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Keywords:

  • rapalogs;
  • endometrial cancer;
  • predictive biomarkers;
  • metformin;
  • stathmin

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

BACKGROUND

Targeting the phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway is of increasing interest as a therapeutic strategy in many tumors. The aim of this study was to identify molecular markers associated with mTOR inhibitor activity in women with metastatic endometrial cancer.

METHODS

Archival tumor samples were collected from 94 women with recurrent or metastatic endometrial cancer who participated in 3 National Cancer Insitute of Canada Clinical Trials Group phase 2 trials investigating single-agent mTOR inhibitors: IND160A and IND160B (temsirolimus) and IND192 (ridaforolimus). Analyses included mutational profiling using the OncoCarta Panel version 1.0 and immunohistochemical expression of the tumor suppressor gene PTEN (phosphatase and tensin homologue) and stathmin, a marker of PI3K activation. Associations between biomarker results and clinical outcomes were assessed.

RESULTS

Mutations were found in 32 of 73 analyzed tumors, PIK3CA (21 patients) was the most common mutated gene. Co-mutations were seen in 8 tumors, most frequently KRAS and PIK3CA (4 cases). PTEN loss was observed in 46 of 85 samples analyzed and increased stathmin expression was observed in 15 of 65 analyzed samples. No correlation was observed between biomarkers and response or progression. In patients taking concurrent metformin, there was a trend toward lower progression, of 11.8% versus 32.5% (P = .14).

CONCLUSIONS

No predictive biomarker or combination of biomarkers for mTOR inhibitor activity were identified in this study. Restriction and enrichment of study entry, especially based on archival tumor tissue, should be undertaken with caution in trials using these agents. Cancer 2014;120:603–610. © 2013 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

Targeting the phosphatidylinositol-3 kinase/serine-threonine kinase (PI3K) mammalian AKT target of rapamycin (mTOR) pathway (Fig. 1) has emerged as an interesting potential therapeutic strategy in many cancers.[1-3] Rapalogs, a class of agents which partially inhibit mTORC1 (part of the MTOR complex), demonstrate clinical activity and generally favorable toxicity profiles.[1-3] Agents from this class have been approved for the treatment of advanced renal cell carcinoma[2] and mantle-cell lymphoma.[3] The clinical benefit associated with rapalogs, as with other pathway-targeting agents, is typically limited to a subset of patients. It has been suggested that patients who benefit from drugs that inhibit the PI3K/AKT/mTOR pathway can be identified by specific protein expression and genomic mutational profiles.[5, 6] As a result, efforts to stratify, and even preselect, patients receiving treatment with mTOR (and PI3K) inhibitors based on specific biomarkers, with the goal of optimizing clinical outcomes, has not only been proposed but is being incorporated into many clinical trial designs.

image

Figure 1. MTOR/PI3K/Akt signaling pathway.

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Women with locally advanced recurrent or metastatic endometrial cancer are incurable and have a poor prognosis.[7-13] Hormonal agents, used in the most common type of endometrial cancer (type I or those with endometrioid histology), have modest efficacy and median survival is short, 7 to 12 months.[7-11] Combination chemotherapy regimens produce objective response rates of approximately 50% to 60% but are often poorly tolerated by a predominantly older population and overall survival is short.[12, 13] Activation of the PI3K/AKT/mTOR pathway (Fig. 1) is a frequent event in endometrial cancers. Loss of expression of tumor suppressor genes including phosphatase and tensin homologue (PTEN) occurs in more than 50% of patients.[14, 15] In addition, loss of tuberous sclerosis complex, TSC1 and TSC2 (13%) and LKB are frequently occurring events.[16] Activating mutations and amplification of PIK3CA, predominantly in the catalytic subunit p110α, occur in 36% of tumors.[17, 18] Mutations in other pathway members including AKT are also common. Inhibitors of this pathway have thus been of interest to evaluate in endometrial cancer.

Between May 2004 and June 2007, 94 women were enrolled in 3, sequential studies conducted by the National Cancer Institute of Canada Clinical Trials Group (NCIC CTG). IND160A and IND160B trials investigated the intravenous (IV) rapalog temsirolimus in women who were either chemotherapy-naive (IND160A) or who had received 1 prior line of chemotherapy for metastatic disease (IND160B).[1] IND192 investigated the rapalog ridaforolimus in a similar population of women, allowing prior adjuvant chemotherapy as part of eligibility criteria.[19] All 3 studies shared a common primary endpoint (Response Evaluation Criteria In Solid Tumors [RECIST]-evaluated response rate [RR]). All patients were treated to progression, and response was evaluated every 8 weeks (Fig. 2). None of the studies preselected patients based on histological or biomarker profile, and access to archival tissue (taken at the time of diagnosis) was required for study entry. Overall, single-agent mTOR inhibition showed promising activity in endometrial cancer. The 18% rate of progression observed in IND160A was the lowest seen in endometrial cancer studies. Many patients had prolonged stable disease (SD), of 69% over 9 months.[1, 19]

image

Figure 2. (A) Study schema. (B) Samples available from the studies for analysis.

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Use of the oral antihyperglycemic metformin has been proposed as having anticancer properties and is currently being actively investigated in preclinical and clinical trials as an anticancer agent. Metformin is associated with the activation of the adenosine monophosphate (AMP)-kinase pathway and the suppression of mTOR and S6 kinase (S6K) activation.[20] Diabetes is a common diagnosis in women with endometrial cancer. For that reason, we were interested to see if patients in whom metformin was being given at the time of initiation of rapalog therapy had any evidence of greater clinical activity.

We had previously examined immunohistochemical (IHC) expression of PTEN, pmTOR, cytoplasmic and nuclear phosphorylated AKT (pAKT), and phosphorylated S6, in archival tumor tissue from patients enrolled on IND160A and IND160B, but no correlations between these markers and outcome were seen.[1] In this report, we have pooled the cases from all 3 trials to undertake further studies including mutational analyses, using the OncoCarta version 1.0 panel (Sequenom, San Diego, Calif) and IHC measures of stathmin. This larger data set, which also includes PTEN expression and clinicopathological variables, was then used to explore associations between multiple molecular and other baseline measures with response and nonprogression to mTOR inhibitor therapy.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

Diagnostic archival formalin-fixed paraffin-embedded (FFPE) tumor samples from patients participating in closed NCIC CTG studies with temsirolimus, IND160A and IND160B and with ridaforolimus IND192 were obtained. All samples underwent specialist (B.C.) pathological review. Sequenom mutational analysis, expression of stathmin, and expression of PTEN was undertaken on available tissue. All these studies had full ethics board approval at each of the participating institutions, and patients signed written informed consent before study entry, which included use of tissue samples.

Mutational Analysis (OncoCarta, Version 1)

The OncoCarta Panel version 1.0 (Sequenom) consists of 24 multiplexed assays, and can detect 238 mutations in 19 oncogenes: ABL-1, AKT1, AKT2, BRAF, CDK-4, EGFR, ERBB2, MET, HRAS, KRAS, NRAS, PDGFRα, PIK3CA, RET, FGFR1, FGFR3, JAK-2, KIT, and FLT3. A total of 10 to 20 ng of input DNA was used in each of 24 assays. In order to analyze the mutation status of each patient's tumor, 5 to 10 unstained sections and one hematoxylin and eosin slide were generated from the most representative paraffin block containing tumor. All tissue samples were reviewed by a pathologist who identified areas of tumor on the hematoxylin and eosin slide. This area was then macrodissected to ensure enrichment for tumor DNA. After macrodissection, tissues were deparaffinized with xylene then treated with proteinase K treatment prior to DNA extraction. DNAs were amplified using the OncoCarta PCR primer mix, and a single base extension reaction performed using extension primers that hybridize immediately adjacent to the mutation. Multiplexed reactions were spotted onto a chip and peaks with different mass resolved by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) on a Mass Array Compact Analyzer. Mutation calling was determined by using data generated from Typer Analyzer software as well as manual analysis. Our laboratory is a CAP/CLIA-certified laboratory. We are thus very familiar with the use and limitations of this technology. Other mutations to be evaluated using this platform include KRAS, NRAS, MET, PIK3CA, AKT1/2 beta catenin, and p10 recurrent mutations. All mutations were confirmed by Sanger sequencing.

PTEN Immunohistochemistry

FFPE tissue sections from archival surgical blocks were dewaxed in xylene and rehydrated through graded alcohol to water. Endogenous peroxidase was blocked in 3% hydrogen peroxide. Heat-induced epitope retrieval was carried out in 10 mM citrate buffer, pH 6.0 in a Milestone T/T Mega microwave oven. After blocking for endogenous biotin (Vector Laboratories) sections were incubated in primary antibody (anti-PTEN, rabbit monoclonal from Cell Signaling Technology, 1:200 dilution) for 16 hours at room temperature in a moist chamber. Following washing in phosphate-buffered saline, secondary incubations were carried out in biotin conjugated anti-rabbit IgG (Vector Laboratories) and streptavidin-HRP (horseradish peroxidase) (ID Labs Inc.) for 30 minutes each. Immunoreactivities were revealed by incubation in NovaRed substrate (Vector Laboratories) for 5 minutes. Slides were counterstained in Mayer's hematoxylin and mounted with Permount.

Tumor cells were scored for PTEN immunoreactivity based on predominant staining intensity and percentage of tumor cells showing staining by 2 independent observers. Tumors were scored as PTEN-negative when there was complete absence of nuclear or cytoplasmic staining in the tumor cells, and positive staining in stroma, lymphocytes, or normal endometrial cells present in the same section.

Stathmin Immunohistochemistry

Antigen retrieval was done by microwaves for 20 minutes in TRS at pH 6. Slides were blocked for peroxidase (Dako S2032) for 8 minutes and incubated for 60 minutes at room temperature with a polyclonal Stathmin antibody (3352 Cell Signaling Technology), diluted 1:50. Staining procedures were carried out manually. The Envision+rabbit HRP-labeled polymer method was used for adding secondary antibody as recommended by DakoCytomation. Finally, slides were briefly counterstained with Dako Real Hematoxylin. Samples were blinded and scored as previously described using a staining index calculated as the product of staining intensity and staining area, range = 0-9: incorporating staining intensity (score 0-3) and area of tumor with positive staining (0, no staining; 1, < 10%; 2, 10%-50%, and 3, > 50% of tumor cells) and the index was categorized as no staining = 0; weak = 0-3; moderate = 3-6; or strong positive = 6-9. Applying 6-9 as cutoff for stathmin overexpression, interobservation k was 0.73.[21]

Statistical Analysis

This study was hypothesis-generating, and Fisher's exact test was used to assess the correlation between the results of the various mutational and expression assays, tumor grade, and histologic type with clinical outcome. For the clinical outcome variable, we examined both response versus nonresponse and progression versus nonprogression as dependent variables. Comparisons included only those patients who were evaluable for the molecular test result.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

Ninety-four tumor samples were obtained from patients enrolled in IND160A (33 patients), IND160B (27 patients), and IND192 (34 patients). Because of quality and quantity of FFPE tissue submitted and minimal assay requirements, not all analyses could be performed in all 94 cases. As shown in Table 1 and Fig. 2B, mutational analysis was available from 73 patient samples, PTEN IHC from 85, and stathmin IHC from 65 patient samples. Central pathological review was available for 93 patient samples. Patient characteristics are also shown in Table 1. For the purpose of this report, a combined database of all 3 trials was created which included all baseline and treatment variables, study toxicity information and treatment, and best independent radiology-reviewed RECIST response. In the combined data set, the overall confirmed response rate was 8.5% (8 patients); SD was seen in 53% (50 patients) and progressive disease (PD) in 29% (27 patients). The median duration of SD was 6.6 months (range, 2.2-24 months).

Table 1. Patient Characteristics
CharacteristicN = 94 (%)
  1. Abbreviations: IHC, immunohistochemistry; PD, progressive disease; PR, partial response; PTEN, phosphatase and tensin homolog; SD, stable disease.

