Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

Imaging Extracellular Matrix Remodeling In Vitro by Diffusion-Sensitive Optical Coherence Tomography

The mammary gland extracellular matrix (ECM) is comprised of biopolymers, primarily collagen I, that are created and maintained by stromal fibroblasts. ECM remodeling by fibroblasts results in changes in ECM fiber spacing (pores) that have been shown to play a critical role in the aggressiveness of breast cancer. However, minimally invasive methods to measure the spatial distribution of ECM pore areas within tissues and in vitro 3D culture models are currently lacking. We introduce diffusion-sensitive optical coherence tomography (DS-OCT) to image the nanoscale porosity of ECM by sensing weakly constrained diffusion of gold nanorods (GNRs). DS-OCT combines the principles of low-coherence interferometry and heterodyne dynamic light scattering. By collecting co- and cross-polarized light backscattered from GNRs within tissue culture, the ensemble-averaged translational self-diffusion rate, DT, of GNRs is resolved within ∼3 coherence volumes (10 × 5 μm, x × z). As GNRs are slowed by intermittent collisions with ECM fibers, DT is sensitive to ECM porosity on the size scale of their hydrodynamic diameter (∼46 nm). Here, we validate the utility of DS-OCT using pure collagen I gels and 3D mammary fibroblast cultures seeded in collagen/Matrigel, and associate differences in artificial ECM pore areas with gel concentration and cell seed density. Across all samples, DT was highly correlated with pore area obtained by scanning electron microscopy (R2 = 0.968). We also demonstrate that DS-OCT can accurately map the spatial heterogeneity of layered samples. Importantly, DS-OCT of 3D mammary fibroblast cultures revealed the impact of fibroblast remodeling, where the spatial heterogeneity of matrix porosity was found to increase with cell density. This provides an unprecedented view into nanoscale changes in artificial ECM porosity over effective pore diameters ranging from ∼43 to 360 nm using a micron-scale optical imaging technique. In combination with the topical deposition of GNRs, the minimally invasive nature of DS-OCT makes this a promising technology for studying tissue remodeling processes

Pregnancy Induces Persistent Changes that Potentiate Apoptotic Signaling and Responses to DNA Damage

A full-term pregnancy reduces the lifetime risk of breast cancer by up to 50%. This effect is mediated, in part, by p53-dependent pathways. Gene expression profiling was used to investigate the mechanisms that alter apoptotic responses to DNA damage in the mammary gland. Radiation-induced responses in BALB/c-Trp53+/+ and BALB/c-Trp53-/- mice identified 121 genes that were altered by radiation and p53 status (p53-IR). To determine the effect of parity, mice were mated, force-weaned and mammary glands were allowed to involute for 21 days (parous) and compared with age-matched nulliparous mice. Gene expression profiles were determined in mammary tissues from nulliparous (N), parous (P), irradiated nulliparous (N-IR) and irradiated parous (P-IR) mice. The p53-IR gene signature did not differ among the N-IR and P-IR groups indicating that transcriptional activity of p53 was not altered by parity. However, expression profiles of apoptosis-related genes differed significantly in the parous group. The alterations in parous mammary tissues was accompanied by over-representation of biological processes that included “signal transduction” (e=1.69E-05). Within this set, Wnt signaling was especially pronounced (e Parity-regulated genes collaborate with p53-dependent targets, which act as a “switch”, to elicit apoptosis following ionizing radiation. The epigenetic states of the parity-regulated genes Tgfb2 and Wnt5a provide a mechanism for the persistent alterations in gene expression and apoptosis in parous mammary epithelial cells

Associations among personal care product use patterns and exogenous hormone use in the NIEHS Sister Study

It is hypothesized that certain chemicals in personal care products may alter the risk of adverse health outcomes. The primary aim of this study was to use a data-centered approach to classify complex patterns of exposure to personal care products and to understand how these patterns vary according to use of exogenous hormone exposures, oral contraceptives (OCs) and post-menopausal hormone therapy (HT). The NIEHS Sister Study is a prospective cohort study of 50,884 US women. Limiting the sample to non-Hispanic blacks and whites (N = 47,019), latent class analysis (LCA) was used to identify groups of individuals with similar patterns of personal care product use based on responses to 48 survey questions. Personal care products were categorized into three product types (beauty, hair, and skincare products) and separate latent classes were constructed for each type. Adjusted prevalence differences (PD) were calculated to estimate the association between exogenous hormone use, as measured by ever/never OC or HT use, and patterns of personal care product use. LCA reduced data dimensionality by grouping of individuals with similar patterns of personal care product use into mutually exclusive latent classes (three latent classes for beauty product use, three for hair, and four for skin care. There were strong differences in personal care usage by race, particularly for haircare products. For both blacks and whites, exogenous hormone exposures were associated with higher levels of product use, especially beauty and skincare products. Relative to individual product use questions, latent class variables capture complex patterns of personal care product usage. These patterns differed by race and were associated with ever OC and HT use. Future studies should consider personal care product exposures with other exogenous exposures when modeling health risks

