CD74 Correlated With Malignancies and Immune Microenvironment in Gliomas

MATES: a deep learning-based model for locus-specific quantification of transposable elements in single cell

Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either 'best-mapped' or 'random-mapped' locations and categorize them at the subfamily levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell omics datasets, MATES shows improved performance over existing methods, enhancing the accuracy of TE quantification and aiding in the identification of marker TEs for identified cell populations. This development facilitates the exploration of single-cell heterogeneity and gene regulation through the lens of TEs, offering an effective transposon quantification tool for the single-cell genomics community.

Slow-replicating leukemia cells represent a leukemia stem cell population with high cell-surface CD74 expression

Persistence of quiescent leukemia stem cells (LSCs) after treatment most likely contributes to chemotherapy resistance and poor prognosis of leukemia patients. Identification of this quiescent cell population would facilitate eradicating LSCs. Here, using a cell-tracing PKH26 (PKH) dye that can be equally distributed to daughter cells following cell division in vivo, we identify a label-retaining slow-cycling leukemia cell population from AML1-ETO9a (AE9a) leukemic mice. We find that, compared with cells not maintaining PKH-staining, a higher proportion of PKH-retaining cells are in G0 phase, and PKH-retaining cells exhibit increased colony formation ability and leukemia initiation potential. In addition, PKH-retaining cells possess high chemo-resistance and are more likely to be localized to the endosteal bone marrow region. Based on the transcriptional signature, HLA class II histocompatibility antigen gamma chain (Cd74) is highly expressed in PKH-retaining leukemia cells. Furthermore, cell surface CD74 was identified to be highly expressed in LSCs of AE9a mice and CD34+ human leukemia cells. Compared to Lin-CD74- leukemia cells, Lin-CD74+ leukemia cells of AE9a mice exhibit higher stemness properties. Collectively, our findings reveal that the identified slow-cycling leukemia cell population represents an LSC population, and CD74+ leukemia cells possess stemness properties, suggesting that CD74 is a candidate LSC surface marker.

Potential protumor function of CD74 in clear cell renal cell carcinoma

CD74 is a transmembrane protein that functions as a specialized chaperone of HLA class II and CD74 in tumor cells was suggested to be involved in cell proliferation in several kinds of malignant tumors. CD74 is also known to be expressed in macrophages, therefore, we investigated the CD74 expression in clear cell renal cell carcinoma (ccRCC). Immunohistochemistry of CD74 indicated that CD74 was expressed not only in cancer cells but also macrophages. CD74 was detected in surface membrane and cytoplasm of cancer cells in 92 of 94 cases (98%) and of 87 of 94 cases (93%). CD74 was expressed both in cancer cells and TAMs in 86 of 94 cases (91%). In vitro studies using cancer cell lines and monocyte-derived macrophages stimulated by anti-CD74 antibodies showed that CD74 signal accelerated cancer cell proliferation and macrophage activation. However, macrophage activation via CD74 signal did not influence macrophage-mediated cancer cell growth. RNA-sequence of macrophages stimulated by anti-CD74 antibodies indicated that CD74 signal was associated to inflammatory responses in macrophages. In conclusion, we examined the expression and functional significance of CD74 in ccRCC using tissue specimens and cell culture studies. The function of CD74 was suggested to be different in cancer cells and in macrophages, and further studies are necessary to clarify the functional significance of CD74 in ccRCC.

Single-cell transcriptome analysis deciphers the CD74-mediated immune evasion and tumour growth in lung squamous cell carcinoma with chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) contributes to the incidence and prognosis of lung cancer. The presence of COPD significantly increases the risk of lung squamous cell carcinoma (LSCC). COPD may promote an immunosuppressive microenvironment in LSCC by regulating the expression of immune-inhibitory factors in T cells, although the mechanisms remain unclear. In this study, we aimed to decipher the tumour microenvironment signature for LSCC with COPD at a single-cell level.

