TTK/hMPS1 is an attractive therapeutic target for triple-negative breast cancer

Targeting TTK Inhibits Tumorigenesis of T-Cell Lymphoma Through Dephosphorylating p38α and Activating AMPK/mTOR Pathway

T-cell lymphoma (TCL) is a group of non-Hodgkin's lymphoma with high heterogeneity and unfavorable prognosis. Current standard treatments have demonstrated limited efficacy in improving the outcomes for TCL patients. Therefore, identification of novel drug targets is urgently needed to improve the prognosis of TCL patients. Through multi-omics analysis, aberrant expression of threonine tyrosine kinase (TTK) in TCL is identified. High expression of TTK is closely associated with poor prognosis in TCL patients. Targeting TTK through gene knockdown exerts anti-tumor effects in vitro and in vivo, including inhibiting the cell proliferation, inducing G2/M phase arrest, enhancing DNA damage and cell apoptosis. Mechanically, p38α is identified as the potential phosphorylation substrate of TTK through phosphoproteomic quantification and motif prediction. Furthermore, inhibition of TTK suppresses activation of p38α through dephosphorylating it at Thr180/Tyr182, thereby promoting the activation of AMPK/mTOR pathway. In addition, targeting TTK enhances the autophagy in TCL cells through dephosphorylating p38α. CFI-402257, a specific inhibitor of TTK, is found to exhibit anti-tumor effects and exerted synergistic efficacy with PI3K inhibitor, Duvelisib, in TCL. The study shows that TTK contributes to the development of TCL by regulating p38α-mediated AMPK/mTOR pathway. CFI-402257 is expected to be a promising strategy for TCL treatment.

Threonine and tyrosine kinase (TTK) mRNA and protein expression in breast cancer; prognostic significance in the neoadjuvant setting

AIMS

Threonine and tyrosine kinase (TTK) is up-regulated in triple-negative breast cancer (TNBC), yet its expression in patients undergoing neoadjuvant chemotherapy (NACT) remains unexplored. This investigation aims to assess TTK protein expression in treatment-naïve pre-treatment cores and paired pre- and post-NACT breast cancer (BC) cohorts, as well as its correlation with microcephaly 1 (MCPH1) protein expression.

METHODS AND RESULTS

Transcriptomic data were sourced from the Gene Expression Omnibus microarray database for mRNA expression analysis. TTK protein expression was evaluated using immunohistochemistry staining, employing receiver operating characteristic curve analysis to determine an optimal TTK expression cut-off point. The association between TTK expression, clinicopathological parameters and survival outcomes was examined. Additionally, MCPH1 protein expression was assessed in a pilot study. Analysis revealed a significantly elevated TTK mRNA expression in BC tissue compared to normal breast tissue, with high TTK mRNA levels predicting reduced overall survival. Notably, TTK protein expression increased significantly post-NACT in a paired cohort. Conversely, decreased TTK protein expression pre-NACT was correlated with improved overall survival.

CONCLUSIONS

High TTK and low MCPH1 protein expression was significantly correlated, highlighting TTK's potential as a biomarker for BC and a therapeutic target for MCPH1-deficient cancer cells.

TTK promotes HER2 + breast cancer cell migration, apoptosis, and resistance to targeted therapy by modulating the Akt/mTOR axis

BACKGROUND

HER2 + breast cancer is a malignant neoplasm with a high degree of aggressiveness and therapeutic challenge. In recent years, studies have indicated a strong correlation between TTK and various tumors, though its role in HER2 + BRCA remains unclear.

OBJECTIVES

Studying the biological function of the TTK gene in HER2 + BRCA and its resistance to targeted therapy it provides new ideas for targeted drug research.

METHODS

TTK was knocked down by small interfering RNA transfection, and its biological function in HER2 + BRCA cells was verified, and its mechanism of action was verified by RT-PCR and Western blot.

RESULTS

The study demonstrated that TTK promoted cell proliferation and migration by activating the Akt/mTOR pathway in HER2 + breast cancer and enhanced the drug sensitivity of BRCA cell lines SKBR3 and BT474 to pyrotinib, in addition, knockdown of TTK induced apoptosis and arrested cells in G1 phase.

CONCLUSION

Which implies that TTK is an oncogene in HER2 + BRCA and is a valuable research target.

CD8+ T cell‑related KCTD5 contributes to malignant progression and unfavorable clinical outcome of patients with triple‑negative breast cancer

Triple‑negative breast cancer (TNBC) is a highly aggressive and heterogeneous subtype of breast cancer that lacks expression of estrogen receptor, progesterone receptor, and HER2, making it more challenging to treat with targeted therapies. The present study aimed to identify CD8+ T cell‑associated genes, which could provide insight into the mechanisms underlying TNBC to facilitate developing novel immunotherapies. TNBC datasets were downloaded from public databases including The Cancer Genome Atlas, Molecular Taxonomy of Breast Cancer International Consortium, and Gene Expression Omnibus. Candidate genes were identified integrating weighted gene co‑expression network analysis (WGCNA), differential gene expression, protein‑protein‑interaction network construction and univariate Cox regression analysis. Kaplan‑Meier survival, multivariate Cox regression and receiver operating characteristic analysis were performed to evaluate the prognostic value of hub genes. Knockdown experiments, alongside wound healing, Cell Counting Kit‑8 and Transwell migration and invasion assays were performed. In total, seven gene modules were associated with CD8+ T cells using WGCNA, among which potassium channel tetramerization domain 5 (KCTD5) was significantly upregulated in TNBC samples and was associated with poor prognosis. KCTD5 expression inversely associated with infiltration ratios of 'Macrophages M1', 'Plasma cells', and 'γδ T cells', but positively with 'activated Mast cells', 'Macrophages M0', and 'Macrophages M2'. As an independent prognostic indicator for TNBC, KCTD5 was also associated with drug sensitivity and the expression of programmed cell death protein 1, Cytotoxic T‑Lymphocyte‑Associated Protein 4 (CTLA4), CD274), Cluster of Differentiation 86 (CD86), Lymphocyte‑Activation Gene 3 (LAG3), T Cell Immunoreceptor with Ig and ITIM Domains (TIGIT). Knockdown of KCTD5 significantly inhibited viability, migration and invasion of TNBC cells in vitro. KCTD5 was suggested to impact the tumor immune microenvironment by influencing the infiltration of immune cells and may serve as a potential therapeutic target for TNBC.

Quercetin and taxifolin inhibits TMPRSS2 activity and its interaction with EGFR in paclitaxel-resistant breast cancer cells: An in silico and in vitro study

Transmembrane protease/serine (TMPRSS2), a type II transmembrane serine protease, plays a crucial role in different stages of cancer. Recent studies have reported that the triggering epidermal growth factor receptor (EGFR) activation through protease action promotes metastasis. However, there are no reports on the interaction of TMPRSS2 with EGFR, especially in triple-negative triple negative (TNBC). The current study investigates the unexplored interaction between TMPRSS2 and EGFR, which are key partners mediating metastasis. This interaction is explored for potential targeting using quercetin (QUE) and taxifolin (TAX). TMPRSS2 expression patterns in breast cancer (BC) tissues and subtypes have been predicted, with the prognostic significance assessed using the GENT2.0 database. Validation of TMPRSS2 expression was performed in normal and TNBC tissues, including drug-resistant cell lines, utilizing GEO datasets. TMPRSS2 was further validated as a predictive biomarker for FDA-approved chemotherapeutics through transcriptomic data from BC patients. The study demonstrated the association of TMPRSS2 with EGFR through in silico analysis and validates the findings in TNBC cohorts using the TIMER2.0 web server and the TCGA dataset through C-Bioportal. Molecular docking and molecular dynamic simulation studies identified QUE and TAX as best leads targeting TMPRSS2. They inhibited cell-free TMPRSS2 activity like clinical inhibitor of TMPRSS2, Camostat mesylate. In cell-based assays focused on paclitaxel-resistant TNBC (TNBC/PR), QUE and TAX demonstrated potent inhibitory activity against extracellular and membrane-bound TMPRSS2, with low IC50 values. Furthermore, ELISA and cell-based AlphaLISA assays demonstrated that QUE and TAX inhibit the interaction of TMPRSS2 with EGFR. Additionally, QUE and TAX exhibited significant inhibition of proliferation and cell cycle accompanied by notable alterations in the morphology of TNBC/PR cells. This study provides valuable insights into potential of QUE and TAX targeting TMPRSS2 overexpressing TNBC.

