Quantifying cell divisions along evolutionary lineages in cancer.

Cell division drives somatic evolution but is challenging to quantify. We developed a framework to count cell divisions with DNA replication-related mutations in polyguanine homopolymers. Analyzing 505 samples from 37 patients, we studied the milestones of colorectal cancer evolution.

Determining the time to cholangiocarcinoma in pediatric-onset PSC-IBD.

Primary sclerosing cholangitis (PSC) is a risk factor for cholangiocarcinoma. When a child is diagnosed with both PSC and inflammatory bowel disease (IBD), evidence-based information on counseling families and risk management of developing cholangiocarcinoma is limited. In this case series (PubMed/collaborators), we included patients with PSC-IBD who developed cholangiocarcinoma and contacted authors to determine an event curve specifying the time between the second diagnosis (IBD or PSC) and a diagnosis of cholangiocarcinoma.

Clinical outcomes and ctDNA correlates for CAPOX BETR: a phase II trial of capecitabine, oxaliplatin, bevacizumab, trastuzumab in previously untreated advanced HER2+ gastroesophageal adenocarcinoma.

Preclinical studies suggest that simultaneous HER2/VEGF blockade may have cooperative effects in gastroesophageal adenocarcinomas. In a single-arm investigator initiated clinical trial for patients with untreated advanced HER2+ gastroesophageal adenocarcinoma, bevacizumab was added to standard of care capecitabine, oxaliplatin, and trastuzumab in 36 patients (NCT01191697). Primary endpoint was objective response rate and secondary endpoints included safety, duration of response, progression free survival, and overall survival.

Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia.

Sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli to the central nervous system. Single-cell RNA sequencing has provided insights into the diversity of sensory ganglia cell types in rodents, nonhuman primates, and humans, but it remains difficult to compare cell types across studies and species. We thus constructed harmonized atlases of the DRG and TG that describe and facilitate comparison of 18 neuronal and 11 non-neuronal cell types across six species and 31 datasets.

Bridging the Clinical-Computational Transparency Gap in Digital Pathology.

Context.—: Computational pathology combines clinical pathology with computational analysis, aiming to enhance diagnostic capabilities and improve clinical productivity. However, communication barriers between pathologists and developers often hinder the full realization of this potential.

Virus-Induced Acute Respiratory Distress Syndrome Causes Cardiomyopathy Through Eliciting Inflammatory Responses in the Heart.

Background: Viral infections can cause acute respiratory distress syndrome (ARDS), systemic inflammation, and secondary cardiovascular complications. Lung macrophage subsets change during ARDS, but the role of heart macrophages in cardiac injury during viral ARDS remains unknown. Here we investigate how immune signals typical for viral ARDS affect cardiac macrophage subsets, cardiovascular health, and systemic inflammation.

Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.

A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment.

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets.

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.

Diagnostic Test Utilization Management Strategies as an Opportunity for Equitable Access to Molecularly Informed Clinical Care.

Background: Companion diagnostics are an essential component of oncology. Timing, cost, and adaptability to new drug/biomarker approvals represent challenges in assuring value-based care. Overcoming these challenges requires strategies for equitable access and efficient integration.

Amplification of Wild-Type Represents a Novel Molecular Subtype of Several Cancer Types With Clinical Response to Selpercatinib.

Purpose: rearrangements and activating point mutations represent targetable genomic alterations in advanced solid tumors. However, the frequency and clinicopathologic characteristics of wild-type amplification in cancer and its potential role as a targetable oncogenic driver are not well-characterized.

Methods: In two institutional cohorts of patients with solid cancers from the Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering Cancer Center (MSKCC) whose tumors underwent next-generation sequencing (NGS), the frequency and clinicopathologic features of wild-type amplification in the absence of rearrangements or activating mutations was assessed.

Lorlatinib and capmatinib in a ROS1-rearranged NSCLC with MET-driven resistance: tumor response and evolution.

Acquired drug resistance remains a major problem across oncogene-addicted cancers. Elucidation of mechanisms of resistance can inform rational treatment strategies for patients relapsing on targeted therapies while offering insights into tumor evolution. Here, we report acquired MET amplification as a resistance driver in a ROS1-rearranged lung adenocarcinoma after sequential treatment with ROS1 inhibitors.

Initial interactions with the FDA on developing a validation dataset as a medical device development tool.

Quantifying tumor-infiltrating lymphocytes (TILs) in breast cancer tumors is a challenging task for pathologists. With the advent of whole slide imaging that digitizes glass slides, it is possible to apply computational models to quantify TILs for pathologists. Development of computational models requires significant time, expertise, consensus, and investment.

Exploring the Skin Brain Link: Biomarkers in the Skin with Implications for Aging Research and Alzheimer's Disease Diagnostics.

Neurodegenerative diseases, including Alzheimer's disease (AD), are challenging to diagnose. Currently the field must rely on imperfect diagnostic modalities. A recent study identified differences in several key bio-mechano-physiological parameters of the skin between AD patients and healthy controls.

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).

Computational pathology in cancer diagnosis, prognosis, and prediction - present day and prospects.

Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging from the prospect of automation of routine diagnostic tasks to the discovery of new prognostic and predictive biomarkers from tissue morphology. Despite the promising potential of computational pathology, its integration in clinical settings has been limited by a range of obstacles including operational, technical, regulatory, ethical, financial, and cultural challenges.

The Cholangiocarcinoma in the Young (CITY) Study: Tumor Biology, Treatment Patterns, and Survival Outcomes in Adolescent Young Adults With Cholangiocarcinoma.

Purpose: Increased awareness of the distinct tumor biology for adolescents and young adults (AYAs) with cancer has led to improvement in outcomes for this population. However, in cholangiocarcinoma (CCA), a paucity of data exist on the AYA population. To our knowledge, we present the largest study to date on AYA disease biology, treatment patterns, and survival outcomes in CCA.

Recruited macrophages elicit atrial fibrillation.

Atrial fibrillation disrupts contraction of the atria, leading to stroke and heart failure. We deciphered how immune and stromal cells contribute to atrial fibrillation. Single-cell transcriptomes from human atria documented inflammatory monocyte and macrophage expansion in atrial fibrillation.