Biology subjects

Dahiya, S.

Publications and source records attributed to Dahiya, S..

8 recordsLinked to original sources

bioRxiv2025

The Stmn1-lineage contributes to acinar regeneration but not to neoplasia upon oncogenic Kras expression

BACKGROUND & AIMSThe exocrine pancreas has a limited regenerative capacity, but to what extent all acinar cells are involved in this process is unclear. Nevertheless, the heterogenous nature of acinar cells suggests that cells exhibiting higher plasticity might play a more prominent role in acinar regeneration. In that regard, Stmn1-expressing acinar cells have been identified as potential facultative progenitor-like cells in the adult pancreas. Here, we studied Stmn1-progeny under physiological conditions, during regeneration, and in the context of KrasG12D expression. METHODSWe followed the fate of Stmn1-progenies both under baseline conditions, following caerulein-induced acute or chronic pancreatitis, pancreatic duct ligation, and in the context of KrasG12D expression. RESULTSThe Stmn1-lineage contributes to baseline acinar cell turnover under physiological conditions. Furthermore, these cells rapidly proliferate and repopulate the acinar compartment in response to acute injury in an ADM-independent manner. Moreover, acinar regeneration during chronic pancreatitis progression is in conjunction with a decline in the proliferative capacity of the Stmn1-lineage. Interestingly, newly generated acinar cells display increased susceptibility to additional injury during recurrent acute pancreatitis (RAP). Finally, given their inability to form ADMs, the Stmn1-lineage fails to form PanINs upon oncogenic Kras expression. CONCLUSIONSOur findings establish the Stmn1-lineage as a pivotal subpopulation for acinar regeneration. The ability of these cells to restore acinar tissue in an ADM-independent manner distinguishes them as a critical regenerative population. This study presents a new paradigm for acinar regeneration and repair in the context of pancreatitis and neoplasia.

cell biology↗

bioRxiv2024

Modeling glioblastoma tumor progression via CRISPR-engineered brain organoids

Glioblastoma (GBM) is an aggressive form of brain cancer that is highly resistant to therapy due to significant intra-tumoral heterogeneity. The lack of robust in vitro models to study early tumor progression has hindered the development of effective therapies. Here, we develop engineered GBM organoids (eGBOs) harboring GBM subtype-specific oncogenic mutations to investigate the underlying transcriptional regulation of tumor progression. Single-cell and spatial transcriptomic analyses revealed that these mutations disrupt normal neurodevelopment gene regulatory networks resulting in changes in cellular composition and spatial organization. Upon xenotransplantation into immunodeficient mice, eGBOs form tumors that recapitulate the transcriptional and spatial landscape of human GBM samples. Integrative single-cell trajectory analysis of both eGBO-derived tumor cells and patient GBM samples revealed the dynamic gene expression changes in developmental cell states underlying tumor progression. This analysis of eGBOs provides an important validation of engineered cancer organoid models and demonstrates their utility as a model of GBM tumorigenesis for future preclinical development of therapeutics.

bioengineering↗

bioRxiv2023

NF2 Loss-of-Function and Hypoxia Drive Radiation Resistance in Grade 2 Meningiomas

