The Breast Cases Challenge (BCC) classroom uses the Google Classroom software, a free web service created by Google (Google, LLC, Mountain View, California) to help improve education via the internet ...and accessed via a web browser or through classroom app. The collaborating institutions include Montefiore Medical Center (Bronx, New York), Weill Cornell Medicine (New York City, New York), Yale University (New Haven, Connecticut), Hospital of the University of Pennsylvania (Philadelphia, Pennsylvania) Danbury Hospital (Danbury, Connecticut), Women and Infants Hospital (Brown University, Providence, Rhode Island), University of Tennessee Health Science Center (Memphis, Tennessee), All India Institute of Medical Sciences (New Delhi, India), and Hospital Alemao Oswaldo Cruz (Sao Paulo, Brazil). Ridin Balakrishnan, MD1; Kamaljeet Singh, MD2; Malini Harigopal, MD3; Susan Fineberg, MD1 1 Department of Pathology, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, New York; 2 Department of Pathology and Laboratory Medicine, Warren Alpert Medical School of Brown University, Women and Infants Hospital of Rhode Island, Providence, Rhode Island; 3 Department of Pathology, Yale University Hospital, New Haven, Connecticut The authors thank the residents and fellows in our classroom who responded to our survey and without whom this study could not have been possible:
Morphological evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer is gaining momentum as evidence strengthens the clinical relevance of this immunological biomarker. TILs in the ...post-neoadjuvant residual disease setting are acquiring increasing importance as a stratifying marker in clinical trials, considering the raising interest on immunotherapeutic strategies after neoadjuvant chemotherapy. TILs in ductal carcinoma in situ, with or without invasive carcinoma, represent an emerging area of clinical breast cancer research. The aim of this report is to update pathologists, clinicians and researchers on TIL assessment in both the post-neoadjuvant residual disease and the ductal carcinoma in situ settings. The International Immuno-Oncology Working Group proposes a method for assessing TILs in these settings, based on the previously published International Guidelines on TIL Assessment in Breast Cancer. In this regard, these recommendations represent a consensus guidance for pathologists, aimed to achieve the highest possible consistency among future studies.
The effects of diet in cancer, in general, and breast cancer in particular, are not well understood. Insulin inhibition in ketogenic, high fat diets, modulate downstream signaling molecules and are ...postulated to have therapeutic benefits. Obesity and diabetes have been associated with higher incidence of breast cancer. Addition of anti-cancer drugs together with diet is also not well studied.
Two diets, one ketogenic, the other standard mouse chow, were tested in a spontaneous breast cancer model in 34 mice. Subgroups of 3-9 mice were assigned, in which the diet were implemented either with or without added rapamycin, an mTOR inhibitor and potential anti-cancer drug.
Blood glucose and insulin concentrations in mice ingesting the ketogenic diet (KD) were significantly lower, whereas beta hydroxybutyrate (BHB) levels were significantly higher, respectively, than in mice on the standard diet (SD). Growth of primary breast tumors and lung metastases were inhibited, and lifespans were longer in the KD mice compared to mice on the SD (p<0.005). Rapamycin improved survival in both mouse diet groups, but when combined with the KD was more effective than when combined with the SD.
The study provides proof of principle that a ketogenic diet a) results in serum insulin reduction and ketosis in a spontaneous breast cancer mouse model; b) can serve as a therapeutic anti-cancer agent; and c) can enhance the effects of rapamycin, an anti-cancer drug, permitting dose reduction for comparable effect. Further, the ketogenic diet in this model produces superior cancer control than standard mouse chow whether with or without added rapamycin.
HHLA2 (B7H7/B7-H5/B7y) is a newly identified B7 family member that regulates human T-cell functions. However, its protein expression in human organs and significance in human diseases are unknown. ...The objective of this study was to analyze HHLA2 protein expression in normal human tissues and cancers, as well as its prognostic significance, to explore mechanisms regulating HHLA2 expression, and to identify candidate HHLA2 receptors.
An immunohistochemistry protocol and a flow cytometry assay with newly generated monoclonal antibodies were developed to examine HHLA2 protein. HHLA2 gene copy-number variation was analyzed from cancer genomic data. The combination of bioinformatics analysis and immunologic approaches was established to explore HHLA2 receptors.
HHLA2 protein was detected in trophoblastic cells of the placenta and the epithelium of gut, kidney, gallbladder, and breast, but not in most other organs. In contrast, HHLA2 protein was widely expressed in human cancers from the breast, lung, thyroid, melanoma, pancreas, ovary, liver, bladder, colon, prostate, kidney, and esophagus. In a cohort of 50 patients with stage I-III triple-negative breast cancer, 56% of patients had aberrant expression of HHLA2 on their tumors, and high HHLA2 expression was significantly associated with regional lymph node metastasis and stage. The Cancer Genome Atlas revealed that HHLA2 copy-number gains were present in 29% of basal breast cancers, providing a potential mechanism for increased HHLA2 protein expression in breast cancer. Finally, Transmembrane and Immunoglobulin Domain Containing 2 (TMIGD2) was identified as one of the receptors for HHLA2.
Wide expression of HHLA2 in human malignancies, together with its association with poor prognostic factors and its T-cell coinhibitory capability, suggests that the HHLA2 pathway represents a novel immunosuppressive mechanism within the tumor microenvironment and an attractive target for human cancer therapy.
Although an important biomarker in breast cancer, Ki67 lacks scoring standardization, which has limited its clinical use. Our previous study found variability when laboratories used their own scoring ...methods on centrally stained tissue microarray slides. In this current study, 16 laboratories from eight countries calibrated to a specific Ki67 scoring method and then scored 50 centrally MIB-1 stained tissue microarray cases. Simple instructions prescribed scoring pattern and staining thresholds for determination of the percentage of stained tumor cells. To calibrate, laboratories scored 18 'training' and 'test' web-based images. Software tracked object selection and scoring. Success for the calibration was prespecified as Root Mean Square Error of scores compared with reference <0.6 and Maximum Absolute Deviation from reference <1.0 (log2-transformed data). Prespecified success criteria for tissue microarray scoring required intraclass correlation significantly >0.70 but aiming for observed intraclass correlation ≥0.90. Laboratory performance showed non-significant but promising trends of improvement through the calibration exercise (mean Root Mean Square Error decreased from 0.6 to 0.4, Maximum Absolute Deviation from 1.6 to 0.9; paired t-test: P=0.07 for Root Mean Square Error, 0.06 for Maximum Absolute Deviation). For tissue microarray scoring, the intraclass correlation estimate was 0.94 (95% credible interval: 0.90-0.97), markedly and significantly >0.70, the prespecified minimum target for success. Some discrepancies persisted, including around clinically relevant cutoffs. After calibrating to a common scoring method via a web-based tool, laboratories can achieve high inter-laboratory reproducibility in Ki67 scoring on centrally stained tissue microarray slides. Although these data are potentially encouraging, suggesting that it may be possible to standardize scoring of Ki67 among pathology laboratories, clinically important discrepancies persist. Before this biomarker could be recommended for clinical use, future research will need to extend this approach to biopsies and whole sections, account for staining variability, and link to outcomes.
Abstract
Background
Current clinical criteria do not discriminate well between women who will or those who will not develop ipsilateral invasive breast cancer (IBC), or a DCIS recurrence after a ...ductal carcinoma in situ (DCIS) diagnosis. The 12-gene Oncotype DX® DCIS assay (RT qPCR gene-based scoring system) was established and shown to predict the risk of subsequent ipsilateral IBC or DCIS recurrence. Recent studies have shown that microRNA (miRNA) expression deregulation can contribute to the development of IBC, but very few have evaluated miRNA deregulation in DCIS lesions. In this study, we sought to determine whether specific miRNA expression changes may correlate with Oncotype DX® DCIS scores.
Methods
For this study, we used archived formalin-fixed, paraffin-embedded (FFPE) specimens from 41 women diagnosed with DCIS between 2012 and 2018. The DCIS lesions were stratified into low (
n
= 26), intermediate (
n
= 10), and high (
n
= 5) risk score groups using the Oncotype DX® DCIS assay. Total RNA was extracted from DCIS lesions by macro-dissection of unstained FFPE sections, and next-generation small-RNA sequencing was performed. We evaluated the correlation between miRNA expression data and Oncotype score, as well as patient age. RT-qPCR validations were performed to validate the topmost differentially expressed miRNAs identified between the different risk score groups.
Results
MiRNA sequencing of 32 FFPE DCIS specimens from the three different risk group scores identified a correlation between expression deregulation of 17 miRNAs and Oncotype scores. Our analyses also revealed a correlation between the expression deregulation of 9 miRNAs and the patient’s age. Based on these results, a total of 15 miRNAs were selected for RT-qPCR validation. Of these, miR-190b (
p
= 0.043), miR-135a (
p
= 0.05), miR-205 (
p
= 0.00056), miR-30c (
p
= 0.011), and miR-744 (
p
= 0.038) showed a decreased expression in the intermediate/high Oncotype group when compared to the low-risk score group. A composite risk score was established using these 5 miRNAs and indicated a significant association between miRNA expression deregulation and the Oncotype DX® DCIS Score (
p
< 0.0021), between high/intermediate and low risk groups.
Conclusions
Our analyses identified a subset of 5 miRNAs able to discriminate between Oncotype DX® DCIS score subgroups. Together, our data suggest that miRNA expression analysis may add value to the predictive and prognostic evaluation of DCIS lesions.
Breast carcinoma grading is an important prognostic feature recently incorporated into the AJCC Cancer Staging Manual. There is increased interest in applying virtual microscopy (VM) using digital ...whole slide imaging (WSI) more broadly. Little is known regarding concordance in grading using VM and how such variability might affect AJCC prognostic staging (PS). We evaluated interobserver variability amongst a multi-institutional group of breast pathologists using digital WSI and how discrepancies in grading would affect PS. A digitally scanned slide from 143 invasive carcinomas was independently reviewed by 6 pathologists and assigned grades based on established criteria for tubule formation (TF), nuclear pleomorphism (NP), and mitotic count (MC). Statistical analysis was performed. Interobserver agreement for grade was moderate (κ = 0.497). Agreement was fair (κ = 0.375), moderate (κ = 0.491), and good (κ = 0.705) for grades 2, 3, and 1, respectively. Observer pair concordance ranged from fair to good (κ = 0.354–0.684) Perfect agreement was observed in 43 cases (30%). Interobserver agreement for the individual components was best for TF (κ = 0.503) and worst for MC (κ = 0.281). Seventeen of 86 (19.8%) discrepant cases would have resulted in changes in PS and discrepancies most frequently resulted in a PS change from IA to IB (n = 9). For two of these nine cases, Oncotype DX results would have led to a PS of 1A regardless of grade. Using VM, a multi-institutional cohort of pathologists showed moderate concordance for breast cancer grading, similar to studies using light microscopy. Agreement was the best at the extremes of grade and for evaluation of TF. Whether the higher variability noted for MC is a consequence of VM grading warrants further investigation. Discordance in grading infrequently leads to clinically meaningful changes in the prognostic stage.
Generalizability of predictive models for pathological complete response (pCR) and overall survival (OS) in breast cancer patients requires diverse datasets. This study employed four machine learning ...models to predict pCR and OS up to 7.5 years using data from a diverse and underserved inner-city population.
Demographics, staging, tumor subtypes, income, insurance status, and data from radiology reports were obtained from 475 breast cancer patients on neoadjuvant chemotherapy in an inner-city health system (01/01/2012 to 12/31/2021). Logistic regression, Neural Network, Random Forest, and Gradient Boosted Regression models were used to predict outcomes (pCR and OS) with fivefold cross validation.
pCR was not associated with age, race, ethnicity, tumor staging, Nottingham grade, income, and insurance status (p > 0.05). ER-/HER2+ showed the highest pCR rate, followed by triple negative, ER+/HER2+, and ER+/HER2- (all p < 0.05), tumor size (p < 0.003) and background parenchymal enhancement (BPE) (p < 0.01). Machine learning models ranked ER+/HER2-, ER-/HER2+, tumor size, and BPE as top predictors of pCR (AUC = 0.74-0.76). OS was associated with race, pCR status, tumor subtype, and insurance status (p < 0.05), but not ethnicity and incomes (p > 0.05). Machine learning models ranked tumor stage, pCR, nodal stage, and triple-negative subtype as top predictors of OS (AUC = 0.83-0.85). When grouping race and ethnicity by tumor subtypes, neither OS nor pCR were different due to race and ethnicity for each tumor subtype (p > 0.05).
Tumor subtypes and imaging characteristics were top predictors of pCR in our inner-city population. Insurance status, race, tumor subtypes and pCR were associated with OS. Machine learning models accurately predicted pCR and OS.
How dedifferentiated stem-like tumor cells evade immunosurveillance remains poorly understood. We show that the lineage-plasticity regulator SOX9, which is upregulated in dedifferentiated tumor ...cells, limits the number of infiltrating T lymphocytes in premalignant lesions of mouse basal-like breast cancer. SOX9-mediated immunosuppression is required for the progression of in situ tumors to invasive carcinoma. SOX9 induces the expression of immune checkpoint B7x/B7-H4 through STAT3 activation and direct transcriptional regulation. B7x is upregulated in dedifferentiated tumor cells and protects them from immunosurveillance. B7x also protects mammary gland regeneration in immunocompetent mice. In advanced tumors, B7x targeting inhibits tumor growth and overcomes resistance to anti-PD-L1 immunotherapy. In human breast cancer, SOX9 and B7x expression are correlated and associated with reduced CD8
T cell infiltration. This study, using mouse models, cell lines, and patient samples, identifies a dedifferentiation-associated immunosuppression mechanism and demonstrates the therapeutic potential of targeting the SOX9-B7x pathway in basal-like breast cancer.
Background
A ductal carcinoma in situ (DCIS) Nomogram integrating 10 clinicopathologic/treatment factors and a Refined DCIS Score (RDS) that incorporates a genomic assay and three clinicopathologic ...factors (Oncotype DX DCIS Score) are available to estimate DCIS 10-year local recurrence risk (LRR). This study compared these estimates.
Methods
Patients 50 years of age or older with DCIS size 2.5 cm or smaller and a genomic assay available were identified. An RDS within 1–2% of the range of Nomogram LRR estimates obtained by assuming use and non-use of endocrine therapy (Nomogram ± ET) was defined as concordant. Assuming a 10-year risk threshold of 10% for recommending radiation, Nomogram ± ET and RDS estimates were compared, and threshold concordance was determined.
Results
For 54 (92%) of 59 patients, the RDS and Nomogram ± ET LRR estimates were concordant. For the remaining 5 (8%) of the 59 patients, the RDS LRR estimates were lower than the Nomogram + ET estimates, with an absolute difference of 3–8%, and thus were discordant. For these five patients, the RDS estimates of 10-year LRR were lower than 10% (range 5–8%) and the Nomogram + ET estimates were 10% or higher (range 11–14%). These five patients with both discordant and threshold-discordant estimates all had close margins (≤ 2 mm).
Conclusions
Among 92% of women 50 years of age or older with DCIS size 2.5 cm or smaller, free-of-charge online Nomogram 10-year LRR estimates were concordant with those obtained using the commercially available RDS (> $4600). Among the 8% with discordant risk estimates, the RDS appeared to underestimate the LRR and may lead to inappropriate omission of radiotherapy. Unless other data show a clinically significant advantage of the RDS (Oncotype DX DCIS Score), the study data suggest that for women 50 years of age or older with DCIS size 2.5 cm or smaller, its use is not warranted.
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