CDKN2A-mediated molecular subtypes characterize the hallmarks of tumor microenvironment and guide precision medicine in triple-negative breast cancer

Emerging phytochemical-based nanocarriers: redefining the perspectives of breast cancer therapy

Breast cancer is recognized as the most prevalent condition impacting women globally, despite several advancements in diagnosis and treatment. Existing therapeutic interventions including surgical procedures, radiation therapy, and chemotherapy often produce harmful effects on healthy tissues, trigger chemo-resistance, and augment the risk of relapse. In response to several unmet challenges, substantial research has been conducted to explore the therapeutic potential of natural compounds for breast cancer therapy. Progress in phytochemistry and pharmacology has facilitated the identification of diverse herbal bioactives with favorable safety profiles and multi-target mechanisms of action against breast cancer cells. Several phytochemicals like flavonoids and tannins have shown significant anticancer potential against breast cancer in diverse preclinical models. However, challenges like limited cellular absorption, low water solubility, and high molecular weight hinder their effective translation into clinical applications. Therefore, the development of novel therapies is imperative for overcoming these hurdles in breast cancer treatment effectively. Nanotechnology has reflected considerable perspective in tackling diverse challenges by encapsulating phytoconstituents within various nanocarriers including polymeric nanoparticles, lipidic nanoparticles, nanoemulsions, nanogels, gold nanoparticles, and silver nanoparticles. This manuscript emphasizes the recent advancements in phytochemical-loaded nanocarriers efficiently tailored for breast cancer therapy along with patents, current challenges, and future perspectives in this avenue.

The important role of cuproptosis and cuproptosis-related genes in the development of thyroid carcinoma revealed by transcriptomic analysis and experiments

OBJECTIVE

Programmed Cell Death (PCD) processes have been suggested to play a role in the development of cancers. The study aimed to investigate the enrichment of different types of PCD and identify important PCD-related genes in Thyroid Carcinoma (THCA).

METHODS

The whole study is based on transcriptomic analysis and Immunohistochemistry (IHC) experiments. For transcriptomic analysis, the transcriptomic data of THCA (n = 493) and normal thyroid samples (n = 58) was used. The enrichment score of different types of PCD in THCA samples was calculated and the most enriched PCD process was identified. Then the expression of PCD-related genes in control and THCA samples were compared and the association between cuproptosis and characteristics of Tumor Microenvironment (TME) in THCA tissues was explored. IHC experiment was performed to confirm gene expressions in THCA and para-tumor samples.

RESULTS

Enrichment analysis showed that cuproptosis was the most enriched type of PCD process and associated with malignancy in THCA. The expression of a cuproptosis-related gene, CDKN2A, was found and confirmed to be higher in THCA than normal samples and associated with poor outcomes and higher clinical stages of patients with THCA. Moreover, CDKN2A expression was associated with immunosuppressive TME in THCA.

CONCLUSION

Our findings indicated the important role of cuproptosis and a cuproptosis-related gene, CDKN2A, in the development and progression of THCA, which might provide novel insights into the understanding of pathophysiology of THCA.

Bioinformatics approaches to multi-omics analysis of the potential of CDKN2A as a biomarker and therapeutic target for uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is a significant cause of cancer-related mortality among women worldwide. Prior research has demonstrated an association between cyclin-dependent kinase inhibitor 2 A (CDKN2A) and various tumors. As a member of the INK4 family, CDKN2A is involved in cell cycle regulation by controlling CDKs. In the present study, bioinformatics was used to analyze public datasets. The expression levels, signaling pathways, and copy number variations of CDKN2A in UCEC were explored, along with its immune cell subset associations. CDKN2A expression was found to be elevated in UCEC, particularly in the signaling pathways involved in cell proliferation and inflammation. Analysis of somatic copy number alterations in the TCGA (The Cancer Genome Atlas)-UCEC dataset revealed a connection between CDKN2A and drug metabolism in UCEC. Assessment of the relationship between CDKN2A and genes involved in immunotherapy for UCEC patients showed a negative correlation between CDKN2A and CD8+ T cell activity, as well as IL-2 and TP53. Collectively, these insights suggest that CDKN2A may be a potential biomarker for prognosis and treatment strategies in UCEC.

Context-dependent effects of CDKN2A and other 9p21 gene losses during the evolution of esophageal cancer

CDKN2A is a tumor suppressor located in chromosome 9p21 and frequently lost in Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC). How CDKN2A and other 9p21 gene co-deletions affect EAC evolution remains understudied. We explored the effects of 9p21 loss in EACs and cancer progressor and non-progressor BEs with matched genomic, transcriptomic and clinical data. Despite its cancer driver role, CDKN2A loss in BE prevents EAC initiation by counterselecting subsequent TP53 alterations. 9p21 gene co-deletions predict poor patient survival in EAC but not BE through context-dependent effects on cell cycle, oxidative phosphorylation and interferon response. Immune quantifications using bulk transcriptome, RNAscope and high-dimensional tissue imaging showed that IFNE loss reduces immune infiltration in BE, but not EAC. Mechanistically, CDKN2A loss suppresses the maintenance of squamous epithelium, contributing to a more aggressive phenotype. Our study demonstrates context-dependent roles of cancer genes during disease evolution, with consequences for cancer detection and patient management.

