Prediction of post-treatment recurrence in early-stage breast cancer using deep-learning with mid-infrared chemical histopathological imaging.

Predicting long-term recurrence of disease in breast cancer (BC) patients remains a significant challenge for patients with early stage disease who are at low to intermediate risk of relapse as determined using current clinical tools. Prognostic assays which utilize bulk transcriptomics ignore the spatial context of the cellular material and are, therefore, of limited value in the development of mechanistic models. In this study, Fourier-transform infrared (FTIR) chemical images of BC tissue were used to train deep learning models to predict future disease recurrence.

Identification of druggable targets from the interactome of the Androgen Receptor and Serum Response Factor pathways in prostate cancer.

Background: The Androgen Receptor (AR) pathway is crucial in driving the progression of prostate cancer (PCa) to an advanced state. Despite the introduction of second-generation AR antagonists, such as enzalutamide, majority of patients develop resistance. Several mechanisms of resistance have been identified, including the constitutive activation of the AR pathway, the emergence of AR spliced variants, and the influence of other signalling pathways.

Using Patient Experience Surveys to Identify Potential Diagnostic Safety Breakdowns: A Mixed Methods Study.

Objectives: One in 20 outpatients in the United States experiences a diagnostic error each year, but there are no validated methods for collecting feedback from patients on diagnostic safety. We examined patient experience surveys to determine whether patients' free text comments indicated diagnostic breakdowns. Our objective was to evaluate associations between patient-perceived diagnostic breakdowns reported in free text comments and patients' responses to structured survey questions.

"What Else Could It Be?" A Scoping Review of Questions for Patients to Ask Throughout the Diagnostic Process.

Background: Diagnostic errors are a global patient safety challenge. Over 75% of diagnostic errors in ambulatory care result from breakdowns in patient-clinician communication. Encouraging patients to speak up and ask questions has been recommended as one strategy to mitigate these failures.

Artificial intelligence in digital histopathology for predicting patient prognosis and treatment efficacy in breast cancer.

Introduction: Histological images contain phenotypic information predictive of patient outcomes. Due to the heavy workload of pathologists, the time-consuming nature of quantitatively assessing histological features, and human eye limitations to recognize spatial patterns, manually extracting prognostic information in routine pathological workflows remains challenging. Digital pathology has facilitated the mining and quantification of these features utilizing whole-slide image (WSI) scanners and artificial intelligence (AI) algorithms.

IMPROVER (Involving Men with Prostate Cancer in Engaged Research): Assessing Patient Experience With Testing, Diagnosis, And Surveillance.

Background: Our understanding of patient experiences with prostate cancer testing for diagnosis and surveillance is limited. The aim of this study was to collaborate with patients and clinicians to understand their lived experience and unmet needs around the early detection, diagnosis and monitoring (active surveillance) of prostate cancer.

Methods: Two focus groups were held with patients (n = 20) and healthcare professionals (n = 16), to identify the main challenges in prostate cancer detection, diagnosis, and monitoring.

A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring.

Here, we establish a CT-radiomics based method for application in invasive, orthotopic rodent brain tumour models. Twenty four NOD/SCID mice were implanted with U87R-Luc2 GBM cells and longitudinally imaged via contrast enhanced (CE-CT) imaging. Pyradiomics was employed to extract CT-radiomic features from the tumour-implanted hemisphere and non-tumour-implanted hemisphere of acquired CT-scans.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples.

Health diplomacy in action: The cancer legacy of the Good Friday Agreement.

2023 marks the 25th anniversary of the Good Friday Agreement, which led peace in Northern Ireland. As well as its impact on peace and reconciliation, the Good Friday Agreement has also had a lasting positive impact on cancer research and cancer care across the island of Ireland. Pursuant to the Good Friday Agreement, a Memorandum of Understanding (MOU) was signed between the respective Departments of Health in Ireland, Northern Ireland and the US National Cancer Institute (NCI), giving rise to the Ireland - Northern Ireland - National Cancer Institute Cancer Consortium, an unparalleled tripartite agreement designed to nurture and develop linkages between cancer researchers, physicians and allied healthcare professionals across Ireland, Northern Ireland and the US, delivering world class research and better care for cancer patients on the island of Ireland and driving research and innovation in the US.

Cannabidiol Inhibits the Proliferation and Invasiveness of Prostate Cancer Cells.

Prostate cancer is the fifth leading cause of cancer death in men, responsible for over 375,000 deaths in 2020. Novel therapeutic strategies are needed to improve outcomes. Cannabinoids, chemical components of the cannabis plant, are a possible solution.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based).

SRF inhibitors reduce prostate cancer cell proliferation through cell cycle arrest in an isogenic model of castrate-resistant prostate cancer.

Castrate-resistant prostate cancer (CRPC) is challenging to treat, despite improvements with next-generation anti-androgens such as enzalutamide, due to acquired resistance. One of the mechanisms of such resistance includes aberrant activation of co-factors of the androgen receptor (AR), such as the serum response factor (SRF), which was associated with prostate cancer progression and resistance to enzalutamide. Here, we show that inhibition of SRF with three small molecules (CCG-1423, CCG-257081 and lestaurtinib), singly and in combination with enzalutamide, reduces cell viability in an isogenic model of CRPC.

Development, Validation, and Clinical Utility of a Six-gene Signature to Predict Aggressive Prostate Cancer.

Background: Molecular signatures in prostate cancer (PCa) tissue can provide useful prognostic information to improve the understanding of a patient's risk of harbouring aggressive disease.

Objective: To develop and validate a gene signature that adds independent prognostic information to clinical parameters for better treatment decisions and patient management.

Design, Setting, And Participants: Expression of 14 genes was evaluated in radical prostatectomy (RP) tissue from an Irish cohort of PCa patients (n = 426).

A potentially fatal cranial pathology in a specimen of Tarchia.

Skulls of the Mongolian ankylosaurids Shamosaurus, Tarchia, and Saichania were scanned for information about their internal anatomy. Computed tomography (CT) imaging of the Tarchia skull revealed substantial internal anatomical differences from known Campanian North American taxa, particularly in the morphology of the airway. In addition, unexpected anomalies were detected within the airway and sinuses.

1,4-dihydroxy quininib modulates the secretome of uveal melanoma tumour explants and a marker of oxidative phosphorylation in a metastatic xenograft model.

Uveal melanoma (UM) is an intraocular cancer with propensity for liver metastases. The median overall survival (OS) for metastatic UM (MUM) is 1.07 years, with a reported range of 0.

An unusual theropod specimen from the late Maastrichtian of New Jersey.

A set of fragmentary bones excavated from the Inversand Company Pit at Sewell, Gloucester County, NJ, contains portions of broken hollow femur bone that display unusual interior structure. Two hypotheses are considered; (1) the lumina represents the distinctive physical features of medullary bone as described by M. Schweitzer in a series of papers; or (2) the interior bone growth is a pathology.

Application of Artificial Intelligence Techniques to Predict Risk of Recurrence of Breast Cancer: A Systematic Review.

Breast cancer is the most common disease among women, with over 2.1 million new diagnoses each year worldwide. About 30% of patients initially presenting with early stage disease have a recurrence of cancer within 10 years.

Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response.

Unlabelled: While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types.

Implementing subtype-specific pre-clinical models of breast cancer to study pre-treatment aspirin effects.

Backgorund: Prior data suggest pre-diagnostic aspirin use impacts breast tumour biology and patient outcome. Here, we employed faithful surgical resection models of HER2+ and triple-negative breast cancer (TNBC), to study outcome and response mechanisms across breast cancer subtypes.

Method: NOD/SCID mice were implanted with HER2+ MDA-MB-231/LN/2-4/H2N, trastuzumab-resistant HER2+ HCC1954 or a TNBC patient-derived xenograft (PDX).

Analytical Validation of a Novel 6-Gene Signature for Prediction of Distant Recurrence in Estrogen Receptor-Positive, HER2-Negative, Early-Stage Breast Cancer.

Background: OncoMasTR is a recently developed multigene prognostic test for early-stage breast cancer. The test has been developed in a kit-based format for decentralized deployment in molecular pathology laboratories. The analytical performance characteristics of the OncoMasTR test are described in this study.

Plant-derived cannabinoids as anticancer agents.

Substantial preclinical evidence demonstrates the antiproliferative, cytotoxic, and antimetastatic properties of plant-derived cannabinoids (phytocannabinoids) such as cannabidiol and tetrahydrocannabinol. The cumulative body of research into the intracellular mechanisms and phenotypic effects of these compounds supports a logical, judicious progression to large-scale phase II/III clinical trials in certain cancer types to truly assess the efficacy of phytocannabinoids as anticancer agents.

Emerging role for the Serum Response Factor (SRF) as a potential therapeutic target in cancer.

Introduction: The Serum Response Factor (SRF) is a transcription factor involved in three hallmarks of cancer: the promotion of cell proliferation, cell death resistance and invasion and metastasis induction. Many studies have demonstrated a leading role in the development and progression of multiple cancer types, thus highlighting the potential of SRF as a prognostic biomarker and therapeutic target, especially for cancers with poor prognosis.

Areas Covered: This review examines the role of SRF in several cancers in promoting cellular processes associated with cancer development and progression.