Pharmacologic and genetic inhibition of cholesterol esterification enzymes reduces tumour burden: A systematic review and meta-analysis of preclinical models.

Cholesterol esterification proteins Sterol-O acyltransferases (SOAT) 1 and 2 are emerging prognostic markers in many cancers. These enzymes utilise fatty acids conjugated to coenzyme A to esterify cholesterol. Cholesterol esterification is tightly regulated and enables formation of lipid droplets that act as storage organelles for lipid soluble vitamins and minerals, and as cholesterol reservoirs. In cancer, this provides rapid access to cholesterol to maintain continual synthesis of the plasma membrane. In this systematic review and meta-analysis, we summarise the current depth of understanding of the role of this metabolic pathway in pan-cancer development. A systematic search of PubMed, Scopus, Web of Science, and Cochrane Library for preclinical studies identified eight studies where cholesteryl ester concentrations were compared between tumour and adjacent-normal tissue, and 24 studies where cholesterol esterification was blocked by pharmacological or genetic approaches. Tumour tissue had a significantly greater concentration of cholesteryl esters than non-tumour tissue (p < 0.0001). Pharmacological or genetic inhibition of SOAT was associated with significantly smaller tumours of all types (p ≤ 0.002). SOAT inhibition increased tumour apoptosis (p = 0.007), CD8 + lymphocyte infiltration and cytotoxicity (p ≤ 0.05), and reduced proliferation (p = 0.0003) and metastasis (p < 0.0001). Significant risk of publication bias was found and may have contributed to a 32% overestimation of the meta-analysed effect size. Avasimibe, the most frequently used SOAT inhibitor, was effective at doses equivalent to those previously reported to be safe and tolerable in humans. This work indicates that SOAT inhibition should be explored in clinical trials as an adjunct to existing anti-neoplastic agents.

An imaging signature to predict outcome in metastatic colorectal cancer using routine computed tomography scans.

BACKGROUND & AIMS: Quantitative analysis of computed tomography (CT) scans of patients with metastatic colorectal cancer (mCRC) can identify imaging signatures that predict overall survival (OS). METHODS: We retrospectively analysed CT images from 1584 mCRC patients on two phase III trials evaluating FOLFOX ± panitumumab (n = 331, 350) and FOLFIRI ± aflibercept (n = 437, 466). In the training set (n = 720), an algorithm was trained to predict OS landmarked from month 2; the output was a signature value on a scale from 0 to 1 (most to least favourable predicted OS). In the validation set (n = 864), hazard ratios (HRs) evaluated the association of the signature with OS using RECIST1.1 as a benchmark of comparison. RESULTS: In the training set, the selected signature combined three features - change in tumour volume, change in tumour spatial heterogeneity, and tumour volume - to predict OS. In the validation set, RECIST1.1 classified patients in three categories: response (n = 166, 19.2%), stable disease (n = 636, 73.6%), and progression (n = 62, 7.2%). The HR was 3.93 (2.79-5.54). Using the same distribution for the signature, the HR was 21.04 (14.88-30.58), showing an incremental prognostic separation. Stable disease by RECIST1.1 was reclassified by the signature along a continuum where patients belonging to the most and least favourable signature quartiles had a median OS of 40.73 (28.49 to NA) months (n = 94) and 7.03 (5.66-7.89) months (n = 166), respectively. CONCLUSIONS: A signature combining three imaging features provides early prognostic information that can improve treatment decisions for individual patients and clinical trial analyses.

Metabolic tumour volume on 18F-FDG PET/CT predicts extended pathological T stages in patients with renal cell carcinoma at staging.

We evaluated the predictive value of 18F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/CT (PET/CT) for extended pathological T (pT) stages (≥ pT3a) in Renal cell carcinoma (RCC) patients at staging. Thirty-eight RCC patients who underwent 18F-FDG PET/CT at staging, followed by radical nephrectomy between September 2016 and September 2018, were included in this prospective study. Patients were classified into two groups (limited pT stage: stage T1/2, n = 17; extended pT stage: T3/4, n = 21). Univariate and multivariate logistic regression analyses were performed to identify clinicopathological and metabolic variables to predict extended pT stages. 18F-FDG metabolic parameters were compared in relation to International Society of Urological Pathology (ISUP) grade and lymphovascular invasion (LVI). In univariate analysis, maximum standardised uptake value, metabolic tumour volume (MTV), and ISUP grade were significant. In multivariate analysis, MTV was the only significant factor of extended pT stages. With a cut-off MTV of 21.2, an area under the curve was 0.944, which was higher than 0.824 for clinical T stages (p = 0.037). In addition, high MTV, but not tumour size, was significantly correlated with aggressive pathologic features (ISUP grade and LVI). High glycolytic tumour volume on 18F-FDG PET/CT in RCC patients at staging is predictive of extended pT stages which could aid decision-making regarding the best type of surgery.

Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging.

PURPOSE: Accurate liver segmentation is key for volumetry assessment to guide treatment decisions. Moreover, it is an important pre-processing step for cancer detection algorithms. Liver segmentation can be especially challenging in patients with cancer-related tissue changes and shape deformation. The aim of this study was to assess the ability of state-of-the-art deep learning 3D liver segmentation algorithms to generalize across all different Barcelona Clinic Liver Cancer (BCLC) liver cancer stages. METHODS: This retrospective study, included patients from an institutional database that had arterial-phase T1-weighted magnetic resonance images with corresponding manual liver segmentations. The data was split into 70/15/15% for training/validation/testing each proportionally equal across BCLC stages. Two 3D convolutional neural networks were trained using identical U-net-derived architectures with equal sized training datasets: one spanning all BCLC stages ("All-Stage-Net": AS-Net), and one limited to early and intermediate BCLC stages ("Early-Intermediate-Stage-Net": EIS-Net). Segmentation accuracy was evaluated by the Dice Similarity Coefficient (DSC) on a dataset spanning all BCLC stages and a Wilcoxon signed-rank test was used for pairwise comparisons. RESULTS: 219 subjects met the inclusion criteria (170 males, 49 females, 62.8±9.1 years) from all BCLC stages. Both networks were trained using 129 subjects: AS-Net training comprised 19, 74, 18, 8, and 10 BCLC 0, A, B, C, and D patients, respectively; EIS-Net training comprised 21, 86, and 22 BCLC 0, A, and B patients, respectively. DSCs (mean±SD) were 0.954±0.018 and 0.946±0.032 for AS-Net and EIS-Net (p<0.001), respectively. The AS-Net 0.956±0.014 significantly outperformed the EIS-Net 0.941±0.038 on advanced BCLC stages (p<0.001) and yielded similarly good segmentation performance on early and intermediate stages (AS-Net: 0.952±0.021; EIS-Net: 0.949±0.027; p = 0.107). CONCLUSION: To ensure robust segmentation performance across cancer stages that is independent of liver shape deformation and tumor burden, it is critical to train deep learning models on heterogeneous imaging data spanning all BCLC stages.

mTORC2-mediated direct phosphorylation regulates YAP activity promoting glioblastoma growth and invasive characteristics.

The Hippo and mTOR signaling cascades are major regulators of cell growth and division. Aberrant regulation of these pathways has been demonstrated to contribute to gliomagenesis and result in enhanced glioblastoma proliferation and invasive characteristics. Several crosstalk mechanisms have been described between these two pathways, although a complete picture of these signaling interactions is lacking and is required for effective therapeutic targeting. Here we report the ability of mTORC2 to directly phosphorylate YAP at serine 436 (Ser436) positively regulating YAP activity. We show that mTORC2 activity enhances YAP transcriptional activity and the induction of YAP-dependent target gene expression while its ablation via genetic or pharmacological means has the opposite affects on YAP function. mTORC2 interacts with YAP via Sin1 and mutational analysis of serine 436 demonstrates that this phosphorylation event affects several properties of YAP leading to enhanced transactivation potential. Moreover, YAP serine 436 mutants display altered glioblastoma growth, migratory capacity and invasiveness both in vitro and in xenograft experiments. We further demonstrate that mTORC2 is able to regulate a Hippo pathway resistant allele of YAP suggesting that mTORC2 can regulate YAP independent of Hippo signaling. Correlative associations between the expression of these components in GBM patient samples also supported the presence of this signaling relationship. These results advance a direct mTORC2/YAP signaling axis driving GBM growth, motility and invasiveness.

Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer.