Cuproptosis: a promising new target for breast cancer therapy

Breast cancer (BC) is the leading cause of cancer-related mortality among women globally, affecting approximately one-quarter of all female cancer patients and accounting for one-sixth of cancer-related deaths in women. Despite significant advancements in diagnostic and therapeutic approaches, breast cancer treatment remains challenging due to issues such as recurrence and metastasis. Recently, a novel form of regulated cell death, termed cuproptosis, has been identified. This process disrupts mitochondrial respiration by targeting the copper-dependent cellular pathways. The role of cuproptosis has been extensively investigated in various therapeutic contexts, including chemotherapy, immunotherapy, radiotherapy, and nanotherapy, with the development of novel drugs significantly improving clinical outcomes. This article aims to further elucidate the connection between cuproptosis and breast cancer, focusing on its therapeutic targets, signaling pathways, and potential biomarkers that could enhance treatment strategies. These insights may offer new opportunities for improved patient care and outcomes in breast cancer therapy.

Cuproptosis, ferroptosis and PANoptosis in tumor immune microenvironment remodeling and immunotherapy: culprits or new hope

Normal life requires cell division to produce new cells, but cell death is necessary to maintain balance. Dysregulation of cell death can lead to the survival and proliferation of abnormal cells, promoting tumor development. Unlike apoptosis, necrosis, and autophagy, the newly recognized forms of regulated cell death (RCD) cuproptosis, ferroptosis, and PANoptosis provide novel therapeutic strategies for tumor treatment. Increasing research indicates that the death of tumor and immune cells mediated by these newly discovered forms of cell death can regulate the tumor microenvironment (TME) and influence the effectiveness of tumor immunotherapy. This review primarily elucidates the molecular mechanisms of cuproptosis, ferroptosis, and PANoptosis and their complex effects on tumor cells and the TME. This review also summarizes the exploration of nanoparticle applications in tumor therapy based on in vivo and in vitro evidence derived from the induction or inhibition of these new RCD pathways.

Immunosuppressive SOX9-AS1 Resists Triple-Negative Breast Cancer Senescence Via Regulating Wnt Signalling Pathway

Long noncoding RNAs (lncRNAs) are involved in the regulation of triple-negative breast cancer (TNBC) senescence, while pro-carcinogenic lncRNAs resist senescence onset leading to the failure of therapy-induced senescence (TIS) strategy, urgently identifying the key senescence-related lncRNAs (SRlncRNAs). We mined seven SRlncRNAs (SOX9-AS1, LINC01152, AC005152.3, RP11-161 M6.2, RP5-968 J1.1, RP11-351 J23.1 and RP11-666A20.3) by bioinformatics, of which SOX9-AS1 was reported to be pro-carcinogenic. In vitro experiments revealed the highest expression of SOX9-AS1 in MDA-MD-231 cells. SOX9-AS1 knockdown inhibited cell growth (proliferation, cycle and apoptosis) and malignant phenotypes (migration and invasion), while SOX9-AS1 overexpression rescued these effects. Additionally, SOX9-AS1 knockdown facilitated tamoxifen-induced cellular senescence and the transcription of senescence-associated secretory phenotype (SASP) factors (IL-1α, IL-1β, IL-6 and IL-8) mechanistically by resisting senescence-induced Wnt signal (GSK-3β/β-catenin) activation. Immune infiltration analysis revealed that low SOX9-AS1 expression was accompanied by a high infiltration of naïve B cells, CD8+ T cells and γδ T cells. In conclusion, SOX9-AS1 resists TNBC senescence via regulating the Wnt signalling pathway and inhibits immune infiltration. Targeted inhibition of SOX9-AS1 enhances SASP and thus mobilises immune infiltration to adjunct TIS strategy.

Elucidating the evolving role of cuproptosis in breast cancer progression

Breast cancer (BC) persists as a highly prevalent malignancy in females, characterized by diverse molecular signatures and necessitating personalized therapeutic approaches. The equilibrium of copper within the organism is meticulously maintained through regulated absorption, distribution, and elimination, underpinning not only cellular equilibrium but also various essential biological functions. The process of cuproptosis is initiated by copper's interaction with lipoylases within the tricarboxylic acid (TCA) cycle, which triggers the conglomeration of lipoylated proteins and diminishes the integrity of Fe-S clusters, culminating in cell demise through proteotoxic stress. In BC, aberrations in cuproptosis are prominent and represent a crucial molecular incident that contributes to the disease progression. It influences BC cell metabolism and affects critical traits such as proliferation, invasiveness, and resistance to chemotherapy. Therapeutic strategies that target cuproptosis have shown promising antitumor efficacy. Moreover, a plethora of cuproptosis-centric genes, including cuproptosis-related genes (CRGs), CRG-associated non-coding RNAs (ncRNAs), and cuproptosis-associated regulators, have been identified, offering potential for the development of risk assessment models or diagnostic signatures. In this review, we provide a comprehensive exposition of the fundamental principles of cuproptosis, its influence on the malignant phenotypes of BC, the prognostic implications of cuproptosis-based markers, and the substantial prospects of exploiting cuproptosis for BC therapy, thereby laying a theoretical foundation for targeted interventions in this domain.

Mechanisms of sensitivity and resistance to CDK4/CDK6 inhibitors in hormone receptor-positive breast cancer treatment

Cell cycle dysregulation is a hallmark of cancer that promotes eccessive cell division. Cyclin-dependent kinase 4 (CDK4) and cyclin-dependent kinase 6 (CDK6) are key molecules in the G1-to-S phase cell cycle transition and are crucial for the onset, survival, and progression of breast cancer (BC). Small-molecule CDK4/CDK6 inhibitors (CDK4/6i) block phosphorylation of tumor suppressor Rb and thus restrain susceptible BC cells in G1 phase. Three CDK4/6i are approved for the first-line treatment of patients with advanced/metastatic hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) BC in combination with endocrine therapy (ET). Though this has improved the clinical outcomes for survival of BC patients, there is no established standard next-line treatment to tackle drug resistance. Recent studies suggest that CDK4/6i can modulate other distinct effects in both BC and breast stromal compartments, which may provide new insights into aspects of their clinical activity. This review describes the biochemistry of the CDK4/6-Rb-E2F pathway in HR+ BC, then discusses how CDK4/6i can trigger other effects in BC/breast stromal compartments, and finally outlines the mechanisms of CDK4/6i resistance that have emerged in recent preclinical studies and clinical cohorts, emphasizing the impact of these findings on novel therapeutic opportunities in BC.

CDKN2A inhibited ferroptosis through activating JAK2/STAT3 pathway to modulate cisplatin resistance in cervical squamous cell carcinoma

Cervical squamous cell carcinoma (CESC) is a significant threat to women's health. Resistance to cisplatin (DDP), a common treatment, hinders the therapeutic efficacy. Understanding the molecular basis of DDP resistance in CESC is imperative. Cyclin-dependent kinase inhibitor 2A (CDKN2A) expression was evaluated through quantitative real-time-PCR and western blot in clinical samples from 30 CESC patients and human cervical epithelial cells and CESC cell lines (SiHa, C33A, and Caski). It was also evaluated through bioinformatics analysis in Timer, Ualcan, and GEPIA database. Cell viability was detected by CCK-8. Apoptosis was detected by Calcein AM/PI assay. Lipid reactive oxygen species (ROS), malondialdehyde, glutathione, Fe 2+ , and iron level were detected by kits. Protein level of JAK2, STAT3, p-JAK2, p-STAT3, ACSL4, GPX4, SLC7A11, and FTL were detected by western blot. In CESC, elevated CDKN2A expression was observed. Cisplatin exhibited a dual effect, inhibiting cell proliferation and inducing ferroptosis in CESC. CDKN2A knockdown in a cisplatin-resistant cell line suppressed proliferation and induced ferroptosis. Moreover, CDKN2A was identified as an inhibitor of erastin-induced ferroptosis. Additionally, targeting the JAK2/STAT3 pathway enhanced ferroptosis in cisplatin-resistant cells. CDKN2A could inhibit ferroptosis in CESC through activating JAK2/STAT3 pathway to modulate cisplatin resistance.

Screening for ferroptosis genes related to endometrial carcinoma and predicting of targeted drugs based on bioinformatics

Endometrial carcinoma is one of most common malignant tumors in women, and ferroptosis is closely related to the development and treatment of endometrial carcinoma. The aim of this study was to screen ferroptosis-related genes associated with endometrial carcinoma and predict targeted drugs through bioinformatics. 761 differentially expressed genes were obtained by the dataset GSE63678 from the GEO database, and most of the genes were enriched in the KEGG_CELL_CYCLE and KEGG_OOCYTE_MEIOSIS signaling pathways. 22 ferroptosis-differentially expressed genes were obtained by intersection with the FerrDb database. These genes were involved in biological processes including macromolecular complex assembly and others, and involved in signal pathways including glutathione metabolism, p53 signaling pathway and others. CDKN2A, IDH1, NRAS, TFRC and GOT1 were obtained as hub genes by PPI network analysis. GEPIA showed that CDKN2A, IDH1, NRAS and TFRC were significantly expressed in endometrial carcinoma. Immunohistochemical results showed that CDKN2A, NRAS and TFRC were significantly expressed in endometrial carcinoma clinical tissue samples. The ROC constructed by TCGA database showed that CDKN2A, NRAS and TFRC had significant value in the diagnosis of endometrial carcinoma, and all had prognostic efficacy. 136,572-09-3 BOSS and others were identified as potential targeted drugs for endometrial carcinoma targeting ferroptosis. Our study has shown that ferroptosis-related genes CDKN2A, NRAS and TFRC are diagnostic markers of endometrial carcinoma, and 136,572-09-3 BOSS, methyprylon BOSS, daunorubicin CTD 00005752, nitroglycerin BOSS and dUTP BOSS, IRON BOSS, Imatinib mesylate BOSS, 2-Butanone BOSS, water BOSS, and L-thyroxine BOSS may be potential therapeutic drugs.

Copper homeostasis and cuproptosis in gynecological disorders: Pathogenic insights and therapeutic implications

This review comprehensively explores the complex role of copper homeostasis in female reproductive system diseases. As an essential trace element, copper plays a crucial role in various biological functions. Its dysregulation is increasingly recognized as a pivotal factor in the pathogenesis of gynecological disorders. We investigate how copper impacts these diseases, focusing on aspects like oxidative stress, inflammatory responses, immune function, estrogen levels, and angiogenesis. The review highlights significant changes in copper levels in diseases such as cervical, ovarian, endometrial cancer, and endometriosis, underscoring their potential roles in disease mechanisms and therapeutic exploration. The recent discovery of 'cuproptosis,' a novel cell death mechanism induced by copper ions, offers a fresh molecular perspective in understanding these diseases. The review also examines genes associated with cuproptosis, particularly those related to drug resistance, suggesting new strategies to enhance traditional therapy effectiveness. Additionally, we critically evaluate current therapeutic approaches targeting copper homeostasis, including copper ionophores, chelators, and nanoparticles, emphasizing their emerging potential in gynecological disease treatment. This article aims to provide a comprehensive overview of copper's role in female reproductive health, setting the stage for future research to elucidate its mechanisms and develop targeted therapeutic strategies.

Bioinformatic analysis and experimental validation of six cuproptosis-associated genes as a prognostic signature of breast cancer

BACKGROUND

Breast carcinoma (BRCA) is a life-threatening malignancy in women and shows a poor prognosis. Cuproptosis is a novel mode of cell death but its relationship with BRCA is unclear. This study attempted to develop a cuproptosis-relevant prognostic gene signature for BRCA.

METHODS

Cuproptosis-relevant subtypes of BRCA were obtained by consensus clustering. Differential expression analysis was implemented using the 'limma' package. Univariate Cox and multivariate Cox analyses were performed to determine a cuproptosis-relevant prognostic gene signature. The signature was constructed and validated in distinct datasets. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were also conducted using the prognostic signature to uncover the underlying molecular mechanisms. ESTIMATE and CIBERSORT algorithms were applied to probe the linkage between the gene signature and tumor microenvironment (TME). Immunotherapy responsiveness was assessed using the Tumor Immune Dysfunction and Exclusion (TIDE) web tool. Real-time quantitative PCR (RT-qPCR) was performed to detect the expressions of cuproptosis-relevant prognostic genes in breast cancer cell lines.

RESULTS

Thirty-eight cuproptosis-associated differentially expressed genes (DEGs) in BRCA were mined by consensus clustering and differential expression analysis. Based on univariate Cox and multivariate Cox analyses, six cuproptosis-relevant prognostic genes, namely SAA1, KRT17, VAV3, IGHG1, TFF1, and CLEC3A, were mined to establish a corresponding signature. The signature was validated using external validation sets. GSVA and GSEA showed that multiple cell cycle-linked and immune-related pathways along with biological processes were associated with the signature. The results ESTIMATE and CIBERSORT analyses revealed significantly different TMEs between the two Cusig score subgroups. Finally, RT-qPCR analysis of cell lines further confirmed the expressional trends of SAA1, KRT17, IGHG1, and CLEC3A.

CONCLUSION

Taken together, we constructed a signature for projecting the overall survival of BRCA patients and our findings authenticated the cuproptosis-relevant prognostic genes, which are expected to provide a basis for developing prognostic molecular biomarkers and an in-depth understanding of the relationship between cuproptosis and BRCA.

Cuproptosis in lung cancer: mechanisms and therapeutic potential

Cuproptosis, a recently identified form of cell death that differs from other forms, is induced by the disruption of the binding of copper to mitochondrial respiratory acylation components. Inducing cell cuproptosis and targeting cell copper death pathways are considered potential directions for treating tumor diseases. We have provided a detailed introduction to the metabolic process of copper. In addition, this study attempts to clarify and summarize the relationships between cuproptosis and therapeutic targets and signaling pathways of lung cancer. This review aims to summarize the theoretical achievements for translating the results of lung cancer and cuproptosis experiments into clinical treatment.

Molecular monitoring by CDKN2A/p16INK4A and RB1 gene methylation in breast cancer

OBJECTIVE

This prospective study aimed to provide a comprehensive analysis of the methylation status of two pivotal genes, CDKN2A/p16INK4A (cyclin-dependent kinase inhibitor 2A) and RB1 (retinoblastoma transcriptional corepressor 1), in breast cancer patients.

METHODS

Samples were obtained from 15 women diagnosed with breast cancer and who underwent a total mastectomy. DNA was extracted from the tumor, non-tumor tissue, and peripheral blood (circulating cell-free DNA). The methylation pattern of cell-free DNA extracted from blood collected on the day of mastectomy was compared with the methylation pattern of cell-free DNA from blood collected 1 year post-surgery. The methylation analysis was carried out by sodium bisulfite conversion and polymerase chain reaction, followed by electrophoresis.

RESULTS

Methylation of CDKN2A/p16INK4A was identified in 13 tumor samples and 12 non-tumor tissue samples. Two patients exhibited CDKN2A/p16INK4A methylation in the cell-free DNA of the first blood collection, while another showed methylation only in the cell-free DNA of the subsequent blood collection. Regarding RB1, 11 tumors and 8 non-tumor tissue samples presented methylation of the gene.

CONCLUSION

This study presents a novel approach for monitoring breast cancer patients through the analysis of cell-free DNA methylation. This analysis can detect changes in methylation patterns before any visible sign of cancer appears in breast tissue and could help predict the recurrence of malignant breast tumors.

Unraveling Biomarker Signatures in Triple-Negative Breast Cancer: A Systematic Review for Targeted Approaches

Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer, marked by poor outcomes and dismal prognosis. Due to the absence of targetable receptors, chemotherapy still represents the main therapeutic option. Therefore, current research is now focusing on understanding the specific molecular pathways implicated in TNBC, in order to identify novel biomarker signatures and develop targeted therapies able to improve its clinical management. With the aim of identifying novel molecular features characterizing TNBC, elucidating the mechanisms by which these molecular biomarkers are implicated in the tumor development and progression, and assessing the impact on cancerous cells following their inhibition or modulation, we conducted a literature search from the earliest works to December 2023 on PubMed, Scopus, and Web Of Science. A total of 146 studies were selected. The results obtained demonstrated that TNBC is characterized by a heterogeneous molecular profile. Several biomarkers have proven not only to be characteristic of TNBC but also to serve as potential effective therapeutic targets, holding the promise of a new era of personalized treatments able to improve its prognosis. The pre-clinical findings that have emerged from our systematic review set the stage for further investigation in forthcoming clinical trials.

