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- De Marchi, Tommaso, et al.
(författare)
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Proteogenomics decodes the evolution of human ipsilateral breast cancer
- 2023
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Ipsilateral breast tumor recurrence (IBTR) is a clinically important event, where an isolated in-breast recurrence is a potentially curable event but associated with an increased risk of distant metastasis and breast cancer death. It remains unclear if IBTRs are associated with molecular changes that can be explored as a resource for precision medicine strategies. Here, we employed proteogenomics to analyze a cohort of 27 primary breast cancers and their matched IBTRs to define proteogenomic determinants of molecular tumor evolution. Our analyses revealed a relationship between hormonal receptors status and proliferation levels resulting in the gain of somatic mutations and copy number. This in turn re-programmed the transcriptome and proteome towards a highly replicating and genomically unstable IBTRs, possibly enhanced by APOBEC3B. In order to investigate the origins of IBTRs, a second analysis that included primaries with no recurrence pinpointed proliferation and immune infiltration as predictive of IBTR. In conclusion, our study shows that breast tumors evolve into different IBTRs depending on hormonal status and proliferation and that immune cell infiltration and Ki-67 are significantly elevated in primary tumors that develop IBTR. These results can serve as a starting point to explore markers to predict IBTR formation and stratify patients for adjuvant therapy.
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| 2. |
- Niméus, Emma, et al.
(författare)
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Cyclin B1 is a prognostic proliferation marker with a high reproducibility in a population-based lymph node negative breast cancer cohort
- 2010
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 127:4, s. 961-967
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Tidskriftsartikel (refereegranskat)abstract
- A large proportion of women with lymph node negative breast cancer treated with chemotherapy do not benefit from such treatment. Proliferation markers have been shown to recognize patients at high risk for recurrence. Ki67 has recently been included in the St Gallen guidelines. We investigated the prognostic importance of cyclin B1 in node negative breast cancer and included a study of reproducibility. In a population-based case-control study 190 women who died from breast cancer were defined as cases and 190 women alive at the time for the corresponding case's death as controls. Inclusion criteria were tumor size < 50 mm, no lymph node metastases, and no adjuvant chemotherapy. Tumor tissue was immunostained for cyclin B1. Two investigators evaluated the staining independently by counting approximately 100, 200, 500, and 1000 cells. Cyclin B1 was statistically significantly associated to breast cancer death, in both uni- and multivariate analyses (adjusted for tumor size, age, and endocrine therapy), with odds ratios 2-3 for both investigators. The agreement between the two investigators was good to very good, regardless of the number of counted cells (kappa values between 0.74 and 0.82).Cyclin B1 is a prognostic factor for breast cancer death in a population-based node negative patient cohort which can identify high-risk patients with a good to very good reproducibility. (c) 2009 UICC.
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| 3. |
- Sjöström, Martin, et al.
(författare)
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Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors
- 2018
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Adjuvant 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. Methods: Fresh-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. Results: Derived 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. Conclusions: Our 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.
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