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1.
Cancer Cell ; 42(1): 135-156.e17, 2024 01 08.
Artículo en Inglés | MEDLINE | ID: mdl-38101410

RESUMEN

Comprehensive molecular analyses of metastatic hepatocellular carcinoma (HCC) are lacking. Here, we generate multi-omic profiling of 257 primary and 176 metastatic regions from 182 HCC patients. Primary tumors rich in hypoxia signatures facilitated polyclonal dissemination. Genomic divergence between primary and metastatic HCC is high, and early dissemination is prevalent. The remarkable neoantigen intratumor heterogeneity observed in metastases is associated with decreased T cell reactivity, resulting from disruptions to neoantigen presentation. We identify somatic copy number alterations as highly selected events driving metastasis. Subclones without Wnt mutations show a stronger selective advantage for metastasis than those with Wnt mutations and are characterized by a microenvironment rich in activated fibroblasts favoring a pro-metastatic phenotype. Finally, metastases without Wnt mutations exhibit higher enrichment of immunosuppressive B cells that mediate terminal exhaustion of CD8+ T cells via HLA-E:CD94-NKG2A checkpoint axis. Collectively, our results provide a multi-dimensional dissection of the complex evolutionary process of metastasis.


Asunto(s)
Carcinoma Hepatocelular , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patología , Linfocitos T CD8-positivos/patología , Multiómica , Mutación , Microambiente Tumoral/genética
2.
Annu Rev Genet ; 57: 201-222, 2023 11 27.
Artículo en Inglés | MEDLINE | ID: mdl-37562413

RESUMEN

Despite accumulating evidence implicating noncoding variants in human diseases, unraveling their functionality remains a significant challenge. Systematic annotations of the regulatory landscape and the growth of sequence variant data sets have fueled the development of tools and methods to identify causal noncoding variants and evaluate their regulatory effects. Here, we review the latest advances in the field and discuss potential future research avenues to gain a more in-depth understanding of noncoding regulatory variants.


Asunto(s)
Predisposición Genética a la Enfermedad , Variación Genética , Humanos , Variación Genética/genética , Estudio de Asociación del Genoma Completo/métodos , Polimorfismo de Nucleótido Simple/genética
3.
G3 (Bethesda) ; 12(1)2022 01 04.
Artículo en Inglés | MEDLINE | ID: mdl-34791188

RESUMEN

RNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation-based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized transcripts per millions of different subcellular fractions without considering the difference in total RNA abundances in different fractions), however, absolute ratios may yield different results on the preference to different cellular compartment. Experimentally, adding external Spike-in RNAs to different fractionation can be used to obtain absolute ratios. In addition, a spike-in independent computational approach based on multiple linear regression model can also be used. However, currently, no custom tool is available. To solve this problem, we developed a method called subcellular fraction abundance estimator to correctly estimate relative RNA abundances of different subcellular fractionations. The ratios estimated by our method were consistent with existing reports. By applying the estimated ratios for different fractions, we explored the RNA localization pattern in cell lines and also predicted RBP motifs that were associated with different localization patterns. In addition, we showed that different isoforms of same genes could exhibit distinct localization patterns. To conclude, we believed our tool will facilitate future subcellular fractionation-related sequencing study to explore the function of RNA localization in various biological problems.


Asunto(s)
Fenómenos Biológicos , ARN , Isoformas de Proteínas/metabolismo , ARN/metabolismo , Fracciones Subcelulares/metabolismo
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