Skip to main content

Microarray expression studies on bone marrow of patients with Shwachman-Diamond syndrome in relation to deletion of the long arm of chromosome 20, other chromosome anomalies or normal karyotype

Abstract

Background

Clonal chromosome changes are often found in the bone marrow (BM) of patients with Shwachman-Diamond syndrome (SDS). The most frequent ones include an isochromosome of the long arm of chromosome 7, i (7)(q10), and an interstitial deletion of the long arm of chromosome 20, del (20)(q). These two imbalances are mechanisms of somatic genetic rescue. The literature offers few expression studies on SDS.

Results

We report the expression analysis of bone marrow (BM) cells of patients with SDS in relation to normal karyotype or to the presence of clonal chromosome anomalies: del (20)(q) (five cases), i (7)(q10) (one case), and other anomalies (two cases). The study was performed using the microarray technique considering the whole transcriptome (WT) and three gene subsets selected as relevant in BM functions. The expression patterns of nine healthy controls and SDS patients with or without chromosome anomalies in the bone marrow showed clear differences.

Conclusions

There is a significant difference between gene expression in the BM of SDS patients and healthy subjects, both at the WT level and in the selected gene sets. The deletion del (20)(q), with the EIF6 gene consistently lost, even in patients with the smallest losses of material, changes the transcription pattern: a low proportion of abnormal cells led to a pattern similar to SDS patients without acquired anomalies, whereas a high proportion yields a pattern similar to healthy subjects. Hence, the benign prognostic value of del (20)(q). The case of i (7)(q10) showed a transcription pattern similar to healthy subjects, paralleling the positive prognostic role of this anomaly as well.

Background

Shwachman-Diamond syndrome (SDS) is an autosomal recessive disorder (Online Mendelian Inheritance in Man #260400) characterized by bone marrow failure, peripheral cytopenias and an increased risk of developing myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML). The patients exhibit several other anomalies, including cognitive impairment [1]. SDS is caused by mutations in the SBDS gene in at least 90% of cases [1], but it is genetically heterogeneous. In addition to other functions, the SBDS protein has a pivotal role in ribosome biogenesis [1]. Furthermore, biallelic mutations of two other genes involved in ribosome biogenesis may cause SDS or an SDS-like condition: DNAJC21 [2, 3] and EFL1 [4]. Moreover, an SDS-like phenotype may be caused by monoallelic mutations in the SRP54 gene, which produces a protein that is a key member of the cotranslation protein-targeting pathway [5]. Therefore, SDS may be considered a ribosomopathy.

Clonal chromosome changes are often found in the bone marrow (BM) of patients with SDS. Among them, the most frequent ones include an isochromosome of the long arm of chromosome 7, i (7)(q10), and an interstitial deletion of the long arm of chromosome 20, del (20)(q) [6]. We already postulated that the presence of del (20)(q), with the loss of the EIF6 gene, results in more efficient ribosome biogenesis and implies both a lower risk of MDS/AML [7] and a milder haematological condition compared to SDS patients without del (20)(q) [8, 9].

The literature offers quite a few expression studies on SDS. Some of them concern the expression of specific genes in SBDS knocked-down cell lines (HeLa, NIH3T3) or in BM cells of SDS patients. These studies reveal interesting results; however, the scope of the presented work is limited to a few sets of considered genes [10,11,12]. We also remark that in some cell lines, such as HeLa, the results of expression analysis might be altered due to high variability of genomic instability and expression profiling among different batches, to the point that some results may be not completely reliable [13]. More extensive expression studies on BM from SDS patients and on other modified cell lines led to the detection of a series of genes that are up- or downregulated. Among those gene sets, many are important in leukaemia pathogenesis or ribosome biogenesis and function [14, 15]. Possible chromosome anomalies were not considered in all those studies.

The benign prognostic role of del (20)(q) that is acquired in BM prompted us to perform an expression study on the BM of patients with del (20)(q) even at the level of the whole transcriptome. In these patients, we report the expression analysis of the EIF6 gene, of the whole genome, and of gene sets selected as relevant in haematopoiesis, myeloid leukaemias, or myeloid differentiation. These results are compared with those obtained from patients who exhibit other clonal chromosome anomalies or show a normal karyotype in relation to healthy controls.

