scholarly journals Mismatch Repair Protein Loss as a Prognostic and Predictive Biomarker in Breast Cancers Regardless of Microsatellite Instability

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Nicola Fusco ◽  
Gianluca Lopez ◽  
Chiara Corti ◽  
Chiara Pesenti ◽  
Patrizia Colapietro ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Microsatellite Instability ◽  
Mismatch Repair ◽  
Statistical Tests ◽  
Immune Checkpoint Blockade ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Protein Loss ◽  
Clinical Value ◽  
Msi Analysis

Abstract Background Breast cancers that harbor mismatch-repair (MMR) deficiency and/or microsatellite instability (MSI) might be sensitive to immune checkpoint blockade, but there are currently no specific guidelines for assessing MMR status in breast cancer. Here, we sought to define the clinical value of MMR immunohistochemistry (IHC) and MSI analysis in breast cancers. Methods We subjected 444 breast cancers to MMR IHC and MSI analysis. Cases were classified as MMR-proficient (pMMR), MMR-deficient (dMMR), and MMR-heterogeneous (hMMR) based on the loss of immunoreactivity; MSI was defined by instability in the five indicators recommended by the National Cancer Institute for endometrial and colorectal cancers. Correlation of MMR status with patients’ survival was assessed using the Kaplan-Meier estimator. Statistical tests were two-sided. Results Loss of MMR proteins was homogeneous (dMMR) in 75 patients (17%) and heterogeneous (hMMR) in 55 (12%). Among luminal breast cancers, there were similar frequencies of dMMR and hMMR tumors. Overall, the rate of discrepancy between IHC and MSI analysis was high (91%). Women with Luminal B-like dMMR carcinomas (n = 44) showed shorter overall survival (median = 77 months, range = 0–115 months) than those with pMMR (n = 205) or hMMR (n = 35) tumors (median = 84 months, range = 0–127 months) (P = .008). On the contrary, patients with estrogen receptor-negative breast cancers treated with chemotherapy lived longer in cases of dMMR (n = 9) than pMMR (n = 33) or hMMR (n = 7) tumors, with 87 months of median survival (range = 73–123 months) for the former compared with 79 months (range = 8–113 months) for the latter two categories (P < .001). Conclusions Immunohistochemistry and MSI are not interchangeable tests in breast carcinomas. MMR protein loss is a more common event than MSI and shows intra-tumor heterogeneity. MMR IHC allows the identification of clinically relevant subclasses of breast cancer patients, provided that multiple areas of the tumor are analyzed.

Detection of subthreshold microsatellite instability in breast cancer: An ongoing investigation.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1089-1089
Author(s):  
Joshua Z. Drago ◽  
Alicia Latham ◽  
Shanu Modi ◽  
Pedram Razavi ◽  
Zsofia Kinga Stadler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Microsatellite Instability ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Clinical Care ◽  
Progression Free Survival ◽  
Immune Checkpoint Blockade ◽  
Breast Cancer Patients ◽  
Histologic Subtype ◽  
Mmr Genes

1089 Background: Microsatellite instability (MSI) and mismatch repair deficiency (MMRd) can occur sporadically in solid tumors across histologic subtype and predict clinical response to immune checkpoint blockade (ICB). MSIsensor uses next generation sequencing to report the percentage of unstable microsatellites in a given tumor sample as a score. While scores of ≥10 and < 3 have excellent sensitivity/specificity for MSI/MMRd, intermediate scores of 3-10 are of unknown clinical significance, and may include patients with MSI-like genomic signatures who would be overlooked by historical assays. Methods: MSIsensor testing was performed on primary or metastatic tumor specimens from 2,371 patients with breast cancer. Scores of 3-10 were considered MSI-Indeterminate (MSI-I). Concurrent somatic mutations were determined using the MSK-IMPACT assay. Results: Of the 2,371 patients tested, 147 were found to have MSI-I tumors. Ninety-nine (67.3%) were metastatic specimens, and 48 (32.7%) were primary specimens. Of the MSI-I patients, 64 (43.5%) were estrogen receptor positive, 57 (38.8%) were triple negative, and 24 (16.3%) were HER-2 amplified. Somatic TP53 mutations were detected in 109 (74.1%) MSI-I patients, including 54 (94.7%) triple negative patients. Fourteen MSI-I patients were found to have somatic mutations in MMR genes ( MLH1, MSH2, MSH6, PMS2 or EPCAM), but no germline mutations were found. Of the 99 patients with MSI-I metastatic disease, 15 received ICB as part of their clinical care, exhibiting a median progression-free-survival (PFS) of 3 months. Of the 4 patients who demonstrated a PFS of > 6 months on ICB, 2 were found to have somatic mutations in MMR genes. Conclusions: We introduce a subpopulation of breast cancer patients whose tumors exhibit genomic signs of microsatellite instability without meeting the classic criteria for MSI/MMRd as previously defined in colon and endometrial cancers. A subset of these patients may exhibit the properties of MSI/MMRd at the epigenetic and protein-expression levels, and thus potentially benefit from ICB.

scholarly journals PTEN Expression as a Complementary Biomarker for Mismatch Repair Testing in Breast Cancer

2020 ◽  
Vol 21 (4) ◽  
pp. 1461 ◽  
Author(s):  
Gianluca Lopez ◽  
Marianna Noale ◽  
Chiara Corti ◽  
Gabriella Gaudioso ◽  
Elham Sajjadi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mismatch Repair ◽  
Expression Analysis ◽  
Tumor Heterogeneity ◽  
Diagnostic Algorithm ◽  
Tissue Microarrays ◽  
Pten Expression ◽  
Breast Cancers ◽  
Protein Loss ◽  
Tensin Homolog

Mismatch repair (MMR) analysis in breast cancer may help to inform immunotherapy decisions but it lacks breast-specific guidelines. Unlike in other neoplasms, MMR protein loss shows intra-tumor heterogeneity and it is not mirrored by microsatellite instability in the breast. Additional biomarkers can improve MMR clinical testing. Phosphatase and tensin homolog (PTEN) inactivation is an early oncogenic event that is associated with MMR deficiency (dMMR) in several tumors. Here, we sought to characterize the diagnostic utility of PTEN expression analysis for MMR status assessment in breast cancer. A total of 608 breast cancers were profiled for their MMR and PTEN status. Proteins expression and distribution were analyzed by immunohistochemistry (IHC) on tissue microarrays and confirmed on full sections; PTEN copy number alterations were detected using a real-time PCR assay. Overall, 78 (12.8%) cases were MMR-heterogeneous (hMMR), while all patterns of PTEN expression showed no intra-tumor heterogeneity. Wild-type PTEN expression was observed in 15 (18.5%) dMMR tumors (p < 0.0001). Survival analyses revealed significant correlations between MMR-proficient (pMMR), PTEN expression, and a better outcome. The positive predictive value of PTEN-retained status for pMMR ranged from 94.6% in estrogen receptor (ER)+/HER2- tumors to 100% in HER2-amplified and ER-/HER2- cases. We propose a novel diagnostic algorithm where PTEN expression analysis can be employed to identify pMMR breast cancers.

scholarly journals Quantitative Mammographic Density Measurements and Molecular Subtypes in Chinese Women with Breast Cancer

2020 ◽  
Author(s):  
Yuan Tian ◽  
Jennifer L Guida ◽  
Hela Koka ◽  
Er-Ni Li ◽  
Bin Zhu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Mammographic Density ◽  
Chinese Women ◽  
Statistical Tests ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Luminal A ◽  
Cancer Subtypes ◽  
Luminal B

Abstract Background Studies investigating associations between mammographic density (MD) and breast cancer subtypes have generated mixed results. We previously showed that having extremely dense breasts was associated with the HER2-enriched subtype in Chinese breast cancer patients. Methods In this study, we re-evaluated the MD-subtype association in 1,549 Chinese breast cancer patients, using VolparaDensity software to obtain quantitative MD measures. All statistical tests were two-sided. Results Compared to women with luminal A tumors, women with luminal B/HER2- (odds ratio [OR]=1.20, 95% confidence interval [CI]: 1.04-1.38, p = 0.01), luminal B/HER2 + (OR = 1.22, 95% CI: 1.03-1.46, p = 0.03), and HER2-enriched tumors (OR = 1.30, 95% CI: 1.06-1.59, p = 0.01) had higher fibroglandular dense volume. These associations were stronger in patients with smaller tumors (&lt;2cm). In contrast, the triple negative subtype was associated with lower non-dense volume (OR = 0.82, 95% CI: 0.68-0.99, p = 0.04), and the association was only seen among older women (&gt;50 years old). Conclusion Although biological mechanisms remain to be investigated, the associations for the HER2-enriched and luminal B subtypes with increasing MD may partially explain the higher prevalence of luminal B and HER2+ breast cancers previously reported in Asian women.

scholarly journals Survival outcomes are associated with genomic instability in luminal breast cancers

2020 ◽  
Author(s):  
Lydia King ◽  
Andrew Flaus ◽  
Aaron Golden
Keyword(s):  
Breast Cancer ◽  
Genomic Instability ◽  
Statistical Tests ◽  
Molecular Taxonomy ◽  
Therapeutic Interventions ◽  
Survival Outcomes ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Luminal A ◽  
Grade 3

AbstractBreast cancer is the leading cause of cancer related death among women. Breast cancers are generally diagnosed and treated based on clinical and histopathological features, along with subtype classification determined by the Prosigna Breast Cancer Prognostic Gene Signature Assay (also known as PAM50). Currently the copy number alteration (CNA) landscape of the tumour is not considered. We set out to examine the role of genomic instability (GI) in breast cancer survival since CNAs reflect GI and correlate with survival in other cancers. We focussed on the 70% of breast cancers classified as luminal and carried out a comprehensive survival and association analysis using Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data to determine whether CNA burden quartiles derived from absolute CNA counts are associated with survival. Luminal A and B patients were stratified by PAM50 subtype and tumour grade and then tested for association with CNA burden using multiple statistical tests. Analysis revealed that patients diagnosed with luminal A grade 3 breast cancer have a CNA landscape associated with disease specific survival, suggesting that these patients could be classified as at-risk. Furthermore, luminal A grade 3 cases largely occupy a region of stratification based on gene expression at the boundary where luminal A and luminal B cases overlap. We conclude that GI reflected by absolute CNA score is a statistically robust prognostic factor for survival in luminal A grade 3 breast cancer. Therefore, luminal A grade 3 breast cancer patients in CNA burden quartiles 3 or 4 may benefit from more aggressive therapy. This demonstrates how individual genomic landscapes can facilitate personalisation of therapeutic interventions to optimise survival outcomes.

scholarly journals Microsatellite instability in Japanese female patients with triple-negative breast cancer

Breast Cancer ◽  
2020 ◽  
Vol 27 (3) ◽  
pp. 490-498 ◽  
Author(s):  
Kanako Kurata ◽  
Makoto Kubo ◽  
Masaya Kai ◽  
Hitomi Mori ◽  
Hitomi Kawaji ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Microsatellite Instability ◽  
Triple Negative ◽  
Cell Cancer ◽  
Low Frequency ◽  
Tumor Infiltrating Lymphocytes ◽  
Metastatic Tumor ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Ki 67

Abstract Background It is important to identify biomarkers for triple-negative breast cancers (TNBCs). Recently, pembrolizumab, an immune checkpoint inhibitor (ICI) for programmed cell death 1 (PD-1), was approved as a treatment strategy for unresectable or metastatic tumor with high-frequency microsatellite instability (MSI-H) or mismatch repair deficiency, such as malignant melanoma, non-small cell lung cancer, renal cell cancer and urothelial cancer. In addition, results from clinical trials suggested that ICI was a promising treatment for TNBCs with accumulated mutations. However, the frequency of MSI in Japanese TNBCs still remains unclear. We aimed to analyze the presence of MSI-H in TNBCs as a biomarker for ICI therapy. Methods In this study, we retrospectively evaluated the MSI of 228 TNBCs using an innovative method, MSI Analysis System Version 1.2 (Promega), consisting of 5 microsatellite markers: BAT-26, NR-21, BAT-25, MONO-27 and NR-24 without a normal tissue control. Results Among 228 tumors, 222 (97.4%) were microsatellite stable, 4 (1.7%) low-frequency MSI and 2 (0.9%) MSI-H, respectively. Two MSI-H tumors were potentially aggressive pathologically as indicated by nuclear grade 3 and high Ki-67 (> 30%), and were classified as basal-like and non-BRCA-like, but were not consistent regarding tumor-infiltrating lymphocytes, CD8 and PD-L1 expression. Conclusions Although we found that MSI-H was uncommon (0.9%) in TNBCs, potential targets for ICIs exist in TNBCs. Therefore, MSI-H breast cancer patients should be picked up using not only conventional methods but also platforms for comprehensive genomic profiling.

scholarly journals Mismatch repair protein loss in breast cancer: clinicopathological associations in a large British Columbia cohort

2019 ◽  
Vol 179 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Angela S. Cheng ◽  
Samuel C. Y. Leung ◽  
Dongxia Gao ◽  
Samantha Burugu ◽  
Meenakshi Anurag ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mismatch Repair ◽  
Checkpoint Inhibitors ◽  
Receptor Expression ◽  
Nuclear Staining ◽  
Breast Cancer Patients ◽  
Protein Loss ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Mmr Deficiency

Abstract Purpose Alterations to mismatch repair (MMR) pathways are a known cause of cancer, particularly colorectal and endometrial carcinomas. Recently, checkpoint inhibitors have been approved for use in MMR-deficient cancers of any type (Prasad et al. in JAMA Oncol 4:157–158, 2018). Functional studies in breast cancer have shown associations between MMR loss, resistance to aromatase inhibitors and sensitivity to palbociclib (Haricharan et al. in Cancer Discov 7:1168–1183, 2017). Herein, we investigate the clinical meaning of MMR deficiency in breast cancer by immunohistochemical assessment of MSH2, MSH6, MLH1 and PMS2 on a large series of breast cancers linked to detailed biomarker and long-term outcome data. Methods Cases were classified as MMR intact when all four markers expressed nuclear reactivity, but MMR-deficient when at least one of the four biomarkers displayed loss of nuclear staining in the presence of positive internal stromal controls on the tissue microarray core. Results Among the 1635 cases with interpretable staining, we identified 31 (1.9%) as MMR-deficient. In our cohort, MMR deficiency was present across all major breast cancer subtypes, and was associated with high-grade, low-progesterone receptor expression and high tumor-infiltrating lymphocyte counts. MMR deficiency is significantly associated with inferior overall (HR 2.29, 95% CI 1.02–5.17, p = 0.040) and disease-specific survival (HR 2.71, 95% CI 1.00–7.35, p = 0.042) in the 431 estrogen receptor-positive patients who were uniformly treated with tamoxifen as their sole adjuvant systemic therapy. Conclusion Overall, this study supports the concept that breast cancer patients with MMR deficiency as assessed by immunohistochemistry may be good candidates for alternative treatment approaches such as immune checkpoint or CDK4 inhibitors.

Prognostic Role of Hedgehog-GLI1 Signaling Pathway in Aggressive and Metastatic Breast Cancers

2020 ◽  
Vol 21 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Prasuja Rokkam ◽  
Shailender Gugalavath ◽  
Deepak Kakara Gift Kumar ◽  
Rahul Kumar Vempati ◽  
Rama Rao Malla
Keyword(s):  
Breast Cancer ◽  
Signaling Pathway ◽  
Neural Development ◽  
Splice Variants ◽  
Metastatic Breast ◽  
Basic Function ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Aberrant Expression ◽  
Cellular Processes

Glioma-associated oncogene homolog 1 (GLI1) is reported as an amplified gene in human glioblastoma cells. It is a krupple like transcription factor, belonging to the zinc finger family. The basic function of GLI1 is normal neural development at various stages of human. The GLI1 gene was first mapped on the chromosome sub-bands 12q13.3-14.1. Further, single nucleotide polymorphism is mostly observed in translating a region of 5’ and 3’- UTR of GLI1 gene in addition to two post-transcriptional splice variants, GLIΔN and tGLI. Additionally, it also regulates a plethora of gene which mediates crucial cellular processes like proliferation, differentiation, oncogenesis, EMT, and metastasis. It also regulates tumor tolerance, chemoresistance, and radioresistance. Aberrant expression of GLI1 predicts the poor survival of breast cancer patients. GLI1 is an essential mediator of the SHH signaling pathway regulating self-renewal of stem cells, angiogenesis, and expression of FOXS1, CYR61. GLI1 mediated HH pathway can induce apoptosis. Hence, GLI1 can be a future diagnostic, prognostic marker, and as well as a potent target of therapeutics in breast cancer.

scholarly journals Iodine Map Radiomics in Breast Cancer: Prediction of Metastatic Status

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2431
Author(s):  
Lukas Lenga ◽  
Simon Bernatz ◽  
Simon S. Martin ◽  
Christian Booz ◽  
Christine Solbach ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast ◽  
Principal Component ◽  
Validation Dataset ◽  
Dual Energy Ct ◽  
Cancer Tissue ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Iodine Map ◽  
Iodine Maps

Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.

scholarly journals Human Plasma Metabolomics for Biomarker Discovery: Targeting the Molecular Subtypes in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 147
Author(s):  
Leticia Díaz-Beltrán ◽  
Carmen González-Olmedo ◽  
Natalia Luque-Caro ◽  
Caridad Díaz ◽  
Ariadna Martín-Blázquez ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Biomarker Discovery ◽  
Molecular Subtypes ◽  
Breast Cancer Subtype ◽  
P Value ◽  
Plasma Samples ◽  
Breast Cancer Patients ◽  
Clinical Value ◽  
Molecular Phenotypes

Purpose: The aim of this study is to identify differential metabolomic signatures in plasma samples of distinct subtypes of breast cancer patients that could be used in clinical practice as diagnostic biomarkers for these molecular phenotypes and to provide a more individualized and accurate therapeutic procedure. Methods: Untargeted LC-HRMS metabolomics approach in positive and negative electrospray ionization mode was used to analyze plasma samples from LA, LB, HER2+ and TN breast cancer patients and healthy controls in order to determine specific metabolomic profiles through univariate and multivariate statistical data analysis. Results: We tentatively identified altered metabolites displaying concentration variations among the four breast cancer molecular subtypes. We found a biomarker panel of 5 candidates in LA, 7 in LB, 5 in HER2 and 3 in TN that were able to discriminate each breast cancer subtype with a false discovery range corrected p-value < 0.05 and a fold-change cutoff value > 1.3. The model clinical value was evaluated with the AUROC, providing diagnostic capacities above 0.85. Conclusion: Our study identifies metabolic profiling differences in molecular phenotypes of breast cancer. This may represent a key step towards therapy improvement in personalized medicine and prioritization of tailored therapeutic intervention strategies.

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