Optimisation of a primary human CAR-NK cell manufacturing pipeline.

Objectives: Autologous chimeric antigen receptor (CAR) T-cell therapy of B-cell malignancies achieves long-term disease remission in a high fraction of patients and has triggered intense research into translating this successful approach into additional cancer types. However, the complex logistics involved in autologous CAR-T manufacturing, the compromised fitness of patient-derived T cells, the high rates of serious toxicities and the overall cost involved with product manufacturing and hospitalisation have driven innovation to overcome such hurdles. One alternative approach is the use of allogeneic natural killer (NK) cells as a source for CAR-NK cell therapy.

PRMT5 and CDK4/6 inhibition result in distinctive patterns of alternative splicing in melanoma.

Drugs targeting cyclin-dependent kinases 4 and 6 (CDK4/6) are promising new treatments for melanoma and other solid malignancies. In studies on CDK4/6 inhibitor resistance, protein arginine methyltransferase 5 (PRMT5) regulation of alternative splicing was shown to be an important downstream component of the CDK4/6 pathway. However, the full effects of inhibition of CDK4/6 on splicing events in melanoma and the extent to which they are dependent on PRMT5 has not been established.

Discovery of a highly potent, selective, orally bioavailable inhibitor of KAT6A/B histone acetyltransferases with efficacy against KAT6A-high ER+ breast cancer.

KAT6A, and its paralog KAT6B, are histone lysine acetyltransferases (HAT) that acetylate histone H3K23 and exert an oncogenic role in several tumor types including breast cancer where KAT6A is frequently amplified/overexpressed. However, pharmacologic targeting of KAT6A to achieve therapeutic benefit has been a challenge. Here we describe identification of a highly potent, selective, and orally bioavailable KAT6A/KAT6B inhibitor CTx-648 (PF-9363), derived from a benzisoxazole series, which demonstrates anti-tumor activity in correlation with H3K23Ac inhibition in KAT6A over-expressing breast cancer.

High temporal resolution RNA-seq time course data reveals widespread synchronous activation between mammalian lncRNAs and neighboring protein-coding genes.

The advent of massively parallel sequencing revealed extensive transcription beyond protein-coding genes, identifying tens of thousands of long noncoding RNAs (lncRNAs). Selected functional examples raised the possibility that lncRNAs, as a class, may maintain broad regulatory roles. Expression of lncRNAs is strongly linked with adjacent protein-coding gene expression, suggesting potential -regulatory functions.

Computational Screening of Anti-Cancer Drugs Identifies a New BRCA Independent Gene Expression Signature to Predict Breast Cancer Sensitivity to Cisplatin.

The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy.

Modular assembly of dynamic models in systems biology.

It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space.

The Ratio of Exhausted to Resident Infiltrating Lymphocytes Is Prognostic for Colorectal Cancer Patient Outcome.

Immunotherapy success in colorectal cancer is mainly limited to patients whose tumors exhibit high microsatellite instability (MSI). However, there is variability in treatment outcomes within this group, which is in part driven by the frequency and characteristics of tumor-infiltrating immune cells. Indeed, the presence of specific infiltrating immune-cell subsets has been shown to correlate with immunotherapy response and is in many cases prognostic of treatment outcome.

The oncogene AAMDC links PI3K-AKT-mTOR signaling with metabolic reprograming in estrogen receptor-positive breast cancer.

Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene amplified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC-dependent promoters.

Stable gene expression for normalisation and single-sample scoring.

Gene expression signatures have been critical in defining the molecular phenotypes of cells, tissues, and patient samples. Their most notable and widespread clinical application is stratification of breast cancer patients into molecular (PAM50) subtypes. The cost and relatively large amounts of fresh starting material required for whole-transcriptome sequencing has limited clinical application of thousands of existing gene signatures captured in repositories such as the Molecular Signature Database.

The cancer-natural killer cell immunity cycle.

Immunotherapy with checkpoint blockade induces rapid and durable immune control of cancer in some patients and has driven a monumental shift in cancer treatment. Neoantigen-specific CD8 T cells are at the forefront of current immunotherapy strategies, and the majority of drug discovery and clinical trials revolve around further harnessing these immune effectors. Yet the immune system contains a diverse range of antitumour effector cells, and these must function in a coordinated and synergistic manner to overcome the immune-evasion mechanisms used by tumours and achieve complete control with tumour eradication.

Harnessing Natural Killer Immunity in Metastatic SCLC.

Introduction: SCLC is the most aggressive subtype of lung cancer, and though most patients initially respond to platinum-based chemotherapy, resistance develops rapidly. Immunotherapy holds promise in the treatment of lung cancer; however, patients with SCLC exhibit poor overall responses highlighting the necessity for alternative approaches. Natural killer (NK) cells are an alternative to T cell-based immunotherapies that do not require sensitization to antigens presented on the surface of tumor cells.

Using singscore to predict mutation status in acute myeloid leukemia from transcriptomic signatures.

Advances in RNA sequencing (RNA-seq) technologies that measure the transcriptome of biological samples have revolutionised our ability to understand transcriptional regulatory programs that underpin diseases such as cancer. We recently published singscore - a single sample, rank-based gene set scoring method which quantifies how concordant the transcriptional profile of individual samples are relative to specific gene sets of interest. Here we demonstrate the application of singscore to investigate transcriptional profiles associated with specific mutations or genetic lesions in acute myeloid leukemia.

