Remus Osan

On initial Brain Activity Mapping of episodic and semantic memory code in the hippocampus.

It has been widely recognized that the understanding of the brain code would require large-scale recording and decoding of brain activity patterns. In 2007 with support from Georgia Research Alliance, we have launched the Brain Decoding Project Initiative with the basic idea which is now similarly advocated by BRAIN project or Brain Activity Map proposal. As the planning of the BRAIN project is currently underway, we share our insights and lessons from our efforts in mapping real-time episodic memory traces in the hippocampus of freely behaving mice. We show that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics. We also provide an example of how the carefully designed, sometime thinking-outside-the-box, behavioral paradigms can be highly instrumental to the unraveling of memory-coding cell assembly organizing principle in the hippocampus. Our observations to date have led us to conclude that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination.

KIFCI, a novel putative prognostic biomarker for ovarian adenocarcinomas: delineating protein interaction networks and signaling circuitries.

BackgroundAmplified centrosomes in cancers are recently garnering a lot of attention as an emerging hub of diagnostic, prognostic and therapeutic targets. Ovarian adenocarcinomas commonly harbor supernumerary centrosomes that drive chromosomal instability. A centrosome clustering molecule, KIFC1, is indispensable for the viability of extra centrosome-bearing cancer cells, and may underlie progression of ovarian cancers.MethodsCentrosome amplification in low- and high- grade serous ovarian adenocarcinomas was quantitated employing confocal imaging. KIFC1 expression was analyzed in ovarian tumors using publically-available databases. Associated grade, stage and clinical information from these databases were plotted for KIFC1 gene expression values. Furthermore, interactions and functional annotation of KIFC1 and its highly correlated genes were studied using DAVID and STRING 9.1.ResultsClinical specimens of ovarian cancers display robust centrosome amplification and deploy centrosome clustering to execute an error-prone mitosis to enable karyotypic heterogeneity that fosters tumor progression and aggressiveness. Our in silico analyses showed KIFC1 overexpression in human ovarian tumors (n = 1090) and its upregulation associated with tumor aggressiveness utilizing publically-available gene expression databases. KIFC1 expression correlated with advanced tumor grade and stage. Dichotomization of KIFC1 levels revealed a significantly lower overall survival time for patients in high KIFC1 group. Intriguingly, in a matched-cohort of primary (n = 7) and metastatic (n = 7) ovarian samples, no significant differences in KIFC1 expression were detectable, suggesting that high KIFC1 expression may serve as a marker of metastases onset. Nonetheless, KIFC1 levels in both primary and matched metastatic sites were significantly higher compared to normal tissue . Ingenuity based network prediction algorithms combined with pre-established protein interaction networks uncovered several novel cell-cycle related partner genes on the basis of interconnectivity, illuminating the centrosome clustering independent agenda of KIFC1 in ovarian tumor progression.ConclusionsOvarian cancers display amplified centrosomes, a feature of aggressive tumors. To cope up with the abnormal centrosomal load, ovarian cancer cells upregulate genes like KIFC1 that are known to induce centrosome clustering. Our data underscore KIFC1 as a putative biomarker that predicts worse prognosis, poor overall survival and may serve as a potential marker of onset of metastatic dissemination in ovarian cancer patients.

Multi-institutional study of nuclear KIFC1 as a biomarker of poor prognosis in African American women with triple-negative breast cancer

Nuclear KIFC1 (nKIFC1) predicts worse outcomes in breast cancer, but its prognostic value within racially distinct triple-negative breast cancer (TNBC) patients is unknown. Thus, nKIFC1 expression was assessed by immunohistochemistry in 163 African American (AA) and 144 White TNBC tissue microarrays (TMAs) pooled from four hospitals. nKIFC1 correlated significantly with Ki67 in White TNBCs but not in AA TNBCs, suggesting that nKIFC1 is not merely a surrogate for proliferation in AA TNBCs. High nKIFC1 weighted index (WI) was associated with significantly worse overall survival (OS), progression-free survival (PFS), and distant metastasis-free survival (DMFS) (Hazard Ratios [HRs] = 3.5, 3.1, and 3.8, respectively; P = 0.01, 0.009, and 0.007, respectively) in multivariable Cox models in AA TNBCs but not White TNBCs. Furthermore, KIFC1 knockdown more severely impaired migration in AA TNBC cells than White TNBC cells. Collectively, these data suggest that nKIFC1 WI an independent biomarker of poor prognosis in AA TNBC patients, potentially due to the necessity of KIFC1 for migration in AA TNBC cells.

