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1.
Nat Cancer ; 2024 Jul 03.
Artículo en Inglés | MEDLINE | ID: mdl-38961276

RESUMEN

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts.

2.
Nat Commun ; 15(1): 5873, 2024 Jul 12.
Artículo en Inglés | MEDLINE | ID: mdl-38997291

RESUMEN

Low response rate, treatment relapse, and resistance remain key challenges for cancer treatment with immune checkpoint blockade (ICB). Here we report that loss of specific tumor suppressors (TS) induces an inflammatory response and promotes an immune suppressive tumor microenvironment. Importantly, low expression of these TSs is associated with a higher expression of immune checkpoint inhibitory mediators. Here we identify, by using in vivo CRISPR/Cas9 based loss-of-function screening, that NF1, TSC1, and TGF-ß RII as TSs regulating immune composition. Loss of each of these three TSs leads to alterations in chromatin accessibility and enhances IL6-JAK3-STAT3/6 inflammatory pathways. This results in an immune suppressive landscape, characterized by increased numbers of LAG3+ CD8 and CD4 T cells. ICB targeting LAG3 and PD-L1 simultaneously inhibits metastatic progression in preclinical triple negative breast cancer (TNBC) mouse models of NF1-, TSC1- or TGF-ß RII- deficient tumors. Our study thus reveals a role of TSs in regulating metastasis via non-cell-autonomous modulation of the immune compartment and provides proof-of-principle for ICB targeting LAG3 for patients with NF1-, TSC1- or TGF-ß RII-inactivated cancers.


Asunto(s)
Antígeno B7-H1 , Inhibidores de Puntos de Control Inmunológico , Proteína del Gen 3 de Activación de Linfocitos , Neoplasias de la Mama Triple Negativas , Proteína 1 del Complejo de la Esclerosis Tuberosa , Microambiente Tumoral , Microambiente Tumoral/inmunología , Animales , Ratones , Femenino , Humanos , Neoplasias de la Mama Triple Negativas/inmunología , Neoplasias de la Mama Triple Negativas/patología , Neoplasias de la Mama Triple Negativas/genética , Inhibidores de Puntos de Control Inmunológico/farmacología , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Proteína 1 del Complejo de la Esclerosis Tuberosa/genética , Proteína 1 del Complejo de la Esclerosis Tuberosa/metabolismo , Antígeno B7-H1/metabolismo , Antígeno B7-H1/genética , Neurofibromina 1/genética , Neurofibromina 1/metabolismo , Línea Celular Tumoral , Linfocitos T CD8-positivos/inmunología , Inflamación/inmunología , Linfocitos T CD4-Positivos/inmunología , Regulación Neoplásica de la Expresión Génica , Sistemas CRISPR-Cas
3.
Sci Adv ; 10(27): eadj7402, 2024 Jul 05.
Artículo en Inglés | MEDLINE | ID: mdl-38959321

RESUMEN

The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like IL1Β and CXCL8, while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response.


Asunto(s)
Bacterias , RNA-Seq , Análisis de la Célula Individual , Humanos , Análisis de la Célula Individual/métodos , RNA-Seq/métodos , Bacterias/genética , Microambiente Tumoral , Células Mieloides/metabolismo , Células Mieloides/microbiología , Análisis de Secuencia de ARN/métodos , Neoplasias Colorrectales/microbiología , Neoplasias Colorrectales/genética , Biología Computacional/métodos , ARN Bacteriano/genética , Neoplasias Esofágicas/microbiología , Neoplasias Esofágicas/genética , Microbiota , Análisis de Expresión Génica de una Sola Célula
6.
Nat Cancer ; 2024 Jun 03.
Artículo en Inglés | MEDLINE | ID: mdl-38831056

RESUMEN

Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features. We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model. LORIS outperforms previous signatures in predicting ICB response and identifying responsive patients even with low tumor mutational burden or programmed cell death 1 ligand 1 expression. LORIS consistently predicts patient objective response and short-term and long-term survival across most cancer types. Moreover, LORIS showcases a near-monotonic relationship with ICB response probability and patient survival, enabling precise patient stratification. As an accurate, interpretable method using a few readily measurable features, LORIS may help improve clinical decision-making in precision medicine to maximize patient benefit. LORIS is available as an online tool at https://loris.ccr.cancer.gov/ .

