Automatic tumor-stroma separation in fluorescence TMAs enables the quantitative high-throughput analysis of multiple cancer biomarkers

The upcoming quantification and automation in biomarker based histological tumor evaluation will require computational methods capable of automatically identifying tumor areas and differentiating them from the stroma. As no single generally applicable tumor biomarker is available, pathology routinely uses morphological criteria as a spatial reference system. We here present and evaluate a method capable of performing the classification in immunofluorescence histological slides solely using a DAPI background stain. Due to the restriction to a single color channel this is inherently challenging. We formed cell graphs based on the topological distribution of the tissue cell nuclei and extracted the corresponding graph features. By using topological, morphological and intensity based features we could systematically quantify and compare the discrimination capability individual features contribute to the overall algorithm. We here show that when classifying fluorescence tissue slides in the DAPI channel, morphological and intensity based features clearly outpace topological ones which have been used exclusively in related previous approaches. We assembled the 15 best features to train a support vector machine based on Keratin stained tumor areas. On a test set of TMAs with 210 cores of triple negative breast cancers our classifier was able to distinguish between tumor and stroma tissue with a total overall accuracy of 88%. Our method yields first results on the discrimination capability of features groups which is essential for an automated tumor diagnostics. Also, it provides an objective spatial reference system for the multiplex analysis of biomarkers in fluorescence immunohistochemistry.     

Development of a Preclinical Orthotopic Xenograft Model of Ewing Sarcoma and Other Human Malignant Bone Disease Using Advanced In Vivo Imaging

Ewing sarcoma and osteosarcoma represent the two most common primary bone tumours in childhood and adolescence, with bone metastases being the most adverse prognostic factor. In prostate cancer, osseous metastasis poses a major clinical challenge. We developed a preclinical orthotopic model of Ewing sarcoma, reflecting the biology of the tumour-bone interactions in human disease and allowing in vivo monitoring of disease progression, and compared this with models of osteosarcoma and prostate carcinoma. Human tumour cell lines were transplanted into non-obese diabetic/severe combined immunodeficient (NSG) and Rag2^−/−/γc^−/− mice by intrafemoral injection. For Ewing sarcoma, minimal cell numbers (1000–5000) injected in small volumes were able to induce orthotopic tumour growth. Tumour progression was studied using positron emission tomography, computed tomography, magnetic resonance imaging and bioluminescent imaging. Tumours and their interactions with bones were examined by histology. Each tumour induced bone destruction and outgrowth of extramedullary tumour masses, together with characteristic changes in bone that were well visualised by computed tomography, which correlated with post-mortem histology. Ewing sarcoma and, to a lesser extent, osteosarcoma cells induced prominent reactive new bone formation. Osteosarcoma cells produced osteoid and mineralised “malignant” bone within the tumour mass itself. Injection of prostate carcinoma cells led to osteoclast-driven osteolytic lesions. Bioluminescent imaging of Ewing sarcoma xenografts allowed easy and rapid monitoring of tumour growth and detection of tumour dissemination to lungs, liver and bone. Magnetic resonance imaging proved useful for monitoring soft tissue tumour growth and volume. Positron emission tomography proved to be of limited use in this model. Overall, we have developed an orthotopic in vivo model for Ewing sarcoma and other primary and secondary human bone malignancies, which resemble the human disease. We have shown the utility of small animal bioimaging for tracking disease progression, making this model a useful assay for preclinical drug testing.     

Immunodetection and clinico-pathological correlates of two tumour growth regulators in laryngeal carcinoma

Activation of telomerase, present in the vast majority of all human cancers, is associated with elongation of chromosomal telomeres and consequent cell immortalization. Telomere length homeostasis is a dynamic process governed by the negative feedback mechanism of the telomeric repeat binding factor 1 (TRF1) which inhibits the action of telomerase in telomerase-positive cells. In an attempt to investigate markers of tumour growth as possible prognostic indicators in laryngeal cancer, we studied the expression of TRF1 and of the proliferation marker Ki67 on 96 invasive squamous carcinomas of the larynx. A standard three step immunoperoxidase staining method was applied on paraffin sections incubated with appropriate polyclonal antibodies. The percentages of Ki67- and TRF1-immunopositive cancerous cells were calculated by image analysis. Univariate and multivariate statistical analysis of the staining results were performed in order to detect any association of the examined immunomarkers with the tumours' classical clinicopathological variables including nuclear morphometric features as well as with patients' disease-free survival. Ki67 immunostaining was positively linked with advanced patients' age, nodal involvement as well as presence of early recurrence. No relation was found between proliferative fraction and TRF1 immunoexpression. TRF1 was expressed in 55.2% of all cases and was positively linked only to tumour size. Multivariate statistical analysis revealed the presence of lymph nodal metastasis and Ki67 immunopositivity index > or = 20% as significant predictors of relapse. Increased Ki67 immunostaining appears to be a promising marker of tumour aggressiveness in laryngeal cancer. After one point at the tumour's natural history, the maintenance of tumour growth does not seem to depend on cell proliferation but on TRF1 immunoexpression. Whether the latter can be used for the identification of immortalized cells in every-day practice is worth investigating.     

Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed.     

The Prognostic Value of Serum Biomarkers in Localized Bone Sarcoma

OBJECTIVE: Certain biomarkers such as the C-reactive protein, serum albumin, and the neutrophils to lymphocyte ratio are of prognostic significance regarding survival in different types of cancers. Data from sarcoma patients are sparse and mainly derived from soft tissue sarcoma and/or metastatic cases. Adjusting for confounders such as comorbidity and age is an essential safeguard against erroneous conclusions regarding the possible prognostic value of these biomarkers. The aim of this study was to assess the prognostic value of a battery of pretreatment biomarkers in the serum of patients with localized bone sarcomas and to adjust for potential confounders. MATERIAL AND METHODS: All patients diagnosed with localized intermediate and high-grade bone sarcoma during 1994 to 2008 were extracted from the Aarhus Sarcoma Registry. The serum levels of albumin, C-reactive protein, hemoglobin, neutrophils, lymphocytes, and sodium were collected from the patient records. The prognostic values of overall and disease-specific mortality were tested for each individual biomarker as well as for the Glasgow prognostic score (GPS) and for a new composite score incorporating five biomarkers (Aarhus composite biomarker score: ACBS). Adjustments were made for comorbidity as well as other possible prognostic factors, such as size, histological type, margin, chemotherapy, and soft tissue extension, using the Cox proportional hazard model. RESULTS: A total of 172 patients with high- or intermediate-grade localized bone sarcoma were included. Of these patients, 63 were diagnosed with chondrosarcoma and 109 patients with Ewing/osteosarcoma. The median age was 55 years for chondrosarcoma and 19 years for Ewing/osteosarcoma patients. The overall 5-year mortality was 31% [95% confidence interval (CI): 21-44] and 41% (95% CI: 33-51), whereas the 5-year disease-specific mortality was 21% (95% CI: 12-34) and 39% (95% CI: 31-49) for chondrosarcoma and Ewing/osteosarcoma, respectively. Comorbidities were present in 12% of the Ewing/osteosarcoma patients and in 24% of the chondrosarcoma patients. After adjustment for comorbidity and other confounders, it was found that elevated levels of CRP, low hemoglobin, low sodium, high GPS, and high ACBS were associated with increased overall mortality. Furthermore, elevated levels of CRP, low hemoglobin, high GPS, and high ACBS were associated with increased disease-specific mortality. CONCLUSION: Elevated levels of CRP, low hemoglobin, high GPS, and high ACBS were all independent prognostic factors for both overall and disease-specific mortality. ACBS is a new three-level score of five biomarkers, but its value has to be confirmed in an independent data set.     

Semantic Focusing Allows Fully Automated Single-Layer Slide Scanning of Cervical Cytology Slides

Liquid-based cytology (LBC) in conjunction with Whole-Slide Imaging (WSI) enables the objective and sensitive and quantitative evaluation of biomarkers in cytology. However, the complex three-dimensional distribution of cells on LBC slides requires manual focusing, long scanning-times, and multi-layer scanning. Here, we present a solution that overcomes these limitations in two steps: first, we make sure that focus points are only set on cells. Secondly, we check the total slide focus quality. From a first analysis we detected that superficial dust can be separated from the cell layer (thin layer of cells on the glass slide) itself. Then we analyzed 2,295 individual focus points from 51 LBC slides stained for p16 and Ki67. Using the number of edges in a focus point image, specific color values and size-inclusion filters, focus points detecting cells could be distinguished from focus points on artifacts (accuracy 98.6%). Sharpness as total focus quality of a virtual LBC slide is computed from 5 sharpness features. We trained a multi-parameter SVM classifier on 1,600 images. On an independent validation set of 3,232 cell images we achieved an accuracy of 94.8% for classifying images as focused. Our results show that single-layer scanning of LBC slides is possible and how it can be achieved. We assembled focus point analysis and sharpness classification into a fully automatic, iterative workflow, free of user intervention, which performs repetitive slide scanning as necessary. On 400 LBC slides we achieved a scanning-time of 13.9±10.1 min with 29.1±15.5 focus points. In summary, the integration of semantic focus information into whole-slide imaging allows automatic high-quality imaging of LBC slides and subsequent biomarker analysis.     

Phospho-Akt Immunoreactivity in Prostate Cancer: Relationship to Disease Severity and Outcome,Ki67 and Phosphorylated EGFR Expression

Background

In the present study, we have investigated the prognostic usefulness of phosphorylated Akt immunoreactivity (pAkt-IR) in prostate cancer using a well-characterised tissue microarray from men who had undergone transurethral resection due to lower urinary tract symptoms.

Methodology/Principal Findings

pAkt-IR in prostate epithelial and tumour cells was assessed using a monoclonal anti-pAkt (Ser⁴⁷³) antibody. Immunoreactive intensity was determined for 282 (tumour) and 240 (non-mlignant tissue) cases. Tumour pAkt-IR scores correlated with Gleason score, tumour Ki67-IR (a marker of cell proliferation) and tumour phosphorylated epidermal growth factor receptor (pEGFR)-IR. For cases followed with expectancy, a high tumour pAkt-IR was associated with a poor disease-specific survival, and the prognostic information provided by this biomarker was additive to that provided by either (but not both) tumour pEFGR-IR or Ki67-IR. Upon division of the cases with respect to their Gleason scores, the prognostic value of pAkt-IR was seen for patients with Gleason score 8–10, but not for patients with Gleason score 6–7.

Conclusions/Significance

Tumour pAkt-IR is associated with both disease severity and disease-specific survival. However, its clinical use as a biomarker is limited, since it does not provide prognostic information in patients with Gleason scores 6–7.     

Clustering methods applied in the detection of Ki67 hot-spots in whole tumor slide images: An efficient way to characterize heterogeneous tissue-based biomarkers

Whole-slide scanners allow the digitization of an entire histological slide at very high resolution. This new acquisition technique opens a wide range of possibilities for addressing challenging image analysis problems, including the identification of tissue-based biomarkers. In this study, we use whole-slide scanner technology for imaging the proliferating activity patterns in tumor slides based on Ki67 immunohistochemistry. Faced with large images, pathologists require tools that can help them identify tumor regions that exhibit high proliferating activity, called "hot-spots" (HSs). Pathologists need tools that can quantitatively characterize these HS patterns. To respond to this clinical need, the present study investigates various clustering methods with the aim of identifying Ki67 HSs in whole tumor slide images. This task requires a method capable of identifying an unknown number of clusters, which may be highly variable in terms of shape, size, and density. We developed a hybrid clustering method, referred to as Seedlink. Compared to manual HS selections by three pathologists, we show that Seedlink provides an efficient way of detecting Ki67 HSs and improves the agreement among pathologists when identifying HSs. ? 2012 International Society for Advancement of Cytometry.     

Quantitative cytological assessment of Ki67 and AgNORs using computer-digitized image analysis of four clinicopathological breast lesions

Analysis of silver-stained proteins associated with nucleolar organiser regions (AgNORs) is proposed as a marker of cellular proliferation. This study describes the application of AgNORs and Ki67 in breast lesions. Sixty-one cases including fibroadenoma (FA), fibrocystic disease (FCD), ductal carcinoma in situ (DCIS) and invasive carcinoma (IC) were studied by image analysis to evaluate quantitative changes in AgNORs in both Ki67-positive, and Ki67-negative smears. The Ki67 index was assessed. Morphometric features of cell nuclei and AgNORs were determined by digitized computer image analysis (Prodit 5.2). The growth fraction was 5.08 for FA, 5.71 for FCD, 16.75 for DCIS and 23.26 for IC. The mean nuclear area was significantly higher in malignant cells than those of fibroadenoma and fibrocystic disease. In Ki67-positive cells the total area, long axis and number of AgNORs increased progressively across disease groups. Eccentricity of AgNORs and AgNORs: nuclear area ratios were significantly increased in malignant breast lesion in comparison with benign lesion in Ki67 positive cells. In Ki67 negative cells, the highest value of AgNORs was observed in DCIS. The AgNORs: nuclear area ratio demonstrated a statistically significant trend across the disease groups. This study demonstrates that the growth fraction, mean nuclear area and selected AgNORs features have potential for differentiating benign from malignant breast tumours.     

