Comprehensive characterization of the alternative splicing landscape in head and neck squamous cell carcinoma reveals novel events associated with tumorigenesis and the immune microenvironment

IGF2BP2 orchestrates global expression and alternative splicing profiles associated with glioblastoma development in U251 cells

Glioblastoma (GBM) is a highly invasive and malignant central nervous system tumor with a median survival duration of 15 months despite multimodal therapy. The insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) has been implicated in various cancers and is known to regulate RNA metabolism and alternative splicing (AS). However, its role in GBM remains unclear. Overexpression of IGF2BP2 led to significant alterations in gene expression, with 472 genes upregulated and 99 downregulated. Gene ontology (GO) analysis indicated enrichment in immune-related biological processes. Notably, IGF2BP2 was found to regulate AS events, with 1372 regulated AS genes (RASGs) and 2096 significantly distinct ASEs identified. Furthermore, IGF2BP2 selectively bound to 3' and 5' untranslated regions (UTRs) via GG[AU]C motifs, and IFIH1 was identified as a direct binding partner and upregulated gene upon IGF2BP2 overexpression. Functional enrichment analysis suggested that IGF2BP2 influences pathways related to RNA splicing and immune responses. Our findings demonstrate that IGF2BP2 plays a crucial role in GBM by modulating the transcriptome and AS events. The upregulation of immune-related genes and the regulation of AS by IGF2BP2 highlight its potential as a therapeutic target in GBM, particularly for immunotherapy. The study provides a foundation for further investigation into the molecular mechanisms of IGF2BP2 in GBM and its implications for cancer treatment.

Genome-wide identification of alternative splicing related with transcription factors and splicing regulators in breast cancer stem cells responding to fasting-mimicking diet

Fasting-mimicking diet (FMD) can effectively inhibit the viability of breast cancer stem cells (CSCs). However, the molecular mechanisms underlying the inhibitory function of FMD on breast CSCs remain largely unknown. Elucidating the mechanisms by which FMD suppresses breast CSCs is beneficial to targeting breast CSCs. Herein, we systematically analyze alternative splicing and RNA binding protein (RBP) expression in breast CSCs during FMD. The analysis results show that a large number of regulated alternative splicing (RAS) and differentially expressed genes (DEGs) appear responding to FMD. Further studies show that there are potential regulatory relationships between transcription factors (TFs) with RAS (RAS-TFs) and their differentially expressed target genes (RAS-TF-DEGs). Moreover, differentially expressed RNA binding proteins (DERBPs) exhibit potential regulatory functions on RAS-TFs. In short, DERBPs potentially control the alternative splicing of TFs (RAS-TFs), regulating their target gene (RAS-TF-DEG) expression, which leads to the regulation of biological processes in breast CSCs during FMD. In addition, the alternative splicing and DEGs are compared between breast CSCs and differentiated cancer cells during FMD, providing new interpretations for the different responses of the two types of cells. Our studies will shed light on the understanding of the molecular mechanisms underlying breast CSC inhibition induced by FMD.

Overcoming cancer drug-resistance calls for novel strategies targeting abnormal alternative splicing

Abnormal gene alternative splicing (AS) events are strongly associated with cancer progression. Here, we summarize AS events that contribute to the development of drug resistance and classify them into three categories: alternative cis-splicing (ACS), alternative trans-splicing (ATS), and alternative back-splicing (ABS). The regulatory mechanisms underlying AS processes through cis-acting regulatory elements and trans-acting factors are comprehensively described, and the distinct functions of spliced variants, including linear spliced variants derived from ACS, chimeric spliced variants arising from ATS, and circRNAs generated through ABS, are discussed. The identification of dysregulated spliced variants, which contribute to drug resistance and hinder effective cancer treatment, suggests that abnormal AS processes may together serve as a precise regulatory mechanism enabling drug-resistant cancer cell survival or, alternatively, represent an evolutionary pathway for cancer cells to adapt to changes in the external environment. Moreover, this review summarizes recent advancements in treatment approaches targeting AS-associated drug resistance, focusing on cis-acting regulatory elements, trans-acting factors, and specific spliced variants. Collectively, gaining an in-depth understanding of the mechanisms underlying aberrant alternative splicing events and developing strategies to target this process hold great promise for overcoming cancer drug resistance.

Pan-cancer analysis of immune checkpoint receptors and ligands in various cells in the tumor immune microenvironment

Drugs that target immune checkpoint have become the most popular weapon in cancer immunotherapy, yet only have practical benefits for a small percentage of patients. Tumor cells constantly interact with their microenvironment, which is made up of a variety of immune cells as well as endothelial cells and fibroblasts. Immune checkpoint expression and blocked signaling of immune cells in the tumor microenvironment (TME) are key to tumor progression. In this study, we perform deliberation convolution on the TCGA database for human lung, breast, and colorectal cancer to infer crosstalk between immune checkpoint receptors (ICRs) and ligands (ICLs) in TME of pan-carcinogenic solid tumor types, validated by flow cytometry. Analysis of immune checkpoints showed that there was little variation between different tumor types. It showed that CD160, LAG3, TIGIT were found to be highly expressed in CD8+ T cells instead of CD4+ T cells, PD-L1, PD-L2, CD86, LGALS9, TNFRSF14, LILRB4 and other ligands were highly expressed on macrophages, FVR, NECTIN2, FGL1 were highly expressed on Epithelial cells, CD200 was highly expressed in Endothelial cells, and CD80 was highly expressed in CD8 High expression on T cells. Overall, our study provides a new resource for the expression of immune checkpoints in TME on various types of cells. Significance: This study provides immune checkpoint expression of immune cells of multiple cancer types to infer immune mechanisms in the tumor microenvironment and provide ideas for the development of new immune checkpoint-blocking drugs.

Splicing Machinery Is Impaired in Oral Squamous Cell Carcinomas and Linked to Key Pathophysiological Features

Alternative splicing dysregulation is an emerging cancer hallmark, potentially serving as a source of novel diagnostic, prognostic, or therapeutic tools. Inhibitors of the activity of the splicing machinery can exert antitumoral effects in cancer cells. We aimed to characterize the splicing machinery (SM) components in oral squamous cell carcinoma (OSCC) and to evaluate the direct impact of the inhibition of SM-activity on OSCC-cells. The expression of 59 SM-components was assessed using a prospective case-control study of tumor and healthy samples from 37 OSCC patients, and the relationship with clinical and histopathological features was assessed. The direct effect of pladienolide-B (SM-inhibitor) on the proliferation rate of primary OSCC cell cultures was evaluated. A significant dysregulation in several SM components was found in OSCC vs. adjacent-healthy tissues [i.e., 12 out of 59 (20%)], and their expression was associated with clinical and histopathological features of less aggressiveness and overall survival. Pladienolide-B treatment significantly decreased OSCC-cell proliferation. Our data reveal a significantly altered expression of several SM-components and link it to pathophysiological features, reinforcing a potential clinical and pathophysiological relevance of the SM dysregulation in OSCC. The inhibition of SM-activity might be a therapeutic avenue in OSCC, offering a clinically relevant opportunity to be explored.

A comprehensive analysis of ribonucleotide reductase subunit M2 for carcinogenesis in pan-cancer

BACKGROUND

Although there is evidence that ribonucleotide reductase subunit M2 (RRM2) is associated with numerous cancers, pan-cancer analysis has seldom been conducted. This study aimed to explore the potential carcinogenesis of RRM2 in pan-cancer using datasets from The Cancer Genome Atlas (TCGA).

METHODS

Data from the UCSC Xena database were analyzed to investigate the differential expression of RRM2 across multiple cancer types. Clinical data such as age, race, sex, tumor stage, and status were acquired to analyze the influence of RRM2 on the clinical characteristics of the patients. The role of RRM2 in the onset and progression of multiple cancers has been examined in terms of genetic changes at the molecular level, including tumor mutational burden (TMB), microsatellite instability (MSI), biological pathway changes, and the immune microenvironment.

RESULTS

RRM2 was highly expressed in most cancers, and there was an obvious correlation between RRM2 expression and patient prognosis. RRM2 expression is associated with the infiltration of diverse immune and endothelial cells, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). Moreover, the cell cycle is involved in the functional mechanisms of RRM2.

CONCLUSIONS

Our pan-cancer study provides a comprehensive understanding of the carcinogenesis of RRM2 in various tumors.

Stiffness promotes cell migration, invasion, and invadopodia in nasopharyngeal carcinoma by regulating the WT-CTTN level

Matrix stiffness potently promotes the malignant phenotype in various biological contexts. Therefore, identification of gene expression to participate in mechanical force signals transduced into downstream biochemical signaling will contribute substantially to the advances in nasopharyngeal carcinoma (NPC) treatment. In the present study, we detected that cortactin (CTTN) played an indispensable role in matrix stiffness-induced cell migration, invasion, and invadopodia formation. Advances in cancer research have highlighted that dysregulated alternative splicing contributes to cancer progression as an oncogenic driver. However, whether WT-CTTN or splice variants (SV1-CTTN or SV2-CTTN) regulate matrix stiffness-induced malignant phenotype is largely unknown. We proved that alteration of WT-CTTN expression modulated matrix stiffness-induced cell migration, invasion, and invadopodia formation. Considering that splicing factors might drive cancer progression through positive feedback loops, we analyzed and showed how the splicing factor PTBP2 and TIA1 modulated the production of WT-CTTN. Moreover, we determined that high stiffness activated PTBP2 expression. Taken together, our findings showed that the PTBP2-WT-CTTN level increases upon stiffening and then promotes cell migration, invasion, and invadopodia formation in NPC.

An anti-PD-1 antisense oligonucleotide promotes the expression of soluble PD-1 by blocking the interaction between SRSF3 and an exonic splicing enhancer of PD-1 exon 3

PD-1 is a key immune checkpoint molecule. Anti-PD-1 immunotherapy is encouraging in cancer treatment. However, it still needs to be improved. PD-1 has at least five isoforms generated by alternative splicing. An isoform without exon 3 encoding soluble PD-1 (sPD-1) can activate anti-tumor immunity by inhibiting the interaction between cellular surface full-length PD-1 (flPD-1) and PD-L1. However, the regulatory mechanism of exon 3 splicing remains largely unknown. Here, we screened the exon 3 sequence by mutation and searched corresponding splicing factors by SpliceAid database and pulldown assay. The alternative splicing of PD-1 exon 3 was analyzed by RT-PCR. The expression levels of flPD-1 and sPD-1 were analyzed by Western blot, flow cytometry, and ELISA. We discovered that an exonic splicing enhancer (ESE) of exon 3 is essential for its inclusion. Moreover, SRSF3 can bind to this ESE and enhance exon 3 inclusion and flPD-1 expression. We designed and screened out an antisense oligonucleotide (ASO) targeting PD-1 to block the interaction between SRSF3 and ESE, and significantly increase exon 3 skipping and sPD-1 expression, which was verified in various tumor cells in addition to oral cancer cells. Altogether, our results uncovered the regulatory mechanism of human PD-1 exon 3 splicing and sPD-1 expression and further designed a novel anti-PD-1 ASO, which are useful for developing a new method of anti-cancer immunotherapy.

Alternative Splicing Landscape of Head and Neck Squamous Cell Carcinoma

Head and neck malignancies are a significant global health concern, with head and neck squamous cell carcinoma (HNSCC) being the sixth most common cancer worldwide accounting for > 90% of cases. In recent years, there has been growing recognition of the potential role of alternative splicing (AS) in the etiology of cancer. Increasing evidence suggests that AS is associated with various aspects of cancer progression, including tumor occurrence, invasion, metastasis, and drug resistance. Additionally, AS is involved in shaping the tumor microenvironment, which plays a crucial role in tumor development and response to therapy. AS can influence the expression of factors involved in angiogenesis, immune response, and extracellular matrix remodeling, all of which contribute to the formation of a supportive microenvironment for tumor growth. Exploring the mechanism of AS events in HNSCC could provide insights into the development and progression of this cancer, as well as its interaction with the tumor microenvironment. Understanding how AS contributes to the molecular changes in HNSCC cells and influences the tumor microenvironment could lead to the identification of new therapeutic targets. Targeted chemotherapy and immunotherapy strategies tailored to the specific AS patterns in HNSCC could potentially improve treatment outcomes and reduce side effects. This review explores the concept, types, processes, and technological advancements of AS, focusing on its role in the initiation, progression, treatment, and prognosis of HNSCC.

Unveiling pathogenic mutations in BRCA1 and BRCA2 genes across head and neck squamous cell carcinoma patients via next generation sequencing

Head and Neck Squamous Cell Carcinoma (HNSC) presents a formidable challenge in the field of oncology due to its aggressive nature and the limited therapeutic options available. In this study, our primary focus was on the Pakistani HNSC patient population, aiming to investigate germline oncogenic mutations within the BRCA1 and BRCA2 genes via Next Generation Sequencing (NGS) and explore their clinical implications. We sought to understand the functional consequences of these mutations via RT-qPCR and Immunohistochemistry (IHC) techniques. The key discovery of our research lies in the identification of three pathogenic mutations, including two within BRCA1 (p.Cys274Ter and p.Glu272Ter) and one within BRCA2 (p.Met1Val), among Pakistani HNSC patients. These mutations previously associated with an increased risk of various cancers. What sets our study apart is the uniqueness of these pathogenic mutations, absent in HNSC patients from other populations. This suggests a distinct genetic profile in Pakistani HNSC patients, possibly contributing to their susceptibility to this malignancy. Furthermore, our research revealed elevated expression levels of BRCA1 and BRCA2 genes in HNSC samples harboring pathogenic mutations, offering insights into mechanisms driving tumor progression in HNSC. Importantly, we identified significant enrichment of BRCA1/2 genes in pathways related to cancer development within the KEGG database. Finally, in our quest to explore therapeutic avenues, we systematically analyzed drugs targeting up-regulated and mutated BRCA1/2 genes, identifying promising candidates for tailored treatment modalities in HNSC. In conclusion, our study reveals the unique genetic profile of HNSC in Pakistani patients, featuring unique pathogenic mutations in BRCA1 and BRCA2 genes. These mutations offer promise as valuable diagnostic markers and potential therapeutic targets.

Integrated analysis of diagnostic, prognostic value and potential drug treatment of GSDME in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) poses a global health challenge. Effective biomarkers for early detection are necessary to improve the survival rate of HNSC patient. The purpose of this study was using integrated bioinformatic analysis to investigate the potential biological roles of GSDME in HNSC.

METHODS

The Gene Expression Omnibus (GEO) and Cancer Gnome Atlas (TCGA) databases were used to analyze the expression of GSDME in different cancer types. The correlation between GSDME expression and immune cell infiltration or immune checkpoint genes was examined by Spearman correlation analysis. DNA methylation analysis of the GSDME gene was conducted using the MethSurv database. Kaplan-Meier (K-M) survival curves, diagnostic receiver operating characteristic (ROC) curves, nomogram model, and Cox regression analysis were chosen to evaluate the diagnostic and prognostic predictive value of GSDME. Connectivity Map (Cmap) online platform, Protein Data Bank (PDB) database and Chem3D, AutoDock Tool and PyMol software were used to predict and visualize potential molecular drugs aimed for GSDME.

RESULTS

GSDME expression level in HNSC was significantly higher than in the controls (p < 0.001). Differentially expressed genes (DEGs) correlation with GSDME were enriched in the GO pathways, such as protein activation cascade, complement activation and classical pathway (p < 0.05). According to GSEA, GSDME-associated differentially expressed genes were significantly enriched in KRAS signaling pathway and cytokine signaling molecule (p < 0.05). There is a significant relation between GSDME expression and immune cell infiltration in HNSC tissues, as well as immune checkpoint genes expression (p < 0.001). DNA methylation status of cg17790129 CpG islands of GSDME gene is correlated with HNSC prognosis (p < 0.05). Based on Cox regression analysis of HNSC patients, GSDME as a potential risk gene has high correlation with overall survival (OS) and disease specific survival (DSS) (p < 0.05). In a ROC curve analysis, HNSC tissues were differentiated from adjacent peritumoral tissues based on GSDME expression levels (AUC = 0.928). Totally six potential drugs targeted for GSDME were screened and the molecular docking tests between GSDME protein and candidate drugs were conducted.

CONCLUSIONS

GSDME is a promising therapeutic target as well as a potential clinical biomarker in HNSC patients.

Targeting alternative splicing in cancer immunotherapy

Tumor immunotherapy has made great progress in cancer treatment but still faces several challenges, such as a limited number of targetable antigens and varying responses among patients. Alternative splicing (AS) is an essential process for the maturation of nearly all mammalian mRNAs. Recent studies show that AS contributes to expanding cancer-specific antigens and modulating immunogenicity, making it a promising solution to the above challenges. The organoid technology preserves the individual immune microenvironment and reduces the time/economic costs of the experiment model, facilitating the development of splicing-based immunotherapy. Here, we summarize three critical roles of AS in immunotherapy: resources for generating neoantigens, targets for immune-therapeutic modulation, and biomarkers to guide immunotherapy options. Subsequently, we highlight the benefits of adopting organoids to develop AS-based immunotherapies. Finally, we discuss the current challenges in studying AS-based immunotherapy in terms of existing bioinformatics algorithms and biological technologies.

CD44 occurring alternative splicing promotes cisplatin resistance and evokes tumor immune response in oral squamous cell carcinoma cells

BACKGROUND

Oral squamous cell carcinoma (OSCC) is the most prevalent malignant tumor in head and neck region. Platinum drug resistance limits the clinical application of chemotherapy regardless of medical development. The aim of our study is to identify cisplatin-resistant genes which can be used as new therapeutic targets and investigate the functional mechanism of OSCC chemoresistance.

METHODS

The OSCC Cal27 and HSC4 cisplatin-resistant cell lines were constructed to screen the differential genes/transcripts expression. GO, KEGG and GSEA were performed to reveal the relevant signaling pathways. Alternative splicing (AS) software rMATs was applied to explore AS events in chemoresistance. R package and TIMER tools were used to evaluate the linear correlation between CD44 and immune cell subpopulations. The co-culture model of dendritic cells (DCs) and OSCC cells was applied to explore the effect of CD44 on immune microenvironment and cisplatin resistance.

RESULTS

Our results showed that CD44 was differentially expressed in cisplatin-resistant OSCC cells. Through bioinformatics prediction and experimental verification, we confirmed that CD44 occurring AS was involved in tumor progression and cisplatin resistance. Moreover, CD44 could further enhance the cisplatin resistance of OSCC by activating DCs, making CD44 to be a potential intervention target. We also identified DC as a new target for platinum drugs to stimulate the growth of OSCC.

CONCLUSION

Our findings not only make it possible to explore new therapeutic methods, such as CD44 inhibitors or antisense oligonucleotides, but also provide insights into the new mechanisms of cisplatin resistance to chemotherapy.