Results

Out of the total 17 patients with SDS, chromosome anomalies were found in eight, and their cytogenetic results, at the date of sampling for RNA study, are summarized in Table 1. All patients are identified by their unique patient number (UPN). The clonal del (20)(q) was present in five patients (UPN 6, 13, 20, 68, 85) encompassing the EIF6 gene in all samples, as demonstrated by array-based comparative genomic hybridization (a-CGH), the i (7)(q10) in one patient (UPN 24) and a clonal unbalanced translocation t(1;16) in one patient (UPN 58). The a-CGH analysis showed that the del (20)(q) in UPN 13 was smaller in the 2017 sample than that in the 2015 sample. One patient (UPN 92), the only one who developed AML, showed clones with complex abnormal karyotypes, with structural anomalies, not better defined, involving chromosomes 1, 2, 3, 5, 8, 10, 11 and 12. Table 1 also provides the percentage of abnormal cells at the date of BM sampling for transcription analysis. These percentages were inferred either from the results of fluorescent in situ hybridization (FISH) on nuclei with informative probes or from the results of a-CGH with the appropriate formula [17] or from chromosome analysis (in one patient).

Table 1 Clonal chromosome anomalies in BM, and percentage of abnormal cells at the date of sampling for RNA study

In nine patients, no anomalies were present in the BM at the date of sampling for RNA study, according to the available results of chromosome analyses, FISH with probes informative for i (7)(q10) and del (20)(q), and a-CGH (UPN 2, 26, 45, 51, 60, 70, 80, 81, 91). In this paper, we designated these patients as SDS-NK (normal karyotype) patients.

In the context of expression studies, we extrapolated the EIF6 RNA levels from the array raw data, and they are shown in Fig. 1a. The mean and the standard error for the expression levels of the nine normal controls and the nine SDS-NK patients are reported in black and grey bars, respectively, whereas the other bars refer to single patient specimens. Figure 1b shows the log2 heatmap for EIF6 expression levels.

Fig. 1
figure1

EIF6 expression. a EIF6 normalized expression extrapolated from array raw data. The expression values for the single probe A_23_P210939, included in the array used have been extrapolated by the imported log2 raw data with baseline normalization. Values of each specimen has been 2-power exponentially transformed in order to obtain the linear values. b The log2 heatmap for EIF6 expression. The patients’ samples are indicated at the bottom and their chromosome anomalies are inserted in the histogram bars, with the percentage of abnormal cells. The black and grey bars refer to the average value of the nine controls and the nine SDS-NK patients; the standard error is indicated

Whole transcriptome (WT) results were analysed by principal component analysis (PCA) from both SDS patients (with and without chromosome anomalies) and controls. The graph showing PCA for all the subjects under study is shown in Fig. 2. A trend indicating the stratification of patients in groups is appreciable. WT cluster analysis led to the dendrogram shown in Fig. 3.

Fig. 2
figure2

Principal Component Analysis (PCA) plot for the whole transcriptome. Healthy controls are indicated by red squares. SDS-NK patients are indicated by light-blue squares. Patients with chromosomal anomalies are identified by their UPN number and the year of the sample near the related colored squares. Component 1 and 2 percentages of variance are indicated in the two axes. The black ellipse indicates the 95% confidence interval

Fig. 3
figure3

Dendrogram of cluster analysis for the whole transcriptome. Two groups (1 and 2) may be identified. Healthy controls are in red and SDS-NK patients are indicated in light blue with their UPN number. Patients with chromosome anomalies are in black with their UPN number and sample (year), followed by the chromosome anomaly and the percentage of abnormal cells

We analysed some specific gene sets by PCA and cluster analysis (Additional file 1: Figures S1, S2, S3, S4, S5 and S6), chosen as relevant in haemopoiesis and leukaemogenesis:

  1. 1)

    Gene set 1: KEGG Haematopoietic Cell Lineage (map 04640): this pathway is composed of 88 genes, the major portion belonging to cytokines, growth factors and cell differentiation markers that drive the differentiation process of the haematopoietic cell lineage [18].