Energy‑stress‑mediated activation of AMPK sensitizes MPS1 kinase inhibition in triple‑negative breast cancer

Monopolar spindle 1 kinase (Mps1, also known as TTK protein kinase) inhibitors exert marked anticancer effects against triple‑negative breast cancer (TNBC) by causing genomic instability and cell death. As aneuploid cells are vulnerable to compounds that induce energy stress through adenosine monophosphate‑activated protein kinase (AMPK) activation, the synergistic effect of Mps1/TTK inhibition and AMPK activation was investigated in the present study. The combined effects of CFI‑402257, an Mps1/TTK inhibitor, and AICAR, an AMPK agonist, were evaluated in terms of cytotoxicity, cell‑cycle distribution, and in vivo xenograft models. Additional molecular mechanistic studies were conducted to elucidate the mechanisms underlying apoptosis and autophagic cell death. The combination of CFI‑402257 and AICAR showed selective cytotoxicity in a TNBC cell line. The formation of polyploid cells was attenuated, and apoptosis was increased by the combination treatment, which also induced autophagy through dual inhibition of the PI3K/Akt/mTOR and mitogen‑activated protein kinase (MAPK) signaling pathways. Additionally, the combination therapy showed strongly improved efficacy in comparison with CFI‑402257 and AICAR monotherapy in the MDA‑MB‑231 xenograft model. The present study suggested that the combination of CFI‑402257 and AICAR is a promising therapeutic strategy for TNBC.

Mitotic kinases are emerging therapeutic targets against metastatic breast cancer

This review aims to outline mitotic kinase inhibitors' roles as potential therapeutic targets and assess their suitability as a stand-alone clinical therapy or in combination with standard treatments for advanced-stage solid tumors, including triple-negative breast cancer (TNBC). Breast cancer poses a significant global health risk, with TNBC standing out as the most aggressive subtype. Comprehending the role of mitosis is crucial for understanding how TNBC advances from a solid tumor to metastasis. Chemotherapy is the primary treatment used to treat TNBC. Some types of chemotherapeutic agents target cells in mitosis, thus highlighting the need to comprehend the molecular mechanisms governing mitosis in cancer. This understanding is essential for devising targeted therapies to disrupt these mitotic processes, prevent or treat metastasis, and improve patient outcomes. Mitotic kinases like Aurora kinase A, Aurora Kinase B, never in mitosis gene A-related kinase 2, Threonine-Tyrosine kinase, and Polo-kinase 1 significantly impact cell cycle progression by contributing to chromosome separation and centrosome homeostasis. When these kinases go awry, they can trigger chromosome instability, increase cell proliferation, and activate different molecular pathways that culminate in a transition from epithelial to mesenchymal cells. Ongoing clinical trials investigate various mitotic kinase inhibitors as potential biological treatments against advanced solid tumors. While clinical trials against mitotic kinases have shown some promise in the clinic, more investigation is necessary, since they induce severe adverse effects, particularly affecting the hematopoietic system.

Identification of shared gene signatures in major depressive disorder and triple-negative breast cancer

BACKGROUND

Patients with major depressive disorder (MDD) have an increased risk of breast cancer (BC), implying that these two diseases share similar pathological mechanisms. This study aimed to identify the key pathogenic genes that lead to the occurrence of both triple-negative breast cancer (TNBC) and MDD.

METHODS

Public datasets GSE65194 and GSE98793 were analyzed to identify differentially expressed genes (DEGs) shared by both datasets. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape to identify key PPI genes using cytoHubba. Hub DEGs were obtained from the intersection of hub genes from a PPI network with genes in the disease associated modules of the Weighed Gene Co-expression Network Analysis (WGCNA). Independent datasets (TCGA and GSE76826) and RT-qPCR validated hub gene expression.

RESULTS

A total of 113 overlapping DEGs were identified between TNBC and MDD. The PPI network was constructed, and 35 hub DEGs were identified. Through WGCNA, the blue, brown, and turquoise modules were recognized as highly correlated with TNBC, while the brown, turquoise, and yellow modules were similarly correlated with MDD. Notably, G3BP1, MAF, NCEH1, and TMEM45A emerged as hub DEGs as they appeared both in modules and PPI hub DEGs. Within the GSE65194 and GSE98793 datasets, G3BP1 and MAF exhibited a significant downregulation in TNBC and MDD groups compared to the control, whereas NCEH1 and TMEM45A demonstrated a significant upregulation. These findings were further substantiated by TCGA and GSE76826, as well as through RT-qPCR validation.

CONCLUSIONS

This study identified G3BP1, MAF, NCEH1 and TMEM45A as key pathological genes in both TNBC and MDD.

Discovery of a potent and selective covalent threonine tyrosine kinase (TTK) inhibitor

Threonine tyrosine kinase (TTK) is a critical component of the spindle assembly checkpoint and plays a pivotal role in mitosis. TTK has been identified as a potential therapeutic target for human cancers. Here, we describe our design, synthesis and evaluation of a class of covalent TTK inhibitors, exemplified by 16 (SYL1073). Compound 16 potently inhibits TTK kinase with an IC50 of 0.016 μM and displays improved selectivity in a panel of kinases. Mass spectrometry analysis reveals that 16 covalently binds to the C604 cysteine residue in the hinge region of the TTK kinase domain. Furthermore, 16 achieves strong potency in inhibiting the growth of various human cancer cell lines, outperforming its relative reversible inhibitor, and eliciting robust downstream effects. Taken together, compound 16 provides a valuable lead compound for further optimization toward the development of drug for treatment of human cancers.

High-Resolution Profiling of Head and Neck Squamous Cells Carcinoma Identifies Specific Biomarkers and Expression Subtypes of Clinically Relevant Vulnerabilities

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) is the seventh most common cancer worldwide. Although there are several options for the treatment of HNSC, there is still a lack of better biomarkers to accurately predict the response to treatment and thus be more able to correctly treat the therapeutic modality.

METHODS

First, we typed cases from the TCGA-HNSC cohort into subtypes by a Bayesian non-negative matrix factorization (BayesNMF)-based consensus clustering approach. Subsequently, genomic and proteomic data from HNSC cell lines were integrated to identify biomarkers of response to targeted therapies and immunotherapies. Finally, associations between HNSC subtypes and CD8 T-cell-associated effector molecules, common immune checkpoint genes, were compared to assess the potential of HNSC subtypes as clinically predictive immune checkpoint blockade therapy.

RESULTS

The 500 HNSC cases from TCGA were put through a consensus clustering approach to identify six HNSC expression subtypes. In addition, subtypes with unique proteomics and dependency profiles were defined based on HNSC cell line histology and proteomics data. Subtype 4 (S4) exhibits hyperproliferative and hyperimmune properties, and S4-associated cell lines show specific vulnerability to ADAT2, EIF5AL1, and PAK2. PD-L1 and CASP1 inhibitors have therapeutic potential in S4, and we have also demonstrated that S4 is more responsive to immune checkpoint blockade therapy.

CONCLUSION

Overall, our HNSC typing approach identified robust tumor-expressing subtypes, and data from multiple screens also revealed subtype-specific biology and vulnerabilities. These HNSC expression subtypes and their biomarkers will help develop more effective therapeutic strategies.

Seize the engine: Emerging cell cycle targets in breast cancer

Breast cancer arises from a series of molecular alterations that disrupt cell cycle checkpoints, leading to aberrant cell proliferation and genomic instability. Targeted pharmacological inhibition of cell cycle regulators has long been considered a promising anti-cancer strategy. Initial attempts to drug critical cell cycle drivers were hampered by poor selectivity, modest efficacy and haematological toxicity. Advances in our understanding of the molecular basis of cell cycle disruption and the mechanisms of resistance to CDK4/6 inhibitors have reignited interest in blocking specific components of the cell cycle machinery, such as CDK2, CDK4, CDK7, PLK4, WEE1, PKMYT1, AURKA and TTK. These targets play critical roles in regulating quiescence, DNA replication and chromosome segregation. Extensive preclinical data support their potential to overcome CDK4/6 inhibitor resistance, induce synthetic lethality or sensitise tumours to immune checkpoint inhibitors. This review provides a biological and drug development perspective on emerging cell cycle targets and novel inhibitors, many of which exhibit favourable safety profiles and promising activity in clinical trials.

Development of MPS1 Inhibitors: Recent Advances and Perspectives

Monopolar spindle kinase 1 (MPS1) plays a pivotal role as a dual-specificity kinase governing spindle assembly checkpoint activation and sister chromatid separation in mitosis. Its overexpression has been observed in various human malignancies. MPS1 reduces spindle assembly checkpoint sensitivity, allowing tumor cells with a high degree of aneuploidy to complete mitosis and survive. Thus, MPS1 has emerged as a promising candidate for cancer therapy. Despite the identification of numerous MPS1 inhibitors, only five have advanced to clinical trials with none securing FDA approval for cancer treatment. In this perspective, we provide a concise overview of the structural and functional characteristics of MPS1 by highlighting its relevance to cancer. Additionally, we explore the structure-activity relationships, selectivity, and pharmacokinetics of MPS1 inhibitors featuring diverse scaffolds. Moreover, we review the reported work on enhancing MPS1 inhibitor selectivity, offering valuable insights into the discovery of novel, highly potent small-molecule MPS1 inhibitors.

