Role of the XRCC5/XRCC6 dimer in carcinogenesis and pharmacogenomics

Lactate reprograms glioblastoma immunity through CBX3-regulated histone lactylation

Glioblastoma (GBM), an aggressive brain malignancy with a cellular hierarchy dominated by GBM stem cells (GSCs), evades antitumor immunity through mechanisms that remain incompletely understood. Like most cancers, GBMs undergo metabolic reprogramming toward glycolysis to generate lactate. Here, we show that lactate production by patient-derived GSCs and microglia/macrophages induces tumor cell epigenetic reprogramming through histone lactylation, an activating modification that leads to immunosuppressive transcriptional programs and suppression of phagocytosis via transcriptional upregulation of CD47, a "don't eat me" signal, in GBM cells. Leveraging these findings, pharmacologic targeting of lactate production augments efficacy of anti-CD47 therapy. Mechanistically, lactylated histone interacts with the heterochromatin component chromobox protein homolog 3 (CBX3). Although CBX3 does not possess direct lactyltransferase activity, CBX3 binds histone acetyltransferase (HAT) EP300 to induce increased EP300 substrate specificity toward lactyl-CoA and a transcriptional shift toward an immunosuppressive cytokine profile. Targeting CBX3 inhibits tumor growth by both tumor cell-intrinsic mechanisms and increased tumor cell phagocytosis. Collectively, these results suggest that lactate mediates metabolism-induced epigenetic reprogramming in GBM that contributes to CD47-dependent immune evasion, which can be leveraged to augment efficacy of immuno-oncology therapies.

Carboplatin-induced upregulation of pan β-tubulin and class III β-tubulin is implicated in acquired resistance and cross-resistance of ovarian cancer

Resistance to platinum- and taxane-based chemotherapy represents a major obstacle to long-term survival in ovarian cancer (OC) patients. Here, we studied the interplay between acquired carboplatin (CBP) resistance using two OC cell models, MES-OV CBP and SK-OV-3 CBP, and non-P-glycoprotein-mediated cross-resistance to paclitaxel (TAX) observed only in MES-OV CBP cells. Decreased platination, mesenchymal-like phenotype, and increased expression of α- and γ-tubulin were observed in both drug-resistant variants compared with parental cells. Both variants revealed increased protein expression of class III β-tubulin (TUBB3) but differences in TUBB3 branching and nuclear morphology. Transient silencing of TUBB3 sensitized MES-OV CBP cells to TAX, and surprisingly also to CBP. This phenomenon was not observed in the SK-OV-3 CBP variant, probably due to the compensation by other β-tubulin isotypes. Reduced TUBB3 levels in MES-OV CBP cells affected DNA repair protein trafficking and increased whole-cell platination level. Furthermore, TUBB3 depletion augmented therapeutic efficiency in additional OC cells, showing vice versa drug-resistant pattern, lacking β-tubulin isotype compensation visible at the level of total β-tubulin (TUBB) in vitro and ex vivo. In summary, the level of TUBB in OC should be considered together with TUBB3 in therapy response prediction.

A novel NHEJ gene signature based model for risk stratification and prognosis prediction in hepatocellular carcinoma

BACKGROUND

Non-homologous DNA end joining (NHEJ) is the predominant DNA double-strand break (DSB) repair pathway in human. However, the relationship between NHEJ pathway and hepatocellular carcinoma (HCC) is unclear. We aimed to explore the potential prognostic role of NHEJ genes and to develop an NHEJ-based prognosis signature for HCC.

METHODS

Two cohorts from public database were incorporated into this study. The Kaplan-Meier curve, the Least absolute shrinkage and selection operator (LASSO) regression analysis, and Cox analyses were implemented to determine the prognostic genes. A NHEJ-related risk model was created and verified by independent cohorts. We derived enriched pathways between the high- and low-risk groups using Gene Set Enrichment Analysis (GSEA). CIBERSORT and microenvironment cell populations-counter algorithm were used to perform immune infiltration analysis. XRCC6 is a core NHEJ gene and immunohistochemistry (IHC) was further performed to elucidate the prognostic impact. In vitro proliferation assays were conducted to investigate the specific effect of XRCC6.

RESULTS

A novel NHEJ-related risk model was developed based on 6 NHEJ genes and patients were divided into distinct risk groups according to the risk score. The high-risk group had a poorer survival than those in the low-risk group (P < 0.001). Meanwhile, an obvious discrepancy in the landscape of the immune microenvironment also indicated that distinct immune status might be a potential determinant affecting prognosis as well as immunotherapy reactiveness. High XRCC6 expression level associates with poor outcome in HCC. Moreover, XRCC6 could promote HCC cell proliferation in vitro.

CONCLUSIONS

In brief, this work reveals a novel NHEJ-related risk signature for prognostic evaluation of HCC patients, which may be a potential biomarker of HCC immunotherapy.

The multi-omics analysis identifies a novel cuproptosis-anoikis-related gene signature in prognosis and immune infiltration characterization of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) has emerged as one of the most aggressive lethal cancers. Anoikis serves as programmed apoptosis initiated by the detachment of cells from the extracel-lular matrix. Cuproptosis is distinct from traditional cell death modalities. The above two modes are both closely related to tumor progression, prognosis, and treatment. However, whether they have synergistic effects in LUAD deserves further investigation.

Methods

The anoikis-related prognostic genes (ANRGs) co-expressed with cuproptosis-associated genes (CAGs) were screened using correlation analysis, analysis of variance, least absolute shrinkage, and selection operator (LASSO), and COX regression followed by functional analysis, and then LUAD risk score model was constructed. Using consensus clustering, the relationship between different subtypes and clinicopathological features, immune infiltration characteristics, and somatic mutations was analyzed. A nomogram was developed by incorporating clinical information, which provided a prediction of the survival of patients. Finally, a comprehensive analysis of ANRGs was performed and verified by the HPA database.

Results

A total of 27 ANRGs associated with cuproptosis were obtained. On this basis, three distinct ANRGs subtypes were identified, and the differences between clinical prognosis and immune infiltration were observed. A risk score model has been constructed by incorporating seven ANRGs signatures (EIF2AK3, IKZF3, ITGAV, OGT, PLK1, TRAF2, XRCC5). A highly reliable nomogram was developed to help formulate treatment strategies based on risk score and the clinicopathological features of LUAD. The seven-gene signature was turned out to be strongly linked to immune cells and validated in single-cell data. Immunohistochemistry proved that all of them are highly expressed in LUAD tissues.

Conclusion

This study reveals the potential relationship between cuproptosis-related ANRGs and clinicopathological features, tumor microenvironment (TME), and mutation characteristics, which can be applied for predicting the prognosis of LUAD and help develop individualized treatment strategies.

E-liquid exposure induces bladder cancer cells to release extracellular vesicles that promote non-malignant urothelial cell transformation

The vaping of electronic cigarettes (E-cigarettes) has recently emerged as a popular alternative to traditional cigarette smoking, but its association with bladder cancer (BC) risk remains to be established. BC patients exhibit high rates of recurrent disease, possibly as a consequence of the field cancerization effect. We have shown that BC-derived extracellular vesicles (BCEVs) can permanently alter recipient urothelial cells in predisposed fields such that they become fully transformed malignant cells. To model the role that BCEVs may play in this potentially oncogenic setting, we treated TCCSUP BC cells with cigarette smoke extract, unflavored E-liquid, or menthol flavored E-liquid. Those treated BCEVs were then tested for their tumorigenic potential. We found that these smoking- and E-cigarette-related BCEVs were able to promote oxidative stress, inflammatory signaling, and DNA damage in recipient SV-HUC urothelial cells. Strikingly, menthol E-liquid-induced BCEVs significantly increased rates of malignant urothelial cell transformation. While further in vivo validation of the simultaneous effects of E-liquid and E-liquid-induced BCEVs on field cancerization is needed, these data highlight the possibility that E-cigarettes may compound user risk in a manner that can contribute to higher rates of BC incidence or recurrence.

