Pan-Cancer Analysis of Human Kinome Gene Expression and Promoter DNA Methylation Identifies Dark Kinase Biomarkers in Multiple Cancers

Integration of CRISPR/dCas9-Based methylation editing with guide positioning sequencing identifies dynamic changes of mrDEGs in breast cancer progression

Dynamic changes in DNA methylation are prevalent during the progression of breast cancer. However, critical alterations in aberrant methylation and gene expression patterns have not been thoroughly characterized. Here, we utilized guide positioning sequencing (GPS) to conduct whole-genome DNA methylation analysis in a unique human breast cancer progression model: MCF10 series of cell lines (representing benign/normal, atypical hyperplasia, and metastatic carcinoma). By integrating with mRNA-seq and matched clinical expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), six representative methylation-related differentially expressed genes (mrDEGs) were identified, including CAVIN2, ARL4D, DUSP1, TENT5B, P3H2, and MMP28. To validate our findings, we independently developed and optimized the dCas9-DNMT3L-DNMT3A system, achieving a high efficiency with a 98% increase in methylation at specific sites. DNA methylation levels significantly increased for the six genes, with CAVIN2 at 67.75 ± 1.05%, ARL4D at 53.29 ± 6.32%, DUSP1 at 57.63 ± 8.46%, TENT5B at 44.00 ± 5.09%, P3H2 at 58.50 ± 3.90%, and MMP28 at 49.60 ± 5.84%. RT-qPCR confirmed an inverse correlation between increased DNA methylation and gene expression. Most importantly, we mimicked tumor progression in vitro, demonstrating that transcriptional silencing of the TENT5B promotes cell proliferation in MCF10A cells owing to the crosstalk between hypermethylation and histone deacetylation. This study unveils the practical implications of DNA methylation dynamics of mrDEGs in reshaping epigenomic features during breast cancer malignant progression through integrated data analysis of the methylome and transcriptome. The application of the CRISPR/dCas9-based methylation editing technique elucidates the regulatory mechanisms and functional roles of individual genes within the DNA methylation signature, providing valuable insights for understanding breast cancer pathogenesis and facilitating potential therapeutic approaches in epigenome editing for patients with breast cancer.

Pan-cancer and multiomics: advanced strategies for diagnosis, prognosis, and therapy in the complex genetic and molecular universe of cancer

The pan-cancer and multi-omics approach is motivated by the genetic and molecular complexity inherent in the varied types of cancer. This method presents itself as a crucial resource for advancing early diagnosis, defining prognoses and identifying treatments that share common bases between different forms of tumors. The aim of this article is to explore pan-cancer analysis in conjunction with multi-omics strategies, evaluating laboratory, computational, clinical procedures and their consequences, as well as examining the tumor microenvironment, epigenetics and future directions of these technologies in patient management. To this end, a literature review was conducted using PUBMED, resulting in the selection of 260 articles, of which 81 were carefully chosen to support this analysis. The pan-cancer methodology is applied to the study of this microenvironment with the aim of investigating its common characteristics through multiomics data. The development of new therapies depends on understanding the oncogenic pathways associated with different cancers. Thus, the integration of multi-omics and pan-cancer analyzes offers an innovative perspective in the search for new control points, metabolic pathways and markers, in addition to facilitating the identification of patterns common to multiple cancer types, allowing the development of targeted treatments. In this way, the convergence of multiomics and clinical approaches promotes a broad view of cancer biology, leading to more effective and personalized therapies.

Impact of protein and small molecule interactions on kinase conformations

Protein kinases act as central molecular switches in the control of cellular functions. Alterations in the regulation and function of protein kinases may provoke diseases including cancer. In this study we investigate the conformational states of such disease-associated kinases using the high sensitivity of the kinase conformation (KinCon) reporter system. We first track BRAF kinase activity conformational changes upon melanoma drug binding. Second, we also use the KinCon reporter technology to examine the impact of regulatory protein interactions on LKB1 kinase tumor suppressor functions. Third, we explore the conformational dynamics of RIP kinases in response to TNF pathway activation and small molecule interactions. Finally, we show that CDK4/6 interactions with regulatory proteins alter conformations which remain unaffected in the presence of clinically applied inhibitors. Apart from its predictive value, the KinCon technology helps to identify cellular factors that impact drug efficacies. The understanding of the structural dynamics of full-length protein kinases when interacting with small molecule inhibitors or regulatory proteins is crucial for designing more effective therapeutic strategies.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Illuminating the druggable genome: Pathways to progress

There are ∼4500 genes within the 'druggable genome', the subset of the human genome that expresses proteins able to bind drug-like molecules, yet existing drugs only target a few hundred. A substantial subset of druggable proteins are largely uncharacterized or understudied, with many falling within G protein-coupled receptor (GPCR), ion channel, and kinase protein families. To improve scientific understanding of these three understudied protein families, the US National Institutes of Health launched the Illuminating the Druggable Genome Program. Now, as the program draws to a close, this review will lay out resources developed by the program that are intended to equip the scientific community with the tools necessary to explore previously understudied biology with the potential to rapidly impact human health.

FusionNW, a potential clinical impact assessment of kinases in pan-cancer fusion gene network

Kinase fusion genes are the most active fusion gene group in human cancer fusion genes. To help choose the clinically significant kinase so that the cancer patients that have fusion genes can be better diagnosed, we need a metric to infer the assessment of kinases in pan-cancer fusion genes rather than relying on the sample frequency expressed fusion genes. Most of all, multiple studies assessed human kinases as the drug targets using multiple types of genomic and clinical information, but none used the kinase fusion genes in their study. The assessment studies of kinase without kinase fusion gene events can miss the effect of one of the mechanisms that enhance the kinase function in cancer. To fill this gap, in this study, we suggest a novel way of assessing genes using a network propagation approach to infer how likely individual kinases influence the kinase fusion gene network composed of ~5K kinase fusion gene pairs. To select a better seed of propagation, we chose the top genes via dimensionality reduction like a principal component or latent layer information of six features of individual genes in pan-cancer fusion genes. Our approach may provide a novel way to assess of human kinases in cancer.

An endoplasmic reticulum stress-related signature could robustly predict prognosis and closely associate with response to immunotherapy in pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors. Endoplasmic reticulum stress (ERS) plays an essential role in PDAC progression. Here, we aim to identify the ERS-related genes in PDAC and build reliable risk models for diagnosis, prognosis and immunotherapy response of PDAC patients as well as investigate the potential mechanism.

METHODS

We obtained PDAC cohorts with transcriptional profiles and clinical data from the ArrayExpress, The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Univariate Cox regression, LASSO regression and multivariate Cox regression analyses were used to construct an ERS-related prognostic signature. The CIBERSORT and ssGSEA algorithms were applied to explore the correlation between the prognostic signature and immune cell infiltration and immune-related pathways. The GDSC database and TIDE algorithm were used to predict responses to chemotherapy and immunotherapy, identifying potential drugs for treating patients with PDAC.

RESULTS

We established and validated an ERS-related prognostic signature comprising eight genes (HMOX1, TGFB1, JSRP1, GAPDH, CAV1, CHRNE, CD74 and ERN2). Patients with higher risk scores displayed worse outcomes than those with lower risk scores. PDAC patients in low-risk groups might benefit from immunotherapy. Dasatinib and lapatinib might have potential therapeutic implications in high-risk PDAC patients.

CONCLUSION

We established and validated an ERS-related prognostic signature comprising eight genes to predict the overall survival outcome of PDAC patients, which closely correlating with the response to immunotherapy and sensitivity to anti-tumor drugs, as well as could be beneficial for formulating clinical strategies and administering individualized treatments.

Comprehensive single cell aging atlas of mammary tissues reveals shared epigenomic and transcriptomic signatures of aging and cancer

Aging is the greatest risk factor for breast cancer; however, how age-related cellular and molecular events impact cancer initiation is unknown. We investigate how aging rewires transcriptomic and epigenomic programs of mouse mammary glands at single cell resolution, yielding a comprehensive resource for aging and cancer biology. Aged epithelial cells exhibit epigenetic and transcriptional changes in metabolic, pro-inflammatory, or cancer-associated genes. Aged stromal cells downregulate fibroblast marker genes and upregulate markers of senescence and cancer-associated fibroblasts. Among immune cells, distinct T cell subsets (Gzmk+, memory CD4+, γδ) and M2-like macrophages expand with age. Spatial transcriptomics reveal co-localization of aged immune and epithelial cells in situ. Lastly, transcriptional signatures of aging mammary cells are found in human breast tumors, suggesting mechanistic links between aging and cancer. Together, these data uncover that epithelial, immune, and stromal cells shift in proportions and cell identity, potentially impacting cell plasticity, aged microenvironment, and neoplasia risk.

How many kinases are druggable? A review of our current understanding

There are over 500 human kinases ranging from very well-studied to almost completely ignored. Kinases are tractable and implicated in many diseases, making them ideal targets for medicinal chemistry campaigns, but is it possible to discover a drug for each individual kinase? For every human kinase, we gathered data on their citation count, availability of chemical probes, approved and investigational drugs, PDB structures, and biochemical and cellular assays. Analysis of these factors highlights which kinase groups have a wealth of information available, and which groups still have room for progress. The data suggest a disproportionate focus on the more well characterized kinases while much of the kinome remains comparatively understudied. It is noteworthy that tool compounds for understudied kinases have already been developed, and there is still untapped potential for further development in this chemical space. Finally, this review discusses many of the different strategies employed to generate selectivity between kinases. Given the large volume of information available and the progress made over the past 20 years when it comes to drugging kinases, we believe it is possible to develop a tool compound for every human kinase. We hope this review will prove to be both a useful resource as well as inspire the discovery of a tool for every kinase.

The dark kinase STK32A regulates hair cell planar polarity opposite of EMX2 in the developing mouse inner ear

The vestibular maculae of the inner ear contain sensory receptor hair cells that detect linear acceleration and contribute to equilibrioception to coordinate posture and ambulatory movements. These hair cells are divided between two groups, separated by a line of polarity reversal (LPR), with oppositely oriented planar-polarized stereociliary bundles that detect motion in opposite directions. The transcription factor EMX2 is known to establish this planar polarized organization in mouse by regulating the distribution of the transmembrane receptor GPR156 at hair cell boundaries in one group of cells. However, the genes regulated by EMX2 in this context were previously not known. Using mouse as a model, we have identified the serine threonine kinase STK32A as a downstream effector negatively regulated by EMX2. Stk32a is expressed in hair cells on one side of the LPR in a pattern complementary to Emx2 expression in hair cells on the opposite side. Stk32a is necessary to align the intrinsic polarity of the bundle with the core planar cell polarity (PCP) proteins in EMX2-negative regions, and is sufficient to reorient bundles when ectopically expressed in neighboring EMX2-positive regions. We demonstrate that STK32A reinforces LPR formation by regulating the apical localization of GPR156. These observations support a model in which bundle orientation is determined through separate mechanisms in hair cells on opposite sides of the maculae, with EMX2-mediated repression of Stk32a determining the final position of the LPR.

Enzalutamide-induced signatures revealed by epigenetic plasticity using single-cell multi-omics sequencing in prostate cancer

Prostate cancer is morphologically and molecularly heterogeneous, which poses obstacles for early diagnosis and treatment. Advancements in understanding the heterogeneity of prostate cancer will help navigate through these challenges and ultimately benefit patients. In this study, we integrated single-cell sequencing for transposase-accessible chromatin and whole transcriptome in prostate cancer cell lines, aiming to decode the epigenetic plasticity upon enzalutamide (ENZ) treatment. By comparing the cell populations representing early-treatment response or resistance to the initial tumor cells, we identified seven signature gene sets; they present consistent trends of chromatin closing co-occurred with down-regulated genes during early response and chromatin opening with up-regulated genes upon maintaining drug resistance. In the molecular signatures, we found genes ZNF337, MAPK15, and ESRRG are favorable in progression-free prognosis during early response, while genes CCDC150, CCDC18, and POC1A marked poor prognosis underpinning the pre-existing drug resistance in The Cancer Genome Atlas prostate adenocarcinoma cohort. Ultimately, drug-target analyses nominated combinatory drug candidates to either enhance early-treatment response or potentially overcome ENZ resistance. Together, our integrative, single-cell multi-omics approach in pre-clinical models is effective in identifying informative signatures from complex molecular events, illustrating diverse drug responses in prostate cancer, and invoking novel combinatory drug strategies to inform clinical decision making.

