Insights from multi-omic modeling of neurodegeneration in xeroderma pigmentosum using an induced pluripotent stem cell system.

Xeroderma pigmentosum (XP) is caused by defective nucleotide excision repair of DNA damage. This results in hypersensitivity to ultraviolet light and increased skin cancer risk, as sunlight-induced photoproducts remain unrepaired. However, many XP patients also display early-onset neurodegeneration, which leads to premature death. The mechanism of neurodegeneration is unknown. Here, we investigate XP neurodegeneration using pluripotent stem cells derived from XP patients and healthy relatives, performing functional multi-omics on samples during neuronal differentiation. We show substantially increased levels of 5',8-cyclopurine and 8-oxopurine in XP neuronal DNA secondary to marked oxidative stress. Furthermore, we find that the endoplasmic reticulum stress response is upregulated and reversal of the mutant genotype is associated with phenotypic rescue. Critically, XP neurons exhibit inappropriate downregulation of the protein clearance ubiquitin-proteasome system (UPS). Chemical enhancement of UPS activity in XP neuronal models improves phenotypes, albeit inadequately. Although more work is required, this study presents insights with intervention potential.

Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network.

Despite technological advances in the proteomics field, sample preparation still represents the main bottleneck in mass spectrometry (MS) analysis. Bead-based protein aggregation techniques have recently emerged as an efficient, reproducible, and high-throughput alternative for protein extraction and digestion. Here, a refined paramagnetic bead-based digestion protocol is described for Opentrons® OT-2 platform (OT-2) as a versatile, reproducible, and affordable alternative for the automatic sample preparation for MS analysis. For this purpose, an artificial neural network (ANN) was applied to maximize the number of peptides without missed cleavages identified in HeLa extract by combining factors such as the quantity (µg) of trypsin/Lys-C and beads (MagReSyn® Amine), % (w/v) SDS, % (v/v) acetonitrile, and time of digestion (h). ANN model predicted the optimal conditions for the digestion of 50 µg of HeLa extract, pointing to the use of 2.5% (w/v) SDS and 300 µg of beads for sample preparation and long-term digestion (16h) with 0.15 µg Lys-C and 2.5 µg trypsin (≈1:17 ratio). Based on the results of the ANN model, the manual protocol was automated in OT-2. The performance of the automatic protocol was evaluated with different sample types, including human plasma, Arabidopsis thaliana leaves, Escherichia coli cells, and mouse tissue cortex, showing great reproducibility and low sample-to-sample variability in all cases. In addition, we tested the performance of this method in the preparation of a challenging biological fluid such as rat bile, a proximal fluid that is rich in bile salts, bilirubin, cholesterol, and fatty acids, among other MS interferents. Compared to other protocols described in the literature for the extraction and digestion of bile proteins, the method described here allowed identify 385 unique proteins, thus contributing to improving the coverage of the bile proteome.

Substitution mutational signatures in whole-genome-sequenced cancers in the UK population.

Whole-genome sequencing (WGS) permits comprehensive cancer genome analyses, revealing mutational signatures, imprints of DNA damage and repair processes that have arisen in each patient's cancer. We performed mutational signature analyses on 12,222 WGS tumor-normal matched pairs, from patients recruited via the UK National Health Service. We contrasted our results to two independent cancer WGS datasets, the International Cancer Genome Consortium (ICGC) and Hartwig Foundation, involving 18,640 WGS cancers in total. Our analyses add 40 single and 18 double substitution signatures to the current mutational signature tally. Critically, we show for each organ, that cancers have a limited number of 'common' signatures and a long tail of 'rare' signatures. We provide a practical solution for utilizing this concept of common versus rare signatures in future analyses.

Targeting the DNA Damage Response Pathways and Replication Stress in Colorectal Cancer.

PURPOSE: Genomic instability is a hallmark of cancer and targeting DNA damage response (DDR) is emerging as a promising therapeutic strategy in different solid tumors. The effectiveness of targeting DDR in colorectal cancer has not been extensively explored. EXPERIMENTAL DESIGN: We challenged 112 cell models recapitulating the genomic landscape of metastatic colorectal cancer with ATM, ATR, CHK1, WEE1, and DNA-PK inhibitors, in parallel with chemotherapeutic agents. We focused then on ATR inhibitors (ATRi) and, to identify putative biomarkers of response and resistance, we analyzed at multiple levels colorectal cancer models highly sensitive or resistant to these drugs. RESULTS: We found that around 30% of colorectal cancers, including those carrying KRAS and BRAF mutations and unresponsive to targeted agents, are sensitive to at least one DDR inhibitor. By investigating potential biomarkers of response to ATRi, we found that ATRi-sensitive cells displayed reduced phospho-RPA32 foci at basal level, while ATRi-resistant cells showed increased RAD51 foci formation in response to replication stress. Lack of ATM and RAD51C expression was associated with ATRi sensitivity. Analysis of mutational signatures and HRDetect score identified a subgroup of ATRi-sensitive models. Organoids derived from patients with metastatic colorectal cancer recapitulated findings obtained in cell lines. CONCLUSIONS: In conclusion, a subset of colorectal cancers refractory to current therapies could benefit from inhibitors of DDR pathways and replication stress. A composite biomarker involving phospho-RPA32 and RAD51 foci, lack of ATM and RAD51C expression, as well as analysis of mutational signatures could be used to identify colorectal cancers likely to respond to ATRi.

Preclinical In Vivo Validation of the RAD51 Test for Identification of Homologous Recombination-Deficient Tumors and Patient Stratification.

PARP inhibitors (PARPi) are approved drugs for platinum-sensitive, high-grade serous ovarian cancer (HGSOC) and for breast, prostate, and pancreatic cancers (PaC) harboring genetic alterations impairing homologous recombination repair (HRR). Detection of nuclear RAD51 foci in tumor cells is a marker of HRR functionality, and we previously established a test to detect RAD51 nuclear foci. Here, we aimed to validate the RAD51 score cut off and compare the performance of this test to other HRR deficiency (HRD) detection methods. Laboratory models from BRCA1/BRCA2-associated breast cancer, HGSOC, and PaC were developed and evaluated for their response to PARPi and cisplatin. HRD in these models and patient samples was evaluated by DNA sequencing of HRR genes, genomic HRD tests, and RAD51 foci detection. We established patient-derived xenograft models from breast cancer (n = 103), HGSOC (n = 4), and PaC (n = 2) that recapitulated patient HRD status and treatment response. The RAD51 test showed higher accuracy than HRR gene mutations and genomic HRD analysis for predicting PARPi response (95%, 67%, and 71%, respectively). RAD51 detection captured dynamic changes in HRR status upon acquisition of PARPi resistance. The accuracy of the RAD51 test was similar to HRR gene mutations for predicting platinum response. The predefined RAD51 score cut off was validated, and the high predictive value of the RAD51 test in preclinical models was confirmed. These results collectively support pursuing clinical assessment of the RAD51 test in patient samples from randomized trials testing PARPi or platinum-based therapies. SIGNIFICANCE: This work demonstrates the high accuracy of a histopathology-based test based on the detection of RAD51 nuclear foci in predicting response to PARPi and cisplatin.

Analysis of T cell receptor clonotypes in tumor microenvironment identifies shared cancer-type-specific signatures.

Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias toward the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood, but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus-driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (i.e., viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer but, in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages, and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific pattern motifs, and these motifs were uniquely found to each cancer type. This suggests that they may be enriched for specificity to common antigens found in the tumor microenvironment of different cancers. The identification of shared TCRs in infiltrating tumor T cells not only adds to our understanding of the tumor-adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

Small-molecule inhibition of METTL3 as a strategy against myeloid leukaemia.

N6-methyladenosine (m6A) is an abundant internal RNA modification1,2 that is catalysed predominantly by the METTL3-METTL14 methyltransferase complex3,4. The m6A methyltransferase METTL3 has been linked to the initiation and maintenance of acute myeloid leukaemia (AML), but the potential of therapeutic applications targeting this enzyme remains unknown5-7. Here we present the identification and characterization of STM2457, a highly potent and selective first-in-class catalytic inhibitor of METTL3, and a crystal structure of STM2457 in complex with METTL3-METTL14. Treatment of tumours with STM2457 leads to reduced AML growth and an increase in differentiation and apoptosis. These cellular effects are accompanied by selective reduction of m6A levels on known leukaemogenic mRNAs and a decrease in their expression consistent with a translational defect. We demonstrate that pharmacological inhibition of METTL3 in vivo leads to impaired engraftment and prolonged survival in various mouse models of AML, specifically targeting key stem cell subpopulations of AML. Collectively, these results reveal the inhibition of METTL3 as a potential therapeutic strategy against AML, and provide proof of concept that the targeting of RNA-modifying enzymes represents a promising avenue for anticancer therapy.

A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies.

Mutational signatures are patterns of mutations that arise during tumorigenesis. We present an enhanced, practical framework for mutational signature analyses. Applying these methods on 3,107 whole genome sequenced (WGS) primary cancers of 21 organs reveals known signatures and nine previously undescribed rearrangement signatures. We highlight inter-organ variability of signatures and present a way of visualizing that diversity, reinforcing our findings in an independent analysis of 3,096 WGS metastatic cancers. Signatures with a high level of genomic instability are dependent on TP53 dysregulation. We illustrate how uncertainty in mutational signature identification and assignment to samples affects tumor classification, reinforcing that using multiple orthogonal mutational signature data is not only beneficial, it is essential for accurate tumor stratification. Finally, we present a reference web-based tool for cancer and experimentally-generated mutational signatures, called Signal (https://signal.mutationalsignatures.com), that also supports performing mutational signature analyses.

Dramatic response of metastatic cutaneous angiosarcoma to an immune checkpoint inhibitor in a patient with xeroderma pigmentosum: whole-genome sequencing aids treatment decision in end-stage disease.

"Mutational signatures" are patterns of mutations that report DNA damage and subsequent repair processes that have occurred. Whole-genome sequencing (WGS) can provide additional information to standard diagnostic techniques and can identify therapeutic targets. A 32-yr-old male with xeroderma pigmentosum developed metastatic angiosarcoma that was unresponsive to three lines of conventional sarcoma therapies. WGS was performed on his primary cancer revealing a hypermutated tumor, including clonal ultraviolet radiation-induced mutational patterns (Signature 7) and subclonal signatures of mutated DNA polymerase epsilon (POLE) (Signature 10). These signatures are associated with response to immune checkpoint blockade. Immunohistochemistry confirmed high PD-L1 expression in metastatic deposits. The anti-PD-1 monoclonal antibody pembrolizumab was commenced off-label given the POLE mutation and high mutational load. After four cycles, there was a significant reduction in his disease with almost complete resolution of the metastatic deposits. This case highlights the importance of WGS in the analysis, interpretation, and treatment of cancers. We anticipate that as WGS becomes integral to the cancer diagnostic pathway, treatments will be stratified to the individual based on their unique genomic and/or transcriptomic profile, enhancing classical approaches of histologically driven treatment decisions.

Genetic modification of primary human B cells to model high-grade lymphoma.

Sequencing studies of diffuse large B cell lymphoma (DLBCL) have identified hundreds of recurrently altered genes. However, it remains largely unknown whether and how these mutations may contribute to lymphomagenesis, either individually or in combination. Existing strategies to address this problem predominantly utilize cell lines, which are limited by their initial characteristics and subsequent adaptions to prolonged in vitro culture. Here, we describe a co-culture system that enables the ex vivo expansion and viral transduction of primary human germinal center B cells. Incorporation of CRISPR/Cas9 technology enables high-throughput functional interrogation of genes recurrently mutated in DLBCL. Using a backbone of BCL2 with either BCL6 or MYC, we identify co-operating genetic alterations that promote growth or even full transformation into synthetically engineered DLBCL models. The resulting tumors can be expanded and sequentially transplanted in vivo, providing a scalable platform to test putative cancer genes and to create mutation-directed, bespoke lymphoma models.

Refinement of two-dimensional electrophoresis for vitreous proteome profiling using an artificial neural network.

