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Supplementary Figures 1-7. Supplementary Figure 1: Assembly of the PWD genome and alignment to the C57BL/6 genome. Supplementary Figure 2: RNA-seq read assignment. Supplementary Figure 3: MeDIP-seq quality controls. Supplementary Figure 4: Histology and distribution of tumors in B6 x PWD consomic mice. Supplementary Figure 5: Transcriptome analyses identify modifier candidate genes on other chromosomes than chromosome 5. Supplementary Figure 6: Strain-specific DNA methylation on chromosome 5 is correlated to CpG availability. Supplementary Figure 7: Assessment of cell types in the intestinal crypt.

Genetic predisposition affects the penetrance of tumor-initiating mutations, such as APC mutations that stabilize β-catenin and cause intestinal tumors in mice and humans. However, the mechanisms involved in genetically predisposed penetrance are not well understood. Here, we analyzed tumor multiplicity and gene expression in tumor-prone ApcMin/+ mice on highly variant C57BL/6J (B6) and PWD/Ph (PWD) genetic backgrounds. (B6 × PWD) F1 APCMin offspring mice were largely free of intestinal adenoma, and several chromosome substitution (consomic) strains carrying single PWD chromosomes on the B6 genetic background displayed reduced adenoma numbers. Multiple dosage-dependent modifier loci on PWD chromosome 5 each contributed to tumor suppression. Activation of β-catenin–driven and stem cell–specific gene expression in the presence of ApcMin or following APC loss remained moderate in intestines carrying PWD chromosome 5, suggesting that PWD variants restrict adenoma initiation by controlling stem cell homeostasis. Gene expression of modifier candidates and DNA methylation on chromosome 5 were predominantly cis controlled and largely reflected parental patterns, providing a genetic basis for inheritance of tumor susceptibility. Human SNP variants of several modifier candidates were depleted in colorectal cancer genomes, suggesting that similar mechanisms may also affect the penetrance of cancer driver mutations in humans. Overall, our analysis highlights the strong impact that multiple genetic variants acting in networks can exert on tumor development.Significance:These findings in mice show that, in addition to accidental mutations, cancer risk is determined by networks of individual gene variants.

Supplementary tables 1-7. Supplementary Table 1: GSEA signatures and references (Wnt target genes are taken from the HALLMARK Signature). Supplementary Table 2: 58 differentially expressed genes on chromosome 5, B6 vs C5 APC min normal intestine. Supplementary Table 3: 116 differentially expressed genes not located on chromosome 5, B6 vs C5 APC min normal intestine. Supplementary table 4: Differentially expressed genes on chromosome 5 regulated in cis, trans, or both. Supplementary table 5: Candidate modifier genes differentially expressed between B6 or PWD chromosome 5. Supplementary Table 6: Polymorphisms in human orthologs of mouse genes located on chromosome 5, polymorphic between B6 and PWD, and expressed in the intestine. Supplementary Table 7: PWD polymorphisms on chr5 in genes that are expressed in the intestine and/or in adenoma.

Type 2 diabetes (T2D) represents a multifactorial metabolic disease with a strong genetic predisposition. Despite elaborate efforts in identifying the genetic variants determining individual susceptibility towards T2D, the majority of genetic factors driving disease development remain poorly understood. With the aim to identify novel T2D risk genes we previously generated an N2 outcross population using the two inbred mouse strains New Zealand obese (NZO) and C3HeB/FeJ (C3H). A linkage study performed in this population led to the identification of the novel T2D-associated quantitative trait locus (QTL) Nbg15 (NZO blood glucose on chromosome 15, Logarithm of odds (LOD) 6.6). In this study we used a combined approach of positional cloning, gene expression analyses and in silico predictions of DNA polymorphism on gene/protein function to dissect the genetic variants linking Nbg15 to the development of T2D. Moreover, we have generated congenic strains that associated the distal sublocus of Nbg15 to mechanisms altering pancreatic beta cell function. In this sublocus, Cbx6, Fam135b and Kdelr3 were nominated as potential causative genes associated with the Nbg15 driven effects. Moreover, a putative mutation in the Kdelr3 gene from NZO was identified, negatively influencing adaptive responses associated with pancreatic beta cell death and induction of endoplasmic reticulum stress. Importantly, knockdown of Kdelr3 in cultured Min6 beta cells altered insulin granules maturation and pro-insulin levels, pointing towards a crucial role of this gene in islets function and T2D susceptibility.

