ADAMTS16 mutations sensitize ovarian cancer cells to platinum-based chemotherapy

Body Weight Correlates with Molecular Variances in Patients with Cancer

Overweight and obesity are identified by a high body mass index (BMI) and carry significant health risks due to associated comorbidities. Although epidemiologic data connect overweight/obesity with 13 cancer types, a better understanding of the molecular mechanisms underlying this correlation is needed to improve prevention and treatment strategies. In this study, we conducted a comprehensive analysis of molecular differences between overweight or obese patients and normal weight patients across 14 different cancer types from The Cancer Genome Atlas. Using the propensity score weighting algorithm to control for confounding factors, obesity-specific mutational features were identified, such as higher mutation burden in rectal cancer and biased mutational signatures in other cancers. Differentially expressed genes (DEG) in tumors from patients with overweight/obesity were predominantly upregulated and enriched in inflammatory and hormone-related pathways. These DEGs were significantly associated with survival rates in various cancer types, highlighting the impact of elevated body fat on gene expression profiles and clinical outcomes in patients with cancer. Interestingly, while high BMI seemed to have a negative impact on most cancer types, the normal weight-biased mutational and gene expression patterns indicated overweight/obesity may be beneficial in endometrial cancer, suggesting the presence of an "obesity paradox" in this context. Body fat also significantly impacted the tumor microenvironment by modulating immune cell infiltration, underscoring the importance of understanding the interplay between weight and immune response in cancer progression. Together, this study systematically elucidates the molecular differences corresponding to body weight in multiple cancer types, offering potentially critical insights for developing precision therapy for patients with cancer.

SIGNIFICANCE

Elucidation of the complex interplay between body weight and the molecular landscape of cancer could potentially guide tailored therapies and improve patient management amid the global obesity crisis.

Prediction of Ovarian Cancer Response to Therapy Based on Deep Learning Analysis of Histopathology Images

BACKGROUND

Ovarian cancer remains the leading gynecological cause of cancer mortality. Predicting the sensitivity of ovarian cancer to chemotherapy at the time of pathological diagnosis is a goal of precision medicine research that we have addressed in this study using a novel deep-learning neural network framework to analyze the histopathological images.

METHODS

We have developed a method based on the Inception V3 deep learning algorithm that complements other methods for predicting response to standard platinum-based therapy of the disease. For the study, we used histopathological H&E images (pre-treatment) of high-grade serous carcinoma from The Cancer Genome Atlas (TCGA) Genomic Data Commons portal to train the Inception V3 convolutional neural network system to predict whether cancers had independently been labeled as sensitive or resistant to subsequent platinum-based chemotherapy. The trained model was then tested using data from patients left out of the training process. We used receiver operating characteristic (ROC) and confusion matrix analyses to evaluate model performance and Kaplan-Meier survival analysis to correlate the predicted probability of resistance with patient outcome. Finally, occlusion sensitivity analysis was piloted as a start toward correlating histopathological features with a response.

RESULTS

The study dataset consisted of 248 patients with stage 2 to 4 serous ovarian cancer. For a held-out test set of forty patients, the trained deep learning network model distinguished sensitive from resistant cancers with an area under the curve (AUC) of 0.846 ± 0.009 (SE). The probability of resistance calculated from the deep-learning network was also significantly correlated with patient survival and progression-free survival. In confusion matrix analysis, the network classifier achieved an overall predictive accuracy of 85% with a sensitivity of 73% and specificity of 90% for this cohort based on the Youden-J cut-off. Stage, grade, and patient age were not statistically significant for this cohort size. Occlusion sensitivity analysis suggested histopathological features learned by the network that may be associated with sensitivity or resistance to the chemotherapy, but multiple marker studies will be necessary to follow up on those preliminary results.

CONCLUSIONS

This type of analysis has the potential, if further developed, to improve the prediction of response to therapy of high-grade serous ovarian cancer and perhaps be useful as a factor in deciding between platinum-based and other therapies. More broadly, it may increase our understanding of the histopathological variables that predict response and may be adaptable to other cancer types and imaging modalities.

Amino acid motifs for the identification of novel protein interactants

Biological systems consist of multiple components of different physical and chemical properties that require complex and dynamic regulatory loops to function efficiently. The discovery of ever more novel interacting sites in complex proteins suggests that we are only beginning to understand how cellular and biological functions are integrated and tuned at the molecular and systems levels. Here we review recently discovered interacting sites which have been identified through rationally designed amino acid motifs diagnostic for specific molecular functions, including enzymatic activities and ligand-binding properties. We specifically discuss the nature of the latter using as examples, novel hormone recognition and gas sensing sites that occur in moonlighting protein complexes. Drawing evidence from the current literature, we discuss the potential implications at the cellular, tissue, and/or organismal levels of such non-catalytic interacting sites and provide several promising avenues for the expansion of amino acid motif searches to discover hitherto unknown protein interactants and interaction networks. We believe this knowledge will unearth unexpected functions in both new and well-characterized proteins, thus filling existing conceptual gaps or opening new avenues for applications either as drug targets or tools in pharmacology, cell biology and bio-catalysis. Beyond this, motif searches may also support the design of novel, effective and sustainable approaches to crop improvements and the development of new therapeutics.

