Copy number variation in triple negative breast cancer samples associated with lymph node metastasis

A comprehensive molecular characterization of a claudin-low luminal B breast tumor

Breast cancer is the most common cause of death from cancer in women. Here, we present the case of a 43-year-old woman, who received a diagnosis of claudin-low luminal B breast cancer. The lesion revealed to be a poorly differentiated high-grade infiltrating ductal carcinoma, which was strongly estrogen receptor (ER)/progesterone receptor (PR) positive and human epidermal growth factor receptor (HER2) negative. Her tumor underwent in-depth chromosomal, mutational and gene expression analyses. We found a pathogenic protein truncating mutation in the TP53 gene, which is predicted to disrupt its transcriptional activity. The patient also harbors germline mutations in some mismatch repair (MMR) genes, and her tumor displays the presence of immune infiltrates, high tumor mutational burden (TMB) status and the apolipoprotein B mRNA editing enzyme catalytic polypeptide 3 (APOBEC3) associated signatures, which, overall, are predictive for the use of immunotherapy. Here, we propose promising prognostic indicators as well as potential therapeutic strategies based on the molecular characterization of the tumor.

Multi-Omics Insights into Disulfidptosis-Related Genes Reveal RPN1 as a Therapeutic Target for Liver Cancer

Disulfidptosis, a newly identified mode of programmed cell death, is yet to be comprehensively elucidated with respect to its multi-omics characteristics in tumors, specific pathogenic mechanisms, and antitumor functions in liver cancer. This study included 10,327 tumor and normal tissue samples from 33 cancer types. In-depth analyses using various bioinformatics tools revealed widespread dysregulation of disulfidptosis-related genes (DRGs) in pan-cancer and significant associations with prognosis, genetic variations, tumor stemness, methylation levels, and drug sensitivity. Univariate and multivariate Cox regression and LASSO regression were used to screen and construct prognosis-related hub DRGs and predictive models in the context of liver cancer. Subsequently, single cell analysis was conducted to investigate the subcellular localization of RPN1, a hub DRG, in various solid tumors. Western blotting was performed to validate the expression of RPN1 at both cellular and tissue levels. Additionally, functional experiments, including CCK8, EdU, clone, and transwell assays, indicated that RPN1 knockdown promoted the proliferative and invasive capacities of liver cancer cells. Therefore, this study elucidated the multi-omics characteristics of DRGs in pan-cancer and established a prognostic model for liver cancer. Additionally, this study revealed the molecular functions of RPN1 in liver cancer, suggesting its potential as a therapeutic target for this disease.

AMD1 promotes breast cancer aggressiveness via a spermidine-eIF5A hypusination-TCF4 axis

BACKGROUND

Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer due to its aggressive characteristics and lack of effective therapeutics. However, the mechanism underlying its aggressiveness remains largely unclear. S-adenosylmethionine decarboxylase proenzyme (AMD1) overexpression occurs specifically in BLBC. Here, we explored the potential molecular mechanisms and functions of AMD1 promoting the aggressiveness of BLBC.

METHODS

The potential effects of AMD1 on breast cancer cells were tested by western blotting, colony formation, cell proliferation assay, migration and invasion assay. The spermidine level was determined by high performance liquid chromatography. The methylation status of CpG sites within the AMD1 promoter was evaluated by bisulfite sequencing PCR. We elucidated the relationship between AMD1 and Sox10 by ChIP assays and quantitative real-time PCR. The effect of AMD1 expression on breast cancer cells was evaluated by in vitro and in vivo tumorigenesis model.

RESULTS

In this study, we showed that AMD1 expression was remarkably elevated in BLBC. AMD1 copy number amplification, hypomethylation of AMD1 promoter and transcription activity of Sox10 contributed to the overexpression of AMD1 in BLBC. AMD1 overexpression enhanced spermidine production, which enhanced eIF5A hypusination, activating translation of TCF4 with multiple conserved Pro-Pro motifs. Our studies showed that AMD1-mediated metabolic system of polyamine in BLBC cells promoted tumor cell proliferation and tumor growth. Clinically, elevated expression of AMD1 was correlated with high grade, metastasis and poor survival, indicating poor prognosis of breast cancer patients.

CONCLUSION

Our work reveals the critical association of AMD1-mediated spermidine-eIF5A hypusination-TCF4 axis with BLBC aggressiveness, indicating potential prognostic indicators and therapeutic targets for BLBC.

