Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification

Abstract Background Spatial heterogeneity in biomarker expression may impact breast cancer classification. The aims of this study were to estimate the frequency of spatial heterogeneity in biomarker expression within tumors, to identify technical and biological factors contributing to spatial heterogeneity, and to examine the impact of discordant biomarker status within tumors on clinical record agreement. Methods Tissue microarrays (TMAs) were constructed using two to four cores (1.0 mm) for each of 1085 invasive breast cancers from the Carolina Breast Cancer Study, which is part of the AMBER Consortium. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) was quantified using automated digital imaging analysis. The biomarker status for each core and for each case was assigned using clinical thresholds. Cases with core-to-core biomarker discordance were manually reviewed to distinguish intratumoral biomarker heterogeneity from misclassification of biomarker status by the automated algorithm. The impact of core-to-core biomarker discordance on case-level agreement between TMAs and the clinical record was evaluated. Results On the basis of automated analysis, discordant biomarker status between TMA cores occurred in 9 %, 16 %, and 18 % of cases for ER, PR, and HER2, respectively. Misclassification of benign epithelium and/or ductal carcinoma in situ as invasive carcinoma by the automated algorithm was implicated in discordance among cores. However, manual review of discordant cases confirmed spatial heterogeneity as a source of discordant biomarker status between cores in 2 %, 7 %, and 8 % of cases for ER, PR, and HER2, respectively. Overall, agreement between TMA and clinical record was high for ER (94 %), PR (89 %), and HER2 (88 %), but it was reduced in cases with core-to-core discordance (agreement 70 % for ER, 61 % for PR, and 57 % for HER2). Conclusions Intratumoral biomarker heterogeneity may impact breast cancer classification accuracy, with implications for clinical management. Both manually confirmed biomarker heterogeneity and misclassification of biomarker status by automated image analysis contribute to discordant biomarker status between TMA cores. Given that manually confirmed heterogeneity is uncommon (<10 % of cases), large studies are needed to study the impact of heterogeneous biomarker expression on breast cancer classification and outcomes

Performance of Three-Biomarker Immunohistochemistry for Intrinsic Breast Cancer Subtyping in the AMBER Consortium

Classification of breast cancer into intrinsic subtypes has clinical and epidemiologic importance. To examine accuracy of immunohistochemistry (IHC)-based methods for identifying intrinsic subtypes, a three-biomarker IHC panel was compared to the clinical record and RNA-based intrinsic (PAM50) subtypes

Analytical variables influencing the performance of a miRNA based laboratory assay for prediction of relapse in stage I non-small cell lung cancer (NSCLC)

<p>Abstract</p> <p>Background</p> <p>Laboratory assays are needed for early stage non-small lung cancer (NSCLC) that can link molecular and clinical heterogeneity to predict relapse after surgical resection. We technically validated two miRNA assays for prediction of relapse in NSCLC. Total RNA from seventy-five formalin-fixed and paraffin-embedded (FFPE) specimens was extracted, labeled and hybridized to Affymetrix miRNA arrays using different RNA input amounts, ATP-mix dilutions, array lots and RNA extraction- and labeling methods in a total of 166 hybridizations. Two combinations of RNA extraction- and labeling methods (assays I and II) were applied to a cohort of 68 early stage NSCLC patients.</p> <p>Results</p> <p>RNA input amount and RNA extraction- and labeling methods affected signal intensity and the number of detected probes and probe sets, and caused large variation, whereas different ATP-mix dilutions and array lots did not. Leave-one-out accuracies for prediction of relapse were 63% and 73% for the two assays. Prognosticator calls ("no recurrence" or "recurrence") were consistent, independent on RNA amount, ATP-mix dilution, array lots and RNA extraction method. The calls were not robust to changes in labeling method.</p> <p>Conclusions</p> <p>In this study, we demonstrate that some analytical conditions such as RNA extraction- and labeling methods are important for the variation in assay performance whereas others are not. Thus, careful optimization that address all analytical steps and variables can improve the accuracy of prediction and facilitate the introduction of microRNA arrays in the clinic for prediction of relapse in stage I non-small cell lung cancer (NSCLC).</p

Frequency of breast cancer subtypes among African American women in the AMBER consortium

Abstract Background Breast cancer subtype can be classified using standard clinical markers (estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2)), supplemented with additional markers. However, automated biomarker scoring and classification schemes have not been standardized. The aim of this study was to optimize tumor classification using automated methods in order to describe subtype frequency in the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Methods Using immunohistochemistry (IHC), we quantified the expression of ER, PR, HER2, the proliferation marker Ki67, and two basal-like biomarkers, epidermal growth factor receptor (EGFR) and cytokeratin (CK)5/6, in 1381 invasive breast tumors from African American women. RNA-based (prediction analysis of microarray 50 (PAM50)) subtype, available for 574 (42%) cases, was used to optimize classification. Subtype frequency was calculated, and associations between subtype and tumor characteristics were estimated using logistic regression. Results Relative to ER, PR and HER2 from medical records, central IHC staining and the addition of Ki67 or combined tumor grade improved accuracy for classifying PAM50-based luminal subtypes. Few triple negative cases (< 2%) lacked EGFR and CK5/6 expression, thereby providing little improvement in accuracy for identifying basal-like tumors. Relative to luminal A subtype, all other subtypes had higher combined grade and were larger, and ER-/HER2+ tumors were more often lymph node positive and late stage tumors. The frequency of basal-like tumors was 31%, exceeded only slightly by luminal A tumors (37%). Conclusions Our findings indicate that automated IHC-based classification produces tumor subtype frequencies approximating those from PAM50-based classification and highlight high frequency of basal-like and low frequency of luminal A breast cancer in a large study of African American women

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma

SummaryWe describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers

USP1 Regulates TAZ Protein Stability Through Ubiquitin Modifications in Breast Cancer

The Hippo signaling pathway is an evolutionarily conserved pathway that was initially discovered in Drosophila melanogaster and was later found to have mammalian orthologues. The key effector proteins in this pathway, YAP/TAZ, are often dysregulated in cancer, leading to a high degree of cell proliferation, migration, metastasis and cancer stem cell populations. Due to these malignant phenotypes it is important to understand the regulation of YAP/TAZ at the protein level. Using an siRNA library screen of deubiquitinating enzymes (DUBs), we identified ubiquitin specific peptidase 1 (USP1) as a novel TAZ (WWTR1) regulator. We demonstrated that USP1 interacts with TAZ and increases TAZ protein stability. Conversely, loss of function of USP1 reduces TAZ protein levels through increased poly-ubiquitination, causing a decrease in cell proliferation and migration of breast cancer cells. Moreover, we showed a strong positive correlation between USP1 and TAZ in breast cancer patients. Our findings facilitate the attainment of better understanding of the crosstalk between these pathways and may lead to potential therapeutic interventions for breast cancer patients

MiR-205 and MiR-375 microRNA assays to distinguish squamous cell carcinoma from adenocarcinoma in lung cancer biopsies.

INTRODUCTION: Identification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) histology of non-small-cell lung cancer (NSCLC) in biopsies is clinically important but can be inaccurate by routine histopathologic examination. We quantify this inaccuracy at a cancer center, and evaluate the utility of a microRNA-based method to histotype AC/SCC in biopsies. METHODS: RNA was extracted from tissue sections with greater than 90% tumor content that were macro- or micro-dissected from formalin-fixed, paraffin-embedded biopsy specimens. MicroRNAs in RNA from the biopsies and from resected tumors were quantified by TaqMan reverse transcription-polymerase chain reaction assays and normalized against the RNU6B housekeeping RNA. Publicly available microRNA expression datasets were examined. RESULTS: NSCLC subtyping of small biopsy specimens by routine histopathologic examination either failed or mistyped the histology of 21% of 190 cases. Using 77 resectates, an reverse transcription-polymerase chain reaction-based assay of microRNAs miR-21, miR-205, and miR-375 was developed to identify AC and SCC subtypes of NSCLC. This method identified the AC/SCC histotypes of 25 biopsies with an accuracy of 96%, and correctly histotyped all 12 cases for which the histology had been mistyped by routine histopathologic examination of the biopsy. Examination of publicly available datasets identified miR-205 and miR-375 as microRNAs with the best ability to histotype AC and SCC, and that levels of the two microRNAs in AC or SCC are unaffected by the pathologic stage of the tumor or the age or race of the patient. CONCLUSIONS: Histotypic microRNA assays can aid the subtyping of NSCLC biopsies as AC or SCC by standard histopathologic methods

Intraobserver and interobserver variability in distinguishing between endocervical and endometrial adenocarcinoma on problematic cases of cervical curettings

We conducted a prospective study where 4 pathologists examined patients' problematic cases of cervical curetting for adenocarcinoma to determine whether it is of endocervical or endometrial origin based on 3 parameters: age, morphology, and immunohistochemistry (IHC) panel. Our aims were to evaluate the intraobserver and interobserver variability and to compare the results using those parameters to the final hysterectomy specimens. The value of morphology, morphology+age, and the combined parameters (morphology+age+IHC) in predicting the correct origin of the tumor was evaluated. The intraobserver agreements ranged from fair to almost perfect for each of morphology, morphology+age, and the combined parameters. The interobserver agreements were fair in the first review and ranged from slight to fair in the second review. The agreements between the diagnosis based on morphology, morphology+age, and the combined parameters compared with the final diagnosis on the hysterectomy specimen were slight (kappa=0.137), fair (kappa=0.290), and moderate (kappa=0.497), respectively. We concluded that (i) discriminating between endocervical and endometrial carcinoma is highly subject to intraobserver and interobserver variability. (ii) Surprisingly, this variability is not affected by pathologists' experience. (iii) An IHC panel adds a useful piece of information to predict the tumor origin. Lastly, even though the combination of morphology, age, and IHC is far from perfect in predicting the correct origin of the tumor, it is still the best available method