bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 624: A case control study of benign breast disease and breast cancer among indigenous African women
Authors: ADEDOKUN BABATUNDE , Odedina Stella , Ojengbede Oladosu , Ademola Adeyinka , Ogundiran Temidayo , Huo Dezheng , Olopade Olufunmilayo , Agwai Imaria , Makumbi Timothy , Ndom Paul , Gakwaya Antony
Published: August 2019

Purpose: To determine the association between benign breast disease (BBD) and breast cancer and if BBD is a mediator of the association between established risk factors and breast cancer among native African women

Methods: We analysed data from 5154 women who participated in a case control study (2405 cases and 2749 controls) between March 1998 and December 2014 in three sub Saharan African countries: Nigeria (n= 4233), Uganda (n=477) and Cameroon (n=444). Breast cancer cases aged 18 years and older were enrolled in two tertiary hospitals in the two countries, unselected for age at diagnosis and family history. Controls who were free of breast cancer were enrolled in the same hospitals. Interviews were conducted to obtain data on potential epidemiological risk factors for breast cancer. We determined the association between breast cancer, history of BBD, age at diagnosis and types of BBD using logistic regression, while adjusting for socio-demographic characteristics and established risk factors. In addition, we estimated the proportion of the effects of other established risk factors mediated by BBD in the etiology of breast cancer.

Results: Less than a tenth (8.1%, 420) of the study participants reported having a history of BBD, 87 of the 420 reported a biopsy diagnosed BBD. Among breast cancer cases, the proportions of BBD and biopsy-confirmed BBD were 10.4% and 3.8%, respectively, compared to 6.3% and 1.3% among controls (both p<0.001). Fibroadenoma (n=100, 45.2%) was the most commonly reported type of benign breast disease, followed by breast cyst (n=31, 15.2%) and fibrocystic diseases (n=19, 10.1%). Overall, the adjusted odds ratio of having breast cancer for those with benign breast disease relative to those without was 1.42 (95% CI 1.13-1.79). The odds ratios were also significantly higher among premenopausal (OR = 1.45, 95% CI: 1.07-1.95) and postmenopausal women (OR = 1.49, 95% CI 1.02-2.19). The proportion mediated by BBD in the association between age at menarche and breast cancer was 13.7%. Less than 1% of the effects of other risk factors that we examined was mediated by BBD.

Conclusions: Benign breast disease is a risk factor for breast cancer among women in SSA. The mediator role of BBD in the effects of established risk factors on breast cancer risk appears very minimal.

Citation Format: BABATUNDE ADEDOKUN, Stella Odedina, Oladosu Ojengbede, Adeyinka Ademola, Temidayo Ogundiran, Dezheng Huo, Olufunmilayo Olopade, Imaria Agwai, Timothy Makumbi, Paul Ndom, Antony Gakwaya. A case control study of benign breast disease and breast cancer among indigenous African women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 624.
Abstract 631: High BMI in relation to low risk of lung cancer among never smokers
Authors: Luu Hung N. , Wang Renwei , Adams-Haduch Jennifer , Jin Aizhen , Koh Woon-Puay , Yuan Jian-Min
Published: August 2019

Background. Lean smokers have increased oxidative DNA damage relative to their non-lean counterparts, indicating their heightened susceptibility to tobacco carcinogens-induced DNA damage. Epidemiological association between body mass index (BMI) and lung cancer is inconclusive. We have reported that BMI is a protective factor for smoking-related lung cancer and so did a recent meta-analysis. Knowledge about the association between BMI and non-smoking related lung cancer is limited as this is rare in Western population. We therefore sought to investigate the association between BMI and the risk of never-smoking related lung cancer in an on-going prospective cohort study, the Singapore Chinese Health Study.

Methods. The current analysis used data from the Singapore Chinese Health Study, a cohort of 63,257 middle-aged and older Chinese men and women enrolled between 1993 and 1998. As of December 31, 2015, 2,001 study participants who were free of lung cancer at baseline developed lung cancer of whom 621 were never smokers. Cox proportional hazard regression method was used to calculate hazard ratio (HR) and the corresponding 95% confidence interval (CI) for lung cancer associated with BMI in never-smokers.

Results. Our results shown that increasing BMI was a protective factor for never-smoking related lung cancer and there is no interaction by gender. The respective HRs and 95% CIs were 0.66 (0.45-0.95) for overall and 0.60 (0.39-0.93) in female for those with BMI>27.5 compared to those with BMI<18.5. Even after eliminating those with exposure to any second-hand smoke in childhood or adulthood, the inverse association between BMI and the risk of never-smoking related lung cancer was stronger and significant (HR=0.31, 95% CI: 0.13-0.75; Ptrend=0.01). There was no difference by histologic subtypes (i.e., adenocarcinomas vs. squamous cell).

Conclusion. There was an inverse association between BMI and the risk of never-smoking related lung cancer and there is no interaction by gender for this association. This association was also not different by histologic subtypes.

