Cancer Driver Research Articles

Drivers of breast cancer and cervical cancer screening among women of reproductive age: insights from the Ghana Demographic and Health Survey

BackgroundThe two major causes of cancer-related deaths among women in Ghana are breast cancer (BC) and cervical cancer (CC). These types of cancers typically do not show any symptoms until they have progressed. Therefore, it is important to screen for early detection. This research aimed to investigate the rate of breast cancer and cervical cancer screening, as well as the factors associated with it, among women of reproductive age in Ghana.MethodsThis study analysed data from the 2022 Ghana Demographic and Health Survey. A total of 15,014 women aged 15 to 49 years were included in the analysis. Descriptive statistics and binary logistic regression were employed to analyse the data with the aid of STATA/SE, version 17.ResultsIt was found that 18.4% and 5.0% of the women had screened for BC and CC, respectively. Women aged 45–49 years were about three times more likely (aOR = 2.83, 95% CI: 1.88–4.24) to screen for BC compared to those aged 15–19 years. Women who had tested for HIV had increased odds (aOR = 1.88, 95% CI: 1.56–2.25) of screening for BC compared to their counterparts. Women within the richest wealth index (aOR = 1.95, 95% CI: 1.40–2.72) had increased odds of screening for BC compared to those in the poorest wealth index. Regarding CC screening, women with higher education (aOR = 2.56, 95% CI: 1.53–4.29) were two times more likely to screen for CC compared to those with no formal education. Women who did not use tobacco (aOR = 0.45, 95% CI: 0.21–0.96) had decreased odds of CC screening compared to their counterparts.ConclusionsThis study showed that the uptake of BC and CC screening services among women in Ghana was very low. The drivers of BC and CC screening included enabling, predisposing, and need factors. Stakeholders can leverage the mass media to raise awareness and educate women in reproductive age about the importance of BC and CC screening. This study provides relevant information that can inform BC and CC policies and programmes in Ghana.

Bioinformatics tools and resources for cancer and application.

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Development of in vitro and in vivo c-Met targeted dual-modal nanoprobes for NIR II fluorescent bioimaging and magnetic resonance imaging of breast carcinoma metastasis

Because of the conventional bioimaging methods, including ultrasound and X-ray examinations often lack accuracy and sensitivity in the early diagnosis, as a heterogeneous subtype of breast cancer, it remains an urgent need to develop efficaciously and sensitively diagnostic drivers of triple negative breast cancer (TNBC). The overexpression of c-mesenchymal epithelial transition-factor (c-Met) is associated with the basal subtype of breast carcinoma and linked with decreased survival rate of TNBC patients. Here, we have synthesized a dual-modal nanoprobe with luminescence imaging in the bio-window of near infrared II region (NIR II, 1000–1700) and magnetic resonance imaging (MRI) performances. After c-Met targeting binding protein decoration, this Fe3O4@mSiO2-ICG/cMBP had outstanding size stability and preeminent biocompatibility. Meaningfully, it presented effective TNBC cells recognition in vitro. Besides, after caudal-vein injection of this nanoprobe, both NIR II luminescence imaging and MRI demonstrated that it can more efficiently concentrated in metastatic TNBC tumors in comparison with Fe3O4@mSiO2-ICG and clinical used Gd-DTPA. Meanwhile, the core–shell nanoprobes also showed negligible toxicity in vivo. All results suggested that our cMBP modified nanocomposite could provide a fascinating and efficient non-invasive diagnostic tool for TNBC detection in clinic.

Transcription factor DDIT3 is a potential driver in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and aggressive tumor that affects the digestive tract, leading to high mortality and poor survival rates. The purpose of the present study was to evaluate the expression levels of DNA damage-inducible transcript 3 (DDIT3) in pancreatic cancer and to investigate its effects in in vitro and in vivo experiments. Bioinformatics analysis indicated that DDIT3 expression was higher in pancreatic cancer tumor tissues and associated with a poor prognosis. Positive or strong positive DDIT3 expression was observed in PDAC, and no or weak expression was observed in normal pancreatic tissues. It was also highly expressed in PDAC cells, while being expressed at lower levels in normal pancreatic ductal epithelial cells. Transfection of short hairpin RNA targeting the DDIT3 gene reduced the proliferation, migration and invasion of PANC-1 cells. In vivo, in an in situ implantation tumor model with Pan02 cells, the size and weight of the tumors were reduced in the DDIT3 knockdown Pan02 cell-implanted group. These data suggested that DDIT3 represents a novel predictive biomarker for the potential treatment of patients presenting with PDAC.

USP11 promotes prostate cancer progression by up-regulating AR and c-Myc activity

Androgen receptor (AR) is a main driver for castration-resistant prostate cancer (CRPC). c-Myc is an oncogene underlying prostate tumorigenesis. Here, we find that the deubiquitinase USP11 targets both AR and c-Myc in prostate cancer (PCa). USP11 expression was up-regulated in metastatic PCa and CRPC. USP11 knockdown (KD) significantly inhibited PCa cell growth. Our RNA-seq studies revealed AR and c-Myc as the top transcription factors altered after USP11 KD. ChIP-seq analysis showed that either USP11 KD or replacement of endogenous USP11 with a catalytic-inactive USP11 mutant significantly decreased chromatin binding by AR and c-Myc. We find that USP11 employs two mechanisms to up-regulate AR and c-Myc levels: namely, deubiquitination of AR and c-Myc proteins to increase their stability and deubiquitination of H2A-K119Ub, a repressive histone mark, on promoters of AR and c-Myc genes to increase their transcription. AR and c-Myc reexpression in USP11-KD PCa cells partly rescued cell growth defects. Thus, our studies reveal a tumor-promoting role for USP11 in aggressive PCa through upregulation of AR and c-Myc activities and support USP11 as a potential target against PCa.

Unveiling hidden connections in omics data via pyPARAGON: an integrative hybrid approach for disease network construction.

Network inference or reconstruction algorithms play an integral role in successfully analyzing and identifying causal relationships between omics hits for detecting dysregulated and altered signaling components in various contexts, encompassing disease states and drug perturbations. However, accurate representation of signaling networks and identification of context-specific interactions within sparse omics datasets in complex interactomes pose significant challenges in integrative approaches. To address these challenges, we present pyPARAGON (PAgeRAnk-flux on Graphlet-guided network for multi-Omic data integratioN), a novel tool that combines network propagation with graphlets. pyPARAGON enhances accuracy and minimizes the inclusion of nonspecific interactions in signaling networks by utilizing network rather than relying on pairwise connections among proteins. Through comprehensive evaluations on benchmark signaling pathways, we demonstrate that pyPARAGON outperforms state-of-the-art approaches in node propagation and edge inference. Furthermore, pyPARAGON exhibits promising performance in discovering cancer driver networks. Notably, we demonstrate its utility in network-based stratification of patient tumors by integrating phosphoproteomic data from 105 breast cancer tumors with the interactome and demonstrating tumor-specific signaling pathways. Overall, pyPARAGON is a novel tool for analyzing and integrating multi-omic data in the context of signaling networks. pyPARAGON is available at https://github.com/netlab-ku/pyPARAGON.

Real-Time Measurement of a Weak Interaction of a Transcription Factor Motif with a Protein Hub at Single-Molecule Precision.

Transcription factors often interact with other protein cofactors, regulating gene expression. Direct detection of these brief events using existing technologies remains challenging due to their transient nature. In addition, intrinsically disordered domains, intranuclear location, and lack of cofactor-dependent active sites of transcription factors further complicate the quantitative analysis of these critical processes. Here, we create a genetically encoded label-free sensor to identify the interaction between a motif of the MYC transcription factor, a primary cancer driver, and WDR5, a chromatin-associated protein hub. Using an engineered nanopore equipped with this motif, WDR5 is probed through reversible captures and releases in a one-by-one and time-resolved fashion. Our single-molecule kinetic measurements indicate a weak-affinity interaction arising from a relatively slow complex association and a fast dissociation of WDR5 from the tethered motif. Further, we validate this subtle interaction by determinations in an ensemble using single nanodisc-wrapped nanopores immobilized on a biolayer interferometry sensor. This study also provides the proof-of-concept for a sensor that reveals unique recognition signatures of different protein binding sites. Our foundational work may be further developed to produce sensing elements for analytical proteomics and cancer nanomedicine.

PARP4 interacts with hnRNPM to regulate splicing during lung cancer progression

BackgroundThe identification of cancer driver genes from sequencing data has been crucial in deepening our understanding of tumor biology and expanding targeted therapy options. However, apart from the most commonly altered genes, the mechanisms underlying the contribution of other mutations to cancer acquisition remain understudied. Leveraging on our whole-exome sequencing of the largest Asian lung adenocarcinoma (LUAD) cohort (n = 302), we now functionally assess the mechanistic role of a novel driver, PARP4.MethodsIn vitro and in vivo tumorigenicity assays were used to study the functional effects of PARP4 loss and mutation in multiple lung cancer cell lines. Interactomics analysis by quantitative mass spectrometry was conducted to identify PARP4’s interaction partners. Transcriptomic data from cell lines and patient tumors were used to investigate splicing alterations.ResultsPARP4 depletion or mutation (I1039T) promotes the tumorigenicity of KRAS- or EGFR-driven lung cancer cells. Disruption of the vault complex, with which PARP4 is commonly associated, did not alter tumorigenicity, indicating that PARP4’s tumor suppressive activity is mediated independently. The splicing regulator hnRNPM is a potentially novel PARP4 interaction partner, the loss of which likewise promotes tumor formation. hnRNPM loss results in splicing perturbations, with a propensity for dysregulated intronic splicing that was similarly observed in PARP4 knockdown cells and in LUAD cohort patients with PARP4 copy number loss.ConclusionsPARP4 is a novel modulator of lung adenocarcinoma, where its tumor suppressive activity is mediated not through the vault complex—unlike conventionally thought, but in association with its novel interaction partner hnRNPM, thus suggesting a role for splicing dysregulation in LUAD tumorigenesis.

Discovery of the Natural Bibenzyl Compound Erianin in Dendrobium Inhibiting the Growth and EMT of Gastric Cancer through Downregulating the LKB1-SIK2/3-PARD3 Pathway.

Erianin, a bibenzyl compound found in dendrobium extract, has demonstrated broad anticancer activity. However, its mechanism of action in gastric cancer (GC) remains poorly understood. LKB1 is a tumor-suppressor gene, and its mutation is an important driver of various cancers. Yet some studies have reported contradictory findings. In this study, we combined bioinformatics and in vitro and in vivo experiments to investigate the effect and potential mechanism of Erianin in the treatment of GC. The results show that LKB1 was highly expressed in patients' tumor tissues and GC cells, and it was associated with poor patient prognosis. Erianin could promote GC cell apoptosis and inhibit the scratch repair, migration, invasion, and epithelial-mesenchymal transition (EMT) characteristics. Erianin dose-dependently inhibited the expression of LKB1, SIK2, SIK3, and PARD3 but had no significant effect on SIK1. Erianin also inhibited tumor growth in CDX mice model. Unexpectedly, 5-FU also exhibited a certain inhibitory effect on LKB1. The combination of Erianin and 5-FU significantly improved the anti-tumor efficacy of 5-FU in the growth of GC cells and xenograft mouse models. In summary, Erianin is a potential anti-GC compound that can inhibit GC growth and EMT properties by targeting the LKB1-SIK2/3-PARD3-signaling axis. The synergistic effect of Erianin and 5-FU suggests a promising therapeutic strategy for GC treatment.

Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations

Cancer driver genes can undergo positive selection for various types of genetic alterations, including gain-of-function or loss-of-function mutations and copy number alterations (CNA). We investigated the landscape of different types of alterations affecting driver genes in 17,644 cancer exomes and genomes. We find that oncogenes may simultaneously exhibit signatures of positive selection and also negative selection in different gene segments, suggesting a method to identify additional tumor types where an oncogene is a driver or a vulnerability. Next, we characterize the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Similarly, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed regardless of the type of CNA and may signal new therapeutic opportunities. An analysis with focus on the somatic CNA two-hit events can help identify additional driver genes relevant to a tumor type. By a global inference of point mutation and CNA selection signatures and interactions thereof across genes and tissues, we identify 9 evolutionary archetypes of driver genes, representing different mechanisms of (in)activation by genetic alterations.

Hotspot Exon 15 Mutations in BRAF Are Uncommon in Feline Tumours.

BRAF is one of multiple RAF proteins responsible for the activation of the MAPK cell signalling cascade involved in cell growth, differentiation, and survival. A hotspot BRAFV600E mutation, in exon 15, was determined to be a driver in 100% hairy cell leukaemias, 50%-60% of human melanomas, 30%-50% of human thyroid carcinomas and 10%-20% of human colorectal carcinomas. The orthologous BRAFV595E mutation was seen in 67% and 80% of canine bladder transitional cell carcinomas and prostatic adenocarcinomas, respectively. Since veterinary and human cancers exploit similar pathways and BRAF is highly conserved across species, BRAF can be expected to be a driver in a feline cancer. Primers were developed to amplify exon 15 of feline BRAF. One hundred ninety-six feline tumours were analysed. Sanger sequencing of the 211 bp PCR amplicon was done. A BRAF mutation was found in one tumour, a cutaneous melanoma. The mutation was a BRAFV597E mutation, orthologous to the canine and human hotspot mutations. A common synonymous variant, BRAFT586T, was seen in 23% (47/196) of tumours. This variant was suspected to be a single nucleotide polymorphism. BRAF was not frequently mutated in common feline tumours or in tumour types that frequently harbour BRAF mutations in human and canine cancers. As is seen in canine cancer genomics, the mutational profile in feline tumours may not parallel the histologic equivalent in human oncology.

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

BackgroundThe genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.ResultsWe studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.ConclusionWe show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

Targeting Hyperactive Ras Signaling in Pediatric Cancer.

Somatic RAS mutations are among the most frequent drivers in pediatric and adult cancers. Somatic KRAS, NRAS, and HRAS mutations exhibit distinct tissue-specific predilections. Germline NF1 and RAS mutations in children with neurofibromatosis type 1 and other RASopathy developmental disorders have provided new insights into Ras biology. In many cases, these germline mutations are associated with increased cancer risk. Promising targeted therapeutic strategies for pediatric cancers and neoplasms with NF1 or RAS mutations include inhibition of downstream Ras effector pathways, directly inhibiting the signal output of oncogenic Ras proteins and associated pathway members, and therapeutically targeting Ras posttranslational modifications and intracellular trafficking. Acquired drug resistance to targeted drugs remains a significant challenge but, increasingly, rational drug combination approaches have shown promise in overcoming resistance. Developing predictive preclinical models of childhood cancers for drug testing is a high priority for the field of pediatric oncology.

Pathogenesis of Endometriosis and Endometriosis-Associated Cancers.

Endometriosis is a hormone-dependent, chronic inflammatory condition that affects 5-10% of reproductive-aged women. It is a complex disorder characterized by the growth of endometrial-like tissue outside the uterus, which can cause chronic pelvic pain and infertility. Despite its prevalence, the underlying molecular mechanisms of this disease remain poorly understood. Current treatment options are limited and focus mainly on suppressing lesion activity rather than eliminating it entirely. Although endometriosis is generally considered a benign condition, substantial evidence suggests that it increases the risk of developing specific subtypes of ovarian cancer. The discovery of cancer driver mutations in endometriotic lesions indicates that endometriosis may share molecular pathways with cancer. Moreover, the application of single-cell and spatial genomics, along with the development of organoid models, has started to illuminate the molecular mechanisms underlying disease etiology. This review aims to summarize the key genetic mutations and alterations that drive the development and progression of endometriosis to malignancy. We also review the significant recent advances in the understanding of the molecular basis of the disorder, as well as novel approaches and in vitro models that offer new avenues for improving our understanding of disease pathology and for developing new targeted therapies.

A Classical Epithelial State Drives Acute Resistance to KRAS Inhibition in Pancreatic Cancer.

Intratumoral heterogeneity in pancreatic ductal adenocarcinoma (PDAC) is characterized by a balance between basal and classical epithelial cancer cell states, with basal dominance associating with chemoresistance and a dismal prognosis. Targeting oncogenic KRAS, the primary driver of pancreatic cancer, shows early promise in clinical trials, but efficacy is limited by acquired resistance. Using genetically engineered mouse models and patient-derived xenografts, we find that basal PDAC cells are highly sensitive to KRAS inhibitors. Employing fluorescent and bioluminescent reporter systems, we longitudinally track cell-state dynamics in vivo and reveal a rapid, KRAS inhibitor-induced enrichment of the classical state. Lineage tracing uncovers that these enriched classical PDAC cells are a reservoir for disease relapse. Genetic or chemotherapy-mediated ablation of the classical cell state is synergistic with KRAS inhibition, providing a preclinical proof of concept for this therapeutic strategy. Our findings motivate combining classical state-directed therapies with KRAS inhibitors to deepen responses and counteract resistance in pancreatic cancer. Significance: KRAS inhibitors hold promise in pancreatic cancer, but responses are limited by acquired resistance. We find that a classical epithelial cancer cell state is acutely resistant to KRAS inhibition and serves as a reservoir for disease relapse. Targeting the classical state alongside KRAS inhibition deepens responses, revealing a potent therapeutic strategy. See related commentary by Marasco and Misale, p. 2018.

Casein Kinase 1α-A Target for Prostate Cancer Therapy?

The androgen receptor (AR) is a key driver of prostate cancer (PCa) and, as such, current mainstay treatments target this molecule. However, resistance commonly arises to these therapies and, therefore, additional targets must be evaluated to improve patient outcomes. Consequently, alternative approaches for indirectly targeting the AR are sought. AR crosstalk with other signalling pathways, including several protein kinase signalling cascades, has been identified as a potential route to combat therapy resistance. The casein kinase 1 (CK1) family of protein kinases phosphorylate a multitude of substrates, allowing them to regulate a diverse range of pathways from the cell cycle to DNA damage repair. As well as its role in several signalling pathways that are de-regulated in PCa, mutational data suggest its potential to promote prostate carcinogenesis. CK1α is one isoform predicted to regulate AR activity via phosphorylation and has been implicated in the progression of several other cancer types. In this review, we explore how the normal biological function of CK1 is de-regulated in cancer, the impact on signalling pathways and how this contributes towards prostate tumourigenesis, with a particular focus on the CK1α isoform as a novel therapeutic target for PCa.