  2. 2)

    Gene set 2: KEGG Acute Myeloid Leukemia (map 05221): this pathway is composed of 60 genes belonging to oncogenes, protein kinases, tumour suppressor genes, translocation cancer genes and transcription factors that might be deregulated in acute myeloid leukaemia patients [19].

  3. 3)

    Gene set 3: Gene Ontology Myeloid Leukocyte Differentiation (GO:0002573): this pathway is composed of 96 genes that drive a relatively unspecialized myeloid precursor cell to acquire the specialized features of any cell of the myeloid leukocyte lineage [20].

The analysis was performed with the same approach as WT for the three gene sets, and Table 2 summarizes a comparison among the results obtained in the patients with chromosome changes with those of the groups defined by PCA and cluster analyses of WT.

Table 2 Transcription study of the selected gene sets relevant in haematopoiesis, leukaemogenesis and myeloid differentiation, identified as 1, 2, and 3 and described in the Results Section: comparison of the results obtained in patients with clonal anomalies (Table 1), grouped here as A and B. Group A includes most healthy controls and Group B all SDS-NK patients. Patient UPN 92, with AML and complex karyotype is not included in the Table, because her expression profile was different from all other subjects investigated and outside the groups identified

Discussion

The nine SDS-NK patients showed levels of EIF6 RNA slightly but significantly decreased in comparison to the nine healthy controls (Student’s t test: p = 0.02). All patients carrying the del (20)(q) showed a more remarkable decrease compared to the healthy controls, with a trend related to the proportion of cells containing the deletion (Table 1, Fig. 1a). We postulate that low RNA levels lead to decreased amounts of EIF6 protein, even if we did not have enough material to prove it. The patient UPN 24, carrying i (7)(q10), exhibits normal EIF6 levels as expected, as does UPN 58 (with another different chromosome anomaly) (Fig. 1a). The patient with AML and a complex karyotype, UPN 92, exhibited increased levels of EIF6 (Fig. 1a); it is worth noting that numerous studies have demonstrated highly aberrant overexpression of EIF6 in human cancer [21].

In the WT study, the stratification of SDS patients shown by PCA offers some relevant conclusions. In particular (Fig. 2), the SDS-NK patients (light blue squares) group on the left, while the controls (red squares) are more dispersed, and most of them are far from the SDS-NK group. We recall that we worked on RNA extracted from whole marrow samples containing heterogeneous populations of cells; this may explain the lack of strictly homogeneous results in controls. The result, however, indicates that the WT expression pattern of these two groups is truly different. The difference from controls is in agreement with data already reported, but these reports were limited to leukaemia-related genes [14], apoptosis-related genes [10], ribosome biogenesis and RNA processing genes, and other specific genes relevant for SDS phenotype [11, 12, 15] without any relation to the presence of clonal chromosome anomalies.

The patients carrying the del (20)(q), which encompasses the EIF6 gene in all cases, are indicated in Fig. 2 by squares of other colours, and they are distributed in the plot partially in agreement with the different percentage of cells of the abnormal clone.

Among these patients, the percentage of abnormal BM cells of UPN 68 and UPN 85 was rather low (Table 1), EIF6 expression was only slightly reduced (Fig. 1a), and the PCA plots these BM samples were near the SDS-NK group. Therefore, these two patients with a small number of cells with del (20)(q) show a WT expression pattern similar to SDS-NK patients.

In contrast, patients UPN 6 and UPN 20 (sample 2013), who carry a high proportion of cells with del (20)(q) in the BM (Table 1), with evident decreased levels of EIF6 transcript (Fig. 1a), are plotted in the PCA graph rather distantly from SDS-NK patients. The other two specimens of UPN 20 (sampled in 2015 and 2017, with similar del (20)(q) cell proportions and EIF6 hypoexpression patterns) are plotted closer to the SDS-NK group. This patient also carried a subclone with a further rearrangement of the del (20)(q), with deletion of the short arm and portions of the chromosome duplicated and deleted [16]. The proportion of this subclone increased from 2013 to 2017, while neutropenia worsened: the difference in expression might be due to this subclone. We postulate that the loss of EIF6 protein was enough to give a transcription pattern similar to controls in 2013 but was less effective in 2015 and 2017. This could explain the different plots of the sample UPN 20–2013 from UPN 20–2015 and UPN 20–2017. The patient UPN 13 exhibited an unexpected pattern for the two specimens from 2013 and 2015. In particular, the UPN 13–2015 sample has a low number of cells with del (20)(q) (Table 1), and EIF6 expression is only slightly reduced (Fig. 1a). It is plotted in the PCA far from the SDS-NK group. In contrast, specimen UPN 13–2013, with a high proportion of cells with del (20)(q) and a remarkably low level of EIF6 transcript, is plotted closer to the SDS-NK group. In fact, patient UPN 13 showed two different extents of the deletion in these two different specimens (Table 1). This could explain the differences in the PCA plots.

In general, these data indicate that patients with a high proportion of cells containing del (20)(q) show a WT expression pattern similar to healthy controls in the absence of further changes that may modify the pattern. The positive prognostic role of del (20)(q) would be a consequence of this type of rescue mechanism [8, 9], although it would be limited to cases with a high proportion of abnormal cells [22].

Patient UPN 24, with the i (7)(q) present in ~ 30% of the cells (Table 1), is plotted by the PCA algorithm far from the SDS-NK group. In the isochromosome, the SBDS gene is present twice in the form of the mild mutation 258 + 2 T > C, and this fact leads to a different form of rescue mechanism in ribosome biogenesis, impaired by SBDS mutations, thanks to some amount of normal SBDS protein [23]. UPN 58, with specimens in 2014 and 2017, carries an unbalanced complex rearrangement that involves chromosomes 1 and 16 (Table 1). The two samples of this patient are plotted differently in the graph. We have no clear-cut explanation for this result, but in conditions different from SDS, gene effects of unbalanced chromosome anomalies may be detected and cause specific pathologic features [24]. The only patient that developed AML (UPN 92) has a complex karyotype (Table 1) and is plotted in the PCA graph far from all the other patients and outside the 95% confidence interval (Fig. 2).

The dendrogram shown in Fig. 3 resembles the PCA plots of Fig. 2. The interconnection lines identify two groups (1 and 2) with similar distribution to the PCA plot commented above.

The transcription study of the selected groups of genes relevant in haematopoiesis, leukaemogenesis and myeloid differentiation defined in the Results section gave results in PCA largely similar to WT: SDS-NK constitute a well-defined group in all gene sets, while most healthy controls do not constitute a real group and are more dispersed in the plot (Additional file 1: Figures S1, S3 and S5). Cluster analysis based on dendrogram diagrams and related heatmaps confirmed this difference, with particular evidence for gene sets 1 and 2 (Additional file 1: Figures S2, S4 and S6).

Regarding patients carrying clonal chromosome changes, Table 2 shows a comparison of their results with healthy donors and SDS-NK patients. Most patients carrying del (20)(q) at low percentages fall in the group of SDS-NK patients for all gene sets (group B in Table 2), which is expected because EIF6 RNA in these patients is close to normal levels and cannot lead to a rescue of the altered SBDS pathway. On the other hand, most of the patients with higher percentages of del (20)(q) fall closer to healthy controls (group A in Table 2), as expected by the rescue mechanism postulated when the level of EIF6 is reduced. Few exceptions are present, and the explanation would be as for WT. Additionally, the only patient with i (7)(q10) falls in the group of the healthy controls, as expected, by the other rescue mechanism described [23].

The following points about the three gene sets analysed are worth highlighting.

  • Gene set 1: An interesting subset of genes, including the oncogene KIT, THPO (Thrombopoietin), EPO (erythropoietin), GP1BA (Glycoprotein 1b Platelet Subunit Alpha), and some cytokines, are upregulated in controls and downregulated in SDS-NK patients (Additional file 1: Figure S2). Another group involving many cluster differentiation (CD) genes and other cytokines is upregulated in the SDS-NK group and downregulated in controls.

  • Gene set 2: The cluster analysis (Additional file 1: Figure S4) firmly indicates a group of genes, including oncogenes and transcription factors, that are upregulated in controls and downregulated in SDS-NK.

