Molecular Analysis of Short- versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma.

Despite having similar histologic features, patients with high-grade serous ovarian carcinoma (HGSC) often experience highly variable outcomes. The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, <3 years) are largely unknown. The present study sought to identify molecular predictors of LTS for women with HGSC. A cohort of 24 frozen HGSC samples was collected (12 LTS and 12 STS) and analyzed at DNA, RNA, and protein levels. OVCAR5 and OVCAR8 cell lines were used for in vitro validation studies. For in vivo studies, we injected OVCAR8 cells into the peritoneal cavity of female athymic nude mice. From RNAseq analysis, 11 genes were found to be differentially expressed between the STS and LTS groups (fold change > 2; false discovery rate < 0.01). In the subsequent validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. CIBERSORT analysis showed that T cells (follicular helper) were found at higher levels in tumors from LTS than STS groups. In vitro data using OVCAR5 and OVCAR8 cells showed decreased proliferation with TMEM62 overexpression and positive correlation with a longevity-regulating pathway (KEGG HSA04213) at the RNA level. In vivo analysis using the OVCAR8-TMEM62-TetON model showed decreased tumor burden in mice with high- vs. low-expressing TMEM62 tumors. Our results demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes

Gene Body Methylation of the Lymphocyte-Specific Gene CARD11 Results in Its Overexpression and Regulates Cancer mTOR Signaling.

Investigations into the function of nonpromoter DNA methylation have yielded new insights into epigenetic regulation of gene expression. Previous studies have highlighted the importance of distinguishing between DNA methylation in discrete functional regions; however, integrated nonpromoter DNA methylation and gene expression analyses across a wide number of tumor types and corresponding normal tissues have not been performed. Through integrated analysis of gene expression and DNA methylation profiles, we examined 32 tumor types and identified 57 tumor suppressors and oncogenes out of 260 genes exhibiting a correlation of > 0.5 between gene body methylation and gene expression in at least one tumor type. The lymphocyte-specific gene CARD11 exhibits robust association between gene body methylation and expression across 19 of 32 tumor types examined. It is significantly overexpressed in kidney renal cell carcinoma (KIRC) and lung adenocarcinoma (LUAD) tumor tissues in comparison with respective control samples; and is significantly associated with lower overall survival in KIRC. Contrary to its canonical function in lymphocyte NFκB activation, CARD11 activates the mTOR pathway in KIRC and LUAD, resulting in suppressed autophagy. Furthermore, demethylation of a CpG island within the gene body of CARD11 decreases gene expression. Collectively, our study highlights how DNA methylation outside the promoter region can impact tumor progression. IMPLICATIONS: Our study describes a novel regulatory role of gene body DNA methylation-dependent CARD11 expression on mTOR signaling and its impact on tumor progression.

Methylation-eQTL analysis in cancer research.

MOTIVATION: DNA methylation is a key epigenetic factor regulating gene expression. While promoter methylation has been well studied, recent publications have revealed that functionally important methylation also occurs in intergenic and distal regions, and varies across genes and tissue types. Given the growing importance of inter-platform integrative genomic analyses, there is an urgent need to develop methods to discover and characterize gene-level relationships between methylation and expression. RESULTS: We introduce a novel sequential penalized regression approach to identify methylation-expression quantitative trait loci (methyl-eQTLs), a term that we have coined to represent, for each gene and tissue type, a sparse set of CpG loci best explaining gene expression and accompanying weights indicating direction and strength of association. Using TCGA and MD Anderson colorectal cohorts to build and validate our models, we demonstrate our strategy better explains expression variability than current commonly used gene-level methylation summaries. The methyl-eQTLs identified by our approach can be used to construct gene-level methylation summaries that are maximally correlated with gene expression for use in integrative models, and produce a tissue-specific summary of which genes appear to be strongly regulated by methylation. Our results introduce an important resource to the biomedical community for integrative genomics analyses involving DNA methylation. AVAILABILITY AND IMPLEMENTATION: We produce an R Shiny app (https://rstudio-prd-c1.pmacs.upenn.edu/methyl-eQTL/) that interactively presents methyl-eQTL results for colorectal, breast and pancreatic cancer. The source R code for this work is provided in the Supplementary Material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

Proteomic Profiling of Signaling Networks Modulated by G-CSF/Plerixafor/Busulfan-Fludarabine Conditioning in Acute Myeloid Leukemia Patients in Remission or with Active Disease prior to Allogeneic Stem Cell Transplantation.

To characterize intracellular signaling in peripheral blood (PB) cells of acute myeloid leukemia (AML) patients undergoing pretransplant conditioning with CXCR4 inhibitor plerixafor, granulocyte colony-stimulating factor (G-CSF), and busulfan plus fludarabine (Bu+Flu) chemotherapy, we profiled 153 proteins in 33 functional groups using reverse phase protein array. CXCR4 inhibition mobilized AML progenitors and clonal AML cells, and this was associated with molecular markers of cell cycle progression. G-CSF/plerixafor and G-CSF/plerixafor/Bu+Flu modulated distinct signaling networks in AML blasts of patients undergoing conditioning with active disease compared to nonleukemic PB cells of patients in remission. We identified AML-specific proteins that remained aberrantly expressed after chemotherapy, representing putative chemoresistance markers in AML.

Pan-cancer genomic analysis links 3'UTR DNA methylation with increased gene expression in T cells.

BACKGROUND: Investigations into the function of non-promoter DNA methylation have yielded new insights into the epigenetic regulation of gene expression. However, integrated genome-wide non-promoter DNA methylation and gene expression analyses across a wide number of tumour types and corresponding normal tissues have not been performed. METHODS: To investigate the impact of non-promoter DNA methylation on cancer pathogenesis, we performed a large-scale analysis of gene expression and DNA methylation profiles, finding enrichment in the 3'UTR DNA methylation positively correlated with gene expression. Filtering for genes in which 3'UTR DNA methylation strongly correlated with gene expression yielded a list of genes enriched for functions involving T cell activation. FINDINGS: The important immune checkpoint gene Havcr2 showed a substantial increase in 3'UTR DNA methylation upon T cell activation and subsequent upregulation of gene expression in mice. Furthermore, this increase in Havcr2 gene expression was abrogated by treatment with decitabine. INTERPRETATION: These findings indicate that the 3'UTR is a functionally relevant DNA methylation site. Additionally, we show a potential novel mechanism of HAVCR2 regulation in T cells, providing new insights for modulating immune checkpoint blockade.

Defining Survivorship Trajectories Across Patients With Solid Tumors: An Evidence-Based Approach.

Importance: Survivorship involves a multidisciplinary approach to surveillance and management of comorbidities and secondary cancers, overseen by oncologists, surgeons, and primary care physicians. Optimal timing and coordination of care, however, is unclear and often based on arbitrary 5-year cutoffs. Objective: To determine high- and low-risk periods for all tumor types that could define when survivorship care might best be overseen by oncologists and when to transition to primary care physicians. Design, Setting, and Participants: In this pan-cancer, longitudinal, observational study, excess mortality hazard, calculated as an annualized mortality risk above a baseline population, was plotted over time. The time this hazard took to stabilize defined a high-risk period. The percent morality elevation above age- and sex-matched controls in the latter low-risk period was reported as a mortality gap. The US population-based Surveillance, Epidemiology, and End Results database defined the cancer population, and the US Census life tables defined controls. Incident cases of patients with cancer were separated into tumor types based on International Classification of Diseases for Oncology definitions. Exposures: Population-level data on incident cancer cases was compared with the general US population. Main Outcomes and Measures: Overall mortality and cause of death were reported on observed cancer cases. Results: A total of 2 317 185 patients (median age, 63 years; 49.8% female) with 66 primary tumor types were evaluated. High-risk surveillance period durations ranged from less than 1 year (breast, prostate, lip, ocular, and parathyroid cancers) up to 19 years (unspecified gastrointestinal cancers). The annualized mortality gap, representing the excess mortality in the stable period, ranged from a median 0.26% to 9.33% excess annual mortality (thyroid and hypopharyngeal cancer populations, respectively). Cluster analysis produced 6 risk cluster groups: group 1, with median survival of 16.2 (5th to 95th percentile range [PR], 10.7-40.2) years and median high-risk period of 2.5 (PR, 0-5.0) years; group 2, 8.3 (PR, 5.1-23.3) and 2.5 (PR, 4.0-8.0) years; group 3, 2.8 (PR, 1.4-3.7) and 7.0 (PR, 6.0-11.1) years; group 4, 1.6 (PR, 1.5-1.8) and 6.0 (PR, 5.1-11.4) years; group 5, 0.8 (PR, 0.5-1.2) and 0.8 (PR, 0.5-1.2) years; and group 6, 0.5 (PR, 0.4-0.8) and 12.0 (PR, 9.3-12.9) years, respectively. Subanalyses of selected tumor types in these groups revealed that stratifying on stage and histologic type can change the risk cluster and guidance for care. Conclusions and Relevance: These findings indicate that a standardized 5-year surveillance period is inadequate for some cancers while excessive for others. High-risk cancers require the most resources with the longest high-risk period, highest persistent baseline mortality risk, and longest period of primary cancer mortality, all arguing for longer follow-up with an oncologist in these cancers.

