Tumor Size Measurements Research Articles

Tumor size measurements predicted by digital mammography, ultrasonography, and magnetic resonance imaging in primary invasive breast cancer disease

Background and objective: The size of the tumor significantly influences the prognosis and treatment approach for breast cancer patients. The aim of this study was to find the most accurate imaging method for estimating pre-treatment tumor size in women with newly diagnosed primary invasive breast cancer by comparing the predicted tumor size obtained from mammography, ultrasonography, and magnetic resonance imaging with the pathologic size obtained from the surgical specimens. Methods: This cross-sectional study included 181 primary invasive breast cancer patients from September 2021 to March 2023. The difference in tumor size was evaluated based on imaging and pathological reports. Variables such as age, breast density, and tumor characteristics like histologic type, grade, location, and side were recorded and analyzed. The American College of Radiology Breast Imaging Reporting and Data System was used for reporting. Data analysis, performed using SPSS Statistics software, included descriptive statistics, Spearman's correlation coefficient, and Lin's index. The statistical significance level was set at P <0.05. Results: The mean tumor size was 29.68, 29.07, 28.37, and 27.7mm by mammography, ultrasonography, magnetic resonance imaging, and pathology, respectively. All diagnostic procedures revealed a statistically significant correlation with pathologic tumor size with the Spearman correlation test, P = 0.000. MRI had the highest Lin’s concordance correlation coefficient (0.93). Conclusion: The study determined that all imaging modalities were accurate in estimating tumor size when compared to the gold standard of pathological specimens and that magnetic resonance imaging outperformed digital mammography and ultrasonography.

Visual predictive check of longitudinal models and dropout.

Visual predictive checks (VPC) are commonly used to evaluate pharmacometrics models. However their performance may be hampered if patients with worse outcomes drop out earlier, as often occurs in clinical trials, especially in oncology. While methods accounting for dropouts have appeared in literature, they vary in assumptions, flexibility, and performance, and the differences between them are not widely understood. This manuscript aims to elucidate which methods can be used to handle VPC with dropout and when, along with a more informative VPC approach using confidence intervals. Additionally, we propose constructing the confidence interval based on the observed data instead of the simulated data. The theoretical framework for incorporating dropout in VPCs is developed and applied to propose two approaches: full and conditional. The full approach is implemented using a parametric time-to-event model, while the conditional approach is implemented using both parametric and Cox proportional-hazard (CPH) models. The practical performances of these approaches are illustrated with an application to the tumor growth dynamics (TGD) modeling of data from two cancer clinical trials of nivolumab and docetaxel, where patients were followed until disease progression. The dataset consisted of 3504 tumor size measurements from 855 subjects, which were described by a TGD model. The dropout of subjects was described by a Weibull or CPH model. Simulated datasets were also used to further illustrate the properties of the VPC methods. The results showed that the more familiar full approach might not provide meaningful improvement for TGD model evaluation over the naive approach of not adjusting for dropout, and could be outperformed by the conditional approach using either the Weibull model or the Cox proportional hazard model. Overall, including confidence intervals in VPC should improve interpretation, the conditional approach was shown to be more generally applicable when dropout occurs, and the nonparametric approach could provide additional robustness.

Loss of histone deubiquitinase Bap1 triggers anti-tumor immunity.

Immunotherapy using PD-L1 blockade is effective in only a small group of cancer patients, and resistance is common. This emphasizes the importance of understanding the mechanisms of cancer immune evasion and resistance. A genome-scale CRISPR-Cas9 screen identified Bap1 as a regulator of PD-L1 expression. To measure tumor size and survival, tumor cells were subcutaneously injected into both syngeneic WT mice and immunocompromised mice. The phenotypic and transcriptional characteristics of Bap1-deleted tumors were examined using flow cytometry, RNA-seq, and CUT&Tag-seq analysis. We found that loss of histone deubiquitinase Bap1 in cancer cells activates a cDC1-CD8+ T cell-dependent anti-tumor immunity. The absence of Bap1 leads to an increase in genes associated with anti-tumor immune response and a decrease in genes related to immune evasion. As a result, the tumor microenvironment becomes inflamed, with more cDC1 cells and effector CD8+ T cells, but fewer neutrophils and regulatory T cells. We also found that the elimination of Bap1-deleted tumors depends on the tumor MHCI molecule and Fas-mediated CD8+ T cell cytotoxicity. Our analysis of TCGA data further supports these findings, showing a reverse correlation between BAP1 expression and mRNA signatures of activated DCs and T-cell cytotoxicity in various human cancers. The histone deubiquitinase Bap1 could be used as a biomarker for tumor stratification and as a potential therapeutic target for cancer immunotherapies.

