In vitro dexamethasone treatment does not induce alternative atm transcripts in cells from ataxia–telangiectasia patients

In vitro dexamethasone treatment does not induce alternative atm transcripts in cells from ataxia–telangiectasia patients

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ABSTRACT Short term treatment with low doses of glucocorticoid analogues has been shown to ameliorate neurological symptoms in Ataxia–Telangiectasia (A–T), a rare autosomal recessive


multisystem disease that mainly affects the cerebellum, immune system, and lungs. Molecular mechanisms underlying this clinical observation are unclear. We aimed at evaluating the effect of


dexamethasone on the induction of alternative _ATM_ transcripts (_ATMdexa1_). We showed that dexamethasone cannot induce an alternative _ATM_ transcript in control and A–T lymphoblasts and


primary fibroblasts, or in an _ATM_-_knockout_ HeLa cell line. We also demonstrated that some of the reported readouts associated with _ATMdexa1_ are due to cellular artifacts and the direct


induction of γH2AX by dexamethasone via DNA-PK_._ Finally, we suggest caution in interpreting dexamethasone effects in vitro for the results to be translated into a rational use of the drug


in A–T patients. SIMILAR CONTENT BEING VIEWED BY OTHERS EXPRESSION OF A LARGE CODING SEQUENCE: GENE THERAPY VECTORS FOR ATAXIA TELANGIECTASIA Article Open access 08 November 2023 THE


TRANSCRIPTION FACTOR DDIT3 IS A POTENTIAL DRIVER OF DYSERYTHROPOIESIS IN MYELODYSPLASTIC SYNDROMES Article Open access 09 December 2022 TRANSGENIC _IDH2_R172K AND _IDH2_R140Q ZEBRAFISH


MODELS RECAPITULATED FEATURES OF HUMAN ACUTE MYELOID LEUKEMIA Article Open access 04 February 2023 INTRODUCTION Ataxia–Telangiectasia (A–T; MIM#208900) is a rare autosomal recessive


multisystem disorder caused by biallelic pathogenic variants in the _ATM_ gene (MIM#607585). Most of these variants are null changes leading to a complete loss of ATM protein function. A–T


patients show early-onset progressive cerebellar neurodegeneration, oculocutaneous telangiectasias, immunodeficiency and a high incidence of infections and cancers1,2,3. In classic A–T,


patients are wheelchair-dependent by the age of 10 years and their life expectancy is approximately 25 years4,5,6. _ATM_ encodes a large 3056 amino acid protein whose main role is


coordinating the cellular response to DNA double strand breaks7, but it is also involved in the response to oxidative stress, and other forms of genotoxic stress. ATM is active in cell


signaling pathways involved in maintaining cellular homeostasis, and is known to directly phosphorylate and regulate a list of several hundreds of substrates7,8,9,10,11,12. Since ATM is


ubiquitously expressed, the reason why cerebellar Purkinje cells are so incredibly sensitive to its loss, while other neurons are unaffected, is still unknown. No effective disease-modifying


therapy is presently available for A–T; however, in recent years, some studies have demonstrated that short-term treatments with low doses of glucocorticoids ameliorate the neurological


symptoms of A–T patients without relevant side effects13,14,15,16,17. After an observational study which suggested that betamethasone may improve neurologic functions in patients with A–T13,


short-term trials confirmed the efficacy of oral betamethasone14. In particular, speech disturbance and stance, as well as the quality of motor coordination, were the most sensitive


neurological parameters14, 15, 18. A recent study suggested that a daily dose of 0.005 mg/kg betamethasone, is effective in some A–T patients, and can be considered for occasional usage


under medical supervision. However, the long-term side-effects versus efficacy of this treatment has not yet been evaluated17. Other research groups showed that infusions of autologous


erythrocytes loaded with dexamethasone were effective in improving neurological symptoms in some A–T patients19. This procedure takes advantage of an autologous erythrocyte-based drug


delivery system, and is currently used in an international, multi-centre, randomized, prospective, double-blind, placebo-controlled, phase III study


(https://clinicaltrials.gov/ct2/show/NCT02770807). The procedure is invasive, requiring monthly blood samples of 50 ml and subsequent transfusions19. The cellular/molecular mechanism(s)


underlying the glucocorticoid clinical effects in A–T are currently unclear. Response to treatment occurs within hours, and incoordination rapidly reoccurs upon suspension of the drug. A–T


patients, who exhibited a good motor response to betamethasone treatment had increased activation in relevant cortical areas has been reported, suggesting that glucocorticoids may facilitate


cortical compensatory mechanisms on cerebellar dysfunction20. An explanation for the corticosteroid response in A–T patients was the description of dexamethasone induction of non-canonical


_ATM_ splicing events in A–T cell lines. Dexamethasone can allow the synthesis of a non-canonical _ATM_ transcript (_ATMdexa1_) and protein (mini-ATM), with some of the full-length ATM


functions (Fig. 1A–D). Here, we investigated this _ATM_ splicing event using B-lymphoblastoid cell lines (LCLs) and fibroblasts from A–T patients with different _ATM_ pathogenic variants and


a HeLa CRISPR/_ATM_-_knockout_ cell line model without finding any evidence of _ATMdexa1_ or other splicing anomalies induced by dexamethasone. MATERIALS AND METHODS CELL LINES A–T


(Supplemental Table 1) and control LCLs were established from fresh lymphocytes infected by Epstein-Barr virus and maintained in RPMI-1640 medium (Sigma Aldrich, Italy) supplemented with 2


mMol Glutamine, 50 U/ml penicillin, 50 µg/ml streptomycin and 10% Fetal Bovine Serum (FBS, Gibco, Thermo Fisher Scientifics, Waltham, MA, USA). A–T and control human primary fibroblasts were


obtained from skin biopsies after overnight incubation in Dulbecco’s Modified Eagle Medium (DMEM, Sigma Aldrich, Italy) with 10% FBS with collagenase (160 µg/ml) and then cultured in DMEM


with 2 mMol Glutamine, 50 U/ml penicillin, 50 µg/ml streptomycin, 1 mMol Sodium Pyruvate and 10% FBS. Cells from passages 5 to 9 were used for all experiments, and cells from A–T patients


and healthy controls at the same passage were compared. HeLa CRISPR/_ATM_-_knockout_ were generated using the CRISPR/Cas9 method and maintained in Minimum Essential Medium (Biowest #L0440),


supplemented with 10% FBS, 2 mMol Glutamine, 1 mMol Sodium Pyruvate, 0.1 mMol non-essential amino acids (NEAA), 50 U/ml penicillin, and 50 µg/ml streptomycin. All cells were maintained at 37


 °C with 5% CO2. Informed consent was obtained from participants for the use of blood and skin samples. The study was approved by the institutional Internal Review Board of the Department of


Medical Sciences, University of Torino, and C. Besta Neurological Institute. Methods were carried out in accordance with the relevant guidelines and regulations. Dexamethasone doses and


times (0.1 μM for 24 h and 72 h) used to analyse mRNA and protein expression were in accordance with published experimental conditions21. _ATM_ TRANSCRIPT AND EXPRESSION ANALYSIS Total RNA


was extracted from 5 × 106 LCLs and from 2 × 105 fibroblasts (from six A–T patients and four healthy controls) and from 2 × 105 HeLa CRISPR/_ATM_-_knockout_ cells using the Direct-zol™ Kits-


RNA extraction kit (Zymo Research, Irvine, California, USA) according to the manufacturer's instructions. Retrotranscription of 1 µg RNA was carried out using the M-MLV Reverse


Transcriptase following the manufacturer’s instructions (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Long range PCR for the _ATM_ transcript (exons 2–56; reference _ATM_ sequence


NM_000051.3) was performed in a total volume of 50 µl with a final concentration of 200 nM of each primer (Supplemental Table 2), 400 μM of dNTPs, 1 × enzyme buffer and 2.5 units of LA


polymerase (Takara Bio Inc., Otsu, Shiga 520–2193, Japan), using the following cycling parameters: 1 min at 94 °C, followed by 30 cycles of 10 s at 98 °C, and 11 min/kb at the annealing


temperature, with a final extension at 72 °C for 10 min. _Beta-actin_ was amplified as a control in a final volume of 25 µl with a final concentration of 500 nM of each primer, 200 µM of


dNTPs, 1 × KAPA2G enzyme buffer and 0.5 units of KAPA2G Fast HotStart polymerase (KAPA Biosystems, Wilmington, MA, USA), under the following cycling parameters: 3 min at 95 °C, followed by


25 cycles of 15 s at 95 °C, and 15 s at 60 °C and 15 s at 72 °C followed by a final extension at 72 °C for 1 min. Amplification products were separated on a 0.6% or 1% TBE-agarose gel for


_ATM_ and _β-actin,_ respectively, then stained with 1X Midori Green DNA stain (Nippon Genetics Europe Gmbh) and visualized using a GelDOC apparatus (Biorad, Hercules, California, United


States). ABSOLUTE QUANTIFICATION BY RT-QPCR For an absolute quantification of full-length _ATM_ and _ATMdexa1_ transcripts, we designed three different reverse-transcription quantitative


real-time PCR (RT-qPCR) assays using the Universal Probe Library method (UPL, Roche, Mannheim, Germany), namely (1) an _ATMdexa1_-specific assay (primers on cDNA spanning the exons 3–53


junction); (2) a full-length _ATM_ specific assay (primers on cDNA spanning the exons 14–15 junction); and (3) an _ATM_ assay able to detect both full length and _ATMdexa1_ (primers on cDNA


spanning the exons 3–4 junction) (Fig. 1E). Amplifications were carried out on an ABI-Prism 7500 Fast instrument, using the ABI 2X TaqMan Gene Expression master mix, according to the


manufacturer’s instructions (Applied Biosystems, Thermo Fisher Scientific). To obtain an absolute quantification, we generated three calibration curves, exploiting two plasmid vectors


containing either the full-length _ATM_ coding sequence (pMAT plasmid22) or an artificial _ATMdexa1_ amplimer (pGEM-ATMdexa1 plasmid). This was generated by the overlap-extension method


described in Supplemental Fig. 1. Each plasmid was prepared at an initial concentration of 1 × 106 copies/µL and a dilution series was prepared (#copies/µL: 103, 5 × 103, 104, 5 × 104, 105,


5 × 105). Each dilution was performed in triplicate and the mean was used as a reference to calculate the calibration curve (Supplemental Table 3). Three A–T and control human LCLs treated


with vehicle (EtOH) or with 0.1 µM dexamethasone were tested using the above UPL assays and the number of mRNA copies was inferred interpolating the Ct values to standard curves


(Supplemental Table 4 in dataset 1). WESTERN BLOTTING Total protein lysates were extracted from LCLs and primary fibroblasts of six A–T patients and four healthy controls, using RIPA Lysis


Buffer [Tris–Cl (50 mM, pH 7.5), NaCl (150 mM), NP40 (1%), Na Deoxycholate (0.5%), DTT (0.1 M), EDTA (5 mM), HaltTM Protease and Phosphatase inhibitor cocktail (Thermo Fisher Scientific)].


Nuclear lysates were extracted from fibroblasts using NE-PER Nuclear and Cytoplasmic Extraction Kit following the manufacturer's protocol (Thermo Fisher Scientific). Protein


quantification was measured using the Bradford assay (Bio-Rad) according to the manufacturer’s protocol. Protein lysates (20 µg) were denatured for 10 min at 70 °C in LaemmLi Sample Buffer


(4% SDS, 20% glycerol, 10% 2-mercaptoethanol, 0.004% bromophenol blue and 125 mM Tris HCl, pH 6.8) and reducing agent (50 mM dithiothreitol, DTT), resolved by SDS–PAGE (4–12%), using


Tris–Glycine-SDS buffer (Thermo Fisher Scientific) and electro-transferred onto nitrocellulose membranes (Bio-Rad) for 1 hr at 125 V. Membranes were blocked with TBS-T [50 mM Tris and 150 mM


NaCl, pH 7.6, and 0.1% Tween-20 (Sigma, Italy)] with 5% BSA and probed with primary antibodies against ATM (2C1) (1:400; Ab sc. 23921, Santa Cruz Biotechnology, Italy), p-ATM (1:5000; Ab


Cat. No. 32420, Abcam, Italy), γH2AX (1:3000; Ab Cat. No. NB100-384, Novus, Europe). β-Actin (1:2000; Cat. No. NB600-532H, Novus, Europe) or Vinculin (1:2000; Cat. No. AB6039, Merck


Millipore, Italy) antibodies were used as loading controls. For western blot analyses, cells were incubated for 72 h in RPMI or DMEM medium supplemented with 5% FBS, before lysis for


extraction of total or nuclear proteins. Band density was quantified by densitometric analysis using the Image Lab 3.0 software (Bio-Rad). LCLs and fibroblasts were irradiated at a dose rate


of 10 Gy/min at a distance of 40 cm (Radgil, Gilardoni Instruments, Italy). Inhibition of DNA-PK kinase activity was performed by adding 10 μM NU7441 (Sigma Aldrich) for 1 h to untreated


cells or cells pre-treated with 0.1 μM dexamethasone for 72 h before irradiation (IR). Cells were then incubated at 37 °C for 1 h before nuclear protein extraction. Drugs were maintained in


growth medium until time of harvest. STATISTICAL ANALYSES Experiments were performed in triplicate and repeated at least twice, unless otherwise specified. Values are given as means and


standard deviations, or as fold-changes. Mean values of variables with a normal distribution were reported, and comparisons between control groups and patient groups were conducted using the


Student's _t_ test. When the distribution of data was not normal (densitometry analyses of all western blots), variables were presented as median values, and differences between two


groups were calculated using the Mann–Whitney test. Significance of gene expression and enzyme activity data was calculated using the Student's _t_ test (unpaired). Statistical


calculations were performed using GraphPad Statistics Software Version 6.0 (GraphPad Software, Inc., USA). _p_ values of < 0.05 were considered statistically significant. RESULTS AND


DISCUSSION The proposed use of glucocorticoids for A–T therapy has prompted in vitro studies aimed at analysing their possible compensating role of _ATM_ deficiency. Our initial aim was to


unravel the effect of glucosteroids on A–T lymphoblastoid cells and primary fibroblasts, two cell types widely used as experimental models in this disease. Dexamethasone has been reported to


induce _ATM_ alternative splicing, resulting in the _ATMdexa1_ transcript_,_ which encodes a functional mini-ATM protein21, 23. To validate this finding, we generated five A–T


lymphoblastoid cell lines (LCLs) with _ATM_ gene pathogenic variants outside the _ATMdexa1_ encoding exons on one or both alleles, and one LCL (AT-38) who carried two nonsense variants in


exons 63 and 65 included in _ATMdexa1_ (Fig. 1A and Supplemental Table 1). To verify the effects of dexamethasone on cell viability, we performed an MTT viability assay, treating control 


LCLs with increasing doses of the drug (0.1, 1, or 10 µM for 24 h). Dexamethasone showed a modest but significant decrease in viability with doses ≥ 1 µM (Fig. 1F), which largely exceeds the


dose of 0.1 µM for 24 h alleged to induce _ATMdexa1_ in vitro. Following the previously published protocol21, we tested the effect of dexamethasone on _ATM_ transcripts in both LCLs and


fibroblasts (0.1 µM, 24 h). Using a forward primer on exon 2 and a reverse primer on exon 56 of the _ATM_ cDNA (NM_00051.3), we were able to amplify the native _ATM_ transcript (~ 9.0 kb) in


both treated and untreated cells (Fig. 1G). No changes were observed after treatment in band intensity or in the appearance of additional bands corresponding to the size expected for


_ATMdexa1_ (~ 1.6 kb). Even if we increased dexamethasone by tenfold compared with the suggested protocol and enhanced gel contrast (1 µM dexamethasone for 24 h), no additional band was


detectable (Supplemental Fig. 2). Analogous results were obtained in primary fibroblast cultures from six A–T patients and four healthy controls, and in a HeLa CRISPR/_ATM_-_knockout_ cell


line (4C18) (data not shown). To have a quantitative measure of _ATM_ transcripts, and evaluate the detection limits of our technique, we set up three real-time quantification assays for


_ATM_ able to detect: 1) full-length _ATM_ and _ATMdexa1;_ 2) full-length _ATM_ only transcripts; 3) _ATMdexa1_ transcripts. To generate the calibration curves, we used a serial dilution


from 103 to 106 copies of a plasmid containing full-length _ATM_ (pMAT) and a plasmid containing _ATMdexa1,_ generated in our laboratory (pGEM-ATMdexa1 plasmid). We were able to clearly


detect as low as 103 copies of both full ATM and _ATMdexa1_, although this was not the lower limit of the test (Fig. 2B). The _ATM_ transcript was expressed at 63 ± 22% (median ± S.D.) in


A–T cases versus controls (Fig. 2C), without any relevant differences between untreated cells or cells treated with dexamethasone, apart from the CTR3 treated cell line (Fig. 2C). We were


unable to detect _ATMdexa1_ in any sample (Fig. 2C). Notably, there was no difference between the number of cDNA copies estimated by the full-length _ATM_ assay, which includes all _ATM_


transcripts_,_ and the full-length _ATM_ specific assay, which does not include _ATMdexa1_. This further corroborates the absence of an _ATMdexa1_ transcript. Using the 2C1 antibody, raised


against the C-terminal portion of the ATM protein (aa. 2577–3056), we were able to reveal a unique band corresponding to the native ATM in control fibroblasts but not in A-T fibroblasts. No


