Metastasis is the leading cause of human cancer deaths.Unfortunately,no approved drugs are available for antimetastatic treatment.In our study,high-throughput sequencing-based high-throughput screening(HTS^2)and a bre...Metastasis is the leading cause of human cancer deaths.Unfortunately,no approved drugs are available for antimetastatic treatment.In our study,high-throughput sequencing-based high-throughput screening(HTS^2)and a breast cancer lung metastasis(BCLM)-associated gene signature were combined to discover anti-metastatic drugs.After screening of thousands of compounds,we identified Ponatinib as a BCLM inhibitor.Ponatinib significantly inhibited the migration and mammosphere formation of breast cancer cells in vitro and blocked BCLM in multiple mouse models.Mechanistically,Ponatinib represses the expression of BCLM-associated genes mainly through the ERK/c-Jun signaling pathway by inhibiting the transcription of JUN and accelerating the degradation of c-Jun protein.Notably,JUN expression levels were positively correlated with BCLM-associated gene expression and lung metastases in breast cancer patients.Collectively,we established a novel approach for the discovery of anti-metastatic drugs,identified Ponatinib as a new drug to inhibit BCLM and revealed c-Jun as a crucial factor and potential drug target for BCLM.Our study may facilitate the therapeutic treatment of BCLM as well as other metastases.展开更多
In order to explore the genomic basis for liver cancer metastasis,whole-exome sequencing(WES)was performed on patient-derived hepatocellular carcinoma(HCC)cell lines with differential metastatic potentials and analyze...In order to explore the genomic basis for liver cancer metastasis,whole-exome sequencing(WES)was performed on patient-derived hepatocellular carcinoma(HCC)cell lines with differential metastatic potentials and analyzed their clonal evolution relationships.An evolutionary tree based on genomic single nucleotide polymorphism(SNP)was constructed in MegaX software.The WES data showed that the average percentage of heterogeneous mutations in each HCC cell lines was 16.55%(range,15.38%e18.17%).C:G>T:A and T:A>C:G somatic transitions were the two most frequent substitutions.In these metastatic HCC cell lines,non-silent gene mutations were found in 21.88%of known driver genes and 10 classical signaling pathways.The protein interaction network was constructed by STRING,and hub genes were found in the shared trunk mutation genes and the heterogeneous branch mutations respectively.In cBioPortal database,some of the selected hub genes were found to be associated with poor overall survival(OS)of HCC patients.Among the mutated HCC driver genes,a novel KEAP1 mutation with a homozygous frameshift truncation at the c-terminal Nrf2 binding region was detected and verified in MHCC97-H and HCC97LM3 cells.In conclusion,WES data demonstrate that HCC cell lines from tumor biopsy specimens of the same patient have obtained different metastatic potentials through repeated selection in rodents in vivo,and they do indeed have a genetic relationship at the genomic level.展开更多
Metastasis is the greatest contributor to cancer?related death.In the era of precision medicine,it is essential to predict and to prevent the spread of cancer cells to significantly improve patient survival.Thanks to ...Metastasis is the greatest contributor to cancer?related death.In the era of precision medicine,it is essential to predict and to prevent the spread of cancer cells to significantly improve patient survival.Thanks to the application of a variety of high?throughput technologies,accumulating big data enables researchers and clinicians to identify aggressive tumors as well as patients with a high risk of cancer metastasis.However,there have been few large?scale gene collection studies to enable metastasis?related analyses.In the last several years,emerging efforts have identi?fied pro?metastatic genes in a variety of cancers,providing us the ability to generate a pro?metastatic gene cluster for big data analyses.We carefully selected 285 genes with in vivo evidence of promoting metastasis reported in the literature.These genes have been investigated in different tumor types.We used two datasets downloaded from The Cancer Genome Atlas database,specifically,datasets of clear cell renal cell carcinoma and hepatocellular carcinoma,for validation tests,and excluded any genes for which elevated expression level correlated with longer overall survival in any of the datasets.Ultimately,150 pro?metastatic genes remained in our analyses.We believe this collection of pro?metastatic genes will be helpful for big data analyses,and eventually will accelerate anti?metastasis research and clinical intervention.展开更多
