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Introduction: Limited clinical data are available regarding the efficacy of EGFR tyrosine kinase inhibitors (EGFR TKIs) in patients with NSCLC harboring uncommon EGFR mutations. This pooled analysis assessed the activity of afatinib in 693 patients with tumors harboring uncommon EGFR mutations treated in randomized clinical trials, compassionate-use and expanded-access programs, phase IIIb trials, noninterventional trials, and case series or studies. Methods: Patients had uncommon EGFR mutations, which were categorized as follows: (1) T790M; (2) exon 20 insertions; (3) "major" uncommon mutations (G719X, L861Q, and S768I, with or without any other mutation except T790M or an exon 20 insertion); (4) compound mutations; and (5) other uncommon mutations. Key end points were overall response rate (ORR), duration of response, and time to treatment failure (TTF). Results: In EGFR TKI-naive patients (n ¼ 315), afatinib demonstrated activity against major uncommon mutations (median TTF ¼ 10.8 mo; 95% confidence interval [CI]: 8.1-16.6; ORR ¼ 60.0%), compound mutations (median TTF ¼ 14.7 mo; 95% CI: 6.8-18.5; ORR ¼ 77.1%), other uncommon mutations (median TTF ¼ 4.5 mo; 95% CI: 2.9-*Corresponding author.

Epidermal growth factor receptor (EGFR) mutations typically occur in exons 18–21 and are established driver mutations in non-small cell lung cancer (NSCLC)1–3. Targeted therapies are approved for patients with ‘classical’ mutations and a small number of other mutations4–6. However, effective therapies have not been identified for additional EGFR mutations. Furthermore, the frequency and effects of atypical EGFR mutations on drug sensitivity are unknown1,3,7–10. Here we characterize the mutational landscape in 16,715 patients with EGFR-mutant NSCLC, and establish the structure–function relationship of EGFR mutations on drug sensitivity. We found that EGFR mutations can be separated into four distinct subgroups on the basis of sensitivity and structural changes that retrospectively predict patient outcomes following treatment with EGFR inhibitors better than traditional exon-based groups. Together, these data delineate a structure-based approach for defining functional groups of EGFR mutations that can effectively guide treatment and clinical trial choices for patients with EGFR-mutant NSCLC and suggest that a structure–function-based approach may improve the prediction of drug sensitivity to targeted therapies in oncogenes with diverse mutations.

Commonly, circulating tumor cells (CTCs) are described as source of metastasis in cancer patients. However, in this process cancer cells of the primary tumor site need to survive the physical and biological challenges in the blood stream before leaving the circulation to become the seed of a new metastatic site in distant parenchyma. Most of the CTCs released in the blood stream will not resist those challenges and will consequently fail to induce metastasis. A few of them, however, interact closely with other blood cells, such as neutrophils, platelets, and/or macrophages to survive in the blood stream. Recent studies demonstrated that the interaction and modulation of the blood microenvironment by CTCs is pivotal for the development of new metastasis, making it an interesting target for potential novel treatment strategies. This review will discuss the recent research on the processes in the blood microenvironment with CTCs and will outline currently investigated treatment strategies.

Definition of tumor mutational burden (TMB) TMB can be defined as the total number of nonsynonymous mutations in the tumor exome (1). Tumor cells are genetically unstable and harbor high levels of somatic mutations which may result in the expression of neoantigens, that are not subject to immune tolerance (2). The presentation of tumor-specific neoantigens on major histocompatibility complex molecules is essential for the recognition of tumors by the T-cells. Patient-specific neoantigens that develop following somatic mutations have been shown to induce a T-cell response (3,4). The

The emergence of immunotherapy as a first-or second-line of treatment has revolutionized the therapeutic management of lung cancer patients. However, not all lung cancer patients receive the same benefit from this treatment, leading to limitations in the number of patients who can receive anti-PD-1/ PD-L1 checkpoint inhibitors because some secondary toxicity has been associated with immunotherapy, and because some patients would benefit more from chemotherapy. In this context, the selection of patients is currently based on PD-L1 immunohistochemistry (IHC), specifically on the percentage of PD-L1 positive tumor cells. To date, this is the only validated biomarker that is used as a companion diagnostic test for immunotherapy in non-small cell carcinoma lung (NSCLC) patients. However, this biomarker is not sufficiently robust and demonstrates many challenges. For example, some patients with more than 50% PD-L1 positive tumor cells are non-responders to anti-PD-1/PD-L1 treatment, while conversely, other patients with no PD-L1 positive tumor cells are good responders. The tumor mutation burden (TMB) or tumor mutation load (TML) emerged recently as a new predictive biomarker for immunotherapy response in NSCLC. However, this biomarker needs to be validated for routine clinical use and shares similar constraints with the PD-L1 IHC biomarker. PD-L1 IHC and TMB are currently the two best predictive biomarkers that could soon be used to systematically inform treatment decisions in advanced or metastatic NSCLC patients. The aim of this review is to consider the possible integration of TMB testing in daily practice through a pros-and cons-debate, and to establish sample quality-dependent algorithms and the main current constraints for laboratories considering TMB assessments.

COVID-19 is an infectious disease caused by SARS-CoV-2, which enters host cells via the cell surface proteins ACE2 and TMPRSS2. Using normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2. We find that ACE2 expression is restricted to a select population of highly epithelial cells and is repressed by ZEB1, in concert with ZEB1's established role in promoting epithelial to mesenchymal transition (EMT). Notably, infection of lung cancer cells with SARS-CoV-2 induces metabolic and transcriptional changes consistent with EMT, including upregulation of ZEB1 and AXL, thereby downregulating ACE2 postinfection. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state and lose ACE2 expression, along with its acute respiratory distress syndrome-protective effect, in a ZEB1-dependent manner. AXL-inhibition and ZEB1-reduction, as with bemcentinib, offers a potential strategy to reverse this effect.

Introduction: The detection of a ROS1 rearrangement in advanced and metastatic lung adenocarcinoma (LUAD) led to a targeted treatment with tyrosine kinase inhibitors with favorable progression-free survival and overall survival of the patients. Thus, it is mandatory to screen for the ROS1 rearrangement in all these patients. ROS1 rearrangements can be detected using break-apart fluorescence in situ hybridization (FISH), which is the gold standard; however, ROS1 immunohistochemistry (IHC) can be used as a screening test because it is widely available, easy and rapid to perform, and cost-effective.Methods: We evaluated the diagnostic accuracy and interpathologist agreement of two anti-ROS1 IHC clones, SP384 (Ventana, Tucson, Arizona) and D4D6 (Cell Signaling, Danvers, Massachusetts), in a training cohort of 51 positive ROS1 FISH LUAD cases, and then in a large validation cohort