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Molecular Profiling for Predictors of Radiosensitivity in Patients with Breast or Head-and-Neck Cancer.

ABSTRACT: Nearly half of all cancers are treated with radiotherapy alone or in combination with other treatments, where damage to normal tissues is a limiting factor for the treatment. Radiotherapy-induced adverse health effects, mostly of importance for cancer patients with long-term survival, may appear during or long time after finishing radiotherapy and depend on the patient's radiosensitivity. Currently, there is no assay available that can reliably predict the individual's response to radiotherapy. We profiled two study sets from breast (n = 29) and head-and-neck cancer patients (n = 74) that included radiosensitive patients and matched radioresistant controls.. We studied 55 single nucleotide polymorphisms (SNPs) in 33 genes by DNA genotyping and 130 circulating proteins by affinity-based plasma proteomics. In both study sets, we discovered several plasma proteins with the predictive power to find radiosensitive patients (adjusted p < 0.05) and validated the two most predictive proteins (THPO and STIM1) by sandwich immunoassays. By integrating genotypic and proteomic data into an analysis model, it was found that the proteins CHIT1, PDGFB, PNKD, RP2, SERPINC1, SLC4A, STIM1, and THPO, as well as the VEGFA gene variant rs69947, predicted radiosensitivity of our breast cancer (AUC = 0.76) and head-and-neck cancer (AUC = 0.89) patients. In conclusion, circulating proteins and a SNP variant of VEGFA suggest that processes such as vascular growth capacity, immune response, DNA repair and oxidative stress/hypoxia may be involved in an individual's risk of experiencing radiation-induced toxicity.

SUBMITTER: Drobin K

PROVIDER: S-EPMC7140105 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Molecular Profiling for Predictors of Radiosensitivity in Patients with Breast or Head-and-Neck Cancer.

Drobin Kimi K Marczyk Michal M Halle Martin M Danielsson Daniel D Papiez Anna A Sangsuwan Traimate T Bendes Annika A Hong Mun-Gwan MG Qundos Ulrika U Harms-Ringdahl Mats M Wersäll Peter P Polanska Joanna J Schwenk Jochen M JM Haghdoost Siamak S

Cancers 20200322 3

Nearly half of all cancers are treated with radiotherapy alone or in combination with other treatments, where damage to normal tissues is a limiting factor for the treatment. Radiotherapy-induced adverse health effects, mostly of importance for cancer patients with long-term survival, may appear during or long time after finishing radiotherapy and depend on the patient's radiosensitivity. Currently, there is no assay available that can reliably predict the individual's response to radiotherapy. ...[more]

PMID: 32235817

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Project description:BackgroundAdjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer.MethodsFresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel.ResultsDerived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response.ConclusionsOur targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer.

Dataset Information

Molecular Profiling for Predictors of Radiosensitivity in Patients with Breast or Head-and-Neck Cancer.

Publications

Molecular Profiling for Predictors of Radiosensitivity in Patients with Breast or Head-and-Neck Cancer.

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