Sex differences in plasma proteomic markers in late-life depression

Previous studies have shown significant sex-specific differences in major depressive disorder (MDD) in multiple biological parameters. Most studies focused on young and middle-aged adults, and there is a paucity of information about sex-specific biological differences in older adults with depression (aka, late-life depression (LLD)). To address this gap, this study aimed to evaluate sex-specific biological abnormalities in a large group of individuals with LLD using an untargeted proteomic analysis. We quantified 344 plasma proteins using a multiplex assay in 430 individuals with LLD and 140 healthy comparisons (HC) (age range between 60 and 85 years old for both groups). Sixty-six signaling proteins were differentially expressed in LLD (both sexes). Thirty-three proteins were uniquely associated with LLD in females, while six proteins were uniquely associated with LLD in males. The main biological processes affected by these proteins in females were related to immunoinflammatory control. In contrast, despite the smaller number of associated proteins, males showed dysregulations in a broader range of biological pathways, including immune regulation pathways, cell cycle control, and metabolic control. Sex has a significant impact on biomarker changes in LLD. Despite some overlap in differentially expressed biomarkers, males and females show different patterns of biomarkers changes, and males with LLD exhibit abnormalities in a larger set of biological processes compared to females. Our findings can provide novel targets for sex-specific interventions in LLD.

Mixed invasive ductal lobular carcinoma is clinically and pathologically more similar to invasive lobular than ductal carcinoma

BACKGROUND

Mixed invasive ductal lobular carcinoma (mDLC) remains a poorly understood subtype of breast cancer composed of coexisting ductal and lobular components.

METHODS

We sought to describe clinicopathologic characteristics and determine whether mDLC is clinically more similar to invasive ductal carcinoma (IDC) or invasive lobular carcinoma (ILC), using data from patients seen at the University of Pittsburgh Medical Center.

RESULTS

We observed a higher concordance in clinicopathologic characteristics between mDLC and ILC, compared to IDC. There is a trend for higher rates of successful breast-conserving surgery after neoadjuvant chemotherapy in patients with mDLC compared to patients with ILC, in which it is known to be lower than in those with IDC. Metastatic patterns of mDLC demonstrate a propensity to develop in sites characteristic of both IDC and ILC. A meta-analysis evaluating mDLC showed shared features with both ILC and IDC with significantly more ER-positive and fewer high grades in mDLC compared to IDC, although mDLCs were significantly smaller and included fewer late-stage tumours compared to ILC.

CONCLUSIONS

These findings support clinicopathologic characteristics of mDLC driven by individual ductal vs lobular components and given the dominance of lobular pathology, mDLC features are often more similar to ILC than IDC. This study exemplifies the complexity of mixed disease.

Fusion Gene Detection in Prostate Cancer Samples Enhances the Prediction of Prostate Cancer Clinical Outcomes from Radical Prostatectomy through Machine Learning in a Multi-Institutional Analysis

Prostate cancer remains one of the most fatal malignancies in men in the United States. Predicting the course of prostate cancer is challenging given that only a fraction of prostate cancer patients experience cancer recurrence after radical prostatectomy or radiation therapy. This study examined the expressions of 14 fusion genes in 607 prostate cancer samples from the University of Pittsburgh, Stanford University, and the University of Wisconsin-Madison. The profiling of 14 fusion genes was integrated with Gleason score of the primary prostate cancer and serum prostate-specific antigen level to develop machine-learning models to predict the recurrence of prostate cancer after radical prostatectomy. Machine-learning algorithms were developed by analysis of the data from the University of Pittsburgh cohort as a training set using the leave-one-out cross-validation method. These algorithms were then applied to the data set from the combined Stanford/Wisconsin cohort (testing set). The results showed that the addition of fusion gene profiling consistently improved the prediction accuracy rate of prostate cancer recurrence by Gleason score, serum prostate-specific antigen level, or a combination of both. These improvements occurred in both the training and testing cohorts and were corroborated by multiple models.

Diagnosis of T-cell-mediated kidney rejection by biopsy-based proteomic biomarkers and machine learning

Background

Biopsy-based diagnosis is essential for maintaining kidney allograft longevity by ensuring prompt treatment for graft complications. Although histologic assessment remains the gold standard, it carries significant limitations such as subjective interpretation, suboptimal reproducibility, and imprecise quantitation of disease burden. It is hoped that molecular diagnostics could enhance the efficiency, accuracy, and reproducibility of traditional histologic methods.

Methods

Quantitative label-free mass spectrometry analysis was performed on a set of formalin-fixed, paraffin-embedded (FFPE) biopsies from kidney transplant patients, including five samples each with diagnosis of T-cell-mediated rejection (TCMR), polyomavirus BK nephropathy (BKPyVN), and stable (STA) kidney function control tissue. Using the differential protein expression result as a classifier, three different machine learning algorithms were tested to build a molecular diagnostic model for TCMR.

Results

The label-free proteomics method yielded 800-1350 proteins that could be quantified with high confidence per sample by single-shot measurements. Among these candidate proteins, 329 and 467 proteins were defined as differentially expressed proteins (DEPs) for TCMR in comparison with STA and BKPyVN, respectively. Comparing the FFPE quantitative proteomics data set obtained in this study using label-free method with a data set we previously reported using isobaric labeling technology, a classifier pool comprised of features from DEPs commonly quantified in both data sets, was generated for TCMR prediction. Leave-one-out cross-validation result demonstrated that the random forest (RF)-based model achieved the best predictive power. In a follow-up blind test using an independent sample set, the RF-based model yields 80% accuracy for TCMR and 100% for STA. When applying the established RF-based model to two public transcriptome datasets, 78.1%-82.9% sensitivity and 58.7%-64.4% specificity was achieved respectively.

Conclusions

This proof-of-principle study demonstrates the clinical feasibility of proteomics profiling for FFPE biopsies using an accurate, efficient, and cost-effective platform integrated of quantitative label-free mass spectrometry analysis with a machine learning-based diagnostic model. It costs less than 10 dollars per test.

Late-Life Depression is Associated With Increased Levels of GDF-15, a Pro-Aging Mitokine

OBJECTIVE

In older adults, major depressive disorder (MDD) is associated with accelerated physiological and cognitive aging, generating interest in uncovering biological pathways that may be targetable by interventions. Growth differentiation factor-15 (GDF-15) plays a significant role in biological aging via multiple biological pathways relevant to age and age-related diseases. Elevated levels of GDF-15 correlate with increasing chronological age, decreased telomerase activity, and increased mortality risk in older adults. We sought to evaluate the circulating levels of GDF-15 in older adults with MDD and its association with depression severity, physical comorbidity burden, age of onset of first depressive episode, and cognitive performance.

DESIGN

This study assayed circulating levels of GDF-15 in 393 older adults (mean ± SD age 70 ± 6.6 years, male:female ratio 1:1.54), 308 with MDD and 85 non-depressed comparison individuals.

RESULTS

After adjusting for confounding variables, depressed older adults had significantly higher GDF-15 serum levels (640.1 ± 501.5 ng/mL) than comparison individuals (431.90 ± 223.35 ng/mL) (t=3.75, d.f.= 391, p=0.0002). Among depressed individuals, those with high GDF-15 had higher levels of comorbid physical illness, lower executive cognitive functioning, and higher likelihood of having late-onset depression.

CONCLUSION

Our results suggest that depression in late life is associated with GDF-15, a marker of amplified age-related biological changes. GDF-15 is a novel and potentially targetable biological pathway between depression and accelerated aging, including cognitive aging.

DiffCircaPipeline: a framework for multifaceted characterization of differential rhythmicity

SUMMARY

Circadian oscillations of gene expression regulate daily physiological processes, and their disruption is linked to many diseases. Circadian rhythms can be disrupted in a variety of ways, including differential phase, amplitude and rhythm fitness. Although many differential circadian biomarker detection methods have been proposed, a workflow for systematic detection of multifaceted differential circadian characteristics with accurate false positive control is not currently available. We propose a comprehensive and interactive pipeline to capture the multifaceted characteristics of differentially rhythmic biomarkers. Analysis outputs are accompanied by informative visualization and interactive exploration. The workflow is demonstrated in multiple case studies and is extensible to general omics applications.

AVAILABILITY AND IMPLEMENTATION

R package, Shiny app and source code are available in GitHub (https://github.com/DiffCircaPipeline) and Zenodo (https://doi.org/10.5281/zenodo.7507989).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Clinicopathological Features and Outcomes Comparing Patients With Invasive Ductal and Lobular Breast Cancer

BACKGROUND

There is increasing interest in better understanding the biology and clinical presentation of invasive lobular cancer (ILC), which is the most common special histological subtype of breast cancer. Limited large contemporary data sets are available allowing comparison of clinicopathologic features between ILC and invasive ductal cancer (IDC).

METHODS

The Great Lakes Breast Cancer Consortium was formed to compare clinical behavior of ILC (n = 3617) and IDC (n = 30 045) from 33 662 patients treated between 1990 and 2017 at 3 large clinical centers. We used Kaplan-Meier analysis, Cox proportional hazards modeling, and propensity score matching to evaluate treatment differences and outcomes. All statistical testing used 2-sided P values.

RESULTS

Compared with IDC, patients with ILC were more frequently diagnosed at later stages and with more lymph node involvement (corrected P < .001). Estrogen receptor-positive ILCs were of lower grade (grade 1 and 2: 90% in ILC vs 72% in IDC) but larger in size (T3 and 4: 14.3% in ILC vs 3.4% in IDC) (corrected P < .001), and since 1990, the mean ILC size detected at diagnosis increased yearly. Patients with estrogen receptor (ER)-positive ILC underwent statistically significantly more mastectomies compared with ER-positive IDC (57% vs 46%). Using Kaplan-Meier analysis, patients with ER-positive ILC had statistically significantly worse disease-free survival and overall survival than ER-positive IDC although 6 times more IDCs were classified as high risk by OncotypeDx Breast Recurrence Score assay.

CONCLUSIONS

This large, retrospective, collaborative analysis with 3 clinical centers identified meaningful differences in clinicopathological features between ILC and IDC, providing further evidence that these are 2 different entities requiring different clinical management.

Association of Molecular Senescence Markers in Late-Life Depression With Clinical Characteristics and Treatment Outcome

IMPORTANCE

Many older adults with depression do not experience remission with antidepressant treatment, and markers of cellular senescence in late-life depression (LLD) are associated with greater severity of depression, greater executive dysfunction, and higher medical illness burden. Since these clinical characteristics are associated with remission in LLD, molecular and cellular senescence abnormalities could be a possible biological mechanism underlying poor treatment response in this population.