7.
iScience ; 27(6): 109926, 2024 Jun 21.
Artículo en Inglés | MEDLINE | ID: mdl-38832027

RESUMEN

Cytotoxic T lymphocyte (CTL) and terminal exhausted T lymphocyte (ETL) activities crucially influence immune checkpoint inhibitor (ICI) response. Despite this, the efficacy of ETL and CTL transcriptomic signatures for response prediction remains limited. Investigating this across the TCGA and publicly available single-cell cohorts, we find a strong positive correlation between ETL and CTL expression signatures in most cancers. We hence posited that their limited predictability arises due to their mutually canceling effects on ICI response. Thus, we developed DETACH, a computational method to identify a gene set whose expression pinpoints to a subset of melanoma patients where the CTL and ETL correlation is low. DETACH enhances CTL's prediction accuracy, outperforming existing signatures. DETACH signature genes activity also demonstrates a positive correlation with lymphocyte infiltration and the prevalence of reactive T cells in the tumor microenvironment (TME), advancing our understanding of the CTL cell state within the TME.

8.
Nat Metab ; 2024 Jun 10.
Artículo en Inglés | MEDLINE | ID: mdl-38858597

RESUMEN

Downregulation of the urea cycle enzyme argininosuccinate synthase (ASS1) in multiple tumors is associated with a poor prognosis partly because of the metabolic diversion of cytosolic aspartate for pyrimidine synthesis, supporting proliferation and mutagenesis owing to nucleotide imbalance. Here, we find that prolonged loss of ASS1 promotes DNA damage in colon cancer cells and fibroblasts from subjects with citrullinemia type I. Following acute induction of DNA damage with doxorubicin, ASS1 expression is elevated in the cytosol and the nucleus with at least a partial dependency on p53; ASS1 metabolically restrains cell cycle progression in the cytosol by restricting nucleotide synthesis. In the nucleus, ASS1 and ASL generate fumarate for the succination of SMARCC1, destabilizing the chromatin-remodeling complex SMARCC1-SNF5 to decrease gene transcription, specifically in a subset of the p53-regulated cell cycle genes. Thus, following DNA damage, ASS1 is part of the p53 network that pauses cell cycle progression, enabling genome maintenance and survival. Loss of ASS1 contributes to DNA damage and promotes cell cycle progression, likely contributing to cancer mutagenesis and, hence, adaptability potential.

9.
Nat Med ; 2024 May 17.
Artículo en Inglés | MEDLINE | ID: mdl-38760587

RESUMEN

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven means to enhance diagnostic accuracy but are also time consuming and not widely available. Here, to address these limitations, we developed Deep lEarning from histoPathoLOgy and methYlation (DEPLOY), a deep learning model that classifies CNS tumors to ten major categories from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from slide images ('direct model'), the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification ('indirect model'), and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicts beta values from histopathology images. Second, using a ten-class model trained on an internal dataset of 1,796 patients, we predict the tumor categories in three independent external test datasets including 2,156 patients, achieving an overall accuracy of 95% and balanced accuracy of 91% on samples that are predicted with high confidence. These results showcase the potential future use of DEPLOY to assist pathologists in diagnosing CNS tumors within a clinically relevant short time frame.

10.
Nat Cancer ; 5(6): 938-952, 2024 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-38637658

RESUMEN

Tailoring optimal treatment for individual cancer patients remains a significant challenge. To address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression-Based Planning for Treatments In ONcology), a precision oncology computational pipeline. Our approach uses publicly available matched bulk and single-cell (sc) expression profiles from large-scale cell-line drug screens. These profiles help build treatment response models based on patients' sc-tumor transcriptomics. PERCEPTION demonstrates success in predicting responses to targeted therapies in cultured and patient-tumor-derived primary cells, as well as in two clinical trials for multiple myeloma and breast cancer. It also captures the resistance development in patients with lung cancer treated with tyrosine kinase inhibitors. PERCEPTION outperforms published state-of-the-art sc-based and bulk-based predictors in all clinical cohorts. PERCEPTION is accessible at https://github.com/ruppinlab/PERCEPTION . Our work, showcasing patient stratification using sc-expression profiles of their tumors, will encourage the adoption of sc-omics profiling in clinical settings, enhancing precision oncology tools based on sc-omics.


