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Background Symptom burden and reduced quality of life (QOL) are considerable hurdles in oncology. The authors used the Patient-Reported Outcomes Measurement Information System (PROMIS), which assesses physical and psychosocial health, to establish a mean symptom burden, examine potential drivers, and characterize severe symptom burden in breast cancer patient subgroups with the goal of characterizing stage IV patient QOL and triaging patients to individualized supportive care services. Methods New patients at the University of California San Francisco Breast Care Center received questionnaires with 8 PROMIS domains: depression, anxiety, fatigue, sleep-related impairment, sleep disturbance, cognitive function, cognitive abilities, and physical function. PROMIS values were scored with the HealthMeasures service and were compared by age, cancer stage, and educational status. Results Stage IV patients with breast cancer (n = 169) reported higher depression and fatigue and worse cognitive function, cognitive abilities, and physical function than patients with stage 0 to III disease (n = 2577). As age increased, cognitive function impairment, depression, anxiety, and sleep-related symptoms decreased. More educated patients showed better physical function and less severe sleep disturbance and fatigue. Across all subgroups, patients with high anxiety had the greatest probability of worse symptom burden and function in other domains. Conclusions This study provides an additional set of PROMIS population estimates across breast cancer demographic groups. The analysis of a large stage IV population reinforces that metastatic patients have impaired QOL across multiple domains. Because anxiety emerged as a potential driver of impaired QOL in other domains, earlier interventions to reduce anxiety could improve QOL overall. These analyses will help to determine appropriate thresholds of intervention. Lay summary Patients receiving treatment for breast cancer can experience decreased quality of life. This study characterized differences in self-reported quality of life among patients of different ages, with different stages of cancer, and with different educational backgrounds. This study also examined the effect of decreased quality of life in one area (eg, anxiety) on another area (eg, difficulty in sleeping). Patients who were younger, had not attended college or technical school, or had stage IV cancer tended to have worse quality of life. Patients who had high levels of anxiety also tended to have high levels of impairment in other areas.

Introduction: One of the principal limiting factors to achieving cures in patients with cancer is drug resistance. Drug repositioning is the application of FDA-approved drug compounds for novel indications beyond the scope of the drug’s original intended use. This approach offers advantages over traditional drug development by reducing development costs and providing shorter paths to approval, as drug safety has already been established during the drug’s original regulatory process. One approach for computational drug repositioning involves generating a disease gene expression signature and then identifying a drug that can reverse this disease signature. In this study, we extracted drug resistance signatures from the I-SPY 2 TRIAL by comparing gene expression profiles of responder and non-responder patients stratified by treatment and molecular subtype. We then applied our drug repositioning pipeline to predict compounds that can reverse the gene expression profiles of these drug resistance signatures. We hypothesize that reversing these drug resistance signatures will resensitize tumors to treatment and improve patient outcome. Methods: We first generated the drug resistance signatures by performing differential expression between responders (RCB 0/I) and non-responders (RCB III) within treatment arms and molecular subtypes. An optimal log fold-change cutoff was selected for each signature by identifying the cutoff that best separates the responder and non-responder samples using k-means clustering. We then applied our drug repositioning pipeline to identify compounds that significantly reverse these signatures using the drug perturbation profiles generated in a breast cancer cell line in the Connectivity Map v2 dataset. Briefly, the pipeline uses a non- parametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov (KS) statistic to assess the enrichment of resistance genes in a ranked drug gene expression list. Significance of each prediction is estimated from a null distribution of scores generated from random gene signatures. Results: We found that few individual genes are shared among the resistance signatures across the treatment arms and molecular subtypes, with the most common genes present in only 5/17 of the treatment arm and molecular subtype groups. At the pathway-level, however, we found that immune-related pathways are generally enriched among the responders and estrogen-response pathways are generally enriched among the non-responders. Although most of our drug predictions are unique to treatment arms and molecular subtypes, our drug repositioning pipeline identified the selective estrogen receptor degrader (SERD) fulvestrant as a compound that can potentially reverse resistance across a majority of the treatment arms and molecular subtypes. Conclusion: We applied our drug repositioning pipeline to identify novel agents to sensitize drug-resistant tumors in the I-SPY 2+ clinical trial and identified a SERD, fulvestrant, as a potential candidate for multiple molecular subtypes and treatment arms. Citation Format: Katharine Yu, Amrita Basu, Christina Yau, Denise Wolf, Gillian Hirst, Laura Sit, Nicholas O’Grady, Thelma Brown, I-SPY 2 TRIAL Investigators, Angela DeMichele, Don Berry, Nola Hylton, Doug Yee, Laura Esserman, Laura van 't Veer, Marina Sirota. Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatment arms and molecular subtypes [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS11-04.

Mechano-activation as a stimuli response in 4D printing offers advantages such as orthogonality to other stimuli and control over the magnitude of applied force. Herein, we demonstrate mechanically...

Background: Breast cancer remains the most frequently diagnosed cancer among women worldwide, accounting for a quarter of all diagnoses. Despite advances in treatment and symptom management, the majority of women will experience some form of drug-related toxicity, psychosocial distress, and subsequent impairments in their quality of life (QoL). Distress and impairments in QoL can interfere with treatment adherence, while engagement in health promoting behaviors and effective management of symptoms has been associated with improved QoL, adherence and increased survival. The utilization of QoL or other Patient Reported Outcome (PRO) measures in clinical trials remains inconsistent, and no uniformly accepted measure exists to integrate QoL data into the assessment of therapeutic agents. There are two goals of the I-SPY 2 QoL Pilot Study: 1) To demonstrate the reporting of an integrated utility-based QOL score, the PROPr, within a novel longitudinal approach that provides a single numerical index of QoL; 2) Generate a Clinical Benefit Index (CBI), a single composite score that integrates the longitudinal PROPr score with a clinical efficacy score, RCB index, to provide a measure that could go beyond clinical efficacy in the evaluation of therapeutic agents in the I-SPY 2 TRIAL. Methods: Study participants were part of the I-SPY 2 TRIAL assessing novel neoadjuvant therapies added to standard chemotherapy in the treatment of Stage 2/3 breast cancer. Participants completed a validated QoL measure at three time points: baseline, prior to surgery, and 1-month post-surgery. QoL was assessed using the NIH PROMIS measure (physical function (four items), anxiety (eight items), depression (eight items), fatigue (eight items), applied cognition (eight items) and social roles (four items)) and results at each time point used to calculate the PROPr, a single utility-based index score to assess overall quality of life. PROPr index utility scores were used to generate a single longitudinal QoL score based on area under the curve modeling. Clinical efficacy was assessed based on the residual cancer burden (RCB) observed at the time of surgery. The CBI was generated by plotting RCB index against the longitudinal PROPr index for each participant and study arm. Results: Only a fraction (n=107) of all patients had complete data across study timepoints and were included in our analyses, and thus our data represent a proof of concept. Patients on the control arm were treated with Paclitaxel followed by anthracycline (AC). Patients in the pilot were assigned either the control arm or six experimental drug arms. The longitudinal PROPr utility index demonstrated a range of outcomes, with some arms more challenging to tolerate, and others much better, ranging from 0.67 to 1.16. The RCB index of the seven study arms ranged from 0.49 to 1.99. The CBI, an integration of the longitudinal PROPr and RCB indexes, also demonstrated a range from 0.43 to 1.60. Conclusion: We are reporting the development of a novel, valid and standardized QoL assessment that should be a routine part of clinical trials in oncology. This proof of concept study suggests that that calculation of the CBI is feasible and can reveal differences in the clinical profiles of therapeutic agents, both in terms of QoL and overall integration of clinical efficacy and QoL. The CBI represents a novel approach to providing summary data that can be easily interpreted as part of clinical trial outcome data. Ideally, these integrated assessments would provide a more comprehensive evaluation of investigational therapies, and ultimately help inform treatment decision discussions between patients and providers. Moving forward, electronic PRO data will be collected as part of routine care in the I-SPY 2 TRIAL, thus enabling the longitudinal PROPr and CBI scores to be generated for every agent evaluated. Citation Format: Amrita Basu, Errol J. Philip, Barry Dewitt, Janel Hanmer, Aheli Chattopadhyay, Christina Yau, Smita Asare, Karyn Digiorgio, Ruby Singhrao, Adam Asare, Jane Perlmutter, I-SPY 2 Consortium, Michelle Melisko, Laura Esserman. The clinical benefit index: A pilot study integrating treatment efficacy and quality of life in oncology clinical trials [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-12-06.

