A Systems Biology Approach to Understand the Racial Disparities in Colorectal Cancer.

Racial disparities between Black/African Americans (AA) and White patients in colorectal cancer are an ever-growing area of concern. Black/AA show the highest incidence and have the highest mortality among major U.S. racial groups. There is no definite cause other than possible sociodemographic, socioeconomic, education, nutrition, delivery of healthcare, screening, and cultural factors. A primary limitation in this field is the lack of and small sample size of Black/AA studies. Thus, this study aimed to investigate whether differences in gene expression contribute to this ongoing unanswered racial disparity issue. In this study, we examined transcriptomic data of Black/AA and White patient cohorts using a bioinformatic and systems biology approach. We performed a Kaplan-Meier overall survival analysis between both patient cohorts across critical colorectal cancer signal transduction networks (STN), to determine the differences in significant genes across each cohort. Other bioinformatic analyses performed included PROGENy (pathway responsive genes for activity inference), RNA sequencing differential expression using DESeq2, multivariable-adjusted regression, and other associated Kaplan-Meier analyses. These analyses identified novel prognostic genes independent from each cohort, 176 differentially expressed genes, and specific patient cohort STN survival associations. Despite the overarching limitation, the results revealed several novel differences in gene expression between the colorectal cancer Black/AA and White patient cohorts, which allows one to dive deeper into and understand the behavior on a systems level of what could be driving this racial difference across colorectal cancer. Concretely, this information can guide precision medicine approaches tailored specifically for colorectal cancer racial disparities. SIGNIFICANCE: The purpose of this work is to investigate the racial disparities in colorectal cancer between Black/AA and White patient cohorts using a systems biology and bioinformatic approach. Our study investigates the underlying biology of each patient cohort. Concretely, the findings of this study include disparity-associated genes and pathways, which provide a tangible starting point to guide precision medicine approaches tailored specifically for colorectal cancer racial disparities.

Transcriptional profiling of early differentiation of primary human mesenchymal stem cells into chondrocytes.

Articular cartilage has only very limited regenerative capacities in humans. Tissue engineering techniques for cartilage damage repair are limited in the production of hyaline cartilage. Mesenchymal stem/stromal cells (MSCs) are multipotent stem cells and can be differentiated into mature cartilage cells, chondrocytes, which could be used for repairing damaged cartilage. Chondrogenesis is a highly complex, relatively inefficient process lasting over 3 weeks in vitro. Methods: In order to better understand chondrogenic differentiation, especially the commitment phase, we have performed transcriptional profiling of MSC differentiation into chondrocytes from early timepoints starting 15 minutes after induction to 16 hours and fully differentiated chondrocytes at 21 days in triplicates.

Proteomic Mapping of the Interactome of KRAS Mutants Identifies New Features of RAS Signalling Networks and the Mechanism of Action of Sotorasib.

RAS proteins are key regulators of cell signalling and control different cell functions including cell proliferation, differentiation, and cell death. Point mutations in the genes of this family are common, particularly in KRAS. These mutations were thought to cause the constitutive activation of KRAS, but recent findings showed that some mutants can cycle between active and inactive states. This observation, together with the development of covalent KRASG12C inhibitors, has led to the arrival of KRAS inhibitors in the clinic. However, most patients develop resistance to these targeted therapies, and we lack effective treatments for other KRAS mutants. To accelerate the development of RAS targeting therapies, we need to fully characterise the molecular mechanisms governing KRAS signalling networks and determine what differentiates the signalling downstream of the KRAS mutants. Here we have used affinity purification mass-spectrometry proteomics to characterise the interactome of KRAS wild-type and three KRAS mutants. Bioinformatic analysis associated with experimental validation allows us to map the signalling network mediated by the different KRAS proteins. Using this approach, we characterised how the interactome of KRAS wild-type and mutants is regulated by the clinically approved KRASG12C inhibitor Sotorasib. In addition, we identified novel crosstalks between KRAS and its effector pathways including the AKT and JAK-STAT signalling modules.

Kinase Suppressor of RAS 1 (KSR1) Maintains the Transformed Phenotype of BRAFV600E Mutant Human Melanoma Cells.

Kinase Suppressor of RAS 1 (KSR1) is a scaffolding protein for the RAS-RAF-MEK-ERK pathway, which is one of the most frequently altered pathways in human cancers. Previous results have shown that KSR1 has a critical role in mutant RAS-mediated transformation. Here, we examined the role of KSR1 in mutant BRAF transformation. We used CRISPR/Cas9 to knock out KSR1 in a BRAFV600E-transformed melanoma cell line. KSR1 loss produced a complex phenotype characterised by impaired proliferation, cell cycle defects, decreased transformation, decreased invasive migration, increased cellular senescence, and increased apoptosis. To decipher this phenotype, we used a combination of proteomic ERK substrate profiling, global protein expression profiling, and biochemical validation assays. The results suggest that KSR1 directs ERK to phosphorylate substrates that have a critical role in ensuring cell survival. The results further indicate that KSR1 loss induces the activation of p38 Mitogen-Activated Protein Kinase (MAPK) and subsequent cell cycle aberrations and senescence. In summary, KSR1 function plays a key role in oncogenic BRAF transformation.

Reversing pathological cell states: the road less travelled can extend the therapeutic horizon.

Acquisition of omics data advances at a formidable pace. Yet, our ability to utilize these data to control cell phenotypes and design interventions that reverse pathological states lags behind. Here, we posit that cell states are determined by core networks that control cell-wide networks. To steer cell fate decisions, core networks connecting genotype to phenotype must be reconstructed and understood. A recent method, cell state transition assessment and regulation (cSTAR), applies perturbation biology to quantify causal connections and mechanistically models how core networks influence cell phenotypes. cSTAR models are akin to digital cell twins enabling us to purposefully convert pathological states back to physiologically normal states. While this capability has a range of applications, here we discuss reverting oncogenic transformation.

Small Gene Networks Delineate Immune Cell States and Characterize Immunotherapy Response in Melanoma.

Single-cell technologies have elucidated mechanisms responsible for immune checkpoint inhibitor (ICI) response, but are not amenable to a clinical diagnostic setting. In contrast, bulk RNA sequencing (RNA-seq) is now routine for research and clinical applications. Our workflow uses transcription factor (TF)-directed coexpression networks (regulons) inferred from single-cell RNA-seq data to deconvolute immune functional states from bulk RNA-seq data. Regulons preserve the phenotypic variation in CD45+ immune cells from metastatic melanoma samples (n = 19, discovery dataset) treated with ICIs, despite reducing dimensionality by >100-fold. Four cell states, termed exhausted T cells, monocyte lineage cells, memory T cells, and B cells were associated with therapy response, and were characterized by differentially active and cell state-specific regulons. Clustering of bulk RNA-seq melanoma samples from four independent studies (n = 209, validation dataset) according to regulon-inferred scores identified four groups with significantly different response outcomes (P < 0.001). An intercellular link was established between exhausted T cells and monocyte lineage cells, whereby their cell numbers were correlated, and exhausted T cells predicted prognosis as a function of monocyte lineage cell number. The ligand-receptor expression analysis suggested that monocyte lineage cells drive exhausted T cells into terminal exhaustion through programs that regulate antigen presentation, chronic inflammation, and negative costimulation. Together, our results demonstrate how regulon-based characterization of cell states provide robust and functionally informative markers that can deconvolve bulk RNA-seq data to identify ICI responders.

Interactome dynamics of RAF1-BRAF kinase monomers and dimers.

RAF kinases play major roles in cancer. BRAFV600E mutants drive ~6% of human cancers. Potent kinase inhibitors exist but show variable effects in different cancer types, sometimes even inducing paradoxical RAF kinase activation. Both paradoxical activation and drug resistance are frequently due to enhanced dimerization between RAF1 and BRAF, which maintains or restores the activity of the downstream MEK-ERK pathway. Here, using quantitative proteomics we mapped the interactomes of RAF1 monomers, RAF1-BRAF and RAF1-BRAFV600E dimers identifying and quantifying >1,000 proteins. In addition, we examined the effects of vemurafenib and sorafenib, two different types of clinically used RAF inhibitors. Using regression analysis to compare different conditions we found a large overlapping core interactome but also distinct condition specific differences. Given that RAF proteins have kinase independent functions such dynamic interactome changes could contribute to their functional diversification. Analysing this dataset may provide a deeper understanding of RAF signalling and mechanisms of resistance to RAF inhibitors.

Memory of stochastic single-cell apoptotic signaling promotes chemoresistance in neuroblastoma.

Gene expression noise is known to promote stochastic drug resistance through the elevated expression of individual genes in rare cancer cells. However, we now demonstrate that chemoresistant neuroblastoma cells emerge at a much higher frequency when the influence of noise is integrated across multiple components of an apoptotic signaling network. Using a JNK activity biosensor with longitudinal high-content and in vivo intravital imaging, we identify a population of stochastic, JNK-impaired, chemoresistant cells that exist because of noise within this signaling network. Furthermore, we reveal that the memory of this initially random state is retained following chemotherapy treatment across a series of in vitro, in vivo, and patient models. Using matched PDX models established at diagnosis and relapse from individual patients, we show that HDAC inhibitor priming cannot erase the memory of this resistant state within relapsed neuroblastomas but improves response in the first-line setting by restoring drug-induced JNK activity within the chemoresistant population of treatment-naïve tumors.

Dynamic regulation of RAS and RAS signaling.

RAS proteins regulate most aspects of cellular physiology. They are mutated in 30% of human cancers and 4% of developmental disorders termed Rasopathies. They cycle between active GTP-bound and inactive GDP-bound states. When active, they can interact with a wide range of effectors that control fundamental biochemical and biological processes. Emerging evidence suggests that RAS proteins are not simple on/off switches but sophisticated information processing devices that compute cell fate decisions by integrating external and internal cues. A critical component of this compute function is the dynamic regulation of RAS activation and downstream signaling that allows RAS to produce a rich and nuanced spectrum of biological outputs. We discuss recent findings how the dynamics of RAS and its downstream signaling is regulated. Starting from the structural and biochemical properties of wild-type and mutant RAS proteins and their activation cycle, we examine higher molecular assemblies, effector interactions and downstream signaling outputs, all under the aspect of dynamic regulation. We also consider how computational and mathematical modeling approaches contribute to analyze and understand the pleiotropic functions of RAS in health and disease.

B-cell and complement signature in severe hidradenitis suppurativa that does not respond to adalimumab.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disorder with significant morbidity. The pathogenesis remains incompletely understood although immune dysregulation plays an important role. It is challenging to treat and approximately 50% of patients respond clinically to adalimumab, the only licensed treatment. OBJECTIVES: To examine differences between lesional and nonlesional HS skin at baseline using bulk RNA sequencing, and to compare the transcriptome in the skin before and after 12 weeks of treatment with adalimumab. To examine transcriptomic differences between adalimumab responders and nonresponders using Hidradenitis Suppurativa Clinical Response and the International Hidradenitis Suppurativa Severity Score System (IHS4); and to compare transcriptomic differences based on disease severity (Hurley stage and IHS4). METHODS: We completed bulk RNA sequencing on lesional and nonlesional skin samples of patients before and after 12 weeks of treatment with adalimumab. RESULTS: Baseline differentially expressed genes and pathways between lesional and nonlesional skin highlighted chemokines and antimicrobial peptides produced by keratinocytes; B-cell function; T-cell-receptor, interleukin-17 and nuclear factor-κB signalling; and T-helper-cell differentiation. Transcriptomic differences were identified in lesional skin at baseline, between subsequent responders and nonresponders. Patients with severe HS who did not respond to adalimumab had enriched complement and B-cell activation pathways at baseline. In addition, logistic regression identified CCL28 in baseline lesional HS skin as a potential biomarker of treatment response. CONCLUSIONS: This highlights the potential for targeting B-cell and complement pathways in HS treatment and the potential of stratifying patients at baseline to the most suitable treatment based on the skin transcriptome. CCL28 has not previously been identified in HS skin and has potential clinical relevance due to its antimicrobial function and homing of B and T cells at epithelial surfaces. Our results provide data to inform future translational and clinical studies on therapeutics in HS.

Oncotherapeutic Strategies in Early Onset Colorectal Cancer.

Early onset colorectal cancer (EOCRC), defined as colorectal cancers in patients aged less than 50 years, is becoming an increasingly common issue, globally. Since 1994, the incidence of this condition has been rising by 2% annually. Approximately one in five patients under 50 years of age diagnosed with colorectal cancer have an underlying genetic predisposition syndrome. The detection of cancer among the other 80% of patients poses a considerable task, as there is no family history to advocate for commencing early screening in this group. Patients with EOCRC have distinct social, spiritual, fertility, and financial needs from their older counterparts that need to be addressed. This review discusses the risk factors associated with the development of EOCRC and current best practice for the management of this disease.

