Polo-like kinase 1: a potential therapeutic option in combination with conventional chemotherapy for the management of patients with triple-negative breast cancer

PLK1 and FoxM1 expressions positively correlate in papillary thyroid carcinoma and their combined inhibition results in synergistic anti-tumor effects

Polo-like kinase 1 (PLK1; also known as serine/threonine-protein kinase PLK1) serves as a central player in cell proliferation, exerting critical regulatory roles in mitotic processes and cell survival. We conducted an analysis of PLK1 protein expression in a large cohort of samples from papillary thyroid carcinoma (PTC) patients and examined its functional significance in PTC cell lines, both in vitro and in vivo. PLK1 overexpression was noted in 54.2% of all PTC and was significantly associated with aggressive clinicopathological parameters; it was also found to be an independent prognostic marker for shorter recurrence-free survival. Given the significant association between PLK1 and forkhead box protein M1 (FoxM1), and their concomitant overexpression in a large proportion of PTC samples, we explored their correlation and their combined inhibitions in PTC in vitro and in vivo. Inhibition of PLK1 expression indeed suppressed cell proliferation, leading to cell cycle arrest and apoptosis in PTC cell lines. Significantly, the downregulation of PLK1 reduced the self-renewal capability of spheroids formed from PTC cells. Immunoprecipitation analysis shows that PLK1 binds to FoxM1 and vice versa in vitro. Mechanistically, PLK1 knockdown suppresses FoxM1 expression, whereas inhibition of FoxM1 does not affect PLK1 expression, which suggests that PLK1 acts through the FoxM1 pathway. The combined treatment of a PLK1 inhibitor (volasertib) and a FoxM1 inhibitor (thiostrepton) demonstrated a synergistic effect in reducing PTC cell growth in vitro and delaying tumor growth in vivo. This study highlights the important role of PLK1 in PTC tumorigenesis and prognosis. It also highlights the synergistic therapeutic potential of dual-targeting PLK1 and FoxM1 in PTC, unveiling a potential innovative therapeutic strategy for managing aggressive forms of PTC.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles

Pathway analysis, including nontopology-based (non-TB) and topology-based (TB) methods, is widely used to interpret the biological phenomena underlying differences in expression data between two phenotypes. By considering dependencies and interactions between genes, TB methods usually perform better than non-TB methods in identifying pathways that include closely relevant or directly causative genes for a given phenotype. However, most TB methods may be limited by incomplete pathway data used as the reference network or by difficulties in selecting appropriate reference networks for different research topics. Here, we propose a gene set correlation enrichment analysis method, Gscore, based on an expression dataset-derived coexpression network to examine whether a differentially expressed gene (DEG) list (or each of its DEGs) is associated with a known gene set. Gscore is better able to identify target pathways in 89 human disease expression datasets than eight other state-of-the-art methods and offers insight into how disease-wide and pathway-wide associations reflect clinical outcomes. When applied to RNA-seq data from COVID-19-related cells and patient samples, Gscore provided a means for studying how DEGs are implicated in COVID-19-related pathways. In summary, Gscore offers a powerful analytical approach for annotating individual DEGs, DEG lists, and genome-wide expression profiles based on existing biological knowledge.

Undifferentially Expressed CXXC5 as a Transcriptionally Regulatory Biomarker of Breast Cancer

This work hypothesizes that some genes undergo radically changed transcription regulations (TRs) in breast cancer (BC), but don't show differential expressions for unknown reasons. The TR of a gene is quantitatively formulated by a regression model between the expression of this gene and multiple transcription factors (TFs). The difference between the predicted and real expression levels of a gene in a query sample is defined as the mqTrans value of this gene, which quantitatively reflects its regulatory changes. This work systematically screens the undifferentially expressed genes with differentially expressed mqTrans values in 1036 samples across five datasets and three ethnic groups. This study calls the 25 genes satisfying the above hypothesis in at least four datasets as dark biomarkers, and the strong dark biomarker gene CXXC5 (CXXC Finger Protein 5) is even supported by all the five independent BC datasets. Although CXXC5 does not show differential expressions in BC, its transcription regulations show quantitative associations with BCs in diversified cohorts. The overlapping long noncoding RNAs (lncRNAs) may have contributed their transcripts to the expression miscalculations of dark biomarkers. The mqTrans analysis serves as a complementary view of the transcriptome-based detections of biomarkers that are ignored by many existing studies.

Recent Advances in Drug Discovery for Triple-Negative Breast Cancer Treatment

Triple-negative breast cancer (TNBC) is one of the most heterogeneous and aggressive breast cancer subtypes with a high risk of death on recurrence. To date, TNBC is very difficult to treat due to the lack of an effective targeted therapy. However, recent advances in the molecular characterization of TNBC are encouraging the development of novel drugs and therapeutic combinations for its therapeutic management. In the present review, we will provide an overview of the currently available standard therapies and new emerging therapeutic strategies against TNBC, highlighting the promises that newly developed small molecules, repositioned drugs, and combination therapies have of improving treatment efficacy against these tumors.

Characteristics and prognostic significance of polo-like kinase-1 (PLK1) expression in breast cancer

AIM

Polo-like kinase-1 (PLK1) plays a crucial role in cell cycle progression, and it is considered a potential therapeutic target in many cancers. Although the role of PLK1 is well established in triple-negative breast cancer (TNBC) as an oncogene, its role in luminal BC is still controversial. In this study, we aimed to evaluate the prognostic and predictive role of PLK1 in BC and its molecular subtypes.

METHODS

A large BC cohort (n = 1208) were immunohistochemically stained for PLK1. The association with clinicopathological, molecular subtypes, and survival data was analysed. PLK1 mRNA was evaluated in the publicly available datasets (n = 6774), including The Cancer Genome Atlas and the Kaplan-Meier Plotter tool.

RESULTS

20% of the study cohort showed high cytoplasmic PLK1 expression. High PLK1 expression was significantly associated with a better outcome in the whole cohort, luminal BC. In contrast, high PLK1 expression was associated with a poor outcome in TNBC. Multivariate analyses indicated that high PLK1 expression is independently associated with longer survival in luminal BC, and in poorer prognosis in TNBC. At the mRNA levels, PLK1 expression was associated with short survival in TNBC consistent with the protein expression. However, in luminal BC, its prognostic value significantly varies between cohorts.

CONCLUSION

The prognostic role of PLK1 in BC is molecular subtype-dependent. As PLK1 inhibitors are introduced to clinical trials for several cancer types, our study supports evaluation of the pharmacological inhibition of PLK1 as an attractive therapeutic target in TNBC. However, in luminal BC, PLK1 prognostic role remains controversial.

