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Development and Validation of a Genomic Profile for the Omission of Local Adjuvant Radiation in Breast Cancer

Publication: Journal of Clinical Oncology

Abstract

Purpose

Adjuvant radiotherapy (RT) is used for women with early-stage invasive breast cancer treated with breast-conserving surgery. However, some women with low risk of recurrence may safely be spared RT. This study aimed to identify these women using a molecular-based approach.

Methods

We analyzed two randomized trials of women with node-negative invasive breast cancer to ± RT following breast-conserving surgery: SweBCG91-RT (stage I-II, no adjuvant systemic therapy) and Princess Margaret (age 50 years or older, T1-T2, adjuvant tamoxifen). Transcriptome-wide profiling was performed (Affymetrix Human Exon 1.0 ST microarray). Patients with estrogen receptor–positive/human epidermal growth factor receptor 2–negative tumors and with gene expression data were included. The SweBCG91-RT cohort was divided into training (N = 243) and validation (N = 354) cohorts. A 16-gene signature named Profile for the Omission of Local Adjuvant Radiation (POLAR) was trained to predict locoregional recurrence (LRR) using elastic net regression. POLAR was then validated in the SweBCG91-RT validation cohort and the Princess Margaret cohort (N = 132).

Results

Patients categorized as POLAR low-risk without RT had a 10-year LRR of 6% (95% CI, 2 to 16) and 7% (0 to 27) in SweBCG91-RT and Princess Margaret cohorts, respectively. There was no significant benefit from RT in POLAR low-risk patients (hazard ratio [HR], 1.1 [0.39 to 3.4], P = .81, and HR, 1.5 [0.14 to 16], P = .74, respectively). Patients categorized as POLAR high-risk had a significant decreased risk of LRR with RT (HR, 0.43 [0.24 to 0.78], P = .0055, and HR, 0.25 [0.07 to 0.92], P = .038, respectively). An exploratory analysis testing for interaction between RT and POLAR in the combined validation cohort was performed (P = .066).

Conclusion

The novel POLAR genomic signature on the basis of LRR biology may identify patients with a low risk of LRR despite not receiving RT, and thus may be candidates for RT omission.

Introduction

Multiple phase III randomized clinical trials have consistently demonstrated the benefit of whole-breast radiotherapy (RT) after breast-conserving surgery (BCS) in reducing locoregional recurrence (LRR), and RT is considered the standard of care for women with early-stage invasive breast cancer (BC).1-8 The Oxford Early Breast Cancer Trialists' Group meta-analysis demonstrated a two third relative risk reduction of local recurrence at 10 years for patients who receive RT, from 30% to 10%, along with a survival benefit of approximately 5% at 15 years.9,10 In addition to the improvement in locoregional disease control, these data also demonstrated the heterogeneity in response and benefit from adjuvant radiation. Even in the previous era of less effective systemic chemotherapy and limited use of endocrine therapy, up to 70% of women did not recur locally without RT, yet clinical tools to identify which women may safely forgo adjuvant radiation therapy are still lacking.

Context

Key Objective
Adjuvant radiotherapy (RT) after breast-conserving surgery for invasive breast cancer is effective at reducing locoregional recurrence (LRR). Although most women will not experience a LRR even without RT, tools to guide selection of patients who can safely omit RT are lacking. This study developed a novel gene expression signature for RT omission, which was tested in two randomized phase III trials of breast-conserving surgery ± RT.
Knowledge Generated
The Profile for the Omission of Local Adjuvant Radiotherapy identified estrogen receptor–positive/human epidermal growth factor receptor 2–negative patients at low risk of LRR without a significant benefit from RT, for whom omission may be considered, and patients at high risk of LRR with a significant benefit from RT, from whom standard-of-care RT should be considered.
Relevance (B.G. Haffty)
With larger validation studies, these data may help in the decision-making process to identify patients at low risk of local recurrence who may not derive significant benefit from postlumpectomy radiation.*
*Relevance section written by JCO Deputy Editor Bruce G. Haffty, MD.
Clinical risk factors such as older age, smaller tumor size, and estrogen receptor–positive (ER+) BCs have been associated with low risk of LRR,11 and attempts have been made to use these features to identify women who may omit RT after BCS. The CALGB 9343 trial enrolled women age 70 years or older with small, ER+ BCs resected with negative margins who were then randomly assigned to receive whole-breast RT and tamoxifen for 5 years or only tamoxifen daily.12 In this trial of over 600 women, RT decreased the risk of LRR at 10 years from 10% to 2% without affecting the rate of breast preservation. Similarly, the PRIME II trial included patients age 65 years or older with small ER+ BCs resected with negative margins who were treated with endocrine therapy and randomly assigned to RT or not. The recently reported 10-year results demonstrated a decrease in ipsilateral breast tumor recurrence (IBTR) from 9.8% to 0.9% with the addition of RT.13,14 As the rate of local recurrence at 10 years for those not treated with RT was 10% in both trials, it can be argued that the 80%-90% relative risk reduction at 10 years with the addition of radiation therapy may be too significant to omit RT in women who have a median life expectancy of above 80 years in the United States. Thus far, no subtype or clinicopathologic variable has been incorporated in clinical practice that predicts lack of benefit of adjuvant breast radiation, making radiation omission decisions challenging clinically.15-17
Interest in the use of genomically informed risk stratifiers has grown in recent years, given the success of such approaches in determining likelihood of systemic chemotherapy benefit in women with BC. Such molecularly informed tests have been shown to be prognostic of outcome in women with BC and/or predictive of benefit of chemotherapy in previous clinical trials.18-23 Although previous attempts to build local recurrence or radiation sensitivity signatures have been made, there exist no widely used signatures to select for patients who may omit radiation in early-stage invasive BC.24-28 In previous work, members of this group developed and validated ARTIC, a 27-gene clinicogenomic signature, prognostic for LRR and predictive for benefit from RT.26 This signature was able to identify patients at higher risk of LRR, with a reduced benefit from RT, and thus may be used to identify those who require intensified treatment. Signatures designed to estimate risk of distant recurrence after systemic therapy have been suggested for use for avoidance of RT, and these are being tested in the context of ongoing clinical trials, but long-term results of these trials will not be available for years to come.29
To this end, our objective was to identify biomarkers prognostic of LRR, develop a radiation omission signature, and test it in cohorts of patients randomly assigned to treatment with adjuvant whole-breast radiation. We hypothesized that identifying biomarkers prognostic for LRR in a cohort with well-defined and long-term recurrence information would lead to a signature able to identify patients at low risk who may safely omit RT.

Methods

Patient Cohorts

SweBCG91-RT was a randomized trial conducted in Sweden and has been described previously.1,15,26 Briefly, the trial randomly assigned 1,178 patients with node-negative, stage I-IIA BC to RT or no RT following BCS. Five hundred ninety‐seven samples from patients with ER+, human epidermal growth factor receptor 2–negative (HER2–) tumors and without treatment by systemic adjuvant therapy had available gene expression data and complete LRR information. Details are provided in the Data Supplement (online only). The trial and follow-up study were approved by the Regional Ethical Review Board at Lund University (2010/127 and 2015/548). Informed oral consent was obtained from all patients.
The Princess Margaret cohort was a randomized trial conducted in Canada and has been previously described.2,17 Briefly, the trial randomly assigned 769 women age 50 years or older with T1 or T2 node-negative BC to adjuvant whole-breast RT or no RT following BCS. All patients in the Princess Margaret trial were treated with tamoxifen. Gene expression data were available from 132 samples from patients with ER+, HER2− tumors and complete LRR information (Data Supplement). The trial and follow-up study were approved by the Research Ethics Board at University Health Network (11-0429).