Exploring Biomarkers in Breast Cancer: Hallmarks of Diagnosis, Treatment, and Follow-Up in Clinical Practice

Breast cancer is a prevalent malignancy in the present day, particularly affecting women as one of the most common forms of cancer. A significant portion of patients initially present with localized disease, for which curative treatments are pursued. Conversely, another substantial segment is diagnosed with metastatic disease, which has a worse prognosis. Recent years have witnessed a profound transformation in the prognosis for this latter group, primarily due to the discovery of various biomarkers and the emergence of targeted therapies. These biomarkers, encompassing serological, histological, and genetic indicators, have demonstrated their value across multiple aspects of breast cancer management. They play crucial roles in initial diagnosis, aiding in the detection of relapses during follow-up, guiding the application of targeted treatments, and offering valuable insights for prognostic stratification, especially for highly aggressive tumor types. Molecular markers have now become the keystone of metastatic breast cancer diagnosis, given the diverse array of chemotherapy options and treatment modalities available. These markers signify a transformative shift in the arsenal of therapeutic options against breast cancer. Their diagnostic precision enables the categorization of tumors with elevated risks of recurrence, increased aggressiveness, and heightened mortality. Furthermore, the existence of therapies tailored to target specific molecular anomalies triggers a cascade of changes in tumor behavior. Therefore, the primary objective of this article is to offer a comprehensive review of the clinical, diagnostic, prognostic, and therapeutic utility of the principal biomarkers currently in use, as well as of their clinical impact on metastatic breast cancer. In doing so, our goal is to contribute to a more profound comprehension of this complex disease and, ultimately, to enhance patient outcomes through more precise and effective treatment strategies.

Identification of genes and pathways associated with menopausal status in breast cancer patients using two algorithms

BACKGROUND

Menopausal status has a known relationship with the levels of estrogen, progesterone, and other sex hormones, potentially influencing the activity of ER, PR, and many other signaling pathways involved in the initiation and progression of breast cancer. However, the differences between premenopausal and postmenopausal breast cancer patients at the molecular level are unclear.

METHODS

We retrieved eight datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) associated with menopausal status in breast cancer patients were identified using the MAMA and LIMMA methods. Based on these validated DEGs, we performed Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) networks were constructed. We used DrugBank data to investigate which of these validated DEGs are targetable. Survival analysis was performed to explore the influence of these genes on breast cancer patient prognosis.

RESULTS

We identified 762 DEGs associated with menopausal status in breast cancer patients. PPI network analysis indicated that these genes are primarily involved in pathways such as the cell cycle, oocyte meiosis and progesterone-mediated oocyte maturation pathways. Notably, several genes played roles in multiple signaling pathways and were associated with patient survival. These genes were also observed to be targetable according to the DrugBank database.

CONCLUSION

We identified DEGs associated with menopausal status in breast cancer patients. The association of these genes with several key pathways may promote understanding of the complex characterizations of breast cancer. Our findings offer valuable insights for developing new therapeutic strategies tailored to the menopausal status of breast cancer patients.

TFR1-Mediated Iron Metabolism Orchestrates Tumor Ferroptosis and Immunity in Non-Small Cell Lung Cancer

This study aimed to investigate the underlying molecular mechanisms of transferrin receptor (TFR1) in non-small cell lung cancer (NSCLC). Histological analysis was performed using hematoxylin-eosin (HE) staining. The number of CD8+ T cell were determined by flow cytometry and immunofluorescence assays. mRNA levels were analyzed by qRT-PCR. Protein expression was detected by western blot. Ferroptosis was detected by using propidium iodide (PI) staining. Xenograft experiment was applied for determining tumor growth. The results showed that interferon (IFN)-γ plus iron dextran (FeDx) induced iron overload and the ferroptosis of NSCLC cells. Moreover, IFN-γ-mediated upregulation of TFR1 promoted ferritinophagy and tumor cell ferroptosis via blocking via blocking ferritin heavy chain 1 (FTH1)/ ferritin light chain (FTL) signaling. However, TFR1 knockout suppressed the ferroptosis of tumor cells. Furthermore, FeDx-mediated iron overload promoted the sensitivity of anti-programmed death ligand 1 (PD-L1) therapies. Clinically, TFR1 was downregulated in NSCLC patients. Low levels of TFR1 predicted decreased CD8+ T cells. Taken together, IFN-γ combined with iron metabolism therapies may provide a novel alternative for NSCLC.

METTL14-Mediated m6a Modification of CDKN2A Promotes the Development of Retinoblastoma by Inhibiting the p53 Pathway

The methyltransferase 14, N6-adenosine-methyltransferase subunit (METTL14) and Cyclin-dependent kinase inhibitor 2A (CDKN2A) have been identified as involved in the regulation of various cancer progression, while their mechanism and regulatory effect in retinoblastoma (RB) is still unclear. Cell colony formation, CCK-8 as well as Western blotting were used to evaluate the proliferation, apoptosis as well as p53 protein level of RB cell line. The METTL14 and CDKN2A levels were detected by qRT-PCR or Western blotting when METTL14 was up-regulated or CDKN2A was down-regulated. MeRIP and Pearson analysis were performed to confirm the regulatory relationship between METTL14 among CDKN2A. We found that the levels of CDKN2A and METTL14 were abundant in RB samples, as well as RB cells. METTL14 enhances N6-methyladenosine (m6A) modification of CDKN2A to upregulate its mRNA and protein levels. The proliferation of RB cells can be inhibited by silencing CDKN2A, which promotes apoptosis and p53 protein level. Furthermore, high-expression of METTL14 eliminated the anti-tumor effect of CDKN2A silencing in RB progression in vitro. CDKN2A is mediated by METTL14-m6A modified and restrains p53 pathway activation to accelerate the malignancy of RB. This points to the METTL14-m6A-CDKN2A-p53 pathway axis as a possible prospective target for the future RB treatment.

Integrating ferroptosis-related genes (FRGs) and prognostic models to enhance UCEC outcome prediction and therapeutic insights

Ferroptosis is closely associated with uterine corpus endometrial carcinoma (UCEC) development. This project aimed to identify new potential biomarkers to predict the prognosis of UCEC. In this work, UCEC transcriptome data along with clinical information was retrieved from the TCGA database including a total of 382 FRGs. We performed univariate Cox regression analysis to evaluate ferroptosis-related genes (FRGs) for prognostic significance. The genes with prognostic significance were then analyzed using LASSO-Cox to construct a prognosis model. The model genes were further characterized through various proteomic analyses and expression detection in clinical samples. A multivariate Cox regression model was constructed containing four FRGs (CDKN1A, CDKN2A, CEBPG, NOS2). Among four FRGs, higher expressions of CDKN2A, CEBPG, and NOS2 were associated with poorer overall survival probability, while higher expression of CDKN1A was associated with better overall survival probability. The area under the receiver operating characteristic curve of the risk model was 0.617, 0.688, and 0.693 for 1 year, 3 years, and 5 years, respectively. Moreover, proteomic analysis showed that the protein expression of CDKN1A, CDKN2A, and CEBPG was higher in tumor tissues than that in normal tissues. Higher protein expression of CDKN1A and CDKN2A predicted poorer survival probability. Besides, CDKN1A protein had an interaction relationship with CDKN2A protein or NOS2 protein. In clinical samples, all four FRGs were upregulated in UCEC tissues, regardless of gene expression or protein expression. Our four FRGs risk model provides new insights for predicting the prognosis of UCEC patients.

MIRS: An AI scoring system for predicting the prognosis and therapy of breast cancer

Tumor-infiltrating immune cells (TIICs) and metastasis are crucial characteristics for tumorigenesis. However, the potential role of their combination in breast cancer (BRCA) remains elusive. Herein, on the basis of quantifying TIICs and tumor metastasis together, we established a precise prognostic scoring system named metastatic and immunogenomic risk score (MIRS) using a neural network model. MIRS showed better performance when compared with other published signatures. MIRS stratifies patients into a high risk subtype (MIRShigh) and a low risk subtype (MIRSlow). The MIRShigh patients exhibit significantly lower survival rate compared with MIRSlow patients (P < 0.0001 ), higher response to chemotherapy, but lower response to immunotherapy. Conversely, higher infiltration level of TIICs and significantly prolonged survival (P = 0.029 ) are observed in MIRSlow patients, indicating sensitive response in immunotherapy. This work presents a promising indicator to guide treatment options of the BRCA population and provides a predicted webtool that is almost universally applicable to BRCA patients.

Cuproptosis and cuproptosis-related genes: Emerging potential therapeutic targets in breast cancer

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

CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model

BACKGROUND

Before the discovery of cuproptosis, copper-loaded nanoparticle is a wildly applied strategy for enhancing the tumor-cell-killing effect of chemotherapy. Although copper(ii)-related researches are wide, details of cuproptosis-related bioprocess in pan-cancer are not clear yet now, especially for prognosis and drug sensitivity prediction yet now.

METHODS

In this study, VOSviewer is used for the literature review, and R4.2.0 is used for data analysis. Public data are collected from TCGA and GEO, local breast cancer cohort is collected to verify the expression level of CDKN2A.

RESULTS

7036 published articles exhibited a time-dependent linear relationship (R=0.9781, p<0.0001), and breast cancer (33.4%) is the most researched topic. Cuproptosis-related-genes (CRGs)-based unsupervised clustering divides pan-cancer subgroups into four groups (CRG subgroup) with differences in prognosis and tumor immunity. 44 tumor-driver-genes (TDGs)-based prediction model of drug sensitivity and prognosis is constructed by artificial intelligence (AI). Based on TDGs and clinical features, a nomogram is (C- index: 0.7, p= 6.958e- 12) constructed to predict the prognosis of breast cancer. Importance analysis identifies CDKN2A has a pivotal role in AI modeling, whose higher expression indicates worse prognosis in breast cancer. Furthermore, inhibition of CDKN2A down-regulates decreases Snail1, Twist1, Zeb1, vimentin and MMP9, while E-cadherin is increased. Besides, inhibition of CDKN2A also decreases the expression of MEGEA4, phosphorylated STAT3, PD-L1, and caspase3, while cleaved-caspase3 is increased. Finally, we find down-regulation of CDKN2A or MAGEA inhibits cell migration and wound healing, respectively.

CONCLUSIONS

AI identified CRG subgroups in pan-cancer based on CRGs-related TDGs, and 44-gene-based AI modeling is a novel tool to identify chemotherapy sensitivity in breast cancer, in which CDKN2A/MAGEA4 pathway played the most important role.

Transcriptomic analysis reveals the potential biological mechanism of AIS and lung adenocarcinoma

Introduction

Acute ischemic stroke (AIS) and lung adenocarcinoma (LUAD) are associated with some of the highest morbidity and mortality rates worldwide. Despite reports on their strong correlation, the causal relationship is not fully understood. The study aimed to identify and annotate the biological functions of hub genes with clinical diagnostic efficacy in AIS and LUAD.

Methods

Transcriptome and single-cell datasets were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We identified the differentially expressed genes (DEGs) upregulated in AIS and LUAD and found 372 genes intersecting both datasets. Hub genes were identified using protein-protein interaction (PPI) networks, and the diagnostic and prognostic utility of these hub genes was then investigated using receiver operating characteristic (ROC) curves, survival analysis, and univariable Cox proportional hazard regression. Single-cell analysis was used to detect whether the hub genes were expressed in tumor epithelial cells. The immune microenvironment of AIS and LUAD was assessed using the CIBERSORT algorithm. The protein expression of these hub genes was tracked using the Human Protein Atlas (HPA). We calculated the number of positive cells using the digital pathology software QuPath. Finally, we performed molecular docking after using the Enrichr database to predict possible medicines.

Results

We identified the molecular mechanisms underlying hub genes in AIS and LUAD and found that CCNA2, CCNB1, CDKN2A, and CDK1 were highly expressed in AIS and LUAD tissue samples compared to controls. The hub genes were mainly involved in the following pathways: the cell cycle, cellular senescence, and the HIF-1 signaling pathway. Using immunohistochemical slices from the HPA database, we confirmed that these hub genes have a high diagnostic capability for AIS and LUAD. Further, their high expression is associated with poor prognosis. Finally, curcumin was tested as a potential medication using molecular docking modeling.

