Final Tumor Volume Research Articles

Tumor-targeted nano-assemblies for energy-blocking cocktail therapy in cancer

Starvation therapy aims to “starve” tumor cells by cutting off their nutritional supply. However, due to the complex and varied energy metabolism of tumors, targeting a single nutrient supply often fails to yield significant therapeutic benefits. This study proposes a tumor energy cocktail therapy that combines metformin, an oxidative phosphorylation inhibitor, with 2-deoxy-d-glucose (2-DG), a glycolysis inhibitor, to target tumor cells. To minimize the dosage of both drugs, we have developed a drug delivery strategy that prepared metformin as a nanoderivative, denoted as MA-dots. These MA-dots not only preserve the antitumor properties of metformin but also serve as a targeted delivery platform for 2-DG, ensuring its direct reach to the tumor site. Upon reaching the acidic tumor environment, the composite disintegrates, releasing 2-DG to inhibit glycolysis by targeting hexokinase 2 (HK2), the key enzyme in glycolysis, while MA-dots inhibit mitochondrial OXPHOS. This dual action significantly reduces ATP production in tumor cells, leading to apoptosis. In human lung tumor cells, the half-maximal inhibitory concentration (IC50) of 2-DG@MA-dots was significantly lower than that of either metformin or 2-DG alone, showing a nearly 100-fold and 30-fold reduction in IC50 values to 11.78 µg mL−1, from 1159 µg mL−1 and 351.20 µg mL−1, respectively. In studies with A549 tumor-bearing mice, the combination of low-dose 2-DG and metformin did not impede tumor growth, whereas 2-DG@MA-dots markedly decreased tumor volume, with the mean final tumor volume in the combination treatment group being approximately 89 times greater than that in the 2-DG@MA-dot group. Statement of significanceMetformin is a promising antitumor agent capable of modulating mitochondrial oxidative phosphorylation to inhibit cancer growth. However, its antitumor efficacy is limited when used alone due to compensatory energy mechanisms. Hence, we introduced glycolysis inhibitor 2-deoxy-d-glucose (2-DG) to inhibit an alternative tumor energy pathway. In our study, we developed a drug delivery strategy using metformin-derived nanomedicine (MA-dots) to load 2-DG. This approach enables the co-delivery of both drugs and their synergistic effect at the tumor site, disrupting both energy pathways and introducing an innovative “energy cocktail therapy”.

Use of integrated multi-omics analysis to determine antitumor efficacy of donafenib in combination with FADS2 inhibition in hepatocellular carcinoma.

e15083 Background: Pharmacotherapy remains a pivotal treatment strategy for patients with advanced hepatocellular carcinoma (HCC). Donafenib, globally the first targeted therapy proven to offer superior survival benefits and safety over sorafenib in a large-scale phase III clinical trial with head-to-head comparison, has been adopted for first-line treatment of advanced HCC. Given the limited basic research on Donafenib both domestically and internationally, and its constrained clinical efficacy, this study aims to explore combination drug therapy for HCC in an attempt to achieve further breakthroughs and enhance the anticancer activity of Donafenib. Methods: A xenograft tumor model in nude mice was established to observe the in vivo antitumor effects of Donafenib. Transcriptomics and proteomics were employed to characterize the gene expression changes in HCC cell lines after Donafenib intervention and to screen for key molecules. A series of assays, including the Cell Counting Kit-8 (CCK8), flow cytometry, scratch assays, Transwell assays, Western blotting, and in vivo tumorigenicity in nude mice, were conducted to determine the impact of the hub gene on the malignant behavior of HCC and to evaluate the combined antitumor effects of the molecular inhibition and Donafenib treatment in HCC. Results: Treatment with Donafenib significantly slowed tumor growth in a nude mouse xenograft model, resulting in a marked reduction in final tumor volumes compared to control subjects. Proteomic analyses post-Donafenib treatment identified FADS2 as the protein with the highest absolute log2 fold change among all differentially expressed proteins in HCC cells. This finding was corroborated by transcriptomic data, which indicated a concurrent downregulation of FADS2 at the mRNA level. Subsequent in vitro and in vivo assays validated the inhibitory effect of FADS2 blockade on the malignant biological behaviors of HCC cells. Importantly, the concomitant administration of Donafenib and the FADS2 inhibitor SC-26196 exhibited a synergistic antitumor action, significantly enhancing therapeutic efficacy in both HCC cell lines and xenografted tumors in nude mice. Conclusions: Combination therapy, a prevalent approach in clinical oncology, has the potential to augment treatment efficacy while simultaneously diminishing toxicity. This study employed an extensive multi-omics approach complemented by a range of both in vitro and in vivo experiments. It revealed that the synergistic use of Donafenib and SC-26196 markedly enhances Donafenib-induced the inhibition of cancer cell growth and metastasis, demonstrating a significant synergistic antitumor effect. These findings from our preclinical investigations may offer a promising new combinational drug regimen for the therapeutic management of HCC patients.

