bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance of a convolutional autoencoder designed to remove electronic noise from p-type point contact germanium detector signals
Authors: Anderson Mark R. , Basu Vasundhara , Martin Ryan D. , Reed Charlotte Z. , Rowe Noah J. , Shafiee Mehdi , Ye Tianai 
Published: December 2022

AbstractWe present a convolutional autoencoder to denoise pulses from a p-type point contact high-purity germanium detector similar to those used in several rare event searches. While we focus on training procedures that rely on detailed detector physics simulations, we also present implementations requiring only noisy detector pulses to train the model. We validate our autoencoder on both simulated data and calibration data from an $$^{241}$$

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Am source, the latter of which is used to show that the denoised pulses are statistically compatible with data pulses. We demonstrate that our denoising method is able to preserve the underlying shapes of the pulses well, offering improvement over traditional denoising methods. We also show that the shaping time used to calculate energy with a trapezoidal filter can be significantly reduced while maintaining a comparable energy resolution. Under certain circumstances, our denoising method can improve the overall energy resolution. The methods we developed to remove electronic noise are straightforward to extend to other detector technologies. Furthermore, the latent representation from the encoder is also of use in quantifying shape-based characteristics of the signals. Our work has great potential to be used in particle physics experiments and beyond.
Abstract A012: Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS
Authors: Colditz Graham A. , Liu Ying , Strand Siri H. , King Lorraine , Marks Jeff , Maley Carlo , West Robert B. , Hwang E. Shelley 
Published: December 2022

Abstract
Purpose: To examine incremental values of estrogen receptor (ER) status, body mass index (BMI), menopausal status, and a multi-gene classifier over commonly used clinical factors (i.e. age, tumor grade, comedonecrosis, surgical margins, and treatment) in predicting risk of ipsilateral recurrence (IR) within five years after DCIS diagnosis. Methods: A derivation cohort consisted of participants in the discovery cohort, a retrospective multicenter cohort study in women undergoing surgical resection for DCIS between 01/01/1998 and 02/29/2016. The validation cohort provided cases meeting the same eligibility criteria as the discovery cohort. This analysis includes 313 participants with RNA-seq data who either developed IR 1-5 years after initial DCIS diagnosis or were free from subsequent breast events at least five years. Cox proportional hazards regression was used to estimate hazard ratios (HRs) of IR in 216 TBCRC participants (76 with IR). We developed the clinical score using clinical predictors (aforementioned clinical factors and ER) and their regression coefficients from the model with the maximum predictive accuracy (e.g. c-index) and the minimum number of predictors, and the summary score integrating the clinical score and multi-gene classifier. Predictive performance of clinical and summary scores was validated in 97 RAHBT patients (20 with IR). Results: In the discovery cohort, ER negativity, but not BMI or menopausal status, was independently associated with a higher IR risk (HR=2.06, 95% CI 1.18-3.58), and adding ER to the clinical factors-based model increased predictive accuracy (c-index 0.68 to 0.70). The clinical score-adjusted HR was 14.96 (95% CI 8.64-25.91) for multi-gene classifier. Summary scores were better in predicting IR risk than clinical scores (c-index 0.82 vs. 0.70). Compared with their low-risk counterparts, the HR was 4.79 (95% CI 2.55-8.98) in the clinical score-defined high-risk group and 29.02 (95% CI 14.23-59.15) in the summary score-defined high-risk group. In the validation cohort, model performance was improved using summary scores as compared to clinical scores (c-index 0.74 vs. 0.58). Conclusion: Combination of clinical factors and multigene classifier provided more accurate risk estimates of IR within five years after excision of DCIS than clinical factors alone.
Citation Format: Graham A. Colditz, Ying Liu, Siri H. Strand, Lorraine King, Jeff Marks, Carlo Maley, Robert B. West, E. Shelley Hwang. Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr A012.
Abstract B002: A facilitating role for semaphorin-7a in regulating cell invasion and matrix remodeling for DCIS progression
Authors: Dahms Petra 
Published: December 2022

