The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases

IntroductionMinimal residual disease (MRD) is commonly assessed in bone marrow (BM) aspirate. However, sample quality can impair the MRD measurement, leading to underestimated residual cells and to false negative results. To define a reliable and reproducible method for the assessment of BM hemodilution, several flow cytometry (FC) strategies for hemodilution evaluation have been compared. MethodsFor each BM sample, cells populations with a well-known distribution in BM and peripheral blood - e.g., mast cells (MC), immature (IG) and mature granulocytes (N) - have been studied by FC and quantified alongside the BM differential count. ResultsThe frequencies of cells' populations were correlated to the IG/N ratio, highlighting a mild correlation with MCs and erythroblasts (R=0.25 and R=0.38 respectively, with p-value=0.0006 and 0.0000052), whereas no significant correlation was found with B or T-cells. The mild correlation between IG/N, erythroblasts and MCs supported the combined use of these parameters to evaluate BM hemodilution, hence the optimization of the ALLgorithMM. Once validated, the ALLgorithMM was employed to evaluate the dilution status of BM samples in the context of MRD assessment. Overall, we found that 32% of FC and 52% of Next Generation Sequencing (NGS) analyses were MRD negative in samples resulted hemodiluted (HD) or at least mildly hemodiluted (mHD). ConclusionsThe high frequency of MRD-negative results in both HD and mHD samples implies the presence of possible false negative MRD measurements, impairing the correct assessment of patients' response to therapy and highlighs the importance to evaluate BM hemodilution

C5 and SRGAP3 Polymorphisms Are Linked to Paediatric Allergic Asthma in the Italian Population

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

OAB-057: Temporal-weight estimation of the copy number alterations of of 1384 Multiple Myeloma patients defines an ancestrality index impacting patients survival

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<0.001).The risk attributed to this “ancestral” category was independent from other high-risk cytogenetic features (i.e. del17p, t(4;14), t(14;20), t(14;20)). 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

A Methodologically Updated De-Novo Extraction of Copy Number Signatures in Multiple Myeloma: Clinical Significance and Putative Aetiologies

BACKGROUND: The tumor genomes of most Multiple Myeloma (MM) patients are heavily burdened with highly heterogenous copy number (CN) alterations, as detected by multiple molecular methods including whole genome sequencing (WGS), and have been shown to have a strong prognostic and predictive significance for patients' survival. Cutting-edge computational developments have made it possible to analyze complex genomic CN changes by identifying CN alterations' recurrent patterns among large cohorts of patients, named CN signatures (CNS), that are the result of cumulative chromosomic instability (CIN) processes throughout the course of cancer cells evolution. In fact, a robust methodological framework for CNS computation, along with a large compendium of CNS aetiologies have been recently published for many cancer types, notably not including MM (Drews 2022). To our knowledge, the only study that analyzes CNS in MM focused on the role of CNS in predicting chromothripsis events, but remarkably it did not include neither CNS aetiologies nor complete CNS characterization for all the discovered CNS (Maclachlan 2021). AIM: To define a novel methodological framework, based on previous studies, aimed at the identification of CNS in MM, in order to assess both the aetiologies and the biological significance of MM CNS and to evaluate their prognostic impact on MM clinical outcome. The newly extracted CNS defined at diagnosis will be also used as novel disease biomarkers, to develop an improved, aetiology-based MM patients' stratification in different molecular subtypes. METHODS: We calculated the MM genomic distributions of the six essential CN features (segment length, breakpoint per 10 Mb, breakpoint per chromosome arm, segment CN change, CN value, length of oscillating CN states) that have been previously shown to encode patterns of CN alterations, underlying the observed tumor CIN. Starting from 886 WGS generated CN profiles, included in the CoMMpass study, the above mentioned features were computed. Features were then categorized into components, by using mixture models' decomposition and CNS were finally extracted from the components, by using both a Hierarchical Dirichlet Process (HDP) and a Non-Negative Matrix Factorization (NNMF) approach. RESULTS: The main novel characteristics of the developed methodological framework aimed at CNS assessment were 1) the use of a "continuous CN value" feature, which enabled the evaluation of sub-clonal events and 2) the use of a logarithmic scale in "segment length" feature, which favored a higher resolution for categorizing focal and/or gene level CN events, that are very common in MM. Thanks to these implementations, 33 Gaussian mixture components were identified (as compared to 28 detected in Maclachlan 2021). After deriving a Sample x Component - Sum of Posteriors Matrix, the signatures were extracted by applying two parallel state-of-art approaches, namely HDP and NNMF. This allowed the extraction of 9 CNS that were characterized by their component's composition. The signature's exposure levels were correlated to well-known MM biomarkers (e.g. TP53 mut and/or del, 1q CN gain, 13q CN loss, t-IgH, hyperdiploidy), showing that all signatures correlated to at least one of the well known MM biomarkers; in particular, CN.SIG5 exposures was found to correlate to high-risk MM biomarkers (TP53 p<0.001, 1q CN gain p<0.001, t(4;14) p<0.001), thus suggesting its possible involvement in the aetiology of this peculiar genomic configuration. Finally, a survival analysis was performed in patients characterized by high exposure (4th quartile) to the CN.SIG5 (75 patients), as compared to the others (811 patients), showing a significant negative impact of this CNS on both overall (OS p<0.001)) and progression free survivals (PFS p<0.001). Cox-analysis revealed an OS HR= 1.37 p<0.001, PFS HR= 1.16, p<0.001, per 5% increase in exposure. CONCLUSION: By employing a novel bio-informatic approach, based on the use of continuous CN data for CNS extraction, 33 feature's components were identified. We observed that CN.SIG5 significantly affected patients carrying well-known high-risk genomic features, and patients highly exposed to this CNS had decreased PFS and OS. Additional characterizations are needed to unveil the biological meaning of CNS exposure; however, MM CNS, while informing on disease outcome, might be considered as new comprehensive biomarkers in this disease

Female reproductive health and inflammatory bowel disease: A practice-based review

Inflammatory bowel diseases, namely ulcerative colitis and Crohn's disease, occur worldwide and affect people of all ages, with a high impact on their quality of life. Sex differences in incidence and prevalence have been reported, and there are also gender-specific issues that physicians should recognize. For women, there are multiple, important concerns regarding issues of body image and sexuality, menstruation, contraception, fertility, pregnancy, breastfeeding and menopause. This practice-based review focuses on the main themes that run through the life of women with inflammatory bowel diseases from puberty to menopause. Gastroenterologists who specialize in inflammatory bowel diseases and other physicians who see female patients with inflammatory bowel diseases should provide support for these problems and offer adequate therapy to ensure that their patients achieve the same overall well-being and health as do women without inflammatory bowel diseases. (c) 2021 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved

Studio di coorte prospettico multicentrico per la validazione italiana della Braden Q per la valutazione del rischio di lesioni da decubito nei neonati e nei bambini fino ad 8 anni

I bambini ricoverati in particolari contesti quali le terapie intensive, le oncologie e le neurologie/neurochirurgiche sono a rischio di sviluppare lesione da pressione. Obiettivo. Validare la versione italiana della Braden Q per la valutazione del rischio di sviluppare lesioni da pressione nei bambini. Metodi. La popolazione è costituita da bambini da 21 giorni agli 8 anni, ricoverati nelle terapie intensive e subintensive. Sono esclusi i bambini prematuri, i ricoverati con lesioni da pressione e anamnesi positiva per cardiopatie congenite. Lo studio è di coorte prospettico, multicentrico con valutazioni del rischio ripetute. La prima rilevazione è stata effettuata dopo 24 ore dal ricovero, con la Braden Q nella versione di Suddaby. Le lesioni da pressione sono state valutate con la Skin Assessment Tool (SAT) e stadiate secondo la National Pressure Ulcer Advisory Panel. Risultati. Su 157 casi sono state eseguite 524 osservazioni. L’incidenza delle lesioni da pressione è del 17.2%. Solo l’analisi per specifiche sottocategorie rileva una buona accuratezza diagnostica: nei bambini dai 3 agli 8 anni l’accuratezza è del 71.4%; nei reparti di terapia sub-intensiva è dell’85.6%. Il valore massimo dell’accuratezza diagnostica (86.2%) è con i bambini dai 3 agli 8 anni ricoverati nei reparti sub intensivi. Conclusione. La scala Braden Q può essere usata affidabilmente ed ha buoni valori di accuratezza diagnostica con i bambini da 3 a 8 anni ricoverati nelle terapie sub-intensive, nei reparti di oncologia o di onco-ematologia pediatrica e di neurologia infantile

Circulating Multiple Myeloma Cells (CMMCs) as Prognostic and Predictive Markers in Multiple Myeloma and Smouldering MM Patients

In recent years, liquid biopsy has emerged as a promising alternative to the bone marrow (BM) examination, since it is a minimally invasive technique allowing serial monitoring. Circulating multiple myeloma cells (CMMCs) enumerated using CELLSEARCH (R) were correlated with patients' prognosis and measured under treatment to assess their role in monitoring disease dynamics. Forty-four MM and seven smouldering MM (SMM) patients were studied. The CMMC medians at diagnosis were 349 (1 to 39,940) and 327 (range 22-2463) for MM and SMM, respectively. In the MM patients, the CMMC count was correlated with serum albumin, calcium, beta 2-microglobulin, and monoclonal components (p < 0.04). Under therapy, the CMMCs were consistently detectable in 15/40 patients (coMMstant = 1) and were undetectable or decreasing in 25/40 patients (coMMstant = 0). High-quality response rates were lower in the coMMstant = 1 group (p = 0.04), with a 7.8-fold higher risk of death (p = 0.039), suggesting that continuous CMMC release is correlated with poor responses. In four MM patients, a single-cell DNA sequencing analysis on residual CMMCs confirmed the genomic pattern of the aberrations observed in the BM samples, also highlighting the presence of emerging clones. The CMMC kinetics during treatment were used to separate the patients into two subgroups based on the coMMstant index, with different responses and survival probabilities, providing evidence that CMMC persistence is associated with a poor disease course

Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients

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

Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features

Abstract The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients’ clinical outcome. Patient’s prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition high- from low-risk patients, preventing the reliable recognition of early relapsing/refractory patients. By a dimensionality reduction approach, here we dissect the genomic landscape of a large cohort of newly diagnosed MM patients, modelling all the possible interactions between any MM chromosomal alterations. We highlight the presence of a distinguished cluster of patients in the low-dimensionality space, with unfavorable clinical behavior, whose biology was driven by the co-occurrence of chromosomes 1q CN gain and 13 CN loss. Presence or absence of these alterations define MM patients overexpressing either CCND2 or CCND1, fostering the implementation of biology-based patients’ classification models to describe the different MM clinical behaviors