ALBERT

Description: Diffuse large B-cell lymphomas (DLBCLs) can be divided into germinal-center B cell–like (GCB) and activated-B cell–like (ABC) subtypes by gene-expression profiling (GEP), with the latter showing a poorer outcome. Although this classification can be mimicked by different immunostaining algorithms, their reliability is the object of controversy. We constructed tissue microarrays with samples of 157 DLBCL patients homogeneously treated with immunochemotherapy to apply the following algorithms: Colomo (MUM1/IRF4, CD10, and BCL6 antigens), Hans (CD10, BCL6, and MUM1/IRF4), Muris (CD10 and MUM1/IRF4 plus BCL2), Choi (GCET1, MUM1/IRF4, CD10, FOXP1, and BCL6), and Tally (CD10, GCET1, MUM1/IRF4, FOXP1, and LMO2). GEP information was available in 62 cases. The proportion of misclassified cases by immunohistochemistry compared with GEP was higher when defining the GCB subset: 41%, 48%, 30%, 60%, and 40% for Colomo, Hans, Muris, Choi, and Tally, respectively. Whereas the GEP groups showed significantly different 5-year progression-free survival (76% vs 31% for GCB and activated DLBCL) and overall survival (80% vs 45%), none of the immunostaining algorithms was able to retain the prognostic impact of the groups (GCB vs non-GCB). In conclusion, stratification based on immunostaining algorithms should be used with caution in guiding therapy, even in clinical trials.

Description: Introduction: DLBCL is biological and clinically highly heterogeneous. Although different genetic aberrations, including recurrent somatic mutations, have been described in this tumor, their clinical impact remains to be clarified. The aim of the present study was to determine somatic mutations and copy number alterations of a selected group of genes in patients with DLBCL, in order to assess their prognostic importance and to identify potential personalized targeted drugs for these patients. Methods: 150 patients (78M/72F; median age, 66 years) diagnosed with de novo DLBCL no otherwise specified at Hospital Clínic and other institutions of the GELCAB, treated with immunochemotherapy, were included in the study. An independent series of 111 patients (54M/57F; median age, 63 years), diagnosed at different Japanese and Spanish institutions, was used to validate the significant findings. Targeted next generation sequencing (NGS) of 106 representative genes related with DLBCL and Copy Number Alterations (CNA) assessment were performed. Ten functional pathways were pre-defined, including NOTCH, tumor suppressor genes, JAK/STAT, epigenome/chromatic modifier, BCR signaling, PI3K-AKT-mTOR, MAP-kinase, B-cell differentiation, immune surveillance and cell cycle alterations. Cell of origin (COO) of the tumors was established using gene expression or the Lymph2Cx assay. Genomic-guided potential therapeutic opportunities for each patient were identified in silico by a Cancer Genome Interpreter platform. Results: A total of 765 potential driver mutations were identified in 89 of the 106 genes with a slightly higher number in germinal center B-cell like (GCB) than activated B-cell-like (ABC) DLBCL subtype. The most frequently mutated genes found in 〉15% of the cases were KMT2D (MLL2), MYD88, CREBBP and TP53, with other 27 genes being mutated in 〉5% of the cases. Several genes were differentially mutated in GCB DLBCL subtype (KMT2D, CREBBP, TNFRSF14, B2M, EZH2, GNA13, FOXO1, ACTB and SOCS1) or ABC subtype (MYD88, PIM1, CD79B and PRDM1). No relevant differences were observed in the clinical features according to individual mutations or CNA. No single gene mutation predicted response to therapy. Genetic alterations in KLHL6, ETV6, SGK1, L8q12.1, CD79B, PIM1 and TP53 predicted poor OS, whereas mutations of SOCS1 were associated with better outcome. Alterations in NOTCH pathway and tumor suppressor pathway were associated with poor outcome, whereas those of JAK/STAT pathway showed favorable prognosis (see table for detailed data). NOTCH pathway (HR 2.8; p=0.006) and tumor suppressor pathway (HR 2.4; p=0.005) maintained independent significance for OS along with R-IPI (H 4.0; p=0.006) in a multivariate analysis that also included COO and beta2-microglobulin. In addition, the prognostic value of NOTCH and tumor suppressor pathways was confirmed in the independent validation series. Finally, we identified 69 cases (46%) carrying at least one genomic alteration in 9 genes considered a biomarker of drug response supported by data of early clinical trials or pre-clinical assays; tumors of additional 26 patients (17%) had at least one gene alteration that could be exploited by a drug repurposing strategy. Conclusions: Integrating the deep sequencing analysis of a panel of selected genes and CNA, we have recognized novel target genes and defined the clinical relevance of alterations of NOTCH and tumor suppressor pathways in DLBCL. Using an in silico prescription pipeline we have also identified a number of candidate drugs with potential therapeutic interactions with driver oncogenic proteins. All these findings may orient future preclinical and clinical intervention strategies in DLBCL. Table Initial features, response to therapy and outcome according to pathways´ status Table. Initial features, response to therapy and outcome according to pathways´ status Disclosures Sancho: Celltrion, Inc: Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gonzalez Barca:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Speakers Bureau; Gilead: Speakers Bureau. Ohshima:Kyowa Hakko Kirin Co., Ltd.: Research Funding, Speakers Bureau; CHUGAI PHARMACEUTICAL CO.,LTD.: Research Funding, Speakers Bureau. Akashi:Sunitomo Dainippon Pharma: Consultancy; Celgene: Research Funding; Kyowa Hakko Kirin: Consultancy, Research Funding; Bristol Meyers Squibb: Research Funding; Asahi Kasei Pharma Corporation: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding; Shionogi & Co., Ltd: Research Funding; Astellas Pharma: Research Funding.

Description: Introduction: MCL is a mature B-cell neoplasm characterized by t(11;14) (q13;q32) and cyclin D1 (CCND1) overexpression. Molecular studies have revealed other alterations in cell-cycle regulation, DNA damage response and cell survival pathways, with a landscape of somatic mutations being recently identified. CNS involvement is a well known complication, occurring in 4-26% of MCL at five years, with an ominous significance. Although different clinical variables have been identified as risk factors for CNS infiltration, the biological parameters related to this complication have not been extensively studied. The aim of the study was to explore the biological parameters associated with CNS involvement in a multicentre and retrospective series of MCL patients. Patients and Methods: 285 patients (M:74%; 64 yr) diagnosed of MCL between 1990-2014 (median survival of 4 years) were analysed. In addition to standard clinico-biological variables, IGHV mutational analysis, chromosomal alteration studies and Sanger sequencing of NOTCH1, NOTCH2, TP53, BIRC3, WHSC1, MEF2B, MLL2, TLR2 and PRDM1 were performed. Results: CNS involvement was observed in 15/285 MCL patients (5.2%), with a 5-yr risk of 9.1% (95%CI: 4.6-13.6), one patient at diagnosis, and at first or second/ulterior progressions in 7 cases each. The clinical, pathological and molecular risk factors identified are detailed in the Table. In addition to what has been already described, CNS involvement was usually observed in MCL cases with a clinical nodal presentation (p=0.05). In fact, no indolent MCL with a non-nodal presentation developed this complication during the follow-up period. No differences were observed in the risk of CNS involvement between patients treated in first-line with conventional or high-dose intense treatment (5-yr risk: 6.1%+/-6% vs. 10.7%+/-10.6%, p=ns). Regarding the biological features, no differences in terms of the IGHV mutational status were observed in cases developing CNS involvement compared to the others (75% vs. 68.7%, using 97% identity cut-off). Similarly, the IGHV gene usage of CNS involved cases corresponded to the more frequent IGHV genes observed in MCL (usually IGHV1-18, IGHV3-23, IGHV4-34, IGHV4-59). Although not significant, a predominance of high number copy number alterations (CNA) (〉4) could be observed in the genetic study of MCL cases with CNS involvement as could be expected for the enrichment in blastoid variants (up to 50% of these cases). In fact, we did not observe any case with CNS involvement among those cases with 3 or less CNA. CNS involvement was not related to common poor prognosis genetic alterations such as 9p, 11p and 17p losses, but the presence of 8q gains was associated with a higher risk of CNS involvement (p=0.05). We did not find any significant association between CNS involvement and the large number of oncogenic mutations studied. Conclusions: CNS involvement in MCL is associated with initial aggressive clinico-biological characteristics. Non-nodal MCL cases with a low number of genetic alterations did not present CNS involvement. Finally, the presence of 8q gains was associated with a higher risk of CNS infiltration. Table Initial Clinical Features Category N 5 yr-CNS involvement (%, 95%CI) HR p Performance status (ECOG) 〉 1 8/51 41.5 (+/-28) 4.2 .003 ≤ 1 7/128 9.4 (+/-5.5) Nodal disease Yes 14/185 13.3 (+/-7.6) 6.1 .05 No 1/77 1.4 (+/-2.7) Hemoglobin (g/L) 〈 105 12/93 24.7 (+/-14.7) 3.2 .05 ≥ 105 3/78 5.3 (+/-6.3) LDH 〉 ULN 4/89 27.1(+/-19.4) 6.7 ULN 11/114 21.6 (+/-14.9) 3.5 .04 〈 ULN 3/66 8.7(+/-10) Molecular & Pathological data Histological variant Blastoid 6/58 17.3 (+/-13.7) 3.5 .02 Others 8/156 1.3 (+/-7.2) Ki-67 〉 30% 5/44 17.5 (+/-14.9) 3.6 .06 ≤ 30% 3/61 6.7 (+/-9.4) SOX11 Positive 8/153 2.9 (+/- 5.7) 2.6 ns Negative 1/42 2.1 (+/-2.4) IGHV ≥97% 6/109 9.5 (+/-9.6) 1.9 ns 4 2/87 3.9 (+/-5.7) 1.1 ns ≤ 4 1/44 2.3 (+/-4.3) Chromotripsis Yes 1/17 12.5 (+/-22) 3.2 ns No 2/106 1.9 (+/-2.7) 8q gain Yes 2/30 13.1(+/-19) 7.5 .05 No 2/97 1 (+/-1.96) CNA: copy number alteration; IGHV: immunoglobulin heavy chain; LDH: Lactate dehydrogenase Disclosures No relevant conflicts of interest to declare.

Description: Abstract 4134 Gene expression profile (GEP) allows to distinguish two groups with different origin in patients with diffuse large B-cell lymphoma (DLBCL): germinal-center (GC) and activated (ABC), with the latter having a significantly poorer outcome. However, GEP is a technique not available in current clinical practice. For this reason, attempts to reproduce GEP data by immunophenotyping algorithms have been made. The aim of this study was to apply the most popular algorithms in a series of patients with DLBCL homogeneously treated with immunochemotherapy, in order to assess the correlation with GEP data and their usefulness to predict response and outcome of the patients. One hundred fifty seven patients (80M/77F; median age 65 years) diagnosed with DLBCL in 5 institutions of the Grup per l'Estudi dels Limfomes de Catalunya I Balears (GELCAB) during a 5-year period, treated with Rituximab-containing regimens (in most cases, R-CHOP), in whom histological material to construct a tissue microarrays (TMA) was available, constituted the subjects of the present study. Four algorithms were applied: Colomo (Blood 2003, 101:78) using CD10, bcl-6 and MUM1/IRF4; Hans (Blood 2004, 103:275) using CD10, bcl-6 and MUM1/IRF4; Muris (J Pathol 2006, 208:714) using CD10 and MUM1/IRF4, and Choi (Clin Cancer Res 2009, 15:5494), using CD10, bcl-6, GCET1, FOXP1 and MUM1/IRF4. The thresholds used were those previously described. GEP studies were performed in 62 patients in whom fresh frozen material was available. Main clinical and evolutive data were recorded and analyzed. The proportion of positive cases for the different single antigens was as follows: CD10 26%, bcl-6 64%, GCET1 46%, FOXP1 78% and MUM1/IRF4 28%. The distribution of cases (GC vs. non-GC) according to the algorithms is detailed in the table. In 88 of 110 patients (80%) with all the antigens available, the patients were allocated in the same group (either GC or non-GC). When the immunochemistry was compared with GEP data, the sensitivity in the GC group was 59%, 52%, 70% and 40% for Colomo, Hans, Muris and Choi algorithms, respectively. The sensitivity in the non-GC group was 81%, 85%, 62% and 84%, respectively. On the other hand, the positive predictive value (PPV) in the GC group was 81%, 83%, 72% and 77%, respectively. In non-GC subset the PPV for the different algorithms was 59%, 55%, 72% and 52%, respectively. We observed a higher percentage of misclassified cases in the GC-phenotype subset than in the non-GC subgroup. None of the immunohistochemical algorithms showed a significant superiority as surrogate of GEP information among the others. The ability of GEP groups as well as of groups defined by the algorithms to predict complete response (CR) rate, progression-free survival (PFS) and overall survival (OS) of the patients is showed in the table. Thus, whereas the GEP groups showed significant prognostic value for CR rate, PFS and OS, none of the immunohistochemical algorithms were able to predict the outcome. In conclusion, in a homogeneous series of DLBCL patients treated with immunochemotherapy, the different immunohistochemical algorithms were not able to mimic the GEP information. The prognostic impact of the groups defined by immunohistochemistry (GC vs. non-GC) was particularly low. N (%) CR rate N (%) 5-year PFS (%) 5-year OS (%) Colomo algorithm GC 53 (44) 39 (74) 48 54 Non-GC 68 (56) 53 (78) 55 62 Hans algorithm GC 61 (41) 47 (77) 54 60 Non-GC 88 (59) 67 (76) 52 59 Muris algorithm GC 87 (57) 63 (72) 48 57 Non-GC 65 (43) 51 (78) 56 63 Choi algorithm GC 45 (33) 32 (71) 48 54 Non-GC 90 (67) 70 (78) 52 61 Gene expression profile 30 (58) 25 (83) 76* 80** GC Activated 22 (42) 17 (77) 31* 45** * p=0.005, ** p=0.03. Disclosures: No relevant conflicts of interest to declare.

Description: The heterogeneous prognosis of patients with intermediate-risk cytogenetics AML (AML-IR) can be partially clarified by screening of NPM1 mutations (NPMmut) and internal tandem duplication of FLT3 (FLT3-ITD). Nonetheless, additional factors might influence the prognostic effect of these molecular lesions, such as the FLT3-ITD mutant level. Moreover, the optimal post-remission strategy might differ depending on the underlying molecular lesion. In this regard, we analyzed the outcome, according to NPM1 and FLT3 mutations and post-remission therapy given, of a series of patients diagnosed with de novo AML-IR in a single institution who received intensive chemotherapy. Patients were treated following 4 sequential protocols of CETLAM group during the period 1994–2006, consisting of 1 or 2 cycles of standard induction chemotherapy and 1 course of high-dose cytarabine-based consolidation therapy. Thereafter, patients underwent hematopoietic stem cell transplantation (HSCT) according to donor availability and presumed risk (protocols LAM 99 & 2003). NPM1 mutations and FLT3-ITD were screened in diagnostic DNA by PCR amplification followed by Genescan analysis. The ratio between FLT3-ITD and wildtype FLT3 alleles (ITD/wt ratio) was calculated using the area under the peak of corresponding alleles. Overall, 134 patients (51% male; median age, 53; range: 17–70) with AML-IR (normal karyotype, 66%) were studied. NPM1mut and FLT3-ITD were found in 45% and 37% of patients, respectively, with a median ITD/wt ratio of 0.59 (0.045–5.5). After induction regimen, 109 patients (81%) achieved complete response (CR). The only variables predictive of a favorable response were NPMmut (90% vs. 75%; p=0.01) and age 50 × 109/L), NPMwt, and FLT3-ITD. Interestingly, the prognostic value of FLT3-ITD depended on the relative mutant level, and detection of FLT3-ITD with a low ITD/wt ratio (i.e.,

Description: Follicular lymphoma (FL) is one of the most common malignant lymphomas. The t(14;18)(q32;q21) is found in about 80% of these cases and is regarded to play a principal role in their lymphomagenesis. However, the molecular mechanisms involved in the development and progression of these tumors are not fully understood. Although the clinical course is usually indolent, FL is sometimes refractory to chemotherapy and 25-35% of cases transform to aggressive lymphomas. This histological transformation is usually associated with a rapid progressive clinical course with around one year overall survival. Until now, several molecular mechanisms of the transformation have been described. P53 mutations, CDKN2A deletions and MYC translocations have been associated with FL transformation but some cases do not carry any of those genetic alterations suggesting that other mechanisms may also play a role. NOTCH signaling pathway is associated with various physiologic cellular processes such as cell proliferation, differentiation and death. Gain-of function mutations of NOTCH1 or NOTCH2 have been reported in acute T-cell lymphoblastic leukemia/lymphoma, chronic lymphocytic leukemia (CLL), mantle cell lymphoma (MCL), splenic marginal zone lymphoma (SMZL) and in most cases have been associated with transformation and a more aggressive biological behavior of the tumor. The presence of NOTCH1 or 2 mutations in FL and its possible relationship to tumor transformation have not been previously studied. Almost all NOTCH 1 or 2 mutations in CLL, MCL and SMZL are truncating mutations of the PEST domain and result in the elimination of degradation signals of NOTCH proteins. This prolongs the half-life of intracellular subunits leading to the activation of NOTCH signaling. In this study we have investigated the mutational status of NOTCH1 and NOTCH2 in 114 FL using the conventional Sanger’s sequencing method. These analyses covered the whole PEST domain and most of the TADD domain. NOTCH1 and NOTCH2 mutations were identified in five and two cases, respectively, (total 7/114, 6.1%). All mutations predicted for truncated protein in the PEST domain and were identical to those identified in other B cell lymphoid neoplasms. Pathologically, four out of the seven cases (57%) with NOTCH mutation had a morphological grade 3. A simultaneous DLBCL component was observed in four cases, three with grade 3 and one grade 2. One additional FL grade 2 subsequently transformed to DLBCL one year after the initial diagnosis. No MYC translocation or TP53 mutations were observed in the 5 FL/DLBCL with NOTCH mutations studied. Transformation to DLBCL histologically confirmed (simultaneously or subsequently) was significantly more frequent in NOTCH mutated (5/7, 71%) than unmutated FL (29/106, 27%)(P=0.025). BCL6 and BCL2 were positive in five out of six cases (83%) while CD10 was positive in three cases (50%). Only one of the NOTCH mutated cases had the t(14;18)(q32;q21) and two carried t(3q27) rearrangements. The frequency of t(14;18) in NOTCH mutated cases, therefore, is significantly lower than that in the NOTCH unmutated cases (14% vs. 72%, respectively; P=0.008). Clinically, extra-nodal involvement was found in six out of the seven (86%) NOTCH mutated cases and spleen involvement in four. Splenic involvement in the NOTCH mutated cases was significantly more frequent than that in the NOTCH unmutated cases (57 vs. 16%, respectively; P=0.027). Interestingly, all NOTCH mutated cases arose in female patients while no sex deviation was identified in the NOTCH unmutated cases (female proportion: 48%) (P=0.013). These results suggests that NOTCH mutations are uncommon in FL but may occur in a small subset of female patients with particular tumors characterized by the absence of the t(14;18), splenic involvement, and frequent transformation to DLBCL. Disclosures: Lopez-Guillermo: Roche: Membership on an entity’s Board of Directors or advisory committees.

Description: Introduction Progression of disease within 2 years after starting rituximab-chemotherapy (POD24) has been identified as a convincing adverse prognostic factor for follicular lymphoma (FL), and can serve as a clinical endpoint to identify patients at high risk of early lymphoma-related mortality. However, POD24 is not accessible at diagnosis. Several stratification models adopting baseline variables have been developed for predicting outcomes in FL patients. The Follicular Lymphoma International Prognostic Index (FLIPI) and PRIMA Prognostic-Index (PRIMA-PI) include clinical characteristics, while m7- Follicular Lymphoma International Prognostic Index (m7-FLIPI) and POD24 Prognostic Index (POD24-PI) integrate gene mutations with clinical features. Moreover, the mutation status of specific genes (including TP53, EZH2, TNFRSF14, and BCL2) has been reported to be relevant to early progression. It has been reported that m7-FLIPI and POD24-PI are predictive for POD24. Here we compare the diagnostic accuracy for POD24 of various stratification models and gene mutations in an institutional cohort of FL. Methods Consecutive patients diagnosed as FL grades 1-3a were enrolled from the Oncology Institute of Southern Switzerland (n=75), the University of Eastern Piedmont (n=118), and the Hematology of the AUSL IRCCS of Reggio Emilia (n=59). DNA was extracted from FFPE tissue specimen obtained at diagnosis. We performed CAPP-seq to detect the mutation status of the genes included in m7-FLIPI and POD24 PI (EZH2,ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), as well as BCL2, TNFRSF14 and TP53. POD24 was the primary endpoint of this research. Sensitivity, specificity, predictive values and balanced accuracy of every stratification model were calculated to estimate the prognostic efficacy. Results With FLIPI score, 34% of patients were classified as low risk, 22% as intermediate risk, and 41% as high risk. With PRIMA-PI, the fractions for low risk, intermediate risk and high risk group were 24%, 21% and 49%, respectively. With m7-FLIPI, 82% of patients were low risk, and 15% high risk. For POD24-PI, 65% of patients were low risk, and 32% high risk. The mutation frequencies of TP53, TNFRSF14, EZH2 and BCL2 were 8%, 28%, 27% and 38%, respectively. We validated the prognostic utility of FLIPI, PRIMA-PI, m7-FLIPI and POD24-PI for progression free survival (PFS) and OS. However, no statistically significant relevance with PFS or OS has been found for TP53, TNFRSF14, EZH2 or BCL2 mutations. POD24 was calculated in the 142 patients who received systemic treatment (immunotherapy or chemoimmunotherapy) within 6 months from diagnosis: 18% of them were POD24-positive. POD24 positivity associated with shorter overall survival (OS) (p=0.0138). After adjusting for multiple comparisons, no high-risk groups identified by TNFRSF14, EZH2 or BCL2 gene mutations, FLIPI, PRIMA-PI, m7-FLIPI or POD24-PI were associated with POD24. In terms of diagnostic performance for POD24, PRIMA-PI showed the highest accuracy (57%), FLIPI had the highest positive predictive value (64%), and m7-FLIPI had the highest negative predictive value (82%). Conclusion The mutation status of specific single genes were not related to POD24, PFS nor OS, indicating that the mutation of single gene may not be sufficient to identify high-risk FL patients. Though retaining their prognostic value, the integration of mutations onto the clinical biomarker-based prognostic scores has a limited discrimination capacity for POD24. Our results prompt the investigation of: i) POD discrimination capacity of prognostic models based on molecular phenotypes (i.e. gene expression) reflecting the tumor-microenvironment milieu; ii) new models based on a combination of biomarkers capturing the most informative clinical, genetic and phenotypic features. Figure 1 Disclosures Moccia: Takeda: Consultancy, Other: Advisory Boards: Roche, Janssen, Takeda; Roche: Consultancy, Other: Advisory Boards: Roche, Janssen, Takeda; Janssen: Consultancy, Other: Advisory Boards: Roche, Janssen, Takeda. Stathis:ADC Therapeutcis: Other, Research Funding; Abbvie: Other: Travel Grant; MEI Pharma: Other, Research Funding; Novartis: Other, Research Funding; Roche: Other, Research Funding; Pfizer: Other, Research Funding; PharmaMar: Other: Travel Grant; Cellestia: Research Funding; Loxo: Honoraria, Other, Research Funding; Member of the steering committee of the trial of this abstract: Other; Bayer: Other, Research Funding; Merck: Other, Research Funding. Gerber:Alnylam: Other: funding for accredited continuing medical education; Axonlab: Other: funding for accredited continuing medical education program ; Bayer: Other: funding for accredited continuing medical education program ; Bristol Myers Squibb: Other: funding for accredited continuing medical education program ; Daiichi-Sankyo: Other: funding for accredited continuing medical education program ; Janssen: Other: funding for accredited continuing medical education program ; Mitsubishi Tanabe Pharma: Other: funding for accredited continuing medical education program ; NovoNordisk: Other: funding for accredited continuing medical education program ; Octapharma: Other; Takeda: Other; Sanofi: Other; SOBI: Other; Thermo Fishe: Other; Axonlab: Other; Pfizer: Other: personal fees ; Sanofi: Other: funding for accredited continuing medical education. Gaidano:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astrazeneca: Membership on an entity's Board of Directors or advisory committees; Sunesys: Membership on an entity's Board of Directors or advisory committees. Rossi:Gilead: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding. Zucca:Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel Grants, Research Funding; Celltrion Healthcare: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Abbvie: Other: Travel Grants; Beigene: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding.