Cancer Genomics: Technology, Discovery, and Translation

In recent years, the increasing awareness that somatic mutations and other genetic aberrations drive human malignancies has led us within reach of personalized cancer medicine (PCM). The implementation of PCM is based on the following premises: genetic aberrations exist in human malignancies; a subset of these aberrations drive oncogenesis and tumor biology; these aberrations are actionable (defined as having the potential to affect management recommendations based on diagnostic, prognostic, and/or predictive implications); and there are highly specific anticancer agents available that effectively modulate these targets. This article highlights the technology underlying cancer genomics and examines the early results of genome sequencing and the challenges met in the discovery of new genetic aberrations. Finally, drawing from experiences gained in a feasibility study of somatic mutation genotyping and targeted exome sequencing led by Princess Margaret Hospital–University Health Network and the Ontario Institute for Cancer Research, the processes, challenges, and issues involved in the translation of cancer genomics to the clinic are discussed.

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Norwegian Cancer Genomics Consortium: a platform for research on personalized cancer medicine in a public health system

Drug Discovery Today ◽

10.1016/j.drudis.2015.10.003 ◽

2015 ◽

Vol 20 (12) ◽

pp. 1419-1421 ◽

Cited By ~ 3

Author(s):

Ola Myklebost

Keyword(s):

Public Health ◽

Health System ◽

Cancer Genomics ◽

Public Health System ◽

Personalized Cancer Medicine ◽

Cancer Medicine ◽

Personalized Cancer

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The whole-genome panorama of cancer drivers

10.1101/190330 ◽

2017 ◽

Cited By ~ 29

Author(s):

Radhakrishnan Sabarinathan ◽

Oriol Pich ◽

Iñigo Martincorena ◽

Carlota Rubio-Perez ◽

Malene Juul ◽

...

Keyword(s):

Cancer Genomics ◽

Tumor Development ◽

Point Mutations ◽

Driver Mutations ◽

Whole Genome ◽

Cancer Genes ◽

Accurate Identification ◽

Personalized Cancer Medicine ◽

Cancer Medicine ◽

Personalized Cancer

SUMMARYThe advance of personalized cancer medicine requires the accurate identification of the mutations driving each patient’s tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patient’s tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.

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The Concept of Personalized Cancer Medicine with Natural Products

Planta Medica ◽

10.1055/s-0032-1307486 ◽

2012 ◽

Vol 78 (05) ◽

Cited By ~ 7

Author(s):

T Efferth

Keyword(s):

Natural Products ◽

Personalized Cancer Medicine ◽

Cancer Medicine ◽

Personalized Cancer

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Personalized Cancer Medicine in the Media: Sensationalism or Realistic Reporting?

Journal of Personalized Medicine ◽

10.3390/jpm11080741 ◽

2021 ◽

Vol 11 (8) ◽

pp. 741

Author(s):

Katherine Hicks-Courant ◽

Jenny Shen ◽

Angela Stroupe ◽

Angel Cronin ◽

Elizabeth F. Bair ◽

...

Keyword(s):

Personalized Medicine ◽

Media Coverage ◽

Disease Risk ◽

Federal Drug Administration ◽

Personalized Cancer Medicine ◽

The Media ◽

Cancer Medicine ◽

Media Reports ◽

Personalized Cancer ◽

Standard Tests

Background: Given that media coverage can shape healthcare expectations, it is essential that we understand how the media frames “personalized medicine” (PM) in oncology, and whether information about unproven technologies is widely disseminated. Methods: We conducted a content analysis of 396 news reports related to cancer and PM published between 1 January 1998 and 31 December 2011. Two coders independently coded all the reports using a pre-defined framework. Determination of coverage of “standard” and “non-standard” therapies and tests was made by comparing the media print/broadcast date to the date of Federal Drug Administration approval or incorporation into clinical guidelines. Results: Although the term “personalized medicine” appeared in all reports, it was clearly defined only 27% of the time. Stories more frequently reported PM benefits than challenges (96% vs. 48%, p < 0.001). Commonly reported benefits included improved treatment (89%), prediction of side effects (30%), disease risk prediction (33%), and lower cost (19%). Commonly reported challenges included high cost (28%), potential for discrimination (29%), and concerns over privacy and regulation (21%). Coverage of inherited DNA testing was more common than coverage of tumor testing (79% vs. 25%, p < 0.001). Media reports of standard tests and treatments were common; however, 8% included information about non-standard technologies, such as experimental medications and gene therapy. Conclusion: Confusion about personalized cancer medicine may be exacerbated by media reports that fail to clearly define the term. While most media stories reported on standard tests and treatments, an emphasis on the benefits of PM may lead to unrealistic expectations for cancer genomic care.

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