T cell receptor clonotype in tumor microenvironment contributes to intratumoral signaling network in patients with colorectal cancer.

Single-cell RNA sequencing (scRNA-seq) has contributed to understanding cellular heterogeneity and immune profiling in cancer. The aim of the study was to investigate gene expression and immune profiling in colorectal cancer (CRC) using scRNA-seq. We analyzed single-cell gene expression and T cell receptor (TCR) sequences in 30 pairs of CRC and matched normal tissue. Intratumoral lymphocytes were measured with digital image analysis. CRC had more T cells, epithelial cells, and myeloid cells than normal colorectal tissue. CRCs with microsatellite instability had more abundant T cells than those without microsatellite instability. Immune cell compositions of CRC and normal colorectal tissue were inversely correlated. CD4 + or CD8 + proliferating T cells, CD4 + effector memory T cells, CD8 + naïve T cells, and regulatory T cells of CRC showed higher TCR clonal expansion. Tumor epithelial cells interacted with immune cells more strongly than normal. T cells, myeloid cells, and fibroblasts from CRCs of expanded T cell clonotypes showed increased expression of genes related to TNF and NFKB signaling and T cell activation. CRCs of expanded T cell clonotypes also showed stronger cellular interactions among immune cells, fibroblasts, and endothelial cells. Pro-inflammatory CXCL and TNF signaling were activated in CRCs of expanded T cell clonotype. In conclusion, scRNA-seq analysis revealed different immune cell compositions, differential gene expression, and diverse TCR clonotype dynamics in CRC. TCR clonality expansion is associated with immune activation through T cell signaling and chemokine signaling. Patients with CRCs of expanded clonotype can be promising candidates for immunotherapy.

Expansion of tumor-infiltrating lymphocytes in non-small cell lung cancer: Clinical potential and efficacy in EGFR mutation subsets.

Our study aimed to expand tumor-infiltrating lymphocytes (TILs) from primary non-small cell lung cancers (NSCLCs) and evaluate their reactivity against tumor cells. We expanded TILs from 103 primary NSCLCs using histopathological analysis, flow cytometry, IFN-γ release assays, cell-mediated cytotoxicity assays, and in vivo efficacy tests. TIL expansion was observed in all cases, regardless of EGFR mutation status. There was also an increase in the median CD4+/CD8+ ratio during expansion. In post-rapid expansion protocol (REP) TILs, 13 out of 16 cases, including all three cases with EGFR mutations, exhibited a two-fold or greater increase in IFN-γ secretion. The cytotoxicity assay revealed enhanced tumor cell death in three of the seven cases, two of which had EGFR mutations. In vivo functional testing in a patient-derived xenograft model showed a reduction in tumor volume. The anti-tumor activity of post-REP TILs underscores their potential as a therapeutic option for advanced NSCLC, irrespective of mutation status.

Improved Diagnostic Accuracy of Thyroid Fine-Needle Aspiration Cytology with Artificial Intelligence Technology.

Background: Artificial intelligence (AI) is increasingly being applied in pathology and cytology, showing promising results. We collected a large dataset of whole slide images (WSIs) of thyroid fine-needle aspiration cytology (FNA), incorporating z-stacking, from institutions across the nation to develop an AI model. Methods: We conducted a multicenter retrospective diagnostic accuracy study using thyroid FNA dataset from the Open AI Dataset Project that consists of digitalized images samples collected from 3 university hospitals and 215 Korean institutions through extensive quality check during the case selection, scanning, labeling, and reviewing process. Multiple z-layer images were captured using three different scanners and image patches were extracted from WSIs and resized after focus fusion and color normalization. We pretested six AI models, determining Inception ResNet v2 as the best model using a subset of dataset, and subsequently tested the final model with total datasets. Additionally, we compared the performance of AI and cytopathologists using randomly selected 1031 image patches and reevaluated the cytopathologists' performance after reference to AI results. Results: A total of 10,332 image patches from 306 thyroid FNAs, comprising 78 malignant (papillary thyroid carcinoma) and 228 benign from 86 institutions were used for the AI training. Inception ResNet v2 achieved highest accuracy of 99.7%, 97.7%, and 94.9% for training, validation, and test dataset, respectively (sensitivity 99.9%, 99.6%, and 100% and specificity 99.6%, 96.4%, and 90.4% for training, validation, and test dataset, respectively). In the comparison between AI and human, AI model showed higher accuracy and specificity than the average expert cytopathologists beyond the two-standard deviation (accuracy 99.71% [95% confidence interval (CI), 99.38-100.00%] vs. 88.91% [95% CI, 86.99-90.83%], sensitivity 99.81% [95% CI, 99.54-100.00%] vs. 87.26% [95% CI, 85.22-89.30%], and specificity 99.61% [95% CI, 99.23-99.99%] vs. 90.58% [95% CI, 88.80-92.36%]). Moreover, after referring to the AI results, the performance of all the experts (accuracy 96%, 95%, and 96%, respectively) and the diagnostic agreement (from 0.64 to 0.84) increased. Conclusions: These results suggest that the application of AI technology to thyroid FNA cytology may improve the diagnostic accuracy as well as intra- and inter-observer variability among pathologists. Further confirmatory research is needed.