子宫内膜和卵巢双原发癌(synchronous endometrial and ovarian carcinoma,SEOC)的概念在上世纪八十年代被Ulbright等[1]提出,病因及发病机制不明确。SEOC诊断困难,主要是因为病理诊断标准复杂,难以与子宫内膜癌卵巢转移(endometrial ca...子宫内膜和卵巢双原发癌(synchronous endometrial and ovarian carcinoma,SEOC)的概念在上世纪八十年代被Ulbright等[1]提出,病因及发病机制不明确。SEOC诊断困难,主要是因为病理诊断标准复杂,难以与子宫内膜癌卵巢转移(endometrial carcinoma with ovarian metastasis,ECO)鉴别。虽然SEOC中子宫内膜及卵巢原发肿瘤多为早期,且大多患者预后好,但治疗缺乏统一标准,突出的问题是将SEOC按照ECO进行术后辅助治疗,存在治疗过度。本文将对SEOC的流行病学、病因、诊断、治疗及预后进行文献综述。展开更多
Affymetrix U133A oligonucleotide microarrays were used to study the differences of gene expressions between high （H） metastatic ovarian cancer cell line, HO-8910PM, and normal ovarian tissues （C）. Bioinformatics w...Affymetrix U133A oligonucleotide microarrays were used to study the differences of gene expressions between high （H） metastatic ovarian cancer cell line, HO-8910PM, and normal ovarian tissues （C）. Bioinformatics was used to identify their chromosomal localizations. A total of 1,237 genes were found to have a difference in expression levels more than eight times. Among them 597 were upregulated [Signal Log Ratio （SLR） ≥3], and 640 genes were downregulated （SLR≤-3）. Except one gene, whose location was unknown, all these genes were randomly distributed on all the chromosomes. However, chromosome 1 contained the most differentially expressed genes （115 genes, 9.3%）, followed by chromosome 2 （94 genes, 7.6%）, chromosome 12 （88 genes, 7.1%）, chromosome 11 （76 genes, 6.1%）, chromosomes X （71 genes, 5.7%）, and chromosomes l7 （69 genes, 5.6%）. These genes were localized on short-arm of chromosome （q）, which had 805 （65.1%） genes, and the short arms of No.13, 14, 15, 21, and 22 chromosomes were the only parts of the chromosomes where the differentially expressed genes were localized. Functional classification showed that most of the genes （306 genes, 24.7%） belonged to the enzymes and their regulator groups. The subsequent group was the nucleic acid binding genes （144 genes, 11.6%）. The rest of the top two groups were signal transduction genes （137 genes, 11.1%） and proteins binding genes （116 genes, 9.4%）. These comprised 56.8% of all the differentially expressed genes. There were also 207 genes whose functions were unknown （16.7 %）. Therefore it was concluded that differentially expressed genes in high metastatic ovarian cancer cell were supposed to be randomly distributed across the genome, but the majority were found on chromosomes 1, 2, 12, 11, 17, and X. Abnormality in four groups of genes, including in enzyme and its regulator, nucleic acid binding, signal transduction and protein binding associated genes, might play important roles in ovarian c展开更多
基金a grant from the National Natural Science Foundation of China(Grant No.81673460)fun ding from Tsinghua-Peking Joint Center for Life Sciences and Beijing Mun icipal Science&Technology Commissi on.
文摘Metastasis is the leading cause of human cancer deaths.Unfortunately,no approved drugs are available for antimetastatic treatment.In our study,high-throughput sequencing-based high-throughput screening(HTS^2)and a breast cancer lung metastasis(BCLM)-associated gene signature were combined to discover anti-metastatic drugs.After screening of thousands of compounds,we identified Ponatinib as a BCLM inhibitor.Ponatinib significantly inhibited the migration and mammosphere formation of breast cancer cells in vitro and blocked BCLM in multiple mouse models.Mechanistically,Ponatinib represses the expression of BCLM-associated genes mainly through the ERK/c-Jun signaling pathway by inhibiting the transcription of JUN and accelerating the degradation of c-Jun protein.Notably,JUN expression levels were positively correlated with BCLM-associated gene expression and lung metastases in breast cancer patients.Collectively,we established a novel approach for the discovery of anti-metastatic drugs,identified Ponatinib as a new drug to inhibit BCLM and revealed c-Jun as a crucial factor and potential drug target for BCLM.Our study may facilitate the therapeutic treatment of BCLM as well as other metastases.
基金This work was supported by the National Natural Science Foundation of China(NSFC,NO.81172066,NO.81472858NO.91529103)+1 种基金Innovation Team Fund of Second Affiliated Hospital of Chongqing Medical UniversityThe authors would like to thank Dr.Zhou-You Tang,Professor&Director,Liver Cancer Institute,Fudan University,for providing the three HCC cell lines(MHCC97-L,MHCC97-H,HCC97LM3).
文摘In order to explore the genomic basis for liver cancer metastasis,whole-exome sequencing(WES)was performed on patient-derived hepatocellular carcinoma(HCC)cell lines with differential metastatic potentials and analyzed their clonal evolution relationships.An evolutionary tree based on genomic single nucleotide polymorphism(SNP)was constructed in MegaX software.The WES data showed that the average percentage of heterogeneous mutations in each HCC cell lines was 16.55%(range,15.38%e18.17%).C:G>T:A and T:A>C:G somatic transitions were the two most frequent substitutions.In these metastatic HCC cell lines,non-silent gene mutations were found in 21.88%of known driver genes and 10 classical signaling pathways.The protein interaction network was constructed by STRING,and hub genes were found in the shared trunk mutation genes and the heterogeneous branch mutations respectively.In cBioPortal database,some of the selected hub genes were found to be associated with poor overall survival(OS)of HCC patients.Among the mutated HCC driver genes,a novel KEAP1 mutation with a homozygous frameshift truncation at the c-terminal Nrf2 binding region was detected and verified in MHCC97-H and HCC97LM3 cells.In conclusion,WES data demonstrate that HCC cell lines from tumor biopsy specimens of the same patient have obtained different metastatic potentials through repeated selection in rodents in vivo,and they do indeed have a genetic relationship at the genomic level.
基金supported by grants from the National Natural Science Foundation of China(No.81272340,No.81472386,No.81672872)the National High Technology Research and Development Program of China(863 Program)(No.2012AA02A501)+1 种基金the Science and Technology Planning Project of Guangdong Province,China(No.2014B020212017,No.2014B050504004 and No.2015B050501005)the Natural Science Foundation of Guangdong Province,China(No.2016A030311011)
文摘Metastasis is the greatest contributor to cancer?related death.In the era of precision medicine,it is essential to predict and to prevent the spread of cancer cells to significantly improve patient survival.Thanks to the application of a variety of high?throughput technologies,accumulating big data enables researchers and clinicians to identify aggressive tumors as well as patients with a high risk of cancer metastasis.However,there have been few large?scale gene collection studies to enable metastasis?related analyses.In the last several years,emerging efforts have identi?fied pro?metastatic genes in a variety of cancers,providing us the ability to generate a pro?metastatic gene cluster for big data analyses.We carefully selected 285 genes with in vivo evidence of promoting metastasis reported in the literature.These genes have been investigated in different tumor types.We used two datasets downloaded from The Cancer Genome Atlas database,specifically,datasets of clear cell renal cell carcinoma and hepatocellular carcinoma,for validation tests,and excluded any genes for which elevated expression level correlated with longer overall survival in any of the datasets.Ultimately,150 pro?metastatic genes remained in our analyses.We believe this collection of pro?metastatic genes will be helpful for big data analyses,and eventually will accelerate anti?metastasis research and clinical intervention.
文摘子宫内膜和卵巢双原发癌(synchronous endometrial and ovarian carcinoma,SEOC)的概念在上世纪八十年代被Ulbright等[1]提出,病因及发病机制不明确。SEOC诊断困难,主要是因为病理诊断标准复杂,难以与子宫内膜癌卵巢转移(endometrial carcinoma with ovarian metastasis,ECO)鉴别。虽然SEOC中子宫内膜及卵巢原发肿瘤多为早期,且大多患者预后好,但治疗缺乏统一标准,突出的问题是将SEOC按照ECO进行术后辅助治疗,存在治疗过度。本文将对SEOC的流行病学、病因、诊断、治疗及预后进行文献综述。
基金National Natural Science Foundation of China (No. 30471819).
文摘Affymetrix U133A oligonucleotide microarrays were used to study the differences of gene expressions between high （H） metastatic ovarian cancer cell line, HO-8910PM, and normal ovarian tissues （C）. Bioinformatics was used to identify their chromosomal localizations. A total of 1,237 genes were found to have a difference in expression levels more than eight times. Among them 597 were upregulated [Signal Log Ratio （SLR） ≥3], and 640 genes were downregulated （SLR≤-3）. Except one gene, whose location was unknown, all these genes were randomly distributed on all the chromosomes. However, chromosome 1 contained the most differentially expressed genes （115 genes, 9.3%）, followed by chromosome 2 （94 genes, 7.6%）, chromosome 12 （88 genes, 7.1%）, chromosome 11 （76 genes, 6.1%）, chromosomes X （71 genes, 5.7%）, and chromosomes l7 （69 genes, 5.6%）. These genes were localized on short-arm of chromosome （q）, which had 805 （65.1%） genes, and the short arms of No.13, 14, 15, 21, and 22 chromosomes were the only parts of the chromosomes where the differentially expressed genes were localized. Functional classification showed that most of the genes （306 genes, 24.7%） belonged to the enzymes and their regulator groups. The subsequent group was the nucleic acid binding genes （144 genes, 11.6%）. The rest of the top two groups were signal transduction genes （137 genes, 11.1%） and proteins binding genes （116 genes, 9.4%）. These comprised 56.8% of all the differentially expressed genes. There were also 207 genes whose functions were unknown （16.7 %）. Therefore it was concluded that differentially expressed genes in high metastatic ovarian cancer cell were supposed to be randomly distributed across the genome, but the majority were found on chromosomes 1, 2, 12, 11, 17, and X. Abnormality in four groups of genes, including in enzyme and its regulator, nucleic acid binding, signal transduction and protein binding associated genes, might play important roles in ovarian c
