The antitumor activity of osimertinib plus palbociclib in non-small cell lung cancer patient-derived xenograft (PDX)/2D/3D culture models harboring EGFR amplification and CDKN2A/2B homozygous deletions.

Non-small cell lung cancer (NSCLC) patients without targetable driver mutation have limited treatment options. In this study, we aimed to explore a new therapeutic strategy by using established nine patient-derived xenograft (PDX) and two-dimensional (2D) /3D culture models with specific genetic alternations. The gene mutations and copy number aberrations were detected by next-generation sequencing and confirmed using polymerase chain reaction (PCR) followed by DNA sequencing, and genomic DNA quantitative PCR. Protein expression was evaluated by immunohistochemistry. Drug sensitivities of PDX/2D/3D models were evaluated by in vivo and in vitro antitumor assays. RNA interference was performed to silence gene expression. Our study found that 44.4 % (4/9) of cases had CDKN2A homozygous deletion (homdel), while 33.3 % (3/9) had CDKN2B homdel. Additionally, 22.2 % (2/9) had amplification (amp) in wildtype CDK4, 44.4 % (4/9) in CDK6, and 44.4 % (4/9) in EGFR. Among the cases, 77.8 % (7/9) lacked CDKN2A, and 33.3 % (3/9) had high CDK4, CDK6, and EGFR had high protein expression. Moreover, 33.3 % (3/9) had KRAS mutations, and 66.7 % (6/9) had TP53 mutations. Antitumor activity of osimertinib plus palbociclib was assessed in four PDX/2D/3D models, two of which had simultaneous EGFR amp and CDKN2A/2B homdel. The data showed that NSCLC with EGFR amp and CDKN2A/2B homdel were sensitive to combined drugs. Additional oncogenic KRAS mutation reduced the drug's antitumor effect. EGFR amp is responsible for osimertinib sensitivity. Osimertinib plus palbociclib effectively treat NSCLC with wildtype EGFR and CDK6 amp and CDKN2A/2B homdel in the absence of oncogenic KRAS mutation.

Ensemble learning prediction framework for EGFR amplification status of glioma based on terahertz spectral features.

Epidermal growth factor receptor (EGFR) plays a pivotal role in the initiation and progression of gliomas. In particular, in glioblastoma, EGFR amplification emerges as a catalyst for invasion, proliferation, and resistance to radiotherapy and chemotherapy. Current approaches are not capable of providing rapid diagnostic results of molecular pathology. In this study, we propose a terahertz spectroscopic approach for predicting the EGFR amplification status of gliomas for the first time. A machine learning model was constructed using the terahertz response of the measured glioma tissues, including the absorption coefficient, refractive index, and dielectric loss tangent. The novelty of our model is the integration of three classical base classifiers, i.e., support vector machine, random forest, and extreme gradient boosting. The ensemble learning method combines the advantages of various base classifiers, this model has more generalization ability. The effectiveness of the proposed method was validated by applying an individual test set. The optimal performance of the integrated algorithm was verified with an area under the curve (AUC) maximum of 85.8 %. This signifies a significant stride toward more effective and rapid diagnostic tools for guiding postoperative therapy in gliomas.

Case report: EGFR fusion mutation combined with EGFR amplification responds to EGFR-TKI therapy.

Given their good antitumor effects, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are standard first-line therapy for EGFR-sensitive mutations, including exon 19 deletions and exon 21 L858R mutations. EGFR fusion mutations and EGFR amplification are very rare in non-small cell lung cancer (NSCLC). We describe 2 patients with NSCLC harboring EGFR fusion mutations (EGFR-MACF1 and EGFR-GNAT3) combined with EGFR amplification. Both patients received EGFR-TKI treatment, and 1 of them showed an antitumor response.

Clinical roles of EGFR amplification in diffuse gliomas: a real-world study using the 2021 WHO classification of CNS tumors.

Background: The 2021 World Health Organization Classification of Central Nervous System Tumors updates glioma subtyping and grading system, and incorporates EGFR amplification (Amp) as one of diagnostic markers for glioblastoma (GBM). Purpose: This study aimed to describe the frequency, clinical value and molecular correlation of EGFR Amp in diffuse gliomas based on the latest classification. Methods: We reviewed glioma patients between 2011 and 2022 at our hospital, and included 187 adult glioma patients with available tumor tissue for detection of EGFR Amp and other 59 molecular markers of interest. Clinical, radiological and pathological data was analyzed based on the status of EGFR Amp in different glioma subtypes. Results: 163 gliomas were classified as adult-type diffuse gliomas, and the number of astrocytoma, oligodendroglioma and GBM was 41, 46, and 76. EGFR Amp was more common in IDH-wildtype diffuse gliomas (66.0%) and GBM (85.5%) than IDH-mutant diffuse gliomas (32.2%) and its subtypes (astrocytoma, 29.3%; oligodendroglioma, 34.8%). EGFR Amp did not stratify overall survival (OS) in IDH-mutant diffuse gliomas and astrocytoma, while was significantly associated with poorer OS in IDH-wildtype diffuse gliomas, histologic grade 2 and 3 IDH-wildtype diffuse astrocytic gliomas and GBM. Conclusion: Our study validated EGFR Amp as a diagnostic marker for GBM and still a useful predictor for shortened OS in this group.

EGFR/CEP7 high polysomy is separate and distinct from EGFR amplification in glioblastoma as determined by fluorescence in situ hybridization.

EGFR amplification in gliomas is commonly defined by an EGFR/CEP7 ratio of ≥2. In testing performed at a major reference laboratory, a small subset of patients had ≥5 copies of both EGFR and CEP7 yet were not amplified by the EGFR/CEP7 ratio and were designated high polysomy cases. To determine whether these tumors are more closely related to traditionally defined EGFR-amplified or nonamplified gliomas, a retrospective search identified 22 out of 1143 (1.9%) gliomas with an average of ≥5 copies/cell of EGFR and CEP7 with an EGFR/CEP7 ratio of <2 displaying high polysomy. Of these cases, 4 had insufficient clinicopathologic data to include in additional analysis, 15 were glioblastomas, 2 were IDH-mutant astrocytomas, and 1 was a high-grade glial neoplasm, NOS. Next-generation sequencing available on 3 cases demonstrated one with a TERT promoter mutation, TP53 mutations in all cases, and no EGFR mutations or amplifications, which most closely matched the nonamplified cases. The median overall survival times were 42.86, 66.07, and 41.14 weeks for amplified, highly polysomic, and nonamplified, respectively, and were not significantly different (p = 0.3410). High chromosome 7 polysomic gliomas are rare but our data suggest that they may be biologically similar to nonamplified gliomas.

Molecular characterization and survival analysis of a cohort of glioblastoma, IDH-wildtype.

Glioblastoma, IDH-wild type, the most common malignant primary central nervous system tumor, represents a formidable challenge in clinical management due to its poor prognosis and limited therapeutic responses. With an evolving understanding of its underlying biology, there is an urgent need to identify prognostic molecular groups that can be subject to targeted therapy. This study established a cohort of 124 sequential glioblastomas from a tertiary hospital and aimed to find correlations between molecular features and survival outcomes. Comprehensive molecular characterization of the cohort revealed prevalent alterations as previously described, such as TERT promoter mutations and involvement of the PI3K-Akt-mTOR, CK4/6-CDKN2A/B-RB1, and p14ARF-MDM2-MDM4-p53 pathways. MGMT promoter methylation is a significant predictor of improved overall survival, aligned with previous data. Conversely, age showed a marginal association with higher mortality. Multivariate analysis to account for the effect of MGMT promoter methylation and age showed that, in contrast to other published series, this cohort demonstrated improved survival for tumors harboring PTEN mutations, and that there was no observed difference for most other molecular alterations, including EGFR amplification, RB1 loss, or the coexistence of EGFR amplification and deletion/exon skipping (EGFRvIII). Despite limitations in sample size, this study contributes data to the molecular landscape of glioblastomas, prompting further investigations to examine these findings more closely in larger cohorts.

Artificial Intelligence Imaging for Predicting High-risk Molecular Markers of Gliomas.

Gliomas, the most prevalent primary malignant tumors of the central nervous system, present significant challenges in diagnosis and prognosis. The fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS5) published in 2021, has emphasized the role of high-risk molecular markers in gliomas. These markers are crucial for enhancing glioma grading and influencing survival and prognosis. Noninvasive prediction of these high-risk molecular markers is vital. Genetic testing after biopsy, the current standard for determining molecular type, is invasive and time-consuming. Magnetic resonance imaging (MRI) offers a non-invasive alternative, providing structural and functional insights into gliomas. Advanced MRI methods can potentially reflect the pathological characteristics associated with glioma molecular markers; however, they struggle to fully represent gliomas' high heterogeneity. Artificial intelligence (AI) imaging, capable of processing vast medical image datasets, can extract critical molecular information. AI imaging thus emerges as a noninvasive and efficient method for identifying high-risk molecular markers in gliomas, a recent focus of research. This review presents a comprehensive analysis of AI imaging's role in predicting glioma high-risk molecular markers, highlighting challenges and future directions.

Relationship Between Cytogenetic Complexity and Peritumoral Edema in High-Grade Astrocytoma

BACKGROUND: The purpose of the study is to reveal the association of cytogenetic compltyexi and peritumoral edema volume (PTEV) and its prognostic significance in high-grade astrocytoma patients by culturing patient tumor cells. METHODS: Twenty-seven high-grade astrocytoma patients were divided into three groups according to karyotype complexity: normal, non-complex karyotype (NCK), and complex karyotype (CK). Endothelial growth factor receptor (EGFR) amplification was detected by FISH, and its association with chromosome 7 abnormalities was analyzed. Mean PTEV of each group was compared by ANOVA to evaluate the relationship between PTEV and cytogenetic complexity. RESULTS: The PTEV of patients in normal (n=6), NCK (n=8), and CK (n=13) groups were 24.52±17.73, 34.26±35.04, and 86.31±48.7 cm3, respectively (P=0.005). Ten out of 11 patients with EGFR amplification showed abnormalities in chromosome 7. The mean PTEV of EGFR-amplified and non-amplified groups were 80.4±53.7 and 41.3±37.9 cm3, respectively (P=0.035). The average survival of patients with PTEV less than 90 cm3 was 30.52±26.11 months, while in patients with PTEVs over or equal to 90 cm3, it was 10.83±5.53 months (P=0.007). CONCLUSIONS: The results show an association of complex karyotype with the PTEV of high-grade astrocytoma. EGFR amplification plays a significant role in the formation of peritumoral edema, causing PTEV to increase, which is related with survival. This implies that cytogenetic karyotype can be applied as a prognostic factor.