Umberto Malapelle
Fabrizio Tabbò
Lucia Anna Muscarella- 1Department of Public Health, University Federico II of Naples, Naples, Italy
- 2SC Oncologia ASLCN2 Alba e BRA, PO Michele e Pietro Ferrero, Verduno, Italy
- 3Laboratory of Oncology, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
Editorial on the Research Topic
Concomitant pathogenic mutations in oncogene-driven subgroups: when next generation biology meets targeted therapy in NSCLC
Starting from the Epidermal Growth Factor Receptor (EGFR) (1) and Anaplastic Lymphoma Kinase (ALK) (2), and continuing with the identification of other well-known driver genes for target therapy in non-small-cell lung cancer (NSCLC), such as Proto-oncogene tyrosine-protein kinase ROS (ROS1) (3), v-Raf murine sarcoma viral oncogene homolog B (BRAF) (4), Kirsten rat sarcoma virus (KRAS) (5), Rearranged During Transfection (RET) (6), Tropomyosin receptor kinase 1-2-3 (NTRK1-2-3) (7), Neuregulin 1 (NRG1) (8), Erythroblastic oncogene B (ERBB2) (9), and MET proto-oncogene (MET) (10), all clinical trials carried out worldwide in the last decade aim to identify and evaluate the efficacy of different generations of target inhibitors (11, 12).
The impressive clinical efficacy of tyrosine kinase inhibitors (TKI) for oncogene-addicted subgroups of NSCLC has inevitably oriented the scientific community towards an oncogene-centric molecular classification paradigm of these tumors, where the identification of single or largely non-overlapping oncogenic driver events guides clinical decisions and forecasts patients’ responses (13). This approach allowed for oncogene-addicted NSCLC patients an unimaginable, but variable objective responses, progression-free survival and overall survival to up-front therapies (14). That was correlated at first instance to phenotypic variability and de novo resistance events, with rare observed complete responses (15–19).
Following the improvement in the knowledge of NSCLC genomic complexity, there was growing evidence that this monocentric model fails to adequately capture the clinical complexity of NSCLC and warrants revision to better modulate therapy in lung cancer patients. The use of molecular analysis techniques, most notably next generation sequencing (NGS), has revealed ever-increasing evidences that molecular intra-driver heterogeneity in tumors could guide the clinical heterogeneity. Beside of distinct effects of individual oncogene alleles (20–22) many under-investigated multiple non-random patterns of co-occurring mutations can be one of the main cause of the observed variations in response to therapies in NSCLC oncogene-dependent patients’ groups (23, 24), depending on several factors: the disease stage of tumors (25, 26), the selective pressure imposed by previous anticancer therapy, the clonal or subclonal nature as well as timing of co-alterations, immune-surveillance and –selection that could drive the oncogenic mutational landscape (27). The significance of such co-mutations as mediators of various NSCLC phenotypes has just lately come into attention, and existing molecular stratification frameworks do not adequately account for their functional influence (28).
The first and most supported evidences in this field were from the most frequent druggable genes of NSCLC, as KRAS and EGFR. The census of major KRAS co-mutations in advanced lung adenocarcinoma identified co-occurred lesions in a set of core gene including LKB1, KEAP1, ATM and RBM10 that are related to early metastatic dissemination, tumor maintenance and an aggressive clinical phenotype in response to standard chemotehrapy, immunotherapy and biological agents (29). It is also crucial to remember that even genetic changes that do not exhibit statistically significant patterns of co-occurrence could nonetheless have crucial biological connections. For example, even though TP53 mutations are less common in KRAS mutant lung adenocarcinoma than in other oncogene-driver subgroups, TP53 inactivation is frequent and has a significant influence in this kind of cancer having an early-stage and chemo-refractory conditions or advanced PDL1-PD1 resistance profile (30, 31). A critical role of TP53 mutations was also observed by analyzing its impact in NSCLC EGFRex20ins mutated patients, where TP53 mutations was established as negative prognostic marker and also correlated to poor prognosis for EGFR ex20ins near-loop patients treated with second-/third-generation EGFR-TKIs, as well as copy number gain instability and higher tumor mutational burden (TMB) (32).
More recently, the co-mutations landscape and genomic architecture of lung adenocarcinoma driven by rare oncogenic alterations, such as BRAF mutations (33) or fusions involving ALK, ROS1 and RET genes was highlighted. Compared with other driver subgroups, rearranged–positive NSCLC showed higher prevalence of CDKN2A and CDKN2B loss co-occurrent with TP53 mutations (34) or MYC amplification (35, 36). By contrast, TP53 mutations are underrepresented in NSCLC patients having MET exon 14 skipping, who frequently showed MDM2 and CDK4 co-occurrent amplifications events as an unfavorable outcome predictor (36).
