Integrated pharmaco-proteogenomics defines two subgroups in isocitrate dehydrogenase wild-type glioblastoma with prognostic and therapeutic opportunities

Systematic Review of Cerebrospinal Fluid Biomarker Discovery in Neuro-Oncology: A Roadmap to Standardization and Clinical Application

Effective diagnosis, prognostication, and management of CNS malignancies traditionally involves invasive brain biopsies that pose significant risk to the patient. Sampling and molecular profiling of cerebrospinal fluid (CSF) is a safer, rapid, and noninvasive alternative that offers a snapshot of the intracranial milieu while overcoming the challenge of sampling error that plagues conventional brain biopsy. Although numerous biomarkers have been identified, translational challenges remain, and standardization of protocols is necessary. Here, we systematically reviewed 141 studies (Medline, SCOPUS, and Biosis databases; between January 2000 and September 29, 2022) that molecularly profiled CSF from adults with brain malignancies including glioma, brain metastasis, and primary and secondary CNS lymphomas. We provide an overview of promising CSF biomarkers, propose CSF reporting guidelines, and discuss the various considerations that go into biomarker discovery, including the influence of blood-brain barrier disruption, cell of origin, and site of CSF acquisition (eg, lumbar and ventricular). We also performed a meta-analysis of proteomic data sets, identifying biomarkers in CNS malignancies and establishing a resource for the research community.

Proteomics of tumor and serum samples from isocitrate dehydrogenase-wildtype glioblastoma patients: is the detoxification of reactive oxygen species associated with shorter survival?

Proteomics has been little used for the identification of novel prognostic and/or therapeutic markers in isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GB). In this study, we analyzed 50 tumor and 30 serum samples from short- and long-term survivors of IDH-wildtype GB (STS and LTS, respectively) by data-independent acquisition mass spectrometry (DIA-MS)-based proteomics, with the aim of identifying such markers. DIA-MS identified 5422 and 826 normalized proteins in tumor and serum samples, respectively, with only three tumor proteins and 26 serum proteins displaying significant differential expression between the STS and LTS groups. These dysregulated proteins were principally associated with the detoxification of reactive oxygen species (ROS). In particular, GB patients in the STS group had high serum levels of malate dehydrogenase 1 (MDH1) and ribonuclease inhibitor 1 (RNH1) and low tumor levels of fatty acid-binding protein 7 (FABP7), which may have enabled them to maintain low ROS levels, counteracting the effects of the first-line treatment with radiotherapy plus concomitant and adjuvant temozolomide. A blood score built on the levels of MDH1 and RNH1 expression was found to be an independent prognostic factor for survival based on the serum proteome data for a cohort of 96 IDH-wildtype GB patients. This study highlights the utility of circulating MDH1 and RNH1 biomarkers for determining the prognosis of patients with IDH-wildtype GB. Furthermore, the pathways driven by these biomarkers, and the tumor FABP7 pathway, may constitute promising therapeutic targets for blocking ROS detoxification to overcome resistance to chemoradiotherapy in potential GB STS.

Proteogenomic Characterization Reveals Estrogen Signaling as a Target for Never-Smoker Lung Adenocarcinoma Patients without EGFR or ALK Alterations

Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major genetic alterations observed in NSLA, and NSLA with these alterations have been well studied and can be treated with targeted therapies. To provide insights into the molecular profile of NSLA without EGFR and ALK alterations (NENA), we selected 141 NSLA tissues and performed proteogenomic characterization, including whole genome sequencing (WGS), transcriptomic, methylation EPIC array, total proteomic, and phosphoproteomic analyses. Forty patients with NSLA harboring EGFR and ALK alterations and seven patients with NENA with microsatellite instability were excluded. Genome analysis revealed that TP53 (25%), KRAS (22%), and SETD2 (11%) mutations and ROS1 fusions (14%) were the most frequent genetic alterations in NENA patients. Proteogenomic impact analysis revealed that STK11 and ERBB2 somatic mutations had broad effects on cancer-associated genes in NENA. DNA copy number alteration analysis identified 22 prognostic proteins that influenced transcriptomic and proteomic changes. Gene set enrichment analysis revealed estrogen signaling as the key pathway activated in NENA. Increased estrogen signaling was associated with proteogenomic alterations, such as copy number deletions in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14. Finally, saracatinib, an Src inhibitor, was identified as a potential drug for targeting activated estrogen signaling in NENA and was experimentally validated in vitro. Collectively, this study enhanced our understanding of NENA NSLA by elucidating the proteogenomic landscape and proposed saracatinib as a potential treatment for this patient population that lacks effective targeted therapies.

SIGNIFICANCE

The proteogenomic landscape in never-smoker lung cancer without known driver mutations reveals prognostic proteins and enhanced estrogen signaling that can be targeted as a potential therapeutic strategy to improve patient outcomes.

Treatment advances in high-grade gliomas

High-grade gliomas (HGG) pose significant challenges in modern tumour therapy due to the distinct biological properties and limitations of the blood-brain barrier. This review discusses recent advancements in HGG treatment, particularly in the context of immunotherapy and cellular therapy. Initially, treatment strategies focus on targeting tumour cells guided by the molecular characteristics of various gliomas, encompassing chemotherapy, radiotherapy and targeted therapy for enhanced precision. Additionally, technological enhancements are augmenting traditional treatment modalities. Furthermore, immunotherapy, emphasising comprehensive tumour management, has gained widespread attention. Immune checkpoint inhibitors, vaccines and CAR-T cells exhibit promising efficacy against recurrent HGG. Moreover, emerging therapies such as tumour treating fields (TTFields) offer additional treatment avenues for patients with HGG. The combination of diverse treatments holds promise for improving the prognosis of HGG, particularly in cases of recurrence.

Quantitative Assessment of Preanalytic Variables on Clinical Evaluation of PI3/AKT/mTOR Signaling Activity in Diffuse Glioma

Biomarker-driven therapeutic clinical trials require the implementation of standardized, evidence-based practices for sample collection. In diffuse glioma, phosphatidylinositol 3 (PI3)-kinase/AKT/mTOR (PI3/AKT/mTOR) signaling is an attractive therapeutic target for which window-of-opportunity clinical trials could facilitate the identification of promising new agents. Yet, the relevant preanalytic variables and optimal tumor sampling methods necessary to measure pathway activity are unknown. To address this, we used a murine model for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) and human tumor tissue, including IDH-wildtype GBM and IDH-mutant diffuse glioma. First, we determined the impact of delayed time-to-formalin fixation, or cold ischemia time (CIT), on the quantitative assessment of cellular expression of 6 phosphoproteins that are readouts of PI3K/AK/mTOR activity (phosphorylated-proline-rich Akt substrate of 40 kDa (p-PRAS40, T246), -mechanistic target of rapamycin (p-mTOR; S2448); -AKT (p-AKT, S473); -ribosomal protein S6 (p-RPS6, S240/244 and S235/236), and -eukaryotic initiation factor 4E-binding protein 1 (p-4EBP1, T37/46). With CITs ≥ 2 hours, typical of routine clinical handling, all had reduced or altered expression with p-RPS6 (S240/244) exhibiting relatively greater stability. A similar pattern was observed using patient tumor samples from the operating room with p-4EBP1 more sensitive to delayed fixation than p-RPS6 (S240/244). Many clinical trials utilize unstained slides for biomarker evaluation. Thus, we evaluated the impact of slide storage conditions on the detection of p-RPS6 (S240/244), p-4EBP1, and p-AKT. After 5 months, storage at -80°C was required to preserve the expression of p-4EBP1 and p-AKT, whereas p-RPS6 (240/244) expression was not stable regardless of storage temperature. Biomarker heterogeneity impacts optimal tumor sampling. Quantification of p-RPS6 (240/244) expression in multiple regionally distinct human tumor samples from 8 patients revealed significant intratumoral heterogeneity. Thus, the accurate assessment of PI3K/AKT/mTOR signaling in diffuse glioma must overcome intratumoral heterogeneity and multiple preanalytic factors, including time-to-formalin fixation, slide storage conditions, and phosphoprotein of interest.

Integrated transcriptomics uncovers an enhanced association between the prion protein gene expression and vesicle dynamics signatures in glioblastomas

BACKGROUND

Glioblastoma (GBM) is an aggressive brain tumor that exhibits resistance to current treatment, making the identification of novel therapeutic targets essential. In this context, cellular prion protein (PrPC) stands out as a potential candidate for new therapies. Encoded by the PRNP gene, PrPC can present increased expression levels in GBM, impacting cell proliferation, growth, migration, invasion and stemness. Nevertheless, the exact molecular mechanisms through which PRNP/PrPC modulates key aspects of GBM biology remain elusive.

METHODS

To elucidate the implications of PRNP/PrPC in the biology of this cancer, we analyzed publicly available RNA sequencing (RNA-seq) data of patient-derived GBMs from four independent studies. First, we ranked samples profiled by bulk RNA-seq as PRNPhigh and PRNPlow and compared their transcriptomic landscape. Then, we analyzed PRNP+ and PRNP- GBM cells profiled by single-cell RNA-seq to further understand the molecular context within which PRNP/PrPC might function in this tumor. We explored an additional proteomics dataset, applying similar comparative approaches, to corroborate our findings.

RESULTS

Functional profiling revealed that vesicular dynamics signatures are strongly correlated with PRNP/PrPC levels in GBM. We found a panel of 73 genes, enriched in vesicle-related pathways, whose expression levels are increased in PRNPhigh/PRNP+ cells across all RNA-seq datasets. Vesicle-associated genes, ANXA1, RAB31, DSTN and SYPL1, were found to be upregulated in vitro in an in-house collection of patient-derived GBM. Moreover, proteome analysis of patient-derived samples reinforces the findings of enhanced vesicle biogenesis, processing and trafficking in PRNPhigh/PRNP+ GBM cells.

CONCLUSIONS

Together, our findings shed light on a novel role for PrPC as a potential modulator of vesicle biology in GBM, which is pivotal for intercellular communication and cancer maintenance. We also introduce GBMdiscovery, a novel user-friendly tool that allows the investigation of specific genes in GBM biology.

GPC2 as a diagnostic and prognostic marker regulated progression of colorectal cancer

BACKGROUND AND STUDY AIMS

Glypican 2 (GPC2) is a member of the glypican gene family and is expressed in multiple kinds of cancer. However, the function and mechanism of GPC2 in colorectal cancer remains unclear. In this study, we aimed to identify the role of GPC2 on tumor cell proliferation and survival in colorectal cancer.

PATIENTS AND METHODS

Ten pairs of colon cancer and matched normal colon tissues were collected in this research. GEPIA was used to analysis the GPC2 gene expression profile in TGCA data base. RT-qPCR and western blot assay were performed to determine the mRNA and protein expressions. CCK-8, Flow cytometry and colon formation assay were applied to evaluate cell viability. IHC staining was performed to evaluate the protein expression in tissues. The function of GPC2 in vivo was verified by an animal model of colon cancer.

RESULTS

Through the bioinformatics analysis and qRT-PCR validation, we found that GPC2 was upregulated in the colon cancer tissues and cells. GPC2 knockdown suppressed cell proliferation in vitro and in vivo was confirmed by the results of CCK-8, colony formation assays, and tumor xenograft models. Moreover, by the analysis of flow cytometry assay and gain-or-loss function experiments, we discovered that CEP164 was highly associated with the expression state of GPC2, and mediated G2/M-phase arrest in GPC2-downregulated tumor cells.

CONCLUSION

GPC2 might be a novel oncogenic gene in colorectal cancer, suggesting that it could be a considerable marker for the diagnosis and prognosis of colorectal cancer.

Flavopiridol Suppresses Cell Proliferation and Migration and Induces Apoptotic Cell Death by Inhibiting Oncogenic FOXM1 Signaling in IDH Wild-Type and IDH-Mutant GBM Cells

Glioblastoma multiforme (GBM) remains one of the most challenging solid cancers to treat due to its highly aggressive and drug-resistant nature. Flavopiridol is synthetic flavone that was recently approved by the FDA for the treatment of acute myeloid leukemia. Flavopiridol exhibits antiproliferative activity in several solid cancer cells and currently evaluated in clinical trials in several solid and hematological cancers. In this study, we investigated the molecular mechanisms underlying antiproliferative effects of flavopiridol in GBM cell lines with wild-type and mutant encoding isocitrate dehydrogenase 1 (IDH1). We found that flavopiridol inhibits proliferation, colony formation, and migration and induces apoptosis in IDH1 wild-type and IDH-mutant cells through inhibition of FOXM1 oncogenic signaling. Furthermore, flavopiridol treatment also inhibits of NF-KB, mediators unfolded protein response (UPR), including, GRP78, PERK and IRE1α, and DNA repair enzyme PARP, which have been shown to be potential therapeutic targets by downregulating FOXM1 in GBM cells. Our findings suggest for the first time that flavopiridol suppresses proliferation, survival, and migration and induces apoptosis in IDH1 wild-type and IDH1-mutant GBM cells by targeting FOXM1 oncogenic signaling which also regulates NF-KB, PARP, and UPR response in GBM cells. Flavopiridol may be a potential novel therapeutic strategy in the treatment of patients IDH1 wild-type and IDH1-mutant GBM.

Identification of a novel potent CDK inhibitor degrading cyclinK with a superb activity to reverse trastuzumab-resistance in HER2-positive breast cancer in vivo

CDK12 is overexpressed in HER2-positive breast cancers and promotes tumorigenesis and trastuzumab resistance. Thus CDK12 is a good therapeutic target for the HER2-positive breast tumors resistant to trastuzumab. We previously reported a novel purine-based CDK inhibitor with an ability to degrade cyclinK. Herein, we further explored and synthesized new derivatives, and identified a new potent pan-CDK inhibitor degrading cyclinK (32e). Compound 32e potently inhibited CDK12/cyclinK with IC50 = 3 nM, and suppressed the growth of the both trastuzumab-sensitive and trastuzumab-resistant HER2-positive breast cancer cell lines (GI50's = 9-21 nM), which is superior to a potent, clinical pan-CDK inhibitor dinaciclib. Moreover, 32e (10, 20 mg/kg, ip, twice a week) showed a dose-dependent inhibition of tumor growth and a more dramatic anti-cancer effect than dinaciclib in mouse in vivo orthotopic breast cancer model of trastuzumab-resistant HCC1954 cells. Kinome-wide inhibition profiling revealed that 32e at 1 μM exhibits a decent selectivity toward CDK-family kinases including CDK12 over other wildtype protein kinases. Quantitative global proteomic analysis of 32e-treated HCC1954 cells demonstrated that 32e also showed a decent selectivity in degrading cyclinK over other cyclins. Compound 32e could be developed as a drug for intractable trastuzumab-resistant HER2-positive breast cancers. Our current study would provide a useful insight in designing potent cyclinK degraders.

Integrated omics landscape of hepatocellular carcinoma suggests proteomic subtypes for precision therapy

Patients with hepatocellular carcinoma (HCC) at the same clinical stage can have extremely different prognoses, and molecular subtyping provides an opportunity for individualized precision treatment. In this study, genomic, transcriptomic, proteomic, and phosphoproteomic profiling of primary tumor tissues and paired para-tumor tissues from HCC patients (N = 160) are integrated. Proteomic profiling identifies three HCC subtypes with different clinical prognosis, which are validated in three publicly available external validation sets. A simplified panel of nine proteins associated with metabolic reprogramming is further identified as a potential subtype-specific biomarker for clinical application. Multi-omics analysis further reveals that three proteomic subtypes have significant differences in genetic alterations, microenvironment dysregulation, kinase-substrate regulatory networks, and therapeutic responses. Patient-derived cell-based drug tests (N = 26) show personalized responses for sorafenib in three proteomic subtypes, which can be predicted by a machine-learning response prediction model. Overall, this study provides a valuable resource for better understanding of HCC subtypes for precision clinical therapy.

Ferroptosis: An Emerging Target for Bladder Cancer Therapy

Bladder cancer (BC), as one of the main urological cancers in the world, possesses the abilities of multiple-drug resistance and metastasis. However, there remains a significant gap in the understanding and advancement of prognosis and therapeutic strategies for BC. Ferroptosis, a novel type of iron-dependent regulated cell death, depends on lipid peroxidation, which has been proven to have a strong correlation with the development and treatment of BC. Its mechanism mainly includes three pathways, namely, lipid peroxidation, the antioxidant system, and the iron overload pathway. In this review, we reviewed the mechanism of ferroptosis, along with the related therapeutic targets and drugs for BC, as it might become a new anticancer treatment in the future.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Untangling the web of glioblastoma treatment resistance using a multi-omic and multidisciplinary approach

Glioblastoma (GBM), the most common human brain tumor, has been notoriously resistant to treatment. As a result, the dismal overall survival of GBM patients has not changed over the past three decades. GBM has been stubbornly resistant to checkpoint inhibitor immunotherapies, which have been remarkably effective in the treatment of other tumors. It is clear that GBM resistance to therapy is multifactorial. Although therapeutic transport into brain tumors is inhibited by the blood brain barrier, there is evolving evidence that overcoming this barrier is not the predominant factor. GBMs generally have a low mutation burden, exist in an immunosuppressed environment and they are inherently resistant to immune stimulation, all of which contribute to treatment resistance. In this review, we evaluate the contribution of multi-omic approaches (genomic and metabolomic) along with analyzing immune cell populations and tumor biophysical characteristics to better understand and overcome GBM multifactorial resistance to treatment.

Biomaterial-based in vitro 3D modeling of glioblastoma multiforme

Adult-onset brain cancers, such as glioblastomas, are particularly lethal. People with glioblastoma multiforme (GBM) do not anticipate living for more than 15 months if there is no cure. The results of conventional treatments over the past 20 years have been underwhelming. Tumor aggressiveness, location, and lack of systemic therapies that can penetrate the blood-brain barrier are all contributing factors. For GBM treatments that appear promising in preclinical studies, there is a considerable rate of failure in phase I and II clinical trials. Unfortunately, access becomes impossible due to the intricate architecture of tumors. In vitro, bioengineered cancer models are currently being used by researchers to study disease development, test novel therapies, and advance specialized medications. Many different techniques for creating in vitro systems have arisen over the past few decades due to developments in cellular and tissue engineering. Later-stage research may yield better results if in vitro models that resemble brain tissue and the blood-brain barrier are used. With the use of 3D preclinical models made available by biomaterials, researchers have discovered that it is possible to overcome these limitations. Innovative in vitro models for the treatment of GBM are possible using biomaterials and novel drug carriers. This review discusses the benefits and drawbacks of 3D in vitro glioblastoma modeling systems.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

Prognosis and Personalized Treatment Prediction in Different Mutation-Signature Hepatocellular Carcinoma

Introduction

Mutation patterns have been extensively explored to decipher the etiologies of hepatocellular carcinoma (HCC). However, the study and potential clinical role of mutation patterns to stratify high-risk patients and optimize precision therapeutic strategies remain elusive in HCC.

Methods

Using exon-sequencing data in public (n=362) and in-house (n=30) cohorts, mutation signatures were extracted to decipher relationships with the etiology and prognosis in HCC. The proteomics (n=159) and cell-line transcriptome data (n=1019) were collected to screen the implication of sensitive drugs. A novel multi-step machine-learning framework was then performed to construct a classification predictor, including recognizing stable reversed gene pairs, establishing a robust prediction model, and validating the robustness of the predictor in five independent cohorts (n=900).

Results

Two heterogeneous mutation signature clusters were identified, and a high-risk prognosis cluster was recognized for further analysis. Notably, mutation signature cluster 1 (MSC1) was featured by activated anti-tumor immune and metabolism dysfunctional states, higher genomic instability (high TMB, SNV neoantigen, indel neoantigens, and total neoantigens), and a dismal prognosis. Notably, MSC performed as an independent risk factor than clinical traits (eg, stage, vascular invasion). Additionally, afatinib and canertinib were recognized which might have potential therapeutic implications in MSC1, and the targets of these drugs presented a higher expression in both gene and protein levels in HCC.

Discussion

Our studies may provide a promising platform for improving prognosis and tailoring therapy in HCC.

Mitochondrial-Targeted Antioxidant MitoQ-Mediated Autophagy: A Novel Strategy for Precise Radiation Protection

Radiotherapy (RT) is one of the most effective cancer treatments. However, successful radiation protection for normal tissue is a clinical challenge. Our previous study observed that MitoQ, a mitochondria-targeted antioxidant, was adsorbed to the inner mitochondrial membrane and remained the cationic moiety in the intermembrane space. The positive charges in MitoQ restrained the activity of respiratory chain complexes and decreased proton production. Therefore, a pseudo-mitochondrial membrane potential (PMMP) was developed via maintenance of exogenous positive charges. This study identified that PMMP constructed by MitoQ could effectively inhibit mitochondrial respiration within normal cells, disrupt energy metabolism, and activate adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) signaling to induce autophagy. As such, it could not lead to starvation-induced autophagy among tumor cells due to the different energy phenotypes between normal and tumor cells (normal cells depend on mitochondrial respiration for energy supply, while tumor cells rely on aerobic glycolysis). Therefore, we successfully protected the normal cells from radiation-induced damage without affecting the tumor-killing efficacy of radiation by utilizing selective autophagy. MitoQ-constructed PMMP provides a new therapeutic strategy for specific radiation protection.

Proteomics separates adult-type diffuse high-grade gliomas in metabolic subgroups independent of 1p/19q codeletion and across IDH mutational status

High-grade adult-type diffuse gliomas are malignant neuroepithelial tumors with poor survival rates in combined chemoradiotherapy. The current WHO classification is based on IDH1/2 mutational and 1p/19q codeletion status. Glioma proteome alterations remain undercharacterized despite their promise for a better molecular patient stratification and therapeutic target identification. Here, we use mass spectrometry to characterize 42 formalin-fixed, paraffin-embedded (FFPE) samples from IDH-wild-type (IDHwt) gliomas, IDH-mutant (IDHmut) gliomas with and without 1p/19q codeletion, and non-neoplastic controls. Based on more than 5,500 quantified proteins and 5,000 phosphosites, gliomas separate by IDH1/2 mutational status but not by 1p/19q status. Instead, IDHmut gliomas split into two proteomic subtypes with widespread perturbations, including aerobic/anaerobic energy metabolism. Validations with three independent glioma proteome datasets confirm these subgroups and link the IDHmut subtypes to the established proneural and classic/mesenchymal subtypes in IDHwt glioma. This demonstrates common phenotypic subtypes across the IDH status with potential therapeutic implications for patients with IDHmut gliomas.

Cost Matrix of Molecular Pathology in Glioma-Towards AI-Driven Rational Molecular Testing and Precision Care for the Future

Gliomas are the most common and aggressive primary brain tumors. Gliomas carry a poor prognosis because of the tumor's resistance to radiation and chemotherapy leading to nearly universal recurrence. Recent advances in large-scale genomic research have allowed for the development of more targeted therapies to treat glioma. While precision medicine can target specific molecular features in glioma, targeted therapies are often not feasible due to the lack of actionable markers and the high cost of molecular testing. This review summarizes the clinically relevant molecular features in glioma and the current cost of care for glioma patients, focusing on the molecular markers and meaningful clinical features that are linked to clinical outcomes and have a realistic possibility of being measured, which is a promising direction for precision medicine using artificial intelligence approaches.

PHGDH Inhibits Ferroptosis and Promotes Malignant Progression by Upregulating SLC7A11 in Bladder Cancer

Background: Bladder cancer (BCa) is a prevalent urologic malignancy that shows a poor prognosis. Abnormal metabolism and its key genes play a critical role in BCa progression. In this study, the role played by PhosphoGlycerol Dehydrogenase (PHGDH), an important molecule of serine metabolism, was investigated with regard to the regulation of ferroptosis in BCa.

Methods: The BCa tissues of 90 patients were analyzed by RNA-sequencing for differential pathways and genes. Western blot, qPCR, and IHC were used to determine PHGDH expression in the cell lines (in vitro) and patient tissues (in vivo). R software was used to analyze PHGDH expression, prognosis, and PHGDH+SLC7A11 score. The biological functions of PHGDH were examined through organoids, and in vitro and in vivo experiments. C11 probes, electron microscopy, and ferroptosis inhibitors/ inducers were used to detect cellular ferroptosis levels. Protein profiling, co-IP, and RIP assays were used to screen proteins that might bind to PHGDH. PHGDH-targeted inhibitor NCT-502 was used to evaluate its effect on BCa cells.

Results: PHGDH was highly expressed in patients with BCa. Knock-down of PHGDH promoted ferroptosis, while the decreased proliferation of BCa cells. Additionally, PHGDH knock-down downregulated the expression of SLC7A11. Co-IP and mass spectrometry experiments indicate that PHGDH binds to PCBP2, an RNA-binding protein, and inhibits its ubiquitination degradation. PCBP2 in turn stabilizes SLC7A11 mRNA and increases its expression. NCT-502, a PHGDH inhibitor, promotes ferroptosis and inhibits tumor progression in BCa. The PHGDH+ SLC7A11 score was significantly correlated with patient prognosis.

Conclusions: To conclude, the PHGDH, via interaction with PCBP2, upregulates SLC7A11 expression. This inhibits ferroptosis and promotes the malignant progression of BCA. The results of this study indicated that NCT-502 could serve as a therapeutic strategy for BCa.

Regulatory pattern of abnormal promoter CpG island methylation in the glioblastoma multiforme classification

Glioblastoma (GBM) is characterized by extensive genetic and phenotypic heterogeneity. However, it remains unexplored primarily how CpG island methylation abnormalities in promoter mediate glioblastoma typing. First, we presented a multi-omics scale map between glioblastoma sample clusters constructed based on promoter CpG island (PCGI) methylation-driven genes, using datasets including methylation profiles, expression profiles, and single-cell sequencing data from multiple highly annotated public clinical cohorts. Second, we identified differences in the tumor microenvironment between the two glioblastoma sample clusters and resolved key signaling pathways between cell clusters at the single-cell level based on comprehensive comparative analyses to investigate the reasons for survival differences between two of these clusters. Finally, we developed a diagnostic map and a prediction model for glioblastoma, and compared theoretical differences of drug sensitivity between two glioblastoma sample clusters. In summary, this study established a classification system for dissecting promoter CpG island methylation heterogeneity in glioblastoma and provides a new perspective for the diagnosis and treatment of glioblastoma.

Integrated proteomic analysis of low-grade gliomas reveals contributions of 1p-19q co-deletion to oligodendroglioma

Diffusely infiltrative low-grade gliomas (LGG) are primary brain tumours that arise predominantly in the cerebral hemispheres of younger adults. LGG can display either astrocytic or oligodendroglial histology and do not express malignant histological features. Vast majority of LGG are unified by IDH mutations. Other genomic features including ATRX as well as copy number status of chromosomes 1p and 19q serve to molecularly segregate this tumor group. Despite the exponential gains in molecular profiling and understanding of LGG, survival rates and treatment options have stagnated over the past few decades with few advancements. In this study, we utilize low grade glioma RNA-seq data from the Cancer Genome Atlas (TCGA-LGG) and tandem mass-spectrometry on an in-house cohort of 54 formalin-fixed paraffin-embedded (FFPE) LGG specimens to investigate the transcriptomic and proteomic profiles across the three molecular subtypes of LGG (Type I: IDH mutant – 1p19q co-deleted, Type II: IDH mutant – 1p19q retained, Type III: IDH wildtype). Within the 3 LGG subtypes, gene expression was driven heavily by IDH mutation and 1p19q co-deletion. In concordance with RNA expression, we were able to identify decreased expressions of proteins coded in 1p19q in Type I LGG. Further proteomic analysis identified 54 subtype specific proteins that were used to classify the three subtypes using a multinomial regression model (AUC = 0.911). Type I LGG were found to have increased protein expression of several metabolic proteins while Type III LGG were found to have increased immune infiltration and inflammation related proteins. Here we present the largest proteomic cohort of LGG and show that proteomic profiles can be successfully analyzed from FFPE tissues. We uncover previously known and novel subtype specific markers that are useful for the proteomic classification of LGG subtypes.

Deephos: Predicted spectral database search for TMT-labeled phosphopeptides and its false discovery rate estimation

MOTIVATION

Tandem mass tag (TMT)-based tandem mass spectrometry (MS/MS) has become the method of choice for the quantification of post-translational modifications in complex mixtures. Many cancer proteogenomic studies have highlighted the importance of large-scale phosphopeptide quantification coupled with TMT labeling. Herein, we propose a predicted Spectral DataBase (pSDB) search strategy called Deephos that can improve both sensitivity and specificity in identifying MS/MS spectra of TMT-labeled phosphopeptides.

RESULTS

With deep learning-based fragment ion prediction, we compiled a pSDB of TMT-labeled phosphopeptides generated from ∼8,000 human phosphoproteins annotated in UniProt. Deep learning could successfully recognize the fragmentation patterns altered by both TMT labeling and phosphorylation. In addition, we discuss the decoy spectra for false discovery rate (FDR) estimation in the pSDB search. We show that FDR could be inaccurately estimated by the existing decoy spectra generation methods and propose an innovative method to generate decoy spectra for more accurate FDR estimation. The utilities of Deephos were demonstrated in multi-stage analyses (coupled with database searches) of glioblastoma, acute myeloid leukemia, and breast cancer phosphoproteomes.

AVAILABILITY

Deephos pSDB and the search software are available at https://github.com/seungjinna/deephos.

TFCP2, a binding protein of ATF3, promotes the progression of glioma by activating the synthesis of serine

Glioma is one of the most common malignancies. De novo serine synthesis promotes glioma progression and therapeutic resistance. Therefore, clarifying the regulatory mechanism of serine synthesis is of great significance for glioma therapy. In this study, we found that the expression of TFCP2 was upregulated in glioma and that TFCP2 promoted glioma cell growth and sphere formation. Knockdown of TFCP2 expression inhibited glioma cell growth, sphere formation and tumorigenicity in nude mice. In terms of its molecular mechanism, TFCP2 was found to interact with ATF3 to cooperatively regulate the de novo synthesis of serine. Knockdown of TFCP2 expression significantly inhibited the binding of ATF3 to the promoter of PHGDH (a rate-limiting enzyme in the serine synthesis process). In conclusion, our studies proved that TFCP2 jointly regulates the de novo synthesis of serine through interaction with ATF3, thus promoting glioma progression. This study suggests that TFCP2 is a potential target for glioma therapy.

Identification of a novel glycolysis-related gene signature for predicting the survival of patients with colon adenocarcinoma

BACKGROUND

The most frequent histologic subtype of colon cancer is colon adenocarcinoma (COAD). A major problem in the diagnosis and treatment of COAD is that there is lack of new biomarkers to indicate the early stage of COAD. Compared with normally differentiated cells, the glycolytic pathways of tumor cells are more active, thus making them more adaptable to the hypoxic environment of solid tumors, which is known as the Warburg effect. Therefore, establishing a diagnostic and prognostic model based on glycolysis-related genes may provide guidance for the precise treatment of colon cancer.

METHODS

The Cancer Genome Atlas (TCGA) mRNA data were used to identify differentially expressed genes (DEGs). The glycolysis-related DEGs were identified using Gene Set Enrichment Analysis (GSEA) with HALLMARK gene sets. Combined with clinical data, we identified prognostic genes in glycolysis-related DEGs based on Cox regression analysis. Four glycolysis-related genes were identified and a predictive model was developed using univariate and multivariate Cox regression analysis. cBioPortal investigated the chromosomal variations of these genes. Following that, survival analysis and receiver operating characteristic (ROC) curve validation were carried out. The correlations between glycolysis-related gene signatures and molecular features and cancer subtypes were analyzed.

RESULTS

We discovered five genes (SPAG4, P4HA1, STC2, ENO3, and GPC1) that are associated with COAD patients' prognosis. The risk score was more accurate in predicting prognosis when based on this gene signature in COAD patients. Furthermore, multivariate Cox regression analysis demonstrated that the glycolysis-related gene signature's predictive value was independent of clinical variables.

CONCLUSION

We identified a glycolysis-related five-gene signature and developed a risk staging model potentially valuable for the clinical management of COAD patients. Our results suggest that prognostic markers based on glycolysis-related genes may be a reliable predictive tool for the prognosis of COAD patients.

It’s Getting Complicated—A Fresh Look at p53-MDM2-ARF Triangle in Tumorigenesis and Cancer Therapy

Anti-tumorigenic mechanisms mediated by the tumor suppressor p53, upon oncogenic stresses, are our bodies’ greatest weapons to battle against cancer onset and development. Consequently, factors that possess significant p53-regulating activities have been subjects of serious interest from the cancer research community. Among them, MDM2 and ARF are considered the most influential p53 regulators due to their abilities to inhibit and activate p53 functions, respectively. MDM2 inhibits p53 by promoting ubiquitination and proteasome-mediated degradation of p53, while ARF activates p53 by physically interacting with MDM2 to block its access to p53. This conventional understanding of p53-MDM2-ARF functional triangle have guided the direction of p53 research, as well as the development of p53-based therapeutic strategies for the last 30 years. Our increasing knowledge of this triangle during this time, especially through identification of p53-independent functions of MDM2 and ARF, have uncovered many under-appreciated molecular mechanisms connecting these three proteins. Through recognizing both antagonizing and synergizing relationships among them, our consideration for harnessing these relationships to develop effective cancer therapies needs an update accordingly. In this review, we will re-visit the conventional wisdom regarding p53-MDM2-ARF tumor-regulating mechanisms, highlight impactful studies contributing to the modern look of their relationships, and summarize ongoing efforts to target this pathway for effective cancer treatments. A refreshed appreciation of p53-MDM2-ARF network can bring innovative approaches to develop new generations of genetically-informed and clinically-effective cancer therapies.

Visualization of tumor heterogeneity and prediction of isocitrate dehydrogenase mutation status for human gliomas using multiparametric physiologic and metabolic MRI

This study aimed to differentiate isocitrate dehydrogenase (IDH) mutation status with the voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and to discover biological underpinnings of the clusters. A total of 69 patients with treatment-naïve diffuse glioma were scanned with pH-sensitive amine chemical exchange saturation transfer MRI, diffusion-weighted imaging, fluid-attenuated inversion recovery, and contrast-enhanced T1-weighted imaging at 3 T. An unsupervised two-level clustering approach was used for feature extraction from acquired images. The logarithmic ratio of the labels in each class within tumor regions was applied to a support vector machine to differentiate IDH status. The highest performance to predict IDH mutation status was found for 10-class clustering, with a mean area under the curve, accuracy, sensitivity, and specificity of 0.94, 0.91, 0.90, and 0.91, respectively. Targeted biopsies revealed that the tissues with labels 7-10 showed high expression levels of hypoxia-inducible factor 1-alpha, glucose transporter 3, and hexokinase 2, which are typical of IDH wild-type glioma, whereas those with labels 1 showed low expression of these proteins. In conclusion, A machine learning model successfully predicted the IDH mutation status of gliomas, and the resulting clusters properly reflected the metabolic status of the tumors.

Unveiling a Ghost Proteome in the Glioblastoma Non-Coding RNAs

Glioblastoma is the most common brain cancer in adults. Nevertheless, the median survival time is 15 months, if treated with at least a near total resection and followed by radiotherapy in association with temozolomide. In glioblastoma (GBM), variations of non-coding ribonucleic acid (ncRNA) expression have been demonstrated in tumor processes, especially in the regulation of major signaling pathways. Moreover, many ncRNAs present in their sequences an Open Reading Frame (ORF) allowing their translations into proteins, so-called alternative proteins (AltProt) and constituting the “ghost proteome.” This neglected world in GBM has been shown to be implicated in protein–protein interaction (PPI) with reference proteins (RefProt) reflecting involvement in signaling pathways linked to cellular mobility and transfer RNA regulation. More recently, clinical studies have revealed that AltProt is also involved in the patient’s survival and bad prognosis. We thus propose to review the ncRNAs involved in GBM and highlight their function in the disease.

Leveraging the CSF proteome toward minimally-invasive diagnostics surveillance of brain malignancies

Background

Diagnosis and prognostication of intra-axial brain tumors hinges on invasive brain sampling, which carries risk of morbidity. Minimally-invasive sampling of proximal fluids, also known as liquid biopsy, can mitigate this risk. Our objective was to identify diagnostic and prognostic cerebrospinal fluid (CSF) proteomic signatures in glioblastoma (GBM), brain metastases (BM), and primary central nervous system lymphoma (CNSL).

Methods

CSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics. Proteomic signatures were identified using machine learning classifiers and survival analyses.

Results

Using 30 µL CSF volumes, we recovered 755 unique proteins across 73 samples. Proteomic-based classifiers identified malignancy with area under the receiver operating characteristic (AUROC) of 0.94 and distinguished between tumor entities with AUROC ≥0.95. More clinically relevant triplex classifiers, comprised of just three proteins, distinguished between tumor entities with AUROC of 0.75-0.89. Novel biomarkers were identified, including GAP43, TFF3 and CACNA2D2, and characterized using single cell RNA sequencing. Survival analyses validated previously implicated prognostic signatures, including blood-brain barrier disruption.

Conclusions

Reliable classification of intra-axial malignancies using low CSF volumes is feasible, allowing for longitudinal tumor surveillance.

Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine

Simple Summary

Radiomics and radiogenomics offer new insight into high-grade glioma biology, as well as into glioma behavior in response to standard therapies. In this article, we provide neuro-oncology, neuropathology, and computational perspectives on the role of radiomics in providing more accurate diagnoses, prognostication, and surveillance of patients with high-grade glioma, and on the potential application of radiomics in clinical practice, with the overarching goal of advancing precision medicine for optimal patient care.

Abstract

Machine learning (ML) integrated with medical imaging has introduced new perspectives in precision diagnostics of high-grade gliomas, through radiomics and radiogenomics. This has raised hopes for characterizing noninvasive and in vivo biomarkers for prediction of patient survival, tumor recurrence, and genomics and therefore encouraging treatments tailored to individualized needs. Characterization of tumor infiltration based on pre-operative multi-parametric magnetic resonance imaging (MP-MRI) scans may allow prediction of the loci of future tumor recurrence and thereby aid in planning the course of treatment for the patients, such as optimizing the extent of resection and the dose and target area of radiation. Imaging signatures of tumor genomics can help in identifying the patients who benefit from certain targeted therapies. Specifying molecular properties of gliomas and prediction of their changes over time and with treatment would allow optimization of treatment. In this article, we provide neuro-oncology, neuropathology, and computational perspectives on the promise of radiomics and radiogenomics for allowing personalized treatments of patients with gliomas and discuss the challenges and limitations of these methods in multi-institutional clinical trials and suggestions to mitigate the issues and the future directions.

Pharmaco-proteogenomic profiling of pediatric diffuse midline glioma to inform future treatment strategies

Diffuse midline glioma (DMG) is a deadly pediatric and adolescent central nervous system (CNS) tumor localized along the midline structures of the brain atop the spinal cord. With a median overall survival (OS) of just 9–11-months, DMG is characterized by global hypomethylation of histone H3 at lysine 27 (H3K27me3), driven by recurring somatic mutations in H3 genes including, HIST1H3B/C (H3.1K27M) or H3F3A (H3.3K27M), or through overexpression of EZHIP in patients harboring wildtype H3. The recent World Health Organization’s 5th Classification of CNS Tumors now designates DMG as, ‘H3 K27-altered’, suggesting that global H3K27me3 hypomethylation is a ubiquitous feature of DMG and drives devastating transcriptional programs for which there are no treatments. H3-alterations co-segregate with various other somatic driver mutations, highlighting the high-level of intertumoral heterogeneity of DMG. Furthermore, DMG is also characterized by very high-level intratumoral diversity with tumors harboring multiple subclones within each primary tumor. Each subclone contains their own combinations of driver and passenger lesions that continually evolve, making precision-based medicine challenging to successful execute. Whilst the intertumoral heterogeneity of DMG has been extensively investigated, this is yet to translate to an increase in patient survival. Conversely, our understanding of the non-genomic factors that drive the rapid growth and fatal nature of DMG, including endogenous and exogenous microenvironmental influences, neurological cues, and the posttranscriptional and posttranslational architecture of DMG remains enigmatic or at best, immature. However, these factors are likely to play a significant role in the complex biological sequelae that drives the disease. Here we summarize the heterogeneity of DMG and emphasize how analysis of the posttranslational architecture may improve treatment paradigms. We describe factors that contribute to treatment response and disease progression, as well as highlight the potential for pharmaco-proteogenomics (i.e., the integration of genomics, proteomics and pharmacology) in the management of this uniformly fatal cancer.

The Big Picture of Glioblastoma Malignancy: A Meta-Analysis of Glioblastoma Proteomics to Identify Altered Biological Pathways

Glioblastoma is a highly malignant cancer with no effective treatment. It is vital to elucidate the mechanisms which drive glioblastoma in order to identify therapeutic targets. The differences in protein expression between glioblastoma, grade I-III glioma, and normal brain tissue reflect the functional alterations driving malignancy. However, proteomic analysis of glioblastoma has been hampered by the heterogeneity of glioblastoma and the variety of methodology used in its study. To reduce these inconsistencies, we performed a meta-analysis of the literature published since 2015, including 14 datasets from eight papers comparing the whole proteome of glioblastoma to normal brain or grade I-III glioma. We found that 154 proteins were commonly upregulated and 116 proteins were commonly downregulated in glioblastoma compared to normal brain. Meanwhile, 240 proteins were commonly upregulated and 125 proteins were commonly downregulated in glioblastoma compared to grade I-III glioma. Functional enrichment analysis revealed upregulation of proteins involved in mRNA splicing and the immune system and downregulation of proteins involved in synaptic signaling and glucose and glutamine metabolism. The identification of these altered biological pathways provides a basis for deeper investigation in the pursuit of an effective treatment for glioblastoma.

Mechanisms of imipridones in targeting mitochondrial metabolism in cancer cells

ONC201 is the first member of the imipridone family of anticancer drugs to enter the clinic for the treatment of diverse solid and hematologic cancers. A subset of pediatric and adult patients with highly aggressive brain tumors has shown remarkable clinical responses to ONC201, and recently, the more potent derivative ONC206 entered clinical trials as a single agent for the treatment of central nervous system (CNS) cancers. Despite the emerging clinical interest in the utility of imipridones, their exact molecular mechanisms are not fully described. In fact, the existing literature points to multiple pathways (e.g. tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) signaling, dopamine receptor antagonism, and mitochondrial metabolism) as putative drug targets. We have performed a comprehensive literature review and highlighted mitochondrial metabolism as the major target of imipridones. In support of this, we performed a meta-analysis of an ONC201 screen across 539 human cancer cell lines and showed that the mitochondrial caseinolytic protease proteolytic subunit (ClpP) is the most significant predictive biomarker of response to treatment. Herein, we summarize the main findings on the anticancer mechanisms of this potent class of drugs, provide clarity on their role, and identify clinically relevant predictive biomarkers of response.

Molecularly Targeted Clinical Trials

Glioblastoma remains incurable despite advances in surgery, radiation, and chemotherapy, underscoring the need for new therapies. The genetic heterogenicity, presence of redundant molecular pathways, and the blood-brain barrier have limited the applicability of molecularly targeted agents. The therapeutic benefit seen with a small subset of patients suggests, however, that patient selection is critical. Recent investigations show that molecularly targeted synthetic lethality is a promising complementary approach. The article provides an overview of the challenges of molecularly targeted therapy in adults with glioblastoma, including current trials and future therapeutic directions.

Reuse of Molecules for Glioblastoma Therapy

Glioblastoma multiforme (GBM) is a highly malignant primary brain tumor. The current standard of care for GBM is the Stupp protocol which includes surgical resection, followed by radiotherapy concomitant with the DNA alkylator temozolomide; however, survival under this treatment regimen is an abysmal 12-18 months. New and emerging treatments include the application of a physical device, non-invasive 'tumor treating fields' (TTFs), including its concomitant use with standard of care; and varied vaccines and immunotherapeutics being trialed. Some of these approaches have extended life by a few months over standard of care, but in some cases are only available for a minority of GBM patients. Extensive activity is also underway to repurpose and reposition therapeutics for GBM, either alone or in combination with the standard of care. In this review, we present select molecules that target different pathways and are at various stages of clinical translation as case studies to illustrate the rationale for their repurposing-repositioning and potential clinical use.

Short review of SEC, a potential dexamethasone-sparing regimen for glioblastoma: Spironolactone, ecallantide, clotrimazole

This paper presents a short review of data supporting a dexamethasone sparing regimen, SEC, to reduce glioblastoma related brain edema. The conclusion of the reviewed data is that the rationale and risk/benefit ratio favors a pilot study to determine if the three drug regimen of SEC can reduce need for corticosteroid use during the course of glioblastoma. Details of how selected pathophysiological aspects of brain edema occurring during the course of glioblastoma and its treatment intersect with the established action of the three old drugs of SEC indicate that they can be repurposed to reduce that edema. Current first-line treatment of this edema is dexamethasone or related corticosteroids. There are multiple negative prognostic implications of both the edema itself and of dexamethasone, prime among them shortened survival, making a dexamethasone sparing regimen highly desirable. SEC uses spironolactone, an antihypertensive potassium-sparing diuretic acting by mineralocorticoid receptor inhibition, ecallantide acting to inhibit kallikrein activation marketed to treat hereditary angioedema, and clotrimazole, an old antifungal drug that inhibits intermediate conductance Ca++ activated K+ channel (KCa3.1). These three old drugs are well known to most clinicians, have a well-tolerated safety history, and have a robust preclinical database showing their potential to reduce the specific edema of glioblastoma. Additionally, these three drugs were chosen by virtue of each having preclinical evidence of glioblastoma growth and/or migration inhibition independent of their edema reduction action. A clinical study of SEC is being planned.

Association of plasma cell-free DNA with survival in patients with IDH wild-type glioblastoma

BACKGROUND

We aimed to determine whether plasma cell-free DNA (cfDNA) concentration is associated with survival in patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM).

METHODS

Pre-operative and post-chemoradiotherapy blood samples were prospectively collected from patients with newly diagnosed IDH wild-type GBM. Patients underwent surgical resection or biopsy and received adjuvant radiotherapy with concomitant temozolomide. Cell-free DNA (cfDNA) was isolated from plasma and quantified using SYBR Green-based q polymerase chain reaction (qPCR).

RESULTS

Sixty-two patients were enrolled and categorized into high vs. low cfDNA groups relative to the pre-operative median value (25.2 ng/mL, range 5.7-153.0 ng/mL). High pre-operative cfDNA concentration was associated with inferior PFS (median progression-free survival (PFS), 3.4 vs. 7.7 months; log-rank P = .004; hazard ratio [HR], 2.19; 95% CI, 1.26-3.81) and overall survival (OS) (median OS, 8.0 vs. 13.9 months; log-rank P = .01; HR, 2.43; 95% CI, 1.19-4.95). After adjusting for risk factors, including O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, pre-operative cfDNA remained independently associated with PFS (HR, 2.70; 95% CI, 1.50-4.83; P = .001) and OS (HR, 2.65; 95% CI, 1.25-5.59; P = .01). Post-hoc analysis of change in cfDNA post-chemoradiotherapy compared to pre-surgery (n = 24) showed increasing cfDNA concentration was associated with worse PFS (median, 2.7 vs. 6.0 months; log-rank P = .003; HR, 4.92; 95% CI, 1.53-15.84) and OS (median, 3.9 vs. 19.4 months; log-rank P < .001; HR, 7.77; 95% CI, 2.17-27.76).

CONCLUSIONS

cfDNA concentration is a promising prognostic biomarker for patients with IDH wild-type GBM. Plasma cfDNA can be obtained noninvasively and may enable more accurate estimates of survival and effective clinical trial stratification.

Co-expression of cancer driver genes: IDH-wildtype glioblastoma-derived tumorspheres

BACKGROUND

Driver genes of GBM may be crucial for the onset of isocitrate dehydrogenase (IDH)-wildtype (WT) glioblastoma (GBM). However, it is still unknown whether the genes are expressed in the identical cluster of cells. Here, we have examined the gene expression patterns of GBM tissues and patient-derived tumorspheres (TSs) and aimed to find a progression-related gene.

METHODS

We retrospectively collected primary IDH-WT GBM tissue samples (n = 58) and tumor-free cortical tissue samples (control, n = 20). TSs are isolated from the IDH-WT GBM tissue with B27 neurobasal medium. Associations among the driver genes were explored in the bulk tissue, bulk cell, and a single cell RNAsequencing techniques (scRNAseq) considering the alteration status of TP53, PTEN, EGFR, and TERT promoter as well as MGMT promoter methylation. Transcriptomic perturbation by temozolomide (TMZ) was examined in the two TSs.

RESULTS

We comprehensively compared the gene expression of the known driver genes as well as MGMT, PTPRZ1, or IDH1. Bulk RNAseq databases of the primary GBM tissue revealed a significant association between TERT and TP53 (p < 0.001, R = 0.28) and its association increased in the recurrent tumor (p  < 0.001, R = 0.86). TSs reflected the tissue-level patterns of association between the two genes (p < 0.01, R = 0.59, n = 20). A scRNAseq data of a TS revealed the TERT and TP53 expressing cells are in a same single cell cluster. The driver-enriched cluster dominantly expressed the glioma-associated long noncoding RNAs. Most of the driver-associated genes were downregulated after TMZ except IGFBP5.

CONCLUSIONS

GBM tissue level expression patterns of EGFR, TERT, PTEN, IDH1, PTPRZ1, and MGMT are observed in the GBM TSs. The driver gene-associated cluster of the GBM single cells were enriched with the glioma-associated long noncoding RNAs.