Radiomics is a method to mine large numbers of quantitative imaging features and develop predictive models. It has shown exciting promise for improved cancer decision support from early detection to personalized precision treatment, and therefore offers a desirable new direction for pancreatic cancer where the mortality remains high despite the current care and intense research. For radiomics, interobserver segmentation variability and its effect on radiomic feature stability is a crucial consideration. While investigations have been reported for high-contrast cancer sites such as lung cancer, no studies to date have investigated it on CT-based radiomics for pancreatic cancer. With three radiation oncology observers and three radiology observers independently contouring on the contrast CT of 21 pancreatic cancer patients, we conducted the first interobserver segmentation variability study on CT-based radiomics for pancreatic cancer. Moreover, our novel investigation assessed whether there exists an interdisciplinary difference between the two disciplines. For each patient, a consensus tumor volume was generated using the simultaneous truth and performance level expectation algorithm, using the dice similarity coefficient (DSC) to assess each observer's delineation against the consensus volume. Radiation oncology observers showed a higher average DSC of 0.81 ± 0.06 than the radiology observers at 0.69 ± 0.16 (p = 0.002). On a panel of 1277 radiomic features, the intraclass correlation coefficients (ICC) was calculated for all observers and those of each discipline. Large variations of ICCs were observed for different radiomic features, but ICCs were generally higher for the radiation oncology group than for the radiology group. Applying a threshold of ICC > 0.75 for considering a feature as stable, 448 features (35%) were found stable for the radiation oncology group and 214 features (16%) were stable from the radiology group. Among them, 205 features were found stable for both groups. Our results provide information for interobserver segmentation variability and its effect on CT-based radiomics for pancreatic cancer. An interesting interdisciplinary variability found in this study also introduces new considerations for the deployment of radiomics models.

Delivery of doxorubicin loaded P18 conjugated-poly(2-ethyl-oxazoline)-DOPE nanoliposomes for targeted therapy of breast cancer.

Breast cancer, a heterogeneous disease, has the highest incidence rate and is a major cause of death in females worldwide. Drug delivery by using nanotechnology has shown great promise for improving cancer treatment. Nanoliposomes are known to have enhanced accumulation ability in tumors due to prolonged systemic circulation. Peptide 18 (P18), a tumor homing peptide targeting keratin-1 (KRT-1), was previously shown to have high binding affinity towards breast cancer cells. In this study, we investigate the ability of P18 conjugated PEtOx-DOPE nanoliposomes (P18-PEtOx-DOPE) for the targeted delivery of doxorubicin to AU565 breast cancer model. Toxicology studies of PEtOx-DOPE nanoliposomes performed on normal breast epithelial cells (MCF10A), showed minimal toxicity. Doxorubicin delivery by P18-PEtOx-DOPE to AU565 cells induces cytotoxicity in a dose and time dependent manner causing mitotic arrest in G2/M phase at 24 h. Anti-cancer activity of P18-PEtOx-DOPE-DOX nanoliposomes on AU565 cells was detected by Annexin V/PI apoptosis assay. In terms of in vivo antitumor efficacy, P18-PEtOx-DOPE-DOX nanoliposomes administration to AU565 CD-1 nu/nu mice model showed significant decrease in tumor volume suggesting that DOX delivered by these nanoliposomes elicited a strong antitumor response comparable to the free delivery of doxorubicin. Overall, our results offered preclinical proof for the use of P18-PEtOx-DOPE-DOX nanoliposomes in KRT-1+ breast cancer therapy.

Urinary concentrations of phenols, parabens, and triclocarban in relation to uterine leiomyomata incidence and growth.

OBJECTIVE: To examine the association of urinary concentrations of phenols, parabens, and triclocarban with incidence and growth of uterine leiomyomata (UL; fibroids). DESIGN: Case-cohort study, nested within the Study of Environment, Lifestyle, and Fibroids, a prospective cohort study. SETTING: Clinic visits at baseline and every 20 months for 60 months. PATIENT(S): 754 Black women aged 23-35 years residing in the Detroit, Michigan area (enrolled during 2010-2012). INTERVENTION: None. MAIN OUTCOME MEASURE(S): At each study visit, women underwent transvaginal ultrasound for measurement of UL incidence and growth and provided urine specimens in which we quantified concentrations of seven phenols, four parabens, and triclocarban. We used Cox proportional hazards regression to estimate hazard ratios and 95% confidence intervals (CIs) characterizing the relation of urinary biomarker concentrations with UL incidence during the 60 months of follow-up. In a subset of UL detected and measured at multiple time points, we used linear regression to assess the associations between biomarker concentrations and UL growth. RESULT(S): Urinary biomarker concentrations were generally inversely associated with UL incidence, but the associations were weak and nonmonotonic. For example, hazard ratios comparing concentrations ≥90th with <50th percentile were 0.77 (95% CI: 0.46, 1.27) for bisphenol A, 0.72 (95% CI: 0.40, 1.28) for bisphenol S, and 0.76 (95% CI: 0.43, 1.33) for methylparaben. Biomarker concentrations were not strongly associated with UL growth. CONCLUSION(S): In this study of reproductive-aged Black women, urinary phenols, parabens, and triclocarban biomarkers were neither strongly nor consistently associated with UL incidence and growth.

Radiomic assessment as a method for predicting tumor mutation burden (TMB) of bladder cancer patients: a feasibility study.

BACKGROUND: Tumor mutation burden (TMB) is an emerging prognostic biomarker of immunotherapy for bladder cancer (BLCA). We aim at investigating radiomic features' value in predicting the TMB status of BLCA patients. METHODS: Totally, 75 patients with BLCA were enrolled. Radiomic features extracted from the volume of interest of preoperative pelvic contrast-enhanced computed tomography (CECT) were obtained for each case. Unsupervised hierarchical clustering analysis was performed based on radiomic features. Sequential univariate Logistic regression, the least absolute shrinkage and selection operator (LASSO) regression and the backward stepwise regression were used to develop a TMB-predicting model using radiomic features. RESULTS: The unsupervised clustering analysis divided the total cohort into two groups, i.e., group A (32.0%) and B (68.0%). Patients in group A had a significantly larger proportion of having high TMB against those in group B (66.7% vs. 41.2%, p = 0.039), indicating the intrinsic ability of radiomic features in TMB-predicting. In univariate analysis, 27 radiomic features could predict TMB. Based on six radiomic features selected by logistic and LASSO regression, a TMB-predicting model was built and visualized by nomogram. The area under the ROC curve of the model reached 0.853. Besides, the calibration curve and the decision curve also revealed the good performance of the model. CONCLUSIONS: Our work firstly proved the feasibility of using radiomics to predict TMB for patients with BLCA. The predictive model based on radiomic features from pelvic CECT has a promising ability to predict TMB. Future study with a larger cohort is needed to verify our findings.

Inhibition of fibronectin accumulation suppresses tumor growth.

Understanding how the extracellular matrix affects cancer development constitutes an emerging research field. Fibronectin and collagen are two intriguing matrix components found in cancer. Large concentrations of fibronectin or collagen type I have been implicated in poor prognosis in patients. In a mouse model, we had shown that genetically decreasing circulating fibronectin resulted in smaller tumors. We therefore aimed to manipulate fibronectin pharmacologically and determine how cancer development is affected. Deletion of fibronectin in human breast cancer cells (MDA-MB-231) using shRNA (knockdown: Kd) improved survival and diminished tumor burden in a model of metastatic lesions and in a model of local growth. Based on these findings, it seemed reasonable to attempt to prevent fibronectin accumulation using a bacterial derived peptide called pUR4. Treatment with this peptide for 10 days in the breast cancer local growth model or for 5 days in a melanoma skin cancer model (B16) was associated with a significant suppression of cancer growth. Treatment aimed at inhibiting collagen type I accumulation without interfering with fibronectin could not affect any changes in vivo. In the absence of fibronectin, diminished cancer progression was due to inhibition of proliferation, even though changes in blood vessels were also detected. Decreased proliferation could be attributed to decreased ERK phosphorylation and diminished YAP expression. In summary, manipulating fibronectin diminishes cancer progression, mostly by suppressing cell proliferation. This suggests that matrix modulation could be used as an adjuvant to conventional therapy as long as a decrease in fibronectin is obtained.

Percentage of Gleason pattern 4 and tumor volume predict adverse pathological stage and margin status at radical prostatectomy in grade Group 2 and grade Group 3 prostate cancers.

