Comprehensive Pan-Cancer Genomic Analysis Reveals PHF19 as a Carcinogenic Indicator Related to Immune Infiltration and Prognosis of Hepatocellular Carcinoma

WTAP-mediated m6A methylation of PHF19 facilitates cell cycle progression by remodeling the accessible chromatin landscape in t(8;21) AML

Wilms' tumor 1-associated protein (WTAP) is a key N6-methyladenosine (m6A) methyltransferase that is upregulated in t(8;21) acute myeloid leukemia (AML) under hypoxia inducible factor 1α-mediated transcriptional activation, promoting leukemogenesis through transcriptome-wide m6A modifications. However, the specific substrates and intrinsic regulatory mechanisms of WTAP are not well understood. Here, we provide evidence that PHD finger protein 19 (PHF19) overexpression is regulated by WTAP-mediated m6A modification and promotes cell cycle progression by altering chromatin accessibility. At the same time, high expression of PHF19 and WTAP in t(8;21) AML patients indicates a worse prognosis. Furthermore, inhibition of PHF19 expression significantly suppresses the growth of t(8;21) AML cells in both in vitro and in vivo. Mechanistically, WTAP enhances the stability of PHF19 mRNA by binding to m6A sites in the 3'-untranslated region, thereby upregulating PHF19 expression. Conversely, WTAP suppression reduces m6A modification levels on the PHF19 transcript, leading to increased instability. Knockdown of PHF19 precipitates loss of H3K27 trimethylation and enhanced chromatin accessibility, ultimately resulting in upregulated expression of genes involved in the cell cycle and DNA damage checkpoints. Therefore, WTAP/m6A-dependent PHF19 upregulation accelerates leukemia progression by coordinating m6A modification and histone methylation, establishing its status as a novel therapeutic target for t(8;21) AML.

Identification of DAP3 as candidate prognosis marker and potential therapeutic target for hepatocellular carcinoma

Background

Among malignant tumors, hepatocellular carcinoma (HCC) is both prevalent and highly lethal. Most patients with advanced-stage liver cancer have a poor prognosis. Death-associated protein 3 (DAP3) is reportedly related to tumors and may hold great promise for the future.

Methods

DAP3 transcriptome data along with related clinical information were obtained from The Cancer Genome Atlas (TCGA), GEO, and ICGC databases. We assessed its prognostic value, clinical relevance, associated pathways, immune infiltration, gene mutations, and sensitivity to chemotherapeutics. A prognostic risk model was subsequently developed and evaluated using receiver operating characteristic (ROC) curves and Kaplan-Meier (KM) plots. Additionally, a nomogram was created and validated through calibration and decision curve analysis (DCA). Furthermore, quantitative real-time PCR (qRT-PCR), Western blot, and immunohistochemical (IHC) staining were performed to examine the expression of DAP3 in HCC. Finally, gene knockdown and overexpression experiments, along with cell counting kit-8 (CCK-8) assays, colony formation assays, and tests for cell apoptosis, migration, and invasion, were conducted to investigate the role of DAP3 in HCC.

Results

The study discovered that DAP3 expression was linked to HCC subtypes, and its high expression was linked to a poor prognosis. There were significant differences in immune infiltration level, mutation level, prognostic value and chemotherapeutic efficacy. Subsequently, we constructed a prognostic model and demonstrated that high risk score was significantly related to a poor survival rate. A predictive nomogram demonstrated that the nomogram model was effective prediction tool that can accurately predict the survival rate of patients with different clinical characteristics. Additionally, DAP3 expression significantly increased in both tissue samples and cell lines. Elevated levels of DAP3 were correlated with larger tumor size and higher alpha-fetoprotein (AFP) levels, and Cox analysis confirmed that DAP3 was a clinically independent prognostic marker. Finally, cell assays revealed that the knockdown of DAP3 significantly impeded cell proliferation and metabolic activity and induced apoptosis. Conversely, the overexpression of DAP3 had opposite effects on these cellular processes.

Conclusions

Our study on DAP3 can provide a reference for HCC diagnosis, treatment and prognosis assessment.

Detecting the Tumor Prognostic Factors From the YTH Domain Family Through Integrative Pan-Cancer Analysis

Objectives

Emerging evidence suggests that N6-methyladenosine (m6A) methylation plays a critical role in cancers through various mechanisms. This work aims to reveal the essential role of m6A methylation "readers" in regulation of cancer prognosis at the pan-cancer level.

Methods

Herein, we focused on one special protein family of the "readers" of m6A methylation, YT521-B homology (YTH) domain family genes, which were observed to be frequently dysregulated in tumor tissues and closely associated with cancer prognosis. Then, a comprehensive analysis of modulation in cancer prognosis was conducted by integrating RNA sequencing (RNAseq) datasets of YTH family genes and clinical information at the pan-cancer level.

Results

YTH family genes were significantly differentially expressed in most of the cancers, particularly increased in Gastrointestinal cancers, and decreased in Endocrine and Urologic cancers. In addition, they were observed to be associated with overall survival (OS) and disease-specific survival (DSS) with various extent, especially in lower grade glioma (LGG), thyroid cancer (THCA), liver hepatocellular carcinoma (LIHC) and kidney clear cell carcinoma (KIRC), so were some "writers" (METLL3, METLL14, WTAP) and "erasers" (FTO, ALKBH5). Further survival analysis illustrated that YTH family genes specifically YTHScore constructed by combining 5 YTH family genes, as well as RWEScore calculated by combining genes from "readers"-"writers"-"erasers" could dramatically distinguish tumor prognosis in 4 representative cancers. As expected, YTHScore presented an equally comparable prognostic classification with RWEScore. Finally, analysis of immune signatures and clinical characteristics implied that, the activity of the innate immune, diagnostic age, clinical stage, Tumor-Node-Metastasis (TNM) stage and immune types, might play specific roles in modulating tumor prognosis.

Conclusions

The study demonstrated that YTH family genes had the potential to predict tumor prognosis, in which the YTHScore illustrated equal ability to predict tumor prognosis compared to RWEScore, thus providing insights into prognostic biomarkers and therapeutic targets at the pan-cancer level.

A comprehensive prognostic and immunological implications of PFKP in pan-cancer

BACKGROUND

Phosphofructokinase P (PFKP) is a key rate-limiting enzyme in glycolysis, playing a crucial role in various pathophysiological processes. However, its specific function in tumors remains unclear. This study aims to evaluate the expression and specific role of PFKP across multiple tumor types (Pan-cancer) and to explore its potential clinical significance as a therapeutic target in cancer treatment.

METHODS

We analyzed the expression of PFKP, immune cell infiltration, and patient prognosis across various cancers using data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Additionally, we conducted a series of experiments in lung cancer cells, including Western blot, CCK-8 assay, colony formation assay, transwell migration assay, scratch wound healing assay, LDH release assay, and flow cytometry, to evaluate the impact of PFKP on tumor cells.

RESULTS

PFKP was found to be highly expressed in most cancers and identified as a prognostic risk factor. Elevated PFKP expression is associated with poorer clinical outcomes, particularly in lung adenocarcinoma (LUAD). Receiver operating characteristic (ROC) curve analysis indicated that PFKP can effectively differentiate between cancerous and normal tissues. The expression of PFKP in most tumors showed significant correlations with tumor mutational burden (TMB), microsatellite instability (MSI), immune score, and immune cell infiltration. In vitro experiments demonstrated that PFKP overexpression promotes lung cancer cell proliferation and migration while inhibiting apoptosis, whereas PFKP deficiency results in the opposite effects.

CONCLUSION

PFKP acts as an oncogene involved in tumorigenesis and may influence the immune microenvironment within the tumor. Our findings suggest that PFKP could serve as a potential biomarker for predicting prognosis and the efficacy of immunotherapy in tumors.

Clinical application value of long non-coding RNAs signatures of genomic instability in predicting prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) presents challenges due to its high recurrence and metastasis rates and poor prognosis. While current clinical diagnostic and prognostic indicators exist, their accuracy remains imperfect due to their biological complexity. Therefore, there is a quest to identify improved biomarkers for HCC diagnosis and prognosis. By combining long non-coding RNA (lncRNA) expression and somatic mutations, Duan et al identified five representative lncRNAs from 88 lncRNAs related to genomic instability (GI), forming a GI-derived lncRNA signature (LncSig). This signature outperforms previously reported LncSig and TP53 mutations in predicting HCC prognosis. In this editorial, we comprehensively evaluate the clinical application value of such prognostic evaluation model based on sequencing technology in terms of cost, time, and practicability. Additionally, we provide an overview of various prognostic models for HCC, aiding in a comprehensive understanding of research progress in prognostic evaluation methods.

Deciphering the dual roles of PHD finger proteins from oncogenic drivers to tumor suppressors

PHD (plant homeodomain) finger proteins emerge as central epigenetic readers and modulators in cancer biology, orchestrating a broad spectrum of cellular processes pivotal to oncogenesis and tumor suppression. This review delineates the dualistic roles of PHD fingers in cancer, highlighting their involvement in chromatin remodeling, gene expression regulation, and interactions with cellular signaling networks. PHD fingers' ability to interpret specific histone modifications underscores their influence on gene expression patterns, impacting crucial cancer-related processes such as cell proliferation, DNA repair, and apoptosis. The review delves into the oncogenic potential of certain PHD finger proteins, exemplified by PHF1 and PHF8, which promote tumor progression through epigenetic dysregulation and modulation of signaling pathways like Wnt and TGFβ. Conversely, it discusses the tumor-suppressive functions of PHD finger proteins, such as PHF2 and members of the ING family, which uphold genomic stability and inhibit tumor growth through their interactions with chromatin and transcriptional regulators. Additionally, the review explores the therapeutic potential of targeting PHD finger proteins in cancer treatment, considering their pivotal roles in regulating cancer stem cells and influencing the immune response to cancer therapy. Through a comprehensive synthesis of current insights, this review underscores the complex but promising landscape of PHD finger proteins in cancer biology, advocating for further research to unlock novel therapeutic avenues that leverage their unique cellular roles.

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies

OBJECTIVE

Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy.

METHODS

We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the "one-class logistic regression (OCLR)" algorithm to obtain the mRNAsi of patients with HCC. We performed "unsupervised consensus clustering" to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient's prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC.

RESULTS

We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient's prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines.

CONCLUSION

The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

The Roles of Myeloid-Derived Suppressor Cells in Liver Disease

Liver disease-related mortality is a major cause of death worldwide. Hepatic innate and adaptive immune cells play diverse roles in liver homeostasis and disease. Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature myeloid cells. MDSCs can be broadly divided into monocytic MDSCs and polymorphonuclear or granulocytic MDSCs, and they functionally interact with both liver parenchymal and nonparenchymal cells, such as hepatocytes and regulatory T cells, to impact liver disease progression. The infiltration and activation of MDSCs in liver disease can be regulated by inflammatory chemokines and cytokines, tumor-associated fibroblasts, epigenetic regulation factors, and gut microbiota during liver injury and cancer. Given the pivotal roles of MDSCs in advanced liver diseases, they can be targeted to treat primary and metastatic liver cancer, liver generation, alcoholic and nonalcoholic liver disease, and autoimmune hepatitis. Currently, several treatments such as the antioxidant and anti-inflammatory agent berberine are under preclinical and clinical investigation to evaluate their therapeutic efficacy on liver disease and their effect on MDSC infiltration and function. Phenotypic alteration of MDSCs in different liver diseases that are in a model-dependent manner and lack special markers for distinct MDSCs are challenges for targeting MDSCs to treat liver disease. Multi-omics study is an option to uncover the features of disease-specific MDSCs and potential gene or protein targets for liver disease treatment. In summary, MDSCs play important roles in the pathogenesis and progression of liver disease by regulating both intrahepatic innate and adaptive immune responses.

Formin protein FMNL1 is a biomarker for tumor-infiltrating immune cells and associated with well immunotherapeutic response

Background: Increased studies on the basis of bulk RNA-sequencing (RNA-seq) data of cancer identify numbers of immune-related genes which may play potential regulatory roles in the tumor microenvironment (TME) without in-depth validation. Methods: In the current study, the immunological correlation and cell subpopulation expression pattern of FMNL1 were analyzed using public data. In addition, the cell subpopulation expression pattern of FMNL1 was also deeply validated using single-cell RNA-sequencing (scRNA-seq) and multiplexed quantitative immunofluorescence (mQIF). Results: Bulk FMNL1 mRNA was related to better prognosis in hepatocellular carcinoma (HCC) and was able to identify immuno-hot tumor in not only HCC but also multiple cancer types. Bulk FMNL1 mRNA also predicted the response to immunotherapy in multiple cancers. Further validation using scRNA-seq and mQIF revealed that FMNL1 was a biomarker for immune cells. Conclusions: FMNL1 is a biomarker for immune cells in not only hepatocellular carcinoma, but also multiple cancer types. Moreover, immune infiltration analysis using the bulk RNA-seq data would be further validated using scRNA-seq and/or mQIF to describe the cell subpopulation expression pattern in tumor tissues for more in-depth and appropriate understanding.

