TP53 Polymorphisms and Colorectal Cancer Risk in Patients with Lynch Syndrome in Taiwan: A Retrospective Cohort Study

Research progress on the biological basis of Traditional Chinese Medicine syndromes of gastrointestinal cancers

Gastrointestinal cancers account for 11.6 % of all cancers, and are the second most frequently diagnosed type of cancer worldwide. Traditional Chinese medicine (TCM), together with Western medicine or alone, has unique advantages for the prevention and treatment of cancers, including gastrointestinal cancers. Syndrome differentiation and treatment are basic characteristics of the theoretical system of TCM. TCM syndromes are the result of the differentiation of the syndrome and the basis of treatment. Genomics, transcriptomics, proteomics, metabolomics, intestinal microbiota, and serology, generated around the central law, are used to study the biological basis of TCM syndromes in gastrointestinal cancers. This review summarizes current research on the biological basis of TCM syndrome in gastrointestinal cancers and provides useful references for future research on TCM syndrome in gastrointestinal cancers.

Genetic analysis of colorectal carcinoma using high throughput single nucleotide polymorphism genotyping technique within the population of Jammu and Kashmir

BACKGROUND

SNP genotyping has become increasingly more common place to understand the genetic basis of complex diseases like cancer. SNP-genotyping through MassARRAY™ is a cost-effective method to quantitatively analyse the variation of gene expression in multiple samples, making it a potential tool to identify the underlying causes of colorectal carcinogenesis.

METHODS

In the present study, SNP genotyping was carried out using Agena MassARRAY™, which is a cost-effective, robust, and sensitive method to analyse multiple SNPs simultaneously. We analysed 7 genes in 492 samples (100 cases and 392 controls) associated with CRC within the population of Jammu and Kashmir. These SNPs were selected based on their association with multiple cancers in literature.

RESULTS

This is the first study to explore these SNPs with colorectal cancer within the J&K population.7 SNPs with a call rate of 90% were selected for the study. Out of these, five SNPs rs2234593, rs1799966, rs2229080, rs8034191, rs1042522 were found to be significantly associated with the current study under the allelic model with an Odds Ratio OR = 2.981(1.731-5.136 at 95% CI); p value = 4.81E-05 for rs2234593,OR = 1.685(1.073-2.647 at 95% CI);; p value = 0.02292 for rs1799966, OR = 1.5 (1.1-2.3 at 95% CI), p value = 0.02 for rs2229080, OR = 1.699(1.035-2.791 at 95% CI); p value = 0.03521 for rs8034191, OR = 20.07 (11.26-35.75); p value = 1.84E-34 for rs1042522 respectively.

CONCLUSION

This is the first study to find the relation of Genetic variants with the colorectal cancer within the studied population using high throughput MassARRAY™ technology. It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

AptaNet as a deep learning approach for aptamer-protein interaction prediction

Aptamers are short oligonucleotides (DNA/RNA) or peptide molecules that can selectively bind to their specific targets with high specificity and affinity. As a powerful new class of amino acid ligands, aptamers have high potentials in biosensing, therapeutic, and diagnostic fields. Here, we present AptaNet-a new deep neural network-to predict the aptamer-protein interaction pairs by integrating features derived from both aptamers and the target proteins. Aptamers were encoded by using two different strategies, including k-mer and reverse complement k-mer frequency. Amino acid composition (AAC) and pseudo amino acid composition (PseAAC) were applied to represent target information using 24 physicochemical and conformational properties of the proteins. To handle the imbalance problem in the data, we applied a neighborhood cleaning algorithm. The predictor was constructed based on a deep neural network, and optimal features were selected using the random forest algorithm. As a result, 99.79% accuracy was achieved for the training dataset, and 91.38% accuracy was obtained for the testing dataset. AptaNet achieved high performance on our constructed aptamer-protein benchmark dataset. The results indicate that AptaNet can help identify novel aptamer-protein interacting pairs and build more-efficient insights into the relationship between aptamers and proteins. Our benchmark dataset and the source codes for AptaNet are available in: https://github.com/nedaemami/AptaNet .

Five P53 SNPs Involved in Low Rectal Cancer Risk and Prognosis in a Chinese Population

Although the impact and potential mechanisms of p53 polymorphisms on human malignancies have been intensively studied, analyses for association between p53 polymorphisms and colorectal cancer (CRC) risk were still limited to some common variants. Moreover, the majority of previous studies did not classify the specimens of CRC based on tumor location. This case-control study aimed to evaluate the association of five p53 polymorphisms (rs1042522, rs12947788, rs1625895, rs2909430 and rs12951053) with the risk of low rectal cancer (LRC) and investigate the prognostic significance. A total of 347 cases and 353 controls from a Chinese population were recruited and genotyped using KASP assay. Individuals carrying the variant rs12947788 A allele were observed to associate with an increased risk of LRC. After stratification for clinicopathological parameters, rs12947788 was significantly co-related with the histological type of LRC under a dominant model. Although none of the selected p53 polymorphisms was significantly associated with patient prognosis in total population, significant associations with the overall survival were revealed in the heterozygosis carriers vs. wild type carriers model through subgroup analyses based on clinical characteristics. Moreover, haplotype analyses showed that C-A-G-A-A haplotype was associated with a significantly higher LRC risk as compared to the other haplotypes. In low rectal cancer, P53 protein expression was obviously higher in p53 rs1042522 mutant carriers than in other genotypes. Our study further proves the involvement of p53 polymorphisms in pathogenesis of LRC and may provide potential therapeutic implications.

Association of mRNA expression of TP53 and the TP53 codon 72 Arg/Pro gene polymorphism with colorectal cancer risk in Asian population: a bioinformatics analysis and meta-analysis

Background

The relationship between TP53 codon 72 Pro/Arg gene polymorphism and colorectal cancer risk in Asians is still controversial, and this bioinformatics analysis and meta-analysis was performed to assess the associations.

Methods

The association studies were identified from PubMed, and eligible reports were included. RevMan 5.3.1 software, Oncolnc, cBioPortal, and Oncomine online tools were used for statistical analysis. A random/fixed effects model was used in meta-analysis. The data were reported as risk ratios or mean differences with corresponding 95% CI.

Results

We confirmed that TP53 was associated with colorectal cancer, the alteration frequency of TP53 was 53% mutation and 7% deep deletion, and TP53 mRNA expression was different in different types of colorectal cancer based on The Cancer Genome Atlas database. Then, 18 studies were included that examine the association of TP53 codon 72 gene polymorphism with colorectal cancer risk in Asians. The meta-analysis indicated that TP53 Pro allele and Pro/Pro genotype were associated with colorectal cancer risk in Asian population, but Arg/Arg genotype was not (Pro allele: odds ratios [OR]=1.20, 95% CI: 1.06 to 1.35, P=0.003; Pro/Pro genotype: OR=1.39, 95% CI: 1.15 to 1.69, P=0.0007; Arg/Arg genotype: OR=0.86, 95% CI: 0.74 to 1.00, P=0.05). Interestingly, in the meta-analysis of the controls from the population-based studies, we found that TP53 codon 72 Pro/Arg gene polymorphism was associated with colorectal cancer risk (Pro allele: OR=1.33, 95% CI: 1.15 to 1.55, P=0.0002; Pro/Pro genotype: OR=1.61, 95% CI: 1.28 to 2.02, P<0.0001; Arg/Arg genotype: OR=0.77, 95% CI: 0.63 to 0.93, P=0.009).

Conclusion

TP53 was associated with colorectal cancer, but the different value levels of mRNA expression were not associated with survival rate of colon and rectal cancer. TP53 Pro allele and Pro/Pro genotype were associated with colorectal cancer risk in Asians.

Polymorphisms of DNA repair genes are associated with colorectal cancer in patients with Lynch syndrome

BACKGROUND

DNA repair genes are crucial for maintaining genomic stability by preventing mutagenesis and carcinogenesis. The present retrospective cohort study aimed at investigating whether MLH1, APEX1, MUTYH, OGG1, NUDT1, XRCC5, XPA, and ERCC2 single nucleotide polymorphisms (SNPs) are associated with colorectal cancer (CRC) in Chinese population with Lynch syndrome.

METHODS

From Amsterdam criteria family registry, we identified 270 patients with Lynch syndrome. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between DNA repair SNPs and CRC were calculated using a weighted Cox proportional hazard regression model.

RESULTS

Heterozygous variants of rs1799832 in NUDT1 (HR = 2.97, 95% CI = 1.51-5.83) and rs13181 in ERCC2 (HR = 2.69, 95% CI = 1.10-6.55) were significantly associated with an increased risk of CRC compared with wild-type homozygous CC and TT genotypes, respectively. However, the variant CG+GG genotype of MUTYH rs3219489 was associated with a decreased risk of CRC (HR = 0.49, 95% CI = 0.26-0.91) compared with the homozygous CC wild-type counterparts.

CONCLUSION

Our findings revealed that polymorphisms of DNA repair genes that include NUDT1, ERCC2, and MUTYH are associated with CRC in patients with Lynch syndrome in Chinese population. Further studies with large sample size are needed to confirm our findings.