Abstract PO1-01-05: Spatial PK/PD Model with HER2 Expression for Predicting Individual Tumor Response to T-DM1

Abstract Introduction: As new antibody drug conjugates are developed, the question of which specific patients will respond to these therapies remains. This work develops a spatial PK/PD model for the antibody drug conjugate trastuzumab emtansine, T-DM1, and explores the relationship between HER2 (target) expression and other individual features of the tumor microenvironment using a computational approach. Methods: We developed a spatial PK/PD model for T-DM1 based upon an allometrically-scaled mouse model (Jumbe, Nelson L., et al., 2010) and the reported outcomes from the KRISTINE trial, which investigated T-DM1 plus pertuzumab in the neoadjuvant early-stage breast cancer setting (Hurvitz, Sara A., et al., 2018). The T-DM1 spatial PK/PD model was then integrated into our previously described 4D biophysical simulation model (Howard, Frederick M., et al., 2022). The biophysical model leverages baseline breast MRI and clinicopathologic features and predicts the individual response to a treatment regimen. Using digital twin tumors from our TumorBank to simulate the KRISTINE trial cohort (n=40), the PD model was parameterized to achieve the trial response rate. To orthogonally validate the spatial PK/PD model, volumetric response and pCR were predicted in an independent cohort of ISPY2 trial patients (n=44) who received T-DM1 followed by dose-dense doxorubicin and cyclophosphamide. We then assessed the added value of the target expression data by developing logistic regression models to predict which patients would achieve pCR based upon HER2 expression alone or HER2 expression combined with the final tumor volume simulated using the spatial PK/PD model. Results: A logistic regression model based upon HER2 expression from transcriptomic data is a strong predictor of response to T-DM1 with an odds ratio of 9.6 and an area under the ROC curve (AUC) of 0.81. The tumorHER2 model, which combines the HER2 expression with the spatial PK/PD model, improves the predictive value of the model with an odds ratio of 34.0 and an AUC of 0.88. Conclusion: The spatial PK/PD improves prognostic predictions compared to HER2 gene expression data alone. In leveraging the SBS biophysical simulation platform, the spatial PK/PD model captures the individual variability in tumor growth rate, tumor perfusion, and drug disposition, all of which influence the treatment efficacy. The rate of target expression will highly influence response to an ADC, but the biophysical model demonstrates that features of the spatial tumor microenvironment also influence response. Table 1. Performance comparison between the SBS tumorHER2model and SBSHER2 Signature. Citation Format: Nicole Hobbs, Bradley Feiger, John Cole, Tricia Carrigan, Joseph Peterson, John Pfeiffer, Daniel Cook. Spatial PK/PD Model with HER2 Expression for Predicting Individual Tumor Response to T-DM1 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-01-05.

Abstract 4761: Understanding three-drug combinations: optimizing scheduling while avoiding toxicity

Abstract The promise of combination therapies in managing tumor resistance is constrained by the therapeutic window (the difference between efficacious and toxic doses). We have sought to understand the impact of dose scheduling on the emergence of resistance, using a mathematical model-based approach linking pharmacokinetics (PK) to a parsimonious evolutionary model of tumor growth incorporating the emergence of drug resistance. Here, we analyze the potential of a three-drug combination to minimize toxicity while preventing the emergence of resistance. We simulated eight tumor subpopulations representing resistance to one, two or three hypothetical drugs, using an exponential growth model with growth penalties based on drug concentrations. We used the model to simulate the effects of pairs of antagonistic, synergistic, and additive drugs on the growth of sensitive and resistant populations in a tumor. Final tumor volume and resistant population were used to compare the efficacy of various drug schedules. We assumed an overlapping neutropenia-like toxicity as the dose-limiting toxicity for the three drug combination, which we have previously shown to be proportional to the peak moving average drug concentration over 18 days. Final tumor volume and peak toxicity were used to compare the effectiveness of various dosing strategies and interaction combinations. Synchronous dosing results in the greatest drug interaction effect between any two drugs. When all interactions between the three drugs are either antagonistic or synergistic, the greatest effect is observed when all drugs are dosed simultaneously. The drugs are most toxic when all three are dosed simultaneously or nearly simultaneously. Our work shows that time sensitivity—that is, the magnitude of the changes in efficacy associated with small changes in schedule—varies with phase offset. Scheduling is most time sensitive when all drugs are dosed simultaneously or nearly simultaneously; dosing of two drugs simultaneously is less time sensitive. Three-drug combinations are an effective means of preventing complete resistance. While simultaneous dosing of two or more drugs confers the greatest efficacy, such simultaneous dosing results in greater peak toxicity because of higher simultaneous drug concentrations. A potential compromise is the simultaneous dosing of two of the three drugs, which results in an intermediate toxicity. Dosing of two drugs simultaneously is also less time sensitive, advantageous in a practical sense as it is more robust to patient dosing error. While the approach used here is based on hypothetical drug properties, it provides a framework that is readily applicable to real-world drug combinations, with the potential for practical insights to guide the framing of the Target Product Profile for three-drug combinations. Citation Format: Madison Stoddard, Lin Yuan, Debra Van Egeren, Andrew Chen, Dean Bottino, Arijit Chakravarty. Understanding three-drug combinations: optimizing scheduling while avoiding toxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4761.

