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

MSFragger-DDA+ enhances peptide identification sensitivity with full isolation window search

Liquid chromatography-mass spectrometry based proteomics, particularly in the bottom-up approach, relies on the digestion of proteins into peptides for subsequent separation and analysis. The most prevalent method for identifying peptides from data-dependent acquisition mass spectrometry data is database search. Traditional tools typically focus on identifying a single peptide per tandem mass spectrum, often neglecting the frequent occurrence of peptide co-fragmentations leading to chimeric spectra. Here, we introduce MSFragger-DDA+, a database search algorithm that enhances peptide identification by detecting co-fragmented peptides with high sensitivity and speed. Utilizing MSFragger's fragment ion indexing algorithm, MSFragger-DDA+ performs a comprehensive search within the full isolation window for each tandem mass spectrum, followed by robust feature detection, filtering, and rescoring procedures to refine search results. Evaluation against established tools across diverse datasets demonstrated that, integrated within the FragPipe computational platform, MSFragger-DDA+ significantly increases identification sensitivity while maintaining stringent false discovery rate control. It is also uniquely suited for wide-window acquisition data. MSFragger-DDA+ provides an efficient and accurate solution for peptide identification, enhancing the detection of low-abundance co-fragmented peptides. Coupled with the FragPipe platform, MSFragger-DDA+ enables more comprehensive and accurate analysis of proteomics data.

Contrast-enhanced ultrasound can differentiate the level of glioma infiltration and correlate it with biological behavior: a study based on local pathology

PURPOSE

The objective of this study is to assess the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) in determining the level of glioma infiltration and to investigate its correlation with pathological markers.

METHODS

A prospective study involving 16 adult glioma patients was conducted. Preoperative US-(Magnetic Resonance)MR fusion imaging was utilized for tumor infiltration localization, while CEUS was employed to assess hemodynamic alterations. Parameters such as peak intensity (PI), rise time (RT), time to peak (TTP), and area under the curve (AUC) were measured. Utilizing contralateral normal brain tissue as the reference standard. The Kruskal-Wallis H-test was conducted to compare CEUS and pathological parameters (significance level, p < 0.05; bonferroni correction) among tumor margins, infiltration zones, and normal tissues, as well as between low-grade glioma (LGG) and high-grade glioma (HGG) within the infiltration zone, based on whole slide pathological images analysis. Spearman correlation analysis was employed to determine the correlation coefficient between hemodynamics and pathology. Receiver operating characteristic (ROC) curves were drawn to evaluate the performance of CEUS in tumor classification.

RESULTS

From tumor margin to normal tissue, PI, AUC, Ki67, EGFR, and 1p/19q showed a significant decreasing trend, while TTP, IDH-1, and MGMT gradually increased. RT was lower at the tumor margin but did not show statistically significant differences. In the infiltration zones, there was a significant increase in parameters such as PI, normalized PI (Nor_PI), AUC, and Ki67 from LGG to HGG, while RT, Nor_RT, TTP, Nor_TTP, IDH-1, and MGMT significantly decreased. Nor_AUC and EGFR increased but were not significant, and 1p/19q decreased but was not significant. RT and Nor_TTP were independent risk factors for distinguishing between LGG and HGG in the infiltration zone, with a combined diagnostic efficacy ROC of 0.891. The sensitivity reached 96.64% and the specificity reached 82.35%. There was a significant correlation between hemodynamic indicators and pathological indicators. CEUS can effectively differentiate levels of infiltration zones, which correlates with their biological behavior, with RT + Nor_TTP showing particularly highest diagnostic efficacy.

CONCLUSION

These findings contribute to improving the accuracy of diagnosing infiltration zones and provide essential biological insights for subsequent treatments.

Tumour-wide RNA splicing aberrations generate actionable public neoantigens

T cell-based immunotherapies hold promise in treating cancer by leveraging the immune system's recognition of cancer-specific antigens1. However, their efficacy is limited in tumours with few somatic mutations and substantial intratumoural heterogeneity2-4. Here we introduce a previously uncharacterized class of tumour-wide public neoantigens originating from RNA splicing aberrations in diverse cancer types. We identified T cell receptor clones capable of recognizing and targeting neoantigens derived from aberrant splicing in GNAS and RPL22. In cases with multi-site biopsies, we detected the tumour-wide expression of the GNAS neojunction in glioma, mesothelioma, prostate cancer and liver cancer. These neoantigens are endogenously generated and presented by tumour cells under physiologic conditions and are sufficient to trigger cancer cell eradication by neoantigen-specific CD8+ T cells. Moreover, our study highlights a role for dysregulated splicing factor expression in specific cancer types, leading to recurrent patterns of neojunction upregulation. These findings establish a molecular basis for T cell-based immunotherapies addressing the challenges of intratumoural heterogeneity.

Overlap of Formalin-Fixed Paraffin-Embedded and Fresh-Frozen Matched Tissues for Proteomics and Phosphoproteomics

Many liquid chromatography-mass spectrometry (LC-MS) studies have compared formalin-fixed paraffin-embedded (FFPE) tissues with matched fresh-frozen (FF) tissues to examine the effect of preservation techniques on the proteome; however, few studies have included the phosphoproteome. A high degree of overlap and correlation between the two preservation techniques would demonstrate the importance of FFPE tissues as a valuable biomedical resource. Our aim was to quantitatively compare the proteome and phosphoproteome of matched FFPE and FF tissues using data-independent acquisition LC-MS. Four organs from three rats were cut in half to produce matched FFPE and FF tissue pairs. Excellent overlaps of 85-97% for the proteome and 82-98% for the phosphoproteome were observed, depending on the organ type, between the two preservation techniques. Most of the unique identifications were found in FF with less than 0.3% being unique to FFPE tissues. Strong agreement between FFPE and FF matched tissue pairs was observed with Pearson correlation coefficients of 0.93-0.97 and 0.79-0.87 for the proteome and phosphoproteome, respectively. Digestion efficiency was slightly higher in FFPE (92-94%) than in FF tissues (86-89%), and a search of a data subset for formaldehyde induced chemical modifications revealed that only 0.05% of precursors were unique to FFPE tissues. This suggests that with quality sample preparation methods it is not necessary to include formaldehyde induced chemical modifications when analyzing FFPE tissues. We attribute the lower number of identifications in FFPE tissues to inaccurate peptide quantitation, which resulted in a lower MS peptide load and tryptic peptide enrichment load. Our results demonstrate that both proteomic and phosphoproteomic analyses of FFPE and FF tissues are highly comparable and highlight the suitability of FFPE tissues for both proteomic and phosphoproteomic analysis.

Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy

Gliomas exhibit high heterogeneity and poor prognosis. Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. In this study, we perform proteomic profiling of gliomas using 343 formalin-fixed and paraffin-embedded tumor samples and 53 normal-appearing brain samples from 188 patients, integrating these data with genomic panel information and clinical outcomes. The proteomic analysis uncovers two distinct subgroups: Subgroup 1, the metabolic neural subgroup, enriched in metabolic enzymes and neurotransmitter receptor proteins, and Subgroup 2, the immune subgroup, marked by upregulation of immune and inflammatory proteins. These proteomic subgroups show significant differences in prognosis, tumorigenesis, microenvironment dysregulation, and potential therapeutics, highlighting the critical roles of metabolic and immune processes in glioma biology and patient outcomes. Through a detailed investigation of metabolic pathways guided by our proteomic findings, dihydropyrimidine dehydrogenase (DPYD) and thymidine phosphorylase (TYMP) emerge as potential prognostic biomarkers linked to the reprogramming of nucleotide metabolism. Functional validation in patient-derived glioma stem cells and animal models highlights nucleotide metabolism as a promising therapy target for gliomas. This integrated multi-omics analysis introduces a proteomic classification for gliomas and identifies DPYD and TYMP as key metabolic biomarkers, offering insights into glioma pathogenesis and potential treatment strategies.

MSFragger-DDA+ Enhances Peptide Identification Sensitivity with Full Isolation Window Search

Liquid chromatography-mass spectrometry (LC-MS) based proteomics, particularly in the bottom-up approach, relies on the digestion of proteins into peptides for subsequent separation and analysis. The most prevalent method for identifying peptides from data-dependent acquisition (DDA) mass spectrometry data is database search. Traditional tools typically focus on identifying a single peptide per tandem mass spectrum (MS2), often neglecting the frequent occurrence of peptide co-fragmentations leading to chimeric spectra. Here, we introduce MSFragger-DDA+, a novel database search algorithm that enhances peptide identification by detecting co-fragmented peptides with high sensitivity and speed. Utilizing MSFragger's fragment ion indexing algorithm, MSFragger-DDA+ performs a comprehensive search within the full isolation window for each MS2, followed by robust feature detection, filtering, and rescoring procedures to refine search results. Evaluation against established tools across diverse datasets demonstrated that, integrated within the FragPipe computational platform, MSFragger-DDA+ significantly increases identification sensitivity while maintaining stringent false discovery rate (FDR) control. It is also uniquely suited for wide-window acquisition (WWA) data. MSFragger-DDA+ provides an efficient and accurate solution for peptide identification, enhancing the detection of low-abundance co-fragmented peptides. Coupled with the FragPipe platform, MSFragger-DDA+ enables more comprehensive and accurate analysis of proteomics data.

Glucose metabolism in glioma: an emerging sight with ncRNAs

Glioma is a primary brain tumor that grows quickly, has an unfavorable prognosis, and can spread intracerebrally. Glioma cells rely on glucose as the major energy source, and glycolysis plays a critical role in tumorigenesis and progression. Substrate utilization shifts throughout glioma progression to facilitate energy generation and biomass accumulation. This metabolic reprogramming promotes glioma cell proliferation and metastasis and ultimately decreases the efficacy of conventional treatments. Non-coding RNAs (ncRNAs) are involved in several glucose metabolism pathways during tumor initiation and progression. These RNAs influence cell viability and glucose metabolism by modulating the expression of key genes of the glycolytic pathway. They can directly or indirectly affect glycolysis in glioma cells by influencing the transcription and post-transcriptional regulation of oncogenes and suppressor genes. In this review, we discussed the role of ncRNAs in the metabolic reprogramming of glioma cells and tumor microenvironments and their abnormal expression in the glucometabolic pathway in glioma. In addition, we consolidated the existing theoretical knowledge to facilitate the use of this emerging class of biomarkers as biological indicators and potential therapeutic targets for glioma.

The ATPase Inhibitory Factor 1 (IF1) Contributes to the Warburg Effect and Is Regulated by Its Phosphorylation in S39 by a Protein Kinase A-like Activity

The relevant role played by the ATPase Inhibitory Factor 1 (IF1) as a physiological in vivo inhibitor of mitochondrial ATP synthase in cancer and non-cancer cells, and in the mitochondria of different mouse tissues, as assessed in different genetic loss- and gain-of-function models of IF1 has been extensively documented. In this review we summarize our findings and those of others that favor the implication of IF1 in metabolic reprogramming to an enhanced glycolytic phenotype, which is mediated by its binding and inhibition of the ATP synthase. Moreover, we emphasize that IF1 is phosphorylated in vivo in its S39 by the c-AMP-dependent PKA activity of mitochondria to render an inactive inhibitor that is unable to interact with the enzyme, thus triggering the activation of ATP synthase. Overall, we discuss and challenge the results that argue against the role of IF1 as in vivo inhibitor of mitochondrial ATP synthase and stress that IF1 cannot be regarded solely as a pro-oncogenic protein because in some prevalent carcinomas, it prevents metastatic disease.

METTL3-Mediated LINC00475 Alternative Splicing Promotes Glioma Progression by Inducing Mitochondrial Fission

Mitochondrial fission promotes glioma progression. The function and regulation mechanisms of lncRNAs in glioma mitochondrial fission are unclear. The expression of LINC00475 and its correlation with clinical parameters in glioma were analyzed using bioinformatics. Then, in vitro and in vivo assays were performed to explore the function of spliced variant LINC00475 (LINC00475-S) in gliomas. To explore the mechanisms, RNA-seq, MeRIP, RIP, pulldown-IP, dCas9-ALKBH5 editing system, LC/MS, and Western blotting were utilized. LINC00475 was confirmed to be overexpressed and with higher frequencies of AS events in gliomas compared to normal brain tissue and was associated with worse prognosis. In vitro and animal tumor formation experiments demonstrated that the effect of LINC00475-S on proliferation, metastasis, autophagy, and mitochondrial fission of glioma cells was significantly stronger than that of LINC00475. Mechanistically, METTL3 induced the generation of LINC00475-S by splicing LINC00475 through m6A modification and subsequently promotes mitochondrial fission in glioma cells by inhibiting the expression of MIF. Pull-down combined LC/MS and RIP assays identified that the m6A recognition protein HNRNPH1 bound to LINC00475 within GYR and GY domains and promoted LINC00475 splicing. METTL3 facilitated HNRNPH1 binding to LINC00475 in an m6A-dependent manner, thereby inducing generation of LINC00475-S. METTL3 facilitated HNRNPH1-mediated AS of LINC00475, which promoted glioma progression by inducing mitochondrial fission. Targeting AS of LINC00475 and m6A editing could serve as a therapeutic strategy against gliomas.

Tumor-wide RNA splicing aberrations generate immunogenic public neoantigens

T-cell-mediated immunotherapies are limited by the extent to which cancer-specific antigens are homogenously expressed throughout a tumor. We reasoned that recurrent splicing aberrations in cancer represent a potential source of tumor-wide and public neoantigens, and to test this possibility, we developed a novel pipeline for identifying neojunctions expressed uniformly within a tumor across diverse cancer types. Our analyses revealed multiple neojunctions that recur across patients and either exhibited intratumor heterogeneity or, in some cases, were tumor-wide. We identified CD8+ T-cell clones specific for neoantigens derived from tumor-wide and conserved neojunctions in GNAS and RPL22 , respectively. TCR-engineered CD8 + T-cells targeting these mutations conferred neoantigen-specific tumor cell eradication. Furthermore, we revealed that cancer-specific dysregulation in splicing factor expression leads to recurrent neojunction expression. Together, these data reveal that a subset of neojunctions are both intratumorally conserved and public, providing the molecular basis for novel T-cell-based immunotherapies that address intratumoral heterogeneity.