Identification of the MMP family as therapeutic targets and prognostic biomarkers in the microenvironment of head and neck squamous cell carcinoma

BACKGROUND

Head and Neck Squamous Cell Carcinoma is a malignant tumor with high morbidity and mortality. The MMP family plays an important role in tumor invasion and metastasis. However, the mechanistic value of the MMP family as a therapeutic target and prognostic biomarker in HNSC has not been fully elucidated.

METHODS

Oncomine, UALCAN, GEPIA, cBioportal, GeneMANIA, STRING, DAVID6.8, TRRUST, TIMER and Linkedomics were used for analysis.

RESULTS

The mRNA expression levels of MMP1, MMP3, ILF3, MMP7, MMP9, MMP10, MMP11, MMP12, MMP13 and MMP16 were higher in HNSC than those in normal tissues, while the mRNA expression level of MMP15 was reduced. The relative expression levels of MMP1 and MMP14 were the highest in HNSC tissues. A significant correlation was found between the expression of MMP3, MMP11, MMP25 and the pathological stage of HNSC patients. There was no significant associations between all the MMP family members expression levels and DFS. Increased mRNA levels of MMP1, MMP8 and MMP25 were significantly associated with OS. In addition, we investigated the genetic changes of the MMP family in HNSC and found that all the MMP family members had genetic changes, most of which were amplification and depth loss. In the analysis of neighbor gene network and protein interaction, we found that the MMP family interacted with 25 neighboring genes, except for ILF3, MMP19, MMP20, MMP21, MMP23B, MMP27 and MMP28, other MMP proteins interacted with each other. Functional enrichment analysis showed that the MMP family could be present in the extracellular matrix, regulate peptidase activity, and participate in the catabolism of collagen. Meanwhile, we identified the transcription factor targets and kinase targets of the MMP family and found that ATM and ATR were the two most common kinase targets in the MMP family. We also found a significant correlation between the MMP family expression and immune cell infiltration. Cox proportional risk model analysis showed that macrophages, MMP14, MMP16, and MMP19 were significantly associated with clinical outcomes in HNSC patients.

CONCLUSION

The MMP family might serve as therapeutic target and prognostic biomarker in HNSC.

New Biomarkers Based on Dendritic Cells for Breast Cancer Treatment and Prognosis Diagnosis

Dendritic cells(DCs) play a protective role in the antitumor immunity of most cancers, which can be divided into conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs). Most current studies are only based on either cDCs or pDCs for the study of the relationship between DCs and breast cancer prognosis, without combining the two together. We aimed to select new biomarkers from pDCs and cDCs. In this paper, the xCell algorithm was first used to calculate the cellular abundance of 64 types of immune cells and stromal cells in tumor samples from the TCGA database, and the high-abundance pDC group and cDC group were divided according to the results of a survival analysis. Then, we looked for the co-expressed gene module of highly infiltrating pDC and cDC patients with a weighted correlation network analysis (WGCNA) and screened out the hub genes, including RBBP5, HNRNPU, PEX19, TPR, and BCL9. Finally, we analyzed the biological functions of the hub genes, and the results showed that RBBP5, TPR, and BCL9 were significantly related to the immune cells and prognosis of patients, and RBBP5 and BCL9 were involved in responding to TCF-related instructions of the Wnt pathway. In addition, we also evaluated the response of pDCs and cDCs with different abundances to chemotherapy, and the results showed that the higher the abundance of pDCs and cDCs, the higher their sensitivity to drugs. This paper revealed new biomarkers related to DCs-among them, BCL9, TPR, and RBBP5 were proven to be closely related to dendritic cells in cancer. For the first time, this paper puts forward that HNRNPU and PEX19 are related to the prognosis of dendritic cells in cancer, which also provides new possibilities for finding new targets for breast cancer immunotherapy.

Novel, alternative splicing signature to detect lymph node metastasis in prostate adenocarcinoma with machine learning

Background

The presence of lymph node metastasis leads to a poor prognosis for prostate cancer (Pca). Recently, many studies have indicated that gene signatures may be able to predict the status of lymph nodes. The purpose of this study is to probe and validate a new tool to predict lymph node metastasis (LNM) based on alternative splicing (AS).

Methods

Gene expression profiles and clinical information of prostate adenocarcinoma cohort were retrieved from The Cancer Genome Atlas (TCGA) database, and the corresponding RNA-seq splicing events profiles were obtained from the TCGA SpliceSeq. Limma package was used to identify the differentially expressed alternative splicing (DEAS) events between LNM and non-LNM groups. Eight machine learning classifiers were built to train with stratified five-fold cross-validation. SHAP values was used to explain the model.

Results

333 differentially expressed alternative splicing (DEAS) events were identified. Using correlation filter and the least absolute shrinkage and selection operator (LASSO) method, a 96 AS signature was identified that had favorable discrimination in the training set and validated in the validation set. The linear discriminant analysis (LDA) was the best classifier after 100 iterations of training. The LDA classifier was able to distinguish between LNM and non-LNM with an area under the receiver operating curve of 0.962 ± 0.026 in the training set (D1 = 351) and 0.953 in the validation set (D2 = 62). The decision curve analysis plot proved the clinical application of the AS-based model.

Conclusion

Machine learning combined with AS data could robustly distinguish between LNM and non-LNM in Pca.

Integrative Analysis Identified CD38 As a Key Node That Correlates Highly with Immunophenotype, Chemoradiotherapy Resistance, And Prognosis of Head and Neck Cancer

Head and neck cancer (HNC) is mainly treated by surgery, radiotherapy, and adjuvant chemotherapy; however, the prognosis of some patients with HNC is poor because of radiotherapy and chemotherapy resistance. In recent years, anti‑PD‑1 monoclonal antibodies have shown certain efficacy, and a change of the tumor immune microenvironment is the main reason for the failure of HNC immunotherapy. The present study aimed to identify and verify that CD38, which is closely related to the prognosis of HNC, is a potential biological marker of radiotherapy and chemotherapy resistance and PD-L1 immunotherapy resistance via a comprehensive bioinformatic analysis in The Cancer Genome Atlas and Gene Expression Omnibus databases. According to the UALCAN database, the transcript level of CD38 in HNC was analyzed using cluster analysis, and the expression of CD38 mRNA in HNC was detected using the Oncomine database. The characteristics of CD38-related oncogenes were identified by gene cluster enrichment analysis in LinkedOmics. The R2 and SEER databases were used to further evaluate the prognostic significance of the CD38 gene in HNC using receiver operating characteristic curve analysis of Kaplan-Meier (KM) survival and the clinical characteristics of the subjects. The protein-protein interaction network of the top 50 genes showing significant positive correlations with CD38 in HNC was analyzed using STRING. Finally, we used a nasopharyngeal carcinoma (NPC) cell line to verify the biological function. The results showed that the levels of CD38 mRNA expression in patients with HNC were significantly higher than those in healthy controls. The levels of CD38 mRNA expression in patients with HNC of different ages, sexes, and races were significantly higher than those in the healthy controls. CD38 is an independent prognostic factor for HNC, and high expression of CD38 indicates poor prognosis. CD38 expression correlated positively with the markers of many kinds of immune cells, and correlated significantly with the expression of PD-L1. We found that the high expression of CD38 suggested a poor prognosis in the subgroup of tumors treated with chemotherapeutic drugs in the G1/S phase. We used HNC cell lines to verify that the high expression of CD38 promoted the proliferation of NPC cells and produced radiotherapy tolerance. Through comprehensive bioinformatics analysis, we suggested that CD38 is a key gene involved in radiotherapy, chemotherapy, and immune drug resistance in HNC. This study provides a reliable biomarker to predict the prognosis of patients with HNC and a reference for clinical comprehensive treatment of HNC. Individualization combined with CD38 monoclonal antibodies might provide a promising treatment strategy for this fatal disease, and this comprehensive treatment might reduce the damage to normal tissue and improve the prognosis and quality of life of patients with HNC.

Screening of Tumor Antigens and Construction of Immune Subtypes for mRNA Vaccine Development in Head and Neck Squamous Cell Carcinoma

BACKGROUND

A growing number of clinical studies have confirmed that mRNA vaccines are effective in the treatment of malignant tumors; however, their efficacy in head and neck squamous cell carcinoma (HNSCC) has not been determined. This study aimed to identify the potential antigens of HNSCC for mRNA vaccine development and further distinguish the immune subtypes of HNSCC to select suitable patients for vaccination.

METHODS

We obtained gene expression profiles and corresponding clinical information of HNSCC from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We visualized the genetic alterations of potential antitumor antigens using cBioPortal and obtained the immune gene set from Immport. The correlation between the expression of the identified antigens and the infiltration of antigen-presenting cells was visualized by Tumor Immune Estimation Resource (TIMER). We evaluated the potential biological functions of different samples and described the immune landscape.

RESULTS

Increased expression of three potential tumor antigens, CCR4, TMCO1, and SPACA4, associated with superior prognoses and infiltration of antigen-presenting cells, was identified in HNSCC. Three immune subtypes (C1-C3) with different molecular, cellular, and clinical characteristics were defined. Patients with C3 tumor had a better prognosis, representing an immune "cold" phenotype, which may be more suitable for mRNA vaccination. In addition, different immune characteristics were observed among the three immune subtypes, including markers of immune cells, mutation burden, expression of immune checkpoints, and immune modulators. Finally, the immune landscape of HNSCC showed a high degree of heterogeneity between individual patients.

CONCLUSION

CCR4, TMCO1, and SPACA4 may be potential antigens for developing mRNA vaccines against HNSCC, especially for patients with C3 tumor. This study could provide a theoretical basis for the development of an mRNA vaccine against HNSCC.