Molecular features of androgen-receptor low, estrogen receptor-negative breast cancers in the Carolina breast cancer study

Purpose: Androgen receptor (AR) expression is absent in 40–90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored. Methods: We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; N = 669) and The Cancer Genome Atlas (TCGA; N = 237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response]. Results: AR-low tumors were more prevalent among younger (RFD = + 10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2 negativity (RFD = − 35%, 95% CI = − 44% to − 26%), higher grade (RFD = + 17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD = + 22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD = + 33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD = + 41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression. Conclusion: Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients

PREDICTION OF TOXICANT-SPECIFIC GENE EXPRESSION SIGNATURES FOLLOWING CHEMOTHERAPEUTIC TREATMENT OF BREAST CELL LINES

Global gene expression profiling has demonstrated that the predominant cellular response to a range of toxicants is a general stress response. This stereotyped environmental stress response commonly includes repression of protein synthesis and cell-cycle–regulated genes and induction of DNA damage and oxidative stress–responsive genes. Our laboratory recently characterized the general stress response of breast cell lines derived from basal-like and luminal epithelium after treatment with doxorubicin (DOX) or 5-fluorouracil (5FU) and showed that each cell type has a distinct response. However, we expected that some of the expression changes induced by DOX and 5FU would be unique to each compound and might reflect the underlying mechanisms of action of these agents. Therefore, we employed supervised analyses (significance analysis of microarrays) to identify genes that showed differential expression between DOX-treated and 5FU-treated cell lines. We then used cross-validation analyses and identified genes that afforded high predictive accuracy in classifying samples into the two treatment classes. To test whether these gene lists had good predictive accuracy in an independent data set, we treated our panel of cell lines with etoposide, a compound mechanistically similar to DOX. We demonstrated that using expression patterns of 100 genes we were able to obtain 100% predictive accuracy in classifying the etoposide samples as being more similar in expression to DOX-treated than to 5FU-treated samples. These analyses also showed that toxicant-specific gene expression patterns, similar to general stress responses, vary according to cell type

The MLL-Menin Interaction is a Therapeutic Vulnerability in <em>NUP98</em>-rearranged AML

\ua9 2023 Wolters Kluwer Health. All rights reserved. Chromosomal translocations involving the NUP98 locus are among the most prevalent rearrangements in pediatric acute myeloid leukemia (AML). AML with NUP98 fusions is characterized by high expression of HOXA and MEIS1 genes and is associated with poor clinical outcome. NUP98 fusion proteins are recruited to their target genes by the mixed lineage leukemia (MLL) complex, which involves a direct interaction between MLL and Menin. Here, we show that therapeutic targeting of the Menin-MLL interaction inhibits the propagation of NUP98-rearrranged AML both ex vivo and in vivo. Treatment of primary AML cells with the Menin inhibitor revumenib (SNDX-5613) impairs proliferation and clonogenicity ex vivo in long-term coculture and drives myeloid differentiation. These phenotypic effects are associated with global gene expression changes in primary AML samples that involve the downregulation of many critical NUP98 fusion protein-target genes, such as MEIS1 and CDK6. In addition, Menin inhibition reduces the expression of both wild-type FLT3 and mutated FLT3-ITD, and in combination with FLT3 inhibitor, suppresses patient-derived NUP98-r AML cells in a synergistic manner. Revumenib treatment blocks leukemic engraftment and prevents leukemia-associated death of immunodeficient mice transplanted with NUP98::NSD1 FLT3-ITD-positive patient-derived AML cells. These results demonstrate that NUP98-rearranged AMLs are highly susceptible to inhibition of the MLL-Menin interaction and suggest the inclusion of AML patients harboring NUP98 fusions into the clinical evaluation of Menin inhibitors

Integrated RNA and DNA sequencing improves mutation detection in low purity tumors

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors