Abstract: Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. METHODS We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. Random-effects Cox proportional hazards multistate modeling was used for developing prognostic models. An independent validation on 318 cases was performed. RESULTS We identify eight MDS groups (clusters) according to specific genomic features. In five groups, dominant genomic features include splicing gene mutations ( SF3B1, SRSF2, and U2AF1) that occur early in disease history, determine specific phenotypes, and drive disease evolution. These groups display different prognosis (groups with SF3B1 mutations being associated with better survival). Specific co-mutation patterns account for clinical heterogeneity within SF3B1- and SRSF2-related MDS. MDS with complex karyotype and/or TP53 gene abnormalities and MDS with acute leukemia–like mutations show poorest prognosis. MDS with 5q deletion are clustered into two distinct groups according to the number of mutated genes and/or presence of TP53 mutations. By integrating 63 clinical and genomic variables, we define a novel prognostic model that generates personally tailored predictions of survival. The predicted and observed outcomes correlate well in internal cross-validation and in an independent external cohort. This model substantially improves predictive accuracy of currently available prognostic tools. We have created a Web portal that allows outcome predictions to be generated for user-defined constellations of genomic and clinical features. CONCLUSION Genomic landscape in MDS reveals distinct subgroups associated with specific clinical features and discrete patterns of evolution, providing a proof of concept for next-generation disease classification and prognosis.

Abstract: Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased risk of cancers and inflammation-related diseases. This phenomenon becomes common in persons aged ≥80 years, in whom the implications of CHIP are not well defined. We performed a mutational screening in 1794 persons aged ≥80 years and investigated the relationships between CHIP and associated pathologies. Mutations were observed in one-third of persons aged ≥80 years and were associated with reduced survival. Mutations in JAK2 and splicing genes, multiple mutations (DNMT3A, TET2, and ASXL1 with additional genetic lesions), and variant allele frequency ≥0.096 had positive predictive value for myeloid neoplasms. Combining mutation profiles with abnormalities in red blood cell indices improved the ability of myeloid neoplasm prediction. On this basis, we defined a predictive model that identifies 3 risk groups with different probabilities of developing myeloid neoplasms. Mutations in DNMT3A, TET2, ASXL1, or JAK2 were associated with coronary heart disease and rheumatoid arthritis. Cytopenia was common in persons aged ≥80 years, with the underlying cause remaining unexplained in 30% of cases. Among individuals with unexplained cytopenia, the presence of highly specific mutation patterns was associated with myelodysplastic-like phenotype and a probability of survival comparable to that of myeloid neoplasms. Accordingly, 7.5% of subjects aged ≥80 years with cytopenia had presumptive evidence of myeloid neoplasm. In summary, specific mutational patterns define different risk of developing myeloid neoplasms vs inflammatory-associated diseases in persons aged ≥80 years. In individuals with unexplained cytopenia, mutational status may identify those subjects with presumptive evidence of myeloid neoplasms.

Abstract: Myelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms in which a risk-adapted treatment strategy is needed. Recently, a new clinical-molecular prognostic model, the Molecular International Prognostic Scoring System (IPSS-M) was proposed to improve the prediction of clinical outcome of the currently available tool (Revised International Prognostic Scoring System [IPSS-R]). We aimed to provide an extensive validation of IPSS-M. METHODS A total of 2,876 patients with primary MDS from the GenoMed4All consortium were retrospectively analyzed. RESULTS IPSS-M improved prognostic discrimination across all clinical end points with respect to IPSS-R (concordance was 0.81 v 0.74 for overall survival and 0.89 v 0.76 for leukemia-free survival, respectively). This was true even in those patients without detectable gene mutations. Compared with the IPSS-R based stratification, the IPSS-M risk group changed in 46% of patients (23.6% and 22.4% of subjects were upstaged and downstaged, respectively). In patients treated with hematopoietic stem cell transplantation (HSCT), IPSS-M significantly improved the prediction of the risk of disease relapse and the probability of post-transplantation survival versus IPSS-R (concordance was 0.76 v 0.60 for overall survival and 0.89 v 0.70 for probability of relapse, respectively). In high-risk patients treated with hypomethylating agents (HMA), IPSS-M failed to stratify individual probability of response; response duration and probability of survival were inversely related to IPSS-M risk. Finally, we tested the accuracy in predicting IPSS-M when molecular information was missed and we defined a minimum set of 15 relevant genes associated with high performance of the score. CONCLUSION IPSS-M improves MDS prognostication and might result in a more effective selection of candidates to HSCT. Additional factors other than gene mutations can be involved in determining HMA sensitivity. The definition of a minimum set of relevant genes may facilitate the clinical implementation of the score.

Abstract: e16565 Background: Grading tissue signatures in ccRCC is a potential tool to improve patients’ selection for anti-angiogenic drugs and immunotherapies. After the molecular audit to the TCGA public platforms, we aimed to grade angiogenic and immune signatures in ccRCC using a new 3D next-generation gross sampling method to overcome intratumoral heterogeneity. Methods: 100 consecutive advanced ccRCCs (≥pT3a) were sampled. Paraffin-embedded blocks were obtained after mapping the position of each sample to the whole tumor, to allow the reconstruction of the entire 3D tumor mass ( fusion 3D). Multisite tumor sampling was performed to analyze the whole tumor. TCGA platforms were assessed for angiogenic and immune molecular signatures: CD31 and CD34 to evaluate the absolute count and density of vessels, while E1L3N and sp263 clones for PD-L1 expression in tumor cells (TCs). The digital analysis was performed with image processing: comparing each tissue block to whole 3D assessment, the coefficient of variation (CV) was the statistical measure of the dispersion of data points in the data series around the mean. CV 〈 0.2 defined the homogeneity of the assessment. Results: 656 gross photographs representative of the 3D tumoral masses were collected and 4231 paraffin blocks and tissue sections were stored. Matching gross photographs with tissue samples was performed. 6324 tissue cores were evaluated after combining standard routine sampling plus the 3D multisite sampling and tissue microarray cores. Only 18% of cores displayed homogeneous profile of angiogenesis (CV 〈 0.2) with two distinct patterns: homogeneous high level of angiogenesis (pattern A) (10% of cases) or homogeneous low level of angiogenesis (pattern B) (8% of cases). The heterogeneous profile of angiogenesis was more frequent than the homogeneous one and was characterized by zones with high and low density of angiogenesis (82% of cases) (pattern C). On the other hand, the homogeneity of PD-L1 expression was more frequently observed both as diffuse absence ( 〈 1% of TCs, grade 0) or high expression (≥50% of TCs, grade 2) compared to low PD-L1 expression (1-49% of TCs, grade 1) (60% plus 7% versus 33% of cases, respectively). After the comparison of grading angiogenic versus immune signatures, we observed that cases with low PD-L1 expression (grade 0/1) usually expressed high density of angiogenesis (pattern A). Conclusions: Grading angiogenic (pattern A, B and C) versus immune (grade 0, 1 and 2) signatures in ccRCCs can be performed using commonly available tissue vascular (CD31 or CD34) and immune (PD-L1) antibodies. We promoted a simple assay to perform fusion 3D gross sampling to reduce at minimum the bias of heterogeneity in RCCs analyses. Both angiogenic versus immune signature by using the grading systems may help treatment decision-making and response assessment in ccRCC patients.

