Over the past few years, the development of antitumoral molecular targeted strategies has replaced the more empiric screening method of researching new cytotoxic drugs. The understanding of molecular mechanisms which underlie carcinogenesis has improved and this favored the development of a pattern of targeted drugs that can specifically inhibit cancer pathways and key molecules implicated in different phases of tumor growth and metastases. Despite these efforts, even though some of these new compounds seem to be promising, failure rates are still high and the impact on survival is modest. This made the research on the role of biomarkers very important in order to select a population who may mostly benefit of targeted agents.

In clinical setting, research requires appropriate designs for proving the predictive role of markers, which have been well codified. Similarly to the grading of quality of evidence for clinical trials, it is possible to define different levels of quality of evidence for studies on predictive factors. The most appropriate are on the basis of prospective randomized studies powered for detecting interaction between marker levels and treatment as primary or at least secondary end point; studies with the lowest methodological quality derive from retrospective data, using univariate analysis. It is not difficult to note that the majority of studies analyzing predictive marker for EGFR-targeting drugs are on the basis of univariate analysis of retrospective data, without control arm, using surrogate markers of clinical outcomes.
Erlotinib is an EGFR tyrosine Kinase inhibitor registered for first-line EGFR mutated patients and for all patients in second and third line for the treatment of Non Small
The SATURN trial demonstrated a benefit in terms of Progression Free Survival (PFS) and Overall Survival (OS) when patients were treated with a “switch” maintenance therapy with erlotinib in patients with “non Progressive” disease after a first line platinum based chemotherapy.  The OS benefit is much more consistent than the PFS benefit, suggesting the presence of prognostic and predictive factors.
As the authors report, the SATURN trial in one of the first trials to prospectively collect biomarkers. This is a praiseworthy contribution, because retrieving results from retrospective analyses may emphasize selection bias and give false positive results.
Unfortunately, the SATURN trial did not address the real issue that it is whether EGFR non mutated patients may benefit from a treatment with this drug. In fact, the co-primary endpoint was PFS in patients with EGFR IHC-positive tumors, while EGFR mutations and EGFR FISH as their interaction were not pre-planned for the final analysis. However, mandatory tumor samples were required before entering the study.
Only in the 83% of patients a EGFR IHC test was performed, and in less than 50% of patients EGFR mutations were assessed. The final analysis showed that erlotinib improved PFS compared to placebo and there is no statistically significant difference when related to EGFR IHC expression. The authors also concluded that there was no demonstrated interaction between EGFR FISH and K-Ras testing. However, erlotinib reduced the risk of progression or death by 90% in patients with EGFR mutated tumors compared to placebo (HR 0.10 95% 0.04 to 0.25; p<0.001). Erlotinib provided significant PFS benefit in EGFR wild type tumors (HR 0.78 CI 063-0.96), but no information was given on OS in this group.
Despite, the great effort made by the authors, again this analysis does not give any final insights on the role of erlotinib in EGFR wild type patients also in the maintenance setting.  We hope with this contribution to create a debate among young oncologists on the strategy to develop biomarkers for the daily clinical practice.

Source:ESMO