Gene Expression Data

Gene expression data (Gene Expression Omnibus, GSE119295) were obtained from primary tumors of 764 patients included in the SweBCG91-RT trial.26 Similar to the SweBCG91-RT cohort, gene expression data for the Princess Margaret cohort were generated from GeneChip Human Exon 1.0 ST Arrays (Thermo Fisher Scientific, South San Francisco, CA) in a CLIA-/CAP-certified laboratory (Decipher Biosciences, San Diego, CA).

Development of Training and Validation Sets

In this analysis, only patients with ER+, HER2− tumors were included. Furthermore, as systemic therapy can influence LRR and only a small portion of SweBCG91-RT patients were treated systemically, patients treated with chemotherapy and/or endocrine therapy were removed from analysis of the SweBCG91-RT cohort to improve result interpretation. After these considerations, 597 patients of the SweBCG91-RT trial were included in this study. The 597 patients were split into a training cohort (N = 243) and a validation cohort (N = 354). For details, see the Data Supplement.

Gene Set Enrichment Analysis

To identify gene sets related to LRR, gene set enrichment analysis (GSEA) was performed within the 131 patients of the training cohort not treated with RT for genes that were prognostic for LRR in a Cox model.30,31 For details, see the Data Supplement.

Model Development

Top prognostic genes as potential candidates for model training were further filtered for being in the most enriched biological pathways in the GSEA and by having a large standard deviation. The resulting genes were fed into an elastic net regression model for training in the full training cohort, using LRR as the end point. This resulted in a final set of 16 genes for the model. The scores were dichotomized to high versus low by applying a prespecified cutoff using the subgroup of patients from the SweBCG91-RT validation dataset who did not receive radiotherapy and who had any progression (locoregional recurrence and/or distant metastasis) or no progression and at least 10 years of follow-up. This threshold was then applied to the SweBCG91-RT and Princess Margaret validation sets. For further details, see the Data Supplement.

Statistical Methods

The primary end point was cumulative incidence of LRR using time to LRR as first event. Cumulative incidences were computed using a competing risk approach, and hazard ratios (HRs) and tests for significant differences were calculated using cause-specific Cox proportional hazards regression. Distant metastasis and death without recurrence were considered competing events. Patients with synchronous distant metastasis and LRR, defined as LRR registered at the same time or within 3 months as the metastasis were regarded as having a LRR. HRs and point estimates are reported with 95% CIs in brackets. A P value < .05 was considered statistically significant. For details, see the Data Supplement.

Results

Biological Concepts Associated With Locoregional Recurrence

In patients not treated with RT in the SweBCG91-RT training cohort, we used GSEA to identify biological pathways associated with LRR in BC. The top positively enriched gene lists (associated with a higher risk for LRR) across the Molecular Signatures database Hallmark, C2 and C5 collections included lists involving cell cycle and proliferation (Data Supplement), whereas the top negatively enriched gene lists (associated with lower risk for LRR) included lists related to the immune system.
Top gene lists were intersected with the most informative and individually prognostic genes for LRR in the patients of the training set who were not given RT. A generalized linear model with elastic net regularization was trained using the LRR end point. The resulting 16-gene signature includes genes from the pathways identified from the GSEA analysis (Table 1). We named this signature the Profile for the Omission of Local Adjuvant Radiation (POLAR).
Table 1. Final 16 Genes Included in POLAR

POLAR Is Prognostic for LRR in Patients Not Treated With RT

In the SweBCG91-RT validation cohort, POLAR was prognostic for LRR in patients not treated with RT (n = 178) in a univariable Cox model with LRR as the end point (HR, 1.6 [1.2 to 2.1], P < .001). The signature remained prognostic in a multivariable model including age, tumor size, grade, and luminal A versus luminal B (HR, 1.6 [1.2 to 2.1], P = .002). In patients not treated with RT in the Princess Margaret data set (n = 62) who all received tamoxifen, POLAR had a similar HR with LRR as the end point, but the P value did not reach statistical significance (HR, 1.7 [0.9 to 2.9], P = .09; Table 2). Although the Princess Margaret cohort by itself had too few observations to allow for a multivariable analysis, the patients not treated with RT in both SweBCG91-RT and Princess Margaret data sets were analyzed together, stratified for cohort in a post hoc exploratory analysis to create univariable and multivariable Cox models. In the combined cohort, POLAR was prognostic for LRR in the univariable model (HR, 1.6 [1.3 to 2.0], P = .0001) and in the multivariable model that included age, tumor size, grade, and luminal A versus luminal B (HR, 1.5 [1.1 to 1.9], P = .006).
Table 2. Cox Proportional Hazards Regression Models for Prognostic Performance of the POLAR for Locoregional Recurrence in Patients Without RT in the SweBCG91-RT and Princess Margaret Validation Cohorts