Abstract 4310: Impact of drug combination schedules on the evolution of tumor resistance

Abstract The emergence of drug resistance during treatment is a critical limiting factor for the long-term effectiveness of anticancer therapies. The use of drug combinations limits the emergence of resistance, thereby prolonging their therapeutic utility. The effect of a drug combination is dependent both on the concentration of the individual drugs and the extent of their interaction (synergistic, additive, or antagonistic). Thus, understanding the scheduling implications for efficacy can be valuable for optimizing tumor response and time to resistance for the combination. To examine this more closely, we used a pharmacokinetic/pharmacodynamic (PK/PD) modeling approach, coupling one-compartment PK models of two hypothetical drugs based on set synchronous or asynchronous (offset) schedules with an evolutionary model of tumor clone growth. We simulated four tumor subpopulations representing binary resistance to one or both drugs, using an exponential growth model with growth penalties based on drug concentrations. We used the model to simulate the effects of pairs of antagonistic, synergistic, and additive drugs on the growth of sensitive and resistant populations in a tumor. Final tumor volume and resistant population were used to compare the efficacy of various drug schedules. As expected, the effect of a drug interaction—either synergistic or antagonistic—is greatest when dosing is synchronous, as this results in the greatest simultaneous drug concentration. The effect of a drug interaction is proportional to the sensitive population size, so the effect of drug interactions decreases over time as the sensitive population is eliminated. Intuitively, the final tumor volume decreases as the strength of a synergistic interaction increases until the sensitive population is eliminated. The resistant populations are unaffected by the strength of the interaction for both antagonistic and synergistic combinations. Resistant populations are not affected by interactions between drugs to which they are resistant, so the growth of resistant populations over time is independent of drug interactions. Crucially, for effective drugs—that is, drugs that eliminate the sensitive population—synergy and antagonism converge to additivity as the sensitive population dies out because the remaining resistant populations are not affected by drug interactions. As synergistic and additive drug combinations are equivalent in the long-term, synergy and asynchronous dosing could be used to limit toxicity without sacrificing efficacy. The evolution of resistance also explains why in vitro synergy or antagonism may not translate in vivo. Taken together, our work provides several unintuitive insights about combination drug scheduling with practical implications for therapeutic design. Citation Format: Madison Stoddard, Andrew Chen, Lin Yuan, Debra Van Egeren, Dean Bottino, Arijit Chakravarty. Impact of drug combination schedules on the evolution of tumor resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4310.

Pre and Post-high-intensity Interval Training Delays Colon Tumor Onset in a Syngeneic Mouse Model.

High-intensity interval training (HIIT) can trigger transient anti-tumor cytotoxicity through the mobilization of natural killer cells (NK cells) and myokines. Yet, the effects of HIIT on tumor development and microenvironment are unclear. Male C57/BL6 mice were administered either MC38 of syngeneic colon cancer cells or vehicle in a single subcutaneous injection. Before injection, the training group completed four weeks of the HIIT program (progressive swimming training, 3/week, 10-12 min, 4-6% of body weight for overload). Following injection, trained mice continued to exercise for two additional weeks. Pre and post-HIIT training was effective in preventing tumor onset (p=0.0065), maintaining body weight gain, and counteracting splenomegaly by 40% compared to the tumor group. However, HIIT had no impact on suppressing tumor growth, modifying final tumor volume, or significantly changing tumor proliferation (Ki-67), connective tissue content, or DNA double-strand damage detected by phospho-histone gamma-H2AX (γ-H2AX). Pre and post-HIIT program is feasible for mice carrying a subcutaneous syngeneic tumor and effective in delaying tumor burden; however, HIIT did not alter colon tumor endpoints.

Non-invasive PD-L1 quantification using [18F]DK222-PET imaging in cancer immunotherapy

BackgroundCombination therapies that aim to improve the clinical efficacy to immune checkpoint inhibitors have led to the need for non-invasive and early pharmacodynamic biomarkers. Positron emission tomography (PET) is a...

Combined use of intraoperative MRI and awake tailored microsurgical resection to respect functional neural networks: preliminary experience.

The combined use of intraoperative MRI and awake surgery is a tailored microsurgical resection to respect functional neural networks (mainly the language and motor ones). Intraoperative MRI has been classically considered to increase the extent of resection for gliomas, thereby reducing neurological deficits. Herein, we evaluated the combined technique of awake microsurgical resection and intraoperative MRI for primary brain tumours (gliomas, metastasis) and epilepsy (cortical dysplasia, non-lesional, cavernomas). Eighteen patients were treated with the commonly used "asleep awake asleep" (AAA) approach at Lille University Hospital, France, from November 2016 until May 2020. The exact anatomical location was insular with various extensions, frontal, temporal or fronto-temporal in 8 (44.4%), parietal in 3 (16.7%), fronto-opercular in 4 (22.2%), Rolandic in two (11.1%), and the supplementary motor area (SMA) in one (5.6%). The patients had a mean age of 38.4 years (median 37.1, range 20.8-66.9). The mean surgical duration was 4.1 hours (median 4.2, range 2.6-6.4) with a mean duration of intraoperative MRI of 28.8 minutes (median 25, range 13-55). Overall, 61% (11/18) of patients underwent further resection, while 39% had no additional resection after intraoperative MRI. The mean preoperative and postoperative tumour volumes of the primary brain tumours were 34.7 cc (median 10.7, range 0.534-130.25) and 3.5 cc (median 0.5, range 0-17.4), respectively. Moreover, the proportion of the initially resected tumour volume at the time of intraoperative MRI (expressed as 100% from preoperative volume) and the final resected tumour volume were statistically significant (p= 0.01, Mann-Whitney test). The tumour remnants were commonly found posterior (5/9) or anterior (2/9) insular and in proximity with the motor strip (1/9) or language areas (e.g. Broca, 1/9). Further resection was not required in seven patients because there were no remnants (3/7), cortical stimulation approaching eloquent areas (3/7) and non-lesional epilepsy (1/7). The mean overall follow-up period was 15.8 months (median 12, range 3-36). The intraoperative MRI and awake microsurgical resection approach is feasible with extensive planning and multidisciplinary collaboration, as these methods are complementary and synergic rather than competitive to improve patient oncological outcomes and quality of life.