The core role of macrophages in hepatocellular carcinoma: the definition of molecular subtypes and the prognostic risk system

Background: In patients with hepatocellular carcinoma (HCC), the tumor microenvironment (TME) is resistant to immunotherapy because of its specificity. It is meaningful to explore the role of macrophage, which is one of the most abundant immune cells in the TME, in cellular communication and its effect on the prognosis and immunotherapy of HCC. Methods: Dimensionality reduction and clustering of the single-cell RNA-seq data from the GSE149614 dataset were carried out to identify the cellular composition of HCC. CellChat was used to analyze the communication between different cells. The specifically highly expressed genes of macrophages were extracted for univariate Cox regression analysis to obtain prognostic genes for HCC cluster analysis, and the risk system of macrophage-specifically highly expressed genes was developed by random forest analysis and multivariate Cox regression analysis. Prognosis, TME infiltration, potential responses to immunotherapy, and antineoplastic drugs were compared among molecular subtypes and between risk groups. Results: We found that HCC included nine identifiable cell types, of which macrophages had the highest communication intensity with each of the other eight cell types. Of the 179 specifically highly expressed genes of macrophage, 56 were significantly correlated with the prognosis of HCC, which classified HCC into three subtypes, which were reproducible and produced different survival outcomes, TME infiltration, and immunotherapy responses among the subtypes. In the integration of four macrophage-specifically highly expressed genes for the development of a risk system, the risk score was significantly involved in higher immune cell infiltration, poor prognosis, immunotherapy response rate, and sensitivity of six drugs. Conclusion: In this study, through single-cell RNA-seq data, we identified nine cell types, among which macrophage had the highest communication intensity with the rest of the cell types. Based on specifically highly expressed genes of macrophage, we successfully divided HCC patients into three clusters with distinct prognosis, TME, and therapeutic response. Additionally, a risk system was constructed, which provided a potential reference index for the prognostic target and preclinical individualized treatment of HCC.

Based on disulfidptosis-related glycolytic genes to construct a signature for predicting prognosis and immune infiltration analysis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) comprises several distinct molecular subtypes with varying prognostic implications. However, a comprehensive analysis of a prognostic signature for HCC based on molecular subtypes related to disulfidptosis and glycolysis, as well as associated metabolomics and the immune microenvironment, is yet to be fully explored.

Methods

Based on the differences in the expression of disulfide-related glycolytic genes (DRGGs), patients with HCC were divided into different subtypes by consensus clustering. Establish and verify a risk prognosis signature. Finally, the expression level of the key gene SLCO1B1 in the signature was evaluated using immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR) in HCC. The association between this gene and immune cells was explored using multiplex immunofluorescence. The biological functions of the cell counting kit-8, wound healing, and colony formation assays were studied.

Results

Different subtypes of patients have specific clinicopathological features, prognosis and immune microenvironment. We identified seven valuable genes and constructed a risk-prognosis signature. Analysis of the risk score revealed that compared to the high-risk group, the low-risk group had a better prognosis, higher immune scores, and more abundant immune-related pathways, consistent with the tumor subtypes. Furthermore, IHC and qRT-PCR analyses showed decreased expression of SLCO1B1 in HCC tissues. Functional experiments revealed that SLCO1B1 overexpression inhibited the proliferation, migration, and invasion of HCC cells.

Conclusion

We developed a prognostic signature that can assist clinicians in predicting the overall survival of patients with HCC and provides a reference value for targeted therapy.

Typing and modeling of hepatocellular carcinoma based on disulfidptosis-related amino acid metabolism genes for predicting prognosis and guiding individualized treatment

Introduction

Hepatocellular carcinoma (HCC) is the most common type of cancer worldwide and is a major public health problem in the 21st century. Disulfidopathy, a novel cystine-associated programmed cell death, plays complex roles in various tumors. However, the relationship between disulfidoptosis and prognosis in patients with HCC remains unclear. This study aimed to explore the relationship between disulfideptosis and the prognosis of liver cancer and to develop a prognostic model based on amino acid metabolism and disulfideptosis genes.

