Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI

Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa aggressiveness, for which a biopsy is required, is fundamental for patient management. Currently, multiparametric (mp) MRI is strongly recommended before biopsy. Quantitative assessment of mpMRI might provide the radiologist with an objective and noninvasive tool for supporting the decision-making in clinical practice and decreasing intra- and inter-reader variability. In this view, high dimensional radiomics features and Machine Learning (ML) techniques, along with Deep Learning (DL) methods working on raw images directly, could assist the radiologist in the clinical workflow. The aim of this study was to develop and validate ML/DL frameworks on mpMRI data to characterize PCas according to their aggressiveness. We optimized several ML/DL frameworks on T2w, ADC and T2w+ADC data, using a patient-based nested validation scheme. The dataset was composed of 112 patients (132 peripheral lesions with Prostate Imaging Reporting and Data System (PI-RADS) score ≥ 3) acquired following both PI-RADS 2.0 and 2.1 guidelines. Firstly, ML/DL frameworks trained and validated on PI-RADS 2.0 data were tested on both PI-RADS 2.0 and 2.1 data. Then, we trained, validated and tested ML/DL frameworks on a multi PI-RADS dataset. We reported the performances in terms of Area Under the Receiver Operating curve (AUROC), specificity and sensitivity. The ML/DL frameworks trained on T2w data achieved the overall best performance. Notably, ML and DL frameworks trained and validated on PI-RADS 2.0 data obtained median AUROC values equal to 0.750 and 0.875, respectively, on unseen PI-RADS 2.0 test set. Similarly, ML/DL frameworks trained and validated on multi PI-RADS T2w data showed median AUROC values equal to 0.795 and 0.750, respectively, on unseen multi PI-RADS test set. Conversely, all the ML/DL frameworks trained and validated on PI-RADS 2.0 data, achieved AUROC values no better than the chance level when tested on PI-RADS 2.1 data. Both ML/DL techniques applied on mpMRI seem to be a valid aid in predicting PCa aggressiveness. In particular, ML/DL frameworks fed with T2w images data (objective, fast and non-invasive) show good performances and might support decision-making in patient diagnostic and therapeutic management, reducing intra- and inter-reader variability.

G9a Knockdown Suppresses Cancer Aggressiveness by Facilitating Smad Protein Phosphorylation through Increasing BMP5 Expression in Luminal A Type Breast Cancer

Epigenetic abnormalities affect tumor progression, as well as gene expression and function. Among the diverse epigenetic modulators, the histone methyltransferase G9a has been focused on due to its role in accelerating tumorigenesis and metastasis. Although epigenetic dysregulation is closely related to tumor progression, reports regarding the relationship between G9a and its possible downstream factors regulating breast tumor growth are scarce. Therefore, we aimed to verify the role of G9a and its presumable downstream regulators during malignant progression of breast cancer. G9a-depleted MCF7 and T47D breast cancer cells exhibited suppressed motility, including migration and invasion, and an improved response to ionizing radiation. To identify the possible key factors underlying these effects, microarray analysis was performed, and a TGF-β superfamily member, BMP5, was selected as a prominent target gene. It was found that BMP5 expression was markedly increased by G9a knockdown. Moreover, reduction in the migration/invasion ability of MCF7 and T47D breast cancer cells was induced by BMP5. Interestingly, a G9a-depletion-mediated increase in BMP5 expression induced the phosphorylation of Smad proteins, which are the intracellular signaling mediators of BMP5. Accordingly, we concluded that the observed antitumor effects may be based on the G9a-depletion-mediated increase in BMP5 expression and the consequent facilitation of Smad protein phosphorylation.

Comparative O-GlcNAc Proteomic Analysis Reveals a Role of O-GlcNAcylated SAM68 in Lung Cancer Aggressiveness

O-GlcNAcylation is a reversible and dynamic post-translational protein modification catalyzed by O-GlcNAc transferase (OGT). Despite the reported association of O-GlcNAcylation with cancer metastasis, the O-GlcNAc proteome profile for cancer aggressiveness remains largely uncharacterized. Here, we report our comparative O-GlcNAc proteome profiling of two differentially invasive lung adenocarcinoma cell lines, which identified 158 down-regulated and 106 up-regulated candidates in highly invasive cells. Among these differential proteins, a nuclear RNA-binding protein, SAM68 (SRC associated in mitosis of 68 kDa), was further investigated. Results showed that SAM68 is O-GlcNAcylated and may interact with OGT in the nucleus. Eleven O-GlcNAcylation sites were identified, and data from mutant analysis suggested that multiple serine residues in the N-terminal region are important for O-GlcNAcylation and the function of SAM68 in modulating cancer cell migration and invasion. Analysis of clinical specimens found that high SAM68 expression was associated with late cancer stages, and patients with high-OGT/high-SAM68 expression in their tumors had poorer overall survival compared to those with low-OGT/low-SAM68 expression. Our study revealed an invasiveness-associated O-GlcNAc proteome profile and connected O-GlcNAcylated SAM68 to lung cancer aggressiveness.

Determination of Exosome Mitochondrial DNA as a Biomarker of Renal Cancer Aggressiveness

Here, the role of non-invasive biomarkers in liquid biopsy was evaluated, mainly in exosomes and mitochondrial DNA (mtDNA) as promising, novel, and stable biomarkers for renal cell carcinoma (RCC). A total of 140 fractions (named from B to F) obtained by ultracentrifugations of whole blood samples from 28 individuals (13 patients and 15 controls) were included. Nanoparticle Tracking Analysis (NTA) was conducted to characterized exosomal fraction. Subsequently, an analysis of digital PCR (dPCR) using the QuantStudio™ 3D Digital PCR platform was performed and the quantification of mtDNA copy number by QuantStudioTM 12K Flex Real-Time PCR System (qPCR) was developed. Moreover, Next Generation Sequencing (NGS) analyses were included using MiSeq system (Illumina, San Diego, CA, USA). An F fraction, which contains all exosome data and all mitochondrial markers, was identified in dPCR and qPCR with statistically significant power (adjusted p values ≤ 0.03) when comparing cases and controls. Moreover, present analysis in mtDNA showed a relevant significance in RCC aggressiveness. To sum up, this is the first time a relation between exosomal mtDNA markers and clinical management of RCC is analyzed. We suggest a promising strategy for future liquid biopsy RCC analysis, although more analysis should be performed prior to application in routine clinical practice.

In Vivo Anticancer Activity of AZD3965: A Systematic Review

Proliferating cancer cells have high energy demands, which is mainly obtained through glycolysis. The transmembrane trafficking of lactate, a major metabolite produced by glycolytic cancer cells, relies on monocarboxylate transporters (MCTs). MCT1 optimally imports lactate, although it can work bidirectionally, and its activity has been linked to cancer aggressiveness and poor outcomes. AZD3965, a specific MCT1 inhibitor, was tested both in vitro and in vivo, with encouraging results; a phase I clinical trial has already been undertaken. Thus, analysis of the experimental evidence using AZD3965 in different cancer types could give valuable information for its clinical use. This systematic review aimed to assess the in vivo anticancer activity of AZD3965 either alone (monotherapy) or with other interventions (combination therapy). Study search was performed in nine different databases using the keywords “AZD3965 in vivo” as search terms. The results show that AZD3965 successfully decreased tumor growth and promoted intracellular lactate accumulation, which confirmed its effectiveness, especially in combined therapy. These results support the setup of clinical trials, but other important findings, namely AZD3965 enhanced activity when given in combination with other therapies, or MCT4-induced treatment resistance, should be further considered in the clinical trial design to improve therapy response.

Epidemiological trends and trajectories of MAFLD-associated hepatocellular carcinoma 2002–2033: the ITA.LI.CA database

BackgroundMetabolic dysfunction-associated fatty liver disease (MAFLD) represents a new inclusive definition of the whole spectrum of liver diseases associated to metabolic disorders. The main objective of this study was to compare patients with MAFLD and non-MAFLD with hepatocellular carcinoma (HCC) included in a nationally representative cohort.MethodsWe analysed 6882 consecutive patients with HCC enrolled from 2002 to 2019 by 23 Italian Liver Cancer centres to compare epidemiological and future trends in three subgroups: pure, single aetiology MAFLD (S-MAFLD); mixed aetiology MAFLD (metabolic and others, M-MAFLD); and non-MAFLD HCC.ResultsMAFLD was diagnosed in the majority of patients with HCC (68.4%). The proportion of both total MAFLD and S-MAFLD HCC significantly increased over time (from 50.4% and 3.6% in 2002–2003, to 77.3% and 28.9% in 2018–2019, respectively, p<0.001). In Italy S-MAFLD HCC is expected to overcome M-MAFLD HCC in about 6 years. Patients with S-MAFLD HCC were older, more frequently men and less frequently cirrhotic with clinically relevant portal hypertension and a surveillance-related diagnosis. They had more frequently large tumours and extrahepatic metastases. After weighting, and compared with patients with non-MAFLD, S-MAFLD and M-MAFLD HCC showed a significantly lower overall (p=0.026, p=0.004) and HCC-related (p<0.001, for both) risk of death. Patients with S-MAFLD HCC showed a significantly higher risk of non-HCC-related death (p=0.006).ConclusionsThe prevalence of MAFLD HCC in Italy is rapidly increasing to cover the majority of patients with HCC. Despite a less favourable cancer stage at diagnosis, patients with MAFLD HCC have a lower risk of HCC-related death, suggesting reduced cancer aggressiveness.

Chromosome compartmentalization alterations in prostate cancer cell lines model disease progression

Prostate cancer aggressiveness and metastatic potential are influenced by gene expression and genomic aberrations, features that can be influenced by the 3D structure of chromosomes inside the nucleus. Using chromosome conformation capture (Hi-C), we conducted a systematic genome architecture comparison on a cohort of cell lines that model prostate cancer progression, from normal epithelium to bone metastasis. We describe spatial compartment identity (A-open versus B-closed) changes with progression in these cell lines and their relation to gene expression changes in both cell lines and patient samples. In particular, 48 gene clusters switch from the B to the A compartment, including androgen receptor, WNT5A, and CDK14. These switches are accompanied by changes in the structure, size, and boundaries of topologically associating domains (TADs). Further, compartment changes in chromosome 21 are exacerbated with progression and may explain, in part, the genesis of the TMPRSS2-ERG translocation. These results suggest that discrete 3D genome structure changes play a deleterious role in prostate cancer progression.

Metabolic Pathways and Targets in Chondrosarcoma

Chondrosarcomas are the second most common primary bone malignancy. Chondrosarcomas are characterized by the production of cartilaginous matrix and are generally resistant to radiation and chemotherapy and the outcomes are overall poor. Hence, there is strong interest in determining mechanisms of cancer aggressiveness and therapeutic resistance in chondrosarcomas. There are metabolic alterations in chondrosarcoma that are linked to the epigenetic state and tumor microenvironment that drive treatment resistance. This review focuses on metabolic changes in chondrosarcoma, and the relationship between signaling via isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), hedgehog, PI3K-mTOR-AKT, and SRC, as well as histone acetylation and angiogenesis. Also, potential treatment strategies targeting metabolism will be discussed including potential synergy with immunotherapies.