The BET PROTAC inhibitor GNE-987 displays anti-tumor effects by targeting super-enhancers regulated gene in osteosarcoma

BackgroundOsteosarcoma (OS) is one of the most common primary malignant tumors of bone in children, which develops from osteoblasts and typically occurs during the rapid growth phase of the bone. Recently, Super-Enhancers(SEs)have been reported to play a crucial role in osteosarcoma growth and metastasis. Therefore, there is an urgent need to identify specific targeted inhibitors of SEs to assist clinical therapy. This study aimed to elucidate the role of BRD4 inhibitor GNE-987 targeting SEs in OS and preliminarily explore its mechanism.MethodsWe evaluated changes in osteosarcoma cells following treatment with a BRD4 inhibitor GNE-987. We assessed the anti-tumor effect of GNE-987 in vitro and in vivo by Western blot, CCK8, flow cytometry detection, clone formation, xenograft tumor size measurements, and Ki67 immunohistochemical staining, and combined ChIP-seq with RNA-seq techniques to find its anti-tumor mechanism.ResultsIn this study, we found that extremely low concentrations of GNE-987(2–10 nM) significantly reduced the proliferation and survival of OS cells by degrading BRD4. In addition, we found that GNE-987 markedly induced cell cycle arrest and apoptosis in OS cells. Further study indicated that VHL was critical for GNE-987 to exert its antitumor effect in OS cells. Consistent with in vitro results, GNE-987 administration significantly reduced tumor size in xenograft models with minimal toxicity, and partially degraded the BRD4 protein. KRT80 was identified through analysis of the RNA-seq and ChIP-seq data. U2OS HiC analysis suggested a higher frequency of chromatin interactions near the KRT80 binding site. The enrichment of H3K27ac modification at KRT80 was significantly reduced after GNE-987 treatment. KRT80 was identified as playing an important role in OS occurrence and development.ConclusionsThis research revealed that GNE-987 selectively degraded BRD4 and disrupted the transcriptional regulation of oncogenes in OS. GNE-987 has the potential to affect KRT80 against OS.

Circulating tumor HPV DNA in the management of HPV+ oropharyngeal cancer and its correlation with MRI.

First aim was to compare ddPCR assays of ctHPVDNA with p16 IHC and qualitative HPV PCR. Second aim was to carry out longitudinal blood sampling to test for association of ctHPVDNA with histological confirmed recurrence. Third aim was to perform a multidimensional assessment which included: (1) clinical features; (2) ctHPVDNA; (3) MRI-based tumor size measurements of primary tumor (PT) and cervical lymph node metastases (CLNM). Plasma samples were collected before treatment and during follow-up, and ddPCR assay comprising E6 of HPV16 and HPV 33 and HPV 35 was used. Present study was conducted at diagnosis in 117 patients and revealed a ctHPVDNA sensitivity of 100% (95% CI 95.5-100) and a specificity of 94.4 (95% CI 81.3-99.3), positive predictive value (PPV) of 94.4 (95% CI 81.3-99.3), and negative predictive value (NPP) of 100% (95% CI 89.7-100). During follow-up ctHPVDNA had a sensitivity of 100% (95% CI 72.1-100)% and specificity of 98.4% (95% CI 91.7-100)%, PPV% of 90.9% (95% CI 62.3-98.4) and NPV% of 100% (95% CI 94.3-100) for ability to detect recurrence. Correlation between both the CLNM volume and the sum of PT and CLNM volume was observed. ctHPVDNA was superior to p16 in identification of HPV-OPSCC at diagnosis. Introduction of ctHPVDNA, beyond diagnostic setting, represents a great opportunity to improve follow-up protocol of OPSCC patients.

LncRNA HOXC-AS3 accelerates malignant proliferation of cervical cancer cells via stabilizing KDM5B

