Clinical and Pathologic Response of the Primary Tumor in Women Receiving Neoadjuvant Docetaxel-Capecitabine (+/- Trastuzumab) Chemotherapy
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE22358 | GEO | 2011/03/18
SECONDARY ACCESSION(S): PRJNA127667
REPOSITORIES: GEO
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Project description:Results: In subjects who completed treatment and surgery, the pCR and near-complete response rates were 15.8% in HER2-negative and 50% in HER2-positive subjects. When stratified by genomic subtype, subjects of the HER2-enriched subtype had the best response (66.7%), the luminal A (11%) and B (4.8%) subtypes the poorest. Of 147 patients tested for p53 mutations using the AmpliChip test, 78 variants were detected; 55 were missense. The response rate among TP53 mutated patients was 30%, significantly higher than the rate in TP53 wild-type patients (10%, P = .0032). Concordance between AmpliChip mutation status versus IHC staining was 65%, with AmpliChip status being predictive of response and IHC status being not being predictive. Conclusion: Capecitabine plus docetaxel in HER2-negative subjects, and with trastuzumab in HER2-positive subjects, provided a good response rate with fewer cycles. p53 mutational analysis using the AmpliChip p53 assay, and genomic subtyping using the PAM50 assay, were promising predictive tests of response. reference x sample
2011-03-18 | E-GEOD-22358 | biostudies-arrayexpress
Project description:Introduction: The I-SPY 1 TRIAL was designed to evaluate complete pathologic response and tumor volume change, measured by magnetic resonance imaging (MRI), stratified by molecular subtypes and link response to 3-year recurrence free survival (RFS).Methods: Eligible patients had T =3 cm and received neoadjuvant chemotherapy with AC plus optional taxane. Serial MRI, biopsy, and blood draws were conducted over the course of treatment, and a database of multiple molecular profiles was assembled.Results: A total of 221 patients were eligible for analysis: median tumor size was 6.0 cm and median age was 49 years. The I-SPY 1 TRIAL patients had tumors with aggressive biology: 45% were estrogen receptor (ER) negative, 31% Her2+; and 91% high risk by the Netherlands Cancer Institute (NKI) 70-gene profile. After a median of 3.9 years, RFS was 77%. HR/HER2 status improved predictability of RFS with the greatest difference between HR+/HER2- and triple-negative disease (hazard ratio 0.39). Wound healing signature activation, p53 mutation, and Risk of Relapse (ROR) score were highly correlated and also significantly improved the accuracy of RFS predictions when added to stage. The rate of pathologic complete response (pCR) varied considerably from a low of 0-2% (NKI low risk, luminal A) to a high of 43-61% (17q Amplified, HER2 enriched, HR-/HER2+). Both pCR and the more refined residual cancer burden (RCB) were significant predictors of RFS for all patients and even more predictive when analyzed within biomarker subsets. Good risk (NKI low, ROR-S low risk, Wound Healing quiescent, p53 wild type) signatures were associated with significantly higher 3-year RFS than poor risk expression signatures (ROR-S high risk, Wound Healing Activated, p53 mutation, NKI high risk).Conclusion: Importantly, in this set of biologically poor prognosis tumors, pCR predicts for better outcome, especially when analyzed within breast cancer subsets. Keywords: reference x sample reference x sample
2012-01-13 | E-GEOD-22226 | biostudies-arrayexpress
Project description:Introduction: The I-SPY 1 TRIAL was designed to evaluate complete pathologic response and tumor volume change, measured by magnetic resonance imaging (MRI), stratified by molecular subtypes and link response to 3-year recurrence free survival (RFS).Methods: Eligible patients had T =3 cm and received neoadjuvant chemotherapy with AC plus optional taxane. Serial MRI, biopsy, and blood draws were conducted over the course of treatment, and a database of multiple molecular profiles was assembled.Results: A total of 221 patients were eligible for analysis: median tumor size was 6.0 cm and median age was 49 years. The I-SPY 1 TRIAL patients had tumors with aggressive biology: 45% were