RPL27 contributes to colorectal cancer proliferation and stemness via PLK1 signaling

Although expression of ribosomal protein L27 (RPL27) is upregulated in clinical colorectal cancer (CRC) tissue, to the best of our knowledge, the oncogenic role of RPL27 has not yet been defined. The present study aimed to investigate whether targeting RPL27 could alter CRC progression and determine whether RPL27 gains an extra‑ribosomal function during CRC development. Human CRC cell lines HCT116 and HT29 were transfected with RPL27‑specific small interfering RNA and proliferation was assessed in vitro and in vivo using proliferation assays, fluorescence‑activated cell sorting (FACS) and a xenograft mouse model. Furthermore, RNA sequencing, bioinformatic analysis and western blotting were conducted to explore the underlying mechanisms responsible for RPL27 silencing‑induced CRC phenotypical changes. Inhibiting RPL27 expression suppressed CRC cell proliferation and cell cycle progression and induced apoptotic cell death. Targeting RPL27 significantly inhibited growth of human CRC xenografts in nude mice. Notably, polo‑like kinase 1 (PLK1), which serves an important role in mitotic cell cycle progression and stemness, was downregulated in both HCT116 and HT29 cells following RPL27 silencing. RPL27 silencing reduced the levels of PLK1 protein and G2/M‑associated regulators such as phosphorylated cell division cycle 25C, CDK1 and cyclin B1. Silencing of RPL27 reduced the migration and invasion abilities and sphere‑forming capacity of the parental CRC cell population. In terms of phenotypical changes in cancer stem cells (CSCs), RPL27 silencing suppressed the sphere‑forming capacity of the isolated CD133+ CSC population, which was accompanied by decreased CD133 and PLK1 levels. Taken together, these findings indicated that RPL27 contributed to the promotion of CRC proliferation and stemness via PLK1 signaling and RPL27 may be a useful target in a next‑generation therapeutic strategy for both primary CRC treatment and metastasis prevention.

CEBP-β and PLK1 as Potential Mediators of the Breast Cancer/Obesity Crosstalk: In Vitro and In Silico Analyses

Over the last two decades, obesity has reached pandemic proportions in several countries, and expanding evidence is showing its contribution to several types of malignancies, including breast cancer (BC). The conditioned medium (CM) from mature adipocytes contains a complex of secretes that may mimic the obesity condition in studies on BC cell lines conducted in vitro. Here, we report a transcriptomic analysis on MCF-7 BC cells exposed to adipocyte-derived CM and focus on the predictive functional relevance that CM-affected pathways/processes and related biomarkers (BMs) may have in BC response to obesity. CM was demonstrated to increase cell proliferation, motility and invasion as well as broadly alter the transcript profiles of MCF-7 cells by significantly modulating 364 genes. Bioinformatic functional analyses unraveled the presence of five highly relevant central hubs in the direct interaction networks (DIN), and Kaplan-Meier analysis sorted the CCAAT/enhancer binding protein beta (CEBP-β) and serine/threonine-protein kinase PLK1 (PLK1) as clinically significant biomarkers in BC. Indeed, CEBP-β and PLK1 negatively correlated with BC overall survival and were up-regulated by adipocyte-derived CM. In addition to their known involvement in cell proliferation and tumor progression, our work suggests them as a possible "deus ex machina" in BC response to fat tissue humoral products in obese women.

Eugenol modulates the NOD1-NF-κB signaling pathway via targeting NF-κB protein in triple-negative breast cancer cells

BACKGROUND

The most aggressive subtype of breast cancer, triple-negative breast cancer (TNBC), has a worse prognosis and a higher probability of relapse since there is a narrow range of treatment options. Identifying and testing potential therapeutic targets for the treatment of TNBC is of high priority.

METHODS

Using a transcriptional signature of triple-negative breast cancer collected from Gene Expression Omnibus (GEO), CMap was utilized to reposition compounds for the treatment of TNBC. CCK8 and colony formation experiments were performed to detect the effect of the candidate drug on the proliferation of TNBC cells. Meanwhile, transwell and wound healing assay were implemented to detect cell metastasis change caused by the candidate drug. Moreover, the proteomic approach was presently ongoing to evaluate the underlying mechanism of the candidate drug in TNBC. Furthermore, drug affinity responsive target stability (DARTS) coupled with LC-MS/MS was carried out to explore the potential drug target candidate in TNBC cells.

RESULTS

We found that the most widely used medication, eugenol, reduced the growth and metastasis of TNBC cells. According to the underlying mechanism revealed by proteomics, eugenol could inhibit TNBC cell proliferation and metastasis via the NOD1-NF-κB signaling pathway. DARTS experiment further revealed that eugenol may bind to NF-κB in TNBC cells.

CONCLUDES

Our findings pointed out that eugenol was a potential candidate drug for the treatment of TNBC.

Checkpoint Kinase 1 (CHK1) Functions as Both a Diagnostic Marker and a Regulator of Epithelial-to-Mesenchymal Transition (EMT) in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is more difficult to treat and has a higher mortality rate than other subtypes. Although hormone receptor-targeted therapy is an effective treatment to increase survival rate in breast cancer patients, it is not suitable for TNBC patients. To address the issues, differentially expressed genes (DEGs) in TNBC patients from the Gene Expression Omnibus (GEO) database were analyzed. A total of 170 genes were obtained from three Genomic Spatial Events (GSEs) using the intersection of each GSE dataset and 61 DEGs were identified after validation with the gene enrichment analysis. We combined this with the degree scores from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network, of which 7 genes were correlated with survival rate. Finally, a proteomics database revealed that only the CHK1 protein level was differently expressed in basal-like compared with other subtypes. We demonstrated that CHK1 expression was higher in TNBC cell lines compared with non-TNBC cell lines, and CHK1 promotes epithelial to mesenchymal transition (EMT) as well as migration and invasion ability. Our study provides new insight into the TNBC subnetwork that may be useful in the prognosis and treatment of TNBC patients.

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.

Present and Future Perspective on PLK1 Inhibition in Cancer Treatment

Polo-like kinase 1 (PLK1) is the principle member of the well conserved serine/threonine kinase family. PLK1 has a key role in the progression of mitosis and recent evidence suggest its important involvement in regulating the G2/M checkpoint, in DNA damage and replication stress response, and in cell death pathways. PLK1 expression is tightly spatially and temporally regulated to ensure its nuclear activation at the late S-phase, until the peak of expression at the G2/M-phase. Recently, new roles of PLK1 have been reported in literature on its implication in the regulation of inflammation and immunological responses. All these biological processes are altered in tumors and, considering that PLK1 is often found overexpressed in several tumor types, its targeting has emerged as a promising anti-cancer therapeutic strategy. In this review, we will summarize the evidence suggesting the role of PLK1 in response to DNA damage, including DNA repair, cell cycle progression, epithelial to mesenchymal transition, cell death pathways and cancer-related immunity. An update of PLK1 inhibitors currently investigated in preclinical and clinical studies, in monotherapy and in combination with existing chemotherapeutic drugs and targeted therapies will be discussed.

Aberrant Activation of Cell-Cycle-Related Kinases and the Potential Therapeutic Impact of PLK1 or CHEK1 Inhibition in Uterine Leiomyosarcoma

PURPOSE

Uterine leiomyosarcoma is among the most aggressive gynecological malignancies. No effective treatment strategies have been established. This study aimed to identify novel therapeutic targets for uterine leiomyosarcoma based on transcriptome analysis and assess the preclinical efficacy of novel drug candidates.

EXPERIMENTAL DESIGN

Transcriptome analysis was performed using fresh-frozen samples of six uterine leiomyosarcomas and three myomas. The Ingenuity Pathway Analysis (IPA) was used to identify potential therapeutic target genes for uterine leiomyosarcoma. Afterward, our results were validated using three independent datasets, including 40 uterine leiomyosarcomas. Then, the inhibitory effects of several selective inhibitors for the candidate genes were examined using SK-UT-1, SK-LMS-1, and SKN cell lines.

