Soft tissue sarcoma is a highly malignant tumor with extensive heterogeneity across multiple omics. However, a comprehensive multi-omics subtyping system has not yet been established.

We integrated sarcoma multi-omics data, including clinical information, transcriptome expression profiles, DNA methylation, and somatic mutations. Using ten advanced clustering algorithms, we identified robust subtypes and validated the reproducibility of our analysis in two independent external datasets. We also identified subtype-specific treatment strategies and analyzed the differences in microenvironments between subtypes using single-cell data.

Based on multi-omics subtyping, we identified two novel sarcoma molecular subtypes, named sarcoma multi-omics subtype 1 (SAMS1) and SAMS2. SAMS2 exhibited a poorer prognosis, with significantly activated Myc, glycolysis, and Wnt beta-catenin signaling pathways. SAMS2 was characterized by a lower abundance of immune cell infiltration and anti-tumor immunity deficiency, which owned a lower response rate to immunotherapy but was sensitive to certain targeted drugs, including pazopanib, axitinib, thapsigargin, and elesclomol. MK886 and NU1025 were identified as effective therapeutic targets for the SAMS2. In SAMS2-like tumor epithelial cells, HOXB13/COL16A1 and BASP1 regulated epithelial-mesenchymal transition. We found that WNT7B was highly expressed in STS and was associated with poor patient prognosis, suggesting its potential as a novel therapeutic target for STS patients.

The STS molecular subtyping system based on multi-omics data effectively distinguishes patients with poor prognosis. The subtyping results are robust and reliable, providing new insights for the precise diagnosis and treatment of these patients.

Atherosclerosis (AS) is a chronic inflammatory disease characterized by endothelial dysfunction, monocyte infiltration, smooth muscle proliferation, and extracellular matrix accumulation. Endothelial cell (EC) dysfunction plays a pivotal role in the initiation and progression of AS. Despite progress in traditional research methods, the complexity of cellular heterogeneity within the disease remains poorly understood, necessitating a more refined approach for uncovering disease mechanisms.

In this study, we employed single-cell RNA sequencing (scRNA-seq) to map the endothelial cell landscape in AS comprehensively. By analyzing cellular heterogeneity, differentiation trajectories, and functional states, we identified critical endothelial subpopulations and their roles in the progression of AS. Functional enrichment and differentiation analyses were conducted, and the findings were validated through in vitro experiments.

The single-cell analysis revealed distinct EC subpopulations with unique contributions to AS progression. Among these, C1 CXCL12+ ECs emerged as a key subpopulation associated with endothelial differentiation, vascular remodeling, and inflammation. These cells demonstrated high proliferative potential and were enriched in pathways related to endothelial migration and repair. Through CCK-8, Transwell assay, EdU staining and angiogenesis ability, we found that knockdown of FOXM1 in C1 CXCL12+ ECs resulted in decreased proliferation, migration and invasion. Thus, it affects the progression of AS.

This study provides a detailed single-cell atlas of endothelial cells in AS, identifying critical subpopulations, regulatory pathways, and key factors driving disease progression. The application of single-cell technologies paves the way for advancing our understanding of cardiovascular diseases and offers significant potential for developing personalized therapeutic strategies in immunology and precision medicine.

Sunitinib remains the preferred systemic treatment option for specific patients with advanced RCC who are ineligible for immune therapy. However, it's essential to recognize that Sunitinib fails to elicit a favourable response in all patients. Moreover, most patients eventually develop resistance to Sunitinib. Therefore, identifying new targets associated with Sunitinib resistance is crucial. Utilizing multiple datasets from public cohorts, we conducted an exhaustive analysis and identified a total of 8 microRNAs and 112 mRNAs displaying significant expression differences between Sunitinib responsive and resistant groups. A particular set of six genes, specifically NIPSNAP1, STK40, SDC4, NEU1, TBC1D9, and PLAUR, were identified as highly significant via WGCNA. To delve deeper into the resistance mechanisms, we performed additional investigations using cell, molecular, and flow cytometry tests. These studies confirmed PLAUR's pivotal role in fostering Sunitinib resistance, both in vitro and in vivo. Our findings suggest that PLAUR could be a promising therapeutic target across various cancer types. In conclusion, this investigation not only uncovers vital genes and microRNAs associated with Sunitinib resistance in RCC but also introduces PLAUR as a prospective therapeutic target for diverse cancers. The outcomes contribute to advancing personalized healthcare and developing superior therapeutic strategies.

