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In the article, Helichrysum maracandicum Popov ex Kirp. grown in vitro. The results of the comparative study of amino acids, macro, micro and ultramicro elements in the flowers and leaves of the plant are presented. 20 amino acids and 44 elements were studied on the basis of inductively coupled plasma mass spectrometry in the generative and vegetative organs of the plant. The results of the study showed that the plant contains 7 non-exchangeable (Threonine, Valine, Methionine, Isoleucine, Leucine, Phenylalanine, Lysine), and the remaining 13 (Aspartic acid, Glutamic acid, Serine, Glycine, Asparagine, Glutamine, Cysteine, Arginine, Alanine, Proline) , Tyrosine, Histidine, Tryptophan) information on the presence of exchangeable amino acids.

Aims • This study was conducted to establish the potential competing endogeneous RNA (ceRNA) network for predicting prognoses in kidney papillary renal cell carcinoma (KIRP) and explore novel therapeutic targets. Methods • The edgeR package in R was used to determine differentially expressed messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), based on data from The Cancer Gene Atlas Program (TCGA) and the Genotype Expression (GTEx) databases. Weighted gene co-expression network analysis (WGCNA) was performed to filter out the mRNAs or lncRNAs that were strongly related to KIRP. The miRNAs that possibly sponged by differentially expressed RNAs lncRNAs (DElncRNAs) were screened using miRcode. Starbase, miRDB, and TargetScan sets were utilized to predict target mRNAs to corresponding miRNAs. LASSO and multivariate Cox regression analyses were applied for the determination of potential prognostic significance. Finally, the lncRNAmiRNA-mRNA ceRNA network was constructed. Results • A total of 1739 DEmRNAs and 1599 DElncRNAs were identified in KIRP. WGCNA analysis suggested that DEmRNAs in the blue module and DElncRNAs in the turquoise module were closely correlated with KIRP. An 8-gene signature was constructed, which had prognostic significance and predictive value in KIRP. Of note, a lncRNA-miRNA-mRNA ceRNA network (including 18 lncRNAs, 5 miRNAs, and 7 mRNAs) was established. Conclusion • This investigation constructed a new lncRNA-miRNA-mRNA ceRNA network, and proposed some genes that may be novel targets, as well as a theoretical basis for the treatment of patients with KIRP. (Altern Ther Health Med. [ABSTRACT FROM AUTHOR]

Background: Malignant cells exhibit reduced period circadian regulator 3 (PER3) expression. However, the underlying mechanisms of variations in PER3 expression in cancers and the specific function of PER3 in tumor progression remain poorly understood. Results: We explored multiple public databases, conducted bioinformatics analyses, and performed in vitro and in vivo experiments for validation. We found PER3 expression was decreased in most types of cancers, and PER3 downregulation was associated with a poor prognosis in 8 types of cancer. PER3 promoter methylation levels were increased in 11 types of cancer. Promoter hypermethylation (CpG islands [CGIs] cg12258811 and cg14204433) correlated with decreased PER3 expression in six cancers (breast invasive carcinoma, colon adenocarcinoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma [KIRP], lung adenocarcinoma [LUAD], and uterine corpus endometrial carcinoma). CGI cg12258811 hypermethylation was associated with reduced survival time and advanced cancer stages. Moreover, the bisulfite pyrosequencing assay confirmed CGI cg12258811 hypermethylation and its negative correlation with PER3 expression. In vitro and in vivo experiments demonstrated that PER3 inhibited KIRP and LUAD progression. Decitabine enhanced PER3 expression and inhibited KIRP cell functions by reducing promoter (cg12258811) methylation level. Conclusions: Our findings advanced the mechanistic understanding of variations in PER3 expression in cancers and confirmed the tumor-associated function of PER3 hypermethylation and downregulation. [ABSTRACT FROM AUTHOR]

Aims: This study was conducted to establish the potential competing endogeneous RNA (ceRNA) network for predicting prognoses in kidney papillary renal cell carcinoma (KIRP) and explore novel therapeutic targets., Methods: The edgeR package in R was used to determine differentially expressed messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), based on data from The Cancer Gene Atlas Program (TCGA) and the Genotype Expression (GTEx) databases. Weighted gene co-expression network analysis (WGCNA) was performed to filter out the mRNAs or lncRNAs that were strongly related to KIRP. The miRNAs that possibly sponged by differentially expressed RNAs lncRNAs (DElncRNAs) were screened using miRcode. Starbase, miRDB, and TargetScan sets were utilized to predict target mRNAs to corresponding miRNAs. LASSO and multivariate Cox regression analyses were applied for the determination of potential prognostic significance. Finally, the lncRNA-miRNA-mRNA ceRNA network was constructed., Results: A total of 1739 DEmRNAs and 1599 DElncRNAs were identified in KIRP. WGCNA analysis suggested that DEmRNAs in the blue module and DElncRNAs in the turquoise module were closely correlated with KIRP. An 8-gene signature was constructed, which had prognostic significance and predictive value in KIRP. Of note, a lncRNA-miRNA-mRNA ceRNA network (including 18 lncRNAs, 5 miRNAs, and 7 mRNAs) was established., Conclusion: This investigation constructed a new lncRNA-miRNA-mRNA ceRNA network, and proposed some genes that may be novel targets, as well as a theoretical basis for the treatment of patients with KIRP.

Abstract Background Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP. Methods RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors. Results In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP. Conclusions We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

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.

Purpose: Kidney renal papillary cell carcinoma (KIRP) is a highly heterogeneous malignancy and current systemic therapeutic strategies are difficult to achieve a satisfactory outcome for advanced disease. Meanwhile, there is a lack of effective biomarkers to predict the prognosis of KIRP. Methods: Using TCGA, GTEx, UALCAN, TIMER, TIMER 2.0 and STRING databases, we analyzed the relationship of SNHG6 with KIRP subtypes, tumor-infiltrating immune cells and potential target mRNAs. Based on TCGA data, ROC curves, Kaplan–Meier survival analysis and COX regression analysis were performed to evaluate the diagnostic and prognostic value of SNHG6 in KIRP. Nomogram was used to predict 3- and 5-year disease-specific survival in KIRP patients. In addition, with the help of Genetic ontology and Gene set enrichment analysis, the biological processes and signalling pathways that SNHG6 may be involved in KIRP were initially explored. Results: In patients with KIRP, SNHG6 was significantly upregulated and associated with a more aggressive subtype (lymph node involvement, pathological stage IV, CIMP phenotype) and poor prognosis. The ROC curve showed good diagnostic efficacy (AUC value: 0.828) and the C-index of the Nomogram for predicting DSS at 3 and 5 years was 0.920 (0.898–0.941). In the immune microenvironment of KIRP, SNHG6 expression levels were negatively correlated with macrophage abundance and positively correlated with cancer-associated fibroblasts. Furthermore, SNHG6 may promote KIRP progression by regulating the expression of molecules such as AURKB, NDC80, UBE2C, NUF2, PTTG1, CENPH, SPC25, CDCA3, CENPM, BIRC5, TROAP, EZH2. Last, GSEA suggests that SNHG6 may be involved in the regulation of the PPAR signalling pathway and the SLIT/ROBO signalling pathway. Conclusions: Our analysis suggests that a high SNHG6 expression status in KIRP is associated with a poorer prognosis for patients, and also elucidates some potential mechanisms contributing to this poorer outcome. This may provide new insights into the treatment and management of KIRP in the foreseeable future. [ABSTRACT FROM AUTHOR]

Background: Kidney renal papillary cell carcinoma (KIRP) is a rare malignancy with a very poor prognosis. Anoikis is a specific form of apoptosis involved in carcinogenesis, but the role of anoikis in KIRP has not been explored. Methods: Anoikis-related genes (ARGs) were obtained from the GeneCards database and Harmonizome database and were used to identify different subtypes of KIRP and construct a prognostic model of KIRP. In addition, we also explored the immune microenvironment and enrichment pathways among different subtypes by consensus clustering into different subtypes. Drug sensitivity analysis was used to screen for potential drugs. Finally, we verified the mRNA and protein expression of the independent prognostic gene PLK1 in patient tissues and various cells and further verified the changes in relevant prognostic functions after constructing a PLK1 stable knockdown model using ShRNA. Results: We identified 99 differentially expressed anoikis-related genes (DEGs) associated with KIRP survival, and selected 3 genes from them to construct a prognostic model, which can well predict the prognosis of KIRP patients. Consensus clustering divided KIRP into two subtypes, and there was a significant difference in survival rates between the two subtypes. Immune profiling revealed differing immune statuses between the two subtypes, and functional analysis reveals the differential activity of different functions in different subtypes. Drug sensitivity analysis screened out 15 highly sensitive drugs in the high-risk group and 11 highly sensitive drugs in the low-risk group. Univariate and multivariate Cox regression analysis confirmed that PLK1 was an independent prognostic factor in KIRP, and its mRNA and protein expression levels were consistent with gene differential expression levels, both of which were highly expressed in KIRP. Functional verification of PLK1 in KIRP revealed significant results. Specifically, silencing PLK1 inhibited cell proliferation, clonogenicity, and migration, which indicated that PLK1 plays an important role in the proliferation and migration of KIRP. Conclusion: The prognosis model constructed by ARGs in this study can accurately predict the prognosis of KIRP patients. ARGs, especially PLK1, play an important role in the development of KIRP. This research can help doctors provide individualized treatment plans for KIRP patients and provide researchers with new research ideas. [ABSTRACT FROM AUTHOR]

