Biology subjects

Haupt, S.

Publications and source records attributed to Haupt, S..

7 recordsLinked to original sources

bioRxiv2022

Machine learning-aided multidimensional phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons

Combining multiple Parkinsons disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic (mDA) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control and genetically unrelated iPSCs into mDA neurons. Using automated fluorescence microscopy in 384-well plate format, we identified elevated levels of -synuclein and Serine 129 phosphorylation (pS129), reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDA neurons according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or -synuclein levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient derived SNCA gene triplication mDA neuronal model. This phenotyping and classification strategy improves the exploitability of mDA neurons for disease modelling and the identification of novel PD drug targets.

neuroscience↗

bioRxiv2020

Computational model investigates the evolution of colonic crypts during Lynch syndrome carcinogenesis

Lynch syndrome (LS), the most common inherited colorectal cancer (CRC) syndrome, increases the cancer risk in affected individuals. LS is caused by pathogenic germline variants in one of the DNA mismatch repair (MMR) genes, complete inactivation of which causes numerous mutations in affected cells. As CRC is believed to originate in colonic crypts, understanding the intra-crypt dynamics caused by mutational processes is essential for a complete picture of LS CRC and may have significant implications for cancer prevention. We propose a computational model describing the evolution of colonic crypts during LS carcinogenesis. Extending existing modeling approaches for the non-Lynch scenario, we incorporated MMR deficiency and implemented recent experimental data demonstrating that somatic CTNNB1 mutations are common drivers of LS-associated CRCs, if affecting both alleles of the gene. Further, we simulated the effect of different mutations on the entire crypt, distinguishing non-transforming and transforming mutations. As an example, we analyzed the spread of mutations in the genes APC and CTNNB1, which are frequently mutated in LS tumors, as well as of MMR deficiency itself. We quantified each mutations potential for monoclonal conversion and investigated the influence of the cell location and of stem cell dynamics on mutation spread. The in silico experiments underline the importance of stem cell dynamics for the overall crypt evolution. Further, simulating different mutational processes is essential in LS since mutations without survival advantages (the MMR deficiency-inducing second hit) play a key role. The effect of other mutations can be simulated with the proposed model. Our results provide first mathematical clues towards more effective surveillance protocols for LS carriers.

cancer biology↗

bioRxiv2020

Genome-wide CRISPR screens reveal APR-246 (Eprenetapopt) triggers ferroptosis and inhibits iron-sulfur cluster biogenesis

The mechanisms by which cells respond and adapt to oxidative stress are largely unknown but are key to developing a rationale for cancer therapies that target antioxidant pathways. APR-246 is a mutant-p53 targeted therapeutic currently under clinical investigation in myeloid dysplastic syndrome (MDS) and acute myeloid leukemia1. Whilst the mechanism of action of APR-246 is thought to be reactivation of wild-type p53 activity through covalent modification of cysteine residues in the core domain of mutant-p53 protein2,3, here we report that the anti-neoplastic capacity of APR-246 lies predominantly in the conjugation of free cysteine. Genome-wide CRISPR perturbation screening, metabolite profiling and proteomics in response to APR-246 treatment in mutant-p53 cancer cells highlighted the role of GSH and mitochondrial metabolism in determining APR-246 efficacy. APR-246 sensitivity was increased through loss of key enzymes in mitochondrial one-carbon metabolism, SHMT2 and MTHFD1L, due to diminished glycine supply for de novo GSH synthesis. Critically, we show that APR-246 induces iron-dependent, apoptotic machinery-independent cell death, ferroptosis. Whole-cell proteomics analyses indicated an upregulation of proteins involved in iron-sulfur cluster biogenesis (eg. FDX1). GSH, acetyl-CoA and NADH levels were also depleted in APR-246 treated cells. Importantly, we found that APR-246 inhibits iron-sulfur cluster biogenesis in the mitochondria of cancer cells through cysteine conjugation. This work not only details novel determinants of APR-246 activity in cancer cells, but also provides a clinical roadmap for targeting antioxidant pathways in tumours - beyond targeting mutant-p53 tumours. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/398867v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@11155f8org.highwire.dtl.DTLVardef@1231cb7org.highwire.dtl.DTLVardef@324881org.highwire.dtl.DTLVardef@136146f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

SLC7A11 is a superior determinant of APR-246 (Eprenetapopt) response than TP53 mutation status

PurposeAPR-246 (Eprenetapopt) is in clinical development with a focus on haematological malignancies and is marketed as a mutant-p53 reactivation therapy. Currently, the detection of at least one TP53 mutation is an inclusion criterion for patient selection into most clinical trials. Preliminary results from our phase Ib/II clinical trial investigating APR-246 combined with combination chemotherapy (cisplatin and 5-Fluorouracil) in metastatic oesophageal cancer, together with previous pre-clinical studies, indicate that TP53 mutation status alone may not be a sufficient biomarker for response to APR-246. This study aimed to identify a robust biomarker for response to APR-246. MethodsCorrelation analysis of the PRIMA-1 activity (lead compound to APR-246) with mutational status, gene expression, protein expression and metabolite abundance across over 800 cancer cell lines was performed. Functional validation and a boutique siRNA screen of over 750 redox-related genes were also conducted. ResultsTP53 mutation status was not predictive of response to APR-246. The expression of SLC7A11, the cystine/glutamate transporter, was identified as a superior determinant of response to APR-246. Genetic regulators of SLC7A11, including ATF4, MDM2, wild-type p53 and c-Myc were confirmed to also regulate cancer cell sensitivity to APR-246. ConclusionsSLC7A11 expression is the major determinant of sensitivity to APR-246 and should be utilised as a predictive biomarker in future clinical investigation of APR-246.

cancer biology↗

bioRxiv2020

Mathematical Modeling of Multiple Pathways in Colorectal Carcinogenesis using Dynamical Systems with Kronecker Structure

Like many other tumors, colorectal cancers develop through multiple pathways containing different driver mutations. This is also true for colorectal carcinogenesis in Lynch syndrome, the most common inherited colorectal cancer syndrome. However, a comprehensive understanding of Lynch syndrome tumor evolution which allows for tailored clinical treatment and even prevention is still lacking. We suggest a linear autonomous dynamical system modeling the evolution of the different pathways. Starting with the gene mutation graphs of the driver genes, we formulate three key assumptions about how these different mutations might be combined. This approach leads to a dynamical system that is built by the Kronecker sum of the adjacency matrices of the gene mutation graphs. This Kronecker structure makes the dynamical system amenable to a thorough mathematical analysis and medical interpretation, even if the number of incorporated genes or possible mutation states is increased. For the case that some of the mathematical key assumptions are not satisfied, we explain possible extensions to our model. Additionally, improved bio-medical measurements or novel medical insights can be integrated into the model in a straightforward manner, as all parameters in the model have a biological interpretation. Modifications of the model are able to account for other forms of colorectal carcinogenesis, such as Lynch-like and familial adenomatous polyposis cases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=49 SRC="FIGDIR/small/250175v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1286ef8org.highwire.dtl.DTLVardef@18d95d2org.highwire.dtl.DTLVardef@67190corg.highwire.dtl.DTLVardef@9d640f_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract:C_FLOATNO From the Medical Hypothesis Over the Modeling Approach To the Mathematical Structure.The medical hypothesis of multiple pathways in carcinogenesis is widely known for various types of cancer. Left: We present a model for this phenomenon at the example of Lynch syndrome, the most common inherited colorectal cancer syndrome, with specific key driver events in the MMR genes, CTNNB1, APC, KRAS and TP53. Middle: This current medical understanding of carcinogenesis is translated into a mathematical model using a specific dynamical system, which can be represented by a graph structure, where each vertex in the graph represents a genotypic state and the edges correspond to the transition probabilities between those states. Starting with all colonic crypts in the state of all genes being wild-type and a single MMR germline mutation due to Lynch syndrome, we are interested in the distribution of the crypts among the graph at different ages of the patient in order to obtain estimates for the number of crypts in specific states, e.g. adenomatous or cancerous states. Right: The underlying matrix of the dynamical system makes use of the Kronecker sum and product. It is a sparse upper triangular matrix accounting for the assumption that mutations cannot be reverted. This allows fast numerical solving by using the matrix exponential. Each nonzero entry of the matrix represents a connection between genotypic states in the graph. C_FIG

