Clinical Research
Abstract
BACKGROUND Proliferation is a key biological feature of cancer and in prostate cancer is modulated by androgen receptor (AR) signalling. Cohort studies have suggested that highly proliferative tumors respond poorly to androgen receptor pathway inhibitors (ARPIs). To clarify whether tumor proliferation interacts with treatment benefit from adding abiraterone to androgen deprivation therapy (ADT), we assessed the Ki-67 proliferation index in prostate core biopsies from participants enrolled in the STAMPEDE platform protocol. METHODS Proliferation was assessed by Ki67 immunohistochemistry on tumors from patients randomized in two sequential but non-overlapping (ie no shared controls) phase 3 trials of abiraterone or abiraterone and enzalutamide conducted in STAMPEDE (NCT00268476), with 14-year survival outcomes. A standardised unweighted global assessment method was used. Survival analyses used Cox proportional hazards models adjusted for established prognostic factors. Ki-67 was examined both continuously and dichotomised at the median. Sensitivity analyses excluded samples exposed to ADT. RESULTS Ki-67 was successfully scored on cancers from 1,605 patients. Higher Ki-67 was strongly prognostic for shorter overall survival across disease states. However, in metastatic patients treated with ADT plus abiraterone, the adverse prognostic impact of high Ki-67 was substantially attenuated (aHR=1.06 per 10-percentage-point increase), with a statistically-significant treatment-biomarker interaction (p<0.001) confirming highly proliferative tumors derived greater treatment benefit. No interaction was observed in non-metastatic disease. CONCLUSION Ki-67 is an independent prognostic biomarker in advanced prostate cancer. In metastatic disease, higher proliferation predicts greater sensitivity to abiraterone added to ADT, suggesting a potential biological vulnerability of rapidly cycling tumors to intensified AR pathway blockade. TRIAL REGISTRATION: NCT00268476
Authors
Larissa Mendes, Peter F. Dutey-Magni, Emily Grist, Ashwin Sachdeva, Sara Santos Vidal, Sharanpreet Lall, Marina A. Parry, Claire L. Amos, Nafisah B. Atako, Anna Wingate, Daniel Wetterskog, Matthew R. Sydes, Chris C. Parker, Noel Clarke, Christopher J. Sweeney, Mahesh KB Parmar, Louise C. Brown, Nicholas D. James, Daniel M. Berney, Gerhardt Attard
Abstract
High levels of L- and D-2-hydroxyglutarate (2HG), the reduced forms of α-ketoglutarate (αKG), are implicated in neurodevelopmental disorders and cancer by modulating αKG-dependent dioxygenases involved in histone, DNA and RNA demethylation. L-2HG dehydrogenase (L2HGDH) deficiency, a rare autosomal recessive inborn error of metabolism associated with systemic L-2HG elevation, causes progressive neurological disability and increased brain tumor risk of unclear mechanism. Using an isogenic, patient-derived induced pluripotent stem cell (iPSC) system, we examined the impact of L2HGDH deficiency on neural progenitor cell (NPC) function and neuronal differentiation. L2HGDH deficiency caused L-2HG accumulation, NPC hyperproliferation, increased clonogenicity, and defective neuronal differentiation in 2D cultures and cortical spheroids. Editing the L2HGDH locus to wild-type reversed these effects. Inhibiting glutaminase reduced L-2HG levels and induced neuronal differentiation. L-2HG-dependent inhibition of KDM5 histone demethylases led to widespread retention of H3K4me2/3, markers of active gene expression, with prominent enrichment at the MYC locus and elevated MYC expression across multiple neural cell types. Despite broadly altered histone methylation, genetically or pharmacologically normalizing MYC completely restored neuronal differentiation. These data indicated that a primary metabolic disturbance activated MYC to favor self-renewal and suppress neuronal lineage commitment.
