Northside Hospital Cancer Institute

Atlanta, GA, United States

Northside Hospital Cancer Institute

Atlanta, GA, United States
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Bailey D.W.,Northside Hospital Cancer Institute
Journal of applied clinical medical physics | Year: 2016

Our study aimed to quantify the effect of the Measurement Uncertainty function on planar dosimetry pass rates, as measured and analyzed with the Sun Nuclear Corporation MapCHECK 2 array and its associated software. This optional function is toggled in the program preferences of the software (though turned on by default upon installation), and automatically increases the dose difference tolerance defined by the user for each planar dose comparison. Dose planes from 109 static-gantry IMRT fields and 40 VMAT arcs, of varying modulation complexity, were measured at 5 cm water-equivalent depth in the MapCHECK 2 diode array, and respective calculated dose planes were exported from a commercial treatment planning system. Planar dose comparison pass rates were calculated within the Sun Nuclear Corporation analytic software using a number of calculation parameters, including Measurement Uncertainty on and off. By varying the percent difference (%Diff) criterion for similar analyses performed with Measurement Uncertainty turned off, an effective %Diff criterion was defined for each field/arc corresponding to the pass rate achieved with Measurement Uncertainty turned on. On average, the Measurement Uncertainty function increases the user-defined %Diff criterion by 0.8%-1.1% for 3%/3 mm analysis, depending on plan type and calculation technique (corresponding to an average change in pass rate of 1.0%-3.5%, and a maximum change of 8.7%). At the 2%/2 mm level, the Measurement Uncertainty function increases the user-defined %Diff criterion by 0.7%-1.2% on average, again depending on plan type and calculation technique (corresponding to an average change in pass rate of 3.5%-8.1%, and a maximum change of 14.2%). The largest increases in pass rate due to the Measurement Uncertainty function are generally seen with poorly matched planar dose comparisons, while the function has a notably smaller effect as pass rates approach 100%. The Measurement Uncertainty function, then, may substantially increase the pass rates for planar dose comparisons. Meanwhile, the types of uncertainties incorporated into the function (and their associated quantitative estimates, as described in the software user's manual) may not be an accurate estimation of actual measurement uncertainty, depending on the user's measurement conditions. Pass rates listed in published reports, comparisons between institutions or simply separate workstations, or comparisons with the calculation methods of other vendors, should clearly indicate whether or not the Measurement Uncertainty function is used, since it has the potential to substantially inflate pass rates for typical IMRT and VMAT dose planes.

Lang K.A.F.,Northside Hospital Cancer Institute
Expert Review of Molecular Diagnostics | Year: 2013

Genetic counselors have been helping patients navigate hereditary cancer risk for decades. The rapidly changing landscape of genetic testing options means the field is again at a unique time in its history. Fears that arose when BRCA testing first became available are again being voiced in light of next-generation sequencing. The origins of genetic counseling, best practices, and recommendations that have come about since those early days need to be well understood before these new challenges can be met. The role of a proper risk assessment in preventing adverse outcomes is vital as options for testing change. In addition, an understanding of how various countries have incorporated genetic testing and genetic counseling into their healthcare systems can provide lessons in moving forward and capitalizing on the new technology that is again creating a genetics revolution. © 2013 Informa UK Ltd.

Pannu V.,Georgia State University | Mittal K.,Georgia State University | Cantuaria G.,Northside Hospital Cancer Institute | Reid M.D.,Emory University | And 8 more authors.
Oncotarget | Year: 2015

