Comprehensive analysis of cuproptosis-related genes and tumor microenvironment infiltration characterization in breast cancer

GLS as a Key Cuproptosis-Related Gene in Periodontitis: Insights from Single-Cell RNA Sequencing

OBJECTIVE

The objective of this study is to investigate the role of cuproptosis-related genes (CRGs) in periodontitis using an integrative approach that combines single-cell RNA sequencing (scRNA-seq) and bioinformatic analyses. The study aims to elucidate the connection between copper-induced cell death (cuproptosis) and periodontitis, a prevalent chronic inflammatory oral disease that leads to tooth-supporting tissue damage and eventual tooth loss.

METHODS

Differentially expressed genes (DEGs) were identified from the GSE10334 dataset, leading to the discovery of 14 differentially expressed CRGs associated with periodontitis. Subsequent application of least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis pinpointed three key CRGs: MTF1, GLS, and DLST. Single-cell sequencing data analysis was further conducted to explore the expression patterns of these genes, particularly GLS, within immune cells and their association with the immune cell network in periodontal tissues.

RESULTS

The study revealed that GLS is widely expressed in immune cells and is closely linked to the complex immune cell interactions within periodontal tissues. This finding underscores GLS as a potential therapeutic target in the context of periodontitis, associated with cuproptosis. The integration of single-cell sequencing data highlighted the significant role of cuproptosis in the diversity and complexity of periodontitis pathogenesis.

CONCLUSION

This research advances the understanding of the crosstalk between periodontitis and cuproptosis, emphasising the role of CRGs, especially GLS, in periodontitis. Furthermore, this study on cuproptosis may contribute to future diagnostic and therapeutic strategies for periodontitis.

Integrated bulk and single-cell transcriptomic analysis unveiled a novel cuproptosis-related lipid metabolism gene molecular pattern and a risk index for predicting prognosis and antitumor drug sensitivity in breast cancer

Breast cancer is the second most prevalent malignant tumor worldwide and is highly heterogeneous. Cuproptosis, a newly identified form of cell death, is intimately connected to lipid metabolism. This study investigated breast cancer heterogeneity through the lens of cuproptosis-related lipid metabolism genes (CLMGs), with the goal of predicting patient prognosis, immunotherapy efficacy, and sensitivity to anticancer drugs. By utilizing transcriptomic data from The Cancer Genome Atlas (TCGA) for breast cancer, we identified 682 CLMGs and applied the nonnegative matrix factorization (NMF) method to categorize breast cancer patients into four distinct clusters: cluster 1, ''immune-cold and stroma-poor''; cluster 2, ''immune-infiltrated''; cluster 3, ''stroma-rich''; and cluster 4, ''moderate infiltration''. We subsequently developed a risk model based on CLMGs that incorporates ACSL1, ATP2B4, ATP7B, ENPP6, HSPH1, PIP4K2C, SRD5A3, and ULBP1. This model demonstrated excellent prognostic predictive performance in both the internal (testing and entire sets) and external (GSE20685 and Kaplan-Meier Plotter sets) validation sets. High-risk patients presented lower expression levels of immune checkpoint-related genes and lower immunophenoscores (IPSs), whereas low-risk patients presented higher CD8+ T-cell infiltration levels and IPSs. Furthermore, the risk index was positively correlated with tumor cell stemness and could predict sensitivity to anticancer drugs. We also confirmed that SRD5A3 was highly expressed in breast cancer and participated in promoting the proliferation and migration of breast cancer cells. In conclusion, the results of this study provide new insights and strategies for assessing prognosis and implementing precision treatment for breast cancer through the lens of CLMGs.

Targeting the initiator to activate both ferroptosis and cuproptosis for breast cancer treatment: progress and possibility for clinical application

Breast cancer is the most commonly diagnosed cancer worldwide. Metal metabolism is pivotal for regulating cell fate and drug sensitivity in breast cancer. Iron and copper are essential metal ions critical for maintaining cellular function. The accumulation of iron and copper ions triggers distinct cell death pathways, known as ferroptosis and cuproptosis, respectively. Ferroptosis is characterized by iron-dependent lipid peroxidation, while cuproptosis involves copper-induced oxidative stress. They are increasingly recognized as promising targets for the development of anticancer drugs. Recently, compelling evidence demonstrated that the interplay between ferroptosis and cuproptosis plays a crucial role in regulating breast cancer progression. This review elucidates the converging pathways of ferroptosis and cuproptosis in breast cancer. Moreover, we examined the value of genes associated with ferroptosis and cuproptosis in the clinical diagnosis and treatment of breast cancer, mainly outlining the potential for a co-targeting approach. Lastly, we delve into the current challenges and limitations of this strategy. In general, this review offers an overview of the interaction between ferroptosis and cuproptosis in breast cancer, offering valuable perspectives for further research and clinical treatment.

Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer

Background

Programmed cell death (PCD) is closely related to the occurrence, development, and treatment of breast cancer. The aim of this study was to investigate the association between various programmed cell death patterns and the prognosis of breast cancer (BRCA) patients.

Methods

The levels of 19 different programmed cell deaths in breast cancer were assessed by ssGSEA analysis, and these PCD scores were summed to obtain the PCDS for each sample. The relationship of PCDS with immune as well as metabolism-related pathways was explored. PCD-associated subtypes were obtained by unsupervised consensus clustering analysis, and differentially expressed genes between subtypes were analyzed. The prognostic signature (PCDRS) were constructed by the best combination of 101 machine learning algorithm combinations, and the C-index of PCDRS was compared with 30 published signatures. In addition, we analyzed PCDRS in relation to immune as well as therapeutic responses. The distribution of genes in different cells was explored by single-cell analysis and spatial transcriptome analysis. Potential drugs targeting key genes were analyzed by Cmap. Finally, the expression levels of key genes in clinical tissues were verified by RT-PCR.

Results

PCDS showed higher levels in cancer compared to normal. Different PCDS groups showed significant differences in immune and metabolism-related pathways. PCDRS, consisting of seven key genes, showed robust predictive ability over other signatures in different datasets. The high PCDRS group had a poorer prognosis and was strongly associated with a cancer-promoting tumor microenvironment. The low PCDRS group exhibited higher levels of anti-cancer immunity and responded better to immune checkpoint inhibitors as well as chemotherapy-related drugs. Clofibrate and imatinib could serve as potential small-molecule complexes targeting SLC7A5 and BCL2A1, respectively. The mRNA expression levels of seven genes were upregulated in clinical cancer tissues.

Conclusion

PCDRS can be used as a biomarker to assess the prognosis and treatment response of BRCA patients, which offers novel insights for prognostic monitoring and treatment personalization of BRCA patients.

Copper homeostasis and Cuprotosis: Exploring novel therapeutic strategies for connective tissue diseases

Copper is an indispensable element for human health, with its balance being critical to prevent the onset of diseases, particularly those affecting connective tissues. Imbalances in copper levels can lead to pathological alterations. Research indicates that copper supplements and chelators hold promise for the treatment of certain conditions, yet the precise mechanisms by which copper imbalances and the cell death mechanism known as cuprotosis contribute to connective tissue diseases remain elusive. This paper delves into the potential role of copper imbalance and cuprotosis in connective tissue diseases and evaluates the underlying cellular mechanisms. The goal is to offer practical insights into targeted therapies for dysregulated copper metabolism, with the aim of devising novel strategies for the treatment of connective tissue diseases.

Construction of a prognostic model based on cuproptosis-related genes and exploration of the value of DLAT and DLST in the metastasis for non-small cell lung cancer

BACKGROUND

To reveal the clinical value of cuproptosis-related genes on prognosis and metastasis in non-small cell lung cancer.

METHODS

Gene expression profiles and clinical information of non-small cell lung cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The data were grouped into training set, internal testing set, and external testing set. A risk prognostic model was constructed by Lasso-Cox regression analysis. Hub genes were identified and evaluated using immunohistochemistry and the transwell migration assay in 50 clinical patients.

RESULTS

A total of 17/19 cuproptosis-related genes were differentially expressed in tumors, 8 were significantly associated with prognosis, and 4 were markedly associated with metastasis. A risk model based on 2 cuproptosis-related genes was constructed and validated for predicting overall survival. The risk score was proven to be an independent risk factor for the prognosis of non-small cell lung cancer. Dihydrolipoamide S-acetyltransferase and dihydrolipoamide S-succinyltransferase, key genes in cuproptosis, were proven to be associated with non-small cell lung cancer prognosis and metastasis. Immunohistochemistry showed that their expression significantly predicted metastasis but failed to predict prognosis in non-small cell lung cancer patients. The transwell migration assay further increased the cellular reliability of our findings.

CONCLUSION

The cuproptosis-related genes prognostic model effectively predicted the prognosis of non-small cell lung cancer. Dihydrolipoamide S-acetyltransferase and dihydrolipoamide S-succinyltransferase may serve as predictive markers for metastasis in non-small cell lung cancer.

The role of cuproptosis in gastric cancer

As a biologically essential transition metal, copper is widely involved in various enzymatic reactions and crucial biological processes in the body. It plays an increasingly important role in maintaining normal cellular metabolism and supporting the growth and development of the human body. As a trace element, copper maintains the dynamic balance of its concentration in body fluids through active homeostatic mechanisms. Both excess and deficiency of copper ions can impair cell function, ultimately leading to cell damage and death. Cuproptosis is a novel form of cell death where copper ions cause cell death by directly binding to the lipoylated components of the citric acid cycle (CAC) in mitochondrial respiration and interfering with the levels of iron-sulfur cluster (Fe-S cluster) proteins, ultimately causing protein toxic stress. Its primary characteristics are Cu2+ concentration dependence and high expression in mitochondrial respiratory cells. Recent research has revealed that, compared to other forms of programmed cell death such as apoptosis, necrosis, and autophagy, cuproptosis has unique morphological and biochemical features. Cuproptosis is associated with the occurrence and development of various diseases, including cancer, neurodegenerative diseases, and cardiovascular diseases. This article focuses on a review of the relevance of cuproptosis in gastric cancer (GC).

A cuproptosis-related prognostic signature for guiding clinical diagnosis and treatment in uveal melanoma patients

Background

Cuproptosis, one of the most recently discovered forms of cell death, is induced by the disruption of copper binding to the mitochondrial respiratory acylation components. However, the mechanism underlying cuproptosis in uveal melanoma (UM) has not yet been adequately studied.

Methods

RNA and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed cuproptosis-related genes were identified by R software. A prognostic signature was constructed by applying LASSO regression and Cox regression models. The associations between the signature and the immune microenvironment, overall survival, and drug sensitivity were studied. In addition, qPCR and Western blotting were performed on UM cells and RPE cell lines to verify the expression levels of the genes encoding dihydrolipoamide dehydrogenase (DLD) and dihydrolipoamide S-succinyltransferase (DLST) in UM cases.

Results

Using a cuproptosis-related prognostic signature, UM samples were classified into high- and low-risk groups. A significant difference in overall survival between the two risk groups was evident. Receiver operating characteristic curves demonstrated that the signature is a reliable predictor of prognosis. Immune cell infiltration, drug sensitivity, and immune checkpoint expression were analysed. Significant immune difference between the two high-risk groups was found, and the high expression of immune checkpoints in high-risk groups suggests significant immunotherapy potential. In addition, drug sensitivity analysis experiments suggest that erlotinib may be a potential treatment for high-risk patients. The results of in vitro experiments confirmed that DLD and DLST had higher expression levels in UM cell lines.

Conclusions

The prognostic signature developed in this study is a reliable biomarker for predicting the prognosis of UM and may serve as a tool for personalised treatment of patients with UM.

Metal ions overloading and cell death

Cell death maintains cell morphology and homeostasis during development by removing damaged or obsolete cells. The concentration of metal ions whithin cells is regulated by various intracellular transporters and repositories to maintain dynamic balance. External or internal stimuli might increase the concentration of metal ions, which results in ions overloading. Abnormal accumulation of large amounts of metal ions can lead to disruption of various signaling in the cell, which in turn can produce toxic effects and lead to the occurrence of different types of cell deaths. In order to further study the occurrence and development of metal ions overloading induced cell death, this paper reviewed the regulation of Ca2+, Fe3+, Cu2+ and Zn2+ metal ions, and the internal mechanism of cell death induced by overloading. Furthermore, we found that different metal ions possess a synergistic and competitive relationship in the regulation of cell death. And the enhanced level of oxidative stress was present in all the processes of cell death due to metal ions overloading, which possibly due to the combination of factors. Therefore, this review offers a theoretical foundation for the investigation of the toxic effects of metal ions, and presents innovative insights for targeted regulation and therapeutic intervention. HIGHLIGHTS: • Metal ions overloading disrupts homeostasis, which in turn affects the regulation of cell death. • Metal ions overloading can cause cell death via reactive oxygen species (ROS). • Different metal ions have synergistic and competitive relationships for regulating cell death.

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.

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.

Understanding tissue-resident macrophages unlocks the potential for novel combinatorial strategies in breast cancer

Tissue-resident macrophages (TRMs) are an integral part of the innate immune system, but their biology is not well understood in the context of cancer. Distinctive resident macrophage populations are identified in different organs in mice using fate mapping studies. They develop from the yolk sac and self-maintain themselves lifelong in specific tissular niches. Similarly, breast-resident macrophages are part of the mammary gland microenvironment. They reside in the breast adipose tissue stroma and close to the ductal epithelium and help in morphogenesis. In breast cancer, TRMs may promote disease progression and metastasis; however, precise mechanisms have not been elucidated. TRMs interact intimately with recruited macrophages, cytotoxic T cells, and other immune cells along with cancer cells, deciding further immunosuppressive or cytotoxic pathways. Moreover, triple-negative breast cancer (TNBC), which is generally associated with poor outcomes, can harbor specific TRM phenotypes. The influence of TRMs on adipose tissue stroma of the mammary gland also contributes to tumor progression. The complex crosstalk between TRMs with T cells, stroma, and breast cancer cells can establish a cascade of downstream events, understanding which can offer new insight for drug discovery and upcoming treatment choices. This review aims to acknowledge the previous research done in this regard while exploring existing research gaps and the future therapeutic potential of TRMs as a combination or single agent in breast cancer.

Ferroptosis and cuproptosis: Metal-dependent cell death pathways activated in response to classical chemotherapy - Significance for cancer treatment?

Apoptosis has traditionally been regarded as the desired cell death pathway activated by chemotherapeutic drugs due to its controlled and non-inflammatory nature. However, recent discoveries of alternative cell death pathways have paved the way for immune-stimulatory treatment approaches in cancer. Ferroptosis (dependent on iron) and cuproptosis (dependent on copper) hold promise for selective cancer cell targeting and overcoming drug resistance. Copper ionophores and iron-bearing nano-drugs show potential for clinical therapy as single agents and as adjuvant treatments. Here we review up-to-date evidence for the involvement of metal ion-dependent cell death pathways in the cytotoxicity of classical chemotherapeutic agents (alkylating agents, topoisomerase inhibitors, antimetabolites, and mitotic spindle inhibitors) and their combinations with cuproptosis and ferroptosis inducers, indicating the prospects, advantages, and obstacles of their use.

Modulation of the tumor microenvironment and mechanism of immunotherapy-based drug resistance in breast cancer

Breast cancer, the most frequent female malignancy, is often curable when detected at an early stage. The treatment of metastatic breast cancer is more challenging and may be unresponsive to conventional therapy. Immunotherapy is crucial for treating metastatic breast cancer, but its resistance is a major limitation. The tumor microenvironment (TME) is vital in modulating the immunotherapy response. Various tumor microenvironmental components, such as cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs), are involved in TME modulation to cause immunotherapy resistance. This review highlights the role of stromal cells in modulating the breast tumor microenvironment, including the involvement of CAF-TAM interaction, alteration of tumor metabolism leading to immunotherapy failure, and other latest strategies, including high throughput genomic screening, single-cell and spatial omics techniques for identifying tumor immune genes regulating immunotherapy response. This review emphasizes the therapeutic approach to overcome breast cancer immune resistance through CAF reprogramming, modulation of TAM polarization, tumor metabolism, and genomic alterations.

Micronutrient Status and Breast Cancer: A Narrative Review

Breast cancer is one of the most common cancers worldwide, at the same time being one of the most prevalent causes of women's death. Many factors such as alcohol, weight fluctuations, or hormonal replacement therapy can potentially contribute to breast cancer development and progression. Another important factor in breast cancer onset includes micronutrient status. In this narrative review, we analyzed 23 micronutrients and their possible influence on breast cancer onset and progression. Further, the aim of this study was to investigate the impact of micronutrient status on the prevention of breast cancer and its possible influence on various therapeutic pathways. We researched meta-analyses, systemic and narrative reviews, retrospective studies, as well as original studies on human and animal models. The results of these studies indicate a possible correlation between the different levels of micronutrients and a decreased risk of breast cancer as well as a better survival rate. However, further studies are necessary to establish adequate doses of supplementation of the chosen micronutrients and the exact mechanisms of micronutrient impact on breast cancer therapy.

Revolutionizing breast cancer treatment: Harnessing the related mechanisms and drugs for regulated cell death (Review)

Breast cancer arises from the malignant transformation of mammary epithelial cells under the influence of various carcinogenic factors, leading to a gradual increase in its prevalence. This disease has become the leading cause of mortality among female malignancies, posing a significant threat to the health of women. The timely identification of breast cancer remains challenging, often resulting in diagnosis at the advanced stages of the disease. Conventional therapeutic approaches, such as surgical excision, chemotherapy and radiotherapy, exhibit limited efficacy in controlling the progression and metastasis of the disease. Regulated cell death (RCD), a process essential for physiological tissue cell renewal, occurs within the body independently of external influences. In the context of cancer, research on RCD primarily focuses on cuproptosis, ferroptosis and pyroptosis. Mounting evidence suggests a marked association between these specific forms of RCD, and the onset and progression of breast cancer. For example, a cuproptosis vector can effectively bind copper ions to induce cuproptosis in breast cancer cells, thereby hindering their proliferation. Additionally, the expression of ferroptosis‑related genes can enhance the sensitivity of breast cancer cells to chemotherapy. Likewise, pyroptosis‑related proteins not only participate in pyroptosis, but also regulate the tumor microenvironment, ultimately leading to the death of breast cancer cells. The present review discusses the unique regulatory mechanisms of cuproptosis, ferroptosis and pyroptosis in breast cancer, and the mechanisms through which they are affected by conventional cancer drugs. Furthermore, it provides a comprehensive overview of the significance of these forms of RCD in modulating the efficacy of chemotherapy and highlights their shared characteristics. This knowledge may provide novel avenues for both clinical interventions and fundamental research in the context of breast cancer.

Serum Levels of Copper and Zinc and Survival in Breast Cancer Patients

There is emerging interest in the relationship between several serum micronutrients and the prognosis of patients with breast cancer. The relationship between serum zinc and copper levels and breast cancer prognosis is unclear. In our study, we included 583 patients with breast cancer diagnosed between 2008 and 2015 in the region of Szczecin, Poland. In a blood sample obtained before treatment, serum zinc and copper levels were quantified by mass spectroscopy. Each patient was assigned to one of four categories (quartiles) based on the distribution of the elements in the entire cohort. Patients were followed from diagnosis to death over a mean of 10.0 years. The 10-year overall survival was 58.3% for women in the highest and 82.1% for those in the lowest quartile of serum copper/zinc ratio (p < 0.001). The multivariate hazard ratio (HR) for breast cancer death was 2.07 (95% CI 1.17-3.63; p = 0.01) for patients in the highest quartile of serum copper/zinc ratio compared to those in the lowest. There is evidence that the serum zinc level and copper/zinc ratio provide an independent predictive value for overall survival and breast cancer-specific survival after breast cancer diagnosis.

HIF-2α-dependent TGFBI promotes ovarian cancer chemoresistance by activating PI3K/Akt pathway to inhibit apoptosis and facilitate DNA repair process

Hypoxia-mediated chemoresistance plays a crucial role in the development of ovarian cancer (OC). However, the roles of hypoxia-related genes (HRGs) in chemoresistance and prognosis prediction and theirs underlying mechanisms remain to be further elucidated. We intended to identify and validate classifiers of hub HRGs for chemoresistance, diagnosis, prognosis as well as immune microenvironment of OC, and to explore the function of the most crucial HRG in the development of the malignant phenotypes. The RNA expression and clinical data of HRGs were systematically evaluated in OC training group. Univariate and multivariate Cox regression analysis were applied to construct hub HRGs classifiers for prognosis and diagnosis assessment. The relationship between classifiers and chemotherapy response and underlying pathways were detected by GSEA, CellMiner and CIBERSORT algorithm, respectively. OC cells were cultured under hypoxia or transfected with HIF-1α or HIF-2α plasmids, and the transcription levels of TGFBI were assessed by quantitative PCR. TGFBI was knocked down by siRNAs in OC cells, CCK8 and in vitro migration and invasion assays were performed to examine the changes in cell proliferation, motility and metastasis. The difference in TGFBI expression was examined between cisplatin-sensitive and -resistant cells, and the effects of TGFBI interference on cell apoptosis, DNA repair and key signaling molecules of cisplatin-resistant OC cells were explored. A total of 179 candidate HRGs were extracted and enrolled into univariate and multivariate Cox regression analysis. Six hub genes (TGFBI, CDKN1B, AKAP12, GPC1, TGM2 and ANGPTL4) were selected to create a HRGs prognosis classifier and four genes (TGFBI, AKAP12, GPC1 and TGM2) were selected to construct diagnosis classifiers. The HRGs prognosis classifier could precisely distinguish OC patients into high-risk and low-risk groups and estimate their clinical outcomes. Furthermore, the high-risk group had higher percentage of Macrophages M2 and exhibited higher expression of immunecheckpoints such as PD-L2. Additionally, the diagnosis classifiers could accurately distinguish OC from normal samples. TGFBI was further verified as a specific key target and demonstrated that its high expression was closely correlated with poor prognosis and chemoresistance of OC. Hypoxia upregulated the expression level of TGFBI. The hypoxia-induced factor HIF-2α but not HIF-1α could directly bind to the promoter region of TGFBI, and facilitate its transcription level. TGFBI was upregulated in cisplatin-sensitive and resistant ovarian cancer cells in a cisplatin time-dependent manner. TGFBI interference downregulated DNA repair-related markers (p-p95/NBS1, RAD51, p-DNA-PKcs, DNA Ligase IV and Artemis), apoptosis-related marker (BCL2) and PI3K/Akt pathway-related markers (PI3K-p110 and p-Akt) in cisplatin-resistant OC cells. In summary, the HRGs prognosis risk classifier could be served as a predictor for OC prognosis and efficacy evaluation. TGFBI, upregulated by HIF-2α as an HRG, promoted OC chemoresistance through activating PI3K/Akt pathway to reduce apoptosis and enhance DNA damage repair pathway.

Lactylation-related gene signature for prognostic prediction and immune infiltration analysis in breast cancer

Background

Lactylation is implicated in various aspects of tumor biology, but its relation to breast cancer remains poorly understood. This study aimed to explore the roles of the lactylation-related genes in breast cancer and its association with the tumor microenvironment.

Methods

The expression and mutation patterns of lactylation-related genes were analyzed using the breast cancer data from The Cancer Genome Atlas (TCGA) database and GSE20685 datasets. Unsupervised clustering was used to identify two lactylation clusters. A lactylation-related gene signature was developed and validated using the training and validation cohorts. Immune cell infiltration and drug response were assessed.

Results

We analyzed the mRNA expression, copy number variations, somatic mutations, and correlation networks of 22 lactylation-related genes in breast cancer tissues. We identified two distinct lactylation clusters with different survival outcomes and immune microenvironments. We further classified the patients into two gene subtypes based on lactylation clusters and identified a 7-gene signature for breast cancer survival prognosis. The prognostic score based on this signature demonstrated prognostic value and predicted the therapeutic response.

Conclusion

Lactylation-related genes play a critical role in breast cancer by influencing tumor growth, immune microenvironment, and drug response. This lactylation-related gene signature may serve as a prognostic marker and a potential therapeutic target for breast cancer.

Homologous recombination deficiency reflects the heterogeneity and monitoring treatment response for patients with breast cancer

BACKGROUND

In breast cancer (BC), homologous recombination defect (HRD) is a common carcinogenic mechanism. It is meaningful to classify BC according to HRD biomarkers and to develop a platform for identifying BC molecular features, pathological features and therapeutic responses.

METHODS

In total, 109 HRD genes were collected and screened by univariate Cox regression analysis to determine the prognostic genes, which were used to construct a consensus matrix to identify BC subtype. Differentially expressed genes (DEGs) were filtered by the Limma package and screened by random forest analysis to build a model to analyze the immunotherapy response and sensitivity and prognosis of patients suffering from BC to different drugs.

RESULTS

Thirteen out of 109 HRD genes were prognostic genes of BC, and BC was classified into two subgroups based on their expression. Cluster 1 had a significantly backward survival outcome and a significantly higher adaptive immunity score relative to cluster 2. Six genes were identified by random forest analysis as factors for developing the model. The model provided a prediction called risk score, which showed a significant stratification effect on BC prognosis, immunotherapy response and IC50 values of 62 drugs.

CONCLUSIONS

In the present study, two HRD subtypes of BC were successfully identified, for which mutation and immunological features were determined. A model based on differential genes of HRD subtypes was established, which was a potential predictor of prognosis, immunotherapy response and drug sensitivity of BC.

Cuproptosis related gene PDHB is identified as a biomarker inversely associated with the progression of clear cell renal cell carcinoma

BACKGROUND

Cuproptosis is a newly discovered programmed cell death dependent on mitochondrial respiratory disorder induced by copper overload. Pyruvate dehydrogenase E1 subunit beta (PDHB) is one of the cuproptosis genesand is a nuclear-encoded pyruvate dehydrogenase, which catalyzes the conversion of pyruvate to acetyl coenzyme A. However, the mechanism of PDHB in clear cell renal cell carcinoma (ccRCC) remains unclear.

METHODS

We used data from TCGA and GEO to assess the expression of PDHB in normal and tumor tissues. We further analyzed the relationship between PDHB and somatic mutations and immune infiltration. Finally, we preliminarily explored the impact of PDHB on ccRCC.

RESULTS

The expression level of PDHB was lower in tumor tissue compared with normal tissue. Meanwhile, the expression level of PDHB was also lower in high-grade tumors than low-grade tumors. PDHB is positively correlated with prognosis in ccRCC. Furthermore, PDHB may be associated with decreased risk of VHL, PBRM1 and KDM5C mutations. In 786-O cells, copper chloride could promote the expression of cuproptosis genes (DLAT, PDHB and FDX1) and inhibit cell growth. Last but not least, we found that PDHB could inhibit the proliferation and migration of ccRCC cells.

CONCLUSION

Our results demonstrated that PDHB could inhibit the proliferation, migration and invasion in ccRCC cells, which might be a prognostic predictor of ccRCC. Targeting this molecular might provide a new therapeutic strategy for patients with advanced ccRCC.

Cuproptosis engages in c-Myc-mediated breast cancer stemness

BACKGROUND

Intra-tumoral heterogeneity (ITH) is a distinguished hallmark of cancer, and cancer stem cells (CSCs) contribute to this malignant characteristic. Therefore, it is of great significance to investigate and even target the regulatory factors driving intra-tumoral stemness. c-Myc is a vital oncogene frequently overexpressed or amplified in various cancer types, including breast cancer. Our previous study indicated its potential association with breast cancer stem cell (BCSC) biomarkers.

METHODS

In this research, we performed immunohistochemical (IHC) staining on sixty breast cancer surgical specimens for c-Myc, CD44, CD24, CD133 and ALDH1A1. Then, we analyzed transcriptomic atlas of 1533 patients with breast cancer from public database.

RESULTS

IHC staining indicated the positive correlation between c-Myc and BCSC phenotype. Then, we used bioinformatic analysis to interrogate transcriptomics data of 1533 breast cancer specimens and identified an intriguing link among c-Myc, cancer stemness and copper-induced cell death (also known as "cuproptosis"). We screened out cuproptosis-related characteristics that predicts poor clinical outcomes and found that the pro-tumoral cuproptosis-based features were putatively enriched in MYC-targets and showed a significantly positive correlation with cancer stemness.

CONCLUSION

In addition to previous reports on its oncogenic roles, c-Myc showed significant correlation to stemness phenotype and copper-induced cell toxicity in breast cancer tissues. Moreover, transcriptomics data demonstrated that pro-tumoral cuproptosis biomarkers had putative positive association with cancer stemness. This research combined clinical samples with large-scale bioinformatic analysis, covered description and deduction, bridged classic oncogenic mechanisms to innovative opportunities, and inspired the development of copper-based nanomaterials in targeting highly heterogeneous tumors.

The therapeutic and prognostic role of cuproptosis-related genes in triple negative breast cancer

BACKGROUND

This study aimed to observe the potential impact of known cuproptosis-related genes (CRGs) on triple negative breast cancer (TNBC) development, as well as their associated molecular mechanisms, immune infiltration mechanisms and potential therapeutic agents.

RESULTS

Based on the Cox Proportional Hazard Model, 11 CRGs may be especially important in TNBC development and progression (considered as the Key-TNBC-CRGs). The expression of several Key-TNBC-CRGs (e.g., ATP7A, PIK3CA, LIAS, and LIPT) are associated with common mutations. The SCNA variation of 11 Key-TNBC-CRGs are related to differences immune infiltration profiles. In particular, depletion of ATP7A, ATP7B, CLS, LIAS, and SCL31A1 and while high amplification of NLRP3 and LIPT2 are correlated with decreased immune infiltration. In our Cox proportional hazards regression model, there is a significant difference in the overall survival between high-risk and low-risk groups. The HR in the high-risk group is 3.891 versus the low-risk group. And this model has a satisfactory performance in Prediction of 5-15-year survival, in particular in the 10-year survival (AUC = 0.836). Finally, we discovered some potential drugs for TNBC treatment based on the strategy of targeting 11 Key-TNBC-CRGs, such as Dasatinib combined with ABT-737, Erastin or Methotrexate, and Docetaxel/Ispinesib combination.

CONCLUSION

In conclusion, CRGs may play important roles in TNBC development, and they can impact tumor immune microenvironment and patient survival. The Key-TNBC-CRGs interact mutually and can be influenced by common BC-related mutations. Additionally, we established a 11-gene risk model with a robust performance in prediction of 5-15-year survival. As well, some new drugs are proposed potentially effective in TNBC based on the CRG strategy.

A novel signature based on cancer-associated fibroblast genes to predict prognosis, immune feature, and therapeutic response in breast cancer

Breast cancer (BC) ranks first in the incidence of tumors in women and remains the most prevalent malignancy in women worldwide. Cancer-associated fibroblasts (CAFs) in the tumor microenvironment (TME) profoundly influence the progression, recurrence, and therapeutic resistance in BC. Here, we intended to establish a risk signature based on screened CAF-associated genes in BC (BCCGs) for patient stratification. Initially, BCCGs were screened by a combination of several CAF gene sets. The identified BCGGs were found to differ significantly in the overall survival (OS) of BC patients. Accordingly, we constructed a prognostic prediction signature of 5 BCCGs, which were independent prognostic factors associated with BC based on univariate and multivariate Cox regression. The risk model divided patients into low- and high-risk groups, accompanied by different OS, clinical features, and immune infiltration characteristics. Receiver operating characteristic (ROC) curves and a nomogram further validated the predictive performance of the prognostic model. Notably, 21 anticancer agents targeting these BCCGs possessed better sensitivity in BC patients. Meanwhile, the elevated expression of the majority of immune checkpoint genes suggested that the high-risk group may benefit more from immune checkpoint inhibitors (ICIs) therapy. Taken together, our well-established model is a robust instrument to precisely and comprehensively predict the prognosis, immune features, and drug sensitivity in BC patients, for combating BC.

