Paraffin-embedded Breast Cancer Tissues Research Articles

InDEL instability in two different tumoral tissues and its forensic significance.

There may be cases where malignant tumor samples can be used for forensic DNA profiling studies. STRs are the first systems preferred in forensic science laboratories for identification purposes. However, genetic instability in tumoral tissues causes STR polymorphism to change, leading to erroneous results. On the other hand, insertion/deletion polymorphism (InDels) are used as genetic markers in forensic science, as they have features that make both STR and SNPs preferable. Although previous studies approved that STR instability is observed in many different tumors, there are only a few studies that have displayed the instability of InDels in tumoral tissues before. In this study, it was aimed to determine whether instability is observed in formalin-fixed paraffin-embedded breast and thyroid tumoral tissues at 36plex InDel Panel. A total of 47 cases, 26 of which were diagnosed as breast cancer and 21 as thyroid cancer, were included in the study. In 21 of 26 (80.76%) breast cancers mutational changes were observed, however only 6 of 21 (28.57%) thyroid carcinoma cases displayed instability.Moreover, in these six cases, mutations were detected at only 1 or 2 loci. The most common change in both tissues was loss of heterozygosity. These findings suggest that paraffin embedded tissues of thyroid tumor can be used in cases of forensic genetic identification, however paraffin embedded breast cancer tissues should be examined with care. In conclusion, low InDel mutation rates compared to STR instability, make InDel analysis from paraffin blocks suitable for forensic genetic identification. However, researchers should keep in mind that there may be differences between the profiles of the tumoral tissues taken as reference and the actual case. In addition, by incorporating additional markers such as SNPs and microhaplotypes with low mutation rates into the study alongside Indels, researchers can significantly enhance the discrimination power in identification processes.

Calreticulin, a potential coregulator of immune checkpoints and biomarker associated with tumor microenvironment and clinical prognostic significance in breast invasive carcinoma.

As a promising immune checkpoint of immunogenic cell death (ICD) and multifunctional calcium-binding molecular chaperone, calreticulin (CALR) has been attracting increasing attention. CALR mainly locates in cellular endoplasmic reticulum and significantly affects cell proliferation, invasion, induction of apoptosis, and angiogenesis in breast invasive carcinoma (BRCA). CALR overexpression might be correlated with a worse outcome. Nonetheless, it remains obscure how CALR correlates with immune infiltration and survival prognosis of BRCA. In this study, we investigated CALR expression utilizing RNAseq data from the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx) database. The prognostic value of CALR was analyzed using clinical survival data. Enrichment analysis was conducted using the R package "clusterProfiler." We downloaded the immune cell infiltration score of TCGA samples from published articles and online databases and performed a correlation analysis between immune cell infiltration levels and CALR expression. We further assessed the association between CALR and immunomodulators. Moreover, we also evaluated the expression of CALR in 100 formalin-fixed and paraffin-embedded breast cancer and adjacent normal breast tissue specimens. Our results found that CALR was highly expressed in BRCA, and CALR expression levels differed in pathological stages, T stages, and N stages. Besides, these results suggested that CALR overexpression may have adverse effects on the progression-free interval (PFI) and disease-free interval (DFI), which may be related to tumor proliferation, invasion, and metastasis, leading to tumor deterioration. Meanwhile, immune cell infiltration analysis revealed a correlation between the expression of CALR and the number of neutrophils and dendritic cells, suggesting that CALR was highly correlated with many immunomodulators in BRCA. Our results provide potential biomarkers of CALR in BRCA. CALR may interact synergistically with other immunomodulators to regulate the immune microenvironment, which could be utilized to develop new immunotherapy drugs.

Performance of a RAD51-based functional HRD test on paraffin-embedded breast cancer tissue

PurposeBRCA-deficient breast cancers (BC) are highly sensitive to platinum-based chemotherapy and PARP inhibitors due to their deficiency in the homologous recombination (HR) pathway. However, HR deficiency (HRD) extends beyond BRCA-associated BC, highlighting the need for a sensitive method to enrich for HRD tumors in an alternative way. A promising approach is the use of functional HRD tests which evaluate the HR capability of tumor cells by measuring RAD51 protein accumulation at DNA damage sites. This study aims to evaluate the performance of a functional RAD51-based HRD test for the identification of HRD BC.MethodsThe functional HR status of 63 diagnostic formalin-fixed paraffin-embedded (FFPE) BC samples was determined by applying the RAD51-FFPE test. Samples were screened for the presence of (epi)genetic defects in HR and matching tumor samples were analyzed with the RECAP test, which requires ex vivo irradiated fresh tumor tissue on the premise that the HRD status as determined by the RECAP test faithfully represented the functional HR status.ResultsThe RAD51-FFPE test identified 23 (37%) of the tumors as HRD, including three tumors with pathogenic variants in BRCA1/2. The RAD51-FFPE test showed a sensitivity of 88% and a specificity of 76% in determining the HR-class as defined by the RECAP test.ConclusionGiven its high sensitivity and compatibility with FFPE samples, the RAD51-FFPE test holds great potential to enrich for HRD tumors, including those associated with BRCA-deficiency. This potential extends to situations where DNA-based testing may be challenging or not easily accessible in routine clinical practice. This is particularly important considering the potential implications for treatment decisions and patient stratification.

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets.

Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typical analysis pipeline in using IR imaging data for chemical pathology often involves iterative processes of segmentation, evaluation, and analysis that necessitate rapid data exploration. Here, we present a fast, reliable, and intuitive method based on a phasor representation of spectra and discuss its unique applicability for IR imaging data. We simulate different features extant in IR spectra and discuss their influence on the phasor waveforms; similarly, we undertake IR image analysis in the transform space to understand spectral similarity and variance. We demonstrate the potential of phasor analysis for biomedical tissue imaging using a variety of samples, using fresh frozen surgical prostate resections and formalin-fixed paraffin-embedded breast cancer tissue microarray samples as model systems that span common histopathology practice. To demonstrate further generalizability of this approach, we apply the method to data from different experimental conditions─including standard (5.5 μm × 5.5 μm pixel size) and high-definition (1.1 μm × 1.1 μm pixel size) Fourier transform IR (FTIR) spectroscopic imaging using transmission and transflection modes. Quantitative segmentation results from our approach are compared to previous studies, showing good agreement and quick visualization. The presented method is rapid, easy to use, and highly capable of deciphering compositional differences, presenting a convenient tool for exploratory analysis of IR imaging data.

Abstract 5357: Estrogen receptor gene expression prediction from H&E-stained whole slide images

Abstract Gene expression profiling (GEP) represents an important approach to inform breast cancer treatment. However, access to GEP involves challenges associated with cost, tissue transportation, and turn around time. In this work, we explore the prediction of estrogen receptor gene (ESR1) expression directly from images of hematoxylin and eosin (H&E) stained, formalin-fixed paraffin-embedded (FFPE) breast cancer tissue. Since H&E staining is a fast and inexpensive component of the standard tissue preparation in pathology, this approach is tissue preserving and requires no additional tissue processing. Our method uses a deep multiple instance learning approach to process cropped image patches from whole-slide images (WSI) into a numeric embedding vector summarizing the information in each patch. A gated attention mechanism then aggregates these embeddings into a single prediction for the WSI. We train and tune the model on a site-based split of The Cancer Genome Atlas (TCGA) BRCA dataset, and evaluate it on both a heldout split of TCGA (independent sites) and a separate dataset from a tertiary teaching hospital (TTH). All splits of TCGA have ESR1 value, immunohistochemistry (IHC) estrogen receptor (ER) status, and limited clinical outcome data. The TTH dataset has IHC-based ER status and clinical outcome, but not ESR1 expression. On the TCGA heldout test split, our model’s root mean square error (RMSE) for predicting normalized gene expression counts (TPM) was 2.90 [95% CI: 2.57, 3.23], and the Pearson correlation was 0.57 [95%CI; 0.46, 0.67]. For predicting IHC-based ER status on the same TCGA split, this weakly-supervised ESR1-predicting model had an area under the receiver-operator curve (AUROC) of 0.81 [0.74, 0.87]. This was comparable to a strongly-supervised method directly predicting ER status (AUROC: 0.85 [0.77, 0.92]). Lastly, when evaluated for association with patient outcomes (progression-free interval; PFI) using the independent TTH dataset, this ESR1-predicting model had a concordance index (c-index) of 0.59 [0.52, 0.65]. For comparison, the c-index for PFI using the IHC-based ER status for these cases was 0.61 [0.54, 0.66]. This work further demonstrates the potential to infer gene expression from H&E stained images in a manner that shows meaningful associations with clinical variables. Because obtaining H&E stained images is substantially easier and faster than genetic testing, the capability to derive molecular genetic information from these images may increase access to this type of information for patient risk stratification and provide research insights into molecular-morphological associations. Future work incorporating more comprehensive sets of genes remains a valuable next step. Citation Format: Anvita A. Srinivas, Ronnachai Jaroensri, Ellery Wulczyn, James H. Wren, Elaine E. Thompson, Niels Olson, Fabien Beckers, Melissa Miao, Yun Liu, Cameron Chen, David F. Steiner. Estrogen receptor gene expression prediction from H&E-stained whole slide images. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5357.

Abstract P5-02-53: P95HER2 Expression in HER2-Positive Breast Cancer

Abstract Background: -HER2-positive breast cancer subtype accounted for around 15-20% of all breast cancer. -The introduction of HER2-targeted therapy such as trastuzumab and pertuzumab has remarkably increased the patients’ prognosis of HER2-positive breast cancer. -However, resistance exists due to impaired drug binding to HER2 receptor and constitutive activation of HER2 downstream signaling pathways. -P95HER2 isoform is a truncated form of HER2 that retains the C terminal domain but lacks an N terminal trastuzumab binding site, leading to trastuzumab resistance in HER2-positive breast cancer. -A new P95HER2 antibody is developed to target the extracellular domain of p95HER2 in formalin-fixed paraffin-embedded (FFPE) HER2-positive breast cancer tissues by using hematoxylin and eosin (HE) staining method. Objectives: To evaluate the expression of P95HER2 and its clinicopathological characteristics in HER2-positive breast cancer. Methods: We assessed 68 HER2-positive patients (IHC 3+ or IHC 2+/in situ hybridization [ISH]+) from Fudan University Shanghai Cancer Center (FUSCC) who underwent breast cancer surgery and were treated with adjuvant chemotherapy (taxane or anthracycline or combination) plus trastuzumab from 2014 to 2016. P95HER2 HE antibody is provided by Simcere Pharma. In this study, we compared 27 patients with primary trastuzumab resistance with 41 non-relapse breast cancer patients. 14 patients have not received trastuzumab targeted therapy. P95HER2 staining of either 1+, 2+ or 3+ observed in any tumor area in HE slides was considered to be P95 HER2 positive. Chi-square test was used to determine the relationship between P95HER2 expression of patients’ characteristics. The main outcome measures were disease free-survival (DFS), distant disease-free survival (DDFS) and overall survival (OS) by using log-rank test. Univariable and multivariable Cox regression analyses were used to identify independent factors related to prognosis. Results: From 2014 to 2016, we assessed the expression of P95HER2 expression in 68 HER2 positive breast cancer patients from FUSCC. Median follow-up was 45 months. In our study, 19 (27.9%) were P95HER2 positive. P95HER2 positive expression rate is higher in premenopausal patients than in postmenopausal patients (68.4% vs 38.8%, P= 0.028). Univariable analysis showed that higher T-stage (P= 0.018), higher N-stage (P= 0.001) and P95HER2 positive expression (P= 0.033) were associated with worse DDFS. Multivariable analysis showed that higher T-stage (hazard ratio, 6.019; 95% CI, 1.205-30.078; P= 0.029) and P95HER2 positive (hazard ratio, 2.349; 95%CI, 1.03-5.358; P= 0.042) independently predicted worse DDFS. P95HER2 positive was significantly associated with shorter 5-year DDFS (42.1% vs 67.6%, P= 0.028), but has no significant difference in DFS (36.8% vs 59.5%, P= 0.072) and OS (74.8% vs 81.2%, P= 0.685). Conclusions: P95HER2 positive was found more in premenopausal patients and was associated with a higher metastasis rate, indicating that P95HER2 expression tends to be a more aggressive isoform type of HER2-positive breast cancer. P95HER2 may serve as a therapeutic target for anti-HER2 therapy. Citation Format: Chih Wan Goh, Liyi Zhang, Wei-Ru Chi, Bingqiu Xiu, Jiajian Chen, Wenqing Yang, Chunxia Ao, Jianxing Tang, Jingyan Xue, Yayun Chi, Jiong Wu. P95HER2 Expression in HER2-Positive Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-02-53.

Expression of substance P, neurokinin 1 receptor, Ki-67 and pyruvate kinase M2 in hormone receptor negative breast cancer and evaluation of impact on overall survival

BackgroundChronic inflammation is a hallmark of cancer, and it can be stimulated by many factors. Substance P (SP), through binding to neurokinin 1 receptor (NK1R), and pyruvate kinase M2 (PKM2) play critical roles in cancer development and progression via modulating the tumor microenvironment. This study aimed to investigate the prognostic significance of SP and PKM2 in combination with NK1R and Ki-67 in hormone receptor negative (HR-ve) breast cancer.MethodsImmunohistochemical expression levels of SP, NK1R, PKM2, and Ki-67 were measured in 144 paraffin-embedded breast cancer tissues (77 h -ve and 67 h + ve). SP, NK1R, and PKM2 were scored semiquantitatively, while Ki-67 was obtained by the percentage of total number of tumor cells with nuclear staining. The optimal cutoff value for SP, NK1R, PKM2, and Ki-67 were assessed by Cutoff Finder.ResultsHigh SP expression in HR -ve breast cancer was associated with TNM stage (p = 0.020), pT stage (p = 0.035), pN stage (p = 0.002), axillary lymph node metastasis (p = 0.003), and NK1R expression level (p = 0.010). In HR + ve breast cancer, SP expression was associated with HER2 status (p = 0.001) and PKM2 expression level (p = 0.012). Regarding PKM2 expression level, it significantly associated with HER2 status (p = 0.001) and history of DCIS (p = 0.046) in HR-ve tumors, and with HER2 status (p < 0.001) and SP expression level (p = 0.012) in HR + ve tumors. Survival analysis revealed that high SP level negatively impacted overall survival in HR-ve tumors that had low NK1R level (p = 0.021). Moreover, high SP negatively impacted overall survival in HR-ve tumors that had low Ki-67 level (p = 0.005). High PKM2 negatively impacted overall survival in HR-ve cases with low SP (p = 0.047).ConclusionCombined expression levels of SP with NK1R or Ki-67, and PKM2 with SP could be used to predict survival in breast cancer patients with HR-ve tumors. Our findings suggest a role of SP/NK1R pathway and PKM2 in HR-ve breast cancer pathogenesis which should be further investigated to unveil the underlying molecular mechanisms.

MALDI-IHC-Guided In-Depth Spatial Proteomics: Targeted and Untargeted MSI Combined.

Recently, a novel technology was published, utilizing the strengths of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) and immunohistochemistry (IHC), achieving highly multiplexed, targeted imaging of biomolecules in tissue. This new technique, called MALDI-IHC, opened up workflows to target molecules of interest using MALDI-MSI that are usually targeted by standard IHC. In this paper, the utility of targeted MALDI-IHC and its complementarity with untargeted on-tissue bottom-up spatial proteomics is explored using breast cancer tissue. Furthermore, the MALDI-2 effect was investigated and demonstrated to improve MALDI-IHC. Formalin-fixed paraffin-embedded (FFPE) human breast cancer tissue sections were stained for multiplex MALDI-IHC with six photocleavable mass-tagged (PC-MT) antibodies constituting a breast cancer antibody panel (CD20, actin-αSM, HER2, CD68, vimentin, and panCK). K-means spatial clusters were created based on the MALDI-IHC images and cut out using laser-capture microdissection (LMD) for further untargeted LC-MS-based bottom-up proteomics analyses. Numerous peptides could be tentatively assigned to multiple proteins, of which three proteins were also part of the antibody panel (vimentin, keratins, and actin). Post-ionization with MALDI-2 showed an increased intensity of the PC-MTs and suggests options for the development of new mass-tags. Although the on-tissue digestion covered a wider range of proteins, the MALDI-IHC allowed for easy and straightforward identification of proteins that were not detected in untargeted approaches. The combination of the multiplexed MALDI-IHC with image-guided proteomics showed great potential to further investigate diseases by providing complementary information from the same tissue section and without the need for customized instrumentation.

Quality Assessment of Proteins and RNA Following Storage in Archival Formalin-Fixed Paraffin-Embedded Human Breast Cancer Tissue Microarray Sections.

Although the immunogenicity of formalin-fixed paraffin-embedded tissue sections can decrease during storage and transport, the exact mechanism of antigenic loss and how to prevent it are not clear. Herein, we investigated changes in the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), E-cadherin, and Ki-67 in human breast tissue microarray (TMA) tissue sections stored for up to 3 months in dry and wet conditions. The positive rates of ER and PR expression were minimally changed after 3 months of storage, but the Allred scores of ER and PR stored in humid conditions decreased remarkably in comparison to fresh-cut tissue. The HER-2 antigenicity and RNA integrity of breast TMA sections stored in dry conditions diminished gradually with storage time, whereas the immunoreactivity and RNA quality of HER-2 in humid conditions decreased sharply as storage length increased. The area and intensity of E-cadherin staining in tissue sections stored in dry conditions did not change significantly and were minimally changed after 3 months, respectively. In contrast, the area and intensity of E-cadherin staining in tissue sections stored in humid conditions decreased significantly as storage length increased. Finally, the Ki-67 labeling index of tissue sections stored for 3 months in dry (9% decrease) and wet (31.9% decrease) conditions was decreased in comparison to fresh sections. In conclusion, these results indicate that water is a crucial factor for protein and RNA degradation in stored tissue sections, and detailed guidelines are required in the clinic.

Relative Quantification of Proteins in Formalin-Fixed Paraffin-Embedded Breast Cancer Tissue Using Multiplexed Mass Spectrometry Assays

The identification of clinically relevant biomarkers represents an important challenge in oncology. This problem can be addressed with biomarker discovery and verification studies performed directly in tumor samples using formalin-fixed paraffin-embedded (FFPE) tissues. However, reliably measuring proteins in FFPE samples remains challenging. Here, we demonstrate the use of liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM/MS) as an effective technique for such applications. An LC-MRM/MS method was developed to simultaneously quantify hundreds of peptides extracted from FFPE samples and was applied to the targeted measurement of 200 proteins in 48 triple-negative, 19 HER2-overexpressing, and 20 luminal A breast tumors. Quantitative information was obtained for 185 proteins, including known markers of breast cancer such as HER2, hormone receptors, Ki-67, or inflammation-related proteins. LC-MRM/MS results for these proteins matched immunohistochemistry or chromogenic in situ hybridization data. In addition, comparison of our results with data from the literature showed that several proteins representing potential biomarkers were identified as differentially expressed in triple-negative breast cancer samples. These results indicate that LC-MRM/MS assays can reliably measure large sets of proteins using the analysis of surrogate peptides extracted from FFPE samples. This approach allows to simultaneously quantify the expression of target proteins from various pathways in tumor samples. LC-MRM/MS is thus a powerful tool for the relative quantification of proteins in FFPE tissues and for biomarker discovery.

Abstract 6399: SP in relation to NK1R and Ki67 predicts survival in hormone receptor negative breast cancer

Abstract Background: Substance P (SP) is a tachykinin that has been implicated in carcinogenesis in several types of cancer through binding to neurokinin 1 receptor (NK1R). This study aimed to investigate the expression levels of SP and NK1R in hormone receptor negative (HR -ve) versus positive (HR +ve) breast cancer tissues and their relationship with clinicopathological characteristics of patients, Ki-67 index, and overall survival rate. Methods: Immunohistochemical expression levels of SP, NK1R and Ki-67 were measured in 144 paraffin-embedded breast cancer tissues (77 HR -ve and 67 HR +ve). SP and NK1R were scored semiquantitatively, while Ki-67 was obtained by the percentage of total number of tumor cells with nuclear staining. The optimal cutoff value for SP, NK1R and Ki-67 were assessed by Cutoff Finder. Pearson Chi-square (χ2) and Fisher’s exact tests were used to compare the staining scores between groups. ANOVA and student’s t-test were used to compare group means. Kaplan-Meier method with log-rank test was used for survival analysis. Results: High expression of SP, NK1R and Ki-67 was observed in 41%, 36.8% and 38.9% of cases, respectively. Association analyses revealed that SP expression in HR -ve breast cancer was higher in pN3 tumors (p=0.002), positive axillary lymph node metastasis (p=0.003), and high NK1R expression (p=0.010). In HR+ve breast cancer, SP was lower in HER2 positive tumors (p=0.001). Regarding NK1R, the association analysis showed that low NK1R expression level in HR +ve tumors was related to stage IV (p=0.023), pN1 (p=0.006), and low Ki-67 index (p=0.038). Survival analysis revealed that high SP level negatively impacted overall survival in HR-ve tumors that had low NK1R level (p=0.021). Moreover, high SP negatively impacted overall survival in HR-ve tumors that had low Ki-67 level (p=0.005). Nevertheless, NK1R expression did not impact survival in HR-ve or HR+ve cases despite stratification by SP and Ki-67 expression (p&amp;gt;0.05). Conclusion: Up to our knowledge, this is the first study to investigate the prognostic potential of SP and NK1R in breast cancer. Combined expression levels of SP and NK1R or Ki-67 could be used to predict survival in breast cancer patients with HR-ve tumors. Our findings suggest the potential role of SP and NK1R as therapeutic targets in breast cancer. Citation Format: Maha S. Al-Keilani, Rana Elstaty, Mohammad A. Alqudah. SP in relation to NK1R and Ki67 predicts survival in hormone receptor negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6399.

Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning.

Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.

The Prognostic Potential of Neurokinin 1 Receptor in Breast Cancer and Its Relationship with Ki-67 Index.

Background Neurokinin 1 receptor (NK1R) is a promising biomarker and therapeutic target in breast cancer. This study was aimed at investigating the expression level of NK1R in breast cancer tissues and its relationship with proliferation index as measured by Ki-67, clinicopathological characteristics of patients, and overall survival rate. Methods Immunohistochemical expression of NK1R and Ki-67 was measured in 164 paraffin-embedded breast cancer tissues of four molecular subtypes (42 HER2-enriched, 40 luminal A, 42 luminal B, and 40 triple negative). NK1R was scored semiquantitatively, while Ki-67 was obtained by the percentage of total number of tumor cells with nuclear staining. The optimal cutoff values for NK1R and Ki-67 were assessed by Cutoff Finder. Pearson's Chi-square (χ2) and Fisher's exact tests were used to compare the staining scores between groups. The Kaplan-Meier method with log-rank test was used for survival analysis. ANOVA and Student's t-test were used to compare group means. Results A total of 164 patients were included in the study which represented females with invasive ductal carcinoma. NK1R was expressed at high levels in about 34% of investigated cases. The mean Ki-67 level was about 27% and 41.5% of sample had high Ki-67 (expression level > 22%). NK1R expression levels were associated with higher tumor grade (p = 0.021) and high Ki-67 (p = 0.012). NK1R expression negatively impacted overall survival in grade II tumors (p = 0.027). Conclusion NK1R contributes to cellular proliferation and is associated with negative prognosis in breast cancer. These findings suggest the potential role of NK1R as a therapeutic target in breast cancer.

Evaluation of the association between centrosome amplification in tumor tissue of breast cancer patients and changes in the expression of CETN1 and CNTROB genes

One of the contributing factors of cancer is the chromosomal aberration caused by centrosome amplification (CA). Changes in the expression of centrosomal genes can cause centrosomal abnormalities. Among the genes involved are CETN1 and CNTROB. Considering the importance and prevalence of breast cancer the aim of this study was to investigate the expression of these genes and its association with CA in breast cancer in women. In this case-control study, 40 breast cancer patients were referred to Mehr hospital selected and invasive breast cancer was confirmed by pathological tests. IHC method was done on paraffin-embedded breast cancer tissue to evaluate centrosome amplification by targeting Pericentrin antibody. Real-time PCR performed to gene expression of CETN1 and CNTROB. The data were analyzed by t-test and ANOVA test. The results showed that CA in breast tumor cells significantly was more than adjacent normal cells (p ≤ 0.05). Results of CETN1 and CNTROB gene expression showed increase expression in tumor tissue compared to control, respectively (p = 0.01, P = 0.02). Our finding showed that alterations of CETN1 and CNTROB gene expression in cancer tissues of patients were excessive in comparison with normal tissues, which could cause cell proliferation, tumor growth and metastasis. It is suggested to find basic strategies for diagnosis and treatment of breast cancer needed more samples of breast cancer, and other genes involved in the function of centrosomes.

The Visualization of Protein-Protein Interactions in Breast Cancer: Deployment Study in Pathological Examination.

The therapeutic strategy is determined by protein expression using immunohistochemistry of estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2 (HER2) in formalin-fixed paraffin-embedded (FFPE) breast cancer tissues. However, few proteins function independently, and many of them functions due to protein-protein interactions (PPIs) with other proteins. Therefore, it is important to focus on PPIs. This review summarizes the PPIs of ER and HER2 in breast cancer, especially those using a proximity ligation assay that can visualize PPIs in FFPE tissues. In particular, assessing the interaction of CEACAM6 with HER2 may serve as a surrogate marker for the efficacy of trastuzumab in patients with breast cancer. Therefore, in this review, the technique used to detect the interaction of CEACAM6 and HER2 in routinely processed pathological specimens will be applied to the clinical practice of drug selection. We showed the possibility as a novel pathological examination method using PPIs.

Quantification of Human Epidermal Growth Factor Receptor 2 by Immunopeptide Enrichment and Targeted Mass Spectrometry in Formalin-Fixed Paraffin-Embedded and Frozen Breast Cancer Tissues

Conventional HER2-targeting therapies improve outcomes for patients with HER2-positive breast cancer (BC), defined as tumors showing HER2 protein overexpression by immunohistochemistry and/or ERBB2 gene amplification determined by in situ hybridization (ISH). Emerging HER2-targeting compounds show benefit in some patients with neither HER2 protein overexpression nor ERBB2 gene amplification, creating a need for new assays to select HER2-low tumors for treatment with these compounds. We evaluated the analytical performance of a targeted mass spectrometry-based assay for quantifying HER2 protein in formalin-fixed paraffin-embedded (FFPE) and frozen BC biopsies. We used immunoaffinity-enrichment coupled to multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) to quantify HER2 protein (as peptide GLQSLPTHDPSPLQR) in 96 frozen and 119 FFPE BC biopsies. We characterized linearity, lower limit of quantification (LLOQ), and intra- and inter-day variation of the assay in frozen and FFPE tissue matrices. We determined concordance between HER2 immuno-MRM-MS and predicate immunohistochemistry and ISH assays and examined the benefit of multiplexing the assay to include proteins expressed in tumor subcompartments (e.g., stroma, adipose, lymphocytes, epithelium) to account for tissue heterogeneity. HER2 immuno-MRM-MS assay linearity was ≥103, assay coefficient of variation was 7.8% (FFPE) and 5.9% (frozen) for spiked-in analyte, and 7.7% (FFPE) and 7.9% (frozen) for endogenous measurements. Immuno-MRM-MS-based HER2 measurements strongly correlated with predicate assay HER2 determinations, and concordance was improved by normalizing to glyceraldehyde-3-phosphate dehydrogenase. HER2 was quantified above the LLOQ in all tumors. Immuno-MRM-MS can be used to quantify HER2 in FFPE and frozen BC biopsies, even at low HER2 expression levels.

Nodal status in luminal A invasive breast cancer: relationships with cytotoxic CD8\u2009+\u2009and regulatory FOXP3\u2009+\u2009cells tumor-associated infiltrate and other prognostic factors

Luminal A breast cancers are generally associated with low metastatic potential and good prognosis. However, there is a proportion of patients, who present with metastases in lymph nodes. The aim of our study was to determine the association between the number of positive lymph nodes and infiltrates of tumor-associated cytotoxic CD8 + (CTLs), regulatory FOXP3 + T cells (Tregs), as well as other prognostic factors. Immunohistochemistry (IHC) for CD8 + and FOXP3 + was performed in 87 formalin-fixed paraffin-embedded primary breast cancer tissues, and cell infiltrate was assessed under light microscope. We observed that node-positive cases were associated with higher numbers of Treg cells and lower CTL/Treg ratio. There was also an inverse correlation between the CTL/Treg ratio and the number of metastatic lymph nodes. Similar relationships were found between the number of metastatic lymph nodes and Treg density or CTL/Treg ratio in pT1 BC. An elevated intratumoral CTL/Treg ratio was associated with pN0 stage. The relationship between lymphovascular invasion (LVI) and Treg density was also noted in node-negative tumors. In addition, more advanced nodal stage was related to LVI, higher pT, and lower PR expression. The numbers of CD8 + and FOXP3 + were also associated with tumor size, histologic grade, PR expression, and mitotic index. The results of our study suggested that the levels of tumor-infiltrating regulatory and cytotoxic cells as well as the balance between them play a role in lymphovascular spread of luminal A breast cancers.

Immunohistochemical expression of substance P in breast cancer and its association with prognostic parameters and Ki-67 index.

The neuropeptide substance P is a potential biomarker and therapeutic target in cancer. The main objectives of this study were to investigate the expression level of substance P in different breast cancer molecular subtypes and identify its association with clinicopathological parameters of patients and with Ki-67 index. A retrospective analysis was performed for a total of 164 paraffin-embedded breast cancer tissue samples [42 Her2/neu-enriched, 40 luminal A, 42 luminal B (triple-positive) and 40 triple negative subtypes]. The tissue microarray slides containing specimens were used to determine the expression of substance p and Ki-67 by immunohistochemical staining. The mean age of the cohort was 51.35 years. Twenty two percent of cases had low substance P expression levels (TS ≤ 5), while 78% had high expression levels (TS > 5). A significant association was found between SP expression level and breast cancer molecular subtype (p = 0.002), TNM stage (p = 0.034), pN stage (p = 0.013), axillary lymph node metastasis (p = 0.004), ER and PR statuses (p<0.001) and history of DCIS (p = 0.009). The average percentage of Ki-67 expression was 27.05%. When analyzed as a continuous variable, significant differences were observed between the mean Ki-67 scores and molecular subtype (p = 0.001), grade (p = 0.003), pN stage (p = 0.007), axillary lymph node metastasis (p = 0.001), and ER and PR statuses (p <0.001). SP is overexpressed in most of the analyzed tissues and has a negative prognostic value in the breast cancer patients. Besides substance P is a potential therapeutic target in breast cancer.

Raman spectroscopy based pathological analysis and discrimination of formalin fixed paraffin embedded breast cancer tissue

The application of Raman microspectroscopy in the histopathological analysis have been widely pursued for characterizing ex vivo biological tissue, and for reducing the number of false positive biopsies and increase the cancer diagnosis accuracy. Many studies have been carried out on fresh or frozen tissue samples, which preserved comprehensive qualitative and quantitative compositional information. However, by the wider applicability of dewaxed formalin-fixed paraffin-embedded (FFPE) samples in the hospital, an abundant tissue bank is a useful resource for the on-site retrospective research to improve diagnosis accuracy. Therefore, we implemented an ex vivo Raman spectroscopic study combined multivariate analysis methods for presenting a better understanding of the sample processing effects and testifying the potential Raman based pathological analysis capabilities of FFPE sections. By comparing 600 spectra from thirty-six fresh frozen (n=18) and FFPE breast tissue samples (n=18), including Healthy tissue, Ductal Carcinoma In Situ, and Invasive Ductal Carcinoma tissue, the results demonstrated that the dewaxing process significantly altered the biochemical composition of the tissues, particularly lipids, proteins, and carotenoids. Even though, the analytical result proved that commonly used multivariate analysis methods, including principal component analysis - linear discriminant analysis (PCA-LDA) and partial least squares- discriminant analysis (PLS-DA), could still distinguish the investigated tissue types effectively with satisfying overall accuracy in which PCA-LDA is 88.3 %, PLS-DA is 93.0 %. Therefore, this study confirmed that FFPE sections have diagnostic potential with multivariate analytical model provided that the biochemical changes, meanwhile tissue processing should be aware.

Detection of Human Cytomegalovirus Proteins in Paraffin-Embedded Breast Cancer Tissue Specimens-A Novel, Automated Immunohistochemical Staining Protocol.

Emerging evidence supports a significant association between human cytomegalovirus (HCMV) and human malignancies, suggesting HCMV as a human oncomodulatory virus. HCMV gene products are found in >90% of breast cancer tumors and seem to be correlated with more aggressive disease. The definitive diagnosis of HCMV relies on identification of virus inclusions and/or viral proteins by different techniques including immunohistochemical staining. In order to reduce biases and improve clinical value of HCMV diagnostics in oncological pathology, automation of the procedure is needed and this was the purpose of this study. Tumor specimens from 115 patients treated for primary breast cancer at Akershus University Hospital in Norway were available for the validation of the staining method in this retrospective study. We demonstrate that our method is highly sensitive and delivers excellent reproducibility for staining of HCMV late antigen (LA), which makes this method useful for future routine diagnostics and scientific applications.