OBJECTIVE

To examine whether the senescence-associated secretory phenotype (SASP) index was associated with the likelihood of remission from a depressive episode in older adults.

DESIGN, SETTING, AND PARTICIPANTS

A nonrandomized, open-label clinical trial was conducted between August 2009 and August 2014 in Pittsburgh, Pennsylvania; St Louis, Missouri; and Toronto, Ontario, Canada, with older adults in a current major depressive episode according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnostic criteria. Data from biomarker analyses were reported according to the clinical trial archived plasma samples run in March 2021. Data were analyzed from June to November 2021.

EXPOSURE

Venlafaxine extended release (dose ranging from 37.5 mg to 300 mg daily) for up to 12 weeks.

MAIN OUTCOMES AND MEASURES

The association between a composite biomarker-based index (SASP index) and treatment remission in older adults with major depression was measured using clinical data and blood samples.

RESULTS

There were 416 participants with a mean (SD) age of 60.02 (7.13) years; 64% (265 participants) were self-reported female, and the mean (SD) Montgomery-Asberg Depression Rating Scale score was 26.6 (5.7). Higher SASP index scores were independently associated with higher rates of nonremission, with an increase of 1 unit in the SASP index score increasing the odds of nonremission by 19% (adjusted odds ratio, 1.19; 95% CI, 1.05-1.35; P = .006). In contrast, no individual SASP factors were associated with remission in LLD.

CONCLUSIONS AND RELEVANCE

Using clinical data and blood samples from a nonrandomized clinical trial, the results of this study suggest that molecular and cellular senescence, as measured with the SASP index, is associated with worse treatment outcomes in LLD. Combining this index score reflecting interrelated biological processes with other molecular, clinical, and neuroimaging markers may be useful in evaluating antidepressant treatment outcomes. These findings inform a path forward for geroscience-guided interventions targeting senescence to improve remission rates in LLD.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00892047.

Immune landscape of human placental villi using single-cell analysis

Maintenance of a healthy pregnancy is reliant on a successful balance between the fetal and maternal immune systems. Although the maternal mechanisms responsible have been well studied, those used by the fetal immune system remain poorly understood. Using suspension mass cytometry and various imaging modalities, we report a complex immune system within the mid-gestation (17-23 weeks) human placental villi (PV). Consistent with recent reports in other fetal organs, T cells with memory phenotypes, although rare in abundance, were detected within the PV tissue and vasculature. Moreover, we determined that T cells isolated from PV samples may be more proliferative after T cell receptor stimulation than adult T cells at baseline. Collectively, we identified multiple subtypes of fetal immune cells within the PV and specifically highlight the enhanced proliferative capacity of fetal PV T cells.

Phase I trial combining chemokine-targeting with loco-regional chemo-immunotherapy for recurrent, platinum-sensitive ovarian cancer shows induction of CXCR3 ligands and markers of type 1 immunity

BACKGROUND

Increased prevalence of cytotoxic T lymphocytes (CTL) in the tumor microenvironment (TME) predicts positive outcomes in patients with epithelial ovarian cancer (EOC), while the regulatory Treg cells predict poor outcomes. Guided by the synergistic activity of TLR3 ligands, interferon-a (IFNa) and cyclooxygenase-2 (COX-2) blockers in selectively enhancing CTL-attractants but suppressing Treg-attractants, we tested a novel intraperitoneal (IP) chemo-immunotherapy combination, to assess its tolerability and TME-modulatory impact in patients with recurrent EOC.

METHODS

Twelve patients were enrolled in phase I portion of the trial NCT02432378, and treated with IP cisplatin, IP rintatolimod (dsRNA, TLR3 ligand) and oral celecoxib (COX-2 blocker). Patients in cohorts 2, 3 and 4 also received IP IFNa at 2, 6 and 18 million units (MU), respectively. Primary objectives were to evaluate safety, identify phase 2 recommended dose (P2RD) and characterize changes in the immune TME. Peritoneal resident cells and IP wash fluid were profiled via NanoString and Meso Scale Discovery (MSD) multiplex assay, respectively.

RESULTS

The P2RD of IFNa was 6 MU. Median progression-free and overall survival were 8.4 and 30 months, respectively. Longitudinal sampling of the peritoneal cavity via IP washes demonstrated local upregulation of interferon-stimulated genes (ISG), including CTL-attracting chemokines (CXCL-9, -10, -11), MHC I/II, perforin and granzymes. These changes were present two days post chemokine modulation and subsided within one week.

CONCLUSION

The chemokine-modulating IP-CITC is safe, tolerable, and associated with ISG changes that favor CTL chemoattraction and function. This combination (plus DC vaccine) will be tested in a phase II trial.

CD16+CD163+ monocytes traffic to sites of inflammation during necrotizing enterocolitis in premature infants

Necrotizing enterocolitis (NEC) is a severe gastrointestinal complication of prematurity. Using suspension and imaging mass cytometry coupled with single-cell RNA sequencing, we demonstrate severe inflammation in patients with NEC. NEC mucosa could be subtyped by an influx of three distinct neutrophil phenotypes (immature, newly emigrated, and aged). Furthermore, CD16⁺CD163⁺ monocytes/Mϕ, correlated with newly emigrated neutrophils, were specifically enriched in NEC mucosa, found adjacent to the blood vessels, and increased in circulation of infants with surgical NEC, suggesting trafficking from the periphery to areas of inflammation. NEC-specific monocytes/Mϕ transcribed inflammatory genes, including TREM1, IL1A, IL1B, and calprotectin, and neutrophil recruitment genes IL8, CXCL1, CXCL2, CXCL5 and had enrichment of gene sets in pathways involved in chemotaxis, migration, phagocytosis, and reactive oxygen species generation. In summary, we identify a novel subtype of inflammatory monocytes/Mϕ associated with NEC that should be further evaluated as a potential biomarker of surgical NEC and a target for the development of NEC-specific therapeutics.

Outcomes After Sentinel Lymph Node Biopsy and Radiotherapy in Older Women With Early-Stage, Estrogen Receptor-Positive Breast Cancer

IMPORTANCE

Overtreatment of early-stage breast cancer with favorable tumor biology in older patients may be harmful without affecting recurrence and survival. Guidelines that recommend deimplementation of sentinel lymph node biopsy (SLNB) (Choosing Wisely) and radiotherapy (RT) (National Comprehensive Cancer Network) have been published.

OBJECTIVE

To describe the use rates and association with disease recurrence of SLNB and RT in older women with breast cancer.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study obtained patient and clinical data from an integrated cancer registry and electronic health record of a single health care system in Pennsylvania. The cohort was composed of consecutive female patients 70 years or older who were diagnosed with early-stage, estrogen receptor-positive, ERBB2 (formerly HER2)-negative, clinically node-negative breast cancer from January 1, 2010, to December 31, 2018, who were treated at 15 community and academic hospitals within the health system.

EXPOSURES

Sentinel lymph node biopsy and adjuvant RT.

MAIN OUTCOMES AND MEASURES

Primary outcomes were 5-year locoregional recurrence-free survival (LRFS) rate and disease-free survival (DFS) rate after SLNB and after RT. Secondary outcomes included recurrence rate, subgroups that may benefit from SLNB or RT, and use rate of SLNB and RT over time. Propensity scores were used to create 2 cohorts to separately evaluate the association of SLNB and RT with recurrence outcomes. Cox proportional hazards regression model was used to estimate hazard ratios (HRs).

RESULTS

From 2010 to 2018, a total of 3361 women 70 years or older (median [interquartile range {IQR}] age, 77.0 [73.0-82.0] years) with estrogen receptor-positive, ERBB2-negative, clinically node-negative breast cancer were included in the study. Of these women, 2195 (65.3%) received SLNB and 1828 (54.4%) received adjuvant RT. Rates of SLNB steadily increased (1.0% per year), a trend that persisted after the 2016 adoption of the Choosing Wisely guideline. Rates of RT decreased slightly (3.4% per year). To examine patient outcomes and maximize follow-up time, the analysis was limited to cases from 2010 to 2014, identifying 2109 patients with a median (IQR) follow-up time of 4.1 (2.5-5.7) years. In the propensity score-matched cohorts, no association was found between SLNB and either LRFS (HR, 1.26; 95% CI, 0.37-4.30; P = .71) or DFS (HR, 1.92; 95% CI, 0.86-4.32; P = .11). In addition, RT was not associated with LRFS (HR, 0.33; 95% CI, 0.09-1.24; P = .10) or DFS (HR, 0.99; 95% CI, 0.46-2.10; P = .97). Subgroup analysis showed that stratification by tumor grade or comorbidity was not associated with LRFS or DFS. Low absolute rates of recurrence were observed when comparing the groups that received SLNB (3.5%) and those that did not (4.5%) as well as the groups that received RT (2.7%) and those that did not (5.5%).

CONCLUSIONS AND RELEVANCE

This study found that receipt of SLNB or RT was not associated with improved LRFS or DFS in older patients with ER-positive, clinically node-negative breast cancer. Despite limited follow-up time and wide 95% CIs, this study supports the continued deimplementation of both SLNB and RT in accordance with the Choosing Wisely and National Comprehensive Cancer Network guidelines.

Sex Differences in Molecular Rhythms in the Human Cortex

BACKGROUND

Diurnal rhythms in gene expression have been detected in the human brain. Previous studies found that males and females exhibit 24-hour rhythms in known circadian genes, with earlier peak expression in females. Whether there are sex differences in large-scale transcriptional rhythms in the cortex that align with observed sex differences in physiological and behavioral rhythms is currently unknown.

METHODS

Diurnal rhythmicity of gene expression was determined for males and females using RNA sequencing data from human postmortem dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC). Sex differences among rhythmic genes were determined using significance cutoffs, threshold-free analyses, and R² difference. Phase concordance was assessed across the DLPFC and ACC for males and females. Pathway and transcription factor analyses were also conducted on significantly rhythmic genes.

RESULTS

Canonical circadian genes had diurnal rhythms in both sexes with similar amplitude and phase. When analyses were expanded to the entire transcriptome, significant sex differences in transcriptional rhythms emerged. There were nearly twice as many rhythmic transcripts in the DLPFC in males and nearly 4 times as many rhythmic transcripts in the ACC in females. Results suggest a diurnal rhythm in synaptic transmission specific to the ACC in females (e.g., GABAergic [gamma-aminobutyric acidergic] and cholinergic neurotransmission). For males, there was phase concordance between the DLPFC and ACC, while phase asynchrony was found in females.

