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PNAS Nexus Jun 2024Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the latest WHO guideline recommends that molecular subgroups of the genes,...
Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the latest WHO guideline recommends that molecular subgroups of the genes, including IDH, 1p/19q, MGMT, TERT, EGFR, Chromosome 7/10, CDKN2A/B, need to be detected to better classify glioma and guide surgery and treatment. Unfortunately, there is no preoperative or intraoperative technology available for accurate and comprehensive molecular subgrouping of glioma. Here, we develop a deep learning-assisted fiber-optic Raman diagnostic platform for accurate and rapid molecular subgrouping of high-grade glioma. Specifically, a total of 2,354 fingerprint Raman spectra was obtained from 743 tissue sites (astrocytoma: 151; oligodendroglioma: 150; glioblastoma (GBM): 442) of 44 high-grade glioma patients. The convolutional neural networks (ResNet) model was then established and optimized for molecular subgrouping. The mean area under receiver operating characteristic curves (AUC) for identifying the molecular subgroups of high-grade glioma reached 0.904, with mean sensitivity of 83.3%, mean specificity of 85.0%, mean accuracy of 83.3%, and mean time expense of 10.6 s. The diagnosis performance using ResNet model was shown to be superior to PCA-SVM and UMAP models, suggesting that high dimensional information from Raman spectra would be helpful. In addition, for the molecular subgroups of GBM, the mean AUC reached 0.932, with mean sensitivity of 87.8%, mean specificity of 83.6%, and mean accuracy of 84.1%. Furthermore, according to saliency maps, the specific Raman features corresponding to tumor-associated biomolecules (e.g. nucleic acid, tyrosine, tryptophan, cholesteryl ester, fatty acid, and collagen) were found to contribute to the accurate molecular subgrouping. Collectively, this study opens up new opportunities for accurate and rapid molecular subgrouping of high-grade glioma, which would assist optimal surgical resection and instant post-operative decision-making.
PubMed: 38860145
DOI: 10.1093/pnasnexus/pgae208 -
Cancer Medicine Jun 2024High-grade glioma (HGG) is known to be characterized by a high degree of malignancy and a worse prognosis. The classical treatment is safe resection supplemented by...
BACKGROUND AND OBJECTIVE
High-grade glioma (HGG) is known to be characterized by a high degree of malignancy and a worse prognosis. The classical treatment is safe resection supplemented by radiotherapy and chemotherapy. Tumor treating fields (TTFields), an emerging physiotherapeutic modality that targets malignant solid tumors using medium-frequency, low-intensity, alternating electric fields to interfere with cell division, have been used for the treatment of new diagnosis of glioblastoma, however, their administration in HGG requires further clinical evidence. The efficacy and safety of TTFields in Chinese patients with HGG were retrospectively evaluated by us in a single center.
METHODS
We enrolled and analyzed 52 patients with newly diagnosed HGG undergoing surgery and standard chemoradiotherapy regimens from December 2019 to June 2022, and followed them until June 2023. Based on whether they used TTFields, they were divided into a TTFields group and a non-TTFields group. Progression-free survival (PFS) and overall survival (OS) were compared between the two groups.
RESULTS
There were 26 cases in the TTFields group and 26 cases in the non-TTFields group. In the TTFields group, the median PFS was 14.2 months (95% CI: 9.50-18.90), the median OS was 19.7 months (95% CI: 14.95-24.25) , the median interval from surgery to the start of treatment with TTFields was 2.47 months (95% CI: 1.47-4.13), and the median duration of treatment with TTFields was 10.6 months (95% CI: 9.57-11.63). 15 (57.69%) patients experienced an adverse event and no serious adverse event was reported. In the non-TTFields group, the median PFS was 9.57 months (95% CI: 6.23-12.91) and the median OS was 16.07 months (95% CI: 12.90-19.24). There was a statistically significant difference in PFS (p = 0.005) and OS (p = 0.007) between the two groups.
CONCLUSIONS
In this retrospective analysis, TTFields were observed to improve newly diagnosed HGG patients' median PFS and OS. Compliance was much higher than reported in clinical trials and safety remained good.
Topics: Adult; Aged; Female; Humans; Male; Middle Aged; Young Adult; Brain Neoplasms; Chemoradiotherapy; China; East Asian People; Electric Stimulation Therapy; Glioma; Neoplasm Grading; Progression-Free Survival; Retrospective Studies; Treatment Outcome
PubMed: 38859683
DOI: 10.1002/cam4.7350 -
Nature Cell Biology Jun 2024Patients with IDH-wild-type glioblastomas have a poor five-year survival rate along with limited treatment efficacy due to immune cell (glioma-associated microglia and...
Patients with IDH-wild-type glioblastomas have a poor five-year survival rate along with limited treatment efficacy due to immune cell (glioma-associated microglia and macrophages) infiltration promoting tumour growth and resistance. To enhance therapeutic options, our study investigated the unique RNA-RNA-binding protein complex LOC-DHX15. This complex plays a crucial role in driving immune cell infiltration and tumour growth by establishing a feedback loop between cancer and immune cells, intensifying cancer aggressiveness. Targeting this complex with blood-brain barrier-permeable small molecules improved treatment efficacy, disrupting cell communication and impeding cancer cell survival and stem-like properties. Focusing on RNA-RNA-binding protein interactions emerges as a promising approach not only for glioblastomas without the IDH mutation but also for potential applications beyond cancer, offering new avenues for developing therapies that address intricate cellular relationships in the body.
Topics: Glioblastoma; Humans; Tumor Microenvironment; Brain Neoplasms; Animals; Isocitrate Dehydrogenase; RNA-Binding Proteins; Cell Line, Tumor; Mice; Mutation; Antineoplastic Agents; Xenograft Model Antitumor Assays; Cell Proliferation; Gene Expression Regulation, Neoplastic
PubMed: 38858501
DOI: 10.1038/s41556-024-01428-5 -
Scientific Reports Jun 2024Safe and effective brain tumor surgery aims to remove tumor tissue, not non-tumoral brain. This is a challenge since tumor cells are often not visually distinguishable...
Safe and effective brain tumor surgery aims to remove tumor tissue, not non-tumoral brain. This is a challenge since tumor cells are often not visually distinguishable from peritumoral brain during surgery. To address this, we conducted a multicenter study testing whether the Sentry System could distinguish the three most common types of brain tumors from brain tissue in a label-free manner. The Sentry System is a new real time, in situ brain tumor detection device that merges Raman spectroscopy with machine learning tissue classifiers. Nine hundred and seventy-six in situ spectroscopy measurements and colocalized tissue specimens were acquired from 67 patients undergoing surgery for glioblastoma, brain metastases, or meningioma to assess tumor classification. The device achieved diagnostic accuracies of 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas. These data show that the Sentry System discriminated tumor containing tissue from non-tumoral brain in real time and prior to resection.
Topics: Humans; Brain Neoplasms; Spectrum Analysis, Raman; Male; Female; Middle Aged; Aged; Meningioma; Glioblastoma; Adult; Machine Learning; Brain
PubMed: 38858389
DOI: 10.1038/s41598-024-62543-9 -
JCO Clinical Cancer Informatics Jun 2024Data on lines of therapy (LOTs) for cancer treatment are important for clinical oncology research, but LOTs are not explicitly recorded in electronic health records...
PURPOSE
Data on lines of therapy (LOTs) for cancer treatment are important for clinical oncology research, but LOTs are not explicitly recorded in electronic health records (EHRs). We present an efficient approach for clinical data abstraction and a flexible algorithm to derive LOTs from EHR-based medication data on patients with glioblastoma multiforme (GBM).
METHODS
Nonclinicians were trained to abstract the diagnosis of GBM from EHRs, and their accuracy was compared with abstraction performed by clinicians. The resulting data were used to build a cohort of patients with confirmed GBM diagnosis. An algorithm was developed to derive LOTs using structured medication data, accounting for the addition and discontinuation of therapies and drug class. Descriptive statistics were calculated and time-to-next-treatment (TTNT) analysis was performed using the Kaplan-Meier method.
RESULTS
Treating clinicians as the gold standard, nonclinicians abstracted GBM diagnosis with a sensitivity of 0.98, specificity 1.00, positive predictive value 1.00, and negative predictive value 0.90, suggesting that nonclinician abstraction of GBM diagnosis was comparable with clinician abstraction. Of 693 patients with a confirmed diagnosis of GBM, 246 patients contained structured information about the types of medications received. Of them, 165 (67.1%) received a first-line therapy (1L) of temozolomide, and the median TTNT from the start of 1L was 179 days.
CONCLUSION
We described a workflow for extracting diagnosis of GBM and LOT from EHR data that combines nonclinician abstraction with algorithmic processing, demonstrating comparable accuracy with clinician abstraction and highlighting the potential for scalable and efficient EHR-based oncology research.
Topics: Humans; Glioblastoma; Electronic Health Records; Algorithms; Female; Male; Middle Aged; Aged; Brain Neoplasms; Adult
PubMed: 38857465
DOI: 10.1200/CCI.23.00091 -
PLoS Genetics Jun 2024Glioblastoma (GBM) invasion studies have focused on coding genes, while few studies evaluate long non-coding RNAs (lncRNAs), transcripts without protein-coding...
INTRODUCTION
Glioblastoma (GBM) invasion studies have focused on coding genes, while few studies evaluate long non-coding RNAs (lncRNAs), transcripts without protein-coding potential, for role in GBM invasion. We leveraged CRISPR-interference (CRISPRi) to evaluate invasive function of GBM-associated lncRNAs in an unbiased functional screen, characterizing and exploring the mechanism of identified candidates.
METHODS
We implemented a CRISPRi lncRNA loss-of-function screen evaluating association of lncRNA knockdown (KD) with invasion capacity in Matrigel. Top screen candidates were validated using CRISPRi and oligonucleotide(ASO)-mediated knockdown in three tumor lines. Clinical relevance of candidates was assessed via The Cancer Genome Atlas(TCGA) and Genotype-Tissue Expression(GTEx) survival analysis. Mediators of lncRNA effect were identified via differential expression analysis following lncRNA KD and assessed for tumor invasion using knockdown and rescue experiments.
RESULTS
Forty-eight lncRNAs were significantly associated with 33-83% decrease in invasion (p<0.01) upon knockdown. The top candidate, LINC03045, identified from effect size and p-value, demonstrated 82.7% decrease in tumor cell invasion upon knockdown, while LINC03045 expression was significantly associated with patient survival and tumor grade(p<0.0001). RNAseq analysis of LINC03045 knockdown revealed that WASF3, previously implicated in tumor invasion studies, was highly correlated with lncRNA expression, while WASF3 KD was associated with significant decrease in invasion. Finally, WASF3 overexpression demonstrated rescue of invasive function lost with LINC03045 KD.
CONCLUSION
CRISPRi screening identified LINC03045, a previously unannotated lncRNA, as critical to GBM invasion. Gene expression is significantly associated with tumor grade and survival. RNA-seq and mechanistic studies suggest that this novel lncRNA may regulate invasion via WASF3.
Topics: RNA, Long Noncoding; Humans; Glioblastoma; Neoplasm Invasiveness; Gene Expression Regulation, Neoplastic; Cell Line, Tumor; Brain Neoplasms; CRISPR-Cas Systems; Gene Knockdown Techniques; Cell Movement; Clustered Regularly Interspaced Short Palindromic Repeats
PubMed: 38857306
DOI: 10.1371/journal.pgen.1011314 -
Briefings in Bioinformatics May 2024Cluster analysis, a pivotal step in single-cell sequencing data analysis, presents substantial opportunities to effectively unveil the molecular mechanisms underlying...
Cluster analysis, a pivotal step in single-cell sequencing data analysis, presents substantial opportunities to effectively unveil the molecular mechanisms underlying cellular heterogeneity and intercellular phenotypic variations. However, the inherent imperfections arise as different clustering algorithms yield diverse estimates of cluster numbers and cluster assignments. This study introduces Single Cell Consistent Clustering based on Spectral Matrix Decomposition (SCSMD), a comprehensive clustering approach that integrates the strengths of multiple methods to determine the optimal clustering scheme. Testing the performance of SCSMD across different distances and employing the bespoke evaluation metric, the methodological selection undergoes validation to ensure the optimal efficacy of the SCSMD. A consistent clustering test is conducted on 15 authentic scRNA-seq datasets. The application of SCSMD to human embryonic stem cell scRNA-seq data successfully identifies known cell types and delineates their developmental trajectories. Similarly, when applied to glioblastoma cells, SCSMD accurately detects pre-existing cell types and provides finer sub-division within one of the original clusters. The results affirm the robust performance of our SCSMD method in terms of both the number of clusters and cluster assignments. Moreover, we have broadened the application scope of SCSMD to encompass larger datasets, thereby furnishing additional evidence of its superiority. The findings suggest that SCSMD is poised for application to additional scRNA-seq datasets and for further downstream analyses.
Topics: Humans; Single-Cell Analysis; Cluster Analysis; Algorithms; Computational Biology; Glioblastoma
PubMed: 38855914
DOI: 10.1093/bib/bbae273 -
Neuro-oncology Advances 2024Based on preclinical studies showing that IDH-mutant (IDHm) gliomas could be vulnerable to PARP inhibition we launched a multicenter phase 2 study to test the efficacy...
BACKGROUND
Based on preclinical studies showing that IDH-mutant (IDHm) gliomas could be vulnerable to PARP inhibition we launched a multicenter phase 2 study to test the efficacy of olaparib monotherapy in this population.
METHODS
Adults with recurrent IDHm high-grade gliomas (HGGs) after radiotherapy and at least one line of alkylating chemotherapy were enrolled. The primary endpoint was a 6-month progression-free survival rate (PFS-6) according to response assessment in neuro-oncology criteria. Pre-defined threshold for study success was a PFS-6 of at least 50%.
RESULTS
Thirty-five patients with recurrent IDHm HGGs were enrolled, 77% at ≥ 2nd recurrence. Median time since diagnosis and radiotherapy were 7.5 years and 33 months, respectively. PFS-6 was 31.4% (95% CI [16.9; 49.3%]). Two patients (6%) had an objective response and 14 patients (40%) had a stable disease as their best response. Median PFS and median overall survival were 2.05 and 15.9 months, respectively. Oligodendrogliomas (1p/19q codeleted) had a higher PFS-6 (53.4% vs. 15.7%, = .05) than astrocytomas while an initial diagnosis of grade 4 astrocytoma tended to be associated with a lower PFS-6 compared to grade 2/3 gliomas (0% vs 31.4%, = .16). A grade 2 or 3 treatment-related adverse event was observed in 15 patients (43%) and 5 patients (14%), respectively. No patient definitively discontinued treatment due to side effects.
CONCLUSIONS
Although it did not meet its primary endpoint, the present study shows that in this heavily pretreated population, olaparib monotherapy was well tolerated and resulted in some activity, supporting further PARP inhibitors evaluation in IDHm HGGs, especially in oligodendrogliomas.
PubMed: 38855053
DOI: 10.1093/noajnl/vdae078 -
Journal of Translational Medicine Jun 2024Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted...
BACKGROUND
Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy.
METHODS
We collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software.
RESULTS
We observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM.
CONCLUSIONS
These biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.
Topics: Humans; Glioblastoma; Tumor Microenvironment; Biomarkers, Tumor; Single-Cell Analysis; Gene Expression Regulation, Neoplastic; Brain Neoplasms; Cluster Analysis; Protein Interaction Maps; DNA Copy Number Variations; Cell Aggregation; Gene Expression Profiling
PubMed: 38851695
DOI: 10.1186/s12967-024-05313-5 -
STAR Protocols Jun 2024Lysosomes are critical for the sustenance of glioblastoma stem-like cells (GSCs) properties. We present a protocol to enrich and purify lysosomes from patient-derived...
Lysosomes are critical for the sustenance of glioblastoma stem-like cells (GSCs) properties. We present a protocol to enrich and purify lysosomes from patient-derived GSCs in culture. We describe the steps required to stably express a tagged lysosomal protein in GSCs, mechanically lyse cells, magnetically immunopurify lysosomes, and qualitatively assess these organelles. We then detail the procedure for retrieving intact and purified lysosomes from GSCs. We also specify cell culture conditions, storage procedures, and sample preparation for immunoblotting. For complete details on the use and execution of this protocol, please refer to Maghe et al..
Topics: Humans; Glioblastoma; Lysosomes; Neoplastic Stem Cells; Immunoprecipitation; Brain Neoplasms
PubMed: 38850538
DOI: 10.1016/j.xpro.2024.103121