BackgroundCervical cancer (CC) is a common malignancy amongst women globally. Ubiquitination plays a dual role in the occurrence and development of cancers. This study analyzed the mechanism of long noncoding RNA HOXC cluster antisense RNA 3 (lncRNA HOXC-AS3) in malignant proliferation of CC cells via mediating ubiquitination of lysine demethylase 5B (KDM5B/JARID1B).MethodsThe expression patterns of lncRNA HOXC-AS3 and KDM5B were measured by real-time quantitative polymerase chain reaction or Western blot analysis. After transfection with lncRNA HOXC-AS3 siRNA and pcDNA3.1-KDM5B, proliferation of CC cells was assessed by the cell counting kit-8, colony formation, and 5-Ethynyl-2’-deoxyuridine staining assays. The xenograft tumor model was established to confirm the impact of lncRNA HOXC-AS3 on CC cell proliferation in vivo by measuring tumor size and weight and the immunohistochemistry assay. The subcellular location of lncRNA HOXC-AS3 and the binding of lncRNA HOXC-AS3 to KDM5B were analyzed. After treatment of lncRNA HOXC-AS3 siRNA or MG132, the protein and ubiquitination levels of KDM5B were determined. Thereafter, the interaction and the subcellular co-location of tripartite motif-containing 37 (TRIM37) and KDM5B were analyzed by the co-immunoprecipitation and immunofluorescence assays.ResultsLncRNA HOXC-AS3 and KDM5B were upregulated in CC tissues and cells. Depletion of lncRNA HOXC-AS3 repressed CC cell proliferation and in vivo tumor growth. Mechanically, lncRNA HOXC-AS3 located in the nucleus directly bound to KDM5B, inhibited TRIM37-mediated ubiquitination of KDM5B, and upregulated the protein levels of KDM5B. KDM5B overexpression attenuated the inhibitory role of silencing lncRNA HOXC-AS3 in CC cell proliferation in vivo and in vitro.ConclusionNucleus-located lncRNA HOXC-AS3 facilitated malignant proliferation of CC cells via stabilization of KDM5B protein levels.

Evaluation of early response in association with pathological response in patients with breast cancer receiving neoadjuvant chemotherapy.

e12628 Background: Neoadjuvant therapy (NAT) has now been widely used for patients with operable breast cancer (BC) to test drug sensitivity. Studies have indicated that early assessment of clinical response to NAT can help identify patients who are resistant to initial regimens, providing an additional opportunity to change treatment plan. However, there is a lack of evidence regarding the optimal timing for conducting early evaluations of clinical response. This prospective study was conducted to evaluate the association between early evaluation of clinical response at different timing (post 2 cycles versus post 4 cycles) and pCR post NAT, in order to determine the most appropriate timing for NAT response evaluation. Clinical evaluations using ultrasound and MRI (magnetic resonance imaging) were also compared. Methods: A prospective cohort study including BC patients who received NAT was conducted between January 2018 and December 2023. Multivariable logistic regression analysis was used to estimate the Odds Ratios (OR) and 95% confidence intervals (CI) for the clinical response evaluated at different timings in association with pCR. The heterogeneity of the associations for the post-cycle 2 and post-cycle 4 assessments was assessed. Linear regression analyses were used to assess the associations between extent of tumor reduction post 2 cycles and that post 4 cycles of NAT. Agreement of tumor measurements using ultrasound and MRI was also assessed. Results: A total of 186 BC patients were consecutively enrolled and included in this analysis. 55 (29.6%) of them achieved pCR. Partial response (PR) post 2 cycles and 4 cycles of NAT were both significantly associated with pCR post NAT, though the point estimate of association for PR post 2 cycles of NAT (OR=5.06, 95%CI:2.29-12.09) was more evident than that post 4 cycles (OR=2.79, 95%CI:1.20-7.21). Extent of tumor reduction post two cycles of NAT was highly correlated with that post four cycles (r=0.89, 95%CI=0.79-0.98, P< 0.01). Poor concordance was observed between ultrasound and MRI measurements of tumor size, whether at initial diagnosis (r=0.66, adjusted r2=0.43) or after two cycles of NAT (r=0.59, adjusted r2=0.35). Among those patients who had PR post 2 cycles of NAT, tumor reduction by greater than 50% was not associated with higher probability of reaching pCR in comparison to those lower than 50% (OR=1.86, 95%CI=0.82-4.37, P=0.143). Conclusions: Tumor response assessed using MRI after two cycles of NAT was highly correlated with pCR, and may be adopted as an optimal strategy for early evaluation of the efficacy of NAT regimen. Further studies are warranted to evaluate changes in treatment plan at early phase of NAT for those resistant to initial regimens.

Deciphering Tumor Response: The Role of Fluoro-18-d-Glucose Uptake in Evaluating Targeted Therapies with Tyrosine Kinase Inhibitors.

