Assessment Of Tumor Aggressiveness Research Articles

ABCG2 Expression as a Potential Survival Predictor in Human Gliomas.

Gliomas are notably challenging to treat due to their invasive nature and resistance to conventional therapies. The ABCG2 protein has attracted attention for its role in multidrug resistance, complicating treatment effectiveness. This study scrutinized the relationship between ABCG2 expression and glioma grade and the role of ABCG2 in the process of glioma progression, aiming to evaluate ABCG2 expression as a predictive factor of tumor progression and patient survival. Conducted at Dubrava University Hospital, Zagreb, Croatia, the study analyzed 152 glioma specimens from 2013 to 2022, assessing ABCG2 expression alongside standard clinical markers. A significant association was found between patients' survival and the ABCG2 profile (p = 0.003, r = 0.24), separately for patients who underwent chemotherapy (p = 0.0004, r = 0.32) and radiotherapy (p = 0.003, r = 0.29). Furthermore, the ABCG2 profile was significantly associated with disease progression (p = 0.007, r = 0.23), tumor grade (p = 0.0002, r = 0.31), and Ki67 expression (p = 0.0004, r = 0.31). ABCG2-positive tumor cells only showed association with Ki67 expression (p = 0.002, r = 0.28). The ABCG2 profile was found to affect the overall patient survival (p = 0.02) and represent a moderate indicator of tumor progression (p = 0.01), unlike the percentage of ABCG2-positive tumor cells. ABCG2 may serve as a marker of angiogenesis and vascular abnormalities within tumors, predicting glioma progression and treatment response. Targeting ABCG2 could enhance chemoradiotherapy efficacy and improve patient outcomes, which highlights its value in assessing tumor aggressiveness and designing treatment strategies.

Relationship between Eccentricity and Volume Determined by Spectral Algorithms Applied to Spatially Registered Bi-Parametric MRI and Prostate Tumor Aggressiveness: A Pilot Study.

(1) Background: Non-invasive prostate cancer assessments using multi-parametric MRI are essential to the reliable detection of lesions and proper management of patients. While current guidelines call for the administration of Gadolinium-containing intravenous contrast injections, eliminating such injections would simplify scanning and reduce patient risk and costs. However, augmented image analysis is necessary to extract important diagnostic information from MRIs. Purpose: This study aims to extend previous work on the signal to clutter ratio and test whether prostate tumor eccentricity and volume are indicators of tumor aggressiveness using bi-parametric (BP)-MRI. (2) Methods: This study retrospectively processed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRIs (apparent diffusion coefficient, high b-value, and T2 images) were resized, translated, cropped, and stitched to form spatially registered BP-MRIs. The International Society of Urological Pathology (ISUP) grade was used to judge cases of prostate cancer as either clinically significant prostate cancer (CsPCa) (ISUP ≥ 2) or clinically insignificant prostate cancer (CiPCa) (ISUP < 2). The Adaptive Cosine Estimator (ACE) algorithm was applied to the BP-MRIs, followed by thresholding, and then eccentricity and volume computations, from the labeled and blobbed detection maps. Then, univariate and multivariate linear regression fittings of eccentricity and volume were applied to the ISUP grade. The fits were quantitatively evaluated by computing correlation coefficients (R) and p-values. Area under the curve (AUC) and receiver operator characteristic (ROC) curve scores were used to assess the logistic fitting to CsPCa/CiPCa. (3) Results: Modest correlation coefficients (R) (>0.35) and AUC scores (0.70) for the linear and/or logistic fits from the processed prostate tumor eccentricity and volume computations for the spatially registered BP-MRIs exceeded fits using the parameters of prostate serum antigen, prostate volume, and patient age (R~0.17). (4) Conclusions: This is the first study that applied spectral approaches to BP-MRIs to generate tumor eccentricity and volume metrics to assess tumor aggressiveness. This study found significant values of R and AUC (albeit below those from multi-parametric MRI) to fit and relate the metrics to the ISUP grade and CsPCA/CiPCA, respectively.

Use of [18F]FLT/PET for assessing the tumor evolution and monitoring the antitumor activity of rosmarinic acid in a mouse 4T1 breast tumor model

The use of the tracer 18F-fluoro-3'-deoxy-3'-L-fluorothymidine ([18F]FLT) in positron emission tomography (PET) has been shown to be an effective tool for assessing tumor aggressiveness and early response to therapy. In this study, we investigated the applicability of [18F]FLT/PET to study the antitumor and anti–lung metastatic effects of rosmarinic acid (RA) in highly invasive breast cancer. 4T1 mammary carcinoma cells were injected into the flank of female Balb/c mice. The animals were treated daily with RA until day 21 after the inoculation of tumor cells. [18F]FLT/PET imaging was used to evaluate the response of primary tumors and lung metastases to RA treatment. PET Images showed a decreased [18F]FLT uptake in the lungs of mice after RA treatment. The antitumor effect of RA appears to be related to the inhibition of cell migration, cell proliferation, and blood vessel formation in the primary tumor. Furthermore, the inflammatory response was modulated by RA, which reduced the accumulation of mast cells and neutrophils in the primary tumor and of macrophages in the lungs. In conclusion, [18F]FLT/PET demonstrates the antitumor and antimetastatic effects of RA in a 4T1 breast tumor model. Furthermore, the findings suggest that RA modulates tumor angiogenesis and inflammation, resulting in antitumor and antimetastatic effects in a 4T1 breast carcinoma model.

Application of Spectral Algorithm Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study

Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of Magnetic Resonance Imaging (MRI) sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement (DCE) in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material and prolonging scanning time. More accurate quantitative MRI without DCE and artificial intelligence approaches are needed. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and correlate with the International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasive management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx + SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade ≥ 2 (&lt;2) was judged as CsPCa (CiPCa). Linear and logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (&gt;0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R ~ 0.17). Patients assessed with combined MRBx + SysBx and from individual MRI scanners achieved higher R (DR = 0.207+/−0.118) than all patients used in the fits. Conclusions: In the first study, to date, spectral approaches for assessing tumor aggressiveness on SRBP-MRI have been applied and tested and achieved high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA, respectively.

A Case of Papillary Thyroid Carcinoma Arising from Struma Ovarii and Extending into the Bladder

Ovarian goiter is a form of single tissue teratoma of the ovary, accounting for 2% - 3% of mature ovarian teratomas. Malignant transformation may occur in rare cases. Papillary thyroid-type carcinoma represents the most common type of malignant struma ovarii, followed by follicular carcinoma. Malignant struma ovarii is commonly seen in women in the fifth decade. The diagnosis is often made post-operatively after histological examination. Histology also helps assess tumor aggressiveness (mitoses, necrosis, poorly differentiated subtype, etc.). Given the rarity of these lesions, no therapeutic consensus or prognostic value had yet been formally established. We report herein, the case of a 76-year-old woman with a cystic tumor of the right ovary and a nodular lesion of the bladder. The clinical symptomatology is nonspecific, associating abdomino-pelvic pain and a right latero-uterine mass on abdominal palpation. After total hysterectomy with bilateral adnexectomy, the diagnosis of papillary carcinoma arising from struma ovarii and extending into the bladder was made. Through this observation, we suggest to discuss the anatomoclinical particularities of this rare pathological entity.

LiSNet: An artificial intelligence -based tool for liver imaging staging of hepatocellular carcinoma aggressiveness.

Presurgical assessment of hepatocellular carcinoma (HCC) aggressiveness can benefit patients' treatment options and prognosis. To develop an artificial intelligence (AI) tool, namely, LiSNet, in the task of scoring and interpreting HCC aggressiveness with computed tomography (CT) imaging. A total of 358 patients with HCC undergoing curative liver resection were retrospectively included. Three subspecialists were recruited to pixel-wise annotate and grade tumor aggressiveness based on CT imaging. LiSNet was trained and validated in 193 and 61 patients with a deep neural network to emulate the diagnostic acumen of subspecialists for staging HCC. The test set comprised 104 independent patients. We subsequently compared LiSNet with an experience-based binary diagnosis scheme and human-AI partnership that combined binary diagnosis and LiSNet for assessing tumor aggressiveness. We also assessed the efficiency of LiSNet for predicting survival outcomes. At the pixel-wise level, the agreement rate of LiSNet with subspecialists was 0.658 (95% confidence interval [CI]: 0.490-0.779), 0.595 (95% CI: 0.406-0.734), and 0.369 (95% CI: 0.134-0.566), for scoring HCC aggressiveness grades I, II, and III, respectively. Additionally, LiSNet was comparable to subspecialists for predicting histopathological microvascular invasion (area under the curve: LiSNet: 0.668 [95% CI: 0.559-0.776] versus subspecialists: 0.699 [95% CI: 0.591-0.806], p>0.05). In a human-AI partnered diagnosis, combining LiSNet and experience-based binary diagnosis can achieve the best predictive ability for microvascular invasion (area under the curve: 0.705 [95% CI: 0.589-0.820]). Furthermore, LiSNet was able to indicate overall survival after surgery. The designed LiSNet tool warrants evaluation as an alternative tool for radiologists to conduct automatic staging of HCC aggressiveness at the pixel-wise level with CT imaging. Its prognostic value might benefit patients' treatment options and survival prediction.

