Summing up: The Science of Reviewing Research

Genetic polymorphisms of cytochrome P450 1A1 (CYP1A1) and glutathione S-transferase M1 (GSTM1) genes might contribute to the variability in individual susceptibility to lung cancer, but the reported results from individual studies are not always consistent. We therefore conducted a meta-analysis to systematically estimate the associations between polymorphisms of these two genes and risk of lung cancer. Twenty-one studies with 8,926 subjects were finally enrolled into this study. Meta-analysis was performed by RevMan 5.2. Odds ratio (OR) and its 95 % confidence interval (CI) were calculated to evaluate the susceptibility to lung cancer. Compared with the wild-type homozygous genotype, significantly elevated risk of lung cancer were associated with variant CYP1A1 MspI (m1/m2 + m2/m2 vs. m1/m1: OR = 1.27, 95 % CI = 1.12–1.43, P < 0.001) and deletion of GSTM1 (null vs. present: OR = 1.26, 95 % CI = 1.13–1.40, P < 0.001). Both the two genetic polymorphisms were independently associated with the risk of lung cancer. The pooled OR of lung cancer for population with both CYP1A1 MspI and GSTM1 mutations (MspI m1/m2 or m2/m2 and GSTM1 null) was 1.62 (95 % CI 1.27–2.07, P < 0.001) when compared with those without any of the above mutations, which is higher than single genetic polymorphism. In the stratified analysis, significantly higher risks of lung cancer associated with above genetic polymorphisms were found only in Asian population. This meta-analysis suggests that the CYP1A1 MspI and GSTM1 polymorphisms correlate with increased lung cancer susceptibility independently, and that there is an interaction between the two genes. However, the associations vary in different ethnic populations.

Combined effects of CYP1A1 MspI and GSTM1 genetic polymorphisms on risk of lung cancer: an updated meta-analysis

Mitochondrial DNA mutations play crucial roles in the pathogenesis and progression of human malignancies. Therefore, to determine whether maternal background or mitochondrial DNA somatic mutations were essential cofactors in the lung cancer of Chinese patients as well, the complete mitochondrial DNA displacement loop of the primary cancerous, matched para-cancerous normal and distant normal tissues for 79 Chinese patients with lung cancer were analyzed in this study. Our results indicated that the higher detected frequency of haplogroups prevalent in southern East Asia (53.16%; 42/79) versus those of northern East Asia in the studied population supported the southern East Asian characteristics of the Chinese lung cancer group. Further statistical analysis revealed that the haplogroups F* and G* contributed to the susceptibility to lung cancer in Chinese patients. In addition, by comparing sequences from different tissues of the same patients, a total of eight somatic mutations from six patients were detected. Combined with the fourteen somatic mutations identified in our previous study, the somatic mutation spectrum of the 79 Chinese patients with lung cancer was 25.32% (20/79). Our results suggest that mitochondrial DNA haplogroups and somatic mutations are associated with lung cancer in patients from Yunnan, Southwest China, and that somatic mitochondrial DNA mutations in the displacement loop can serve as potential biomarkers for clinical utility.

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Mitochondrial DNA haplogroups and somatic mutations are associated with lung cancer in patients from Southwest China.

The associations between single nucleotide polymorphisms (SNPs) in the displacement loop (D-loop) of mitochondrial DNA (mtDNA) and cancer risk and disease outcome have been extensively analyzed. We investigated the association between age-at-onset and SNPs in the mitochondrial D-loop using a population-based series of non-small cell lung cancer (NSCLC) patients. The D-loop region of mtDNA from NSCLC patients was amplified and sequenced. The age-at-onset curve of NSCLC patients was calculated using the Kaplan-Meier method at each SNP site and values were compared using the log-rank test. The SNP sites of nucleotides 200G/A and 16362T/C were identified to determine their association with age-at-onset of NSCLC using the log-rank test. The nucleotide 207G/A was identified for its association with age-at-onset at a borderline significance level (P = 0.060). We found that genetic polymorphisms in the D-loop were predictive markers for age-at-onset in NSCLC patients. Accordingly, the analysis of genetic polymorphisms in the mitochondrial D-loop can be used to identify NSCLC patient subgroups at high risk of early onset.

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Single nucleotide polymorphisms in the mitochondrial displacement loop and age-at-onset of non-small cell lung cancer.

Osteosarcoma is one of the most common bone malignancies in adolescents, and hereditary factors may influence its susceptibility. We assessed the association between XRCC3 Thr241Met polymorphism and susceptibility to osteosarcoma in a Chinese population. Between May 2012 and May 2014, a total of 136 osteosarcoma patients and 136 healthy control subjects were included in our study. The XRCC3 Thr241Met polymorphism was analyzed using a polymerase chain reaction restriction fragment length polymorphism assay. By multiple logistic regression analysis, individuals carrying the Met/Met genotype of XRCC3 Thr241Met were at significantly increased risk of osteosarcoma when compared with the Thr/Thr (OR = 2.50, 95%CI = 1.13-5.66). The Thr/Met+Met/Met genotype of XRCC3 Thr241Met was furthermore found to be correlated with an elevated increased risk of osteosarcoma when compared with the Thr/Thr genotype (OR = 1.71, 95%CI = 1.03-2.87), and Met/Met genotype of XRCC3 Thr241Met was associated with an increased risk of osteosarcoma compared to the Thr/Thr (OR = 3.50, 95%CI = 1.51-8.79). In conclusion, our study firstly reports that XRCC3 Thr241Met gene polymorphism is associated with an elavated risk of osteosarcoma.

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Association between XRCC3 Thr241Met polymorphism and risk of osteosarcoma in a Chinese population.

Inconsistent results are often found regarding the risk of genetic variants in lung cancer association studies. To alleviate these conflicts, we performed a large-scale meta-analysis to evaluate the effect of variants on lung cancer in East Asian population (Han Chinese, Japanese, and Korean). Forty-three genetic variants with data from at least three independent case-control studies were under investigation of which two variants (rs1800734 in hMLH1, rs2273953-rs1801173 bi-marker in P73) were first meta-analyzed in East Asians. We found that three variants in CYP1A1, GSTM1, and XRCC1 showed consistently significant associations with lung cancer in mixed analysis and stratified analysis, and several variants showed diverse effects interacting with different environmental factors in stratified analysis. Our study presents a comprehensive and systematic analysis of lung cancer association studies in East Asians and confirms the effect of three variants in lung cancer risk. Additionally, result from stratified analysis suggests the importance of inclusion of environmental factors, such as smoking and tumor histology, in the analysis.

Lung cancer risk and genetic variants in East Asians: a meta-analysis.

Energy-optimal DNN model placement in UAV-enabled edge computing networks

The application requirements of object detection models based on deep learning are very extensive. However, high computing power requirements often seriously restrict the application of these models on resource-constrained devices with high energy efficiency requirements. To address this problem, a YOLO model accelerator architecture is proposed based on PYNQ. Based on the FPGA hardware platform, the hardware accelerator is designed by making full use of pipeline, loop unrolling, data reordering and other methods to accelerate the computationally intensive units in the YOLOv2 model such as the convolution and pooling layers. In order to reduce the delay in the data transmission process, the multi-channel transmission architecture combined with the ping-pong buffer is designed, and block-by-block reading strategy is adopted to read the off-chip data. The proposed YOLO model accelerator has been implemented and verified on Xilinx PYNQ-z2 platform. The experimental results show that the system has high detection accuracy and far lower power consumption than CPU and GPU. It can also be deployed on mobile devices to detect the surrounding environment.

Lin Wang

Papers

Lung cancer risk and genetic variants in East Asians: a meta-analysis.

Energy-optimal DNN model placement in UAV-enabled edge computing networks

Design of a YOLO Model Accelerator Based on PYNQ Architecture