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Background: Early detection of breast cancer is crucial for optimal patient outcomes but cannot always be accomplished based on symptoms or screening mammography. Biomarker-based screening could aid early detection of breast cancer by improving sensitivity and specificity. Exai Bio has developed a novel liquid biopsy technology that detects and analyzes small non-coding RNAs that are cancer specific, termed orphan non-coding RNAs (oncRNAs). Previous work in patients with diagnosed breast cancer demonstrated that changes in oncRNAs in serum reflected treatment response and event-free survival. In this study, we developed an assay that measures oncRNAs in serum to detect breast cancer across the range of tumor stages and sizes. Methods: Previously, a library of ~260,000 oncRNAs from 32 different cancers was compiled based on smRNA sequences found in tumor tissues and largely absent in tumor-adjacent normal tissues from The Cancer Genome Atlas (TCGA). To refine this library for applications in serum, we sequenced smRNA in 31 control serum samples. These smRNA sequences were filtered from the larger library, reducing its size to 250,332 oncRNAs. The diagnostic performance of these oncRNAs was then assessed in an independent cohort of archived serum samples from 96 female patients with clinically diagnosed, untreated breast cancer and 95 age- and sex-matched individuals with no known history of cancer. We sequenced smRNAs at an average depth of 17.7 million 50-bp single-end reads per sample. Of the 250,332 oncRNAs in our library, 171,981 (68.7%) were detected in our independent study cohort. An ensemble of logistic regression models was trained with 5-fold cross-validation, using only those oncRNAs yielding an odds ratio >1 and observed in >6% of samples within each training set. Results: The cohort of 96 breast cancer patients and 95 matched controls had mean ages of 59.4 and 56.3 years, respectively. Area under the receiver operating characteristic curve (AUC) for detecting breast cancer was 0.94 (95% CI, 0.85–0.96). Sensitivities for detecting breast cancer at 95% specificity ranged from 0.75 to 0.87 among the four breast cancer stages, including a sensitivity of 0.81 for tumor stage I (Table 1); and from 0.67 to 0.87 among the four main TNM T categories (Table 2). Sensitivities at 95% specificity were relatively high for small tumors, at 0.75 (95% CI, 0.40–0.97) for T1b (>5mm to ≤10mm; n = 9) and 0.80 (0.68–0.94) for T1c (>10mm to ≤20mm; n = 37). Conclusions We have demonstrated the potential value of an oncRNA-based liquid biopsy assay by showing that oncRNAs can be used to detect breast cancer in serum samples with high sensitivity, and that detection requires fewer reads than are needed with other platforms. Moreover, we found that this oncRNA-based assay performed well in detecting early-stage breast cancer and small tumors. This suggests that an oncRNA-based liquid biopsy assay may be beneficial for early detection of breast cancer. Table 1. Model sensitivity by tumor stage. For the indicated numbers of cases (N), sensitivity and Pearson-Clopper 95% confidence intervals are reported for tumor detection by the oncRNA-based model at 95% specificity by tumor stage, as defined by the AJCC 7th Edition breast cancer staging system. Table 2. Model sensitivity by tumor size. For the indicated numbers of cases (N), sensitivity and Pearson-Clopper 95% confidence intervals are reported for tumor detection by the oncRNA-based model at 95% specificity by TNM T category, as defined by the AJCC 7th Edition breast cancer staging system. Citation Format: Taylor B. Cavazos, Jeffrey Wang, Oluwadamilare I. Afolabi, Alice Huang, Dung Ngoc Lam, Seda Kilinc, Jieyang Wang, Lisa Fish, Xuan Zhao, Andy Pohl, Helen Li, Kimberly H. Chau, Patrick A. Arensdorf, Fereydoun Hormozdiari, Hani Goodarzi, Babak Alipanahi. Orphan non-coding RNAs for early detection of breast cancer with liquid biopsy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-18.

