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BRAFV600E mutation is the pathogenic driver of hairy cell leukemia (HCL) found in the vast majority of cases both at onset and during recurrences. The identification of the mutated allele in blood and marrow correlates with the presence of neoplastic cells and can be considered a marker of active disease. Likewise, the absence of themutation after treatment may indicate a state of deep response. The BRAFV600E burden was measured by droplet digital polymerase chain reaction (ddPCR) and expressed as fractional abundance in 35 HCL patients at different stages of disease (onset, relapse, complete response [CR] after treatment, long-term remission) in peripheral blood and/or bone marrow (when available). Mean values of fractional abundance for patients at diagnosis, relapse and response, respectively, were 12.26%, 16.52% and 0.02% in peripheral blood and 23.51%, 13.96% and 0.26% in bone marrow. Four patients out of 6 evaluated at response were molecularly negative for BRAFV600E in peripheral blood. Mean fractional abundance in peripheral blood tested in 14 patients with long lasting CR was 0.05%, and 10 patients were BRAFV600E negative. These preliminary results suggest that ddPCR permits to assess the active tumor burden in HCL at different disease phases and support the hypothesis that some patients in CR qualify for a molecular CR.

DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways’ genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells’ differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells’ phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future.

Background MM is a hematological malignancy always evolving from pre-malignant stages, with progressive increase of genomic complexity. MM is characterized by a large abundance of copy number alterations (CNA); many of them, regarded as “driver”, stack up progressively from early tumor stages, causing biological changes that give rise to tumor hallmarks and malignant phenotypes. The combined application of whole genome analysis and mathematical models allows to deeply describe these alterations and to infer their order of acquisition during oncogenesis from their clonality levels, assuming that clonal ones are more ancestral than subclonal. Aims: (1) To define the temporal order of acquisition of CNA, leading to the onset of symptomatic MM and (2) to define a scoring model able to stratify patients (pts) according to the ancestrality of the alterations observed in their genomic landscape. Methods Genomic data collected from a total of 1384 newly diagnosed MM pts were included in the study: SNPs array data were collected from 514 pts of our Institution (BO dataset); in 870 pts, WES data were downloaded from CoMMpass study. CN calls and clonality levels were harmonized by an analysis pipeline including ASCAT, GISTIC v2 and custom R scripts. Timing estimates were obtained with BradleyTerry2 package. Survival analysis were performed on R. Results A full call-set of CNAs was obtained by harmonizing BO and CoMMpass datasets. The clonality information was first extrapolated from the whole call-set, to define the temporal order of acquisition of non-primary CNAs. CNAs were then accurately ranked, by using the obtained timing estimates, characterized by a quite narrow confidence interval. Of interest, chr 1q gains and chr 13q losses were frequently clonal and ranked as ancestral events, whereas chr 17p losses were late occurring events. By weighting the CNAs carried by any given pts at diagnosis with their relative timing estimate in a combinatorial process, an Ancestrality Index (AI) was defined for each pts (median AI=3.4, IQR=1.7-6.0). The AI was found to be significantly associated with progression free (PFS) and overall survival (OS) (p3.4 (i.e. with a more “ancestral” profile) had a worse outcome as compared to the rest of pts (OS 40% vs 58%, PFS 42% vs 56%, at a median follow up of 92m and 34m, p Conclusions By means of whole genome analysis and dataset harmonizing, the temporal order of acquisition of MM CNAs has been confidently described. A score reflecting the disease ancestrality of MM pts at diagnosis was generated and associated to survival outcomes. Overall, these findings support the evidence that MM pts at diagnosis carrying an excess of ancestral alterations, expected to likely be drivers, are prone to have a dismal prognosis.

Introduction Multiple Myeloma (MM) is a genetically complex disease, characterized by the recurrence of several chromosomal aberrations, which impair the disease prognosis. The use of genome-wide technologies has recently highlighted the existence of Complex Chromosomal Events (CCEs), caused by distinct phenomenons: Chromothripsis (CT), caused by single-step genomic events, and Stepwise Events (SE), consequence of multiple, small and sequential genomic events, occurring throughout subsequent cell cycles. The prognostic impact of CT in MM has not yet been fully elucidated. Aims of our study were: (1) to detect CCEs in MM, with a focus on CT, by using an original and reliable bio-informatic algorithm, (2) to characterize the genetic and genomic context of CT and (3) to correlate the presence of CTwith pts prognosis. Methods A total of 488 newly diagnosed MM patients (pts) have been included in the study. Genomic data have been obtained by SNPs arrays on bone marrow (BM) aspirates CD138+ enriched cell fractions; data were analysed by Affymetrix’s programs and R-scripts. Results An original algorithm able to discriminate among the 2 different CCEs (CT and SE),was set up and tested, by implementing the most commonly reported guidelines for CCEs identification with knowledges on MM-specific highly heterogeneous genomic context. CCEs were detected in 174 pts (36% with at least one CCE): in particular, 46/174 pts (26%) carried CT. CT can affect any chromosome, yet showing significant associations with the following genomic regions: chr1p (p=8.37E-15), chr2q (p=4.27E-8), chr11q (p=6.99E-5) and chr22q (p=5.15E-7). Pts carrying CT were more likely to carry also IgH translocations associated to bad prognosis (p=0.002, HR 3.4) and TP53 deletions (p=1.16E-5, HR=6.26). The presence of any CT event conferred hazard ratio of 1.52 (p=0.019) and 1.68 (p=0.019) to pts’ progression-free (PFS) and overall survival (OS), respectively, independently from the presence of both TP53 deletion and translocation t(4;14), as evaluated in a multivariated model. An association between CT events and XBP1 gene deletion was observed; since XBP1 expression has been correlated to an effective proteasome inhibitor (PI) therapy response, CT events particularly impacted survival expectancies of PI-treated pts, whose PFS and OS were significanlty worse than those of other pts (p=0.0098 and =0.023, respecitvely). Finally, the same CT events acquired at diagnosis were observed in those 4/55 pts, whose BM aspirates were analysed also at relapse, thus suggesting that, once occurred, CT might have a driver role for disease progression. Conclusion Our results showed that CT impact MM pts prognosis, independently from the genomic region affected and the pts’ genomic backgroung. Acknowledgment AIRC_IG2014, RF-2016.

BACKGROUND: Multiple Myeloma (MM) maintenance therapy is a low intensive, prolonged treatment, commonly administered to newly diagnosed patients (pts) at the end of front-line regimens. Lenalidomide (LEN) is considered the best available maintenance option for MM, the actual benefits or disadvantages of a LEN-based maintenance and its potential role as “selective pressure” on MM sublcones are still unclear. AIM: In this study we estimated the role of LEN maintenance therapy in eliciting genomic changes in a cohort of MM pts homogeneously up-front treated. PATIENTS-METHODS: Whole genome Copy Number Alterations (CNA) was obtained by SNPs array in 54 pts samples collected both at diagnosis(D) and at first relapse(R). Pts had an high-risk (HR) disease, defined by a median TTP of 29m. A custom gene-level CN calling algorithm was set up, to compute the evolution of every gene CN value and the genomic evolutive trajectories associated to changes of these values. High-risk genomic loci were defined using GISTIC to derive target genomic relevant for MM biology. After PIs induction therapy, 31/54 pts were treated with HD chemotherapy followed by either single or double ASCT; LEN maintenance therapy was then offered both to 20/31 auto-transplanted and to 6/23 not auto-transplanted pts. RESULTS: Three main evolutive trajectories (linear L, drift D, and