Poor PS, short period of time since the previous treatment, and more than one metastatic location were associated with poorer prognostic.

Purpose Treatment guidelines for advanced non–small-cell lung cancer (aNSCLC) recommend broad molecular profiling for targeted therapy selection. This study prospectively assessed comprehensive next-generation sequencing (NGS) of cell-free circulating tumor DNA (cfDNA) compared with standard-of-care (SOC) tissue-based testing to identify guideline-recommended alterations in aNSCLC. PATIENTS AND METHODS Patients with treatment-naïve aNSCLC were tested using a well-validated NGS cfDNA panel, and results were compared with SOC tissue testing. The primary objective was noninferiority of cfDNA vs. tissue analysis for the detection of two guideline-recommended biomarkers ( EGFR and ALK) and an additional six actionable biomarkers. Secondary analyses included tissue versus cfDNA biomarker discovery, overall response rate (ORR), progression-free survival (PFS) to targeted therapy, and positive predictive value (PPV) of cfDNA. RESULTS The primary objective was met with cfDNA identifying actionable mutations in 46 patients versus 48 by tissue ( P < .05). In total, 0/186 patients were genotyped for all eight biomarkers with tissue, compared with 90.8% using cfDNA. Targetable alterations or KRAS were identified in 80.7% when cfDNA was used first versus 57.1% when tissue was used first. PPV for cfDNA-detected EGFR was 100.0% (25/25). ORR and PFS in patients receiving targeted therapy based on tissue or cfDNA were similar to those previously reported. Conclusion This prospective study confirms a previous report that comprehensive cfDNA testing is noninferior to SOC tissue testing in detecting aNSCLC-recommended biomarkers. Furthermore, cfDNA-based first-line therapy produced outcomes similar to tissue-based testing, demonstrating the clinical utility of comprehensive cfDNA genotyping as the initial genotyping modality in patients with treatment-naïve aNSCLC when tissue is insufficient or when all actionable biomarkers cannot be rapidly assessed.

Numerous targeted therapies have been evaluated for the treatment of non-small cell lung cancer (NSCLC). To date, however, only a few agents have shown promising results. Recent advances in cancer immunotherapy, most notably immune checkpoint inhibitors (ICI), have transformed the treatment scenario for these patients. Although some patients respond well to ICIs, many patients do not benefit from ICIs, leading to disease progression and/or immune-related adverse events. New biomarkers capable of reliably predicting response to ICIs are urgently needed to improve patient selection. Currently available biomarkers—including programmed death protein 1 (PD-1) and its ligand (PD-L1), and tumor mutational burden (TMB)—have major limitations. At present, no well-validated, reliable biomarkers are available. Ideally, these biomarkers would be obtained through less invasive methods such as plasma determination or liquid biopsy. In the present review, we describe recent advances in the development of novel soluble biomarkers (e.g., circulating immune cells, TMB, circulating tumor cells, circulating tumor DNA, soluble factor PD-L1, tumor necrosis factor, etc.) for patients with NSCLC treated with ICIs. We also describe the potential use of these biomarkers as prognostic indicators of treatment response and toxicity.

After publication of the PACIFIC trial results, immune checkpoint inhibitor-based immunotherapy was included in the treatment algorithm of locally advanced non-small cell lung cancer (NSCLC). The PACIFIC trial demonstrated that 12 mo of durvalumab consolidation therapy after radical-intent platinum doublet chemotherapy with concomitant radiotherapy improved both progression-free survival and overall survival in patients with unresectable stage III NSCLC. This is the first treatment in decades to successfully improve survival in this clinical setting, with manageable toxicity and without deterioration in quality of life. The integration of durvalumab in the management of locally advanced NSCLC accentuates the need for multidisciplinary, coordinated decision-making among lung cancer specialists, bringing new challenges and controversies as well as important changes in clinical work routines. The aim of the present article is to review—from a practical, multidisciplinary perspective—the findings and implications of the PACIFIC trial. We evaluate the immunobiological basis of durvalumab as well as practical aspects related to programmed cell death ligand 1 determination. In addition, we comprehensively assess the efficacy and toxicity data from the PACIFIC trial and discuss the controversies and practical aspects of incorporating durvalumab into routine clinical practice. Finally, we discuss unresolved questions and future challenges. In short, the present document aims to provide clinicians with a practical guide for the application of the PACIFIC regimen in routine clinical practice.

Introduction Non-inferiority (NI) analysis is not usually considered in the early phases of clinical development. In some negative phase II trials, a post-hoc NI analysis justified additional phase III trials that were successful. However, the risk of false positive achievements was not controlled in these early phase analyses. We propose to preplan NI analyses in superiority-based Simon's two-stage designs to control type I and II error rates. Methods Simulations have been proposed to assess the control of type I and II errors rates with this method. A total of 12,768 two-stage Simon's design trials were constructed based on different assumptions of rejection response probability, desired response probability, type I and II errors, and NI margins. P-value and type II error were calculated with stochastic ordering using Uniformly Minimum Variance Unbiased Estimator. Type I and II errors were simulated using the Monte Carlo method. The agreement between calculated and simulated values was analyzed with Bland-Altman plots. Results We observed the same level of agreement between calculated and simulated type I and II errors from both two-stage Simon's superiority designs and designs in which NI analysis was allowed. Different examples has been proposed to explain the utility of this method. Conclusion Inclusion of NI analysis in superiority-based single-arm clinical trials may be useful for weighing additional factors such as safety, pharmacokinetics, pharmacodynamic, and biomarker data while assessing early efficacy. Implementation of this strategy can be achieved through simple adaptations to existing designs for one-arm phase II clinical trials.

Background: Studies of patients with cancer affected by coronavirus disease 2019 (COVID-19) are needed to assess the impact of the disease in this sensitive population, and the influence of different cancer treatments on the COVID-19 infection and seroconversion. Material and Methods: We performed a retrospective analysis of all patients hospitalized with RT-PCR positive for COVID-19 in our region to assess the prevalence of cancer patients and describe their characteristics and evolution (Cohort 1). Concurrently, a transversal study was carried out in patients on active systemic cancer treatment for symptomatology and seroprevalence (IgG/IgM by ELISA-method) against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) (Cohort 2). Results: A total of 215 patients (Cohort 1) were admitted to hospital with a confirmed COVID-19 infection between February 28 and April 30, 2020, and 17 died (7.9%). A medical record of cancer was noted in 43 cases (20%), 6 of them required Intensive care unit ICU attention (14%), and 7 died (16%). There were thirty-six patients (83%) who tested IgG/IgM positive for SARS-CoV-2. Patients on immunosuppressive therapies presented a lower ratio of seroconversion (40% vs. 8%; p = 0.02). In Cohort 2, 166 patients were included in a symptoms-survey and tested for SARS-CoV-2. Any type of potential COVID-19-related symptom was referred up to 67.4% of patients (85.9% vs. 48.2% vs. 73.9%, for patients on chemotherapy, immunotherapy and targeted therapies respectively, p < 0.05). The seroprevalence ratio was 1.8% for the whole cohort with no significant differences by patient or treatment characteristics. Conclusion: Patients with cancer present higher risks for hospital needs for COVID-19 infection. The lack of SARS-CoV-2 seroconversion may be a concern for patients on immunosuppressive therapies. Patients receiving systematic therapies relayed a high rate of potentially COVID-19-related symptoms, particularly those receiving chemotherapy. However, the seroconversion rate remains low and in the range of general population.

Method: Ten NSCLC patients' FFPE were retrieved for DNA extraction. All qualified samples were analyzed using NGS on 45 cancer genes panel on Ion Torrent system NGS Gene read Qiagen Lung Cancer Panel. Variants from NGS with coverage of are higher than 1000X. The cutoff 1% and 3% of variant allele frequency were considered positive. EGFR, BRAF, KRAS were validated by Real-time PCR technique using the Amoy DX and Actionable Insights Tumor Panel in GeneReader NGS system. Result: We found 90%/30% EGFR-mutation, 40% BRAF V600E, 70%/ 30% KRAS-mutation by NGS using allele frequency cutoff at 1% and 3%, respectively. We validated by Real-Time PCR and Actionable GeneReader showed 70%/40% EGFR-mutation, 20%/10% BRAF V600E, and 0%/30% of KRAS-mutation (Table1). Regarding EGFRmutation, 5 cases of discordance showed positive at 1% but negative at 3% cutoff allele frequency by NGS and validated by Real-Time showed positive all 5 cases. Two negative cases by Real-Time PCR show positive in NGS cutoff 1% (2/2) and 3% (1/2). In early stage (80%), there was 60% of EGFR 19 del detected by NGS cutoff 1%. The patients have continued follow-up at the clinic with the mDFS of 4.7 years. Two stage IV patients with exon19del were death and received EGFR-TKI as a second-line treatment with mOS at 1.1 and 1.2 years. Table 1 Conclusion: Different platform of NGS and different cutoff variant allele frequency gave the different result of gene frequency. We need to explore the standard of NGS testing including the proper cutoff for allele frequency in order to establish the most efficient method and correlate with the clinical treatment outcomes.

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