Laurien De Roeck

Background: A brain tumor can lead to functional impairment, which is particularly concerning for adolescents and young adults (AYA). Patient-reported outcomes (PROs) have typically been examined as isolated domains, rather than as covarying symptoms. This study modeled PRO networks, symptom clustering, and topology among AYA oncology survivors. Methods: Patient-reported outcome networks from 4005 survivors were compared in topology between survivors of primary CNS tumors (n = 164) and non-CNS tumors (n = 3841). Survivors were diagnosed between 1999 and 2015 at ages 18 to 39 years, who completed the EORTC QLQ-SURV100 (Mdn follow-up = 12.31 years). Group-specific networks were estimated based on 33 health-related quality of life (HRQoL) scale scores using graphical LASSO. Wilcoxon rank-sum tests and the Network Comparison Test assessed group differences in the original PRO scales and their network centrality, respectively. Within the CNS subgroup (n = 164), associations with tumor-related and treatment-related characteristics were explored. Results: Survivors of central nervous system (CNS) tumors reported higher symptom burden on most PRO scales, along with a more diffuse network showing weaker within-domain cohesion (lower nodal strength and expected influence) and limited cross-domain integration (lower bridge strength). A small subset of nodes showed higher bridge expected influence (ie, fatigue, physical functioning, sexual problems when sexually active, work), which may represent key targets for intervention. Across both groups, negative health outlook, health distress, and physical functioning emerged as consistent core targets. Conclusion: Core symptoms may warrant prioritization in clinical follow-up and treatment of cancer survivors. These findings contribute to further development and optimization of tailored neurorehabilitation programs in neuro-oncological care.

The brain operates through networks of interconnected regions, which can be disrupted by glial tumors and their treatment. This study investigates associations between this altered functional network topology and cognition in gliomas. We studied 50 adult glioma survivors (>1-year posttherapy) and 50 healthy controls. Participants underwent cognitive assessments across six domains and an 8-min resting-state functional MRI. Based on the BOLD signal, partial correlations were computed among 78 brain regions. From their absolute values, whole-brain and nodal graph metrics were derived and normalized to random graphs. Group differences in whole-brain and nodal graph metrics were assessed with Mann–Whitney U tests and mixed-design analyses of variance, respectively. Metrics exhibiting significant intergroup differences were correlated with cognitive scores, with pbonf < 0.050 indicating significance. Among controls, 8 of 78 nodes were identified as hubs. Patients exhibited significantly higher whole-brain clustering, correlating with intelligence (r(98) = −0.409, pbonf < 0.001) and executive functioning (r(98) = 0.300, pbonf = 0.014). Lower centrality, higher nodal clustering, and assortativity were also observed in patients, particularly in hubs, correlating with language and executive functioning, respectively (all r(98) > 0.300, pbonf < 0.050). Glioma patients commonly experience cognitive deficits alongside posttreatment alterations in functional network topology. Alterations in clustering, assortativity, and centrality may specifically act as compensatory mechanisms, significantly influencing cognitive functioning.

Background: Cranial irradiation is a key component of neuro-oncological treatment but can result in cognitive side effects. Preserving cognition from radiotherapy-(RT)-induced toxicity remains an ongoing debate. To spatially map radiotoxic effects in patients who underwent cranial RT, this study applied a voxel-based approach. Methods: Cognitive assessments (Controlled Word Association (COWA), Hopkins Verbal Learning (HVLT-R), and Trail Making Tests (TMT A,B)) were conducted prospectively before, 6 months and 1 year post-RT in 111 intracranial tumor patients (18–80 years). Reliable change indices indicated cognitive changes across timepoints. CT and T1-weighted MRI scans acquired at diagnosis were co-registered, normalized to standard space, and smoothed. Voxel-wise permutation-based regression analyses examined the relationship between RT dose and cognitive decline (α < 0.05 at cluster level). Results: Images of 111 patients (Mdn age = 55.39 years; 47% male; lesions were gliomas (61%), meningiomas (18%), other (21%); in frontal (33%), temporal (25%), other location (42%)) were analyzed. Reliable decline was most pronounced at 6 months, particularly on the TMT A (25.77%), TMT B (24.21%), and HVLT immediate recall (21%). At 1 year, 20% of patients continued to show a decline in TMT B. Higher RT doses to frontal gyri, temporal, occipital, and para-central regions were associated with declines in verbal fluency, memory, processing speed, and flexibility at both peak- and cluster-level. Conclusion: Differential voxel-wise RT dose effects at peak versus cluster level suggest local and network-based recruitment of diverse functional regions and vulnerability to cranial RT. These insights may help re-define key regions at risk from a network-based perspective, preserving cognition in future RT planning.

Background: Emerging evidence suggests that cognitive dysfunction may result from damage to the brain’s functional network. This study explores the dose-dependent susceptibility of functional hubs to radiotherapy (RT) and associations with cognitive outcomes. Methods: Attention, language, memory, motor, and executive functioning were assessed ≥1-year post-radiotherapy in 39 WHO grade 2 or 3 glioma patients with lesions predominantly located in the left frontal lobe and 50 matched healthy controls. Using resting-state functional imaging, weighted functional graphs were constructed for each participant, identifying hubs through graph measures. Linear regression models and Spearman’s rho correlations assessed associations between mean RT dose per region and cognitive domains. Results: Higher RT doses to the left fusiform and inferior temporal gyri were linked to memory impairment (r(37) ≥ −0.565, PFDR ≤ 0.026), while poorer language outcomes were associated with higher doses to the left pars opercularis, rostral middle frontal gyrus, and caudate (r(37) ≥ −0.510, PFDR ≤ .040). Attention deficits were linked to higher doses to the left posterior cingulate, precentral, supramarginal, and postcentral gyrus ((37) ≥ −0.499, PFDR ≤ .040), with the left postcentral gyrus also associated with executive dysfunction (r(37) = −0.526, PFDR = .029). Significant correlations between RT dose and cognitive outcomes were more frequent in hubs than in non-hubs (50% vs. 12%, P = .005) and exclusively found in left-sided regions. Conclusions: RT seems to adversely affect left-sided functional hubs in a dose-dependent manner in glioma patients, which may contribute to cognitive dysfunction. Protecting these regions from the dose may potentially mitigate cognitive side effects in glioma patients. However, since most lesions were located in the left hemisphere and baseline testing was unavailable, a potential effect of tumor location cannot be entirely ruled out.

Structural brain network topology can be altered in case of a brain tumor, due to both the tumor itself and its treatment. In this study, we explored the role of structural whole-brain and nodal network metrics and their association with cognitive functioning. Fifty WHO grade 2–3 adult glioma survivors (> 1-year post-therapy) and 50 matched healthy controls underwent a cognitive assessment, covering six cognitive domains. Raw cognitive assessment scores were transformed into w-scores, corrected for age and education. Furthermore, based on multi-shell diffusion-weighted MRI, whole-brain tractography was performed to create weighted graphs and to estimate whole-brain and nodal graph metrics. Hubs were defined based on nodal strength, betweenness centrality, clustering coefficient and shortest path length in healthy controls. Significant differences in these metrics between patients and controls were tested for the hub nodes (i.e. n = 12) and non-hub nodes (i.e. n = 30) in two mixed-design ANOVAs. Group differences in whole-brain graph measures were explored using Mann–Whitney U tests. Graph metrics that significantly differed were ultimately correlated with the cognitive domain-specific w-scores. Bonferroni correction was applied to correct for multiple testing. In survivors, the bilateral putamen were significantly less frequently observed as a hub (p_bonf < 0.001). These nodes’ assortativity values were positively correlated with attention (r(90) > 0.573, p_bonf < 0.001), and proxy IQ (r(90) > 0.794, p_bonf < 0.001). Attention and proxy IQ were significantly more often correlated with assortativity of hubs compared to non-hubs (p_bonf < 0.001). Finally, the whole-brain graph measures of clustering coefficient (r = 0.685), global (r = 0.570) and local efficiency (r = 0.500) only correlated with proxy IQ (p_bonf < 0.001). This study demonstrated potential reorganization of hubs in glioma survivors. Assortativity of these hubs was specifically associated with cognitive functioning, which could be important to consider in future modeling of cognitive outcomes and risk classification in glioma survivors.

Background: Cognitive functioning is increasingly assessed as a secondary outcome in neuro-oncological trials. However, which cognitive domains or tests to assess, remains debatable. In this meta-analysis, we aimed to elucidate the longer-term test-specific cognitive outcomes in adult glioma patients. Methods: A systematic search yielded 7098 articles for screening. To investigate cognitive changes in glioma patients and differences between patients and controls 1-year follow-up, random-effects meta-analyses were conducted per cognitive test, separately for studies with a longitudinal and cross-sectional design. A meta-regression analysis with a moderator for interval testing (additional cognitive testing between baseline and 1-year posttreatment) was performed to investigate the impact of practice in longitudinal designs. Results: Eighty-three studies were reviewed, of which 37 were analyzed in the meta-analysis, involving 4078 patients. In longitudinal designs, semantic fluency was the most sensitive test to detect cognitive decline over time. Cognitive performance on mini-mental state exam (MMSE), digit span forward, phonemic and semantic fluency declined over time in patients who had no interval testing. In cross-sectional studies, patients performed worse than controls on the MMSE, digit span backward, semantic fluency, Stroop speed interference task, trail-making test B, and finger tapping. Conclusions: Cognitive performance of glioma patients 1 year after treatment is significantly lower compared to the norm, with specific tests potentially being more sensitive. Cognitive decline over time occurs as well, but can easily be overlooked in longitudinal designs due to practice effects (as a result of interval testing). It is warranted to sufficiently correct for practice effects in future longitudinal trials.

CML, PV, ET and PMF are so called classical MPN with distinct clinical phenotypes. The discovery of the BCR-ABL1 translocation and mutations in driver genes JAK2, MPL and CALR has provided novel insights in their pathogenesis. While these mutations are thought to be mutually exclusive, rare cases of MPN with coexisting driver mutations have been reported. However, little is known about the clinical, biological and molecular characteristics of these patients and the interaction of the neoplastic clones. We retrospectively studied 11 MPN patients with coexisting driver mutations (JAK2 V617F + BCR-ABL1: n = 8; CALR type 2 + BCR-ABL1: n = 1; JAK2 V617F + MPL W515: n = 1; JAK2 V617F + CALR type 1: n = 1). To assess possible associated molecular aberrations, we analysed DNA of six patients using NGS. In four CML patients, decreasing BCR-ABL1 transcript levels with increasing JAK2 V617F allele burden under TKI were observed. This strongly suggests that the coexistence of driver mutations originates from two different clones growing independently. Additional somatic mutations were detected in 5 out of 6 (83%) patients affecting 4 different genes, confirming the heterogeneity of this study cohort. Suboptimal response to TKI was observed with a higher frequency (4/8 patients) than reported in conventional series of CML and the overall tolerance of treatment with hydroxyurea and/or imatinib in our series was poor. Given the emergence of NGS in clinical practice, more similar cases will be identified in the coming years. The optimal treatment strategy for this rare group of patients is uncertain and toxicity of combination treatment may have to be considered.