Cellular and molecular effects of PNCK, a non-canonical kinase target in renal cell carcinoma

Renal cell carcinoma (RCC) is a fatal disease when advanced. While immunotherapy and tyrosine kinase inhibitor-based combinations are associated with improved survival, the majority of patients eventually succumb to the disease. Through a comprehensive pan-cancer, pan-kinome analysis of the Cancer Genome Atlas (TCGA), pregnancy-upregulated non-ubiquitous calcium-calmodulin-dependent kinase (PNCK), was identified as the most differentially overexpressed kinase in RCC. PNCK overexpression correlated with tumor stage, grade and poor survival. PNCK overexpression in RCC cells was associated with increased CREB phosphorylation, increased cell proliferation, and cell cycle progression. PNCK down-regulation, conversely, was associated with the opposite, in addition to increased apoptosis. Pathway analyses in PNCK knockdown cells showed significant down-regulation of hypoxia and angiogenesis pathways, as well as the modulation of the cell cycle, DNA damage, and apoptosis pathways. These results demonstrate for the first time the biological role of PNCK, an understudied kinase, in RCC and validate PNCK as a druggable target.

Identification of biological pathways and processes regulated by NEK5 in breast epithelial cells via an integrated proteomic approach

Specific members of the Nima-Related Kinase (NEK) family have been linked to cancer development and progression, and a role for NEK5, one of the least studied members, in breast cancer has recently been proposed. However, while NEK5 is known to regulate centrosome separation and mitotic spindle assembly, NEK5 signalling mechanisms and function in this malignancy require further characterization. To this end, we established a model system featuring overexpression of NEK5 in the immortalized breast epithelial cell line MCF-10A. MCF-10A cells overexpressing NEK5 exhibited an increase in clonogenicity under monolayer conditions and enhanced acinar size and abnormal morphology in 3D Matrigel culture. Interestingly, they also exhibited a marked reduction in Src activation and downstream signalling. To interrogate NEK5 signalling and function in an unbiased manner, we applied a variety of MS-based proteomic approaches. Determination of the NEK5 interactome by Bio-ID identified a variety of protein classes including the kinesins KIF2C and KIF22, the mitochondrial proteins TFAM, TFB2M and MFN2, RhoH effectors and the negative regulator of Src, CSK. Characterization of proteins and phosphosites modulated upon NEK5 overexpression by global MS-based (phospho)proteomic profiling revealed impact on the cell cycle, DNA synthesis and repair, Rho GTPase signalling, the microtubule cytoskeleton and hemidesmosome assembly. Overall, the study indicates that NEK5 impacts diverse pathways and processes in breast epithelial cells, and likely plays a multifaceted role in breast cancer development and progression. Video Abstract.

Promotor methylation status of MAPK4 is a novel epigenetic biomarker for prognosis of recurrence in patients with thymic epithelial tumors

BACKGROUND

The prognosis of thymic epithelial tumors (TETs) currently relies on the commonly adopted WHO classification and Masaoka staging system, which cannot reflect the undefined biological behaviors limiting them as prognostic factors.

METHODS

In this study, we first identified 40 genes and 179 genes, respectively that were epigenetically upregulated and silenced, corresponding to a total of 509 functionally methylated CpG sites between thymomas and thymic carcinomas by using the TCGA dataset.

RESULTS

The methylation β-values of cg20068620 in MAPK4 and cg18770944 in USP51 were significantly associated with recurrence-free survival (RFS). In the independent validation cohort, only WHO classification and methylation β-values of cg20068620 in MAPK4 were independent prognostic factors for RFS in Chinese patients with TETs. A linear weighted model including these two factors was used to calculate the recurrence risk score (RRS). Time-dependent ROC curve analysis revealed that RRS was overwhelmingly superior to WHO classification for predicting 3-, 5-, and 10-year RFS and Masaoka stage for 3- and 5-year RFS.

CONCLUSIONS

These results suggested that the methylation site cg20068620 in MAPK4 can improve the accuracy of the WHO classification alone regarding the prognostic value of TETs recurrence.