Abstract
Approximately 25% of newly diagnosed breast cancer cases are non-invasive or pre-invasive breast cancers known as ductal carcinoma in situ (DCIS). DCIS can progress to invasive ductal carcinoma (IDC), conferring a more dangerous prognosis; however, there is a gap in knowledge regarding what ultimately causes this transition. Understanding epithelial invasion in the mammary gland will provide insight on how DCIS ultimately progresses to IDC. Our lab has found that DCIS transforms to IDC under the “wound-healing” pressure of postpartum tissue remodeling – termed postpartum mammary gland involution. This invasive transformation is dependent, in part, on collagen-induced cyclooxygenase (COX2) expression. We identified that a membrane-bound signaling molecule, semaphorin-7a (SEMA7A), promotes both collagen deposition and COX-2 expression and therefore DCIS progression. SEMA7A is also naturally upregulated in mammary epithelial cells during postpartum involution and in DCIS relative to normal epithelium. We have identified that inhibition or silencing of SEMA7A can inhibit DCIS invasion. While this demonstrates that SEMA7A expression is sufficient to promote innate capacity for tumor cell invasiveness, we have yet to investigate how SEMA7A interacts with the tumor microenvironment (TME) to promote stromal changes known to advance this transition, such as collagen remodeling or immune cell recruitment. We have demonstrated a potential role for DCIS-associated macrophages in facilitating this transition. Additionally, we have found that SEMA7A polarizes macrophages to an M2-like state, and this promotes remodeling of the lymphatic vasculature as well as tumor cell entry into lymphatic vessels. Furthermore, we have shown that SEMA7A promotes expression of matrix remodeling enzymes that can, in turn, promote shedding of SEMA7A into the TME where it can affect other cell types. We are utilizing intravital imaging to visualize tumor/lymphatic/macrophage interactions as well as second harmonic imaging to visualize SEMA7A-dependent changes in the collagen structure surrounding DCIS lesions. Our results suggest that SEMA7A mediates DCIS invasion through both intrinsic and extrinsic mechanisms, which could facilitate progression to metastasis. By understanding how SEMA7A regulates DCIS progression we can begin to introduce potential targets for preventative therapies for development of invasive disease – including targeting SEMA7A itself. Since SEMA7A is low in most adult tissues it is expected that such a therapeutic would be less toxic for patients than the current prescribed therapies.
Citation Format: Petra Dahms. A facilitating role for semaphorin-7a in regulating cell invasion and matrix remodeling for DCIS progression [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B002.
Abstract B010: Dynamics of fibril collagen remodeling in early DCIS invasions: integrating in silico modeling and tumor histology
Authors: Rejniak Katarzyna A. , Poonja Sharan , Mathur Shreya , Damaghi Mehdi , Bui Marilyn 
Published: December 2022

Abstract
Progression from a ductal carcinoma in situ (DCIS) to an invasive ductal carcinoma (IDC) involves changes in the surrounding extracellular matrix (ECM) fibril patterns before and during the development of ductal microinvasions, i.e., small cohorts of tumor cells that breach the duct and migrate through the stroma. We used a combination of mathematical modeling (with the hybrid agent-based model silicoDCIS) and advanced image analysis techniques applied to histological and fluorescent images in order to identify the rules of cell-ECM interactions that guide the emergence of various alignment patterns of the ECM fibrils. This includes the three tumor associated collagen signatures (TACS) previously observed in laboratory experiments. This integrated approach provides an in silico tool for testing biomechanical hypotheses of tumor cell-tumor matrix interactions. These findings can be compared to the patient histology samples and may help to define criteria for identification of DCIS to IDC transition and future development of new diagnostic methods.
Citation Format: Katarzyna A. Rejniak, Sharan Poonja, Shreya Mathur, Mehdi Damaghi, Marilyn Bui. Dynamics of fibril collagen remodeling in early DCIS invasions: integrating in silico modeling and tumor histology [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B010.
Abstract B012: Exosome microRNAs are progressively altered and contribute to invasive progression of ductal carcinoma in situ
Authors: Hannafon Bethany , Dogra Samrita , Elayapillai Sugantha Priya , Lausen James , Bruns Matthew , Behbod Fariba , Gin Amy , Xu Chao , Zhang Roy , Ding Wei-Qun 
Published: December 2022

Abstract
Ductal carcinoma in situ (DCIS) is a benign breast condition that increases the risk of invasive breast cancer (IBC). Clinically, not all DCIS will progress to IBC and the major drivers of progression are not well understood. The role of small extracellular vesicles, also known as exosomes, is well described in advanced cancers, however, little is known about their role in the invasive progression of in situ breast disease. In this study, we sought to evaluate the role of exosomes and their RNA contents in the progression of DCIS, using the MCF10 isogenic series, in vitro assays and the mouse intraductal model of breast cancer progression. We observed a significant increase of exosome loading of microRNAs (miRNAs) between normal and benign states that increased with each stage. We demonstrate that pro-invasive programs were attenuated when overall exosome and miRNA secretion was inhibited by Rab27A and Dicer knockdown, respectively. Comparisons of exosome miRNA expression changes revealed the greatest differential expression between in situ and invasive cells, with miR-205 being the most significantly different, suggesting a mechanistic role for exosome miRNAs in invasive progression. Modulation of miR-205 levels affected epithelial to mesenchymal transition and the invasive programs in vitro. Progression of DCIS in vivo resulted in increased levels of specific circulating exosome miRNAs, while inhibition of exosome secretion (Rab27A knockdown) attenuated invasive progression and reduced circulating levels of exosome miRNAs. These observations suggest that exosome miRNAs are differentially loaded and expressed, and promote the invasive progression of DCIS and that circulating exosome miRNAs are a potential source of biomarkers of the DCIS to invasive transition.
Citation Format: Bethany Hannafon, Samrita Dogra, Sugantha Priya Elayapillai, James Lausen, Matthew Bruns, Fariba Behbod, Amy Gin, Chao Xu, Roy Zhang, Wei-Qun Ding. Exosome microRNAs are progressively altered and contribute to invasive progression of ductal carcinoma in situ [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B012.
Abstract B014: Improving prediction of second events after DCIS using whole breast mammogram images
Authors: Jiang Shu (Joy) , Colditz Graham A. 
Published: December 2022