Background: While the side effects of anthracycline and taxane based chemotherapy are well characterized, introduction of experimental agents and immunotherapy in the neoadjuvant and adjuvant setting may significantly alter the toxicity profiles of these regimens, resulting in short and long-term changes in patient quality of life (QOL). Trial Design: I-SPY 2 is a phase 2 trial investigating novel targeted therapies and immunotherapy in combination with standard chemotherapy in the neoadjuvant setting for Mammaprint high-risk stage 2 and 3 breast cancers. A QOL sub-study was introduced into the I-SPY 2 trial platform in 2012. All patients who consent to screen for the I-SPY 2 trial receive a baseline QOL questionnaire. Patients who consent to the treatment phase of I-SPY 2 also complete questionnaires on the first day of treatment, mid-way through neoadjuvant treatment, prior to surgery, and then 1, 6, 12 and 24 months post-surgery. Instruments have included the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC) QLQ C30 and BR23, as well as NCI Patient-Reported Outcomes Measurement Information System (PROMIS) measures, the National Comprehensive Cancer Network (NCCN) Distress Thermometer, and a Fear of Recurrence (FOR) instrument. We are currently implementing an electronic platform for survey collection and modifying the survey instruments to incorporate 31 items from the Patient Reported Outcomes-Common Terminology Criteria for Adverse Events (PRO-CTCAE) measurement system along with previously included PROMIS items in domains of physical, psychological, cognitive, and sexual function, the Distress Thermometer, and the FOR instrument. During neoadjuvant treatment, patients will also complete weekly abbreviated surveys containing PRO-CTCAE items only. We are using the data from these measures to generate a Clinical Benefit Index (CBI), a single composite score that integrates a PROMIS Preference (PROPr) score with a clinical efficacy assessment (residual cancer burden- RCB index) to provide new insight into the overall impact that therapeutic agents in I-SPY2 have on cancer recurrence risk, general health, and QOL. Specific Aims: The primary objective of the QOL study is to evaluate the short- and long-term impact on QOL of novel agents added to standard treatment in high-risk breast cancer patients receiving neoadjuvant therapy. Factors including patient age, hormone receptor and HER2 status, and response to treatment by residual cancer burden will be evaluated to understand their impact on a patients’ QOL trajectory over time. A secondary objective is to compare patient reported toxicities (using PRO-CTCAE measures) with clinician-reported adverse events. Accrual: The I-SPY 2 trial has registered 2729 patients to date and there are 18 sites open across the US. Since the initiation of the QOL study, at least one QOL survey has been collected from 1066 patients. Given the adaptive design, enrollment for each agent varies based on patient outcomes, but collection of PRO measures on all patients will continue as new agents enter the trial. Clinical trial information: NCT01042379. Citation Format: Hila Ghersin, Aheli Chattopadhyay, Anne Blaes, Tara Sanft, Dawn Hershman, Amrita Basu, Ruby Singhrao, Susie Brain, Diane Heditsian, Hope S Rugo, Laura Esserman, Michelle Melisko. Introducing an electronic platform to collect patient reported outcomes in the I-SPY 2 trial, a neoadjuvant clinical trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr OT3-19-02.

Background: The Athena Breast Health Network is a multi-site effort aimed at integrating cutting-edge research and clinical care for breast cancer screening and treatment. At the University of California, San Francisco (UCSF) Breast Care Center (BCC), an Athena-based electronic Health Questionnaire System (eHQS) is distributed to all new patients. This questionnaire assesses self-reported personal and familial health history, comorbidities, and Patient-Reported Outcome Measurement and Information System (PROMIS) quality of life domains. Based on these responses, patients are proactively triaged to genetic counseling, psycho-oncology, onco-fertility, smoking cessation, peer support, nutritional counseling, behavioral sleep, and social work. These referrals are based on pre-defined thresholds, such as Ashkenazi Jewish Ancestry (referral to Genetic Counseling), or PROMIS Depression and Anxiety scores greater than or equal to 9 and 11, respectively. This analysis aims to assess the eHQS as a means to refer patients to supportive care services and assess if high-need patients (those with the highest symptom burden as assessed by quality of life PROMIS scores) are referred to services more frequently. Patients and Methods: Since Athena’s launch in 2013, over 6,000 patients have completed the online intake questionnaire at the UCSF BCC, 4,984 of whom have consented to research. 3,627 patients completed all relevant data to this study and were used in our analysis. A review of patient referrals was conducted to assess the number of referrals as a result of eHQS completion. PROMIS T-Scores in 8 domains (depression, anxiety, fatigue, sleep-related impairment and disturbance, cognitive function, applied cognition and physical function) were calculated with the Health Measures system and compared across patients stratified by age and cancer type and against the US general population. Results: When compared to the US population as a whole, PROMIS scores indicate that UCSF BCC patients have impaired quality of life in every assessed PROMIS domain except for depression. As age increases, PROMIS scores across multiple domains (depression, anxiety, sleep disturbance, cognitive function) increase, signifying lower symptom burden. Importantly, high symptom burden in the anxiety PROMIS domain was suggestive of lower quality of life scores in 6 out of the other 7 assessed PROMIS domains. 39% (1408 patients) of all analyzed BCC patients received at least one referral to a supportive care service. 721 of 1450 (50%) patients with an Invasive Breast Cancer (IBC) diagnosis and 246 of 571 (43%) patients with a DCIS diagnosis triggered at least one referral. 31% of all patients received a referral to genetic counseling, 16.3% to psycho-oncology, 11% to behavioral sleep, 8% to nutritional counseling, 7.6% to social work, 2.4% to smoking cessation, and 1.6% to onco-fertility. When compared to patients with DCIS or without a cancer diagnosis, patients with IBC are most likely to receive a referral to genetic counseling and psychosocial services. Referrals to supportive care services are less frequent as age increases. Conclusion: The Athena online intake form at the UCSF BCC effectively triages patients with high levels of anxiety (PROMIS > 8) and depression (PROMIS >10) to supportive care services. Preliminary results regarding the correlation between anxiety and overall poor quality of life suggest that referrals to psycho-oncology may be most efficacious in decreasing symptom burden. Using these analyses, we aim to refine our use of the eHQS to tailor the most relevant and effective referrals to the highest-need patients. Citation Format: Madeline Matthys, André Dempsey, Amrita Basu, Emily Wong, Nickolas Dreher, Irene Acerbi, Suzanne Ackerson, Laura Esserman, Athena Breast Health Network Investigators and Advocate Partners, Michelle Melisko, Laura van 't Veer. Triaging breast care center patients to supportive care services based on the Athena Breast Health Network online intake form and the patient-reported outcomes measurement information system (PROMIS) [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-12-08.

Breast cancer (BC) prevention remains the ultimate cost-effective method to reduce the global burden of invasive breast cancer (IBC). To date, surgery and chemoprevention remain the main risk-reducing modalities for those with hereditary cancer syndromes, as well as high-risk non-hereditary breast lesions such as ADH, ALH, or LCIS. Ductal carcinoma in situ (DCIS) is a preinvasive malignant lesion of the breast that closely mirrors IBC and, if left untreated, develops into IBC in up to 50% of lesions. Certain high-risk patients with DCIS may have a 25% risk of developing recurrent DCIS or IBC, even after surgical resection. The development of breast cancer elicits a strong immune response, which brings to prominence the numerous advantages associated with immune-based cancer prevention over drug-based chemoprevention, supported by the success of dendritic cell vaccines targeting HER2-expressing BC. Vaccination against BC to prevent or interrupt the process of BC development remains elusive but is a viable option. Vaccination to intercept preinvasive or premalignant breast conditions may be possible by interrupting the expression pattern of various oncodrivers. Growth factors may also function as potential immune targets to prevent breast cancer progression. Furthermore, neoantigens also serve as effective targets for interception by virtue of strong immunogenicity. It is noteworthy that the immune response also needs to be strong enough to result in target lesion elimination to avoid immunoediting as it may occur in IBC arising from DCIS. Overall, if the issue of vaccine targets can be solved by interrupting premalignant lesions, there is a potential to prevent the development of IBC.

Current success of immunotherapy in cancer has drawn attention to the subsets of TH cells in the tumor which are critical for activation of anti-tumor response either directly by themselves or by stimulating cytotoxic T cell activity. However, presence of immunosuppressive pro-tumorigenic TH subsets in the tumor milieu further contributes to the complexity of regulation of TH cell-mediated immune response. In this review, we present an overview of the multifaceted positive and negative effects of TH cells, with an emphasis on regulation of different TH cell subtypes by various immune cells, and how a delicate balance of contradictory signals can influence overall success of cancer immunotherapy. We focus on the regulatory network that encompasses dendritic cell-induced activation of CD4+ TH1 cells and subsequent priming of CD8+ cytotoxic T cells, along with intersecting anti-inflammatory and pro-tumorigenic TH2 cell activity. We further discuss how other tumor infiltrating immune cells such as immunostimulatory TH9 and Tfh cells, immunosuppressive Treg cells, and the duality of TH17 function contribute to tip the balance of anti- vs pro-tumorigenic TH responses in the tumor. We highlight the developing knowledge of CD4+ TH1 immune response against neoantigens/oncodrivers, impact of current immunotherapy strategies on CD4+ TH1 immunity, and how opposing action of TH cell subtypes can be explored further to amplify immunotherapy success in patients. Understanding the nuances of CD4+ TH cells regulation and the molecular framework undergirding the balancing act between anti- vs pro-tumorigenic TH subtypes is critical for rational designing of immunotherapies that can bypass therapeutic escape to maximize the potential of immunotherapy.

Herein, we report a strategy for additive manufacturing of a mechanochemically active silicone ink primarily composed of PDMS microbeads. Extruded, stable structures of cured microbeads were held together with a “bridging material” comprising uncured PDMS and spiropyran in a water medium. The mechanochromic silicone ink was a shear-thinning gel that exhibited a yield stress, and thus, was suitable for direct-write 3D printing. The spiropyran was stable to mild conditions of the printing process, and after a thermal curing step, the printed silicone displayed reversible mechanochromic activity. The extruded composite displays chromophore activation at lower mechanical strains under uniaxial tension (60–70%) than in a film without the microbeads (130–140%). Multi-layered 3D printed constructs were fabricated and displayed mechanochromic activity in tension and compression. These experiments demonstrate the versatility of these silicone inks to produce 3D printed functional elastomers with mechanochemical activity.

Stimuli-responsive materials can enhance the field of three-dimensional (3D) printing by generating objects that change shape in response to external cues. While temperature and pH are common inputs for initiating a response in a 3D-printed object, there are few examples of using a mechanical input to afford a response. Herein, we report a suite of mechanochromic ionic liquid gel inks that can be used to fabricate 3D-printed objects that use a single mechanoactivation event to elicit both a mechanochromic response and an autonomous shape change. Direct-ink write 3D printing was used to deposit ionic liquid gel inks to create multimaterial objects that underwent a predetermined mechanoactivated shape change (mechanomorphic) when the sample was pulled and then released. When spiropyran was incorporated into the inks, the onset of spiropyran isomerization into its purple merocyanine form occurred at strains dependent upon the particular ion gel ink formulation. We suggest that the color onset could be used as a simple indicator for when the strain required to achieve a predetermined change in shape has been reached, potentially serving as real-time visual cue for the user. Such morphing 3D-printed structures with integrated instructions have potential application to areas including stowable structures as well as multiresponsive autonomous components and sensors.