Discussion

Our findings suggest that the hub genes we found in this study contribute to the development and progression of AIS and LUAD by altering the cellular senescence pathway. Thus, they may be promising markers for diagnosis and prognosis.

Role of cuproptosis in understanding diseases

Cell death is involved in a wide range of physiological and pathological processes. Recently, the term "cuproptosis" was coined to describe a novel type of cell death. This type of cell death, characterized by copper accumulation and proteotoxic stress, is a copper-dependent manner of death. Despite the progress achieved toward a better understanding of cuproptosis, mechanisms and related signaling pathways in physiology and pathology across various diseases remain to be proved. This mini review summarizes current research on cuproptosis and diseases, providing insights into prospective clinical therapies via targeting cuproptosis.

Comprehensive analysis of a cuproptosis-related ceRNA network implicates a potential endocrine therapy resistance mechanism in ER-positive breast cancer

BACKGROUND

While adjuvant endocrine therapy (ET) may decrease the mortality rate of estrogen receptor-positive (ER+) breast cancer (BC), the likelihood of relapse and metastasis due to ET resistance remains high. Cuproptosis is a recently discovered regulated cell death (RCD), whose role in tumors has yet to be elucidated. Thus, there is a need to study its specific regulatory mechanism in resistance to ET in BC, to identify novel therapeutic targets.

METHODS

The prognostic cuproptosis-related genes (CRGs) in ER+ BC were filtered by undergoing Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses in TCGA-BRCA, and a CRGs risk signature was constructed using the correlation coefficient. Immune infiltration analysis, immune function analysis, tumor microenvironment (TME) analysis, immune checkpoint analysis, immunotherapy response analysis, drug sensitivity analysis, and pathway activation analysis were carried out among the high- and low-risk groups in turn. The central CRG of cuproptosis in ER+ BC resistance to ET was acquired through the intersection of protein interaction network (PPI) analysis, genes differentially expressed (DEGs) between human BC cells LCC9 and MCF-7 (GSE159968), and CRGs with prognostic significance in TCGA-BRCA ER+ BC. The miRNAs upstream of the core CRGs were predicted based on the intersection of 4 databases, miRDB, RNA22, miRWalk, and RNAlnter. Candidate miRNAs consisted of the intersection of predicted miRNAs and miRNAs differentially expressed in the LCC9 and MCF-7 cell lines (GSE159979). Candidate lncRNAs were the intersection of the differential lncRNAs from the LCC9 and MCF-7 cell lines and the survival-related lncRNAs obtained from a univariate Cox regression analysis. Pearson's correlation analysis was performed between mRNA-miRNA, miRNA-lncRNA, and mRNA-lncRNA expression separately.

RESULTS

We constructed A risk signature of 4-CRGs to predict the prognosis of ER+ BC in TCGA-BRCA, a risk score = DLD*0.378 + DBT*0.201 + DLAT*0.380 + ATP7A*0.447 was used as the definition of the formula. There were significant differences between the high- and low-risk groups based on the risk score of 4-CRGs in aspects of immune infiltration, immune function, expression levels of immune checkpoint genes, and signaling pathways. DLD was determined to be the central CRG of cuproptosis in ER+ BC resistance to ET through the intersection of the PPI network analysis, DEGs between LCC9 and MCF-7 and 4-CRGs. Two miRNAs hsa-miR-370-3p and hsa-miR-432-5p were found taking DLD mRNA as a target, and the lncRNA C6orf99 has been hypothesized to be a competitive endogenous RNA that regulates DLD mRNA expression by sponging off hsa-miR-370-3p and hsa-miR-432-5p.

CONCLUSION

This study built a prognostic model based on genes related to cuproptosis in ER+ BC. We considered DLD to be the core gene associated with resistance to ET in ER+ BC via copper metabolism. The search for promising therapeutic targets led to the establishment of a cuproptosis-related ceRNA network C6orf99/hsa-miR-370-3p and hsa-miR-432-5p/DLD.

DNA methylation age in paired tumor and adjacent normal breast tissue in Chinese women with breast cancer

BACKGROUND

Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong.

METHODS

We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors.

RESULTS

DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA.

CONCLUSIONS

Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

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.

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.

Identification of a Novel Cuproptosis-Related Gene Signature and Integrative Analyses in Thyroid Cancer

Cuproptosis is a novel programmed cell death that depends on copper. The role and potential mechanism of cuproptosis-related genes (CRGs) in thyroid cancer (THCA) are still unclear. In our study, we randomly divided THCA patients from the TCGA database into a training set and a testing set. A cuproptosis-related signature consisting of six genes (SLC31A1, LIAS, DLD, MTF1, CDKN2A, and GCSH) was constructed using the training set to predict the prognosis of THCA and was verified with the testing set. All patients were classified into low- and high-risk groups according to risk score. Patients in the high-risk group had a poorer overall survival (OS) than those in the low-risk group. The area under the curve (AUC) values for 5 years, 8 years, and 10 years were 0.845, 0.885, and 0.898, respectively. The tumor immune cell infiltration and immune status were significantly higher in the low-risk group, which indicated a better response to immune checkpoint inhibitors (ICIs). The expression of six cuproptosis-related genes in our prognostic signature were verified by qRT-PCR in our THCA tissues, and the results were consistent with TCGA database. In summary, our cuproptosis-related risk signature has a good predictive ability regarding the prognosis of THCA patients. Targeting cuproptosis may be a better alternative for THCA patients.

