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

Molecular characterization of pregnancy-associated breast cancer and insights on timing from GEICAM-EMBARCAM study

Pregnancy-associated breast cancer (PABC), diagnosed during or shortly after pregnancy, is a challenging entity with an aggressive biology and poor prognosis. This study analyzed the clinicopathological characteristics and gene expression profile of 33 PABC and 26 non-PABC patients using the nCounter BC360 Panel (NanoString). Notably, PABC showed a higher prevalence of basal-like tumors than non-PABC (48.48% vs 15.38%, p = 0.012) and displayed 73 differentially expressed genes (e.g., DEPDC1, CCNA2, PSAT1, CDKN3, and FAM83D), enriched in DNA repair and cell proliferation pathways. Through the PPI network, we also identified a cluster of cell-cycle regulation genes like MYC, FOXM1, or PTEN. Interestingly, differences emerged when comparing patients diagnosed during gestation (PABC-GS) and the postpartum period (PABC-PP), with PABC-PP showing increased expression of immune-related genes, including PD-1, and greater immune cell infiltration (Tregs, macrophages, neutrophils, B-cells). These findings suggest an enhanced proliferative capacity and impaired DNA repair in PABC, and underscore the role of immune infiltration in postpartum cases; providing insights into its aggressive nature and potential targets.

Integrated analysis of hub genes and intrinsically disordered regions in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most prevalent breast cancer subtype. Its prognosis is poor because there are no effective treatment targets. Despite several attempts, the molecular pathways of TNBC remain unknown, posing a significant clinical barrier in the search for viable targets. Two microarray datasets were used to identify possible targets for TNBC, GSE38959 and GSE45827, retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in TNBC samples compared with normal samples were identified using the GEO2R program. KEGG pathway enrichment and Gene Ontology functions were assessed for DEG pathways and functional annotation using ShinyGO 0.77. The STRING database and Cytoscape program were used for protein-protein interaction (PPI) analysis. Furthermore, we evaluated the predictive significance of hub gene expression in TNBC patients using the GEPIA2 online tool. We developed a comprehensive technique to assess whether intrinsically disordered regions (IDRs) are present in the TNBC hub genes. There were 48 DEGs were identified, all of which were upregulated. A putative protein complex containing these four core genes was selected for further analysis. Breast cancer patients with TTK, TOP2A, CENPF, and CCNA2 upregulation had a poor prognosis; TTK and CCNA2 were partially disordered, whereas TOP2A and CENPF were primarily disordered, according to IDR analysis. According to our study, TOP2A and CENPF may be useful therapeutic targets for disruption of the TNBC PPI network.

Intermittent Fasting Attenuates Obesity-Induced Triple-Negative Breast Cancer Progression by Disrupting Cell Cycle, Epithelial-Mesenchymal Transition, Immune Contexture, and Proinflammatory Signature

Obesity is associated with one-fifth of cancer deaths, and breast cancer is one of the obesity-related cancers. Triple-negative breast cancer (TNBC) lacks estrogen and progesterone receptors and human epidermal growth factor receptor 2, leading to the absence of these therapeutic targets, followed by poor overall survival. We investigated if obesity could hasten TNBC progression and intermittent fasting (IF) could attenuate the progression of obesity-related TNBC. Our meta-analysis of the TNBC outcomes literature showed that obesity led to poorer overall survival in TNBC patients. Fasting-mimicking media reduced cell proliferation disrupted the cell cycle, and decreased cell migration and invasion. IF decreased body weight in obese mice but no change in normal mice. Obese mice exhibited elevated plasma glucose and cholesterol levels, increased tumor volume and weight, and enhanced macrophage accumulation in tumors. The obesity-exacerbated TNBC progression was attenuated after IF, which decreased cyclin B1 and vimentin levels and reduced the proinflammatory signature in the obesity-associated tumor microenvironment. IF attenuated obesity-induced TNBC progression through reduced obesity and tumor burdens in cell and animal experiments, supporting the potential of a cost-effective adjuvant IF therapy for TNBC through lifestyle change. Further evidence is needed of these IF benefits in TNBC, including from human clinical trials.

