Kinesin Family Member C1 (KIFC1/HSET) Underlies Aggressive Disease in Androgen Receptor-Low and Basal-Like Triple-Negative Breast Cancers

Quadruple-negative breast cancer (QNBC) lacks traditional actionable targets, including androgen receptor (AR). QNBC disproportionately afflicts and impacts patients of African genetic ancestry. Kinesin family member C1 (KIFC1/HSET), a centrosome clustering protein that prevents cancer cells from undergoing centrosome-amplification-induced apoptosis, has been reported to be upregulated in TNBCs and African-American (AA) TNBCs. Herein, we analyzed KIFC1 RNA levels and their associations with clinical features and outcomes among AR-low and AR-high TNBC tumors in three distinct publicly available gene expression datasets and in the breast cancer gene expression database (bc-GenExMiner). KIFC1 levels were significantly higher in AR-low and basal-like TNBCs than in AR-high and non-basal-like TNBCs, irrespective of the stage, grade, tumor size, and lymph node status. KIFC1 levels were also upregulated in AR-low tumors relative to AR-high tumors among Black and premenopausal women with TNBC. High KIFC1 levels conferred significantly shorter overall survival, disease-free survival, and distant metastasis-free survival among AR-low and basal-like TNBC patients in Kaplan-Meier analyses. In conclusion, KIFC1 levels may be upregulated in AR-low tumors and, specifically, in those of African descent, wherein it may promote poor outcomes. KIFC1 may be an actionable cancer-cell-specific target for the AR-low TNBC subpopulation and could aid in alleviating racial disparities in TNBC outcomes.

Molecular features of androgen-receptor low, estrogen receptor-negative breast cancers in the Carolina breast cancer study

PURPOSE

Androgen receptor (AR) expression is absent in 40-90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored.

METHODS

We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; N = 669) and The Cancer Genome Atlas (TCGA; N = 237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response].

RESULTS

AR-low tumors were more prevalent among younger (RFD =  + 10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2 negativity (RFD = - 35%, 95% CI = - 44% to - 26%), higher grade (RFD =  + 17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD =  + 22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD =  + 33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD =  + 41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression.

CONCLUSION

Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients.

Molecular Features of Androgen-Receptor Low, Estrogen Receptor-Negative Breast Cancers in the Carolina Breast Cancer Study

PURPOSE

Androgen receptor (AR) expression is absent in 40-90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored.

METHODS

We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; n=669) and The Cancer Genome Atlas (TCGA; n=237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response].

RESULTS

AR-low tumors were more prevalent among Black (relative frequency difference (RFD) = +7%, 95% CI = 1% to 14%) and younger (RFD = +10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2-negativity (RFD = -35%, 95% CI = -44% to -26%), higher grade (RFD = +17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD = +22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD = +33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD = +41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression.

CONCLUSION

Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients.

The DARC Side of Inflamm-Aging: Duffy Antigen Receptor for Chemokines (DARC/ACKR1) as a Potential Biomarker of Aging, Immunosenescence, and Breast Oncogenesis among High-Risk Subpopulations

The proclivity of certain pre-malignant and pre-invasive breast lesions to progress while others do not continues to perplex clinicians. Clinicians remain at a crossroads with effectively managing the high-risk patient subpopulation owing to the paucity of biomarkers that can adequately risk-stratify and inform clinical decisions that circumvent unnecessary administration of cytotoxic and invasive treatments. The immune system mounts the most important line of defense against tumorigenesis and progression. Unfortunately, this defense declines or "ages" over time-a phenomenon known as immunosenescence. This results in "inflamm-aging" or the excessive infiltration of pro-inflammatory chemokines, which alters the leukocyte composition of the tissue microenvironment, and concomitant immunoediting of these leukocytes to diminish their antitumor immune functions. Collectively, these effects can foster the sequelae of neoplastic transformation and progression. The erythrocyte cell antigen, Duffy antigen receptor for chemokines(DARC/ACKR1), binds and internalizes chemokines to maintain homeostatic levels and modulate leukocyte trafficking. A negative DARC status is highly prevalent among subpopulations of West African genetic ancestry, who are at higher risk of developing breast cancer and disease progression at a younger age. However, the role of DARC in accelerated inflamm-aging and malignant transformation remains underexplored. Herein, we review compelling evidence suggesting that DARC may be protective against inflamm-aging and, therefore, reduce the risk of a high-risk lesion progressing to malignancy. We also discuss evidence supporting that immunotherapeutic intervention-based on DARC status-among high-risk subpopulations may evade malignant transformation and progression. A closer look into this unique role of DARC could glean deeper insight into the immune response profile of individual high-risk patients and their predisposition to progress as well as guide the administration of more "cyto-friendly" immunotherapeutic intervention to potentially "turn back the clock" on inflamm-aging-mediated oncogenesis and progression.

Adaptation to Hypoxia May Promote Therapeutic Resistance to Androgen Receptor Inhibition in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) surpasses other BC subtypes as the most challenging to treat due to its lack of traditional BC biomarkers. Nearly 30% of TNBC patients express the androgen receptor (AR), and the blockade of androgen production and AR signaling have been the cornerstones of therapies for AR-positive TNBC. However, the majority of women are resistant to AR-targeted therapy, which is a major impediment to improving outcomes for the AR-positive TNBC subpopulation. The hypoxia signaling cascade is frequently activated in the tumor microenvironment in response to low oxygen levels; activation of the hypoxia signaling cascade allows tumors to survive despite hypoxia-mediated interference with cellular metabolism. The activation of hypoxia signaling networks in TNBC promotes resistance to most anticancer drugs including AR inhibitors. The activation of hypoxia network signaling occurs more frequently in TNBC compared to other BC subtypes. Herein, we examine the (1) interplay between hypoxia signaling networks and AR and (2) whether hypoxia and hypoxic stress adaptive pathways promote the emergence of resistance to therapies that target AR. We also pose the well-supported question, “Can the efficacy of androgen-/AR-targeted treatments be enhanced by co-targeting hypoxia?” By critically examining the evidence and the complex entwinement of these two oncogenic pathways, we argue that the simultaneous targeting of androgen biosynthesis/AR signaling and hypoxia may enhance the sensitivity of AR-positive TNBCs to AR-targeted treatments, derail the emergence of therapy resistance, and improve patient outcomes.

Hypoxia Drives Centrosome Amplification in Cancer Cells via HIF1α-dependent Induction of Polo-Like Kinase 4

Centrosome amplification (CA) has been implicated in the progression of various cancer types. Although studies have shown that overexpression of PLK4 promotes CA, the effect of tumor microenvironment on polo-like kinase 4 (PLK4) regulation is understudied. The aim of this study was to examine the role of hypoxia in promoting CA via PLK4. We found that hypoxia induced CA via hypoxia-inducible factor-1α (HIF1α). We quantified the prevalence of CA in tumor cell lines and tissue sections from breast cancer, pancreatic ductal adenocarcinoma (PDAC), colorectal cancer, and prostate cancer and found that CA was prevalent in cells with increased HIF1α levels under normoxic conditions. HIF1α levels were correlated with the extent of CA and PLK4 expression in clinical samples. We analyzed the correlation between PLK4 and HIF1A mRNA levels in The Cancer Genome Atlas (TCGA) datasets to evaluate the role of PLK4 and HIF1α in breast cancer and PDAC prognosis. High HIF1A and PLK4 levels in patients with breast cancer and PDAC were associated with poor overall survival. We confirmed PLK4 as a transcriptional target of HIF1α and demonstrated that in PLK4 knockdown cells, hypoxia-mimicking agents did not affect CA and expression of CA-associated proteins, underscoring the necessity of PLK4 in HIF1α-related CA. To further dissect the HIF1α-PLK4 interplay, we used HIF1α-deficient cells overexpressing PLK4 and showed a significant increase in CA compared with HIF1α-deficient cells harboring wild-type PLK4. These findings suggest that HIF1α induces CA by directly upregulating PLK4 and could help us risk-stratify patients and design new therapies for CA-rich cancers.

IMPLICATIONS

Hypoxia drives CA in cancer cells by regulating expression of PLK4, uncovering a novel HIF1α/PLK4 axis.

Abstract 3560: PLK4 is a HIF-1α target gene: A novel mechanism inducing centrosome amplification in tumor cells

Background: The presence of supernumerary or abnormally large centrosomes, also known as centrosome amplification (CA), drives tumor progression by enhancing chromosomal instability, and altering cellular microtubule cytoskeletons and tissue cytoarchitectures to promote the migration and invasion capabilities of cancer cells. Although the prevalence of CA is documented in a variety of cancer types, it remains unclear how CA is induced in tumor cells.This study aims to examine the role of intratumoral hypoxia in inducing CA via HIF-1α.

Methods: We (a) exposed cultured breast, pancreatic, colorectal and prostate cancer cells to hypoxia, and (b) genetically manipulated hypoxia [via overexpression (OE) or knock-out (KO) of HIF-1α], and quantitated CA employing immunocytofluorescence methods. We also quantitated the levels of CA-associated genes and proteins by qRT-PCR and western blot, respectively. Next, to discern the biological pathway through which HIF-1α induces CA, we performed ChIP and Luciferase reporter assays. We immunohistochemically labeled breast (n=24), colon (38), prostate (n=52), and pancreatic (n=34) cancer tissue samples for HIF-1α and PLK4. Serial sections from the same tumors were also immunofluorescently labeled for γ-tubulin and CA was quantitated. Using public microarray datasets (TCGA), we investigated whether centrosomal gene expression is enriched in tumors characterized by a high expression of a hypoxia gene expression signature.

Results: Cells cultured in hypoxic conditions exhibited higher CA (p<0.05) than the cells cultured in normoxic conditions. CA levels increased when cells with HIF-1α OE were cultured in normoxic conditions and no significant induction of CA was observed when the HIF-1α KO cells were cultured under hypoxic conditions. ChIP and Luciferase assay confirmed that HIF-1α induced CA by directly upregulating the expression of PLK4. Moreover, when tumor cells were exposed to hypoxia after knock-down of PLK4, no significant changes in CA and CA-associated proteins were observed. In clinical patient samples (breast, colon, pancreatic and prostate cancer), we observed that HIF-1α expression was significantly (p<0.05) correlated with PLK4 expression at the protein level (breast ρ=0.81, colon ρ=0.76, prostate ρ=0.68, and pancreatic ρ=0.67). Findings from our in silico analyses further validated these observations by showing a strong correlation between the expressions of HIF-1α and PLK4 at the transcriptional level. We also found that centrosomal gene expression is enriched in tumors with high hypoxia score (TCGA dataset of breast, colon, pancreatic and prostate cancer).

Conclusion: Collectively, our findings suggest that hypoxia drives CA in tumor cells through HIF-1α-mediated transcriptional upregulation of PLK4. Given the development of several promising HIF-1α inhibitors, this research could potentially aid in patient risk stratification for clinical decision-making, and enable design of new therapies.

Citation Format: Karuna Mittal, Jaspreet Kaur, Shaligram Sharma, Ishita Choudhary, Guanhao Wei, Precious Imhansi Jacob, Da Hoon Choi, Nagini Maganti, Shrikant Pawar, Michael S. Toss, Emiel A. Janssen, Meenakshi V. Gupta, Michelle D. Reid, Emad A. Rakha, Padmashree Rida, Ritu Aneja. PLK4 is a HIF-1α target gene: A novel mechanism inducing centrosome amplification in tumor cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3560.

A Quantitative Centrosomal Amplification Score Predicts Local Recurrence of Ductal Carcinoma In Situ

PURPOSE

The purpose of this study is to predict risk of local recurrence (LR) in ductal carcinoma in situ (DCIS) with a new visualization and quantification approach using centrosome amplification (CA), a cancer cell-specific trait widely associated with aggressiveness.

EXPERIMENTAL DESIGN

This first-of-its-kind methodology evaluates the severity and frequency of numerical and structural CA present within DCIS and assigns a quantitative centrosomal amplification score (CAS) to each sample. Analyses were performed in a discovery cohort (DC, n = 133) and a validation cohort (VC, n = 119).

RESULTS

DCIS cases with LR exhibited significantly higher CAS than recurrence-free cases. Higher CAS was associated with a greater risk of developing LR (HR, 6.3 and 4.8 for DC and VC, respectively; P < 0.001). CAS remained an independent predictor of relapse-free survival (HR, 7.4 and 4.5 for DC and VC, respectively; P < 0.001) even after accounting for potentially confounding factors [grade, age, comedo necrosis, and radiotherapy (RT)]. Patient stratification using CAS (P < 0.0001) was superior to that by Van Nuys Prognostic Index (VNPI; HR for CAS = 6.2 vs. HR for VNPI = 1.1). Among patients treated with breast-conserving surgery alone, CAS identified patients likely to benefit from adjuvant RT.

CONCLUSIONS

CAS predicted 10-year LR risk for patients who underwent surgical management alone and identified patients who may be at low risk of recurrence, and for whom adjuvant RT may not be required. CAS demonstrated the highest concordance among the known prognostic models such as VNPI and clinicopathologic variables such as grade, age, and comedo necrosis.

Combined HER3-EGFR score in triple-negative breast cancer provides prognostic and predictive significance superior to individual biomarkers

Epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 3 (HER3) have been investigated as triple-negative breast cancer (TNBC) biomarkers. Reduced EGFR levels can be compensated by increases in HER3; thus, assaying EGFR and HER3 together may improve prognostic value. In a multi-institutional cohort of 510 TNBC patients, we analyzed the impact of HER3, EGFR, or combined HER3-EGFR protein expression in pre-treatment samples on breast cancer-specific and distant metastasis-free survival (BCSS and DMFS, respectively). A subset of 60 TNBC samples were RNA-sequenced using massive parallel sequencing. The combined HER3-EGFR score outperformed individual HER3 and EGFR scores, with high HER3-EGFR score independently predicting worse BCSS (Hazard Ratio [HR] = 2.30, p = 0.006) and DMFS (HR = 1.78, p = 0.041, respectively). TNBCs with high HER3-EGFR scores exhibited significantly suppressed ATM signaling and differential expression of a network predicted to be controlled by low TXN activity, resulting in activation of EGFR, PARP1, and caspases and inhibition of p53 and NFκB. Nuclear PARP1 protein levels were higher in HER3-EGFR-high TNBCs based on immunohistochemistry (p = 0.036). Assessing HER3 and EGFR protein expression in combination may identify which adjuvant chemotherapy-treated TNBC patients have a higher risk of treatment resistance and may benefit from a dual HER3-EGFR inhibitor and a PARP1 inhibitor.

Panoptic Overview of Triple-Negative Breast Cancer in Nigeria: Current Challenges and Promising Global Initiatives

Purpose

Triple-negative breast cancer (TNBC) is the most deadly form of breast cancer (BC) today. TNBC treatment is fraught with challenges because of the extensive interpatient heterogeneity in clinical behavior and scarcity of stratifying biomarkers and actionable targets. Women of African ancestry face a disproportionate burden resulting from this disease, which affects them earlier and more aggressively and has a higher propensity to spread and resist conventional treatments. A much higher proportion of Nigerian patients with BC have TNBC compared with patients with BC in the United States and Europe.

Methods

This article spotlights Nigeria as an example of a nation wherein genetic and nongenetic spheres of influence intersect to affect the prevalence of this disease, the scale of its challenge, and its toll.

Results

Studies have illuminated the inherently different tumor biology of Nigerian TNBCs, which show distinct genetic variants and gene expression patterns compared with European or European-American TNBCs. Parallels are apparent between TNBC phenotypes among African Americans and Nigerians, implicating the common thread of shared genetic ancestry between these populations. Reproductive, lifestyle, socioeconomic, and cultural factors also shape TNBC outcomes in Nigeria, as do resource constraints in Nigerian health care and research sectors.

Conclusion

Increasing our understanding of how these factors contribute to poorer outcomes among Nigerian women may uncover valuable insights and strategies in alleviating the TNBC burden in many countries of the world and help reduce the racial disparity in BC-related outcomes here in the United States. Importantly, this review also highlights collaborative global and local initiatives that converge expertise and resources to advance research on effective management of TNBC in diverse populations.

Machine learning-based prediction of breast cancer growth rate in vivo

Background

Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.

Methods

A serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.

Results

SM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.

Conclusion

Our Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications.

A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk

Background

Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mastectomy or adjuvant radiation can reduce recurrence risk, there are significant concerns regarding patient over-/under-treatment. Current clinicopathological markers are insufficient to accurately assess the recurrence risk. To address this issue, we developed a novel machine learning (ML) pipeline to predict risk of ipsilateral recurrence using digitized whole slide images (WSI) and clinicopathologic long-term outcome data from a retrospectively collected cohort of DCIS patients (n = 344) treated with lumpectomy at Nottingham University Hospital, UK.

Methods

The cohort was split case-wise into training (n = 159, 31 with 10-year recurrence) and validation (n = 185, 26 with 10-year recurrence) sets. The sections from primary tumors were stained with H&E, then digitized and analyzed by the pipeline. In the first step, a classifier trained manually by pathologists was applied to digital slides to annotate the areas of stroma, normal/benign ducts, cancer ducts, dense lymphocyte region, and blood vessels. In the second step, a recurrence risk classifier was trained on eight select architectural and spatial organization tissue features from the annotated areas to predict recurrence risk.

Results

The recurrence classifier significantly predicted the 10-year recurrence risk in the training [hazard ratio (HR) = 11.6; 95% confidence interval (CI) 5.3–25.3, accuracy (Acc) = 0.87, sensitivity (Sn) = 0.71, and specificity (Sp) = 0.91] and independent validation [HR = 6.39 (95% CI 3.0–13.8), p < 0.0001;Acc = 0.85, Sn = 0.5, Sp = 0.91] cohorts. Despite the limitations of our cohorts, and in some cases inferior sensitivity performance, our tool showed superior accuracy, specificity, positive predictive value, concordance, and hazard ratios relative to tested clinicopathological variables in predicting recurrences (p < 0.0001). Furthermore, it significantly identified patients that might benefit from additional therapy (validation cohort p = 0.0006).

Conclusions

Our machine learning-based model fills an unmet clinical need for accurately predicting the recurrence risk for lumpectomy-treated DCIS patients.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1165-5) contains supplementary material, which is available to authorized users.

Disadvantaged neighborhoods and racial disparity in breast cancer outcomes: the biological link

Neighborhoods encompass complex environments comprised of unique economic, physical, and social characteristics that have a profound impact on the residing individual's health and, collectively, on the community's wellbeing. Neighborhood disadvantage (ND) is one of several factors that prominently contributes to racial breast cancer (BC) health disparities in American women. African American (AA) women develop more aggressive breast cancer features, such as triple-negative receptor status and more advanced histologic grade and tumor stage, and suffer worse clinical outcomes than European American (EA) women. While the adverse effects of neighborhood disadvantage on health, including increased risk of cancer and decreased longevity, have recently come into focus, the specific molecular mechanisms by which neighborhood disadvantage increases BC risk and worsens BC outcomes (survivorship, recurrence, mortality) are not fully elucidated. This review illuminates the probable biological links between neighborhood disadvantage and predominantly BC risk, with an emphasis on stress reactivity and inflammation, epigenetics and telomere length in response to adverse neighborhood conditions.

Targeting risk factors for reducing the racially disparate burden in breast cancer

African-American (AA) women are more likely to die from breast cancer (BC), at any age, compared to European-American women. Although breakthroughs in pre-clinical studies have resulted in potentially actionable targets in AA BC, drugs that were rationally designed for these targets have performed poorly in clinical trials. Challenges with interpatient and intratumoral heterogeneity, lack of drug sensitivity and specificity, suboptimal biomarker cut-offs, lack of drug response predictive biomarkers, drug side effects, high costs of drug development, and under-representation of AAs in clinical trials complicate the development of targeted therapies for AA BC patients. Accumulating evidence suggests that racial disparities exist in non-genetic risk factors that can alter genetic and epigenetic programs to promote breast tumorigenesis. Herein, we present a "roadmap" that addresses non-genetic risk factors that are suspected to contribute to the racial disparity in BC mortality. Increased targeting of these non-genetic risk factors may proffer a safer and more economical route to alleviating the racially disparate burden in BC.

Time will tell: Circadian clock dysregulation in triple negative breast cancer

Growing evidence now links circadian disruption (CD) to increased risk of developing multiple types of cancer, including breast cancer (BC). In the US, African-American (AA) BC patients have a higher mortality rate than European-Americans (EAs) with BC, and a prime suspect in this racially disparate burden has been the greater incidence of an aggressive and highly heterogeneous BC subtype called triple-negative BC (TNBC), among AAs. AAs are also more prone to CD as larger proportions of AAs engage in night shift work than EAs, and the chronotype of AAs makes it harder for them to adapt to CD than EAs. Although clock gene dysregulation has been shown to perturb transactivation of key cell cycle and apoptosis regulators, little is known about how clock gene mis-expression affects TNBC outcomes. This review examines the prognostic value of clock genes in TNBC, and evaluates patterns of clock gene dysregulation in the individual TNBC molecular subtypes. Better understanding of how CD contributes to TNBC biology may illuminate new paths to improving disease outcomes and reducing BC-related racial disparities.

First international TNBC conference meeting report

Recently, Georgia State University's Centennial Hall was the premier location for the 2017 International Conference on Triple Negative Breast Cancer (TNBC): Illuminating Actionable Biology, which was held from Sept. 18 to 20, 2017, in Atlanta, USA. The conference featured a stellar line-up of domestic and international speakers and diverse participants including TNBC survivors, luminaries in breast cancer research, medical students and fellows, clinicians, translational researchers, epidemiologists, biostatisticians, bioinformaticians, and representatives from the industry. This report distills the burning questions that spiked the event and summarizes key themes, findings, unique opportunities and future directions that emerged from this confluence of thought leaders.

Abstract PR13: Disparities in centrosomal profiles: Prediction of metastatic risk in African American and European American breast cancer patients

Centrosome amplification has long been established as a hallmark of cancer. More than 80% of invasive breast tumors display this cellular trait. Centrosomal aberrations underlie chromosome instability (CIN) thus corroborating the extensive clonal intratumoral heterogeneity existent within breast lesions that fuels tumor evolution. Sub-clonal heterogeneity drives emergence of aggressive clones with a propensity to migrate and invade, resulting in tumor dissemination and metastases. Thus, centrosome amplification is a critical driver of tumor progression and metastases. Although numerous studies have linked centrosomal overload to tumor aggressiveness, no studies have yet quantified this cell-biological feature to establish a well-defined relationship between the severity and extent of centrosome amplification and tumor aggressiveness. Utilizing an innovative and rationally-guided approach, we have derived an algorithm that allows the precise quantitation of the frequency and severity of both structural and numerical aberrations in supernumerary centrosomes present in clinical samples. Our novel method thus uncovers previously unrecognized differences in the centrosomal profiles of grade-matched breast tumors from African-American (AA) (n=71) and European American (EA) (n=104) women. Our data demonstrate that AA breast tumors exhibit higher numeral, structural and total centrosome amplification scores than grade-matched EA tumors. Interestingly, tumors displaying lymph node and distant metastasis exhibited higher structural amplification than grade-matched non-metastatic tumors. Hence, our novel quantification tool offers valuable information that can potentially predict the risk of AA breast tumors rapidly progressing to metastatic disease and uncovers a hitherto unappreciated organelle-specific disparity marker among racially distinct breast tumors.

This abstract was also presented as Poster B6.

Citation Format: Nikita Wright, Vaishali Pannu, Padmashree Rida, Karuna Mittal, Sergey Klimov, Farida N. Yada, Michelle D. Reid, Guilherme Cantuaria, Ritu Aneja. Disparities in centrosomal profiles: Prediction of metastatic risk in African American and European American breast cancer patients. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr PR13.

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

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.