Isabel Jabara
Ph.D. Student in Biology, admitted Autumn 2021
All Publications
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Phase 2 study of amivantamab plus lazertinib in previously-treated patients with EGFR mutant lung cancers with brain and leptomeningeal metastases.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
2025
Abstract
Despite improved central nervous system (CNS) disease control with osimertinib, 20% of patients will develop CNS progression. Amivantamab and lazertinib have demonstrated activity in patients with EGFR-mutant lung cancer. This trial evaluated amivantamab and lazertinib in patients with new or progressive CNS metastases after prior therapy (NCT04965090).We evaluated amivantamab and lazertinib in 2 cohorts: patients with 1) brain metastases (BrM) or 2) leptomeningeal disease (LMD) diagnosed by cytology in patients with lung cancers with sensitizing EGFR-activating mutations or exon 20 insertions. The primary endpoint was composite best overall response rate (ORR) per RECIST v 1.1 and RANO-BM or -LM. Secondary endpoints were toxicity, systemic ORR, CNS ORR, time on treatment (ToT), progression-free survival (PFS), CNS PFS, and overall survival (OS).We treated 20 pts with BrM and 21 pts with LMD. 41% had EGFR del19, 37% L858R, 12% ex20ins, and 10% uncommon mutations. Median lines of prior therapy: 2 (range 1-7). The ORR by a combination of RECIST and RANO-BM/RANO-LM respectively for pts with BrM was 50% (95% CI, 27-73%) and 33% (95% CI, 15-57%) for pts with LMD. The median PFS was 5.8 months (95% CI 3.6-not reached (NR)) and 7.8 months (95% CI 4.2-12.2) for the BrM and LMD cohorts respectively. Median OS was 17.4 months (15.4-NR) in the BrM cohort and 14.4 months (8.9-NR) in the LMD cohort.Amivantamab+lazertinib has anti-tumor activity in patients with EGFR-mutant lung cancers who develop new or progressing brain or leptomeningeal metastases. This trial demonstrates the feasibility of including patients with LMD in prospective clinical trials.
View details for DOI 10.1016/j.jtho.2025.10.012
View details for PubMedID 41139066
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An ultrasensitive method for detection of cell-free RNA.
Nature
2025
Abstract
Sensitive methods for detection of cell-free RNA (cfRNA) could facilitate non-invasive gene expression profiling and monitoring of diseases1-6. Here we describe RARE-seq (random priming and affinity capture of cfRNA fragments for enrichment analysis by sequencing), a method optimized for cfRNA analysis. We demonstrate that platelet contamination can substantially confound cfRNA analyses and develop an approach to overcome it. In analytical validations, we find RARE-seq to be approximately 50-fold more sensitive for detecting tumour-derived cfRNA than whole-transcriptome RNA sequencing (RNA-seq), with a limit of detection of 0.05%. To explore clinical utility, we profiled 437 plasma samples from 369 individuals with cancer or non-malignant conditions and controls. Detection of non-small-cell lung cancer expression signatures in cfRNA increased with stage (6 out of 20 (30%) in stage I; 5 out of 8 (63%) in stage II; 10 out of 15 (67%) in stage III; 80 out of 96 (83% sensitivity) in stage IV at 95% specificity) and RARE-seq was more sensitive than tumour-naive circulating tumour DNA (ctDNA) analysis. In patients with EGFR-mutant non-small-cell lung cancer who developed resistance to tyrosine kinase inhibitors, we detected both histological transformation and mutation-based resistance mechanisms. Finally, we demonstrate the potential utility of RARE-seq for determination of tissue of origin, assessing benign pulmonary conditions and tracking response to mRNA vaccines. These results highlight the potential value of ultrasensitive cfRNA analysis and provide proof of concept for diverse clinical applications.
View details for DOI 10.1038/s41586-025-08834-1
View details for PubMedID 40240612
View details for PubMedCentralID 8060291
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A phase 2 study of amivantamab plus lazertinib in patients with <i>EGFR</i>-mutant lung cancer and active central nervous system disease
LIPPINCOTT WILLIAMS & WILKINS. 2024
View details for Web of Science ID 001275557402015