DEVELOPMENT OF ARTIFICIAL NEURAL NETWORKS CAPABLE OF IDENTIFYING CRYPTOSPORIDIUM PARVUM OOCYSTS STAINED WITH 4', 6 DIAMIDINO-2-PHENYLINDOLE

Cryptosporidium parvum is a coccidian protozoan parasite capable of infecting a variety of mammalian hosts, and can cause gastro-enteric disease within humans. C. parvum oocysts were stained with varying concentrations of 4', 6 diamidino-2-phenylindole (DAPI). After microscopic observation, objects of interest were captured using a CCD color digital camera. The microscopic images were classified based on their DAPI stain properties as either DAPI positive or negative. Individual oocysts were cropped, converted to grayscale, applied to a binary threshold filter, and were further processed into a numerical data array. DAPI positive and negative images (100 each) were randomly removed for artificial neural network (ANN) testing. The remaining image data were used for ANN training using a commercially available software program. After training experimentation, a final network design was implemented possessing 95 input, 400 hidden, and 2 output neurons. Additional control image sets (ranging from 165 to 119 images) were collected to better ascertain ANN performance. These images consisted of DAPI positive oocysts and two types of DAPI negative images (either formalin treated oocysts or algal cultures). Selected ANN correctly identified, as a range, 82.4–93.8% of the DAPI positive oocysts, 97–98.2% of the DAPI negative oocysts, and 52.9–57% of the DAPI negative algal cells. The control image sets were unique data, never presented during ANN training. Because of this, combined with the high number of correct image identifications for certain image sets, ANN technology may provide a means to identify C. parvum oocysts through automated analysis.     

Effects of blocking developmental cell death on sexually dimorphic calbindin cell groups in the preoptic area and bed nucleus of the stria terminalis

Background

Malignant melanoma is the most deadly form of skin cancer. Female sex is known to have a protective effect on incidence, tumour characteristics, and mortality from melanoma. However, the potentially modifying effect of sex on the prognostic significance of clinicopathological and investigative factors is generally not taken into consideration in biomarker studies. In this study, we compared the sex-specific distribution and prognostic value of established tumour characteristics and Ki67 expression in 255 cases of incident primary melanoma in a prospective, population-based cohort study.

Methods

The study included 255 incident cases of melanoma, 132 females and 123 males, in the Malm? Diet and Cancer Study. Tumours from 226 (88.6%) cases had been assembled in tissue microarrays. Clinicopathological factors and immunohistochemical Ki67 expression were assessed and correlated with disease-free survival (DFS) and overall survival (OS) using Kaplan-Meier analysis, log rank test and univariable and multivariable Cox regression analyses, stratified for gender. Effect of gender on melanoma-specific survival (MSS) after first recurrence was also analysed.

Results

Women were significantly younger at diagnosis than men (p?=?0.012). The most common tumour sites were the legs in women (37.5%) and the dorsal trunk in men (37.8%). Kaplan-Meier analysis revealed that tumour location had no prognostic impact in women, but in men, location to the frontal trunk was significantly associated with a reduced DFS compared with all other locations combined and location to the dorsal trunk was significantly associated with a prolonged OS. High Ki67 expression was significantly associated with a reduced DFS and OS in men but not in women, also when adjusted for other factors. In men, but not in women, ulceration was an independent prognostic factor for both DFS and OS. MSS after first local, regional or distant recurrence was significantly shorter for men than for women.

Conclusions

The results from this study demonstrate that the prognostic value of tumour location, Ki67 expression and ulceration in melanoma differs according to gender. These findings need to be validated in future studies, as they may help improve prognostication in patients with melanoma. Moreover, our findings demonstrate that sex-stratified analyses add valuable information to biomarker studies.     

Image cytometry of aneuploidy, growth fraction (MoAb Ki-67) and hormone receptors (ER, PR) immunocytochemical assays in breast carcinomas

DNA nuclear content was assessed in human breast carcinomas (n = 132) using image cytometry. Optical density histograms of Feulgen stained cell imprints from fresh tissue samples, subsequently frozen for immunocytochemical assays, were determined by the SAMBA system and used for the DNA index, the ploidy balance (PB) and the proliferation index (PI) computation. The three parameters were correlated to (i) histological data (tumour grade, vascular and/or lymph node invasion) and to (ii) growth fraction (Ki67), hormone receptor antigenic sites (ER, PR) and intramedullar (bone marrow) biopsies and anti-KL1-positive epithelial cells. It was shown that 57% of breast carcinomas were aneuploid. Aneuploidy PI significantly correlated to the criteria of poor prognosis such as high tumour grade, vascular and lymphatic invasion and to increased Ki67-positive cells, and the absence of or low ER and PR. Since image cytometry is easy to handle and perfectly suitable for current diagnostic practice in pathology departments, particularly for tumour cell ploidy assessment and standardized analysis of immunostaining procedures with morphological control of the preparation, we conclude that image cytometry, as performed with the SAMBA, must be regarded as a relevant tool for prognosis evaluation and therapy guidance in individual patients.     

Quantitative image analysis of connective tissue progenitors

OBJECTIVE: To develop an image analysis system to automatically identify colony-forming units (CFUs) in in vitro cell cultures of connective tissue progenitors. This system was designed to quantitatively assess colony morphology and number of colonies in 4-cm(2) culture wells. STUDY DESIGN: Large field-of-view high-resolution fluorescence images of 4',6-diamidino-2-phenylindole (DAPI)- and alkaline phosphatase (AP)-stained bone marrow cell cultures were obtained using an epi-fluorescence microscope and automated scanning stage. Cell nuclei were identified in the DAPI-stained images after removal of fluorescent debris from the image. An Euclidean distance map (EDM) of the segmented cell nuclei was used to cluster cell nuclei into colonies. The automated system was evaluated using 40 tissue culture wells of bone marrow aspirate samples. The results of the automated analysis were compared to the manual tracings of colonies by 3 reviewers. RESULTS: The automated method agreed with all 3 reviewers on average 87.5% of the time. Additionally, reviewers identified other colonies not outlined by the reviewers on average 2.7 times more than the automated method. CONCLUSION: The automated method is a less biased method for identifying CFUs than individual reviewers, it provides more quantitative information about colony morphology than can be obtained manually and it is less time consuming.     

A Comparison of Visual Assessment and Automated Digital Image Analysis of Ki67 Labeling Index in Breast Cancer

Background

Ki67 labeling index (LI) is critical for treatment options and prognosis evaluation in breast cancer. Visual assessment (VA) is widely used to assess Ki67 LI, but has some limitations. In this study, we compared the consistency between VA and automated digital image analysis (DIA) of Ki67 LI in breast cancer, and to evaluate the application value of DIA in Ki67 LI assessment.

Methods

Ki67 immunostained slides of 155 cases of primary invasive breast cancer were eyeballing assessed by five breast pathologists and automated digital image analyzed by one breast pathologist respectively. Two score methods, hot-spot score and average score, were used to choose score areas. The intra-class correlation coefficient (ICC) was used to analyze the consistency between VA and DIA, and Wilcoxon signed-rank test was used to compare the median of paired-difference between VA and DIA values.

Results

(1) A perfect agreement was demonstrated between VA and DIA of Ki67 LI by ICC analysis (P<0.0001) in the whole cohort. A perfect agreement between VA and DIA of Ki67 LI was also showed in G2-G3, ER positive/HER2 negative cases. Average score and hot-spot score methods both demonstrated a perfect concordance between VA and DIA of Ki67 LI. (2) All cases were classified into three groups by VA values (≤10%, 11%-30% and >30% Ki67 LI). The concordance was relatively lower in intermediate Ki67 LI group (11%-30%) compared with high (>30%) Ki67 LI groups according to both methods. (3) All cases were classified into three groups by paired-difference (d) between VA values of hot-spot score and average score (d<5, 5≤d<10, d≥10) to evaluate the correlation between Ki67 staining distribution (heterogeneous or homogenous) and reproducibility of assessment. A perfect agreement was all demonstrated in three groups, and a slightly better Ki67 LI agreement between VA and DIA was indicated in homogenous staining slides than in heterogeneous staining ones. (4) VA values were relatively smaller than DIA values (average score: median of paired-difference -3.72; hot-spot score: median of paired-difference -9.12).

Conclusions

An excellent agreement between VA and DIA of Ki67 LI in breast cancer was demonstrated in the whole mixed cohort, suggesting that VA and DIA both could be used to assess Ki67 LI in clinical practice. Average score and hot-spot score methods both demonstrated a perfect concordance between VA and DIA of Ki67 LI. The almost perfect agreement between VA and DIA was observed in high Ki67 LI cases, displaying a homogenous staining pattern. The consistency between VA and DIA was relatively low in intermediate Ki67 LI group. The heterogeneity of tumors may slightly affect the concordance between VA and DIA of Ki67 LI. Assessment of VA provides lower Ki67 values than DIA, the biological importance of these values are not known at the moment.     

Robust automated tumour segmentation on histological and immunohistochemical tissue images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.     

Establishment of a novel patient-derived Ewing’s sarcoma cell line,NCC-ES1-C1

Ewing’s sarcoma is an aggressive mesenchymal tumor characterized by the presence of a unique EWSR1-FLI1 translocation. Ewing’s sarcoma primarily occurs in the bone and soft tissues. Cell lines enable researchers to investigate the molecular backgrounds of disease and the significance of genetic alterations in relevant cellular contexts. Here, we report the establishment and characterization of a novel Ewing’s sarcoma cell line following primary Ewing’s sarcoma tumor tissue culture. The established cell line was authenticated by DNA microsatellite short tandem repeat analysis, characterized by in vitro assays, and named NCC-ES1-C1. The NCC-ES1-C1 cell line grew well for 15 mo and was subcultured more than 50 times during this period. Characterization of the cells revealed that they were not adherent and showed floating features. In conclusion, we successfully established a novel Ewing’s sarcoma cell line, NCC-ES1-C1, from primary tumor tissue. The cell line has the characteristic EWSR1-FLI1 gene fusion and exhibits aggressive growth in vitro. Thus, the NCC-ES1-C1 cell line will be a useful tool for investigating the mechanisms of disease and the biological role of the EWSR1-FLI1 fusion gene.     

Urokinase Plasminogen Activator Receptor (uPAR) and Plasminogen Activator Inhibitor-1 (PAI-1) Are Potential Predictive Biomarkers in Early Stage Oral Squamous Cell Carcinomas (OSCC)

Oral squamous cell carcinoma (OSCC) is often associated with metastatic disease and a poor 5 year survival rate. Patients diagnosed with small tumours generally have a more favourable outcome, but some of these small tumours are aggressive and lead to early death. To avoid harmful overtreatment of patients with favourable prognosis, there is a need for predictive biomarkers that can be used for treatment stratification. In this study we assessed the possibility to use components of the plasminogen activator (PA) system as prognostic markers for OSCC outcome and compared this to the commonly used biomarker Ki-67. A tissue-micro-array (TMA) based immunohistochemical analysis of primary tumour tissue obtained from a North Norwegian cohort of 115 patients diagnosed with OSCC was conducted. The expression of the biomarkers was compared with clinicopathological variables and disease specific death. The statistical analyses revealed that low expression of uPAR (p = 0.031) and PAI-1 (p = 0.021) in the tumour cells was significantly associated with low disease specific death in patients with small tumours and no lymph node metastasis (T1N0). The commonly used biomarker, Ki-67, was not associated with disease specific death in any of the groups of patients analysed. The conclusion is that uPAR and PAI-1 are potential predictive biomarkers in early stage tumours and that this warrants further studies on a larger cohort of patients.     

Software for quantification of labeled bacteria from digital microscope images by automated image analysis

Automated image analysis software, CellC, was developed and validated for quantification of bacterial cells from digital microscope images. CellC enables automated enumeration of bacterial cells, comparison of total count and specific count images [e.g., 4',6-diamino-2-phenylindole (DAPI) and fluorescence in situ hybridization (FISH) images], and provides quantitative estimates of cell morphology. The software includes an intuitive graphical user interface that enables easy usage as well as sequential analysis of multiple images without user intervention. Validation of enumeration reveals correlation to be better than 0.98 when total bacterial counts by CellC are compared with manual enumeration, with all validated image types. The software is freely available and modifiable: the executable files and MATLAB source codes can be obtained at www. cs. tut.fi/sgn/csb/cellc.     

Ki67与核酸荧光共染在细胞周期研究中的应用

病原微生物与宿主细胞的相互作用是感染过程中的一个重要环节,也是研究肿瘤生物学的一项重要内容。动态研究细胞周期变化对了解病原体作用于细胞具有重要意义。本研究用Ki67/4′,6-二脒基-2-苯基吲哚(4′,6-diamidino-2-phenylindole,DAPI)和Ki67/碘化丙啶(propidium iodide,PI)共染技术分析了小鼠脾细胞的细胞周期变化,并介绍其具体应用。