Quantitative analysis of tumor growth rate and changes in tumor marker level: specific growth rate versus doubling time

Tumor and Nodal Disease Growth Rates in Patients with Oropharyngeal Squamous Cell Carcinoma

Though specific growth rate (SGR) has potential prognostic value for oropharyngeal squamous cell carcinoma (OPSCC), there is sparse literature defining these rates. Our aims were to establish the SGRs of primary tumors (PTs) and lymph nodes (LNs) in OPSCC and to correlate SGR with oncologic outcome. A pilot study was designed with a retrospective analysis examining 54 patients from the University of California, Davis with OPSCC (diagnosed 2012-2019). Radiation oncology software and pretreatment serial CT scans were used to measure PT and LN volumes to calculate SGR and doubling time (DT). The mean PT-SGR was 1.2 ± 2.2%/day and the mean LN-SGR was 1.6 ± 1.9%/day. There was no statistically significant difference between slow-growing and fast-growing cohorts in terms of age, gender, smoking status, tumor subsite, HPV status (as determined with p16 staining), initial volume, or overall stage. SGR had no impact on 2-year overall survival, disease-free survival, or disease-specific survival. We found the average daily growth rates for OPSCC to be 1.2%/day and 1.6%/day. Our findings suggest PT- and LN-SGR are independent factors, not heavily influenced by known biomarkers and patient characteristics, without a statistical impact on prognosis. This information has value in patient counseling regarding tumor growth and in providing patients worried about fast-growing tumors the appropriate reassurance.

Physics-based tissue simulator to model multicellular systems: A study of liver regeneration and hepatocellular carcinoma recurrence

We present a multiagent-based model that captures the interactions between different types of cells with their microenvironment, and enables the analysis of the emergent global behavior during tissue regeneration and tumor development. Using this model, we are able to reproduce the temporal dynamics of regular healthy cells and cancer cells, as well as the evolution of their three-dimensional spatial distributions. By tuning the system with the characteristics of the individual patients, our model reproduces a variety of spatial patterns of tissue regeneration and tumor growth, resembling those found in clinical imaging or biopsies. In order to calibrate and validate our model we study the process of liver regeneration after surgical hepatectomy in different degrees. In the clinical context, our model is able to predict the recurrence of a hepatocellular carcinoma after a 70% partial hepatectomy. The outcomes of our simulations are in agreement with experimental and clinical observations. By fitting the model parameters to specific patient factors, it might well become a useful platform for hypotheses testing in treatments protocols.

Cabozantinib sensitizes microsatellite stable colorectal cancer to immune checkpoint blockade by immune modulation in human immune system mouse models

Immune checkpoint inhibitors have been found to be effective in metastatic MSI-high colorectal cancers (CRC), however, have no efficacy in microsatellite stable (MSS) cancers, which comprise the majority of mCRC cases. Cabozantinib is a small molecule multi-tyrosine kinase inhibitor that is FDA approved in advanced renal cell, medullary thyroid, and hepatocellular carcinoma. Using Human Immune System (HIS) mice, we tested the ability of cabozantinib to prime MSS-CRC tumors to enhance the potency of immune checkpoint inhibitor nivolumab. In four independent experiments, we implanted distinct MSS-CRC patient-derived xenografts (PDXs) into the flanks of humanized BALB/c-Rag2nullIl2rγnullSirpαNOD (BRGS) mice that had been engrafted with human hematopoietic stem cells at birth. For each PDX, HIS-mice cohorts were treated with vehicle, nivolumab, cabozantinib, or the combination. In three out of the four models, the combination had a lower tumor growth rate compared to vehicle or nivolumab-treated groups. Furthermore, interrogation of the HIS in immune organs and tumors by flow cytometry revealed increased Granzyme B+, TNFα+ and IFNγ+ CD4+ T cells among the human tumor infiltrating leukocytes (TIL) that correlated with reduced tumor growth in the combination-treated HIS-mice. Notably, slower growth correlated with increased expression of the CD4+ T cell ligand, HLA-DR, on the tumor cells themselves. Finally, the cabozantinib/nivolumab combination was tested in comparison to cobimetinib/atezolizumab. Although both combinations showed tumor growth inhibition, cabozantinib/nivolumab had enhanced cytotoxic IFNγ and TNFα+ T cells. This pre-clinical in vivo data warrants testing the combination in clinical trials for patients with MSS-CRC.