Label-Free Quantitative Proteomics Analysis of Adriamycin Selected Multidrug Resistant Human Lung Cancer Cells

The development of drug resistance in lung cancer is a major clinical challenge, leading to a 5-year survival rate of only 18%. Therefore, unravelling the mechanisms of drug resistance and developing novel therapeutic strategies is of crucial importance. This study systematically explores the novel biomarkers of drug resistance using a lung cancer model (DLKP) with a series of drug-resistant variants. In-depth label-free quantitative mass spectrometry-based proteomics and gene ontology analysis shows that parental DLKP cells significantly differ from drug-resistant variants, and the cellular proteome changes even among the drug-resistant subpopulations. Overall, ABC transporter proteins and lipid metabolism were determined to play a significant role in the formation of drug resistance in DKLP cells. A series of membrane-related proteins such as HMOX1, TMB1, EPHX2 and NEU1 were identified to be correlated with levels of drug resistance in the DLKP subpopulations. The study also showed enrichment in biological processes and molecular functions such as drug metabolism, cellular response to the drug and drug binding. In gene ontology analysis, 18 proteins were determined to be positively or negatively correlated with resistance levels. Overall, 34 proteins which potentially have a therapeutic and diagnostic value were identified.

Bioinformatics analysis identifies potential biomarkers involved in the metastasis of locoregionally advanced nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is one of the malignant epithelial tumors with a high metastasis rate. This study aimed to screen potential novel biomarkers involved in NPC metastasis. Microarray data of locoregionally advanced NPC (LA-NPC; GSE103611) were obtained from the database of Gene Expression Omnibus. The differentially expressed genes (DEGs) between LA-NPC tissues with and without distant metastasis after radical treatment were screened. Functional analysis was performed and the protein-protein interaction and submodule were analyzed. The univariate Cox regression analysis was performed to identify prognostic genes in NPC in the validation microarray dataset GSE102349. The drug-gene interactions and key genes were identified. Totally, 107 DEGs were identified. The upregulated DEGs and the key nodes in the protein-protein interaction network were associated with pathways or biological processes related to the cell cycle. Four genes including CD44, B2M, PTPN11, and TRIM74 were associated with disease-free survival in NPC. The drug-gene interaction analysis revealed that upregulated genes CXCL10, CD44, B2M, XRCC5, and RPL11 might be potential druggable genes for patients with LA-NPC metastasis by regulating cell cycle, autophagy, and drug resistance. Upregulated CXCL10, CD44, B2M, XRCC5, and RPL11 might play important roles in LA-NPC metastasis by regulating cell cycle-related pathways.

Identifying Breast Cancer-Related Genes Based on a Novel Computational Framework Involving KEGG Pathways and PPI Network Modularity

Complex diseases, such as breast cancer, are often caused by mutations of multiple functional genes. Identifying disease-related genes is a critical and challenging task for unveiling the biological mechanisms behind these diseases. In this study, we develop a novel computational framework to analyze the network properties of the known breast cancer–associated genes, based on which we develop a random-walk-with-restart (RCRWR) algorithm to predict novel disease genes. Specifically, we first curated a set of breast cancer–associated genes from the Genome-Wide Association Studies catalog and Online Mendelian Inheritance in Man database and then studied the distribution of these genes on an integrated protein–protein interaction (PPI) network. We found that the breast cancer–associated genes are significantly closer to each other than random, which confirms the modularity property of disease genes in a PPI network as revealed by previous studies. We then retrieved PPI subnetworks spanning top breast cancer–associated KEGG pathways and found that the distribution of these genes on the subnetworks are non-random, suggesting that these KEGG pathways are activated non-uniformly. Taking advantage of the non-random distribution of breast cancer–associated genes, we developed an improved RCRWR algorithm to predict novel cancer genes, which integrates network reconstruction based on local random walk dynamics and subnetworks spanning KEGG pathways. Compared with the disease gene prediction without using the information from the KEGG pathways, this method has a better prediction performance on inferring breast cancer–associated genes, and the top predicted genes are better enriched on known breast cancer–associated gene ontologies. Finally, we performed a literature search on top predicted novel genes and found that most of them are supported by at least wet-lab experiments on cell lines. In summary, we propose a robust computational framework to prioritize novel breast cancer–associated genes, which could be used for further in vitro and in vivo experimental validation.

Identifying Breast Cancer-Related Genes Based on a Novel Computational Framework Involving KEGG Pathways and PPI Network Modularity

Complex diseases, such as breast cancer, are often caused by mutations of multiple functional genes. Identifying disease-related genes is a critical and challenging task for unveiling the biological mechanisms behind these diseases. In this study, we develop a novel computational framework to analyze the network properties of the known breast cancer-associated genes, based on which we develop a random-walk-with-restart (RCRWR) algorithm to predict novel disease genes. Specifically, we first curated a set of breast cancer-associated genes from the Genome-Wide Association Studies catalog and Online Mendelian Inheritance in Man database and then studied the distribution of these genes on an integrated protein-protein interaction (PPI) network. We found that the breast cancer-associated genes are significantly closer to each other than random, which confirms the modularity property of disease genes in a PPI network as revealed by previous studies. We then retrieved PPI subnetworks spanning top breast cancer-associated KEGG pathways and found that the distribution of these genes on the subnetworks are non-random, suggesting that these KEGG pathways are activated non-uniformly. Taking advantage of the non-random distribution of breast cancer-associated genes, we developed an improved RCRWR algorithm to predict novel cancer genes, which integrates network reconstruction based on local random walk dynamics and subnetworks spanning KEGG pathways. Compared with the disease gene prediction without using the information from the KEGG pathways, this method has a better prediction performance on inferring breast cancer-associated genes, and the top predicted genes are better enriched on known breast cancer-associated gene ontologies. Finally, we performed a literature search on top predicted novel genes and found that most of them are supported by at least wet-lab experiments on cell lines. In summary, we propose a robust computational framework to prioritize novel breast cancer-associated genes, which could be used for further in vitro and in vivo experimental validation.

Super Secondary Structures of Proteins with Post-Translational Modifications in Colon Cancer

New advances in protein post-translational modifications (PTMs) have revealed a complex layer of regulatory mechanisms through which PTMs control cell signaling and metabolic pathways, contributing to the diverse metabolic phenotypes found in cancer. Using conformational templates and the three-dimensional (3D) environment investigation of proteins in patients with colorectal cancer, it was demonstrated that most PTMs (phosphorylation, acetylation, and ubiquitination) are localized in the supersecondary structures (helical pairs). We showed that such helical pairs are represented on the outer surface of protein molecules and characterized by a largely accessible area for the surrounding solvent. Most promising and meaningful modifications were observed on the surface of vitamin D-binding protein (VDBP), complement C4-A (CO4A), X-ray repair cross-complementing protein 6 (XRCC6), Plasma protease C1 inhibitor (IC1), and albumin (ALBU), which are related to colorectal cancer developing. Based on the presented data, we propose the impact of the observed modifications in immune response, inflammatory reaction, regulation of cell migration, and promotion of tumor growth. Here, we suggest a computational approach in which high-throughput analysis for identification and characterization of PTM signature, associated with cancer metabolic reprograming, can be improved to prognostic value and bring a new strategy to the targeted therapy.

The up-regulation of NDRG1 by HIF counteracts the cancer-promoting effect of HIF in VHL-deficient clear cell renal cell carcinoma

BACKGROUND

Hypoxia-inducible factors (HIFs) are thought to play important roles in the carcinogenesis and progression of VHL-deficient clear cell renal cell carcinoma (ccRCC).

METHODS

The roles of HIF-1/2α in VHL-deficient clear cell renal cell carcinoma were evaluated by bioinformatics analysis, immunohistochemistry staining and Kaplan-Meier survival analysis. The downstream genes that counteract the cancer-promoting effect of HIF were analysed by unbiased proteomics and verified by in vitro and in vivo assays.

RESULTS

There was no correlation between the high protein level of HIF-1/2α and the poor prognosis of ccRCC patients in our large set of clinical data. Furthermore, NDRG1 was found to be up-regulated by both HIF-1α and -2α at the cellular level and in ccRCC tissues. Intriguingly, the high NDRG1 expression was correlated with lower Furman grade, TNM stage and longer survival for ccRCC patients compared with the low NDRG1 expression. In addition, NDRG1 suppressed the expression of series oncogenes as well as the proliferation, metastasis and invasion of VHL-deficient ccRCC cells in vitro and vivo.