Despite technological advances, two-dimensional electrophoresis (2DE) of biological fluids, such as vitreous, remains a major challenge. In this study, artificial neural network was applied to optimize the recovery of vitreous proteins and its detection by 2DE analysis through the combination of several solubilizing agents (CHAPS, Genapol, DTT, IPG buffer), temperature, and total voltage. The highest protein recovery (94.9% ± 4.5) was achieved using 4% (w/v) CHAPS, 0.1% (v/v) Genapol, 20 mM DTT, and 2% (v/v) IPG buffer. Two iterations were required to achieve an optimized response (580 spots) using 4% (w/v) CHAPS, 0.2% (v/v) Genapol, 60 mM DTT, and 0.5% (v/v) IPG buffer at 35 kVh and 25 °C, representing a 2.4-fold improvement over the standard initial conditions of the experimental design. The analysis of depleted vitreous using the optimized protocol resulted in an additional 1.3-fold increment in protein detection over the optimal output, with an average of 761 spots detected in vitreous from different vitreoretinopathies. Our results clearly indicate the importance of combining the appropriate amount of solubilizing agents with a suitable control of the temperature and voltage to obtain high-quality gels. The high-throughput of this model provides an effective starting point for the optimization of 2DE protocols. This experimental design can be adapted to other types of matrices. Graphical abstract.

SRPK1 maintains acute myeloid leukemia through effects on isoform usage of epigenetic regulators including BRD4.

We recently identified the splicing kinase gene SRPK1 as a genetic vulnerability of acute myeloid leukemia (AML). Here, we show that genetic or pharmacological inhibition of SRPK1 leads to cell cycle arrest, leukemic cell differentiation and prolonged survival of mice transplanted with MLL-rearranged AML. RNA-seq analysis demonstrates that SRPK1 inhibition leads to altered isoform levels of many genes including several with established roles in leukemogenesis such as MYB, BRD4 and MED24. We focus on BRD4 as its main isoforms have distinct molecular properties and find that SRPK1 inhibition produces a significant switch from the short to the long isoform at the mRNA and protein levels. This was associated with BRD4 eviction from genomic loci involved in leukemogenesis including BCL2 and MYC. We go on to show that this switch mediates at least part of the anti-leukemic effects of SRPK1 inhibition. Our findings reveal that SRPK1 represents a plausible new therapeutic target against AML.

Glutaminolysis is a metabolic dependency in FLT3ITD acute myeloid leukemia unmasked by FLT3 tyrosine kinase inhibition.

FLT3 internal tandem duplication (FLT3ITD) mutations are common in acute myeloid leukemia (AML) associated with poor patient prognosis. Although new-generation FLT3 tyrosine kinase inhibitors (TKI) have shown promising results, the outcome of FLT3ITD AML patients remains poor and demands the identification of novel, specific, and validated therapeutic targets for this highly aggressive AML subtype. Utilizing an unbiased genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screen, we identify GLS, the first enzyme in glutamine metabolism, as synthetically lethal with FLT3-TKI treatment. Using complementary metabolomic and gene-expression analysis, we demonstrate that glutamine metabolism, through its ability to support both mitochondrial function and cellular redox metabolism, becomes a metabolic dependency of FLT3ITD AML, specifically unmasked by FLT3-TKI treatment. We extend these findings to AML subtypes driven by other tyrosine kinase (TK) activating mutations and validate the role of GLS as a clinically actionable therapeutic target in both primary AML and in vivo models. Our work highlights the role of metabolic adaptations as a resistance mechanism to several TKI and suggests glutaminolysis as a therapeutically targetable vulnerability when combined with specific TKI in FLT3ITD and other TK activating mutation-driven leukemias.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology.

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple-to-use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257).

Erratum: CamOptimus: a tool for exploiting complex adaptive evolution to optimise experiments and processes in biotechnology.

[This corrects the article DOI: 10.1099/mic.0.000477.].

Development and validation of a comprehensive genomic diagnostic tool for myeloid malignancies.

The diagnosis of hematologic malignancies relies on multidisciplinary workflows involving morphology, flow cytometry, cytogenetic, and molecular genetic analyses. Advances in cancer genomics have identified numerous recurrent mutations with clear prognostic and/or therapeutic significance to different cancers. In myeloid malignancies, there is a clinical imperative to test for such mutations in mainstream diagnosis; however, progress toward this has been slow and piecemeal. Here we describe Karyogene, an integrated targeted resequencing/analytical platform that detects nucleotide substitutions, insertions/deletions, chromosomal translocations, copy number abnormalities, and zygosity changes in a single assay. We validate the approach against 62 acute myeloid leukemia, 50 myelodysplastic syndrome, and 40 blood DNA samples from individuals without evidence of clonal blood disorders. We demonstrate robust detection of sequence changes in 49 genes, including difficult-to-detect mutations such as FLT3 internal-tandem and mixed-lineage leukemia (MLL) partial-tandem duplications, and clinically significant chromosomal rearrangements including MLL translocations to known and unknown partners, identifying the novel fusion gene MLL-DIAPH2 in the process. Additionally, we identify most significant chromosomal gains and losses, and several copy neutral loss-of-heterozygosity mutations at a genome-wide level, including previously unreported changes such as homozygosity for DNMT3A R882 mutations. Karyogene represents a dependable genomic diagnosis platform for translational research and for the clinical management of myeloid malignancies, which can be readily adapted for use in other cancers.

An artificial neural network for membrane-bound catechol-O-methyltransferase biosynthesis with Pichia pastoris methanol-induced cultures.

BACKGROUND: Membrane proteins are important drug targets in many human diseases and gathering structural information regarding these proteins encourages the pharmaceutical industry to develop new molecules using structure-based drug design studies. Specifically, membrane-bound catechol-O-methyltransferase (MBCOMT) is an integral membrane protein that catalyzes the methylation of catechol substrates and has been linked to several diseases such as Parkinson's disease and Schizophrenia. Thereby, improvements in the clinical outcome of the therapy to these diseases may come from structure-based drug design where reaching MBCOMT samples in milligram quantities are crucial for acquiring structural information regarding this target protein. Therefore, the main aim of this work was to optimize the temperature, dimethylsulfoxide (DMSO) concentration and the methanol flow-rate for the biosynthesis of recombinant MBCOMT by Pichia pastoris bioreactor methanol-induced cultures using artificial neural networks (ANN). RESULTS: The optimization trials intended to evaluate MBCOMT expression by P. pastoris bioreactor cultures led to the development of a first standard strategy for MBCOMT bioreactor biosynthesis with a batch growth on glycerol until the dissolved oxygen spike, 3 h of glycerol feeding and 12 h of methanol induction. The ANN modeling of the aforementioned fermentation parameters predicted a maximum MBCOMT specific activity of 384.8 nmol/h/mg of protein at 30°C, 2.9 mL/L/H methanol constant flow-rate and with the addition of 6% (v/v) DMSO with almost 90% of healthy cells at the end of the induction phase. These results allowed an improvement of MBCOMT specific activity of 6.4-fold in comparison to that from the small-scale biosynthesis in baffled shake-flasks. CONCLUSIONS: The ANN model was able to describe the effects of temperature, DMSO concentration and methanol flow-rate on MBCOMT specific activity, as shown by the good fitness between predicted and observed values. This experimental procedure highlights the potential role of chemical chaperones such as DMSO in improving yields of recombinant membrane proteins with a different topology than G-coupled receptors. Finally, the proposed ANN shows that the manipulation of classic fermentation parameters coupled with the addition of specific molecules can open and reinforce new perspectives in the optimization of P. pastoris bioprocesses for membrane proteins biosynthesis.

Dynamic metabolic modelling of volatile fatty acids conversion to polyhydroxyalkanoates by a mixed microbial culture.

In this work, we present a dynamic metabolic model that describes the uptake of complex mixtures of volatile fatty acids (VFA) and respective conversion into PHA by mixed microbial cultures (MMC). This model builds upon a previously published flux balance analysis model [1] that identified the minimization of TCA cycle activity as the key metabolic objective to predict PHA storage fluxes and respective composition. The model was calibrated either with experimental data of PHA production from fermented sugar cane molasses or from synthetic mixtures of VFA. All PHA production experiments were performed using a MMC selected with fermented sugar cane molasses under feast and famine regimen. The model was able to capture the process dynamics denoted by an excellent fit between experimental and computed time profiles of concentrations with the regression coefficients always above 0.92. The introduced VFA uptake regulatory factor reflects the decrease of acetyl-CoA and propionyl-CoA available to TCA cycle in conformity with the hypothesis that the minimization of TCA cycle is a key metabolic objective for MMC subjected to feast and famine regimen for the maximization of PHA production.