A new gene expression signature, the ClinicoMolecular Triad Classification, may improve prediction and prognostication of breast cancer at the time of diagnosis

Abstract Introduction When making treatment decisions, oncologists often stratify breast cancer (BC) into a low-risk group (low-grade estrogen receptor-positive (ER+)), an intermediate-risk group (high-grade ER+) and a high-risk group that includes Her2+ and triple-negative (TN) tumors (ER-/PR-/Her2-). None of the currently available gene signatures correlates to this clinical classification. In this study, we aimed to develop a test that is practical for oncologists and offers both molecular characterization of BC and improved prediction of prognosis and treatment response. Methods We investigated the molecular basis of such clinical practice by grouping Her2+ and TN BC together during clustering analyses of the genome-wide gene expression profiles of our training cohort, mostly derived from fine-needle aspiration biopsies (FNABs) of 149 consecutive evaluable BC. The analyses consistently divided these tumors into a three-cluster pattern, similarly to clinical risk stratification groups, that was reproducible in published microarray databases (n = 2,487) annotated with clinical outcomes. The clinicopathological parameters of each of these three molecular groups were also similar to clinical classification. Results The low-risk group had good outcomes and benefited from endocrine therapy. Both the intermediate- and high-risk groups had poor outcomes, and their BC was resistant to endocrine therapy. The latter group demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in Myc, E2F1, Ras, β-catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. On the basis of multivariate analysis, we found that this new gene signature, termed the "ClinicoMolecular Triad Classification" (CMTC), predicted recurrence and treatment response better than all pathological parameters and other prognostic signatures. Conclusions CMTC correlates well with current clinical classifications of BC and has the potential to be easily integrated into routine clinical practice. Using FNABs, CMTC can be determined at the time of diagnostic needle biopsies for tumors of all sizes. On the basis of using public databases as the validation cohort in our analyses, CMTC appeared to enable accurate treatment guidance, could be made available in preoperative settings and was applicable to all BC types independently of tumor size and receptor and nodal status. The unique oncogenic signaling pathway pattern of each CMTC group may provide guidance in the development of new treatment strategies. Further validation of CMTC requires prospective, randomized, controlled trials

Comparison of Whole Genome Amplification Methods for Analysis of DNA Extracted from Microdissected Early Breast Lesions in Formalin-Fixed Paraffin-Embedded Tissue

To understand cancer progression, it is desirable to study the earliest stages of its development, which are often microscopic lesions. Array comparative genomic hybridization (aCGH) is a valuable high-throughput molecular approach for discovering DNA copy number changes; however, it requires a relatively large amount of DNA, which is difficult to obtain from microdissected lesions. Whole genome amplification (WGA) methods were developed to increase DNA quantity; however their reproducibility, fidelity, and suitability for formalin-fixed paraffin-embedded (FFPE) samples are questioned. Using aCGH analysis, we compared two widely used approaches for WGA: single cell comparative genomic hybridization protocol (SCOMP) and degenerate oligonucleotide primed PCR (DOP-PCR). Cancer cell line and microdissected FFPE breast cancer DNA samples were amplified by the two WGA methods and subjected to aCGH. The genomic profiles of amplified DNA were compared with those of non-amplified controls by four analytic methods and validated by quantitative PCR (Q-PCR). We found that SCOMP-amplified samples had close similarity to non-amplified controls with concordance rates close to those of reference tests, while DOP-amplified samples had a statistically significant amount of changes. SCOMP is able to amplify small amounts of DNA extracted from FFPE samples and provides quality of aCGH data similar to non-amplified samples

Mapping genomic and transcriptomic alterations spatially in epithelial cells adjacent to human breast carcinoma.

