Table of Contents

    Topic review

    Recurrent Glioblastoma

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    Submitted by: Pim French

    Definition

    Glioblastoma (GBM) is the most aggressive central nervous system (CNS) primary malignancy in adults, with a median age at diagnosis of 65 years.

    1. Introduction

    The annual incidence of glioblastoma is approximately 3 per 100,000 per person year. The disease is more common in males and incidence increases with age [1][2]. The standard of care in newly diagnosed GBM includes maximal safe surgical resection, followed by radiotherapy and concurrent and adujvant temozolomide (TMZ) [3]. Median overall survival (OS) varies between 12–18 months [4][5] and the 5-year survival in GBM is below 7% [1][6]. In adults, younger age and a good performance status (Karnofsky performance score KPS > 70 or WHO score 0) at diagnosis are favorable prognostic factors [1][4].

    After first line medical management, the tumour virtually always recurs and when it does prognosis is very poor (i.e., median PFS of 1.5–6 months and median OS of 2–9 months) [7][8][9]. Treatment options for recurrent GBM (rGBM) patiens are limited and the management remains a challenge. Loco-regional therapy may be evaluated in selected cases while traditional systemic therapy showed limited efficacy. In recent years, with greater knowledge of the underlying molecular characteristics, a multitude of new drugs and new combination regimens have been tested for efficacy in rGBM patients.

    2. Molecular Characteristics of rGBM

    2.1. MGMT Promoter Methylation in rGBM

    It was first discovered over two decades ago that MGMT promoter methylation is associated with response to alkylating chemotherapy in GBM patients [10]. The predictive role of this biomarker was completed following confirmation in a randomized controlled clinical trial, and further strengthened in two trials in elderly GBM patients [11][12][13]. Perhaps somewhat less well known is the observation that MGMT promoter methylation is also prognostic: GBM patients with a methylated MGMT promoter have a longer survival, irrespective of treatment with alkylating chemotherapy.

    Several studies have shown that MGMT promoter methylation is also prognostic at the time of recurrence in GBM patients. In general, post-progression survival is around 3–4 months longer in patients harbouring MGMT-promoter methylated v unmethylated tumors (10.9 v 7.2 months, 8.4 v 6.6 months, 12.5 v 7.9 months and 13.5 v 8.0 months in studies reported by the German Glioma Network, EORTC 1542 (GSAM), the DIRECTOR trial and the EORTC 26101 trial, respectively) [14][15][16][17]. Most of these studies defined MGMT promoter methylation using data from the primary tumor. This is possible since MGMT promoter methylation is relatively stable. At least three independent studies on paired primary-rGBM samples demonstrated that methylation status is maintained in approximately 70–90% of tumor samples [15][16][18]. Data therefore indicate that patients harbouring MGMT-promoter methylated rGBMs have a slightly better post-progression survival.

    Evidence for a predictive effect of MGMT promoter methylation in response to alkylating chemotherapy in patients with relapsed or rGBM is quite scarce. One study reported improved outcomes in patients with MGMT-promoter methylated v. unmethylated tumors treated with fotemustine, where the opposite was observed when tumors were treated with bevacizumab [19]. As bevacizumab has limited clinical efficacy in GBMs, this study suggests that MGMT-promoter methylation is predictive of response to alkylating chemotherapy at tumor progression. However, other studies did not observe such differences between treatment and control (LOMUSTINE) arms in methylated v unmethylated tumors [20][21][22]. Establishing this potential predictive role, therefore, remains to be determined but is important to guide treatment decisions at tumor recurrence.

    2.2. The Genomic Landscape of rGBMs

    To understand what makes rGBMs unique, and thus expose potential treatment targets, one has to compare differences between tumors at diagnosis and at recurrence. For this review, we will only focus on tumors that were also diagnosed as GBMs (IDH-wildtype, if known) at initial diagnosis: lower grade gliomas (IDH-mutant) that evolve into secondary GBMs represent an entirely different tumor entity with unique evolutionary trajectories. Firstly, and perhaps slightly surprising, the number of mutations in known cancer genes does not appear to increase at tumor recurrence, at least for the majority of tumors [16][23][24][25] (though there is an increase in the overall mutational burden [25]). In line with the stability of the number of mutations in driver genes is the observation that many of them (on average ~80%) are retained in the recurrent tumor [16][24][25][26][27]. One study reported preferential gains of mutations in LTBP4, MSH6, PRDM2 and IGF1R genes [24], though apart from the DNA mismatch repair gene MSH6, these have not been confirmed in other large cohort studies. No common larger chromosomal changes have been documented at tumor progression [16], but some individual gains and losses may show within tumor pairs [28]. Despite this apparent similarity in genetic makeup, there is evidence for gain of selective events in the majority (64%) of recurrent tumors and patients harbouring such tumors have worse outcomes [25].

    Although this relatively large concordance in the genetic makeup between primary and rGBM is true for the majority of tumors, there are some notable exceptions. Firstly, mutation retention is lower in the case of a distant recurrence [26], though distant recurrences are quite rare. Second, despite a generally high mutation retention rate in driver mutations, there are some marked differences between individual genes. For example, mutations in the TERT promoter show the highest mutation retention rate (~90%), whereas mutations in the EGFR gene is at the other end of the spectrum with a retention rate of approximately 50% [16][25][29]. Of note, there can be ‘driver switches’ where the same gene (such as EGFR) is affected in primary and recurrent gliomas, but the mutation differs [16][24]. Hypermutated tumors are the third main exception to the relatively stable genotype ‘rule’. These are detailed in a separate section of this review.

    Cataloguing the retention rate is important for clinicians when designing molecular targeted therapy trials. This is because trials at tumor recurrence are usually based on molecular data from the primary tumor (repeat surgeries are not often performed) and potential loss of a mutation should therefore be taken into account. To give an example, when an objective response rate of ~40% is considered positive, the number of patients to be included in a trial is 41 (assuming a power of 80% and a one-sided alpha of 0.025). However, when the genetic change is lost in 20% of samples, the number of patients to achieve similar power is almost doubled (n = 80) [16].

    Similarities between primary and rGBM are also apparent at RNA level, where unsupervised analysis highlighted a significant overlap between primary and rGBM [30]. Expression-based molecular subtypes are also relatively stable during tumor progression [31][32]. Some changes are however noticeable when looking at the expression of individual genes, for example, in stemness-related genes [33][34]. Methylation classes are also stable at progression in ~85% of cases [31]. This contrasts IDH-mutant low-grade gliomas which, at recurrence, often exhibit lower overall DNA methylation levels, an increase in the frequency of poorer prognostic subclasses and worse outcomes for patients at progression [35][36].

    Despite this similarity between primary and recurrent glioblastomas, there is evidence for considerable intratumoral heterogeneity in both. For example, spatially separated samples taken from the same resection may differ with respect to their genetic makeup [27][37]. Even if most studies on intratumoral heterogeneity have been performed on primary tumor samples it is therefore likely such heterogeneity also exist in recurrent glioblastomas and may affect treatment response [38]. In summary, recurrent gliomas generally retain the genetic and epi-genetic makeup of the primary tumor and, as such, are likely to require similar treatment regimens.

    2.3. Hypermutated GBMs

    A subset of temozolomide-treated GBMs gain inactivating mutations in DNA damage repair genes, such as MSH6, MSH2 and MLH1, as first described in 2006 by the Sanger institute [39]. Because of their impaired DNA repair pathways, these tumors fail to correctly repair the damage inflicted by the alkylating agent and as a consequence, acquire an exceptionally large number of mutations (often > 10 mutations per megabase) [40]. Temozolomide-induced hypermutated tumors are characterized by G:C > T:A transitions within a specific genetic context (COSMIC mutational signature 11) [41][42]. Hypermutated tumors may also arise de novo, which occurs in the context of germline mutations in DNA mismatch repair genes [40][43][44]. Such tumors have mutational signatures associated with mismatch repair pathways [40]. Although hypermutation is common in recurrent (IDH-mutant) low grade gliomas, it is quite rare in rGBMs, with frequencies generally reported in the order of less than 10% (6/89 [24]), 14/186 [16], 16/99 [25] and 0/29 [26]). Hypermutation appears to occur more often in MGMT-methylated GBMs (23%) compared to MGMT-unmethylated tumors (5.6%) [40].

    Despite the large difference in the genetic makeup of hypermutated tumors, it is unclear whether patients with such tumors have a different clinical course. One report suggested a longer survival [24], although other studies noted no survival differences [16][25][45][46] or even a trend towards poorer survival in IDH-wt rGBMs [40]. There is scarce evidence on the efficacy of treatment of hypermutated GBMs. The effect of alkylating chemotherapy seems limited: a retrospective analysis found highly similar survival between hypermutated and non-hypermutated tumors treated with alkylating chemotherapy [25] and preclinical evidence suggested hypermutated tumors are resistant to temozolomide [40]. Because of their increased mutational burden, it has been speculated that hypermutated tumors may be more susceptible to immune checkpoint inhibition. Initial anecdotal evidence supported this notion [44][47], although a later retrospective analysis of gliomas with high mutational burden found no evidence for this, with no increased immune infiltration [40]. However, evidence in larger trials is thus-far lacking and to date, there are no specific treatment options for hypermutated GBMs [48].

    3. Management of rGBM

    3.1. Diagnosis of rGBM

    The diagnosis of rGBM relies on clinical status and MRI findings, according to Response Assessment in Neuro-Oncology (RANO) criteria and medical history [49]. MRI features of rGBM are heterogeneously described [50]. GBM may recur: (i) at the initial tumor site—most frequently <2 cm from lesion—in about 80% of cases [50] and/or, (ii) distant, with unifocal/multifocal parenchymal lesions or leptomeningeal spread [51]. Surprisingly, among different localizations, cortical GBMs seem more prone to multifocal recurrence [52].

    The distinction between disease recurrence and treatment-related complications is challenging and needs specific attention. The main treatment-related complications are pseudoprogression (PsP) and radionecrosis [7]. PsP, more common in MGMT methylated GBM, is seen in up to 30% of patients treated with standard of care [53][54]. Usually, PsP is characterized by tumor volume increase within 3 months post-chemoradiation therapy, but delayed cases have been reported [5][55]. This phenomenon is also seen after immunotherapies with a longer time frame leading to the development of dedicated assessment tools: iRANO [54][57][56][58]. Radiation necrosis is another complication seen later in GBM patients treated with both radio and chemotherapy [7][55]. It usually appears between 3-12 months after radiotherapy [55]. In both situations, RANO and iRANO criteria suggest: (i) careful selection of reference imaging, (ii) close clinical and radiological follow-up and, (iii) avoidance of premature discontinuation of a potentially efficient treatment in the absence of worsening symptoms [7][54][58]. Multimodal imaging including spectroscopy MR, dynamic susceptibility MR perfusion and nuclear imaging can help reach a final diagnosis [5][7][50]. The importance of multimodal imaging is even more apparent with blood-brain barrier permeability modifiers, such as antiangiogenic drugs [55].

    Moreover, functional molecular imaging such as positron emission tomography (PET) using amino acid tracers emerged as a promising investigational strategy in the setting of diagnosis, biopsy, resection and response assessment [59]. Histological proof remains the best approach to get molecular features of rGBM for potential molecular targeted therapies. However, a limited number of rGBM patients are eligible for second biopsy or resection due to their frailty. Therefore, in this setting, multimodal approach including PET and MRI appear an interesting alternative [5].

    3.2. Prognostic Factors in rGBM

    Older age at diagnosis and a decreased performance score (KPS or WHO) at recurrence have been associated with a poor outcome in multiple cohorts of rGBM patients [4][9]. In the same line, localization of recurrence (i.e., contact with SVZ and/or ventricle) and ependymal spread on MRI have been linked to a poor outcome [52][61][62]. In contrast, cortical localization, volume of FLAIR hyperintensities on MRI do not significantly impact outcome [4][61][63]. rGBM localization in eloquent areas and tumor volume [60] time to first recurrence [4] and RTOG-RPA class [9] were also proposed as prognostic indicators, but data are conflicting and warrant further investigations. As described previously, the MGMT promoter methylation status can represent an important factor correlating with survival in rGBM patients.

    3.3. Treatment of rGBM

    Less than 50% of rGBM patients are eligible for second surgery (12–48%) [63][64][65]. When feasible, surgical resection is associated with increased OS (i.e., 5–11 months) and preserved neurological status (i.e., >90% of patients) [4][63][64][65][66][67]. In these studies, an age of less than 65 years, a good performance status, radical surgery, tumor location and chemotherapy treatment before recurrence were founded predictors of re-surgery benefits; in the presence of these clinical and surgical parameters, second surgery at the time of GBM recurrence could be considered as a therapeutic strategy in selected patients. However, the observed increased survival should be taken with extreme caution due to a selection bias of prognostically favorable patients for second surgery. The impact of surgery in rGBM was never assessed in a prospective manner, nor compared to medical treatments.

    Reirradiation (re-RT) can be a therapeutic option in rGBM. A secondary analysis of the Radiation Therapy Oncology Group (RTOG) 0525 trial demonstrated a modest clinical benefit of re-RT compared to best supportive care alone in rGBM patients (HR 0.74, 95% CI, 0.43–1.28). This survival benefit is amplified when re-RT is combined with systemic therapies (HR 0.44, 95% CI, 0.30–0.63) [68]. A systematic review and a metanalysis of 50 studies support the benefit of re-RT with a PFS6 of 43% (95% CI, 35–50%, I2 = 82%) [69]. However, the lack of prospective trials, the heterogeneity of studies for patients and the radiotherapy regimen limit the drawing of robust conclusions in rGBM [69][70]. Re-RT can only be proposed after careful consideration of the risk of radionecrosis [55]. A phase III trial has currently been withdrawn due to funding issues (NCT01830101). Stereotactic radiosurgery has been shown to be associated with a better PFS6 (47%). It has the theoretical advantage of sparing normal tissue but is restricted to small tumors with well-defined borders - a rare condition in rGBM [7][69].

    With regard to systemic treatments in rGBM, multiple therapeutic options may be considered: (i) temozolomide rechallenging [71], (ii) lomustine or bevacizumab or both [14], and (iii) tumor-treating fields [72], but most agents proved to be limited or had no efficacy in randomized trial settings (median PFS of 2–3 months and PFS6 rate below 15% [6][7]). Thus, due to a lack of validated standard of care, the National Comprehensive Cancer Network (NCCN) recommends clinical trials as the preferred option for eligible patients [5][70].

    The entry is from 10.3390/cancers13010047

    References

    1. Ostrom, Q.T.; Cioffi, G.; Gittleman, H.; Patil, N.; Waite, K.; Kruchko, C.; Barnholtz-Sloan, J.S. CBTRUS Statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2012–2016. Neuro-oncology 2019, 21, v1–v100, doi:10.1093/neuonc/noz150.
    2. Leece, R.; Xu, J.; Ostrom, Q.T.; Chen, Y.; Kruchko, C.; Barnholtz-Sloan, J.S. Global incidence of malignant brain and other central nervous system tumors by histology, 2003–2007. Neuro-oncology 2017, 19, 1553–1564, doi:10.1093/neuonc/nox091.
    3. Stupp, R.; Mason, W.P.; van den Bent, M.J.; Weller, M.; Fisher, B.; Taphoorn, M.J.B.; Belanger, K.; Brandes, A.A.; Marosi, C.; Bogdahn, U.; et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 2005, 352, 987–996, doi:10.1056/NEJMoa043330.
    4. Seyve, A.; Lozano-Sanchez, F.; Thomas, A.; Mathon, B.; Tran, S.; Mokhtari, K.; Giry, M.; Marie, Y.; Capelle, L.; Peyre, M.; et al. Initial surgical resection and long time to occurrence from initial diagnosis are independent prognostic factors in resected recurrent IDH wild-type glioblastoma. Clin. Neurol. Neurosurg. 2020, 196, 106006, doi:10.1016/j.clineuro.2020.106006.
    5. Wen, P.Y.; Weller, M.; Lee, E.Q.; Alexander, B.M.; Barnholtz-Sloan, J.S.; Barthel, F.P.; Batchelor, T.T.; Bindra, R.S.; Chang, S.M.; Chiocca, E.A.; et al. Glioblastoma in adults: A Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions. Neuro-oncology 2020, 22, 1073–1113, doi:10.1093/neuonc/noaa106.
    6. Ostrom, Q.T.; Truitt, G.; Gittleman, H.; Brat, D.J.; Kruchko, C.; Wilson, R.; Barnholtz-Sloan, J.S. Relative survival after diag-nosis with a primary brain or other central nervous system tumor in the National Program of Cancer Registries, 2004 to 2014. Neuro-Oncol. Pract. 2020, 7, 306–312, doi:10.1093/nop/npz059.
    7. Weller, M.; Cloughesy, T.; Perry, J.R.; Wick, W. Standards of care for treatment of recurrent glioblastoma—are we there yet? Neuro-oncology 2013, 15, 4–27, doi:10.1093/neuonc/nos273.
    8. Weller, M.; Le Rhun, E. How did lomustine become standard of care in recurrent glioblastoma? Cancer Treat. Rev. 2020, 87, 102029, doi:10.1016/j.ctrv.2020.102029.
    9. Audureau, E.; Chivet, A.; Ursu, R.; Corns, R.; Metellus, P.; Noel, G.; Zouaoui, S.; Guyotat, J.; Le Reste, P.-J.; Faillot, T.; et al. Prognostic factors for survival in adult patients with recurrent glioblastoma: A decision-tree-based model. J. Neurooncol. 2018, 136, 565–576, doi:10.1007/s11060-017-2685-4.
    10. Esteller, M.; Garcia-Foncillas, J.; Andion, E.; Goodman, S.N.; Hidalgo, O.F.; Vanaclocha, V.; Baylin, S.B.; Herman, J.G. Inacti-vation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N. Engl. J. Med. 2000, 343, 1350–1354, doi:10.1056/NEJM200011093431901.
    11. Malmstrom, A.; Gronberg, B.H.; Marosi, C.; Stupp, R.; Frappaz, D.; Schultz, H.; Abacioglu, U.; Tavelin, B.; Lhermitte, B.; Hegi, M.E.; et al. Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: The Nordic randomised, phase 3 trial. Lancet Oncol. 2012, 13, 916–926, doi:10.1016/S1470-2045(12)70265-6.
    12. Wick, W.; Platten, M.; Meisner, C.; Felsberg, J.; Tabatabai, G.; Simon, M.; Nikkhah, G.; Papsdorf, K.; Steinbach, J.P.; Sabel, M.; et al. Temozolomide chemotherapy alone versus radiotherapy alone for malignant astrocytoma in the elderly: The NOA-08 randomised, phase 3 trial. Lancet Oncol. 2012, 13, 707–715, doi:10.1016/S1470-2045(12)70164-X;
    13. Hegi, M.E.; Diserens, A.C.; Gorlia, T.; Hamou, M.F.; de Tribolet, N.; Weller, M.; Kros, J.M.; Hainfellner, J.A.; Mason, W.; Mar-iani, L.; et al. MGMT gene silencing and benefit from temozolomide in glioblastoma. N. Engl. J. Med. 2005, 352, 997–1003, doi:10.1056/NEJMoa043331.
    14. Wick, W.; Gorlia, T.; Bendszus, M.; Taphoorn, M.; Sahm, F.; Harting, I.; Brandes, A.A.; Taal, W.; Domont, J.; Idbaih, A.; et al. Lomustine and Bevacizumab in Progressive Glioblastoma. N. Engl. J. Med. 2017, 377, 1954–1963, doi:10.1056/NEJMoa1707358.
    15. Felsberg, J.; Thon, N.; Eigenbrod, S.; Hentschel, B.; Sabel, M.C.; Westphal, M.; Schackert, G.; Kreth, F.W.; Pietsch, T.; Loffler, M.; et al. Promoter methylation and expression of MGMT and the DNA mismatch repair genes MLH1, MSH2, MSH6 and PMS2 in paired primary and recurrent glioblastomas. Int J Cancer 2011, 129, 659–670, doi:10.1002/ijc.26083.
    16. Draaisma, K.; Chatzipli, A.; Taphoorn, M.; Kerkhof, M.; Weyerbrock, A.; Sanson, M.; Hoeben, A.; Lukacova, S.; Lombardi, G.; Leenstra, S.; et al. Molecular evolution of IDH wild-type glioblastomas treated with standard of care affects survival and design of precision medicine trials: A report from the EORTC 1542 study. J. Clin. Oncol. 2020, 38, 81–99, doi:10.1200/JCO.19.00367.
    17. Weller, M.; Tabatabai, G.; Kastner, B.; Felsberg, J.; Steinbach, J.P.; Wick, A.; Schnell, O.; Hau, P.; Herrlinger, U.; Sabel, M.C.; et al. MGMT promoter methylation is a strong prognostic biomarker for benefit from dose-intensified temozolomide re-challenge in progressive glioblastoma: The DIRECTOR trial. Clin. Cancer Res. 2015, 21, 2057–2064, doi:10.1158/1078-0432.CCR-14-2737.
    18. Brandes, A.A.; Franceschi, E.; Paccapelo, A.; Tallini, G.; De Biase, D.; Ghimenton, C.; Danieli, D.; Zunarelli, E.; Lanza, G.; Silini, E.M.; et al. Role of MGMT methylation status at time of diagnosis and recurrence for patients with glioblastoma: Clinical implications. Oncologist 2017, 22, 432–437, doi:10.1634/theoncologist.2016-0254.
    19. Brandes, A.A.; Finocchiaro, G.; Zagonel, V.; Reni, M.; Caserta, C.; Fabi, A.; Clavarezza, M.; Maiello, E.; Eoli, M.; Lombardi, G.; et al. AVAREG: A phase II, randomized, noncomparative study of fotemustine or bevacizumab for patients with recur-rent glioblastoma. Neuro-oncology 2016, 18, 1304–1312, doi:10.1093/neuonc/now035.
    20. Lombardi, G.; De Salvo, G.L.; Brandes, A.A.; Eoli, M.; Rudà, R.; Faedi, M.; Lolli, I.; Pace, A.; Daniele, B.; Pasqualetti, F.; et al. Regorafenib compared with lomustine in patients with relapsed glioblastoma (REGOMA): A multicentre, open-label, ran-domised, controlled, phase 2 trial. Lancet Oncol. 2019, 20, 110–119, doi:10.1016/S1470-2045(18)30675-2.
    21. Erdem-Eraslan, L.; van den Bent, M.J.; Hoogstrate, Y.; Naz-Khan, H.; Stubbs, A.; van der Spek, P.; Böttcher, R.; Gao, Y.; de Wit, M.; Taal, W.; et al. Identification of patients with recurrent glioblastoma who may benefit from combined bevaci-zumab and CCNU therapy, a report from the BELOB trial. Cancer Res. 2016, 76, 525–534.
    22. Taal, W.; Oosterkamp, H.M.; Walenkamp, A.M.; Dubbink, H.J.; Beerepoot, L.V.; Hanse, M.C.; Buter, J.; Honkoop, A.H.; Boerman, D.; de Vos, F.Y.; et al. Single-agent bevacizumab or lomustine versus a combination of bevacizumab plus lo-mustine in patients with recurrent glioblastoma (BELOB trial): A randomised controlled phase 2 trial. Lancet Oncol. 2014, 15, 943–953, doi:10.1016/S1470-2045(14)70314-6.
    23. Muscat, A.M.; Wong, N.C.; Drummond, K.J.; Algar, E.M.; Khasraw, M.; Verhaak, R.; Field, K.; Rosenthal, M.A.; Ashley, D.M. The evolutionary pattern of mutations in glioblastoma reveals therapy-mediated selection. Oncotarget 2018, 9, 7844–7858, doi:10.18632/oncotarget.23541.
    24. Wang, J.; Cazzato, E.; Ladewig, E.; Frattini, V.; Rosenbloom, D.I.S.; Zairis, S.; Abate, F.; Liu, Z.; Elliott, O.; Shin, Y.-J.; et al. Clonal evolution of glioblastoma under therapy. Nat. Genet. 2016, 48, 768–776, doi:10.1038/ng.3590.
    25. Barthel, F.P.; Johnson, K.C.; Varn, F.S.; Moskalik, A.D.; Tanner, G.; Kocakavuk, E.; Anderson, K.J.; Abiola, O.; Aldape, K.; Al-faro, K.D.; et al. Longitudinal molecular trajectories of diffuse glioma in adults. Nature 2019, doi:10.1038/s41586-019-1775-1.
    26. Kim, J.; Lee, I.H.; Cho, H.J.; Park, C.K.; Jung, Y.S.; Kim, Y.; Nam, S.H.; Kim, B.S.; Johnson, M.D.; Kong, D.S.; et al. Spatiotem-poral evolution of the primary glioblastoma genome. Cancer Cell 2015, 28, 318–328, doi:10.1016/j.ccell.2015.07.013.
    27. Kim, H.; Zheng, S.; Amini, S.S.; Virk, S.M.; Mikkelsen, T.; Brat, D.J.; Grimsby, J.; Sougnez, C.; Muller, F.; Hu, J.; et al. Whole-genome and multisector exome sequencing of primary and post-treatment glioblastoma reveals patterns of tumor evolu-tion. Genome Res. 2015, 25, 316–327, doi:10.1101/gr.180612.114.
    28. Riehmer, V.; Gietzelt, J.; Beyer, U.; Hentschel, B.; Westphal, M.; Schackert, G.; Sabel, M.C.; Radlwimmer, B.; Pietsch, T.; Rei-fenberger, G.; et al. Genomic profiling reveals distinctive molecular relapse patterns in IDH1/2 wild-type glioblastoma. Genes. Chromosomes Cancer 2014, 53, 589–605, doi:10.1002/gcc.22169.
    29. van den Bent, M.J.; Gao, Y.; Kerkhof, M.; Kros, J.M.; Gorlia, T.; van Zwieten, K.; Prince, J.; van Duinen, S.; Sillevis Smitt, P.A.; Taphoorn, M.; et al. Changes in the EGFR amplification and EGFRvIII expression between paired primary and recurrent glioblastomas. Neuro-oncology 2015, 17, 935–941, doi:10.1093/neuonc/nov013.
    30. Kim, E.L.; Sorokin, M.; Kantelhardt, S.R.; Kalasauskas, D.; Sprang, B.; Fauss, J.; Ringel, F.; Garazha, A.; Albert, E.; Gaifullin, N.; et al. Intratumoral heterogeneity and longitudinal changes in gene expression predict differential drug sensitivity in newly diagnosed and recurrent glioblastoma. Cancers 2020, 12, 520, doi:10.3390/cancers12020520.
    31. Wang, Q.; Hu, B.; Hu, X.; Kim, H.; Squatrito, M.; Scarpace, L.; deCarvalho, A.C.; Lyu, S.; Li, P.; Li, Y.; et al. Tumor evolution of glioma-intrinsic gene expression subtypes associates with immunological changes in the microenvironment. Cancer Cell 2018, 33, 152, doi:10.1016/j.ccell.2017.12.012.
    32. Gravendeel, L.A.; Kouwenhoven, M.C.; Gevaert, O.; de Rooi, J.J.; Stubbs, A.P.; Duijm, J.E.; Daemen, A.; Bleeker, F.E.; Bralten, L.B.; Kloosterhof, N.K.; et al. Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology. Cancer Res. 2009, 69, 9065–9072, doi:10.1158/0008-5472.CAN-09-2307.
    33. Kwon, S.M.; Kang, S.H.; Park, C.K.; Jung, S.; Park, E.S.; Lee, J.S.; Kim, S.H.; Woo, H.G. Recurrent glioblastomas reveal mo-lecular subtypes associated with mechanistic implications of drug-resistance. PLoS ONE 2015, 10, e0140528, doi:10.1371/journal.pone.0140528.
    34. Nejo, T.; Matsushita, H.; Karasaki, T.; Nomura, M.; Saito, K.; Tanaka, S.; Takayanagi, S.; Hana, T.; Takahashi, S.; Kitagawa, Y.; et al. Reduced neoantigen expression revealed by longitudinal multiomics as a possible immune evasion mechanism in glioma. Cancer Immunol. Res. 2019, 7, 1148–1161, doi:10.1158/2326-6066.CIR-18-0599.
    35. Mazor, T.; Pankov, A.; Johnson, B.E.; Hong, C.; Hamilton, E.G.; Bell, R.J.; Smirnov, I.V.; Reis, G.F.; Phillips, J.J.; Barnes, M.J.; et al. DNA methylation and somatic mutations converge on the cell cycle and define similar evolutionary histories in brain tumors. Cancer Cell 2015, 28, 307–317, doi:10.1016/j.ccell.2015.07.012.
    36. de Souza, C.F.; Sabedot, T.S.; Malta, T.M.; Stetson, L.; Morozova, O.; Sokolov, A.; Laird, P.W.; Wiznerowicz, M.; Iavarone, A.; Snyder, J.; et al. A distinct DNA methylation shift in a subset of glioma CpG island methylator phenotypes during tumor recurrence. Cell Rep. 2018, 23, 637–651, doi:10.1016/j.celrep.2018.03.107.
    37. Sottoriva, A.; Spiteri, I.; Piccirillo, S.G.M.; Touloumis, A.; Collins, V.P.; Marioni, J.C.; Curtis, C.; Watts, C.; Tavaré, S. Intra-tumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics. Proc. Natl. Acad. Sci. USA 2013, 110, 4009–4014, doi:10.1073/pnas.1219747110.
    38. Neftel, C.; Laffy, J.; Filbin, M.G.; Hara, T.; Shore, M.E.; Rahme, G.J.; Richman, A.R.; Silverbush, D.; Shaw, M.L.; Hebert, C.M.; et al. An integrative model of cellular states, plasticity, and genetics for glioblastoma. Cell 2019, 178, 835–849.e21, doi:10.1016/j.cell.2019.06.024.
    39. Hunter, C.; Smith, R.; Cahill, D.P.; Stephens, P.; Stevens, C.; Teague, J.; Greenman, C.; Edkins, S.; Bignell, G.; Davies, H.; et al. A hypermutation phenotype and somatic MSH6 mutations in recurrent human malignant gliomas after alkylator chemo-therapy. Cancer Res. 2006, 66, 3987–3991.
    40. Touat, M.; Li, Y.Y.; Boynton, A.N.; Spurr, L.F.; Iorgulescu, J.B.; Bohrson, C.L.; Cortes-Ciriano, I.; Birzu, C.; Geduldig, J.E.; Pel-ton, K.; et al. Mechanisms and therapeutic implications of hypermutation in gliomas. Nature 2020, 580, 517–523, doi:10.1038/s41586-020-2209-9.
    41. Alexandrov, L.B.; Kim, J.; Haradhvala, N.J.; Huang, M.N.; Tian Ng, A.W.; Wu, Y.; Boot, A.; Covington, K.R.; Gordenin, D.A.; Bergstrom, E.N.; et al. The repertoire of mutational signatures in human cancer. Nature 2020, 578, 94–101, doi:10.1038/s41586-020-1943-3.
    42. Alexandrov, L.B.; Nik-Zainal, S.; Wedge, D.C.; Aparicio, S.A.J.R.; Behjati, S.; Biankin, A.V.; Bignell, G.R.; Bolli, N.; Borg, A.; Børresen-Dale, A.-L.; et al. Signatures of mutational processes in human cancer. Nature 2013, 500, 415–421, doi:10.1038/nature12477.
    43. Sa, J.K.; Choi, S.W.; Zhao, J.; Lee, Y.; Zhang, J.; Kong, D.S.; Choi, J.W.; Seol, H.J.; Lee, J.I.; Iavarone, A.; et al. Hypermutagene-sis in untreated adult gliomas due to inherited mismatch mutations. Int. J. Cancer 2019, 144, 3023–3030, doi:10.1002/ijc.32054.
    44. Bouffet, E.; Larouche, V.; Campbell, B.B.; Merico, D.; de Borja, R.; Aronson, M.; Durno, C.; Krueger, J.; Cabric, V.; Ramaswa-my, V.; et al. Immune checkpoint inhibition for hypermutant glioblastoma multiforme resulting from germline biallelic mismatch repair deficiency. J. Clin. Oncol. 2016, 34, 2206–2211, doi:10.1200/JCO.2016.66.6552.
    45. Touat, M.; Li, Y.; Boynton, A.; Spurr, L.; Iorglescu, B.; Geduldig, J.; Birzu, C.; Lim Fat, M.; Santagata, S.; Coulet, F.; et al. Clinical significance of hypermutation in gliomas. Neuro-Oncology 2019, 21, iii18.
    46. Caccese, M.; Ius, T.; Simonelli, M.; Fassan, M.; Cesselli, D.; Dipasquale, A.; Cavallin, F.; Padovan, M.; Salvalaggio, A.; Gardiman, M.P.; et al. Mismatch-repair protein expression in high-grade gliomas: A large retrospective multicenter study. Int. J. Mol. Sci. 2020, 21, 6716, doi:10.3390/ijms21186716.
    47. Johanns, T.M.; Miller, C.A.; Dorward, I.G.; Tsien, C.; Chang, E.; Perry, A.; Uppaluri, R.; Ferguson, C.; Schmidt, R.E.; Dahiya, S.; et al. Immunogenomics of hypermutated glioblastoma: A patient with germline pole deficiency treated with checkpoint blockade immunotherapy. Cancer Discov. 2016, 6, 1230–1236, doi:10.1158/2159-8290.CD-16-0575.
    48. Weenink, B.; French, P.J.; Smitt, P.A.E.S.; Debets, R.; Geurts, M. Immunotherapy in glioblastoma: Current shortcomings and future perspectives. Cancers 2020, 12, doi:10.3390/cancers12030751.
    49. Wen, P.Y.; Macdonald, D.R.; Reardon, D.A.; Cloughesy, T.F.; Sorensen, A.G.; Galanis, E.; Degroot, J.; Wick, W.; Gilbert, M.R.; Lassman, A.B.; et al. Updated response assessment criteria for high-grade gliomas: Response assessment in neuro-oncology working group. J. Clin. Oncol. 2010, 28, 1963–1972, doi:10.1200/JCO.2009.26.3541.
    50. Piper, R.J.; Senthil, K.K.; Yan, J.-L.; Price, S.J. Neuroimaging classification of progression patterns in glioblastoma: A sys-tematic review. J. Neurooncol. 2018, 139, 77–88, doi:10.1007/s11060-018-2843-3.
    51. Bordignon, K.C.; Neto, M.C.; Ramina, R.; de Meneses, M.S.; Zazula, A.D.; de Almeida, L.G.M.P. Patterns of neuroaxis dis-semination of gliomas: Suggestion of a classification based on magnetic resonance imaging findings. Surg. Neurol. 2006, 65, 472–477, doi:10.1016/j.surneu.2005.08.019; discussion 477.
    52. Jungk, C.; Warta, R.; Mock, A.; Friauf, S.; Hug, B.; Capper, D.; Abdollahi, A.; Debus, J.; Bendszus, M.; von Deimling, A.; et al. Location-dependent patient outcome and recurrence patterns in IDH1-wildtype glioblastoma. Cancers 2019, 11, 122, doi:10.3390/cancers11010122.
    53. Balaña, C.; Capellades, J.; Pineda, E.; Estival, A.; Puig, J.; Domenech, S.; Verger, E.; Pujol, T.; Martinez‐García, M.; Oleaga, L.; et al. Pseudoprogression as an adverse event of glioblastoma therapy. Cancer Med. 2017, 6, 2858–2866, doi:10.1002/cam4.1242.
    54. Reardon, D.A.; Weller, M. Pseudoprogression: Fact or wishful thinking in neuro-oncology? Lancet Oncol. 2018, 19, 1561–1563, doi:10.1016/S1470-2045(18)30654-5.
    55. Zikou, A.; Sioka, C.; Alexiou, G.A.; Fotopoulos, A.; Voulgaris, S.; Argyropoulou, M.I. Radiation necrosis, pseudoprogres-sion, pseudoresponse, and tumor recurrence: Imaging challenges for the evaluation of treated gliomas. Contrast Media Mol. Imaging 2018, 2018, doi:10.1155/2018/6828396.
    56. Omuro, A.; Vlahovic, G.; Lim, M.; Sahebjam, S.; Baehring, J.; Cloughesy, T.; Voloschin, A.; Ramkissoon, S.H.; Ligon, K.L.; Latek, R.; et al. Nivolumab with or without ipilimumab in patients with recurrent glioblastoma: Results from exploratory phase I cohorts of CheckMate 143. Neuro-oncology 2018, 20, 674–686, doi:10.1093/neuonc/nox208.
    57. Weller, M.; Butowski, N.; Tran, D.D.; Recht, L.D.; Lim, M.; Hirte, H.; Ashby, L.; Mechtler, L.; Goldlust, S.A.; Iwamoto, F.; et al. Rindopepimut with temozolomide for patients with newly diagnosed, EGFRvIII-expressing glioblastoma (ACT IV): A ran-domised, double-blind, international phase 3 trial. Lancet Oncol. 2017, 18, 1373–1385, doi:10.1016/S1470-2045(17)30517-X.
    58. Okada, H.; Weller, M.; Huang, R.; Finocchiaro, G.; Gilbert, M.R.; Wick, W.; Ellingson, B.M.; Hashimoto, N.; Pollack, I.F.; Brandes, A.A.; et al. Immunotherapy response assessment in neuro-oncology: A report of the RANO working group. Lancet Oncol. 2015, 16, e534–e542, doi:10.1016/S1470-2045(15)00088-1.
    59. Law, I.; Albert, N.L.; Arbizu, J.; Boellaard, R.; Drzezga, A.; Galldiks, N.; la Fougere, C.; Langen, K.J.; Lopci, E.; Lowe, V.; et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radio-labelled amino acids and [(18)F]FDG: version 1.0. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 540–557, doi:10.1007/s00259-018-4207-9.
    60. Park, J.K.; Hodges, T.; Arko, L.; Shen, M.; Dello Iacono, D.; McNabb, A.; Olsen Bailey, N.; Kreisl, T.N.; Iwamoto, F.M.; Sul, J.; et al. Scale to predict survival after surgery for recurrent glioblastoma multiforme. J. Clin. Oncol. 2010, 28, 3838–3843, doi:10.1200/JCO.2010.30.0582.
    61. Bette, S.; Barz, M.; Huber, T.; Straube, C.; Schmidt-Graf, F.; Combs, S.E.; Delbridge, C.; Gerhardt, J.; Zimmer, C.; Meyer, B.; et al. Retrospective analysis of radiological recurrence patterns in glioblastoma, their prognostic value and association to postoperative infarct volume. Sci. Rep. 2018, 8, 4561, doi:10.1038/s41598-018-22697-9.
    62. Sonoda, Y.; Saito, R.; Kanamori, M.; Kumabe, T.; Uenohara, H.; Tominaga, T. The association of subventricular zone in-volvement at recurrence with survival after repeat surgery in patients with recurrent glioblastoma. Neurol. Med. Chir. (To-kyo) 2014, 54, 302–309, doi:10.2176/nmc.oa.2013-0226.
    63. Woodroffe, R.W.; Zanaty, M.; Soni, N.; Mott, S.L.; Helland, L.C.; Pasha, A.; Maley, J.; Dhungana, N.; Jones, K.A.; Monga, V.; et al. Survival after reoperation for recurrent glioblastoma. J. Clin. Neurosci. 2020, 73, 118–124, doi:10.1016/j.jocn.2020.01.009.
    64. Helseth, R.; Helseth, E.; Johannesen, T.B.; Langberg, C.W.; Lote, K.; Rønning, P.; Scheie, D.; Vik, A.; Meling, T.R. Overall sur-vival, prognostic factors, and repeated surgery in a consecutive series of 516 patients with glioblastoma multiforme: Sur-vival, prognostic factors, and repeat surgery in GBM patients. Acta Neurol. Scand. 2010, 122, 159–167, doi:10.1111/j.1600-0404.2010.01350.x.
    65. Barbagallo, G.M.V.; Jenkinson, M.D.; Brodbelt, A.R. ‘Recurrent’ glioblastoma multiforme, when should we reoperate? Br. J. Neurosurg. 2008, 22, 452–455, doi:10.1080/02688690802182256.
    66. Suchorska, B.; Weller, M.; Tabatabai, G.; Senft, C.; Hau, P.; Sabel, M.C.; Herrlinger, U.; Ketter, R.; Schlegel, U.; Marosi, C.; et al. Complete resection of contrast-enhancing tumor volume is associated with improved survival in recurrent glioblasto-ma-results from the DIRECTOR trial. Neuro-oncology 2016, 18, 549–556, doi:10.1093/neuonc/nov326.
    67. Ringel, F.; Pape, H.; Sabel, M.; Krex, D.; Bock, H.C.; Misch, M.; Weyerbrock, A.; Westermaier, T.; Senft, C.; Schucht, P.; et al. Clinical benefit from resection of recurrent glioblastomas: Results of a multicenter study including 503 patients with recur-rent glioblastomas undergoing surgical resection. Neuro-oncology 2016, 18, 96–104, doi:10.1093/neuonc/nov145.
    68. Shi, W.; Scannell Bryan, M.; Gilbert, M.R.; Mehta, M.P.; Blumenthal, D.T.; Brown, P.D.; Valeinis, E.; Hopkins, K.; Souhami, L.; Andrews, D.W.; et al. Investigating the effect of reirradiation or systemic therapy in patients with glioblastoma after tumor progression: A secondary analysis of NRG oncology/radiation therapy oncology group trial 0525. Int. J. Radiat. Oncol. Biol. Phys. 2018, 100, 38–44, doi:10.1016/j.ijrobp.2017.08.038.
    69. Kazmi, F.; Soon, Y.Y.; Leong, Y.H.; Koh, W.Y.; Vellayappan, B. Re-irradiation for recurrent glioblastoma (GBM): A systemat-ic review and meta-analysis. J. Neurooncol. 2019, 142, 79–90, doi:10.1007/s11060-018-03064-0.
    70. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) Central Nervus System Cancers; 2020; https://www.nccn.org/professionals/physician_gls/default.aspx (accessed on 20 July 2020).
    71. Perry, J.R.; Bélanger, K.; Mason, W.P.; Fulton, D.; Kavan, P.; Easaw, J.; Shields, C.; Kirby, S.; Macdonald, D.R.; Eisenstat, D.D.; et al. Phase II trial of continuous dose-intense temozolomide in recurrent malignant glioma: RESCUE study. J. Clin. Oncol. 2010, 28, 2051–2057, doi:10.1200/JCO.2009.26.5520.
    72. Stupp, R.; Wong, E.T.; Kanner, A.A.; Steinberg, D.; Engelhard, H.; Heidecke, V.; Kirson, E.D.; Taillibert, S.; Liebermann, F.; Dbalý, V.; et al. NovoTTF-100A versus physician’s choice chemotherapy in recurrent glioblastoma: A randomised phase III trial of a novel treatment modality. Eur. J. Cancer 2012, 48, 2192–2202, doi:10.1016/j.ejca.2012.04.011.
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