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1.
Nat Commun ; 15(1): 1957, 2024 Mar 04.
Artículo en Inglés | MEDLINE | ID: mdl-38438348

RESUMEN

Almost all Glioblastoma (GBM) are either intrinsically resistant to the chemotherapeutical drug temozolomide (TMZ) or acquire therapy-induced mutations that cause chemoresistance and recurrence. The genome maintenance mechanisms responsible for GBM chemoresistance and hypermutation are unknown. We show that the E3 ubiquitin ligase RAD18 (a proximal regulator of TLS) is activated in a Mismatch repair (MMR)-dependent manner in TMZ-treated GBM cells, promoting post-replicative gap-filling and survival. An unbiased CRISPR screen provides an aerial map of RAD18-interacting DNA damage response (DDR) pathways deployed by GBM to tolerate TMZ genotoxicity. Analysis of mutation signatures from TMZ-treated GBM reveals a role for RAD18 in error-free bypass of O6mG (the most toxic TMZ-induced lesion), and error-prone bypass of other TMZ-induced lesions. Our analyses of recurrent GBM patient samples establishes a correlation between low RAD18 expression and hypermutation. Taken together we define molecular underpinnings for the hallmark tumorigenic phenotypes of TMZ-treated GBM.


Asunto(s)
Glioblastoma , Humanos , Glioblastoma/tratamiento farmacológico , Glioblastoma/genética , Síntesis Translesional de ADN , Reparación de la Incompatibilidad de ADN/genética , Resistencia a Antineoplásicos/genética , Temozolomida/farmacología , Proteínas de Unión al ADN , Ubiquitina-Proteína Ligasas/genética
2.
Res Sq ; 2023 Oct 16.
Artículo en Inglés | MEDLINE | ID: mdl-37886584

RESUMEN

Almost all Glioblastoma (GBM) are either intrinsically resistant to the chemotherapeutical drug temozolomide (TMZ) or acquire therapy-induced mutations that cause chemoresistance and recurrence. The genome maintenance mechanisms responsible for GBM chemoresistance and hypermutation are unknown. We show that the E3 ubiquitin ligase RAD18 (a proximal regulator of TLS) is activated in a Mismatch repair (MMR)-dependent manner in TMZ-treated GBM cells, promoting post-replicative gap-filling and survival. An unbiased CRISPR screen provides a new aerial map of RAD18-interacting DNA damage response (DDR) pathways deployed by GBM to tolerate TMZ genotoxicity. Analysis of mutation signatures from TMZ-treated GBM reveals a role for RAD18 in error-free bypass of O6mG (the most toxic TMZ-induced lesion), and error-prone bypass of other TMZ-induced lesions. Our analyses of recurrent GBM patient samples establishes a correlation between low RAD18 expression and hypermutation. Taken together we define novel molecular underpinnings for the hallmark tumorigenic phenotypes of TMZ-treated GBM.

3.
bioRxiv ; 2023 Oct 19.
Artículo en Inglés | MEDLINE | ID: mdl-37905107

RESUMEN

Almost all Glioblastoma (GBM) are either intrinsically resistant to the chemotherapeutical drug temozolomide (TMZ) or acquire therapy-induced mutations that cause chemoresistance and recurrence. The genome maintenance mechanisms responsible for GBM chemoresistance and hypermutation are unknown. We show that the E3 ubiquitin ligase RAD18 (a proximal regulator of TLS) is activated in a Mismatch repair (MMR)-dependent manner in TMZ-treated GBM cells, promoting post-replicative gap-filling and survival. An unbiased CRISPR screen provides a new aerial map of RAD18-interacting DNA damage response (DDR) pathways deployed by GBM to tolerate TMZ genotoxicity. Analysis of mutation signatures from TMZ-treated GBM reveals a role for RAD18 in error-free bypass of O6mG (the most toxic TMZ-induced lesion), and error-prone bypass of other TMZ-induced lesions. Our analyses of recurrent GBM patient samples establishes a correlation between low RAD18 expression and hypermutation. Taken together we define novel molecular underpinnings for the hallmark tumorigenic phenotypes of TMZ-treated GBM.