Much more scientific advances are demanded to close the gap in this field and they must necessarily go through a re-evaluation of current clinical trials by including the genetic landscape of lung tumors.
Moreover, the identification of the clonal or subclonal architecture as well as the arising time of co-alterations may help to clarify the clinical complexity of NSCLC and reveal crucial details about their contributions to various stages of carcinogenesis (37), the nature of the microenvironment surrounding NSCLC (38), and its immune context (37). Due to all of these factors, it will be necessary in the future to compile a list of co-occurring pathogenic abnormalities in NSCLC, functionalize them, and assess their therapeutic value. This information will then be used to develop more specialized treatment plans that will translate in better clinical results for patients.
Actually, technology is helping us and the gold standard to identify co-occurring mutations is actually NGS on DNA/RNA extracted from tissue biopsy since it represents less time- and money-consuming approach to obtaining information about the molecular status of driver genes for target therapies (Yang et al.). In addition, the growing field of precision immunotherapy, the discovery of co-mutations in liquid biopsy, and the comparison of genetic results from analyses of tissues and blood will offer for personalized anticancer therapy challenges and opportunities (39). Multiregional sequencing analysis by large consortia has demonstrated the ability of ctDNA to capture the clonal structure from tumor tissue as well as to unveil additional heterogeneity at relapse when compared to tissue samples (37). The measurements of sub-clonal expansion in different clinical time may also enable to predict future metastatic sub-clones and give the chance to eradicate such clones months or even years before the clinical relapse of tumors.
Author contributions
UM, FT and LAM: conceptualization, writing—original draft preparation, writing—review and editing, and supervision. All the authors have read and agreed to the published version of the manuscript.
Conflict of interest
UM has received personal fees as consultant and/or speaker bureau from Boehringer Ingelheim, Roche, MSD, Amgen, Thermo Fisher Scientifics, Eli Lilly, Diaceutics, GSK, Merck and AstraZeneca, Janssen, Diatech, Novartis, and Hedera, for work performed outside of the current study. FT has received personal fees as speaker bureau/honoraria from AstraZeneca, Roche, Novartis, Takeda for work performed outside of the current study. LAM has received personal fees as speaker bureau/honoraria from Qbgroup, Diatech Pharmacogenetics, ElmaResearch and AstraZeneca for work performed outside of the current study.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med (2004) 350(21):2129–39. doi: 10.1056/NEJMoa040938
2. Soda M, Choi YL, Enomoto M, Takada S, Yamashita Y, Ishikawa S, et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature (2007) 448(7153):561–6. doi: 10.1038/nature05945
3. Bergethon K, Shaw AT, Ou SH, Katayama R, Lovly CM, McDonald NT, et al. ROS1 rearrangements define a unique molecular class of lung cancers. J Clin Oncol (2012) 30(8):863–70. doi: 10.1200/JCO.2011.35.6345
4. Planchard D, Smit EF, Groen HJM, Mazieres J, Besse B, Helland A, et al. Dabrafenib plus trametinib in patients with previously untreated BRAF(V600E)-mutant metastatic non-small-cell lung cancer: an open-label, phase 2 trial. Lancet Oncol (2017) 18(10):1307–16. doi: 10.1016/S1470-2045(17)30679-4
5. Skoulidis F, Li BT, Dy GK, Price TJ, Falchook GS, Wolf J, et al. Sotorasib for lung cancers with KRAS p.G12C mutation. N Engl J Med (2021) 384(25):2371–81. doi: 10.1056/NEJMoa2103695
6. Kohno T, Ichikawa H, Totoki Y, Yasuda K, Hiramoto M, Nammo T, et al. KIF5B-RET fusions in lung adenocarcinoma. Nat Med (2012) 18(3):375–7. doi: 10.1038/nm.2644