Deep learning models for benign and malign ocular tumor growth estimation

Relatively abundant availability of medical imaging data has provided significant support in the development and testing of Neural Network based image processing methods. Clinicians often face issues in selecting suitable image processing algorithm for medical imaging data. A strategy for the selection of a proper model is presented here. The training data set comprises optical coherence tomography (OCT) and angiography (OCT-A) images of 50 mice eyes with more than 100 days follow-up. The data contains images from treated and untreated mouse eyes. Four deep learning variants are tested for automatic (a) differentiation of tumor region with healthy retinal layer and (b) segmentation of 3D ocular tumor volumes. Exhaustive sensitivity analysis of deep learning models is performed with respect to the number of training and testing images using eight performance indices to study accuracy, reliability/reproducibility, and speed. U-net with UVgg16 is best for malign tumor data set with treatment (having considerable variation) and U-net with Inception backbone for benign tumor data (with minor variation). Loss value and root mean square error (R.M.S.E.) are found most and least sensitive performance indices, respectively. The performance (via indices) is found to be exponentially improving regarding a number of training images. The segmented OCT-Angiography data shows that neovascularization drives the tumor volume. Image analysis shows that photodynamic imaging-assisted tumor treatment protocol is transforming an aggressively growing tumor into a cyst. An empirical expression is obtained to help medical professionals choose a particular model given the number of images and types of characteristics. We recommend that the presented exercise should be taken as standard practice before employing a particular deep learning model for biomedical image analysis.

Nanocrystal-loaded liposome for targeted delivery of poorly water-soluble antitumor drugs with high drug loading and stability towards efficient cancer therapy

Nanocrystals (NCs) enable the delivery of poorly water-soluble drugs with improved dissolution and bioavailability. However, their uncontrolled release and instability make targeted delivery challenging. Herein, a nano-in-nano delivery system composed of a drug nanocrystal core and liposome shell (NC@Lipo) is presented, which merges the advantages of drug nanocrystals (high drug loading) and liposomes (easy surface functionalization and high stability) for targeted delivery of hydrophobic drugs to tumors. CHMFL-ABL-053 (053), a hydrophobic drug candidate discovered by our group, was employed as a model drug to demonstrate the performance of NC@Lipo delivery system. Surface PEGylated (053-NC@PEG-Lipo) and folic acid-functionalized (053-NC@FA-Lipo) formulations were fabricated by wet ball milling combined with probe sonication. 053-NC@Lipo enabled high drug loading (up to 19.51%), considerably better colloidal stability, and longer circulation in vivo than 053-NC. Compared with free 053, 053-NC@PEG-Lipo and 053-NC@FA-Lipo exhibited higher tumor accumulation and considerably better in vivo antitumor efficacy in K562 xenograft mice with tumor growth inhibition rate (TGI) of up to 98%. Additionally, more effective tumor cell targeting in vitro and higher TGI in vivo were achieved with 053-NC@FA-Lipo. The NC@Lipo strategy may contribute to the targeted delivery of poorly water-soluble drugs with high drug loading, high stability, and tailorable surface, and has potential for the development of more efficient nanocrystal- and liposome-based formulations for commercial and clinical applications. It may also provide new opportunities for potential clinical application of candidate 053.

Temporal regulation of tumor growth in nocturnal mammals: In vivo studies and chemotherapeutical potential

Tumors of the nervous system including glioblastoma multiforme (GBM) are the most frequent and aggressive form of brain tumors; however, little is known about the impact of the circadian timing system on the formation, growth, and treatment of these tumors. We investigated day/night differences in tumor growth after injection of A530 glioma cells isolated from malignant peripheral nerve sheath tumor (MPNSTs) of NPcis (Trp53+/- ; Nf1+/- ) mice. Synchronized A530 cell cultures expressing typical glial markers were injected at the beginning of the day or night into the sciatic nerve zone of C57BL/6 mice subject to a 12:12 hours light/dark (LD) cycle or after being released to constant darkness (DD). Tumors generated in animals injected early at night in the LD cycle or in DD showed higher growth rates than in animals injected diurnally. No differences were found when animals were injected at the same time with cultures synchronized 12 hours apart. Similar experiments performed with B16 melanoma cells showed higher tumor growth rates in animals injected at the beginning of the night compared to those injected in the daytime. A higher tumor growth rate than that in controls was observed when mice were injected with knocked-down clock gene Bmal1 cells. Finally, when we compared day/night administration of different doses of the proteasome inhibitor Bortezomib (0.5-1.5 mg/kg) in tumor-bearing animals, we found that low-dose chemotherapy displayed higher efficacy when administered at night. Results suggest the existence of a precise temporal control of tumor growth and of drug efficacy in which the host state and susceptibility are critical.

Tumor growth kinetics by CA 19-9 in patients with unresectable pancreatic cancer receiving chemotherapy: A retrospective analysis

BACKGROUND

Recently, measures of tumor growth kinetics calculated by carbohydrate antigen 19-9 (CA 19-9) determinations after cytotoxic chemotherapy (CHT) have been reported as effective prognostic indicators in locally-advanced unresectable and metastatic pancreatic adenocarcinoma (mPDAC). The study aims to evaluate the prognostic role of tumor kinetics measured by CA 19-9 in patients with mPDAC, measuring it by three different ways.

