Karnofsky Performance Status (KPS) ≤60 Is Strongly Associated With Shorter Brain-Specific Progression-Free Survival Among Patients With Metastatic Breast Cancer With Brain Metastases

ObjectiveTo examine the association between Karnofsky Performance Status (“KPS”) and brain-specific progression-free survival (“bsPFS”) among patients with breast cancer brain metastases (“BCBrM”).MethodsUsing a previously compiled retrospective cohort of 683 patients who were treated for BCBrM with surgery and/or radiotherapy at the Sunnybrook Odette Cancer Centre from 2008-2018, electronic records were reviewed to impute KPS scores at the time of BCBrM diagnosis. Patients were then grouped into KPS ≤60 and KPS >60 cohorts. The dataset was analyzed to identify variables that were prognostic for bsPFS and/or overall survival (“OS”) using univariable and multivariable Cox proportional hazards models.ResultsThe mean age of patients was 57 (range 24-93). Most patients (n=622, 91%) had extracranial metastatic disease and 174 (25%) had leptomeningeal disease. 247 patients (36%) had hormone receptor (“HR”)-positive/human endothelial growth factor receptor 2 (“HER2”)-negative tumours, 189 (28%) had HER2-positive disease, and 153 (22%) had triple-negative breast cancer. Of the 331 patients (48%) who could be assigned a KPS cohort, 102 (31%) had KPS ≤60. Most patients were treated with whole brain radiotherapy (n=498, 73%) and/or stereotactic radiosurgery (“SRS”) (n=128, 19%). Median bsPFS was 9 months (95% CI 8-10 months) and median OS was not reached. In univariable analyses, KPS ≤60, presence of leptomeningeal disease, neurological symptoms, ≥2 brain metastases, and not undergoing SRS were factors associated with shorter bsPFS. In a multivariable analysis, KPS ≤60 was the only statistically significant determinant of bsPFS (HR 1.86, 95% CI 1.20-2.88). Although survival data was limited, KPS ≤60 was associated with shorter OS in both univariable (HR 3.12, 95% CI 1.85-5.26) and multivariable (HR 2.95, 95% CI 1.55-5.58) analyses.ConclusionPatients with BCBrM who have a KPS ≤60 have significantly shorter bsPFS and OS than those with KPS >60. KPS should be documented routinely at the time of diagnosis of brain metastases to improve prognostication

Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic Grade

Background: Evaluating histologic grade for breast cancer diagnosis is standard and associated with prognostic outcomes. Current challenges include the time required for manual microscopic evaluation and interobserver variability. This study proposes a computer-aided diagnostic (CAD) pipeline for grading tumors using artificial intelligence. Methods: There were 138 patients included in this retrospective study. Breast core biopsy slides were prepared using standard laboratory techniques, digitized, and pre-processed for analysis. Deep convolutional neural networks (CNNs) were developed to identify the regions of interest containing malignant cells and to segment tumor nuclei. Imaging-based features associated with spatial parameters were extracted from the segmented regions of interest (ROIs). Clinical datasets and pathologic biomarkers (estrogen receptor, progesterone receptor, and human epidermal growth factor 2) were collected from all study subjects. Pathologic, clinical, and imaging-based features were input into machine learning (ML) models to classify histologic grade, and model performances were tested against ground-truth labels at the patient-level. Classification performances were evaluated using receiver-operating characteristic (ROC) analysis. Results: Multiparametric feature sets, containing both clinical and imaging-based features, demonstrated high classification performance. Using imaging-derived markers alone, the classification performance demonstrated an area under the curve (AUC) of 0.745, while modeling these features with other pathologic biomarkers yielded an AUC of 0.836. Conclusion: These results demonstrate an association between tumor nuclear spatial features and tumor grade. If further validated, these systems may be implemented into pathology CADs and can assist pathologists to expeditiously grade tumors at the time of diagnosis and to help guide clinical decisions