7. Vaishnavi A, Capelletti M, Le AT, Kako S, Butaney M, Ercan D, et al. Oncogenic and drug-sensitive NTRK1 rearrangements in lung cancer. Nat Med (2013) 19(11):1469–72. doi: 10.1038/nm.3352
8. Fernandez-Cuesta L, Plenker D, Osada H, Sun R, Menon R, Leenders F, et al. CD74-NRG1 fusions in lung adenocarcinoma. Cancer Discovery (2014) 4(4):415–22. doi: 10.1158/2159-8290.CD-13-0633
9. Stephens P, Hunter C, Bignell G, Edkins S, Davies H, Teague J, et al. Lung cancer: intragenic ERBB2 kinase mutations in tumours. Nature (2004) 431(7008):525–6. doi: 10.1038/431525b
10. Frampton GM, Ali SM, Rosenzweig M, Chmielecki J, Lu X, Bauer TM, et al. Activation of MET via diverse exon 14 splicing alterations occurs in multiple tumor types and confers clinical sensitivity to MET inhibitors. Cancer Discovery (2015) 5(8):850–9. doi: 10.1158/2159-8290.CD-15-0285
11. Mateo J, Chakravarty D, Dienstmann R, Jezdic S, Gonzalez-Perez A, Lopez-Bigas N, et al. A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO scale for clinical actionability of molecular targets (ESCAT). Ann Oncol (2018) 29(9):1895–902. doi: 10.1093/annonc/mdy263
12. Martin-Romano P, Mezquita L, Hollebecque A, Lacroix L, Rouleau E, Gazzah A, et al. Implementing the European society for medical oncology scale for clinical actionability of molecular targets in a comprehensive profiling program: impact on precision medicine oncology. JCO Precis Oncol (2022) 6:e2100484. doi: 10.1200/PO.21.00484
13. Tan AC, Tan DSW. Targeted therapies for lung cancer patients with oncogenic driver molecular alterations. J Clin Oncol (2022) 40(6):611–25. doi: 10.1200/JCO.21.01626
14. Thai AA, Solomon BJ, Sequist LV, Gainor JF, Heist RS. Lung cancer. Lancet (2021) 398(10299):535–54. doi: 10.1016/S0140-6736(21)00312-3
15. Cooper AJ, Sequist LV, Lin JJ. Third-generation EGFR and ALK inhibitors: mechanisms of resistance and management. Nat Rev Clin Oncol (2022) 19(8):499–514. doi: 10.1038/s41571-022-00639-9
16. Tumbrink HL, Heimsoeth A, Sos ML. The next tier of EGFR resistance mutations in lung cancer. Oncogene (2021) 40(1):1–11. doi: 10.1038/s41388-020-01510-w
17. Kobayashi Y, Oxnard GR, Cohen EF, Mahadevan NR, Alessi JV, Hung YP, et al. Genomic and biological study of fusion genes as resistance mechanisms to EGFR inhibitors. Nat Commun (2022) 13(1):5614. doi: 10.1038/s41467-022-33210-2
18. Harada G, Yang SR, Cocco E, Drilon A. Rare molecular subtypes of lung cancer. Nat Rev Clin Oncol (2023) 20(4):229–49. doi: 10.1038/s41571-023-00733-6
19. Awad MM, Liu S, Rybkin II, Arbour KC, Dilly J, Zhu VW, et al. Acquired resistance to KRAS(G12C) inhibition in cancer. N Engl J Med (2021) 384(25):2382–93. doi: 10.1056/NEJMoa2105281
20. Robichaux JP, Elamin YY, Tan Z, Carter BW, Zhang S, Liu S, et al. Mechanisms and clinical activity of an EGFR and HER2 exon 20-selective kinase inhibitor in non-small cell lung cancer. Nat Med (2018) 24(5):638–46. doi: 10.1038/s41591-018-0007-9
21. Lin JJ, Zhu VW, Yoda S, Yeap BY, Schrock AB, Dagogo-Jack I, et al. Impact of EML4-ALK variant on resistance mechanisms and clinical outcomes in ALK-positive lung cancer. J Clin Oncol (2018) 36(12):1199–206. doi: 10.1200/JCO.2017.76.2294
22. Ostrem JM, Shokat KM. Direct small-molecule inhibitors of KRAS: from structural insights to mechanism-based design. Nat Rev Drug Discovery (2016) 15(11):771–85. doi: 10.1038/nrd.2016.139
23. Cancer Genome Atlas Research N. Comprehensive molecular profiling of lung adenocarcinoma. Nature (2014) 511(7511):543–50. doi: 10.1038/nature13385
24. Campbell JD, Alexandrov A, Kim J, Wala J, Berger AH, Pedamallu CS, et al. Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nat Genet (2016) 48(6):607–16. doi: 10.1038/ng.3564