Identification of RNA-splicing factor Lsm12 as a novel tumor-associated gene and a potent biomarker in Oral Squamous Cell Carcinoma (OSCC)

Background

Oral squamous cell carcinoma (OSCC) is one of the common cancers worldwide. The lack of specific biomarkers and therapeutic targets leads to delayed diagnosis and hence the poor prognosis of OSCC patients. Thus, it is urgent to identify effective biomarkers and therapeutic targets for OSCC.

Methods

We established the golden hamster carcinogenic model of OSCC induced by 7,12-dimethylbenz(a) anthrancene (DMBA) and used mRNA microarrays to detect the differentially expressed genes (DEGs). DEGs were validated in OSCC clinical tissue microarrays using immunohistochemistry method. Whole transcriptome sequencing was performed to obtain an overview of biological functions of Lsm12. PCR assay and sequencing were employed to investigate the alternative splicing of genes regulated by Lsm12. Cell proliferation, colony formation, Transwell migration and invasion assay and in vivo tumor formation assay were performed to investigate the roles of Lsm12 and two transcript variants of USO1 in OSCC cells.

Results

Lsm12 was identified to be significantly up-regulated in the animal model of OSCC tumorigenesis, which was validated in the clinical OSCC samples. In the paired normal tissues, Lsm12 staining was negative (91%, 92/101) or weak, while in OSCC tissues, positive rate is 100% and strong staining spread over the whole tissues in 93 (93/101, 92%) cases. Lsm12 overexpression significantly promoted OSCC cell growth, colony formation, migration and invasion abilities, while Lsm12 knockdown showed the opposite trends on these phenotypes and obviously inhibited the tumor formation in vivo. Furthermore, Lsm12 overexpression caused the inclusion of USO1 exon 15 and Lsm12 knockdown induced exon 15 skipping. Exon 15-retained USO1 significantly promoted the malignant phenotypes of OSCC cells when compared with the exon 15-deleted USO1.

Conclusions

We identified Lsm12, a novel tumorigenesis-related gene, as an important regulator involved in OSCC tumorigenesis. Lsm12 is a novel RNA-splicing related gene and can regulate the alternative splicing of USO1 exon 15 which was associated closely with OSCC carcinogenesis. Our findings thus provide that Lsm12 might be a potent biomarker and potential therapeutic target for OSCC.

Construction of the prognostic signature of alternative splicing revealed the prognostic predictor and immune microenvironment in head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinoma (HNSC) is a prevalent and heterogeneous malignancy with poor prognosis and high mortality rates. There is significant evidence of alternative splicing (AS) contributing to tumor development, suggesting its potential in predicting prognosis and therapeutic efficacy. This study aims to establish an AS-based prognostic signature in HNSC patients.

Methods: The expression profiles and clinical information of 486 HNSC patients were downloaded from the TCGA database, and the AS data were downloaded from the TCGA SpliceSeq database. The survival-associated AS events were identified by conducting a Cox regression analysis and utilized to develop a prognostic signature by fitting into a LASSO-regularized Cox regression model. Survival analysis, univariate and multivariate Cox regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to evaluate the signature and an independent cohort was used for validation. The immune cell function and infiltration were analyzed by CIBERSORT and the ssGSEA algorithm.

Results: Univariate Cox regression analysis identified 2726 survival-associated AS events from 1714 genes. The correlation network reported DDX39B, PRPF39, and ARGLU1 as key splicing factors (SF) regulating these AS events. Eight survival-associated AS events were selected and validated by LASSO regression to develop a prognostic signature. It was confirmed that this signature could predict HNSC outcomes independent of other variables via multivariate Cox regression analysis. The risk score AUC was more than 0.75 for 3 years, highlighting the signature’s prediction capability. Immune infiltration analysis reported different immune cell distributions between the two risk groups. The immune cell content was higher in the high-risk group than in the low-risk group. The correlation analysis revealed a significant correlation between risk score, immune cell subsets, and immune checkpoint expression.

Conclusion: The prognostic signature developed from survival-associated AS events could predict the prognosis of HNSC patients and their clinical response to immunotherapy. However, this signature requires further research and validation in larger cohort studies.

[CircPCSK5 is highly expressed in gastric cancer and promotes cancer cell proliferation, invasion and epithelial-mesenchymal transition]

OBJECTIVE

To investigate the expression of circPCSK5 in gastric cancer (GC) and its role in regulation of the proliferation, invasion and epithelial-mesenchymal transition (EMT) of GC cells.

METHODS

High-throughput sequencing was performed in 3 pairs of GC and adjacent gastric mucosa tissues to obtain the differential expression profile of circRNA. The expression of circPCSK5 was detected in 62 patients undergoing radical surgery for GC using RT-qPCR, and the correlation between circPCSK5 expression level and clinicopathological data of the patients was analyzed. The overall survival and disease-free survival of the patients were assessed with Kaplan-Meier survival analysis, and the independent risk factors affecting the patients' prognosis were analyzed using Cox proportional hazards regression model. The stability and subcellular localization of circPCSK5 were assessed using RNase R and actinomycin D assays, fluorescence in situ hybridization and nucleocytoplasmic separation assay. CCK-8 assay, EdU assay and Transwell assay were employed to examine the changes in proliferation, migration and invasion of GC cells with circPCSK5 knockdown or overexpression; Western blotting and RT-qPCR assays were used to detect the expression levels of EMT markers in the transfected cells.

RESULTS

The expression of circPCSK5 was significantly upregulated in GC tissues and cells (P < 0.001, P < 0.01). The expression level of circPCSK5 was positively correlated with tumor size, vascular invasion, lymph node metastasis and AJCC stage of GC (P < 0.05). The overall survival and disease-free survival were significantly lower in GC patients with high circPCSK5 expression than in those with low circPCSK5 expression (P < 0.001). High circPCSK5 expression was an independent risk factor for a poor prognosis of GC patients (P < 0.05). Knockdown of circPCSK5 significantly inhibited the proliferation, migration and invasion of HGC27 cells (P < 0.01), increased the expressions of E-cadherin, and decreased the expression of N-cadherin and vimentin (P < 0.01). CircPCSK5 overexpression promoted the proliferation, migration and invasion of MKN45 cells (P < 0.01), reduced E-cadherin expression and increased N-cadherin and vimentin expressions (P < 0.01).

CONCLUSION

CircPCSK5 is highly expressed in GC and promotes the proliferation, invasion and EMT of GC cells, suggesting its potential as a prognostic biomarker and therapeutic target for GC.

Exosome loaded hydroxyapatite (HA) scaffold promotes bone regeneration in calvarial defect: an in vivo study

In this study, hydroxyapatite (HA) scaffolds were synthesized and characterized, following the osteogenic and angiogenic effects of HA scaffolds with or without endometrial mesenchymal stem stromal cells (hEnSCs) derived Exosomes were investigated in rat animal model with calvaria defect. The X-ray diffraction (XRD) analysis of HA powder formation was confirmed with Joint Corporation of Powder Diffraction Standards (JCPDS) files numbers of 34-0010 and 24-0033A and Ball mill, and sintering manufactured Nano-size particles. Obtained results containing FE-SEM images presented that the surface of scaffolds has a rough and porous structure, which makes them ideal and appropriate for tissue engineering. Additionally, the XRD showed that these scaffolds exhibited a crystallized structure without undergoing phase transformation; meanwhile, manufactured scaffolds consistently release exosomes; moreover, in vivo findings containing hematoxylin-eosin staining, immunohistochemistry, Masson's trichrome staining, and histomorphometric analysis confirmed that our implant has an osteogenic and angiogenic characteristic. So prepared scaffolds containing exosomes can be proposed as a promising substitute in tissue engineering.

IQGAP1 and RNA Splicing in the Context of Head and Neck via Phosphoproteomics

IQGAP1 (IQ motif-containing GTPase-activating protein 1) scaffolds several signaling pathways in mammalian cells that are implicated in carcinogenesis, including the RAS and PI3K pathways that involve multiple protein kinases. IQGAP1 has been shown to promote head and neck squamous cell carcinoma (HNSCC); however, the underlying mechanism(s) remains unclear. Here, we report a mass spectrometry-based analysis identifying differences in phosphorylation of cellular proteins in vivo and in vitro in the presence or absence of IQGAP1. By comparing the esophageal phosphoproteome profiles between Iqgap1+/+ and Iqgap1-/- mice, we identified RNA splicing as one of the most altered cellular processes. Serine/arginine-rich splicing factor 6 (SRSF6) was the protein with the most downregulated levels of phosphorylation in Iqgap1-/- tissue. We confirmed that the absence of IQGAP1 reduced SRSF6 phosphorylation both in vivo and in vitro. We then expanded our analysis to human normal oral keratinocytes. Again, we found factors involved in RNA splicing to be highly altered in the phosphoproteome profile upon genetic disruption of IQGAP1. Both the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Cancer Genome Atlas (TCGA) data sets indicate that phosphorylation of splicing-related proteins is important in HNSCC prognosis. The Biological General Repository for Interaction Datasets (BioGRID) repository also suggested multiple interactions between IQGAP1 and splicing-related proteins. Based on these collective observations, we propose that IQGAP1 regulates the phosphorylation of splicing proteins, which potentially affects their splicing activities and, therefore, contributes to HNSCC. Raw data are available from the MassIVE database with identifier MSV000087770.

Immune Infiltration-Related ceRNA Network Revealing Potential Biomarkers for Prognosis of Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC.

Materials and Methods

ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed.

Results

Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress.

Conclusion

In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Prognostic alternative splicing events related splicing factors define the tumor microenvironment and pharmacogenomic landscape in lung adenocarcinoma

Background: Recent studies identified correlations between splicing factors (SFs) and tumor progression and therapy. However, the potential roles of SFs in immune regulation and the tumor microenvironment (TME) remain unknown.

Methods: We used UpSet plots to screen for prognostic-related alternative splicing (AS) events. We evaluated SF patterns in specific immune landscapes. Single sample gene set enrichment analysis (ssGSEA) algorithms were used to quantify relative infiltration levels in immune cell subsets. Principal component analysis (PCA) algorithm-based SFscore were used to evaluate SF patterns in individual tumors with an immune response.

Results: From prognosis-related AS events, 16 prognosis-related SFs were selected to construct three SF patterns. Further TME analyses showed these patterns were highly consistent with immune-inflamed, immune-excluded, and immune-desert landscapes. Based on SFscore constructed using differentially expressed genes (DEGs) between SF patterns, patients were classified into two immune-subtypes associated with differential pharmacogenomic landscapes and cell features. A low SFscore was associated with high immune cell infiltration, high tumor mutation burden (TMB), and elevated expression of immune check points (ICPs), indicating a better immune response.

Conclusions: SFs are significantly associated with TME remodeling. Evaluating different SF patterns enhances our understanding of the TME and improves effective immunotherapy strategies.

Metabolic heterogeneity protects metastatic mucosal melanomas cells from ferroptosis

Cancer heterogeneity has been proposed to be one of the main causes of metastatic dissemination and therapy failure. However, the underlying mechanisms of this phenomenon remain poorly understood. Melanoma is an aggressive malignancy with a high heterogeneity and metastatic potential. Therefore, the present study investigated the possible association between cancer heterogeneity and metastasis in melanoma. In total, two novel Chinese oral mucosal melanoma (COMM) cell lines, namely COMM-1 and COMM-2, were established for exploring methods into preventing the loss of cellular heterogeneity caused by long-term cell culture. Each cell line was grown under two different models of culture, which yielded two subtypes, one exhibited an adhesive morphology (COMM-AD), whereas the other was grown in suspension (COMM-SUS). Compared with the COMM-AD cells, the COMM-SUS cells exhibited higher metastatic capacities and autofluorescence. Further investigations indicated that the COMM-SUS cells exhibited metabolic reprogramming by taking up lactate produced by COMM-AD cells at increased levels to accumulate NADH through monocarboxylate transporter 1, whilst also increasing NADPH levels through the pentose phosphate pathway (PPP). Additionally, increased NADH and NADPH levels in the COMM-SUS cells, coupled with the upregulation of the anti-ferroptotic proteins, glutathione peroxidase 4 and ferroptosis suppressor protein 1, enabled them to resist ferroptotic cell death induced by oxidative stress during hematogenous dissemination. The inhibition of ferroptosis was found to substantially increase the metastatic capacity of COMM-AD cells. Furthermore, suppressing lactate uptake and impairing PPP activation significantly decreased the metastatic potential of the COMM-SUS cells. Thus, the present study on metabolic heterogeneity in COMM cells potentially provides a novel perspective for exploring this mechanism underlying cancer metastasis.

N6-methyladenosine RNA methylation regulator-related alternative splicing gene signature as prognostic predictor and in immune microenvironment characterization of patients with low-grade glioma

Background: N6-methyladenosine (m6A) RNA methylation is an important epigenetic modification affecting alternative splicing (AS) patterns of genes to regulate gene expression. AS drives protein diversity and its imbalance may be an important factor in tumorigenesis. However, the clinical significance of m6A RNA methylation regulator-related AS in the tumor microenvironment has not been investigated in low-grade glioma (LGG).

Methods: We used 12 m6A methylation modulatory genes (WTAP, FTO, HNRNPC, YTHDF2, YTHDF1, YTHDC2, ALKBH5, YTHDC1, ZC3H13, RBM15, METTL14, and METTL3) from The Cancer Genome Atlas (TCGA) database as well as the TCGA-LGG (n = 502) dataset of AS events and transcriptome data. These data were downloaded and subjected to machine learning, bioinformatics, and statistical analyses, including gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Univariate Cox, the Least Absolute Shrinkage and Selection Operator (LASSO), and multivariable Cox regression were used to develop prognostic characteristics. Prognostic values were validated using Kaplan-Maier survival analysis, proportional risk models, ROC curves, and nomograms. The ESTIMATE package, TIMER database, CIBERSORT method, and ssGSEA algorithm in the R package were utilized to explore the role of the immune microenvironment in LGG. Lastly, an AS-splicing factor (SF) regulatory network was examined in the case of considering the role of SFs in regulating AS events.

Results: An aggregate of 3,272 m6A regulator-related AS events in patients with LGG were screened using six machine learning algorithms. We developed eight AS prognostic characteristics based on splice subtypes, which showed an excellent prognostic prediction performance. Furthermore, quantitative prognostic nomograms were developed and showed strong validity in prognostic prediction. In addition, prognostic signatures were substantially associated with tumor immune microenvironment diversity, ICB-related genes, and infiltration status of immune cell subtypes. Specifically, UGP2 has better promise as a prognostic factor for LGG. Finally, splicing regulatory networks revealed the potential functions of SFs.

Conclusion: The present research offers a novel perspective on the role of AS in m6A methylation. We reveal that m6A methylation regulator-related AS events can mediate tumor progression through the immune-microenvironment, which could serve as a viable biological marker for clinical stratification of patients with LGG so as to optimize treatment regimens.

Landscape of Alternative Splicing Events Related to Prognosis and Immune Infiltration in Glioma: A Data Analysis and Basic Verification

Background

Glioma is a prevalent primary brain cancer with high invasiveness and typical local diffuse infiltration. Alternative splicing (AS), as a pervasive transcriptional regulatory mechanism, amplifies the coding capacity of the genome and promotes the progression of malignancies. This study was aimed at identifying AS events and novel biomarkers associated with survival for glioma.

Methods

RNA splicing patterns were collected from The Cancer Genome Atlas SpliceSeq database, followed by calculating the percentage of splicing index. Expression profiles and related clinical information of glioma were integrated based on the UCSC Xena database. The AS events in glioma were further analyzed, and glioma prognosis-related splicing factors were identified with the use of bioinformatics analysis and laboratory techniques. Further immune infiltration analysis was performed.

Results

Altogether, 9028 AS events were discovered. Upon univariate Cox analysis, 425 AS events were found to be related to the survival of patients with glioma, and 42 AS events were further screened to construct the final prognostic model (area under the curve = 0.974). Additionally, decreased expression of the splicing factors including Neuro-Oncological Ventral Antigen 1 (NOVA1), heterogeneous nuclear ribonucleoprotein C (HNRNPC), heterogeneous nuclear ribonucleoprotein L-like protein (HNRNPLL), and RNA-Binding Motif Protein 4 (RBM4) contributed to the poor survival in glioma. The immune infiltration analysis demonstrated that AS events were related to the proportion of immune cells infiltrating in glioma.

Conclusions

It is of great value for comprehensive consideration of AS events, splicing networks, and related molecular subtype clusters in revealing the underlying mechanism and immune microenvironment remodeling for glioma, which provides clues for the further verification of related therapeutic targets.

Tumor cell-derived exosome RNF126 affects the immune microenvironment and promotes nasopharyngeal carcinoma progression by regulating PTEN ubiquitination

This study aimed to investigate the role and regulatory mechanism of RNF126 in nasopharyngeal carcinoma. Firstly, the expression and prognosis of RNF126 were analyzed by TCGA database. The expression of RNF126 was further verified by NPC tissue samples and cells. An ectopic xenograft model was constructed to verify the regulatory role of RNF126 in NPC tumor progression. The regulatory effect of RNF126 on macrophage polarization and migration was verified by co-culture of tumor cells and THP-1 cells. The role of RNF126 in tumor exosomes involved in intercellular communication was further verified by nanoparticle tracking technology, western blotting and immunofluorescence assays. QRT-PCR, half-life assay and WB assay were used to verify the regulatory effect of RNF126 on PTEN ubiquitination and PI3K/AKT pathway. Finally, an in vivo assay was used to verify the regulation of exosomes on tumor growth and metastasis. In summary, we found for the first time that tumor-derived exosomal PTEN degrades PTEN through ubiquitination to regulate the tumor immune microenvironment and promote NPC growth and metastasis. These results provide the basis for the screening of early markers of NPC and targeted therapy.

Immunological Characteristics of Alternative Splicing Profiles Related to Prognosis in Bladder Cancer

Several studies have found that pathological imbalance of alterative splicing (AS) events is associated with cancer susceptibility. carcinogenicity. Nevertheless, the relationship between heritable variation in AS events and carcinogenicity has not been extensively explored. Here, we downloaded AS event signatures, transcriptome profiles, and matched clinical information from The Cancer Genome Atlas (TCGA) database, identified the prognostic AS-related events via conducting the univariate Cox regression algorism. Subsequently, the prognostic AS-related events were further reduced by the least absolute shrinkage and selection operator (LASSO) logistic regression model, and employed for constructing the risk model. Single-sample (ssGSEA), ESTIMATE, and the CIBERSORT algorithms were conducted to evaluate tumor microenvironment status. CCK8, cell culture scratch, transwell invasion assays and flow cytometry were conducted to confirm the reliability of the model. We found 2751 prognostic-related AS events, and constructed a risk model with seven prognostic-related AS events. Compared with high-risk score patients, the overall survival rate of the patients with low-risk score was remarkably longer. Besides, we further found that risk score was also closely related to alterations in immune cell infiltration and immunotherapeutic molecules, indicating its potential as an observation of immune infiltration and clinical response to immunotherapy. In addition, the downstream target gene (DYM) could be a promising prognostic factor for bladder cancer. Our investigation provided an indispensable reference for ulteriorly exploring the role of AS events in the tumor microenvironment and immunotherapy efficiency, and rendered personalized prognosis monitoring for bladder cancer.

Genome-Wide Identification of Immune-Related Alternative Splicing and Splicing Regulators Involved in Abdominal Aortic Aneurysm

The molecular mechanism of AAA formation is still poorly understood and has not been fully elucidated. The study was designed to identify the immune-related genes, immune-RAS in AAA using bioinformatics methods. The GSE175683 datasets were downloaded from the GEO database. The DEseq2 software was used to identify differentially expressed genes (DEGs). SUVA pipeline was used to quantify AS events and RAS events. KOBAS 2.0 server was used to identify GO terms and KEGG pathways to sort out functional categories of DEGs. The CIBERSORT algorithm was used with the default parameter for estimating immune cell fractions. Nine samples from GSE175683 were used to construct the co-disturbed network between expression of SFs and splicing ratio of RAS events. PCA analysis was performed by R package factoextra to show the clustering of samples, and the pheatmap package in R was used to perform the clustering based on Euclidean distance. The results showed that there were 3,541 genes significantly differentially expressed, of which 177 immune-related genes were upregulated and 48 immune-related genes were downregulated between the WT and WTA group. Immune-RAS events were mainly alt5P and IR events, and about 60% of it was complex splicing events in AAA. The WT group and the WTA group can be clearly distinguished in the first principal component by using the splicing ratio of immune-RAS events. Two downregulated genes, Nr4a1 and Nr4a2, and eight upregulated genes, Adipor2, Akt2, Bcl3, Dhx58, Pparg, Ptgds, Sytl1, and Vegfa were identified among the immune-related genes with RAS and DEGs. Eighteen differentially expressed SFs were identified and displayed by heatmap. The proportion of different types of cells and ratio of the average ratio of different cells were quite different. Both M1 and M2 types of macrophages and plasma cells were upregulated, while M0 type was downregulated in AAA. The proportion of plasma cells in the WTA group had sharply increased. There is a correlation between SF expression and immune cells/immune-RAS. Sf3b1, a splicing factor with significantly different expression, was selected to bind on a mass of immune-related genes. In conclusion, our results showed that immune-related genes, immune-RAS, and SFs by genome-wide identification were involved in AAA.

Immunological significance of alternative splicing prognostic signatures for bladder cancer

Background

Bladder cancer (BLCA) is the most common malignant tumor in the genitourinary system, and the complex tumor microenvironment (TME) of BLCA is the main factor in its difficult treatment. Accumulated evidence supports that alternative splicing (AS) events frequently occur in cancer and are closely related to the TME. Therefore, there is an urgent need to comprehensively analyze the prognostic value of AS events in BLCA.

Method

The clinical, transcriptome and AS data of BLCA were downloaded from the Cancer Genome Atlas database, and a Cox proportional hazard regression model and LASSO regression were used to establish a prognostic signature. Then, the prognostic value of the signature was verified by clinical survival status, clinicopathologic features, tumor immune microenvironment (TIME), and immune checkpoint. Next, we screened the AS-related genes with the largest expression differences between tumor and normal samples by gene differential expression analysis. Finally, the regulatory network of AS-splicing factors (SFs) was established to unravel the potential regulatory mechanism of AS events in BLCA.

Results

A BLCA prognostic signature related to seven AS events was constructed, and the prognostic value of the signature was also verified from multiple perspectives. Moreover, there was significant abnormal expression of PTGER3, a gene implicated in AS events, the expression of which was associated with the survival, clinicopathological features, TIME, and immunotherapy of BLCA, suggesting that it has potential clinical application value. Furthermore, the AS-SF regulatory network indicated that splicing factors (PRPF39, LUC7L, HSPA8 and DDX21) might be potential biomarkers of BLCA.

Conclusions

Our study revealed the potential role of AS events in the prognosis, TIME and immunotherapy of BLCA and yielded new insights into the molecular mechanisms of and personalized immunotherapy for BLCA.

Immune-related lncRNA classification of head and neck squamous cell carcinoma

Background

Long noncoding RNAs (lncRNAs) play a critical role in innate and adaptive immune responses. Thus, we aimed to identify ideal subtypes for head and neck squamous cell carcinoma (HNSCC) based on immune-related lncRNAs.

Methods

TCGA HNSCC cohort was divided into two datasets (training and validation dataset), and 960 previously characterized immune-related lncRNAs were extracted for non-negative matrix factorization analysis. We characterized our HNSCC subtypes based on biological behaviors, immune landscape and response to immunotherapy in both training and validation cohort. A lncRNA-signature was generated to predict our HNSCC subtypes, and essential lncRNAs involved in tumor microenvironment (TME) were identified.

Results

We developed and validated two HNSCC subtypes (C1 and C2) based on the 70 lncRNAs in the training and validation cohort. C2 subtype displayed good prognosis, high immune cell infiltration, immune-related genes expression and sensitivity to PD-1 blockade. C1 subtype was associated with high activity of mTORC1 signaling and glycolysis as well as high fraction of inactive immune cells. Finally, we generated a 31-lncRNA signature that could predict our above subtypes with high accurate. Additionally, TRG-AS1 was identified as the essential lncRNA involving TME formation. Knockdown of TRG-AS1 inhibited the expression of HLA-A, HLA-B, HLA-C, CXCL9, CXCL10 and CXCL11. High expression of TRG-AS1 indicated a favorable prognosis in HNSCC and anti-PD-L1 cohort (IMvigor210).

Conclusions

Our study establishes a novel HNSCC classification on the basis of 31-lncRNA, helping to identify beneficiaries for anti-PD-1 treatment. In addition, a critical lncRNA TRG-AS1 is identified as a new potential prognosis biomarker as well as therapeutic target.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02450-z.

Systemic characterization of alternative splicing related to prognosis, immune infiltration, and drug sensitivity analysis in ovarian cancer

Background

Alternative splicing (AS) plays an essential role in tumorigenesis and progression. This study intended to construct an innovative prognostic model based on AS events to gain more precise survival prediction and search for potential therapeutic targets in ovarian cancer.

Methods

Seven types of AS events in ovarian serous cystadenocarcinoma (OV) patients with RNA-seq were obtained using The Cancer Genome Atlas (TCGA) SpliceSeq tool and database. Cox and Kaplan-Meier curve analyses were employed to establish the prognostic models. Relying on drug sensitivity data from the CellMiner database, Genomics of Drug Sensitivity (GDS) was adopted to estimate the platinum-sensitive analysis. Furthermore, a prognostic splicing factor (SF)-AS network was constructed using Cytoscape. Finally, in order to explore the influence of the tumor microenvironment on the prognosis of OV patients, we first combined a similar network fusion and consensus clustering (SNF-CC) algorithm to identify three OV subtypes based on survival-related AS events and then utilized single-sample Gene Set Enrichment Analysis (ssGSEA) method to perform immune cell infiltration analysis.

Results

A total of 48,049 AS events and 21,841 related genes were selected from 318 OV samples, and 2,206 AS events associated with disease-free survival (DFS) were identified. Multivariate Cox and Kaplan-Meier curve analyses were then employed to establish the prognostic models. Receiver operating characteristic (ROC) analysis from 0.59 to 0.75 showed that these models were highly efficient in distinguishing patient survival. GDS was adopted with the CellMiner database to provide some insights for platinum-sensitive analysis of OV. Furthermore, a prognostic SF-AS network, which discovered a significant connection between SFs and prognostic AS genes, was constructed using Cytoscape. The combined SNF-CC algorithm revealed three distinct OV subtypes based on the prognostic AS events, and the associations between this novel molecular classification and immune cell infiltration were further explored.

Conclusions

We developed a powerful prognostic AS signature for OV and provided a deeper understanding of SF-AS network regulatory mechanisms, as well as platinum-sensitive and cancer immune microenvironments. These results revealed various candidate biomarkers and potential targets for OV treatment strategies.

Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer

Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable model to predict patients’ outcomes. Public database including The Cancer Genome Atlas (TCGA), TCGA SpliceSeq, and the Genomics of Drug Sensitivity in Cancer databases were used to detect the AS expression, immune cell infiltration and IC50. The prognosis-related AS model was constructed and validated by using Cox regression, LASSO regression, C-index, calibration plots, and ROC curves. A total of eight AS events (including FLT3LG|50942|AP) were selected to establish the prognosis-related AS model. Compared with high-risk group, low-risk group had a better outcome (P = 1.794e-06), was more sensitive to paclitaxel (P = 0.022), and higher proportions of plasma cells. We explored the upstream regulatory mechanisms of prognosis-related AS and found that two splicing factor and 156 tag single nucleotide polymorphisms may be involved in the regulation of prognosis-related AS. In order to assess patient prognosis more comprehensively, we constructed a clinically applicable model combining risk score and clinicopathological features, and the 1 -, and 3-year AUCs of the clinically applicable model were 0.812, and 0.726, which were 7.5% and 3.3% higher than that of the risk score. We constructed a prognostic signature for OV patients and comprehensively analysed the regulatory characteristics of the prognostic AS events in OV.

Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

Objectives

Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients.

Methods and Results

Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis.

Conclusions

We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.

Loss of TACC1 variant25 inducing cell proliferation and suppressing autophagy in head and neck squamous carcinoma

Transforming acidic coiled-coil containing protein1 (TACC1) is closely related to transcription, translation and centrosome dynamics. Dysregulation of TACC1 is associated with multiple malignancies. Alternative splicing (AS) of TACC1 produces multiple variants, which are of great significance in cancer biology. However, the expression and biological functions of TACC1 variants in head and neck squamous cell carcinoma (HNSCC) remain unclear. In this study, we found for the first time that TACC1 variants exhibited a characteristic expression pattern and that TACC1 variant25 (TACC1v25) was downregulated in HNSCC tissues and cell lines. Overexpression of TACC1v25 in Cal27 and Fadu cells significantly inhibited proliferation and promoted autophagy. Moreover, expression levels of nuclear pERK and p-mTOR were significantly decreased, while the expression of Beclin-1 and the LC3II/LC3I ratio were increased in TACC1v25-overexpressed Cal27 and Fadu cells. After the addition of AKT activator SC79 to TACC1v25-overexpressed Cal27 and Fadu cells, the autophagy levels were remarkably rescued. In conclusion, TACC1v25 inhibits HNSCC progression through the ERK and AKT/mTOR pathways by inhibiting proliferation and increasing autophagy. TACC1v25 might have potential use as a tumour suppressor in HNSCC.

The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment

Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.

Systematic Genome-Wide Profiles Reveal Alternative Splicing Landscape and Implications of Splicing Regulator DExD-Box Helicase 21 in Aggressive Progression of Adrenocortical Carcinoma

Alternative splicing (AS) in the tumor biological process has provided a novel perspective on carcinogenesis. However, the clinical significance of individual AS patterns of adrenocortical carcinoma (ACC) has been underestimated, and in-depth investigations are lacking. We selected 76 ACC samples from the Cancer Genome Atlas (TCGA) SpliceSeq and SpliceAid2 databases, and 39 ACC samples from Fudan University Shanghai Cancer Center (FUSCC). Prognosis-related AS events (PASEs) and survival analysis were evaluated based on prediction models constructed by machine-learning algorithm. In total, 23,984 AS events and 3,614 PASEs were detected in the patients with ACC. The predicted risk score of each patient suggested that eight PASEs groups were significantly correlated with the clinical outcomes of these patients (p < 0.001). Prognostic models produced AUC values of 0.907 in all PASEs' groups. Eight splicing factors (SFs), including BAG2, CXorf56, DExD-Box Helicase 21 (DDX21), HSPB1, MBNL3, MSI1, RBMXL2, and SEC31B, were identified in regulatory networks of ACC. DDX21 was identified and validated as a novel clinical promoter and therapeutic target in 115 patients with ACC from TCGA and FUSCC cohorts. In conclusion, the strict standards used in this study ensured the systematic discovery of profiles of AS events using genome-wide cohorts. Our findings contribute to a comprehensive understanding of the landscape and underlying mechanism of AS, providing valuable insights into the potential usages of DDX21 for predicting prognosis for patients with ACC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-021-00026-x.

Identification of tumour immune microenvironment-related alternative splicing events for the prognostication of pancreatic adenocarcinoma

PURPOSE

Pancreatic adenocarcinoma (PAAD) is characterized by low antitumour immune cell infiltration in an immunosuppressive microenvironment. This study aimed to systematically explore the impact on prognostic alternative splicing events (ASs) of tumour immune microenvironment (TIME) in PAAD.

METHODS

The ESTIMATE algorithm was implemented to compute the stromal/immune-related scores of each PAAD patient, followed by Kaplan-Meier (KM) survival analysis of patients with different scores grouped by X-tile software. TIME-related differentially expressed ASs (DEASs) were determined and evaluated through functional annotation analysis. In addition, Cox analyses were implemented to construct a TIME-related signature and an AS clinical nomogram. Moreover, comprehensive analyses, including gene set enrichment analysis (GSEA), immune infiltration, immune checkpoint gene expression, and tumour mutation were performed between the two risk groups to understand the potential mechanisms. Finally, Cytoscape was implemented to illuminate the AS-splicing factor (SF) regulatory network.

RESULTS

A total of 437 TIME-related DEASs significantly related to PAAD tumorigenesis and the formation of the TIME were identified. Additionally, a robust TIME-related prognostic signature based on seven DEASs was generated, and an AS clinical nomogram combining the signature and four clinical predictors also exhibited prominent discrimination by ROC (0.762 ~ 0.804) and calibration curves. More importantly, the fractions of CD8 T cells, regulatory T cells and activated memory CD4 T cells were lower, and the expression of four immune checkpoints-PD-L1, CD47, CD276, and PVR-was obviously higher in high-risk patients. Finally, functional analysis and tumour mutations revealed that aberrant immune signatures and activated carcinogenic pathways in high-risk patients may be the cause of the poor prognosis.

CONCLUSION

We extracted a list of DEASs associated with the TIME through the ESTIMATE algorithm and constructed a prognostic signature on the basis of seven DEASs to predict the prognosis of PAAD patients, which may guide advanced decision-making for personalized precision intervention.

Analysis of Prognostic Alternative Splicing Reveals the Landscape of Immune Microenvironment in Thyroid Cancer

Background

The incidence of thyroid cancer (THCA) continues to increase in recent decades. Accumulating evidence showed that the unbalanced alternative splicing (AS) promotes the occurrence of cancers and leads to poor prognosis of patients. However, the research on alternative splicing events in THCA is lacking, and its underlying mechanism is not fully understood. This study identifies a novel prognostic signature based on AS events to reveal the relationship of AS with tumor immune microenvironment.

Methods

Based on the AS data, transcriptional data, and clinical information, the differentially expressed alternative splicings (DEASs) were screened out. Least absolute shrinkage and selection operator (LASSO) regression and multi-Cox regression analyses were employed to identify prognostic results related to AS events and establish a prognostic signature. The predictive ability of the signature was assessed by Kaplan-Meier (K-M) survival curve, risk plots, and receiver operating characteristic (ROC) curves. Furthermore, correlations between tumor-infiltrating immune cells, immune checkpoints, immune score and prognostic signature were analyzed.

Results

According to the LASSO regression analysis, a total of five AS events were selected to construct the signature. K-M survival curve showed that the higher the risk score, the worse the OS of the patients. Risk plots further confirmed this result. ROC curves indicated the high predictive efficiency of the prognostic signature. As for tumor immune microenvironment, patients in the high-risk group had a higher proportion of immune cells, including plasma cell, CD8+ T cell, macrophages (M0 and M2), and activated dendritic cell. Immune checkpoint proteins, such as PDCD1LG2, HAVCR2, CD274, etc., were significantly higher in the high-risk group. We also found that the ESTIMATE score, stromal score, and immune score were lower in the high-risk group, while the result of tumor purity was the opposite.

Conclusions

Collectively, a prognostic signature consisting of five AS events in THCA was established. Furthermore, there was an inextricable correlation between immune cell infiltration, immune checkpoint proteins, and AS events. This study will provide a basis for THCA immunotherapy in the future.

Comprehensive analysis of aberrant alternative splicing related to carcinogenesis and prognosis of papillary thyroid cancer

As a key mechanism, alternative splicing (AS) plays a role in the cancer initiation and development. However, in papillary thyroid cancer (PTC), data for the comprehensive AS event profile and its clinical implications are lacking. Herein, a genome-wide AS event profiling using RNA-Seq data and its correlation with matched clinical information was performed using a 389 PTC patient cohort from the project of The Cancer Genome Atlas (TCGA). We identified 1,925 cancer-associated AS events (CASEs) by comparing paired tumors and neighboring healthy tissues. Parent genes with CASEs remarkably enriched in the pathways were linked with carcinogenesis, such as P53, KRAS, IL6-JAK-STAT3, apoptosis, and MYC signaling. The regulatory networks of AS implied an obvious correlation between the expression of splicing factor and CASE. We identified eight CASEs as predictors for overall survival (OS) and disease-free survival (DFS). The established risk score model based on DFS-associated CASEs successfully predicted the prognosis of PTC patients. From the unsupervised clustering analysis results, it is found that different clusters based on AS correlated with prognosis, molecular features, and immune characteristics. Taken together, the comprehensive genome-wide AS landscape analysis in PTC showed new AS events linked with tumorigenesis and prognosis, which provide new insights for clinical monitoring and therapy for PTC.

Prognostic association of starvation-induced gene expression in head and neck cancer

Autophagy-related genes (ARGs) have been implicated in the initiation and progression of malignant tumor promotion. To investigate the dynamics of expression of genes, including ARGs, head and neck squamous cell carcinoma (HNSCC) cells were placed under serum-free conditions to induce growth retardation and autophagy, and these starved cells were subjected to transcriptome analysis. Among the 21 starvation-induced genes (SIGs) located in the autophagy, cell proliferation, and survival signaling pathways, we identified SIGs that showed prominent up-regulation or down-regulation in vitro. These included AGR2, BST2, CALR, CD22, DDIT3, FOXA2, HSPA5, PIWIL4, PYCR1, SGK3, and TRIB3. The Cancer Genome Atlas (TCGA) database of HNSCC patients was used to examine the expression of up-regulated genes, and CALR, HSPA5, and TRIB3 were found to be highly expressed relative to solid normal tissue in cancer and the survival rate was reduced in patients with high expression. Protein-protein interaction analysis demonstrated the formation of a dense network of these genes. Cox regression analysis revealed that high expression of CALR, HSPA5, and TRIB3 was associated with poor prognosis in patients with TCGA-HNSCC. Therefore, these SIGs up-regulated under serum starvation may be molecular prognostic markers in HNSCC patients.

Role of IQGAP1 in Carcinogenesis

Scaffolding proteins can play important roles in cell signaling transduction. IQ motif-containing GTPase-activating protein 1 (IQGAP1) influences many cellular activities by scaffolding multiple key signaling pathways, including ones involved in carcinogenesis. Two decades of studies provide evidence that IQGAP1 plays an essential role in promoting cancer development. IQGAP1 is overexpressed in many types of cancer, and its overexpression in cancer is associated with lower survival of the cancer patient. Here, we provide a comprehensive review of the literature regarding the oncogenic roles of IQGAP1. We start by describing the major cancer-related signaling pathways scaffolded by IQGAP1 and their associated cellular activities. We then describe clinical and molecular evidence for the contribution of IQGAP1 in different types of cancers. In the end, we review recent evidence implicating IQGAP1 in tumor-related immune responses. Given the critical role of IQGAP1 in carcinoma development, anti-tumor therapies targeting IQGAP1 or its associated signaling pathways could be beneficial for patients with many types of cancer.

A Novel Immune-Related Prognostic Signature in Head and Neck Squamous Cell Carcinoma

The immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, very limited robust and reliable immunological biomarkers have been developed that are capable of estimating prognosis in HNSCC patients. In this study, we aimed to identify the effects of novel immune-related gene signatures (IRGs) that can predict HNSCC prognosis. Based on gene expression profiles and clinical data of HNSCC patient cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, a total of 439 highly variable expressed immune-related genes (including 239 upregulated and 200 downregulated genes) were identified by using differential gene expression analysis. Pathway enrichment analysis indicated that these immune-related differentially expressed genes were enriched in inflammatory functions. After process screening in the training TCGA cohort, six immune-related genes (PLAU, STC2, TNFRSF4, PDGFA, DKK1, and CHGB) were significantly associated with overall survival (OS) based on the LASSO Cox regression model. Integrating these genes with clinicopathological features, a multivariable model was built and suggested better performance in determining patients’ OS in the testing cohort, and the independent validation cohort. In conclusion, a well-established model encompassing both immune-related gene signatures and clinicopathological factors would serve as a promising tool for the prognostic prediction of HNSCC.

Construction of Two Alternative Polyadenylation Signatures to Predict the Prognosis of Sarcoma Patients

Background

Increasing evidence indicates that alternative polyadenylation (APA) is associated with the prognosis of cancers.

Methods

We obtained gene expression and APA profiles of 259 sarcoma patients from the TCGA dataportal and TC3A database, respectively. The prognostic signatures, clinical nomograms, and regulatory networks were studied by integrated bioinformatics analyses. Then, the immune cell infiltration profile was obtained from the ImmuCellAI. The association between APA-based signature and immune cells was studied.

Results

A total of 61 and 38 APA events were identified as overall survival (OS)- and progress free-survival (PFS)-related biomarkers, respectively. Two signatures were generated. The area under the curves (AUC) values of OS signature were 0.900, 0.928, and 0.963 over 2-, 4-, and 6-years, respectively. And the AUC values of PFS signature at 2-, 4-, and 6-years were 0.826, 0.840, and 0.847, respectively. Overall and subgroup analyses indicated that high-risk patients had a worse prognosis than low-risk patients (all p-values < 0.05). In addition, immunomics analyses indicated that there are different patterns of immune cell infiltration between low- and high-risk patients. Furthermore, two clinical-APA nomograms were established and the C-indexes were 0.813 and 0.809 for OS nomogram and PFS nomogram, respectively. Finally, two APA regulatory networks were constructed. FIP1L1-VPS26B was identified as a key regulating relationship and validated in the pan-cancer analyses.

Conclusion

In this study, we identified prognostic predictors based on APA events with high accuracy for risk stratification in sarcoma patients and uncovered interesting regulatory networks in sarcoma that could be underlying mechanisms. This study not only provides novel potential prognostic biomarkers but promote precision medicine and provide potential novel research interests for immunotherapy.

Identification and Validation of a Prognostic Immune-Related Alternative Splicing Events Signature for Glioma

Background

Glioma is the most common malignant brain tumor in adults, with its tumor-promoting immune microenvironment always being intricate to handle with. Amounts of evidence has accumulated to suggest that alternative splicing (AS) is related to tumor immune microenvironment. However, comprehensive analysis of immune-related AS events and their clinical significance are still lacking in glioma.

Methods

AS events and transcriptome data of 653 glioma patients were downloaded online. ssGSEA was performed on transcriptome data of 653 patients to divided them into low, medium and high immune cell infiltration groups. Immune-related AS events were filtrated based on this grouping. Then lasso Cox regression analysis and multivariate Cox regression analysis were done to achieve an immune-related AS events prognostic signature for glioma. Kaplan-Meier analysis, ROC analyses, univariate Cox regression and multivariate Cox regression were performed to reveal the independent prognostic role of this signature. Meanwhile, a nomogram was constructed to achieved better prognostic value for glioma patients. Besides, functional enrichment analyses and correlation analyses with immune cells infiltration were used to validated the immune-related characteristic of this signature.

Results

36 immune-related AS events were achieved based on the grouping mentioned above. A nine-immune-related alternative splicing event signature was built for glioma patients. This signature showed an independent prognostic value and a nomogram containing gender, age, Karnofsky performance score, grade, IDH status, MGMT promoter status and risk score derived from the signature was constructed with a higher predictive ability for overall survival. Association with the infiltration of immune cell subtypes was validated and functional enrichment analysis found that the signature was mainly enriched in immune-related and pro-tumor functions.

Conclusion

Our research presented all immune-related AS events in glioma, identified an immune-related prognostic AS events risk model and a nomogram was constructed to predict the prognosis individually and more precisely. Tight connection was verified between this signature and clinical characteristics. Also, immune cells infiltration and immune checkpoints expression level were proved to link to risk scores, which enhanced the understanding of relationship between AS events and glioma immune microenvironment, firstly revealing the potential role of AS in immunotherapy of glioma.

Alternative Splicing Events in Tumor Immune Infiltration in Colorectal Cancer

Despite extensive research, the exact mechanisms involved in colorectal cancer (CRC) etiology and pathogenesis remain unclear. This study aimed to examine the correlation between tumor-associated alternative splicing (AS) events and tumor immune infiltration (TII) in CRC. We analyzed transcriptome profiling and clinical CRC data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq and Innate databases, respectively to develop and validate a risk model of differential AS events and subsequently a TII risk model. We then conducted a two-factor survival analysis to study the association between TII and AS risk and evaluated the associations between immune signatures and six types of immune cells based on the TIMER database. Subsequently, we studied the distribution of six types of TII cells in high- and low-risk groups for seven AS events and in total. We obtained the profiles of AS events/genes for 484 patients, which included 473 CRC tumor samples and 41 corresponding normal samples, and detected 22581 AS events in 8122 genes. Exon Skip (ES) (8446) and Mutually Exclusive Exons (ME) (74) exhibited the most and fewest AS events, respectively. We then classified the 433 patients with CRC into low-risk (n = 217) and high-risk (n = 216) groups based on the median risk score in different AS events. Compared with patients with low-risk scores (mortality = 11.8%), patients with high-risk scores were associated with poor overall survival (mortality = 27.6%). The risk score, cancer stage, and pathological stage (T, M, and N) were closely correlated with prognosis in patients with CRC (P < 0.001). We identified 6479 differentially expressed genes from the transcriptome profiles of CRC and intersected 468 differential immune-related signatures. High-AS-risk and high-TII-risk predicted a poor prognosis in CRC. Different AS types were associated with different TII risk characteristics. Alternate Acceptor site (AA) and Alternate Promoter (AP) events directly affected the concentration of CD4T cells, and the level of CD8T cells was closely correlated with Alternate Terminator (AT) and Exon Skip (ES) events. Thus, the concentration of CD4T and CD8T cells in the CRC immune microenvironment was not specifically modulated by AS. However, B cell, dendritic cell, macrophage, and neutrophilic cell levels were strongly correlated with AS events. These results indicate adverse associations between AS event risk levels and immune cell infiltration density. Taken together, our findings show a clear association between tumor-associated alternative splicing and immune cell infiltration events and patient outcome and could form a basis for the identification of novel markers and therapeutic targets for CRC and other cancers in the future.

Comprehensive Analysis of Myeloid Signature Genes in Head and Neck Squamous Cell Carcinoma to Predict the Prognosis and Immune Infiltration

Myeloid cells are a major heterogeneous cell population in the tumor immune microenvironment (TIME). Imbalance of myeloid response remains a major obstacle to a favorable prognosis and successful immune therapy. Therefore, we aimed to construct a risk model to evaluate the myeloid contexture, which may facilitate the prediction of prognosis and immune infiltration in patients with head and neck squamous cell carcinoma (HNSCC). In our study, six myeloid signature genes (including CCL13, CCR7, CD276, IL1B, LYVE1 and VEGFC) analyzed from 52 differentially expressed myeloid signature genes were finally pooled to establish a prognostic risk model, termed as myeloid gene score (MGS) in a training cohort and validated in a test cohort and an independent external cohort. Furthermore, based on the MGS subgroups, we were able to effectively identify patients with a poor prognosis, aggressive clinical parameters, immune cell infiltration status and immunotherapy response. Thus, MGS may serve as an effective prognostic signature and predictive indicator for immunotherapy response in patients with HNSCC.