Biology subjects

Nykter, M.

Publications and source records attributed to Nykter, M..

23 records · Page 2Linked to original sources

bioRxiv2021

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

Prostate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

cancer biology↗

bioRxiv2020

Chromatin accessibility analysis uncovers regulatory element landscape in prostate cancer progression

Aberrant oncogene functions and structural variation alter the chromatin structure in cancer cells. While gene regulation by chromatin states has been studied extensively, chromatin accessibility and its relevance in aberrant gene expression during prostate cancer progression is not well understood. Here, we report a genome-wide chromatin accessibility analysis of clinical tissue samples of benign prostatic hyperplasia (BPH), untreated primary prostate cancer (PC) and castration-resistant prostate cancer (CRPC) and integrative analysis with transcriptome, methylome, and proteome profiles of the same samples to uncover disease-relevant regulatory elements and their association to altered gene expression during prostate cancer progression. While promoter accessibility is consistent during disease initiation and progression, at distal sites chromatin accessibility is variable enabling transcription factors (TFs) binding patterns that are differently activated in different patients and disease stages. We identify consistent progression-related chromatin alterations during the progression to CRPC. By studying the TF binding patterns, we demonstrate the activation and suppression of androgen receptor-driven regulatory programs during PC progression and identify complementary TF regulatory modules characterized by e.g. MYC and glucocorticoid receptor. By correlation analysis we assign at least one putative regulatory region for 62% of genes and 85% of proteins differentially expressed during prostate cancer progression. Taken together, our analysis of the chromatin landscape in PC identifies putative regulatory elements for the majority of cancer-associated genes and characterizes their impact on the cancer phenotype.

cancer biology↗

bioRxiv2019

Prostate Specific Membrane Antigen expression in the vasculature of primary lung carcinomas associates with faster metastatic dissemination to brain

Glioblastomas and brain metastases (BM) of solid tumors are the most common central nervous system neoplasms associated with very unfavorable prognosis. In this study, we report the association of Prostate Specific Membrane Antigen with various clinical parameters in a large cohort of primary and secondary brain tumors. A tissue micro array containing 371 cases of ascending grade gliomas pertaining to astrocytic origin, samples of 52 cases of primary lung carcinomas with matching brain metastases with follow-up time accounting to 10.4 years was evaluated for PSMA expression using immunohistochemistry. In addition, PSMA expression was studied in brain metastases arising from melanomas and breast carcinomas. Neovascular expression of PSMA was evident alongside with high expression in the proliferating microvasculature of glioblastomas when compared to the tumor cell expression. This result corroborated with the results obtained from the in silico (cancer genome databases) analyses. In the matched primary lung cancers and their brain metastases (n = 52), vascular PSMA expression in primary tumors led to significantly accelerated metastatic dissemination to the brain with a tendency towards poor overall survival. Taken together, we report the vascular expression of PSMA in the primary and secondary brain tumors that globally associates with the malignant progression and poor outcome of the patients.

pathology↗

bioRxiv2019

Immunogenomic landscape of hematological malignancies

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. Here, we integrated over 8,000 transcriptomes and over 1,000 samples with multilevel genomic data of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival. Infiltration of cytotoxic immune cells was associated with distinct microenvironmental responses and driver alterations in different cancers, such as TP53 in acute myeloid leukemia and DTX1 in diffuse large B cell lymphoma. Epigenetic modification of CIITA regulating antigen presentation, cancer type-specific immune checkpoints such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity. Prognostic models highlighted the significance of immunological properties in predicting survival. Our study represents the most comprehensive effort to date to link immunology with cancer subtypes and genomics in hematological malignancies, providing a resource to guide future studies and immunotherapy development.

immunology↗

bioRxiv2018

Data-driven characterization of molecular phenotypes across heterogenous sample collections

The existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on their molecular profile. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensional reduction algorithm t-SNE with multi-center and multi-platform data representing hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation of molecular disease subtypes, comparison of sample groups between separate t-SNE representations, or maps, and characterization of the obtained clusters based on pathway databases and additional multi-omics data. In the example application, our approach revealed differential activity of SAM-dependent DNA methylation pathway in the acute myeloid leukemia patient cluster characterized with CEBPA mutations that accordingly was validated to have globally elevated DNA methylation levels.

bioinformatics↗