Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types.

BACKGROUND: The human proteasome gene family (PSM) consists of 49 genes that play a crucial role in cancer proteostasis. However, little is known about the effect of PSM gene expression and genetic alterations on clinical outcome in different cancer forms. METHODS: Here, we performed a comprehensive pan-cancer analysis of genetic alterations in PSM genes and the subsequent prognostic value of PSM expression using data from The Cancer Genome Atlas (TCGA) containing over 10,000 samples representing up to 33 different cancer types. External validation was performed using a breast cancer cohort and KM plotter with four cancer types. RESULTS: The PSM genetic alteration frequency was high in certain cancer types (e.g. 67%; esophageal adenocarcinoma), with DNA amplification being most common. Compared with normal tissue, most PSM genes were predominantly overexpressed in cancer. Survival analysis also established a relationship with PSM gene expression and adverse clinical outcome, where PSMA1 and PSMD11 expression were linked to more unfavorable prognosis in ≥ 30% of cancer types for both overall survival (OS) and relapse-free interval (PFI). Interestingly, PSMB5 gene expression was associated with OS (36%) and PFI (27%), and OS for PSMD2 (42%), especially when overexpressed. CONCLUSION: These findings indicate that several PSM genes may potentially be prognostic biomarkers and novel therapeutic targets for different cancer forms.

Trefoil factor family proteins as potential diagnostic markers for mucinous invasive ovarian carcinoma.

Introduction: Ovarian cancer (OC) is the leading cause of gynecological cancer-related death. Of the main OC histologic subtypes, invasive mucinous carcinomas (MC) account for only 3% of OC cases and are frequently associated with favorable prognosis. Nevertheless, MCs differ greatly from the other OC histotypes in clinical, pathological, and biological behavior. However, the origin and molecular pathogenesis of MC are not yet fully understood. Therefore, identification of novel diagnostic markers could potentially facilitate early diagnosis of OC, particularly the MC histotype, thereby leading to the development of histotype-specific treatment regimens and improved survival rates. Methods: In the present study, Trefoil factor gene family members (TFF1, TFF2 and TFF3) were identified as MC histotype-specific biomarkers using RNA sequencing (RNA-seq) data for 95 stage I-II OCs. The diagnostic value of TFF1, TFF2 and TFF3 was then evaluated by immunohistochemistry on 206 stage I-II OCs stratified by histotype (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], clear cell carcinoma [CCC], and MC). Results: We showed significantly elevated intracytoplasmic protein expression levels for TFF1, TFF2 and TFF3 in MC samples, thereby revealing an association between expression of Trefoil factor gene family members and the MC histotype. Taken together, these findings suggest that the TFF proteins may play a pivotal role in tumor initiation and progression for the MC histotype. Conclusion: Taken together, these findings suggest that the TFF proteins may play a pivotal role in tumor initiation and progression for the MC histotype. Moreover, these novel histotype-specific diagnostic biomarkers may not only improve patient stratification of early-stage ovarian carcinomas but may also be candidates for the development of molecular targeted therapies.

Discordance of PIK3CA and TP53 mutations between breast cancer brain metastases and matched primary tumors.

There is limited knowledge of the biology of breast cancer (BC) brain metastasis (BM). We primarily aimed to determine the mutations in BCBM and to compare the mutational pattern with the matched primary breast cancer (BC). Secondary aims were to determine mutations in each subgroup (Luminal A-/B-like, HER2+ and TNBC) of BCBM, and to determine survival according to specific mutations. We investigated 57 BCBMs, including 46 cases with matched primary tumors (PT) by targeted Next Generation Sequencing (NGS) using the Cancer Hotspot Panel v2 (ThermoFisher Scientific) covering 207 targeted regions in 50 cancer related genes. Subtype according to immunohistochemistry was re-evaluated. NGS results fulfilling sequencing quality criteria were obtained from 52 BM and 41 PT, out of which 37 were matched pairs. Pathogenic mutations were detected in 66% of PTs (27/41), and 62% of BMs (32/52). TP53 mutations were most frequent; 49% (20/41) of PTs and 48% (25/52) in BMs, followed by PIK3CA mutations; 22% (9/42) in PTs and 25% (13/52) in BMs. Mutations in CDH1, EGFR, HRAS, RB1 CDKN2A and PTEN were detected in single pairs or single samples. Mutational pattern was discordant in 24% of matched pairs. We show a discordance of PIK3CA and TP53 mutations of roughly 25% indicating the need to develop methods to assess mutational status in brain metastasis where analysis of cell-free DNA from cerebrospinal fluid (CSF) has shown promising results.