METHODS

We performed single-cell RNA sequencing on tumour tissues from LSCC with or without COPD, then investigated the features of the immune and tumour cells. We employed multiple techniques, including multispectral imaging, flow cytometry, tissue microarray analysis, survival analysis, co-culture systems and in vitro and in vivo treatment experiments, to validate the findings obtained from single-cell analyses.

RESULTS

LSCC with COPD showed increased proportions of tumour-associated macrophages (TAMs) and higher levels of CD8+ T cell exhaustion molecules, which contributed to an immunosuppressive microenvironment. Further analysis revealed a critical cluster of CD74+ tumour cells that expressed both epithelial and immune cell signatures, exhibited a stronger capacity for tumorigenesis and predicted worse overall survival. Notably, migration inhibitory factor (MIF) secreted by TAMs from LSCC with COPD may promote the activation of CD74. MIF-CD74 may interact with CD8+ T cells and impair their anti-tumour activity by regulating the PI3K-STAT3-programmed cell death-1 ligand 1 signalling pathway, facilitating tumour proliferation and immune evasion.

CONCLUSIONS

Our comprehensive picture of the tumour ecosystem in LSCC with COPD provides deeper insights into relevant immune evasion mechanisms and potential targets for immunotherapy.

HIGHLIGHT

Our results demonstrated higher proportions of tumour-associated macrophages (TAMs) and higher levels of exhaustion molecules in CD8+ T cells in the microenvironment of LSCC with COPD. CD74+tumour cells were associated with poor disease prognosis. Migration inhibitory factor (MIF)-CD74 may interact with CD8+ T cells and impair their anti-tumour activity by regulating the PI3K-STAT3-PD-L1 signalling pathway, facilitating immune evasion.

Therapeutic targets of formononetin for treating prostate cancer at the single-cell level

Prostate cancer is one of the serious health problems of older male, about 13% of male was affected by prostate cancer. Prostate cancer is highly heterogeneity disease with complex molecular and genetic alterations. So, targeting the gene candidates in prostate cancer in single-cell level can be a promising approach for treating prostate cancer. In the present study, we analyzed the single cell sequencing data obtained from 2 previous reports to determine the differential gene expression of prostate cancer in single-cell level. By using the network pharmacology analysis, we identified the therapeutic targets of formononetin in immune cells and tissue cells of prostate cancer. We then applied molecular docking to determine the possible direct binding of formononetin to its target proteins. Our result identified a cluster of differential gene expression in prostate cancer which can serve as novel biomarkers such as immunoglobulin kappa C for prostate cancer prognosis. The result of network pharmacology delineated the roles of formononetin's targets such CD74 and THBS1 in immune cells' function of prostate cancer. Also, formononetin targeted insulin receptor and zinc-alpha-2-glycoprotein which play important roles in metabolisms of tissue cells of prostate cancer. The result of molecular docking suggested the direct binding of formononetin to its target proteins including INSR, TNF, and CXCR4. Finally, we validated our findings by using formononetin-treated human prostate cancer cell DU145. For the first time, our result suggested the use of formononetin for treating prostate cancer through targeting different cell types in a single-cell level.

Insights into the prognostic value and immunological role of CD74 in pan-cancer

BACKGROUND

CD74 is a non-polymorphic type II transmembrane glycoprotein. It is involved in the regulation of T and B cell development, and dendritic cell (DC) motility. Numerous studies have found that CD74 exerts an essential role in tumor immunity, but the expression profile of CD74 is still not systematically reported, and its value in human pan-cancer analysis is unknown. In this study, we analyzed the expression pattern of CD74 in 33 cancers, and evaluated the significance of CD74 in prognosis prediction and cancer immunity.

METHODS

Pan-cancer dataset from UCSC Xena.We used the Sangerbox website combined with R software' Timer, CIBERSORT method and IOBR package to analyze and plot the data. Survival was assessed using the Kaplan-Meier method and log-rank test for 33 cancer types (p < 0.05). In addition, to explore the relationship between CD74 expression and immune checkpoints, immune cell infiltration, tumor mutational burden (TMB) and microsatellite instability (MSI), Spearman correlation analysis was performed.

RESULTS

This study comprehensively analyzed CD74 expression in 33 different tumor types, revealing that CD74 play an crucial role in cancer formation and development.

CONCLUSIONS

CD74 gene expression in different cancers is associated with immune cell infiltration and immunomodulators and may provide a promising target for survival and immunotherapy. Our study shows that CD74 has an essential role as a biomarker of prognosis during tumor development, which highlights the possibility of new targeted therapies.

MIF and CD74 as Emerging Biomarkers for Immune Checkpoint Blockade Therapy

Immune checkpoint blockade (ICB) therapy is used to treat a wide range of cancers; however, some patients are at risk of developing treatment resistance and/or immune-related adverse events (irAEs). Thus, there is a great need for the identification of reliable predictive biomarkers for response and toxicity. The cytokine MIF (macrophage migration inhibitory factor) and its cognate receptor CD74 are intimately connected with cancer progression and have previously been proposed as prognostic biomarkers for patient outcome in various cancers, including solid tumors such as malignant melanoma. Here, we assess their potential as predictive biomarkers for response to ICB therapy and irAE development. We provide a brief overview of their function and roles in the context of cancer and autoimmune disease. We also review the evidence showing that MIF and CD74 may be of use as predictive biomarkers of patient response to ICB therapy and irAE development. We also highlight that careful consideration is required when assessing the potential of serum MIF levels as a biomarker due to its reported circadian expression in human plasma. Finally, we suggest future directions for the establishment of MIF and CD74 as predictive biomarkers for ICB therapy and irAE development to guide further research in this field.

CD74 is associated with inflamed tumor immune microenvironment and predicts responsiveness to PD-1/CTLA-4 bispecific antibody in patients with solid tumors

INTRODUCTION

Cadonilimab (AK104) is a first-in-class tetravalent bispecific antibody that targets both PD-1 and CTLA-4, showing a manageable safety profile and favorable clinical benefits. This study aimed to identify the biomarkers of clinical response and explore the immune response within the tumor microenvironment upon the AK104 therapy in advanced solid tumors.

MATERIAL AND METHODS

Gene expression profiles of paired pre- and post-treatment tumor tissues from twenty-one patients were analyzed. The association of gene expression levels with either clinical efficacy or prognosis was evaluated and subsequently validated with published datasets using log-rank for Kaplan-Meier estimates. Comparative immune profile analyses of tumor microenvironment before and after AK104 treatment were conducted. The visualization of tumor-infiltrating lymphocytes was performed using multiplex immunohistochemistry. The predictive value of CD74 was further validated with protein expression by immunohistochemistry.

RESULTS

Baseline CD74 gene expression was associated with favorable patient outcomes (overall survival [OS], HR = 0.33, 95% CI 0.11-1.03, p = 0.0463), which was further confirmed with the published datasets. Tumors with high CD74 gene expression at baseline were more likely to exhibit an immune-inflamed microenvironment. AK104 efficiently enhanced the infiltration of immune cells in the tumor microenvironment. Additionally, high CD74 protein expression (≥ 10% of the tumor area occupied by CD74 stained immune cells) at baseline was associated with better progressive-free survival (HR = 0.21, 95% CI 0.06-0.68, p = 0.0065) and OS (HR = 0.35, 95% CI 0.12-1.08, p = 0.0615).

CONCLUSIONS

Our findings demonstrate that CD74 is a promising predictive biomarker for AK104 therapeutic response in advanced solid tumors. Trial registration number NCT03261011.

Identification of invasive subpopulations using spatial transcriptome analysis in thyroid follicular tumors

BACKGROUND

Follicular tumors include follicular thyroid adenomas and carcinomas; however, it is difficult to distinguish between the two when the cytology or biopsy material is obtained from a portion of the tumor. The presence or absence of invasion in the resected material is used to differentiate between adenomas and carcinomas, which often results in the unnecessary removal of the adenomas. If nodules that may be follicular thyroid carcinomas are identified preoperatively, active surveillance of other nodules as adenomas is possible, which reduces the risk of surgical complications and the expenses incurred during medical treatment. Therefore, we aimed to identify biomarkers in the invasive subpopulation of follicular tumor cells.

