Series 720 www.thelancet.com Vol 382 August 24, 2013 Lung Cancer 2 Genetics and biomarkers in personalisation of lung cancer treatment Rafael Rosell, Trever G Bivona, Niki Karachaliou Non-small-cell lung cancer is often diagnosed at the metastatic stage, with median survival of just 1 year. The identification of driver mutations in the epidermal growth factor receptor (EGFR) as the primary oncogenic event in a subset of lung adenocarcinomas led to a model of targeted treatment and genetic profiling of the disease. EGFR tyrosine kinase inhibitors confer remission in 60% of patients, but responses are short-lived. The pre-existing EGFR Thr790Met mutation could be a subclonal driver responsible for these transient responses. Overexpression of AXL and reduced MED12 function are hallmarks of resistance to tyrosine kinase inhibitors in EGFR-mutant non-small- cell lung cancer. Crosstalk between signalling pathways is another mechanism of resistance; therefore, identification of the molecular components involved could lead to the development of combination therapies cotargeting these molecules instead of EGFR tyrosine kinase inhibitor monotherapy. Additionally, novel biomarkers could be identified through deep sequencing analysis of serial rebiopsies before and during treatment. Introduction Non-small-cell lung cancer is the most frequent type of lung cancer and the most common cause of death from cancer. 1 Poor survival in non-small-cell lung cancer is partly due to the development of drug resistance. Despite extensive research into resistance mechanisms, preclinical data have not been incorporated into the selection of patients or tailored treatment regimens in clinical trials. Therefore, we still do not have an accurate idea of how efficient treatment can be in the right setting. Preselection studies are complicated by the potential occurrence of several different resistance mechanisms, which can affect the optimum biomarkers to use depending on the specific driver gene mutation—a mutation that confers a selective growth advantage to the cell in which it occurs. 2 Until recently, few studies had attempted to preselect patients with specific biomarkers that could predict response to a specific treatment regimen. 3 For example, in patients with non-small-cell lung cancer with epidermal growth factor receptor (EGFR) mutations, the response rate to erlotinib was 58%. 4 Although remissions were transient, with progression-free survival of 9·7 months, 4 this outcome was a substantial improvement over results achieved with chemotherapy. Based on these data, the US Food and Drug Administration approved the use of erlotinib as first- line treatment for non-small-cell lung cancer driven by EGFR mutations. Driver genes can be classified into one or more of 12 signalling pathways that regulate cell fate and survival. 2 The selection of one driver gene mutation for treatment with a matching drug is limited by feedback and crosstalk circuits between signalling pathways. Further research to identify which pathways are activated could lead to targeting of cancer with combination therapies, 5 which will allow patients to live with stable disease for longer. The identification of genetic aberrations that are unique to defined subgroups of patients and the develop- ment of drugs that specifically target oncogenic foci and Lancet 2013; 382: 720–31 See Editorial page 659 This is the second in a Series of three papers about lung cancer Catalan Institute of Oncology Badalona, Spain (R Rosell MD); Breakthrough Cancer Research Unit, Pangaea Biotech, Barcelona, Spain (R Rosell, N Karachaliou MD); Cancer Therapeutics Innovation Group, New York, NY, USA (R Rosell, T G Bivona MD, N Karachaliou); Department of Medicine, Division of Hematology and Oncology, UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA (T G Bivona); and Quirón Dexeus University Hospital, Barcelona, Spain (N Karachaliou) Correspondence to: Dr Rafael Rosell, Head, Medical Oncology Service, Catalan Institute of Oncology, Hospital Germans Trias i Pujol, Ctra Canyet, s/n, 08916 Badalona (Barcelona), Spain [email protected]Key messages • Lung cancer is a serious disease, with chemotherapy providing only limited benefit and short survival times. • Genetic assessment by PCR and sequencing allows the identification of several driver mutations in a meaningful proportion of lung adenocarcinomas. However, many driver alterations are not identified. Only EGFR mutations in lung adenocarcinomas are universally recognised, and treatment with EGFR tyrosine kinase inhibitors is the primary treatment in these cases. KRAS mutations—although frequent—can receive only specific treatment in clinical trials. Recent evidence indicates that the combination of MAP2K inhibitors plus docetaxel could be an optimum synthetic lethal approach. EML4–ALK translocations respond to crizotinib, although screening is still not uniform. ROS and RET translocations require further molecular refinement, and clinical trials are ongoing. • In squamous-cell lung cancer, FGFR1 has been reported as a potential biomarker. However, only a few clinical trials are ongoing, and diagnostic methods need to be standardised. • Mechanisms of resistance and predictive biomarkers need to be identified. • Deep sequencing analysis of tumours from serial rebiopsies could lead to the identification of the altered signalling pathway and the potential discovery of novel driver alterations that could optimise personalised treatment. Search strategy and selection criteria Data for this review were identified by a search of the Medline database with the following search terms in various combinations: ”kinase-driven cancer”, “synthetic lethality”, ”apoptosis”, “signalling pathways”, ”subclones”, ”EGFR”, ”KRAS”, ”BIM”, “erlotinib”, and “acquired resistance”. The search was limited to articles written in English and published in peer-reviewed journals from 1988 onwards. Additional references were taken from review articles and the individual authors’ own publications.
Transcript
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Lung Cancer 2
Genetics and biomarkers in personalisation of lung cancer treatmentRafael Rosell, Trever G Bivona, Niki Karachaliou
Non-small-cell lung cancer is often diagno sed at the metastatic stage, with median survival of just 1 year. The identifi cation of driver mutations in the epidermal growth factor receptor (EGFR) as the primary oncogenic event in a subset of lung adenocarcinomas led to a model of targeted treatment and genetic profi ling of the disease. EGFR tyrosine kinase inhibitors confer remission in 60% of patients, but responses are short-lived. The pre-existing EGFR Thr790Met mutation could be a subclonal driver responsible for these transient responses. Overexpression of AXL and reduced MED12 function are hallmarks of resistance to tyrosine kinase inhibitors in EGFR-mutant non-small-cell lung cancer. Crosstalk between signalling pathways is another mechanism of resistance; therefore, identifi cation of the molecular components involved could lead to the development of combination therapies cotargeting these molecules instead of EGFR tyrosine kinase inhibitor monotherapy. Additionally, novel biomarkers could be identifi ed through deep sequencing analysis of serial rebiopsies before and during treatment.
