Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs.

SIGNIFICANCE

The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

Abstract 5407: A pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis

Patient-derived xenografts (PDXs) model human intra-tumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histological imaging via hematoxylin and eosin (H&E) staining is performed on PDX samples for routine assessment and, in principle, captures the complex interplay between tumor and stromal cells. Deep learning (DL)-based analysis of large human H&E image repositories has extracted inter-cellular and morphological signals correlated with disease phenotype and therapeutic response. Here, we present an extensive, pan-cancer repository of nearly 1,000 PDX and paired human progenitor H&E images. These images, curated from the PDXNet consortium, are associated with genomic and transcriptomic data, clinical metadata, pathological assessment of cell composition, and, in several cases, detailed pathological annotation of tumor, stroma, and necrotic regions. We demonstrate that DL can be applied to these images to classify tumor regions with an accuracy of 0.87. Further, we show that DL can predict xenograft-transplant lymphoproliferative disorder, the unintended outgrowth of human lymphocytes at the transplantation site, with an accuracy of 0.97. This repository enables PDX-specific investigations of cancer biology through histopathological analysis and contributes important model system data that expand on existing human histology repositories. We expect the PDXNet Image Repository to be valuable for controlled digital pathology analysis, both for the evaluation of technical issues such as stain normalization and for development of novel computational methods based on spatial behaviors within cancer tissues.

Citation Format: Brian S. White, Xing Yi Woo, Soner Koc, Todd Sheridan, Steven B. Neuhauser, Shidan Wang, Yvonne A. Evrard, John David Landua, R Jay Mashl, Sherri R. Davies, Bingliang Fang, Maria Gabriela Raso, Kurt W. Evans, Matthew H. Bailey, Yeqing Chen, Min Xiao, Jill Rubinstein, Ali Foroughi pour, Lacey Elizabeth Dobrolecki, Maihi Fujita, Junya Fujimoto, Guanghua Xiao, Ryan C. Fields, Jacqueline L. Mudd, Xiaowei Xu, Melinda G. Hollingshead, Shahanawaz Jiwani, PDXNet consortium, Tiffany A. Wallace, Jeffrey A. Moscow, James H. Doroshow, Nicholas Mitsiades, Salma Kaochar, Chong-xian Pan, Moon S. Chen, Luis G. Carvajal-Carmona, Alana L. Welm, Bryan E. Welm, Ramaswamy Govindan, Shunqiang Li, Michael A. Davies, Jack A. Roth, Funda Meric-Bernstam, Yang Xie, Meenhard Herlyn, Li Ding, Michael T. Lewis, Carol J. Bolt, Dennis A. Dean, Jeffrey H. Chuang. A pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5407.

A randomized phase 2 study of neoadjuvant carboplatin and paclitaxel with or without atezolizumab in triple negative breast cancer (TNBC) - NCI 10013

Atezolizumab with chemotherapy has shown improved progression-free and overall survival in patients with metastatic PD-L1 positive triple negative breast cancer (TNBC). Atezolizumab with anthracycline- and taxane-based neoadjuvant chemotherapy has also shown increased pathological complete response (pCR) rates in early TNBC. This trial evaluated neoadjuvant carboplatin and paclitaxel with or without atezolizumab in patients with clinical stages II-III TNBC. The co-primary objectives were to evaluate if chemotherapy and atezolizumab increase pCR rate and tumor infiltrating lymphocyte (TIL) percentage compared to chemotherapy alone in the mITT population. Sixty-seven patients (ages 25-78 years; median, 52 years) were randomly assigned - 22 patients to Arm A, and 45 to Arm B. Median follow up was 6.6 months. In the modified intent to treat population (all patients evaluable for the primary endpoints who received at least one dose of combination therapy), the pCR rate was 18.8% (95% CI 4.0-45.6%) in Arm A, and 55.6% (95% CI 40.0-70.4%) in Arm B (estimated treatment difference: 36.8%, 95% CI 8.5-56.6%; p = 0.018). Grade 3 or higher treatment-related adverse events occurred in 62.5% of patients in Arm A, and 57.8% of patients in Arm B. One patient in Arm B died from recurrent disease during the follow-up period. TIL percentage increased slightly from baseline to cycle 1 in both Arm A (mean ± SD: 0.6% ± 21.0%) and Arm B (5.7% ± 15.8%) (p = 0.36). Patients with pCR had higher median TIL percentages (24.8%) than those with non-pCR (14.2%) (p = 0.02). Although subgroup analyses were limited by the small sample size, PD-L1-positive patients treated with chemotherapy and atezolizumab had a pCR rate of 75% (12/16). The addition of atezolizumab to neoadjuvant carboplatin and paclitaxel resulted in a statistically significant and clinically relevant increased pCR rate in patients with clinical stages II and III TNBC. (Funded by National Cancer Institute).

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.

Abstract 1202: A repository of PDX histology images for exploring spatial heterogeneity and cancer dynamics

Patient-derived xenografts (PDXs) recapitulate intratumoral spatial heterogeneity and simulate a tumor microenvironment in which human immune and stromal cells in the PDX are replaced over passages by murine cells partially lacking immune function. Histological imaging enables exploring the spatial heterogeneity and dynamics of cancer, stromal, and immune cell interactions as correlates of tumor stage and therapeutic response over passages. We created a repository of curated, haematoxylin and eosin (H&E) images as a community resource for addressing these questions.

Images were generated at five sites within the NCI’s PDX Development and Trial Centers Research Network (PDXNet) and the NCI Patient-Derived Models Repository. Over 900 images, including 739 from PDXs and 190 from paired patients, are hosted on the Seven Bridges Genomics Cancer Genomics Cloud. They represent 42 cancer subtypes, including breast cancer (n=134), colon adenocarcinoma (COAD; n=94), pancreatic cancer (n=87), lung adenocarcinoma (LUAD; n=80), melanoma (n=71), and squamous cell lung cancer (LUSC; n=65). Paired human/PDX images are available for each of these cancers. Human and/or PDX images generated following patient treatment are available for 37 of the subtypes. Most images are from early passages (P0: 158; P1: 292; P2: 152; P3: 69; >P3: 55). Annotations include sex, age, race, ethnicity, and, for most images, pathological assessment of tissue-level percent cancer, stromal, and necrotic cell content (n=639) and tumor stage (n=650). RNA and exome sequencing data are available for 99 and 228 images, respectively, matched at the patient or sample level.

Quality control was performed using HistoQC. Cells were segmented and labeled as neoplastic, necrotic, immune, stromal, or other using Hover-Net and predictions of total neoplastic cell area correlated with whole-slide pathological assessment of cancer cell percentage (COAD: r=0.51; LUSC: r=0.59). HD-Staining, another classification approach, was applied to a subset of images and our clinical annotations will facilitate validation of this and related methods. Features of 512 x 512 pixel tiles were computed using the Inception V3 convolutional neural network pre-trained on ImageNet. Unsupervised clustering of these features demonstrate inter-patient heterogeneity within pathologist-annotated tumor regions. A classifier developed using pathologist-annotated cancer, stromal, and necrotic regions and trained on the features in LUSC images (n=10 images) achieved a cross-validation accuracy of 96% for cancer tiles across (n=5) LUAD images. Accuracy was lower for stromal classification (90%), likely reflecting current limitations of our small, but growing, labeled training set.

Our repository of clinically-annotated PDX H&E images should aid the community in studying spatial heterogeneity and in training deep learning-based image analysis methods.

Citation Format: Brian S. White, Xingyi Woo, Soner Koc, Todd Sheridan, Steven B. Neuhauser, Akshat M. Savaliya, Lacey E. Dobrolecki, John D. Landua, Matthew H. Bailey, Maihi Fujita, Kurt W. Evans, Bingliang Fang, Junya Fujimoto, Maria Gabriela Raso, Shidan Wang, Guanghua Xiao, Yang Xie, Sherri R. Davies, Ryan C. Fields, R Jay Mashl, Jacqueline L. Mudd, Yeqing Chen, Min Xiao, Xiaowei Xu, Melinda G. Hollingshead, Shahanawaz Jiwani, PDXNet Consortium, Yvonne A. Evrard, Tiffany A. Wallace, Jeffrey A. Moscow, James H. Doroshow, Nicholas Mitsiades, Salma Kaochar, Chong-xian Pan, Moon S. Chen, Luis G. Carvajal-Carmona, Alana L. Welm, Bryan E. Welm, Michael T. Lewis, Ramaswamy Govindan, Li Ding, Shunqiang Li, Meenhard Herlyn, Michael A. Davies, Jack A. Roth, Funda Meric-Bernstam, Carol J. Bult, Brandi Davis-Dusenbery, Dennis A. Dean, Jeffrey H. Chuang. A repository of PDX histology images for exploring spatial heterogeneity and cancer dynamics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1202.

Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors.

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Functional Annotation of ESR1 Gene Fusions in Estrogen Receptor-Positive Breast Cancer

RNA sequencing (RNA-seq) detects estrogen receptor alpha gene (ESR1) fusion transcripts in estrogen receptor-positive (ER⁺) breast cancer, but their role in disease pathogenesis remains unclear. We examined multiple ESR1 fusions and found that two, both identified in advanced endocrine treatment-resistant disease, encoded stable and functional fusion proteins. In both examples, ESR1-e6>YAP1 and ESR1-e6>PCDH11X, ESR1 exons 1-6 were fused in frame to C-terminal sequences from the partner gene. Functional properties include estrogen-independent growth, constitutive expression of ER target genes, and anti-estrogen resistance. Both fusions activate a metastasis-associated transcriptional program, induce cellular motility, and promote the development of lung metastasis. ESR1-e6>YAP1- and ESR1-e6>PCDH11X-induced growth remained sensitive to a CDK4/6 inhibitor, and a patient-derived xenograft (PDX) naturally expressing the ESR1-e6>YAP1 fusion was also responsive. Transcriptionally active ESR1 fusions therefore trigger both endocrine therapy resistance and metastatic progression, explaining the association with fatal disease progression, although CDK4/6 inhibitor treatment is predicted to be effective.

Research-based PAM50 signature and long-term breast cancer survival

Purpose

Multi-gene signatures provide biological insight and risk stratification in breast cancer. Intrinsic molecular subtypes defined by mRNA expression of 50 genes (PAM50) are prognostic in hormone-receptor positive postmenopausal breast cancer. Yet, for 25–40% in the PAM50 intermediate risk group, long-term risk remains uncertain. Our study aimed to (i) test the long-term prognostic value of the PAM50 signature in pre- and post-menopausal breast cancer; (ii) investigate if the PAM50 model could be improved by addition of other mRNAs implicated in oncogenesis.

Methods

We used archived FFPE samples from 1723 breast cancer survivors; high quality reads were obtained on 1253 samples. Transcript expression was quantified using a custom codeset with probes for > 100 targets. Cox models assessed gene signatures for breast cancer relapse and survival.

Results

Over 15 + years of follow-up, PAM50 subtypes were (P < 0.01) associated with breast cancer outcomes after accounting for tumor stage, grade and age at diagnosis. Results did not differ by menopausal status at diagnosis. Women with Luminal B (versus Luminal A) subtype had a > 60% higher hazard. Addition of a 13-gene hypoxia signature improved prognostication with > 40% higher hazard in the highest vs lowest hypoxia tertiles.

Conclusions

PAM50 intrinsic subtypes were independently prognostic for long-term breast cancer survival, irrespective of menopausal status. Addition of hypoxia signatures improved risk prediction. If replicated, incorporating the 13-gene hypoxia signature into the existing PAM50 risk assessment tool, may refine risk stratification and further clarify treatment for breast cancer.

Electronic supplementary material

The online version of this article (10.1007/s10549-019-05446-y) contains supplementary material, which is available to authorized users.

miRNAs and Long-term Breast Cancer Survival: Evidence from the WHEL Study

BACKGROUND

There is substantial variation in breast cancer survival rates, even among patients with similar clinical and genomic profiles. New biomarkers are needed to improve risk stratification and inform treatment options. Our aim was to identify novel miRNAs associated with breast cancer survival and quantify their prognostic value after adjusting for established clinical factors and genomic markers.

METHODS

Using the Women's Healthy Eating and Living (WHEL) breast cancer cohort with >15 years of follow-up and archived tumor specimens, we assayed PAM50 mRNAs and 25 miRNAs using the Nanostring nCounter platform.

RESULTS

We obtained high-quality reads on 1,253 samples (75% of available specimens) and used an existing research-use algorithm to ascertain PAM50 subtypes and risk scores (ROR-PT). We identified miRNAs significantly associated with breast cancer outcomes and then tested these in independent TCGA samples. miRNAs that were also prognostic in TCGA samples were further evaluated in multiple regression Cox models. We also used penalized regression for unbiased discovery.

