L'Écho : grand quotidien d'information du Centre Ouest

30 décembre 19351935/12/30 (A64).Appartient à l’ensemble documentaire : PoitouCh

La Croix du Nord : supplément régional à la Croix de Paris ["puis" grand journal quotidien du Nord de la France]

10 septembre 19111911/09/10 (A22,N7617).Appartient à l’ensemble documentaire : NordPdeC

Additional file 2: Table S1. of Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response

1977 Cancer Gene Panel. This file lists all 1,977 genes in the Cancer Gene Panel, used in this study. (XLS 111 kb

Additional file 4: Table S3. of Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response

List of all mutations. This file shows all mutations passing thresholds as explained in “Methods”. The column “confirmed” shows mutations that have been confirmed by either Sanger Sequencing or deep whole exome sequencing in another research project (unpublished data). The column “included in analysis” shows the mutations that passed our threshold for putative driver mutations, based on effect, SIFT, polyphen scores and COSMIC (see “Methods”). The column “dubious” shows the mutations that might be dubious based on gene length, expression or replication time [20]. (XLSX 64 kb

Additional file 9: Figure S3. of Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response

Validation of TTK, TP53BP2 and genome-wide copy number profiles with Nimblegen 135 K aCGH arrays. aCGH and exome data, for the samples for which aCGH data were available (three cases for TTK, five cases for TP53BP2). Arrow indicates respectively the TTK and TP53BP2 locus. From page 3 on we show all 14 samples for which we have both exome and aCGH data, irrespective of TTK and TP53BP2 status. In these rainbow plots, the samples containing a TTK or TP53BP2 gain are indicated with an arrow at the respective genomic location. (PDF 1639 kb

Survival analysis.

<p>Relapse free survival (RFS) curves according to R497K polymorphism groups (A, B), pathological complete response (pCR) (C, D) and BC subtypes (E, F) in patients from INCA cohort (A, C, E) and NKI-AVL cohort (B, D, F).</p

Impact of R497K polymorphism and other variables on the response to neoadjuvant chemotherapy.

<p>Impact of R497K polymorphism and other variables on the response to neoadjuvant chemotherapy.</p

Evaluation of the <i>EGFR</i> polymorphism R497K in two cohorts of neoadjuvantly treated breast cancer patients

<div><p>Pathological response of breast cancer to neoadjuvant chemotherapy (NAC) presents great variability, and new prognostic biomarkers are needed. Our aim was to evaluate the association of the epidermal growth factor receptor gene (<i>EGFR</i>) polymorphism R497K (rs2227983) with prognostic features and clinical outcomes of breast cancer, including the pathological response to NAC and the recurrence-free survival (RFS). Tumoral complete response (tCR) was defined by no remaining invasive cancer in the excised breast, whereas pathological complete response (pCR) was defined by no remaining invasive cancer both in the excised breast and lymph nodes. Two independent cohorts were analyzed: one from Brazil (INCA, n = 288) and one from The Netherlands (NKI-AVL, n = 255). In the INCA cohort, the variant (Lys-containing) genotypes were significantly associated with lower proportion of tCR (OR_adj = 0.92; 95%CI = 0.85–0.99), whereas in the NKI-AVL cohort they were associated with tumor grade 3 (p = 0.035) and with triple-negative subtype (p = 0.032), but not with clinical outcomes. Such distinct prognostic associations may have arisen due to different neoadjuvant protocols (p < 0.001), or to lower age at diagnosis (p < 0.001) and higher proportion of tumor grade 3 (p = 0.018) at the NKI-AVL cohort. Moreover, NKI-AVL patients achieved better proportion of pCR (21.2% <i>vs</i> 8.3%, p < 0.001) and better RFS (HR_adj = 0.48; 95% _adjCI = 0.26–0.86) than patients from INCA. In conclusion, large scale studies comprehending different populations are needed to evaluate the impact of genome variants on breast cancer outcomes.</p></div

Distribution of clinical and histopathological variables according to R497K genotypes in INCA and NKI-AVL cohorts.

<p>Distribution of clinical and histopathological variables according to R497K genotypes in INCA and NKI-AVL cohorts.</p