Targeted Therapies for Lung Cancer Patients With Oncogenic Driver Molecular Alterations

Lung cancer has traditionally been classified by histology. However, a greater understanding of disease biology and the identification of oncogenic driver alterations has dramatically altered the therapeutic landscape. Consequently, the new classification paradigm of non–small-cell lung cancer is further characterized by molecularly defined subsets actionable with targeted therapies and the treatment landscape is becoming increasingly complex. This review encompasses the current standards of care for targeted therapies in lung cancer with driver molecular alterations. Targeted therapies for EGFR exon 19 deletion and L858R mutations, and ALK and ROS1 rearrangements are well established. However, there is an expanding list of approved targeted therapies including for BRAF V600E, EGFR exon 20 insertion, and KRAS G12C mutations, MET exon 14 alterations, and NTRK and RET rearrangements. In addition, there are numerous other oncogenic drivers, such as HER2 exon 20 insertion mutations, for wh..... READ ARTICLE

Journal of Clinical Oncology DOI:10.1200/JCO.21.01626

Authors: Aaron C. Tan and Daniel S. W. Tan

Review PaperKirk SmithJanuary 5, 2022targetable oncogenic driver, precision oncology

JuLI: accurate detection of DNA fusions in clinical sequencing for precision oncology

Accurate detection of genomic fusions by high-throughput sequencing in clinical samples with inadequate tumor purity and formalin-fixed paraffin embedded (FFPE) tissue is an essential task in precise oncology. We developed the fusion detection algorithm Junction Location Identifier (JuLI) for optimization of high-depth clinical sequencing. We implemented novel filtering steps to minimize false positives and a joint calling function to increase sensitivity in clinical setting. We comprehensively validated the algorithm using high-depth sequencing data from cancer cell lines and clinical samples and whole genome sequencing data from NA12878. We showed that JuLI outperformed state-of-the-art fusion callers in cases with high-depth clinical sequencing and rescued a driver fusion from false negative in plasma cell-free DNA. JuLI is freely available via GitHub (https://github.com/sgilab/JuLI). READ ARTICLE

The Journal of Molecular Diagnostics DOI:10.1016/j.jmoldx.2019.10.015

Authors: Hyun-Tae Shin, Nayoung K. D. Kim, Jae Won Yun, Boram Lee, Sungkyu Kyung, Ki-Wook Lee, Daeun Ryu, Jinho Kim, Joon Seol Bae, Donghyun Park, Yoon-La Choi, Se-Hoon Lee, Myung-Ju Ahn, Keunchil Park, Woong-Yang Park

Pre-ClinicalKirk SmithDecember 24, 2019JuLI, DNA fusions, clinical sequencing, precision oncology