Anaplastic lymphoma kinase (ALK)

Dissecting the role of negative feedback inhibition in ALK+ lung cancer

2014

Christine Lovly, MD, PhD

Vanderbilt University School of Medicine

Nashville

A subset of lung cancer patients have mutations in a gene called ALK. Dr. Lovly will identify new molecular targets that can be blocked in combination with ALK inhibitors to overcome the resistance that often develops after successful treatment and to promote better responses.

Research Summary

Molecular alterations in the ALK gene are detected in a subset of patients with lung cancer. Drugs which inhibit the activity of ALK have demonstrated remarkable clinical results in patients with ALK+ lung cancer. Unfortunately, despite these remarkable results, “acquired resistance,” defined as tumor growth after initial tumor regression, has emerged as an important clinical problem for patients receiving ALK inhibitor therapy. The overarching goal of this project is to develop novel, rationally selected therapeutic strategies to delay and/or overcome acquired resistance to ALK inhibitors. Using a combination of experimental approaches including cell culture models, biochemical assays, and a study of patient tumor samples prior to and at the time of acquired resistance to ALK TKI therapy, this project will study how ALK transmits signals to promote cancer growth and how these signals become altered in the context of acquired resistance to ALK inhibitors. This project will identify novel targets that can be blocked, in combination with ALK inhibitors, to promote enhanced anti-tumor responses. The results of this research are expected not only to provide additional insight into ALK+ lung cancer, but will also extend to many other cancer subtypes which also harbor ALK molecular alterations.

Technical Abstract

The ALK tyrosine kinase inhibitor (TKI) crizotinib has demonstrated significant activity in patients with ALK+ lung cancer, but its efficacy is limited by the development of acquired resistance. One potential resistance mechanism involves activation of the EGFR and HER2 kinases. This activation occurs in the absence of EGFR/HER2 mutation or amplification, suggesting an alternative mechanism for up-regulation of these kinases. We discovered a novel association between ALK and the EGFR/HER2 negative regulator, MIG-6. MIG-6 is known to inhibit EGFR/HER2 kinase activity through direct binding. However, to date, there is no known link between ALK and MIG-6. In our preliminary data, we demonstrate that MIG-6 protein levels decrease after ALK TKI treatment, a process abrogated by addition of a proteasome inhibitor. Furthermore, MIG-6 transcript and total protein levels are decreased in ALK+/TKI resistant compared to isogenic ALK+/TKI sensitive cells. The decline in MIG-6 correlates with an increase in EGFR and HER2 protein levels in the resistant cells. Based upon these data, we hypothesize that ALK serves as an upstream regulator of MIG-6, and that MIG-6 suppression drives EGFR/HER2 activation in the ALK TKI resistant state. To test this hypothesis, we propose to: 1) elucidate the molecular mechanisms whereby ALK regulates MIG-6 expression, and 2) determine the mechanisms whereby MIG-6 contributes to EGFR/HER2 pathway activation in TKI-resistant ALK+ lung cancer cells. The proposed studies may lead to strategies that augment or restore expression of MIG-6 and therefore will represent a novel therapeutic approach for patients with acquired resistance to ALK inhibitor therapy.

Key words

Acquired resistance

Anaplastic lymphoma kinase (ALK)

HER2

Non-small cell lung cancer (NSCLC)

Targeted therapy

Tyrosine kinase inhibitors (TKIs)

Read more about Dissecting the role of negative feedback inhibition in ALK+ lung cancer

Molecular predictors of outcome in non-small cell lung cancer

2012

Career Development Award

Christopher A. Maher, PhD

Washington University in St. Louis

St. Louis

Dr. Maher is working to improve on the accuracy and usability of tests that identify lung cancer patients who are likely to relapse. He is using next-generation sequencing techniques to develop a signature set of key genetic changes and convert it to a clinical test that will be able to predict who is at high risk for relapse.

Research Summary

Currently, approximately 30% of non-small cell lung cancer (NSCLC) patients will die from recurrent disease despite undergoing surgery. Therefore, there is a critical need to develop accurate markers to distinguish high-risk patients who are more likely to have recurrent disease from patients who are at a lower risk for recurrent disease. To date several groups have applied high-throughput methods to identify a set of genes, or a “signature,” that will classify patients as high-risk or low-risk. However, there are two limitations to existing approaches. First, technological advances in sequencing technology offer an opportunity to identify additional markers, which would have eluded previous approaches, and therefore could result in a more accurate signature. Second, previous methods for developing a signature were developed on tumor material that is not routinely collected in clinics. This presents a critical need to develop an assay that can effectively apply a predictive signature on samples collected in the clinic. Therefore, our proposal focuses on using newer sequencing technologies to generate a refined signature for predicting which patients have more aggressive disease. We then proposed two goals for adapting this signature into a clinically useful assay. First, we intend to confirm that the predictive signature works on the same sample material collected in a clinic. Second, we intend to test our predictive signature on a completely independent cohort of patients to ensure it accurately stratifies patients with more aggressive disease. Overall, if the proposed aims are met, this research could lead to an improved assay that could be widely adopted in the clinic to stratify high-risk patients for more aggressive therapies and assign less aggressive treatments to patients at low risk for recurrence.

Technical Abstract

Approximately 30% of patients with stage 1 non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection . Currently, there is a lack of reliable molecular predictors being routinely used in the clinic for identifying patients at high risk for developing recurrent disease and therefore may benefit from more aggressive therapies. To date several groups have applied microarray-based methods for global gene expression profiling of frozen tumor tissues in an attempt to identify prognostic ‘signatures’ in patients with early stage NSCLC. Building upon this, through a meta-analysis of seven independent microarray studies Govindan et al. were able to identify a 64-gene signature that is highly predictive of survival in patients with stage I NSCLC. However, recent advances in high-throughput sequencing have enabled an unbiased view of the transcriptome including novel transcriptional events such as gene fusions, splicing variants, and novel transcripts. This offers an opportunity to incorporate additional markers, which may have eluded previous technologies, but could serve for improving a predictive signature of survival in non-small cell lung cancer (NSCLC). However, despite the potential of RNA-Seq to improve existing predictive signatures, we are still faced with the challenge of translating these findings into a platform where they can be reliably applied to formalin fixed paraffin embedded (FFPE) clinical tissue specimens routinely collected in tertiary referral centers. Therefore, this proposal focuses on refining the 64-gene predictive signature using transcriptome sequencing and developing a NanoString nCounter assay to reliably predict survival of patients with resected stage I NSCLC, using RNA derived from FFPE tumor blocks. To accomplish this we have proposed the following specific aims: (1) use transcriptome sequencing to detect molecular predictors of outcome in patients with stage I NSCLC, (2) validate the technical performance of the NanoString nCounter using an RNA-Seq predictive signature across FFPE tumor blocks of resected stage I NSCLC, and (3) clinically validate the prognostic power of the predictive signature across an independent sample set. Overall, if the proposed aims are met, this research could lead to an improved assay that could be translated into future prospective studies for risk-stratifying stage I NSCLC patients.

Key words

Anaplastic lymphoma kinase (ALK)

Biomarker or biomarker testing

KRAS

Molecular profile or molecular testing

Mutation profile

Non-small cell lung cancer (NSCLC)

Recurrent

Stage I