ObjectivesIn this paper, we discuss leveraging cloud-based platforms to collect, visualize, analyze, and share data in the context of a clinical trial. Our cloud-based infrastructure, Patient Repository of Biomolecular Entities (PRoBE), has given us the opportunity for uniform data structure, more efficient analysis of valuable data, and increased collaboration between researchers.Materials and MethodsWe utilize a multi-cloud platform to manage and analyze data generated from the clinical Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis 2 (I-SPY 2 TRIAL). A collaboration with the Institute for Systems Biology Cancer Gateway in the Cloud has additionally given us access to public genomic databases. Applications to I-SPY 2 data have been built using R Shiny, while leveraging Google's BigQuery tables and SQL commands for data mining.ResultsWe highlight the implementation of PRoBE in several unique case studies including prediction of biomarkers associated with clinical response, access to the Pan-Cancer Atlas, and integrating pathology images within the cloud. Our data integration pipelines, documentation, and all codebase will be placed in a Github repository.Discussion and conclusionWe are hoping to develop risk stratification diagnostics by integrating additional molecular, magnetic resonance imaging, and pathology markers into PRoBE to better predict drug response. A robust cloud infrastructure and tool set can help integrate these large datasets to make valuable predictions of response to multiple agents. For that reason, we are continuously improving PRoBE to advance the way data is stored, accessed, and analyzed in the I-SPY 2 clinical trial.

The discovery of human epidermal growth factor receptor 2 (HER2) and its role in breast cancer led to the development of the first targeted antibody treatment for HER2-positive breast cancer. This treatment breakthrough led to remarkable improvements in both early and late survival. Unfortunately, not all patients with HER2 breast cancer responded positively; some have innate resistance to treatment and others develop resistance over time. In this review, we discuss some research that is currently underway to understand HER2 resistance and strategies in overcoming it.

Metastatic spread in breast cancer patients is the major driver of cancer-related deaths. A unique subset of cells disseminated from pre-invasive or primary tumor lesions are recognized as the main seeds for metastatic outgrowth. Disseminated cancer cells (DCCs) can migrate to distant organs and settle in a dormant state for a prolonged period until they emerge to overt metastases. Understanding the biology of breast cancer cells dissemination, dormancy and reactivation to form overt metastases has become an important focus. In this review, we discuss the recent advancements of molecular pathways involving breast cancer cell dissemination, role of chemokine-chemokine receptor networks in DCCs migration, DCCs phenotypic heterogeneity and unique genes signatures in tumor dormancy, microenvironmental regulation and specific niches that favors DCCs homing and dormancy. In addition, we also discuss recent findings relating to the role of immune response on DCC dissemination and dormancy. With recent advances in the field of immunotherapy/targeted therapy and its beneficial effects in cancer treatment, this review will focus on their impact on DCCs, reversal of stemness, tumor dormancy and metastatic relapse.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute–funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders’ titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was “intersections between informatics, data science, and population science.” We conclude with a discussion on “hot topics” on the horizon for cancer informatics.

The majority of women diagnosed with breast cancer will experience some form of drug-related toxicity and subsequent impairments in Health-related Quality of Life (HRQoL). Despite this, HRQoL is assessed inconsistently and there is no validated method to integrate HRQoL data into the assessment of therapeutic agents. This proof of concept study utilizes data from the neoadjuvant I-SPY 2 clinical trial to describe the development of the Quality of Life Index (QoLI) measure. The QoLI represents a single composite score that incorporates validated longitudinal measures of clinical efficacy and QoL and one that permits a more comprehensive, direct comparison of individual therapeutic agents. Preliminary data suggest the QoLI is able to distinguish between agents based on their efficacy and toxicity; with further validation, the QoLI has the potential to provide more patient-centered evaluations in clinical trials and help guide treatment decision making in breast cancer and other oncologic diseases.

Shear-thinning hydrogels are often employed in direct-write 3D printing, however, the viscoelastic behaviors that define a printable hydrogel have not been fully established. Herein, we demonstrate a library of hydrogel inks based on the incorporation of water-soluble reactive meth(acrylate) monomers into F127-dimethacrylate hydrogels. This strategy afforded printed hydrogels with a broad range of chemical functionalities and mechanical properties. A systematic investigation was also performed to correlate the printability and mechanical properties to the viscoelastic properties of the hydrogel ink formulations. The materials with a high dynamic yield stress afforded extruded filaments that correlated well with the inner diameter of the printing nozzle. The static yield stress of the material was correlated to the extrusion pressure and print speed required for optimal printing. Thus, this study provides a guide for the future development of hydrogel inks for direct-write 3D printing along with a new set of functional hydrogel inks.

Patients with metastatic HER2 breast cancer (MBC) often become resistant to HER 2 targeted therapy and have recurrence of disease. The Panacea trial suggested that HER2 MBC patients were more likely to respond to checkpoint therapy if TIL were present or if tumor expressed PD-L1. We assessed whether type I polarized dendritic cells (DC1) could improve checkpoint therapy in a preclinical model of HER2+ breast cancer. TUBO bearing mice were vaccinated with either MHC class I or class II HER2 peptide pulsed DC1 (class I or class II HER2-DC1) concurrently or sequentially with administration of anti-PD-1 or anti-PDL1. Infiltration of tumors by immune cells, induction of anti-HER2 immunity and response to therapy was evaluated. Class I or class II HER2-DC1 vaccinated mice generated anti-HER2 CD8 or CD4+ T cell immune responses and demonstrated delayed tumor growth. Combining both MHC class I and II HER2-pulsed DC1 did not further result in inhibition of tumor growth or enhanced survival compared to individual administration. Interestingly class II HER2-DC1 led to both increased CD4 and CD8 T cells in the tumor microenvironment while class I peptides typically resulted in only increased CD8 T cells. Anti-PD-1 but not anti-PD-L1 administered sequentially with class I or class II HER2-DC1 vaccine could improve the efficacy of HER2-DC1 vaccine as measured by tumor growth, survival, infiltration of tumors by T cells and increase in systemic anti-HER2 immune responses. Depletion of CD4+ T cells abrogated the anti-tumor efficacy of combination therapy with class II HER2-DC1 and anti-PD-1, suggesting that tumor regression was CD4 dependent. Since class II HER2-DC1 was as effective as class I, we combined class II HER2-DC1 vaccine with anti-rat neu antibodies and anti-PD-1 therapy. Combination therapy demonstrated further delay in tumor growth, and enhanced survival compared to control mice. In summary, Class II HER2-DC1 drives both a CD4 and CD8 T cell tumor infiltration that leads to increased survival, and in combination with anti-HER2 therapy and checkpoint blockade can improve survival in preclinical models of HER2 positive breast cancer and warrants exploration in patients with HER2 MBC.

Breast cancer, one of the leading causes of death in women in the United States, challenges therapeutic success in patients due to tumor heterogeneity, treatment resistance, metastasis and disease recurrence. Knowledge of immune system involvement in normal breast development and breast cancer has led to extensive research into the immune landscape of breast cancer and multiple immunotherapy clinical trials in breast cancer patients. However, poor immunogenicity and T-cell infiltration along with heightened immunosuppression in the tumor microenvironment have been identified as potential challenges to the success of immunotherapy in breast cancer. Oncodrivers, owing to their enhanced expression and stimulation of tumor cell proliferation and survival, present an excellent choice for targeted immunotherapy development in breast cancer. Loss of anti-tumor immune response specific to oncodrivers has been reported in breast cancer patients as well. Dendritic cell vaccines have been tested for their efficacy in generating anti-tumor T-cell response against specific tumor-associated antigens and oncodrivers and have shown improved survival outcome in patients. Here, we review the current status of immunotherapy in breast cancer, focusing on dendritic cell vaccines and their therapeutic application in breast cancer. We further discuss future directions of breast cancer immunotherapy and potential combination strategies involving dendritic cell vaccines and existing chemotherapeutics for improved efficacy and better survival outcome in breast cancer.

