Search Results (22)

Currently, there is no standard treatment for renal cell carcinoma (RCC) that is free of side effects and resistance. Additionally, limited information exists on how curcumin affects the gene expression profiles of patients with translocation renal cell carcinoma (tRCC) and papillary renal cell carcinoma (pRCC). The pathways responsible for metastasis in tRCC are still not well understood, and there is no established treatment or reliable biomarker to predict outcomes for metastatic tRCC. Primary clinical data from patients were retrieved from the TCGA database and analyzed using cBioPortal, stitch, string, R and Python. Various analyses were performed, including differential gene expression, protein-protein interaction (PPI) network analysis, drug-targeted gene analysis, gene ontology (GO), enrichment analyses, and systematic searches to assess the impact of curcumin on the transcriptomic profiles of tRCC, pRCC, and clear cell renal cell carcinoma (ccRCC). No significant impact of sensitive genes on survival in KIRC and KIRP was found, though a trend suggested they may delay disease progression. The combination of curcumin with sunitinib showed promise in overcoming drug resistance in ccRCC by inducing ferroptosis, reducing iron, and increasing ADAMTS18 expression. This study, leveraging data from the TCGA database and other databases explored the impact of curcumin on transcriptomic profiles in tRCC, pRCC, and clear cell RCC (ccRCC). Gene analysis revealed immune and metabolic differences, with KIRC showing a stronger immune response. This study is the first to propose that future research into the miR-148/ADAMTS18 genes and the ferroptosis pathway in tRCC and pRCC could lead to the development of new therapies and the identification of novel therapeutic targets, potentially overcoming drug resistance and metastasis. Full article

Lecithin cholesterol acyltransferase (LCAT) is a crucial enzyme in high-density lipoprotein (HDL) metabolism that is often dysregulated in cancers, affecting tumor growth and therapy response. We extensively studied LCAT expression in various malignancies, linking it to clinical outcomes and genetic/epigenetic alterations. We analyzed LCAT expression in multiple cancers and used the Cox regression model to correlate it with patient survival metrics, including overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). We also examined the copy number variations (CNVs), single-nucleotide variations (SNVs), DNA methylation, and N6-methyladenosine (m6A) modifications of LCAT and their connections to tumor immune responses and drug sensitivity. LCAT expression varies among cancers and correlates with patient outcomes. Low expression is linked to poor prognosis in low-grade glioma (LGG) and liver hepatocellular carcinoma (LIHC), while high expression is associated with better outcomes in adrenocortical carcinoma (ACC) and colon adenocarcinoma (COAD). In kidney renal papillary cell carcinoma (KIRP) and uterine corpus endometrial carcinoma (UCEC), LCAT CNV and methylation levels are prognostic markers. LCAT interacts with m6A modifiers and immune molecules, suggesting a role in immune evasion and as a biomarker for immunotherapy response. LCAT expression correlates with chemotherapeutic drug IC50 values, indicating potential for predicting treatment response. In ACC and COAD, LCAT may promote tumor growth, while in LGG and LIHC, it may inhibit progression. LCAT expression and activity regulation could be a new cancer therapy target. As a key molecule linking lipid metabolism, immune modulation, and tumor progression, the potential of LCAT in cancer therapy is significant. Our findings provide new insights into the role of LCAT in cancer biology and support the development of personalized treatment strategies. Full article

Background: Retinol-binding protein 4 (RBP4) is primarily recognized for its role in retinoid transport, but has recently been implicated in cancer progression and prognosis. However, a comprehensive pan-cancer analysis of RBP4’s expression, prognostic significance, and functional associations across various cancers is lacking. Methods: We conducted a pan-cancer analysis of RBP4 using data from public databases. RBP4 expression levels were examined in 33 tumor types, and correlations with clinical outcomes, immune cell infiltration, DNA methylation, and gene mutations were assessed. Enrichment analyses of RBP4 and its co-expressed genes were performed to explore associated biological pathways. Additionally, in vitro experiments were conducted to assess the effects of RBP4 on cell migration and proliferation. Results: RBP4 showed differential expression between tumor and normal tissues, with downregulation in 21 cancer types and upregulation in 6. High expression levels of RBP4 were associated with poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in specific cancers, notably in BRCA, HNSC, and STAD, whereas it was a favorable prognostic factor in cancers such as KIRP and MESO. RBP4 expression was also associated with immune cell infiltration, particularly with CD4+ Th2 cells and immune checkpoint genes. DNA methylation analysis suggested that the methylation of RBP4 may play a role in its regulatory mechanisms across cancer types. Enrichment analyses revealed that RBP4 and its co-expressed genes are involved in metabolism-related pathways and immune regulation. Functional assays indicated that RBP4 knockdown promoted tumor cell migration and proliferation. Conclusions: This study provides a comprehensive pan-cancer analysis of RBP4, identifying its prognostic potential and possible involvement in tumor immunity and metabolism. Our findings suggest that RBP4 could serve as a novel biomarker and therapeutic target in cancer, although further experimental studies are required to elucidate its precise mechanisms in specific cancer types. Full article

