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JCO Clinical Cancer Informatics Jun 2024The estimation of prognosis and life expectancy is critical in the care of patients with advanced cancer. To aid clinical decision making, we build a prognostic strategy...
PURPOSE
The estimation of prognosis and life expectancy is critical in the care of patients with advanced cancer. To aid clinical decision making, we build a prognostic strategy combining a machine learning (ML) model with explainable artificial intelligence to predict 1-year survival after palliative radiotherapy (RT) for bone metastasis.
MATERIALS AND METHODS
Data collected in the multicentric PRAIS trial were extracted for 574 eligible adults diagnosed with metastatic cancer. The primary end point was the overall survival (OS) at 1 year (1-year OS) after the start of RT. Candidate covariate predictors consisted of 13 clinical and tumor-related pre-RT patient characteristics, seven dosimetric and treatment-related variables, and 45 pre-RT laboratory variables. ML models were developed and internally validated using the Python package. The effectiveness of each model was evaluated in terms of discrimination. A Shapley Additive Explanations (SHAP) explainability analysis to infer the global and local feature importance and to understand the reasons for correct and misclassified predictions was performed.
RESULTS
The best-performing model for the classification of 1-year OS was the extreme gradient boosting algorithm, with AUC and F1-score values equal to 0.805 and 0.802, respectively. The SHAP technique revealed that higher chance of 1-year survival is associated with low values of interleukin-8, higher values of hemoglobin and lymphocyte count, and the nonuse of steroids.
CONCLUSION
An explainable ML approach can provide a reliable prediction of 1-year survival after RT in patients with advanced cancer. The implementation of SHAP analysis provides an intelligible explanation of individualized risk prediction, enabling oncologists to identify the best strategy for patient stratification and treatment selection.
Topics: Humans; Machine Learning; Bone Neoplasms; Palliative Care; Male; Female; Prognosis; Aged; Middle Aged; Algorithms
PubMed: 38917384
DOI: 10.1200/CCI.24.00027 -
ELife Jun 2024Adaptive motor behavior depends on the coordinated activity of multiple neural systems distributed across the brain. While the role of sensorimotor cortex in motor...
Adaptive motor behavior depends on the coordinated activity of multiple neural systems distributed across the brain. While the role of sensorimotor cortex in motor learning has been well established, how higher-order brain systems interact with sensorimotor cortex to guide learning is less well understood. Using functional MRI, we examined human brain activity during a reward-based motor task where subjects learned to shape their hand trajectories through reinforcement feedback. We projected patterns of cortical and striatal functional connectivity onto a low-dimensional manifold space and examined how regions expanded and contracted along the manifold during learning. During early learning, we found that several sensorimotor areas in the dorsal attention network exhibited increased covariance with areas of the salience/ventral attention network and reduced covariance with areas of the default mode network (DMN). During late learning, these effects reversed, with sensorimotor areas now exhibiting increased covariance with DMN areas. However, areas in posteromedial cortex showed the opposite pattern across learning phases, with its connectivity suggesting a role in coordinating activity across different networks over time. Our results establish the neural changes that support reward-based motor learning and identify distinct transitions in the functional coupling of sensorimotor to transmodal cortex when adapting behavior.
Topics: Humans; Magnetic Resonance Imaging; Reward; Male; Learning; Female; Adult; Young Adult; Sensorimotor Cortex; Brain Mapping; Motor Activity; Cerebral Cortex
PubMed: 38916598
DOI: 10.7554/eLife.91928 -
Frontiers in Medicine 2024Immunotherapy targeted to immune checkpoint inhibitors, such as the program cell death receptor (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment.... (Review)
Review
Immunotherapy targeted to immune checkpoint inhibitors, such as the program cell death receptor (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment. However, it is now well-known that PD-1/PD-L1 immunotherapy response is inconsistent among patients. The current challenge is to customize treatment regimens per patient, which could be possible if the PD-1/PD-L1 expression and dynamic landscape are known. With positron emission tomography (PET) imaging, it is possible to image these immune targets non-invasively and system-wide during therapy. A successful PET imaging tracer should meet specific criteria concerning target affinity, specificity, clearance rate and target-specific uptake, to name a few. The structural profile of such a tracer will define its properties and can be used to optimize tracers in development and design new ones. Currently, a range of PD-1/PD-L1-targeting PET tracers are available from different molecular categories that have shown impressive preclinical and clinical results, each with its own advantages and disadvantages. This review will provide an overview of current PET tracers targeting the PD-1/PD-L1 axis. Antibody, peptide, and antibody fragment tracers will be discussed with respect to their molecular characteristics and binding properties and ways to optimize them.