IntroductionNon-small-cell lung cancer is the most frequent type of lung cancer and the most common cause of death from cancer.1 Poor survival in non-small-cell lung cancer is partly due to the development of drug resistance. Despite extensive research into resistance mechanisms, preclinical data have not been incorporated into the selection of patients or tailored treatment regimens in clinical trials. Therefore, we still do not have an accurate idea of how effi cient treatment can be in the right setting. Preselection studies are complicated by the potential occurrence of several diff erent resistance mechanisms, which can aff ect the optimum biomarkers to use depending on the specifi c driver gene mutation—a mutation that confers a selective growth advantage to the cell in which it occurs.2 Until
recently, few studies had attempted to preselect patients with specifi c biomarkers that could predict response to a specifi c treatment regimen.3 For example, in patients with non-small-cell lung cancer with epidermal growth factor receptor (EGFR) mutations, the response rate to erlotinib was 58%.4 Although remissions were transient, with progression-free survival of 9·7 months,4 this outcome was a substantial improvement over results achieved with chemotherapy. Based on these data, the US Food and Drug Administration approved the use of erlotinib as fi rst-line treatment for non-small-cell lung cancer driven by EGFR mutations. Driver genes can be classifi ed into one or more of 12 signalling pathways that regulate cell fate and survival.2 The selection of one driver gene mutation for treatment with a matching drug is limited by feedback and crosstalk circuits between sig nalling pathways. Further research to identify which pathways are activated could lead to targeting of cancer with combination therapies,5 which will allow patients to live with stable disease for longer.
The identifi cation of genetic aberrations that are unique to defi ned subgroups of patients and the develop-ment of drugs that specifi cally target oncogenic foci and
Lancet 2013; 382: 720–31
See Editorial page 659
This is the second in a Series of three papers about lung cancer
Catalan Institute of Oncology Badalona, Spain (R Rosell MD);
Breakthrough Cancer Research Unit, Pangaea Biotech,
Barcelona, Spain (R Rosell, N Karachaliou MD); Cancer
Therapeutics Innovation Group, New York, NY, USA (R Rosell,
T G Bivona MD, N Karachaliou); Department of Medicine,
Division of Hematology and Oncology, UCSF Helen Diller
Family Comprehensive Cancer Center, University of California,
San Francisco, CA, USA (T G Bivona); and Quirón Dexeus
University Hospital, Barcelona, Spain (N Karachaliou)
Correspondence to:Dr Rafael Rosell, Head, Medical
Oncology Service, Catalan Institute of Oncology, Hospital
Germans Trias i Pujol, Ctra Canyet, s/n, 08916 Badalona
• Lung cancer is a serious disease, with chemotherapy providing only limited benefi t and short survival times.
• Genetic assessment by PCR and sequencing allows the identifi cation of several driver mutations in a meaningful proportion of lung adenocarcinomas. However, many driver alterations are not identifi ed. Only EGFR mutations in lung adenocarcinomas are universally recognised, and treatment with EGFR tyrosine kinase inhibitors is the primary treatment in these cases. KRAS mutations—although frequent—can receive only specifi c treatment in clinical trials. Recent evidence indicates that the combination of MAP2K inhibitors plus docetaxel could be an optimum synthetic lethal approach. EML4–ALK translocations respond to crizotinib, although screening is still not uniform. ROS and RET translocations require further molecular refi nement, and clinical trials are ongoing.
• In squamous-cell lung cancer, FGFR1 has been reported as a potential biomarker. However, only a few clinical trials are ongoing, and diagnostic methods need to be standardised.
• Mechanisms of resistance and predictive biomarkers need to be identifi ed.• Deep sequencing analysis of tumours from serial rebiopsies could lead to the
identifi cation of the altered signalling pathway and the potential discovery of novel driver alterations that could optimise personalised treatment.
Search strategy and selection criteria
Data for this review were identifi ed by a search of the Medline database with the following search terms in various combinations: ”kinase-driven cancer”, “synthetic lethality”, ”apoptosis”, “signalling pathways”, ”subclones”, ”EGFR”, ”KRAS”, ”BIM”, “erlotinib”, and “acquired resistance”. The search was limited to articles written in English and published in peer-reviewed journals from 1988 onwards. Additional references were taken from review articles and the individual authors’ own publications.
their signalling pathways have been achieved in lung adenocarcinomas—fi rst with EGFR mutations and then with ALK gene translocations, with response rates to crizotinib of up to 57%.6 Other druggable targets, also mainly in lung adenocarcinomas, include ROS1 and RET translocations and HER2 (also known as ERBB2), BRAF, PIK3CA, and CTNNB1 mutations.7–10 Mutations of KRAS are not a chemically druggable target but can be treated with synthetic lethal approaches such as the combination of MEK inhibitors plus PIK3CA or AKT1 inhibitors.11
Mutational profi ling of 200 lung adenocarcinomas in Korean patients identifi ed mutations of EGFR in 60·5%, KRAS in 12%, and translocations in ALK, ROS1, and RET in 8·5% of cases. Other mutations were reported at very low frequencies, and potential actionable mutations were unknown in only 13% of cases.12 Similarly, the Centre of Integrated Oncology in Cologne, Germany has also under taken large-scale screening in lung adenocarcinoma and recorded KRAS mutations in a high proportion and EGFR mutations in a lower proportion of cases. They noted BRAF mutations in less than 1% of cases; such mutations can be targeted, and studies of BRAF inhibitors are ongoing.13 Amplifi cation of FGFR1 and mutations of DDR2 are potential new targets in the treatment of patients with squamous cell lung cancer.8,14,15 Many non-small-cell lung cancers still need to be defi ned genetically, and outcomes after chemotherapy have not changed in the past two decades, with median survival of less than 1 year.16,17 Chemotherapy is not curative and its benefi t is measured in months. However, recent evidence shows that chemotherapy removes the incumbent clones, in a “mass extinction” event,18 and shifts the evolutionary landscape, which leads to early relapse because more aggressive subclones arise with high expression of pre-existing NRG1. NRG1 signalling in experimental models can be mediated by either the HER3 or HER4 receptor, and inhibition of this signalling prevents primary tumour growth and enhances the magnitude and duration of response to chemotherapy. These fi ndings create new opportunities to develop strategies that combine chemo-therapy with antibodies that block NRG1, HER3, or HER4 signalling.19 Custom isation of chemotherapy on the basis of the expression of genes involved in DNA damage repair (BRCA1-A complex) has not yet been validated and is not discussed here.20
Compounds with dual inhibition of PIK3CA and MAPK1 (also known as ERK2) or MAPK3 (also known as ERK1) have a broad range of activity in primary patient samples and cell lines that are resistant to conventional treatments. This activity does not rely exclusively on driver mutations or alterations, such as in EGFR, HER2, KRAS, TP53, or PTEN,21 which can help the development of biomarkers with a more general assessment of the propensity of tumour cells to undergo apoptosis, such as basal apoptotic assays.22
The identifi cation of biomarkers based on driver gene mutations is still at an early stage and is presently limited
in clinical practice to non-small-cell lung cancer driven by EGFR mutations.10 Nevertheless, our existing know ledge of cancer genomes and signalling pathways is suffi cient to guide more precise therapeutic inter ven tions.2 This review is therefore structured into seven main sections, each of which discusses a specifi c class of potentially useful biomarkers. We will focus on the role of EGFR mutations, crosstalk between signalling path ways involved in intrinsic and acquired resistance, and potential new clinical strategies. The practical issues of the availability of high-quality tumour DNA, single and multigene assays, quality control, and the monitoring of mutations in circulating DNA23 are beyond the scope of this review.
Basal apoptotic assaysMost chemotherapeutic agents induce apoptosis through two distinct pathways. The extrinsic pathway acts through TNFSF10 (also known as TRAIL). This protein binds to the death receptors TNFRSF10A and TNFRSF10B and recruits the adaptor protein FADD and procaspase 8, which then activates the eff ector caspase 3 to trigger a caspase cascade that leads to apoptosis (fi gure 1). Clinical trials of TNFSF10 need suitable biomarkers, such as mRNA overexpression of the peptidyl O-glycosyltransferase GALNT14, which correlates with TNFSF10 sensitivity in non-small-cell lung cancer.24 GALNT14 and FUT3 or FUT6 are being assessed in phase 2 clinical trials as biomarkers to predict sensitivity to the pro-apoptopic TNFSF10 death receptor agonists dulaner min and drozitumab25 (fi gure 1). Prediction of a response to TNFSF10 therapy could involve screening for markers of sensitivity (eg, high GALNT14 expression), the presence of at least one of the functional TNFSF10 receptors, and low or absent expression of SIX1 (which induces resistance to TNSF10;22 fi gure 1). A TNFSF10-resistant phenotype in non-small-cell lung cancer is also associated with overexpression of PEA15,26 which regulates MAPK1 and MAPK3 localisation, blocks apoptosis27 (fi gure 2), and also seems to regulate cell survival by interfering with both the extrinsic and intrinsic apoptotic path-ways.28 PEA15 is a key regulator in TNFSF10-mediated cell death.
The intrinsic mitochondrial apoptosis pathway is usually activated by DNA damage but can also be activated by caspase 8 (fi gure 1). This pathway is controlled by interactions between the pro-apoptotic and anti-apoptotic members of the BCL2 protein family. One central gene is BCL2L11 (also known as BIM), which encodes BCL2L11, a BH3-only protein member of the BCL2 family. Other key pro-apoptotic BH3-only family members are BID and BBC3. The BH3-only proteins activate cell death either by opposing the anti-apoptotic members of the BCL2 family (BCL2, BCLXL, MCL1, and BCL2A1) or by binding to the pro-apoptotic family members (BAX and BAK1) and directly activating their pro-apoptotic function (fi gure 1). BAX and BAK1 trigger
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release of cytochrome c from mitochondria, where it interacts with APAF1 and caspase 9 to promote the activation of caspase 3 and thus trigger apoptosis. Importantly, several kinase-driven cancers, including chronic myeloid leukaemia and EGFR-driven non-small cell lung cancers, maintain a survival advantage by suppressing BCL2L11 transcription and by targeting the BCL2L11 protein for proteasomal degradation through MAPK-dependent phosphorylation29–32 (fi gure 2). AKT1 or MAP2K inhibitors or chemotherapy can abrogate such events and induce apoptosis through activation of FOXO3 and its targets, including BCL2LL (fi gure 2).
BH3 mimetics that bind to anti-apoptotic BCL2 family members upregulate free BH3-only proteins, including BCL2L11. Gefi tinib combined with the BH3 mimetic ABT-737 increased apoptosis in H1650 cells (which harbour an exon 19 deletion with low BCL2L11 mRNA expression).30 TP53 could also act in a similar way to BH3-only proteins, by liberating apoptotic eff ectors from anti-apoptotic BCL2 family members. The oncogenic transcription factor MYC activates AMP-activated protein kinase, which induces TP53 accumulation in the mitochondria, releasing BAK1 and causing apoptosis.33
Although tumour cells mostly use the MAPK–pro tea-some axis to escape from BCL2L11-induced apoptosis, AKT1 also suppresses the BCL2L11 transcription factor FOXO3 by phosphorylating it (fi gure 2). The amount of BCL2L11 expression can control the fate of tumour cells.34 A new compound, TIC10, upregulates TNFSF10 through indirect inhibition of AKT1 and MAP2K1 (MEK) or
MAPK, leading to activation of FOXO3 (fi gure 2). MAPK and AKT1 usually phosphorylate FOXO3, which down-regu lates it, leading to cell prolifer ation and tumorigenesis (fi gure 2). The phos phorylation events create docking sites for 14-3-3 proteins that bind to FOXO3 and sequester it in the cytoplasm, thereby inhibiting its transcriptional activity. Therefore, TIC10 inhibits FOXO3 phos phoryl-ation, allowing its trans location to the nucleus, where it binds to the TNFSF10 promoter that contains a FOXO binding site. This binding stimulates transcription and translation of TNFSF10, increasing the amount of this protein on the cell surface21 (fi gure 2). Expression of TNFSF10 and FOXO3 mRNA, together with BCL2L11, could provide an initial assess ment of the likelihood of a positive response to targeted treat ments in mutation-driven tumours, includ ing EGFR-driven non-small-cell lung cancers, since amounts of BCL2L11 can aff ect outcome in such tumours treated with EGFR tyrosine kinase inhibitors.35 An inverse relation between miR-494 and BCL2L11 expression has been reported in a group of non-small-cell lung cancer cells. The overexpression of miR-494 in H460 TNFSF10-sensitive cells increased resistance to TNFSF10-induced apoptosis through down-regulation of BCL2L11. Moreover, in the TNFSF10-resistant A549 cell line, the down regulation of miR-494 made A549 more sensitive to TNFSF10-induced apop-tosis. These fi nd ings suggest the existence of a pathway involving MAPK1 and MAPK3, together with BCL2L11 and TNFSF10 (through miR-494), which could enable the development of specifi c thera peutic strategies for lung cancer27 (fi gure 2).
Figure 1: Extrinsic and intrinsic apoptosis pathwaysThe extrinsic apoptotic pathway is triggered by ligand binding to cell-surface receptors. The death-inducing signalling complex promotes activation of caspase 8, which then activates caspase 3. The intrinsic pathway is activated by diff erent apoptotic stimuli that lead to release of cytochrome c from mitochondria and activation of caspase 9. For full details of the pathways, see main text.
MCL1 MCL1
BCL2
BAX
FADDGALNT14BCLXL
Intrinsic pathway
MALAT1
FBXW7
BCL2A1
FUT3/6
ABT-737ABT-263 (navitoclax)
Cytochrome C
APAF1
BID
DulanerminDrozitumab
Extrinsic pathway
ApoptosisApoptosome
Caspase cascade
TNFSF10
TNFRSF10A/TNFRSF10B
Vorinostat
P
BCL2L11
PMAIP1
FRAT2
BBC3BAK1
Procaspase 9Caspase 9
Caspase 3
Procaspase 8
Caspase 8
SIX1
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KRAS-mutant non-small-cell lung cancer and crosstalk of signalling pathwaysKRAS is mutated in roughly 20% of non-small-cell lung cancers. Drug resistance to AZD6244 (selumetinib), a MAP2K1 and MAP2K2 inhibitor, could be related to impaired nuclear localisation of FOXO3, reduced FOXO3-mediated transcriptional activity, and decreased expres sion of the FOXO3 target gene BCL2L1111 (fi gure 2). Paclitaxel and PIK3CA or AKT1 inhibitors (triciribine36) can activate FOXO3 nuclear translocation and thus sensitise selumetinib-resistant cancer cells, which sug gests that combination treatment with either selu metinib plus AKT1 inhibitors or selumetinib plus paclitaxel could overcome resistance to selumetinib.11 Concentrations of nuclear FOXO3 measured by immuno histochemistry, and FOXO3 and BCL2L11
mRNA, could be biomarkers to predict response of KRAS-mutant non-small-cell lung cancers to the combination of PIK3CA or AKT1 inhibitors plus selumetinib, or the combination of selumetinib with docetaxel or paclitaxel (fi gure 2). Results of a recent phase 2 trial in patients with KRAS-mutant non-small-cell lung cancer who did not respond to fi rst-line treatment showed improved progression-free survival in patients treated with selumetinib plus docetaxel com pared with those given selumetinib alone (5·3 vs 2·1 months, HR 0·58, p=0·014).37 These results are similar to those of a coclinical trial in mice with lung cancer harbouring only KRAS mutations,38 although mice with both KRAS and STK11 mutations had primary resistance to the com bination of docetaxel and selu metinib.38 However, mouse models of non-small-cell
Figure 2: Regulation of pro-apoptotic proteins by phosphorylation-dependent ubiquitin–proteasome degradation pathwaysBinding of ligands to EGFR stimulates dimerisation of the receptor and subsequently activates downstream pathways, including the MAPK and PIK3CA pathways. Alternatively, binding of ligands to GPBAR1 raises the intracellular concentration of the second messenger cAMP, which activates PKA to block the activation of MAPK by both inhibiting RAS-dependent activation of RAF1 and by directly downregulating RAF1 kinase activity. For full details of the pathways and their interactions, see main text. EGFR=epidermal growth factor receptor. PKA=protein kinase A.