Centrosome amplification (CA), a cell-biological trait, characterizes pre-neoplastic and pre-invasive lesions and is associated with tumor aggressiveness. Recent studies suggest that CA leads to malignant transformation and promotes invasion in mammary epithelial cells. Triple negative breast cancer (TNBC), a histologically-aggressive subtype shows high recurrence, metastases, and mortality rates. Since TNBC and non- TNBC follow variable kinetics of metastatic progression, they constitute a novel test bed to explore if severity and nature of CA can distinguish them apart. We quantitatively assessed structural and numerical centrosomal aberrations for each patient sample in a large-cohort of grade-matched TNBC (n = 30) and non-TNBC (n = 98) cases employing multi-color confocal imaging. Our data establish differences in incidence and severity of CA between TNBC and non-TNBC cell lines and clinical specimens. We found strong correlation between CA and aggressiveness markers associated with metastasis in 20 pairs of grade-matched TNBC and non-TNBC specimens (p < 0.02). Time-lapse imaging of MDA-MB-231 cells harboring amplified centrosomes demonstrated enhanced migratory ability. Our study bridges a vital knowledge gap by pinpointing that CA underlies breast cancer aggressiveness. This previously unrecognized organellar inequality at the centrosome level may allow early-risk prediction and explain higher tumor aggressiveness and mortality rates in TNBC patients.

Pawar S.,Georgia State University | Donthamsetty S.,Georgia State University | Pannu V.,Georgia State University | Rida P.,Georgia State University | And 5 more authors.
Journal of Ovarian Research | Year: 2014

Background: Amplified 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. Methods. Centrosome 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. Results: Clinical 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. Conclusions: Ovarian 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. © 2014 Pawar et al.; licensee BioMed Central Ltd.

Mukkavilli R.,Advinus Therapeutics Ltd | Gundala S.R.,Georgia State University | Yang C.,Georgia State University | Donthamsetty S.,Georgia State University | And 5 more authors.
PLoS ONE | Year: 2014

Natural and complementary therapies in conjunction with mainstream cancer care are steadily gaining popularity. Ginger extract (GE) confers significant health-promoting benefits owing to complex additive and/or synergistic interactions between its bioactive constituents. Recently, we showed that preservation of natural "milieu" confers superior anticancer activity on GE over its constituent phytochemicals, 6-gingerol (6G), 8-gingerol (8G), 10-gingerol (10G) and 6-shogaol (6S), through enterohepatic recirculation. Here we further evaluate and compare the effects of GE and its major bioactive constituents on cytochrome P450 (CYP) enzyme activity in human liver microsomes by monitoring metabolites of CYP-specific substrates using LC/MS/MS detection methods. Our data demonstrate that individual gingerols are potent inhibitors of CYP isozymes, whereas GE exhibits a much higher half-maximal inhibition value, indicating no possible herb-drug interactions. However, GE's inhibition of CYP1A2 and CYP2C8 reflects additive interactions among the constituents. In addition, studies performed to evaluate transporter-mediated intestinal efflux using Caco-2 cells revealed that GE and its phenolics are not substrates of P-glycoprotein (Pgp). Intriguingly, however, 10G and 6S were not detected in the receiver compartment, indicating possible biotransformation across the Caco-2 monolayer. These data strengthen the notion that an interplay of complex interactions among ginger phytochemicals when fed as whole extract dictates its bioactivity highlighting the importance of consuming whole foods over single agents. Our study substantiates the need for an in-depth analysis of hepatic biotransformation events and distribution profiles of GE and its active phenolics for the design of safe regimens. © 2014 Mukkavilli et al.

Pannu V.,Georgia State University | Rida P.C.G.,Georgia State University | Ogden A.,Georgia State University | Turaga R.C.,Georgia State University | And 8 more authors.
Oncotarget | Year: 2015

Human breast tumors harbor supernumerary centrosomes in almost 80% of tumor cells. Although amplified centrosomes compromise cell viability via multipolar spindles resulting in death-inducing aneuploidy, cancer cells tend to cluster extra centrosomes during mitosis. As a result cancer cells display bipolar spindle phenotypes to maintain a tolerable level of aneuploidy, an edge to their survival. HSET/KifC1, a kinesin-like minus-end directed microtubule motor has recently found fame as a crucial centrosome clustering molecule. Here we show that HSET promotes tumor progression via mechanisms independent of centrosome clustering. We found that HSET is overexpressed in breast carcinomas wherein nuclear HSET accumulation correlated with histological grade and predicted poor progression-free and overall survival. In addition, deregulated HSET protein expression was associated with gene amplification and/or translocation. Our data provide compelling evidence that HSET overexpression is pro-proliferative, promotes clonogenic-survival and enhances cellcycle kinetics through G2 and M-phases. Importantly, HSET co-immunoprecipitates with survivin, and its overexpression protects survivin from proteasome-mediated degradation, resulting in its increased steady-state levels. We provide the first evidence of centrosome clustering-independent activities of HSET that fuel tumor progression and firmly establish that HSET can serve both as a potential prognostic biomarker and as a valuable cancer-selective therapeutic target.