BackgroundWorld Health Organization Grade 2 meningiomas (G2Ms) exhibit an aggressive natural history characterized by recurrence and therapy resistance. G2Ms with histopathological necrosis have been associated with worse local control (LC) following radiation therapy, but drivers and biomarkers of radiation resistance in these G2Ms remain unknown. MethodsWe performed genetic sequencing and histopathological analysis of 113 G2Ms and investigated the role of intratumoral hypoxia as well as genes of interest through knockdown and clonogenic survival following ionizing radiation. Lastly, we performed transcriptional profiling of our in vitro model and 18 G2M tumors using RNA sequencing. ResultsNF2 loss-of-function (LOF) mutations were associated with necrosis in G2Ms (p=0.0127). Tumors with NF2 mutation and necrosis had worse post-radiation LC compared to NF2 wildtype tumors without necrosis (p=0.035). Under hypoxic conditions, NF2 knockdown increased radiation resistance in vitro (p<0.001). Bulk RNA sequencing of our in vitro model revealed NF2- and hypoxia-specific changes and a 50-gene set signature specific to radiation resistant, NF2 knockdown and hypoxic cells, which could distinguish NF2 mutant and necrotic patient G2Ms by unsupervised clustering. Gene set enrichment analysis of patient tumor and in vitro data revealed downregulation of apoptosis and upregulation of proliferation in NF2-deficient and hypoxic cells, which we validated with functional assays. ConclusionsNF2 LOF in the setting of hypoxia confers radiation resistance through transcriptional programs that reduce apoptosis and promote proliferation. These pathways may identify tumors resistant to radiation and represent therapeutic targets that in the future could improve LC in patients with radiation resistant G2Ms. KEY POINTS1. Spontaneous necrosis with NF2 mutations is associated with radio-resistance in WHO G2Ms. 2. NF2 knockdown in the setting of hypoxia confers radio-resistance to meningioma cells in vitro and is driven by increased cell proliferation and decreased apoptosis. IMPORTANCE OF THE STUDYWorld Health Organization Grade 2 meningiomas (G2M) are often treated with surgical resection followed by radiation, especially in the case of recurrence. However, the mechanisms underlying radiation resistance in G2Ms remain to be identified, and moreover, we lack biomarkers to distinguish G2Ms that will respond to radiotherapy from those that are refractory. In this study we perform histological and molecular analysis of a large cohort of G2Ms to identify predictors of radiation resistance. Using these data and an in vitro model of radiation therapy, we demonstrate that radiation resistance in G2Ms is likely driven by the combination of NF2 gene mutations and the hypoxia that accompanies tumor necrosis. Patients whose tumors bear these two features may therefore benefit from alternative treatments that target specific pathways implicated in radiation resistance.

molecular biology↗

bioRxiv2021

Identification of Differentially Expressed Genes and associated pathways common to Eyelid and Non-Ocular Basal Cell Carcinoma to understand the Molecular Biology of BCC

BackgroundEyelid BCC accounts for more than 90% of Eyelid malignant neoplasms. Various aberrant signalling pathways and genes in Non-Ocular BCC have been found whereas Eyelid bcc remains elusive. ObjectiveThis study aims to find the common DEGs of Eyelid and Non-Ocular BCC using bioinformatic analysis and text mining to gain more insights into the molecular aspects common to both BCC non-ocular and Eyelid BCC and to identify common potential prognostic markers. Material and methodThe Gene Expression profiles of Eyelid BCC (GSE103439) and Non-Ocular BCC (GSE53462) were obtained from the NCBI GEO database followed by identification of common DEGs. Protein-Protein interaction and Pathway Enrichment analysis of these screened genes was done using bioinformatic tools like STRING, Cytoscape and BiNGO, DAVID, KEGG respectively. ResultsA total of 181 genes were found common in both datasets. A PPI network was formed for the screened genes and 20 HUB genes were sorted which included CTNNB1, MAPK14, BTRC, EGFR, ADAM17. Pathway enrichment of HUB genes showed that they were dysregulated in carcinogenic and apoptotic pathways that seem to play a role in the progression of both the BCC. ConclusionThe result and findings of bioinformatic analysis highlighted the molecular pathways and genes enriched in both Eyelid BCC as well as Non-Ocular BCC. The identified pathways should be studied further to recognise common molecular events that would lead to the progression of BCC. This may provide a window to explore the prognostic and therapeutic strategies common to both BCC.

bioinformatics↗

bioRxiv2021

Targeting conserved viral virulence determinants by single domain antibodies to block SARS-CoV2 infectivity

We selected SARS-CoV2 specific single domain antibodies (sdAbs) from a previously constructed phage display library using synthetic immunogenic peptides of the virus spike (S) protein as bait. The sdAbs targeting the cleavage site (CS) and the receptor binding domain (RBD) in S protein efficiently neutralised the infectivity of a pseudovirus expressing SARS-CoV2 S protein. Anti-CS sdAb blocked the virus infectivity by inhibiting proteolytic processing of SARS-CoV2 S protein. Both the sdAbs retained characteristic structure within the pH range of 2 to 12 and remained stable upto 65{degrees}C. Furthermore, structural disruptions induced by a high temperature in both the sdAbs were largely reversed upon their gradual cooling and the resulting products neutralised the reporter virus. Our results therefore suggest that targeting CS in addition to the RBD of S protein by sdAbs could serve as a viable option to reduce SARS-CoV2 infectivity and that proteolytic processing of the viral S protein is critical for infection.

immunology↗

bioRxiv2020

Diffusion Basis Spectrum Imaging with Deep Neural Network Differentiates Distinct Histology in Pediatric Brain Tumors

High-grade pediatric brain tumors constitute the highest mortality of cancer-death in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumor clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of pediatric brain tumor. We employed a novel Diffusion Histology Imaging (DHI) approach that incorporates diffusion basis spectrum imaging (DBSI) and deep neural network. DHI aims to detect, differentiate, and quantify heterogenous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor (DC tumor), less densely cellular tumor (LDC tumor), infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 83.3%. Receiver operating analysis (ROC) analysis suggested DHIs great capability in distinguishing individual tumor histology with AUC values (95%CI) of 0.983 (0.985-0.989), 0.961 (0.957-0.964), 0.993 (0.992-0.994), 0.953 (0.947-0.958), 0.974 (0.970-0.978) and 0.980 (0.977-0.983) for normal WM, DC tumor, LDC tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

neuroscience↗

bioRxiv2019

Diffusion Histology Imaging Detects and Classifies Glioblastoma Pathology Missed by Conventional Magnetic Resonance Imaging

PurposeGlioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted for examining GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of GBMs. Experimental DesignWe employ a novel Diffusion Histology Imaging (DHI) approach, combining diffusion basis spectrum imaging (DBSI) and machine learning, to detect, differentiate, and quantify areas of high cellularity, tumor necrosis, and tumor infiltration in GBM. ResultsGd-enhanced T1W or hyper-intense FLAIR failed to reflect the morphological complexity underlying tumor in GBM patients. Contrary to the conventional wisdom that apparent diffusion coefficient (ADC) negatively correlates with increased tumor cellularity, we demonstrate disagreement between ADC and histologically confirmed tumor cellularity in glioblastoma specimens, whereas DBSI-derived restricted isotropic diffusion fraction positively correlated with tumor cellularity in the same specimens. By incorporating DBSI metrics as classifiers for a supervised machine learning algorithm, we accurately predicted high tumor cellularity, tumor necrosis, and tumor infiltration with 87.5%, 89.0% and 93.4% accuracy, respectively. ConclusionOur results suggest that DHI could serve as a favorable alternative to current neuroimaging techniques for guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of glioblastoma. Translational RelevanceCurrent clinical diagnosis, surgical planning, and assessment of treatment response for GBM patients relies heavily on gadolinium-enhanced T1-weighted MRI, which is non-specific for tumor growth and merely reflects a disrupted blood-brain barrier. The complex tumor microenvironment and spatial heterogeneity make GBM difficult to characterize using current clinical imaging modalities. In this study, we developed a novel imaging technique to characterize and accurately predict key histological features of GBM - high tumor cellularity, tumor necrosis, and tumor infiltration. While further validation in a larger cohort of patients is needed, the current proof-of-concept approach could provide a solution to resolve important clinical questions such as the identification of true tumor progression vs. pseudoprogression or radiation necrosis.

neuroscience↗

bioRxiv2017

Temporal and Clonal Progression in a Pediatric Ependymoma Patient Through Multiple Treatments

BackgroundMultiple recurrences after complete resection and irradiation of supratentorial ependymoma are common and frequently result in patient death. However, the molecular basis for treatment resistance, the impact that radiation and other adjuvant therapies have in promoting recurrence, and the use of this information to rationally design effective approaches to treat recurrent ependymoma are unknown. Due to the rarity of these tumors and the even less likely banking of multiple recurrent samples from the same patient, we initiated a study to characterize the evolution of a single patients ependymoma in response to therapy.\n\nMethods and FindingsA combination of high depth, whole genome and exome-based DNA sequencing of germline and tumor specimens, RNA sequencing of tumor specimens, and advanced computational analyses were employed to reconstruct the natural history of a supratentorial ependymoma case in which there were four local recurrences. The findings reveal the extent to which treatment with radiation and chemotherapies resulted in the diversification of the tumor subclonal architecture and shaped the neo-antigen landscape, and provide new insights into possible molecular mechanisms of oncogenesis, treatment response and recurrence.\n\nConclusionsAlthough the recurrent tumors we studied were clearly shaped by therapy, the founding clone was never eradicated by any treatment. We conclude that DNA and RNA sequencing may provide critical prognostic indicators to identify ependymoma patients that should be observed, rather than irradiated, post gross total resection.

cancer biology↗