Eligibility criteria for intraoperative radiotherapy for breast cancer: study employing 12,025 patients treated in two cohorts.

BACKGROUND: We wished to estimate the proportion of patients with breast cancer eligible for an exclusive targeted intraoperative radiotherapy (TARGIT) and to evaluate their survival without local recurrence. METHODS: We undertook a retrospective study examining two cohorts. The first cohort was multicentric (G3S) and contained 7580 patients. The second cohort was monocentric (cohort 2) comprising 4445 patients. All patients underwent conservative surgery followed by external radiotherapy for invasive breast cancer (T0-T3, N0-N1) between 1980 and 2005. Within each cohort, two groups were isolated according to the inclusion criteria of the TARGIT A study (T group) and RIOP trial (R group).In the multicentric cohort (G3S) eligible patients for TARGIT A and RIOP trials were T1E and R1E subgroups, respectively. In cohort number 2, the corresponding subgroups were T2E and R2E. Similarly, non-eligible patients were T1nE, R1nE and T2nE, and R2nE.The eligible groups in the TARGIT A study that were not eligible in the RIOP trial (TE-RE) were also studied. The proportion of patients eligible for TARGIT was calculated according to the criteria of each study. A comparison was made of the 5-year survival without local or locoregional recurrence between the TE versus TnE, RE versus RnE, and RE versus (TE-RE) groups. RESULTS: In G3S and cohort 2, the proportion of patients eligible for TARGIT was, respectively, 53.2% and 33.9% according the criteria of the TARGIT A study, and 21% and 8% according the criteria of the RIOP trial. Survival without five-year locoregional recurrence was significantly different between T1E and T1nE groups (97.6% versus 97% [log rank=0.009]), R1E and R1nE groups (98% versus 97.1% [log rank=0.011]), T2E and T2nE groups (96.6% versus 93.1% [log rank<0. 0001]) and R2E and R2nE groups (98.6% versus 94% [log rank=0.001]). In both cohorts, no significant difference was found between RE and (TE-RE) groups. CONCLUSIONS: Almost 50% of T0-2 N0 patients could be eligible for TARGIT.

miRNA expression profiling of inflammatory breast cancer identifies a 5-miRNA signature predictive of breast tumor aggressiveness.

IBC (inflammatory breast cancer) is a rare but very aggressive form of breast cancer with a particular phenotype. The molecular mechanisms responsible for IBC remain largely unknown. In particular, genetic and epigenetic alterations specific to IBC remain to be identified. MicroRNAs, a class of small noncoding RNAs able to regulate gene expression, are deregulated in breast cancer and may therefore serve as tools for diagnosis and prediction. This study was designed to determine miRNA expression profiling (microRNAome) in IBC. Quantitative RT-PCR was used to determine expression levels of 804 miRNAs in a screening series of 12 IBC compared to 31 non-stage-matched non-IBC and 8 normal breast samples. The differentially expressed miRNAs were then validated in a series of 65 IBC and 95 non-IBC. From a set of 18 miRNAs of interest selected from the screening series, 13 were differentially expressed with statistical significance in the validation series of IBC compared to non-IBC. Among these, a 5-miRNA signature comprising miR-421, miR-486, miR-503, miR-720 and miR-1303 was shown to be predictive for IBC phenotype with an overall accuracy of 89%. Moreover, multivariate analysis showed that this signature was an independent predictor of poor Metastasis-Free Survival in non-IBC patients.

Breast carcinoma metastasis within granulosa cell tumor of the ovary: morphologic, immunohistologic, and molecular analyses of the two different tumor cell populations.

Gynecologic metastasis of breast carcinoma is not an infrequent event, but metastases within another tumor is very rare. We report a case of unilateral ovarian tumor arising in a 63-year-old woman receiving tamoxifen therapy with a past history of breast carcinoma. The microscopic appearance was principally that of a granulosa cell tumor, but the presence of atypical cells closely admixed within the classical areas was reminiscent of metastasis from breast carcinoma. The diagnosis of this first reported case of breast carcinoma metastasis within granulosa cell tumor was supported by immunohistologic analysis. The diagnosis of tumor-to-tumor metastasis was also confirmed by molecular study using microdissections of samples from the initial breast tumor and from the subsequent ovarian tumor. When compared with normal tissue, carcinomatous cells in the breast tissue exhibited genomic abnormality at the same locus as the metastatic cells in the ovary. In contrast, granulosa cell tumor areas did not show any loss of heterozygosity or instability for the microsatellites analyzed.

Prognostic value of isolated tumor cells and micrometastases of lymph nodes in early-stage breast cancer: a French sentinel node multicenter cohort study.

To define the prognostic value of isolated tumor cells (ITC), micrometastases (pN1mi) and macrometastases in early stage breast cancer (ESBC). We conducted a retrospective multicenter cohort study at 13 French sites. All the eligible patients who underwent SLNB from January 1999 to December 2008 were identified, and appropriate data were extracted from medical records and analyzed. Among 8001 patients, including 70% node-negative (n = 5588), 4% ITC (n = 305), 10% pN1mi (n = 794) and 16% macrometastases (n = 1314) with a median follow-up of 61.3 months, overall survival (OS) and recurrence-free survival (RFS) rates at 84 months were not statistically different in ITC or pN1mi compared to tumor-free nodes. Axillary recurrence (AR) was significantly more frequent in ITC (1.7%) and pN1mi (1.5%) compared to negative nodes (0.6%). Survival and AR rates of single macrometastases were not different from those of ITC or pN1mi. In case of 2 macrometastases or more, survival rates decreased and recurrence rates increased significantly. Micrometastases and ITC do not have a negative prognostic value. Single macrometastases might have an intermediate prognostic value while 2 macrometastases or more are associated with poorer prognosis.

Reasons of not having breast reconstruction: a historical cohort of 1937 breast cancer patients undergoing mastectomy.

BACKGROUND: The aims of the study were to investigate the factors associated with not having breast reconstruction following mastectomy and to assess patient satisfaction with information on reconstruction. PATIENTS AND METHODS: We analysed a historical cohort of 1937 consecutive patients who underwent mastectomy at Institut Curie between January 2004 and February 2007. Their sociodemographic and clinicobiological characteristics were recorded in a prospective database. A questionnaire was sent to 10% of nonreconstructed patients. RESULTS: The proportion of patients with invasive cancer was 82.7%. The rate of nonreconstruction in patients with in situ and invasive cancer was 34.6% and 74.9%, respectively. On multivariate analysis, only employment outside the home was associated with reconstruction in patients with in situ cancer (p < 0.001). In patients with invasive cancer, employment status (p < 0.001) and smoking (p = 0.045) were associated with reconstruction, while age > 50, ASA score >1, radiotherapy (p < 0.0001) and metastatic status (p = 0.018) were associated with nonreconstruction. For 80% of questionnaire responders, nonreconstruction was a personal choice, mainly for the following reasons: refusal of further surgery, acceptance of body asymmetry, risk of complications and advanced age. Information on reconstruction was entirely unsatisfactory or inadequate for 62% of patients. CONCLUSION: Better understanding the factors that influence decision of nonreconstruction can help us adapt the information to serve the patient's personal needs.

Non sentinel node involvement prediction for sentinel node micrometastases in breast cancer: nomogram validation and comparison with other models.

PURPOSE: The risk of non sentinel node (NSN) involvement varies in function of the characteristics of sentinel nodes (SN) and primary tumor. Our aim was to determine and validate a statistical tool (a nomogram) able to predict the risk of NSN involvement in case of SN micro or sub-micrometastasis of breast cancer. We have compared this monogram with other models described in the literature. METHODS: We have collected data on 905 patients, then 484 other patients, to build and validate the nomogram and compare it with other published scores and nomograms. RESULTS: Multivariate analysis conducted on the data of the first cohort allowed us to define a nomogram based on 5 criteria: the method of SN detection (immunohistochemistry or by standard coloration with HES); the ratio of positive SN out of total removed SN; the pathologic size of the tumor; the histological type; and the presence (or not) of lympho-vascular invasion. The nomogram developed here is the only one dedicated to micrometastasis and developed on the basis of two large cohorts. The results of this statistical tool in the calculation of the risk of NSN involvement is similar to those of the MSKCC (the similarly more effective nomogram according to the literature), with a lower rate of false negatives. CONCLUSION: this nomogram is dedicated specifically to cases of SN involvement by metastasis lower or equal to 2 mm. It could be used in clinical practice in the way to omit ALND when the risk of NSN involvement is low.

Non-sentinel lymph node metastasis prediction in breast cancer with metastatic sentinel lymph node: impact of molecular subtypes classification.

INTRODUCTION: To decipher the interaction between the molecular subtype classification and the probability of a non-sentinel node metastasis in breast cancer patients with a metastatic sentinel lymph-node, we applied two validated predictors (Tenon Score and MSKCC Nomogram) on two large independent datasets. MATERIALS AND METHODS: Our datasets consisted of 656 and 574 early-stage breast cancer patients with a metastatic sentinel lymph-node biopsy treated at first by surgery. We applied both predictors on the whole dataset and on each molecular immune-phenotype subgroups. The performances of the two predictors were analyzed in terms of discrimination and calibration. Probability of non-sentinel lymph node metastasis was detailed for each molecular subtype. RESULTS: Similar results were obtained with both predictors. We showed that the performance in terms of discrimination was as expected in ER Positive HER2 negative subgroup in both datasets (MSKCC AUC Dataset 1 = 0.73 [0.69-0.78], MSKCC AUC Dataset 2 = 0.71 (0.65-0.76), Tenon Score AUC Dataset 1 = 0.7 (0.65-0.75), Tenon Score AUC Dataset 2 = 0.72 (0.66-0.76)). Probability of non-sentinel node metastatic involvement was slightly under-estimated. Contradictory results were obtained in other subgroups (ER negative HER2 negative, HER2 positive subgroups) in both datasets probably due to a small sample size issue. We showed that merging the two datasets shifted the performance close to the ER positive HER2 negative subgroup. DISCUSSION: We showed that validated predictors like the Tenon Score or the MSKCC nomogram built on heterogeneous population of breast cancer performed equally on the different subgroups analyzed. Our present study re-enforce the idea that performing subgroup analysis of such predictors within less than 200 samples subgroup is at major risk of misleading conclusions.