A comprehensive analysis of SOX17 expression by immunohistochemistry in human epithelial tumors, with an emphasis on gynecologic tumors.

OBJECTIVES: The objective of this study was to evaluate SOX17, a transcription factor from the Sry high-mobility group-related box superfamily, as a diagnostic marker to determine site of origin using both whole-tissue sections and tissue microarrays (TMAs). METHODS: SOX17 immunohistochemistry was performed on gynecologic and nongynecologic tissues (N = 1004) using whole-tissue sections and both internally constructed and commercially available TMAs. SOX17 nuclear reactivity was scored as positive or negative on the whole-tissue sections and using the semiquantitative H score method on TMAs. RESULTS: Using both whole-tissue sections and TMAs, SOX17 was positive in 94% (n = 155) of endometrial tumors and 96% (n = 242) of ovarian tumors. All breast cases (n = 241) and vulvar/cervical squamous cell carcinomas (n = 150) were negative. Among 1004 tumors from 20 sites, the only organs with positive tumors were ovary, uterus, and testis. CONCLUSIONS: SOX17 is a sensitive and specific marker for gynecologic origin in the tissues tested and may be a valuable adjunct to PAX8 and other commonly used markers to confirm endometrial or ovarian origin. SOX17 expression is lower in mucinous tumors, endocervical adenocarcinoma, high-grade neuroendocrine tumors, and undifferentiated/dedifferentiated endometrial carcinoma.

Immunohistochemical Profile of Triple-Negative Breast Cancers: SOX10 and AR Dual Negative Tumors Have Worse Outcomes.

Triple-negative breast cancer (TNBC) refers to an estrogen receptor-negative, progesterone receptor-negative, and HER2-negative breast cancer. Although accepted as a clinically valid category, TNBCs are heterogeneous at the histologic, immunohistochemical, and molecular levels. Gene expression profiling studies have molecularly classified TNBCs into multiple groups, but the prognostic significance is unclear except for a relatively good prognosis for the luminal androgen receptor subtype. Immunohistochemistry (IHC) has been used as a surrogate for basal and luminal subtypes within TNBC, but prognostication of TNBC using IHC is not routinely performed. We aimed to study immunophenotypic correlations in a well-annotated cohort of consecutive TNBCs, excluding postneoadjuvant chemotherapy cases. Tissue microarrays were constructed from a total of 245 TNBC cases. IHC stains were performed and consisted of luminal (AR and INPP4B), basal (SOX10, nestin, CK5, and EGFR), and diagnostic (GCDFP15, mammaglobin, GATA3, and TRPS1) markers. Survival analysis was performed to assess the significance of clinical-pathologic variables including age, histology, grade, lymphovascular invasion, Nottingham prognostic index category, American Joint Committee on Cancer (AJCC) stage, stromal tumor-infiltrating lymphocytes at 10% increment, CD8+ T-cell count, Ki-67 index, PD-L1 status, and chemotherapy along with the results of IHC markers. Apocrine tumors show prominent reactivity for luminal markers and GCDFP15, whereas no special-type carcinomas are often positive for basal markers. TRPS1 is a sensitive marker of breast carcinoma but shows low or no expression in apocrine tumors. High AJCC stage, lack of chemotherapy, and dual SOX10/AR negativity are associated with worse outcomes on both univariable and multivariable analyses. Lymphovascular invasion and higher Nottingham prognostic index category were associated with worse outcomes on univariable but not multivariable analysis. The staining for IHC markers varies based on tumor histology, which may be considered in determining breast origin. Notably, we report that SOX10/AR dual negative status in TNBC is associated with a worse prognosis along with AJCC stage and chemotherapy status.

Characteristics and utility of high-resolution optical coherence microscopy images of endocervical canal lesions.

OBJECTIVES: To investigate optical coherence microscopy (OCM) imaging features and the application value of these high-resolution images for identifying endocervical canal lesions (ECLs), which is a clinical dilemma in cervical cancer screening programs. METHODS: In total, 520 OCM images were obtained by scanning the cervical canal lesions with an ultra-high-resolution OCM system (204 specimens from 73 patients). The OCM morphologic characteristics of ECLs were observed and summarized, and then 3 researchers performed a diagnostic test of OCM images of cervical canal lesions. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, 95% confidence interval of each parameter, and interinvestigator agreement (κ) were calculated. RESULTS: Normal endocervix, cysts, squamous metaplasia, high-grade squamous intraepithelial lesions involving glands, and invasive carcinoma had distinct OCM characteristics, which correlated well with corresponding H&E histologic sections. The accuracy, sensitivity, and specificity of the 3 researchers were 90.6%, 89.3% (95% CI, 86.5%-91.7%) and 91.6% (95% CI, 89.2%-93.5%), respectively. The positive predictive value was 90.1% (95% CI, 87.3%-92.4%), and the negative predictive value was 90.9% (95% CI, 88.5%-92.9%), with almost perfect agreement (κ = 0.874). CONCLUSIONS: The application of the OCM system in cervical canal lesions is feasible and could help improve detection of occult ECLs in cervical cancer screening programs. This study lays the foundation for further research on OCM in cervical canal lesions in vivo, which also has a potential impact on projecting pathologic evaluation beyond what is currently possible, perhaps globally.

Upgrade Rates of Variant Lobular Carcinoma In Situ Compared to Classic Lobular Carcinoma In Situ Diagnosed in Core Needle Biopsies: A 10-Year Single Institution Retrospective Study.

The primary aim of this study was to determine the upgrade rates of variant lobular carcinoma in situ (V-LCIS, ie, combined florid [F-LCIS] and pleomorphic [P-LCIS]) compared with classic LCIS (C-LCIS) when diagnosed on core needle biopsy (CNB). The secondary goal was to determine the rate of progression/development of invasive carcinoma on long-term follow-up after primary excision. After institutional review board approval, our institutional pathology database was searched for patients with "pure" LCIS diagnosed on CNB who underwent subsequent excision. Radiologic findings were reviewed, radiologic-pathologic (rad-path) correlation was performed, and follow-up patient outcome data were obtained. One hundred twenty cases of LCIS were identified on CNB (C-LCIS = 97, F-LCIS = 18, and P-LCIS = 5). Overall upgrade rates after excision for C-LCIS, F-LCIS, and P-LCIS were 14% (14/97), 44% (8/18), and 40% (2/5), respectively. Of the total cases, 79 (66%) were deemed rad-path concordant. Of these, the upgrade rate after excision for C-LCIS, F-LCIS, and P-LCIS was 7.5% (5 of 66), 40% (4 of 10), and 0% (0 of 3), respectively. The overall upgrade rate for V-LCIS was higher than for C-LCIS (P = .004), even for the cases deemed rad-path concordant (P value: .036). Most upgraded cases (23 of 24) showed pT1a disease or lower. With an average follow-up of 83 months, invasive carcinoma in the ipsilateral breast was identified in 8/120 (7%) cases. Six patients had died: 2 of (contralateral) breast cancer and 4 of other causes. Because of a high upgrade rate, V-LCIS diagnosed on CNB should always be excised. The upgrade rate for C-LCIS (even when rad-path concordant) is higher than reported in many other studies. Rad-path concordance read, surgical consultation, and individualized decision making are recommended for C-LCIS cases. The risk of developing invasive carcinoma after LCIS diagnosis is small (7% with ∼7-year follow-up), but active surveillance is required to diagnose early-stage disease.

Clinicopathologic and genomic features of lobular like invasive mammary carcinoma: is it a distinct entity?

This study describes "lobular-like invasive mammary carcinomas" (LLIMCas), a group of low- to intermediate-grade invasive mammary carcinomas with discohesive, diffusely infiltrative cells showing retained circumferential membranous immunoreactivity for both E-cadherin and p120. We analyzed the clinical-pathologic features of 166 LLIMCas compared to 104 classical invasive lobular carcinomas (ILCs) and 100 grade 1 and 2 invasive ductal carcinomas (IDCs). Tumor size and pT stage of LLIMCas were intermediate between IDCs and ILCs, and yet often underestimated on imaging and showed frequent positive margins on the first resection. Despite histomorphologic similarities to classical ILC, the discohesion in LLIMCa was independent of E-cadherin/p120 immunophenotypic alteration. An exploratory, hypothesis-generating analysis of the genomic features of 14 randomly selected LLIMCas and classical ILCs (7 from each category) was performed utilizing an FDA-authorized targeted capture sequencing assay (MSK-IMPACT). None of the seven LLIMCas harbored CDH1 loss-of-function mutations, and none of the CDH1 alterations detected in two of the LLIMCas was pathogenic. In contrast, all seven ILCs harbored CDH1 loss-of-function mutations coupled with the loss of heterozygosity of the CDH1 wild-type allele. Four of the six evaluable LLIMCas were positive for CDH1 promoter methylation, which may partially explain the single-cell infiltrative morphology seen in LLIMCa. Further studies are warranted to better define the molecular basis of the discohesive cellular morphology in LLIMCa. Until more data becomes available, identifying LLIMCas and distinguishing them from typical IDCs and ILCs would be justified. In patients with LLIMCas, preoperative MRI should be entertained to guide surgical management.

Utility of TRPS1 immunohistochemistry in confirming breast carcinoma: Emphasis on staining in triple-negative breast cancers and gynecologic tumors.

OBJECTIVES: Our aim was to explore the performance of TRPS1 as an immunohistochemical diagnostic marker; find the optimal conditions for its use in breast carcinomas, especially triple-negative breast cancers (TNBCs); and compare its results in carcinomas of a select few organ sites, with an emphasis on gynecologic tumors. METHODS: Tissue microarrays from breast carcinomas (n = 197), endometrial adenocarcinomas (n = 69), ovarian tumors (n = 250), vulvar squamous cell carcinomas (n = 97), pancreatic ductal adenocarcinomas (n = 20), and gastric adenocarcinomas (n = 12) were stained with TRPS1 using 2 different conditions (protocol 1: high pH; protocol 2: low pH). Breast carcinomas consisted of hormone receptor (HR)-positive/ERBB2 (formerly HER2 or HER2/neu)-negative (n = 53) samples, HR-positive/ERBB2-positive (n = 6) samples, and TNBCs (n = 138). RESULTS: Comparing TRPS1 results in breast carcinomas vs tumors from other organ sites, the sensitivity of TRPS1 was 91% and 87%, respectively, while the specificity was 66% and 74% for protocol 1 and 2, respectively. For TNBCs vs gynecologic tumors, the sensitivity of TRPS1 was 89% and 85%, respectively, while the specificity was 65% and 73%, respectively. CONCLUSIONS: TRPS1 stains approximately 90% of breast carcinomas but also up to 71% of endometrial carcinomas, albeit with a weaker median expression. Our data show that although TRPS1 is a highly sensitive marker for TNBCs, it is not as highly specific as previously reported.

The Utility of SOX10 Immunohistochemical Staining in Breast Pathology.

OBJECTIVES: SOX10 expression helps identify melanocytic lesions. Over time, novel uses have been identified, such as expression in triple-negative breast cancer (TNBC). We evaluated the usefulness of SOX10 in breast pathology-specifically, identification and subtyping of TNBC and distinction from gynecologic carcinomas, use as a myoepithelial marker, and in the distinction of usual ductal hyperplasia (UDH) from atypical ductal hyperplasia (ADH). METHODS: Several breast and gynecologic carcinoma tissue microarrays containing a total of 492 cases were stained with SOX10. Whole sections of 34 ADH, 50 UDH, and 29 ductal carcinoma in situ (DCIS) samples were also stained with SOX10. RESULTS: SOX10 expression was identified in 67% of consecutive TNBC cases. Expression was mostly seen in nonapocrine, androgen receptor (AR)-negative TNBCs. All gynecologic carcinomas (n = 157) were negative. All UDH cases showed mosaic SOX10 expression, while all ADH cases lacked expression. All estrogen receptor (ER)-positive DCIS (n = 19) specimens were negative for SOX10, while 2 of 10 ER-negative DCIS specimens were positive for SOX10. The latter 2 cases showed SOX10-positive invasive carcinomas. CONCLUSIONS: SOX10 identifies nonluminal AR-type TNBC and is useful in distinguishing TNBC from gynecologic carcinomas. SOX10 can distinguish UDH from ADH. SOX10 is not useful in distinguishing ADH from DCIS.

