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High need for biomarkers for stage III lung cancer

WCLC 2019
Despite the fact that patients with metastatic lung cancer are routinely tested for biomarkers –and this is impacted hugely on the treatment choices that are subsequently made as well as outcomes– patients with locally advanced lung cancer currently miss out as there are no biomarker-driven treatment for this population [1,2].

Treatment for stage III NSCLC includes surgery, chemotherapy, and radiotherapy (or a combination thereof), or chemoradiation followed by durvalumab consolidation therapy. The question remains whether biomarker-driven treatment may improve current outcomes. Moreover, the risk of recurrence for early stage lung cancers remains high and a large proportion of patients with stage III lung cancer (more than 60%) will succumb to the disease [3]. It has been suggested by a subset analysis of the PACIFIC study that patients with PD-L1 0% expression may not derive benefit from durvalumab. This may mean that PD-L1 expression could serve as a biomarker to select patients for whom adjuvant durvalumab will most likely be beneficial. This needs to be confirmed in (large) studies (editor note: until then, the addition of durvalumab to chemotherapy remains the standard of care).

Another interesting field of research concerns ctDNA clearance which has shown to be able to predict recurrence-free survival in localised lung cancer patients. By identifying residual/recurrent disease earlier than standard-of-care radiologic imaging is capable of, this method can facilitate personalised adjuvant treatment, especially at an early time [4]. Again, more ctDNA-driven clinical trials are needed to further investigate the possibilities of this biomarker. This should be followed by defining the prognosis of ctDNA positivity, intervening after standard therapy if a patient is found to be ctDNA-positive and adapt the therapy if patients are found to be persistently ctDNA-positive. When ctDNA-negativity is observed, therapy should be redefined, omitted, or shortened. By applying a biomarker-driven risk stratification, it will be possible to treat the right patients and ultimately, cure more patients [5].

  1.  Jordan EJ, et al. Cancer discovery 2017;7:596-609.
  2.  Sequist LV, et al. J Clin Oncol. 2013;20;31(27):3327-34.
  3.  Pisters KM, et al. J Clin Oncol 2007;25:5506-5518.
  4.  Chaudhuri AA, et al. Canc Disc. 2017; doi:10.1158/2159-8290.CD-17-0716.
  5. Yu H, et al. ES02.01. WCLC 2019.

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