Cuproptosis-Associated lncRNA Establishes New Prognostic Profile and Predicts Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Mechanisms of cuproptosis and its relevance to distinct diseases

Copper is a trace element required by the organism, but once the level of copper exceeds the threshold, it becomes toxic and even causes death. The underlying mechanisms of copper-induced death are inconclusive, with different studies showing different opinions on the mechanism of copper-induced death. Multiple investigations have shown that copper induces oxidative stress, endoplasmic reticulum stress, nucleolar stress, and proteasome inhibition, all of which can result in cell death. The latest research elucidates a copper-dependent death and denominates it as cuproptosis. Cuproptosis takes place through the combination of copper and lipoylated proteins of the tricarboxylic acid cycle, triggering agglomeration of lipoylated proteins and loss of iron-sulfur cluster proteins, leading to proteotoxic stress and ultimately death. Given the toxicity and necessity of copper, abnormal levels of copper lead to diseases such as neurological diseases and cancer. The development of cancer has a high demand for copper, neurological diseases involve the change of copper contents and the binding of copper to proteins. There is a close relationship between these two kinds of diseases and copper. Here, we summarize the mechanisms of copper-related death, and the association between copper and diseases, to better figure out the influence of copper in cell death and diseases, thus advancing the clinical remedy of these diseases.

A cuproptosis-related lncRNAs signature predicts prognosis and reveals pivotal interactions between immune cells in colon cancer

Copper-mediated cell death presents distinct pathways from established apoptosis processes, suggesting alternative therapeutic approaches for colon cancer. Our research aims to develop a predictive framework utilizing long-noncoding RNAs (lncRNAs) related to cuproptosis to predict colon cancer outcomes while examining immune interactions and intercellular signaling. We obtained colon cancer-related human mRNA expression profiles and clinical information from the Cancer Genome Atlas repository. To isolate lncRNAs involved in cuproptosis, we applied Cox proportional hazards modeling alongside the least absolute shrinkage and selection operator technique. We elucidated the underlying mechanisms by examining the tumor mutational burden, the extent of immune cell penetration, and intercellular communication dynamics. Based on the model, drugs were predicted and validated with cytological experiments. A 13 lncRNA-cuproptosis-associated risk model was constructed. Two colon cancer cell lines were used to validate the predicted representative mRNAs with high correlation coefficients with copper-induced cell death. Survival enhancement in the low-risk cohort was evidenced by the trends in Kaplan-Meier survival estimates. Analysis of immune cell infiltration suggested that survival was induced by the increased infiltration of naïve CD4+ T cells and a reduction of M2 macrophages within the low-risk faction. Decreased infiltration of naïve B cells, resting NK cells, and M0 macrophages was significantly associated with better overall survival. Combined single-cell analysis suggested that CCL5-ACKR1, CCL2-ACKR1, and CCL5-CCR1 pathways play key roles in mediating intercellular dialogues among immune constituents within the neoplastic microhabitat. We identified three drugs with a high sensitivity in the high-risk group. In summary, this discovery establishes the possibility of using 13 cuproptosis-associated lncRNAs as a risk model to assess the prognosis, unravel the immune mechanisms and cell communication, and improve treatment options, which may provide a new idea for treating colon cancer.

Cuproptosis, the novel type of oxidation-induced cell death in thoracic cancers: can it enhance the success of immunotherapy?

Copper is an important metal micronutrient, required for the balanced growth and normal physiological functions of human organism. Copper-related toxicity and dysbalanced metabolism were associated with the disruption of intracellular respiration and the development of various diseases, including cancer. Notably, copper-induced cell death was defined as cuproptosis which was also observed in malignant cells, representing an attractive anti-cancer instrument. Excess of intracellular copper leads to the aggregation of lipoylation proteins and toxic stress, ultimately resulting in the activation of cell death. Differential expression of cuproptosis-related genes was detected in normal and malignant tissues. Cuproptosis-related genes were also linked to the regulation of oxidative stress, immune cell responses, and composition of tumor microenvironment. Activation of cuproptosis was associated with increased expression of redox-metabolism-regulating genes, such as ferredoxin 1 (FDX1), lipoic acid synthetase (LIAS), lipoyltransferase 1 (LIPT1), dihydrolipoamide dehydrogenase (DLD), drolipoamide S-acetyltransferase (DLAT), pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1), and pyruvate dehydrogenase E1 subunit beta (PDHB)). Accordingly, copper-activated network was suggested as an attractive target in cancer therapy. Mechanisms of cuproptosis and regulation of cuproptosis-related genes in different cancers and tumor microenvironment are discussed in this study. The analysis of current findings indicates that therapeutic regulation of copper signaling, and activation of cuproptosis-related targets may provide an effective tool for the improvement of immunotherapy regimens.

PDE3B regulates KRT6B and increases the sensitivity of bladder cancer cells to copper ionophores

Cuproptosis is a new Cu-dependent programmed cell death manner that has shown regulatory functions in many tumor types, however, its mechanism in bladder cancer remains unclear. Here, we reveal that Phosphodiesterase 3B (PDE3B), a cuproptosis-associated gene, could reduce the invasion and migration of bladder cancer. PDE3B is downregulated in bladder cancer tissues, which is correlated with better prognosis. Conversely, overexpression of PDE3B in bladder cancer cell could significantly resist invasion and migration, which is consistent with the TCGA database results. Future study demonstrate the anti-cancer effect of PDE3B is mediated by Keratin 6B (KRT6B) which leads to the keratinization. Therefore, PDE3B can reduce KRT6B expression and inhibit the invasion and migration of bladder cancer. Meanwhile, increased expression of PDE3B was able to enhance the sensitivity of Cuproptosis drug thiram. This study show that PDE3B/KRT6B is a potential cancer therapeutic target and PDE3B activation is able to increase the sensitivity of bladder cancer cells to copper ionophores.

Prediction of the survival status and tumor microenvironment in colorectal cancer through genotyping analysis based on toll-like receptors

BACKGROUND

Colorectal cancer (CRC) ranks third in both the incidence and mortality rates among male and female cancers, and it is the leading digestive system cancer. Due to the inter- and intratumor heterogeneity of cancer, the TNM system is insufficient for predicting prognosis, necessitating the use of molecular biomarkers for prognostic prediction. Toll-like receptors (TLRs) have been associated with CRC survival rates. This study focused on the investigation of the role and potential value of TLRs in CRC genotyping to aid in immunotherapy for CRC patients.

METHODS

Differential gene expression analysis was performed on CRC transcriptomic data from The Cancer Genome Atlas database. TLRs were referred from the literature, and their intersection with differentially expressed genes (DEGs) in CRC yielded TLR-DEGs. The expression patterns of TLR-DEGs were predicted using the STRING website, and copy number variations of TLR-DEGs were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on TLR-DEGs. ConsensusClusterPlus R package was used for clustering CRC patients, and ESTIMATE and GSEAbase were employed to analyze immune characteristics of different subtypes. Immune phenotyping scores and tumor immune dysfunction and exclusion scores were evaluated. DEGs of different subtypes were analyzed, followed by GO and KEGG enrichment analyses, the protein-protein interaction (PPI) network analysis, and further selection of hub genes. The sensitivity of drugs was assessed using the identified hub genes.

RESULTS

We identified 37 TLR-DEGs, and the PPI analysis revealed their coexpression, although they were distributed on different chromosomes. Enrichment analyses indicated that the 37 TLR-DEGs were linked to cancer cell immune response. Based on these TLR-DEGs, CRC patients were classified into three subtypes. Cluster2 exhibited lower survival rates and higher immune infiltration levels and predicted poorer response to immune checkpoint inhibitor therapy. The intersection of DEGs from cluster2 and cluster1 with DEGs from cluster2 and cluster3 yielded a set of 426 commonly shared DEGs. Enrichment analyses revealed that these shared DEGs might regulate immune cell viability. Eight common hub genes for different subtypes were further identified to predict drug-related correlations.

CONCLUSION

The developed TLR genotyping was used to predict the survival status and tumor microenvironment of CRC, providing a foundation for understanding the molecular mechanisms of TLR signaling and deepening its clinical significance.

LncRNA KIFAP3-5:1 inhibits epithelial-mesenchymal transition of renal tubular cell through PRRX1 in diabetic nephropathy

Long noncoding RNAs play an important role in several pathogenic processes in diabetic nephropathy, but the relationship with epithelial-mesenchymal transition in DN is unclear. Herein, we found that KIFAP3-5:1 expression was significantly down-regulated in DN plasma samples, db/db mouse kidney tissues and high glucose treated renal tubular epithelial cells compared to normal healthy samples and untreated cells. Overexpression of KIFAP3-5:1 improved renal fibrosis in db/db mice and rescued epithelial-mesenchymal transition of high glucose cultured renal tubular epithelial cells. The silence of KIFAP3-5:1 will exacerbate the progression of EMT. Mechanistically, KIFAP3-5:1 was confirmed to directly target to the -488 to -609 element of the PRRX1 promoter and negatively modulate PRRX1 mRNA and protein expressions. Furthermore, rescue assays demonstrated that the knockdown of PRRX1 counteracted the KIFAP3-5:1 low expression-mediated effects on EMT in hRPTECs cultured under high glucose. The plasma KIFAP3-5:1 of DN patients is highly correlated with the severity of renal dysfunction and plays an important role in the prediction model of DN diseases. These findings suggested that KIFAP3-5:1 plays a critical role in regulation of renal EMT and fibrosis through suppress PRRX1, and highlight the clinical potential of KIFAP3-5:1 to assist in the diagnosis of diabetic nephropathy.

Unravelling infiltrating T-cell heterogeneity in kidney renal clear cell carcinoma: Integrative single-cell and spatial transcriptomic profiling

Kidney renal clear cell carcinoma (KIRC) pathogenesis intricately involves immune system dynamics, particularly the role of T cells within the tumour microenvironment. Through a multifaceted approach encompassing single-cell RNA sequencing, spatial transcriptome analysis and bulk transcriptome profiling, we systematically explored the contribution of infiltrating T cells to KIRC heterogeneity. Employing high-density weighted gene co-expression network analysis (hdWGCNA), module scoring and machine learning, we identified a distinct signature of infiltrating T cell-associated genes (ITSGs). Spatial transcriptomic data were analysed using robust cell type decomposition (RCTD) to uncover spatial interactions. Further analyses included enrichment assessments, immune infiltration evaluations and drug susceptibility predictions. Experimental validation involved PCR experiments, CCK-8 assays, plate cloning assays, wound-healing assays and Transwell assays. Six subpopulations of infiltrating and proliferating T cells were identified in KIRC, with notable dynamics observed in mid- to late-stage disease progression. Spatial analysis revealed significant correlations between T cells and epithelial cells across varying distances within the tumour microenvironment. The ITSG-based prognostic model demonstrated robust predictive capabilities, implicating these genes in immune modulation and metabolic pathways and offering prognostic insights into drug sensitivity for 12 KIRC treatment agents. Experimental validation underscored the functional relevance of PPIB in KIRC cell proliferation, invasion and migration. Our study comprehensively characterizes infiltrating T-cell heterogeneity in KIRC using single-cell RNA sequencing and spatial transcriptome data. The stable prognostic model based on ITSGs unveils infiltrating T cells' prognostic potential, shedding light on the immune microenvironment and offering avenues for personalized treatment and immunotherapy.

Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

PURPOSE

This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database.

METHODS

First, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan-Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and cuproptosis, and may promote ccRCC progression.

RESULTS

We constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan-Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group.

CONCLUSION

Overall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.

Highly cytotoxic Cu(II) terpyridine complexes as chemotherapeutic agents

Cancer is considered as the biggest medicinal challenge worldwide. During a typical treatment, the tumorous tissue is removed in a surgical procedure and the patient further treated by chemotherapy. One of the most frequently applied drugs are platinum complexes. Despite their clinical success, these compounds are associated with severe side effects and low therapeutic efficiency. To overcome these limitations, herein, the synthesis and biological evaluation of Cu(II) terpyridine complexes as chemotherapeutic drug candidates is suggested. The compounds were found to be highly cytotoxic in the nanomolar range against various cancer cell lines. Mechanistic insights revealed that the compounds primarily accumulated in the cytoplasm and generated reactive oxygen species in this organelle, triggering cell death by apoptosis. Based on their high therapeutic effect, these metal complexes could serve as a starting point for further drug development.

SSH3 promotes pancreatic cancer proliferation and migration by activating the notch signaling pathway

Recent studies have indicated that the dual-specificity phosphatases (DUSP) family may play a role in the advancement of pancreatic cancer. Exploring the role of the DUSP family in pancreatic cancer development and discovering novel therapeutic targets are crucial for pancreatic cancer therapy. A critical subset of 20 genes exhibiting differential expression was identified, with particular emphasis on four key genes: DUSP10, PTP4A2, SSH3, and CDKN3 by multivariate Cox proportional hazards analysis. These genes were integral to developing a novel risk model for PC, which has been independently validated as a prognostic factor for patients. To provide help for clinical treatment, we performed tumor immune analysis and predicted potential chemical drugs. Notably, our research unveiled elevated expression levels of SSH3 in human PC cells and tissues. Intriguingly, SSH3 expression correlates with the patient grade, staging, and T stage in PC. Additional studies reveal SSH3's role in enhancing PC cell proliferation and migration, intricately linked to the activation of the Notch signaling pathway. These insights provide a deeper understanding of PC pathophysiology and pave the way for novel therapeutic interventions.

Deciphering the molecular landscape: integrating single-cell transcriptomics to unravel myofibroblast dynamics and therapeutic targets in clear cell renal cell carcinomas

Background

Clear cell renal cell carcinomas (ccRCCs) epitomize the most formidable clinical subtype among renal neoplasms. While the impact of tumor-associated fibroblasts on ccRCC progression is duly acknowledged, a paucity of literature exists elucidating the intricate mechanisms and signaling pathways operative at the individual cellular level.

Methods

Employing single-cell transcriptomic analysis, we meticulously curated UMAP profiles spanning substantial ccRCC populations, delving into the composition and intrinsic signaling pathways of these cohorts. Additionally, Myofibroblasts were fastidiously categorized into discrete subpopulations, with a thorough elucidation of the temporal trajectory relationships between these subpopulations. We further probed the cellular interaction pathways connecting pivotal subpopulations with tumors. Our endeavor also encompassed the identification of prognostic genes associated with these subpopulations through Bulk RNA-seq, subsequently validated through empirical experimentation.

Results

A notable escalation in the nFeature and nCount of Myofibroblasts and EPCs within ccRCCs was observed, notably enriched in oxidation-related pathways. This phenomenon is postulated to be closely associated with the heightened metabolic activities of Myofibroblasts and EPCs. The Myofibroblasts subpopulation, denoted as C3 HMGA1+ Myofibroblasts, emerges as a pivotal subset, displaying low differentiation and positioning itself at the terminal point of the temporal trajectory. Intriguingly, these cells exhibit a high degree of interaction with tumor cells through the MPZ signaling pathway network, suggesting that Myofibroblasts may facilitate tumor progression via this pathway. Prognostic genes associated with C3 were identified, among which TUBB3 is implicated in potential resistance to tumor recurrence. Finally, experimental validation revealed that the knockout of the key gene within the MPZ pathway, MPZL1, can inhibit tumor activity, proliferation, invasion, and migration capabilities.

Conclusion

This investigation delves into the intricate mechanisms and interaction pathways between Myofibroblasts and ccRCCs at the single-cell level. We propose that targeting MPZL1 and the oxidative phosphorylation pathway could serve as potential key targets for treating the progression and recurrence of ccRCC. This discovery paves the way for new directions in the treatment and prognosis diagnosis of ccRCC in the future.

Frontier knowledge and future directions of programmed cell death in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common renal malignancies of the urinary system. Patient outcomes are relatively poor due to the lack of early diagnostic markers and resistance to existing treatment options. Programmed cell death, also known as apoptosis, is a highly regulated and orchestrated form of cell death that occurs ubiquitously throughout various physiological processes. It plays a crucial role in maintaining homeostasis and the balance of cellular activities. The combination of immune checkpoint inhibitors plus targeted therapies is the first-line therapy to advanced RCC. Immune checkpoint inhibitors(ICIs) targeted CTLA-4 and PD-1 have been demonstrated to prompt tumor cell death by immunogenic cell death. Literatures on the rationale of VEGFR inhibitors and mTOR inhibitors to suppress RCC also implicate autophagic, apoptosis and ferroptosis. Accordingly, investigations of cell death modes have important implications for the improvement of existing treatment modalities and the proposal of new therapies for RCC. At present, the novel modes of cell death in renal cancer include ferroptosis, immunogenic cell death, apoptosis, pyroptosis, necroptosis, parthanatos, netotic cell death, cuproptosis, lysosomal-dependent cell death, autophagy-dependent cell death and mpt-driven necrosis, all of which belong to programmed cell death. In this review, we briefly describe the classification of cell death, and discuss the interactions and development between ccRCC and these novel forms of cell death, with a focus on ferroptosis, immunogenic cell death, and apoptosis, in an effort to present the theoretical underpinnings and research possibilities for the diagnosis and targeted treatment of ccRCC.

Recent Development on Copper-Sensor and its Biological Applications: A Review

Metal ion recognition is one of the most prospective research topics in the field of chemical sensors due to its wide range of clinical, biological and environmental applications. In this context, hydrazones are well known compounds that exhibit metal sensing and several biological properties due to the presence of N=CH- bond. Some of the biological properties includes anti-cancer, anti-tumor, anti-oxidant, anti-microbial activities. Hydrazones are also used as a ligand to detect metal ion as well as to generate metal complexes that exhibit medicinal properties. Thus, in recent years, many attempts were made to develop novel ligands with enhanced metal sensing and medicinal properties. In this review, some of the recent development on the hydrazones and their copper complexes are covered from the last few years from 2015-2023. These includes significance of copper ions, synthesis, biological properties, mechanism and metal sensing properties of some of the copper complexes were discussed.

The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA

Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.

Copper Metabolism and Cuproptosis: Molecular Mechanisms and Therapeutic Perspectives in Neurodegenerative Diseases

Copper is an essential trace element, and plays a vital role in numerous physiological processes within the human body. During normal metabolism, the human body maintains copper homeostasis. Copper deficiency or excess can adversely affect cellular function. Therefore, copper homeostasis is stringently regulated. Recent studies suggest that copper can trigger a specific form of cell death, namely, cuproptosis, which is triggered by excessive levels of intracellular copper. Cuproptosis induces the aggregation of mitochondrial lipoylated proteins, and the loss of iron-sulfur cluster proteins. In neurodegenerative diseases, the pathogenesis and progression of neurological disorders are linked to copper homeostasis. This review summarizes the advances in copper homeostasis and cuproptosis in the nervous system and neurodegenerative diseases. This offers research perspectives that provide new insights into the targeted treatment of neurodegenerative diseases based on cuproptosis.