Overcoming doxorubicin resistance in triple-negative breast cancer using the class I-targeting HDAC inhibitor bocodepsin/OKI-179 to promote apoptosis

BACKGROUND

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with a poor prognosis. Doxorubicin is part of standard curative therapy for TNBC, but chemotherapy resistance remains an important clinical challenge. Bocodepsin (OKI-179) is a small molecule class I histone deacetylase (HDAC) inhibitor that promotes apoptosis in TNBC preclinical models. The purpose of this study was to investigate the combination of bocodepsin and doxorubicin in preclinical TNBC models and evaluate the impact on terminal cell fate, including apoptosis and senescence.

METHODS

TNBC cell lines were treated with doxorubicin and CellTiter-Glo was used to assess proliferation and determine doxorubicin sensitivity. Select cell lines were treated with OKI-005 (in vitro version of bocodepsin) and doxorubicin and assessed for proliferation, apoptosis as measured by Annexin V/PI, and cell cycle by flow cytometry. Immunoblotting was used to assess changes in mediators of apoptosis, cell cycle arrest, and senescence. Senescence was measured by the senescence-associated β-galactosidase assay. An MDA-MB-231 xenograft in vivo model was treated with bocodepsin, doxorubicin, or the combination and assessed for inhibition of tumor growth. shRNA knockdown of p53 was performed in the CAL-51 cell line and proliferation, apoptosis and senescence were assessed in response to combination treatment.

RESULTS

OKI-005 and doxorubicin resulted in synergistic antiproliferative activity in TNBC cells lines regardless of p53 mutation status. The combination led to increased apoptosis and decreased senescence. In vivo, the combination resulted in increased tumor growth inhibition compared to either single agent. shRNA knock-down of p53 led to increased doxorubicin-induced senescence that was decreased with the addition of OKI-005 in vitro.

CONCLUSION

The addition of bocodepsin to doxorubicin resulted in synergistic antiproliferative activity in vitro, improved tumor growth inhibition in vivo, and promotion of apoptosis which makes this a promising combination to overcome doxorubicin resistance in TNBC. Bocodepsin is currently in clinical development and has a favorable toxicity profile compared to other HDAC inhibitors supporting the feasibility of evaluating this combination in patients with TNBC.

Breast Cancer Molecular Subtyping in Practice: A Real-World Study of the APIS Breast Cancer Subtyping Assay in a Consecutive Series of Breast Core Biopsies

The APIS Breast Cancer Subtyping Kit is an mRNA-based assessment of the seven parameters including three biomarkers routinely assessed in all the newly diagnosed breast cancers (BC), oestrogen receptor (ER), progesterone receptor (PR) and HER-2 and an additional four genes that create a novel proliferation signature, MKI67, PCNA, CCNA2 and KIF23. Taken together, the data are used to produce a molecular subtype for every sample. The kit was evaluated against the current standard protocol of immunohistochemistry (IHC) and/or in situ hybridisation (ISH) in breast cancer patients. The data were presented at the weekly breast multidisciplinary team (MDT) meeting. A total of 98 consecutive cases of pre-operative breast cancer core biopsies and two core biopsies of nodal metastases yielding 100 cases were assessed. IHC and APIS results were available for 100 and 99 cases. ER was concordant in 97% cases, PR was concordant in 89% and HER-2 results were concordant with IHC/ISH in 100% of the cases. Ki-67 IHC was discordant in 3% of cases when compared with MK167 alone but discordant in 24% when compared with the four-gene proliferation signature. In conclusion, our study indicates that the APIS Breast Cancer Subtyping Kit is highly concordant when compared to the results produced for ER/PR/HER-2 by IHC and/or ISH. The assay could play a role in the routine assessment of newly diagnosed breast cancer (BC) specimens.

Mechanism of Erianin anti-triple negative breast cancer based on transcriptomics methods and network pharmacology

Triple negative breast cancer (TNBC) is a highly aggressive illness that lacks effective targeted treatments. Although Erianin has shown potential antitumor properties, its precise mechanism of action and target in TNBC remain unclear, hampering the development of drugs. The present study investigated the underlying mechanism of action of Erianin in treating TNBC by using transcriptomics and network pharmacology approaches. We evaluated Erianin's bioactivity in TNBC cell lines and xenograft tumor models. The results showed that Erianin significantly inhibited TNBC cell proliferation and impeded tumor growth. A subsequent analysis of transcriptomic and network pharmacological data identified 51 mutual targets. Analysis of protein-protein interactions identified eight hub targets. Furthermore, molecular docking indicated that the PPARA binding energy was the lowest for Erianin among the hub targets, followed by ROCK2, PDGFRB, CCND1, MUC1, and CDK1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis showed that the common targets were associated with multiple cancer-related signaling pathways, including focal adhesion, PI3K-Akt signaling pathway, Rap1 signaling pathway, microRNAs in cancer, and human papillomavirus infection. The results of the Western blot and immunohistochemistry experiment further showed that Erianin could suppress PI3K/Akt signaling pathway activation. After co-incubation with SC79, the cell inhibition rate of Erianin was decreased, which further confirmed that Erianin inhibits TNBC progression via the PI3K-AKT signaling pathway. In conclusion, our results indicated that Erianin has the potential to inhibit the proliferation of TNBC by downregulating the PI3K/AKT signaling pathway by transcriptomics and network pharmacology. Therefore, Erianin appears to be a promising compound for the effective treatment of TNBC.

Comprehensive and Accurate Molecular Profiling of Breast Cancer through mRNA Expression of ESR1, PGR, ERBB2, MKI67, and a Novel Proliferation Signature

BACKGROUND

An accurate status determination of breast cancer biomarkers (ER, PR, HER2, Ki67) is crucial for guiding patient management. The "gold standard" for assessing these biomarkers in FFPE tissue is IHC, which faces challenges in standardization and exhibits substantial variability. In this study, we compare the concordance of a new commercial RT-qPCR kit with IHC in determining BC biomarker status.

METHODS

The performance was evaluated using 634 FFPE specimens, which underwent histological analysis in accordance with standard of care methods. HER2 2+ tumors were referred to ISH testing. An immunoreactive score of ≥2/12 was considered positive for ER/PR and 20% staining was used as a cut-off for Ki67 high/low score. RT-qPCR and results calling were performed according to the manufacturer's instructions.

RESULTS

High concordance with IHC was seen for all markers (93.2% for ER, 87.1% for PR, 93.9% for HER2, 77.9% for Ki67 and 80.1% for proliferative signature (assessed against Ki67 IHC)).

CONCLUSIONS

By assessing the concordance with the results obtained through IHC, we sought to demonstrate the reliability and utility of the kit for precise BC subtyping. Our findings suggest that the kit provides a highly precise and accurate quantitative assessment of BC biomarkers.

Hsa_circ_0137652 Regulates miR-1205/CCNB1 Axis to Accelerate the Malignancy of Breast Cancer

CircRNAs have become a hotspot in tumor research owing to their high stability and specific functions. We investigated the function of hsa_circ_0137652 in the onset and progression of breast cancer (BC). The expression of circ_0137652, miR-1205, and CCNB1 in BC tissues and cell lines were detected using RT-qPCR and/or western blotting. Dual-luciferase reporter and RNA immunoprecipitation chip assays were used to confirm any potential connections between circ_0137652, miR-1205, and CCNB1. CCK-8 and clone formation assays (CFA) were used to measure the proliferation of BC cells. The Transwell assay was used to investigate the migration of BC cells, and the impact of circ_0137652 on BC tumor formation in vivo was validated using animal experiments. RT-qPCR results showed that circ_0137652 and CCNB1 in breast cancer tissues were notably upregulated in normal tissues, whereas miR-1205 was prominently downregulated. After silencing circ_0137652, the growth and migration of BC cells were reduced. Animal experiments showed that circ_0137652 hampers the tumorigenesis of BC cells in vivo. Additionally, we found that circ_0137652 functions as a sponge for miR-1205. Moreover, the miR-1205 inhibitor notably facilitated cell proliferation and migration and attenuated the action of circ_0137652 knockdown. Furthermore, miR-1205 inhibits BC progression by targeting CCNB1. Circ_0137652 controls the miR-1205/CCNB1 axis to induce increased breast cancer malignancy. Our findings suggest that circ_0137652 may be a novel target for BC therapy.

