Using large-scale genomics data to identify driver mutations in lung cancer: methods and challenges

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From: Pharmacogenomics(Vol. 16, Issue 10)
Publisher: Future Medicine Ltd.
Document Type: Report
Length: 9,044 words
Lexile Measure: 1890L

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Author(s): Andrew M Hudson aff1 , Christopher Wirth aff2 , Natalie L Stephenson aff1 , Shameem Fawdar aff3 , John Brognard [*] aff1 , Crispin J Miller [*] aff2

Keywords:

cancer genomics; challenges; driver mutation; genetic dependency screen; in silico analysis; lung cancer

Lung cancer is the most common cause of cancer death in the world; only 16.8% of patients survive to 5 years following a diagnosis of lung cancer [ 1 ]. This is in stark contrast to prostate cancer (98.9% surviving to 5 years) and breast cancer (89.2% surviving to 5 years). A major reason for this disparity is that metastatic disease is diagnosed at presentation in the majority of lung cancer cases. In addition, the median age of lung cancer diagnosis is around 70 years, and patients have often smoked for a large period of their life, making successful treatment of lung cancer patients extremely challenging. As a consequence of smoking, many patients possess severe co-existing medical conditions that preclude them from receiving potentially toxic chemotherapeutic regimens. These patients cannot receive an active anticancer treatment and are only eligible for symptomatic palliation. Further, while some patients will benefit from palliative chemotherapy to extend survival, this is often short-lived and accompanied by toxic side effects. Therefore, the promise offered by targeted therapies, with their better-tolerated side effects, is of particular significance for lung cancer patients.

Most clinically effective targeted therapies rely on disruption of 'oncogene addiction' that occurs through genetic mutation or overexpression of genes conferring tumorigenic properties in line with the hallmarks of cancer [2,3 ]. The success of targeted precision therapies lies in identifying mutated genes that confer a growth or survival advantage (driver mutations) that can be subsequently targeted therapeutically. There have been some notable successes with this approach. EGF receptor (EGFR) inhibitors were first introduced into the clinic for the treatment of non small-cell lung cancer (NSCLC). The IPASS study compared the EGFR inhibitor gefitinib with a standard doublet chemotherapy regimen in patients from East Asia with first-line advanced lung adenocarcinoma [4 ]. It showed superior progression-free survival (PFS) in the gefitinib arm as well as lower rates of severe toxicity. While the study did not stratify treatment based on EGFR mutation status, subgroup analysis showed that EGFR mutation positive patients had longer PFS with gefitinib while EGFR mutation negative patients had longer PFS with standard chemotherapy. The study population, consisting of East Asian never or light-smokers, was enriched for EGFR mutations (59.7%) compared with the heavy smoking population that forms the majority of Western lung adenocarcinoma cases (11% with EGFR mutation) [ 5 ]. Subsequent trials of gefitinib, erlotinib and afatinib have demonstrated superior PFS in EGFR mutation positive patients when compared with standard chemotherapy leading to these agents being routinely used for treatment in EGFR mutation positive patients [6-9 ]. More recently, ALK rearrangements have been identified in approximately 5% of NSCLC [ 10 ]. Again patients with ALK rearrangements are more likely to be never/light smokers [11 ]. Crizotinib, a small-molecule inhibitor of ALK (as well as MET and ROS1...

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Gale Document Number: GALE|A428534844