Differential Effect of RT on Patients With Low and High POLAR Risk

The cumulative incidence of LRR for SweBCG91-RT patients categorized as low risk in the validation cohort by POLAR was < 10% at 10 years regardless of whether they received RT or not, and a benefit from RT could not be shown (10-year LRR cumulative incidence no RT: 6% [2 to 16], RT: 5% [1 to 13], HR = 1.1 [0.39 to 3.4], P = .81; Fig 1A). However, these results must be interpreted with caution, given the small number of patients (n = 108). For SweBCG91-RT patients categorized as high-risk by the signature, RT resulted in a significantly lower risk of LRR compared with those who did not receive RT (10-year locoregional cumulative incidence for no RT: 19% [13 to 27], RT: 8% [4 to 14], HR = 0.43 [0.24 to 0.78], P = .0055; Fig 1B).
Fig 1. Cumulative incidence of LRR with or without adjuvant RT in the SweBCG91-RT validation cohort for patients classified by POLAR as (A) low risk or (B) high risk. HRs of effect of RT and P values are calculated using a cause-specific Cox proportional hazards regression model. HR, hazard ratio; LRR, locoregional recurrence; POLAR, Profile for the Omission of Local Adjuvant Radiation; RT, radiotherapy.
We then evaluated POLAR in 132 patients of the Princess Margaret trial (Fig 2). For women treated with tamoxifen alone after BCS, patients categorized as low risk by POLAR had a 10-year cumulative incidence of LRR of 7% [0 to 27] without RT and 13% [2 to 34] with RT. A benefit from RT could not be shown in these low risk women (HR, 1.5 [0.14 to 16], P = .74), although the small number of patients (n = 34) preclude a definitive conclusion (Fig 2A). Women classified by POLAR as high risk had a cumulative incidence of LRR at 10 years of 22% [10 to 36] without RT, and 8% [2 to 20] with RT, and a significant benefit of RT (HR, 0.25 [0.07 to 0.92], P = .038).
Fig 2. Cumulative incidence of LRR with or without adjuvant RT in the Princess Margaret validation cohort for patients classified by POLAR as (A) low risk or (B) high risk. HRs of affect of RT and P values are calculated using a cause-specific Cox proportional hazards regression model. HR, hazard ratio; LRR, locoregional recurrence; POLAR, Profile for the Omission of Local Adjuvant Radiation; RT, radiotherapy.
Although understanding that the data may be underpowered for analysis even when combined, we performed a post hoc exploratory analysis by testing for interaction between RT and the continuous POLAR score in the total of N = 486 patients of the SweBCG91-RT and Princess Margaret evaluable samples, and the interaction P value was .066.

