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1. Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue using Deep Learning

   https://doi.org/10.34133/2022/9786242  

   Bai, Bijie; Wang, Hongda; Li, Yuzhu; de Haan, Kevin; Colonnese, Francesco; Wan, Yujie; Zuo, Jingyi; Doan, Ngan B.; Zhang, Xiaoran; Zhang, Yijie; et al (October 2022, BME Frontiers)

   The immunohistochemical (IHC) staining of the human epidermal growth factor receptor 2 (HER2) biomarker is widely practiced in breast tissue analysis, preclinical studies, and diagnostic decisions, guiding cancer treatment and investigation of pathogenesis. HER2 staining demands laborious tissue treatment and chemical processing performed by a histotechnologist, which typically takes one day to prepare in a laboratory, increasing analysis time and associated costs. Here, we describe a deep learning-based virtual HER2 IHC staining method using a conditional generative adversarial network that is trained to rapidly transform autofluorescence microscopic images of unlabeled/label-free breast tissue sections into bright-field equivalent microscopic images, matching the standard HER2 IHC staining that is chemically performed on the same tissue sections. The efficacy of this virtual HER2 staining framework was demonstrated by quantitative analysis, in which three board-certified breast pathologists blindly graded the HER2 scores of virtually stained and immunohistochemically stained HER2 whole slide images (WSIs) to reveal that the HER2 scores determined by inspecting virtual IHC images are as accurate as their immunohistochemically stained counterparts. A second quantitative blinded study performed by the same diagnosticians further revealed that the virtually stained HER2 images exhibit a comparable staining quality in the level of nuclear detail, membrane clearness, and absence of staining artifacts with respect to their immunohistochemically stained counterparts. This virtual HER2 staining framework bypasses the costly, laborious, and time-consuming IHC staining procedures in laboratory and can be extended to other types of biomarkers to accelerate the IHC tissue staining used in life sciences and biomedical workflow. 

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2. Deep UV Microscopy Identifies Prostatic Basal Cells: An Important Biomarker for Prostate Cancer Diagnostics

   https://doi.org/10.34133/2022/9847962  

   Soltani, Soheil; Cheng, Brian; Osunkoya, Adeboye O.; Robles, Francisco E. (January 2022, BME Frontiers)

   Objective and Impact Statement . Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge. In this work, we developed an approach based on label-free, high-resolution molecular imaging with multispectral deep ultraviolet (UV) microscopy which identifies important prostate tissue components, including basal cells. This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer. Introduction . One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts. However, identifying basal cells using hematoxylin and eosin (H&E) stains, which is the standard of care, can be difficult in a subset of cases. In such situations, pathologists often resort to immunohistochemical (IHC) stains for a definitive diagnosis. However, IHC is expensive and time-consuming and requires more tissue sections which may not be available. In addition, IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis. Methods . We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells, luminal cells, and inflammatory cells. The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information. Results . Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity, free of any staining procedures, based on the presence or absence of basal cells. We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells, even in cases where IHC stains fail. Conclusion . Our simple, low-cost, and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components. 

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3. Cellphone enabled point-of-care assessment of breast tumor cytology and molecular HER2 expression from fine-needle aspirates

   https://doi.org/10.1038/s41523-021-00290-0  

   Joh, Daniel Y.; Heggestad, Jacob T.; Zhang, Shengwei; Anderson, Gray R.; Bhattacharyya, Jayanta; Wardell, Suzanne E.; Wall, Simone A.; Cheng, Amy B.; Albarghouthi, Faris; Liu, Jason; et al (July 2021, npj Breast Cancer)

   Abstract Management of breast cancer in limited-resource settings is hindered by a lack of low-cost, logistically sustainable approaches toward molecular and cellular diagnostic pathology services that are needed to guide therapy. To address these limitations, we have developed a multimodal cellphone-based platform—the EpiView-D4—that can evaluate both cellular morphology and molecular expression of clinically relevant biomarkers directly from fine-needle aspiration (FNA) of breast tissue specimens within 1 h. The EpiView-D4 is comprised of two components: (1) an immunodiagnostic chip built upon a “non-fouling” polymer brush-coating (the “D4”) which quantifies expression of protein biomarkers directly from crude cell lysates, and (2) a custom cellphone-based optical microscope (“EpiView”) designed for imaging cytology preparations and D4 assay readout. As a proof-of-concept, we used the EpiView-D4 for assessment of human epidermal growth factor receptor-2 (HER2) expression and validated the performance using cancer cell lines, animal models, and human tissue specimens. We found that FNA cytology specimens (prepared in less than 5 min with rapid staining kits) imaged by the EpiView-D4 were adequate for assessment of lesional cellularity and tumor content. We also found our device could reliably distinguish between HER2 expression levels across multiple different cell lines and animal xenografts. In a pilot study with human tissue (n = 19), we were able to accurately categorize HER2-negative and HER2-positve tumors from FNA specimens. Taken together, the EpiView-D4 offers a promising alternative to invasive—and often unavailable—pathology services and may enable the democratization of effective breast cancer management in limited-resource settings. 

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4. Tumor core biopsies adequately represent immune microenvironment of high-grade serous carcinoma

   https://doi.org/10.1038/s41598-019-53872-1  

   Lara, Olivia D.; Krishnan, Santhoshi; Wang, Zhihui; Corvigno, Sara; Zhong, YanPing; Lyons, Yasmin; Dood, Robert; Hu, Wei; Qi, Lisha; Liu, Jinsong; et al (November 2019, Scientific Reports)

   Abstract The prognostic and therapeutic value of the tumor microenvironment (TME) in various cancer types is of major interest. Characterization of the TME often relies on a small representative tissue sample. However, the adequacy of such a sample for assessing components of the TME is not yet known. Here, we used immunohistochemical (IHC) staining and 7-color multiplex staining to evaluate CD8 (cluster of differentiation 8), CD68, PD-L1 (programmed death-ligand 1), CD34, FAP (fibroblast activation protein), and cytokeratin in 220 tissue cores from 26 high-grade serous ovarian cancer samples. Comparisons were drawn between a larger tumor specimen and smaller core biopsies based on number and location (central tumor vs. peripheral tumor) of biopsies. Our analysis found that the correlation between marker-specific cell subsets in larger tumorversussmaller core was stronger with two core biopsies and was not further strengthened with additional biopsies. Moreover, this correlation was consistently strong regardless of whether the biopsy was taken at the center or at the periphery of the original tumor sample. These findings could have a substantial impact on longitudinal assessment for detection of biomarkers in clinical trials. 

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5. A Pooled Case-only Analysis of Reproductive Risk Factors and Breast Cancer Subtype Among Black Women in the Southeastern United States

   14. Sanderson, M; Pal, T; Beeghly-Fadiel, A; Fadden, M. K; Dujon, S. A; Clinton, C; Jimenez, C; Davis, J; Fortune, M; Thompson, J; et al (July 2021, Cancer epidemiology biomarkers prevention)

   Background: We investigated the association between reproductive risk factors and breast cancer subtype in Black women. On the basis of the previous literature, we hypothesized that the relative prevalence of specific breast cancer subtypes might differ according to reproductive factors. Methods: We conducted a pooled analysis of 2,188 (591 premenopausal, 1,597 postmenopausal) Black women with a primary diagnosis of breast cancer from four studies in the southeastern United States. Breast cancers were classified by clinical subtype. Case-only polytomous logistic regression models were used to estimate ORs and 95% confidence intervals (CI) for HER2+ and triple-negative breast cancer (TNBC) status in relation to estrogen receptor–positive (ER+)/HER2− status (referent) for reproductive risk factors. Results: Relative to women who had ER+/HER2− tumors, women who were age 19–24 years at first birth (OR, 1.78; 95% CI, 1.22–2.59) were more likely to have TNBC. Parous women were less likely to be diagnosed with HER2+ breast cancer and more likely to be diagnosed with TNBC relative to ER+/HER2− breast cancer. Postmenopausal parous women who breastfed were less likely to have TNBC [OR, 0.65 (95% CI, 0.43–0.99)]. Conclusions: This large pooled study of Black women with breast cancer revealed etiologic heterogeneity among breast cancer subtypes. Impact: Black parous women who do not breastfeed are more likely to be diagnosed with TNBC, which has a worse prognosis, than with ER+/HER2− breast cancer. 

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