In Vivo Tumor Growth Rate Measured by US in Preoperative Period and Long Term Disease Outcome in Breast Cancer Patients

Tumor Growth Rate of Luminal and Nonluminal Invasive Breast Cancer Calculated on MRI Imaging

PURPOSE

Calculation of the size growth of different types of breast carcinoma based on follow-up data in breast MRI.

PATIENTS AND METHODS

Patients were included if they had been diagnosed with an invasive breast carcinoma in the current MRI (aMRI), and had also undergone a breast MRI (pMRI) with unsuspicious findings (MR BIRADS 1 or 2) within 5 years prior to diagnosis. If retrospective analysis of pMRI revealed signs of the current carcinoma, a quantitative one-dimensional-analysis of size progression of the carcinoma over time was performed, and growth rates for different tumor types were calculated.

RESULTS

About 204 patients with 208 invasive breast carcinomas (74 luminal A, 105 luminal B, nonluminal 29) were included. In 129 carcinomas, there were signs of the current tumor in the pMRI. Based on the interval between pMRI and aMRI (average 21 months), the average tumor doubling time was 1126 days (3.1 years), 624 days (1.7 years), and 254 days (0.7 years) of luminal A, luminal B, and nonluminal. The average tumor size was 4.3 mm in the pMRI, and 9.5 mm in aMRI. In 79 cases, the pMRI showed no signs of the actual carcinoma. In this group, the average current tumor size was 8.5 mm.

CONCLUSION

The study provides specific information on the growth rate of luminal and nonluminal breast cancer. According to this, early detection intervals for nonhigh-risk women using MRI of 2 to 3 years, and for high-risk (HR) women of 1 year appear reasonable. Data also provide a well-founded basis for medico-legal judgements.

The prognostic potential of mammographic growth rate of invasive breast cancer in the Nijmegen breast cancer screening cohort

OBJECTIVES

Insight into the aggressiveness of potential breast cancers found in screening may optimize recall decisions. Specific growth rate (SGR), measured on mammograms, may provide valuable prognostic information. This study addresses the association of SGR with prognostic factors and overall survival in patients with invasive carcinoma of no special type (NST) from a screened population.

METHODS

In this historic cohort study, 293 women with NST were identified from all participants in the Nijmegen screening program (2003-2007). Information on clinicopathological factors was retrieved from patient files and follow-up on vital status through municipalities. On consecutive mammograms, tumor volumes were estimated. After comparing five growth functions, SGR was calculated using the best-fitting function. Regression and multivariable survival analyses described associations between SGR and prognostic factors as well as overall survival.

RESULTS

Each one standard deviation increase in SGR was associated with an increase in the Nottingham prognostic index by 0.34 [95% confidence interval (CI): 0.21-0.46]. Each one standard deviation increase in SGR increased the odds of a tumor with an unfavorable subtype (based on histologic grade and hormone receptors; odds ratio 2.14 [95% CI: 1.45-3.15]) and increased the odds of diagnosis as an interval cancer (versus screen-detected; odds ratio 1.57 [95% CI: 1.20-2.06]). After a median of 12.4 years of follow-up, 78 deaths occurred. SGR was not associated with overall survival (hazard ratio 1.12 [95% CI: 0.87-1.43]).

CONCLUSIONS

SGR may indicate prognostically relevant differences in tumor aggressiveness if serial mammograms are available. A potential association with cause-specific survival could not be determined and is of interest for future research.

Engineering dense tumor constructs via cellular contraction of extracellular matrix hydrogels

Physical characteristics of solid tumors such as dense internal microarchitectures and pathological stiffness influence cancer progression and treatment. While it is routine to engineer culture substrates and scaffolds with elastic moduli that approximate tumors, these models often fail to capture characteristic internal microarchitectures such as densely compacted concentric ECM fibers at the stromal interface. Contractile mesenchymal cells can solve this engineering challenge by deforming, contracting, and compacting extracellular matrix (ECM) hydrogels to decrease tissue volume and increase tissue density. Here we demonstrate that allowing human fibroblasts of varying origins to freely contract collagen type I-containing hydrogels co-seeded with carcinoma cell spheroids produces a tissue engineered construct with structural features that mimic dense solid tumors in vivo. Morphometry and mechanical testing were conducted in tandem with biochemical analysis of proliferation and viability to confirm that dense carcinoma constructs engineered using this approach capture relevant physical characteristics of solid carcinomas in a tractable format that preserves viability and is amenable to extended culture. The reported method is adaptable to the use of multiple mesenchymal cell types and the inclusion of fibrin in the ECM combined with seeding of endothelial cells to produce prevascularized constructs. The physical dense carcinoma constructs engineered using this approach may provide more clinically relevant venues for studying cancer pathophysiology and the challenges associated with the delivery of macromolecular drugs and cellular immunotherapies to solid tumors.

Mechanistic Effects of Estrogens on Breast Cancer

PURPOSE

Current concepts regarding estrogen and its mechanistic effects on breast cancer in women are evolving. This article reviews studies that address estrogen-mediated breast cancer development, the prevalence of occult tumors at autopsy, and the natural history of breast cancer as predicted by a newly developed tumor kinetic model.

METHODS

This article reviews previously published studies from the authors and articles pertinent to the data presented.

RESULTS

We discuss the concepts of adaptive hypersensitivity that develops in response to long-term deprivation of estrogen and results in both increased cell proliferation and apoptosis. The effects of menopausal hormonal therapy on breast cancer in postmenopausal women are interpreted based on the tumor kinetic model. Studies of the administration of a tissue selective estrogen complex in vitro, in vivo, and in patients are described. We review the various clinical studies of breast cancer prevention with selective estrogen receptor modulators and aromatase inhibitors. Finally, the effects of the underlying risk of breast cancer on the effects of menopausal hormone therapy are outlined.

DISCUSSION

The overall intent of this review is to present data supporting recent concepts, discuss pertinent literature, and critically examine areas of controversy.

Three-dimensional bioprinted cancer models: A powerful platform for investigating tunneling nanotube-like cell structures in complex microenvironments

Bioprinting technology offers layer-by-layer positioning of cells within 3D space with complexity and a defined architecture. Cancer models based in this biofabrication technique are important tools to achieve representative and realistic in vivo conditions of the tumor microenvironment. Here, we show the development of a proof-of-concept three-dimensional bioprinted cancer model that successfully recapitulates the intercellular communication via the assembly of functional tunneling nanotube (TNT)-like cell projections. Different combinations of collagen-containing culture medium, sodium alginate and gelatin were initially prepared and rheologically evaluated. The optimized mixture was used to print two preliminary 3D models for cancer cell seeding. Favourable results in cell viability and proliferation led to the inclusion of 786-O renal cancer cells into the biomaterial mixture to directly bioprint the most suitable 3D model with embedded cells. Bioprinted cells remained viable for at least 15 days of culture and proliferated. More importantly, these cancer cells were able to build TNT-like cellular projections inside the hydrogel that established direct contacts between distant cells. We show that these structures were used as channels for the scrolling and intercellular transfer of mitochondria thus reproducing TNT's function in 2D culture systems. This 3D bioprinted renal cancer model provides a novel alternative tool for studying the functional relevance of TNT-like structures in tumorigenesis and anticancer drug susceptibility in a highly controlled and reproducible tumor microenvironment.

Has tumor doubling time in breast cancer changed over the past 80 years? A systematic review

Over the past century, epidemiologic changes and implementation of screening may have had an impact on tumor doubling time in breast cancer. Our study was designed to evaluate changes in tumor doubling time in breast cancer over the past 80 years. A systematic review of published literature and meta-regression analysis was performed. An online electronic database search was undertaken using the PubMed platform from inception until June 2020. All studies that measured tumor doubling time in breast cancer were included. A total of 151 publications were retrieved. Among them, 16 full-text articles were included in the qualitative analysis. An exponential growth model was used for quantitative characterization of tumor growth rate. Tumor doubling time has remained stable over the past 80 years. Recent studies have not only identified "fast growing tumor" (grade 3, human epidermal growth factor receptor 2-positive, triple-negative, or tumor with an elevated Ki-67) but also "inactive breast cancer" feeding the ongoing debate of overdiagnosis due to screening programs. The stability of tumor doubling time over the past 80 years, despite increasing and changing risk factors, supports the validity for our screening guidelines. Prospective studies based on more precise measurement of tumor size and adjustment for tumor characteristics are necessary to more clearly characterize the prognostic and predictive impact of tumor doubling time in breast cancer.

Breast cancer progression when definitive surgery is delayed

Deferment of definitive surgery for some breast cancers has been proposed as a way to conserve hospital resources during the COVID-19 pandemic. However, it is currently unknown which, if any, breast cancers are capable of progressing during a few to several months of observation. The difference between clinical size at diagnosis and final pathology size was assessed in 315 stage I-III primary invasive breast cancer patients who were divided into three groups based on the time between diagnosis and definitive surgery. Size differences over time were used to estimate specific growth rates. Compared with the group with ≤60 days between diagnosis and surgery, tumor growth was observed for 12% of tumors in the 61- to 120-day group and 17% of tumors in the >120-day group (p for trend = 0.032). Significantly greater specific growth rates were observed for tumors >2 cm by pathology measurement and for pathology node-positive patients (p < 0.0001 and p = 0.006, respectively). Specific growth rates were significantly greater for luminal B breast cancers than for luminal A breast cancers (p = 0.029) but not for triple-negative or HER2-positive breast cancers not selected for neo-adjuvant chemotherapy. There was no evidence of nodal progression with surgery delay. Fewer than 20% of stage I-III breast cancers not selected for neo-adjuvant chemotherapy evidence size progression during follow-up periods ranging from 61 to 294 days. Clinical-pathological features cannot reliably predict which tumors will grow. Luminal B phenotype was the only clinical variable known at the time of diagnosis that strongly predicted growth. If resource limitations mandate prioritization schemes for breast cancer surgery, luminal B breast cancer may be the highest priority.

Modeling breast cancer survival and metastasis rates from moderate-sized clinical data

Predicting time-dependent survival probability of a breast cancer patient using information such as primary tumor size, grade, node spread status, and patient age at the time of surgery can be of immense help in managing life expectations and strategizing postoperative treatment. However, for moderate-sized clinical datasets the application of standard Kaplan-Meier theory to determine survival probability as a function of multiple cofactors can become challenging when continuous variables like tumor diameter and survival time are segmented into a large number of narrow intervals, a problem commonly termed the curse of dimensionality. We circumvent this problem by modeling the patient-to-patient distribution of primary tumor diameter with a realistic, right-skewed function, and then matching the diameter-marginalized survival with the mean Kaplan-Meier survival for the data. We apply this procedure on a recent clinical data from 1875 breast cancer patients and develop parameters that can be readily used to estimate post-surgery survival for an arbitrary time length. Finally, we show that the observed fraction of node-positive patients can be quantitatively explained within a simple tumor growth and metastasis framework. Employing two different tumor growth models from the literature (i.e., Gompertz and logistic growth models), we utilize the observed fraction-node-positive data to determine metastasis rates from the surface of a primary tumor and its patient-to-patient distribution.

A Mathematical Model to Predict Diagnostic Periods for Secondary Distant Metastases in Patients with ER/PR/HER2/Ki-67 Subtypes of Breast Cancer

Previously, a consolidated mathematical model of primary tumor (PT) growth and secondary distant metastasis (sdMTS) growth in breast cancer (BC) (CoMPaS) was presented. The aim was to detect the diagnostic periods for visible sdMTS via CoMPaS in patients with different subtypes ER/PR/HER2/Ki-67 (Estrogen Receptor/Progesterone Receptor/Human Epidermal growth factor Receptor 2/Ki-67 marker) of breast cancer. CoMPaS is based on an exponential growth model and complementing formulas, and the model corresponds to the tumor-node-metastasis (TNM) staging system and BC subtypes (ER/PR/HER2/Ki-67). The CoMPaS model reflects (1) the subtypes of BC, such as ER/PR/HER2/Ki-67, and (2) the growth processes of the PT and sdMTSs in BC patients without or with lymph node metastases (MTSs) in accordance with the eighth edition American Joint Committee on Cancer prognostic staging system for breast cancer. CoMPaS correctly describes the growth of the PT in the ER/PR/HER2/Ki-67 subtypes of BC patients and helps to calculate the different diagnostic periods, depending on the tumor volume doubling time of sdMTS, when sdMTSs might appear. CoMPaS and the corresponding software tool can help (1) to start the early treatment of small sdMTSs in BC patients with different tumor subtypes (ER/PR/HER2/Ki-67), and (2) to consider the patient almost healthy if sdMTSs do not appear during the different diagnostic periods.

Tumor Proliferation and Invasiveness Derived From Ultrasound Appearances of Invasive Breast Cancers: Moving Beyond the Routine Differential Diagnosis

OBJECTIVES

To investigate the correlation between ultrasound (US) appearances of invasive breast cancers and tumor proliferation and invasiveness measured according to the histologic grade, Ki-67 expression, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI).

METHODS

This study evaluated 676 patients who underwent primary surgical treatment of invasive breast cancers. The preoperative US reports and postoperative pathologic and immunohistochemical results of the patients were retrospectively reviewed. Ultrasound characteristics were evaluated according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) lexicon. Logistic regression analyses were used to identify independent predictive US features that were correlated with tumor proliferation and invasiveness of breast cancers. Odds ratios (ORs) were calculated.

RESULTS

Posterior acoustic enhancement and calcifications on US images were independent predictive factors of a higher histologic grade and a higher Ki-67 level (OR, 1.69-6.54; P < .05). Meanwhile, a noncircumscribed margin (OR, 2.61; P < .05) and posterior acoustic shadow (OR, 1.62; P < .05) were independent predictors of ALNM. An irregular shape (OR, 2.13; P < .05) and calcifications (OR, 1.69; P < .05) were independent risk factors for LVI. Infiltrative breast cancers scored as BI-RADS category 5 had higher probability to be associated with ALNM (OR, 3.33; P < .0005) and LVI (OR, 2.87; P < .0005).

CONCLUSIONS

Ultrasound features of invasieve breast cancers might have a predictive value for tumor proliferation and invasiveness. The US features correlated with a high cellular proliferation rate were different from those associated with ALNM. The tumor shape, margin, posterior acoustic pattern, and calcifications at US are suggested to be considered by clinicians when making clinical decisions.

Tumor Volume Kinetic Analyses Might Explain Excellent Prognoses in Young Patients with Papillary Thyroid Carcinoma

Introduction

Young patients with papillary thyroid carcinoma (PTC) generally have excellent prognoses despite their often-advanced disease status. The reasons for this excellent prognosis are poorly understood.

Objective

To investigate the natural history of PTC in young patients, we compared the observed tumor volume-doubling rate (TV-DR) with the hypothetical tumor volume-doubling rate (hTV-DR) before presentation in young PTC patients. DR is an inverse of the doubling time and indicates the number of doublings that occur in a unit of time. A negative value indicates the number of times the volume is reduced by half per unit time.

Methods

We enrolled 20 patients with the following characteristics: age ≤19 years, diagnosed with PTC according to the cytology results between 2013 and 2018 and followed-up with periodical ultrasound examinations for ≥3 months before surgery for various reasons. Seventeen patients later underwent surgery confirming the diagnosis. We calculated TV-DRs using serial measurements of tumor diameters after presentation and hTV-DRs using tumor diameters and patients' age at presentation, assuming that a single cancer cell was present at the patient's birth and that the tumor grew at a constant rate. These values indicate the lowest growth rates necessary for a single cancer cell to achieve the full tumor size at presentation.

Results

Thirteen patients had positive TV-DRs (/year) ranging from 0.09 to 1.89, indicating tumor growth, and the remaining seven patients had negative values (−0.08 to −1.21), indicating regression. The median TV-DR was 0.29. The hTV-DRs (1.48–2.66, median 1.71) were significantly larger than the TV-DRs (p < 0.001), indicating much faster growth before presentation.

Conclusions

These data suggest that deceleration of tumor growth had already occurred at presentation in the majority of the cases. This might explain why disease-specific survival is excellent despite frequent findings of advanced disease in young patients with PTC.

Radiological audit of interval breast cancers: Estimation of tumour growth rates

INTRODUCTION

This multicentre, retrospective study aimed to establish correlation between estimated tumour volume doubling times (TVDT) from a series of interval breast cancers with their clinicopathological features. The potential impact of delayed diagnosis on prognosis was also explored.

MATERIALS AND METHODS

Interval cancers, where screening mammograms demonstrated changes that were retrospectively classified as either uncertain or suspicious, were reviewed from five screening units within the UK NHS Breast Screening Programme (NHSBSP). Data collected included the time interval between screening mammogram and cancer diagnosis, the size of the initial mammographic abnormality and of the subsequent cancer, demographics, mammographic density and tumour biology. We estimated volume doubling times and the estimated change in size and node status, which would have followed if these cancers had been detected at the previous screen.

RESULTS

306 interval cancers meeting the inclusion criteria were identified. Average time from screening to diagnosis was 644 days (SD 276 days). 19% were diagnosed in the first twelve months, 42% in the subsequent twelve months and 39% thereafter. Overall average estimated TVDT was 167 days (95% CI 151-186). Significant differences were noted with age (p = 0.01), grade (p < 0.001) and ER status (p < 0.001) with women under 60, grade 3 cancers and ER negative cancers having shorter TVDTs. HER2 positive tumours had shorter doubling times than HER2 negative, but this difference was not statistically significant. It was estimated that diagnosing these cancers at the previous screen would have increased ten-year survival from 82% to 86%.

CONCLUSION

High grade, ER negativity and younger age were associated with shorter durations of TVDT. The role of HER2 status on interval cancer growth rate requires further assessment. It is likely that the delayed diagnosis of interval cancers confers a 4% reduction in ten-year survival.

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

OBJECTIVES

To investigate the value of ultrasound (US) feature-based models in predicting the proliferation and invasiveness of invasive breast cancer (IBC) and to compare the performance of models based solely on US features with models that combined US features, patient age, tumor size, and axilla status from US.

METHODS

With ethical approval, 746 patients with a pathologic diagnosis of IBC were reviewed for preoperative clinical, US, and postoperative pathologic data. The proliferation and invasiveness properties of the IBC included the histologic grade and Ki-67 status and lymphovascular invasion (LVI) and axillary lymph node metastasis (ALNM), respectively. Logistic regression analyses were used to identify independent risk factors for tumor proliferation and invasiveness.

RESULTS

Posterior echo enhancement, calcification, a tumor size larger than 2 cm, and suspicion of ALNM from axillary US were independent risk factors for a high histologic grade and high Ki-67 expression of IBC (P < .05). A posterior echo shadow, patient age younger than 45 years, and suspicious findings on axillary US imaging were independent variables for predicting the presence of LVI and ALNM in IBC (P < .05). Calcification was the independent factor for predicting LVI (P = .013). The predictive performance of the combined models was improved compared with the US feature-based models, with a higher accuracy rate and negative predictive value. The area under curve of the combined models was also significantly higher than that of the single models (P < .05).

CONCLUSIONS

Compared with the US feature-based models, the combined models yielded better predictive performance. This may provide a more robust model to predict the tumor biological properties of IBC before surgery.

Molecular natural history of breast cancer: Leveraging transcriptomics to predict breast cancer progression and aggressiveness

BACKGROUND

Characterizing breast cancer progression and aggressiveness relies on categorical descriptions of tumor stage and grade. Interpreting these categorical descriptions is challenging because stage convolutes the size and spread of the tumor and no consensus exists to define high/low grade tumors.

METHODS

We address this challenge of heterogeneity in patient-specific cancer samples by adapting and applying several tools originally created for understanding heterogeneity and phenotype development in single cells (specifically, single-cell topological data analysis and Wanderlust) to create a continuous metric describing breast cancer progression using bulk RNA-seq samples from individual patient tumors. We also created a linear regression-based method to predict tumor aggressiveness in vivo from bulk RNA-seq data.

RESULTS

We found that breast cancer proceeds along three convergent phenotype trajectories: luminal, HER2-enriched, and basal-like. Furthermore, 31 296 genes (for luminal cancers), 17 827 genes (for HER2-enriched), and 18 505 genes (for basal-like) are dynamically differentially expressed during breast cancer progression. Across progression trajectories, our results show that expression of genes related to ADP-ribosylation decreased as tumors progressed (while PARP1 and PARP2 increased or remained stable), suggesting the potential for a differential response to PARP inhibitors based on cancer progression. Additionally, we developed a 132-gene expression regression equation to predict mitotic index and a 23-gene expression regression equation to predict growth rate from a single breast cancer biopsy.

CONCLUSION

Our results suggest that breast cancer dynamically changes during disease progression, and growth rate of the cancer cells is associated with distinct transcriptional profiles.

Dissecting Effects of Anti-cancer Drugs and Cancer-Associated Fibroblasts by On-Chip Reconstitution of Immunocompetent Tumor Microenvironments

A major challenge in cancer research is the complexity of the tumor microenvironment, which includes the host immunological setting. Inspired by the emerging technology of organ-on-chip, we achieved 3D co-cultures in microfluidic devices (integrating four cell populations: cancer, immune, endothelial, and fibroblasts) to reconstitute ex vivo a human tumor ecosystem (HER2⁺ breast cancer). We visualized and quantified the complex dynamics of this tumor-on-chip, in the absence or in the presence of the drug trastuzumab (Herceptin), a targeted antibody therapy directed against the HER2 receptor. We uncovered the capacity of the drug trastuzumab to specifically promote long cancer-immune interactions (>50 min), recapitulating an anti-tumoral ADCC (antibody-dependent cell-mediated cytotoxicity) immune response. Cancer-associated fibroblasts (CAFs) antagonized the effects of trastuzumab. These observations constitute a proof of concept that tumors-on-chip are powerful platforms to study ex vivo immunocompetent tumor microenvironments, to characterize ecosystem-level drug responses, and to dissect the roles of stromal components.

Machine learning-based prediction of breast cancer growth rate in vivo

Background

Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.

Methods

A serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.

Results

SM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.

Conclusion

Our Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications.

Does breast cancer growth rate really depend on tumor subtype? Measurement of tumor doubling time using serial ultrasonography between diagnosis and surgery

BACKGROUND

Breast cancer growth is generally expected to differ between tumor subtypes. We aimed to evaluate tumor doubling time (DT) using ultrasonography and verify whether each tumor subtype has a unique DT.

METHODS

This retrospective study included 265 patients with invasive breast cancer who received serial ultrasonography between diagnosis and surgery. Tumor diameters were measured in three directions and DTs were calculated according to an exponential growth model using the volume change during serial ultrasonography. We investigated the relationships between DT, tumor subtype, and histopathological factors.

RESULTS

Volumes did not change in 95 (36%) of 265 tumors and increased in 170 (64%) tumors during serial ultrasonography (mean interval, 56.9 days). The mean volume increases of all tumors and volume-increased tumors were 22.1% and 34.5%, respectively. Triple-negative tumors had greater volume increases (40% vs. 20%, p = 0.001) and shorter DT (124 vs. 185 days, p = 0.027) than estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)- tumors. Volume-increased tumors had higher Ki-67 indices than those of volume-stable tumors in ER+/HER2- (p = 0.002) and ER+/HER2+ tumors (p = 0.011) and higher histological grades in all tumors except triple-negative tumors (p < 0.001). Triple-negative tumors with DTs < 90 days (short-DT) showed higher Ki-67 indices than those with DTs > 90 days (long-DT) (p = 0.008). In ER+/HER2- tumors, histological grades were higher for short-DT than for long-DT tumors (p = 0.022).

CONCLUSION

Differences in tumor DT depending on breast cancer subtype, Ki-67 index, and histological grade were confirmed using serial ultrasonography even during preoperative short interval.

Chemotherapeutic dosing implicated by pharmacodynamic modeling of in vitro cytotoxic data: a case study of paclitaxel

Conventional maximum tolerated doses (MTD) in chemotherapy are recently challenged by an alternative dosing method with low doses and high dosing frequency (LDHF). Still, it remains unclear which chemotherapies would potentially benefit from LDHF. The pharmacokinetic (PK) differences between MTD and LDHF are drug exposure magnitude (concentration) and exposure duration (time), two fundamental PK elements that are associated with the pharmacodynamics (PD) of chemotherapies. Here we hypothesized that quantitatively analyzing the contribution of each PK element to the overall cytotoxic effects would provide insights to the selection of the preferred chemotherapeutic dosing. Based on in vitro cytotoxic data, we developed a cellular PD model, which assumed that tumor cells were generally comprised of two subpopulations that were susceptible to either concentration- or time-dependent cytotoxicity. The developed PD model exhibited high flexibility to describe diverse patterns of cell survival curves. Integrated with a PK model, the cellular PD model was further extended to predict and compare the anti-tumor effect of paclitaxel in two dosing regimens: multiple MTD bolus and continuous constant infusion (an extreme LDHF). Our simulations of paclitaxel in treatment of three types of cancers were consistent with clinical observations that LDHF yielded higher patient efficacy than MTD. Our further analysis suggested that the ratio between drug steady-state concentrations and its cytotoxic sensitivity (C _ss /KC ₅₀ ) was a critical factor that largely determines favored dosing regimen. LDHF would produce higher efficacy when the ratio C _ss /KC ₅₀ is greater than 1. Otherwise MTD was favored. The developed PD model presented an approach simply based on in vitro cytotoxic data to predict the potentially favored chemotherapeutic dosing between MTD and LDHF.

Accuracy of Tumor Sizing in Breast Cancer: A Comparison of Strain Elastography, 3-D Ultrasound and Conventional B-Mode Ultrasound with and without Compound Imaging

The objective of this study was to compare the accuracy of strain elastography (SE), 3-D ultrasound (US), B-mode US with compound imaging (CI) and B-mode US without compound imaging for lesion sizing in breast cancer. The prospective study included 93 patients with invasive breast cancer. The largest tumor diameters measured by B-mode US, B-mode US with CI, SE and 3-D US were compared in Bland-Altman plots versus pathology as reference. A general linear model repeated measures (GLM Rep) was applied to investigate factors influencing tumor sizing. All methods underestimated pathologic size, with SE (-0.08 ± 7.7 mm) and 3-D US (-1.4 ± 6.5 mm) having the smallest mean differences from pathology. Bland-Altman plots revealed that B-mode US, B-mode US with CI and 3-D US systematically underestimated large tumor sizes, and only SE was technically comparable to pathology. The study indicates that sonographic underestimation of tumor size occurs mainly in tumors >20 mm; in this subgroup, SE is superior to other ultrasound methods.

Tumor growth rate of invasive breast cancers during wait times for surgery assessed by ultrasonography

Several studies suggest that delay in the surgical treatment of breast cancer is significantly associated with lower survival. This study evaluated the tumor growth rate (TGR) of invasive breast cancers during wait times for surgery quantitatively using ultrasonography (US) and identified clinicopathologic factors associated with TGR.This retrospective study was approved by our institutional review board and the requirement for written informed consent was waived. Between August 2013 and September 2014, a total of 323 unifocal invasive breast cancers in 323 women with serial US images at the time of diagnosis and surgery were included. Tumor diameters and volumes were measured using 2-orthogonal US images. TGR during wait times for surgery was quantified as specific growth rates (SGR; %/day) and was compared with clinicopathologic variables using univariate and multivariate analyses.Median time from diagnosis to surgery was 31 days (range, 8-78 days). Maximum tumor diameters and volumes at the time of surgery (mean, 15.6 mm and 1.6 cm) were significantly larger than at diagnosis (14.7 mm and 1.3 cm) (P < 0.001). On multivariate analysis, surrogate molecular subtype was a significant independent factor of SGR (P = 0.001); triple negative cancers showed the highest SGR (1.003%/day) followed by HER2-positive (0.859 %/day) and luminal cancers (luminal B, 0.208 %/day; luminal A, 0.175%/day) (P < 0.001). Clinical T stage was more frequently upgraded in nonluminal (triple negative, 18% [12/67]; HER2-positive, 14% [3/22]) than luminal cancers (luminal B, 3% [1/30]; luminal A, 2% [4/204]) (P < 0.001).Invasive breast cancers with aggressive molecular subtypes showed faster TGR and more frequent upgrading of clinical T stage during wait times for surgery.