Wei B.,University of Alabama at Birmingham | Eldaif S.M.,Northside Hospital Cancer Institute | Cerfolio R.J.,University of Alabama at Birmingham
Surgical Oncology Clinics of North America | Year: 2016

Robotic-assisted pulmonary lobectomy can be considered for patients able to tolerate conventional lobectomy. Contraindications to resection via thoracotomy apply to patients undergoing robotic lobectomy. Team training, familiarity with equipment, troubleshooting, and preparation are critical for successful robotic lobectomy. Robotic lobectomy is associated with decreased rates of blood loss, blood transfusion, air leak, chest tube duration, length of stay, and mortality compared with thoracotomy. Robotic lobectomy offers many of the same benefits in perioperative morbidity and mortality, and additional advantages in optics, dexterity, and surgeon ergonomics as video-assisted thoracic lobectomy. Long-term oncologic efficacy and cost implications remain areas of study. © 2016 Elsevier Inc.

PubMed | Roswell Park Cancer Institute and Northside Hospital Cancer Institute
Type: Journal Article | Journal: Medical physics | Year: 2017

To quantify the effect of the Measurement Uncertainty function on planar dosimetry pass rates, as analyzed with Sun Nuclear Corporation analytic software (MapCHECK or SNC Patient). This optional function is toggled on by default upon software installation, and automatically increases the user-defined dose percent difference (%Diff) tolerance for each planar dose comparison.Dose planes from 109 IMRT fields and 40 VMAT arcs were measured with the MapCHECK 2 diode array, and compared to calculated planes from a commercial treatment planning system. Pass rates were calculated within the SNC analytic software using varying calculation parameters, including Measurement Uncertainty on and off. By varying the %Diff criterion for each dose comparison performed with Measurement Uncertainty turned off, an effective %Diff criterion was defined for each field/arc corresponding to the pass rate achieved with MapCHECK Uncertainty turned on.For 3%/3mm analysis, the Measurement Uncertainty function increases the user-defined %Diff by 0.8-1.1% average, depending on plan type and calculation technique, for an average pass rate increase of 1.0-3.5% (maximum +8.7%). For 2%, 2 mm analysis, the Measurement Uncertainty function increases the user-defined %Diff by 0.7-1.2% average, for an average pass rate increase of 3.5-8.1% (maximum +14.2%). The largest increases in pass rate are generally seen with poorly-matched planar dose comparisons; the MapCHECK Uncertainty effect is markedly smaller as pass rates approach 100%.The Measurement Uncertainty function may substantially inflate planar dose comparison pass rates for typical IMRT and VMAT planes. The types of uncertainties incorporated into the function (and their associated quantitative estimates) as described in the software users manual may not accurately estimate realistic measurement uncertainty for the users measurement conditions. Pass rates listed in published reports or otherwise compared to the results of other users or vendors should clearly indicate whether the Measurement Uncertainty function is used.

PubMed | Northside Hospital Cancer Institute, Georgia State University, Emory University and West Georgia Hospitals
Type: Journal Article | Journal: PloS one | Year: 2017

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.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.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).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.

News Article | February 21, 2017

ATLANTA--Having high levels of a certain biomarker is linked to poor prognosis in African-American patients with triple-negative breast cancer, while the same biomarker doesn't influence disease outcomes in white patients, according to a new study. Racial disparities in disease, particularly breast cancer, continue to pose a major challenge in healthcare. African-American breast cancer patients are more likely to suffer from a more aggressive course of disease and higher mortality compared to other racial groups. In particular, African-American patients with triple-negative breast cancer have a dismal prognosis. The dire outcome of this group could indicate that high-risk, African-American breast cancer patients are not being identified as such using standard clinical prognostic tools and aren't being prescribed sufficiently aggressive treatment. Therefore, it's critical to find novel biomarkers that could identify differences in tumor biology between racial groups and serve as risk predictors to help alleviate health disparity in disease outcomes. In this study, a research team led by Georgia State University examined whether a biomarker called nuclear KIFC1, which has been associated with worse outcomes in breast cancer, can predict risk in triple-negative breast cancer, a subtype that disproportionately affects African-American women. The researchers assessed the nuclear KIFC1 biomarker in triple-negative breast cancer tissue samples from 163 African-American patients and 144 white patients who were treated between the years 2003-2008 at Grady Memorial and Emory University hospitals, 2005-2013 at Northside Hospital and 2001-2012 at Baylor Scott & White Medical Center. Race information in medical records was self-declared by patients. The findings are published in the online journal Scientific Reports. "We looked at the levels of nuclear KIFC1 in their tumors, and interestingly, we found that African-American women had slightly higher levels, but it was only within African-American patients that the levels mattered for their outcome," said Angela Ogden, lead author of the study and a Ph.D. candidate in Dr. Ritu Aneja's laboratory in Georgia State's Biology Department. "African-American women with high nuclear KIFC1 levels tended to do poorly, whereas in white women, it didn't matter if they had high or low levels. It had no effect on their outcomes." The researchers further investigated why the biomarker only seems to matter in African-American patients by studying triple-negative breast tumor cells from African-American and white patients. "We found that if we silence the KIFC1 gene, it had a greater impact on the migration of the African-American cells than it did on the white cells," Ogden said. "It may be that for whatever reason, in African-American breast cancer tumors, KIFC1 helps the cells to migrate and spread to other parts of the body. And for reasons that we currently don't know, that's not the case in white tumors. Ultimately, it may even be that African-American patients could potentially be treated with a KIFC1 inhibitor to help prevent metastasis, but that's for future studies." The study is multi-institutional with tumor samples from breast cancer patients treated at four different hospitals, so the results can likely be generalized. To ensure certain factors didn't confound the results, the researchers adjusted for tumor stage, age at diagnosis, receipt of chemotherapy and the hospital where patients received chemotherapy. They found nuclear KIFC1 had a significant effect on outcomes in African-American patients, even after adjusting for these factors. Biomarkers of relevance to specific racial groups are starting to be explored more in scientific studies, Ogden said. "The approach of treating all patients the same, regardless of their racial or ethnic background, may not be the best approach as genetic ancestry matters," she said. "There may be biomarkers and treatments that work better for people of a certain ancestry, race or ethnicity, instead of a one-size-fits-all approach." Co-authors of the study include Chakravarthy Garlapati, Ravi Chakra Turaga, Nikita Wright, Shristi Bhattarai, Karuna Mittal, Dr. Remus Osan, Ansa Riaz, Sergey Klimov and Dr. Aneja of Georgia State; Dr. Ceyda S?nmez Wetherilt of Georgia State and Emory University School of Medicine; Dr. Padmashree C. G. Rida of Georgia State and Novazoi Theranostics; Drs. Xiaoxian (Bill) Li, Gabriela Oprea-Ilies, Uma Krishnamurti, Michelle D. Reid and Sonal Pattni of Emory University School of Medicine; Mildred Jones and Dr. Guilherme Cantuaria of Northside Hospital Cancer Institute; Dr. Meenakshi Gupta of West Georgia Medical Center; and Dr. Arundhati Rao of Scott and White Medical Center, BSWHealth in Temple, Texas. The study was funded by the National Cancer Institute and the National Institute on Minority Health and Health Disparities of the National Institutes of Health.

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