Biology subjects

Hicks, J.

Publications and source records attributed to Hicks, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatial multi-omics and single-cell transcriptomics uncover senescence-associated cellular programs during colon adenoma to cancer progression

Colorectal cancer develops through a normal-adenoma-carcinoma sequence, yet only 5-10% of adenomas progress to malignancy, and the cellular programs governing that sequence remain poorly defined. Here we generate a spatial multi-omics atlas of human colon adenomas, combining Visium CytAssist and protein co-detection across 24 nonadvanced and advanced tubular adenomas with single-cell resolution Xenium Prime 5K profiling of 101 patient-matched normal, adenoma, and carcinoma cores from 16 patients. Integrating whole-transcriptome and 31-plex protein data identifies nine spatial clusters and two dysplastic epithelial populations that co-express stemness, proliferation, and senescence programs. These programs occupy a shared, spatially confined epithelial niche that expands from adenoma to carcinoma. Spatial analysis revealed GDF15, a senescence-associated secretory factor, mediated the coupling between senescence and stemness in advanced adenomas, and that GDF15-high epithelium locally excludes CD8+ T cells in adenoma and, more broadly, in carcinoma. These findings position senescence as a spatially instructive rather than merely tumor-suppressive program during colorectal carcinogenesis and suggest GDF15 might be a potential candidate target for cancer prevention and interception in the colon.

cancer biology↗

bioRxiv2026

Simulation-guided design of exotendons to reduce the energetic cost of running

A passive device that attaches to the feet, called an exotendon, can reduce the energetic cost of running at moderate speeds, but its efficacy and optimal design parameters at higher speeds are unknown. Identifying optimal parameters at new speeds experimentally would require many experimental trials with different exotendon designs, which is challenging for participants at higher running speeds. We developed a muscle-driven simulation framework to predict the effect of various exotendon designs on the energetic cost of running at an experimentally untested speed (4 m/s). We used these predictions to select four designs, which we evaluated experimentally as users ran at this speed. The framework correctly predicted that an exotendon that reduced energetic cost at 2.7 m/s would also reduce energetic cost at 4 m/s (10% predicted vs. 5.7% measured) and that a short, stiff exotendon and a long, compliant exotendon would not significantly reduce energetic cost. However, exotendon parameters predicted by the simulation to maximize energetic savings did not significantly reduce energetic cost when evaluated experimentally. There was variability between participants in both the magnitude of maximum energy savings and the exotendon condition associated with those savings. In a 5-km time trial performed with and without the exotendon condition that elicited the largest energy savings for each participant during the experiment, we observed a lower average heart rate (-3.9 {+/-} 3.8 beats/min; P=0.03; mean {+/-} standard deviation) and increased cadence (15.9 {+/-} 9.6 steps/min; P=0.002) when participants ran with the exotendon but did not observe a statistically significant difference in finishing time (-13.5 {+/-} 24.6 sec; P=0.3). These results demonstrate exotendons can reduce energetic cost across multiple running speeds and that predictive simulations provide a framework for guiding experiments to evaluate assistive device designs. Author summaryDesigning assistive devices that help people move more efficiently usually requires many experimental trials. These studies can be time-consuming and physically demanding, especially when testing multiple device designs. In this study, we explored whether computer simulations could help guide the design of an assistive device for running called an exotendon. The exotendon is a simple elastic band that connects the feet and can help runners use less energy. Previous experiments showed that the device reduces the energy needed to run at moderate speeds, but it was unclear whether it would also work at faster speeds or which design would lead to energetic savings. We first used simulations of human running to test many possible exotendon designs at a faster speed. These simulations allowed us to identify promising designs before conducting experiments. We then tested a small number of these designs with runners. The experiments confirmed that the exotendon can reduce the energy required to run at faster speeds, although the efficacy of different designs varied between individuals. Our results show that computer simulations can help researchers rapidly evaluate a variety of assistive device ideas and focus experimental testing on the most promising designs.

bioengineering↗

bioRxiv2026

DNA ligase Lig E increases transformation with damaged extracellular DNA

Lig E is a periplasm-targeted ATP-dependent DNA ligase found in many Gram-negative bacteria including Neisseria gonorrhoeae. Although Lig E has been shown to have a role in biofilm formation, many Lig E-possessing bacteria are also naturally competent, suggesting a possible function in transformation with extracellular DNA. Here, we demonstrate that Lig E participates in bacterial competence by increasing transformation with nuclease-damaged extracellular DNA that contains single-stranded or cohesive breaks. We show that increased transformation with this restricted DNA is ATP-dependent, and that the ATP concentration increases in the extracellular milieu during maintenance of N. gonorrhoeae in liquid culture. Impact StatementNatural transformation is an important route of horizontal gene transfer that enables competent bacteria to acquire novel phenotypic traits such as antibiotic resistance or virulence factors. By demonstrating that Lig E increases transformation of N. gonorrhoeae with damaged resistance-encoding DNA, we provide a mechanism which competent bacteria can use to overcome nucleolytic damage sustained by environmental DNA, making this more readily available as a source of novel and potentially pathogen-enhancing genes.

microbiology↗

bioRxiv2026

Subclonal Complete Loss of CDKN1B as a Common Genomic Alteration in Prostate Cancer: Associations with Race and Prostate Cancer Outcomes

BackgroundHomozygous biallelic inactivation of CDKN1B is thought to be rare in cancer. Herein we evaluate the prevalence of intratumoral (subclonal) complete p27 protein loss (IPPL) in primary prostate cancer. Experimental DesignWe used immunohistochemistry (IHC) for p27 in a large cohort of whole tissue sections from radical prostatectomy (n=412) and metastases from self-identified African American (AA) and European American (EA) individuals. IPPL was evaluated alongside CDKN1B mRNA in-situ hybridization and next generation sequencing of laser captured cancer regions. Cox proportional hazards analyses assessed the association of IPPL with biochemical recurrence and development of metastases after radical prostatectomy. ResultsIPPL was detected in 18.1% of AA versus 12.2% of EA cases and was tightly correlated with CDKN1B mRNA loss and biallelic genomic loss. IPPL was associated with [≥]pT3 pathologic stage and pN1 disease, however these associations were only significant among AA participants. IPPL was further associated in both univariate and multivariate analyses with the development of biochemical recurrence and metastasis after primary treatment, specifically in AA individuals. The prevalence of p27 genomic alterations in metastatic disease is higher than that of primary prostate cancer in publicly available datasets as well as our analysis of autopsy cases via IHC, indicating that complete p27 loss may be selected for in metastatic disease. ConclusionsSubclonal biallelic loss of CDKN1B resulting in complete p27 protein loss is one of the most commonly occurring biallelic tumor suppressor genomic alterations in primary prostate cancer, and could contribute to worse prostate cancer outcomes, specifically in AA males.

cancer biology↗

bioRxiv2025

Running with an exotendon reduces compressive knee contact force

An exotendon--a spring that couples the dynamics of the legs when attached to a runners shoes--reduces the energetic cost of running, but the effects on joint contact forces are unknown. This study examined whether running with an exotendon alters the forces in the hip, knee and ankle. We used muscle-driven simulations of experimental data to compute compressive and shear contact forces at the hip, knee, and ankle joints for five participants running at 2.7 m/s with and without an exotendon. We found that runners using the exotendon experienced a 9.4% reduction in peak knee compressive contact force (1.0 {+/-} 0.6 BW; P=0.036), and no change in the peak knee shear contact force. The primary contributor to this reduction was lower forces in the quadriceps muscles, which decreased their contribution to peak knee compressive contact force by 14.2% (-0.9 {+/-} 0.6 BW; P=0.026). We observed no change in the peak compressive or shear contact forces in the hip or ankle joints. Though the exotendon was not originally designed to reduce joint forces, our findings highlight the ability of this simple device to make changes to gait that reduce both energetic cost and compressive knee force.

bioengineering↗

bioRxiv2025

Imaging CRISPR-Edited CAR-T Cell Therapies with Optical and Positron Emission Tomography Reporters

