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Novel patterns of cancer genome evolution

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Oncology and Translational Medicine 2015年第5期1卷 222-225页

作者： Xia Zhang Xiaodi Deng Yu Zhang Zhiguang Li Institute of cancer Stem Cell Second Affiliated HospitalCancer CenterDalian Medical University

Cells usually undergo a long journey of evolution during the progression from normal to precancerous cells and finally to full-fledged cancer cells. Multiple genomic aberrations are acquired during this journey that could either act as drivers to confer significant growth advantages or act as passengers with little effect on the tumor growth. Recent advances in sequencing technology have made it feasible to decipher the evolutionary course of a cancer cell on a genome-wide level by evaluating the relative number of mutated alleles. Novel terms such as chromothripsis and chromoplexy have been introduced to describe the newly identified patterns of cancer genome evolution. These new insights have greatly expanded our understanding of the initiation and progression of cancers,which should aid in improving the efficiency of cancer management and treatment.

关键词： cancer genome evolution chromothripsis chromoplexy

Genomic alterations and molecular subtypes of gastric cancers in Asians

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Chinese Journal of cancer 2016年第8期35卷 403-409页

作者： Xiang S.Ye Chunping Yu Amit Aggarwal Christoph Reinhard Lilly(China) R&D Center Lilly Research Laboratories Lilly Corporate CenterEli Lilly and Company

Gastric cancer(GC) is a highly heterogenic disease,and it is the second leading cause of cancer death in the *** chemotherapies are not very effective for GC,which often presents as an advanced or metastatic disease at *** options are limited,and the prognosis for advanced GCs is *** landscape of genomic alterations in GCs has recently been characterized by several international cancer genome programs,including studies that focused exclusively on GCs in *** studies identified major recurrent driver mutations and provided new insights into the mutational heterogeneity and genetic profiles of *** analysis of gene expression data by the Asian cancer Research Group(ACRG) further uncovered four distinct molecular subtypes with well-defined clinical features and their intersections with actionable genetic alterations to which targeted therapeutic agents are either already available or under clinical *** this article,we review the ACRG GC *** also discuss the implications of the genetic and molecular findings from various GC genomic studies with respect to developing more precise diagnoses and treatment approaches for GCs.

关键词： Gastric cancer cancer genome Molecular subtyping Heterogeneity Oncogenic drivers Targeted therapy

Application of third-generation sequencing in cancer research

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Medical Review 2021年第2期1卷 150-171页

作者： Zhiao Chen Xianghuo He Fudan University Shanghai cancer Center and Institutes of Biomedical Sciences Fudan University302 Rm.7#Bldg270 Dong An RoadShanghai 200032China Department of Oncology Shanghai Medical CollegeFudan UniversityShanghaiChina

In the past several years,nanopore sequencing technology from Oxford Nanopore Technologies(ONT)and single-molecule real-time(SMRT)sequencing technology from Pacific BioSciences(PacBio)have become available to researchers and are currently being tested for cancer *** methods offer many advantages over most widely used high-throughput short-read sequencing approaches and allow the comprehensive analysis of transcriptomes by identifying full-length splice isoforms and several other posttranscriptional *** addition,these platforms enable structural variation characterization at a previously unparalleled resolution and direct detection of epigenetic marks in native DNA and ***,we present a comprehensive summary of important applications of these technologies in cancer research,including the identification of complex structure variants,alternatively spliced isoforms,fusion transcript events,and exogenous ***,we discuss the impact of the newly developed nanopore direct RNA sequencing(RNA-Seq)approach in advancing epitranscriptome research in *** the unique challenges still present for these new singlemolecule long-read methods,they will unravel many aspects of cancer genome complexity in unprecedented ways and present an encouraging outlook for continued application in an increasing number of different cancer research settings.

关键词： alternative splicing application cancer genome epigenome

Information Science Should Take a Lead in Future Biomedical Research

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Engineering 2019年第6期5卷 1155-1158页

作者： Kenta Nakai The Institute of Medical Science The University of TokyoTokyo 108-8639Japan

In this commentary, I explain my perspective on the relationship between arti cial intelligence (AI)/data science and biomedicine from a long-range retrospective view. The development of modern biomedicine has always been accelerated by the repeated emergence of new technologies. Since all life systems are basically governed by the information in their own DNA, information science has special importance for the study of biomedicine. Unlike in physics, no (or very few) leading laws have been found in biology. Thus, in biology, the “data-to-knowledge” approach is important. AI has historically been applied to bio- medicine, and the recent news that an AI-based approach achieved the best performance in an interna- tional competition of protein structure prediction may be regarded as another landmark in the eld. Similar approaches could contribute to solving problems in genome sequence interpretation, such as identifying cancer-driving mutations in the genome of patients. Recently, the explosive development of next-generation sequencing (NGS) has been producing massive data, and this trend will accelerate. NGS is not only used for “reading” DNA sequences, but also for obtaining various types of information at the single-cell level. These data can be regarded as grid data points in climate simulation. Both data science and AI will become essential for the integrative interpretation/simulation of these data, and will take a leading role in future precision medicine.

关键词： Data science Artificial intelligence Next-generation sequencing DNA cancer genome Single-cell transcriptomics