Comparison of residual cancer burden, American Joint Committee on Cancer staging and pathologic complete response in breast cancer after neoadjuvant chemotherapy: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657)

Purpose: Several pathologic staging systems characterize residual tumor in patients undergoing neoadjuvant chemotherapy for breast cancer. Pathologic complete response (pCR) is now accepted by the Food and Drug Administration as an endpoint for granting accelerated drug approval. Two other systems of post-neoadjuvant pathologic tumor staging—residual cancer burden (RCB) and the American Joint Committee on Cancer post-neoadjuvant therapy staging system (yAJCC)—have been developed to characterize residual tumors when patients do not achieve pCR. The optimal system and the ways in which these systems complement each other have not been fully determined. Methods: Using data from the I-SPY 1 TRIAL, we compared pCR, RCB, and yAJCC as predictors of early recurrence-free survival (RFS) to identify ways to improve post-neoadjuvant pathologic evaluation. Results: Among 162 patients assessed, pCR identified patients at lowest risk of recurrence, while RCB and yAJCC identified patients at highest risk. Hormone-receptor (HR) and HER2 subtypes further improved risk prediction. Recursive partitioning indicated that triple-negative or HER2+ patients with yAJCC III or RCB 3 have the highest recurrence risk, with an RFS of 27%. Our analysis also highlighted discrepancies between RCB and yAJCC stratification: 31% of patients had discrepant RCB and yAJCC scores. We identified differential treatment of lymph node involvement and tumor cellularity as drivers of these discrepancies. Conclusions: These data indicate that there is benefit to reporting both RCB and yAJCC for patients in order to identify those at highest risk of relapse

Atypical glandular cells in conventional cervical smears: Incidence and follow-up

BACKGROUND: Atypical glandular cells on cervical smears are often associated with clinically significant uterine lesions. The frequency and accuracy of AGC-NOS (i.e. atypical glandular cells, not otherwise specified) diagnoses, regardless of the gland cell type or the degree of suspicion, and their outcome were investigated. METHODS: From January 1, 1990 to December 31, 1999 a total of 261 patients had an AGC-NOS diagnosis made by conventional cervical Papanicolaou smear interpretation representing 0.05% of all Pap-smears analyzed at the national level. 191 (73.2%) patients had a subsequent histological examination, 8 samples were not representative by origin and were excluded. RESULTS: Out of 183 AGC-NOS diagnosed, 56.3% (103/183) were associated with tissue-proven precancerous and/or cancerous lesions, 44% being of endocervical and 56% of endometrial origin. 75% of all AGC-patients were asymptomatic. 66.7% (6/9) of the patients with subsequent invasive endocervical adenocarcinoma (AC) and 56% (28/50) of those patients with invasive endometrial AC were without clinical symptoms. 3 patients out of 9 with an invasive endocervical AC were 35 years of age or less. 10.1% and 12.3% of all 'new' tissue-proven invasive endocervical or endometrial AC respectively recorded by the national Morphologic Tumour Registry (MTR) were first identified by a cytological AGC-NOS diagnosis. CONCLUSION: Our findings emphasize the importance of the cytological AGC-category even in the absence of a precise origin or cell type specification. 56% of the AGC-diagnoses being associated with significant cancerous or precancerous conditions, a complete and careful evaluation is required

Identification of Molecular Distinctions Between Normal Breast-Associated Fibroblasts and Breast Cancer-Associated Fibroblasts

Stromal fibroblasts influence the behavior of breast epithelial cells. Fibroblasts derived from normal breast (NAF) inhibit epithelial growth, whereas fibroblasts from breast carcinomas (CAF) have less growth inhibitory capacity and can promote epithelial growth. We sought to identify molecules that are differentially expressed in NAF versus CAF and potentially responsible for their different growth regulatory abilities. To determine the contribution of soluble molecules to fibroblast–epithelial interactions, NAF were grown in 3D, transwell or direct contact co-cultures with MCF10AT epithelial cells. NAF suppressed proliferation of MCF10AT in both direct contact and transwell co-cultures, but this suppression was significantly greater in direct co-cultures, indicating involvement of both soluble and contact factors. Gene expression profiling of early passage fibroblast cultures identified 420 genes that were differentially expressed in NAF versus CAF. Of the eight genes selected for validation by real-time PCR, FIBULIN 1, was overexpressed in NAF, and DICKKOPF 1, NEUREGULIN 1, PLASMINOGEN ACTIVATOR INHIBITOR 2, and TISSUE PLASMINOGEN ACTIVATOR were overexpressed in CAF. A higher expression of FIBULIN 1 in normal- than cancer-associated fibroblastic stroma was confirmed by immunohistochemistry of breast tissues. Among breast cancers, stromal expression of Fibulin 1 protein was higher in estrogen receptor α-positive cancers and low stromal expression of Fibulin 1 correlated with a higher proliferation of cancer epithelial cells. In conclusion, expression profiling of NAF and CAF cultures identified many genes with potential relevance to fibroblast–epithelial interactions in breast cancer. Furthermore, these early passage fibroblast cultures can be representative of gene expression in stromal fibroblasts in vivo

The potential biomarkers in predicting pathologic response of breast cancer to three different chemotherapy regimens: a case control study

<p>Abstract</p> <p>Background</p> <p>Preoperative chemotherapy (PCT) has become the standard of care in locally advanced breast cancer. The identification of patient-specific tumor characteristics that can improve the ability to predict response to therapy would help optimize treatment, improve treatment outcomes, and avoid unnecessary exposure to potential toxicities. This study is to determine whether selected biomarkers could predict pathologic response (PR) of breast tumors to three different PCT regimens, and to identify a subset of patients who would benefit from a given type of treatment.</p> <p>Methods</p> <p>118 patients with primary breast tumor were identified and three PCT regimens including DEC (docetaxel+epirubicin+cyclophosphamide), VFC (vinorelbine/vincristine+5-fluorouracil+cyclophosphamide) and EFC (epirubicin+5-fluorouracil+cyclophosphamide) were investigated. Expression of steroid receptors, HER2, P-gp, MRP, GST-pi and Topo-II was evaluated by immunohistochemical scoring on tumor tissues obtained before and after PCT. The PR of breast carcinoma was graded according to Sataloff's classification. Chi square test, logistic regression and Cochran-Mantel-Haenszel assay were performed to determine the association between biomarkers and PR, as well as the effectiveness of each regimen on induction of PR.</p> <p>Results</p> <p>There was a clear-cut correlation between the expression of ER and decreased PR to PCT in all three different regimens (<it>p </it>< 0.05). HER2 expression is significantly associated with increased PR in DEC regimen (<it>p </it>< 0.05), but not predictive for PR in EFC and VFC groups. No significant correlation was found between biomarkers PgR, Topo-II, P-gp, MRP or GST-pi and PR to any tested PCT regimen. After adjusted by a stratification variable of ER or HER2, DEC regimen was more effective in inducing PR in comparison with VFC and EFC regimens.</p> <p>Conclusion</p> <p>ER is an independent predictive factor for PR to PCT regimens including DEC, VFC and EFC in primary breast tumors, while HER2 is only predictive for DEC regimen. Expression of PgR, Topo-II, P-gp, MRP and GST-pi are not predictive for PR to any PCT regimens investigated. Results obtained in this clinical study may be helpful for the selection of appropriate treatments for breast cancer patients.</p

Information retrieval and text mining technologies for chemistry

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.A.V. and M.K. acknowledge funding from the European Community’s Horizon 2020 Program (project reference: 654021 - OpenMinted). M.K. additionally acknowledges the Encomienda MINETAD-CNIO as part of the Plan for the Advancement of Language Technology. O.R. and J.O. thank the Foundation for Applied Medical Research (FIMA), University of Navarra (Pamplona, Spain). This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia), and FEDER (European Union), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). We thank Iñigo Garciá -Yoldi for useful feedback and discussions during the preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Pathologic Complete Response Predicts Recurrence-Free Survival More Effectively by Cancer Subset: Results From the I-SPY 1 TRIAL—CALGB 150007/150012, ACRIN 6657

Neoadjuvant chemotherapy for breast cancer provides critical information about tumor response; how best to leverage this for predicting recurrence-free survival (RFS) is not established. The I-SPY 1 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis) was a multicenter breast cancer study integrating clinical, imaging, and genomic data to evaluate pathologic response, RFS, and their relationship and predictability based on tumor biomarkers