Ferritin light chain as a potential biomarker for the prognosis of liver hepatocellular carcinoma.

High expression of the ferritin light chain (FTL) in cancer promotes its onset and progression and is associated with tumour evolution. However, the significance of FTL in pan-cancer progression and prognosis in humans remains unclear. Therefore, we selected various bioinformatics databases to perform a pan-cancer analysis on a public dataset. Our results showed that FTL was differentially expressed in pan-cancer tissues compared to normal tissues. High FTL expression significantly correlated with the clinicopathological characteristics of patients with liver hepatocellular carcinoma (LIHC). The subsequent validation experiments confirmed these observations. Notably, our study found for the first time that FTLs are closely associated with LIHC and that FTLs have important clinical diagnostic and prognostic value for patients with LIHC. We confirmed that FTL expression was closely associated with altered DNA cycles and immune infiltration in LIHC. In conclusion, high levels of FTL expression are associated with poor prognosis in LIHC patients and are expected to be a potential prognostic and immune marker for LIHC.

TIMM9 as a prognostic biomarker in multiple cancers and its associated biological processes.

TIMM9 has been identified as a mediator of essential functions in mitochondria, but its association with pan-cancer is poorly understood. We herein employed bioinformatics, computational chemistry techniques and experiments to investigate the role of TIMM9 in pan-cancer. Our analysis revealed that overexpression of TIMM9 was significantly associated with tumorigenesis, pathological stage progression, and metastasis. Missense mutations (particularly the S49L variant), copy number variations (CNV) and methylation alterations in TIMM9 were found to be associated with poor cancer prognosis. Moreover, TIMM9 was positively related with cell cycle progression, mitochondrial and ribosomal function, oxidative phosphorylation, TCA cycle activity, innate and adaptive immunity. Additionally, we discovered that TIMM9 could be regulated by cancer-associated signaling pathways, such as the mTOR pathway. Using molecular simulations, we identified ITFG1 as the protein that has the strongest physical association with TIMM9, which show a promising structural complement.

CD24 affects the immunosuppressive effect of tumor-infiltrating cells and tumor resistance in a variety of cancers.

BACKGROUND: Cluster of differentiation 24 (CD24) is a highly glycosylated glycosylphosphatidylinositol (GPI)-anchored surface protein, expressed in various tumor cells, as a "don't eat me" signaling molecule in tumor immune. This study aimed to investigate the potential features of CD24 in pan-cancer. METHODS: The correlations between 22 immune cells and CD24 expression were using TIMER analysis. R package "ESTIMATE" was used to predict the proportion of immune and stromal cells in pan-cancer. Spearman's correlation analysis was performed to evaluate the relationships between CD24 expression and immune checkpoints, chemokines, mismatch repair, tumor mutation burden and microsatellite instability, and qPCR and western blot were conducted to assess CD24 expression levels in liver hepatocellular carcinoma (LIHC). In addition, loss of function was performed for the biological evaluation of CD24 in LIHC. RESULTS: CD24 expression was positively correlated with myeloid cells, including neutrophils and myeloid-derived suppressor cells, in various tumors, such as BLCA, HNSC-HPV, HNSC, KICH, KIRC, KIRP, TGCT, THCA, THYM, and UCEC. In contrast, anti-tumor NK cells and NKT cells showed a negative association with CD24 expression in BRCA-Her2, ESCA, HNSC-HPV, KIRC, THCA, and THYM. The top three tumors with the highest correlation between CD24 and ImmuneScore were TGCT, THCA, and SKCM. Functional enrichment analysis revealed CD24 expression was negatively associated with various immune-related pathways. Immune checkpoints and chemokines also exhibited inverse correlations with CD24 in CESC, CHOL, COAD, ESCA, READ, TGCT, and THCA. Additionally, CD24 was overexpressed in most tumors, with high CD24 expression in BRCA, LIHC, and CESC correlating with poor prognosis. The TIDE database indicated tumors with high CD24 expression, particularly melanoma, were less responsive to PD1/PD-L1 immunotherapy. Finally, CD24 knockdown resulted in impaired proliferation and cell cycle progression in LIHC. CONCLUSION: CD24 participates in regulation of immune infiltration, influences patient prognosis and serves as a potential tumor marker.