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning

Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models were developed to estimate the risk of site-specific DM following local-regional therapy. This retrospective study cohort included 175 patients diagnosed with invasive BC who later developed DM. Clinicopathological information was collected for analysis. Outcome variables were the first site of metastasis (brain, bone or visceral) and the time interval (months) to developing DM. Multivariate statistical analysis and ML-based multivariable gradient boosting machines identified factors associated with these outcomes. Machine learning models predicted the site of DM, demonstrating an area under the curve of 0.74, 0.75, and 0.73 for brain, bone and visceral sites, respectively. Overall, most patients (57%) developed bone metastases, with increased odds associated with estrogen receptor (ER) positivity. Human epidermal growth factor receptor-2 (HER2) positivity and non-anthracycline chemotherapy regimens were associated with a decreased risk of bone DM, while brain metastasis was associated with ER-negativity. Furthermore, non-anthracycline chemotherapy alone was a significant predictor of visceral metastasis. Here, clinicopathologic and treatment variables used in ML prediction models predict the first site of metastasis in BC. Further validation may guide focused patient-specific surveillance practices.</jats:p

Functional features of gene expression profiles differentiating gastrointestinal stromal tumours according to KIT mutations and expression

<p>Abstract</p> <p>Background</p> <p>Gastrointestinal stromal tumours (GISTs) represent a heterogeneous group of tumours of mesenchymal origin characterized by gain-of-function mutations in <it>KIT </it>or <it>PDGFRA </it>of the type III receptor tyrosine kinase family. Although mutations in either receptor are thought to drive an early oncogenic event through similar pathways, two previous studies reported the mutation-specific gene expression profiles. However, their further conclusions were rather discordant. To clarify the molecular characteristics of differentially expressed genes according to GIST receptor mutations, we combined microarray-based analysis with detailed functional annotations.</p> <p>Methods</p> <p>Total RNA was isolated from 29 frozen gastric GISTs and processed for hybridization on GENECHIP^®HG-U133 Plus 2.0 microarrays (Affymetrix). <it>KIT </it>and <it>PDGFRA </it>were analyzed by sequencing, while related mRNA levels were analyzed by quantitative RT-PCR.</p> <p>Results</p> <p>Fifteen and eleven tumours possessed mutations in <it>KIT </it>and <it>PDGFRA</it>, respectively; no mutation was found in three tumours. Gene expression analysis identified no discriminative profiles associated with clinical or pathological parameters, even though expression of hundreds of genes differentiated tumour receptor mutation and expression status. Functional features of genes differentially expressed between the two groups of GISTs suggested alterations in angiogenesis and G-protein-related and calcium signalling.</p> <p>Conclusion</p> <p>Our study has identified novel molecular elements likely to be involved in receptor-dependent GIST development and allowed confirmation of previously published results. These elements may be potential therapeutic targets and novel markers of <it>KIT </it>mutation status.</p

Complete Genome Characterisation of a Novel 26th Bluetongue Virus Serotype from Kuwait

Bluetongue virus is the “type” species of the genus Orbivirus, family Reoviridae. Twenty four distinct bluetongue virus (BTV) serotypes have been recognized for decades, any of which is thought to be capable of causing “bluetongue” (BT), an insect-borne disease of ruminants. However, two further BTV serotypes, BTV-25 (Toggenburg orbivirus, from Switzerland) and BTV-26 (from Kuwait) have recently been identified in goats and sheep, respectively. The BTV genome is composed of ten segments of linear dsRNA, encoding 7 virus-structural proteins (VP1 to VP7) and four distinct non-structural (NS) proteins (NS1 to NS4). We report the entire BTV-26 genome sequence (isolate KUW2010/02) and comparisons to other orbiviruses. Highest identity levels were consistently detected with other BTV strains, identifying KUW2010/02 as BTV. The outer-core protein and major BTV serogroup-specific antigen “VP7” showed 98% aa sequence identity with BTV-25, indicating a common ancestry. However, higher level of variation in the nucleotide sequence of Seg-7 (81.2% identity) suggests strong conservation pressures on the protein of these two strains, and that they diverged a long time ago. Comparisons of Seg-2, encoding major outer-capsid component and cell-attachment protein “VP2” identified KUW2010/02 as 26th BTV, within a 12th Seg-2 nucleotype [nucleotype L]. Comparisons of Seg-6, encoding the smaller outer capsid protein VP5, also showed levels of nt/aa variation consistent with identification of KUW2010/02 as BTV-26 (within a 9th Seg-6 nucleotype - nucleotype I). Sequence data for Seg-2 of KUW2010/02 were used to design four sets of oligonucleotide primers for use in BTV-26, type-specific RT-PCR assays. Analyses of other more conserved genome segments placed KUW2010/02 and BTV-25/SWI2008/01 closer to each other than to other “eastern” or “western” BTV strains, but as representatives of two novel and distinct geographic groups (topotypes). Our analyses indicate that all of the BTV genome segments have evolved under strong purifying selection

How to Succeed in Research During Medical Training: A Qualitative Study

Purpose: The objective of this study was to examine the characteristics of the medical trainee (resident), the supervisor and the project that contribute to successful completion of resident-led research and publication in a peer-reviewed scientific journal. Methods: Qualitative, interview-based study of Internal Medicine trainees and their supervisors. All interviewed trainees published at least one first-author research paper based on a project they completed during residency. Thematic analysis was used to explore key themes from interview transcripts. An iterative, team-based approach was used to develop a coding framework, which was then applied to the data and summarized. Six investigators independently reviewed and coded transcripts, discussed the data collectively and developed key themes by consensus. Results: Thirty participants (15 residents and 15 supervisors) were interviewed. Three major themes for successful resident research projects emerged: 1) the resident is the project champion; 2) supervisors ensure feasibility and timeliness of the project; and, 3) limited time is a challenge that can be overcome. Residents were motivated by fellowship aspirations, prioritized the project and were genuinely interested in the content area. Supervisors were responsible for setting deadlines, limiting the scope of the project and ensuring feasibility of the study design. Existing research funds and infrastructure from other projects were frequently used by supervisors to support research done by trainees. Conclusions: Successful resident-led research projects require leadership and motivation by the resident and engagement, reality-checking and deadline-setting by the supervisor. Responsibilities and expectations in the resident-supervisor relationship should be set early and adequate program resources and funding are required

HR+/HER2– Advanced Breast Cancer Treatment in the First-Line Setting: Expert Review

The approval of CDK4/6 inhibitors has dramatically improved care for the treatment of HR+/HER2– advanced breast cancer, but navigating the rapidly-expanding treatment evidence base is challenging. In this narrative review, we provide best-practice recommendations for the first-line treatment of HR+/HER2– advanced breast cancer in Canada based on relevant literature, clinical guidelines, and our own clinical experience. Due to statistically significant improvements in overall survival and progression-free survival, ribociclib + aromatase inhibitor is our preferred first-line treatment for de novo advanced disease or relapse ≥12 months after completion of adjuvant endocrine therapy and ribociclib or abemaciclib + fulvestrant is our preferred first-line treatment for patients experiencing early relapse. Abemaciclib or palbociclib may be used when alternatives to ribociclib are needed, and endocrine therapy can be used alone in the case of contraindication to CDK4/6 inhibitors or limited life expectancy. Considerations for special populations—including frail and fit elderly patients, as well as those with visceral disease, brain metastases, and oligometastatic disease—are also explored. For monitoring, we recommend an approach across CDK4/6 inhibitors. For mutational testing, we recommend routinely performing ER/PR/HER2 testing to confirm the subtype of advanced disease at the time of progression and to consider ESR1 and PIK3CA testing for select patients. Where possible, engage a multidisciplinary care team to apply evidence in a patient-centric manner

The Canadian Breast Cancer Symposium 2023 Meeting Report

On 15–16 June 2023, healthcare professionals and breast cancer patients and advocates from across Canada met in Toronto, Ontario, for the 2023 Canadian Breast Cancer Symposium (CBSC.). The CBSC. is a national, multidisciplinary event that occurs every 2 years with the goal of developing a personalized approach to the management of breast cancer in Canada. Experts provided state-of-the-art information to help optimally manage breast cancer patients, including etiology, prevention, diagnosis, experimental biology, and therapy of breast cancer and premalignant breast disease. The symposium also had the objectives of increasing communication and collaboration among breast cancer healthcare providers nationwide and providing a comprehensive and real-life review of the many facets of breast cancer. The sessions covered the patient voice, the top breast cancer papers from different disciplines in 2022, artificial intelligence in breast cancer, systemic therapy updates, the management of central nervous system metastases, multidisciplinary management of ductal carcinoma in situ, special populations, optimization-based individual prognostic factors, toxicity management of novel therapeutics, survivorship, and updates in surgical oncology. The key takeaways of these sessions have been summarized in this conference report.Other UBCNon UBCReviewedFacultyResearche