The Novel Protein ADAMTS16 Promotes Gastric Carcinogenesis by Targeting IFI27 through the NF-κb Signaling Pathway

A disintegrin and metalloproteinase with thrombospondin motifs 16 (ADAMTS16) has been reported to be involved in the pathogenesis of solid cancers. However, its role in gastric cancer (GC) is unclear. In this study, the role of ADAMTS16 in gastric cancer was investigated. The effects of ADAMTS16 on cell migration, invasion, and proliferation were investigated by functional experiments in vivo and in vitro. Downstream signal pathways of ADAMTS16 were confirmed by using bioinformatics analysis, co-immunoprecipitation, and immunofluorescence. Meanwhile, bioinformatics analysis, qRT-PCR, western blot, and dual-luciferase reporter gene analysis assays were used to identify ADAMTS16 targets. The expression of ADAMTS16 in GC was analyzed in public datasets. The expression of ADAMTS16 and its correlations with the clinical characteristics of GC were investigated by immunohistochemistry. Ectopic ADAMTS16 expression significantly promoted tumor cell migration, invasion, and growth. Bioinformatics analysis and western blot showed that ADAMTS16 upregulated the IFI27 protein through the NF-κb pathway, which was confirmed by immunofluorescence and western blot. Dual-luciferase reporter gene analysis identified a binding site between P65 and IFI27 that may be directly involved in the transcriptional regulation of IFI27. IFI27 knockdown reversed the promoting effect of ADAMTS16 on cell invasion, migration, and proliferation indicating that ADAMTS16 acts on GC cells by targeting the NF-κb/IFI27 axis. ADAMTS16 was associated with poor prognosis in clinical characteristics. ADAMTS16 promotes cell migration, invasion, and proliferation by targeting IFI27 through the NF-κB pathway and is a potential progressive and survival biomarker of GC.

Advances in ADAMTS biomarkers

A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS) are major mediators in extracellular matrix (ECM) turnover and have gained increasing interest over the last years as major players in ECM remodeling during tissue homeostasis and the development of diseases. Although, ADAMTSs are recognized in playing important roles during tissue remodeling, and loss of function in various member of the ADAMTS family could be associated with the development of numerous diseases, limited knowledge is available about their specific substrates and mechanism of action. In this chapter, we will review current knowledge about ADAMTSs and their use as disease biomarkers.

Resistance of B-Cell Lymphomas to CAR T-Cell Therapy Is Associated With Genomic Tumor Changes Which Can Result in Transdifferentiation

Despite the impressive efficacy of chimeric antigen receptor (CAR) T-cell therapy (CART) in B-cell non-Hodgkin lymphomas, durable responses are uncommon. The histopathologic and molecular features associated with treatment failure are still largely unknown. Therefore, we have analyzed 19 sequential tumor samples from 9 patients, prior anti-CD19 CART (pre-CART) and at relapse (post-CART), using immunohistochemistry, fluorescence in situ hybridization, array comparative genomic hybridization, next-generation DNA and RNA sequencing, and genome-scale DNA methylation. The initial diagnosis was diffuse large B-cell lymphoma (n=6), double-hit high-grade B-cell lymphoma (n=1), and Burkitt lymphoma (n=2). Histopathologic features were mostly retained at relapse in 7/9 patients, except the frequent loss of 1 or several B-cell markers. The remaining 2 cases (1 diffuse large B-cell lymphoma and 1 Burkitt lymphoma) displayed a dramatic phenotypic shift in post-CART tumors, with the drastic downfall of B-cell markers and emergence of T-cell or histiocytic markers, despite the persistence of identical clonal immunoglobulin gene rearrangements. The post-CART tumor with aberrant T-cell phenotype showed reduced mRNA expression of most B-cell genes with increased methylation of their promoter. Fluorescence in situ hybridization and comparative genomic hybridization showed global stability of chromosomal alterations in all paired samples, including 17p/TP53 deletions. New pathogenic variants acquired in post-CART samples included mutations triggering the PI3K pathway (PIK3R1, PIK3R2, PIK3C2G) or associated with tumor aggressiveness (KRAS, INPP4B, SF3B1, SYNE1, TBL1XR1). These results indicate that CART-resistant B-cell non-Hodgkin lymphomas display genetic remodeling, which may result in profound dysregulation of B-cell differentiation. Acquired mutations in the PI3K and KRAS pathways suggest that some targeted therapies could be useful to overcome CART resistance.

Mutational drivers of cancer cell migration and invasion

Genomic instability and mutations underlie the hallmarks of cancer-genetic alterations determine cancer cell fate by affecting cell proliferation, apoptosis and immune response, and increasing data show that mutations are involved in metastasis, a crucial event in cancer progression and a life-threatening problem in cancer patients. Invasion is the first step in the metastatic cascade, when tumour cells acquire the ability to move, penetrate into the surrounding tissue and enter lymphatic and blood vessels in order to disseminate. A role for genetic alterations in invasion is not universally accepted, with sceptics arguing that cellular motility is related only to external factors such as hypoxia, chemoattractants and the rigidity of the extracellular matrix. However, increasing evidence shows that mutations might trigger and accelerate the migration and invasion of different types of cancer cells. In this review, we summarise data from published literature on the effect of chromosomal instability and genetic mutations on cancer cell migration and invasion.

Infiltration of T cells promotes the metastasis of ovarian cancer cells via the modulation of metastasis-related genes and PD-L1 expression

Due to its high ability to disseminate, ovarian cancer remains one of the largest threats to women's health, worldwide. Evidence showed that the immune cells infiltrating the tumor microenvironment are crucial in mediating metastasis. Therefore, it is necessary to understand which types of immune cells are involved in metastasis, and to determine the mechanisms by which they influence the process. By immunohistochemistry, we found that higher concentrations of intratumoral CD8⁺ T cells were found to be correlated with an advanced grade and stage of ovarian cancer. Additionally, the infiltration of stromal CD8⁺ T cells was also significantly higher in tissues with advanced stages and metastatic tumors. A positive correlation between the infiltration of FoxP3⁺ Treg cells and histological grade was also observed, regardless of location. PD-L1 expression in metastatic tumors was also higher than that in paired primary ovarian tumors. Transwell migration and invasion assays revealed the increased migration and invasion of ovarian cancer cell lines (A2780CP and ES2) and ascites-derived ovarian cancer cells following co-culturing with CD8⁺ T cells. Enhanced expression of MMP-9, uPA, VEGF, bFGF, IL-8, IL-10, and PD-L1 by cancer cells following co-culturing with CD8⁺ T cells were also detected by qPCR, ELISA or flow cytometry. In conclusion, our findings suggest that the infiltrated T cells could promote the development of ovarian cancer, and provide another mechanism of immune evasion mediated by T cells.

A Selective Extracellular Matrix Proteomics Approach Identifies Fibronectin Proteolysis by A Disintegrin-like and Metalloprotease Domain with Thrombospondin Type 1 Motifs (ADAMTS16) and Its Impact on Spheroid Morphogenesis

Secreted and cell-surface proteases are major mediators of extracellular matrix (ECM) turnover, but their mechanisms and regulatory impact are poorly understood. We developed a mass spectrometry approach using a cell-free ECM produced in vitro to identify fibronectin (FN) as a novel substrate of the secreted metalloprotease ADAMTS16. ADAMTS16 cleaves FN between its (I)5 and (I)6 modules, releasing the N-terminal 30 kDa heparin-binding domain essential for FN self-assembly. ADAMTS16 impairs FN fibrillogenesis as well as fibrillin-1 and tenascin-C assembly, thus inhibiting formation of a mature ECM by cultured fibroblasts. Furthermore ADAMTS16 has a marked morphogenetic impact on spheroid formation by renal tubule-derived MDCKI cells. The N-terminal FN domain released by ADAMTS16 up-regulates MMP3, which cleaves the (I)5-(I)6 linker of FN similar to ADAMTS16, therefore creating a proteolytic feed-forward mechanism. Thus, FN proteolysis not only regulates FN turnover, but also FN assembly, with potential long-term consequences for ECM assembly and morphogenesis.

The Many Facets of Metzincins and Their Endogenous Inhibitors: Perspectives on Ovarian Cancer Progression

Approximately sixty per cent of ovarian cancer patients die within the first five years of diagnosis due to recurrence associated with chemoresistance. The metzincin family of metalloproteinases is enzymes involved in matrix remodeling in response to normal physiological changes and diseased states. Recently, there has been a mounting awareness of these proteinases and their endogenous inhibitors, the tissue inhibitors of metalloproteinases (TIMPs), as superb modulators of cellular communication and signaling regulating key biological processes in cancer progression. This review investigates the role of metzincins and their inhibitors in ovarian cancer. We propose that understanding the metzincins and TIMP biology in ovarian cancer may provide valuable insights in combating ovarian cancer progression and chemoresistance-mediated recurrence in patients.