The role of cuproptosis-related genes in pan-cancer and the development of cuproptosis-related risk model in colon adenocarcinoma.

Cancer is widely regarded as a leading cause of death in humans, with colon adenocarcinoma (COAD) ranking among the most prevalent types. Cuproptosis is a novel form of cell death mediated by protein lipoylation. Cuproptosis-related genes (CRGs) participate in tumourigenesis and development. Their role in pan-cancer and COAD require further investigation. This study comprehensively evaluated the relationship among CRGs, pan-cancer, and COAD. Our research revealed the differential expression of CRGs and the cuproptosis potential index (CPI) between normal and tumour tissues, and further explored the correlation of CRGs or CPI with prognosis, immune infiltration, tumor mutant burden(TMB), microsatellite instability (MSI), and drug sensitivity in pan-cancer. Gene set enrichment analysis (GSEA) revealed that oxidative phosphorylation and fatty acid metabolism pathways were significantly enriched in the high CPI group of most tumours. FDX1 and CDKN2A were chosen for further exploration, and we found an independent association between FDX1 and CDKN2A and prognosis, immune infiltration, TMB, and MSI in pan-cancer. Furthermore, a prognostic risk model based on the association between CRGs and COAD was built, and the correlations between the risk score and prognosis, immune-related characteristics, and drug sensitivity were analysed. COAD was then divided into three subtypes using cluster analysis, and the differences among the subtypes in prognosis, CPI, immune-related characteristics, and drug sensitivity were determined. Due to the level of LIPT1 was notably positive related with the risk score, the cytological identification was carried out to identify the association of LIPT1 with proliferation and migration of colon cancer cells. In summary, CRGs can be used as potential prognostic biomarkers to predict immune infiltration levels in patients with pan-cancer. In addition, the risk model could more accurately predict the prognosis and immune infiltration levels of COAD and better guide the direction of clinical medication. Thus, FDX1, CDKN2A, and LIPT1 may serve as prospective new targets for cancer therapy.

RAB42 overexpression correlates with poor prognosis, immune cell infiltration and chemoresistance.

Background: RAB42 (Ras-related protein 42) is a new small GTPase that controls the vesicular trafficking from endosomes to trans-Golgi network in mammalian cells. However, the role of RAB42 in multiple cancers, especially in liver hepatocellular carcinoma (LIHC), has not been well investigated. Methods: A variety of cancer-related databases and online tools, including TCGA, GTEx, TARGET, QUANTISEQ, EPIC, RNAactDrug, CTR-DB, TIMER algorithms and Sangerbox, were applied to explore the correlation of RAB42 expression with prognosis, immune microenvironment, immune regulatory network, RNA modification, pathway activation and drug sensitivity in pan-cancer. The prognostic, immunomodulatory and tumor-promoting effects of RAB42 were verified in various malignancies and determined by a series of in vitro cellular experiments. Results: RAB42 is significantly overexpressed in most cancers with advanced pathological stages. Its overexpression is correlated with poor survival in pan-cancer. RAB42 overexpression has a high diagnostic accuracy of various cancers (AUC > 0.80). RAB42 overexpression not only correlates with distinct stromal immune infiltration and level of immune checkpoint molecules, but also associates with weak immune cell infiltration, immunomodulatory genes expression, and immunotherapeutic response to immune checkpoint inhibitors (ICIs). Additionally, RAB42 overexpression correlates with enhanced expression of m6A RNA methylation-related genes (MRGs) and its interactors. Moreover, overexpression of RAB42 serves as a drug-resistant marker to certain chemotherapies and acts as a potential biomarker for LIHC. Notably, RAB42 overexpression or activation promotes the cellular proliferation, migration and invasion of LIHC. Conclusion: Overexpressed RAB42 serves as a potential prognostic biomarker and therapeutic target in pan-cancer, especially in LIHC.

Scinderin is a potential prognostic biomarker and correlated with immunological regulation: from pan-cancer analysis to liver hepatocellular carcinoma.

