Many studies have shown that uridylation, a post- transcriptional modification that results in the addition of non-templated uridines to the 3' ends of various RNAs, effect the stability of these transcripts. Belonging to the same family as canonical nucleotidyl transferases such as the well characterized poly(A) polymerase, non- canonical nucleotidyl-transferases (nc-rNTrs) are template -independent polymerases capapble of catalyzing the transfer of single or multiple nucleotide residues to the 3' ends of various RNAs. Here we identified the in vitro activities of six of the seven human nc-rNTrs. We found that TUTases 4 and 7 are prefer to add uridines, while TUTases 2, 3 and 5 prefer to add adenines. Furthermore, we studied uridylation of microRNA-directed 5' cleavage products in vivo. Our preliminary results identified TUTase 2 and 7 as the enzymes that may be responsible for the uridylation of the 5' cleavage fragment. Knockdown of these enzymes in combination led to a decrease in uridylated transcripts. Here, we laid the groundwork for future experiments that will help elucidate the effects of uridylation on mRNA stability

Treatment of early diabetes mellitus, the most common cause of chronic kidney disease (CKD), may prevent or slow the progression of diabetic nephropathy and lower mortality and the incidence of cardiovascular disease in the general diabetic population and in patients with early stages of CKD. It is unclear whether glycemic control in patients with advanced CKD, including those with end-stage renal disease (ESRD) who undergo maintenance dialysis treatment is beneficial. Aside from the uncertain benefits of treatment in ESRD, hypoglycemic interventions in this population are also complicated by the complex changes in glucose homeostasis related to decreased kidney function and to dialytic therapies, occasionally leading to spontaneous resolution of hyperglycemia and normalization of hemoglobin A1c levels, a condition which might be termed "burnt-out diabetes." Further difficulties in ESRD are posed by the complicated pharmacokinetics of antidiabetic medications and the serious flaws in our available diagnostic tools used for monitoring long-term glycemic control. We review the physiology and pathophysiology of glucose homeostasis in advanced CKD and ESRD, the available antidiabetic medications and their specifics related to kidney function, and the diagnostic tools used to monitor the severity of hyperglycemia and the therapeutic effects of available treatments, along with their deficiencies in ESRD. We also review the concept of burnt-out diabetes and summarize the findings of studies that examined outcomes related to glycemic control in diabetic ESRD patients, and emphasize areas in need of further research.

Objectives

We investigated whether androgen deprivation therapy (ADT) in prostate cancer patients was associated with a decreased risk for second primary lung cancer in US veterans.

Methods

Prostate cancer diagnoses in the US Veterans Affairs Cancer Registry between 1999 and 2008 were identified. Use of hormonal therapy and diagnoses of second primary lung cancer were determined from the registry. Synchronous prostate and lung cancers, defined as 2 diagnoses made within 1 year, were excluded from the analysis. Cancer-free survival was estimated using the Kaplan-Meier method and hazard ratios were estimated using Cox proportional hazard models.

Results

Among the 63,141 identified patients with prostate cancer, 18,707 subjects were eligible for the study. Hormonal therapy was used in 38% of patients and the median follow-up period was 28 months. ADT use was associated with longer lung cancer-free survival in prostate cancer patients (log-rank p=0.01). After adjusting for age, race, smoking and prostate cancer stage, ADT use was associated with decreased lung cancer risk by 15, 21, and 24% after 1, 2, and 3 years, respectively.

Conclusions

ADT in prostate cancer patients may be associated with decreased second primary lung cancer risk among US veterans.

Objectives

Survival machine learning (ML) has been suggested as a useful approach for forecasting future events, but a growing concern exists that ML models have the potential to cause racial disparities through the data used to train them. This study aims to develop race/ethnicity-specific survival ML models for Hispanic and black women diagnosed with breast cancer to examine whether race/ethnicity-specific ML models outperform the general models trained with all races/ethnicity data.

Methods

We used the data from the US National Cancer Institute's Surveillance, Epidemiology and End Results programme registries. We developed the Hispanic-specific and black-specific models and compared them with the general model using the Cox proportional-hazards model, Gradient Boost Tree, survival tree and survival support vector machine.

Results

A total of 322 348 female patients who had breast cancer diagnoses between 1 January 2000 and 31 December 2017 were identified. The race/ethnicity-specific models for Hispanic and black women consistently outperformed the general model when predicting the outcomes of specific race/ethnicity.

Discussion

Accurately predicting the survival outcome of a patient is critical in determining treatment options and providing appropriate cancer care. The high-performing models developed in this study can contribute to providing individualised oncology care and improving the survival outcome of black and Hispanic women.

Conclusion

Predicting the individualised survival outcome of breast cancer can provide the evidence necessary for determining treatment options and high-quality, patient-centred cancer care delivery for under-represented populations. Also, the race/ethnicity-specific ML models can mitigate representation bias and contribute to addressing health disparities.

OBJECTIVE: The study aimed to develop natural language processing (NLP) algorithms to automate extracting patient-centred breast cancer treatment outcomes from clinical notes in electronic health records (EHRs), particularly for women from under-represented populations. METHODS: The study used clinical notes from 2010 to 2021 from a tertiary hospital in the USA. The notes were processed through various NLP techniques, including vectorisation methods (term frequency-inverse document frequency (TF-IDF), Word2Vec, Doc2Vec) and classification models (support vector classification, K-nearest neighbours (KNN), random forest (RF)). Feature selection and optimisation through random search and fivefold cross-validation were also conducted. RESULTS: The study annotated 100 out of 1000 clinical notes, using 970 notes to build the text corpus. TF-IDF and Doc2Vec combined with RF showed the highest performance, while Word2Vec was less effective. RF classifier demonstrated the best performance, although with lower recall rates, suggesting more false negatives. KNN showed lower recall due to its sensitivity to data noise. DISCUSSION: The study highlights the significance of using NLP in analysing clinical notes to understand breast cancer treatment outcomes in under-represented populations. The TF-IDF and Doc2Vec models were more effective in capturing relevant information than Word2Vec. The study observed lower recall rates in RF models, attributed to the datasets imbalanced nature and the complexity of clinical notes. CONCLUSION: The study developed high-performing NLP pipeline to capture treatment outcomes for breast cancer in under-represented populations, demonstrating the importance of document-level vectorisation and ensemble methods in clinical notes analysis. The findings provide insights for more equitable healthcare strategies and show the potential for broader NLP applications in clinical settings.

A number of single nucleotide polymorphisms (SNPs) within the mprF open reading frame (ORF) have been associated with daptomycin-resistance (DAP-R) in Staphylococcus aureus. Such SNPs have been found throughout the mprF ORF, although there are clearly preferred hot spots within this gene frequently linked to DAP-R phenotype. These mprF SNPs are often correlated with a gain-in-function phenotype, either in terms of increased production (synthase activity) and/or enhanced translocation (translocase activity) of lysyl-phosphatidylglycerol (L-PG) within its cell membrane. However, it is unclear if multiple hot spot mprF SNPs can accumulate within mprF ORFs and cause additive elevations of DAP minimum inhibitory concentrations (MICs). In this study, we used a previously well-characterized plasmid complementation system in S. aureus Newman ΔmprF mutant to express: (1) single point-mutated forms of mprF ORFs cloned from two DAP-R S. aureus strains (mprFS295L or mprFT345A) and (2) dual point-mutated forms of mprF ORFs simultaneously harboring SNPs in the central bifunctional domain and synthase domain in MprF, respectively (mprFS295L+L826F or mprFT345A+L826F). The current study revealed that, although individual hot spot point mutations within mprF ORF can recapitulate signature DAP-R-associated phenotypes (i.e., increased DAP MICs, enhanced surface positive charge, and increased L-PG synthesis), accumulation of such hot spot point mutations paradoxically caused reduction in these latter three metrics.

During gastrulation, neural crest cells are specified at the neural plate border, as characterized by Pax7 expression. Using single-cell RNA sequencing coupled with high-resolution in situ hybridization to identify novel transcriptional regulators, we show that chromatin remodeler Hmga1 is highly expressed prior to specification and maintained in migrating chick neural crest cells. Temporally controlled CRISPR-Cas9-mediated knockouts uncovered two distinct functions of Hmga1 in neural crest development. At the neural plate border, Hmga1 regulates Pax7-dependent neural crest lineage specification. At premigratory stages, a second role manifests where Hmga1 loss reduces cranial crest emigration from the dorsal neural tube independent of Pax7. Interestingly, this is rescued by stabilized ß-catenin, thus implicating Hmga1 as a canonical Wnt activator. Together, our results show that Hmga1 functions in a bimodal manner during neural crest development to regulate specification at the neural plate border, and subsequent emigration from the neural tube via canonical Wnt signaling.

Medullary thyroid carcinoma (MTC) is a neuroendocrine tumor mainly caused by mutations in the RET proto-oncogene. We previously demonstrated that depletion of the mitochondrial molecular chaperone, mortalin, can effectively suppress human MTC cells in culture and in mouse xenografts, by disrupting mitochondrial bioenergetics and subsequently inducing apoptosis and RET downregulation. Similar effects were induced by MKT-077, a water-soluble rhodocyanine dye analog known to inhibit mortalin, but with notable toxicity in animals. These observations led us to evaluate recently developed MKT-077 analogs that exhibited higher selectivity to HSP70 proteins and improved bioavailability. We validated the MTC cell-suppressive effects of mortalin depletion in three-dimensional cultures of the human MTC lines, TT, and MZ-CRC-1, and then evaluated different MKT-077 analogs in two- and three-dimensional cell cultures, to show that the MKT-077 analogs, JG-98 and JG-194, effectively and consistently inhibited propagation of TT and MZ-CRC-1 cells in these cultures. Of note, these compounds also effectively suppressed the viability of TT and MZ-CRC-1 progenies resistant to vandetanib and cabozantinib. Moreover, JG-231, an analog with improved microsomal stability, consistently suppressed TT and MZ-CRC-1 xenografts in mice. These data suggest that mortalin inhibition may have therapeutic potential for MTC.