Browsing by Subject "Prognostic markers"
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Item A breast cancer classification and immune landscape analysis based on cancer stem-cell-related risk panel(Springer Nature, 2023-12-08) Hu, Haihong; Zou, Mingxiang; Hu, Hongjuan; Hu, Zecheng; Jiang, Lingxiang; Escobar, David; Zhu, Hongxia; Zhan, Wendi; Yan, Ting; Zhang, Taolan; Radiation Oncology, School of MedicineThis study sought to identify molecular subtypes of breast cancer (BC) and develop a breast cancer stem cells (BCSCs)-related gene risk score for predicting prognosis and assessing the potential for immunotherapy. Unsupervised clustering based on prognostic BCSC genes was used to determine BC molecular subtypes. Core genes of BC subtypes identified by non-negative matrix factorization algorithm (NMF) were screened using weighted gene co-expression network analysis (WGCNA). A risk model based on prognostic BCSC genes was constructed using machine learning as well as LASSO regression and multivariate Cox regression. The tumor microenvironment and immune infiltration were analyzed using ESTIMATE and CIBERSORT, respectively. A CD79A+CD24-PANCK+-BCSC subpopulation was identified and its spatial relationship with microenvironmental immune response state was evaluated by multiplexed quantitative immunofluorescence (QIF) and TissueFAXS Cytometry. We identified two distinct molecular subtypes, with Cluster 1 displaying better prognosis and enhanced immune response. The constructed risk model involving ten BCSC genes could effectively stratify patients into subgroups with different survival, immune cell abundance, and response to immunotherapy. In subsequent QIF validation involving 267 patients, we demonstrated the existence of CD79A+CD24-PANCK+-BCSC in BC tissues and revealed that this BCSC subtype located close to exhausted CD8+FOXP3+ T cells. Furthermore, both the densities of CD79A+CD24-PANCK+-BCSCs and CD8+FOXP3+T cells were positively correlated with poor survival. These findings highlight the importance of BCSCs in prognosis and reshaping the immune microenvironment, which may provide an option to improve outcomes for patients.Item A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure(Springer Nature, 2021-12-03) Yang, Zhijian; Nasrallah, Ilya M.; Shou, Haochang; Wen, Junhao; Doshi, Jimit; Habes, Mohamad; Erus, Guray; Abdulkadir, Ahmed; Resnick, Susan M.; Albert, Marilyn S.; Maruff, Paul; Fripp, Jurgen; Morris, John C.; Wolk, David A.; Davatzikos, Christos; iSTAGING Consortium; Baltimore Longitudinal Study of Aging (BLSA); Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of MedicineHeterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical heterogeneity contrasted against normal brain structure, to identify disease subtypes through neuroimaging signatures. When applied to regional volumes derived from T1-weighted MRI (two studies; 2,832 participants; 8,146 scans) including cognitively normal individuals and those with cognitive impairment and dementia, Smile-GAN identified four patterns or axes of neurodegeneration. Applying this framework to longitudinal data revealed two distinct progression pathways. Measures of expression of these patterns predicted the pathway and rate of future neurodegeneration. Pattern expression offered complementary performance to amyloid/tau in predicting clinical progression. These deep-learning derived biomarkers offer potential for precision diagnostics and targeted clinical trial recruitment.Item A proteogenomic view of Parkinson's disease causality and heterogeneity(Springer Nature, 2023-02-11) Kaiser, Sergio; Zhang, Luqing; Mollenhauer, Brit; Jacob, Jaison; Longerich, Simonne; Del-Aguila, Jorge; Marcus, Jacob; Raghavan, Neha; Stone, David; Fagboyegun, Olumide; Galasko, Douglas; Dakna, Mohammed; Bilican, Bilada; Dovlatyan, Mary; Kostikova, Anna; Li, Jingyao; Peterson, Brant; Rotte, Michael; Sanz, Vinicius; Foroud, Tatiana; Hutten, Samantha J.; Frasier, Mark; Iwaki, Hirotaka; Singleton, Andrew; Marek, Ken; Crawford, Karen; Elwood, Fiona; Messa, Mirko; Serrano-Fernandez, Pablo; Medical and Molecular Genetics, School of MedicineThe pathogenesis and clinical heterogeneity of Parkinson’s disease (PD) have been evaluated from molecular, pathophysiological, and clinical perspectives. High-throughput proteomic analysis of cerebrospinal fluid (CSF) opened new opportunities for scrutinizing this heterogeneity. To