Kidney cancer has caused more than 150,000 deaths in 185 countries around the world and is a serious threat to human life. Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. FDX1, a crucial gene for regulating copper death, plays an important role in tumors. However, its specific role in ccRCC remains unclear. In this study, by analysing data from the TCGA-KIRC and GEO databases and validation in clinical samples from our center, the expression characteristics of FDX1 and its relationship with tumor clinicopathological features and patient prognosis were clarified; the effects of FDX1 overexpression on ccRCC cell proliferation, apoptosis, migration, and invasion were determined via cell phenotype experiments and mouse orthotopic renal tumor growth models; and the downstream regulatory mechanism of FDX1 was determined via TMT proteomic sequencing, Co-IP assays, and RNA-sequencing detection. Our results confirmed that FDX1 was significantly underexpressed in ccRCC and that reduced FDX1 expression was associated with adverse clinicopathologic features and poor prognosis. FDX1 overexpression markedly inhibited the proliferation, migration, and invasion of ccRCC cells and promoted cell apoptosis in vitro. Mechanistically, FDX1 bound to the FMR1 protein and upregulated its expression, subsequently restraining Bcl-2 and N-cadherin expression and enhancing ALCAM, Cleaved Caspase-3, and E-cadherin expression. In mouse models, FDX1 overexpression significantly suppressed the growth and metastasis of renal tumors, but this inhibitory effect was markedly reversed after FMR1 expression was knocked down. Thus, our results confirmed that FDX1 expression is significantly reduced in ccRCC and serves as a prognostic marker for ccRCC patients and that its overexpression suppresses the growth and metastasis ability of ccRCC by promoting the expression of FRM1.

Colorectal cancer (CRC) is a usual cancer and a kind of lethiferous cancer. Cuproptosis-related gene ferredoxin 1 (FDX1) has been discovered to act as a suppressor, thereby suppressing some cancers' progression. But, the regulatory functions of FDX1 in CRC progression keep vague. In this work, at first, through TCGA database, it was revealed that FDX1 exhibited lower expression in COAD (colon adenocarcinoma) tissues, and CRC patients with lower FDX1 expression had worse prognosis. Furthermore, FDX1 expression was verified to be down-regulated in CRC tissues (n = 30) and cells. It was further uncovered that FDX1 expression was positively correlated with CDH1 and TJP1 (epithelial marker), and negatively correlated with CDH2, TWIST1, and FN1 (stromal marker), suggesting that FDX1 was closely associated with the epithelial-mesenchymal transition (EMT) progress. Next, it was demonstrated that overexpression of FDX1 suppressed cell viability, invasion, and migration in CRC. Furthermore, it was verified that FDX1 retarded the EMT progress in CRC. Lastly, through rescue assays, the inhibited CRC progression mediated by FDX1 overexpression was rescued by EGF (EMT inducer) treatment. At last, it was uncovered that the tumor growth and metastasis were relieved after FDX1 overexpression, but these changes were reversed after EGF treatment. In conclusion, FDX1 inhibited the growth and progression of CRC by inhibiting EMT progress. This discovery hinted that FDX1 may act as an effective candidate for CRC treatment.

Background: Recently, exportin gene family members have been demonstrated to play essential roles in tumor progression. However, research on the clinical significance of exportin gene family members is limited in clear cell renal cell carcinoma (ccRCC). Methods: Pan-cancer data, ccRCC multiomics data, and single-cell sequence were included to analyze the differences in DNA methylation modification, single nucleotide variations (SNVs), copy number variations (CNVs), and expression levels of exportin gene family members. Non-negative matrix factorization was used to identify molecular subtypes based on exportin gene family members, and the prognostic and biological differences of different molecular subtypes were compared across multiple dimensions. Results: Exportin gene family members were upregulated in pan-cancer expression, and their aberrant expression was significantly influenced by DNA methylation, SNV, and CNV, particularly in ccRCC. Based on the expression matrix of exportin gene family members, two molecular subtypes, exportin famliy genes (XPO)-based subtype 1 (XPS1) and exportin famliy genes (XPO)-based subtype 2 (XPS2), were identified. The expression levels of exportin gene family members in the XPS2 subtype were significantly higher than those in XPS1, and the prognosis was poorer. The XPS2 subtype had lower immune component abundance and higher immune exhaustion scores. Its response rate to immunotherapy was significantly lower than that of the XPS1 subtype, but it was more sensitive to small molecules, including mercaptopurine and nutlin. Among them, exportin-1 (XPO1) is a potential diagnostic and therapeutic target for ccRCC, which can promote renal cancer progression by activating the PI3K-AKT-mTOR (phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase (AKT)/mechanistic target of rapamycin (MTOR)) and interferon alpha pathways. Conclusion: This study analyzed the variations of exportin gene family members at the pan-cancer level and identified two distinct ccRCC subtypes, which can guide personalized management of patients.

Emerging evidence suggests that the APOBEC family is implicated in multiple cancers and might be utilized as a new target for cancer detection and treatment. However, the dysregulation and clinical implication of the APOBEC family in clear cell renal cell cancer (ccRCC) remain elusive. TCGA multiomics data facilitated a comprehensive exploration of the APOBEC family across cancers, including ccRCC. Remodeling analysis classified ccRCC patients into two distinct subgroups: APOBEC family pattern cancer subtype 1 (APCS1) and subtype 2 (APCS2). The study investigated differences in clinical parameters, tumor immune microenvironment, therapeutic responsiveness, and genomic mutation landscapes between these subtypes. An APOBEC family-related risk model was developed and validated for predicting ccRCC patient prognosis, demonstrating good sensitivity and specificity. Finally, the overview of APOBEC3B function was investigated in multiple cancers and verified in clinical samples. APCS1 and APCS2 demonstrated considerably distinct clinical features and biological processes in ccRCC. APCS1, an aggressive subtype, has advanced clinical stage and a poor prognosis. APCS1 exhibited an oncogenic and metabolically active phenotype. APCS1 also exhibited a greater tumor mutation load and immunocompromised condition, resulting in immunological dysfunction and immune checkpoint treatment resistance. The genomic copy number variation of APCS1, including arm gain and loss, was much more than that of APCS2, which may help explain the tired immune system. Furthermore, the two subtypes have distinct drug sensitivity patterns in clinical specimens and matching cell lines. Finally, we developed a predictive risk model based on subtype biomarkers that performed well for ccRCC patients and validated the clinical impact of APOBEC3B. Aberrant APOBEC family expression patterns might modify the tumor immune microenvironment by increasing the genome mutation frequency, thus inducing an immune-exhausted phenotype. APOBEC family-based molecular subtypes could strengthen the understanding of ccRCC characterization and guide clinical treatment. Targeting APOBEC3B may be regarded as a new therapeutic target for ccRCC.

Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown.

In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified.

We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy.

This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

Copper, an indispensable micronutrient, is implicated in numerous vital biological processes and is essential for all physiological activities. Recently, the discovery of a novel type of copper-dependent cell death, known as cuproptosis, has shed light on its role in cancer development. Extensive research is currently underway to unravel the mechanisms underlying cuproptosis and its correlation with various cancer types. In this review, we summarize the findings regarding the roles and mechanisms of cuproptosis in various cancer types, including colorectal cancer, lung cancer, gastric cancer, breast cancer, liver cancer and cutaneous melanoma. Furthermore, the effects of copper-related agents such as copper chelators and copper ionophores on cell proliferation, apoptosis, angiogenesis, tumor immunity, and chemotherapy resistance have been explored in cancer preclinical and clinical trials. These insights provide promising avenues for the development of prospective anticancer drugs aimed at inducing cuproptosis.

Clear Cell Renal Cell Carcinoma (ccRCC) is the most common type of kidney cancer, characterized by high heterogeneity and complexity. Recent studies have identified mitochondrial defects and autophagy as key players in the development of ccRCC. This study aims to delve into the changes in mitophagic activity within ccRCC and its impact on the tumor microenvironment, revealing its role in tumor cell metabolism, development, and survival strategies.

Comprehensive analysis of ccRCC tumor tissues using single cell sequencing and spatial transcriptomics to reveal the role of mitophagy in ccRCC. Mitophagy was determined to be altered among renal clear cells by gene set scoring. Key mitophagy cell populations and key prognostic genes were identified using NMF analysis and survival analysis approaches. The role of UBB in ccRCC was also demonstrated by in vitro experiments.