Background/Objectives: The inhibitory effects of tyrosine kinase inhibitors (TKIs) on glucose uptake through their binding to human glucose transporter-1 (GLUT-1) have been well documented. Thus, our research aimed to explore the potential impact of various TKIs of GLUT-1 on the standard [18F]FDG-PET monitoring of tumor response in patients. Methods: To achieve this, we conducted an analysis on three patients who were undergoing treatment with different TKIs and harbored actionable alterations. Alongside the assessment of FDG data (including SUVmax, total lesion glycolysis (TLG), and metabolic tumor volume (MTV)), we also examined the changes in tumor sizes through follow-up [18F]FDG-PET/CT imaging. Notably, our patients harbored alterations in BRAFV600, RET, and c-KIT and exhibited positive responses to the targeted treatment. Results: Our analysis revealed that FDG data derived from SUVmax, TLG, and MTV offered quantifiable outcomes that were consistent with the measurements of tumor size. Conclusions: These findings lend support to the notion that the inhibition of GLUT-1, as a consequence of treatment efficacy, could be indirectly gauged through [18F] FDG-PET/CT imaging in cancer patients undergoing TKI therapy.

Digital "flipbooks" for enhanced visual assessment of simple and complex brain tumors.

Typical longitudinal radiographic assessment of brain tumors relies on side-by-side qualitative visualization of serial magnetic resonance images (MRIs) aided by quantitative measurements of tumor size. However, when assessing slowly growing tumors and/or complex tumors, side-by-side visualization and quantification may be difficult or unreliable. Whole-brain, patient-specific "digital flipbooks" of longitudinal scans are a potential method to augment radiographic side-by-side reads in clinical settings by enhancing the visual perception of changes in tumor size, mass effect, and infiltration across multiple slices over time. In this approach, co-registered, consecutive MRI scans are displayed in a slide deck, where one slide displays multiple brain slices of a single timepoint in an array (eg, 3 × 5 "mosaic" view of slices). The flipbooks are viewed similarly to an animated flipbook of cartoons/photos so that subtle radiographic changes are visualized via perceived motion when scrolling through the slides. Importantly, flipbooks can be created easily with free, open-source software. This article describes the step-by-step methodology for creating flipbooks and discusses clinical scenarios for which flipbooks are particularly useful. Example flipbooks are provided in Supplementary Material.

Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer.

Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000 deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments exist. Preoperative diagnostic imaging is common in high-income countries and MRI measured tumor size routinely guides treatment allocation of cervical cancer patients. Recently, the role of MRI radiomics has been recognized. However, its potential to independently predict survival and treatment response requires further clarification. This retrospective cohort study demonstrates how non-invasive, preoperative, MRI radiomic profiling may improve prognostication and tailoring of treatments and follow-ups for cervical cancer patients. By unsupervised clustering based on 293 radiomic features from 132 patients, we identify three distinct clusters comprising patients with significantly different risk profiles, also when adjusting for FIGO stage and age. By linking their radiomic profiles to genomic alterations, we identify putative treatment targets for the different patient clusters (e.g., immunotherapy, CDK4/6 and YAP-TEAD inhibitors and p53 pathway targeting treatments).

Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet neoadjuvant clinical trials are rarely preceded by preclinical testing involving neoadjuvant treatment, surgery, and post-surgery monitoring of the disease. Here we used a mouse model of spontaneous metastasis occurring after surgical removal of orthotopically implanted primary tumors to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Treatment outcomes were used to validate a novel mathematical kinetics-pharmacodynamics model predictive of perioperative disease progression. Longitudinal measurements of presurgical primary tumor size and postsurgical metastatic burden were compiled using 128 mice receiving variable neoadjuvant treatment doses and schedules (released publicly at https://zenodo.org/records/10607753). A non-linear mixed-effects modeling approach quantified inter-animal variabilities in metastatic dynamics and survival, and machine-learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (CD31 and Ki67). Our computational simulations show that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery and treatment cessation. Machine learning algorithms that included support vector machines, random forests, and artificial neural networks, confirmed a lack of definitive biomarkers, which shows the value of preclinical modeling studies to identify potential failures that should be avoided clinically.

Abstract PO2-13-04: Single cell characterization of senescent CD8+ T cell promotes immunotherapy resistance in early-stage triple-negative breast cancer

Abstract Background: Immune checkpoint blockade (ICB) has been explored in triple-negative breast cancer (TNBC) and has been proven to improve patient survival in advanced TNBCs (IMpassion130) or increase the pathological complete response rate in early TNBCs (KEYNOTE522). However, ICB could only benefit a subset of patients, highlighting the urgent need to optimize patient selection. Unlike in advanced TNBCs, a predictive biomarker for ICB in early TNBCs is still lacking. The main reason might be that previous studies neglected the heterogeneity of tumor ecosystems between early and advanced TNBCs. There is an urgent need to understand the unique ecosystem of early-stage TNBC and develop biomarkers for precision immunotherapy. Objective: This study aims to characterize the micro-loop associated with the immune efficacy of early TNBC, so as to explain the mechanisms behind the differences in early and late efficacy markers, identify efficacy markers in early TNBC immunotherapy, and search for clinical targeting strategies to sensitize TNBC for neoadjuvant therapy. Methods: We conducted an in-depth analysis of 32 single-cell transcriptomes, comprising 26 early-stage TNBC enrolled in prospective clinical trials (NCT04418154 and NCT04613674), receiving neoadjuvant chemotherapy alone (n=8) or combined with anti-PD1 (n=18), and 6 advanced TNBC. We analyzed the microenvironmental differences between early and advanced tumors, and between different treatment response groups in early stages, and identified a subpopulation of cells specific to early stages and associated with immunotherapeutic efficacy. We used mIHC, flow-through, and validated the presence of this cell in clinical samples. We also explored its predictive performance on four independent cohorts of TNBCs with ICB treatment (GSE194040, NCT04129996, GSE169246, GSE124821). Furthermore, to understand the impact of ISG+ T cells on immunotherapy efficacy and explore targeting strategies, we employed a multi-faceted approach to assess their tumor-killing ability, response to Anti-PD1 treatment, and sensitization effect of drugs targeting ISG+ T cells. ISG+ T cells were sorted using flow cytometry for further experiment. In vitro, we established a co-culture model of primary TNBC patients-derived organoid (PDO) and tumor infiltrated CD8+T cells and evaluated the tumor cell viability as well as T cell cytotoxicity. In vivo, we established TS/A tumor cell bearing BalB/c mouse and E0771 tumor cell-bearing C57BL mouse and measured tumor size and tumor microenvironment by flow cytometry. Results: We obtained 236,017 high-quality cells and identified cell subsets across 32 samples with different stages, treatments and responses. We then uncovered an enriched subset of interferon-induced (ISG+) CD8+ T cells specific to early TNBC, serving as a predictive factor for ICB resistance. Mechanistically, the upregulation of the IFN pathway in early-stage TNBC triggers a transition in ISG+ CD8+ T cells, resulting in cellular senescence, diminished cytotoxicity, and impaired response to ICB. Encouragingly, we made a noteworthy discovery that Nicotinamide mononucleotide, an anti-aging drug, effectively restores the functionality of ISG+ CD8+ T cells, amplifying immunotherapy sensitivity. Conclusions: This study provided a comprehensive single-cell transcriptome atlas of early-stage TNBC and depicted stage-related ISG+CD8+ T cell for predicting ICB response in early TNBC. We emphasize the critical role of T cell dysfunction prompted by cellular senescence in driving ICB resistance during the early stages of TNBC and propose an approach for sensitizing immunotherapy with aging drugs. Citation Format: Tong Fu, Yi-Yu Chen, Xi Jin, Yi-Zhou Jiang, Zhi-Ming Shao. Single cell characterization of senescent CD8+ T cell promotes immunotherapy resistance in early-stage triple-negative breast cancer [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 PO2-13-04.

Abstract LB063: Anti-tumor activity in preclinical models utilizing a conditional bispecific redirected activation molecule (COBRA) targeting Her2

Abstract Among strategies to recruit cytotoxic T-cells into the tumor micro-environment (TME) are the use of T-cell engager molecules. One such therapeutic modality are molecules that recognize specific tumor associated antigens (TAA) but are activated preferentially in the TME. Conditional Bispecific Redirected Activation molecules (COBRA) are designed to be administered as a prodrug, and cleaved via matrix metalloproteinase to engage with both a tumor TAA and CD3 (Panachi, et.al. MAbs 2020 12(1) 1792130). In this study, we sought to determine the preclinical efficacy of a COBRA molecule targeting the Her2 receptor. Sub-cutaneous xenograft models (SCID mice using adoptive T-cell transfer) were utilized representing various levels of the TAA (HT-55, SNU-16, JIMT-1, and HCC827) to measure both efficacy and mechanism of action (T-cell extravasation). The COBRA molecule was dosed at 0.03, 0.1, 0.3, and 1 mg/kg using a Q3dx7 schedule. A non-cleavable COBRA molecule with the Her2 TAA was included as a control at 1 mg/kg. Efficacy was determined by caliper measurements of sub-cutaneous tumor size twice per week after dosing, and T-cell extravasation into the TME was measured by immunohistochemistry (IHC) at days 10, 19, and termination. IHC data was quantified using HALO imaging software. In our study, we measured dose-dependent tumor regression and/or stasis in all models tested. No anti-tumor activity was measured after dosing with the non-cleavable COBRA molecule. T-cell extravasation as measured by IHC and Halo analysis followed a dose and time dependent course. Comparison of Day 19 T-cell extravasation (one day after the last dose) showed a linear relationship to TAA expression. Our data indicate that treatment with a COBRA molecule in preclinical models with a Her2 TAA results in anti-tumor activity as measured by tumor stasis/regression, and exhibit the expected mechanism of action as evaluated by T-cell extravasation into the TME. Citation Format: Bradley Stringer, Johara Chouitar, Jacqualine Cerbone, Sarah Fortin, Alina Ainbinder, Cassie Kysilovsky, Brittany Scott, Antara Banerjee. Anti-tumor activity in preclinical models utilizing a conditional bispecific redirected activation molecule (COBRA) targeting Her2 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB063.

Abstract 700: Impact of heterogeneity for mismatch repair activity on colon tumor development and therapeutic response

Abstract Background: Colorectal cancers (CRC) that are deficient for DNA mismatch repair (dMMR) proteins have high levels of genetic instability and consequently high mutational burden, creating numerous neoantigens that can elicit an immune response. Therefore, dMMR CRC are the best candidates for immune checkpoint inhibition (ICI) compared to proficient DNA mismatch repair (pMMR) CRC. Early clinical trials revealed that only 30-55% metastatic dMMR CRC responded to ICI. Recent studies utilizing allograft models have demonstrated that tumor immune landscape can be primed with radiopharmaceutical therapy (RPT). Although early results have been quite promising, allograft models often fail to accurately predict efficacy for many reasons, but most often are due to a lack of heterogeneity. Methods: To better understand how heterogenous MMR expression impacts tumor development and response to ICI alone or in combination with RPT, we developed a new mouse model that develops three tumor types: (1) homotypic dMMR tumors that express green fluorescent protein, (2) homotypic pMMR tumors that express red fluorescent protein, and (3) heterotypic tumors with a mixture of dMMR and pMMR cells. Surveillance bright field and fluorescent colonoscopies allow us to assess treatment response by measuring tumor size and proportion of dMMR and pMMR tumor cells in real-time. These outcomes are verified through ex vivo imaging and histological analysis. Results: Tumor response to anti-PD-L1 ICI was dependent on MMR status. Homotypic dMMR tumors exhibited the strongest response: significantly smaller in treated mice than controls, exhibited areas of vascular congestion and increased CD8+ cytotoxic T-cells infiltration. Response of heterotypic MMR tumors varied depending on percentage of dMMR cells; tumors with a high percentage of dMMR cells remained small, whereas tumors with a low percentage of dMMR had an outgrowth of pMMR cells. Treated and untreated homotypic pMMR tumors were indistinguishable. To enhance the response of all three tumor types, mice were treated with dual ICI treatment, anti-PD-L1 and anti-CTLA-4, or RPT. Animals administered the tri-therapy (dual ICI + RPT) survived significantly longer with fewer tumors than animals treated with either dual ICI or RPT alone. Conclusions: Our innovative mouse model allows for the highly detailed characterization of tumor response to therapies. Simplistic allograft models may not adequately account for the dynamic effects that neighboring cell death may have on radio-resistant cells, on tumor vascular perfusion and oxygenation, or on tumor immune infiltration and adaptive immune recognition of remaining cells. We begin to fill these critical gaps in knowledge and therefore the results from our studies will help guide the translation and integrated use of ICIs and RPTs in clinic. Citation Format: Santina M. Snow, Dawn Albrecht, Paul A. Clark, Caroline P. Kerr, Joseph J. Grudzinski, Justin J. Jeffery, Hansel Comas Rojas, Reinier Hernandez, Kristina A. Matkowskyj, Jamey P. Weichert, Zachary S. Morris, Richard B. Halberg. Impact of heterogeneity for mismatch repair activity on colon tumor development and therapeutic response [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 700.

Abstract B069: Bone marrow-derived adipocytes promote ovarian cancer progression and metastasis

Abstract B069: Bone marrow-derived adipocytes promote ovarian cancer progression and metastasis

Accuracy of cone-beam breast computed tomography for assessing breast cancer tumor size-comparison with breast magnetic resonance imaging.

Accurate preoperative assessment of tumor size is important in developing a surgical plan for breast cancer. The purpose of this study was to evaluate the accuracy of cone-beam breast computed tomography (CBBCT) and magnetic resonance imaging (MRI) in the assessment of tumor size and to analyze the factors influencing the discordance. In this retrospective study, patients with breast cancer who underwent preoperative contrast-enhanced CBBCT (CE-CBBCT) and dynamic contrast-enhanced MRI (DCE-MRI) and received a complete pathologic diagnosis from August 2020 to December 2021 were included, using the pathological result as the gold standard. Two radiologists assessed the CBBCT and MRI features and measured the tumor size with a 2-week washout period. Intraclass correlation coefficient (ICC) and Bland-Altman analyses were used to assess inter-observer reproducibility and agreement based on CBBCT, MRI and pathology. Univariate analyses of differences in clinical, pathological and CBBCT/MRI features between the concordant and discordant groups was performed using the t-test, Mann-Whitney U-test, Chi-squared test and Fisher's exact test. Multivariate analyses were used to identify factors associated with discordance of CBBCT/MRI with pathology. A total of 115 female breast cancer patients (115 lesions) were included. All patients had a single malignant tumor of the unilateral breast. The reproducibility and the agreement ranged from moderate to excellent (ICC =0.607-0.983). Receiver operating characteristic (ROC) analyses showed that the cut-off values of CBBCT-pathology and MRI-pathology discordance were 2.25 and 2.65 cm, respectively. CBBCT/MRI-pathology concordance was significantly associated with the extent of pathology, lesion type, presence of calcification, human epidermal growth factor receptor 2 (HER2) status and fatty infiltration (P<0.05). In lesions containing calcification, the difference of CBBCT-pathology was significantly smaller than MRI-pathology (P=0.021). Non-mass enhancement (NME) was the main predictor of CBBCT- or MRI-pathology discordance [odds ratio (OR) =3.293-6.469, P<0.05], and HER2 positivity was a predictor of CBBCT-pathology discordance (OR =3.514, P=0.019). CBBCT and MRI have comparable accuracy in measurement of tumor size, and CBBCT is advantageous in assessing the size of calcified lesions. NME and HER2 positivity are significant predictors of CBBCT-pathology discordance. This suggests that CBBCT might serve as an alternative imaging technique to assess tumor size when patients do not tolerate MRI.

PRECISE Version 2: Updated Recommendations for Reporting Prostate Magnetic Resonance Imaging in Patients on Active Surveillance for Prostate Cancer

Background and objectiveThe Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations standardise the reporting of prostate magnetic resonance imaging (MRI) in patients on active surveillance (AS) for prostate cancer. An international consensus group recently updated these recommendations and identified the areas of uncertainty. MethodsA panel of 38 experts used the formal RAND/UCLA Appropriateness Method consensus methodology. Panellists scored 193 statements using a 1–9 agreement scale, where 9 means full agreement. A summary of agreement, uncertainty, or disagreement (derived from the group median score) and consensus (determined using the Interpercentile Range Adjusted for Symmetry method) was calculated for each statement and presented for discussion before individual rescoring. Key findings and limitationsParticipants agreed that MRI scans must meet a minimum image quality standard (median 9) or be given a score of ‘X’ for insufficient quality. The current scan should be compared with both baseline and previous scans (median 9), with the PRECISE score being the maximum from any lesion (median 8). PRECISE 3 (stable MRI) was subdivided into 3-V (visible) and 3-NonV (nonvisible) disease (median 9). Prostate Imaging Reporting and Data System/Likert ≥3 lesions should be measured on T2-weighted imaging, using other sequences to aid in the identification (median 8), and whenever possible, reported pictorially (diagrams, screenshots, or contours; median 9). There was no consensus on how to measure tumour size. More research is needed to determine a significant size increase (median 9). PRECISE 5 was clarified as progression to stage ≥T3a (median 9). Conclusions and clinical implicationsThe updated PRECISE recommendations reflect expert consensus opinion on minimal standards and reporting criteria for prostate MRI in AS.

A study on the radiomic correlation between CBCT and pCT scans based on modified 3D-RUnet image segmentation.

