The quantitative detection of total HER2 load by quantum dots and the identification of a new subtype of breast cancer with different 5-year prognosis

Quantum Dot Research in Breast Cancer: Challenges and Prospects

The multifaceted role of quantum dots (QDs) in breast cancer research highlights significant advancements in diagnostics, targeted therapy, and drug delivery systems. This comprehensive review addresses the development of precise imaging techniques for early cancer detection and the use of QDs in enhancing the specificity of therapeutic delivery, particularly in challenging cases like triple-negative breast cancer (TNBC). The paper also discusses the critical understanding of QDs' interactions with cancer cells, offering insights into their potential for inducing cytotoxic effects and facilitating gene therapy. Limitations such as biocompatibility, toxicity concerns, and the transition from laboratory to clinical practice are critically analyzed. Future directions emphasize safer, non-toxic QD development, improved targeting mechanisms, and the integration of QDs into personalized medicine, aiming to overcome the current challenges and enhance breast cancer management.

Purified fluorescent nanohybrids based on quantum dot-HER2-antibody for breast tumor target imaging

Quantum dots (QDs) have been widely used for bioimaging in vivo because of their excellent optical properties. As part of the preparation process of QD-based nanohybrids, purification is an important step for minimizing contaminants and improving the quality of the product. In this work, we describe high-performance size exclusion chromatography (HPSEC) used to purify nanohybrids of CdSe/ZnS QDs and anti-human epidermal growth factor receptor 2 antibodies (QD-HER2-Ab). The unbound antibody and suspended agglomerates were removed from freshly prepared QD-HER2-Ab via HPSEC. Pure and homogeneous QD-HER2-Ab were then used as immunofluorescence target imaging bioprobes in vivo. The QD-HER2-Ab did not cause any obvious acute toxicity in mice one week after a single intravenous injection of 15 nmol/kg. The purified QD-HER2-Ab bioprobes showed high tumor targeting ability in a human breast tumor xenograft nude mouse model (24 h after injected) with the possibility of in vivo immunofluorescence tumor imaging. The immunofluorescence imaging background signal and acute toxicity in vivo were minimized because of the reduction of residual QDs. HPSEC-purified QD-HER2-Ab is an accurate and convenient tool for in vivo tumor target imaging and HER2 detection, thus providing a basis for the purification of other QD-based bioprobes.

Surface-enhanced Raman scattering holography chip for rapid, sensitive and multiplexed detection of human breast cancer-associated MicroRNAs in clinical samples

MicroRNAs (miRNAs) are promising biomarkers for the early diagnosis of breast cancer. Yet, simultaneous achievement of rapid, sensitive and accurate detection of diverse miRNAs in clinical samples is still challenging due to the low abundance of miRNAs and the complex procedures of RNA extraction and separation. Herein, we develop an innovative three-dimensional (3D) surface-enhanced Raman scattering (SERS) holography sensing strategy for rapid, sensitive and multiplexed detection of human breast cancer-associated miRNAs. To establish a proof of concept, nine kinds of human breast cancer-associated miRNAs are isothermally amplified by Exonuclease (Exo) III enzyme, and the products could be spatially separated to corresponding sensing region on silicon SERS substrates. Each region has been modified with corresponding hairpin DNA probes, which are used to identify and quantify the miRNAs. Different DNA probes are labeled with different Raman reporters, which serve as "SERS tags" to incorporate spectroscopic information into computer-generated 3D SERS hologram within ~9 min. We demonstrate that 3D SERS holography chip not only achieves an ultrahigh sensitivity down to ~1 aM but also feature a high correlation with RT-qPCR in the detection of nine miRNAs in 30 clinical serum samples. This work provides a feasible tool to improve the diagnosis of breast cancer.

Tenascin-C immobilizes infiltrating T lymphocytes through CXCL12 promoting breast cancer progression

Immune checkpoint therapy, where CD8 tumor infiltrating T lymphocytes (TIL) are reactivated, is a promising anti-cancer treatment approach, yet with low response rates. The extracellular matrix, in particular tenascin-C, may generate barriers for TIL. To investigate this possibility, we used a MMTV-NeuNT and syngeneic mammary gland grafting model derived thereof with engineered tenascin-C levels and observed accumulation of CD8 TIL in tenascin-C-rich stroma. Inhibition studies revealed that tenascin-C induced CXCL12 through TLR4. By binding CXCL12, tenascin-C retained CD8 TIL in the stroma. Blockade of CXCR4, the receptor of CXCL12, enhanced macrophage and CD8 TIL infiltration and reduced tumor growth and subsequent metastasis. Retention of CD8 TIL by tenascin-C/CXCL12 was also observed in human breast cancer by tissue staining. Moreover, whereas high CD8 TIL numbers correlated with longer metastasis-free survival, this was not the case when also tenascin-C and CXCL12 levels were high. Altogether, these results may be useful for improving tumor immunity as diagnostic tool and to formulate a future "TIL-matrix-release-and-reactivate" strategy.

Computerized Assessment of the Tumor-stromal Ratio and Proposal of a Novel Nomogram for Predicting Survival in Invasive Breast Cancer

Background: Various studies have verified the prognostic significance of the tumor-stromal ratio (TSR) in several types of carcinomas using manually assessed H&E stained histologic sections. This study aimed to establish a computerized method to assess the TSR in invasive breast cancer (BC) using immunohistochemistry (IHC)-stained tissue microarrays (TMAs), and integrate the TSR into a novel nomogram for predicting survival.

Methods: IHC-staining of cytokeratin (CK) was performed in 7 prepared TMAs containing 240 patients with 480 invasive BC specimens. The ratio of tumor areas and stromal areas was determined by the computerized method, and categorized as stroma-low and stroma-high groups using the X-tile software. The prognostic value of the TSR at 5-year disease free survival (5-DFS) in each subgroup was analyzed. Univariate and multivariate analyses were performed and a novel nomogram for predicting survival in invasive breast cancer was established and assessed.

Results: The newly developed computerized method could accurately recognize CK-labeled tumor areas and non-labeled stromal areas, and automatically calculate the TSR. Stroma-low and stroma-high accounted for 38.8% (n = 93) and 61.2% (n = 147) of the cases, according to the cut-off value of 55.5% for stroma ratio. The Kaplan-Meier analysis showed that patients in the stroma-high group had a worse 5-DFS compared to patients in the stroma-low group (P = 0.031). Multivariable analysis indicated that the T stage, N status, histological grade, ER status, HER-2 gene, and the TSR were potential risk factors of invasive BC patients, which were included into the nomogram (P < 0.10 for all). The nomogram was well calibrated to predict the probability of 5-DFS and the C-index was 0.817, which was higher than any single predictor. A dynamic nomogram was built for convenient use. The area under the curve (AUC) of the nomogram was 0.870, while that of the TNM staging system was 0.723. The Kaplan-Meier analysis showed that the nomogram had a better risk stratification for invasive BC patients than the TNM staging system.

Conclusions: Based on IHC staining of CK on TMAs, this study successfully developed a computerized method for TSR assessment and established a novel nomogram for predicting survival in invasive BC patients.

CdSe quantum dots evaluation in primary cellular models or tissues derived from patients

In recent years quantum dots (QDs) have risen as useful luminescent nanoparticles with multiple applications ranging from laser, image displays and biomedical applications. Here we review and discuss the studies of these nanoparticles in patient derived cellular samples or tissues, including cellular models from iPSCs from patients, biopsied and post-mortem tissue. QD-based multiplexed imaging has been proved to overcome most of the major drawbacks of conventional techniques, exhibiting higher sensitivity, reliability, accuracy and simultaneous labeling of key biomarkers. In this sense, QDs are very promising tools to be further used in clinical applications including diagnosis and therapy approaches. Analyzing the possibilities of these materials in these biological samples gives an overview of the future applications of the nanoparticles in models closer to patients and their specific disease.

Prognostic Significance of the Tumor-Stromal Ratio in Invasive Breast Cancer and a Proposal of a New Ts-TNM Staging System

Background

Previous studies have demonstrated that the tumor-stromal ratio (TSR) was an independent prognostic factor in several types of carcinomas. This study aimed at exploring the prognostic significance of the TSR in invasive breast cancer using immunohistochemistry (IHC)-stained tissue microarrays (TMAs) and integrating the TSR into the traditional tumor-node-metastasis (TNM) staging system.

Methods

The prepared 7 TMAs containing 240 patients with 480 invasive BC specimens were stained with cytokeratin (CK) by the IHC staining method. The ratio of tumor cells and stromal cells was visually assessed. TSR > 1 and TSR ≤ 1 were categorized as the high TSR (low stroma) and low TSR (high stroma) groups, respectively, and the prognostic value of the TSR at 5-year disease-free survival (5-DFS) was analyzed. A new Ts-TNM (tumor stroma-tumor-node-metastasis) staging system was established and assessed.

Results

IHC staining of CK could specifically label tumor cells with clear contrast, making it easy to manually assess TSR. High TSR (low stroma) and low TSR (high stroma) were observed in 52.5% (n = 126) and 47.5 (n = 114) of the cases, according to the division of value 1. A Kaplan-Meier analysis showed that patients in the low TSR group had a worse 5-DFS compared with patients in the high TSR group (P=0.022). Multivariable analysis indicated that the T stage (P=0.014), N status (P < 0.001), histological grade (P < 0.001), estrogen receptor status (P=0.015), and TSR (P=0.011) were independent prognostic factors of invasive BC patients. The new Ts-TNM staging system combining TSR, tumor staging, lymph node status, and metastasis staging was established. The receiver operating characteristic (ROC) curve analysis demonstrated that the ability of the Ts-TNM staging system to predict recurrence was not lower than that of the TNM staging system.

Conclusions

This study confirms that the TSR is a prognostic indicator for invasive breast cancer. The Ts-TNM staging system containing stromal and tumor information may optimize risk stratification for invasive breast cancer.

Single-Virus Tracking: From Imaging Methodologies to Virological Applications

Uncovering the mechanisms of virus infection and assembly is crucial for preventing the spread of viruses and treating viral disease. The technique of single-virus tracking (SVT), also known as single-virus tracing, allows one to follow individual viruses at different parts of their life cycle and thereby provides dynamic insights into fundamental processes of viruses occurring in live cells. SVT is typically based on fluorescence imaging and reveals insights into previously unreported infection mechanisms. In this review article, we provide the readers a broad overview of the SVT technique. We first summarize recent advances in SVT, from the choice of fluorescent labels and labeling strategies to imaging implementation and analytical methodologies. We then describe representative applications in detail to elucidate how SVT serves as a valuable tool in virological research. Finally, we present our perspectives regarding the future possibilities and challenges of SVT.

Quantum Dot-Based Simultaneous Multicolor Imaging

Quantum dots have attracted a great deal of attention among researchers in optical imaging because of their unique physicochemical properties. Their adjustable size allows quantum dots to emit visible fluorescence with different wavelengths excited by a single light source, allowing them to play an unmatched role in multitarget simultaneous multicolor imaging of tissues and cells compared with other molecular biotechnologies and traditional fluorescent materials. This technology affords real-time observation in situ of multiple biomarkers, allowing us to quantify their expression levels, and helping us to gain a deeper understanding of the interactions among biomolecules and the relationship between biomolecules and disease occurrence, progression, and prognosis. This has potential to aid in clinical diagnosis and treatment decision making.

Advances in HER2 testing

HER2-positive breast cancer is a particularly aggressive type of breast cancer. Indication of HER2 positivity is essential for its treatment. In addition to a few FDA-approved methods such as immunohistochemical (IHC) detection of HER2 protein expression and in situ hybridization (ISH) assessment of HER2 gene amplification, several novel methods have been developed for HER2 testing in recent years. This chapter provides an overview of HER2 testing with emphasis on those new methods.

Automated Quantification of Extranuclear ERα using Phosphor-integrated Dots for Predicting Endocrine Therapy Resistance in HR+/HER2- Breast Cancer

In addition to genomic signaling, Estrogen receptor alpha (ERα) is associated with cell proliferation and survival through extranuclear signaling contributing to endocrine therapy (ET) resistance. However, the relationship between extranuclear ERα and ET resistance has not been extensively studied. We sought to measure extranuclear ERα expression by immunohistochemistry using phosphor-integrated dots (IHC-PIDs) and to assess its predictive value for ET resistance. After quantitative detection of ERα by IHC-PIDs in vitro, we developed “the nearest-neighbor method” to calculate the extranuclear ERα. Furthermore, tissue sections from 65 patients with HR+/HER2- BC were examined by IHC-PIDs, and the total ERα, nuclear ERα, extranuclear ERα PIDs score, and ratio of extranuclear-to-nuclear ERα (ENR) were measured using the novel method. We demonstrate that quantification of ERα using IHC-PIDs exhibited strong correlations to real-time qRT-PCR (r² = 0.94) and flow cytometry (r² = 0.98). High ERα ENR was significantly associated with poor overall survival (p = 0.048) and disease-free survival (DFS) (p = 0.007). Multivariate analysis revealed that the ERα ENR was an independent prognostic factor for DFS [hazard ratio, 3.8; 95% CI, 1.4–11.8; p = 0.006]. Our automated measurement has high accuracy to localize and assess extranuclear ERα. A high ERα ENR in HR⁺/HER2⁻ BC indicates decreased likelihood of benefiting from ET.