Persistence and enrichment of dominant T cell clonotypes in expanded tumor-infiltrating lymphocytes of breast cancer.

BACKGROUND: Adoptive cell therapy using tumor-infiltrating lymphocytes (TILs) has shown promising results in cancer treatment, including breast cancer. However, clonal dynamics and clinical significance of TIL expansion ex vivo remain poorly understood. METHODS: We investigated T cell receptor (TCR) repertoire changes in expanded TILs from 19 patients with breast cancer. We compared TCR repertoire of TILs at different stages of expansion, including initial (2W TILs) and rapid expansion (REP TILs), and their overlap with formalin fixed paraffin embedded (FFPE) and peripheral blood. Additionally, we examined differences in TCR repertoire between CD4+ and CD8+ REP TILs. RESULTS: In descending order of proportion, average of 60% of the top 10% clonotypes of FFPE was retained in 2W TIL (60% in TRB, 64.7% in TRA). Among the overlapped clonotypes between 2W TILs and REP TILs, 69.9% was placed in top 30% of 2W TIL. The proportion of clonotypes in 2W TIL and REP TIL showed a significant positive correlation. CD4+ and CD8+ T cells show similar results in diversity and CDR3 length. CONCLUSIONS: Our study traces the changes in TILs repertoire from FFPE to 2W TIL and REP TIL and confirmed that clonotypes with high frequencies in TILs have a high likelihood of maintaining their priority throughout culture process.

Expansion of tumor-infiltrating lymphocytes from head and neck squamous cell carcinoma to assess the potential of adoptive cell therapy.

BACKGROUND: Adoptive transfer of in vitro expanded tumor-infiltrating lymphocytes (TILs) has been effective in regressing several types of malignant tumors. This study assessed the yield and factors influencing the successful expansion of tumor-infiltrating lymphocytes (TILs) from head and neck squamous cell carcinoma (HNSCC), along with their immune phenotypes. METHODS: TILs were expanded from 47 surgically resected HNSCC specimens and their metastasized lymph nodes. The cancer tissues were cut into small pieces (1-2 mm) and underwent initial expansion for 2 weeks. Tumor location, smoking history, stromal TIL percentage, human papillomavirus infection, and programmed death-ligand 1 score were examined for their impact on successful expansion of TILs. Expanded TILs were evaluated by flow cytometry using fluorescence-activated cell sorting. A second round of TIL expansion following the rapid expansion protocol was performed on a subset of samples with successful TIL expansion. RESULTS: TILs were successfully expanded from 36.2% samples. Failure was due to contamination (27.6%) or insufficient expansion (36.2%). Only the stromal TIL percentage was significantly associated with successful TIL expansion (p = 0.032). The stromal TIL percentage also displayed a correlation with the expanded TILs per fragment (r = 0.341, p = 0.048). On flow cytometry analysis using 13 samples with successful TIL expansion, CD4 + T cell dominancy was seen in 69.2% of cases. Effector memory T cells were the major phenotype of expanded CD4 + and CD8 + T cells in all cases. CONCLUSION: We could expand TILs from approximately one-third of HNSCC samples. TIL expansion could be applicable in HNSCC samples with diverse clinicopathological characteristics.

Artificial-Intelligence-Assisted Detection of Metastatic Colorectal Cancer Cells in Ascitic Fluid.