additional proteins were evident, further proving the absence of mini-ATM (Fig. 2C). Since _ATMdexa1_ was reported in both stimulated and non-stimulated cells, we searched available


databases (UCSC, ENSEMBL) to have _in-silico_ evidence of the _ATMdexa1_ transcript. _ATM_ had a single validated protein-encoding transcript (NM_000051.3), and some shorter transcripts,


none of which had any similarity with the _ATMdexa1._ A previous study21, also raised unanswered questions on how _ATMdexa1_ is formed: (1) an atypical splicing event should take place


between exons 4 and 53, without any canonical splicing site. The authors state this can happen by a rare SDR-splicing, reported only once in _Oryza sativa_, and never described in Metazoa24;


(2) the generation of the “mini-ATM” protein starts from a non-canonical ATG-encoding first methionine within exon 58 (Met 2806), in the absence of a translational-initiation consensus.


This ATG would produce an ATM variant protein beginning from codon 841821, and lacking the N-terminal, which carries nuclear localization sequences, several critical phosphorylation sites,


and binding sites for chromatin and ATM-interacting proteins. Published data are against the notion that such a protein is functional, at least for its nuclear activity. ATM without the


N-terminus is unable to fully localize to the nucleus and therefore activate DNA repair effectors7, 25,26,27,28. To assess if dexamethasone influences known ATM-pathway substrates, in the


absence of ATM itself, we measured the phosphorylation of H2AX at Ser139 (γH2AX), a sensitive marker of DNA damage responses29. We analyzed the expression of γH2AX in our A–T LCLs, both at a


basal level and after 72 h of treatment with 0.1 µM dexamethasone. We found a basal phosphorylation of H2AX in both A–T and control LCLs, which increased by ~ 30–40% after dexamethasone


treatment. Similar results were obtained after DNA double-strand break (DSB) induction by ionizing radiation (IR), with an additive effect of dexamethasone and IR combined treatment (Fig. 


3A). This result suggests that LCLs that are EBV-transformed cell lines are not a reliable cellular model to study dexamethasone effects30. Our data suggest a possible role of dexamethasone


in activating H2AX, regardless of DSB damage, and explain part of the results attributed to _ATMdexa1_21. Histone H2AX is a substrate of several phosphoinositide 3-kinase-related protein


kinases (PIKKs): besides ATM, ATR (ATM and Rad3-related) phosphorylates H2AX in response to single-stranded DNA breaks and during replication stress31,32,33,34, and DNA-PK (DNA-dependent


protein kinase) mediates phosphorylation of H2AX in cells under hypertonic conditions and during apoptotic DNA fragmentation24, 25, 35, 36. Finally, several reports in the literature have


shown that LCLs have such an inter-experimental variability that it can be concluded that they are an unsuitable model for DNA repair studies30, 37, 38. We therefore decided to analyze H2AX


activation in response to dexamethasone in primary cells, such as fibroblasts, in which basal γH2AX was almost undetectable (Fig. 3B). After irradiation, H2AX was phosphorylated in control


fibroblasts and, to a lesser extent, in A–T fibroblasts, as expected, due to the absence of the ATM protein in A–T fibroblasts. We noticed dexamethasone did not increase γH2AX, either alone


or in combination with IR (Fig. 3B). Experimental data from other groups reported that DNA-PK can vicariate ATM in the DNA damage response39,40,41,42. Hence, we assessed the role of DNA-PK


in H2AX activation using NU7441, a specific DNA-PK inhibitor. H2AX phosphorylation was reduced in irradiated A–T fibroblasts treated with NU7441 (Fig. 3B; _p_ < 0.01; ~ 30% decrease;


Supplemental Fig. 2). In this experimental condition, dexamethasone treatment did not affect γH2AX levels. Dexamethasone can only increase γH2AX levels in LCLs, but not in A–T and control


fibroblasts, probably because LCLs undergo significant transformations to become immortal, which can alter the biology of the cell37. In conclusion, our data and literature do not support


the effect of dexamethasone on inducing _ATM_ alternative transcripts. We reiterate that LCLs are not a suitable model to study H2AX activation, possibly due to their rapid replication.


Taken together, our results suggest alternative explanations to _ATMdexa1_ must be considered in interpreting the in vivo effects of dexamethasone in A–T treatment. DATA AVAILABILITY All


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PubMed  PubMed Central  Google Scholar  Download references ACKNOWLEDGEMENTS The authors are gratefully indebted to the patients and their families for taking part into the study. The work


was supported by Associazione “Gli Amici di Valentina”, “Un vero sorriso” and “Noi per Lorenzo”. CM and EG were recipient of a fellowship from Fondazione Umberto Veronesi 2017–2018. This


research received funding specifically appointed to Department of Medical Sciences from the Italian Ministry for Education, University and Research (Ministero dell’Istruzione,


dell’Università e della Ricerca—MIUR) under the programme “Dipartimenti di Eccellenza 2018–2022” Project code D15D18000410001. We also thank Drs. Stefania Saoncella, Beatrice Tassone and


Vincenzo Calautti for technical help and critical discussion. AUTHOR INFORMATION Author notes * These authors contributed equally: Simona Cavalieri and Alfredo Brusco. AUTHORS AND


AFFILIATIONS * Department of Medical Sciences, University of Torino, via Santena 19, 10126, Turin, Italy Elisa Pozzi, Elisa Giorgio, Cecilia Mancini, Stefania Augeri, Marta Ferrero, Ada


Funaro, Simona Cavalieri & Alfredo Brusco * Laboratory of Immune-Mediated Diseases, San Raffaele Diabetes Research Institute (DRI), 20132, Milan, Italy Nicola Lo Buono * Unit of Medical


Genetics, “Città Della Salute E Della Scienza” University Hospital, 10126, Turin, Italy Eleonora Di Gregorio & Alfredo Brusco * Department of Public Health and Pediatrics, University of


Torino, 10126, Turin, Italy Evelise Riberi * DNA Metabolism Laboratory, FIRC Institute of Molecular Oncology (IFOM), 20139, Milan, Italy Maria Vinciguerra & Vincenzo Costanzo * Unit of


Genetics of Neurodegenerative and Metabolic Diseases, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, 20133, Milan, Italy Lorenzo Nanetti & Caterina Mariotti * Department of


Molecular Biotechnologies and Health Sciences, Neuroscience Institute Cavalieri Ottolenghi, 10043, Orbassano, TO, Italy Federico Tommaso Bianchi * Istituto Nazionale di RIcerca Metrologica


INRIM, 10135, Turin, Italy Maria Paola Sassi Authors * Elisa Pozzi View author publications You can also search for this author inPubMed Google Scholar * Elisa Giorgio View author


publications You can also search for this author inPubMed Google Scholar * Cecilia Mancini View author publications You can also search for this author inPubMed Google Scholar * Nicola Lo


Buono View author publications You can also search for this author inPubMed Google Scholar * Stefania Augeri View author publications You can also search for this author inPubMed Google


Scholar * Marta Ferrero View author publications You can also search for this author inPubMed Google Scholar * Eleonora Di Gregorio View author publications You can also search for this


author inPubMed Google Scholar * Evelise Riberi View author publications You can also search for this author inPubMed Google Scholar * Maria Vinciguerra View author publications You can also


search for this author inPubMed Google Scholar * Lorenzo Nanetti View author publications You can also search for this author inPubMed Google Scholar * Federico Tommaso Bianchi View author


publications You can also search for this author inPubMed Google Scholar * Maria Paola Sassi View author publications You can also search for this author inPubMed Google Scholar * Vincenzo


Costanzo View author publications You can also search for this author inPubMed Google Scholar * Caterina Mariotti View author publications You can also search for this author inPubMed Google


Scholar * Ada Funaro View author publications You can also search for this author inPubMed Google Scholar * Simona Cavalieri View author publications You can also search for this author


inPubMed Google Scholar * Alfredo Brusco View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS E.P., S.C. conceived and designed the analysis,


performed experiments, collected, and interpreted data, and wrote the manuscript. E.G., C.M., N.L.B., S.A., M.F., E.D.G., E.R., M.V., F.T.B., M.P.S., V.C. performed experiments, collected,


and interpreted data. C.M. and L.N. recruited patients. A.F. and A.B. supervised the work and wrote the manuscript. All authors revised the manuscript. CORRESPONDING AUTHOR Correspondence to


Alfredo Brusco. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER'S NOTE Springer Nature remains neutral with regard


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Mancini, C. _et al._ In vitro dexamethasone treatment does not induce alternative _ATM_ transcripts in cells from Ataxia–Telangiectasia patients. _Sci Rep_ 10, 20182 (2020).


https://doi.org/10.1038/s41598-020-77352-z Download citation * Received: 12 December 2018 * Accepted: 05 November 2020 * Published: 19 November 2020 * DOI:


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