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Sunderam, U.

Publications and source records attributed to Sunderam, U..

5 recordsLinked to original sources

Wnt stimulation and inhibition in the development and phenotype of patient-derived gallbladder organoids

Gallbladder cancer (GBC) is a highly lethal malignancy with limited experimental models to study disease biology or evaluate therapeutic responses. Although canonical Wnt activation is commonly used for patient-derived organoid (PDO) development and expansion, gallbladder PDOs has also been generated under Wnt-inhibitory conditions. No comparative assessment has determined how Wnt pathway modulation influences gallbladder PDO development, phenotype or drug response. This study systematically compared the impact of canonical Wnt activation (WNTAct medium containing CHIR99021) versus inhibition (WNTInh medium containing DKK1) on the establishment, propagation, molecular features and therapeutic responses of PDOs generated from malignant or non-malignant gallbladder tissues derived from the same patient. Both media supported successful PDO generation with comparable efficiency, preserving biliary epithelial functions and marker expression. Transcriptomic profiling confirmed selective enrichment of canonical Wnt target genes in PDOs generated in WNTAct cultures. WNTAct conditions enabled markedly superior long-term propagation, whereas WNTInh cultures more consistently retained the dysplastic features in malignant samples. Gemcitabine response assays demonstrated significantly greater drug sensitivity in PDOs grown in WNTAct medium, a phenotype reversible upon media switching but requiring extended adaptation, indicating a dynamic and context-dependent influence of Wnt signaling on chemotherapeutic vulnerability. Collectively, the findings reveal a trade-off between long-term propagation and histological fidelity in gallbladder PDOs and show that Wnt signaling modulates gemcitabine sensitivity in a reversible manner. This comparative framework provides practical guidance for selecting culture conditions for gallbladder PDO based disease modelling and precision oncology applications.

cell biology↗

Insights into gallbladder cancer pathogenesis from a living organoid gallbladder cholangiocyte biorepository

Gallbladder cancer (GBC) while rare worldwide has a high prevalence in India. Pathogenesis is unclear and outcomes poor. Gallbladder cholangiocyte organoids (GCOs) or gallbladder carcinoma organoids (GBCOs) were developed and serially propagated from surgically resected gallbladder tissues with benign or malignant diseases, respectively. Patient derived organoids (PDOs) were derived from 15 normal; 58 inflamed; 12 xanthogranulomatous cholecystitis (XGC); 5 pre-invasive neoplasm and 13 invasive malignant gallbladder pathologies. Protocol optimisation achieved 58% (69/119) success in organoid generation and expansion. Organoids maintained tight junction integrity; P-gp pump and enzymatic activity; preserved tissue-specific gene and protein marker expression; histological features and genetic variations. Cryopreserved organoids from 62 patients with primary tissue and high-quality DNA, RNA and protein derivatives have been banked. In gene expression analyses of tissue, XGC samples clustered with malignant subtypes, separate from benign pathologies. Derived XGC organoids showed a similar clustering. Enriched hallmark pathways in XGC support neoplastic change through chronic inflammation. PDOs generated from different gallbladder pathologies are a promising model to investigate the pathogenesis of GBC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/651639v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@465f3dorg.highwire.dtl.DTLVardef@16c5f0org.highwire.dtl.DTLVardef@11d4807org.highwire.dtl.DTLVardef@163d072_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Identifying Factors Important for Conservation at Sites of Synonymous Variations

Synonymous mutations can have a deleterious effect leading to disease, even though they are not protein altering. Variations at genomic sites leading to synonymous variants are frequently highly conserved across species. Several prediction methods have been developed to assess the impact of synonymous mutations and are highly dependent on having validated sets of both deleterious and benign synonymous mutations. However, validated data available for deleterious synonymous mutations is sparse unlike for missense mutations. Rather than develop a model for predicting pathogenicity of synonymous variants, we seek to understand the relative importance of various factors that lead to conservation at sites of synonymous variants. Our study built machine learning models using various features on a large set of reported and generated synonymous variants (Zeng Z et al, 2019) to predict conservation (Genomic Evolutionary Rate Profiling - Rejected Substitution (GERP RS) base scores and Phylogenetic p-values for 100 vertebrates (PP100)) at genomic sites. We used the extreme gradient boosting classifier to classify sites as high, medium and low conservation at different cutoffs. Our experiments report an AUC between 0.74-0.79 and the sensitivity was significant. Of the features we explored, a few alternate allele independent properties were repeatedly flagged as having high impact. These findings provide information for predictors to further improve models for synonymous variant impact.

bioinformatics↗

Perturbation robustness analyses reveal important parameters in variant interpretation pipelines

MotivationGenome sequencing is being used routinely in clinical and research applications, but subsequent variant interpretation pipelines can vary widely. A systematic approach for exploring parameter choices and selection plays an important role in designing robust pipelines for specific clinical applications. ResultsWe present a framework to be applied in scenarios with limited data whereby expert knowledge informs pipeline refinement. Starting from initial reference variant interpretation pipelines with commonly used parameters, we derived pipelines by perturbing the parameters one by one to determine which parameters can yield meaningful changes in a pipelines performance. We updated the reference pipeline by fixing the value of parameters which have small impact on the pipelines performance. Then we conducted new rounds of perturbation as the process converged, yielding a stable pipeline which is robust. We applied the framework for genetic disease prediction in de-identified exomes from a cohort of 138 individuals with rare Mendelian inborn errors of metabolism (IEMs) and systematically explored how perturbing different parameters affected the pipelines sensitivity and specificity. For this application, we perturbed commonly used parameters in variant interpretation pipelines, including choices of genes, variant callers, transcript models, databases of allele frequencies, databases of curated disease variants, and tools for variant impact prediction. Our analyses showed that choice of variant callers, variant impact prediction tools, MAF threshold, and MAF databases can meaningfully alter results from a pipeline. This work informs the development of exome analysis pipelines designed for newborn metabolic disorder screening and suggests the general application of perturbation analysis in genome interpretation pipeline design.

bioinformatics↗

DNA from dried blood spots yields high quality sequences for exome analysis

BackgroundDNA sequencing of archived dried blood spots (DBS) collected by newborn screening programs constitutes a potential health resource to study newborn disorders and understand genotype-phenotype relationships. However, its essential to verify that sequencing reads from DBS derived DNA are suitable for variant discovery. ResultsWe explored 16 metrics to comprehensively assess the quality of sequencing reads from 180 DBS and 35 whole blood (WB) samples. These metrics were used to assess a) mapping of reads to the reference genome, b) degree of DNA damage, and c) variant calling. Reads from both sets mapped with similar efficiencies, had similar overall DNA damage rates, measured by the mismatch rate with the reference genome, and produced variant calls sets with similar Transition-Transversion ratios. While evaluating single nucleotide changes that may have arisen from DNA damage, we observed that the A>T and T>A changes were more frequent in DNA from DBS than from WB. However, this did not affect the accuracy of variant calling, with DBS samples yielding a comparable count of high quality SNVs and indels in samples with at least 50x coverage. ConclusionsOverall, DBS DNA provided exome sequencing data of sufficient quality for clinical interpretation.

genomics↗