GLINT: GlucoCEST in neoplastic tumors at 3 T—clinical results of GlucoCEST in gliomas

Objective Clinical relevance of dynamic glucose enhanced (DGE) chemical exchange saturation transfer (CEST) imaging has mostly been demonstrated at ultra-high field (UHF) due to low effect size. Results of a cohort study at clinical field strength are shown herein. Materials and methods Motion and field inhomogeneity corrected T1ρ‐based DGE (DGE⍴) images were acquired before, during and after a d-glucose injection with 6.3 s temporal resolution to detect accumulation in the brain. Six glioma patients with clear blood–brain barrier (BBB) leakage, two glioma patients with suspected BBB leakage, and three glioma patients without BBB leakage were scanned at 3 T. Results In high-grade gliomas with BBB leakage, d-glucose uptake could be detected in the gadolinium (Gd) enhancing region as well as in the tumor necrosis with a maximum increase of ∆DGE⍴ around 0.25%, whereas unaffected white matter did not show any significant DGE⍴ increase. Glioma patients without Gd enhancement showed no detectable DGE⍴ effect within the tumor. Conclusion First application of DGE⍴ in a patient cohort shows an association between BBB leakage and DGE signal irrespective of the tumor grade. This indicates that glucoCEST corresponds more to the disruptions of BBB with Gd uptake than to the molecular tumor profile or tumor grading.

CT Texture Analysis of Pulmonary Neuroendocrine Tumors—Associations with Tumor Grading and Proliferation

Texture analysis derived from computed tomography (CT) might be able to provide clinically relevant imaging biomarkers and might be associated with histopathological features in tumors. The present study sought to elucidate the possible associations between texture features derived from CT images with proliferation index Ki-67 and grading in pulmonary neuroendocrine tumors. Overall, 38 patients (n = 22 females, 58%) with a mean age of 60.8 ± 15.2 years were included into this retrospective study. The texture analysis was performed using the free available Mazda software. All tumors were histopathologically confirmed. In discrimination analysis, “S(1,1)SumEntrp” was significantly different between typical and atypical carcinoids (mean 1.74 ± 0.11 versus 1.79 ± 0.14, p = 0.007). The correlation analysis revealed a moderate positive association between Ki-67 index with the first order parameter kurtosis (r = 0.66, p = 0.001). Several other texture features were associated with the Ki-67 index, the highest correlation coefficient showed “S(4,4)InvDfMom” (r = 0.59, p = 0.004). Several texture features derived from CT were associated with the proliferation index Ki-67 and might therefore be a valuable novel biomarker in pulmonary neuroendocrine tumors. “Sumentrp” might be a promising parameter to aid in the discrimination between typical and atypical carcinoids.

Comparison of risk assessment in 1652 early ER positive, HER2 negative breast cancer in a real-world data set: classical pathological parameters vs. 12-gene molecular assay (EndoPredict)

Background Risk assessment on the molecular level is important in predictive pathology to determine the risk of metastatic disease for ERpos, HER2neg breast cancer. The gene expression test EndoPredict (EP) was trained and validated for prediction of a 10-year risk of distant recurrence to support therapy decisions regarding endocrine therapy alone or in combination with chemotherapy. The EP test provides the 12-gene Molecular Score (MS) and the EPclin-Score (EPclin), which combines the molecular score with tumor size and nodal status. In this project we investigated the correlation of 12-gene MS and EPclin scores with classical pathological markers. Methods EndoPredict-based gene expression profiling was performed prospectively in a total of 1652 patients between 2017 and 2020. We investigated tumor grading and Ki67 cut-offs of 20% for binary classification as well as 10% and 30% for three classes (low, intermediate, high), based on national and international guidelines. Results 410 (24.8%) of 1652 patients were classified as 12-gene MS low risk and 626 (37.9%) as EPclin low risk. We found significant positive associations between 12-gene MS and grading (p < 0.001), EPclin and grading (p = 0.001), 12-gene MS and Ki67 (p < 0.001), and EPclin and Ki67 (p < 0.001). However, clinically relevant differences between EP test results, Ki67 and tumor grading were observed. For example, 118 (26.3%) of 449 patients with Ki67 > 20% were classified as low risk by EPclin. Same differences were seen comparing EP test results and tumor grading. Conclusion In this study we could show that EP risk scores are distributed differentially among Ki67 expression groups, especially in Ki67 low and high tumors with a substantial proportion of patients with EPclin high risk results in Ki67 low tumors and vice versa. This suggests that classical pathological parameters and gene expression parameters are not interchangeable, but should be used in combination for risk assessment.

Molecular Characterization of Peritoneal Involvement in Primary Colon and Ovary Neoplasm: The Possible Clinical Meaning of the P2X7 Receptor-Inflammasome Complex

<b><i>Introduction:</i></b> Colon cancer (CC) and epithelial ovarian cancer (EOC) are common and severe neoplasms frequently sharing a massive inflammatory involvement of peritoneum. A detailed molecular characterization of such carcinomatosis has not been performed, so far. <b><i>Methods:</i></b> Omental adipocytes were isolated from thirty-three adult women who underwent primary surgery for CC or EOC. Expression of several pro-inflammatory genes was determined by real-time PCR and immunofluorescence. Data were related to the clinical phenotype of the patients. <b><i>Results:</i></b> CD68, FGFR1, and IL-6 were significantly more expressed in adipocytes from CC patients and VEGF in adipocytes from EOC. TNFα, TGFβ, or MCP-1, as well as the pro-inflammatory platform P2X7R-NLRP3, did not differ between the 2 cancers. White blood cell count, mirroring systemic inflammation, was related to adipocyte P2X7R (<i>R</i> = 0.508, <i>p</i> = 0.003), NLRP3 (<i>R</i> = 0.405; <i>p</i> = 0.02), and MCP-1 (<i>R</i> = 0.448; <i>p</i> = 0.009). P2X7R and NLRP3 were the only inflammatory factors significantly more expressed in patients carrying both omental and peritoneal carcinosis, who were also characterized by a higher leukocytosis. None of the tested inflammatory markers was associated with tumor grading for both neoplasms; however, the presence of metastases was associated with a higher adipocyte expression of FGFR1 and TGFβ. <b><i>Conclusion:</i></b> We show here that rarely measured molecules seem to specifically characterize omental carcinomatosis of CC or EOC, while more common inflammatory agents like TNFα, TGFβ, or MCP-1 do not; the P2X7R-NLRP3 complex marks omental and peritoneal carcinosis and is related to circulating white blood cells and MCP-1, involved in monocyte-macrophage tissue infiltration; increased TGFβ and FGFR1 characterize the tumoral dissemination.

Association of miR-1251-5p/miR-6892-5p Expression With Clinicopathological Factors in Premenopausal Endometrial Cancer

Background This study is aim to profile the differentially expressed microRNAs (DEMs) of premenopausal endometrial cancer (EC), identify their target genes and understand their roles in carcinogenesis. Methods Next-generation sequencing (NGS) was performed on 3 premenopausal EC and 3 premenopausal normal endometrial tissues. Selection of candidate miRNAs and subsequent validation were performed by qRT-PCR on 20 premenopausal EC, 30 premenopausal normal endometrial and 40 postmenopausal EC samples. The relationship between DEMs and clinical characteristics was analyzed. Moreover, bioinformatic software programs and databases were applied to predict miRNA target genes, molecular functions, and signaling pathways. Results 136 upregulated and 131 downregulated DEMs were identified. The expression of miR-1251-5p was highly upregulated in premenopausal EC samples compared with premenopausal normal endometrial samples and significantly downregulated compared with postmenopausal EC samples. The expression of miR-6892-5p was highly upregulated in premenopausal EC samples compared with premenopausal normal endometrial samples and postmenopausal EC samples. In the premenopausal EC group, miR-1251-5p expression was closely correlated with menarche age, number of pregnancies, tumor grading, myometrial infiltration and lymph node metastasis; miR-6892-5p expression was closely correlated with BMI, hypertension, tumor grading, and metastasis. Conclusions miR-1251-5p and miR-6892-5p may play important roles in tumorigenesis progression of premenopausal EC.

Resection of Non-Functional Pancreatic Neuroendocrine Neoplasms—A Single-Center Retrospective Outcome Analysis

Surgery remains the only curative treatment of pancreatic neuroendocrine neoplasms (pNEN). Here, we report the outcome after surgery for non-functional pNEN at a European Neuroendocrine Tumor Society (ENETS) center in Germany between 2000 and 2019; cases were analyzed for surgical (Clavien–Dindo classification; CDc) and oncological outcomes. Forty-nine patients (tumor grading G1 n = 25, G2 n = 22, G3 n = 2), with a median age of 56 years, were included. Severe complications (CDc ≥ grade 3b) occurred in 11 patients (22.4%) and type B/C pancreatic fistulas (POPFs) occurred in 5 patients (10.2%); in-hospital mortality was 2% (n = 1). Six of seven patients with tumor recurrence (14.3%) had G2 tumors in the pancreatic body/tail. The median survival was 5.7 years (68 months; [1–228 months]). Neither the occurrence (p = 0.683) nor the severity of complications had an influence on the relapse behavior (p = 0.086). This also applied for a POPF (≥B, p = 0.609). G2 pNEN patients (n = 22) with and without tumor recurrence had similar median tumor sizes (4 cm and 3.9 cm, respectively). Five of the six relapsed G2 patients (83.3%) had tumor-positive lymph nodes (N+); all G2 pNEN patients with recurrence had initially been treated with distal pancreatic resection. Pancreatic resections for pNEN are safe but associated with relevant postoperative morbidity. Future studies are needed to evaluate suitable resection strategies for G2 pNEN.

Increased lysophosphatidylcholine acyltransferase 1 expression is unrelated to prognosis of esophageal cancer patients

Introduction Lysophosphatidylcholine acyltransferase 1 (LPCAT1) has repeatedly been suggested to be associated with tumorigenesis. To evaluate the role of LPCAT1 in esophageal cancer, LPCAT1 immunostaining was analyzed on a tissue microarray containing samples from esophageal cancer patients. Results In benign esophageal tissue, LPCAT1 staining was detectable in low intensities. LPCAT1 staining was increased in malignant as compared to benign esophageal tissue and was found in high intensity in 26.4% of 288 interpretable esophageal adenocarcinomas (EACs) and in 23.2% of 211 squamous cell carcinomas (ESCCs). Increased LPCAT1 staining was linked to undifferentiated tumor grading in both subtypes of EACs and ESCCs (p = 0.0273 and p = 0.0085). Conclusion However, LPCAT1 was not associated with prognosis of EAC and ESCC patients (p = 0.6838 and p = 0.4695) and thus cannot be considered a prognostic biomarker in esophageal cancers.

Development and External Validation of Deep-Learning-Based Tumor Grading Models in Soft-Tissue Sarcoma Patients Using MR Imaging

Background: In patients with soft-tissue sarcomas, tumor grading constitutes a decisive factor to determine the best treatment decision. Tumor grading is obtained by pathological work-up after focal biopsies. Deep learning (DL)-based imaging analysis may pose an alternative way to characterize STS tissue. In this work, we sought to non-invasively differentiate tumor grading into low-grade (G1) and high-grade (G2/G3) STS using DL techniques based on MR-imaging. Methods: Contrast-enhanced T1-weighted fat-saturated (T1FSGd) MRI sequences and fat-saturated T2-weighted (T2FS) sequences were collected from two independent retrospective cohorts (training: 148 patients, testing: 158 patients). Tumor grading was determined following the French Federation of Cancer Centers Sarcoma Group in pre-therapeutic biopsies. DL models were developed using transfer learning based on the DenseNet 161 architecture. Results: The T1FSGd and T2FS-based DL models achieved area under the receiver operator characteristic curve (AUC) values of 0.75 and 0.76 on the test cohort, respectively. T1FSGd achieved the best F1-score of all models (0.90). The T2FS-based DL model was able to significantly risk-stratify for overall survival. Attention maps revealed relevant features within the tumor volume and in border regions. Conclusions: MRI-based DL models are capable of predicting tumor grading with good reproducibility in external validation.