Authors
Wen Gu, Xun Wang, Ashley Solmonson, Ling Cai, Yi Xiao, Alpaslan Tasdogan, Jordan Franklin, Yuannyu Zhang, Hua Zhang, Aundrea K. Westfall, Ashley Rowe, Hetali Trivedi, Brandon Faubert, Zheng Wu, Jessica Sudderth, Lauren G. Zacharias, Bushra Afroze, Ilya Bezprozvanny, Sunil Sudarshan, Feng Cai, Samuel K. McBrayer, Thomas P. Mathews, Ralph J. DeBerardinis
Abstract
Authors
Seong-Keun Yoo, Jinha Hwang, Jung Yong Hong, Seung Tae Kim, Se Hoon Park, Joon Oh Park, Jeeyun Lee
Abstract
BACKGROUND. Immune checkpoint inhibitors (ICIs) targeting the programmed cell death-1 axis have revolutionized metastatic non–small cell lung cancer (mNSCLC) treatment. However, disease progression remains a concern, and the role of the complex tumor microenvironment (TME) in treatment failure is not fully understood. METHODS. In this biomarker study involving 103 patients with mNSCLC—including 81 patients who received ICI treatment—we evaluated the association between heterogeneous immune cell subsets and ICI efficacy through single-cell spatial profiling of pretreatment tumor tissue, using a 29-marker multiplex immunohistochemistry platform built for in-depth dissection of the TME. RESULTS. Among various types of intratumoral lymphocytes including T-helper 1 cells, regulatory T cells, and natural killer cells, only CD8+ T cells (TILs) were associated with ICI efficacy. Computational tissue segmentation underscored the importance of direct physical interactions between CD8+ TILs and cancer cells for ICI efficacy. TIL phenotyping identified CD39/CD103/Ki-67 positivity as a hallmark of exhausted yet functional tumor-reactive CD8+ TILs. Immunosuppressive tumor-associated macrophages (TAMs) and cancer-associated fibroblasts were independent unfavorable adversaries. High CD73 expression on cancer cells was suggested to confer tolerance to ICI in EGFR/ALK-oncogene+ NSCLC, potentially through M2-TAM accumulation and aberrant angiogenesis. CONCLUSION. Our study delineates the clinical relevance of heterogeneous immune cell subsets in ICI-treated mNSCLC, aiding the development of targeted therapeutic strategies. TRIAL REGISTRATION. Not applicable because this is a retrospective study. FUNDING. Osaka Cancer Society, KANAE Foundation for the Promotion of Medical Science, SGH Foundation, and YOKOYAMA Foundation for Clinical Pharmacology.
Authors
Kohsuke Isomoto, Koji Haratani, Takahiro Tsujikawa, Shuta Tomida, Yusuke Makutani, Masayuki Takeda, Kimio Yonesaka, Kaoru Tanaka, Tsutomu Iwasa, Kazuko Sakai, Kazuto Nishio, Akihiko Ito, Kazuhiko Nakagawa, Hidetoshi Hayashi
Abstract
Osteofibrous dysplasia (OFD) is a skeletal RASopathy presenting with periosteal bone lesions that may progress to fracture and delayed healing (pseudarthrosis). MET gene mutations reducing ubiquitin-mediated protein degradation via loss of the juxtamembrane domain (METΔJMD) were previously identified in OFD patients, resulting in ligand-dependent gain-of-function. The impact of METΔJMD expression on skeletal progenitor cell differentiation and the potential efficacy of targeted therapies remain unclear. We engineered MetΔJMD mice and showed that MetΔJMD expression inhibited osteogenic differentiation of skeletal progenitor cells in vitro and impaired cortical bone development and reduced bone stiffness in vivo. In contrast, conditional deletion of Met enhanced osteogenic differentiation of periosteal progenitor cells. Inhibition of MAPK signaling with MEK inhibitors restored osteogenic differentiation of mouse MetΔJMD skeletal progenitor cells and promoted activation of transcriptional signatures associated with skeletal development and osteoblast differentiation in OFD patient pseudarthrosis-derived primary cells. With this preclinical support, we treated with the MEK inhibitor mirdametinib a pediatric OFD patient suffering from a 3-year history of persistent pseudarthrosis, resulting in fracture union. Our findings demonstrate a bi-directional role for MET in regulating osteogenic differentiation of skeletal progenitor cells and a therapeutic avenue to improve clinical outcomes for this, and potential other, skeletal RASopathies.
