulating DNA.

12 Goal 1 To characterize specific mutational patterns and heterogeneity in preneoplasia (OSCC) Leukoplakia (30 patients) OSCC (30 patients) Longitudinal Gene collection expression analysis (15 patients) 10 mild dysplasia 10 moderate dysplasia 10 severe dysplasia Zone 1 Zone 4 Zone 2 Zone 3 Multiregion sequencing dysplasia Mutational and methylation analysis OSCC Copy number variation Goal 2. To delineate tumor clonal heterogeneity as a function of tumor progression (which ones progress?) We will assess the frequency of cancer associated mutational events in longitudinally collected samples to further identify key drivers of cancer progression in the same patient. Longitudinal collection (15 patients) dysplasia OSCC Gene expression analysis Mutational and Methyaltion analysis Copy number variation Comprehensive comparison of clonal heterogeneity between the crosswise and longitudinally collected samples will allow us to identify harbingers of malignant transition and confirm key events in progression. Goal 3. To detect and validate the key mutational events identified above in matched bodily fluids (for e.g. saliva and plasma samples) Validation of mutational events which characterize relevant lesions that may actually progress to cancers will allow us to better predict the fate of these early lesions noninvasively.