Allelic expression imbalance polymorphisms in susceptibility chromosome regions and the risk and survival of breast cancer

Signaling lymphocytic activation molecule family receptors as potential immune therapeutic targets in solid tumors

Recently, cancer immunotherapy has revolutionized cancer treatment. Various forms of immunotherapy have a manageable safety profile and result in prolongation of overall survival in patients with solid tumors, but only in a proportion of patients. Various factors in the tumor microenvironment play critical roles and may be responsible for this lack of therapeutic response. Signaling lymphocytic activation molecule family (SLAMF) members are increasingly being studied as factors impacting the tumor immune microenvironment. SLAMF members consist of nine receptors mainly expressed in immune cells. However, SLAMF receptors have also been detected in cancer cells, and they may be involved in a spectrum of anti-tumor immune responses. Here, we review the current knowledge of the expression of SLAMF receptors in solid tumors and tumor-infiltrating immune cells and their association with patient outcomes. Furthermore, we discuss the therapeutic potential of targeting SLAMF receptors to improve outcomes of cancer therapy in solid tumors. We believe the research on SLAMF receptor-targeted strategies may enhance anti-cancer immunity in patients with solid tumors and improve clinical outcomes.

CHRAC1 promotes human lung cancer growth through regulating YAP transcriptional activity

ATP-dependent chromatin remodeling complexes regulate chromatin structure and play important roles in gene expression, differentiation, development and cancer progression. Dysregulation in the subunits of the complexes often has been found in different cancers, but how they influence cancer initiation and progression is not fully understood. Here we show that Chromatin Accessibility Complex Subunit 1 (CHRAC1), the accessory subunit of chromatin remodeling complex, is highly expressed in lung cancer tissues, which correlates with poor prognosis in lung cancer patients. CHRAC1 overexpression promotes lung cancer cell proliferation and migration in vitro and tumor growth in genetically engineered Kras G12D.LSL lung adenocarcinoma mouse model. Consistent with this, CHRAC1 silencing inhibits cell proliferation and migration in lung cancer cells and suppresses tumor growth in xenograft mouse model. Further, CHRAC1 binds to the transcription co-activator Yes-associated protein (YAP), enhances the transcription of downstream target oncogenes in Hippo pathway and thus promotes the tumor growth. Together, our study defines a critical role of CHRAC1 in promoting YAP transcriptional activity and lung cancer tumorigenesis, which makes it a potential target for lung cancer.

Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis

Background

Previous studies have found that the microenvironment of cervical cancer (CESC) affects the progression and treatment of this disease. Thus, we constructed a multigene model to assess the survival of patients with cervical cancer.

Methods

We scored 307 CESC samples from The Cancer Genome Atlas (TCGA) and divided them into high and low matrix and immune scores using the ESTIMATE algorithm for differential gene analysis. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The multigene signature prognostic model was constructed by Cox analyses. Multivariate Cox analysis was applied to evaluate the significance of the multigene signature for cervical cancer prognosis. Prognosis was assessed by Kaplan–Meier curves comparing the different groups, and the accuracy of the prognostic model was analyzed by receiver operating characteristic-area under the curve (ROC-AUC) analysis and calibration curve. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the relationship between the multigene signature and immune cell infiltration.

Results

We obtained 420 differentially expressed genes in the tumor microenvironment from 307 patients with cervical cancer. A three-gene signature (SLAMF1, CD27, SELL) model related to the tumor microenvironment was constructed to assess patient survival. Kaplan–Meier analysis showed that patients with high risk scores had a poor prognosis. The ROC-AUC value indicated that the model was an accurate predictor of cervical cancer prognosis. Multivariate cox analysis showed the three-gene signature to be an independent risk factor for the prognosis of cervical cancer. A nomogram combining the three-gene signature and clinical features was constructed, and calibration plots showed that the nomogram resulted in an accurate prognosis for patients. The three-gene signature was associated with T stage, M stage and degree of immune infiltration in patients with cervical cancer.

Conclusions

This research suggests that the developed three-gene signature may be applied as a biomarker to predict the prognosis of and personalized therapy for CESC.

Identification of novel hub genes and lncRNAs related to the prognosis and progression of pancreatic cancer by microarray and integrated bioinformatics analysis

BACKGROUND

Pancreatic cancer (PC) is one of the most invasive and metastatic neoplasms among the fatal malignancies of the digestive system. Abnormal expression of genes and long non-coding RNAs (lncRNAs) are reportedly linked to multiple cancers. However, the lncRNA-mRNA expression profiles and their molecular mechanisms in PC progression are poorly known. This study aimed to map the hub genes and lncRNAs which might play core roles in the development of PC.

