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Opitz, L.

Publications and source records attributed to Opitz, L..

8 recordsLinked to original sources

Multiomic profiling of human and canine soft-tissue sarcomas reveals extensive molecular homology across species and identifies clinically relevant subgroups

Soft-tissue sarcoma (STS) are rare and heterogeneous mesenchymal tumours with over 100 recognized human subtypes. Despite advances in cytogenetic and molecular characterization, diagnostic precision and therapeutic options remain limited for most subtypes. Spontaneously occurring canine STS could represent valuable translational models, due to their higher incidence and clinical similarity to human counterparts. However, molecular cross-species comparisons of specific subtypes are largely missing. Here, we performed a tissue-resolved, cross-species analysis of tumour and matched adjacent normal tissue (NT) in human and canine fibrosarcoma (FSA) and myxofibrosarcoma (MFS) by laser-capture microdissection of FFPE specimens combined with RNAseq and LC-MS/MS. Multimodal profiling revealed FSA and MFS to represent a molecular continuum rather than distinct entities in both species, resulted in identification of clinically relevant subgroups based on immune activation, proliferative activity and copy number alterations, and identified a novel canine STS subtype associated with a gene fusion. Moreover, our analyses revealed cross-species conserved transcriptomic and proteomic alterations distinguishing tumour from NT, including pathways linked to extracellular matrix remodelling, immune modulation, and cell proliferation. These data establish the first comprehensive molecular comparison of canine and human FSA and MFS, highlight the translational relevance of canine models, and identify candidate biomarkers for diagnostic refinement and development of targeted therapeutic modalities.

cancer biology↗

The impact of PCR duplication on RNA-seq data generated using NovaSeq 6000, NovaSeq X, AVITI and G4 sequencers.

RNA sequencing (RNA-seq) is a powerful technology for gene expression and functional genomics profiling. Expression profiles generated using this approach can be impacted by the methods utilised for cDNA library generation. Selection of the optimal parameters for each step during the protocol are crucial for acquisition of high-quality data. Polymerase chain reaction (PCR) amplification of transcripts is a common step in many RNA-seq protocols and, if not optimised, high PCR duplicate proportions can be generated, resulting in the inflation of transcript counts and introduction of bias. In this study, we investigate the impact of input amount and PCR cycle number on the PCR duplication rate and on the RNA-seq data quality using a broad range of inputs (1 ng -1,000 ng) for RNA-seq library preparation with unique molecular identifiers (UMIs) and sequencing the data on four different short-read sequencing platforms: Illumina NovaSeq 6000, Illumina NovaSeq X, Element Biosciences AVITI, and Singular Genomics G4. Across all platforms, samples of input amounts greater than 125 ng had a negligible PCR duplication rate and the number of PCR cycles did not have a significant effect on data quality. However, for input amounts lower than 125ng we observed a strong negative correlation between input amount and the proportion of PCR duplicates; between 34% and 96% of reads were discarded via deduplication. Fortunately, UMIs were effective for removing in silico PCR duplicates without removing valuable biological information. Removal of PCR duplicates resulted in more comparable gene expression obtained from the different PCR cycles. Data generated with each of the four sequencing platforms presented similar associations between starting material amount and the number of PCR cycles on PCR duplicates, a similar number of genes detected, and comparable gene expression profiles. However, the sequencers using conversion kits for Illumina libraries (AVITI, G4) exhibited lower adapter dimer abundance across all input amounts, but also a higher PCR duplication rate in very low input amounts (<15ng). Overall, this study showed that the choice of input amount and number of PCR cycles are important parameters for obtaining high-quality RNA-seq data across all sequencing platforms. UMI deduplication is an effective way to remove PCR duplicates, improving the data quality and removing any variation caused by the conversion kits.

genomics↗

Human effector CD8+ T cells with an exhausted-like phenotype control tumor growth in vivo

BackgroundHumanized tumor models could be particularly valuable for cancer immunotherapy research, as they may better reflect human-specific aspects of the interfaces between tumor and immune system of human cancer. However, endogenous antitumor immunity in humanized models is still largely undefined. MethodsWe established a novel autologous humanized mouse tumor model by using NSG mice reconstituted with human immune cells from hematopoietic progenitors and tumors generated from transformed autologous human B cells. We demonstrate growth of solid lymphoid tumors after subcutaneous implantation, infiltration by endogenous human immune cells and immunocompetence of the model. FindingsWe found human T cell subsets described in human cancer, including progenitor exhausted (Tpex), terminally exhausted (Tex-term) and tissue-resident (TRM) cells in tumor-bearing humanized mice with accumulation of Tex-term and TRM in the tumor. In addition, we identified tumor-reactive CD8+ T cells through expression of CD137. This subpopulation of de novo arising human CD137+ CD8+ T cells displayed a highly proliferative, fully activated effector and exhausted-like phenotype with enhanced expression of activation and exhaustion markers like PD-1, CD39, CD160, TIM-3, TIGIT and TOX, the senescence marker CD57 (B3GAT1) and cytolytic effector molecules such as PRF1, GZMH and NKG7. Moreover, these CD137+ CD8+ T cells exhibited tumor-specific clonal expansion and presented signature overlap with tumor-reactive CD8+ T cells described in human cancer. We demonstrate superior anticancer activity of this exhausted-like human CD8+ T cell subset by adoptive transfer experiments using recipients bearing autologous human tumors. Mice adoptively transferred with CD137+ CD8+ T cells showed reduced tumor growth and higher CD8+ T cell tumor infiltration, correlating with control of human tumors. InterpretationWe established an immunocompetent humanized tumor model, providing a tool for immunotherapy research and defined effective anticancer activity of human effector CD8+ T cells with an exhausted-like phenotype, supporting clinical exploration of such cells in adoptive T cell therapies. FundingSwiss Cancer Research foundation. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAntitumor immune responses and outcome of immunotherapeutic interventions are not always consistent between mouse models of cancer and data available in humans. This may be due to species-specific differences, therefore models with a potential for better translatability are needed, such as humanized mouse models. However, there is limited data on human antitumor T cell immunity in humanized mice. Added value of this studyIn this study, we established an immunocompetent humanized tumor model that recapitulates hallmarks of human antitumor T cell responses, offering the possibility for further translational investigation of the interface between human tumors and endogenous anticancer immunity. Furthermore, using functional in vitro assays and adoptive transfer, our study demonstrates the key importance of human effector CD8+ T cells with an activated and exhausted-like phenotype in the antitumor immune response. Implications of all the available evidenceThe autologous humanized tumor model provided in this study can serve as a tool to elucidate human-specific immune features. By bridging a gap between syngeneic mouse tumor models and human-specific antitumor immune responses, the model may help open up avenues for greater translatability of preclinical data. Our findings suggest that exhausted-like effector CD8+ T cells can be harnessed for clinical development of adoptive T cell therapies.

immunology↗

Transcriptomic gene profiles in an ex vivo model of erythropoiesis to unravel molecular pathomechanisms in sickle cell disease

We characterized the transcriptional profiles of erythroid cells differentiated from peripheral blood mononuclear cells (PBMCs) from peripheral blood collected from patients diagnosed with Sickle Cell Disease (SCD), which have been treated with Hydroxyurea (HU) in comparison to untreated SCD patients and healthy controls (HC) using bulk RNAseq. We identified 1398 differentially expressed genes (DEGs) in SCD non-treated-derived erythroid cells and 495 DEGs in SCD HU-treated patient-derived erythroid cells compared to HC. We found biological processes such as oxidative phosphorylation pathway, proteasome, autophagy, natural killer cell (NK) cytotoxicity, adaptive immune response or inflammatory response to be significantly enriched in our patient study groups by using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Our findings collectively suggest different as well as common molecular signatures between our groups. We could validate 12 of our top DEGs in treated patients by qRT-PCR. We found similar regulation patterns when comparing the mRNA levels of mutS homolog 5-Suppressor APC Domain Containing 1 (MSH5-SAPCD1), G protein subunit gamma 4 (GNG4), stabilin 1/ clever-1 (STAB1) and Fas Binding Factor 1 (FBF1) from the bone marrow cells and spleen tissue from the Berkely SCD mouse model to the expressions observed in the transcriptome of our ex-vivo patient-derived erythropoiesis model.

molecular biology↗

Mycobacterium tuberculosis infection associated immune perturbations correlate with antiretroviral immunity

Infection with Mycobacterium tuberculosis (MTB) remains one of the most important opportunistic infections in people with HIV-1 (PWH). While active Tuberculosis (TB) leads to rapid progression of immunodeficiency in PWH, the interaction between MTB and HIV-1 during the asymptomatic phase of both infections remains poorly understood. In a cohort of individuals with HIV (PWH) with and without suppressed HIV-1 viral load, the transcriptomic profiles of peripheral blood mononuclear cells (PBMC) clustered in individuals infected with Mycobacterium tuberculosis (MTB) compared to carefully matched controls. Subsequent functional annotation analysis disclosed alterations in the IL-6, TNF, and KRAS pathways. Notably, MTB-associated genes demonstrated an inverse correlation with HIV-1 viremia, evident at both on individual gene level and when employed as a gene score. In sum, our data show that MTB infection in PWH is associated with a shift in the activation state of the immune system, displaying an inverse relationship with HIV-1 viral load. These results could provide an explanation for the observed increased antiretroviral control associated with MTB infection in PWH.

immunology↗

HiDRA-seq: High-Throughput SARS-CoV-2 Detection by RNA Barcoding and Amplicon Sequencing

The recent outbreak of a new coronavirus that causes a Severe Acute Respiratory Syndrome in humans (SARS-CoV-2) has developed into a global pandemic with over 6 million reported cases and more than 375,000 deaths worldwide. Many countries have faced a shortage of diagnostic kits as well as a lack of infrastructure to perform necessary testing. Due to these limiting factors, only patients showing symptoms indicating infection were subjected to testing, whilst asymptomatic individuals, who are widely believed to be responsible for the fast dispersion of the virus, were largely omitted from the testing regimes. The inability to implement high throughput diagnostic and contact tracing strategies has forced many countries to institute lockdowns with severe economic and social consequences. The World Health Organization (WHO) has encouraged affected countries to increase testing capabilities to identify new cases, allow for a well-controlled lifting of lockdown measures, and prepare for future outbreaks. Here, we propose HiDRA-seq, a rapidly implementable, high throughput, and scalable solution that uses NGS lab infrastructure and reagents for population-scale SARS-CoV-2 testing. This method is based on the use of indexed oligo-dT primers to generate barcoded cDNA from a large number of patient samples. From this, highly multiplexed NGS libraries are prepared targeting SARS-CoV-2 specific regions and sequenced. The low amount of sequencing data required for diagnosis allows the combination of thousands of samples in a sequencing run, while reducing the cost to approximately 2 CHF/EUR/USD per RNA sample. Here, we describe in detail the first version of the protocol, which can be further improved in the future to increase its sensitivity and to identify other respiratory viruses or analyze individual genetic features associated with disease progression.

genomics↗

Long fragments achieve lower base quality in Illumina paired-end sequencing

Illuminas technology provides high quality reads of DNA fragments with error rates below 1/1000 per base. Runs typically generate a millions of reads where the vast majority of the reads has also an average error rate below 1/1000. However, some paired-end sequencing data show the presence of a subpopulation of reads where the second read has lower average qualities. We show that the fragment length is a major driver of increased error rates in the R2 reads. Fragments above 500 nt tend to yield lower base qualities and higher error rates than shorter fragments. We demonstrate the fragment length dependency of the R2 read qualities using publicly available Illumina data generated by various library protocols, in different labs and using different sequencer models. Our finding extends the understanding of the Illumina read quality and has implications on error models for Illumina reads. It also sheds a light on the importance of the fragmentation during library preparation and the resulting fragment length distribution.

bioinformatics↗

Engineered Peptide Barcodes for In-Depth Analyses of Binding Protein Ensembles

Binding protein generation relies on laborious screening cascades that process candidate molecules individually. To break with this paradigm, we developed NestLink, a binder selection and identification technology able to biophysically characterize thousands of library members at once without handling individual clones at any stage of the process. NestLink builds on genetically fused barcoding peptides, termed flycodes, which are designed for maximal detectability by mass spectrometry and serve as unique molecular identifiers for accurate deep sequencing. We applied NestLink to overcome current limitations of binder generation. Rare binders against an integral membrane protein were identified directly in the cellular environment of a human pathogen. Hundreds of binder candidates were simultaneously ranked according to kinetic parameters. Adverse effects of target immobilization were overcome by selecting nanobodies against an ABC transporter entirely in solution. NestLink may provide a basis for the selection of tailored binder characteristics directly in tissues or in living organisms.

bioengineering↗