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  • 1
    In: Blood, American Society of Hematology, Vol. 116, No. 21 ( 2010-11-19), p. 2951-2951
    Abstract: Abstract 2951 Background: The identification of stereotyped immunoglobulin (IG) receptors has improved our knowledge on the pathogenesis of several B-cell malignancies, suggesting the role of antigen-driven stimulation in chronic lymphocitic leukemia (CLL), marginal-zone lymphoma (MZL) and mantle-cell lymphoma (MCL). Multiple myeloma (MM) is a terminally-differentiated neoplasm no longer expressing surface IG; however some reports suggest the existence of early B-lymphocyte precursors which could be susceptible to antigen-driven stimulation. IG heavy chain (IGH) repertoire has not been extensively investigated in MM, with the largest available reports containing less than 80 complete sequences. Aims: To address this issue we created a database of MM IGH sequences including our institutional records (mostly derived from minimal residual disease studies) and sequences available from the literature. We planned a two-step analysis: a) first we characterized the MM repertoire and performed intra-MM clustering analysis; b) then we compared our MM series to a large public database of IGH sequences from neoplastic and non-neoplastic B-cells in search of similarities between MM sequences and other normal or neoplastic IGH repertoires. Patients and methods: 131 MM IGH genes were amplified and sequenced at our Institutions and belonged to Italian patients, while 214 MM IGH sequences from non-Italian patients were derived from published databases (NCBI-EMBL-IMGT/LIGM-DB) for a total of 345 fully interpretable MM sequences (out of 396). 28590 IGH sequences from other malignant and non-malignant B-cells were retrieved from the same public databases, including approximately 4500 CLL/Non-Hodgkin lymphoma (NHL) sequences and comprising 500 sequences from Italian patients. All sequences were analyzed using the IMGT database and tools (Lefranc et al., Nucleic Acid Res. 2005; http://imgt.cines.fr/) to identify IGHV-D-J gene usage, to assess the somatic hypermutation (SHM) rate and to identify HCDR3. HCDR3 aminoacidic sequences were aligned together using the ClustalX 2.0 software (Larkin et al., Bioinformatics, 2007; http://www.clustal.org/). Subsets of stereotyped IGH receptors were defined according to Stamatopoulos et al. (Blood, 2007). Result: IGHV analysis in MM was almost in keeping with the normal B-cell repertoire, showing a less remarkably biased IGH usage compared to CLL, MCL and MZL (with seven genes accounting for 40% of cases, compared to respectively five, three and two genes). However, a modest but significant over-representation of IGHV1-69, 2–5, 2–70, 3–21, 3–30-3, 3–43, 5–51 and 6-1 genes and under-representation of the IGHV1-18, 1–8, 3–30, 3–53 and 4–34 was noticed. The rate of somatic hypermutation in MM followed a Gaussian distribution with a median value of 7.8%. Intra-MM search for HCDR3 similarities never met minimal requirements for stereotyped receptors. When MM sequences were compared to non-MM database, only a minority of MM sequences (2.6%, n=9) clustered with sequences from lymphoid tumors and normal B-cells (figure 1A). In particular two non-Italian MM sequences clustered with previously characterized, uncommon CLL subsets (n.37 and n.71 according to Murray et al., Blood 2008). Moreover, novel provisional clusters were observed including three MM-CLL subsets, one MM-NHL subset, and three MM-normal B-cell subsets. While the MM-normal B-cell clusters involved non-Italian patients, we unexpectedly noticed that the four MM-CLL/MM-NHL clusters were composed exclusively of Italian patients, as shown in figure 1B, although Italian subjects represented less than 12% of the entire CLL-NHL database. Conclusion: The analysis of the largest currently available database of MM IGH sequences indicates the following: 1) MM IGH repertoire is closer to physiological distribution than that of CLL, MCL and MZL; 2) MM specific clusters do not occur to a frequency detectable with currently available databases; 3) 98% of MM sequences are not related to other “highly-clustered” lymphoproliferative disorders; 4) Uncommon clustering phenomena may follow a geographical rather than a disease-related pattern. Disclosures: No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2010
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  • 2
    In: American Journal of Roentgenology, American Roentgen Ray Society, Vol. 210, No. 1 ( 2018-01), p. 24-29
    Type of Medium: Online Resource
    ISSN: 0361-803X , 1546-3141
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    Language: English
    Publisher: American Roentgen Ray Society
    Publication Date: 2018
    detail.hit.zdb_id: 2012224-X
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  • 3
    In: La radiologia medica, Springer Science and Business Media LLC, Vol. 124, No. 7 ( 2019-7), p. 628-635
    Type of Medium: Online Resource
    ISSN: 0033-8362 , 1826-6983
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2225828-0
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  • 4
    In: Journal of Neuroimaging, Wiley, Vol. 29, No. 4 ( 2019-07), p. 527-535
    Abstract: Brain atrophy accelerates at the age of 60 in healthy individuals (HI) and at disease onset in multiple sclerosis (MS) patients. Whether there is an exacerbating effect of aging superimposed on MS‐related brain atrophy is unknown. We estimated the aging effect on lateral ventricular volume (LVV) and whole brain volume (WBV) changes in MS patients. METHODS 1,982 MS patients (mean follow‐up: 4.8 years) and 351 HI (mean follow‐up: of 3.1 years), aged from 20 to 79 years old (yo), were collected retrospectively. Percent LVV change (PLVVC) and percent brain volume change (PBVC) on 1.5T and 3T MRI scanners (median of 3.9 scans per subject) were calculated. These were determined between all‐time points and subjects were divided in six‐decade age groups. MRI differences between age groups were calculated using analysis of covariance (ANCOVA). RESULTS Compared to HI, at first MRI, MS patients had significantly increased LVV in the age groups: 30–39 yo, 40–49 yo, 50–59 yo, 60–69 yo (all P 〈 .0001), and 70–79 yo ( P = .029), and decreased WBV in the age groups: 20–29 yo ( P = .024), 30–39 yo ( P = .031), 40–49 yo, and 50–59 yo (all P 〈 .0001). Annualized PLVVC was significantly different between the age groups 20–59 and 60–79 yo in MS patients ( P = .005) and HI ( P 〈 .0001), as was for PBVC in MS patients ( P = .001), but not for HI ( P = .521). There was a significant aging interaction effect in the annualized PLVVC ( P = .001) between HI and MS patients, which was not observed for the annualized PBVC ( P = .380). CONCLUSIONS Development of brain atrophy manifests progressively in MS patients, and occurs with a different pattern, as compared to aging HI. PLVVC increased across age in HI as compared to MS, while PBVC decreased across ages in both HI and MS.
    Type of Medium: Online Resource
    ISSN: 1051-2284 , 1552-6569
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2035400-9
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