Publications by authors named "A Carina Ståhlberg"

107 Publications

Ultrasensitive circulating tumor DNA analysis enables precision medicine: experimental workflow considerations.

Expert Rev Mol Diagn 2021 Mar 8:1-12. Epub 2021 Mar 8.

Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.

Circulating tumor DNA (ctDNA) has become a relevant biomarker in cancer management, allowing tumor assessment through analysis of minimally invasive liquid biopsies. Applications include screening, diagnostics, monitoring of treatment efficacy and detection of minimal residual disease as well as relapse. The potential of ctDNA analysis is significant, but several biological and technical challenges need to be addressed before widespread clinical implementation. Several clinical applications where ctDNA analysis may be beneficial require detection of individual DNA molecules. Consequently, to acquire accurate and informative data the entire workflow from sampling to final data interpretation needs to be optimized. In this review, we discuss the biological and technical challenges of ctDNA analysis and how preanalytical and analytical approaches affect different cancer applications. While numerous studies have demonstrated the potential of using ctDNA in cancer applications, yet few reports about true clinical utility exist. Despite encouraging data, the sensitivity of ctDNA analyses, . the probability to detect presence of cancer in liquid biopsies, is still an issue. Analysis of multiple mutations in combination with simultaneous assessment of other analytes is one solution. Improved standardization and guidelines will also facilitate the introduction of ctDNA analysis into clinical routine.
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http://dx.doi.org/10.1080/14737159.2021.1889371DOI Listing
March 2021

DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics.

Int J Mol Sci 2021 Jan 30;22(3). Epub 2021 Jan 30.

Oslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway.

The growing attention toward the benefits of single-cell RNA sequencing (scRNA-seq) is leading to a myriad of computational packages for the analysis of different aspects of scRNA-seq data. For researchers without advanced programing skills, it is very challenging to combine several packages in order to perform the desired analysis in a simple and reproducible way. Here we present DIscBIO, an open-source, multi-algorithmic pipeline for easy, efficient and reproducible analysis of cellular sub-populations at the transcriptomic level. The pipeline integrates multiple scRNA-seq packages and allows biomarker discovery with decision trees and gene enrichment analysis in a network context using single-cell sequencing read counts through clustering and differential analysis. DIscBIO is freely available as an R package. It can be run either in command-line mode or through a user-friendly computational pipeline using Jupyter notebooks. We showcase all pipeline features using two scRNA-seq datasets. The first dataset consists of circulating tumor cells from patients with breast cancer. The second one is a cell cycle regulation dataset in myxoid liposarcoma. All analyses are available as notebooks that integrate in a sequential narrative R code with explanatory text and output data and images. R users can use the notebooks to understand the different steps of the pipeline and will guide them to explore their scRNA-seq data. We also provide a cloud version using Binder that allows the execution of the pipeline without the need of downloading R, Jupyter or any of the packages used by the pipeline. The cloud version can serve as a tutorial for training purposes, especially for those that are not R users or have limited programing skills. However, in order to do meaningful scRNA-seq analyses, all users will need to understand the implemented methods and their possible options and limitations.
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http://dx.doi.org/10.3390/ijms22031399DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866810PMC
January 2021

Breast cancer patient-derived scaffolds as a tool to monitor chemotherapy responses in human tumor microenvironments.

J Cell Physiol 2021 Jun 23;236(6):4709-4724. Epub 2020 Dec 23.

Department of Laboratory Medicine, Sahlgrenska Center for Cancer Research, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Breast cancer is a heterogeneous disease where the tumor microenvironment, including extracellular components, plays a crucial role in tumor progression, potentially modulating treatment response. Different approaches have been used to develop three-dimensional models able to recapitulate the complexity of the extracellular matrix. Here, we use cell-free patient-derived scaffolds (PDSs) generated from breast cancer samples that were recellularized with cancer cell lines as an in vivo-like culture system for drug testing. We show that PDS cultured MCF7 cancer cells increased their resistance against the front-line chemotherapy drugs 5-fluorouracil, doxorubicin and paclitaxel in comparison to traditional two-dimensional cell cultures. The gene expression of the environmentally adapted cancer cells was modulated in different ways depending on the drug and the concentration used. High doses of doxorubicin reduced cancer stem cell features, whereas 5-fluorouracil increased stemness and decreased the proliferative phenotype. By using PDSs repopulated with other breast cancer cell lines, T-47D and MDA-MB-231, we observed both general and cell line specific drug responses. In summary, PDSs can be used to examine the extracellular matrix influence on cancer drug responses and for testing novel compounds in in vivo-like microenvironments.
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http://dx.doi.org/10.1002/jcp.30191DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049042PMC
June 2021

Patient-derived scaffolds as a model of colorectal cancer.

Cancer Med 2021 02 23;10(3):867-882. Epub 2020 Dec 23.

Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.

Background: Colorectal cancer is the second most common cause of cancer-related death worldwide and standardized therapies often fail to treat the more aggressive and progressive types of colorectal cancer. Tumor cell heterogeneity and influence from the surrounding tumor microenvironment (TME) contribute to the complexity of the disease and large variability in clinical outcomes.

Methods: To model the heterogeneous nature of colorectal cancer, we used patient-derived scaffolds (PDS), which were obtained via decellularization of surgically resected tumor material, as a growth substrate for standardized cell lines.

Results: After confirmation of native cell absence and validation of the structural and compositional integrity of the matrix, 89 colorectal PDS were repopulated with colon cancer cell line HT29. After 3 weeks of PDS culture, HT29 cells varied their gene and protein expression profiles considerably compared to 2D-grown HT29 cells. Markers associated with proliferation were consistently decreased, while markers associated with pluripotency were increased in PDS-grown cells compared to their 2D counterparts. When comparing the PDS-induced changes in HT29 cells with clinically relevant tumor information from individual patients, we observed significant associations between stemness/pluripotency markers and tumor location, and between epithelial-to-mesenchymal transition (EMT) markers and cancer mortality. Kaplan-Meier analysis revealed that low PDS-induced EMT correlated with worse cancer-specific survival.

Conclusions: The colorectal PDS model can be used as a simplified personalized tool that can potentially reveal important diagnostic and pathophysiological information related to the TME.
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http://dx.doi.org/10.1002/cam4.3668DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897946PMC
February 2021

Ultrasensitive DNA Immune Repertoire Sequencing Using Unique Molecular Identifiers.

Clin Chem 2020 09;66(9):1228-1237

Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.

Background: Immune repertoire sequencing of the T-cell receptor can identify clonotypes that have expanded as a result of antigen recognition or hematological malignancies. However, current sequencing protocols display limitations with nonuniform amplification and polymerase-induced errors during sequencing. Here, we developed a sequencing method that overcame these issues and applied it to γδ T cells, a cell type that plays a unique role in immunity, autoimmunity, homeostasis of intestine, skin, adipose tissue, and cancer biology.

Methods: The ultrasensitive immune repertoire sequencing method used PCR-introduced unique molecular identifiers. We constructed a 32-panel assay that captured the full diversity of the recombined T-cell receptor delta loci in γδ T cells. The protocol was validated on synthetic reference molecules and blood samples of healthy individuals.

Results: The 32-panel assay displayed wide dynamic range, high reproducibility, and analytical sensitivity with single-nucleotide resolution. The method corrected for sequencing-depended quantification bias and polymerase-induced errors and could be applied to both enriched and nonenriched cells. Healthy donors displayed oligoclonal expansion of γδ T cells and similar frequencies of clonotypes were detected in both enrichment and nonenriched samples.

Conclusions: Ultrasensitive immune repertoire sequencing strategy enables quantification of individual and specific clonotypes in a background that can be applied to clinical as well as basic application areas. Our approach is simple, flexible, and can easily be implemented in any molecular laboratory.
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http://dx.doi.org/10.1093/clinchem/hvaa159DOI Listing
September 2020