Cancer cells often co-opt post-transcriptional regulatory mechanisms to achieve pathologic expression of gene networks that drive metastasis. Translational control is a major regulatory hub in oncogenesis; however, its effects on cancer progression remain poorly understood. Here, to address this, we used ribosome profiling to compare genome-wide translation efficiencies of poorly and highly metastatic breast cancer cells and patient-derived xenografts. We developed dedicated regression-based methods to analyse ribosome profiling and alternative polyadenylation data, and identified heterogeneous nuclear ribonucleoprotein C (HNRNPC) as a translational controller of a specific mRNA regulon. We found that HNRNPC is downregulated in highly metastatic cells, which causes HNRNPC-bound mRNAs to undergo 3′ untranslated region lengthening and, subsequently, translational repression. We showed that modulating HNRNPC expression impacts the metastatic capacity of breast cancer cells in xenograft mouse models. In addition, the reduced expression of HNRNPC and its regulon is associated with the worse prognosis in breast cancer patient cohorts.

Small non-coding RNAs can be secreted through a variety of mechanisms, including exosomal sorting, in small extracellular vesicles, and within lipoprotein complexes1,2. However, the mechanisms that govern their sorting and secretion are still not well understood. In this study, we present ExoGRU, a machine learning model that predicts small RNA secretion probabilities from primary RNA sequence. We experimentally validated the performance of this model through ExoGRU-guided mutagenesis and synthetic RNA sequence analysis, and confirmed that primary RNA sequence is a major determinant in small RNA secretion. Additionally, we used ExoGRU to revealcisandtransfactors that underlie small RNA secretion, including known and novel RNA-binding proteins, e.g., YBX1, HNRNPA2B1, and RBM24. We also developed a novel technique called exoCLIP, which reveals the RNA interactome of RBPs within the cell-free space. We used exoCLIP to reveal the RNA interactome of HNRNPA2B1 and RBM24 in extracellular vesicles. Together, our results demonstrate the power of machine learning in revealing novel biological mechanisms. In addition to providing deeper insight into complex processes such as small RNA secretion, this knowledge can be leveraged in therapeutic and synthetic biology applications.

RBMS1 putative regulons, RBMS1 target list, RBMS1 80-gene signature list

Supplementary Figure 4

Supplementary Methods

The description of benchmarking PRADA

The schematics of the data flow used for analysis

Identifying master regulators that drive pathologic gene expression is a key challenge in precision oncology. Here, we have developed an analytic framework, named PRADA, that identifies oncogenic RNA-binding proteins through the systematic detection of coordinated changes in their target regulons. Application of this approach to data collected from clinical samples, patient-derived xenografts, and cell line models of colon cancer metastasis revealed the RNA-binding protein RBMS1 as a suppressor of colon cancer progression. We observed that silencing RBMS1 results in increased metastatic capacity in xenograft mouse models, and that restoring its expression blunts metastatic liver colonization. We have found that RBMS1 functions as a posttranscriptional regulator of RNA stability by directly binding its target mRNAs. Together, our findings establish a role for RBMS1 as a previously unknown regulator of RNA stability and as a suppressor of colon cancer metastasis with clinical utility for risk stratification of patients.Significance:By applying a new analytic approach to transcriptomic data from clinical samples and models of colon cancer progression, we have identified RBMS1 as a suppressor of metastasis and as a post-transcriptional regulator of RNA stability. Notably, RBMS1 silencing and downregulation of its targets are negatively associated with patient survival.See related commentary by Carter, p. 1261.This article is highlighted in the In This Issue feature, p. 1241

RNA structural switches are key regulators of gene expression in bacteria, yet their characterization in Metazoa remains limited. Here we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3’UTR of the RORC transcript.In vivoDMS-MaPseq, coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identifytransfactors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated mRNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally-driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

The search for new approaches in cancer therapy requires a mechanistic understanding of cancer vulnerabilities and anti-cancer drug mechanisms of action. Problematically, some effective therapeutics target cancer vulnerabilities that we do not understand and have poorly defined mechanisms of anti-cancer activity. One such drug is decitabine, which is a frontline therapeutic approved for the treatment of high-risk acute myeloid leukemia (AML). Decitabine is thought to kill cancer cells selectively via inhibition of DNA methyltransferase enzymes, but the genes and mechanisms involved remain unclear. Here, we apply an integrated multiomics and CRISPR functional genomics approach to identify genes and processes associated with response to decitabine in AML cells. Our integrated multiomics approach reveals RNA dynamics are key regulators of DNA hypomethylation induced cell death. Specifically, regulation of RNA decapping, splicing and RNA methylation emerge as critical regulators of decitabine killing. Our results provide insights into the mechanisms of decitabine anti-cancer activity in treatment of AML and identify combination therapies which could potentiate decitabine anti-cancer activity.

