Methods for Prediction of Clinical Outcome to Epidermal Growth Factor Receptor Inhibitors by Cancer Patients

Abstract

Disclosed are biomarkers, methods and assay kits for the identification of cancer patients who are predicted to benefit, or not to benefit, from the therapeutic administration of an epidermal growth factor receptor (EGFR) inhibitor. The biomarkers of the present invention include detection of EGFR and HER 2 gene amplification and polysomy, EGFR protein expression, EGFR mutations, phosphorylated Akt protein expression, and various combinations of such biomarkers, as well as the combination of these biomarkers with mutations in the tyrosine kinase domain of the EGFR gene. Increased EGFR gene copy number, increased HER2 gene copy number, increased EGFR, protein expression, activated AKT protein expression (phosphorylated AKT) and EGFR mutations are all associated with better outcome for cancer patients treated with EGFR inhibitors. The invention provides a diagnostic paradigm based on each of these tests and combinations of these tests to select cancer patients who will benefit from EGFR inhibitor therapy, as well as a diagnostic paradigm to select cancer patients who will not benefit from EGFR inhibitor therapy.

Description

FIELD OF THE INVENTION[0001]The present invention generally relates to biomarkers, methods and assay kits for the identification of cancer patients who are predicted to benefit from EGFR inhibitor therapy.BACKGROUND OF THE INVENTION[0002]Neoplasia, or a process of rapid cellular proliferation resulting in new, abnormal growth, is a characteristic of many diseases which can be serious, and sometimes, life-threatening. Typically, neoplastic growth of cells and tissues is characterized by greater than normal proliferation of cells, wherein the cells continue to grow even after the instigating factor (e.g., tumor promoter, carcinogen, virus) is no longer present. The cellular growth tends to show a lack of structural organization and / or coordination with the normal tissue and usually creates a mass of tissue (e.g., a tumor) which may be benign or malignant. Malignant cellular growth, or malignant tumors (cancer), are a leading cause of death worldwide, and the development of effective t...

AI Technical Summary

Benefits of technology

[0011]In one aspect of this embodiment, selection of the patient in step (d) based on EGFR gene amplification or polysomy is reversed if the patient is selected as being predicted to benefit from therapeutic administration of the EGFR inhibitor based on HER2 gene amplification or polysomy. In another aspect of this embodiment, the selection of the patient in step (c) based on EGFR gene amplification or polysomy and the positive selection of the patient based on HER2 gene amplification or polysomy increases the likelihood that the patient will respond to treatment with the EGFR inhibitor as compared to selection of the patient in step (c) based on EGFR gene amplification or polysomy alone.

Problems solved by technology

Although a variety of innovative approaches to treat and prevent cancers have been proposed, many cancers continue to cause a high rate of mortality and may be difficult to treat or relatively unresponsive to conventional therapies.

While chemotherapy has produced modest survival benefits in advanced stages, standard two-drug combinations generate considerable toxicity and require intravenous administration (Non-small Cell Lung Cancer Collaborative Group, 1995; Schiller et al., 2002; Kelly et al., 2001).

Importantly, this survival benefit was not confined to objective responders, nor to a single gender or histology, which makes selection based on clinical and histopathological features alone difficult.

However, while objective response has been reported in up to 18% and symptomatic improvement in 40% of the unselected gefitinib treated NSCLC patients (Fukuoka et al., 2003; Kris et al., 2003, JAMA), the frequency of these mutations in unselected US patients is low (Paez et al., 2004).

Furthermore, while these activating mutations identify patients with high response rates, they cannot account for the high stable disease rates, reported to occur in about 30% of NSCLC patients treated with gefitinib (Fukuoka et al., 2003; Kris et al., 2003, JAMA).

In summary, there are no reliable selection criteria for determining which cancer patients, including NSCLC patients, will benefit from treatment with EGFR inhibitors exemplified by, but not limited to, gefitinib.

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