Methods

We downloaded the clinicopathological information and gene expression data of patients with HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and classified them into different molecular subtypes based on the expression patterns of disulfidoptosis-associated amino acid metabolism genes (DRAGs). Patients were then classified into different gene subtypes using the differential genes between the molecular subtypes, and the predictive value of staging was assessed using survival and clinicopathological analyses. Subsequently, risk prognosis models were constructed based on Cox regression analysis to assess patient prognosis, receiver operating characteristic (ROC) curves, somatic mutations, microsatellite instability, tumor microenvironment, and sensitivity to antitumor therapeutic agents.

Results

Patients were classified into two subtypes based on differential DRAGs gene expression, with cluster B having a better survival outcome than cluster A. Three gene subtypes were identified based on the differential genes between the two DRAGs molecular subtypes. The patients in cluster B had the best prognosis, whereas those in cluster C had the worst prognosis. The heat map showed better consistency in the patient subtypes obtained using both typing methods. We screened six valuable genes and constructed a prognostic signature. By scoring, we found that patients in the low-risk group had a better prognosis, higher immune scores, and more abundant immune-related pathways compared to the high-risk group, which was consistent with the tumor subtype results.

Discussion

In conclusion, we developed a prognostic signature of disulfidptosis-related amino acid metabolism genes to assist clinicians in predicting the survival of patients with HCC and provide a reference value for targeted therapy and immunotherapy for HCC.

Aberrant acetylated modification of FGF21‑KLB signaling contributes to hepatocellular carcinoma metastasis through the β‑catenin pathway

β‑Klotho (KLB) is a vital element of the fibroblast growth factor (FGF) receptor complex and acts as a co‑receptor to facilitate the binding of FGF19 and FGF21 to the FGFRs on the target cells. The present study aimed to determine the contribution of FGF21‑KLB signaling to hepatocellular carcinoma (HCC) metastasis. KLB expression was measured in HCC tissues and cell lines using western blot and reverse transcription‑quantitative PCR. Furthermore, the proliferation, apoptosis and metastasis capacity of KLB‑knockdown Huh7 cells (human HCC cell line) were assessed by Cell Counting Kit‑8 assay, 5‑ethynyl‑2'‑deoxyuridine assay, flow cytometry, wound‑healing assay and Transwell assay. Enrichment analysis was used to explore the underlying regulatory mechanisms of KLB. The metastasis potential of human HCC cells in the context of FGF21 with or without KLB inhibition was determined in vitro and in vivo. Acetylated modification of KLB was determined using a co‑immunoprecipitation assay. The results indicated a significant upregulation of KLB in HCC tissues compared with the corresponding normal tissues. In addition, KLB expression was closely associated with HCC metastasis. Migration and invasion assays revealed that KLB knockdown promoted the metastatic capability of HCC cells. Gene set variation analysis and subsequent mechanistic investigations revealed that KLB is the upstream regulatory factor of β‑catenin signaling. Furthermore, FGF21 was indicated to suppress HCC metastasis by inhibiting β‑catenin signaling‑driven epithelial‑mesenchymal transition (EMT), while KLB knockdown and simultaneous FGF21 overexpression promoted HCC cell motility. Histone deacetylase 3 (HDAC3) was further characterized as the potential deacetylase for KLB. Furthermore, the results revealed that HDAC3 inhibitor‑mediated acetylated modification led to KLB inactivation, resulting in the blockade of FGF21‑KLB signaling, which further triggered the expression of EMT induction‑related genes in Huh7 cells. In conclusion, the present study demonstrated that aberrant acetylated modification of KLB inhibited FGF21‑KLB signaling, thereby promoting β‑catenin signaling‑driven EMT and HCC metastasis.