Ascites cytology is a cost-effective test for metastatic colorectal cancer (CRC) in the abdominal cavity. However, metastatic carcinoma of the peritoneum is difficult to diagnose based on biopsy findings, and ascitic aspiration cytology has a low sensitivity and specificity and a high inter-observer variability. The aim of the present study was to apply artificial intelligence (AI) to classify benign and malignant cells in ascites cytology patch images of metastatic CRC using a deep convolutional neural network. Datasets were collected from The OPEN AI Dataset Project, a nationwide cytology dataset for AI research. The numbers of patch images used for training, validation, and testing were 56,560, 7068, and 6534, respectively. We evaluated 1041 patch images of benign and metastatic CRC in the ascitic fluid to compare the performance of pathologists and an AI algorithm, and to examine whether the diagnostic accuracy of pathologists improved with the assistance of AI. This AI method showed an accuracy, a sensitivity, and a specificity of 93.74%, 87.76%, and 99.75%, respectively, for the differential diagnosis of malignant and benign ascites. The diagnostic accuracy and sensitivity of the pathologist with the assistance of the proposed AI method increased from 86.8% to 90.5% and from 73.3% to 79.3%, respectively. The proposed deep learning method may assist pathologists with different levels of experience in diagnosing metastatic CRC cells of ascites.

Factors associated with engraftment success of patient-derived xenografts of breast cancer.

BACKGROUND: Patient-derived xenograft (PDX) models serve as a valuable tool for the preclinical evaluation of novel therapies. They closely replicate the genetic, phenotypic, and histopathological characteristics of primary breast tumors. Despite their promise, the rate of successful PDX engraftment is various in the literature. This study aimed to identify the key factors associated with successful PDX engraftment of primary breast cancer. METHODS: We integrated clinicopathological data with morphological attributes quantified using a trained artificial intelligence (AI) model to identify the principal factors affecting PDX engraftment. RESULTS: Multivariate logistic regression analyses demonstrated that several factors, including a high Ki-67 labeling index (Ki-67LI) (p < 0.001), younger age at diagnosis (p = 0.032), post neoadjuvant chemotherapy (NAC) (p = 0.006), higher histologic grade (p = 0.039), larger tumor size (p = 0.029), and AI-assessed higher intratumoral necrosis (p = 0.027) and intratumoral invasive carcinoma (p = 0.040) proportions, were significant factors for successful PDX engraftment (area under the curve [AUC] 0.905). In the NAC group, a higher Ki-67LI (p < 0.001), lower Miller-Payne grade (p < 0.001), and reduced proportion of intratumoral normal breast glands as assessed by AI (p = 0.06) collectively provided excellent prediction accuracy for successful PDX engraftment (AUC 0.89). CONCLUSIONS: We found that high Ki-67LI, younger age, post-NAC status, higher histologic grade, larger tumor size, and specific morphological attributes were significant factors for predicting successful PDX engraftment of primary breast cancer.

A Nationwide Study on HER2-low Breast Cancer in South Korea: Its Incidence of 2022 Real World Data and the Importance of Immunohistochemical Staining Protocols.

Purpose: Notable effectiveness of trastuzumab deruxtecan (T-DXd) in patients with HER2-low advanced breast cancer (BC) has focused pathologists' attention. We studied the incidence and clinicopathologic characteristics of HER2-low BC, and the effects of immunohistochemistry (IHC) associated factors on HER2 IHC results. Materials and Methods: The Breast Pathology Study Group of the Korean Society of Pathologists conducted a nationwide study using real-world data on HER2 status generated between January 2022 and December 2022. Information on HER2 IHC protocols at each participating institution was also collected. Results: Total 11,416 patients from twenty-five institutions included in this study. Of these patients, 40.7% (range: 6.0%-76.3%) were classified as HER2-zero, 41.7% (range: 10.5%-69.1%) as HER2-low, and 17.5% (range: 6.7%-34.0%) as HER2-positive. HER2-low tumors were associated with positive ER and PR statuses (p<0.001 and p<0.001, respectively). Antigen retrieval times (≥ 36 min vs. < 36 min) and antibody incubation times (≥ 12 min vs. < 12 min) affected on the frequency of HER2 IHC 1+ BC at institutions using the PATHWAY HER2 (4B5) IHC assay and BenchMark XT or Ultra staining instruments. Furthermore, discordant results between core needle biopsy (CNB) and subsequent resection specimen HER2 statuses were observed in 24.1% (787/3259) of the patients. Conclusion: The overall incidence of HER2-low BC in South Korea concurs with those reported in previously published studies. Significant inter-institutional differences in HER2 IHC protocols were observed, and it may have impact on HER2-low status. Thus, we recommend standardizing HER2 IHC conditions to ensure precise patient selection for targeted therapy.

CCR10-mediated Enhancement of T Cell Trafficking for Improved Tumor Immunotherapy.

BACKGROUND/AIM: The effectiveness of adoptive T cell therapy for solid tumors remains suboptimal, partly attributed to insufficient T cell infiltration into the tumor site. A promising strategy involves directing T cells towards the tumor utilizing tumor-specific chemokine receptors. MATERIALS AND METHODS: We analyzed chemokine receptor expression in activated T cells and chemokine expression in breast and lung cancer using The Cancer Genome Atlas (TCGA) data. Subsequently, we generated 1G4 T cell receptor-engineered T (TCR-T) cells with CCR10 and performed in vitro and in vivo efficacy tests. RESULTS: CCR10 exhibited insufficient expression in various human T cells. Analysis of TCGA RNA sequencing data revealed elevated expression of the chemokine CCL28, the corresponding chemokine for CCR10, in breast and lung cancer. Consequently, we generated CCR10-1G4 TCR-T cells. CCR10-1G4 dual expressing TCR-T cells exhibited comparable cellular cytotoxicity but increased mobility compared to 1G4 TCR-T cells in vitro. Furthermore, injecting CCR10-1G4 dual expressing TCR-T cells into a xenograft tumor model demonstrated enhanced in vivo trafficking and a greater reduction of tumor burden. CONCLUSION: This study highlights the potential of CCR10 for developing efficient adoptive T-cell treatments targeting solid tumors.

Proteomic analysis of breast cancer based on immune subtypes.

BACKGROUND: Immunotherapy is applied to breast cancer to resolve the limitations of survival gain in existing treatment modalities. With immunotherapy, a tumor can be classified into immune-inflamed, excluded and desert based on the distribution of immune cells. We assessed the clinicopathological features, each subtype's prognostic value and differentially expressed proteins between immune subtypes. METHODS: Immune subtyping and proteomic analysis were performed on 56 breast cancer cases with neoadjuvant chemotherapy. The immune subtyping was based on the level of tumor-infiltrating lymphocytes (TILs) and Klintrup criteria. If the level of TILs was ≥ 10%, it was classified as immune-inflamed type without consideration of the Klintrup criteria. In cases of 1-9% TIL, Klintrup criteria 1-3 were classified as the immune-excluded subtype and Klintrup criteria not available (NA) was classified as NA. Cases of 1% TILs and Klintrup 0 were classified as the immune-desert subtype. Mass spectrometry was used to identify differentially expressed proteins in formalin-fixed paraffin-embedded biopsy tissues. RESULTS: Of the 56 cases, 31 (55%) were immune-inflamed, 21 (38%) were immune-excluded, 2 (4%) were immune-desert and 2 (4%) were NA. Welch's t-test revealed two differentially expressed proteins between immune-inflamed and immune-excluded/desert subtypes. Coronin-1A was upregulated in immune-inflamed tumors (adjusted p = 0.008) and α-1-antitrypsin was upregulated in immune-excluded/desert tumors (adjusted p = 0.008). Titin was upregulated in pathologic complete response (pCR) than non-pCR among immune-inflamed tumors (adjusted p = 0.036). CONCLUSIONS: Coronin-1A and α-1-antitrypsin were upregulated in immune-inflamed and immune-excluded/desert subtypes, respectively. Titin's elevated expression in pCR within the immune-inflamed subtype may indicate a favorable prognosis. Further studies involving large representative cohorts are necessary to validate these findings.

21-gene expression assay and clinical outcomes of premenopausal patients with hormone receptor-positive breast cancer.