Incorporating gold nanoclusters and target-directed liposomes as a synergistic amplified colorimetric sensor for HER2-positive breast cancer cell detection

Breast cancer is the second leading cause of cancer-related mortality in women. Successful development of sensitive nanoprobes for breast cancer cell detection is of great importance for breast cancer diagnosis and symptomatic treatment. Herein, inspired by the intrinsic peroxidase property of gold nanoclusters, high loading, and targeting ability of ErbB2/Her2 antibody functionalized liposomes, we report that gold nanoclusters-loaded, target-directed, functionalized liposomes can serve as a robust sensing platform for amplified colorimetric detection of HER2-positive breast cancer cells. This approach allows HER2-positive breast cancer cell identification at high sensitivity with high selectivity. In addition, the colorimetric “readout” offers extra advantages in terms of low-cost, portability, and easy-to-use applications. The practicality of this platform was further proved by successful detection of HER2-positive breast cancer cells in human serum samples and in breast cancer tissue, which indicated our proposed method has potential for application in cancer theranostics.

A Comparative Performance Analysis of Multispectral and RGB Imaging on HER2 Status Evaluation for the Prediction of Breast Cancer Prognosis

Despite the extensive application of multispectral imaging (MSI) in biomedical multidisciplinary researches, there is a paucity of data available regarding the implication of MSI in tumor prognosis prediction. We compared the behaviors of multispectral (MS) and conventional red-green-blue (RGB) images on assessment of human epidermal growth factor receptor 2 (HER2) immunohistochemistry to explore their impact on outcome in patients with invasive breast cancer (BC). Tissue microarrays containing 240 BC patients were introduced to compare the performance of MS and RGB imaging methods on the quantitative assessment of HER2 status and the prognostic value of 5-year disease-free survival (5-DFS). Both the total and average signal optical density values of HER2 MS and RGB images were analyzed, and all patients were divided into two groups based on the different 5-DFS. The quantification of HER2 MS images was negatively correlated with 5-DFS in lymph node–negative and –positive patients (P < .05), but RGB images were not in lymph node–positive patients (P = .101). Multivariate analysis indicated that the hazard ratio (HR) of HER2 MS was higher than that of HER2 RGB (HR = 2.454; 95% confidence interval [CI], 1.636-3.681 vs HR = 2.060; 95% CI, 1.361-3.119). Additionally, area under curve (AUC) by receiver operating characteristic analysis for HER2 MS was greater than that for HER2 RGB (AUC = 0.649; 95% CI, 0.577-0.722 vs AUC = 0.596; 95% CI, 0.522-0.670) in predicting the risk for recurrence. More importantly, the quantification of HER2 MS images has higher prediction accuracy than that of HER2 RGB images (69.6% vs 65.0%) on 5-DFS. Our study suggested that better information on BC prognosis could be obtained from the quantification of HER2 MS images and MS images might perform better in predicting BC prognosis than conventional RGB images.

Quantum dot-based molecular imaging of cancer cell growth using a clone formation assay

This aim of the present study was to investigate clonal growth behavior and analyze the proliferation characteristics of cancer cells. The MCF‑7 human breast cancer cell line, SW480 human colon cancer cell line and SGC7901 human gastric cancer cell line were selected to investigate the morphology of cell clones. Quantum dot‑based molecular targeted imaging techniques (which stained pan‑cytokeratin in the cytoplasm green and Ki67 in the cell nucleus yellow or red) were used to investigate the clone formation rate, cell morphology, discrete tendency, and Ki67 expression and distribution in clones. From the cell clone formation assay, the MCF‑7, SW480 and SGC7901 cells were observed to form clones on days 6, 8 and 12 of cell culture, respectively. These three types of cells had heterogeneous morphology, large nuclear:cytoplasmic ratios, and conspicuous pathological mitotic features. The cells at the clone periphery formed multiple pseudopodium. In certain clones, cancer cells at the borderline were separated from the central cell clusters or presented a discrete tendency. With quantum dot‑based molecular targeted imaging techniques, cells with strong Ki67 expression were predominantly shown to be distributed at the clone periphery, or concentrated on one side of the clones. In conclusion, cancer cell clones showed asymmetric growth behavior, and Ki67 was widely expressed in clones of these three cell lines, with strong expression around the clones, or aggregated at one side. Cell clone formation assay based on quantum dots molecular imaging offered a novel method to study the proliferative features of cancer cells, thus providing a further insight into tumor biology.

Application of multispectral imaging in quantitative immunohistochemistry study of breast cancer: a comparative study

Multispectral imaging (MSI) based on imaging and spectroscopy, as relatively novel to the field of histopathology, has been used in biomedical multidisciplinary researches. We analyzed and compared the utility of multispectral (MS) versus conventional red-green-blue (RGB) images for immunohistochemistry (IHC) staining to explore the advantages of MSI in clinical-pathological diagnosis. The MS images acquired of IHC-stained membranous marker human epidermal growth factor receptor 2 (HER2), cytoplasmic marker cytokeratin5/6 (CK5/6), and nuclear marker estrogen receptor (ER) have higher resolution, stronger contrast, and more accurate segmentation than the RGB images. The total signal optical density (OD) values for each biomarker were higher in MS images than in RGB images (all P < 0.05). Moreover, receiver operator characteristic (ROC) analysis revealed that a greater area under the curve (AUC), higher sensitivity, and specificity in evaluation of HER2 gene were achieved by MS images (AUC = 0.91, 89.1 %, 83.2 %) than RGB images (AUC = 0.87, 84.5, and 81.8 %). There was no significant difference between quantitative results of RGB images and clinico-pathological characteristics (P > 0.05). However, by quantifying MS images, the total signal OD values of HER2 positive expression were correlated with lymph node status and histological grades (P = 0.02 and 0.04). Additionally, the consistency test results indicated the inter-observer agreement was more robust in MS images for HER2 (inter-class correlation coefficient (ICC) = 0.95, r s = 0.94), CK5/6 (ICC = 0.90, r s = 0.88), and ER (ICC = 0.94, r s = 0.94) (all P < 0.001) than that in RGB images for HER2 (ICC = 0.91, r s = 0.89), CK5/6 (ICC = 0.85, r s = 0.84), and ER (ICC = 0.90, r s = 0.89) (all P < 0.001). Our results suggest that the application of MS images in quantitative IHC analysis could obtain higher accuracy, reliability, and more information of protein expression in relation to clinico-pathological characteristics versus conventional RGB images. It may become an optimal IHC digital imaging system used in quantitative pathology.

Expression of Epstein-Barr virus-induced gene 3 in cervical cancer: Association with clinicopathological parameters and prognosis

Epstein-Barr virus-induced gene 3 (EBI3) encodes a secretory glycoprotein, and has previously been identified as upregulated in a series of cancers. However, the clinical significance of EBI3 in cervical cancer and the potential of EBI3 as a therapeutic target for this disease have not been elucidated. In the present study, EBI3 expression was analyzed by immunohistochemistry in 90 clinicopathologically characterized cervical cancer tissue samples. The association between EBI3 expression and survival of patients with cervical cancer was also analyzed. The expression level of EBI3 in cervical cancer tissues was found to be significantly increased compared with the expression levels in the normal squamous epithelium. In addition, EBI3 expression was significantly correlated with the clinical stage and size of tumors (P<0.05). Furthermore, the presence of EBI3 expression was associated with a poor prognosis compared with patients without EBI3 expression. Multivariate analysis revealed that EBI3 expression was an independent predictor of overall survival (hazard ratio, 4.032; 95% confidence interval, 1.538-7.436; P=0.035). To the best of our knowledge, the present results indicate for the first time that EBI3 expression is significantly associated with the progression and poor prognosis of cervical cancer. EBI3 may be a potential prognostic marker and a therapeutic target in cervical cancer.

Quantum dot-based in situ simultaneous molecular imaging and quantitative analysis of EGFR and collagen IV and identification of their prognostic value in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a unique breast cancer subtype with high heterogeneity and poor prognosis. Currently, the treatment effect of TNBC has reached a bottleneck, rendering new breakthroughs difficult. Cancer invasion is not an entirely cell-autonomous process, requiring the cells to transmigrate across the surrounding extracellular matrix (ECM) barriers. Developing a new system that integrates key constituents in the tumor microenvironment with pivotal cancer cell molecules is essential for the in-depth investigation of the mechanism of invasion in TNBC. We describe a computer-aided algorithm developed using quantum dot (QD)-based multiplex molecular imaging of TNBC tissues. We performed in situ simultaneous imaging and quantitative detection of epidermal growth factor receptor (EGFR), expressed in the TNBC cell membrane, and collagen IV, the major ECM constituent; calculated the EGFR/collagen IV ratio; and investigated the prognostic value of the EGFR/collagen IV ratio in TNBC. We simultaneously imaged and quantitatively detected EGFR and collagen IV in the TNBC samples. In all patients, quantitative determination showed a statistically significant negative correlation between EGFR and collagen IV. The 5-year disease-free survival (5-DFS) of the high and low EGFR/collagen IV ratio subgroups was significantly different. The EGFR/collagen IV ratio was predictive and was an independent prognostic indicator in TNBC. Compared with EGFR expression, the EGFR/collagen IV ratio had a greater prognostic value for 5-DFS. Our findings open up a new avenue for predicting the clinical outcome in TNBC from the perspective of integrating molecules expressed in both cancer cells and the ECM.

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors.

Quantum dots-based quantitative and in situ multiple imaging on ki67 and cytokeratin to improve ki67 assessment in breast cancer

Background

As a marker for tumor cell proliferation, Ki67 has important impacts on breast cancer (BC) prognosis. Although immunohistochemical staining is the current standard method, variations in analytical practice make it difficult for pathologists to manually measure Ki67 index. This study was to develop a fluorescent spectrum-based quantitative analysis of Ki67 expression by quantum-dots (QDs) multiple imaging technique.

Methods

A QDs-based in situ multiple fluorescent imaging method was developed, which stained nuclear Ki67 as red signal and cytoplasmic cytokeratin (CK) as green signal. Both Ki67 and CK signals were automatically separated and quantified by professional spectrum analysis software. This technique was applied to tissue microarrays from 240 BC patients. Both Ki67 and CK values, and Ki67/CK ratio were obtained for each patient, and their prognostic value on 5-year disease free survival was assessed.

Results

This method simultaneously stains nuclear Ki67 and cytoplasmic CK with clear signal contrast, making it easy for signal separation and quantification. The total fluorescent signal intensities of both Ki67 sum and CK sum were obtained, and Ki67/CK ratio calculated. Ki67 sum and Ki67/CK ratio were each attributed into two grades by X-tile software based on the best P value principle. Multivariate analysis showed Ki67 grade (P = 0.047) and Ki67/CK grade (P = 0.004) were independent prognostic factors. Furthermore, area under curve (AUC) of ROC analysis for Ki67/CK grade (AUC: 0.683, 95%CI: 0.613–0.752) was higher than Ki67 grade (AUC: 0.665, 95%CI: 0.596–0.734) and HER-2 gene (AUC: 0.586, 95%CI: 0.510–0.661), but lower than N stage (AUC: 0.760, 95%CI: 0.696–0.823) and histological grade (AUC: 0.756, 95%CI: 0.692–0.820) on predicting the risk for recurrence.

Conclusions

A QDs-based quantitative and in situ multiple imaging on Ki67 and CK was developed to improve Ki67 assessment in BC, and Ki67/CK grade had better performance than Ki67 grade in predicting prognosis.

Quantum dots-based tissue and in vivo imaging in breast cancer researches: current status and future perspectives

As the most common malignant tumor for females, breast cancer (BC) is a highly heterogeneous disease regarding biological behaviors. Precisely targeted imaging on BC masses and biomarkers is critical to BC detection, treatment, monitoring, and prognostic evaluation. As an important imaging technique, quantum dots (QDs)-based imaging has emerged as a promising tool in BC researches owe to its outstanding optical properties. However, few reviews have been specifically devoted to discussing applications of QDs-based imaging in BC researches. This review summarized recent promising works in QDs-based tissue and in vivo imaging for BC studies. Physicochemical and optical properties of QDs and its potential applications were briefly described first. Then QDs-based imaging studies in BC were systematically reviewed, including tissue imaging for studying biomarkers interactions, and evaluating prognostic biomarkers, in vivo imaging for mapping axillary lymphatic system, showing BC xenograft tumor, and detecting BC metastases. At last, the future perspectives with special emphasis on the potential clinical applications have also been discussed. Potential applications of QDs-based imaging on clinical BC in the future are mainly focused on tissue study, especially in BC molecular pathology due to its optimal optical properties and quantitative information capabilities on multiple biomarkers.

Quantum dots immunofluorescence histochemical detection of EGFR gene mutations in the non-small cell lung cancers using mutation-specific antibodies

BACKGROUND

Epidermal growth factor receptor (EGFR) mutation status plays an important role in therapeutic decision making for non-small cell lung cancer (NSCLC) patients. Since EGFR mutation-specific antibodies (E746-A750del and L858R) have been developed, EGFR mutation detection by immunohistochemistry (IHC) is a suitable screening test. On this basis, we want to establish a new screening test, quantum dots immunofluorescence histochemistry (QDs-IHC), to assess EGFR gene mutation in NSCLC tissues, and we compared it to traditional IHC and amplification refractory mutation system (ARMS).

MATERIALS AND METHODS

EGFR gene mutations were detected by QDs-IHC, IHC, and ADx-ARMS in 65 cases of NSCLC composed of 55 formalin-fixed, paraffin-embedded specimens and ten pleural effusion cell blocks, including 13 squamous cell carcinomas, two adenosquamous carcinomas, and 50 adenocarcinomas.

RESULTS

Positive rates of EGFR gene mutations detected by QDs-IHC, IHC, and ADx-ARMS were 40.0%, 36.9%, and 46.2%, respectively, in 65 cases of NSCLC patients. The sensitivity of QDs-IHC when detecting EGFR mutations, as compared to ADx-ARMS, was 86.7% (26/30); the specificity for both antibodies was 100.0% (26/26). IHC sensitivity was 80.0% (24/30) and the specificity was 92.31% (24/26). When detecting EGFR mutations, QDs-IHC and ADx-ARMS had perfect consistency (κ  =0.882; P<0.01). Excellent agreement was observed between IHC and ADx-ARMS when detecting EGFR mutations (κ  =0.826; P<0.01).

CONCLUSION

QDs-IHC is a simple and standardized method to detect EGFR mutations with its high sensitivity and specificity, as compared with real-time polymerase chain reaction. In addition, the development of specific antibodies against EGFR mutation proteins might be useful for the diagnosis and treatment of lung cancer.

Nuclear translocation of telomerase reverse transcriptase is a critical process in lymphatic metastasis of nasopharyngeal carcinoma

Telomerase reverse transcriptase (TERT) is the predominant functional unit of telomerase and maintains the telomere length and the stability of chromosomes. Recently, TERT has been shown to be a critical factor in a number of other biological processes, including cell proliferation and cancer metastasis. In addition, although numerous studies have been conducted, the subcellular localization of the TERT protein and the association of such with cancer metastasis remains unclear. To investigate the involvement of TERT in in vivo metastasis, quantum dots-based immunofluorescence and western blot analysis were conducted to detect changes in the subcellular localization of TERT in human nasopharyngeal carcinoma (NPC) tissues and metastatic lymph nodes. To further investigate, metastatic and non-metastatic models of NPC were generated using 5-8F (high metastasis capability) and 6-10B (low metastasis capability) cell lines, respectively. It was found that TERT protein was overexpressed in NPC tissue samples and metastatic lymph nodes and TERT was predominantly located in the cytoplasm of primary NPC tissues, while TERT was predominantly located in the nucleus of the metastatic lymph nodes. The ratio of cytoplasmic TERT/nuclear TERT for the primary tumor of the 6-10B cell line was almost six-fold higher than that of the metastatic lymph nodes of the 5-8F cell line. TERT translocation from the cytoplasm to nucleus may present a critical step in the lymphatic metastasis of NPC. Thus, TERT translocation may be more useful than TERT expression level and telomerase activity for predicting the metastasis of NPC.

Quantum dot-based immunofluorescent imaging of Ki67 and identification of prognostic value in HER2-positive (non-luminal) breast cancer

BACKGROUND

The immunohistochemical assessment of Ki67 antigen (Ki67) is the most widely practiced measurement of breast cancer cell proliferation; however, it has some disadvantages and thus the prognostic value of Ki67 in breast cancer remains controversial. Our previous studies confirmed the advantages of quantum dots-based nanotechnology for quantitative analysis of biomarkers compared with conventional immunohistochemistry (IHC). This study was designed to assess Ki67 by quantum dot-immunohistochemistry (QD-IHC) and investigate the prognostic value of the Ki67 score in human epidermal growth factor receptor 2 (HER2)-positive (non-luminal) breast cancer.

METHODS

Ki67 expression in 108 HER2-positive (non-luminal) breast cancer specimens was detected by IHC and QD-IHC. Two observers assessed the Ki67 score independently and comparisons between the two methods were made. The prognostic value of the Ki67 score for five-year disease-free survival was estimated.

RESULTS

The same antigen localization, high correlation of staining rates (r=0.993), and high agreement of measurements (κ=0.874) of Ki67 expression (cutoff: 30%) in breast cancer were found by QD-IHC and conventional IHC. The QD-IHC had a better interobserver agreement for the Ki67 score than conventional IHC (t=-7.280, P<0.01). High Ki67 expression (cutoff: 30%) was associated with shorter disease-free survival (log-rank test; IHC, P=0.026; QD-IHC, P=0.001), especially in the lymph node-negative subgroups (log-rank test; IHC, P=0.017; QD-IHC, P=0.002).

CONCLUSION

QD-IHC imaging of Ki67 was an easier and more accurate method for detecting and assessing Ki67. The Ki67 score was an independent prognosticator in the HER2-positive (non-luminal) breast cancer patients.

Near-infrared quantum dots for HER2 localization and imaging of cancer cells

Background

Quantum dots are fluorescent nanoparticles with unique photophysical properties that allow them to be used as diagnostic, therapeutic, and theranostic agents, particularly in medical and surgical oncology. Near-infrared-emitting quantum dots can be visualized in deep tissues because the biological window is transparent to these wavelengths. Their small sizes and free surface reactive groups that can be conjugated to biomolecules make them ideal probes for in vivo cancer localization, targeted chemotherapy, and image-guided cancer surgery. The human epidermal growth factor receptor 2 gene (HER2/neu) is overexpressed in 25%–30% of breast cancers. The current methods of detection for HER2 status, including immunohistochemistry and fluorescence in situ hybridization, are used ex vivo and cannot be used in vivo. In this paper, we demonstrate the application of near-infrared-emitting quantum dots for HER2 localization in fixed and live cancer cells as a first step prior to their in vivo application.

Methods

Near-infrared-emitting quantum dots were characterized and their in vitro toxicity was established using three cancer cell lines, ie, HepG2, SK-BR-3 (HER2-overexpressing), and MCF7 (HER2-underexpressing). Mouse antihuman anti-HER2 monoclonal antibody was conjugated to the near-infrared-emitting quantum dots.

Results

In vitro toxicity studies showed biocompatibility of SK-BR-3 and MCF7 cell lines with near-infrared-emitting quantum dots at a concentration of 60 μg/mL after one hour and 24 hours of exposure. Near-infrared-emitting quantum dot antiHER2-antibody bioconjugates successfully localized HER2 receptors on SK-BR-3 cells.

Conclusion

Near-infrared-emitting quantum dot bioconjugates can be used for rapid localization of HER2 receptors and can potentially be used for targeted therapy as well as image-guided surgery.

Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications

Background

Hormone receptors, including the estrogen receptor and progesterone receptor, human epidermal growth factor receptor 2 (HER2), and other biomarkers like Ki67, epidermal growth factor receptor (EGFR, also known as HER1), the androgen receptor, and p53, are key molecules in breast cancer. This study evaluated the relationship between HER2 and hormone receptors and explored the additional prognostic value of Ki67, EGFR, the androgen receptor, and p53.

Methods

Quantitative determination of HER2 and EGFR was performed in 240 invasive breast cancer tissue microarray specimens using quantum dot (QD)-based nanotechnology. We identified two subtypes of HER2, ie, high total HER2 load (HTH2) and low total HER2 load (LTH2), and three subtypes of hormone receptor, ie, high hormone receptor (HHR), low hormone receptor (LHR), and no hormone receptor (NHR). Therefore, breast cancer patients could be divided into five subtypes according to HER2 and hormone receptor status. Ki67, p53, and the androgen receptor were determined by traditional immunohistochemistry techniques. The relationship between hormone receptors and HER2 was investigated and the additional value of Ki67, EGFR, the androgen receptor, and p53 for prediction of 5-year disease-free survival was assessed.

Results

In all patients, quantitative determination showed a statistically significant (P<0.001) negative correlation between HER2 and the hormone receptors and a significant positive correlation (P<0.001) between the estrogen receptor and the progesterone receptor (r=0.588), but a significant negative correlation (P<0.001, r=−0.618) with the HHR subtype. There were significant differences between the estrogen receptor, progesterone receptor, and HER2 subtypes with regard to total HER2 load and hormone receptor subtypes. The rates of androgen receptor and p53 positivity were 46.3% and 57.0%, respectively. Other than the androgen receptor, differences in expression of Ki67, EGFR, and p53 did not achieve statistical significance (P>0.05) between the five subtypes. EGFR and Ki67 had prognostic significance for 5-year disease-free survival in univariate analysis, but the androgen receptor and p53 did not. Multivariate analysis identified that EGFR expression had predictive significance for 5-year disease-free survival in hormone-receptor positive patients and in those with the lymph node-positive breast cancer subtype.

Conclusion

Hormone receptor expression was indeed one of the molecular profiles in the subtypes identified by quantitative HER2 and vice versa. EGFR status may provide discriminative prognostic information in addition to HER2 and hormone receptor status, and should be integrated into routine practice to help formulate more specific prediction of the prognosis and appropriate individualized treatment.

Quantitative assessment of Tn antigen in breast tissue micro-arrays using CdSe aqueous quantum dots

In this study, we examined the use of CdSe aqueous quantum dots (AQDs) each conjugated to three streptavidin as a fluorescent label to image Tn antigen expression in various breast tissues via a sandwich staining procedure where the primary monoclonal anti-Tn antibody was bound to the Tn antigen on the tissue, a biotin-labeled secondary antibody was bound to the primary anti-Tn antibody, and finally the streptavidin-conjugated AQDs were bound to the biotin on the secondary antibody. We evaluated the AQD staining of Tn antigen on tissue microarrays consisting of 395 cores from 115 cases including three tumor cores and one normal-tissue core from each breast cancer case and three tumor cores from each benign case. The results indicated AQD-Tn staining was positive in more than 90% of the cells in the cancer cores but not the cells in the normal-tissue cores and the benign tumor cores. As a result, AQD-Tn staining exhibited 95% sensitivity and 90% specificity in differentiating breast cancer against normal breast tissues and benign breast conditions. These results were better than the 90% sensitivity and 80% specificity exhibited by the corresponding horse radish peroxidase (HRP) staining using the same antibodies on the same tissues and those of previous studies that used different fluorescent labels to image Tn antigen. In addition to sensitivity and specificity, the current AQD-Tn staining with a definitive threshold was quantitative.

Computer-based image studies on tumor nests mathematical features of breast cancer and their clinical prognostic value

Background

The expending and invasive features of tumor nests could reflect the malignant biological behaviors of breast invasive ductal carcinoma. Useful information on cancer invasiveness hidden within tumor nests could be extracted and analyzed by computer image processing and big data analysis.

Methods

Tissue microarrays from invasive ductal carcinoma (n = 202) were first stained with cytokeratin by immunohistochemical method to clearly demarcate the tumor nests. Then an expert-aided computer analysis system was developed to study the mathematical and geometrical features of the tumor nests. Computer recognition system and imaging analysis software extracted tumor nests information, and mathematical features of tumor nests were calculated. The relationship between tumor nests mathematical parameters and patients' 5-year disease free survival was studied.

Results

There were 8 mathematical parameters extracted by expert-aided computer analysis system. Three mathematical parameters (number, circularity and total perimeter) with area under curve >0.5 and 4 mathematical parameters (average area, average perimeter, total area/total perimeter, average (area/perimeter)) with area under curve <0.5 in ROC analysis were combined into integrated parameter 1 and integrated parameter 2, respectively. Multivariate analysis showed that integrated parameter 1 (P = 0.040) was independent prognostic factor of patients' 5-year disease free survival. The hazard risk ratio of integrated parameter 1 was 1.454 (HR 95% CI [1.017–2.078]), higher than that of N stage (HR 1.396, 95% CI [1.125–1.733]) and hormone receptor status (HR 0.575, 95% CI [0.353–0.936]), but lower than that of histological grading (HR 3.370, 95% CI [1.125–5.364]) and T stage (HR 1.610, 95% CI [1.026 –2.527]).

Conclusions

This study indicated integrated parameter 1 of mathematical features (number, circularity and total perimeter) of tumor nests could be a useful parameter to predict the prognosis of early stage breast invasive ductal carcinoma.

Multispectral Imaging

The field of anatomic pathology has changed significantly over the last decades and, as a result of the technological developments in molecular pathology and genetics, has had increasing pressures put on it to become quantitative and to provide more information about protein expression on a cellular level in tissue sections. Multispectral imaging (MSI) has a long history as an advanced imaging modality and has been used for over a decade now in pathology to improve quantitative accuracy, enable the analysis of multicolor immunohistochemistry, and drastically reduce the impact of contrast-robbing tissue autofluorescence common in formalin-fixed, paraffin-embedded tissues. When combined with advanced software for the automated segmentation of different tissue morphologies (eg, tumor vs stroma) and cellular and subcellular segmentation, MSI can enable the per-cell quantitation of many markers simultaneously. This article covers the role that MSI has played in anatomic pathology in the analysis of formalin-fixed, paraffin-embedded tissue sections, discusses the technological aspects of why MSI has been adopted, and provides a review of the literature of the application of MSI in anatomic pathology.

In vitro invasive pattern of hepatocellular carcinoma cell line HCCLM9 based on three-dimensional cell culture and quantum dots molecular imaging

This study aimed to establish a new in vitro three-dimensional (3D) cell culture and use quantum dots (QDs) molecular imaging to examine the invasive behaviors of hepatocellular carcinoma (HCC) cells. Each well of the 24-well cell culture plate was cover-slipped. Matrigel diluted with serum-free DMEM was added and HCCLM9 cells were cultured on the Matrigel. The cell morphological and cell growth characteristics were observed by inverted microscopy and laser confocal microscopy at different culture time. Cell invasive features were monitored by QDs-based real-time molecular imaging techniques. The results showed that on this 3D cell culture platform, HCCLM9 cells exhibited typical multi-step invasive behaviors, including reversion of cell senescence, active focal proliferation and dominant clones invasion. During the process, cells under 3D cell culture showed biological behaviors of spatio-temporal characteristics. Cells first merged on the surface of matrix, then gradually infiltrated and migrated into deep part of matrix, presenting polygonal morphology with stretched protrusions, forming tubular, annular and even network structure, which suggested that HCC cells have the morphological basis for vasculogenic mimicry. In addition, small cell clones with their edges well-circumscribed in early stage, progressed into a large irregular clone with ill-defined edge, while the other cells developed invadopodia. And QDs probing showed MT1-MMP was strongly expressed in the invadopodia. These findings indicate that a novel 3D cell culture platform has been successfully established, which can mimic the in vivo tumor microenvironment, and when combined with QDs-based molecular imaging, it can help to better investigate the invasive behaviors of HCC cells.

Quantum dots for cancer research: current status, remaining issues, and future perspectives

Cancer is a major threat to public health in the 21st century because it is one of the leading causes of death worldwide. The mechanisms of carcinogenesis, cancer invasion, and metastasis remain unclear. Thus, the development of a novel approach for cancer detection is urgent, and real-time monitoring is crucial in revealing its underlying biological mechanisms. With the optical and chemical advantages of quantum dots (QDs), QD-based nanotechnology is helpful in constructing a biomedical imaging platform for cancer behavior study. This review mainly focuses on the application of QD-based nanotechnology in cancer cell imaging and tumor microenvironment studies both in vivo and in vitro, as well as the remaining issues and future perspectives.

Telomerase reverse transcriptase promotes the proliferation of human laryngeal carcinoma cells through activation of the activator protein 1

TERT is the main functional unit of telomerase, which maintains telomere length and chromosome structure stability. TERT has been shown to act as a key factor in various biological processes, such as cell proliferation, via uncharacterized mechanisms. We transfected HEp-2 laryngeal carcinoma cells with a TERT overexpressing adenovirus (Ad-TERT) and TERT shRNA silencing adenovirus (Ad-sh-TERT), and examined the effect on TERT and the AP-1 transcription factor subunits c-Fos and c-Jun using RT-PCR and western blot analysis. TERT mRNA expression was quantified using RT-PCR in 24 human laryngeal carcinoma samples, and TERT protein co-expression with AP-1 was investigated in a human laryngeal carcinoma tissue microarray using quantum-dot based immunofluorescence. The effect of specific ERK and p38 inhibitors on ERK, p38, c-Jun and c-Fos phosphorylation was investigated in TERT-overexpressing HEp-2 cells. TERT overexpression led to increased TERT, c-Jun and c-Fos mRNA and protein expression and increased cell proliferation, while TERT silencing had the opposite effects. TERT mRNA expression levels were positively correlated with c-Fos and c-Jun mRNA in human laryngeal carcinoma tissue. TERT and AP-1 protein were expressed at high levels and positively correlated in laryngeal carcinoma tissues. Treatment of TERT-overexpressing HEp-2 cells with specific p38 and ERK inhibitors indicated that TERT modulates the expression and phosphorylation of the AP-1 subunits c-Jun and c-Fos through the p38 and ERK signaling pathways. In conclusion, the results of this study indicate that TERT is capable of promoting cell proliferation via activation of the AP-1 subunits, c-Jun and c-Fos, in laryngeal carcinoma cells.

Semiconductor quantum dots for bioimaging and biodiagnostic applications

Semiconductor quantum dots (QDs) are light-emitting particles on the nanometer scale that have emerged as a new class of fluorescent labels for chemical analysis, molecular imaging, and biomedical diagnostics. Compared with traditional fluorescent probes, QDs have unique optical and electronic properties such as size-tunable light emission, narrow and symmetric emission spectra, and broad absorption spectra that enable the simultaneous excitation of multiple fluorescence colors. QDs are also considerably brighter and more resistant to photobleaching than are organic dyes and fluorescent proteins. These properties are well suited for dynamic imaging at the single-molecule level and for multiplexed biomedical diagnostics at ultrahigh sensitivity. Here, we discuss the fundamental properties of QDs; the development of next-generation QDs; and their applications in bioanalytical chemistry, dynamic cellular imaging, and medical diagnostics. For in vivo and clinical imaging, the potential toxicity of QDs remains a major concern. However, the toxic nature of cadmium-containing QDs is no longer a factor for in vitro diagnostics, so the use of multicolor QDs for molecular diagnostics and pathology is probably the most important and clinically relevant application for semiconductor QDs in the immediate future.

Tapping the potential of quantum dots for personalized oncology: current status and future perspectives

Cancer is one of the most serious health threats worldwide. Personalized oncology holds potential for future cancer care in clinical practice, where each patient could be delivered individualized medicine on the basis of key biological features of an individual tumor. One of the most urgent problems is to develop novel approaches that incorporate the increasing molecular information into the understanding of cancer biological behaviors for personalized oncology. Quantum dots are a heterogeneous class of engineered fluorescent nanoparticles with unique optical and chemical properties, which make them promising platforms for biomedical applications. With the unique optical properties, the utilization of quantum dot-based nanotechnology has been expanded into a wide variety of attractive biomedical applications for cancer diagnosis, monitoring, pathogenesis, treatment, molecular pathology and heterogeneity in combination with cancer biomarkers. Here, we focus on the clinical application of quantum dot-based nanotechnology in personalized oncology, covering topics on individualized cancer diagnosis and treatment by in vitro and in vivo molecular imaging technologies, and in-depth understanding of the biological behaviors of tumors from a nanotechnology perspective. In addition, the major challenges in translating quantum dot-based nanotechnology into clinical application and promising future directions in personalized oncology are also discussed.

Digital image analysis: a review of reproducibility, stability and basic requirements for optimal results

Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides optimized for light microscopy and the human eye. With improved technical methods and the acknowledgement that computerized readings are different from analysis by human eye, recognition has been achieved that to really empower DIA, histological slides must be optimized for the digital 'eye', with reproducible results correlating with clinical findings. In this review, we focus on the basic expectations and requirements for DIA to gain wider use in histopathological research and diagnostics. With a reference to studies that specifically compare DIA with conventional methods, this review discusses reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques.

Quantum dots in cancer therapy

INTRODUCTION

Quantum dots (QDs) are nanometer-size luminescent semiconductor nanocrystals. Their unique optical properties, such as high brightness, long-term stability, simultaneous detection of multiple signals and tunable emission spectra, make them appealing as potential diagnostic and therapeutic systems in the field of oncology.

AREAS COVERED

This paper summarizes the recent progress of promising applications of QDs in cancer therapy, from the following aspects: identifying molecular targets, sentinel lymph-node mapping, surgical oncology, drug delivery and tracking, fluorescence resonance energy transfer and photodynamic therapy, personalized and predictive medicine, and multifunctional design and development. Limitations and toxicity issues related to QDs in living organisms are also discussed.

EXPERT OPINION

Bioconjugated QDs can be used to identify potential molecular biomarkers for cancer diagnosis, treatment and prognosis. They may allow the surgeon to map sentinel lymph nodes and perform a complete surgical resection. Their unique optical properties make them ideal donors of fluorescence resonance energy transfer and photodynamic therapy studies. Multifunctional QDs have become effective materials for synchronous cancer diagnosis, targeting and treatment. For QDs, toxicity remains the major barrier to clinical translation.

Quantum dot-based quantitative immunofluorescence detection and spectrum analysis of epidermal growth factor receptor in breast cancer tissue arrays

BACKGROUND

The epidermal growth factor receptor (EGFR) is a promising therapeutic target in cancer, but its clinical value in breast cancer remains controversial. Our previous studies have found that quantitative analysis of biomarkers with quantum dot-based nanotechnology had better detection performance than conventional immunohistochemistry. The present study was undertaken to investigate the prognostic value of EGFR in breast cancer using quantum dot-based quantitative spectral analysis.

METHODS

EGFR expression in 65 breast cancer specimens was detected by immunohistochemistry and quantum dot-immunohistochemistry, and comparisons were made between the two methods. EGFR expression in tissue microarrays of 240 breast cancer patients was then detected by quantum dot-immunohistochemistry and spectral analysis. The prognostic value of EGFR immunofluorescence area (EGFR area) for five-year recurrence-free survival was investigated.

RESULTS

The same antigen localization, high correlation of staining rates (r = 0.914), and high agreement of measurement (κ = 0.848) of EGFR expression in breast cancer were found by quantum dot-immunohistochemistry and immunohistochemistry. The EGFR area showed significant differences by tumor grade, lymph node status, HER2 status, and hormone receptor status (all P < 0.05). Patients in the large EGFR area (≥ 30.51) group had a significantly higher five-year recurrence rate (47.2% versus 27.4%, P = 0.002) and worse five-year recurrence-free survival (log-rank test, P = 0.0015) than those in the small EGFR area (<30.51) group. In the subgroups, EGFR area was an independent prognosticator in the HER2-positive and lymph node-positive subgroups.

CONCLUSION

Quantum dot-based quantitative detection demonstrates the prognostic value of EGFR area in the HER2-positive and lymph node-positive subgroups of invasive breast cancer.

Quantum dots-based molecular classification of breast cancer by quantitative spectroanalysis of hormone receptors and HER2

The emerging molecular breast cancer (BC) classification based on key molecules, including hormone receptors (HRs), and human epidermal growth factor receptor 2 (HER2) has been playing an important part of clinical practice guideline. The current molecular classification mainly based on their fingerprints, however, could not provide enough essential information for treatment decision making. The molecular information on both patterns and quantities could be more helpful to heterogeneities understanding for BC personalized medicine. Here we conduct quantitative determination of HRs and HER2 by quantum dots (QDs)-based quantitative spectral analysis, which had excellent consistence with traditional method. Moreover, we establish a new molecular classification system of BC by integrating the quantitative information of HER2 and HRs, which could better reveal BC heterogeneity and identify 5 molecular subtypes with different 5-year prognosis. Furthermore, the emerging 5 molecular subtypes based on simple quantitative molecules information could be as informative as multi-genes analysis in routine practice, and might help formulate a more personalized comprehensive therapy strategy and prognosis prediction.

Quantum dots-based double-color imaging of HER2 positive breast cancer invasion

It has been well recognized that human epidermal growth factor receptor 2 (HER2) level in breast cancer (BC) is closely related to the malignant biologic behaviors of the tumor, including invasion and metastasis. Yet, there has been a lack of directly observable evidence to support such notion. Here we report a quantum dots (QDs)-based double-color imaging technique to simultaneously show the HER2 level on BC cells and the type IV collagen in the tumor matrix. In benign breast tumor, the type IV collagen was intact. With the increasing of HER2 expression level, there has been a progressive decrease in type IV collagen around the cancer nest. At HER2 (3+) expression level, there has virtually been a total destruction of type IV collagen. Moreover, HER2 (3+) BC cells also show direct invasion into the blood vessels. This novel imaging method provides direct observable evidence to support the theory that the HER2 expression level is directly related to BC invasion.

Detection of cancer cells in the cerebrospinal fluid: current methods and future directions

The spread of cancer into the central nervous system is a serious problem leading to neurological symptoms and rapid mortality. The current tools available for detecting the spread of cancer into the cerebrospinal fluid (CSF) are cytology, neurologic examination, and neuroimaging. All three of these methods can be applied in concert to reach a diagnosis, but they all suffer from a lack of sensitivity, leading to delays in treatment in many cases. An overview of research tools in the field of CSF cancer detection reveals a variety of promising technologies that can be used to answer questions about the biology of metastatic cancer and to develop more powerful clinical detection methods. Methods currently under investigation include new immunocytochemistry methods and flow cytometry for the in vitro detection of cells. Additionally, polymerase chain reaction, fluorescence in situ hybridization, capillary electrophoresis with laser-induced fluorescence, and mass spectrometry using matrix-assisted laser absorption-deionization time-of-flight and surface-enhanced laser desorption/ionization time-of-flight techniques are being tested for in vitro assessment of the non-cellular biomarkers in CSF. For in vivo detection of cancer in the CSF, research techniques include certain quantum dot platforms as well as magnetic iron oxide nanoparticles. As systemic therapies for cancer improve, the CNS is becoming a more common site of disease recurrence. This increases the importance of effective detection methods in the CSF, since early intervention can maximize therapeutic benefit. Furthermore, many cell-based detection methods can be combined with therapeutic agents to serve multiple medical functions through a common targeting system.