Background: Orphan non-coding RNAs (oncRNAs) are a novel category of small non-coding RNAs that are present in the tumor tissue and blood of people with cancer and largely absent in people without cancer. To examine the potential of using oncRNAs for early cancer detection via liquid biopsy, we assessed the oncRNA content of serum from people with and without non-small cell lung cancer (NSCLC) and developed a prediction model for NSCLC. Methods: A total of 540 serum samples were obtained from Indivumed (Hamburg, Germany) and MT Group (Los Angeles, CA) and divided into cohort A for training (150 NSCLC cases, 219 controls; female: 30.7%/36.1%; mean age: 67.9 ± 8.9/62.4 ± 9.2; ever-smoker: 95.3%/26.9%, respectively) and cohort B for internal validation (88 NSCLC cases, 83 controls; female: 40.9%/54.2%; mean age: 62.7 ± 9.2/54.1 ± 12.4; ever-smoker: 89.8%/6.0%, respectively). We used RNA isolated from 0.5 mL of serum to generate and sequence libraries at an average depth of 18.5 ± 6.5 million 50-bp single-end reads using next-generation sequencing. Previously, we created a large catalog of NSCLC oncRNAs found in 999 NSCLC tumor tissues and largely absent in 679 normal samples from The Cancer Genome Atlas (TCGA) smRNA-seq database. This catalog was distilled by removing smRNA species found in the serum of an independent cohort of 31 non-cancer donors to yield a final NSCLC oncRNA catalog of 81,004 distinct oncRNA species. This distilled catalog was the reference for identifying NSCLC oncRNAs in the present study. Using oncRNA data we generated by sequencing samples from cohort A, we trained a logistic regression model for predicting NSCLC presence. The model was then validated in cohort B. Results: From the 540 samples sequenced, we detected 64,379 oncRNAs from the distilled TCGA oncRNA catalog in at least one sample across both cohorts (A: 55,650, B: 47,539).Using 5-fold cross-validation, the AUC of the logistic regression model was 0.95 (95% CI: 0.93-0.97) for the training cohort, and was 0.98 (0.97-0.99) for the validation cohort. Sensitivities for detecting NSCLC at 95% specificity were 0.78 (0.69-0.86) for early stage (I/II) cancer and 0.75 (0.60-0.87) for late stage (III/IV) cancer in the training cohort, and 0.92 (0.83-0.98) and 1.0 (0.85-1.0), respectively, in the validation cohort. Conclusion: These results demonstrate the potential for accurate, sensitive, and early detection of NSCLC through sequencing the oncRNA content of a routine blood draw. The performance of the model trained on one cohort and internally validated in a separate cohort supports the generalizability of this approach in detecting NSCLC. Citation Format: Mehran Karimzadeh, Jeffrey Wang, Aiden Sababi, Oluwadamilare I. Afolabi, Dung Ngoc Lam, Alice Huang, Diana R. Corti, Kristle C. Garcia, Seda Kilinc, Xuan Zhao, Jieyang Wang, Taylor B. Cavazos, Patrick Arensdorf, Kimberly H. Chau, Helen Li, Hani Goodarzi, Lisa Fish, Fereydoun Hormozdiari, Babak Alipanahi. Blood-based early detection of non-small cell lung cancer using orphan noncoding RNAs. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5711.

Background The current guidelines on Cushing's Disease management recommend surgically resecting adenomas larger than 10 mm in size.1 For smaller adenomas, inferior petrosal sinus sampling (IPSS) is considered the gold standard to distinguish between Cushing's disease and ectopic ACTH production. We report a case where IPSS testing and the size of the adenoma on MRI were misleading in determining the final diagnosis, prompting us to challenge the existing guidelines. Clinical Case A 40-year-old female with a past medical history of hyperlipidemia, obesity (BMI 42) and prediabetes presented with secondary infertility, galactorrhea, headaches, blurred vision and weight gain (30 lbs) over the past year. Physical examination was notable for acanthosis nigricans of the neck and bilateral milky nipple discharge. Prolactin level was elevated to 46.9 ng/ml (n 4.8-23.3 ng/mL). ACTH was elevated to 83.5 pg/mL (n 7.2-63.3 pg/mL) and cortisol to 17.4 ug/dL (n 2.7-10.5 ug/dL). Salivary cortisol was elevated to 0.216 ug/dL (n Conclusion Current guidelines recommend surgery for adenomas >10 mm in size, IPSS for adenomas < 6 mm and further diagnostics (IPSS or serum CRH and DDAVP stimulation tests plus whole-body CT) for those 6-9 mm. IPSS is strongly preferred. 1 IPSS is operator dependent and has low efficacy in tumour lateralisation. With the advent of high-resolution CT imaging and emerging data corroborating non-invasive stimulation tests,2 it may be time to shift away from IPSS as a first line test for adenomas irrespective of size. IPSS can present a costly, invasive, oft misleading, and hence superfluous testing strategy; it is high time the medical community re-evaluates its reliance on it.References1. Fleseriu M et al. Consensus on diagnosis and management of Cushing's disease: a guideline update. Lancet Diabetes Endocrinol. 2021 Dec;9(12): 847-875.2.Caroline Frete et al. Non-invasive Diagnostic Strategy in ACTH-dependent Cushing's Syndrome, The Journal of Clinical Endocrinology & Metabolism, Volume 105, Issue 10, October 2020, Pages 3273–3284 Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

Antisense RNAs are ubiquitous in human cells, yet the role that they play in healthy and diseased states remains largely unexplored. Here, we developed a computational framework to catalog and profile antisense RNAs and applied it to poorly and highly metastatic breast cancer cell lines. We identified one antisense RNA that plays a functional role in driving breast cancer progression by upregulating the redox enzyme NQO1, and hence named NQO1-antisense RNA or NQO1-AS. This upregulation occurs via a stabilizing interaction between NQO1-AS and its complementary region in the 3’UTR of NQO1 mRNA. By increasing expression of NQO1 protein, breast cancer cells are able to tolerate higher levels of oxidative stress, enabling them to colonize the lung. During this process the cancer cells become dependent on NQO1 to protect them from ferroptosis. We have shown that this dependence can be exploited therapeutically in xenograft models of metastasis. Together, our findings establish a previously unknown role for NQO1-AS in the progression of breast cancer by serving as a post-transcriptional regulator of RNA processing and decay for its sense mRNA.

Cancer cells often co-opt post-transcriptional regulatory mechanisms to achieve pathologic expression of gene networks that drive metastasis. Translational control is a major regulatory hub in oncogenesis, however its effects on cancer progression remain poorly understood. To address this, we used ribosome profiling to compare genome-wide translation efficiencies of poorly and highly metastatic breast cancer cells and patient-derived xenografts. We developed novel regression-based methods to analyze ribosome profiling and alternative polyadenylation data, and identified HNRNPC as a translational controller of a specific mRNA regulon. Mechanistically, HNRNPC, in concert with PABPC4, binds near to poly(A) signals, thereby governing the alternative polyadenylation of a set of mRNAs. We found that HNRNPC and PABPC4 are downregulated in highly metastatic cells, which causes HNRNPC-bound mRNAs to undergo 3’ UTR lengthening and subsequently, translational repression. We showed that modulating HNRNPC expression impacts the metastatic capacity of breast cancer cells in xenograft mouse models. We also found that a small molecule, previously shown to induce a distal-to-proximal poly(A) site switching, counteracts the HNRNPC-PABPC4 driven deregulation of alternative polyadenylation and decreases the metastatic lung colonization by breast cancer cells in vivo.