METHODS

Patients with mPDAC receiving a first-line CHT between 2009 and 2017 were identified, and those for whom CA 19-9 data were available were enrolled. Three CA 19-9-related variables were calculated: CA 19-9 related reduction rate (RR) and tumor growth rate (G), after 8 weeks of CHT, tumor growth and inflammation index (TGII), after 90 days of CHT. The relationships with the outcome were analysed, and a Cox model has been build with each of the three variables.

RESULTS

Of 118 patients only 48 were eligible for the analysis. RR, G, or TGII appear as significant prognostic factors, and, after multivariate analysis, a reduction rate of 20% the baseline or more was associated with good survival (HR 0.321; CIs 0.156-0.661) as well as a G > -0.4%/day (HR 2.114; CIs 1.034-4.321), whereas TGII >190 was not correlated with the outcome (HR 1.788; CIs 0.789-4.055).

CONCLUSIONS

In patients with mPDAC, after 8 weeks of first-line CHT, CA 19-9-related tumor reduction or growth rate appear as valuable prognostic factors.

Neutrophil count kinetics during the first cycle of chemotherapy predicts the outcome of patients with locally advanced or metastatic pancreatic cancer

BACKGROUND

Neutrophil count reduction after chemotherapy has been related with longer survival of patients with metastatic pancreatic adenocarcinoma, but there is not a standardized measurement for this phenomenon.

METHODS

Some parameters related to the change in neutrophil count between the first and the second cycle of chemotherapy or between the baseline count and the nadir have been evaluated among patients with advanced pancreatic cancer at a single institution. A Cox regression model was built which included, in addition to the common prognostic variables, some variables related to the change of the neutrophil count after chemotherapy.

RESULTS

One hundred patients were selected. Two neutrophil kinetics related variables predicted overall survival independently, such as the neutrophil count growth rate (hazard ratio [HR] = 1.245; confidence intervals [CIs], 1.077-1.440) and the chemotherapy-induced neutropenia after one cycle (HR = 0.499; CIs, 0.269-0.927).

CONCLUSION

The kinetics of neutrophil count after chemotherapy is an early and independent prognostic factor, which appears to be simple to measure at the start of the second cycle of chemotherapy by means of the neutrophil count growth rate.

Impact of primary tumor-specific growth rate on treatment failure for nonoropharyngeal head and neck cancers

OBJECTIVES

To investigate the prognostic impact of primary tumor-specific growth rate (TSGR) on treatment outcomes after definitive radiation therapy (RT) for nonoropharyngeal squamous cell carcinoma (non-OPSCC).

METHODS

The diagnostic tumor and nodal volumes of 39 non-OPSCC patients were contoured and compared to corresponding RT planning scan volumes to determine TSGR. Overall survival (OS), disease-free survival (DFS), and local recurrence-free survival were evaluated according to the Kaplan-Meier method; and hazard ratios (HR) were estimated using Cox regression. Based on the 75th percentile TSGR of 2.18%, we stratified patients into a high TSGR group (≥ 2.18% per day) and low TSGR group (< 2.18% per day).

RESULTS

The median follow-up was 22 months (range: 1-86 months) and median time between diagnostic and simulation computed tomography scans was 22 days (range: 7-170 days). Median RT dose was 70 Gy (range: 60-79.2 Gy). Based on the 75th percentile TSGR, OS at median follow-up was 50.0% for the high TSGR group compared to 92.5% for the low TSGR group (HR [95% confidence interval (CI)] = 2.12[1.16-11.42], P = 0.018). There was a trend toward worse DFS at median follow-up for the high versus low TSGR groups, at 55.6% and 82.3%, respectively (HR [95% CI] = 2.29[0.82-6.38], P = 0.103).

CONCLUSION

Our study contributes to growing literature on TSGR as a temporal biomarker in patients with non-OPSCC. Patients with high TSGR ≥2.18% per day have significantly worse OS compared to those with TSGR below this threshold. Efforts to address treatment initiation delays may benefit patients with particularly aggressive and rapidly growing tumors.

LEVEL OF EVIDENCE

4 Laryngoscope, 130:2378-2384, 2020.

Clinical significance of pretreatment tumor growth rate for locally advanced non-small cell lung cancer

Background

Locally advanced non-small cell lung cancer (NSCLC) may exhibit significant tumor growth before the initiation of definitive chemoradiation therapy (CRT). We thus investigated the prognostic value of pretreatment tumor growth rate as measured by specific growth rate (SGR).

