Pembrolizumab for First-Line Treatment of Advanced Non-Small-Cell Lung Cancer: Analysis of Prognostic Factors of Outcomes.

BACKGROUND: In advanced non-small-cell lung cancer, without activating mutations and with PD-L1≥50%, Pembrolizumab monotherapy is the therapeutic standard in Europe. OBJECTIVE: To evaluate retrospectively the safety and efficacy of this drug and to investigate potential prognostic factors in daily clinical practice. METHODS: From September 2017 to September 2019, 205 consecutive patients from 14 Italian Medical Oncology Units were enrolled in the study. Gender, Age (> or <70 years), ECOG-PS (0-1 or 2), histology (squamous or nonsquamous), presence of brain, bone and liver metastases at baseline, PD-L1 score (>90% or <90%), smoking status (never or former or current) were applied to the stratified log-rank. Cox's proportional hazards model was used for multivariate analysis. RESULTS: At a median follow-up of 15.2 months, median progression-free and overall survival (mPFS and mOS) were 9.2 months (95% C.I., 4.8-13.5) and 15.9 months (95% C.I., not yet evaluable), respectively. Patients with Eastern Cooperative Oncology Group performance status (ECOG-PS) 2 had mPFS of 2.8 months (95% C.I., 2.1-3.4) and mOS of 3.9 months (95% C.I., 2.5-5.3). Patients with liver metastases at diagnosis had an mPFS of 3.2 months (95% C.I., 0.6-5.8) and an mOS of 6.0 months (95% C.I., 3.7-8.4). At multivariate analysis for OS gender, ECOG-PS 2, and presence of liver metastases were independent prognostic factors. CONCLUSION: Patients with ECOG-PS 2 derived little benefit from the use of first-line pembrolizumab. In patients with liver metastases, the association of pembrolizumab with platinum-based chemotherapy could be a better option than pembrolizumab alone.

KRAS and NRAS mutation detection in circulating DNA from patients with metastatic colorectal cancer using BEAMing assay: Concordance with standard biopsy and clinical evaluation.

Patients with metastatic colorectal cancer (mCRC) are routinely screened for either K- and N-RAS to select the appropriate treatment. The present study aimed to evaluate the concordance between K- and NRAS status in the tissue (either primary tumor or metastasis) and the plasma of patients with mCRC and to identify the associations between K- and NRAS mutations in ctDNA and the clinicopathological parameters. Samples from a total of 31 patients with mCRC with measurable disease according to the Response Evaluation Criteria in Solid Tumors were analyzed. For all patients, K- and NRAS status was determined in the tissue by matrix-assisted laser desorption/ionization time of flight mass spectrometry. For the detection of RAS mutations in cell-free tumor DNA also defined as circulating tumor DNA (ctDNA), the OncoBEAM® RAS CRC kit (Sysmex Inostics) was used. A total of 6/31 tissue samples expressed wild-type KRAS, whereas 25/31 presented mutations. In addition, 7/31 plasma samples expressed wild-type KRAS, mutations were detected in 22/31 patients, and for 2/31 patients, the test did not provide a conclusive result. A total of 24/31 patients expressed wild-type NRAS, 6/31 had mutations and 1/21 was not informative. For the KRAS mutational status, a moderate concordance (agreement, 85.18%; Cohen's k, 0.513) between the tissue and plasma analysis was observed; for NRAS, a fair agreement (agreement, 83.33%; Cohen's k, 0.242) was obtained. In conclusion, both tissue and plasma analyses should be performed for the management of patients with mCRC. To better exploit the beads, emulsions, amplification, magnetics (BEAMing) technique in the clinical setting, studies aimed at determining the RAS status to monitor therapy and during follow-up are warranted.

Metabolomics to Assess Response to Immune Checkpoint Inhibitors in Patients with Non-Small-Cell Lung Cancer.

In the treatment of advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitors have shown remarkable results. However, not all patients with NSCLC respond to this drug treatment or receive durable benefits. Thus, patient stratification and selection, as well as the identification of predictive biomarkers, represent pivotal aspects to address. In this framework, metabolomics can be used to support the discrimination between responders and non-responders. Here, metabolomics was used to analyze the sera samples from 50 patients with NSCL treated with immune checkpoint inhibitors. All the samples were collected before the beginning of the treatment and were analyzed by NMR spectroscopy and multivariate statistical analyses. Significantly, we show that the metabolomic fingerprint of serum acts as a predictive "collective" biomarker to immune checkpoint inhibitors response, being able to predict individual therapy outcome with > 80% accuracy. Metabolomics represents a potential strategy for the real-time selection and monitoring of patients treated with immunotherapy. The prospective identification of responders and non-responders could improve NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies.