Tumour volume doubling time of molecular breast cancer subtypes assessed by serial breast ultrasound

Predicting Tumor Volume Doubling Time and Progression-Free Survival in Untreated Patients from Patient-Derived-Xenograft (PDX) Models: A Translational Model-Based Approach

Tumor volume doubling time (TVDT) has been shown to be a potential surrogate marker of biological tumor activity. However, its availability in clinics is strongly limited due to ethical and practical reasons, as its assessment requires at least two subsequent tumor volume measurements in untreated patients. Here, a translational modeling framework to predict TVDT distributions in untreated cancer patient populations from tumor growth data in patient-derived xenograft (PDX) mice is proposed. Eleven solid cancer types were considered. For each of them, a set of tumor growth studies in PDX mice was selected and analyzed through a mathematical model to characterize the distribution of the exponential tumor growth rate in mice. Then, assuming an exponential growth of the tumor mass in humans, the growth rates were scaled from PDX mice to humans through an allometric scaling approach and used to predict TVDTs in untreated patients. A very good agreement was found between model predicted and clinically observed TVDTs, with 91% of the predicted TVDT medians fell within 1.5-fold of observations. Further, exploiting the intrinsic relationship between tumor growth dynamics and progression free survival (PFS), the exponential growth rates in humans were used to generate the expected PFS curves in absence of anticancer treatment. Predicted curves were extremely close to published PFS data from studies involving patient cohorts treated with supportive care or low effective therapies. The proposed approach shows promise as a potential tool to increase knowledge about TVDT in humans without the need of directly measuring tumor dimensions in untreated patients, and to predict PFS curves in untreated patients, that could fill the absence of placebo-controlled arms against which to compare treaded arms during clinical trials. However, further validation and refinement are needed to fully assess its effectiveness in this regard.

Tumor Doubling Time and Screening Interval

The goal of screening is to detect breast cancers when still curable to decrease breast cancer-specific mortality. Breast cancer screening in the United States is routinely performed with digital mammography and digital breast tomosynthesis. This article reviews breast cancer doubling time by tumor subtype and examines the impact of doubling time on breast cancer screening intervals. By the article's end, the reader will be better equipped to have informed discussions with patients and medical professionals regarding the benefits and disadvantages of the currently recommended screening mammography intervals.

Minimum latency effects for cancer associated with exposures to radiation or other carcinogens

BACKGROUND

In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data.

METHODS

We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability.

RESULTS

There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability.

CONCLUSIONS

Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

Consulting a neurosurgeon upon initial medical assessment reduces the time to the first surgery and potentially contributes to improved prognosis for glioblastoma patients

BACKGROUND

The neurological status of glioblastoma patients rapidly deteriorates. We recently demonstrated that early diagnosis and surgery within 3 weeks from the initial symptoms are associated with improved survival. While glioblastoma is a semi-urgent disease, the prehospital behaviors and clinical outcomes of glioblastoma patients are poorly understood. We aimed to disclose how prehospital patient behavior influences the clinical outcomes of glioblastoma patients.

METHODS

Isocitrate dehydrogenase-wildtype glioblastoma patients treated at our institution between January 2010 and December 2019 were reviewed. Patients were divided into two groups, neurosurgeon and non-neurosurgeon groups, based on the primary doctor whom patients sought for an initial evaluation. Patient demographics and prognoses were examined.

RESULTS

Of 170 patients, 109 and 61 were classified into the neurosurgeon and non-neurosurgeon groups, respectively. The median age of neurosurgeon group was significantly younger than the non-neurosurgeon group (61 vs. 69 years old, P = 0.019) and in better performance status (preoperative Karnofsky performance status scores $\ge$80: 72.5 vs. 55.7%, P = 0.027). The neurosurgeon group exhibited a significantly shorter duration from the first hospital visit to the first surgery than the non-neurosurgeon group (18 vs. 29 days, P < 0.0001). Furthermore, the overall survival of the neurosurgeon group was significantly more prolonged than that of the non-neurosurgeon group (22.9 vs. 14.0 months, P = 0.038).

CONCLUSION

Seeking an initial evaluation by a neurosurgeon was potentially associated with prolonged survival in glioblastoma patients. A short duration from the first hospital visit to the first surgery is essential in enhancing glioblastoma patient prognosis.

Breast Cancer Growth on Serial MRI: Volume Doubling Time Based on 3-Dimensional Tumor Volume Assessment

BACKGROUND

The volume doubling time (VDT) of breast cancer was most frequently calculated using the two-dimensional (2D) diameter, which is not reliable for irregular tumors. It was rarely investigated using three-dimensional (3D) imaging with tumor volume on serial magnetic resonance imaging (MRI).

PURPOSE

To investigate the VDT of breast cancer using 3D tumor volume assessment on serial breast MRIs.

STUDY TYPE

Retrospective.

SUBJECTS

Sixty women (age at diagnosis: 57 ± 10 years) with breast cancer, assessed by two or more breast MRI examinations. The median interval time was 791 days (range: 70-3654 days).

FIELD STRENGTH/SEQUENCE

3-T, fast spin-echo T2-weighted imaging (T2WI), single-shot echo-planar diffusion-weighted imaging (DWI), and gradient echo dynamic contrast-enhanced imaging.

ASSESSMENT

Three radiologists independently reviewed the morphological, DWI, and T2WI features of lesions. The whole tumor was segmented to measure the volume on contrast-enhanced images. The exponential growth model was fitted in the 11 patients with at least three MRI examinations. The VDT of breast cancer was calculated using the modified Schwartz equation.

STATISTICAL TESTS

Mann-Whitney U test, Kruskal-Wallis test, Chi-squared test, intraclass correlation coefficients, and Fleiss kappa coefficients. A P-value <0.05 was considered statistically significant. The exponential growth model was evaluated using the adjusted R2 and root mean square error (RMSE).

RESULTS

The median tumor diameter was 9.7 mm and 15.2 mm on the initial and final MRI, respectively. The median adjusted R2 and RMSE of the 11 exponential models were 0.97 and 15.8, respectively. The median VDT was 540 days (range: 68-2424 days). For invasive ductal carcinoma (N = 33), the median VDT of the non-luminal type was shorter than that of the luminal type (178 days vs. 478 days). On initial MRI, breast cancer manifesting as a focus or mass lesion showed a shorter VDT than that of a non-mass enhancement (NME) lesion (median VDT: 426 days vs. 665 days).

DATA CONCLUSION

A shorter VDT was observed in breast cancer manifesting as focus or mass as compared to an NME lesion.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Long-Term Performance of an Image-Based Short-Term Risk Model for Breast Cancer

PURPOSE

Image-derived artificial intelligence-based short-term risk models for breast cancer have shown high discriminatory performance compared with traditional lifestyle/familial-based risk models. The long-term performance of image-derived risk models has not been investigated.

METHODS

We performed a case-cohort study of 8,604 randomly selected women within a mammography screening cohort initiated in 2010 in Sweden for women age 40-74 years. Mammograms, age, lifestyle, and familial risk factors were collected at study entry. In all, 2,028 incident breast cancers were identified through register matching in May 2022 (206 incident breast cancers were found in the subcohort). The image-based model extracted mammographic features (density, microcalcifications, masses, and left-right breast asymmetries of these features) and age from study entry mammograms. The Tyrer-Cuzick v8 risk model incorporates self-reported lifestyle and familial risk factors and mammographic density to estimate risk. Absolute risks were estimated, and age-adjusted AUC model performances (aAUCs) were compared across the 10-year period.

RESULTS

The aAUCs of the image-based risk model ranged from 0.74 (95% CI, 0.70 to 0.78) to 0.65 (95% CI, 0.63 to 0.66) for breast cancers developed 1-10 years after study entry; the corresponding Tyrer-Cuzick aAUCs were 0.62 (95% CI, 0.56 to 0.67) to 0.60 (95% CI, 0.58 to 0.61). For symptomatic cancers, the aAUCs for the image-based model were ≥0.75 during the first 3 years. Women with high and low mammographic density showed similar aAUCs. Throughout the 10-year follow-up, 20% of all women with breast cancers were deemed high-risk at study entry by the image-based risk model compared with 7.1% using the lifestyle familial-based model (P < .01).

CONCLUSION

The image-based risk model outperformed the Tyrer-Cuzick v8 model for both short-term and long-term risk assessment and could be used to identify women who may benefit from supplemental screening and risk reduction strategies.

Impact of the COVID-19 Pandemic on Melanoma Diagnosis: Increased Breslow Thickness in Primary Melanomas-A Single Center Experience

Early melanoma diagnosis plays a key role in ensuring best prognosis with good survival rates. The ongoing global COVID-19 pandemic has greatly impacted global and national healthcare systems, thus making it a real challenge. The aim of this study was to evaluate the impact of the pandemic on diagnostic delay in melanoma patients in Serbia. In this retrospective study, we included patients treated at the university hospital in Serbia's capitol over a period of five years and three months. We compared the prepandemic (01/JAN/17-14/MAR/20) and pandemic periods (15/MAR/20-31/MAR/22) by evaluating patient demographic data, melanoma subtype, Breslow thickness, Clark level, ulceration status, mitotic index rate and pT staging. We observed a significant reduction in the number of diagnosed patients (86.3 vs. 13.7%; p = 0.036), with melanomas having an increased median Breslow thickness (1.80 vs. 3.00; p = 0.010), a higher percentage of Clark IV-V level lesions (44.0% vs. 63.0%; p = 0.009), an increase in median mitotic index rate (2 vs. 5; p < 0.001) and a trend of increase in lesions thicker than 2 mm (37.8% vs. 53.7%; p = 0.026). We believe that this study can be a useful scenario guide for future similar events, highlighting the importance of preventive measures and timely diagnosis for the best patient outcomes.

Early Diagnosis and Surgical Intervention Within 3 Weeks From Symptom Onset Are Associated With Prolonged Survival of Patients With Glioblastoma

BACKGROUND

Glioblastoma (GBM) is a rapidly growing and most life-threatening malignant brain tumor. The significance of early treatment to the clinical outcomes of patients with GBM is unclear.

OBJECTIVE

To determine whether early diagnosis and surgery improve the preoperative and postoperative Karnofsky performance status (KPS) and prognosis of patients with GBM.

METHODS

Data of isocitrate dehydrogenase-wildtype patients with GBM treated at our institution between January 2010 and December 2019 were reviewed. Patients were classified into early or late diagnosis groups with a threshold of 14 days from initial symptoms. In addition, patients were divided into early, intermediate, and late surgery groups with thresholds of 21 and 35 days. Representative symptoms and patient prognoses were examined.

RESULTS

Of 153 patients, 72 and 81 were classified into the early and late diagnosis groups. The median tumor volume was significantly smaller in the former group. The proportion of patients with preoperative KPS scores 90 was 48.6% and 29.6% in the early and late diagnosis groups ( P = .016). The early, intermediate, and late surgery groups included 43, 24, and 86 patients. The median overall survival was significantly longer in the early surgery group than in the late surgery group (28.4 vs 18.7 months, P = .006). Multivariate analysis demonstrated that significant predictors of shorter survival included extent of tumor resection (partial or biopsy), preoperative and postoperative KPS 60, and O6-methylguanine-DNA-methyltransferase promoter status (unmethylated).

CONCLUSION

Early diagnosis within 2 weeks and surgical interventions within 3 weeks from the symptom onset are associated with prolonged patient survival. Early GBM treatment will benefit patients with GBM.

Effectiveness of Organized Mammography Screening for Different Breast Cancer Molecular Subtypes

Simple Summary

We evaluated the short-term effectiveness of a mammography screening program in all women who participated in the screening program and were diagnosed with screen-detected or interval breast cancer (BC) in Flanders (2008–2018). The evaluation was performed for the major molecular subtypes of invasive BC separately and considering the regularity of participation. We found that screen-detected BC was more likely to be diagnosed at early stages than interval BC of luminal, luminal-HER2-positive, and triple-negative BC (TNBC) type, but not for the human epidermal growth factor receptor 2-positive (HER2 positive) subtype. In addition, regular participation was related to a higher likelihood of screening detection than irregular participation for luminal, luminal-HER2-positive, and TNBC, but not for the HER2 positive subtype, either. Our results indicate that regular screening as compared to irregular screening is effective for all breast cancers except for the HER2 subtype.

Abstract

Background: Screening program effectiveness is generally evaluated for breast cancer (BC) as one disease and without considering the regularity of participation, while this might have an impact on detection rate. Objectives: To evaluate the short-term effectiveness of a mammography screening program for the major molecular subtypes of invasive BC. Methods: All women who participated in the screening program and were diagnosed with screen-detected or interval BC in Flanders were included in the study (2008–2018). Molecular subtypes considered were luminal and luminal-HER2-positive, human epidermal growth factor receptor 2-positive, and triple-negative BC (TNBC). The relationship between the BC stage at diagnosis (early (I–II) versus advanced (III–IV)) and the method of detection (screen-detected or interval) and the relationship between the method of detection and participation regularity (regular versus irregular) were evaluated by multi-variable logistic regression models. All models were performed for each molecular subtype and adjusted for age. Results: Among the 12,318 included women, BC of luminal and luminal-HER2-positive subtypes accounted for 70.9% and 11.3%, respectively. Screen-detected BC was more likely to be diagnosed at early stages than interval BC with varied effect sizes for luminal, luminal-HER2-positive, and TNBC with OR:2.82 (95% CI: 2.45–3.25), OR:2.39 (95% CI: 1.77–3.24), and OR:2.29 (95% CI: 1.34–4.05), respectively. Regular participation was related to a higher likelihood of screening detection than irregular participation for luminal, luminal-HER2-positive, and TNBC with OR:1.21 (95% CI: 1.09–1.34), OR: 1.79 (95% CI: 1.38–2.33), and OR: 1.62 (95% CI: 1.10–2.41), respectively. Conclusions: Regular screening as compared to irregular screening is effective for all breast cancers except for the HER2 subtype.