date, this is the most comprehensive CSF-based proteomics profiling study in PD with 569 patients (350 idiopathic patients, 65 GBA + mutation carriers and 154 LRRK2 + mutation carriers), 534 controls, and 4135 proteins analyzed. Combining CSF aptamer-based proteomics with genetics we determined protein quantitative trait loci (pQTLs). Analyses of pQTLs together with summary statistics from the largest PD genome wide association study (GWAS) identified 68 potential causal proteins by Mendelian randomization. The top causal protein, GPNMB, was previously reported to be upregulated in the substantia nigra of PD patients. We also compared the CSF proteomes of patients and controls. Proteome differences between GBA + patients and unaffected GBA + controls suggest degeneration of dopaminergic neurons, altered dopamine metabolism and increased brain inflammation. In the LRRK2 + subcohort we found dysregulated lysosomal degradation, altered alpha-synuclein processing, and neurotransmission. Proteome differences between idiopathic patients and controls suggest increased neuroinflammation, mitochondrial dysfunction/oxidative stress, altered iron metabolism and potential neuroprotection mediated by vasoactive substances. Finally, we used proteomic data to stratify idiopathic patients into “endotypes”. The identified endotypes show differences in cognitive and motor disease progression based on previously reported protein-based risk scores.Our findings not only contribute to the identification of new therapeutic targets but also to shape personalized medicine in CNS neurodegeneration.Item Alterations of brain microstructures in a mouse model of prenatal opioid exposure detected by diffusion MRI(Springer Nature, 2022-10-12) Grecco, Gregory G.; Shahid, Syed Salman; Atwood, Brady K.; Wu, Yu‑Chien; Pharmacology and Toxicology, School of MedicineGrowing opioid use among pregnant women is fueling a crisis of infants born with prenatal opioid exposure. A large body of research has been devoted to studying the management of opioid withdrawal during the neonatal period in these infants, but less substantive work has explored the long-term impact of prenatal opioid exposure on neurodevelopment. Using a translationally relevant mouse model of prenatal methadone exposure (PME), the aim of the study is to investigate the cerebral microstructural differences between the mice with PME and prenatal saline exposure (PSE). The brains of eight-week-old male offspring with either PME (n = 15) or PSE (n = 15) were imaged using high resolution in-vivo diffusion magnetic resonance imaging on a 9.4 Tesla small animal scanner. Brain microstructure was characterized using diffusion tensor imaging (DTI) and Bingham neurite orientation dispersion and density imaging (Bingham-NODDI). Voxel-based analysis (VBA) was performed using the calculated microstructural parametric maps. The VBA showed significant (p < 0.05) bilateral alterations in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI) and dispersion anisotropy index (DAI) across several cortical and subcortical regions, compared to PSE. Particularly, in PME offspring, FA, MD and AD were significantly higher in the hippocampus, dorsal amygdala, thalamus, septal nuclei, dorsal striatum and nucleus accumbens. These DTI-based results suggest widespread bilateral microstructural alterations across cortical and subcortical regions in PME offspring. Consistent with the observations in DTI, Bingham-NODDI derived ODI exhibited significant reduction in PME offspring within the hippocampus, dorsal striatum and cortex. NODDI-based results further suggest reduction in dendritic arborization in PME offspring across multiple cortical and subcortical regions. To our best knowledge, this is the first study of prenatal opioid exposure to examine microstructural organization in vivo. Our findings demonstrate perturbed microstructural complexity in cortical and subcortical regions persisting into early adulthood which could interfere with critical neurodevelopmental processes in individuals with prenatal opioid exposure.Item Amyloid-associated increases in soluble tau relate to tau aggregation rates and cognitive decline in early Alzheimer’s disease(Springer Nature, 2022-11-04) Pichet Binette, Alexa; Franzmeier, Nicolai; Spotorno, Nicola; Ewers, Michael; Brendel, Matthias; Biel, Davina; Alzheimer’s Disease Neuroimaging Initiative; Strandberg, Olof; Janelidze, Shorena; Palmqvist, Sebastian; Mattsson-Carlgren, Niklas; Smith, Ruben; Stomrud, Erik; Ossenkoppele, Rik; Hansson, Oskar; Radiology and Imaging Sciences, School of MedicineFor optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, we need to better understand the pathophysiological cascade of Aβ- and tau-related processes. Therefore, we set out to investigate how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with PET and subsequent cognitive decline across the Alzheimer's disease (AD) continuum. Using human cross-sectional and longitudinal neuroimaging and cognitive assessment data, we show that in early stages of AD, increased concentration of soluble CSF p-tau is strongly associated with accumulation of insoluble tau aggregates across the brain, and CSF p-tau levels mediate the effect of Aβ on tau aggregation. Further, higher soluble p-tau concentrations are mainly related to faster accumulation of tau aggregates in the regions with strong functional connectivity to individual tau epicenters. In this early stage, higher soluble p-tau concentrations is associated with cognitive decline, which is mediated by faster increase of tau aggregates. In contrast, in AD dementia, when Aβ fibrils and soluble p-tau levels have plateaued, cognitive decline is related to the accumulation rate of insoluble tau aggregates. Our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD, before widespread insoluble tau aggregates.Item Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease(Springer Nature, 2022-03-21) Duong, Michael Tran; Das, Sandhitsu R.; Lyu, Xueying; Xie, Long; Richardson, Hayley; Xie, Sharon X.; Yushkevich, Paul A.; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Wolk, David A.; Nasrallah, Ilya M.; Radiology and Imaging Sciences, School of MedicineAlzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.Item Inflammatory cytokines and distant recurrence in HER2-negative early breast cancer(Springer Nature, 2022-02-08) Sparano, Joseph A.; O’Neill, Anne; Graham, Noah; Northfelt, Donald W.; Dang, Chau T.; Wolff, Antonio C.; Sledge, George W.; Miller, Kathy D.; Medicine, School of MedicineSystemic inflammation is believed to contribute to the distant recurrence of breast cancer. We evaluated serum samples obtained at diagnosis from 249 case:control pairs with stage II-III Her2-negative breast cancer with or without subsequent distant recurrence. Conditional logistic regression analysis, with models fit via maximum likelihood, were used to estimate hazard ratios (HRs) and test for associations of cytokines with distant recurrence risk. The only biomarker associated with a significantly increased distant recurrence risk when adjusted for multiple testing was the proinflammatory cytokine IL-6 (HR 1.37, 95% confidence intervals [CI] 1.15, 1.65, p = 0.0006). This prospective-retrospective study provides evidence indicating that higher levels of the cytokine IL-6 at diagnosis are associated with a significantly higher distant recurrence risk.Item Inflammatory cytokines and distant recurrence in HER2-negative early breast cancer(Springer, 2022-02-08) Sparano, Joseph A.; O’Neill, Anne; Graham, Noah; Northfelt, Donald W.; Dang, Chau T.; Wolff, Antonio C.; Sledge, George W.; Miller , Kathy D.; Medicine, School of MedicineSystemic inflammation is believed to contribute to the distant recurrence of breast cancer. We evaluated serum samples obtained at diagnosis from 249 case:control pairs with stage II-III Her2-negative breast cancer with or without subsequent distant recurrence. Conditional logistic regression analysis, with models fit via maximum likelihood, were used to estimate hazard ratios (HRs) and test for associations of cytokines with distant recurrence risk. The only biomarker associated with a significantly increased distant recurrence risk when adjusted for multiple testing was the proinflammatory cytokine IL-6 (HR 1.37, 95% confidence intervals [CI] 1.15, 1.65, p = 0.0006). This prospective-retrospective study provides evidence indicating that higher levels of the cytokine IL-6 at diagnosis are associated with a significantly higher distant recurrence risk.Item Internal capsule microstructure mediates the relationship between childhood maltreatment and PTSD following adulthood trauma exposure(Springer Nature, 2023) Wong, Samantha A.; Lebois, Lauren A. M.; Ely, Timothy D.; van Rooij, Sanne J. H.; Bruce, Steven E.; Murty, Vishnu P.; Jovanovic, Tanja; House, Stacey L.; Beaudoin, Francesca L.; An, Xinming; Zeng, Donglin; Neylan, Thomas C.; Clifford, Gari D.; Linnstaedt, Sarah D.; Germine, Laura T.; Bollen, Kenneth A.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Kurz, Michael C.; Swor, Robert A.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Miller, Mark W.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Harte, Steven E.; Elliott, James M.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; Ressler, Kerry J.; Stevens, Jennifer S.; Harnett, Nathaniel G.; Emergency Medicine, School of MedicineChildhood trauma is a known risk factor for trauma and stress-related disorders in adulthood. However, limited research has investigated the impact of childhood trauma on brain structure linked to later posttraumatic dysfunction. We investigated the effect of childhood trauma on white matter microstructure after recent trauma and its relationship with future posttraumatic dysfunction among trauma-exposed adult participants (n = 202) recruited from emergency departments as part of the AURORA Study. Participants completed self-report scales assessing prior childhood maltreatment within 2-weeks in addition to assessments of PTSD, depression, anxiety, and dissociation symptoms within 6-months of their traumatic event. Fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI) collected at 2-weeks and 6-months was used to index white matter microstructure. Childhood maltreatment load predicted 6-month PTSD symptoms (b = 1.75, SE = 0.78, 95% CI = [0.20, 3.29]) and inversely varied with FA in the bilateral internal capsule (IC) at 2-weeks (p = 0.0294, FDR corrected) and 6-months (p = 0.0238, FDR corrected). We observed a significant indirect effect of childhood maltreatment load on 6-month PTSD symptoms through 2-week IC microstructure (b = 0.37, Boot SE = 0.18, 95% CI = [0.05, 0.76]) that fully mediated the effect of childhood maltreatment load on PCL-5 scores (b = 1.37, SE = 0.79, 95% CI = [−0.18, 2.93]). IC microstructure did not mediate relationships between childhood maltreatment and depressive, anxiety, or dissociative symptomatology. Our findings suggest a unique role for IC microstructure as a stable neural pathway between childhood trauma and future PTSD symptoms following recent trauma. Notably, our work did not support roles of white matter tracts previously found to vary with PTSD symptoms and childhood trauma exposure, including the cingulum bundle, uncinate fasciculus, and corpus callosum. Given the IC contains sensory fibers linked to perception and motor control, childhood maltreatment might impact the neural circuits that relay and process threat-related inputs and responses to trauma.Item Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast(Springer Nature, 2021) Badve, Sunil S.; Cho, Sanghee; Gökmen-Polar, Yesim; Sui, Yunxia; Chadwick, Chrystal; McDonough, Elizabeth; Sood, Anup; Taylor, Marian; Zavodszky, Maria; Tan, Puay Hoon; Gerdes, Michael; Harris, Adrian L.; Ginty, Fiona; Pathology and Laboratory Medicine, School of MedicineBackground: There is limited knowledge about DCIS cellular composition and relationship with breast cancer events (BCE). Methods: Immunofluorescence multiplexing (MxIF) was used to image and quantify 32 cellular biomarkers in FFPE DCIS tissue microarrays. Over 75,000 DCIS cells from 51 patients (median 9 years follow-up for non-BCE cases) were analysed for profiles predictive of BCE. K-means clustering was used to evaluate cellular co-expression of epithelial markers with ER and HER2. Results: Only ER, PR and HER2 significantly correlated with BCE. Cluster analysis identified 6 distinct cell groups with different levels of ER, Her2, cMET and SLC7A5. Clusters 1 and 3 were not significant. Clusters 2 and 4 (high ER/low HER2 and SLC7A5/mixed cMET) significantly correlated with low BCE risk (P = 0.001 and P = 0.034), while cluster 6 (high HER2/low ER, cMET and SLC7A5) correlated with increased risk (P = 0.018). Cluster 5 (similar to cluster 6, except high SLC7A5) trended towards significance (P = 0.072). A continuous expression score (Escore) based on these 4 clusters predicted likelihood of BCE (AUC = 0.79, log-rank test P = 5E-05; LOOCV AUC = 0.74, log-rank test P = 0.006). Conclusion: Multiplexed spatial analysis of limited tissue is a novel method for biomarker analysis and predicting BCEs. Further validation of Escore is needed in a larger cohort.