TrametinibSelumetinibTriciribine
ErlotinibGefitinib
Procaspase 8
FADD
TNFSF10EGF
Cell exterior
Cytoplasm
Nucleus
del19, Leu858 Arg/Thr790Met
EGFR
PIK3CA
AKT1
KRASG12C
BRAFV600E RAF1
MAP2K
Ligands
GPBAR1
G proteins ATP cAMP
TNFRSF10A/TNFRSF10B
MAPK3/1
TNFSF10
ELK1/MED23
Proliferative and antiapoptotic genes
PTEN
PEA15
ASAH1
VemurafenibDabrafenib
TIC10
FOXO3
TIC10
Paclitaxel
Bevacizumab
PDE4 inhibitors
P
P
miR-494 BCL2L11
BCL2L11
VEGFA
VEGFA
PDE4A/D
PKA
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lung cancer with KRAS and STK11 mutations respond to phenformin monotherapy because phen formin induces apoptosis in STK11-defi cient non-small-cell lung cancer cells.39 These fi ndings suggest that com-bination treat ment with metformin has therapeutic potential. Recently, the combination of IGF1R and MAP2K inhibitors success fully inhibited the growth of KRAS-mutant NSCLC cell lines and KRAS-driven lung tumours in transgenic mouse models, which also sug-gests possible new treatments.40
The theory that to combine PIK3CA and MAP2K inhibitors was synergistic in KRAS-mutant lung cancer has been discussed by Engelman and colleagues.41 How-ever, crosstalk between signalling pathways can reduce the effi cacy of MAP2K inhibitors plus docetaxel because of upregulation of the NOTCH pathway. Delta-like or Jagged activate the NOTCH3 receptor in neighbouring cells. Aberrant activation of this receptor, which occurs in 40% of non-small-cell lung cancers, leads to the release of NOTCH intracellular domain and to the overexpression of the downstream eff ector HES1 (fi gure 3). A com bination of a -secretase inhibitor with
erlotinib had an anti-tumour eff ect in vivo and enhanced BCL2L11 expression in a xenograft model with non-small-cell lung cancer H460 cells harbouring KRAS mutations.42 Patients with non-small-cell lung cancer with high expression of nuclear HES1 had shorter overall survival.43 HES1 directly binds to and represses the promoter of DUSP1, leading to MAPK activation (fi gure 3). Treatment with a -secretase inhibitor induced DUSP1 expression and was associated with loss of MAPK phosphorylation and MAPK activity.43 HES1 expression could be a new biomarker to predict the effi cacy of targeted therapy in KRAS-mutant non-small-cell lung cancer. Changes in the NOTCH pathway include the loss of NUMB expression in 30% of non-small-cell lung cancers, and a strong inverse association between mRNA expression of NUMB, which suppresses NOTCH signalling, and HES1 has also been reported44 (fi gure 3).
Other synthetic lethal interventions have been reported in KRAS-mutant tumours. For example, the use of ABT-263 (navitoclax), a chemical inhibitor that blocks BCLXL’s ability to bind to and inhibit pro-apoptotic proteins
Figure 3: Predictors of acquired resistance to targeted therapiesEGFR=epidermal growth factor receptor, HH=Hedgehog. mTOR=mammalian target of rapamycin. aPKC=atypical protein kinase C. NICD=NOTCH intracellular domain.
γ
γ
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(fi gure 1) in combination with a MAP2K inhibitor led to apoptosis in many mutant cell lines. MAP2K inhibition alone cannot induce eff ective apoptosis in KRAS-mutant cancer cells since the induction of BCL2L11 can be neutralised by BCL2L11 binding to anti-apoptotic proteins such as BCLXL. Therefore, the appropriate synthetic lethal treatment could be a combination of MAP2K inhibitors plus drugs such as ABT-263, which targets BCLXL directly.45
The mediator complex is a 26-subunit transcriptional regulator that bridges DNA regulatory sequences to the RNA polymerase II initiation complex.46 Through physical interactions between transcription factors and specifi c mediator subunits, the mediator complex functions as an integrative hub for diff erent signalling pathways.46 MED23 functions as a nuclear downstream target in the RAS–RAF–MAP2K–MAPK pathway and, together with its binding partner ELK1, acts as a crucial regulator in this signalling pathway in tumours with EGFR, RAS, or BRAF mutations47 (fi gure 2). MED23 should therefore be considered as a diagnostic marker in future studies.
Squamous cell carcinomas of the lung can also harbour KRAS mutations, although at lower frequencies (6%).14 Squamous cell lung cancers could be MCL1-dependent, and BCL2L11 concentrations can predict response to com bination therapies with histone de-acetyl ase in hibitors, such as vorinostat, and the BH3 mimetic ABT-737 (fi gure 1). Vorinostat targets MCL1 to disable the axis, releasing BCL2L11 from MCL1 to BCL2 and BCLXL,48 and can also upregulate the BH3-only proteins BCL2L11 and PMAIP1 (also known as NOXA), thereby inducing apoptosis.49 The discovery that MCL1 plays a central part in sequestering BCL2L11 paves the way for combinations targeting both MCL1 and BCL2 or BCLXL survival models. FBXW7 has a pivotal role in the degradation of MCL (it induces FRAT2-dependent phosphorylation of MCL1) and could be an additional biomarker50 (fi gure 1). However, FBXW7 can cause resistance to imatinib in chronic myeloid leukaemia because it maintains the quiescence of leukaemia-initiating cells by reducing the amount of MYC.51 Another molecule of interest is MALAT1, a non-coding RNA. It is a prognostic marker for metastasis and sur-vival in non-small-cell lung cancer52 and can upregulate BCL2 and BCLXL53 (fi gure 1); how ever, its predictive role needs further investigation.
Predictors of acquired resistance to targeted therapies in EGFR-mutant non-small-cell lung cancersSince we are at the beginning of the era of targeted therapies, the mechanisms of resistance have not yet been fully studied and new diagnostic policies, includ ing rebiopsies at the time of clinical progression, are needed. Several mechanisms are believed to be respon sible for acquired resistance to EGFR tyrosine
kinase inhibitors, including the secondary EGFR Thr790Met mutation,10 MET amplifi cation,54 trans for-mation of non-small-lung cancer into small-cell lung cancer,54 and loss of the EGFR mutant allele55 and AXL kinase activation.56 The over expression of AXL had previously been identifi ed in imatinib-resistant gastro-intestinal stromal tumours57 and in trastuzumab-resistant or lapatinib-resistant HER2 breast cancers.58 We have noted that AXL overexpression is a new mechan ism of resistance to EGFR tyrosine kinase inhibitors in EGFR-mutant non-small cell lung cancer.56 Stimulation of the AXL–GAS6 signalling pathway recruits NF-κB59 (fi gure 3). The IκB kinase (IKK) complex is the core element of the NF-κB cascade. IKKs phosphorylate the IκB protein, which results in proteosomal degradation of IκB and nuclear trans location of NF-κB family members, such as RELA and NFκB1, which trigger activation of NFκB anti-apoptopic genes (fi gure 3). We also showed that activation of NF-κB rescued EGFR-mutant lung cancer cells from EGFR tyrosine kinase inhibitor treatment, and reduced expression of NFKBIA was associated with shorter progression-free survival in erlotinib-treated patients with EGFR-mutant non-small-cell lung cancer.60
AXL inhibition blocks interleukin-6 secretion and activation of STAT3 in prostate cancer cells.61 Over-expression of interleukin-6 and STAT3 often occurs in EGFR-mutant cell lines, and tumour growth is inhibited by a pan-JAK inhibitor.62 However, AXL overexpression could be the tip of the iceberg. Many lung tumours express kinases activated above average concentrations, including several receptor tyrosine kinases (MAP2K, ALK, DDR1, ROS1, KDR, IGF1R, PDGFRA, EGFR, and AXL) and non-receptor tyrosine kinases (PTK2, LYN, FYN, HCK, FRK, PTK6, among others).63 Simultaneous coactivation of several receptor tyrosine kinases has been described in some non-small-cell lung cancer cell lines, including A549, which harbours KRAS mutations and overexpresses EGFR, MET, ERBB3, EPHA2, and AXL.64 In several non-small-cell lung cancer cell lines (eg, A549 and H460), a synergistic tumour growth inhibitory eff ect has been achieved by erlotinib combined with an AXL inhibitor.65 The table shows examples of synthetic lethal combinations.
