Tumor volume doubling time estimated from digital breast tomosynthesis mammograms distinguishes invasive breast cancers from benign lesions.

OBJECTIVES: The aim of this study was to determine whether lesion size metrics on consecutive screening mammograms could predict malignant invasive carcinoma versus benign lesion outcome. METHODS: We retrospectively reviewed suspicious screen-detected lesions confirmed by biopsy to be invasive breast cancers or benign that were visible on current and in-retrospect prior screening mammograms performed with digital breast tomosynthesis from 2017 to 2020. Four experienced radiologists recorded mammogram dates, breast density, lesion type, lesion diameter, and morphology on current and prior exams. We used logistic regression models to evaluate the association of invasive breast cancer outcome with lesion size metrics such as maximum dimension, average dimension, volume, and tumor volume doubling time (TVDT). RESULTS: Twenty-eight patients with invasive ductal carcinoma or invasive lobular carcinoma and 40 patients with benign lesions were identified. The mean TVDT was significantly shorter for invasive breast cancers compared to benign lesions (0.84 vs. 2.5 years; p = 0.0025). Patients with a TVDT of less than 1 year were shown to have an odds ratio of invasive cancer of 6.33 (95% confidence interval, 2.18-18.43). Logistic regression adjusted for age, lesion maximum dimension, and lesion volume demonstrated that shorter TVDT was the size variable significantly associated with invasive cancer outcome. CONCLUSION: Invasive breast cancers detected on current and in-retrospect prior screening mammograms are associated with shorter TVDT compared to benign lesions. If confirmed to be sufficiently predictive of benignity in larger studies, lesions visible on mammograms which in comparison to prior exams have longer TVDTs could potentially avoid additional imaging and/or biopsy. KEY POINTS: • We propose tumor volume doubling time as a measure to distinguish benign from invasive breast cancer lesions. • Logistic regression results summarized the utility of the odds ratio in retrospective clinical mammography data.

Detecting cancers through tumor-activatable minicircles that lead to a detectable blood biomarker.

Earlier detection of cancers can dramatically improve the efficacy of available treatment strategies. However, despite decades of effort on blood-based biomarker cancer detection, many promising endogenous biomarkers have failed clinically because of intractable problems such as highly variable background expression from nonmalignant tissues and tumor heterogeneity. In this work we present a tumor-detection strategy based on systemic administration of tumor-activatable minicircles that use the pan-tumor-specific Survivin promoter to drive expression of a secretable reporter that is detectable in the blood nearly exclusively in tumor-bearing subjects. After systemic administration we demonstrate a robust ability to differentiate mice bearing human melanoma metastases from tumor-free subjects for up to 2 wk simply by measuring blood reporter levels. Cumulative change in reporter levels also identified tumor-bearing subjects, and a receiver operator-characteristic curve analysis highlighted this test's performance with an area of 0.918 ± 0.084. Lung tumor burden additionally correlated (r(2) = 0.714; P < 0.05) with cumulative reporter levels, indicating that determination of disease extent was possible. Continued development of our system could improve tumor detectability dramatically because of the temporally controlled, high reporter expression in tumors and nearly zero background from healthy tissues. Our strategy's highly modular nature also allows it to be iteratively optimized over time to improve the test's sensitivity and specificity. We envision this system could be used first in patients at high risk for tumor recurrence, followed by screening high-risk populations before tumor diagnosis, and, if proven safe and effective, eventually may have potential as a powerful cancer-screening tool for the general population.

A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation.

The targeted inactivation of individual oncogenes can elicit regression of cancers through a phenomenon called oncogene addiction. Oncogene addiction is mediated by cell-autonomous and immune-dependent mechanisms. Therapeutic resistance to oncogene inactivation leads to recurrence but can be counteracted by immune surveillance. Predicting the timing of resistance will provide valuable insights in developing effective cancer treatments. To provide a quantitative understanding of cancer response to oncogene inactivation, we developed a new 3-compartment mathematical model of oncogene-driven tumor growth, regression and recurrence, and validated the model using a MYC-driven transgenic mouse model of T-cell acute lymphoblastic leukemia. Our mathematical model uses imaging-based measurements of tumor burden to predict the relative number of drug-sensitive and drug-resistant cancer cells in MYC-dependent states. We show natural killer (NK) cell adoptive therapy can delay cancer recurrence by reducing the net-growth rate of drug-resistant cells. Our studies provide a novel way to evaluate combination therapy for personalized cancer treatment.

Minicircles for a two-step blood biomarker and PET imaging early cancer detection strategy.

