Targeting DNA binding proteins for cancer therapy

Dissecting microenvironment in cystadenomas and hepatic cysts based on single nucleus RNA-sequencing data

Hepatic cystadenoma is a rare disease, accounting for about 5% of all cystic lesions, with a high tendency of malignant transformation. The preoperative diagnosis of cystadenoma is difficult, and some cystadenomas are easily misdiagnosed as hepatic cysts at first. Hepatic cyst is a relatively common liver disease, most of which are benign, but large hepatic cysts can lead to pressure on the bile duct, resulting in abnormal liver function. To better understand the difference between the microenvironment of cystadenomas and hepatic cysts, we performed single-nuclei RNA-sequencing on cystadenoma and hepatic cysts samples. In addition, we performed spatial transcriptome sequencing of hepatic cysts. Based on nucleus RNA-sequencing data, a total of seven major cell types were identified. Here we described the tumor microenvironment of cystadenomas and hepatic cysts, particularly the transcriptome signatures and regulators of immune cells and stromal cells. By inferring copy number variation, it was found that the malignant degree of hepatic stellate cells in cystadenoma was higher. Pseudotime trajectory analysis demonstrated dynamic transformation of hepatocytes in hepatic cysts and cystadenomas. Cystadenomas had higher immune infiltration than hepatic cysts, and T cells had a more complex regulatory mechanism in cystadenomas than hepatic cysts. Immunohistochemistry confirms a cystadenoma-specific T-cell immunoregulatory mechanism. These results provided a single-cell atlas of cystadenomas and hepatic cyst, revealed a more complex microenvironment in cystadenomas than in hepatic cysts, and provided new perspective for the molecular mechanisms of cystadenomas and hepatic cyst.

Role of Natural Binding Proteins in Therapy and Diagnostics

This review systematically investigates the critical role of natural binding proteins (NBPs), encompassing DNA-, RNA-, carbohydrate-, fatty acid-, and chitin-binding proteins, in the realms of oncology and diagnostics. In an era where cancer continues to pose significant challenges to healthcare systems worldwide, the innovative exploration of NBPs offers a promising frontier for advancing both the diagnostic accuracy and therapeutic efficacy of cancer management strategies. This manuscript provides an in-depth examination of the unique mechanisms by which NBPs interact with specific molecular targets, highlighting their potential to revolutionize cancer diagnostics and therapy. Furthermore, it discusses the burgeoning research on aptamers, demonstrating their utility as 'nucleic acid antibodies' for targeted therapy and precision diagnostics. Despite the promising applications of NBPs and aptamers in enhancing early cancer detection and developing personalized treatment protocols, this review identifies a critical knowledge gap: the need for comprehensive studies to understand the diverse functionalities and therapeutic potentials of NBPs across different cancer types and diagnostic scenarios. By bridging this gap, this manuscript underscores the importance of NBPs and aptamers in paving the way for next-generation diagnostics and targeted cancer treatments.

Discovering DNA shape motifs with multiple DNA shape features: generalization, methods, and validation

DNA motifs are crucial patterns in gene regulation. DNA-binding proteins (DBPs), including transcription factors, can bind to specific DNA motifs to regulate gene expression and other cellular activities. Past studies suggest that DNA shape features could be subtly involved in DNA-DBP interactions. Therefore, the shape motif annotations based on intrinsic DNA topology can deepen the understanding of DNA-DBP binding. Nevertheless, high-throughput tools for DNA shape motif discovery that incorporate multiple features altogether remain insufficient. To address it, we propose a series of methods to discover non-redundant DNA shape motifs with the generalization to multiple motifs in multiple shape features. Specifically, an existing Gibbs sampling method is generalized to multiple DNA motif discovery with multiple shape features. Meanwhile, an expectation-maximization (EM) method and a hybrid method coupling EM with Gibbs sampling are proposed and developed with promising performance, convergence capability, and efficiency. The discovered DNA shape motif instances reveal insights into low-signal ChIP-seq peak summits, complementing the existing sequence motif discovery works. Additionally, our modelling captures the potential interplays across multiple DNA shape features. We provide a valuable platform of tools for DNA shape motif discovery. An R package is built for open accessibility and long-lasting impact: https://zenodo.org/doi/10.5281/zenodo.10558980.

ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein-DNA Interaction Hotspots

Protein-DNA interactions are pivotal to various cellular processes. Precise identification of the hotspot residues for protein-DNA interactions holds great significance for revealing the intricate mechanisms in protein-DNA recognition and for providing essential guidance for protein engineering. Aiming at protein-DNA interaction hotspots, this work introduces an effective prediction method, ESPDHot based on a stacked ensemble machine learning framework. Here, the interface residue whose mutation leads to a binding free energy change (ΔΔG) exceeding 2 kcal/mol is defined as a hotspot. To tackle the imbalanced data set issue, the adaptive synthetic sampling (ADASYN), an oversampling technique, is adopted to synthetically generate new minority samples, thereby rectifying data imbalance. As for molecular characteristics, besides traditional features, we introduce three new characteristic types including residue interface preference proposed by us, residue fluctuation dynamics characteristics, and coevolutionary features. Combining the Boruta method with our previously developed Random Grouping strategy, we obtained an optimal set of features. Finally, a stacking classifier is constructed to output prediction results, which integrates three classical predictors, Support Vector Machine (SVM), XGBoost, and Artificial Neural Network (ANN) as the first layer, and Logistic Regression (LR) algorithm as the second one. Notably, ESPDHot outperforms the current state-of-the-art predictors, achieving superior performance on the independent test data set, with F1, MCC, and AUC reaching 0.571, 0.516, and 0.870, respectively.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

MTA2 is one of 14 Transcription factors predicting recurrence free survival in gastric cancer and promotes cancer progression by targeting MCM5

Gastric cancer (GC) is a leading cause of cancer-related death worldwide. Transcription factors (TFs) are essential gene expression regulators, and play critical roles in cancer development. However, the biological actions and prognostic value of TFs in GC remain unclear. In this study, we identified a risk model based on a 14-TF signature to predict recurrence-free survival in patients with GC. We further analyzed the ability of 14-TF to predict recurrence-free survival time in GC and found that a higher expression level of metastasis-associated protein 2 (MTA2) was associated with shorter overall survival and disease-free survival time in GC. Through in vitro and in vivo experiments, we demonstrated that MTA2 significantly promotes GC growth and metastasis. Furthermore, we identified MTA2 binding to the promoter of minichromosome maintenance deficient 5 (MCM5), thereby promoting GC progression. Overall, these findings strongly support the prognostic potential of the 14-TFs signature and suggest that targeting MTA2 may be a promising strategy to treat GC.

Inside the stemness engine: Mechanistic links between deregulated transcription factors and stemness in cancer

Cell identity is largely determined by its transcriptional profile. In tumour, deregulation of transcription factor expression and/or activity enables cancer cell to acquire a stem-like state characterised by capacity to self-renew, differentiate and form tumours in vivo. These stem-like cancer cells are highly metastatic and therapy resistant, thus warranting a more complete understanding of the molecular mechanisms downstream of the transcription factors that mediate the establishment of stemness state. Here, we review recent research findings that provide a mechanistic link between the commonly deregulated transcription factors and stemness in cancer. In particular, we describe the role of master transcription factors (SOX, OCT4, NANOG, KLF, BRACHYURY, SALL, HOX, FOX and RUNX), signalling-regulated transcription factors (SMAD, β-catenin, YAP, TAZ, AP-1, NOTCH, STAT, GLI, ETS and NF-κB) and unclassified transcription factors (c-MYC, HIF, EMT transcription factors and P53) across diverse tumour types, thereby yielding a comprehensive overview identifying shared downstream targets, highlighting unique mechanisms and discussing complexities.

The expression and methylation of PITX genes is associated with the prognosis of head and neck squamous cell carcinoma

Background: The PITX gene family, comprising PITX1, PITX2, and PITX3, is critical in organogenesis and has been evolutionary conserved in animals. PITX genes are associated with the advanced progression and poor prognosis of multiple cancers. However, the relationship between the PITX genes and head and neck squamous cell carcinoma (HNSC) has not been reported.

Methods: We used data from The Cancer Genome Atlas (TCGA) to analyze the association between PITX mRNA expression and clinicopathological parameters of patients with HNSC. The prognostic value of PITX genes was evaluated using the Kaplan-Meier plotter. Multivariate Cox analysis was used to screen out prognosis-associated genes to identify better prognostic indicators. The potential roles of PITX1 and PITX2 in HNSC prognosis were investigated using the protein-protein interaction (PPI) network, Gene Ontology (GO) analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The correlation between PITX1 and PITX2 expression or methylation and immune cell infiltration was evaluated using the tumor-immune system interaction database (TISIDB). MethSurv was used to identify DNA methylation and its effect on HNSC prognosis.

Results:PITX genes expression was correlated with different cancers. PITX1 and PITX2 expression was lower in the patients with HNSC. In HNSC, PITX1 expression was significantly related to the clinical stage, histologic grade, and N stage, while PITX2 expression was only significantly related to the histologic grade. The high expression of PITX3 was significantly related to the histologic grade, T stage, and N stage. Survival analysis revealed that PITX genes had prognostic value in HNSC, which was supported by multivariate Cox analysis. PPI network and enrichment analysis showed that the genes interacting with PITX1 and PITX2 belonged predominantly to signaling pathways associated with DNA binding and transcription. Of the CpG DNA methylation sites in PITX1 and PITX2, 28 and 22 were related to the prognosis of HNSC, respectively. Additionally, PITX1 and PITX2 expression and methylation was associated with tumor-infiltrating lymphocytes (TILs).

Conclusion: The PITX genes were differentially expressed in patients with HNSC, highlighting their essential role in DNA methylation and tumor-infiltrating immune cell regulation, as well as overall prognostic value in HNSC.

DNA- and RNA-Binding Proteins Linked Transcriptional Control and Alternative Splicing Together in a Two-Layer Regulatory Network System of Chronic Myeloid Leukemia

DNA- and RNA-binding proteins (DRBPs) typically possess multiple functions to bind both DNA and RNA and regulate gene expression from more than one level. They are controllers for post-transcriptional processes, such as splicing, polyadenylation, transportation, translation, and degradation of RNA transcripts in eukaryotic organisms, as well as regulators on the transcriptional level. Although DRBPs are reported to play critical roles in various developmental processes and diseases, it is still unclear how they work with DNAs and RNAs simultaneously and regulate genes at the transcriptional and post-transcriptional levels. To investigate the functional mechanism of DRBPs, we collected data from a variety of databases and literature and identified 118 DRBPs, which function as both transcription factors (TFs) and splicing factors (SFs), thus called DRBP-SF. Extensive investigations were conducted on four DRBP-SFs that were highly expressed in chronic myeloid leukemia (CML), heterogeneous nuclear ribonucleoprotein K (HNRNPK), heterogeneous nuclear ribonucleoprotein L (HNRNPL), non-POU domain–containing octamer–binding protein (NONO), and TAR DNA-binding protein 43 (TARDBP). By integrating and analyzing ChIP-seq, CLIP-seq, RNA-seq, and shRNA-seq data in K562 using binding and expression target analysis and Statistical Utility for RBP Functions, we discovered a two-layer regulatory network system centered on these four DRBP-SFs and proposed three possible regulatory models where DRBP-SFs can connect transcriptional and alternative splicing regulatory networks cooperatively in CML. The exploration of the identified DRBP-SFs provides new ideas for studying DRBP and regulatory networks, holding promise for further mechanistic discoveries of the two-layer gene regulatory system that may play critical roles in the occurrence and development of CML.

Application of next-generation sequencing in the diagnosis of gastric cancer

Objectives: Gastric cancer (GC) is a disease with high mortality, poor prognosis and numerous risk factors. GC has an asymptomatic nature in early stages of the diseases, making timely diagnosis complicated using common conventional approaches, namely pathological examinations and imaging tests. Recently, molecular profiling of GC using next generation sequencing (NGS) has opened new doors to efficient prognostic, diagnostic, and therapeutic strategies. The current review aims to thoroughly discuss and compare the current NGS techniques and commercial platforms utilized for GC diagnosis and treatment, highlighting the most recent NGS-based GC studies. Furthermore, this review addresses the challenges of clinical implementation of NGS in GC.Materials and methods: This review was conducted according to the eligible studies identified via search of Web of Science, PubMed, Scopus, Embase and the Cochrane Library. In the present study, data on gastric cancer patients and NGS methods used to diagnose the disease were reviewed.Conclusion: Given the ever-rising advancements in NGS technologies, bioinformatics, healthcare guidelines and refined classifications, it is hoped that these technologies can actualize their advantages and optimize GC patients' experience.

Environmentally sensitive fluorescent nucleoside analogues as probes for nucleic acid - protein interactions: molecular design and biosensing applications

Fluorescent nucleoside analogues (FNAs) are indispensable in studying the interactions of nucleic acids with nucleic acid-binding proteins. By replacing one of the poorly emissive natural nucleosides, FNAs enable real-time optical monitoring of the binding interactions in solutions, under physiologically relevant conditions, with high sensitivity. Besides that, FNAs are widely used to probe conformational dynamics of biomolecular complexes using time-resolved fluorescence methods. Because of that, FNAs are tools of high utility for fundamental biological research, with potential applications in molecular diagnostics and drug discovery. Here I review the structural and physical factors that can be used for the conversion of the molecular binding events into a detectable fluorescence output. Typical environmentally sensitive FNAs, their properties and applications, and future challenges in the field are discussed.

Determination of WWOX Function in Modulating Cellular Pathways Activated by AP-2α and AP-2γ Transcription Factors in Bladder Cancer

Following the invention of high-throughput sequencing, cancer research focused on investigating disease-related alterations, often inadvertently omitting tumor heterogeneity. This research was intended to limit the impact of heterogeneity on conclusions related to WWOX/AP-2α/AP-2γ in bladder cancer which differently influenced carcinogenesis. The study examined the signaling pathways regulated by WWOX-dependent AP-2 targets in cell lines as biological replicates using high-throughput sequencing. RT-112, HT-1376 and CAL-29 cell lines were subjected to two stable lentiviral transductions. Following CAGE-seq and differential expression analysis, the most important genes were identified and functionally annotated. Western blot was performed to validate the selected observations. The role of genes in biological processes was assessed and networks were visualized. Ultimately, principal component analysis was performed. The studied genes were found to be implicated in MAPK, Wnt, Ras, PI3K-Akt or Rap1 signaling. Data from pathways were collected, explaining the differences/similarities between phenotypes. FGFR3, STAT6, EFNA1, GSK3B, PIK3CB and SOS1 were successfully validated at the protein level. Afterwards, a definitive network was built using 173 genes. Principal component analysis revealed that the various expression of these genes explains the phenotypes. In conclusion, the current study certified that the signaling pathways regulated by WWOX and AP-2α have more in common than that regulated by AP-2γ. This is because WWOX acts as an EMT inhibitor, AP-2γ as an EMT enhancer while AP-2α as a MET inducer. Therefore, the relevance of AP-2γ in targeted therapy is now more evident. Some of the differently regulated genes can find application in bladder cancer treatment.

Prognostic significance of AP-2α/γ targets as cancer therapeutics

Identifying genes with prognostic importance could improve cancer treatment. An increasing number of reports suggest the existence of successful strategies based on seemingly "untargetable" transcription factors. In addition to embryogenesis, AP-2 transcription factors are known to play crucial roles in cancer development. Members of this family can be used as prognostic factors in oncological patients, and AP-2α/γ transcription factors were previously investigated in our pan-cancer comparative study using their target genes. The present study investigates tumors that were previously found similar with an emphasis on the possible role of AP-2 factors in specific cancer types. The RData workspace was loaded back to R environment and 3D trajectories were built via Monocle3. The genes that met the requirement of specificity were listed using top_markers(), separately for mutual and unique targets. Furthermore, the candidate genes had to meet the following requirements: correlation with AP-2 factor (through Correlation AnalyzeR) and validated prognostic importance (using GEPIA2 and subsequently KM-plotter or LOGpc). Eventually, the ROC analysis was applied to confirm their predictive value; co-dependence of expression was visualized via BoxPlotR. Some similar tumors were differentiated by AP-2α/γ targets with prognostic value. Requirements were met by only fifteen genes (EMX2, COL7A1, GRIA1, KRT1, KRT14, SLC12A5, SEZ6L, PTPRN, SCG5, DPP6, NTSR1, ARX, COL4A3, PPEF1 and TMEM59L); of these, the last four were excluded based on ROC curves. All the above genes were confronted with the literature, with an emphasis on the possible role played by AP-2 factors in specific cancers. Following ROC analysis, the genes were verified using immunohistochemistry data and progression-related signatures. Staining differences were observed, as well as co-dependence on the expression of e.g. CTNNB1, ERBB2, KRAS, SMAD4, EGFR or MKI67. In conclusion, prognostic value of targets suggested AP-2α/γ as candidates for novel cancer treatment. It was also revealed that AP-2 targets are related to tumor progression and that some mutual target genes could be inversely regulated.

A New Amino Acid for Improving Permeability and Solubility in Macrocyclic Peptides through Side Chain-to-Backbone Hydrogen Bonding

Despite the notoriously poor membrane permeability of peptides, many cyclic peptide natural products show high passive membrane permeability and potently inhibit a variety of "undruggable" intracellular targets. A major impediment to the design of cyclic peptides with good permeability is the high desolvation energy associated with the peptide backbone amide NH groups. While several strategies have been proposed to mitigate this deleterious effect, only few studies have used polar side chains to sequester backbone NH groups. We investigated the ability of N,N-pyrrolidinylglutamine (Pye), whose side chain contains a powerful hydrogen-bond-accepting C═O amide group but no hydrogen-bond donors, to sequester exposed backbone NH groups in a series of cyclic hexapeptide diastereomers. Analyses revealed that specific Leu-to-Pye substitutions conferred dramatic improvements in aqueous solubility and permeability in a scaffold- and position-dependent manner. Therefore, this approach offers a complementary tool for improving membrane permeability and solubility in cyclic peptides.

MicroRNAs and Corresponding Targets in Esophageal Cancer as Shown In Vitro and In Vivo in Preclinical Models

Squamous cell carcinoma of the esophagus is associated with a dismal prognosis. Therefore, identification of new targets and implementation of new treatment modalities are issues of paramount importance. Based on a survey of the literature, we identified microRNAs conferring antitumoral activity in preclinical in vivo experiments. In the category of miRs targeting secreted factors and transmembrane receptors, four miRs were up-regulated and 10 were down-regulated compared with five out of nine in the category transcription factors, and six miRs were down-regulated in the category enzymes, including metabolic enzymes. The down-regulated miRs have targets which can be inhibited by small molecules or antibody-related entities, or re-expressed by reconstitution therapy. Up-regulated miRs have targets which can be reconstituted with small molecules or inhibited with antagomirs.

Immobilized Titanium (IV) Ion Affinity Chromatography Contributes to Efficient Proteomics Analysis of Cellular Nucleic Acid-Binding Proteins

Cellular nucleic acid-binding proteins (NABPs), namely, DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs), play important roles in many biological processes. However, extracting NABPs with high efficiency in living cells is challenging, which greatly limited their proteomics analysis and comprehensive characterization. Here, we discovered that titanium (IV) ion-immobilized metal affinity chromatography (Ti⁴⁺-IMAC) material could enrich DNA and RNA with high efficiency (96.82 ± 2.67 and 85.75 ± 2.99%, respectively). We therefore developed a Ti⁴⁺-IMAC method for the joint extraction of DBPs and RBPs. Through utilizing formaldehyde (FA) cross-linking, DBPs and RBPs were covalently linked to nucleic acids (NAs) and further denatured by organic solvents. After Ti⁴⁺-IMAC capture, 2000 proteins were identified in 293T cells, among which 417 DBPs and 999 RBPs were revealed, showing promising selectivity for NABPs. We further applied the Ti⁴⁺-IMAC capture method to lung cancer cell lines 95C and 95D, which have different tumor progression abilities. The DNA- and RNA-binding capabilities of many proteins have been dysregulated in 95D. Under our conditions, Ti⁴⁺-IMAC can be used as a selective and powerful tool for the comprehensive characterization of both DBPs and RBPs, which might be utilized to study their dynamic interactions with nucleic acids.

AML1/ETO and its function as a regulator of gene transcription via epigenetic mechanisms

The chromosomal translocation t(8;21) and the resulting oncofusion gene AML1/ETO have long served as a prototypical genetic lesion to model and understand leukemogenesis. In this review, we describe the wide-ranging role of AML1/ETO in AML leukemogenesis, with a particular focus on the aberrant epigenetic regulation of gene transcription driven by this AML-defining mutation. We begin by analyzing how structural changes secondary to distinct genomic breakpoints and splice changes, as well as posttranscriptional modifications, influence AML1/ETO protein function. Next, we characterize how AML1/ETO recruits chromatin-modifying enzymes to target genes and how the oncofusion protein alters chromatin marks, transcription factor binding, and gene expression. We explore the specific impact of these global changes in the epigenetic network facilitated by the AML1/ETO oncofusion on cellular processes and leukemic growth. Furthermore, we define the genetic landscape of AML1/ETO-positive AML, presenting the current literature concerning the incidence of cooperating mutations in genes such as KIT, FLT3, and NRAS. Finally, we outline how alterations in transcriptional regulation patterns create potential vulnerabilities that may be exploited by epigenetically active agents and other therapeutics.

Transcription Factors: The Fulcrum Between Cell Development and Carcinogenesis

Higher eukaryotic development is a complex and tightly regulated process, whereby transcription factors (TFs) play a key role in controlling the gene regulatory networks. Dysregulation of these regulatory networks has also been associated with carcinogenesis. Transcription factors are key enablers of cancer stemness, which support the maintenance and function of cancer stem cells that are believed to act as seeds for cancer initiation, progression and metastasis, and treatment resistance. One key area of research is to understand how these factors interact and collaborate to define cellular fate during embryogenesis as well as during tumor development. This review focuses on understanding the role of TFs in cell development and cancer. The molecular mechanisms of cell fate decision are of key importance in efforts towards developing better protocols for directed differentiation of cells in research and medicine. We also discuss the dysregulation of TFs and their role in cancer progression and metastasis, exploring TF networks as direct or indirect targets for therapeutic intervention, as well as specific TFs’ potential as biomarkers for predicting and monitoring treatment responses.

Transcription Factors BARX1 and DLX4 Contribute to Progression of Clear Cell Renal Cell Carcinoma via Promoting Proliferation and Epithelial-Mesenchymal Transition

Dysregulation of transcription factors contributes to the carcinogenesis and progression of cancers. However, their roles in clear cell renal cell carcinoma remain largely unknown. This study aimed to evaluate the clinical significance of TFs and investigate their potential molecular mechanisms in ccRCC. Data were accessed from the cancer genome atlas kidney clear cell carcinoma cohort. Bioinformatics algorithm was used in copy number alterations mutations, and differentially expressed TFs’ analysis. Univariate and multivariate Cox regression analyses were performed to identify clinically significant TFs and construct a six-TF prognostic panel. TFs’ expression was validated in human tissues. Gene set enrichment analysis (GSEA) was utilized to find enriched cancer hallmark pathways. Functional experiments were conducted to verify the cancer-promoting effect of BARX homeobox 1 (BARX1) and distal-less homeobox 4 (DLX4) in ccRCC, and Western blot was performed to explore their downstream pathways. As for results, many CNAs and mutations were identified in transcription factor genes. TFs were differentially expressed in ccRCC. An applicable predictive panel of six-TF genes was constructed to predict the overall survival for ccRCC patients, and its diagnostic efficiency was evaluated by the area under the curve (AUC). BARX1 and DLX4 were associated with poor prognosis, and they could promote the proliferation and migration of ccRCC. In conclusion, the six-TF panel can be used as a prognostic biomarker for ccRCC patients. BARX1 and DLX4 play oncogenic roles in ccRCC via promoting proliferation and epithelial–mesenchymal transition. They have the potential to be novel therapeutic targets for ccRCC.

Targeting DNA binding proteins for cancer therapy

Dysregulation or mutation of DNA binding proteins such as transcription factors (TFs) is associated with the onset and progression of various types of disease, including cancer. Alteration of TF activity occurs in numerous cancer tissues due to gene amplification, deletion, and point mutations, and epigenetic modification. Although cancer‐associated TFs are promising targets for cancer therapy, development of drugs targeting these TFs has historically been difficult due to the lack of high‐throughput screening methods. Recent advances in technology for identification and selective inhibition of DNA binding proteins enable cancer researchers to develop novel therapeutics targeting cancer‐associated TFs. In the present review, we summarize known cancer‐associated TFs according to cancer type and introduce recently developed high‐throughput approaches to identify selective inhibitors of cancer‐associated TFs.