RationaleChimeric antigen receptor (CAR) T cell therapies have shown remarkable success in treating hematological cancers and are increasingly demonstrating potential for solid tumors. CRISPR-based genome editing offers a promising approach to enhance the potency and safety of CAR-T cells. However, several challenges persist, including inefficient tumor homing and treatment-related toxicities in normal tissues, which continue to hinder widespread adoption. Advanced imaging technologies, including bioluminescence imaging (BLI) and positron emission tomography (PET), provide real-time insights into CAR-T cell distribution and activity in vivo, both in preclinical models and in patients. Here, we developed Trackable Reporter Adaptable CRISPR-Edited CAR (tRACE-CAR) T cells, a modular system for site-specific integration of CARs and imaging reporters. MethodsThe luciferase reporter AkaLuciferase (AkaLuc) or the human sodium iodide symporter (NIS) were cloned downstream of the CAR in adeno-associated virus (AAV) donors for BLI or PET tracking, respectively. CARs with imaging reporters were knocked into the TRAC locus of primary human T cells via CRISPR editing and AAV transduction. Editing efficiency was evaluated by flow cytometry and junction PCR. In vitro cytotoxicity was assessed by BLI using firefly luciferase (Fluc)-expressing cancer cells co-cultured with CAR-T cells at varying effector-to-target ratios. In vivo, BLI and PET imaging assessed CAR-AkaLuc and CAR-NIS T cell expansion and trafficking in Nod-SCID-gamma mice bearing xenograft tumors. ResultsT cell receptor (TCR) knockout efficiency exceeded 85%, with CAR expression observed in 70-80% of cells, depending on the reporter used. Reporter-engineered CAR-T cells retained functionality in vitro and exhibited significant cytotoxicity against target cancer cells, outperforming naive T cells. In vivo, AkaLuc BLI and 18F-tetrafluoroborate PET enabled non-invasive tracking of viable CAR-T cells. Notably, the route of administration (intravenous, peritumoral, or intraperitoneal) significantly influenced the distribution of CAR-T cells and their therapeutic effectiveness. ConclusiontRACE-CAR enabled precise optical and PET tracking of CAR-T cells in models of B cell leukemia and ovarian cancer, allowing dynamic, non-invasive monitoring of cell distribution in both tumors and off-target tissues. This imaging platform could lead to more personalized, effective CRISPR-edited CAR cell therapies.

immunology↗

bioRxiv2025

Characterisation of O-acetylserine sulfhyrdrylase (CysK) enzymes from bacteria lacking a sulfate reduction pathway

Sulfur metabolism plays an important role in bacterial pathogenesis. Elucidation of differences in sulfur metabolism across bacterial pathogens furthers our understanding of host survival and offers opportunities to disrupt these pathways for new therapies. Withing bacteria sulfur metabolism converges at the synthesis of L-cysteine. One of the key mechanisms of obtaining sulfur for the synthesis of L-cysteine is the successive reduction of sulfate to sulfide via the sulfate reduction pathway. Accordingly, L-cysteine biosynthesis is a critical metabolic pathway for bacterial survival, particularly in pathogenic species such as Neisseria gonorrhoeae and Staphylococcus aureus, which lack the sulfate reduction pathway. O-acetylserine sulfhydrylase catalyses the second step of the two-step synthesis reaction, condensing sulfide or thiosulfate (in the case of OASS-A/CysK or OASS-B/CysM respectively) with O-acetylserine to synthesize cysteine. Here we investigate the enzymatic properties and functional characterization of O-acetylserine sulfhydrylase, from N. gonorrhoeae and S. aureus, with a focus on substrate specificity, kinetic parameters, and cysteine synthase complex (CSC) formation. Using small angle X-ray scattering and kinetic assays we demonstrate that both N. gonorrhoeae and S. aureus CysK enzymes utilise only sodium sulfide for the synthesis of cysteine, despite the lack of a sulfate reduction pathway (to generate sulfide) in these organisms. Both enzymes demonstrate a higher affinity for O-acetylserine (OAS) compared to sodium sulfide (Na2S). We also show that the two cysteine synthesis enzymes, CysE and CysK that traditionally form the cysteine synthase complex do not form a complex in N. gonorrhoeae. These findings highlight the functional divergence in sulfur metabolism strategies among bacteria lacking sulfate reduction and provide deeper insights into the adaptive mechanisms of N. gonorrhoeae and S. aureus in sulfur flux.

biochemistry↗

bioRxiv2025

Influence of the ATP-dependent DNA ligase, Lig E, on Neisseria gonorrhoeae microcolony and biofilm formation

BackgroundNeisseria gonorrhoeae, the causative agent of the sexually transmitted infection, gonorrhoea, is known to form biofilms rich in extracellular DNA on human cervical cells. Biofilm formation is conducive to increased antimicrobial resistance and evasion of the host immune system, potentially causing asymptomatic infections. Using plate-based assays we have previously shown that disruption of a potential extracellular DNA ligase, Lig E, in N. gonorrhoeae (Ngo-Lig E) impacts biofilm formation. In this research, we further explored this phenotype using confocal and scanning electron microscopy to directly visualise the morphology of microcolony and biofilm formation. Biofilm growth on artificial surfaces and on 3-dimensional human vaginal epithelial tissue was evaluated for strains where ngo-lig E was either disrupted or overexpressed. ResultsResults demonstrated that Ngo-Lig E was important for the formation of robust, compact N. gonorrhoeae microcolonies, as well as extensive biofilms on artificial surfaces. The ngo-lig E deletion strain also had the highest tendency to be retained on the surface of epithelial tissues, with decreased invasion and damage to host cell layers. ConclusionsThese findings support a role for Ngo-Lig E to be secreted from N. gonorrhoeae cells for the purpose of inter-cell adhesion and biofilm formation. We suggest that Ngo-Lig E strengthens the extracellular matrix and hence microcolony and biofilm formation of N. gonorrhoeae by ligation of extracellular DNA.

microbiology↗

bioRxiv2025

Unsupervised Detection of Rare Events in Liquid Biopsy Assays

The use of liquid biopsies in the detection, diagnosis and treatment monitoring of different types of cancers and other diseases often requires identifying and enumerating instances of analytes that are rare. Most current techniques that aim to computationally isolate these rare instances or events first learn the signature of the event, and then scan the appropriate biological assay for this signature. While such techniques have proven to be very useful, they are limited because they must first establish what signature to look for, and only then identify events that are consistent with this signature. In contrast to this, in this study, we present an automated approach that does not require the knowledge of the signature of the rare event. It works by breaking the assay into a sequence of components, learning the probability distribution of these components, and then isolating those that are rare. This is done with the help of deep generative algorithms in an unsupervised manner, meaning without a-priori knowledge of the rare event associated with an analyte. In this study, this approach is applied to immunofluorescence microscopy images of peripheral blood, where it is shown that it successfully isolates biologically relevant events in blood from normal donors spiked with cancer-related cells and in blood from patients with late-stage breast cancer.

bioinformatics↗

bioRxiv2024

Identification of novel inhibitors targeting serine acetyltransferase from Neisseria gonorrhoeae

Neisseria gonorrhoeae is an obligate human pathogen and the etiological agent of the sexually transmitted infection, gonorrhoea. The rapid emergence of extensively antimicrobial-resistant strains, including those resistant to all frontline antibiotics, has led to N. gonorrhoeae being labelled a priority pathogen by the World Health Organization, highlighting the need for new antimicrobial treatments. Given its absence in humans, targeting de novo cysteine biosynthesis has been identified as a promising avenue for developing new antimicrobials against drug-resistant bacteria. The biosynthesis of cysteine is catalyzed by two enzymes; serine acetyltransferase (SAT/CysE) which catalyzes the first step and O-acetylserine sulfhydrylase (OASS/CysK) that catalyzes the second step incorporating sulfur to form L-cysteine. CysE is reported to be essential for bacterial survival in several bacterial pathogens including N. gonorrhoeae. Here, we have conducted virtual inhibitor screening of commercially available compound libraries against SAT from N. gonorrhoeae (NgSAT). We have identified a hit compound with an IC50 of 13.9 {micro}M and analyzed its interactions with the enzymes active site. This provides a platform for the identification and development of novel SAT inhibitors to combat drug-resistant bacterial pathogens.

biochemistry↗

bioRxiv2024

GeTMoR: Simultaneous genomic, transcriptomic, andmorphological profiling of rare single cells

1Circulating tumor cells (CTCs), and circulating tumor related cells, are extremely rare cells that intravasate from the tumor into the circulatory system and can be captured via a liquid biopsy. Although CTCs contribute to the metastatic cascade, and diverse phenotypes of CTCs have been observed - including the cytokeratin expressing CTCs, CTC clusters, large polyploid CTCs, and CTCs undergoing epithelial to mesenchymal transition - little is known about their functionality. By virtue of CTCs being rare, a detection method that maximizes the information obtained per cell would be ideal to understand their biology and for use in diagnostic approaches. The challenge is that rare cell detection necessitates extensive processing steps, during which molecular content, such as RNA and DNA, needs to be preserved for downstream single cell analysis. We developed GEnomic, Transcriptomic, and MOrphological profiling of Rare cells (GeTMoR), a method that extends the High Definition Single Cell Assay for detecting rare cancer related cells to simultaneously image and profile the genome and transcriptome from single rare cells. We validated GeTMoR by spiking in cancer cell lines into whole blood to evaluate the quality of recovered gene expression and copy number profile from the same cell. The GeTMoR approach provides the ability to link the phenotype of rare cells, including CTCs, to their genome and transcriptome, thereby enabling insight into rare cell biology.

genomics↗

bioRxiv2024

Polyploid cancer cells reveal signatures of chemotherapy resistance

Therapeutic resistance in cancer significantly contributes to mortality, with many patients eventually experiencing recurrence after initial treatment responses. Recent studies have identified therapy-resistant large polyploid cancer cells in patient tissues, particularly in late-stage prostate cancer, linking them to advanced disease and relapse. Here, we analyzed bone marrow aspirates from 44 advanced prostate cancer patients and found the presence of circulating tumor cells with increased genomic content (CTC-IGC) was significantly associated with poorer progression- free survival. Single cell copy number profiling of CTC-IGC displayed clonal origins with typical CTCs, suggesting complete polyploidization. Induced polyploid cancer cells from PC3 and MDA-MB-231 cell lines treated with docetaxel or cisplatin were examined through single cell DNA sequencing, RNA sequencing, and protein immunofluorescence. Novel RNA and protein markers, including HOMER1, TNFRSF9, and LRP1, were identified as linked to chemotherapy resistance. These markers were also present in a subset of patient CTCs and associated with recurrence in public gene expression data. This study highlights the prognostic significance of large polyploid tumor cells, their role in chemotherapy resistance, and their expression of markers tied to cancer relapse, offering new potential avenues for therapeutic development.

cancer biology↗

bioRxiv2024

Marker Data Enhancement For Markerless Motion Capture

ObjectiveHuman pose estimation models can measure movement from videos at a large scale and low cost; however, open-source pose estimation models typically detect only sparse keypoints, which leads to inaccurate joint kinematics. OpenCap, a freely available service for researchers to measure movement from videos, addresses this issue using a deep learning model-- the marker enhancer--that transforms sparse keypoints into dense anatomical markers. However, OpenCap performs poorly on movements not included in the training data. Here, we create a much larger and more diverse training dataset and develop a more accurate and generalizable marker enhancer. MethodsWe compiled marker-based motion capture data from 1176 subjects and synthesized 1433 hours of keypoints and anatomical markers to train the marker enhancer. We evaluated its accuracy in computing kinematics using both benchmark movement videos and synthetic data representing unseen, diverse movements. ResultsThe marker enhancer improved kinematic accuracy on benchmark movements (mean error: 4.1{degrees}, max: 8.7{degrees}) compared to using video keypoints (mean: 9.6{degrees}, max: 43.1{degrees}) and OpenCaps original enhancer (mean: 5.3{degrees}, max: 11.5{degrees}). It also better generalized to unseen, diverse movements (mean: 4.1{degrees}, max: 6.7{degrees}) than OpenCaps original enhancer (mean: 40.4{degrees}, max: 252.0{degrees}). ConclusionOur marker enhancer demonstrates both accuracy and generalizability across diverse movements. SignificanceWe integrated the marker enhancer into OpenCap, thereby offering its thousands of users more accurate measurements across a broader range of movements.

bioengineering↗

bioRxiv2024

Cells in the Polyaneuploid Cancer Cell State are Pro-Metastatic

There remains a large need for a greater understanding of the metastatic process within the prostate cancer field. Our research aims to understand the adaptive - ergo potentially metastatic - responses of cancer to changing microenvironments. Emerging evidence has implicated a role of the Polyaneuploid Cancer Cell (PACC) state in metastasis, positing the PACC state as capable of conferring metastatic competency. Mounting in vitro evidence supports increased metastatic potential of cells in the PACC state. Additionally, our recent retrospective study of prostate cancer patients revealed that PACC presence in the prostate at the time of radical prostatectomy was predictive of future metastatic progression. To test for a causative relationship between PACC state biology and metastasis, we leveraged a novel method designed for flow-cytometric detection of circulating tumor cells (CTCs) and disseminated tumor cells (DTCs) in subcutaneous, caudal artery, and intracardiac mouse models of metastasis. This approach provides both quantitative and qualitative information about the number and PACC-status of recovered CTCs and DTCs. Collating data from all models, we found that 74% of recovered CTCs and DTCs were in the PACC state. In vivo colonization assays proved PACC populations can regain proliferative capacity at metastatic sites following dormancy. Additional direct and indirect mechanistic in vitro analyses revealed a PACC-specific partial Epithelial-to-Mesenchymal-Transition phenotype and a pro-metastatic secretory profile, together providing preliminary evidence that PACCs are mechanistically linked to metastasis. Statement of SignificanceWe provide the first evidence that cells in the polyaneuploid cancer cell state contribute to increased metastatic competency in vivo.

cancer biology↗

bioRxiv2023

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation

ObjectiveRecent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing self-supervised learning (SSL) techniques to leverage large IMU datasets to pre-train deep learning models, which can improve the accuracy and data efficiency of IMU-based GRF estimation. MethodsWe performed SSL by masking a random portion of the input IMU data and training a transformer model to reconstruct the masked portion. We systematically compared a series of masking ratios across three pre-training datasets that included real IMU data, synthetic IMU data, or a combination of the two. Finally, we built models that used pre-training and labeled data to estimate GRF during three prediction tasks: overground walking, treadmill walking, and drop landing. ResultsWhen using the same amount of labeled data, SSL pre-training significantly improved the accuracy of 3-axis GRF estimation during walking compared to baseline models trained by conventional supervised learning. Fine-tuning SSL model with 1-10% of walking data yielded comparable accuracy to training baseline model with 100% of walking data. The optimal masking ratio for SSL is 6.25-12.5%. ConclusionSSL leveraged large real and synthetic IMU datasets to increase the accuracy and data efficiency of deep-learning-based GRF estimation, reducing the need for labeled data. SignificanceThis work, with its open-source code and models, may unlock broader use cases of IMU-driven kinetic assessment by mitigating the scarcity of GRF measurements in practical applications.

bioengineering↗

bioRxiv2023

A role for the ATP-dependent DNA ligase Lig E of Neisseria gonorrhoeae in biofilm formation

The ATP-dependent DNA ligase Lig E is present as an accessory DNA ligase in numerous proteobacterial genomes, including many disease-causing species. Here we have constructed a genomic Lig E knock-out in the obligate human pathogen Neisseria gonorrhoeae and characterised its growth and infection characteristics. This demonstrates that N. gonorrhoeae Lig E is a non-essential gene and its deletion does not cause defects in replication or survival of DNA-damaging stressors. Knock-out strains were partially defective in biofilm formation on an artificial surface as well as adhesion to epithelial cells which coupled with the predicted extracellular/ periplasmic location of Lig E indicates a role in extracellular DNA joining. In addition to in vivo characterisation, we have recombinantly expressed and assayed N. gonorrhoeae Lig E and determined the crystal structure of the enzyme-adenylate engaged with DNA substrate in an open non-catalytic conformation, providing insight into the binding dynamics of these minimal DNA ligases.

microbiology↗

bioRxiv2023

Convergent alterations in the tumor microenvironment of MYC-driven human and murine prostate cancer

