Biology subjects

Bhargava, R.

Publications and source records attributed to Bhargava, R..

18 recordsLinked to original sources

bioRxiv2026

Programmable DNA Assemblies Reconstitute Supramolecular Protein Function

Biological processes are often regulated through reactions involving supramolecular protein complexes organized with nanoscale precision, such as the apoptosome that activates procaspase-9 through defined stoichiometry to induce apoptosis. Here we report designer CASCAD (CARD Assembly on SCAffold DNA), a self-assembled DNA nanoplatform that spatially organizes caspase recruitment domains (CARDs), exhibiting catalytic intracellular caspase-9 activation. By functioning like a natural apoptosome, CASCAD enhances caspase-9 oligomerization and promotes valency-dependent enzymatic activation. Further, after incorporating targeting aptamers and membrane-interacting peptides for cellular uptake and cytosolic delivery, CASCAD has successfully reconstituted apoptosome function and downstream apoptotic signaling in in-vitro 2D and 3D cultures. Our molecular design paradigm establishes CASCAD as versatile and programmable DNA nanomaterial for reconstructing signaling pathways driven by diverse supramolecular complexes, including inflammasomes and myddosomes, providing a general chemical framework for engineering cellular signaling and directing cellular function and fate.

synthetic biology↗

bioRxiv2026

Predicting Human mRNA Isoform Levels from Site-Specific Splicing Kinetics in silico

Splicing of pre-mRNA can result in multiple possible mRNA isoforms per gene due to alternative splicing. The frequency at which individual isoforms occur depends on the intrinsic splicing kinetics of the pre-mRNA as well as intracellular chemical conditions. Computational modeling can potentially provide a platform to rapidly assess how variations in intracellular and environmental conditions, for example differential levels of regulatory splicing proteins, affect kinetics and resulting mRNA isoforms. Overcoming the vast combinatoric possibilities of splicing, however, has remained a significant challenge in modeling its kinetics. Here we report the development of a stochastic kinetic model of splicing that is extensible to most protein-coding genes in the human genome. Our model allows for variations in site-specific reaction rates as well as the ability to introduce additional splicing factors. We experimentally validate the predictive capability of our computational model by exploring the spliced isoform ratio of a target gene (SRSF6) under normoxia and hypoxia. This work provides a resource for quantitative, computational analysis of pre-mRNA splicing, allowing for a rapid computational-experimental approach to assess biological hypotheses. Author summarymRNA splicing is a key step in human gene expression with deep impact on the molecular processes determining cell physiology and affecting development and disease. Computational models of splicing are highly attractive to understand life processes but so far have been limited in directly accounting for the chemistry of splicing and are not extensible to most of the human genome. We report here a model that overcomes both of these challenges, providing a computational benchtop to probe splicing kinetics for most genes in the human genome. This model has the capability to rapidly pose biological hypotheses for experimental validation. As a targeted demonstration, we explore the effects of the pathologically-relevant chemical condition hypoxia on the pre-mRNA of a single gene.

biophysics↗

bioRxiv2026

Rapid Podocyte ablation Causes Acute Renal Tubule Cell Necrosis and Interstitial Fibrosis

It remains unclear whether podocyte loss directly causes acute renal tubular cell (RTC) damage and interstitial fibrosis, thereby leading to renal failure. Here, we applied intermedilysin (ILY)-mediated human CD59 (hCD59) cell ablation to generate an acute, specific podocyte-ablation mouse model. Cre-induced hCD59 transgenics (ihCD59) were crossed with Nphs2Cre to generate ihCD59+/-/Nphs2Cre+/- mice. The specific and rapid podocyte-ablation mediated by ILY injection directly caused RTC necrosis, leading to renal failure and even death within 2-3 days in a dose-dependent manner. Treating mice that received an ILY lethal dose with peritoneal dialysis or administering a non-lethal dose, we extended their survival beyond six weeks and found that mice developed interstitial fibrosis and glomerulosclerosis with persistent proteinuria and tubule damage. Podocyte-ablation caused massive disruption of glomerular function at week 1, and then partial recovery by week 2. Genes and pathways of TLRs and apoptosis, and mitochondrial functions were respectively upregulated and downregulated in both ablated-podocyte mouse and biopsied-glomerulonephritis patient kidney samples. Together, this rapid podocyte-ablation causes acute RTC necrosis that progresses to interstitial fibrosis in this mouse model, which is applicable for dissecting mechanisms underlying podocyte injury-mediated tubular damage and glomerular repair, with the potential to reveal novel therapeutic targets for kidney diseases.

