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转移性黑色素瘤中激酶同工型表达的特征分析和聚类。

Characterization and clustering of kinase isoform expression in metastatic melanoma.

机构信息

Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America.

Lymphocyte Nuclear Biology, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.

出版信息

PLoS Comput Biol. 2022 May 13;18(5):e1010065. doi: 10.1371/journal.pcbi.1010065. eCollection 2022 May.

DOI:10.1371/journal.pcbi.1010065
PMID:35560144
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9132324/
Abstract

Mutations to the human kinome are known to play causal roles in cancer. The kinome regulates numerous cell processes including growth, proliferation, differentiation, and apoptosis. In addition to aberrant expression, aberrant alternative splicing of cancer-driver genes is receiving increased attention as it could lead to loss or gain of functional domains, altering a kinase's downstream impact. The present study quantifies changes in gene expression and isoform ratios in the kinome of metastatic melanoma cells relative to primary tumors. We contrast 538 total kinases and 3,040 known kinase isoforms between 103 primary tumor and 367 metastatic samples from The Cancer Genome Atlas (TCGA). We find strong evidence of differential expression (DE) at the gene level in 123 kinases (23%). Additionally, of the 468 kinases with alternative isoforms, 60 (13%) had significant difference in isoform ratios (DIR). Notably, DE and DIR have little correlation; for instance, although DE highlights enrichment in receptor tyrosine kinases (RTKs), DIR identifies altered splicing in non-receptor tyrosine kinases (nRTKs). Using exon junction mapping, we identify five examples of splicing events favored in metastatic samples. We demonstrate differential apoptosis and protein localization between SLK isoforms in metastatic melanoma. We cluster isoform expression data and identify subgroups that correlate with genomic subtypes and anatomic tumor locations. Notably, distinct DE and DIR patterns separate samples with BRAF hotspot mutations and (N/K/H)RAS hotspot mutations, the latter of which lacks effective kinase inhibitor treatments. DE in RAS mutants concentrates in CMGC kinases (a group including cell cycle and splicing regulators) rather than RTKs as in BRAF mutants. Furthermore, isoforms in the RAS kinase subgroup show enrichment for cancer-related processes such as angiogenesis and cell migration. Our results reveal a new approach to therapeutic target identification and demonstrate how different mutational subtypes may respond differently to treatments highlighting possible new driver events in cancer.

摘要

人类激酶组的突变已知在癌症中起着因果作用。激酶组调节着许多细胞过程,包括生长、增殖、分化和凋亡。除了异常表达外,癌症驱动基因的异常选择性剪接也越来越受到关注,因为它可能导致功能域的丢失或获得,从而改变激酶的下游影响。本研究定量分析了转移性黑素瘤细胞与原发性肿瘤相比激酶组中的基因表达和同工型比例的变化。我们比较了 103 个原发性肿瘤和 367 个来自癌症基因组图谱(TCGA)的转移性样本中的 538 个总激酶和 3040 个已知激酶同工型。我们在 123 个激酶(23%)中发现了基因水平上差异表达(DE)的有力证据。此外,在具有替代同工型的 468 个激酶中,60 个(13%)同工型比例有显著差异(DIR)。值得注意的是,DE 和 DIR 相关性很小;例如,虽然 DE 突出了受体酪氨酸激酶(RTKs)的富集,但 DIR 确定了非受体酪氨酸激酶(nRTKs)中的剪接改变。使用外显子连接映射,我们确定了在转移性样本中优先发生的五个剪接事件。我们证明了转移性黑素瘤中 SLK 同工型之间的差异凋亡和蛋白定位。我们对同工型表达数据进行聚类,并确定与基因组亚型和解剖肿瘤位置相关的亚组。值得注意的是,具有 BRAF 热点突变和(N/K/H)RAS 热点突变的样本之间存在明显的 DE 和 DIR 模式分离,后者缺乏有效的激酶抑制剂治疗。RAS 突变体中的 DE 集中在 CMGC 激酶(包括细胞周期和剪接调节剂)中,而不是像 BRAF 突变体中的 RTKs 那样。此外,RAS 激酶亚组中的同工型表现出对癌症相关过程的富集,如血管生成和细胞迁移。我们的结果揭示了一种新的治疗靶点识别方法,并展示了不同的突变亚型如何对治疗产生不同的反应,突出了癌症中可能存在的新驱动事件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/57dfad5a5211/pcbi.1010065.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/0e3252e2fde8/pcbi.1010065.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/0f907bdf507d/pcbi.1010065.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/ab0527b85df7/pcbi.1010065.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/bcfa61d2df38/pcbi.1010065.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/515bd3708a38/pcbi.1010065.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/ddb1f00ae26f/pcbi.1010065.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/a0a05ad1f2e1/pcbi.1010065.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/517d9044b4c9/pcbi.1010065.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/57dfad5a5211/pcbi.1010065.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/0e3252e2fde8/pcbi.1010065.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/0f907bdf507d/pcbi.1010065.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/ab0527b85df7/pcbi.1010065.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/bcfa61d2df38/pcbi.1010065.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/515bd3708a38/pcbi.1010065.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/ddb1f00ae26f/pcbi.1010065.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/a0a05ad1f2e1/pcbi.1010065.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/517d9044b4c9/pcbi.1010065.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1819/9132324/57dfad5a5211/pcbi.1010065.g009.jpg

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