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Tumor cells can modify the immune response in primary tumors and in the axillary lymph nodes with metastasis (ALN+) in breast cancer (BC), influencing patient outcome. We investigated whether patterns of immune cells in the primary tumor and in the axillary lymph nodes without metastasis (ALN-) differed between patients diagnosed without ALN+ (diagnosed-ALN-) and with ALN+ (diagnosed-ALN+) and the implications for clinical outcome. Eleven immune markers were studied using immunohistochemistry, tissue microarray, and digital image analysis in 141 BC patient samples (75 diagnosed-ALN+ and 66 diagnosed-ALN-). Two logistic regression models were derived to identify the clinical, pathologic, and immunologic variables associated with the presence of ALN+ at diagnosis. There are immune patterns in the ALN- associated with the presence of ALN+ at diagnosis. The regression models revealed a small subgroup of diagnosed-ALN+ with ALN- immune patterns that were more similar to those of the ALN- of the diagnosed-ALN-. This small subgroup also showed similar clinical behavior to that of the diagnosed-ALN-. Another small subgroup of diagnosed-ALN- with ALN- immune patterns was found whose members were more similar to those of the ALN- of the diagnosed-ALN+. This small subgroup had similar clinical behavior to the diagnosed-ALN+. These data suggest that the immune response present in ALN- at diagnosis could influence the clinical outcome of BC patients.

Background The axillary lymph nodes (ALNs) in breast cancer patients are the body regions to where tumoral cells most often first disseminate. The tumour immune response is important for breast cancer patient outcome, and some studies have evaluated its involvement in ALN metastasis development. Most studies have focused on the intratumoral immune response, but very few have evaluated the peritumoral immune response. The aim of the present article is to evaluate the immune infiltrates of the peritumoral area and their association with the presence of ALN metastases. Methods The concentration of 11 immune markers in the peritumoral areas was studied in 149 patients diagnosed with invasive breast carcinoma of no special type (half of whom had ALN metastasis at diagnosis) using tissue microarrays, immunohistochemistry and digital image analysis procedures. The differences in the concentration of the immune response of peritumoral areas between patients diagnosed with and without metastasis in their ALNs were evaluated. A multivariate logistic regression model was developed to identify the clinical-pathological variables and the peritumoral immune markers independently associated with having or not having ALN metastases at diagnosis. Results No statistically significant differences were found in the concentrations of the 11 immune markers between patients diagnosed with or without ALN metastases. Patients with metastases in their ALNs had a higher histological grade, more lymphovascular and perineural invasion and larger-diameter tumours. The multivariate analysis, after validation by bootstrap simulation, revealed that only tumour diameter (OR = 1.04; 95% CI [1.00–1.07]; p = 0.026), lymphovascular invasion (OR = 25.42; 95% CI [9.57–67.55]; p p = 0.033) and 3 (OR = 5.18; 95% CI [1.40–19.17]; p = 0.014) were associated with the presence of ALN metastases at diagnosis. This study is one of the first to study the association of the peritumoral immune response with ALN metastasis. We did not find any association of peritumoral immune infiltrates with the presence of ALN metastasis. Nevertheless, this does not rule out the possibility that other peritumoral immune populations are associated with ALN metastasis. This matter needs to be examined in greater depth, broadening the types of peritumoral immune cells studied, and including new peritumoral areas, such as the germinal centres of the peritumoral tertiary lymphoid structures found in extensively infiltrated neoplastic lesions.

Background: Digital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented. Methods: The first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures. Results and conclusions: There was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.

Introduction Lymph nodes are one of the main sites where an effective immune response develops. Normally, axillary nodes are the first place where breast cancer produces metastases. Several studies have demonstrated the importance of immune cells, especially dendritic cells, in the evolution of breast cancer. The goal of the project is to identify differences in the patterns of immune infiltrates, with particular emphasis on dendritic cells, in tumour and axillary node biopsies between patients with and without metastases in the axillary nodes at the time of diagnosis. It is expected that these differences will be able to explain differences in survival, relapse and clinicopathological variables between the two groups. Methods and analysis The study will involve 100 patients diagnosed with invasive breast cancer between 2000 and 2007, 50% of whom have metastases in the axillary lymph node at diagnosis. In selected patients, two cylinders from biopsies of representative areas of tumour and axillary nodes (with and without metastasis) will be selected and organised in tissue microarrays. Samples will be stained using immunohistochemical techniques for different markers of immune response and dendritic cells. Two images of each cylinder will be captured under standardised conditions for each marker. Each marker will be quantified automatically by digital image procedures using Image-Pro Plus and Image-J software. Associations of survival, relapse and other clinicopathological variables with the automatically quantified levels of immune infiltrates in patients with and without axillary node metastasis will be sought. Ethics and dissemination The present project has been approved by the Clinical Research Ethics Committee of the Hospital Universitari Joan XXIII (Ref: 22p/2011). Those patients whose biopsies and clinical data are to be used will give their signed informed consent. Results will be published in peer-reviewed journals.

The “removal” of background from digital images (DIs) to identify only the objects of interest is difficult due to the overlapping color values of pixels of the nuclei and background. We outline a new automated procedure to quantify only immunohistochemically stained nuclear markers, despite the similar color of the background. This procedure was compared with the gold standard manual method and a previous method developed for low-background DIs.

In the current practice of pathology, the evaluation of immunohistochemical (IHC) markers represents an essential tool. The manual quantification of these markers is still laborious and subjective, and the use of computerized systems for digital image (DI) analysis has not yet resolved the problems of nuclear aggregates (clusters). Furthermore, the volume of DI storage continues to be an important problem in computer-assisted pathology. In the present study we have developed an automated procedure to quantify IHC nuclear markers in DI with a high level of clusters. Furthermore the effects of JPEG compression in the image analysis were evaluated. The results indicated that there was an agreement with the results of both methods (automated vs. manual) in almost 90% of the analyzed images. On the other hand, automated count differences increase as the compression level increase, but only in images with a high number of stained nuclei (nuclei/image) or with high area cluster (25μm2). Some corrector factors were developed in order to correct this count differences. In conclusion, the proposed automated procedure is an objective, faster than manual counting and reproducible method that has more than 90% of similarity with manual count. Moreover, the results demonstrate that with correction factors, it is possible to carry out unbiased automated quantifications on IHC nuclear markers in compressed DIs.

Hodgkin's lymphoma represents one of the most frequent lymphoproliferative syndromes, especially in young population. Although HL is considered one of the most curable tumors, a sizeable fraction of patients recur after successful upfront treatment or, less commonly, are primarily resistant. This work tries to summarize the data on clinical, histological, pathological, and biological factors in HL, with special emphasis on the improvement of prognosis and their impact on therapeutical strategies. The recent advances in our understanding of HL biology and immunology show that infiltrated immune cells and cytokines in the tumoral microenvironment may play different functions that seem tightly related with clinical outcomes. Strategies aimed at interfering with the crosstalk between tumoral Reed-Sternberg cells and their cellular partners have been taken into account in the development of new immunotherapies that target different cell components of HL microenvironment. This new knowledge will probably translate into a change in the antineoplastic treatments in HL in the next future and hopefully will increase the curability rates of this disease.

Background: Digital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented. Methods: The first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures. Results and conclusions: There was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.