Authors
Aysha Khalid, Kristin Denton, Nandina Paria, Ila Oxendine, Meghan Wassell, Reuel Cornelia, Sasidhar Uppuganti, Jeffry S. Nyman, G. Jayashree Jagadeesh, Carlos R. Ferreira, Simon J. Conway, Robert E. Hammer, John O. Ritter, Mylinh Nguyen, David A. Podeszwa, Laura J. Klesse, Carol A. Wise, Jonathan J. Rios
Abstract
Authors
Stephen G. Kaler
Abstract
Authors
Vishal M. Gohil, Michael J. Petris, Francesc Palau
Abstract
BACKGROUND Chronic graft-versus-host disease (cGVHD) is a major contributor to nonrelapse mortality (NRM) following hematopoietic cell transplantation (HCT). Whether machine-learning (ML) models with biomarkers improve the accuracy for predicting future cGVHD/NRM is not established.METHODS We developed BIOPREVENT (BIOmarkers PREVENTion), a ML algorithm using data from 1,310 HCT recipients, incorporating 7 plasma proteins measured at Day 90/100 post-HCT and 9 clinical variables. Patients were divided into training and validation datasets. ML models — including CoxXGBoost, Group SCAD, Adaptive Group Lasso, Random Survival Forests, and Bayesian Additive Regression Trees (BART) — were used to estimate time-varying Area Under the ROC Curve (AUCt) at Days 180, 270, 360, and 540. Deep learning models were also evaluated.RESULTS ML models with biomarkers outperformed clinical-only models for predicting cGVHD, with BART and CoxXGBoost achieving AUCt greater than 0.65 at 1 year. For NRM, models with biomarkers achieved AUCt ranging from 0.75–0.91. Deep learning did not outperform other ML approaches. BART consistently demonstrated high predictive accuracy and was selected for the final BIOPREVENT model. Calibration curves aligned with observed values. Variable importance analysis identified MMP3 and CXCL9 as key for cGVHD prediction and IL1RL1 and sCD163 for NRM. Cumulative incidences of cGVHD and NRM differed significantly based on BIOPREVENT-defined cutpoints.CONCLUSION BIOPREVENT accurately predicts individual risk of future cGVHD and NRM using biomarkers at 3 months post-HCT. A publicly available R Shiny web application supports its clinical use. Further studies are needed to explore its role in guiding preemptive therapy.TRIAL REGISTRATION BMTCTN 0201, BMTCTN 1202, and NCT02194439.FUNDING R01CA264921, U10HL069294, U24HL138660, R01HD074587, and P01HL158505.