Aim: This study aimed to systematically dissect the role of Scinderin (SCIN) in tumorigenesis. Methods: Bioinformatics techniques were employed based on cancer data from TCGA, ENCORI, HPA, GEPIA2, UALCAN, Kaplan-Meier plotter, TIMER, TISIDB, cBioPortal, HCCDB, GeneMANIA and LinkedOmics database. Experiments in vitro and in vivo were conducted to dissect the role of SCIN in liver hepatocellular carcinoma (LIHC). Results: Significantly differential expression of SCIN was found in nine types of cancers, including LIHC. Through pan-cancer analysis, the correlations between SCIN expression with prognosis and immune cell infiltration were proven, especially in LIHC, ovarian serous cystadenocarcinoma and lung adenocarcinoma. The highest frequency of alteration in SCIN (6.81%) was seen in patients with uterine corpus endometrial carcinoma, in which "mutation" was the predominant type, with a frequency of about 5.29%; meanwhile, S673F and S381Y were the two most frequent mutation sites. Furthermore, the abnormal expression of SCIN exhibited a strong relationship with immune cell subtypes, immune checkpoint genes, tumor mutation burden, microsatellite instability, neoantigen, molecular subtypes, mismatch repair signatures and DNA methyl-transferase in different cancer types. Through comparative analysis, we discovered that SCIN was dramatically up-regulated in LIHC, and associated with poor survival. Experiments in vitro and in vivo suggested the knockdown of SCIN could suppress tumor cell proliferation and improve the survival rate partly in animal models. Conclusion: This study reveals SCIN may be a promising biomarker for prognosis and treatment in certain cancers, especially in LIHC.

Comprehensively prognostic and immunological analyses of GLP-1 signaling-related genes in pan-cancer and validation in colorectal cancer.

Background: Glucagon-like peptide-1 (GLP-1) has crucial impact on glycemic control and weight loss physiologically. GLP-1 receptor agonists have been approved for treatment of diabetes and obesity. Emerging evidence suggests that GLP-1 receptor agonists exert anticancer effect in tumorigenesis and development. However, the role and mechanism of GLP-1 signaling-related genes in pan-cancer still need further study. Methods: We comprehensively investigated the aberrant expression and genetic alterations of GLP-1 signaling-related genes in 33 cancer types. Next, GLP-1 signaling score of each patient in The Cancer Genome Atlas were established by the single-sample gene set enrichment analysis. In addition, we explored the association of GLP-1 signaling score with prognostic significance and immune characteristics. Furthermore, qRT-PCR and immunohistochemistry staining were applied to verify the expression profiling of GLP-1 signaling-related genes in colorectal cancer (CRC) tissues. Wound-healing assays and migration assays were carried out to validate the role of GLP-1 receptor agonist in CRC cell lines. Results: The expression profiling of GLP-1 signaling-related genes is commonly altered in pan-cancer. The score was decreased in cancer tissues compared with normal tissues and the lower expression score was associated with worse survival in most of cancer types. Notably, GLP-1 signaling score was strongly correlated with immune cell infiltration, including T cells, neutrophils, dendritic cells and macrophages. In addition, GLP-1 signaling score exhibited close association with tumor mutation burden, microsatellite instability and immunotherapy response in patients with cancer. Moreover, we found that the expression of GLP-1 signaling-related genes ITPR1 and ADCY5 were significantly reduced in CRC tissues, and GLP-1 receptor agonist semaglutide impaired the migration capacity of CRC cells, indicating its protective role. Conclusion: This study provided a preliminary understanding of the GLP-1 signaling-related genes in pan-cancer, showing the prognosis significance and potential immunotherapeutic values in most cancer types, and verified the potential anticancer effect of GLP-1 receptor agonist in CRC.

Pan-cancer analyses reveal the molecular and clinical characteristics of TET family members and suggests that TET3 maybe a potential therapeutic target.