branching B) were defined according to the CN changes' direction, reflecting a putative positive, negative, or both positive and negative selective pressure, respectively. A fourth, stable (S) trajectory was also observed, characterized by the absence of CN changes. Overall, 29, 15 and 10 pts relapsed with B/D, L and S pattern, respectively; at R, all LEN-treated pts changed their sub-clonal architecture: a B/D evolutive pattern characterized 70% of pts. By contrast, genome remained mostly stable in 61% of not-treated pts. We then focused on CN changes of specific chromosomal regions and/or genomic loci identified as high-risk, whose prognostic role has been already established in MM (i.e. TP53, CDKN2C, CKS1B). When present at D, these CNA tended to persist throughout the disease course, regardless of whether pts received or not maintenance. The emersion of any of these CNAs at R was widely observed both in pts receiving or not maintenance, whereas a negative selective pressure over them was more likely to occur in pts receiving maintenance, as compared to the others (50% vs 11% of B/D trajectories in LEN-treated vs not-treated pts, respectively). Strikingly, in LEN-treated pts, the extension of both TTP and OS was favored by the extinction and/or negative selection (B/D patterns) of the HR CNAs, and shortened by their stability or positive selection (L/S patterns) (median TTP 46 vs 32m HR=3.6, p=0.01; median OS 111 vs 63m HR 5.7, p=0.04 in B/D vs L/S pts, respectively). On the contrary, the absence of maintenance selective pressure seemed to affect neither the evolution trajectory, nor the clinical course of not-treated pts. CONCLUSION: The extinction of sub-clones carrying HR lesions in pts receiving maintenance therapy is likely to be associated to the negative selection exerted by the therapy. This might explain the extended survival of these pts. On the contrary, the subclones of pts not receiving maintenance might randomly evolve, due to the absence of a specific selective pressure. Citation Format: Andrea Poletti, Vincenza Solli, Marina Martello, Enrica Borsi, Lucia Pantani, Agboyi Lakpo, Silvia Armuzzi, Luca Nunzio Cifarelli, Elena Zamagni, Paola Tacchetti, Serena Rocchi, Katia Mancuso, Ilaria Rizzello, Giulia Marzocchi, Nicoletta Testoni, Luca Dozza, Maria Teresa Petrucci, Anna Marina Liberati, Giuseppe Rossi, Mario Boccadoro, Michele Cavo, Carolina Terragna. Negative selective pressure exerted by maintenance therapy promotes the extinction of sub-clones carrying high-risk lesions in multiple myeloma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2700.

Asthma is a complex and heterogeneous disease, caused by the interaction between genetic and environmental factors with a predominant allergic background in children. The role of specific genes in asthmatic bronchial reactivity is still not clear, probably because of the many common pathways shared with other allergic disorders. This study is focused on 11 SNPs possibly related to asthma that were previously identified in a GWAS study. The genetic variability of these SNPs has been analysed in a population of 773 Italian healthy controls, and the presence of an association between the polymorphisms and the asthma onset was evaluated performing genotyping analysis on 108 children affected with asthma compared with the controls. Moreover, a pool of 171 patients with only allergic rhinoconjunctivitis has been included in the case–control analysis. The comparison of allele frequencies in asthmatic patients versus healthy controls identified two SNPs—rs1162394 (p = 0.019) and rs25681 (p = 0.044)—associated with the asthmatic condition, which were not differentially distributed in the rhinoconjunctivitis group. The rs25681 SNP, together with three other SNPs, also resulted in not being homogenously distributed in the Italian population. The significantly higher frequency of the rs25681 and rs1162394 SNPs (located, respectively, in the C5 and SRGAP3 genes) in the asthmatic population suggests an involvement of these genes in the asthmatic context, playing a role in increasing the inflammatory condition that may influence asthma onset and clinical course.