Compared to normal kidney tissue, various cell types within ccRCC tumor tissues exhibited significantly increased levels of mitophagy, especially renal clear cells. Key genes associated with increased mitophagy levels, such as UBC, UBA52, TOMM7, UBB, MAP1LC3B, and CSNK2B, were identified, with their high expression closely linked to poor patient prognosis. Particularly, the ubiquitination process involving the UBB gene was found to be crucial for mitophagy and its quality control.

This study highlights the central role of mitophagy and its regulatory factors in the development of ccRCC, revealing the significance of the UBB gene and its associated ubiquitination process in disease progression.

Stomach adenocarcinoma (STAD) is one of the main reasons for cancer-related deaths worldwide. This investigation aimed to define the connection between STAD and Cuproptosis-related genes (CRGs). Cuproptosis is a newly identified form of mitochondrial cell death triggered by copper.

To explore the identification of potential biomarkers for STAD disease based on cuproptosis.

A predictive model using Gene Ontology (GO), Least Absolute Shrinkage and Selection Operator (LASSO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Variation Analysis (GSVA), and Gene Set Enrichment Analysis analyzed gene interconnections, focusing on 3 copper-related genes and their expression in The Cancer Genome Atlas-STAD. Networks for mRNA-miRNA and mRNA-transcription factor interactions were constructed. The prognostic significance of CRG scores was evaluated using time-receiver operating characteristic, Kaplan-Meier curves, and COX regression analysis. Validation was conducted with datasets GSE26942, GSE54129, and GSE66229. Expression of copper-related differentially expressed genes was also analyzed in various human tissues and gastric cancer subpopulations using the human protein atlas.

Three significant genes (FDX1, LIAS, MTF1) were identified and selected via LASSO analysis to predict and classify individuals with STAD into high and low CRG score subgroups. These genes were down-regulated in both risk categories. GO and KEGG analyses highlighted their involvement mainly in the electron transport chain. After validating their differential expression, FDX1 emerged as the most accurate diagnostic marker for gastric cancer. Additionally, the RCircos package localized FDX1 on chromosome 11.

Our study revealed that FDX1 could be a potential biomarker and treatment target for gastric malignancy, providing new ideas for further scientific research.

This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE22153, and GSE65904 cohorts from GEO database were processed and harmonized to mitigate batch effects. Lactate metabolism scores were assigned to individual cells using the 'AUCell' package. Weighted Co-expression Network Analysis (WGCNA) was employed to identify gene modules correlated with lactate metabolism. Machine learning algorithms were applied to construct a prognostic model, and its performance was evaluated in multiple cohorts. Immune correlation, mutation analysis, and enrichment analysis were conducted to further characterize the prognostic model's biological implications. Finally, the function of key gene NDUFS7 was verified by cell experiments. Machine learning resulted in an optimal prognostic model, demonstrating significant prognostic value across various cohorts. In the different cohorts, the high-risk group showed a poor prognosis. Immune analysis indicated differences in immune cell infiltration and checkpoint gene expression between risk groups. Mutation analysis identified genes with high mutation loads in SKCM. Enrichment analysis unveiled enriched pathways and biological processes in high-risk SKCM patients. NDUFS7 was found to be a hub gene in the protein-protein interaction network. After the expression of NDUFS7 was reduced by siRNA knockdown, CCK-8, colony formation, transwell and wound healing tests showed that the activity, proliferation and migration of A375 and WM115 cell lines were significantly decreased. This study offers insights into the prognostic significance of lactate metabolism-related genes in SKCM.

