A phase II randomized trial of individualized neoantigen peptide vaccine combined with unusual radiotherapy (iNATURE) in advanced solid tumors-GCOG0028.

Background: Neoantigen-based vaccines show promising therapeutic potential in solid tumors such as melanoma, GBM, NSCLC, and CRC. However, clinical responses remain suboptimal in stage IV patients, due to ineffective T-cell function and high tumor burdens. To overcome these limitations, our study investigates a combination strategy using neoantigen peptide vaccines and precision critical lesion radiotherapy (CLERT), which delivers immunomodulatory doses to key tumor regions synergistically enhance immune activation and inhibit progression in multifocal stage IV patients.

Implementing a PREcision meDICine Thoracic (PREDICT) service using in-house reflex testing in a large academic-community practice.

Background: Broad genomic testing is necessary to treat stage IV non-small cell lung cancer (NSCLC) patients. We describe a NSCLC precision medicine service at an academic-community practice and provide model-based estimates of the impact of a similar intervention.

Research Question: Will implementation of a precision medicine service increase NSCLC next-generation sequencing (NGS) rates, improve testing turnaround times (TAT), and increase rates of actionable genomic alterations (AGAs)?

Study Design And Methods: PREDICT (PREcision meDICine Thoracic) consisted of: 1) system-wide reflex testing of stage IV NSCLC patients by in-house solid tumor NGS focused assay and PD-L1 testing, 2) navigator, 3) molecular tumor board (MTB), 4) integrated information portal (OncoTracker) for real-time updates on samples processing, results, and treatment recommendations by the MTB.

Collagen disorder architecture features are associated with clinical, molecular, genetic factors and survival outcomes in colon cancer.

We developed a computational pathology pipeline to extract and analyze collagen disorder architecture (CoDA) features from whole slide images (WSIs) of 2,212 colon cancer (CC) patients across multiple institutions. CoDA features-capturing collagen fragmentation, bundling, anisotropy, density, and rigidity, were evaluated for associations with clinical variables (overall stage, T/N/M stage), molecular classifications (Consensus Molecular Subtypes [CMS1-4]), and genetic mutations (KRAS, BRAF, NRAS) using the Mann-Whitney U test with Bonferroni correction. These analyses revealed significant differences in CoDA feature distributions across multiple subgroups, suggesting that collagen architecture varies meaningfully with tumor stage, molecular subtype, and mutation status.

Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men.

Purpose: To quantify population-specific differences in prostate cancer (PCa) presentation between African American (AA) and White (W) men on MRI using radiomics.

Materials And Methods: We identified N = 149 men with PCa who underwent 3T MRI, a confirmatory biopsy and for whom self-reported race was available. Patient studies were partitioned into training (D) and hold-out test set (D).

miRNAs Regulating GSTP1 as Potential Diagnostic Biomarkers in Prostate Cancer.

Background: Specific and sensitive minimally-invasive biomarker(s) for early detection of prostate cancer is urgently needed to reduce false detection and odds of overtreatment. MicroRNAs (miRNAs) are 19-24-nt noncoding RNAs that regulate gene expression, have emerged as promising blood-based biomarkers due to their frequent dysregulation in cancer.

Methods: miRNA levels were quantified in a total of 86 human plasma samples, consisting of 44 prostate cancer patients and 42 individuals with no cancer, using quantitative real-time PCR.

Durable responses to immune checkpoint inhibitor-based regimens for metastatic clear cell renal cell carcinoma stratified by IMDC risk groups: A pooled analysis of four randomized phase 3 trials.

Background: An immune checkpoint inhibitor (ICI) backbone is a standard of care for frontline metastatic clear cell renal cell carcinoma, involving either ICI doublet or tyrosine kinase inhibitor (TKI) with ICI. These phase 3 trials used a sunitinib control arm. The optimal regimen is uncertain.

Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer.

Endometrial cancer (EC) disproportionately affects African American (AA) women in terms of progression and death. In our study, we sought to employ computerized image and bioinformatic analysis to tease out morphologic and molecular differences in EC between AA and European-American (EA) populations. We identified the differences in immune cell spatial patterns between AA and EA populations with markers of tumor biology, including histologic and molecular subtypes.

Computationally integrating radiology and pathology image features for predicting treatment benefit and outcome in lung cancer.

Lung cancer, the leading cause of cancer-related deaths globally, includes non-small cell lung cancer (NSCLC) (85% of cases) and small cell lung cancer (SCLC) (13-15%). While accurate diagnosis and treatment selection are critical, the absence of reliable predictive or prognostic biomarkers remains a significant challenge. This study explored the combined use of radiomics from CT scans and pathomics from H&E slides in three contexts: (1) predicting disease recurrence in early-stage NSCLC, (2) predicting immunotherapy response in advanced-stage NSCLC, and (3) predicting chemotherapy response in SCLC.

Deep Learning Model of Primary Tumor and Metastatic Cervical Lymph Nodes From CT for Outcome Predictions in Oropharyngeal Cancer.

Importance: Primary tumor (PT) and metastatic cervical lymph node (LN) characteristics are highly associated with oropharyngeal squamous cell carcinoma (OPSCC) prognosis. Currently, there is a lack of studies to combine imaging characteristics of both regions for predictions of p16+ OPSCC outcomes.

Objectives: To develop and validate a computed tomography (CT)-based deep learning classifier that integrates PT and LN features to predict outcomes in p16+ OPSCC and to identify patients with stage I disease who may derive added benefit associated with chemotherapy.

Outcomes in patients with multiple sclerosis and solid organ cancers treated with immune checkpoint inhibitors.

Background: Multiple sclerosis (MS) patients are excluded from studies of immune checkpoint inhibitors (ICIs) due to concern for MS flare. This study aims to report the incidence of MS relapse, immune-related adverse events (irAEs), and cancer outcomes in MS patients with solid-organ malignancy treated with ICIs.

Methods: In this retrospective study, MS patients who received ICIs at University Hospitals Seidman Cancer Center were identified electronically.

A Review of Current Literature and Real-World Outcomes With Neoadjuvant Chemotherapy in Hormone Receptor Positive, HER2 Negative Breast Cancer.

Background: Neoadjuvant chemotherapy has been used to downstage locally advanced ER+/HER2- breast cancer with low response rates. The optimal neoadjuvant regimen for this population is unknown.

Patients And Methods: Between 2017 and 2022, 192 patients (ages 28-78) with stage II/III ER+/Her2- breast cancer at our institution were evaluated.

Computational pathology assessments of cardiac stromal remodeling: Clinical correlates and prognostic implications in heart transplantation.

Background: The hostile immune environment created by allotransplantation can accelerate pathologic tissue remodeling. Both overt and indolent inflammatory insults propel this remodeling, but there is a paucity of tools for monitoring the speed and severity of remodeling over time.

Methods: This retrospective cohort consisted of  = 2,167 digitized heart transplant biopsy slides along with records of prior inflammatory events and future allograft outcomes (cardiac death or allograft vasculopathy).

ADAM: automated digital phenotyping and morphological texture analysis of bone biopsy images using deep learning.

Histomorphometric analysis of undecalcified bone biopsy images provides quantitative assessment of bone turnover, volume, and mineralization using static and dynamic parameters. Traditionally, quantification has relied on manual annotation and tracing of relevant tissue structures, a process that is time-intensive and subject to inter-operator variability. We developed ADAM, an automated pipeline for digital phenotyping, to quantify tissue and cellular components pertinent to static histomorphometric parameters such as bone and osteoid area, osteoclast and osteoblast count, and bone marrow adipose tissue (BMAT) area.

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

Background: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology and radiology focused AI-based prognostic models have been independently developed for OPSCC, but their integration incorporating both primary tumour (PT) and metastatic cervical lymph node (LN) remains unexamined.

Methods: We investigate the prognostic value of an AI approach termed the swintransformer-based multimodal and multi-region data fusion framework (SMuRF).

Melphalan 140 mg/m is Safe and Effective for Frail and Older Multiple Myeloma Patients With Comparable Rates of Minimal Residual Disease Negativity.

Background: Despite therapeutic advances, multiple myeloma (MM) remains challenging to treat effectively. High-dose melphalan (Mel200) with autologous stem cell transplantation (ASCT) is the standard treatment for transplant-eligible patients. Reduced-dose melphalan (Mel140) is an alternative for older or frail patients, yet its efficacy data remain unclear.

Blood-based tumor mutational burden impacts clinical outcomes of immune checkpoint inhibitor treated breast and prostate cancers.

Background: Breast and prostate tumors are known to be less responsive to immune checkpoint inhibitors (ICIs). Tissue-based tumor mutation burden (tTMB) has emerged as a predictive biomarker of response to ICIs, including in these "cold tumors". In clinical practice, when tTMB is not available, blood-based TMB score (bTMB) can be used to consider treatment with ICIs.

Machine Vision-Detected Peritumoral Lymphocytic Aggregates Are Associated With Disease-Free Survival in Patients With Papillary Thyroid Carcinoma.

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with a disease recurrence rate of around 20%. Lymphoid formations, which occur in nonlymphoid tissues during chronic inflammatory, infectious, and immune responses, have been linked with tumor suppression. Lymphoid aggregates potentially enhance the body's antitumor response, offering an avenue for attracting tumor-infiltrating lymphocytes and fostering their coordination.

A novel computational pathology approach for identifying gene signatures prognostic of disease-free survival for papillary thyroid carcinomas.

Introduction: Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with the classical and follicular variants representing most cases. Despite generally favorable prognoses, approximately 10% of patients experience recurrence post-surgery and radioactive iodine therapy. Attempts to stratify risk of recurrence have relied on gene expression-based prognostic and predictive signatures with a focus on mutations of well-known driver genes, while hallmarks of tumor morphology have been ignored.

Image analysis Uncovers associations between immune landscape, collagen structure, and neoadjuvant chemotherapy in high-grade serous ovarian carcinomas.

Background: The changes in the tumor microenvironment of high-grade serous ovarian carcinomas following neoadjuvant chemotherapy are a complex area of study. Previous research underscores the importance of investigating the immune and collagen components within the tumor microenvironment for prognostic implications.

Methods: In this study, we utilized computational pathology techniques with Hematoxylin and Eosin-stained images to quantitatively characterize the immune and collagen architecture within the tumor microenvironment of patients with high-grade serous ovarian carcinoma.

A Pilot Trial of Proton-Based Cardiac Sparing Accelerated Fractionated Radiation Therapy in Unresectable Non-small Cell Lung Cancer With Extended Durvalumab Therapy (PARTICLE-D).

Purpose: Concurrent chemoradiation therapy is the current nonsurgical standard of care for locally advanced non-small cell lung cancer. However, this is a difficult regimen to tolerate, especially for those who are elderly, have multiple comorbidities, or have poor performance status. Alternative treatment regimens are needed for this vulnerable population.

A prognostic and predictive computational pathology immune signature for ductal carcinoma in situ: retrospective results from a cohort within the UK/ANZ DCIS trial.

Background: The density of tumour-infiltrating lymphocytes (TILs) could be prognostic in ductal carcinoma in situ (DCIS). However, manual TIL quantification is time-consuming and suffers from interobserver and intraobserver variability. In this study, we developed a TIL-based computational pathology biomarker and evaluated its association with the risk of recurrence and benefit of adjuvant treatment in a clinical trial cohort.

Haplo-cord transplant. Realizing the potential of umbilical cord blood grafts. - A review of techniques and analysis of outcomes.

The combination of cord blood transplant with progenitor cells from partially HLA-matched adult donors has been used over the past two decades. In Europe and the US the adult donor graft is CD34 selected and provides early hematopoiesis, but durable engraftment derives from the cord blood graft . Neutrophil recovery is prompt and rates of acute and chronic GVHD are low.

Outcomes of initial therapy for synchronous brain metastases from small cell lung cancer: a single-institution retrospective analysis.

Small cell lung cancer (SCLC) has a propensity for brain metastases, which is associated with poor prognosis. We sought to determine predictors of overall survival (OS) and brain progression-free survival (bPFS) in SCLC patients with synchronous brain metastases at the time of initial SCLC diagnosis. A total of 107 SCLC patients with synchronous brain metastases treated at a single institution were included in this retrospective analysis.

Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.

Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this study we employed machine learning and statistical atlas-based approaches to explore possible changes in lung shape among COVID-19 patients and evaluated whether the extent of these changes was associated with COVID-19 severity. On a large multi-institutional dataset (N = 3443), three different populations were defined; a) healthy (no COVID-19), b) mild COVID-19 (no ventilator required), c) severe COVID-19 (ventilator required), and the presence of lung shape differences between them were explored using baseline chest CT.

Computational Pathology Assessments of Cardiac Stromal Remodeling: Clinical Correlates and Prognostic Implications in Heart Transplantation.

Both overt and indolent inflammatory insults in heart transplantation can accelerate pathologic cardiac remodeling, but there are few tools for monitoring the speed and severity of remodeling over time. To address this need, we developed an automated computational pathology system to measure pathologic remodeling in transplant biopsy samples in a large, retrospective cohort of n=2167 digitized heart transplant biopsy slides. Biopsy images were analyzed to identify the pathologic stromal changes associated with future allograft loss or advanced allograft vasculopathy.