Genomic Alterations Affecting Competitive Endogenous RNAs (ceRNAs) and Regulatory Networks (ceRNETs) with Clinical Implications in Triple-Negative Breast Cancer (TNBC)

The concept of competitive endogenous RNA regulation has brought on a change in the way we think about transcriptional regulation by miRNA-mRNA interactions. Rather than the relatively simple idea of miRNAs negatively regulating mRNA transcripts, mRNAs and other non-coding RNAs can regulate miRNAs and, therefore, broad networks of gene products through competitive interactions. While this concept is not new, its significant roles in and implications on cancer have just recently come to light. The field is now ripe for the extrapolation of technologies with a substantial clinical impact on cancer. With the majority of the genome consisting of non-coding regions encoding regulatory RNAs, genomic alterations in cancer have considerable effects on these networks that have been previously unappreciated. Triple-negative breast cancer (TNBC) is characterized by high mutational burden, genomic instability and heterogeneity, making this aggressive breast cancer subtype particularly relevant to these changes. In the past few years, much has been learned about the roles of competitive endogenous RNA network regulation in tumorigenesis, disease progression and drug response in triple-negative breast cancer. In this review, we present a comprehensive view of the new knowledge and future perspectives on competitive endogenous RNA networks affected by genomic alterations in triple-negative breast cancer. An overview of the competitive endogenous RNA (ceRNA) hypothesis and its bearing on cellular function and disease is provided, followed by a thorough review of the literature surrounding key competitive endogenous RNAs in triple-negative breast cancer, the genomic alterations affecting them, key disease-relevant molecular and functional pathways regulated by them and the clinical implications and significance of their dysregulation. New knowledge of the roles of these regulatory mechanisms and the current acceleration of research in the field promises to generate insights into the diagnosis, classification and treatment of triple-negative breast cancer through the elucidation of new molecular mechanisms, therapeutic targets and biomarkers.

IMPA2 promotes basal-like breast cancer aggressiveness by a MYC-mediated positive feedback loop

Basal-like breast cancer (BLBC) is the most aggressive subtype with poor prognosis; however, the mechanisms underlying aggressiveness in BLBC remain poorly understood. In this study, we showed that in contrast to other subtypes, inositol monophosphatase 2 (IMPA2) was dramatically increased in BLBC. Mechanistically, IMPA2 expression was upregulated due to copy number amplification, hypomethylation of IMPA2 promoter and MYC-mediated transcriptional activation. IMPA2 promoted MI-PI cycle and IP3 production, and IP3 then elevated intracellular Ca2+ concentration, leading to efficient activation of NFAT1. In turn, NFAT1 up-regulated MYC expression, thereby fulfilling a positive feedback loop that enhanced aggressiveness of BLBC cells. Knockdown of IMPA2 expression caused the inhibition of tumorigenicity and metastasis of BLBC cells in vitro and in vivo. Clinically, high IMPA2 expression was strongly correlated with large tumor size, high grade, metastasis and poor survival, indicating poor prognosis in breast cancer patients. These findings suggest that IMPA2-mediated MI-PI cycle allows crosstalk between metabolic and oncogenic pathways to promote BLBC progression.

Multi-omics characteristics of tumor-associated macrophages in the tumor microenvironment of gastric cancer and their exploration of immunotherapy potential

The incidence and mortality rate of gastric cancer (GC) have remained high worldwide. Although some progress has been made in immunotargeted therapy, the treatment effect remains limited. With more attention has been paid to the immune potential of tumor-associated macrophages (TAMs), but the specific mechanisms of tumor immunity are still unclear. Thus, we screened marker genes in TAMs differentiation (MDMs) through single-cell RNA sequencing, and combined with GC transcriptome data from TCGA and GEO databases, the clinical and TME characteristics, prognostic differences, immune infiltration, and drug sensitivity among different subtypes of patients with GC in different data sets were analyzed. A prognostic model of GC was constructed to evaluate the prognosis and immunotherapy response of patients with GC. In this study, we extensively studied the mutations in MDMs such as CGN, S100A6, and C1QA, and found differences in the infiltration of immune cells and immune checkpoints including M2 TAMs, T cells, CD274, and CTLA4 in different GC subtypes. In the model, we constructed a predictive scoring system with high accuracy and screened out key MDMs-related genes associated with prognosis and M2 TAMs, among which VKORC1 may be involved in GC progression and iron death in tumor cells. Therefore, this study explores the therapeutic strategy of TAMs reprogramming in-depth, providing new ideas for the clinical diagnosis, treatment, and prognosis assessment of GC.

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BACKGROUND

Breast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.

METHODS

Tumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman's rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan-Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.

RESULTS

Herein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.

CONCLUSIONS

We conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

Imprinted small nucleolar RNAs: Missing link in development and disease?

The 14q32.2 (DLK1-DIO3) and 15q11-q13 (SNURF-SNRPN) imprinted gene loci harbor the largest known small nucleolar RNA clusters expressed from the respective maternal and paternal alleles. Recent studies have demonstrated significant roles for the 15q11-q13 located SNORD115-SNORD116 C/D box snoRNAs in Prader-Willi syndrome (PWS), a neurodevelopmental disorder. Even though the effect of SNORD116 deletion is apparent in the PWS phenotype, similar effects of a SNORD113-SNORD114 cluster deletion from the 14q32.2 locus in Kagami-Ogata syndrome (KOS14) and upregulation in Temple syndrome (TS14) remain to be explored. Moreover, apart from their probable involvement in neurodevelopmental disorders, snoRNAs from the SNORD113-SNORD114 cluster have been implicated in multiple biological processes, including pluripotency, development, cancers, and RNA modifications. Here we summarize the current understanding of the system to explore the possibility of a link between developmental disorders and C/D box snoRNA expression from the imprinted 14q32.2 locus. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development RNA Processing > Processing of Small RNAs.

Single-cell and genetic multi-omics analysis combined with experiments confirmed the signature and potential targets of cuproptosis in hepatocellular carcinoma

Background: Cuproptosis, as a recently discovered type of programmed cell death, occupies a very important role in hepatocellular carcinoma (HCC) and provides new methods for immunotherapy; however, the functions of cuproptosis in HCC are still unclear. Methods: We first analyzed the transcriptome data and clinical information of 526 HCC patients using multiple algorithms in R language and extensively described the copy number variation, prognostic and immune infiltration characteristics of cuproptosis related genes (CRGs). Then, the hub CRG related genes associated with prognosis through LASSO and Cox regression analyses and constructed a prognostic prediction model including multiple molecular markers and clinicopathological parameters through training cohorts, then this model was verified by test cohorts. On the basis of the model, the clinicopathological indicators, immune infiltration and tumor microenvironment characteristics of HCC patients were further explored via bioinformation analysis. Then, We further explored the key gene biological function by single-cell analysis, cell viability and transwell experiments. Meantime, we also explored the molecular docking of the hub genes. Results: We have screened 5 hub genes associated with HCC prognosis and constructed a prognosis prediction scoring model. And the model results showed that patients in the high-risk group had poor prognosis and the expression levels of multiple immune markers, including PD-L1, CD276 and CTLA4, were higher than those patients in the low-risk group. We found a significant correlation between risk score and M0 macrophages and memory CD4+ T cells. And the single-cell analysis and molecular experiments showed that BEX1 were higher expressed in HCC tissues and deletion inhibited the proliferation, invasion and migration and EMT pathway of HCC cells. Finally, it was observed that BEX1 could bind to sorafenib to form a stable conformation. Conclusion: The study not only revealed the multiomics characteristics of CRGs in HCC but also constructed a new high-accuracy prognostic prediction model. Meanwhile, BEX1 were also identified as hub genes that can mediate the cuproptosis of hepatocytes as potential therapeutic targets for HCC.

Establishment of a N1-methyladenosine-related risk signature for breast carcinoma by bioinformatics analysis and experimental validation

OBJECTIVES

Breast carcinoma (BRCA) has resulted in a huge health burden globally. N1-methyladenosine (m¹A) RNA methylation has been proven to play key roles in tumorigenesis. Nevertheless, the function of m¹A RNA methylation-related genes in BRCA is indistinct.

METHODS

The RNA sequencing (RNA-seq), copy-number variation (CNV), single-nucleotide variant (SNV), and clinical data of BRCA were acquired via The Cancer Genome Atlas (TCGA) database. In addition, the GSE20685 dataset, the external validation set, was acquired from the Gene Expression Omnibus (GEO) database. 10 m¹A RNA methylation regulators were obtained from the previous literature, and further analyzed through differential expression analysis by rank-sum test, mutation by SNV data, and mutual correlation by Pearson Correlation Analysis. Furthermore, the differentially expressed m¹A-related genes were selected through overlapping m¹A-related module genes obtained by weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) in BRCA and DEGs between high- and low- m¹A score subgroups. The m¹A-related model genes in the risk signature were derived by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. In addition, a nomogram was built through univariate and multivariate Cox analyses. After that, the immune infiltration between the high- and low-risk groups was investigated through ESTIMATE and CIBERSORT. Finally, the expression trends of model genes in clinical BRCA samples were further confirmed by quantitative real-time PCR (RT‒qPCR).

RESULTS

Eighty-five differentially expressed m¹A-related genes were obtained. Among them, six genes were selected as prognostic biomarkers to build the risk model. The validation results of the risk model showed that its prediction was reliable. In addition, Cox independent prognosis analysis revealed that age, risk score, and stage were independent prognostic factors for BRCA. Moreover, 13 types of immune cells were different between the high- and low-risk groups and the immune checkpoint molecules TIGIT, IDO1, LAG3, ICOS, PDCD1LG2, PDCD1, CD27, and CD274 were significantly different between the two risk groups. Ultimately, RT-qPCR results confirmed that the model genes MEOX1, COL17A1, FREM1, TNN, and SLIT3 were significantly up-regulated in BRCA tissues versus normal tissues.

CONCLUSIONS

An m¹A RNA methylation regulator-related prognostic model was constructed, and a nomogram based on the prognostic model was constructed to provide a theoretical reference for individual counseling and clinical preventive intervention in BRCA.

IRF4 as a novel target involved in malignant transformation of oral submucous fibrosis into oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) in the context of oral submucous fibrosis (OSF) has a high incidence owing to undefined pathogenesis. Identifying key genes and exploring the underlying molecular mechanisms involved in the conversion of OSF into OSCC are in urgent need. Differentially expressed genes (DEGs) between OSCC and OSF were dug from GEO databases and a total of 170 DEGs were acquired. Functional association of DEGs were analyzed by GO and KEGG. Protein-protein interactions (PPIs) analysis was carried out and candidate biomarkers were identified by Gene co-expression analysis and Cox analyses. Hub genes were confirmed by qRT-PCR in tissues and cell lines, of which we found that IRF4 mRNA was successively up-regulated from Normal to OSF and then to OSCC and associated with immune infiltrating levels. In addition, Immunohistochemical (IHC) and Immunofluorescence (IF) assays were conducted to validate the consistent upregulation of IRF4 and the oncogene role of IRF4 in OSF and OSCC at translation level. IRF4 may be indicative biomarker in transformation of OSF into OSCC. High IRF4 expression contribute to increased immune infiltration of OSCC and may provide a novel diagnostic marker for OSCC patients translated from OSF.

Changes of Mutations and Copy-Number and Enhanced Cell Migration during Breast Tumorigenesis

Although cancer stem cells (CSCs) play a major role in tumorigenesis and metastasis, the role of genetic alterations in invasiveness of CSCs is still unclear. Tumor microenvironment signals, such as extracellular matrix (ECM) composition, significantly influence cell behaviors. Unfortunately, these signals are often lost in in vitro cell culture. This study determines putative CSC populations, examines genetic changes during tumorigenesis of human breast epithelial stem cells, and investigates single-cell migration properties on ECM-mimetic platforms. Whole exome sequencing data indicate that tumorigenic cells have a higher somatic mutation burden than non-tumorigenic cells, and that mutations exclusive to tumorigenic cells exhibit higher predictive deleterious scores. Tumorigenic cells exhibit distinct somatic copy number variations (CNVs) including gain of duplications in chromosomes 5 and 8. ECM-mimetic topography selectively enhances migration speed of tumorigenic cells, but not of non-tumorigenic cells, and results in a wide distribution of tumorigenic single-cell migration speeds, suggesting heterogeneity in cellular sensing of contact guidance cues. This study identifies mutations and CNVs acquired during breast tumorigenesis, which can be associated with enhanced migration of breast tumorigenic cells, and demonstrates that a nanotopographically-defined platform can be applied to recapitulate an ECM structure for investigating cellular migration in the simulated tumor microenvironment.