Cuproptosis provides a new therapeutic strategy for cancer treatment and is thought to have broad clinical application prospects. Nevertheless, some oncological clinical trials have yet to demonstrate favorable outcomes, highlighting the need for further research into the molecular mechanisms underlying cuproptosis in tumors. Cuproptosis primarily hinges on the intracellular accumulation of copper, with lipid metabolism exerting a profound influence on its course. The interaction between copper metabolism and lipid metabolism is closely related to cuproptosis. Copper imbalance can affect mitochondrial respiration and lipid metabolism changes, while lipid accumulation can promote copper uptake and absorption, and inhibit cuproptosis induced by copper. Anomalies in lipid metabolism can disrupt copper homeostasis within cells, potentially triggering cuproptosis. The interaction between cuproptosis and lipid metabolism regulates the occurrence, development, metastasis, chemotherapy drug resistance, and tumor immunity of cancer. Cuproptosis is a promising new target for cancer treatment. However, the influence of lipid metabolism and other factors should be taken into consideration. This review provides a brief overview of the characteristics of the interaction between cuproptosis and lipid metabolism in cancer and analyses potential strategies of applying cuproptosis for cancer treatment.

Metastasis of clear cell renal cell carcinoma (ccRCC) to the thyroid gland is rare, and simultaneous occurrence of ccRCC and papillary thyroid carcinoma (PTC) is even rarer. Due to the occult nature of the disease, the clinical diagnosis is difficult. In the case of multiple tumors, the possibility of thyroid metastasis should not be ignored during the clinical diagnosis and treatment of PTC. The present study reported a case with initial diagnosis of PTC and accidental discovery of thyroid metastasis of ccRCC. This case study aims to improve the understanding of occult thyroid metastasis, providing a reference for its clinical diagnosis and treatment. Accordingly, misdiagnosis and missed diagnosis of this disease may be reduced and the survival rate and the life quality of patients can be improved.

Breast cancer is one of the most common malignant tumors in women worldwide, and thus, it is important to enhance its treatment efficacy [1]. Copper has emerged as a critical trace element that affects various intracellular signaling pathways, gene expression, and biological metabolic processes [2], thereby playing a crucial role in the pathogenesis of breast cancer. Recent studies have identified cuproptosis, a newly discovered type of cell death, as an emerging therapeutic target for breast cancer treatment, thereby offering new hope for breast cancer patients. Tsvetkov's research has elucidated the mechanism of cuproptosis and uncovered the critical genes involved in its regulation [3]. Manipulating the expression of these genes could potentially serve as a promising therapeutic strategy for breast cancer treatment. Additionally, using copper ionophores and copper complexes combined with nanomaterials to induce cuproptosis may provide a potential approach to eliminating drug-resistant breast cancer cells, thus improving the therapeutic efficacy of chemotherapy, radiotherapy, and immunotherapy and eventually eradicating breast tumors. This review aims to highlight the practical significance of cuproptosis-related genes and the induction of cuproptosis in the clinical diagnosis and treatment of breast cancer. We examine the potential of cuproptosis as a novel therapeutic target for breast cancer, and we explore the present challenges and limitations of this approach. Our objective is to provide innovative ideas and references for the development of breast cancer treatment strategies based on cuproptosis.

The deregulation of fatty acid metabolism plays a pivotal role in cancer. Our objective is to construct a prognostic model for patients with endometrial carcinoma (EC) based on genes related to fatty acid metabolism-related genes (FAMGs). RNA sequencing and clinical data for EC were obtained from The Cancer Genome Atlas (TCGA). Lasso-Penalized Cox regression was employed to derive the risk formula for the model, the score = esum(corresponding coefficient × each gene's expression). Gene set enrichment analysis (GSEA) was utilized to examine the enrichment of KEGG and GO pathways within this model. Correlation analysis of immune function was conducted using Single-sample GSEA (ssGSEA). The "ESTIMATE" package in R was utilized to evaluate the tumor microenvironment. The support vector machine recursive feature elimination (SVM-RFE) and randomforest maps were employed to identify key genes. The effects of PTGIS on the malignant biological behavior of EC were assessed through CCK-8 assay, transwell invasion assay, cell cycle analysis, apoptosis assay, and tumor xenografts in nude mice. A novel prognostic signature comprising 10 FAMGs (INMT, ACACB, ACOT4, ACOXL, CYP4F3, FAAH, GPX1, HPGDS, PON3, PTGIS) was developed. This risk score serves as an independent prognostic marker validated for EC. According to ssGSEA analysis, the low- and high-risk groups exhibited distinct immune enrichments. The key gene PTGIS was screened by SVM-RFE and randomforest method. Furthermore, we validated the expression of PTGIS through qRT-PCR. In vitro and in vivo experiments also confirmed the effect of PTGIS on the malignant biological behavior of EC.