Almost all genomic studies of breast cancer have focused on well-established tumours because it is technically challenging to study the earliest mutational events occurring in human breast epithelial cells. To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations. Rather, we find a possibility of field cancerization surrounding the primary tumour by constructing a classifier that evaluates where epithelial samples were obtained relative to a tumour (cross-validated micro-averaged AUC = 0.74). We implement a spectral co-clustering algorithm to define biclusters. Relating to over-represented bicluster pathways, we further validate two genes with tissue microarrays and in vitro experiments. We highlight evidence suggesting that bicluster perturbation occurs early in tumour development

BC4GO: a full-text corpus for the BioCreative IV GO task

Gene function curation via Gene Ontology (GO) annotation is a common task among Model Organism Database groups. Owing to its manual nature, this task is considered one of the bottlenecks in literature curation. There have been many previous attempts at automatic identification of GO terms and supporting information from full text. However, few systems have delivered an accuracy that is comparable with humans. One recognized challenge in developing such systems is the lack of marked sentence-level evidence text that provides the basis for making GO annotations. We aim to create a corpus that includes the GO evidence text along with the three core elements of GO annotations: (i) a gene or gene product, (ii) a GO term and (iii) a GO evidence code. To ensure our results are consistent with real-life GO data, we recruited eight professional GO curators and asked them to follow their routine GO annotation protocols. Our annotators marked up more than 5000 text passages in 200 articles for 1356 distinct GO terms. For evidence sentence selection, the inter-annotator agreement (IAA) results are 9.3% (strict) and 42.7% (relaxed) in F1-measures. For GO term selection, the IAAs are 47% (strict) and 62.9% (hierarchical). Our corpus analysis further shows that abstracts contain ∼10% of relevant evidence sentences and 30% distinct GO terms, while the Results/Experiment section has nearly 60% relevant sentences and >70% GO terms. Further, of those evidence sentences found in abstracts, less than one-third contain enough experimental detail to fulfill the three core criteria of a GO annotation. This result demonstrates the need of using full-text articles for text mining GO annotations. Through its use at the BioCreative IV GO (BC4GO) task, we expect our corpus to become a valuable resource for the BioNLP research community

Heterogeneity of circulating tumour cell-associated genomic gains in breast cancer and its association with the host immune response.

Tumor cells that preferentially enter circulation include the precursors of metastatic cancer. Previously, we characterized circulating tumor cells (CTC) from patients with breast cancer and identified a signature of genomic regions with recurrent copy-number gains. Through FISH, we now show that these CTC-associated regions are detected within the matched untreated primary tumors of these patients (21% to 69%, median 55.5%, n = 19). Furthermore, they are more prevalent in the metastases of patients who died from breast cancer after multiple rounds of treatment (70% to 100%, median 93%, samples n = 41). Diversity indices revealed that higher spatial heterogeneity for these regions within primary tumors is associated with increased dissemination and metastasis. An identified subclone with multiple regions gained (MRG clone) was enriched in a posttreatment primary breast carcinoma as well as multiple metastatic tumors and local breast recurrences obtained at autopsy, indicative of a distinct early subclone with the capability to resist multiple lines of treatment and eventually cause death. In addition, multiplex immunofluorescence revealed that tumor heterogeneity is significantly associated with the degree of infiltration of B lymphocytes in triple-negative breast cancer, a subtype with a large immune component. Collectively, these data reveal the functional potential of genetic subclones that comprise heterogeneous primary breast carcinomas and are selected for in CTCs and posttreatment breast cancer metastases. In addition, they uncover a relationship between tumor heterogeneity and host immune response in the tumor microenvironment. SIGNIFICANCE: As breast cancers progress, they become more heterogeneous for multiple regions amplified in circulating tumor cells, and intratumoral spatial heterogeneity is associated with the immune landscape

Real-world and natural history data for drug evaluation in Duchenne muscular dystrophy: suitability of the North Star Ambulatory Assessment for comparisons with external controls

Using external controls based on real-world or natural history data (RWD/NHD) for drug evaluations in Duchenne muscular dystrophy (DMD) is appealing given the challenges of enrolling placebo-controlled trials, especially for multi-year trials. Comparisons to external controls, however, face risks of bias due to differences in outcomes between trial and RWD/NHD settings. To assess this bias empirically, we conducted a multi-institution study comparing mean 48-week changes in North Star Ambulatory Assessment (NSAA) total score between trial placebo arms and RWD/NHD sources, with and without adjustment for baseline prognostic factors. Analyses used data from three placebo arms (235 48-week intervals, N = 235 patients) and three RWD/NHD sources (348 intervals, N = 202 patients). Differences in mean ΔNSAA between placebo arms and RWD/NHD sources were small before adjustment (-1.2 units, 95% CI: [-2.0 -0.5]) and were attenuated and no longer statistically significant after adjustment (0.1 units (95% CI: [-0.6, 0.8]). Results were similar whether adjusting using multivariable regression or propensity score matching. This consistency in ΔNSAA between trial placebo arms and RWD/NHD sources accords with prior findings for the six-minute walk distance, provides a well-validated framework for baseline adjustment of prognostic factors, and supports the suitability of RWD/NHD external controls for drug evaluations in ambulatory DMD

Meaningful changes in motor function in Duchenne muscular dystrophy (DMD): A multi-center study

Evaluations of treatment efficacy in Duchenne muscular dystrophy (DMD), a rare genetic disease that results in progressive muscle wasting, require an understanding of the ‘meaningfulness’ of changes in functional measures. We estimated the minimal detectable change (MDC) for selected motor function measures in ambulatory DMD, i.e., the minimal degree of measured change needed to be confident that true underlying change has occurred rather than transient variation or measurement error. MDC estimates were compared across multiple data sources, representing >1000 DMD patients in clinical trials and real-world clinical practice settings. Included patients were ambulatory, aged ≥4 to 80% confidence in true change were 2.8 units for the North Star Ambulatory Assessment (NSAA) total score, 1.3 seconds for the 4-stair climb (4SC) completion time, 0.36 stairs/second for 4SC velocity and 36.3 meters for the 6-minute walk distance (6MWD). MDC estimates were similar across clinical trial and real-world data sources, and tended to be slightly larger than MCIDs for these measures. The identified thresholds can be used to inform endpoint definitions, or as benchmarks for monitoring individual changes in motor function in ambulatory DMD

Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens

Abstract Background The ability of gene profiling to predict treatment response and prognosis in breast cancers has been demonstrated in many studies using DNA microarray analyses on RNA from fresh frozen tumor specimens. In certain clinical and research situations, performing such analyses on archival formalin fixed paraffin-embedded (FFPE) surgical specimens would be advantageous as large libraries of such specimens with long-term follow-up data are widely available. However, FFPE tissue processing can cause fragmentation and chemical modifications of the RNA. A number of recent technical advances have been reported to overcome these issues. Our current study evaluates whether or not the technology is ready for clinical applications. Methods A modified RNA extraction method and a recent DNA microarray technique, cDNA-mediated annealing, selection, extension and ligation (DASL, Illumina Inc) were evaluated. The gene profiles generated from FFPE specimens were compared to those obtained from paired fresh fine needle aspiration biopsies (FNAB) of 25 breast cancers of different clinical subtypes (based on ER and Her2/neu status). Selected RNA levels were validated using RT-qPCR, and two public databases were used to demonstrate the prognostic significance of the gene profiles generated from FFPE specimens. Results Compared to FNAB, RNA isolated from FFPE samples was relatively more degraded, nonetheless, over 80% of the RNA samples were deemed suitable for subsequent DASL assay. Despite a higher noise level, a set of genes from FFPE specimens correlated very well with the gene profiles obtained from FNAB, and could differentiate breast cancer subtypes. Expression levels of these genes were validated using RT-qPCR. Finally, for the first time we correlated gene expression profiles from FFPE samples to survival using two independent microarray databases. Specifically, over-expression of ANLN and KIF2C, and under-expression of MAPT strongly correlated with poor outcomes in breast cancer patients. Conclusion We demonstrated that FFPE specimens retained important prognostic information that could be identified using a recent gene profiling technology. Our study supports the use of FFPE specimens for the development and refinement of prognostic gene signatures for breast cancer. Clinical applications of such prognostic gene profiles await future large-scale validation studies