Discussion

In this study, we describe the development of POLAR, a 16-gene profile for the omission of local adjuvant radiation. For clinical utility, this signature would need to identify patients with a low risk of LRR in the absence of RT. Perhaps, more importantly, this signature would need to demonstrate which patients benefit from RT and which patients do not derive benefit. Using patient tumor samples from SweBCG91-RT, a previously completed phase III randomized trial of BCS ± radiation, we identified and incorporated top-performing biological pathways related to LRR in a genomic signature. Patients identified as low risk by this signature had a 10-year LRR risk of 6% (2 to 16) if treated with surgery alone, and RT could not be shown to provide a benefit. In the independent Princess Margaret cohort, we found similar results in patients who were treated with systemic endocrine therapy, although the results should be interpreted with caution, given the low number of patients. Patients identified as low risk by POLAR without RT had 7% (0 to 27) risk of LRR at 10 years after surgery, and RT could not be shown to demonstrate a significant reduction of LRR. To our knowledge, this is the first molecular signature to identify low-risk patients who may be candidates for omission of RT after BCS for invasive BC.
Previous attempts to develop RT omission classifiers have been limited by factors involving the lack of a RT omission cohort from randomized trials ± radiation for comparison,27 training to end points other than LRR,25 loss of genes when expanding from fresh-frozen tissue to paraffin-embedded tissue,28 or lack of external validation in cohorts other than those in which the signature was derived.32-36 Given these mixed results, efforts are underway to prospectively test signatures developed to be prognostic for distant metastatic events in clinical trials to identify patients who do not benefit from radiation and are at low risk of LRR. These trials, including DEBRA, TAILOR RT, IDEA, PRECISION, LUMINA, and EXPERT, use molecular signatures on the basis of RNA or protein expression to identify low-risk patient groups in whom the risk of in-breast tumor recurrence is sufficiently low enough to safely omit radiation. The long-term results of these genomically stratified trials to identify such low-risk patient groups are eagerly awaited, with the earliest results in a few years.29 However, the first LUMINA results have been recently reported and demonstrate a low risk of local recurrence (2.3% at 5 years) in women ≥ 55 years with T1, grade 1-2, luminal A (ER+, PgR+, HER2−, and Ki67 ≤ 13.25%) tumors using endocrine therapy without breast radiation.37 Furthermore, a Swedish multicenter cohort study of omission of RT in 603 patients age older than 65 years and with ER+, grade 1-2, and T1 tumors treated with endocrine agents found a very low rate of IBTR (1.2% at 5 years).38 These results demonstrate proof of principle that RT can be safely omitted in select patients.
Previously published genomic signatures relied on data sets where all patients received RT after BCS; thus, the identified genes may skew toward those related to high risk of disease recurrence, which might not be ideal for determining radiation omission.26,27 In the GSEA assessment of gene lists enriched specifically for LRR, we found that several gene lists related to the immune system (eg, HALLMARK_TNFA_SIGNALING_VIA_NFKB, GO_B_CELL_RECEPTOR_SIGNALING_PATHWAY) were in the top negatively enriched gene lists, suggesting that a higher immune response is associated with a lower risk of LRR. This is consistent with prior reports that an activated immune response is associated with a favorable outcome and reduced risk for IBTR and/or LRR, although the potentially modulating effect of RT has seen conflicting results.39-41 There is only one gene included in POLAR that is also included in PAM50, the 21-gene recurrence score (OncotypeDx), 70-gene assay (Mammaprint), or in our previous signature for RT intensification ARTIC (MMP11, included in PAM50 and the 21‐gene recurrence score), suggesting that POLAR could provide additional information. This is further corroborated by the result that POLAR remains prognostic for LRR also after adjusting for luminal A versus luminal B subtype, and that POLAR is only very weakly correlated with ARTIC score in the SweBCG91-RT validation cohort (Rho 0.094, P = .038, data not shown). Thus, one could envision that biomarker testing in ER+/HER2− BC to guide adjuvant therapy will be based on classifiers optimized separately for chemotherapy or RT. To aid specifically in the decision to give adjuvant RT after BCS, a sequential testing strategy where patients are tested with POLAR to determine if omission of RT should be considered, and if not, testing with ARTIC to determine if a RT boost, or other treatment intensification, would be needed. This testing strategy would be plausible, given that the information needed to calculate both POLAR and ARTIC can be derived from the same gene expression analysis without the need for additional testing. However, as with all biomarkers, ultimate clinical utility needs to be studied in prospective clinical trials, which are currently being planned.
Despite analyzing two randomized trials of ± adjuvant RT, there remain limitations to this study. The overall number of patients was relatively small, and our strategy for optimization of biological signal during the training of POLAR further means that the characteristics of the validation cohort part of SweBCG91-RT are somewhat different from the full SweBCG91-RT trial. Additional independent validation in cohorts of patients treated within phase III randomized trials of breast-conservation surgery randomly assigned to ± radiation therapy would further strengthen these findings. Furthermore, these patients were enrolled and treated in the 1990s, when axillary dissection was routinely performed instead of sentinel-node biopsy (which is likely more sensitive to identify low-volume lymph node metastasis, while examining fewer nodes). Thus, the LRR rates may be expected to be lower in contemporary cohorts. That said, this makes the need to identify current patients in whom RT can be safely omitted even more compelling. Another limitation of the SweBCG91-RT study is the lack of widespread adjuvant endocrine therapy, which was addressed by the results in the Princess Margaret cohort, where all patients received tamoxifen, although the number from this trial is small.
In an era of prognostic and predictive gene signatures that allows for more precise treatment recommendations for systemic chemotherapy and endocrine therapy, the development of a prognostic and predictive genomic signature for radiation benefit has the potential to further refine treatment recommendations. POLAR has the potential to identify patients whose disease is locally indolent without benefit from adjuvant RT. When considering the cost and morbidity of such therapy, this signature has the potential to improve patient outcomes, emotional well-being, and overall quality of life without compromising cancer control.