METHODS

We performed a spatial transcriptome analysis of a case of follicular thyroid carcinoma and examined the dynamics of CD74 expression in 36 cases.

RESULTS

We identified a subpopulation in a region close to the invasive area, and this subpopulation expressed high levels of CD74. Immunohistochemically, CD74 was highly expressed in the invasive and peripheral areas of the tumor.

CONCLUSIONS

Although high CD74 expression has been reported in papillary and anaplastic thyroid carcinomas, it has not been analyzed in follicular thyroid carcinomas. Furthermore, the heterogeneity of CD74 expression in thyroid tumors has not yet been reported. The CD74-positive subpopulation identified in this study may be useful in predicting invasion of follicular thyroid carcinomas.

Analysis of CD74 Occurrence in Oncogenic Fusion Proteins

CD74 is a type II cell surface receptor found to be highly expressed in several hematological and solid cancers, due to its ability to activate pathways associated with tumor cell survival and proliferation. Over the past 16 years, CD74 has emerged as a commonly detected fusion partner in multiple oncogenic fusion proteins. Studies have found CD74 fusion proteins in a range of cancers, including lung adenocarcinoma, inflammatory breast cancer, and pediatric acute lymphoblastic leukemia. To date, there are five known CD74 fusion proteins, CD74-ROS1, CD74-NTRK1, CD74-NRG1, CD74-NRG2α, and CD74-PDGFRB, with a total of 16 different variants, each with unique genetic signatures. Importantly, the occurrence of CD74 in the formation of fusion proteins has not been well explored despite the fact that ROS1 and NRG1 families utilize CD74 as the primary partner for the formation of oncogenic fusions. Fusion proteins known to be oncogenic drivers, including those of CD74, are typically detected and targeted after standard chemotherapeutic plans fail and the disease relapses. The analysis reported herein provides insights into the early intervention of CD74 fusions and highlights the need for improved routine assessment methods so that targeted therapies can be applied while they are most effective.

Integrated analysis of single-cell and bulk RNA-sequencing data reveals the prognostic value and molecular function of THSD7A in gastric cancer

The biological role and prognostic value of thrombospondin domain-containing 7A (THSD7A) in gastric cancer remain unclear. Our purpose was to determine the molecular mechanisms underlying the functioning of THSD7A and its prognostic value in gastric cancer. Gastric cancer-associated single cell and bulk RNA sequencing data obtained from two databases, were analyzed. We used bulk RNA sequencing to examine the differential expression of THSD7A in gastric cancer and normal gastric tissues and explored the relationship between THSD7A expression and clinicopathological characteristics. Kaplan-Meier survival and Cox analyses revealed the prognostic value of THSD7A. Gene set enrichment and immune infiltration analyses were used to determine the cancer-promoting mechanisms of THSD7A and its effect on the immune microenvironment. We explored the relationship between THSD7A expression and sensitivity of anti-tumor drugs and immune checkpoint levels. Biological functions of THSD7A were validated at single-cell and in vitro levels. THSD7A expression was significantly increased in gastric cancer samples. High THSD7A expression was associated with poor clinical phenotypes and prognoses. Cox analysis showed that THSD7A was an independent risk factor for patients with gastric cancer. Enrichment analysis suggested that epithelial-mesenchymal transition and inflammatory responses may be potential pro-cancer mechanisms of THSD7A. Upregulation of THSD7A promoted infiltration by M2 macrophages and regulatory T cells. High THSD7A expression suppressed the sensitivity of patients with gastric cancer to drugs, such as 5-fluorouracil, bleomycin, and cisplatin, and upregulated immune checkpoints, such as HAVCR2, PDCD1LG2, TIGIT, and CTLA4. At the single cell level, THSD7A was an endothelial cell-associated gene and endothelial cells overexpressing THSD7A showed unique pro-oncogenic effects. In vitro experiments confirmed that THSD7A was overexpressed in gastric cancer samples and cells, and that knocking out THSD7A significantly inhibited gastric cancer cell proliferation and invasion. THSD7A overexpression may be a unique prognostic marker and therapeutic target in gastric cancer. Therefore, our study provides a new perspective on the precise treatment of gastric cancer.