Background The introduction of novel agents into the therapeutic algorithm of Multiple Myeloma (MM) has led to remarkable improvements in the rate of Minimal Residual Disease (MRD) negative status. Sustained MRD negativity is a robust prognosticator and a driver of treatment strategies. Therefore, it is expected that MRD molecular tracking would become critical in the management of MM, and could be included in daily clinical practice. Aim To evaluate the performances of next generation sequencing (NGS), implemented as best practice in MM MRD daily evaluation. Methods A cohort of 166 newly diagnosed transplant-eligible and -ineligible MM pts were screened to define the ID clonotypes. MRD was firstly assessed at achievement of at least a very good partial response during maintenance, and thereafter once a year. In high-risk pts, MRD was also detected between 1° and 2° autologous stem-cell transplantation (ASCT). The ID clonotypes screening has been performed by NGS, using an assay covering IgH and Igk genes (Invivoscribe®). The MRD tracking has been done both by conventional ASO-qPCR and by NGS. Data were analyzed by Lymphotrack Dx and MRD software (Invivoscribe®). Results The ID clonotypes screening was successful in 158/166 pts (95%), even though a small proportion of pts resulted polyclonal (14/158). Overall, 63, 27 and 54 pts had IgH, Igk and IgH/k ID clonotypes, respectively, mainly restricted to the VH3 (47%) family genes. MRD assessment was performed by NGS in 124/144 pts (overall, 96 MRD samples for 64 pts monitored to date), with 10-5 sensitivity in most cases (75/96). 44 pts were assessed during maintenance and 23 achieved MRD-negativity. On the contrary, 20 pts were evaluated between 1° and 2° ASCT, resulting MRD-positive in all cases. Overall, few FU samples (13/96) were reported as “positive-not-quantifiable” (PNQ), since had residual disease levels of 10-7, much lower than the internal control. In a subset of 20 pts with trackable IgH/Igk sequences, pts-specific assays were designed, according to the EuroMRD guidelines. In these pts, MRD was tested both by ASO-qPCR (including a standard curve and healthy donor cells, to define the sensitivity and the specificity, respectively) and by NGS. Overall, ASO-qPCR allowed the tracking of a single MRD clone (with up to 10-4 sensitivity) in 12/20 pts (60%), whereas NGS was feasible in all of them, confirming the ASO-qPCR results, yet with higher sensitivity and >95% confidence. Moreover, in 2 cases, NGS allowed to disclose ASO-qPCR PNQ results due to nonspecific amplification, thus unveiling MRD negativity with 10-5 sensitivity. Conclusion NGS has been successfully implemented as best practice in the management of MM pts, showing the superiority of this method over ASO-qPCR conventional approach. The ID clonotype was defined in almost all pts included in the workflow, thus allowing their MRD molecular monitoring, according to the clinical requirements. Acknowledgment AIRC IG2018-22059

Background Multiple Myeloma (MM) is a plasma cell (PC) disorder characterized by the presence of multiple lytic lesions at the time of diagnosis. Recently, cell-free DNA (cfDNA) has proven to resume the heterogeneity of spatially distributed clones. However, the potential of cfDNA to track the evolutionary dynamics and the heterogeneity of MM, possibly anticipating the emergence of therapy resistant residual cells, remains to be confirmed. Aim of this study is to evaluate cfDNA at diagnosis and during follow-up in order to compare this approach with both bone marrow (BM) molecular and whole-body imaging residual disease assessment. Methods A total of 97 patients (pts) were screened at baseline and during follow-up with 18F-FDG PET/CT and NMR, and molecularly assessed by Ultra Low Pass-Whole Genome Sequencing (ULP-WGS). ULP-WGS was used to characterize both the neoplastic PC clone from BM (gDNA) and the cfDNA from peripheral blood. Data were analysed by ichorCNA and Clonality R packages. Results Overall, cfDNA tumour fraction (TF) at diagnosis was significantly lower as compared to gDNA TF [median (M) TF: 3.0%vs.74.4%, respectively]. Nevertheless, high cfDNA TF levels (49/97 pts = 50%, M cfDNA TF: 10%, range : 3.0-40.6%) correlated with high gDNA TF levels (M gDNA TF: 84%, range: 5.9-95.2%). Similarly, a significant correlation was shown between cfDNA TF and the BM plasma cells clone throughout disease progression, highlighting a parallel dynamics of tumour burden from SMM to MM to +3m post-induction (cfDNA TF vs. % CD138+/CD38+ BM cells: 1.5 vs 1.0; 3.0 vs. 2.3; 1.2 vs. 0.01, respectively, p: 0.008). Pts with high cfDNA TF were likely to have more sites of extramedullary disease (EMD) at PET-CT, a higher number of PET lesions and higher tumour metabolic activity, as compared to pts with low TF (EMD 8/49, 17% vs. 2/49, 3.4%; M n. PET lesions: 8 vs. 2; SUVmax: 12.9 vs. 3.9). Similarly, bone involvement as detected by MRI, was more evident in pts with high cfDNA TF (M n. focal lesions: 6 vs. 1). More interestingly, after 3 cycles of induction therapy, imaging and cfDNA TF dynamics were concordant: indeed, in those cases where FDG activity and focal lesions still persisted (4/10=40%: SUVmax 5.8; >2 PET lesions), cfDNA TF as well was still detectable (>1 TF).Finally, the comparison between cfDNA and BM genomic profiles showed an overall concordance of the copy number alterations (CNAs) landscape in most patients (83/97; 86.4%), whereas three patients (10/97; 10,3%) displayed a different genomic profile in cfDNA, as compared to BM. Conclusions although only few cases showed genomic evidence of spatial heterogeneity, in pts with high cfDNA TF, imaging data overall suggested a propensity to a metastatic spread of the disease. Future studies will be addressed to exploit the use of cfDNA in disease monitoring. Acknowledgements AIRC IG2018-22059.

In recent years, a connection between psychoanalysis and neuroscience has been sought. The meeting point between these two branches is represented by neuropsychoanalysis. The goal of the relationship between psychoanalysis and neuroscience is to test psychoanalytic hypotheses in the human brain, using a scientific method. A literature search was conducted on May 2015. PubMed and Scopus databases were used to find studies for the inclusion in the systematic review. Common results of the studies investigated are represented by a reduction, a modulation, or a normalization of the activation patterns found after the psychoanalytic therapy. New findings in the possible and useful relationship between psychoanalysis and neuroscience could change the modalities of relating to patients for psychoanalysts and the way in which neuroscientists plan their research. Researchers should keep in mind that in any scientific research that has to do with people, neuroscience and a scientific method cannot avoid subjective interpretation.

Introduction The differentiation status plasticity of Multiple Myeloma (MM) plasma cells (PCs) is an adaptive strategy that might confer a specific fitness to tumour cells, enabling their interaction with an evolving microenvironment. Therefore, proliferation rates of MM clones are not constant, and the immunophenotypic profile of the most skilled MM PCs might be the expression of specific genetic and genomic programs, that emerge under the therapeutic pressure and promote tumour development. However, the genomic background that supports any diverse plasma cell differentiation phenotypes has not yet been inferred. Aim To correlate the genetic and genomic background with the immunophenotypic profile of MM clones at diagnosis, in order to stratify patients (pts) according to a Maturation Index, and ultimately to evaluate the impact of this stratification on the disease outcome. Patients and Methods 117 newly diagnosed MM (NDMM) pts, mostly treated up-front with a proteasome inhibitor (PI) -based treatment, were included in the study. For each pts, both neoplastic PCs and CD19+ B cells compartments were characterized by 8-color multi-parameter flow cytometry analysis, combining CD138-PE, CD38-PE-Cy7, CD56-APC-Cy7, CD20-APC, CD19-FITC, CD27-APC, CD45-PerCp, CD28-APC, CD117-FITC, CD28-APC, CD81-APC, IgK-APC and IgL-FITC. In a subgroup of pts, both a SNP array profile for copy number alterations (CNAs) and a 25-genes targeted mutational panel were assessed in CD138+ PCs. A custom ddPCR assay was also employed to evaluate through a 10-Hh gene signature the self-renewal status of PCs. Results In order to define a Maturation Index, pts were evaluated at different levels of heterogeneity for: a) differential expression of CD19/CD81 markers; b) level of chromosomal instability (CIN) and point mutations; d) self-renewal status. Based on the co-expression of CD19 and CD81 markers, pts