Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Designing of neoepitopes based vaccine against breast cancer using integrated immuno and bioinformatics approach

Cancer is characterized by genetic instability due to accumulation of somatic mutations in the genes which generate neoepitopes (mutated epitopes) for targeting by Cytotoxic T lymphocytes (CTL). Breast cancer has a high transformation rate with unique composition of mutational burden and neoepitopes load that open a platform to designing a neoepitopes-based vaccine. Neoepitopes-based therapeutic cancer vaccines designed by neoantigens have shown to be feasible, nontoxic, and immunogenic in cancer patients. Stimulation of CTL by neoepitope-based vaccine of self-antigenic proteins plays a key role in distinguishing cancer cells from normal cells and selectively targets only malignant cells. A neoepitopes-based vaccine to combat breast cancer was designed by combining immunology and bioinformatics approaches. The vaccine construct was assembled by the fusion of CTL neoepitopes, helper sequences (used for better separation of the epitopes), and adjuvant together with linkers. The neoepitopes were identified from somatic mutations in the MUC16, TP53, RYR2, F5, DNAH17, ASPM, and ABCA13 self-antigenic proteins. The vaccine construct was undertaken to study the immune simulations (IS), physiochemical characteristics (PP), molecular docking (MD) and simulations, and cloning in appropriate vector. Together, these parameters establish safety, stability, and a strong binding affinity against class I MHC molecules capable of inducing a complete immune response against breast cancer cells.Communicated by Ramaswamy H. Sarma.

KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker

KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.

Doxorubicin downregulates cell cycle regulatory hub genes in breast cancer cells

Breast cancer (BC) is the leading commonly diagnosed cancer in the world, with complex mechanisms underlying its development. There is an urgent need to enlighten key genes as potential therapeutic targets crucial to advancing BC treatment. This study sought to investigate the influence of doxorubicin (DOX) on identified key genes consistent across numerous BC datasets obtained through bioinformatic analysis. To date, a meta-analysis of publicly available coding datasets for expression profiling by array from the Gene Expression Omnibus (GEO) has been carried out. Differentially Expressed Genes (DEGs) identified using GEO2R revealed a total of 23 common DEGs, including nine upregulated genes and 14 downregulated genes among the datasets of three platforms (GPL570, GPL6244, and GPL17586), and the commonly upregulated DEGs, showed significant enrichment in the cell cycle in KEGG analysis. The top nine genes, NUSAP1, CENPF, TPX2, PRC1, ANLN, BUB1B, AURKA, CCNB2, and CDK-1, with higher degree values and MCODE scores in the cytoscape program, were regarded as hub genes. The hub genes were activated in disease states commonly across all the subclasses of BC and correlated with the unfavorable overall survival of BC patients, as verified by the GEPIA and UALCAN databases. qRT-PCR confirmed that DOX treatment resulted in reduced expression of these genes in BC cell lines, which reinforces the evidence that DOX remains an effective drug for BC and suggests that developing modified formulations of doxorubicin to reduce toxicity and resistance, could enhance its efficacy as an effective therapeutic option for BC.

Reversal of the tamoxifen‑resistant breast cancer malignant phenotype by proliferation inhibition with bromosulfonamidine amino‑podophyllotoxin

One of the lignans isolated from plants within the genus Podophyllum is podophyllotoxin (PPT). PPT and its derivatives are pharmacologically active compounds with potential antiproliferative properties in several kinds of tumors. Although these compounds have been used to treat other malignancies, no PPT derivative-based chemotherapeutic agent has been used to cure tamoxifen (TAM)-resistant breast cancer in clinical trials, to the best of our knowledge. Thus, using TAM-resistant breast cancer as a disease model, the present study assessed the effects of a recently synthesized PPT derivative, bromosulfonamidine amino-PPT (BSAPPT), on TAM-resistant breast cancer. Using the tamoxifen-resistant breast cancer cell model (MCF-7/TAMR) in vitro, Cell Counting Kit-8 and colony formation assays were adopted to evaluate the effect of BSAPPT on cell proliferation. Cell apoptosis and cell cycle assays were used to assess the influence of BSAPPT on cell apoptosis and the cell cycle in MCF-7/TAMR. The targets of the potential mechanism of action were analyzed by RT-qPCR and western blotting. The present study demonstrated that BSAPPT suppressed MCF-7/TAMR cell proliferation in a dose-dependent manner. By modulating the level of expression of genes linked to both apoptosis and the cell cycle, BSAPPT triggered MCF-7/TAMR cells to undergo apoptosis and prevented them from entering the cell cycle. Consequently, BSAPPT blocked these cells from proliferating, thereby halting the malignant advancement of TAM-resistant breast cancer. Therefore, these findings indicate that new therapeutic agents involving BSAPPT may be developed to facilitate the treatment of TAM-resistant breast cancer.

KIF2C as a potential therapeutic target: insights from lung adenocarcinoma subtype classification and functional experiments

Objective: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. Methods: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and in vivo experiments. Results: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. Conclusion: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD.

A Case of Multi-Organ Tuberculosis Misdiagnosed as Lung Cancer and a Literature Review

Background

Tuberculosis (TB) is a very common and easily diagnosed as a malignancy. However, studies have described the difference between TB and lung cancer. Single-organ TB and lung cancer are often easily distinguished clinically. Atypical systemic hematogenous disseminated TB (HDTB) is uncommon, including rare cases involving multiple organs such as cervical lymph nodes, pleura, liver, and lung TB simultaneously, which are more confusing and easily misdiagnosed in clinical practice.

Case Presentation

A HIV-negative 56-year-old male was hospitalized for chest disease with main symptoms of chest tightness, chest pain, fatigue, anorexia, and weight loss. Heart rate 109 times/min, the computed tomography (CT) scans of the neck, chest, and abdomen revealed multiple nodules in the right pleura, right pleural encapsulated effusion, and limited, incomplete expansion of the middle and lower lobes of the right lung, enlarged lymph nodes in the right hilar and mediastinal and diaphragm groups, and multiple slightly low-density nodules in the liver, bone destruction in the 2nd thoracic vertebra, raising the possibility of multiple liver metastases of right lung cancer and malignant pleural fluid. The lymph nodes in the neck, mediastinum, abdomen, and pelvis were enlarged bilaterally. After comprehensive analysis, the patient was diagnosed with atypical systemic HDTB. After three months of conventional anti-TB treatment, the patient refused our hospital follow-up, and his symptoms improved significantly during the telephone follow-up.

Conclusion

Most previous TB misdiagnoses involved a single organ, and this case enriches the clinical experience of diagnosing atypical HDTB. We encourage clinicians to establish a dynamic diagnostic and therapeutic mindset, emphasizing the value of biopsy and pathology.

DLGAP5 Regulates the Proliferation, Migration, Invasion, and Cell Cycle of Breast Cancer Cells via the JAK2/STAT3 Signaling Axis

The aim of this study was to discover new biomarkers to detect breast cancer (BC), which is an aggressive cancer with a high mortality rate. In this study, bioinformatic analyses (differential analysis, weighted gene co-expression network analysis, and machine learning) were performed to identify potential candidate genes for BC to study their molecular mechanisms. Furthermore, Quantitative Real-time PCR and immunohistochemistry assays were used to examine the protein and mRNA expression levels of a particular candidate gene (DLGAP5). And the effects of DLGAP5 on cell proliferation, migration, invasion, and cell cycle were further assessed using the Cell Counting Kit-8 assay, colony formation, Transwell, wound healing, and flow cytometry assays. Moreover, the changes in the JAK2/STAT3 signaling-pathway-related proteins were detected by Western Blot. A total of 44 overlapping genes were obtained by differential analysis and weighted gene co-expression network analysis, of which 25 genes were found in the most tightly connected cluster. Finally, NEK2, CKS2, UHRF1, DLGAP5, and FAM83D were considered as potential biomarkers of BC. Moreover, DLGAP5 was highly expressed in BC. The down-regulation of DLGAP5 may inhibit the proliferation, migration, invasion, and cell cycle of BC cells, and the opposite was true for DLGAP5 overexpression. Correspondingly, silencing or overexpression of the DLGAP5 gene inhibited or activated the JAK2/STAT3 signaling pathway, respectively. DLGAP5, as a potential biomarker of BC, may impact the cell proliferation, migration, invasion, cell cycle, and BC development by modulating the JAK2/STAT3 signaling pathway.