Abstract 2721: Accurate prediction of tumor growth and doubling times for triple negative breast cancer (TNBC) allows for patient-specific assessment of tumor aggressiveness

Abstract TNBC is the most aggressive of breast cancer subtypes and lacks targeted therapies. Thus, tumor aggressiveness is an important factor to determine escalation of care for TNBC patients. Currently, aggressiveness is evaluated based on tumor spread and markers of cell growth. Although these features are significantly associated with tumor volume doubling time (TVDT), TVDT distributions are not simply separated by any of these criteria. Therefore, for single patients, no clear predictor of TVDT (tumor aggressiveness) exists. We sought to test the SimBioSys TumorScope (TS), a biophysical modeling software, to determine whether it could be used for predicting tumor growth and TVDT in TNBC patients. We used the TS software to simulate tumor growth in 30 TNBC patients. We compared the calculated TVDTs from our simulations to values obtained from literature. Using our metabolic modeling platform, we simulated tumor average specific growth rates (SGRs) from RNA-seq data taken from the TCGA BRCA data set. We found that coordinated gene expression profiles act to regulate SGR differentially across breast cancer receptor subtypes (p = 2x10-16), with ER+/PR+ tumors growing slowest (SGR = 0.49 %/day +/- 0.33, median +/- stdev) and TNBC tumors growing fastest (SGR = 1.03 %/day +/- 0.35), which match well with previously reported values of SGR in breast cancers (reported SGR = 0.175 +/- 0.979 %/day for Luminal A and SGR = 1.003 +/- 1.121 %/day for TNBC, mean +/- stdev). We next tested how these growth rates are integrated with tumor biology to produce TVDTs on the order of 100-200 days in TNBC patients. We selected 30 patients with TNBC whose MRI data and electronic medical record (EMR) information are available in our TumorBank to use for this study. We then selected representative TNBC tumor metabolic models and mapped patients to these metabolic models based on patient phenotype. We used clinical measurements to predict unspecified model parameters for TS simulations, resulting in a model with a single free parameter (growing fraction of tumor cells). We tuned this parameter within reported values to simulate TVDT in our patient cohort. Simulating the growth of these tumors resulted in a median TVDT = 163 days with a standard deviation of 111 days, closely matching clinically measured TVDTs in TNBC patients (reported mean TVDT = 127 +/- 48 days). In summary, TS biophysical modeling software accurately predicts TVDTs in TNBC patients. Importantly, this was accomplished without parameter fitting outside of physiologically-measured values and serves as a powerful validation of the our modeling approach. In the future, this high accuracy modeling framework can be further personalized by accounting for additional patient features, including, but not limited to, patient-specific mitotic index, blood chemistry data, and tumor-specific RNA-sequencing. Citation Format: John Whitman, Daniel Cook, Snehal Patel, Lance Munn, John A. Cole, The SimBioSys Team. Accurate prediction of tumor growth and doubling times for triple negative breast cancer (TNBC) allows for patient-specific assessment of tumor aggressiveness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2721.

Intravoxel Incoherent Motion (IVIM) MR Quantification in Locally Advanced Cervical Cancer (LACC): Preliminary Study on Assessment of Tumor Aggressiveness and Response to Neoadjuvant Chemotherapy.

The aim of this study was to determine whether quantitative parameters obtained from intravoxel incoherent motion (IVIM) model at baseline magnetic resonance imaging (MRI) correlate with histological parameters and response to neoadjuvant chemotherapy in patients with locally advanced cervical cancer (LACC). Methods: Twenty patients with biopsy-proven cervical cancer, staged as LACC on baseline MRI and addressed for neoadjuvant chemotherapy were enrolled. At treatment completion, tumor response was assessed with a follow-up MRI evaluated using the revised response evaluation criteria in solid tumors (RECIST; version 1.1), and patients were considered good responders (GR) if they had complete response or partial remission, and poor responders/non-responders (PR/NR) if they had stable or progressive disease. MRI protocol included conventional diffusion-weighted imaging (DWI; b = 0 and 1000 s/mm2) and IVIM acquisition using eight b-values (range: 0–1500 s/mm2). MR-images were analyzed using a dedicated software to obtain quantitative parameters: diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp) from the IVIM model; apparent diffusion coefficient (ADC) from conventional DWI. Histologic subtype, grading, and tumor-infiltrating lymphocytes (TILs) were assessed in each LACC. Results: D showed significantly higher values in GR patients (p = 0.001) and in moderate/high TILs (p = 0.018). Fp showed significantly higher values in squamous cell tumors (p = 0.006). Conclusions: D extracted from the IVIM model could represent a promising tool to identify tumor aggressiveness and predict response to therapy.

