Dataset Information

Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.

ABSTRACT:

Background

Somatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches.

Methods

Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status.

Results

Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74-0.77) in the training and 0.77 (95% CI, 0.74-0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients.

Conclusions

We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC.

Impact

The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

SUBMITTER: Schmid S

PROVIDER: S-EPMC9063819 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.

Schmid Sabine S Jiang Mei M Brown M Catherine MC Fares Aline A Garcia Miguel M Soriano Joelle J Dong Mei M Thomas Sera S Kohno Takashi T Leal Leticia Ferro LF Diao Nancy N Xie Juntao J Wang Zhichao Z Zaridze David D Holcatova Ivana I Lissowska Jolanta J Świątkowska Beata B Mates Dana D Savic Milan M Wenzlaff Angela S AS Harris Curtis C CC Caporaso Neil E NE Ma Hongxia H Fernandez-Tardon Guillermo G Barnett Matthew J MJ Goodman Gary G Davies Michael P A MPA Pérez-Ríos Mónica M Taylor Fiona F Duell Eric J EJ Schoettker Ben B Brenner Hermann H Andrew Angeline A Cox Angela A Ruano-Ravina Alberto A Field John K JK Marchand Loic Le LL Wang Ying Y Chen Chu C Tardon Adonina A Shete Sanjay S Schabath Matthew B MB Shen Hongbing H Landi Maria Teresa MT Ryan Brid M BM Schwartz Ann G AG Qi Lihong L Sakoda Lori C LC Brennan Paul P Yang Ping P Zhang Jie J Christiani David C DC Reis Rui Manuel RM Shiraishi Kouya K Hung Rayjean J RJ Xu Wei W Liu Geoffrey G

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20220301 3

<h4>Background</h4>Somatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches.<h4>Methods</h4>Through analysis of the International Lung Cancer Consortium ...[more]

PMID: 35027437

Similar Datasets

Project description:BackgroundEpidermal growth factor receptor (EGFR) mutations are present in the majority of patients with non-small cell lung cancer (NSCLC) responsive to the EGFR tyrosine kinase inhibitors (TKIs) gefitinib or erlotinib. These EGFR-dependent tumors eventually become TKI resistant, and the common secondary T790M mutation accounts for half the tumors with acquired resistance to gefitinib. However, the key proapoptotic proteins involved in TKI-induced cell death and other secondary mutations involved in resistance remain unclear. The objective of this study was to identify the mechanism of EGFR TKI-induced apoptosis and secondary resistant mutations that affect this process.Methods and findingsTo study TKI-induced cell death and mechanisms of resistance, we used lung cancer cell lines (with or without EGFR mutations), Ba/F3 cells stably transfected with EGFR mutation constructs, and tumor samples from a gefitinib-resistant patient. Here we show that up-regulation of the BH3-only polypeptide BIM (also known as BCL2-like 11) correlated with gefitinib-induced apoptosis in gefitinib-sensitive EGFR-mutant lung cancer cells. The T790M mutation blocked gefitinib-induced up-regulation of BIM and apoptosis. This blockade was overcome by the irreversible TKI CL-387,785. Knockdown of BIM by small interfering RNA was able to attenuate apoptosis induced by EGFR TKIs. Furthermore, from a gefitinib-resistant patient carrying the activating L858R mutation, we identified a novel secondary resistant mutation, L747S in cis to the activating mutation, which attenuated the up-regulation of BIM and reduced apoptosis.ConclusionsOur results provide evidence that BIM is involved in TKI-induced apoptosis in sensitive EGFR-mutant cells and that both attenuation of the up-regulation of BIM and resistance to gefitinib-induced apoptosis are seen in models that contain the common EGFR T790M and the novel L747S secondary resistance mutations. These findings also suggest that induction of BIM may have a role in the treatment of TKI-resistant tumors.

Project description:BackgroundThe epidermal growth factor receptor (EGFR) gene is the prototype member of the type I receptor tyrosine kinase (TK) family and plays a pivotal role in cell proliferation and differentiation. There are three well described polymorphisms that are associated with increased protein production in experimental systems: a polymorphic dinucleotide repeat (CA simple sequence repeat 1 [CA-SSR1]) in intron one (lower number of repeats) and two single nucleotide polymorphisms (SNPs) in the promoter region, -216 (G/T or T/T) and -191 (C/A or A/A). The objective of this study was to examine distributions of these three polymorphisms and their relationships to each other and to EGFR gene mutations and allelic imbalance (AI) in non-small cell lung cancers.Methods and findingsWe examined the frequencies of the three polymorphisms of EGFR in 556 resected lung cancers and corresponding non-malignant lung tissues from 336 East Asians, 213 individuals of Northern European descent, and seven of other ethnicities. We also studied the EGFR gene in 93 corresponding non-malignant lung tissue samples from European-descent patients from Italy and in peripheral blood mononuclear cells from 250 normal healthy US individuals enrolled in epidemiological studies including individuals of European descent, African-Americans, and Mexican-Americans. We sequenced the four exons (18-21) of the TK domain known to harbor activating mutations in tumors and examined the status of the CA-SSR1 alleles (presence of heterozygosity, repeat number of the alleles, and relative amplification of one allele) and allele-specific amplification of mutant tumors as determined by a standardized semiautomated method of microsatellite analysis. Variant forms of SNP -216 (G/T or T/T) and SNP -191 (C/A or A/A) (associated with higher protein production in experimental systems) were less frequent in East Asians than in individuals of other ethnicities (p < 0.001). Both alleles of CA-SSR1 were significantly longer in East Asians than in individuals of other ethnicities (p < 0.001). Expression studies using bronchial epithelial cultures demonstrated a trend towards increased mRNA expression in cultures having the variant SNP -216 G/T or T/T genotypes. Monoallelic amplification of the CA-SSR1 locus was present in 30.6% of the informative cases and occurred more often in individuals of East Asian ethnicity. AI was present in 44.4% (95% confidence interval: 34.1%-54.7%) of mutant tumors compared with 25.9% (20.6%-31.2%) of wild-type tumors (p = 0.002). The shorter allele in tumors with AI in East Asian individuals was selectively amplified (shorter allele dominant) more often in mutant tumors (75.0%, 61.6%-88.4%) than in wild-type tumors (43.5%, 31.8%-55.2%, p = 0.003). In addition, there was a strong positive association between AI ratios of CA-SSR1 alleles and AI of mutant alleles.ConclusionsThe three polymorphisms associated with increased EGFR protein production (shorter CA-SSR1 length and variant forms of SNPs -216 and -191) were found to be rare in East Asians as compared to other ethnicities, suggesting that the cells of East Asians may make relatively less intrinsic EGFR protein. Interestingly, especially in tumors from patients of East Asian ethnicity, EGFR mutations were found to favor the shorter allele of CA-SSR1, and selective amplification of the shorter allele of CA-SSR1 occurred frequently in tumors harboring a mutation. These distinct molecular events targeting the same allele would both be predicted to result in greater EGFR protein production and/or activity. Our findings may help explain to some of the ethnic differences observed in mutational frequencies and responses to TK inhibitors.

Dataset Information

Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.

Background

Methods

Results

Conclusions

Impact

Publications

Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets