No abstract

While next-generation sequencing (NGS) has transformed genetic testing, it generates large quantities of noisy data that require a significant amount of bioinformatics to generate useful interpretation. The accuracy of variant calling is therefore critical. Although GATK HaplotypeCaller is a widely used tool for this purpose, newer methods such as DeepVariant have shown higher accuracy in assessments of gold-standard samples for whole-genome sequencing (WGS) and whole-exome sequencing (WES), but a side-by-side comparison on clinical samples has not been performed. Trio WES was used to compare GATK (4.1.2.0) HaplotypeCaller and DeepVariant (v0.8.0). The performance of the two pipelines was evaluated according to the Mendelian error rate, transition-to-transversion (Ti/Tv) ratio, concordance rate, and pathological variant detection rate. Data from 80 trios were analyzed. The Mendelian error rate of the 77 biological trios calculated from the data by DeepVariant (3.09 ± 0.83%) was lower than that calculated from the data by GATK (5.25 ± 0.91%) (p < 0.001). DeepVariant also yielded a higher Ti/Tv ratio (2.38 ± 0.02) than GATK (2.04 ± 0.07) (p < 0.001), suggesting that DeepVariant proportionally called more true positives. The concordance rate between the 2 pipelines was 88.73%. Sixty-three disease-causing variants were detected in the 80 trios. Among them, DeepVariant detected 62 variants, and GATK detected 61 variants. The one variant called by DeepVariant but not GATK HaplotypeCaller might have been missed by GATK HaplotypeCaller due to low coverage. OTC exon 2 (139 bp) deletion was not detected by either method. Mendelian error rate calculation is an effective way to evaluate variant callers. By this method, DeepVariant outperformed GATK, while the two pipelines performed equally in other parameters.

Growing evidence suggests that immune-related genes (IRGs) and long non-coding RNAs (lncRNAs) can serve as prognostic markers of overall survival (OS) in patients with colon cancer. This study aimed to identify an immune-related lncRNA signature for the prospective assessment of prognosis in these patients. Gene expression and clinical data of colon cancer patients were downloaded from The Cancer Genome Atlas (TCGA). Immune-related lncRNAs were identified by a correlation analysis between IRGs and lncRNAs. In total, 447 samples were divided into a training cohort (224 samples) and a testing cohort (223 samples). Univariate, lasso and multivariate Cox regression analyses identified an immune-related nine-lncRNA signature closely related to OS in colon cancer patients in the training dataset. A risk score formula involving nine immunerelated lncRNAs was developed to evaluate the prognostic value of the lncRNA signature in the training dataset. Colon cancer patients with a high risk score had poorer OS than those with a low risk score. A multivariate Cox regression analysis confirmed that the immune-related nine-lncRNA signature could be an independent prognostic factor in colon cancer patients. The results were further confirmed in the testing cohort and the entire TCGA cohort. Furthermore, a gene set enrichment analysis revealed several pathways with significant enrichment in the high-and low-risk groups that may be helpful in formulating clinical strategies and understanding the underlying mechanisms. Finally, a quantitative real-time polymerase chain reaction assay found that the nine lncRNAs were significantly differentially expressed in colon cancer cell lines. The results of this study indicate that this signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in colon cancer patients. These lncRNAs could be potential biomarkers affecting the prognosis of colon cancer.

Fresh-cut fruits and vegetables are the main sources of foodborne illness outbreaks with implicated pathogens such as Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes. This study aimed at investigating the influence of two key parameters (concentration of curcumin and illumination time) on the effects of curcumin-based photodynamic sterilization on the preservation of fresh-cut Hami melons. The results indicated that illumination with 50 μmol/L curcumin for 60 min using a blue LED lamp reduced the total aerobic microorganism count by ~1.8 log CFU/g in fresh-cut Hami melons. Besides this, the effects of photodynamic sterilization on the soluble solids content, color, water content, firmness, and sensory indices of the fresh-cut Hami melons were also evaluated. Compared to the control group, photodynamic sterilization can effectively delay the browning rate and maintain the luminosity, firmness, water content, and soluble solids content of fresh-cut Hami melon. The sensory quality was indeed preserved well after 9 days of storage in a fridge. These results showed that photodynamic sterilization is an effective and promising technology to prolong the shelf life of fresh-cut Hami melons.

Increasing evidence has clarified that the tumor microenvironment (TME) is closely related to the prognosis and therapeutic efficacy of cancer. However, there is no reliable TME evaluation system used to accurately predict the prognosis of and therapeutic efficacy in gastric cancer. We evaluated the immune microenvironment score (IMS) of 1422 gastric cancer samples based on 51 immune cell signatures. We explored the relationship between the IMS and prognosis, immune cell infiltration, cancer subtype, and potential immune escape mechanisms. The results show that activation of the stroma and decreased levels of immune infiltration were associated with a low IMS. A high IMS was characterized by Epstein–Barr virus infection, increased mutation load, microsatellite instability, and immune cell infiltration. A high IMS was also related to high expression of immune checkpoint molecules (PD-1/PD-L1). Finally, patients with a high IMS had a better response to PD-1/PD-L1 inhibitors and may be more suitable for immune checkpoint inhibitors (area under the curve = 0.81). In addition, a low IMS may be converted into the immune-infiltrating subtype after romidepsin treatment. Stratification based on the IMS may enable gastric cancer patients to benefit more from immunotherapy and help identify new cancer treatment strategies.