Cancer Driver Research Articles

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

DriverDetector: An R package providing multiple statistical methods for cancer driver genes detection and tools for downstream analysis

Identifying driver genes in cancer is a difficult task because of the heterogeneity of cancer as well as the complex interactions among genes. As sequencing data become more readily available, there is a growing need for detecting cancer driver genes based on statistical and mathematical modeling methods. Currently, plenty of driver gene identification algorithms have been published, but they fail to achieve consistent results. In order to obtain gene sets with high confidence, we present DriverDetector, an R package providing a convenient workflow for cancer driver genes detection and downstream analysis. We develop the background mutation rate calculating module based on the distance between genes in covariate space and binomial test, followed by the driver gene selection module which integrates 11 methods, including two already recognized approaches, a de novo method, and five variants of Fisher's method which are applied to driver gene identification for the first time. Through verification on 12 TCGA datasets, each method is able to identify a set of confirmed driver genes while the number of resulting genes vary significantly across different methods. For robust driver genes detection, a voting strategy based on 10 of the statistical methods is further applied. Results show that the collective prediction based on the voting strategy demonstrates superiority in achieving the consistency of prediction while ensuring a reasonable number of predicted genes and confirmed drivers. By comparing the results of each cancer dataset, we also find that sample size has a huge impact on the number of predicted genes. For downstream analysis, DriverDetector automatically generates plenty of plots and tables to elaborate the results. We propose DriverDetector as a user-friendly tool promoting early diagnosis of cancer and the development of targeted drugs.

Drop the MYC: An expansion of triple-negative breast cancer driver genes

Drop the MYC: An expansion of triple-negative breast cancer driver genes

Stabilization of GTSE1 by cyclin D1-CDK4/6 promotes cell proliferation: relevance in cancer prognosis.

Cyclin D1 is the activating subunit of the cell cycle kinases CDK4 and CDK6, and its dysregulation is a well-known oncogenic driver in many human cancers. The biological function of cyclin D1 has been primarily studied by focusing on the phosphorylation of the retinoblastoma (RB) gene product. Here, using an integrative approach combining bioinformatic analyses and biochemical experiments, we show that GTSE1 (G2 and S phases expressed protein 1), a protein positively regulating cell cycle progression, is a previously unknown substrate of cyclin D1-CDK4/6. The phosphorylation of GTSE1 mediated by cyclin D1-CDK4/6 inhibits GTSE1 degradation, leading to high levels of GTSE1 also during the G1 phase of the cell cycle. Functionally, the phosphorylation of GTSE1 promotes cellular proliferation and is associated with poor prognosis within a pan-cancer cohort. Our findings provide insights into cyclin D1's role in cell cycle control and oncogenesis beyond RB phosphorylation.

Genomic alteration discordance in the paired primary-recurrent ovarian cancers: based on the comprehensive genomic profiling (CGP) analysis

PurposeOvarian cancer (OC) is characterized by a high recurrence rate, and homologous recombination deficiency (HRD) is an important biomarker in the clinical management of OC. We investigated the differences in clinical genomic profiles between the primary and platinum-sensitive recurrent OC (PSROC), focusing on HRD status.Materials and methodsA total of 40 formalin-fixed paraffin-embedded (FFPE) tissues of primary tumors and their first platinum-sensitive recurrence from 20 OC patients were collected, and comprehensive genomic profiling (CGP) analysis of FoundationOne®CDx (F1CDx) was applied to explore the genetic (dis)similarities of the primary and recurrent tumors.ResultsBy comparing between paired samples, we found that genomic loss of heterozygosity (gLOH) score had a high intra-patient correlation (r2 = 0.79) and that short variants (including TP53, BRCA1/2 and NOTCH1 mutations), tumor mutational burden (TMB) and microsatellite stability status remained stable. The frequency of (likely) pathological BRCA1/2 mutations was 30% (12/40) in all samples positively correlated with gLOH scores, but the proportion of gLOH-high status (score > 16%) was 50% (10/20) and 55% (11/20) in the primary and recurrent samples, respectively. An additional 20% (4/20) of patients needed attention, a quarter of which carried the pathological BRCA1 mutation but had a gLOH-low status (gLOH < 16%), and three-quarters had different gLOH status in primary-recurrent pairs. Furthermore, we observed the PSROC samples had higher gLOH scores (16.1 ± 9.24 vs. 19.4 ± 11.1, p = 0.007), more CNVs (36.1% vs. 15.1% of discordant genomic alternations), and significant enrichment of altered genes in TGF-beta signaling and Hippo signaling pathways (p < 0.05 for all) than their paired primaries. Lastly, mutational signature and oncodrive gene analyses showed that the computed mutational signature similarity in the primary and recurrent tumors were best matched the COSMI 3 signature (Aetiology of HRD) and had consistent candidate cancer driver genes of MSH2, NOTCH1 and MSH6.ConclusionThe high genetic concordance of the short variants remains stable along OC recurrence. However, the results reveal significantly higher gLOH scores in the recurrent setting than in paired primaries, supporting further clinically instantaneity HRD assay strategy.

Repeat treatment of organotypic airway cultures with ethyl methanesulfonate causes accumulation of somatic cell mutations without expansion of bronchial-carcinoma-specific cancer driver mutations

The human in vitro organotypic air-liquid-interface (ALI) airway tissue model is structurally and functionally similar to the human large airway epithelium and, as a result, is being used increasingly for studying the toxicity of inhaled substances. Our previous research demonstrated that DNA damage and mutagenesis can be detected in human airway tissue models under conditions used to assess general and respiratory toxicity endpoints. Expanding upon our previous proof-of-principle study, human airway epithelial tissue models were treated with 6.25–100 µg/mL ethyl methanesulfonate (EMS) for 28 days, followed by a 28-day recovery period. Mutagenesis was evaluated by Duplex Sequencing (DS), and clonal expansion of bronchial-cancer-specific cancer-driver mutations (CDMs) was investigated by CarcSeq to determine if both mutation-based endpoints can be assessed in the same system. Additionally, DNA damage and tissue-specific responses were analyzed during the treatment and following the recovery period. EMS exposure led to time-dependent increases in mutagenesis over the 28-day treatment period, without expansion of clones containing CDMs; the mutation frequencies remained elevated following the recovery. EMS also produced an increase in DNA damage measured by the CometChip and MultiFlow assays and the elevated levels of DNA damage were reduced (but not eliminated) following the recovery period. Cytotoxicity and most tissue-function changes induced by EMS treatment recovered to control levels, the exception being reduced proliferating cell frequency. Our results indicate that general, respiratory-tissue-specific and genotoxicity endpoints increased with repeat EMS dosing; expansion of CDM clones, however, was not detected using this repeat treatment protocol. DisclaimerThis article reflects the views of its authors and does not necessarily reflect those of the U.S. Food and Drug Administration. Any mention of commercial products is for clarification only and is not intended as approval, endorsement, or recommendation.

HER2 overexpression in urothelial carcinoma with GATA3 and PPARG copy number gains.

HER2, encoded by the ERBB2 gene, is an important druggable driver of human cancer gaining increasing importance as a therapeutic target in urothelial carcinoma (UC). The genomic underpinnings of HER2 overexpression in ERBB2 nonamplified UC are poorly defined. To address this knowledge gap, we investigated 172 UC tumors from patients treated at the University of California San Francisco, using immunohistochemistry and next-generation sequencing. We found that GATA3 and PPARG copy number gains individually predicted HER2 protein expression independently of ERBB2 amplification. To validate these findings, we interrogated the Memorial Sloan Kettering/The Cancer Genome Atlas (MSK/TCGA) dataset and found that GATA3 and PPARG copy number gains individually predicted ERBB2 mRNA expression independently of ERBB2 amplification. Our findings reveal a potential link between the luminal marker HER2 and the key transcription factors GATA3 and PPARG in UC and highlight the utility of examining GATA3 and PPARG copy number states to identify UC tumors that overexpress HER2 in the absence of ERBB2 amplification. In summary, we found that an increase in copy number of GATA3 and PPARG was independently associated with higher ERBB2 expression in patient samples of UC. This finding provides a potential explanation for HER2 overexpression in UC tumors without ERBB2 amplification and a way to identify these tumors for HER2-targeted therapies.

Differences in the molecular organisation of tumours along the colon are linked to interactions within the tumour ecosystem

Tumours exhibit significant heterogeneity in their molecular profiles across patients, largely influenced by the tissue of origin, where certain driver gene mutations are predominantly associated with specific cancer types. Here, we unveil an additional layer of complexity: some cancer types display anatomic location-specific mutation profiles akin to tissue-specificity.To better understand this phenomenon, we concentrate on colon cancer. While prior studies have noted changes of the frequency of molecular alterations along the colon, the underlying reasons and whether those changes occur rather gradual or are distinct between the left and right colon, remain unclear. Developing and leveraging stringent statistical models on molecular data from 522 colorectal tumours from The Cancer Genome Atlas, we reveal disparities in molecular properties between the left and right colon affecting many genes. Interestingly, alterations in genes responsive to environmental cues and properties of the tumour ecosystem, including metabolites which we quantify in a cohort of 27 colorectal cancer patients, exhibit continuous trends along the colon.Employing network methodologies, we uncover close interactions between metabolites and genes, including drivers of colon cancer, showing continuous abundance or alteration profiles. This underscores how anatomic biases in the composition and interactions within the tumour ecosystem help explaining gradients of carcinogenesis along the colon.

Structural insights into the role and targeting of EGFRvIII

The epidermal growth factor receptor (EGFR) is a well-known oncogenic driver in lung and other cancers. In glioblastoma multiforme (GBM), the EGFR deletion variant III (EGFRvIII) is frequently found alongside EGFR amplification. Agents targeting the EGFR axis have shown limited clinical benefits in GBM and the role of EGFRvIII in GBM is poorly understood. To shed light on the role of EGFRvIII and its potential as a therapeutic target, we determined X-ray crystal structures of a monomeric EGFRvIII extracellular region (ECR). The EGFRvIII ECR resembles the unliganded conformation of EGFR, including the orientation of the C-terminal region of domain II. Domain II is mostly disordered, but the ECR structure is compact. We selected a nanobody with preferential binding to EGFRvIII relative to EGFR and structurally defined an epitope on domain IV that is occluded in the unliganded intact EGFR. These findings suggest new avenues for EGFRvIII targeting in GBM.

Cancer research is not correlated with driver gene mutation burdens

Cancer research is pursued with the goal of positively impacting patients with cancer. Decisions regarding how to allocate research funds reflect a complex balancing of priorities and factors. Even though these are subjective decisions, they should be made with consideration of all available objective facts. An accurate estimate of the affected cancer patient population by mutation is one variable that has only recently become available to inform funding decisions. We compared the overall incident burden of mutations within each cancer-associated gene with two measures of cancer research efforts: research grant funding amounts and numbers of academic manuscripts. We ask to what degree the aggregate set of cancer research efforts reflects the relative burdens of the different cancer genetic drivers. We thoroughly investigate the design of our queries to ensure that the presented results are robust and conclusions are well justified. We find cancer research is generally not correlated with the relative burden of mutation within the different genetic drivers of cancer. We suggest that cancer research would benefit from incorporating, among other factors, an epidemiologically informed mutation-estimate baseline into a larger framework for funding and research allocation decisions. This work was supported in part by the National Institutes of Health (NIH) P30CA014195 and NIH DP2AT011327.

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression.

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1 , ETV1 , CRKL , and ID4 . Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC , on the same complex amplicons such as ecDNA. We characterized a MYC - ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC 's enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.

In vivo CRISPR screens reveal SCAF1 and USP15 as drivers of pancreatic cancer

Functionally characterizing the genetic alterations that drive pancreatic cancer is a prerequisite for precision medicine. Here, we perform somatic CRISPR/Cas9 mutagenesis screens to assess the transforming potential of 125 recurrently mutated pancreatic cancer genes, which revealed USP15 and SCAF1 as pancreatic tumor suppressors. Mechanistically, we find that USP15 functions in a haploinsufficient manner and that loss of USP15 or SCAF1 leads to reduced inflammatory TNFα, TGF-β and IL6 responses and increased sensitivity to PARP inhibition and Gemcitabine. Furthermore, we find that loss of SCAF1 leads to the formation of a truncated, inactive USP15 isoform at the expense of full-length USP15, functionally coupling SCAF1 and USP15. Notably, USP15 and SCAF1 alterations are observed in 31% of pancreatic cancer patients. Our results highlight the utility of in vivo CRISPR screens to integrate human cancer genomics and mouse modeling for the discovery of cancer driver genes with potential prognostic and therapeutic implications.