Abstract P1-04-08: Independent Validation of a Novel, Non-invasive Approach to Predict Pathologic Complete Response (pCR) in a Blinded, Prospectively-Run Single Center Trial

Abstract Background: As pathologic complete response (pCR) is correlated with higher rates of event free survival, accurately forecasting pCR advances our collective endeavors in precision oncology to discern and translate individual patient-specific data into risk stratification. We developed the TumorScope engine, a software platform that utilizes pretreatment diagnostic data to build a computational tumor model that simulates in vivo tumor characteristics and interactions, incorporating morphology, metabolism, vascularity, and nutrient and drug delivery. This non-invasive approach enables accurate forecasting of a patient’s response to physician-chosen neoadjuvant chemotherapy-based treatment (NAC). Here we validate the prognostic capacity of this technology at a single site cancer center. Methods: A blinded, prospective trial using retrospective data was conducted at UNC. The study cohort included patients aged 18 years or older diagnosed with any subtype of breast cancer who were treated with a NAC regimen and had a pre-treatment T1-weighted dynamic contrast enhanced (DCE) MRI available. Pre-treatment diagnostic and planned treatment data (demographics, drug regimen, receptor status (ER/PR/HER2), DCE MRI, and pathology) were input into the TumorScope engine to simulate predicted final tumor volumes (Vt) for each tumor and predict pCR or residual disease (RD); pCR predictions were compared to post-surgery pathologic assessments defined as ypT0/is/N0. Predicted pCR was set at pre-defined threshold of predicted Vt less than 0.01 cm^3, or at least a 99.9% Vt reduction. Results: One hundred and fifty subjects with 157 tumors were enrolled in the study. After excluding missing data (absent DCE-MRI), a total of 143 cases in 136 patients were included. The majority of patients self-identified as Caucasian (63%) or African American (23%). TumorScope had a pCR overall prediction accuracy of 92.3% (95% CI: 86.7 - 96.1%) with a sensitivity of 90.9 % (95% CI: 75.7 - 98.1 %) and specificity of 92.7% (95% CI: 86.2 – 96.8%). Based on our subgroup analysis, predictive accuracy remained reliable for HR+/HER2- (n=65; 95.4%), HR+/HER2+ (n=20; 85.0%), HR-/HER2+ (n=21; 85.7%) and TNBC (n=37; 94.6%) subtypes. Predictive performance remained stable across ethnic subtypes and tumor grade (see Table 1). Conclusion: The TumorScope noninvasive method that incorporates imaging, pathologic, demographic and planned treatment data appears to accurately predict an individual patient’s probability of pCR across clinical subtypes. Table 1. TumorScope prediction performance. Citation Format: Cherie Kuzmiak, Terry S. Hartman, Thad Benefield, Joseph Peterson, Anuja K. Antony, Tushar Pandey, John A. Cole Jr, Benjaminc C. Calhoun, Lisa Carey. Independent Validation of a Novel, Non-invasive Approach to Predict Pathologic Complete Response (pCR) in a Blinded, Prospectively-Run Single Center Trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-04-08.

Doxorubicin Efficacy Prediction for Glioblastomas using Deep Learning and Differential Equations

This paper presents a novel approach for predicting the efficacy of Doxorubicin treatment for glioblastoma. Glioblastomas' rapid growth places them among the most aggressive cancers, killing thousands of Americans every year. The rapid progression of glioblastoma coupled with the high cost of cranial imaging makes clinical decision-making uniquely challenging. Doxorubicin is a commonly used chemotherapy drug to treat glioblastomas. However, predicting the treatment's efficacy remains challenging and time-consuming. Inaccurate predictions can lead to ineffective treatments, severe side effects, and even death. To address this issue, a framework was developed that amalgamates deep learning and differential equations to accurately predict tumor volume growth over time. Specifically, a 2D U-net convolutional neural network (CNN) was employed to segment MRI brain tumor regions and obtain initial volumes. The Gompertz differential equation was then utilized to model the predicted tumor volume growth over time, achieving a mean absolute percent error of 4.98 %. The Gompertz model was modified to incorporate the cytotoxic effect of Doxorubicin treatment. The methodology predicted the final tumor volume of the tumor after being treated with Doxorubicin over multiple 21-day cycles, enabling us to predict the efficacy of treatment and identify patients who may benefit most from this therapy. A user-friendly web application was developed to allow users to input NIFTI files of MRI scans and receive as output a time-course prediction of tumor volume with and without chemotherapy treatment. This approach provides a prediction of Doxorubicin treatment efficacy and can improve patient outcomes and treatment plans.

MRI- and PET-Based Assessment of Radiological and Clinical Factors Associated With Cervical Cancer Response to External Beam Radiation Therapy.

Introduction In the era of MRI-guided external beam radiation therapy (EBRT), complete radiological response (CR) is often seen in cervical cancer (CC) with 4-6 weeks of chemotherapy and EBRT. The clinical and radiological factors associated with this observation were investigated in this study. Materials and methods One hundred and twenty-four CC patients treated with concurrent chemotherapy, EBRT, and brachytherapy (BT) from January 2008 to July 2015 were retrospectively screened. Initial primary gross tumor volume (GTVINITIAL) was estimated after contouring on a planning CT scan registered with pre-EBRT PET and MRI. The maximum standardized uptake value (SUV) of GTVINITIAL from each PET scan report was collected. Spearman's rank correlation coefficient (rho) values were calculated to assess the relationships among age, tumor size, and SUV. Tumor radiological response during EBRT prior to BT was calculated by contouring the final primary gross tumor volume (GTVFINAL) using MRI obtained prior to BT. CRrates during EBRT were estimated from GTVINITIAL and GTVFINAL and compared by the level of various factors using Fisher's exact test (two-sided). Results Forty-eight patients met the inclusion criteria of the study with a median age of 50 years. The median GTVINITIAL was 82 cc. The median SUV was 14.9. A significant correlation was seen between SUV and GTVINITIAL with a larger tumor size associated with a higher SUV. CR rates were numerically higher for patients who were aged <50 years, or with >37.5 Gy radiation dose at or before the second MRI, or with GTVINITIAL <100 cc, or with no nodes involved or with stages IB or IIA. Conclusions Our study identified higher CC primary tumor CR rates during EBRT in younger patients (<50) with smaller tumors (100 cc) without nodal involvements as well as a positive correlation between PET FDG (18F-fluorodeoxyglucose)-SUV and CC primary tumor size.

Lentivirus-mediated short hairpin RNA interference of CENPK inhibits growth of colorectal cancer cells with overexpression of Cullin 4A.

BACKGROUNDColorectal cancer (CRC) is one of the most common malignant tumors worldwide. The identification of novel diagnostic and prognostic biomarkers for CRC is a key research imperative. Immunohistochemical analysis has revealed high expression of centromere protein K (CENPK) in CRC. However, the role of CENPK in the progression of CRC is not well characterized.AIMTo evaluate the effects of knockdown of CENPK and overexpression of Cullin 4A (CUL4A) in RKO and HCT116 cells.METHODSHuman colon cancer samples were collected and tested using a human gene expression chip. We identified CENPK as a potential oncogene for CRC based on bioinformatics analysis. In vitro experiments verified the function of this gene. We investigated the expression of CENPK in RKO and HCT116 cells using quantitative polymerase chain reaction (qPCR), western blot, and flow cytometry. The effect of short hairpin RNA (shRNA) virus-infected RKO cells on tumor growth was evaluated in vivo using quantitative analysis of fluorescence imaging. To evaluate the effects of knockdown of CENPK and overexpression of CUL4A in RKO and HCT116 cells, we performed a series of in vitro experiments, using qPCR, western blot, MTT assay, and flow cytometry.RESULTSWe demonstrated overexpression of CENPK in human colon cancer samples. CENPK was an independent risk factor in patients with CRC. The downstream genes FBX32, CUL4A, and Yes-associated protein isoform 1 were examined to evaluate the regulatory action of CENPK in RKO cells. Significantly delayed xenograft tumor emergence, slower growth rate, and lower final tumor weight and volume were observed in the CENPK short hairpin RNA virus infected group compared with the CENPK negative control group. The CENPK gene interference inhibited the proliferation of RKO cells in vitro and in vivo. The lentivirus-mediated shRNA interference of CENPK inhibited the proliferation of RKO and HCT116 colon cancer cells, with overexpression of the CUL4A.CONCLUSIONWe indicated a potential role of CENPK in promoting tumor proliferation, and it may be a novel diagnostic and prognostic biomarker for CRC.

Reduction of sporadic and neurofibromatosis type 2-associated vestibular schwannoma growth in vitro and in vivo after treatment with the c-Jun N-terminal kinase inhibitor AS602801.