An Overview of Circulating Cell-Free Nucleic Acids in Diagnosis and Prognosis of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer due to its molecular heterogeneity and poor clinical outcomes. Analysis of circulating cell-free tumor nucleic acids (ctNAs) can improve our understanding of TNBC and provide efficient and non-invasive clinical biomarkers that may be representative of tumor heterogeneity. In this review, we summarize the potential of ctNAs to aid TNBC diagnosis and prognosis. For example, tumor fraction of circulating cell-free DNA (TFx) may be useful for molecular prognosis of TNBC: high TFx levels after neoadjuvant chemotherapy have been associated with shorter progression-free survival and relapse-free survival. Mutations and copy number variations of TP53 and PIK3CA/AKT genes in plasma may be important markers of TNBC onset, progression, metastasis, and for clinical follow-up. In contrast, the expression profile of circulating cell-free tumor non-coding RNAs (ctncRNAs) can be predictive of molecular subtypes of breast cancer and thus aid in the identification of TBNC. Finally, dysregulation of some circulating cell-free tumor miRNAs (miR17, miR19a, miR19b, miR25, miR93, miR105, miR199a) may have a predictive value for chemotherapy resistance. In conclusion, a growing number of efforts are highlighting the potential of ctNAs for future clinical applications in the diagnosis, prognosis, and follow-up of TNBC.

Elevated transcription and glycosylation of B3GNT5 promotes breast cancer aggressiveness

Background

Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer because of its aggressive biological characteristics and no effective targeted agents. However, the mechanism underlying its aggressive behavior remain poorly understood. β1,3-N-acetylglucosaminyltransferase V (B3GNT5) overexpression occurs specifically in BLBC. Here, we studied the possible molecular mechanisms of B3GBT5 promoting the aggressiveness of BLBC.

Methods

The potential effects of B3GNT5 on breast cancer cells were tested by colony formation, mammosphere formation, cell proliferation assay, flow cytometry and Western blotting. The glycosylation patterns of B3GNT5 and associated functions were determined by Western blotting, quantitative real-time PCR and flow cytometry. The effect of B3GNT5 expression on BLBC was assessed by in vitro and in vivo tumorigenesis model.

Results

In this study, we showed that B3GNT5 copy number amplification and hypomethylation of B3GNT5 promoter contributed to the overexpression of B3GNT5 in BLBC. Knockout of B3GNT5 strongly reduced surface expression of SSEA-1 and impeded cancer stem cell (CSC)-like properties of BLBC cells. Our results also showed that B3GNT5 protein was heavily N-glycosylated, which is critical for its protein stabilization. Clinically, elevated expression of B3GNT5 was correlated with high grade, large tumor size and poor survival, indicating poor prognosis of breast cancer patients.

Conclusions

Our work uncovers the critical association of B3GNT5 overexpression and glycosylation with enhanced CSCs properties in BLBC. These findings suggest that B3GNT5 has the potential to become a prognostic marker and therapeutic target for BLBC.

Supplementary information

The online version contains supplementary material available at 10.1186/s13046-022-02375-5.

Prognostic Value of Copy Number Alteration Burden in Early-Stage Breast Cancer and the Construction of an 11-Gene Copy Number Alteration Model

The increasing burden of breast cancer has prompted a wide range of researchers to search for new prognostic markers. Considering that tumor mutation burden (TMB) is low and copy number alteration burden (CNAB) is high in breast cancer, we built a CNAB-based model using a public database and validated it with a Chinese population. We collected formalin-fixed, paraffin-embedded (FFPE) tissue samples from 31 breast cancer patients who were treated between 2010 and 2014 at the National Cancer Center (CICAMS). METABRIC and TCGA data were downloaded via cBioPortal. In total, 2295 patients with early-stage breast cancer were enrolled in the study, including 1427 in the METABRIC cohort, 837 in the TCGA cohort, and 31 in the CICAMS cohort. Based on the ROC curve, we consider 2.2 CNA/MBp as the threshold for the CNAB-high and CNAB-low groupings. In both the TCGA cohort and the CICAMS cohort, CNAB-high had a worse prognosis than CNAB-low. We further simplified this model by establishing a prognostic nomogram for early breast cancer patients by 11 core genes, and this nomogram was highly effective in both the TCGA cohort and the CICAMS cohort. We hope that this model will subsequently help clinicians with prognostic assessments.

