Ion channel modulator DPI-201-106 significantly enhances antitumor activity of DNA damage response inhibitors in glioblastoma.

Background: Glioblastoma, a lethal high-grade glioma, has not seen improvements in clinical outcomes in nearly 30 years. Ion channels are increasingly associated with tumorigenesis, and there are hundreds of brain-penetrant drugs that inhibit ion channels, representing an untapped therapeutic resource. The aim of this exploratory drug study was to screen an ion channel drug library against patient-derived glioblastoma cells to identify new treatments for brain cancer.

Grb7, Grb10 and Grb14, encoding the growth factor receptor-bound 7 family of signalling adaptor proteins have overlapping functions in the regulation of fetal growth and post-natal glucose metabolism.

Background: The growth factor receptor bound protein 7 (Grb7) family of signalling adaptor proteins comprises Grb7, Grb10 and Grb14. Each can interact with the insulin receptor and other receptor tyrosine kinases, where Grb10 and Grb14 inhibit insulin receptor activity. In cell culture studies they mediate functions including cell survival, proliferation, and migration.

View from the PEAKs: Insights from structural studies on the PEAK family of pseudokinases.

The PEAK family of pseudokinase scaffolds, comprising PEAK1 (originally termed SgK269), PEAK2 (SgK223, the human orthologue of rat Pragmin) and PEAK3 (C19orf35), have emerged as important regulators and integrators of cellular signaling and also play oncogenic roles in a variety of human cancers. These proteins undergo both homo- and heterotypic association that act to diversify signal output. Recently, structural and functional characterization of PEAK3 and its protein-protein interactions have shed light on PEAK signaling dynamics and the interdependency of PEAK family members, how PEAK dimerization regulates the binding of downstream effectors, and how 14-3-3 binding acts to regulate PEAK3 signal output.

BMP4-Induced Suppression of Breast Cancer Metastasis Is Associated with Inhibition of Cholesterol Biosynthesis.

We reported previously that in preclinical models, BMP4 is a potent inhibitor of breast cancer metastasis and that high BMP4 protein levels predict favourable patient outcomes. Here, we analysed a breast cancer xenograft with or without enforced expression of BMP4 to gain insight into the mechanisms by which BMP4 suppresses metastasis. Transcriptomic analysis of cancer cells recovered from primary tumours and phosphoproteomic analyses of cancer cells exposed to recombinant BMP4 revealed that BMP4 inhibits cholesterol biosynthesis, with many genes in this biosynthetic pathway being downregulated by BMP4.

Integrative Modeling of Signaling Network Dynamics Identifies Cell Type-Selective Therapeutic Strategies for FGFR4-Driven Cancers.

Oncogenic FGFR4 signaling represents a potential therapeutic target in various cancer types, including triple-negative breast cancer and hepatocellular carcinoma. However, resistance to FGFR4 single-agent therapy remains a major challenge, emphasizing the need for effective combinatorial treatments. Our study sought to develop a comprehensive computational model of FGFR4 signaling and to provide network-level insights into resistance mechanisms driven by signaling dynamics.

Proteome-based molecular subtyping and therapeutic target prediction in gastric cancer.

Different molecular classifications for gastric cancer (GC) have been proposed based on multi-omics platforms with the long-term goal of improved precision treatment. However, the GC (phospho)proteome remains incompletely characterized, particularly at the level of tyrosine phosphorylation. In addition, previous multiomics-based stratification of patient cohorts has lacked identification of corresponding cell line models and comprehensive validation of broad or subgroup-selective therapeutic targets.

Feed-forward stimulation of CAMK2 by the oncogenic pseudokinase PEAK1 generates a therapeutically "actionable" signalling axis in triple negative breast cancer.

The PEAK family of pseudokinases, comprising PEAK1-3, are signalling scaffolds that play oncogenic roles in several poor prognosis human cancers, including triple negative breast cancer (TNBC). However, therapeutic targeting of pseudokinases is challenging due to their lack of catalytic activity. To address this, we screened for PEAK1 effectors by affinity purification and mass spectrometry, identifying calcium/calmodulin-dependent protein kinase 2 (CAMK2)D and CAMK2G.

Pediatric glioma histone H3.3 K27M/G34R mutations drive abnormalities in PML nuclear bodies.

Background: Point mutations in histone variant H3.3 (H3.3K27M, H3.

Surformer: An interpretable pattern-perceptive survival transformer for cancer survival prediction from histopathology whole slide images.

Background And Objective: High-resolution histopathology whole slide images (WSIs) contain abundant valuable information for cancer prognosis. However, most computational pathology methods for survival prediction have weak interpretability and cannot explain the decision-making processes reasonably. To address this issue, we propose a highly interpretable neural network termed pattern-perceptive survival transformer (Surformer) for cancer survival prediction from WSIs.

Structural mapping of PEAK pseudokinase interactions identifies 14-3-3 as a molecular switch for PEAK3 signaling.

PEAK pseudokinases regulate cell migration, invasion and proliferation by recruiting key signaling proteins to the cytoskeleton. Despite lacking catalytic activity, alteration in their expression level is associated with several aggressive cancers. Here, we elucidate the molecular details of key PEAK signaling interactions with the adapter proteins CrkII and Grb2 and the scaffold protein 14-3-3.

Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification.

Motivation: Multiple instance learning (MIL) is a powerful technique to classify whole slide images (WSIs) for diagnostic pathology. The key challenge of MIL on WSI classification is to discover the critical instances that trigger the bag label. However, tumor heterogeneity significantly hinders the algorithm's performance.

Cell-Type-Specific Signalling Networks Impacted by Prostate Epithelial-Stromal Intercellular Communication.

Prostate cancer is the second most common cause of cancer death in males. A greater understanding of cell signalling events that occur within the prostate cancer tumour microenvironment (TME), for example, between cancer-associated fibroblasts (CAFs) and prostate epithelial or cancer cells, may identify novel biomarkers and more effective therapeutic strategies for this disease. To address this, we used cell-type-specific labelling with amino acid precursors (CTAP) to define cell-type-specific (phospho)proteomic changes that occur when prostate epithelial cells are co-cultured with normal patient-derived prostate fibroblasts (NPFs) versus matched CAFs.

A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer.

Precision medicine has emerged as an important paradigm in oncology, driven by the significant heterogeneity of individual patients' tumour. A key prerequisite for effective implementation of precision oncology is the development of companion biomarkers that can predict response to anti-cancer therapies and guide patient selection for clinical trials and/or treatment. However, reliable predictive biomarkers are currently lacking for many anti-cancer therapies, hampering their clinical application.

The pseudokinase NRBP1 activates Rac1/Cdc42 via P-Rex1 to drive oncogenic signalling in triple-negative breast cancer.

We have determined that expression of the pseudokinase NRBP1 positively associates with poor prognosis in triple negative breast cancer (TNBC) and is required for efficient migration, invasion and proliferation of TNBC cells in culture as well as growth of TNBC orthotopic xenografts and experimental metastasis. Application of BioID/MS profiling identified P-Rex1, a known guanine nucleotide exchange factor for Rac1, as a NRBP1 binding partner. Importantly, NRBP1 overexpression enhanced levels of GTP-bound Rac1 and Cdc42 in a P-Rex1-dependent manner, while NRBP1 knockdown reduced their activation.

Integrative characterisation of secreted factors involved in intercellular communication between prostate epithelial or cancer cells and fibroblasts.

Reciprocal interactions between prostate cancer cells and carcinoma-associated fibroblasts (CAFs) mediate cancer development and progression; however, our understanding of the signalling pathways mediating these cellular interactions remains incomplete. To address this, we defined secretome changes upon co-culture of prostate epithelial or cancer cells with fibroblasts that mimic bi-directional communication in tumours. Using antibody arrays, we profiled conditioned media from mono- and co-cultures of prostate fibroblasts, epithelial and cancer cells, identifying secreted proteins that are upregulated in co-culture compared to mono-culture.

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.

Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality.

Background: Prostate cancer is a clinically heterogeneous disease with a subset of patients rapidly progressing to lethal-metastatic prostate cancer. Current clinicopathological measures are imperfect predictors of disease progression. Epigenetic changes are amongst the earliest molecular changes in tumourigenesis.

Enhancing therapeutic anti-cancer responses by combining immune checkpoint and tyrosine kinase inhibition.

Over the past decade, immune checkpoint inhibitor (ICI) therapy has been established as the standard of care for many types of cancer, but the strategies employed have continued to evolve. Recently, much clinical focus has been on combining targeted therapies with ICI for the purpose of manipulating the immune setpoint. The latter concept describes the equilibrium between factors that promote and those that suppress anti-cancer immunity.

Proteomic characterisation of prostate cancer intercellular communication reveals cell type-selective signalling and TMSB4X-dependent fibroblast reprogramming.

Background: In prostate cancer, the tumour microenvironment (TME) represents an important regulator of disease progression and response to treatment. In the TME, cancer-associated fibroblasts (CAFs) play a key role in tumour progression, however the mechanisms underpinning fibroblast-cancer cell interactions are incompletely resolved. Here, we address this by applying cell type-specific labelling with amino acid precursors (CTAP) and mass spectrometry (MS)-based (phospho)proteomics to prostate cancer for the first time.

CDK8 and CDK19 regulate intestinal differentiation and homeostasis via the chromatin remodeling complex SWI/SNF.

Initiation and maintenance of transcriptional states are critical for controlling normal tissue homeostasis and differentiation. The cyclin dependent kinases CDK8 and CDK19 (Mediator kinases) are regulatory components of Mediator, a highly conserved complex that orchestrates enhancer-mediated transcriptional output. While Mediator kinases have been implicated in the transcription of genes necessary for development and growth, its function in mammals has not been well defined.

Novel Therapeutic Targets and Biomarkers Associated with Prostate Cancer-Associated Fibroblasts (CAFs).

Despite advances in treatment, prostate cancer remains a significant cause of morbidity and mortality worldwide. While the vast majority of prostate cancer research has centered on malignant epithelial cells, the tumor mi croenvironment (TME) has recently become increasingly recognized as an important regulator of tumor progression and response to treatment. Among the diverse cell types within the TME, stromal fibroblasts, in particular cancer-associated fibroblasts (CAFs), play an important role in prostate cancer progression.

Preface: Novel Therapeutic Targets and Biomarkers in Prostate Cancer.

CRO special issue: Novel Therapeutic Targets and Biomarkers in Prostate Cancer.

DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images.

Motivation: The molecular subtyping of gastric cancer (adenocarcinoma) into four main subtypes based on integrated multiomics profiles, as proposed by The Cancer Genome Atlas (TCGA) initiative, represents an effective strategy for patient stratification. However, this approach requires the use of multiple technological platforms, and is quite expensive and time-consuming to perform. A computational approach that uses histopathological image data to infer molecular subtypes could be a practical, cost- and time-efficient complementary tool for prognostic and clinical management purposes.

Cell graph neural networks enable the precise prediction of patient survival in gastric cancer.

Gastric cancer is one of the deadliest cancers worldwide. An accurate prognosis is essential for effective clinical assessment and treatment. Spatial patterns in the tumor microenvironment (TME) are conceptually indicative of the staging and progression of gastric cancer patients.

Global ubiquitinome profiling identifies NEDD4 as a regulator of Profilin 1 and actin remodelling in neural crest cells.

The ubiquitin ligase NEDD4 promotes neural crest cell (NCC) survival and stem-cell like properties to regulate craniofacial and peripheral nervous system development. However, how ubiquitination and NEDD4 control NCC development remains unknown. Here we combine quantitative analysis of the proteome, transcriptome and ubiquitinome to identify key developmental signalling pathways that are regulated by NEDD4.