RESULTS

We identified 512 considerably dysregulated genes in uterine leiomyosarcoma compared with myoma. The IPA revealed that the function of several genes, including CHEK1 and PLK1, were predicted to be activated in uterine leiomyosarcoma. Through an in vitro drug screening, PLK1 or CHEK1 inhibitors (BI-2536 or prexasertib) were found to exert a superior anticancer effect against cell lines at low nanomolar concentrations and induce cell-cycle arrest. In SK-UT-1 tumor-bearing mice, BI-2536 monotherapy remarkably suppressed tumorigenicity. Moreover, the prexasertib and cisplatin combination therapy inhibited tumor proliferation and prolonged the time to tumor progression.

CONCLUSIONS

We identified upregulated expressions of PLK1 and CHEK1; their kinase activity was activated in uterine leiomyosarcoma. BI-2536 and prexasertib demonstrated a significant anticancer effect. Therefore, cell-cycle-related kinases may present a promising therapeutic strategy for the treatment of uterine leiomyosarcoma.

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.

A Novel Allosteric Inhibitor Targets PLK1 in Triple Negative Breast Cancer Cells

While Polo-like kinase 1 (PLK1) inhibitors have shown promise in clinical settings for treating triple-negative breast cancer tumors and other solid tumors, they are limited by their ability to bind non-selectively to the ATP kinase domain. Therefore, we sought to develop a PLK1 allosteric inhibitor targeting the PLK1 T-loop (a switch responsible for activation) and evaluate its effects in triple-negative breast cancer cells. A novel compound, RK-10, was developed based on an in silico model, and its effects on specificity, viability, migration, and cell cycle regulation in MCF-10A and MDA-MB 231 cells were evaluated. When MDA-MB 231 cells were treated with 0−50 µg/mL RK-10, phospho-PLK1 (Thr-210) was decreased in cells cultured adherently and cells cultured as mammospheres. RK-10 significantly inhibited viability after 24 h; however, by 48 h, 25−50 µM RK-10 caused >50% reduction. RK-10 attenuated wound healing by up to 99.7% and caused S and G2/M cell cycle arrest, which was associated with increased p21 expression. We developed a novel allosteric inhibitor which mediates anti-proliferative and anti-migratory properties through targeting phospho-PLK1 (Thr-210) in mammospheres and causing S phase and G2/M cell cycle arrest. Further development of PLK1 allosteric inhibitors may be a promising approach for TNBC treatment.

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.

Synergistic apoptotic effect of miR-183-5p and Polo-Like kinase 1 inhibitor NMS-P937 in breast cancer cells

MicroRNAs (miRNAs) are small noncoding RNAs that act as endogenous regulatory molecules targeting specific mRNAs for translational repression. Studies of breast cancer genomics indicate that breast cancer subtypes are distinguished and regulated by specific sets of miRNAs which affect activities such as tumor initiation, progression, and even drug response. Polo-like Kinase 1 (PLK1) is widely considered to be a proto-oncogene due to its increased expression in multiple tumor types, as well as its crucial role in regulating mitosis. Pharmacological inhibition of PLK1 can reduce tumor volume and induce tumor cell death in solid and hematologic malignancies. This prompted us to investigate how PLK1 inhibition with the target-specific inhibitor NMS-P937 would impact breast cancer cells, and how miRNAs may influence the overall response of these cells to this inhibition. We found that miR-183-5p targets PLK1 gene, effectively reducing its protein expression. Such miRNA-driven regulation of PLK1 expression sensitizes breast cancer cells to NMS-P937, resulting in synergistically increased apoptosis. We also show that the miRNA-regulated reduction of PLK1 influences the expression of apoptosis-related key proteins and possibly inducing further indirect PLK1 downmodulation through a DNMT1-p53 axis. These results suggest a potential biologically significant link between the expression of miR-183-5p and the efficacy of PLK1-specific inhibitors in breast cancer cells. Our work further elucidates how miR-183-5p regulates PLK1 gene while also enhancing NMS-P937 effect in breast cancer. Future studies assessing the role of miR-183-5p as a novel biomarker for anti-PLK1 chemotherapy agents are warranted.

PLK1 inhibition-based combination therapies for cancer management

Polo-like kinase I (PLK1), a cell cycle regulating kinase, has been shown to have oncogenic function in several cancers. Although PLK1 inhibitors, such as BI2536, BI6727 (volasertib) and NMS-1286937 (onvansertib) are generally well-tolerated with a favorable pharmacokinetic profile, clinical successes are limited due to partial responses in cancer patients, especially those in advanced stages. Recently, combination therapies targeting multiple pathways are being tested for cancer management. In this review, we first discuss structure and function of PLK1, role of PLK1 in cancers, PLK1 specific inhibitors, and advantages of using combination therapy versus monotherapy followed by a critical account on PLK1-based combination therapies in cancer treatments, especially highlighting recent advancements and challenges. PLK1 inhibitors in combination with chemotherapy drugs and targeted small molecules have shown superior effects against cancer both in vitro and in vivo. PLK1-based combination therapies have shown increased apoptosis, disrupted cell cycle, and potential to overcome resistance in cancer cells/tissues over monotherapies. Further, with successes in preclinical experiments, researchers are validating such approaches in clinical trials. Although PLK1-based combination therapies have achieved initial success in clinical studies, there are examples where they have failed to improve patient survival. Therefore, further research is needed to identify and validate novel biologically informed co-targets for PLK1-based combinatorial therapies. Employing a network-based analysis, we identified potential PLK1 co-targets that could be examined further. In addition, understanding the mechanisms of synergism between PLK1 inhibitors and other agents may lead to a better approach on which agents to pair with PLK1 inhibition for optimum cancer treatment.

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.

Polo-Like Kinase 1 Regulates Chromosomal Instability and Paclitaxel Resistance in Breast Cancer Cells

Purpose

Chromosomal instability (CIN) contributes to intercellular genetic heterogeneity and has been implicated in paclitaxel (PTX) resistance in breast cancer. In this study, we explored polo-like kinase 1 (PLK1) as an important regulator of mitotic integrity and as a useful predictive biomarker for PTX resistance in breast cancer.

Methods

We performed PTX resistance screening using the human kinome CRISPR/Cas9 library in breast cancer cells. In vitro cell proliferation and apoptosis assays and in vivo xenograft experiments were performed to determine the effects of PLK1 on breast cancer cells. Immunofluorescence microscopy was used to measure the degree of multipolar cell division.

Results

Kinome-wide CRISPR/Cas9 screening identified various kinases involved in PTX resistance in breast cancer cells; among these, PLK1 was chosen for further experiments. PLK1 knockdown inhibited the proliferation of MDA-MB-231 and MDA-MB-468 cells in vitro and in vivo. Moreover, PLK1 silencing sensitized breast cancer cells and mouse xenograft tumor models to PTX cytotoxicity. Silencing of PLK1 induced the formation of multipolar spindles and increased the percentage of multipolar cells. In addition, PLK1 silencing resulted in the downregulation of BubR1 and Mad2 in breast cancer cells. Furthermore, PLK1 upregulation in primary breast cancer was associated with decreased overall patient survival based on the analysis of The Cancer Genome Atlas and Molecular Taxonomy of Breast Cancer International Consortium databases.

Conclusion

PLK1 plays an important role in PTX resistance by regulating CIN in breast cancer cells. Targeting PLK1 may be an effective treatment strategy for PTX-resistant breast cancers.

Identifying the Effect of Ursolic Acid Against Triple-Negative Breast Cancer: Coupling Network Pharmacology With Experiments Verification

Triple negative breast cancer (TNBC) is a subtype of breast cancer with complex heterogeneity, high invasiveness, and long-term poor prognosis. With the development of molecular pathology and molecular genetics, the gene map of TNBC with distinctive biological characteristics has been outlined more clearly. Natural plant extracts such as paclitaxel, vinblastine, colchicine etc., have occupied an important position in the treatment of hormone-independent breast cancer. Ursolic acid (UA), a triterpenoid acid compound derived from apple, pear, loquat leaves, etc., has been reported to be effective in a variety of cancer treatments, but there are few reports on the treatment of TNBC. This study performed comprehensive bioinformatics analysis and in vitro experiments to identify the effect of UA on TNBC treatment and its potential molecular mechanism. Our results showed that UA could not only reduce the proliferation, migration, and invasion in MDA-MB-231 and MDA-MB-468 cell lines with a dose-dependent manner but also induce cell cycle arrest and apoptosis. Meanwhile, we collected the gene expression data GSE45827 and GSE65194 from GEO for comparison between TNBC and normal cell type and obtained 724 DEGs. Subsequently, PLK1 and CCNB1 related to TNBC were screened as the key targets via topological analysis and molecular docking, and gene set enrichment analysis identified the key pathway as the p53 signaling pathway. In addition, quantitative real-time PCR and western blot verified the key genes were PLK1 and CCNB1. In vivo and in vitro experiments showed that UA could inhibit the growth of TNBC cells, and down-regulate the protein expression levels of PLK1 and CCNB1 by mediating p53 signaling pathway. These findings provide strong evidence for UA intervention in TNBC via multi-target therapy.

Tumor suppressor PLK2 may serve as a biomarker in triple-negative breast cancer for improved response to PLK1 therapeutics

Polo-like kinase (PLK) family members play important roles in cell cycle regulation. The founding member PLK1 is oncogenic and preclinically validated as a cancer therapeutic target. Paradoxically, frequent loss of chromosome 5q11-35 which includes PLK2 is observed in basal-like breast cancer. In this study, we found that PLK2 was tumor suppressive in breast cancer, preferentially in basal-like and triple-negative breast cancer (TNBC) subtypes. Knockdown of PLK1 rescued phenotypes induced by PLK2-loss both in vitro and in vivo. We also demonstrated that PLK2 directly interacted with PLK1 at prometaphase through the kinase but not the polo-box domains of PLK2, suggesting PLK2 functioned at least partially through the interaction with PLK1. Furthermore, an improved treatment response was seen in both Plk2-deleted/low mouse preclinical and PDX TNBC models using the PLK1 inhibitor volasertib alone or in combination with carboplatin. Re-expression of PLK2 in an inducible PLK2-null mouse model reduced the therapeutic efficacy of volasertib. In summary, this study delineates the effects of chromosome 5q loss in TNBC that includes PLK2, the relationship between PLK2 and PLK1, and how this may render PLK2-deleted/low tumors more sensitive to PLK1 inhibition in combination with chemotherapy.

Cytosolic protein delivery using pH-responsive, charge-reversible lipid nanoparticles

Although proteins have attractive features as biopharmaceuticals, the difficulty in delivering them into the cell interior limits their applicability. Lipid nanoparticles (LNPs) are a promising class of delivery vehicles. When designing a protein delivery system based on LNPs, the major challenges include: (i) formulation of LNPs with defined particle sizes and dispersity, (ii) efficient encapsulation of cargo proteins into LNPs, and (iii) effective cellular uptake and endosomal release into the cytosol. Dioleoylglycerophosphate-diethylenediamine (DOP-DEDA) is a pH-responsive, charge-reversible lipid. The aim of this study was to evaluate the applicability of DOP-DEDA-based LNPs for intracellular protein delivery. Considering the importance of electrostatic interactions in protein encapsulation into LNPs, a negatively charged green fluorescent protein (GFP) analog was successfully encapsulated into DOP-DEDA-based LNPs to yield diameters and polydispersity index of < 200 nm and < 0.2, respectively. Moreover, ~ 80% of the cargo proteins was encapsulated into the LNPs. Cytosolic distribution of fluorescent signals of the protein was observed for up to ~ 90% cells treated with the LNPs, indicating the facilitated endocytic uptake and endosomal escape of the cargo attained using the LNP system.

Metabolic memory underlying minimal residual disease in breast cancer

Tumor relapse from treatment-resistant cells (minimal residual disease, MRD) underlies most breast cancer-related deaths. Yet, the molecular characteristics defining their malignancy have largely remained elusive. Here, we integrated multi-omics data from a tractable organoid system with a metabolic modeling approach to uncover the metabolic and regulatory idiosyncrasies of the MRD. We find that the resistant cells, despite their non-proliferative phenotype and the absence of oncogenic signaling, feature increased glycolysis and activity of certain urea cycle enzyme reminiscent of the tumor. This metabolic distinctiveness was also evident in a mouse model and in transcriptomic data from patients following neo-adjuvant therapy. We further identified a marked similarity in DNA methylation profiles between tumor and residual cells. Taken together, our data reveal a metabolic and epigenetic memory of the treatment-resistant cells. We further demonstrate that the memorized elevated glycolysis in MRD is crucial for their survival and can be targeted using a small-molecule inhibitor without impacting normal cells. The metabolic aberrances of MRD thus offer new therapeutic opportunities for post-treatment care to prevent breast tumor recurrence.

PLK1 Inhibition Sensitizes Breast Cancer Cells to Radiation via Suppressing Autophagy

PURPOSE

Polo-like kinase 1 (PLK1) is a protein kinase that is overexpressed in breast cancer and may represent an attractive target for breast cancer treatment. However, few studies have investigated the relationship between PLK1 and radiosensitivity in breast cancer. Here, we attempted to explore whether PLK1 inhibition could sensitize breast cancer cells to radiation.

METHODS AND MATERIALS

Breast cancer cells were treated with PLK1 small interference RNA or the PLK1-inhibitor, GSK461364. Cell proliferation was assessed using a colony formation assay. Cell cycle analyses were performed by flow cytometry. DNA damage, autophagy, and reactive oxygen species induced by ionizing radiation were detected by immunofluorescence, Western blot, and flow cytometry, respectively. Microtubule-associated protein 1 light chain 3 alpha (LC3) puncta were detected using an immunofluorescence assay. A clonogenic survival assay was used to determine the effect of PLK1 inhibition on cell radiosensitivity. A xenograft mouse model of breast cancer cells was used to investigate the potential synergistic effects of PLK1 inhibition and irradiation in vivo. Finally, the expression of PLK1 and LC3 in the breast cancer tissues was evaluated by immunohistochemistry.

RESULTS

PLK1 inhibition significantly suppressed the proliferation and increased the radiosensitivity of breast cancer cells. Pharmacologic inhibition of PLK1 by the selective inhibitor, GSK461364, enhanced the radiosensitivity of breast cancer cells in vivo (n = 4, P = .002). Mechanistically, PLK1 inhibition led to the downregulation of radiation-induced reactive oxygen species and autophagy, thereby increasing the radiosensitivity of breast cancer cells. Additionally, we detected a positive correlation between the expression of PLK1 and LC3 in human breast cancer samples (n = 102, R = 0.486, P = .005).

CONCLUSIONS

Our findings indicate that PLK1 inhibition enhances the radiosensitivity of breast cancer cells in a manner associated with the suppression of radiation-induced autophagy. The inhibition of PLK1 represents a promising strategy for radiosensitizing breast cancer.

FRL: An Integrative Feature Selection Algorithm Based on the Fisher Score, Recursive Feature Elimination, and Logistic Regression to Identify Potential Genomic Biomarkers

Accurate screening on cancer biomarkers contributes to health assessment, drug screening, and targeted therapy for precision medicine. The rapid development of high-throughput sequencing technology has identified abundant genomic biomarkers, but most of them are limited to single-cancer analysis. Based on the combination of Fisher score, Recursive feature elimination, and Logistic regression (FRL), this paper proposes an integrative feature selection algorithm named FRL to explore potential cancer genomic biomarkers on cancer subsets. Fisher score is initially used to calculate the weights of genes to rapidly reduce the dimension. Recursive feature elimination and Logistic regression are then jointly employed to extract the optimal subset. Compared to the current differential expression analysis tool GEO2R based on the Limma algorithm, FRL has greater classification precision than Limma. Compared with five traditional feature selection algorithms, FRL exhibits excellent performance on accuracy (ACC) and F1-score and greatly improves computational efficiency. On high-noise datasets such as esophageal cancer, the ACC of FRL is 30% superior to the average ACC achieved with other traditional algorithms. As biomarkers found in multiple studies are more reliable and reproducible, and reveal stronger association on potential clinical value than single analysis, through literature review and spatial analyses of gene functional enrichment and functional pathways, we conduct cluster analysis on 10 diverse cancers with high mortality and form a potential biomarker module comprising 19 genes. All genes in this module can serve as potential biomarkers to provide more information on the overall oncogenesis mechanism for the detection of diverse early cancers and assist in targeted anticancer therapies for further developments in precision medicine.

Evaluating the transcriptional fidelity of cancer models

BACKGROUND

Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors.

METHODS

We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence.

RESULTS

We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity.

CONCLUSIONS

CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

Identification of potential oncogenes in triple-negative breast cancer based on bioinformatics analyses

Triple-negative breast cancer (TNBC) is a subtype with high rates of metastasis, poor prognosis and limited therapeutic options. The present study aimed to identify the potential pivotal genes for prognosis and treatment in TNBC. A total of two microarray expression datasets, GSE38959 and GSE65212, were downloaded from the Gene Expression Omnibus database, and RNA-sequencing data of breast cancer from The Cancer Genome Atlas database were analyzed to screen out differentially expressed genes (DEGs) between TNBC tissues and normal tissues. The intersection of DEGs was submitted to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. A protein-protein interaction (PPI) network was constructed and visualized using Cytoscape software. Furthermore, module, centrality and survival analyses were performed to identify the potential hub genes. Reverse transcription-quantitative (RT-q)PCR analysis was performed to detect the expression levels of key genes in TNBC samples, and 377 DEGs were identified. Functional analysis revealed that the DEGs were significantly involved in cell cycle process, nuclear division and the p53 signaling pathway. A PPI network was constructed with these DEGs, and 66 core genes with high centrality features in module 1 were selected. Relapse-free survival analysis confirmed that high expression levels of five genes [cyclin B1 (CCNB1), GINS complex subunit 2, non-SMC condensin I complex subunit G (NCAPG), minichromosome maintenance 4 (MCM4) and ribonucleotide reductase regulatory subunit M2 (RRM2)] were significantly associated with poor prognosis in TNBC. RT-qPCR analysis demonstrated that CCNB1, NCAPG, MCM4 and RRM2 were significantly upregulated in 25 TNBC tissues compared with adjacent normal breast tissues. Furthermore, gene set enrichment analysis revealed that CCNB1, NCAPG, MCM4 and RRM2 were closely associated with tumor proliferation. Taken together, these results suggest that CCNB1, NCAPG, MCM4 and RRM2 are associated with tumorigenesis and TNBC progression, and thus may act as promising prognostic biomarkers and therapeutic targets for TNBC.

PLK1 Induces Chromosomal Instability and Overrides Cell-Cycle Checkpoints to Drive Tumorigenesis

Polo-like kinase 1 (PLK1) is an essential cell-cycle regulator that is frequently overexpressed in various human cancers. To determine whether Plk1 overexpression drives tumorigenesis, we established transgenic mouse lines that ubiquitously express increased levels of Plk1. High Plk1 levels were a driving force for different types of spontaneous tumors. Increased Plk1 levels resulted in multiple defects in mitosis and cytokinesis, supernumerary centrosomes, and compromised cell-cycle checkpoints, allowing accumulation of chromosomal instability (CIN), which resulted in aneuploidy and tumor formation. Clinically, higher expression of PLK1 positively associated with an increase in genome-wide copy-number alterations in multiple human cancers. This study provides in vivo evidence that aberrant expression of PLK1 triggers CIN and tumorigenesis and highlights potential therapeutic opportunities for CIN-positive cancers. SIGNIFICANCE: These findings establish roles for PLK1 as a potent proto-oncogene and a CIN gene and provide insights for the development of effective treatment regimens across PLK1-overexpressing and CIN-positive cancers.

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.

Small-molecule inhibitors of breast cancer-related targets: Potential therapeutic agents for breast cancer

Despite dramatic advances in cancer research and therapy, breast cancer remains a tricky health problem and represents a top biomedical research priority. Nowadays, breast cancer is still the leading cause of malignancy-related deaths in women, and incidence and mortality rates of it are expected to increase significantly the next years. Currently more and more researchers are interested in the study of breast cancer by its arising in young women. The common treatment options of breast cancer are chemotherapy, immunotherapy, hormone therapy, surgery, and radiotherapy. Most of them require chemical agents, such as PARP inhibitors, CDK4/6 inhibitors, and HER2 inhibitors. Recent studies suggest that some targets or pathways, including BRD4, PLK1, PD-L1, HDAC, and PI3K/AKT/mTOR, are tightly related to the occurrence and development of breast cancer. This article reviews the interplay between these targets and breast cancer and summarizes the progress of current research on small molecule inhibitors of these anti-breast cancer targets. The review aims to provide structural and theoretical basis for designing novel anti-breast cancer agents.

LINC00467, Driven by Copy Number Amplification and DNA Demethylation, Is Associated with Oxidative Lipid Metabolism and Immune Infiltration in Breast Cancer

Breast cancer (BRCA) is a malignant tumor with a high incidence and poor prognosis in females. However, its pathogenesis remains unclear. In this study, based on bioinformatic analysis, we found that LINC00467 was highly expressed in BRCA and was associated with tumor metastasis and poor prognosis. The genomic and epigenetic analysis showed that LINC00467 may also be regulated by copy number amplification (CNA), chromatin openness, and DNA methylation. In vitro experiments showed that it could promote the proliferation, migration, and invasion of BRCA cells. Competitive endogenous RNA (ceRNA) regulatory network analysis and weighted gene coexpression network analysis (WGCNA) suggested that LINC00467 may play a role in signaling pathways of peroxisomal lipid metabolism, immunity, and others through microRNAs (miRNAs) targeting transforming growth factor beta 2 (TGFB2). In addition, copy number amplification and high expression of LINC00467 were associated with the low infiltration of CD8+ and CD4+ T cells. In conclusion, we found that LINC00467, driven by copy number amplification and DNA demethylation, may be a potential biomarker for the diagnosis and prognosis of BRCA and a tumor promoter acting as a potential therapeutic target for BRCA as well.

Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1

Background

Breast cancer is the most common malignancy in women. Triple-negative breast cancer (TNBC) refers to a special subtype that is deficient in the expression of estrogen (ER), progesterone (PR), and human epidermal growth factor receptor 2 (HER-2). In this study, a variety of bioinformatics analysis tools were used to screen Hub genes related to the occurrence and development of triple negative breast cancer, and their biological functions were analyzed.

Methods

Gene Expression Omnibus (GEO) breast cancer microarray data GSE62931 was selected as the research object. The differentially expressed genes (DEGs) were screened and the protein-protein interaction (PPI) network of DEGs was constructed using bioinformatics tools. The Hub genes were also screened. The Gene Ontology (GO) knowledgebase and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for biological enrichment analysis. The Gene Expression Profiling Interactive Analysis (GEPIA) online tool was used to verify the expression of the screened genes and patient survival. The effects of polo-like kinase 1 (PLK1) on the proliferation, invasion, migration, and dryness of breast cancer cells were verified using cell counting kit 8 (CCK-8), transwell migration assays, scratch tests, and clone formation tests. An animal model of subcutaneous xenotransplantation of breast cancer was established to evaluate the effect of PLK1 on the proliferation of breast cancer.

Results

A total of 824 DEGs were screened by GSE62931 microarray data; 405 of which were up-regulated and 419 of which were down-regulated. Functional enrichment analysis showed that these DEGs were mainly enriched in cancer-related pathways and were primarily involved in biological processes (BP) such as cell and mitotic division. From the Hub gene screening, PLK1 was further identified as the Hub gene associated with TNBC. Cell and animal experiments indicated that PLK1 promotes the proliferation, invasion, migration, and clone formation of breast cancer cells.

Conclusions

Gene chip combined with bioinformatics methods can effectively analyze the DEGs related to the occurrence and development of breast cancer, and the screening of PLK1 can provide theoretical guidance for further research on the molecular mechanism of breast cancer and the screening of molecular markers.

Targeting DNA damage response kinases in cancer therapy

Cancer cells die when their decimated DNA damage response (DDR) unsuccessfully handles DNA damage. This notion has been successfully exploited when targeting PARP (poly ADP-ribose polymerase) in homologous recombination-deficient cells. With the greater understanding of DDR achieved in the last decade, new cancer therapy targets within the DDR network have been identified. Intriguingly, many of the molecules that have advanced into clinical trials are inhibitors of DDR kinases. This special issue is devoted to discussing the mechanism of cell killing and the level of success that such inhibitors have reached in pre-clinical and clinical settings.

An in-silico method leads to recognition of hub genes and crucial pathways in survival of patients with breast cancer

Breast cancer is a highly heterogeneous disorder characterized by dysregulation of expression of numerous genes and cascades. In the current study, we aim to use a system biology strategy to identify key genes and signaling pathways in breast cancer. We have retrieved data of two microarray datasets (GSE65194 and GSE45827) from the NCBI Gene Expression Omnibus database. R package was used for identification of differentially expressed genes (DEGs), assessment of gene ontology and pathway enrichment evaluation. The DEGs were integrated to construct a protein-protein interaction network. Next, hub genes were recognized using the Cytoscape software and lncRNA-mRNA co-expression analysis was performed to evaluate the potential roles of lncRNAs. Finally, the clinical importance of the obtained genes was assessed using Kaplan-Meier survival analysis. In the present study, 887 DEGs including 730 upregulated and 157 downregulated DEGs were detected between breast cancer and normal samples. By combining the results of functional analysis, MCODE, CytoNCA and CytoHubba 2 hub genes including MAD2L1 and CCNB1 were selected. We also identified 12 lncRNAs with significant correlation with MAD2L1 and CCNB1 genes. According to The Kaplan-Meier plotter database MAD2L1, CCNA2, RAD51-AS1 and LINC01089 have the most prediction potential among all candidate hub genes. Our study offers a framework for recognition of mRNA-lncRNA network in breast cancer and detection of important pathways that could be used as therapeutic targets in this kind of cancer.

The CINs of Polo-Like Kinase 1 in Cancer

Simple Summary

Many alterations specific to cancer cells have been investigated as targets for targeted therapies. Chromosomal instability is a characteristic of nearly all cancers that can limit response to targeted therapies by ensuring the tumor population is not genetically homogenous. Polo-like Kinase 1 (PLK1) is often up regulated in cancers and it regulates chromosomal instability extensively. PLK1 has been the subject of much pre-clinical and clinical studies, but thus far, PLK1 inhibitors have not shown significant improvement in cancer patients. We discuss the numerous roles and interactions of PLK1 in regulating chromosomal instability, and how these may provide an avenue for identifying targets for targeted therapies. As selective inhibitors of PLK1 showed limited clinical success, we also highlight how genetic interactions of PLK1 may be exploited to tackle these challenges.

Abstract

Polo-like kinase 1 (PLK1) is overexpressed near ubiquitously across all cancer types and dysregulation of this enzyme is closely tied to increased chromosomal instability and tumor heterogeneity. PLK1 is a mitotic kinase with a critical role in maintaining chromosomal integrity through its function in processes ranging from the mitotic checkpoint, centrosome biogenesis, bipolar spindle formation, chromosome segregation, DNA replication licensing, DNA damage repair, and cytokinesis. The relation between dysregulated PLK1 and chromosomal instability (CIN) makes it an attractive target for cancer therapy. However, clinical trials with PLK1 inhibitors as cancer drugs have generally displayed poor responses or adverse side-effects. This is in part because targeting CIN regulators, including PLK1, can elevate CIN to lethal levels in normal cells, affecting normal physiology. Nevertheless, aiming at related genetic interactions, such as synthetic dosage lethal (SDL) interactions of PLK1 instead of PLK1 itself, can help to avoid the detrimental side effects associated with increased levels of CIN. Since PLK1 overexpression contributes to tumor heterogeneity, targeting SDL interactions may also provide an effective strategy to suppressing this malignant phenotype in a personalized fashion.

Bioengineered siRNA-Based Nanoplatforms Targeting Molecular Signaling Pathways for the Treatment of Triple Negative Breast Cancer: Preclinical and Clinical Advancements

Triple negative breast cancer (TNBC) is one of the most aggressive types of breast cancer. Owing to the absenteeism of hormonal receptors expressed at the cancerous breast cells, hormonal therapies and other medications targeting human epidermal growth factor receptor 2 (HER2) are ineffective in TNBC patients, making traditional chemotherapeutic agents the only current appropriate regimen. Patients' predisposition to relapse and metastasis, chemotherapeutics' cytotoxicity and resistance and poor prognosis of TNBC necessitates researchers to investigate different novel-targeted therapeutics. The role of small interfering RNA (siRNA) in silencing the genes/proteins that are aberrantly overexpressed in carcinoma cells showed great potential as part of TNBC therapeutic regimen. However, targeting specificity, siRNA stability, and delivery efficiency cause challenges in the progression of this application clinically. Nanotechnology was highlighted as a promising approach for encapsulating and transporting siRNA with high efficiency-low toxicity profile. Advances in preclinical and clinical studies utilizing engineered siRNA-loaded nanotherapeutics for treatment of TNBC were discussed. Specific and selective targeting of diverse signaling molecules/pathways at the level of tumor proliferation and cell cycle, tumor invasion and metastasis, angiogenesis and tumor microenvironment, and chemotherapeutics' resistance demonstrated greater activity via integration of siRNA-complexed nanoparticles.

Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer

Background

Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and prognosis.

Material/Methods

Three independent data sets (GSE45827, GSE38959, GSE65194) were downloaded from the Gene Expression Omnibus (GEO). The R software packages were used to integrate the gene profiles and identify differentially expressed genes (DEGs). A variety of bioinformatics tools were used to explore the hub genes, including the DAVID database, STRING database and Cytoscape software. Reverse transcription quantitative PCR (RT-qPCR) was used to verify the hub genes in 14 pairs of TNBC paired tissues.

Results

In this study, we screened out 161 DEGs between 222 non-TNBC and 126 TNBC samples, of which 105 genes were up-regulated and 56 were down-regulated. These DEGs were enriched for 27 GO terms and two pathways. GO analysis enriched mainly in “cell division”, “chromosome, centromeric region” and “microtubule motor activity”. KEGG pathway analysis enriched mostly in “Cell cycle” and “Oocyte meiosis”. PPI network was constructed and then 10 top hub genes were screened. According to the analysis results of the Kaplan-Meier survival curve, the expression levels of only NUF2, FAM83D and CENPH were associated with the recurrence-free survival in TNBC samples (P < 0.05). RT-qPCR confirmed that the expression levels of NUF2 and FAM83D in TNBC tissues were indeed up-regulated significantly.

Conclusions

The comprehensive analysis showed that NUF2 and FAM83D could be used as potential biomarkers for diagnosis and prognosis of TNBC.

PLK1 inhibition exhibits strong anti-tumoral activity in CCND1-driven breast cancer metastases with acquired palbociclib resistance

A significant proportion of patients with oestrogen receptor (ER) positive breast cancers (BC) develop resistance to endocrine treatments (ET) and relapse with metastatic disease. Here we perform whole exome sequencing and gene expression analysis of matched primary breast tumours and bone metastasis-derived patient-derived xenografts (PDX). Transcriptomic analyses reveal enrichment of the G2/M checkpoint and up-regulation of Polo-like kinase 1 (PLK1) in PDX. PLK1 inhibition results in tumour shrinkage in highly proliferating CCND1-driven PDX, including different RB-positive PDX with acquired palbociclib resistance. Mechanistic studies in endocrine resistant cell lines, suggest an ER-independent function of PLK1 in regulating cell proliferation. Finally, in two independent clinical cohorts of ER positive BC, we find a strong association between high expression of PLK1 and a shorter metastases-free survival and poor response to anastrozole. In conclusion, our findings support clinical development of PLK1 inhibitors in patients with advanced CCND1-driven BC, including patients progressing on palbociclib treatment.

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.

Target Analysis and Mechanism of Podophyllotoxin in the Treatment of Triple-Negative Breast Cancer

Background

As the original compound of many podophyllotoxin derivatives, podophyllotoxin has a beneficial antitumor effect. The mechanism of podophyllotoxin activity in triple-negative breast cancer still needs to be explored.

Methods

We used cell proliferation assay, scratch and transwell experiments, and cell cycle and apoptosis analyses to observe the intervention effect of podophyllotoxin on breast cancer. Furthermore, we analyzed the differences between GSE31448, GSE65194, and GSE45827 in the Gene Expression Omnibus database (GEO) and explored the differential genes using a STRING database. Centiscape2.2, MCODE cluster analysis and KEGG pathway analysis were used to identify the most significant gene differences. Next, we utilized BATMAN-TCM and TCMSP databases for further screening to identify key genes. Finally, quantitative RT-PCR (qRT-PCR) and Western blotting were performed to detect the expression of key targets.

Results

Our research confirmed that podophyllotoxin could not only inhibit the migration and invasion of triple-negative breast cancer but also affect the cell cycle and induce apoptosis. In total, 566 differential genes were obtained by using the GEO database. After topological network analysis, cluster analysis, and molecular docking screening, we finally identified PLK1, CCDC20, and CDK1 as key target genes. The results of the qRT-PCR assay showed that the mRNA levels of PLK1, CDC20, and CDK1 decreased, while the expression of upstream P53 increased, after drug induction. The Gene Set Enrichment Analysis (GSEA) and conetwork analysis showed that PLK1 is a more critical regulatory factor. Further Western blotting analysis revealed that there was a negative regulatory relationship between the key gene PLK1 and P53 on the protein level. The results were presented as the mean ± standard deviation of triplicate experiments and P<0.05 was considered to indicate a statistically significant difference.

Conclusion

Podophyllotoxin has an intervention effect on the development of triple-negative breast cancer. The expression of PLK1, CDC20, and CDK1 in the cell cycle pathway is inhibited by regulating P53. Our research shows that natural drugs inhibit tumor activity by regulating the expression of cyclins, and the combination of natural drugs and modern extensive database analysis has a wide range of potential applications in the development of antitumor therapies.

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.

Multi-Omics Characterization of the 4T1 Murine Mammary Gland Tumor Model

Background: Tumor models are critical for our understanding of cancer and the development of cancer therapeutics. The 4T1 murine mammary cancer cell line is one of the most widely used breast cancer models. Here, we present an integrated map of the genome, transcriptome, and immunome of 4T1.

Results: We found Trp53 (Tp53) and Pik3g to be mutated. Other frequently mutated genes in breast cancer, including Brca1 and Brca2, are not mutated. For cancer related genes, Nav3, Cenpf, Muc5Ac, Mpp7, Gas1, MageD2, Dusp1, Ros, Polr2a, Rragd, Ros1, and Hoxa9 are mutated. Markers for cell proliferation like Top2a, Birc5, and Mki67 are highly expressed, so are markers for metastasis like Msln, Ect2, and Plk1, which are known to be overexpressed in triple-negative breast cancer (TNBC). TNBC markers are, compared to a mammary gland control sample, lower (Esr1), comparably low (Erbb2), or not expressed at all (Pgr). We also found testis cancer antigen Pbk as well as colon/gastrointestinal cancer antigens Gpa33 and Epcam to be highly expressed. Major histocompatibility complex (MHC) class I is expressed, while MHC class II is not. We identified 505 single nucleotide variations (SNVs) and 20 insertions and deletions (indels). Neoantigens derived from 22 SNVs and one deletion elicited CD8⁺ or CD4⁺ T cell responses in IFNγ-ELISpot assays. Twelve high-confidence fusion genes were observed. We did not observe significant downregulation of mismatch repair (MMR) genes or SNVs/indels impairing their function, providing evidence for 6-thioguanine resistance. Effects of the integration of the murine mammary tumor virus were observed at the genome and transcriptome level.

Conclusions: 4T1 cells share substantial molecular features with human TNBC. As 4T1 is a common model for metastatic tumors, our data supports the rational design of mode-of-action studies for pre-clinical evaluation of targeted immunotherapies.

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.

PLK1 promotes proliferation and suppresses apoptosis of renal cell carcinoma cells by phosphorylating MCM3

Minichromosome maintenance 3 (MCM3) protein has been widely studied due to its essential role in DNA replication. In addition, it is overexpressed in several human tumor types. However, the role of this protein in renal cell carcinoma (RCC) is not widely known. In this study, we demonstrated that polo-like kinase 1 (PLK1)-mediated MCM3 phosphorylation regulates proliferation and apoptosis in RCC. Our results confirm that PLK1 and phospho-MCM3 (p-MCM3) are highly expressed in renal cell carcinoma. The expression of PLK1 is closely related to the clinical characteristics of renal cell carcinoma. They play important roles in the proliferation and apoptosis of RCC. In vitro, after overexpression of PLK1 or MCM3, the proliferation of RCC cells was significantly enhanced and cell apoptosis was inhibited, while after knockout, the proliferation of RCC cells was weakened and cell apoptosis was promoted. In addition, Mn2+-Phos-tag SDS-PAGE, western blotting, and immunofluorescence were utilized to determine that MCM3 is a physiological substrate of PLK1, which is phosphorylated on serine 112 (Ser112) in a PLK1-dependent manner. PLK1-mediated MCM3 phosphorylation promotes RCC cell cycle proliferation and suppresses apoptosis in vitro. Moreover, we found that PLK1-mediated MCM3 phosphorylation induced cellular proliferation and decreased apoptosis, as well as tumor growth in mice. Overall, we conclude that PLK1-mediated MCM3 phosphorylation is a novel mechanism to regulate RCC proliferation and apoptosis.

Therapeutic opportunities for PLK1 inhibitors: Spotlight on BRCA1-deficiency and triple negative breast cancers

Polo-Like Kinases (PLKs) are central players of mitotic progression in Eukaryotes. Given the intimate relationship between cell cycle progression and cancer development, PLKs in general and PLK1 in particular have been thoroughly studied as biomarkers and potential therapeutic targets in oncology. The oncogenic properties of PLK1 overexpression across different types of human cancers are attributed to its roles in promoting mitotic entry, centrosome maturation, spindle assembly and cytokinesis. While several academic labs and pharmaceutical companies were able to develop potent and selective inhibitors of PLK1 (PLK1i) for preclinical research, such compounds have reached only limited success in clinical trials despite their great pharmacokinetics. Even though this could be attributed to multiple causes, the housekeeping roles of PLK1 in both normal and cancer cells are most likely the main reason for clinical trials failure and withdraw due to toxicities issues. Therefore, great efforts are being invested to position PLK1i in the treatment of specific types of cancers with revised dosages schemes. In this mini review we focus on two potential niches for PLK1i that are supported by recent evidence: triple negative breast cancers (TNBCs) and BRCA1-deficient cancers. On the one hand, we recollect several lines of strong evidence indicating that TNBCs are among the cancers with highest PLK1 expression and sensitivity to PLK1i. These findings are encouraging because of the limited therapeutics options available for TNBC patients, which rely mainly on classic chemotherapy. On the other hand, we discuss recent evidence that unveils synthetic lethality induction by PLK1 inhibition in BRCA1-deficient cancers cells. This previously unforeseen therapeutic link between PLK1 and BRCA1 is promising because it defines novel therapeutic opportunities for PLK1i not only for breast cancer (i.e. TNBCs with BRCA1 deficiencies), but also for other types of cancers with BRCA1-deficiencies, such as pancreatic and prostate cancers.

Upregulated cyclins may be novel genes for triple-negative breast cancer based on bioinformatic analysis

BACKGROUND

Triple-negative breast cancer (TNBC) is one of the leading causes of death among females around the world. However, the molecular mechanism of the disease among TNBC patients remains to be further studied.

METHODS

In our study, four microarray data and two high throughput sequencing data were acquired from the GEO database, and the differentially expressed genes (DEGs) between TNBC and normal tissues had been analyzed. Analysis of functional enrichment and pathway enrichment of DEGs was conducted by the Funrich software, and protein-protein interaction (PPI) network gained from the STRING, and hub genes were confirmed by the Cytoscape. Kaplan-Meier plotter (KM plotter) online dataset had been used to analyze DEGs of overall survival (OS), and progression-free survival (PFS).

RESULTS

In total, 1638 DEGs were gained in our study covering 984 upregulated and 654 downregulated genes. Moreover, a PPI network was constructed, and cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), and cyclin A2 (CCNA2) were found as top genes with higher node degrees. CDK1, CCNA2, and CCNB1were obviously enriched in the cell cycle. The top upregulated genes including CDK1, CCNB1, CCNA2, and PLK1 were overexpressed in TNBC, and correlated with worse OS in breast cancer. High expression of CCNB1 was correlated with worse PFS in TNBC (HR = 1.42, 95% CI: 1.04-1.94, P = 0.028). Besides, there was a correlation between CCNB1 and CDK1 in TNBC, as well as between CCNA2 and CDK1 (r = 0.804, P < 0.001; r = 0.577, P < 0.001, respectively).

CONCLUSION

Our results suggest that cyclin CDK1, CCNB1, and CCNA2 are overexpressed in TNBC and they could act as novel biomarkers for the diagnosis and treatment of TNBC.

Inhibition of TMEM16A suppresses growth and induces apoptosis in hepatocellular carcinoma

BACKGROUND

Increase of the Ca²⁺-activated chloride channel TMEM16A is contribute to tumorigenesis. However, the expression level of TMEM16A and its underlying molecular mechanism for TMEM16Apromotingliver carcinogenesis is remains unknown.

METHODS

In the present study, the expression of TMEM16A in hepatocellular carcinoma (HCC) tissues were measured by quantitative reverse-transcription polymerase chain reaction (qRT-PCR), Western blot and immunohistochemical. Cell proliferation was detected using CCK-8, EdU staining and colony formation methods. Flow cytometry was carried out for detecting cell cycle distribution and apoptosis rate. Migration and invasion abilities were analyzed using transwell and wound healing assay. Western blot method was performed to analyze protein expression.

RESULTS

Here, we found TMEM16A was significantly increased in HCC tissues, and a higher TMEM16A expression levels were detected in larger tumor size, higher tumor grade, with distant metastasis and poor differentiation. Moreover, overexpression of TMEM16A promoted HCC growth, migration and invasion, and suppressed apoptosis in vitro and in vivo. Knockdown of TMEM16A inhibited HCC growth, migration and invasion, and induced apoptosis in vitro and in vivo. Furthermore, TMEM16A regulated PI3K/AKT-MAKP signaling pathway.

CONCLUSION

Our data indicate that TMEM16A may represent a novel biomarker of HCC and may be a potential therapeutic target for diagnosis and therapy.

Berberine Impairs the Survival of Triple Negative Breast Cancer Cells: Cellular and Molecular Analyses

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype. Non-available targeted therapy for TNBC represents its biggest treatment challenge. Thus, finding new promising effective drugs is urgently needed. In the present study, we investigated how berberine, a natural isoquinoline, impairs the survival of TNBC cells in both cellular and molecular levels. Our experimental model was based on the use of eight TNBC cell lines: MDA-MB-468, MDA-MB-231, HCC70, HCC38, HCC1937, HCC1143, BT-20, and BT-549. Berberine was cytotoxic against all treated TNBC cell lines. The most sensitive cell lines were HCC70 (IC₅₀ = 0.19 µM), BT-20 (IC₅₀ = 0.23 µM) and MDA-MB-468 (IC₅₀ = 0.48 µM). Using flow cytometry techniques, berberine, at 0.5 and 1 µM for 120 and 144 h, not only induced cell cycle arrest, at G1 and/or G2/M phases, but it also triggered significant apoptosis. At the molecular level, these results are consistent with the expression of their related proteins using Western blot assays. Interestingly, while berberine was cytotoxic against TNBC cells, it had no effect on the viability of normal human breast cells MCF10A cultured in a 3D matrigel model. These results suggest that berberine may be a good potential candidate for TNBC drug development.