Vestibular schwannomas (VSs) are benign nerve sheath tumors that result from mutation in the tumor suppressor gene NF2, with functional loss of the protein merlin. The authors have previously shown that c-Jun N-terminal kinase (JNK) is constitutively active in human VS cells and plays a central role in their survival by suppressing accumulation of mitochondrial superoxides, implicating JNK inhibitors as a potential systemic treatment for VS. Thus, the authors hypothesized that the adenosine 5'-triphosphate-competitive JNK inhibitor AS602801 would demonstrate antitumor activity in multiple VS models. Treatment with AS602801 was tested in primary human VS cultures, human VS xenografts, and a genetic mouse model of schwannoma (Postn-Cre;Nf2flox/flox). Primary human VS cell cultures were established from freshly obtained surgical tumor specimens; treatment group media was enriched with AS602801. VS xenograft tumors were established in male athymic nude mice from freshly collected human tumor. Four weeks postimplantation, a pretreatment MRI scan was obtained, followed by 65 days of AS602801 (n = 18) or vehicle control (n = 19) treatment. Posttreatment MRI scans were used to measure final tumor volume. Tumors were then harvested. Finally, Postn-Cre;Nf2flox/flox mice were treated with AS602801 (n = 10) or a vehicle (n = 13) for 65 days. Posttreatment auditory brainstem responses were obtained. Dorsal root ganglia from Postn-Cre;Nf2flox/flox mice were then harvested. In all models, schwannoma identity was confirmed with anti-S100 staining, cell proliferation was measured with the EdU assay, and cell death was measured with terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling staining. All protocols were approved by the local institutional review board and Institutional Animal Care and Use Committees. Treatment with AS602801 decreased cell proliferation and increased apoptosis in primary human VS cultures. The systemic administration of AS602801 in mice with human VS xenografts reduced tumor volume and cell proliferation. Last, the AS602801-treated Postn-Cre;Nf2flox/flox mice demonstrated decreased cell proliferation in glial cells in the dorsal root ganglia. However, AS602801 did not significantly delay hearing loss in Postn-Cre;Nf2flox/flox mice up to 3 months posttreatment. The data suggest that JNK inhibition with AS602801 suppresses growth of sporadic and neurofibromatosis type 2-associated VSs. As such, AS602801 is a potential systemic therapy for VS and warrants further investigation.

Prolonged blood circulation outperforms active targeting for nanocarriers-mediated enhanced hepatocellular carcinoma therapy in vivo.

Successful hepatocellular carcinoma (HCC) therapy in vivo remains a significant challenge due to the down-regulated expression of the receptors on the surface of tumor cells for compromised active targeting efficiency and cellular uptake of nanoparticles (NPs)-based drug delivery systems (DDSs) and "accelerated blood clearance" and premature unpackaging of NPs in vivo induced by the poly(ethylene glycol)ylation (PEGylation). Inspired by the repeatedly highlighted prolonged blood circulation property of RBCm-camouflaged NPs, we hypothesis that the prolonged blood circulation property resulting from RBCm coating outperforms the active targeting mechanisms of various targeting ligands for enhanced HCC therapy in vivo. Clarification of this hypothesis is therefore of great significance and urgency to break the afore mentioned bottlenecks that hamper the efficient HCC treatment in vivo. For this purpose, we reported in this study the first identification of a determining factor of nanocarriers for enhanced HCC therapy in vivo by the use of the previously fabricated pectin-doxorubicin nanoparticles (PDC-NPs) as a typical example, i.e., the natural RBCm was used as a stealth coating of PDC-NPs for the fabrication of biomimetic DDSs, PDC@RBC-NPs via hypotonic dialysis and mechanical co-extrusion methods. Comprehensive in vitro and in vivo evaluation and comparison of the properties and performance of PDC@RBC-NPs and PDC-NPs were performed in terms of colloidal stability, biosafety, drug release profiles, macrophage escape, anti-HCC effect. The resulting PDC@RBC-NPs outperformed PDC-NPs for HCC therapy in vitro and in vivo. Notably, PDC@RBC-NPs-treated BALB/c nude mice showed a significantly smaller final average tumor volume of 613 mm3 after 16days than the PDC-NPs-treated group with an average value of 957 mm3. Therefore, the PDC@RBC-NPs developed herein showed great potential for clinical transformations due to the facile preparation and superior therapeutic efficiency against HCC. Most importantly, prolonged blood circulation was identified as a determining factor of nanocarriers instead of active targeting for enhanced HCC therapy in vivo, which could be used to direct the future design and development of advanced DDSs with greater therapeutic efficiency for HCC.

Abstract 2477: PD-L1 PET quantifies the pharmacodynamic effects of immunotherapy

Abstract Introduction: Immune checkpoint protein targeted therapeutics have transformed cancer treatment but only a subset of patients derive benefit. To improve efficacy, a variety of combination therapies are being studied. Programmed death ligand-1 (PD-L1) immunohistochemistry (IHC) is used as a biomarker to guide many of those therapies. Non-invasive evaluation of therapy induced changes in PD-L1 levels in the whole body could provide insights to guide those therapies. Here, we investigated the potential of [18F]DK222, a novel PD-L1 binding positron emission tomography (PET) imaging agent, to quantify PD-L1 levels and pharmacodynamics in humanized mouse modes. Methods: Non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and melanoma cell lines were screened by flow cytometry (FC) for PD-L1 expression and density. In vitro cell uptake assays, in vivo PET imaging and ex vivo biodistribution studies were used to evaluate the specificity of [18F]DK222 to bind PD-L1 (n=5-6/tumor). To quantify immunotherapy induced changes in PD-L1, A375 melanoma xenografts were inoculated in NSG mice humanized with CD34+ cells. Mice were treated with either 5 mg/kg anti- PD-1; (pembrolizumab) or 5 mg/kg of anti-PD-1 + 4 mg/kg of anti- CTLA-4 (ipilimumab) (n=5) and [18F]DK222 PET was acquired before and 7 days after start of treatment. Tumor growth was monitored. FC of tumors was performed to measure changes in TME and immune cell infiltrates. Results: In vitro uptake of [18F]DK222 in NSCLC (H244 &amp;gt; H226 &amp;gt; A549) and UC (BFTC909 &amp;gt; T24 &amp;gt; SCaBER) correlated with PD-L1 density (R2=0.96). [18F]DK222 PET and biodistribution studies in mice with NSCLC and UC xenografts revealed high and variable tumor uptake at 60 min, which was in agreement with PD-L1 levels detected by IHC. These data established sensitivity of [18F]DK222 PET to quantify variable PD-L1 levels in vivo. We next sought to quantify therapy induced changes in PD-L1 levels. We observed higher [18F]DK222 uptake in tumors of mice treated with combination therapy compared to monotherapy (1.83 vs 0.47 %ID/cc). A significant delay in tumor growth was observed with combination therapy compared to monotherapy. Two out of five mice with highest increase in [18F]DK222 uptake in combination therapy group exhibited least tumor growth. Also, final tumor volumes negatively correlated with [18F]DK222 uptake (R2=0.33) irrespective of treatment regimen. FC analysis showed higher immune infiltrates (1320 vs 230 per milligram of tumor), PD-L1+ cells (6005 vs 2739/mg) and ratio of CD8+ to CD4+ cells (1.94 vs 0.47) in tumors treated with combination therapy compared with monotherapy. These observations confirmed that immunotherapy induced changes in PD-L1 levels in tumors can be quantified using [18F]DK222 PET. Conclusion: [18F]DK222 PET can effectively quantify variable PD-L1 levels in tumors. Moreover, [18F]DK222 PET exhibits the sensitivity to quantify PD-L1 pharmacodynamics to inform on tumor response to therapy. Citation Format: Akhilesh Mishra, Dhiraj Kumar, Kuldeep Gupta, Patrick M. Forde, Edward Gabrielson, Sridhar Nimmagadda. PD-L1 PET quantifies the pharmacodynamic effects of immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2477.

Assessing the performance of different outcomes for tumor growth studies with animal models.

The consistency of reporting results for patient‐derived xenograft (PDX) studies is an area of concern. The PDX method commonly starts by implanting a derivative of a human tumor into a mouse, then comparing the tumor growth under different treatment conditions. Currently, a wide array of statistical methods (e.g., t‐test, regression, chi‐squared test) are used to analyze these data, which ultimately depend on the outcome chosen (e.g., tumor volume, relative growth, categorical growth). In this simulation study, we provide empirical evidence for the outcome selection process by comparing the performance of both commonly used outcomes and novel variations of common outcomes used in PDX studies. Data were simulated to mimic tumor growth under multiple scenarios, then each outcome of interest was evaluated for 10 000 iterations. Comparisons between different outcomes were made with respect to average bias, variance, type‐1 error, and power. A total of 18 continuous, categorical, and time‐to‐event outcomes were evaluated, with ultimately 2 outcomes outperforming the others: final tumor volume and change in tumor volume from baseline. Notably, the novel variations of the tumor growth inhibition index (TGII)—a commonly used outcome in PDX studies—was found to perform poorly in several scenarios with inflated type‐1 error rates and a relatively large bias. Finally, all outcomes of interest were applied to a real‐world dataset.

“X”ploring the multifaceted functions of NLRX1 in triple-negative breast cancer

Abstract Breast cancer is a devastatingly common and deadly malignancy, and despite improved survival resulting from improved detection and treatment, triple-negative breast cancer (TNBC) remains difficult to treat. While historically studied in the context of infectious diseases, a multifaceted anti-inflammatory pattern recognition receptor called NLRX1 has recently been investigated in several types of cancers due to its involvement in several pathways significant to tumorigenesis and disease progression. This project seeks to define the role of NLRX1 in TNBC. To achieve this, we generated novel Nlrx1−/−(KO) mice compatible with the widely-used 4T1 murine model of TNBC. We also generated 4T1 cells that either overexpress or knockdown NLRX1, as well as their respective controls (4T1OE, 4T1OE-CTL, 4T1KD, 4T1KD-CTL). KO and wild-type (WT) mice were then injected with unaltered 4T1 cells or one of the four altered 4T1 cell lines. We then quantified tumor growth, final tumor volume, and lung metastasis as a measure of disease burden. This in vivo work demonstrated that NLRX1 is protective against disease burden when expressed in healthy host tissues but is problematic when overexpressed by 4T1 cells. Ex vivo and in vitro experiments then revealed a pro-migratory phenotype in 4T1OE cells, likely as the result of altered TGF-β signaling and/or the PI3K-Akt-mTOR pathway as a means to impact epithelial-mesenchymal transition. Combined, we believe the function of NLRX1 in TNBC depends on the cell in which it is expressed (i.e. healthy vs cancerous), and that this function may ultimately be a result of altered epithelial-mesenchymal transition pathways.

Hearing loss and volumetric growth rate in untreated vestibular schwannoma.

In this study, the authors aimed to clarify the relationship between hearing loss and tumor volumetric growth rates in patients with untreated vestibular schwannoma (VS). Records of 128 treatment-naive patients diagnosed with unilateral VS between 2012 and 2018 with serial audiometric assessment and MRI were reviewed. Tumor growth rates were determined from initial and final tumor volumes, with a median follow-up of 24.3 months (IQR 8.5-48.8 months). Hearing changes were based on pure tone averages, speech discrimination scores, and American Academy of Otolaryngology-Head and Neck Surgery hearing class. Primary outcomes were the loss of class A hearing and loss of serviceable hearing, estimated using the Kaplan-Meier method and with associations estimated from Cox proportional hazards models and reported as hazard ratios. Larger initial tumor size was associated with an increased risk of losing class A (HR 1.5 for a 1-cm3 increase; p = 0.047) and serviceable (HR 1.3; p < 0.001) hearing. Additionally, increasing volumetric tumor growth rate was associated with elevated risk of loss of class A hearing (HR 1.2 for increase of 100% per year; p = 0.031) and serviceable hearing (HR 1.2; p = 0.014). Hazard ratios increased linearly with increasing growth rates, without any evident threshold growth rate that resulted in a large, sudden increased risk of hearing loss. Larger initial tumor size and faster tumor growth rates were associated with an elevated risk of loss of class A and serviceable hearing.

Patient derived tumor xenograft study with CDK4/6 inhibitor plus AKT inhibitor for management of metastatic castrate resistant prostate cancer.

176 Background: Despite androgen deprivation therapy, prostate cancer will develop resistance known as castrate resistant prostate cancer (CRPC). Androgen signaling is associated with pathways that influence cell proliferation and survival via cell cycle regulation. AR signaling results in inactivation of Rb tumor suppressor by way of AKT and reduction in intrinsic CDK4/6 inhibitors. Since PTEN loss is found in 40% of mCRPC and AKT pathway is a mechanism of CDK4/6 inhibitor resistance, we hypothesize adding an AKT inhibitor to a CDK4/6 inhibitor will have synergistic activity while delaying CDK4/6 inhibitor resistance. Preclinical xenografts have been shown to recapitulate patient response, therefore, can be used to guide clinical trials using novel combinations. Methods: We have established patient derived tumor xenograft models (GUR-017M, TMA-027 and PRJ-88T) from patients with mCRPC with each having a unique genomic alteration profile. In the clinical setting, GUR-017M was resistant to abiraterone, enzalutamide, cabazitaxel and had exposure to docetaxel. TMA-027 and PRJ-88T were resistant to enzalutamide. We combined a CDK4/6 inhibitor with an AKT inhibitor and treated each of these patient tumors in NOD-SCID mice for a total duration of 40 days. Mice were implanted and separated into 4 groups (placebo, CDK4/6 inhibitor, AKT inhibitor and CDK4/6 + AKT inhibitor) with 10-13 mice in each group. Tumor volumes were measured twice a week. For GUR-017M, abemaciclib (50 mg/kg) was combined with MK2206 (120 mg/kg) and was compared to each placebo and each single agent alone. For TMA-027, palbociclib (50 mg/kg) was combined with ipatasertib (50 mg/kg). After 40 days, tumors were harvested for immunohistochemistry analysis. PRJ-88T was grown as 3D spheroids in ultra-low attachment plates and treated with palbociclib + ipatasertib (10 uM-100uM) to evaluate for synergy. Results: GUR-017M and TMA-027 showed significant delayed tumor growth compared to placebo or either single agent alone. In the GUR-017M group, the final mean tumor volume for the combination group was 149 mm3, compared to 377 mm3 (abemaciclib), 358 mm3 (MK2206) and 527 mm3 placebo group, representing a percent decrease compared to control by 72%, 29%, and 32%, respectively. For TMA-027, the final mean tumor volume for the combination group was 102 mm3, compared to 259 mm3 (palbociclib), 416 mm3 (ipatasertib), and 402 mm3 placebo group, representing a percent decrease compared to control by 75%, 36%, and 4%, respectively. PRJ-88T 3D spheroids showed synergy with palbociclib + ipatasertib. In vivo experiments using PRJ-88T are in progress. Conclusions: The preclinical results show combining CDK4/6 inhibitors with AKT inhibitors is a promising treatment strategy and provides the basis for a clinical trial in patients with mCRPC.

Effective Dose Fractionation Schemes of Radiotherapy for Prostate Cancer

Radiation therapy has remained as one of the main cancer treatment modalities and a highly cost-effective single modality treatment of cancer care. Typical regimens for fractionated external beam radiotherapy comprise a constant dose administered on weekdays, and no radiation on weekends. However, every patient has a tumor with distinct properties depending on intra-tumor heterogeneity, aggressiveness, and interactive properties with other cells that may make it more resistant or sensitive to radiation treatment. Accordingly, the concept of personalized cancer treatment is emerging to specialize each patient treatment case to the unique properties of the tumor. In this paper, we examine adaptive radiation treatment strategies for heterogeneous tumors using a dynamical system model that consists of radiation-resistant and parental cell populations with unique interactive properties. We study different adaptive dosage strategies for PC3 and DU145 prostate cancer cell lines. We show that stronger doses of radiation given in longer time intervals, while keeping the overall dosage the same, reduce final tumor volume by more than half in PC3 cell lines, but by only five percent in DU145 cell lines. In addition, we tested an adaptive dosing schedule by administering a stronger dosage on Friday to compensate for the treatment-off period during the weekend, which was effective in decreasing the final tumor volume of both cell lines. This result creates interesting possibilities for new radiotherapy strategies at clinics that cannot provide treatment on weekends. Finally, we propose a dosage plan incorporating our findings.