The cuproptosis-associated 11 gene signature as a predictor for outcomes and response to Bacillus Calmette-Guerin and immune checkpoint inhibitor therapies in bladder carcinoma

Bladder cancer (BC) or carcinoma (BLCA) is predominantly derived from urothelium and includes non-muscle invasive BC (NMIBC) and muscle invasive BC (MIBC). Bacillus Calmette-Guerin (BCG) has long been applied for NMIBC to effectively reduce disease recurrence or progression, whereas immune checkpoint inhibitors (ICIs) were recently introduced to treat advanced BLCA with good efficacy. For BCG and ICI applications, reliable biomarkers are required to stratify potential responders for better personalized interventions, and ideally, they can replace or reduce invasive examinations such as cystoscopy in monitoring treatment efficacy. Here we developed the cuproptosis-associated 11 gene signature (CuAGS-11) model to accurately predict survival and response to BCG and ICI regimens in BLCA patients. In both discovery and validation cohorts where BLCA patients were divided into high- and low-risk groups based on a median CuAGS-11 score as the cutoff, the high-risk group was associated with significantly shortened overall survival (OS) and progression-free survival (PFS) independently. The survival predictive accuracy was comparable between CuAGS-11 and stage, and their combination-based nomograms showed high consistence between predicted and observed OS/PFS. The analysis of 3 BLCA cohorts treated with BCG unveiled lower response rates and higher frequencies of recurrence or progression coupled with shorter survival in CuAGS-11 high-risk groups. In contrast, almost none of patients underwent progression in low-risk groups. In IMvigor210 cohort of 298 BLCA patients treated with ICI Atezolizumab, complete/partial remissions were 3-fold higher accompanied by significantly longer OS in the CuAGS-11 low- than high-risk groups (P = 7.018E-06). Very similar results were obtained from the validation cohort (P = 8.65E-05). Further analyses of Tumor Immune Dysfunction and Exclusion (TIDE) scores revealed that CuAGS-11 high-risk groups displayed robustly higher T cell exclusion scores in both discovery (P = 1.96E-05) and validation (P = 0.008) cohorts. Collectively, the CuAGS-11 score model is a useful predictor for OS/PFS and BCG/ICI efficacy in BLCA patients. For BCG-treated patients, reduced invasive examinations are suggested for monitoring the CuAGS-11 low-risk patients. The present findings thus provide a framework to improve BLCA patient stratification for personalized interventions and to reduce invasive monitoring inspections.

Prognostic implication of cuproptosis related genes associates with immunity in Ewing's sarcoma

Growing evidence demonstrated that cuproptosis play critical roles in human cancers. We aimed to identify the roles of cuproptosis related genes (CRGs) in prognosis and immunity of Ewing's sarcoma. The data of GSE17674 and GSE63156 were obtained from GEO. The expression of 17 CRGs and immune cells were explored, then correlation was analyzed. Based on CRGs, two molecular clusters were identified by consensus clustering algorithm. KM survival and IME features including immune cells, immune response, checkpoint genes between clusters were evaluated. NFE2L2, LIAS, and CDKN2A were screened out as prognostic signatures by univariate, LASSO and step regression. A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values. The accuracy of risk model was also well validated in external dataset. A nomogram was constructed and evaluated by calibration curves and DCA. Low level of immune cells, immune response, and enriched checkpoint genes were found in high-risk group. GSEA of signatures and GSVA of ES-related pathways revealed the potential molecular mechanism involved in ES progression. Several drugs showed sensitivity to ES samples. DEGs between risk groups were screened out, and function enrichment was conducted. Finally, scRNA analysis of GSE146221 was done. NFE2L2, and LIAS played crucial role in the evolution of ES by pesudotime and trajectory methods. Our study provided new aspects for further research in ES.

Copper-related genes predict prognosis and characteristics of breast cancer

Background

The role of copper in cancer treatment is multifaceted, with copper homeostasis-related genes associated with both breast cancer prognosis and chemotherapy resistance. Interestingly, both elimination and overload of copper have been reported to have therapeutic potential in cancer treatment. Despite these findings, the exact relationship between copper homeostasis and cancer development remains unclear, and further investigation is needed to clarify this complexity.

Methods

The pan-cancer gene expression and immune infiltration analysis were performed using the Cancer Genome Atlas Program (TCGA) dataset. The R software packages were employed to analyze the expression and mutation status of breast cancer samples. After constructing a prognosis model to separate breast cancer samples by LASSO-Cox regression, we examined the immune statement, survival status, drug sensitivity and metabolic characteristics of the high- and low-copper related genes scoring groups. We also studied the expression of the constructed genes using the human protein atlas database and analyzed their related pathways. Finally, copper staining was performed with the clinical sample to investigate the distribution of copper in breast cancer tissue and paracancerous tissue.

Results

Pan-cancer analysis showed that copper-related genes are associated with breast cancer, and the immune infiltration profile of breast cancer samples is significantly different from that of other cancers. The essential copper-related genes of LASSO-Cox regression were ATP7B (ATPase Copper Transporting Beta) and DLAT (Dihydrolipoamide S-Acetyltransferase), whose associated genes were enriched in the cell cycle pathway. The low-copper related genes scoring group presented higher levels of immune activation, better probabilities of survival, enrichment in pathways related to pyruvate metabolism and apoptosis, and higher sensitivity to chemotherapy drugs. Immunohistochemistry staining showed high protein expression of ATP7B and DLAT in breast cancer samples. The copper staining showed copper distribution in breast cancer tissue.

Conclusion

This study displayed the potential impacts of copper-related genes on the overall survival, immune infiltration, drug sensitivity and metabolic profile of breast cancer, which could predict patients' survival and tumor statement. These findings may serve to support future research efforts aiming at improving the management of breast cancer.

Construct ceRNA Network and Risk Model of Breast Cancer Using Machine Learning Methods under the Mechanism of Cuproptosis

Breast cancer (BRCA) has an undesirable prognosis and is the second most common cancer among women after lung cancer. A novel mechanism of programmed cell death called cuproptosis is linked to the development and spread of tumor cells. However, the function of cuproptosis in BRCA remains unknown. To this date, no studies have used machine learning methods to screen for characteristic genes to explore the role of cuproptosis-related genes (CRGs) in breast cancer. Therefore, 14 cuproptosis-related characteristic genes (CRCGs) were discovered by the feature selection of 39 differentially expressed CRGs using the three machine learning methods LASSO, SVM-RFE, and random forest. Through the PPI network and immune infiltration analysis, we found that PRNP was the key CRCG. The miRTarBase, TargetScan, and miRDB databases were then used to identify hsa-miR-192-5p and hsa-miR-215-5p as the upstream miRNA of PRNP, and the upstream lncRNA, CARMN, was identified by the StarBase database. Thus, the mRNA PRNP/miRNA hsa-miR-192-5p and hsa-miR-215-5p/lncRNA CARMN ceRNA network was constructed. This ceRNA network, which has not been studied before, is extremely innovative. Furthermore, four cuproptosis-related lncRNAs (CRLs) were screened in TCGA-BRCA by univariate Cox, LASSO, and multivariate Cox regression analysis. The risk model was constructed by using these four CRLs, and the risk score = C9orf163 * (1.8365) + PHC2-AS1 * (-2.2985) + AC087741.1 * (-0.9504) + AL109824.1 * (0.6016). The ROC curve and C-index demonstrated the superior predictive capacity of the risk model, and the ROC curve demonstrated that the AUC of 1-, 3-, and 5-year OS in all samples was 0.721, 0.695, and 0.633, respectively. Finally, 50 prospective sensitive medicines were screened with the pRRophetic R package, among which 17-AAG may be a therapeutic agent for high-risk patients, while the other 49 medicines may be suitable for the treatment of low-risk patients. In conclusion, our study constructs a new ceRNA network and a novel risk model, which offer a theoretical foundation for the treatment of BRCA and will aid in improving the prognosis of BRCA.

FNBP4 is a Potential Biomarker Associated with Cuproptosis and Promotes Tumor Progression in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that lacks an efficient therapeutic approach because of its elusive molecular mechanisms. This study aimed to investigate the biological function and potential mechanism of formin-binding protein 4 (FNBP4) in HCC.

Methods

FNBP4 expression in tissues and cells were detected by quantitative real-time PCR (qRT‒PCR), Western blot, and immunohistochemistry (IHC). The Kaplan-Meier method was used to explore the correlation between the FNBP4 expression and clinical survival. MTT, EdU incorporation, colony formation, and Transwell assays were performed to evaluate the function of FNBP4 in cell proliferation and migration in vitro. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to explore the potential mechanism of FNBP4. The prognostic risk signature and nomogram were constructed to demonstrate the prognostic value of FNBP4.

Results

We found that FNBP4 was upregulated in patients with HCC and associated with poor overall survival (OS). Furthermore, knockdown of FNBP4 inhibited the proliferation and migration in HCC cells. Then, we performed a KEGG pathway analysis of the coexpressed genes associated with FNBP4 and found that FNBP4 may be associated with tumor-related signaling pathways and cuproptosis. We verified that FNBP4 could cause cell cycle progression and inactivation of the hippo signaling pathway. A prognostic risk signature containing three FNBP4-related differentially expressed cuproptosis regulators (DECRs) was established and can be used as an independent risk factor to evaluate the prognosis of patients with HCC. In addition, a nomogram including a risk score and clinicopathological factors was used to predict patient survival probabilities.

Conclusion

FNBP4, as a potential biomarker associated with cuproptosis, promotes HCC cell proliferation and metastasis. We provide a new potential strategy for HCC treatment by targeting FNBP4.

Comprehensive Analysis of Cuproptosis Genes and Identification of Cuproptosis Subtypes in Breast Cancer

BACKGROUND

Copper-induced death (cuproptosis) is copper-dependent regulated cell death, which is different from known death mechanisms and is dependent on mitochondrial respiration. However, its effect on breast cancer (BRCA) is unclear.

OBJECTIVE

The objective of this study is to explore the important clinical significance of cuproptosis genes and to provide a new idea for guiding the personalized immunotherapy strategy of BRCA patients.

MATERIALS AND METHODS

We collected cuproptosis genes from published work. The gene alteration, differential expression, and prognostic value of cuproptosis genes were explored in BRCA based on TCGA database. We identified two subtypes (clusters A and B) by performing unsupervised clustering. The difference between two clusters was deeply explored, including clinical features, differential expressed genes (DEGs), pathways, and immune cell infiltration. Based on the DEGs between two clusters, a cuproptosis score was constructed and its predictive capability for overall survival of BRCA patients was validated.

RESULTS AND DISCUSSION

Patients with high cuproptosis score have worse survival status, with an increased infiltration level of most immune cells. Further analysis suggested that BRCA patients with high cuproptosis score may be sensitive to immune checkpoint inhibitor (ICI) treatment.

CONCLUSION

Our findings may improve our understanding of cuproptosis in BRCA and may distinguish patients suitable for ICI treatment.