pathology↗

bioRxiv2026

Multi-omics and spatial analysis of microgravity-grown glioblastoma organoids reveals superior modeling of advanced disease after long-term spaceflight

Glioblastoma (GBM) is an incurable brain cancer characterized by its highly immunosuppressive tumor microenvironment and aggressive malignant features that resist treatment. To overcome limitations of Earth-based models (sedimentation and disaggregation) and leverage the unique biological effects of space (accelerated disease progression and immune dysregulation), we developed a panel of GBM-myeloid organoids for extended culture on the International Space Station. After 40 days, the spaceflight-grown organoids had more uniform and reproducible morphology compared to identical ground controls. Organoids containing GBM cells + monocytes had increased expression of chronic innate inflammation, adaptive immune activation, and tissue and vascular remodeling-associated genes. There was an increase in organization of gene expression patterns, with mesenchymal-related genes enriched in the core and inflammation-related genes enriched at the periphery, mimicking GBM tumor architecture. Secretomics confirmed the generation of more immunosuppressive organoids, with enrichment of proteins associated with more aggressive disease, including CXCL12 and LOX-1. GBM co-culture organoids thus had enhanced transcriptomic, proteomic, and architectural features when grown in microgravity that are associated with worse patient outcomes from retrospective data. Infrared laser scanning microscopy confirmed spatial chemical gradients for DNA, protein, and lipid species in both space- and terrestrially-grown organoids. In summary, we present not only a novel and superior model of glioblastoma for more relevant basic, mechanistic, and translational research, but also demonstrate methods to acquire high-quality and diverse data from organoids compatible with the unique experimental constraints of biological research in space to help establish a working model for orbital oncology.

cancer biology↗

bioRxiv2025

Non-invasive detection of local microstructural damage in tendonvia Diffusion Tensor MRI

Tendon is critical for musculoskeletal function as it transfers forces generated by muscle to bone and stores energy during movement. Impaired mechanical function in tendon limits mobility and results from fatigue-induced damage progression that outpaces the restorative processes maintaning tissue health, a phenomenom we term mechanopathology. Early and non-invasive detection of tendon mechanopathologies is vital to prevent further damage, but is lacking in the clinical space. Here, we evaluate the ability of diffusion tensor magnetic resonance imaging (DT-MRI) to detect mechanical fatigue damage in tendon, and validate our findings using histologic assessments of collagen fiber microstructure and molecular structure. We found that fatigue-induced changes in DT-MRI metrics of tendon are spatially heterogeneous, and correspond to regions with damaged collagen fiber microstructure. While secondary structures of collagen molecules were damaged by fatigue loading, they do not spatially correspond to fatigue-induced changes in DT-MRI metrics. Fatigueinduced changes in DT-MRI metrics can be partially explained by quantitative metrics of post-fatigue collagen fiber microstructure, estimating the limit of detection of DT-MRI metrics to fatigue-induced damage in tendon. Our findings indicate that DT-MRI metrics are sensitive to fatigue-induced local damage in tendon, supporting the potential of DT-MRI as a non-invasive and translatable tool to clinically detect mechanopathologies in tendon.

bioengineering↗

bioRxiv2025

Identification and Credentialing of Patient Derived Xenograft Models of Invasive Lobular Breast Carcinoma using Multi-omics and Histopathology assessment

Breast cancer is a heterogeneous disease with numerous histological subtypes. Invasive lobular cancer (ILC) is the most common special subtype, accounting for 10-15% of all breast cancers. The pathognomonic feature of ILC is the loss of E-cadherin (CDH1), which leads to a unique single-file growth pattern of discohesive cells. Although ILCs show better prognostic factors than the most common No Special Type (NST) of breast cancer, patients with ILC have worse long-term outcomes, which is not well understood. In this study, we aimed to identify and characterize Patient-Derived Xenograft (PDX) models of ILC based upon the presence of truncating CDH1 mutations and/or low CDH1 mRNA expression among 128 human breast cancer PDX models. We selected 8 PDX models for validation using Immunohistochemical (IHC) analysis for E-Cadherin, p120, ER, PR, and HER2. We confirmed that seven of these PDX models are indeed ILC while one was identified as mixed NST-ILC PDX. Molecular analysis of the confirmed ILC PDX models showed enrichment of truncating CDH1 mutations, significantly lower levels of CDH1 mRNA expression and predominantly luminal subtypes compared to NST PDX models, in line with the molecular characteristics of human ILC disease. The commonly altered genes in the ILC PDX models included PIK3CA (57%), CDH1 (57%) and TP53 (57%) among others. Our study confirms and characterizes new ILC PDX models, offering valuable tools to advance our understanding of human ILC biology and support the development of innovative treatment strategies.