25. Blakely CM, Watkins TBK, Wu W, Gini B, Chabon JJ, McCoach CE, et al. Evolution and clinical impact of co-occurring genetic alterations in advanced-stage EGFR-mutant lung cancers. Nat Genet (2017) 49(12):1693–704. doi: 10.1038/ng.3990
26. Jamal-Hanjani M, Wilson GA, McGranahan N, Birkbak NJ, Watkins TBK, Veeriah S, et al. Tracking the evolution of non-Small-Cell lung cancer. N Engl J Med (2017) 376(22):2109–21. doi: 10.1056/NEJMoa1616288
27. Marty R, Kaabinejadian S, Rossell D, Slifker MJ, van de Haar J, Engin HB, et al. MHC-I genotype restricts the oncogenic mutational landscape. Cell (2017) 171(6):1272–83 e15. doi: 10.1016/j.cell.2017.09.050
28. Skoulidis F, Heymach JV. Co-Occurring genomic alterations in non-small-cell lung cancer biology and therapy. Nat Rev Cancer (2019) 19(9):495–509. doi: 10.1038/s41568-019-0179-8
29. Arbour KC, Jordan E, Kim HR, Dienstag J, Yu HA, Sanchez-Vega F, et al. Effects of Co-occurring genomic alterations on outcomes in patients with KRAS-mutant non-small cell lung cancer. Clin Cancer Res (2018) 24(2):334–40. doi: 10.1158/1078-0432.CCR-17-1841
30. Skoulidis F, Byers LA, Diao L, Papadimitrakopoulou VA, Tong P, Izzo J, et al. Co-Occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discovery (2015) 5(8):860–77. doi: 10.1158/2159-8290.CD-14-1236
31. Skoulidis F, Goldberg ME, Greenawalt DM, Hellmann MD, Awad MM, Gainor JF, et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discovery (2018) 8(7):822–35. doi: 10.1158/2159-8290.CD-18-0099
32. Schrock AB, Frampton GM, Suh J, Chalmers ZR, Rosenzweig M, Erlich RL, et al. Characterization of 298 patients with lung cancer harboring MET exon 14 skipping alterations. J Thorac Oncol (2016) 11(9):1493–502. doi: 10.1016/j.jtho.2016.06.004
33. Negrao MV, Raymond VM, Lanman RB, Robichaux JP, He J, Nilsson MB, et al. Molecular landscape of BRAF-mutant NSCLC reveals an association between clonality and driver mutations and identifies targetable non-V600 driver mutations. J Thorac Oncol (2020) 15(10):1611–23. doi: 10.1016/j.jtho.2020.05.021
34. Kron A, Alidousty C, Scheffler M, Merkelbach-Bruse S, Seidel D, Riedel R, et al. Impact of TP53 mutation status on systemic treatment outcome in ALK-rearranged non-small-cell lung cancer. Ann Oncol (2018) 29(10):2068–75. doi: 10.1093/annonc/mdy333
35. Alidousty C, Baar T, Martelotto LG, Heydt C, Wagener S, Fassunke J, et al. Genetic instability and recurrent MYC amplification in ALK-translocated NSCLC: a central role of TP53 mutations. J Pathol (2018) 246(1):67–76. doi: 10.1002/path.5110
36. Michels S, Scheel AH, Scheffler M, Schultheis AM, Gautschi O, Aebersold F, et al. Clinicopathological characteristics of RET rearranged lung cancer in European patients. J Thorac Oncol (2016) 11(1):122–7. doi: 10.1016/j.jtho.2015.09.016
37. Frankell AM, Dietzen M, Al Bakir M, Lim EL, Karasaki T, Ward S, et al. The evolution of lung cancer and impact of subclonal selection in TRACERx. Nature (2023) 616(7957):525–33. doi: 10.1038/s41586-023-05783-5
38. Al Bakir M, Huebner A, Martinez-Ruiz C, Grigoriadis K, Watkins TBK, Pich O, et al. The evolution of non-small cell lung cancer metastases in TRACERx. Nature (2023) 616(7957):534–42. doi: 10.1038/s41586-023-05729-x
Keywords: NSCLC, oncogene driver, co-occurrent mutations, targeted therapy, prognosis
Citation: Malapelle U, Tabbò F and Muscarella LA (2023) Editorial: Concomitant pathogenic mutations in oncogene-driven subgroups: when next generation biology meets targeted therapy in NSCLC. Front. Oncol. 13:1239304. doi: 10.3389/fonc.2023.1239304
Received: 13 June 2023; Accepted: 13 June 2023;
Published: 22 June 2023.
Edited and Reviewed by:
Alfredo Addeo, Hôpitaux universitaires de Genève (HUG), SwitzerlandCopyright © 2023 Malapelle, Tabbò and Muscarella. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Lucia Anna Muscarella, l.muscarella@operapadrepio.it