A Network of 17 Microtubule-Related Genes Highlights Functional Deregulations in Breast Cancer

A wide panel of microtubule-associated proteins and kinases is involved in coordinated regulation of the microtubule cytoskeleton and may thus represent valuable molecular markers contributing to major cellular pathways deregulated in cancer. We previously identified a panel of 17 microtubule-related (MT-Rel) genes that are differentially expressed in breast tumors showing resistance to taxane-based chemotherapy. In the present study, we evaluated the expression, prognostic value and functional impact of these genes in breast cancer. We show that 14 MT-Rel genes (KIF4A, ASPM, KIF20A, KIF14, TPX2, KIF18B, KIFC1, AURKB, KIF2C, GTSE1, KIF15, KIF11, RACGAP1, STMN1) are up-regulated in breast tumors compared with adjacent normal tissue. Six of them (KIF4A, ASPM, KIF20A, KIF14, TPX2, KIF18B) are overexpressed by more than 10-fold in tumor samples and four of them (KIF11, AURKB, TPX2 and KIFC1) are essential for cell survival. Overexpression of all 14 genes, and underexpression of 3 other MT-Rel genes (MAST4, MAPT and MTUS1) are associated with poor breast cancer patient survival. A Systems Biology approach highlighted three major functional networks connecting the 17 MT-Rel genes and their partners, which are centered on spindle assembly, chromosome segregation and cytokinesis. Our studies identified mitotic Aurora kinases and their substrates as major targets for therapeutic approaches against breast cancer.

KIF2C is a prognostic biomarker associated with immune cell infiltration in breast cancer

BACKGROUND

The kinesin-13 family member 2C (KIF2C) is a versatile protein participating in many biological processes. KIF2C is frequently up-regulated in multiple types of cancer and is associated with cancer development. However, the role of KIF2C in immune cell infiltration of tumor microenvironment and immunotherapy in breast cancer remains unclear.

METHODS

The expression of KIF2C was analyzed using Tumor Immune Estimation Resource (TIMER) database and further verified by immunohistochemical staining in human breast cancer tissues. The correlation between KIF2C expression and clinical parameters, the impact of KIF2C on clinical prognosis and independent prognostic factors were analyzed by using TCGA database, the Kaplan-Meier plotter, and Univariate and multivariate Cox analyses, respectively. The nomograms were constructed according to independent prognostic factors and validated with C-index, calibration curves, ROC curves, and decision curve analysis. A gene set enrichment analysis (GSEA) was performed to explore the underlying molecular mechanisms of KIF2C. The degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA (ssGSEA). The Tumor mutational burden and Tumor Immune Dysfunction and Rejection (TIDE) were used to analyze immunotherapeutic efficiency. Finally, the KIF2C-related competing endogenous RNA (ceRNA) network was constructed to predict the putative regulatory mechanisms of KIF2C.

RESULTS

KIF2C was remarkably up-regulated in 18 different types of cancers, including breast cancer. Kaplan-Meier survival analysis showed that high KIF2C expression was associated with poor overall survival (OS). KIF2C expression was associated with clinical parameters such as age, TMN stage, T status, and molecular subtypes. We identified age, stage, estrogen receptor (ER) and KIF2C expression as OS-related independent prognosis factors for breast cancer. An OS-related nomogram was developed based on these independent prognosis factors and displayed good predicting ability for OS of breast cancer patients. Finally, our results revealed that KIF2C was significantly related to immune cell infiltration, tumor mutational burden, and immunotherapy in patients with breast cancer.

CONCLUSION

KIF2C was overexpressed in breast cancer and was positively correlated with immune cell infiltration and immunotherapy response. Therefore, KIF2C can serve as a potential biomarker for prognosis and immunotherapy in breast cancer.

Recent Trends in Biosensing and Diagnostic Methods for Novel Cancer Biomarkers

Cancer is one of the major public health issues in the world. It has become the second leading cause of death, with approximately 75% of cancer deaths transpiring in low- or middle-income countries. It causes a heavy global economic cost estimated at more than a trillion dollars per year. The most common cancers are breast, colon, rectum, prostate, and lung cancers. Many of these cancers can be treated effectively and cured if detected at the primary stage. Nowadays, around 50% of cancers are detected at late stages, leading to serious health complications and death. Early diagnosis of cancer diseases substantially increases the efficient treatment and high chances of survival. Biosensors are one of the potential screening methodologies useful in the early screening of cancer biomarkers. This review summarizes the recent findings about novel cancer biomarkers and their advantages over traditional biomarkers, and novel biosensing and diagnostic methods for them; thus, this review may be helpful in the early recognition and monitoring of treatment response of various human cancers.

Identification of prognostic and therapeutic biomarkers in type 2 papillary renal cell carcinoma

BACKGROUND

Papillary renal cell carcinoma (PRCC) can be divided into type 1 (PRCC1) and type 2 (PRCC2) and PRCC2 share a more invasive phenotype and worse prognosis. This study aims to identify potential prognostic and therapeutic biomarkers in PRCC2.

METHODS

A cohort from The Cancer Genome Atlas and two datasets from Gene Expression Omnibus were examined. Common differentially expressed genes (DEGs) were screened and potential biomarkers were explored by using Kaplan-Meier method and cox regression analysis. Functional enrichment analysis was utilized to evaluate the potential biological functions. Tumor infiltrating immune cells were estimated by CIBERSORT algorithm. Ninety-two PRCC2 samples from Fudan University Shanghai Cancer Center were obtained, and immunostaining was performed to validate prognostic and therapeutic significance of the potential biomarker.

RESULTS

PRCC2 has worse overall survival and shares distinct molecular characteristics from PRCC1. There was significant higher expression level of Targeting protein for Xklp2 (TPX2) in PRCC2 compared with normal tissues. Higher expression level of TPX2 was significantly associated with worse overall survival in PRCC2 and kinesin family genes expression were found significantly elevated in high risk PRCC2. Abundance of tumor infiltrating M1 macrophage was significantly higher in PRCC2 and it was also associated with worse overall survival. In the FUSCC cohort, higher TPX2 expression was significantly correlated with worse overall and progression-free survival. Retrospective analysis indicated that mTOR inhibitor (everolimus) had greater efficacy in the high-risk group than in the low-risk group (overall response rate: 28.6% vs. 16.7%) and that everolimus had greater efficacy than sunitinib in the high-risk group (overall response rate: 28.6% vs. 20%).

CONCLUSIONS

TPX2 was a prognostic and therapeutic biomarker in PRCC2. Higher abundance of tumor infiltrating M1 macrophage was significantly associated with worse overall survival in PRCC2. mTOR inhibitors may have good efficacy in patients with high-risk PRCC2.

Integrated transcriptome and network analysis identifies EZH2/CCNB1/PPARG as prognostic factors in breast cancer

Breast cancer (BC) has high morbidity, with significant relapse and mortality rates in women worldwide. Therefore, further exploration of its pathogenesis is of great significance. This study selected therapy genes and possible biomarkers to predict BC using bioinformatic methods. To this end, the study examined 21 healthy breasts along with 457 BC tissues in two Gene Expression Omnibus (GEO) datasets and then identified differentially expressed genes (DEGs). Survival-associated DEGs were screened using the Kaplan-Meier curve. Based on Gene Ontology (GO) annotation, survival-associated DEGs were mostly associated with cell division and cellular response to hormone stimulus. The enriched Kyoto Encyclopedia of Gene and Genome (KEGG) pathway was mostly correlated with cell cycle and tyrosine metabolism. Using overlapped survival-associated DEGs, a survival-associated PPI network was constructed. PPI analysis revealed three hub genes (EZH2, CCNB1, and PPARG) by their degree of connection. These hub genes were confirmed using The Cancer Genome Atlas (TCGA)-BRCA dataset and BC tissue samples. Through Gene Set Enrichment Analysis (GSEA), the molecular mechanism of the potential therapy and prognostic genes were evaluated. Thus, hub genes were shown to be associated with KEGG_CELL_CYCLE and VANTVEER_BREAST_CANCER_POOR_PROGNOSIS gene sets. Finally, based on integrated bioinformatics analysis, this study identified three hub genes as possible prognostic biomarkers and therapeutic targets for BC. The results obtained further understanding of the underground molecular mechanisms related to BC occurrence and prognostic outcomes.

Construction and analysis of a survival-associated competing endogenous RNA network in breast cancer

Background

Recently, increasing studies have shown that non-coding RNAs are closely associated with the progression and metastasis of cancer by participating in competing endogenous RNA (ceRNA) networks. However, the role of survival-associated ceRNAs in breast cancer (BC) remains unknown.

Methods

The Gene Expression Omnibus database and The Cancer Genome Atlas BRCA_dataset were used to identify differentially expressed RNAs. Furthermore, circRNA-miRNA interactions were predicted based on CircInteractome, while miRNA-mRNA interactions were predicted based on TargetScan, miRDB, and miRTarBase. The survival-associated ceRNA networks were constructed based on the predicted circRNA-miRNA and miRNA-mRNA pairs. Finally, the mechanism of miRNA-mRNA pairs was determined. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of survival-related mRNAs were performed using the hypergeometric distribution formula in R software.The prognosis of hub genes was confirmed using gene set enrichment analysis.

Results

Based on the DE-circRNAs of the top 10 initial candidates, 162 DE-miRNAsand 34 DE-miRNAs associated with significant overall survival were obtained. The miRNA target genes were then identified using online tools and verified using the Cancer Genome Atlas (TCGA) database. Overall, 46 survival-associated DE-mRNAs were obtained. The results of GO and KEGG pathway enrichment analyses implied that up-regulated survival-related DE-mRNAs were mostly enriched in the "regulation of cell cycle" and "chromatin" pathways, while down-regulated survival-related DE-mRNAs were mostly enriched in "negative regulation of neurotrophin TRK receptor signaling" and "interleukin-6 receptor complex" pathways. Finally, the survival-associated circRNA-miRNA-mRNA ceRNA network was constructed using 34 miRNAs, 46 mRNAs, and 10 circRNAs. Based on the PPI network, two ceRNA axes were identified. These ceRNA axescould be considered biomarkers for BC.GSEA results revealed that the hub genes were correlated with "VANTVEER_BREAST_CANCER_POOR_PROGNOSIS", and the hub genes were verified using BC patients' tissues.

Conclusions

In this study, we constructed a circRNA-mediated ceRNA network related to BC. This network provides new insight into discovering potential biomarkers for diagnosing and treating BC.

TOP2A deficiency leads to human recurrent spontaneous abortion and growth retardation of mouse pre-implantation embryos

BACKGROUND

Recurrent spontaneous abortion (RSA), is a dangerous pregnancy-related condition and is a subject of debate in the gynaecology and obstetrics communities. The objective of this study was to determine the function of DNA Topoisomerase II Alpha (TOP2A) in RSA and elucidate the underlying molecular mechanisms.

METHODS

In vitro models of TOP2A-knockdown and -overexpression were generated by transfecting specific sh-RNA lentivirus and overexpression plasmid, respectively. An in vitro TOP2A inhibition model was established by culturing mouse embryos at the two-cell stage in a medium containing PluriSIn2, a TOP2A inhibitor. Immunohistochemical staining was used to analyse expression of TOP2A in villi tissues of patients with RSA. Western blotting and qRT-PCR were used to analyse the expression of TOP2A and proteins involved in trophoblast functions, the FOXO signalling pathway, and the development of pre-implantation embryos. 5-Ethynyl-2'-deoxyuridine staining, TUNEL assay and flow cytometry were used to further evaluate the effect of TOP2A on cell proliferation and apoptosis. Transwell and wound healing assays were used to evaluate migration and invasion. Moreover, the effect of TOP2A inhibitor on embryos was determined by immunofluorescence and mitochondrial-related dyes.

RESULTS

Evaluation of clinical samples revealed that the villi tissues of patients that have experienced RSA had lower TOP2A expression compared with that from women who have experienced normal pregnancy (P < 0.01). In vitro, TOP2A knockdown decreased the proliferation, migration, and invasion of trophoblast cell lines, and increased apoptosis and activation of the FOXO signalling pathway (P < 0.05). Conversely, TOP2A overexpression reversed these effects. Moreover, in vivo experiments confirmed that inhibition of TOP2A impairs trophectoderm differentiation, embryonic mitochondrial function as well as the developmental rate; however, no differences were noted in the expression of zygotic genome activation-related genes.

CONCLUSIONS

Collectively, our data suggest that lower TOP2A expression is related to RSA as it inhibits trophoblast cell proliferation, migration, and invasion by activation of the FOXO signalling pathway. Additionally, TOP2A inhibition resulted in impaired development of pre-implantation embryos in mice, which could be attributed to excessive oxidative stress.

Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response

Background: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to develop a predictive signature based on long non-coding RNAs (LncRNAs) associated with m7G to predict the prognosis of breast cancer patients.

Methods: The Cancer Genome Atlas (TCGA) database provided us with the RNA-seq data and matching clinical information of individuals with breast cancer. To identify the signature of N7-Methylguanosine-Related LncRNAs and create a prognostic model, we employed co-expression network analysis, least absolute shrinkage selection operator (LASSO) regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. The signature was assessed using the Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) curve. A nomogram and principal component analysis (PCA) were employed to confirm the predictive signature’s usefulness. Then, we examined the drug sensitivity between the two risk groups and utilized single-sample gene set enrichment analysis (ssGSEA) to investigate the association between predictive factors and the tumor immune microenvironment in high-risk and low-risk groups.

Results: Nine m7G-related LncRNAs (LINC01871, AP003469.4, Z68871.1, AC245297.3, EGOT, TFAP2A-AS1, AL136531.1, SEMA3B-AS1, AL606834.2) that are independently associated with the overall survival time (OS) of BC patients make up the signature we developed. For predicting 1-, 3-, and 5-year survival rates, the areas under the ROC curve (AUC) were 0.715, 0.724, and 0.726, respectively. The Kaplan-Meier analysis revealed that the prognosis of BC patients in the high-risk group was worse than that of those in the low-risk group. When compared to clinicopathological variables, multiple regression analysis demonstrated that risk score was a significant independent predictive factor for BC patients. The results of the ssGSEA study revealed a substantial correlation between the predictive traits and the BC patients’ immunological status, low-risk BC patients had more active immune systems, and they responded better to PD1/L1 immunotherapy.