CONCLUSIONS

There are robust sex differences in molecular rhythms of genes in the DLPFC and ACC, providing potential mechanistic insights into how neurotransmission and synaptic function are modulated in a circadian-dependent and sex-specific manner.

Abstract PS11-02: Comprehensive comparative analysis of invasive ductal and lobular breast cancer cases in great lakes breast cancer consortium

Background: Invasive lobular breast cancer (ILC) is the second most common histologic subtype of breast cancer following invasive ductal cancer (IDC). ILC accounts for ~10-15% of all breast cancers (~26-40,000 cases annually in the US) and ranks as the 6th most common cancer in women in the US. While there is increasing recognition that ILC has distinct clinical, histologic, molecular, and biological characteristics compared to IDC, it remains understudied. There are very few large cohort analyses comparing clinic-pathological features of ILC, and therefore we performed a large multi-institutional retrospective cohort study. Methods: Investigators from UPMC Hillman Cancer Center, James Cancer Hospital/OSU, and Cleveland Clinic Taussig Cancer Institute/CWRU formed the Great Lakes Breast Cancer consortium, and worked with their respective cancer registries to collect comprehensive data on patients with IDC and ILC seen at their institutions between 1990 and 2017. Descriptive statistics were performed to compare clinic-pathological features, treatments, metastases sites, and co-morbidities. Survival rates were analyzed using the Kaplan-Meier (KM) method and compared using the Cox proportional hazards model. A total of N=38,175 records (N=15,792 for UPMC, N=13,040 for CCF, and N=9,343 for OSU) were included in the study. Results Among the N=38,175 records, we identified N=30,100 unique IDC (not otherwise specific, NOS) (89.3%) and N=3,618 unique ILC cases (10.7%). There were no significant differences between IDC and ILC with respect to laterality of the cancer (IDC: Left 51%, Right 49%; 0.2% Other vs ILC: Left 51%, Right 48%, Other 0.5%) and body mass index (IDC: 28.4 vs ILC: 28.2). In contrast, we observed significant difference with respect to age - patients with ILC were significantly older (61.2 vs 57.5 years; p&lt;0.0001), and there were significant differences in race (7.6% vs 9.2% African American patients in ILC vs IDC, respectively; p=0.004). Among ILC cases, there were fewer grade III tumors (11.4% vs 40.3% in IDC; p&lt;0.0001). ILCs were more frequently stage III (16.6% vs 8.0% in IDC) and stage IV (3.7% vs 2.4% in IDC) (p&lt;0.0001), and ILC were significantly larger than IDC (13.7% T3 vs 2.8% in IDC, p&lt;0.0001). There was also significantly more lymph node involvement in patients with ILC (N2: 5.3% vs 4.0%; N3: 4.6% vs 1.5%) (p&lt;0.0001). The ILC cohort had significantly fewer HER2+ cases (5.5% vs 18.1% in IDC) (p&lt;0.0001), and the proportion of patients with a high recurrence score as determined by 21 gene recurrence score was significantly lower in ILC compared to IDC (1.7% vs 10.4% in IDC; p&lt;0.0001). As expected, there was a significant enrichment of ER+ tumors in ILC (96.1% compared to IDC (76.6%) (p&lt;0.0001). Age, stage, grade, ER, Her2, and lymph node involvement remained significantly associated with histology in a logistic regression analysis. KM analysis showed significantly shortened disease-free (p=0.041) and overall survival (p&lt;0.0001) for patients with ER+ ILC (N=2,565) compared to ER+ IDC N=17,278). The estimated 5yr and 10yr DFS rates for patients with IDC are 0.94 and 0.89, and for ILC 0.94 and 0.86, confirming prior data of late recurrences in patients with ILC. Conclusions: In the largest cohort of patients with ILC made possible by multi-center collaborations we show that lobular histology carries distinct prognostic implications and that outcomes are significantly worse. This highlights the need for more ILC research and clinical trials for patients with ILC.

Citation Format: Steffi Oesterreich, Azadeh Nasrazadani, Jian Zou, Tiffany Onger, Matthew Wright, George Tseng, Bhuvana Ramaswamy, Adrian V Lee, Nicole Williams, Megan Kruse. Comprehensive comparative analysis of invasive ductal and lobular breast cancer cases in great lakes breast cancer consortium [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS11-02.

Abstract PS7-15: Mixed invasive ductal lobular carcinomas (mDLC) are clinically more similar to invasive lobular carcinoma (ILC) than to invasive ductal carcinoma (IDC)

Clinicopathologic differences between histological subtypes of invasive breast cancer are increasingly being appreciated. Mixed invasive ductal lobular carcinomas (mDLC) are thought to be composed of both ductal and lobular components, and we sought to determine whether mDLC clinically align more closely with invasive ductal (IDC) or invasive lobular (ILC) carcinoma subtypes or if they display intermediate or unique features dissimilar to either type. Key clinical and histologic parameters were compared between cohorts of patients with mDLC (N = 410), IDC (N = 12,979), and ILC (N = 1,569) identified from cancer registry data of a single large healthcare system.Patients with mDLC were older (59 years (49 - 68)) than those with IDC (57 years (48 - 67), p = 0.014)) and younger than those with ILC (61 years (51 - 70), p = 0.006). Tumor size in mDLC was larger (19mm (12 - 27)) than IDC (16mm (10 - 25), p &lt; 0.001) and smaller than ILC (20mm (12 - 35), p = 0.036). Similar to ILC, mDLC were more likely than IDC to be ER+ (92% vs 78% in IDC, p &lt; 0.001), and less likely to be HER2+ (8% vs 15% in IDC, p = 0.04). mDLC were also similar to ILC with regards to higher likelihood of diagnosis at higher stage (p &lt; 0.001), yet with lower grade (p &lt; 0.001), at diagnosis as compared to IDC. Heatmap visualization, as well as dimension reduction by multidimentional scaling (MDS), demonstrates significant overlap of the mDLC and ILC cohorts. Furthermore, an elastic net regression model based on clinicopathologic parameters predicts mDLC to align more closely with ILC than IDC. For patients for whom oncotype Dx scores were available, there was a trend for enrichment of low risk RS scores with rare high-risk RS tumors in mDLC, similar to ILC. With regards to response to neoadjuvant chemotherapy, a subset of the aforementioned cohorts who had received neoadjuvant chemotherapy, mDLC (N = 17), IDC (N = 180), and ILC (N = 57), were compared. Among patients in whom breast conserving surgery (BCS) was attempted, patients with IDC were more likely to have a successful BCS than those with ILC, with less margin positivity thereby avoiding re-excision and/or completion mastectomy (70% vs 32%, respectively; p = 0.003). Successful BCS was achieved with mDLC 56% of the time, although compared to IDC and ILC statistical significance was not reached. In a limited cohort receiving neoadjuvant endocrine therapy (mDLC (N = 7), IDC (N = 37), and ILC (N = 21)) no differences with regard to rates of successful BCS were identified. Pathologic complete response rates (pCR) were additionally evaluated, although small study numbers precluded our ability to perform statistical analysis.Collectively, the aforementioned findings support a higher concordance between mDLC and ILC as compared to IDC. It is feasible that the lobular component of mDLC tumors is predominant, leading to the observed histopathologic similarities noted between mDC and ILC cohorts. We are planning meta-analyses including data from other institutions, and molecular studies to further understand complexities of mDLC.The authors acknowledge grant support from ASCO Conquer Cancer (to NW and AN).

Citation Format: Azadeh Nasrazadani, Yujia Li, Yusi Fang, Osama Shah, Jennifer M Atkinson, Joanna S Lee, Priscilla F McAuliffe, Adrian V Lee, George Tseng, Peter Lucas, Steffi Oesterreich, Norman Wolmark. Mixed invasive ductal lobular carcinomas (mDLC) are clinically more similar to invasive lobular carcinoma (ILC) than to invasive ductal carcinoma (IDC) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-15.

Abstract PS1-10: Outcomes after sentinel lymph node biopsy and radiation therapy in women over 70 years old with ER+, HER2-, clinically node negative breast cancer

Overtreatment of early-stage breast cancer with favorable tumor biology in elderly patients can result in higher rates of complications and morbidities without impacting survival. Guidelines directed towards deimplementation of sentinel lymph node biopsy (SLNB) (Choosing Wisely) and radiation therapy (RT) (National Comprehensive Cancer Network) have been recommended. We sought to describe rates and impact on disease recurrence and survival of SLNB and RT in elderly patients with early breast cancer. Patient data were obtained from the cancer registry and electronic health record from University of Pittsburgh Medical Center, multicenter, single health care system. Consecutive female patients aged ≥ 70 with ER+, HER2- clinically node-negative breast cancer within a health care system from 2010 to 2018 were identified. Rates and patient characteristics associated with receipt of SLNB and RT, as well as local recurrence free survival (LRFS) and disease-free survival (DFS) were compared for patients that were diagnosed between 2010 and 2014 to allow for adequate follow up time. Cox proportional hazards regression was used to estimate hazard ratios (HRs) of mortality. Among 3,361 identified women, 2,195 (65.3%) received SLNB and 1,828 (54.4%) received RT. Rates of SLNB steadily increased (1.0% per year); this trend persisted in 2017 and 2018, even after the Society of Surgical Oncology adopted the Choosing Wisely Guidelines in 2016. During the same time period, rates of RT declined (3.4% per year). To examine outcomes, we limited the analysis to 2109 cases from 2010-2014; median (IQR) follow up time was 4.1 (2.5-5.7) years. Median (IQR) age was 77 (73-82) years. 1373 (65.1%) received SLNB and 1,219 (57.8%) received RT. Patients receiving SLNB were younger (P &lt; 0.001) with smaller (P &lt; 0.0001) and lower stage (P &lt; 0.0001) tumors. They had fewer comorbidities (P &lt; 0.001), longer follow-up times (P &lt; 0.001), were less likely on Medicaid/Medicare (P = 0.0091), and were more often seen at an academic center (P &lt; 0.0001). There was no difference in grade between those that did and did not receive SLNB (P = 0.31) and those that did and did not receive RT (P = 0.13). Multivariate cox proportional hazard analysis showed no effect of SLNB on LRFS (HR = 1.17, 95% CI 0.29-4.75, P = 0.83) or DFS (HR = 0.90, 95% CI 0.44-1.83, P = 0.77). Log rank test showed no difference in 5-year LRFS (P = 0.78) between patients who received (98.5%, 95% CI 97.7%-99.7%) and did not receive (98.1%, 95% CI 96.7%-99.5%) SLNB, but an increase was seen with 5-year DFS (P = 0.023), with 96.2% (95% CI 95.0%-97.4%) of patients disease-free among those who did receive SLNB vs. 93.0% (95% CI 90.6%-95.4%) with no SLNB. Multivariate cox proportional hazard analysis showed that RT was associated with improved LRFS (HR = 0.13, 95% CI 0.03-0.51, P &lt; 0.01) and DFS (HR = 0.32, 95% CI 0.15-0.68, P &lt; 0.01). Log rank test showed a difference in 5-year LRFS (P &lt; 0.0001) for those who received RT (99.4%, 95% CI 98.8%-100%) against those who did not (96.5%, 95% CI 95.0%-98.1%), and a similar difference in 5-year DFS (P &lt; 0.0001) in patients who did (97.0%, 95% CI 95.8%-98.1%) and did not (92.4%, 95% CI 90.2%-94.7%) receive RT. Lower age (OR = 0.89, 95% CI 0.87-0.92) and comorbidities (OR = 0.79, 95% CI 0.66-0.94) were associated with receipt of SLNB, while only age (OR = 0.91, 95% CI 0.88-0.94) was associated with receipt of RT.

