Biology subjects

Tran, L. M.

Publications and source records attributed to Tran, L. M..

8 recordsLinked to original sources

bioRxiv2025

Archetype analysis of lung adenocarcinoma premalignancy links heterogeneity in premalignant lesions to diverging features of invasive disease

ABSTRACTLung adenocarcinoma (LUAD), the most common form of lung cancer, is a heterogeneous disease with highly variable histopathologic features and clinical outcomes. LUAD premalignant lesions (PMLs) are localized proliferative lesions of atypical pneumocytes that proliferate along the alveolar walls. In this study, we characterized the molecular heterogeneity across PMLs, regardless of histologic designation, and identified four unique groups or "archetypes" of PMLs using bulk RNA and exome sequencing data from laser captured microdissected PMLs, normal, and tumor tissue from LUAD resection cases. The archetypes were defined based on expression of recurrent gene co-expression modules discovered using the LUAD PMLs we profiled and three publicly available datasets. One PML archetype, termed "proliferation", was associated with increased expression of genes involved in cell proliferation, a pro-tumor immune environment, and enrichment for EGFR driver mutations. Another archetype, termed "normal-like", was associated with similar features to normal tissue, an anti-tumor immune response, and lacked enrichment for driver mutations compared to other archetypes. We projected the PML archetypes into independent gene expression datasets profiling LUAD and found that tumors closest to the proliferation archetype were enriched for multiple features of aggressive LUAD, including high tumor grade and lymph node invasion, and had significantly lower disease-free survival. Proliferation archetype PMLs may represent a subset of lesions with more aggressive features that could improve patient stratification and suggest novel targets for lung cancer interception.

cancer biology↗

bioRxiv2023

A shift in the mechanisms controlling hippocampal engram formation during brain maturation

The ability to form precise, episodic memories develops with age, with young children only able to form gist-like memories that lack precision. The cellular and molecular events in the developing hippocampus that underlie the emergence of precise, episodic-like memory formation are unclear. In mice, the absence of a competitive neuronal engram allocation process in the immature hippocampus precluded the formation of sparse engrams and precise memories until the fourth postnatal week, when inhibitory circuits in the hippocampus mature. This age-dependent shift in precision of episodic-like memories involved the functional maturation of parvalbumin-expressing interneurons in subfield CA1 by extracellular perineuronal nets which is necessary and sufficient for the onset of competitive neuronal allocation, sparse engram formation, and memory precision. One-Sentence SummaryEpisodic-like memory precision requires maturation of hippocampal inhibitory interneurons by the extracellular matrix.

neuroscience↗

bioRxiv2022

Can neurogenesis act as a neural regularizer?

New neurons are continuously generated in the subgranular zone of the dentate gyrus throughout adulthood. These new neurons gradually integrate into hippocampal circuits, forming new naive synapses. Viewed from this perspective, these new neurons may represent a significant source of wiring noise in hippocampal networks. In machine learning, such noise injection is commonly used as a regularization technique. Regularization techniques help prevent overfitting training data, and allow models to generalize learning to new, unseen data. Using a computational modeling approach, here we ask whether a neurogenesis-like process similarly acts as a regularizer, facilitating generalization in a category learning task. In a convolutional neural network (CNN) trained on the CIFAR-10 object recognition dataset, we modeled neurogenesis as a replacement/turnover mechanism, where weights for a randomly chosen small subset of neurons in a chosen hidden layer were re-initialized to new values as the model learned to categorize 10 different classes of objects. We found that neurogenesis enhanced generalization on unseen test data compared to networks with no neurogenesis. Moreover, neurogenic networks either outperformed or performed similarly to networks with conventional noise injection (i.e., dropout, weight decay, and neural noise). These results suggest that neurogenesis can enhance generalization in hippocampal learning through noise-injection, expanding on the roles that neurogenesis may have in cognition. Author SummaryIn deep neural networks, various forms of noise injection are used as regularization techniques to prevent overfitting and promote generalization on unseen test data. Here, we were interested in whether adult neurogenesis- the lifelong production of new neurons in the hippocampus- might similarly function as a regularizer in the brain. We explored this question computationally, assessing whether implementing a neurogenesis-like process in a hidden layer within a convolutional neural network trained in a category learning task would prevent overfitting and promote generalization. We found that neurogenesis regularization was as least as effective as, or more effective than, conventional regularizers (i.e., dropout, weight decay and neural noise) in improving model performance. These results suggest that optimal levels of hippocampal neurogenesis may improve memory-guided decision making by preventing overfitting, thereby promoting the formation of more generalized memories that can be applied in a broader range of circumstances. We outline how these predictions may be evaluated behaviorally in rodents with altered hippocampal neurogenesis.

neuroscience↗

bioRxiv2021

Metabolomics of lung microdissections reveals region- and sex-specific metabolic effects of acute naphthalene exposure in mice

Naphthalene is a ubiquitous environmental contaminant produced by combustion of fossil fuels and is a primary constituent of both mainstream and side stream tobacco smoke. Naphthalene elicits region-specific toxicity in airway club cells through cytochrome P450 (P450)-mediated bioactivation, resulting in depletion of glutathione and subsequent cytotoxicity. While effects of naphthalene in mice have been extensively studied, few experiments have characterized global metabolomic changes in the lung. In individual lung regions, we found metabolomic changes in microdissected mouse lung conducting airways and parenchyma obtained from animals sacrificed 2, 6, and 24 hours following naphthalene treatment. Data on 577 unique identified metabolites were acquired by accurate mass spectrometry-based assays focusing on lipidomics and non-targeted metabolomics of hydrophilic compounds. Statistical analyses revealed distinct metabolite profiles between the two major lung regions. In addition, the number and magnitude of statistically significant exposure-induced changes in metabolite abundance were different between lung airways and parenchyma for unsaturated lysophosphatidylcholines (LPCs), dipeptides, purines, pyrimidines, and amino acids. Importantly, temporal changes were found to be highly distinct for male and female mice, with males exhibiting predominant treatment-specific changes only at two hours post-exposure. In females, metabolomic changes persisted until six hours post-naphthalene treatment, which may explain the previously characterized higher susceptibility of female mice to naphthalene toxicity. In both males and females, treatment-specific changes corresponding to lung remodeling, oxidative stress response, and DNA damage were observed, which may provide insights into potential mechanisms contributing to the previously reported effects of naphthalene exposure in the lung.

pharmacology and toxicology↗

bioRxiv2020

Single-cell characterization of subsolid and solid lesions in the lung adenocarcinoma spectrum

Determining the clinical significance of CT scan-detected subsolid pulmonary nodules requires an understanding of the molecular and cellular features that may foreshadow disease progression. We studied the alterations at the transcriptome level in both immune and non-immune cells, utilizing single-cell RNA sequencing, to compare the microenvironment of subsolid, solid, and non-involved lung tissues from surgical resection specimens. This evaluation of early spectrum lung adenocarcinoma reveals a significant decrease in the cytolytic activities of natural killer and natural killer T cells, accompanied by a reduction of effector T cells as well as an increase of CD4+ regulatory T cells in subsolid lesions. Characterization of non-immune cells revealed that both cancer-associated alveolar type 2 cells and fibroblasts contribute to the deregulation of the extracellular matrix, potentially affecting immune infiltration in subsolid lesions through ligand-receptor interactions. These findings suggest a decrement of immune surveillance in subsolid lesions.

cancer biology↗

bioRxiv2020

Automated curation of CNMF-E-extracted ROI spatial footprints and calcium traces using open-source AutoML tools

In vivo 1-photon calcium imaging is an increasingly prevalent method in behavioural neuroscience. Numerous analysis pipelines have been developed to improve the reliability and scalability of pre-processing and ROI extraction for these large calcium imaging datasets. Despite these advancements in pre-processing methods, manual curation of the extracted spatial footprints and calcium traces of neurons remains important for quality control. Here, we propose an additional semi-automated curation step for sorting spatial footprints and calcium traces from putative neurons extracted using the popular CNMF-E algorithm. We used the automated machine learning tools TPOT and AutoSklearn to generate classifiers to curate the extracted ROIs trained on a subset of human-labeled data. AutoSklearn produced the best performing classifier, achieving an F1 score > 92% on the ground truth test dataset. This automated approach is a useful strategy for filtering ROIs with relatively few labeled data points, and can be easily added to pre-existing pipelines currently using CNMF-E for ROI extraction.

neuroscience↗

bioRxiv2020

Novel Kras-mutant murine models of non-small cell lung cancer possessing co-occurring oncogenic mutations and increased tumor mutational burden

Despite recent advances in lung cancer immunotherapy, a major obstacle to the progress in the field is the lack of preclinical models that recapitulate the genetic and immunologic complexity of human disease. Conditional genetically engineered mouse models (GEMMs) of non-small cell lung cancer (NSCLC) harbor the common oncogenic mutations of the disease, but these models possess low tumor mutational burden (TMB), which limits their utility in immunotherapy studies. Here, we establish novel Kras-mutant murine models of NSCLC bearing common genetic alterations associated with the disease and increased TMB, by in vitro exposure of cell lines derived from GEMMs of NSCLC [KrasG12D (K), KrasG12DTp53-/- (KP), KrasG12DTp53+/-Lkb1-/- (KPL)] to the alkylating agent N-methyl-N-nitrosourea (MNU). Increased TMB was associated with enhanced anti-tumor T cell responses and improved anti-PD-1 efficacy in syngeneic models, across all genetic backgrounds. However, anti-PD-1 efficacy was comparatively modest in the KPL cell lines with increased TMB, which possessed a distinct immunosuppressed tumor microenvironment (TME) primarily composed of granulocytic myeloid-derived suppressor cells (G-MDSCs). This phenotype is consistent with findings in human NSCLC where LKB1 loss is a driver of primary resistance to PD-1 blockade. In summary, these novel Kras-mutant murine NSCLC models bearing common co-occurring mutations with increased TMB possess clinically relevant TMEs and recapitulate the genetic complexity and therapeutic vulnerabilities of human NSCLC. We anticipate that these immunogenic models will facilitate the development of novel immunotherapies in NSCLC.

cell biology↗

bioRxiv2018

A compact head-mounted endoscope for in vivo calcium imaging in freely-behaving mice

Miniaturized fluorescence microscopes for imaging calcium transients are a promising tool for investigating the relationship between behaviour and population-level neuronal activity in rodents. However, commercially available miniature microscopes may be costly, and, because they are closed-source, may not be easily modified based on particular experimental requirements. Here, we describe how to build and use a low-cost compact head-mounted endoscope (CHEndoscope) system for in vivo calcium imaging. The CHEndoscope uses an implanted gradient index (GRIN) lens along with the genetically encoded calcium indicator GCaMP6 to image calcium transients from hundreds of neurons simultaneously in awake behaving mice. This system is affordable, open-source, and flexible, permitting modification depending on the particular experiment. This Unit describes in detail the assembly, surgical implantation, data collection, and processing of calcium signals using the CHEndoscope system. The aim of this open framework model is to provide an accessible set of miniaturized calcium imaging tools for the neuroscience research community.\n\nSignificance StatementThe ability to image calcium transients in awake, behaving rodents using miniature microscopes opens exciting and novel avenues for gaining insights into how information is encoded in neural circuits. The development of this tool has already had a significant impact on neuroscience research. The cost of commercial systems, however, may be prohibitive for many laboratories. Here, we describe an affordable, open-source compact head-mounted endoscope (CHEndoscope) system for performing in vivo calcium imaging in freely-behaving mice. CHEndoscopes may be manufactured by individual laboratories at relatively minor cost. Our hope is that greater availability of affordable, open-source tools (such as the one presented here) will accelerate the pace of discoveries in systems neuroscience.

neuroscience↗