Biology subjects

Schultz, N.

Publications and source records attributed to Schultz, N..

28 records · Page 2Linked to original sources

bioRxiv2022

Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples

Spatially resolved transcriptomics (SRT) has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of unbiased SRT methods targeting the polyA tail of mRNA, relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available SRT assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), an SRT workflow designed to improve mRNA recovery from fresh frozen (FF) specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we demonstrate the RRST protocol on tissue sections collected from 5 challenging tissue types, including: human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyzed 52 tissue sections and our results demonstrate that RRST is a versatile, powerful, and reproducible protocol for FF specimens of different qualities and origins.

genomics↗

bioRxiv2022

Integrative analysis of the MD Anderson Prostate Cancer Patient-Derived Xenograft Series (MDA PCa PDX)

Progress in understanding prostate cancer (PCa) metastasis and therapy resistance has been hampered by the lack of models, representative of the clinical spectrum and biologic complexity of the disease. Our laboratory is home to one of the largest worldwide repositories of PCa patient-derived xenografts (PDXs), the MDA PCa PDX series, a collection of clinically annotated PDXs reflecting the full spectrum of potentially lethal disease, that includes tumors that are not end stage and not castration-resistant PCa. We performed whole genome sequencing, targeted sequencing and RNA sequencing of 46 MDA PCa PDX models derived from biopsy and surgical specimens from 39 patients, selected in order to reflect the clinicopathological PCa subtypes (data available in cBioPortal). MDA PCa PDXs genomic characterization shows that the cohort recapitulates the mutational landscape found in PCa, highlighting the clinical relevance of these models. Interestingly and consistently with the clinic, certain models lack the typical PCa driver alterations, thus providing a suitable tool for discovery of novel drivers. Our cohort also includes PDXs derived from different areas of the same tumor and longitudinal samples, allowing to study disease heterogeneity and progression. Finally, we have developed a procedure to grow organoids from PDXs, thus providing a powerful in vitro platform that supports hypothesis generation, and testing of clinically relevant observations. Genomic and transcriptomic characterization of MDA PCa PDXs together with the ability to grow them as organoids for in vitro experimentation, provides a unique resource to address the existing clinical gap in PCa, helping to better understand mechanisms of response and resistance. One Sentence SummaryMDA PCa PDX series is a dynamic resource capturing the molecular landscape of prostate cancer; a platform for discovery and personalized medicine

cancer biology↗

bioRxiv2021

BRCA mutational status shapes the stromal microenvironment of pancreatic cancer linking CLU+ CAF expression with HSF1 signaling

Cancer-associated fibroblasts (CAFs) give rise to desmoplastic stroma, which supports tumor progression and metastasis, and comprises up to 90% of the tumor mass in pancreatic cancer. Recent work by us and others has shown that CAFs are transcriptionally rewired by adjacent cancer cells to form heterogeneous subtypes. Whether this rewiring is differentially affected by different driver mutations in cancer cells is largely unknown. Here we address this question by dissecting and comparing the stromal landscape of BRCA-mutated and BRCA Wild-type (WT) pancreatic ductal adenocarcinoma (PDAC). We comprehensively analyze PDAC samples from a cohort of 42 patients by laser-capture microdissection, RNA-sequencing and multiplexed immunofluorescence, revealing different CAF subtype compositions in germline BRCA-mutated vs. BRCA-WT tumors. In particular, we detect an increase in a subset of Clusterin (CLU)-positive CAFs in BRCA-mutated tumors. We further unravel a network of stress responses upregulated in BRCA-mutated tumors. Using cancer organoids and cell co-cultures, we show that the transcriptional shift of pancreatic stellate cells into CLU+ CAFs is mediated through activation of heat-shock factor 1 (HSF1), the transcriptional regulator of Clu. Our findings unravel a new dimension of stromal heterogeneity, influenced by germline mutations in cancer cells, with direct translational implications for clinical research. SignificanceBRCA1/2 mutations initiate some of the deadliest cancers, yet the fibroblastic microenvironment of BRCA-mutated cancers remains uncharted. Our work addresses a major unsolved question - to what extent is the tumor microenvironment determined by cancer mutations? We find that BRCA mutations in the cancer cells affect the composition of CAFs in PDAC. These findings have direct implications for diagnosis and for efforts to exploit CAFs for therapy.

cancer biology↗

bioRxiv2021

The spatial landscape of clonal somatic mutations in benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

genomics↗

bioRxiv2021

Genomic and Metabolic Hallmarks of SDH- and FH-Deficient Renal Cell Carcinomas

PurposeSuccinate dehydrogenase-deficient and fumarate hydratase-deficient renal cell carcinomas (SDHRCC and FHRCC) are rare kidney cancers driven by loss of metabolically proximal enzymes. We sought to define and compare the genomic and metabolomic hallmarks of these entities. Experimental DesignWe analyzed SDHRCC and FHRCC tumors with either immunohistochemical evidence of loss of protein expression or genomically-confirmed biallelic inactivation of SDHA/B/C/D/AF2 or FH. Somatic alterations were identified using clinical pipelines, and allele-specific copy number changes were identified using FACETS. Mass-spectrometry-based metabolomic profiling was performed on available SDHRCC and FHRCC tumors. ResultsForty two patients were analyzed (25 FHRCC, 17 SDHRCC). In the germline analysis, 16/17 SDHRCC harbored a germline alteration in SDHB, whereas only 17/22 FHRCC had pathogenic germline FH variants. SDHRCC had a lower mutation burden (p = 0.02) and copy number alteration burden (p = 0.0002) than FHRCC. All SDHRCC presented with deletion of chromosome 1p (overlapping SDHB), whereas FHRCC demonstrated high but not ubiquitous loss of 1q (FH locus). Both SDHRCC and FHRCC demonstrated significant, idiopathic accumulation of the metabolite guanine. FHRCC tumors had elevated levels of urea cycle metabolites (argininosuccinate, citrulline, and fumarate), whereas SDHRCC had elevation of numerous acylcarnitines. These characteristic metabolic changes enabled the identification of a previously unrecognized SDH-deficient RCC. ConclusionDespite sharing similar genetic etiology, SDHRCC and FHRCC represent distinct molecular entities with unique genetic and metabolic abnormalities. Translational RelevanceMutations to the TCA cycle enzymes Succinate Dehydrogenase (SDH) and Fumarate Hydratase (FH) predispose individuals to unique subtypes of renal cell carcinoma (SDHRCC and FHRCC, respectively). Defining the genetic and metabolic hallmarks of these diseases is critical for advancing new diagnostic and therapeutic approaches for these rare but biologically intriguing entities. Despite a superficially similar genetic etiology, SDHRCC and FHRCC demonstrated significantly fewer secondary mutations to other cancer-associated genes and copy number aberrations than FHRCC, and was distinguished by universal loss-of-heterozygosity of chromosome 1p. Metabolomic analysis identified pathways disrupted in both SDHRCC and FHRCC, including the massive accumulation of free guanine, as well as pathways uniquely disrupted in each of the two entities. These metabolomic findings enabled the identification of a previously unidentified case of unclassified RCC with SDH deficiency, suggesting that metabolomic profiling may aid in phenotypic classification of tumors and uncover novel therapeutic targets.

cancer biology↗

bioRxiv2019

Lower dormancy with rapid germination is an important strategy for seeds in an arid zone with unpredictable rainfall

Seed germination traits are key drivers of population dynamics, yet they are under-represented in community ecology studies, which have predominately focussed on adult plant and seed morphological traits. We studied the seed traits and germination strategy of eight woody plant species to investigate regeneration strategies in the arid zone of eastern Australia. To cope with stochastic and minimal rainfall, we predict that arid seeds will either have rapid germination across a wide range of temperatures, improved germination under cooler temperatures, or dormancy and/or longevity traits to delay or stagger germination across time. To understand how temperature affects germination responses, seeds of eight keystone arid species were germinated under laboratory conditions, and under three diurnal temperatures (30/20{degrees}C, 25/15{degrees}C and 17/7{degrees}C) for 30 days. Seeds of species in this study are currently stored for minesite restoration projects, hence we tested for decline in seed viability across 24 months in dry storage at similar storage conditions ({approx}20{degrees}C). Six of the eight arid species studied had non-dormant, rapidly germinating seeds, and only two species had physiological dormancy traits. Seed longevity differed widely between species, from one recalcitrant species surviving only months in storage (P50 = <3 months) and one serotinous species surviving for many years (P50 = 84 months). Our results highlight the importance of understanding the reproductive strategies of plant species in arid environments. Rapid germination, the dominant seed trait of species included in this study, allows arid species to capitalise on sporadic rainfall. However, some species also exhibit dormancy and delayed germination; this an alternative strategy which spreads the risk of germination failure over time. We highlight important seed traits and germination strategies of plants from an arid zone with stochastic rainfall and discuss the implications for their restoration.

plant biology↗

bioRxiv2019

MTH1 promotes mitotic progression to avoid oxidative DNA damage in cancer cells

BACKGROUNDWe developed MTH1 inhibitors (MTH1i) TH588 and TH1579 showing broad anti-cancer activity, while structurally distinct MTH1i fail to kill cancer cells. Here, we describe a new role of MTH1 in mitosis and the detailed mechanism of action of TH1579 (karonudib) and other structurally distinct MTH1i.\n\nMATERIALS AND METHODSCancer cell lines or zebrafish embryos were treated with MTH1i or siRNA targeting MTH1 and analysed primarily by live cell and immunofluorescence microscopy, survival assays, DNA fibre or COMET assays. MTH1 and tubulin interactions were analysed in vitro using co-immunoprecipitation and tubulin polymerisation assays.\n\nRESULTSHere, we describe a mitotic role for the MTH1 protein, which binds to tubulin, is required for microtubule polymerisation, correct spindle assembly, mitosis progression and suppression reactive oxygen species (ROS) generation in mitosis. Potent MTH1i display differential abilities to break the MTH1-tubulin interaction and cause mitotic arrest, demonstrating 8-oxodGTPase and mitotic function of MTH1 are mechanistically distinct. TH588 and TH1579 have more profound effect on mitotic arrest than other MTH1i explained by additional direct inhibition of tubulin polymerisation. MTH1i only inhibiting 8-oxodGTPase activity synergize with mitotic poisons.\n\nCONCLUSIONSEfficient MTH1 have a dual mechanism of action: inhibiting mitosis (to generate ROS) and promoting 8-oxodGTP incorporation into DNA during mitotic replication, dependent on ROS generation. Direct inhibition of tubulin polymerisation of TH588 and TH1579 increase their ability to arrest cells and generate ROS in mitosis. Furthermore, non-cytotoxic MTH1 can become effective and increase incorporation of oxidised nucleotides into DNA when combined with sub-therapeutic concentrations of mitotic inhibitors or challenged directly by 8-oxodGTP.

cancer biology↗

bioRxiv2018

A harmonized meta-knowledgebase of clinical interpretations of cancer genomic variants

Precision oncology relies on the accurate discovery and interpretation of genomic variants to enable individualized diagnosis, prognosis, and therapy selection. We found that knowledgebases containing clinical interpretations of somatic cancer variants are highly disparate in interpretation content, structure, and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. With the cooperation of experts of the Global Alliance for Genomics and Health (GA4GH) and six prominent cancer variant knowledgebases, we developed a framework for aggregating and harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations covering 3,437 unique variants in 415 genes, 357 diseases, and 791 drugs. We demonstrated large gains in overlap between resources across variants, diseases, and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 56% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide an open and freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

bioinformatics↗

bioRxiv2018

Integration and analysis of CPTAC proteomics data in the context of cancer genomics in the cBioPortal

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced extensive mass spectrometry based proteomics data for selected breast, colon and ovarian tumors from The Cancer Genome Atlas (TCGA). We have incorporated the CPTAC proteomics data into the cBioPotal to support easy exploration and integrative analysis of these proteomic datasets in the context of the clinical and genomics data from the same tumors. cBioPortal is an open source platform for exploring, visualizing, and analyzing multi-dimensional cancer genomics and clinical data. The public instance of the cBioPortal (http://cbioportal.org/) hosts more than 100 cancer genomics studies including all of the data from TCGA. Its biologist-friendly interface provides many rich analysis features, including a graphical summary of gene-level data across multiple platforms, correlation analysis between genes or other data types, survival analysis, and network visualization. Here, we present the integration of the CPTAC mass spectrometry based proteomics data into the cBioPortal, consisting of 77 breast, 95 colorectal, and 174 ovarian tumors that already have been profiled by TCGA for mutations, copy number alterations, gene expression, and DNA methylation. As a result, the CPTAC data can now be easily explored and analyzed in the cBioPortal in the context of clinical and genomics data. By integrating CPTAC data into cBioPortal, limitations of TCGA proteomics array data can be overcome while also providing a user-friendly web interface, a web API and an R client to query the mass spectrometry data together with genomic, epigenomic, and clinical data.

cancer biology↗

bioRxiv2017

Enabling cross-study analysis of RNA-Sequencing data

Driven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data. While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources poses a great challenge, due to differences in sample and data processing. Here, we present a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment and gene expression quantification as well as batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA) and have successfully corrected for study-specific biases, enabling comparative analysis across studies. The normalized data are available for download via GitHub (at https://github.com/mskcc/RNAseqDB).

bioinformatics↗