Reanalysis of single-cell data reveals macrophage subsets associated with the immunotherapy response and prognosis of patients with endometrial cancer

Endometrial cancer (EC) is an aggressive gynecological malignancy with an increased incidence rate. The immune landscape crucially affects immunotherapy efficacy and prognosis in EC patients. Here, we characterized the distinct tumor microenvironment signatures of EC tumors by analyzing single-cell RNA sequencing data from Gene Expression Omnibus and bulk RNA sequencing data from The Cancer Genome Atlas, which were compared with normal endometrium. Three macrophage subsets were identified, and two of them showed tissue-specific distribution. One of the macrophage subsets was dominant in macrophages derived from EC and exhibited characteristic behaviors such as promoting tumor growth and metastasis. One of the other macrophage subsets was mainly found in normal endometrium and served functions related to antigen presentation. We also identified a macrophage subset that was found in both EC and normal endometrial tissue. However, the pathway and cellular cross-talk of this subset were completely different based on the respective origin, suggesting a tumor-related differentiation mechanism of macrophages. Additionally, the tumor-enriched macrophage subset was found to predict immunotherapy responses in EC. Notably, we selected six genes from macrophage subset markers that could predict the survival of EC patients, SCL8A1, TXN, ANXA5, CST3, CD74 and NANS, and constructed a prognostic signature. To verify the signature, we identified immunohistochemistry for the tumor samples of 83 EC patients based on the selected genes and further followed up with the survival of the patients. Our results provide strong evidence that the signature can effectively predict the prognosis of EC patients.

CD74 Promotes a Pro-Inflammatory Tumor Microenvironment by Inducing S100A8 and S100A9 Secretion in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive form of pancreatic cancer with a poor prognosis and low survival rates. The prognostic and predictive biomarkers of PDAC are still largely unknown. The receptor CD74 was recently identified as a regulator of oncogenic properties in various cancers. However, the precise molecular mechanism of CD74 action in PDAC remains little understood. We investigated the role of CD74 by silencing CD74 in the pancreatic cancer cell line Capan-1. CD74 knockdown led to reductions in cell proliferation, migration, and invasion and increased apoptosis. Moreover, silencing CD74 resulted in the decreased expression and secretion of S100A8 and S100A9. An indirect co-culture of fibroblasts and tumor cells revealed that fibroblasts exposed to conditioned media from CD74 knockdown cells exhibited a reduced expression of inflammatory cytokines, suggesting a role of CD74 in influencing cytokine secretion in the tumor microenvironment. Overall, our study provides valuable insights into the critical role of CD74 in regulating the oncogenic properties of pancreatic cancer cells and its influence on the expression and secretion of S100A8 and S100A9. Taken together, these findings indicate CD74 as a potential diagnostic biomarker and therapeutic target for pancreatic cancer.

The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma

Cuproptosis is a recently described copper-dependent cell death pathway. Consequently, there are still few studies on lung adenocarcinoma (LUAD)-related cuproptosis, and we aimed to deepen in this matter. In this study, data from 503 patients with lung cancer from the TCGA-LUAD cohort data collection and 11 LUAD single-cells from GSE131907 as well as from 10 genes associated with cuproptosis were analyzed. The AUCell R package was used to determine the copper-dependent cell death pathway activity for each cell subpopulation, calculate the CellChat score, and display cell communication for each cell subpopulation. The PROGENy score was calculated to show the scores of tumor-related pathways in different cell populations. GO and KEGG analyses were used to calculate pathway activity. Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models. The ssGSEA and xCell algorithms were used to calculate the immunocyte infiltration score. Based on data from the GDSC database, the drug sensitivity score was calculated using oncoPredict. Finally, in vitro experiments were performed to determine the role of TLE1, the most important gene in the prognostic model. The 11 LUAD single-cell samples were classified into 8 different cell populations, from which epithelial cells showed the highest copper-dependent cell death pathway activity. Epithelial cell subsets were significantly positively correlated with MAKP, hypoxia, and other pathways. In addition, cell subgroup communication showed highly active collagen and APP pathways. Using the Findmark algorithm, differentially expressed genes (DEGs) between epithelial and other cell types were identified. Combined with the bulk data in the TCGA-LUAD database, DEGs were enriched in pathways such as EGFR tyrosine kinase inhibitor resistance, Hippo signaling pathway, and tight junction. Subsequently, we selected 4 genes (out of 112) with prognostic significance, ANKRD29, RHOV, TLE1, and NPAS2, and used them to construct a prognostic model. The high- and low-risk groups, distinguished by the median risk score, showed significantly different prognoses. Finally, we chose TLE1 as a biomarker based on the relative importance score in the prognostic model. In vitro experiments showed that TLE1 promotes tumor proliferation and migration and inhibits apoptosis.

Dynamics of human hematopoietic stem and progenitor cell differentiation to the erythroid lineage

Erythropoiesis, the development of erythrocytes from hematopoietic stem cells, occurs through four phases: erythroid progenitor (EP) development, early erythropoiesis, terminal erythroid differentiation (TED), and maturation. According to the classical model that is based on immunophenotypic profiles of cell populations, each of these phases comprises multiple differentiation states that arise in a hierarchical manner. After segregation of lymphoid potential, erythroid priming begins during progenitor development and progresses through progenitor cell types that have multilineage potential. Complete separation of the erythroid lineage is achieved during early erythropoiesis with the formation of unipotent EPs: burst-forming unit-erythroid and colony-forming unit-erythroid. These erythroid-committed progenitors undergo TED and maturation, which involves expulsion of the nucleus and remodeling to form functional biconcave, hemoglobin-filled erythrocytes. In the last decade or so, many studies employing advanced techniques such as single-cell RNA-sequencing (scRNA-seq) as well as the conventional methods, including colony-forming cell assays and immunophenotyping, have revealed heterogeneity within the stem, progenitor, and erythroblast stages, and uncovered alternate paths for segregation of erythroid lineage potential. In this review, we provide an in-depth account of immunophenotypic profiles of all cell types within erythropoiesis, highlight studies that demonstrate heterogeneous erythroid stages, and describe deviations to the classical model of erythropoiesis. Overall, although scRNA-seq approaches have provided new insights, flow cytometry remains relevant and is the primary method for validation of novel immunophenotypes.

Applying causal discovery to single-cell analyses using CausalCell

Correlation between objects is prone to occur coincidentally, and exploring correlation or association in most situations does not answer scientific questions rich in causality. Causal discovery (also called causal inference) infers causal interactions between objects from observational data. Reported causal discovery methods and single-cell datasets make applying causal discovery to single cells a promising direction. However, evaluating and choosing causal discovery methods and developing and performing proper workflow remain challenges. We report the workflow and platform CausalCell (http://www.gaemons.net/causalcell/causalDiscovery/) for performing single-cell causal discovery. The workflow/platform is developed upon benchmarking four kinds of causal discovery methods and is examined by analyzing multiple single-cell RNA-sequencing (scRNA-seq) datasets. Our results suggest that different situations need different methods and the constraint-based PC algorithm with kernel-based conditional independence tests work best in most situations. Related issues are discussed and tips for best practices are given. Inferred causal interactions in single cells provide valuable clues for investigating molecular interactions and gene regulations, identifying critical diagnostic and therapeutic targets, and designing experimental and clinical interventions.

circMMD reduction following tumor treating fields inhibits glioblastoma progression through FUBP1/FIR/DVL1 and miR-15b-5p/FZD6 signaling

BACKGROUND

Tumor treating fields (TTF) is the latest treatment for GBM. Circular RNA (circRNA) has been demonstrated to play critical roles in tumorigenesis. However, the molecular mechanism of TTF remained largely unknown and the role of circRNA in TTF was not reported. The aim of this study was to elucidate the role and mechanism of circMMD in TTF treatment of GBM.

