Importanza del test genetico nel carcinoma mammario ed ovarico

Transcription

1 Importanza del test genetico nel carcinoma mammario ed ovarico Lorena Incorvaia Azienda Ospedaliera Universitaria Policlinco «P.Giaccone» Palermo UOC Oncologia Medica

2 Ovarian Cancer Breast Cancer The range of DNA opportunities Prognostic Preventive Predictive

3 Ovarian Cancer: setting the scene No new front-line therapy for >20 years

4 Ovarian Cancer: setting the scene No new front-line therapy for >20 years Choise of treatment: The platinum free interval dogma No predictive factors! Relapsed ovarian cancer categories Refractory Resistent Partially sensitive Fully sensitive

5 Ovarian Cancer: Genetic Testing What did we know? What do we know today? BRCA1/BRCA2 Germline Mutations Beyond gbrca1/brca2: Not only germline mutations: somatic! Not only BRCA: HRD phenotype Family history OC/BC Age at diagnosis BRCA mutation is not associate to age and family history Surveillance program Prophylactic surgery BRCA testing prognostic and predictive value: BIOMARKER!

6 BRCA mutation: age and family history At least 25% of BRCA 1-2 mutation carriers are >60 yrs old Approximately 35%-40% of BRCA 1-2 mutation carriers do not have a family history of cancer Available evidence Median Age BRCA 1/2 BRCA Mutation BRCA 1 Carriers + BRCA 2 + Yrs Who Lack a Family Yrs History (%) Yrs Walsh et Alsop al. et al Soegaard Soegaard et al. et al Malander Risch et al. et al Risch et Malander al. et al Alsop et al. Song et al Song et al. 39 Family Age history not is a not good a good predictor predictor of BRCA of BRCA mutation mutation

7 BRCA mutation: histotype The backstage. Epithelial ovarian tumors: from singular to plural

8 Epithelial Ovarian cancer is not a unique disease Epithelial ovarian tumors

9 Impact of histological subtype

10 BRCA mutation is not correlated to histotype Available evidence BRCA mutation in 14.1% of the studied population Epithelial ovarian tumors 16.6% of serous histotype 22.6% of high grade serous subtype 6.3% of clear cell subtype 8.4% of endometrioid subtype Alsop K, et al. J Clin Oncol 2012; 30:

11 Available evidence Total population (%) Serous (%) Endometrioid (%) Clear Cell (%) Mucinous (%) Alsop et al NA Risch et al Soegaard et al Jacobi et al Malander et al Histotype is not a good predictor of BRCA mutation Soergaard M. et al., Clin Cancer Rev. 2008; Risch HA et al., JNCI 2006; Alsop K et al., JCO 2012 Malander S. et al., EJC, 2004; Jacobi CE et al., Genet Med, 2007

12 Ovarian Cancer: Genetic Testing What did we know? What do we know today? BRCA1/BRCA2 Germline Mutations Beyond gbrca1/brca2: Not only germline mutations: somatic! Not only BRCA: HRD phenotype Family history OC/BC Age at diagnosis BRCA mutation is not correlate to age and family history Surveillance program Prophylactic surgery BRCA testing prognostic and predictive value: BIOMARKER!

13 1. Prognostic BRCA: impact of germline mutations 5-year survival: BRCA1 44% BRCA2 61% No mutation 25% Patients with BRCA mutated ovarian cancer show a significantly more favourable prognosis Bolton KL, et al. JAMA. 2012;307(4): Zhong Q et al. Clin Cancer Res. 2014;21(1):

14 1. Prognostic Pts with gbrca mutations have a longer survival than in women with sporadic ovarian cancer

15 2. Predictive BRCA: impact on patient therapy Improved survival in BRCA-mutated ovarian cancer patients treated with Intraperitoneal cisplatin and paclitaxel Lesnock JL, Br J Cancer, 2013

16 2. Predictive BRCA: impact on patient therapy

17 2. Predictive BRCA: impact on patient therapy Trabectedin in patients with BRCA-mutated and BRCAness phenotype Advanced Ovarian Cancer (AOC): Phase II Prospective MITO-15 Study

18 2. Predictive BRCA: impact on patient therapy Analysis of OV-301 according to BRCA status Monk BJ Ann Oncol 2015

19 Proportion of patients progressionfree 2. Predictive BRCA: impact on patient therapy Study 19: OLAPARIB. PFS by BRCAm status Number at risk Olaparib BRCAm Placebo BRCAm Olaparib BRCAm Placebo BRCAm Time from randomization (months) BRCAm (n=136) Olaparib Placebo Events: total pts (%) 26:74 (35.1) 46:62 (74.2) Median PFS, months HR= % CI (0.11, 0.31); P< % reduction in risk of disease progression or death with olaparib

20 Progression-free survival (%) SOLO 2, PFS by investigator assessment No. at risk Olaparib Placebo Months since randomization Olaparib Placebo 29 6 Olaparib (n=196) 3 0 Placebo (n=99) Events (%) 107 (54.6) 80 (80.8) Median PFS, months HR % CI 0.22 to 0.41 P< Median follow-up was 22.1 months in the olaparib group and 22.2 months for placebo Presented by Pujade-Lauraine at SGO 2017 annual meeting

21 Major interactive pathways involved in DNA damage and repair Abbreviations: MMR, mismatch repair; BER, base excision repair; NHEJ, nonhomologous endjoining; HRR, homologous recombination repair; NER, nucleotide excision repair; TLJ, translesional joining.