Advanced-Stage Melanoma at Presentation Following the Peak of the Pandemic: A COVID-19 Cancer Canary in a Coal Mine

Background

For melanoma patients, timely identification and tumor thickness are directly correlated with outcomes. COVID-19 impacted both patients’ ability and desire to see physicians. We sought to identify whether the pandemic correlated with changes in melanoma thickness at presentation and subsequent treatment timeline.

Methods

Retrospective chart review was performed on patients who underwent surgery for melanoma in an academic center surgical oncology practice from May 2019 to September 2021. Patients were split into two cohorts: “pre-pandemic” from May 2019 to May 2020 and “pandemic,” after May 2020, representing when these patients received their initial diagnostic biopsy. Demographic and melanoma-specific variables were recorded and analyzed.

Results

A total of 112 patients were identified: 51 patients from the “pre-pandemic” and 61 from the “pandemic” time period. The pandemic cohort more frequently presented with lesions greater than 1 mm thickness compared to pre-pandemic (68.8% v 49%, p = 0.033) and were found to have significantly more advanced T stage (p = 0.02) and overall stage disease (p = 0.022). Additionally, trends show that for pandemic patients more time passed from patient-reported lesion appearance/change to diagnostic biopsy (5.7 ± 2.0 v 7.1 ± 1.5 months, p = 0.581), but less time from biopsy to operation (42.9 ± 2.4 v 52.9 ± 5.0 days, p = 0.06).

Conclusions

“Pandemic” patients presented with thicker melanoma lesions and more advanced-stage disease. These results may portend a dangerous trend toward later stage at presentation, for melanoma and other cancers with rapid growth patterns, that will emerge as the prolonged effects of the pandemic continue to impact patients’ presentation for medical care.

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.

Combined diagnosis of multiparametric MRI-based deep learning models facilitates differentiating triple-negative breast cancer from fibroadenoma magnetic resonance BI-RADS 4 lesions

PURPOSE

To investigate the value of the combined diagnosis of multiparametric MRI-based deep learning models to differentiate triple-negative breast cancer (TNBC) from fibroadenoma magnetic resonance Breast Imaging-Reporting and Data System category 4 (BI-RADS 4) lesions and to evaluate whether the combined diagnosis of these models could improve the diagnostic performance of radiologists.

METHODS

A total of 319 female patients with 319 pathologically confirmed BI-RADS 4 lesions were randomly divided into training, validation, and testing sets in this retrospective study. The three models were established based on contrast-enhanced T1-weighted imaging, diffusion-weighted imaging, and T2-weighted imaging using the training and validation sets. The artificial intelligence (AI) combination score was calculated according to the results of three models. The diagnostic performances of four radiologists with and without AI assistance were compared with the AI combination score on the testing set. The area under the curve (AUC), sensitivity, specificity, accuracy, and weighted kappa value were calculated to assess the performance.

RESULTS

The AI combination score yielded an excellent performance (AUC = 0.944) on the testing set. With AI assistance, the AUC for the diagnosis of junior radiologist 1 (JR1) increased from 0.833 to 0.885, and that for JR2 increased from 0.823 to 0.876. The AUCs of senior radiologist 1 (SR1) and SR2 slightly increased from 0.901 and 0.950 to 0.925 and 0.975 after AI assistance, respectively.

CONCLUSION

Combined diagnosis of multiparametric MRI-based deep learning models to differentiate TNBC from fibroadenoma magnetic resonance BI-RADS 4 lesions can achieve comparable performance to that of SRs and improve the diagnostic performance of JRs.

Model-based inference of metastatic seeding rates in de novo metastatic breast cancer reveals the impact of secondary seeding and molecular subtype

We present a stochastic network model of metastasis spread for de novo metastatic breast cancer, composed of tumor to metastasis (primary seeding) and metastasis to metastasis spread (secondary seeding), parameterized using the SEER (Surveillance, Epidemiology, and End Results) database. The model provides a quantification of tumor cell dissemination rates between the tumor and metastasis sites. These rates were used to estimate the probability of developing a metastasis for untreated patients. The model was validated using tenfold cross-validation. We also investigated the effect of HER2 (Human Epidermal Growth Factor Receptor 2) status, estrogen receptor (ER) status and progesterone receptor (PR) status on the probability of metastatic spread. We found that dissemination rate through secondary seeding is up to 300 times higher than through primary seeding. Hormone receptor positivity promotes seeding to the bone and reduces seeding to the lungs and primary seeding to the liver, while HER2 expression increases dissemination to the bone, lungs and primary seeding to the liver. Secondary seeding from the lungs to the liver seems to be hormone receptor-independent, while that from the lungs to the brain appears HER2-independent.

Management of Non-Mass Enhancement at Breast Magnetic Resonance in Screening Settings Referred for Magnetic Resonance-Guided Biopsy

Rationale and Objectives

According to the Breast Imaging and Reporting Data System (BI-RADS), one of the main limitations of MRI is diagnosing the non-mass enhancement (NME). The NME lesion is challenging since it is unique to the MRI lexicon. This study aims to report our experience with NME lesions diagnosed by MRI referred for MRI-guided biopsies and discuss the management and follow-up of these lesions.

Materials and Methods

We retrospectively evaluated all MRI-guide breast biopsies. We included all patients referred for NME breast MRI-guided biopsy in screening settings. All patients had a negative second-look mammography or ultrasonography. We correlated the distribution and internal enhancement pattern (IEP) of the NME lesions with histology. Invasive ductal carcinomas (IDC) of no special type and ductal carcinoma in situ (DCIS) were considered malignant lesions.

Results

From January-2018 to July-2021, we included 96 women with a total of 96 lesions in the study. There were 90 benign and 6 malignant lesions with DCIS prevalence (5/6 cancers). The most frequent benign lesion type was fibrocystic changes. There were no NME lesions with diffuse or multiple area distribution features referred to MRI-guided biopsy. The positive-predictive values (PPV) were respectively 0.0%, 2.5%, 9.0%, and 11.0% for linear, focal, regional, and segmental distribution describers, and 0.0, 3.0%, 7.9%, and 50% for homogenous, heterogeneous, clumped, and clustered-ring enhancement patterns.

Conclusion

We observe the high potential risk for malignancy in the clustered-ring enhancement followed by the clumped pattern. Segmental distribution presented the highest predictive-positive values.

Development and evaluation of a method for tumor growth simulation in virtual clinical trials of breast cancer screening

Purpose: Image-based analysis of breast tumor growth rate may optimize breast cancer screening and diagnosis by suggesting optimal screening intervals and guide the clinical discussion regarding personalized screening based on tumor aggressiveness. Simulation-based virtual clinical trials (VCTs) can be used to evaluate and optimize medical imaging systems and design clinical trials. This study aimed to simulate tumor growth over multiple screening rounds. Approach: This study evaluates a preliminary method for simulating tumor growth. Clinical data on tumor volume doubling time (TVDT) was used to fit a probability distribution ("clinical fit") of TVDTs. Simulated tumors with TVDTs sampled from the clinical fit were inserted into 30 virtual breasts ("simulated cohort") and used to simulate mammograms. Based on the TVDT, two successive screening rounds were simulated for each virtual breast. TVDTs from clinical and simulated mammograms were compared. Tumor sizes in the simulated mammograms were measured by a radiologist in three repeated sessions to estimate TVDT. Results: The mean TVDT was 297 days (standard deviation, SD, 169 days) in the clinical fit and 322 days (SD, 217 days) in the simulated cohort. The mean estimated TVDT was 340 days (SD, 287 days). No significant difference was found between the estimated TVDTs from simulated mammograms and clinical TVDT values ( p > 0.5 ). No significant difference ( p > 0.05 ) was observed in the reproducibility of the tumor size measurements between the two screening rounds. Conclusions: The proposed method for tumor growth simulation has demonstrated close agreement with clinical results, supporting potential use in VCTs of temporal breast imaging.

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.

Assessing lead time bias due to mammography screening on estimates of loss in life expectancy

BACKGROUND

An increasingly popular measure for summarising cancer prognosis is the loss in life expectancy (LLE), i.e. the reduction in life expectancy following a cancer diagnosis. The proportion of life lost (PLL) can also be derived, improving comparability across age groups as LLE is highly age-dependent. LLE and PLL are often used to assess the impact of cancer over the remaining lifespan and across groups (e.g. socioeconomic groups). However, in the presence of screening, it is unclear whether part of the differences across population groups could be attributed to lead time bias. Lead time is the extra time added due to early diagnosis, that is, the time from tumour detection through screening to the time that cancer would have been diagnosed symptomatically. It leads to artificially inflated survival estimates even when there are no real survival improvements.

METHODS

In this paper, we used a simulation-based approach to assess the impact of lead time due to mammography screening on the estimation of LLE and PLL in breast cancer patients. A natural history model developed in a Swedish setting was used to simulate the growth of breast cancer tumours and age at symptomatic detection. Then, a screening programme similar to current guidelines in Sweden was imposed, with individuals aged 40-74 invited to participate every second year; different scenarios were considered for screening sensitivity and attendance. To isolate the lead time bias of screening, we assumed that screening does not affect the actual time of death. Finally, estimates of LLE and PLL were obtained in the absence and presence of screening, and their difference was used to derive the lead time bias.

RESULTS

The largest absolute bias for LLE was 0.61 years for a high screening sensitivity scenario and assuming perfect screening attendance. The absolute bias was reduced to 0.46 years when the perfect attendance assumption was relaxed to allow for imperfect attendance across screening visits. Bias was also present for the PLL estimates.

CONCLUSIONS

The results of the analysis suggested that lead time bias influences LLE and PLL metrics, thus requiring special consideration when interpreting comparisons across calendar time or population groups.

A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration

Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development. We used gene expression profiles of tumors to estimate the relative abundance of each immune cell and group patients based on their immune patterns. Dynamical results show the complex interplay between cells and molecules, and sensitivity analysis emphasizes the direct effects of macrophages and adipocytes on cancer cell growth. In addition, we observed the dual effect of IFN-γ on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.

VIRTUAL CLINICAL TRIALS IN MEDICAL IMAGING SYSTEM EVALUATION AND OPTIMISATION

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.

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.

Development of a Model to Estimate the Association Between Delay in Cancer Treatment and Local Tumor Control and Risk of Metastases

IMPORTANCE

The coronavirus disease 2019 (COVID-19) pandemic has led to treatment delays for many patients with cancer. While published guidelines provide suggestions on which cases are appropriate for treatment delay, there are no good quantitative estimates on the association of delays with tumor control or risk of new metastases.

OBJECTIVES

To develop a simplified mathematical model of tumor growth, control, and new metastases for cancers with varying doubling times and metastatic potential and to estimate tumor control probability (TCP) and metastases risk as a function of treatment delay interval.

DESIGN, SETTING, AND PARTICIPANTS

This decision analytical model describes a quantitative model for 3 tumors (ie, head and neck, colorectal, and non-small cell lung cancers). Using accepted ranges of tumor doubling times and metastatic development from the clinical literature from 2001 to 2020, estimates of tumor growth, TCP, and new metastases were analyzed for various treatment delay intervals.

MAIN OUTCOMES AND MEASURES

Risk estimates for potential decreases in local TCP and increases in new metastases with each interval of treatment delay.

RESULTS

For fast-growing head and neck tumors with a 2-month treatment delay, there was an estimated 4.8% (95% CI, 3.4%-6.4%) increase in local tumor control risk and a 0.49% (0.47%-0.51%) increase in new distal metastases risk. A 6-month delay was associated with an estimated 21.3% (13.4-30.4) increase in local tumor control risk and a 6.0% (5.2-6.8) increase in distal metastases risk. For intermediate-growing colorectal tumors, there was a 2.1% (0.7%-3.5%) increase in local tumor control risk and a 2.7% (2.6%-2.8%) increase in distal metastases risk at 2 months and a 7.6% (2.2%-14.2%) increase in local tumor control risk and a 24.7% (21.9%-27.8%) increase in distal metastases risk at 6 months. For slower-growing lung tumors, there was a 1.2% (0.0%-2.8%) increase in local tumor control risk and a 0.19% (0.18%-0.20%) increase in distal metastases risk at 2 months, and a 4.3% (0.0%-10.6%) increase in local tumor control risk and a 1.9% (1.6%-2.2%) increase in distal metastases risk at 6 months.

CONCLUSIONS AND RELEVANCE

This study proposed a model to quantify the association of treatment delays with local tumor control and risk of new metastases. The detrimental associations were greatest for tumors with faster rates of proliferation and metastasis. The associations were smaller, but still substantial, for slower-growing tumors.