The prognostic role of the recurrence score (RS) based on the 21-gene expression assay in premenopausal women is not well delineated, and we investigated the association of outcomes and the RS in premenopausal patients who had 21-gene expression assay at Asan Medical Center, Seoul, Korea, between June 2005 and July 2018. Invasive breast cancer-free survival (IBCFS) by STEEP version 2.0 was compared according to the RS and clinical risk factors. A total of 554 patients were included in our study and 116 patients (20.9%) had age <40 years, 238 patients (43.0%) had luminal B subtype (Ki67 ≥ 20%), and 83 patients (15.0%) had RS >25. All patients received adjuvant tamoxifen ± chemotherapy. Overall, patients with RS >25 showed trend toward worse IBCFS from multivariable analysis (adjusted HR 1.89 [95% CI: 0.95-3.73], P = .069). When comparing outcomes according to age and luminal subtypes, patients with luminal B subtype and age <40 years (n = 60) showed significantly worse outcomes compared to the others (luminal A or luminal B + age ≥40 years, n = 494; adjusted HR 2.95 [95% CI: 1.49-5.82], log-rank P < .001). Among patients with luminal B subtype and age <40 years, there was no significant association observed between IBCFS and the RS (log-rank P = .51). In conclusion, while RS >25 showed association with poor outcomes in premenopausal women, it may have less prognostic significance among those with luminal B subtype and age <40 years.

Long-term prognostic value of the GenesWell BCT score in Asian women with hormone receptor-positive/HER2-negative early breast cancer.

BACKGROUND: Accurate prediction of the risk of recurrence is crucial for optimal treatment decisions in hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer. The GenesWell BCT is a molecular assay to predict the 10-year risk of distant metastasis. In this study, we evaluated the long-term prognostic value of the GenesWell BCT assay. METHODS: The BCT score was assessed in patients with HR-positive/HER2-negative early breast cancer who did not receive chemotherapy. We compared the 15-year distant metastasis-free survival (DMFS) between risk groups classified based on the BCT score. The risk of early (0-5 years) and late (5-15 years) recurrence was evaluated based on the BCT score classification. RESULTS: According to the BCT score, 366 patients from Japan and Korea were categorized as BCT low risk (83.6%) and high risk (16.4%) for distant metastasis. Median follow-up time was 17.4 years. The 15-year DMFS rate was significantly lower in the BCT high-risk group (63.3%) than in the BCT low-risk group (93.6%) (P < 0.001). The BCT risk group was an independent prognostic factor for 15-year DMFS (hazard ratio, 4.59; 95% confidence interval 2.13-9.88; P < 0.001). Furthermore, the BCT score was a significant predictor of late recurrence (5-15 years) in patients aged ≤ 50 years and those aged > 50 years, and added prognostic information to traditional clinical prognostic factors. CONCLUSION: The BCT score can identify patients at low risk for recurrence who may not require adjuvant chemotherapy or extended endocrine therapy, regardless of age.

Deep learning-based diagnosis of lung cancer using a nationwide respiratory cytology image set: improving accuracy and inter-observer variability.

Deep learning (DL)-based image analysis has recently seen widespread application in digital pathology. Recent studies utilizing DL in cytopathology have shown promising results, however, the development of DL models for respiratory specimens is limited. In this study, we designed a DL model to improve lung cancer diagnosis accuracy using cytological images from the respiratory tract. This retrospective, multicenter study used digital cytology images of respiratory specimens from a quality-controlled national dataset collected from over 200 institutions. The image processing involves generating extended z-stack images to reduce the phase difference of cell clusters, color normalizing, and cropping image patches to 256 × 256 pixels. The accuracy of diagnosing lung cancer in humans from image patches before and after receiving AI assistance was compared. 30,590 image patches (1,273 whole slide images [WSIs]) were divided into 27,362 (1,146 WSIs) for training, 2,928 (126 WSIs) for validation, and 1,272 (1,272 WSIs) for testing. The Densenet121 model, which showed the best performance among six convolutional neural network models, was used for analysis. The results of sensitivity, specificity, and accuracy were 95.9%, 98.2%, and 96.9% respectively, outperforming the average of three experienced pathologists. The accuracy of pathologists after receiving AI assistance improved from 82.9% to 95.9%, and the inter-rater agreement of Fleiss' Kappa value was improved from 0.553 to 0.908. In conclusion, this study demonstrated that a DL model was effective in diagnosing lung cancer in respiratory cytology. By increasing diagnostic accuracy and reducing inter-observer variability, AI has the potential to enhance the diagnostic capabilities of pathologists.

Diagnostic proficiency test using digital cytopathology and comparative assessment of whole slide images of cytologic samples for quality assurance program in Korea.

BACKGROUND: The Korean Society for Cytopathology introduced a digital proficiency test (PT) in 2021. However, many doubtful opinions remain on whether digitally scanned images can satisfactorily present subtle differences in the nuclear features and chromatin patterns of cytological samples. METHODS: We prepared 30 whole-slide images (WSIs) from the conventional PT archive by a selection process for digital PT. Digital and conventional PT were performed in parallel for volunteer institutes, and the results were compared using feedback. To assess the quality of cytological assessment WSIs, 12 slides were collected and scanned using five different scanners, with four cytopathologists evaluating image quality through a questionnaire. RESULTS: Among the 215 institutes, 108 and 107 participated in glass and digital PT, respectively. No significant difference was noted in category C (major discordance), although the number of discordant cases was slightly higher in the digital PT group. Leica, 3DHistech Pannoramic 250 Flash, and Hamamatsu NanoZoomer 360 systems showed comparable results in terms of image quality, feature presentation, and error rates for most cytological samples. Overall satisfaction was observed with the general convenience and image quality of digital PT. CONCLUSIONS: As three-dimensional clusters are common and nuclear/chromatin features are critical for cytological interpretation, careful selection of scanners and optimal conditions are mandatory for the successful establishment of digital quality assurance programs in cytology.

Association of cyclooxygenase-2 expression with endoplasmic reticulum stress and autophagy in triple-negative breast cancer.

Cyclooxygenase-2 plays a role in oncogenesis and its overexpression is associated with triple-negative breast cancer. However, the mechanisms whereby cyclooxygenase-2 contribute to breast cancer are complex and not well understood. Cyclooxygenase-2 overexpression causes hypoxia, oxidative stress, and endoplasmic reticulum stress. The aim of this study is to investigate the correlations among cyclooxygenase-2 expression, endoplasmic reticulum stress-associated molecules, and autophagy-associated molecules in triple-negative breast cancer. Surgical specimens from two cohorts of triple-negative breast cancer patients without neoadjuvant systemic therapy were analyzed: cohorts 1 and 2 consisted of 218 cases from 2004 to 2006 and 221 cases from 2007 to 2009, respectively. Specimens were evaluated by immunohistochemical examination of cyclooxygenase-2, endoplasmic reticulum stress markers, and autophagy markers expression using tissue microarrays. Cyclooxygenase-2 was overexpressed in 29.8% and 23.9% of cases in cohorts 1 and 2, respectively; and it was positively correlated with two out of three endoplasmic reticulum stress-associated molecules (XBP1, p = 0.025 and p = 0.003 in cohort 1 and cohort 2, respectively; PERK, p < 0.001 in both cohorts). Cyclooxygenase-2 was also positively correlated with two out of three autophagy markers (p62, p = 0.002 and p = 0.003 in cohort 1 and cohort 2, respectively; beclin1, p < 0.001 in both cohorts). Although cyclooxygenase-2 was not an independent prognostic factor for distant metastasis free survival and overall survival, its expression was associated with the expression of endoplasmic reticulum stress and autophagy molecules in triple-negative breast cancer.

Ki-67, 21-Gene Recurrence Score, Endocrine Resistance, and Survival in Patients With Breast Cancer.

Importance: Both high 21-gene recurrence score (RS) and high Ki-67 level are poor prognostic factors in patients with estrogen receptor (ER)-positive ERBB2-negative (ER+/ERBB-) breast cancer; however, a discrepancy between the 2 has been noted. Survival differences according to these 2 biomarkers are not well known. Objective: To assess the associations between RS and Ki-67 expression and between Ki-67 expression and recurrence-free survival in patients with ER+/ERBB- breast cancer with low RS. Design, Setting, and Participants: This cohort study included women treated for ER+/ERBB2- breast cancer who underwent the 21-gene RS test from March 2010 to December 2020 in 2 hospitals in Korea. Exposures: Recurrence score and Ki-67 level. Main Outcomes and Measures: A Cox proportional hazards regression model was used to examine the association of Ki-67 with recurrence-free survival (RFS), while a binary logistic regression model was used to examine the association between Ki-67 and secondary endocrine resistance. High Ki-67 expression was defined as 20% or greater, and low genomic risk as an RS of 25 or less. Secondary endocrine resistance was defined as breast cancer recurrence that occurred after at least 2 years of endocrine therapy and during or within the first year after completing 5 years of adjuvant endocrine therapy. Results: A total of 2295 female patients were included (mean [SD] age, 49.8 [9.3] years), of whom 1948 (84.9%) were in the low genomic risk group and 1425 (62.1%) had low Ki-67 level. The median follow-up period was 40 months (range, 0-140 months). The RS and Ki-67 level had a moderate correlation (R = 0.455; P < .001). Of the patients with low Ki-67 level, 1341 (94.1%) had low RS, whereas 607 of 870 patients with high Ki-67 level (69.8%) had low RS. In patients with low RS, the RFS differed significantly according to Ki-67 level (low Ki-67, 98.5% vs high Ki-67, 96.5%; P = .002). Among the 1807 patients with low genomic risk who did not receive chemotherapy, high Ki-67 level was independently associated with recurrence (hazard ratio, 2.51; 95% CI, 1.27-4.96; P = .008). Recurrence after 3 years differed significantly according to Ki-67 level (low Ki-67, 98.7% vs high Ki-67, 95.7%; P = .003), whereas recurrence within 3 years did not differ (low Ki-67, 99.3% vs high Ki-67, 99.3%; P = .90). In addition, Ki-67 was associated with secondary endocrine resistance in patients with low RS who did not receive chemotherapy (odds ratio, 2.49; 95% CI, 1.13-5.50; P = .02). Conclusions and Relevance: In this cohort study of patients with ER+/ERBB2- breast cancer, a moderate correlation was observed between Ki-67 and RS, and high Ki-67 level in patients with low genomic risk was associated with increased risk of secondary endocrine resistance.

Prognostic implications of HER2 changes after neoadjuvant chemotherapy in patients with HER2-zero and HER2-low breast cancer.

BACKGROUND: The transition of human epidermal growth factor receptor 2 (HER2) status after neoadjuvant chemotherapy (NAC) in HER2-low breast cancer has not been thoroughly evaluated. Here, we evaluated the HER2 transition among HER2-zero and HER2-low breast cancer cases post-NAC and its impact on clinical outcomes. METHODS: We included 1288 patients with HER2-low or zero breast cancer who underwent NAC and surgery between 2014 and 2018 and had paired pre- and post-therapeutic HER2 status results. RESULTS: Among patients who were HER2-zero pre-NAC (n = 650), 68% and 29% were HER2-zero and HER2-low, respectively, post-NAC. Among patients who were HER2-low pre-NAC (n = 638), 32% of patients showed HER2 changes (low to zero), and 59% of patients had a constant HER2-low status post-NAC. Patients with constant HER2-low or transitions from HER2-low to zero had a higher proportion of hormone receptor positivity (84% and 79%) than those with changes from HER2-zero to low (77%) or with constant HER2-zero (56%), respectively. Multivariable logistic regression analysis revealed that patients with oestrogen receptor positivity had a higher probability of gaining HER2-low expression than those with oestrogen receptor negativity (odds ratio 2.48). No significant differences were observed in terms of overall survival or disease-free survival between patients with and without HER2-changes according to their hormone receptor status, except in the post-therapeutic HER2-low, hormone receptor-negativity subset. CONCLUSION: Temporal heterogeneity of HER2-low expression is observed in substantial numbers of post-NAC breast cancer patients. Clinical outcomes show no significant associations, except in the post-therapeutic HER2-low, hormone receptor negativity subset. The prognostic implications of HER2 transition in HER2-low breast cancer require further investigation.

Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid.

A Pleural effusion cytology is vital for treating metastatic breast cancer; however, concerns have arisen regarding the low accuracy and inter-observer variability in cytologic diagnosis. Although artificial intelligence-based image analysis has shown promise in cytopathology research, its application in diagnosing breast cancer in pleural fluid remains unexplored. To overcome these limitations, we evaluate the diagnostic accuracy of an artificial intelligence-based model using a large collection of cytopathological slides, to detect the malignant pleural effusion cytology associated with breast cancer. This study includes a total of 569 cytological slides of malignant pleural effusion of metastatic breast cancer from various institutions. We extracted 34,221 augmented image patches from whole-slide images and trained and validated a deep convolutional neural network model (DCNN) (Inception-ResNet-V2) with the images. Using this model, we classified 845 randomly selected patches, which were reviewed by three pathologists to compare their accuracy. The DCNN model outperforms the pathologists by demonstrating higher accuracy, sensitivity, and specificity compared to the pathologists (81.1% vs. 68.7%, 95.0% vs. 72.5%, and 98.6% vs. 88.9%, respectively). The pathologists reviewed the discordant cases of DCNN. After re-examination, the average accuracy, sensitivity, and specificity of the pathologists improved to 87.9, 80.2, and 95.7%, respectively. This study shows that DCNN can accurately diagnose malignant pleural effusion cytology in breast cancer and has the potential to support pathologists.

Randomized phase III trial of a neoadjuvant regimen of four cycles of adriamycin plus cyclophosphamide followed by four cycles of docetaxel (AC4-D4) versus a shorter treatment of three cycles of FEC followed by three cycles of docetaxel (FEC3-D3) in node-positive breast cancer (Neo-shorter; NCT02001506).

PURPOSE: To determine whether six cycles of FEC3-D3 has a comparable efficacy to eight of AC4-D4. METHODS: The enrolled patients (pts) were clinically diagnosed with stage II or III breast cancer. The primary endpoint was a pathologic complete response (pCR), and the secondary endpoints were 3 year disease-free survival (3Y DFS), toxicities, and health-related quality of life (HRQoL). We calculated that 252 pts were needed in each treatment group to enable the detection of non-inferiority (non-inferiority margin of 10%). RESULTS: In terms of ITT analysis, 248 pts were finally enrolled. The 218 pts who completed the surgery were included in the current analysis. The baseline characteristics of these subjects were well balanced between the two arms. By ITT analysis, pCR was achieved in 15/121 (12.4%) pts in the FEC3-D3 arm and 18/126 (14.3%) in the AC4-D4 arm. With a median follow up of 64.1 months, the 3Y DFS was comparable between the two arms (75.8% in FEC3-D3 vs. 75.6% in AC4-D4). The most common adverse event (AE) was Grade 3/4 neutropenia, which arose in 27/126 (21.4%) AC4-D4 arm pts vs 23/121 (19.0%) FEC3-D3 arm cases. The primary HRQoL domains were similar between the two groups (FACT-B scores at baseline, P = 0.35; at the midpoint of NACT, P = 0.20; at the completion of NACT, P = 0.44). CONCLUSION: Six cycles of FEC3-D3 could be an alternative to eight of AC4-D4. Trial registration ClinicalTrials.gov NCT02001506. Registered December 5,2013. https://clinicaltrials.gov/ct2/show/NCT02001506.

Immune repertoire and responses to neoadjuvant TCHP therapy in HER2-positive breast cancer.

Background: Despite the introduction of trastuzumab, pathologic complete response (pCR) is not attained in approximately 30-40% of Human epithelial growth factor receptor-2-positive breast cancer. Tumor-infiltrating lymphocytes (TIL) have been suggested as a predictive marker of treatment response, albeit not always effective. We investigated the relationship between trastuzumab, docetaxel, carboplatin, and pertuzumab (TCHP) treatment and immune repertoire as a treatment response predictor. Design: In all, 35 cases were divided into two experimental groups: 10 and 25 cases in the preliminary and main experiments, respectively. In the preliminary experiment, the biopsy tissues before TCHP treatment and the surgical tissues after TCHP treatment were compared. In the main experiment, the biopsy tissues before TCHP treatment were compared according to the TCHP treatment response. Methods: The T-cell repertoire for TRA, TRB, TRG, and TRD, and B-cell repertoire for immunoglobulin heavy, immunoglobulin kappa, and immunoglobulin lambda were evaluated. Whole transcriptome sequencing was also performed. Results: In the preliminary experiment, the density and richness of the T-cell receptor (TCR) and B-cell receptor (BCR) repertoires decreased after treatment, regardless of TCHP response. In the main experiment, the Shannon's entropy index, density, and length of CDR3 of the TCR and BCR repertoires did not differ significantly in patients who did and did not achieve pCR. The pCR and non-pCR subgroups according to the level of TILs revealed that the non-pCR/lowTIL group had a higher proportion of low-frequency clones than the pCR/lowTIL group in TRA (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 63% versus 45.3%; <0.01%, 32.9% versus 51.8%, p < 0.001) and TRB (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 26.5% versus 14.7%; <0.01%, 72.0% versus 84.1%, p < 0.001). Conclusions: The role of the diversity, richness, and density of the TCR and BCR repertoires as predictive markers for TCHP response was not identified. Compositions of low-frequency clones could be candidates for predictive factors of TCHP response; however, validation studies and further research are necessary.