Distinctions in Breast Tumor Recurrence Patterns Post-Therapy among Racially Distinct Populations

Background Clinical studies have revealed a higher risk of breast tumor recurrence in African-American (AA) patients compared to European-American (EA) patients, contributing to the alarming inequality in clinical outcomes among the ethnic groups. However, distinctions in recurrence patterns upon receiving hormone, radiation, and/or chemotherapy between the races remain poorly characterized. Methods We compared patterns and rates (per 1000 cancer patients per 1 year) of recurrence following each form of treatment between AA (n = 1850) and EA breast cancer patients (n = 7931) from a cohort of patients (n = 10504) treated between 2005–2015 at Northside Hospital in Atlanta, GA. Results Among patients who received any combination of adjuvant therapy, AA displayed higher overall rates of recurrence than EA (p = 0.015; HR: 1.699; CI: 1.108–2.606). Furthermore, recurrence rates were higher in AA than EA among stage I (p = 0.031; HR: 1.736; CI: 1.052–2.864) and T1 classified patients (p = 0.003; HR: 2.009; CI: 1.263–3.197). Interestingly, among patients who received neoadjuvant chemotherapy, AA displayed higher rates of local recurrence than EA (p = 0.024; HR: 7.134; CI: 1.295–39.313). Conclusion Our analysis revealed higher incidence rates of recurrence in AA compared to EA among patients that received any combination of adjuvant therapy. Moreover, our data demonstrates an increased risk of tumor recurrence in AA than EA among patients diagnosed with minimally invasive disease. This is the first clinical study to suggest that neoadjuvant chemotherapy improves breast cancer recurrence rates and patterns in AA.

On brain activity mapping: insights and lessons from Brain Decoding Project to map memory patterns in the hippocampus

The BRAIN project recently announced by the president Obama is the reflection of unrelenting human quest for cracking the brain code, the patterns of neuronal activity that define who we are and what we are. While the Brain Activity Mapping proposal has rightly emphasized on the need to develop new technologies for measuring every spike from every neuron, it might be helpful to consider both the theoretical and experimental aspects that would accelerate our search for the organizing principles of the brain code. Here we share several insights and lessons from the similar proposal, namely, Brain Decoding Project that we initiated since 2007. We provide a specific example in our initial mapping of real-time memory traces from one part of the memory circuit, namely, the CA1 region of the mouse hippocampus. We show how innovative behavioral tasks and appropriate mathematical analyses of large datasets can play equally, if not more, important roles in uncovering the specific-to-general feature-coding cell assembly mechanism by which episodic memory, semantic knowledge, and imagination are generated and organized. Our own experiences suggest that the bottleneck of the Brain Project is not only at merely developing additional new technologies, but also the lack of efficient avenues to disseminate cutting edge platforms and decoding expertise to neuroscience community. Therefore, we propose that in order to harness unique insights and extensive knowledge from various investigators working in diverse neuroscience subfields, ranging from perception and emotion to memory and social behaviors, the BRAIN project should create a set of International and National Brain Decoding Centers at which cutting-edge recording technologies and expertise on analyzing large datasets analyses can be made readily available to the entire community of neuroscientists who can apply and schedule to perform cutting-edge research.

Abstract PR06: Differences in tumor-infiltrating lymphocytes between racially distinct triple-negative breast tumors