cancer biology↗

bioRxiv2025

Lack of Bcl6 promotes anti-tumor immunity by activating glycolysis to rescue CD8 T cell function

T cells are one of the most powerful weapons to fight cancer; however, T cell exhaustion and dysfunction restrict their long-lasting function in anti-tumor immunity. B-cell lymphoma 6 (BCL6) has many functions in CD8 T cells but it is unclear how it regulates the effector function and exhaustion of CD8 cells. Overall, a low level of BCL6 mRNA in human cancer samples is associated with better outcomes. We found that BCL6 deficiency in activated CD8 T cells enhanced tumor repression in multiple mouse models. More IL-2-expressing CD8 T cells and reduced proportions of exhausted or dysfunctional CD8 T cells were detected within tumors when Bcl6 was knocked out upon T cell activation. Glycolysis was promoted in BCL6-deficient CD8 T cells owing to derepression of glucose transporter GLUT3 (encoded by Slc2a3). The BCL6 inhibitor Fx1 promoted anti-tumor immunity in a T cell-dependent manner. These findings suggest a novel pathway to restore effector function of CD8 T cells by changing their energy utilization pathways to facilitate long-term tumor resistance. Summary BlurbBCL6 limits CD8 T cell responses to tumors by inhibiting Glut3 expression. Conditional deletion of Bcl6 in activated CD8 T cells or pharmacological inhibition of BCL6 in mice represses tumor growth.

immunology↗

bioRxiv2025

An innovative approach in identifying a network of priority wetland sites in the East Asian-Australasian Flyway for a new sustainable management investment programme

The East Asian-Australasian Flyway (EAAF) is widely recognised to be the most threatened of the eight flyways in the world, with wetlands rapidly lost due to land cover change, unsustainable use, and the wider impacts of climate change. The recently established Regional Flyway Initiative aims to bring a network of priority wetlands in the EAAF under improved protection, management, and restoration in 10 Asian countries, while mobilising resources for sustainable agriculture, aquaculture, ecotourism, and other livelihoods for local communities. A major step in the development of this initiative is the identification of priority wetland sites through the application of international criteria, based on modern waterbird count data collated from wetland sites across Asia. Through existing analyses and stakeholder consultations, we short-listed 400 internationally important wetlands as candidate sites for further assessment. Count data of EAAF waterbird species was then assessed against international criteria aligned with the Convention on Wetlands (Ramsar Convention), the EAAF Partnerships Flyway Site Network and Important Bird Areas and Biodiversity for each site to iteratively identify a subset of priority sites, drawing on newly available species population thresholds. Each site was scored and ranked using a metric (Prioritisation Criterion1) calculated from the proportions of every occurring EAAF species against published population thresholds. We identified a total of 147 wetland sites of high conservation priority across the 10 countries, thereby representing the full suite of wetland landscapes and habitats in Asia, both freshwater and coastal, all critical sites for the conservation of migratory waterbirds in the flyway. At least 34 threatened species, including significant proportions of their global populations are represented in this network of 147 sites. To ensure that conservation opportunities are maximised for species and ecosystem services, there is a need to ensure that selected sites and landscapes are reconciled with the conservation and development priorities of each country, and to evaluate priority sites for their ecosystem services.

ecology↗

bioRxiv2025

A Machine Learning-based Approach for Quantification of Protein Secondary Structures from Discrete Frequency Infrared Images

Discrete frequency infrared (IR) imaging is an exciting experimental technique that has shown promise in various applications in biomedical science. This technique often involves acquiring IR absorptive images at specific frequencies of interest that enable pathologically relevant chemical contrast. However, certain applications, such as tracking the spatial variations in protein secondary structure of tissue specimens, necessary for the characterization of neurodegenerative diseases, require deeper analysis of spectral data. In such cases, the conventional analytical approach involves band fitting the hyperspectral data to extract the relative populations of different structures through their fitted areas under the curve (AUCs). While Gaussian spectral fitting for one spectrum is viable, expanding that to an image with millions of pixels, as often applicable for tissue specimens, becomes a computationally expensive process. Alternatives like Principal Component Analysis (PCA) are less structurally interpretable and incompatible with sparsely sampled data. Furthermore, this detracts from the key advantages of discrete frequency imaging by necessitating acquisition of a more finely sampled spectral data that is optimal for curve fitting, resulting in significantly longer data acquisition times, larger datasets and additional computational overhead. In this work we demonstrate that a simple two-step regressive neural network model can be utilized to mitigate these challenges and employ discrete frequency imaging for retrieving the results from band fitting without significant loss of fidelity. Our model reduces the data acquisition time nearly 6-fold by requiring only seven wavenumbers to accurately interpolate spectral information at a higher resolution, and subsequently using the upscaled spectra to accurate predict the component AUCs, which is more than 3000 times faster than spectral fitting. Our approach thus drastically cuts down the data acquisition and analysis time and predicts key differences in protein structure that can be vital towards broadening potential applications of discrete frequency imaging.

biophysics↗

bioRxiv2024

Glioblastoma Drives Protease-Independent Extracellular Matrix Invasion of Microglia

Glioblastoma (GBM) is the most common and lethal form of primary brain cancer. Microglia infiltration into the tumor microenvironment is associated with immunosuppression and poor prognosis. Improved physicochemical understanding of microglia activation and invasion may provide novel GBM therapeutic strategies essential for improving long-term treatment efficacy. Here, we combine microfluidic systems with 3-D collagen hydrogels to systematically investigate microglia activation, invasion, contractility and cytokine secretion in response of GBM-microglia crosstalk. GBM inflammatory biomolecules significantly promote activation and 3D invasion of microglia. Interestingly, microglia invasion is not significantly affected by inhibitors of MMP activity or cellular glycolysis. In contrast, ROCK-pathway inhibition significantly impedes microglia invasion. Infrared microscopy analyses show that GBM co-culture does not significantly alter microglia lipid content. Further, GBM conditioned media resulted in significantly increased collagen hydrogel contraction, suggesting the importance of microglia contractility to physically remodel the local extracellular matrix (ECM). We also identify a panel of soluble proteins that may contribute to microglia chemotaxis, such as TIMP-1 and CXCL12. Taken together, this study suggests that the presence of GBM cells can enhance microglia invasion via increased cellular contractility, independent of MMP activity and cellular glycolysis.

bioengineering↗

bioRxiv2024

Hope for Others: Research Results from the University of Pittsburgh Rapid Autopsy Program for Breast Cancer

Breast cancer affects 1/8 of women throughout their lifetimes, with over 90% of cancer deaths being caused by metastasis. However, metastasis poses unique challenges to research, as complex changes in the microenvironment in different metastatic sites and difficulty obtaining tissue for study hinder the ability to examine in depth the changes that occur during metastasis. Rapid autopsy programs thus fill a unique need in advancing metastasis research. Here, we describe our protocol and processes for establishing and improving the US-based Hope for OTHERS (Our Tissue Helping Enhance Research and Science) program for organ donation in metastatic breast cancer. As of August 2024, we consented 114 patients and performed 37 autopsies, from which we collected 551 unique metastatic frozen tumor samples, 1244 FFPE blocks, 90 longitudinal liquid biopsy samples and developed 14 patient-derived organoid and 8 patient-derived xenograft models. We report in-depth clinical and histopathological information and discuss extensive new research and novel findings in patient outcomes, metastatic phylogeny, and factors in successful living model development. Our results reveal key logistical and protocol improvements that are uniquely beneficial to certain programs based on identifiable features, such as working closely with patient advocates, methods to rescue RNA quality in cases where tissue quality may degrade due to time delays, as well as guidelines and future expansions of our program. Statement of SignificanceRapid autopsy programs are unique research settings with huge potential for studying metastatic cancer, however, they have complex research challenges. Our work provides a valuable resource in advancing this field of research.

cancer biology↗

bioRxiv2024

TRIM24 directs replicative stress responses to maintain ALT telomeres via chromatin signaling

An inability to replicate the genome can cause replication stress and genome instability. Here, we develop BLOCK-ID, a proteomic method to identify and visualize proteins at stressed replication forks. This approach successfully identified novel mediators of the replication stress response, including the chromatin acetylation reader protein TRIM24. In validating TRIM24 function, we uncovered its crucial role in coordinating Alternative Lengthening of Telomeres (ALT), a cancer-specific telomere extension pathway involving replication stress. Our data reveal that TRIM24 is directed to telomeres via a p300/CBP-dependent acetylation chromatin signaling cascade, where it organizes ALT-associated PML bodies (APBs) to promote telomere DNA synthesis. Strikingly, we demonstrate that when artificially tethered at telomeres, TRIM24 can stimulate new telomere DNA synthesis in a SUMO-dependent manner, independently of p300/CBP or PML-dependent APBs. Thus, this study identifies a TRIM24 chromatin signaling pathway required for ALT telomere maintenance.

cell biology↗

bioRxiv2023

Identification of proteotoxic and proteoprotective bacteria that non-specifically affect proteins associated with neurodegenerative diseases

Neurodegenerative protein conformational diseases (PCDs), such as Alzheimers, Parkinsons, and Huntingtons, are a leading cause of death and disability worldwide and have no known cures or effective treatments. Emerging evidence suggests a role for the gut microbiota in the pathogenesis of neurodegenerative PCDs; however, the influence of specific bacteria on the culprit proteins associated with each of these diseases remains elusive, primarily due to the complexity of the microbiota. In the present study, we employed a single-strain screening approach to identify human bacterial isolates that enhance or suppress the aggregation of culprit proteins and the associated toxicity in Caenorhabditis elegans expressing A{beta}1-42, -synuclein, and polyglutamine tracts. Here, we reveal the first comprehensive analysis of the human microbiome for its effect on proteins associated with neurodegenerative diseases. Our results suggest that bacteria affect the aggregation of metastable proteins by modulating host proteostasis rather than selectively targeting specific disease-associated proteins. These results reveal bacteria that potentially influence the pathogenesis of PCDs and open new promising prevention and treatment opportunities by altering the abundance of beneficial and detrimental microbes.

microbiology↗

bioRxiv2023

Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures and actionable driver mutations

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially-resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity (e.g., MDLC with TNBC/basal ductal and ER+/luminal lobular regions), distinct enrichment of senescence/dormancy and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular, but not ductal regions, and single-cell ductal and lobular sub-populations with unique oncogenic signatures further highlighting intra-regional heterogeneity. Altogether, we demonstrated that the intra-tumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma. SignificanceMDLC displays both ductal and lobular tumor regions. Our multi-omic profiling approach revealed that these morphologically distinct tumor regions harbor distinct intrinsic subtypes and oncogenic features that may cause prognostic uncertainty and therapeutic dilemma. Thus histopathological/molecular profiling of individual tumor regions may guide clinical decision making and benefit patients with MDLC, particularly in the advanced setting where there is increased reliance on next generation sequencing.

cancer biology↗

bioRxiv2023

Intermediate antiparallel beta structure in amyloid plaques revealed by infrared spectroscopic imaging

Aggregation of amyloid beta (A{beta}) peptides into extracellular plaques is a hallmark of the molecular pathology of Alzheimers disease (AD). Amyloid aggregates have been extensively studied in-vitro, and it is well known that mature amyloid fibrils contain an ordered parallel {beta} structure. The structural evolution from unaggregated peptide to fibrils can be mediated through intermediate structures that deviate significantly from mature fibrils, such as antiparallel {beta}-sheets. However, it is currently unknown if these intermediate structures exist in plaques, which limits the translation of findings from in-vitro structural characterizations of amyloid aggregates to AD. This arises from the inability to extend common structural biology techniques to ex-vivo tissue measurements. Here we report the use of infrared (IR) imaging, wherein we can spatially localize plaques and probe their protein structural distributions with the molecular sensitivity of IR spectroscopy. Analyzing individual plaques in AD tissues, we demonstrate that fibrillar amyloid plaques exhibit antiparallel {beta}-sheet signatures, thus providing a direct connection between in-vitro structures and amyloid aggregates in AD brain. We further validate results with IR imaging of in-vitro aggregates and show that antiparallel {beta}-sheet structure is a distinct structural facet of amyloid fibrils.

biophysics↗

bioRxiv2021

The DNAPKcs long-range C-NHEJ complex is required for blunt DNA end joining when XLF is weakened

