Comprehensive analysis of gene mutations and mismatch repair in Chinese colorectal cancer patients

BACKGROUND RAS,BRAF,and mismatch repair(MMR)/microsatellite instability(MSI)are crucial biomarkers recommended by clinical practice guidelines for colorectal cancer(CRC).However,their characteristics and influencing factors in Chinese patients have not been thoroughly described.AIM To analyze the clinicopathological features of KRAS,NRAS,BRAF,and PIK3CA mutations and the DNA MMR status in CRC.METHODS We enrolled 2271 Chinese CRC patients at the China-Japan Friendship Hospital.MMR proteins were tested using immunohistochemical analysis,and the KRAS/NRAS/BRAF/PIK3CA mutations were determined using quantitative polymerase chain reaction.Microsatellite status was determined using an MSI detection kit.Statistical analyses were conducted using SPSS software and logistic regression.RESULTS The KRAS,NRAS,BRAF,and PIK3CA mutations were detected in 44.6%,3.4%,3.7%,and 3.9% of CRC patients,respectively.KRAS mutations were more likely to occur in patients with moderate-to-high differentiation.BRAF mutations were more likely to occur in patients with right-sided CRC,poorly differentiated,or no perineural invasion.Deficient MMR(dMMR)was detected in 7.9% of all patients and 16.8% of those with mucinous adenocarcinomas.KRAS,NRAS,BRAF,and PIK3CA mutations were detected in 29.6%,1.1%,8.1%,and 22.3% of patients with dMMR,respectively.The dMMR was more likely to occur in patients with a family history of CRC,aged<50 years,right-sided CRC,poorly differentiated histology,no perineural invasion,and with carcinoma in situ,stage I,or stage II tumors.CONCLUSION This study analyzed the molecular profiles of KRAS,NRAS,BRAF,PIK3CA,and MMR/MSI in CRC,identifying key influencing factors,with implications for clinical management of CRC.

Revealing the roles of TLR7, a nucleic acid sensor for COVID-19 in pan-cancer

Recent studies suggested that cancer was a risk factor for coronavirus disease 2019 (COVID-19). Toll-like receptor 7 (TLR7), a severe acute respiratory syndrome 2 (SARS-CoV-2) virus’’s nucleic acid sensor, was discovered to be aberrantly expressed in many types of cancers. However, its expression pattern across cancers and association with COVID-19 has not been systematically studied. In this study, we proposed a computational framework to comprehensively study the roles of TLR7 in COVID-19 and pan-cancers at genetic, gene expression, protein, epigenetic, and single-cell levels. We found TLR7 mRNA expression was significantly up-regulated in 6 cancer types and down-regulated in 6 cancer types, further validated in the HPA database at the protein level. The genes significantly co-expressed with TLR7 were mainly enriched in the toll-like receptor signaling pathway, endolysosome, and signaling pattern recognition receptor activity. In addition, the abnormal TLR7 expression was associated with Mismatch repair (MMR), microsatellite instability (MSI), tumor mutational burden (TMB) in various cancers. Mined by the ESTIMATE algorithm, the expression of TLR7 was also closely linked to various immune infiltration patterns in pan-cancer, and TLR7 was mainly enriched in macrophages, as revealed by single-cell RNA sequencing. Finally, TLR7 expressions were very sensitive to a few targeted drugs, such as Alectinib and Imiquimod. In conclusion, TLR7 might be essential in the pathogenesis of COVID-19 and cancers.

Genomic variation,origin tracing,and vaccine development of SARS-CoV-2:A systematic review

COVID-19 has spread globally to over 200 countries with more than 40 million confirmed cases and one million deaths as of November 1,2020.The SARS-CoV-2 virus,leading to COVID-19,shows extremely high rates of infectivity and replication,and can result in pneumonia,acute respiratory distress,or even mortality.SARS-CoV-2 has been found to continue to rapidly evolve,with several genomic variants emerging in different regions throughout the world.In addition,despite intensive study of the spike protein,its origin,and molecular mechanisms in mediating host invasion are still only partially resolved.Finally,the repertoire of drugs for COVID-19 treatment is still limited,with several candidates still under clinical trial and no effective therapeutic yet reported.Although vaccines based on either DNA/mRNA or protein have been deployed,their efficacy against emerging variants requires ongoing study,with multivalent vaccines supplanting the first-generation vaccines due to their low efficacy against new strains.Here,we provide a systematic review of studies on the epidemiology,immunological pathogenesis,molecular mechanisms,and structural biology,as well as approaches for drug or vaccine development for SARSCoV-2.

Molecular cloning and functional characterization of multiple ApOSCs from Andrographis paniculata

Triterpenoids have been described in Andrographis paniculata. Oleanolic acid exhibits high biological activity and is widely used in the clinic, and β-sitosterol not only has good biological activity but also plays an important physiological role in plants.However, analysis of the biosynthetic pathway of triterpenoids in Andrographis paniculata has not been reported. Here, we provide the first report of the isolation and identification of nine 2, 3-oxidosqualene cyclases(ApOSC3 to ApOSC11) from A. paniculata. The results showed that ApOSC4 represented a monofunctional synthase that could convert 2, 3-oxidosqualene to β-amyrin. ApOSC5 as a bifunctional 2, 3-oxidosqualene cyclases, could transfer 2, 3-oxidosqualene to β-amyrin and α-amyrin. ApOSC6 to ApOSC8 composed the multifunctional 2, 3-oxidosqualene cyclases that could convert 2, 3-oxidosqualene to β-amyrin, α-amyrin and one or two undetermined triterpenoids. This study provides a better understanding of the biosynthetic pathway of triterpenoids in A. paniculata, and the discovery of multifunctional 2, 3-oxidosqualene cyclases ApOSC5 to ApOSC8 of the facilitates knowledge of the compounds diversity in A. paniculata.

Single-cell technologies:From research to application

In recent years,more and more single-cell technologies have been developed.A vast amount of single-cell omics data has been generated by large projects,such as the Human Cell Atlas,the Mouse Cell Atlas,the Mouse RNA Atlas,the Mouse ATAC Atlas,and the Plant Cell Atlas.Based on these single-cell big data,thousands of bioinformatics algorithms for quality control,clustering,cell-type annotation,developmental inference,cell-cell transition,cell-cell interaction,and spatial analysis are developed.With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence,the molecular landscape at the single-cell level can be revealed.