The Ten-Eleven Translocation (TET) family genes are implicated in a wide array of biological functions across various human cancers. Nonetheless, there is a scarcity of studies that comprehensively analyze the correlation between TET family members and the molecular phenotypes and clinical characteristics of different cancers. Leveraging updated public databases and employing several bioinformatics analysis methods, we assessed the expression levels, somatic variations, methylation levels, and prognostic values of TET family genes. Additionally, we explored the association between the expression of TET family genes and pathway activity, tumor microenvironment (TME), stemness score, immune subtype, clinical staging, and drug sensitivity in pan-cancer. Molecular biology and cytology experiments were conducted to validate the potential role of TET3 in tumor progression. Each TET family gene displayed distinct expression patterns across at least ten detected tumors. The frequency of Single Nucleotide Variant (SNV) in TET genes was found to be 91.24%, primarily comprising missense mutation types, with the main types of copy number variant (CNV) being heterozygous amplifications and deletions. TET1 gene exhibited high methylation levels, whereas TET2 and TET3 genes displayed hypomethylation in most cancers, which correlated closely with patient prognosis. Pathway activity analysis revealed the involvement of TET family genes in multiple signaling pathways, including cell cycle, apoptosis, DNA damage response, hormone AR, PI3K/AKT, and RTK. Furthermore, the expression levels of TET family genes were shown to impact the clinical staging of tumor patients, modulate the sensitivity of chemotherapy drugs, and thereby influence patient prognosis by participating in the regulation of the tumor microenvironment, cellular stemness potential, and immune subtype. Notably, TET3 was identified to promote cancer progression across various tumors, and its silencing was found to inhibit tumor malignancy and enhance chemotherapy sensitivity. These findings shed light on the role of TET family genes in cancer progression and offer insights for further research on TET3 as a potential therapeutic target for pan-cancer.

Pan-cancer analysis of the prognostic and immunological role of RPL4.

Ribosomal proteins (RPs) play an important role in the overall stability, function, and integrity of ribosomes. Ribosomal protein L4 (RPL4), which is encoded by RPL4, is assumed to play different roles in different cancers due to the strong correlation between them. However, research based on the underlying mechanisms of this correlations is limited. Therefore, this study investigated the biological role of RPL4 in various cancers. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to compare the differential expression of RPL4 in tumor and normal tissues. The Sangerbox database and Kaplan-Meier method were employed to assess RPL4's impact on the prognosis of pan-cancer. Analyses using the cBioPortal tool, Shiny Methylation Analysis Resource Tool (SMART), and MethSurv provided insights into the methylation and epigenetic alterations of RPL4. Gene enrichment analysis revealed that RPL4 is involved in ribosome biogenesis through multiple pathways, and its enrichment in signaling pathways directly or indirectly influence tumor development. Tumor Immune Single-cell Hub (TISCH) was used to analyze RPL4 expression levels and cellular functions in the tumor microenvironment. Tumor Immune Estimation Resource Database 2.0 (TIMER2.0) and Tumor-Immune System Interactions Database (TISIDB) tools revealed that RPL4 affected the immune infiltration potential of tumors. Furthermore, the application of the ROC mapper and CellMiner databases indicated an association between RPL4 and sensitivity to multiple antitumor drugs. Additionally, RPL4 was found to remodel the tumor immune microenvironment, leading to the development of chemoresistance. In conclusion, the findings suggest that RPL4 can be used as a potential tumor biomarker and may serve as a target for immunotherapy in various cancers. Genetic testing of RPL4 provides a foundation for the diagnosis, prognosis, and treatment of clinical tumors.

Integrative and comprehensive pan-cancer analysis of ubiquitin specific peptidase 11 (USP11) as a prognostic and immunological biomarker.

