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1.
Nat Commun ; 12(1): 5444, 2021 09 14.
Artigo em Inglês | MEDLINE | ID: mdl-34521850

RESUMO

Kawasaki disease (KD) is the most common cause of acquired heart disease in children in developed countries. Although functional and phenotypic changes of immune cells have been reported, a global understanding of immune responses underlying acute KD is unclear. Here, using single-cell RNA sequencing, we profile peripheral blood mononuclear cells from seven patients with acute KD before and after intravenous immunoglobulin therapy and from three age-matched healthy controls. The most differentially expressed genes are identified in monocytes, with high expression of pro-inflammatory mediators, immunoglobulin receptors and low expression of MHC class II genes in acute KD. Single-cell RNA sequencing and flow cytometry analyses, of cells from an additional 16 KD patients, show that although the percentage of total B cells is substantially decreased after therapy, the percentage of plasma cells among the B cells is significantly increased. The percentage of CD8+ T cells is decreased in acute KD, notably effector memory CD8+ T cells compared with healthy controls. Oligoclonal expansions of both B cell receptors and T cell receptors are observed after therapy. We identify biological processes potentially underlying the changes of each cell type. The single-cell landscape of both innate and adaptive immune responses provides insights into pathogenesis and therapy of KD.


Assuntos
Linfócitos B/imunologia , Linfócitos T CD8-Positivos/imunologia , Monócitos/imunologia , Síndrome de Linfonodos Mucocutâneos/genética , Plasmócitos/imunologia , Doença Aguda , Imunidade Adaptativa/efeitos dos fármacos , Linfócitos B/efeitos dos fármacos , Linfócitos B/patologia , Linfócitos T CD8-Positivos/efeitos dos fármacos , Linfócitos T CD8-Positivos/patologia , Estudos de Casos e Controles , Proliferação de Células , Criança , Pré-Escolar , Células Clonais , Feminino , Expressão Gênica , Humanos , Imunidade Inata/efeitos dos fármacos , Imunoglobulinas Intravenosas/uso terapêutico , Imunofenotipagem , Masculino , Monócitos/efeitos dos fármacos , Monócitos/patologia , Síndrome de Linfonodos Mucocutâneos/tratamento farmacológico , Síndrome de Linfonodos Mucocutâneos/imunologia , Síndrome de Linfonodos Mucocutâneos/patologia , Plasmócitos/efeitos dos fármacos , Plasmócitos/patologia , Receptores de Antígenos de Linfócitos B/genética , Receptores de Antígenos de Linfócitos B/imunologia , Receptores de Antígenos de Linfócitos T/genética , Receptores de Antígenos de Linfócitos T/imunologia , Análise de Sequência de RNA , Análise de Célula Única
2.
Nat Commun ; 12(1): 4902, 2021 08 12.
Artigo em Inglês | MEDLINE | ID: mdl-34385461

RESUMO

Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the sequence context predictable via machine-learning methods. By changing the species origin and relative position of uracil-DNA glycosylase and deaminase, together with codon optimization, we obtain optimized C-to-G BEs (OPTI-CGBEs) for efficient C-to-G transversion. The motif preference of OPTI-CGBEs for editing 100 endogenous sites is determined in HEK293T cells. Using a sgRNA library comprising 41,388 sequences, we develop a deep-learning model that accurately predicts the OPTI-CGBE editing outcome for targeted sites with specific sequence context. These OPTI-CGBEs are further shown to be capable of efficient base editing in mouse embryos for generating Tyr-edited offspring. Thus, these engineered CGBEs are useful for efficient and precise base editing, with outcome predictable based on sequence context of targeted sites.


