Functional Assessment of ATRX Alterations Improves Glioma Diagnosis

Functional Assessment of ATRX Alterations Improves Glioma Diagnosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Functional Assessment of ATRX Alterations Improves Glioma Diagnosis Clemence Guerriau, Camille Léonce, Catherine Carpentier, Franck Bielle, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6974009/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Acta Neuropathologica Communications → Version 1 posted 10 You are reading this latest preprint version Abstract Loss of ATRX function, a diagnostic criterion of IDH-mutant astrocytoma, is closely associated with alternative lengthening of telomeres (ALT), a telomere maintenance mechanism (TMM). As immunohistochemical (IHC) assessment of ATRX is error-prone, sequencing has been integrated into clinical workflows. While frameshift and nonsense variants can be classified as loss-of-function (LOF) mutations, missense variants remain difficult to interpret. To address this, we analyzed ATRX -altered gliomas from TCGA (N = 539 tumors, 591 alterations) and a local cohort of 100 diffuse gliomas. Aside from IDH-mutant astrocytomas and H3.3-mutant gliomas, glioblastoma (12–18%), oligodendroglioma (2%), and MAPK-altered tumors (1–6%) were consistently represented in both cohorts. Missense mutations accounted for 18% (TCGA) and 29% (local) of variants. Functional annotation of TCGA missense mutations using IHC, NGS-based TMM status, transcript levels, and RNA-seq–derived telomerase signatures (EXTEND) allowed us to functionally annotate only 3 of 106 variants. Therefore, we directly assessed the TMM status in the local cohort, using the TeloDIAG assay and retrieved 80% of ALT-positive samples, corresponding to 96% (N = 53) of IDH-mutant astrocytomas and 79% (N = 19) of histone-mutant gliomas, as expected. Importantly, ALT activity was also observed in 39% (N = 18) of glioblastomas and 83% (N = 6) of MAPK-altered gliomas, indicating potential implications for clinical behavior and therapeutic targeting. Overall, 68% (N = 28) of missense mutations were functionally classified as LOF. Notably, 83% (N = 24) of them were located within the major functional domains of the ATRX protein, compared to only 59% when considering all missense mutations, highlighting the functional relevance of the assay. As compared to TeloDIAG, IHC showed limited sensitivity (74%), dropping to 44% (N = 18) in cases with missense mutation. Collectively, these findings emphasize the clinical value of functional TMM assessment in refining glioma diagnosis. Last, targeting of ALT-associated DNA-damage deficiency and immunogenic context is under clinical investigation, highlighting the promising theranostic potential of TMM assessment. glioblastoma IDH-mutant ATRX ALT telomere database telomerase MAPK extend Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction ATRX stands for X-linked alpha-thalassemia/mental retardation syndrome, due to its initial identification in patients with severe psychomotor retardation, characteristic facial features, genital abnormalities, and alpha-thalassemia [ 9 ]. ATRX exhibits ATP-dependent nucleosome remodeling activity and is specialized in depositing the histone variant H3.3 at repetitive, transcriptionally inactive sites, such as pericentromeric and telomeric heterochromatin [ 2 ]. ATRX also contributes to telomere maintenance and replication, partly by regulating the formation and/or resolution of G-quadruplex structures (intramolecular rearrangements of the telomeric G-rich strand) [ 34 ] and R-loops [ 22 ] (RNA:DNA heteroduplexes). Hence, ATRX loss induces replicative stress at telomeres [ 34 ], and its inactivation facilitates the initiation of the “alternative lengthening of telomere” (ALT) process [ 20 , 27 ]. ALT is an "alternative" telomere maintenance mechanism (TMM) to telomerase reactivation, used by 7–10% of tumors to maintain telomere length and avoid senescence or mitotic crisis. This process relies on aberrant repair mechanism, produces extrachromosomal telomere sequences (ECTR), mainly occurs in ALT-associated PML bodies (APBs), and results in long heterogeneous telomeres. Thus, ALT can be detected on the basis of telomere length by Telo-FISH, Telo-qPCR or long read sequencing. The latter two technologies also quantify ECTR, such as C-circle (CC), which are partially double-stranded telomeric circle detected after a pre-amplification step [ 11 ]. In humans, neuroepithelial and mesenchymal tumors, such as gliomas and sarcomas, show the highest rates of ALT activation [ 12 , 33 ]. Importantly, in gliomas, ATRX loss (detected by immunohistochemistry) is a diagnostic criterion for grade 2 to 4 IDH-mutant astrocytomas, which represent 20–25% of diffuse gliomas. ATRX loss is also frequently observed in H3.3-mutated gliomas (G34R/V and K27M), including nearly 100% of hemispheric G34R/V-mutant gliomas and approximately 30% of midline diffuse gliomas [ 30 ]. ATRX loss is often associated with TP53 loss and genomic instability [ 17 , 34 ]. Other diffuse gliomas, such as glioblastomas (GBM, 65% of gliomas) and IDH1/2-mutant oligodendrogliomas (OD, 10% of gliomas), typically maintain their telomeres by reactivating the telomerase enzyme through mutations in TERT (telomerase reverse transcriptase) promoter (p TERT mt), which leads to TERT re-expression [ 16 ]. Routine detection of ATRX loss by immunohistochemistry (IHC) faces two significant challenges: (i) inter-observer variability, and (ii) inability to detect mutations that do not affect protein stability, resulting in 11 to 21% false-negative results compared to the Telo-FISH method [ 1 , 21 , 30 ]. Sequencing of the ATRX gene, which spans approximately 300 kb and includes 36 exons, has recently become an alternative due to the widespread adoption of next-generation sequencing (NGS). However, interpreting the clinical significance of mutations remains challenging in the absence of a functional database for ATRX . While hemi/homozygous deletion, frameshift and re-arrangement are considered as loss-of-function (LOF) and “probably pathogenic” alterations, the impact of missense mutations and small in-frame insertions/deletions remains unclear. We therefore propose (i) to exhaustively describe the spectrum of ATRX alterations in a large cohort of 591 gliomas from the TCGA, in relation to published data on TMM, and (ii) to functionally assess the ALT process in a cohort of 100 gliomas, correlating findings with standard clinical diagnostic criteria (NGS, IHC). Importantly, these cohorts include gliomas beyond astrocytomas, covering the full spectrum of contexts in which ATRX mutations occur. For functional testing, we employed the TeloDIAG, a combined assay that integrates telomere content quantification [ 14 ] with CC detection [ 11 ], thereby providing a robust evaluation of the functional consequences of ATRX mutations for clinical glioma diagnosis. Material and Methods Design and setting of the study For the first dataset, clinical and histomolecular information was extracted from the cBioPortal interface of The cancer Genome Atlas (TCGA). A total of 12 studies were selected: brain_cptac_2020, difg_glass_2019, gbm_columbia_2019, gbm_cptac_2021, gbm_mayo_pdx_sarkaria_2019, gbm_tcga, glioma_msk_2018, glioma_mskcc_2019, lgg_ucsf_2014, lgggbm_tcga_pub, odg_msk_2017, and past_dkfz_heidelberg_2013. After removing duplicates (on the basis of sample ID), 3,924 cases were compiled. Filtering for ATRX alterations resulted in the selection of 539 samples, encompassing 591 genetic alterations. The allelic variant frequency (VAF) of ATRX mutations, ranging from 0.03 to 0.99, was compared to the VAF of other alterations within the same sample and classified as either *heterozygous (wild-type allele present) or **homozygous/hemizygous (no wild-type allele)(Sup. Table 1). Frameshift, nonsense, splicing-site mutations and gene rearrangements were classified as loss-of-function (LOF) alterations. Diagnoses were assigned according to the WHO 2021 classification, based on available histological and molecular parameters. The second dataset consists of 100 gliomas from the Pitié Salpétrière Onconeurotek collection (certified 96900), which had previously undergone ATRX sequencing for diagnostic purposes. All the patients signed a written informed consent (CPP authorization N° 2023-A02763-42). These samples were included for functional testing. Pathogenicity data for missense mutations were available for only 4 variants in ClinVar database. Figures were done using excel and powerpoint (Microsoft). ALT status determination Two telomere parameters were assessed using the TeloDIAG assay, as previously described [ 4 ]: telomere content, corresponding to telomere length (TL), and C-circles (CC). TL was quantified by qPCR relative to the reference gene ( RPLP0 ) using the formula (TL = E − CT TEL /E − CT RPLP0 ). C-circles, if present, were amplified by rolling circle amplification using the Φ29 DNA polymerase. A sample was considered positive for CC if the ratio of telomeric sequences quantification with and without incubation with the Φ29 (TL +Φ /TL −Φ ) was ≥ 1.3. In regard with our previous publication, samples were considered ALT + in two situations : if CC were detectable or in situation of long telomeres (TL > 1.7 arbitrary units [au]) with or without detectable CC (fixative-induced DNA oxidation and breakage in old samples can open circles and preclude amplification, as previously demonstrated [ 4 ]). Samples negative for CC (CC < 1.3) and with short telomeres (TL < 1.7au) were considered to maintain telomeres via telomerase activity. Statistical analysis Statistical analyses and boxplots were generated using R software (R Core Team (2024). R: A language and environment for statistical computing . R Foundation for Statistical Computing, Vienna, Austria). Comparisons of group means were conducted using the non-parametric Wilcoxon rank-sum test. Results Information on ATRX alterations in public datasets To evaluate the informativeness of clinical testing, we aggregated data from 12 glioma-focused studies available in the TCGA database. After removing duplicates and filtering by diagnosis according to the WHO 2021 criteria, we selected 539 glioma samples with ATRX variants identified by NGS. The majority of gliomas were astrocytomas (80%), but the dataset also included glioblastomas (GBM, 12%) and oligodendrogliomas (OD, 2%), which are typically p TERT mt telomerase-positive (TA+) tumors (Fig. 1 a). These 539 samples contained a total of 591 ATRX variants, as 47 tumors exhibited multiple ATRX alterations. The types of alterations included hemi- or homozygous deletions (4.5%), nonsense mutations (25%), frameshift mutations (44%), missense mutations (18%), splice site mutations (6%), and rare deletions-insertions or rearrangements (Fig. 1 a). Except for missense mutations and small INDELs, all these alterations can be classified as loss-of-function (LOF) variants. To further analyze missense mutations, we used immunohistochemistry (IHC) ATRX status, which was available for 218 tumors (40%). Of note, only 2% (N = 11) of these samples retained ATRX expression (ATRXwt), including 10 out of the 11 cases with hemi- or homozygous gene deletions, which are typically associated with protein loss. Similarly, all samples bearing missense mutations (N = 32) were classified as lost for ATRX protein (ATRXloss), despite the expectation that the protein should still be expressed, albeit non-functional. This suggests potential biases in copy number variation (CNV) detection and/or misinterpretation of IHC results. Indeed, high interoperator variability has been reported for ATRX testing compared to functional testing by Telo-FISH [ 1 , 21 , 30 , 35 ]. Therefore, IHC data were further ultimately considered non-informative for this analysis. Several publications have developed algorithms to predict ALT or TA prediction based on whole-genome sequencing (WGS) [ 6 ] [ 15 ] [ 31 ] [ 23 ]. We examined these predictions for common TCGA samples. However, these models have almost exclusively included LOF alterations, such as frameshift mutations, and were mainly used as controls to validate the models. As a result, no additional relevant information was retrieved except for two missense mutations, Y2418N and E2172A, classified as ALT- (Supp. Table 1). Alternatively, data from the EXTEND signature [ 18 ], based on RNA-seq analysis and estimating the telomerase activity spectrum, were available for 114 out of the 529 ATRX -altered samples. Additionally, we included 77 ATRXwt IDHwt GBM samples as controls. The EXTEND signature aligned with the classification of tumors bearing ATRX alterations, all of which belonging to the ALT group (Fig. 2 a). However, since the EXTEND signature was developed by comparing p TERT mt samples (OD and GBM) versus ATRX/DAXX altered samples (mostly astrocytomas), it may reflect tumor cell origin/entity rather than TMM status, as demonstrated by Nonneville et al.[ 23 ]. We then inquired the expression levels of ATRX and TERT using RNA-seq data available from 197 samples. TERT expression was nearly absent in most tumors harboring ATRX variants. Interestingly, three single missense variants (V128A, Y2418N, R1131G), found in OD and GBM, were associated with TERT expression and preserved ATRX expression; among these, Y2418N was notable. Regarding ATRX expression levels, LOF variants showed a clear decrease (Fig. 2 b), whereas single missense variants exhibited no reduction compared to WT samples, consistent with the fact that amino-acid changes does not necessarily lead to protein loss. Overall, of the 106 missense mutations analyzed, only four could be classified as “probably benign” or “benign”, and no additional meaningful insight into the TMM could be derived from the other samples. In summary, we identified 106 missense mutations across 80 samples: 71 samples harbored a single hit, 9 samples had two missense mutations (N = 18), and 17 samples carried another LOF alteration. All variants were classified as “non informative”, except for two classed as benign (Y2418N and E2172A) and two as probably benign (V128A, R1131G) [ 15 ]. These findings highlight the limitations of NGS-based predictive models and emphasize the need for functional studies to improve the annotation of clinical databases for molecular diagnosis in glioma. Functional Testing of ALT status in ATRX -altered gliomas As emphasized by Nonneville et al., the CC assay should be used to accurately assess the TMM [ 23 ]. We have thus investigated directly the TMM activated by tumors in a cohort of 100 gliomas from the Pitié-Salpêtrière Tumor bank, including 92 with ATRX mutations. This cohort comprised 53 IDH1/2-mutant astrocytomas, 19 histone-mutant tumors, 6 with MAPK pathway alterations (BRAF, NF1), 18 GBM (13 p TERT mt), 2 OD (1p TERT mt), and 2 unclassified gliomas. Frameshift, nonsense and missense mutations accounted for 45%, 18% and 29% of all mutations, respectively, consistent with the proportions observed in the TCGA cohort (Fig. 1 b)(rearrangements and copy number alterations were not addresses in this study). Regarding ATRX status determined by IHC (N = 95), protein expression was lost in 63% (60/95) of tested samples (Fig. 1 b). The TeloDIAG assay [ 4 ] assesses the presence of CC and TL to identify ALT + samples; its ALT- counterparts was defined as TA+. Using this classification, 80% of the samples were ALT+ (Fig. 3 a,b). Regarding diagnosis, 96% (51/53) of astrocytomas were classified as ALT+ (42 of which showed ATRX loss), along with 79% (15/19) of histone-mutant tumors, consistent with previous studies [ 30 ]. Interestingly, among tumors usually assumed to re-express the telomerase, 39% (7/18) of GBMs with ATRX alteration were indeed ALT+ (1/7 was ATRXloss, 4/7 were also p TERT mt (regarding the VAF, 2 were subclonal TMM activation, 1 non available, 1 same ATRX-pTERT VAF) and 83% (5/6) of MAPK activated gliomas also exhibited ALT + status (3/5 with ATRXloss, all p TERT wt). This finding is noteworthy as the subcellular mechanisms and molecular alterations differ between ALT and telomerase contexts, impacting clinical behavior and tumor evolution [ 4 , 25 ]. Notably 12–18% of ATRX -altered samples identified by NGS in our database were GBMs, of which 39% (7/18) were ALT+. Functional testing identifies pathogenic missense ATRX mutations Comparing immune-histochemical detection of ATRX loss (N = 95) with TMM status, 72 samples showed concordance: 57 were ATRXloss/ALT + and 15 were TA+/ATRXwt. However, three samples with ATRX loss by IHC were classified as TA + by functional testing (false positives for IHC). These included a glioneural tumor with a heterozygous alteration, a GBM with a clonal alteration, and a histone-mutant tumor without sequencing data, possibly reflecting secondary hits without biological significance. Additionally, 20 samples were ALT + but showed wild-type ATRX by IHC (false negatives). This was expected for 10 samples with missense mutations, but surprising for 7 samples bearing frameshift or nonsense alterations. Overall, using TMM status as the gold standard, IHC detection of ATRX loss showed a sensitivity of 74% and specificity of 83%. Considering the type of alteration in relation to the detected TMM, 86% (56/64) of LOF alterations (frameshift and nonsense mutations) were classified as ALT+ (Fig. 3 c). Among the 8 samples with LOF alteration but TA + status, 5 were ATRXwt by IHC, 2 showed ATRXloss (a GBM with a clonal mutation and a glioneural with a heterozygous mutation), and 1 lacked IHC data. These observations may be linked to either secondary mutations without biological impact or minor subclonal alterations. Regarding the 28 missense alterations (Fig. 3 c), 19 were detected as ALT+ (8 of which showed ATRX loss by IHC and were further classified as LOF), while 9 were classified as TA + and preserved ATRX expression by IHC (8 GBM and 1 OD), considered likely secondary mutations (Sup. Table 1). Another factor to be taken into account to classify a mutation as pathogenic is its impact on protein translation. Mutations from both databases were reported across all 36 exons of ATRX, with higher frequencies observed in the ADD and helicase domains. Frameshift and nonsense mutations (Fig. 4 , lower track) were distributed randomly, with only 30% (153/504) located within functional domains. In contrast, 59% of missense mutations occurred within functional domains (ADD, SNF2-related, and helicase C-terminal). Interestingly, this proportion reaches 83% (20/24) for mutations classified as LOF and drops to 39% (5/13) for those deemed non-pathogenic. These findings further support our functional testing results. In conclusion, considering the TMM as the gold standard, the sensitivity of IHC is 74% (57/87) but decreases to 44% (8/18) when focused specifically on samples with missense alterations. Among all the NGS-detected alterations, 81% were associated with ALT + status, but once more this percentage drops to 68% when considering the more challenging missense mutations. These results underscore the importance of functional TMM testing to improve diagnostic accuracy. Discussion Numerous approaches have been proposed to determine the TMM in tumors. Beyond the reference standard functional assays such as C-circle detection, TeloFISH, and telomere Southern blot (Telo-Blot), recent studies have explored NGS-based modeling. For instance, TelomereHunter estimates telomere content (including telomeric variants) using WGS, as initially described by Feuerback [ 6 ], and later by Pickett et al. [ 15 ]. Other algorithms focus on identifying specific telomeric variant repeats (TVR) and interstitial telomeric sequences (ITSs), using truncating ATRX mutations as a surrogate gold standard for ALT positivity [ 31 ]. One recent study integrated TL and TVR distribution but also critically addressed the limitations of using truncating ATRX mutations as a reference. Using C-circle assays, it demonstrated that 27% of tumors with truncating variants were in fact ALT negative [ 23 ]. Importantly, none of these NGS-based models assessed missense mutations, as ATRX-altered samples were mostly used as ALT positive controls, and were typically limited to LOF variants. For instance, in the Pickett et al study [ 15 ], eight of our cohort samples were included, all carrying LOF alterations (frameshift or nonsense mutations). These approaches are useful for large-scale data analysis but remain inadequate for routine diagnostic use. Recently, long-read telomere sequencing has shown high accuracy in TMM classification and can simultaneously provide mutational information, making it a promising alternative, particularly for frozen samples [ 29 ]. However, the TeloDIAG offers several practical advantages: it is most cost-effective, can be completed within two days on FFPE samples, requires only a small amount of DNA, and does not rely on complex bioinformatics. Expanded Horizons for ALT Activation in Brain Tumors and emerging therapeutic options Unexpectedly, a significant proportion of ATRX-altered gliomas (18% in the TCGA cohort and 28% in our local cohort) were not classic IDH-mutant astrocytomas or histone-mutant gliomas. Instead, ATRX alterations were also found in GBMs (12–18%), ODs (2%), and tumors of glioneural origin with MAPK pathway alterations, including NF1, BRAF, and FGFR1 (1–6%). Using the TeloDIAG assay, we confirmed that 7 out of 18 GBM samples with ATRX alterations were indeed ALT+. This finding is consistent with our previous observation that approximately 20% of pTERTwt GBM are ALT+ [ 4 ]. These results expand the landscape of ATRX alterations beyond the traditionally recognized tumor types. Importantly, GBMs with ATRX loss have been associated with better clinical outcome [ 25 ], a trend we also observed in ALT + GBMs, regardless of ATRX status [ 4 ]. This opens new avenues for patient stratification and highlights the potential clinical relevance of TMM determination. Among MAPK pathway-altered tumors, 5 out of 6 cases were ultimately classified as ALT+. We and others have previously reported that specific MAPK pathway mutations (BRAF, FGFR1, and NF1) can promote activation of the ALT mechanism to maintain telomere length [ 26 , 28 ]. In pediatric high-grade gliomas (pHGG), without IDH or p TERT mutations, Telo-FISH analysis identified ALT activity in 24 out of 52 tumors, 9 of which did not harbor histone mutations [ 19 ]. More recently, a study using the CC assay combined with TL measurement confirmed ALT positivity in 38% (24 out of 63) of pHGG, including 40 non-histone-mutant tumors. Notably, 5 of these exhibited mismatch repair deficiency (dMMR), and 3 displayed a high tumor mutation burden (TMB) [ 32 ]. This is particularly relevant since high TMB and dMMR have also been identified in adult GBMs with ATRX loss [ 3 ]. Such molecular features are associated with enhanced immunogenicity and may identify patients who are more likely to benefit from immunotherapy. Supporting this, Hariharan et al. reported that ALT + IDH-mutant astrocytomas exhibit a more active innate immune response compared to their ATRX wild-type telomerase-positive OD counterparts [ 10 ]. These findings further underline the biological distinctiveness of ALT + tumors and suggest a potential link between TMM, DNA damage response and immunotherapeutic responsiveness. Clues of this assumption will soon be available, thanks to the ongoing clinical evaluation of nivolumab in IDH-mutant astrocytoma. In parallel, various therapeutic strategies are being explored to specifically target the ALT pathway. These include recombination inhibitors, PARP-inhibitor, G-quadruplex stabilizers, and ALT-associated PML body (APB) inhibitors [ 7 , 8 , 13 , 36 ]. As an example, in vitro , ALT + H3.3mt have higher DNA damage and better respond to PARP inhibitor than their TA + counterpart [ 13 ]. Given the aggressive nature and poor prognosis of both adult and pediatric high-grade gliomas (HGG), identifying ALT activation through functional testing could have dual value, serving not only as diagnostic tool but also as theranostic marker, guiding patients toward emerging ALT-targeted therapies. TeloDIAG: a simple and universal test for ALT + tumors Using the TeloDIAG assay, we identified 20 ALT + samples among 35 tumors classified as ATRXwt by IHC, representing false negatives. Similarly, Stundon et al. reported a 50% false-negative rate (24 cases) in pediatric HGG when using the CC assay combined with telomere sequencing [ 32 ], a finding corroborated by Minasi et al. [ 19 ]. These discrepancies may be attributed to technical limitations and the challenges of interpreting IHC results, particularly in the presence of missense mutations that preserve ATRX protein expression despite functional loss. In addition, mutations that activate the ALT pathway independently of ATRX also contribute to ALT + phenotypes. Diplas et al. identified SMARCAL1 as a novel ALT activator in gliomas lacking both pTERT and ATRX mutations[ 5 ]. In sarcomas, TOP3A amplification is a known driver of ALT in ATRX wild-type tumors [ 24 ], and this alteration has also been observed in pediatric HGG [ 18 ]. In neuroendocrine pancreatic tumors, DAXX, the histone chaperone partner of ATRX, is frequently altered in ALT + cases, and has similarly been implicated in pHGG [ 30 ]. The spectrum of ALT activators continues to expand, likely varying with glioma subtype and etiology. As new functional testing technologies for ALT become available, identifying these alternative drivers and their biological context is critical for the development of targeted therapies. In this context, functional testing is the most accurate strategy for determining the TMM status, offering a reliable basis for both diagnosis and therapeutic-decision making. Conclusions This study highlights the limitations of ATRX genetic sequencing and IHC assessment for clinical diagnosis, and underscores the value of functional TMM testing, such as TeloDIAG, in accurately identifying ALT + tumors. We provide proof of concept that a simple, robust assay like TeloDIAG can support the development of a curated database to assess the pathogenicity of ATRX alterations. Beyond its diagnostic value, such functional testing could rapidly become a companion biomarker in future clinical trials targeting telomere biology, paving the way for personalized therapeutic strategies in this era of precision oncology. Abbreviations ALT Alternative Lengthening of Telomere AMP amplification ATRX Ataxia alpha thalassemia/mental retardation syndrome X-linked CC C-circle DELINS deletion and/or insertion Fs frameshift GBM glioblastoma H3.3 histone H3.3 mutant glioma HOMO DEL homozygous deletion IHC immune-histo-chemistry LOF loss-of-function MAPK mutant glioma with NF1, BRAF or FGFR1 mutations OD oligodendroglioma na not available NGS Next Generation Sequencing ni non informative TA telomerase activity TC telomere content TL telomere length TMM Telomere Maintenance Mechnism VUS Variant of Unknown Significance Declarations Ethics approval and consent to participate Considering the 100 gliomas from the Pitié Salpétrière Onconeurotek collection (certified 96900), all the patients signed an written informed consent (CPP authorization N° 2023-A02763-42). Competing interests The authors declare that they have no competing interests Funding D.P. benefit from the program “Equipe Labellisée ARC” (ARCPGA2021120004256_4864), and LYriCAN+ (INCa-DGOS-INSERM-ITMO cancer_18003) and local support from the Hospices Civils de Lyon (“jeune chercheur”). The team is part of the and EURACAN networks on rare cancer of the brain and spinal cord. Work in part supported by the LNCC (équipe labellisée) and by a grant from the INCa-DGOS-INSERM (SiRIC CURAMUS) (CC, FB, ADA, MS, LCV). Author Contribution C.G. performed molecular testing, C.C. and A.D.A. collected clinical and biological information and managed sample preparation. C.L. participated in article redaction and data interpretation. F.B. performed histo-molecular diagnosis. D.P. performed database analyses. M.S and D.P design the study and interpreted the results. D.M and P.L supported the development of the TeloDIAG. L.C-V. contributed to the critical revision of the manuscript for important intellectual content and provided grammatical and stylistic editing. D.P. and M.S. wrote the manuscript. Acknowledgement We acknowledge Dr. Karima Mokhtari and Suzan Tran for their help in molecular diagnosis. Availability of data and materials The results published here are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga . All data generated and analyzed during this study are included in this published article and its additional information files. References Abedalthagafi M, Phillips JJ, Kim GE, Mueller S, Haas-Kogen DA, Marshall RE, Croul SE, Santi MR, Cheng J, Zhou S, Sullivan LM, Martinez-Lage M, Judkins AR, Perry A (2013) The alternative lengthening of telomere phenotype is significantly associated with loss of ATRX expression in high-grade pediatric and adult astrocytomas: a multi-institutional study of 214 astrocytomas. 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Supplementary Files AdditionalmaterialTable1.xlsx Cite Share Download PDF Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Acta Neuropathologica Communications → Version 1 posted Editorial decision: Revision requested 02 Sep, 2025 Reviews received at journal 06 Aug, 2025 Reviewers agreed at journal 28 Jul, 2025 Reviewers agreed at journal 27 Jul, 2025 Reviews received at journal 23 Jul, 2025 Reviewers agreed at journal 16 Jul, 2025 Reviewers invited by journal 14 Jul, 2025 Editor assigned by journal 09 Jul, 2025 Submission checks completed at journal 09 Jul, 2025 First submitted to journal 25 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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11:08:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6974009/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6974009/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40478-025-02164-z","type":"published","date":"2025-12-20T15:58:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87043572,"identity":"1361f533-af89-469b-aac9-1e301dc2450a","added_by":"auto","created_at":"2025-07-18 14:18:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":169223,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHistomolecular Characterization of the Two Cohorts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDistribution of glioma subtypes (left), types of \u003cem\u003eATRX\u003c/em\u003egene alterations (middle), and ATRX immunolabeling status (right) in the selected TCGA cohorts (N = 591 \u003cem\u003eATRX\u003c/em\u003e alterations corresponding to 539 tumors) (a) and in our local dataset (N = 100 tumors with 93 \u003cem\u003eATRX\u003c/em\u003ealterations) (b). Abbreviations: GBM - glioblastoma; H3.3 - histone H3.3-mutant glioma; MAPK mutant - gliomas with NF1, BRAF, or FGFR1 mutations; OD - oligodendroglioma; Fs - frameshift; DELINS - deletion and/or insertion; AMP - amplification; HOMO DEL – homozygous or hemizygous deletion; na - not available.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6974009/v1/5971e394f74a9451fdf0a255.png"},{"id":87042277,"identity":"79039ef6-6819-4caf-8339-6e29d8128bd8","added_by":"auto","created_at":"2025-07-18 14:10:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67820,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTMM-related Information in the TCGA cohort\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe EXTEND signature (N=191), as well as the expression levels of \u003cem\u003eATRX\u003c/em\u003e and \u003cem\u003eTERT\u003c/em\u003e(N=264) were retrieved for the TCGA cohort. The control wild-type (WT) samples are IDHwt GBM. WT – wild type; LOF- loss-of-function; DEL- homo/hemizygous deletion; Mis-misense; * - one hit; ** two hits; p-value : NS – non significant; * \u0026lt;0.01; **\u0026lt;0.001; ***\u0026lt;0.0001\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6974009/v1/e62888eac056fb922039a446.png"},{"id":87042285,"identity":"5e16128d-dd09-47a5-8cbb-dfbda0850f11","added_by":"auto","created_at":"2025-07-18 14:10:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":222915,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional TMM Testing in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eATRX\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-Altered Gliomas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) TMM classification as a function of histomolecular diagnostic markers (IDH1/2 mutations, \u003cem\u003epTERT\u003c/em\u003e mutations, 1p/19q codeletion), ATRX protein loss (IHC), or \u003cem\u003eATRX\u003c/em\u003e gene mutations (NGS). (b) distribution of TMM and ATRX (IHC) status according to glioma subtype. c) Functional TMM results (ALT+ or TA+) as a function of ATRX immunolabelling status for LOF alterations (N=64) and missense mutations (N=28) (N=8 na values). *: one residual allele; **: no WT allele; SNP - single nucleotide polymorphism; clonal alteration; na - not available.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6974009/v1/958d2b9aff0c84b0d88d0da2.png"},{"id":87043575,"identity":"1a133736-7c1f-4659-a719-0060fa7ee355","added_by":"auto","created_at":"2025-07-18 14:18:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":132643,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eATRX\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e Gene Alterations Across ATRX Protein Domains\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ATRX coding sequence is represented in the center, with grey arrows indicating exon-exon junctions. Functional domains are highlighted in red: the ADD (ATRX-DNMT3-DNMT3L) domain, involved in binding H3K9me\u003csup\u003e3\u003c/sup\u003e marks, and the two helicase domains (ATPase and C-terminal). Interaction domains are indicated in green for the following partners: EZH2 (enhancer of zeste homolog 2), HP1α (heterochromatin protein 1 alpha), MECP2 (methyl-CpG binding protein 2), and DAXX (death-domain associated protein). Localization signals, such as nuclear localization signals 1 and 2 (NLS1, NLS2) and PML nuclear bodies (PML-NB), are shown in grey. Above the gene, circles represent missense mutations classified as pathogenic (red), benign (green), or of unknown significance (grey). Below the gene, open red circles indicate frameshift, splice site mutation or rearrangement while red crosses indicate nonsense mutations. Abbreviations: VUS - variant of unknown significance; LOF - loss of function; Fs: frameshift.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6974009/v1/8389098ac22e9c45efdd5207.png"},{"id":98814163,"identity":"ce735afa-e1e7-4ee0-8563-c2a79a9f7fba","added_by":"auto","created_at":"2025-12-22 16:11:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1327807,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6974009/v1/13df43c0-a7d3-4cbb-ab72-11af7a1b86e9.pdf"},{"id":87043571,"identity":"b2ef9588-cbdf-4a60-b913-a28e5f6896e7","added_by":"auto","created_at":"2025-07-18 14:18:04","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":55339,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalmaterialTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6974009/v1/11179a7311b742ab11ab1d02.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Functional Assessment of ATRX Alterations Improves Glioma Diagnosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eATRX\u003c/em\u003e stands for X-linked alpha-thalassemia/mental retardation syndrome, due to its initial identification in patients with severe psychomotor retardation, characteristic facial features, genital abnormalities, and alpha-thalassemia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. ATRX exhibits ATP-dependent nucleosome remodeling activity and is specialized in depositing the histone variant H3.3 at repetitive, transcriptionally inactive sites, such as pericentromeric and telomeric heterochromatin [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. ATRX also contributes to telomere maintenance and replication, partly by regulating the formation and/or resolution of G-quadruplex structures (intramolecular rearrangements of the telomeric G-rich strand) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and R-loops [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] (RNA:DNA heteroduplexes). Hence, ATRX loss induces replicative stress at telomeres [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and its inactivation facilitates the initiation of the \u0026ldquo;alternative lengthening of telomere\u0026rdquo; (ALT) process [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. ALT is an \"alternative\" telomere maintenance mechanism (TMM) to telomerase reactivation, used by 7\u0026ndash;10% of tumors to maintain telomere length and avoid senescence or mitotic crisis. This process relies on aberrant repair mechanism, produces extrachromosomal telomere sequences (ECTR), mainly occurs in ALT-associated PML bodies (APBs), and results in long heterogeneous telomeres. Thus, ALT can be detected on the basis of telomere length by Telo-FISH, Telo-qPCR or long read sequencing. The latter two technologies also quantify ECTR, such as C-circle (CC), which are partially double-stranded telomeric circle detected after a pre-amplification step [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn humans, neuroepithelial and mesenchymal tumors, such as gliomas and sarcomas, show the highest rates of ALT activation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Importantly, in gliomas, ATRX loss (detected by immunohistochemistry) is a diagnostic criterion for grade 2 to 4 IDH-mutant astrocytomas, which represent 20\u0026ndash;25% of diffuse gliomas. ATRX loss is also frequently observed in H3.3-mutated gliomas (G34R/V and K27M), including nearly 100% of hemispheric G34R/V-mutant gliomas and approximately 30% of midline diffuse gliomas [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. ATRX loss is often associated with \u003cem\u003eTP53\u003c/em\u003e loss and genomic instability [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Other diffuse gliomas, such as glioblastomas (GBM, 65% of gliomas) and IDH1/2-mutant oligodendrogliomas (OD, 10% of gliomas), typically maintain their telomeres by reactivating the telomerase enzyme through mutations in \u003cem\u003eTERT\u003c/em\u003e (telomerase reverse transcriptase) promoter (p\u003cem\u003eTERT\u003c/em\u003emt), which leads to TERT re-expression [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRoutine detection of ATRX loss by immunohistochemistry (IHC) faces two significant challenges: (i) inter-observer variability, and (ii) inability to detect mutations that do not affect protein stability, resulting in 11 to 21% false-negative results compared to the Telo-FISH method [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Sequencing of the \u003cem\u003eATRX\u003c/em\u003e gene, which spans approximately 300 kb and includes 36 exons, has recently become an alternative due to the widespread adoption of next-generation sequencing (NGS). However, interpreting the clinical significance of mutations remains challenging in the absence of a functional database for \u003cem\u003eATRX\u003c/em\u003e. While hemi/homozygous deletion, frameshift and re-arrangement are considered as loss-of-function (LOF) and \u0026ldquo;probably pathogenic\u0026rdquo; alterations, the impact of missense mutations and small in-frame insertions/deletions remains unclear.\u003c/p\u003e\u003cp\u003eWe therefore propose (i) to exhaustively describe the spectrum of \u003cem\u003eATRX\u003c/em\u003e alterations in a large cohort of 591 gliomas from the TCGA, in relation to published data on TMM, and (ii) to functionally assess the ALT process in a cohort of 100 gliomas, correlating findings with standard clinical diagnostic criteria (NGS, IHC). Importantly, these cohorts include gliomas beyond astrocytomas, covering the full spectrum of contexts in which \u003cem\u003eATRX\u003c/em\u003e mutations occur. For functional testing, we employed the TeloDIAG, a combined assay that integrates telomere content quantification [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] with CC detection [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], thereby providing a robust evaluation of the functional consequences of \u003cem\u003eATRX\u003c/em\u003e mutations for clinical glioma diagnosis.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cb\u003eDesign and setting of the study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the first dataset, clinical and histomolecular information was extracted from the cBioPortal interface of The cancer Genome Atlas (TCGA). A total of 12 studies were selected: brain_cptac_2020, difg_glass_2019, gbm_columbia_2019, gbm_cptac_2021, gbm_mayo_pdx_sarkaria_2019, gbm_tcga, glioma_msk_2018, glioma_mskcc_2019, lgg_ucsf_2014, lgggbm_tcga_pub, odg_msk_2017, and past_dkfz_heidelberg_2013. After removing duplicates (on the basis of sample ID), 3,924 cases were compiled. Filtering for \u003cem\u003eATRX\u003c/em\u003e alterations resulted in the selection of 539 samples, encompassing 591 genetic alterations. The allelic variant frequency (VAF) of \u003cem\u003eATRX\u003c/em\u003e mutations, ranging from 0.03 to 0.99, was compared to the VAF of other alterations within the same sample and classified as either *heterozygous (wild-type allele present) or **homozygous/hemizygous (no wild-type allele)(Sup. Table\u0026nbsp;1). Frameshift, nonsense, splicing-site mutations and gene rearrangements were classified as loss-of-function (LOF) alterations. Diagnoses were assigned according to the WHO 2021 classification, based on available histological and molecular parameters.\u003c/p\u003e\u003cp\u003eThe second dataset consists of 100 gliomas from the Piti\u0026eacute; Salp\u0026eacute;tri\u0026egrave;re Onconeurotek collection (certified 96900), which had previously undergone \u003cem\u003eATRX\u003c/em\u003e sequencing for diagnostic purposes. All the patients signed a written informed consent (CPP authorization N\u0026deg; 2023-A02763-42). These samples were included for functional testing. Pathogenicity data for missense mutations were available for only 4 variants in ClinVar database. Figures were done using excel and powerpoint (Microsoft).\u003c/p\u003e\u003cp\u003e\u003cb\u003eALT status determination\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo telomere parameters were assessed using the TeloDIAG assay, as previously described [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]: telomere content, corresponding to telomere length (TL), and C-circles (CC). TL was quantified by qPCR relative to the reference gene (\u003cem\u003eRPLP0\u003c/em\u003e) using the formula (TL\u0026thinsp;=\u0026thinsp;E\u003csup\u003e\u0026minus;\u0026thinsp;CT\u003c/sup\u003e\u003csub\u003eTEL\u003c/sub\u003e/E\u003csup\u003e\u0026minus;\u0026thinsp;CT\u003c/sup\u003e\u003csub\u003eRPLP0\u003c/sub\u003e). C-circles, if present, were amplified by rolling circle amplification using the Φ29 DNA polymerase. A sample was considered positive for CC if the ratio of telomeric sequences quantification with and without incubation with the Φ29 (TL\u003csub\u003e+Φ\u003c/sub\u003e/TL\u003csub\u003e\u0026minus;Φ\u003c/sub\u003e) was \u0026ge;\u0026thinsp;1.3. In regard with our previous publication, samples were considered ALT\u0026thinsp;+\u0026thinsp;in two situations : if CC were detectable or in situation of long telomeres (TL\u0026thinsp;\u0026gt;\u0026thinsp;1.7 arbitrary units [au]) with or without detectable CC (fixative-induced DNA oxidation and breakage in old samples can open circles and preclude amplification, as previously demonstrated [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]). Samples negative for CC (CC\u0026thinsp;\u0026lt;\u0026thinsp;1.3) and with short telomeres (TL\u0026thinsp;\u0026lt;\u0026thinsp;1.7au) were considered to maintain telomeres via telomerase activity.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses and boxplots were generated using R software (R Core Team (2024). \u003cem\u003eR: A language and environment for statistical computing\u003c/em\u003e. R Foundation for Statistical Computing, Vienna, Austria). Comparisons of group means were conducted using the non-parametric Wilcoxon rank-sum test.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eInformation on\u003c/strong\u003e \u003cstrong\u003eATRX\u003c/strong\u003e \u003cstrong\u003ealterations in public datasets\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the informativeness of clinical testing, we aggregated data from 12 glioma-focused studies available in the TCGA database. After removing duplicates and filtering by diagnosis according to the WHO 2021 criteria, we selected 539 glioma samples with \u003cem\u003eATRX\u003c/em\u003e variants identified by NGS. The majority of gliomas were astrocytomas (80%), but the dataset also included glioblastomas (GBM, 12%) and oligodendrogliomas (OD, 2%), which are typically p\u003cem\u003eTERT\u003c/em\u003emt telomerase-positive (TA+) tumors (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). These 539 samples contained a total of 591 \u003cem\u003eATRX\u003c/em\u003e variants, as 47 tumors exhibited multiple \u003cem\u003eATRX\u003c/em\u003e alterations. The types of alterations included hemi- or homozygous deletions (4.5%), nonsense mutations (25%), frameshift mutations (44%), missense mutations (18%), splice site mutations (6%), and rare deletions-insertions or rearrangements (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). Except for missense mutations and small INDELs, all these alterations can be classified as loss-of-function (LOF) variants. To further analyze missense mutations, we used immunohistochemistry (IHC) ATRX status, which was available for 218 tumors (40%). Of note, only 2% (N\u0026thinsp;=\u0026thinsp;11) of these samples retained ATRX expression (ATRXwt), including 10 out of the 11 cases with hemi- or homozygous gene deletions, which are typically associated with protein loss. Similarly, all samples bearing missense mutations (N\u0026thinsp;=\u0026thinsp;32) were classified as lost for ATRX protein (ATRXloss), despite the expectation that the protein should still be expressed, albeit non-functional. This suggests potential biases in copy number variation (CNV) detection and/or misinterpretation of IHC results. Indeed, high interoperator variability has been reported for ATRX testing compared to functional testing by Telo-FISH [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. Therefore, IHC data were further ultimately considered non-informative for this analysis.\u003c/p\u003e\n\u003cp\u003eSeveral publications have developed algorithms to predict ALT or TA prediction based on whole-genome sequencing (WGS) [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e] [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e] [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. We examined these predictions for common TCGA samples. However, these models have almost exclusively included LOF alterations, such as frameshift mutations, and were mainly used as controls to validate the models. As a result, no additional relevant information was retrieved except for two missense mutations, Y2418N and E2172A, classified as ALT- (Supp. Table\u0026nbsp;1). Alternatively, data from the EXTEND signature [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e], based on RNA-seq analysis and estimating the telomerase activity spectrum, were available for 114 out of the 529 \u003cem\u003eATRX\u003c/em\u003e-altered samples. Additionally, we included 77 ATRXwt IDHwt GBM samples as controls. The EXTEND signature aligned with the classification of tumors bearing \u003cem\u003eATRX\u003c/em\u003e alterations, all of which belonging to the ALT group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). However, since the EXTEND signature was developed by comparing p\u003cem\u003eTERT\u003c/em\u003emt samples (OD and GBM) versus ATRX/DAXX altered samples (mostly astrocytomas), it may reflect tumor cell origin/entity rather than TMM status, as demonstrated by Nonneville et al.[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. We then inquired the expression levels of \u003cem\u003eATRX\u003c/em\u003e and \u003cem\u003eTERT\u003c/em\u003e using RNA-seq data available from 197 samples. \u003cem\u003eTERT\u003c/em\u003e expression was nearly absent in most tumors harboring \u003cem\u003eATRX\u003c/em\u003e variants. Interestingly, three single missense variants (V128A, Y2418N, R1131G), found in OD and GBM, were associated with \u003cem\u003eTERT\u003c/em\u003e expression and preserved ATRX expression; among these, Y2418N was notable. Regarding \u003cem\u003eATRX\u003c/em\u003e expression levels, LOF variants showed a clear decrease (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb), whereas single missense variants exhibited no reduction compared to WT samples, consistent with the fact that amino-acid changes does not necessarily lead to protein loss. Overall, of the 106 missense mutations analyzed, only four could be classified as \u0026ldquo;probably benign\u0026rdquo; or \u0026ldquo;benign\u0026rdquo;, and no additional meaningful insight into the TMM could be derived from the other samples.\u003c/p\u003e\n\u003cp\u003eIn summary, we identified 106 missense mutations across 80 samples: 71 samples harbored a single hit, 9 samples had two missense mutations (N\u0026thinsp;=\u0026thinsp;18), and 17 samples carried another LOF alteration. All variants were classified as \u0026ldquo;non informative\u0026rdquo;, except for two classed as benign (Y2418N and E2172A) and two as probably benign (V128A, R1131G) [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. These findings highlight the limitations of NGS-based predictive models and emphasize the need for functional studies to improve the annotation of clinical databases for molecular diagnosis in glioma.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional Testing of ALT status in\u003c/strong\u003e \u003cstrong\u003eATRX\u003c/strong\u003e\u003cstrong\u003e-altered gliomas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs emphasized by Nonneville et al., the CC assay should be used to accurately assess the TMM [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. We have thus investigated directly the TMM activated by tumors in a cohort of 100 gliomas from the Piti\u0026eacute;-Salp\u0026ecirc;tri\u0026egrave;re Tumor bank, including 92 with \u003cem\u003eATRX\u003c/em\u003e mutations. This cohort comprised 53 IDH1/2-mutant astrocytomas, 19 histone-mutant tumors, 6 with MAPK pathway alterations (BRAF, NF1), 18 GBM (13 p\u003cem\u003eTERT\u003c/em\u003emt), 2 OD (1p\u003cem\u003eTERT\u003c/em\u003emt), and 2 unclassified gliomas. Frameshift, nonsense and missense mutations accounted for 45%, 18% and 29% of all mutations, respectively, consistent with the proportions observed in the TCGA cohort (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb)(rearrangements and copy number alterations were not addresses in this study). Regarding ATRX status determined by IHC (N\u0026thinsp;=\u0026thinsp;95), protein expression was lost in 63% (60/95) of tested samples (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e\n\u003cp\u003eThe TeloDIAG assay [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e] assesses the presence of CC and TL to identify ALT\u0026thinsp;+\u0026thinsp;samples; its ALT- counterparts was defined as TA+. Using this classification, 80% of the samples were ALT+ (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea,b). Regarding diagnosis, 96% (51/53) of astrocytomas were classified as ALT+ (42 of which showed ATRX loss), along with 79% (15/19) of histone-mutant tumors, consistent with previous studies [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Interestingly, among tumors usually assumed to re-express the telomerase, 39% (7/18) of GBMs with \u003cem\u003eATRX\u003c/em\u003e alteration were indeed ALT+ (1/7 was ATRXloss, 4/7 were also p\u003cem\u003eTERT\u003c/em\u003emt (regarding the VAF, 2 were subclonal TMM activation, 1 non available, 1 same \u003cem\u003eATRX-pTERT\u003c/em\u003e VAF) and 83% (5/6) of MAPK activated gliomas also exhibited ALT\u0026thinsp;+\u0026thinsp;status (3/5 with ATRXloss, all p\u003cem\u003eTERT\u003c/em\u003ewt). This finding is noteworthy as the subcellular mechanisms and molecular alterations differ between ALT and telomerase contexts, impacting clinical behavior and tumor evolution [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Notably 12\u0026ndash;18% of \u003cem\u003eATRX\u003c/em\u003e-altered samples identified by NGS in our database were GBMs, of which 39% (7/18) were ALT+.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional testing identifies pathogenic missense\u003c/strong\u003e \u003cstrong\u003eATRX\u003c/strong\u003e \u003cstrong\u003emutations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComparing immune-histochemical detection of ATRX loss (N\u0026thinsp;=\u0026thinsp;95) with TMM status, 72 samples showed concordance: 57 were ATRXloss/ALT\u0026thinsp;+\u0026thinsp;and 15 were TA+/ATRXwt. However, three samples with ATRX loss by IHC were classified as TA\u0026thinsp;+\u0026thinsp;by functional testing (false positives for IHC). These included a glioneural tumor with a heterozygous alteration, a GBM with a clonal alteration, and a histone-mutant tumor without sequencing data, possibly reflecting secondary hits without biological significance. Additionally, 20 samples were ALT\u0026thinsp;+\u0026thinsp;but showed wild-type ATRX by IHC (false negatives). This was expected for 10 samples with missense mutations, but surprising for 7 samples bearing frameshift or nonsense alterations. Overall, using TMM status as the gold standard, IHC detection of ATRX loss showed a sensitivity of 74% and specificity of 83%.\u003c/p\u003e\n\u003cp\u003eConsidering the type of alteration in relation to the detected TMM, 86% (56/64) of LOF alterations (frameshift and nonsense mutations) were classified as ALT+ (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec). Among the 8 samples with LOF alteration but TA\u0026thinsp;+\u0026thinsp;status, 5 were ATRXwt by IHC, 2 showed ATRXloss (a GBM with a clonal mutation and a glioneural with a heterozygous mutation), and 1 lacked IHC data. These observations may be linked to either secondary mutations without biological impact or minor subclonal alterations.\u003c/p\u003e\n\u003cp\u003eRegarding the 28 missense alterations (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec), 19 were detected as ALT+ (8 of which showed ATRX loss by IHC and were further classified as LOF), while 9 were classified as TA\u0026thinsp;+\u0026thinsp;and preserved ATRX expression by IHC (8 GBM and 1 OD), considered likely secondary mutations (Sup. Table\u0026nbsp;1).\u003c/p\u003e\n\u003cp\u003eAnother factor to be taken into account to classify a mutation as pathogenic is its impact on protein translation. Mutations from both databases were reported across all 36 exons of ATRX, with higher frequencies observed in the ADD and helicase domains. Frameshift and nonsense mutations (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, lower track) were distributed randomly, with only 30% (153/504) located within functional domains. In contrast, 59% of missense mutations occurred within functional domains (ADD, SNF2-related, and helicase C-terminal). Interestingly, this proportion reaches 83% (20/24) for mutations classified as LOF and drops to 39% (5/13) for those deemed non-pathogenic. These findings further support our functional testing results.\u003c/p\u003e\n\u003cp\u003eIn conclusion, considering the TMM as the gold standard, the sensitivity of IHC is 74% (57/87) but decreases to 44% (8/18) when focused specifically on samples with missense alterations. Among all the NGS-detected alterations, 81% were associated with ALT\u0026thinsp;+\u0026thinsp;status, but once more this percentage drops to 68% when considering the more challenging missense mutations. These results underscore the importance of functional TMM testing to improve diagnostic accuracy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNumerous approaches have been proposed to determine the TMM in tumors. Beyond the reference standard functional assays such as C-circle detection, TeloFISH, and telomere Southern blot (Telo-Blot), recent studies have explored NGS-based modeling. For instance, TelomereHunter estimates telomere content (including telomeric variants) using WGS, as initially described by Feuerback [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and later by Pickett et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Other algorithms focus on identifying specific telomeric variant repeats (TVR) and interstitial telomeric sequences (ITSs), using truncating ATRX mutations as a surrogate gold standard for ALT positivity [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. One recent study integrated TL and TVR distribution but also critically addressed the limitations of using truncating ATRX mutations as a reference. Using C-circle assays, it demonstrated that 27% of tumors with truncating variants were in fact ALT negative [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Importantly, none of these NGS-based models assessed missense mutations, as ATRX-altered samples were mostly used as ALT positive controls, and were typically limited to LOF variants. For instance, in the Pickett et al study [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], eight of our cohort samples were included, all carrying LOF alterations (frameshift or nonsense mutations).\u003c/p\u003e\u003cp\u003eThese approaches are useful for large-scale data analysis but remain inadequate for routine diagnostic use. Recently, long-read telomere sequencing has shown high accuracy in TMM classification and can simultaneously provide mutational information, making it a promising alternative, particularly for frozen samples [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, the TeloDIAG offers several practical advantages: it is most cost-effective, can be completed within two days on FFPE samples, requires only a small amount of DNA, and does not rely on complex bioinformatics.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExpanded Horizons for ALT Activation in Brain Tumors and emerging therapeutic options\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUnexpectedly, a significant proportion of ATRX-altered gliomas (18% in the TCGA cohort and 28% in our local cohort) were not classic IDH-mutant astrocytomas or histone-mutant gliomas. Instead, \u003cem\u003eATRX\u003c/em\u003e alterations were also found in GBMs (12\u0026ndash;18%), ODs (2%), and tumors of glioneural origin with MAPK pathway alterations, including NF1, BRAF, and FGFR1 (1\u0026ndash;6%). Using the TeloDIAG assay, we confirmed that 7 out of 18 GBM samples with \u003cem\u003eATRX\u003c/em\u003e alterations were indeed ALT+. This finding is consistent with our previous observation that approximately 20% of pTERTwt GBM are ALT+ [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These results expand the landscape of \u003cem\u003eATRX\u003c/em\u003e alterations beyond the traditionally recognized tumor types. Importantly, GBMs with ATRX loss have been associated with better clinical outcome [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], a trend we also observed in ALT\u0026thinsp;+\u0026thinsp;GBMs, regardless of \u003cem\u003eATRX\u003c/em\u003e status [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This opens new avenues for patient stratification and highlights the potential clinical relevance of TMM determination.\u003c/p\u003e\u003cp\u003eAmong MAPK pathway-altered tumors, 5 out of 6 cases were ultimately classified as ALT+. We and others have previously reported that specific MAPK pathway mutations (BRAF, FGFR1, and NF1) can promote activation of the ALT mechanism to maintain telomere length [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In pediatric high-grade gliomas (pHGG), without IDH or p\u003cem\u003eTERT\u003c/em\u003e mutations, Telo-FISH analysis identified ALT activity in 24 out of 52 tumors, 9 of which did not harbor histone mutations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. More recently, a study using the CC assay combined with TL measurement confirmed ALT positivity in 38% (24 out of 63) of pHGG, including 40 non-histone-mutant tumors. Notably, 5 of these exhibited mismatch repair deficiency (dMMR), and 3 displayed a high tumor mutation burden (TMB) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This is particularly relevant since high TMB and dMMR have also been identified in adult GBMs with ATRX loss [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Such molecular features are associated with enhanced immunogenicity and may identify patients who are more likely to benefit from immunotherapy. Supporting this, Hariharan et al. reported that ALT\u0026thinsp;+\u0026thinsp;IDH-mutant astrocytomas exhibit a more active innate immune response compared to their ATRX wild-type telomerase-positive OD counterparts [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These findings further underline the biological distinctiveness of ALT\u0026thinsp;+\u0026thinsp;tumors and suggest a potential link between TMM, DNA damage response and immunotherapeutic responsiveness. Clues of this assumption will soon be available, thanks to the ongoing clinical evaluation of nivolumab in IDH-mutant astrocytoma.\u003c/p\u003e\u003cp\u003eIn parallel, various therapeutic strategies are being explored to specifically target the ALT pathway. These include recombination inhibitors, PARP-inhibitor, G-quadruplex stabilizers, and ALT-associated PML body (APB) inhibitors [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. As an example, \u003cem\u003ein vitro\u003c/em\u003e, ALT\u0026thinsp;+\u0026thinsp;H3.3mt have higher DNA damage and better respond to PARP inhibitor than their TA\u0026thinsp;+\u0026thinsp;counterpart [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given the aggressive nature and poor prognosis of both adult and pediatric high-grade gliomas (HGG), identifying ALT activation through functional testing could have dual value, serving not only as diagnostic tool but also as theranostic marker, guiding patients toward emerging ALT-targeted therapies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTeloDIAG: a simple and universal test for ALT\u0026thinsp;+\u0026thinsp;tumors\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUsing the TeloDIAG assay, we identified 20 ALT\u0026thinsp;+\u0026thinsp;samples among 35 tumors classified as ATRXwt by IHC, representing false negatives. Similarly, Stundon et al. reported a 50% false-negative rate (24 cases) in pediatric HGG when using the CC assay combined with telomere sequencing [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], a finding corroborated by Minasi et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These discrepancies may be attributed to technical limitations and the challenges of interpreting IHC results, particularly in the presence of missense mutations that preserve ATRX protein expression despite functional loss. In addition, mutations that activate the ALT pathway independently of ATRX also contribute to ALT\u0026thinsp;+\u0026thinsp;phenotypes. Diplas et al. identified \u003cem\u003eSMARCAL1\u003c/em\u003e as a novel ALT activator in gliomas lacking both \u003cem\u003epTERT\u003c/em\u003e and \u003cem\u003eATRX\u003c/em\u003e mutations[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In sarcomas, \u003cem\u003eTOP3A\u003c/em\u003e amplification is a known driver of ALT in \u003cem\u003eATRX\u003c/em\u003e wild-type tumors [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and this alteration has also been observed in pediatric HGG [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In neuroendocrine pancreatic tumors, DAXX, the histone chaperone partner of ATRX, is frequently altered in ALT\u0026thinsp;+\u0026thinsp;cases, and has similarly been implicated in pHGG [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The spectrum of ALT activators continues to expand, likely varying with glioma subtype and etiology. As new functional testing technologies for ALT become available, identifying these alternative drivers and their biological context is critical for the development of targeted therapies. In this context, functional testing is the most accurate strategy for determining the TMM status, offering a reliable basis for both diagnosis and therapeutic-decision making.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study highlights the limitations of ATRX genetic sequencing and IHC assessment for clinical diagnosis, and underscores the value of functional TMM testing, such as TeloDIAG, in accurately identifying ALT\u0026thinsp;+\u0026thinsp;tumors. We provide proof of concept that a simple, robust assay like TeloDIAG can support the development of a curated database to assess the pathogenicity of \u003cem\u003eATRX\u003c/em\u003e alterations. Beyond its diagnostic value, such functional testing could rapidly become a companion biomarker in future clinical trials targeting telomere biology, paving the way for personalized therapeutic strategies in this era of precision oncology.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlternative Lengthening of Telomere\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAMP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eamplification\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cem\u003eATRX\u003c/em\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e\u003cem\u003eAtaxia alpha thalassemia/mental retardation syndrome X-linked\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-circle\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDELINS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003edeletion and/or insertion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eframeshift\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGBM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eglioblastoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eH3.3\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehistone H3.3 mutant glioma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHOMO DEL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehomozygous deletion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eimmune-histo-chemistry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLOF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eloss-of-function\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMAPK mutant\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eglioma with NF1, BRAF or FGFR1 mutations\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eoligodendroglioma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ena\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enot available\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNGS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNext Generation Sequencing\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eni\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enon informative\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etelomerase activity\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etelomere content\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etelomere length\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTMM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTelomere Maintenance Mechnism\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVUS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVariant of Unknown Significance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsidering the 100 gliomas from the Piti\u0026eacute; Salp\u0026eacute;tri\u0026egrave;re Onconeurotek collection (certified 96900), all the patients signed an written informed consent (CPP authorization N\u0026deg; 2023-A02763-42).\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;\u003c/h2\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eD.P. benefit from the program \u0026ldquo;Equipe Labellis\u0026eacute;e ARC\u0026rdquo; (ARCPGA2021120004256_4864), and LYriCAN+ (INCa-DGOS-INSERM-ITMO cancer_18003) and local support from the Hospices Civils de Lyon (\u0026ldquo;jeune chercheur\u0026rdquo;). The team is part of the and EURACAN networks on rare cancer of the brain and spinal cord. Work in part supported by the LNCC (\u0026eacute;quipe labellis\u0026eacute;e) and by a grant from the INCa-DGOS-INSERM (SiRIC CURAMUS) (CC, FB, ADA, MS, LCV).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eC.G. performed molecular testing, C.C. and A.D.A. collected clinical and biological information and managed sample preparation. C.L. participated in article redaction and data interpretation. F.B. performed histo-molecular diagnosis. D.P. performed database analyses. M.S and D.P design the study and interpreted the results. D.M and P.L supported the development of the TeloDIAG. L.C-V. contributed to the critical revision of the manuscript for important intellectual content and provided grammatical and stylistic editing. D.P. and M.S. wrote the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe acknowledge Dr. Karima Mokhtari and Suzan Tran for their help in molecular diagnosis.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe results published here are in part based upon data generated by the TCGA Research Network: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cancer.gov/tcga\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eAll data generated and analyzed during this study are included in this published article and its additional information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbedalthagafi M, Phillips JJ, Kim GE, Mueller S, Haas-Kogen DA, Marshall RE, Croul SE, Santi MR, Cheng J, Zhou S, Sullivan LM, Martinez-Lage M, Judkins AR, Perry A (2013) The alternative lengthening of telomere phenotype is significantly associated with loss of ATRX expression in high-grade pediatric and adult astrocytomas: a multi-institutional study of 214 astrocytomas. 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Acta Neuropathol 126:443\u0026ndash;451. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00401-013-1156-z\u003c/span\u003e\u003cspan address=\"10.1007/s00401-013-1156-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao R, Xu M, Yu X, Wondisford AR, Lackner RM, Salsman J, Dellaire G, Chenoweth DM, O\u0026rsquo;Sullivan RJ, Zhao X, Zhang H (2024) SUMO promotes DNA repair protein collaboration to support alternative telomere lengthening in the absence of PML. Genes Dev. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/gad.351667.124\u003c/span\u003e\u003cspan address=\"10.1101/gad.351667.124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anec","sideBox":"Learn more about [Acta Neuropathologica Communications](https://actaneurocomms.biomedcentral.com/)","snPcode":"40478","submissionUrl":"https://submission.springernature.com/new-submission/40478/3","title":"Acta Neuropathologica Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"glioblastoma, IDH-mutant, ATRX, ALT, telomere, database, telomerase, MAPK, extend","lastPublishedDoi":"10.21203/rs.3.rs-6974009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6974009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLoss of ATRX function, a diagnostic criterion of IDH-mutant astrocytoma, is closely associated with alternative lengthening of telomeres (ALT), a telomere maintenance mechanism (TMM). As immunohistochemical (IHC) assessment of ATRX is error-prone, sequencing has been integrated into clinical workflows. While frameshift and nonsense variants can be classified as loss-of-function (LOF) mutations, missense variants remain difficult to interpret.\u003c/p\u003e\u003cp\u003eTo address this, we analyzed \u003cem\u003eATRX\u003c/em\u003e-altered gliomas from TCGA (N\u0026thinsp;=\u0026thinsp;539 tumors, 591 alterations) and a local cohort of 100 diffuse gliomas. Aside from IDH-mutant astrocytomas and H3.3-mutant gliomas, glioblastoma (12\u0026ndash;18%), oligodendroglioma (2%), and MAPK-altered tumors (1\u0026ndash;6%) were consistently represented in both cohorts. Missense mutations accounted for 18% (TCGA) and 29% (local) of variants. Functional annotation of TCGA missense mutations using IHC, NGS-based TMM status, transcript levels, and RNA-seq\u0026ndash;derived telomerase signatures (EXTEND) allowed us to functionally annotate only 3 of 106 variants. Therefore, we directly assessed the TMM status in the local cohort, using the TeloDIAG assay and retrieved 80% of ALT-positive samples, corresponding to 96% (N\u0026thinsp;=\u0026thinsp;53) of IDH-mutant astrocytomas and 79% (N\u0026thinsp;=\u0026thinsp;19) of histone-mutant gliomas, as expected. Importantly, ALT activity was also observed in 39% (N\u0026thinsp;=\u0026thinsp;18) of glioblastomas and 83% (N\u0026thinsp;=\u0026thinsp;6) of MAPK-altered gliomas, indicating potential implications for clinical behavior and therapeutic targeting.\u003c/p\u003e\u003cp\u003eOverall, 68% (N\u0026thinsp;=\u0026thinsp;28) of missense mutations were functionally classified as LOF. Notably, 83% (N\u0026thinsp;=\u0026thinsp;24) of them were located within the major functional domains of the ATRX protein, compared to only 59% when considering all missense mutations, highlighting the functional relevance of the assay. As compared to TeloDIAG, IHC showed limited sensitivity (74%), dropping to 44% (N\u0026thinsp;=\u0026thinsp;18) in cases with missense mutation.\u003c/p\u003e\u003cp\u003eCollectively, these findings emphasize the clinical value of functional TMM assessment in refining glioma diagnosis. Last, targeting of ALT-associated DNA-damage deficiency and immunogenic context is under clinical investigation, highlighting the promising theranostic potential of TMM assessment.\u003c/p\u003e","manuscriptTitle":"Functional Assessment of ATRX Alterations Improves Glioma Diagnosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 14:10:00","doi":"10.21203/rs.3.rs-6974009/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-02T13:55:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-06T15:00:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166631770862427334558594182149242577895","date":"2025-07-28T18:08:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193079795495597034453358717618575443299","date":"2025-07-27T11:40:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-23T13:48:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183867111065063332360952632609363161577","date":"2025-07-16T12:33:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-14T13:41:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-09T12:27:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-09T12:26:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Acta Neuropathologica Communications","date":"2025-06-25T11:00:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anec","sideBox":"Learn more about [Acta Neuropathologica Communications](https://actaneurocomms.biomedcentral.com/)","snPcode":"40478","submissionUrl":"https://submission.springernature.com/new-submission/40478/3","title":"Acta Neuropathologica Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b08c6d48-8f8f-4ce1-8004-461923e1b83f","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:05:42+00:00","versionOfRecord":{"articleIdentity":"rs-6974009","link":"https://doi.org/10.1186/s40478-025-02164-z","journal":{"identity":"acta-neuropathologica-communications","isVorOnly":false,"title":"Acta Neuropathologica Communications"},"publishedOn":"2025-12-20 15:58:07","publishedOnDateReadable":"December 20th, 2025"},"versionCreatedAt":"2025-07-18 14:10:00","video":"","vorDoi":"10.1186/s40478-025-02164-z","vorDoiUrl":"https://doi.org/10.1186/s40478-025-02164-z","workflowStages":[]},"version":"v1","identity":"rs-6974009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6974009","identity":"rs-6974009","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}