There are limited methods to analyze both efficacy of a drug and toxicity to a patient in response to treatment. We have developed a metric, the clinical benefit index (CBI) which is quantitative, and a scalable way to integrate patient-reported side effects and efficacy for adaptive randomization. Instead of using efficacy as a singular attribute in decision making for agent selection, we will consider the impact on QoL since many of the newer agents will be less toxic. This will be developed in effort to standardize PRO analysis methods. The clinical benefit index provides an alternative framework for evaluation and would help us to develop a regulatory model for approval of those drugs that have less toxicity by providing a replicable model for measuring toxicity and integrating it with efficacy. Reporting of clinical data can inform the management of toxicity and the integration into a clinical benefit index will help promote regulatory evaluation and preference for less toxic drug/combinations.

Purpose: Standard treatment for ductal carcinoma in situ (DCIS) involves surgical excision usually with radiation therapy or mastectomy and often endocrine therapy, treatments that are the same as for invasive cancer (IDC). It is clear, however that not all patients with DCIS will develop IDC and so the question is who benefits from early surgical intervention? Active Surveillance (AS) with endocrine risk reduction presents an opportunity to improve outcomes by identifying those lesions that can be managed with endocrine therapy alone without immediate surgical intervention. An active surveillance cohort of women who chose not to have surgery at diagnosis were followed with serial MRIs to identify the imaging features associated with successful AS and those with IDC. Methods: Patients with DCIS were enrolled in MRI surveillance studies between 2002 and 2019 and analyzed retrospectively with IRB approval. Per medical record review, these patients sought to avoid surgical intervention. Inclusion criteria included at least two breast MRIs performed for purposes of surveillance. The final cohort of patients included 64 cases with at least two breast MRIs, with 27 patients having more than 4 MRIs. All breast MRIs consisted of routine sequences, including both pre and post IV contrast images with at least 2 post-contrast time points. Lesion conspicuity, change in lesion, background parenchymal enhancement (BPE), change in BPE, and likelihood of invasive cancer at each MRI timepoint, were subjectively measured independently by two breast radiologists. A Likert scale was used to grade each imaging feature. Radiologists were blinded to the clinical outcome of whether the patient had IDC at surgery or not. Input variables included all imaging features collected and classification trees were trained and bootstrapped on 90% of the data using recursive partitioning to distinguish imaging features predictive of clinical outcome. Proportionality tests were conducted to test whether IDC was associated with age, menopausal status, and breast composition among other clinical variables.Results: Women in the cohort had a mean age of 53.6 years (range 29.8 to 78.9). 98.3% were HR+. Of the 64 cases in the cohort, 57 received endocrine therapy (89.1%). A total of 31 cases (48.4%) eventually had surgical excision and 33 (51.6%) remained on AS. At surgery, 17 patients had IDC (26.6%). Classification trees revealed that the most distinguishing features in the model correlating with IDC were if the lesion was distinct from background at MRI timepoint 1, an increase in BPE between MRI timepoints 1 and 2, and an increase in the lesion size or conspicuity between MRI timepoints 1 and 2. At diagnosis, 56.3% demonstrated a more diffuse pattern of enhancement where the DCIS lesion was not distinguishable above background. Of those with lesions that did not stand out above background at diagnosis and whose BPE did not increase, only 1 of 31 patients developed IDC (3%) with mean follow up of 4.62 years. Patients with IDC were proportionately older (>60) and post-menopausal (73% with IDC were postmenopausal), although only 57% were postmenopausal at diagnosis. Other variables such as breast composition were not enriched in either the IDC versus the non-IDC population. Conclusion: Our study suggests that imaging markers such as BPE and conspicuity of lesion enhancement may provide information to better understand and stratify the risk of DCIS and avoid overtreatment. Importantly, MRI may provide insight as to when a diagnosis of DCIS is more likely to be a global risk factor amenable to endocrine risk reduction, versus a lesion best treated with surgical excision. Pathology correlation is underway. We are currently developing methods to improve reproducibility and harmonization between radiologists, and performance on a validation set will be presented. Citation Format: Heather Greenwood, Rita Freimanis, Case Brabham, Rita Mukhtar, Gillian Hirst, Paul Kim, April Liang, Laura Esserman, Nola Hylton, Amrita Basu. Magnetic resonance imaging insights from an active surveillance cohort of women with DCIS [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD5-01.

Background Comorbidities in metastatic breast cancer patients (pts) impact treatment decisions, eligibility for clinical trials, and influence prognosis and quality of life (QoL). The aim of this study was to evaluate the concordance between pt-reported and physician-documented (PD) comorbidities in an electronic medical record to (1) reliably document pts’ health histories to establish eligibility for clinical trials and novel therapeutics, and, (2) identify comorbidities that may be more comprehensively reported by pts rather than physicians. Patients and Methods All new pts at UCSF’s Breast Care Center (BCC) are administered an electronic intake survey that includes an assessment of pt-reported health history, comorbidities and symptoms. Between November 2016 and March 2020, 305 pts self-reported metastatic breast cancer (described as “breast cancer spread to sites other than breast or axillary lymph nodes”), and 222 consented to use of their clinical data for research. Chart-reviews were conducted for PD comorbidities at their initial BCC clinic visit. Pt and physician concordance was summarized for 54 comorbidities. Cohen’s kappa (κ) was used to quantify level of agreement. Concordance was classified using Landis and Koch thresholds with agreement as poor or slight (κ Results Of the 222 pts, 37 pts (17%) incorrectly reported having metastatic breast cancer, 4 (2%) had duplicate surveys, 7 (3%) cancelled appointment and 5 (2%) had metastatic cancer from another primary. Thus, 168 pts with confirmed metastatic disease were included in the analysis (median age, 56 years; age range, 29-86 years; median time from diagnosis of metastatic breast cancer, 0.46 years). Highest PD comorbidities were obesity, hypertension (HTN) and thyroid disease, while highest reported comorbidities by pts were HTN, depression and arthritis. 23 of 54 comorbidities had a moderate to high level of agreement between physician and pt reports (κ≥0.40). As shown in Table 1, agreement was high for diabetes (type 1 or 2), HTN and thyroid disease, moderate for asthma/bronchitis and depression, and low for obesity, anxiety, stomach ulcers/gastroesophageal reflux disease (GERD) and arthritis. Conclusion In this review of data collected as part of routine care at an academic medical center, rates of comorbidities were relatively low, and there is substantial variance in the concordance of comorbidity reporting between pt and physicians. Pt-reported comorbidity data may help physicians more comprehensively document conditions such as depression, anxiety, arthritis and stomach ulcers/GERD, which in some cases may be subjective in nature but may significantly impact a pt’s quality of life and performance status. However, pts may underreport conditions such as obesity and heart disease, and inaccurately report other conditions such as non-insulin dependent diabetes. Recognition of depression, anxiety and GERD as comorbidities is important since some medications for these conditions may be contraindicated in some clinical trials. Understanding this concordance data may inform how we collect pt reported data to optimize understanding of a pt’s global health condition. Table 1: Concordance between physician-documented and patient-reported comorbiditiesComorbidityPhysician ReportedPatient ReportedConcordanceκDiabetes6%5%98%0.83Hypertension24%20%93%0.79Thyroid Disease20%18%92%0.74Insulin dependent Diabetes1%1%99%0.66Depression11%20%87%0.51Asthma/bronchitis12%15%89%0.51Stomach ulcers/ GERD11%18%84%0.36Obesity34%15%75%0.36Heart disease/heart valve disease7%4%93%0.32Anxiety10%18%83%0.30Non-insulin dependent diabetes3%1%97%0.27Arthritis9%20%78%0.14 Citation Format: Saumya Umashankar, Michelle E. Melisko, Madeline Matthys, Laura Van't Veer, Amrita Basu. Concordance between patient-reported and physician-documented comorbidities among stage 4 breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS9-05.