Targeting KRAS in Pancreatic Cancer.

Pancreatic cancer is mainly driven by mutations in the KRAS oncogene. While this cancer has shown remarkable therapy resistance, new approaches to inhibit mutated KRAS, KRAS activators and effectors show promise in breaking this therapeutic deadlock. Here, we review these innovations in therapies that target RAS signaling in pancreatic cancer from a clinical point of view. A number of promising approaches are currently in clinical trials or in clinical development. We focus on small-molecule drugs but also discuss immunotherapies and tumor vaccines.

Control of cell state transitions.

Understanding cell state transitions and purposefully controlling them is a longstanding challenge in biology. Here we present cell state transition assessment and regulation (cSTAR), an approach for mapping cell states, modelling transitions between them and predicting targeted interventions to convert cell fate decisions. cSTAR uses omics data as input, classifies cell states, and develops a workflow that transforms the input data into mechanistic models that identify a core signalling network, which controls cell fate transitions by influencing whole-cell networks. By integrating signalling and phenotypic data, cSTAR models how cells manoeuvre in Waddington's landscape1 and make decisions about which cell fate to adopt. Notably, cSTAR devises interventions to control the movement of cells in Waddington's landscape. Testing cSTAR in a cellular model of differentiation and proliferation shows a high correlation between quantitative predictions and experimental data. Applying cSTAR to different types of perturbation and omics datasets, including single-cell data, demonstrates its flexibility and scalability and provides new biological insights. The ability of cSTAR to identify targeted perturbations that interconvert cell fates will enable designer approaches for manipulating cellular development pathways and mechanistically underpinned therapeutic interventions.

CRABP2 - A novel biomarker for high-risk endometrial cancer.

OBJECTIVE: Investigate the clinical and functional implications of elevated CRABP2 expression in endometrial cancer (EC) patients. METHODS: Patients were stratified into high and low CRABP2 expression groups using a decision tree classifier. Univariate and multivariate statistical analyses determined the prognostic and clinicopathological consequences of increased CRABP2 expression. A CRABP2 gene signature was generated using differential expression analysis, and analyzed using network-based approaches. The findings were validated in The Clinical Proteomic Tumor Analysis Consortium (CPTAC), a newly generated cohort of 120 endometrial tissues, and The Cancer Dependency Map (DepMap). RESULTS: 60 (11%) patients in TCGA had high CRABP2 expression, whilst 468 (89%) had low expression. High expression was associated with serous EC, reduced overall survival, advanced stage and grade. Downstream retinoic acid receptors (RARG and RARA) were correlated with CRABP2 expression and were associated with worse prognosis in serous EC. The CRABP2 gene signature was enriched for Polycomb target gene sets, and was regulated by ELP3 and BMP7. BMP7 expression was increased in the CRABP2-high group, was associated with worse prognosis, and CRISPR-Cas9 screens revealed correlations in its cell-fitness score with CRABP2 following gene knockout. The opposite was true for ELP3, suggesting opposing effects from both master regulators. CONCLUSIONS: CRABP2 expression is associated with poor prognosis and advanced EC. The expression of RARA and RARG correlates with CRABP2 and are associated with worse prognosis in advanced histological subtypes. Polycomb target gene sets and two master regulators, ELP3 and BMP7, were identified as functionally relevant mechanisms driving aberrant CRABP2 expression.

A Systems Biology Approach to Investigate Kinase Signal Transduction Networks That Are Involved in Triple Negative Breast Cancer Resistance to Cisplatin.

Triple negative breast cancer (TNBC) remains a therapeutic challenge due to the lack of targetable genetic alterations and the frequent development of resistance to the standard cisplatin-based chemotherapies. Here, we have taken a systems biology approach to investigate kinase signal transduction networks that are involved in TNBC resistance to cisplatin. Treating a panel of cisplatin-sensitive and cisplatin-resistant TNBC cell lines with a panel of kinase inhibitors allowed us to reconstruct two kinase signalling networks that characterise sensitive and resistant cells. The analysis of these networks suggested that the activation of the PI3K/AKT signalling pathway is critical for cisplatin resistance. Experimental validation of the computational model predictions confirmed that TNBC cell lines with activated PI3K/AKT signalling are sensitive to combinations of cisplatin and PI3K/AKT pathway inhibitors. Thus, our results reveal a new therapeutic approach that is based on identifying targeted therapies that synergise with conventional chemotherapies.