Prognostic Significance of Three-Tiered World Health Organization Classification of Phyllodes Tumor and Correlation to Singapore General Hospital Nomogram.

OBJECTIVES: Phyllodes tumors (PTs) are categorized by the World Health Organization (WHO) as benign, borderline, and malignant. Singapore General Hospital (SGH) nomogram is a recurrence risk assessment tool for PT, which uses cytologic atypia, mitosis, stromal overgrowth, and the surgical margin status. We studied the prognostic significance of WHO classification and its correlation to the SGH nomogram. METHODS: We identified 270 consecutive cases of PT (195 benign, 49 borderline, 26 malignant). Follow-up was available on 246 cases (mean follow-up of 51 months). RESULTS: The recurrence rates were 2% (4 of 176) for benign, 4% (2 of 46) for borderline, and 25% (6 of 24) for malignant (log-rank test P < .0001 for recurrence-free survival). Only five patients with malignant PT experienced distant recurrence. Stromal overgrowth was an independent predictor of recurrence-free survival on multivariable analysis. The mean nomogram scores for benign, borderline, and malignant PT were 20, 20.3, and 32, respectively. The higher than expected score for benign PT was due to positive margins in 39% of cases. CONCLUSIONS: The WHO three-tiered classification of PT is prognostic. Despite positive margin status, most benign PTs do not recur. Other features of the nomogram help in determining recurrence but are also used for WHO classification.

Clinical-pathologic characteristics and response to neoadjuvant chemotherapy in triple-negative low Ki-67 proliferation (TNLP) breast cancers.

Triple-negative breast cancers (TNBCs) often have a high Ki-67 proliferation index and respond favorably to neoadjuvant chemotherapy (NACT) with pathologic complete response (pCR) resulting in ~40% of cases. Nevertheless, morbidity/mortality remain high, mostly due to recurrence in patients with residual disease. In contrast, the incidence and clinical features of TNBC with low proliferation (TNLP), defined as TNBC with a Ki-67 index of ≤30% remains unknown. We report 70 cases of TNLP identified at our center from 2008 to 2018, including 18 treated with NACT. TNLP tumors represent <1% of all breast cancers, and ~5-10% of TNBCs. Ninety percent of carcinomas were grade I/II and 70% were either pure apocrine or showed apocrine differentiation. Fifty cases had available immunohistochemistry results; 80%, 84%, 22%, and 20% were positive for AR, INPP4B, nestin, and SOX10, respectively. With a median follow-up of 72 months, 14% experienced recurrence, and 11% died of breast cancer. The tumor stage was prognostic. Among 39 stage-I patients, 18 (46%) received chemotherapy, but this did not impact survival. There was a trend for improved recurrence-free survival with chemotherapy in stage-II patients. Of the 18 patients treated with NACT, 2 (11%) showed pCR; these were notable for either high stromal TILs or a high mitotic count despite a low Ki-67 index. TNLPs are enriched in low to intermediate-grade carcinomas with apocrine features. Due to overall good prognosis of stage-I TNLP and the lack of clear benefit of chemotherapy, de-escalation of chemotherapy may be considered in select patients with stage-I TNLP.

Explainable AI (xAI) for Anatomic Pathology.

Pathologists are adopting whole slide images (WSIs) for diagnosis, thanks to recent FDA approval of WSI systems as class II medical devices. In response to new market forces and recent technology advances outside of pathology, a new field of computational pathology has emerged that applies artificial intelligence (AI) and machine learning algorithms to WSIs. Computational pathology has great potential for augmenting pathologists' accuracy and efficiency, but there are important concerns regarding trust of AI due to the opaque, black-box nature of most AI algorithms. In addition, there is a lack of consensus on how pathologists should incorporate computational pathology systems into their workflow. To address these concerns, building computational pathology systems with explainable AI (xAI) mechanisms is a powerful and transparent alternative to black-box AI models. xAI can reveal underlying causes for its decisions; this is intended to promote safety and reliability of AI for critical tasks such as pathology diagnosis. This article outlines xAI enabled applications in anatomic pathology workflow that improves efficiency and accuracy of the practice. In addition, we describe HistoMapr-Breast, an initial xAI enabled software application for breast core biopsies. HistoMapr-Breast automatically previews breast core WSIs and recognizes the regions of interest to rapidly present the key diagnostic areas in an interactive and explainable manner. We anticipate xAI will ultimately serve pathologists as an interactive computational guide for computer-assisted primary diagnosis.

Oncologic Safety of Fat Grafting for Autologous Breast Reconstruction in an Animal Model of Residual Breast Cancer.

BACKGROUND: Clinical outcomes suggest that postoncologic reconstruction with fat grafting yields cumulative incidence curves of recurrence comparable to those of other breast reconstruction procedures; however, results from experimental research studies suggest that adipose stem cells can stimulate cancer growth. In this study, a novel animal model of residual cancer was developed in mouse mammary pads to test whether lipofilling impacts the probability of locoregional recurrence of breast cancer after breast conserving surgery. METHODS: Mammary fat pads of female NOD-SCID gamma mice were each injected with MCF-7 cells in Matrigel. Tumors were allowed to engraft for 2 weeks, after which time either sterile saline (n = 20) or human fat graft (n = 20) was injected adjacent to tumor sites. After 8 weeks, tumors were assessed for volume measurement, histologic grade, Ki67 positivity, and metastatic spread. RESULTS: Animals receiving lipofilling after tumor cell engraftment had lower tumor volume and mass (p = 0.046 and p = 0.038, respectively). Macroscopic invasion was higher in the saline group. Histologic grade was not significantly different in the two groups (p = 0.17). Ki67 proliferation index was lower in tumors surrounded by fat graft (p = 0.01). No metastatic lesion was identified in any animal. CONCLUSIONS: Adipose transfer for breast reconstruction performed in the setting of residual breast tumor in a clinically relevant animal model did not increase tumor size, proliferation, histologic grade, or metastatic spread. This study supports the oncologic safety of lipofilling as part of the surgical platform for breast reconstruction after cancer therapy.

Pathologists' Computer-Assisted Diagnosis: A Mock-up of a Prototype Information System to Facilitate Automation of Pathology Sign-out.

CONTEXT: - Pathologists' computer-assisted diagnosis (pCAD) is a proposed framework for alleviating challenges through the automation of their routine sign-out work. Currently, hypothetical pCAD is based on a triad of advanced image analysis, deep integration with heterogeneous information systems, and a concrete understanding of traditional pathology workflow. Prototyping is an established method for designing complex new computer systems such as pCAD. OBJECTIVE: - To describe, in detail, a prototype of pCAD for the sign-out of a breast cancer specimen. DESIGN: - Deidentified glass slides and data from breast cancer specimens were used. Slides were digitized into whole-slide images with an Aperio ScanScope XT, and screen captures were created by using vendor-provided software. The advanced workflow prototype was constructed by using PowerPoint software. RESULTS: - We modeled an interactive, computer-assisted workflow: pCAD previews whole-slide images in the context of integrated, disparate data and predefined diagnostic tasks and subtasks. Relevant regions of interest (ROIs) would be automatically identified and triaged by the computer. A pathologist's sign-out work would consist of an interactive review of important ROIs, driven by required diagnostic tasks. The interactive session would generate a pathology report automatically. CONCLUSIONS: - Using animations and real ROIs, the pCAD prototype demonstrates the hypothetical sign-out in a stepwise fashion, illustrating various interactions and explaining how steps can be automated. The file is publicly available and should be widely compatible. This mock-up is intended to spur discussion and to help usher in the next era of digitization for pathologists by providing desperately needed and long-awaited automation.

Spatial Statistics for Segmenting Histological Structures in H&E Stained Tissue Images.

Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g., tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. This paper focuses on segmenting histological structures in hematoxylin- and eosin-stained images of breast tissues, e.g., invasive carcinoma, carcinoma in situ, atypical and normal ducts, adipose tissue, and lymphocytes. We propose two graph-theoretic segmentation methods based on local spatial color and nuclei neighborhood statistics. For benchmarking, we curated a data set of 232 high-power field breast tissue images together with expertly annotated ground truth. To accurately model the preference for histological structures (ducts, vessels, tumor nets, adipose, etc.) over the remaining connective tissue and non-tissue areas in ground truth annotations, we propose a new region-based score for evaluating segmentation algorithms. We demonstrate the improvement of our proposed methods over the state-of-the-art algorithms in both region- and boundary-based performance measures.

Exploring virtual reality technology and the Oculus Rift for the examination of digital pathology slides.

BACKGROUND: Digital slides obtained from whole slide imaging (WSI) platforms are typically viewed in two dimensions using desktop personal computer monitors or more recently on mobile devices. To the best of our knowledge, we are not aware of any studies viewing digital pathology slides in a virtual reality (VR) environment. VR technology enables users to be artificially immersed in and interact with a computer-simulated world. Oculus Rift is among the world's first consumer-targeted VR headsets, intended primarily for enhanced gaming. Our aim was to explore the use of the Oculus Rift for examining digital pathology slides in a VR environment. METHODS: An Oculus Rift Development Kit 2 (DK2) was connected to a 64-bit computer running Virtual Desktop software. Glass slides from twenty randomly selected lymph node cases (ten with benign and ten malignant diagnoses) were digitized using a WSI scanner. Three pathologists reviewed these digital slides on a 27-inch 5K display and with the Oculus Rift after a 2-week washout period. Recorded endpoints included concordance of final diagnoses and time required to examine slides. The pathologists also rated their ease of navigation, image quality, and diagnostic confidence for both modalities. RESULTS: There was 90% diagnostic concordance when reviewing WSI using a 5K display and Oculus Rift. The time required to examine digital pathology slides on the 5K display averaged 39 s (range 10-120 s), compared to 62 s with the Oculus Rift (range 15-270 s). All pathologists confirmed that digital pathology slides were easily viewable in a VR environment. The ratings for image quality and diagnostic confidence were higher when using the 5K display. CONCLUSION: Using the Oculus Rift DK2 to view and navigate pathology whole slide images in a virtual environment is feasible for diagnostic purposes. However, image resolution using the Oculus Rift device was limited. Interactive VR technologies such as the Oculus Rift are novel tools that may be of use in digital pathology.

Advanced Imaging Techniques for the Pathologist.

Advanced imaging refers to direct microscopic imaging of tissue, without the need for traditional hematoxylin-eosin (H&E) microscopy, including microscope slides or whole-slide images. A detailed example is presented of optical coherence tomography (OCT), an imaging technique based on reflected light. Experience and example images are discussed in the larger context of the evolving relationship of surgical pathology to clinical patient care providers. Although these techniques are diagnostically promising, it is unlikely that they will directly supplant H&E histopathology. It is likely that OCT and related technologies will provide narrow, targeted diagnosis in a variety of in vivo (patient) and ex vivo (specimen) applications.

Advanced Imaging Techniques for the Pathologist.

Advanced imaging refers to direct microscopic imaging of tissue, without the need for traditional hematoxylin-eosin (H&E) microscopy, including microscope slides or whole-slide images. A detailed example is presented of optical coherence tomography (OCT), an imaging technique based on reflected light. Experience and example images are discussed in the larger context of the evolving relationship of surgical pathology to clinical patient care providers. Although these techniques are diagnostically promising, it is unlikely that they will directly supplant H&E histopathology. It is likely that OCT and related technologies will provide narrow, targeted diagnosis in a variety of in vivo (patient) and ex vivo (specimen) applications.

A Role for Histone H2B Variants in Endocrine-Resistant Breast Cancer.

Acquired resistance to aromatase inhibitors (AIs) remains a major clinical problem in the treatment of estrogen receptor-positive (ER+) breast cancer. We and others have previously reported widespread changes in DNA methylation using breast cancer cell line models of endocrine resistance. Here, we show that the histone variant HIST1H2BE is hypomethylated in estrogen deprivation-resistant C4-12 and long-term estrogen-deprived (LTED) cells compared with parental MCF-7 cells. As expected, this hypomethylation associates with increased expression of HIST1H2BE in C4-12 and LTED cells. Both overexpression and downregulation of HIST1H2BE caused decreased proliferation in breast cancer cell lines suggesting the need for tightly controlled expression of this histone variant. Gene expression analysis showed varied expression of HIST1H2BE in a large panel of breast cancer cell lines, without restriction to specific molecular subtypes. Analysis of HIST1H2BE messenger RNA (mRNA) expression in ER+ AI-treated breast tumors showed significantly higher expression in resistant (n = 19) compared with sensitive (n = 37) tumors (p = 0.01). Using nanostring analysis, we measured expression of all 61 histone variants in endocrine-resistant and endocrine-sensitive tumors. We found significant overexpression of 22 variant histone genes in tumors resistant to AI therapy. In silico The Cancer Genome Atlas (TCGA) analysis showed frequent amplification of the HIST1 locus. In summary, our studies show, for the first time, that overexpression of histone variants might be important in endocrine response in ER+ breast cancer, and that overexpression is at least in part mediated via epigenetic mechanisms and amplifications. Future studies addressing endocrine response should include a potential role of these currently understudied histone variants.

21(st) century workflow: A proposal.

Digital pathology is rapidly developing, but early systems have been slow to gain traction outside of niche applications such as: Second-opinion telepathology, immunostain interpretation, and intraoperative telepathology. Pathologists have not yet developed a well-articulated plan for effectively utilizing digital imaging technology in their work. This paper outlines a proposal that is intended to begin meaningful progress toward achieving helpful computer-assisted pathology sign-out systems, such as pathologists' computer-assisted diagnosis (pCAD). pCAD is presented as a hypothetical intelligent computer system that would integrate advanced image analysis and better utilization of existing digital pathology data from lab information systems. A detailed example of automated digital pathology is presented, as an automated breast cancer lymph node sign-out. This proposal provides stakeholders with a conceptual framework that can be used to facilitate development work, communication, and identification of new automation strategies.

Can digital pathology result in cost savings? A financial projection for digital pathology implementation at a large integrated health care organization.

BACKGROUND: Digital pathology offers potential improvements in workflow and interpretive accuracy. Although currently digital pathology is commonly used for research and education, its clinical use has been limited to niche applications such as frozen sections and remote second opinion consultations. This is mainly due to regulatory hurdles, but also to a dearth of data supporting a positive economic cost-benefit. Large scale adoption of digital pathology and the integration of digital slides into the routine anatomic/surgical pathology "slide less" clinical workflow will occur only if digital pathology will offer a quantifiable benefit, which could come in the form of more efficient and/or higher quality care. AIM: As a large academic-based health care organization expecting to adopt digital pathology for primary diagnosis upon its regulatory approval, our institution estimated potential operational cost savings offered by the implementation of an enterprise-wide digital pathology system (DPS). METHODS: Projected cost savings were calculated for the first 5 years following implementation of a DPS based on operational data collected from the pathology department. Projected savings were based on two factors: (1) Productivity and lab consolidation savings; and (2) avoided treatment costs due to improvements in the accuracy of cancer diagnoses among nonsubspecialty pathologists. Detailed analyses of incremental treatment costs due to interpretive errors, resulting in either a false positive or false negative diagnosis, was performed for melanoma and breast cancer and extrapolated to 10 other common cancers. RESULTS: When phased in over 5-years, total cost savings based on anticipated improvements in pathology productivity and histology lab consolidation were estimated at $12.4 million for an institution with 219,000 annual accessions. The main contributing factors to these savings were gains in pathologist clinical full-time equivalent capacity impacted by improved pathologist productivity and workload distribution. Expanding the current localized specialty sign-out model to an enterprise-wide shared general/subspecialist sign-out model could potentially reduce costs of incorrect treatment by $5.4 million. These calculations were based on annual over and under treatment costs for breast cancer and melanoma estimated to be approximately $26,000 and $11,000/case, respectively, and extrapolated to $21,500/case for other cancer types. CONCLUSIONS: The projected 5-year total cost savings for our large academic-based health care organization upon fully implementing a DPS was approximately $18 million. If the costs of digital pathology acquisition and implementation do not exceed this value, the return on investment becomes attractive to hospital administrators. Furthermore, improved patient outcome enabled by this technology strengthens the argument supporting adoption of an enterprise-wide DPS.