Age, y 
Median63
Range41-89
Histological subtype 
Endometrioid66 (70)
Serous12 (13)
Clear cell4 (4)
Unknown12(13)
Tumor grade 
134 (36)
217 (18)
315 (16)
N/A28 (30)
Study 
IND160A33 (35)
IND160B27 (29)
IND19234 (36)
Response 
PR8 (8.5)
SD50 (53)
PD27 (29)
Prior therapy 
Chemotherapy37 (39)
Hormonal therapy30 (32)
Radiotherapy56 (60)
Other5 (5)
Use of metformin 
Yes17 (18)
No77(82)
Archival tissue 
Mutational analysis73 (78)
PTEN IHC85 (90)
Stathmin IHC65 (69)

Mutational Analysis and Outcome

Mutations were identified in 32 (43.8%) of the 73 patient samples analyzed. Mutations most commonly occurred in PIK3CA (21 patients), where 7 different activating mutations were seen, followed by KRAS (10 patients) (Table 2). Co-mutations were observed in 9 tumor samples, and 8 patients with PIK3CA mutations also had mutations in other genes (Table 2). No significant association was seen between the presence (or absence) of mutation or with specific gene mutations and either response or progression (Table 2). Because PIK3CA mutations were of particular interest, the waterfall plot (Fig. 3A) illustrates the pattern of mutations observed compared to best tumor response for all analyzed patients. Figure 3B illustrates duration of therapy in relation to PIK3CA mutation and in relation to the presence of RAS co-mutations.

Table 2. Mutational Analysis and Association With Outcomes Among 73 Evaluable Patients
Mutation GroupNo. (%a)Response (%b)PProgression (%b)P
  1. a

    Of 73 evaluable patients;

  2. b

    Of patients in each group.

Any mutation  1.00 1.00
Yes32 (43.8)3 (9.4) 10 (31.3) 
No41 (56.2)4 (9.8) 13 (31.7) 
PIK3CA mutation  .40 .79
Yes21 (28.8)3 (14.3) 6 (28.6) 
No52 (71.2)4 (7.7) 17 (32.7) 
Type of PIK3CA mutation     
R88Q7 (9.6)    
H104R6 (8.2)    
E545K4 (5.5)    
C420R2 (2.7)    
H1047L1 (1.4)    
P539R1 (1.4)    
E542K1 (1.4)    
KRAS mutation  .58 .49
Yes10 (13.7)0 (0.0) 2 (20.0) 
No63 (86.3)7 (11.1) 21 (33.3) 
MET mutation  .34 1.00
Yes4 (5.5)1 (25.0) 1 (25.0) 
No69 (94.5)6 (8.7) 22 (31.9) 
NRAS mutation  1.00 .55
Yes3 (4.1)0 (0.0) 0 (0.0) 
No70 (95.9)7 (10.0) 23 (32.9) 
AKT1 mutation  1.00 1.00
Yes3 (4.1)0 (0.0) 1 (33.3) 
No70 (95.9)7 (10.0) 22 (31.4) 
EGFR  .10 1.00
Yes1 (1.4)1 (100.0) 0 (0.0) 
No72 (98.6)6 (8.3) 23 (31.9) 
Co-mutations   
PIK3CA + KRAS4(5.5)  
PIK3CA + KRAS + MET1 (1.4)  
PI3KCA + NRAS1 (1.4)  
PIK3CA + EGFR1 (1.4)  
PI3KCA + MET1 (1.4)  
AKT1 + MET1 (1.4)  
image

Figure 3. (A) Waterfall plot for best response showing tumors with PIK3CA mutation. (B) Duration of therapy with PIK3CA and RAS mutations shown.

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PTEN Expression and Outcome

Forty-six (54.1%) of the 85 evaluable patient samples examined had lost expression of PTEN (Fig. 4A,B). There was no association between response (P = .46) or progression (P = .35) and loss of PTEN expression as shown in Table 3.

Table 3. Association of PTEN (Phosphatase and Tensin Homologue) and Stathmin Expressions, Histology Subtype (by Central Pathology Review), and Use of Metformin With Outcomes
GroupNo.Response (%a)PProgression (%a)P
  1. a

    Of patients in each group

PTEN expression  0.46 .35
Negative463 (6.5) 12 (26.1) 
Positive395 (12.8) 14 (35.9) 
Stathmin expression  0.89 .34
Negative20 (0.0) 1 (50.0) 
Weak212 (9.5) 5 (23.8) 
Moderate272 (7.4) 7 (25.9) 
Strong152 (13.3) 7 (46.7) 
Histologic subtype  0.74 .69
Endometrioid666 (9.1) 19 (28.8) 
Clear cell40 (0.0) 0 (0.0) 
Serous122 (16.7) 3 (25.0) 
Use of metformin  0.34 .14
Yes173 (17.7) 2 (11.8) 
No775 (6.5) 25 (32.5) 