Background: Angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) allow entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into host cells and play essential roles in cancer therapy. However, the functions of ACE2 and TMPRSS2 in kidney cancer remain unclear, especially as kidneys are targets for SARS-CoV-2 infection. Methods: UCSC Xena project, the Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) databases (GSE30589 and GSE59185) were searched for gene expression in human tissues, gene expression data, and clinical information. Several bioinformatics methods were utilized to analyze the correlation between ACE2 and TMPRSS2 with respect to the prognosis of kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). Results: ACE2 expression was significantly upregulated in tumor tissue, while its downregulation was associated with low survival in KIRC and KIRP patients. TMPRSS2 was downregulated in KIRC and KIRP, and its expression was not correlated with patient survival. According to clinical risk factor-based prediction models, ACE2 exhibits predictive accuracy for kidney cancer prognosis and is correlated with metabolism and immune infiltration. In an animal model, ACE2 expression was remarkably downregulated in SARS-CoV-2-infected cells compared to in the control. Conclusion: ACE2 expression is highly correlated with various metabolic pathways and is involved in immune infiltration.it plays a crucial role than TMPRSS2 in diagnosing and prognosis of kidney cancer patients. The overlap in ACE2 expression between kidney cancer and SARS-CoV-2 infection suggests that patients with KIRC or KIRP are at high risk of developing serious symptoms., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

BackgroundErythropoietin-producing human hepatocellular (Eph) receptors stand out as the most expansive group of receptor tyrosine kinases (RTKs). Accumulating evidence suggests that within this expansive family, the EphA subset is implicated in driving cancer cell progression, proliferation, invasion, and metastasis, making it a promising target for anticancer treatment. Nonetheless, the extent of EphA family involvement across diverse cancers, along with its intricate interplay with immunity and the tumor microenvironment (TME), remains to be fully illuminated.MethodsThe relationships between EphA gene expression and patient survival, immunological subtypes, and TME characteristics were investigated based on The Cancer Genome Atlas (TCGA) database. The analyses employed various R packages.ResultsA significant difference in expression was identified for most EphA genes when comparing cancer tissues and non-cancer tissues. These genes independently functioned as prognostic factors spanning multiple cancer types. Moreover, a significant correlation surfaced between EphA gene expression and immune subtypes, except for EphA5, EphA6, and EphA8. EphA3 independently influenced the prognosis of papillary renal cell carcinoma (KIRP). This particular gene exhibited links with immune infiltration subtypes and clinicopathologic parameters, holding promise as a valuable biomarker for predicting prognosis and responsiveness to immunotherapy in patients with KIRP.ConclusionBy meticulously scrutinizing the panorama of EphA genes in a spectrum of cancers, this study supplemented a complete map of the effect of EphA family in Pan-cancer and suggested that EphA family may be a potential target for cancer therapy.

In the present work the composition of biogenic volatile organic compounds (BVOCs) and the essential oil (EO) of Helichrysum araxinum Takht. ex Kirp. aerial parts, together with the antimicrobial activity, were investigated. The results showed the prevalence of sesquiterpene hydrocarbons in both spontaneous emissions as well as in the EO. The main compounds of BVOCs were γ-curcumene (10.7%), γ-muurolene (9.2%), and β-selinene (8.5%). This latter constituent also showed a similar amount in the EO and represented the most abundant compounds together with α-selinene (8.0%). It is Interesting to note the same percentage of monoterpene hydrocarbons (MHs) in both the aroma profile and the EO (18.0%) with the same most abundant compounds: β-pinene (6.3% in BVOCs vs. 5.1% in EO, respectively) and limonene (4.5% in VOCs vs. 4.9% in EO, respectively). With regard to the antimycotic activity, the EO showed to be inactive against the tested strains, while a moderate antibacterial activity was shown against Staphylococcus isolates.

Simple Summary: This study aimed to identify and validate genes specific for the survival of patients with papillary renal cell carcinoma (PRCC) in the TCGA-KIRP and Korean-KIRP databases. Using machine learning with statistical analysis, 40 survival-specific genes were identified in TCGA-KIRP. Of them, 10 were verified as survival-specific genes for Korean-KIRP patients through next-generation sequencing. Among these, BAP1, PCSK2, and SPATA13 showed significant survival specificity in both overall survival and disease-free survival. Survival gene signatures, including PCSK2, which are commonly obtained from 40 gene signatures in TCGA and 10 gene signatures in Korean databases, are expected to provide insight into predicting the survival of PRCC patients and developing new treatments. 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. [ABSTRACT FROM AUTHOR]

Abstract Background Kidney renal papillary cell carcinoma (KIRP) is a dangerous cancer, which accounts for 15–20% of all kidney malignancies. Ferroptosis is a rare kind of cell death that overcomes medication resistance. Ferroptosis-related long non-coding RNAs (LNCRNAs) in KIRP, remain unknown. Method We wanted to express how ferroptosis-related LNCRNAs interact with immune cell infiltration in KIRP. Gene set enrichment analysis in the GO and KEGG databases were used to explore gene expression enrichment. The prognostic model was constructed using Lasso regression. In addition, we also analyzed the modifications in the tumor microenvironment (TME) and immunological association. Result The expression of LNCRNA was closely connected to the ferroptosis, according to co-expression analyses. CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were found to be significantly increased in the high-risk group, indicating that all of these markers implicates the malignancy processes for KIRP patients and may be cancer-promoting variables. LNCTAM34A and AC024022.1 were shown to be significantly elevated in the low-risk group; these might represent as the KIRP tumor suppressor genes. According to the TCGA, CCR, and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of CD160, TNFSF4, CD80, BTLA, and TNFRSF9 was different in the two risk groups. Conclusion LNCRNAs associated with ferroptosis were linked to the occurrence and progression of KIRP. Ferroptosis-related LNCRNAs and immune cell infiltration in the TME may be potential biomarkers in KIRP that should be further investigated.

Background: There is a surprising paucity of studies investigating the potential mechanism of SKA3 in the progression and prognosis of kidney renal papillary cell carcinoma (KIRP). Methods: We used TCGA and other databases to analyze the expression, clinical value, and potential mechanisms of SKA3 in KIRP patients. We also explored therapeutic agents for KIRP through GSCALite. Results: SKA3 mRNA expression was significantly upregulated and the area under the curve was 0.792 (95% CI 0.727– 0.856). Increased SKA3 expression was related to shorter overall survival, disease-specific survival and progression-free survival. Hub genes in protein–protein interactions were CDK1, CDC20, CCNB1, CCNA2, BUB1, AURKB, BUB1B, PLK1, CCNB2, and MAD2L1, which were differentially expressed and also associated with KIRP prognosis. Gene-set enrichment analysis indicated that E2F targets, epithelial–mesenchymal transition, glycolysis, the WNT signaling pathway, and other pathways were highly enriched upon SKA3 upregulation. Gene-set variation analysis of SKA3 and its ten hub genes showed that the significant correlation of cancer-related pathways included the cell cycle, DNA damage, hormone androgen receptor, hormone estrogen receptor, PI3K/Akt, and Ras/MAPK. In addition, we found that MEK inhibitors, ie, trametinib, selumetinib, PD0325901, and RDEA119, may be feasible targeting agents for KIRP patients. Conclusion: SKA3 might contribute to poor prognosis of KIRP through cell cycle, DNA damage, hormone androgen receptor, hormone estrogen receptor, PI3K/Akt, and RAS/MAPK. SKA3 potentially serves as a prognostic biomarker and target for KIRP. [ABSTRACT FROM AUTHOR]

Ferroptosis, an iron-dependent form of selective cell death, is involved in the development of many cancers. However, the role of ferroptosis-related genes (FRGs) in kidney renal papillary cell carcinoma (KIRP) is unclear. In this study, we examined the mRNA expression profiles and clinical data of patients with KIRP from the TCGA cohort. Consequently, 41 differentially-expressed FRGs were screened using the limma package, and 17 prognostic-related FRGs were identified by survival analysis and univariate Cox regression analyses. Thereafter, a ferroptosis-related gene prognostic index (FRGPI) was constructed based on five FRGs (AKR1C3, SAT1, FANCD2, HSBP1 and SQLE), using lasso Cox and multivariate Cox regression analyses. KIRP patients with high FRGPI scores displayed worse outcomes. Furthermore, the FRGPI was shown to be a reliable independent prognostic factor in both the training and testing cohorts. Comprehensive analysis also showed that the FRGPI can distinguish gene mutation, functional enrichment of immune cells and molecular function-related pathways. Interestingly, low FRGPI score could be more benefit from immune checkpoint inhibitors (ICIs) therapy. Then, the two hub prognostic genes (AKR1C3 and FANCD2) as a risk gene for KIRP were identified based on the FRGPI module, and the expression profiles of these two genes were validated using human KIRP cells, besides, we furthermore discovered that Fancd2 is significantly up-regulated in most cancers and is associated with prognosis. In conclusion, these findings showed that FRGPI can accurately predict the prognosis of patients with KIRP, suggesting that this risk model is a promising prognostic biomarker for these patients. Moreover, targeting ferroptosis (FANCD2) could be a potential therapeutic alternative for various cancers. [ABSTRACT FROM AUTHOR]