Trends in breast, colon, pancreatic, and uterine cancers in women during the COVID-19 pandemic in North Carolina.

IMPORTANCE: The COVID-19 pandemic led to reductions in primary care and cancer screening visits, which may delay detection of some cancers. The impact on incidence has not been fully quantified. We examined change in cancer incidence to determine how the COVID-19 pandemic may have altered the characteristics of cancers diagnosed among women. METHODS: This study included female patients aged ≥18 years and diagnosed with breast (n = 9489), colon (n = 958), pancreatic (n = 669), or uterine (n = 1991) cancer at three hospitals in North Carolina. Using interrupted time series, we compared incidence of cancers diagnosed between March 2020 and November 2020 (during pandemic) with cancers diagnosed between January 2016 and February 2020 (pre-pandemic). RESULTS: During the pandemic, incidence of breast and uterine cancers was significantly lower than expected compared to pre-pandemic (breast-18%, p = 0.03; uterine -20%, p = 0.05). Proportions of advanced pathologic stage and hormone receptor-negative breast cancers, and advanced clinical stage and large size uterine cancers were more prevalent during the pandemic. No significant changes in incidence were detected for pancreatic (-20%, p = 0.08) or colon (+14%, p = 0.30) cancers. CONCLUSION AND RELEVANCE: In women, the COVID-19 pandemic resulted in a significant reduction in the incidence of breast and uterine cancers, but not colon or pancreatic cancers. A change in the proportion of poor prognosis breast and uterine cancers suggests that some cancers that otherwise would have been diagnosed at an earlier stage will be detected in later years. Continued analysis of long-term trends is needed to understand the full impact of the pandemic on cancer incidence and outcomes.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study.

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Tamoxifen Response at Single-Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors.

PURPOSE: In estrogen receptor-positive (ER+)/HER2- breast cancer, multiple measures of intratumor heterogeneity are associated with a worse response to endocrine therapy. We sought to develop a novel experimental model to measure heterogeneity in response to tamoxifen treatment in primary breast tumors. EXPERIMENTAL DESIGN: To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live normal breast specimens and human tumors immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. Live primary cell suspensions were treated ex vivo with tamoxifen (10 µmol/L) or control media for 12 hours, and single-cell RNA libraries were generated using the 10X Genomics droplet-based kit. RESULTS: In total, we obtained and processed normal breast tissue from two women undergoing reduction mammoplasty and tumor tissue from 10 women with ER+/HER2- invasive breast carcinoma. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from resistant subpopulations predict poor outcomes in two large cohorts of ER+ breast cancer patients and are enriched in endocrine therapy-resistant tumors. CONCLUSIONS: This novel ex vivo model system now provides the foundation to define responsive and resistant subpopulations within heterogeneous human tumors, which can be used to develop precise single cell-based predictors of response to therapy and to identify genes and pathways driving therapeutic resistance.

Pathological measurement and staging of residual breast cancer after neoadjuvant chemotherapy.

AIMS: The 8th Edition of the American Joint Committee on Cancer Staging System (yAJCC) excludes treatment-related fibrosis from the measurement of residual tumour after neoadjuvant chemotherapy (NAC) for breast cancer. The impact of the 8th Ed. yAJCC on post-NAC pathologic staging was examined in 188 breast cancer specimens from 183 patients with measurable residual tumour. METHODS: Tumour size, ypT, and ypN categories were reassessed with the current yACC criteria and compared to the original pathology reports. Histological patterns of response in the breast were categorised as concentric or scattered. RESULTS: The reassessed breast tumour size or ypT category differed from the original report in 101 (53.7%) cases. Changes in the ypT and/or ypN category resulted in downstaging of 45/185 (24.3%). A smaller reassessed tumour size or lower ypT category occurred more often in hormone receptor-positive/HER2-negative (HR+/HER2-) (68.3%) and HER2-positive (HER2+) tumours (74.0%) than triple-negative breast cancer (TNBC) (37.5%) (P < 0.001). A scattered pattern of response was more frequent in HR+/HER2- (54.9%) and HER2+ (66.0%) tumours than TNBC (35.7%) (P = 0.006). Changes in size, ypT, or multifocality based on the 8th Ed. yAJCC criteria were more frequent in tumours with a scattered pattern of response (P < 0.001). CONCLUSION: Strict adherence to yAJCC criteria for measurement of the residual breast tumour after NAC resulted in smaller tumour size, lower ypT category, lower yAJCC stage, and more frequent classification of residual tumour as multifocal. Downstaging based on 8th Ed. yAJCC criteria was associated with tumour subtype and histological pattern of response.

Tamoxifen Response at Single Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors.

In ER+/HER2- breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER+ breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.

Reproducibility and intratumoral heterogeneity of the PAM50 breast cancer assay.

BACKGROUND: The PAM50 assay is used routinely in clinical practice to determine breast cancer prognosis and management; however, research assessing how technical variation and intratumoral heterogeneity contribute to misclassification and reproducibility of these tests is limited. METHODS: We evaluated the impact of intratumoral heterogeneity on the reproducibility of results for the PAM50 assay by testing RNA extracted from formalin-fixed paraffin embedded breast cancer blocks sampled at distinct spatial locations. Samples were classified according to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, Basal-like, or Normal-like) and risk of recurrence with proliferation score (ROR-P, high, medium, or low). Intratumoral heterogeneity and technical reproducibility (replicate assays on the same RNA) were assessed as percent categorical agreement between paired intratumoral and replicate samples. Euclidean distances between samples, calculated across the PAM50 genes and the ROR-P score, were compared for concordant vs. discordant samples. RESULTS: Technical replicates (N = 144) achieved 93% agreement for ROR-P group and 90% agreement on PAM50 subtype. For spatially distinct biological replicates (N = 40 intratumoral replicates), agreement was lower (81% for ROR-P and 76% for PAM50 subtype). The Euclidean distances between discordant technical replicates were bimodal, with discordant samples showing higher Euclidian distance and biologic heterogeneity. CONCLUSION: The PAM50 assay achieved very high technical reproducibility for breast cancer subtyping and ROR-P, but intratumoral heterogeneity is revealed by the assay in a small proportion of cases.

Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population.

Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency. Significance: Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants.

Pure Mucinous Carcinoma of the Breast: Radiologic-Pathologic Correlation.

Mucinous carcinoma (MC) of the breast is a rare, specialized subtype of invasive breast carcinoma (IBC) accounting for approximately 1% to 4% of all primary breast malignancies. Mucinous carcinoma occurs predominantly in patients who are postmenopausal or elderly. It is usually detected on screening mammography, but occasionally the patient may present with a palpable mass. The most common mammographic appearance is an equal to high density, oval or round mass with circumscribed or indistinct margins; MC can mimic a benign lesion. Histologically, MC is a well-differentiated cancer characterized by pools of mucin around neoplastic cells. Depending on mucin content, the tumor is classified as pure (≥90% mucin) or mixed (>10% and <90% mucin). Pure MCs (PMCs) are of low or intermediate nuclear grade, and the vast majority are hormone receptor-positive and human epidermal growth factor-2 receptor-negative (luminal A subtype). Pure MCs may be classified as hypocellular (type A) or hypercellular (type B) and have a lower rate of axillary lymph node involvement and more favorable prognosis than IBCs, no special type. The purpose of this article is to review the clinical features, imaging appearances, associated histopathology, and management of PMC.

High-risk and selected benign breast lesions diagnosed on core needle biopsy: Evidence for and against immediate surgical excision.

The vast majority of image-detected breast abnormalities are diagnosed by percutaneous core needle biopsy (CNB) in contemporary practice. For frankly malignant lesions diagnosed by CNB, the standard practice of excision and multimodality therapy have been well-defined. However, for high-risk and selected benign lesions diagnosed by CNB, there is less consensus on optimal patient management and the need for immediate surgical excision. Here we outline the arguments for and against the practice of routine surgical excision of commonly encountered high-risk and selected benign breast lesions diagnosed by CNB. The entities reviewed include atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ, intraductal papillomas, and radial scars. The data in the peer-reviewed literature confirm the benefits of a patient-centered, multidisciplinary approach that moves away from the reflexive "yes" or "no" for routine excision for a given pathologic diagnosis.

The Landscape of Immune Microenvironments in Racially Diverse Breast Cancer Patients.

BACKGROUND: Immunotherapy is a rapidly evolving treatment option in breast cancer; However, the breast cancer immune microenvironment is understudied in Black and younger (<50 years) patients. METHODS: We used histologic and RNA-based immunoprofiling methods to characterize the breast cancer immune landscape in 1,952 tumors from the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1,030) and young women (n = 1,039). We evaluated immune response leveraging markers for 10 immune cell populations, compared profiles to those in The Cancer Genome Atlas (TCGA) Project [n = 1,095 tumors, Black (n = 183), and young women (n = 295)], and evaluated in association with clinical and demographic variables, including recurrence. RESULTS: Consensus clustering identified three immune clusters in CBCS (adaptive-enriched, innate-enriched, or immune-quiet) that varied in frequency by race, age, tumor grade and subtype; however, only two clusters were identified in TCGA, which were predominantly comprised of adaptive-enriched and innate-enriched tumors. In CBCS, the strongest adaptive immune response was observed for basal-like, HER2-positive (HER2+), triple-negative breast cancer (TNBC), and high-grade tumors. Younger patients had higher proportions of adaptive-enriched tumors, particularly among estrogen receptor (ER)-negative (ER-) cases. Black patients had higher frequencies of both adaptive-enriched and innate-enriched tumors. Immune clusters were associated with recurrence among ER- tumors, with adaptive-enriched showing the best and innate-enriched showing the poorest 5-year recurrence-free survival. CONCLUSIONS: These data suggest that immune microenvironments are intricately related to race, age, tumor subtype, and grade. IMPACT: Given higher mortality among Black and young women, more defined immune classification using cell-type-specific panels could help explain higher recurrence and ultimately lead to targetable interventions.

Risk-Associated Lesions of the Breast in Core Needle Biopsies: Current Approaches to Radiological-Pathological Correlation.

Image-guided core needle biopsies (CNBs) of the breast frequently result in a diagnosis of a benign or atypical lesion associated with breast cancer risk. The subsequent clinical management of these patients is variable, reflecting a lack of consensus on criteria for selecting patients for clinical and radiological follow-up versus immediate surgical excision. In this review, the evidence from prospective studies of breast CNB with radiological-pathological correlation is evaluated and summarized. The data support an emerging consensus on the importance of radiologic-pathologic correlation in standardizing the selection of patients for active surveillance versus surgery.

Evaluating the efficacy of a priming dose of cyclophosphamide prior to pembrolizumab to treat metastatic triple negative breast cancer.

PURPOSE: Triple negative breast cancer (TNBC) is characterized by the presence of immune cells in the tumor microenvironment, however, the response to single-agent immune checkpoint inhibitor (ICI) therapy is modest. Preclinical models have demonstrated that intratumoral regulatory T cells (Tregs) dampen the antitumor response to ICI. We performed a single-arm phase II trial to evaluate the efficacy of a single low dose of cyclophosphamide (Cy) to deplete Tregs administered before initiating pembrolizumab. PATIENTS AND METHODS: 40 patients with pretreated metastatic TNBC were enrolled. The primary endpoints were progression-free survival (PFS) and change in peripheral blood Tregs after Cy. Secondary endpoints included overall response rate (ORR), duration of response, overall survival, treatment-related adverse events (AEs), and correlative evaluations. RESULTS: Median PFS was 1.8 months, and the ORR was 21%. Tregs were not significantly decreased after Cy prior to ICI (-3.3%, p=0.19), and increased significantly after the first cycle of therapy (+21% between cycles 1 and 2, p=0.005). Immune-related AEs were similar to historical pembrolizumab monotherapy, and were associated with response to therapy (p=0.02). Patients with pretreatment tumors harboring increased expression of B cell metagene signatures and increased circulating B cell receptor repertoire diversity were associated with clinical response and immune-related toxicity (IRT). CONCLUSIONS: Among patients with heavily pretreated TNBC, Cy prior to pembrolizumab did not significantly deplete Tregs, and in those with decreased numbers there was rapid recovery following therapy. Increased B cell gene expression in baseline samples was associated with clinical response and IRT.

Quantitative analysis of breast cancer tissue composition and associations with tumor subtype.

The tumor microenvironment is an important determinant of breast cancer progression, but standard methods for describing the tumor microenvironment are lacking. Measures of microenvironment composition such as stromal area and immune infiltrate are labor-intensive and few large studies have systematically collected this data. However, digital histologic approaches are becoming more widely available, allowing high-throughput, quantitative estimation. We applied such methods to tissue microarrays of tumors from 1687 women (mean 4 cores per case) in the Carolina Breast Cancer Study Phase 3. Tumor composition was quantified as percentage of epithelium, stroma, adipose, and lymphocytic infiltrate (with the latter as presence/absence using a ≥1% cutoff). Composition proportions and presence/absence were evaluated in association with clinical and molecular features of breast cancer (intrinsic subtype and RNA-based risk of recurrence [ROR] scores) using multivariable linear and logistic regression. Lower stromal content was associated with aggressive tumor phenotypes, including triple-negative (31.1% vs. 41.6% in HR+/HER2-; RFD [95% CI]: -10.5%, [-13.1, -7.9]), Basal-like subtypes (29.0% vs. 44.0% in Luminal A; RFD [95% CI]: -14.9%, [-17.8, -12.0]), and high RNA-based PAM50 ROR scores (27.6% vs. 48.1% in ROR low; RFD [95% CI]: -20.5%, [24.3, 16.7]), after adjusting for age and race. HER2+ tumors also had lower stromal content, particularly among RNA-based HER2-enriched (35.2% vs. 44.0% in Luminal A; RFD [95% CI]: -8.8%, [-13.8, -3.8]). Similar associations were observed between immune infiltrate and tumor phenotypes. Quantitative digital image analysis of the breast cancer microenvironment showed significant associations with demographic characteristics and biological indicators of aggressive behavior.

Clinical and Financial Implications of Second-Opinion Surgical Pathology Review.

OBJECTIVES: Second-opinion pathology review identifies clinically significant diagnostic discrepancies for some patients. Discrepancy rates and laboratory-specific costs in a single health care system for patients referred from regional affiliates to a comprehensive cancer center ("main campus") have not been reported. METHODS: Main campus second-opinion pathology cases for 740 patients from eight affiliated hospitals during 2016 to 2018 were reviewed. Chart review was performed to identify changes in care due to pathology review. To assess costs of pathology interpretation, reimbursement rates for consultation Current Procedural Terminology billing codes were compared with codes that would have been used had the cases originated at the main campus. RESULTS: Diagnostic discrepancies were identified in 104 (14.1%) patients, 30 (4.1%) of which resulted in a change in care. In aggregate, reimbursement for affiliate cases was 65.6% of the reimbursement for the same cases had they originated at the main campus. High-volume organ systems with low relative consultation reimbursement included gynecologic, breast, and thoracic. CONCLUSIONS: Preventable diagnostic errors are reduced by pathology review for patients referred within a single health care system. Although the resulting changes in care potentially lead to overall cost savings, the financial value of referral pathology review could be improved.

Protein-based immune profiles of basal-like vs. luminal breast cancers.

Tumor-infiltrating lymphocytes play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest in formalin-fixed paraffin embedded tissue sections. Forty-four antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with regulatory T-cell (Treg) markers (CD4, CD25, and FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n = 75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with breast cancer subtype, suggesting possible prognostic, or targetable differences.

Outcomes of Hormone-Receptor Positive, HER2-Negative Breast Cancers by Race and Tumor Biological Features.

Background: Black women have higher hormone receptor positive (HR+) breast cancer mortality than White women. Early recurrence rates differ by race, but little is known about genomic predictors of early recurrence among HR+ women. Methods: Using data from the Carolina Breast Cancer Study (phase III, 2008-2013), we estimated associations between race and recurrence among nonmetastatic HR+/HER2-negative tumors, overall and by PAM50 Risk of Recurrence score, PAM50 intrinsic subtype, and tumor grade using survival curves and Cox models standardized for age and stage. Relative frequency differences (RFD) were estimated using multivariable linear regression. To assess intervention opportunities, we evaluated treatment patterns by race among patients with high-risk disease. Results: Black women had higher recurrence risk relative to White women (crude hazard ratio = 1.81, 95% confidence interval [CI] = 1.34 to 2.46), which remained elevated after standardizing for clinical covariates (hazard ratio = 1.42, 95% CI = 1.05 to 1.93). Racial disparities were most pronounced among those with high PAM50 Risk of Recurrence score (5-year standardized recurrence risk = 18.9%, 95% CI = 8.6% to 29.1% in Black women vs 12.5%, 95% CI = 2.0% to 23.0% in White women) and high grade (5-year standardized recurrence risk = 16.6%, 95% CI = 11.7% to 21.5% in Black women vs 12.0%, 95% CI = 7.3% to 16.7% in White women). However, Black women with high-grade tumors were statistically significantly less likely to initiate endocrine therapy (RFD = -8.3%, 95% CI = -15.9% to -0.6%) and experienced treatment delay more often than White women (RFD = +9.0%, 95% CI = 0.3% to 17.8%). Conclusions: Differences in recurrence by race appear greatest among women with aggressive tumors and may be influenced by treatment differences. Efforts to identify causes of variation in cancer treatment are critical to reducing outcome disparities.

JOINT AND INDIVIDUAL ANALYSIS OF BREAST CANCER HISTOLOGIC IMAGES AND GENOMIC COVARIATES.

The two main approaches in the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genomics. While both histopathology and genomics are fundamental to cancer research, the connections between these fields have been relatively superficial. We bridge this gap by investigating the Carolina Breast Cancer Study through the development of an integrative, exploratory analysis framework. Our analysis gives insights - some known, some novel - that are engaging to both pathologists and geneticists. Our analysis framework is based on Angle-based Joint and Individual Variation Explained (AJIVE) for statistical data integration and exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction. CNNs raise interpretability issues that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features.