Clinical, genomic, and histopathologic diversity in cerebral cavernous malformations

Cerebral cavernous malformations (CCMs) are hemorrhagic vascular disorders with varied clinical and radiological presentations, occurring sporadically due to MAP3K3 or PIK3CA mutations or through inherited germline mutations of CCM genes. This study aimed to clarify the clinical, genetic, and pathological features of CCMs using a multicenter cohort across three Chinese centers. We analyzed 290 surgical specimens from symptomatic CCM patients, utilizing whole-exome sequencing, droplet digital PCR, and targeted panel sequencing, alongside immunohistology to examine genotypic and phenotypic differences. Among 290 cases, 201 had somatic MAP3K3, PIK3CA, or germline CCM mutations, each associated with distinct clinical parameters: hemorrhage risk (P < 0.001), lesion size (P = 0.019), non-hemorrhagic epilepsy (P < 0.001), Zabramski classifications (P < 0.001), developmental venous anomaly presence (P < 0.001), and MRI-detected edema (P < 0.001). PIK3CA mutations showed a higher hemorrhage risk than MAP3K3 and combined MAP3K3 & PIK3CA mutations (P < 0.001). Within PIK3CA mutations, the p.H1047R variant correlated with higher bleeding risk than p.E545K (P = 0.007). For non-hemorrhagic epilepsy, patients with single MAP3K3 mutations or combined MAP3K3 & PIK3CA mutations were at greater risk than those with PIK3CA mutations alone. Histopathologically, lesions with PIK3CA mutations displayed cyst walls, pS6-positive dilated capillaries, and fresh blood cells, while MAP3K3 and double mutation lesions exhibited classic CCM pathology with SMA-positive and KLF4-positive vessels, collagen, and calcification. PIK3CA lesions had fewer KLF4-positive cells than double mutations lesions (P < 0.001), and EndMT (SMA-positive) cells compared to double mutation lesions (P < 0.05) and MAP3K3 mutations (P < 0.001), with more pS6 compared to MAP3K3 mutations (P < 0.05). This study underscores the diverse clinical, genomic, and histopathological characteristics in CCMs, suggesting potential predictive markers based on mutation subtypes and MRI features.