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.

Cholangiocarcinoma With FGFR Genetic Aberrations: A Unique Clinical Phenotype.

PURPOSE: FGFR genetic aberrations (GAs) occur in an estimated 10% to 16% of intrahepatic cholangiocarcinomas (CCAs). The natural history of CCA with FGFR GAs, the prognostic role of coexisting GAs, and the outcome with FGFR-targeted inhibitors are unknown. PATIENTS AND METHODS: Patients with CCA with FGFR GAs were identified using next-generation sequencing or fluorescence in situ hybridization from four tertiary cancer centers and compared with FGFR wild-type counterparts. Data reviewed included demographic, treatment, overall survival (OS), and GA data. Fisher's exact test, Kaplan-Meier plots, and log-rank tests were used for statistical analysis. RESULTS: Three hundred seventy-seven patients with CCA were identified, and 95 had FGFR GAs. FGFR2 GA was most common (n = 74, with 63 fusions) and seen in intrahepatic CCA. In patients with CCA, FGFR GAs occurred more frequently in younger patients (≤ 40 years; 20%) compared with older patients (> 40 years; 6.7%; P < .001), presented at an earlier stage (TNM stage I/II v III/IV: 35.8% v 22%, respectively; P = .001), and were associated with a longer OS compared with patients without FGFR GAs (37 v 20 months, respectively; P < .001). This difference remained significant after excluding 36 patients treated with FGFR inhibitors. There was no OS difference (P = .60) between CCA with FGFR2 fusions (n = 63) versus other FGFR GAs (n = 29). Patients with FGFR GAs had a better OS with FGFR-targeted therapy compared with standard treatment (P = .01). BAP1 mutation was the most common coexisting mutation without prognostic impact, whereas TP53 (P = .04) and CDKN2A/B (P = .04) were correlated with a shorter OS. CONCLUSION: CCA with FGFR GAs represents a unique subtype occurring in younger patients with an indolent disease course. FGFR-targeted therapy may have a positive impact on OS in this subgroup.

Genetic Polymorphisms of CFH and ARMS2 Do Not Predict Response to Antioxidants and Zinc in Patients with Age-Related Macular Degeneration: Independent Statistical Evaluations of Data from the Age-Related Eye Disease Study.

PURPOSE: Considerable controversy has erupted in recent years regarding whether genotyping should be part of standard care for patients with age-related macular degeneration (AMD) who are being considered for treatment with antioxidants and zinc. We aimed to determine whether genotype predicts response to supplements in AMD. DESIGN: Three separate statistical teams reanalyzed data derived from the Age-Related Eye Disease Study (AREDS), receiving data prepared by the AREDS investigators and, separately, data from investigators reporting findings that support the use of genotyping. PARTICIPANTS: The population of interest was AREDS participants with AMD worse than category 1 and genotyping data available. Data from the 2 groups overlap imperfectly with respect to measurements made: the largest common set involved 879 participants for whom the same CFH and ARMS2 single nucleotide polymorphisms were measured by both groups. METHODS: Each team took a separate but complementary approach. One team focused on data concordance between conflicting studies. A second team focused on replicating the key claim of an interaction between genotype and treatment. The third team took a blank slate approach in attempting to find baseline predictors of treatment response. MAIN OUTCOME MEASURES: Progression to advanced AMD. RESULTS: We found errors in the data used to support the initial claim of genotype-treatment interaction. Although we found evidence that high-risk patients had more to gain from treatment, we were unable to replicate any genotype-treatment interactions after adjusting for multiple testing. We tested 1 genotype claim on an independent set of data, with negative results. Even if we assumed that interactions in fact did exist, we did not find evidence to support the claim that supplementation leads to a large increase in the risk of advanced AMD in some genotype subgroups. CONCLUSIONS: Patients who meet criteria for supplements to prevent AMD progression should be offered zinc and antioxidants without consideration of genotype.

Dissecting Pathway Disturbances Using Network Topology and Multi-platform Genomics Data.

Complex diseases such as cancers usually result from accumulated disturbance of pathways instead of the disruptions of one or a few major genes. As opposed to single-platform analyses, it is likely that integrating diverse molecular regulatory elements and their interactions can lead to more insights on pathway-level disturbances of biological systems and their potential consequences in disease development and progression. To explore the benefit of pathway-based analysis, we focus on mutli-platform genomics, epigenomics and transcriptomics (-omics, for short) from 11 cancer types collected by the Cancer Genome Atlas (TCGA) project. Specifically, we use a well-studied oncogenetic pathway, the BRAF pathway, to investigate the relevant copy number variants, methylations and gene expressions, and quantify their effects on discovering tumor-specific aberrations across multiple tumor lineages. We also perform simulation studies to further investigate the effects of network topology and multiple omics on dissecting pathway disturbances. Our analysis shows that adding molecular regulatory elements such as copy number variants (CNVs) and/or methylations to the baseline mRNA molecules can improve our power of discovering tumorous aberrances. Also, incorporating copy number variants with the baseline mRNA molecules can be more beneficial than incorporating methylations. Moreover, employing regulatory topologies can improve the discoveries of tumorous aberrances. Finally, our analysis reveals similarities and differences among diverse cancer types based on disturbance of the BRAF pathway.

Macrophage depletion through colony stimulating factor 1 receptor pathway blockade overcomes adaptive resistance to anti-VEGF therapy.

Anti-angiogenesis therapy has shown clinical benefit in patients with high-grade serous ovarian cancer (HGSC), but adaptive resistance rapidly emerges. Thus, approaches to overcome such resistance are needed. We developed the setting of adaptive resistance to anti-VEGF therapy, and performed a series of in vivo experiments in both immune competent and nude mouse models. Given the pro-angiogenic properties of tumor-associated macrophages (TAMs) and the dominant role of CSF1R in macrophage function, we added CSF1R inhibitors following emergence of adaptive resistance to anti-VEGF antibody. Mice treated with a CSF1R inhibitor (AC708) after anti-VEGF antibody resistance had little to no measurable tumor burden upon completion of the experiment while those that did not receive a CSF1R inhibitor still had abundant tumor. To mimic clinically used regimens, mice were also treated with anti-VEGF antibody and paclitaxel until resistance emerged, and then a CSF1R inhibitor was added. The addition of a CSF1R inhibitor restored response to anti-angiogenesis therapy, resulting in 83% lower tumor burden compared to treatment with anti-VEGF antibody and paclitaxel alone. Collectively, our data demonstrate that the addition of a CSF1R inhibitor to anti-VEGF therapy and taxane chemotherapy results in robust anti-tumor effects.

Surface PD-L1, E-cadherin, CD24, and VEGFR2 as markers of epithelial cancer stem cells associated with rapid tumorigenesis.

Cancer cells require both migratory and tumorigenic property to establish metastatic tumors outside the primary microenvironment. Identifying the characteristic features of migratory cancer stem cells with tumorigenic property is important to predict patient prognosis and combat metastasis. Here we established one epithelial and two mesenchymal cell lines from ascites of a bladder cancer patient (i.e. cells already migrated outside primary tumor). Analyses of these cell lines demonstrated that the epithelial cells with surface expression of PD-L1, E-cadherin, CD24, and VEGFR2 rapidly formed tumors outside the primary tumor microenvironment in nude mice, exhibited signatures of immune evasion, increased stemness, increased calcium signaling, transformation, and novel E-cadherin-RalBP1 interaction. The mesenchymal cells on the other hand, exhibited constitutive TGF-ß signaling and were less tumorigenic. Hence, targeting epithelial cancer stem cells with rapid tumorigenesis signatures in future might help to combat metastasis.

Maternal 25(OH)D concentrations ≥40 ng/mL associated with 60% lower preterm birth risk among general obstetrical patients at an urban medical center.

BACKGROUND: Given the high rate of preterm birth (PTB) nationwide and data from RCTs demonstrating risk reduction with vitamin D supplementation, the Medical University of South Carolina (MUSC) implemented a new standard of care for pregnant women to receive vitamin D testing and supplementation. OBJECTIVES: To determine if the reported inverse relationship between maternal 25(OH)D and PTB risk could be replicated at MUSC, an urban medical center treating a large, diverse population. METHODS: Medical record data were obtained for pregnant patients aged 18-45 years between September 2015 and December 2016. During this time, a protocol that included 25(OH)D testing at first prenatal visit with recommended follow-up testing was initiated. Free vitamin D supplements were offered and the treatment goal was ≥40 ng/mL. PTB rates (<37 weeks) were calculated, and logistic regression and locally weighted regression (LOESS) were used to explore the association between 25(OH)D and PTB. Subgroup analyses were also conducted. RESULTS: Among women with a live, singleton birth and at least one 25(OH)D test during pregnancy (N = 1,064), the overall PTB rate was 13%. The LOESS curve showed gestational age rising with increasing 25(OH)D. Women with 25(OH)D ≥40 ng/mL had a 62% lower risk of PTB compared to those <20 ng/mL (p<0.0001). After adjusting for socioeconomic variables, this lower risk remained (OR = 0.41, p = 0.002). Similar decreases in PTB risk were observed for PTB subtypes (spontaneous: 58%, p = 0.02; indicated: 61%, p = 0.006), by race/ethnicity (white: 65%, p = 0.03; non-white: 68%, p = 0.008), and among women with a prior PTB (80%, p = 0.02). Among women with initial 25(OH)D <40 ng/mL, PTB rates were 60% lower for those with ≥40 vs. <40 ng/mL on a follow-up test (p = 0.006); 38% for whites (p = 0.33) and 78% for non-whites (p = 0.01). CONCLUSIONS: Maternal 25(OH)D concentrations ≥40 ng/mL were associated with substantial reduction in PTB risk in a large, diverse population of women.

Elevation of TP53 Autoantibody Before CA125 in Preclinical Invasive Epithelial Ovarian Cancer.

Purpose: The TP53 tumor-suppressor gene is mutated in >95% of high-grade serous ovarian cancers. Detecting an autologous antibody response to TP53 that might improve early detection.Experimental Design: An immunoassay was developed to measure TP53 autoantibody in sera from 378 cases of invasive epithelial ovarian cancer and 944 age-matched healthy controls from the United States, Australia, and the United Kingdom. Serial preclinical samples from cases and controls were also assayed from the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).Results: Using a cutoff value of 78 U/mL to achieve a specificity of 97.4%, TP53 autoantibody was elevated in 30% of 50 cases from MD Anderson, 21.3% of 108 cases from the Australian Ovarian Cancer Study, and 21% of 220 cases from the UKCTOCS. Among 164 cases with rising CA125 detected with the UKCTOCS risk of ovarian cancer algorithm (ROCA), 20.7% had elevated TP53 autoantibody. In cases missed by the ROCA, 16% of cases had elevated TP53 autoantibody. Of the 34 ovarian cancer cases detected with the ROCA, TP53 autoantibody titers were elevated 11.0 months before CA125. In the 9 cases missed by the ROCA, TP53 autoantibody was elevated 22.9 months before cancer diagnosis. Similar sensitivity was obtained using assays with specific mutant and wild-type TP53.Conclusions: TP53 autoantibody levels provide a biomarker with clinically significant lead time over elevation of CA125 or an elevated ROCA value. Quantitative assessment of autoantibodies in combination with CA125 holds promise for earlier detection of invasive epithelial ovarian cancer. Clin Cancer Res; 23(19); 5912-22. ©2017 AACR.

High-throughput profiling of signaling networks identifies mechanism-based combination therapy to eliminate microenvironmental resistance in acute myeloid leukemia.

The bone marrow microenvironment is known to provide a survival advantage to residual acute myeloid leukemia cells, possibly contributing to disease recurrence. The mechanisms by which stroma in the microenvironment regulates leukemia survival remain largely unknown. Using reverse-phase protein array technology, we profiled 53 key protein molecules in 11 signaling pathways in 20 primary acute myeloid leukemia samples and two cell lines, aiming to understand stroma-mediated signaling modulation in response to the targeted agents temsirolimus (MTOR), ABT737 (BCL2/BCL-XL), and Nutlin-3a (MDM2), and to identify the effective combination therapy targeting acute myeloid leukemia in the context of the leukemia microenvironment. Stroma reprogrammed signaling networks and modified the sensitivity of acute myeloid leukemia samples to all three targeted inhibitors. Stroma activated AKT at Ser473 in the majority of samples treated with single-agent ABT737 or Nutlin-3a. This survival mechanism was partially abrogated by concomitant treatment with temsirolimus plus ABT737 or Nutlin-3a. Mapping the signaling networks revealed that combinations of two inhibitors increased the number of affected proteins in the targeted pathways and in multiple parallel signaling, translating into facilitated cell death. These results demonstrated that a mechanism-based selection of combined inhibitors can be used to guide clinical drug selection and tailor treatment regimens to eliminate microenvironment-mediated resistance in acute myeloid leukemia.

Integrated MicroRNA-mRNA Profiling Identifies Oncostatin M as a Marker of Mesenchymal-Like ER-Negative/HER2-Negative Breast Cancer.

MicroRNAs (miRNAs) simultaneously modulate different oncogenic networks, establishing a dynamic system of gene expression and pathway regulation. In this study, we analyzed global miRNA and messenger RNA (mRNA) expression profiles of 17 cell lines representing different molecular breast cancer subtypes. Spearman's rank correlation test was used to evaluate the correlation between miRNA and mRNA expression. Hierarchical clustering and pathway analysis were also performed. Publicly available gene expression profiles (n = 699) and tumor tissues (n = 80) were analyzed to assess the relevance of key miRNA-regulated pathways in human breast cancer. We identified 39 significantly deregulated miRNAs, and the integration between miRNA and mRNA data revealed the importance of immune-related pathways, particularly the Oncostatin M (OSM) signaling, associated with mesenchymal-like breast cancer cells. OSM levels correlated with genes involved in the inflammatory response, epithelial-to-mesenchymal transition (EMT), and epidermal growth factor (EGF) signaling in human estrogen receptor (ER)-negative/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Our results suggest that the deregulation of specific miRNAs may cooperatively impair immune and EMT pathways. The identification of the OSM inflammatory pathway as an important mediator of EMT in triple-negative breast cancer (TNBC) may provide a novel potential opportunity to improve therapeutic strategies.

Immune cell profiling in cancer: molecular approaches to cell-specific identification.

The immune system has many important regulatory roles in cancer development and progression. Given the emergence of effective immune therapies against many cancers, reliable predictors of response are needed. One method of determining response is by evaluating immune cell populations from treated and untreated tumor samples. The amount of material obtained from tumor biopsies can be limited; therefore, gene-based or protein-based analyses may be attractive because they require minimal tissue. Cell-specific signatures are being analyzed with use of the latest technologies, including NanoString's nCounter technology, intracellular staining flow cytometry, cytometry by time-of-flight, RNA-Seq, and barcoding antibody-based protein arrays. These signatures provide information about the contributions of specific types of immune cells to bulk tumor samples. To date, both tumor tissue and immune cells have been analyzed for molecular expression profiles that can assess genes and proteins that are specific to immune cells, yielding results of varying specificity. Here, we discuss the importance of profiling tumor tissue and immune cells to identify immune-cell-associated genes and proteins and specific gene profiles of immune cells. We also discuss the use of these signatures in cancer treatment and the challenges faced in molecular expression profiling of immune cell populations.

Functional CAR models for large spatially correlated functional datasets.

We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on functions defined on higher dimensional domains such as images. Through simulation studies, we demonstrate that accounting for the spatial correlation in our modeling leads to improved functional regression performance. Applied to a high-throughput spatially correlated copy number dataset, the model identifies genetic markers not identified by comparable methods that ignore spatial correlations.