The significance of USP11 as a critical regulator in cancer has garnered substantial attention, primarily due to its catalytic activity as a deubiquitinating enzyme. Nonetheless, a thorough evaluation of USP11 across various cancer types in pan-cancer studies remains absent. Our analysis integrates data from a variety of sources, including five immunotherapy cohorts, thirty-three cohorts from The Cancer Genome Atlas (TCGA), and sixteen cohorts from the Gene Expression Omnibus (GEO), two of which involve single-cell transcriptomic data. Our findings indicate that aberrant USP11 expression is predictive of survival outcomes across various cancer types. The highest frequency of genomic alterations was observed in uterine corpus endometrial carcinoma (UCEC), with single-cell transcriptome analysis revealing significantly higher USP11 expression in plasmacytoid dendritic cells and mast cells. Notably, USP11 expression was associated with the infiltration levels of CD8+ T cells and natural killer (NK) activated cells. Additionally, in the skin cutaneous melanoma (SKCM) phs000452 cohort, patients with higher USP11 mRNA levels during immunotherapy experienced a significantly shorter median progression-free survival. USP11 emerges as a promising molecular biomarker with significant potential for predicting patient prognosis and immunoreactivity across various cancer types.

Occlusion enhanced pan-cancer classification via deep learning.

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces "GENESO," a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called "Symmetrical Occlusion (SO)". It collaborates with the baseline LSTM network, mimicking the "gain of function" and "loss of function" of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test.

Pan-cancer analysis of SERPINE1 with a concentration on immune therapeutic and prognostic in gastric cancer.

The serine protease inhibitor clade E member 1 (SERPINE1) is a key modulator of the plasminogen/plasminase system and has been demonstrated to promote tumor progression and metastasis in various tumours. However, although much literature has explored the cancer-promoting mechanism of SERPINE1, the pan-cancer analyses of its predictive value and immune response remain unexplored. The differential expression, and survival analysis of SERPINE1 expression in multiple cancers were analysed using The Cancer Genome Atlas and Genotype-Tissue Expression database. Kaplan-Meier (K-M) plotter and survival data analysis were used to analyze the prognostic value of SERPINE1 expression, including overall survival (OS), disease-specific survival, disease-free interval and progression-free interval and investigated the relationship of SERPINE1 expression with microsatellite instability. We further analysed the correlation between the expression of SERPINE1 and immune infiltration. The Kyoto Encyclopaedia of Genes and Genomes pathway was used for enrichment analysis, and the Gene Set Enrichment Analysis (GSEA) database was used to perform pathway analysis. Finally, in vitro experiments demonstrated that knockdown or overexpression of SERPINE1 could alter the proliferation and migration of gastric cancer (GC) cells. The results indicated that SERPINE1 expression levels different significantly between cancer and normal tissues, meanwhile, it was highly expressed in various cancers. By analysing online data, it has been observed that the gene SERPINE1 exhibits heightened expression levels across a variety of human cancers, significantly impacting patient survival rates. Notably, the presence of SERPINE1 was strongly associated with decrease OS and disease-free survival in individuals diagnosed with GC. Furthermore, an observed link indicates that higher levels of SERPINE expression are associated with increased infiltration of immune cells in GC. Finally, in vitro experiments showed that knockdown or overexpression of SERPINE1 inhibited the growth, and migration, of GC cells. SERPINE1expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in GC. This study shows that SERPINE1 is an oncogene that participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in GC. These findings underscore the importance of further investigating the role of SERPINE1 in cancer progression and offer a promising direction for the development of new therapeutic strategies.

Pan­cancer analysis on the role of KMT2C expression in tumor progression and immunotherapy.