Citation Format: Hung N. Luu, Renwei Wang, Jennifer Adams-Haduch, Aizhen Jin, Woon-Puay Koh, Jian-Min Yuan. High BMI in relation to low risk of lung cancer among never smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 631.
Abstract 650: Gut microbiota population may be used to predict chemotherapeutic responsiveness in triple negative breast cancer
Authors: Bawaneh Alaa , Wilson Adam S. , Clear Kenysha YJ , Chiba Akiko , Cook Katherine L.
Published: August 2019

Triple negative breast cancer (TNBC) accounts for 15-20% of all breast cancers and predominately affects young and minority women. TNBC is characterized by a high recurrence rate, with about 34% of TNBC patients relapsing around 2.6 years. This type of breast cancer lacks targeted therapy options and is limited to chemotherapy treatment options. The purpose of our study was to determine whether gut microbiota populations correlate with chemotherapeutic responsiveness and may be a predictive biomarker of outcome. Moreover, we want to determine the impact of targeting the microbiome on chemotherapy efficacy. In this study, 8-week old female BALB/c mice were injected with TNBC 4T1-luciferase cells into their L4/5 mammary fat pad. Once tumors developed, mice were either untreated (control group), treated with 1 x weekly 2.5 mg/kg IV doxorubicin (DOX), or treated with doxorubicin + antibiotics (mixture of streptomycin, ampicillin, and colistin in the drinking water to ablate host bacterial populations). Tumors were collected at the end of the study. Fecal samples were collected at time point 0 weeks (T0; before therapy when tumors were approximately 100 mm3) and time point 4 weeks (T4; after treatment). We subdivided the doxorubicin treated group into DOX-responders (tumors stopped growing or shrank) or DOX-nonresponders (tumors continued to grow on treatment). Tumors from the DOX-responders and DOX + antibiotics groups were significantly smaller and mice from these groups displayed reduced lung weight, suggesting decreased lung metastatic burden. 16S-bacterial sequencing analysis was performed on breast tumor tissue and feces. We demonstrate that at T0, elevated fecal Ruminococcus correlates with DOX-nonresponsiveness. Furthermore, at T4, we show increased fecal abundance of Oscillospira and Bacteroidales are associated with better therapeutic outcome. Protein analysis of primary 4T1 breast tumor tissue indicate a significant elevation of apoptosis (cleaved caspase-3 protein levels) in DOX-responders and DOX + antibiotic treated mice. We also stained breast tumor tissue and lung tissue for bacteria to confirm presence of microbiota by immunohistochemistry. Taken together our data demonstrates that chemotherapy efficacy is modulated by the microbiome. Moreover, fecal microbiota populations could be used as a predictive biomarker of chemotherapeutic responsiveness and suggests that modulation of the gut microbiome through dietary or probiotic interventions may affect therapeutic outcomes.

Citation Format: Alaa Bawaneh, Adam S. Wilson, Kenysha YJ Clear, Akiko Chiba, Katherine L. Cook. Gut microbiota population may be used to predict chemotherapeutic responsiveness in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 650.
Abstract 652: Racial/ethnic differences in BRCA testing and test results among adult women
Authors: Guo Fangjian , Fuchs Erika L. , Berenson Abbey B. , Kuo Yong-Fang
Published: August 2019

Introduction: BRCA mutation testing has been recommended for targeted, individualized cancer prevention and treatment among women whose family histories or ethnic backgrounds are associated with increased risks for BRCA mutations. This study was to assess BRCA testing in different racial/ethnic groups in the US.

Methods: We used data from ClinformaticsTM Data Mart (CDM) Electronic Health Records. We included 134,827 women 18-65 years old with BRCA testing results from 1/1/2015-9/1/2017. BRCA testing rates and test result positive rates were calculated by race/ethnicity. Women with positive test results had a high risk for developing susceptible cancers - breast or ovarian cancer. As we only had data through 9/1/2017, we calculated annual test rates based on data in 2016.

Results: The BRCA mutation test rate in 2016 was highest among non-Hispanic Whites (582 per 100,000), while it was 313 per 100,000 in non-Hispanic Black women, 310 per 100,000 in Hispanic Women, and 281 per 100,000 in women of other races/ethnicities. Percentage of positive results was lowest among non-Hispanic White women tested (75.7%), and highest among non-Hispanic Black test takes (85.1%). After adjusting for age, region of residence, education, income, and family history of breast or ovarian cancer, adjusted odds ratio for having a positive test among non-Hispanic Black women tested vs. non-Hispanic White women tested was 1.71, 95% confidence interval 1.61-1.82, and adjusted odds ratio for Hispanics vs non-Hispanic Whites was 1.21, 95% confidence interval 1.13-1.31.

Conclusions: There are significant differences in test utilization and test results. Test utilization was highest in non-Hispanic Whites, who were also less likely to have a positive test result. Non-Hispanic Black women tested were more likely to have a positive test result, suggesting a more stringent test selection criteria for this underserved population.