Proteasomal down-regulation of the proapoptotic MST2 pathway contributes to BRAF inhibitor resistance in melanoma.

The RAS-RAF-MEK-ERK pathway is hyperactivated in most malignant melanomas, and mutations in BRAF or NRAS account for most of these cases. BRAF inhibitors (BRAFi) are highly efficient for treating patients with BRAFV600E mutations, but tumours frequently acquire resistance within a few months. Multiple resistance mechanisms have been identified, due to mutations or network adaptations that revive ERK signalling. We have previously shown that RAF proteins inhibit the MST2 proapoptotic pathway in a kinase-independent fashion. Here, we have investigated the role of the MST2 pathway in mediating resistance to BRAFi. We show that the BRAFV600E mutant protein, but not the wild-type BRAF protein, binds to MST2 inhibiting its proapoptotic signalling. Down-regulation of MST2 reduces BRAFi-induced apoptosis. In BRAFi-resistant cell lines, MST2 pathway proteins are down-regulated by ubiquitination and subsequent proteasomal degradation rendering cells refractory to MST2 pathway-induced apoptosis. Restoration of apoptosis can be achieved by increasing MST2 pathway protein expression using proteasome inhibitors. In summary, we show that the MST2 pathway plays a role in the acquisition of BRAFi resistance in melanoma.

Analysis of Alternative mRNA Splicing in Vemurafenib-Resistant Melanoma Cells.

Alternative mRNA splicing is common in cancers. In BRAF V600E-mutated malignant melanoma, a frequent mechanism of acquired resistance to BRAF inhibitors involves alternative splicing (AS) of BRAF. The resulting shortened BRAF protein constitutively dimerizes and conveys drug resistance. Here, we have analysed AS in SK-MEL-239 melanoma cells and a BRAF inhibitor (vemurafenib)-resistant derivative that expresses an AS, shortened BRAF V600E transcript. Transcriptome analysis showed differential expression of spliceosome components between the two cell lines. As there is no consensus approach to analysing AS events, we used and compared four common AS softwares based on different principles, DEXSeq, rMATS, ASpli, and LeafCutter. Two of them correctly identified the BRAF V600E AS in the vemurafenib-resistant cells. Only 12 AS events were identified by all four softwares. Testing the AS predictions experimentally showed that these overlapping predictions are highly accurate. Interestingly, they identified AS caused alterations in the expression of melanin synthesis and cell migration genes in the vemurafenib-resistant cells. This analysis shows that combining different AS analysis approaches produces reliable results and meaningful, biologically testable hypotheses.

A comparative analysis of extracellular vesicles (EVs) from human and feline plasma.

Extracellular vesicles (EVs) are nanoparticles found in all biological fluids, capable of transporting biological material around the body. Extensive research into the physiological role of EVs has led to the development of the Minimal Information for Studies of Extracellular Vesicles (MISEV) framework in 2018. This framework guides the standardisation of protocols in the EV field. To date, the focus has been on EVs of human origin. As comparative medicine progresses, there has been a drive to study similarities between diseases in humans and animals. To successfully research EVs in felines, we must validate the application of the MISEV guidelines in this group. EVs were isolated from the plasma of healthy humans and felines. EV characterisation was carried out according to the MISEV guidelines. Human and feline plasma showed a similar concentration of EVs, comparable expression of known EV markers and analogous particle to protein ratios. Mass spectrometry analyses showed that the proteomic signature of EVs from humans and felines were similar. Asymmetrical flow field flow fractionation, showed two distinct subpopulations of EVs isolated from human plasma, whereas only one subpopulation was isolated from feline plasma. Metabolomic profiling showed similar profiles for humans and felines. In conclusion, isolation, and characterisation of EVs from humans and felines show that MISEV2018 guidelines may also be applied to felines. Potential comparative medicine studies of EVs may provide a model for studying naturally occurring diseases in both humans and felines.