Assuntos
Sistemas CRISPR-Cas , Citidina Desaminase/metabolismo , Edição de Genes/métodos , Aprendizado de Máquina , Uracila-DNA Glicosidase/metabolismo , Animais , Sequência de Bases , Sítios de Ligação/genética , Caenorhabditis elegans/genética , Códon/genética , Citidina Desaminase/genética , Escherichia coli/genética , Feminino , Biblioteca Gênica , Células HEK293 , Humanos , Camundongos , Reprodutibilidade dos Testes , Uracila-DNA Glicosidase/genética
3.
J Leukoc Biol ; 110(2): 257-270, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34075637

RESUMO

Immune cells such as T cells, macrophages, dendritic cells, and other immunoregulatory cells undergo metabolic reprogramming in cancer and inflammation-derived microenvironment to meet specific physiologic and functional demands. Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature myeloid cells that are characterized by immunosuppressive activity, which plays a key role in host immune homeostasis. In this review, we have discussed the core metabolic pathways, including glycolysis, lipid and fatty acid biosynthesis, and amino acid metabolism in the MDSCs under various pathologic situations. Metabolic reprogramming is a determinant of the phenotype and functions of MDSCs, and is therefore a novel therapeutic possibility in various diseases.


Assuntos
Metabolismo Energético , Imunomodulação , Redes e Vias Metabólicas , Células Supressoras Mieloides/imunologia , Células Supressoras Mieloides/metabolismo , Adenosina/metabolismo , Aminoácidos/metabolismo , Biomarcadores , Microambiente Celular/imunologia , Gerenciamento Clínico , Suscetibilidade a Doenças , Espaço Extracelular/metabolismo , Glucose/metabolismo , Homeostase , Humanos , Metabolismo dos Lipídeos , Terapia de Alvo Molecular , Células Supressoras Mieloides/efeitos dos fármacos
4.
J Mol Cell Biol ; 2021 Jun 07.
Artigo em Inglês | MEDLINE | ID: mdl-34097054

RESUMO

Tumor development is a process involving loss of the differentiation phenotype and acquisition of stem-like characteristics, which is driven by intracellular rewiring of signaling network. The measurement of network reprogramming and disorder would be challenging due to the complexity and heterogeneity of tumors. Here, we proposed signaling entropy to assess the degree of tumor network disorder. We calculated signaling entropy for 33 tumor types in The Cancer Genome Atlas database based on transcriptomic and proteomic data. The signaling entropy of tumors was significantly higher than that of normal samples and was highly correlated with cell stemness, cancer type, tumor grade, and metastasis. We further demonstrated the sensitivity and accuracy of using local signaling entropy in prognosis prediction and drug response evaluation. Overall, signaling entropy could reveal cancer network disorders related to tumor malignant potency, clinical prognosis, and drug response.

5.
Genomics ; 113(5): 3216-3223, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34051323

RESUMO

The European rabbit (Oryctolagus cuniculus) is important as a biomedical model given its unique features in immunity and metabolism. The current reference genome OryCun2.0 established with whole-genome shotgun sequencing was quite fragmented and had not been updated for ten years. In this work, we provided a new rabbit genome assembly UM_NZW_1.0 to improve OryCun2.0 by leveraging the contig lengths based on long-read sequencing and a wealth of available Illumina paired-end sequence data. UM_NZW_1.0 showed a remarkable increase of continuity compared with OryCun2.0, with 5 times longer contig N50 and approximately 75% gaps closed. Many of the closed gaps were overlapped with protein-coding genes or transcriptional features, resulting in an enhancement of gene annotations. In particular, UM_NZW_1.0 presented a more complete landscape of the MHC region and the IGH locus, therefore provided a valuable resource for future researches on rabbits.

6.
J Genet Genomics ; 48(7): 540-551, 2021 07 20.
Artigo em Inglês | MEDLINE | ID: mdl-34023295

RESUMO

The response rate of most anti-cancer drugs is limited because of the high heterogeneity of cancer and the complex mechanism of drug action. Personalized treatment that stratifies patients into subgroups using molecular biomarkers is promising to improve clinical benefit. With the accumulation of preclinical models and advances in computational approaches of drug response prediction, pharmacogenomics has made great success over the last 20 years and is increasingly used in the clinical practice of personalized cancer medicine. In this article, we first summarize FDA-approved pharmacogenomic biomarkers and large-scale pharmacogenomic studies of preclinical cancer models such as patient-derived cell lines, organoids, and xenografts. Furthermore, we comprehensively review the recent developments of computational methods in drug response prediction, covering network, machine learning, and deep learning technologies and strategies to evaluate immunotherapy response. In the end, we discuss challenges and propose possible solutions for further improvement.

