Application of CRISPR-cas-based technology for the identification of tuberculosis, drug discovery and vaccine development.

Tuberculosis (TB), which caused by Mycobacterium tuberculosis, is the leading cause of death from a single infectious agent and continues to be a major public health burden for the global community. Despite being the only globally licenced prophylactic vaccine, Bacillus Calmette-Guérin (BCG) has multiple deficiencies, and effective diagnostic and therapeutic options are limited. Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated proteins) is an adaptive immune system that is found in bacteria and has great potential for the development of novel antituberculosis drugs and vaccines. In addition, CRISPR-Cas is currently recognized as a prospective tool for the development of therapies for TB infection with potential diagnostic and therapeutic value, and CRISPR-Cas may become a viable tool for eliminating TB in the future. Herein, we systematically summarize the current applications of CRISPR-Cas-based technology for TB detection and its potential roles in drug discovery and vaccine development.

Bulk and single-cell transcriptome profiling reveal necroptosis-based molecular classification, tumor microenvironment infiltration characterization, and prognosis prediction in colorectal cancer.

BACKGROUND: Necroptosis is a new form of programmed cell death that is associated with cancer initiation, progression, immunity, and chemoresistance. However, the roles of necroptosis-related genes (NRGs) in colorectal cancer (CRC) have not been explored comprehensively. METHODS: In this study, we obtained NRGs and performed consensus molecular subtyping by "ConsensusClusterPlus" to determine necroptosis-related subtypes in CRC bulk transcriptomic data. The ssGSEA and CIBERSORT algorithms were used to evaluate the relative infiltration levels of different cell types in the tumor microenvironment (TME). Single-cell transcriptomic analysis was performed to confirm classification related to NRGs. NRG_score was developed to predict patients' survival outcomes with low-throughput validation in a patients' cohort from Fudan University Shanghai Cancer Center. RESULTS: We identified three distinct necroptosis-related classifications (NRCs) with discrepant clinical outcomes and biological functions. Characterization of TME revealed that there were two stable necroptosis-related phenotypes in CRC: a phenotype characterized by few TME cells infiltration but with EMT/TGF-pathways activation, and another phenotype recognized as immune-excluded. NRG_score for predicting survival outcomes was established and its predictive capability was verified. In addition, we found NRCs and NRG_score could be used for patient or drug selection when considering immunotherapy and chemotherapy. CONCLUSIONS: Based on comprehensive analysis, we revealed the potential roles of NRGs in the TME, and their correlations with clinicopathological parameters and patients' prognosis in CRC. These findings could enhance our understanding of the biological functions of necroptosis, which thus may aid in prognosis prediction, drug selection, and therapeutics development.

Ferroptosis-associated molecular classification characterized by distinct tumor microenvironment profiles in colorectal cancer.

Ferroptosis is a non-apoptotic form of cell death recognized in recent years. Nonetheless, the potential role of ferroptosis-associated genes in immune regulation and tumor microenvironment formation remains unknown. In this study, we characterized the ferroptosis-associated patterns of colorectal cancer through integrative analyses of multiple datasets with transcriptomics, genomics, and single-cell transcriptome profiling. Three distinct ferroptosis-associated clusters (FAC1, FAC2 and FAC3) were identified from 1251 CRC bulk samples, which were associated with different clinical outcomes and biological pathways. The TME characterization revealed that the three patterns were highly consistent with known immune profiles: immune-desert (FAC1), immune-inflamed (FAC2) and immune-excluded (FAC3), respectively. Ferroptosis-associated immune and stromal-activated genes were obtained and characterized by corresponding function in CRC tumorigenesis. Further single-cell analyses identified the ferroptosis-associated immune responding tumor cells and ferroptosis-associated stromal cells infiltration pattern. Based on the Fersig score, which was extracted from the ferroptosis phenotype-related signature, patients with lower Fersig score were characterized by prolonged survival time and effective immune responses. Collectively, we uncovered the ferroptosis-associated patterns associated with TME diversity and immune response phenotype. The Fersig we constructed could be the potential therapeutic target genes to improve the efficacy of patients' immunotherapy. The Fersig scoring scheme could enhance the understanding of TME infiltration associated with ferroptosis and prediction of immunotherapy efficacy.

Comprehensive Transcriptomic Analysis Reveals Prognostic Value of an EMT-Related Gene Signature in Colorectal Cancer.

Lymph node metastasis (LNM) is closely related to the postoperative recurrence of colorectal cancer (CRC), and greatly affects patient survival. Conducting Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA), we found that the epithelial-mesenchymal transition (EMT) signaling pathway is the signaling pathway most relevant to the process of LNM. An EMT-related gene signature was identified from a discovery dataset obtained 489 patients using LIMMA and LASSO Cox methods. Six external independent dataset analyses including a total of 1,045 CRC patients and stratification analysis showed that EMT-related gene signature could sort out those high- and low-risk CRC patients accurately. Functional analysis and loss-of-function exploration in vitro and in vivo indicated that the EMT-related-signature-associated coding genes might play functional roles in the sophisticated regulation of CRC proliferation and metastasis. Prognostic nomograms integrating the EMT-related gene signature and clinicopathological risk factors were constructed for use as numerical prediction tools to assess clinical prognosis and clinical decision-makings. The comprehensive transcriptomic analysis in this article highlights the prognostic value of an EMT-related gene signature for postoperative disease recurrence in CRC patients and reveals a potential prognostic and therapeutic biomarker for CRC.

Hematopoietic Gene Expression Regulation Through m6A Methylation Predicts Prognosis in Stage III Colorectal Cancer.

BACKGROUND: Methylation of N6 adenosine (m6A) plays important regulatory roles in diverse biological processes. The purpose of this research was to explore the potential mechanism of m6A modification level on the clinical outcome of stage III colorectal cancer (CRC). METHODS: Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were adopted to reveal the signal pathway which was most likely affected by m6A methylation. The linear models for microarray data (LIMMA) method and the least absolute shrink-age and selection operator (LASSO) Cox regression model were used to identify the signature. The signature can sensitively separate the patients into high and low risk indicating the relapse-free survival (RFS) time based on time-dependent receiver operating characteristic (ROC) analysis. Then, the multi-gene signature was validated in GSE14333 and the Cancer Genome Atlas (TCGA) cohort. The number of the samples in GSE14333 and TCGA cohort are 63 and 150. Finally, two nomograms were set up and validated to predict prognosis of patients with stage III CRC. RESULTS: The hematopoietic cell lineage (HCL) signaling pathway was disclosed through GSEA and GSVA. Seven HCL-related genes were determined in the LASSO model to construct signature, with AUC 0.663, 0.708, and 0.703 at 1-, 3-, and 5-year RFS, respectively. Independent datasets analysis and stratification analysis indicated that the HCL-related signature was reliable in distinguishing high- and low-risk stage III CRC patients. Two nomograms incorporating the signature and pathological N stage were set up, which yielded good discrimination and calibration in the predictions of prognosis for stage III CRC patients. CONCLUSIONS: A novel HCL-related signature was developed as a predictive model for survival rate of stage III CRC patients. Nomograms based on the signature were advantageous to facilitate personalized counseling and treatment in stage III CRC.