Acknowledgment

The authors would like to thank Dave Hall, Barry Grobman, Rick Baehner, Christy Russell, Stephen Eckert, and Jennifer Duke for their critical review of this manuscript.

Data Supplements

Authors retain all rights in any data supplements associated with their articles.

The ideas and opinions expressed in this Data Supplement do not necessarily reflect those of the American Society of Clinical Oncology (ASCO). The mention of any product, service, or therapy in this Data Supplement should not be construed as an endorsement of the products mentioned. It is the responsibility of the treating physician or other health care provider, relying on independent experience and knowledge of the patient, to determine drug dosages and the best treatment for the patient. Readers are advised to check the appropriate medical literature and the product information currently provided by the manufacturer of each drug to be administered to verify approved uses, the dosage, method, and duration of administration, or contraindications. Readers are also encouraged to contact the manufacturer with questions about the features or limitations of any products. ASCO and JCO assume no responsibility for any injury or damage to persons or property arising out of or related to any use of the material contained in this publication or to any errors or omissions. Readers should contact the corresponding author with any comments related to Data Supplement materials.

Prior Presentation

Presented in part at the 2021 ASCO Annual Meeting, Chicago, IL, June 4‐8, 2021, and the San Antonio Breast Cancer Symposium, San Antonio, TX, December 7–10, 2021.

Support

Supported by The Swedish Breast Cancer Association, the Swedish Cancer Society, the Gunnar Nilsson Cancer Foundation, the Anna and Edwin Berger Foundation, the Swedish Cancer and Allergy Foundation, the Mrs. Berta Kamprad Research Foundation, the Faculty of Medicine at Lund University, the Lund University Research Foundation, Skåne County Research Foundation, the LUA/ALF agreement in West of Sweden health care region (Grant No. ALFGBG-716711), Governmental Funding of Research within the National Health Service (ALF), the King Gustav Vth Jubilee Clinic Cancer Foundation in Gothenburg (Grant No. 2017:130), Canadian Institutes of Health Research, and PFS Genomics.