Abstract P5-12-13: Exploring the impact of the tumor microenvironment on nuclear morphometry: Lessons learned for sensitivity to cytotoxic treatment

Abstract Globally, breast cancer remains the leading cause of death in females. While systemic therapy for breast cancer may work effectively in the early phases, for more than 10% of primary and 50% of metastatic cases, the disease eventually progresses, resisting treatments. To overcome this issue, recognizing markers of resistance as early as possible is critical. Microenvironmental factors influence tumors, and increased stiffness of the extracellular matrix (ECM) is associated with cancer progression. Additionally, neighboring cells such as non-neoplastic epithelial cells(that may constitute an important portion of the tumor microenvironment -TME) are suspected to affect tumors, but details on their impact are lacking. Here, we asked whether the response to increased ECM stiffness differed depending on the degree of aggressiveness of triple negative breast cancers (TNBC) and the presence of the non-neoplastic epithelium. We investigated two morphometric parameters, nuclear circularity and area (used in cancer pathology), and tumors’ sensitivity to cisplatin to assess tumor aggressiveness- with TNBC cultured at normal (770 Pa) and increased (2000 and 3300 Pa) collagen I stiffness. Reduced nuclear circularity and increased heterogeneity for this parameter in the cancer cell population resulted from higher matrix stiffness and were associated with decreased sensitivity to the cytotoxic drug, cisplatin, notably in the more invasive cancer type. Interestingly, the impact of stiffness increase was reduced by the conditioned medium from the non-neoplastic cells. These findings warrant further investigations to identify whether changes in nuclear circularity that illustrate a global nuclear reorganization affect gene expression profiles linked to cell survival. Citation Format: Apekshya Chhetri. Exploring the impact of the tumor microenvironment on nuclear morphometry: Lessons learned for sensitivity to cytotoxic treatment [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-12-13.

18F-Fluorodeoxyglucose Positron Emission Tomography Is Useful in the Evaluation of Prognosis in Retroperitoneal Sarcoma.

Simple SummaryRetroperitoneal sarcomas are difficult malignancies to treat because complete surgical resection is the only effective treatment option, but it is difficult to secure sufficient surgical margins. It is essential for developing a treatment strategy to assess tumor aggressiveness and predict prognosis for patients. However, the aggressiveness of retroperitoneal sarcomas before treatment cannot be fully evaluated. In patients with resectable soft tissue sarcomas or several carcinomas, SUV evaluated with FDG-PET has been reported to be a valuable prognostic parameter. However, the correlation between SUVmax on FDG-PET and the prognosis of several histological subtypes in retroperitoneal sarcoma, including dedifferentiated liposarcoma, well-differentiated liposarcoma, and leiomyosarcoma, remains uncertain. This study revealed that SUVmax calculated with FDG-PET was useful as a prognostic factor in retroperitoneal sarcoma, especially in dedifferentiated liposarcoma and Grade2 retroperitoneal sarcoma.Background: Retroperitoneal sarcomas are rare neoplasms that occur in the retroperitoneum. Complete surgical resection is the only effective treatment option. The prediction of prognosis by histological diagnosis has not yet been established. The purpose of this study was to identify the usefulness of [18-F] fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging for validating the prognosis of retroperitoneal sarcoma (RPS) established by histological diagnosis. Methods: We retrospectively reviewed 201 patients with RPS treated at the Osaka International Cancer Institute between 2010 and 2021. We extracted the clinical data, including standardized uptake values (SUVs), evaluated with FDG-PET, and statistically analyzed the data. Results: The median age of patients was 64 years (range, 31–85 years). A total of 101 (50.2%) patients were men, and 100 (49.8%) were women. Surgical resection was performed in 155 (77.1%) patients. On histological analysis, 75 (37.3%), 52 (25.9%), and 29 (14.4%) patients were diagnosed with dedifferentiated liposarcoma, well-differentiated liposarcoma, and leiomyosarcoma, respectively. The median survival time for patients with high maximum SUV (SUVmax) (≥4) or low SUVmax (<4) was 275.8 months and 79.5 months, respectively. Furthermore, among the patients with dedifferentiated liposarcoma, the overall survival rate for patients with high SUVmax (≥4) was significantly lower than that of those with low SUVmax (<4). Conclusions: The present study demonstrated that SUVmax calculated with FDG-PET was useful as a prognostic factor in RPS, especially in dedifferentiated liposarcoma and Grade2 RPS. To devise a treatment strategy for RPS, SUVmax during FDG-PET scan may be considered for clinical assessment.

Amplification of mutant KRASG12D in a patient with advanced metastatic pancreatic adenocarcinoma detected by liquid biopsy: A case report.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancer types. Activating oncogenic KRAS mutations are commonly observed in PDAC; however, oncogenic KRAS amplification is rarely observed, and its significance in prognosis and resistance to therapy remains poorly characterized. The present report describes the case of a 52-year-old male patient diagnosed with advanced PDAC with liver metastasis. The patient received modified FOLFIRINOX (mFFX) therapy to which the patient became intolerant with a strong inflammatory response. Subsequent treatment with gemcitabine plus nab-paclitaxel failed to control the disease. Targeted genetic analysis revealed KRASG12D and TP53R248Q mutations in the primary tumor and liver metastases. Analysis of circulating tumor DNA (ctDNA) before the first line of treatment confirmed these genetic findings and revealed a >4-fold amplification of the mutant KRASG12D not detected in the primary tumor. Additionally, subsequent analysis confirmed a 5-fold amplification of the KRASG12D allele in liver metastasis. Consecutive monitoring of ctDNA revealed an initial decrease in the tumor burden 2 weeks after the first cycle of mFFX. However, coinciding with treatment intolerance, a sharp increase in tumor mutational levels and KRASG12D amplification was observed 1 month later. The patient died 70 days after treatment initiation. Overall, amplification of oncogenic KRASG12D was not only associated with an aggressive phenotype, but also supported cancer resistance to chemotherapy. Importantly, this case suggests that plasma detection of KRASG12D amplification is feasible in the clinical routine and constitutes a powerful tool for assessing tumor aggressiveness.

Role of dual-time point 18F-FDG PET/CT imaging in the primary diagnosis and staging of hilar cholangiocarcinoma.

The aim of this study was to evaluate the role of dual-time point 18F-FDG PET/CT imaging in the primary diagnosis and staging of hilar cholangiocarcinoma (HCCA). Dual-time point FDG PET/CT findings, including early phase whole-body scanning and abdominal delayed phased performed 1 and 2h after radiotracer injection, respectively, were retrospective reviewed in 69 patients conformed HCCA by histology. PET/CT was evaluated based on visual interpretation and the semiquantitative index of SUVmax and tumor-to-normal liver tissue ratio (TNR) for both early and delayed images. For all 69 HCCA patients, the mean SUVmax of the lesion and TNR in delayed phase was significantly higher than that in early phase (6.1 ± 4.7, 2.2 ± 1.7, vs 5.1 ± 3.4, 1.6 ± 1.1; P < 0.001). The sensitivity and accuracy value of detection primary lesions was 69.6% and 70% in early phase vs 76.8% and 76.8% in delay phase, respectively. There was a significant correlation between lesion SUVmax and Ki67 index in both dual-time imaging (r = 0.462, P < 0.001 in early phase vs r = 0.47, P < 0.001 in delay phase). The sensitivity, specificity and accuracy value of metastatic lymph nodes prediction was 50%, 67.3% and 71% in early phase vs 62.5%, 73.3% and 76.8% in delayed phase, respectively. The sensitivity, specificity and accuracy of FDG PET/CT in detecting distant metastasis in our study was 75%, 100% and 97.1%. There was no difference of predicting distant metastasis between early phase and delayed phase. Delayed phase in dual-time point 18F-FDG PET/CT scan provides additional usefulness for detection primary tumor and lymph nodes metastases in HCCA, but there was no added benefit of delayed PET/CT imaging in detection of distant metastases in this study. SUVmax in early and delayed phase could be used to assess tumor aggressiveness in pre-treatment HCCA.

Tumor-associated macrophages: Harbingers of aggressiveness in oral squamous cell carcinoma.

Background:The significance of the tumor microenvironment (TME) as a modulator of tumor behavior was acknowledged by Hanahan and Weinberg in 2011 as the emerging hallmarks and enabling characteristics of the hallmarks of cancer. Subsequently, the role of inflammation, in conferring aggressiveness to a tumor, was regarded as a fundamental process in the evolution of the TME. Tumor-associated macrophages (TAMs) are distinctly polarized inflammatory cells and key shapers of a protumorigenic microenvironment.Aims:The aim of the study was to evaluate the distribution of TAMs and the expression of CD-163 as a marker to evince tumor aggressiveness, in oral squamous cell carcinoma (OSCC).Settings and Design:A retrospective institutional study was approved by the institutional ethics committee, and random sampling was carried out. Cases fulfilling the inclusion criteria were subjected to S(site), T(tumor), N( node), M( metastasis), P(pathology) STNMP staging along with immunohistochemical evaluation of CD-163.Methods:Samples for this study included 58 archival cases of OSCC. Demographic details were recorded, and the STNMP stage ascertained, following which, each case was reevaluated histopathologically for the invasive front. Cases with sufficient stroma and demonstrating the invasive front were further subjected to immunohistochemical evaluation of CD-163 for TAMs. The density of CD-163-positive cells was assessed by three pathologists, independently, in a double-blinded evaluation using Image-J©.Statistical Analysis:Descriptive data were evaluated and analyzed statistically using Spearman's/Pearson's correlation tests based on the distribution of data.Results:The density of TAMs was noted to be directly proportional to the STNMP stage. In addition, a strong positive, statistically significant correlation was noted between the density of TAMs and tumor size, nodal status and STNMP stage.Conclusion:The crucial role of the tumor microenvironment must be considered when evaluating OSCC. TAMs prove to be a reliable marker for assessing tumor aggressiveness and could aid in improved prognostication of OSCC, while also being potential targets for therapy.

