Copy Number Profiling of MammaPrint™ Genes Reveals Association with the Prognosis of Breast Cancer Patients

A Number of the N-terminal RASSF Family: RASSF7

The Ras association domain family 7 (RASSF7, also named HRC1), a potential tumor-related gene, located on human chromosome 11p15, has been identified as an important member of the N-terminal RASSF family. Whereas, the molecular biological mechanisms of RASSF7 in tumorigenesis remain to be further established. We perform a systematic review of the literature and assessment from PUBMED and MEDLINE databases in this article. RASSF7 plays a significant role in mitosis, microtubule growth, apoptosis, proliferation and differentiation. Many research literature shows that the RASSF7 could promote the occurrence and advance of human tumors by regulating Aurora B, MKK4, MKK7, JNK, YAP, MEK, and ERK, whereas, it might inhibit c-Myc and thus lead to the suppression of tumorigenesis. The pregulation of RASSF7 often occurs in various malignancies such as lung cancer, neuroblastoma, thyroid neoplasm, hepatocellular cancer, breast cancer and gastric cancer. The expression stage of RASSF7 is positively correlated with the tumor TNM stage. In this review, we primarily elaborate on the acknowledged structure and progress in the various biomechanisms and research advances of RASSF7, especially the potential relevant signaling pathways. We hope that RASSF7 , a prospective therapeutic target for human malignancies, could play an available role in future anti-cancer treatment.

The biology of SCUBE

The SCUBE [Signal peptide-Complement C1r/C1s, Uegf, Bmp1 (CUB)-Epithelial growth factor domain-containing protein] family consists of three proteins in vertebrates, SCUBE1, 2 and 3, which are highly conserved in zebrafish, mice and humans. Each SCUBE gene encodes a polypeptide of approximately 1000 amino acids that is organized into five modular domains: (1) an N-terminal signal peptide sequence, (2) nine tandem epidermal growth factor (EGF)-like repeats, (3) a large spacer region, (4) three cysteine-rich (CR) motifs, and (5) a CUB domain at the C-terminus. Murine Scube genes are expressed individually or in combination during the development of various tissues, including those in the central nervous system and the axial skeleton. The cDNAs of human SCUBE orthologs were originally cloned from vascular endothelial cells, but SCUBE expression has also been found in platelets, mammary ductal epithelium and osteoblasts. Both soluble and membrane-associated SCUBEs have been shown to play important roles in physiology and pathology. For instance, upregulation of SCUBEs has been reported in acute myeloid leukemia, breast cancer and lung cancer. In addition, soluble SCUBE1 is released from activated platelets and can be used as a clinical biomarker for acute coronary syndrome and ischemic stroke. Soluble SCUBE2 enhances distal signaling by facilitating the secretion of dual-lipidated hedgehog from nearby ligand-producing cells in a paracrine manner. Interestingly, the spacer regions and CR motifs can increase or enable SCUBE binding to cell surfaces via electrostatic or glycan-lectin interactions. As such, membrane-associated SCUBEs can function as coreceptors that enhance the signaling activity of various serine/threonine kinase or tyrosine kinase receptors. For example, membrane-associated SCUBE3 functions as a coreceptor that promotes signaling in bone morphogenesis. In humans, SCUBE3 mutations are linked to abnormalities in growth and differentiation of both bones and teeth. In addition to studies on human SCUBE function, experimental results from genetically modified mouse models have yielded important insights in the field of systems biology. In this review, we highlight novel molecular discoveries and critical directions for future research on SCUBE proteins in the context of cancer, skeletal disease and cardiovascular disease.

The Multifaceted Role of Signal Peptide-CUB-EGF Domain-Containing Protein (SCUBE) in Cancer

Signal peptide, CUB, and EGF-like domain-containing proteins (SCUBE) are secretory cell surface glycoproteins that play key roles in the developmental process. SCUBE proteins participate in the progression of several diseases, including cancer, and are recognized for their oncogenic and tumor suppressor functions depending on the cellular context. SCUBE proteins promote cancer cell proliferation, angiogenesis, invasion, or metastasis, stemness or self-renewal, and drug resistance. The association of SCUBE with other proteins alters the expression of signaling pathways, including Hedgehog, Notch, TGF-β/Smad2/3, and β-catenin. Further, SCUBE proteins function as potential prognostic and diagnostic biomarkers for breast cancer, renal cell carcinoma, endometrial carcinoma, and nasopharyngeal carcinoma. This review presents key features of SCUBE family members, and their structure and functions, and highlights their contribution in the development and progression of cancer. A comprehensive understanding of the role of SCUBE family members offers novel strategies for cancer therapy.

Integrative analysis of expression, prognostic significance and immune infiltration of RFC family genes in human sarcoma

Objective: To reveal the expression and prognostic value of replication factor C family genes (RFCs) in patients with sarcoma.

Results: The results showed that the mRNA expression levels of RFC2, RFC3, RFC4, and RFC5 were increased in sarcoma tissues. In addition, Cancer Cell Line Encyclopedia (CCLE) dataset analysis indicated that RFC1, RFC2, RFC3, RFC4, and RFC5 were elevated expressed in sarcoma cell lines. Moreover, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter showed that highly expressed RFC2-5 were associated with poor overall survival (OS) or relapse-free survival (RFS) in sarcoma patients. The results of the Tumor Immune Estimation Resource (TIMER) database indicated that the expression of RFCs was negatively correlated with the infiltration of CD4+ T cells and macrophages.

Conclusions: There were significant differences in the expression of RFCs between normal tissue and sarcoma tissue, and RFC2, RFC3, RFC4, and RFC5 might be promising prognostic biomarkers for sarcoma.

Methods: The expression of RFCs was analyzed using the ONCOMINE dataset and GEPIA dataset. CCLE dataset was used to assess the expression of RFCs in the cancer cell line. The prognostic value of RFCs was evaluated by GEPIA and Kaplan-Meier analysis. Furthermore, the association between RFCs and their co-expressed genes were explored via ONCOMINE and GEPIA datasets. We used the TIMER dataset to analyze the immune cell infiltration of RFCs in sarcoma.

Progesterone activates GPR126 to promote breast cancer development via the Gi pathway

The steroid hormone progesterone is highly involved in different physiological–pathophysiological processes, including bone formation and cancer progression. Understanding the working mechanisms, especially identifying the receptors of progesterone hormones, is of great value. In the present study, we identified GPR126 as a membrane receptor for both progesterone and 17-hydroxyprogesterone and triggered its downstream G protein signaling. We further characterized the residues of GPR126 that interact with these two ligands and found that progesterone promoted the progression of a triple-negative breast cancer model through GPR126-dependent Gi-SRC signaling. Therefore, developing antagonists targeting GPR126-Gi may provide an alternative therapeutic option for patients with triple-negative breast cancer.

GPR126 is a member of the adhesion G protein-coupled receptors (aGPCRs) that is essential for the normal development of diverse tissues, and its mutations are implicated in various pathological processes. Here, through screening 34 steroid hormones and their derivatives for cAMP production, we found that progesterone (P4) and 17-hydroxyprogesterone (17OHP) could specifically activate GPR126 and trigger its downstream Gi signaling by binding to the ligand pocket in the seven-transmembrane domain of the C-terminal fragment of GPR126. A detailed mutagenesis screening according to a computational simulated structure model indicated that K1001^ECL2 and F1012^ECL2 are key residues that specifically recognize 17OHP but not progesterone. Finally, functional analysis revealed that progesterone-triggered GPR126 activation promoted cell growth in vitro and tumorigenesis in vivo, which involved Gi-SRC pathways in a triple-negative breast cancer model. Collectively, our work identified a membrane receptor for progesterone/17OHP and delineated the mechanisms by which GPR126 participated in potential tumor progression in triple-negative breast cancer, which will enrich our understanding of the functions and working mechanisms of both the aGPCR member GPR126 and the steroid hormone progesterone.

Identification of biomarkers for acute leukemia via machine learning-based stemness index

Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as retroviral insertion mutagenesis, non-physiological level gene expression, non-physiological expansion, and difficulty to construct. The mRNAsi index for each sample of the Cancer Genome Atlas (TCGA) could avoid these potential pitfalls by machine learning. In this work, we aimed to construct a network of LSC genes utilizing the mRNAsi. First, mRNAsi value was analyzed with expressions distributions, survival analysis, age, and gender in acute myeloid leukemia (AML) samples. Then, we used the weighted gene co-expression network analysis (WGCNA) to construct modules of stemness genes. The correlation of the LSC genes transcription and interplay among LSC proteins was analyzed. We performed functional and pathway enrichment analysis to annotate stemness genes. Survival analysis further identified prognostic biomarkers by clinical data of TCGA and the Gene Expression Omnibus (GEO) database. We found that the result of mRNAsi overall survival is not significant, which may be due to the heterogeneity of AML in the stage of myeloid differentiation, French-American-British (FAB) classification systems. Enrichment analysis indicated that the stemness genes were biologically clustered as a group and mainly associated with cell cycle and mitosis. Moreover, 10 key genes (SNRNP40, RFC4, RFC5, CDC6, HSPE1, PA2G4, SNAP23P, DARS2, MIS18A, and HPRT1) were screened by survival analysis with the data from TCGA and GEO. Among them, RFC4 and RFC5 were the distinguished biomarkers for their double-validated prognostic value in both databases. Additionally, the expression of RFC4 and RFC5 had the same trend as mRNAsi score in FAB subtypes. In conclusion, our result demonstrated that mRNAsi based LSC-related genes were found to have strong interactions as a cluster. These genes, especially RFC4 and RFC5, could be the therapeutic targets for inhibiting the stemness characteristics of AML. This work is also a comprehensive pipeline for future cancer stem cell studies.

MammaPrint and BluePrint comprehensively capture the cancer hallmarks in early-stage breast cancer patients

MammaPrint® (MP) is a 70‐gene signature that stratifies early‐stage breast cancer patients into low‐ and high risk of distant relapse. Further stratification of MP risk results identifies four risk subgroups, ultra‐low (UL), low, high 1, and high 2, with specific prognostic and predictive outcomes. BluePrint® (BP) is an 80‐gene signature that classifies breast tumors as basal, luminal, or HER2 molecular subtype. To gain insight into their biological significance, we annotated the MP 70‐ and BP 80‐genes with respect to the 10 hallmarks of cancer (HoC). Furthermore, we related gene expression profiles of the extreme ends of the MP low‐ and high‐risk patients (here called, ultra‐low (UL) and ultra‐high (UH) or High2, respectively), to the 10 HoC per BP subtype by differential gene expression and pathway analysis. MP and BP gene functions reflected all 10 HoCs. Most MP and BP genes were associated with sustaining proliferative signaling, followed by genome instability and mutation categories. Based on the gene expression profiles, UL and UH subgroup pathways were down ‐or upregulated, respectively, reflecting proliferative and metastatic features, such as G2M checkpoint, DNA repair, oxidative phosphorylation, immune invasion, PI3K/AKT/mTOR signaling, and hypoxia pathways. Notably, the UH HER2‐type was enriched in several immune signaling pathways, such as IL2/STAT5 signaling and TNFα signaling via NFκB. Our results show that MP and BP gene signatures represent and capture all 10 HoCs and highlight underlying biological processes of MP extreme samples, which might guide treatment decisions as the signature captures the full spectrum of early breast cancers.