Citation Format: Fangjian Guo, Erika L. Fuchs, Abbey B. Berenson, Yong-Fang Kuo. Racial/ethnic differences in BRCA testing and test results among adult women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 652.
Abstract 658: Antiproliferative effects of type II diabetes agents in Fanconi derived oral squamous carcinoma
Authors: Miller Kim , Wuertz Beverly , Potter David , Ondrey Frank G.
Published: August 2019

Fanconi anemia is a rare disease characterized by bone marrow failure requiring transplantation at a young age. Patients with Fanconi Anemia are at risk for the development of squamous cell carcinomas of the skin and mucosal surfaces at risks several hundred fold higher than control populations and these malignancies can pursue an aggressive, often fatal, course. Our group has been interested in repurposing Type 2 diabetes agents for oral cancer prevention and treatment. Presently, we examined the effects of the thiazolidinedione drug, pioglitazone, and an experimental biguanide, N1-hexyl-N5-benzyl-biguanide (HBB), on the proliferation of Fanconi-derived oral carcinoma cells. We incubated MOP FA1,a, VU-1131, and VU-1365 b, and C squamous cell carcinoma cell lines with vehicle controls or the thiazolidinedione pioglitazone or biguanide (HBB). We found dose-dependent decreases in cellular proliferation in all three Fanconi-derived cell lines at physiologically relevant concentrations (10 - 50 µM) after 1 to 3 days in several experiments. The effects were not due to simple cytotoxicity as judged by trypan blue staining. In other non-squamous cell lines of cervical and oral cavity origins we have previously discovered similar effects. These agents affect PPAR gamma associated pathways (pioglitazone) or mTOR and mitochondrial glucose metaboliscm pathways (HBB). Since Fanconi anemia patients are highly susceptible to DNA damaging effects of cytotoxic chemotherapy, these classes of agents might be attractive in Fanconi Anemia oral cancer treatment or prevention. Metformin, another biguanide, is currently postulated to delay bone marrow failure in the Fanconi population and is currently in use in an early phase clinical trial. Our results may, therefore, be attratciveattractive for oral cancer prevention and treatment in this population, as they are well tolerated. Further examination of molecular mechanisms will likely generate putative pharmacodynamics markers for future clinical trials.

Citation Format: Kim Miller, Beverly Wuertz, David Potter, Frank G. Ondrey. Antiproliferative effects of type II diabetes agents in Fanconi derived oral squamous carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 658.
Abstract 661: Adipose specific monocyte chemotactic protein-1 knockdown reduces pulmonary metastasis of Lewis lung carcinoma in mice
Authors: Sundaram Sneha , Yan Lin
Published: August 2019

Adipose accumulation is a strong indicator of detrimental health outcomes because adipose tissue produces pro-inflammatory adipokines that participate in many pathological processes including cancer. Monocyte chemotactic protein-1 (MCP-1) is a potent adipokine and body adiposity is positively correlated with adipose MCP-1 expression. This study tested the hypothesis that adipose-produced MCP-1 contributes to metastasis. In a metastasis model of Lewis lung carcinoma (LLC), male adipose MCP-1 knockdown (MCP-1-/-) and wild-type (WT) mice were fed the standard AIN93G diet or a high-fat diet (HFD) containing 16% or 45% of energy from soybean oil. The duration of experimental feeding was 11 weeks. The expression of MCP-1 in epididymal adipose tissue was analyzed by quantitative real-time PCR and ELISA. Pulmonary metastases from a primary tumor, established by subcutaneous injection of LLC cells, were the primary endpoints. There was no significant difference in fat body mass between MCP-1-/- and WT mice fed the same diet. There were no differences in energy intake among the four groups. The HFD increased and adipose MCP-1 knockdown decreased MCP-1 mRNA and protein in adipose tissue compared to their respective controls. The HFD increased the number of metastases formed in the lungs in WT mice. The number of metastasis was lower in MCP-1-/- mice fed the HFD than in WT mice fed the HFD but was higher compared to WT mice fed the AIN93G diet. The volume of metastases was smaller in MCP-1-/- mice than in WT mice, regardless of diet. Adipose MCP-1-/- mice, compared to WT mice, exhibited lower concentrations of insulin, pro-inflammatory adipokines (leptin, plasminogen activator inhibitor-1, and resistin), and angiogenic markers (vascular endothelial growth factor, hepatic growth factor, and angiopoietin-2) in plasma. These results indicate that adipose MCP-1 knockdown may lead to the down-regulation of inflammatory and angiogenic pathways during malignant spread. We conclude that adipose MCP-1 deficiency attenuates HFD-enhanced pulmonary metastasis of LLC and supports our hypothesis that adipose-produced MCP-1 contributes to malignant spread.

Citation Format: Sneha Sundaram, Lin Yan. Adipose specific monocyte chemotactic protein-1 knockdown reduces pulmonary metastasis of Lewis lung carcinoma in mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 661.
Abstract 665: Cancer neoantigen and autoantibody discovery with PEP functional proteomics platform
Authors: Wang Xing , Landon Trevor
Published: August 2019

Proteins play essential roles in numerous biological processes and being able to pinpoint functional differences between cell or tissue samples can greatly aid in understanding disease processes and metabolic changes. The PEP technology allows systematic analysis of protein functions within a proteome. Hundreds of functional proteins can be separated and functionally assayed to generate a comprehensive three-dimensional landscape of protein families such as protein kinases, phosphatases, proteinases and oxido-reductases. This information can then be integrated into other genomic and proteomic knowledge bases to provide further insight of important biological processes such as cancer development and aging. Array Bridge has developed a 2-Dimensional separation technology called PEP (Protein Elution Plate) that can separate proteins into two-dimensional display and efficiently recover all the separated proteins into 384-microplates that can be probed in a standard ELISA format with high throughput. Our initial studies using breast cancer cell line proteins indicated that the PEP technology can be used to separate the proteins efficiently and probed with plasma from cancer patient for autoantibody discovery. Using the autoantibodies exist in the cancer patient, strong signals can be detected from a subset of proteins from the breast cancer cell line. We also use this platform to separate proteins from the cancer cell lines and probed with the plasma from the same cancer patient to identify the neoantigen candidates with mass spectrometry identification, the identified neoantigens can be used for the development of personalized immunotherapy such as CAR-T and other treatments.

