Immunohistochemical and molecular analyses of HER2 status in breast cancers are highly concordant and complementary approaches.
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ABSTRACT:
SUBMITTER: Lehmann-Che J
PROVIDER: S-EPMC3111154 | biostudies-other | 2011 May
REPOSITORIES: biostudies-other
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Project description:Hormones and growth factors accelerate cell proliferation of breast cancer cells, and these molecules are well investigated targets for drug development and application. The mechanisms of cell proliferation of breast cancers lacking estrogen receptor (ER) and HER2 have not been fully understood. The purpose of the present study is to find genes that are differentially expressed in breast cancers and that might significantly contribute to cell proliferation in these cancers. Forty tumor samples, consisting of ten each of immunohistochemically ER(+)/HER2(-), ER(+)/HER2(+), ER(-)/HER2(+), and ER(-)/HER2(-) cancer were analyzed using oligonucleotide microarrays. Both genes and tumor samples were subjected to hierarchical clustering. ER(+)/HER2(-) breast cancers and ER(-)/HER2(-) cancers tended to form a tumor cluster, but HER2 positive breast cancers were split into different tumor clusters. Significant differential expression between IHC-ER(-)/HER2(-) and other tumors was defined as having an expression level at least 2-fold higher or 2-fold lower, and analyzed by multi-step two-way ANOVA. Genes overexpressed differently in IHC-ER(-)/HER2(-) breast cancers compared to other all three types were 8 genes (FABP7, GABRP, GAL, CXCL13, CDC42EP4, C2F, FOXM1, CSDA), and underexpressed genes were nine including ITGB5, KIAA0310, MAGED2, PRSS11, SORL1, TGFB3, KRT18, CPE, BCAS1. No gene was directly related to cell proliferation such as cyclins, cyclin-dependent kinase, p53, p16, and the pRb and p21 families. We had a particular focus on a transcriptional factor E2F-5 from a list of genes overexpressed in ER negative breast cancers compared to ER positive breast cancers, and further examined. Gene amplification of E2F-5 was detected in 5/57 (8.8%) in breast cancers by FISH. No point mutation was found at the binding domain with DNA or dimerization partner of E2F-5. Immunohistochemically E2F-5 positive cancers were more frequent in ER(-)/HER2(-) cancer (14/27, 51.9%) than in other types of cancer (5/30, 16.7%) (p=0.05). E2F-5 positive cancers had higher Ki-67 labeling index (59.5%) than E2F-5 negative cancers (36.3%). E2F-5 positive cancers showed higher histological grade including metaplastic carcinoma, and worse clinical outcome with shorter disease free survival in node negative patients. In conclusion, we demonstrated that there is a population of breast cancer with overexpression of a cell cycle related transcriptional factor E2F-5. E2F-5 positive breast cancers were frequent in ER(-)/HER2(-) group with high Ki-67 labeling index, high histological grade and worse clinical outcome. Keywords: immunohistochemical phenotype
2009-03-14 | GSE6367 | GEO
Project description:Importance:The 2013/2014 American Society of Clinical Oncology and College of American Pathologists (ASCO-CAP) guidelines for HER2 testing by fluorescence in situ hybridization (FISH) designated an "equivocal" category (average HER2 copies per tumor cell ?4-6 with HER2/CEP17 ratio <2.0) to be resolved as negative or positive by assessments with alternative control probes. Approximately 4% to 12% of all invasive breast cancers are characterized as HER2-equivocal based on FISH. Objective:To evaluate the following hypotheses: (1) genetic loci used as alternative controls are heterozygously deleted in a substantial proportion of breast cancers; (2) use of these loci for assessment of HER2 by FISH leads to false-positive assessments; and (3) these HER2 false-positive breast cancer patients have outcomes that do not differ from clinical outcomes for patients with HER2-negative breast cancer. Design, Setting, and Participants:We retrospectively assessed the use of chromosome 17 p-arm and q-arm alternative control genomic sites (TP53, D17S122, SMS, RARA, TOP2A), as recommended by the 2013/2014 ASCO-CAP guidelines for HER2 testing, in patients whose data were available through Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and whose tissues were available through the Breast Cancer International Research Group clinical trials. We used data from an international cohort database of invasive breast cancers (1980 participants) and international clinical trial of adjuvant chemotherapy in invasive, node-positive breast cancer patients. Main Outcomes and Measures:The primary objectives were to (1) assess frequency of heterozygous deletions in chromosome 17 genomic sites used as FISH internal controls for evaluation of HER2 status among HER2-equivocal cancers; (2) characterize impact of using deleted sites for determination of HER2-to-internal-control-gene ratios; (3) assess HER2 protein expression in each subgroup; and (4) compare clinical outcomes for each subgroup. Results:Of the 1980 patients in METABRIC,1915 patients were fully evaluated. In addition, 100 HER2-equivocal breast cancers by FISH and 100 comparator FISH-negative breast cancers from the BCIRG-005 trial were analyzed. Heterozygous deletions, particularly in specific p-arm sites, were common in both HER2-amplified and HER2-not-amplified breast cancers. Use of alternative control probes from these regions to assess HER2 by FISH in HER2-equivocal as well as HER2-not-amplified breast cancers resulted in high rates of false-positive ratios (HER2-to-alternative control ratio ?2.0) owing to heterozygous deletions of control p-arm genomic sites used in ratio denominators. Misclassification of HER2 status was observed not only in breast cancers with ASCO-CAP equivocal status but also in breast cancers with an average of fewer than 4.0 HER2 copies per tumor cell when using alternative control probes. Conclusions and Relevance:The indiscriminate use of alternative control probes to calculate HER2 FISH ratios in HER2-equivocal breast cancers may lead to false-positive interpretations of HER2 status resulting from unrecognized heterozygous deletions in 1 or more of these alternative control genomic sites and incorrect HER2 ratio determinations.
| S-EPMC6439848 | biostudies-literature
Project description:HER2 and HER3 play key driving functions in the pathophysiology of HER2-amplified breast cancers, but this function is less well characterized in other cancers driven by HER2 amplification. This study aimed to explore the role of HER2 and HER3 signaling in other types of HER2-amplified cancer. The expression and signaling activity of HER2, HER3, and downstream pathway proteins were studied in cell panels representing HER2-amplified cancers of the breast, bladder, colon and rectal, stomach, esophagus, lung, tongue, and endometrium along with controls lacking HER2 amplification. We report that HER2-amplified cancers are addicted to HER2 across different cancer types and the depth of addiction is best linked with the expression level of HER2, but not with HER3 expression. We report that the expression and constitutive phosphorylation of HER3 are ubiquitous in HER2-amplified breast cancer cell lines, but much more variable in HER2-amplified cancer cells from other tissues. We observed the lapatinib-induced compensatory upregulation of HER3 signaling in many types of HER2-amplified cancers, although with much variability. We find that HER3 expression is essential for in vivo tumorigenic growth in some HER2-amplified tumors but not others. Importantly HER3 expression level does not correlate well with its functional importance. More biomarkers will be needed to guide the optimal use of HER3 inhibitors in HER2-amplified cancers from non-breast origin. Unlike oncogenes activated through mutational events, the activation of HER2 through overexpression represents a gradient of activities and depth of addiction and the response to inhibitors follows a similar gradient.
| S-EPMC8079373 | biostudies-literature
Project description:BackgroundAccording to 2018 ASCO/CAP guideline, HER2 FISH-equivocal breast cancers will be categorized as HER2 negative except those with IHC 3+. However, whether or not HER2 FISH-equivocal breast cancers was a heterogeneous group has not been well illustrated.Methods195 HER2 FISH-equivocal breast cancer samples were collected from 2014 to 2018. The molecular subtype was identified according to 2013 St Gallen consensus, and HER2 status was also re-determined following 2018 ASCO/CAP guideline. All samples were classified into 4 groups according to the average HER2 copy number (4.0-4.4, 4.5-4.9, 5.0-5.4, 5.5-5.9 signals/cell). The relationship between HER2 copy number and clinicopathological parameters was analyzed.Results183 (93.8%) of 195 FISH-equivocal cases were classified as luminal-like subtype, while the other 12 (6.2%) were undetermined. Following 2018 ASCO/CAP guideline, all FISH-equivocal cases were recategorized as HER2 negative. Therefore, 31(15.9%) cases were luminal A-like, 152 (77.9%) were luminal B-like (HER2 negative) and 12 (6.2%) were triple negative. The average HER2 copy number showed a positive correlation with chromosome 17 polysomy, but had no significant association with other clinicopathological parameters as well as prognosis. 17 (8.7%) patients were treated with trastuzumab, but showed no difference in prognosis with those who didn't receive targeted therapy.ConclusionsIn this study, all HER2 FISH-equivocal breast cancers were recategorized as HER2 negative according to 2018 ASCO/CAP guideline. Most of these patients were luminal B-like (HER2 negative). The average HER2 copy number had no significant association with clinicopathological parameters, as well as prognosis.
