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Genomics driven-oncology: challenges and perspectives


Molecularly defined subgroups of tumors characterized by specific driver mutations have been identified in the majority of cancers. The availability of novel drugs capable of targeting signaling pathways activated by genetic derangements has led to hypothesize the possibility to treat patients based on their genomic profile. A clear example is represented by lung adenocarcinoma for which it has been possible to identify driver genetic alterations in approximately 75% of the cases. Among these, RET fusion transcripts are detectable in about 1–2% of lung adenocarcinomas and might represent targets for therapeutic intervention with RET kinase inhibitors. However, a number of issues need to be addressed to make genomics-driven oncology routinely accessible for cancer patients, including: 1) the availability of novel methods in molecular diagnostics that allow a comprehensive molecular characterization of lung tumors starting from a low input DNA/RNA; 2) identification of reliable and reproducible biomarkers of response/resistance to targeted agents; 3) the assessment of the role of tumor heterogeneity in the response to drugs targeting molecular pathways.

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Somatic alterations of genes involved in the regulation of cell proliferation, differentiation and survival play a pivotal role in the pathogenesis and progression of the majority of human cancers. In many cancer types it has been possible to identify molecularly defined subgroups of tumors that are characterized by driver mutations (genetic alterations causally associated with carcinogenesis) that are often mutually exclusive [1]. An example is represented by the adenocarcinoma subgroup of non-small-cell lung cancer (NSCLC), in which using high throughput technology it has been possible to identify driver genetic alterations in approximately 75% of the cases [2].

The identification of such driver mutations and the availability of novel drugs capable of targeting signaling pathways activated by genetic derangements has led to hypothesize the possibility to treat patients based on their genomic profile (Table 1). An example of this potential approach, defined genomics driven-oncology, is represented by RET rearrangements in lung cancer [3]. Chimeric RET proteins generated by chromosomal rearrangements leading to RET fusion transcripts have been identified in ~1–2% of lung adenocarcinomas but might represent as many as 6–19% of tumors from never-smokers without other driver mutations [3]. Response to treatment with RET inhibitors such as vandetanib or cabozantinib has been reported in selected cases [4-7]. Phase 2 clinical trials of RET kinase inhibitors in lung cancer patients harboring RET rearrangement are ongoing (Table 2). In this regard, a retrospective analysis of RET translocations, gene copy number gains and expression from four randomized trials of vandetanib in NSCLC is published in this issue of BMC Cancer [8]. Noteworthy, this is the first series of patients from clinical trials that have been extensively screened for RET molecular alterations, although retrospectively.

Table 1 Selected genetic alterations representing potential biomarkers in lung adenocarcinoma and related drugs in clinical development
Table 2 Phase II clinical trials of RET tyrosine kinase inhibitors in RET-rearranged lung carcinoma


While the absolute number of RET-positive tumors reported in the paper by Platt et al. [8] is too low to draw any firm conclusion, this study provides important insights of critical discussion that can be generalized to the entire field of genomics-driven oncology:

  1. 1.

    The rate of RET rearrangement in NSCLC was as low as 0.7%, while previous studies have reported frequencies up to 6%. RET rearrangements have been suggested to be more frequent in Asian patients, in non-smoker and in the adenocarcinoma subgroup. Therefore, the selection of the study population might significantly affect the frequency at which RET rearrangements are detected. In addition, RET rearrangement is usually mutually exclusive to other driver mutations, and its frequency results higher in patients that do not harbor the more frequent KRAS and EGFR mutations [3]. Nevertheless, this observation poses a major problem for molecular diagnostics that is common to many cancer types. In fact, the number of potential predictive biomarkers that might offer possibility of therapeutic intervention in lung cancer as well as in other tumor types is increasing exponentially (Table 1). Identification of driver mutations might result in a survival advantage for cancer patients that have access to novel drugs through clinical trials or, in selected cases, to receive an off-label treatment with agents approved for other indications [9]. However, the time, the cost, and the amount of tissue needed for a wide molecular profiling using routine diagnostic methods are not compatible with the standard clinical workup, in particular in lung cancer. In many European countries diagnosis of lung cancer is based in over 50% of the cases on cytology samples or small biopsies that might not be sufficient for analysis of somatic mutations and gene rearrangements in several different genes using sequencing, Real Time PCR and/or FISH. Indeed, a 26.9% failure rate in FISH analysis due to an inadequate number of tumor cells or sample quality was reported by Platt and colleagues [8]. This observation underlines the need for novel methods in molecular diagnostics that allow a comprehensive molecular characterization of lung tumors in the routine clinical workout [10]. In this respect, different methods to detect mutations and fusions using genotyping or targeted next generation sequencing are being explored, and might be ready in a short timeframe for clinical implementation [11-14].