We conclude that receipt of SLNB has no impact upon DFS or LRFS. This data supports deimplementation of SLNB for this patient population. Receipt of RT is important for controlling locoregional recurrence, supporting use of RT in this patient cohort.

Citation Format: Priscilla F McAuliffe, Neil M Carleton, Jian Zou, Yusi Fang, Stephen E Koscumb, Osama Shah, Fangyuan Chen, Sushil Beriwal, Emilia J Diego, Adam M Brufsky, Steffi Oesterreich, Steve D Shapiro, Robert Ferris, Leisha A Emens, George Tseng, Oscar C Marroquin, Adrian V Lee. Outcomes after sentinel lymph node biopsy and radiation therapy in women over 70 years old with ER+, HER2-, clinically node negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS1-10.

In utero human intestine harbors unique metabolome, including bacterial metabolites

Symbiotic microbial colonization through the establishment of the intestinal microbiome is critical to many intestinal functions, including nutrient metabolism, intestinal barrier integrity, and immune regulation. Recent studies suggest that education of intestinal immunity may be ongoing in utero. However, the drivers of this process are unknown. The microbiome and its byproducts are one potential source. Whether a fetal intestinal microbiome exists is controversial, and whether microbially derived metabolites are present in utero is unknown. Here, we aimed to determine whether bacterial DNA and microbially derived metabolites can be detected in second trimester human intestinal samples. Although we were unable to amplify bacterial DNA from fetal intestines, we report a fetal metabolomic intestinal profile with an abundance of bacterially derived and host-derived metabolites commonly produced in response to microbiota. Though we did not directly assess their source and function, we hypothesize that these microbial-associated metabolites either come from the maternal microbiome and are vertically transmitted to the fetus to prime the fetal immune system and prepare the gastrointestinal tract for postnatal microbial encounters or are produced locally by bacteria that were below our detection threshold.

A unique human fetal metabolomic intestinal profile is reported with an abundance of bacterially derived metabolites.

Single-Cell Analyses of Colon and Blood Reveal Distinct Immune Cell Signatures of Ulcerative Colitis and Crohn's Disease

BACKGROUND & AIMS

Studies are needed to determine the mechanisms of mucosal dysregulation in patients with inflammatory bowel diseases (IBDs) and differences in inflammatory responses of patients with ulcerative colitis (UC) vs Crohn's disease (CD). We used mass cytometry (CyTOF) to characterize and compare immune cell populations in the mucosa and blood from patients with IBD and without IBD (controls) at single-cell resolution.

METHODS

We performed CyTOF analysis of colonic mucosa samples (n = 87) and peripheral blood mononuclear cells (n = 85) from patients with active or inactive UC or CD and controls. We also performed single-cell RNA sequencing, flow cytometry, and RNA in situ hybridization analyses to validate key findings. We used random forest modeling to identify differences in signatures across subject groups.

RESULTS

Compared with controls, colonic mucosa samples from patients with IBD had increased abundances of HLA-DR+CD38+ T cells, including T-regulatory cells that produce inflammatory cytokines; CXCR3+ plasmablasts; and IL1B+ macrophages and monocytes. Colonic mucosa samples from patients with UC were characterized by expansion of IL17A+ CD161+ effector memory T cells and IL17A+ T-regulatory cells; expansion of HLA-DR+CD56+ granulocytes; and reductions in type 3 innate lymphoid cells. Mucosal samples from patients with active CD were characterized by IL1B+HLA-DR+CD38+ T cells, IL1B+TNF+IFNG⁺ naïve B cells, IL1B+ dendritic cells (DCs), and IL1B+ plasmacytoid DCs. Peripheral blood mononuclear cells from patients with active CD differed from those of active UC in that the peripheral blood mononuclear cells from patients with CD had increased IL1B+ T-regulatory cells, IL1B+ DCs and IL1B+ plasmacytoid DCs, IL1B+ monocytes, and fewer group 1 innate lymphoid cells. Random forest modeling differentiated active UC from active CD in colonic mucosa and blood samples; top discriminating features included many of the cellular populations identified above.

CONCLUSIONS

We used single-cell technologies to identify immune cell populations specific to mucosa and blood samples from patients with active or inactive CD and UC and controls. This information might be used to develop therapies that target specific cell populations in patients with different types of IBD.

Patient treatment and outcome after breast cancer orbital and periorbital metastases: a comprehensive case series including analysis of lobular versus ductal tumor histology

BACKGROUND

Breast cancer is the most common malignancy to spread to the orbit and periorbit, and the invasive lobular carcinoma (ILC) histologic subtype of breast cancer has been reported to form these ophthalmic metastases (OM) more frequently than invasive ductal carcinomas (IDC). We herein report our single academic institution experience with breast cancer OM with respect to anatomical presentation, histology (lobular vs. ductal), treatment, and survival.

METHODS

We employed the natural language processing platform, TIES (Text Information Extraction System), to search 2.3 million de-identified patient pathology and radiology records at our institution in order to identify patients with OM secondary to breast cancer. We then compared the resultant cohort, the "OM cohort," to two other representative metastatic breast cancer patient (MBC) databases from our institution. Histological analysis of selected patients was performed.

RESULTS

Our TIES search and manual refinement ultimately identified 28 patients who were diagnosed with breast cancer between 1995 and 2016 that subsequently developed OM. Median age at diagnosis was 54 (range 28-77) years of age. ER, PR, and HER2 status from the 28 patients with OM did not differ from other patients with MBC from our institution. The relative proportion of patients with ILC was significantly higher in the OM cohort (32.1%) than in other MBC patients in our institution (11.3%, p = 0.007). Median time to first OM in the OM cohort was 46.7 months, and OM were the second most frequent first metastases after bony metastases. After diagnosis of the first distant metastasis of any kind, median survival of patients with ILC (21.4 months) was significantly shorter than that of patients with IDC (55.3 months, p = 0.03). Nine patients developed bilateral OM. We observed a significant co-occurrence of OM and central nervous system metastases (p = 0.0053). The histological analysis revealed an interesting case in which the primary tumor was of a mixed ILC/IDC subtype, while only ILC was present in the OM.

CONCLUSIONS

OM from breast cancer are illustrative of the difference in metastatic behavior of ILC versus IDC and should be considered when treating patients with ILC, especially in those with complaints of visual acuity changes.

Metastatic behavior of mixed invasive ductal lobular carcinoma (mIDC/ILC)

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Background: Mixed invasive ductal lobular carcinoma (mIDC/ILC) is a poorly described subtype of invasive breast cancer, characterized by its composition of both ductal and lobular histopathology. It is unclear if individual or both components drive metastasis. Literature is sparse regarding sites of metastatic spread of this elusive subtype of invasive breast cancer. Methods: Cohorts of patients with mIDC/ILC, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) were identified from the UPMC Network Cancer Registry. Among these, 46 patients with mIDC/ILC, 1,131 patients with IDC, and 145 patients with ILC seen at UPMC Magee Women’s Hospital from 1990 – 2017 were found to have developed distant metastasis during the course of their disease. The metastatic pattern of spread was compared between the cohorts. Formalin-fixed, paraffin-embedded patient samples from the metastatic sites of a portion of the mIDC/ILC cases (n = 19) was acquired and evaluated by H&E staining. Results: Patients with IDC were more likely than patients with ILC to have metastasis to the liver (p = 0.001) and lung (p < 0.001), and less likely to have metastasis to the peritoneum (p < 0.001). Patients with mIDC/ILC were more likely than patients with IDC to have peritoneal metastasis (p = 0.01), similar to patients with ILC. Compared to patients with ILC, patients with mIDC/ILC were more likely to have liver metastasis (p = 0.001), similar to patients with IDC. Evaluation of the metastatic lesions originating from mIDC/ILC displayed a spectrum of histopathology including mixed histology (n = 3), pure IDC (n = 3), pure ILC (n = 5), and indeterminate lesions with features of both IDC and ILC (n = 6). Two cases were uninterpretable due to significant crush artifact. Metastatic mIDC/ILC lesions with retained mIDC/ILC histology were found in vertebral, pleural, and skin tissues. Metastatic mIDC/ILC lesions with IDC histology were found in a cerebellar, liver, and chest wall lesion; whereas, those with ILC histology were found in bowel, omental fat, ovary, bone, and sacrum. Indeterminate histology metastatic lesions were found at liver, chest wall, cerebellar, and bone sites. Conclusions: mIDC/ILC metastasizes to a range of distant sites with a higher preference to the liver and peritoneum as compared to ILC and IDC, respectively. Metastatic lesions arising from mIDC/ILC tumors showed a spectrum of histologies, including mIDC/ILC, IDC, ILC and indeterminate lesions with features of both IDC and ILC. Ongoing genomics studies will provide further insight into development of metastases from mIDC/ILC tumors.

