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

Published On 2024/1/20

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 …

Published On

2024/1/20

Volume

42

Page

12-12

Authors

Bert Vogelstein

Bert Vogelstein

Johns Hopkins University

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Kenneth Kinzler

Kenneth Kinzler

Johns Hopkins University

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Jeremy Shapiro

Jeremy Shapiro

Monash University

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Rachel Wong

Rachel Wong

Monash University

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Gastrointestinal and lung cancers

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Christopher Douville

Christopher Douville

Johns Hopkins University

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Other Articles from authors

Christopher Douville

Christopher Douville

Johns Hopkins University

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

Rachel Wong

Rachel Wong

Monash University

ESMO Real World Data and Digital Oncology

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BackgroundThis study explores the potential benefits of neoadjuvant chemotherapy in borderline resectable (BR) pancreatic adenocarcinoma. Despite neoadjuvant treatment (NAT) increasingly being utilised, uncertainty remains as to the optimal approach.Patients and methodsThis study assessed clinical outcomes for 218 consecutive BR patients from the PURPLE registry. We compared initial surgery (IS) to NAT overall, and between different chemotherapy regimens.ResultsOf 1314 non-metastatic patients enrolled, 218 (17%) were considered BR. Of 28 planned for IS, 11/28 (39%) had their tumour excised compared to 68/152 (45%) with NAT (P = 0.59). Among those who received NAT and were resected, 52/100 (52%) received FOLFIRINOX (P = 0.234) and 8/28 (29%) received nab-paclitaxel with gemcitabine (nabPGem). There was no difference in median overall survival (OS) [hazard ratio (HR) 0.72, P = 0 …

Kenneth Kinzler

Kenneth Kinzler

Johns Hopkins University

Nature

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 …

Kenneth Kinzler

Kenneth Kinzler

Johns Hopkins University

Science Translational Medicine

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 …

Bert Vogelstein

Bert Vogelstein

Johns Hopkins University

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.

Bert Vogelstein

Bert Vogelstein

Johns Hopkins University

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

Christopher Douville

Christopher Douville

Johns Hopkins University

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.

Jeremy Shapiro

Jeremy Shapiro

Monash University

ESMO Real World Data and Digital Oncology

Impact of neoadjuvant FOLFIRINOX over upfront resection in borderline resectable pancreatic cancer—an international, multicentre, real-world analysis

BackgroundThis study explores the potential benefits of neoadjuvant chemotherapy in borderline resectable (BR) pancreatic adenocarcinoma. Despite neoadjuvant treatment (NAT) increasingly being utilised, uncertainty remains as to the optimal approach.Patients and methodsThis study assessed clinical outcomes for 218 consecutive BR patients from the PURPLE registry. We compared initial surgery (IS) to NAT overall, and between different chemotherapy regimens.ResultsOf 1314 non-metastatic patients enrolled, 218 (17%) were considered BR. Of 28 planned for IS, 11/28 (39%) had their tumour excised compared to 68/152 (45%) with NAT (P = 0.59). Among those who received NAT and were resected, 52/100 (52%) received FOLFIRINOX (P = 0.234) and 8/28 (29%) received nab-paclitaxel with gemcitabine (nabPGem). There was no difference in median overall survival (OS) [hazard ratio (HR) 0.72, P = 0 …

Christopher Douville

Christopher Douville

Johns Hopkins University

GENOME BIOLOGY

Critical assessment of genome interpretation consortium. CAGI, the critical assessment of genome interpretation, establishes progress and pprospects for computational genetic …

Background: The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors. Results: Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic. Conclusions: Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.Critical assessment of genome interpretation consortium. CAGI, the critical assessment of genome interpretation, establishes progress and pprospects for computational genetic variant interpretation methods/Jain, Shantanu; Bakolitsa, Constantina; E Brenner, Steven; Radivojac, Predrag; Moult, John; Repo, Susanna; A Hoskins, Roger; Andreoletti, Gaia; Barsky, Daniel; Chellapan, Ajithavalli; Chu, Hoyin; Dabbiru, Navya; K Kollipara, Naveen; Ly, Melissa; J Neumann, Andrew; R Pal, Lipika; Odell, Eric; Pandey, Gaurav; C Peters …

Kenneth Kinzler

Kenneth Kinzler

Johns Hopkins University

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 …

Bert Vogelstein

Bert Vogelstein

Johns Hopkins University

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.

Bert Vogelstein

Bert Vogelstein

Johns Hopkins University

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.

Jeremy Shapiro

Jeremy Shapiro

Monash University

Clinical Genitourinary Cancer

Carboplatin in Metastatic Castrate Resistant Prostate Cancer: A retrospective study of heavily pre-treated patients (COMPACT)

IntroductionMany clinicians consider carboplatin monotherapy in advanced castrate-resistant prostate cancer (CRPC) patients who have progressed through all available hormonal and standard chemotherapy treatment options, despite the limited evidence to justify its use.Patients and MethodsThis retrospective analysis aimed to evaluate the use of carboplatin monotherapy in patients with refractory prostate cancer in Australia. Efficacy (PSA response, duration, and survival) as well as toxicity was evaluated. Demographic data, PSA response rates, survival data and details of carboplatin treatment protocols, including dose and duration, were collected. Exploratory analyses were conducted on potential prognostic factors.Results51 patients received carboplatin: median age 68 (range 55–86 years). Most patients (78.3%) received carboplatin AUC 5 at 3-week intervals. The median number of cycles of carboplatin …

Christopher Douville

Christopher Douville

Johns Hopkins University

The American Journal of Surgical Pathology

Morphologic and Molecular Heterogeneity of High-grade Serous Carcinoma Precursor Lesions

Serous tubal intraepithelial carcinoma (STIC) is the fallopian tube precursor lesion for most cases of pelvic high-grade serous carcinoma (HGSC). To date, the morphologic, molecular, and clinical heterogeneity of STIC and a less atypical putative precursor lesion, termed serous tubal intraepithelial lesion, has not been well characterized. Better understanding of precursor heterogeneity could impact the clinical management of women with incidental STICs (without concurrent carcinoma) identified in cases of prophylactic or opportunistic salpingectomy. This study analyzed morphologic and molecular features of 171 STICs and 21 serous tubal intraepithelial lesions. We assessed their histologic features, Ki-67 and p53 staining patterns, and genome-wide DNA copy number alterations. We classified all precursor lesions into 2 morphologic subtypes, one with a flat surface (Flat) and the other characterized by budding …

Christopher Douville

Christopher Douville

Johns Hopkins University

CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

Background The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The fve complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors. Results Performance was particularly strong for clinical pathogenic variants, including some difcult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical efects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less defnitive and indicates performance potentially suitable for auxiliary use in the clinic. Conclusions Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly la

Rachel Wong

Rachel Wong

Monash University

Clinical Colorectal Cancer

Adjuvant Chemotherapy for Older Patients With Stage III Colorectal Cancer: A Real-World Analysis of Treatment Recommendations, Treatment Administered and Impact on Cancer …

BackgroundA substantial proportion of patients with stage III colorectal cancer (CRC) are older than 70 years. Optimal adjuvant chemotherapy (AC) for older patients (OP) continues to be debated, with subgroup analyses of randomized trials not demonstrating a survival benefit from the addition of oxaliplatin to a fluoropyrimidine backbone.Patients and MethodsWe analyzed the multisite Australian ACCORD registry, which prospectively collects patient, tumor and treatment data along with long term clinical follow-up. We compared OP (≥70) with stage III CRC to younger patients ([YP] <70), including the proportion recommended AC and any reasons for not prescribing AC. AC administration, regimen choice, completion rates, and survival outcomes were also examined.ResultsOne thousand five hundred twelve patients enrolled in the ACCORD registry from 2005 to 2018 were included. Median follow-up was 57.0 …

Kenneth Kinzler

Kenneth Kinzler

Johns Hopkins University

Methods and materials for treating t cell cancers

LOKCTEFSRHRXRJ-UHFFFAOYSA-I dipotassium trisodium dihydrogen phosphate hydrogen phosphate dichloride Chemical compound P (= O)(O)(O)[O-].[K+]. P (= O)(O)([O-])[O-].[Na+].[Na+].[Cl-].[K+].[Cl-].[Na+] LOKCTEFSRHRXRJ-UHFFFAOYSA-I 0.000 description 8

Kenneth Kinzler

Kenneth Kinzler

Johns Hopkins University

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