CONCLUSIONS

Our study demonstrated that HIF downstream gene of NDRG1 may counteract the cancer-promoting effect of HIF. These results provided evidence that NDRG1 may be a potential prognostic biomarker as well as a therapeutic target in ccRCC.

Evaluation of X-Ray Repair Cross-Complementing Family Members as Potential Biomarkers for Predicting Progression and Prognosis in Hepatocellular Carcinoma

The X-ray repair cross-complementing (XRCC) gene family has been revealed to participate in the carcinogenesis and development of numerous cancers. However, the expression profiles and prognostic values of XRCCs (XRCC1-6) in hepatocellular carcinoma (HCC) have not been explored up to now. The transcriptional levels of XRCCs in primary HCC tissues were analyzed by UALCAN and GEPIA. The relationship between XRCCs expression and HCC clinical characteristics was evaluated using UALCAN. Moreover, the prognostic values of XRCCs expression and mutations in HCC patients were investigated via the GEPIA and cBioPortal, respectively. Last but not least, the functions and pathways of XRCCs in HCC were also predicted by cBioPortal and DVAID. The transcriptional levels of all XRCCs in HCC tissues were notably elevated compared with normal liver tissues. Meanwhile, upregulated XRCCs expression was positively associated with clinical stages and tumor grades of HCC patients. Survival analysis using the GEPIA database revealed that high transcription levels of XRCC2/3/4/5/6 were associated with lower overall survival (OS) and high transcription levels of XRCC1/2/3/6 were correlated with poor disease-free survival (DFS) in HCC patients. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated the possible mechanisms of XRCCs and their associated genes participating in the oncogenesis of HCC. Our findings systematically elucidate the expression profiles and distinct prognostic values of XRCCs in HCC, which might provide promising therapeutic targets and novel prognostic biomarkers for HCC patients.

Overexpression of miR-623 suppresses progression of hepatocellular carcinoma via regulating the PI3K/Akt signaling pathway by targeting XRCC5

It has been reported that miR-623 is deregulated in lung adenocarcinoma and inhibits tumor growth and invasion. However, it is unclear whether miR-623 has a role in the progression of hepatocellular carcinoma (HCC). Herein, we found that miR-623 was significantly downregulated in HCC, and that its expression was related to poor clinical outcomes of patients with HCC. Upregulation of miR-623 decreased cell proliferation, viability, migration, and invasion and further promoted apoptosis in 7721, Huh7, and Bel-7402 cells. Moreover, we also observed that miR-623 regulated the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), Wnt/β-catenin, and extracellular regulated protein kinases/c-Jun N-terminal kinase (ERK/JNK) signaling pathways as well as the expression level of related proteins. Further, X-ray repair cross complementing 5 (XRCC5) was a direct target for miR-623, and the suppression of PI3K/Akt, Wnt/β-catenin, and ERK/JNK signaling pathways and cell proliferation and invasion abilities caused by miR-623 in HCC cells was significantly reversed by the upregulation of XRCC5. Collectively, our data suggested that miR-623 suppressed the progression of HCC by regulating the PI3K/Akt, Wnt/β-catenin, and ERK/JNK pathways by targeting XRCC5 in HCC in vitro, indicating that miR-623 may be a target for the therapy of HCC.

XRCC4 c.1394G>T Single Nucleotide Polymorphisms and Breast Cancer Risk among Filipinos

Background:

The identification of cancer-associated single nucleotide polymorphisms (SNP) and mutation genes is a promising approach in recognizing individuals who are at risk of developing cancer. Hence, this study was conducted to determine the association between XRCC4 c.1394G>T SNP and breast cancer development among Filipinos.

Methods:

Genotyping for XRCC4 c.1394G>T SNP was performed on breast cancer patients (n=103) and their age- and sex- matched clinically healthy controls (n=103) by polymerase chain reaction – restriction fragment length polymorphism.

Results:

Significant difference in genotype (p=0.007) and allele (p=0.003) frequencies in XRCC4 c.1394G>T was observed between the breast cancer cases and controls. Carriers of the XRCC4 c.1394 G>T genotype were observed to have significantly higher risk of developing breast cancer compared to individuals with T/T genotype (OR=2.67, 95% CI: 1.36 – 5.25). XRCC4 c.1394G>T combined with passive smoking may also significantly increase risk of breast cancer (OR=14.73; 95% CI= 9.88-18.86).

Conclusion:

XRCC4 c. 1394G>T may be associated with breast cancer development among Filipinos.

Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets.

The relationship between polymorphisms of XRCC5 genes with astrocytoma prognosis in the Han Chinese population

BACKGROUND

Gliomas are highly malignant with a poor prognosis. Studies have reported that DNA repair genes influence risk for glioma, but its relationship with prognosis is unclear. In this study, we want to explore the relationship between DNA repair genes (XRCC3, XRCC4 and XRCC5) and prognosis of astrocytoma in the Chinese Han population.

MATERIALS AND METHODS

160 astrocytoma cases were recruited in our study. Survival probabilities were estimated by using Kaplan-Meier analysis, and significant differences were analyzed by using the log-rank test. Cox proportional hazards models were used to analyze the associations between genotypes with astrocytoma survival. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using multivariable models. All tests were two-sided and p < 0.05 was considered to be significant.

RESULTS

The SNP (rs9288516) in XRCC5 (HR: 1.69, 95%CI: 1.04 - 2.77, p = 0.049), surgical approach (HR: 0.61, 95%CI: 0.43 - 0.88, p = 0.003) and chemotherapy (HR: 0.71, 95%CI: 0.50 - 0.99, p = 0.029) were associated with astrocytoma prognosis. Further, the "A/A" genotype of rs9288516 in XRCC5 (HR: 1.67, 95%CI: 1.02 - 2.72, p = 0.042) had significantly outcomes after adjusting for potential confounders, patients with poor tumor differentiation and the coexistence of the unfavorable genotypes.

CONCLUSION

These results suggest that polymorphisms of XRCC5 play an important role in astrocytoma prognosis in the Chinese Han population which could be used in the determination of astrocytoma prognosis in clinical researches.

Ku80 cooperates with CBP to promote COX-2 expression and tumor growth

Cyclooxygenase-2 (COX-2) plays an important role in lung cancer development and progression. Using streptavidin-agarose pulldown and proteomics assay, we identified and validated Ku80, a dimer of Ku participating in the repair of broken DNA double strands, as a new binding protein of the COX-2 gene promoter. Overexpression of Ku80 up-regulated COX-2 promoter activation and COX-2 expression in lung cancer cells. Silencing of Ku80 by siRNA down-regulated COX-2 expression and inhibited tumor cell growth in vitro and in a xenograft mouse model. Ku80 knockdown suppressed phosphorylation of ERK, resulting in an inactivation of the MAPK pathway. Moreover, CBP, a transcription co-activator, interacted with and acetylated Ku80 to co-regulate the activation of COX-2 promoter. Overexpression of CBP increased Ku80 acetylation, thereby promoting COX-2 expression and cell growth. Suppression of CBP by a CBP-specific inhibitor or siRNA inhibited COX-2 expression as well as tumor cell growth. Tissue microarray immunohistochemical analysis of lung adenocarcinomas revealed a strong positive correlation between levels of Ku80 and COX-2 and clinicopathologic variables. Overexpression of Ku80 was associated with poor prognosis in patients with lung cancers. We conclude that Ku80 promotes COX-2 expression and tumor growth and is a potential therapeutic target in lung cancer.

The current progress and future prospects of personalized radiogenomic cancer study

