Publications by authors named "Vanessa V Michelini"
Identification of targetable BRAF ΔN486_P490 variant by whole-genome sequencing leading to dabrafenib-induced remission of a -mutant pancreatic adenocarcinoma.
Cold Spring Harb Mol Case Stud
December 2019
The tumor genome of a patient with advanced pancreatic cancer was sequenced to identify potential therapeutic targetable mutations after standard of care failed to produce any significant overall response. Matched tumor-normal whole-genome sequencing revealed somatic mutations in , , , and a focal deletion of The variant was an in-frame deletion mutation (ΔN486_P490), which had been previously demonstrated to be a kinase-activating alteration in the BRAF kinase domain. Working with the Novartis patient assistance program allowed us to treat the patient with the BRAF inhibitor, dabrafenib.
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Article Synopsis
- A clinical study was conducted in New York City with 30 glioblastoma patients to compare the effectiveness of whole genome sequencing (WGS) and RNA sequencing (RNA-seq) against targeted panel sequencing in identifying treatment options.
- WGS/RNA-seq uncovered significantly more actionable clinical results—90% of the time—with an average of 16 times more unique variants identified, leading to 84 calls for actionable treatments that targeted panels missed.
- The study found good agreement between manual and automated variant identification, showing that clinicians modified treatment plans based on this data in 10% of cases, marking a significant advancement in cancer treatment analysis.
Evaluating Clinical Genome Sequence Analysis by Watson for Genomics.
Front Med (Lausanne)
November 2018
Oncologists increasingly rely on clinical genome sequencing to pursue effective, molecularly targeted therapies. This study assesses the validity and utility of the artificial intelligence Watson for Genomics (WfG) for analyzing clinical sequencing results. This study identified patients with solid tumors who participated in in-house genome sequencing projects at a single cancer specialty hospital between April 2013 and October 2016.
View Article and Find Full Text PDFBackground: Using next-generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human "molecular tumor boards" (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB.
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- The study aimed to analyze a glioblastoma tumor specimen using three different methods to identify actionable variants.
- Tumor DNA was assessed through targeted panel analysis, whole-genome sequencing (WGS), and RNA sequencing (RNA-seq), with data evaluated by both human experts and IBM Watson Genomic Analytics (WGA).
- Results showed that WGS and RNA-seq identified more variants than targeted panels, and WGA performed the analysis much faster than human analysts, highlighting the potential for improved patient care with human-machine collaboration.