  • Gene set 3: The cluster analysis also showed that the gene ANXA2 is extremely downregulated in the healthy controls, while it is expressed within the baseline level in the SDS-NK group (Additional file 1: Figure S6). ANXA2 is frequently upregulated in many types of cancers [25]. A group of genes (IL31RA, TNFSF11, TNFSF11A, KIT, CSF1, CSF2, CSF3, IL25, GPC3, FARP2, EFNA2, EPHA2, BMP4, CASP10) is upregulated in healthy controls and, interestingly, in UPN 6, UPN 13–2015, UPN 20–2013, with del (20)(q), in UPN 24, with i (7)(q10), and in UPN 58–2014, with the der (16)(t(1;16). These genes are transcription factors, oncogenes, cytokines, signal transduction genes, growing factors and apoptotic regulators; they play an important role in many biological systems, including leukocyte differentiation, bone morphogenesis, and macrophage differentiation.

Conclusions

In summary, our transcription study shows the following:

  • There is a difference between gene expression in BM of SDS patients and healthy subjects, both at the level of WT and that of selected gene sets relevant for BM functions;

  • In SDS patients, the presence of clonal chromosome anomalies also makes the difference at the transcription level;

  • The deletion del (20)(q), with the loss of EIF6 gene, present even in the smallest deletions, changes the transcription pattern of BM: a low proportion of abnormal cells led to a pattern similar to SDS patients without acquired chromosome anomalies, whereas a high proportion exhibit a pattern similar to healthy subjects; hence, the benign prognostic value of the del (20)(q) which has already been demonstrated in many patients [8];

  • The single case of i (7)(q10) included in this study showed a benign transcription pattern, similar to healthy subjects, paralleling the already established positive prognostic role of this anomaly as well;

  • Too little is known about other acquired clonal anomalies to reach any relevant conclusions for prognosis.

Methods

Patient selection and sample preparation

The materials for our study consisted of 23 BM samples from 17 patients with SDS, as in four cases the analysis was repeated at two different dates (two cases) or three (two other cases). The patients included three females and 14 males, with an age range of 2–44 years at the time of sampling for RNA analysis. All patients are part of the cohort of 97 Italian patients who have been followed for cytogenetics since 1999. All patients had biallelic mutations in the SBDS gene, including 14/17 cases with the two most frequent mutations. Some analyses were repeated at different dates in subsequent years, as the proportion of abnormal cells may vary considerably in time. A portion of the cytogenetic results has already been reported [16, 22, 26,27,28]. Table 1 gives the years of the cytogenetic analyses performed at the time of sampling for expression studies. All patients are identified by their UPN, as in our previous publications. We reported and discussed the haematological parameters of the patients with del (20)(q) [8], although the sampling date is often not the same as the present RNA study. Some additional haematological data of all the SDS patients reported here are provided in Additional file 2: Table S1.

Nine healthy subjects were used as controls, and their BM was drawn because they were donors for haematopoietic stem cell transplantation (HSCT).

Informed consent for this study was obtained according to the principles of the Declaration of Helsinki from the patients or the patients’ parents.

Chromosome analyses were performed on BM with routine methods. FISH on BM nuclei was carried out by standard techniques with the following bac probes, informative for the deletion del (20)(q) detected in each patient: RP11-17F3 (UPN 6, 13, 20), CTD-2559C9 (UPN 13), XL Del(20q) probe (Metasystems, Altlussheim, Germany) (UPN 68), RP11-17F3 + RP11-29E13 (UPN 85).

The a-CGH was performed on DNA from BM samples with the 244 K genome-wide system (Agilent Technologies Inc., Santa Clara, CA, USA) according to the manufacturer’s instructions, as already described [29]. All DNA was extracted from BM using a liquid-based Flexigene kit (Qiagen, Hilden, Germany) as recommended by Nacheva et al., 2017 [30].