Identification of a cancer driver gene-associated lncRNA signature for prognostic prediction and immune response evaluation in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) predominates among kidney cancer cases and is influenced by mutations in cancer driver genes (CDGs). However, significant obstacles persist in the early diagnosis and treatment of ccRCC. While various genetic models offer new hopes for improving ccRCC management, the relationship between CDG-related long non-coding RNAs (CDG-RlncRNAs) and ccRCC remains poorly understood. Therefore, this study aims to construct prognostic molecular features based on CDG-RlncRNAs to predict the prognosis of ccRCC patients, and aims to provide a new strategy to enhance clinical management of ccRCC patients. This study employed Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses to comprehensively investigate the association between lncRNAs and CDGs in ccRCC. Leveraging The Cancer Genome Atlas (TCGA) dataset, we identified 97 prognostically significant CDG-RlncRNAs and developed a robust prognostic model based on these CDG-RlncRNAs. The performance of the model was rigorously validated using the TCGA dataset for training and the International Cancer Genome Consortium (ICGC) dataset for validation. Functional enrichment analysis elucidated the biological relevance of CDG-RlncRNA features in the model, particularly in tumor immunity. Experimental validation further confirmed the functional role of representative CDG-RlncRNA SNHG3 in ccRCC progression. Our analysis revealed that 97 CDG-RlncRNAs are significantly associated with ccRCC prognosis, enabling patient stratification into different risk groups. Development of a prognostic model incorporating key lncRNAs such as HOXA11-AS, AP002807.1, APCDD1L-DT, AC124067.2, and SNHG3 demonstrated robust predictive accuracy in both training and validation datasets. Importantly, risk stratification based on the model revealed distinct immune-related gene expression patterns. Notably, SNHG3 emerged as a key regulator of the ccRCC cell cycle, highlighting its potential as a therapeutic target. Our study established a concise CDG-RlncRNA signature and underscored the pivotal role of SNHG3 in ccRCC progression. It emphasizes the clinical relevance of CDG-RlncRNAs in prognostic prediction and targeted therapy, offering potential avenues for personalized intervention in ccRCC.

Discovery of novel indazole derivatives as second-generation TRK inhibitors

NTRK gene fusion leads to the activation of downstream signaling pathways, which is a oncogenic driver in various cancers. NTRK fusion-positive cancers can be treated with the first-generation TRK inhibitors, larotrectinib and entrectinib. Unfortunately, the patients eventually face the dilemma of no drugs available as the emergence of certain resistance mutations. The development of efficient and broad-spectrum second-generation TRK inhibitors is still of great significance. Here, we analyzed the binding modes of compounds 6, 10 with TRKA protein, respectively, a series of novel indazole TRK inhibitors were designed and synthesized using molecular hybridization strategy. Among them, the optimal compound B31 showed strong antiproliferative activities against Km-12, Ba/F3-TRKAG595R, and Ba/F3-TRKAG667C cell lines with IC50 values of 0.3, 4.7, and 9.9 nM, respectively. And the inhibitory effect against TRKAG667C (IC50 = 9.9 nM) was better than that of selitrectinib (IC50 = 113.1 nM). Further, compound B31 exhibited moderate kinase selectivity and excellent plasma stability (t1/2 > 480 min). In vivo pharmacokinetic studies in Sprague-Dawley rats showed that B31 had acceptable pharmacokinetic properties.

Oncogenic Roles of UHRF1 in Cancer.

Ubiquitin-like with PHD and RING finger domains 1 (UHRF1) is an essential protein involved in the maintenance of repressive epigenetic marks, ensuring epigenetic stability and fidelity. As an epigenetic regulator, UHRF1 comprises several functional domains (UBL, TTD, PHD, SRA, RING) that are collectively responsible for processes like DNA methylation, histone modification, and DNA repair. UHRF1 is a downstream effector of the RB/E2F pathway, which is nearly universally deregulated in cancer. Under physiological conditions, UHRF1 protein levels are cell cycle-dependent and are post-translationally regulated by proteasomal degradation. Conversely, UHRF1 is overexpressed and serves as an oncogenic driver in multiple cancers. This review focuses on the functional domains of UHRF1, highlighting its key interacting proteins and oncogenic roles in solid tumors including retinoblastoma, osteosarcoma, lung cancer, and breast cancer. Additionally, current therapeutic strategies targeting UHRF1 domains or its interactors are explored, providing an insight on potential clinical applications.

Multi-Network Graph Contrastive Learning for Cancer Driver Gene Identification

Multi-Network Graph Contrastive Learning for Cancer Driver Gene Identification