Expression pattern, prognostic value and potential microRNA silencing of FZD8 in breast cancer

Breast cancer (BC) is one of the most widespread types of cancer affecting females, and therefore, early diagnosis is critical. BC is a complex heterogeneous disease affected by several key pathways. Among these, WNT proteins and their frizzled receptors (FZD) have been demonstrated to be crucial in regulating a number of cellular and molecular events in BC tumorigenesis. The role of the WNT receptor, FZD8, in BC has received minimal attention; for that reason, the present study examined the prognostic value of its protein expression pattern in a BC cohort. FZD8 cytoplasmic expression pattern analysis revealed that ~38% of the primary samples presented with a high expression profile, whereas ~63% of the samples had a low expression profile. Overall, ~46% of the malignant tissues in the lymph node-positive samples exhibited an increased FZD8 cytoplasmic expression, whereas 54% exhibited low expression levels. An increased expression of FZD8 was associated with several clinicopathological characteristics of the patients, including a low survival rate, tumor vascular invasion, tumor size and grade, and molecular subtypes. Affymetrix microarray triple-negative BC datasets were analyzed and compared with healthy breast tissues in order to predict the potential interfering microRNAs (miRNAs) in the WNT/FZD8 signaling pathway. A total of 29 miRNAs with the potential to interact with the WNT/FZD8 signaling pathway were identified, eight of which exhibited a significant prediction score. The target genes for each predicted miRNA were identified. On the whole, the findings of the present study suggest that FZD8 is a potential prognostic marker for BC, shedding some light onto the silencing mechanisms involved in the complex BC signaling.

CWH43 Is a Novel Tumor Suppressor Gene with Negative Regulation of TTK in Colorectal Cancer

Colorectal cancer (CRC) ranks among the most prevalent forms of cancer globally, and its late-stage survival outcomes are less than optimal. A more nuanced understanding of the underlying mechanisms behind CRC's development is crucial for enhancing patient survival rates. Existing research suggests that the expression of Cell Wall Biogenesis 43 C-Terminal Homolog (CWH43) is reduced in CRC. However, the specific role that CWH43 plays in cancer progression remains ambiguous. Our research seeks to elucidate the influence of CWH43 on CRC's biological behavior and to shed light on its potential as a therapeutic target in CRC management. Utilizing publicly available databases, we examined the expression levels of CWH43 in CRC tissue samples and their adjacent non-cancerous tissues. Our findings indicated lower levels of both mRNA and protein expressions of CWH43 in cancerous tissues. Moreover, we found that a decrease in CWH43 expression correlates with poorer prognoses for CRC patients. In vitro experiments demonstrated that the suppression of CWH43 led to increased cell proliferation, migration, and invasiveness, while its overexpression had inhibitory effects. Further evidence from xenograft models showed enhanced tumor growth upon CWH43 silencing. Leveraging data from The Cancer Genome Atlas (TCGA), our Gene Set Enrichment Analysis (GSEA) indicated a positive relationship between low CWH43 expression and the activation of the epithelial-mesenchymal Transition (EMT) pathway. We conducted RNA sequencing to analyze gene expression changes under both silenced and overexpressed CWH43 conditions. By identifying core genes and executing KEGG pathway analysis, we discovered that CWH43 appears to have regulatory influence over the TTK-mediated cell cycle. Importantly, inhibition of TTK counteracted the tumor-promoting effects caused by CWH43 downregulation. Our findings propose that the decreased expression of CWH43 amplifies TTK-mediated cell cycle activities, thus encouraging tumor growth. This newly identified mechanism offers promising avenues for targeted CRC treatment strategies.

Immune-related biomarkers predict the prognosis and immune response of breast cancer based on bioinformatic analysis and machine learning

Breast cancer (BC) is the malignancy with the highest mortality rate among women, identification of immune-related biomarkers facilitates precise diagnosis and improvement of the survival rate in early-stage BC patients. 38 hub genes significantly positively correlated with tumor grade were identified based on weighted gene coexpression network analysis (WGCNA) by integrating the clinical traits and transcriptome analysis. Six candidate genes were screened from 38 hub genes basing on least absolute shrinkage and selection operator (LASSO)-Cox and random forest. Four upregulated genes (CDC20, CDCA5, TTK and UBE2C) were identified as biomarkers with the log-rank p < 0.05, in which high expression levels of them showed a poor overall survival (OS) and recurrence-free survival (RFS). A risk model was finally constructed using LASSO-Cox regression coefficients and it possessed superior capability to identify high risk patients and predict OS (p < 0.0001, AUC at 1-, 3- and 5-years are 0.81, 0.73 and 0.79, respectively). Decision curve analysis demonstrated risk score was the best prognostic predictor, and low risk represented a longer survival time and lower tumor grade. Importantly, multiple immune cell types and immunotherapy targets were observed increase in expression levels in high-risk group, most of which were significantly correlated with four genes. In summary, the immune-related biomarkers could accurately predict the prognosis and character the immune responses in BC patients. In addition, the risk model is conducive to the tiered diagnosis and treatment of BC patients.

Comprehensive analysis of the expression and prognosis for RAI2: A promising biomarker in breast cancer

Introduction

Retinoic acid-induced 2 (RAI2) was initially related to cell differentiation and induced by retinoic acid. RAI2 has been identified as an emerging tumor suppressor in breast cancer and colorectal cancer.

Methods

In this study, we performed systematic analyses of RAI2 in breast cancer. Meta-analysis and Kaplan-Meier survival curves were applied to identify the survival prediction potential of RAI2. Moreover, the association between RAI2 expression and the abundance of six tumor-infiltrating immune cells was investigated by TIMER, including B cells, CD8+ T cells, CD4+ T cells, B cells, dendritic cells, neutrophils, and macrophages. The expression profiles of high and low RAI2 mRNA levels in GSE7390 were compared to identify differentially expressed genes (DEGs) and the biological function of these DEGs was analyzed by R software, which was further proved in GSE7390.

Results

Our results showed that the normal tissues had more RAI2 expression than breast cancer tissues. Patients with high RAI2 expression were related to a favorable prognosis and more immune infiltrates. A total of 209 DEGs and 182 DEGs were identified between the expression profiles of high and low RAI2 mRNA levels in the GSE7390 and GSE21653 databases, respectively. Furthermore, Gene Ontology (GO) enrichment indicated that these DEGs from two datasets were both mainly distributed in “biological processes” (BP), including “organelle fission” and “nuclear division”. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis demonstrated that these DEGs from two datasets were both significantly enriched in the “cell cycle”. Common hub genes between the DEGs in GSE7390 and GSE21653 were negatively associated with RAI2 expression, including CCNA2, MAD2L1, MELK, CDC20, and CCNB2.

Discussions

These results above suggested that RAI2 might play a pivotal role in preventing the initiation and progression of breast cancer. The present study may contribute to understanding the molecular mechanisms of RAI2 and enriching biomarkers to predict patient prognosis in breast cancer.

Ethnic and racial-specific differences in levels of centrosome-associated mitotic kinases, proliferative and epithelial-to-mesenchymal markers in breast cancers

Molecular epidemiology evidence indicates racial and ethnic differences in the aggressiveness and survival of breast cancer. Hispanics/Latinas (H/Ls) and non-Hispanic Black women (NHB) are at higher risk of breast cancer (BC)-related death relative to non-Hispanic white (NHW) women in part because they are diagnosed with hormone receptor-negative (HR) subtype and at higher stages. Since the cell cycle is one of the most commonly deregulated cellular processes in cancer, we propose that the mitotic kinases TTK (or Mps1), TBK1, and Nek2 could be novel targets to prevent breast cancer progression among NHBs and H/Ls. In this study, we calculated levels of TTK, p-TBK1, epithelial (E-cadherin), mesenchymal (Vimentin), and proliferation (Ki67) markers through immunohistochemical (IHC) staining of breast cancer tissue microarrays (TMAs) that includes samples from 6 regions in the Southeast of the United States and Puerto Rico -regions enriched with NHB and H/L breast cancer patients. IHC analysis showed that TTK, Ki67, and Vimentin were significantly expressed in triple-negative (TNBC) tumors relative to other subtypes, while E-cadherin showed decreased expression. TTK correlated with all of the clinical variables but p-TBK1 did not correlate with any of them. TCGA analysis revealed that the mRNA levels of multiple mitotic kinases, including TTK, Nek2, Plk1, Bub1, and Aurora kinases A and B, and transcription factors that are known to control the expression of these kinases (e.g. FoxM1 and E2F1-3) were upregulated in NHBs versus NHWs and correlated with higher aneuploidy indexes in NHB, suggesting that these mitotic kinases may be future novel targets for breast cancer treatment in NHB women.

Cancer informatics analysis indicates high CHAC2 associated with unfavorable prognosis in breast cancer

Breast cancer remains the most commonly diagnosed cancer worldwide and exhibits a poor prognosis. The induction of genetic changes deregulates several genes that increase the disposal towards this life-threatening disease. CHAC2, a member of the glutathione degrading enzyme family has been shown to suppress gastric and colorectal cancer progression, however, the expression of CHAC2 in breast cancer has not been reported. We did an analysis of CHAC2 expression in breast cancer patients from various online tools like UALCAN, GEPIA2, GENT2, TIMER2, and bcGenExminer v4.8. Further, we used the Kaplan-Meier plotter to establish the significance of CHAC2 in BC patient survival and prognosis while TISIDB and TIMER databases were used to investigate the filtration of immune cells. The results showed that CHAC2 levels were high in breast cancer patients and elevated CHAC2 was associated with low overall survival. Taken together, the results of the present study show that like its paralog CHAC1, CHAC2 may also be an important biomarker and could have a potential therapeutic implication in breast cancer.

Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis

Triple-negative breast cancer (TNBC) has a high degree of malignancy, lack of effective diagnosis and treatment, and poor prognosis. Bioinformatics methods are used to screen the hub genes and signal pathways involved in the progress of TNBC to provide reliable biomarkers for the diagnosis and treatment of TNBC. Download the raw data of four TNBC-related datasets from the Gene Expression Omnibus (GEO) database and use them for bioinformatics analysis. GEO2R tool was used to analyze and identify differentially expressed (DE) mRNAs. DAVID database was used to carry out gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genome Pathways (KEGG) signal pathway enrichment analysis for DE mRNAs. STRING database and Cytoscape were used to build DE mRNAs protein-protein interaction (PPI) network diagram and visualize PPI network, respectively. Through cytoHubba, cBioPortal database, Kaplan-Meier mapper database, Gene Expression Profiling Interactive Analysis (GEPIA) Database, UALCAN Database, The Cancer Genome Atlas (TCGA) database, Tumor Immunity Estimation Resource identify hub genes. Perform qRT-PCR, Human Protein Atlas analysis, mutation analysis, survival analysis, clinical-pathological characteristics, and infiltrating immune cell analysis. 22 DE mRNAs were identified from the four datasets, including 16 upregulated DE mRNAs and six downregulated DE mRNAs. Enrichment analysis of the KEGG showed that DE mRNAs were principally enriched in pathways in cancer, mismatch repair, cell cycle, platinum drug resistance, breast cancer. Six hub genes were screened based on the PPI network diagram of DE mRNAs. Survival analysis found that TOP2A, CCNA2, PCNA, MSH2, CDK6 are related to the prognosis of TNBC. In addition, mutations, clinical indicators, and immune infiltration analysis show that these five hub genes play an important role in the progress of TNBC and immune monitoring. Compared with MCF-10A, MCF-7, and SKBR-3 cells, TOP2A, PCNA, MSH2, and CDK6 were significantly upregulated in MDA-MB-321 cells. Compared with normal, luminal, and Her-2 positive tissues, CCNA2, MSH2, and CDK6 were significantly upregulated in TNBC. Through comparative analysis of GEO datasets related to colorectal cancer and lung adenocarcinoma, it was determined that these five hub genes were unique differentially expressed genes of TNBC. At last, the hub genes related to the progression, prognosis, and immunity of TNBC have been successfully screened. They are indeed specific to TNBC as prognostic features. They can be used as potential markers for the prognosis of TNBC and provide potential therapeutic targets.

ELIMINATOR: essentiality analysis using multisystem networks and integer programming

A gene is considered as essential when it is indispensable for cells to grow and replicate in a certain environment. However, gene essentiality is not a structural property but rather a contextual one, which depends on the specific biological conditions affecting the cell. This circumstantial essentiality of genes is what brings the attention of scientist since we can identify genes essential for cancer cells but not essential for healthy cells. This same contextuality makes their identification extremely challenging. Huge experimental efforts such as Project Achilles where the essentiality of thousands of genes is measured together with a plethora of molecular data (transcriptomics, copy number, mutations, etc.) in over one thousand cell lines can shed light on the causality behind the essentiality of a gene in a given environment. Here, we present an in-silico method for the identification of patient-specific essential genes using constraint-based modelling (CBM). Our method expands the ideas behind traditional CBM to accommodate multisystem networks. In essence, it first calculates the minimum number of lowly expressed genes required to be activated by the cell to sustain life as defined by a set of requirements; and second, it performs an exhaustive in-silico gene knockout to find those that lead to the need of activating additional lowly expressed genes. We validated the proposed methodology using a set of 452 cancer cell lines derived from the Cancer Cell Line Encyclopedia where an exhaustive experimental large-scale gene knockout study using CRISPR (Achilles Project) evaluates the impact of each removal. We also show that the integration of different essentiality predictions per gene, what we called Essentiality Congruity Score, reduces the number of false positives. Finally, we explored our method in a breast cancer patient dataset, and our results showed high concordance with previous publications. These findings suggest that identifying genes whose activity is fundamental to sustain cellular life in a patient-specific manner is feasible using in-silico methods. The patient-level gene essentiality predictions can pave the way for precision medicine by identifying potential drug targets whose deletion can induce death in tumour cells.

Autocrine pro-legumain promotes breast cancer metastasis via binding to integrin αvβ3

Tumor metastasis is the leading cause of cancer-associated mortality. Unfortunately, the underlying mechanism of metastasis is poorly understood. Expression of legumain (LGMN), an endo-lysosomal cysteine protease, positively correlates with breast cancer metastatic progression and poor prognosis. Here, we report that LGMN is secreted in the zymogen form by motile breast cancer cells. Through binding to cell surface integrin αvβ3 via an RGD motif, the autocrine pro-LGMN activates FAK-Src-RhoA signaling in cancer cells and promotes cancer cell migration and invasion independent of LGMN protease activity. Either silencing LGMN expression or mutationally abolishing pro-LGMN‒αvβ3 interaction significantly inhibits cancer cell migration and invasion in vitro and breast cancer metastasis in vivo. Finally, we developed a monoclonal antibody against LGMN RGD motif, which blocks pro-LGMN‒αvβ3 binding, and effectively suppresses cancer cell migration and invasion in vitro and breast cancer metastasis in vivo. Thus, disruption of pro-LGMN‒integrin αvβ3 interaction may be a potentially promising strategy for treating breast cancer metastasis.

Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer

Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein-protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.

Translocon-associated protein subunit SSR3 determines and predicts susceptibility to paclitaxel in breast cancer and glioblastoma

PURPOSE

Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for glioblastomas (GBMs). Despite the widespread use of PTX for breast cancer, and the initiative to repurpose this drug for gliomas, there are no predictive biomarkers to inform which patients will likely benefit from this therapy.

EXPERIMENTAL DESIGN

To identify predictive biomarkers for susceptibility to PTX, we performed a genome-wide CRISPR knock-out (KO) screen using human glioma cells. The genes whose KO was most enriched in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort using progression-free survival.

RESULTS

Combination of CRISPR screen results with outcomes from taxane-treated breast cancer patients led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with susceptibility to PTX in breast cancer cells, glioma cells and in multiple intracranial glioma xenografts models. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. Mechanistically, SSR3 confers susceptibility to PTX through regulation of phosphorylation of ER stress sensor IRE1α.

CONCLUSION

Our hypothesis generating study showed SSR3 as a putative biomarker for susceptibility to PTX, warranting its prospective clinical validation.

Low level of Fibrillarin, a ribosome biogenesis factor, is a new independent marker of poor outcome in breast cancer

Background

A current critical need remains in the identification of prognostic and predictive markers in early breast cancer. It appears that a distinctive trait of cancer cells is their addiction to hyperactivation of ribosome biogenesis. Thus, ribosome biogenesis might be an innovative source of biomarkers that remains to be evaluated.

Methods

Here, fibrillarin (FBL) was used as a surrogate marker of ribosome biogenesis due to its essential role in the early steps of ribosome biogenesis and its association with poor prognosis in breast cancer when overexpressed. Using 3,275 non-metastatic primary breast tumors, we analysed FBL mRNA expression levels and protein nucleolar organisation. Usage of TCGA dataset allowed transcriptomic comparison between the different FBL expression levels-related breast tumours.

Results

We unexpectedly discovered that in addition to breast tumours expressing high level of FBL, about 10% of the breast tumors express low level of FBL. A correlation between low FBL mRNA level and lack of FBL detection at protein level using immunohistochemistry was observed. Interestingly, multivariate analyses revealed that these low FBL tumors displayed poor outcome compared to current clinical gold standards. Transcriptomic data revealed that FBL expression is proportionally associated with distinct amount of ribosomes, low FBL level being associated with low amount of ribosomes. Moreover, the molecular programs supported by low and high FBL expressing tumors were distinct.

Conclusion

Altogether, we identified FBL as a powerful ribosome biogenesis-related independent marker of breast cancer outcome. Surprisingly we unveil a dual association of the ribosome biogenesis FBL factor with prognosis. These data suggest that hyper- but also hypo-activation of ribosome biogenesis are molecular traits of distinct tumors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09552-x.

First-in-man, first-in-class phase I study with the monopolar spindle 1 kinase inhibitor S81694 administered intravenously in adult patients with advanced, metastatic solid tumours

BACKGROUND

S81694 is an inhibitor of monopolar spindle 1 kinase, a target expressed in proliferating cells. CL1-81694-001 was the first-in-human study aiming at identifying a safe dosing schedule in solid tumour patients.

PATIENTS AND METHODS

This trial was based on inter-individual dose-escalation of single agent S81694 in cohorts of ≥3 patients to assess the safety and tolerability and determine dose-limiting toxicities (DLTs), maximum tolerated dose (MTD) and recommended phase II dose (RP2D), with S81694 given on days 1,8,15 of a 28-day cycle as 1-h infusion.