Differential co-expression-based detection of conditional relationships in transcriptional data: comparative analysis and application to breast cancer.

Background: Elucidation of regulatory networks, including identification of regulatory mechanisms specific to a given biological context, is a key aim in systems biology. This has motivated the move from co-expression to differential co-expression analysis and numerous methods have been developed subsequently to address this task; however, evaluation of methods and interpretation of the resulting networks has been hindered by the lack of known context-specific regulatory interactions.

Results: In this study, we develop a simulator based on dynamical systems modelling capable of simulating differential co-expression patterns.

Therapeutic blockade of activin-A improves NK cell function and antitumor immunity.

Natural killer (NK) cells are innate lymphocytes that play a major role in immunosurveillance against tumor initiation and metastatic spread. The signals and checkpoints that regulate NK cell fitness and function in the tumor microenvironment are not well defined. Transforming growth factor-β (TGF-β) is a suppressor of NK cells that inhibits interleukin-15 (IL-15)-dependent signaling events and increases the abundance of receptors that promote tissue residency.

Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA).

Epithelial-mesenchymal transition (EMT) has been a subject of intense scrutiny as it facilitates metastasis and alters drug sensitivity. Although EMT-regulatory roles for numerous miRNAs and transcription factors are known, their functions can be difficult to disentangle, in part due to the difficulty in identifying direct miRNA targets from complex datasets and in deciding how to incorporate 'indirect' miRNA effects that may, or may not, represent biologically relevant information. To better understand how miRNAs exert effects throughout the transcriptome during EMT, we employed Exon-Intron Split Analysis (EISA), a bioinformatic technique that separates transcriptional and post-transcriptional effects through the separate analysis of RNA-Seq reads mapping to exons and introns.

A Gene Signature Predicting Natural Killer Cell Infiltration and Improved Survival in Melanoma Patients.

Natural killer (NK) cell activity is essential for initiating antitumor responses and may be linked to immunotherapy success. NK cells and other innate immune components could be exploitable for cancer treatment, which drives the need for tools and methods that identify therapeutic avenues. Here, we extend our gene-set scoring method to investigate NK cell infiltration by applying RNA-seq analysis to samples from bulk tumors.

The Emergence of Natural Killer Cells as a Major Target in Cancer Immunotherapy.

Immune 'checkpoint' inhibitors can increase the activity of tumor-resident cytotoxic lymphocytes and have revolutionized cancer treatment. Current therapies block inhibitory pathways in tumor-infiltrating CD8 T cells and recent studies have shown similar programs in other effector populations such as natural killer (NK) cells. NK cells are critical for immunosurveillance, particularly the control of metastatic cells or hematological cancers.

Single sample scoring of molecular phenotypes.

Background: Gene set scoring provides a useful approach for quantifying concordance between sample transcriptomes and selected molecular signatures. Most methods use information from all samples to score an individual sample, leading to unstable scores in small data sets and introducing biases from sample composition (e.g.

A thermodynamic framework for modelling membrane transporters.

Membrane transporters contribute to the regulation of the internal environment of cells by translocating substrates across cell membranes. Like all physical systems, the behaviour of membrane transporters is constrained by the laws of thermodynamics. However, many mathematical models of transporters, especially those incorporated into whole-cell models, are not thermodynamically consistent, leading to unrealistic behaviour.

Combinatorial Targeting by MicroRNAs Co-ordinates Post-transcriptional Control of EMT.

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression, functioning in part by facilitating the degradation of target mRNAs. They have an established role in controlling epithelial-mesenchymal transition (EMT), a reversible phenotypic program underlying normal and pathological processes. Many studies demonstrate the role of individual miRNAs using overexpression at levels greatly exceeding physiological abundance.

Bond graph modelling of the cardiac action potential: implications for drift and non-unique steady states.

Mathematical models of cardiac action potentials have become increasingly important in the study of heart disease and pharmacology, but concerns linger over their robustness during long periods of simulation, in particular due to issues such as model drift and non-unique steady states. Previous studies have linked these to violation of conservation laws, but only explored those issues with respect to charge conservation in specific models. Here, we propose a general and systematic method of identifying conservation laws hidden in models of cardiac electrophysiology by using bond graphs, and develop a bond graph model of the cardiac action potential to study long-term behaviour.

A Transcriptional Program for Detecting TGFβ-Induced EMT in Cancer.

Most cancer deaths are due to metastasis, and epithelial-to-mesenchymal transition (EMT) plays a central role in driving cancer cell metastasis. EMT is induced by different stimuli, leading to different signaling patterns and therapeutic responses. TGFβ is one of the best-studied drivers of EMT, and many drugs are available to target this signaling pathway.

Determining the Significance of Protein Network Features and Attributes Using Permutation Testing.

Network analysis methods are increasing in popularity. An approach commonly applied to analyze proteomics data involves the use of protein-protein interaction (PPI) networks to explore the systems-level cooperation between proteins identified in a study. In this context, protein interaction networks can be used alongside the statistical analysis of proteomics data and traditional functional enrichment or pathway enrichment analyses.