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Clin Cancer Res ; 2021 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-34526363


PURPOSE: Targeted therapy and immunotherapy are transforming the treatment approach for intrahepatic cholangiocarcinoma (ICC). However, little is known about the intertumor heterogeneity (ITH) of multifocal ICC and its impacts on patient response to these treatments. We aimed to characterize the immunogenomic and epigenomic heterogeneity of multifocal ICC to guide treatment decision making. EXPERIMENTAL DESIGN: We obtained 66 tumor samples from 16 patients with multifocal ICC and characterized the tumor and immune heterogeneity using whole-exome sequencing, bulk and single-cell RNA sequencing, methylation microarray, and multiplex immunostaining. Patients were divided into high- or low-ITH groups according to the median ITH index. Two independent cohorts were used to validate findings. Responses to anti-PD-1 therapy were assessed. RESULTS: Multifocal ICC presented considerable intertumor genomic, transcriptional, and epigenomic heterogeneity within a patient in high ITH group. The immune profile among multiple tumors within a patient was relatively less heterogeneous in high- or low-ITH group, and consistent responses of multiple tumors to anti-PD-1 immunotherapy were observed. Unsupervised clustering of immune markers identified one low and one high immune subtype, with higher immune cell infiltration, closer tumor-immune cell interactions, and upregulated IFN-signature expression in high-immune subtype. Determining expression levels of CD8B and ICOS facilitated this immune classification and prediction of patient prognosis. Finally, promoter DNA methylation contributed to different immune profiles of two subtypes by regulating immune-gene expression. CONCLUSIONS: There is comprehensive heterogeneity in the genome, transcriptome, and epigenome of multifocal ICC. On the basis of the less heterogeneous immune profile of ICC, we suggest an immune classification that stratifies patients' prognosis and may support personalized immunotherapy.

Nucleic Acids Res ; 48(D1): D789-D796, 2020 01 08.
Artigo em Inglês | MEDLINE | ID: mdl-31665503


The early detection of cancer holds the key to combat and control the increasing global burden of cancer morbidity and mortality. Blood-based screenings using circulating DNAs (ctDNAs), circulating RNA (ctRNAs), circulating tumor cells (CTCs) and extracellular vesicles (EVs) have shown promising prospects in the early detection of cancer. Recent high-throughput gene expression profiling of blood samples from cancer patients has provided a valuable resource for developing new biomarkers for the early detection of cancer. However, a well-organized online repository for these blood-based high-throughput gene expression data is still not available. Here, we present BBCancer (, a web-accessible and comprehensive open resource for providing the expression landscape of six types of RNAs, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), microRNAs (miRNAs), circular RNAs (circRNAs), tRNA-derived fragments (tRFRNAs) and Piwi-interacting RNAs (piRNAs) in blood samples, including plasma, CTCs and EVs, from cancer patients with various cancer types. Currently, BBCancer contains expression data of the six RNA types from 5040 normal and tumor blood samples across 15 cancer types. We believe this database will serve as a powerful platform for developing blood biomarkers.

Biomarcadores Tumorais , Bases de Dados de Compostos Químicos , Detecção Precoce de Câncer/métodos , Neoplasias/diagnóstico , RNA/sangue , Biomarcadores Tumorais/sangue , Biomarcadores Tumorais/genética , Perfilação da Expressão Gênica , Humanos
Cancer Res ; 79(8): 2076-2083, 2019 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-30786995


Long noncoding RNAs (lncRNA) have emerged as promising biomarkers in cancer diagnosis, treatment, and prognosis. Recent studies suggest that a large number of coding gene expression microarray probes could be reannotated as lncRNAs. Microarray, once the most cutting-edge high-throughput gene expression technology, has been used for thousands of cancer studies and has brought invaluable resources for studying the functions of lncRNA in cancer development. However, a comprehensive lncRNA resource based on microarray data is still lacking. Here, we present lnCAR (lncRNAs from cancer arrays), a comprehensive open resource for providing expression profiles and prognostic landscape of lncRNAs derived from reannotation of public microarray data. Currently, lnCAR contains 52,300 samples for differential expression analysis and 12,883 samples for survival analysis from 10 cancer types. lnCAR allows users to interactively explore any annotated or novel lncRNAs. We believe lnCAR will serve as a valuable resource for the community focused on lncRNA research in cancer. SIGNIFICANCE: lnCAR, a new interactive tool of reannotated public cancer-related microarray data, provides expression profiles and prognostic landscapes of lncRNAs across thousands of samples and multiple cancer types.

Biomarcadores Tumorais/genética , Neoplasias da Mama/genética , Bases de Dados Genéticas , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , RNA Longo não Codificante/genética , Software , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/terapia , Feminino , Humanos , Prognóstico , Taxa de Sobrevida , Interface Usuário-Computador