Identification and Functional Characterization of PI3K/Akt/mTOR Pathway-Related lncRNAs in Lung Adenocarcinoma: A Retrospective Study

OBJECTIVE

This paper aimed to investigate the PI3K/Akt/mTOR signal-pathway regulator factor-related lncRNA signatures (PAM-SRFLncSigs), associated with regulators of the indicated signaling pathway in patients with lung adenocarcinoma (LUAD) undergoing immunotherapy.

MATERIALS AND METHODS

In this retrospective study, we employed univariate Cox, multivariate Cox, and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostically relevant long non-coding RNAs (lncRNAs), construct prognostic models, and perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Subsequently, immunoassay and chemotherapy drug screening were conducted. Finally, the prognostic model was validated using the Imvigor210 cohort, and tumor stem cells were analyzed.

RESULTS

We identified seven prognosis-related lncRNAs (AC084757.3, AC010999.2, LINC02802, AC026979.2, AC024896.1, LINC00941 and LINC01312). We also developed prognostic models to predict survival in patients with LUAD. KEGG enrichment analysis confirmed association of LUAD with the PI3K/Akt/mTOR signaling pathway. In the analysis of immune function pathways, we discovered three good prognostic pathways (Cytolytic_activity, Inflammation-promoting, T_cell_co-inhibition) in LUAD. Additionally, we screened 73 oncology chemotherapy drugs using the "pRRophetic" algorithm.

CONCLUSION

Identification of seven lncRNAs linked to regulators of the PI3K/Akt/mTOR signaling pathway provided valuable insights into predicting the prognosis of LUAD, understanding the immune microenvironment and optimizing immunotherapy strategies.

Cuproptosis-Related lncRNAs Modulate the Prognosis of MIBC by Regulating the Expression Pattern of Immunosuppressive Molecules Within the Tumor Microenvironment

Background

Cuproptosis-related gene and long non-coding RNA (lncRNA) modulation of cancer regulation is well-established. This investigation aimed to elucidate the prognostic implications of cuproptosis-associated lncRNAs in muscle-invasive bladder cancer (MIBC).

Methods

Employing the Cancer Genome Atlas (TCGA) and IMvigor210 cohorts, bioinformatics and statistical analyses probed the prognostic relevance of cuproptosis-related lncRNAs.

Results

Co-expression analysis revealed tight associations between lncRNA expression and cuproptosis-linked genes, with 13 cuproptosis-related lncRNAs found to correlate with MIBC prognosis. Lasso regression identified a six-lncRNA prognostic signature, enabling patient stratification into high- and low-risk categories. Tissue validation substantiated differential expression of FAM13A-AS1, GHRLOS, LINC00456, OPA1-AS1, RAP2C-AS1, and UBE2Q1-AS1 between MIBC tumor and normal tissues. Comparative analyses of tumor microenvironments and immune profiles between risk groups disclosed elevated immunosuppressive molecule expression, including programmed cell death-1 (PD-L1) and T-cell immunoglobulin-3 (TIM-3), in high-risk individuals.

Conclusion

These findings suggest that cuproptosis-related lncRNAs may modulate the expression of immunosuppressive molecules, thereby influencing MIBC tumorigenesis and progression. Further exploration is warranted to unveil novel therapeutic targets for MIBC based on the expression patterns of cuproptosis-related lncRNAs and their impact on immune responses in the tumor microenvironment.

Novel cuproptosis-related prognostic gene profiles in preeclampsia

BACKGROUND

Preeclampsia (PE) is a pregnancy-specific disorder with complex pathogenesis. Cuproptosis is a novel identified form of programmed cell death, however, the link between cuproptosis and clinical outcomes in PE is still not fully understood. In this study, we searched for cuproptosis-related genes (CRGs) in the placental tissues of normal and PE patients to clarify the importance of cuproptosis in the development of PE and provide potential predictive indicators for the occurrence of PE.

METHODS

Using RNA sequencing data in the GEO database, we conducted functional enrichment analysis of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), supported by linear regression model and operating characteristic curve (ROC) curve analysis, and summarized the role of CRGs in preeclampsia.

RESULTS

A total of 2831 differentially expressed genes related to PE were screened through multiple database analyses. After further intersection with 19 reported CRGs, 5 CRGs have been closely associated with the pathogenesis of PE, including NFE2L2, PDHA1, PDHB, DLD and GLS. NFE2L2 was identified as a key central gene. Pearson correlation analysis showed that CRGs could be related to several maternal and fetal outcome factors, including the highest pregnancy blood pressure, placenta weight, umbilical blood flow pulsatility index (PI), and neonatal weight. Linear regression equation revealed that the expression of NFE2L2 is negatively correlated with the highest pregnancy blood pressure and umbilical blood flow PI but positively correlated with placental weight and neonatal weight. QRT-PCR showed that the expression of these CRGs was significantly lower in placental tissues.

CONCLUSIONS

This cuproptosis pattern may be a potential prognostic factor in patients with PE and could provide new insights into disease progression.

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Disulfidptosis, a novel form of regulated cell death, occurs due to the aberrant accumulation of intracellular cystine and other disulfides. Moreover, targeting disulfidptosis could identify promising approaches for cancer treatment. Long non-coding RNAs (lncRNAs) are known to be critically implicated in clear cell renal cell carcinoma (ccRCC) development. Currently, the involvement of disulfidptosis-related lncRNAs in ccRCC is yet to be elucidated. This study primarily dealt with identifying and validating a disulfidptosis-related lncRNAs-based signature for predicting the prognosis and immune landscape of individuals with ccRCC. Clinical and RNA sequencing data of ccRCC samples were accessed from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted for the identification of the disulfidptosis-related lncRNAs. Additionally, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator Cox regression, and stepwise multivariate Cox analysis were executed to develop a novel risk prognostic model. The prognosis-predictive capacity of the model was then assessed using an integrated method. Variation in biological function was noted using GO, KEGG, and GSEA. Additionally, immune cell infiltration, the tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores were calculated to investigate differences in the immune landscape. Finally, the expression of hub disulfidptosis-related lncRNAs was validated using qPCR. We established a novel signature comprised of eight lncRNAs that were associated with disulfidptosis (SPINT1-AS1, AL121944.1, AC131009.3, AC104088.3, AL035071.1, LINC00886, AL035587.2, and AC007743.1). Kaplan-Meier and receiver operating characteristic curves demonstrated the acceptable predictive potency of the model. The nomogram and C-index confirmed the strong correlation between the risk signature and clinical decision-making. Furthermore, immune cell infiltration analysis and ssGSEA revealed significantly different immune statuses among risk groups. TMB analysis revealed the link between the high-risk group and high TMB. It is worth noting that the cumulative effect of the patients belonging to the high-risk group and having elevated TMB led to decreased patient survival times. The high-risk group depicted greater TIDE scores in contrast with the low-risk group, indicating greater potential for immune escape. Finally, qPCR validated the hub disulfidptosis-related lncRNAs in cell lines. The established novel signature holds potential regarding the prognosis prediction of individuals with ccRCC as well as predicting their responses to immunotherapy.

Identification of a 5-Gene Cuproptosis Signature Predicting the Prognosis for Colon Adenocarcinoma Based on WGCNA

Background: Colorectal cancer is a highly aggressive malignant tumor that primarily affects the digestive system. It is frequently diagnosed at an advanced stage. Cuproptosis is a copper-dependent form cell death mechanism, distinct from all other known pathways underlying cell death, tumor progression, prognosis, and immune response. Although the role of cuproptosis in colorectal cancer has been investigated over time, there is still an urgent need to explore new methods and insights to understand its potential function. Methods: The Gene Expression Omnibus and The Cancer Genome Atlas gene expression data were systematically explored to investigate the role of cuproptosis in colon adenocarcinoma. The weighted gene coexpression network analysis was used to construct a gene coexpression network and identify the critical module and cuproptosis-related genes correlated with colon adenocarcinoma prognosis. A cuproptosis-related genes prognostic signature for colon adenocarcinoma was identified and validated. To validate the identified gene signature, quantitative reverse transcription-polymerase chain reaction was performed. Cell proliferation assays were analyzed by CCK8 and cell cycle detection. In addition, reactive oxygen species assay was also analyzed. Results: Five hub cuproptosis-related genes (Dihydrolipoamide S-acetyltransferase, Cyclin-dependent kinase inhibitor 2A, ATOX1, VEGFA, and ULK1) were screened and a prognostic risk model for predicting overall survival was established based on these genes. The model was successfully tested in the validation cohort and the GEPIA database. Colon adenocarcinoma patients were categorized into high-risk and low-risk groups based on risk scores. The study revealed that patients with higher risk scores were more likely to have a poor prognosis. Moreover, Dihydrolipoamide S-acetyltransferase was a tumor suppressor gene that can induce cell death and affected the redox reactions in the colon cancer cell line. Conclusions: These findings suggest that the newly identified 5-gene signature may serve as a more reliable prognostic factor than clinical factors such as age and stage of disease. These findings offer a theoretical foundation for further investigation into potential cuproptosis-related biomarkers for predicting colon adenocarcinoma prognosis in the future.

Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients' survival under immunotherapy, and could provide valuable assistance for clinical practice.

Research progress in cuproptosis in liver cancer

Copper, like iron, is an essential trace metal element for human cells. The role of iron overload and ferroptosis has been gradually clarified in tumors, but the role of copper overload and cuproptosis is still being explored. Cuproptosis is a novel mode of cell death, secondary to impaired mitochondrial function induced by copper overload, and characterized by copper-dependent and programmed. The excessive copper leads to protein toxicity stress by binding to sulfhydryl proteins in the tricarboxylic acid (TCA) cycle of mitochondria, disrupting cellular homeostasis and triggering cuproptosis. Copper accumulation has carcinogenic effects on normal cells, dual effects on tumor cells. Liver cancer is one of the most common malignant tumors in China and even globally, with hepatocellular carcinoma (HCC) being the most common histological subtype. Copper exhibits dualism in HCC, as it both contributes to the growth and invasion of HCC cells, and exerts anticancer effects by inducing cuproptosis. Also, cuproptosis-related genes can be the evaluation of immunotherapy effect and the construction of prognostic models. Clarifying the role of copper death in liver cancer can help explore new methods for liver cancer screening, treatment, and prognosis evaluation.

Identification and validation of a seven cuproptosis-associated lncRNA signature to predict the prognosis of endometrial cancer

OBJECTIVE

Endometrial cancer (EC) is one of the most prevalent cancers in women. Long non-coding RNAs (lncRNAs) are potential diagnostic biomarkers in patients with EC.

METHODS

We obtained clinical information and transcriptome data for 552 patients with EC from The Cancer Genome Atlas database. Cuproptosis-associated lncRNAs were obtained through Pearson's correlation analysis. Univariate and multivariate Cox regression analyses were applied and a signature predicting overall survival (OS) among patients with EC was constructed. We also analyzed the tumor immune microenvironment and drug sensitivity. The results were validated by quantitative real time-polymerase chain reaction, and 5-ethynyl-2'-deoxyuridine and wound-healing assays.

RESULTS

Seven cuproptosis-associated lncRNAs related to prognosis were screened out and a signature was constructed. OS was significantly superior in the low-risk group. In addition, patients in the low-risk group had more CD8+ T cell infiltration, a stronger type II interferon response, and greater cisplatin sensitivity. Expression levels of some of the lncRNAs were significantly increased by cuproptosis. Furthermore, silencing of lncRNA AC084117.1 significantly inhibited the proliferation and migration of EC cells.

CONCLUSION

We constructed a seven cuproptosis-associated lncRNA signature to predict the prognosis of patients with EC with good predictive power.

Alternative splicing variants involved in pyroptosis and cuproptosis contribute to phenotypic remodeling of the tumor microenvironment in cervical cancer

Cervical cancer (CC) remains a prevalent gynecological malignancy, posing a significant health burden among women worldwide. With the remarkable discoveries of cellular pyroptosis and cuproptosis, there has been a growing focus on exploring the intricate relationship between these two forms of cell death and their impact on tumor progression. In recent years, alternative splicing has emerged as a significant field in cancer research. Thus, the integration of alternative splicing, pyroptosis, and cuproptosis holds immense value in studying their collective impact on the occurrence and progression of cervical cancer. In this study, alternative splicing data of pyroptosis- and cuproptosis-associated genes were integrated with public databases, including TCGA, to establish a prognostic model for cervical cancer based on COX regression modeling. Subsequently, the tumor microenvironment (TME) phenotypes in the high-risk and low-risk patient groups were characterized through a comprehensive bioinformatics analysis. The findings of this study revealed that the low-risk group exhibited a predominant immune-active TME phenotype, while the high-risk group displayed a tumor-favoring metabolic phenotype. These results indicate that the alternative splicing of pyroptosis- and cuproptosis-associated genes plays a pivotal role in remodeling the phenotypic landscape of the cervical cancer TME by modulating immune responses and metabolic pathways. This study provides valuable insights into the interplay between alternative splicing variants involved in pyroptosis and cuproptosis and the TME, contributing to a deeper understanding of cervical cancer pathogenesis and potential therapeutic avenues.

Identification of a novel cuproptosis-related gene signature for rheumatoid arthritis-A prospective study

BACKGROUND

Rheumatoid arthritis (RA) is a multifactorial systemic autoimmune disease characterized by ongoing synovial inflammation, leading to the degradation of cartilage. Cuproptosis, as a newly characterized form of cell death, may influence RA progression by regulating immune cells and chondrocytes. This study sets out to identify the hub cuproptosis-related gene (CRG) associated with the pathogenesis of RA.

METHODS

A series of bioinformatic analyses were performed to evaluate the expression score of CRGs and the immune infiltration landscape between RA and normal samples. The hub gene was screened through the correlation analysis of CRGs, and the interaction network between the hub gene and transcription factors (TFs) was constructed. Finally, the hub gene was validated through quantitative real-time polymerase chain reaction (qRT-PCR) of patient samples and cell experiments.

RESULTS

Drolipoamide S-acetyltransferase (DLAT) was screened as the hub gene. Correlation analysis between the hub gene and immune microenvironment demonstrated that DLAT had the highest correlation with T follicular helper cells. Eight pairs of DLAT-TF interaction networks were constructed. Single-cell sequencing showed that CRGs were highly expressed in RA chondrocytes, and chondrocytes could be classified into three different subsets. qRT-PCR was used to validate the above results. Dlat knockdown in immortalized human chondrocytes led to significantly improved mitochondrial membrane potentials and reduced levels of intracellular reactive oxygen species (ROS), mitochondrial ROS and apoptosis.

CONCLUSIONS

This study rudimentarily demonstrates the correlation between CRGs and immune cell infiltration in RA. The biomarker DLAT may provide comprehensive insights into the pathogenesis and drug targets of RA.

A comprehensive prognostic and immunological analysis of telomere-related lncRNAs in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent malignant tumors of the urinary system, with a high recurrence and metastasis rate. Telomeres and long non-coding RNAs (lncRNAs) have been documented playing critical roles in cancer progression. However, the prognostic significance of telomere-related lncRNA (TRLs) in KIRC is less well-defined. The Cancer Genome Atlas database was applied to retrieve the expression profiles and corresponding clinical information of KIRC patients. To create the TRLs prognostic signature, univariate Cox regression, least absolute shrinkage and selection operator analyses were performed. The prognostic signature, comprised of nine prognostic TRLs, was developed and demonstrated superior prognostic ability for KIRC patients. Additionally, the risk score acted as an independent prognostic indicator. A nomogram incorporating age, grade, stage, and signature-based risk scores was also developed and exhibited excellent predictive accuracy. Several immune activities were associated with the signature, as determined by gene function analysis. Further analysis revealed differences in the status of immunity and the tumor microenvironment between low- and high-risk groups. Notably, KIRC patients with high-risk scores were more responsive to immunotherapy and chemotherapy. To summarize, our study developed a new prognostic signature consisting of nine telomere-related lncRNA that can precisely predict the prognosis of KIRC patients. The signature was shown to be of substantial value for the tumor microenvironment and tumor mutation burden, thereby contributing to a framework for the individualized treatment of patients.

Disulfidptosis-associated long non-coding RNA signature predicts the prognosis, tumor microenvironment, and immunotherapy and chemotherapy options in colon adenocarcinoma

BACKGROUND

Disulfidptosis is independent of apoptosis, ferroptosis, and cuproptosis and is associated with cancer progression, treatment response, and prognosis. However, the predictive potential of disulfidptosis-associated lncRNAs in colon adenocarcinoma (COAD) and their features in the tumor immune microenvironment (TIME) require further elucidation.

METHODS

RNA transcriptome, clinical information, and mutation data of COAD samples were obtained from the TCGA database. The risk model was first constructed by co-expression analysis of disulfidptosis genes and lncRNAs, and prognostic lncRNAs were screened using Cox regression, followed by least absolute shrinkage and selection operator analysis. Enrichment analyses were performed to explore the underlying biological functions and signaling of model-associated differentially expressed genes (MADEGs). Moreover, TIME of MADEGs was analyzed to assess the immunotherapy. Finally, the expression levels of the lncRNAs were verified by taking specimens of patients with COAD from the Affiliated Hospital of Qingdao University.

RESULTS

We constructed a prognosis-related risk model based on four disulfidptosis-associated lncRNAs (ZEB1-AS1, SNHG16, SATB2-AS1, and ALMS1-IT1). By analyzing the survival of patients in the whole, training, and test groups, we found that patients with COAD in the low-risk group had better overall survival than those in the high-risk group. Validation of the model via Cox analysis and clinical indicators demonstrated that the model had a decent potential for predicting the prognosis of patients with COAD. Enrichment analyses revealed that the MADEGs were related to disulfidptosis-associated biological functions and cancer pathways. Furthermore, patients with COAD in the high-risk group had more positive responses to immune checkpoint inhibitors (ICIs) than those in the low-risk group, as confirmed by TIME analysis. ZEB1-AS1, SNHG16, and ALMS1-IT1 were expressed at higher levels in tumor samples than those in the corresponding paracancerous samples (p < 0.05), whereas SATB2-AS1 was upregulated in the paracancerous samples (p < 0.05).

CONCLUSIONS

This signature may guide prognosis, molecular mechanisms, and treatment strategies, including ICIs and chemotherapy, in patients with COAD.