Note: This abstract was not presented at the meeting.

Citation Format: Xing Wang, Trevor Landon. Cancer neoantigen and autoantibody discovery with PEP functional proteomics platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 665.
Abstract 669: Dynamic modeling of responses to PDL-1 inhibitors in non-small cell lung cancer: implications for precision combination therapy
Authors: Tavassoly Iman
Published: August 2019

Immunotherapy by immune checkpoint blockade has had a promising impact on the treatment of Non-Small Cell Lung Cancer (NSCLC). Although single and combination therapy with checkpoint inhibitors such as PDL-1 inhibitors have been proved to be effective in making the survival of patients with NSCLC longer, but there is always a population of patients which shows resistance to these therapeutic modalities. The source of resistance emerges from signaling pathways and regulatory systems in tumors and the immune system, but the dynamics among tumor components, T cells, and tumor microenvironment contribute in this process as well. To understand the complex system of these interactions, a mathematical model of these pathways and interactions are presented using Ordinary Differential Equations (ODEs). The specific characteristics of NSCLC tumors including metabolic reprogramming have been considered in this model. The model is capable of decoding patient-to-patient variabilities regarding responses to PDL-1 inhibitors, and parameter-sensitivity analysis shows the vulnerable biomarkers to be targeted by combination therapy to give better results in killing the tumor cells. The model can be integrated with PK/PD models to provide an in-silico platform for investigating the therapeutic responses in NSCLC for precision oncology.

Note: This abstract was not presented at the meeting.

Citation Format: Iman Tavassoly. Dynamic modeling of responses to PDL-1 inhibitors in non-small cell lung cancer: implications for precision combination therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 669.
Abstract 675: Network modeling of drug resistance mechanisms and drug combinations in breast cancer
Authors: Zañudo Jorge Gómez Tejeda , Mao Pingping , Montero Joan , Xu Guotai , Kowalski Kailey J. , Johnson Gabriela N. , Baselga José , Scaltriti Maurizio , Letai Anthony G. , Wagle Nikhil , Albert Reka
Published: August 2019

Durable control of invasive solid tumors is thwarted by the lack of knowledge of effective drug combinations and of the acquired and intrinsic resistance mechanisms of drugs. In an effort to tackle this problem, the SU2C-NSF-TVF Drug Combination Convergence Team is using mechanistic models of cancer cell signaling based on therapeutic and cell line data in order to identify elements within cancer cells that might eventually be exploited through therapeutic combinations.

Here we present a comprehensive mechanistic network model of signal transduction in ER+ PIK3CA-mutant breast cancer. Focusing on PI3K inhibitors, the model recapitulates known resistance mechanisms and predicts other possibilities for resistance: loss of RB1, FOXO3, P27, or PRAS40. To test these predictions, we analyzed genome-wide CRISPR screens of two breast cell lines in the presence of PI3K inhibitors (BYL719 and GDC0032) and found that the predicted genes (RB1, FOXO3, P27, and PRAS40) were significantly enriched in the screens. Some of these resistance genes (e.g. loss of RB1) were found to be cell-line specific and follow-up experiments in RB1-KO cells confirmed the cell-line-specific nature of PI3K-inhibitor resistance. The model also reveals known and novel combinatorial interventions that are more effective than PI3K inhibition alone. For example, the model predicts that the combination of PI3K inhibitors with inhibitors of anti-apoptotic protein MCL1 would be effective. Follow up experiments in cell lines using cell viability assays, cell death analyses, and dynamic BH3 profiling experiments to determine increases in apoptotic priming upon treatment confirmed that MCL1 inhibitors (S63845) enhance the effect of PI3K inhibitors (BYL719) and that this combinatorial effect is cell-line-specific, similarly to what was found in the resistance genes case.

In conclusion, the model predicted drug resistance mechanisms and effective drug combinations, some of which were verified experimentally and found to be cell-line-specific. Next iterations of the model will incorporate the identified discrepancies and newly identified resistance mechanisms to drugs of clinical interest.

Citation Format: Jorge Gómez Tejeda Zañudo, Pingping Mao, Joan Montero, Guotai Xu, Kailey J. Kowalski, Gabriela N. Johnson, José Baselga, Maurizio Scaltriti, Anthony G. Letai, Nikhil Wagle, Reka Albert. Network modeling of drug resistance mechanisms and drug combinations in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 675.
Abstract 679: Quantitative systems pharmacology modeling of immunotherapies in B-cell acute lymphoblastic leukemia
Authors: Demin Oleg , Nikitich Antonina , Demin Oleg
Published: August 2019

Introduction: Multiple T-cell engaging antibody-based molecules and CAR-T therapies are in development for the treatment of B-cell acute lymphoblastic leukemia (B-ALL). Moreover, two therapies have already been approved by FDA: blinatumomab (CD19/CD3 bispecific T-cell engager) and tisagenlecleucel (anti-CD19 CAR-T therapy). This work employs quantitative systems pharmacology (QSP) modeling approach to investigate factors affecting outcomes of administration of such types of therapy.

Methods: Model was developed on the basis of Immune Response Template (QSP model of immune system). It describes leukemic blasts, hematopoiesis of normal B cells, CD4+ and CD8+ T-cell subsets, and cytokines (IL-6, TNFα, IFNγ, TGFβ, etc.) in bone marrow and blood. The model takes into account the different level of expression of CD19 on various subsets of normal B cells and leukemic cells. Model parameters were estimated and fitted against in vitro, in vivo human data. Small part of clinical data on blinatumomab and anti-CD19 CAR-T therapies was used for model calibration, other part was used for model validation.

Results: Our model reproduced clinically relevant blinatumomab and anti-CD19 CAR-T hallmark data including depletion of CD19+ cells, T-cell subset dynamics and cytokine release post infusion. The model successfully described the clinically observed phenomenon on progressive cytokine release attenuation with subsequent blinatumomab treatment cycles. It confirmed the dose step strategy for decreasing initial cytokine release. Model showed that treatment outcome is very sensitive to target expression, level of immune cells, disease progression rate and expression of PD-L1 on leukemic cells. The proportion of CD19+ and CD19- leukemic blasts before treatment can be used as a biomarker to predict probability of relapse in patients to stratify patients.

Conclusions: This work provides a quantitative modeling framework to predict responses to immunotherapies in B-ALL on the basis of realistic baseline conditions and reveal the factors affecting treatment outcome.

Citation Format: Oleg Demin Jr, Antonina Nikitich, Oleg Demin. Quantitative systems pharmacology modeling of immunotherapies in B-cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 679.
Abstract 687: Implementation of inter-patient variability in semi-mechanistic model of melanoma treatment with vemurafenib
Authors: Shchelokov Dmitry , Demin Oleg , Demin Oleg
Published: August 2019

Introduction: The number of parameters in quantitative systems pharmacology (QSP), mechanistic and semi-mechanistic models is greater than in conventional PK/PD models. That is why it is not possible to implement inter-patient variability using only clinical data. The objective of this study was to describe inter-patient variability in the semi-mechanistic model of melanoma treatment with vemurafenib, a BRAF inhibitor, on the basis of published human in vitro, in vivo and clinical data, and to predict overall response from phase 2 clinical trial.

Methods: Model described melanoma progression and its treatment with vemurafenib. It includes (i) proliferation, apoptosis, and transition between states (c-MET negative/positive and sensitive/resistant to BRAF inhibitor) of cancer cells; (ii) HGF effect on proliferation of melanoma cells; (iii) PK/PD of vemurafenib. Various types of data were used to extract inter-patient variability, for example: (a) in vitro data on effect of vemurafenib on melanoma cell lines [1]; (b) in vivo data on tumor growth in melanoma patients without treatment [2]; (c) in vivo data on HGF level in blood plasma of melanoma patients [3].

Results: Different virtual patients developed by the model reproduce all types of tumor response to vemurafenib monotherapy according to RECIST criteria: complete response, partial response, stable disease and progressive disease. To evaluate the predictive ability of the model in a quantitative manner we compared results of simulation of virtual patients population with clinical outcomes. An overall response rate was 70% in the model versus 53% (95% CI, 44 to 62) observed in phase 2 clinical trial [4]. Overestimation can be explained by intermittent administration and dose reduction in case of adverse events in clinical trials which were not taken into account in the model.

Conclusions: Our work establishes the benefit of using of in vitro and in vivo data in addition to clinical data to predict the variability in treatment outcomes of cancer patients.

[1] Stones et al. Front Genet. 2013 May 8;4:66

[2] Hartung et al. PLoS One. 2017 May 4;12(5):e0176080

[3] Hügel et al. Melanoma Res. 2016 Aug;26(4):354-60

[4] Sosman et al. N Engl J Med. 2012 Feb 23;366(8):707-14

Citation Format: Dmitry Shchelokov, Oleg Demin Jr, Oleg Demin. Implementation of inter-patient variability in semi-mechanistic model of melanoma treatment with vemurafenib [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 687.
Abstract 691: Simulating TTFields-induced temperature changes within a patient’s brain - a proof of concept study
Authors: Naveh Ariel , Bomzon Ze'ev
Published: August 2019

Introduction: TTFields is an antimitotic cancer treatment that utilizes low intensity (1-3 V/cm) alternating electric fields in the intermediate frequency (100-300 kHz) that are delivered in two orthogonal directions using 2 pairs of transducer arrays. TTFields are currently approved for Glioblastoma Multiforme (GBM). Preclinical studies show that the effect of TTFields is intensity-dependent with a therapeutic threshold of 1 V/cm, and that as the intensity rises so does the efficacy. However, delivery of high field intensities could result in temperature increases within the body that lead to thermal damage to tissue. In practice, during treatment with TTFields, tissue heating is limited by a closed loop that adjusts the delivery of TTFields to ensure that skin temperature remains within the safety limits. Since heating limits the intensity at which TTFields is delivered, accurate models of tissue heating during TTFields therapy could provide insights into new approaches for the delivery of TTFields. Since measuring the temperature spatial distribution within a patient’s brain is extremely challenging, simulating the heat flow within the head during treatment is a more practical approach. Here, we present preliminary results from a study aimed at developing a valid computational model of heat transfer in the head during TTFields therapy.