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype that lacks hormone receptors [estrogen receptor (ER), progesterone receptor (PR)] and overexpression of human epidermal growth factor receptor 2 (HER2/neu). The disease is characterized by an aggressive clinical disease course, and a high risk of disease progression within 5 years of diagnosis. There are currently no targeted treatments available for TNBC, and surgery and chemotherapy are the mainstay of TNBC treatment. TNBC afflicts African-American (AA) women at a 2-3 times higher rate than European-American (EA) women. AAs also present with more aggressive clinicopathologic characteristics such as higher grade and stage at diagnosis, and experience poorer clinical outcomes than EAs among TNBC patients. Furthermore, AAs harbor more aggressive TNBC subtypes such as a basal-like phenotype and quadruple-negative [androgen receptor (AR)-negative TNBC] breast cancer than EA TNBC patients. This disparate burden underscores an urgent need to identify distinctions in inherent tumor biology between racially distinct TNBCs. Tumor-infiltrating lymphocytes (TILs) are implicated in killing tumor cells and thus have been associated with better clinical outcomes and response to neoadjuvant chemotherapy. Studies have also reported that TILs are associated with more aggressive clinicopathologic characteristics such as such as higher grade, stage, Ki67, TNBC status, and increased lymph node metastasis. In formalin-fixed, paraffin-embedded resection samples from TNBC patients who received adjuvant chemotherapy at Emory Hospital in Atlanta, GA, we compared overall (intratumoral and peripheral) TIL counts between AA and EA patients (n=121). We observed a trend of more TILs among AA (n=87) compared to EA (n=34) TNBC patients (p=0.02). Among early-stage (I-II) TNBC patients, we found that AAs (n=71) harbored significantly more TILs than EAs (n=32) (p=0.019) but not among late-stage (III-IV) patients (p=0.86). Among early-stage AA TNBC patients, more TILs negatively correlated with younger age at diagnosis (ρ=-0.25; p=0.03) and positively correlated with intramammary lymph node involvement (ρ=0.36; p=0.002). Furthermore, TILs correlated negatively with AR expression (ρ=-0.25; p=0.04) and positively with BRCA1-associated protein (ρ=0.3; p=0.02) and programmed cell death protein 1 (ρ=0.56; p Citation Format: Nikita Wright, Chaeyun Lee, Wei Guanhao, Uma Krishnamurti, Xiaoxian Li, Padmashree C. G. Rida, Remus Osan, Ritu Aneja. Differences in tumor-infiltrating lymphocytes between racially distinct triple-negative breast tumors [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr PR06.

Abstract PR02: β-Catenin overexpression underlies the aggressive disease course in African American triple-negative breast cancer patients who lack androgen receptor

Background: Androgen receptor (AR) has emerged as a new target for treating TNBC. AR is expressed in 10-43% of TNBCs. Although there are conflicting reports in the literature about the effect of AR status on TNBC prognosis, agents targeting AR signaling (enzalutamide) are already being evaluated in AR-positive TNBCs in early-stage clinical trials. However, no study so far has evaluated the association/correlation of AR status with ethnicity in TNBCs and downstream effects of AR loss in TNBCs. Given the association of AR loss with poor prognosis in breast cancer and that the African American (AA) with TNBC suffers aggressive disease course when compared to European American (EA) TNBCs, we hypothesized that AR loss might be an underlying cause of aggressive disease course in AR-negative TNBCs. Thus, in this project we aimed to study if loss or gain of AR in AA and EA TNBCs regulates the expression of β-catenin and leads to more aggressive disease course by activating downstream canonical Wnt-beta catenin signaling. Methods: We evaluated AR expression immunohistochemically in 424 formalin-fixed, paraffin-embedded samples from TNBC patients for whom complete clinicopathologic and overall survival (OS) data were available. Samples with Results: IHC staining of AR indicated that 79.5% of AA TNBCs (n=214) and 70% of EA TNBCs (n=210) were AR negative. Loss of AR was associated with poor overall survival in adjuvant-treated high Ki67 (>14%) (HR=1.72; p=0.095) AA TNBC (n=98) when compared to EA TNBCs (n=80). These data were validated by our in silico findings, which suggested that EA TNBCs (n=81) exhibited higher levels of AR mRNA compared to AA TNBCs (n=41) (p Conclusion: This study suggests that increased expression of β-catenin coupled with AR loss in AAs may underlie the ethnic disparity in outcomes among TNBC patients and strongly supports the prognostic role of AR and β-catenin in this breast cancer subtype. Citation Format: Karuna Mittal, Shristi Bhattarai, Sergey Klimov, Uma Krishnamurthi, Xiaoxian Li, Ceyda Sonmez Wetherilt, Mohammad A. Aleskandaran, Andrew A. Green, Emad A. Rakha, Ian O. Ellis, Guilherme Cantuaria, Guanhao Wei, Remus Mihai Osan, Meenakshi V. Gupta, Upender Manne, Padmashree C.G Rida, Ritu Aneja. β-Catenin overexpression underlies the aggressive disease course in African American triple-negative breast cancer patients who lack androgen receptor [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr PR02.