Integrated Analysis of Copy Number Variation, Microsatellite Instability, and Tumor Mutation Burden Identifies an 11-Gene Signature Predicting Survival in Breast Cancer

Genetic variants such as copy number variation (CNV), microsatellite instability (MSI), and tumor mutation burden (TMB) have been reported to associate with the immune microenvironment and prognosis of patients with breast cancer. In this study, we performed an integrated analysis of CNV, MSI, and TMB data obtained from The Cancer Genome Atlas, thereby generating two genetic variants-related subgroups. We characterized the differences between the two subgroups in terms of prognosis, MSI burden, TMB, CNV, mutation landscape, and immune landscape. We found that cluster 2 was marked by a worse prognosis and lower TMB. According to these groupings, we identified 130 differentially expressed genes, which were subjected to univariate and least absolute shrinkage and selection operator-penalized multivariate modeling. Consequently, we constructed an 11-gene signature risk model called the genomic variation-related prognostic risk model (GVRM). Using ROC analysis and a calibration plot, we estimated the prognostic prediction of this GVRM. We confirmed the predictive efficiency of this GVRM by validating it in another independent International Cancer Genome Consortium cohort. Our results conclude that an 11-gene signature developed by integrated analysis of CNV, MSI, and TMB has a high potential to predict breast cancer prognosis, which provided a strong rationale for further investigating molecular mechanisms and guiding clinical decision-making in breast cancer.

Establishment of a novel CNV-related prognostic signature predicting prognosis in patients with breast cancer

Background

Copy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data.

Methods

Breast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance.

Results

A total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC.

Conclusion

The current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00823-y.

Early B-cell factors involve in the tumorigenesis and predict the overall survival of gastric cancer

Gastric cancer (GC) is a heavy health burden around the world, which is the fifth most frequent tumor and leads to the third most common cancer-related deaths. It is urgent to identify prognostic markers as the guideline for personalized treatment and follow-up. We accessed the prognostic value of Early B-cell factors (EBFs) in GC. A total of 415 GC tissues and 34 normal tissues from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort, 616 external patients from GSE15459, GSE22377, GSE51105, GSE62245 were enrolled for analysis. Univariate and multivariate Cox regression analyses were employed to evaluate the sole and integrative prognostic value of EBFs, respectively. Genetic alterations, DNA methylation of EBFs were also evaluated, as well as the involved signaling pathways. We revealed that increased EBFs associated with the poor prognosis of GC patients, the prognostic model was established in TCGA-STAD cohort, and validated in Gene Expression Omnibus (GEO) cohorts, with effectiveness in both HER2 positive and negative patients. DNA methylation was involved in the impact on prognosis. Cell cycle, immune-associated, and MAPK pathways were influenced by EBFs. Anti-CTLA4 immunotherapy is more suitable for EBFs determining high-risk groups, but not anti-PD-1/PD-L1 therapy. 5-Fluorouracil, methotrexate, vorinostat are suitable to inhibit the function of EBFs. Our new findings provide novel insight into the prediction of prognosis and clinical treatment of GC patients based on EBFs.

A zinc finger protein gene signature enables bladder cancer treatment stratification

Bladder cancer (BC) is a commonly occurring malignant tumor affecting the urinary tract. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and are therefore attractive biomarker candidates for BC prognosis. In this study, we profiled the expression of ZNFs in The Cancer Genome Atlas (TCGA) BC cohort and developed a novel prognostic signature based on 7 ZNF-coding genes. After external validation of the model in the GSE48276 dataset, we integrated the 7-ZNF-gene signature with patient clinicopathological data to construct a nomogram that forecasted 1-, 2-, and 3-year OS with good predictive accuracy. We then accessed The Genomics of Drug Sensitivity in Cancer database to predict the therapeutic drug responses of signature-defined high- and low-risk BC patients in the TCGA cohort. Greater sensitivity to chemotherapy was revealed in the low-risk group. Finally, we conducted gene set enrichment analysis of the signature genes and established, by applying the ESTIMATE algorithm, distinct correlations between the two risk groups and the presence of stromal and immune cell types in the tumor microenvironment. By allowing effective risk stratification of BC patients, our novel ZNF gene signature may enable tailoring more intensive treatment for high-risk patients.

RFC4 promotes the progression and growth of Oral Tongue squamous cell carcinoma in vivo and vitro

OBJECTIVE

Currently, many studies have found that RFC4 was up-regulated in various cancers, and related to the progression and development. While the effects of RFC4 in oral tongue squamous cell carcinoma remain unclear, the main purpose of this research is to explore the role of RFC4 in oral tongue squamous cell carcinoma.

METHODS

The expression of RFC4 in various cancers was analyzed in GEPIA database, and the results were further verified by IHC assay. The relationship between RFC4 and several clinical parameters was analyzed; the proliferation was further observed by knockdown RFC4 in vitro. Finally, we constructed related nude mouse models by planting cells subcutaneous of nude mice, and the discrepancy was observed.

RESULTS

Based on GEPIA database, RFC4 was up-regulated in various cancers, including colorectal cancer, breast cancer, prostate cancer, lung cancer, and liver cancer. RFC4 was up-regulated in oral tongue squamous cell carcinoma compared with the normal tissue from GEPIA online database; we further found that the expression of RFC4 was tightly associated with TNM stage (p = 0.005), but not with age, gender, and differentiation (p > 0.05). We further found that the proliferation of oral tongue squamous cell carcinoma was obviously restrained in vitro, and the carcinogenesis was also inhibited in vivo.

CONCLUSIONS

We found that RFC4 was up-regulated and related to the progression of oral tongue squamous cell carcinoma, and knockdown RFC4 could restrain the proliferation and progression. RFC4 might serve a potential biomarker and provide a new treatment strategy for lots of patients with oral tongue squamous cell carcinoma.

GPR126 regulates colorectal cancer cell proliferation by mediating HDAC2 and GLI2 expression

The G‐protein‐coupled receptor 126 (GPR126) may play an important role in tumor development, although its role remains poorly understood. We found that GPR126 had higher expression in most colorectal cancer cell lines than in normal colon epithelial cell lines, and higher expression levels in colorectal cancer tissues than in normal adjacent colon tissues. GPR126 knockdown induced by shRNA inhibited cell viability and colony formation in HT‐29, HCT116, and LoVo cells, decreased BrdU incorporation into newly synthesized proliferating HT‐29 cells, led to an arrest of cell cycle progression at the G1 phase in HCT‐116 and HT‐29 cells, and suppressed tumorigenesis of HT‐29, HCT116, and LoVo cells in nude mouse xenograft models. GPR126 knockdown engendered decreased transcription and translation of histone deacetylase 2 (HDAC2), previously implicated in the activation of GLI1 and GLI2 in the Hedgehog signaling pathway. Ectopic expression of HDAC2 in GPR126‐silenced cells restored cell viability and proliferation, GLI2 luciferase reporter activity, partially recovered GLI2 expression, and reduced the cell cycle arrest. HDAC2 regulated GLI2 expression and, along with GLI2, it bound to the PTCH1 promoter, as evidenced by a chip assay with HT‐29 cells. Purmorphamine, a hedgehog agonist, largely restored the cell viability and expression of GLI2 proteins in GPR126‐silenced HT‐29 cells, whereas GANT61, a hedgehog inhibitor, further enhanced the GPR126 knockdown‐induced inhibitory effects. Our findings demonstrate that GPR126 regulates colorectal cancer cell proliferation by mediating the expression of HDAC2 and GLI2, therefore it may represent a suitable therapeutic target for colorectal cancer treatment.

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.

Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data

Background

Cervical squamous cancer (CESC) is an intractable gynecological malignancy because of its high mortality rate and difficulty in early diagnosis. Several biomarkers have been found to predict the prognose of CESC using bioinformatics methods, but they still lack clinical effectiveness. Most of the existing bioinformatic studies only focus on the changes of oncogenes but neglect the differences on the protein level and molecular biology validation are rarely conducted.