MED12, a component of the mediator complex, modu lates response to inhibitors of EGFR, ALK, and BRAF68 by negatively regulating TGF-βR2. Inhibition of TGF-βR signalling restored drug responsiveness in MED12-defi cient cells; this mechanism could induce synthetic lethality in drug-resistant tumours without MED12.68 Loss of MED12 activates TGF-β collateral signalling of MAP2K and MAPK, consistent with the activity of TGF-β in non-SMAD signalling,73 causing resistance to EGFR, ALK, and BRAF inhibitors in oncogene-driven tumours. The TGF-β inhibitor LY2157299 showed strong synergism with crizotinib or gefi tinib, suppressing the MAPK activation driven by
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MED12 knockdown in H3122 (which harbours the ELM4-ALK rearrangement) and PC9 cells (which harbour EGFR mutations).68 Drug-resistant MED12-knockdown cancer cells showed features of epithelial to mesenchymal transition, with increased vimentin and N-cadherin.68 The prototypic stimulus for epithelial to mesenchymal tran sition is TGF-β, which induces phosphorylation of β-catenin and the subsequent activation of several transcription factors, including SNAI1. Clinical research with sampling from serial biopsies is warranted to confi rm the role of MED12 as a mechanism of resistance in several oncogene-driven tumours.74 As a proof of concept, erlotinib-resistant PC9 cells overexpress TGF-β2 and enhanced motility was inhibited by the combination of erlotinib plus
LY364967, a TGF-βR1 inhibitor69 (table). Other potential drivers of acquired resistance are reviewed elsewhere.9
Acquired resistance related to pre-existing mutationsKRAS mutations have been reported in the plasma of 60% of patients with colorectal cancer with wild-type KRAS tumours treated with cetuximab, and are predictive of shorter progression-free survival.75 The EGFR Thr790Met acquired mutation has been detected in up to 68% of rebiopsies of patients with acquired clinical resistance to EGFR tyrosine kinase inhibitors,76–78 but has also been reported as a pretreatment mutation in as many as 65% of patients.79–82 The presence of this pretreatment mutation has been associated with shorter
Validation of biomarkers Potential therapeutic combinations Clinical trials
Intrinsic apoptopic pathway
MCL1, FBXW7, PMAIP1, BCL2L11 In vitro30, 48–50 Vorinostat plus ABT-737; gefi tinib plus ABT-737 ··
KRAS-mutant tumours: BCLXL, BCL2L11 In vitro and in vivo45 ABT-263 (navitoclax) plus selumetinib ··
Extrinsic apoptopic pathway
TNFSF10, BCL2L11, FOXO3, miR-494 In vitro and in vivo21,27 TIC10 plus EGFR TKIs ··
TNFRSF10A, TNFRSF10B, PEA15 TNFRSF10A, TNFRSF10B: in phase 1 and 2 clinical trials;22 PEA15: TNFSF10 sensitivity in vitro26
Monoclonal antibody TNFRSF10A/TNFRSF10B agonists
Phase 1/222
MAPK/AKT/PRKAA2
FOXO3, BCL2L11, MED23 In vitro34 EGFR TKIs plus taxanes ··
VEGFA, Thr790Met In vitro and in vivo66 Erlotinib plus bevacizumab Ongoing phase 2 BELIEF trial (NCT01562028)
KRAS-mutant tumours: FOXO3, STK11, IGF1R STK11: in vitro and in vivo;38,39 IGF1R: in vitro and in vivo40
Selumetinib/trametinib;selumetinib/trametinib plus triciribine; selumetinib/trametinib plus paclitaxel;phenformin/metformin; IGF1R inhibitors plus selumetinib/trametinib
Phase 237,41
NOTCH3
HES1, DUSP1, NUMB In vitro42–44 EGFR TKIs plus γ-secretase inhibitor ··
TP53
MDM2, PPP1R13L In vitro and in vivo67 BRAF inhibitors plus MDM2 inhibitors plus PPP1R13L inhibitors
··
AXL
AXL, GAS6, RELA, NFκB In vitro and in vivo60,65 EGFR TKIs plus AXL inhibitors ··
IL-6
IL-6, JAK, STAT3 In vitro61,62 EGFR TKIs plus AXL inhibitors; EGFR TKIs plus pan-JAK inhibitors
··
TGF-β
TGF-βR2, MED12ITK phenotype
In vitro68,69 EGFR TKIs plus TGF-β inhibitors ··
HEDGEHOG
GLI1, SOX2, SOX9, CXCR4, FGF19, aPKCl/λ In vitro70 EGFR TKIs plus aPKCl/λ inhibitors ··
mTOR/ RPS6KB1 In vitro71 EGFR TKIs plus mTOR inhibitors ··
cAMP–PKA
PKA, PDE4A/D In vitro72 EGFR TKIs plus PDE4 inhibitors ··
EGFR=epidermal growth factor receptor. TKI=tyrosine kinase inhibitor. aPKC=atypical protein kinase C. mTOR=mammalian target of rapamycin. PKA=protein kinase A.