Feasibility and performance of a novel probe panel to detect somatic DNA copy number alterations in clinical specimens for predicting prostate cancer progression.

To assess the feasibility of a novel DNA-based probe panel to detect copy number alterations (CNAs) in prostate tumor DNA and its performance for predicting clinical progression. A probe panel was developed and optimized to measure CNAs in trace amounts of tumor DNA (2 ng) isolated from formalin-fixed paraffin-embedded tissues. Ten genes previously associated with aggressive disease were targeted. The panel's feasibility and performance were assessed in 175 prostate cancer (PCa) patients who underwent radical prostatectomy with a median 10-year follow-up, including 42 men who developed disease progression (either metastasis and/or PCa-specific death). Association with disease progression was tested using univariable and multivariable analyses. The probe panel detected CNAs in all 10 genes in tumor DNA isolated from either diagnostic biopsies or surgical specimens. A four-gene model (PTEN/MYC/BRCA2/CDKN1B) had the strongest association with disease progression; 64.3% of progressors and 22.5% of non-progressors had at least one CNA in these four genes, odds ratio (OR) (95% confidence interval) = 6.21 (2.77-13.87), P = 8.48E-06. The association with disease progression remained significant after adjusting for known clinicopathological variables. Among the seven progressors of the 65 patients with clinically low-risk disease, three (42.9%) had at least one CNA in these four genes. The probe panel can detect CNAs in trace amounts of tumor DNA from biopsies or surgical tissues at the time of diagnosis or surgery. CNAs independently predict metastatic/lethal cancer, particularly among men with clinically low-risk disease at diagnosis. If validated, this may improve current abilities to assess tumor aggressiveness.

Preoperative CT Radiomics Predicting the SSIGN Risk Groups in Patients With Clear Cell Renal Cell Carcinoma: Development and Multicenter Validation.

Objective: The stage, size, grade, and necrosis (SSIGN) score can facilitate the assessment of tumor aggressiveness and the personal management for patients with clear cell renal cell carcinoma (ccRCC). However, this score is only available after the postoperative pathological evaluation. The aim of this study was to develop and validate a CT radiomic signature for the preoperative prediction of SSIGN risk groups in patients with ccRCC in multicenters.Methods: In total, 330 patients with ccRCC from three centers were classified into the training, external validation 1, and external validation 2 cohorts. Through consistent analysis and the least absolute shrinkage and selection operator, a radiomic signature was developed to predict the SSIGN low-risk group (scores 0–3) and intermediate- to high-risk group (score ≥ 4). An image feature model was developed according to the independent image features, and a fusion model was constructed integrating the radiomic signature and the independent image features. Furthermore, the predictive performance of the above models for the SSIGN risk groups was evaluated with regard to their discrimination, calibration, and clinical usefulness.Results: A radiomic signature consisting of sixteen relevant features from the nephrographic phase CT images achieved a good calibration (all Hosmer–Lemeshow p > 0.05) and favorable prediction efficacy in the training cohort [area under the curve (AUC): 0.940, 95% confidence interval (CI): 0.884–0.973] and in the external validation cohorts (AUC: 0.876, 95% CI: 0.811–0.942; AUC: 0.928, 95% CI: 0.844–0.975, respectively). The radiomic signature performed better than the image feature model constructed by intra-tumoral vessels (all p < 0.05) and showed similar performance with the fusion model integrating radiomic signature and intra-tumoral vessels (all p > 0.05) in terms of the discrimination in all cohorts. Moreover, the decision curve analysis verified the clinical utility of the radiomic signature in both external cohorts.Conclusion: Radiomic signature could be used as a promising non-invasive tool to predict SSIGN risk groups and to facilitate preoperative clinical decision-making for patients with ccRCC.

Neuroimaging of aggressive pituitary tumors.

Aggresssive pituitary tumors are defined as radiologically invasive, exhibiting a rapid growth and a poor response to the medical and surgical treatment options. The role of magnetic resonance imaging (MRI) is fundamental to assess tumor aggressiveness before surgical exploration. Distinction between cavernous sinus invasion and cavernous sinus compression is often challenging and cannot be solved always by using the Knosp criteria. Ideally, T2W images demonstrating the ruptured internal dural wall of cavernous sinus is the ultimate proof of cavernous sinus invasion. Subtle tumor volume increase in a short time can be shown when sequential MR images are rigorously replicable. A microcystic pattern observed on T2W images frequently reflects a potentially aggressive tumor as observed in silent corticotroph pituitary adenomas.

Pancreas deformation in the presence of tumors using feature tracking from free-breathing XD-GRASP MRI.

Quantifying the biomechanical properties of pancreatic tumors could potentially help with assessment of tumor aggressiveness, prognosis, and prediction of therapy response. To quantify respiratory-induced deformation in the pancreas and pancreatic lesions using XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel), MRI. Retrospective study where patients undergoing clinically indicated abdominal MRI which included free-breathing radial T1 -weighted (T1 W) imaging were studied. Thirty-two patients (12 male and 20 female) including nine with pancreatic lesions constituted our study cohort. 3.0 T with T1 WI contrast-enhanced gradient echo radial free-breathing acquisition. Using the XD-GRASP imaging technique, the acquired free-breathing radial data were sorted and binned into 10 consecutive respiratory motion states that were jointly reconstructed. 3D deformation fields along the respiratory dimension were computed using an optical flow method and were analyzed in the pancreas. The Wilcoxon signed-rank test was used to assess the difference in average displacement across pancreatic regions, while the Wilcoxon rank-sum test was used for displacement differences between patients with and without tumors. The interclass correlation coefficient (ICC) was computed to assess consistency between observers for each image quality measure. There was a significantly larger displacement in the pancreatic tail compared with the head (8.2 ± 3.7 mm > 5.8 ± 2.4 mm; P < 0.001) and body regions (8.2 ± 3.7 mm > 6.6 ± 2.9 mm; P < 0.001). Furthermore, there was reduced normalized average displacement in patients with pancreatic lesions compared with subjects without lesions (0.33 ± 0.1 < 0.69 ± 0.26, P < 0.001 for the head; 0.30 ± 0.1 < 0.84 ± 0.31, P < 0.001 for the body; and 0.44 ± 0.31 < 1.08 ± 0.53, P < 0.001 for the tail, respectively). Free-breathing respiratory motion-sorted XD-GRASP MRI has the potential to noninvasively characterize the biomechanical properties of the pancreas by quantifying breathing-induced mechanical displacement. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1633-1640.

The value of histogram quantitative analysis based on diffusion kurtosis imaging in detecting prostate cancer and assessing tumor aggressiveness

Objective To explore the application value of histogram quantitative analysis based on diffusion kurtosis imaging (DKI) in detecting prostate cancer (PCa) and assessing tumor aggressiveness. Methods One hundred and twenty patients were retrospectively enrolled in Zhongnan Hospital of Wuhan University from November 2014 to November 2016, with diagnosis confirmed by prostate biopsy, definitive Gleason score(GS) results and prostate MRI examinations. There were 90 tumor foci in 67 prostate cancer patients, including 23 cases with GS≤6 (37 tumor foci), 7 GS 3+4=7(7 tumor foci), 3 GS 4+3=7(3 tumor foci). Thirty four cases who were with GS≥8(43 tumor foci) were divided into low-grade PCa (37 GS ≤6) and high-grade PCa (53 GS≥7). Fifty three patients were diagnosed with benign prostatic hyperplasia (BPH). All patients underwent conventional prostate MRI examination and multi b value DKI examination. The apparent diffusion coefficient (Dapp) corrected by non-Gaussian model, apparent kurtosis coefficient (Kapp) and ADC value were obtained for histogram analysis. Student's t test was executed to compare the differences of ADCs, Dapp and Kapp values between prostate cancer(PCa) and BPH, low-grade PCa and high-grade PCa. ROC curves were used to evaluate the diagnostic value of ADCs, Dapp and Kapp values in differentiating PCa from BPH and differentiating high-grade PCa from low-grade PCa. Pearson correlation was used to assess the correlations between the histogram quantitative parameters of ADCs, Dapp and Kapp values and Gleason score. Results Except skew of Kapp, the other histogram quantitative parameters of Kapp between PCa and BPH were statistically significant (all P<0.05). Except the skew of Kapp, the other histogram quantitative parameters of Kapp between low-grade PCa and high-grade PCa were statistically significant (all P<0.05). The median, mean and standard deviation of ADC, Dapp and Kapp have good diagnostic value in detecting PCa from BPH and differing high-grade PCa from low-grade PCa. The area under ROC curve was ranging from 0.558 to 0.985. There were moderate to high correlations between median, mean of ADC (r=-0.701 and -0.676, respectively), median, mean of Dapp (r=-0.712 and -0.701, respectively), median, standard deviation, and kurtosis of Kapp (r=0.458, 0.516 and -0.528, respectively) and Gleason score (all P<0.05). Conclusion The DKI parameters combined with histogram quantitative analysis is helpful in detecting prostate cancer and assessing tumor aggressiveness. Key words: Prostate neoplasms; Magnetic resonance imaging; Diffusion kurtosis imaging; Histogram analysis

Toward a noninvasive estimate of interstitial fluid pressure by dynamic contrast-enhanced MRI in a rat model of cerebral tumor.