During the last twenty years, mounting studies have supported the hypothesis that there is a genetic component that plays an important role in clinically observed variability in individual tissue/organ toxicity after radiotherapy. We propose the term “Personalized Radiogenomics” for the translational study of individual genetic variations that may associate with or contribute to the responses of tissues to radiation therapy used in the treatment of all types of cancer. The missions of personalized radiogenomic research are 1) to reveal the related genes, proteins, and biological pathways responsible for non-tumor or tumor tissue toxicity resulting from radiotherapy that could be targeted with radio-sensitizing and/or radio-protective agents, and 2) to identify specific genetic markers that can be used in risk prediction and evaluation models before and after clinical cancer surgery. For the members of the Terry Fox Cancer Research Lab in China Medical University and Hospital, the long-term goal is to develop SNP-based risk models that can be used to stratify patients to more precisely tailored radiotherapy protocols. Worldwide, the field has evolved over the last two decades in parallel with rapid advances in genetic and genomic technology, moving step by step from narrowly focused candidate gene studies to large-scale, collaborative genome-wide association studies. This article will summarize the candidate gene association studies published so far from the Terry Fox Cancer Research Lab as well as worldwide on the risk of radiation-related cancers and highlight some wholegenome association studies showing feasibility in fulfilling the dream of personalized radiogenomic cancer therapy.

Genomic profiling reveals distinctive molecular relapse patterns in IDH1/2 wild-type glioblastoma

Molecular changes associated with the progression of glioblastoma after standard radiochemotherapy remain poorly understood. We compared genomic profiles of 27 paired primary and recurrent IDH1/2 wild-type glioblastomas by genome-wide array-based comparative genomic hybridization. By bioinformatic analysis, primary and recurrent tumor profiles were normalized and segmented, chromosomal gains and losses identified taking the tumor cell content into account, and difference profiles deduced. Seven of 27 (26%) pairs lacked DNA copy number differences between primary and recurrent tumors (equal pairs). The recurrent tumors in 9/27 (33%) pairs contained all chromosomal imbalances of the primary tumors plus additional ones, suggesting a sequential acquisition of and/or selection for aberrations during progression (sequential pairs). In 11/27 (41%) pairs, the profiles of primary and recurrent tumors were divergent, i.e., the recurrent tumors contained additional aberrations but had lost others, suggesting a polyclonal composition of the primary tumors and considerable clonal evolution (discrepant pairs). Losses on 9p21.3 harboring the CDKN2A/B locus were significantly more common in primary tumors from sequential and discrepant (nonequal) pairs. Nonequal pairs showed ten regions of recurrent genomic differences between primary and recurrent tumors harboring 46 candidate genes associated with tumor recurrence. In particular, copy numbers of genes encoding apoptosis regulators were frequently changed at progression. In summary, approximately 25% of IDH1/2 wild-type glioblastoma pairs have stable genomic imbalances. In contrast, approximately 75% of IDH1/2 wild-type glioblastomas undergo further genomic aberrations and alter their clonal composition upon recurrence impacting their genomic profile, a process possibly facilitated by 9p21.3 loss in the primary tumor. © 2014 Wiley Periodicals, Inc.

Genetic polymorphisms in DNA repair genes XRCC4 and XRCC5 and aflatoxin B1-related hepatocellular carcinoma

BACKGROUND

Genetic polymorphisms in DNA repair genes may influence individual variation in DNA repair capacity and may play an important role in carcinogenesis. We investigated the role of genetic polymorphisms at XRCC4 codon 247 (rs3734091, XRCC4P) and XRCC5 codon 180 (rs80309960, XRCC5P) in liver cancer (hepatocellular carcinoma) caused by aflatoxin B1 (AFB1).

METHODS

A hospital-based case-control study, including 1499 liver cancer cases and 2045 controls without any liver disease, was conducted in a high aflatoxin exposure area in the Guangxi region of China to assess the relationship between these two polymorphisms and aflatoxin-related liver cancer risk and prognosis. Genotypes, mRNA levels, and the hot-spot mutation of TP53 gene (TP53M) related to AFB1 exposure was tested using TaqMan-PCR technique. XRCC4 protein level was analyzed by immunohistochemistry.

RESULTS

For XRCC4P and XRCC5P, only XRCC4P modified liver cancer risk. Compared with the homozygote of XRCC4 codon 247 Ala alleles (XRCC4-AA), the genotypes of XRCC4 codon 247 Ser alleles (namely XRCC4-AS or -SS) increased liver cancer risk (odds ratio [OR] = 1.35 and 2.02, respectively). Significant interactive effects between risk genotypes (OR > 1) and aflatoxin exposure status were also observed in the joint effects analysis. Moreover, this polymorphism was associated not only with lower XRCC4 expression levels but also with higher AFB1-DNA adduct levels and increasing TP53M and portal vein tumor risk. Additionally, XRCC4P modified the recurrence-free survival and overall survival of cases, especially under conditions of high aflatoxin exposure.

CONCLUSION

XRCC4P may be a genetic modifier for the risk and outcome of hepatocellular carcinoma induced by AFB1 exposure.

Quantitative assessment of the association between XRCC6 C1310G polymorphism and cancer risk

X-ray cross-complementing group 6 (XRCC6) plays an important role in the DNA double-strand breaks repair and the maintenance of genomic integrity. XRCC6 C1310G polymorphism may be involved in the development of cancer through increasing genomic damages. However, studies investigating the relationship between XRCC6 C1310G polymorphism and cancer risk yielded contradictory results. To shed some light on these inconsistent findings, a meta-analysis was performed to clarify the effect of XRCC6 C1310G polymorphism on the susceptibility of cancer. A systemic literature search of PubMed, EMBASE, and China National Knowledge Infrastructure databases was conducted from their inception to September 26, 2012. The association between XRCC6 C1310G and cancer risk was assessed by the pooled odds ratio (OR) with 95 % confidence intervals (95 % CI) calculated by meta-analysis. A total of 15 eligible studies (4,642 cancer cases and 6,059 controls) were identified. Overall, there was obvious evidence for an association between XRCC6 C1310G polymorphism and increased risk of cancer under two genetic comparisons (GG vs. CC: fixed-effect OR 1.35, 95 % CI 1.10-1.66, I (2) = 17.0 %; GG vs. CG/CC: fixed-effect OR 1.25, 95 % CI 1.02-1.53, I (2) = 0.0 %). Subgroup analysis indicated that the association was significant in Asians (G vs. C: random-effect OR 1.13, 95 % CI 1.01-1.26, I (2) = 51.3 %; GG vs. CC: fixed-effect OR 1.43, 95 % CI 1.14-1.81, I (2) = 0.0 %; GG vs. CG/CC: fixed-effect OR 1.37, 95 % CI 1.09-1.72, I (2) = 0.0 %), but not in Europeans. Data from the current meta-analysis support the existence of an association between XRCC6 C1310G polymorphism and cancer risk in Asians. Studies with larger sample size are needed to further evaluate the influence of XRCC6 C1310G polymorphism on susceptibility of various cancers.

Genomic determinants of normal tissue toxicity after radiotherapy for head and neck malignancy: a systematic review

Interindividual variations in radiotoxicity responses exist despite uniform treatment protocols. It is speculated that normal genetic variants, particularly single nucleotide polymorphisms (SNPs) may influence normal head and neck (HN) tissue radiotoxicity. This first-ever systematic review was undertaken to evaluate the association of SNPs with normal HN tissues radiotoxicity. Multiple databases (1950-February 2012) were reviewed using a combination of related keywords and MeSH terms. All published HN radiotoxicity studies with sufficient relevant data for extraction were included. The outcomes evaluated were acute and late radiotoxicity endpoints. Methodological quality assessment based on the STrengthening the REporting of Genetic Association (STREGA) statement was performed. Seven articles from 692 articles searched fulfilled the eligibility criteria. Recruited sample sizes were small (range, 32-140). There were 5/7 case-control studies. All studies used multimodality treatment with heterogeneous radiation parameters. Candidate gene approach was used in all studies. Fourteen SNPs from 9 genes were evaluated from the following pathways: DNA damage response, radiation fibrogenesis and oxidative/xenobiotic metabolism. Acute radiotoxicity events were associated with SNPs of DNA repair genes (OR, 3.01-4.08). SNPs of TGFβ1 were associated with osteoradionecrosis (OR, 4.2) and subcutaneous fibrosis. Genetic association studies in HN radiotoxicity currently provide hypothesis-generating findings that require validation in larger studies. Future studies must incorporate critical methodological issues and technological improvements, including using a genome-wide approach. Headway is possible through case-pooling of existing clinical trial data which could create a larger sample size of well-characterized treatment and endpoints. Also, on-going HN cancer clinical trials should consider extending their toxicity evaluation to include genetic association studies.