Authors
Michael J. Martens, Debjani Dutta, Yongzi Yu, Lisa E. Rein, Jerome Ritz, Brent R. Logan, Sophie Paczesny
Abstract
BACKGROUND. Plasma heparan sulfate, a glycosaminoglycan released during endothelial glycocalyx degradation, predicts sepsis mortality. Chondroitin sulfate is a circulating glycosaminoglycan not specific to glycocalyx degradation; its relevance to sepsis is unknown. METHODS. We studied the associations of plasma chondroitin sulfate with (a) mortality in patients with sepsis-associated hypotension and (b) the relative effectiveness of a randomly-assigned liberal versus restrictive intravenous fluid resuscitation strategy. We selected 574 patients enrolled in the Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis trial using an outcome-enriched sampling strategy. We used liquid chromatography-mass spectrometry to quantify plasma chondroitin sulfate. In comparison, we measured hyaluronic acid as a glycocalyx degradation marker and IL-6 as an inflammatory biomarker. We conducted Cox proportional hazards regression analyses to examine associations of baseline biomarker concentrations with mortality and resuscitation strategy effectiveness. We used inverse probability of selection weights and generalized raking to account for the non-representative sampling design. RESULTS. Plasma chondroitin sulfate, hyaluronic acid, and IL-6 were associated with mortality within 90 days. As baseline chondroitin sulfate increased, subsequent randomization to a restrictive strategy was increasingly beneficial (p = 0.022): treatment effect hazard ratio (restrictive versus liberal) for mortality was estimated as 1.49 (95% CI 0.98–2.27), 1.30 (1.00–1.69), 1.09 (0.82–1.44), 0.88 (0.66–1.16), and 0.71 (0.52–0.97) for 10th, 25th, 50th, 75th and 90th percentiles of baseline chondroitin sulfate. CONCLUSIONS. Plasma chondroitin sulfate predicts sepsis mortality and may modify the response to a subsequent liberal vs. restrictive intravenous fluid resuscitation strategy. TRIAL. ClinicalTrials.gov NCT03434028.
Authors
Kaori Oshima, Bailu Yan, Ran Tao, Gustavo Amorim, Chiara Di Gravio, Sarah A. McMurtry, Ryan C. Burke, Yunbi Nam, Ina Nikolli, Max S. Kravitz, Daniel Stephenson, Aaron Issaian, Kirk C. Hansen, Angelo D'Alessandro, Ivor S. Douglas, Wesley H. Self, Christopher J. Lindsell, Carolyn Leroux, Angelika Ringor, Michael A. Matthay, Jonathan S. Schildcrout, Nathan I. Shapiro, Eric P. Schmidt
Abstract
Radiotherapy (RT) is a central treatment for prostate cancer (PCa), acting by inducing DNA double-strand breaks (DSBs). Tumor ability to repair these breaks limits RT efficacy, making DSB repair inhibitors potential radiosensitizers. Therefore, tumor-specific radiosensitization strategies are critically needed for PCa. Approximately 50% of PCa cases harbor the TMPRSS2-ERG gene fusion, leading to overexpression of the ERG transcription factor (ERG+). We demonstrate that ERG+ tumors shift DSB repair toward the PARP1-dependent end-joining (PARP1-EJ) pathway. Proteomic and western blot analyses revealed elevated PARP1, XRCC1, and LIG3 in ERG+ cells. PARP inhibition with olaparib increased residual γH2AX/53BP1 foci post-irradiation in ERG+ cells, indicating enhanced radiosensitization. In tissue-slice-cultures (TSCs) from 53 tumors of 40 high-risk PCa patients, olaparib selectively increased H2AX/53BP1 foci selectively in ERG+ samples. ERG+ patient-derived organoids also showed significantly delayed growth and survival when treated with olaparib plus RT compared to either treatment alone. Interestingly, ERG-negative cells within ERG+ TSCs were similarly radiosensitized by olaparib, likely through bystander effect, with residual 53BP1 foci levels comparable to ERG+ cells, confirmed by medium exchange experiments. These findings suggest that ERG expression promotes dependency on PARP1-EJ, rendering ERG+ PCa more susceptible to PARP inhibition. Combining PARP inhibitors with RT may offer a tumor-selective radiosensitization for ERG+ PCa patients.
Authors
Sabrina Köcher, Mohamed E. Elsesy, Ayham Moustafa, Wahid Mohammadi, Adriana Perugachi Heinsohn, Yamini Nagaraj, Su Jung Oh-Hohenhorst, Jan Hahn, Bente Siebels, Thomas Mair, Susanne Burdak-Rothkamm, Pierre Tennstedt, Ronald Simon, Tobias Lange, Derya Tilki, Thorsten Frenzel, Tobias Maurer, Cordula Petersen, Hartmut Schlüter, Carsten Bokemeyer, Gunhild von Amsberg, Kai Rothkamm, Wael Y. Mansour
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