Stathmin Expression and Outcome

Twenty-three patients (35.3%) of the 65 patient samples examined had weak (21 patients) or no (2 patients) staining for stathmin, 27 (41.5%) were moderately positive, and 15 (23.1%) had strong positive staining for stathmin. In line with previous studies (28), there was no association between the level of stathmin expression and the presence or absence of PIK3CA mutations P = .75. Furthermore, there was no association between stathmin expression and response (P = .89) or progression (P = .34) (Table 3).

Histology and Outcome

No association was seen between histological subtype and response (P = .74) or progression (P = .69). No association was seen with tumor grade and response (P = 1.0) or progression (P = .69) (Table 3).

Metformin Use and Outcome

A total of 17 women reported using metformin during the 3 clinical trials. There was no statistical association with response or progression; however, numbers were low (Table 3).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

This is the largest comprehensive analysis of samples obtained from patients with endometrial cancer who were enrolled in single-agent rapalog studies. Patients were followed in a uniform manner, and tissue was available from nearly all cases. Analysis of tissue for previously documented activating mutations in the PI3K/AKT/mTOR and the related mitogen-activated protein kinase (MAPK) pathway together with PTEN loss and stathmin, a suggested surrogate marker of PI3K activation and PTEN loss, were performed. Robust assays were used and analyses were conducted in CAP/CLIA-certified laboratories. Mutations were found in 43.8% of evaluable patient samples, and mutation in PIK3CA was the most commonly identified (28.8% of evaluable patients). PTEN expression was lost in 54% of evaluable patients and strong staining for stathmin seen in 23.1% of evaluable cases. These data are consistent with previously reported findings in endometrial cancer.[14-18]

Although the study included only 94 patients and between 65 and 85 samples were analyzed for the markers of interest, we would have 80% power to detect, at a 2-sided 5% significance level, a difference in response rate (RR) between 35% and 40% among 2 marker subgroups when the RR in the group with lower response is approximately 10% or a difference in PD rate approximately 30% when the lowest PD rate in the groups is approximately 20%. Despite this, and despite the large number of biologically plausible markers studied, not one showed a significant association with treatment outcome.

Co-mutations are common in endometrial cancer.[23, 24] Simultaneous mutations in PIK3CA and the MAPK pathway (KRAS, NRAS) have been proposed as mediators of resistance to mTOR (and PI3K) inhibitors.[4, 5] In our study, coexisting mutations occurred in 9 tumor samples. The most common co-mutations were in PIK3CA and KRAS, with one mutation occurring in NRAS. Figure 3B suggests that although PIK3CA/KRAS mutations do appear to occur in the lower half of the plot, where duration of therapy is shorter, there is a range and not all patients appear to be demonstrating resistance. Increased sensitivity to mTOR inhibitors has been proposed for tumors with PIK3CA mutations which have lost PTEN expression.[25] In our series, although the patient with the PIK3CA mutation who remained on treatment for the longest period (96.3 months) had lost PTEN expression, there did not appear to be any noticeable pattern in the other patients. These observations are limited by the fact that duration of therapy may not reflect treatment effect but underlying tumor biology. There have been suggestions that a combination of a genetic defect (PIK3CA mutation or PTEN mutation/loss) and a functional output (pAKT, pMTOR, or pS6 for example) might be more reliable in identifying a predictive signature. Previously, in a limited subset of patients, we failed to identify an association between outcome and pAKT, pmTOR, or pS6.[1] There are, however, limitations in examining phosphoprotein expression in archival FFPE samples. Ideally, these types of analyses would be performed on fresh tissue collected under rigorously controlled conditions. In terms of this article, we are also aware of the risks inherent in “overanalyzing” our data given that multiple testing is likely, by chance, to produce a significant result.

PIK3CA mutations appear to cluster in patients showing a reduction in tumor size (Fig. 3A) but this did not, however, necessarily translate into a clear relationship between mutational status and RECIST defined response or nonprogression. Rapalogs are incomplete MTORC1 inhibitors and lead to activation of AKT and other pathways potentially allowing escape from the growth inhibitory effects of the drug.[26]

These analyses were conducted on archival, diagnostic samples. Although this has been a successful strategy in some tumor types,[27-31] the possibility of discordance between the mutational and proteomic profiles of tumor samples taken at diagnosis and recurrence exists. A change in stathmin expression was reported for 31% of paired endometrial tumor samples taken at diagnosis and recurrence.[27] It is therefore possible that stathmin expression might correlate with response if analyzed in samples taken just prior to treatment. However, stathmin expression does not correlate with PIK3CA mutation in this analysis.. To optimize the potential for future correlative research, clinical trials should be designed incorporating tumor sampling prior to commencing a new therapy, and preferably sequential specimen collection during treatment and at the time of progression. Furthermore, recent data suggest that the search for predictive (and potentially prognostic) biomarkers may be further complicated not only by temporal but also by spatial tumoral heterogeneity.[28] This potentially poses even greater challenges when designing and evaluating, tissue based, biomarker studies.

Although extensive, our interrogation of the genome in these samples was not all inclusive. The PIK3CA mutations included in the OncoCarta panel encompass the commonly found mutations in the catalytic p110α subunit. However, it does not include some of the less frequently occurring mutations in P110α or those occurring in the regulatory subunit p85. A small number of the samples, therefore, may have been misclassified as nonmutated when in fact a mutation existed that was not evaluated as part of the panel. Whole-genome sequencing would almost certainly have yielded more findings of mutations within molecular components of the PI3K or ras/raf/MEK pathways, but would also have brought greater complexity in terms of analysis.

Stathmin expression in this study was not associated with either PIK3CA mutations or clinical outcomes. Clinical trials of PI3K inhibitors are evaluating potential preselection of patients based on mutation status and stathmin expression in archival tissue. Our data suggest this may be premature.

Seventeen women in our study reported that they took metformin while participating in these trials. No statistically significant association of response or nonprogression with metformin use was seen; however, the observed results showed a numerically lower proportion of metformin users versus nonusers with a best response of progression (11.8% versus 32.5%, respectively) (Table 3), suggesting that further investigation is warranted. Numbers, however, were low and metformin use was self-reported, so these results should be interpreted with caution.

Identifying patients who may (or more importantly may not) benefit from a specific therapeutic strategy or molecularly targeted agent is conceptually very attractive. Proof of principle for this approach comes from a number of solid tumors, including colorectal cancer (KRAS mutations and lack of efficacy of EGFR-targeting agents),[28] and lung cancer (EML4-ALK translocations and response to ALK inhibitors.[27] These markers have been identified in archival tissue. This approach may not be successful for all targeted agents and may in fact only apply to a minority. Agents targeting pathways with pleiotropic interactions and effects such as those targeting the PI3K/AKT/mTOR pathway not only have direct effects within tumor cells but effect angiogenesis, immune response and other tumor microenvironment interactions. It is therefore possible that there may not be a single (or even double) biomarker of sensitivity but rather a predictive molecular signature. It is imperative that future trials incorporate high quality correlative studies to explore this. Continued longitudinal profiling will be essential to further improve our understanding of the basis for mechanisms of drug resistance and response.

The ability to use genetic or proteomic markers to identify which patients will most (or least) benefit from molecularly targeted drugs is key if we are to optimize and rationalize the use of the plethora of agents currently entering the clinic. However, it is vital that we recognize that “what we think we know” is not always what there is to know about these pathways, the tumor (and its environment) or the action of the agents that target them. While continuing to investigate strategies to predict response, it is important that restricting trial entry based on existing biological hypotheses should be done with extreme caution.

FUNDING SOURCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

Funding support for the phase 2 trials: Canadian Cancer Society (IND.160A, 160 B); Ariad/Merck (IND.192); Drug Supply: Cancer Therapy Evaluation Program (IND.160A, IND.160B); Ariad/Merck (IND.192).

Funding for Correlative Science Studies: Ontario Institute for Cancer Research Canadian Cancer Society Princess Margaret Hospital Foundation Helse Vest, Research Council of Norway and The Norwegian Cancer Society, Harald Anderesens legat.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES
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