Conclusion: The prognostic signature, which is based on m7G-related LncRNAs, can be utilized to inform patients’ customized treatment plans by independently predicting their prognosis and how well they would respond to immunotherapy.

A genomic and transcriptomic study toward breast cancer

Background: Breast carcinoma is well recognized to be having the highest global occurrence rate among all cancers, being the leading cause of cancer mortality in females. The aim of this study was to elucidate breast cancer at the genomic and transcriptomic levels in different subtypes so that we can develop more personalized treatments and precision medicine to obtain better outcomes.

Method: In this study, an expression profiling dataset downloaded from the Gene Expression Omnibus database, GSE45827, was re-analyzed to compare the expression profiles of breast cancer samples in the different subtypes. Using the GEO2R tool, different expression genes were identified. Using the STRING online tool, the protein–protein interaction networks were conducted. Using the Cytoscape software, we found modules, seed genes, and hub genes and performed pathway enrichment analysis. The Kaplan–Meier plotter was used to analyze the overall survival. MicroRNAs and transcription factors targeted different expression genes and were predicted by the Enrichr web server.

Result: The analysis of these elements implied that the carcinogenesis and development of triple-negative breast cancer were the most important and complicated in breast carcinoma, occupying the most different expression genes, modules, seed genes, hub genes, and the most complex protein–protein interaction network and signal pathway. In addition, the luminal A subtype might occur in a completely different way from the other three subtypes as the pathways enriched in the luminal A subtype did not overlap with the others. We identified 16 hub genes that were related to good prognosis in triple-negative breast cancer. Moreover, SRSF1 was negatively correlated with overall survival in the Her2 subtype, while in the luminal A subtype, it showed the opposite relationship. Also, in the luminal B subtype, CCNB1 and KIF23 were associated with poor prognosis. Furthermore, new transcription factors and microRNAs were introduced to breast cancer which would shed light upon breast cancer in a new way and provide a novel therapeutic strategy.

Conclusion: We preliminarily delved into the potentially comprehensive molecular mechanisms of breast cancer by creating a holistic view at the genomic and transcriptomic levels in different subtypes using computational tools. We also introduced new prognosis-related genes and novel therapeutic strategies and cast new light upon breast cancer.

ASPM promotes ATR-CHK1 activation and stabilizes stalled replication forks in response to replication stress

ASPM (encoded by MCPH5) is a frequently mutated protein, and such mutations occur in >40% of cases of primary microcephaly (MCPH). Here, we characterize a function of ASPM in DNA replication and the replication stress response. ASPM serves as a scaffold to load stimulators required for ATR-CHK1 checkpoint signaling upon replication stress, which protects stalled replication forks from degradation. ASPM deficiency leads to genomic instability and the sensitization of cancer cells to replication stressors.

ASPM is a protein encoded by primary microcephaly 5 (MCPH5) and is responsible for ensuring spindle position during mitosis and the symmetrical division of neural stem cells. We recently reported that ASPM promotes homologous recombination (HR) repair of DNA double strand breaks. However, its potential role in DNA replication and replication stress response remains elusive. Interestingly, we found that ASPM is dispensable for DNA replication under unperturbed conditions. However, ASPM is enriched at stalled replication forks in a RAD17-dependent manner in response to replication stress and promotes RAD9 and TopBP1 loading onto chromatin, facilitating ATR-CHK1 activation. ASPM depletion results in failed fork restart and nuclease MRE11-mediated nascent DNA degradation at the stalled replication fork. The overall consequence is chromosome instability and the sensitization of cancer cells to replication stressors. These data support a role for ASPM in loading RAD17-RAD9/TopBP1 onto chromatin to activate the ATR-CHK1 checkpoint and ultimately ensure genome stability.

FN1 overexpression is correlated with unfavorable prognosis and immune infiltrates in breast cancer

Objective: To investigate the correlation of fibronectin 1 (FN1) expression with prognosis and tumor-infiltrating immune cells in breast cancer (BRCA).

