Publications by authors named "Erdogan Pekcan Erkan"

Anti-tumor immunity is crucial for high-grade serous ovarian cancer (HGSC) prognosis, yet its adaptation upon standard chemotherapy remains poorly understood. Here, we conduct spatial and molecular characterization of 117 HGSC samples collected before and after chemotherapy. Our single-cell and spatial analyses reveal increasingly versatile immune cell states forming spatiotemporally dynamic microcommunities.

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To uncover the intricate, chemotherapy-induced spatiotemporal remodeling of the tumor microenvironment, we conducted integrative spatial and molecular characterization of 97 high-grade serous ovarian cancer (HGSC) samples collected before and after chemotherapy. Using single-cell and spatial analyses, we identify increasingly versatile immune cell states, which form spatiotemporally dynamic microcommunities at the tumor-stroma interface. We demonstrate that chemotherapy triggers spatial redistribution and exhaustion of CD8+ T cells due to prolonged antigen presentation by macrophages, both within interconnected myeloid networks termed "Myelonets" and at the tumor stroma interface.

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Long interspersed nuclear elements (LINE-1s/L1s) are a group of retrotransposons that can copy themselves within a genome. In humans, it is the most successful transposon in nucleotide content. L1 expression is generally mild in normal human tissues, but the activity has been shown to increase significantly in many cancers.

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The broad research use of organoids from high-grade serous ovarian cancer (HGSC) has been hampered by low culture success rates and limited availability of fresh tumor material. Here, we describe a method for generation and long-term expansion of HGSC organoids with efficacy markedly improved over previous reports (53% vs. 23%-38%).

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Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing.

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Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected.

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Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients.

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Motivation: A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples.

Results: To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell-type-specific whole-transcriptome profiles adapted to each individual sample.

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Meningiomas are primary central nervous system (CNS) tumors that originate from the arachnoid cells of the meninges. Recurrence occurs in higher grade meningiomas and a small subset of Grade I meningiomas with benign histology. Currently, there are no established circulating tumor markers which can be used for diagnostic and prognostic purposes in a non-invasive way for meningiomas.

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Homologous recombination deficiency (HRD) correlates with platinum sensitivity in patients with ovarian cancer, which clinically is the most useful predictor of sensitivity to PARPi. To date, there are no reliable diagnostic tools to anticipate response to platinum-based chemotherapy, thus we aimed to develop an functional HRD detection test that could predict both platinum-sensitivity and patient eligibility to targeted drug treatments. We obtained a functional HR score by quantifying homologous recombination (HR) repair after ionizing radiation-induced DNA damage in primary ovarian cancer samples ( = 32).

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Background: Overexpression of minichromosome maintenance (MCM) proteins 2, 3, and 7 is associated with migration and invasion in medulloblastoma (MB). However, expression profiling of all prereplication complex (pre-RC) has not been addressed in MBs.

Procedure: We performed mRNA expression profiling of a large set of pre-RC elements in cell lines and tumor tissues of MB.

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Fibrotic skin diseases are characterized by the accumulation of collagen. The hallmarks of fibrotic skin diseases are unbalanced fibroblast proliferation and differentiation, extracellular matrix production and transforming growth factor-β signalling. Numerous studies have investigated the possibility that microRNAs (miRNAs or miRs) are involved in the pathogenesis of certain fibrotic diseases, including skin, heart, lung and liver diseases.

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Background: Genomic instability is a hallmark of cancer cells, and this cellular phenomenon can emerge as a result of replicative stress. It is possible to take advantage of replicative stress, and enhance it in a targeted way to fight cancer cells. One of such strategies involves targeting the cell division cycle 7-related protein kinase (CDC7), a protein with key roles in regulation of initiation of DNA replication.

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Extracellular vesicles (EVs) are different types of membrane-derived vesicles that originate from the endosomal pathway or the plasma membrane. These vesicles are used as "carriers" in intercellular communication, and are responsible for the transfer of biological cargo (lipids, proteins, RNA species, and DNA) between different cells. Despite the shortcomings in our knowledge of EV biology, attempts to employ EVs as natural delivery tools for therapeutic purposes have been partly successful in different settings.

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Despite intensive studies, the molecular mechanisms by which the genetic materials are uploaded into microvesicles (MVs) are still unknown. This is the first study describing a zipcode-like 25 nucleotide (nt) sequence in the 3'-untranslated region (3'UTR) of mRNAs, with variants of this sequence present in many mRNAs enriched in MVs, as compared to their glioblastoma cells of origin. When this sequence was incorporated into the 3'UTR of a reporter message and expressed in a different cell type, it led to enrichment of the reporter mRNA in MVs.

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miRNAs have been recently implicated as drivers in several carcinogenic processes, where they can act either as oncogenes or as tumor suppressors. Schwannomas arise from Schwann cells, the myelinating cells of the peripheral nervous system. These benign tumors typically result from loss of the neurofibromatosis type 2 (NF2) tumor suppressor gene.

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