22 PARP inhibitor and tumor selective synthetic lethality Mutation in BRCA1 or BRCA2 gene Functioning PARP1 Repaired DNA PARP1 Singlestrand break PARP1 1 PARPinhibitor Singlestrand break No DNA repair Collapsed replication fork Doublestrand break No homologous recombination No repair PARPisensitive Cell death Incorvaia et Al, Oncotarget 2016

23 Key points Age and family history are not sufficient criteria for BRCA testing Histologic type (except mucinous) is not a sufficient criterio for BRCA testing BRCA is predictive of PARP-inhibitor sensitivity Genetic Testing: Predictive!

24 Ovarian Cancer: Genetic Testing What did we know? What do we know today? BRCA1/BRCA2 Germline Mutations Beyond gbrca1/brca2: Not only germline mutations: somatic! Not only BRCA: HRD phenotype Family history OC/BC Age at diagnosis BRCA mutation is not correlate to age and family history Surveillance program Prophylactic surgery BRCA testing prognostic and predictive value: BIOMARKER!

25 Beyond germline BRCA1/2 mutations Not only germline mutations Not only BRCA mutations

26 Beyond BRCA: HRD phenotype BRCA germline mutation BRCA somatic mutation HR mutation, non-brca BRCA-like signature Sensitivity to DNA repair inhibitors?

27 Parp-inhibitor trials for sporadic, BRCA WT, ovarian cancer: Do we have one? 2 Randomised maintenance trials following platinum-based chemotherapy in BRCAm and BRCAwt gbrcamut Rucaparib, Ariel 3 trial BRCA-like Biomarker negative Niraparib, NOVA trial gbrcamut Non-gBRCAmut

28 Homologous Recombination Deficiency (HRD) Assay Do we have one? Rucaparib, Ariel 2 trial McNeish IA, et al. J Clin Oncol. 2015;

29 Homologous Recombination Deficiency (HRD) Assay Do we have one? Rucaparib, Ariel 2 trial gbrcamut ORR 80% BRCA-like ORR 29% Biomarker negative ORR 10% ARIEL 2, ASCO 2015

30 Homologous Recombination Deficiency (HRD) Assay Do we have another? Developed HRD score in the NOVA trial incorporating 3 components: Loss of heterozygosity (LOH) Telomeric allelic imbalance (TAI) Large-scale state transitions (LST) HRD score is sum of LOH + TAI + LST scores - Presented evidence of correlation between HRD score and in vitro/in vivo response to niraparib in 106 tumor samples Thus: - Two assays under further evaluation, as key elements in 2 randomized maintenance trials, with niraparib and rucaparib in sporadic and BRCAmassociated ovarian cancer Haluska P et al, NCI/EORTC/AACR 2014 (Eur J Cancer. 2014)

31 NOVA trial, Niraparib PFS Non-gBRCAmut gbrcamut Non-gBRCAmut cohort, HRDpos group Mirza MR et al. N Engl J Med. 2016

32 Germline BRCA1/BRCA2 HRD phenotype Olaparib Niraparib Rucaparib... OC and HR: How the debate is evolving? Need for Biomarkers! Identifying the HR Deficiency Signature Identifying the subset of BRCA-like tumors, which respond to HRR-directed therapy

33 OC and HR: How the debate is evolving? Panel testing Ready for the clinics? 1. Which genes? Analyzing BIG data 2. What is the clinical utility of non-brca genes? 3. Who should order and interpret the findings of panel testing? Clinically relevant? 18% carried a germline mutation: 15% in BRCA1 or BRCA2 3% in BRIP1, RAD51C, RAD51D, PALB2, BARD1 0.4% in a MMR gene Norquist BM, et al. JAMA Oncol. 2015

34 OC and HR: How the debate is evolving? Tumor Heterogeneity! How can we account for heterogeneity and dynamic changes that occur in response to a given targeted therapy?