Comprehensive Analysis of Prognosis and Immune Landscapes Based on Lipid-Metabolism- and Ferroptosis-Associated Signature in Uterine Corpus Endometrial Carcinoma

(1) Background: The effect of tumor immunotherapy is influenced by the immune microenvironment, and it is unclear how lipid metabolism and ferroptosis regulate the immune microenvironment of uterine corpus endometrial carcinoma (UCEC). (2) Methods: Genes associated with lipid metabolism and ferroptosis (LMRGs-FARs) were extracted from the MSigDB and FerrDb databases, respectively. Five hundred and forty-four UCEC samples were obtained from the TCGA database. The risk prognostic signature was constructed by consensus clustering, univariate cox, and LASSO analyses. The accuracy of the risk modes was assessed through receiver operating characteristic (ROC) curve, nomogram, calibration,, and C-index analyses. The relationship between the risk signature and immune microenvironment was detected by the ESTIMATE, EPIC, TIMER, xCELL, quan-TIseq, and TCIA databases. The function of a potential gene, PSAT1, was measured by in vitro experiments. (3) Results: A six-gene (CDKN1A, ESR1, PGR, CDKN2A, PSAT1, and RSAD2) risk signature based on MRGs-FARs was constructed and evaluated with high accuracy in UCEC. The signature was identified as an independent prognostic parameter and it divided the samples into high- and low-risk groups. The low-risk group was positively associated with good prognosis, high mutational status, upregulated immune infiltration status, high expression of CTLA4, GZMA and PDCD1, anti-PD-1 treatment sensitivity, and chemoresistance. (4) Conclusions: We constructed a risk prognostic model based on both lipid metabolism and ferroptosis and evaluated the relationship between the risk score and tumor immune microenvironment in UCEC. Our study has provided new ideas and potential targets for UCEC individualized diagnosis and immunotherapy.

Novel diagnostic biomarkers of T cell-mediated tumor killing characteristics for early-stage triple negative breast cancer: A SEER analysis and molecular portraits

The primary objective was to investigate the epidemiology, molecular characteristics, and clinical survival to identify potential transcriptome biomarkers to promote early diagnosis and screening of triple-negative breast cancer patients. Early-stage triple-negative breast cancer patients (E-TNBC) and late-stage triple-negative breast cancer patients (L-TNBC) were identified from the Surveillance, Epidemiology, and End Results database from 2010 to 2019. The difference in cancer specific survival (CSS) and overall survival (OS) between E-TNBC and L-TNBC was analyzed via a Kaplan-Meier plotter. 118 triple-negative breast cancer samples and 114 normal samples with the RNA sequencing expression data were selected from the cohort of TCGA breast cancer from UCSC Xena Database. The study involved 13,690 patients with L-TNBC and 44,994 patients with E-TNBC. L-TNBC patients were more frequently to be ≤ 60 years old (54.9% vs 52.2%), multiple primary site (44.0% vs 30.1%), and were more likely to receive radiotherapy (49.6% vs 47.4%) and chemotherapy (81.1% vs 72.1%), while L-TNBC patients were less likely to be white (68.7% vs 73.0%), married or with domestic partner (46.7% vs 54.7%), poorly differentiated grade (54.0% vs 61.9%), < 3 months from diagnosis to treatment (91.6% vs 96.4%), and were less likely to receive surgery (72.3% vs 95.4%). Stage-stratified survival analysis revealed that the prognosis of L-TNBC was worse when compared to E-TNBC, Kaplan-Meier analysis demonstrated that there were striking differences in OS and CSS between E-TNBC and L-TNBC. In the multivariable regression models, L-TNBC was the single highest risk factor, with a death risk that was 4.741 and 6.074 times higher than E-TNBC in terms of OS and CSS, respectively. The results also showed that treatment with surgery, radiation, or chemotherapy was effective for a better prognosis. Transcriptome analyses revealed that the top 5 upregulated genes in L-TNBC were, respectively, ISX, ALOX15B, MADCAM1, TP63, and ARG1 compared with E-TNBC. And the top 5 downregulated genes were, respectively, CTAG1B, CT45A1, MAGEC2, TFF2, and TNFRSF11B. The L-TNBC exhibited a lower rate of survival than E-TNBC, and the 2 groups differed in terms of transcriptome characteristics. To date, the diagnostic value of T cell-mediated tumor killing portraits on E-TNBC may not be completely recognized.

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.

Prognostic Significance of Cuproptosis-Related Gene Signatures in Breast Cancer Based on Transcriptomic Data Analysis

Breast cancer (BRCA) remains a serious threat to women's health, with the rapidly increasing morbidity and mortality being possibly due to a lack of a sophisticated classification system. To date, no reliable biomarker is available to predict prognosis. Cuproptosis has been recently identified as a new form of programmed cell death, characterized by the accumulation of copper in cells. However, little is known about the role of cuproptosis in breast cancer. In this study, a cuproptosis-related genes (CRGs) risk model was constructed, based on transcriptomic data with corresponding clinical information relating to breast cancer obtained from both the TCGA and GEO databases, to assess the prognosis of breast cancer by comprehensive bioinformatics analyses. The CRGs risk model was constructed and validated based on the expression of four genes (NLRP3, LIPT1, PDHA1 and DLST). BRCA patients were then divided into two subtypes according to the CRGs risk model. Furthermore, our analyses revealed that the application of this risk model was significantly associated with clinical outcome, immune infiltrates and tumor mutation burden (TMB) in breast cancer patients. Additionally, a new clinical nomogram model based on risk score was established and showed great performance in overall survival (OS) prediction, confirming the potential clinical significance of the CRGs risk model. Collectively, our findings revealed that the CRGs risk model can be a useful tool to stratify subtypes and that the cuproptosis-related signature plays an important role in predicting prognosis in BRCA patients.