Methods

We conducted a retrospective review of 42 patients with locally advanced NSCLC treated with definitive concurrent CRT. For each patient, we contoured the primary gross tumor volume (GTV) on the pretreatment diagnostic chest computed tomography (CT) scan and the radiation therapy (RT) planning CT scan. We then calculated SGR based on the primary GTV from each scan and the time interval between scans. We used log-rank tests and univariate Cox regression models to quantify differences in progression-free survival (PFS), overall survival (OS) and recurrence based on SGR.

Results

We divided patients into two groups for analysis: those with an SGR greater than or equal to the upper tercile value of 0.94%/day (high SGR) and those with SGR less than 0.94%/day (low SGR). Patients with high SGRs versus low SGRs experienced inferior PFS (median, 5.6 vs. 13.6 months, P=0.016), without a significant difference in OS. The inferior PFS in the high SGR group persisted on multivariate analysis [adjusted hazard ratio (HR) 2.37, 95% confidence interval (CI): 1.07-5.25, P=0.034]. The risk of distant recurrence was higher in the high SGR group (HR 2.62, 95% CI: 1.08-6.38, P=0.033), but there was no difference in the risk of locoregional recurrence between groups.

Conclusions

Pretreatment SGR was associated with inferior PFS and distant control among patients with locally advanced NSCLC treated with concurrent CRT. Further studies in larger populations may aid in elucidating optimal SGR cut-off points for risk stratification.

Specific growth rates calculated from CTs in patients with head and neck squamous cell carcinoma: a retrospective study performed in Austria

OBJECTIVE

To provide data on specific growth rates (SGRs) of primary tumours (PT-SGR) and largest pathological cervical lymph nodes (LN-SGR) for head and neck squamous cell carcinoma (HNSCC). To explore PT-SGR's and LN-SGR's correlation with selected biomarkers epidermal growth factor receptor (EGFR), Ki67 and CD44.

DESIGN AND SETTING

Retrospective study performed at a tertiary oncological referral centre in Innsbruck, Austria.

PARTICIPANTS

Adult patients with incident HNSCC treated with primary radiotherapy (RT) or radiochemotherapy (RCT).

OUTCOME MEASURES

Volumes of the primary tumour (PT-volume) and largest pathological cervical lymph node (LN-volume) were measured in CT scans obtained at time of diagnosis and subsequent planning CTs immediately prior to RT or RCT. SGRs were calculated assuming an exponential growth function. PT-SGR's and LN-SGR's correlation with EGFR, Ki67 and CD44 were explored.

RESULTS

In 123 patients, mean interval between diagnostic and planning CT was 29±21 days. PT-SGR was 1.8±1.8% (mean±SD) per day and was positively correlated with EGFR, Ki67 and CD44 expression (p=0.02; p=0.02; p=0.03). LN-SGR was 1.7±2.0% per day and increased with larger initial LN-volume, was lower in laryngeal cancer (p=0.003) and slowed down with time. LN-SGR was not correlated with EGFR, Ki67 or CD44 expression in primary tumours (p>0.12). New cartilage or bone infiltration occurred in 10 patients and new central lymph node necrosis in 8 patients.

CONCLUSIONS

HNSCCs are fast-growing tumours for which treatment must not be delayed. Clinical tumour growth rates are influences by EGFR, KI67 and CD44 expression.

Volumetric trends of progressive in-field recurrences after stereotactic radiosurgery of metastatic intracranial tumors

OBJECTIVE

Local recurrence after stereotactic radiosurgery for brain metastasis is a well-known problem. We analyzed volumetric trends from the time of radiosurgery to time of treatment to understand progression behavior.

METHODS

A retrospective review of patients who underwent treatment for post-radiation progressive lesions was performed. Volumetric trends were obtained by plotting individual lesion volumes from the post-radiation nadir volume to volume at treatment and then fitted to exponential decay or linear regressions.

RESULTS

Twenty-eight post-radiation recurrences demonstrated exponential growth and thirteen followed a linear pattern. For lesions exhibiting exponential growth, the average nadir volume was 0.26cm³ (SEM=0.06) at an average of 298 days before treatment and mean volume at treatment was 2.39cm³ (SEM=0.33). The average adjusted R² was 0.94 (SEM=0.013) and doubling factor was 68.60days (SEM=12.55). In the linear growth cohort, the mean nadir volume was 1.43cm³ (SEM=0.25) at an average of 158 days before treatment and average volume at treatment was 6.90cm³ (SEM=1.43). The mean R² was 0.92 (SEM=0.02) and average growth rate was 0.034cm³/day. Majority of lesions from primary non-small cell lung cancer (81%) and breast cancer (63%) followed exponential growth.

CONCLUSIONS

Exponential and linear regressions are accurate representations of post-radiation progression behavior and may be valuable in understanding the growth patterns for recurrences ultimately requiring treatment.

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.

CA19-9-related tumor kinetics after first-line chemotherapy of patients with advanced pancreatic cancer: a monoinstitutional experience

The absolute value of carbohydrate antigen 19-9 (CA19-9) pretreatment and its reduction after chemotherapy are established prognostic variables for patients with advanced pancreatic cancer. The present study is a retrospective monoinstitutional evaluation of the prognostic role of the CA19-9 reduction and some CA19-9-related tumor kinetics parameters, such as tumor growth rate constant (G), kinetic tumor response and log ratio. Forty-one cases met the selection criteria. After 8 weeks only G reported an inverse relationship with OS (r = -0.494) that was confirmed by regression analysis (R (2) = 0.192). G after 8 weeks of chemotherapy appears as a possible surrogate end point of overall survival.

Tumor Growth Kinetics Before and After First-line Chemotherapy in Metastatic Castration-resistant Prostate Cancer: A Prostate-specific Antigen-based Retrospective Analysis

OBJECTIVES

The role of the tumor growth fraction has been investigated poorly in metastatic castration-resistant prostate cancer (mCRPC). The aim of this study was to assess whether some prostate-specific antigen (PSA)-related variables of tumor cell kinetics predict the overall survival in early and late mCRPC, and to explore changes in the tumor growth fraction after chemotherapy.

METHODS

A retrospective analysis of 3 tumor cell kinetic variables in patients with mCRPC receiving first-line chemotherapy has been performed. The PSA-related tumor growth rate, the log ratio, and the tumor response have been measured at 3 different times. A further analysis has been performed after stratification by the Gleason score and chemotherapy. Finally, tumor growth after progression to chemotherapy has been explored.

RESULTS

G at castration resistance is significantly associated with survival after chemotherapy among patients with a low Gleason score (r=-0.650, P-value=0.022). At the time of first-line chemotherapy, both G and PSA response rates report a significant relationship with survival. At the time of postchemotherapy progression, only the G after 12 weeks of chemotherapy maintains a relationship with survival in patients with a low Gleason score (r=-0.483, P-value=0.023); in particular, a tumor growth rate <-0.5%/day appears to be associated with a poor postprogression survival. Despite the lack of correlation between postprogression G and postprogression survival, the response to chemotherapy defines 2 groups with different growth characteristics.

CONCLUSIONS

Among patients with mCRPC, tumor cell kinetics appears to be able to predict the outcome, especially in tumors with a low Gleason score.

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

OBJECTIVE

The aim of our study was to evaluate the effect of tumor growth rate, calculated from tumor size measurements by US, on breast cancer patients' outcome.

PATIENTS AND METHODS

Breast cancer patients who received at least two serial breast ultrasonographies (US) in our institution during preoperative period and were surgically treated between 2002 and 2010 were reviewed. Tumor growth rate was determined by specific growth rate (SGR) using the two time point tumor sizes by US.

RESULTS

A total of 957 patients were analyzed. The median duration between initial and second US was 28 days (range, 8-140). The median initial tumor size was 1.7 cm (range, 0.4-7.0) and median second size was 1.9 cm (range, 0.3-7.2). 523 (54.6%) cases had increase in size. The median SGR(x10-2) was 0.59 (range, -11.90~31.49) and mean tumor doubling time was 14.51 days. Tumor growth rate was higher when initial tumor size was smaller. Lymphovascular invasion, axillary lymph node metastasis, and higher histologic grade were significantly associated with higher SGR. SGR was significantly associated with disease-free survival (DFS) in a univariate analysis (p = 0.04), but not in a multivariate Cox analysis (p>0.05). High SGR was significantly associated with worse DFS in a subgroup of initial tumor size >2 cm (p = 0.018), but not in those with tumor size <2 cm (p>0.05).

CONCLUSION

Our results showed that tumor growth rate measured by US in a relatively short time interval was associated with other worse prognostic factors and DFS, but it was not an independent prognostic factor in breast cancer patients.

Mammary cancer initiation and progression studied with magnetic resonance imaging

Introduction

Previous work from this laboratory demonstrated that magnetic resonance imaging (MRI) detects early murine mammary cancers and reliably differentiates between in situ and invasive cancer. Based on this previous work, we used MRI to study initiation and progression of murine mammary cancer, and monitor the transition from the in situ to the invasive phase.

Methods

In total, seven female C3(1) SV40 Tag mice were imaged every two weeks between the ages of 8 to 23 weeks. Lesions were identified on T2-weighted images acquired at 9.4 Tesla based on their morphology and growth rates. Lesions were traced manually on MR images of each slice. Volume of each lesion was calculated by adding measurements from individual slices. Plots of lesion volume versus time were analyzed to obtain the specific growth rate (SGR). The time at which in situ cancers (referred to as ‘mammary intraepithelial neoplasia (MIN)’) and invasive cancers were first detected; and the time at which in situ cancers became invasive were recorded.

Results

A total of 121 cancers (14 to 25 per mouse) were identified in seven mice. On average the MIN lesions and invasive cancers were first detected when mice were 13 and 18 weeks old, respectively. The average SGR was 0.47 ± 0.18 week^-1 and there were no differences (P >0.05) between mice. 74 lesions had significantly different tumor growth rates before and after ~17 weeks of age; with average doubling times (DT) of 1.88 and 1.27 weeks, respectively. The average DT was significantly shorter (P <0.0001) after 17 weeks of age. However, the DT for some cancers was longer after 17 weeks of age, and about 10% of the cancers detected did not progress to the invasive stage.

Conclusions

A wide range of growth rates were observed in SV40 mammary cancers. Most cancers transitioned to a more aggressive phenotype at approximately 17 weeks of age, but some cancers became less aggressive. The results suggest that the biology of mammary cancers is extremely heterogeneous. This work is a first step towards use of MRI to improve understanding of factors that control and/or signal the development of aggressive breast cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-014-0495-6) contains supplementary material, which is available to authorized users.

Precise engineering of siRNA delivery vehicles to tumors using polyion complexes and gold nanoparticles

For systemic delivery of siRNA to solid tumors, a size-regulated and reversibly stabilized nanoarchitecture was constructed by using a 20 kDa siRNA-loaded unimer polyion complex (uPIC) and 20 nm gold nanoparticle (AuNP). The uPIC was selectively prepared by charge-matched polyionic complexation of a poly(ethylene glycol)-b-poly(L-lysine) (PEG-PLL) copolymer bearing ∼40 positive charges (and thiol group at the ω-end) with a single siRNA bearing 40 negative charges. The thiol group at the ω-end of PEG-PLL further enabled successful conjugation of the uPICs onto the single AuNP through coordinate bonding, generating a nanoarchitecture (uPIC-AuNP) with a size of 38 nm and a narrow size distribution. In contrast, mixing thiolated PEG-PLLs and AuNPs produced a large aggregate in the absence of siRNA, suggesting the essential role of the preformed uPIC in the formation of nanoarchitecture. The smart uPIC-AuNPs were stable in serum-containing media and more resistant against heparin-induced counter polyanion exchange, compared to uPICs alone. On the other hand, the treatment of uPIC-AuNPs with an intracellular concentration of glutathione substantially compromised their stability and triggered the release of siRNA, demonstrating the reversible stability of these nanoarchitectures relative to thiol exchange and negatively charged AuNP surface. The uPIC-AuNPs efficiently delivered siRNA into cultured cancer cells, facilitating significant sequence-specific gene silencing without cytotoxicity. Systemically administered uPIC-AuNPs showed appreciably longer blood circulation time compared to controls, i.e., bare AuNPs and uPICs, indicating that the conjugation of uPICs onto AuNP was crucial for enhancing blood circulation time. Finally, the uPIC-AuNPs efficiently accumulated in a subcutaneously inoculated luciferase-expressing cervical cancer (HeLa-Luc) model and achieved significant luciferase gene silencing in the tumor tissue. These results demonstrate the strong potential of uPIC-AuNP nanoarchitectures for systemic siRNA delivery to solid tumors.

Tumor growth kinetics versus RECIST to assess response to locoregional therapy in breast cancer liver metastases

RATIONALE AND OBJECTIVES

The aim of our study was to evaluate changes in growth kinetics of breast cancer liver metastasis in response to locoregional therapy and compare them to Response Evaluation Criteria in Solid Tumors (RECIST).

MATERIALS AND METHODS

This Health Insurance Portability and Accountability Act-compliant retrospective study was Institutional Review Board approved. Thirty-four chemorefractory breast cancer liver metastases from 21 patients treated with yttrium-90 ((90)Y) were evaluated. Pre- and posttreatment computed tomography (CT) scans were used to calculate tumor growth kinetics. The growth parameter analyzed was reciprocal of doubling time (RDT). RDT range for stable disease (SD) was defined by the measurement error rate. A negative RDT below the SD range defined response and was categorized as either partial response (PR) or complete response, whereas a positive RDT value above the SD range indicated progressive disease (PD). Comparison was made to tumor response classification according to percentage change in the lesion's maximal diameter per RECIST. Lin's concordance correlation coefficient, Bland-Altman plot, Wilcoxon signed rank test, and Student t test were used for analysis. Significance was set at 0.05.