The lingering mysteries of metastatic recurrence in breast cancer

Despite being the hallmark of cancer that is responsible for the highest number of deaths, very little is known about the biology of metastasis. Metastatic disease typically manifests after a protracted period of undetectable disease following surgery or systemic therapy, owing to relapse or recurrence. In the case of breast cancer, metastatic relapse can occur months to decades after initial diagnosis and treatment. In this review, we provide an overview of the known key factors that influence metastatic recurrence, with the goal of highlighting the critical unanswered questions that still need to be addressed to make a difference in the mortality of breast cancer patients.

Delay in surgery is associated with axillary upstaging of clinically node negative breast cancer patients

BACKGROUND AND OBJECTIVES

Most breast cancer (BC) patients present with early disease and clinically negative lymph nodes (cN0). Timing of surgery has not been standardized. We hypothesized that surgical delay results in an increased likelihood of nodal metastasis.

METHODS

Patients diagnosed with cN0 BC undergoing surgery with sentinel lymph node biopsy as initial therapy between 2006 and 2014 were identified in the NCDB and divided into four groups based on time intervals between diagnosis and surgery (<4 weeks, 4-8 weeks, 8-12 weeks, and >12 weeks). Regression analysis evaluated the independent impact of surgical timing on axillary upstaging and survival.

RESULTS

Of 355,443 patients with cN0 BC, 39.6% had surgery within 4 weeks and 5.4% more than 12 weeks from diagnosis. After controlling for relevant factors, a month delay in surgery was associated with an increased likelihood of nodal positivity (odds ratio: 1.04; 95% confidence interval [CI]: 1.04-1.05; p < .001) and decreased overall survival (hazard ratio: 1.03; 95% CI: 1.02-1.04; p < .001). When compared to patients who underwent surgery less than 4 weeks from diagnosis, the absolute increase in nodal positivity and relative risks were 5.3% (95% CI: 0.047-0.059) and 1.34 (95% CI: 1.30-1.38), respectively, in the more than 12 weeks group.

CONCLUSIONS

Delay in BC surgery in cN0 patients was associated with an increased likelihood of axillary upstaging and decreased survival.

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.

The natural history of untreated estrogen receptor-positive, Her2-negative invasive breast cancer

BACKGROUND

Using prior mammograms from patients with delays in their breast cancer diagnoses, we sought to describe in-vivo growth kinetics of untreated breast cancer to determine if the time they became clinically apparent can be predicted.

METHODS

Patient and tumor characteristics were collected from those who presented with "missed," untreated breast cancer to a breast center in a single institution. Only patients whose biopsied masses revealed estrogen receptor-positive, Her2-negative (ER+/Her2-) invasive cancers were included. Two attending radiologists reviewed images from prior mammograms. Rates of change in volume were calculated in mm³/day, and a logarithmic equation was used to calculate tumor volume doubling time (TVDT). A Spearman's Rho correlation was performed for the continuous variables, and the Mann-Whitney U and Kruskal-Wallis tests were used to compare categorical data. A p value < 0.05 was considered statistically significant. Logistic regression was performed to determine if patient or tumor characteristics were correlated to tumor growth velocity.

RESULTS

Of the 36 ER+/Her2- invasive breast cancers included in the analysis, 13 (36%) were at least cT2 (of TNM), 7 (19%) were grade 3, and 7 (19%) were node positive at diagnosis. Grade (p = 0.043) and pathologic invasive tumor size (p = 0.001) were positively correlated to tumor growth velocity. Median TVDT was 385 days (23-1897). Age, nodal positivity, Oncotype Dx® Recurrence Score, time of diagnostic delay, and spheroid-ellipsoid discrepancy (SED) were not related to tumor growth velocity in this sample.

CONCLUSION

In this cohort of patients with untreated ER+/Her2- invasive breast cancers, grade and pathologic tumor size were found to be positively correlated to growth velocity. The growth rates in a homogeneous group of tumors varied widely and could not be predicted. One possible explanation for this finding is that other difficult-to-measure biologic factors such as tumor microenvironment may play a greater role in tumor progression than traditional clinicopathologic characteristics.

Targeted lapatinib anti-HER2/ErbB2 therapy resistance in breast cancer: opportunities to overcome a difficult problem

Approximately 20% of invasive breast cancers have upregulation/gene amplification of the oncogene human epidermal growth factor receptor-2 (HER2/ErbB2). Of these, some also express steroid receptors (the so-called Luminal B subtype), whereas others do not (the HER2 subtype). HER2 abnormal breast cancers are associated with a worse prognosis, chemotherapy resistance, and sensitivity to selected anti-HER2 targeted therapeutics. Transcriptional data from over 3000 invasive breast cancers suggest that this approach is overly simplistic; rather, the upregulation of HER2 expression resulting from gene amplification is a driver event that causes major transcriptional changes involving numerous genes and pathways in breast cancer cells. Most notably, this includes a shift from estrogenic dependence to regulatory controls driven by other nuclear receptors, particularly the androgen receptor. We discuss members of the HER receptor tyrosine kinase family, heterodimer formation, and downstream signaling, with a focus on HER2 associated pathology in breast carcinogenesis. The development and application of anti-HER2 drugs, including selected clinical trials, are discussed. In light of the many excellent reviews in the clinical literature, our emphasis is on recently developed and successful strategies to overcome targeted therapy resistance. These include combining anti-HER2 agents with programmed cell death-1 ligand or cyclin-dependent kinase 4/6 inhibitors, targeting crosstalk between HER2 and other nuclear receptors, lipid/cholesterol synthesis to inhibit receptor tyrosine kinase activation, and metformin, a broadly inhibitory drug. We seek to facilitate a better understanding of new approaches to overcome anti-HER2 drug resistance and encourage exploration of two other therapeutic interventions that may be clinically useful for HER+ invasive breast cancer patients.

Cancer recurrence times from a branching process model

As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where metastatic lesions are initiated at a rate which depends on the size of the primary tumor. The evolution of each metastasis is described as an independent branching process. We assume that the primary tumor is resected at a given size and study the earliest time at which any metastasis reaches a minimal detectable size. The parameters of our model are estimated independently for breast, colorectal, headneck, lung and prostate cancers. We use these estimates to compare predictions from our model with values reported in clinical literature. For some cancer types, we find a remarkably wide range of resection sizes such that metastases are very likely to be present, but none of them are detectable. Our model predicts that only very early resections can prevent recurrence, and that small delays in the time of surgery can significantly increase the recurrence probability.

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.

Quantitative Systems Pharmacology Model of a Masked, Tumor-Activated Antibody

PROBODY therapeutics (Pb‐Tx) are protease‐activatable prodrugs of monoclonal antibodies (mAbs) designed to target tumors where protease activity is elevated while avoiding normal tissue. They are composed of a parental mAb, a mask that inhibits antibody binding to target, and a protease‐cleavable substrate between the mask and the mAb. We report a quantitative systems pharmacology model for the rational design and clinical translation of Pb‐Tx. The model adequately described monkey pharmacokinetic data following the administration of six anti‐CD166 Pb‐Tx of varying mask strength and substrate cleavability and captured the trend of decreasing Pb‐Tx systemic clearance with increasing mask strength. Projections to humans suggested both higher levels of Pb‐Tx in tumor relative to parental mAb and an optimal mask strength for maximizing tumor receptor–mediated uptake. Simulations further suggested the majority of circulating species in humans would be intact/masked Pb‐Tx, with no significant flux of cleaved/activated species from tumor to the systemic compartment.

Natural History of Gastric Cancer: Observational Study of Gastric Cancer Patients Not Treated During Follow-Up

BACKGROUND

Understanding the natural progression of untreated gastric cancer is critical for determining the disease prognosis as well as treatment options and timing. The aim of this study is to analyze the natural history of gastric cancer.

PATIENTS AND METHODS

We included patients with gastric cancer who had not received any treatment and were staged using endoscopy/endoscopic ultrasonography and computed tomography on at least two follow-up visits during intervals of nontreatment. Tumor volumes were also measured in addition to the staging. Survival of each stage at diagnosis was also analyzed.

RESULTS

A total of 101 patients were included. The mean follow-up period was 35.1 ± 34.4 months. The gastric cancer doubling time was 11.8 months for T1 and 6.2 months for T4. The progression time from early gastric cancer to advanced gastric cancer was 34 months. It decreased as the stages advanced: from 34 months between tumor-nodes-metastasis stage I and II to 1.8 months between stage III and IV. No variable was identified as a risk factor for cancer progression. The 5-year survival rates of untreated patients were 46.2% in stage I and 0% in stage II, stage III, and stage IV.

CONCLUSIONS

The progression and doubling times of gastric cancer shorten as the stages advance. Objective data reported in this study can be a critical factor in determining treatment timing and screening interval.

Growth Dynamics of Mammographic Calcifications: Differentiating Ductal Carcinoma in Situ from Benign Breast Disease

Background Most ductal carcinoma in situ (DCIS) lesions are first detected on screening mammograms as calcifications. However, false-positive biopsy rates for calcifications range from 30% to 87%. Improved methods to differentiate benign from malignant calcifications are thus needed. Purpose To quantify the growth rates of DCIS and benign breast disease that manifest as mammographic calcifications. Materials and Methods All calcifications (n = 2359) for which a stereotactic biopsy was performed from 2008 through 2015 at Duke University Medical Center were retrospectively identified. Mammograms from all cases of DCIS (n = 404) were reviewed for calcifications that were visible on mammograms taken at least 6 months before biopsy. Women with at least one prior mammogram with visible calcifications were age- and race-matched 1:2 to women with a benign breast biopsy and calcifications visible on prior mammograms. The long axis of the calcifications was measured on all mammograms. Multivariable adjusted linear mixed-effects models estimated the association of calcification growth rates with patholo findings. Hierarchical clustering accounted for matching benign and DCIS groups. Results A total of 74 DCIS calcifications and 148 benign calcifications were included for final analysis. The median patient age was 62 years (interquartile range, 51-71 years). No significant difference in breast density (P > .05) or number of available mammograms (P > .05) was detected between groups. Calcifications associated with DCIS were larger than those associated with benign breast disease at biopsy (median, 10 mm vs 6 mm, respectively; P < .001). After adjustment, the relative annual increase in the long-axis length of DCIS calcifications was greater than that of benign breast calcifications (96% [95% confidence interval: 72%, 224%] vs 68% [95% confidence interval: 56%, 80%] per year, respectively; P < .001). Conclusion Ductal carcinoma in situ calcifications are more extensive at diagnosis and grow faster in extent than those associated with benign breast disease. The rate of calcification change may help to discriminate benign from malignant calcifications. © RSNA, 2019 Online supplemental material is available for this article.

In silico simulation of a clinical trial with anti-CTLA-4 and anti-PD-L1 immunotherapies in metastatic breast cancer using a systems pharmacology model

The low response rate of immune checkpoint blockade in breast cancer has highlighted the need for predictive biomarkers to identify responders. While a number of clinical trials are ongoing, testing all possible combinations is not feasible. In this study, a quantitative systems pharmacology model is built to integrate immune-cancer cell interactions in patients with breast cancer, including central, peripheral, tumour-draining lymph node (TDLN) and tumour compartments. The model can describe the immune suppression and evasion in both TDLN and the tumour microenvironment due to checkpoint expression, and mimic the tumour response to checkpoint blockade therapy. We investigate the relationship between the tumour response to checkpoint blockade therapy and composite tumour burden, PD-L1 expression and antigen intensity, including their individual and combined effects on the immune system, using model-based simulations. The proposed model demonstrates the potential to make predictions of tumour response of individual patients given sufficient clinical measurements, and provides a platform that can be further adapted to other types of immunotherapy and their combination with molecular-targeted therapies. The patient predictions demonstrate how this systems pharmacology model can be used to individualize immunotherapy treatments. When appropriately validated, these approaches may contribute to optimization of breast cancer treatment.

Why is pancreatic cancer so deadly? The pathologist's view

The remarkable aggressiveness of pancreatic cancer has never been fully explained. Although clearly multifactorial, we postulate that venous invasion, a finding seen in most pancreatic cancers but not in most cancers of other organs, may be a significant, underappreciated contributor to the aggressiveness of this disease. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Solid component tumor doubling time is a prognostic factor in non-small cell lung cancer patients

Background

Recently, several reports investigating tumor doubling times (TDTs) in lung cancer have demonstrated that lung cancer patients with shorter TDTs have poor prognoses. Although data have shown that the solid component of a tumor is clinically more important, relationships between solid component TDTs and lung cancer prognoses remain unclear.

Methods

To evaluate relationships between TDT and survival, we retrospectively evaluated 231 patients who underwent surgical resection for non-small cell lung cancer. The TDTs of whole and solid components were calculated using preoperative thin-slice chest computed tomography scans with a cut-off of 400 d between scans.

Results

Patients with short TDTs (< 400 d) both in the solid and whole components had poor prognoses. Among pathological stage I patients (n = 176), short solid component TDT (< 400 d) significantly influenced prognosis only in pathological stage IB patients. Moreover, we found that patients with shorter solid component TDTs had significantly worse prognosis compared with patients who showed shorter whole component TDTs.

Conclusions

Short solid component TDTs (< 400 d) could be a poor prognostic indicator for non-small cell lung cancer patients undergoing surgical resection; furthermore, clinicians should pay particularly close attention to cases with rapid growth of the solid tumor component.

Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy

Genomic changes observed across treatment may result from either clonal evolution or geographically disparate sampling of heterogeneous tumors. Here we use computational modeling based on analysis of fifteen primary breast tumors and find that apparent clonal change between two tumor samples can frequently be explained by pre-treatment heterogeneity, such that at least two regions are necessary to detect treatment-induced clonal shifts. To assess for clonal replacement, we devise a summary statistic based on whole-exome sequencing of a pre-treatment biopsy and multi-region sampling of the post-treatment surgical specimen and apply this measure to five breast tumors treated with neoadjuvant HER2-targeted therapy. Two tumors underwent clonal replacement with treatment, and mathematical modeling indicates these two tumors had resistant subclones prior to treatment and rates of resistance-related genomic changes that were substantially larger than previous estimates. Our results provide a needed framework to incorporate primary tumor heterogeneity in investigating the evolution of resistance.

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.

Comparison of Ultrasound Elastography and Color Doppler Ultrasonography for Distinguishing Small Triple-Negative Breast Cancer From Fibroadenoma

OBJECTIVES

To compare the performance of ultrasound elastography and color Doppler ultrasonography (US) in distinguishing small, oval, or round triple-negative breast cancer from fibroadenoma and the influence on the further management decision at US.

METHODS

In total, 131 biopsy-proven oval or round fibroadenomas (n = 68) and triple-negative breast cancers (n = 63) smaller than 2 cm were included. Three blinded readers assessed the images from US, elastography, and color Doppler imaging according to the Breast Imaging Reporting and Data System lexicon independently. Interobserver agreement was assessed, and sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve values for each data set were compared. Pathologic results were reference standards.

RESULTS

The interobserver agreements were excellent (intraclass correlation coefficients, 0.856 for US, 0.948 for elastography, and 0.864 for color Doppler). The specificity and accuracy of US with elastography were increased compared with US alone or US with Doppler imaging without statistically significant differences in sensitivity. The average area under the curve for US with elastography (0.869) was increased compared with US alone (0.650) or US with color Doppler (0.576).

CONCLUSIONS

Elastography is more useful than color Doppler imaging for distinguishing small, oval, or round triple-negative breast cancer from fibroadenoma, and elastography can help avoid biopsy of benign masses.

Imaging Phenotypes in Women at High Risk for Breast Cancer on Mammography, Ultrasound, and Magnetic Resonance Imaging Using the Fifth Edition of the Breast Imaging Reporting and Data System

OBJECTIVE

To assess imaging phenotypes of familial breast cancer on mammography (MG), ultrasound (US), and magnetic resonance imaging (MRI) using the fifth edition of the BI-RADS; to investigate inter-observer agreement and to correlate imaging phenotypes with risk status, histopathology, and molecular subtypes derived by immunohistochemical surrogate.

MATERIALS AND METHODS

Forty-nine women (BRCA-1/2 mutation carriers and women with >20% lifetime risk) were diagnosed with breast cancer within our high-risk screening program. BI-RADS MG, US, and MRI imaging descriptors were correlated with risk status, histopathology, and molecular subtypes derived by immunohistochemical surrogate. Inter-rater agreement for BI-RADS MG, US, and MRI categories was assessed.

RESULTS

Fifty-two breast cancers were diagnosed and 98% were detectable in at least one modality. MRI detected more cancers (P < 0.001). No lesion had benign morphology on BI-RADS. BRCA-1 had triple-negative and high-grade tumors in the posterior part and in the upper-outer quadrant (P ≤ 0.01); positive-family-history patients had intermediate-grade neoplasms (P < 0.01) in the middle part (P = 0.04) and in the upper-outer quadrants (P = 0.05). There was moderate inter-rater agreement for the assigned BI-RADS assessment for MG (k = 0.554) and MRI (k = 0.512) and substantial inter-rater agreement for US (k = 0.741).

CONCLUSIONS

Imaging phenotypes of familial breast cancers with BI-RADS are malignant in all imaging modalities. Risk status seems to influence cancer location.

Intrinsic Subtypes of Breast Cancers Initially Assessed as Probably Benign or of Low Suspicion on Ultrasonography Differ According to Tumor Size

OBJECTIVES

To investigate whether the intrinsic subtypes of breast cancers initially assessed as American College of Radiology Breast Imaging and Reporting System (BI-RADS) category 3 or 4a differ according to tumor size.

METHODS

A total of 444 breast cancers in 439 patients initially assessed as BI-RADS 3 or 4a through ultrasound-guided core needle biopsy were included. Tumors were classified by the size criterion of 10 mm or smaller or larger than 10 mm and categorized as the luminal type (estrogen receptor [ER] positive and/or progesterone receptor [PR] positive and human epidermal growth factor receptor 2 [HER2] negative), HER2 type (HER2 positive regardless of ER or PR status), or triple-negative type (ER negative, PR negative, and HER2 negative). The relationships between tumor size and breast cancer intrinsic subtypes were analyzed.

RESULTS

A total of 247 (55.6%) cancers were 10 mm or smaller, and 197 (44.4%) were larger than 10 mm. The luminal type was more frequently present in tumors of 10 mm or smaller (185 of 247 [74.9%]) than those larger than 10 mm (112 of 197 [56.9%]; P < .001). No significant difference was noted in the frequency of the HER2 type in tumors of 10 and mm smaller and those larger than 10 mm (27 of 247 [10.9%] versus 36 of 197 [18.3%]; P = .084). The triple-negative type was more frequently present in tumors larger than 10 mm than those of 10 mm or smaller (49 of /197 [24.9%] versus 35 of 247 [14.2%]; P = .012).

CONCLUSIONS

Breast cancers assessed as BI-RADS category 3 or 4a had differing intrinsic subtypes according to tumor size, as the luminal type was more frequently present in tumors of 10 mm or smaller than those larger than 10 mm, whereas the triple-negative type was more frequently present in tumors larger than 10 mm.

Sonographic features that can be used to differentiate between small triple-negative breast cancer and fibroadenoma

PURPOSE

Our study investigated whether any sonographic findings could be useful for differentiating between small triple-negative breast cancer (TNBC) and fibroadenoma.

METHODS

This retrospective study was approved by our Institutional Review Board, which waived the requirement for patient consent. From January 2009 to December 2010, the sonographic features of 181 pathologically proven TNBC tumors and 172 fibroadenomas measuring less than or equal to 2 cm in the longest dimension were reviewed and analyzed according to the fifth edition of the Breast Imaging Reporting and Data System (BI-RADS) lexicon. Mean tumor roundness was also measured using in-house software.

RESULTS

The median longest lesion dimension was 16 mm (range, 13 to 18 mm) in TNBCs and 13 mm (range, 10 to 16 mm) in fibroadenomas. In comparison to fibroadenomas, small TNBC tumors presented with a higher incidence of irregular shapes (66.9%), noncircumscribed margins (91.7%), hypoechoic echotexture (59.1%), posterior acoustic enhancement (65.2%), and associated features (24.4%). Most TNBCs were classified as BI-RADS category 4 (65.2%) or 5 (28.2%). The mean tumor roundness of small TNBCs was greater than that of fibroadenomas (60%±12% vs. 53%±13%). Multivariate analysis showed that older patient age, irregular shape, nonparallel orientation, posterior acoustic enhancement, associated features, a BI-RADS final assessment category of 4 or 5, and greater tumor roundness were significant independent factors indicative of TNBCs.

CONCLUSION

TNBC tumors tend to demonstrate more suspicious sonographic features and greater tumor roundness than fibroadenomas. These features may have the potential to help differentiate between small TNBCs and fibroadenomas.

Correlation Factors Analysis of Breast Cancer Tumor Volume Doubling Time Measured by 3D-Ultrasound

BACKGROUND Tumor volume doubling time (TVDT) is relatively important for breast cancer diagnosis and prognosis evaluation. This study aimed to analyze the related factors that may affect the TVDT of breast cancer by three-dimensional ultrasound (3D-US). MATERIAL AND METHODS A total of 69 breast cancer patients were selected. 3D-US was applied to measure the volume of breast lumps diagnosed as BI-RADS-US 4A by conventional ultrasound. TVDT was calculated according to the formula TVDT=DT×log2/log(V2/V1). Multiple linear regression analysis was performed to analyze the factors influencing breast cancer TVDT. RESULTS The mean and median TVDT were 185±126 (range 66-521) and 164 days, respectively. TVDT showed no statistical significance according to regular shape, coarse margin, spicule sign, peripheral hyperechoic halo, microcalcification, and different posterior echo characteristics (P>0.05). Patients grouped by age, axillary lymphatic metastasis, histological differentiation, and Nottingham prognostic index (NPI) score exhibited significantly different TVDT (P<0.05). On the contrary, patients with different menstrual conditions, breast cancer family history, or pathological types presented similar TVDT (P>0.05). TVDT was obviously different in breast cancer with different ER, PR, Ki-67, and molecular subtyping but not HER2 expression. Multivariate analysis revealed that NPI score, axillary lymphatic metastasis, Ki-67, and molecular subtyping were risk factors of TVDT in breast cancer (P<0.05). CONCLUSIONS Breast cancer TVDT was significantly correlated with NPI score, axillary lymphatic metastasis, Ki-67, and molecular subtyping. Triple-negative breast cancer exhibited the most rapid growth.

Dihydroorotate dehydrogenase (DHODH) inhibitors affect ATP depletion, endogenous ROS and mediate S-phase arrest in breast cancer cells

Dihydroorotate dehydrogenase (DHODH) is the key enzyme in de novo biosynthesis of pyrimidine in both prokaryotes and eukaryotes. The de novo pathway of pyrimidine biosynthesis is essential in cancer cells proliferation. Leflunomide is an approved DHODH inhibitor that has been widely used for the treatment of arthritis. Similarly, brequinar sodium is another DHODH inhibitor that showed anti-tumour effect in MC38 colon carcinoma cells when used in combination with fluorouracil. Despite the potential role of DHODH inhibitors in cancer therapy, their mechanisms of action remain obscure and await further elucidation. Here, we evaluated the effect of DHODH inhibitors on the production of ATP and ROS in sensitive and non-sensitive breast cancer cells. Subsequently, the effects of DHODH inhibitors on cell cycle as well as on signalling molecules such as p53, p65 and STAT6 were evaluated in sensitive T-47D and non-sensitive MDAMB-436 cells. The correlations between DHODH protein expression, proliferation speed and sensitivity to DHODH inhibitors were also investigated in a panel of cancer cell lines. DHODH inhibitors-sensitive T-47D and MDAMB-231 cells appeared to preserve ROS production closely to endogenous ROS level whereas the opposite was observed in non-sensitive MDAMB-436 and W3.006 cells. In addition, we observed approximately 90% of intracellular ATP depletion in highly sensitive T-47D and MDAMB-231 cells compared to non-sensitive MDAMB-436 cells. There was significant over-expression of p53, p65 and STAT6 signalling molecules in sensitive cells which may be involved in mediating the S-phase arrest in cell cycle progression. The current study suggests that DHODH inhibitors are most effective in cells that express high levels of DHODH enzyme. The inhibition of cell proliferation by these inhibitors appears to be accompanied by ROS production as well as ATP depletion. The increase in expression of signalling molecules observed may be due to pyrimidine depletion which subsequently leads to cell cycle arrest at S-phase.

Cancer Measurement at Ultrasound: State of the Art

Reliable and reproducible tumor measurement is fundamental in the oncologic decision making. In this article, we first highlight the importance of a precise tumor measurement, reviewing the correct modality of measuring tumor lesions at ultrasound. Then we analyze the measurement discrepancies between ultrasound and pathology as well as the discrepancies reported between ultrasound and other imaging modalities. Thereafter, basing on the existent literature and on our experience, we discuss the factors influencing the tumor size measurements at ultrasound. Finally, we illustrate the current strategies to improve the effectiveness of cancer lesions measurement.

Pattern of metastatic spread and subcategories of breast cancer

PURPOSE

The development of metastases is the most aggressive attribute of breast cancer. In this retrospective multicenter study, we evaluated if and how the different pathological breast cancer subtypes influence the spreading of tumor cells, the development of metastasis and the survival of breast cancer patients.

METHODS

This retrospective German multicenter study is based on the BRENDA collective including 9625 breast cancer patients treated in the adjuvant setting. We used the χ ² tests for the analysis of the categorical variables between groups of patients with different sites of metastasis. Survival distributions and median survival times were estimated using the Kaplan-Meier product-limit method. The log-rank test was applied to compare survival rates. The Cox proportional hazards model was used to estimate the hazard ratio and confidence intervals.

RESULTS

886 women developed metastases during a time interval of 53 months after primary diagnosis. Luminal A tumor patients were more likely to get bone metastases than lung, liver or CNS metastases. Patients with a triple-negative subtype were, however, the least affected by metastasis in the skeleton. They were most likely to develop visceral metastases. Location, numbers of metastases herein and the subtype influenced the overall survival (OAS). Altogether, the best OAS was found in patients with the luminal A subtype, the worst in patients with the triple-negative subtype.

CONCLUSIONS

Knowledge of the typical metastatic pattern of the subtypes of breast cancer will help to personalize therapeutic options and follow-up examinations of cancer patients.

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.