Polycomb-like Proteins in Gene Regulation and Cancer

Polycomb-like proteins (PCLs) are a crucial group of proteins associated with the Polycomb repressive complex 2 (PRC2) and are responsible for setting up the PRC2.1 subcomplex. In the vertebrate system, three homologous PCLs exist: PHF1 (PCL1), MTF2 (PCL2), and PHF19 (PCL3). Although the PCLs share a similar domain composition, they differ significantly in their primary sequence. PCLs play a critical role in targeting PRC2.1 to its genomic targets and regulating the functionality of PRC2. However, they also have PRC2-independent functions. In addition to their physiological roles, their dysregulation has been associated with various human cancers. In this review, we summarize the current understanding of the molecular mechanisms of the PCLs and how alterations in their functionality contribute to cancer development. We particularly highlight the nonoverlapping and partially opposing roles of the three PCLs in human cancer. Our review provides important insights into the biological significance of the PCLs and their potential as therapeutic targets for cancer treatment.

RBM10 Is a Biomarker Associated with Pan-Cancer Prognosis and Immune Infiltration: System Analysis Combined with In Vitro and Vivo Experiments

RNA binding motif protein 10 (RBM10) is a splicing factor that has been reported to be involved in the occurrence and progression of multiple malignancies. However, the RBM10 involvement in pan-cancer immunotherapy is not clear. In here, we provide the first comprehensive assessment of the prognostic value and immunological function of RBM10 in human pan-cancer utilizing multiple public databases. Data reveal the aberrant RBM10 expression in most tumors, and its expression is positively or negatively linked with the clinical prognosis of various cancers, depending on the different types and subtypes of cancers. In most tumors, RBM10 mutations are frequently occurred, which is closely related to tumor progression. Moreover, our results also show that RBM10 is considerably linked with most of the immune checkpoint genes, tumor immune cell infiltration, tumor mutation burden, and microsatellite instability. Additionally, RBM10 is significantly positively correlated with the sensitivity of trametinib, 17-AAG, PD-0325901, RDEA119, cetuximab, and afatinib, indicating potential antagonism between RBM10 inhibitors and these antitumor drugs, and more likely to develop drug resistance. We also verify that downregulation of RBM10 enhances the malignant phenotype of lung adenocarcinoma cells using in vitro cell experiments, and in vivo animal experiments show that the overexpression of RBM10 reduces the growth of tumors. Furthermore, upregulating RBM10 greatly reduces the PD-L1 protein levels, while silencing RBM10 considerably enhances PD-L1 protein levels. Moreover, the overexpression of RBM10 decreases the protein stability of PD-L1. To sum up, our pan-cancer analysis indicates that RBM10 is a promising biomarker for prognosis and immunotherapy, which provides a new insight for cancer immunotherapy.

TIMM8A is associated with dysfunction of immune cell in BRCA and UCEC for predicting anti-PD-L1 therapy efficacy

Background

TIMM8A is a protein-coding gene located on the X chromosome. There is evidence that TIMM8A plays an important role in mitochondrial morphology and fission. Studies have shown that mitophagy and fission could affect the function of immune cells. However, there is currently no research on this gene’s role in cancer occurrence and progression.

Methods

TIMM8A expression was analyzed via the Tumor Immune Estimation Resource (TIMER) site and UALCAN database. We evaluated the influence of TIMM8A on clinical prognosis using Kaplan-Meier plotter, the PrognoScan database, and Human Protein Atlas (HPA). The correlations between TIMM8A and cancer immune infiltrates were investigated via TIMER. Tumor Immune Dysfunction and Exclusion (TIDE) was used to evaluate the potential of tumor immune evasion. Functions of TIMM8A mutations and 50 genes significantly associated with TIMM8A mutations in breast cancer (BRCA) and uterine corpus endometrial cancer (UCEC) were analyzed by GO and KEGG in LinkedOmics database.

Results

We investigated the role of TIMM8A in multiple cancers and found that it was significantly associated with poor prognosis in BRCA and UCEC. After analyzing the effect of TIMM8A on immune infiltration, we found Th2 CD4+ T cells might be a common pathway by which TIMM8A contributed to poor prognosis in BRCA and UCEC. Our results suggested that myeloid-derived suppressor cells (MDSC) and tumor-associated M2 macrophages (TAM M2) might be important factors in immune evasion through T cell rejection in both cancers, and considered TIMM8A as a biomarker to predict the efficacy of this therapy in BRCA and UCEC. The results of TIMM8A enrichment analysis showed us that abnormally expressed TIMM8A might affect the mitochondrial protein in BRCA and UCEC.

Conclusions

Contributed to illustrating the value of TIMM8A as a prognostic biomarker, our findings suggested that TIMM8A was correlated with prognosis and immune infiltration, including CD8+ T cells, Th2 CD4+ T cells, and macrophages in BRCA and UCEC. In addition, TIMM8A might affect immune infiltration and prognosis in BRCA and UCEC by affecting mitophagy. We believed it could also be a biomarker to predict the efficacy of anti-PD-L1 therapy and proposed to improve the efficacy by eliminating MDSC and TAM M2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02736-6.

Comprehensive analysis of histone methylation modification regulators for predicting prognosis and drug sensitivity in lung adenocarcinoma

Histone methylation is an epigenetic modification regulated by histone methyltransferases, histone demethylases, and histone methylation reader proteins that play important roles in the pathogenic mechanism of cancers. However, the prognostic value of histone methylation in lung adenocarcinoma (LUAD) remains unknown. Here, we found that LUAD cases could be divided into 2 subtypes by the 144 histone methylation modification regulators (HMMRs), with a significant difference in OS time. Ninety-five of the HMMRs were identified as differentially expressed genes (DEGs) between normal and tumor samples, and 13 of them were further discovered to be survival-related genes (SRGs). By applying the least absolute shrinkage and selector operator (LASSO) Cox regression, we constructed an 8-gene-based risk signature according to the TCGA (training) cohort, and the risk score calculated by the signature was proven to be an independent factor in both the training and validation cohorts. We then discovered that the immune functions were generally impaired in the high-risk groups defined by the HMMR signature (especially for the DCs and immune check-point pathway). Functional analyses showed that the DEGs between the low- and high-risk groups were related to the cell cycle. The drug sensitivity analysis indicated that our risk model could predict the sensitivity of commonly used drugs. Moreover, according to the DEGs between the low- and high-risk groups, we discovered several new compounds that showed potential therapeutic value for high-risk LUAD patients. In conclusion, our study demonstrated that HMMRs were promising predictors for the prognoses and drug therapeutic effects for LUAD patients.

Overexpression of CDCP1 is Associated with Poor Prognosis and Enhanced Immune Checkpoints Expressions in Breast Cancer

CUB-domain containing protein 1 (CDCP1) is a transmembrane protein acting as an effector of SRC family kinases, which play an oncogenic role in multiple human cancers. However, its clinical and immune correlations in breast cancer (BrCa) have not been explored. To define the expression, prognostic value, and potential molecular role of CDCP1 in BrCa, multiple public datasets, and an in-house cohort were used. Compared with paratumor tissue, CDCP1 was remarkably upregulated in the tumor tissues at both mRNA and protein levels. In the in-house cohort, CDCP1 protein expression was related to several clinicopathological parameters, including age, ER status, PR status, molecular type, and survival status. Kaplan–Meier analysis and Cox regression analysis exhibited that CDCP1 was an important prognostic biomarker in BrCa. In addition, enrichment analysis uncovered that CDCP1 was not only involved in multiple oncogenic pathways, but correlated with overexpression of immune checkpoints. Overall, we reported that increased expression of CDCP1 is a favorable prognostic factor in patients with BrCa. In addition, the correlations between CDCP1 and immune checkpoints provide a novel insight into the adjuvant treatment for immune checkpoint blockade via targeting CDCP1.

GPR87 promotes tumor cell invasion and mediates the immunogenomic landscape of lung adenocarcinoma

The purpose of this study is to examine the association between G protein-coupled receptor 87 (GPR87) and lung adenocarcinoma (LUAD) metastasis and immune infiltration. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets extract clinical data. According to the TCGA database, increased GPR87 expression predicts poor overall survival, progression-free interval, and disease-specific survival in LUAD patients. The meta-analysis also reveals a significant association between high GPR87 expression and poor overall survival. Moreover, functional experiments demonstrate that GPR87 silencing reduces LUAD cell invasion and migration. Immunoblotting shows that GPR87 knockdown decreased Vimentin and N-cadherin expression and increased E-cadherin expression in LUAD cells. GPR87 expression in LUAD is positively correlated with immune infiltration. In addition, GPR87 expression is associated with immune and chemotherapy resistance in LUAD patients. Our findings indicate that GPR87 promotes tumor progression and is correlated with immune infiltration, suggesting GPR87 as a possible biomarker for prognosis prediction in LUAD.

GPR87 is reported as a central player in lung adenocarcinoma and in resistance to immunotherapy, by promoting tumor cell invasion and mediating the immunogenomic landscape.