cancer biology↗

bioRxiv2020

MDM2 Inhibition in Combination with Endocrine Therapy and CDK4/6 Inhibition for the Treatment of ER-Positive Breast Cancer.

BackgroundResistance to endocrine therapy is a major clinical challenge in the management of estrogen receptor (ER)-positive breast cancer. In this setting p53 is frequently wildtype and its activity may be suppressed via upregulation of its key regulator MDM2. This underlies our rationale to evaluate MDM2 inhibition as a therapeutic strategy in treatment resistant ER-positive breast cancer. MethodsWe used the MDM2 inhibitor NVP-CGM097 to treat in vitro and in vivo models alone and in combination with fulvestrant or palbociclib. We perform cell viability, cell cycle, apoptosis and senescence assays to evaluate antitumor effects in p53 wildtype and p53 mutant ER positive cell lines (MCF-7, ZR75-1, T-47D) and MCF-7 lines resistant to endocrine therapy and to CDK4/6 inhibition. We further assess the drug effects in patient-derived xenograft (PDX) models of endocrine-sensitive and -resistant ER positive breast cancer. ResultsWe demonstrate that MDM2 inhibition results in cell cycle arrest and increased apoptosis in p53-wildtype in vitro and in vivo breast cancer models, leading to potent anti-tumour activity. We find that endocrine therapy or CDK4/6 inhibition synergises with MDM2 inhibition but does not further enhance apoptosis. Instead, combination treatments result in profound regulation of cell cycle-related transcriptional programmes, with synergy achieved through increased antagonism of cell cycle progression. Combination therapy pushes cell lines resistant to fulvestrant or palbociclib to become senescent and significantly reduces tumour growth in a fulvestrant resistant patient derived xenograft model. ConclusionsWe conclude that MDM2 inhibitors in combination with ER degraders or CDK4/6 inhibitors represent a rational strategy for treating advanced, endocrine resistant ER-positive breast cancer, operating through synergistic activation of cell cycle co-regulatory programs.

cancer biology↗

bioRxiv2019

The shared neoantigen landscape of MSI cancers reflects immunoediting during tumor evolution

The immune system can recognize and attack cancer cells, especially those with a high load of mutation-induced neoantigens. Such neoantigens are particularly abundant in DNA mismatch repair (MMR)-deficient, microsatellite-unstable (MSI) cancers. MMR deficiency leads to insertion/deletion (indel) mutations at coding microsatellites (cMS) and to neoantigen-inducing translational frameshifts. The abundance of mutational neoantigens renders MSI cancers sensitive to immune checkpoint blockade. However, the neoantigen landscape of MMR-deficient cancers has not yet been systematically mapped. In the present study, we used a novel tool to monitor neoantigen-inducing indel mutations in MSI colorectal and endometrial cancer. Our results show that MSI cancers share several highly immunogenic neoantigens that result from specific, recurrent indel mutation events. Notably, the frequency of such indel mutations was negatively correlated to the predicted immunogenicity of the resulting neoantigens. These observations suggest continuous immunoediting of emerging MMR-deficient cells during tumor evolution.\n\nOne sentence summaryQuantitative indel mutation analysis reveals evidence of immune selection in mismatch repair-deficient cancers

cancer biology↗