The present study is based on evidence indicating a potential correlation between cone-beam CT (CBCT) measurements of tumor size, shape, and the stage of locally advanced rectal cancer. To further investigate this relationship, the study quantitatively assesses the correlation between positioning CT (pCT) and CBCT in the radiomics features of these cancers, and examines their potential for substitution. In this study, 103 patients diagnosed with locally advanced rectal cancer and undergoing neoadjuvant chemoradiotherapy were selected as participants. Their CBCT and pCT images were used to divide the participants into two groups: a training set and a validation set, with a 7:3 ratio. An improved conventional 3D-RUNet (CLA-UNet) deep learning model was trained on the training set data and then applied to the validation set. The DSC, HD95 and ASSD were calculated for quantitative evaluation purposes. Then, radiomics features were extracted from 30 patients of the test set. The experiments demonstrate that, the modified model achieves an average DSC score 0.792 for pCT and 0.672 for CBCT scans. 1037 features were extracted from each patient's CBCT and pCT images, 73 image features were found to have R values greater than 0.9, including three features related to the staging and prognosis of rectal cancer. In this study, we proposed an automatic, fast, and consistent method for rectal cancer GTV segmentation for pCT and CBCT scans. The findings of radiomic results indicate that CBCT images have significant research value in the field of radiomics.

Exploration of tumor size measurement methods in preoperative breast cancer assessment using whole-body silicon photomultiplier PET: feasibility and first results

PurposeWhole-body silicon photomultiplier positron emission tomography (WB SiPM PET) could be used to diagnose breast cancer spread before lumpectomy. We aimed to investigate the method of measuring the tumor size by WB SiPM PET as a basis for diagnosing breast cancer spread in the breast.Materials and methodsWe retrospectively reviewed 35 breast cancer lesions in 32 patients who underwent WB SiPM PET/CT in the prone position as preoperative breast cancer examinations from September 2020 to March 2022.In all cases, a 20-mm spherical VOI was placed in the normal mammary gland to measure the mean standardised uptake value (SUVmean) and the standard deviation (SD) of 18F-fluorodeoxyglucose (FDG) uptake. We prepared four types of candidates (SUVmean + 2 SD, SUVmean + 3 SD, 1.5 SUVmean + 2 SD, 1.5 SUVmean + 3 SD) for thresholds for delineating tumor contours on PET images. On the semiautomatic viewer soft, the maximum tumor sizes were measured at each of the four thresholds and compared with the pathological tumor sizes, including the extensive intraductal component (EIC).ResultsThe lesion detection sensitivity was 97% for WB SiPM PET. PET detected 34 lesions, excluding 4-mm ductal carcinomas in situ (DCIS). PET measurements at the '1.5 SUVmean + 2 SD' threshold demonstrated values closest to the pathological tumor sizes, including EIC. Moreover, '1.5 SUVmean + 2 SD' had the highest concordance (63%).ConclusionsThe study demonstrated that among various PET thresholds, the '1.5 SUVmean + 2 SD' threshold exhibited the best performance. However, even with this threshold, the concordance rate was limited to only 63%.

The Role of Magnetic Resonance Imaging in the Preoperative Staging and Treatment of Invasive Lobular Carcinoma

IntroductionInvasive lobular carcinoma (ILC) is known for its diffuse growth pattern and its associated challenges in diagnosing. Magnetic resonance imaging (MRI) is the most accurate imaging modality and might aid in improving preoperative staging compared to full field digital mammography (FFDM) and ultrasound (US), however current literature is inconsistent. The aim of this paper is to evaluate the accuracy of MRI staging compared to FFDM/US and pathology results. MethodsIn this single-centre retrospective study, all patients diagnosed with ILC between 2014 and 2019 who underwent preoperative MRI were included. Specific parameters studied were: (1) the need for second-look targeted biopsies, (2) detection of new tumors (ie, contralateral or multifocal), (3) changes in cTNM-classification, and (4) impact on final treatment plan. Bland-Altman plots were used to compare the tumor sizes measured on MRI and FFDM/US with actual pathological tumor sizes. ResultsNinety-nine patients were included. After performing preoperative MRI, 9 (9.1%) multifocal tumors were diagnosed after additional biopsies. Contralateral tumors were detected twice (2.0%) and cN classification was upgraded in 7 cases (7.1%). Surgical treatment or neoadjuvant treatment plans were changed in 16 patients (16.1%). Compared to histopathological results, FFDM/US underestimated tumor size with a mean of 0.4 cm (Limit of agreement (LoA): -2.8 cm to 2.0 cm) whereas MRI overestimated tumor size with a mean of 0.6 cm (LoA: -1.9 cm to 3.0 cm). ConclusionsIn our study, mean differences in tumor size measurements using FFDM/US and MRI were comparable, with similar random errors. MRI correctly diagnosed multifocal and contralateral tumors more often and provided a better cN staging.