Erectile dysfunction (ED) is a big issue in various populations with up to 30% of young men suffering from this condition. Unfortunately, treatment schemes are currently mainly focused on elderly patients with chronic disorders. In younger patients, ED is more a vascular problem, which affects the storage capacity of the penis. The impact of penile blood supply on erectile function was recognized some 500 years ago. At the turn of the twentieth century, the first results of penile venous ligation were published. Simple isolated ligation of the deep dorsal vein in humans for ED due to venous leak is currently not recommended, due to some reported low long-term success rates. This was, as shown in several literature reports, obviously due to insufficient technical possibilities. Technical development in imaging and vascular and endovascular treatment have dramatically evolved our understanding of this underlying condition in the past 20 years and turned this disease into a long-term treatable condition. The current state-of-the-art work-up of the underlying condition, using the newest imaging technologies with color Doppler ultrasound and CT scan with additional three-dimensional reconstruction, is to show the surgeon exactly the points to focus on. Additionally, a so-called corporo-venous insufficiency can be recognized as a mainly combined condition, affecting peripheral and more proximal drainage pathways at the same time.

Molecular interactions are key drivers of biological function. Providing interaction resources to the research community is important since they allow functional interpretation and network-based analysis of molecular data. ConsensusPathDB (http://consensuspathdb.org) is a meta-database combining interactions of diverse types from 31 public resources for humans, 16 for mice and 14 for yeasts. Using ConsensusPathDB, researchers commonly evaluate lists of genes, proteins and metabolites against sets of molecular interactions defined by pathways, Gene Ontology and network neighborhoods and retrieve complex molecular neighborhoods formed by heterogeneous interaction types. Furthermore, the integrated protein–protein interaction network is used as a basis for propagation methods. Here, we present the 2022 update of ConsensusPathDB, highlighting content growth, additional functionality and improved database stability. For example, the number of human molecular interactions increased to 859 848 connecting 200 499 unique physical entities such as genes/proteins, metabolites and drugs. Furthermore, we integrated regulatory datasets in the form of transcription factor–, microRNA– and enhancer–gene target interactions, thus providing novel functionality in the context of overrepresentation and enrichment analyses. We specifically emphasize the use of the integrated protein–protein interaction network as a scaffold for network inferences, present topological characteristics of the network and discuss strengths and shortcomings of such approaches.

Type 2 diabetes (T2D) represents a multifactorial metabolic disease with a strong genetic predisposition. Despite elaborate efforts in identifying the genetic variants determining individual susceptibility towards T2D, the majority of genetic factors driving disease development remain poorly understood. With the aim to identify novel T2D risk genes we previously generated an N2 outcross population using the two inbred mouse strains New Zealand obese (NZO) and C3HeB/FeJ (C3H). A linkage study performed in this population led to the identification of the novel T2D-associated quantitative trait locus (QTL)

Bacteriocins are gaining immense importance in therapeutics since they show significant antibacterial potential. This study reports the bacteriocin KAE01 from

Many methods for haplotyping have materialized, but their application on a significant scale has been rare to date. Here we summarize analyses that were carried out in 1092 genomes from the 1000 Genomes Consortium and validated in an unprecedented number of 184 PGP genomes that have been experimentally haplotype-resolved by application of the Long-Fragment Read (LFR) technology. These analyses provided first insights into the diplotypic nature of human genomes and its potential functional implications. Thus, protein-changing variants were not randomly distributed between the two homologues of 18,121 autosomal protein-coding genes but occurred significantly more frequently in cis than in trans configurations in virtually each of the 1276 phased genomes. This resulted in global cis/trans ratios of ~60:40, establishing "cis abundance" as a universal characteristic of diploid human genomes. This phenomenon was based on two different classes of genes, a larger one exhibiting cis configurations of protein-changing variants in excess, so-called "cis-abundant" genes, and a smaller one of "trans-abundant" genes. These two gene classes, which together constitute a common diplotypic exome, were further functionally distinguished by means of gene ontology (GO) and pathway enrichment analysis. Moreover, they were distinguishable in terms of their effects on the human interactome, where they constitute distinct cis and trans modules, as shown with network propagation on a large integrated protein-protein interaction network. These analyses, recently performed with updated database and analysis tools, further consolidated the characterization of cis- and trans-abundant genes while expanding previous results. In this chapter, we present the key results along with the materials and methods to motivate readers to investigate these findings independently and gain further insights into the diplotypic nature of genes and genomes.

Long-read transcriptome sequencing (LRTS) holds the promise to refine our understanding of alternative splicing, however, the nature of splicing is highly complex, and computational tools need to cope with this complexity by maximum flexibility at different steps of the work-flow. For this purpose we developed IsoTools, a Python-based LRTS analysis package. IsoTools provides broad functionality for transcriptome reconstruction and quantification of isoforms. Additionally, we implemented a graph-based method for the identification of alternative splicing events and a statistical approach based on the beta-binomial distribution for the detection of differential events. To demonstrate our methods, we generated PacBio LRTS data of human hepatocytes treated with the HDAC inhibitor valproic acid. Contrasted with short read RNA-seq, this analysis shows that LRTS provides valuable additional insights for a better understanding of alternative splicing, in particular with respect to complex novel and differential splicing patterns. IsoTools is available at https://github.com/MatthiasLienhard/isotools.

Background: We recently showed that a combined solution containing alpha-ketoglutarate (aKG) and 5-hydroxymethyl-furfural (5-HMF) has a solid antitumoral effect on the Jurkat cell line due to the fact of its antioxidative, caspase-3 and apoptosis activities, but no negative effect on human fibroblasts was obtained. The question arises how the single compounds, aKG and 5-HMF, affect peroxynitrite (ONOO−) and nitration of tyrosine residues, Jurkat cell proliferation and caspase-activated apoptosis. Methods: The ONOO− luminol-induced chemiluminescence reaction was used to measure the ONOO− scavenging function of aKG or 5-HMF, and their protection against nitration of tyrosine residues on bovine serum albumin was estimated with the ELISA technique. The Jurkat cell line was cultivated in the absence or presence of aKG or 5-HMF solutions between 0 and 3.5 µM aKG or 0 and 4 µM 5-HMF. Jurkat cells were tested for cell proliferation, mitochondrial activity and caspase-activated apoptosis. Results: aKG showed a concentration-dependent reduction in ONOO−, resulting in a 90% elimination of ONOO− using 200 mM aKG. In addition, 20 and 200 mM 5-HMF were able to reduce ONOO− only by 20%, while lower concentrations of 5-HMF remained stable in the presence of ONOO−. Nitration of tyrosine residues was inhibited 4 fold more effectively with 5-HMF compared to aKG measuring the IC50%. Both substances, aKG and 5-HMF, were shown to cause a reduction in Jurkat cell growth that was dependent on the dose and incubation time. The aKG effectively reduced Jurkat cell growth down to 50% after 48 and 72 h of incubation using the highest concentration of 3.5 µM, and 1, 1.6, 2, 3 and 4 µM 5-HMF inhibited any cell growth within (i) 24 h; 1.6, 2, 3 and 4 µM 5-HMF within 48 h (ii); 2, 3 and 4 µM 5-HMF within 72 h (iii). Furthermore, 4 µM was able to eliminate the starting cell number of 20,000 cells after 48 and 72 h down to 11,233 cells. The mitochondrial activity measurements supported the data on aKG or 5-HMF regarding cell growth in Jurkat cells, in both a dose- and incubation-time-dependent manner: the highest concentration of 3.5 µM aKG reduced the mitochondrial activity over 24 h (67.7%), 48 h (57.9%) and 72 h (46.8%) of incubation with Jurkat cells compared to the control incubation without aKG (100%). 5-HMF was more effective compared to aKG; the mitochondrial activity in the presence of 4 µM 5-HMF decreased after 24 h down to 68.4%, after 48 h to 42.9% and after 72 h to 32.0%. Moreover, 1.7 and 3.4 µM aKG had no effect on caspase-3-activated apoptosis (0.58% and 0.56%) in the Jurkat cell line. However, 2 and 4 µM 5-HMF increased the caspase-3-activated apoptosis up to 22.1% and 42.5% compared to the control (2.9%). A combined solution of 1.7 µM aKG + 0.7 µM 5-HMF showed a higher caspase-3-activated apoptosis (15.7%) compared to 1.7 µM aKG or 2 µM 5-HMF alone. In addition, 3.5 µM µg/mL aKG + 1.7 µM 5-HMF induced caspase-activated apoptosis up to 55.6% compared to 4.5% or 35.6% caspase-3 activity using 3.5 µM aKG or 4 µM 5-HMF. Conclusion: Both substances showed high antioxidative potential in eliminating either peroxynitrite or nitration of tyrosine residues, which results in a better inhibition of cell growth and mitochondrial activity of 5-HMF compared to aKG. However, caspase-3-activated apoptosis measurements revealed that the combination of both substances synergistically is the most effective compared to single compounds.

Background: Epirubicin (EPI) is an important anticancer drug that is well-known for its cardiotoxic side effect. Studying epigenetic modification such as DNA methylation can help to understand the EPI-related toxic mechanisms in cardiac tissue. In this study, we analyzed the DNA methylation profile in a relevant human cell model and inspected the expression of differentially methylated genes at the transcriptome level to understand how changes in DNA methylation could affect gene expression in relation to EPI-induced cardiotoxicity. Methods: Human cardiac microtissues were exposed to either therapeutic or toxic (IC20) EPI doses during 2 weeks. The DNA and RNA were collected from microtissues in triplicates at 2, 8, 24, 72, 168, 240, and 336 hours of exposure. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) analysis was used to detect DNA methylation levels in EPI-treated and control samples. The MeDIP-seq data were analyzed and processed using the QSEA package with a recently published workflow. RNA sequencing (RNA-seq) was used to measure global gene expression in the same samples. Results: After processing the MeDIP-seq data, we detected 35, 37, 15 candidate genes which show strong methylated alterations between all EPI-treated, EPI therapeutic and EPI toxic dose-treated samples compared to control, respectively. For several genes, gene expressions changed compatibly reflecting the DNA methylation regulation. Conclusions: The observed DNA methylation modifications provide further insights into the EPI-induced cardiotoxicity. Multiple differentially methylated genes under EPI treatment, such as SMARCA4, PKN1, RGS12, DPP9, NCOR2, SDHA, POLR2A, and AGPAT3, have been implicated in different cardiac dysfunction mechanisms. Together with other differentially methylated genes, these genes can be candidates for further investigations of EPI-related toxic mechanisms. Data Repository: The data has been generated by the HeCaToS project (http://www.ebi.ac.uk/biostudies) under accession numbers S-HECA433 and S-HECA434 for the MeDIP-seq data and S-HECA11 for the RNA-seq data. The R code is available on Github (https://github.com/NhanNguyen000/MeDIP).

Genetic predisposition affects the penetrance of tumor-initiating mutations, such as APC mutations that stabilize β-catenin and cause intestinal tumors in mice and humans. However, the mechanisms involved in genetically predisposed penetrance are not well understood. Here, we analyzed tumor multiplicity and gene expression in tumor-prone ApcMin/+ mice on highly variant C57BL/6J (B6) and PWD/Ph (PWD) genetic backgrounds. (B6 × PWD) F1 APCMin offspring mice were largely free of intestinal adenoma, and several chromosome substitution (consomic) strains carrying single PWD chromosomes on the B6 genetic background displayed reduced adenoma numbers. Multiple dosage-dependent modifier loci on PWD chromosome 5 each contributed to tumor suppression. Activation of β-catenin–driven and stem cell–specific gene expression in the presence of ApcMin or following APC loss remained moderate in intestines carrying PWD chromosome 5, suggesting that PWD variants restrict adenoma initiation by controlling stem cell homeostasis. Gene expression of modifier candidates and DNA methylation on chromosome 5 were predominantly cis controlled and largely reflected parental patterns, providing a genetic basis for inheritance of tumor susceptibility. Human SNP variants of several modifier candidates were depleted in colorectal cancer genomes, suggesting that similar mechanisms may also affect the penetrance of cancer driver mutations in humans. Overall, our analysis highlights the strong impact that multiple genetic variants acting in networks can exert on tumor development. Significance: These findings in mice show that, in addition to accidental mutations, cancer risk is determined by networks of individual gene variants.

To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue, defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with body mass index and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will throw light on the mechanism by which Sgcg may protect from the development of obesity.

Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug’s inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells. We derive an extension to the well-established drug sensitivity regression model PaccMann that employs a ranking loss and focuses on the ratio of inhibitory concentration and therapeutic dosage range. We find that the ranking extension significantly enhances the model’s capability to identify the most effective anticancer drugs for unseen tumor cell profiles based in on in-vitro data.

The generation of peroxynitrite (ONOO−) is associated with several diseases, including atherosclerosis, hypertension, neurodegeneration, cancer, inflammation, and sepsis. Alpha-ketoglutarate (αKG) is a known potential highly antioxidative agent for radical oxidative species such as peroxides. The question arises as to whether αKG is also a potential scavenger of ONOO− and a potential protector against ONOO−-mediated nitration of proteins. NMR studies of 1 mM αKG in 100 mM phosphate-buffered saline at pH 7.4 and pH 6.0 were carried out in the presence or absence of a final concentration of 2 mM ONOO−. An ONOO−–luminol-induced chemiluminescence reaction was used to measure the scavenging function of several concentrations of αKG, quantification of αKG was performed via spectrophotometric enzymatic assay of αKG in the absence or presence of 0, 1, or 2 mM ONOO−. The nitration of tyrosine residues on proteins was measured on ONOO−-treated bovine serum albumin (BSA) in the presence or absence of 0–24 mM αKG by an ELISA technique using a specific anti-IgG against nitro-tyrosine. The addition of ONOO− to αKG led to the formation of succinic acid and nitrite at pH 7.0, but not at pH 6.0, as αKG was stable against ONOO−. The absorbance of enzymatically estimated αKG at the time point of 30 min was significantly lower in favour of ONOO− (1 mM: 0.21 ± 0.03, 2 mM: 0.12 ± 0.05 vs. 0 mM: 0.32 ± 0.02, p &lt, 0.001). The luminol technique showed an inverse logarithmic correlation of the ONOO− and αKG concentrations (y = −2 × 105 ln(x) + 1 × 106, r2 = 0.99). The usage of 4 mM αKG showed a significant reduction by nearly half in the chemiluminescence signal (284,456 ± 29,293 cps, p &lt, 0.001) compared to the control (474,401 ± 18,259), for 20 and 200 mM αKG, there were further reductions to 163,546 ± 26,196 cps (p &lt, 0.001) and 12,658 ± 1928 cps (p &lt, 0.001). Nitrated tyrosine residues were estimated using the ELISA technique. A negative linear correlation was obtained by estimating nitrated tyrosine residues in the presence of αKG (r2 = 0.94): a reduction by half of nitrated tyrosine was estimated using 12 mM αKG compared to the control (326.1 ± 39.6 nmol vs. 844.5 ± 128.4 nmol, 0.001).

Mutations in splicing factor genes have a severe impact on the survival of cancer patients. Splicing factor 3b subunit 1 (SF3B1) is one of the most frequently mutated genes in chronic lymphocytic leukemia (CLL), patients carrying these mutations have a poor prognosis. Since the splicing machinery and the epigenome are closely interconnected, we investigated whether these alterations may affect the epigenomes of CLL patients. While an overall hypomethylation during CLL carcinogenesis has been observed, the interplay between the epigenetic stage of the originating B cells and SF3B1 mutations, and the subsequent effect of the mutations on methylation alterations in CLL, have not been investigated. We profiled the genome-wide DNA methylation patterns of 27 CLL patients with and without SF3B1 mutations and identified local decreases in methylation levels in SF3B1mut CLL patients at 67 genomic regions, mostly in proximity to telomeric regions. These differentially methylated regions (DMRs) were enriched in gene bodies of cancer-related signaling genes, e.g., NOTCH1, HTRA3, and BCL9L. In our study, SF3B1 mutations exclusively emerged in two out of three epigenetic stages of the originating B cells. However, not all the DMRs could be associated with the methylation programming of B cells during development, suggesting that mutations in SF3B1 cause additional epigenetic aberrations during carcinogenesis.

SARS-CoV-2 has evolved rapidly towards higher infectivity and partial immune escape over the course of the pandemic. This evolution is driven by the enormous virus population, that has infected close to 200 million people by now. Therefore, cost effective and scalable methods are needed to monitor viral evolution globally. Mutation-specific PCR approaches have become inadequate to distinguish the variety of circulating SARS-CoV-2 variants and are unable to detect novel ones. Conversely, whole genome sequencing protocols remain too labor- and cost-intensive to monitor SARS-CoV-2 at the required density. By adapting SARSeq we present a simple, fast, and scalable S-gene tiling pipeline for focused sequencing of the S-gene encoding for the spike protein. This method reports on all sequence positions with known importance for infectivity and immunity, yet scales to >20K samples per run. S-gene tiling is used for nationwide surveillance of SARS-CoV-2 at a density of 10% to 50% of all cases of infection in Austria. SARSeq S-tiling uncovered several infection clusters with variants of concern such as the biggest known cluster of Beta/B.1.351 outside Africa and successfully informed public health measures in a timely manner, allowing their successful implementation. Our close monitoring of mutations further highlighted evolutionary constraints and freedom of the spike protein ectodomain and sheds light on foreseeable evolutionary trajectories.

Long-read transcriptome sequencing (LRTS) holds the promise to boost our understanding of alternative splicing. Recent advances in accuracy and throughput have diminished the major limitations and enabled the direct quantification of isoforms. Considering the complexity of the data and the broad range of potential applications, it is clear that highly flexible, accurate analysis tools are crucial. Here, we present IsoTools, a comprehensive Python-based analysis package, for the improvement of alternative and differential splicing analysis. Iso-Tools provides a comprehensive data structure that integrates genomic information from LRTS transcripts together with the reference annotation, and enables broad functionality to quality control, visualize and analyze the data. Additionally, we implemented a graph-based method for the identification of alternative splicing events and a statistical approach based on the beta binomial distribution for the detection of differential events. To demonstrate our methods, we generated PacBio Iso-Seq data of human hepatocytes treated with the HDAC inhibitor valproic acid, a compound known to induce widespread transcriptional changes. Contrasted with short read RNA-Seq of the same samples, this analysis shows that LRTS provides valuable additional insights for a better understanding of alternative splicing, in particular with respect to complex novel and differential splicing events. IsoTools is made available for the community along with extensive documentation at https://github.com/MatthiasLienhard/isotools.

Background There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. Methods In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. Results We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap. Conclusions Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.

Current molecular tumor diagnostics encompass panel sequencing to detect mutations, copy number alterations, and rearrangements. However, tumor suppressor genes can also be inactivated by methylation within their promoter region. These epigenetic alterations are so far rarely assessed in the clinical setting. Therefore, we established the AllCap protocol facilitating the combined detection of mutations and DNA methylation at the coding and promoter regions of 342 DNA repair genes in one experiment. We demonstrate the use of the protocol by applying it to ovarian cancer cell lines with different responsiveness to poly(ADP-ribose) polymerase inhibition. BRCA1, ATM, ATR, and EP300 mutations and methylation of the BRCA1 promoter were detected as potential predictors for therapy response. The required amount of input DNA was optimized, and the application to formalin-fixed, paraffin-embedded tissue samples was verified to improve the clinical applicability. Thus, by adding DNA methylation values to panel resequencings, the AllCap assay will add another important level of information to clinical tests and will improve stratification of patients for systemic therapies.

To fully understand human genetic variation and its functional consequences, the specific distribution of variants between the two chromosomal homologues of genes must be known. The ‘phase’ of variants can significantly impact gene function and phenotype. To assess patterns of phase at large scale, we have analyzed 18 121 autosomal genes in 1092 statistically phased genomes from the 1000 Genomes Project and 184 experimentally phased genomes from the Personal Genome Project. Here we show that genes with cis-configurations of coding variants are more frequent than genes with trans-configurations in a genome, with global cis/trans ratios of ∼60:40. Significant cis-abundance was observed in virtually all genomes in all populations. Moreover, we identified a large group of genes exhibiting cis-configurations of protein-changing variants in excess, so-called ‘cis-abundant genes’, and a smaller group of ‘trans-abundant genes’. These two gene categories were functionally distinguishable, and exhibited strikingly different distributional patterns of protein-changing variants. Underlying these phenomena was a shared set of phase-sensitive genes of importance for adaptation and evolution. This work establishes common patterns of phase as key characteristics of diploid human exomes and provides evidence for their functional significance, highlighting the importance of phase for the interpretation of protein-coding genetic variation and gene function.

Uncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin). Dynamic molecular analysis at in vivo drug exposure levels reveal a network of 175 disease-associated proteins and identify common modules of anthracycline cardiotoxicity in vitro, related to mitochondrial and sarcomere function as well as remodeling of extracellular matrix. These in vitro-identified modules are transferable and are evaluated with biopsies of cardiomyopathy patients. This to our knowledge most comprehensive study on anthracycline cardiotoxicity demonstrates a reproducible workflow for molecular medicine and serves as a template for detecting adverse drug responses from complex omics data., Using a network propagation approach with integrated multi-omic data, Selevsek et al. develop a reproducible workflow for identifying drug toxicity effects in cellular systems. This is demonstrated with the analysis of anthracycline cardiotoxicity in cardiac microtissues under the effect of multiple drugs.