Journal of Translational Medicine

Speckle-type POZ protein (SPOP) is an E3 ubiquitin ligase adaptor protein that functions as a potential tumor suppressor, and SPOP mutations have been identified in ~10% of human prostate cancers. However, it remains unclear if mutant SPOP proteins can be utilized as biomarkers for early detection, diagnosis, prognosis or targeted therapy of prostate cancer. Moreover, the SPOP mutation sites are distributed in a relatively short region with multiple lysine residues, posing significant challenges for bottom-up proteomics analysis of the SPOP mutations. To address this issue, PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing)-SRM (selected reaction monitoring) mass spectrometry assays have been developed for quantifying wild-type SPOP protein and 11 prostate cancer-derived SPOP mutations. Despite inherent limitations due to amino acid sequence constraints, all the PRISM-SRM assays developed using Arg-C digestion showed a linear dynamic range of at least two orders of magnitude, with limits of quantification ranged from 0.1 to 1 fmol/μg of total protein in the cell lysate. Applying these SRM assays to analyze HEK293T cells with and without expression of the three most frequent SPOP mutations in prostate cancer (Y87N, F102C or F133V) led to confident detection of all three SPOP mutations in corresponding positive cell lines but not in the negative cell lines. Expression of the F133V mutation and wild-type SPOP was at much lower levels compared to that of F102C and Y87N mutations; however, at present, it is unknown if this also affects the biological activity of the SPOP protein. In summary, PRISM-SRM enables multiplexed, isoform-specific detection of mutant SPOP proteins in cell lysates, providing significant potential in biomarker development for prostate cancer.

Colorectal cancer (CRC) is the third most common cancer and leading cause of cancer-related deaths worldwide. Aberrant cellular metabolism is a hallmark of cancer cells, and disturbed metabolism showed clinical significance in CRC. The membrane-associated RING-CH 8 (MARCH8) protein, the first MARCH E3 ligase, plays an oncogenic role and serves as a prognostic marker in multiple cancers, however, the role of MARCH8 in CRC is unclear. In the present study, we aimed to investigate the biomarkers and their underlying mechanism for CRC. In this study, we first examined the function of MARCH8 in CRC by analysing public database. Besides, we performing gene silencing studies and generating cellular overexpression and xenograft models. Then its protein substrate was identified and validated. In addition, the expression of MARCH8 was investigated in tissue samples from CRC patients, and the molecular basis for decreased expression was analysed. Systematic analysis reveals that MARCH8 is a beneficial prognostic marker in CRC. In CRC, MARCH8 exhibited tumor-suppressive activity both in vivo and in vitro. Furthermore, we found that MARCH8 is negatively correlated with hexokinase 2 (HK2) protein in CRC patients. MARCH8 regulates glycolysis and promotes ubiquitination-mediated proteasome degradation to reduces HK2 protein levels. Then HK2 inhibitor partially rescues the effect of MARCH8 knockdown in CRC. Poised chromatin and elevated miR-32 repressed MARCH8 expression. In summary, we propose that in CRC, poised chromatin and miR-32 decrease the expression of MARCH8, further bind and add ubiquitin, induce HK2 degradation, and finally repress glycolysis to promote tumor suppressors in CRC.

Recent advances in animal models of glioma have facilitated a better understanding of biological mechanisms underlying gliomagenesis and glioma progression. The limitations of existing therapy, including surgery, chemotherapy, and radiotherapy, have prompted numerous investigators to search for new therapeutic approaches to improve quantity and quality of survival from these aggressive lesions. One of these approaches involves triggering a tumor specific immune response. However, a difficulty in this approach is the the scarcity of animal models of primary CNS neoplasms which faithfully recapitulate these tumors and their interaction with the host's immune system. In this article, we review the existing methods utilized to date for modeling gliomas in rodents, with a focus on the known as well as potential immunological aspects of these models. As this review demonstrates, many of these models have inherent immune system limitations, and the impact of these limitations on studies on the influence of pre-clinical therapeutics testing warrants further attention.

Temozolomide (TMZ) is the preferred chemotherapy strategy for glioma therapy. As a second-generation alkylating agent, TMZ provides superior oral bio-availability. However, limited response rate (less than 50%) and high incidence of drug resistance seriously restricts TMZ’s application, there still lack of strategies to increase the chemotherapy sensitivity. Luci-GL261 glioma orthotopic xenograft model combined bioluminescence imaging was utilized to evaluate the anti-tumor effect of TMZ and differentiate TMZ sensitive (S)/non-sensitive (NS) individuals. Integrated microbiomics and metabolomics analysis was applied to disentangle the involvement of gut bacteria in TMZ sensitivity. Spearman’s correlation analysis was applied to test the association between fecal bacteria levels and pharmacodynamics indices. Antibiotics treatment combined TMZ treatment was used to confirm the involvement of gut microbiota in TMZ response. Flow cytometry analysis, ELISA and histopathology were used to explore the potential role of immunoregulation in gut microbiota mediated TMZ response. Firstly, gut bacteria composition was significantly altered during glioma development and TMZ treatment. Meanwhile, in vivo anti-cancer evaluation suggested a remarkable difference in chemotherapy efficacy after TMZ administration. Moreover, 16s rRNA gene sequencing and non-targeted metabolomics analysis revealed distinct different gut microbiota and immune infiltrating state between TMZ sensitive and non-sensitive mice, while abundance of differential gut bacteria and related metabolites was significantly correlated with TMZ pharmacodynamics indices. Further verification suggested that gut microbiota deletion by antibiotics treatment could accelerate glioma development, attenuate TMZ efficacy and inhibit immune cells (macrophage and CD8α+ T cell) recruitment. The current study confirmed the involvement of gut microbiota in glioma development and individualized TMZ efficacy via immunomodulation, hence gut bacteria may serve as a predictive biomarker as well as a therapeutic target for clinical TMZ application.

Computational models are increasingly used in high-impact decision making in science, engineering, and medicine. The National Aeronautics and Space Administration (NASA) uses computational models to perform complex experiments that are otherwise prohibitively expensive or require a microgravity environment. Similarly, the Food and Drug Administration (FDA) and European Medicines Agency (EMA) have began accepting models and simulations as forms of evidence for pharmaceutical and medical device approval. It is crucial that computational models meet a standard of credibility when using them in high-stakes decision making. For this reason, institutes including NASA, the FDA, and the EMA have developed standards to promote and assess the credibility of computational models and simulations. However, due to the breadth of models these institutes assess, these credibility standards are mostly qualitative and avoid making specific recommendations. On the other hand, modeling and simulation in systems biology is a narrower domain and several standards are already in place. As systems biology models increase in complexity and influence, the development of a credibility assessment system is crucial. Here we review existing standards in systems biology, credibility standards in other science, engineering, and medical fields, and propose the development of a credibility standard for systems biology models.