Methods

Gene set data from the NCBI-GEO database were used in this study to compare the differences of gene and protein levels between normal and cancer tissues through significant pathway selection and core gene signature analysis to screen potential clinical biomarkers of CESC. Subsequently, the molecular and protein levels of clinical samples were verified by quantitative transcription PCR, western blot and immunohistochemistry.

Results

Three differentially expressed genes (RFC4, MCM2, TOP2A) were found to have a significant survival (P < 0.05) and highly expressed in CESC tissues. Molecular biological verification using quantitative reverse transcribed PCR, western blotting and immunohistochemistry assays exhibited significant differences in the expression of RFC4 between CESC and para-cancerous tissues (P < 0.05).

Conclusion

This study identified three potential biomarkers (RFC4, MCM2, TOP2A) of CESC which may be useful to clarify the underlying mechanisms of CESC and predict the prognosis of CESC patients.

3D printing approaches for cardiac tissue engineering and role of immune modulation in tissue regeneration

Conventional tissue engineering, cell therapy, and current medical approaches were shown to be successful in reducing mortality rate and complications caused by cardiovascular diseases (CVDs). But still they have many limitations to fully manage CVDs due to complex composition of native myocardium and microvascularization. Fabrication of fully functional construct to replace infarcted area or regeneration of progenitor cells is important to address CVDs burden. Three-dimensional (3D) printed scaffolds and 3D bioprinting technique have potential to develop fully functional heart construct that can integrate with native tissues rapidly. In this review, we presented an overview of 3D printed approaches for cardiac tissue engineering, and advances in 3D bioprinting of cardiac construct and models. We also discussed role of immune modulation to promote tissue regeneration.

Copy number profiling of Oncotype DX genes reveals association with survival of breast cancer patients

Copy number variations (CNVs) are key contributors in breast cancer initiation and progression. However, to date, no CNV-based gene signature is developed for breast cancer. 21-gene Oncotype DX, a clinically validated signature, was identified using only RNA expression data in breast cancer patients. In this study, we evaluated whether CNVs of Oncotype DX genes can be used to predict the prognosis of breast cancer patients. Transcriptomic data of 547 and genomic data of 816 of breast cancer patients were downloaded from The Cancer Genome Atlas database. To establish the prognostic relevance between the CNVs of Oncotype DX genes and clinicopathological features, statistical analysis including Pearson Correlation, Fisher-exact, Chi square, Kaplan-Meier survival and Cox regression analyses were performed. 86% genes showed positive CNV-expression correlation. CNVs in 52% and 47.6% genes showed association with ER+ and PR+ status, respectively. 71% of the genes (including ERBB2, CTSV, CD68, GRB7, MKI67, MMP1, PGR, RPLP0, TFRC, BAG1, BCL2, BIRC5, FLNB, GSTM1 and SCUBE2) showed association with poor overall survival. 14% of the genes (including CTSV, RPLP0 and BIRC5) genes showed association with disease free survival. Cox regression analysis revealed ESR1, metastasis and node stage as independent prognostic factors for overall survival of breast cancer patients. The results suggested that CNV-based assay of Oncotype DX genes can be used to predict the survival of breast cancer patients. In future, identifying new gene signatures for better breast cancer prognosis using CNV level information will be worth investigating.

Multifaceted regulation and functions of replication factor C family in human cancers

Replication factor C (RFC) family is a complex comprised of the RFC1, RFC2, RFC3, RFC4, and RFC5 subunits, which acts as a primer recognition factor for DNA polymerase. It is reported that RFC, biologically active in various malignant tumors, may play an important role in the proliferation, progression, invasion, and metastasis of cancer cells. It could act as an oncogene or tumor suppressor gene based on the cellular and histological characteristics of the tumor. In this review, we summarized the updated researches on the structure, physiological function, and expression pattern of RFC in a variety of tumors, the underlying mechanisms on carcinogenesis, and the potentials of RFC family members in the diagnosis and prognosis prediction.