METHODS

Divergent primer was designed to verify the existence of circMMD in GBM cells. The prognostic role of circMMD was explored in glioma specimens. The knockdown and overexpressed plasmids were used to evaluate the effect of circMMD on GBM cell proliferation and TTF efficacy. RNA pull-down and RNA immunoprecipitation were performed to identify binding proteins of circMMD. Subcutaneous and intracranial tumor models were established to validate findings in vivo.

RESULTS

The expression of circMMD was elevated in GBM and its high expression indicated poor prognoses. TTF intervention could reduce circMMD synthesis, which suppressed GBM proliferation and increased TTF-mediated apoptosis. The reduction of circMMD promoted the interaction between FUBP1 and FIR, which decreased DVL1 transcription. Meanwhile, decreased circMMD would promote the activity of miR-15b-5p to degrade FZD6. Finally, the diminished expression of DVL1 and FZD6 expression suppressed the activation of Wnt/β-catenin pathway.

CONCLUSIONS

Our study revealed a novel mechanism of TTF that TTF-mediated reduction of circMMD could inhibit Wnt/β-catenin pathway to suppress GBM proliferation.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

Long-term anti-tumor effects following both conventional radiotherapy and FLASH in fully immunocompetent animals with glioblastoma

Radiotherapy can induce an immunological response. One limiting factor is side effects on normal tissue. Using FLASH radiotherapy, side effects could possibly be reduced. The efficacy of FLASH in relation to conventional radiotherapy (CONV-RT) has not been extensively explored in fully immunocompetent animals. Fully immunocompetent Fischer 344 rats were inoculated with NS1 glioblastoma cells subcutaneously or intracranially. Radiotherapy was delivered with FLASH or CONV-RT at 8 Gy × 2 (subcutaneous tumors) and 12.5 Gy × 2 (intracranial tumors). Cured animals were re-challenged in order to explore long-term anti-tumor immunity. Serum analytes and gene expression were explored. The majority of animals with subcutaneous tumors were cured when treated with FLASH or CONV-RT at 8 Gy × 2. Cured animals could reject tumor re-challenge. TIMP-1 in serum was reduced in animals treated with FLASH 8 Gy × 2 compared to control animals. Animals with intracranial tumors survived longer when treated with FLASH or CONV-RT at 12.5 Gy × 2, but cure was not reached. CONV-RT and FLASH were equally effective in fully immunocompetent animals with glioblastoma. Radiotherapy was highly efficient in the subcutaneous setting, leading to cure and long-term immunity in the majority of the animals.

New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis

BACKGROUND

Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors contributing to gliomas, the role of single genes as diagnostic and prognostic biomarkers is limited. The aim of the current study is to discover the predictive and prognostic genetic markers for LGG.

METHODS

Transcriptome data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We first performed the tumor microenvironment (TME) survival analysis using the Kaplan-Meier method. An analysis was undertaken to screen for differentially expressed genes. The function of these genes was studied by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Following which a protein-protein interaction network (PPI) was constructed and visualized. Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes. The key genes were selected by an intersection of core and prognostic genes. A clinical correlation analysis of single-gene expression was undertaken. GSEA enrichment analysis was performed to identify the function of key genes. Finally, a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG.

RESULTS

A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA. Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment. The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified. Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG. Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration, positively related to macrophage M1 phenotype, and negatively related to activation of NK cells.

CONCLUSIONS

HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients. It may also be associated with the immune infiltration phenotype in LGG.