RESULTS

RDT range for SD ranged from -0.46 to +2.17. Six lesions with PR based on RECIST showed PR based on their volumetric growth rate (mean RDT of -17.3 ± 2.6). Similarly, one lesion with PD according to RECIST was categorized as PD based on its growth kinetics (RDT of 10.2). However, 14 (51.85%) lesions classified as SD by RECIST had PR according to growth kinetics (mean RDT of -7.8), six (22.22%) lesions were categorized as SD (mean RDT of 0.8), whereas seven (25.93%) lesions showed PD (mean RDT of 4.5). Growth kinetic parameters were significantly different for lesions with PR when compared to lesions with PD (P < .0001).

CONCLUSIONS

In patients with breast cancer liver metastases undergoing locoregional therapy, RECIST categorization may not be an accurate reflection of treatment response.

Impact of pretreatment tumor growth rate on outcome of early-stage lung cancer treated with stereotactic body radiation therapy

PURPOSE

To determine the influence of pretreatment tumor growth rate on outcomes in patients with early-stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT).

METHODS AND MATERIALS

A review was conducted on 160 patients with T1-T2N0M0 NSCLC treated with SBRT at single institution. The patient's demographic and clinical data, time interval (t) between diagnostic and planning computed tomography (CT), vital status, disease status, and cause of death were extracted from a prospectively kept database. Differences in gross tumor volume between diagnostic CT (GTV1) and planning CT (GTV2) were recorded, and growth rate was calculated by use of specific growth rate (SGR). Kaplan-Meier curves were constructed for overall survival (OS). Differences between groups were compared with a log-rank test. Multivariate analyses were performed by use of the Cox proportional hazard model with SGR and other relevant clinical factors. Cumulative incidence was calculated for local, regional, and distant failures by use of the competing risk approach and was compared with Gray's test.

RESULTS

The median time interval between diagnostic and planning CT was 82 days. The patients were divided into 2 groups, and the median SGR was used as a cut-off. The median survival times were 38.6 and 27.7 months for the low and high SGR groups, respectively (P=.03). Eastern Cooperative Oncology Group performance status (P=.01), sex (P=.04), SGR (P=.03), and GTV2 (P=.002) were predictive for OS in multivariable Cox regression analysis and, except sex, were similarly predictive for failure-free survival (FFS). The 3-year cumulative incidences of regional failure were 19.2% and 6.0% for the high and low SGR groups, respectively (P=.047).

CONCLUSION

High SGR was correlated with both poorer OS and FFS in patients with early-stage NSCLC treated with SBRT. If validated, this measurement may be useful in identifying patients most likely to benefit from adjuvant therapy after SBRT.

Analysis of inter-patient variations in tumour growth rate

Purpose

Inter-patient variations in tumour growth rate are usually interpreted as biological heterogeneity among patients due to, e.g., genetic variability. However, these variations might be a result of non-exponential, e.g. the Gompertzian, tumour growth kinetics. The aim was to study if the natural tumour growth deceleration, i.e. non-exponential growth, is a dominant factor in such variations.

Materials and methods

The correlation between specific growth rate (SGR) and the logarithm of tumour volume, Ln(V), was calculated for tumours in patients with meningioma, hepatocellular carcinoma, pancreatic carcinoma, primary lung cancer, post-chemotherapy regrowth of non-small cell lung cancer (NSCLC), and in nude mice transplanted with human midgut carcinoid GOT1, a tumour group which is biologically more homogeneous than patient groups.

Results

The correlation between SGR and Ln(V) was statistically significant for meningioma, post-chemotherapy regrowth of NSCLC, and the mouse model, but not for any other patient groups or subgroups, based on differentiation and clinical stage.

Conclusion

This method can be used to evaluate the homogeneity of tumour growth kinetics among patients. Homogeneity of post-chemotherapy regrowth pattern of NSCLC suggests that, in contrast to untreated tumours, the remaining resistant cells or stem cells (if exist) might have similar biological characteristics among these patients.

A new method to estimate parameters of the growth model for metastatic tumours

Purpose

Knowledge of natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal scheduling of chemotherapy, and assessing tumour spread. However, mathematical modelling in individuals is hampered by the limited data available. We aimed to develop a method to estimate parameters of the growth model and formation rate of metastases in individual patients.

Materials and methods

Data from one patient with liver metastases from a primary ileum carcinoid and one patient with lung metastases from a primary renal cell carcinoma were used to demonstrate this new method. Metastatic growth models were estimated by direct curve fitting, as well as with the new proposed method based on the relationship between tumour growth rate and tumour volume. The new model was derived from the Gompertzian growth model by eliminating the time factor (age of metastases), which made it possible to perform the calculations using data from all metastases in each patient. Finally, the formation time of each metastasis and, consecutively, the formation rate of metastases in each patient were estimated.