BACKGROUND: Increasing percentages of Gleason pattern 4 (GP4%) in radical prostatectomy (RP) correlate with an increased likelihood of nonorgan-confined disease and earlier biochemical recurrence (BCR). However, there are no detailed RP studies assessing the impact of GP4% and corresponding tumor volume (TV) on extraprostatic extension (EPE), seminal vesicle (SV) invasion (SV+), and positive surgical margin (SM) status (SM+). METHODS: In 1301 consecutive RPs, we analyzed each tumor nodule (TN) for TV, Grade Group (GG), presence of focal versus nonfocal EPE, SV+ , and SM+. Using GG1 (GP4% = 0) TNs as a reference, we recorded GP4% for all GG2 or GG3 TNs. We performed a multivariable analysis (MVA) using a mixed effects logistic regression that tested significant variables for risk of EPE, SV+, and SM+, as well as a multinomial logistic regression model that tested significant variables for risks of nonorgan-confined disease (pT2+, pT3a, and pT3b) versus organ-confined disease (pT2). RESULTS: We identified 3231 discrete TNs ranging from 1 to 7 (median: 2.5) per RP. These included GG1 (n = 2115), GG2 (n = 818), GG3 (n = 274), and GG4 (n = 24) TNs. Increasing GP4% weakly paralleled increasing TV (tau = 0.07, p < .001). In MVA, increasing GP4% and TV predicted a greater likelihood of EPE (odds ratio [OR]: 1.03 and 4.41), SV+ (OR: 1.03 and 3.83), and SM+ (1.01, p = .01 and 2.83), all p < .001. Our multinomial logistic regression model demonstrated an association between GP4% and the risk of EPE (i.e., pT3a and pT3b disease), as well as an association between TV and risk of upstaging (all p < .001). CONCLUSIONS: Both GP4% and TV are independent predictors of adverse pathological stage and margin status at RP. However, the risks for adverse outcomes associated with GP4% are marginal, while those for TV are strong. The prognostic significance of GP4% on BCR-free survival has not been studied controlling for TV and other adverse RP findings. Whether adverse pathological stage and margin status associated with larger TV could decrease BCR-free survival to a greater extent than increasing RP GP4% remains to be studied.

Fas-threshold signalling in MSCs promotes pancreatic cancer progression and metastasis.

Mesenchymal stem cells (MSCs) belong to the tumour microenvironment and have been implicated in tumour progression. We found that the number of MSCs significantly increased in tumour-burdened mice driven by Fas-threshold signalling. Consequently, MSCs lacking Fas lost their ability to induce metastasis development in a pancreatic cancer model. Mixing of MSCs with pancreatic cancer cells led to sustained production of the pro-metastatic cytokines CCL2 and IL6 by the stem cells. The levels of these cytokines were dependent on the number of MSCs, linking Fas-mediated MSC-proliferation to their capacity to promote tumour progression. Furthermore, we discovered that CCL2 and IL6 were induced by pancreatic cancer cell-derived IL1. Importantly, analysis of patient transcriptomic data revealed that high FasL expression correlates with high levels of MSC markers as well as increased IL6 and CCL2 levels in pancreatic tumours. Moreover, both FasL and CCL2 are linked to elevated levels of markers specific for monocytes known to possess further pro-metastatic activities. These results confirm our experimental findings of a FasL-MSC-IL1-CCL2/IL6 axis in pancreatic cancer and highlights the role of MSCs in tumour progression.

Agrimol B present in Agrimonia pilosa Ledeb impedes cell cycle progression of cancer cells through G0 state arrest.

Cancer recurrence poses a significant challenge. At the cellular level, recurrence takes place as a result of reactivation of dormant cancer cells residing at G0 phase. The aim of the study was to identify compounds that can trap prostate and lung cancer cells in G0 phase from a new Chinese herb recipe, Astringent recipe, consisting of Radix Paeoniae Alba, Agrimonia pilosa Ledeb, Fructus Mume, Fritillaria thunbergii Miq., Ganoderma Lucidum Karst, and Astragalus membranaceus (Fisch.) Bunge. Astringent recipe impeded cell cycle progression in prostate and lung cancer cells by rounding them up at G0 phase by flow cytometric analysis of cancer cells stained with Hoechst 33342 and Pyronin Y, respectively, for DNA and RNA. The anti-cancer efficacy of the recipe was found to be attributable to Agrimonia pilosa Ledeb. Further study established that agrimol B, a polyphenol derived from Agrimonia pilosa Ledeb, contributed to the activity of the herb. The action of agrimol B on the cancer cells was likely derived from its effect on c-MYC, SKP2 and p27 by immunoblotting and immunofluorescence. Oral administration of Agrimonia pilosa Ledeb or agrimol B reduced growth of prostate cancer cell xenograft in animal. In conclusion, Agrimol B can enrich for prostate and lung cancer cells in G0 state and influence key regulators that govern G0 status.