estrogen receptor (ER) negative, 31% Her2+; and 91% high risk by the Netherlands Cancer Institute (NKI) 70-gene profile. After a median of 3.9 years, RFS was 77%. HR/HER2 status improved predictability of RFS with the greatest difference between HR+/HER2- and triple-negative disease (hazard ratio 0.39). Wound healing signature activation, p53 mutation, and Risk of Relapse (ROR) score were highly correlated and also significantly improved the accuracy of RFS predictions when added to stage. The rate of pathologic complete response (pCR) varied considerably from a low of 0-2% (NKI low risk, luminal A) to a high of 43-61% (17q Amplified, HER2 enriched, HR-/HER2+). Both pCR and the more refined residual cancer burden (RCB) were significant predictors of RFS for all patients and even more predictive when analyzed within biomarker subsets. Good risk (NKI low, ROR-S low risk, Wound Healing quiescent, p53 wild type) signatures were associated with significantly higher 3-year RFS than poor risk expression signatures (ROR-S high risk, Wound Healing Activated, p53 mutation, NKI high risk).Conclusion: Importantly, in this set of biologically poor prognosis tumors, pCR predicts for better outcome, especially when analyzed within breast cancer subsets. Keywords: reference x sample
2012-01-13 | GSE22226 | GEO
Project description:Background: Breast cancer is a heterogeneous neoplasm. Distinct subtypes of breast cancer have been defined, suggesting the existence of molecular differences contributing to their clinical outcomes. However, the molecular differences between HER2 positive and negative breast cancer tumors remain unclear. Objective: The aim of this study was to identify a gene expression profile for breast tumors based on HER2 status. Material and methods: The HER2 status was determined by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) in 54 breast tumor samples. Using Affymetrix microarray data from these breast tumors, we established the expression profiling of breast cancer based on HER2 IHC and FISH results. To validate microarray experiment data, real-time quantitative reverse transcription-PCR was performed. Results: We found significant differences between the HER2-positive and HER2-negative breast tumor samples, which included overexpression of HER2, as well as other genes located on 17q12, and genes functionally related to migration. Conclusion: Our study shows the potential of integrated genomics profiling to shed light on the molecular knowledge of HER2-positive breast tumors.
2011-12-22 | GSE29431 | GEO
Project description:Background: Breast cancer is a heterogeneous neoplasm. Distinct subtypes of breast cancer have been defined, suggesting the existence of molecular differences contributing to their clinical outcomes. However, the molecular differences between HER2 positive and negative breast cancer tumors remain unclear. Objective: The aim of this study was to identify a gene expression profile for breast tumors based on HER2 status. Material and methods: The HER2 status was determined by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) in 54 breast tumor samples. Using Affymetrix microarray data from these breast tumors, we established the expression profiling of breast cancer based on HER2 IHC and FISH results. To validate microarray experiment data, real-time quantitative reverse transcription-PCR was performed. Results: We found significant differences between the HER2-positive and HER2-negative breast tumor samples, which included overexpression of HER2, as well as other genes located on 17q12, and genes functionally related to migration. Conclusion: Our study shows the potential of integrated genomics profiling to shed light on the molecular knowledge of HER2-positive breast tumors. The tumor samples under study correspond to 54 primary breast carcinomas. They included 15 cases with a HER2 IHC3+ score with HER2 gene amplification, 13 cases with IHC2+ score with amplification and 13 without HER2 gene amplification, and 13 cases IHC0/1+ score without HER2 gene amplification. 12 samples of breast normal tissues from breast cancer patients were also included as a reference. Neither overexpression nor amplification of HER2 was observed.
2011-12-22 | E-GEOD-29431 | biostudies-arrayexpress
Project description:Purpose: Mutations in TP53 induce autoantibody immune responses in a subset of cancer patients, which have been proposed as biomarkers for early detection. Here, we investigate the association of p53 specific autoantibodies with multiple tumor subtypes and determine the association with p53 mutation status and epitope specificity. Experimental Design: IgG p53 autoantibodies (p53-AAb), were quantified in 412 serum saples using a programmable ELISA assay from patients with serous ovarian, pancreatic adenocarcinoma, and breast cancer. To determine if patients generated mutation specific autoantibodies we designed a panel of the most relevant 51 p53 point mutant proteins, to be displayed on custom programmable protein microarrays. To determine the epitope specificity we displayed 12 overlapping tiling fragments and 38 N- and C-terminal deletions spanning the length of the wild-type p53 proteins. Results: We detected p53-AAb with sensitivities of 58.8% (ovarian), 22% (pancreatic), 32% (triple negative breast cancer), and 10.2% (HER2+ breast cancer) at 94% specificity. Sera with p53-AAb contained broadly-reactive autoantibodies to 51 displayed p53 mutant proteins, demonstrating a polyclonal response to common epitopes. All p53-AAb displayed broad polyclonal immune response to both continuous and discontinuous epitopes at the N- and C-terminus as well as the DNA binding domain. Conclusion and clinical relevance: In this comprehensive analysis, mutations in tumor p53 induce strong, polyclonal autoantibodies with broadly reactive epitope specificity. The immunoreactivity was compared between 60 pancreactic ductal adenocarcinoma cases and 63 benign pancreatic disease controls against 52 unique mutant p53 and 379 human proteins that were printed on microscope slides. [Contributor] Arizona State University
2016-06-01 | E-GEOD-77949 | biostudies-arrayexpress
Project description:Platinum-based treatment (e.g., cisplatin, carboplatin) is generally the first-line chemotherapy for muscle-invasive bladder cancer (MIBC) and mediates regression in approximately 50% of the patients. The goal of this study was to improve the response rate to platinum-based treatment by developing a genomics-based method capable of classifying MIBC patients as being either likely to respond to therapy versus not likely to respond. Aberrations in TP53 and its downstream effectors play a key role in promoting bladder cancer progression, however, TP53 mutation status is neither an independent indicator of treatment response nor survival in MIBC. The hypothesis of this study was that evaluating overall TP53 function would be informative in predicting responsiveness to therapy. Towards this goal, we developed a custom-designed “TP53 functional miRGE assay”, which assesses TP53 function by simultaneously measuring the expression of 105 TP53-responsive mRNAs and miRNAs using NanoString nCounter technology. Expression profiling was performed on a panel of 34 therapy-naïve MIBC specimens with known outcomes of either being responsive or resistant. Clustering analysis identified a 7-gene subset of TP53 network genes (BAK1, BAX, BBC3, CDKN1A, MDM2, PMAIP1, TP53), which identified patients who did not respond to chemotherapy with 92.3% accuracy. Furthermore, higher TP53 function was associated more with resistant MIBCs in that these exhibited higher relative expression of TP53 target genes. Our results demonstrate a 7-gene TP53 functional assay using NanoString technology has the potential to predict patient response to platinum-based chemotherapy, and that validation of this method using a larger patient sample set is warranted.
2019-02-01 | GSE80711 | GEO
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1μg Cy3 labeled cRNA and 1 μg Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.
2008-06-13 | E-GEOD-5546 | biostudies-arrayexpress
Project description:Primary outcome(s): A concordance of HER2 status assessment between GPA and IHC/FISH
| 2654500 | ecrin-mdr-crc
Project description:Purpose: Mutations in TP53 induce autoantibody immune responses in a subset of cancer patients, which have been proposed as biomarkers for early detection. Here, we investigate the association of p53 specific autoantibodies with multiple tumor subtypes and determine the association with p53 mutation status and epitope specificity. Experimental Design: IgG p53 autoantibodies (p53-AAb), were quantified in 412 serum saples using a programmable ELISA assay from patients with serous ovarian, pancreatic adenocarcinoma, and breast cancer. To determine if patients generated mutation specific autoantibodies we designed a panel of the most relevant 51 p53 point mutant proteins, to be displayed on custom programmable protein microarrays. To determine the epitope specificity we displayed 12 overlapping tiling fragments and 38 N- and C-terminal deletions spanning the length of the wild-type p53 proteins. Results: We detected p53-AAb with sensitivities of 58.8% (ovarian), 22% (pancreatic), 32% (triple negative breast cancer), and 10.2% (HER2+ breast cancer) at 94% specificity. Sera with p53-AAb contained broadly-reactive autoantibodies to 51 displayed p53 mutant proteins, demonstrating a polyclonal response to common epitopes. All p53-AAb displayed broad polyclonal immune response to both continuous and discontinuous epitopes at the N- and C-terminus as well as the DNA binding domain. Conclusion and clinical relevance: In this comprehensive analysis, mutations in tumor p53 induce strong, polyclonal autoantibodies with broadly reactive epitope specificity.
2016-06-01 | GSE77949 | GEO