Method: A realistic computational head model of a healthy male was used in this study. Virtual transducer arrays were placed on the head. To simulate the delivery of TTFields to the brain, we used ZMT's Sim4Life v4.0 electro-quasi-static solver. The results of the electric field simulation were then used as heat source for the heat simulation. The heat simulation solves the Pennes bio-heat model, taking into account tissue heat capacity and conductivity, and also accounting for heat convection through blood perfusion. Sensitivity analysis was performed to establish the sensitivity of the temperature distribution within the brain to the thermal properties of the various tissue types.

Results: Average temperatures within the brain tissue were well below 38° C for all simulations. Temperature distributions within the brain were highly sensitive to the perfusion coefficient assigned to the cerebrospinal fluid as well as other tissues.Conclusions: We have established a computational framework for investigating heat transfer in the brain during TTFields therapy. Further work is needed to correctly establish the thermal properties of the various tissue types. This may require experimental measurements in which the heat transfer model is fine-tuned and validated.

Citation Format: Ariel Naveh, Ze'ev Bomzon. Simulating TTFields-induced temperature changes within a patient’s brain - a proof of concept study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 691.
Abstract 693: Deep learning analysis of circulating tumor DNA identified a pan-tumor molecular subtype with enhanced response to durvalumab (anti-PDL1)
Authors: Wu Song , Sridhar Sriram , Si Han , Kuziora Michael , Englert Judson , Abdullah Shaad E. , Dennis Philip , Xiao Feng , Gao Guozhi , Ranade Koustubh , Higgs Brandon W.
Published: August 2019

Tumor mutation burden (TMB) has emerged as a promising predictive biomarker for anti-PD1/L1; however, whether somatic mutations in specific genes can sensitize to immunotherapy is poorly understood. We used deep learning to identify molecular subtypes from mutations detectable in circulating tumor DNA (ctDNA) and associated these with outcomes with anti-PDL1 (durvalumab) and durvalumab + anti-CTLA4 (tremelimumab) therapy.

Patient blood samples from 4 nonrandomized phase 2 trials evaluating durvalumab (NCT01693562, 1L+ solid tumors; NCT02087423, 3L+ NSCLC) or durvalumab+ tremelimumab (NCT02000947, 2L+ NSCLC; NCT02261220, 2L+ solid tumors) were sequenced with the Guardant 360 assay of 73 genes. CtDNA mutations were examined pre-treatment in a discovery cohort of 818 patients composed of >15 tumor types and validated in a cohort of 94 patients composed of >5 tumor types. Deep learning neuron network was computed using Tensorflow to identify 4 unique molecular subgroups. Kaplan-Meier analysis was calculated and objective response rates (ORR) were assessed with RECISIST v1.1.

The subgroups consisted of: DS1 (N = 215/818, 26%) enriched in RB1 mutations (17%) and low TMB, DS2 (N = 237/818, 29%) enriched in ARID1A (33%), NFE2L2 (8%), and cKIT (13%) mutations, DS3 (N = 251/818, 31%) enriched in EGFR, ERBB2, BRAF and STK11 mutations, and DS4 (N = 115/818, 14%) enriched in TERT, FGFR3, and PIK3CA mutations. In the discovery cohort, the DS2 subgroup had most improved outcomes (mOS=24.6 months, mPFS=3.7 months, ORR=27%) compared to the other 3 subgroups. DS1 subgroup had the worst outcomes (mOS=6.3 months, mPFS=1.6 months, ORR=10%), while the biomarker evaluable population (BEP, n=818) had ORR=17%. In the validation cohort, DS2 also had the most improved outcomes (mOS=not reached, mPFS=13.2 months, and ORR=64%), with the BEP (n=94) having an ORR=37%. PD-L1 was not correlated with any specific molecular subgroup, while an IFNg mRNA signature trended with correlation with subgroup DS2.

Deep learning analysis of ctDNA identified a molecular subgroup with enhanced response to anti-PDL1 treatment in multiple tumor types.

Citation Format: Song Wu, Sriram Sridhar, Han Si, Michael Kuziora, Judson Englert, Shaad E. Abdullah, Philip Dennis, Feng Xiao, Guozhi Gao, Koustubh Ranade, Brandon W. Higgs. Deep learning analysis of circulating tumor DNA identified a pan-tumor molecular subtype with enhanced response to durvalumab (anti-PDL1) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 693.
Abstract 694: Mathematical modeling of stromal fibroblast-mediated adaptive resistance to bortezomib in multiple myeloma
Authors: Eton Elliot , Kaveh Kamran , Khiste Sachin , Fernandes Andrea , Agarwal Ashima , Sengupta Shiladitya , Goldman Aaron
Published: August 2019

Understanding intrinsic and adaptive resistance is crucial to overcoming multiple myeloma chemotherapy failure. We recently demonstrated that standard chemotherapy can induce cancer cells to phenotypically transition to a transient state of dormancy and drug tolerance. Further, targeting cells precisely during this transition can thwart the emergence of adaptive resistance (Goldman, 2015). However, it is not yet understood how the stromal contexture may contribute to this chemotherapy-induced drug tolerance.

