[Show abstract][Hide abstract] ABSTRACT: Neoadjuvant systemic therapy is being used increasingly in the treatment of early-stage breast cancer. Response, in the form of pathological complete response, is a validated and evaluable surrogate end point of survival after neoadjuvant therapy. Thus, pathological complete response has become a primary end point for clinical trials. However, there is a current lack of uniformity in the definition of pathological complete response. A review of standard operating procedures used by 28 major neoadjuvant breast cancer trials and/or 25 sites involved in such trials identified marked variability in specimen handling and histologic reporting. An international working group was convened to develop practical recommendations for the pathologic assessment of residual disease in neoadjuvant clinical trials of breast cancer and information expected from pathology reports. Systematic sampling of areas identified by informed mapping of the specimen and close correlation with radiological findings is preferable to overly exhaustive sampling, and permits taking tissue samples for translational research. Controversial areas are discussed, including measurement of lesion size, reporting of lymphovascular space invasion and the presence of isolated tumor cells in lymph nodes after neoadjuvant therapy, and retesting of markers after treatment. If there has been a pathological complete response, this must be clearly stated, and the presence/absence of residual ductal carcinoma in situ must be described. When there is residual invasive carcinoma, a comment must be made as to the presence/absence of chemotherapy effect in the breast and lymph nodes. The Residual Cancer Burden is the preferred method for quantifying residual disease in neoadjuvant clinical trials in breast cancer; other methods can be included per trial protocols and regional preference. Posttreatment tumor staging using the Tumor-Node-Metastasis system should be included. These recommendations for standardized pathological evaluation and reporting of neoadjuvant breast cancer specimens should improve prognostication for individual patients and allow comparison of treatment outcomes within and across clinical trials.Modern Pathology advance online publication, 24 July 2015; doi:10.1038/modpathol.2015.74.
Modern Pathology 07/2015; 28(9). DOI:10.1038/modpathol.2015.74 · 6.19 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Nucleotide alterations detected by next generation sequencing are not always true biological changes but could represent sequencing errors. Even highly accurate methods can yield substantial error rates when applied to millions of nucleotides. In this study, we examined the reproducibility of nucleotide variant calls in replicate sequencing experiments of the same genomic DNA. We performed targeted sequencing of all known human protein kinase genes (kinome) (~3.2 Mb) using the SOLiD v4 platform. Seventeen breast cancer samples were sequenced in duplicate (n=14) or triplicate (n=3) to assess concordance of all calls and single nucleotide variant (SNV) calls. The concordance rates over the entire sequenced region were >99.99%, while the concordance rates for SNVs were 54.3-75.5%. There was substantial variation in basic sequencing metrics from experiment to experiment. The type of nucleotide substitution and genomic location of the variant had little impact on concordance but concordance increased with coverage level, variant allele count (VAC), variant allele frequency (VAF), variant allele quality and p-value of SNV-call. The most important determinants of concordance were VAC and VAF. Even using the highest stringency of QC metrics the reproducibility of SNV calls was around 80% suggesting that erroneous variant calling can be as high as 20-40% in a single experiment. The sequence data have been deposited into the European Genome-phenome Archive (EGA) with accession number EGAS00001000826.
PLoS ONE 07/2015; 10(7):e0119230. DOI:10.1371/journal.pone.0119230 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The residual cancer burden index was developed as a method to quantify residual disease ranging from pathological complete response to extensive residual disease. The aim of this study was to evaluate the inter-Pathologist reproducibility in the residual cancer burden index score and category, and in their long-term prognostic utility. Pathology slides and pathology reports of 100 cases from patients treated in a randomized neoadjuvant trial were reviewed independently by five pathologists. The size of tumor bed, average percent overall tumor cellularity, average percent of the in situ cancer within the tumor bed, size of largest axillary metastasis, and number of involved nodes were assessed separately by each pathologist and residual cancer burden categories were assigned to each case following calculation of the numerical residual cancer burden index score. Inter-Pathologist agreement in the assessment of the continuous residual cancer burden score and its components and agreement in the residual cancer burden category assignments were analyzed. The overall concordance correlation coefficient for the agreement in residual cancer burden score among pathologists was 0.931 (95% confidence interval (CI) 0.908-0.949). Overall accuracy of the residual cancer burden score determination was 0.989. The kappa coefficient for overall agreement in the residual cancer burden category assignments was 0.583 (95% CI 0.539-0.626). The metastatic component of the residual cancer burden index showed stronger concordance between pathologists (overall concordance correlation coefficient=0.980; 95% CI 0.954-0.992), than the primary component (overall concordance correlation coefficient=0.795; 95% CI 0.716-0.853). At a median follow-up of 12 years residual cancer burden determined by each of the pathologists had the same prognostic accuracy for distant recurrence-free and survival (overall concordance correlation coefficient=0.995; 95% CI 0.989-0.998). Residual cancer burden assessment is highly reproducible, with reproducible long-term prognostic significance.Modern Pathology advance online publication, 1 May 2015; doi:10.1038/modpathol.2015.53.
Modern Pathology 05/2015; 28(7). DOI:10.1038/modpathol.2015.53 · 6.19 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Purpose: Previous efforts to develop transcriptional markers of chemotherapy sensitivity in TNBC had limited success due to the heterogeneity of this disease. The purpose of this study was to identify genomic differences between extremely chemotherapy sensitive and highly chemotherapy resistant TNBC through whole exome sequencing and to assess measures of genomic heterogeneity as predictive markers.
Methods: Twenty nine cases were selected from a prospectively collected cohort of fine needle aspiration specimens obtained before preoperative chemotherapy (MDACC) to represent two extreme response cohorts including pathologic complete response (pCR, N=17) or extensive residual cancer (eRD, N=12). DNA was extracted from specimens stored in RNAlater, exomes were captured using NimbleGen SeqCap EZ Exome Library preparation and paired-end sequencing of 75 base pair fragments was performed on Illumina HiSeq 2000. Alignment and variant calling were performed with BWA and GATK haplotype caller. Variants were filtered against the 1000 Genomes and TCGA normal breast samples to identify candidate somatic variants. Fisher-exact test was used to identify variant genes associated with sensitivity to chemotherapy. We calculated overall mutational load and normal-adjusted clonal entropy of driver mutations as measures of genome heterogeneity. The chi-squared test was used to compare differences in mutational spectra and genome heterogeneity between the two response groups.
Results: The mean coverage was over 150X and 93% of target regions had > 20X coverage. The number of non-silent COSMIC mutations was similar in tumors from the two response groups (pCR: 63, range 49-82; eRD: 59, range 43-78) as well as the number of novel non-silent mutations (eRD: 223, range 113-388; pCR: 192, range 125-293). Gene level aggregation of variants identified 4 genes (MUC21, SLCO5A1, LRBA, STNE1) with response-associated mutational patterns. However, mutations were non recurrent and p-values were modest, ranging from 0.04 to 0.005. We observed greater overall mutational load and subclonal heterogeneity (clonal entropy of cancer related mutations) associated with eRD compared to pCR. Both measures suggest that higher genomic DNA diversity is associated with chemotherapy resistance. However, some genes (BRCA1 and MKI67) had higher mutational load (sum of minor allele frequencies per gene) associated with pCR compared to eRD. In general, a higher proportion of C>T transition (P=0.011) and lower A>G transition (P=0.028) was associated with eRD. The same mutational spectrum shift was previously described in the comparison of trunk and branch driver events suggesting that eRD tumors may undergo heterogeneous branched evolution.
Conclusion: We observed greater genomic diversity and distinctive mutational spectra in original pre-treatment samples of TNBC that were associated with extensive residual disease compared to pCR. Our analysis suggests that broad measures of genomic diversity may serve as markers of resistance to chemotherapy.
Cancer Research 05/2015; 75(9 Supplement):PD3-2-PD3-2. DOI:10.1158/1538-7445.SABCS14-PD3-2 · 9.33 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A subset of early stage estrogen receptor (ER)-positive breast cancers considered "high risk" for recurrence with endocrine therapy alone by current genomic prognostic predictors, such as Oncotype DX, is no longer high risk after receiving adjuvant chemotherapy. We hypothesized that a recently described gene expression-based outcome predictor adjuvant chemotherapy and endocrine therapy sensitivity (ACES) could re-stratify these patients into high and low risk groups for relapse when treated with both chemo- and endocrine therapies. ACES involves four separate modules (endocrine sensitivity, chemotherapy sensitivity, chemotherapy resistance, and survival prediction) that yield a prediction for good or poor outcome with current standard of care multimodality therapy. ACES was applied to Affymetrix gene expression data from 2 retrospectively collected ER-positive and HER2-negative patient cohorts that were uniformly treated with adjuvant endocrine and chemotherapy (n = 250). Each sample was first risk stratified by a genomic surrogate of Oncotype DX, and the high risk patients (n = 76) were re-stratified by ACES. Recurrence-free survival (RFS) was evaluated with ACES risk categories. The Oncotype DX high risk but ACES good prognosis patients (n = 24, 32 %) had an RFS of 95 % compared to 76 % in the poor prognosis group (n = 52; log-rank p = 0.033) at 5 years. ACES risk category remained an independent predictor in multivariate analysis after adjusting for age, T-stage, and lymph node involvement at diagnosis (hazard ratio 0.15; p = 0.072). Tertiary risk prediction that takes into account chemotherapy and endocrine sensitivity, and baseline prognosis may help identify high risk ER-positive patients who have excellent survival after chemotherapy.
Breast Cancer Research and Treatment 02/2015; 149(3). DOI:10.1007/s10549-015-3277-7 · 3.94 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background:
The purpose of this study was (i) to test the hypothesis that combining Ki67 with residual cancer burden (RCB) following neoadjuvant chemotherapy, as the residual proliferative cancer burden (RPCB), provides significantly more prognostic information than either alone; (ii) to determine whether also integrating information on ER and grade improves prognostic power.
Patients and methods:
A total of 220 patients treated with neoadjuvant chemotherapy for primary breast cancer were included in the study. Analyses employed a Cox proportional hazard model. Prognostic indices (PIs) were created adding in Ki67, grade and ER to RCB. Leave-one-out cross-validation was used to reduce bias. The overall change in χ(2) of the best model for each index was used to compare the prognostic ability of the different indices.
All PIs provided significant prognostic information for patients with residual disease following neoadjuvant chemotherapy. RPCB (χ(2) = 61.4) was significantly more prognostic than either RCB (χ(2) = 38.1) or Ki67 (χ(2) = 53.8) alone P < 0.001. A PI incorporating RCB, Ki67 grade and ER provided the most prognostic information overall and gave χ(2) = 73.8.
This study provides proof of principle that the addition of post-treatment Ki67 to RCB improves the prediction of long-term outcome. Prediction may be further improved by addition of post-treatment grade and ER and warrants further investigation for estimating post-neoadjuvant risk of recurrence. These indices may have utility in stratifying patients for novel therapeutic interventions after neoadjuvant chemotherapy.
Annals of Oncology 10/2014; 26(1). DOI:10.1093/annonc/mdu508 · 7.04 Impact Factor