Lung cancer treatment has changed in the last twenty years since the discovery of EGFR mutations. In this article, we will review the current state of the art for non-small cell lung cancer (NSCLC) actionable genomic alterations (AGA). AGAs are mostly found in lung adenocarcinomas, a subtype of non-small cell lung cancers. We will focus on the current treatment for EGFR mutations, ALK fusions, ROS1 fusions, BRAF V600E mutations, MET exon 14-skipping mutations, RET fusions, KRAS G12C mutations, ERBB2 mutations (also called HER2 mutations), and NTRK fusions. We will also touch on the key toxicities associated with these medications. Treatments are mostly available for the metastatic stage, but we will also discuss adjuvant therapy for EGFR mutations and ALK fusions, as well as stage III post-chemoradiotherapy treatment for EGFR lung cancer.

Rearrangements in the anaplastic lymphoma kinase (ALK) gene are found in approximately 5% of non–small cell lung carcinoma (NSCLC). Here, we present a comprehensive genomic landscape of 11 patients with ALK+ NSCLC and investigate its relationship with response to crizotinib. Using whole-exome sequencing and RNAseq data, we identified four rare ALK fusion partners (HIP1, GCC2, ERC1, and SLC16A7) and one novel partner (CEP55). At the mutation level, TP53 was the most frequently mutated gene and was only observed in patients with the shortest progression-free survival (PFS). Of note, only 4% of the genes carrying mutations are present in more than 1 patient. Analysis of somatic copy number aberrations (SCNA) demonstrated that a gain in EML4 was associated with longer PFS, and a loss of ALK or gain in EGFR was associated with shorter PFS. This study is the first to report a comprehensive view of the ALK+ NSCLC copy number landscape and to identify SCNA regions associated with clinical outcome. Our data show the presence of TP53 mutation as a strong prognostic indication of poor clinical response in ALK+ NSCLC. Furthermore, new and rare ALK fusion partners were observed in this cohort, expanding our knowledge in ALK+ NSCLC.

Lung cancer treatment has changed in the last twenty years since the discovery of EGFR mutations. In this article, we will review the current state of the art for non-small cell lung cancer actionable genomic alterations (AGA). AGA are mostly found in lung adenocarcinomas, a subtype of non-small cell lung cancers. We will focus on current treatment for EGFR mutations, ALK fusions, ROS1 fusions, BRAF V600E mutations, MET exon 14 skipping mutations, RET fusions, KRAS G12C mutations, ERBB2 mutations (also called HER2 mutations) and NTRK fusions. We will also touch on key toxicities associated with these medications. Treatments are mostly available for metastatic stage, but we will also discuss adjuvant therapy for EGFR mutations and ALK fusions as well as stage III post chemoradiotherapy treatment for EGFR lung cancer.

Since July 2017, pembrolizumab has been approved as a first-line treatment of metastatic non-small cell lung cancer (NSCLC) in patients with a PD-L1 score ≥ 50% in Quebec. Study objectives were to describe and assess the real-world use of pembrolizumab; report progression-free survival (PFS), overall survival (OS), and immune-related adverse events (IRAEs); and compare outcomes between a fixed dose (FD) and a weight-based capped dose (WCD). Medical records of patients treated in one of Quebec’s four adult university teaching hospitals who received pembrolizumab between 1 November 2017 and 31 October 2019 were reviewed and followed until 29 February 2020. Two hundred and seventy-nine patients were included. The median real-world PFS and OS were 9.4 (95% CI, 6.6 to 11.2) and 17.3 months (95% CI, 12.9 to not reached), respectively. IRAEs causing delays or treatment interruptions were seen in 34.4% of patients. Initiating treatment with a FD (49 patients) or using a WCD (230 patients) does not appear to affect PFS, OS, or the occurrence of IRAEs. The use of a WCD strategy allowed approximately CAD 5.8 million in savings during the course of our study. These findings support the effectiveness and safety of pembrolizumab in a real-world setting. The use of a WCD does not appear to have a negative impact on patient outcomes.

Background/Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of advanced non-small cell lung cancer (NSCLC), yet 70% of patients experience disease progression, underscoring the critical need for predictive biomarkers. Programmed death-ligand 1 (PD-L1) expression remains the most adopted biomarker for ICIs. With the emergence of machine learning, the development of radiomics algorithms based on CT scan images has demonstrated potential as a novel addition to the biomarker landscape in oncology. In this study, we aimed to develop a non-invasive surrogate of PD-L1 expression (rad-PDL1) derived from computed tomography (CT) scan imaging and compare its predictive value to pathological assessments. Furthermore, we evaluated its generalizability across advanced and limited-stage NSCLC. Methods: Radiomics features extracted from pretreatment CT were analyzed using a self-training pipeline that incorporated the feature tokenizer Transformer model to classify tumors as high vs. low PD-L1 expression. We included 482 advanced NSCLC patients treated with ICIs across three medical centers who were divided into training and hold-out validation sets. The algorithm was then further validated in an independent cohort of 51 patients with limited NSCLC treated with neoadjuvant ICI and chemotherapy. Results: Our pipeline demonstrated strong predictive performance in primary and independent validation (AUC = 0.75 and 0.68, accuracy = 0.73 and 0.69, respectively), highlighting its generalizability and adaptability to various disease stages. Kaplan–Meier curves revealed a longer progression-free survival for patients in the high rad-PDL1. Conclusions: These results demonstrate the feasibility of a CT-based radiomic surrogate of PD-L1 expression, showing partial generalization to an independent neoadjuvant cohort, while highlighting the need for larger prospective multi-site validation before clinical implementation.