A zinc finger protein gene signature enables bladder cancer treatment stratification

An innovative prognostic auxiliary for colon adenocarcinoma based on zinc finger protein genes

Background

The carcinogenesis and progression of colon adenocarcinoma (COAD) are intensively related to the abnormal expression of the zinc finger (ZNF) protein genes. We aimed to employ these genes to provide a reliable prognosis and treatment stratification tool for COAD patients.

Methods

Cox and the least absolute shrinkage and selection operator (LASSO) regression analysis were applied, utilizing The Cancer Genome Atlas (TCGA) metadata, to build a ZNF protein gene-based prognostic model. Using this model, patients in the training cohort and testing cohort (GSE17537) were labelled as either high or low risk. Kaplan-Meier (KM) survival analysis and time-dependent receiver operating characteristic (ROC) curve analysis were performed in the patients with opposite risk status to assess the predictive ability in each cohort. The potentiality of the mechanism was explored by the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE), single-sample gene set enrichment analysis (ssGSEA), gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, the degrees of expression of model genes were validated by immunohistochemistry (IHC).

Results

The prognostic model consisting of INSM1, PHF21B, RNF138, SYTL4, WRNIP1, ZNF585B, and ZNF514, classified patients into opposite risk statuses. Patients in the high-risk subset had a considerably lower chance of surviving compared to those in the low-risk subset. There is a high probability that these model genes were attached to immune-related biological processes, which can be confirmed by the results of the above mechanistic methods. Moreover, patients in the low-risk subset also significantly outperformed the patients in the high-risk subset when calculating immune cells and function scores. Drug sensitivity and tumor immune dysfunction and exclusion (TIDE) analyses showed a clear difference in the immunological and chemotherapeutic efficacy predictions within the two risk groups. Additionally, the degrees of expression of model genes in high-risk and low-risk subsets presented great discrepancies.

Conclusions

The signature may be applied as a predictive classifier to shepherd special medication for COAD patients.

Implications of ZNF334 gene in lymph node metastasis of lung SCC: potential bypassing of cellular senescence

BACKGROUND

The primary goal of this work is to identify biomarkers associated with lung squamous cell carcinoma and assess their potential for early detection of lymph node metastasis.

METHODS

This study investigated gene expression in lymph node metastasis of lung squamous cell carcinoma using data from the Cancer Genome Atlas and R software. Protein-protein interaction networks, hub genes, and enriched pathways were analyzed. ZNF334 and TINAGL1, two less explored genes, were further examined through in vitro, ex vivo, and in vivo experiments to validate the findings from bioinformatics analyses. The role of ZNF334 and TINAGL1 in senescence induction was assessed after H2O2 and UV induced senescence phenotype determined using β-galactosidase activity and cell cycle status assay.

RESULTS

We identified a total of 611 up- and 339 down-regulated lung squamous cell carcinoma lymph node metastasis-associated genes (FDR < 0.05). Pathway enrichment analysis highlighted the central respiratory pathway within mitochondria for the subnet genes and the nuclear DNA-directed RNA polymerases for the hub genes. Significantly down regulation of ZNF334 gene was associated with malignancy lymph node progression and senescence induction has significantly altered ZNF334 expression (with consistency in bioinformatics, in vitro, ex vivo, and in vivo results). Deregulation of TINAGL1 expression with inconsistency in bioinformatics, in vitro (different types of lung squamous cancer cell lines), ex vivo, and in vivo results, was also associated with malignancy lymph node progression and altered in senescence phenotype.

CONCLUSIONS

ZNF334 is a highly generalizable gene to lymph node metastasis of lung squamous cell carcinoma and its expression alter certainly under senescence conditions.

The role of zinc finger proteins in malignant tumors

Zinc finger proteins (ZNFs) are the largest family of transcriptional factors in mammalian cells. Recently, their role in the development, progression, and metastasis of malignant tumors via regulating gene transcription and translation processes has become evident. Besides, their possible involvement in drug resistance has also been found, indicating that ZNFs have the potential to become new biological markers and therapeutic targets. In this review, we summarize the oncogenic and suppressive roles of various ZNFs in malignant tumors, including lung, breast, liver, gastric, colorectal, pancreatic, and other cancers, highlighting their role as prognostic markers, and hopefully provide new ideas for the treatment of malignant tumors in the future.

A 3-Gene Random Forest Model to Diagnose Non-obstructive Azoospermia Based on Transcription Factor-Related Henes

Non-obstructive azoospermia (NOA) is one of the most severe forms of male infertility, but its diagnosis biomarkers with high sensitivity and specificity are largely unknown. Transcription factors (TFs) play essential roles in many pathological processes in different diseases. Herein, we aimed to identify the TFs showing high diagnosis ability for NOA through machine learning algorithms. The transcriptome data of the testicular tissue from 11 control and 47 NOA subjects were set as the training dataset; meanwhile, 1665 TFs were retrieved from the HumanTFDB. Through the feature extraction methods, including genomic difference analysis, Lasso, Boruta, SVM-RFE, and logistic regression, ETV2, TBX2, and ZNF689 were ultimately screened and then were included in the random forest (RF) diagnosis model. The RF model displayed high predictive power in the training (F-measure = 1) and two external validation (n = 31, F-measure = 0.902; n = 20, F-measure = 0.941) cohorts. The seminal plasma and testicular biopsy samples of 20 control and 20 NOA patients were collected from the local hospital, and the expression levels of ETV2, TBX2, and ZNF689 were measured via RT-qPCR and immunohistochemistry. The RF model could also distinguish the NOA samples in the local cohort (F-measure = 0.741). Single-cell RNA sequencing analysis, which was based on the 432 testicular cell samples from an NOA patient, showed that ETV2, TBX2, and ZNF689 were all significantly associated with spermatogenesis. In all, a 3-TF random forest diagnosis model was successfully established, providing novel insights into the latent mechanisms of NOA.