Respective Prognostic Value of Genomic Grade and Histological Proliferation Markers in Early Stage (pN0) Breast Carcinoma

Genomic grade (GG) is a 97-gene signature which improves the accuracy and prognostic value of histological grade (HG) in invasive breast carcinoma. Since most of the genes included in the GG are involved in cell proliferation, we performed a retrospective study to compare the prognostic value of GG, Mitotic Index and Ki67 score.A series of 163 consecutive breast cancers was retained (pT1-2, pN0, pM0, 10-yr follow-up). GG was computed using MapQuant Dx(R).GG was low (GG-1) in 48%, high (GG-3) in 31% and equivocal in 21% of cases. For HG-2 tumors, 50% were classified as GG-1, 18% as GG-3 whereas 31% remained equivocal. In a subgroup of 132 ER+/HER2- tumors GG was the most significant prognostic factor in multivariate Cox regression analysis adjusted for age and tumor size (HR = 5.23, p = 0.02).In a reference comprehensive cancer center setting, compared to histological grade, GG added significant information on cell proliferation in breast cancers. In patients with HG-2 carcinoma, applying the GG to guide the treatment scheme could lead to a reduction in adjuvant therapy prescription. However, based on the results observed and considering (i) the relatively close prognostic values of GG and Ki67, (ii) the reclassification of about 30% of HG-2 tumors as Equivocal GG and (iii) the economical and technical requirements of the MapQuant micro-array GG test, the availability in the near future of a PCR-based Genomic Grade test with improved performances may lead to an introduction in clinical routine of this test for histological grade 2, ER positive, HER2 negative breast carcinoma

Epigenomic Alterations in Breast Carcinoma from Primary Tumor to Locoregional Recurrences

International audienceIntroduction: Epigenetic modifications such as aberrant DNA methylation has long been associated with tumorogenesis. Little is known, however, about how these modifications appear in cancer progression. Comparing the methylome of breast carcinomas and locoregional evolutions could shed light on this process. Methods: The methylome profiles of 48 primary breast carcinomas (PT) and their matched axillary metastases (PT/AM pairs, 20 cases), local recurrences (PT/LR pairs, 17 cases) or contralateral breast carcinomas (PT/CL pairs, 11 cases) were analyzed. Univariate and multivariate analyzes were performed to determine differentially methylated probes (DMPs), and a similarity score was defined to compare methylation profiles. Correlation with copy-number based score was calculated and metastatic-free survival was compared between methods. Results: 49 DMPs were found for the PT/AM set, but none for the others (FDR < 5%). Hierarchical clustering clustered 75% of the PT/AM, 47% of the PT/LR, and none of the PT/CL pairs together. A methylation-based score (MS) was defined as a clonality measure. The PT/AM set contained a high proportion of clonal pairs while PT/LR pairs were evenly split between high and low MS score, suggesting two groups: true recurrences (TR) and new primary tumors (NP). CL were classified as new tumors. MS score was significantly correlated with copy-number based scores. There was no significant difference between the metastatic-free survival of groups of patients based on different classifications. Conclusion: Epigenomic alterations are well suited to study clonality and track cancer progression. Methylation-based classification of TR and NP performed as well as clinical and copy-number based methods suggesting that these phenomenons are tightly linked

Comparison of classification methods for clonality between pairs in the PT/LR cohort.

<p><b>Cor</b> (Correspondence): correspondence number with the Bollet/Servant cohort. <b>scores</b>: scores obtained with partial identity (PIS) or methylation (MS). <b>Time</b>: time elapsed between diagnosis of the PT and diagnosis of the recurrence. <b>Classification</b>: classification of the recurrence based on copy number (PIS), methylation (MS) or clinical features (clinical). <b>Divergence</b>: which method deviated from the others.</p

Significantly differentially methylated genes between PT and AM samples.

<p><b>CpG</b>: CpG probe name. <b>Gene</b>: Associated gene. <b>Pvalue</b>: FDR corrected p-value. <b>Methylation Variation</b>: Mean variation of methylation from the primary tumor to the axillary metastasis.</p

Kaplan-Meier estimates of the metastasis-free survival between TR and NP for the different classification methods.

<p>The full black (resp. green) line corresponds to the survival for samples classified as TR (resp. NP) and the corresponding dashed lines correspond to upper and lower 95 CI. The red crosses represent censored data. Panel A (resp. B, resp. C) represent the methylation-based (resp. copy-number based, resp. clinical based) classification.</p

Summarized PT/AM Clinical and histological features.

<p><b>Age</b>: Age of the patient at diagnosis of the primary tumor in years, <b>Type</b>: histological type of the tumor (D =  ductal, L =  lobular, Meta = Metaplasia), <b>Grade</b>: Aggressiveness of the tumor (1 to 3), <b>ER</b>: presence of estrogen receptors, <b>PR</b>: presence of progesterone receptors, <b>HER2</b>: presence of HER2 receptors.</p

Study of similarity between matched primary tumors and recurrences by hierarchical clustering.

<p>Hierarchical clustering based on the manhattan distance between methylome profiles with complete linkage was performed. Real pairs that are closer to each other than to any other samples are underlined. Panel A (resp. B, resp. C) represents the PT/AM (resp. PT/LR, resp. PT/CL) set.</p

Correlation between methylation and copy-number scores.

<p>The horizontal red line (resp. vertical dashed blue line) corresponds to the 95% quantile of the distribution of the methylation-scores (resp. partial identity scores) for the unrelated pairs: (resp. ). PT/AM (resp. PT/LR, resp. PT/CL) pairs are colored in yellow (resp. blue, resp. pink). The black line corresponds to the linear regression between methylation and copy-number scores for all the datasets.</p