A cuproptosis-related lncRNA signature-based prognostic model featuring on metastasis and drug selection strategy for patients with lung adenocarcinoma

Introduction: Lung adenocarcinoma is a common cause of mortality in patients with cancer. Recent studies have indicated that copper-related cell death may not occur in the same way as previously described. Long non-coding RNAs (lncRNAs) play a key role in the occurrence and development of tumors; however, the relationship between cuproptosis and lncRNAs in tumorigenesis and lung adenocarcinoma (LUAD) treatment has not been well established. Our study aimed to construct a model to analyze the prognosis of lung adenocarcinoma in patients using a carcinogenesis-related lncRNA (CR) signature. Methods: The transcriptional profiles of 507 samples from The Cancer Genome Atlas were assessed. Cox regression and co-expression analyses, and the least absolute shrinkage and selection operator (LASSO) were used to filter the CR and develop the model. The expression status of the six prognostic CRs was used to classify all samples into high- and low-risk groups. The overall disease-free survival rate was compared between the two groups. The Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used to identify the pathways and mechanisms involved in this model. Subsequently, immunotherapy response, sensitivity, and correlation analyses for several anti-tumor medications were performed. In vitro experiments, including qPCR, were conducted in nine lung adenocarcinoma cell lines and 16 pairs of lung adenocarcinoma and para-carcinoma tissues. Results: After confirmation using the ROC curve, patients in the low-risk category benefited from both overall and disease-free survival. Gene Ontology analysis highlighted cell movement in the model. In the in vitro experiments, qPCR results showed the expression levels of six CRs in 16 pairs of carcinoma and para-carcinoma tissues, which were in accordance with the results of the model. AL138778.1 is a protective factor that can weaken the invasion and migration of A549 cells, and AL360270.1 is a hazardous factor that promotes the invasion and migration of A549 cells. According to this model, targeted treatments such as axitinib, gefitinib, linsitinib, pazopanib, and sorafenib may be more appropriate for low-risk patients. Conclusion: Six CR profiles (AL360270.1, AL138778.1, CDKN2A-DT, AP003778.1, LINC02718, and AC034102.8) with predictive values may be used to evaluate the prognosis of patients with lung adenocarcinoma undergoing therapy.

Construction and validation of cuproptosis-related lncRNA prediction signature for bladder cancer and immune infiltration analysis

Bladder cancer (BC) is a common urologic tumor with a high recurrence rate. Cuproptosis and long noncoding RNAs (lncRNAs) have demonstrated essential roles in the tumorigenesis of many malignancies. Nevertheless, the prognostic value of cuproptosis-related lncRNA (CRLs) in BC is still unclear. The public data used for this study were acquired from the Cancer Genome Atlas database. A comprehensive exploration of the expression profile, mutation, co-expression, and enrichment analyses of cuproptosis-related genes was performed. A total of 466 CRLs were identified using Pearson's correlation analysis. 16 prognostic CRLs were then retained by univariate Cox regression. Unsupervised clustering divided the patients into two clusters with diverse survival outcomes. The signature consists of 7 CRLs was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Survival curves and receiver operating characteristics showed the prognostic signature possessed good predictive value, which was validated in the testing and entire sets. The reliability and stability of our signature were further confirmed by stratified analysis. Additionally, the signature-based risk score was confirmed as an independent prognostic factor. Gene set enrichment analysis showed molecular alteration in the high-risk group was closely associated with cancer. We then developed the clinical nomogram using independent prognostic indicators. Notably, the infiltration of immune cells and expression of immune checkpoints were higher in the high-risk group, suggesting that they may benefit more from immunotherapy. In summary, the prognostic signature might effectively predict the prognosis and provide new insight into the clinical treatment of BC patients.

[Construction of Lung Adenocarcinoma Prognosis Model and Drug Sensitivity Analysis Based on Cuproptosis Related Genes]

BACKGROUND

Lung cancer is one of the most common malignant tumors in the world, and the current lung cancer screening and treatment strategies are constantly improving, but its 5-year survival rate is still very low, which seriously endangers human health. Therefore, it is critical to explore new biomarkers to provide personalized treatment and improve the prognosis. Cuproptosis is a newly discovered type of cell death, which is due to the accumulation of excess copper ions in the cell, eventually leading to cell death, which has been suggested by studies to be closely related to the occurrence and development of lung adenocarcinoma (LUAD). Based on The Cancer Genome Atlas (TCGA) database, this study explored the association between cuproptosis-related genes (CRGs) and LUAD prognosis, established a prognostic risk model, and analyzed the interaction between CRGs and LUAD immune cell infiltration.

METHODS

The RNA-seq data of LUAD tissue and paracancerous or normal lung tissue were downloaded from the TCGA database; the RNA-seq data of normal lung tissue was downloaded from the Genotype-tissue Expression (GTEx) database, and the data of 462 lung adenocarcinoma cases were downloaded from the Gene Expression Omnibus repository (GEO) as verification. T the risk score model to assess prognosis was constructed by univariate Cox and Lasso-Cox regression analysis, and the predictive ability of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Immune-related and drug susceptibility analysis was further performed on high- and low-risk groups.

RESULTS

A total of 1656 CRGs and 1356 differentially expressed CRGs were obtained, and 13 CRGs were screened out based on univariate Cox and Lasso-Cox regression analysis to construct a prognostic risk model, and the area under the curves (AUCs) of ROC curves 1-, 3- and 5- year were 0.749, 0.740 and 0.689, respectively. Further study of immune-related functions and immune checkpoint differential analysis between high- and low-risk groups was done. High-risk groups were more sensitive to drugs such as Savolitinib, Palbociclib, and Cytarabine and were more likely to benefit from immunotherapy.

CONCLUSIONS

The risk model constructed based on 13 CRGs has good prognostic value, which can assist LUAD patients in individualized treatment, and provides an important theoretical basis for the treatment and prognosis of LUAD.

Multi-omics analysis uncovers clinical, immunological, and pharmacogenomic implications of cuproptosis in clear cell renal cell carcinoma

OBJECTIVE

The latest research proposed a novel copper-dependent programmed cell death named cuproptosis. We aimed to elucidate the influence of cuproptosis in clear cell renal cell carcinoma (ccRCC) from a multi-omic perspective.

METHODS

This study systematically assessed mRNA expression, methylation, and genetic alterations of cuproptosis genes in TCGA ccRCC samples. Through unsupervised clustering analysis, the samples were classified as different cuproptosis subtypes, which were verified through NTP method in the E-MTAB-1980 dataset. Next, the cuproptosis score (Cuscore) was computed based on cuproptosis-related genes via PCA. We also evaluated clinical and immunogenomic features, drug sensitivity, immunotherapeutic response, and post-transcriptional regulation.

RESULTS

Cuproptosis genes presented multi-layer alterations in ccRCC, and were linked with patients' survival and immune microenvironment. We defined three cuproptosis subtypes [C1 (moderate cuproptosis), C2 (low cuproptosis), and C3 (high cuproptosis)], and the robustness and reproducibility of this classification was further proven. Overall survival was best in C3, moderate in C1, and worst in C2. C1 had the highest sensitivity to pazopanib, and sorafenib, while C2 was most sensitive to sunitinib. Furthermore, C1 patients benefited more from anti-PD-1 immunotherapy. Patients with high Cuscore presented the notable survival advantage. Cuscore was highly linked with immunogenomic features, and post-transcriptional events that contributed to ccRCC development. Finally, several potential compounds and druggable targets (NMU, RARRES1) were selected for low Cuscore group.

CONCLUSION

Overall, our study revealed the non-negligible role of cuproptosis in ccRCC development. Evaluation of the cuproptosis subtypes improves our cognition of immunogenomic features and better guides personalized prognostication and precision therapy.

Cuproptosis-related gene expression is associated with immune infiltration and CD47/CD24 expression in glioblastoma, and a risk score based on these genes can predict the survival and prognosis of patients

Introduction

Glioblastoma (GBM) is the most invasive type of glioma, is insensitive to radiotherapy and chemotherapy, and has high proliferation and invasive ability, with a 5-year survival rate of <5%. Cuproptosis-related genes (CRGs) have been successfully used to predict the prognosis of many types of tumors. However, the relationship between cuproptosis and GBM remains unclear.

Methods

Here, we sought to identify CRGs in GBM and elucidate their role in the tumor immune microenvironment and prognosis. To that aim, changes in CRGs in The Cancer Genome Atlas (TCGA) transcriptional and Gene Expression Omnibus (GEO) datasets (GEO4290 and GEO15824) were characterized, and the expression patterns of these genes were analyzed.

Results

A risk score based on CRG expression characteristics could predict the survival and prognosis of patients with GBM and was significantly associated with immune infiltration levels and the expression of CD47 and CD24, which are immune checkpoints of the "don't eat me "signal. Furthermore, we found that the CDKN2A gene may predict GBM sensitivity and resistance to drugs.

Discussion

Our findings suggest that CRGs play a crucial role in GBM outcomes and provide new insights into CRG-related target drugs/molecules for cancer prevention and treatment.