4.
Lancet ; 402(10401): 529-544, 2023 08 12.
Artículo en Inglés | MEDLINE | ID: mdl-37385280

RESUMEN

BACKGROUND: According to current consensus guidelines for type 2 diabetes management, bodyweight management is as important as attaining glycaemic targets. Retatrutide, a single peptide with agonist activity at the glucose-dependent insulinotropic polypeptide (GIP), GLP-1, and glucagon receptors, showed clinically meaningful glucose-lowering and bodyweight-lowering efficacy in a phase 1 study. We aimed to examine the efficacy and safety of retatrutide in people with type 2 diabetes across a range of doses. METHODS: In this randomised, double-blind, double-dummy, placebo-controlled and active comparator-controlled, parallel-group, phase 2 trial, participants were recruited from 42 research and health-care centres in the USA. Adults aged 18-75 years with type 2 diabetes, glycated haemoglobin (HbA1c) of 7·0-10·5% (53·0-91·3 mmol/mol), and BMI of 25-50 kg/m2 were eligible for enrolment. Eligible participants were treated with diet and exercise alone or with a stable dose of metformin (≥1000 mg once daily) for at least 3 months before the screening visit. Participants were randomly assigned (2:2:2:1:1:1:1:2) using an interactive web-response system, with stratification for baseline HbA1c and BMI, to receive once-weekly injections of placebo, 1·5 mg dulaglutide, or retatrutide maintenance doses of 0·5 mg, 4 mg (starting dose 2 mg), 4 mg (no escalation), 8 mg (starting dose 2 mg), 8 mg (starting dose 4 mg), or 12 mg (starting dose 2 mg). Participants, study site personnel, and investigators were masked to treatment allocation until after study end. The primary endpoint was change in HbA1c from baseline to 24 weeks, and secondary endpoints included change in HbA1c and bodyweight at 36 weeks. Efficacy was analysed in all randomly assigned, except inadvertently enrolled, participants, and safety was assessed in all participants who received at least one dose of study treatment. The study is registered at ClinicalTrials.gov, NCT04867785. FINDINGS: Between May 13, 2021, and June 13, 2022, 281 participants (mean age 56·2 years [SD 9·7], mean duration of diabetes 8·1 years [7·0], 156 [56%] female, and 235 [84%] White) were randomly assigned and included in the safety analysis (45 in the placebo group, 46 in the 1·5 mg dulaglutide group, and 47 in the retatrutide 0·5 mg group, 23 in the 4 mg escalation group, 24 in the 4 mg group, 26 in the 8 mg slow escalation group, 24 in the 8 mg fast escalation group, and 46 in the 12 mg escalation group). 275 participants were included in the efficacy analyses (one each in the retatrutide 0·5 mg group, 4 mg escalation group, and 8 mg slow escalation group, and three in the 12 mg escalation group were inadvertently enrolled). 237 (84%) participants completed the study and 222 (79%) completed study treatment. At 24 weeks, least-squares mean changes from baseline in HbA1c with retatrutide were -0·43% (SE 0·20; -4·68 mmol/mol [2·15]) for the 0·5 mg group, -1·39% (0·14; -15·24 mmol/mol [1·56]) for the 4 mg escalation group, -1·30% (0·22; -14·20 mmol/mol [2·44]) for the 4 mg group, -1·99% (0·15; -21·78 mmol/mol [1·60]) for the 8 mg slow escalation group, -1·88% (0·21; -20·52 mmol/mol [2·34]) for the 8 mg fast escalation group, and -2·02% (0·11; -22·07 mmol/mol [1·21]) for the 12 mg escalation group, versus -0·01% (0·21; -0·12 mmol/mol [2·27]) for the placebo group and -1·41% (0·12; -15·40 mmol/mol [1·29]) for the 1·5 mg dulaglutide group. HbA1c reductions with retatrutide were significantly greater (p<0·0001) than placebo in all but the 0·5 mg group and greater than 1·5 mg dulaglutide in the 8 mg slow escalation group (p=0·0019) and 12 mg escalation group (p=0·0002). Findings were consistent at 36 weeks. Bodyweight decreased dose dependently with retatrutide at 36 weeks by 3·19% (SE 0·61) for the 0·5 mg group, 7·92% (1·28) for the 4 mg escalation group, 10·37% (1·56) for the 4 mg group, 16·81% (1·59) for the 8 mg slow escalation group, 16·34% (1·65) for the 8 mg fast escalation group, and 16·94% (1·30) for the 12 mg escalation group, versus 3·00% (0·86) with placebo and 2·02% (0·72) with 1·5 mg dulaglutide. For retatrutide doses of 4 mg and greater, decreases in weight were significantly greater than with placebo (p=0·0017 for the 4 mg escalation group and p<0·0001 for others) and 1·5 mg dulaglutide (all p<0·0001). Mild-to-moderate gastrointestinal adverse events, including nausea, diarrhoea, vomiting, and constipation, were reported in 67 (35%) of 190 participants in the retatrutide groups (from six [13%] of 47 in the 0·5 mg group to 12 [50%] of 24 in the 8 mg fast escalation group), six (13%) of 45 participants in the placebo group, and 16 (35%) of 46 participants in the 1·5 mg dulaglutide group. There were no reports of severe hypoglycaemia and no deaths during the study. INTERPRETATION: In people with type 2 diabetes, retatrutide showed clinically meaningful improvements in glycaemic control and robust reductions in bodyweight, with a safety profile consistent with GLP-1 receptor agonists and GIP and GLP-1 receptor agonists. These phase 2 data also informed dose selection for the phase 3 programme. FUNDING: Eli Lilly and Company.


Asunto(s)
Diabetes Mellitus Tipo 2 , Adulto , Femenino , Humanos , Masculino , Persona de Mediana Edad , Glucemia , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Diabetes Mellitus Tipo 2/complicaciones , Método Doble Ciego , Glucagón/uso terapéutico , Péptido 1 Similar al Glucagón , Receptor del Péptido 1 Similar al Glucagón/uso terapéutico , Péptidos Similares al Glucagón/efectos adversos , Glucosa , Hipoglucemiantes/efectos adversos , Receptores de Glucagón/uso terapéutico , Resultado del Tratamiento , Adolescente , Adulto Joven , Anciano
5.
Stat Interface ; 16(4): 505-515, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38344146

RESUMEN

In this article, we propose a general framework to learn optimal treatment rules for type 2 diabetes (T2D) patients using electronic health records (EHRs). We first propose a joint modeling approach to characterize patient's pretreatment conditions using longitudinal markers from EHRs. The estimation accounts for informative measurement times using inverse-intensity weighting methods. The predicted latent processes in the joint model are used to divide patients into a finite of subgroups and, within each group, patients share similar health profiles in EHRs. Within each patient group, we estimate optimal individualized treatment rules by extending a matched learning method to handle multicategory treatments using a one-versus-one approach. Each matched learning for two treatments is implemented by a weighted support vector machine with matched pairs of patients. We apply our method to estimate optimal treatment rules for T2D patients in a large sample of EHRs from the Ohio State University Wexner Medical Center. We demonstrate the utility of our method to select the optimal treatments from four classes of drugs and achieve a better control of glycated hemoglobin than any one-size-fits-all rules.

6.
Stat Med ; 40(8): 1930-1946, 2021 04 15.
Artículo en Inglés | MEDLINE | ID: mdl-33586187

RESUMEN

Electronic health records (EHRs) from type 2 diabetes (T2D) patients consist of longitudinally and sparsely measured health markers at clinical encounters. Our goal is to use such data to learn latent patterns that can inform patient's health status related to T2D while accounting for challenges in retrospectively collected EHRs. To handle challenges such as correlated longitudinal measurements, irregular and informative encounter times, and mixed marker types, we propose multivariate generalized linear models to learn latent patient subgroups. In our model, covariate effects were time-dependent and latent Gaussian processes were introduced to model between-marker correlations over time. Using inferred latent processes, we integrated the irregularly measured health markers of mixed types into composite scores and applied hierarchical clustering to learn latent subgroup structures among T2D patients. Application to an EHR dataset of T2D patients showed different trends of age, sex, and race effects on hypertension/high blood pressure, total cholesterol, glycated hemoglobin, high-density lipoprotein, and medications. The associations among these markers varied over time during the study window. Clustering results revealed four subgroups, each with distinct health status. The same patterns were further confirmed using new EHR records of the same cohort. We developed a novel latent model to integrate longitudinal health markers in EHRs and characterize patient latent heterogeneities. Analysis indicated that there were distinct subgroups of T2D patients, suggesting that effective healthcare managements for these patients should be performed separately for each subgroup.


Asunto(s)
Diabetes Mellitus Tipo 2 , Registros Electrónicos de Salud , Estudios de Cohortes , Hemoglobina Glucada/análisis , Humanos , Estudios Retrospectivos
7.
NAR Cancer ; 3(1): zcaa037, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33447826

RESUMEN

The E3 ubiquitin ligase Rad18 promotes a damage-tolerant and error-prone mode of DNA replication termed trans-lesion synthesis that is pathologically activated in cancer. However, the impact of vertebrate Rad18 on cancer genomes is not known. To determine how Rad18 affects mutagenesis in vivo, we have developed and implemented a novel computational pipeline to analyze genomes of carcinogen (7, 12-Dimethylbenz[a]anthracene, DMBA)-induced skin tumors from Rad18+/+ and Rad18- / - mice. We show that Rad18 mediates specific mutational signatures characterized by high levels of A(T)>T(A) single nucleotide variations (SNVs). In Rad18- /- tumors, an alternative mutation pattern arises, which is characterized by increased numbers of deletions >4 bp. Comparison with annotated human mutational signatures shows that COSMIC signature 22 predominates in Rad18+/+ tumors whereas Rad18- / - tumors are characterized by increased contribution of COSMIC signature 3 (a hallmark of BRCA-mutant tumors). Analysis of The Cancer Genome Atlas shows that RAD18 expression is strongly associated with high SNV burdens, suggesting RAD18 also promotes mutagenesis in human cancers. Taken together, our results show Rad18 promotes mutagenesis in vivo, modulates DNA repair pathway choice in neoplastic cells, and mediates specific mutational signatures that are present in human tumors.

8.
J Clin Invest ; 130(11): 5893-5908, 2020 11 02.
Artículo en Inglés | MEDLINE | ID: mdl-32730228

RESUMEN

As a hallmark of immunological aging, low-grade, chronic inflammation with accumulation of effector memory T cells contributes to increased susceptibility to many aging-related diseases. While the proinflammatory state of aged T cells indicates a dysregulation of immune homeostasis, whether and how aging drives regulatory T cell (Treg) aging and alters Treg function are not fully understood owing to a lack of specific aging markers. Here, by a combination of cellular, molecular, and bioinformatic approaches, we discovered that Tregs senesce more severely than conventional T (Tconv) cells during aging. We found that Tregs from aged mice were less efficient than young Tregs in suppressing Tconv cell function in an inflammatory bowel disease model and in preventing Tconv cell aging in an irradiation-induced aging model. Furthermore, we revealed that DDB1- and CUL4-associated factor 1 (DCAF1) was downregulated in aged Tregs and was critical to restrain Treg aging via reactive oxygen species (ROS) regulated by glutathione-S-transferase P (GSTP1). Importantly, interfering with GSTP1 and ROS pathways reinvigorated the proliferation and function of aged Tregs. Therefore, our studies uncover an important role of the DCAF1/GSTP1/ROS axis in Treg senescence, which leads to uncontrolled inflammation and immunological aging.


Asunto(s)
Envejecimiento/inmunología , Senescencia Celular/inmunología , Proteínas Serina-Treonina Quinasas/inmunología , Especies Reactivas de Oxígeno/inmunología , Transducción de Señal/inmunología , Linfocitos T Reguladores/inmunología , Envejecimiento/genética , Envejecimiento/patología , Animales , Senescencia Celular/genética , Modelos Animales de Enfermedad , Regulación hacia Abajo/genética , Regulación hacia Abajo/inmunología , Gutatión-S-Transferasa pi/genética , Gutatión-S-Transferasa pi/inmunología , Enfermedades Inflamatorias del Intestino/genética , Enfermedades Inflamatorias del Intestino/inmunología , Enfermedades Inflamatorias del Intestino/patología , Ratones , Ratones Noqueados , Proteínas Serina-Treonina Quinasas/genética , Transducción de Señal/genética , Linfocitos T Reguladores/patología
9.
Immunity ; 49(5): 886-898.e5, 2018 11 20.
Artículo en Inglés | MEDLINE | ID: mdl-30446383

RESUMEN

Pathogenic Th17 (pTh17) cells drive inflammation and immune-pathology, but whether pTh17 cells are a Th17 cell subset whose generation is under specific molecular control remains unaddressed. We found that Ras p21 protein activator 3 (RASA3) was highly expressed by pTh17 cells relative to non-pTh17 cells and was required specifically for pTh17 generation in vitro and in vivo. Mice conditionally deficient for Rasa3 in T cells showed less pathology during experimental autoimmune encephalomyelitis. Rasa3-deficient T cells acquired a Th2 cell-biased program that dominantly trans-suppressed pTh17 cell generation via interleukin 4 production. The Th2 cell bias of Rasa3-deficient T cells was due to aberrantly elevated transcription factor IRF4 expression. RASA3 promoted proteasome-mediated IRF4 protein degradation by facilitating interaction of IRF4 with E3-ubiquitin ligase Cbl-b. Therefore, a RASA3-IRF4-Cbl-b pathway specifically directs pTh17 cell generation by balancing reciprocal Th17-Th2 cell programs. These findings indicate that a distinct molecular program directs pTh17 cell generation and reveals targets for treating pTh17 cell-related pathology and diseases.


Asunto(s)
Diferenciación Celular/genética , Proteínas Activadoras de GTPasa/genética , Células Th17/citología , Células Th17/metabolismo , Células Th2/citología , Células Th2/metabolismo , Animales , Autoinmunidad , Biomarcadores , Encefalomielitis Autoinmune Experimental/etiología , Encefalomielitis Autoinmune Experimental/metabolismo , Encefalomielitis Autoinmune Experimental/patología , Proteínas Activadoras de GTPasa/metabolismo , Expresión Génica , Inmunofenotipificación , Factores Reguladores del Interferón/genética , Factores Reguladores del Interferón/metabolismo , Ratones , Proteolisis , ARN Mensajero , Células Th17/inmunología , Células Th2/inmunología
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