Background: Morphological evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer is gaining momentum as an immunological biomarker. This experiment evaluates the role of TILs in distant tumors as a measure of abscopal effect from cryoablation of breast cancer. Methods: BALB/c mice underwent bilateral orthotopic transplant with 4T1-12B (triple-negative) cells. At 2 weeks, left tumors were treated by either resection (standard of care group) or cryoablation (intervention group) followed by resection of the distant right tumors 1 week posttreatment. TIL scores were calculated from hematoxylin and eosin-stained sections and phenotyped for cytotoxic T-lymphocyte (CTL) markers by immunofluorescence. Primarily resected tumors served as baseline (T_baseline), whereas resected distant right-sided served as the readout for abscopal effect (Abs_Res or Abs_Cryo). Mice were monitored for tumor recurrence and metastasis. Results: The Abs_Cryo had a significant mean (SD) increase in stromal (2.8 [1.1]%; p = 0.015) and invasive margin TILs (50 [12]%; p = 0.02) compared with T_Baseline (1.0 [0]% and 31 [4.9]%, respectively). CTL phenotyping revealed a significant increase in mean (SD) CD8⁺ T cells (15.7 [12.1]; p = 0.02) and granzyme B (4.8 [3.6]; p = 0.048) for the Abs_Cryo compared with T_Baseline (5.2 [4.7] and 2.4 [0.9], respectively). Posttreatment, the cryoablation group had no recurrence or metastasis, whereas the resected group showed local recurrence and lung metastasis in 40% of the mice. Postprocedure increase in TIL score of distant tumors was associated with decrease in tumor relapse (p = 0.02). Conclusions: Cryoablation induced a robust tumor-specific TIL response compared with resection, suggesting an abscopal effect leading to the prevention of cancer recurrence and metastasis.

Detection of tumor-infiltrating lymphocytes (TILs) in cancer images has gained significant importance as these lymphocytes can be used as a biomarker in cancer detection and treatment procedures. Our goal was to develop and apply a TILs detection tool that utilizes deep learning models, following two sequential steps. First, based on the guidelines from the International Immuno-Oncology Biomarker Working Group (IIOBWG) on Breast Cancer, we labeled 63 large pathology imaging slides and annotated the TILs in the stroma area to create the dataset required for model development. In the second step, various machine learning models were employed and trained to detect the stroma where U-Net deep learning structure was able to achieve 98% accuracy. After detecting the stroma area, a Mask R-CNN model was employed for the TILs detection task. The R-CNN model detected the TILs in various images and was used as the backbone analysis network for the GUI development of the TILs detection tool. This is the first study to combine two deep learning models for TILs detection at the cellular level in breast tumor histopathology slides. Our novel approach can be applied to scoring TILs in large cancer slides. Statistical analysis showed that the output of the implemented approach had 95% concordance with the scores assigned by the pathologists, with a p-value of 0.045 (n = 63). This demonstrated that the results from the developed software were statistically meaningful and highly accurate. The implemented approach in analyzing whole tumor histology slides and the newly developed TILs detection tool can be used for research purposes in biomedical and pathology applications and it can provide researchers and clinicians with the TIL score for various input images. Future research using additional breast cancer slides from various sources for further training and validation of the developed models is necessary for more inclusive, rigorous, and robust clinical applications.

Background: Widespread use of screening mammography has allowed breast cancer to be detected at earlier stages. This allows for increased customization of treatment and less aggressive management. De-escalation of therapy plays an important role in decreasing treatment burden and improving patient quality of life. This report examines cryoablation as the next step in the surgical de-escalation of breast cancer. Methods: Women with a diagnosis of clinically node-negative, estrogen receptor-positive (ER +), progesterone receptor-positive (PR +), human epidermal growth factor receptor 2-negative (HER2 −) infiltrating ductal carcinomas 1.5 cm or smaller underwent ultrasound-guided cryoablation. Either the Visica 2 treatment system (before 2020) or the ProSense treatment system (since 2020) was used to perform the cryoablation. Patients received mammograms and ultrasounds at a 6 months follow-up visit, and magnetic resonance images at baseline, then at 1 year follow-up intervals. Adjuvant therapy decisions and disease status were recorded. Results: This study enrolled 32 patients who underwent 33 cryoablation procedures (1 patient had bilateral cancer). One patient had a sentinel node biopsy in addition to clinical staging of the axilla. For all the patients, adjuvant endocrine therapy was recommended, and six patients (18.75%) received adjuvant radiation. Of the 32 patients, 20 (60.6%) have been followed up for 2 years or longer, with no residual or recurrent disease at the site of ablation. Conclusion: Cryoablation of the primary tumor foregoing sentinel node biopsy offers an oncologically safe and feasible minimally invasive office-based procedure option in lieu of surgery for patients with early-stage, low-risk breast cancer.