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PURPOSE Clinical outcomes of patients with CNS lymphomas (CNSLs) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure is challenging. Furthermore, CNSL diagnosis often remains unconfirmed because of contraindications for invasive stereotactic biopsies. Therefore, improved biomarkers are needed to better stratify patients into risk groups, predict treatment response, and noninvasively identify CNSL. PATIENTS AND METHODS We explored the value of circulating tumor DNA (ctDNA) for early outcome prediction, measurable residual disease monitoring, and surgery-free CNSL identification by applying ultrasensitive targeted next-generation sequencing to a total of 306 tumor, plasma, and CSF specimens from 136 patients with brain cancers, including 92 patients with CNSL. RESULTS Before therapy, ctDNA was detectable in 78% of plasma and 100% of CSF samples. Patients with positive ctDNA in pretreatment plasma had significantly shorter progression-free survival (PFS, P < .0001, log-rank test) and overall survival (OS, P = .0001, log-rank test). In multivariate analyses including established clinical and radiographic risk factors, pretreatment plasma ctDNA concentrations were independently prognostic of clinical outcomes (PFS HR, 1.4; 95% CI, 1.0 to 1.9; P = .03; OS HR, 1.6; 95% CI, 1.1 to 2.2; P = .006). Moreover, measurable residual disease detection by plasma ctDNA monitoring during treatment identified patients with particularly poor prognosis following curative-intent immunochemotherapy (PFS, P = .0002; OS, P = .004, log-rank test). Finally, we developed a proof-of-principle machine learning approach for biopsy-free CNSL identification from ctDNA, showing sensitivities of 59% (CSF) and 25% (plasma) with high positive predictive value. CONCLUSION We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings highlight the role of ctDNA as a noninvasive biomarker and its potential value for personalized risk stratification and treatment guidance in patients with CNSL. [Media: see text]

PI3K/mTOR signaling is frequently upregulated in breast cancer making inhibitors of this pathway highly promising anticancer drugs. However, PI3K-inhibitors have a low therapeutic index. Therefore, finding novel combinatory treatment options represents an important step towards clinical implementation of PI3K pathway inhibition in breast cancer therapy. Here, we propose proteases as potential synergistic partners with simultaneous PI3K inhibition in breast cancer cells.We performed mRNA expression studies and unbiased functional genetic synthetic lethality screens by a miR-E based knockdown system targeting all genome-encoded proteases, i.e. the degradome of breast cancer cells. Importantly theses RNA interference screens were done in combination with two PI3K pathway inhibitors. Protease hits were validated in human and murine breast cancer cell lines as well as in non-cancerous cells by viability and growth assays.The degradome-wide genetic screens identified 181 proteases that influenced susceptibility of murine breast cancer cells to low dose PI3K inhibition. Employing independently generated inducible knockdown cell lines we validated 12 protease hits in breast cancer cells. In line with the known tumor promoting function of these proteases we demonstrated Usp7 and Metap2 to be important for murine and human breast cancer cell growth and discovered a role for Metap1 in this context. Most importantly, we demonstrated that Usp7, Metap1 or Metap2 knockdown combined with simultaneous PI3K inhibition resulted in synergistic impairment of murine and human breast cancer cell growth Conclusion: We successfully established proteases as combinatory targets with PI3K inhibition in human and murine breast cancer cells. Usp7, Metap1 and Metap2 are synthetic lethal partners of simultaneous protease/PI3K inhibition, which may refine future breast cancer therapy.

This prospective trial aimed to investigate whether tumor-specific cKIT and PDGFRA mutations can be detected and quantified in circulating tumor (ct)DNA in patients with active GIST, and whether detection indicates disease activity. We included 25 patients with active disease and cKIT or PDGFRA mutations detected in tissue. Mutant ctDNA was detected in the peripheral blood plasma using allele-specific ligation (L-)PCR and droplet digital (d)PCR. CtDNA harboring tumor-specific cKIT or PDGFRA mutations was detected at least once in 16 out of 25 patients using L-PCR (64%) and in 20 out of 25 patients with dPCR (80%). Using dPCR, the absolute numbers of ctDNA fragments (DNA copies/ml) and the mutant allele frequency (MAF; in percent of wild-type control) strongly correlated with tumor size expressed as RECIST1.1 sum of diameter (SOD) in mm (ρ = 0.3719 and 0.408, respectively, p < 0.0001) and response status (ρ = 0.3939 and 0.392, respectively, p < 0.0001 and p < 0.001). Specificity of dPCR for detection of progression was 79.2% with a sensitivity of 55.2% and dPCR discriminated CR from active disease with a specificity of 96% and s sensitivity of 44.7%. With L-PCR, correlations of MAF with tumor size and response status were less prominent. Serial ctDNA measurement reflected individual disease courses over time. Targeted panel sequencing of four patients detected additional driver mutations in all cases and secondary resistance mutations in two cases. Thus, ctDNA indicates disease activity in patients with GIST and should be incorporated as companion biomarker in future prospective trials.

Introduction: Clinical outcomes for patients with central nervous system lymphoma (CNSL) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure remains challenging with existing methods. In addition, diagnosis of CNSL requires invasive neurosurgical biopsies that carry procedural risks and often cannot be performed in frail or elderly patients. Circulating tumor DNA (ctDNA) has shown great potential as a noninvasive biomarker in systemic lymphomas. Yet, previous studies revealed low ctDNA detection rates in blood plasma of CNSL patients. In this study, we utilized ultrasensitive targeted high-throughput sequencing technologies to explore the role of ctDNA for disease classification, MRD detection, and early prediction of clinical outcomes in patients with CNSL. Methods: We applied Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) and Phased Variant Enrichment and Detection Sequencing (PhasED-Seq, Kurtz et al, Nat Biotech 2021) to 85 tumor biopsies, 131 plasma samples, and 62 CSF specimens from 92 CNSL patients and 44 patients with other brain cancers or inflammatory cerebral diseases, targeting 794 distinct genetic regions. Concentrations of ctDNA were correlated with radiological measures of tumor burden and tested for associations with clinical outcomes at distinct clinical time points. We further developed a novel classifier to noninvasively distinguish CNS lymphomas from other CNS tumors based on their mutational landscapes in plasma and CSF, using supervised training of a machine learning approach from tumor whole genome sequencing data and own genotyping analyses, followed by its independent validation. Results: We identified genetic aberrations in 100% of CNSL tumor biopsies (n=63), with a median of 262 mutations per patient. Pretreatment plasma ctDNA was detectable in 78% of plasma samples and in 100% of CSF specimens (Fig. 1a), with ctDNA concentrations ranging from 0.0004 - 5.94% allele frequency (AF, median: 0.01%) in plasma and 0.0049 - 50.47% AF (median: 0.62%) in CSF (Fig. 1b). Compared to ctDNA concentrations in patients with systemic diffuse large B-cell lymphoma (DLBCL, data from Kurtz et al., J Clin Oncol, 2018), plasma ctDNA levels in CNSL were in median more than 200-fold lower (Fig. 1b). We observed a significant correlation of ctDNA concentrations with total radiographic tumor volumes (TRTV) measured by MRI (Fig. 1c,d), but no association with clinical risk scores (i.e., MSKCC score) or concurrent steroid treatment. Assessment of ctDNA at pretreatment time points predicted progression-free survival (PFS) and overall survival (OS), both as continuous and binary variable (Fig. 1e,f). Notably, patients could be stratified into risk groups with particularly favorable or poor prognoses by combining ctDNA and TRTV as pretreatment biomarkers (Fig. 1g). Furthermore, ctDNA positivity during curative-intent induction therapy was significantly associated with clinical outcomes, both PFS and OS (Fig. 1h). Finally, we applied our novel machine learning classifier to 207 specimens from an independent validation cohort of CNSL and Non-CNSL patients. We observed high specificity (100%) and positive predictive value (100%) for noninvasive diagnosis of CNSL, with a sensitivity of 57% for CSF and 21% for plasma, suggesting that a significant subset of CNSL patients might be able to forego invasive surgical biopsies. Conclusions: We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings suggest that ctDNA accurately mirrors tumor burden and serves as a valuable clinical biomarker for risk stratification, outcome prediction, and surgery-free lymphoma classification in CNSL. We foresee an important potential future role of ctDNA as a decision-making tool to guide treatment in patients with CNSL. Figure 1 Figure 1. Disclosures Esfahani: Foresight Diagnostics: Current holder of stock options in a privately-held company. Kurtz: Genentech: Consultancy; Roche: Consultancy; Foresight Diagnostics: Consultancy, Current holder of stock options in a privately-held company. Schorb: Riemser Pharma GmbH: Honoraria, Research Funding; Roche: Research Funding; AbbVie: Research Funding. Diehn: BioNTech: Consultancy; RefleXion: Consultancy; Roche: Consultancy; AstraZeneca: Consultancy; Foresight Diagnostics: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; CiberMed: Current holder of stock options in a privately-held company, Patents & Royalties; Illumina: Research Funding; Varian Medical Systems: Research Funding. Alizadeh: Foresight Diagnostics: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Gilead: Consultancy; Roche: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Janssen Oncology: Honoraria; CAPP Medical: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Forty Seven: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Cibermed: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Bristol Myers Squibb: Research Funding.

Summary: Molecular chaperones such as heat-shock proteins (HSPs) help in protein folding. Their function in the cytosol has been well studied. Notably, chaperones are also present in the nucleus, a compartment where proteins enter after completing de novo folding in the cytosol, and this raises an important question about chaperone function in the nucleus. We performed a systematic analysis of the nuclear pool of heat-shock protein 90. Three orthogonal and independent analyses led us to the core functional interactome of HSP90. Computational and biochemical analyses identify host cell factor C1 (HCFC1) as a transcriptional regulator that depends on HSP90 for its stability. HSP90 was required to maintain the expression of HCFC1-targeted cell-cycle genes. The regulatory nexus between HSP90 and the HCFC1 module identified in this study sheds light on the relevance of chaperones in the transcription of cell-cycle genes. Our study also suggests a therapeutic avenue of combining chaperone and transcription inhibitors for cancer treatment. : What do chaperones do in the nucleus? Antonova et al. perform a comprehensive genetic and physical interactome analysis of nuclear HSP90 in human cells. HSP90 stabilizes the HCFC1 complex at chromatin, contributing to the expression of HCFC1-targeted cell-cycle genes. The simultaneous inhibition of HSP90 and transcription is synergistic in killing cancer cells. Keywords: chaperone, HSP90, HCFC1, chromatin, cancer, synergistic inhibition

Nitrogen is frequently limiting microbial growth in the environment. As a response, many filamentous cyanobacteria differentiate heterocysts, cells devoted to N fixation. Heterocyst differentiation is under the control of the master regulator HetR. Through the characterization of the HetR-dependent transcriptome in Nostoc sp. PCC 7120, we identified the new candidate genes likely involved in heterocyst differentiation. According to their maximum induction, we defined E-DIF (early in differentiation) and L-DIF (late in differentiation) genes. Most of the genes known to be involved in the critical aspects of heterocyst differentiation or function were also classified into these groups, showing the validity of the approach. Using fusions to gfp, we verified the heterocyst-specific transcription of several of the found genes, antisense transcripts and potentially trans-acting sRNAs. Through comparative sequence analysis of promoter regions, we noticed the prevalence of the previously described DIF1 motif and identified a second motif, called DIF2, in other promoters of the E-DIF cluster. Both motifs are widely conserved in heterocystous cyanobacteria. We assigned alr2522 as a third member, besides nifB and nifP, to the CnfR regulon. The elements identified here are of interest for understanding cell differentiation, engineering of biological nitrogen fixation or production of O-sensitive molecules in cyanobacteria.

Acute myeloid leukemia (AML) is the most common type of acute leukemia in adults, and remains a difficult to treat disease, especially in elderly patients. AML arises in hematopoietic stem and progenitor cells and frequently carries alterations in genes involved in epigenetic regulation. Furthermore, azacitidine (AZA) and decitabine (DAC), two nucleoside analogs inhibiting DNA methylation (DNMTi), have shown clinical efficacy in the therapy of myelodysplastic syndrome (MDS) and AML, highlighting the importance of epigenetic regulation in AML. Up to now, the mechanism of action of AZA and DAC in AML has not been fully elucidated, and reliable biomarkers of therapy response to these drugs do not yet exist. To identify epigenetic response modifiers towards AZA and DAC treatment, we conducted a pooled shRNA-based screen in three human leukemia cell lines using an inducible custom shRNA library targeting more than 660 different genes involved in epigenetic pathways. After selection of retrovirally infected cells, shRNA expression was induced and a fraction of cells were treated with either AZA, DAC or left untreated. 10 days after shRNA induction, genomic DNA was extracted and deep-sequenced to identify genes conferring a selective advantage/disadvantage under these conditions. By comparing shRNA representation changes between the differentially treated groups, we identified multiple candidate genes sensitizing or protecting leukemic cells to/from AZA and DAC treatment. Notably, the DNMT1 gene itself expectedly emerged as an important sensitizer to DNMTi, as did other CXXC domain-containing genes binding to (un-)methylated CpG domains. Another prominent set of genes in the pooled analysis belonged to the DNA damage pathway, including genes such as PARP1 and BRCA1. The identified candidate genes were validated and confirmed in more than 80% when tested in single shRNAs competition assays. Their impact on DNA methylation and gene expression is currently being assessed, with ongoing experiments focusing on the mechanistic role of some of the validated target, as well as the clinical potential for combinatorial therapies. Thus, using an unbiased functional genetic approach, we identified multiple genes including CpG binding proteins and members of the DNA damage pathway as important modulators of DNMTi response. Our results will increase our understanding of the molecular mechanisms driving DNMTi efficacy, and may help to identify new biomarkers and novel targets for combinational therapy in AML. Disclosures No relevant conflicts of interest to declare.

Summary • Dual targeting of proteins to more than one subcellular localization has been found in animals, in fungi and in plants. In the latter, ambiguous N-terminal targeting signals have been described that result in the protein being located in both mitochondria and plastids. We have developed ambiguous targeting predictor (ATP), a machine-learning implementation that classifies such ambiguous targeting signals. • Ambiguous targeting predictor is based on a support vector machine implementation that makes use of 12 different amino acid features. Prediction results were validated using fluorescent protein fusion. • Both in silico and in vivo evaluations demonstrate that ambiguous targeting predictor is useful for predicting dual targeting to mitochondria and plastids. Proteins that are targeted to both organelles by tandemly arrayed signals (so-called twin targeting) can be predicted by both ambiguous targeting predictor and a combination of single targeting prediction tools. Comparison of ambiguous targeting predictor with previous experimental approaches, as well as in silico approaches, shows good congruence. • Based on the prediction results, land plant genomes are expected to encode, on average, > 400 proteins that are located in mitochondria and plastids. Ambiguous targeting predictor is helpful for functional genome annotation and can be used as a tool to further our understanding about dual protein targeting and its evolution.

In contrast to Synechococcus elongatus PCC 7942, few data exist on the timing mechanism of the widely used cyanobacterium Synechocystis sp. PCC 6803. The standard kaiAB1C1 operon present in this organism was shown to encode a functional KaiC protein that interacted with KaiA, similar to the S. elongatus PCC 7942 clock. Inactivation of this operon in Synechocystis sp. PCC 6803 resulted in a mutant with a strong growth defect when grown under light–dark cycles, which was even more pronounced when glucose was added to the growth medium. In addition, mutants showed a bleaching phenotype. No effects were detected in mutant cells grown under constant light. Microarray experiments performed with cells grown for 1 day under a light–dark cycle revealed many differentially regulated genes with known functions in the ΔkaiABC mutant in comparison with the WT. We identified the genes encoding the cyanobacterial phytochrome Cph1 and the light-repressed protein LrtA as well as several hypothetical ORFs with a complete inverse behaviour in the light cycle. These transcripts showed a stronger accumulation in the light but a weaker accumulation in the dark in ΔkaiABC cells in comparison with the WT. In general, we found a considerable overlap with microarray data obtained for hik31 and sigE mutants. These genes are known to be important regulators of cell metabolism in the dark. Strikingly, deletion of the ΔkaiABC operon led to a much stronger phenotype under light–dark cycles in Synechocystis sp. PCC 6803 than in Synechococcus sp. PCC 7942.

Prochlorococcus is a genus of abundant and ecologically important marine cyanobacteria. Here, we present a comprehensive comparison of the structure and composition of the transcriptomes of two Prochlorococcus strains, which, despite their similarities, have adapted their gene pool to specific environmental constraints. We present genome-wide maps of transcriptional start sites (TSS) for both organisms, which are representatives of the two most diverse clades within the two major ecotypes adapted to high- and low-light conditions, respectively. Our data suggest antisense transcription for three-quarters of all genes, which is substantially more than that observed in other bacteria. We discovered hundreds of TSS within genes, most notably within 16 of the 29 prochlorosin genes, in strain MIT9313. A direct comparison revealed very little conservation in the location of TSS and the nature of non-coding transcripts between both strains. We detected extremely short 5′ untranslated regions with a median length of only 27 and 29 nt for MED4 and MIT9313, respectively, and for 8% of all protein-coding genes the median distance to the start codon is only 10 nt or even shorter. These findings and the absence of an obvious Shine–Dalgarno motif suggest that leaderless translation and ribosomal protein S1-dependent translation constitute alternative mechanisms for translation initiation in Prochlorococcus. We conclude that genome-wide antisense transcription is a major component of the transcriptional output from these relatively small genomes and that a hitherto unrecognized high degree of complexity and variability of gene expression exists in their transcriptional architecture.

There has been an increasing interest in cyanobacteria because these photosynthetic organisms convert solar energy into biomass and because of their potential for the production of biofuels. However, the exploitation of cyanobacteria for bioengineering requires knowledge of their transcriptional organization. Using differential RNA sequencing, we have established a genome-wide map of 3,527 transcriptional start sites (TSS) of the model organism Synechocystis sp. PCC6803. One-third of all TSS were located upstream of an annotated gene; another third were on the reverse complementary strand of 866 genes, suggesting massive antisense transcription. Orphan TSS located in intergenic regions led us to predict 314 noncoding RNAs (ncRNAs). Complementary microarray-based RNA profiling verified a high number of noncoding transcripts and identified strong ncRNA regulations. Thus, ∼64% of all TSS give rise to antisense or ncRNAs in a genome that is to 87% protein coding. Our data enhance the information on promoters by a factor of 40, suggest the existence of additional small peptide-encoding mRNAs, and provide corrected 5′ annotations for many genes of this cyanobacterium. The global TSS map will facilitate the use of Synechocystis sp. PCC6803 as a model organism for further research on photosynthesis and energy research.