Abstract B12: Racial differences in Androgen Receptor status among triple-negative breast cancers

Background: Triple Negative Breast Cancer (TNBC) is an aggressive subtype of breast cancer with high recurrence and mortality rates. Currently, there are no effective targeted therapies available for TNBC. Emerging data suggest that androgen receptor (AR), a nuclear steroid hormone receptor expressed in 10-43% of TNBCs, has emerged as a promising new biomarker with potential predictive value for certain TNBC subtypes. African American (AA) women suffer from earlier onset of the breast cancer along with significant aggressive disease course when compared to European American (EA) women. This study aimed to determine the prognostic value of AR in a large TNBC cohort and evaluate racewise trends in AR expression status among TNBCs. Methods: We evaluated AR expression immunohistochemically in formalin-fixed paraffin-embedded samples from 822 TNBC patients (142, 95 and 264 patients from Emory, Northside and Grady Memorial Hospitals, respectively, in Atlanta, and 321 from Nottingham Hospital, UK) for whom complete clinicopathologic and overall survival (OS) data were available. Ethnicity data were available for 138 AA and 675 EA TNBC cases. Samples with Results: In this study, 45.6% of the TNBC cases were QN and AAs had a much higher proportion (80.8%) of QN cases than EAs (40.1%, p 14%) proliferative index (p Conclusion: This study suggest that a higher prevalence of QN breast cancer among AAs may be a plausible reason for the ethnic disparity in outcomes among TNBC patients and strongly support the prognostic role of AR in this breast cancer subtype. Citation Format: Bhattarai Shristi, Jun Xia, Ceyda Sonmez Wetherilt, Sergey Klimov, Ansa Riaz, Sonal Pattni, Mohammad A. Aleskandarany, Andrew R. Green, Emad A. Rakha, Ian O. Ellis, Guilherme Cantuaria, Xiaoxian (Bill) Li, Uma Krishnamurthi, Remus Mihai Osan, Padmashree CG Rida, Ritu Aneja. Racial differences in Androgen Receptor status among triple-negative breast cancers. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr B12.

Abstract B08: Identifying high-risk triple negative breast cancer patients using a novel cycling kinetics metric

Background Ki67 Index (KI) and Mitotic Index (MI) are proliferation markers with established prognostic value in breast cancer. These indices are evaluated individually and on disparate measurement scales; they thereforefail to capture information about cell cycling kinetics of proliferating cells. Within the triple negative (TNBC) subtype , we rationally integrate the two markers to identify high-risk patients whose proliferative cells exhibit fast cycling kinetics. Methods Pathology reports of breast cancer patients (n=10,504 from Northside Hospital, Atlanta and n=1560 from Nottingham Hospital, UK) were retrospectively analyzed for mitotic scores, KI and clinical outcomes. Mitotic counts in 267 HE n=322 from Nottingham Hospital, UK, and n=108 from OlabisiOnabanjo University, Nigeria). Stratification of KAMS, KI and MI were performed onthe thresholdsthat produced the lowest AIC (best model fit).Slow-cycling and fast-cycling TNBC subgroups from Nottingham Hospital were analyzed for biomarker expression. Results Kaplan-Meier survival analyses, AIC andc2 values showed that KAMS-based stratification of TNBCs into two subgroups was superior to that by either KI or MI, regardless of hospital, and KAMS retained its significance in multivariate analyses, controlling for stage and age. Fast-cycling TNBCs have poorer prognosis than slow-cycling TNBCs, perhaps due to higher intratumoral heterogeneity in fast cycling tumors. Fast-cycling TNBCs showed high expression of proteins implicated in DNA damage response, sumoylation, EGFR signaling and metastasis. By contrast, slow-cycling TNBCs showed extensive chromatin modification. Conclusion KAMS quantifies cell cycling kinetics, stratifies TNBCs and yields new risk-predictive information that is not revealed by either KI or MI. KAMS reveals the underlying heterogeneity in cycling kinetics among TNBCs and helps identify TNBCs who might benefit from treatments that target the cell cycle machinery. Citation Format: Sergey Klimov, Guanhao Wei, Andrew Green, Mohammed Aleskandarany, Emad Rakha, Ian Ellis, Guilherme Cantuaria, Ayodeji O. Agboola, Michelle Reid, Li Xiaoxian, Rida C. G. Padmashree, Remus Osan, Ritu Aneja. Identifying high-risk triple negative breast cancer patients using a novel cycling kinetics metric. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr B08.

Analytically tractable studies of traveling waves of activity in integrate-and-fire neural networks

In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration depends quadratically on the instantaneous speed of the activity propagation. We use this property to analytically compute the network spike dynamics and to highlight the emergence of a natural time scale for the evolution of the traveling waves. These results allow us to examine other applications of this model such as the effect that a nonconductive gap of tissue has on further activity propagation. Furthermore we show that activity propagation also depends on local conditions for other more general connectivity functions, by converting the evolution equations for network dynamics into a low-dimensional system of ordinary differential equations. This approach greatly enhances our intuition into the mechanisms of the traveling waves evolution and significantly reduces the simulation time for this class of models.