Table: Potential biomarkers (grouped by pathway) and targeted combination therapies to overcome resistance to targeted monotherapy
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progression-free survival after treatment with EGFR tyrosine kinase inhibitors.79–81,83
Innate resistanceFewer than 60% of EGFR-mutant non-small-cell lung cancers respond to EGFR tyrosine kinase inhibitors, and resistance can be caused by crosstalk between signalling pathways. The assessment of BCL2L11, FOXO3, and TNFSF10 could be tentatively used as an apoptotic assay to predict chances of response. We have reported that in EGFR-mutant patients given erlotinib, the response rate was 100% in those with high BCL2L11 mRNA expression but 30% when BCL2L11 was low,83 and multivariate analysis showed that high BCL2L11 expression was a marker of longer progression-free and overall survival.83 The upregulation of BCL2L11 by ABT737 enhanced the induction of apoptosis by lapatinib in breast cancer cells with HER2 amplifi cation.84 BCL2L11 expression is regulated by the MAPK pathway, which can be cross-regulated by the cAMP pathway, as shown by inhibition of the RAF1 kinase by protein kinase A (PKA), a main eff ector of cAMP.85,86 Upregulation of the tumour-promoting factors PDE4A and PDE4D in lung cancer (including the H1975 cell line) impairs cAMP generation through cAMP hydrolysis, activating the MAPK pathway and thus enhancing VEGFA expression under normoxic conditions72 (fi gure 2). PDE4 inhibition suppresses induction of VEGFA through the PDE4–cAMP–PKA axis. Thus, the use of PDE4 inhibitors, which are used to treat asthma and chronic obstructive pulmonary disease,87 warrants further investigation in conjunction with EGFR tyrosine kinase inhibitors in EGFR-mutant non-small-cell lung cancer. The combination of erlotinib with the VEGF inhibitor bevacizumab inhibited growth of tumours harbouring the Thr790Met mutation.66 As proof of concept, in the ongoing European phase 2 BELIEF trial (NCT01562028), investigators are studying the effi cacy of erlotinib plus bevacizumab in patients with EGFR-mutant non-small-cell lung cancer stratifi ed according to the presence of the Thr790Met mutation.
Additionally, crosstalk between the EGF, NOTCH, Wnt, and Hedgehog pathways could be involved, and downstream components of these pathways, for which MED12 serves as an integrative hub,74 warrant further study. An example is the crosstalk between the Hedgehog and EGFR signalling pathways in diff erent types of Hedgehog-driven tumours.88 Cooperation between Hedgehog and GLI–EGFR synergistically induced the expression of SOX2 and SOX9 (two trans-cription factors involved in the regulation of stem cell fate) and of CXCR4 and FGF1989 (fi gure 3). Simul-taneous stimulation of the Hedgehog–GLI pathway and EGFR signalling syner gistic ally activates the pathways’ cooperation response genes, thereby promoting malignant trans formation (fi gure 3). Recent genome-wide tran scriptional profi ling showed that atypical protein kinase C ι/λ (aPKCι/λ) and SMO control the
expression of similar genes in tumour cells. aPKCι/λ functions downstream of SMO to phosphorylate and activate GLI1, resulting in maximum transcription activation (fi gure 3). Activated aPKCι/λ is upregulated in tumours that are resistant to SMO inhibitors (eg, vismodegib), and targeting of aPKCι/λ suppresses signalling and growth of resistant basal cell carcinoma cell lines70 (fi gure 3). This fi nding shows that aPKCι/λ is crucial for Hedgehog pathway-dependent processes and implicates the molecule as a new tumour-selective therapeutic target for the treatment of SMO inhibitor-resistant cancers70 (table). Furthermore, SMO-indepen-dent stimulation of GLI can occur through interactions with RAS–MAP2K–MAPK and PIK3CA–AKT1 or growth factor pathways such as TGF-β and EGFR signalling.89 Stimulation of MAP2K or MAPK promotes the nuclear import of GLI. The SMO-independent activation of GLI by the mammalian target of rapamycin (mTOR)–RPS6KB1 pathway is sensitive to inhibitors of the mTOR pathway71 (fi gure 3).
Adaptive resistanceAdaptive resistance can occur almost immediately after initiation of targeted therapy through rapid rewiring of cancer cell signalling. When they lose MAPK-negative feedback on receptor tyrosine kinase expression (EGF and FGF),90 cancer cells are exposed to the stimuli of several ligands, and the ensuing activation of several receptor tyrosine kinases reprogrammes all the estab-lished signalling pathways. The overexpression of several receptor tyrosine kinases (EGF, AXL, HER3, FGF, and NRG) was noted in breast cancer cell lines treated with a MAP2K inhibitor91 and in BRAFV600E mela noma cell lines treated with BRAF inhibitors.92 This rebound eff ect of overexpression of several receptor tyrosine kinases, including ERBB3, also occurs in lung cancers driven by KRAS or EGFR mutations when treated with MAP2K, PIK3CA, or dual PIK3CA–mTOR inhibitors.93
We speculate that adaptive resistance occurs rapidly and routinely in a substantial proportion of patients with EGFR mutations. Whole genome sequencing of tumours from serial rebiopsies within hours after initiation of treatment with EGFR tyrosine kinase inhibitors can identify which receptor tyrosine kinases are over expressed after treatment and enable effi cient cotargeting of these molecules, leading to synthetic lethality.
Genetic biomarker identifi cation through deep sequencing analysisThe treatment of genotype-selected patients with non-small-cell lung cancer with genotype-directed treatment almost invariably results in adaptive changes in cell signalling networks that lead to drug resistance. Although several key changes that occur in drug-resistant non-small-cell lung cancers have been identifi ed, we do not have a complete molecular annotation of the changes that mark and drive drug resistance in patients because molecular
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profi ling investigation in drug-resistant non-small-cell lung cancers has, until now, focused on the analysis of a small subset of genes. Furthermore, emerging evidence indicates that substantial genetic heterogeneity exists among and within individual non-small-cell lung cancers. This heterogeneity presents itself as clonal and subclonal mutations in a tumour and provides a potential explanation for both innate and acquired drug resistance.2,9,94 As such, targeted therapy against one genetic change could select for the enrichment or acquisition of a fi tter and more drug-resistant clone, leading to clinical drug resistance. In view of the substantial genetic heterogeneity and plasticity of signalling pathways in individual non-small-cell lung cancers, drug resistance could occur through unexpected genetic changes. Therefore, successful characterisation and therapeutic exploitation of drug resistance bio-markers to overcome resistance will need an unbiased, systematic, and genome-wide analysis of individual tumours in every patient.
Whole exome and transcriptome deep sequencing is a powerful and promising approach to completely molecularly annotate drug response and resistance biomarkers and direct the treatment of patients with non-small-cell lung cancer. The use of deep sequencing analysis in a clinical setting is becoming increasingly feasible because the cost is falling and devices for data analysis and interpretation are evolving and improving rapidly. The many genetic changes discovered in most tumours make it diffi cult to distinguish those that drive tumour initiation, progression, or therapeutic resistance from those that are passengers. Recent data show the usefulness of unbiased functional genomics strategies to complement informatics-based eff orts to identify the drivers of key disease phenotypes.5,45,60 Many of these functional genomics eff orts employ loss-of-function
RNA interference-based screens in patient-derived tumour models to functionally annotate the genetic changes uncovered through genomic analyses of human tumours. Data emerging from functional genomics screening have provided new rationales for clinical trials to test genetically directed therapies to enhance responses or overcome drug resistance in patients.
Deep sequencing analysis of individual tumours can not only identify drug response and resistance bio-markers but also characterise clonal and subclonal genetic populations in the tumour. Whereas whole exome sequencing analysis identifi es structural variants in DNA that are biomarkers of therapeutic sensitivity, transcriptome profi ling off ers the ability to identify genetic programmes and signalling pathways that mark responder and non-responder populations. The orthogonal integration of exome and transcriptome datasets can be used to ascertain the eff ects of somatic changes on transcriptional programmes that dictate therapeutic sensitivity, to provide a more complete map of biomarkers for clinical use. This integrated genomic analysis approach could be applied serially in patients to characterise the molecular natural history of disease in every patient by monitoring drug sensitivity biomarkers in real time (fi gure 4). This approach off ers the potential to use serial biomarker analysis of clinical samples acquired from each patient to direct the initial and subsequent treatment to prevent or overcome drug resistance in patients. Recent work by our groups with use of whole exome and transcriptome sequencing of tumours from serial rebiopsies starting hours after initiation of treatment with an EGFR tyrosine kinase inhibitor has identifi ed molecular biomarkers and signatures of response that include key components of pro-survival and pro-death signalling pathways.95 Indeed, adaptive molecular changes occurred in responders and non-responders after short-term treatment, and those recorded in tyrosine kinase inhibitor-treated patients occurred before any change in tumour size detected by high-resolution CT scan. The serial use of integrated genomic biomarker analysis allows the identifi cation of adaptive changes that occur longitudinally during treatment and thus the identifi cation of changes in both individual molecules and in network level pathways, which are biomarkers of disease course in a patient. Such an integrated molecular annotation of the natural history of disease in individual patients means that mechanism-based therapies to preclude or overcome resistance can be designed.
ConclusionsMolecular genotyping of lung cancer is warranted for diagnosis in metastatic non-small-cell lung cancer. EGFR mutations are detected frequently, especially in adeno-carcinomas of never-smokers, and other rarer genetic subclasses of non-small-cell lung cancer, such as those with ALK rearrangements, are also druggable. Clinical
Figure 4: Integrated genomic analysis to identify biomarkers of drug response and personalise treatment of patients with non-small-cell lung cancerThe serial use of deep sequencing analysis of tumour specimens from patients throughout the natural history of disease, including therapy, can identify molecular biomarkers of response and resistance that can be used to assess therapeutic effi cacy and direct treatment. Diff erent heatmap patterns show the adaptive changes in cell signalling networks that lead to drug resistance.
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trials are needed to validate the effi cacy of targeted therapies, for example in tumours with HER2 insertions and PIK3CA mutations. An ongoing trial is studying the eff ect of dabrafenib in tumours with the infrequent BRAFV600E mutation. Standard care should include acquisition of genomic DNA for adequate genotyping and personalised treatment. The transient responses to EGFR tyrosine kinase inhibitors indicate that genotyping needs to be enriched with additional biomarkers to predict the signalling pathways involved in adaptive resistance, which can then be treated with combinations of targeted treatments. Studies of serial rebiopsies through deep sequencing analysis can further clarify the genomic landscape of non-small-cell lung cancer. Unfortunately, the use of pharmacogenomic markers is still scarce because of issues involving insurance coverage, health regulatory aspects, and hospital policies.96 However, the rapid implementation of multigene assays could help the integrative genetic classifi cation and treatment of non-small-cell lung cancer.ContributorsAll authors contributed to the literature search, fi gures, and writing of the review.
Confl icts of interestRR and TGB are consultants for Cancer Therapeutics Innovation Group. The other authors declare that they have no confl icts of interest.
AcknowledgmentsWork in RR’s laboratory is supported by a grant from LaCaixa Foundation and by a grant from Redes Temáticas de Investigación en Cáncer (RD12/0036/0072). TGB acknowledges research funding support from the following sources: NIH Director’s New Innovator Award, Howard Hughes Medical Institute, Doris Duke Charitable Foundation, American Lung Association, National Lung Cancer Partnership, Sidney Kimmel Foundation for Cancer Research, Searle Scholars Program, Wendell and Eddi Van Auken, and California Institute for Quantitative Biosciences. The funding agencies had no role in the drafting of the report or in the decision to publish.
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