Cancer Genome Landscapes

Cancer Genome Landscapes

2013 March 29 | Bert Vogelstein, Nickolas Papadopoulos, Victor E. Velculescu, Shibin Zhou, Luis A. Diaz Jr., and Kenneth W. Kinzler
The article discusses the genomic landscapes of human cancers, revealing that most cancers have a small number of "driver" genes (genes that promote tumorigenesis) and many "passenger" genes (mutations that do not confer a selective growth advantage). These driver genes are involved in three core cellular processes: cell fate, cell survival, and genome maintenance. Over the past decade, comprehensive sequencing efforts have identified approximately 140 driver genes, with each tumor containing two to eight of these mutations. The remaining mutations are passengers. Driver genes are classified into 12 signaling pathways that regulate these core processes. Understanding these pathways is crucial for cancer research and treatment. The article also discusses the timing of mutations in tumors, noting that mutations occur over time, with the first mutation providing a selective growth advantage to a normal cell. Subsequent mutations lead to clonal expansion, eventually resulting in a malignant tumor. The number of mutations in certain tumors is directly correlated with age, with older individuals having more mutations. The timing of mutations is also relevant to metastasis, which is responsible for most cancer deaths. The article suggests that metastatic lesions may not require additional genetic alterations, as normal cells can grow into organoids under suitable conditions. Other types of genetic alterations in tumors include chromosomal changes, such as aneuploidy, deletions, inversions, and translocations. These changes can affect the expression of genes and contribute to tumorigenesis. The article also discusses the distinction between driver and passenger mutations, noting that driver mutations confer a selective growth advantage, while passenger mutations do not. The article introduces the concept of "Mut-driver genes" and "Epi-driver genes," with Mut-driver genes containing sufficient driver mutations to distinguish them from other genes, while Epi-driver genes are altered through epigenetic changes. The article also discusses the concept of "dark matter" in cancer genomes, referring to mutations that are not easily identifiable due to technical limitations or the complexity of the genome. These mutations may include epigenetic changes that affect gene expression without altering the DNA sequence. The article highlights the importance of understanding these mutations for developing effective cancer treatments. The article concludes by discussing the importance of signaling pathways in tumors, noting that cancer cells rely on a limited number of cellular signaling pathways to promote growth and survival. Understanding these pathways is essential for developing targeted therapies for cancer. The article also discusses the challenges of interpatient heterogeneity in cancer, noting that cancer patients can have different genetic mutations, making it difficult to develop uniformly effective treatments. The article emphasizes the importance of individualized treatments based on the genetic profile of each patient.The article discusses the genomic landscapes of human cancers, revealing that most cancers have a small number of "driver" genes (genes that promote tumorigenesis) and many "passenger" genes (mutations that do not confer a selective growth advantage). These driver genes are involved in three core cellular processes: cell fate, cell survival, and genome maintenance. Over the past decade, comprehensive sequencing efforts have identified approximately 140 driver genes, with each tumor containing two to eight of these mutations. The remaining mutations are passengers. Driver genes are classified into 12 signaling pathways that regulate these core processes. Understanding these pathways is crucial for cancer research and treatment. The article also discusses the timing of mutations in tumors, noting that mutations occur over time, with the first mutation providing a selective growth advantage to a normal cell. Subsequent mutations lead to clonal expansion, eventually resulting in a malignant tumor. The number of mutations in certain tumors is directly correlated with age, with older individuals having more mutations. The timing of mutations is also relevant to metastasis, which is responsible for most cancer deaths. The article suggests that metastatic lesions may not require additional genetic alterations, as normal cells can grow into organoids under suitable conditions. Other types of genetic alterations in tumors include chromosomal changes, such as aneuploidy, deletions, inversions, and translocations. These changes can affect the expression of genes and contribute to tumorigenesis. The article also discusses the distinction between driver and passenger mutations, noting that driver mutations confer a selective growth advantage, while passenger mutations do not. The article introduces the concept of "Mut-driver genes" and "Epi-driver genes," with Mut-driver genes containing sufficient driver mutations to distinguish them from other genes, while Epi-driver genes are altered through epigenetic changes. The article also discusses the concept of "dark matter" in cancer genomes, referring to mutations that are not easily identifiable due to technical limitations or the complexity of the genome. These mutations may include epigenetic changes that affect gene expression without altering the DNA sequence. The article highlights the importance of understanding these mutations for developing effective cancer treatments. The article concludes by discussing the importance of signaling pathways in tumors, noting that cancer cells rely on a limited number of cellular signaling pathways to promote growth and survival. Understanding these pathways is essential for developing targeted therapies for cancer. The article also discusses the challenges of interpatient heterogeneity in cancer, noting that cancer patients can have different genetic mutations, making it difficult to develop uniformly effective treatments. The article emphasizes the importance of individualized treatments based on the genetic profile of each patient.
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