| S-EPMC8742337 | biostudies-literature
Project description:Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorithm can learn objective histologic H&E features that predict the clinical subtypes of breast cancer, as assessed by immunostaining for estrogen, progesterone, and Her2 receptors (ER/PR/Her2). Translating deep learning to this and related problems in histopathology presents a challenge due to the lack of large, well-annotated data sets, which are typically required for the algorithms to learn statistically significant discriminatory patterns. To overcome this limitation, we introduce the concept of "tissue fingerprints," which leverages large, unannotated datasets in a label-free manner to learn H&E features that can distinguish one patient from another. The hypothesis is that training the algorithm to learn the morphological differences between patients will implicitly teach it about the biologic variation between them. Following this training internship, we used the features the network learned, which we call "fingerprints," to predict ER, PR, and Her2 status in two datasets. Despite the discovery dataset being relatively small by the standards of the machine learning community (n = 939), fingerprints enabled the determination of ER, PR, and Her2 status from whole slide H&E images with 0.89 AUC (ER), 0.81 AUC (PR), and 0.79 AUC (Her2) on a large, independent test set (n = 2531). Tissue fingerprints are concise but meaningful histopathologic image representations that capture biological information and may enable machine learning algorithms that go beyond the traditional ER/PR/Her2 clinical groupings by directly predicting theragnosis.
| S-EPMC7190637 | biostudies-literature
Project description:Molecular mechanisms of lapatinib resistance in breast cancer are not well understood. The aim of this study was to correlate expression of selected proteins involved in ErbB family signaling pathways with clinical efficacy of lapatinib. Study group included 270 HER2-positive advanced breast cancer patients treated with lapatinib and capecitabine. Immunohistochemical expression of phosphorylated adenosine monophosphate-activated protein (p-AMPK), mitogen-activated protein kinase (p-MAPK), phospho (p)-p70S6K, cyclin E, phosphatase and tensin homolog were analyzed in primary breast cancer samples. The best discriminative value for progression-free survival (PFS) was established for each biomarker and subjected to multivariate analysis. At least one biomarker was determined in 199 patients. Expression of p-p70S6K was independently associated with longer (HR 0.45; 95% CI: 0.25-0.81; p = 0.009), and cyclin E with shorter PFS (HR 1.83; 95% CI: 1.06-3.14; p = 0.029). Expression of p-MAPK (HR 1.61; 95% CI 1.13-2.29; p = 0.009) and cyclin E (HR 2.99; 95% CI: 1.29-6.94; p = 0.011) was correlated with shorter, and expression of estrogen receptor (HR 0.65; 95% CI 0.43-0.98; p = 0.041) with longer overall survival. Expression of p-AMPK negatively impacted response to treatment (HR 3.31; 95% CI 1.48-7.44; p = 0.004) and disease control (HR 3.07; 95% CI 1.25-7.58; p = 0.015).the efficacy of lapatinib seems to be associated with the activity of downstream signaling pathways - AMPK/mTOR and Ras/Raf/MAPK. Further research is warranted to assess the clinical utility of these data and to determine a potential role of combining lapatinib with MAPK pathway inhibitors.
| S-EPMC4808017 | biostudies-literature
Project description:The immunohistochemical (IHC) staining of the human epidermal growth factor receptor 2 (HER2) biomarker is widely practiced in breast tissue analysis, preclinical studies, and diagnostic decisions, guiding cancer treatment and investigation of pathogenesis. HER2 staining demands laborious tissue treatment and chemical processing performed by a histotechnologist, which typically takes one day to prepare in a laboratory, increasing analysis time and associated costs. Here, we describe a deep learning-based virtual HER2 IHC staining method using a conditional generative adversarial network that is trained to rapidly transform autofluorescence microscopic images of unlabeled/label-free breast tissue sections into bright-field equivalent microscopic images, matching the standard HER2 IHC staining that is chemically performed on the same tissue sections. The efficacy of this virtual HER2 staining framework was demonstrated by quantitative analysis, in which three board-certified breast pathologists blindly graded the HER2 scores of virtually stained and immunohistochemically stained HER2 whole slide images (WSIs) to reveal that the HER2 scores determined by inspecting virtual IHC images are as accurate as their immunohistochemically stained counterparts. A second quantitative blinded study performed by the same diagnosticians further revealed that the virtually stained HER2 images exhibit a comparable staining quality in the level of nuclear detail, membrane clearness, and absence of staining artifacts with respect to their immunohistochemically stained counterparts. This virtual HER2 staining framework bypasses the costly, laborious, and time-consuming IHC staining procedures in laboratory and can be extended to other types of biomarkers to accelerate the IHC tissue staining used in life sciences and biomedical workflow.
| S-EPMC10521710 | biostudies-literature
Project description:Intrinsic resistance to anti-HER2 therapy in breast cancer remains an obstacle in the clinic, limiting its efficacy. However, the biological basis for intrinsic resistance is poorly understood. Here we performed a CRISPR/Cas9-mediated loss-of-function genetic profiling and identified TALDO1, which encodes the rate-limiting transaldolase (TA) enzyme in the non-oxidative pentose phosphate pathway, as essential for cellular survival following pharmacological HER2 blockade. Suppression of TA increases cell susceptibility to HER2 inhibition in two intrinsically resistant breast cancer cell lines with HER2 amplification. Mechanistically, TA depletion combined with HER2 inhibition significantly reduces cellular NADPH levels, resulting in excessive ROS production and deficient lipid and nucleotide synthesis. Importantly, higher TA expression correlates with poor response to HER2 inhibition in a breast cancer patient cohort. Together, these results pinpoint TA as a novel metabolic enzyme possessing synthetic lethality with HER2 inhibition that can potentially be exploited as a biomarker or target for combination therapy.
| S-EPMC6189078 | biostudies-literature
Project description:Inhibition of HER2 in HER2-amplified breast cancer has been remarkably successful clinically, as demonstrated by the efficacy of HER-kinase inhibitors and HER2-antibody treatments. Whilst resistance to HER2 inhibition is common in the metastatic setting, the specific programs downstream of HER2 driving resistance are not established. Through genomic profiling of 733 HER2-amplified breast cancers, we identify enrichment of somatic alterations that promote MEK/ERK signaling in metastatic tumors with shortened progression-free survival on anti-HER2 therapy. These mutations, including NF1 loss and ERBB2 activating mutations, are sufficient to mediate resistance to FDA-approved HER2 kinase inhibitors including tucatinib and neratinib. Moreover, resistant tumors lose AKT dependence while undergoing a dramatic sensitization to MEK/ERK inhibition. Mechanistically, this driver pathway switch is a result of MEK-dependent activation of CDK2 kinase. These results establish genetic activation of MAPK as a recurrent mechanism of anti-HER2 therapy resistance that may be effectively combated with MEK/ERK inhibitors.
| S-EPMC8602441 | biostudies-literature
Project description:It is well documented that human epidermal growth factor receptor 2 (HER2) overexpression/amplification is associated with poor survival in breast cancer patients. However, it is largely unknown whether HER2 somatic mutations are associated with survival in HER2-negative breast cancer patients. Here, we identified HER2 somatic mutations in tumors from 1348 unselected breast cancer patients by sequencing the entire HER2 coding region. All of these mutations were tested for in corresponding blood samples to determine whether they were somatic or germline mutations. We further investigated the associations between HER2 somatic mutations and recurrence-free survival and distant recurrence-free survival in this cohort of patients. We found that 27 of 1348 (2.0%) of these patients carried a HER2 somatic mutation. In vitro experiments indicated that some of the novel mutations and those with unknown functions increased HER2 activity. HER2 status was available for 1306 patients, and the HER2 somatic mutation rates in HER2-positive (n = 353) and HER2-negative breast cancers (n = 953) were 1.4% and 2.3%, respectively. Among the HER2-negative patients, those with a HER2 somatic mutation had a significantly worse recurrence-free survival (unadjusted hazard ratio = 2.67; 95% confidence interval, 1.25-5.72, P = 0.002) and distant recurrence-free survival (unadjusted hazard ratio = 2.50; 95% confidence interval, 1.10-5.68, P = 0.004) than those with wild-type HER2. Taken together, our findings suggested that HER2 somatic mutations occur at a higher frequency in HER2-negative breast cancer, and HER2-negative breast cancer patients with these mutations have poor survival. Therefore, HER2-negative patients with a HER2 somatic mutation are potentially good candidates for HER2-targeted therapy.
| S-EPMC5406600 | biostudies-literature