For expression analysis of patients with SDS and controls, 2 ml of BM material was immediately pipetted into a PAXgene Bone Marrow RNA Tube (Qiagen, Hilden, Germany). The extraction was performed with the PAXgene Bone Marrow RNA Kit (Qiagen, Hilden, Germany). RNA integrity was assessed by Agilent’s Bioanalyzer 2100 instrument (Agilent Technologies, Santa Clara, USA) according to the manufacturer’s instructions. All the RNA samples used in this study exhibited an RNA Integrity Number (RIN) [31] above 8.0.

Whole transcriptome microarray and bioinformatical analysis

We used the Agilent Microarray System (Agilent Technologies, Santa Clara, USA) to perform microarray expression profiling according to Agilent’s One-Color Microarray-Based Gene Expression Analysis Low Input Quick Amp Labelling Protocol (Version 6.9.1) with Agilent’s Whole Transcriptome (WT) Oligo Human Microarray slides 8 × 60 K format (G4851A, AMADID #028004).

Data analysis was performed using Agilent GeneSpring 14.9.1 software. Data from each sample were imported into the software with the following parameters: Threshold: 1, Logbase: 2, Normalization: Shift to 75.0 percentile, Baseline Transformation: median of all samples.

Clustering analysis was performed by hierarchical analysis on normalized intensity values with Euclidean Distance Metrics and Ward’s linkage rules both on all genes as well as on selected gene sets. PCA was performed by the internal software plugin both with all genes as well as on selected gene sets.

Availability of data and materials

The data used and analyzed in the current study are available from the corresponding author on reasonable request.

Abbreviations

a-CGH:

Array-based comparative genomic hybridization

AML:

Acute myeloid leukaemia

BM:

Bone marrow

DNA:

Deoxyribonucleic acid

FISH:

Fluorescent in situ hybridization

HSCT:

Haematopoietic stem cell transplantation

MDS:

Myelodysplastic syndrome

PCA:

Principal component analysis

RIN:

RNA integrity number

RNA:

Ribonucleic acid

SDS:

Shwachman Diamond syndrome

SDS-NK:

SDS with normal karyotype

UPN:

Unique patient number

WT:

Whole transcriptome

References

  1. 1.

    Warren AJ. Molecular basis of the human ribosomopathy Shwachman-diamond syndrome. Adv Biol Regul. 2018;67:109–27.

    CAS  Article  Google Scholar 

  2. 2.

    Dhanraj S, Matveev A, Li H, et al. Biallelic mutations in DNAJC21 cause Shwachman-diamond syndrome. Blood. 2017;129:1557–62.

    CAS  Article  Google Scholar 

  3. 3.

    D’Amours G, Lopes F, Gauthier J, et al. Refining the phenotype associated with biallelic DNAJC21 mutations. Clin Genet. 2018;94:252–8.

    Article  Google Scholar 

  4. 4.

    Stepensky P, Chacón-Flores M, Kim KH, et al. Mutations in EFL1, an SBDS partner, are associated with infantile pancytopenia, exocrine pancreatic insufficiency and skeletal anomalies in a Shwachman-diamond like syndrome. J Med Genet. 2017;54:558–66.

    CAS  Article  Google Scholar 

  5. 5.

    Carapito R, Konantz M, Paillard C, et al. Mutations in signal recognition particle SRP54 cause syndromic neutropenia with Shwachman-diamond-like features. J Clin Invest. 2017;127:4090–103.

    Article  Google Scholar 

  6. 6.

    Myers KC, Davies SM, Shimamura A. Clinical and molecular pathophysiology of Shwachman-diamond syndrome: an update. Hematol Oncol Clin North Am. 2013;27:117–28.

    Article  Google Scholar 

  7. 7.

    Pressato B, Valli R, Marletta C, et al. Deletion of chromosome 20 in bone marrow of patients with Shwachman-diamond syndrome, loss of the EIF6 gene and benign prognosis. Br J Haematol. 2012;157:503–5.

    Article  Google Scholar 

  8. 8.

    Valli R, Minelli A, Galbiati M, et al. Shwachman-diamond syndrome with clonal interstitial deletion of the long arm of chromosome 20 in bone marrow: haematological features, prognosis and genomic instability. Br J Haematol. 2019;184:974–81.

    CAS  Article  Google Scholar 

  9. 9.

    Revy P, Kannengiesser C, Fischer A. Somatic genetic rescue in Mendelian haematopoietic diseases. Nat Rev Genet. 2019;20:582–98.

    CAS  Article  Google Scholar 

  10. 10.

    Rujkijyanont P, Watanabe K, Ambekar C, et al. SBDS-deficient cells undergo accelerated apoptosis through the Fas-pathway. Haematologica. 2008;93:363–71.

    CAS  Article  Google Scholar 

  11. 11.

    Nihrane A, Sezgin G, Dsilva S, et al. Depletion of the Shwachman-diamond syndrome gene product, SBDS, leads to growth inhibition and increased expression of OPG and VEGF-A. Blood Cells Mol Dis. 2009;42:85–91.

    CAS  Article  Google Scholar 

  12. 12.

    In K, Zaini MA, Müller C, et al. Shwachman-Bodian-diamond syndrome (SBDS) protein deficiency impairs translation re-initiation from C/EBPα and C/EBPβ mRNAs. Nucleic Acids Res. 2016;44:4134–46.

    CAS  Article  Google Scholar 

  13. 13.

    Frattini A, Fabbri M, Valli R, et al. High variability of genomic instability and gene expression profiling in different HeLa clones. Sci Rep. 2015;5:15377. https://doi.org/10.1038/srep15377.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Rujkijyanont P, Beyene J, Wei K, et al. Leukaemia-related gene expression in bone marrow cells from patients with the preleukaemic disorder Shwachman-diamond syndrome. Br J Haematol. 2007;137:537–44.

    CAS  Article  Google Scholar 

  15. 15.

    Rujkijyanont P, Adams SL, Beyene J, et al. Bone marrow cells from patients with Shwachman-diamond syndrome abnormally express genes involved in ribosome biogenesis and RNA processing. Br J Haematol. 2009;145:806–15.

    CAS  Article  Google Scholar 

  16. 16.

    Valli R, De Paoli E, Nacci L, et al. Novel recurrent chromosome anomalies in Shwachman-diamond syndrome. Pediatr Blood Cancer. 2017;64:e26454.

    Article  Google Scholar 

  17. 17.

    Valli R, Maserati E, Marletta C, et al. Evaluating chromosomal mosaicism by array comparative genomic hybridization in haematological malignancies: the proposal of a formula. Cancer Gene Ther. 2011;204:216–8.

    CAS  Article  Google Scholar 

  18. 18.

    Kyoto Encyclopedia of Genes and Genomes (KEGG): map 04640 Hematopoietic Cell lineage http://software.broadinstitute.org/gsea/msigdb/gene_families.jsp?geneSetName=KEGG_HEMATOPOIETIC_CELL_LINEAGE Accessed on 16 July 2019.

  19. 19.

    Kyoto Encyclopedia of Genes and Genomes (KEGG): map 05221 Acute Myeloid Leukemia http://software.broadinstitute.org/gsea/msigdb/cards/KEGG_ACUTE_MYELOID_LEUKEMIA.html Accessed on 16 July 2019.

  20. 20.

    The Gene Ontology Resource Gene set 3: M10998 - GO Myeloid Leukocyte Differentiation http://software.broadinstitute.org/gsea/msigdb/cards/GO_MYELOID_LEUKOCYTE_DIFFERENTIATION.htm Accessed on 16 July 2019.

  21. 21.

    Zhu W, Li GX, Chen HL, et al. The role of eukaryotic translation initiation factor 6 in tumors (review). Oncol Lett. 2017;14:3–9.

    CAS  Article  Google Scholar 

  22. 22.

    Pressato B, Valli R, Marletta C, et al. Cytogenetic monitoring in Shwachman-diamond syndrome: a note on clonal progression and a practical warning. J Pediatr Hematol Oncol. 2015;37:307–10.

    Article  Google Scholar 

  23. 23.

    Valli R, Frattini A, Minelli A. Shwachman-diamond syndrome: diagnosis, pathogenesis and prognosis. Expert Opin Orphan Drugs. 2017;5:753–67.

    CAS  Article  Google Scholar 

  24. 24.

    Noris P, Valli R, Pecci A, et al. Clonal chromosome anomalies affecting FLI1 mimic inherited thrombocytopenia of the Paris-trousseau type. Eur J Haematol. 2012;89:345–9.

    Article  Google Scholar 

  25. 25.

    Wang CY, Lin CF. Annexin A2: its molecular regulation and cellular expression in cancer development. Dis Markers. 2014:308976, e-pub ahead of print 23 January 2014. https://doi.org/10.1155/2014/308976.

    Google Scholar 

  26. 26.

    Maserati E, Minelli A, Pressato B, et al. Shwachman syndrome as mutator phenotype responsible for myeloid dysplasia/neoplasia through karyotype instability and chromosome 7 and 20 anomalies. Genes Chromosom Cancer. 2006;45:375–82.

    CAS  Article  Google Scholar 

  27. 27.

    Maserati E, Pressato B, Valli R, et al. The route to development of myelodysplastic sindrome/acute myeloid leukaemia in Shwachman-diamond syndrome: the role of ageing, karyotype instability, and acquired chromosome anomalies. Br J Haematol. 2009;145:190–7.

    CAS  Article  Google Scholar 

  28. 28.

    Valli R, Pressato B, Marletta C, et al. Different loss of material in recurrent chromosome 20 interstitial deletions in Shwachman-diamond syndrome and in myeloid neoplasms. Mol Cytogenet. 2013;6:56.

    Article  Google Scholar 

  29. 29.

    Valli R, De Bernardi F, Frattini A, et al. Comparative genomic hybridization on microarray (a-CGH) in olfactory neuroblastoma: analysis of ten cases and review of the literature. Genes Chromosom Cancer. 2015;54:771–5.

    CAS  Article  Google Scholar 

  30. 30.

    Nacheva E, Mokretar K, Soenmez A, et al. DNA isolation protocol effects on nuclear DNA analysis by microarrays, droplet digital PCR, and whole genome sequencing, and on mitochondrial DNA copy number estimation. PLoS One. 2017;12:e0180467.

    Article  Google Scholar 

  31. 31.

    Schroeder A, Mueller O, Stocker S, et al. The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Mol Biol. 2006;7:3.

    Article  Google Scholar 

Download references

Acknowledgements

The support of Associazione Italiana Sindrome di Shwachman (AISS) is gratefully acknowledged. The research leading to the microarray data resulted also from access to the Nanobiotechnology Laboratory under the Framework for open access to the Joint Research Centre Research Infrastructures of the European Commission. The authors thank Pascal Colpo. Abdul Waheed Khan is a PhD student enrolled in the Life Sciences and Biotechnology program of the XXXIII cycle.

Funding

This work was supported by grants from the Associazione Italiana Sindrome di Shwachman (AISS). This research was supported by a Grant from the Italian Ministry of Education, University and Research (MIUR) to the Department of Molecular Medicine of the University of Pavia under the initiative “Dipartimenti di Eccellenza (2018–2022)”.

Author information

Affiliations

Authors

Contributions

AWK, AM, AF, GM, AB, MF, GP, FA, RV performed the research and analyzed the data. RMP, EB, RM, AP, SC, MC, MZ, FL followed the patients and contributed with all clinical data. RV, CD, EM, FP designed the research, analyzed the data and wrote the paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Roberto Valli.

Ethics declarations

Ethics approval and consent to participate

Informed consent to this study was obtained according to the principles of the Declaration of Helsinki from the patients, the patients’ parents, and from healthy controls.

Consent for publication

Informed consent for publication was obtained from the patients, the patients’ parents, and from healthy controls.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Khan, A.W., Minelli, A., Frattini, A. et al. Microarray expression studies on bone marrow of patients with Shwachman-Diamond syndrome in relation to deletion of the long arm of chromosome 20, other chromosome anomalies or normal karyotype. Mol Cytogenet 13, 1 (2020). https://doi.org/10.1186/s13039-019-0466-9

Download citation

Keywords

  • Shwachman-diamond syndrome
  • Expression analysis
  • Clonal chromosome anomalies in bone marrow
  • EIF6 gene
  • Risk of MDS/AML
  • Somatic genetic rescue