Abstract
Purpose: We aim to improve prediction of subsequent events after DCIS. Current models show relatively poor performance predicting subsequent events and often are limited to ipsilateral events. National population-based SEER data including over160,000 cases of DCIS and followed an average of 90 months indicate that second events (including risk of invasive breast cancer – IBC) are equality likely in the ipsilateral and contralateral breast. Thus, additional information on risk may be obtained by more complete modeling of risk estimating recurrence. Mammographic images have been largely ignored despite evidence that even breast density improves prediction of breast cancer in the general population. Furthermore, we have shown whole breast mammogram images (WBI) included in Cox models significantly improves prediction of breast cancer risk over using mammographic breast density alone and breast cancer risk factors. Population: We retrieved digital mammograms for women diagnosed with DCIS at Washington University School of Medicine from 2008 onwards and followed for subsequent diagnosis of pathology confirmed breast lesions. Using more than 100 cases and controls matched on year of mammogram and age we fit Cox models to evaluate risk of ipsilateral invasive breast cancer. To compare and accommodate laterality of subsequent breast lesions, we fit competing risk models using baseline covariates that are available on the women-level as well as WBI that are side-specific. Results: Preliminary analysis shows WBI predicts subsequent invasive breast cancer. Further, we will demonstrate appropriate models adjusting for competing risk gives unbiased estimates of invasive breast cancer. Conclusion: WBI and competing risk analysis improves our understanding of associations for side of occurrence of subsequent breast lesions after an initial diagnosis of DCIS.
Citation Format: Shu (Joy) Jiang, Graham A. Colditz. Improving prediction of second events after DCIS using whole breast mammogram images [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B014.
Abstract B017: Analysis of Wnt signaling and metastasis related protein in invasive ductal carcinoma
Authors: Adeshina Anuoluwapo A. , Ajayi Babajide O. 
Published: December 2022

Abstract
Ductal carcinoma in situ (DCIS) characterizes about 20% of all breast cancers. Breast cancer is the most common cancer among women, the number one cause of cancer mortality, and one of the leading causes of morbidity and mortality for women worldwide. Wnt signaling have been implicated in more than 45% of breast cancer patients and has been shown to decrease survival in breast cancer patients. One of the major challenges of Breast cancer treatment is that it is a heterogeneous disease comprised of four main sub types. Therefore, there is a need to investigate possible signaling pathways that may be specific for each subtype of breast cancer, so as to establish a targeted therapy and management protocol for breast cancer patients This study analyzed the expression of Wnt signaling and metastasis related protein, reversion-inducing cysteine-rich protein with kazal motif (RECK) in molecular subtypes of breast cancer samples of DCIS origin. Formalin Fixed Paraffin Embedded (FFPE) breast tumor samples were used for this study. The breast cancer tissues were divided into estrogen receptor/progesterone receptor (ER/PR) positive, ER positive, human epidermal growth factor receptor 2 (HER-2) positive, Triple negative and Triple positive based on immunohistochemical reactivity for breast cancer subtype specific antibody. These tissues were further processed for expression of Wnt signaling and metastatic related protein. Result from this study showed that Beta-catenin was highly expressed in estrogen receptor and progesterone receptor subtypes of breast cancer whereas adenomatous polyposis coli was positive for estrogen receptor and negative for the other subtypes. Furthermore, the triple negative breast cancer may metastasize earlier than other sub types of breast cancer because it has low expression of RECK when compared with other breast cancer sub-types. In conclusion, subtypes of breast cancer have different expression of Wnt signaling and metastatic related protein expression and as such Wnt signaling may correlate with metastasis in breast cancer.
Citation Format: Anuoluwapo A. Adeshina, Babajide O. Ajayi. Analysis of Wnt signaling and metastasis related protein in invasive ductal carcinoma [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B017.
Abstract IA006: Co-evolving artificial intelligence and pathology
Authors: Yuan Yinyin 
Published: December 2022

Abstract
A fundamental question in cancer biology is how cancers evolve heterogeneity and treatment resistance. The evolution trajectory of cancer is dictated by selective pressures from treatments and the tumor ecosystem. Artificial intelligence (AI) enables us to directly study geographical patterns of the microenvironment in pathological samples, to infer cancer habitats and niches. Significant challenges and open questions remain: how to establish multidisciplinary platforms, develop reproducible AI tools, and how to leverage pathology, genetic, molecular, and clinical data to improve personalized oncology. Charles Darwin described how the intimate coexistence between flowering plants and insects leads to reciprocal evolutionary changes; this is now known as coevolution. Today, through the demolition of disciplinary barriers, AI and pathology can co-evolve to create evolutionary changes and new paradigms. I will discuss our latest progress on combining AI and experimental technologies for spatial histology and omics data analysis. We aim to understand how cancer evolves within diverse environmental conditions. Our work has revealed a high level of geospatial variation in the tumor microenvironment, with profound implications for early diagnosis, biomarker development, and cancer therapeutics.
Citation Format: Yinyin Yuan. Co-evolving artificial intelligence and pathology [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA006.
Abstract IA019: Surgery for DCIS: If, what and when
Authors: Thompson Alastair M. , Bonefas Elizabeth , Carter Stacey , marin Ivan , Javaid Huma , Montalvan Jessica 
Published: December 2022

Abstract
DCIS is traditionally viewed as a surgical problem managed in a comparable way to invasive breast cancer, by breast conservation or mastectomy, to prevent the evolution of intraductal to invasive disease. The need for surgery has been challenged by retrospective case series demonstrating that progression from DCIS to invasive disease is variable, increases with time, but may be modified by endocrine therapy. This data has led to the innovative trials currently under way of active monitoring compared with surgery – the “if” of whether surgery is needed. What surgery to perform requires pathology confirmation of the diagnosis, awareness of the heterogeneity of DCIS (and the potential for sampling to miss invasive disease) together with imaging by mammography, ultrasound and/or MRI. Clinical impressions, imaging and pathology findings direct treatment options. Surgery comprises lumpectomy versus simple, skin sparing or nipple sparing mastectomy (with consideration for reconstruction) potentially partnered with axillary node surgery, at least for those undergoing mastectomy. When (and how) to perform surgical and allied techniques is undergoing change. The required surgical margins of 2mm (for pure DCIS) at the time of conservation to reduce local recurrence remains challenging, with technologies such as optical coherence tomography demonstrating promise for intraoperative determination of adequate margins. Rather than routine sentinel lymph node biopsy, with the attendant risks of lymphedema, iron oxide/dextran coated particles injected prior to surgery, rapidly migrate to and lodge in the axillary nodes and provide an option for delayed axillary surgery if invasive disease is identified. Neoadjuvant approaches to DCIS, targeting the estrogen receptor or HER2, to downstage the extent of surgery are less favored than for invasive breast cancers, but DCIS may be the residue left after neoadjuvant treatment for invasive disease. However, adjuvant endocrine therapy and adjuvant radiotherapy may each have an impact on reducing the chance of re-occurrence of DCIS or development of invasive cancer. Currently, surgery remains the primary treatment for DCIS. If surgery is performed, what is done and when surgery takes place varies with the nature, the extent of the DCIS and is influenced by patient preference.
Citation Format: Alastair M. Thompson, Elizabeth Bonefas, Stacey Carter, Ivan marin, Huma Javaid, Jessica Montalvan. Surgery for DCIS: If, what and when [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA019.
Abstract IA035: DCIS to IDC progression - a key step of immune escape
Authors: Polyak Kornelia 
Published: December 2022

Abstract
The cellular and molecular mechanisms underlying ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) transition are poorly understood. We have analyzed genetic, gene expression, epigenetic profiles of cells composing the tumor and identified cell type-specific changes during tumor progression. Importantly, we detected significant changes in the immune cell composition during tumor progression implying immune escape in invasive tumors and active adaptive immune response in DCIS. We demonstrate that these progression stage-specific alterations are also present in a rat model of breast cancer and that combined targeting of multiple components of the tumor ecosystem increases the efficacy of anti-cancer therapies. Our data highlight the role of microenvironmental, especially immune-related changes in driving breast tumor progression and emphasize the importance of studying pre-invasive tumors.
Citation Format: Kornelia Polyak. DCIS to IDC progression - a key step of immune escape [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA035.