This study demonstrates a DCE-MRI estimate of tumor interstitial fluid pressure (TIFP) and hydraulic conductivity in a rat model of glioblastoma, with validation against an invasive wick-in-needle (WIN) technique. An elevated TIFP is considered a mark of aggressiveness, and a decreased TIFP a predictor of response to therapy. The DCE-MRI studies were conducted in 36 athymic rats (controls and posttreatment animals) with implanted U251 cerebral tumors, and with TIFP measured using a WIN method. Using a model selection paradigm and a novel application of Patlak and Logan plots to DCE-MRI data, the MRI parameters required for estimating TIFP noninvasively were estimated. Two models, a fluid-mechanical model and a multivariate empirical model, were used for estimating TIFP, as verified against WIN-TIFP. Using DCE-MRI, the mean estimated hydraulic conductivity (MRI-K) in U251 tumors was (2.3 ± 3.1) × 10-5 (mm2 /mmHg-s) in control studies. Significant positive correlations were found between WIN-TIFP and MRI-TIFP in both mechanical and empirical models. For instance, in the control group of the fluid-mechanical model, MRI-TIFP was a strong predictor of WIN-TIFP (R2 = 0.76, p < .0001). A similar result was found in the bevacizumab-treated group of the empirical model (R2 = 0.93, p = .014). This research suggests that MRI dynamic studies contain enough information to noninvasively estimate TIFP in this, and possibly other, tumor models, and thus might be used to assess tumor aggressiveness and response to therapy.

Abstract OT1-06-05: Atomic force microscopy (AFM) - a novel nanotool for cancer diagnostics: A prospective, blinded study of nanomechanical profiling of human breast tissue as a potential biomarker for stratifying low- and high-risk breast cancer subtypes

Abstract Background The crucial point in making treatment decisions for breast cancer patients is the assessment of tumour aggressiveness. The established prognostic markers may be insufficient to stratify cancer patients into treatment relevant risk groups. Emerging evidence indicates that mechanical properties of cancer cells and their microenvironment that occur on a nanometre scale play a critical role in cancer invasion and metastases. Therefore, detecting these nanomechanical changes could serve as biomarker of cancer aggressiveness. Trial design We conduct a prospective, blinded study in a routine clinical setting. Using minimal invasive breast biopsies we measure the nanomechanical (stiffness) properties of human breast tissue with our atomic force microscope (AFM) based method known as ARTIDIS (Automated and Reliable Tissue Diagnostics). These properties can only be measured using fresh (non-fixed) tissue under physiological conditions (Custodiol transplant buffer). This novel method is based on the use of a micro-fabricated 20nm-sharp tip that indents several thousand individual locations across tissue specimens within 60-180 minutes. Each indentation effectively measures the stiffness of local structures (e.g. cancer cells, extracellular matrix) located under the tip. Thus we obtain a quantitative, biopsy-wide, nanomechanical profile. Post-AFM the same biopsy is used for routine histopathological diagnosis, the current diagnostic gold standard to which the nanomechanical profile is then correlated. Eligibility criteria All women undergoing a minimal invasive breast biopsy (core needle or vacuum assisted biopsy) at the breast centre of the University of Basel. Exclusion criteria: age younger than 18years, necrotic/disintegrated biopsy, and technical limitations Specific aims Our primary endpoint is to differentiate benign from cancerous breast lesions based on their nanomechanical properties. Our secondary endpoint is to subclassify biopsies with cancerous lesions into the current four main breast cancer subgroups (Luminal A, Luminal B, HER2+ and basal-like). Statistical analysis The full dataset will include all patients with valid AFM measurements. Primary analysis: the proportion of true positive results divided by the total number of patients with malignant tumour (sensitivity) will be estimated and presented together with its 95% confidence interval. The histological diagnosis of the same biopsy as analysed by AFM will serve as gold standard. Present accrual and target accrual Present accrual as of June 12, 2017: 200 breast tissue biopsies. Target accrual is 508 biopsies. This will allow for a power of 0.8 and a sensitivity of 90%. Contact information: Rosemarie.Burian@usb.ch Citation Format: Burian R, Appenzeller T, Oertle P, Raez C, Lim R, Forte S, Dellas S, Münst S, Obermann E, Plodinec M. Atomic force microscopy (AFM) - a novel nanotool for cancer diagnostics: A prospective, blinded study of nanomechanical profiling of human breast tissue as a potential biomarker for stratifying low- and high-risk breast cancer subtypes [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr OT1-06-05.