Endocrine biomarkers in low-grade serous ovarian cancers (LGSC) and serous ovarian tumors of low malignant potential (LMP)

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Background: LGSC and serous ovarian LMP tumors are rare entities along a disease continuum. Because they are relatively chemotherapy resistant, there is interest in targeted treatment, including endocrine therapy. In studies of endocrine agents for treatment of recurrent ovarian cancer, tumor estrogen receptor (ER) status alone does not effectively predict outcomes. The objective of this study is to utilize protein and gene expression from ER and downstream targets to identify signaling components that will act as prognostic and predictive biomarkers. Methods: A single institution tumor registry was queried for patients with LGSC or serous LMP tumors between 1993-2016. Formalin-fixed, paraffin embedded (FFPE) tissue was obtained. Clinicopathologic data was collected. Immunohistochemistry (IHC) was performed and scored as dichotomous (+/-) and continuous (H-score). NanoString nCounter platform was used for gene expression of a predesigned endocrine biomarker panel. Wilcoxon Rank Sum was used to compare mRNA and protein expression. Survival analyses were performed using Cox proportional hazard (PH) method with elastic net to fit the prediction model for the gene panel. Results: Tissue was analyzed from 23 LGSC, 71 serous LMP tumors, and 2 recurrences. At diagnosis, 86% of patients with LMP tumors had stage I disease vs 78% of patients with LGSC had stage III/IV disease. There were 7 (10%) LMP and 13 (56.5%) LGSC recurrences. Median initial PFS was 76 and 37 months and median OS was 88 and 82 months for LMP and LGSC, respectively. Fourteen received endocrine therapy; nine for treatment of recurrent LGSC. Median therapy was 21 months, with 3 complete responses, 2 partial responses and 1 stable disease. All tumors were ER+ (median H-score 210) and 89% were PR+ (median H-score 130). ER H-scores and ESR1 expression levels were not significantly different between LGSC and LMP tumors (p = 0.1942, p = 0.0893). PR H-scores were higher in LMP tumors (p < 0.00001) but PGR expression was not significantly different (p = 0.6581). In the Cox PH analysis, ER H-score was a significant predictor of both PFS and OS (p < 0.001, p = 0.004). The Cox model identified independent sets of gene expression associated with PFS and OS in both the LGSC and LMP cohorts (c-indices 0.679, 0.570, 0.626, 0.689). Conclusions: Endocrine therapy is an active area of interest in the treatment of ovarian neoplasms. ER H-score and gene expression of downstream ER targets could improve upon the use of hormone receptors to determine risk of recurrence and guide use of adjuvant endocrine therapy.

Recent Advances in Computer-Assisted Algorithms for Cell Subtype Identification of Cytometry Data

The progress in the field of high-dimensional cytometry has greatly increased the number of markers that can be simultaneously analyzed producing datasets with large numbers of parameters. Traditional biaxial manual gating might not be optimal for such datasets. To overcome this, a large number of automated tools have been developed to aid with cellular clustering of multi-dimensional datasets. Here were review two large categories of such tools; unsupervised and supervised clustering tools. After a thorough review of the popularity and use of each of the available unsupervised clustering tools, we focus on the top six tools to discuss their advantages and limitations. Furthermore, we employ a publicly available dataset to directly compare the usability, speed, and relative effectiveness of the available unsupervised and supervised tools. Finally, we discuss the current challenges for existing methods and future direction for the new generation of cell type identification approaches.

Quantitative Proteomics for Monitoring Renal Transplant Injury

PURPOSE

This study is aimed at developing a molecular diagnostics platform to enhance the interpretation of renal allograft biopsies using quantitative proteomic profiling of formalin-fixed and paraffin-embedded (FFPE) specimens.

EXPERIMENTAL DESIGN

A quantitative proteomics platform composed of 1) an optimized FFPE protein sample preparation method, 2) a tandem mass tag TMT10-plex-based proteomic workflow, and 3) a systematic statistical analysis pipeline to reveal differentially expressed proteins has been developed. This platform is then tested on a small sample set (five samples per phenotype) to reveal proteomic signatures that can differentiate T-cell mediated rejection (TCMR) and polyomavirus BK nephropathy (BKPyVN) from healthy functionally stable kidney tissue (STA).

RESULTS

Among 2798 quantified proteins, the expression levels of 740 BKPyVN and 638 TCMR associated proteins are significantly changed compared to STA specimens. Principal component analysis demonstrated good segregation of all three phenotypes investigated. Protein detection and quantitation are highly reproducible: replicate comparative analyses demonstrated 71-84% overlap of detected proteins, and the coefficient of variation for protein measurements is <15% in triplicate liquid chromatography-tandem mass spectrometry runs.

CONCLUSIONS AND CLINICAL RELEVANCE

Quantitative proteomics can be applied to archived FFPE specimens to differentiate different causes of renal allograft injury.

Biomarkers that differentiate false positive urinalyses from true urinary tract infection

BACKGROUND

The specificity of the leukocyte esterase test (87%) is suboptimal. The objective of this study was to identify more specific screening tests that could reduce the number of children who unnecessarily receive antimicrobials to treat a presumed urinary tract infection (UTI).

METHODS

Prospective cross-sectional study to compare inflammatory proteins in blood and urine samples collected at the time of a presumptive diagnosis of UTI. We also evaluated serum RNA expression in a subset.

RESULTS

We enrolled 200 children; of these, 89 were later demonstrated not to have a UTI based on the results of the urine culture obtained. Urinary proteins that best discriminated between children with UTI and no UTI were involved in T cell response proliferation (IL-9, IL-2), chemoattractants (CXCL12, CXCL1, CXCL8), the cytokine/interferon pathway (IL-13, IL-2, INFγ), or involved in innate immunity (NGAL). The predictive power (as measured by the area under the curve) of a combination of four urinary markers (IL-2, IL-9, IL-8, and NGAL) was 0.94. Genes in the pathways related to inflammation were also upregulated in serum of children with UTI.

CONCLUSIONS

Urinary proteins involved in the inflammatory response may be useful in identifying children with false positive results with current screening tests for UTI; this may reduce unnecessary treatment.

Diurnal rhythms in gene expression in the prefrontal cortex in schizophrenia

Schizophrenia is associated with disrupted cognitive control and sleep-wake cycles. Here we identify diurnal rhythms in gene expression in the human dorsolateral prefrontal cortex (dlPFC), in schizophrenia and control subjects. We find significant diurnal (24 h) rhythms in control subjects, however, most of these transcripts are not rhythmic in subjects with schizophrenia. Instead, subjects with schizophrenia have a different set of rhythmic transcripts. The top pathways identified in transcripts rhythmic only in subjects with schizophrenia are associated with mitochondrial function. Importantly, these rhythms drive differential expression patterns of these and several other genes that have long been implicated in schizophrenia (including BDNF and GABAergic-related transcripts). Indeed, differential expression of these transcripts is only seen in subjects that died during the night, with no change in subjects that died during the day. These data provide insights into a potential mechanism that underlies changes in gene expression in the dlPFC with schizophrenia.

Sleep disturbance is common in psychiatric disease, and this may contribute to altered circadian rhythm in gene expression. Here the authors show that rhythms in gene expression in the dorsolateral prefrontal cortex in schizophrenia are different to that seen in healthy controls.

P-value evaluation, variability index and biomarker categorization for adaptively weighted Fisher's meta-analysis method in omics applications

MOTIVATION

Meta-analysis methods have been widely used to combine results from multiple clinical or genomic studies to increase statistical powers and ensure robust and accurate conclusions. The adaptively weighted Fisher's method (AW-Fisher), initially developed for omics applications but applicable for general meta-analysis, is an effective approach to combine P-values from K independent studies and to provide better biological interpretability by characterizing which studies contribute to the meta-analysis. Currently, AW-Fisher suffers from the lack of fast P-value computation and variability estimate of AW weights. When the number of studies K is large, the 3K - 1 possible differential expression pattern categories generated by AW-Fisher can become intractable. In this paper, we develop an importance sampling scheme with spline interpolation to increase the accuracy and speed of the P-value calculation. We also apply bootstrapping to construct a variability index for the AW-Fisher weight estimator and a co-membership matrix to categorize (cluster) differentially expressed genes based on their meta-patterns for intuitive biological investigations.

RESULTS

The superior performance of the proposed methods is shown in simulations as well as two real omics meta-analysis applications to demonstrate its insightful biological findings.

AVAILABILITY AND IMPLEMENTATION

An R package AWFisher (calling C++) is available at Bioconductor and GitHub (https://github.com/Caleb-Huo/AWFisher), and all datasets and programing codes for this paper are available in the Supplementary Material.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Host and Bacterial Markers that Differ in Children with Cystitis and Pyelonephritis

OBJECTIVE

To determine whether treatment for urinary tract infections in children could be individualized using biomarkers for acute pyelonephritis.

STUDY DESIGN

We enrolled 61 children with febrile urinary tract infections, collected blood and urine samples, and performed a renal scan within 2 weeks of diagnosis to identify those with pyelonephritis. Renal scans were interpreted centrally by 2 experts. We measured inflammatory proteins in blood and urine using LUMINEX or an enzyme-linked immunosorbent assay. We evaluated serum RNA expression using RNA sequencing in a subset of children. Finally, for children with Escherichia coli isolated from urine cultures, we performed a polymerase chain reaction for 4 previously identified virulence genes.

RESULTS

Urinary markers that best differentiated pyelonephritis from cystitis included chemokine (C-X-C motif) ligand (CXCL)1, CXCL9, CXCL12, C-C motif chemokine ligand 2, INF γ, and IL-15. Serum procalcitonin was the best serum marker for pyelonephritis. Genes in the interferon-γ pathway were upregulated in serum of children with pyelonephritis. The presence of E coli virulence genes did not correlate with pyelonephritis.

CONCLUSIONS

Immune response to pyelonephritis and cystitis differs quantitatively and qualitatively; this may be useful in differentiating these 2 conditions.

MethylSeqDesign: a framework for Methyl-Seq genome-wide power calculation and study design issues

Bisulfite DNA methylation sequencing (Methyl-Seq) becomes one of the most important technologies to study methylation level difference at a genome-wide scale. Due to the complexity and large scale of methyl-Seq data, power calculation and study design method have not been developed. Here, we propose a "MethylSeqDesign" framework for power calculation and study design of Methyl-Seq experiments by utilizing information from pilot data. Differential methylation analysis is based on a beta-binomial model. Power calculation is achieved using mixture model fitting of p-values from pilot data and a parametric bootstrap procedure. To circumvent the issue of existing tens of millions of methylation sites, we focus on the inference of pre-specified targeted regions. The performance of the method was evaluated with simulations. Two real examples are analyzed to illustrate our method. An R package "MethylSeqDesign" to implement this method is publicly available.

Mixed invasive ductal-lobular carcinoma: Clinicopathological characterization and clinical outcomes

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Background: Mixed Invasive Ductal-Lobular Carcinoma (IDC-L) is a histological subtype of invasive breast carcinoma comprised of both ductal and lobular morphologies. There is limited information on the relative proportions of the individual components in IDC-L and on outcomes compared to invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC). Methods: Clinical information was abstracted from 16,308 patients with invasive breast cancer seen at UPMC Magee Women’s Hospital from 1990-2017 using the UPMC Network Cancer Registry. A systematic chart review was performed on a subset of patients annotated with IDC-L (n=806); however, a thorough review of pathology reports led to the exclusion of all but 408 patients for further analysis, due to the lack of a standardized definition of IDC-L. Of the 408 cases, 92% were estrogen receptor (ER)+. Survival of patients with ER+ IDC-L (n=376) was compared to ER+ IDC (n=9,716) and ER+ ILC (1,465). For a subset of IDC-L cases (n=54), distributions of individual subtype components were abstracted from pathology reports. Results: IDC-L made up 2.5% of the total cases (408/16,308). IDC-L tumors were on average 31% ductal and 69% lobular (p =0.001). Survival analysis showed worse disease free survival (DFS) (p=0.05) and overall survival (OS) (p=0.002) in patients with ER+ ILC compared to ER+ IDC, with ER+ IDC-L patients showing a median OS superior to ILC yet inferior to IDC counterparts (ns). Conclusions: Identification of patients with IDC-L through cancer registry protocols representative of standard practices by national cancer registries revealed a lack of a standardized definition of mixed IDC-L. Reliance on accuracy of these diagnoses calls in to question the reliability of prior clinico-pathologic analyses reported on this topic. DFS and OS of IDC-L patients falls between that of IDC and ILC patients while ILC patients showed significantly worse outcome. The predominant distribution of lobular morphology in IDC-L tumors suggests this subtype may have additional characteristics similar to lobular rather than ductal carcinomas. Comprehensive clinical and molecular characterization of a carefully identified IDC-L cohort is underway.

BAYESIAN LATENT HIERARCHICAL MODEL FOR TRANSCRIPTOMIC META-ANALYSIS TO DETECT BIOMARKERS WITH CLUSTERED META-PATTERNS OF DIFFERENTIAL EXPRESSION SIGNALS

Due to the rapid development of high-throughput experimental techniques and fast-dropping prices, many transcriptomic datasets have been generated and accumulated in the public domain. Meta-analysis combining multiple transcriptomic studies can increase the statistical power to detect disease-related biomarkers. In this paper, we introduce a Bayesian latent hierarchical model to perform transcriptomic meta-analysis. This method is capable of detecting genes that are differentially expressed (DE) in only a subset of the combined studies, and the latent variables help quantify homogeneous and heterogeneous differential expression signals across studies. A tight clustering algorithm is applied to detected biomarkers to capture differential meta-patterns that are informative to guide further biological investigation. Simulations and three examples, including a microarray dataset from metabolism-related knockout mice, an RNA-seq dataset from HIV transgenic rats, and cross-platform datasets from human breast cancer, are used to demonstrate the performance of the proposed method.

Identification of recurrent fusion genes across multiple cancer types

Chromosome changes are one of the hallmarks of human malignancies. Chromosomal rearrangement is frequent in human cancers. One of the consequences of chromosomal rearrangement is gene fusions in the cancer genome. We have previously identified a panel of fusion genes in aggressive prostate cancers. In this study, we showed that 6 of these fusion genes are present in 7 different types of human malignancies with variable frequencies. Among them, the CCNH-C5orf30 and TRMT11-GRIK2 gene fusions were found in breast cancer, colon cancer, non-small cell lung cancer, esophageal adenocarcinoma, glioblastoma multiforme, ovarian cancer and liver cancer, with frequencies ranging from 12.9% to 85%. In contrast, four other gene fusions (mTOR-TP53BP1, TMEM135-CCDC67, KDM4-AC011523.2 and LRRC59-FLJ60017) are less frequent. Both TRMT11-GRIK2 and CCNH-C5orf30 are also frequently present in lymph node metastatic cancer samples from the breast, colon and ovary. Thus, detecting these fusion transcripts may have significant biological and clinical implications in cancer patient management.

Cisplatin-induced immune modulation in ovarian cancer mouse models with distinct inflammation profiles

The backbone of ovarian cancer treatment is platinum-based chemotherapy and aggressive surgical debulking. New therapeutic approaches using immunotherapy via immune checkpoint blockade, which have demonstrated clinical efficacy in other tumor types, have been less promising in ovarian cancer. To increase their clinical efficacy, checkpoint inhibitors are now being tested in clinical trials in combination with chemotherapy. Here, we evaluated the impact of cisplatin on tumor immunogenicity and its in vivo roles when used alone or in combination with anti-PD-L1, in two novel murine ovarian cancer cell models. The 2F8 and its platinum-resistant derivative 2F8cis model, display distinct inflammatory profiles and chemotherapy sensitivities, and mirror the primary and recurrent human disease, respectively. Acute and chronic exposure to cisplatin enhances tumor immunogenicity by increasing calreticulin, MHC class I, antigen presentation and T-cell infiltration. Cisplatin also upregulates PD-L1 expression in vitro and in vivo, demonstrating a dual, paradoxical immune modulatory effect and supporting the rationale for combination with immune checkpoint blockade. One of the pathways activated by cisplatin treatment is the cGAS/STING pathway. Chronic cisplatin treatment led to upregulation of cGAS and STING proteins in 2F8cis compared to parental 2F8 cells, while acute exposure to cisplatin further increases cGAS and STING levels in both 2F8 and 2F8cis cells. Overexpression of cGAS/STING modifies tumor immunogenicity by upregulating PD-L1, MHC I and calreticulin in tumor cells. Anti-PD-L1 alone in a platinum-sensitive model or with cisplatin in a platinum-resistant model increases survival. These studies have high translational potential in ovarian cancer.

Diagnosis of T-cell-mediated kidney rejection in formalin-fixed, paraffin-embedded tissues using RNA-Seq-based machine learning algorithms

Molecular diagnosis is being increasingly used in transplant pathology to render more objective and quantitative determinations that also provide mechanistic and prognostic insights. This study performed RNA-Seq on biopsies from kidneys with stable function (STA) and biopsies with classical findings of T-cell-mediated rejection (TCMR). Machine learning tools were used to develop prediction models for distinguishing TCMR and STA samples using the top genes identified by DSeq2. The prediction models were tested on 703 biopsies with Affymetrix chip gene expression profiles available in the public domain. Linear discriminant analysis predicted TCMR in 55 of 67 biopsies labeled TCMR, and 65 of 105 biopsies designated as antibody-mediated rejection. The random forest and support vector machine models showed comparable performance. These data illustrate the feasibility of using RNA-Seq for molecular diagnosis of TCMR in formalin-fixed tissue. Application of the derived diagnostic algorithms to publicly available data sets demonstrates frequent coexistence of TCMR in biopsies designated as antibody-mediated rejection. This underrecognition of TCMR in renal allograft biopsies has significant implications with respect to patient care.

Gene Expression Signatures Can Aid Diagnosis of Sexually Transmitted Infection-Induced Endometritis in Women

Sexually transmitted infection (STI) of the upper reproductive tract can result in inflammation and infertility. A biomarker of STI-induced upper tract inflammation would be significant as many women are asymptomatic and delayed treatment increases risk of sequelae. Blood mRNA from 111 women from three cohorts was profiled using microarray. Unsupervised analysis revealed a transcriptional profile that distinguished 9 cases of STI-induced endometritis from 18 with cervical STI or uninfected controls. Using a hybrid feature selection algorithm we identified 21 genes that yielded maximal classification accuracy within our training dataset. Predictive accuracy was evaluated using an independent testing dataset of 5 cases and 10 controls. Sensitivity was evaluated in a separate test set of 12 women with asymptomatic STI-induced endometritis in whom cervical burden was determined by PCR; and specificity in an additional test set of 15 uninfected women with pelvic pain due to unknown cause. Disease module preservation was assessed in 42 women with a clinical diagnosis of pelvic inflammatory disease (PID). We also tested the ability of the biomarker to discriminate STI-induced endometritis from other diseases. The biomarker was 86.7% (13/15) accurate in correctly distinguishing cases from controls in the testing dataset. Sensitivity was 83.3% (5/6) in women with high cervical Chlamydia trachomatis burden and asymptomatic endometritis, but 0% (0/6) in women with low burden. Specificity in patients with non-STI-induced pelvic pain was 86.7% (13/15). Disease modules were preserved in all 8 biomarker predicted cases. The 21-gene biomarker was highly discriminatory for systemic infections, lupus, and appendicitis, but wrongly predicted tuberculosis as STI-induced endometritis in 52.4%. A 21-gene biomarker can identify asymptomatic women with STI-induced endometritis that places them at risk for chronic disease development and discriminate STI-induced endometritis from non-STI pelvic pain and other diseases.

Abstract B33: Neoepitope peptide vaccines and immune checkpoint blockade in a new preclinical ovarian cancer model

Objective: Therapeutic success currently seen with immune checkpoint blockade (ICB) occurs primarily in immunogenic tumors and can be partly explained by the high rates of non-synonymous genetic mutations (single nucleotide variants, SNV) in tumor cells, leading to neoepitope presentations and robust T-cell infiltration. Despite showing mutations in fewer genes (most frequently TP53), high-grade serous ovarian cancer (HGSOC) displays signs of T-cell inflammation and responds, albeit modestly, to ICB. We focus on immune therapy tailored to the genomic characteristics of the tumor, especially to structural aberrations (SAs), like gene fusions. Our hypothesis is that SAs that are expressed as proteins are antigenic and immunogenic, and represent a source of neoantigens for combination immunotherapies that can overcome locoregional immune suppression. DNA structural aberrations can result in intergenic fusions and intragenic rearrangements, such as exon duplications (dup) and deletions (del). Here we focus on identifying gene fusion and exon dup/del-derived neoepitopes based on RNA-seq data for a combination of retrospective and prospective sample collections. Our hypothesis is that these gene rearrangements resulting from SVs may contribute to the immunogenicity and antigenicity of HGSOC.

Methods: FusionCatcher was used to evaluate RNA sequencing data for in-frame gene fusions events in banked human HGSOC. HLAminer was used to determine individual haplotypes. Upon detection of fusion events (validated via PCR) we identified the MHC-I and MHC-II restricted peptides with predicted high or intermediate (IC50&lt;500nM) binding affinity. The peptides (with sequences across the fusion point) were synthesized and pulsed onto HLA-matched PBMCs, for in vitro T cells stimulation assay. Following antigen priming and in vitro restimulation, IFNγ production by T cells was measured by ELISA. The efficacy of SA-derived neoepitopes was tested in vivo with two new preclinical mouse models based on MKP-Lung and MKP-Liver cells ovarian cancer cell lines. RNA-seq data of their complete mutanome were used to generate neoepitopes. RNA from normal mouse OSE isolated from healthy mice was used as reference for mutation calling. For vaccine generation, peptides were pulsed onto dendritic cells matured into Th1-inducing phenotype (DC1). Mice were treated with Rat IgG, anti-PDL1, or vaccine + anti PD-L1. Objective response was measured by tumor volume.

Results: Our results demonstrate neoepitopes-specific human T-cell responses in vitro. RNA-seq data were available for nine patients; eight MHC-I and five MHC-II neoantigens were synthesized from gene fusions from three different patients represented by six sets of haplotype specific PBMCs. In vitro, neoantigen-treated PBMCs showed increased cell clumping. An objective IFN gamma response on ELISA was seen for six peptides at two different concentrations and five peptides at one concentration. Analysis of RNA-seq of murine tumors shows that the metastatic MKP-Lung cells (which carry molecular signatures associated with recurrent ovarian cancer), have an increased number of mutations (SNVs, indels) including gene fusions, in line with findings from human tumors. Using in silico prediction tools, we identified 16 potential peptide binders (IC50&lt; 500), two with strong and 14 with moderate binding. The transcript variants were validated via PCR. The vaccine comprised the top seven MHC-I restricted peptide candidates with IC50&lt;500Nm and one large (MHC-II) candidate peptide for CD4 T-cell responses. No difference was seen between treatment groups (ANOVA p=0.35).

Conclusion: Our results demonstrate that PBMC pulsed with a combination of short and large peptides release increased IFNγ, supporting the proposed vaccine design. Structural variants contribute to tumor immunogenic potential. Immunogenicity data from this project will be further used to refine the target selection for individualized, mutanome-based vaccines.

Citation Format: Malcolm S. Ross, Ma Tianzhou, Lixin Zhang, Nolan Priedigkeit, George Tseng, Adrian V. Lee, Robert P. Edwards, Anda M. Vlad. Neoepitope peptide vaccines and immune checkpoint blockade in a new preclinical ovarian cancer model. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B33.

Abstract B25: Hormone receptor expression and response in ovarian tumors of low malignant potential

Objective: Primary treatment for ovarian low malignant potential (LMP) tumors is surgical resection with little proven effect of cytotoxic chemotherapy. New therapeutic strategies are needed to prevent and treat recurrence. The objective of this study is to investigate the role of hormone receptors in ovarian low malignant potential tumors.

Methods: We obtained formalin-fixed, paraffin embedded (FFPE) tissue samples from patients with ovarian LMP tumors. Clinicopathologic data were collected for all available specimens. Immunohistochemistry (IHC) was performed to determine protein expression. Gene expression was measured using the NanoString nCounter platform. Differences in expression between histologic subtypes were by t-test, followed by a Bonferroni adjustment for multiple comparisons (p&lt;0.01).

Results: Thirty-eight patients were included in this study. The histologic subtypes were divided between 20 serous and 18 mucinous tumors. All serous tumors were ERα and PR positive by IHC and 6 of 20 (30%) were ERβ positive. Only one of the 18 mucinous tumors (5.6%) was positive for both ERα and PR, and all the samples were negative for ERβ. ERβ mRNA levels were elevated in the mucinous LMP tumors and ERα mRNA was higher in the serous samples. ERα and PR protein expression correlated with mRNA expression of ESR1 (r2=0.5606) and PR (r2=0.42), respectively. ERβ expression did not correlate with mRNA expression of ESR2 (r2=0.038). Measurement of estrogen-regulated genes and genes involved in ER signaling (n=236) revealed a clear separation of serous from mucinous subtypes, with 44 genes showing a statistically significant difference (p&lt;0.01) between the serous and mucinous subtypes.

Conclusion: High levels of ERα, PR, and downstream ERα targets in serous LMP tumors suggest hormone responsiveness and that these tumors are potentially treatable with endocrine therapy. Mucinous tumors largely did not express hormone receptors. In light of this, differences in gene expression observed are more likely attributable to underlying lineage differences than differences in estrogen signaling. Additional large-scale analyses are warranted to better understand the differences between subtypes and to identify avenues for targeted therapy in mucinous LMPs.

Citation Format: Sarah E. Taylor, Courtney L. Andersen, Rohit Bhargava, George Tseng, Steffi Oesterreich, Robert P. Edwards, Adrian V. Lee. Hormone receptor expression and response in ovarian tumors of low malignant potential. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B25.

Abstract B23: The evolution of estrogen receptor signaling in the progression of endometriosis to endometriosis-associated ovarian cancer

Objectives: To investigate changes in estrogen receptor–alpha (ERα) signaling during the progression of endometriosis to endometriosis-associated ovarian cancer (EAOC) as a putative driver of malignant transformation.

Methods: We procured tissue samples of normal endometrium (n=23), endometriosis (benign, n=19; atypical, n=11; concurrent with EAOC, n=9), and EAOC (n=21). In this cohort, we evaluated expression of a 236-gene signature of estrogen signaling. ANOVA and unsupervised clustering were used to identify distinct gene expression profiles across disease states. These profiles were compared to public profiles of estrogen regulation in preclinical cancer models from the Gene Expression Omnibus (GEO). Gene set enrichment analysis (GSEA) was performed to determine whether gene expression in EAOC was consistent with ERα activity.

Results: ANOVA revealed 158 differentially expressed genes (q&lt;0.05) and unsupervised clustering identified 4 distinct gene clusters. Cluster 1 comprises genes with increasing expression from benign endometriosis to EAOC (e.g. FGF18, ESR2). Clusters 2 and 3 include genes that are overexpressed or downregulated in EAOC compared to benign endometriosis, respectively (e.g., NRIP1, IGFBP3). Cluster 4 consists of genes with an incremental decrease in expression from benign endometriosis to EAOC (e.g., ESR1, PGR, and GREB1). The estrogen signaling profile of EAOC was not consistent with activated ERα in the preclinical models. Further, GSEA did not identify signatures of activated ERα in EAOC but instead identified expression patterns consistent with loss of ERα function and development of endocrine resistance.

Conclusions: Gene expression data suggest that classical ERα signaling becomes inactivated throughout the progression of endometriosis to EAOC. Rather, the gene expression pattern in EAOC is more consistent with profiles of endocrine resistance. De-repression of ERα target genes such as FGF18 may contribute to evolution of endometriosis into EAOC.

Citation Format: Michelle Boisen, Courtney Andersen, Matt Sikora, Tianzhou Ma, George Tseng, Anda Vlad, Esther Elishaev, Uma Chandran, Robert Edwards, Steffi Oesterreich. The evolution of estrogen receptor signaling in the progression of endometriosis to endometriosis-associated ovarian cancer. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B23.

Abstract 2486: PTEN fusion gene promotes growth in cancer

Deletion or mutation of PTEN is frequent in a variety of human cancers and is an underlying mechanism for cancer development. Here, we report a PTEN-involved fusion gene and the corresponding genome breakpoint in human cancers. Pten fusion is highly recurrent in cancers and their matched lymph nodes and is located nucleoli. Targeted knockout of this fusion gene in Du145 and MCF7 cells impeded tumor cell growths, retarded S phase entry, and reduced invasiveness, and was prone to the UV- induced apoptosis. Knockout of PTEN-fusion blocked xenografted-tumor growth in mice, while forced-expression of PTEN -fusion through hydrodynamic injection into mice led to hepatocellular carcinoma. These findings indicate that the genome rearrangement of PTEN-fusion results in an oncogenic fusion protein in addition to the loss of Pten as an underlying mechanism in driving cancer development.

Citation Format: Yanping Yu, Silvia Chang, Baoguo Ren, George Michalopoulos, George Tseng, Jianhua Luo. PTEN fusion gene promotes growth in 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 2486.

MAN2A1-FER Fusion Gene Is Expressed by Human Liver and Other Tumor Types and Has Oncogenic Activity in Mice

BACKGROUND & AIMS

Human tumors and liver cancer cell lines express the product of a fusion between the first 13 exons in the mannosidase α class 2A member 1 gene (MAN2A1) and the last 6 exons in the FER tyrosine kinase gene (FER), called MAN2A1-FER. We investigated whether MAN2A1-FER is expressed by human liver tumors and its role in liver carcinogenesis.

METHODS

We performed reverse transcription polymerase chain reaction analyses of 102 non-small cell lung tumors, 61 ovarian tumors, 70 liver tumors, 156 glioblastoma multiform samples, 27 esophageal adenocarcinomas, and 269 prostate cancer samples, as well as 10 nontumor liver tissues and 20 nontumor prostate tissues, collected at the University of Pittsburgh. We also measured expression by 15 human cancer cell lines. We expressed a tagged form of MAN2A1-FER in NIH3T3 and HEP3B (liver cancer) cells; Golgi were isolated for analysis. MAN2A1-FER was also overexpressed in PC3 or DU145 (prostate cancer), NIH3T3 (fibroblast), H23 (lung cancer), and A-172 (glioblastoma multiforme) cell lines and knocked out in HUH7 (liver cancer) cells. Cells were analyzed for proliferation and in invasion assays, and/or injected into flanks of severe combined immunodeficient mice; xenograft tumor growth and metastasis were assessed. Mice with hepatic deletion of PTEN were given tail-vein injections of MAN2A1-FER.

RESULTS

We detected MAN2A1-FER messenger RNA and fusion protein (114 kD) in the hepatocellular carcinoma cell line HUH7, as well as in liver tumors, esophageal adenocarcinoma, glioblastoma multiforme, prostate tumors, non-small cell lung tumors, and ovarian tumors, but not nontumor prostate or liver tissues. MAN2A1-FER protein retained the signal peptide for Golgi localization from MAN2A1 and translocated from the cytoplasm to Golgi in cancer cell lines. MAN2A1-FER had tyrosine kinase activity almost 4-fold higher than that of wild-type FER, and phosphorylated the epidermal growth factor receptor at tyrosine 88 in its N-terminus. Expression of MAN2A1-FER in 4 cell lines led to epidermal growth factor receptor activation of BRAF, MEK, and AKT; HUH7 cells with MAN2A1-FER knockout had significant decreases in phosphorylation of these proteins. Cell lines that expressed MAN2A1-FER had increased proliferation, colony formation, and invasiveness and formed larger (>2-fold) xenograft tumors in mice, with more metastases, than cells not expressing the fusion protein. HUH7 cells with MAN2A1-FER knockout formed smaller xenograft tumors, with fewer metastases, than control HUH7 cells. HUH7, A-172, and PC3 cells that expressed MAN2A1-FER were about 2-fold more sensitive to the FER kinase inhibitor crizotinib and the epidermal growth factor receptor kinase inhibitor canertinib; these drugs slowed growth of xenograft tumors from MAN2A1-FER cells and prevented their metastasis in mice. Hydrodynamic tail-vein injection of MAN2A1-FER resulted in rapid development of liver cancer in mice with hepatic disruption of Pten.

CONCLUSIONS

Many human tumor types and cancer cell lines express the MAN2A1-FER fusion, which increases proliferation and invasiveness of cancer cell lines and has liver oncogenic activity in mice.

Abstract 3612: Combination FGFR4 and ER-targeted therapy for invasive lobular carcinoma

Background Invasive Lobular Carcinoma (ILC) is an understudied subtype of breast cancer. Distinctive properties of ILC include growth patterns, metastatic behavior, receptor status (almost universally estrogen receptor (ER) positive), and survival outcomes (Long-term survival is lower in patients with ER+ ILC compared to the other main histological subtype, invasive ductal carcinoma). Our lab recently generated six long-term estrogen deprivation (LTED) models of ILC cells. We performed RNA-Sequencing on these six LTED cell lines and identified differentially expressed genes compared to their parental cells cultured with estrogen. We overlapped these results with a previously published analysis of a tamoxifen-resistant ILC cell line and found that FGFR4 is the most consistently overexpressed gene in the setting of acquired resistance to endocrine therapy in ILC cells.

Hypothesis FGFR4 is an important mediator of resistance to endocrine therapy in ILC.

Methods To study the role of FGFR4 in acquired resistance to endocrine therapy, we used siRNA, multiple shRNAs, and specific small molecule inhibition for growth assays of ILC cells. To study the role of FGFR4 in de novo resistance to endocrine therapy, we collected 129 well curated ER+ ILC tumor specimens. We performed gene expression analysis on the pre-treatment samples using a custom NanoString panel.

Results FGFR4 inhibition decreases parental and LTED ILC cell growth in classic 2D growth conditions, in the setting of ultra-low attachment, and in colony formation assays. Mechanistically, FGFR4 and estrogen signaling are antagonistic in parental ILC cells. In our clinical samples, increased expression of FGFR4 is predictive of shorter time to distant recurrence.

Conclusion FGFR4 may play an important role in both acquired and de novo resistance to endocrine therapy in ILC. Future studies will assess the efficacy of combining FGFR4 inhibitors with ER-targeted therapy for patients with ILC.

Citation Format: Kevin Levine, Jian Chen, Matthew Sikora, Nilgun Tasdemir, George Tseng, Shannon Puhalla, Rachel Jankowitz, David Dabbs, Priscilla McAuliffe, Adrian Lee, Steffi Oesterreich. Combination FGFR4 and ER-targeted therapy for invasive lobular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3612. doi:10.1158/1538-7445.AM2017-3612

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K-means (is-K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is-K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency.

Multiplex profiling identifies distinct local and systemic alterations during intraperitoneal chemotherapy for ovarian cancer: An NRG Oncology/Gynecologic Oncology Group Study

OBJECTIVES

Ovarian cancer leads to abdominal carcinomatosis and late stage (III/IV) diagnosis in 75% of patients. Three randomized phase III trials have demonstrated that intraperitoneal (IP) chemotherapy improves outcomes in epithelial ovarian cancer. While IP treatment is validated by clinical trials, there is a poor understanding of the mechanism(s) leading to the survival advantage other than the increased concentration of cytotoxic drugs within the tumor microenvironment. A better understanding of this process through analysis of dynamic biomarkers should promote novel approaches that may enhance tumor clearance. We propose this pilot study to confirm the feasibility of collecting serial peritoneal samples from implanted catheters in women receiving IP chemotherapy. We believe these specimens may be used for multiplex analysis to reveal unique biomarker fluctuations when compared to peripheral blood.

METHODS

From 13 women participating on GOG 252, 30 whole blood, 12 peritoneal fluid (PF), and 20 peritoneal wash (PW) with 30mL saline were obtained. Samples were requested prior to the first three chemotherapy cycles. Samples were assessed for volume, cell populations, protein, RNA, and miRNA content changes.

RESULTS

Median volume for PF was 1.6mL and 3.1mL for PW. PW is a dilution of PF capable of capturing measurable biomarkers. Peritoneal aspirates contain a unique profile of biomarkers distinct from blood. miRNA undergo earlier alteration with chemotherapy than genes. Flow cytometry does not adequately capture biomarker fluctuations.

CONCLUSIONS

As a proof of principle study, this trial provides evidence that sampling the peritoneal cavity can be adapted for biomarker analysis.

Active Estrogen Receptor-alpha Signaling in Ovarian Cancer Models and Clinical Specimens

Purpose: High-grade serous ovarian cancer (HGSOC) is an aggressive disease with few available targeted therapies. Despite high expression of estrogen receptor-alpha (ERα) in approximately 80% of HGSOC and some small but promising clinical trials of endocrine therapy, ERα has been understudied as a target in this disease. We sought to identify hormone-responsive, ERα-dependent HGSOC.Experimental Design: We characterized endocrine response in HGSOC cells across culture conditions [ two-dimensional (2D), three-dimensional (3D), forced suspension] and in patient-derived xenograft (PDX) explants, assessing proliferation and gene expression. Estrogen-regulated transcriptome data were overlapped with public datasets to develop a comprehensive panel of ERα target genes. Expression of this panel and ERα H-score were assessed in HGSOC samples from patients who received endocrine therapy. Time on endocrine therapy was used as a surrogate for clinical response.Results: Proliferation is ERα-regulated in HGSOC cells in vitro and in vivo, and is partly dependent on 3D context. Transcriptomic studies identified genes shared by cell lines and PDX explants as ERα targets. The selective ERα downregulator (SERD) fulvestrant is more effective than tamoxifen in blocking ERα action. ERα H-score is predictive of efficacy of endocrine therapy, and this prediction is further improved by inclusion of target gene expression, particularly IGFBP3Conclusions: Laboratory models corroborate intertumor heterogeneity of endocrine response in HGSOC but identify features associated with functional ERα and endocrine responsiveness. Assessing ERα function (e.g., IGFBP3 expression) in conjunction with H-score may help select patients who would benefit from endocrine therapy. Preclinical data suggest that SERDs might be more effective than tamoxifen. Clin Cancer Res; 23(14); 3802-12. ©2017 AACR.

Enhanced Molecular Aging in Late-Life Depression: the Senescent-Associated Secretory Phenotype

OBJECTIVE

This study aims to investigate whether a systemic molecular pattern associated with aging (senescent-associated secretory phenotype [SASP]) is elevated in adults with late-life depression (LLD), compared with never-depressed elderly comparison participants.

DESIGN

Cross-sectional study.

PARTICIPANTS

We included 111 older adults (80 with LLD and 31 comparison participants) in this study.

MEASUREMENT

A panel of 22 SASP-related proteins was extracted from a previous multiplex protein panel performed in these participants. We conducted a principal component analysis to create the SASP index based on individual weights of each of protein.

RESULTS

Participants with LLD showed a significantly increased SASP index compared with comparison participants, after controlling for age, depressive symptoms, medical comorbidity (CIRS-G) scores, sex, and cognitive performance (F(1,98) = 7.3, p = 0.008). Correlation analyses revealed that the SASP index was positively correlated with age (r = 0.2, p = 0.03) and CIRS score (r = 0.27, p = 0.005), and negatively correlated with information processing speed (r = -0.34, p = 0.001), executive function (r = -0.27, p = 0.004) and global cognitive performance (r = -0.28, p = 0.007).

CONCLUSIONS

To the best of our knowledge, this is the first study to show that a set of proteins (i.e., SASP index) primarily associated with cellular aging is abnormally regulated and elevated in LLD. These results suggest that individuals with LLD display enhanced aging-related molecular patterns that are associated with higher medical comorbidity and worse cognitive function. Finally, we provide a set of proteins that can serve as potential therapeutic targets and biomarkers to monitor the effects of therapeutic or preventative interventions in LLD.

Biomarker detection and categorization in ribonucleic acid sequencing meta-analysis using Bayesian hierarchical models

Meta-analysis combining multiple transcriptomic studies increases statistical power and accuracy in detecting differentially expressed genes. As the next-generation sequencing experiments become mature and affordable, increasing number of RNA-seq datasets are available in the public domain. The count-data based technology provides better experimental accuracy, reproducibility and ability to detect low-expressed genes. A naive approach to combine multiple RNA-seq studies is to apply differential analysis tools such as edgeR and DESeq to each study and then combine the summary statistics of p-values or effect sizes by conventional meta-analysis methods. Such a two-stage approach loses statistical power, especially for genes with short length or low expression abundance. In this paper, we propose a full Bayesian hierarchical model (namely, BayesMetaSeq) for RNA-seq meta-analysis by modelling count data, integrating information across genes and across studies, and modelling potentially heterogeneous differential signals across studies via latent variables. A Dirichlet process mixture (DPM) prior is further applied on the latent variables to provide categorization of detected biomarkers according to their differential expression patterns across studies, facilitating improved interpretation and biological hypothesis generation. Simulations and a real application on multi-brain-region HIV-1 transgenic rats demonstrate improved sensitivity, accuracy and biological findings of the proposed method.

Circulating biosignatures of late-life depression (LLD): Towards a comprehensive, data-driven approach to understanding LLD pathophysiology

There is scarce information about the pathophysiological processes underlying Late-Life Depression (LLD). We aimed to determine the neurobiological abnormalities related to LLD through a multi-modal biomarker approach combining a large, unbiased peripheral proteomic panel and structural brain imaging. We examined data from 44 LLD and 31 control participants. Plasma proteomic analysis was performed using a multiplex immunoassay. We evaluated the differential protein expression between groups with random intercept models. We carried out enrichment pathway analyses (EPA) to uncover biological pathways and processes related to LLD. Machine learning analysis was applied to the combined dataset to determine the accuracy with which specific proteins could correctly discriminate LLD versus control participants. Sixty-one proteins were differentially expressed in LLD (p < 0.05 and FDR < 0.01). EPA showed that these proteins were related to abnormal immune-inflammatory control, cell survival and proliferation, proteostasis control, lipid metabolism, intracellular signaling. Machine learning analysis showed that a panel of three proteins (C-peptide, FABP-liver, ApoA-IV) discriminated LLD and control participants with 100% accuracy. The plasma proteomic profile in LLD revealed dysregulation in biological processes essential to the maintenance of homeostasis at cellular and systemic levels. These abnormalities increase brain and systemic allostatic load leading to the downstream negative outcomes of LLD, including increased risk of medical comorbidities and dementia. The peripheral biosignature of LLD has predictive power and may suggest novel putative therapeutic targets for prevention, treatment, and neuroprotection in LLD.