Publications by authors named "Lorraine King"

Article Synopsis
  • A study using single-cell RNA sequencing analyzed ductal carcinoma in situ (DCIS) to understand its growth mechanisms and how it may progress to invasive cancer.
  • Researchers identified a mix of cancerous and normal epithelial cells, uncovering significant genetic diversity and different cell states driven by estrogen receptor expression.
  • The findings suggest that changes in specific cell states and loss of basement membrane integrity are linked to the transition from DCIS to invasive breast cancer, highlighting the biological complexity of preinvasive breast diseases.
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Progression from pre-cancers like ductal carcinoma (DCIS) to invasive disease (cancer) is driven by somatic evolution and is altered by clinical interventions. We hypothesized that genetic and/or phenotypic intra-tumor heterogeneity would predict clinical outcomes for DCIS since it serves as the substrate for natural selection among cells. We profiled two samples from two geographically distinct foci from each DCIS in both cross-sectional (N = 119) and longitudinal cohorts (N = 224), with whole exome sequencing, low-pass whole genome sequencing, and a panel of immunohistochemical markers.

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  • * Out of 112 respondents, which included both surgeons and hand therapists, the study found significant variability in surgical decision-making and imaging practices, with most centers favoring ligament reconstruction using a bone anchor.
  • * Findings suggest that there is inconsistency in the treatment approaches for UCL ruptures and a strong interest among medical professionals for future clinical trials to standardize management practices.
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Introduction: Patient-reported outcomes measures (PROMs) are valuable tools for assessing health-related quality of life and treatment effectiveness in individuals with traumatic brain injuries (TBIs). Understanding the experiences of individuals with TBIs in completing PROMs is crucial for improving their utility and relevance in clinical practice.

Methods: Sixteen semi-structured interviews were conducted with a sample of individuals with TBIs.

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Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations.

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Article Synopsis
  • Ductal carcinoma in situ (DCIS) serves as a significant precursor to invasive breast cancer, but its progression to more severe disease is not well understood due to genomic profiling difficulties.
  • The Arc-well method was developed to enable high-throughput single-cell DNA sequencing from challenging formalin-fixed paraffin-embedded samples, validating its efficacy on a variety of tumor types.
  • Analysis revealed that primary DCIS often exhibits whole-genome doubling and diversification, indicating shared genomic origins with recurring cancers, and highlights specific chromosome aberrations linked to the recurrence.
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Ductal carcinoma in-situ (DCIS) accounts for 20-25% of all new breast cancer diagnoses. DCIS has an uncertain risk of progression to invasive breast cancer and a lack of predictive biomarkers may result in relatively high levels (~ 75%) of overtreatment. To identify unique prognostic biomarkers of invasive progression, crystallographic and chemical features of DCIS microcalcifications have been explored.

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  • Ductal carcinoma in situ (DCIS) is the leading precursor to invasive breast cancer (IBC) and varies in its likelihood of progressing.
  • Researchers analyzed 774 DCIS samples over 7.3 years, identifying 812 genes tied to recurrent cancer and creating a predictive classifier for recurrence.
  • The study uncovered important biological pathways related to recurrence, including proliferation and immune response, using advanced methods to create a detailed atlas of breast precancer changes.
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Hypoxia promotes aggressive tumor phenotypes and mediates the recruitment of suppressive T cells in invasive breast carcinomas. We investigated the role of hypoxia in relation to T-cell regulation in ductal carcinoma in situ (DCIS). We designed a deep learning system tailored for the tissue architecture complexity of DCIS, and compared pure DCIS cases with the synchronous DCIS and invasive components within invasive ductal carcinoma cases.

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Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases.

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Ductal carcinoma (DCIS) is frequently associated with breast calcification. This study combines multiple analytical techniques to investigate the heterogeneity of these calcifications at the micrometre scale. X-ray diffraction, scanning electron microscopy and Raman and Fourier-transform infrared spectroscopy were used to determine the physicochemical and crystallographic properties of type II breast calcifications located in formalin fixed paraffin embedded DCIS breast tissue samples.

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Objective: Strict competency frameworks exist for training in, and provision of, clinical neuropsychological assessment practice. However, as in all disciplines, daily clinical practice may drift from the gold standard practice without routine monitoring and audit. A simple-to-use, but thorough and evidence-based audit tool has been developed to facilitate the tracking, maintenance, and discussion of best practice over time.

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Background Improving diagnosis of ductal carcinoma in situ (DCIS) before surgery is important in choosing optimal patient management strategies. However, patients may harbor occult invasive disease not detected until definitive surgery. Purpose To assess the performance and clinical utility of mammographic radiomic features in the prediction of occult invasive cancer among women diagnosed with DCIS on the basis of core biopsy findings.

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In mammography, calcifications are one of the most common signs of breast cancer. Detection of such lesions is an active area of research for computer-aided diagnosis and machine learning algorithms. Due to limited numbers of positive cases, many supervised detection models suffer from overfitting and fail to generalize.

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Article Synopsis
  • The study aimed to identify factors that predict whether individuals with traumatic brain injuries (TBI) attend their first outpatient neuropsychology appointment.
  • A telephone triaging system was introduced, and data from 161 patients were analyzed, revealing that higher age, shorter wait times, and responding to the triage call increased attendance likelihood.
  • The findings suggest that both patient characteristics and service practices influence attendance, emphasizing the need for targeted outreach, particularly for younger patients and those facing longer wait times.
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Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic pipeline to use existing variant-calling strategies to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers.

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  • Evidence shows that tumour infiltrating lymphocytes (TILs) play a crucial role in breast cancer, but their variability in ductal carcinoma in situ (DCIS) and its impact on cancer progression is not fully understood.
  • A new deep learning tool called UNMaSk was created to analyze the spatial arrangement of DCIS tissue and TILs, using automated detection methods for clarity.
  • Findings revealed that pure DCIS had higher overall TIL counts than adjacent DCIS, but TILs were less likely to cluster around pure DCIS ducts, suggesting a different inflammation pattern in adjacent cases that might influence cancer development.
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Abnormalities in cell nuclear morphology are a hallmark of cancer. Histological assessment of cell nuclear morphology is frequently used by pathologists to grade ductal carcinoma in situ (DCIS). Objective methods that allow standardization and reproducibility of cell nuclear morphology assessment have potential to improve the criteria needed to predict DCIS progression and recurrence.

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Intra-tumoral heterogeneity (ITH) could represent clonal evolution where subclones with greater fitness confer more malignant phenotypes and invasion constitutes an evolutionary bottleneck. Alternatively, ITH could represent branching evolution with invasion of multiple subclones. The two models respectively predict a hierarchy of subclones arranged by phenotype, or multiple subclones with shared phenotypes.

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Objective: The goal of this study is to use adjunctive classes to improve a predictive model whose performance is limited by the common problems of small numbers of primary cases, high feature dimensionality, and poor class separability. Specifically, our clinical task is to use mammographic features to predict whether ductal carcinoma in situ (DCIS) identified at needle core biopsy will be later upstaged or shown to contain invasive breast cancer.

Methods: To improve the prediction of pure DCIS (negative) versus upstaged DCIS (positive) cases, this study considers the adjunctive roles of two related classes: atypical ductal hyperplasia (ADH), a non-cancer type of breast abnormity, and invasive ductal carcinoma (IDC), with 113 computer vision based mammographic features extracted from each case.

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The present study investigated the effects of a relaxation training program on self-reported depression and anxiety in participants living with long-term neurological conditions, including acquired brain injury, stroke, Parkinson's disease, and multiple sclerosis.: A five-session relaxation training program, plus a follow-up session was offered to people living with a long-term neurological condition as part of routine clinical practice, and was delivered in their own homes. A self-report measure (Hospital Anxiety and Depression Scale) was administered at the pre- and post-intervention time points and at follow-up, around 5 weeks after the final session.

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Purpose: The aim of this study was to determine whether deep features extracted from digital mammograms using a pretrained deep convolutional neural network are prognostic of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core needle biopsy.

Methods: In this retrospective study, digital mammographic magnification views were collected for 99 subjects with DCIS at biopsy, 25 of which were subsequently upstaged to invasive cancer. A deep convolutional neural network model that was pretrained on nonmedical images (eg, animals, plants, instruments) was used as the feature extractor.

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Rationale And Objectives: This study aimed to determine whether mammographic features assessed by radiologists and using computer algorithms are prognostic of occult invasive disease for patients showing ductal carcinoma in situ (DCIS) only in core biopsy.

Materials And Methods: In this retrospective study, we analyzed data from 99 subjects with DCIS (74 pure DCIS, 25 DCIS with occult invasion). We developed a computer-vision algorithm capable of extracting 113 features from magnification views in mammograms and combining these features to predict whether a DCIS case will be upstaged to invasive cancer at the time of definitive surgery.

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Background: The Papanicolaou (Pap) screen has been successful in reducing cervical cancer; but exhibits low sensitivity when detecting cervical dysplasia. Use of molecular biomarkers in Pap tests may improve diagnostic accuracy.

Design: Monoclonal antibodies to Minichromosome Maintenance Protein 2 (MCM2) and DNA Topoisomerase II α (TOP2A) were selected for use in IHC based on their ability to differentiate normal from diseased cervical tissues in tissue microarrays.

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