Identification of pyroptosis related subtypes and tumor microenvironment infiltration characteristics in breast cancer

Understanding the association of pyroptosis with tumor progression, prognosis and effect on immunotherapeutic response in breast cancer (BC) is limited. This study analysed forty pyroptosis-related genes to construct the pyroptosis score. Association of the pyroptosis score with the overall survival, clinical features, tumor mutation load, immune cell infiltration, and treatment sensitivity of patients with BC was analysed. Out of 983 BC samples, 304 (30.93%) had genetic alterations with the highest TP53 frequency. We identified three separate subtypes associated with pyroptosis action. These subtypes correlate with the clinicopathological characteristics, TME immune cell infiltration, and disease prognosis. Based on the expression levels of the pyroptosis genes, we divided the pyroptosis score into a high group and a low group. The immune-activated pyroptosis subtype had a higher score with a better prognosis. We also observed that the pyroptosis score correlates with the tumor mutation burden. The pyroptosis score and disease prognosis were directly proportional. A higher pyroptosis score indicated a better prognosis. Results suggest that the pyroptosis-related gene prognosis model is closely related to the immune cell infiltration of BC. The three pyroptosis subtypes associated with BC assist in accurately identifying the tumor subtype, the prognosis of immunotherapy drugs and the patient’s therapeutic response.

Distribution of copy number variations and rearrangement endpoints in human cancers with a review of literature

Copy number variations (CNVs) which include deletions, duplications, inversions, translocations, and other forms of chromosomal re-arrangements are common to human cancers. In this report we investigated the pattern of these variations with the goal of understanding whether there exist specific cancer signatures. We used re-arrangement endpoint data deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC) for our analysis. Indeed, we find that human cancers are characterized by specific patterns of chromosome rearrangements endpoints which in turn result in cancer specific CNVs. A review of the literature reveals tissue specific mutations which either drive these CNVs or appear as a consequence of CNVs because they confer an advantage to the cancer cell. We also identify several rearrangement endpoints hotspots that were not previously reported. Our analysis suggests that in addition to local chromosomal architecture, CNVs are driven by the internal cellular or nuclear physiology of each cancer tissue.

Prognostic Value of Long Noncoding RNA DLEU2 and Its Relationship with Immune Infiltration in Kidney Renal Clear Cell Carcinoma and Liver Hepatocellular Carcinoma

Background

DLEU2 is a long noncoding RNA considered important in the progression of many cancers. However, correlations between DLEU2 and kidney renal clear cell carcinoma (KIRC) and liver hepatocellular carcinoma (LIHC) have rarely been reported.

Methods

We first analysed the expression of DLEU2 across cancers and the correlation between DLEU2 and the clinical features of KIRC and LIHC by using the “ggplot2” package in R and searched the Oncomine database and Timer website platform. We verified the expression of DLEU2 in the GEO dataset (GSE105261 and GSE45267). Receiver operating characteristic (ROC) curves were drawn using the “pROC” and “ggplot2” packages in R, and we constructed a DLEU2-based prognostic nomogram for KIRC and LIHC by using the “survival” and “rms” packages in R. Then, we analysed the correlation between DLEU2 expression and prognosis in R as well as the correlation between DLEU2 and immune cell infiltration in the TIMER database. Finally, we explored the causes of DLEU2 upregulation in the UCSC Xena and UALCAN databases.

Results

We found that DLEU2 was upregulated in many cancers, including KIRC and LIHC. Expression of DLEU2 is associated with tumour stage, grade, lymphatic metastasis, and distant metastasis in KIRC as well as alpha-fetoprotein (AFP), tumour stage, grade, lymphatic metastasis, and distant metastasis in LIHC. DLEU2 is an adverse factor for the prognosis of KIRC and LIHC. In addition, DLEU2 has moderate accuracy in diagnosing KIRC and LIHC and predicting their prognosis. Moreover, we found that expression of DLEU2 correlated positively with immune cell infiltration in KIRC and LIHC, and upregulation of DLEU2 in KIRC and LIHC suggests a poor prognosis based on immune cells analysis. Genetic and epigenetic analyses of DLEU2 indicate that copy number variations (CNVs) and methylation contribute to the upregulation of DLEU2.

Conclusion

The long noncoding RNA DLEU2 has the potential to predict the prognosis and immune infiltration of KIRC and LIHC.