7.
Genome Biol ; 22(1): 4, 2021 01 04.
Artigo em Inglês | MEDLINE | ID: mdl-33397441

RESUMO

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers due to its high metastasis rate in the liver. However, little is known about the molecular features of hepatic metastases due to difficulty in obtaining fresh tissues and low tumor cellularity. RESULTS: We conduct exome sequencing and RNA sequencing for synchronous surgically resected primary tumors and the paired hepatic metastases from 17 hepatic oligometastatic pancreatic ductal adenocarcinoma and validate our findings in specimens from 35 of such cases. The comprehensive analysis of somatic mutations, copy number alterations, and gene expressions show high similarity between primary tumors and hepatic metastases. However, hepatic metastases also show unique characteristics, such as a higher degree of 3p21.1 loss, stronger abilities of proliferation, downregulation of epithelial to mesenchymal transition activity, and metabolic rewiring. More interesting, altered tumor microenvironments are observed in hepatic metastases, especially a higher proportion of tumor infiltrating M2 macrophage and upregulation of complement cascade. Further experiments demonstrate that expression of C1q increases in primary tumors and hepatic metastases, C1q is mainly produced by M2 macrophage, and C1q promotes migration and invasion of PDAC cells. CONCLUSION: Taken together, we find potential factors that contribute to different stages of PDAC metastasis. Our study broadens the understanding of molecular mechanisms driving PDAC metastasis.

8.
Bioinformatics ; 37(3): 429-430, 2021 04 20.
Artigo em Inglês | MEDLINE | ID: mdl-32717036

RESUMO

SUMMARY: Dysfunctional regulations of gene expression programs relevant to fundamental cell processes can drive carcinogenesis. Therefore, systematically identifying dysregulation events is an effective path for understanding carcinogenesis and provides insightful clues to build predictive signatures with mechanistic interpretability for cancer precision medicine. Here, we implemented a machine learning-based gene dysregulation analysis framework in an R package, DysRegSig, which is capable of exploring gene dysregulations from high-dimensional data and building mechanistic signature based on gene dysregulations. DysRegSig can serve as an easy-to-use tool to facilitate gene dysregulation analysis and follow-up analysis. AVAILABILITY AND IMPLEMENTATION: The source code and user's guide of DysRegSig are freely available at Github: https://github.com/SCBIT-YYLab/DysRegSig. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Neoplasias , Software , Humanos , Aprendizado de Máquina , Neoplasias/genética
9.
J Mol Cell Biol ; 12(11): 881-893, 2021 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-32717065

RESUMO

The implementation of cancer precision medicine requires biomarkers or signatures for predicting prognosis and therapeutic benefits. Most of current efforts in this field are paying much more attention to predictive accuracy than to molecular mechanistic interpretability. Mechanism-driven strategy has recently emerged, aiming to build signatures with both predictive power and explanatory power. Driven by this strategy, we developed a robust gene dysregulation analysis framework with machine learning algorithms, which is capable of exploring gene dysregulations underlying carcinogenesis from high-dimensional data with cooperativity and synergy between regulators and several other transcriptional regulation rules taken into consideration. We then applied the framework to a colorectal cancer (CRC) cohort from The Cancer Genome Atlas. The identified CRC-related dysregulations significantly covered known carcinogenic processes and exhibited good prognostic effect. By choosing dysregulations with greedy strategy, we built a four-dysregulation (4-DysReg) signature, which has the capability of predicting prognosis and adjuvant chemotherapy benefit. 4-DysReg has the potential to explain carcinogenesis in terms of dysfunctional transcriptional regulation. These results demonstrate that our gene dysregulation analysis framework could be used to develop predictive signature with mechanistic interpretability for cancer precision medicine, and furthermore, elucidate the mechanisms of carcinogenesis.

10.
Aging (Albany NY) ; 12(23): 23849-23871, 2020 11 20.
Artigo em Inglês | MEDLINE | ID: mdl-33221766

RESUMO

Hepatocellular carcinoma (HCC) is a heterogeneous disease with various genetic and epigenetic abnormalities. Previous studies of HCC driver genes were primarily based on frequency of mutations and copy number alterations. Here, we performed an integrative analysis of genomic and epigenomic data from 377 HCC patients to identify driver genes that regulate gene expression in HCC. This integrative approach has significant advantages over single-platform analyses for identifying cancer drivers. Using this approach, HCC tissues were divided into four subgroups, based on expression of the transcription factor E2F and the mutation status of TP53. HCC tissues with E2F overexpression and TP53 mutation had the highest cell cycle activity, indicating a synergistic effect of E2F and TP53. We found that overexpression of the identified driver genes, stratifin (SFN) and SPP1, correlates with tumor grade and poor survival in HCC and promotes HCC cell proliferation. These findings indicate SFN and SPP1 function as oncogenes in HCC and highlight the important role of enhancers in the regulation of gene expression in HCC.


Assuntos
Biomarcadores Tumorais/genética , Carcinoma Hepatocelular/genética , Biologia Computacional , Genômica , Neoplasias Hepáticas/genética , Integração de Sistemas , Proteínas 14-3-3/genética , Carcinoma Hepatocelular/mortalidade , Carcinoma Hepatocelular/patologia , Carcinoma Hepatocelular/terapia , Linhagem Celular Tumoral , Proliferação de Células , Variações do Número de Cópias de DNA , Metilação de DNA , Bases de Dados Genéticas , Fatores de Transcrição E2F/genética , Epigênese Genética , Exorribonucleases/genética , Dosagem de Genes , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Predisposição Genética para Doença , Humanos , Neoplasias Hepáticas/patologia , Neoplasias Hepáticas/terapia , Mutação , Gradação de Tumores , Osteopontina/genética , Fenótipo , Proteína Supressora de Tumor p53/genética
11.
EBioMedicine ; 61: 103048, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33039712

RESUMO

BACKGROUND: Microbial communities and their metabolic components in the gut are of vital importance for immune homeostasis and have an influence on the susceptibility of the host to a number of immune-mediated diseases like acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). However, little is known about the functional connections between microbiome and metabolome in aGVHD due to the complexity of the gastrointestinal environment. METHOD: Initially, gut microbiota and fecal metabolic phenotype in aGVHD murine models were unleashed by performing 16S ribosomal DNA gene sequencing and ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS)-based metabolomics. FINDINGS: The group with aGVHD experienced a significant drop in Lachnospiraceae_unclassified but an increase in the relative abundance of Clostridium XI, Clostridium XIVa and Enterococcus. Meanwhile, a lower content of tyrosine was observed in the gut of aGVHD mice. The correlation analysis revealed that tyrosine-related metabolites were inversely correlated with Clostridium XIVa, besides, Blautia and Enterococcus also displayed the negative tendency in aGVHD condition. Apart from exploring the importance and function of tyrosine, different tyrosine diets were offered to mice during transplantation. Additional tyrosine supplements can improve overall survival, ameliorate symptoms at the early stage of aGVHD and change the structure and composition of gut microbiota and fecal metabolic phenotype. In addition, aGVHD mice deprived from tyrosine displayed worse manifestations than the vehicle diet group. INTERPRETATION: The results demonstrated the roles and mechanisms of gut microbiota, indispensable metabolites and tyrosine in the progression of aGVHD, which can be an underlying biomarker for aGVHD diagnosis and treatment. FUNDING: This research was funded by the International Cooperation and Exchange Program (81520108002), the National Key R&D Program of China, Stem Cell and Translation Research (2018YFA0109300), National Natural Science Foundation of China (81670169, 81670148, 81870080 and 91949115) and Natural Science Foundation of Zhejiang Province (LQ19H080006).

12.
Cancer Cell ; 38(5): 734-747.e9, 2020 11 09.
Artigo em Inglês | MEDLINE | ID: mdl-32888432

RESUMO

We integrate the genomics, proteomics, and phosphoproteomics of 480 clinical tissues from 146 patients in a Chinese colorectal cancer (CRC) cohort, among which 70 had metastatic CRC (mCRC). Proteomic profiling differentiates three CRC subtypes characterized by distinct clinical prognosis and molecular signatures. Proteomic and phosphoproteomic profiling of primary tumors alone successfully distinguishes cases with metastasis. Metastatic tissues exhibit high similarities with primary tumors at the genetic but not the proteomic level, and kinase network analysis reveals significant heterogeneity between primary colorectal tumors and their liver metastases. In vivo xenograft-based drug tests using 31 primary and metastatic tumors show personalized responses, which could also be predicted by kinase-substrate network analysis no matter whether tumors carry mutations in the drug-targeted genes. Our study provides a valuable resource for better understanding of mCRC and has potential for clinical application.


Assuntos
Antineoplásicos/uso terapêutico , Neoplasias Colorretais/tratamento farmacológico , Genômica/métodos , Metástase Neoplásica/tratamento farmacológico , Proteínas Quinases/genética , Proteínas Quinases/metabolismo , Proteômica/métodos , Animais , Antineoplásicos/farmacologia , China , Estudos de Coortes , Neoplasias Colorretais/genética , Neoplasias Colorretais/metabolismo , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Humanos , Camundongos , Terapia de Alvo Molecular , Metástase Neoplásica/genética , Fosforilação , Medicina de Precisão , Prognóstico , Proteínas Quinases/farmacologia , Ensaios Antitumorais Modelo de Xenoenxerto
13.
Nat Protoc ; 15(9): 3009-3029, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32796939

RESUMO

Genome editing holds great potential for correcting pathogenic mutations. We developed a method called GOTI (genome-wide off-target analysis by two-cell embryo injection) to detect off-target mutations by editing one blastomere of two-cell mouse embryos using either CRISPR-Cas9 or base editors. GOTI directly compares edited and non-edited cells without the interference of genetic background and thus could detect potential off-target variants with high sensitivity. Notably, the GOTI method was designed to detect potential off-target variants of any genome editing tools by the combination of experimental and computational approaches, which is critical for accurate evaluation of the safety of genome editing tools. Here we provide a detailed protocol for GOTI, including mice mating, two-cell embryo injection, embryonic day 14.5 embryo digestion, fluorescence-activated cell sorting, whole-genome sequencing and data analysis. To enhance the utility of GOTI, we also include a computational workflow called GOTI-seq (https://github.com/sydaileen/GOTI-seq) for the sequencing data analysis, which can generate the final genome-wide off-target variants from raw sequencing data directly. The protocol typically takes 20 d from the mice mating to sequencing and 7 d for sequencing data analysis.


Assuntos
Embrião de Mamíferos/metabolismo , Edição de Genes/métodos , Animais , Feminino , Injeções , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Mutação
14.
PeerJ ; 8: e9458, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32704448

RESUMO

Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has emerged as a new hallmark of cancer cells, accumulating evidences have suggested that metabolism-related genes may serve as key regulators of tumorigenesis and potential biomarkers. In this study, we analyzed a set of reprogramming energy metabolism-related genes by transcriptome analysis in colon cancer and revealed a five-gene signature that could significantly predict the overall survival. The reprogramming energy metabolism-related signature could distinguish patients into high-risk and low-risk groups with significantly different survival times (P = 0.0011; HR = 1.92; 95% CI [1.29-2.87]). Its prognostic value was confirmed in another two independent colon cancer cohorts (P = 5.2e-04; HR = 2.09, 95%; CI [1.37-3.2] for GSE17538 and P = 3.8e-04; HR = 2.08, 95% CI [1.37-3.16] for GSE41258). By multivariable analysis, we found that the signature was independent of clinicopathological features. Its power in promoting risk stratification of the current clinical stage was then evaluated by stratified analysis. Moreover, the signature could improve the power of the TNM stage for the prediction of overall survival and could be used in patients who received adjuvant chemotherapy. Overall, our results demonstrated the important role of the reprogramming energy metabolism-related signature in promoting stratification of high-risk patients, which could be diagnostic of adjuvant therapy benefit.

15.
Hum Genomics ; 14(1): 23, 2020 06 10.
Artigo em Inglês | MEDLINE | ID: mdl-32522283

RESUMO

BACKGROUND: Genetic research on longevity has provided important insights into the mechanism of aging and aging-related diseases. Pinpointing import genetic variants associated with aging could provide insights for aging research. METHODS: We performed a whole-genome sequencing in 19 centenarians to establish the genetic basis of human longevity. RESULTS: Using SKAT analysis, we found 41 significantly correlated genes in centenarians as compared to control genomes. Pathway enrichment analysis of these genes showed that immune-related pathways were enriched, suggesting that immune pathways might be critically involved in aging. HLA typing was next performed based on the whole-genome sequencing data obtained. We discovered that several HLA subtypes were significantly overrepresented. CONCLUSIONS: Our study indicated a new mechanism of longevity, suggesting potential genetic variants for further study.

16.
BioData Min ; 13: 4, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32536974

RESUMO

Background: Late-onset Parkinson's disease (LOPD) is a common neurodegenerative disorder and lacks disease-modifying treatments, attracting major attentions as the aggravating trend of aging population. There were numerous evidences supported that accelerated aging was the primary risk factor for LOPD, thus pointed out that the mechanisms of PD should be revealed thoroughly based on aging acceleration. However, how PD was triggered by accelerated aging remained unclear and the systematic prediction model was needed to study the mechanisms of PD. Results: In this paper, an improved PD predictor was presented by comparing with the normal aging process, and both aging and PD markers were identified herein using machine learning methods. Based on the aging scores, the aging acceleration network was constructed thereby, where the enrichment analysis shed light on key characteristics of LOPD. As a result, dysregulated energy metabolisms, the cell apoptosis, neuroinflammation and the ion imbalances were identified as crucial factors linking accelerated aging and PD coordinately, along with dysfunctions in the immune system. Conclusions: In short, mechanisms between aging and LOPD were integrated by our computational pipeline.

17.
Nat Methods ; 17(6): 600-604, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32424272

RESUMO

Cytosine base editors (CBEs) offer a powerful tool for correcting point mutations, yet their DNA and RNA off-target activities have caused concerns in biomedical applications. We describe screens of 23 rationally engineered CBE variants, which reveal mutation residues in the predicted DNA-binding site can dramatically decrease the Cas9-independent off-target effects. Furthermore, we obtained a CBE variant-YE1-BE3-FNLS-that retains high on-target editing efficiency while causing extremely low off-target edits and bystander edits.


Assuntos
Proteína 9 Associada à CRISPR/genética , Citosina/metabolismo , DNA/genética , Edição de Genes/métodos , RNA/genética , Sequência de Bases , Sistemas CRISPR-Cas/genética , Células HEK293 , Humanos , Mutação , Mutação Puntual
18.
Clin Immunol ; 215: 108412, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32278085

RESUMO

The infiltration of immune cells is highly associated with the development and progression of cancer. Thus, integrating the immune cell infiltrating profile into an immune cell infiltrating score may predict the survival of cancer patients. Here, by combining the infiltration proportion of 22 immune cells inferred from bulk tumor transcriptome of 879 patients, we identified an immune cell infiltrating indicator including five types of immune cells: resting T cells CD4 memory, macrophages M0-M2, and activated mast cells. The signature distinguished patients into two groups (high-risk and low-risk) with significantly different survival in the training cohort (HR = 1.96, 95% CI = 1.29-2.98, P = .0013) and two additional cohorts (HR = 1.78, 95%, CI = 1.16-2.75, P = .0079 and HR = 2.01, 95% CI = 1.28-3.14, P = .0019). The indicator remained as an independent prognostic factor after adjusting for clinicopathological factors by multivariable analysis in all cohorts. Stratification analysis showed that the signature consistently and significantly predicted survival of high-stage colon cancer patients in the training cohort (P = .00053) and validation cohorts (P = .017 and P = .0035). Moreover, we found that the low-risk patients were significantly correlated with deficient mismatch repair and the high-risk patients had a weak ability of trafficking of immune cells to tumors in the cancer immunity cycle. Overall, our results showed that integrating multiple tumor-infiltrating immune cells was an effective strategy for uncovering robust prognostic factor for tumor patients, and potentially was a promising response marker for precision oncology to be explored.