Early cancer detection can dramatically increase treatment options and survival rates for patients, yet detection of early-stage tumors remains difficult. Here, we demonstrate a two-step strategy to detect and locate cancerous lesions by delivering tumor-activatable minicircle (MC) plasmids encoding a combination of blood-based and imaging reporter genes to tumor cells. We genetically engineered the MCs, under the control of the pan-tumor-specific Survivin promoter, to encode: 1) Gaussia Luciferase (GLuc), a secreted biomarker that can be easily assayed in blood samples; and 2) Herpes Simplex Virus Type 1 Thymidine Kinase mutant (HSV-1 sr39TK), a PET reporter gene that can be used for highly sensitive and quantitative imaging of the tumor location. We evaluated two methods of MC delivery, complexing the MCs with the chemical transfection reagent jetPEI or encapsulating the MCs in extracellular vesicles (EVs) derived from a human cervical cancer HeLa cell line. MCs delivered by EVs or jetPEI yielded significant expression of the reporter genes in cell culture versus MCs delivered without a transfection reagent. Secreted GLuc correlated with HSV-1 sr39TK expression with R2 = 0.9676. MC complexation with jetPEI delivered a larger mass of MC for enhanced transfection, which was crucial for in vivo animal studies, where delivery of MCs via jetPEI resulted in GLuc and HSV-1 sr39TK expression at significantly higher levels than controls. To the best of our knowledge, this is the first report of the PET reporter gene HSV-1 sr39TK delivered via a tumor-activatable MC to tumor cells for an early cancer detection strategy. This work explores solutions to endogenous blood-based biomarker and molecular imaging limitations of early cancer detection strategies and elucidates the delivery capabilities and limitations of EVs.

A blood biomarker for monitoring response to anti-EGFR therapy.

BACKGROUND AND OBJECTIVE: To monitor therapies targeted to epidermal growth factor receptors (EGFR) in non-small cell lung cancer (NSCLC), we investigated Peroxiredoxin 6 (PRDX6) as a biomarker of response to anti-EGFR agents. METHODS: We studied cells that are sensitive (H3255, HCC827) or resistant (H1975, H460) to gefitinib. PRDX6 was examined with either gefitinib or vehicle treatment using enzyme-linked immunosorbent assays. We created xenograft models from one sensitive (HCC827) and one resistant cell line (H1975) and monitored serum PRDX6 levels during treatment. RESULTS: PRDX6 levels in cell media from sensitive cell lines increased significantly after gefitinib treatment vs. vehicle, whereas there was no significant difference for resistant lines. PRDX6 accumulation over time correlated positively with gefitinib sensitivity. Serum PRDX6 levels in gefitinib-sensitive xenograft models increased markedly during the first 24 hours of treatment and then decreased dramatically during the following 48 hours. Differences in serum PRDX6 levels between vehicle and gefitinib-treated animals could not be explained by differences in tumor burden. CONCLUSIONS: Our results show that changes in serum PRDX6 during the course of gefitinib treatment of xenograft models provide insight into tumor response and such an approach offers several advantages over imaging-based strategies for monitoring response to anti-EGFR agents.

Mathematical model identifies blood biomarker-based early cancer detection strategies and limitations.

Most clinical blood biomarkers lack the necessary sensitivity and specificity to reliably detect cancer at an early stage, when it is best treatable. It is not yet clear how early a clinical blood assay can be used to detect cancer or how biomarker-based strategies can be improved to enable earlier detection of smaller tumors. To address these issues, we developed a mathematical model describing dynamic plasma biomarker kinetics in relation to the growth of a tumor, beginning with a single cancer cell. To exemplify a realistic scenario in which biomarker is shed by both cancerous and noncancerous cells, we primed the model on ovarian tumor growth and CA125 shedding data, for which tumor growth parameters and shedding rates are readily available in published literature. We found that a tumor could grow unnoticed for more than 10.1 years and reach a volume of about π/6(25.36 mm)(3), corresponding to a spherical diameter of about 25.36 mm, before becoming detectable by current clinical blood assays. Model parameters were perturbed over log orders of magnitude to quantify ideal shedding rates and identify other blood-based strategies required for early submillimeter tumor detectability. The detection times we estimated are consistent with recently published tumor progression time lines based on clinical genomic sequencing data for several cancers. Here, we rigorously showed that shedding rates of current clinical blood biomarkers are likely 10(4)-fold too low to enable detection of a developing tumor within the first decade of tumor growth. The model presented here can be extended to virtually any solid cancer and associated biomarkers.

Role of endosomal trafficking dynamics on the regulation of hepatic insulin receptor activity: models for Fao cells.

Evidence indicates that endosomal insulin receptor (IR) trafficking plays a role in regulating insulin signal transduction. To evaluate its importance, we developed a series of biokinetic models for quantifying activated surface and endosomal IR dynamics from published experimental data. Starting with a published two-compartment Fao hepatoma model, a four-pool model was formulated that depicts IR autophosphorylation after receptor binding, IR endosomal internalization/trafficking, insulin dissociation from and dephosphorylation of internalized IR, and recycling of unliganded, dephosphorylated IR to the plasma membrane. Quantification required three additional data sets, two measured, but unmodeled by the same group. A five-pool model created to include endosomal trafficking of the nonphosphorylated insulin-IR complex was fitted using the same data sets, augmented with another published data set. Creation of a six-pool model added the physiologically relevant dissociation of insulin ligand from the activated endosomal IR. More importantly, all three models, validated against additional data not used in model fitting, predict that, mechanistically, internalization of activated IR is a rate-limiting step, at least under the receptor saturating conditions of the fitting data. This rate includes the transit time to a site where insulin dissociation from and/or dephosphorylation of the IR occurs by docking with protein-tyrosine phosphatases (PTPases), or where a sufficient conformational change occurs in the IR, perhaps due to insulin-IR dissociation, where associated PTPases may complete IR dephosphorylation. Our new models indicate that key events in endosomal IR trafficking have significance in mediating IR activity, possibly serving to regulate insulin signal transduction.