PubMed: 38915766
DOI: 10.3389/fmed.2024.1401515 -
BioRxiv : the Preprint Server For... Jun 2024Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell...
Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell segmentation tools are often optimized for high signal-to-noise ratio (SNR) images, such as fluorescently labeled cells, and unsurprisingly perform poorly on low SNR autofluorescence images. Therefore, new cell segmentation tools are needed for autofluorescence microscopy. Cellpose is a deep learning network that is generalizable across diverse cell microscopy images and automatically segments single cells to improve throughput and reduce inter-human biases. This study aims to validate Cellpose for autofluorescence imaging, specifically from multiphoton intensity images of NAD(P)H. Manually segmented nuclear masks of NAD(P)H images were used to train new Cellpose models. These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (across 9 patients) treated with chemotherapies. These datasets include co-registered fluorescence lifetime imaging microscopy (FLIM) of NAD(P)H and FAD, so fluorescence decay parameters and the optical redox ratio (ORR) were compared between masks generated by the new Cellpose model and manual segmentation. The Dice score between repeated manually segmented masks was significantly lower than that of repeated Cellpose masks (p<0.0001) indicating greater reproducibility between Cellpose masks. There was also a high correlation (R >0.9) between Cellpose and manually segmented masks for the ORR, mean NAD(P)H lifetime, and mean FAD lifetime across 2D and 3D cell culture treatment conditions. Masks generated from Cellpose and manual segmentation also maintain similar means, variances, and effect sizes between treatments for the ORR and FLIM parameters. Overall, Cellpose provides a fast, reliable, reproducible, and accurate method to segment single cells in autofluorescence microscopy images such that functional changes in cells are accurately captured in both 2D and 3D culture.
PubMed: 38915614
DOI: 10.1101/2024.06.07.597994 -
BioRxiv : the Preprint Server For... Jun 2024White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's...
White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's disease. Despite their frequent appearance and their association with cognitive decline, the molecular factors contributing to WMHs remain unclear. In this study, we investigated the transcriptomic profiles of two commonly affected brain regions with coincident AD pathology-frontal subcortical white matter (frontal-WM) and occipital subcortical white matter (occipital-WM)-and compared with age-matched healthy controls. Through RNA-sequencing in frontal- and occipital-WM bulk tissues, we identified an upregulation of genes associated with brain vasculature function in AD white matter. To further elucidate vasculature-specific transcriptomic features, we performed RNA-seq analysis on blood vessels isolated from these white matter regions, which revealed an upregulation of genes related to protein folding pathways. Finally, comparing gene expression profiles between AD individuals with high-versus low-WMH burden showed an increased expression of pathways associated with immune function. Taken together, our study characterizes the diverse molecular profiles of white matter changes in AD compared to normal aging and provides new mechanistic insights processes underlying AD-related WMHs.
PubMed: 38915516
DOI: 10.1101/2024.06.13.598845 -
Clinical Kidney Journal Jun 2024The aim of this work was to create and evaluate a preoperative non-contrast-enhanced (CE) magnetic resonance imaging (MRI)/angiography (MRA) protocol to assess renal...
BACKGROUND
The aim of this work was to create and evaluate a preoperative non-contrast-enhanced (CE) magnetic resonance imaging (MRI)/angiography (MRA) protocol to assess renal function and visualize renal arteries and any abnormalities in potential living kidney donors.
METHODS
In total, 28 subjects were examined using scintigraphy to determine renal function. In addition, 3D-pseudocontinuous arterial spin labeling (pCASL), a 2D-non-CE electrocardiogram-triggered radial quiescent interval slice-selective (QISS-MRA), and 4D-CE time-resolved angiography with interleaved stochastic trajectories (CE-MRA) were performed to assess renal perfusion, visualize renal arteries and detect any abnormalities. Two glomerular filtration rates [described by Gates (GFR) and according to the Chronic Kidney Disease Epidemiology Collaboration formula (GFR)]. The renal volumes were determined using both MRA techniques.
RESULTS
The mean value of regional renal blood flow (rRBF) on the right side was significantly higher than that on the left. The agreements between QISS-MRA and CE-MRA concerning the assessment of absence or presence of an aberrant artery and renal arterial stenosis were perfect. The mean renal volumes measured in the right kidney with QISS-MRA were lower than the corresponding values of CE-MRA. In contrast, the mean renal volumes measured in the left kidney with both MRA techniques were similar. The correlation between the GFR and rRBF was compared in the same manner as that between GFR and rRBF.
CONCLUSION
The combination of pCASL and QISS-MRA constitute a reliable preoperative protocol with a total measurement time of <10 min without the potential side effects of gadolinium-based contrast agents or radiation exposure.
PubMed: 38915436
DOI: 10.1093/ckj/sfae101 -
Frontiers in Immunology 2024This study aimed to investigate the dynamics of programmed death-ligand 1 (PD-L1) expression, spatial heterogeneity, and binding affinity of FDA-approved anti-PD-L1...
INTRODUCTION
This study aimed to investigate the dynamics of programmed death-ligand 1 (PD-L1) expression, spatial heterogeneity, and binding affinity of FDA-approved anti-PD-L1 antibodies (avelumab and atezolizumab) in gastric cancer. Additionally, we determined how PD-L1 glycosylation impacts antibody accumulation in gastric cancer cells.
METHODS
Dynamic PD-L1 expression was examined in NCIN87 gastric cancer cells. Comparative binding studies of avelumab and atezolizumab were conducted in gastric cancer models, both and . Antibody uptake in tumors was visualized through positron emission tomography (PET) imaging. PD-L1 glycosylation status was determined via Western blot analyses before and after PNGase F treatment.
RESULTS
Consistent findings revealed time-dependent PD-L1 induction in NCIN87 gastric cancer cells and spatial heterogeneity in tumors, as shown by PET imaging and immunofluorescence. Avelumab displayed superior binding affinity to NCIN87 cells compared to atezolizumab, confirmed by PET imaging and biodistribution analyses. Notably, PD-L1 glycosylation at approximately 50 kDa was observed, with PNGase F treatment inducing a shift to 35 kDa in molecular weight. Tissue samples from patient-derived xenografts (PDXs) validated the presence of both glycosylated and deglycosylated PD-L1 (degPD-L1) forms in gastric cancer. Immunofluorescence microscopy and binding assays demonstrated enhanced avelumab binding post-deglycosylation.
DISCUSSION
This study provides an understanding of dynamic and spatially heterogeneous PD-L1 expression in gastric cancer. Anti-PD-L1 immunoPET was able to visualize gastric tumors, and PD-L1 glycosylation has significant implications for antibody recognition. These insights contribute to demonstrating the complexities of PD-L1 in gastric cancer, holding relevance for refining PD-L1 imaging-based approaches.
Topics: Stomach Neoplasms; B7-H1 Antigen; Humans; Animals; Mice; Cell Line, Tumor; Glycosylation; Antibodies, Monoclonal, Humanized; Xenograft Model Antitumor Assays; Female; Positron-Emission Tomography
PubMed: 38915392
DOI: 10.3389/fimmu.2024.1405485 -
Journal of Biological Engineering Jun 2024Breast cancer remains a challenge for physicians. Metformin, an antidiabetic drug, show promising anticancer properties against cancers. An emerging quantum dot (QD)...
BACKGROUND
Breast cancer remains a challenge for physicians. Metformin, an antidiabetic drug, show promising anticancer properties against cancers. An emerging quantum dot (QD) material improves therapeutic agents' anticancer and imaging properties. QD are nano-sized particles with extreme application in nanotechnology captured by cells and accumulated inside cells, suggesting bioimaging and effective anticancer outcomes. In this study, a simple one-pot hydrothermal method was used to synthesize fluorescent metformin-derived carbon dots (M-CDs) and then investigated the cytotoxic effects and imaging features on two human breast cancer cell lines including, MCF-7 and MDA-MB-231 cells.
RESULTS
Results showed that M-CDs profoundly decreased the viability of both cancer cells. IC50 values showed that M-CDs were more cytotoxic than metformin either 24-48 h post-treatment. Cancer cells uptake M-CDs successfully, which causes morphological changes in cells and increased levels of intracellular ROS. The number of Oil Red O-positive cells and the expression of caspase-3 protein were increased in M-CDs treated cells. Authophagic factors including, AMPK, mTOR, and P62 were down-regulated, while p-AMPK, Becline-1, LC3 I, and LC3 II were up-regulated in M-CDs treated cells. Finally, M-CDs caused a decrease in the wound healing rate of cells.
CONCLUSIONS
For the first, M-CDs were synthesized by simple one-pot hydrothermal treatment without further purification. M-CDs inhibited both breast cancer cells through modulating autophagy signalling.
PubMed: 38915025
DOI: 10.1186/s13036-024-00433-4 -
Journal of Nanobiotechnology Jun 2024Photothermal therapy (PTT) is a promising cancer treatment method due to its ability to induce tumor-specific T cell responses and enhance therapeutic outcomes. However,...
Photothermal therapy (PTT) is a promising cancer treatment method due to its ability to induce tumor-specific T cell responses and enhance therapeutic outcomes. However, incomplete PTT can leave residual tumors that often lead to new metastases and decreased patient survival in clinical scenarios. This is primarily due to the release of ATP, a damage-associated molecular pattern that quickly transforms into the immunosuppressive metabolite adenosine by CD39, prevalent in the tumor microenvironment, thus promoting tumor immune evasion. This study presents a photothermal nanomedicine fabricated by electrostatic adsorption among the Fe-doped polydiaminopyridine (Fe-PDAP), indocyanine green (ICG), and CD39 inhibitor sodium polyoxotungstate (POM-1). The constructed Fe-PDAP@ICG@POM-1 (FIP) can induce tumor PTT and immunogenic cell death when exposed to a near-infrared laser. Significantly, it can inhibit the ATP-adenosine pathway by dual-directional immunometabolic regulation, resulting in increased ATP levels and decreased adenosine synthesis, which ultimately reverses the immunosuppressive microenvironment and increases the susceptibility of immune checkpoint blockade (aPD-1) therapy. With the aid of aPD-1, the dual-directional immunometabolic regulation strategy mediated by FIP can effectively suppress/eradicate primary and distant tumors and evoke long-term solid immunological memory. This study presents an immunometabolic control strategy to offer a salvage option for treating residual tumors following incomplete PTT.
Topics: Animals; Photothermal Therapy; Immunotherapy; Mice; Nanomedicine; Tumor Microenvironment; Cell Line, Tumor; Humans; Indocyanine Green; Neoplasms; Adenosine Triphosphate; Adenosine; Mice, Inbred C57BL; Apyrase; Female; Phototherapy
PubMed: 38915007
DOI: 10.1186/s12951-024-02643-w -
Communications Biology Jun 2024Chromatin organization and dynamics play important roles in governing the regulation of nuclear processes of biological cells. However, due to the constant diffusive...
Chromatin organization and dynamics play important roles in governing the regulation of nuclear processes of biological cells. However, due to the constant diffusive motion of chromatin, examining chromatin nanostructures in living cells has been challenging. In this study, we introduce interferometric scattering correlation spectroscopy (iSCORS) to spatially map nanoscopic chromatin configurations within unlabeled live cell nuclei. This label-free technique captures time-varying linear scattering signals generated by the motion of native chromatin on a millisecond timescale, allowing us to deduce chromatin condensation states. Using iSCORS imaging, we quantitatively examine chromatin dynamics over extended periods, revealing spontaneous fluctuations in chromatin condensation and heterogeneous compaction levels in interphase cells, independent of cell phases. Moreover, we observe changes in iSCORS signals of chromatin upon transcription inhibition, indicating that iSCORS can probe nanoscopic chromatin structures and dynamics associated with transcriptional activities. Our scattering-based optical microscopy, which does not require labeling, serves as a powerful tool for visualizing dynamic chromatin nano-arrangements in live cells. This advancement holds promise for studying chromatin remodeling in various crucial cellular processes, such as stem cell differentiation, mechanotransduction, and DNA repair.
Topics: Chromatin; Humans; Spectrum Analysis; Interferometry; Chromatin Assembly and Disassembly; Cell Nucleus
PubMed: 38914653
DOI: 10.1038/s42003-024-06457-2