Abstract: e16545 Background: The Meet-URO 18 study is ongoing to assess the prognostic role of I-TME in advanced RCC patients treated with ≥second line nivolumab divided into two cohorts according to clinical benefit [progression-free survival ≥ 12 and ≤ 3 months]. We primarily assessed the feasibility of multiple antibody testing related to I-TME on matched metastases and primary tumor. Methods: Immunohistochemical analyses were used for the TME assessment of T-lineage (CD3, CD4, CD8), FOXP-3, granulocytes (CD15), macrophage-lineage (CD68), natural killer (NK)-cells (CD56), tumor cells (TCs) (CD56), B-lineage (CD20) and phosphorylated mTOR (phmTOR). TCs were quantitatively assessed for CD15, CD56 and phmTOR positivity. For T-, B- and CD68 cells within TC nests, the number of immunoreactive cells were counted with a microscopic field of x200 (0.933 mm 2 ). Results: Overall, 42 tumor tissue samples (primary tumors, metastases) were available and for 17 patients both metastatic and primary tumor tissues were assessable for matched analyses. Among these patients, 12 had clear cell, 1 papillary and 4 mucinous tubular and spindle cell histotype according to WHO 2016 classification. Intratumoral T/CD8 cells ranged from 32 to 〉 400 spots (mean 240; 〉 400 in 7 samples) and intratumoral T/CD4 cells from 4 to 〉 400 spots (mean 168; 〉 400 in 5 samples). Nine samples showed absence of phmTOR expression, while 8 ranged from 10% to 90% of positive TCs. We did not observe countable NK-cells, whereas CD56 was visible in 5 samples (mean 55% of positive TCs). Intratumoral CD68 cells ranged from 34 to 〉 400 spots (mean 175, 〉 400 in 3 patients). Agreement of CD15 method of reporting granulocytic presence was high, thus only CD15 neoplastic expression was reported and ranged from 12% to 55% (mean 30%) in 15 patients. TME multiple analysis resulted equally clustered in 8 patients ( 〈 20% variability of single immuno-test) whereas the remaining 9 patients showed significant differences as percentage of immuno-tissue expression in at least one of the 5 immuno-indicators (T/CD8-CD4, C15, CD68, CD56, phmTOR). The remaining 8 samples of patients without matched analyses were used to test the feasibility of multiple analyses; among all antibodies exclusion of the CD20 and FOXP-3 final evaluation was needed, due to technical standardization. According to the 5 immuno-indicators, double-triple positive or penta-positive TME indicators may be identified and graded. Conclusions: Providing multiple immunoexpression platforms on a single specimen may be used as routine workflow. Profiling I-TME, especially CD56, CD15 on TCs and CD68 cells and phmTOR, deserves investigation with extensive control groups. A validation cohort will be tested at tissue level and in correlation with peripheral blood markers.

Abstract: Introduction Sex represents a major source of diversity among patients in terms of pathophysiology, clinical presentation, prognosis and response to therapy, and therefore sex (gender)-informed medicine is becoming a new paradigm to refine clinical decision making process in different human diseases. Myelodysplastic syndromes (MDS) are heterogeneous disease characterized by ineffective hematopoiesis and risk of leukemic evolution. We aimed to study clinical effect of sex in MDS as a basis to improve patient prognostication and personalized treatment. Material and Methods We analysed three MDS populations from disease-specific registries (Italian registry n=3015, Dusseldorf registry, n=1185 and Spanish registry, n=7678). Results We first analysed the association of sex with clinical and biological disease-specific features. These analyses were conducted on Italian MDS cohort. Considering WHO categories, female patients showed higher prevalence of single lineage dysplasia and MDS with del(5q), while males were characterized by higher frequency of multilineage dysplasia and excess blasts (P & lt;.001). Considering cytogenetic abnormalities, an increased frequency of del(5q) in female patients was observed (P & lt;.001). We analysed mutations in 47 MDS-associated genes. Males presented higher prevalence of mutations with respect to females (82.2% vs. 76.2%, P & lt;.001), with higher prevalence of co-mutations. Considering specific gene pathways, splicing factors mutations were reported more frequently in males vs. females (66% vs. 56%, P & lt;.001). Focusing on MDS with ring sideroblasts (MDS-RS), we noticed a significant different distribution of splicing factor mutations according to sex: SF3B1 was mutated in large majority of female patients (95% of mutated cases), while SRSF2 and ZRSR2 mutations accounts for a significant proportion (26%) of mutated cases in males. In addition, males showed higher prevalence of mutations in DNA methylation genes (P & lt;.001), while tumor suppressor genes (TP53) were more frequently mutated in female patients. Clustering analysis showed specific co-mutation patterns in splicing and DNA methylation genes according to sex. Overall survival was significantly worse for male vs. female patients (P & lt;.001). In a multivariable analysis including age, neutrophils, hemoglobin and platelet counts, percentage of marrow blasts and cytogenetics as covariate, sex showed an independent effect on probability of survival (HR for female vs. male patients 0.56, P=.012). The prognostic effect of sex was observed in very-low, low and intermediate risk category according to IPSS-R (Table 1). The independent prognostic effect of sex was confirmed in two independent populations (Dusseldorf and Spanish registries). Competitive risk analysis showed higher prevalence of non-leukemic vs. leukemic deaths (P & lt;.001) in patients with early disease stage. In these patients, we observed a higher prevalence of cardiac comorbidity/deaths in males vs. females (P & lt;.001 and P=.005, respectively). Moreover, the risk of non-leukemic death was higher in males vs. females especially when hemoglobin levels were & lt;10 g/dl. These results suggest that in MDS patients, sex may capture prognostic information on the detrimental interactions between anemia and cardiac comorbidity. As a final step we aimed to integrate the prognostic value of sex into currently available prognostic systems (IPSS-R). We used random effects Cox proportional-hazards multistate modelling for developing an innovative personalized prognostic model ("Sex and age-adjusted IPSS-R", IPSS-RAS). All the three study populations were included (n=11.878). The predicted and observed outcomes correlate well in internal cross-validation. IPSS-RAS substantially improved predictive accuracy of original IPSS-R (concordance 0.68 vs. 0.62), especially in patients with early disease stage. Interestingly, demographic factors (age and sex) accounted for & gt;30% of whole prognostic power. Conclusion In MDS, sex captures additional prognostic information at individual patient level, possibly reflecting a different molecular background and, most importantly, a sex-specific interaction between disease-related factors and comorbidity. Our results strengthen the rationale to include sex in personalized prognostic assessment in these diseases. Table 1 Disclosures Voso: Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Passamonti:Roche: Other: Support of parent study and funding of editorial support; Novartis: Speakers Bureau; BMS: Speakers Bureau. Santoro:Bristol-Myers Squibb, SERVIER, Gilead Sciences, Pfizer, Eisai, Bayer, MSD, Sanofi, ArQule: Consultancy; Takeda, Roche, Abbvie, Amgen, Celgene, AstraZeneca, ArQule, Lilly, Sandoz, Novartis, Bristol-Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, MSD: Speakers Bureau; Takeda, Roche, Abbvie, Amgen, Celgene, AstraZeneca, ArQule, Lilly, Sandoz, Novartis, Bristol-Myers Squibb, Servier, Gilead Sciences, Pfizer, Eisai, Bayer, MSD: Speakers Bureau; Arqule, Sanofi: Consultancy; Bristol-Myers Squibb, SERVIER, Gilead Sciences, Pfizer, Eisai, Bayer, MSD, Sanofi, ArQule: Consultancy, Speakers Bureau; Bristol-Myers Squibb, SERVIER, Gilead Sciences, Pfizer, Eisai, Bayer, MSD, Sanofi, ArQule: Consultancy; Bristol Myers Squibb, Servier, Gilead, Pfizer, Eisai, Bayer, MSD: Membership on an entity's Board of Directors or advisory committees. Santini:Menarini: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Acceleron: Consultancy; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria; Johnson & Johnson: Honoraria. Sanz:Takeda Pharmaceutical Ltd.: Membership on an entity's Board of Directors or advisory committees; LaHoffman Roche Ltd.: Membership on an entity's Board of Directors or advisory committees; Abbvie Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Helsinn: Membership on an entity's Board of Directors or advisory committees. Diez-Campelo:Celgene BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau.