Biology subjects

Dogan, A.

Publications and source records attributed to Dogan, A..

13 recordsLinked to original sources

bioRxiv2026

Peptide screening enables optimised biofunctional hydrogels for cultivated meat tissue engineering

Cultivated meat is an emerging biotechnology that aims to produce edible tissues in an ethical and sustainable manner. However, the recreation of skeletal muscle tissue that replicates the protein composition and sensory characteristics of traditional meat is a major challenge. Skeletal muscle tissue engineering requires non-animal-based scaffolds which are inexpensive and food-safe, while meeting specific mechanical requirements with respect to viscosity, stress-relaxation and stiffness. While many of these characteristics can be fulfilled by alginate-based biomaterials, a key limitation of alginate is its lack of intrinsic attachment sites for animal cells, preventing efficient adhesion, differentiation and tissue formation. Here, we established a screening platform to evaluate extracellular matrix (ECM)-mimicking peptides as functionalisations of alginate scaffolds in 2D. Our platform enables high-throughput assessment of cell/peptide interactions, serving as a predictive tool for 3D tissue constructs. Our screen identified two RGD-containing sequences (vitronectin- and fibronectin-mimicking peptides) as most effective in promoting attachment and myogenic fusion of bovine satellite cells. Notably, these peptides outperformed more complex mixtures containing up to seven different ECM-mimicking peptides. Our findings provide a streamlined approach for optimising biomaterial functionalisations for cultivated meat applications, and lay the groundwork for future advancements in scalable, sustainable skeletal muscle tissue engineering.

bioengineering↗

bioRxiv2026

Ecological determinants of disease and immunity in myelodysplastic syndromes

Myelodysplastic syndromes (MDS) are clonal hematopoietic malignancies characterized by ineffective hematopoiesis, dysplastic morphology, and risk of progression to acute myeloid leukemia. While genomic alterations intrinsic to malignant MDS disease-initiating cells have been well-characterized, molecular assessment of the bone marrow in situ has been limited. Here we present single cell spatial assessment of gene expression, T cell receptors, as well as MDS-defining mutations and RNA isoforms within fixed, decalcified human bone marrow core biopsies (41 MDS, 15 controls) paired with single cell immunogenomic analysis of bone marrow aspirates (35 MDS, 6 controls). Bone marrow spatial analyses of >7.47x106 cells identified hematopoietic and non-hematopoietic populations not readily captured in dissociated tissue. We developed computational methods to compare ecological niche structures, revealing enriched hematopoietic niches and reorganization of T cell immunity in MDS patient bone marrow. In situ genotyping of mutant cells revealed increased TGF{beta} expression in malignant megakaryocytes suppressing local T cell cytotoxicity. By contrast, TGF{beta} signaling was disrupted in mutant cells due to aberrant splicing of multiple TGF{beta} signaling components. This study provides a spatially resolved landscape of human MDS bone marrow and uncovers mechanisms by which malignant cells simultaneously promote intrinsic clonal persistence while rewiring the microenvironment for immune escape.

cancer biology↗

bioRxiv2025

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision oncology. While machine learning approaches have been applied to both digital pathology and cancer genomics, previous work has been limited in sample size and has typically aggregated granular cancer subtypes into coarse groupings, likely obfuscating informative molecular and prognostic associations and phenotypic variation of more detailed tumor subtypes. Accordingly, we collated 378,123 hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) with matched targeted DNA clinical sequencing results and OncoTree detailed cancer subtypes from a real-world cohort of 71,142 patients. Using this scaled, granular dataset and a cancer subtype knowledge graph, we developed Mosaic: a family of calibrated machine learning models using H&E WSI embeddings to classify tumors and identify molecular phenotypes across 163 detailed subtypes. The cancer subtyping module (Aeon) achieved an area under the receiver operating characteristic curve (AUROC) of 0.992 overall, with 161/163 subtypes reaching an AUROC [≥] 0.90 and improved performance over a state-of-the-art genomics-based classifier. The genomic inference module (Paladin) achieved an AUROC [≥] 0.80 for 167 pairs of detailed subtypes and genomic targets. We further used the learned histopathologic representations to i) identify key associations of the histopathologic embeddings with clinical biomarkers; ii) identify unsupervised sub-clusters of tumors with genomic determinants of tumor phenotype; iii) specify granular diagnoses for cancers of unknown primary, evaluated by genomic associations and expected clinical outcome distributions; iv) annotate functional significance for variants of uncertain significance (VUS); and v) identify cases that mimic the phenotypic effect of known DNA variants on H&E in the absence of detectable DNA alterations. Taken together, this work advances our understanding of phenotypic variation of granular tumor subtypes, their relevance to enhanced diagnostics, and their potential utility in risk stratification with multimodal machine learning in cancer.