Canonical non-homologous end joining (C-NHEJ) factors can assemble into a long-range (LR) complex with DNA ends relatively far apart that contains DNAPKcs, XLF, XRCC4, LIG4, and the KU heterodimer and a short-range (SR) complex lacking DNAPKcs that has the ends positioned for ligation. Since the SR complex can form de novo, the role of the LR complex (i.e., DNAPKcs) for chromosomal EJ is unclear. We have examined EJ of chromosomal blunt DNA double-strand breaks (DSBs), and found that DNAPKcs is significantly less important than XLF and XRCC4 for such EJ. However, weakening XLF via disrupting interaction interfaces (e.g., disrupting the XLF homodimer interface) causes a marked requirement for DNAPKcs, its kinase activity, and its ABCDE-cluster autophosphorylation sites for blunt DSB EJ. In contrast, other aspects of genome maintenance are sensitive to DNAPKcs kinase inhibition in a manner that is not further enhanced by XLF loss (i.e., suppression of homology-directed repair and structural variants, and IR-resistance). We suggest that DNAPKcs is required to position a weakened XLF in an LR complex that can transition into a functional SR complex for blunt DSB EJ, but also has distinct functions for other aspects of genome maintenance.

molecular biology↗

bioRxiv2018

A Fully Automated, Faster Noise Reduction Approach to Increasing the Analytical Capability of Chemical Imaging for Digital Histopathology

High dimensional data, for example from infrared spectral imaging, involves an inherent trade-off in the acquisition time and quality of spatial-spectral data. Minimum Noise Fraction (MNF) developed by Green et al. [1] has been extensively studied as an algorithm for noise removal in HSI (Hyper-Spectral Imaging) data. However, there is a speed-accuracy trade-off in the process of manually deciding the relevant bands in the MNF space, which by current methods could become a person month time for analyzing an entire TMA (Tissue Micro Array). We propose three approaches termed Fast MNF, Approx MNF and Rand MNF where the computational time of the algorithm is reduced, as well as the entire process of band selection is fully automated. This automated approach is shown to perform at the same level of reconstruction accuracy as MNF with large speedup factors, resulting in the same task to be accomplished in hours. The different approximations of the algorithm, show the reconstruction accuracy vs storage (50x) and runtime speed (60x) trade-off. We apply the approach for automating the denoising of different tissue histology samples, in which the accuracy of classification (differentiating between the different histologic and pathologic classes) strongly depends on the SNR (signal to noise ratio) of recovered data. Therefore, we also compare the effect of the proposed denoising algorithms on classification accuracy. Since denoising HSI data is done without any ground truth, we also use a metric that assesses the quality of denoising in the image domain between the noisy and denoised image in absence of ground truth.

bioinformatics↗

bioRxiv2017

Exome-Capture RNA-Sequencing Of Decade-Old Breast Cancers And Matched Decalcified Bone Metastases Identifies Clinically Actionable Targets

Bone metastases (BoM) are a significant cause of morbidity in patients with Estrogen-receptor (ER)-positive breast cancer, yet characterizations of human specimens are limited. In this study, exome-capture RNA-sequencing (ecRNA-seq) on aged (8-12 years), formalin-fixed paraffin-embedded (FFPE) and decalcified cancer specimens was first evaluated. Gene expression values and RNA-seq quality metrics from FFPE or decalcified tumor RNA showed minimal differences when compared to matched flash-frozen or non-decalcified tumors. ecRNA-seq was then applied on a longitudinal collection of 11 primary breast cancers and patient-matched de novo or recurrent BoM. BoMs harbored shifts to more Her2 and LumB PAM50 intrinsic subtypes, temporally influenced expression evolution, recurrently dysregulated prognostic gene sets and altered expression of clinically actionable genes, particularly in the CDK-Rb-E2F and FGFR-signaling pathways. Taken together, this study demonstrates the use of ecRNA-seq on decade-old and decalcified specimens and defines expression-based tumor evolution in long-term, estrogen-deprived metastases that may have immediate clinical implications.\n\nGrant SupportResearch funding for this project was provided in part by a Susan G. Komen Scholar award to AVL and to SO, the Breast Cancer Research Foundation (AVL and SO), the Fashion Footwear Association of New York, the Magee-Womens Research Institute and Foundation, and through a Postdoctoral Fellowship awarded to RJW from the Department of Defense (BC123242). NP was supported by a training grant from the NIH/NIGMS (2T32GM008424-21) and an individual fellowship from the NIH/NCI (5F30CA203095).\n\nConflicts of Interest DisclosureNo relevant conflicts of interest disclosed for this study.\n\nAuthor ContributionsStudy concept and design (NP, RJW, SO, AVL); acquisition, analysis, or interpretation of data (all authors); drafting of the manuscript (NP, RJW, SO, AVL); critical revision of the manuscript for important intellectual content (all authors); administrative, technical, or material support (PCL, AB, RB, KRW, WH, JK, MR, ZF, AMB).

cancer biology↗