Matrix Metalloproteinase-9 Expression Is Associated with the Absence of Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Patients.

Triple-negative breast cancer (TNBC) is particularly challenging due to the weak or absent response to therapeutics and its poor prognosis. The effectiveness of neoadjuvant chemotherapy (NAC) response is strongly influenced by changes in elements of the tumor microenvironment (TME). This work aimed to characterize the residual TME composition in 96 TNBC patients using immunohistochemistry and in situ hybridization techniques and evaluate its prognostic implications for partial responders vs. non-responders. Compared with non-responders, partial responders containing higher levels of CD83+ mature dendritic cells, FOXP3+ regulatory T cells, and IL-15 expression but lower CD138+ cell concentration exhibited better OS and RFS. However, along with tumor diameter and positive nodal status at diagnosis, matrix metalloproteinase-9 (MMP-9) expression in the residual TME was identified as an independent factor associated with the impaired response to NAC. This study yields new insights into the key components of the residual tumor bed, such as MMP-9, which is strictly associated with the lack of a pathological response to NAC. This knowledge might help early identification of TNBC patients less likely to respond to NAC and allow the establishment of new therapeutic targets.

Prognostic Implications of the Residual Tumor Microenvironment after Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Patients without Pathological Complete Response.

With a high risk of relapse and death, and a poor or absent response to therapeutics, the triple-negative breast cancer (TNBC) subtype is particularly challenging, especially in patients who cannot achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Although the tumor microenvironment (TME) is known to influence disease progression and the effectiveness of therapeutics, its predictive and prognostic potential remains uncertain. This work aimed to define the residual TME profile after NAC of a retrospective cohort with 96 TNBC patients by immunohistochemical staining (cell markers) and chromogenic in situ hybridization (genetic markers). Kaplan-Meier curves were used to estimate the influence of the selected TME markers on five-year overall survival (OS) and relapse-free survival (RFS) probabilities. The risks of each variable being associated with relapse and death were determined through univariate and multivariate Cox analyses. We describe a unique tumor-infiltrating immune profile with high levels of lymphocytes (CD4, FOXP3) and dendritic cells (CD21, CD1a and CD83) that are valuable prognostic factors in post-NAC TNBC patients. Our study also demonstrates the value of considering not only cellular but also genetic TME markers such as MUC-1 and CXCL13 in routine clinical diagnosis to refine prognosis modelling.

CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients.

BACKGROUND: The foremost cause of death of breast cancer (BC) patients is metastasis, and the first site to which BC predominantly metastasizes is the axillary lymph node (ALN). Thus, ALN status is a key prognostic indicator at diagnosis. The immune system has an essential role in cancer progression and dissemination, so its evaluation in ALNs could have significant applications. In the present study we aimed to investigate the association of clinical-pathological and immune variables in the primary tumour and non-metastatic ALNs (ALNs-) of a cohort of luminal A and triple-negative BC (TNBC) patients with cancer-specific survival (CSS) and time to progression (TTP). METHODS: We analysed the differences in the variables between patients with different outcomes, created univariate and multivariate Cox regression models, validated them by bootstrapping and multiple imputation of missing data techniques, and used Kaplan-Meier survival curves for a 10-years follow-up. RESULTS: We found some clinical-pathological variables at diagnosis (tumour diameter, TNBC molecular profile and presence of ALN metastasis), and the levels of several immune markers in the two studied sites, to be associated with worse CSS and TTP. Nevertheless, only CD68 and CD83 in ALNs- were confirmed as independent prognostic factors for TTP. CONCLUSIONS: The study identified the importance of macrophage and dendritic cell markers as prognostic factors of relapse for BC. We highlight the importance of studying the immune response in ALNs-, which could be relevant to the prediction of BC patients' outcome.

Differences in the Immune Response of the Nonmetastatic Axillary Lymph Nodes between Triple-Negative and Luminal A Breast Cancer Surrogate Subtypes.

Breast cancer (BC) comprises four immunohistochemical surrogate subtypes of which triple-negative breast cancer (TNBC) has the highest risk of mortality. Axillary lymph nodes (ALNs) are the regions where BC cells first establish before distant metastasis, and the presence of tumor cells in the ALN causes an immune tolerance profile that contrasts with that of the nonmetastatic ALN (ALN-). However, few studies have compared the immune components of the ALNs- in BC subtypes. The present study aimed to determine whether differences between immune populations in the primary tumor and ALNs- were associated with the luminal A or TNBC subtype. We evaluated a retrospective cohort of 144 patients using paraffin-embedded biopsies. The TNBC samples tended to have a higher histologic grade and proliferation index and had higher levels of immune markers compared with luminal A in primary tumors and ALNs-. Two methods for validating the multivariate analysis found that histologic grade, intratumoral S100 dendritic cells, and CD8 T lymphocytes and CD57 natural killer cells in the ALNs- were factors associated with TNBC, whereas CD83 dendritic cells in the ALNs- were associated with the luminal A subtype. In conclusion, we found that intratumoral regions and ALNs- of TNBC contained higher concentrations of markers related to immune tolerance than luminal A. This finding partially explains the worse prognosis of patients with TNBC.

Night-time heart rate cut-off point definition by resting office tachycardia in untreated hypertensive patients: data of the Spanish ABPM registry.

OBJECTIVE: Epidemiological studies have shown that an elevated resting heart rate (HR) is a risk factor for both total and cardiovascular mortality. Our aim was to estimate the night-time HR cut-off point that best predicts cardiovascular risk office tachycardia in hypertensive patients. DESIGN AND METHOD: Untreated hypertensive patients without concomitant cardiovascular diseases were included. Office and ambulatory HRs were measured. Cardiovascular risk office tachycardia was defined by office HR at least 85 beats per minute (bpm). Different night-time HR cut-offs were estimated by receiver operating characteristic curve analyses to predict cardiovascular risk office tachycardia. The best cut-off was selected on the basis of its combined sensitivity and specificity. RESULTS: A total of 32 569 hypertensive patients were included: 46.5% women, mean age (SD) 52 (14) years, office blood pressure 146 (16)/89 (11) mmHg, diabetes 10.3%, smoking 19.2%, BMI 29 (6.8) kg/m, office HR 77 (11.2) bpm, and night-time HR 64.9 (9.3) bpm. A total of 7070 (21.7%) patients were found to have cardiovascular risk office tachycardia. The night-time HR value that better predicted cardiovascular risk office tachycardia was more than 66 bpm. In comparison with patients with night HR below this value, those with night-time tachycardia were predominantly women, younger, with higher ambulatory blood pressure, greater BMI, and higher prevalence of diabetes and smoking. All comparisons were statistically significant (P less than 0.001). CONCLUSION: A mean night-time HR more than 66 bpm is a good predictor of cardiovascular risk office tachycardia in untreated hypertensive patients and could be considered a variable associated with an increased cardiovascular risk.

Digital image analysis in breast cancer: an example of an automated methodology and the effects of image compression.

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.