Bert Vogelstein

Bert Vogelstein

Johns Hopkins University

H-index: 289

North America-United States

Professor Information

University

Johns Hopkins University

Position

___

Citations(all)

497107

Citations(since 2020)

96773

Cited By

444283

hIndex(all)

289

hIndex(since 2020)

144

i10Index(all)

770

i10Index(since 2020)

565

Email

University Profile Page

Johns Hopkins University

Research & Interests List

Cancer

Biology

Top articles of Bert Vogelstein

Circulating mutant dna to assess tumor dynamics

DNA containing somatic mutations is highly tumor specific and thus, in theory, can provide optimum markers. However, the number of circulating mutant gene fragments is small compared to the number of normal circulating DNA fragments, making it difficult to detect and quantify them with the sensitivity required for meaningful clinical use. We apply a highly sensitive approach to quantify circulating tumor DNA (ctDNA) in body samples of patients. Measurements of ctDNA can be used to reliably monitor tumor dynamics in subjects with cancer, especially those who are undergoing surgery or chemotherapy. This personalized genetic approach can be generally applied.

Published Date

2024/1/4

Methods of detecting high risk barrett's esophagus with dysplasia, and esophageal adenocarcinoma

AOJJSUZBOXZQNB-VTZDEGQISA-N 4'-epidoxorubicin Chemical compound O ([C@ H] 1C [C@@](O)(CC= 2C (O)= C3C (= O) C= 4C= CC= C (C= 4C (= O) C3= C (O) C= 21) OC) C (= O) CO)[C@ H] 1C [C@ H](N)[C@@ H](O)[C@ H](C) O1 AOJJSUZBOXZQNB-VTZDEGQISA-N 0.000 claims description 6GAGWJHPBXLXJQN-UORFTKCHSA-N Capecitabine Chemical compound C1= C (F) C (NC (= O) OCCCCC)= NC (= O) N1 [C@ H] 1 [C@ H](O)[C@ H](O)[C@@ H](C) O1 GAGWJHPBXLXJQN-UORFTKCHSA-N 0.000 claims description 6

Published Date

2024/2/29

Signal

A method for classifying data using non-negative matrix factorization can include receiving a population of sample data, generating a first matrix of the amplicon counts per sample data, dividing the first matrix into a product of a second matrix and a third matrix, in the second matrix, determining whether each signature is a long or short fragment per each amplicon count, in the third matrix, determining intensities of each signature per the sample data, and classifying the sample data based on the intensities of each signature. The population can include amplicon counts per sample data. The second matrix can include signatures of short and long DNA fragments and the third matrix can include intensities of each signature of the short and long DNA fragments.

Published Date

2024/2/8

Methods and materials for treating clonal t cell expansions

This document relates to methods and materials for treating T cell cancers. For example, a composition containing one or more bispecific molecules targeting T cell receptor É chain constant region (TRBC) can be administered to a mammal having a T cell cancer to treat the mammal. For example, this document provides methods and materials for using one or more bispecific molecules to treat a mammal having a T cell cancer.

Published Date

2024/4/18

Machine learning to detect the SINEs of cancer

We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a machine learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to 7615 samples from 5178 individuals, 2073 with solid cancer and the remainder without cancer. Samples from patients with cancer and controls were prespecified into four cohorts used for model training, analyte integration, and threshold determination, validation, and reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the …

Authors

Christopher Douville,Kamel Lahouel,Albert Kuo,Haley Grant,Bracha Erlanger Avigdor,Samuel D Curtis,Mahmoud Summers,Joshua D Cohen,Yuxuan Wang,Austin Mattox,Jonathan Dudley,Lisa Dobbyn,Maria Popoli,Janine Ptak,Nadine Nehme,Natalie Silliman,Cherie Blair,Katharine Romans,Christopher Thoburn,Jennifer Gizzi,Robert E Schoen,Jeanne Tie,Peter Gibbs,Lan T Ho-Pham,Bich NH Tran,Thach S Tran,Tuan V Nguyen,Michael Goggins,Christopher L Wolfgang,Tian-Li Wang,Ie-Ming Shih,Anne Marie Lennon,Ralph H Hruban,Chetan Bettegowda,Kenneth W Kinzler,Nickolas Papadopoulos,Bert Vogelstein,Cristian Tomasetti

Journal

Science Translational Medicine

Published Date

2024/1/24

TRBC1-targeting antibody–drug conjugates for the treatment of T cell cancers

Antibody and chimeric antigen receptor (CAR) T cell-mediated targeted therapies have improved survival in patients with solid and haematologic malignancies 1, 2, 3, 4, 5, 6, 7, 8, 9. Adults with T cell leukaemias and lymphomas, collectively called T cell cancers, have short survival 10, 11 and lack such targeted therapies. Thus, T cell cancers particularly warrant the development of CAR T cells and antibodies to improve patient outcomes. Preclinical studies showed that targeting T cell receptor β-chain constant region 1 (TRBC1) can kill cancerous T cells while preserving sufficient healthy T cells to maintain immunity 12, making TRBC1 an attractive target to treat T cell cancers. However, the first-in-human clinical trial of anti-TRBC1 CAR T cells reported a low response rate and unexplained loss of anti-TRBC1 CAR T cells 13, 14. Here we demonstrate that CAR T cells are lost due to killing by the patient’s normal T …

Authors

Tushar D Nichakawade,Jiaxin Ge,Brian J Mog,Bum Seok Lee,Alexander H Pearlman,Michael S Hwang,Sarah R DiNapoli,Nicolas Wyhs,Nikita Marcou,Stephanie Glavaris,Maximilian F Konig,Sandra B Gabelli,Evangeline Watson,Cole Sterling,Nina Wagner-Johnston,Sima Rozati,Lode Swinnen,Ephraim Fuchs,Drew M Pardoll,Kathy Gabrielson,Nickolas Papadopoulos,Chetan Bettegowda,Kenneth W Kinzler,Shibin Zhou,Surojit Sur,Bert Vogelstein,Suman Paul

Journal

Nature

Published Date

2024/4

Circulating tumor DNA analysis informing adjuvant chemotherapy in locally advanced rectal cancer: The randomized AGITG DYNAMIC-Rectal study.

12Background: Adjuvant chemotherapy (CT) following neoadjuvant chemoradiation and surgery for locally advanced rectal cancer (LARC) is widely adopted, despite uncertain survival benefit. Circulating tumor DNA (ctDNA) detection after surgery has been shown to be a strong prognostic marker in localized colorectal cancer and potentially could inform adjuvant treatment decision making. Methods: AGITG DYNAMIC-Rectal is a multi-centre randomized controlled phase II trial. Eligible patients (pts) had LARC (cT3-4 and/or cN+) treated with neoadjuvant chemoradiation, total mesorectal excision, and were fit for adjuvant CT. Pts were randomly assigned 2:1 to ctDNA-guided management or standard management (clinician decision). A tumor-informed personalized ctDNA assay was used. For the ctDNA-guided group, a positive result at 4 and/or 7 weeks after surgery prompted 4 months of oxaliplatin-based or …

Authors

Jeanne Tie,Joshua D Cohen,Yuxuan Wang,Pablo Gonzalez Ginestet,Rachel Wong,Jeremy David Shapiro,Rob Campbell,Fiona Day,Theresa M Hayes,Morteza Aghmesheh,Christos Stelios Karapetis,Maria Popoli,Lisa Dobbyn,Janine Ptak,Natalie Silliman,Christopher B Douville,Nickolas Papadopoulos,Kenneth W Kinzler,Bert Vogelstein,Peter Gibbs

Published Date

2024/1/20

Safe sequencing system

The identification of mutations that are present in a small fraction of DNA templates is essential for progress in several areas of biomedical research. Though massively parallel sequencing instruments are in principle well-suited to this task, the error rates in such instruments are generally too high to allow confident identification of rare variants. We here describe an approach that can substantially increase the sensitivity of massively parallel sequencing instruments for this purpose. One example of this approach, called “Safe-SeqS” for (Safe-Sequencing System) includes (i) assignment of a unique identifier (UID) to each template molecule;(ii) amplification of each uniquely tagged template molecule to create UID-families; and (iii) redundant sequencing of the amplification products. PCR fragments with the same UID are truly mutant (“super-mutants”) if≥ 95% of them contain the identical mutation. We illustrate the …

Published Date

2023/10/3

Professor FAQs

What is Bert Vogelstein's h-index at Johns Hopkins University?

The h-index of Bert Vogelstein has been 144 since 2020 and 289 in total.

What are Bert Vogelstein's research interests?

The research interests of Bert Vogelstein are: Cancer, Biology

What is Bert Vogelstein's total number of citations?

Bert Vogelstein has 497,107 citations in total.

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