were stratified in 3 different subgroups, recapitulating a progressive PC maturation process: the most immature, which included pts with CD19+/CD81+ PCs (18/117 = 15%), the intermediate, including CD19-/CD81+ PCs (42/117 = 36%) and the most mature, including CD19-/CD81- PCs (57/117 = 49%). The advanced PC differentiation status characterizing this latter subgroup was further confirmed by the high expression of CD28 and CD44, and the reduced expression of CD20, CD27 and CD45, commonly associated with less mature stages of the disease (p CIN was defined according both to the total CNAs count and to the number of chromosomes' breakpoints (BPs). Pts with an advanced differentiation status displayed a higher number of total CNAs and BPs (median tot. CNAs = 550 vs. 105, and median BPs nr. = 18.5 vs. 8 in CD19-81- and CD19+81+ pts, respectively, p Finally, a more mature PC clone was significantly related to a higher prevalence of unfavourable features at baseline (e.g. ≥ 3 PET lesions, ≥ 100 k/l ratio, ISS III disease stage p Conclusions A Maturation Index defined NDMM pts with an advanced differentiation status both at immunophenotypic and molecular level, finding lastly associated with a prevalence of poor prognostic features. Chromosomal instability, together with cellular phenotypic plasticity, represents an important, yet poorly defined, mechanism by which MM clones accelerate their own evolution and survival. Acknowledgements: AIRC_IG2014-15839, RF-2016-02362532. Disclosures Mancuso: Celgene: Honoraria, Speakers Bureau; Amgen: Honoraria; Takeda: Honoraria; Janssen: Honoraria. Zamagni:Sanofi: Honoraria, Other: Advisory Board, Speakers Bureau; Celgene Corporation: Honoraria, Other: Advisory board, Speakers Bureau; Janssen: Honoraria, Other: Advisory board, Speakers Bureau; Amgen: Honoraria, Other: Advisory board, Speakers Bureau; BMS: Honoraria, Other: Advisory Board, Speakers Bureau; Takeda: Honoraria, Speakers Bureau. Tacchetti:Oncopeptides: Honoraria, Speakers Bureau; Takeda: Honoraria, Speakers Bureau; BMS: Honoraria; Celgene: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Janssen: Honoraria. Zinzani:CELGENE: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; PORTOLA: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; ROCHE: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; GILEAD: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; JANSSEN-CILAG: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; SERVIER: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; SANDOZ: Membership on an entity's Board of Directors or advisory committees; IMMUNE DESIGN: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; EUSAPHARMA: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; KYOWA KIRIN: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; SANOFI: Consultancy; MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CELLTRION: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; VERASTEM: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Cavo:janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

Multiple Myeloma (MM) maintenance therapy is a low intensive, prolonged treatment, commonly administered to newly diagnosed patients (pts) at the end of fixed-time, front-line regimens. Lenalidomide (LEN) is considered the best available maintenance option for MM able to prolong pts survival. However, the actual benefits or disadvantages of a LEN-based continuous maintenance and its potential role as selective pressure able to induce genomic changes are still unclear. The identification of specific therapy-driven modifications has been so far prevented by the scarce number of homogeneously-treated cohorts of pts with paired samples (diagnosis, D and relapse, R). In this study we estimated the role of LEN maintenance therapy in eliciting genomic changes in a cohort of MM pts homogeneously up-front treated with PI-based regimens. Whole genome Copy Number Aberrations (CNAs) landscape was obtained by SNPs array in 54 pts whose BM-CD138+ were collected both at D and at first R. Pts had an high-risk (HR) disease, as defined both by the presence of HR cytogenetic aberration at baseline in 81% of pts and by the 29 m median TTP. RawCopy 1.10 was used for the segmentation of SNPs array signals; samples' purity was adjusted by using manually reviewed ASCAT solutions. A custom gene-level CN calling approach was set up, to match every gene's CN value at D and R, thus generating genomic evolutive patterns based on changes of these values. Finally, high-risk genomic loci were computed using GISTIC 2.0_v7 to derive focal regions with oncogene and/or tumor suppressor genes relevant for MM biology. After induction therapy, 31/54 pts were treated with HD chemotherapy followed by either single or double ASCT; LEN maintenance therapy was then offered both to 20/31 auto-transplanted and to 6/23 not auto-transplanted pts. Three main evolutive trajectories (linear L, drift D, and branching B) were defined according to the CN changes' direction, reflecting a putative positive, negative, or both positive and negative selective pressure, respectively. A fourth, stable (S) trajectory was also observed, characterized by the absence of CN changes between D and R. Overall, 29, 15 and 10 pts relapsed with B/D, L and S pattern, respectively; at R, all LEN-treated pts quantitively and qualitatively changed their sub-clonal architecture: a B/D evolutive pattern characterized 70% of pts. By contrast, genome remained mostly stable in 61% of not-treated pts. We then focused on CN changes of specific chromosomal regions and/or genomic loci, whose prognostic role has been already established in MM (i.e. CN losses of TP53 on chr17p, RB1 on chr13q, CYLD on chr16q, CDKN2C and FAM46C on chr1p; CN gain of CKS1B on chr1q). When present at D these CNAs tended to persist throughout the disease course regardless of whether pts received or not maintenance. The emersion of any of these CNAs at R was widely observed both in pts receiving or not maintenance, whereas a negative selective pressure over them was more likely to occur in pts receiving maintenance, as compared to the others (50% vs 11% of B/D trajectories in LEN-treated vs not-treated pts, respectively). Strikingly, in LEN-treated pts, the extension of both TTP and OS was favored by the extinction and/or negative selection of the HR CNAs (B/D patterns), and shortened by their stability or positive selection (L/S patterns) (median TTP 46 vs 32 m HR=3,6 CI 1,2-10,6, p=0.01; median OS 111 vs 63 m HR 5,7 CI 1,1-32,4, p=0.04 in B/D vs L/S pts, respectively). On the contrary, the absence of maintenance selective pressure seemed to affect neither the evolution trajectory, nor the clinical course of not-treated pts (fig 1). The extinction of sub-clones carrying HR lesions in pts receiving maintenance therapy is likely to be associated to the negative selection exerted by the therapy itself. This might explain the extended survival of pts receiving maintenance and relapsing with B/D evolution patterns, as compared to that of pts whose genomic landscape either tended to remain stable or let the prevalent emersion of HR genomic features. On the contrary, the sub-clonal architecture of pts not receiving maintenance seemed to randomly evolve, due to the absence of a specific therapy-related selective pressure. Overall, information on the genomic changes occurring throughout the disease course might be relevant for the recognition of pts most benefitting from a continuous therapy. Thanks to AIRC_IG2014-15839, RF-2016-02362532 Disclosures Zamagni: Takeda: Honoraria, Speakers Bureau; Sanofi: Honoraria, Other: Advisory Board, Speakers Bureau; Janssen: Honoraria, Other: Advisory board, Speakers Bureau; Amgen: Honoraria, Other: Advisory board, Speakers Bureau; BMS: Honoraria, Other: Advisory Board, Speakers Bureau; Celgene Corporation: Honoraria, Other: Advisory board, Speakers Bureau. Tacchetti:BMS: Honoraria; Takeda: Honoraria, Speakers Bureau; Janssen: Honoraria; Oncopeptides: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau. Mancuso:Celgene: Honoraria, Speakers Bureau; Janssen: Honoraria; Takeda: Honoraria; Amgen: Honoraria. Petrucci:Janssen-Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Liberati:Incyte: Consultancy; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Bristol & Mayer: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Rossi:Roche: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Jazz: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Mundipharma: Honoraria; BMS: Honoraria; Sandoz: Honoraria. Boccadoro:Bristol-Myers Squibb: Honoraria, Research Funding; Mundipharma: Research Funding; Sanofi: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; AbbVie: Honoraria. Cavo:amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.