Pan-Cancer Analysis Shows That ALKBH5 Is a Potential Prognostic and Immunotherapeutic Biomarker for Multiple Cancer Types Including Gliomas

Background

AlkB homolog 5 (ALKBH5) is a N⁶-methyladenosine (m⁶A) demethylase associated with the development, growth, and progression of multiple cancer types. However, the biological role of ALKBH5 has not been investigated in pan-cancer datasets. Therefore, in this study, comprehensive bioinformatics analysis of pan-cancer datasets was performed to determine the mechanisms through which ALKBH5 regulates tumorigenesis.

Methods

Online websites and databases such as NCBI, UCSC, CCLE, HPA, TIMER2, GEPIA2, cBioPortal, UALCAN, STRING, SangerBox, ImmuCellAl, xCell, and GenePattern were used to extract data of ALKBH5 in multiple cancers. The pan-cancer patient datasets were analyzed to determine the relationship between ALKBH5 expression, genetic alterations, methylation status, and tumor immunity. Targetscan, miRWalk, miRDB, miRabel, LncBase databases and Cytoscape tool were used to identify microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) that regulate expression of ALKBH5 and construct the lncRNA-miRNA-ALKBH5 network. In vitro CCK-8, wound healing, Transwell and M2 macrophage infiltration assays as well as in vivo xenograft animal experiments were performed to determine the biological functions of ALKBH5 in glioma cells.

Results

The pan-cancer analysis showed that ALKBH5 was upregulated in several solid tumors. ALKBH5 expression significantly correlated with the prognosis of cancer patients. Genetic alterations including duplications and deep mutations of the ALKBH5 gene were identified in several cancer types. Alterations in the ALKBH5 gene correlated with tumor prognosis. GO and KEGG enrichment analyses showed that ALKBH5-related genes were enriched in the inflammatory, metabolic, and immune signaling pathways in glioma. ALKBH5 expression correlated with the expression of immune checkpoint (ICP) genes, and influenced sensitivity to immunotherapy. We constructed a lncRNA-miRNA network that regulates ALKBH5 expression in tumor development and progression. In vitro and in vivo experiments showed that ALKBH5 promoted proliferation, migration, and invasion of glioma cells and recruited the M2 macrophage to glioma cells.

Conclusions

ALKBH5 was overexpressed in multiple cancer types and promoted the development and progression of cancers through several mechanisms including regulation of the tumor-infiltration of immune cells. Our study shows that ALKBH5 is a promising prognostic and immunotherapeutic biomarker in some malignant tumors.

Ferroptosis Activation Scoring Model Assists in Chemotherapeutic Agents' Selection and Mediates Cross-Talk With Immunocytes in Malignant Glioblastoma

Gliomas are aggressive tumors in the central nervous system and glioblastoma is the most malignant type. Ferroptosis is a programmed cell death that can modulate tumor resistance to therapy and the components of tumor microenvironment. However, the relationship between ferroptosis, tumor immune landscape, and glioblastoma progression is still elusive. In this work, data from bulk RNA-seq analysis, single cell RNA-seq analysis, and our own data (the Xiangya cohort) are integrated to reveal their relationships. A scoring system is constructed according to ferroptosis related gene expression, and high scoring samples resistant to ferroptosis and show worse survival outcome than low scoring samples. Notably, most of the high scoring samples are aggressive glioblastoma subtype, mesenchymal, and classical, by calculating RNA velocity. Cross-talk between high scoring glioblastoma cells and immunocytes are explored by R package 'celltalker'. Ligand-receptor pairs like the TRAIL or TWEAK signaling pathway are identified as novel bridges implying how ferroptosis modulate immunocytes' function and shape tumor microenvironment. Critically, potential drugs target to high scoring samples are predicted, namely, SNX2112, AZ628, and bortezomib and five compounds from the CellMiner database. Taken together, ferroptosis associates with glioblastoma aggressiveness, cross-talk with immunocytes and offer novel chemotherapy strategy.