scholarly journals Prognostic and predictive value of tumor-infiltrating lymphocytes in breast cancer (literature review)

2021 ◽  
Vol 4 (1) ◽  
pp. 39-44
Author(s):  
M.O. Bilych
Keyword(s):  
Breast Cancer ◽  
Predictive Factor ◽  
Predictive Value ◽  
Tumor Infiltrating Lymphocytes ◽  
Breast Cancer Subtypes ◽  
Cancer Type ◽  
Primary Tumors ◽  
Positive Correlation ◽  
Cancer Subtypes ◽  
Infiltrating Lymphocytes

Background. Breast cancer is the leading cancer type in women. Improvement in its management requires a continuous investigation of new tools for diagnosis and treatment. Biomarkers for breast cancer remain a field of great interest, despite existing knowledge. Extensive research recognizes the critical role played by tumor-infiltrating lymphocytes (TILs) in terms of prognosis and prediction, but much uncertainty still exists about the application of this biomarker in clinical practice. Thus, the purpose of this paper is to review recent researches about the role of TILs as a prognostic and predictive factor in the clinical management of breast cancer subtypes. Materials and methods. Eligible studies from Medline, Pubmed, Google Scholar (2010–2020) databases were analyzed and retrieved. Results. For primary tumors, a positive correlation was found between TILs and survival prognosis for HER2+ and TNBC subtypes, while for luminal subtypes it was a negative correlation. The predictive value of TILs in the neoadjuvant setting is established for HER2+, TNBC subtypes. In the case of using TILs as a predictive factor for HER2-targeted therapy, it remains a concern due to controversial data. For residual tumor, it is growing body of evidence about the positive correlation of TILs and prognosis for all subtypes, but data are limited. Conclusions. TILs were found to have prognostic and predictive value. However, due to the heterogeneity of breast cancer subtypes, TILs as a biomarker should be interpreted with caution. Further studies need to be carried out to determine the validity of making a clinical decision based on TILs count.

scholarly journals Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data

2020 ◽  
pp. 480-490 ◽  
Author(s):  
Zixiao Lu ◽  
Siwen Xu ◽  
Wei Shao ◽  
Yi Wu ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Strong Association ◽  
Tumor Infiltrating Lymphocytes ◽  
Genetic Alterations ◽  
Image Features ◽  
Cancer Immunology ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Subtypes ◽  
Cancer Subtypes ◽  
Infiltrating Lymphocytes

PURPOSE Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers. However, fully automatic assessment of TILs on WSIs currently remains a great challenge because of the heterogeneity and large size of WSIs. We present an automatic pipeline based on a cascade-training U-net to generate high-resolution TIL maps on WSIs. METHODS We present global cell-level TIL maps and 43 quantitative TIL spatial image features for 1,000 WSIs of The Cancer Genome Atlas patients with breast cancer. For more specific analysis, all the patients were divided into three subtypes, namely, estrogen receptor (ER)–positive, ER-negative, and triple-negative groups. The associations between TIL scores and gene expression and somatic mutation were examined separately in three breast cancer subtypes. Both univariate and multivariate survival analyses were performed on 43 TIL image features to examine the prognostic value of TIL spatial patterns in different breast cancer subtypes. RESULTS The TIL score was in strong association with immune response pathway and genes (eg, programmed death-1 and CLTA4). Different breast cancer subtypes showed TIL score in association with mutations from different genes suggesting that different genetic alterations may lead to similar phenotypes. Spatial TIL features that represent density and distribution of TIL clusters were important indicators of the patient outcomes. CONCLUSION Our pipeline can facilitate computational pathology-based discovery in cancer immunology and research on immunotherapy. Our analysis results are available for the research community to generate new hypotheses and insights on breast cancer immunology and development.

The value of tumor-infiltrating lymphocytes and CD8 expression as a predictor of response to anthracycline-based neoadjuvant chemotherapy in invasive breast carcinoma of no special type

2021 ◽  
pp. 1-6
Author(s):  
Upik A. Miskad ◽  
Rizki A. Rifai ◽  
Rina Masadah ◽  
Berti Nelwan ◽  
Djumadi Ahmad ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune System ◽  
Breast Carcinoma ◽  
Neoadjuvant Chemotherapy ◽  
Predictive Value ◽  
Disease Free Survival ◽  
Tumor Infiltrating Lymphocytes ◽  
Invasive Breast Carcinoma ◽  
Study Results ◽  
Infiltrating Lymphocytes

BACKGROUND: The immune system is known to play an important role in tumor cell eradication. Although cancer cells were able to escape from the immune system, many studies showed mononuclear inflammatory cell infiltrates known as tumor-infiltrating lymphocytes (TILs) on breast cancer histopathology specimens showed better prognosis, including in disease-free survival (DFS) and chemotherapy responses. OBJECTIVE: This study aimed to reveal the predictive value of tumor-infiltrating lymphocytes (TILs) levels and CD8 expression in invasive breast carcinoma of no special type patients’ samples on response to anthracycline-based neoadjuvant chemotherapy. METHODS: 75 pre-treatment biopsy samples that were diagnosed as invasive breast carcinoma of no special type were evaluated. TILs level determined following recommendations of International TILs Working Group 2014, CD8 expression assessed semiquantitatively after immunohistochemistry staining. Response to anthracycline-based neoadjuvant chemotherapy evaluated clinically using Response Evaluation Criteria in Solid Tumours (RECIST) criteria and pathologically by evaluating hematoxylin and eosin (H&E)-stained slides from mastectomy specimens after 3 or 4 cycles of neoadjuvant chemotherapy. RESULTS: Chi-squared analysis showed a significant relationship between TILs level and CD8 expression with chemotherapy responses clinically (p = 0.011 and p = 0.017 respectively) but not pathologically. Furthermore, the logistic regression test exhibit the predictive value of TILs level was 66.7% and CD8 expression was 64%. CONCLUSIONS: This study results suggest that TILs level and CD8 expression may be added as predictive factors to the response of anthracycline-based neoadjuvant chemotherapy, and oncologists may take benefit in breast cancer patient’s management.

Prognostic and predictive value of tumor infiltrating lymphocytes in early breast cancer

2016 ◽  
Vol 50 ◽  
pp. 205-207 ◽  
Author(s):  
Carmen Criscitiello ◽  
Angela Esposito ◽  
Dario Trapani ◽  
Giuseppe Curigliano
Keyword(s):  
Breast Cancer ◽  
Early Breast Cancer ◽  
Predictive Value ◽  
Tumor Infiltrating Lymphocytes ◽  
Infiltrating Lymphocytes

Number of tumor-infiltrating lymphocytes in breast cancer brain metastases compared to matched breast primaries.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 2049-2049 ◽  
Author(s):  
Jessie Narloch ◽  
Catherine Luedke ◽  
Gloria Broadwater ◽  
Nolan Priedigkeit ◽  
Allison Hall ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Metastasis ◽  
Brain Metastases ◽  
Tumor Infiltrating Lymphocytes ◽  
Cox Proportional Hazards Model ◽  
Her2 Status ◽  
Primary Tumors ◽  
Metastatic Setting ◽  
Breast Cancer Brain Metastasis ◽  
Infiltrating Lymphocytes

2049 Background: Breast cancer brain metastasis (BCBM) is frequent in advanced disease, has limited therapies, and is associated with poor prognosis. Increased stromal tumor infiltrating lymphocytes (sTILs) are prognostic in triple-negative breast cancer (TNBC) and predictive of therapeutic response in early breast cancer (BC). However, little is known about sTILs in the metastatic setting. We compared %sTILs between the largest known cohort of matched primary tumors and BCBM and correlated the results with clinical endpoints. Methods: We retrospectively investigated 37 matched primary tumors and BCBM tissue from three institutions. In addition, we identified 29 primary tumors from patients later diagnosed with BCBM. H&E-stained sections were manually measured for %sTILs using standard criteria. Wilcoxon signed rank tests assessed for changes in %sTILs between primary and metastatic lesions. A Cox proportional hazards model was used to determine if %sTILs in the breast tissue predicts time from primary tumor biopsy to diagnosis of brain metastasis (TTDBM) while adjusting for clinicopathologic features. Results: Average age at time of BCBM diagnosis was 53.6 (SD 12.3). 52% (34/66) of primary tumors were hormone receptor (HR) positive. Of 60 patients with known HER2 status, 28% (17) were HER2 positive and 40% (24) TNBC. Median %sTILS was significantly different between all primary tumors (15, IQR 5-20) and brain metastases (10, IQR 5-10), p = 0.001. The TNBC subtype (n = 11) showed the largest decrease in %sTILs between primary tumors (20, IQR 10-20) and brain metastases (5, IQR 5-10), p = 0.022. Comparing primary tumors and brain metastases, there was a 5% decrease in %sTILs in HR-/HER2+ (n = 5, p = 0.13) and HR+/HER2- (n = 7, p = 0.13), and a 5% increase in %sTILs in the HR+/Her2+ subtype (n = 9, p = 0.69). Percent sTILs in the primary tumors was not a significant predictor of TTDBM, when adjusting for race, age, HR status, and HER2 status, p = 0.87. Conclusions: BCBM have a significantly decreased %sTILs compared to their primary tumors, most prominent in TNBC. These results suggest altered tumor immunogenicity in the metastatic setting which has broad implications for the development of immunotherapy.

Sign in / Sign up

Export Citation Format

Share Document