Purpose: Papillary renal cell carcinoma (PRCC), the second most common kidney cancer, is morphologically, genetically, and molecularly heterogeneous with diverse clinical manifestations. Genetic variations of PRCC and their association with survival are not yet well-understood. This study aimed to identify and validate survival-specific genes in PRCC and explore their clinical utility. Materials and Methods: Using machine learning, 293 patients from the Cancer Genome Atlas-Kidney Renal Papillary Cell Carcinoma (TCGA-KIRP) database were analyzed to derive genes associated with survival. To validate these genes, DNAs were extracted from the tissues of 60 Korean PRCC patients. Next generation sequencing was conducted using a customized PRCC gene panel of 202 genes, including 171 survival-specific genes. Kaplan–Meier and Log-rank tests were used for survival analysis. Fisher’s exact test was performed to assess the clinical utility of variant genes. Results: A total of 40 survival-specific genes were identified in the TCGA-KIRP database through machine learning and statistical analysis. Of them, 10 (BAP1, BRAF, CFDP1, EGFR, ITM2B, JAK1, NODAL, PCSK2, SPATA13, and SYT5) were validated in the Korean-KIRP database. Among these survival gene signatures, three genes (BAP1, PCSK2, and SPATA13) showed survival specificity in both overall survival (OS) (p = 0.00004, p = 1.38 × 10⁻⁷, and p = 0.026, respectively) and disease-free survival (DFS) (p = 0.00002, p = 1.21 × 10⁻⁷, and p = 0.036, respectively). Notably, the PCSK2 mutation demonstrated survival specificity uniquely in both the TCGA-KIRP (OS: p = 0.010 and DFS: p = 0.301) and Korean-KIRP (OS: p = 1.38 × 10⁻⁷ and DFS: p = 1.21 × 10⁻⁷) databases. Conclusions: We discovered and verified genes specific for the survival of PRCC patients in the TCGA-KIRP and Korean-KIRP databases. The survival gene signature, including PCSK2 commonly obtained from the 40 gene signature of TCGA and the 10 gene signature of the Korean database, is expected to provide insight into predicting the survival of PRCC patients and developing new treatment. Full article

The transketolase 1 gene (TKTL1) is an essential factor that contributes to brain development. Some studies have shown the influence of TKTL1 in cancers, but it has been rarely reported in kidney cancer. Furthermore, the role of TKTL1 in the prognosis and tumor infiltration of immune cells in various cancers, particularly kidney cancer, remains unknown. In this study, TKTL1 expression and its clinical characteristics were investigated using a variety of databases. TIMER was used to investigate the relationship between TKTL1 and immune infiltrates in various types of cancer. We also studied the relationship between TKTL1 expression and response to PD-1 blocker immunotherapy in renal cancer. We conducted TKTL1 agonists virtual screening from 13,633 natural compounds (L6020), implemented secondary library construction according to the types of top results, and then conducted secondary virtual screening for 367 alkaloids. Finally, in vitro assays of cell viability assays and colony formation assays were performed to demonstrate the pharmacological potency of the screening of TKTL1 agonists. Using these methods, we determined that TKTL1 significantly affects the prognostic potential in different types of kidney cancer patients. The underlying mechanism might be that the TKTL1 expression level was positively associated with devious immunocytes in kidney renal clear cell carcinoma (KIRC) rather than in kidney renal papillary cell carcinoma (KIRP) and kidney chromophobe (KICH). This recruitment may result from the up-regulation of the mTOR signaling pathway affecting T cell metabolism. We also found that TKTL1 may act as an immunomodulator in KIRC patients’ response to anti-PD-1 therapy. Moreover, we also found that piperine and glibenclamide are potent agonists of TKTL1. We have demonstrated, in vitro, that piperine and glibenclamide can inhibit the proliferation and clone formation of Caki-2 cell lines by agonizing the expression of TKTL1. In summary, our discovery implies that TKTL1 may be a promising prognostic biomarker for KIRC patients who respond to anti-PD-1 therapy. Piperine and glibenclamide may be effective therapeutic TKTL1 agonists, providing a theoretical basis for the clinical treatment of kidney cancer. Full article

Kidney renal papillary cell carcinoma (KIRP) is a highly heterogeneous type of kidney cancer, resulting in limited effective prognostic targets for KIRP patients. Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in the regulation of ferroptosis and iron metabolism, making them potential targets for the treatment and prognosis of KIRP. In this study, we constructed a ferroptosis-related lncRNA risk score model (FRM) based on the TCGA-KIRP dataset, which represents a novel subtype of KIRP not previously reported. The model demonstrated promising diagnostic accuracy and holds potential for clinical translation. We observed significant differences in metabolic activities, immune microenvironment, mutation landscape, ferroptosis sensitivity, and drug sensitivity between different risk groups. The high-risk groups exhibit significantly higher fractions of cancer-associated fibroblasts (CAFs), hematopoietic stem cells (HSC), and pericytes. Drugs (IC50) analysis provided a range of medication options based on different FRM typing. Additionally, we employed single-cell transcriptomics to further analyze the impact of immune invasion on the occurrence and development of KIRP. Overall, we have developed an accurate prognostic model based on the expression patterns of ferroptosis-related lncRNAs for KIRP. This model has the potential to contribute to the evaluation of patient prognosis, molecular characteristics, and treatment modalities, and can be further translated into clinical applications. Full article

The objective of our research was to examine the antioxidant and membrane-protective characteristics of a few medicinal plant extracts belonging to the Asteracea family, along with their flavonoid and polyphenolic content, in order to identify strategies for enhancing beverage composition and boosting the antioxidant capacity of green and black tea. The activity of aqueous-ethanolic extracts from the dried parts of plants, such as Arictum tomentosum Mill., Ghnapilum kasachstanicum Kirp. & Kuprian. ex Kirp., Artemisia schrenkiana Ledeb., A. rutifolia Steph. ex Spreng., A. cina O.Berg, and A. vulgaris L., were examined using a model of Wistar rats. Thiobarbituric acid-reacting substances (TBARS), a marker of malondialdehyde concentration, were used to measure the amount of lipid peroxidation (LPO) in liver microsomes. Considering the outcomes, the extracts from A. tomentosum, G. kasachstanicum, and A. vulgaris exhibit the strongest membrane-stabilizing action among those examined. At a concentration of 5 g/mL, the extracts of these plants demonstrated a significant anti-hemolitic impact, whereas the remaining extracts displayed a similar effect at doses above 10 g/mL. Accordingly, among the extracts studied, the A. tomentosum, G. kasachstanicum, A. schrenkiana, A. rutifolia, A. cina, and A. vulgaris extracts have significant antioxidant properties. The integrated antioxidant and antihemolytic qualities of A. tomentosum and green tea extracts were comparable to those of the individual plant extracts. When the extracts of A. schrenkiana and green tea were combined, similar outcomes were seen, suggesting that there was no appreciable synergistic interaction. Full article

Renal cell carcinoma (RCC) is the most common form of kidney cancer, consisting of multiple distinct subtypes. RCC has the highest mortality rate amongst the urogenital cancers, with kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), and kidney chromophobe carcinoma (KICH) being the most common subtypes. The Paired-box (PAX) gene family encodes transcription factors, which orchestrate multiple processes in cell lineage determination during embryonic development and organogenesis. Several PAX genes have been shown to be expressed in RCC following its onset and progression. Here, we performed real-time quantitative polymerase chain reaction (RT-qPCR) analysis on a series of human RCC cell lines, revealing significant co-expression of PAX2, PAX6, and PAX8. Knockdown of PAX2 or PAX8 mRNA expression using RNA interference (RNAi) in the A498 RCC cell line resulted in inhibition of cell proliferation, which aligns with our previous research, although no reduction in cell proliferation was observed using a PAX2 small interfering RNA (siRNA). We downloaded publicly available RNA-sequencing data and clinical histories of RCC patients from The Cancer Genome Atlas (TCGA) database. Based on the expression levels of PAX2, PAX6, and PAX8, RCC patients were categorized into two PAX expression subtypes, PAXClusterA and PAXClusterB, exhibiting significant differences in clinical characteristics. We found that the PAXClusterA expression subgroup was associated with favorable clinical outcomes and better overall survival. These findings provide novel insights into the association between PAX gene expression levels and clinical outcomes in RCC patients, potentially contributing to improved treatment strategies for RCC. Full article

Angiopoietin-like proteins (ANGPTL) constitute a family of eight proteins (1–8) which play a pivotal role in the regulation of various pathophysiological processes. The current study sought to identify high-risk, “non-synonymous, single-nucleotide polymorphisms” (nsSNPs) in both ANGPTL3 and ANGPTL8 to evaluate the role that these nsSNPs play in various types of cancer. We retrieved a total of 301 nsSNPs from various databases; 79 of these candidates constitute high-risk nsSNPs. Moreover, we identified eleven high-risk nsSNPs that cause various types of cancer: seven candidates for ANGPTL3 (L57H, F295L, L309F, K329M, R332L, S348C, and G409R) and four candidates for ANGPTL8 (P23L, R85W, R138S, and E148D). Protein–protein interaction analysis revealed a strong association of ANGPTL proteins with several tumor-suppressor proteins such as ITGB3, ITGAV, and RASSF5. ‘Gene-expression profiling interactive analysis’ (GEPIA) showed that expression of ANGPTL3 is significantly downregulated in five cancers: sarcoma (SARC); cholangio carcinoma (CHOL); kidney chromophobe carcinoma (KICH); kidney renal clear cell carcinoma (KIRC); and kidney renal papillary cell carcinoma (KIRP). GEPIA also showed that expression of ANGPTL8 remains downregulated in three cancers: CHOL; glioblastoma (GBM); and breast invasive carcinoma (BRCA). Survival rate analysis indicated that both upregulation and downregulation of ANGPTL3 and ANGPTL8 leads to low survival rates in various types of cancer. Overall, the current study revealed that both ANGPTL3 and ANGPTL8 constitute potential prognostic biomarkers for cancer; moreover, nsSNPs in these proteins might lead to the progression of cancer. However, further in vivo investigation will be helpful to validate the role of these proteins in the biology of cancer. Full article

There are several studies on the deregulated gene expression profiles in kidney cancer, with varying results depending on the tumor histology and other parameters. None of these, however, have identified the networks that the co-deregulated genes (co-DEGs), across different studies, create. Here, we reanalyzed 10 Gene Expression Omnibus (GEO) studies to detect and annotate co-deregulated signatures across different subtypes of kidney cancer or in single-gene perturbation experiments in kidney cancer cells and/or tissue. Using a systems biology approach, we aimed to decipher the networks they form along with their upstream regulators. Differential expression and upstream regulators, including transcription factors [MYC proto-oncogene (MYC), CCAAT enhancer binding protein delta (CEBPD), RELA proto-oncogene, NF-kB subunit (RELA), zinc finger MIZ-type containing 1 (ZMIZ1), negative elongation factor complex member E (NELFE) and Kruppel-like factor 4 (KLF4)] and protein kinases [Casein kinase 2 alpha 1 (CSNK2A1), mitogen-activated protein kinases 1 (MAPK1) and 14 (MAPK14), Sirtuin 1 (SIRT1), Cyclin dependent kinases 1 (CDK1) and 4 (CDK4), Homeodomain interacting protein kinase 2 (HIPK2) and Extracellular signal-regulated kinases 1 and 2 (ERK1/2)], were computed using the Characteristic Direction, as well as GEO2Enrichr and X2K, respectively, and further subjected to GO and KEGG pathways enrichment analyses. Furthermore, using CMap, DrugMatrix and the LINCS L1000 chemical perturbation databases, we highlight putative repurposing drugs, including Etoposide, Haloperidol, BW-B70C, Triamterene, Chlorphenesin, BRD-K79459005 and β-Estradiol 3-benzoate, among others, that may reverse the expression of the identified co-DEGs in kidney cancers. Of these, the cytotoxic effects of Etoposide, Catecholamine, Cyclosporin A, BW-B70C and Lasalocid sodium were validated in vitro. Overall, we identified critical co-DEGs across different subtypes in kidney cancer, and our results provide an innovative framework for their potential use in the future. Full article

KIF18A belongs to the Kinesin family, which participates in the occurrence and progression of tumors. However, few pan-cancer analyses have been performed on KIF18A to date. We used multiple public databases such as TIMER, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) to explore KIF18A mRNA expression in 33 tumors. We performed immunohistochemistry on liver cancer and pancreatic cancer tissues and corresponding normal tissues to examine the expression of KIF18A protein. Univariate Cox regression and Kaplan–Meier survival analysis were applied to detect the effect of KIF18A on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of patients with these tumors. Subsequently, we explored KIF18A gene alterations in different tumor tissues using cBioPortal. The relationship between KIF18A and clinical characteristics, tumor microenvironment (TME), immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repairs (MMRs), DNA methylation, RNA methylation, and drug sensitivity was applied for further study using the R language. Gene Set Enrichment Analysis (GSEA) was utilized to explore the molecular mechanism of KIF18A. Bioinformatic analysis and immunohistochemical experiments confirmed that KIF18A was up-regulated in 27 tumors and was correlated with the T stage, N stage, pathological stage, histological grade, and Ki-67 index in many cancers. The overexpression of KIF18A had poor OS, DSS, and PFI in adrenocortical carcinoma (ACC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower-grade glioma (LGG), liver cancer (LIHC), lung adenocarcinoma (LUAD), and pancreatic cancer (PAAD). Univariate and multivariate regression analysis confirmed KIF18A as an independent prognostic factor for LIHC and PAAD. The mutation frequency of KIF18A is the highest in endometrial cancer. KIF18A expression levels were positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, MMRs, DNA methylation, RNA methylation, and drug sensitivity in certain cancers. In addition, we discovered that KIF18A participated in the cell cycle at the single-cell level and GSEA analysis for most cancers. These findings suggested that KIF18A could be regarded as a latent prognostic marker and a new target for cancer immunological therapy. Full article

Cuproptosis, a new cell death pattern, is promising as an intervention target to treat tumors. Abnormal long non-coding RNA (lncRNA) expression is closely associated with the occurrence and development of papillary renal cell carcinoma (pRCC). However, cuproptosis-related lncRNAs (CRLs) remain largely unknown as prognostic markers for pRCC. We aimed to forecast the prognosis of pRCC patients by constructing models according to CRLs and to examine the correlation between the signatures and the inflammatory microenvironment. From the Cancer Genome Atlas (TCGA), RNA sequencing, genomic mutations and clinical data of TCGA-KIRP (Kidney renal papillary cell carcinoma) were analyzed. Randomly selected pRCC patients were allotted to the training and testing sets. To determine the independent prognostic impact of the training characteristic, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized, together with univariate and multivariate Cox regression models. Further validation was performed in the testing and whole cohorts. External datasets were utilized to verify the prognostic value of CRLs as well. The CRLs prognostic features in pRCC were established based on the five CRLs (AC244033.2, LINC00886, AP000866.1, MRPS9-AS1 and CKMT2-AS1). The utility of CRLs was evaluated and validated in training, testing and all sets on the basis of the Kaplan–Meier (KM) survival analysis. The risk score could be a robust prognostic factor to forecast clinical outcomes for pRCC patients by the LASSO algorithm and univariate and multivariate Cox regression. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data demonstrated that differentially expressed genes (DEGs) are primarily important for immune responses and the PI3K-Akt pathway. Arachidonic acid metabolism was enriched in the high-risk set by Gene Set Enrichment Analysis (GSEA). In addition, Tumor Immune Dysfunction and Exclusion (TIDE) analysis suggested that there was a high risk of immune escape in the high-risk cohort. The immune functions of the low- and high-risk sets differed significantly based on immune microenvironment analysis. Finally, four drugs were screened with a higher sensitivity to the high-risk set. Taken together, a novel model according to five CRLs was set up to forecast the prognosis of pRCC patients, which provides a potential strategy to treat pRCC by a combination of cuproptosis and immunotherapy. Full article

