Molecular Profiling and the Reclassification of Cancer: Divide and Conquer

Author(s):  
Javier Munoz ◽  
Charles Swanton ◽  
Razelle Kurzrock

Cancer is one of the leading causes of mortality in the world. Choosing the best treatment is dependent on making the right diagnosis. The diagnostic process has been based on light microscopy and the identification of the organ of tumor origin. Yet we now know that cancer is driven by molecular processes, and that these do not necessarily segregate by organ of origin. Fortunately, revolutionary changes in technology have enabled rapid genomic profiling. It is now apparent that neoplasms classified uniformly (e.g., non-small cell lung cancer) are actually comprised of up to 100 different molecular entities. For instance, tumors bearing ALK alterations make up about 4% of non-small cell lung cancers, and tumors bearing epidermal growth factor receptor (EGFR) mutations, approximately 5% to 10%. Importantly, matching patients to therapies targeted against their driver molecular aberrations has resulted in remarkable response rates. There is now a wealth of evidence supporting a divide-and-conquer strategy. Herein, we provide a concise primer on the current state-of-the-art of molecular profiling in the cancer clinic.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 9028-9028
Author(s):  
Haiyan Tu ◽  
Ee Ke ◽  
Yue-Li Sun ◽  
Ming-Ying Zheng ◽  
Jin-Ji Yang ◽  
...  

9028 Background: Non-small-cell lung cancers with uncommon epidermal growth factor receptor ( EGFR) mutations are regarded as a heterogeneous group with variable responses to EGFR-targeted drugs. Here we designed this retrospective study to describe the epidemiology and clinical outcomes of uncommon EGFR mutations in a Chinese cohort of lung cancer patients. Methods: Between June 2007 and June 2014, 5363 lung cancer patients whose EGFR genotyping was performed successfully at Guangdong Lung Cancer Institute (GLCI, Guangzhou, China) were screened. 1837 patients were included in the epidemiological analysis. The clinical outcome was analyzed in 97 advanced-stage patients harboring uncommon EGFR mutations with follow-up data. Results: 218 patients harbored uncommon EGFR mutations, making up 11.9% of all cancers with documented EGFR mutations. Compared with common mutants, those with uncommon mutations were more commonly found in smokers and male patients. The most frequently detected uncommon mutations were exon 20 insertions, G719X mutations and L858R complex mutations, occurring in 30.7%, 21.1% and 17.0% of all EGFR-uncommon-mutation cases. G719X and L858R complex mutations were associated with similar benefit from EGFR-TKI; median PFS was 15.2 (95% CI 8.7-21.7) and 11.6 (95% CI 3.6-19.6) months, respectively. T790M or 20INS was associated with a poorer EGFR-TKI response; median PFS was 1.0 (95% CI 0.0-2.2) and 3.0 (95% CI 1.3-4.7) months, respectively. Of note, two patients with 23% and 65% tumor shrinkages had N771_P772insN and H773_V774insQ, with PFS of 5.7 and 6.1 months respectively. Conclusions: Favorable responses were observed in specific subtypes including complex L858R and G719X, and our results suggested first-line EGFR-TKI should be preferable in such patients.


Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3553
Author(s):  
Dylan A. Farnsworth ◽  
Yankuan T. Chen ◽  
Georgia de Rappard Yuswack ◽  
William W. Lockwood

Epidermal growth factor receptor (EGFR) mutations are the molecular driver of a subset of non-small cell lung cancers (NSCLC); tumors that harbor these mutations are often dependent on sustained oncogene signaling for survival, a concept known as “oncogene addiction”. Inhibiting EGFR with tyrosine kinase inhibitors has improved clinical outcomes for patients; however, successive generations of inhibitors have failed to prevent the eventual emergence of resistance to targeted agents. Although these tumors have a well-established dependency on EGFR signaling, there remain questions about the underlying genetic mechanisms necessary for EGFR-driven oncogenesis and the factors that allow tumor cells to escape EGFR dependence. In this review, we highlight the latest findings on mutant EGFR dependencies, co-operative drivers, and molecular mechanisms that underlie sensitivity to EGFR inhibitors. Additionally, we offer perspective on how these discoveries may inform novel combination therapies tailored to EGFR mutant NSCLC.


2009 ◽  
Vol 27 (9) ◽  
pp. 1394-1400 ◽  
Author(s):  
Akira Inoue ◽  
Kunihiko Kobayashi ◽  
Kazuhiro Usui ◽  
Makoto Maemondo ◽  
Shoji Okinaga ◽  
...  

Purpose This multicenter phase II study was undertaken to investigate the efficacy and feasibility of gefitinib for patients with advanced non–small-cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations without indication for chemotherapy as a result of poor performance status (PS). Patients and Methods Chemotherapy-naïve patients with poor PS (patients 20 to 74 years of age with Eastern Cooperative Oncology Group PS 3 to 4, 75 to 79 years of age with PS 2 to 4, and ≥ 80 years of age with PS 1 to 4) who had EGFR mutations examined by the peptide nucleic acid-locked nucleic acid polymerase chain reaction clamp method were enrolled and received gefitinib (250 mg/d) alone. Results Between February 2006 and May 2007, 30 patients with NSCLC and poor PS, including 22 patients with PS 3 to 4, were enrolled. The overall response rate was 66% (90% CI, 51% to 80%), and the disease control rate was 90%. PS improvement rate was 79% (P < .00005); in particular, 68% of the 22 patients improved from ≥ PS 3 at baseline to ≤ PS 1. The median progression-free survival, median survival time, and 1-year survival rate were 6.5 months, 17.8 months, and 63%, respectively. No treatment-related deaths were observed. Conclusion This is the first report indicating that EGFR mutation-positive patients with extremely poor PS benefit from first-line gefitinib. Because there previously has been no standard treatment for these patients with short life expectancy other than best supportive care, examination of EGFR mutations as a biomarker is recommended in this patient population.


2009 ◽  
Vol 27 (16) ◽  
pp. 2653-2659 ◽  
Author(s):  
Hua Bai ◽  
Li Mao ◽  
hang Shu Wang ◽  
Jun Zhao ◽  
Lu Yang ◽  
...  

Purpose Mutations in the epidermal growth factor receptor (EGFR) kinase domain can predict tumor response to tyrosine kinase inhibitors (TKIs) in non–small-cell lung cancer (NSCLC). However, obtaining tumor tissues for mutation analysis is challenging. We hypothesized that plasma-based EGFR mutation analysis is feasible and has value in predicting tumor response in patients with NSCLC. Patients and Methods Plasma DNA samples and matched tumors from 230 patients with stages IIIB to IV NSCLC were analyzed for EGFR mutations in exons 19 and 21 by using denaturing high-performance liquid chromatography. We compared the mutations in the plasma samples and the matched tumors and determined an association between EGFR mutation status and the patients' clinical outcomes prospectively. Results In 230 patients, we detected 81 EGFR mutations in 79 (34.3%) of the patients' plasma samples. We detected the same mutations in 63 (79.7%) of the matched tumors. Sixteen plasma (7.0%) and fourteen tumor (6.1%) samples showed unique mutations. The mutation frequencies were significantly higher in never-smokers and in patients with adenocarcinomas (P = .012 and P = .009, respectively). In the 102 patients who failed platinum-based treatment and who were treated with gefitinib, 22 (59.5%) of the 37 with EGFR mutations in the plasma samples, whereas only 15 (23.1%) of the 65 without EGFR mutations, achieved an objective response (P = .002). Patients with EGFR mutations had a significantly longer progression-free survival time than those without mutations (P = .044) in plasma. Conclusion EGFR mutations can be reliably detected in plasma DNA of patients with stages IIIB to IV NSCLC and can be used as a biomarker to predict tumor response to TKIs.


2015 ◽  
Vol 51 ◽  
pp. S610-S611
Author(s):  
C. Charoentum ◽  
N. Lertprasertsuke ◽  
C. Phanthunane ◽  
T. Theerakittikul ◽  
C. Liwsrisakun ◽  
...  

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