METHODS

This study used microarray expression analysis to screen for both differentially expressed genes (DEGs) and differentially expressed lncRNAs (DElncRNAs) between PC and matched adjacent non-tumor (AN) tissues. In order to clarify the functional classification of DEGs, we conducted GO and KEGG pathway enrichment analyses via the Enrichr database. LncRNA-mRNA co-expressed networks were also constructed to explore the probable core regulating DEGs and DElncRNAs. Subsequently, the hub genes and lncRNAs were validated via the ONCOMINE and GEPIA databases and the co-expressed networks.

RESULTS

By analyzing an mRNA-lncRNA microarray, we identified 943 mRNAs and 1,138 lncRNAs differentially expressed in PC tumors compared with the matched AN tissues. GO analysis confirmed that both up-regulated and down-regulated DEGs were enriched in multiple terms. The KEGG pathways enrichment analyses revealed that DEGs were mostly enriched in the focal adhesion and glutathione metabolism pathways, amongst others. Co-expressed networks were established to reveal the differential interactions between DEGs and DElncRNAs, and to indicate the core regulatory factors located at the core nodes of the co-expressed networks. The expression levels of potential core-regulating DEGs were validated by the GEPIA and ONCOMINE databases, and the relationship between overall survival and tumor stage and the potential core-regulating DEGs was analyzed using the GEPIA database. As a result, five genes and sixteen lncRNAs were finally considered as the hub transcripts in PC.

CONCLUSIONS

This study identified DEGs and DElncRNAs between PC tumors and matched AN tissues, and these transcripts were connected with malignant phenotypes in PC through different BPs and signaling pathways. Furthermore, five hub genes and sixteen lncRNAs were identified, which are expected to represent candidate diagnostic biomarkers or potential therapeutic targets for PC.

Deconvolution of the Genomic and Epigenomic Interaction Landscape of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer. Emerging evidenced suggests that both genetics and epigenetic factors play a role in the pathogenesis of TNBC. However, oncogenic interactions and cooperation between genomic and epigenomic variation have not been characterized. The objective of this study was to deconvolute the genomic and epigenomic interaction landscape in TNBC using an integrative genomics approach, which integrates information on germline, somatic, epigenomic and gene expression variation. We hypothesized that TNBC originates from a complex interplay between genomic (both germline and somatic variation) and epigenomic variation. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect entire molecular networks and signaling pathways which, in turn, drive TNBC. We addressed these hypotheses using germline variation from genome-wide association studies and somatic, epigenomic and gene expression variation from The Cancer Genome Atlas (TCGA). The investigation revealed signatures of functionally related genes containing germline, somatic and epigenetic variations. DNA methylation had an effect on gene expression. Network and pathway analysis revealed molecule networks and signaling pathways enriched for germline, somatic and epigenomic variation, among them: Role of BRCA1 in DNA Damage Response, Hereditary Breast Cancer Signaling, Molecular Mechanisms of Cancer, Estrogen-Dependent Breast Cancer, p53, MYC Mediated Apoptosis, and PTEN Signaling pathways. The investigation revealed that integrative genomics is a powerful approach for deconvoluting the genomic-epigenomic interaction landscape in TNBC. Further studies are needed to understand the biological mechanisms underlying oncogenic interactions between genomic and epigenomic factors in TNBC.

Joint effects of multiple sleep characteristics on breast cancer progression by menopausal status

OBJECTIVES

Sleep has been closely linked to breast cancer risk. However, the association between sleep and breast cancer prognosis remains unclear. The aim of this study was to evaluate the separate and joint effects of multiple sleep characteristics on breast cancer prognosis among Chinese women.

METHODS

A total of 1580 breast cancer patients were recruited between October 2008 and December 2014 and followed up until December 31, 2017 in Guangzhou. Multivariate Cox models were conducted to estimate the hazard ratios (HR) and 95% confidence intervals (95%CI) for breast cancer prognosis in association with sleep characteristics.

RESULTS

Long sleep duration at night (>9 h) (HR = 2.33, 95%CI: 1.01-5.42), poor sleep quality (HR = 3.08, 95%CI: 1.74-5.47), and impaired daytime function (HR = 2.49, 95%CI: 1.65-3.79) after diagnosis were associated with an increased risk of breast cancer progression. Both short sleep duration (<6 h) (HR = 2.00, 95%CI: 1.06-3.77, P_interaction = 0.011) and long sleep duration (>9 h) (HR = 4.69, 95%CI: 1.31-16.78, P_interaction = 0.187) increased the progression risk only among patients with impaired but not normal daytime function. In addition, daytime napping significantly modified the effect of short sleep duration on the progression (HR = 3.55, 0.59, 95%CI: 1.55-7.97, 0.23-1.53 for patients without and with daytime napping, respectively, P_interaction = 0.005). Stratification results suggested that the associations were more evident among pre-menopausal patients, although no significant interaction was observed.

CONCLUSION

Our findings suggested that inadequate sleep duration to feel one's best and poor sleep quality after diagnosis were associated with an increased risk of breast cancer progression, particularly for pre-menopausal women.

XRCC1 rs1799782 (C194T) polymorphism correlated with tumor metastasis and molecular subtypes in breast cancer

BACKGROUND

Breast cancer, a malignant tumor with its highest incidence in women, affects physical and mental health, and can even be life-threatening. In recent years, its incidence has continued to grow, accompanied by a trend of younger onset. XRCC1 is well known as a DNA-repair gene, and its abnormal expression is related to the occurrence of various malignant tumors.

METHODS

In this study, we detected XRCC1 expression and investigated its association with the XRCC1 rs1799782 polymorphism. XRCC1 was overexpressed to investigate its effect on in breast cancer cells. CCK8 and clone formation efficiency assay were used to detect cell proliferation. Transwell assay was performed to confirm cell migration and invasion. Flow cytometry was used to detect cell apoptosis.

RESULTS

In 118 breast cancer samples, CC genotype frequency was 49.15% (58 of 118), CT genotype frequency was 42.37% (50 of 118), and TT genotype frequency was 8.48% (ten of 118). Lymphatic metastasis was associated with a higher frequency of XRCC1 rs1799782 polymorphism (P<0.05), and breast cancer patients with positive PR, HER2, and negative ER had high XRCC1 rs1799782 frequency (P<0.05). Meanwhile, XRCC1 had low expression in breast cancer (74.6%, 88 of 118) and high expression in ER-negative, PR-negative, HER2-positive and Ki67-low-expression patients. XRCC1 rs1799782 may play an important role in the development and metastasis of breast cancer. These results differ from previous studies that did not suggest that rs1799782 is effective in breast cancer. We also investigated the role of XRCC1 in breast cancer progression.

CONCLUSION

We have proved that XRCC1 can inhibit proliferation and invasion and promote apoptosis of breast cancer cells. XRCC1 expression was regulated by the JNK pathway. We found that the JNK inhibitor SP600125 significantly inhibited the growth of breast cancer cells, and consider it a potential drug for breast cancer.

Systematic pan-cancer analysis of somatic allele frequency

Imbalanced expression of somatic alleles in cancer can suggest functional and selective features, and can therefore indicate possible driving potential of the underlying genetic variants. To explore the correlation between allele frequency of somatic variants and total gene expression of their harboring gene, we used the unique data set of matched tumor and normal RNA and DNA sequencing data of 5523 distinct single nucleotide variants in 381 individuals across 10 cancer types obtained from The Cancer Genome Atlas (TCGA). We analyzed the allele frequency in the context of the variant and gene functional features and linked it with changes in the total gene expression. We documented higher allele frequency of somatic variants in cancer-implicated genes (Cancer Gene Census, CGC). Furthermore, somatic alleles bearing premature terminating variants (PTVs), when positioned in CGC genes, appeared to be less frequently degraded via nonsense-mediated mRNA decay, indicating possible favoring of truncated proteins by the tumor transcriptome. Among the genes with multiple PTVs with high allele frequency, ARID1, TP53 and NSD1 were known key cancer genes. All together, our analyses suggest that high allele frequency of tumor somatic variants can indicate driving functionality and can serve to identify potential cancer-implicated genes.

Polymorphisms in homologous recombination repair genes and the risk and survival of breast cancer

BACKGROUND

Immunoglobulin (Ig)A antibody of Epstein-Barr virus (EBV) was found to associate with breast cancer (BC), whereas IgA positivity was related to a series of genetic markers in the genes of homologous recombination repair system (HRRs). We assessed the associations of the polymorphisms in HRR genes with the risk and survival of BC.

METHODS

A case-control study was conducted with 1551 bc cases and 1605 age-matched healthy controls between October 2008 and March 2012 in the Guangzhou Breast Cancer Study (GZBCS), China, and the case population were followed up until 31 January 2016. Five single nucleotide polymorphisms of candidate genes in HRR system were genotyped. Odds ratios (ORs) and hazards ratios (HRs) were calculated using multivariate logistic regression and Cox proportional hazards regression to estimate the risk and prognostic effect, respectively.

RESULTS

RFC1 rs6829064 (AA) was associated with an increased BC risk [OR = 1.35; 95% confidence interval (CI) = 1.06-1.73] compared to the wild genotype (GG). NRM rs1075496 (GT/TT versus GG) was associated with a worse progression-free survival (PFS) and the HR was 1.34 (95% CI = 1.01-1.78), particularly among advanced patients. LIG3 rs1052536 (CT/TT versus CC) was associated with a better PFS and the HR was 0.70 (95% CI = 0.53-0.93). However, RAD54L rs1710286 and RPA1 rs11078676 were not observed to be associated with either the risk or survival of BC.

CONCLUSIONS

The findings of the present study suggest that the polymorphisms in HRR genes were associated with BC risk (RFC1 rs6829064) and prognosis (NRM rs1075496 and LIG3 rs1052536), whereas RAD54L rs1710286 and RPA1 rs11078676 had null associations with BC.

Identification of expression quantitative trait loci (eQTLs) in human peripheral blood mononuclear cells (PBMCs) and shared with liver and brain

PBMCs are essential for immunity and involved in various diseases. To identify genetic variations contributing to PBMCs transcriptome-wide gene expression, we performed a genome-wide eQTL analysis by using genome-wide SNPs data and transcriptome-wide mRNA expression data. To assess whether there are common regulation patterns shared among different tissues/organs, public datasets were utilized to identify common eQTLs shared with PBMCs in lymphoblastoid, monocytes, liver, and brain. Allelic expression imbalance (AEI) assay was employed to validate representative eQTLs identified. We identified 443 cis- and 2386 trans-eSNPs (FDR <0.05), which regulated 128 and 635 target genes, respectively. A transcriptome-wide expression regulation network was constructed, highlighting the importance of 28 pleiotropic eSNPs and 18 dually (cis- and trans-) regulated genes. Three genes, that is, TIPRL, HSPB8, and EGLN3, were commonly regulated by hundreds of eSNPs and constituted a very complex interaction network. Strikingly, the missense SNP rs371513 trans- regulated 25 target genes, which were functionally related to poly(A) RNA binding. Among 8904 eQTLs (P < 0.001) identified herein in PBMCs, a minority (163) was overlapped with lymphoblastoid, monocytes, liver, and/or brain. Besides, two cis-eSNPs in PBMC were confirmed by AEI. The present results demonstrated a comprehensive expression regulation network for human PBMCs and may provide novel insights into the pathogenesis of immunological diseases related to PBMCs.

Overexpressed somatic alleles are enriched in functional elements in Breast Cancer

Asymmetric allele content in the transcriptome can be indicative of functional and selective features of the underlying genetic variants. Yet, imbalanced alleles, especially from diploid genome regions, are poorly explored in cancer. Here we systematically quantify and integrate the variant allele fraction from corresponding RNA and DNA sequence data from patients with breast cancer acquired through The Cancer Genome Atlas (TCGA). We test for correlation between allele prevalence and functionality in known cancer-implicated genes from the Cancer Gene Census (CGC). We document significant allele-preferential expression of functional variants in CGC genes and across the entire dataset. Notably, we find frequent allele-specific overexpression of variants in tumor-suppressor genes. We also report a list of over-expressed variants from non-CGC genes. Overall, our analysis presents an integrated set of features of somatic allele expression and points to the vast information content of the asymmetric alleles in the cancer transcriptome.

Modification effects of genetic polymorphisms in FTO, IL-6, and HSPD1 on the associations of diabetes with breast cancer risk and survival

The contribution of diabetes to breast cancer remains uncertain among Chinese females, which may result from different genetic factors. We evaluated the associations of diabetes, combined with the polymorphisms in the genes of fat mass and obesity-associated gene (FTO), interleukin 6 (IL-6), and heat shock protein 60 (HSPD1), with breast cancer risk and survival in a Chinese Han population. The information on the history of diabetes was collected from 1551 incident breast cancer cases and 1605 age-frequency matched controls in Guangzhou, China. In total, 1168 cases were followed up. Diabetes was associated with both an increased risk of breast cancer [OR (95%CI): 1.67 (1.11, 2.52)] and a poor overall survival and progression free survival for breast cancer patients [HRs (95%CIs): 2.66 (1.10, 6.44) and 2.46 (1.29, 4.70), respectively]. IL-6 rs1800796 and HSPD1 rs2605039 had interactions with diabetes on breast cancer risk. Among women with CC genotype of IL-6 rs1800796 or GG genotype of HSPD1 rs2605039, diabetic individuals had a remarkably increased risk of breast cancer compared to non-diabetic women with ORs and 95%CIs of 2.53 (1.45, 4.41) and 6.40 (2.29, 17.87), respectively. GT/TT genotypes of HSPD1 rs2605039 was also associated with a better progression free survival for breast cancer patients [HR (95%CI): 0.70 (0.49, 0.99)]. Our results suggest that the contribution of diabetes to breast cancer risk might be modified by IL-6 rs1800796 and HSPD1 rs2605039. Diabetes and HSPD1 rs2605039 might also influence breast cancer prognosis.

Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.