Assuntos
Neoplasias do Colo/imunologia , Linfócitos do Interstício Tumoral/imunologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Biomarcadores Tumorais/imunologia , Linfócitos T CD4-Positivos/imunologia , Estudos de Coortes , Feminino , Humanos , Memória Imunológica/imunologia , Macrófagos/imunologia , Masculino , Mastócitos/imunologia , Pessoa de Meia-Idade , Medicina de Precisão , Prognóstico , Transcriptoma/imunologia , Adulto Jovem
19.
BMC Bioinformatics ; 21(1): 127, 2020 Apr 03.
Artigo em Inglês | MEDLINE | ID: mdl-32245364

RESUMO

BACKGROUND: Hybrid capture-based next-generation sequencing of DNA has been widely applied in the detection of circulating tumor DNA (ctDNA). Various methods have been proposed for ctDNA detection, but low-allelic-fraction (AF) variants are still a great challenge. In addition, no panel-wide calling algorithm is available, which hiders the full usage of ctDNA based 'liquid biopsy'. Thus, we developed the VBCALAVD (Virtual Barcode-based Calling Algorithm for Low Allelic Variant Detection) in silico to overcome these limitations. RESULTS: Based on the understanding of the nature of ctDNA fragmentation, a novel platform-independent virtual barcode strategy was established to eliminate random sequencing errors by clustering sequencing reads into virtual families. Stereotypical mutant-family-level background artifacts were polished by constructing AF distributions. Three additional robust fine-tuning filters were obtained to eliminate stochastic mutant-family-level noises. The performance of our algorithm was validated using cell-free DNA reference standard samples (cfDNA RSDs) and normal healthy cfDNA samples (cfDNA controls). For the RSDs with AFs of 0.1, 0.2, 0.5, 1 and 5%, the mean F1 scores were 0.43 (0.25~0.56), 0.77, 0.92, 0.926 (0.86~1.0) and 0.89 (0.75~1.0), respectively, which indicates that the proposed approach significantly outperforms the published algorithms. Among controls, no false positives were detected. Meanwhile, characteristics of mutant-family-level noise and quantitative determinants of divergence between mutant-family-level noises from controls and RSDs were clearly depicted. CONCLUSIONS: Due to its good performance in the detection of low-AF variants, our algorithm will greatly facilitate the noninvasive panel-wide detection of ctDNA in research and clinical settings. The whole pipeline is available at https://github.com/zhaodalv/VBCALAVD.


Assuntos
Algoritmos , DNA Tumoral Circulante/química , Análise de Sequência de DNA/métodos , Simulação por Computador , Humanos , Mutação
20.
Artigo em Inglês | MEDLINE | ID: mdl-32154224

RESUMO

Long non-coding RNAs (lncRNAs), as important ncRNA regulators, play crucial roles in the regulation of various biological processes, and their aberrant expression is related to the occurrence and development of diseases, which is gradually validated by more and more studies. Alzheimer's disease (AD) is a chronic neurodegenerative disease that often develops slowly and gradually deteriorates over time. However, which functions the lncRNAs perform in AD are almost unknown. In this study, we performed transcriptome analysis in AD, containing 12,892 known lncRNAs and 19,053 protein-coding genes (PCGs). Further, 14 down-regulated and 39 up-regulated lncRNAs were identified, compared with normal brain samples, which indicated that these lncRNAs might play critical roles in the pathogenesis of AD. In addition, 19 down-regulated and 28 up-regulated PCGs were also detected. Using the differentially expressed lncRNAs and PCGs through the WGCNA method, an lncRNA-mRNA co-expressed network was constructed. The results showed that lncRNAs RP3-522J7, MIR3180-2, and MIR3180-3 were frequently co-expressed with known AD risk PCGs. Interestingly, PCGs in the network are significantly enriched in brain- or AD-related biological functions, including the brain renin-angiotensin system, cell adhesion, neuroprotective role of THOP1 in AD, and so on. Furthermore, it was shown that 18 lncRNAs and 7 PCGs were highly expressed in normal brain tissue relative to other normal tissue types, suggesting their potential as diagnostic markers of AD, especially RP3-522J7, MIR3180-2, MIR3180-3, and CTA-929C8. In total, our study identified a compendium of AD-related dysregulated lncRNAs and characterized the corresponding biological functions of these lncRNAs in AD, which will be helpful to understand the molecular basis and pathogenesis of AD.

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