The tissue microenvironment in prostate cancer is profoundly altered. While such alterations have been implicated in driving prostate cancer initiation and progression to aggressive disease, how prostate cancer cells and their precursors mediate those changes is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we performed extensive single-cell RNA-sequencing (scRNA-seq) and rigorous molecular pathology of the comparative biology between human prostate cancer and key time points in the disease evolution of a genetically engineered mouse model (GEMM) of prostate cancer. Our studies of human tissues, with validation in a large external data set, revealed that cancer cell-intrinsic activation of MYC signaling was the top up-regulated pathway in human cancers, representing a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Likewise, numerous non-malignant cell states in the tumor microenvironment (TME), including non-cancerous epithelial, immune, and fibroblast cell compartments, were conserved across individuals, raising the possibility that these cell types may be a sequelae of the convergent MYC activation in the cancer cells. To test this hypothesis, we employed a GEMM of prostate epithelial cell-specific MYC activation in two mouse strains. Cell communication network and pathway analyses suggested that MYC oncogene-expressing neoplastic cells, directly and indirectly, reprogrammed the TME during carcinogenesis, leading to the emergence of cascading cell state alterations in neighboring epithelial, immune, and fibroblast cell types that paralleled key findings in human prostate cancer. Importantly, among these changes, the progression from a precursor-enriched to invasive-cancer-enriched state was accompanied by a cell-intrinsic switch from pro-immunogenic to immunosuppressive transcriptional programs with coinciding enrichment of immunosuppressive myeloid and Treg cells in the immune microenvironment. These findings implicate activation of MYC signaling in reshaping convergent aspects of the TME of prostate cancer as a common denominator across the otherwise well-documented molecular heterogeneity of human prostate cancer.

cancer biology↗

bioRxiv2023

Simulated musculoskeletal optimization for sprinting and marathon running

Musculoskeletal geometry and muscle volumes vary widely in the population and are intricately linked to the performance of tasks ranging from walking and running to jumping and sprinting. However, our ability to understand how these parameters affect task performance has been limited due to the high computational cost of modelling the necessary complexity of the musculoskeletal system and solving the requisite multi-dimensional optimization problem. For example, sprinting and running are fundamental to many forms of sport, but past research on the relationships between musculoskeletal geometry, muscle volumes, and running performance has been limited to observational studies, which have not established cause-effect relationships, and simulation studies with simplified representations of musculoskeletal geometry. In this study, we developed a novel musculoskeletal simulator that is differentiable with respect to musculoskeletal geometry and muscle volumes. This simulator enabled us to find the optimal body segment dimensions and optimal distribution of added muscle volume for sprinting and marathon running. Our simulation results replicate experimental observations, such as increased muscle mass in sprinters, as well a mass in the lower end of the healthy BMI range and a higher leg-length-to-height ratio in marathon runners. The simulations also reveal new relationships, for example showing that hip musculature is vital to both sprinting and marathon running. We found hip flexor and extensor moment arms were maximized to optimize sprint and marathon running performance, and hip muscles the main target when we simulated strength training for sprinters. Our simulation results can help sprint and marathon runners customize strength training, and our simulator can be extended to other athletic tasks, such as jumping, or to non-athletic applications, such as designing interventions to improve mobility in older adults or individuals with movement disorders. AUTHOR SUMMARYOur study addresses the challenge of determining optimal musculoskeletal parameters for tasks like sprinting and marathon running. Existing research has been limited to observational studies and simplified simulations. To overcome these limitations, we developed a differentiable musculoskeletal simulator to optimize running performance. We replicated past findings and uncovered new insights. We confirmed the benefits of increased muscle mass for sprinters and identified key factors for marathon runners, such a mass in the lower end of the healthy BMI range and an increased leg-length-to-height ratio. Hip musculature was found to be critical for both sprinting and marathon running. Our simulation results have practical implications. They can inform customized strength training for sprinters and marathon runners. Additionally, the simulator can be extended to other athletic tasks, benefiting various sporting events. Beyond athletics, our open-source simulator has broader applications. It can determine minimal strength requirements for daily activities, guide strength training in the elderly, and estimate the effects of simulated musculoskeletal surgery.

bioengineering↗