We developed a deterministic mathematical model containing a system of differential equations to examine how stromal fibroblasts temporally affect phenotypic switching between active and dormant, bortezomib-tolerant cancer cell states. The equations describe the total growth rate of each cell state population, which is influenced by that population’s count and baseline growth rate, the frequencies of transitions to and from the other cell state, the drug treatment concentration, and the population carrying capacity. The model also establishes that the presence of fibroblasts affects the frequency of transitions between the cell states. This framework is calibrated to in vitro data, and model simulations predict that bortezomib-tolerant myeloma cells may escape more quickly from dormancy and proliferate when they are incubated in the presence of fibroblasts than in their absence. This prediction is supported by preliminary experimental observations. The mathematical model could be adapted to predict how stromal fibroblasts, or the tumor microenvironment generally, may influence phenotypic switching in other cancers.

Citation Format: Elliot Eton, Kamran Kaveh, Sachin Khiste, Andrea Fernandes, Ashima Agarwal, Shiladitya Sengupta, Aaron Goldman. Mathematical modeling of stromal fibroblast-mediated adaptive resistance to bortezomib in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 694.
Abstract 696: High-throughput screening of therapeutic combinations against ovarian cancer
Authors: Zhou Peng , Wong Alan S.
Published: August 2019

Applying synergistic drug combinations can increase efficacy of cancer treatment. However, conventional methods for identifying those combinations involve testing of every possible combination including different dosages for each agent, are difficult to scale due to the huge amount of efforts and costs needed. To tackle this problem, we have developed CombiGEM-CRISPR (combinatorial genetics en masse-CRISPR) to enable high-throughput assembly and screening of pair-wise gene combinations. By applying CombiGEM-CRISPR,phenotypes of combinatorial gene knockouts could be used to predict the effects of drug inhibitor combinations targeting the matching gene products. We designed a pair-wise sgRNA library comprising 25,281 combinations for interrogating 52 genes that are overexpressed in ovarian cancers. By pooled evaluation of their effects on cell proliferation, our screening identified new combinations that inhibit ovarian cancer cell growth. Therefore, our work accelerates the discovery of new therapeutic options against ovarian cancer through applying CombiGEM-CRISPR.

Citation Format: Peng Zhou, Alan S. Wong. High-throughput screening of therapeutic combinations against ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 696.
Abstract 78: IGF-1R inhibition activates p70S6K1 to promote survival via MEK1/2 activation in colon cancer cells
Authors: Wang Qing , Yang Hsin-Sheng
Published: August 2019

The insulin-like growth factor 1 receptor (IGF-1R) is a heterotetramer with tyrosine kinase activity, composed of two α subunits containing the ligand-binding site and two β subunits harboring the tyrosine kinase activity. Upon binding with ligands (IGF-1, IGF-2, and insulin), IGF-1R leads to activation of downstream pathways including PI3-K/AKT and Ras/MAPK, two frequently activated pathways for promoting cell survival and proliferation in various cancers including colorectal cancer. Immunohistochemical studies revealed that IGF-1R is over-expressed in colorectal cancer tissues compared to the adjacent normal tissues. Most importantly, a higher expression of IGF-1R is associated with a higher grade and stage in colorectal cancer patients. Since the IGF-1R signaling pathway plays an essential role in development, maintenance, and survival of tumors, many small molecule compounds and antibodies targeting IGF-1R have been developed. Unfortunately, these anti-IGF-1R agents demonstrate very limited efficacy in clinical trials, suggesting the existence of a mechanism to overcome the inhibitory effect of IGF-1R in cancer cells. In this study, we aim to understand the resistance mechanism of IGF-1R inhibition in colon cancer cells. Prolonged treatment of IGF-1R resistant colon cancer cells with IGF-1R inhibitors (OSI-906, BMS-754807, and GSK1838705A) stimulates p70S6K1 activation, a well-known kinase signaling for cell survival. We also found that p70S6K1 activation is independent of mutation of K-RAS and PIK3CA, frequently occurring in colorectal cancer. Genetic knockdown or pharmacologic inhibition of p70S6K1 efficiently suppresses cell viability in response to IGF-1R inhibition, indicating that p70S6K1 activation contributes to the survival of IGF-1R inhibitor-treated cells. In addition to the increased phosphorylation of p70S6K1, phosphorylation of MEK1/2 is also elevated in colon cancer cells with prolonged inhibition of IGF-1R. Knockdown of MEK1/2 results in reduction of p70S6K1 activation in response to IGF-1R inhibition and subsequently increases apoptosis, suggesting that MEK1/2 is involved in p70S6K1 activation for survival. Furthermore, the combination of BMS754807 and U0126, a MEK1/2 inhibitor, effectively decreases the cell viability and increases apoptosis. Our data suggest that inhibition of MEK1/2 enhances the anti-proliferation effects of IGF-1R inhibitors, pointing out a new direction for overcoming the resistance of IGF-1R inhibition in colorectal cancer.

Citation Format: Qing Wang, Hsin-Sheng Yang. IGF-1R inhibition activates p70S6K1 to promote survival via MEK1/2 activation in colon cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 78.
Abstract 863: Functions of FRAS1 as a driver gene of liver metastasis from gastric cancer analyzed by the genome editing technology
Authors: Umeda Shinichi , Kanda Mitsuro , Tanaka Haruyoshi , Sonohara Fuminori , Takami Hideki , Hattori Norifumi , Hayashi Masamichi , Tanaka Chie , Kobayashi Daisuke , Yamada Suguru , Nakayama Goro , Koike Masahiko , Fujiwara Michitaka , Kodera Yasuhiro
Published: August 2019

Background: The prognosis of patients with liver metastasis from gastric cancer (GC) is dismal and it remains a serious problem in the management of GC. To elucidate complex molecular mechanisms underlying formation of liver metastasis is necessary for development of novel therapeutic modality.

Methods: Transcriptome analysis of 57749 molecules with 4 groups (no recurrence, peritoneal recurrence, liver recurrence and nodal recurrence) was conducted to screen out the candidate molecules specific for liver metastasis. Subsequently, the stable knockout (KO) cells were established using the CRISPR/Cas9 system and cell functions, apoptosis, cell cycle, oxidative stress and cancer stemness were analyzed. PCR and antibody array analyses were conducted to identify the co-regulated molecules. Mouse subcutaneous xenograft models and liver metastasis models were generated to evaluate tumorigenicity of the KO cells in vivo. Tissue mRNA expression levels were determined by qRT-PCR in patients with stage II/III GC and correlated with recurrence patterns.

Results: Fraser extracellular matrix complex subunit 1 (FRAS1) was identified as a candidate molecule overexpressed specifically in the liver metastasis group. Proliferation, adhesion, invasion and migration abilities were suppressed in FRAS1-KO cells compared to the control cells. Cell cycle alternation, increased proportions of apoptotic cells, increased oxidative stress and decreased cancer stemness were also observed in FRAS1-KO cells. PCR array analysis revealed that FRAS1 mRNA expression was positively correlated with TGFB1, MAP1B, AHNKA and negatively correlated with BMP2. Pathway analysis demonstrated that expression of MUC1, Survivin, Ki67 and Met proteins were decreased in FRAS1-KO cells. The tumorigenicity of FRAS1-KO cells was reduced in a mouse subcutaneous model and more clearly in liver metastasis models. Patients with high FRAS1 mRNA expression had a significantly higher incidence of liver recurrences after curative gastrectomy.

Conclusion: Our results indicated that FRAS1 contributes to formation of liver metastasis from GC and is a potential therapeutic target.

Citation Format: Shinichi Umeda, Mitsuro Kanda, Haruyoshi Tanaka, Fuminori Sonohara, Hideki Takami, Norifumi Hattori, Masamichi Hayashi, Chie Tanaka, Daisuke Kobayashi, Suguru Yamada, Goro Nakayama, Masahiko Koike, Michitaka Fujiwara, Yasuhiro Kodera. Functions of FRAS1 as a driver gene of liver metastasis from gastric cancer analyzed by the genome editing technology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 863.
Abstract 9: Effect of C8-side chain on the cytotoxicity and NF-kB inhibitory capacity of pyrrolobenzodiazepines
Authors: Corcoran David B. , Lewis Thomas , Nahar Kazi S. , Fegan Christopher , Pepper Chris , Thurston David E. , Rahman Khondaker Miraz
Published: August 2019

Pyrrolobenzodiazepines (PBDs) have long been of interest in chemotherapeutic research as potential clinical agents. Recently, the conjugation of non-covalently interactive moieties to the C8-position of the PBD structure via a linker of variable length has emerged as a strategy to enhance the DNA sequence specificity of PBDs. This has led to the development of highly cytotoxic agents, which also act as inhibitors of transcription factors such as NF-κB. For example, GWL-78, a C8-linked PBD-Py-Py (Py = pyrrole) conjugate, has been shown to block interaction of the transcription factor NF-Y, and KMR-28-39, a C8-linked PBD-MPB conjugate with an affinity for GC-rich sequences of DNA inhibits activity of the transcription factor NF-κB. As up-regulation of NF-κB has been implicated in the development and progression of several cancer types, this may contribute to the high potency observed for PBD monomers such as KMR-28-39 (i.e., femtomolar IC50 values in some cell lines). In this study, the relationship between the cytotoxicity and transcription factor inhibition of a series of C8-linked PBD hybrid structures was explored. The systematic shortening of the non-covalent element of a C8-linked PBD conjugate, DC-1-92 led to the synthesis of a 19-member library of novel C8-PBD monomers. The critical elements of DC-1-92, which were required to render the molecule cytotoxic, were elucidated by an annexin V assay. The effects of shortening the non-covalent element of the molecule on transcription factor inhibitory capacity were also explored through an ELISA-based measurement of nuclear NF-κB subunit DNA binding following exposure of JJN3 cells to the synthesised molecules. While shortening the non-covalently interactive component of DC-1-92 had less of an effect than expected upon cytotoxicity, the shortening notably reduced the NF-κB inhibitory activity of the shortened analogues. DC-1-92, containing the longest non-covalently interactive C8-element, displayed the most effective inhibition of NF-κB, and effects upon nuclear p65, and RelB levels appeared to diminish in tandem with the shortening of the length of the C8 side chain. These data suggest that the length of the C8 side chain of PBD hybrid structures impacts upon the DNA binding of both canonical and non-canonical NF-κB subunits but this is independent of their cytotoxic effects.

Citation Format: David B. Corcoran, Thomas Lewis, Kazi S. Nahar, Christopher Fegan, Chris Pepper, David E. Thurston, Khondaker Miraz Rahman. Effect of C8-side chain on the cytotoxicity and NF-kB inhibitory capacity of pyrrolobenzodiazepines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 9.