Jing-Ping Yuan

Collagen as a double-edged sword in tumor progression

It has been recognized that cancer is not merely a disease of tumor cells, but a disease of imbalance, in which stromal cells and tumor microenvironment play crucial roles. Extracellular matrix (ECM) as the most abundant component in tumor microenvironment can regulate tumor cell behaviors and tissue tension homeostasis. Collagen constitutes the scaffold of tumor microenvironment and affects tumor microenvironment such that it regulates ECM remodeling by collagen degradation and re-deposition, and promotes tumor infiltration, angiogenesis, invasion and migration. While collagen was traditionally regarded as a passive barrier to resist tumor cells, it is now evident that collagen is also actively involved in promoting tumor progression. Collagen changes in tumor microenvironment release biomechanical signals, which are sensed by both tumor cells and stromal cells, trigger a cascade of biological events. In this work, we discuss how collagen can be a double-edged sword in tumor progression, both inhibiting and promoting tumor progression at different stages of cancer development.

Recognition and capture of metastatic hepatocellular carcinoma cells using aptamer-conjugated quantum dots and magnetic particles

Metastatic recurrence is the most important biological behavior of hepatocellular carcinoma (HCC) and the main cause of treatment failure. Early prediction of metastasis is currently impossible due to the lack of specific molecular probes to recognize metastatic HCC cells. Aptamers have recently emerged as promising potential molecular probes for biomedical applications. Two well-matched HCC cell lines including HCCLM9 with high metastatic potential and MHCC97-L with low metastatic potential, were used to select aptamers for HCC metastasis. With a whole-cell-SELEX strategy, in which HCCLM9 cells were used as target cells and MHCC97-L cells as subtractive cell, 6 potential aptamers had been generated. Detailed study on selected aptamer LY-1 revealed that it could bind metastatic HCC cells with high affinity and specificity, not only in cells culture and animal models of HCC metastasis, but also in clinical HCC specimens. Moreover, the aptamer LY-1 and magnetic particles conjugates could efficiently capture the HCC cells from complex mixture whole blood. These studies demonstrated that this HCC specific aptamer LY-1 could be a promising molecular probe to recognize metastatic HCC cells.

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.

Segmentation of Hematoxylin-Eosin stained breast cancer histopathological images based on pixel-wise SVM classifier

Hematoxylin-Eosin (HE) staining is the routine diagnostic method for breast cancer (BC), and large amounts of HE stained histopathological images are available for analysis. It is emergent to develop computational methods to efficiently and objectively analyze these images, with the aim of providing potentially better diagnostic and prognostic information for BC. This work focus on analyzing our in-house HE stained histopathological images of breast cancer tissues. Since tumor nests (TNs) and stroma morphological characteristics can reflect the biological behaviors of breast invasive ductal carcinoma (IDC), accurate segmentation of TNs and the stroma is the first step towards the subsequent quantitative analysis. We first propose a method based on the pixel-wise support vector machine (SVM) classifier for segmenting TNs and the stroma, then extract four morphological characters related to the TNs from the images and investigate their relationships with the patients’ 8-year disease free survival (8-DFS). The evaluation result shows that the classification based segmentation method is able to distinguish between TNs and stroma with 87.1% accuracy and 80.2% precision, suggesting that the proposed method is promising in segmenting HE stained IDC histopathological images. The Kaplan-Meier survival curves show that three morphological characters (number of TNs, total perimeter, and average area of TNs) in the images have statistical correlations with 8-DFS of the patients, illustrating that the segmented images can help to identify new morphological factors in IDC TNs for the prediction of BC prognosis.抽象创新点苏木素-伊红 (Hematoxylin-Eosin, HE) 染色组织病理图像分析是乳腺癌的常规诊断方法. 随着数字病理的发展, 病理实验室采集了大量数字化HE组织病理图像, 迫切需要开发基于计算机的高效客观的病理图像分析方法. 医学领域认为病理图像中癌巢和间质的形态学特征可以反映乳腺浸润性导管癌的生物学行为趋势, 因此精确分割癌巢和间质是计算机辅助分析的基础. 本文将图像分割问题看作是像素点的分类问题, 提出了一种基于像素级特征的支持向量机分类算法来识别癌巢/间质像素点, 从而实现癌巢-间质的分割. 基于此算法, 我们对本实验采集的HE 染色病理图像进行分割, 结果显示该算法在分割癌巢-间质时有87.1%的准确率和80.2%的精度. 我们提取出癌巢的4个形态学特征, Kaplan-Meier生存分析揭示其中三个癌巢形态学特征(癌巢数量、 癌巢总周长以及癌巢平均面积)与患者8年无病生存期 (8-DFS) 具有显著的统计相关性, 该结果表明该分割算法有助于鉴别乳腺浸润性导管癌新的病理学形态预后因子.

Quantum dot-based multiplexed imaging in malignant ascites: a new model for malignant ascites classification.

Purpose The aims of this study are to establish a new method for simultaneously detecting the interactions between cancer cells and immunocytes in malignant ascites (MA) and to propose a new model for MA classification. Methods A quantum dot (QD)-based multiplexed imaging technique was developed for simultaneous in situ imaging of cancer cells, lymphocytes, and macrophages. This method was first validated in gastric cancer tissues, and then was applied to MA samples from 20 patients with peritoneal carcinomatosis from gastrointestinal and gynecological origins. The staining features of MA and the interactions between cancer cells and immunocytes in the ascites were further analyzed and correlated with clinical features. Results The QD-based multiplexed imaging technique was able to simultaneously show gastric cancer cells, infiltrating macrophages, and lymphocytes in tumor tissue, and the technique revealed the distinctive features of the cancer tumor microenvironment. When this multiplexed imaging protocol was applied to MA cytology, different features of the interactions and quantitative relations between cancer cells and immunocytes were observed. On the basis of these features, MA could be classified into immunocyte-dominant type, immunocyte-reactive type, cancer cell-dominant type, and cell deletion type; the four categories were statistically different in terms of the ratio of cancer cells to immunocytes (P<0.001). Moreover, in the MA, the ratio of cancer cells to immunocytes was higher for patients with gynecological and gastric cancers than for those with colorectal cancer. Conclusion The newly developed QD-based multiplexed imaging technique was able to better reveal the interactions between cancer cells and immunocytes. This advancement allows for better MA classification and, thereby, allows for treatment decisions to be more individualized.

Tumor invasion unit in gastric cancer revealed by QDs-based in situ molecular imaging and multispectral analysis.

In tumor tissues, cancer cells, tumor infiltrating macrophages and tumor neo-vessels in close spatial vicinity with one another form tumor invasion unit, which is a biologically important tumor microenvironment of metastasis to facilitate cancer invasion and metastasis. Establishing an in situ molecular imaging technology to simultaneously reveal these three components is essential for the in-depth investigation of tumor invasion unit. In this report, we have developed a computer-aided algorithm by quantum dots (QDs)-based multiplexed molecular imaging technique for such purpose. A series of studies on gastric cancer tumor tissues demonstrated that the tumor invasion unit was correlated with major unfavorable pathological features and worse clinical outcomes, which illustrated the significantly negative impacts and predictive power of tumor invasion unit on patient overall survival. This study confirmed the technical advantages of QDs-based in situ and simultaneous molecular imaging of key cancer molecules to gain deeper insights into the biology of cancer invasion.

A Clinical Database of Breast Cancer Patients Reveals Distinctive Clinico-pathological Characteristics: a Study From Central China

BACKGROUND Breast cancer is the most common malignant tumor in females worldwide. Many differences exist in clinico-pathological characteristics of breast cancer patients between China and Western countries. This study aimed to analyze clinico-pathological characteristics of breast cancer from central China. METHODS Clinico- pathological information on breast cancer from three hospitals in central China was collected and analyzed. RESULTS From 1994 to 2012, 2,525 patients with a median age 50 years were included in this study. The 45-49-year age group and invasive ductal carcinoma not otherwise specified accounted for the highest proportions (19.1%, 480/2,525 and 81.0%, 1,982/2,446). Stages 0-I, II and III accounted for 28.0% (682/2,441), 48.4% (1,180/2,441), and 23.7% (578/2,441), respectively. Distribution of N stage showed that N0 accounted for 53.2% (1,344/2,525), and proportion of N0 rose from 51.1% (157/307) in 30-39-year age group to 64.3% (110/171) in ≥ 70-year age group, with an average increase of 2.1% in each age group. Modified radical mastectomy, radical mastectomy, breast-conserving surgery and simple mastectomy were performed for 71.8% (1,812/2,525), 18.0% (454/2,525), 5.2% (131/2,525) and 2.6% (66/2,525), respectively. Proportions of breast-conserving surgery in age ≤ 44-year group (68/132, 51.5%) and simple mastectomy in age ≥ 60-year group (57/89, 64.0%) were higher than in the other age groups. Breast cancers positive for estrogen receptor accounted for 53.0% (1,107/ 2,112). The comparisons among this study and other reports showed higher proportion of younger patients, lower proportion of breast- conserving surgery and positive estrogen receptor patients in China than western countries. CONCLUSIONS Clinico-pathological characteristics in this study demonstrated clear differences between the center of China than Western countries. Additional classification systems should be developed to guide grading of early breast cancer more accurately, especially for N0 patients. Invasive ductal carcinoma is a focus for intensive research.

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.

Quantum dot-based multispectral fluorescent imaging to quantitatively study co-expressions of Ki67 and HER2 in breast cancer.

Both Ki67 and HER2 are key prognostic molecules for invasive breast cancer (BC), but the individual relative impacts on prognosis of these molecules are not known. This study was aimed at establishing a quantum dot (QD)-based double-color in-situ quantitative imaging technique to study the co-expressions of Ki67 and HER2, and delineate the individual impacts of these molecules on prognosis. The QD-based fluorescent immunostaining technique could simultaneously image the co-expressions of Ki67 and HER2 in BC specimens, with the former stained as clear red fluorescence in cancer cell nucleus, and the latter as bright green fluorescence on cancer cell membrane. Both Ki67 and HER2 expressions were significantly correlated with 8-year disease free survival (8-DFS) (P<0.05). However, the two molecules had different weights in terms of negative impacts on clinical prognosis. The median 8-DFS was statistically significantly shorter in High-Ki67 High-HER2 subgroup than Low-Ki67 High-HER2 subgroup (11.7 vs. 60.1months, P<0.05), shorter in High-Ki67 Low-HER2 subgroup than Low-Ki67 Low-HER2 subgroup (16.4 vs. 96.0months, P<0.01), shorter in High-Ki67 High-HER2 subgroup than Low-Ki67 Low-HER2 subgroup (11.7 vs. 96.0months, P<0.01), but there were no statistically significant differences in median 8-DFS between High-Ki67 Low-HER2 subgroup and High-Ki67 High-HER2 subgroup (11.7 vs. 16.4months, P=0.586). The hazard ratio (HR) of Ki67 negative impact on 8-DFS was about 3 fold of that of HER2 (HR 4.493 vs. 1.481). This study demonstrated that QD-based fluorescent imaging technique could help the quantitative study on the co-expressions of Ki67 and HER2 in BC, and Ki67 has a greater negative impact on BC prognosis than HER2.

Coevolution of the tumor microenvironment revealed by quantum dot-based multiplexed imaging of hepatocellular carcinoma

AIM This study aimed to provide new insights into the mechanisms of hepatocellular carcinoma (HCC) invasion by simultaneously imaging tumor cells and major components of the tumor microenvironment. MATERIALS & METHODS Formalin-fixed paraffin-embedded human HCC tissues were studied by conventional immunohistochemistry and quantum dot-based multiplexed imaging to reveal type IV collagen, LOX and tumor angiogenesis. RESULTS Type IV collagen degradation and repatterning in the extracellular matrix (ECM) was a continuous process, making the ECM harder, although more fragile and less resistant to cancer invasion. The distribution of LOX among cancer nests was heterogeneous, with higher expression in small cancer nests and lower expression in large cancer nests. LOX expression in cancer cells was associated with rigid stroma and tumor angiogenesis. Tumor angiogenesis occurred with type IV collagen presence. At the cancer invasion front, the ECM was hydrolyzed, with the prominent linear reorientation of type IV collagen surrounding cancer nests adjacent to neovessels. CONCLUSION The visualization of the temporal-spatial relationship between type IV collagen, LOX and tumor angiogenesis revealed the coevolution process of HCC cells and their microenvironment, emphasizing an active role of the ECM during cancer invasion.