Cuproptosis-related lncRNAs predict prognosis and immune response of thyroid carcinoma

Objective: To estimate the survival and prognosis of patients with thyroid carcinoma (THCA) based on the Long non-coding RNA (lncRNA) traits linked to cuproptosis and to investigate the connection between the immunological spectrum of THCA and medication sensitivity. Methods: RNA-Seq data and clinical information for THCA were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We built a risk prognosis model by identifying and excluding lncRNAs associated with cuproptosis using Cox regression and LASSO methods. Both possible biological and immune infiltration functions were investigated using Principal Component Analysis (PCA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immunoassays. The sensitivity of the immune response to possible THCA medicines was assessed using ratings for tumor immune dysfunction and exclusion (TIDE) and tumor mutational burden (TMB). Results: Seven cuproptosis-related lncRNAs were used to construct our prognostic prediction model: AC108704.1, DIO3OS, AL157388.1, AL138767.3, STARD13-AS, AC008532.1, and PLBD1-AS1. Using data from TCGA's training, testing, and all groups, Kaplan-Meier and ROC curves demonstrated this feature's adequate predictive validity. Different clinical characteristics have varying effects on cuproptosis-related lncRNA risk models. Further analysis of immune cell infiltration and single sample Gene Set Enrichment Analysis (ssGSEA) supported the possibility that cuproptosis-associated lncRNAs and THCA tumor immunity were closely connected. Significantly, individuals with THCA showed a considerable decline in survival owing to the superposition effect of patients in the high-risk category and high TMB. Additionally, the low-risk group had a higher TIDE score compared with the high-risk group, indicating that these patients had suboptimal immune checkpoint blocking responses. To ensure the accuracy and reliability of our results, we further verified them using several GEO databases. Conclusion: The clinical and risk aspects of cuproptosis-related lncRNAs may aid in determining the prognosis of patients with THCA and improving therapeutic choices.

Multi-omics identification of an immunogenic cell death-related signature for clear cell renal cell carcinoma in the context of 3P medicine and based on a 101-combination machine learning computational framework

Background

Clear cell renal cell carcinoma (ccRCC) is a prevalent urological malignancy associated with a high mortality rate. The lack of a reliable prognostic biomarker undermines the efficacy of its predictive, preventive, and personalized medicine (PPPM/3PM) approach. Immunogenic cell death (ICD) is a specific type of programmed cell death that is tightly associated with anti-cancer immunity. However, the role of ICD in ccRCC remains unclear.

Methods

Based on AddModuleScore, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network (WGCNA) analyses, ICD-related genes were screened at both the single-cell and bulk transcriptome levels. We developed a novel machine learning framework that incorporated 10 machine learning algorithms and their 101 combinations to construct a consensus immunogenic cell death-related signature (ICDRS). ICDRS was evaluated in the training, internal validation, and external validation sets. An ICDRS-integrated nomogram was constructed to provide a quantitative tool for predicting prognosis in clinical practice. Multi-omics analysis was performed, including genome, single-cell transcriptome, and bulk transcriptome, to gain a more comprehensive understanding of the prognosis signature. We evaluated the response of risk subgroups to immunotherapy and screened drugs that target specific risk subgroups for personalized medicine. Finally, the expression of ICD-related genes was validated by qRT-PCR.

Results

We identified 131 ICD-related genes at both the single-cell and bulk transcriptome levels, of which 39 were associated with overall survival (OS). A consensus ICDRS was constructed based on a 101-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. ICDRS can also be used to predict the occurrence, development, and metastasis of ccRCC. Multivariate analysis verified it as an independent prognostic factor for OS, progression-free survival (PFS), and disease-specific survival (DSS) of ccRCC. The ICDRS-integrated nomogram provided a quantitative tool in clinical practice. Moreover, we observed distinct biological functions, mutation landscapes, and immune cell infiltration in the tumor microenvironment between the high- and low-risk groups. Notably, the immunophenoscore (IPS) score showed a significant difference between risk subgroups, suggesting a better response to immunotherapy in the high-risk group. Potential drugs targeting specific risk subgroups were also identified.

Conclusion

Our study constructed an immunogenic cell death-related signature that can serve as a promising tool for prognosis prediction, targeted prevention, and personalized medicine in ccRCC. Incorporating ICD into the PPPM framework will provide a unique opportunity for clinical intelligence and new management approaches.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00327-3.

Oncogenic roles and related mechanisms of the long non-coding RNA MINCR in human cancers

Long non-coding RNAs (lncRNAs) play vital roles in regulating epigenetic mechanisms and gene expression levels, and their dysregulation is closely associated with a variety of diseases such as cancer. Several studies have demonstrated that lncRNAs are dysregulated during tumor progression. Recently, the MYC-induced long non-coding RNA MINCR, a newly identified lncRNA, has been demonstrated to act as an oncogene in different cancers, including gallbladder cancer, hepatocellular cancer, colorectal cancer, non-small cell lung cancer, oral squamous cell carcinoma, nasopharyngeal cancer, and glioma. Moreover, MINCR has been reported to act as a biomarker in the prognosis of patients with different cancers. In this review, we summarize and analyze the oncogenic roles of MINCR in a variety of human cancers in terms of its clinical significance, biological functions, cellular activities, and regulatory mechanism. Our analysis of the literature suggests that MINCR has potential as a novel biomarker and therapeutic target in human cancers.

A bibliometric analysis of ferroptosis, necroptosis, pyroptosis, and cuproptosis in cancer from 2012 to 2022

This study aims to visualize research hotspots and trends of "ferroptosis in cancer", "necroptosis in cancer", "pyroptosis in cancer", and "cuproptosis in cancer" through a bibliometric analysis to facilitate understanding of future developments in basic and clinical research and to provide a new perspective on cancer treatment. From January 1, 2012 to October 31, 2022, in the field of "ferroptosis in cancer", a total of 2467 organizations from 79 different countries published 3302 articles. 2274 organizations from 72 different countries published 2233 articles in the field of " necroptosis in cancer". 1366 institutions from 58 different countries contributed 1445 publications in the field of "pyroptosis in cancer". In the field of " cuproptosis in cancer", the number of articles published in the last 10 years is relatively low, with a total of 109 articles published by 116 institutions from four different countries. In the field of "ferroptosis in cancer", Tang Daolin had published 66 documents, ranked the first, while Dixon SJ is the most cited author, cited 3148 times; In the fields of "necroptosis in cancer", Vandenabeele peter had published 35 papers and Degterev had been cited 995 times, ranked the first, respectively; Kanneganti thirumala-devi had published 24 papers, is the highest number of publications in the fields of "pyroptosis in cancer", while Shi JJ was the most cited author with being cited 508 times. Both Huang Yan and Wang Tao published three papers and tied for first place and Tsvetkov p ranks first with being cited 107 times in "cuproptosis in cancer". "Cell", "Cell", "Nature", and "Science" was the most frequently co-cited journal on "ferroptosis in cancer", "necroptosis in cancer", "pyroptosis in cancer", and "cuproptosis in cancer", respectively. Further exploration of inhibitors of different Programmed cell death (PCD) and their targeted therapies are potential treatment options for cancer, but more direct clinical evidence as well as higher level clinical trials remain to be explored. Further clarification of the mechanisms of crosstalk between these PCDs may provide effective cancer treatments. And the role of different types of PCDs, especially the novel ones discovered, in cancer can be expected to remain a hot topic of research in the cancer field for quite some time to come.

A novel oxidative-stress related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a primary malignant tumour of tubular epithelial origin and is most common in the urinary tract. Growing evidence suggests that oxidative stress (OS), generates high levels of reactive oxygen species (ROS) and free radicals, and plays a critical role in cancer in humans. However, the predictive value of OS-related long non-coding RNAs (lncRNAs) in ccRCC remains unclear. We constructed a predictive signature of survival based on OS-related lncRNAs that were obtained from The Cancer Genome Atlas (TCGA-KIRC), to predict the prognosis of patients with ccRCC. The signature comprised seven lncRNAs: SPART-AS1, AL162586.1, LINC00944, LINC01550, HOXB-AS4, LINC02027, and DOCK9-DT. OS-related signature of lncRNAs had diagnostic efficiency higher than that of clinicopathological variables, with an area of 0.794 under the receiver operating characteristic curve. Additionally, the nomogram based on risk scores and clinicopathological variables (age, gender, grade, stage, M-stage, and N-stage) showed strong predictive performance. Patients with high-risk were found to be more sensitive to the therapeutic drugs ABT.888, AICAR, MS.275, sunitinib, AZD.2281, and GDC.0449. Our constructed the predictive signature can independently predict the prognosis of patients with ccRCC; however, the underlying mechanism needs further investigation.

Clinical significance and integrative analysis of the cuproptosis-associated genes in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is a kind of malignant tumor originating from the oropharynx, larynx, nasopharynx and oral cavity. The incidence of HNSC is increasing and it is the sixth malignant tumor in the world at present. "Cuprotosis" is a novel cuper-dependent cell death mode that is closely related to mitochondrial respiration. Tumorigenesis is closely related to the dysregulation of cell death. However, the relationship between cuprotosis and HNSC remains unclear. Here, we investigated the association between 10 cuprotosis-associated genes (CAGs) and HNSC using multi-omics public data. We found that CAGs had abnormal expression and significant genetic changes in HNSC, especially CDKN2A with 54% mutation rate. Expression of CAGs significantly correlates with the prognosis of HNSC patients. Moreover, the CAGs expression is correlated with the immune checkpoints expression and immune cells infiltration. These CAGs expression was associated with multiple drugs sensitivity of cancer cells, such as cisplatin and docetaxel. These findings indicate that CAGs are likely to serve an essential role in the diagnosis, prognosis, immunotherapy and drug therapy prediction of HNSC.

Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients

BACKGROUND

Renal carcinoma is a common malignant tumor of the urinary system. Advanced renal carcinoma has a low 5-year survival rate and a poor prognosis. More and more studies have confirmed that chromatin regulators (CRs) can regulate the occurrence and development of cancer. This article investigates the functional and prognostic value of CRs in renal carcinoma patients.

