ANKLE1 as New Hotspot Mutation for Breast Cancer in Indian Population and Has a Role in DNA Damage and Repair in Mammalian Cells

Characterization of a prognostic model for lung squamous cell carcinoma based on eight stemness index-related genes

Background

Cancer stem cells (CSCs) are implicated in cancer progression, chemoresistance, and poor prognosis; thus, they may be promising therapeutic targets. In this study, we aimed to investigate the prognostic application of differentially expressed CSC-related genes in lung squamous cell carcinoma (LUSC).

Methods

The mRNA stemness index (mRNAsi)-related differentially expressed genes (DEGs) in tumors were identified and further categorized by LASSO Cox regression analysis and 1,000-fold cross-validation, followed by the construction of a prognostic score model for risk stratification. The fractions of tumor-infiltrating immune cells and immune checkpoint genes were analyzed in different risk groups.

Results

We found 404 mRNAsi-related DEGs in LUSC, 77 of which were significantly associated with overall survival. An eight-gene prognostic signature (PPP1R27, TLX2, ANKLE1, TIGD3, AMH, KCNK3, FLRT3, and PPBP) was identified and used to construct a risk score model. The TCGA set was dichotomized into two risk groups that differed significantly (p = 0.00057) in terms of overall survival time (1, 3, 5-year AUC = 0.830, 0.749, and 0.749, respectively). The model performed well in two independent GEO datasets (p = 0.029, 0.033; 1-year AUC = 0747, 0.783; 3-year AUC = 0.746, 0.737; 5-year AUC = 0.706, 0.723). Low-risk patients had markedly increased numbers of CD8+ T cells and M1 macrophages and downregulated immune checkpoint genes compared to the corresponding values in high-risk patients (p < 0.05).

Conclusion

A stemness-related prognostic model based on eight prognostic genes in LUSC was developed and validated. The results of this study would have prognostic and therapeutic implications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02011-0.

Collective analysis of the expression and prognosis for LEM-domain proteins in prostate cancer

BACKGROUND

Mammalian LEM-domain proteins (LEMs) are encoded by seven genes, including LAP2, EMD, LEMD1, LEMD2, LEMD3, ANKLE1, and ANKLE2. Though some LEMs were involved in various tumor progression, the expression and prognostic values of LEMs in prostate adenocarcinoma (PRAD) have yet to be analyzed.

METHODS

Herein, we investigated the expression, survival data, and immune infiltration levels of LEMs in PRAD patients from ATCG, TIMER, LinkedOmics, and TISIDB databases. We also further validated the mRNA and protein expression levels of ANKLE1, EMD, and LEMD2 in human prostate tumor specimens by qPCR, WB, and IHC.

RESULTS

We found that all LEM expressions, except for that of LAP2, were markedly altered in PRAD compared to the normal samples. Among all LEMs, only the expressions of ANKLE1, EMD, and LEMD2 were correlated with advanced tumor stage and survival prognosis in PRAD. Consistent with the predicted computational results, the mRNA and protein expression levels of these genes were markedly increased in the PRAD group. We then found that ANKLE1, EMD, and LEMD2 expressions were markedly correlated with immune cell infiltration levels. High ANKLE1, EMD, and LEMD2 expressions predicted a worse prognosis in PRAD based on immune cells. DNA methylation or/and copy number variations may contribute to the abnormal upregulation of ANKLE1, EMD, and LEMD2 in PRAD.

CONCLUSIONS

Taken together, this study implied that ANKLE1, EMD, and LEMD2 were promising prognosis predictors and potential immunotherapy targets for PRAD patients.

Exploration of Reduced Mitochondrial Content–Associated Gene Signature and Immunocyte Infiltration in Colon Adenocarcinoma by an Integrated Bioinformatic Analysis

Purpose: Mitochondrial dysfunction refers to cancer immune evasion. A novel 7-gene prognostic signature related to the mitochondrial DNA copy number was utilized to evaluate the immunocyte infiltration in colon cancer according to the risk scores and to predict the survival for colon cancer.

Experimental design: We performed an integrated bioinformatic analysis to analyze transcriptome profiling of the EB-treated mitochondrial DNA–defected NCM460 cell line with differentially expressed genes between tumor and normal tissues of COAD in TCGA. The LASSO analysis was utilized to establish a prognostic signature. ESTIMATE and CIBERSORT validated the differences of immunocyte infiltration between colon cancer patients with high- and low-risk scores.

Results: Our study identified a 7-gene prognostic signature (LRRN2, ANKLE1, GPRASP1, PRAME, TCF7L1, RAB6B, and CALB2). Patients with colon cancer were split into the high- and low-risk group by the risk scores in TCGA (training cohort: HR = 2.50 p &lt; 0.0001) and GSE39582 (validation cohort: HR = 1.43 p &lt; 0.05). ESTIMATE and CIBERSORT revealed diverseness of immune infiltration in the two groups, especially downregulated T-cell infiltration in the patients with high-risk scores. Finally, we validated the colon patients with a low expression of the mitochondrial number biomarker TFAM had less CD3+ and CD8+ T-cell infiltration in clinical specimens.

Conclusion: An mtDNA copy number-related 7-gene prognostic signature was investigated and evaluated, which may help to predict the prognosis of colon cancer patients and to guide clinical immunotherapy via immunocyte infiltration evaluation.

Comparative Analysis of Transcriptional Responses to Genotoxic and Non-Genotoxic Agents in the Blood Cell Model TK6 and the Liver Model HepaRG

Transcript signatures are a promising approach to identify and classify genotoxic and non-genotoxic compounds and are of interest as biomarkers or for future regulatory application. Not much data, however, is yet available about the concordance of transcriptional responses in different cell types or tissues. Here, we analyzed transcriptomic responses to selected genotoxic food contaminants in the human p53-competent lymphoblastoid cell line TK6 using RNA sequencing. Responses to treatment with five genotoxins, as well as with four non-genotoxic liver toxicants, were compared with previously published gene expression data from the human liver cell model HepaRG. A significant overlap of the transcriptomic changes upon genotoxic stress was detectable in TK6 cells, whereas the comparison with the HepaRG model revealed considerable differences, which was confirmed by bioinformatic data mining for cellular upstream regulators or pathways. Taken together, the study presents a transcriptomic signature for genotoxin exposure in the human TK6 blood cell model. The data demonstrate that responses in different cell models have considerable variations. Detection of a transcriptomic genotoxin signature in blood cells indicates that gene expression analyses of blood samples might be a valuable approach to also estimate responses to toxic exposure in target organs such as the liver.

The Last Chance Saloon

Accurate chromosome segregation requires the removal of all chromatin bridges, which link chromosomes before cell division. When chromatin bridges fail to be removed, cell cycle progression may halt, or cytokinesis failure and ensuing polyploidization may occur. Conversely, the inappropriate severing of chromatin bridges leads to chromosome fragmentation, excessive genome instability at breakpoints, micronucleus formation, and chromothripsis. In this mini-review, we first describe the origins of chromatin bridges, the toxic processing of chromatin bridges by mechanical force, and the TREX1 exonuclease. We then focus on the abscission checkpoint (NoCut) which can confer a transient delay in cytokinesis progression to facilitate bridge resolution. Finally, we describe a recently identified mechanism uncovered in C. elegans where the conserved midbody associated endonuclease LEM-3/ANKLE1 is able to resolve chromatin bridges generated by various perturbations of DNA metabolism at the final stage of cell division. We also discuss how LEM-3 dependent chromatin bridge resolution may be coordinated with abscission checkpoint (NoCut) to achieve an error-free cleavage, therefore acting as a "last chance saloon" to facilitate genome integrity and organismal survival.