Prostate Cancer Risk Stratification in NRG Oncology Phase III Randomized Trials Using Multimodal Deep Learning With Digital Histopathology.

Purpose: Current clinical risk stratification methods for localized prostate cancer are suboptimal, leading to over- and undertreatment. Recently, machine learning approaches using digital histopathology have shown superior prognostic ability in phase III trials. This study aims to develop a clinically usable risk grouping system using multimodal artificial intelligence (MMAI) models that outperform current National Comprehensive Cancer Network (NCCN) risk groups.

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life, and there remain no validated predictive models to guide its use. METHODS: We used digital pathology images from pretreatment prostate tissue and clinical data from 5727 patients enrolled in five phase 3 randomized trials, in which treatment was radiotherapy with or without ADT, as our data source to develop and validate an artificial intelligence (AI)–derived predictive patient-specific model that would determine which patients would develop the primary end point of distant metastasis.

External Validation of a Digital Pathology-based Multimodal Artificial Intelligence Architecture in the NRG/RTOG 9902 Phase 3 Trial.

Background: Accurate risk stratification is critical to guide management decisions in localized prostate cancer (PCa). Previously, we had developed and validated a multimodal artificial intelligence (MMAI) model generated from digital histopathology and clinical features. Here, we externally validate this model on men with high-risk or locally advanced PCa treated and followed as part of a phase 3 randomized control trial.

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

Background: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life and there remain no validated predictive models to guide its use.

Methods: Digital pathology image and clinical data from pre-treatment prostate tissue from 5,727 patients enrolled on five phase III randomized trials treated with radiotherapy +/- ADT were used to develop and validate an artificial intelligence (AI)-derived predictive model to assess ADT benefit with the primary endpoint of distant metastasis.

Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials.

Prostate cancer is the most frequent cancer in men and a leading cause of cancer death. Determining a patient's optimal therapy is a challenge, where oncologists must select a therapy with the highest likelihood of success and the lowest likelihood of toxicity. International standards for prognostication rely on non-specific and semi-quantitative tools, commonly leading to over- and under-treatment.

FOXP3-positive regulatory T lymphocytes and epithelial FOXP3 expression in synchronous normal, ductal carcinoma in situ, and invasive cancer of the breast.

FOXP3-expressing T regulatory lymphocytes (Tregs) have been described as putative mediators of immune tolerance, and thus facilitators of tumor growth. When found in association with various malignancies, Tregs are generally markers of poor clinical outcome. However, it is unknown whether they are also associated with cancer progression.

Genomic alterations and phenotype of large compared to small high-grade ductal carcinoma in situ.

A clinically distinct subgroup of pure ductal carcinoma in situ presents as an extensive, high-grade lesion, which nevertheless lacks invasion. We sought to evaluate differences between those ductal carcinomas in situ presenting as large versus small lesions while controlling for high-grade, to determine whether there exist phenotypic and genetic differences between the 2 groups. Fifty-two cases of pure high-grade ductal carcinomas in situ were collected retrospectively, consisting of 27 large (>40 mm) and 25 small (<15 mm) cases.

Similarity in genetic alterations between paired well-differentiated and dedifferentiated components of dedifferentiated liposarcoma.

Liposarcoma represents a unique model insofar as some well-differentiated liposarcomas progress to non-lipogenic, so-called 'dedifferentiated,' forms. The well-differentiated and dedifferentiated family of liposarcomas demonstrates amplification of the chromosome subregion 12q13-q15 with resultant amplification of the MDM2 and CDK4 genes. However, the specific genetic changes that distinguish between well-differentiated and dedifferentiated liposarcomas are less well understood.

Genetic and phenotypic characteristics of pleomorphic lobular carcinoma in situ of the breast.

The clinical, pathologic, and molecular features of pleomorphic lobular carcinoma in situ (PLCIS) and the relationship of PLCIS to classic LCIS (CLCIS) are poorly defined. In this study, we analyzed 31 cases of PLCIS (13 apocrine and 18 nonapocrine subtypes) and compared the clinical, pathologic, immunophenotypic, and genetic characteristics of these cases with those of 24 cases of CLCIS. Biomarker expression was examined using immunostaining for E-cadherin, gross cystic disease fluid protein-15, estrogen, progesterone, androgen receptor, human epidermal growth factor receptor2, CK5/6, and Ki67.

Pathologic and biologic response to preoperative endocrine therapy in patients with ER-positive ductal carcinoma in situ.

Background: Endocrine therapy is commonly recommended in the adjuvant setting for patients as treatment for ductal carcinoma in situ (DCIS). However, it is unknown whether a neoadjuvant (preoperative) anti-estrogen approach to DCIS results in any biological change. This study was undertaken to investigate the pathologic and biomarker changes in DCIS following neoadjuvant endocrine therapy compared to a group of patients who did not undergo preoperative anti-estrogenic treatment to determine whether such treatment results in detectable histologic alterations.

Protein acetylation and histone deacetylase expression associated with malignant breast cancer progression.

Purpose: Excess histone deacetylase (HDAC) activity can induce hypoacetylation of histone and nonhistone protein substrates, altering gene expression patterns and cell behavior potentially associated with malignant transformation. However, HDAC expression and protein acetylation have not been studied in the context of breast cancer progression.

Experimental Design: We assessed expression levels of acetylated histone H4 (ac-H4), ac-H4K12, ac-tubulin, HDAC1, HDAC2, and HDAC6 in 22 reduction mammoplasties and in 58 specimens with synchronous normal epithelium, ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) components.

Fluorescence in situ hybridization of ductal lavage samples identifies malignant phenotypes from cytologically normal cells in women with breast cancer.

Background: Ductal lavage (DL) does not routinely identify cytologically malignant cells. For this study, the authors asked whether molecular analyses of DL specimens from women with cancer would identify abnormal cells, even if they appeared cytologically normal.

Methods: DL was performed and yielded fluid in 29 of 45 consenting women who were undergoing breast cancer surgery.

Identification of a robust gene signature that predicts breast cancer outcome in independent data sets.

Background: Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients.

Methods: We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression.

Genomic and transcriptional aberrations linked to breast cancer pathophysiologies.

This study explores the roles of genome copy number abnormalities (CNAs) in breast cancer pathophysiology by identifying associations between recurrent CNAs, gene expression, and clinical outcome in a set of aggressively treated early-stage breast tumors. It shows that the recurrent CNAs differ between tumor subtypes defined by expression pattern and that stratification of patients according to outcome can be improved by measuring both expression and copy number, especially high-level amplification. Sixty-six genes deregulated by the high-level amplifications are potential therapeutic targets.

A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes.

Recent studies suggest that thousands of genes may contribute to breast cancer pathophysiologies when deregulated by genomic or epigenomic events. Here, we describe a model "system" to appraise the functional contributions of these genes to breast cancer subsets. In general, the recurrent genomic and transcriptional characteristics of 51 breast cancer cell lines mirror those of 145 primary breast tumors, although some significant differences are documented.

Breast tumor copy number aberration phenotypes and genomic instability.

Background: Genomic DNA copy number aberrations are frequent in solid tumors, although the underlying causes of chromosomal instability in tumors remain obscure. Genes likely to have genomic instability phenotypes when mutated (e.g.

Bladder cancer stage and outcome by array-based comparative genomic hybridization.

Purpose: Bladder carcinogenesis is believed to follow alternative pathways of disease progression driven by an accumulation of genetic alterations. The purpose of this study was to evaluate associations between measures of genomic instability and bladder cancer clinical phenotype.

Experimental Design: Genome-wide copy number profiles were obtained for 98 bladder tumors of diverse stages (29 pT(a), 14 pT1, 55 pT(2-4)) and grades (21 low-grade and 8 high-grade superficial tumors) by array-based comparative genomic hybridization (CGH).

Bladder cancer outcome and subtype classification by gene expression.

Models of bladder tumor progression have suggested that genetic alterations may determine both phenotype and clinical course. We have applied expression microarray analysis to a divergent set of bladder tumors to further elucidate the course of disease progression and to classify tumors into more homogeneous and clinically relevant subgroups. cDNA microarrays containing 10,368 human gene elements were used to characterize the global gene expression patterns in 80 bladder tumors, 9 bladder cancer cell lines, and 3 normal bladder samples.

Clinical application of array-based comparative genomic hybridization to define the relationship between multiple synchronous tumors.

Array-based comparative genomic hybridization (CGH) is a technique that allows genome wide screening of gains and losses in DNA copy number. In cases where multiple tumors are encountered, this genetic technique may prove useful in differentiating new primary tumors from recurrences. In this case report, we used array-based CGH to examine the genomic relationships among two leiomyosarcomas and two breast cancers in the same patient, three of which were diagnosed synchronously.

Array-based comparative genomic hybridization from formalin-fixed, paraffin-embedded breast tumors.

Identification of prognostic and predictive genomic markers requires long-term clinical follow-up of patients. Extraction of high-quality DNA from archived formalin-fixed, paraffin-embedded material is essential for such studies. Of particular importance is a robust reproducible method of whole genome amplification for small tissue samples.

Patterns of chromosomal alterations in breast ductal carcinoma in situ.

Purpose: Ductal carcinoma in situ (DCIS) is thought to be a nonobligate precursor of invasive cancer. Genomic changes specific to pure DCIS versus invasive cancer, as well as alterations unique to individual DCIS subtypes, have not been fully defined.

Experimental Design: Chromosomal copy number alterations were examined by comparative genomic hybridization in 34 cases of pure DCIS and compared with 12 cases of paired synchronous DCIS and invasive ductal cancer, as well as to 146 additional cases of invasive breast cancer of ductal or lobular histology.

Clonality of lobular carcinoma in situ and synchronous invasive lobular carcinoma.

Background: Lobular carcinoma in situ (LCIS) of the breast is considered a marker for an increased risk of carcinoma in both breasts. However, the frequent association of LCIS with invasive lobular carcinoma (ILC) suggests a precursor-product relation. The possible genomic relation between synchronous LCIS and ILC was analyzed using the technique of array-based comparative genomic hybridization (CGH).

Array-based comparative genomic hybridization of ductal carcinoma in situ and synchronous invasive lobular cancer.

It has been increasingly recognized that ductal carcinoma in situ (DCIS), lobular carcinoma in situ (LCIS) and invasive cancer of the breast are often closely associated with one another. However, the genomic relationship between these histologically distinct entities has not been well characterized. Refinements in high-resolution comparative genomic hybridization (CGH) techniques allow for a detailed comparison of genomic alterations in synchronously occurring tumors.

LM-PCR permits highly representative whole genome amplification of DNA isolated from small number of cells and paraffin-embedded tumor tissue sections.

Analysis of genetic changes is often hampered by insufficient starting DNA from limited clinical tissue specimens. We employed ligation-mediated PCR (LM-PCR) for global amplification of the genome to overcome this limitation, generating up to 5 microg of representative amplicons of genomic DNA from as little as one cell. We demonstrate successful global genome amplification in high-quality starting DNA source like laser-captured cultured cells, as well as partially degraded starting DNA from old formalin-fixed paraffin-embedded tissue sections.