Proteogenomics of diffuse gliomas reveal molecular subtypes associated with specific therapeutic targets and immune-evasion mechanisms

IDH mutation, glioma immunogenicity, and therapeutic challenge of primary mismatch repair deficient IDH-mutant astrocytoma PMMRDIA: a systematic review

In 2021, Suwala et al. described Primary Mismatch Repair Deficient IDH-mutant Astrocytoma (PMMRDIA) as a distinct group of gliomas. In unsupervised clustering, PMMRDIA forms distinct cluster, separate from other IDH-mutant gliomas, including IDH-mutant gliomas with secondary mismatch repair (MMR) deficiency. In the published cohort, three patients received treatment with an immune checkpoint blocker (ICB), yet none exhibited a response, which aligns with existing knowledge about the decreased immunogenicity of IDH-mutant gliomas in comparison to IDH-wildtype. In the case of PMMRDIA, the inherent resistance to the standard-of-care temozolomide caused by MMR deficiency is an additional challenge. It is known that a gain-of-function mutation of IDH1/2 genes produces the oncometabolite R-2-hydroxyglutarate (R-2-HG), which increases DNA and histone methylation contributing to the characteristic glioma-associated CpG island methylator phenotype (G-CIMP). While other factors could be involved in remodeling the tumor microenvironment (TME) of IDH-mutant gliomas, this systematic review emphasizes the role of R-2-HG and the subsequent G-CIMP in immune suppression. This highlights a potential actionable pathway to enhance the response of ICB, which might be relevant for addressing the unmet therapeutic challenge of PMMRDIA.

Advances in cancer diagnosis and therapy by alginate-based multifunctional hydrogels: A review

The field of oncology has been changed by the application of hydrogels. These 3D polymeric networks have demonstrated significant promise in the treatment of cancer and can boost the efficacy of conventional therapeutics including chemotherapy and immunotherapy. Noteworthy, the development of biocompatible and effective hydrogels has been of interest. In this case, alginate as a biopolymer and carbohydrate polymer has been used to modify or synthesis multifunctional nanoparticles for the treatment of human diseases, especially cancer. Therefore, highlighting the function of alginate in the development of hydrogels in cancer therapy can provide new insights for improving outcome and survival rate of patients. Alginate hydrogels improve the specific and selective delivery of cargo and therefore, they reduce the systemic toxicity of drugs, while they enhance anti-cancer activity. Alginate hydrogels protect the genes against degradation by enzymes and increase blood circulation time. The alginate hydrogels can respond to the specific stimuli in the tumor microenvironment including pH, redox and light to improve the site-specific release of cargo. The nanoparticles can be incorporated in the structure of alginate hydrogels to augment their anti-cancer activity. In addition, alginate hydrogels can accelerate immunotherapy and phototherapy through delivery of immunomodulators and photosensitizers, respectively.

Identifying and validating necroptosis-associated features to predict clinical outcome and immunotherapy response in patients with glioblastoma

BACKGROUND

Necroptosis is a type of programmed cell death involved in the pathogenesis of cancers. This work developed a prognostic glioblastoma (GBM) model based on necroptosis-related genes.

METHODS

RNA-Seq data were collected from the TCGA database. The "WGCNA" method was used to identify co-expression modules, based on which GO and KEGG analyses were conducted. A protein-protein interaction (PPI) network was compiled. The number of key prognostic genes was reduced applying COX regression and least absolute shrinkage and selection operator (LASSO) analysis to build a RiskScore model. Differences in immune microenvironments were assessed using CIBERSORT, ESTIMATE, MCP-count, and TIMER databases. The potential impact of key prognostic genes on GBM was validated by cellular experiments.

RESULTS

GBM patients in the higher necroptosis score group had higher immune scores and worse survival. The Brown module, which was closely related to the necroptosis score, was considered as a key gene module. Three key genes (GZMB, PLAUR, SOCS3) were obtained by performing regression analysis on the five clusters. The RiskScore model was significantly, positively, correlated with necroptosis score. Low-risk patients could benefit from immunotherapy, while high-risk patients may be more suitable to take multiple chemotherapy drugs. The nomogram showed strong performance in survival prediction. GZMB, PLAUR, and SOCS3 played key roles in GBM development. Among them, high-expressed GZMB was related to the invasive and migratory abilities of GBM cells.

CONCLUSIONS

A genetic signature associated with necroptosis was developed, and we constructed a RiskScore model to provide reference for predicting clinical outcomes and immunotherapy responses of patients with GBM.

starTracer is an accelerated approach for precise marker gene identification in single-cell RNA-Seq analysis

Revealing the heterogeneity among tissues is the greatest advantage of single-cell-sequencing. Marker genes not only act as the key to correctly identify cell types, but also the bio-markers for cell-status under certain experimental imputations. Current analysis methods such as Seurat and Monocle employ algorithms which compares one cluster to all the rest and select markers according to statistical tests. This pattern brings redundant calculations and thus, results in low calculation efficiency, specificity and accuracy. To address these issues, we introduce starTracer, a novel algorithm designed to enhance the efficiency, specificity and accuracy of marker gene identification in single-cell RNA-seq data analysis. starTracer operates as an independent pipeline, which exhibits great flexibility by accepting multiple input file types. The primary output is a marker matrix, where genes are sorted by the potential to function as markers, with those exhibiting the greatest potential positioned at the top. The speed improvement ranges by 2 ~ 3 orders of magnitude compared to Seurat, as observed across three independent datasets with lower false positive rate as observed in a simulated testing dataset with ground-truth. It's worth noting that starTracer exhibits increasing speed improvement with larger data volumes. It also excels in identifying markers in smaller clusters. These advantages solidify starTracer as an important tool for single-cell RNA-seq data, merging robust accuracy with exceptional speed.

Increased matrix stiffness in pituitary neuroendocrine tumors invading the cavernous sinus is activated by TAFs: focus on the mechanical signatures

PURPOSE

Pituitary neuroendocrine tumors (PitNETs) with invasion of the cavernous sinus (CS) are particularly challenging to treat. Tumor associated fibroblasts (TAFs) are recognized for their pivotal role in reprogramming extracellular matrix (ECM). Herein, we aimed to explore the potential involvement of TAFs in ECM reprogramming and elucidate the underlying mechanism involved.

METHODS

We applied dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to measure tumor vessel permeability and applied atomic force microscopy (AFM) to measure the matrix stiffness of PitNETs located in both CS and sella turcica (ST). Western blotting, immunofluorescence, immunohistochemistry, and quantitative RT-PCR were utilized to analyze the ECM components. Proteomic biochemical analysis was utilized to uncover potential mechanisms governing ECM dynamics.

RESULTS

We found that PitNETs in the CS were stiffer than those in the ST. Increased ECM stiffness within the CS facilitated the acquisition of stem-like properties, enhanced proliferation, and induced epithelial-to-mesenchymal transition (EMT) of GH3 cells. Furthermore, the expression levels of lysyl oxidase (LOX), matrix metallopeptidase 2 (MMP2) and MMP9 in pituitary adenoma cells increased in the stiffer matrix. Proteomic analysis suggested TAFs were activated in the CS area and contributed enhanced matrix stiffness by secreting Col-1 and Col-3. Furthermore, mTOR pathway was activated under higher matrix stiffness and the migration and invasion of GH3 cells be repressed by mTOR inhibitor.

CONCLUSION

These findings demonstrated that activated TAFs contributed to stiffer matrix and increased ECM stiffness stimulating mTOR pathway in pituitary tumor cells. Our study indicated that mTOR inhibitor was a promising treatment strategy from the standpoint of PitNET biomechanical properties.

Proteogenomic insights into the biology and treatment of pan-melanoma

Melanoma is one of the most prevalent skin cancers, with high metastatic rates and poor prognosis. Understanding its molecular pathogenesis is crucial for improving its diagnosis and treatment. Integrated analysis of multi-omics data from 207 treatment-naïve melanomas (primary-cutaneous-melanomas (CM, n = 28), primary-acral-melanomas (AM, n = 81), primary-mucosal-melanomas (MM, n = 28), metastatic-melanomas (n = 27), and nevi (n = 43)) provides insights into melanoma biology. Multivariate analysis reveals that PRKDC amplification is a prognostic molecule for melanomas. Further proteogenomic analysis combined with functional experiments reveals that the cis-effect of PRKDC amplification may lead to tumor proliferation through the activation of DNA repair and folate metabolism pathways. Proteome-based stratification of primary melanomas defines three prognosis-related subtypes, namely, the ECM subtype, angiogenesis subtype (with a high metastasis rate), and cell proliferation subtype, which provides an essential framework for the utilization of specific targeted therapies for particular melanoma subtypes. The immune classification identifies three immune subtypes. Further analysis combined with an independent anti-PD-1 treatment cohort reveals that upregulation of the MAPK7-NFKB signaling pathway may facilitate T-cell recruitment and increase the sensitivity of patients to immunotherapy. In contrast, PRKDC may reduce the sensitivity of melanoma patients to immunotherapy by promoting DNA repair in melanoma cells. These results emphasize the clinical value of multi-omics data and have the potential to improve the understanding of melanoma treatment.

Evaluation of Microvascular Density in Glioblastomas in Relation to p53 and Ki67 Immunoexpression

Glioblastoma is the most aggressive tumor in the central nervous system, with a survival rate of less than 15 months despite multimodal therapy. Tumor recurrence frequently occurs after removal. Tumoral angiogenesis, the formation of neovessels, has a positive impact on tumor progression and invasion, although there are controversial results in the specialized literature regarding its impact on survival. This study aims to correlate the immunoexpression of angiogenesis markers (CD34, CD105) with the proliferation index Ki67 and p53 in primary and secondary glioblastomas. This retrospective study included 54 patients diagnosed with glioblastoma at the Pathology Department of County Emergency Clinical Hospital Târgu Mureș. Microvascular density was determined using CD34 and CD105 antibodies, and the results were correlated with the immunoexpression of p53, IDH1, ATRX and Ki67. The number of neoformed blood vessels varied among cases, characterized by different shapes and calibers, with endothelial cells showing modified morphology and moderate to marked pleomorphism. Neovessels with a glomeruloid aspect, associated with intense positivity for CD34 or CD105 in endothelial cells, were observed, characteristic of glioblastomas. Mean microvascular density values were higher for the CD34 marker in all cases, though there were no statistically significant differences compared to CD105. Mutant IDH1 and ATRX glioblastomas, wild-type p53 glioblastomas, and those with a Ki67 index above 20% showed a more abundant microvascular density, with statistical correlations not reaching significance. This study highlighted a variety of percentage intervals of microvascular density in primary and secondary glioblastomas using immunohistochemical markers CD34 and CD105, respectively, with no statistically significant correlation between evaluated microvascular density and p53 or Ki67.

Revolutionizing Glioblastoma Treatment: A Comprehensive Overview of Modern Therapeutic Approaches

Glioblastoma is the most common malignant primary brain tumor in the adult population, with an average survival of 12.1 to 14.6 months. The standard treatment, combining surgery, radiotherapy, and chemotherapy, is not as efficient as we would like. However, the current possibilities are no longer limited to the standard therapies due to rapid advancements in biotechnology. New methods enable a more precise approach by targeting individual cells and antigens to overcome cancer. For the treatment of glioblastoma, these are gamma knife therapy, proton beam therapy, tumor-treating fields, EGFR and VEGF inhibitors, multiple RTKs inhibitors, and PI3K pathway inhibitors. In addition, the increasing understanding of the role of the immune system in tumorigenesis and the ability to identify tumor-specific antigens helped to develop immunotherapies targeting GBM and immune cells, including CAR-T, CAR-NK cells, dendritic cells, and immune checkpoint inhibitors. Each of the described methods has its advantages and disadvantages and faces problems, such as the inefficient crossing of the blood-brain barrier, various neurological and systemic side effects, and the escape mechanism of the tumor. This work aims to present the current modern treatments of glioblastoma.

Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy

Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.

Drivers of heterogeneity in the glioblastoma immune microenvironment

Glioblastoma is the most common and aggressive primary brain tumor, characterized by a highly complex and heterogeneous tumor immune microenvironment (TIME). In this review, we discuss the impact of tumor-intrinsic and tumor-extrinsic drivers that contribute to heterogeneity in the adult glioblastoma TIME, focusing on four main factors: genetic drivers, sex, age, and standard of care therapy. We describe recent insights into how each of these factors affects key aspects ranging from TIME composition to therapy response, with an emphasis on the cross-talk between tumor and immune cells. Deciphering these local interactions is fundamental to understanding therapy resistance and identifying novel immunomodulatory strategies.

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics

BACKGROUND

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories.

RESULTS

Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics.

CONCLUSION

Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

Cyclers' kinases in cell division: from molecules to cancer therapy

Faithful eucaryotic cell division requires spatio-temporal orchestration of multiple sequential events. To ensure the dynamic nature of these molecular and morphological transitions, a swift modulation of key regulatory pathways is necessary. The molecular process that most certainly fits this description is phosphorylation, the post-translational modification provided by kinases, that is crucial to allowing the progression of the cell cycle and that culminates with the separation of two identical daughter cells. In detail, from the early stages of the interphase to the cytokinesis, each critical step of this process is tightly regulated by multiple families of kinases including the Cyclin-dependent kinases (CDKs), kinases of the Aurora, Polo, Wee1 families, and many others. While cell-cycle-related CDKs control the timing of the different phases, preventing replication machinery errors, the latter modulate the centrosome cycle and the spindle function, avoiding karyotypic abnormalities typical of chromosome instability. Such chromosomal abnormalities may result from replication stress (RS) and chromosome mis-segregation and are considered a hallmark of poor prognosis, therapeutic resistance, and metastasis in cancer patients. Here, we discuss recent advances in the understanding of how different families of kinases concur to govern cell cycle, preventing RS and mitotic infidelity. Additionally, considering the growing number of clinical trials targeting these molecules, we review to what extent and in which tumor context cell-cycle-related kinases inhibitors are worth exploiting as an effective therapeutic strategy.