Background: Epistaxis is a common otorhinological emergency seen in children. Aetiology and treatment differ in different age group. Methods: A retrospective study conducted in a tertiary care hospital and data of pediatric patients (under 18 year) admitted with epistaxis were divided into three different age group. Group A (2 years to

Purpose In breast MRI, contrast enhancement of normal fibroglandular tissue is referred to as background parenchymal enhancement (BPE). Hormonal status significantly affects the degree of BPE, potentially due to the association with mammary vascularity and activity1-5. Studies have shown that BPE may be associated with breast cancer survival6, treatment response to neoadjuvant chemotherapy (NAC)7,8 and future breast cancer risk9. In most patients undergoing NAC, BPE is suppressed by the nonspecific anti-proliferative effects of chemotherapy on normal breast and/or ovary5,10. However, some patients exhibit equivalent or even stronger BPE post-NAC compared to pre-NAC. We hypothesized that non-suppressed BPE in post-NAC MRI may be associated with inferior treatment response. This study aimed to investigate the association between BPE suppression and treatment response as defined by pathologic complete response (pCR). Methods This study included patients with stage II/III breast cancer enrolled in the I-SPY 2 TRIAL being treated with standard NAC with or without investigational agents. The whole cohort was split into two subgroups based on hormone receptor status (HR+, n= 536; HR-, n=452). Patients underwent dynamic contrast enhanced MRIs at four time points during NAC: baseline (T0), after 3 weeks of the first regimen (T1), inter-regimen (T2), and pre-surgery (T3). Using in-house software, the contralateral breast parenchyma was automatically segmented for the entire breast volume. Quantitative BPE (qBPE) was calculated as the mean early (~150s post-contrast injection) percent enhancement of the central 50% of the axial slices. A breast radiologist reviewed all exams and excluded those where automated segmentation failed to accurately define tissue. For T1, T2 and T3, BPE was categorized based on the change from T0 as suppressed (qBPE < qBPE[T0]) or non-suppressed (qBPE ≥ qBPE[T0]). Chi-squared test was used to examine the association between BPE suppression and pCR, with p Results HR+ cohort: pCR rates were lower for patients with non-suppressed BPE than those with suppressed BPE at every visit (T1-T3) (Table 1). The difference was statistically significant at T2 (p=0.04) and T3 (p=0.01). Table 1: HR+ cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall22.8122414536BPE at T1suppressed23.6822663480.45non-suppressed20.532124156BPE at T2suppressed25.7972803770.04*non-suppressed16.01789106BPE at T3suppressed25.7982833810.01*non-suppressed12.5128496 HR- cohort: pCR rates were slightly lower for the non-suppressed BPE group, but no statistically significant association was found (Table 2). Table 2: HR- cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall44.7202250452BPE at T1suppressed46.81411603010.66non-suppressed44.45265117BPE at T2suppressed48.81441512950.79non-suppressed47.3434891BPE at T3suppressed49.31461502960.94non-suppressed48.9434588 Conclusion In HR+ breast cancer, lack of BPE suppression may indicate inferior treatment response. The contrasting results in HR+ and HR- cohorts are noteworthy in terms of the possible relationship between suppression of normal mammary and ovarian activity and treatment response in HR+ cancer. Reference Radiographics 2014; 34: 234-47. Radiology 1997; 203: 137-44. Radiology 1997; 203: 145-9. Breast J 2005; 11: 236-41. AJR Am J Roentgenol 2015; 204: 669-73. Eur Radiol 2018; 28: 4705-16. Eur Radiol 2016; 26: 1590-6. Transl Oncol 2015; 8: 204-9. J Clin Oncol 2019; : JCO1800378. Radiology 2015; 277: 687-96. Citation Format: Natsuko Onishi, Wen Li, David C. Newitt, Roy Harnish, Jessica Gibbs, Ella F. Jones, Alex Nguyen, Lisa Wilmes, Bonnie N. Joe, Michael J. Campbell, Amrita Basu, Laura J. van’t Veer, Angela DiMichele, Douglas Yee, Donald A. Berry, Kathy S. Albain, Judy C. Boughey, A. Jo Chien, Amy S. Clark, Kirsten K. Edmiston, Anthony D. Elias, Erin D. Ellis, David M. Euhus, Heather S. Han, Claudine Isaacs, Qamar J. Khan, Julie E. Lang, Janice Lu, Jane L. Meisel, Zaha Mitri, Rita Nanda, Donald W. Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K. Viscusi, Anne M. Wallace, Rachel Yung, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, W. Fraser Symmans, Smita M. Asare, Julie E. Yau, Christina Yau, Laura J. Esserman, Nola M. Hylton. Lack of background parenchymal enhancement suppression in breast MRI during neoadjuvant chemotherapy may be associated with inferior treatment response in hormone receptor positive breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-05.

In patients with HER2-expressing breast cancer many develop resistance to HER2 targeted therapies. We show that high and intermediate HER2-expressing cancer cell lines are driven toward apoptosis and tumor senescence when treated with either CD4+ Th1 cells, or Th1 cytokines TNF-α and IFN-γ, in a dose dependent manner. Depletion of HER2 activity by either siRNA or trastuzumab and pertuzumab, and subsequent treatment with either anti-HER2 Th1 cells or TNF-α and IFN-γ resulted in synergistic increased tumor senescence and apoptosis in cells both sensitive and cells resistant to trastuzumab which was inhibited by neutralizing anti-TNF-α and IFN-γ. Th1 cytokines induced minimal senescence or apoptosis in triple negative breast cancer cells (TNBC); however, inhibition of EGFR in combination with Th1 cytokines sensitized those cells causing both senescence and apoptosis. TNF-α and IFN-γ led to increased Stat1 phosphorylation through serine and tyrosine sites and a compensatory reduction in Stat3 activation. Single agent IFN-γ enhanced Stat1 phosphorylation on tyrosine 701 and similar effects were observed in combination with TNF-α and EGFR inhibition. These results demonstrate Th1 cytokines and antioncodriver blockade cooperate in causing tumor senescence and apoptosis in TNBC and HER2-expressing breast cancer, suggesting these combinations could be explored as non-cross-reactive therapy preventing recurrence in breast cancer. Fil: Rosemblit, Cinthia. H. Lee Moffitt Cancer Center; Estados Unidos. University of Pennsylvania; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Datta, Jashodeep. University of Pennsylvania; Estados Unidos Fil: Lowenfeld, Lea. University of Pennsylvania; Estados Unidos Fil: Xu, Shuwen. University of Pennsylvania; Estados Unidos Fil: Basu, Amrita. H. Lee Moffitt Cancer Center; Estados Unidos Fil: Kodumudi, Krithika. H. Lee Moffitt Cancer Center; Estados Unidos Fil: Wiener, Doris. H. Lee Moffitt Cancer Center; Estados Unidos Fil: Czerniecki, Brian J.. H. Lee Moffitt Cancer Center; Estados Unidos. University of Pennsylvania; Estados Unidos

Image and video processing is currently active research field during the past few years. Different coding schemes are available in the literature for image and video compression to improve compression ratio while maintaining picture quality. Many of the algorithms use ROI coding such as saliency based concept using different image features. But very few works related to depth cues preserving compression. In this paper, we present a behavioral study to state that the images compressed using defocus cue preserving compression yields better depth perception as compared to standard JPEG compression. We compare images compressed using different schemes against the original image. We collect data from different participants by showing original and compressed images to them. The responses are analyzed using analysis of variance. The analysis shows that the images compressed using defocus cue based compression provides the better perception of the raw image as compared to standard JPEG compressed image.

Background Symptom burden and reduced quality of life are considerable hurdles in cancer treatment. The Patient-Reported Outcomes Measurement Information System (PROMIS) assesses physical and psychosocial functional status in clinical and research settings. We use PROMIS scores to establish mean symptom burden within a breast cancer patient population, identifying how subgroups compare to one another, examining potential drivers, and characterizing severe symptom burden between subgroups. Methods New cancer patients at the UCSF Breast Care Center (BCC) receive electronic intake questionnaires assessing demographics, health history, and 8 PROMIS domains: depression, anxiety, fatigue, sleep-related impairment and disturbance, cognitive function, applied cognition and physical function. Patients were separated by age and stage of cancer and mean PROMIS reference values for each group were calculated using the NCI’s Health Measures scoring system. We computed enrichment of higher levels of anxiety, sleep impairment, fatigue, physical function impairment, and cognitive decline in metastatic patients versus all other cases. Results Compared to stage 0-III, BCC stage IV patients had lower mean values for all assessed domains (p Conclusions PROMIS scores indicate that stage IV patients have impaired quality of life in multiple domains. Reference values for demographic groups provide improved guidance in tailoring supportive care referrals. Anxiety emerged as one of the biggest drivers of impairment of other physical, mental, and social functions and thus increased priority addressing anxiety early will likely correspond with improved symptom burden. Our analysis on quality of life will also help determine appropriate thresholds of intervention to trigger referrals and manage a patient’s quality-of-life trajectory more systematically. Legal entity responsible for the study Athena Breast Health Network. Funding Athena Breast Health Network, University of California, San Francisco. Disclosure All authors have declared no conflicts of interest.

e23171 Background: NCI PROMIS assesses physical, mental and social health across multiple health conditions. Despite interest in using PROMIS in oncology trials and clinical care, reference values in cancer are not well established. Methods: Electronic intake questionnaires assessing self-reported history and 8 PROMIS domains (depression, anxiety, fatigue, sleep-related impairment (SRI), sleep disturbance, cognitive function, applied cognition and physical function) are sent to all new patients (pts). 2886 pts with self-reported breast cancer completed the questionnaire/consented to research. PROMIS T-Scores were calculated using the Health Measures system. Results: For all domains except depression, cognitive function and applied cognition, pts had clinically meaningful ( > 3 point diff.) worse mean PROMIS scores than US means (50). Compared to stage 0-III, stage IV pts had worse scores for all assessed domains (p < 0.05). Among Stage IV pts < 49, QoL was significantly worse in 7/8 domains (see table). Across all age groups, there were significant differences in mean PROMIS scores for Stage IV pts in anxiety, depression, cognitive function and applied cognition (p < 0.05). Conclusions: PROMIS scores among pts indicate impaired QoL in multiple domains. These scores provide insight into the physical, mental and social health of our pts and can serve as robust estimates for breast cancer trials and clinical care. [Table: see text]

Oncodrivers are a promising target in novel breast cancer therapy development, owing to oncogene addiction of breast cancer cells to sustain their malignancy. We have previously shown progressive loss of CD4+ T-helper type 1 response to oncodrivers in triple negative breast cancer (TNBC) patients. TNBC is marked by lack of cell surface ER, PR and Her2 receptors and is the most aggressive subtype of breast cancer. Lack of therapeutic targets, resistance to existing hormone therapy, metastasis and poor survival in TNBC patients underline the need for novel TNBC therapy development. In this study, we investigated the effect of EGFR inhibitors (cetuximab, erlotinib and lapatinib) alone or combination with Th1 cytokines (IFN-γ and TNF-α) on growth and proliferation of MDA-MB-231 and MDA-MB-468 TNBC cells. We observed decrease in EGFR expression in TNBC cells when treated with IFN-γ alone and in combination with EGFR inhibitors. In addition, IFN-γ alone, in combination with TNF-α and all three EGFR inhibitors, markedly increased STAT1 phosphorylation, indicating suppression of growth and proliferation in TNBC cells. Decreased STAT3 phosphorylation by combination treatment in TNBC cells may induce apoptosis and inhibit proliferation further. Combination of cetuximab and IFN-γ increased cleaved caspase-3 expression in MDA-MB-231, but not in MDA-MB-468 TNBC cells. EGFR inhibition and Th1 cytokine treatment showed combination treatment resulted in severe cell loss and morphological alteration, while Th1 cytokines alone did not induce significant senescence in MDA-MB-231 cells in senescence associated β-galactosidase assay. We are currently investigating activation status of other signaling pathways in TNBC cells, following Th1 cytokines treatment with EGFR inhibition. Our data suggests a combinatorial treatment approach, including DC1 vaccination to elicit Th1 immune response and inhibition of EGFR oncodriver, may lead to an effective and novel therapeutic strategy for triple negative breast cancer. Citation Format: Amrita Basu, Krithika Kodumudi, Doris Wiener, Brian Czerniecki. Th1 cytokines and EGFR inhibition: A combinatorial therapeutic strategy in TNBC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 826.

e18603Background: Data harmonization refers to the processes that enable data from different sources and studies to be combined, queried, and analyzed. This process is becoming exceptionally onerou...

