Abstract:
Recent advances in our understanding of cancer biology and genetics have led to the development of numerous genomic tests exploring somatic and germline mutational profiles as well as gene expression signatures for clinical use. Somatic mutation panels and gene expression signatures are potentially useful to guide cancer treatment, to estimate the risk of recurrence of individual cancers and to screen patients for eligibility to “basket” and “umbrella” oncology clinical trials. Germline tests are increasingly useful to quantify individual risk of malignancy, particularly in patients with informative family histories. Recent success stories have highlighted the power of genomics to inform clinical decisions. The first FDA approval of an anti-neoplastic agent (pembrolizumab) based exclusively on the genomic profile of tumors rather than on tumor site or histology was a landmark in oncology, and very likely the first of many such approvals. The results of large clinical trials like GeparSixto, MINDACT and TAILORx have demonstrated that gene expression signatures can successfully predict the likelihood of complete pathological remission (cPR) in triple-negative and Her2- enriched breast cancers and identify patients who do not require chemotherapy. Virtually every malignancy is now classified into molecular rather than merely histological subtypes, and these subtypes often have strikingly different outcomes. “Liquid biopsies” hold the promise of highly sensitive detection of recurrence and mutational profiling of emerging cancer clones. That said, the field of cancer precision medicine is still in its infancy, and significant challenges remain. Most of the data on which outcome predictions are based derives from European or European-American patients, and is not validated in populations of diverse ancestry. Our own research has shown significant differences in gene expression profiles of breast cancers based on ancestry. For somatic mutation panels, tumor heterogeneity remains a potential confounder. Clonal evolution under therapy-induced selection leads to the emergence of clones with novel driver mutations. Hence, a mutational profile obtained from a surgical specimen in an untreated patient may or may not reflect the molecular portrait of the tumor after multiple cycles of chemo- radio- or targeted therapy. One might argue that longitudinal molecular follow-up of cancers coupled with adaptive treatment strategies will become necessary to obtain the most useful information for patient management. Additionally, novel variants in genes of potential biological importance pose an interpretation challenge. Bioinformatics research is improving tools to predict the biological impact of newly identified mutations in coding as well as non-coding regions of the genome, but these are not yet used in the clinic. That means that variants that may affect tumor response but are not well characterized and included in large databases (e.g., COSMIC) are often classified as “Variants of Unknown Significance” (VUS). The sensitivity of liquid biopsies is influenced by tumor location, tumor burden, background, non-pathogenic mutations in leukocytes and depth of sequencing. Finally, the speed of data interpretation and reporting must be increased if clinical decisions are to be made “in real time” in response to molecular tests. 17th SEP.2018, Monday - 09:00 Page 16 Oncology and Radiology 2nd International Conference on ICOR 2018 From the standpoint of germline genetic risk, outside the well-known group of genes with high penetrance and large effects on risk (e.g., BRCA1/2, PTEN, TP53, PALB2 etc.), the main challenge is the large number and cooperativity of genes with relatively small effects on cancer risk. Individually, many of the genes recently identified have small effects on relative risk. However, these effects may be clinically meaningful when integrated with other information, such as clinicopathological, lifestyle, environmental and socioeconomic factors. “Big data” analytics on large, multidimensional datasets such as the ones expected from the American Cancer Society’s Cancer Prevention 3 or the National Institute of Health’s “All of Us” Precision Medicine initiative will undoubtedly produce breakthroughs in the next few years. In summary, the future of cancer precision medicine and prevention is bright, but the field will require considerable additional clinical, molecular and epidemiological research to reach its full potential to improve our management of cancer at the individual and population levels.