Histone lysine N-methyltransferase 2C (KMT2C) is involved in transcriptional regulation and DNA damage repair. Mutations in KMT2C have been implicated in the progression, metastasis, and drug resistance of multiple cancer types. However, the roles of KMT2C in the regulation of tumor prognosis, immune cell infiltration and the immune microenvironment in these multiple cancer types remain unclear. Therefore, in the present study, data from The Cancer Genome Atlas and Genotype-Tissue Expression databases were used for KMT2C expression analyses. Kaplan-Meier and univariate Cox regression analyses were also performed to investigate the prognostic role of KMT2C. In addition, Gene Set Enrichment Analysis (GSEA) was conducted to study the KMT2C-related signaling pathways. Tumor immune estimation resource 2 and single-sample GSEA were conducted to investigate the correlation between KMT2C expression and immune cell infiltrations, and Spearman's analysis was conducted to study the correlations among KMT2C, tumor mutational burden, microsatellite instability, immune regulators, chemokines and immune receptors. Immunohistochemistry of patient kidney tumor samples was performed to verify the correlation between KMT2C and programmed death-ligand 1 (PD-L1) expression. Finally, RNA interference, wound healing and colony formation assays were conducted to evaluate the effects of KMT2C expression on cell proliferation and metastasis. The results of the present study demonstrated that KMT2C was highly expressed in multiple cancer types, was a protective factor in kidney renal clear cell carcinoma and ovarian serous cystadenocarcinoma, and a risk factor for lung squamous cell carcinoma and uveal melanoma. In addition, KMT2C levels were negatively correlated with immune-activated pathways and the infiltration of immune cells, and positively correlated with inhibitory immune factors and tumor angiogenesis. Patients with low KMT2C expression had higher objective response rates to immunotherapy, and drug sensitivity analysis indicated that topoisomerase, histone deacetylase, DOT1-like histone H3K79 methyltransferase and G9A nuclear histone lysine methyltransferase inhibitors could potentially be used to treat tumors with high KMT2C expression levels. Finally, the KMT2C and PD-L1 expression levels were shown to be positively correlated, and KMT2C knockdown markedly promoted the proliferation and invasion capacities of A549 cells. In conclusion, the present study revealed that low KMT2C expression may be a promising biomarker for predicting the response of patients with cancer to immunotherapy. Conversely, high KMT2C expression was shown to promote tumor angiogenesis, which may contribute to the formation of the immunosuppressive tumor microenvironment.

A pan-cancer cuproptosis signature predicting immunotherapy response and prognosis.

Background: Cuproptosis may represent a potential biomarker for predicting prognosis and immunotherapy response, but the available evidence is insufficient. Methods: The multiple single-cell RNA sequencing (scRNA-seq) datasets were analyzed to investigate the specific occurrence of cuproptosis in distinct cell populations. Utilizing 28 scRNA-seq datasets, TCGA pan-cancer cohort, and 10 immunotherapy cohorts, we developed a cuproptosis signature (Cup.Sig). This signature was used to construct prediction models for immunotherapy response and identify potential prognostic biomarkers for pan-cancer using 11 different machine learning algorithms. Results: Malignant cells demonstrate the higher cuproptosis scores in comparison to other cell types across diverse cancer types. The Cup.Sig exhibits significant associations with cancer hallmarks and immune cell response in multiple cancer types. Leveraging the Cup.Sig, the robust pan-cancer immunotherapy prediction model and prognostic biomarker have been established and validated using diverse datasets from various platforms. Conclusions: We developed a pan-cancer cuproptosis signature for predicting survival and immunotherapy response.

Pan-cancer investigation of RFX family and associated genes identifies RFX8 as a therapeutic target in leukemia.

Background: Several transcription factors and co-factors are encoded by the RFX (Regulatory Factor X) family (RFX1-8) and associated genes (RFXAP and RFXANK). Increasing evidence suggests that the RFX family and associated genes are involved in the development and progression of cancer. However, no prior research has focused on a multi-omic analysis of these genes to evaluate their role in tumor progression. Methods: Using combined TCGA and GTEx pan-cancer data, we investigated the expression patterns and survival profiles of these ten genes. We then focused on RFX8 to analyze its clinicopathological and therapeutic features. Finally, we conducted experimental validation of RFX8 function in acute myeloid leukemia (AML). Results: RFX5 and RFXANK showed higher expression levels, while RFX6 showed lower expression levels in most types of cancer, with RFX8 being the most upregulated in LAML. RFX2 and RFXAP demonstrated prognostic significance in eight types of cancer, and RFX8 showed significance in six types of cancer. The expression of these ten genes exhibited specific characteristics in immune subtypes, tumor microenvironment, and stemness. The expression of RFX8 was correlated with various tumor stages, microsatellite instability (MSI), tumor mutation burden (TMB), immune cell infiltration, and immune-checkpoint expression. Additionally, RFX8 was found to regulate tumorigenesis and sensitivity to chelerythrine in AML. Conclusions: Our work delineated the landscape of the RFX family and associated genes in the pan-cancer context and the specific role of RFX8 in AML. These findings might offer cues for further investigations of these genes in cancer biology.

Pan-cancer analysis and single-cell analysis reveals FAM110B as a potential target for survival and immunotherapy.

Background: FAM110B belongs to the family that has a 110 sequence similarity (FAM110) and is located in the centrosome and mitotic spindle. FAM110B has been linked to tumor cell growth in earlier research. Uncertainty exists regarding FAM110B's function within the tumor microenvironment is unclear as well as pan-cancer. Methods: In order to assess the variation in FAM110B expression within normal and pan-cancer tissues, we combined the TCGA and GTEx databases. The cBioPortal database and the GSCALite platform were used to examine the variation in genome and methylation alteration of FAM110B. Cox regression, Kaplan-Meier, and SangerBox were employed to examine the clinical features and prognosis of FAM110B and pan-cancer. The purpose of the correlational research was to investigate the associations within immunerelated genes, tumor mutation burden, microsatellite instability, immune-related genes, and immunological checkpoints and FAM110B expression. ESTIMATE, EPIC, QUANTISEQ, and MCPCOUNTER methods were used to calculate the interaction among FAM110B expression as well as the tumor immune microenvironment. The immunoinfiltration and function of FAM110B were analyzed by single-cell databases (TISCH and CancerSEA). Finally, we evaluated the sensitivity of FAM110B to small-molecule medications through GDSC and CTRP databases. Results: The transcription and protein expression of FAM110B varies significantly throughout cancer types, and this has predictive value for the prognosis of some tumors; including brain lower grade glioma (LGG), stomach adenocarcinoma (STAD), pancreatic adenocarcinoma (PAAD), etc. In the tumor microenvironment, the expression level of FAM110B was associated with immune cell infiltration, immune checkpoint immune regulatory genes, tumor mutational burden, and microsatellite fragility to a certain extent. Conclusion: This work investigates the possibility of utility of FAM110B as a marker to forecast pan-cancer immunotherapy response, providing a theoretical basis for cancer therapy.

PRNP is a pan-cancer prognostic and immunity-related to EMT in colorectal cancer.

Background: Prion protein gene (PRNP) is widely expressed in a variety of tissues. Although the roles of PRNP in several cancers have been investigated, no pan-cancer analysis has revealed its relationship with tumorigenesis and immunity. Methods: Comprehensive analyses were conducted on The Cancer Genome Atlas (TCGA) Pan-Cancer dataset from the University of California Santa Cruz (UCSC) database to determine the expression of PRNP and its potential prognostic implications. Immune infiltration and enrichment analysis methods were used to ascertain correlations between PRNP expression levels, tumor immunity, and immunotherapy. Additionally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were employed to examine possible signaling pathways involving PRNP. In vitro experiments using CCK-8 assay, Wound healing assay, and Transwell assay to detect the effect of Cellular prion protein (PrPC) on proliferation, migration, and invasion in colorectal cancer (CRC) cells. The expression levels of epithelial-mesenchymal transition (EMT)-related proteins (N-cadherin, E-cadherin, Vimentin and Snail) were detected by western blot. Results: Among most cancer types, PRNP is expressed at high levels, which is linked to the prognosis of patients. PRNP expression is strongly associated with immune infiltrating cells, immunosuppressive cell infiltration and immune checkpoint molecules. In addition to tumor mutation burden (TMB), substantial correlations are detected between PRNP expression and microsatellite instability (MSI) in several cancers. In vitro cell studies inferred that PrPC enhanced the proliferation, migration, invasion, and EMT of CRC cells. Conclusion: PRNP serves as an immune-related prognostic marker that holds promise for predicting outcomes related to CRC immunotherapy while simultaneously promoting cell proliferation, migration, and invasion activities. Furthermore, it potentially plays a role in governing EMT regulation within CRC.

Targeting treatment resistance: unveiling the potential of RNA methylation regulators and TG-101,209 in pan-cancer neoadjuvant therapy.

BACKGROUND: Tumor recurrence and mortality rates remain challenging in cancer patients despite comprehensive treatment. Neoadjuvant chemotherapy and immunotherapy aim to eliminate residual tumor cells, reducing the risk of recurrence. However, drug resistance during neoadjuvant therapy is a significant hurdle. Recent studies suggest a correlation between RNA methylation regulators (RMRs) and response to neoadjuvant therapy. METHODS: Using a multi-center approach, we integrated advanced techniques such as single-cell transcriptomics, whole-genome sequencing, RNA sequencing, proteomics, machine learning, and in vivo/in vitro experiments. Analyzing pan-cancer cohorts, the association between neoadjuvant chemotherapy/immunotherapy effectiveness and RNA methylation using single-cell sequencing was investigated. Multi-omics analysis and machine learning algorithms identified genomic variations, transcriptional dysregulation, and prognostic relevance of RMRs, revealing distinct molecular subtypes guiding pan-cancer neoadjuvant therapy stratification. RESULTS: Our analysis unveiled a strong link between neoadjuvant therapy efficacy and RNA methylation dynamics, supported by pan-cancer single-cell sequencing data. Integration of omics data and machine learning algorithms identified RMR genomic variations, transcriptional dysregulation, and prognostic implications in pan-cancer. High-RMR-expressing tumors displayed increased genomic alterations, an immunosuppressive microenvironment, poorer prognosis, and resistance to neoadjuvant therapy. Molecular investigations and in vivo/in vitro experiments have substantiated that the JAK inhibitor TG-101,209 exerts notable effects on the immune microenvironment of tumors, rendering high-RMR-expressing pan-cancer tumors, particularly in pancreatic cancer, more susceptible to chemotherapy and immunotherapy. CONCLUSIONS: This study emphasizes the pivotal role of RMRs in pan-cancer neoadjuvant therapy, serving as predictive biomarkers for monitoring the tumor microenvironment, patient prognosis, and therapeutic response. Distinct molecular subtypes of RMRs aid individualized stratification in neoadjuvant therapy. Combining TG-101,209 adjuvant therapy presents a promising strategy to enhance the sensitivity of high-RMR-expressing tumors to chemotherapy and immunotherapy. However, further validation studies are necessary to fully understand the clinical utility of RNA methylation regulators and their impact on patient outcomes.

Comprehensive pan-cancer analysis of ACSS3 as a biomarker for prognosis and immunotherapy response.

Background: ACSS3 (acyl-CoA synthetase short-chain family member 3) is found in numerous tissues and is linked to tumor cell type development and metastasis. Methods: We conducted a comprehensive pan-cancer analysis of ACSS3. The TCGA (Cancer Genome Atlas), CPTAC (Clinical Proteomic Tumor Analysis Consortium), and HPA databases were used to ascertain the connection between ACSS3 and various types of tumors. Genes in the TCGA database would be identified using cBioPortal queries, and their transcriptome expression would then be verified using GEO data. ACSS3 expression and cellular localization in various tumor tissues of most cancer types were analyzed using single-cell sequencing data from the TISCH database. According to HPA and CPTAC databases, we analyzed and evaluated protein expression levels. Predictive analysis based on precise survival data of ACSS3 expression levels for 26 cancer types predicted using the TCGA database. Furthermore, we investigated the relationship between ACSS3 and immune microenvironments in different tumor tissues using the TIMER and TISCH databases. CellMiner, GDSC, and CTRP data would clarify the relationship between ACSS3 and drug resistance and explore the chemicals that affect ACSS3 expression. The final part of our study explored and validated the role ACSS3 played in glioma proliferation, migration, and invasion. Results: ACSS3 is differentially expressed in various tumors and exhibits early diagnostic value. ACSS3 expression is associated with clinical features, and high ACSS expression anticipates a worse prognosis in multiple tumors and may impact drug sensitivity. The changes in the immunosuppressive microenvironment of gliomas are closely related to the upregulation of ACSS3. Conclusions: ACSS3 is a novel biomarker for forecasting different human cancer prognoses, as it can influence the biological process by modulating the immune microenvironment. ACSS3 is a critical prognostic factor for glioma and is related to its proliferation, migration, and invasion.