cancer biology↗

bioRxiv2024

Temporal Genomic Dynamics Shape Clinical Trajectory in Multiple Myeloma

To comprehensively unravel the temporal relationship between initiating and driver events and its impact on clinical outcomes, we analyzed 421 whole-genome sequencing profiles from 382 patients. Using clock-like mutational signatures, we estimated a time lag of 2-4 decades between initiating events and diagnosis. In patients with hyperdiploidy, we demonstrate that trisomies of odd-numbered chromosomes can be acquired simultaneously with other chromosomal gains, such as 1q gain. We provide evidence that hyperdiploidy is acquired after canonical IGH translocation when both events are present. Finally, patients with early 1q gain had adverse outcomes similar to those with 1q amplification (>1 extra-copies), but faring worse than those with late 1q gain. This underscores that the prognostic impact of 1q gain/amp depends more on the timing of acquisition than on the number of extra copies gained. Overall, this study contributes to a better understanding of the life history of MM and may have prognostic implications.

cancer biology↗

bioRxiv2023

Short-stranded zein fibers for muscle tissue engineering in alginate-based hydrogels

Cultivated meat is a nascent technology that aims to produce an environmentally and animal-friendly alternative to conventional meat. Producing skeletal muscle tissue in an animal-free system allowing for high levels of myofusion and maturation is important for the nutritional and sensorial value of cultivated meat. Alginate is an attractive biomaterial to support muscle formation as it is food-safe, sustainable, cheap, and can be cross-linked using non-toxic methods. Although alginate can be functionalized to promote cell attachment, limitations in its mechanical properties, including form, viscosity and stress relaxation, hinder cellular capacity for myogenic differentiation and maturation in alginate-based hydrogels. Here, we show that the addition of electrospun short-stranded zein fibers increased hydrogel degradation, resulting in faster compaction, improved cell-gel interaction and enhanced alignment of bovine muscle precursor cells. We conclude that fiber-hydrogel composites are a promising approach to support optimal formation of 3D constructs, by improving tissue stability and thus prolonging culture duration. Together, this improves muscle-related protein content by facilitating myogenic differentiation and priming muscle organoids for maturation.

bioengineering↗

bioRxiv2023

Optimisation of cell fate determination for cultured muscle differentiation

Production of cultured meat requires defined medium formulations for the robust differentiation of myogenic cells into mature skeletal muscle fibers in vitro. Whilst such formulations can drive myogenic differentiation to an extent similar to serum-starvation based protocols, these cultures are invariably heterogeneous in nature, with a significant proportion of cells not participating in myofusion, limiting maturation of the muscle. Here, we use RNA sequencing to characterise this heterogeneity at single-nucleus resolution, identifying distinct cellular subpopulations, including proliferative cells that fail to exit the cell cycle, and reserve cells that do not commit to myogenic differentiation. We show that the ERK, NOTCH and RXR pathways act during the first stages of myogenic cell fate determination, and by targeting these pathways, cell cycle exit can be promoted whilst abrogating reserve cell formation. Under these improved culture conditions, fusion indices close to 100% can be robustly obtained in 2D culture. Finally, we demonstrate that this translates to higher levels of myotube formation and muscle protein accumulation in animal component-free bioartificial muscle constructs, providing proof of principle for the generation of highly differentiated cultured muscle with excellent mimicry to traditional muscle.

cell biology↗

bioRxiv2023

DeepHeme: A generalizable, bone marrow classifierwith hematopathologist-level performance

Morphology-based classification of cells in the bone marrow aspirate (BMA) is a key step in the diagnosis and management of hematologic malignancies. However, it is time-intensive and must be performed by expert hematopathologists and laboratory professionals. We curated a large, high-quality dataset of 41,595 hematopathologist consensus-annotated single-cell images extracted from BMA whole slide images (WSIs) containing 23 morphologic classes from the clinical archives of the University of California, San Francisco. We trained a convolutional neural network, DeepHeme, to classify images in this dataset, achieving a mean area under the curve (AUC) of 0.99. DeepHeme was then externally validated on WSIs from Memorial Sloan Kettering Cancer Center, with a similar AUC of 0.98, demonstrating robust generalization. When compared to individual hematopathologists from three different top academic medical centers, the algorithm outperformed all three. Finally, DeepHeme reliably identified cell states such as mitosis, paving the way for image-based quantification of mitotic index in a cell-specific manner, which may have important clinical applications.

bioinformatics↗

bioRxiv2022

Single cell genotypic and phenotypic analysis of measurable residual disease in acute myeloid leukemia

Measurable residual disease (MRD), defined as the population of cancer cells which persists following therapy, serves as the critical reservoir for disease relapse in acute myeloid leukemia (AML) and other malignancies. Understanding the biology enabling MRD clones to resist therapy is necessary to guide the development of more effective curative treatments. Discriminating between residual leukemic clones, preleukemic clones and normal precursors remains a challenge with current MRD tools. Herein, we developed a single cell (sc) MRD assay by combining flow cytometric enrichment of the targeted precursor/blast population with integrated scDNA sequencing and immunophenotyping. Our scMRD assay shows high sensitivity of approximately 0.01%, deconvolutes clonal architecture and provides clone-specific immunophenotypic data. In summary, our scMRD assay enhances MRD detection and simultaneously illuminates the clonal architecture of clonal hematopoiesis/pre-leukemic and leukemic cells surviving AML therapy. Statement of significanceScMRD assay integrates mutation and immunophenotype at single cell resolution and therefore distinguishes clonal hematopoiesis/preleukemic vs. leukemic clones. This study serves as a framework for identifying high-risk MRD clones and improving our understanding of both the molecular drivers and vulnerabilities of therapy resistant AML clones.

pathology↗

bioRxiv2020

Copy number signatures predict chromothripsis and associate with poor clinical outcomes in patients with newly diagnosed multiple myeloma

Chromothripsis is detectable in 20-30% of newly diagnosed multiple myeloma (NDMM) patients and is emerging as a new independent adverse prognostic factor. In this study, we interrogate 752 NDMM patients using whole genome sequencing (WGS) to study the relationship of copy number (CN) signatures to chromothripsis and show they are highly associated. CN signatures are highly predictive of the presence of chromothripsis (AUC=0.90) and can be used to identify its adverse prognostic impact. The ability of CN signatures to predict the presence of chromothripsis was confirmed in a validation series of WGS comprised of 235 hematological cancers (AUC=0.97) and an independent series of 34 NDMM (AUC=0.87). We show that CN signatures can also be derived from whole exome data (WES) and using 677 cases from the same series of NDMM, we were able to predict both the presence of chromothripsis (AUC=0.82) and its adverse prognostic impact. CN signatures constitute a flexible tool to identify the presence of chromothripsis and is applicable to WES and WGS data.

genomics↗

bioRxiv2020

Whole genome sequencing provides evidence of two biologically and clinically distinct entities of asymptomatic monoclonal gammopathies: progressive versus stable myeloma precursor condition

Multiple myeloma (MM) is consistently preceded by precursor conditions recognized clinically as monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). We interrogate, for the first time, the whole genome sequence (WGS) profile of 18 MGUS and compare them with those from 14 SMMs and 80 MMs. We show that cases with a non-progressing, clinically stable myeloma precursor condition (n=15) are characterized by later initiation in the patients life and by the absence of myeloma defining genomic events including: chromothripsis, templated insertions, mutations in driver genes, aneuploidy, and canonical APOBEC mutational activity. This data provides evidence that WGS can be used to recognize two biologically and clinically distinct myeloma precursor entities that are either progressive or stable.

cancer biology↗

bioRxiv2020

Plasmacytoid dendritic cell expansion defines a distinct subset of RUNX1 mutated acute myeloid leukemia

Plasmacytoid dendritic cells (pDC) are the principal natural type I interferon producing dendritic cells. Neoplastic expansion of pDCs and pDC precursors leads to blastic plasmacytoid dendritic cell neoplasm (BPDCN) and clonal expansion of mature pDCs has been described in chronic myelomonocytic leukemia (CMML). The role of pDC expansion in acute myeloid leukemia (AML) is poorly studied. Here we characterize AML patients with pDC expansion (pDC-AML), which we observe in approximately 5% of AML. pDC-AML often possess crosslineage antigen expression and have adverse risk stratification with poor outcome. RUNX1 mutations are the most common somatic alterations in pDC-AML (>70%) and are much more common than in AML without PDC expansion. We demonstrate that pDCs are clonally related to, and originate from, leukemic blasts in pDC-AML. We further demonstrate that leukemic blasts from RUNX1-mutated AML upregulate a pDC transcriptional program, poising the cells towards pDC differentiation and expansion. Finally, tagraxofusp, a targeted therapy directed to CD123, reduces leukemic burden and eliminates pDCs in a patient-derived xenograft model. In conclusion, pDC-AML is characterized by a high frequency of RUNX1 mutations and increased expression of a pDC transcriptional program. CD123 targeting represents a potential treatment approach for pDC-AML.Competing Interest StatementConflict-of-interest disclosure: W.X. has received research support from Stemline Therapeutics. S.F.C. is a consultant for Imago Biosciences and has received honoraria from DAVA Oncology. A.D.G. served on advisory boards or as a consultant for Abbvie, Aptose, Celgene, Daiichi Sanyko, Genentech, received research funding from Abbvie, ADC Therapeutics, Aprea, AROG, Daiichi Sanyko, Pfizer, received Honoraria from Dava Oncology. R.K.R has received consulting fees from: Constellation, Incyte, Celgene, Promedior, CTI, Jazz Pharmaceuticals, Blueprint, Stemline, and research funding from Incyte, Constellation, and Stemline Therapeutics. M.S.T has received research funding from AbbVie, Cellerant, Orsenix, ADC Therapeutics, Biosight, Glycomimetics, Rafael Pharmaceuticals and Amgen. He also served on advisory Boards for AbbVie, BioLineRx, Daiichi-Sankyo, Orsenix, KAHR, Rigel, Nohla, Delta Fly Pharma, Tetraphase, Oncolyze, Jazz Pharma, Roche, Biosight and Novartis. He received royalties from UpToDate. R.L.L. is on the supervisory board of Qiagen and is a scientific advisor to Loxo (until 2019), Auron, Ajax, Mission Bio, Imago, C4 Therapeutics and Isoplexis, which each include an equity interest. He receives research support from and consulted for Celgene and Roche, he has received research support from Prelude Therapeutics, and he has consulted for Incyte, Novartis and Janssen. He has received honoraria from Lilly and Amgen for invited lectures and from Gilead for grant reviews.View Full Text

pathology↗

bioRxiv2020

Accelerated single cell seeding in relapsed multiple myeloma

The malignant progression of multiple myeloma is characterized by the seeding of cancer cells in different anatomic sites followed by their clonal expansion. It has been demonstrated that this spatial evolution at varying anatomic sites is characterized by genomic heterogeneity. However, it is unclear whether each anatomic site at relapse reflects the expansion of pre-existing but previously undetected disease or secondary seeding from other sites. Furthermore, genomic evolution over time at spatially distinct sites of disease has not been investigated in a systematic manner. To address this, we interrogated 25 samples, by whole genome sequencing, collected at autopsy from 4 patients with relapsed multiple myeloma and demonstrated that each site had a unique evolutionary trajectory characterized by distinct single and complex structural variants and copy number changes. By analyzing the landscape of mutational signatures at these sites and for an additional set of 125 published whole exomes collected from 51 patients, we demonstrate the profound mutagenic effect of melphalan and platinum in relapsed multiple myeloma. Chemotherapy-related mutagenic processes are known to introduce hundreds of unique mutations in each surviving cancer cell. These mutations can be detectable by bulk sequencing only in cases of clonal expansion of a single cancer cell bearing the mutational signature linked to chemotherapy exposure thus representing a unique single-cell genomic barcode linked to a discrete time window in each patients life. We leveraged this concept to show that multiple myeloma systemic seeding is accelerated at clinical relapse and appears to be driven by the survival and subsequent expansion of a single myeloma cell following treatment with high dose melphalan therapy and autologous stem cell transplant.

cancer biology↗

bioRxiv2019

Revealing the impact of recurrent and rare structural variants in multiple myeloma

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive classification and analysis of SVs in multiple myeloma, interrogating a large cohort of 762 patients with whole genome and RNA sequencing. We identified 100 SV hotspots involving 31 new candidate driver genes, including drug targets BCMA (TNFRSF17) and SLAMF7. Complex SVs, including chromothripsis and templated insertions, were present in 61 % of patients and frequently resulted in the simultaneous acquisition of multiple drivers. After accounting for all recurrent events, 63 % of SVs remained unexplained. Intriguingly, these rare SVs were associated with up to 7-fold enrichment for outlier gene expression, indicating that many rare driver SVs remain unrecognized and are likely important in the biology of individual tumors.

genomics↗