35 Spatial and Temporal Heterogeneity BRCA2 BRCA1 RAD51 BRIP EMSY FANCF TP53 CHECK2 ATM ATR HGS-EOC Tp53 Tp53 Tp53 Tp53 Tp53 ATM/ BRCA1/2 ATR BRCA1/2 Tp53 BRCA1/2 Tp53 BRCA1/2 Tp53 BRCA1/2 ATM/ BRCA1/2 Tp53 Tp53 ATR BRCA1/2 Tp53 Tp53 BRCA1/2 BRCA1/2 BRCA1/2 Tp53 Non- HGS-EOC ATM/ ATR BRCA1/2 BRCA1/2 Tp53 BRCA1/2 BRCA1/2 Tp53 Tp53 BRCA1/2 BRCA1/2 ATM/ ATR AF=1%-20% AF=20%-50% AF=50%-100% Beltrame L et al., Ann Oncol 2015

36 Where to go next? Until we identify actionable target, the severe genomic instability found across HGSOC remains the fulcrum

37 Synthetic Lethality HRD iparp

38 New opportunities.. Clinical Synthetic Lethality Chemical synthetic lethality Leverage DNA damage response (DDR) Contextual synthetic lethality Targeting the molecular and microenvironmental characteristics of tumor Endogenous tumor factors HRD TP53 Cell cycle regulation + Exogenous tumor factors Hypoxia Immune activation Glucose metabolism

39 Hypoxia Hypoxia downregulates key genes in the homologousrecomination and mismatch-repair pathway (RAD 51, RAD 52, BRCA, MSH2, and MSH6) Leveraging hypoxia to induce HRD-like environment Hypoxia is presumed to be generated locally by angiogenesis inhibitors

40 Testing the hypothesis: PARPi + VEGFRi Chemical synthetic lethality Leverage DNA damage response (DDR) Contextual synthetic lethality Targeting the molecular and microenvironmental characteristics of tumor Endogenous tumor factors HRD TP53 Cell cycle regulation + Exogenous tumor factors Hypoxia Immune activation Glucose metabolism

41 Olaparib + Cediranib Sinergy between hypoxia and inhibition of DNA repair Olaparib + Cediranib signifcantly increased PFS in patients without BRCA mutation Poster 5535 ASCO 2017

42 New opportunities.. Clinical Synthetic Lethality Chemical synthetic lethality Leverage DNA damage response (DDR) Contextual synthetic lethality Targeting the molecular and microenvironmental characteristics of tumor Endogenous tumor factors HRD TP53 Cell cycle regulation + Exogenous tumor factors Hypoxia Immune activation Glucose metabolism

43 Ovarian Cancer Immunogenic T cell infiltration affect outcome

44 Anti PD1/PDL1 -ORR 15% -Very rarely long lasting responses Other Studies -Disis et Al, Avelumab: ORR 9.7% -Brahmer et al, Nivolumab: 17 pts, 1 PR, 2 SD

45 Testing the hypothesis: PARPi + Immunotherapy Chemical synthetic lethality Leverage DNA damage response (DDR) Contextual synthetic lethality Targeting the molecular and microenvironmental characteristics of tumor Endogenous tumor factors HRD TP53 Cell cycle regulation + Exogenous tumor factors Hypoxia Immune activation Glucose metabolism

46 Why combine DDR inhibitors + immunotherapy HGSOC has intermediate mutational load with high genomic instability, causing neoantigen production Inhibition of DDR pathways would be expected to propagate DNA damage and thus increase neoantigen potential Promising start! J-m Lee et al, JCO 2017

47 Navigating the new information. Hypoxia Epigenetic generation of HRD Immunotherapy combinations The range of DNA opportunities Combine with other DNA repair targets Cell cycle dysregulation

48 Ovarian Cancer Breast Cancer The range of DNA opportunities Prognostic Preventive Predictive

49 Genomic landscape of breast cancer: key findings 1.Wide range of cancer genes can operate (upto90) Balko Cancer Discovery Different subtypes have different genomic features 3.Extensive heterogeneity

50 Do mutations predict response?

51 Role of platinum compounds in gbrca advanced BC pts: TNT trial Overall population: No difference gbrca: Carboplatin superior to docetaxel Tutt A SABCS 2016

52 But BRCA mutation and methylation in primary show very different relationships with platinum response measured in metastatic disease Platinum sensitivity not associated with higher HRD scores in mtnbc Tutt A IMPAKT 2017

53 PARP Inhibitors in Development Polyak K, Garber J. Nat Med. 2011

54 Olaparib versus physicians choice: The phase III OLYMPIAD study in advanced gbrca carriers

55 Potential benefits of genomic testing Conclusions Estimation of the lifetime risk of cancer in an individual and/or her family Identification of individuals at sufficient risk to consider enhanced screening or prevention strategies Provide prognostic information about standard therapy Offers opportunities for therapeutic intervention: predictive information about response to specific therapies

56 Potential benefits of genomic testing Conclusions Improve understanding of tumor biology: -Spectrum of mutations becoming clearer -Need to consider beyond the «singol gene» vision: beyond mutations, to gene expression, pathway activation, tumor microenvironment, cooperation between mutation, tumor heterogeneity. -Need to understand clinical utility of other mutations and the evolution of tumors under treatment stress

57 Conclusions Novel driver alterations, driver genes, driver-target and driver-draug associations. Options likely will increase in tandem with our understanding as long as we keep asking relevant questions.???????? Thanks