Authors' Disclosures of Potential Conflicts of Interest

Development and Validation of a Genomic Profile for the Omission of Local Adjuvant Radiation in Breast Cancer

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center.
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Martin Sjöström

Research Funding: PFS Genomics (Inst)

David McCready

Stock and Other Ownership Interests: Johnson & Johnson

S. Laura Chang

Employment: Exact Sciences
Stock and Other Ownership Interests: Exact Sciences
Patents, Royalties, Other Intellectual Property: Coinventor on patent for genomic signature of radiotherapy
Other Relationship: PFS Genomics

Felix Y. Feng

Stock and Other Ownership Interests: Artera
Consulting or Advisory Role: Janssen Biotech, Astellas Pharma, SerImmune, Foundation Medicine, Exact Sciences, Bristol Myers Squibb, Varian Medical Systems, Novartis, Roivant, Bayer, BlueStar Genomics, Myovant Sciences, Tempus, Artera
Research Funding: Zenith Epigenetics

Corey W. Speers

Consulting or Advisory Role: Exact Sciences
Patents, Royalties, Other Intellectual Property: Compositions and Methods for the Analysis of Radiosensitivity, UM-33550/US-1, Coinventor, Submitted on 09/2013, Methods and Genomic Classifiers for Prognosis of Breast Cancer and Predicting Benefit from Adjuvant Radiotherapy, Application No. 61/205,279, Coinventor

Lori J. Pierce

Stock and Other Ownership Interests: PFS Genomics
Patents, Royalties, Other Intellectual Property: UpToDate, PFS Genomics
Uncompensated Relationships: Bristol Myers Squibb
Uncompensated Relationships: Exact Sciences

Erik Holmberg

Patents, Royalties, Other Intellectual Property: Research contract with PFS Genomics. IP regarding genomic profile, Contract with Prelude DX; intellectual property; royalties

Mårten Fernö

Honoraria: Roche, AstraZeneca
Consulting or Advisory Role: Mavatar
Patents, Royalties, Other Intellectual Property: PFS Genomics
Travel, Accommodations, Expenses: Roche, AstraZeneca

Per Malmström

Patents, Royalties, Other Intellectual Property: Participation in royalty sharing agreements PFS Genomics United States

Per Karlsson

Consulting or Advisory Role: AstraZeneca
Patents, Royalties, Other Intellectual Property: Pending application of patent for a RT biomarker, Contract with Prelude DX regarding biomarkers for radiation sensitivity, research contract with PFS Genomics regarding gene profiling and intelectual property/royalties
No other potential conflicts of interest were reported.

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Information & Authors

Information

Published In

Journal of Clinical Oncology
Pages: 1533 - 1540
PubMed: 36599119

History

Published online: January 04, 2023
Published in print: March 10, 2023

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Data Sharing Statement

Gene expression data from the SweBCG91-RT cohort are available at Gene Expression Omnibus (GEO, accession number GSE119295) and gene expression data from the Princess Margaret cohort are available as a Data Supplement. Additional data are available from the corresponding author upon reasonable request, and after additional ethical approval as necessary.

Authors

Affiliations

Martin Sjöström, MD, PhD https://orcid.org/0000-0002-2629-9966
Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
Department of Radiation Oncology, University of California San Francisco, San Francisco, CA
Anthony Fyles, MD
Princess Margaret Cancer Centre and University of Toronto, Toronto, ON, Canada
Princess Margaret Cancer Centre and University of Toronto, Toronto, ON, Canada
David McCready, MD
Princess Margaret Cancer Centre and University of Toronto, Toronto, ON, Canada
Princess Margaret Cancer Centre and University of Toronto, Toronto, ON, Canada
Katrina Rey-McIntyre, MBA, BSc
Princess Margaret Cancer Centre and University of Toronto, Toronto, ON, Canada
S. Laura Chang, PhD
Exact Sciences, Madison, WI
Department of Radiation Oncology, University of California San Francisco, San Francisco, CA
Corey W. Speers, MD, PhD https://orcid.org/0000-0002-2362-2860
Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
Per Malmström, MD, PhD
Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
Department of Haematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Notes

Per Karlsson, MD, PhD, Department of Oncology, Blå stråket 2, Sahlgrenska Comprehensive Cancer Center, 413 45 Gothenburg, Sweden; e-mail: [email protected].

Author Contributions

Conception and design: Martin Sjöström, Anthony Fyles, Fei-Fei Liu, S. Laura Chang, Felix Y. Feng, Corey W. Speers, Lori J. Pierce, Mårten Fernö, Per Malmström, Per Karlsson
Financial support: Anthony Fyles, S. Laura Chang, Corey W. Speers, Mårten Fernö, Per Karlsson
Administrative support: Katrina Rey-McIntyre, Mårten Fernö, Per Malmström, Per Karlsson
Provision of study materials or patients: Anthony Fyles, Fei-Fei Liu, Katrina Rey-McIntyre, Erik Holmberg, Mårten Fernö, Per Malmström, Per Karlsson
Collection and assembly of data: Martin Sjöström, Anthony Fyles, David McCready, Wei Shi, Katrina Rey-McIntyre, S. Laura Chang, Felix Y. Feng, Corey W. Speers, Mårten Fernö, Per Malmström, Per Karlsson
Data analysis and interpretation: Martin Sjöström, Anthony Fyles, Fei-Fei Liu, David McCready, S. Laura Chang, Felix Y. Feng, Corey W. Speers, Lori J. Pierce, Erik Holmberg, Mårten Fernö, Per Karlsson
Manuscript writing: All authors
Final approval of manuscript: All authors
Accountable for all aspects of the work: All authors

Disclosures

Martin Sjöström
Research Funding: PFS Genomics (Inst)
David McCready
Stock and Other Ownership Interests: Johnson & Johnson
S. Laura Chang
Employment: Exact Sciences
Stock and Other Ownership Interests: Exact Sciences
Patents, Royalties, Other Intellectual Property: Coinventor on patent for genomic signature of radiotherapy
Other Relationship: PFS Genomics
Felix Y. Feng
Stock and Other Ownership Interests: Artera
Consulting or Advisory Role: Janssen Biotech, Astellas Pharma, SerImmune, Foundation Medicine, Exact Sciences, Bristol Myers Squibb, Varian Medical Systems, Novartis, Roivant, Bayer, BlueStar Genomics, Myovant Sciences, Tempus, Artera
Research Funding: Zenith Epigenetics
Corey W. Speers
Consulting or Advisory Role: Exact Sciences
Patents, Royalties, Other Intellectual Property: Compositions and Methods for the Analysis of Radiosensitivity, UM-33550/US-1, Coinventor, Submitted on 09/2013, Methods and Genomic Classifiers for Prognosis of Breast Cancer and Predicting Benefit from Adjuvant Radiotherapy, Application No. 61/205,279, Coinventor
Lori J. Pierce
Stock and Other Ownership Interests: PFS Genomics
Patents, Royalties, Other Intellectual Property: UpToDate, PFS Genomics
Uncompensated Relationships: Bristol Myers Squibb
Uncompensated Relationships: Exact Sciences
Erik Holmberg
Patents, Royalties, Other Intellectual Property: Research contract with PFS Genomics. IP regarding genomic profile, Contract with Prelude DX; intellectual property; royalties
Mårten Fernö
Honoraria: Roche, AstraZeneca
Consulting or Advisory Role: Mavatar
Patents, Royalties, Other Intellectual Property: PFS Genomics
Travel, Accommodations, Expenses: Roche, AstraZeneca
Per Malmström
Patents, Royalties, Other Intellectual Property: Participation in royalty sharing agreements PFS Genomics United States
Per Karlsson
Consulting or Advisory Role: AstraZeneca
Patents, Royalties, Other Intellectual Property: Pending application of patent for a RT biomarker, Contract with Prelude DX regarding biomarkers for radiation sensitivity, research contract with PFS Genomics regarding gene profiling and intelectual property/royalties
No other potential conflicts of interest were reported.

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Martin Sjöström, Anthony Fyles, Fei-Fei Liu, David McCready, Wei Shi, Katrina Rey-McIntyre, S. Laura Chang, Felix Y. Feng, Corey W. Speers, Lori J. Pierce, Erik Holmberg, Mårten Fernö, Per Malmström, Per Karlsson
Journal of Clinical Oncology 2023 41:8, 1533-1540

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