RESULTS

38 patients were treated at doses ranging from 4 to 135 mg/m²/week; 144 cycles were administered (median 2/patient; range 1-32 cycles). Patients discontinued treatment for disease progression (78.9%), adverse events (AE; 18.4%) or withdrawal of consent (2.6%). Treatment modifications occurred in 22 patients (57.9%; 49 cycles). Common treatment-emergent AEs were fatigue (22 patients;57.9%), anaemia (17;44.7%) and nausea (12;31.6%). Haematological toxicity was mild, with Grade 3 anaemia observed in three patients and neutropenia mainly seen at the 135 mg/m² dose level. Three first cycle DLTs included G3 anaemia (4 mg/m² dose), G4 hypertension (20 mg/m²), G3 fatigue (135 mg/m²). MTD was not reached due to premature discontinuation of enrolment based on a sponsor decision. Among 35 patients evaluable for response, one (renal cell carcinoma) had a complete response, one (hepatocellular carcinoma) had a transient decrease of target lesions and 13 had stable disease. Seven patients remained on study for ≥6 cycles, two at the 135 mg/m² dose.

CONCLUSIONS

S81694 can be administered safely as a single agent in adults with solid tumours on days 1,8,15 of a 28-day cycle up to a dose of 135 mg/m²/week without reaching MTD. The RP2D was not defined due to the prioritization of the use of S81694 in combination with cytotoxic agents, based on emerging preclinical data.

TRIAL REGISTRATION

EudraCT number: 2014-002023-10; ISRCTN registry ISRCTN35641359.

Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes

Known genes in the breast cancer study literature could not be confirmed whether they are vital to breast cancer formations due to lack of convincing accuracy, although they may be biologically directly related to breast cancer based on present biological knowledge. It is hoped vital genes can be identified with the highest possible accuracy, for example, 100% accuracy and convincing causal patterns beyond what has been known in breast cancer. One hope is that finding gene-gene interaction signatures and functional effects may solve the puzzle. This research uses a recently developed competing linear factor analysis method in differentially expressed gene detection to advance the study of breast cancer formation. Surprisingly, 3 genes are detected to be differentially expressed in TNBC and non-TNBC (Her2, Luminal A, Luminal B) samples with 100% sensitivity and 100% specificity in 1 study of triple-negative breast cancers (TNBC, with 54 675 genes and 265 samples). These 3 genes show a clear signature pattern of how TNBC patients can be grouped. For another TNBC study (with 54 673 genes and 66 samples), 4 genes bring the same accuracy of 100% sensitivity and 100% specificity. Four genes are found to have the same accuracy of 100% sensitivity and 100% specificity in 1 breast cancer study (with 54 675 genes and 121 samples), and the same 4 genes bring an accuracy of 100% sensitivity and 96.5% specificity in the fourth breast cancer study (with 60 483 genes and 1217 samples). These results show the 4-gene-based classifiers are robust and accurate. The detected genes naturally classify patients into subtypes, for example, 7 subtypes. These findings demonstrate the clearest gene-gene interaction patterns and functional effects with the smallest numbers of genes and the highest accuracy compared with findings reported in the literature. The 4 genes are considered to be essential for breast cancer studies and practice. They can provide focused, targeted researches and precision medicine for each subtype of breast cancer. New breast cancer disease types may be detected using the classified subtypes, and hence new effective therapies can be developed.

Upregulation of BAX and caspase-3, as well as downregulation of Bcl-2 during treatment with indeno[1,2-b]quinoxalin derivatives, mediated apoptosis in human cancer cells

Cancer is the world's foremost cause of death. There are over 100 different forms of cancer. Cancers are frequently named after the organs or tissues in which they develop. As a part of our aim to develop promising anticancer agents, a series of new indeno[1,2-b]quinoxaline derivatives were synthesized. All of the synthesized compounds were tested for anticancer activity in vitro in three human cancer cell lines: the HCT-116 colon cancer cell line, the HepG-2 liver cancer cell line, and the MCF-7 breast cancer cell line. Among the tested derivatives, 2, 3, 5, 12, 21, and 22 showed exceptional antiproliferative activities against the three tested cell lines compared to the reference standard imatinib. These compounds were, therefore, selected for further investigations. Evaluation of their cytotoxicity against a normal human cell line (WI-38) was performed, to ensure their safety and selectivity (IC₅₀  > 92 μM). Then, induction of apoptosis by the most active compounds was found to be accomplished by downregulation of Bcl-2 and upregulation of BAX and caspase-3. After that, the most promising apoptotic compound that increases the caspase-3 and BAX expression and downregulates Bcl-2 activity (3) was assessed for its impact on the cell cycle distribution in HepG-2 cells: The most potent derivative (3) induced cell cycle arrest at the G2/M phase. Finally, in silico evaluation of the ADME properties indicated that compound 3 is orally bioavailable and can be readily synthesized on a large scale.

PRMT1 Regulates EGFR and Wnt Signaling Pathways and Is a Promising Target for Combinatorial Treatment of Breast Cancer

Simple Summary

Patients with triple-negative breast cancer (TNBC) respond well to chemotherapy initially but are prone to relapse. Searching for new therapeutic targets, we found that PRMT1 is highly expressed in TNBC tumor samples and is essential for breast cancer cell survival. Furthermore, this study proposes that targeting PRMT1 in combination with chemotherapies could improve the survival outcome of TNBC patients.

Abstract

Identifying new therapeutic strategies for triple-negative breast cancer (TNBC) patients is a priority as these patients are highly prone to relapse after chemotherapy. Here, we found that protein arginine methyltransferase 1 (PRMT1) is highly expressed in all breast cancer subtypes. PRMT1 depletion decreases cell survival by inducing DNA damage and apoptosis in various breast cancer cell lines. Transcriptomic analysis and chromatin immunoprecipitation revealed that PRMT1 regulates the epidermal growth factor receptor (EGFR) and the Wnt signaling pathways, reported to be activated in TNBC. PRMT1 enzymatic activity is also required to stimulate the canonical Wnt pathway. Type I PRMT inhibitors decrease breast cancer cell proliferation and show anti-tumor activity in a TNBC xenograft model. These inhibitors display synergistic interactions with some chemotherapies used to treat TNBC patients as well as erlotinib, an EGFR inhibitor. Therefore, targeting PRMT1 in combination with these chemotherapies may improve existing treatments for TNBC patients.

Association of High Expression of Mitochondrial Fission Regulator 2 with Poor Survival of Patients with Esophageal Squamous Cell Carcinoma

Mitochondrial fission regulator 2 (MTFR2) is associated with mitochondrial fission, while few studies have assessed the associations between MTFR2 expression and clinical characteristics or prognosis of esophageal squamous cell carcinoma (ESCC). In this study, we compared the expression of MTFR2 in 6 ESCC tumors and relative normal tissues by immunohistochemistry (IHC). To assess the effect of MTFR2 expression on clinicopathologic characteristics and survival, 115 paraffin embedded ESCC tissue samples were assessed by IHC staining. Furthermore, the association between clinicopathological properties and MTFR2 expression in patients with ESCC was examined. The survival analysis was performed using the Cox regression models. We found that MTFR2 expression was significantly increased in ESCC tumors compared with normal esophageal epithelial cells. IHC analysis of 115 paraffin embedded ESCC tumor specimens of the patients showed that the expression of MTFR2 was significantly associated with clinical stage (P < 0.001), tumor classification (P < 0.001), histological grade (P < 0.001), and other clinicopathological characteristics. Both univariate and multivariate analyses showed that MTFR2 expression was inversely correlated with the survival of ESCC patients. In conclusion, the expression of MTFR2 is significantly associated with clinicopathologic characteristics and prognosis of ESCC. Thus, MTFR2 expression could serve as a potentially important prognostic biomarker and clinical target for patients with ESCC.

Hsp90 regulates the tumorigenic function of tyrosine protein kinase in osteosarcoma

Despite recent advances in diagnosis and treatment, osteosarcoma remains as the most common bone cancer in children and is associated with poor prognosis. Growing evidence has supported dysregulation of threonine and tyrosine protein kinase (TTK) expression as a hallmark of multiple cancers, however, its function in osteosarcoma remains to be elucidated. In the present study, we found that TTK was frequently overexpressed in osteosarcoma and associated with increased tumour growth and progression. Moreover, using both in vitro and in vivo assays, we provided evidence that TTK level was regulated by a molecular chaperone, heat shock protein 90 (Hsp90). Hsp90 directly interacted with TTK and prevents proteasome-dependent TTK degradation, leading to the accumulation of TTK in osteosarcoma cells. Elevated TTK promoted cancer cell proliferation and survival by activating cell-cycle progression and inhibiting apoptosis. Consistently, depletion of TTK by Hsp90 inhibition induced cell-cycle arrest, generated aneuploidy and eventually resulted in apoptotic cancer cell death. Together, our study revealed an important Hsp90-TTK regulatory axis in osteosarcoma cells to promote cancer cell growth and survival. These findings expand our knowledge on osteosarcoma pathogenesis and offer novel therapeutic options for clinical practice.

The Expression and Prognostic Value of SUMO1-Activating Enzyme Subunit 1 and Its Potential Mechanism in Triple-Negative Breast Cancer

Background: Triple-negative breast cancer (TNBC) is the most invasive and metastatic subtype of breast cancer. SUMO1-activating enzyme subunit 1 (SAE1), an E1-activating enzyme, is indispensable for protein SUMOylation. SAE1 has been found to be a relevant biomarker for progression and prognosis in several tumor types. However, the role of SAE1 in TNBC remains to be elucidated.

Methods: In the research, the mRNA expression of SAE1 was analyzed via the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database. Cistrome DB Toolkit was used to predict which transcription factors (TFs) are most likely to increase SAE1 expression in TNBC. The correlation between the expression of SAE1 and the methylation of SAE1 or quantity of tumor-infiltrating immune cells was further invested. Single-cell analysis, using CancerSEA, was performed to query which functional states are associated with SAE1 in different cancers in breast cancer at the single-cell level. Next, weighted gene coexpression network (WGCNA) was applied to reveal the highly correlated genes and coexpression networks of SAE1 in TNBC patients, and a prognostic model containing SAE1 and correlated genes was constructed. Finally, we also examined SAE1 protein expression of 207 TNBC tissues using immunohistochemical (IHC) staining.

Results: The mRNA and protein expression of SAE1 were increased in TNBC tissues compared with adjacent normal tissues, and the protein expression of SAE1 was significantly associated with overall survival (OS) and disease-free survival (DFS). Correlation analyses revealed that SAE1 expression was positively correlated with forkhead box M1 (FOXM1) TFs and negatively correlated with SAE1 methylation site (cg14042711) level. WGCNA indicated that the genes coexpressed with SAE1 belonged to the green module containing 1,176 genes. Through pathway enrichment analysis of the module, 1,176 genes were found enriched in cell cycle and DNA repair. Single-cell analysis indicated that SAE1 and its coexpression genes were associated with cell cycle, DNA damage, DNA repair, and cell proliferation. Using the LASSO COX regression, a prognostic model including SAE1 and polo-like kinase 1 (PLK1) was built to accurately predict the likelihood of DFS in TNBC patients.

Conclusion: In conclusion, we comprehensively analyzed the mRNA and protein expression, prognosis, and interaction genes of SAE1 in TNBC and constructed a prognostic model including SAE1 and PLK1. These results might be important for better understanding of the role of SAE1 in TNBC. In addition, DNA methyltransferase and TFs inhibitor treatments targeting SAE1 might improve the survival of TNBC patients.

Frequent expression of a novel cancer testis antigen, protein kinase human monopolar spindle 1 (hMps1/TTK) in human urinary bladder transitional cell carcinoma

Urothelial bladder cancer (UBC) is a frequently occurring malignancy of the urinary tract. The present study was undertaken to evaluate the mRNA and immunohistochemical (IHC) expression of protein kinase human monopolar spindle 1 (hMps1/TTK) gene in transitional cell carcinoma (TCC) of the bladder and correlate its expression with the clinicopathological characteristics of patients. In the present study, quantitative real-time reverse-transcriptase polymerase chain reaction (qRT-PCR) was used to evaluate TTK mRNA expression in TCC. IHC analysis of TTK was also evaluated. Independent Student's t, ANOVA and chi-square (χ²) tests were used to analyze the data statistically. The frequency of TTK mRNA over expression was detected in 50% of UBC (38/76) by qRT-PCR. Relative mean fold expression of TTK mRNA was found significantly (p < 0.05) higher in muscle-invasive bladder cancer (MIBC) as compared to non-muscle-invasive bladder cancer (NMIBC) patients (8.96 ± 4.51 vs. 5.64 ± 3.53, p = 0.03). Moreover, IHC reveals heterogenous immunostaining pattern of TTK in TCC tissues. The frequency of TTK protein over expression was detected in 56.9% (37 of 65) UBC patients. No significant IHC expression of TTK was detected among adjacent noncancerous tissues (ANCTs) and benign prostatic hyperplasia (BPH) used as control. Collectively our study observations conclude that TTK is a novel cancer/testis antigen (CTA) as a diagnostic marker for early diagnosis of UBC.

Structure-Guided Optimization Provides a Series of TTK Protein Inhibitors with Potent Antitumor Activity

TTK is an essential spindle assembly checkpoint enzyme in many organisms. It plays a central role in tumor cell proliferation and is aberrantly overexpressed in a wide range of tumor types. We recently reported on a series of potent and selective TTK inhibitors with strong antiproliferative activity in triple negative breast cancer (TNBC) cell lines (8: TTK IC₅₀ = 3.0 nM; CAL-51 IC₅₀ = 84.0 nM). Inspired by previously described potent tricyclic TTK inhibitor 6 (TTK IC₅₀ = 0.9 nM), we embarked on a structure-enabled design and optimization campaign to identify an improved series with excellent potency, TTK selectivity, solubility, CYP inhibition profile, and in vivo efficacy in a TNBC xenograft model. These efforts culminated in the discovery of 25 (TTK IC₅₀ = 3.0 nM; CAL-51 IC₅₀ = 16.0 nM), which showed significant single-agent efficacy when dosed iv in a TNBC xenograft model without body weight loss.

Identification of Potential Biomarkers From Hepatocellular Carcinoma With MT1 Deletion

Background: Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide. Metallothioneins (MTs) are metal-binding proteins involved in multiple biological processes such as metal homeostasis and detoxification, as well as in oncogenesis. Copy number variation (CNV) plays a vital role in pathogenesis and carcinogenesis. Nevertheless, there is no study on the role of MT1 CNV in HCC. Methods: Array-based Comparative Genomic Hybridization (aCGH) analysis was performed to obtain the CNV data of 79 Guangxi HCC patients. The prognostic effect of MT1-deletion was analyzed by univariate and multivariate Cox regression analysis. The differentially expressed genes (DEGs) were screened based on The Gene Expression Omnibus database (GEO) and the Liver Hepatocellular Carcinoma of The Cancer Genome Atlas (TCGA-LIHC). Then function and pathway enrichment analysis, protein-protein interaction (PPI) and hub gene selection were applied on the DEGs. Lastly, the hub genes were validated by immunohistochemistry, tissue expression and prognostic analysis. Results: The MT1-deletion was demonstrated to affect the prognosis of HCC and can act as an independent prognostic factor. 147 common DEGs were screened. The most significant cluster of DEGs identified by Molecular Complex Detection (MCODE) indicated that the expression of four MT1s were down-regulated. MT1X and other five hub genes (TTK, BUB1, CYP3A4, NR1I2, CYP8B1) were associated with the prognosis of HCC. TTK, could affect the prognosis of HCC with MT1-deletion and non-deletion. NR1I2, CYP8B1, and BUB1 were associated with the prognosis of HCC with MT1-deletion. Conclusions: In the current study, we demonstrated that MT1-deletion can be an independent prognostic factor in HCC. We identified TTK, BUB1, NR1I2, CYP8B1 by processing microarray data, for the first time revealed the underlying function of MT1 deletion in HCC, MT1-deletion may influence the gene expression in HCC, which may be the potential biomarkers for HCC with MT1 deletion.

Identification of Potential Therapeutic Genes and Pathways in Phytoestrogen Emodin Treated Breast Cancer Cell Lines via Network Biology Approaches

Phytoestrogens have been investigated for their potential anti-tumorigenic effects in various cancers including breast cancer. Emodin being a phytoestrogen shows anti-carcinogenic properties especially in estrogen receptor positive (ER+) breast cancers. The aim of this study is to identify the molecular mechanism and related biological pathways in both (ER+) MCF-7 and (ER-) MDA-MB-231 breast cancer cell lines upon Emodin treatment via microarray analysis in order to find out therapeutic biomarkers. In both cell lines, first differentially expressed genes were identified, then gene ontology and functional pathway enrichment analyses were performed. Genes regulated through multiple pathways were studied together with literature and a gene cluster was determined for each cell line. Further GeneMANIA and STRING databases were used to study the interactions within the related gene clusters. The results showed that, the genes which are related to cell cycle were significantly regulated in both cell lines. Also, Forkhead Box O1-related genes were found to be prominent in MCF-7 cells. In MDA-MB-231 cells, spindle attachment checkpoint mechanism-related genes were regulated, remarkably. As a result, novel gene regulations reported in this study in response to Emodin will give more information about its metabolism and antiproliferative effect, especially in ER + cells.

CuBlock: a cross-platform normalization method for gene-expression microarrays

Motivation

Cross-(multi)platform normalization of gene-expression microarray data remains an unresolved issue. Despite the existence of several algorithms, they are either constrained by the need to normalize all samples of all platforms together, compromising scalability and reuse, by adherence to the platforms of a specific provider, or simply by poor performance. In addition, many of the methods presented in the literature have not been specifically tested against multi-platform data and/or other methods applicable in this context. Thus, we set out to develop a normalization algorithm appropriate for gene-expression studies based on multiple, potentially large microarray sets collected along multiple platforms and at different times, applicable in systematic studies aimed at extracting knowledge from the wealth of microarray data available in public repositories; for example, for the extraction of Real-World Data to complement data from Randomized Controlled Trials. Our main focus or criterion for performance was on the capacity of the algorithm to properly separate samples from different biological groups.

Results

We present CuBlock, an algorithm addressing this objective, together with a strategy to validate cross-platform normalization methods. To validate the algorithm and benchmark it against existing methods, we used two distinct datasets, one specifically generated for testing and standardization purposes and one from an actual experimental study. Using these datasets, we benchmarked CuBlock against ComBat (Johnson et al., 2007), UPC (Piccolo et al., 2013), YuGene (Lê Cao et al., 2014), DBNorm (Meng et al., 2017), Shambhala (Borisov et al., 2019) and a simple log₂ transform as reference. We note that many other popular normalization methods are not applicable in this context. CuBlock was the only algorithm in this group that could always and clearly differentiate the underlying biological groups after mixing the data, from up to six different platforms in this study.

Availability and implementation

CuBlock can be downloaded from https://www.mathworks.com/matlabcentral/fileexchange/77882-cublock.

Supplementary information

Supplementary data are available at Bioinformatics online.

N-(6-Chloro-3-nitropyridin-2-yl)-5-(1-methyl-1H-pyrazol-4-yl)isoquinolin-3-amine

Here we describe the synthesis of N-(6-chloro-3-nitropyridin-2-yl)5-(1-methyl-1H-pyrazol-4-yl)isoquinolin-3-amine via a three-step procedure including a Buchwald–Hartwig arylamination with benzophenone imine and a highly regioselective nucleophilic aromatic substitution. The title compound was analyzed by nuclear magnetic resonance spectroscopy (1H, 13C, HSQC, HMBC, COSY, DEPT90 and NOESY), high resolution mass spectrometry (ESI-TOF-HRMS) and infrared spectroscopy (ATR-IR) and its structure was confirmed by single crystal X-ray diffraction. The inhibitory potency of the title compound was evaluated for selected kinases harboring a rare cysteine in the hinge region (MPS1, MAPKAPK2 and p70S6Kβ/S6K2).

Ribosomal RNA 2'O-methylation as a novel layer of inter-tumour heterogeneity in breast cancer

Recent epitranscriptomics studies unravelled that ribosomal RNA (rRNA) 2′O-methylation is an additional layer of gene expression regulation highlighting the ribosome as a novel actor of translation control. However, this major finding lies on evidences coming mainly, if not exclusively, from cellular models. Using the innovative next-generation RiboMeth-seq technology, we established the first rRNA 2′O-methylation landscape in 195 primary human breast tumours. We uncovered the existence of compulsory/stable sites, which show limited inter-patient variability in their 2′O-methylation level, which map on functionally important sites of the human ribosome structure and which are surrounded by variable sites found from the second nucleotide layers. Our data demonstrate that some positions within the rRNA molecules can tolerate absence of 2′O-methylation in tumoral and healthy tissues. We also reveal that rRNA 2′O-methylation exhibits intra- and inter-patient variability in breast tumours. Its level is indeed differentially associated with breast cancer subtype and tumour grade. Altogether, our rRNA 2′O-methylation profiling of a large-scale human sample collection provides the first compelling evidence that ribosome variability occurs in humans and suggests that rRNA 2′O-methylation might represent a relevant element of tumour biology useful in clinic. This novel variability at molecular level offers an additional layer to capture the cancer heterogeneity and associates with specific features of tumour biology thus offering a novel targetable molecular signature in cancer.

Identification of grade-related genes and construction of a robust genomic-clinicopathologic nomogram for predicting recurrence of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common tumor in the urinary system with a high recurrence rate. The individualized treatment and follow-up after surgery is the key to a successful outcome. Currently, the surveillance strategies are mainly depending on tumor stage and grade. Previous evidence has proved that tumor grade was a significant and independent risk factor of BC recurrence. Exploring the grade-related genes may provide us a new approach to predict prognosis and guide the post-operative treatment in BC patients.

METHODS

In this study, the weighted gene co-expression network analysis was applied to identify the hub gene module correlated with BC grade using GSE71576. After constructing a protein-protein interaction (PPI) network with the hub genes inside the hub gene module, we identified some potential core genes. TCGA and another independent dataset were used for further validation.

RESULTS

The results revealed that the expression of AURKA, CCNA2, CCNB1, KIF11, TTK, BUB1B, BUB1, and CDK1 were significantly higher in high-grade BC, showing a strong ability to distinguish BC grade. The expression levels of the 8 genes in normal, paracancerous, tumorous, and recurrent bladder tissues were progressively increased. By conducting survival analysis, we proved their prognostic value in predicting the recurrence of BC. Eventually, we constructed a prognostic nomogram by combining the 8-core-gene panel with clinicopathologic features, which had shown great performance in predicting the recurrence of BC.

CONCLUSION

We identified 8 core genes that revealed a significant correlation with the tumor grade as well as the recurrence of BC. Finally, we proved the value of a novel prognostic nomogram for predicting the relapse-free survival of BC patients after surgery, which could guide their treatment and follow-up.

Overexpression of MTFR2 Predicts Poor Prognosis of Breast Cancer

Background

Mitochondrial fission regulator 2 (MTFR2) has been reported to promote proliferation, migration and invasion in tumors; however, little is known about its function in breast cancer. Thus, we investigated the effect of MTFR2 expression on prognosis of breast cancer.

Methods

The expression of MTFR2 in breast cancer tissues was detected by immunohistochemistry, and overall survival (OS) and recurrence free survival (RFS) were evaluated by the Log rank test and Cox model.

Results

We found that MTFR2 expression was significantly associated with clinical stage (P<0.001), T classification (P=0.005), N classification (P=0.001), M classification (P=0.041), HER2 expression (P= 0.001), and molecular subtypes (P=0.002), respectively. Compared with low MTFR2 expression, the patients with higher expression of MTFR2 exhibited significantly shorter OS and RFS (All P < 0.001). Both univariate and multivariate analyses showed that MTFR2 was an independent prognostic factor for OS (HR, 2.8, 95% CI 1.1-6.8, P = 0.023) and RFS (HR, 2.8, 95% CI 1.2-6.4, P = 0.015) in breast cancer patients. Moreover, in HER2 positive and TNBC subtype, the associations between high MTFR2 expression and poor OS and RFS were more pronounced.

Conclusion

Taken together, our results demonstrated that high MTFR2 expression was associated with poor prognosis of breast cancer patients, and such an association was more pronounced in the patients with aggressive tumors. Therefore, MTFR2 expression might be a potentially important prognostic biomarker and clinical target for patients with breast cancer.

Identification of unique long non-coding RNAs as putative biomarkers for chromophobe renal cell carcinoma

Aim: To investigate whether long non-coding RNAs (lncRNAs) can be utilized as molecular biomarkers in predicting the occurrence and progression of chromophobe renal cell carcinoma. Methods & results: Genetic and related clinical traits of chromophobe renal cell carcinoma were downloaded from the Cancer Genome Atlas and used to construct modules using weighted gene coexpression network analysis. In total, 44,889 genes were allocated into 21 coexpression modules depending on intergenic correlation. Among them, the green module was the most significant key module identified by module-trait correlation calculations (R² = 0.43 and p = 4e-04). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses demonstrated that genes in the green module were enriched in many pathways. Coexpression, protein-protein interaction networks, screening for differentially expressed genes, and survival analysis were used to select hub lncRNAs. Five hub lncRNAs (TTK, CENPE, KIF2C, BUB1, and RAD51AP1) were selected out. Conclusion: Our findings suggest that the five lncRNAs may act as potential biomarkers for chromophobe renal cell carcinoma progression and prognosis.

Targeting Hypoxia Sensitizes TNBC to Cisplatin and Promotes Inhibition of Both Bulk and Cancer Stem Cells

Development of targeted therapies for triple-negative breast cancer (TNBC) is an unmet medical need. Cisplatin has demonstrated its promising potential for the treatment of TNBC in clinical trials; however, cisplatin treatment is associated with hypoxia that, in turn, promotes cancer stem cell (CSC) enrichment and drug resistance. Therapeutic approaches to attenuate this may lead to increased cisplatin efficacy in the clinic for the treatment of TNBC. In this report we analyzed clinical datasets of TNBC and found that TNBC patients possessed higher levels of EGFR and hypoxia gene expression. A similar expression pattern was also observed in cisplatin-resistant ovarian cancer cells. We, thus, developed a new therapeutic approach to inhibit EGFR and hypoxia by combination treatment with metformin and gefitinib that sensitized TNBC cells to cisplatin and led to the inhibition of both CD44+/CD24− and ALDH+ CSCs. We demonstrated a similar inhibition efficacy on organotypic cultures of TNBC patient samples ex vivo. Since these drugs have already been used frequently in the clinic; this study illustrates a novel, clinically translatable therapeutic approach to treat patients with TNBC.

Construction and Comprehensive Analysis of a ceRNA Network to Reveal Potential Novel Biomarkers for Triple-Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is the most common and aggressive type of breast cancer with an unfavourable outcome worldwide. Novel therapeutic targets are urgently required to explore this malignancy. This study explored the ceRNA network and the important genes for predicting the therapeutic targets.