Doublesex and Mab-3 related Transcription Factor 3 (DMRT3) is associated with the prognosis of some tumors. It is possible to explore the role of DMRT3 in the cancer process using bioinformatic approaches and experimental validation. We comprehensively explored the clinical and immunological characteristics of DMRT3. The DMRT3 expression is abnormal in human cancers and correlates with clinical staging. A high DMRT3 expression is significantly associated with poor overall survival (OS) in KIRC, KIRP, LUAD, and UCEC. Amplification was the greatest frequency of the DMRT3 alterations in pan-cancer. The OS was significantly lower in the DMRT3 altered group than in the DMRT3 unaltered group (P = 0.0276). The DMRT3 expression was significantly associated with MSI in three cancer types and TMB in six cancer types. The DMRT3 expression was significantly correlated with the level of the immune cell infiltration and the immune checkpoint genes. The DMRT3 was involved in some pathways in pan-cancer. DMRT3 may play a role in chemotherapy and may be associated with chemoresistance. A ceRNA network of KCNQ1OT1/miR-335-5p/DMRT3 was constructed in LUAD. DMRT3 was significantly upregulated in the LUAD cell lines. DMRT3 was aberrantly expressed in pan-cancer and may promote tumorigenesis and progression via different mechanisms. DMRT3 can be used as a therapeutic target to treat cancer in humans. Full article

The succinate receptor, SUCNR1, has been attributed to tumor progression, metastasis, and immune response modulation upon its activation via the oncometabolite succinate. Nonetheless, little is known about the prognostic relevance of SUCNR1 and its association with tumor immune infiltrates and microbiota in renal cell carcinoma (RCC). Herein, publicly available platforms including Human Protein Atlas, cBioPortal, TIMER2.0, and TISIDB were utilized to depict a divergent implication of SUCNR1 in the immune microenvironment of clear cell RCC (KIRC) and papillary RCC (KIRP); the two major subtypes of RCC. Our results showed that the SUCNR1 expression level was augmented in RCC compared to other solid cancers, yet with opposite survival rate predictions in RCC subtypes. Consequently, a higher expression level of SUCNR1 was associated with a good disease-specific survival rate (p = 5.797 × 10⁻⁵) in KIRC patients albeit a poor prognostic prediction in KIRP patients (p = 1.9282 × 10⁻³). Intriguingly, SUCNR1 was mainly correlated to immunomodulators and diverse immune infiltrates in KIRP. Additionally, the SUCNR1 was mostly associated with a repertoire of microbes including beneficial bacteria that likely influenced a better disease-specific survival rate in KIRC. Our findings illustrate a significant novel subtype-specific role of SUCNR1 in RCC which potentially modulates tumor immune infiltration and microbiome signature, hence altering the prognosis of cancer patients. Full article

Tumor cells can be recognized through tumor surface antigens by immune cells and antibodies, which therefore can be used as drug targets for chimeric antigen receptor-T (CAR-T) therapies and antibody drug conjugates (ADCs). In this study, we aimed to identify novel tumor-specific antigens as targets for more effective and safer CAR-T cell therapies and ADCs. Here, we performed differential expression analysis of pan-cancer data obtained from the Cancer Genome Atlas (TCGA), and then performed a series of conditional screenings including Cox regression analysis, Pearson correlation analysis, and risk-score calculation to find tumor-specific cell membrane genes. A tumor tissue-specific and highly expressed gene set containing 3919 genes from 17 cancer types was obtained. Moreover, the prognostic roles of these genes and the functions of these highly expressed membrane proteins were assessed. Notably, 427, 584, 431 and 578 genes were identified as risk factors for LIHC, KIRC, UCEC, and KIRP, respectively. Functional enrichment analysis indicated that these tumor-specific surface proteins might confer tumor cells the ability to invade and metastasize. Furthermore, correlation analysis displayed that most overexpressed membrane proteins were positively correlated to each other. In addition, 371 target membrane protein-coding genes were sifted out by excluding proteins expressed in normal tissues. Apart from the identification of well-validated genes such as GPC3, MSLN and EGFR in the literature, we further confirmed the differential protein expression of 23 proteins: ADD2, DEF6, DOK3, ENO2, FMNL1, MICALL2, PARVG, PSTPIP1, FERMT1, PLEK2, CD109, GNG4, MAPT, OSBPL3, PLXNA1, ROBO1, SLC16A3, SLC26A6, SRGAP2, and TMEM65 in four types of tumors. In summary, our findings reveal novel tumor-specific antigens, which could be potentially used for next-generation CAR-T cell therapies and ADC discovery. Full article