CONCLUSIONS

Two miRNAs, 210 and 29c, were associated with breast cancer outcomes in the WHEL and TCGA studies and further improved risk stratification within PAM50 risk groups: 10-year survival was 62% in the node-negative high miR-210-high ROR-PT group versus 75% in the low miR-210- high ROR-PT group. Similar results were obtained for miR-29c. We identified three additional miRNAs, 187-3p, 143-3p, and 205-5p, via penalized regression.

IMPACT

Our findings suggest that miRNAs might be prognostic for long-term breast cancer survival and might improve risk stratification. Further research to incorporate miRNAs into existing clinicogenomic signatures is needed.

Abstract 5240: Functional and therapeutic significance of ESR1 gene fusions in breast cancer

RNA sequencing detects estrogen receptor alpha gene (ESR1) fusion transcripts in estrogen receptor positive (ER+) breast cancer but their role in disease pathogenesis remains unclear. Herein we examined multiple in-frame and out-of-frame ESR1 fusions and found only two, both identified in advanced endocrine treatment resistant disease, encoded stable and functional in-frame fusion proteins. In both examples, ESR1-e6&gt;YAP1 and ESR1-e6&gt;PCDH11X, the N-terminal, DNA binding and dimerization motifs encoded by exons 2-6 were fused to C-terminal sequences from the partner gene. Functional properties included estrogen-independent growth, constitutive expression of ER target genes, anti-estrogen resistance, induction of cellular motility in vitro and the development of lung metastasis in vivo. Chromatin immunoprecipitation and RNA sequencing experiments showed both fusions uniquely activated a metastasis-associated transcriptional program. ESR1-e6&gt;YAP1 and ESR1-e6&gt;PCDH11X-induced growth remained sensitive to a CDK4/6 inhibitor, palbociclib, and a patient-derived xenograft (PDX) expressing the ESR1-e6&gt;YAP1 fusion was also responsive. Transcriptionally active ESR1 fusions therefore trigger both endocrine therapy resistance and metastatic progression explaining the association with fatal disease progression, although CDK4/6 inhibitor treatment is predicted to be effective.

Citation Format: Jonathan T. Lei, Jieya Shao, Jin Zhang, Michael Iglesia, Doug W. Chan, Jin Cao, Meenakshi Anurag, Purba Singh, Xiaping He, Yoshimasa Kosaka, Ryoichi Matsunuma, Robert Crowder, Jeremy Hoog, Chanpheng Phommaly, Rodrigo Goncalves, Susana Romalho, Raquel M. Peres, Nindo Punturi, Cheryl Schmidt, Alex Bartram, Eric Jou, W V. Lai, Oliver Hampton, Anna Rogers, Ethan Tobias, Poojan Parikh, Sherri R. Davies, Shunqiang Li, Cynthia X. Ma, Vera Suman, Kelly K. Hunt, Mark A. Watson, Katherine A. Hoadley, E A. Thompson, Xi Chen, Shyam M. Kavuri, Chad J. Creighton, Christopher A. Maher, Charles M. Perou, Svasti Haricharan, Matthew J. Ellis. Functional and therapeutic significance of ESR1 gene fusions in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5240.

Mass Spectrometry-Based Proteomics Reveals Potential Roles of NEK9 and MAP2K4 in Resistance to PI3K Inhibition in Triple-Negative Breast Cancers

Activation of PI3K signaling is frequently observed in triple-negative breast cancer (TNBC), yet PI3K inhibitors have shown limited clinical activity. To investigate intrinsic and adaptive mechanisms of resistance, we analyzed a panel of patient-derived xenograft models of TNBC with varying responsiveness to buparlisib, a pan-PI3K inhibitor. In a subset of patient-derived xenografts, resistance was associated with incomplete inhibition of PI3K signaling and upregulated MAPK/MEK signaling in response to buparlisib. Outlier phosphoproteome and kinome analyses identified novel candidates functionally important to buparlisib resistance, including NEK9 and MAP2K4. Knockdown of NEK9 or MAP2K4 reduced both baseline and feedback MAPK/MEK signaling and showed synthetic lethality with buparlisib in vitro A complex in/del frameshift in PIK3CA decreased sensitivity to buparlisib via NEK9/MAP2K4-dependent mechanisms. In summary, our study supports a role for NEK9 and MAP2K4 in mediating buparlisib resistance and demonstrates the value of unbiased omic analyses in uncovering resistance mechanisms to targeted therapy.Significance: Integrative phosphoproteogenomic analysis is used to determine intrinsic resistance mechanisms of triple-negative breast tumors to PI3K inhibition. Cancer Res; 78(10); 2732-46. ©2018 AACR.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

Breast tumors educate the proteome of stromal tissue in an individualized but coordinated manner

Cancer forms specialized microenvironmental niches that promote local invasion and colonization. Engrafted patient-derived xenografts (PDXs) locally invade and colonize naïve stroma in mice while enabling unambiguous molecular discrimination of human proteins in the tumor from mouse proteins in the microenvironment. To characterize how patient breast tumors form a niche and educate naïve stroma, subcutaneous breast cancer PDXs were globally profiled by species-specific quantitative proteomics. Regulation of PDX stromal proteins by breast tumors was extensive, with 35% of the stromal proteome altered by tumors consistently across different animals and passages. Differentially regulated proteins in the stroma clustered into six signatures, which included both known and previously unappreciated contributors to tumor invasion and colonization. Stromal proteomes were coordinately regulated; however, the sets of proteins altered by each tumor were highly distinct. Integrated analysis of tumor and stromal proteins, a comparison made possible in these xenograft models, indicated that the known hallmarks of cancer contribute pleiotropically to establishing and maintaining the microenvironmental niche of the tumor. Education of the stroma by the tumor is therefore an intrinsic property of breast tumors that is highly individualized, yet proceeds by consistent, nonrandom, and defined tumor-promoting molecular alterations.

An mRNA Gene Expression-Based Signature to Identify FGFR1-Amplified Estrogen Receptor-Positive Breast Tumors

Fibroblast growth factor receptor 1 (FGFR1) amplification drives poor prognosis and is an emerging therapeutic target. We sought to construct a multigene mRNA expression signature to efficiently identify FGFR1-amplified estrogen receptor-positive (ER⁺) breast tumors. Five independent breast tumor series were analyzed. Genes discriminative for FGFR1 amplification were screened transcriptome-wide by receiver operating characteristic analyses. The METABRIC series was leveraged to construct/evaluate four approaches to signature composition. A locked-down signature was validated with 651 ER⁺ formalin-fixed, paraffin-embedded tissues (the University of British Columbia-tamoxifen cohort). A NanoString nCounter assay was designed to profile selected genes. For a gold standard, FGFR1 amplification was determined by fluorescent in situ hybridization (FISH). Prognostic effects of FGFR1 amplification were assessed by survival analyses. Eight 8p11-12 genes (ASH2L, BAG4, BRF2, DDHD2, LSM1, PROSC, RAB11FIP1, and WHSC1L1) together with the a priori selected FGFR1 gene, highly discriminated FGFR1 amplification (area under the receiver operating characteristic curve ≥0.82, all genes and all cohorts). The nine-gene signature Call-FGFR1-amp accurately identified FGFR1 FISH-amplified ER⁺ tumors in the University of British Columbia-tamoxifen cohort (specificity, 0.94; sensitivity, 0.96) and exhibited prognostic effects (disease-specific survival hazard ratio, 1.57; 95% CI, 1.14-2.16; P = 0.005). Call-FGFR1-amp includes several understudied 8p11-12 amplicon-driven oncogenes and accurately identifies FGFR1-amplified ER⁺ breast tumors. Our study demonstrates an efficient approach to diagnosing rare amplified therapeutic targets with FISH as a confirmatory assay.

Proteogenomic integration reveals therapeutic targets in breast cancer xenografts

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities.

Patient-derived xenografts recapitulate major genomic signatures and transcriptome profiles of their original tumours. Here, the authors, performing proteomic and phosphoproteomic analyses of 24 breast cancer PDX models, demonstrate that druggable candidates can be identified based on a comprehensive proteogenomic profiling.

Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays

BACKGROUND

For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays.

CONTENT

The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

Proteogenomics connects somatic mutations to signalling in breast cancer

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. We describe quantitative mass spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers of which 77 provided high-quality data. Integrated analyses allowed insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated against the Library of Integrated Network-based Cellular Signatures, thereby connecting CETN3 and SKP1 loss to elevated expression of EGFR, and SKP1 loss also to increased SRC. Global proteomic data confirmed a stromal-enriched group in addition to basal and luminal clusters and pathway analysis of the phosphoproteome identified a G Protein-coupled receptor cluster that was not readily identified at the mRNA level. Besides ERBB2, other amplicon-associated, highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Affective learning in adults with intellectual disability: an experiment using evaluative conditioning

BACKGROUND

Evaluative conditioning is a form of affective learning in which initially neutral stimuli acquire an affective value through association with negative or positive stimuli. Recent research shows an important role for cognitive resources in this type of learning. This form of affective learning has rarely been studied in intellectual disability (ID).

METHOD

We examined evaluative conditioning in 16 adults with mild to moderate ID compared to age- and gender-matched control participants. Neutral shapes and symbols were repeatedly paired with positive, neutral or negative unconditioned stimuli (faces or International Affective Picture System images). There was also an extinction phase.

RESULTS

There was significant acquisition of conditioning in both groups. Stimuli paired with positive images were evaluated more positively, and stimuli paired with negative images were evaluated more negatively. Post-extinction ratings however show that these novel affective associations were not maintained by individuals with ID as much as by individuals in the control group.

CONCLUSIONS

We conclude that ID modulates some aspects of affective learning but not necessarily initial preference acquisition.

PAM50 gene signatures and breast cancer prognosis with adjuvant anthracycline- and taxane-based chemotherapy: correlative analysis of C9741 (Alliance)

PAM50 intrinsic breast cancer subtypes are prognostic independent of standard clinicopathologic factors. CALGB 9741 demonstrated improved recurrence-free (RFS) and overall survival (OS) with 2-weekly dose-dense (DD) versus 3-weekly therapy. A significant interaction between intrinsic subtypes and DD-therapy benefit was hypothesized. Suitable tumor samples were available from 1,471 (73%) of 2,005 subjects. Multiplexed gene-expression profiling generated the PAM50 subtype call, proliferation score, and risk of recurrence score (ROR-PT) for the evaluable subset of 1,311 treated patients. The interaction between DD-therapy benefit and intrinsic subtype was tested in a Cox proportional hazards model using two-sided alpha = 0.05. Additional multivariable Cox models evaluated the proliferation and ROR-PT scores as continuous measures with selected clinical covariates. Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete data set (RFS; hazard ratio = 1.20; 95% confidence interval = 0.99-1.44) with 12.3-year median follow-up. Intrinsic subtypes were prognostic of RFS (P < 0.0001) irrespective of treatment assignment. No subtype-specific treatment effect on RFS was identified (interaction P = 0.44). Proliferation and ROR-PT scores were prognostic for RFS (both P < 0.0001), but no association with treatment benefit was seen (P = 0.14 and 0.59, respectively). Results were similar for OS. The prognostic value of PAM50 intrinsic subtype was greater than estrogen receptor/HER2 immunohistochemistry classification. PAM50 gene signatures were highly prognostic but did not predict for improved outcomes with DD anthracycline- and taxane-based therapy. Clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize treatment based on expected risks of distant recurrence.

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (∼80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the "peptide-to-protein" inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay

BACKGROUND

The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories.

METHODS

514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies.

RESULTS

The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online.

CONCLUSIONS

The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

Abstract 1999: Proteogenomic characterization of breast cancer sub-types in patient derived xenografts

The goal of this talk is to introduce an integrated quantitative proteogenomic approach to comprehensively map proteomic information back to their encoding genes. We seek evidence from mass spectrometry-based large-scale proteomic data of patient populations in conjunction with patient-centric next-generation sequencing data and unbiased sequencing strategies to study breast cancer (BC) subtypes from a genomic context.

We have obtained global and phosphoproteomic data with matching next generation sequencing data for 18 patient-derived xenografts (PDXs) representing the major clinical subtypes of BC. Our workflow starts with the creation of several protein sequence databases that serve as a template for mass spectrometry database identifications. These databases include 1) completely annotated reference protein sequences, 2) patient-specific databases that were created using next generation sequencing data, 3) isoform databases that contain all possible splicing combinations, and 4) amino acid sequence database resulting from a six-frame translation of the entire human reference and customized genomes. All mass spectrometry raw data are searched against the databases for obtaining identifications at the peptide level, and assembly of peptides for quantification using taxonomy-based label-free quantitation (LFQ) that can specifically quantify unique human peptide sequences found in PDXs. The peptides are then mapped to the human genome and visualized using a genome browser. Quantitative changes across PDXs are presented at the protein level or at the isoform level via peptide role-up to specific exons and visualized as a quantitative data track.

By combining search results from these databases we obtain a comprehensive view of our PDXs. The complementary nature of the databases enable greater proteomic depth, i.e. databases with complete splicing combinations capture proteomic evidence when patient-specific databases fail due to possible erroneous RNA-seq reads. Similarly, 6-frame translated amino acid databases can capture potentially novel coding regions but are unable to detect splicing. Peptide maps are obtained for individual genes or specific protein isoforms covering both knowledge-driven and novel genomic annotation types. We compile peptides carrying variants, splice junctions, fusions, and new coding regions specific to each PDX or in common with a specific BC subtype. Majority of data is mapped back to the genome loci using unmodified peptides via global proteomics while phosphopeptides that contain variants and splicing are also mapped in a similar manner using phosphoproteomic data.

We have currently annotated 455 novel proteogenomic hits covering many examples outlined above for genes related to breast cancer and show how these can be specifically identified and in some instances differentially quantified in the PDX models.

Citation Format: Harsha P. Gunawardena, John A. Wrobel, Jonathon O'Brien, Ling Xie, Petra Erdmann-Gilmore, Sherri R. Davies, Shunqiang Li, Song Cao, Michael McLellan, Kelly V. Ruggles, David Fenyo, R. Reid Townsend, Li Ding, Bahjat F. Qaqish, Matthew J. Ellis, Xian Chen. Proteogenomic characterization of breast cancer sub-types in patient derived xenografts. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1999. doi:10.1158/1538-7445.AM2015-1999

Abstract 959: Aromatase inhibition shapes the clonal architecture of estrogen receptor-positive breast cancers

BACKGROUND:

Aromatase inhibitors are routinely used to treat estrogen receptor (ER)-positive breast cancer in postmenopausal women. Yet, one-third of ER positive tumors are resistant to aromatase inhibitors with a further one-third developing resistance over time. The underlying mechanism conferring resistance to endocrine therapy is poorly understood. In the current work, we study the effect of aromatase inhibitor therapy on the clonal evolution of breast cancer and how it relates to therapy response.

MATERIALS AND METHODS:

We selected 12 aromatase inhibitor sensitive (post-treatment Ki67 &lt; 10%) and 10 aromatase inhibitor resistant tumors (Ki67 &gt; 10%) that had previously been whole genome sequenced (Ellis, et al. 2014). We obtained surgical samples of the same tumors after ∼4 months of aromatase inhibitor treatment, whole-genome sequenced them, and also obtained RNA-sequencing data for 19 of the pre-treatment and 18 of the post-treatment tumors. To better understand spatial heterogeneity we also whole-genome sequenced 11 secondary core biopsies taken from a subset of both the baseline and surgical tumors.

RESULTS AND DISCUSSION:

We classified each tumor based on its clonal heterogeneity, as inferred with the sciClone R package, and found 3 ‘simple’ tumors, comprised of only a founding clone, and 19 ‘complex’ tumors that contain one or more subclones. We further classified each tumor based on a stability metric, where ‘stable’ tumors (n = 4) showed little or no evidence of evolution between baseline and surgical intervention and ‘complex’ tumors (n = 18) exhibited a spectrum of clonal changes. These changes ranged from moderate shifts in subclonal frequencies to whole-scale remodeling, where minor subclonal populations gained near-complete dominance. In one extreme case, we observed co-occurring tumors of independent origin, with selection against an ER-positive population and relative expansion of an ER-negative tumor. Spatial heterogeneity was widespread as well, with 6 out of 11 secondary cores containing clonal architecture that differed from the primary.

We find that the majority of tumors are both ‘complex’ and ‘dynamic’ in that they are made up of multiple subclones at baseline that undergo clonal selection following endocrine therapy. This clonal evolution may provide a path by which a tumor can bypass therapeutic intervention. Further study is needed to identify the genetic aberrations that underlie this differential response. Our results suggest that clonal heterogeneity is widespread in hormone positive breast cancer and has relevance to endocrine therapy response.

Citation Format: Christopher A. Miller, Yevgeniy Gindin, Charles Lu, Obi Griffith, Malachi Griffith, Dong Shen, Jeremy Hoog, Mark Watson, Sherri R. Davies, Kelly Hunt, Jacqueline E. Snider, Katherine DeSchryver, Richard K. Wilson, Mathew J. Ellis, Elaine Mardis. Aromatase inhibition shapes the clonal architecture of estrogen receptor-positive breast cancers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 959. doi:10.1158/1538-7445.AM2015-959

Comprehensive quantitative analysis of ovarian and breast cancer tumor peptidomes

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high-throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with postexcision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics and provides insights not readily obtainable from such approaches.

Estrogen receptor expression is high but is of lower intensity in tubular carcinoma than in well-differentiated invasive ductal carcinoma

CONTEXT

Tubular carcinoma (TC) is a rare, luminal A subtype of breast carcinoma with excellent prognosis, for which adjuvant chemotherapy is usually contraindicated.

OBJECTIVE

To examine the levels of estrogen receptor (ER) and progesterone receptor expression in cases of TC and well-differentiated invasive ductal carcinoma as compared to normal breast glands and to determine if any significant differences could be detected via molecular testing.

DESIGN

We examined ER and progesterone receptor via immunohistochemistry in tubular (N = 27), mixed ductal/tubular (N = 16), and well-differentiated ductal (N = 27) carcinomas with comparison to surrounding normal breast tissue. We additionally performed molecular subtyping of 10 TCs and 10 ductal carcinomas via the PAM50 assay.

RESULTS

Although ER expression was high for all groups, TC had statistically significantly lower ER staining percentage (ER%) (P = .003) and difference in ER expression between tumor and accompanying normal tissue (P = .02) than well-differentiated ductal carcinomas, with mixed ductal/tubular carcinomas falling between these 2 groups. Mean ER% was 79%, 87%, and 94%, and mean tumor-normal ER% differences were 13.6%, 25.9%, and 32.6% in tubular, mixed, and ductal carcinomas, respectively. Most tumors that had molecular subtyping were luminal A (9 of 10 tubular and 8 of 10 ductal), and no significant differences in specific gene expression between the 2 groups were identified.

CONCLUSIONS

Tubular carcinoma exhibited decreased intensity in ER expression, closer to that of normal breast parenchyma, likely as a consequence of a high degree of differentiation. Lower ER% expression by TC may represent a potential pitfall when performing commercially available breast carcinoma prognostic assays that rely heavily on ER-related gene expression.

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.

Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts

To characterize patient-derived xenografts (PDXs) for functional studies, we made whole-genome comparisons with originating breast cancers representative of the major intrinsic subtypes. Structural and copy number aberrations were found to be retained with high fidelity. However, at the single-nucleotide level, variable numbers of PDX-specific somatic events were documented, although they were only rarely functionally significant. Variant allele frequencies were often preserved in the PDXs, demonstrating that clonal representation can be transplantable. Estrogen-receptor-positive PDXs were associated with ESR1 ligand-binding-domain mutations, gene amplification, or an ESR1/YAP1 translocation. These events produced different endocrine-therapy-response phenotypes in human, cell line, and PDX endocrine-response studies. Hence, deeply sequenced PDX models are an important resource for the search for genome-forward treatment options and capture endocrine-drug-resistance etiologies that are not observed in standard cell lines. The originating tumor genome provides a benchmark for assessing genetic drift and clonal representation after transplantation.

The pre-hospital epidemiology and management of spinal cord injuries in New South Wales: 2004-2008

CONTEXT

Patients who have sustained a traumatic spinal cord injury require appropriate management in the immediate post-injury period for both survival and to reduce the chances of costly and disabling permanent neurological deficits. Emerging time-critical neuroprotective therapies require the prompt recognition and transfer of patients to a specialised centre for early intervention.

METHODS

The Ambulance Research Institute, with the New South Wales State Spinal Cord Injury Service retrospectively linked prehospital data to spinal cord injury unit (SCIU) outcome data for all 324 patients transported by ambulance and subsequently admitted to a SCIU with a persisting traumatic spinal cord injury (SCI) between January 2004 and June 2008, with the aim of identifying factors that impact on the provision of timely and appropriate care.

RESULTS

Paramedics appropriately managed 88% of SCI patients. Only 4.9% of patients had initial vital signs potentially indicative of neurological injury. The median time to a SCIU was 12h, with 60% of patients undergoing multiple transfers. The odds of reaching a SCIU in over 24h were 1.71 times greater for patients injured in a major city (95% CI 1.00-2.90) in comparison to other areas of NSW. More SCI patients with multiple trauma experienced delays in reaching a SCIU (59%), compared to patients with isolated SCI (40%; p=0.039). Patients initially transported to a designated major trauma centre were more likely to be delayed in reaching a SCIU, regardless of whether their injury was an isolated SCI or associated with multiple trauma, compared with other patients. Patients who took greater than 24h to reach a SCIU were 2.5 times more likely to develop a secondary complication (95% CI 1.51-4.17, p=0.0004). Patients who sustained their SCI as a result of a low fall were older and less likely to have their SCI identified and treated early, with less than half of this group reaching a SCIU within 24h compared with other SCI patients (OR 0.42, 95% CI 0.19-0.93, p=0.004).

CONCLUSION

Early recognition, appropriate prehospital management, triage, timely and appropriate interfacility transfers of all SCI patients are critical for access to specialised care and reducing preventable complications. Elderly fallers present particular challenges to early identification.

A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer

PURPOSE

To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)-positive breast cancers from patients uniformly treated with adjuvant tamoxifen.

EXPERIMENTAL DESIGN

Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell's C-index was used to compare fixed models trained in independent data sets, including proliferation signatures.

RESULTS

Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR-based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior.

CONCLUSION

The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points.

PIK3CA and PIK3CB inhibition produce synthetic lethality when combined with estrogen deprivation in estrogen receptor-positive breast cancer

Several phosphoinositide 3-kinase (PI3K) catalytic subunit inhibitors are currently in clinical trial. We therefore sought to examine relationships between pharmacologic inhibition and somatic mutations in PI3K catalytic subunits in estrogen receptor (ER)-positive breast cancer, in which these mutations are particularly common. RNA interference (RNAi) was used to determine the effect of selective inhibition of PI3K catalytic subunits, p110alpha and p110beta, in ER(+) breast cancer cells harboring either mutation (PIK3CA) or gene amplification (PIK3CB). p110alpha RNAi inhibited growth and promoted apoptosis in all tested ER(+) breast cancer cells under estrogen deprived-conditions, whereas p110beta RNAi only affected cells harboring PIK3CB amplification. Moreover, dual p110alpha/p110beta inhibition potentiated these effects. In addition, treatment with the clinical-grade PI3K catalytic subunit inhibitor BEZ235 also promoted apoptosis in ER(+) breast cancer cells. Importantly, estradiol suppressed apoptosis induced by both gene knockdowns and BEZ235 treatment. Our results suggest that PI3K inhibitors should target both p110alpha and p110beta catalytic subunits, whether wild-type or mutant, and be combined with endocrine therapy for maximal efficacy when treating ER(+) breast cancer.

A comparative genomic analysis between human breast cancer and paired tumor lines derived from transplanation of tumor biopsies into NOD/SCID mice

Abstract #41

Background: Successful preclinical studies of experimental anticancer agents require model systems that recapitulate breast cancer biology and genomic abnormalities as accurately as possible. The use of primary human tumor explants engrafted into the humanized mammary fat pad of NOD SCID mice (HIM technique for "human in mouse") is promising in this regard, but the evidence that the genomic profile of the tumor is stable during serial translatation of human tumors into mice and between mouse passages has not beeen clearly demonstrated.&#x2028; Methods: 4th mammary glands of NOD/SCID mice were humanized by removing mouse mammary epithelia and implanting immortalized human breast fibroblasts. Human breast tumor tissues were dissociated into single cell suspensions and injected into the “humanized” mammary fat pads of NOD/SCID mice. Patient tumors were micro-dissected from the surrounding normal tissue by laser capture microdissection and tumor RNA and DNA was isolated. In addition, tumor RNA and DNA was isolated from xenografts at passage 1, 2, and 3. Agilent 4 x 44K whole genome expression array and 244K array-based comparative genomic hybridization (aCGH) was performed on established xenografts (passage 1-3) as well as the original tumor samples. Exon 9 and 20 of PIK3CA and exon 4 to 9 of TP53 were targeted for mutation detection since these genes are commonly mutated in human breast cancer.&#x2028; Results: To date, eight HIM tumor lines have been successfully established and serially passaged. The HIM number and source of tumor are as follows: HIM2 (primary tumor); HIM 3 (primary tumor); HIM 4 (abdominal wall metastasis); HIM 5 (brain metastasis from the patient used to establish HIM 2); HIM6 (primary breast cancer); HIM7 (chest wall metastasis); HIM 8 (chest wall metastasis); HIM9 (chest wall metastasis). Passage 3 HIM tumors serially transplanted in NOD/SCID mice have similar histopathological features to their original human counterparts (HCP). Sequence analyses of the eight HIM lines reveals mutations in the TP53 gene in three tumor lines and a mutation in PIK3CA gene in one tumor line that are also present in the HCP. aCGH analysis, where available, also demonstated that the positions of the major gene amplifications and deletions in HIM lines are also consistent with the HCP. Furthermore, aCGH shows that genomic structure of the grafts are stable with passage. Immunohistochemistry shows that HIM8 and its HCP are positive for HER2. Molecular subtyping by PAM50 gene list indicates that HIM 2 – 8 tumor lines and their HCP are basal type breast cancer. HIM9 tumor line and its HCP are luminal subtypes, although the proliferation signature was activated in the mouse graft.&#x2028; Conclusions: The HIM mouse system faithfully reproduces the genotypic features of the respective HCP's and is therefore a valuable research engine for the preclinical development of biomarkers, imaging techniques and for the assessment of novel therapeutic approaches, particularly for Basal-type breast cancer.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 41.

A novel tumor necrosis factor alpha-responsive CCAAT/enhancer binding protein site regulates expression of the cartilage-derived retinoic acid-sensitive protein gene in cartilage

OBJECTIVE

Inflammatory processes in rheumatoid arthritis are primarily regulated by the cytokines tumor necrosis factor alpha (TNFalpha) and interleukin-1beta (IL-1beta). Previous studies in our laboratory have shown that IL-1beta represses expression of the cartilage characteristic genes, cartilage-derived retinoic acid-sensitive protein (cd-rap) and type II collagen (COL2A1); this mechanism of repression involves activation of a CCAAT/enhancer binding protein (c/EBP) site within promoter regions. The aim of this study was to investigate novel TNFalpha-mediated mechanisms that regulate the expression of cd-rap.

METHODS

Rat chondrosarcoma cells were transiently transfected with complementary DNA constructs encoding cd-rap, in the presence of TNFalpha. The expression of c/EBPbeta, SOX9, and p300 in rat chondrosarcoma cells and primary human articular chondrocytes after treatment with TNFalpha was examined by reverse transcription-polymerase chain reaction and Western blotting. The effect of TNFalpha on endogenous binding of c/EBPbeta or SOX9 to the cd-rap promoter was examined by chromatin immunoprecipitation assays.

RESULTS

We identified a new c/EBP binding site in the cd-rap promoter (from position -1059 bp to position -1046 bp). Binding of c/EBP to this site was regulated by TNFalpha but not IL-1beta, resulting in down-regulation of cd-rap expression. This effect was reversed by mutational inactivation of the c/EBP motif. In addition, the activation potential of SOX9 and CREB binding protein/p300 on the cd-rap promoter was enhanced after mutation of the new c/EBP binding site, indicating that blockage of this site would increase transcription.

CONCLUSION

TNFalpha regulates the expression and/or DNA-binding potential of key positive-acting and negative-acting transcription factors that control the expression of the cartilage matrix gene, cd-rap.

Expression of the WASP verprolin-homologues (WAVE members) in human breast cancer

BACKGROUND

The WASP family proteins have been indicated to play a vital role in the formation of membrane protrusions required for cell locomotion. WAVE proteins are an important subfamily that also plays a crucial role in actin polymerisation, which is vital to cell migration. However, not much is known about the clinical significance of this subfamily in cancers. We report, for the first time, the expression of the WAVE molecules, at protein and mRNA levels, in human breast cancer.

MATERIALS AND METHODS

The expression of the 3 WAVE molecules at the mRNA and protein levels in a cohort of 122 human breast cancers and 32 normal breast tissues were analysed and correlated with the patients' pathological and clinical information as well as outcome (120 months follow-up).

RESULTS

All 3 WAVE molecules were detected in mammary tissues. WAVE2 transcripts were expressed in high levels in all breast tumours. Over-expression of WAVE2 was seen in node-positive cases as well as in moderately and poorly differentiated tumours. Also, high levels of WAVE2 expression were associated with death due to disease (p = 0.02) at follow-up. No distinct associations were found between the WAVE1 and WAVE3 transcripts and the breast cancer cells.

Computational identification and functional validation of regulatory motifs in cartilage-expressed genes

Chondrocyte gene regulation is important for the generation and maintenance of cartilage tissues. Several regulatory factors have been identified that play a role in chondrogenesis, including the positive transacting factors of the SOX family such as SOX9, SOX5, and SOX6, as well as negative transacting factors such as C/EBP and delta EF1. However, a complete understanding of the intricate regulatory network that governs the tissue-specific expression of cartilage genes is not yet available. We have taken a computational approach to identify cis-regulatory, transcription factor (TF) binding motifs in a set of cartilage characteristic genes to better define the transcriptional regulatory networks that regulate chondrogenesis. Our computational methods have identified several TFs, whose binding profiles are available in the TRANSFAC database, as important to chondrogenesis. In addition, a cartilage-specific SOX-binding profile was constructed and used to identify both known, and novel, functional paired SOX-binding motifs in chondrocyte genes. Using DNA pattern-recognition algorithms, we have also identified cis-regulatory elements for unknown TFs. We have validated our computational predictions through mutational analyses in cell transfection experiments. One novel regulatory motif, N1, found at high frequency in the COL2A1 promoter, was found to bind to chondrocyte nuclear proteins. Mutational analyses suggest that this motif binds a repressive factor that regulates basal levels of the COL2A1 promoter.

A promoter element of the CD-RAP gene is required for repression of gene expression in non-cartilage tissues in vitro and in vivo

The cartilage-derived retinoic acid-sensitive protein (CD-RAP) gene is expressed predominately in cartilage. Previous studies in transgenic mice have shown that the DNA promoter segment from -2,251 bp to -2,068 bp of the CD-RAP gene contains elements critical for gene expression. Subsequent studies revealed both positive and negative regulatory motifs in this 183 bp element. Here we show that this element demonstrates activation or repression of gene expression in vitro and in vivo based on cell type and content of transcription factors. The distribution of Sox (positive) and C/EBP (negative) transcription factors in cell lines and in mouse tissues is consistent with their positive and negative roles. In transgenic mice, when the 183-bp element was removed from a 3,345-bp cartilage-specific CD-RAP promoter, expression of the reporter gene became widespread, being observed in muscle, bone, lung, and liver in addition to cartilage. In vitro, mutation of the C/EBP site activated the inactive 3,345-bp CD-RAP gene promoter in myoblastic cells, suggesting that this site is responsible for (-2,079 bp) repression. These results indicate that the 183-bp element plays an important role in cartilage-specific gene expression by acting as a chondrocyte-regulatory module repressing transcription in non-chondrocytes and contributing to activation in chondrocytes. This is the first report of a functional DNA element necessary for repression in non-cartilage tissues in vivo.

Alternative splicing of type II procollagen exon 2 is regulated by the combination of a weak 5' splice site and an adjacent intronic stem-loop cis element

Alternative splicing of the type II procollagen gene (COL2A1) is developmentally regulated during chondrogenesis. Chondroprogenitor cells produce the type IIA procollagen isoform by splicing (including) exon 2 during pre-mRNA processing, whereas differentiated chondrocytes synthesize the type IIB procollagen isoform by exon 2 skipping (exclusion). Using a COL2A1 mini-gene and chondrocytes at various stages of differentiation, we identified a non-classical consensus splicing sequence in intron 2 adjacent to the 5' splice site, which is essential in regulating exon 2 splicing. RNA mapping confirmed this region contains secondary structure in the form of a stem-loop. Mutational analysis identified three cis elements within the conserved double-stranded stem region that are functional only in the context of the natural weak 5' splice site of exon 2; they are 1) a uridine-rich enhancer element in all cell types tested except differentiated chondrocytes; 2) an adenine-rich silencer element, and 3) an enhancer cis element functional in the context of secondary structure. This is the first report identifying key cis elements in the COL2A1 gene that modulate the cell type-specific alternative splicing switch of exon 2 during cartilage development.

Tissue-restricted expression of the Cdrap/Mia gene within a conserved multigenic housekeeping locus

The mouse cartilage-derived retinoic acid-sensitive protein (Cdrap/Mia) gene is expressed primarily in cartilage. Various promoter motifs that participate in restricted gene expression have been identified. To define mechanisms of regulation further, we determined the DNA sequence of 12 kb flanking this gene. We show that two genes, Snrpa and Rab4b, that have characteristics of housekeeping genes, including ubiquitous expression, closely flank Cdrap/Mia. We found the exon/intron structure and the organization of the gene locus to be conserved between the mouse and the human chromosomes, suggestive of functional relevance. DNase I hypersensitivity assays comparing expressing and nonexpressing cells indicate that the chromatin structure surrounding Cdrap/Mia is not greatly altered for transcription. The tissue-restricted expression of Cdrap/Mia, located between two housekeeping genes, provides a distinctive model for restricted transcriptional regulation from a multigenic locus.

Distribution of the transcription factors Sox9, AP-2, and [delta]EF1 in adult murine articular and meniscal cartilage and growth plate

The control of extracellular matrix (ECM) production is important for the development, maintenance, and repair of cartilage tissues. Matrix molecule synthesis is generally regulated by the rate of gene transcription determined by DNA transcription factors. We have shown that transcription factors Sox9, AP-2, and [delta]EF1 are able to alter the rate of CD-RAP transcription in vitro: Sox9 upregulates, AP-2 exhibits biphasic effects, and [delta]EF1 represses expression of the CD-RAP gene. To correlate these in vitro activities in vivo, transcription factors were co-immunolocalized with ECM proteins in three different cartilage tissues in which the rates of biosynthesis are quite different: articular, meniscal, and growth plate. Immunoreactivities of type II collagen and CD-RAP were higher in growth plate than in either the articular or meniscal cartilages and correlated positively with Sox9 protein. Sox9 staining decreased with hypertrophy and was low in articular and meniscal cartilages. In contrast, AP-2 and [delta]EF1 were low in proliferating chondrocytes but high in lower growth plate, articular, and meniscal cartilages. This increase was also accompanied by intense nuclear staining. These immunohistochemical results are the first to localize both [delta]EF1 and AP-2 to adult articular, meniscal, and growth plate cartilages and provide in vivo correlation of previous molecular biological studies.

A selenopyrylium photosensitizer for photodynamic therapy related in structure to the antitumor agent AA1 with potent in vivo activity and no long-term skin photosensitization

Cationic chalcogenopyrylium dyes 5 were synthesized in six steps from p-aminophenylacetylene (9), have absorption maxima in methanol of 623, 654, and 680 nm for thio-, seleno-, and telluropyrylium dyes, respectively, and generate singlet oxygen with quantum yields [Phi((1)O(2))] of 0.013, 0.029, and 0.030, respectively. Selenopyrylium dye 5-Se was phototoxic to cultured murine Colo-26 and Molt-4 cells. Initial acute toxicity studies in vivo demonstrate that, at 29 mg (62 micromol)/kg, no toxicity was observed with 5-Se in animals followed for 90 days under normal vivarium conditions. In animals given 10 mg/kg of 5-Se via intravenous injection, 2-8 nmol of 5-Se/g of tumor was found at 3, 6, and 24 h postinjection. Animals bearing R3230AC rat mammary adenocarcinomas were treated with 10 mg/kg of 5-Se via tail-vein injection and with 720 J cm(-2) of 570-750-nm light from a filtered tungsten lamp at 200 mW cm(-2) (24 h postinjection of 5-Se). Treated animals gave a tumor-doubling time of 9 +/- 4 days, which is a 300% increase in tumor-doubling time relative to the 3 +/- 2 days for untreated dark controls. Mechanistically, the mitochondria appear to be a target. In cultured R3230AC rat mammary adenocarcinoma cells treated with 0.1 and 1.0 microM 5-Se and light, mitochondrial cytochrome c oxidase activity was inhibited relative to cytochrome c oxidase activity in untreated cells. Irradiation of isolated mitochondrial suspensions treated with 10 microM dye 5-Se inhibited cytochrome c oxidase activity. The degree of enzyme inhibition was abated in a reduced oxygen environment. Superoxide dismutase, at a final concentration of 30 U, did not alter the photosensitized inhibition of mitochondrial cytochrome c oxidase by dye 5-Se. The data suggest that singlet oxygen may play a major role in the photosensitized inhibition of mitochondrial cytochrome c oxidase.