Deubiquitylase YOD1 regulates CDK1 stability and drives triple-negative breast cancer tumorigenesis

BACKGROUND

Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with the initiation and progression of Triple-negative breast cancer (TNBC). The publicly available TCGA database of breast cancer data was used to analyze the OTUD deubiquitinating family members that were correlated with survival of breast cancer and ovarian tumor domain-containing 2 (OTUD-2), or YOD1 was identified. The aim of present study was to assess YOD1 expression and function in human TNBC and then explored the underlying molecular events.

METHODS

We detected the expression of YOD1 in 32 TNBC and 44 NTNBC samples by qRT-PCR, Western blot and immunohistochemistry. Manipulation of YOD1 expression was assessed in vitro and in vivo for TNBC cell proliferation, migration, invasion, cell-cycle and drug resistance, using colony formation assay, transwell assay, CCK8 assay, TUNEL assay, flow cytometric analysis and xenograft tumor assay. Next, proteomic analysis, Western blot, proximity ligation assay, Immunoprecipitation, and Immunofluorescence were conducted to assess downstream targets.

RESULTS

It was found that YOD1 was significantly upregulated in TNBC tissues compared with non-triple-negative breast cancer (NTNBC), which was positively correlated with poor survival in TNBC patients. Knockdown of YOD1 effectively inhibited TNBC cell migration, proliferation, cell cycle and resistance to cisplatin and paclitaxel. Mechanistically, YOD1 promoted TNBC progression in a manner dependent on its catalytic activity through binding with CDK1, leading to de-polyubiquitylation of CDK1 and upregulation of CDK1 expression. In addition, YOD1 overexpression was found to be correlated with CDK1 overexpression in human TNBC specimens. Finally, in vivo study demonstrated that YOD1 knockdown or YOD1 inhibitor could inhibit CDK1 expression and suppress the growth and metastasis of TNBC tumors.

CONCLUSION

Our study highlights that YOD1 functions as an oncogene in TNBC via binding to CDK1 and mediated its stability and oncogenic activity. Interfering with YOD1 expression or YOD1 inhibitor could suppress TNBC cells in vitro and in vivo, suggesting that YOD1 may prove to be a promising therapeutic target for TNBC.

Ampelopsin induces MDA-MB-231 cell cycle arrest through cyclin B1-mediated PI3K/AKT/mTOR pathway in vitro and in vivo

Breast cancer is one of the most common malignant tumors in women and it is the most frequently diagnosed cancer in the world. Ampelopsin (AMP) is a purified component from the root of Ampelopsis grossedentata. It is reported that AMP could significantly inhibit the proliferation of breast cancer cells. However, the antitumor mechanism against breast cancer has not yet been fully elucidated. The purpose of this work was to study the role of AMP against breast cancer MDA-MB-231 cells and to further investigate the underlying mechanism. PI3K/AKT/mTOR plays a very important role in tumor cell growth and proliferation and we hypothesize that AMP may inhibit this pathway. In the present work, the results showed that AMP could significantly inhibit the growth of breast cancer MDA-MB-231 cells in vitro and in vivo. In addition, treatment with AMP decreased the levels of PI3K, AKT and mTOR, as well as cyclin B1 expression, followed by p53/p21 pathway activation to arrest the cell cycle at G2/M. Moreover, it demonstrated a positive association between cyclin B1 and PI3K/AKT/mTOR levels. Importantly, this pathway was found to be regulated by cyclin B1 in MDA-MB-231 cells treated with AMP. Also, it was observed that cyclin B1 overexpression attenuated cell apoptosis and weakened the inhibitory effects of AMP on cell proliferation. Together, AMP could inhibit breast cancer MDA-MB-231 cell proliferation in vitro and in vivo, due to cell cycle arrest at G2/M by inactivating PI3K/AKT/mTOR pathway regulated by cyclin B1.

Z-Guggulsterone Induces Cell Cycle Arrest and Apoptosis by Targeting the p53/CCNB1/PLK1 Pathway in Triple-Negative Breast Cancer

Myrrh is the dried resin of Commiphora Myrrh Engl., which exerts anticancer properties. However, its effects and molecular mechanisms in triple-negative breast cancer (TNBC) remain unclear. In this study, we used network pharmacology to screen Z-Guggulsterone (Z-GS) as a characteristic active component of myrrh. Cell Counting Kit-8 proliferation assays showed that Z-GS inhibited proliferation of the TNBC cell lines MDA-MB-468 and BT-549. Transwell assays also showed that Z-GS inhibited TNBC migration and invasion phenotypes. Our network pharmacology combined with RNA-sequencing analyses showed that Z-GS affected cell cycle and apoptosis processes in TNBC cells, mainly via p53 signaling, to regulate key CCNB1 (cyclin B1), PLK1 (polo-like kinase 1), and p53 targets. Flow cytometry revealed that Z-GS arrested the cell cycle at the G2/M phase and increased apoptosis in TNBC cells. Western blotting and quantitative real-time polymerase chain reaction studies confirmed that Z-GS functioned via the p53-mediated downregulation of CCNB1 and PLK1 expression. In vivo studies showed that Z-GS effectively inhibited TNBC progression. Collectively, Z-GS exhibited potential anti-TNBC activity and may functions via the p53/CCNB1/PLK1 pathway.

WINNER: A network biology tool for biomolecular characterization and prioritization

BACKGROUND AND CONTRIBUTION

In network biology, molecular functions can be characterized by network-based inference, or "guilt-by-associations." PageRank-like tools have been applied in the study of biomolecular interaction networks to obtain further the relative significance of all molecules in the network. However, there is a great deal of inherent noise in widely accessible data sets for gene-to-gene associations or protein-protein interactions. How to develop robust tests to expand, filter, and rank molecular entities in disease-specific networks remains an ad hoc data analysis process.

RESULTS

We describe a new biomolecular characterization and prioritization tool called Weighted In-Network Node Expansion and Ranking (WINNER). It takes the input of any molecular interaction network data and generates an optionally expanded network with all the nodes ranked according to their relevance to one another in the network. To help users assess the robustness of results, WINNER provides two different types of statistics. The first type is a node-expansion p-value, which helps evaluate the statistical significance of adding "non-seed" molecules to the original biomolecular interaction network consisting of "seed" molecules and molecular interactions. The second type is a node-ranking p-value, which helps evaluate the relative statistical significance of the contribution of each node to the overall network architecture. We validated the robustness of WINNER in ranking top molecules by spiking noises in several network permutation experiments. We have found that node degree-preservation randomization of the gene network produced normally distributed ranking scores, which outperform those made with other gene network randomization techniques. Furthermore, we validated that a more significant proportion of the WINNER-ranked genes was associated with disease biology than existing methods such as PageRank. We demonstrated the performance of WINNER with a few case studies, including Alzheimer's disease, breast cancer, myocardial infarctions, and Triple negative breast cancer (TNBC). In all these case studies, the expanded and top-ranked genes identified by WINNER reveal disease biology more significantly than those identified by other gene prioritizing software tools, including Ingenuity Pathway Analysis (IPA) and DiAMOND.

CONCLUSION

WINNER ranking strongly correlates to other ranking methods when the network covers sufficient node and edge information, indicating a high network quality. WINNER users can use this new tool to robustly evaluate a list of candidate genes, proteins, or metabolites produced from high-throughput biology experiments, as long as there is available gene/protein/metabolic network information.

Microarray data reveal potential genes that regulate triple-negative breast cancer

Objective

Triple-negative breast cancer (TNBC) is characterized by a lack of targeted therapies and poor patient prognosis, and its underlying pathological mechanisms remain unclear. This study aimed to identify potential key genes and related pathways that are required for TNBC development.

Methods

We screened the Gene Expression Omnibus database for transcriptome data and identified differently expressed genes in TNBC. Then, we performed Gene Ontology analysis to determine the genes and pathways involved in TNBC development. We correlated significantly expressed genes and miRNAs using miRDB, TargetScan, miRWalk, and DIANA, and then validated the expression of CDK1 and miR-143-3p in TNBC patients.

Results

Eighteen genes were significantly upregulated in TNBC patients, and these were found to be enriched in cell metabolic process, cell division, mitochondrion, and respiratory chain. MiR-143-3p was found to be an upstream regulator of CDK1. Validation experiments revealed that CDK1 was upregulated while miR-143-3p was downregulated in clinical TNBC specimens.

Conclusions

Collectively, our results revealed 18 upregulated genes in TNBC. Notably, CDK1 and its related microRNA miR-143-3p could be potential therapeutic targets for TNBC.

Identification of Key Prognostic Genes of Triple Negative Breast Cancer by LASSO-Based Machine Learning and Bioinformatics Analysis

Improved insight into the molecular mechanisms of triple negative breast cancer (TNBC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify key genes which may affect the prognosis of TNBC patients by bioinformatic analysis. In our study, the RNA sequencing (RNA-seq) expression data of 116 breast cancer lacking ER, PR, and HER2 expression and 113 normal tissues were downloaded from The Cancer Genome Atlas (TCGA). We screened out 147 differentially co-expressed genes in TNBC compared to non-cancerous tissue samples by using weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were constructed, revealing that 147 genes were mainly enriched in nuclear division, chromosomal region, ATPase activity, and cell cycle signaling. After using Cytoscape software for protein-protein interaction (PPI) network analysis and LASSO feature selection, a total of fifteen key genes were identified. Among them, BUB1 and CENPF were significantly correlated with the overall survival rate (OS) difference of TNBC patients (p value < 0.05). In addition, BUB1, CCNA2, and PACC1 showed significant poor disease-free survival (DFS) in TNBC patients (p value < 0.05), and may serve as candidate biomarkers in TNBC diagnosis. Thus, our results collectively suggest that BUB1, CCNA2, and PACC1 genes could play important roles in the progression of TNBC and provide attractive therapeutic targets.

E2F1 transcriptionally regulates CCNA2 expression to promote triple negative breast cancer tumorigenicity

BACKGROUND

Triple-negative breast cancer (TNBC) is a highly malignant breast cancer subtype with a poor prognosis. The cell cycle regulator cyclin A2 (CCNA2) plays a role in tumor development. Herein, we explored the role of CCNA2 in TNBC.

METHODS

We analyzed CCNA2 expression in 15 pairs of TNBC and adjacent tissues and assessed the relationship between CCNA2 expression using the tissue microarray cohort. Furthermore, we used two TNBC cohort datasets to analyze the correlation between CCNA2 and E2F transcription factor 1 (E2F1) and a luciferase reporter to explore their association. Through rescue experiments, we analyzed the effects of E2F1 knockdown on CCNA2 expression and cellular behavior.

RESULTS

We found that CCNA2 expression in TNBC was significantly higher than that in adjacent tissues with similar observations in MDA-MB-231 and MDA-MB-468 cells. E2F1 was highly correlated with CCNA2 as observed through bioinformatics analysis (R= 0.80, P< 0.001) and through TNBC tissue verification analysis (R= 0.53, P< 0.001). We determined that E2F1 binds the +677 position within the CCNA2 promoter. Moreover, CCNA2 overexpression increased cell proliferation, invasion, and migration owing to E2F1 upregulation in TNBC.

CONCLUSION

Our data indicate that E2F1 promotes TNBC proliferation and invasion by upregulating CCNA2 expression. E2F1 and CCNA2 are potential candidates that may be targeted for effective TNBC treatment.

Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer

Introduction

Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer.

Methods

Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson’s correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan–Meier. Immunohistochemistry was used to analyze the expression of CCNA2.

Results

A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of CCNA2 was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that CCNA2 expression in carcinoma tissues was elevated compared with normal control.

Discussion

CCNA2 identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research.

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

BACKGROUND

Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV.

METHODS

Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored.

RESULTS

A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8).

CONCLUSION

The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.

Interplay of tRNA-Derived Fragments and T Cell Activation in Breast Cancer Patient Survival

Effector CD8+ T cell activation and its cytotoxic function are positively correlated with improved survival in breast cancer. tRNA-derived fragments (tRFs) have recently been found to be involved in gene regulation in cancer progression. However, it is unclear how interactions between expression of tRFs and T cell activation affect breast cancer patient survival. We used Kaplan-Meier survival and multivariate Cox regression models to evaluate the effect of interactions between expression of tRFs and T cell activation on survival in 1081 breast cancer patients. Spearman correlation analysis and weighted gene co-expression network analysis were conducted to identify genes and pathways that were associated with tRFs. tRFdb-5024a, 5P_tRNA-Leu-CAA-4-1, and ts-49 were positively associated with overall survival, while ts-34 and ts-58 were negatively associated with overall survival. Significant interactions were detected between T cell activation and ts-34 and ts-49. In the T cell exhaustion group, patients with a low level of ts-34 or a high level of ts-49 showed improved survival. In contrast, there was no significant difference in the activation group. Breast cancer related pathways were identified for the five tRFs. In conclusion, the identified five tRFs associated with overall survival may serve as therapeutic targets and improve immunotherapy in breast cancer.

Identification of prognosis-related genes and construction of multi-regulatory networks in pancreatic cancer microenvironment by bioinformatics analysis

Background

As one of the most lethal cancers, pancreatic cancer has been characterized by abundant supportive tumor-stromal cell microenvironment. Although the advent of tumor-targeted immune checkpoint blockers has brought light to patients with other cancers, its clinical efficacy in pancreatic cancer has been greatly limited due to the protective stroma. Thus, it is urgent to find potential new targets and establish multi-regulatory networks to predict patient prognosis and improve treatment.

Methods

We followed a strategy based on mining the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm to obtain the immune scores and stromal scores. Differentially expressed genes (DEGs) associated with poor overall survival of pancreatic cancer were screened from a TCGA cohort. By comparing global gene expression with high vs. low immune scores and subsequent Kaplan–Meier analysis, DEGs that significantly correlate with poor overall survival of pancreatic cancer in TCGA cohort were extracted. After constructing the protein–protein interaction network using STRING and limiting the genes within the above DEGs, we utilized RAID 2.0, TRRUST v2 database and degree and betweenness analysis to obtain non-coding RNA (ncRNA)-pivotal nodes and TF-pivotal nodes. Finally, multi-regulatory networks have been constructed and pivotal drugs with potential benefit for pancreatic cancer patients were obtained by screening in the DrugBank.

Results

In this study, we obtained 246 DEGs that significantly correlate with poor overall survival of pancreatic cancer in the TCGA cohort. With the advent of 38 ncRNA-pivotal nodes and 7 TF-pivotal nodes, the multi-factor regulatory networks were constructed based on the above pivotal nodes. Prognosis-related genes and factors such as HCAR3, PPY, RFWD2, WSPAR and Amcinonide were screened and investigated.

Conclusion

The multi-regulatory networks constructed in this study are not only beneficial to improve treatment and evaluate patient prognosis with pancreatic cancer, but also favorable for implementing early diagnosis and personalized treatment. It is suggested that these factors may play an essential role in the progression of pancreatic cancer.