RESULTS: In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are related to Alzheimer's disease; 2. ZNF329 and RB1 significantly regulate those 'mesenchymal' gene expression signature genes for brain tumors.
CONCLUSION: By merely leveraging gene expression data, CBDN can efficiently infer the existence of gene-gene interactions as well as their regulatory directions. The constructed networks are helpful in the identification of important regulators for complex diseases.
RESULTS: In the present study, in silico prediction of MAR/SAR was performed in the ABL gene. More than 80% of the predicted MAR/SAR sites are closely associated with previously reported patient breakpoint cluster regions (BCR). By using inverse polymerase chain reaction (IPCR), we demonstrated that hydrogen peroxide (H2O2)-induced apoptosis in normal nasopharyngeal epithelial and NPC cells led to chromosomal breakages within the ABL BCR that contains a MAR/SAR. Intriguingly, we detected two translocations in H2O2-treated cells. Region of microhomology was found at the translocation junctions. This observation is consistent with the operation of microhomology-mediated NHEJ.
CONCLUSIONS: Our findings suggested that oxidative stress-induced apoptosis may participate in chromosome rearrangements of NPC. A revised model for oxidative stress-induced apoptosis mediating chromosome rearrangement in NPC is proposed.
DESIGN: We used genome sequencing data to assess the prevalence of mutations in syndromic HH genes in an international cohort of patients with HH of unknown genetic cause.
PATIENTS: We undertook genome sequencing in 82 infants with HH without a clinical diagnosis of a known syndrome at referral for genetic testing.
MEASUREMENTS: Within this cohort, we searched for the genetic aetiologies causing 20 different syndromes where HH had been reported as a feature.
RESULTS: We identified a pathogenic KMT2D variant in a patient with HH diagnosed at birth, confirming a genetic diagnosis of Kabuki syndrome. Clinical data received following the identification of the mutation highlighted additional features consistent with the genetic diagnosis. Pathogenic variants were not identified in the remainder of the cohort.
CONCLUSIONS: Pathogenic variants in the syndromic HH genes are rare; thus, routine testing of these genes by molecular genetics laboratories is unlikely to be justified in patients without syndromic phenotypes.
METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.
MATERIALS AND METHODS: A total of 17 patients were selected fulfilling one of the Bethesda criteria: colorectal cancer diagnosed in a patient aged less than 50 years old, having synchronous and metachronous colorectal cancer or with a strong family history. Immunohistochemical staining was performed on paraffin embedded tumour tissue samples using four antibodies: MLH1, MSH2, MSH6 and PMS2.
RESULTS: Twelve out of 17 patients (70.6%) were noted to have a family history. A total of 41% (n=7) of the patients had abnormal immunohistochemical staining with one or more of the four antibodies. Loss of expression were noted in 13 tumour tissues with a negative staining score <4. Of 13 tumour tissues, four showed loss expression of MLH1. For PMS2, loss of expression were noted in five cases. Both MSH2 and MSH6 showed loss of expression in two tumour tissues respectively.
CONCLUSIONS: Revised Bethesda criteria and immunohistochemical analysis constituted a convenient approach and is recommended to be a first-line screening for Lynch syndrome in Malay cohorts.
METHODS: Seven single-nucleotide polymorphisms (SNPs) in IKZF1, three SNPs in DDC, two SNPs in CDKN2A, two SNPs in CEBPE, and three SNPs in LMO1 were genotyped in 289 Yemeni children (136 cases and 153 controls), using the nanofluidic Dynamic Array (Fluidigm 192.24 Dynamic Array). Logistic regression analyses were used to estimate ALL risk, and the strength of association was expressed as odds ratios with 95% confidence intervals.
RESULTS: We found that the IKZF1 SNP rs10235796 C allele (p = 0.002), the IKZF1 rs6964969 A>G polymorphism (p = 0.048, GG vs. AA), the CDKN2A rs3731246 G>C polymorphism (p = 0.047, GC+CC vs. GG), and the CDKN2A SNP rs3731246 C allele (p = 0.007) were significantly associated with ALL in Yemenis of Arab-Asian descent. In addition, a borderline association was found between IKZF1 rs4132601 T>G variant and ALL risk. No associations were found between the IKZF1 SNPs (rs11978267; rs7789635), DDC SNPs (rs3779084; rs880028; rs7809758), CDKN2A SNP (rs3731217), the CEBPE SNPs (rs2239633; rs12434881) and LMO1 SNPs (rs442264; rs3794012; rs4237770) with ALL in Yemeni children.
CONCLUSION: The IKZF1 SNPs, rs10235796 and rs6964969, and the CDKN2A SNP rs3731246 (previously unreported) could serve as risk markers for ALL susceptibility in Yemeni children.