Methods

It identified the differentially expressed genes of mRNAs, lncRNAs and miRNAs between TNBC and non-TNBC samples in four cohorts (TCGA, GSE38959, GSE45827 and GSE65194) to explore the novel therapeutic targets for TNBC. Downstream analyses, including functional enrichment analysis, ceRNA network, protein–protein interaction and survival analysis, were then conducted by bioinformatics analysis. Finally, the potential core protein of the ceRNA network in TNBC was validated by immunohistochemistry.

Results

A total of 1,045 lncRNAs and 28 miRNAs were differentially expressed in the TCGA TNBC samples, and the intersections of 282 mRNAs (176 upregulations and 106 downregulations) between the GEO and TCGA databases were identified. A ceRNA network composed of 7 lncRNAs, 62 mRNAs, 12 miRNAs and 244 edges specific to TNBC was established. The functional assay showed dysregulated genes, and GO, DO and KEGG enrichment analysis were performed. Survival analysis showed that mRNA LIFR and lncRNA AC124312.3 were significantly correlated with the overall survival of patients with TNBC in the TCGA databases (P < 0.05). Finally, the LIFR protein was validated, and immunohistochemical results showed the upregulated expression of LIFR in TNBC tissues.

Conclusion

Thus, our study presents an enhanced understanding of the ceRNA network in TNBC, where the key gene LIFR may be a new promising potential therapeutic target for patients with TNBC.

BIK drives an aggressive breast cancer phenotype through sublethal apoptosis and predicts poor prognosis of ER-positive breast cancer

Apoptosis is fundamental to normal animal development and is the target for many anticancer therapies. Recent studies have explored the consequences of "failed apoptosis" where the apoptotic program is initiated but does not go to completion and does not cause cell death. Nevertheless, this failed apoptosis induces DNA double-strand breaks generating mutations that facilitate tumorigenesis. Whether failed apoptosis is relevant to clinical disease is unknown. BCL-2 interacting killer (BIK) is a stress-induced BH3-only protein that stimulates apoptosis in response to hormone and growth factor deprivation, hypoxia, and genomic stress. It was unclear whether BIK promotes or suppresses tumor survival within the context of breast cancer. We investigated this and show that BIK induces failed apoptosis with limited caspase activation and genomic damage in the absence of extensive cell death. Surviving cells acquire aggressive phenotypes characterized by enrichment of cancer stem-like cells, increased motility and increased clonogenic survival. Furthermore, by examining six independent cohorts of patients (total n = 969), we discovered that high BIK mRNA and protein levels predicted clinical relapse of Estrogen receptor (ER)-positive cancers, which account for almost 70% of all breast cancers diagnosed but had no predictive value for hormone receptor-negative (triple-negative) patients. Thus, this study identifies BIK as a biomarker for tumor recurrence of ER-positive patients and provides a potential mechanism whereby failed apoptosis contributes to cancer aggression.

Evaluation of ASPM and TEF Gene Expressions as Potential Biomarkers for Bladder Cancer

Bladder cancer is one of the most predominant tumors of the genitourinary tract. In addition to pathological findings, the molecular modifications that might affect tumorigenesis and tumor outcome should be considered when treating bladder cancer. Accordingly, we aimed to investigate the expression levels of both the ASPM and TEF genes in bladder cancer tissues and their value in disease prognosis. The expression levels of the ASPM and TEF genes were analyzed by quantitative real-time PCR (qRT-PCR) in 90 bladder cancer tissue specimens and 90 specimens of normal urinary bladder tissue taken away from the tumor site. The upregulation of ASPM expression and the downregulation of TEF expression were observed in bladder cancer tissues compared to adjacent normal tissues, and these levels were correlated with high-grade tumors, advanced stage disease and the presence of metastasis. Both genes had the ability to predict metastatic association with sensitivity (84.62%) and specificity (68.42%; *P < 0.001) for the ASPM gene and for the TEF gene with sensitivity (80.77%) and specificity (78.95%; *P < 0.001). Additionally, Kaplan-Meier survival analysis indicated that elevated ASPM expression levels and reduced TEF expression levels significantly correlated with decreased overall survival and progression-free survival. The current analysis concludes that ASPM and TEF expressions might be used as potential biomarkers in bladder cancer patients.

Identification of CXCR4 and CXCL10 as Potential Predictive Biomarkers in Triple Negative Breast Cancer (TNBC)

BACKGROUND Efficacious therapy for triple negative breast cancer (TNBC) continues to be a profound clinical challenge, but the key driven genes and convoluted signaling pathways are still unknown. MATERIAL AND METHODS A total of 223 samples (163 TNBC and 60 healthy breast tissues) were taken and deeply integrated analyzed by R software from 4 expression profiles in the study, including GSE53752, GSE45827, GSE65194, and GSE38959. We examined differentially expressed genes (DEGs) and screen for critical genes and pathways enrichment. The protein‑protein interaction (PPI) network of DEGs-associated was built through the STRING Version: 11.0 database and Cytoscape software to filter the hub gene. Then, we verified hug gene expression levels through the Oncomine database. Also, we analyzed the prognostic value of TNBC patient's hub genes using the Kaplan-Meier plotter database. RESULTS In our study, we filter out 365 DEGs, including 212 upregulated genes and 153 downregulated genes. Then, 10 hub genes were picked out by the intersection of 12 algorithms. At the same time, we discovered that CXCR4 and CXCL10 overexpression are favorable prognostic factors for recurrence-free survival of TNBC through the Kaplan-Meier plotter database. CONCLUSIONS Our research found that CXCR4 and CXCL10 overexpressed, and they were a favorable prognostic factor in patients with TNBC. CXCR4 and CXCL10 might be effective targets for TNBC therapy.

Mitotic checkpoint kinase Mps1/TTK predicts prognosis of colon cancer patients and regulates tumor proliferation and differentiation via PKCα/ERK1/2 and PI3K/Akt pathway

Mps1/TTK plays an important role in development of many tumors. The purpose of the present study was designed to investigate the role of TTK in colon cancer. We analyzed TTK and colon cancer in the GEO database, colon cancer tissues and normal tissues were collected to verify the results by immunohistochemistry. We detected the TTK expression in the colon cancer cell lines, and overexpressed or silenced TTK expression in colon cancer cell lines. GEO database showed that the expression of TTK was higher in the colon cancer tissues than normal tissues, higher level of TTK shows unfavourable prognosis in colon patients. Furthermore, high differentiation of colon shows the lower expression of TTK. The higher expression of TTK links with the high microsatellite status. However, the expression of TTK has no significant difference among the different stages of colon cancer patients, and has no significant relationship with recurrence or relapse. Here, we also report that the differential expression of TTK in colon cancer cells alters the intrinsic negative regulation of cell proliferation and differentiation, resulting in the difference of proliferation and differentiation capacity. TTK could activate the PKCα/ERK1/2 to influence the proliferation and inactivate the PI3K/AKT pathway to inhibition the expression of MUC2 and TFF3 that related to the differentiation of colon cells. In conclusions, TTK promote the colon cancer cell proliferation via activation of PKCα/ERK1/2 and inhibit the differentiation via inactivation of PI3K/Akt pathway. TTK inhibition may be the potential therapeutic pathway for the treatment of colon cancer.

Identification of microRNA clusters cooperatively acting on epithelial to mesenchymal transition in triple negative breast cancer

MicroRNAs play important roles in many biological processes. Their aberrant expression can have oncogenic or tumor suppressor function directly participating to carcinogenesis, malignant transformation, invasiveness and metastasis. Indeed, miRNA profiles can distinguish not only between normal and cancerous tissue but they can also successfully classify different subtypes of a particular cancer. Here, we focus on a particular class of transcripts encoding polycistronic miRNA genes that yields multiple miRNA components. We describe 'clustered MiRNA Master Regulator Analysis (ClustMMRA)', a fully redesigned release of the MMRA computational pipeline (MiRNA Master Regulator Analysis), developed to search for clustered miRNAs potentially driving cancer molecular subtyping. Genomically clustered miRNAs are frequently co-expressed to target different components of pro-tumorigenic signaling pathways. By applying ClustMMRA to breast cancer patient data, we identified key miRNA clusters driving the phenotype of different tumor subgroups. The pipeline was applied to two independent breast cancer datasets, providing statistically concordant results between the two analyses. We validated in cell lines the miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative breast cancer (TNBC) phenotype through its control of proliferation and EMT.

Druggable Molecular Targets for the Treatment of Triple Negative Breast Cancer

Breast cancer (BC) is still the most common cancer among women worldwide. Amongst the subtypes of BC, triple negative breast cancer (TNBC) is characterized by deficient expression of estrogen, progesterone, and human epidermal growth factor receptor 2 receptors. These patients are therefore not given the option of targeted therapy and have worse prognosis as a result. Consequently, much research has been devoted to identifying specific molecular targets that can be utilized for targeted cancer therapy, thereby limiting the progression and metastasis of this invasive tumor, and improving patient outcomes. In this review, we have focused on the molecular targets in TNBC, categorizing these into targets within the immune system such as immune checkpoint modulators, intra-nuclear targets, intracellular targets, and cell surface targets. The aim of this review is to introduce and summarize the known targets and drugs under investigation in phase II or III clinical trials, while introducing additional possible targets for future drug development. This review brings a tangible benefit to cancer researchers who seek a comprehensive comparison of TNBC treatment options.