Asunto(s)
Resistencia a Antineoplásicos , Medicina de Precisión , Análisis de la Célula Individual , Transcriptoma , Humanos , Análisis de la Célula Individual/métodos , Medicina de Precisión/métodos , Resistencia a Antineoplásicos/genética , Neoplasias/genética , Neoplasias/tratamiento farmacológico , Perfilación de la Expresión Génica/métodos , Femenino , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/tratamiento farmacológico , Regulación Neoplásica de la Expresión Génica , Línea Celular Tumoral , Biología Computacional/métodos
11.
Adv Sci (Weinh) ; 11(17): e2307263, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38441406

RESUMEN

Ferroptosis and apoptosis are key cell-death pathways implicated in several human diseases including cancer. Ferroptosis is driven by iron-dependent lipid peroxidation and currently has no characteristic biomarkers or gene signatures. Here a continuous phenotypic gradient between ferroptosis and apoptosis coupled to transcriptomic and metabolomic landscapes is established. The gradual ferroptosis-to-apoptosis transcriptomic landscape is used to generate a unique, unbiased transcriptomic predictor, the Gradient Gene Set (GGS), which classified ferroptosis and apoptosis with high accuracy. Further GGS optimization using multiple ferroptotic and apoptotic datasets revealed highly specific ferroptosis biomarkers, which are robustly validated in vitro and in vivo. A subset of the GGS is associated with poor prognosis in breast cancer patients and PDXs and contains different ferroptosis repressors. Depletion of one representative, PDGFA-assaociated protein 1(PDAP1), is found to suppress basal-like breast tumor growth in a mouse model. Omics and mechanistic studies revealed that ferroptosis is associated with enhanced lysosomal function, glutaminolysis, and the tricarboxylic acid (TCA) cycle, while its transition into apoptosis is attributed to enhanced endoplasmic reticulum(ER)-stress and phosphatidylethanolamine (PE)-to-phosphatidylcholine (PC) metabolic shift. Collectively, this study highlights molecular mechanisms underlying ferroptosis execution, identified a highly predictive ferroptosis gene signature with prognostic value, ferroptosis versus apoptosis biomarkers, and ferroptosis repressors for breast cancer therapy.


Asunto(s)
Apoptosis , Biomarcadores de Tumor , Ferroptosis , Ferroptosis/genética , Humanos , Animales , Ratones , Apoptosis/genética , Femenino , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Neoplasias de la Mama/genética , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Línea Celular Tumoral , Modelos Animales de Enfermedad , Biomarcadores/metabolismo
12.
Cancer Res ; 84(10): 1719-1732, 2024 May 15.
Artículo en Inglés | MEDLINE | ID: mdl-38451249

RESUMEN

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predicted consensus molecular subtypes in patients with metastatic colorectal cancer. Analysis of plasma evRNA also enabled monitoring of changes in transcriptomic subtype under treatment selection pressure and identification of molecular pathways associated with recurrence. This approach also revealed expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of using transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to the identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. SIGNIFICANCE: The development of an approach to interrogate molecular subtypes, cancer-associated pathways, and differentially expressed genes through RNA sequencing of plasma extracellular vesicles lays the foundation for liquid biopsy-based longitudinal monitoring of patient tumor transcriptomes.


Asunto(s)
Biomarcadores de Tumor , Vesículas Extracelulares , Perfilación de la Expresión Génica , Transcriptoma , Humanos , Vesículas Extracelulares/genética , Vesículas Extracelulares/metabolismo , Perfilación de la Expresión Génica/métodos , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/sangre , Biopsia Líquida/métodos , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/sangre , Neoplasias Colorrectales/patología , Regulación Neoplásica de la Expresión Génica , Neoplasias/genética , Neoplasias/sangre , Neoplasias/patología
13.
Nat Commun ; 15(1): 2608, 2024 Mar 23.
Artículo en Inglés | MEDLINE | ID: mdl-38521835

RESUMEN

Identifying sex differences in outcomes and toxicity between males and females in oncology clinical trials is important and has also been mandated by National Institutes of Health policies. Here we analyze the Trialtrove database, finding that, strikingly, only 472/89,221 oncology clinical trials (0.5%) had curated post-treatment sex comparisons. Among 288 trials with comparisons of survival, outcome, or response, 16% report males having statistically significant better survival outcome or response, while 42% reported significantly better survival outcome or response for females. The strongest differences are in trials of EGFR inhibitors in lung cancer and rituximab in non-Hodgkin's lymphoma (both favoring females). Among 44 trials with side effect comparisons, more trials report significantly lesser side effects in males (N = 22) than in females (N = 13). Thus, while statistical comparisons between sexes in oncology trials are rarely reported, important differences in outcome and toxicity exist. These considerable outcome and toxicity differences highlight the need for reporting sex differences more thoroughly going forward.


Asunto(s)
Neoplasias Pulmonares , Linfoma no Hodgkin , Estados Unidos , Femenino , Humanos , Masculino , Rituximab/uso terapéutico , Linfoma no Hodgkin/tratamiento farmacológico , Neoplasias Pulmonares/tratamiento farmacológico , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico
14.
NPJ Genom Med ; 9(1): 16, 2024 Feb 26.
Artículo en Inglés | MEDLINE | ID: mdl-38409211

RESUMEN

The majority of human genetic diseases are caused by single nucleotide variants (SNVs) in the genome sequence. Excitingly, new genomic techniques known as base editing have opened efficient pathways to correct erroneous nucleotides. Due to reliance on deaminases, which have the capability to convert A to I(G) and C to U, the direct applicability of base editing might seem constrained in terms of the range of mutations that can be reverted. In this evaluation, we assess the potential of DNA and RNA base editing methods for treating human genetic diseases. Our findings indicate that 62% of pathogenic SNVs found within genes can be amended by base editing; 30% are G>A and T>C SNVs that can be corrected by DNA base editing, and most of them by RNA base editing as well, and 29% are C>T and A>G SNVs that can be corrected by DNA base editing directed to the complementary strand. For each, we also present several factors that affect applicability such as bystander and off-target occurrences. For cases where editing the mismatched nucleotide is not feasible, we introduce an approach that calculates the optimal substitution of the deleterious amino acid with a new amino acid, further expanding the scope of applicability. As personalized therapy is rapidly advancing, our demonstration that most SNVs can be treated by base editing is of high importance. The data provided will serve as a comprehensive resource for those seeking to design therapeutic base editors and study their potential in curing genetic diseases.

15.
bioRxiv ; 2024 Jan 22.
Artículo en Inglés | MEDLINE | ID: mdl-38313282

RESUMEN

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers, a phenomenon that has been investigated without resolution since the late 1980s. Expanding beyond previous gene-centric studies, we investigate the co-occurrence in a genome-wide manner taking an evolutionary perspective. First, by mining large tumor aneuploidy data, we predict that the more likely order is 10 loss followed by 7 gain. Second, by analyzing extensive genomic and transcriptomic data from both patients and cell lines, we find that this co-occurrence can be explained by functional rescue interactions that are highly enriched on 7, which can possibly compensate for any detrimental consequences arising from the loss of 10. Finally, by analyzing transcriptomic data from normal, non-cancerous, human brain tissues, we provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

16.
Med ; 5(1): 73-89.e9, 2024 Jan 12.
Artículo en Inglés | MEDLINE | ID: mdl-38218178

RESUMEN

BACKGROUND: Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Because more than 25 years have passed since SL was proposed as a promising way to selectively target cancer vulnerabilities, it is timely to comprehensively assess its impact so far and discuss its future. METHODS: We systematically analyzed the literature and clinical trial data from the PubMed and Trialtrove databases to portray the preclinical and clinical landscape of SL oncology. FINDINGS: We identified 235 preclinically validated SL pairs and found 1,207 pertinent clinical trials, and the number keeps increasing over time. About one-third of these SL clinical trials go beyond the typically studied DNA damage response (DDR) pathway, testifying to the recently broadening scope of SL applications in clinical oncology. We find that SL oncology trials have a greater success rate than non-SL-based trials. However, about 75% of the preclinically validated SL interactions have not yet been tested in clinical trials. CONCLUSIONS: Dissecting the recent efforts harnessing SL to identify predictive biomarkers, novel therapeutic targets, and effective combination therapy, our systematic analysis reinforces the hope that SL may serve as a key driver of precision oncology going forward. FUNDING: Funded by the Samsung Research Funding & Incubation Center of Samsung Electronics, the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Republic of Korea government (MSIT), the Kwanjeong Educational Foundation, the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), and Center for Cancer Research (CCR).


Asunto(s)
Neoplasias , Humanos , Oncología Médica , Neoplasias/genética , Neoplasias/terapia , Medicina de Precisión , República de Corea , Mutaciones Letales Sintéticas/genética , Estados Unidos , Ensayos Clínicos como Asunto
17.
Blood ; 143(8): 697-712, 2024 Feb 22.
Artículo en Inglés | MEDLINE | ID: mdl-38048593

RESUMEN

ABSTRACT: Aberrant expression of stem cell-associated genes is a common feature in acute myeloid leukemia (AML) and is linked to leukemic self-renewal and therapy resistance. Using AF10-rearranged leukemia as a prototypical example of the recurrently activated "stemness" network in AML, we screened for chromatin regulators that sustain its expression. We deployed a CRISPR-Cas9 screen with a bespoke domain-focused library and identified several novel chromatin-modifying complexes as regulators of the TALE domain transcription factor MEIS1, a key leukemia stem cell (LSC)-associated gene. CRISPR droplet sequencing revealed that many of these MEIS1 regulators coordinately controlled the transcription of several AML oncogenes. In particular, we identified a novel role for the Tudor-domain-containing chromatin reader protein SGF29 in the transcription of AML oncogenes. Furthermore, SGF29 deletion impaired leukemogenesis in models representative of multiple AML subtypes in multiple AML subtype models. Our studies reveal a novel role for SGF29 as a nononcogenic dependency in AML and identify the SGF29 Tudor domain as an attractive target for drug discovery.


Asunto(s)
Proteínas de Homeodominio , Leucemia Mieloide Aguda , Humanos , Proteínas de Homeodominio/genética , Cromatina/genética , Factores de Transcripción/genética , Proteína 1 del Sitio de Integración Viral Ecotrópica Mieloide/genética , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/metabolismo , Carcinogénesis
18.
bioRxiv ; 2023 Nov 02.
Artículo en Inglés | MEDLINE | ID: mdl-38076973

RESUMEN

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to target tissues is challenging. To address this, we assessed whether primary and metastatic tumors resemble their tissue of origin or target tissue in terms of gene expression. We analyzed gene expression profiles from various cancer types, including single-cell and bulk RNA-seq data, in both paired and unpaired primary and metastatic patient cohorts. We quantified the transcriptomic distances between tumor samples and their normal tissues, revealing that primary tumors are more similar to their tissue of origin, while metastases shift towards the target tissue. Pathway-level analysis highlighted critical transcriptomic changes during metastasis. Notably, primary cancers exhibited higher activity in cancer hallmarks, including Activating Invasion and Metastasis , compared to metastatic cancers. This comprehensive landscape analysis provides insight into how cancer tumors adapt to their metastatic environments, providing a transcriptome-wide view of the processes involved.

19.
bioRxiv ; 2023 Nov 29.
Artículo en Inglés | MEDLINE | ID: mdl-38077050

RESUMEN

Decreased intra-tumor heterogeneity (ITH) correlates with increased patient survival and immunotherapy response. However, even highly homogenous tumors may display variability in their aggressiveness, and how immunologic-factors impinge on their aggressiveness remains understudied. Here we studied the mechanisms responsible for the immune-escape of murine tumors with low ITH. We compared the temporal growth of homogeneous, genetically-similar single-cell clones that are rejected vs. those that are not-rejected after transplantation in-vivo using single-cell RNA sequencing and immunophenotyping. Non-rejected clones showed high infiltration of tumor-associated-macrophages (TAMs), lower T-cell infiltration, and increased T-cell exhaustion compared to rejected clones. Comparative analysis of rejection-associated gene expression programs, combined with in-vivo CRISPR knockout screens of candidate mediators, identified Mif (macrophage migration inhibitory factor) as a regulator of immune rejection. Mif knockout led to smaller tumors and reversed non-rejection-associated immune composition, particularly, leading to the reduction of immunosuppressive macrophage infiltration. Finally, we validated these results in melanoma patient data.

20.
NAR Genom Bioinform ; 5(4): lqad092, 2023 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-37859800

RESUMEN

Given the current status of coronavirus disease 2019 (COVID-19) as a global pandemic, it is of high priority to gain a deeper understanding of the disease's development and how the virus impacts its host. Adenosine (A)-to-Inosine (I) RNA editing is a post-transcriptional modification, catalyzed by the ADAR family of enzymes, that can be considered part of the inherent cellular defense mechanism as it affects the innate immune response in a complex manner. It was previously reported that various viruses could interact with the host's ADAR enzymes, resulting in epigenetic changes both to the virus and the host. Here, we analyze RNA-seq of nasopharyngeal swab specimens as well as whole-blood samples of COVID-19 infected individuals and show a significant elevation in the global RNA editing activity in COVID-19 compared to healthy controls. We also detect specific coding sites that exhibit higher editing activity. We further show that the increment in editing activity during the disease is temporary and returns to baseline shortly after the symptomatic period. These significant epigenetic changes may contribute to the immune system response and affect adverse outcomes seen in post-viral cases.

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