METHODS

mRNA expression and clinical information were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and LASSO regression analysis were used to select prognostic chromatin-regulated genes and use them to construct a risk model for predicting the prognosis of renal cancer. Differences in prognosis between high-risk and low-risk groups were compared using Kaplan-Meier analysis. In addition, we analyzed the relationship between chromatin regulators and tumor immune infiltration, and explored differences in drug sensitivity between risk groups.

RESULTS

We constructed a model consisting of 11 CRs to predict the prognosis of renal cancer patients. We not only successfully validated its feasibility, but also found that the 11 CR-based model was an independent prognostic factor. Functional analysis showed that CRs were mainly enriched in cancer development-related signalling pathways. We also found through the TIMER database that CR-based models were also associated with immune cell infiltration and immune checkpoints. At the same time, the genomics of drug sensitivity in cancer database was used to analyze the commonly used drugs of renal clear cell carcinoma patients. It was found that patients in the low-risk group were sensitive to medicines such as axitinib, pazopanib, sorafenib, and gemcitabine. In contrast, those in the high-risk group may be sensitive to sunitinib.

CONCLUSION

The chromatin regulator-related prognostic model we constructed can be used to assess the prognostic risk of patients with clear cell renal cell carcinoma. The results of this study can bring new ideas for targeted therapy of clear cell renal carcinoma, helping doctors to take corresponding measures in advance for patients with different risks.

Cuproptosis: mechanisms and links with cancers

Cuproptosis was a copper-dependent and unique kind of cell death that was separate from existing other forms of cell death. The last decade has witnessed a considerable increase in investigations of programmed cell death, and whether copper induced cell death was an independent form of cell death has long been argued until mechanism of cuproptosis has been revealed. After that, increasing number of researchers attempted to identify the relationship between cuproptosis and the process of cancer. Thus, in this review, we systematically detailed the systemic and cellular metabolic processes of copper and the copper-related tumor signaling pathways. Moreover, we not only focus on the discovery process of cuproptosis and its mechanism, but also outline the association between cuproptosis and cancers. Finally, we further highlight the possible therapeutic direction of employing copper ion ionophores with cuproptosis-inducing functions in combination with small molecule drugs for targeted therapy to treat specific cancers.

A prognostic cuproptosis-related lncRNA predictive signature for bladder cancer patients

Cuproptosis is a novel form of cell death in tumours. However, the clinical impact and mechanism of cuproptosis in bladder cancer (BC) remain unclear. This study aimed to explore the functions of long noncoding RNAs (lncRNAs) related to cuproptosis in BC and develop a prognostic predictive model. RNA sequencing and clinicopathological data were derived from The Cancer Genome Atlas and randomly divided into training and validation groups. Cuproptosis-related lncRNAs were identified by Cox regression analysis and least absolute shrinkage and selection operator, and the patients were divided into high- and low-risk groups according to the median value of the signature-based risk score. We established a signature of 17 cuproptosis-associated lncRNAs in the training set. In both sets, patients with higher signature-based risk scores had a notably higher probability of death (P ≤ 0.001) and a shorter survival duration. Cox regression analyses confirmed the risk score as an independent predictor of BC prognosis in the entire set. The area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.767, 0.734, and 0.764, respectively, confirming that the signature could determine the prognosis of BC. A signature-based nomogram was developed, and its prediction accuracy was validated using calibration curves. Several drugs, including Gemcitabine, Oxaliplatin, Mitoxantrone, Camptothecin, Cytarabine and Irinotecan may benefit low-risk BC patients more. Finally, in vitro experiments confirmed that the cuproptosis-related lncRNAs are highly expressed in bladder cancer cells after cuproptosis induced by exogenous copper ions. In conclusion, a cuproptosis-related lncRNA signature independently predicted prognosis in BC, indicating a possible mechanism and clinical treatment approach.

Potential of Copper and Copper Compounds for Anticancer Applications

Inducing cancer cell death has always been a research hotspot in life sciences. With the continuous deepening and diversification of related research, the potential value of metal elements in inducing cell death has been explored. Taking iron as an example, ferroptosis, mainly characterized by increasing iron load and driving the production of large amounts of lipid peroxides and eventually leading to cell death, has recently attracted great interest in the cancer research community. After iron, copper, a trace element, has received extensive attention in cell death, especially in inducing tumor cell death. Copper and its complexes can induce autophagy or apoptosis in tumor cells through a variety of different mechanisms of action (activation of stress pathways, arrest of cell cycle, inhibition of angiogenesis, cuproptosis, and paraptosis), which are promising in cancer therapy and have become new hotspots in cancer treatment research. This article reviews the main mechanisms and potential applications of novel copper and copper compound-induced cell death, focusing on copper compounds and their anticancer applications.

Cuproptosis-related LncRNAs are correlated with immunity and predict prognosis in HNSC independent of TMB

Aims: Cuproptosis is a novel cell death pathway, and the regulatory mechanism in head and neck squamous cell carcinoma (HNSC) remains to be explored. We determined whether cuproptosis-related lncRNAs (CRLs) could predict prognosis in HNSC. Methods and Results: First, we identified 10 prognostic CRLs by Pearson correlation and univariate Cox regression analyses. Next, we constructed the CRLs prognostic model based on 5 CRLs screened by the least absolute shrinkage and selection operator (LASSO) Cox analysis. Following this, we calculated the risk score for HNSC patients and divided patients into high- and low-risk groups. In our prognostic model, HNSC patients with higher risk scores had poorer outcomes. Based on several prognostic features, a predictive nomogram was established. Furthermore, we investigated principal component analysis to distinguish two groups, and functional enrichment analysis of 176 differentially expressed genes (DEGs) between risk groups was performed. Finally, we analyzed relationships between tumor mutation burden (TMB) and risk scores. Conclusion: Cuproptosis-related lncRNAs can be applied to predict HNSC prognosis independent of TMB, which is closely correlated with tumor immunity.

Construction and comprehensive analysis of a curoptosis-related lncRNA signature for predicting prognosis and immune response in cervical cancer

Cuproptosis (copper-ion-dependent cell death) is an unprogrammed cell death, and intracellular copper accumulation, causing copper homeostasis imbalance and then leading to increased intracellular toxicity, which can affect the rate of cancer cell growth and proliferation. This study aimed to create a newly cuproptosis-related lncRNA signature that can be used to predict survival and immunotherapy in patients with cervical cancer, but also to predict prognosis in patients treated with radiotherapy and may play a role in predicting radiosensitivity. First of all, we found lncRNAs associated with cuproptosis between cervical cancer tumor tissues and normal tissues. By LASSO-Cox analysis, overlapping lncRNAs were then used to construct lncRNA signatures associated with cuproptosis, which can be used to predict the prognosis of patients, especially the prognosis of radiotherapy patients, ROC curves and PCA analysis based on cuprotosis-related lncRNA signature and clinical signatures were developed and demonstrated to have good predictive potential. In addition, differences in immune cell subset infiltration and differences in immune checkpoint expression between high-risk and low-risk score groups were analyzed, and we investigated the relationship between this signature and tumor mutation burden. In summary, we constructed a lncRNA prediction signature associated with cuproptosis. This has important clinical implications, including improving the predictive value of cervical cancer patients and providing a biomarker for cervical cancer.

Molecular Targets of Shenqi Dihuang, A Traditional Chinese Herbal Medicine, and Its Potential Role in Renal Cell Carcinoma Therapy

Chinese herbal medicine (CHM), which includes herbal slices and proprietary products, is widely used in China. Shenqi Dihuang (SQDH) is a traditional Chinese medicine (TCM) formula with ingredients that affect tumor growth. Despite recent advances in prognosis, patients with renal cell carcinoma (RCC) cannot currently receive curative treatment. The present study aimed to explore the potential target genes closely associated with SQDH. The gene expression data for SQDH and RCC were obtained from the TCMSP and TCGA databases. The SQDH-based prognostic prediction model reveals a strong correlation between RCC and SQDH. In addition, the immune cell infiltration analysis indicated that SQDH might be associated with the immune response of RCC patients. Based on this, we successfully built the prognostic prediction model using SQDH-related genes. The results demonstrated that CCND1 and NR3C2 are closely associated with the prognosis of RCC patients. Finally, the pathways enrichment analysis revealed that response to oxidative stress, cyclin binding, programmed cell death, and immune response are the most enriched pathways in CCND1. Furthermore, transcription regulator activity, regulation of cell population proliferation, and cyclin binding are closely associated with the NR3C2.

Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease. Therefore, more reliable biomarkers are required to better predict the prognosis of DLBCL. Cuproptosis is a novel identified form of programmed cell death (PCD) that is different from oxidative stress-related cell death (e.g., apoptosis, ferroptosis, and necroptosis) by Tsvetkov and colleagues in a recent study released in Science. Cuproptosis is copper-dependent PCD that is closely tied to mitochondrial metabolism. However, the prognostic value of cuproptosis-related genes (CRGs) in DLBCL remains to be further elucidated. In the present study, we systematically evaluated the molecular changes of CRGs in DLBCL and found them to be associated with prognosis. Subsequently, based on the expression profiles of CRGs, we characterized the heterogeneity of DLBCL by identifying two distinct subtypes using consensus clustering. Two isoforms exhibited different survival, biological functions, chemotherapeutic drug sensitivity, and immune microenvironment. After identifying differentially expressed genes (DEGs) between CRG clusters, we built a prognostic model with the Least absolute shrinkage and selection operator (LASSO) Cox regression analysis and validated its prognostic value by Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. In addition, the risk score can predict clinical characteristics, levels of immune cell infiltration, and prognosis. Furthermore, a nomogram incorporating clinical features and risk score was generated to optimize risk stratification and quantify risk assessment. Compared to the International Prognostic Index (IPI), the nomogram has demonstrated more accuracy in survival prediction. Furthermore, we validated the prognostic gene expression levels through external experiments. In conclusion, cuproptosis-related gene signature can serve as a potential prognostic predictor in DLBCL patients and may provide new insights into cancer therapeutic targets.

A novel cuproptosis-related prognostic gene signature and validation of differential expression in hepatocellular carcinoma

Background: Cuproptosis is a newly discovered form of programmed cell death, which is characterized by accumulation of intra-cellular copper ion leading to the aggregation of lipoproteins and destabilization of Fe-S cluster proteins in mitochondrial metabolism, thereby affecting the prognosis of patients with cancer. However, the role of cuproptosis-related genes (CRGs) in hepatocellular carcinoma (HCC) remains elusive. Methods: Mutation signature, copy number variation and the expression of 10 CRGs were assessed in HCC from TCGA-LIHC dataset. ICGC-LIRI-JP dataset was used as further validation cohort. The least absolute shrinkage and selection operator (LASSO) was used to construct the prognostic model. Kaplan Meier curves, time-ROC curves, nomogram, univariate and multivariate Cox regression were utilized to evaluate the predictive efficacy of CRGs-score. Immune infiltration was analyzed by CIBERSOFT, ssGSEA algorithm, and TIMER database. The expression of prognostic CRGs was validated by qPCR both in-vitro and in-vivo. Drug sensitivity analysis was performed by pRRophetic. Results: All of the CRGs were differentially expressed in HCC and 5 out of them (CDKN2A, DLAT, GLS, LIPT1, MTF1) correlated with patient survival. These signature genes were selected by LASSO analysis to establish a prognosis model to stratify HCC patients into high and low CRGs-score subgroups. High CRGs-score was associated with a worse prognosis. Subsequently, univariate and multivariate Cox regression verified that CRGs-score was an independent cancer risk factor that correlated with clinical factors including stage and grade. Nomogram integrating the CRGs-score and clinical risk factors performed well to predict patient survival. Immune infiltration analysis further revealed that the expression of immune checkpoint genes was significantly enhanced in high CRGs-score group, especially PD-1 and PD-L1. An independent validation cohort (ICGC) confirmed that CRGs-score as a stable and universally applicable indicator in predicting HCC patient survival. Concordantly, the expression of five confirmed signature genes were also differentially expressed in human HCC cell lines and mouse HCC model. In addition, we also analyzed the sensitivity of 10 clinical targeted therapies between high and low CRGs-score groups. Conclusion: This study elucidated the role of dysregulated CRGs in HCC cohort, with validation with in-vitro and in-vivo models. The CRGs-score might be applied as a novel prognostic factor in HCC.

A novel cuproptosis-related prognostic 2-lncRNAs signature in breast cancer

Background: Cuproptosis, a newly defined regulated form of cell death, is mediated by the accumulation of copper ions in cells and related to protein lipoacylation. Seven genes have been reported as key genes of cuproptosis phenotype. Cuproptosis may be developed by subsequent research as a target to treat cancer, such as breast cancer. Long-noncoding RNA (lncRNA) has been proved to play a vital role in regulating the biological process of breast cancer. However, the role of lncRNAs in cuproptosis is poorly studied. Methods: Based on TCGA (The Cancer Genome Atlas) database and integrated several R packages, we screened out 153 cuproptosis-related lncRNAs and constructed a novel cuproptosis-related prognostic 2-lncRNAs signature (BCCuS) in breast cancer and then verified. By using pRRophetic package and machine learning, 72 anticancer drugs, significantly related to the model, were screened out. qPCR was used to detect the differentially expression of two model lncRNAs and seven cuproptosis genes between 10 pairs of breast cancer tissue samples and adjacent samples. Results: We constructed a novel cuproptosis-related prognostic 2-lncRNAs (USP2-AS1, NIFK-AS1) signature (BCCuS) in breast cancer. Univariate COX analysis (p < .001) and multivariate COX analysis (p < .001) validated that BCCuS was an independent prognostic factor for breast cancer. Overall survival Kaplan Meier-plotter, ROC curve and Risk Plot validated the prognostic value of BCCuS both in test set and verification set. Nomogram and C-index proved that BCCuS has strong correlation with clinical decision-making. BCCuS still maintain inspection efficiency when patients were splitting into Stage I-II (p = .024) and Stage III-IV (p = .003) breast cancer. BCCuS-high group and BCCuS-low group showed significant differences in gene mutation frequency, immune function, TIDE (tumor immune dysfunction and exclusion) score and other phenotypes. TMB (tumor mutation burden)-high along with BCCuS-high group had the lowest Survival probability (p = .005). 36 anticancer drugs whose sensitivity (IC50) was significantly related to the model were screened out using pRRophetic package. qPCR results showed that two model lncRNAs (USP2-AS1, NIFK-AS1) and three Cuproptosis genes (FDX1, PDHA1, DLAT) expressed differently between 10 pairs of breast cancer tissue samples and adjacent samples. Conclusion: The current study reveals that cuproptosis-related prognostic 2-lncRNAs signature (BCCuS) may be useful in predicting the prognosis, biological characteristics, and appropriate treatment of breast cancer patients.

A cuproptosis-related LncRNA signature: Integrated analysis associated with biochemical recurrence and immune landscape in prostate cancer

Background: As a new form of regulated cell death, cuproptosis differs profoundly from apoptosis, ferroptosis, pyroptosis, and necroptosis. The correlation between cuproptosis and long non-coding RNAs (lncRNAs) has been increasingly studied recently. In this study, a novel cuproptosis-related lncRNA prognostic signature was developed to investigate biochemical recurrence (BCR) and tumor immune landscape in prostate cancer (PCa). Methods and Materials: The transcriptome data and clinicopathologic information of PCa patients were downloaded from The Cancer Genome Atlas (TCGA). Pearson's correlation analysis was applied to identify lncRNAs associated with cuproptosis. Based on Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a cuproptosis-related lncRNA prognostic model (risk score) to predict the BCR of PCa patients. Additionally, we also constructed a nomogram with the risk score and clinicopathologic features. The biological function, tumor mutation burden (TMB), immune cell infiltration, expression levels of immune checkpoint genes, and anti-cancer drug sensitivity were investigated. Results: We constructed and validated the cuproptosis-related lncRNA signature prognostic model (risk score) by six crlncRNAs. All patients were divided into the low- and high-risk groups based on the median risk score. The Kaplan-Meier (KM) survival analysis revealed that the high-risk group had shorter BCR-free survival (BCRFS). The risk score has been proven to be an independent prognostic factor of BCR in PCa patients. In addition, a nomogram of risk scores and clinicopathologic features was established and demonstrated an excellent predictive capability of BCR. The ROC curves further validated that this nomogram had higher accuracy of predicting the BCR compared to other clinicopathologic features. We also found that the high-risk group had higher TMB levels and more infiltrated immune cells. Furthermore, patients with high TMB in the high-risk group were inclined to have the shortest BCRFS. Finally, patients in the high-risk group were more susceptible to docetaxel, gefitinib, methotrexate, paclitaxel, and vinblastine. Conclusion: The novel crlncRNA signature prognostic model shows a greatly prognostic prediction value of BCR for PCa patients, extends our thought on the association of cuproptosis and PCa, and provides novel insights into individual-based treatment strategies for PCa.

Construction and Validation of Protein Expression-related Prognostic Models in Clear Cell Renal Cell Carcinoma

Objective: To construct a prognostic evaluation model for clear cell renal cell carcinoma (ccRCC) patients using bioinformatics method and to screen potential drugs for ccRCC. Methods: ccRCC RNA sequencing data, clinical data, and protein expression data were downloaded from the TCGA database. Univariate Cox and Lasso regression analyses were performed on the combined data to screen out the proteins related to the prognosis, and they were included in a multivariate Cox proportional hazard model. The patients were divided into high and low-risk groups for a survival difference analysis. The predictive power of the model was evaluated on the basis of overall survival, progression-free survival, independent prognostic, clinically relevant receiver operating characteristic (ROC) curve, C-index, principal component, and clinical data statistics analyses. GSEA enrichment and immune function correlation analyses were performed. The samples were divided into different subtypes based on the expression of the risk proteins, and survival analysis of the subtypes was performed. The risk-related protein and RNA sequencing data were analyzed to screen out sensitive drugs with significant differences between the high and low-risk groups. Results: A total of 469 ccRCC-related proteins were screened, of which 13 proteins with independent prognostic significance were screened by univariate Cox, Lasso, and multivariate Cox regression analyses to construct the prognostic model. The sensitivity and accuracy of the model in predicting the survival of patients with ccRCC were high (1 year: 0.811, 3 years: 0.783, 5 years: 0.777). The 13 proteins were closely related to immunity, and the model proteins were different between kidney and tumor tissues according to the HPA database. The samples were divided into three subtypes, and there were obvious clinical characteristics of the three subtypes in the grade and T, N and M stages. According to the IC50 values, CGP-60474, vinorelbine, doxorubicin, etoposide, FTI-277, JQ12, OSU-03012, pyrimethamine, and other drugs were more sensitive in the high-risk group. Conclusions: A prognostic model of protein expression in ccRCC was successfully constructed, which had good predictive ability for the prognosis of ccRCC patients. The ccRCC-related proteins in the model can be used as targets for studying the pathogenesis and targeted therapy.