  2. 2.

    Oncogenic pathways can be activated by different molecular mechanisms. Indeed, Platt and colleagues found RET amplification in 2.8% of the cases, low RET gene copy number gain in 8.1%, and RET protein expression in 8.3% [8]. Although the relative low number of positive cases prevents any firm conclusion, the finding that the response rate to vandetanib did not correlate with any of these markers does suggest that they have little predictive utility to identify those patients who will benefit from vandetanib therapy. This observation has two important implications. First, activation of RET through amplification or low copy number gain might not represent a driver molecular alteration in lung cancer. In addition, based on the data presented in this issue of BMC Cancer by Platt et al. [8], immunohistochemical detection of RET protein is not a surrogate of RET rearrangement. In fact, RET protein expression was found in cases that did not harbor RET rearrangement. Surprisingly, no RET protein expression was found in some cases with RET rearrangement. This might be due to technical limitations of the immunohistochemistry protocol. Nevertheless, it might be worth to explore whether protein expression levels might affect response to RET inhibitors in patients with RET rearranged lung tumors.

  3. 3.

    Only three RET-rearrangement positive patients received vandetanib treatment in the trials reported by Platt et al. [8], and this low number does not allow to make any conclusion regarding association of vandetanib treatment with efficacy in the RET rearrangement positive subpopulation. However, it is quite surprising that none of the three vandetanib-treated RET-rearrangement-positive patients had an objective response. Importantly, one patient received a 100 mg dose of vandetanib in the ZODIAC trial. Two patients were treated with the standard 300 mg dose of vandetanib in the ZEPHYR study, and both showed radiologic evidence of tumor shrinkage although a response could not be confirmed at the next visit. The ongoing phase 2 clinical trial of vandetanib in lung cancer patients harboring RET rearrangement is employing a 300 mg dose and will clear out the efficacy of the drug in this subgroup of patients (Table 2). Nevertheless, we have come to expect that a tumor harboring a driver mutation will respond to a specific inhibitor, which was not the case in this study. On the other hand, increasing evidence suggests that tumors, including lung carcinoma, are heterogeneous: many tumors contain several clones of neoplastic cells that accumulate during tumor progression different molecular alterations, which might represent mechanisms of resistance to target-based agents [15]. Therefore, it is possible that even tumors with a driver mutation show resistance to specific inhibitors. Indeed, the response rate of lung cancer patients with EGFR mutations to EGFR tyrosine kinase inhibitors ranged between 56% and 86% in different clinical trials, thus suggesting that primary resistance is a phenomenon common to different tumors with driver mutations [16]. In this regard, a more comprehensive molecular characterization of lung tumors might allow to better identify those patients that will benefit from specific targeted agents.


Identification of relatively rare mutations is transforming tumors with high incidence such as lung adenocarcinoma in some rare diseases, each characterized by a specific molecular alteration. Molecular classification of lung tumors based on driver mutations represents a major challenge for molecular diagnostics, but also an important opportunity for cancer patients to access to novel drugs. In this regard, a number of issues need still to be addressed to make genomics-driven oncology routinely accessible for cancer patients.


  1. Garraway LA. Genomics-driven oncology: framework for an emerging paradigm. J Clin Oncol. 2013;31(15):1806–14.

    Article  PubMed  Google Scholar 

  2. Network TCGAR. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511(7511):543–50.

    Article  Google Scholar 

  3. Mulligan LM. RET revisited: expanding the oncogenic portfolio. Nat Rev Cancer. 2014;14(3):173–86.

    Article  CAS  PubMed  Google Scholar 

  4. Drilon A, Wang L, Hasanovic A, Suehara Y, Lipson D, Stephens P, et al. Response to Cabozantinib in patients with RET fusion-positive lung adenocarcinomas. Cancer Discov. 2013;3(6):630–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Falchook GS, Ordonez NG, Bastida CC, Stephens PJ, Miller VA, Gaido L, et al. Effect of the RET Inhibitor Vandetanib in a Patient With RET Fusion-Positive Metastatic Non-Small-Cell Lung Cancer. J Clin Oncol 2014. [Epub ahead of print]

  6. Gautschi O, Zander T, Keller FA, Strobel K, Hirschmann A, Aebi S, et al. A patient with lung adenocarcinoma and RET fusion treated with vandetanib. J Thorac Oncol. 2013;8(5):e43–4.

    Article  PubMed  Google Scholar 

  7. Mukhopadhyay S, Pennell NA, Ali SM, Ross JS, Ma PC, Velcheti V. RET-Rearranged Lung Adenocarcinomas with Lymphangitic Spread, Psammoma Bodies, and Clinical Responses to Cabozantinib. J Thorac Oncol. 2014;9(11):1714–9.

    Article  CAS  PubMed  Google Scholar 

  8. Platt A, Morten J, Ji Q, Elvin P, Womack C, Su X, et al. A retrospective analysis of RET translocation, 1 gene copy number gain and expression in NSCLC patients treated with vandetanib in four randomized Phase III studies. BMC Cancer 2014.

  9. Kris MG, Johnson BE, Berry LD, Kwiatkowski DJ, Iafrate AJ, Wistuba II, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. Jama. 2014;311(19):1998–2006.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Normanno N, Rachiglio AM, Roma C, Fenizia F, Esposito C, Pasquale R, et al. Molecular diagnostics and personalized medicine in oncology: challenges and opportunities. J Cell Biochem. 2013;114(3):514–24.

    Article  CAS  PubMed  Google Scholar 

  11. Lira ME, Choi YL, Lim SM, Deng S, Huang D, Ozeck M, et al. A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer. J Mol Diagn. 2014;16(2):229–43.

    Article  CAS  PubMed  Google Scholar 

  12. Magdaleno SM, Cheng A, Petraroli R, Sheils O, Tops B, Corre DL, et al. Abstract 3575: The OncoNetwork Consortium: A global collaborative research study on the development and verification of an Ion AmpliSeq RNA gene lung fusion panel. Cancer Res. 2014;74:3575.

    Article  Google Scholar 

  13. Ciardiello F, Normanno N, Maiello E, Martinelli E, Troiani T, Pisconti S, et al. Clinical activity of FOLFIRI plus cetuximab according to extended gene mutation status by next-generation sequencing: findings from the CAPRI-GOIM trial. Ann Oncol. 2014;25(9):1756–61.

    Article  CAS  PubMed  Google Scholar 

  14. Scarpa A, Sikora K, Fassan M, Rachiglio AM, Cappellesso R, Antonello D, et al. Molecular typing of lung adenocarcinoma on cytological samples using a multigene next generation sequencing panel. PLoS One. 2013;8(11):e80478.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501(7467):338–45.

    Article  CAS  PubMed  Google Scholar 

  16. Rossi A, Pasquale R, Esposito C, Normanno N. Should epidermal growth factor receptor tyrosine kinase inhibitors be considered ideal drugs for the treatment of selected advanced non-small cell lung cancer patients? Cancer Treat Rev. 2013;39(5):489–97.

    Article  CAS  PubMed  Google Scholar 

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N. Normanno is supported by a grant from the Associazione Italiana per la Ricerca sul Cancro (AIRC) - Grant number: IG12118.

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Correspondence to Nicola Normanno.

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NN and IAC prepared the main text, discussion and conclusion. Both authors read and approved the final manuscript.

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Normanno, N., Cree, I.A. Genomics driven-oncology: challenges and perspectives. BMC Cancer 15, 141 (2015).

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