Mutation Profiling of Lung Cancers with Long-Term Response to Gefitinib Therapy

Abstract

Background: The role of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) in the treatment of patients with advanced non-small cell lung cancer (NSCLC) and unknown EGFR mutation status has recently been questioned. Patients and Methods: We conducted a retrospective study of patients with unknown EGFR mutation status and long-term response (LTR) to gefitinib in the Swiss Iressa expanded access program (EAP). We assessed patient characteristics, and performed Sanger sequencing and next generation sequencing on archived tumor tissue. We hypothesized that EGFR mutations are prevalent in patients with LTR. Results: Of 430 patients in the EAP, 18 (4%) fulfilled our definition of LTR, and 16 of them had archived tumor tissue. Patient characteristics were as expected for age, sex, and smoking history. Median duration of therapy was 38 months (range 24-142 months). Sanger sequencing revealed EGFR exon 18-21 mutations in 6 (38%) of the tumors. Next generation sequencing revealed no further EGFR-mutated cases, but reported in 15 (94%) of the tumors mutations in other genes (ALK, BRAF, DDR2, KEAP1, MET, PTEN, STK11) previously associated with NSCLC. Conclusion: Larger studies are needed to define the prognostic values of different driver mutations in patients with NSCLC.

Co-occurrence CDK4/6 amplification serves as biomarkers of de novo EGFR TKI resistance in sensitizing EGFR mutation non-small cell lung cancer

“…Patients were categorized into 3 groups based on EGFR TKI responsiveness (1) de novo resistance, EGFR TKI resistance who were defined as the best response was progressive disease (PD) or SD less than 3 months while receiving EGFR TKIs. This group represented intrinsic resistance to EGFR TKIs 16 ; (2) intermediate responder, developed acquired resistance to EGFR TKIs according to the proposed criteria by Jackman 17 and (3) long-term responder, durable disease control with EGFR TKIs more than 2 years 18 . Patient characteristics of the three groups were listed in Table 1 .…”

“…Objective response rate (ORR) was determined according to the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) and classified as a progressive disease (PD), complete response (CR), partial response (PR), or stable disease (SD). Patients were categorized into three groups based on responsiveness to EGFR TKI treatment: (1) those with de novo EGFR TKI resistance who were defined as the best response were PD or SD less than 3 months while receiving EGFR TKI 16 (de novo resistance); (2) those who developed acquired resistance to EGFR TKIs according to the proposed criteria by Jackman 17 (Intermediate responder) and (3) those treated with EGFR TKIs for at least 2 years 18 (Long-term responder). Independent radiologist blind to molecular characteristic had reviewed imaging responses of 65 patients who obtained available tissue for WES.…”

First-line afatinib for advanced EGFRm+ NSCLC: Analysis of long-term responders in the LUX-Lung 3, 6, and 7 trials

“…For example, some investigators defined LTRs as patients who achieved at least stable disease for > 6 months following treatment with gefitinib or erlotinib [5,6]. Conversely, in a recent expanded access program (EAP) study of 430 patients treated with gefitinib, 4% were considered LTRs because they received a minimum duration of 2 years of therapy [7]. Two other EAP studies found that 6.3% and 1.0% of patients were LTRs, respectively, when this group was defined in both studies as those treated with gefitinib for more than, or at least, 3 years [22,23].…”

“…While most patients treated with EGFR tyrosine kinase inhibitors (TKIs) eventually experience disease progression within 8-19 months after starting treatment [4], some patients can remain on treatment and achieve very durable responses, remaining on treatment for years. Currently, data on clinical outcomes in patients with long-term responses to EGFR TKIs are limited, and this is further complicated by the varying definitions of a long-term response in different studies [5][6][7]. Importantly, identifying demographic and/or clinical characteristics that may predict long-term response to therapy could be instrumental in determining optimal treatment strategies for individual patients.…”