A Computational Framework to Identify Biomarkers for Glioma Recurrence and Potential Drugs Targeting Them

Background: Recurrence is still a major obstacle to the successful treatment of gliomas. Understanding the underlying mechanisms of recurrence may help for developing new drugs to combat gliomas recurrence. This study provides a strategy to discover new drugs for recurrent gliomas based on drug perturbation induced gene expression changes.Methods: The RNA-seq data of 511 low grade gliomas primary tumor samples (LGG-P), 18 low grade gliomas recurrent tumor samples (LGG-R), 155 glioblastoma multiforme primary tumor samples (GBM-P), and 13 glioblastoma multiforme recurrent tumor samples (GBM-R) were downloaded from TCGA database. DESeq2, key driver analysis and weighted gene correlation network analysis (WGCNA) were conducted to identify differentially expressed genes (DEGs), key driver genes and coexpression networks between LGG-P vs LGG-R, GBM-P vs GBM-R pairs. Then, the CREEDS database was used to find potential drugs that could reverse the DEGs and key drivers.Results: We identified 75 upregulated and 130 downregulated genes between LGG-P and LGG-R samples, which were mainly enriched in human papillomavirus (HPV) infection, PI3K-Akt signaling pathway, Wnt signaling pathway, and ECM-receptor interaction. A total of 262 key driver genes were obtained with frizzled class receptor 8 (FZD8), guanine nucleotide-binding protein subunit gamma-12 (GNG12), and G protein subunit β2 (GNB2) as the top hub genes. By screening the CREEDS database, we got 4 drugs (Paclitaxel, 6-benzyladenine, Erlotinib, Cidofovir) that could downregulate the expression of up-regulated genes and 5 drugs (Fenofibrate, Oxaliplatin, Bilirubin, Nutlins, Valproic acid) that could upregulate the expression of down-regulated genes. These drugs may have a potential in combating recurrence of gliomas.Conclusion: We proposed a time-saving strategy based on drug perturbation induced gene expression changes to find new drugs that may have a potential to treat recurrent gliomas.

Predictive Factors for Skip Lymph Node Metastasis and Their Implication on Recurrence in Papillary Thyroid Carcinoma

Skip lymph node (LN) metastases in papillary thyroid carcinoma (PTC) belong to N1b classification in the absence of central neck LN involvement. This study aimed to evaluate the predictive factors of skip metastases and their impact on recurrence in PTC patients with pN1b. A total of 334 PTC patients who underwent total thyroidectomy with LN dissection (central and lateral neck compartment) followed by radioactive iodine ablation were included. Patients with skip metastases tended to have a small primary tumor (≤1 cm) and single lateral neck level involvement. Tumor size ≤ 1 cm was an important predictive factor for skip metastases. Univariate analysis for recurrence showed that patients with a central LN ratio > 0.68, lateral LN ratio > 0.21, and stimulated thyroglobulin (Tg) levels > 7.3 ng/mL had shorter RFS (recurrence-free survival). The stimulated Tg level was associated with shorter RFS on multivariate analysis (>7.3 vs. ≤7.3 ng/mL; hazard ratio, 4.226; 95% confidence interval, 2.226−8.022; p < 0.001). Although patients with skip metastases tended to have a small primary tumor and lower burden of lateral neck LN involvement, there was no association between skip metastases and RFS in PTC with pN1b. Stimulated Tg level was a strong predictor of recurrence.

Automatic segmentation of head and neck primary tumors on MRI using a multi-view CNN

Background Accurate segmentation of head and neck squamous cell cancer (HNSCC) is important for radiotherapy treatment planning. Manual segmentation of these tumors is time-consuming and vulnerable to inconsistencies between experts, especially in the complex head and neck region. The aim of this study is to introduce and evaluate an automatic segmentation pipeline for HNSCC using a multi-view CNN (MV-CNN). Methods The dataset included 220 patients with primary HNSCC and availability of T1-weighted, STIR and optionally contrast-enhanced T1-weighted MR images together with a manual reference segmentation of the primary tumor by an expert. A T1-weighted standard space of the head and neck region was created to register all MRI sequences to. An MV-CNN was trained with these three MRI sequences and evaluated in terms of volumetric and spatial performance in a cross-validation by measuring intra-class correlation (ICC) and dice similarity score (DSC), respectively. Results The average manual segmented primary tumor volume was 11.8±6.70 cm3 with a median [IQR] of 13.9 [3.22-15.9] cm3. The tumor volume measured by MV-CNN was 22.8±21.1 cm3 with a median [IQR] of 16.0 [8.24-31.1] cm3. Compared to the manual segmentations, the MV-CNN scored an average ICC of 0.64±0.06 and a DSC of 0.49±0.19. Improved segmentation performance was observed with increasing primary tumor volume: the smallest tumor volume group (<3 cm3) scored a DSC of 0.26±0.16 and the largest group (>15 cm3) a DSC of 0.63±0.11 (p<0.001). The automated segmentation tended to overestimate compared to the manual reference, both around the actual primary tumor and in false positively classified healthy structures and pathologically enlarged lymph nodes. Conclusion An automatic segmentation pipeline was evaluated for primary HNSCC on MRI. The MV-CNN produced reasonable segmentation results, especially on large tumors, but overestimation decreased overall performance. In further research, the focus should be on decreasing false positives and make it valuable in treatment planning.

Systemic Injection of Oncolytic Vaccinia Virus Suppresses Primary Tumor Growth and Lung Metastasis in Metastatic Renal Cell Carcinoma by Remodeling Tumor Microenvironment

Immune checkpoint inhibitors and tyrosine kinase inhibitors are the first-line treatment for metastatic renal cell carcinoma (mRCC), but their benefits are limited to specific patient subsets. Here, we aimed to evaluate the therapeutic efficacy of JX-594 (pexastimogene devacirepvec, Pexa-vec) monotherapy by systemic injection in comparison with sunitinib monotherapy in metastatic orthotopic RCC murine models. Two highly metastatic orthotopic RCC models were developed to compare the treatment efficacy in the International Metastatic RCC Database Consortium favorable-risk and intermediate- or poor-risk groups. JX-594 was systemically injected through the peritoneum, whereas sunitinib was orally administered. Post-treatment, tumor microenvironment (TME) remodeling was determined using immunofluorescence analysis. Systemic JX-594 monotherapy injection demonstrated therapeutic benefit in both early- and advanced-stage mRCC models. Sunitinib monotherapy significantly reduced the primary tumor burden and number of lung metastases in the early-stage, but not in the advanced-stage mRCC model. Systemic JX-594 delivery remodeled the primary TME and lung metastatic sites by increasing tumor-infiltrating CD4/8+ T cells and dendritic cells. Systemic JX-594 monotherapy demonstrated significantly better therapeutic outcomes compared with sunitinib monotherapy in both early- and advanced-stage mRCCs by converting cold tumors into hot tumors. Sunitinib monotherapy effectively suppressed primary tumor growth and lung metastasis in early-stage mRCC.

The initial hormone receptor/HER2 subtype is the main determinator of subtype discordance in advanced breast cancer: a study of the SONABRE registry

Purpose The hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) are the main parameters in guiding systemic treatment choices in breast cancer, but can change during the disease course. This study aims to evaluate the biopsy rate and receptor subtype discordance rate in patients diagnosed with advanced breast cancer (ABC). Methods Patients diagnosed with ABC in seven hospitals in 2007–2018 were selected from the SOutheast Netherlands Advanced BREast cancer (SONABRE) registry. Multivariable logistic regression analyses were performed to identify factors influencing biopsy and discordance rates. Results Overall, 60% of 2854 patients had a biopsy of a metastatic site at diagnosis. One of the factors associated with a reduced biopsy rate was the HR + /HER2 + primary tumor subtype (versus HR + /HER2- subtype: OR = 0.68; 95% CI: 0.51–0.90). Among the 748 patients with a biopsy of the primary tumor and a metastatic site, the overall receptor discordance rate was 18%. This was the highest for the HR + /HER2 + primary tumor subtype, with 55%. In 624 patients with metachronous metastases, the HR + /HER2 + subtype remained the only predictor significantly related to a higher discordance rate, irrespective of prior (neo-)adjuvant therapies (OR = 7.49; 95% CI: 3.69–15.20). Conclusion The HR + /HER2 + subtype has the highest discordance rate, but the lowest biopsy rate of all four receptor subtypes. Prior systemic therapy was not independently related to subtype discordance. This study highlights the importance of obtaining a biopsy of metastatic disease, especially in the HR + /HER2 + subtype to determine the most optimal treatment strategy.

Construction and validation of a risk prediction model for clinical axillary lymph node metastasis in T1–2 breast cancer

The current diagnostic technologies for assessing the axillary lymph node metastasis (ALNM) status accurately in breast cancer (BC) remain unsatisfactory. Here, we developed a diagnostic model for evaluating the ALNM status using a combination of mRNAs and the T stage of the primary tumor as a novel biomarker. We collected relevant information on T1–2 BC from public databases. An ALNM prediction model was developed by logistic regression based on the screened signatures and then internally and externally validated. Calibration curves and the area under the curve (AUC) were employed as performance metrics. The prognostic value and tumor immune infiltration of the model were also determined. An optimal diagnostic model was created using a combination of 11 mRNAs and T stage of the primary tumor and showed high discrimination, with AUCs of 0.828 and 0.746 in the training sets. AUCs of 0.671 and 0.783 were achieved in the internal validation cohorts. The mean external AUC value was 0.686 and ranged between 0.644 and 0.742. Moreover, the new model has good specificity in T1 and hormone receptor-negative/human epidermal growth factor receptor 2- negative (HR−/HER2−) BC and good sensitivity in T2 BC. In addition, the risk of ALNM and 11 mRNAs were correlated with the infiltration of M2 macrophages, as well as the prognosis of BC. This novel prediction model is a useful tool to identify the risk of ALNM in T1–2 BC patients, particularly given that it can be used to adjust surgical options in the future.

Metastatic Progression of Osteosarcomas: A Review of Current Knowledge of Environmental versus Oncogenic Drivers

Metastases of osteosarcomas are heterogeneous. They may grow simultaneously with the primary tumor, during treatment or shortly after, or a long time after the end of the treatment. They occur mainly in lungs but also in bone and various soft tissues. They can have the same histology as the primary tumor or show a shift towards a different differentiation path. However, the metastatic capacities of osteosarcoma cells can be predicted by gene and microRNA signatures. Despite the identification of numerous metastasis-promoting/predicting factors, there is no efficient therapeutic strategy to reduce the number of patients developing a metastatic disease or to cure these metastatic patients, except surgery. Indeed, these patients are generally resistant to the classical chemo- and to immuno-therapy. Hence, the knowledge of specific mechanisms should be extended to reveal novel therapeutic approaches. Recent studies that used DNA and RNA sequencing technologies highlighted complex relations between primary and secondary tumors. The reported results also supported a hierarchical organization of the tumor cell clones, suggesting that cancer stem cells are involved. Because of their chemoresistance, their plasticity, and their ability to modulate the immune environment, the osteosarcoma stem cells could be important players in the metastatic process.

Prognostic Value of The Ratio of Maximum To Minimum Diameter of Primary Tumor In Metastatic Clear Cell Renal Cell Carcinoma

Background: Several models and markers were developed and found to predict outcome of advanced renal cell carcinoma. This study aimed to evaluate the prognostic value of the ratio of maximum to minimum tumor diameter (ROD) in metastatic clear cell renal cell carcinoma (mccRCC).Methods: Patients with mccRCC (n=213) treated with sunitinib from January 2008 to December 2018 were identified. Cut-off value for ROD was determined using receiver operating characteristic. Patients with different ROD scores were grouped and evaluated. Survival outcomes were estimated by Kaplan-Meier method.Results: The optimal ROD cutoff value of 1.34 was determined for progression free survival (PFS) and overall survival (OS). Patients in ROD≥1.34 group had shorter PFS (9.6 versus 17.7 months, p<0.001) and OS (25.5 versus 32.6 months, p<0.001) than patients in ROD<1.34 group. After adjustment for other factors, multivariate analysis showed ROD≥1.34 was an independent prognostic factor for PFS (p<0.001) and OS (p=0.006). Patients in ROD³1.34 group presented higher proportions of T3/4 stage (92.9% versus 7.1%, p=0.012), WHO/ISUP grade III/IV (72.0% versus 28.0%, p=0.010), tumor necrosis (71.0% versus 29.0%, p=0.039), sarcomatoid differentiation (79.1% versus 20.9%, p=0.007), poor MSKCC risk score (78.4% versus 21.6%, p<0.001) and poor IMDC risk score (74.4% versus 25.6%, p<0.001) than ROD<1.34 group.Conclusion: Primary tumor with higher ROD was an independently prognostic factor for both PFS and OS in patients with mccRCC who received targeted therapy. Higher ROD was also associated with high T stage, high WHO/ISUP grade, sarcomatoid features, tumor necrosis, poor MSKCC and IMDC risk score.