Background: Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation. Aim: The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI) in normal human subjects. Materials and Methods: Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2FNx01-weighted gradient-echo echo-planar imaging (GE-EPI) sequence (TR 4523 ms, TE 64 ms, flip angle 90º) with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s) with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2) with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD) signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps. Results: Single subject analysis of the functional data (FWE-corrected, P≤0.001) revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG), superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG), anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001) revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas. Conclusions: Group data analysis revealed a cerebellar-occipital-fusiform-thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these areas facilitate language comprehension by activating a semantic association network of words processed postlexical access. This finding is important when assessing the extent of cognitive damage and/or recovery and can be used for presurgical planning after optimization.

Relationships in biological systems are frequently represented as networks with the goal of abstracting a system’s components to nodes and connections between them. While such representations allow modeling and analysis using abstract computational methods, there are certain aspects of such modeling that are particularly important for biological networks. We explore features that are deemed necessary for living and evolving organisms and reflect the evolutionary origins of biological networks. Biological networks are robust to random alterations of their nodes and connections yet may be vulnerable to attacks targeting essential genes. Biological systems are dynamic and modular, and so are their network representations. Comparisons of biological networks across species can reveal conserved and evolved regions and shed light on evolutionary events and processes. It is important to understand networks as a whole, as significant insights might emerge from the network approach that cannot be attributed to properties of the nodes alone. Network-based approaches have a potential to significantly increase our understanding of biological systems and consequently, our understanding and treatment of human diseases.

Precision oncology requires predictive models for therapy selection using variety of biomarkers and clinical features as input. Building and validating these models requires analysis of large numbers of diverse cases in order to relate markers and treatments to positive outcomes. The -omics technologies provide a rich source of genetic and epigenetic markers but demand large compute and storage systems to process the data. Thus, there is an urgent need for scalable and reliable information systems to support nation-scale research and delivery of precision oncology. At Lockheed Martin, we deliver operational solutions to complex problems. Here, we present our vision for a precision oncology platform. This solution integrates best-in-class capabilities from multiple sources/vendors to support innovation, research and clinical care for a whole nation. We not only thought about the basic -omics based data collection, but also an infrastructure to collect and store data within a compliant privacy and security framework that also facilitates collaborative analytics and data sharing for deeper insight. Taking a systems engineering approach, we have examined some of the challenges to implement such a platform. For instance, running the basic genomic data processing pipelines to yield variant calls, which in turn will feed the variant store, should be a single scalable workflow. Accounting for multiple data sources, various use cases and selections of tools are at the core of an adaptable workflow. A variant store design that can scale and support a national cohort with an overlaying cohort selection tool are all part of this intricate design. It is our vision that a systems engineering and integration approach can deliver a unified solution for the national precision oncology roadmap. It is paramount that all the individual pieces should be well tuned to deliver scalability and reliability and simultaneously work in complete harmony. Only then we can process data at-scale needed for finding actionable mutations, designing effective treatments and implementing prevention strategies, affordably and reliably. Citation Format: Ogan Abaan, Amrita Basu, David Deal, Michael Hultner. Adaptive operations and technology platform for nation-scale precision oncology. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3632.

We present a novel perception-driven approach to low-cost tele-presence systems, to support immersive experience in continuity between projected video and conferencing room.We use geometry and spectral correction to impart for perceptual continuity to the whole scene. The geometric correction comes from a learning-based approach to identifying horizontal and vertical surfaces. Our method redraws the projected video to match its vanishing point with that of the conference room in which it is projected. We quantify intuitive concepts such as the depth-of-field using a Gabor filter analysis of overall images of the conference room. We equalise spectral features across the projected video and the conference room, for spectral continuity between the two.

Language, regarded as a hierarchical cognitive code activated by functional operational modes of the brain by most neuropsychologists, is characterized by increased cognitive load in successively higher levels of processing. Language comprehension is posited to be executed through symbolic-iconic information being encoded neurally as modulated phenomena, and can be studied in vivo by functional brain imaging. Using a lexical decision-making task in conjunction with syntactic error correction that effectively isolated the regulatory neural substrate of processing structural-functional information, and minimizing the possible confounds of gender and proficiency, functional magnetic resonance imaging (fMRI) was performed on bilingual volunteers to ascertain the attentional modulation of second language lexical and sentence processing. Our results indicate that while a right posterior cingulate gyrus-precuneus-lingual gyrus-cerebellar loop processes lexical information, the left inferior and middle frontal cortices are critically involved in the implementation of a structural-functional decision-making procedural loop in mediating second language comprehension.

Our understanding of the genetic basis for cancer is advancing at a rapid rate due to the application of next generation sequencing (NGS) technologies. It is becoming common to sequence tumors and patients in an attempt to find actionable mutations that could offer the patient a more targeted and effective treatment. However, the genomics of cancer is very complex and only a handful of actionable mutations have been characterized. Larger-scale studies are needed to understand the pathogenic spectrum of cancer variants and deliver reliable clinical decision-making support to providers. Several large-scale sequencing projects are underway to collect NGS data on tumors (e.g. TCGA, ICGC, and TARGET) but a national platform for analysis, interpretation, and reporting does not exist. We propose that a consolidated informatics platform for the collection of outcomes data with genomics and clinical data would accelerate research and provide patients with the opportunity for personalized cancer treatment. In addition, with 1,665,540 new cancer cases predicted in the US for 2014, a national-scale genomics platform is needed, capable of sequencing 3 million genomes per year, storing exabytes of data, while supporting over 20,000 oncologists, researchers, and analysts. At Lockheed Martin, we deliver highly scalable and reliable information systems for a variety of missions and citizen services. Here, we will present our vision for a national cancer genomics platform to include NGS data collection, cost-efficient storage, scalable and modular processing pipelines, and collaborative analytics and data sharing capabilities, within a compliant privacy and security framework. In conclusion, by leveraging the scale of clinical cancer sequencing and capturing these data into a case management system for translational research, this platform provides data at-scale needed for finding actionable mutations, designing effective treatments and implementing prevention strategies, faster. Citation Format: Ogan Abaan, Amrita Basu, Noah Brown, Bret Light, David Deal, Michael Hultner. A population-based approach to address clinical cancer care: The national genomics platform. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4743. doi:10.1158/1538-7445.AM2015-4743