Methods: FN1 mRNA and protein expressions were analyzed through Tumor Immune Estimation Resource (TIMER), Gene Set Cancer Analysis (GSCA), Human Protein Atlas (HPA) databases, and immunohistochemical analysis. The clinicopathological characteristics and genetic factors affecting the FN1 mRNA expression were assessed by various public databases. Then, we analyzed the prognostic value of FN1 in BRCA by Kaplan-Meier plotter, receiver operating characteristic, and Cox regression analyses. Further, the UCSC Xena database was used to retrieve TCGA-BRCA expression profiles for functional enrichment analysis and immune cell infiltration analysis. The potential drugs for the BRCA patients with high- FN1 expression were identified using the connectivity map analysis.

Results: FN1 was upregulated in BRCA tissues compared with normal tissues. High FN1 mRNA expression was correlated with poor clinical outcomes and had good performance in predicting the survival status of BRCA patients. Further, Cox regression analysis showed that FN1 was an independent prognostic factor for predicting the overall survival of patients with BRCA. Moreover, hypermethylation of FN1 contributed to a better prognosis for BRCA patients. Functional enrichment analyses revealed the ECM-receptor interaction pathway and focal adhesion as the common pathways. Moreover, FN1 showed a significant association with tumor-infiltrating immune cells and immune checkpoint inhibitors. Several drugs such as telmisartan, malotilate, and seocalcitol may have therapeutic effects in BRCA patients with high FN1 expression.

Conclusion: FN1 might serve as a novel prognostic biomarker and a novel therapeutic target for BRCA. Besides, the association of FN1 with immune cells and immune checkpoint inhibitors may provide assistance for BRCA treatment.

Identification and verification of immune-related gene prognostic signature based on ssGSEA for breast cancer

Introduction

Breast cancer (BC) is the most common cancer in women worldwide and has a high mortality rate. The fact that the tumor microenvironment affects clinical outcomes of all types of cancers underlines the involvement of various immune-related genes (IRGs). Therefore, this study aimed to establish an IRGs-based signature for the prognosis of BC patients.

Material and methods

In this study, 12 immune cell infiltrating degrees in 1,102 BC cases from The Cancer Genome Atlas (TCGA) database were assessed, and RNA-sequencing (RNA-seq) data of these samples were analyzed by single-sample gene set enrichment analysis (ssGSEA). Based on the results, high, low, and middle immune infiltrating clusters were constructed. A total of 138 overlapped differentially expressed genes (DEGs) were identified in the high and low infiltrating clusters, as well as in normal and BC samples. Univariate Cox regression and LASSO analyses were also performed. Furthermore, GSEA suggested some highly enriched pathways in the different immune infiltrating clusters, leading to a better understanding of potential mechanisms of immune infiltration in BC.

Results

Finally, 19 immune-related genes were identified that could be utilized as a potential prognostic biomarker for BC. Kaplan-Meier plot and ROC curve, univariate as well as multivariate Cox analyses were carried out, which suggested that the 19-IRG-based signature is a significant prognosis factor independent of clinical features. Based on the analysis of protein-protein interactions (PPI), the three hub genes were identified.

Conclusions

These results provide a new method to predict the prognosis and survival of BC based on the three genes' features.

Type IIA topoisomerase (TOP2A) triggers epithelial-mesenchymal transition and facilitates HCC progression by regulating Snail expression

Type IIA topoisomerase (TOP2A) is upregulated in hepatocellular carcinoma (HCC) and its expression is positively correlated with poor prognosis. However, the underlying molecular mechanism of this connection are poorly understood. Hence, the present work aimed to examine the possible mechanisms which may be useful in identifying a potential therapeutic strategy. The differential expression of TOP2A mRNA in HCC as compared with adjacent normal tissue was analyzed using the Oncomine database. The expression levels of TOP2A in HCC specimens and cell lines were assessed by Western blot and RT-qPCR. Stable cell lines were generated to knockdown or overexpress TOP2A, and then cell growth, migration, and invasion were analyzed. Furthermore, this study examined epithelial-mesenchymal transition (EMT) as well as the activation of related pathways. Additionally, the correlation between TOP2A levels and E-cadherin/Snail expression was determined in 72 HCC specimens. Higher expression levels of TOP2A were observed in HCC in Oncomine datasets, and the results were verified using 40 pairs of HCC specimens and peritumoral tissues. TOP2A expression levels were remarkably elevated in cells with great metastatic capacity. In addition, HCC cell growth, migration, and invasion were suppressed after TOP2A knockdown in MHCC97H cells (MHCC97H-shRNA-TOP2A), while these capabilities were promoted in TOP2A-overexpressing Hep3B cells (Hep3B-TOP2A). Furthermore, EMT was inhibited in MHCC97H-shRNA-TOP2A cells, but induced in Hep3B-TOP2A cells. The induction of EMT by TOP2A was shown to be mediated by Snail, as TOP2A promoted Snail expression through the p-ERK1/2/p-SMAD2 signaling pathway. TOP2A level showed a negative correlation with E-cadherin, whereas a positive correlation with that of vimentin and Snail in human HCC specimens by immunohistochemistry analyses. Kaplan-Meier survival curves revealed that TOP2A upregulation showed a positive correlation with poor prognosis patients. Taken together, TOP2A possibly enhances the metastasis of HCC by promoting EMT through the mediation of the p-ERK1/2/p-SMAD2/Snail pathway. This indicates that TOP2A maybe a potential factor to predict the prognosis of HCC.

KIF2C Is a Novel Prognostic Biomarker and Correlated with Immune Infiltration in Endometrial Cancer

Endometrial cancer (EC) is commonly diagnosed cancer in women, and the prognosis of advanced types of EC is extremely poor. Kinesin family member 2C (KIF2C) has been reported as an oncogene in cancers. However, its pathophysiological roles and the correlation with tumor-infiltrating lymphocytes in EC remain unclear. The mRNA and protein levels of KIF2C in EC tissues were detected by qRT-PCR, Western blot (WB), and IHC. CCK8, Transwell, and colony formation assay were applied to assess the effects of KIF2C on cell proliferation, migration, and invasion. Cell apoptosis and cell cycle were analyzed by flow cytometry. The antitumor effect was further validated in the nude mouse xenograft cancer model and humanized mouse model. KIF2C expression was higher in EC. Knockdown of KIF2C prolonged the G1 phases and inhibited EC cell proliferation, migration, and invasion in vitro. Bioinformatics analysis indicated that KIF2C is negatively correlated with the infiltration level of CD8⁺ T cells but positively with the poor prognosis of EC patients. The apoptosis of CD8⁺ T cell was inhibited after the knockdown of KIF2C and was further inhibited when it is combined with anti-PD1. Conversely, compared to the knockdown of KIF2C expression alone, the combination of anti-PD1 further promoted the apoptosis of Ishikawa and RL95-2 cells. Moreover, the knockdown of KIF2C inhibited the expression of Ki-67 and the growth of tumors in the nude mouse xenograft cancer model. Our study found that the antitumor efficacy was further evaluated by the combination of anti-PD1 and KIF2C knockdown in a humanized mouse model. This study indicated that KIF2C is a novel prognostic biomarker that determines cancer progression and also a target for the therapy of EC and correlated with tumor immune cells infiltration in EC.

Silencing Aurora-kinase-A (AURKA) reinforced the sensitivity of diffuse large B-cell lymphoma cells to cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) via suppressing β-Catenin and RAS-extracellular signal-regulated protein kinase (ERK1/2) pathway

The therapeutic effects of standard cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) therapy for prevalent lymphoma diffuse large B-cell lymphoma (DLBC, DLBCL) still require improvement. Cancer-related aurora-kinase-A (AURKA) may work as a target for DLBCL treatment and its effect on CHOP therapy was investigated in the present study. The Gene Expression Profiling Interactive Analysis 2 was applied to analyze AURKA expression in DLBC tumor tissues and normal lymphoid tissues. The DLBCL tissues and normal lymphoid tissues were obtained from the DLBCL patients and healthy volunteers. Clinic data of patients were recorded, and AURKA expression in tissues and cells was detected and analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry. After AURKA in DLBCL cells was silenced or overexpressed and treated with CHOP, viability and apoptosis were detected by Cell Counting Kit-8 (CCK-8) assay and flow cytometry. Expressions of AURKA, β-Catenin, phosphorylated (p)-β-Catenin, extracellular signal-regulated protein kinase (ERK1/2), p-ERK1/2 and RAS were detected using qRT-PCR and Western blot. AURKA was highly expressed in DLBCL tissues and cells. Silencing AURKA inhibited AURKA expression and viability, but promoted apoptosis of DLBCL cells. CHOP had no obvious effects on AURKA expression while reducing viability and promoting apoptosis of DLBCL cells. Silencing AURKA enhanced the effects of CHOP on cell apoptosis of DLBCL cells by inhibiting the expressions of RAS and β-Catenin as well as the ratio of p-ERK1/2/ERK1/2 and promoting the ratio of p-β-Catenin/β-Catenin. Silencing AURKA reinforced the therapeutic effects of CHOP on reducing viability and promoting apoptosis of DLBCL cell via repressing β-Catenin and RAS-ERK1/2 pathway.