Metabolic reprogramming due to hypoxia in pancreatic cancer: Implications for tumor formation, immunity, and more.

Hypoxia is a common phenomenon in most malignant tumors, especially in pancreatic cancer (PC). Hypoxia is the result of unlimited tumor growth and plays an active role in promoting tumor survival, progression, and invasion. As the part of the hypoxia microenvironment in PC is gradually clarified, hypoxia is becoming a key determinant and an important therapeutic target of pancreatic cancer. To adapt to the severe hypoxia environment, cells have changed their metabolic phenotypes to maintain their survival and proliferation. Enhanced glycolysis is the most prominent feature of cancer cells' metabolic reprogramming in response to hypoxia. It provides the energy source for hypoxic cancer cells (although it provides less than oxidative phosphorylation) and produces metabolites that can be absorbed and utilized by normoxic cancer cells. In addition, the uptake of glutamine and fatty acids by hypoxic cancer cells is also increased, which is also conducive to tumor progression. Their metabolites are pooled in the hexosamine biosynthesis pathway (HBP). As a nutrition sensor, HBP, in turn, can coordinate glucose and glutamine metabolism. Its end product, UDP-GlcNAc, is the substrate of protein post-translational modification (PTM) involved in various signaling pathways supporting tumor progression. Adaptive metabolic changes of cancer cells promote their survival and affect tumor immune cells in the tumor microenvironment (TME), which contributes to tumor immunosuppressive microenvironment and induces tumor immunotherapy resistance. Here, we summarize the hypoxic microenvironment, its effect on metabolic reprogramming, and its contribution to immunotherapy resistance in pancreatic cancer.

Intravital mesoscopic fluorescence molecular tomography allows non-invasive in vivo monitoring and quantification of breast cancer growth dynamics.

Preclinical breast tumor models are an invaluable tool to systematically study tumor progression and treatment response, yet methods to non-invasively monitor the involved molecular and mechanistic properties under physiologically relevant conditions are limited. Here we present an intravital mesoscopic fluorescence molecular tomography (henceforth IFT) approach that is capable of tracking fluorescently labeled tumor cells in a quantitative manner inside the mammary gland of living mice. Our mesoscopic approach is entirely non-invasive and thus permits prolonged observational periods of several months. The relatively high sensitivity and spatial resolution further enable inferring the overall number of oncogene-expressing tumor cells as well as their tumor volume over the entire cycle from early tumor growth to residual disease following the treatment phase. Our IFT approach is a promising method for studying tumor growth dynamics in a quantitative and longitudinal fashion in-vivo.

Have Volume-based Parameters of Positron Emission Tomography/Computed Tomography Prognostic Relevance for Patients With Potentially Platinum-responsive Recurrent Ovarian Cancer? A Single Center Italian Study.

BACKGROUND/AIM: To assess the prognostic relevance of volume-based parameters [whole body (wb)-metabolic tumor volume (MTV) and wb-total lesion glycolysis (TLG)] of pretreatment PET/CT in patients with potentially platinum-responsive recurrent ovarian cancer. PATIENTS AND METHODS: This retrospective investigation analyzed 67 patients at first relapse. RESULTS: At univariate analysis, post-relapse survival and overall survival correlated with residual disease after primary surgery (RD) (p=0.015 and 0.049, respectively), time to recurrence (p=0.005 and p=0.0003), number of recurrence sites (p=0.001 and p=0.0005), treatment at recurrence (p=0.044 and 0.043) and wb-MTV (p=0.023 and 0.021) but not with wb-TLG. RD, time to recurrence and number of recurrence sites, but not wb-MTV, were independent prognostic variables for post-relapse survival, and time to recurrence and number of recurrence sites, but not wb-MTV, were independent prognostic factors for overall survival. CONCLUSION: Volume-based parameters of PET/CT are not independent predictors of clinical outcome in potentially platinum-responsive recurrent ovarian cancer.

Treatment Volume, Dose Prescription and Delivery Techniques for Dose-intensification in Rectal Cancer: A National Survey.

BACKGROUND/AIM: The aim of the study was to investigate boost volume definition, doses, and delivery techniques for rectal cancer dose intensification. PATIENTS AND METHODS: An online survey was made on 25 items (characteristics, simulation, imaging, volumes, doses, planning and treatment). RESULTS: Thirty-eight radiation oncologists joined the study. Twenty-one delivered long-course radiotherapy with dose intensification. Boost volume was delineated on diagnostic magnetic resonance imaging (MRI) in 18 centres (85.7%), and computed tomography (CT) and/or positron emission tomography-CT in 9 (42.8%); 16 centres (76.2%) performed co-registration with CT-simulation. Boost dose was delivered on gross tumor volume in 10 centres (47.6%) and on clinical target volume in 11 (52.4%). The most common total dose was 54-55 Gy (71.4%), with moderate hypofractionation (85.7%). Intensity-modulated radiotherapy (IMRT) was used in all centres, with simultaneous integrated boost in 17 (80.8%) and image-guidance in 18 (85.7%). CONCLUSION: A high quality of treatment using dose escalation can be inferred by widespread multidisciplinary discussion, MRI-based treatment volume delineation, and radiation delivery relying on IMRT with accurate image-guided radiation therapy protocols.

Tumor Size and N2 Lymph Node Metastasis Are Significant Risk Factors for Early Recurrence in Completely Resected Centrally Located Primary Lung Cancer Patients.

BACKGROUND/AIM: In centrally-located lung cancer treatment, it is difficult to attain a sufficient resection margin. It is important to investigate recurrent styles in centrally-located lung cancer patients. PATIENTS AND METHODS: Primary lung cancer located at the hilar area that requires pneumonectomy or sleeve lobectomy is defined as centrally-located lung cancer. Early recurrence was defined as that within 1 year after surgery. RESULTS: This study included 43 centrally-located lung cancer patients. Ten patients underwent pneumonectomy and 33 underwent sleeve lobectomy. Eleven patients experienced early recurrence. Non-squamous cell carcinoma (p=0.012), tumor size>64 mm (p<0.001) and pathological N2 (p=0.012) were significant predictors for early recurrence by univariate analysis. Also, tumor size >64 mm (p=0.006) and pathological N2 (p=0.019) were independent predictors by multivariate analysis. CONCLUSION: Non-squamous cell carcinoma, tumor size and pathological N2 were significant predictors of early recurrence in centrally-located lung cancer. The type of surgical procedure did not affect recurrence development.

Co-delivery of CPP decorated doxorubicin and CPP decorated siRNA by NGR-modified nanobubbles for improving anticancer therapy.

A combination of doxorubicin (DOX) and small interfering RNA (siRNA) is proven effective for the reverse of multidrug resistance. However, rapid degradation and poor cellular internalization of siRNA hinder their synergistic action. To improve the combination effect, asparagine-glycine-arginine peptide (NGR) -modified nanobubbles (NBs) containing cell-penetrating peptide (CPP) decorated DOX and CPP decorated c-myc siRNA were constructed. Diameters of these NBs were about 245 nm and zeta potentials were about -3 mV. Encapsulation efficiencies (EE) of DOX exceeded 80%. Release of DOX could be triggered by ultrasound (US) since above 80% DOX was released from NBs after sonication while less than 5% DOX was discharged without treatment of US. These NBs were considered stable during 24 h since the decrease of particle size was no more than 10 nm, variances of EE were less than 5%, and changes of transmission (ΔT) were less than 3%. More drugs in formulation decorated with CPP and NGR were accumulated in the tumor when combined with sonication. The evident synergistic action of DOX, siRNA, NBs, and US was verified in mice with strong antitumor efficacy. Taken together, NGR-modified NBs containing CPP-DOX and CPP-siRNA are able to realize time- and spatial-controlled drug delivery and show potential application prospects.