Integrative genomics approach identifies molecular features associated with early-stage ovarian carcinoma histotypes.

Ovarian cancer comprises multiple subtypes (clear-cell (CCC), endometrioid (EC), high-grade serous (HGSC), low-grade serous (LGSC), and mucinous carcinomas (MC)) with differing molecular and clinical behavior. However, robust histotype-specific biomarkers for clinical use have yet to be identified. Here, we utilized a multi-omics approach to identify novel histotype-specific genetic markers associated with ovarian carcinoma histotypes (CCC, EC, HGSC, and MC) using DNA methylation, DNA copy number alteration and RNA sequencing data for 96 primary invasive early-stage (stage I and II) ovarian carcinomas. More specifically, the DNA methylation analysis revealed hypermethylation for CCC in comparison with the other histotypes. Moreover, copy number imbalances and novel chromothripsis-like rearrangements (n = 64) were identified in ovarian carcinoma, with the highest number of chromothripsis-like patterns in HGSC. For the 1000 most variable transcripts, underexpression was most prominent for all histotypes in comparison with normal ovarian samples. Overall, the integrative approach identified 46 putative oncogenes (overexpressed, hypomethylated and DNA gain) and three putative tumor suppressor genes (underexpressed, hypermethylated and DNA loss) when comparing the different histotypes. In conclusion, the current study provides novel insights into molecular features associated with early-stage ovarian carcinoma that may improve patient stratification and subclassification of the histotypes.

Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens.

Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Poor experimental design and lack of scientific transparency may cause experimental biases that in turn affect data quality, robustness and reproducibility. Here, we pinpoint sources of experimental variability in conventional 2D cell-based cancer drug screens to determine the effect of confounders on cell viability for MCF7 and HCC38 breast cancer cell lines treated with platinum agents (cisplatin and carboplatin) and a proteasome inhibitor (bortezomib). Variance component analysis demonstrated that variations in cell viability were primarily associated with the choice of pharmaceutical drug and cell line, and less likely to be due to the type of growth medium or assay incubation time. Furthermore, careful consideration should be given to different methods of storing diluted pharmaceutical drugs and use of DMSO controls due to the potential risk of evaporation and the subsequent effect on dose-response curves. Optimization of experimental parameters not only improved data quality substantially but also resulted in reproducible results for bortezomib- and cisplatin-treated HCC38, MCF7, MCF-10A, and MDA-MB-436 cells. Taken together, these findings indicate that replicability (the same analyst re-performs the same experiment multiple times) and reproducibility (different analysts perform the same experiment using different experimental conditions) for cell-based drug screens can be improved by identifying potential confounders and subsequent optimization of experimental parameters for each cell line.

Validation of Novel Prognostic Biomarkers for Early-Stage Clear-Cell, Endometrioid and Mucinous Ovarian Carcinomas Using Immunohistochemistry.

Early-stage (I and II) ovarian carcinoma patients generally have good prognosis. Yet, some patients die earlier than expected. Thus, it is important to stratify early-stage patients into risk groups to identify those in need of more aggressive treatment regimens. The prognostic value of 29 histotype-specific biomarkers identified using RNA sequencing was evaluated for early-stage clear-cell (CCC), endometrioid (EC) and mucinous (MC) ovarian carcinomas (n = 112) using immunohistochemistry on tissue microarrays. Biomarkers with prognostic significance were further evaluated in an external ovarian carcinoma data set using the web-based Kaplan-Meier plotter tool. Here, we provide evidence of aberrant protein expression patterns and prognostic significance of 17 novel histotype-specific prognostic biomarkers [10 for CCC (ARPC2, CCT5, GNB1, KCTD10, NUP155, RPL13A, RPL37, SETD3, SMYD2, TRIO), three for EC (CECR1, KIF26B, PIK3CA), and four for MC (CHEK1, FOXM1, KIF23, PARPBP)], suggesting biological heterogeneity within the histotypes. Combined predictive models comprising the protein expression status of the validated CCC, EC and MC biomarkers together with established clinical markers (age, stage, CA125, ploidy) improved the predictive power in comparison with models containing established clinical markers alone, further strengthening the importance of the biomarkers in ovarian carcinoma. Further, even improved predictive powers were demonstrated when combining these models with our previously identified prognostic biomarkers PITHD1 (CCC) and GPR158 (MC). Moreover, the proteins demonstrated improved risk prediction of CCC-, EC-, and MC-associated ovarian carcinoma survival. The novel histotype-specific prognostic biomarkers may not only improve prognostication and patient stratification of early-stage ovarian carcinomas, but may also guide future clinical therapy decisions.

Clinical outcome of patients with brain metastases from breast cancer - A population based study over 21 years.

BACKGROUND: Brain metastases (BM) are a feared progression of breast cancer (BC) with impact on quality of life and survival. Despite improved treatments, it is believed patients suffering from BM are increasing. AIMS: To study potential changes in the number of BM, the possible links between BC subgroup and extent of BM with prognosis. To investigate the interval between primary BC/extra cranial recurrence, and diagnosis of BM in the years 1994-2014. PATIENTS AND METHODS: Clinical data from 191 patients with BM diagnosed 1994-2014, was retrieved from charts. Primary tumours where re-evaluated histologically. RESULTS: There was an increase of BM in 5 years cohorts (1994-99 (n = 9); 2000-04 (n = 36); 2005-09 (n = 60); 2010-14 (n = 86)). We found no difference in the time interval from primary BC to BM but an insignificant increase in time from extra cranial relapse to development of BM in the time periods 1994-2004 and 2005-2014 of 15.5 and 25.0 months (p = 0.0612). Survival after BM was 7 months (95% CI 6-10) with a statistically significant difference between HER2 positive and TNBC with an inferior outcome for the latter (p = 0.018) whilst no differences were present when Luminal BC were compared with HER2 positive BC (p = 0.073). CONCLUSIONS: We show an increase of BM over time whilst the time span from primary BC to BM is unchanged supports earlier findings that adjuvant treatments have little preventive function. Time from extra cranial recurrence to BM was prolonged with one year. Patients with TNBC or more advance extent of BM had the shortest survival with BM.

A 17-marker panel for global genomic instability in breast cancer.

Genomic instability is a hallmark of cancer that plays a pivotal role in breast cancer development and evolution. A number of existing prognostic gene expression signatures for breast cancer are based on proliferation-related genes. Here, we identified a 17-marker panel associated with genome stability. A total of 136 primary breast carcinomas were stratified by genome stability. Matched gene expression profiles showed an innate segregation based on genome stability. We identified a 17-marker panel stratifying the training and validation cohorts into high- and low-risk patients. The 17 genes associated with genomic instability strongly impacted clinical outcome in breast cancer. Pathway analyses determined chromosome organisation, cell cycle regulation, and RNA processing as the underlying biological processes, thereby offering options for drug development and treatment tailoring. Our work supports the applicability of the 17-marker panel to improve clinical outcome prediction for breast cancer patients based on a signature accounting for genomic instability.

Immunohistochemical validation of COL3A1, GPR158 and PITHD1 as prognostic biomarkers in early-stage ovarian carcinomas.

BACKGROUND: Ovarian cancer is the main cause of gynecological cancer-associated death. However, 5-year survival rates differ dramatically between the five main ovarian carcinoma histotypes. Therefore, we need to have a better understanding of the mechanisms that promote histotype-specific ovarian carcinogenesis and identify novel prognostic biomarkers. METHODS: Here, we evaluated the prognostic role of 29 genes for early-stage (I and II) ovarian carcinomas (n = 206) using immunohistochemistry (IHC). RESULTS: We provide evidence of aberrant protein expression patterns for Collagen type III alpha 1 chain (COL3A1), G protein-coupled receptor 158 (GPR158) and PITH domain containing 1 (PITHD1). Kaplan-Meier survival analysis revealed that COL3A1 expression was associated with shorter overall survival in the four major histotypes of epithelial ovarian carcinoma patients (P value = 0.026, HR = 2.99 (95% CI 1.089-8.19)). Furthermore, GPR158 and PITHD1 were shown to be histotype-specific prognostic biomarkers, with elevated GPR158 expression patterns in mucinous ovarian carcinoma patients with unfavorable overall survival (P value = 0.00043, HR = 6.13 (95% CI 1.98-18.98)), and an association with lower PITHD1 protein expression and unfavorable overall and disease-specific survival in clear-cell ovarian carcinoma patients (P value = 0.012, HR = 0.22 (95% CI 0.058-0.80); P value = 0.003, HR = 0.17 (95% CI 0.043-0.64)). CONCLUSIONS: The novel biomarkers identified here may improve prognostication at the time of diagnosis and may assist in the development of future individualized therapeutic strategies for ovarian carcinoma patients.

Radiation-induced genomic instability in breast carcinomas of the Swedish hemangioma cohort.

Radiation-induced genomic instability (GI) is hypothesized to persist after exposure and ultimately promote carcinogenesis. Based on the absorbed dose to the breast, an increased risk of developing breast cancer was shown in the Swedish hemangioma cohort that was treated with radium-226 for skin hemangioma as infants. Here, we screened 31 primary breast carcinomas for genetic alterations using the OncoScan CNV Plus Assay to assess GI and chromothripsis-like patterns associated with the absorbed dose to the breast. Higher absorbed doses were associated with increased numbers of copy number alterations in the tumor genome and thus a more unstable genome. Hence, the observed dose-dependent GI in the tumor genome is a measurable manifestation of the long-term effects of irradiation. We developed a highly predictive Cox regression model for overall survival based on the interaction between absorbed dose and GI. The Swedish hemangioma cohort is a valuable cohort to investigate the biological relationship between absorbed dose and GI in irradiated humans. This work gives a biological basis for improved risk assessment to minimize carcinogenesis as a secondary disease after radiation therapy.

Effect of Radiotherapy After Breast-Conserving Surgery Depending on the Presence of Tumor-Infiltrating Lymphocytes: A Long-Term Follow-Up of the SweBCG91RT Randomized Trial.

PURPOSE: The effects of radiotherapy (RT) on the basis of the presence of stromal tumor infiltrating lymphocytes (TILs) have not been studied. The purpose of this study was to analyze the association of TILs with the effect of postoperative RT on ipsilateral breast tumor recurrence (IBTR) in a large randomized trial. METHODS: In the SweBCT91RT (Swedish Breast Cancer Group 91 Radiotherapy) trial, 1,178 patients with breast cancer stage I and II were randomly assigned to breast-conserving surgery plus postoperative RT or breast-conserving surgery only and followed for a median of 15.2 years. Tumor blocks were retrieved from 1,003 patients. Stromal TILs were assessed on whole-section hematoxylin-eosin-stained slides using a dichotomized cutoff of 10%. Subtypes were scored using immunohistochemistry on tissue microarray. In total, 936 patients were evaluated. RESULTS: Altogether, 670 (71%) of patients had TILs less than 10%. In a multivariable regression analysis with IBTR as dependent variable and RT, TILs, subtype, age, and grade as independent variables, RT (hazard ratio [HR], 0.42; 95% CI, 0.29 to 0.61; P < .001), high TILs (HR, 0.61; 95% CI, 0.39 to 0.96, P = .033) grade (3 v 1; HR, 2.17; 95% CI, 1.08 to 4.34; P = .029), and age (≥ 50 v < 50 years; HR, 0.55; 95% CI, 0.38 to 0.80; P = .002) were predictive of IBTR. RT was significantly beneficial in the low TILs group (HR, 0.37; 95% CI, 0.24 to 0.58; P < .001) but not in the high TILs group (HR, 0.58; 95% CI, 0.28 to 1.19; P = .138). The test for interaction between RT and TILs was not statistically significant (P = .317). CONCLUSION: This study shows that high values of TILs in the primary tumor independently seem to reduce the risk for an IBTR. Our findings further suggest that patients with breast cancer with low TILs may derive a larger benefit from RT regarding the risk of IBTR.

The prognostic relevance of FOXA1 and Nestin expression in breast cancer metastases: a retrospective study of 164 cases during a 10-year period (2004-2014).

BACKGROUND: Current prognostic markers cannot adequately predict the clinical outcome of breast cancer patients. Therefore, additional biomarkers need to be included in routine immune panels. FOXA1 was a significant predictor of favorable outcome in primary breast cancer, while Nestin expression is preferentially found in triple-negative tumors with increased rate of nodal metastases, and reduced survival. No studies have investigated the prognostic value of FOXA1 and Nestin expression in breast cancer metastases. METHODS: Breast cancer metastases (n = 164) from various anatomical sites were retrospectively analyzed by immunohistochemistry for FOXA1, Nestin and GATA3 expression. Cox regression analysis assessed the prognostic value of FOXA1 and Nestin expression. RESULTS: In breast cancer metastases, FOXA1 expression was associated with Nestin-negativity, GATA3-positivity, ER-positivity, HER2-positivity and non-triple-negative status (P < 0.05). In contrast, Nestin expression was associated with FOXA1-negative, GATA3-negative, ER-negative, and triple-negative metastases (P < 0.05). Univariate Cox regression analysis showed FOXA1 expression was predictive of overall survival (OS, P = 0.00048) and metastasis-free survival (DMFS, P = 0.0011), as well as, distant metastasis-free survival in ER-positive patients (P = 0.036) and overall survival in ER-negative patients (P = 0.024). Multivariate analysis confirmed the significance of FOXA1 for both survival endpoints in metastatic breast cancer patients (OS, P = 0.0033; DMFS, P = 0.015). CONCLUSIONS: In our study, FOXA1 was expressed mostly in ER-positive breast cancer metastases. Expression of Nestin was related to triple-negative metastases, where brain was the most frequent metastatic site. These findings highlight the clinical utility of FOXA1 and Nestin expression and warrant their inclusion in routine immunohistochemical panels for breast carcinoma.

Transcriptomic and genomic profiling of early-stage ovarian carcinomas associated with histotype and overall survival.

Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I and II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.

Clonal relatedness in tumour pairs of breast cancer patients.

BACKGROUND: Molecular classification of tumour clonality is currently not evaluated in multiple invasive breast carcinomas, despite evidence suggesting common clonal origins. There is no consensus about which type of data (e.g. copy number, mutation, histology) and especially which statistical method is most suitable to distinguish clonal recurrences from independent primary tumours. METHODS: Thirty-seven invasive breast tumour pairs were stratified according to laterality and time interval between the diagnoses of the two tumours. In a multi-omics approach, tumour clonality was analysed by integrating clinical characteristics (n = 37), DNA copy number (n = 37), DNA methylation (n = 8), gene expression microarray (n = 7), RNA sequencing (n = 3), and SNP genotyping data (n = 3). Different statistical methods, e.g. the diagnostic similarity index (SI), were used to classify the tumours as clonally related recurrences or independent primary tumours. RESULTS: The SI and hierarchical clustering showed similar tendencies and the highest concordance with the other methods. Concordant evidence for tumour clonality was found in 46% (17/37) of patients. Notably, no association was found between the current clinical guidelines and molecular tumour features. CONCLUSIONS: A more accurate classification of clonal relatedness between multiple breast tumours may help to mitigate treatment failure and relapse by integrating tumour-associated molecular features, clinical parameters, and statistical methods. Guidelines need to be defined with exact thresholds to standardise clonality testing in a routine diagnostic setting.

Genome-wide multi-omics profiling of the 8p11-p12 amplicon in breast carcinoma.

Genomic instability contributes to the neoplastic phenotype by deregulating key cancer-related genes, which in turn can have a detrimental effect on patient outcome. DNA amplification of the 8p11-p12 genomic region has clinical and biological implications in multiple malignancies, including breast carcinoma where the amplicon has been associated with tumor progression and poor prognosis. However, oncogenes driving increased cancer-related death and recurrent genetic features associated with the 8p11-p12 amplicon remain to be identified. In this study, DNA copy number and transcriptome profiling data for 229 primary invasive breast carcinomas (corresponding to 185 patients) were evaluated in conjunction with clinicopathological features to identify putative oncogenes in 8p11-p12 amplified samples. Illumina paired-end whole transcriptome sequencing and whole-genome SNP genotyping were subsequently performed on 23 samples showing high-level regional 8p11-p12 amplification to characterize recurrent genetic variants (SNPs and indels), expressed gene fusions, gene expression profiles and allelic imbalances. We now show previously undescribed chromothripsis-like patterns spanning the 8p11-p12 genomic region and allele-specific DNA amplification events. In addition, recurrent amplification-specific genetic features were identified, including genetic variants in the HIST1H1E and UQCRHL genes and fusion transcripts containing MALAT1 non-coding RNA, which is known to be a prognostic indicator for breast cancer and stimulated by estrogen. In summary, these findings highlight novel candidate targets for improved treatment of 8p11-p12 amplified breast carcinomas.

GATA3 as a putative marker of breast cancer metastasis-A retrospective immunohistochemical study.

Diagnostic verification of breast cancer metastasis with histopathology and imaging analysis is essential to determine tumor staging. The aim of this study was to validate the utility of GATA3 immunohistochemistry as a diagnostic marker for breast cancer metastases and metastases of unknown primary origin. Retrospective immunohistochemical analysis of GATA3 expression in 164 breast cancer metastases diagnosed between 2004 and 2014 showed a striking difference between mammaglobin and GATA3 expression (51.2% vs 94% positivity). These findings highlight GATA3 as a more reliable and sensitive diagnostic marker for breast cancer metastases and possibly metastatic tumors of unknown origin than mammaglobin.

A Novel 18-Marker Panel Predicting Clinical Outcome in Breast Cancer.

Background: Gene expression profiling has made considerable contributions to our understanding of cancer biology and clinical care. This study describes a novel gene expression signature for breast cancer-specific survival that was validated using external datasets.Methods: Gene expression signatures for invasive breast carcinomas (mainly luminal B subtype) corresponding to 136 patients were analyzed using Cox regression, and the effect of each gene on disease-specific survival (DSS) was estimated. Iterative Bayesian model averaging was applied on multivariable Cox regression models resulting in an 18-marker panel, which was validated using three external validation datasets. The 18 genes were analyzed for common pathways and functions using the Ingenuity Pathway Analysis software. This study complied with the REMARK criteria.Results: The 18-gene multivariable model showed a high predictive power for DSS in the training and validation cohort and a clear stratification between high- and low-risk patients. The differentially expressed genes were predominantly involved in biological processes such as cell cycle, DNA replication, recombination, and repair. Furthermore, the majority of the 18 genes were found to play a pivotal role in cancer.Conclusions: Our findings demonstrated that the 18 molecular markers were strong predictors of breast cancer-specific mortality. The stable time-dependent area under the ROC curve function (AUC(t)) and high C-indices in the training and validation cohorts were further improved by fitting a combined model consisting of the 18-marker panel and established clinical markers.Impact: Our work supports the applicability of this 18-marker panel to improve clinical outcome prediction for breast cancer patients. Cancer Epidemiol Biomarkers Prev; 26(11); 1619-28. ©2017 AACR.

Response to Radiotherapy After Breast-Conserving Surgery in Different Breast Cancer Subtypes in the Swedish Breast Cancer Group 91 Radiotherapy Randomized Clinical Trial.

Purpose To evaluate the effect of adjuvant radiotherapy (RT) after breast conservation surgery in different breast cancer subtypes in a large, randomized clinical trial with long-term follow-up. Patients and Methods Tumor tissue was collected from 1,003 patients with node-negative, stage I and II breast cancer who were randomly assigned in the Swedish Breast Cancer Group 91 Radiotherapy trial between 1991 and 1997 to breast conservation surgery with or without RT. Systemic adjuvant treatment was sparsely used (8%). Subtyping was performed with immunohistochemistry and in situ hybridization on tissue microarrays for 958 tumors. Results RT reduced the cumulative incidence of ipsilateral breast tumor recurrence (IBTR) as a first event within 10 years for luminal A-like tumors (19% v 9%; P = .001), luminal B-like tumors (24% v 8%; P < .001), and triple-negative tumors (21% v 6%; P = .08), but not for human epidermal growth factor receptor 2-positive (luminal and nonluminal) tumors (15% v 19%; P = .6); however, evidence of an overall difference in RT effect between subtypes was weak ( P = .21). RT reduced the rate of death from breast cancer (BCD) for triple-negative tumors (hazard ratio, 0.35; P = .06), but not for other subtypes. Death from any cause was not improved by RT in any subtype. A hypothesized clinical low-risk group did not have a low risk of IBTR without RT, and RT reduced the rate of IBTR as a first event after 10 years (20% v 6%; P = .008), but had no effect on BCD or death from any cause. Conclusion Subtype was not predictive of response to RT, although, in our study, human epidermal growth factor receptor 2-positive tumors seemed to be most radioresistant, whereas triple-negative tumors had the largest effect on BCD. The effect of RT in the presumed low-risk luminal A-like tumors was excellent.