Results

With limited measurements in clinical studies, fitting different growth curves was insufficient to estimate true tumour growth, even if patients were followed for several years. Growth of liver metastases was well described with a general growth model for all metastases. However, the lung metastases from renal cell carcinoma were better described by heterogeneous exponential growth with various growth rates.

Conclusion

Analysis of the regression of tumour growth rate with the logarithm of tumour volume can be used to estimate parameters of the tumour growth model and metastasis formation rates, and therefore the number and size distribution of metastases in individuals.

Selection of Mesenchymal-Like Metastatic Cells in Primary Tumors - An in silico Investigation

In order to metastasize, cancer cells must undergo phenotypic transition from an anchorage-dependent form to a motile form via a process referred to as epithelial to mesenchymal transition. It is currently unclear whether metastatic cells emerge late during tumor progression by successive accumulation of mutations, or whether they derive from distinct cell populations already present during the early stages of tumorigenesis. Similarly, the selective pressures that drive metastasis are poorly understood. Selection of cancer cells with increased proliferative capacity and enhanced survival characteristics may explain how some transformations promote a metastatic phenotype. However, it is difficult to explain how cancer cells that disseminate can emerge due to such selective pressure, since these cells usually remain dormant for prolonged periods of time. In the current study, we have used in silico modeling and simulation to investigate the hypothesis that mesenchymal-like cancer cells evolve during the early stages of primary tumor development, and that these cells exhibit survival and proliferative advantages within the tumor microenvironment. In an agent-based tumor microenvironment model, cancer cell agents with distinct sets of attributes governing nutrient consumption, proliferation, apoptosis, random motility, and cell adhesion were allowed to compete for space and nutrients. These simulation data indicated that mesenchymal-like cancer cells displaying high motility and low adhesion proliferate more rapidly and display a survival advantage over epithelial-like cancer cells. Furthermore, the presence of mesenchymal-like cells within the primary tumor influences the macroscopic properties, emergent morphology, and growth rate of tumors.

MDCT evaluation of the growth kinetics of serous and benign mucinous cystic neoplasms of the pancreas

We assessed the growth kinetics of pathologically proven benign neoplastic cystic lesions of the pancreas. The volume and longest axial diameter (LAD) of 20 pathologically proven pancreatic cystic lesions (12 mucinous cystic neoplasms (MCN) and 8 serous cystadenomas (SCN)) on 2 multidetector computed tomography scans, obtained before resection, were measured. Reciprocal of doubling time, doubling time and growth rate based on volume and LAD were calculated. A P value <0.05 was considered significant. For all cysts, growth kinetics based on volume were: reciprocal of doubling time (mean = 3.03, median=1.0), doubling time (mean = 644, median = 388 days) and growth rate (mean = 74.7, median = 5.7 ml/year). Results based on LAD were: reciprocal of doubling time (mean = 3.09, median = 1.3), doubling time (mean = 752, median = 273 days) and growth rate (mean = 24.5, median = 5.6 mm/year). These variables were not statistically different between MCNs and SCNs (P > 0.05 in all instances). Reciprocal of doubling time based on volume and LAD were comparable (P > 0.05). We concluded that the mean reciprocal of doubling time was 3.03 and 3.09 using volume and LAD, respectively. This may aid in designing follow-up guidelines for pancreatic cysts.

Objective assessment of tumour response to therapy based on tumour growth kinetics

Background:

Current standards for assessment of tumour response to therapy (a) categorise therapeutic efficacy values, inappropriate for patient-specific and deterministic studies, (b) neglect the natural growth characteristics of tumours, (c) are based on tumour shrinkage, inappropriate for cytostatic therapies, and (d) do not accommodate integration of functional/biological means of therapeutic efficacy assessed with, for example, positron emission tomography or magnetic resonance imaging, with data from anatomical changes in tumour.

Methods:

A quantity for tumour response was formulated assuming that an effective treatment may decrease the cell proliferation rate (cytostatic) and/or increase the cell loss rate (cytotoxic) of the tumour. Tumour response values were analysed for 11 non-Hodgkin's lymphoma patients treated with ¹³¹I-labelled anti-B1 antibody and 12 prostate cancer patients treated with a nutritional supplement.

Results:

Tumour response was found to be equal to the logarithm of the ratio of post-treatment tumour volume to the volume of corresponding untreated tumour. Neglecting the natural growth characteristics of tumours results in underestimation of treatment effectiveness based on currently used methods. The model also facilitates the integration of data from tumour volume changes, with data from functional imaging.

Conclusion:

Tumour response to therapy can be assessed with a continuous dimensionless quantity for both cytotoxic and cytostatic treatments.