Comprehensive Transcriptome Profiling Reveals Multigene Signatures in Triple-Negative Breast Cancer

Beyond the Usual Suspects: Examining the Role of Understudied Histone Variants in Breast Cancer

The incorporation of histone variants has structural ramifications on nucleosome dynamics and stability. Due to their unique sequences, histone variants can alter histone-histone or histone-DNA interactions, impacting the folding of DNA around the histone octamer and the overall higher-order structure of chromatin fibers. These structural modifications alter chromatin compaction and accessibility of DNA by transcription factors and other regulatory proteins to influence gene regulatory processes such as DNA damage and repair, as well as transcriptional activation or repression. Histone variants can also generate a unique interactome composed of histone chaperones and chromatin remodeling complexes. Any of these perturbations can contribute to cellular plasticity and the progression of human diseases. Here, we focus on a frequently overlooked group of histone variants lying within the four human histone gene clusters and their contribution to breast cancer.

Multi-omics analysis of disulfidptosis regulators and therapeutic potential reveals glycogen synthase 1 as a disulfidptosis triggering target for triple-negative breast cancer

Disruption of disulfide homeostasis during biological processes can have fatal consequences. Excess disulfides induce cell death in a novel manner, termed as "disulfidptosis." However, the specific mechanism of disulfidptosis has not yet been elucidated. To determine the cancer types sensitive to disulfidptosis and outline the corresponding treatment strategies, we firstly investigated the crucial functions of disulfidptosis regulators pan-cancer at multi-omics levels. We found that different tumor types expressed dysregulated levels of disulfidptosis regulators, most of which had an impact on tumor prognosis. Moreover, we calculated the disulfidptosis activity score in tumors and validated it using multiple independent datasets. Additionally, we found that disulfidptosis activity was correlated with classic biological processes and pathways in various cancers. Disulfidptosis activity was also associated with tumor immune characteristics and could predict immunotherapy outcomes. Notably, the disulfidptosis regulator, glycogen synthase 1 (GYS1), was identified as a promising target for triple-negative breast cancer and validated via in vitro and in vivo experiments. In conclusion, our study elucidated the complex molecular phenotypes and clinicopathological correlations of disulfidptosis regulators in tumors, laying a solid foundation for the development of disulfidptosis-targeting strategies for cancer treatment.

A Comparison of In Vitro Studies between Cobalt(III) and Copper(II) Complexes with Thiosemicarbazone Ligands to Treat Triple Negative Breast Cancer

Metal complexes have gained significant attention as potential anti-cancer agents. The anti-cancer activity of [Co(phen)2(MeATSC)](NO3)3•1.5H2O•C2H5OH 1 (where phen = 1,10-phenanthroline and MeATSC = 9-anthraldehyde-N(4)-methylthiosemicarbazone) and [Cu(acetylethTSC)Cl]Cl•0.25C2H5OH 2 (where acetylethTSC = (E)-N-ethyl-2-[1-(thiazol-2-yl)ethylidene]hydrazinecarbothioamide) was investigated by analyzing DNA cleavage activity. The cytotoxic effect was analyzed using CCK-8 viability assay. The activities of caspase 3/7, 9, and 1, reactive oxygen species (ROS) production, cell cycle arrest, and mitochondrial function were further analyzed to study the cell death mechanisms. Complex 2 induced a significant increase in nicked DNA. The IC50 values of complex 1 were 17.59 μM and 61.26 μM in cancer and non-cancer cells, respectively. The IC50 values of complex 2 were 5.63 and 12.19 μM for cancer and non-cancer cells, respectively. Complex 1 induced an increase in ROS levels, mitochondrial dysfunction, and activated caspases 3/7, 9, and 1, which indicated the induction of intrinsic apoptotic pathway and pyroptosis. Complex 2 induced cell cycle arrest in the S phase, ROS generation, and caspase 3/7 activation. Thus, complex 1 induced cell death in the breast cancer cell line via activation of oxidative stress which induced apoptosis and pyroptosis while complex 2 induced cell cycle arrest through the induction of DNA cleavage.

ELOVL2-AS1 suppresses tamoxifen resistance by sponging miR-1233-3p in breast cancer

Tamoxifen (Tam) has long been a top treatment option for breast cancer patients, but the challenge of eliminating cancer recurrence remains. Here, we identify a signalling pathway involving ELOVL2, ELOVL2-AS1, and miR-1233-3p, which contributes to drug resistance in Tam-resistant (TamR) breast cancer. ELOVL2-AS1, a long noncoding RNA, was significantly upregulated by its antisense gene, ELOVL2, which is known to be downregulated in TamR cells. Additionally, ELOVL2-AS1 underwent the most hypermethylation in MCF-7/TamR cells. Furthermore, patients with breast cancer who developed TamR during chemotherapy had significantly lower expression of ELOVL2-AS1 compared to those who responded to Tam. Ectopic downregulation of ELOVL2-AS1 by siRNA both stimulated cancer cell growth and deteriorated TamR. We also found that ELOVL2-AS1 sponges miR-1233-3p, which has pro-proliferative activity and elevates TamR, leading to the activation of potential target genes, such as MYEF2, NDST1, and PIK3R1. These findings suggest that ELOVL2-AS1, in association with ELOVL2, may contribute to the suppression of drug resistance by sponging miR-1233-3p in breast cancer.

Identification of DDIT4 as a potential prognostic marker associated with chemotherapeutic and immunotherapeutic response in triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. It has been reported that the overexpression of DNA damage-inducible transcript 4 gene (DDIT4) is associated with resistance to neoadjuvant chemotherapy and poor prognosis in patients with TNBC. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases.

METHODS

RNA sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Sequencing data were further analyzed by the R package "edgeR" and "clusterProfiler" to identify the profile of differentially expressed genes (DEGs) and annotate gene functions. The prognostic and predictive value of DDIT4 expression in patients with TNBC was further validated by published online data resources, including TIMER, UALCAN, Kaplan-Meier plotter, and LinkedOmics, and GeneMANIA and GSCALite were used to investigate the functional networks and hub genes related to DDIT4, respectively.

RESULTS

Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues and found that patients with DDIT4 overexpression showed poor survival outcomes. Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression, but correlated positively with immune checkpoint molecules. Furthermore, DDIT4 and its hub genes (ADM, ENO1, PLOD1, and CEBPB) involved in the activation of apoptosis, cell cycle, and EMT pathways. Eventually, we found ADM, ENO1, PLOD1, and CEBPB showed poor overall survival in BC patients.

CONCLUSION

In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential molecular targets and improve therapeutic strategies against TNBC.

Hypoxia-induced loss of SRSF2-dependent DNA methylation promotes CTCF-mediated alternative splicing of VEGFA in breast cancer

Alternative splicing of vascular endothelial growth factor A (VEGFA) generates numerous isoforms with unique roles in tumor angiogenesis, and investigating the underlying mechanism during hypoxia necessitates diligent pursuance. Our research systematically demonstrated that the splicing factor SRSF2 causes the inclusion of exon-8b, leading to the formation of the anti-angiogenic VEGFA-165b isoform under normoxic conditions. Additionally, SRSF2 interacts with DNMT3A and maintains methylation on exon-8a, inhibiting CCCTC-binding factor (CTCF) recruitment and RNA polymerase II (pol II) occupancy, causing exon-8a exclusion and decreased expression of pro-angiogenic VEGFA-165a. Conversely, SRSF2 is downregulated by HIF1α-induced miR-222-3p under hypoxic conditions, which prevents exon-8b inclusion and reduces VEGFA-165b expression. Furthermore, reduced SRSF2 under hypoxia promotes hydroxymethylation on exon-8a, increasing CTCF recruitment, pol II occupancy, exon-8a inclusion, and VEGFA-165a expression. Overall, our findings unveil a specialized dual mechanism of VEGFA-165 alternative splicing, instrumented by the cross-talk between SRSF2 and CTCF, which promotes angiogenesis under hypoxic conditions.

A novel PD-1/PD-L1 pathway molecular typing-related signature for predicting prognosis and the tumor microenvironment in breast cancer

BACKGROUND

Currently, the development of breast cancer immunotherapy based on the PD-1/PD-L1 pathway is relatively slow, and the specific mechanism affecting the immunotherapy efficacy in breast cancer is still unclear.

METHODS

Weighted correlation network analysis (WGCNA) and the negative matrix factorization (NMF) were used to distinguish subtypes related to the PD-1/PD-L1 pathway in breast cancer. Then univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were used to construct the prognostic signature. A nomogram was established based on the signature. The relationship between the signature gene IFNG and breast cancer tumor microenvironment was analyzed.

RESULTS

Four PD-1/PD-L1 pathway-related subtypes were distinguished. A prognostic signature related to PD-1/PD-L1 pathway typing was constructed to evaluate breast cancer's clinical characteristics and tumor microenvironment. The nomogram based on the RiskScore could be used to accurately predict breast cancer patients' 1-year, 3-year, and 5-year survival probability. The expression of IFNG was positively correlated with CD8+ T cell infiltration in the breast cancer tumor microenvironment.

CONCLUSION

A prognostic signature is constructed based on the PD-1/PD-L1 pathway typing in breast cancer, which can guide the precise treatment of breast cancer. The signature gene IFNG is positively related to CD8+ T cell infiltration in breast cancer.

Yin Yang 1 promotes aggressive cell growth in high-grade breast cancer by directly transactivating kinectin 1

Invasive cancer growth and metastasis account for the poor prognosis of high-grade breast cancer. Recently, we reported that kinectin 1 (KTN1), a member of the kinesin-binding protein family, promotes cell invasion of triple-negative breast cancer and high-grade breast cancer cells by augmenting the NF-κB signaling pathway. However, the upstream mechanism regulating KTN1 is unknown. Therefore, this functional study was performed to decipher the regulatory cohort of KTN1 in high-grade breast cancer. Bioinformatic analysis indicated that transcription factor Yin Yang 1 (YY1) was a potential transactivator of KTN1. High YY1 expression correlated positively with pathological progression and poor prognosis of high-grade breast cancer. Additionally, YY1 promoted cell invasive growth both in vitro and in vivo, in a KTN1-dependent manner. Mechanistically, YY1 could transactivate the KTN1 gene promoter. Alternatively, YY1 could directly interact with a co-factor, DEAD-box helicase 3 X-linked (DDX3X), which significantly co-activated YY1-mediated transcriptional expression of KTN1. Moreover, DDX3X augmented YY1-KTN1 signaling-promoted invasive cell growth of breast cancer. Importantly, overexpression of YY1 enhanced tumor aggressive growth in a mouse breast cancer model. Our findings established a novel DDX3X-assisted YY1-KTN1 regulatory axis in breast cancer progression, which could lead to the development novel therapeutic targets for breast cancer.

Predictive and Prognostic Value of Non-Coding RNA in Breast Cancer

For decades since the central dogma, cancer biology research has been focusing on the involvement of genes encoding proteins. It has been not until more recent times that a new molecular class has been discovered, named non-coding RNA (ncRNA), which has been shown to play crucial roles in shaping the activity of cells. An extraordinary number of studies has shown that ncRNAs represent an extensive and prevalent group of RNAs, including both oncogenic or tumor suppressive molecules. Henceforth, various clinical trials involving ncRNAs as extraordinary biomarkers or therapies have started to emerge. In this review, we will focus on the prognostic and diagnostic role of ncRNAs for breast cancer.

Comprehensive Analysis of Metabolic Isozyme Targets in Cancer

Metabolic reprogramming is a hallmark of malignant transformation, and loss of isozyme diversity (LID) contributes to this process. Isozymes are distinct proteins that catalyze the same enzymatic reaction but can have different kinetic characteristics, subcellular localization, and tissue specificity. Cancer-dominant isozymes that catalyze rate-limiting reactions in critical metabolic processes represent potential therapeutic targets. Here, we examined the isozyme expression patterns of 1,319 enzymatic reactions in 14 cancer types and their matching normal tissues using The Cancer Genome Atlas mRNA expression data to identify isozymes that become cancer-dominant. Of the reactions analyzed, 357 demonstrated LID in at least one cancer type. Assessment of the expression patterns in over 600 cell lines in the Cancer Cell Line Encyclopedia showed that these reactions reflect cellular changes instead of differences in tissue composition; 50% of the LID-affected isozymes showed cancer-dominant expression in the corresponding cell lines. The functional importance of the cancer-dominant isozymes was assessed in genome-wide CRISPR and RNAi loss-of-function screens: 17% were critical for cell proliferation, indicating their potential as therapeutic targets. Lists of prioritized novel metabolic targets were developed for 14 cancer types; the most broadly shared and functionally validated target was acetyl-CoA carboxylase 1 (ACC1). Small molecule inhibition of ACC reduced breast cancer viability in vitro and suppressed tumor growth in cell line- and patient-derived xenografts in vivo. Evaluation of the effects of drug treatment revealed significant metabolic and transcriptional perturbations. Overall, this systematic analysis of isozyme expression patterns elucidates an important aspect of cancer metabolic plasticity and reveals putative metabolic vulnerabilities.

SIGNIFICANCE

This study exploits the loss of metabolic isozyme diversity common in cancer and reveals a rich pool of potential therapeutic targets that will allow the repurposing of existing inhibitors for anticancer therapy. See related commentary by Kehinde and Parker, p. 1695.

The Transcriptomic Portrait of Locally Advanced Breast Cancer and Its Prognostic Value in a Multi-Country Cohort of Latin American Patients

Purposes

Most molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches.

Patients and Methods

We collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival (DFS) stages, was compared. Pathway analyses (GSEA, GSVA and MetaCore) were performed to explore differences among intrinsic subtypes.

Results

PAM50 classification of the MPBCS cohort defined 42·6% of tumors as LumA, 21·3% as LumB, 13·3% as HER2E and 16·6% as Basal. Both OSC and DFS for LumA tumors were significantly better than for other subtypes, while Basal tumors had the worst prognosis. While the prognostic power of traditional subtypes calculated with hormone receptors (HR), HER2 and Ki67 determinations showed an acceptable performance, PAM50-derived risk of recurrence best discriminated low, intermediate and high-risk groups. Transcriptomic pathway analysis showed high proliferation (i.e. cell cycle control and DNA damage repair) associated with LumB, HER2E and Basal tumors, and a strong dependency on the estrogen pathway for LumA. Terms related to both innate and adaptive immune responses were seen predominantly upregulated in Basal tumors, and, to a lesser extent, in HER2E, with respect to LumA and B tumors.

Conclusions

This is the first study that assesses molecular features at the transcriptomic level in a multicountry Latin American breast cancer patient cohort. Hormone-related and proliferation pathways that predominate in PAM50 and other breast cancer molecular classifications are also the main tumor-driving mechanisms in this cohort and have prognostic power. The immune-related features seen in the most aggressive subtypes may pave the way for therapeutic approaches not yet disseminated in Latin America.

Clinical Trial Registration

ClinicalTrials.gov (Identifier: NCT02326857).

The early-stage triple-negative breast cancer landscape derives a novel prognostic signature and therapeutic target

PURPOSE

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Patients with early-stage TNBCs have distinct likelihood of distant recurrence. This study aimed to develop a prognostic signature of early-stage TNBC patients to improve risk stratification.

METHODS

Using RNA-sequencing data, we analyzed 189 pathologically confirmed pT1-2N0M0 TNBC patients and identified 21 mRNAs that were highly expressed in tumor and related to relapse-free survival. All-subset regression program was used for constructing a 7-mRNA signature in the training set (n = 159); the accuracy and prognostic value were then validated using an independent validation set (n = 158).

RESULTS

Here, we profiled the transcriptome data from 189 early-stage TNBC patients along with 50 paired normal tissues. Early-stage TNBCs mainly consisted of basal-like immune-suppressed subtype and had higher homologous recombination deficiency scores. We developed a prognostic signature including seven mRNAs (ACAN, KRT5, TMEM101, LCA5, RPP40, LAGE3, CDKL2). In both the training (n = 159) and validation set (n = 158), this signature could identify patients with relatively high recurrence risks and served as an independent prognostic factor. Time-dependent receiver operating curve showed that the signature had better prognostic value than traditional clinicopathological features in both sets. Functionally, we showed that TMEM101 promoted cell proliferation and migration in vitro, which represented a potential therapeutic target.

CONCLUSIONS

Our 7-mRNA signature could accurately predict recurrence risks of early-stage TNBCs. This model may facilitate personalized therapy decision-making for early-stage TNBCs individuals.

Recent advances of transcriptomics and proteomics in triple-negative breast cancer prognosis assessment

Triple-negative breast cancer (TNBC), a heterogeneous tumour that lacks the expression of oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), is often characterized by aggressiveness and tends to recur or metastasize. TNBC lacks therapeutic targets compared with other subtypes and is not sensitive to endocrine therapy or targeted therapy except chemotherapy. Therefore, identifying the prognostic characteristics and valid therapeutic targets of TNBC could facilitate early personalized treatment. Due to the rapid development of various technologies, researchers are increasingly focusing on integrating 'big data' and biological systems, which is referred to as 'omics', as a means of resolving it. Transcriptomics and proteomics analyses play an essential role in exploring prospective biomarkers and potential therapeutic targets for triple-negative breast cancers, which provides a powerful engine for TNBC's therapeutic discovery when combined with complementary information. Here, we review the recent progress of TNBC research in transcriptomics and proteomics to identify possible therapeutic goals and improve the survival of patients with triple-negative breast cancer. Also, researchers may benefit from this article to catalyse further analysis and investigation to decipher the global picture of TNBC cancer.

CDK5RAP3, a New BRCA2 Partner That Regulates DNA Repair, Is Associated with Breast Cancer Survival

BRCA2 is essential for homologous recombination DNA repair. BRCA2 mutations lead to genome instability and increased risk of breast and ovarian cancer. Similarly, mutations in BRCA2-interacting proteins are also known to modulate sensitivity to DNA damage agents and are established cancer risk factors. Here we identify the tumor suppressor CDK5RAP3 as a novel BRCA2 helical domain-interacting protein. CDK5RAP3 depletion induced DNA damage resistance, homologous recombination and single-strand annealing upregulation, and reduced spontaneous and DNA damage-induced genomic instability, suggesting that CDK5RAP3 negatively regulates double-strand break repair in the S-phase. Consistent with this cellular phenotype, analysis of transcriptomic data revealed an association between low CDK5RAP3 tumor expression and poor survival of breast cancer patients. Finally, we identified common genetic variations in the CDK5RAP3 locus as potentially associated with breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Our results uncover CDK5RAP3 as a critical player in DNA repair and breast cancer outcomes.

MiRNA-142-3P and FUS can be Sponged by Long Noncoding RNA DUBR to Promote Cell Proliferation in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) represents a frequently occurring adulthood acute leukemia (AL). Great progresses have been achieved in the treatment of AML, but its pathogenic mechanism remains unclear. This study reported the biological functions of lncRNA DUBR in AML pathogenic mechanism. As a result, lncRNA DUBR showed high expression level within AML, resulting in poor prognosis, especially in M4 AML. In vitro studies elucidated that knockdown of DUBR with small interfering RNA (siRNA) resulted in the suppression of survival and colony formation ability, as well as induction of apoptosis, in AML cells. RNA pull-down assay and computational revealed that DUBR could sponge with miRNA-142-3P and interact with FUS protein. MiRNA-142-3P have a negative correlation with DUBR and overexpression of miRNA-142-3P inhibited cell growth in AML. Meanwhile, DUBR promoted the expression of FUS protein, targeting inhibition of FUS significantly promoted cell apoptosis in AML cell lines. In conclusion, these results revealed new mechanism of lncRNA DUBR in AML malignant behavior, and suggested that the manipulation of DUBR expression could serve as a potential strategy in AML therapy.

Prognostic value of gamma-interferon-inducible lysosomal thiol reductase expression in female patients diagnosed with breast cancer

Because of the high heterogeneity of breast cancer outcome, identification of novel prognostic biomarkers is critical to improve patient stratification and guide precise treatment. We examined the prognostic value of gamma-interferon-inducible lysosomal thiol reductase (GILT) expression in a training set of 416 breast cancer patients and a validation set of 210 patients, and performed functional studies to investigate the functions and underlying mechanisms of GILT on breast cancer prognosis. Our results indicated that high GILT expression in breast cancer cells was associated with improved disease-free survival (DFS; hazard ratio [HR] = 0.189, 95% confidence interval [CI]: 0.099-0.361) and breast cancer-specific survival (BCSS; HR = 0.187, 95% CI: 0.080-0.437) of breast cancer patients both in the training set and the external validation set (HR = 0.453, 95% CI: 0.235-0.873 for DFS, HR = 0.488, 95% CI: 0.245-0.970 for BCSS). In vitro and in vivo studies showed that GILT overexpression inhibited breast cancer cells proliferation, invasion, migration and tumor formation in nude mice and increased sensitivity of breast cancer cells to standard treatment. Proteomics analysis indicated that GILT inhibited reactive oxygen species (ROS) and autophagy activation in breast cancer cells, and GILT overexpression-mediated tumor growth was further enhanced in the presence of autophagy or ROS inhibitors. Our results demonstrate that GILT expression can be effectively used to predict the prognosis and guide treatment strategies of breast cancer patients.

A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer

Background

The prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment.

Methods

We analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model.

Results

A clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size.

Conclusions

The proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.

A Machine Learning Model to Predict the Triple Negative Breast Cancer Immune Subtype

Background

Immune checkpoint blockade (ICB) has been approved for the treatment of triple-negative breast cancer (TNBC), since it significantly improved the progression-free survival (PFS). However, only about 10% of TNBC patients could achieve the complete response (CR) to ICB because of the low response rate and potential adverse reactions to ICB.

Methods

Open datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were downloaded to perform an unsupervised clustering analysis to identify the immune subtype according to the expression profiles. The prognosis, enriched pathways, and the ICB indicators were compared between immune subtypes. Afterward, samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate the correlation of immune subtype with prognosis. Data from patients who received ICB were selected to validate the correlation of the immune subtype with ICB response. Machine learning models were used to build a visual web server to predict the immune subtype of TNBC patients requiring ICB.

Results

A total of eight open datasets including 931 TNBC samples were used for the unsupervised clustering. Two novel immune subtypes (referred to as S1 and S2) were identified among TNBC patients. Compared with S2, S1 was associated with higher immune scores, higher levels of immune cells, and a better prognosis for immunotherapy. In the validation dataset, subtype 1 samples had a better prognosis than sub type 2 samples, no matter in overall survival (OS) (p = 0.00036) or relapse-free survival (RFS) (p = 0.0022). Bioinformatics analysis identified 11 hub genes (LCK, IL2RG, CD3G, STAT1, CD247, IL2RB, CD3D, IRF1, OAS2, IRF4, and IFNG) related to the immune subtype. A robust machine learning model based on random forest algorithm was established by 11 hub genes, and it performed reasonably well with area Under the Curve of the receiver operating characteristic (AUC) values = 0.76. An open and free web server based on the random forest model, named as triple-negative breast cancer immune subtype (TNBCIS), was developed and is available from https://immunotypes.shinyapps.io/TNBCIS/.

Conclusion

TNBC open datasets allowed us to stratify samples into distinct immunotherapy response subgroups according to gene expression profiles. Based on two novel subtypes, candidates for ICB with a higher response rate and better prognosis could be selected by using the free visual online web server that we designed.

A ten N6-methyladenosine-related long non-coding RNAs signature predicts prognosis of triple-negative breast cancer

Background

Patients with triple‐negative breast cancer (TNBC) face a major challenge of the poor prognosis, and N6‐methyladenosine‐(m6A) mediated regulation in cancer has been proposed. Therefore, this study aimed to explore the prognostic roles of m6A‐related long non‐coding RNAs (LncRNAs) in TNBC.

Methods

Clinical information and expression data of TNBC samples were collected from TCGA and GEO databases. Pearson correlation, univariate, and multivariate Cox regression analysis were employed to identify independent prognostic m6A‐related LncRNAs to construct the prognostic score (PS) risk model. Receiver operating characteristic (ROC) curve was used to evaluate the performance of PS risk model. A competing endogenous RNA (ceRNA) network was established for the functional analysis on targeted mRNAs.

Results

We identified 10 independent prognostic m6A‐related LncRNAs (SAMD12‐AS1, BVES‐AS1, LINC00593, MIR205HG, LINC00571, ANKRD10‐IT1, CIRBP‐AS1, SUCLG2‐AS1, BLACAT1, and HOXB‐AS1) and established a PS risk model accordingly. Relevant results suggested that TNBC patients with lower PS had better overall survival status, and ROC curves proved that the PS model had better prognostic abilities with the AUC of 0.997 and 0.864 in TCGA and GSE76250 datasets, respectively. Recurrence and PS model status were defined as independent prognostic factors of TNBC. These ten LncRNAs were all differentially expressed in high‐risk TNBC compared with controls. The ceRNA network revealed the regulatory axes for nine key LncRNAs, and mRNAs in the network were identified to function in pathways of cell communication, signaling transduction and cancer.

Conclusion

Our findings proposed a ten‐m6A‐related LncRNAs as potential biomarkers to predict the prognostic risk of TNBC.

An Immune Model to Predict Prognosis of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy Based on Support Vector Machine

Tumor microenvironment has been increasingly proved to be crucial during the development of breast cancer. The theory about the conversion of cold and hot tumor attracted the attention to the influences of traditional therapeutic strategies on immune system. Various genetic models have been constructed, although the relation between immune system and local microenvironment still remains unclear. In this study, we tested and collected the immune index of 262 breast cancer patients before and after neoadjuvant chemotherapy. Five indexes were selected and analyzed to form the prediction model, including the ratio values between after and before neoadjuvant chemotherapy of CD4⁺/CD8⁺ T cell ratio; lymphosum of T, B, and natural killer (NK) cells; CD3⁺CD8⁺ cytotoxic T cell percent; CD16⁺CD56⁺ NK cell absolute value; and CD3⁺CD4⁺ helper T cell percent. Interestingly, these characters are both the ratio value of immune status after neoadjuvant chemotherapy to the baseline. Then the prediction model was constructed by support vector machine (accuracy rate = 75.71%, area under curve = 0.793). Beyond the prognostic effect and prediction significance, the study instead emphasized the importance of immune status in traditional systemic therapies. The result provided new evidence that the dynamic change of immune status during neoadjuvant chemotherapy should be paid more attention.

Developing Tumor Radiosensitivity Signatures Using LncRNAs

Long non-coding RNAs (lncRNAs) are involved in diverse biological processes, including DNA damage repair, and are of interest as potential biomarkers of radiosensitivity. We investigated whether lncRNA radiosensitivity signatures could be derived for use in cancer patients treated with radiotherapy. Signature development involved radiosensitivity measurements for cell lines and primary tumor samples, and patient outcome after radiotherapy. A 10-lncRNA signature trained on radiosensitivity measurements in bladder cell lines showed a trend towards independent validation. In multivariable analyses, patients with tumors classified as radioresistant by the lncRNA signature had poorer local relapse-free survival (P = 0.065) in 151 patients with muscle-invasive bladder cancer who underwent radiotherapy. An mRNA-based radiosensitivity index signature performed similarly to the lncRNA bladder signature for local relapse-free survival (P = 0.055). Pathway analysis showed the lncRNA signature associated with molecular processes involved in radiation responses. Knockdown of one of the lncRNAs in the signature showed a modest increase in radiosensitivity in one cell line. An alternative approach involved training on primary cervical tumor radiosensitivity or local control after radiotherapy. Both approaches failed to generate a cervix lncRNA radiosensitivity signature, which was attributed to the age of samples in our cohorts. Our work highlights challenges in validating lncRNA signatures as biomarkers in archival tissue from radiotherapy cohorts, but supports continued investigation of lncRNAs for a role in radiosensitivity.

LINC00470 accelerates the proliferation and metastasis of melanoma through promoting APEX1 expression

Recently studies found that APEX1 was abnormally expressed in melanoma, indicating that it might be involved in the development of melanoma. However, the underlying mechanism and the interaction between APEX1 and LINC00470 in melanoma are not clear. Therefore, we aimed to investigate the role of LINC00470 in the development of melanoma in this work. We discovered that LINC00470 was overexpressed in melanoma tissues and cells compared with the adjacent normal tissues and cells by qPCR. The overexpression of LINC00470 promoted the proliferation and migration of melanoma cells. The functional investigation demonstrated that LINC00470 activated the transcription factor, ZNF131, to regulate the APEX1 expression, which finally promoted cell proliferation and migration. In contrast, knockdown of LINC00470 could significantly inhibit the melanoma cell proliferation and migration, and suppress the growth of tumor in vivo. Overexpression of APEX1 could reverse the impact of the silence of LINC00470 in melanoma cells. In summary, our studies revealed that LINC00470 promoted melanoma proliferation and migration by enhancing the expression of APEX1, which indicated that LINC00470 might be a therapeutic target for the treatment of melanoma.

Vitamin D and Non-coding RNAs: New Insights into the Regulation of Breast Cancer

Breast cancer, a life-threatening serious disease with a high incident rate among women, is responsible for thousands of cancer-associated death worldwide. Numerous investigations have evaluated the possible mechanisms related to this malignancy. Among them, non-coding RNAs (ncRNAs), i.e., microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs have recently attracted attention of researchers. In addition to recent studies for evaluating the role of ncRNAs in breast cancer etiology, some investigations have revealed that vitamin D has regulatory and therapeutic roles in breast cancer. Moreover, an important link between vitamin D and ncRNAs in cancer therapy has been highlighted. Herein, the aim of this study was to discuss the available data on the mentioned link in breast cancer.

Molecular Mechanisms of Oncogenesis through the Lens of Nucleosomes and Histones

At the cellular level, cancer is the disease of both the genome and the epigenome, and the interplay between genetic mutations and epigenetic states may occur at the level of elementary chromatin units, the nucleosomes. They are formed by a segment of DNA wrapped around an octamer of histone proteins. In this review, we survey various mechanisms of cancer etiology and progression mediated by histones and nucleosomes. In particular, we discuss the effects of mutations in histones, changes in their expression and slicing on epigenetic dysregulation and carcinogenesis. The links between cancer phenotypes and differential expression of histone variants and isoforms are summarized. Finally, we discourse the geometric and steric effects of DNA compaction in nucleosomes on DNA mutation rate, interactions with transcription factors, including pioneer transcription factors, and prospects of cancer cells' genome and epigenome editing.

The long non-coding RNA landscape in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a type of breast cancer that has a higher risk of distant recurrence and metastasis, leading to a relatively aggressive biological behaviour and poor outcome. So far, the clinical management of TNBC is challenging because of its heterogeneity and paucity of specific targeted therapy. Recently, various studies have identified a lot of differently expressed long non-coding RNAs (lncRNAs) in TNBC. Those lncRNAs have been reported to play important roles in the multistep process of TNBC tumorigenesis. Here, we review the biological characteristics of lncRNAs, and present the current state of knowledge concerning the expression, function and regulation of lncRNAs in TNBC. Accumulating studies explored the potential lncRNAs-based therapeutics in TNBC, including the techniques of genetic modification using antisense oligonucleotides, locked nucleic acid and RNA nanotechnology. In current review, we also discuss the future prospects of studies about lncRNAs in TNBC and development of lncRNA-based strategies for clinical TNBC patients.

Up-regulation of L Antigen Family Member 3 Associates With Aggressive Progression of Breast Cancer

The role of L Antigen Family Member 3 (LAGE3) in breast cancer (BC) has not been sufficiently studied. In this study, we explored the clinical value and biological functions of LAGE3 in BC. Comprehensive analysis of LAGE3 was carried out on The Cancer Genome Atlas, Molecular Taxonomy of Breast Cancer International Consortium and Gene Expression Omnibus datasets. Results showed that LAGE3 expression was higher in BC tissues than in normal breast tissues of public datasets and our local cohort. Moreover, its expression was higher in BC patients with larger tumor size, significant lymph node metastasis, higher tumor grade, and more advanced disease stage. High expression of LAGE3 was correlated with poor prognosis, and LAGE3 could independently predict survival of BC patients. Functional enrichment analysis revealed a correlation between LAGE3 expression and biochemical metabolism and immune-related terms and cancer-related pathways. Analysis of tumor microenvironment indicated that LAGE3 expression was associated with the immune cell infiltration and anti-cancer immunity cycle. LAGE3 expression was higher in triple-negative breast cancer (TNBC) compared to hormone receptor-positive BC, but not HER2-positive subtype. Suppression of LAGE3 expression inhibited the proliferation and induced apoptosis of TNBC cell lines. Besides, the down-regulation of LAGE3 attenuated the migration and invasion but reduced the expression level of epithelial-mesenchymal-transition related proteins in TNBC cell lines. In conclusion, this study demonstrated for the first time that LAGE3 promotes the progression of BC. Therefore, it may be a potential diagnostic and prognostic biomarker, as well as a treatment target for BC.

Transcriptome profiling reveals an integrated mRNA-lncRNA signature with predictive value for long-term survival in diffuse large B-cell lymphoma

For patients with diffuse large B-cell lymphoma (DLBCL), survival at 24 months is a milestone for long-term survival. The purpose of this study was to develop a multigene risk score (MGRS) to refine the International Prognostic Index (IPI) model to identify patients with DLBCL at high risk of death within 24 months. Using a robust statistical strategy, we built a MGRS incorporating nine mRNAs and two lncRNAs. Stratification and multivariable Cox regression analysis confirmed the MGRS as an independent risk factor. A nomogram based on IPI+MGRS model was constructed and its calibration plot showed close agreement between predicted 2-year survival rate and observed rate. The 2-year AUC was bigger with the IPI+MGRS model (ΔAUC=0.162; 95%CI 0.1295–0.1903) than with the IPI model, and the IPI+MGRS model more accurately predicted the prognostic risk of DLBCL. The 2-year survival decision curve revealed the IPI+MGRS model was more useful clinically than the IPI model. Functional enrichment analysis showed that the MGRS correlated with cell cycle, DNA replication and repair. The results were validated using an independent external dataset. In conclusion, we successfully developed an integrated mRNA–lncRNA signature to refine the IPI model for predicting long-term survival of patients with DLBCL.

A Novel Promoter CpG-Based Signature for Long-Term Survival Prediction of Breast Cancer Patients

DNA methylation has been reported as one of the most critical epigenetic aberrations during the tumorigenesis and development of breast cancer (BC). This study explored a novel promoter CpG-based signature for long-term survival prediction of BC patients. We used The Cancer Genome Atlas (TCGA) data as training set, and results were validated in an independent dataset from Gene Expression Omnibus (GEO). First, the differential methylation CpG sites were screened in TCGA dataset, of which the candidate promoter CpG sites were preliminarily identified with the univariate Cox regression analysis and the least absolute shrinkage and selection operator regression analysis. Second, the signature was constructed with stepwise regression analysis and multivariate Cox proportional hazards model, which was validated with the survival analysis of two cohorts each from TCGA and GEO databases. The 10-year receiver operating characteristic curves of risk score presented an area under the curve of over 0.7 for both cohorts. A nomogram was also constructed and released. Moreover, Gene Set Enrichment Analysis was performed to identify the more active pathways in high-risk patients. The CpG sites-target gene correlations and differential methylation regions were further explored. In conclusion, the promoter CpG-based signature exhibited good prognostic prediction efficacy in the long-term overall survival of BC patients.

Hypoxia-induced TGF-β-RBFOX2-ESRP1 axis regulates human MENA alternative splicing and promotes EMT in breast cancer

Hypoxic microenvironment heralds epithelial-mesenchymal transition (EMT), invasion and metastasis in solid tumors. Deregulation of alternative splicing (AS) of several cancer-associated genes has been instrumental in hypoxia-induced EMT. Our study in breast cancer unveils a previously unreported mechanism underlying hypoxia-mediated AS of hMENA, a crucial cytoskeleton remodeler during EMT. We report that the hypoxia-driven depletion of splicing regulator ESRP1 leads to skipping of hMENA exon 11a producing a pro-metastatic isoform, hMENAΔ11a. The transcriptional repression of ESRP1 is mediated by SLUG, which gets stimulated via hypoxia-driven TGF-β signaling. Interestingly, RBFOX2, an otherwise RNA-binding protein, is also found to transcriptionally repress ESRP1 while interacting with SLUG. Similar to SLUG, RBFOX2 gets upregulated under hypoxia via TGF-β signaling. Notably, we found that the exosomal delivery of TGF-β contributes to the elevation of TGF-β signaling under hypoxia. Moreover, our results show that in addition to hMENA, hypoxia-induced TGF-β signaling contributes to global changes in AS of genes associated with EMT. Overall, our findings reveal a new paradigm of hypoxia-driven AS regulation of hMENA and insinuate important implications in therapeutics targeting EMT.

Managing therapeutic resistance in breast cancer: from the lncRNAs perspective

Breast cancer (BC) is the most common female malignancy and the second leading cause of cancer-related death worldwide. In spite of significant advances in clinical management, the mortality of BC continues to increase due to the frequent occurrence of treatment resistance. Intensive studies have been conducted to elucidate the molecular mechanisms underlying BC therapeutic resistance, including increased drug efflux, altered drug targets, activated bypass signaling pathways, maintenance of cancer stemness, and deregulated immune response. Emerging evidence suggests that long noncoding RNAs (lncRNAs) are intimately involved in BC therapy resistance through multiple modes of action. Therefore, an in-depth understanding of the implication of lncRNAs in resistance to clinical therapies may improve the clinical outcome of BC patients. Here, we highlight the role and underlying mechanisms of lncRNAs in regulating BC treatment resistance with an emphasis on lncRNAs-mediated resistance in different clinical scenarios, and discuss the potential of lncRNAs as novel biomarkers or therapeutic targets to improve BC therapy response.

Circular RNA hsa_circ_0131242 Promotes Triple-Negative Breast Cancer Progression by Sponging hsa-miR-2682

Objective

CircRNAs are emerging as vital regulators in a variety of cancers. However, the expression pattern and potential mechanism of circRNAs in triple-negative breast cancer remain unclear. In this study, we aim to systematically investigate circRNAs alteration in triple-negative breast cancer tissues.

Methods

Microarray and bioinformatics analyses were used to identify circRNAs expression in cancer tissues. qRT-PCR was conducted to measure the expression of RNAs. Cell Counting Kit‐8, wound-healing and transwell assays were conducted to investigate the function of circRNAs. Dual-luciferase reporter assay was performed to validate target binding.

Results

Hsa_circ_0131242 was highly expressed in both cancer tissues and cell lines compared to control. Subsequently, statistical analyses revealed that high expression of hsa_circ_0131242 was positively correlated with advanced tumor stages and poorer clinical features in cancer patients. Hsa_circ_0131242 knockdown could suppress the progression of breast cancer cells. Bioinformatics prediction and luciferase reporter assay showed that hsa_circ_0131242 acted as a sponge for hsa-miR-2682. Moreover, co-transfection of hsa-miR-2682 inhibitor and si-hsa_circ_0131242 rescued cell proliferation and migration in BT549 and MDA-MB-468 cell lines.

Conclusion

Our study identified hsa_circ_0131242 expression in TNBC for the first time and found that hsa_circ_0131242 may promote triple-negative breast cancer progression by sponging hsa-miR-2682.

Systematic characterization of non-coding RNAs in triple-negative breast cancer

Triple‐negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer with negativity for oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2). Non‐coding RNAs (ncRNAs) make up most of the transcriptome and are widely present in eukaryotic cells. In recent years, emerging evidence suggests that ncRNAs, mainly microRNAs (miRNAs), long ncRNAs (lncRNAs) and circular RNAs (circRNAs), play prominent roles in the tumorigenesis and development of TNBC, but the functions of most ncRNAs have not been fully described. In this review, we systematically elucidate the general characteristics and biogenesis of miRNAs, lncRNAs and circRNAs, discuss the emerging functions of these ncRNAs in TNBC and present future perspectives in clinical practice.

ZGRF1 Is Associated with Poor Prognosis in Triple-Negative Breast Cancer and Promotes Cancer Stemness Based on Bioinformatics

Background

Recently, long non-coding RNAs (lncRNAs) are important populations of non-coding RNAs with defined key roles in normal breast development as well as breast tumorigenesis. Triple-negative breast cancer (TNBC) is a particular breast cancer subtype with poor prognosis because of highly invasive and no specific drug treatment yet. Breast cancer stems cells (BCSCs) cause a high risk of invasion, metastasis and drug resistance for breast cancer patients.

Methods

Two microarrays of BCSCs and no-BCSCs were isolated from mammosphere-3D-cultured MCF-7 cells, differentially expressed lncRNAs (DELs) were screened out by Gene Expression Omnibus (GEO). Gene ontology enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed to analyze DELs features. Using the STRING database to analyze DELs interaction network module to further screen the hub lncRNAs related to tumor stemness and make functional annotations. The expressions of hub DELs were validated using data from The Cancer Genome Atlas database. In addition, the expression analysis and survival analysis were conducted using GEO was utilized to analyze DELs in TNBC using GEPIA database.

Results

A total of 143 aberrantly expressed lncRNAs in BCSCs were identified, and 25 lncRNAs were downregulated and 118 lncRNAs were upregulated compared to non-BCSCs. Up- and downregulated top 3 lncRNAs were selected and verified by RT-PCR. Notably, GO enrichment analysis and KEGG pathway analysis indicated that RNA transport, spliceosome, oxidative phosphorylation, NOD-like receptor signaling pathway, PI3K-Akt signaling pathway, and metabolic pathways may serve important roles in BCSCs. Additionally, the function loss assay indicated that ZGRF1 positively upregulated phenotype and biological functions of BCSCs in vitro. Collectively, our work establishes the lncRNAs signature in BCSCs and these findings assess us with evidence to explore further functionalities of lncRNAs in BCSCs and provide a novel therapeutic strategy for breast cancer.

Conclusion

Our work establishes the lncRNAs signature in BCSCs and these findings assess us with evidence to explore further functionalities of lncRNAs in BCSCs and provide a novel therapeutic strategy for breast cancer. ZGRF1 expression is upregulated in TNBC patients and has a poor prognosis, which can be promising biomarkers.

Significant association between long non-coding RNA H19 polymorphisms and cancer susceptibility: A PRISMA-compliant meta-analysis and bioinformatics prediction

BACKGROUND

H19, a well-known long non-coding RNA, is involved in carcinogenesis and progression of multiple cancers. Molecular epidemiological research suggests that polymorphisms in H19 are associated with an increased risk of cancer, but the results are inconsistent. Thus, we performed a meta-analysis to estimate the associations between H19 polymorphisms and cancer susceptibility.

METHODS

PubMed, Embase, and Web of Science databases were searched. Odds ratios with 95% confidence interval were applied to assess the association between H19 rs2107425, rs217727, rs2839698, rs2735971, rs3024270, and rs3741219 polymorphisms and cancer susceptibility in all 5 models. We also predicted the H19 secondary structure, as well as the generation and abolishment of miRNA binding sites on H19 through the selected SNPs.

RESULTS

Eighteen related studies, involving 17,090 patients and 23,532 control samples, were analyzed. The pooled data showed that rs2839698 polymorphism was significantly associated with an increased cancer susceptibility. As for rs217727 and rs3024270 polymorphisms, similarly increased risks were found in specific genetic models and stratified groups. However, significant decreases in cancer risk were observed for rs2107425 and rs2735971 in the total population, as well as in subgroup analyses. In addition, no significant associations were found in all 5 models for rs3741219 polymorphism. Furthermore, RNAfold prediction revealed that the centroid secondary structure was markedly altered in rs217727 and rs2735971. We also identified that rs217727 G>A and rs2839689 G>A alleles could create and destroy miRNA binding sites on H19.

CONCLUSION

The results of our meta-analyses suggest that H19 polymorphisms may be associated with the risk of cancer development.

Identification of candidate RNA signatures in triple-negative breast cancer by the construction of a competing endogenous RNA network with integrative analyses of Gene Expression Omnibus and The Cancer Genome Atlas data

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is characterized by aggressive and metastatic clinical characteristics and generally leads to earlier distant recurrence and poorer prognosis than other molecular subtypes. Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) serve a crucial role in a wide variety of biological processes by interacting with microRNAs (miRNAs) as competing endogenous RNAs (ceRNAs) and, thus, affect the expression of target genes in multiple types of cancer. Seven datasets from the Gene Expression Omnibus (GEO) database, including 444 tumor and 88 healthy tissue samples, were utilized to investigate the underlying mechanisms of TNBC and identify prognostic biomarkers. Differentially expressed genes (DEGs) were further validated in The Cancer Genome Atlas database and the associations between their expression levels and clinical information were analyzed to identify prognostic values. A potential lncRNA-miRNA-mRNA ceRNA network was also constructed. Finally, 69 mRNAs from the integrated Gene Expression Omnibus datasets were identified as DEGs using the robust rank aggregation method with |log2FC|>1 and adjusted P<0.01 set as the significance cut-off levels. In addition, 29 lncRNAs, 21 miRNAs and 27 mRNAs were included in the construction of the ceRNA network. The present study elucidated the mechanisms underlying the progression of TNBC and identified novel prognostic biomarkers for TNBC.

Long non-coding RNA CCAT2 promotes oncogenesis in triple-negative breast cancer by regulating stemness of cancer cells

Triple-negative breast cancers (TNBC) are more aggressive due to lacking receptors for hormone therapy and maintaining stemness features in cancer cells. Herein we found long non-coding RNA CCAT2 overexpressed specially in TNBC, and in breast cancer stem cells (BCSC) as well. Enforced overexpression and targeted knockdown demonstrated the oncogenic function of CCAT2 both in vitro and in vivo. CCAT2 promoted the expression of stemness markers including OCT4, Nanog and KLF4, increased mammosphere formation and induced ALDH+ cancer stem cell population in TNBC. A chromosomally adjacent gene OCT4-PG1, as a pseudogene of OCT4, was upregulated by CCAT2, and positively regulated the stemness features of TNBC cells. miR-205 was identified as a target gene of CCAT2 in TNBC. Point-mutation in CCAT2 impaired the sponge inhibition of miR-205. Overexpression of miR-205 rescued the oncogenic phenotypes induced by CCAT2. In addition, Notch2, as a target gene of miR-205, was downregulated by miR-205 and upregulated by CCAT2 in TNBC. Collectively, the current study revealed a novel function of CCAT2 in promoting tumor initiation and progression in TNBC through upregulating OCT4-PG1 expression and activating Notch signaling. These findings not only demonstrated a lncRNA-based therapeutic strategy in treatment of TNBC, but also added a node to the regulatory network of CCAT2 that controls aggressiveness of breast cancer stem cells.

LncRNA LINC00470 promotes proliferation through association with NF45/NF90 complex in hepatocellular carcinoma

Increasing evidence demonstrates that long noncoding RNAs (lncRNAs) play an important role in the development and progression of human cancers. LncRNA LINC00470 has been reported to function as an oncogene in glioblastoma. Until now, the roles and underlying mechanisms of LINC00470 in the progression of hepatocellular carcinoma (HCC) remain unclear. Here, we found that LINC00470 was upregulated in HCC cells and tissues. High-level LINC00470 was significantly correlated with bigger tumor size, advanced TNM stage and poor prognosis in patients with HCC. Functional studies showed that knockdown of LINC00470 expression inhibited HCC cell proliferation and cell cycle progression, while overexpression of LINC00470 showed the opposite effects. Further investigation suggested that LINC00470 was associated with NF45/NF90 complex and increased its interaction with cyclin E1 mRNA, thus inhibiting the degradation of cyclin E1 mRNA. Additionally, knockdown of cyclin E1 in LINC00470-overexpressed cells abolished its promotive effects on HCC cell proliferation. In summary, our findings suggest that targeting LINC00470 could be a potential therapeutic approach in treating HCC patients.

The identification of a TNBC liver metastasis gene signature by sequential CTC-xenograft modeling

Triple-negative breast cancer (TNBC) liver metastasis is associated with poor prognosis and low patient survival. It occurs when tumor cells disseminate from primary tumors, circulate in blood/lymph [circulating tumor cells (CTCs)], and acquire distinct characteristics during disease progression toward the metastatic phenotype. The purpose of this study was to decipher the genomic/transcriptomic properties of TNBC liver metastasis and its recurrence for potential therapeutic targeting. We employed a negative depletion strategy to isolate and interrogate CTCs from the blood of patients with TNBC, and to establish sequential generations of CTC-derived xenografts (CDXs) through injection of patient CTCs in immunodeficient mice. The isolation and validation of CDX-derived cell populations [analyses of CTCs were paired with bone marrow-resident cells (BMRTCs) and liver tissue cells obtained from the same animal] were performed by multiparametric flow cytometry, immune phenotyping, and genomic sequencing of putative CTCs. Comprehensive characterization of gene expression arrays from sequentially generated CDX-derived cell populations, online gene expression arrays, and TCGA databases were employed to discover a CTC-driven, liver metastasis-associated TNBC signature. We discovered a distinct transcriptomic signature of TNBC patient-isolated CTCs from primary TNBCs, which was consistent throughout sequential CDX modeling. We established a novel TNBC liver metastasis-specific CDX model that selectively recapitulates CTC biology for four sequential generations of mice. The evaluation of online databases and CDX-derived populations revealed 597 genes specific to the TNBC liver metastasis signatures. Further investigation of the TNBC liver metastasis signature predicted 16 hub genes, 6 biomarkers with clinically available drugs, and 22 survival genes. The sequential interrogation of CDX-CTCs is an innovative liquid biopsy-based approach for the discovery of organ metastasis-specific signatures of CTCs. This represents the first step for mechanistic and analytical validation in their application as prognostic indicators and therapeutic targets. Targeting CTC drug candidate biomarkers along with combination therapy can improve the clinical outcome of TNBC patients in general and recurrence of liver metastasis in particular.

Replication-dependent histone isoforms: a new source of complexity in chromatin structure and function

Replication-dependent histones are expressed in a cell cycle regulated manner and supply the histones necessary to support DNA replication. In mammals, the replication-dependent histones are encoded by a family of genes that are located in several clusters. In humans, these include 16 genes for histone H2A, 22 genes for histone H2B, 14 genes for histone H3, 14 genes for histone H4 and 6 genes for histone H1. While the proteins encoded by these genes are highly similar, they are not identical. For many years, these genes were thought to encode functionally equivalent histone proteins. However, several lines of evidence have emerged that suggest that the replication-dependent histone genes can have specific functions and may constitute a novel layer of chromatin regulation. This Survey and Summary reviews the literature on replication-dependent histone isoforms and discusses potential mechanisms by which the small variations in primary sequence between the isoforms can alter chromatin function. In addition, we summarize the wealth of data implicating altered regulation of histone isoform expression in cancer.

The effect of long noncoding RNAs HOX transcript antisense intergenic RNA single-nucleotide polymorphisms on breast cancer, cervical cancer, and ovarian cancer susceptibility: A meta-analysis

Recent studies have shown that long noncoding RNAs (lncRNA) HOX transcript antisense intergenic RNA (HOTAIR) polymorphisms are associated with cancer susceptibility. The greatest threat to women's health among a variety of cancers is breast cancer (BC), cervical cancer (CC), and ovarian cancer (OC), and the incidence of it is increasing. We performed a meta-analysis to clarify the relationship between lncRNA HOTAIR expression and BC, CC, and OC susceptibility. We thoroughly searched PubMed, Embase, and the Cochrane Library to obtain the relevant literature. We extracted data from case groups and control groups for each single-nucleotide polymorphism (SNP) (rs4759314, rs920778, rs189663, rs12826786, rs7958904, and rs874945) and compared the relationship between alleles, codominance models, dominant and invisible models and BC, CC, and OC susceptibility. Our study included 11 studies with a total of 5322 patients. There was a significant association between the rs4759314 polymorphism of HOTAIR and susceptibility to BC, CC, and OC (codominant model: AG/AA odds ratio [OR] = 1.13 [95% confidence intervals [CI], 1.00-1.29], GG/AA OR = 1.54 [95% CI, 1.06-2.23]; dominant model: GG + AG/AA OR = 1.16 [95% CI, 1.02-1.32]; and recessive model: GG/AA + AG OR = 1.51 [95% CI, 1.05-2.19]). The association between the expression of rs920778 and BC, CC, and OC susceptibility was not clear (alleles T/C: OR = 1.28 [95% CI, 0.87-1.89]; in codominant model: CT/CC OR = 1.10, [95% CI, 0.71-1.71], TT/CC OR = 1.29 [95% CI, 0.59-2.80]; dominant model: TC + TT/CC OR = 1.16, [95% CI, 0.73-1.86]; and recessive model: TT/TC + CC OR = 1.43, [95% CI, 0.83-2.47]). HOTAIR polymorphism rs1899663 was associated with BC, CC, and OC susceptibility to a certain extent, (alleles T/G OR = 0.90 [95% CI, 0.69-1.16]; in the codominant model: GT/GG OR = 0.81 [95% CI, 0.50-1.30], TT/GG OR = 1.04 [95% CI, 0.63-1.72]; dominant model: GT + TT/GG OR = 0.82 [95% CI, 0.52-1.29]; and recessive model: TT/GT + GG OR = 1.21 [95% CI, 0.76-1.94]). The rs12826786, rs7958904, and rs874945 polymorphisms were associated with a certain degree of BC, CC, and OC susceptibility, but they were not statistically significant. HOTAIR rs4759314 increased susceptibility to BC, CC, and OC in some patients; rs029778 and rs1899663 also increased susceptibility to some extent. SNPs rs12826786, rs7958904, and rs874945 did not correlate with an effect on patient susceptibility to BC, CC, and OC.

Transcriptome profiling reveals an integrated mRNA-lncRNA signature with predictive value of early relapse in colon cancer

The purpose of our study was to develop a multigene signature based on transcriptome profiles of both mRNAs and lncRNAs to identify a group of patients who are at high risk of early relapse in stages II-III colon cancer. Firstly, propensity score matching was conducted between patients in early relapse group and long-term survival group from GSE39582 training series (N = 359) and patients were matched 1:1. Global transcriptome analysis was then performed between the paired groups to identify tumor specific mRNAs and lncRNAs. Finally, using LASSO Cox regression model, we built a multigene early relapse classifier incorporating 15 mRNAs and three lncRNAs. The prognostic and predictive accuracy of the signature was internally validated in 102 colon cancer patients and externally validated in other 241 patients. In the training set, patients with high risk score were more likely to suffer from relapse than those with low risk score (HR: 2.67, 95% CI: 2.07-3.46, P < 0.001). The results were validated in the internal validation set (HR: 2.23, 95% CI: 1.23-3.78, P = 0.003) and external validation (HR 1.88, 95% CI 1.42-2.48; P < 0.001) set. Time-dependent receiver operating curve at 1 year showed that the integrated mRNA-lncRNA signature [area under curve (AUC) = 0.742] had better prognostic accuracy than AJCC TNM stage (AUC = 0.615) in the entire 702 patients. In addition, survival decision curve analyses at 12 months revealed a good clinical usefulness of the integrated mRNA-lncRNA signature. In conclusion, we successfully developed an integrated mRNA-lncRNA signature that can accurately predict early relapse.

miR-148b-3p, miR-190b, and miR-429 Regulate Cell Progression and Act as Potential Biomarkers for Breast Cancer

Purpose

Breast cancer is the most frequently diagnosed malignancy in women worldwide. MicroRNAs (miRNAs) are thought to serve as potential biomarkers in various cancers, including breast cancer.

Methods

We evaluated the miRNA expression profiles in 1,083 breast cancer samples and 104 normal breast tissues from The Cancer Genome Atlas database. We used the edgeR package of R software to analyze the differentially expressed miRNAs in normal and cancer tissues, and screened survival-related miRNAs by Kaplan-Meier analysis. A receiver operating characteristic curve was generated to evaluate the accuracy of these miRNAs as molecular markers for breast cancer diagnosis. Furthermore, the functional role of these miRNAs was verified using cell experiments. Targets of candidate miRNAs were predicted using 9 online databases, and Gene Ontology (GO) functional annotation and pathway analyses were conducted using Database for Annotation, Visualization and Integrated Discovery online tool.

Results

A total of 68 miRNAs showed significantly different expression patterns between the groups (p < 0.001), and 13 of these miRNAs were significantly associated with poor survival (p < 0.05). Three miRNAs with high specificity and sensitivity, namely, miR-148b-3p, miR-190b, and miR-429, were selected. In vitro experiments showed that the overexpression of these 3 miRNAs significantly promoted the proliferation and migration of MDA-MB-468 and T47D cells and reduced the apoptosis of T47D cells. GO and pathway enrichment analyses revealed that the targets of these dysregulated miRNAs were involved in many critical cancer-related biological processes and pathways.

Conclusion

The miR-148b-3p, miR-190b, and miR-429 may serve as potential diagnostic and prognostic markers for breast cancer. This study demonstrated the roles of these 3 miRNAs in the initiation and progression of breast cancer.

LSECtin on tumor-associated macrophages enhances breast cancer stemness via interaction with its receptor BTN3A3

Macrophages have been suggested to contribute to constructing a cancer stem cell (CSC) niche. However, whether and how macrophages regulate the activity of CSCs through juxtacrine signaling are poorly understood. Here we report LSECtin, a transmembrane protein highly expressed on tumor-associated macrophages (TAMs), enhances stemness of breast cancer cells (BCCs). We identified BTN3A3, a B7 family member with previously unknown functions as the receptor for LSECtin on BCCs responsible for stemness-promoting effect of LSECtin. In mice bearing human tumor xenografts, either macrophage-specific ablation of LSECtin or silencing of BTN3A3 in BCCs decreased CSC frequency and tumor growth. Admixture of LSECtin-positive macrophages increased the tumorigenic activity of BCCs dependent on BTN3A3. Disruption of the LSECtin-BTN3A3 axis with BTN3A3-Fc or anti-BTN3A3 mAb has a therapeutic effect on breast cancer. These findings define a juxtacrine signaling mechanism by which TAMs promote cancer stemness. Targeting this axis in the CSC niche may provide potential therapies to breast cancer.

DSCAM-AS1 regulates the G1 /S cell cycle transition and is an independent prognostic factor of poor survival in luminal breast cancer patients treated with endocrine therapy

DSCAM-AS1 is one of the few intensively studied lncRNAs with high specific expression in luminal breast cancer. It is directly regulated by estrogen receptor α (ERα) and plays vital roles in tumor proliferation, invasion, and tamoxifen resistance. However, the detailed function of DSCAM-AS1 in tumor progression and its clinical significance remain unclear. We reveal that DSCAM-AS1 regulates cell proliferation and colony formation by inducing the G1/S transition. RNA-seq analysis demonstrated that DSCAM-AS1 participates in crucial biological processes, including DNA replication, the G1/S phase transition, sister chromatid cohesion, chromosome segregation, protein localization to the chromosome and DNA recombination. Most importantly, in the retrospectively registered clinical analysis, high expression of DSCAM-AS1 is a poor prognostic factor in patients with luminal breast cancer treated with endocrine therapy. In conclusion, DSCAM-AS1 is a promising clinical therapeutic target that may prolong survival of luminal breast cancer patients treated with endocrine therapy.

Long non-coding RNA DANCR stabilizes HIF-1α and promotes metastasis by interacting with NF90/NF45 complex in nasopharyngeal carcinoma

Long noncoding RNAs (lncRNAs) play an important role in the development and progression of cancers. However, the clinical significances of lncRNAs and their functions and mechanisms in nasopharyngeal carcinoma (NPC) remain largely unclear. Methods: Quantitative RT-PCR was used to determine DANCR expression and Kaplan-Meier curves were used to evaluate its prognostic value. RNA sequencing followed by bioinformatic analysis was performed to determine the potential function of DANCR. In vitro and in vivo experiments were conducted to investigate its biological effects. DANCR-interacting proteins were identified by RNA pull-down assay followed by mass spectrometry and western blotting, and then confirmed by RNA immunoprecipitation (RIP) assays. Results: Our previous microarray analysis identified a metastasis-associated lncRNA DANCR. Here, we found that DANCR was upregulated in NPC, especially in those with lymph lode metastasis, and its upregulation could predict poor survival. We then constructed a prognostic predictive model. RNA sequencing followed by bioinformatic analysis revealed that DANCR was responsible for NPC metastasis and hypoxia phenotype. Functional studies showed that DANCR promoted NPC cell invasion and metastasis in vitro and in vivo. Further investigation suggested that DANCR could increase HIF-1α mRNA stability through interacting with the NF90/NF45 complex. Additionally, overexpression of HIF-1α in DANCR knockdown cells restored its suppressive effects on NPC cell migration and invasion. Conclusions: Taken together, our results suggest that DANCR acts as a prognostic biomarker and increases HIF-1α mRNA stability by interacting with NF90/NF45, leading to metastasis and disease progression of NPC.

Transcriptome analysis reveals an altered expression profile of zinc transporters in colorectal cancer

Zinc is a transition metal and catalytic cofactor involved in many biological processes including proliferation, development, differentiation, and metabolism. Zinc transporters (ZnTs) play a fundamental role in cellular zinc homeostasis. ZnTs are responsible of zinc efflux and are encoded by 10 genes belonging to solute carrier family 30A (SLC30A1-10), while zinc-regulated transporter (ZRT)/iron-regulated transporter (IRT)-like protein (ZIP) transporters are responsible for the influx of zinc into the cytoplasm and are encoded by 14 genes belonging to solute carrier family 39A (SLC39A1-14). In this study, we analyzed, by transcriptome analysis, the microRNA levels of ZnT-encoding and ZIP-encoding genes in colorectal cancer (CRC) samples matched to normal colon tissues and in CRC cell lines. Results revealed an upregulation of specific ZnT and ZIP transcripts in CRC. Upregulation of SLC30A5, SLC30A6, SLC30A7 transcripts, encoding zinc efflux transporters ZnT5, ZnT6, ZnT7, localized on endoplasmic reticulum membranes, might be part of a coordinated transcriptional program associated to the increased activity of the early secretory pathway, while transcriptional upregulation of several specific ZIP transporters (SLC39A6, SLC39A7, SLC39A9, SLC39A10, and SLC39A11) could contribute in meeting the increased demand of zinc in cancer cells. Moreover, exon-level analysis of SLC30A9, a nuclear receptor coactivator involved in the transcriptional regulation of Wnt-responsive genes, revealed the differential expression of alternative transcripts in CRC and normal colonic mucosa.

MicroRNA-493 is a prognostic factor in triple-negative breast cancer

Breast cancer is one of the most common malignant diseases in women. Triple‐negative breast cancer (TNBC) shows higher aggressiveness and recurrence rates than other subtypes, and there are no effective targets or tailored treatments for TNBC patients. Thus, finding effective prognostic markers for TNBC could help clinicians in their ability to care for their patients. We used tissue microarrays (TMAs) to detect microRNA‐493 (miR‐493) expression in breast cancer samples. A miRCURY LNA detection probe specific for miR‐493 was used in in situ hybridization assays. Staining results were reviewed by two independent pathologists and classified as high or low expression of miR‐493. Kaplan–Meier survival plots and multivariate Cox analysis were carried out to clarify the relationship between miR‐493 and survival. In the Kaplan–Meier analysis, patients with high miR‐493 expression had better disease‐free survival than patients with low miR‐493 expression. After adjusting for common clinicopathological factors in breast cancer, the expression level of miR‐493 was still a significant prognostic factor in breast cancer. Further subtype analysis revealed that miR‐493 expression levels were only significantly prognostic in TNBC patients. These results were validated in the Molecular Taxonomy of Breast Cancer International Consortium database for overall survival. We proved the prognostic role of miR‐493 in TNBC by using one of the largest breast cancer TMAs available and validated it in a large public RNA sequencing database.

The HOTAIR, PRNCR1 and POLR2E polymorphisms are associated with cancer risk: a meta-analysis

Long non-coding RNAs (LncRNAs) have been widely studied and aberrant expression of lncRNAs are involved in diverse cancers. Genetic variation in lncRNAs can influence the lncRNAs expression and function. At present, there are many studies to investigate the association between lncRNAs polymorphisms and cancer susceptibility. However, it has no systematic study to evaluate the association. We performed a meta-analysis to summarize the results of common lncRNAs (HOTAIR, PRNCR1, POLR2E and H19) polymorphisms on cancer risk, by using the random-effect model to obtain the odds ratio (ORs) and 95% confidence interval (95%CI). We also applied the meta-regression and publication bias analysis to seek the source of heterogeneity and evaluate the stability of results, respectively. The summary results indicated that HOTAIR rs920778 increased the cancer risk in recessive model (OR = 1.61, 95% CI = 1.08-2.41, P_{heterogeneity}<0.001). For PRNCR1 (rs1016343, rs16901946) and POLR2E (rs3787016), we also found the significant association with incresed risk of cancer (all P<0.05). However, we did not observe any significant association between H19 rs2107425 and cancer risk. Our meta-analysis results revealed that these four lncRNAs polymorphisms (HOTAIR rs920778, PRNCR1 rs1016343 and rs16901946, POLR2E rs3787016) can contribute to cancer risk. Further studies should confirm these findings.

Applications of RNA Indexes for Precision Oncology in Breast Cancer

Precision oncology aims to offer the most appropriate treatments to cancer patients mainly based on their individual genetic information. Genomics has provided numerous valuable data on driver mutations and risk loci; however, it remains a formidable challenge to transform these data into therapeutic agents. Transcriptomics describes the multifarious expression patterns of both mRNAs and non-coding RNAs (ncRNAs), which facilitates the deciphering of genomic codes. In this review, we take breast cancer as an example to demonstrate the applications of these rich RNA resources in precision medicine exploration. These include the use of mRNA profiles in triple-negative breast cancer (TNBC) subtyping to inform corresponding candidate targeted therapies; current advancements and achievements of high-throughput RNA interference (RNAi) screening technologies in breast cancer; and microRNAs as functional signatures for defining cell identities and regulating the biological activities of breast cancer cells. We summarize the benefits of transcriptomic analyses in breast cancer management and propose that unscrambling the core signaling networks of cancer may be an important task of multiple-omic data integration for precision oncology.

Dysregulation of long non-coding RNA in breast cancer: an overview of mechanism and clinical implication

Long non-coding RNAs (lncRNAs), which occupy nearly 98% of genome, have crucial roles in cancer development, including breast cancer. Breast cancer is a disease with high incidence. Despite of recent progress in understanding the molecular mechanisms and combined therapy strategies, the functions and mechanisms of lncRNAs in breast cancer remains unclear. This review presents the currently basic knowledge and research approaches of lncRNAs. We also highlight the latest advances of seven classic lncRNAs and three novel lncRNAs in breast cancer, elucidating their mechanisms and possible therapeutic targets. Additionally, association between lncRNA and specific molecular subtype of breast cancer is reported. Lastly, we briefly delineate the potential roles of lncRNAs in clinical applications as biomarkers and treatment targets.