Aims Diabetic ketoacidosis (DKA) is an emergency with high morbidity and mortality. This study examined patient factors associated with hospitalization for recurrent DKA. Methods Characteristics of 265 subjects admitted for DKA at Hennepin County Medical Center between January 2017 and January 2019 were retrospectively analyzed. Differences between subjects with a single admission versus multiple were reviewed. Results Forty-eight out of 265 patients had recurrent DKA. Risk factors included African American race (adjusted odds ratio (aOR) versus white non-Hispanic = 4.6, 95% CI 1.8–13, p = 0.001) or other race/ethnicity (aOR = 8.6, 2.9–28, p p = 0.10; aOR 53-99y versus 18-36y = 0.37, 0.12–0.99, p = 0.05), type 1 diabetes mellitus (aOR = 2.4, 1.1–5.5, p = 0.04), ever homeless (aOR = 2.5, 1.1–5.4, p = 0.03), and drug abuse (aOR = 3.2, 1.3–7.8, p = 0.009). DKA cost a median of $29,981 per admission. Conclusions Recurrent DKA is costly, and social determinants are strong predictors of recurrence. This study highlights the need for targeted preventative care programs.

Small non-coding RNAs (sncRNAs) have established roles as post-transcriptional regulators of cancer pathogenesis. We recently reported a novel and previously unannotated class of cancer-specific sncRNAs in breast cancer and demonstrated that breast cancer cells exploit a specific sncRNA to promote cancer metastasis. However, the extent to which these sncRNAs, which we have collectively termed orphan non-coding RNAs (oncRNAs), are present in other cancer types is unknown. To address this question and define a high-confidence set of oncRNAs, we used smRNA-seq data from 6 cancer sites (breast, colorectal, kidney, liver, lung, and stomach) and their corresponding normal tissues from The Cancer Genome Atlas (TCGA; 4,445 cancer, 431 normal) and identified a total of 144,695 oncRNAs that are significantly present in cancer and largely absent in normal tissue (Fisher’s Exact Test and Benjamini-Hochberg correction, FDR < 0.1). To evaluate if this set of TCGA-derived oncRNAs could be validated in independent datasets, we examined smRNA-seq data from two large independent cohorts comprising these same cancer and normal tissue types (Indivumed, Hamburg, Germany). Cohort A consists of 4,024 samples (2,245 cancer, 1,779 normal) and cohort B consists of 2,874 samples (2,063 cancer; 811 normal). oncRNAs in these cohorts were annotated following the same procedure used for TCGA data. TCGA-derived oncRNAs were considered validated in the independent cohorts if they were present in a significantly higher number of cancer samples compared to adjacent normal tissue samples. In cohort A, 140,191 (96.9%) of TCGA-derived oncRNAs were detected in at least one sample, of which 74,634 (51.6%) were validated as oncRNAs. In cohort B, 140,147 (96.9%) oncRNAs were observed and 68,366 (47.2%) were validated. The degree of overlap between the validated oncRNAs in each cohort was significant, with 54,294 (37.5%) overlapping oncRNAs (hypergeometric test, P=0). We also found that oncRNAs are informative of cancer tissue of origin, demonstrating the existence of consistent cancer-specific oncRNA expression profiles in independent studies. Using the TCGA-derived oncRNAs as features, we trained an eXtreme Gradient Boosting (XGB) model on TCGA data to classify cancer samples by the 6 tissues of origin. The TCGA-trained model showed high performance when evaluated on both cohorts A and B, achieving accuracies of 91.5% (95% CI: 90.3%-92.7%) and 96% (94.7%-97%), respectively. For comparison, this model achieved an accuracy of 96% (94.5%-97.2%) on held-out TCGA data (80/20 train/test split). Our results show a robust validation of TCGA-derived oncRNAs in external, independently sourced and processed cancer tissue cohorts across a heterogeneous set of cancer sites. Our machine learning model also demonstrates that oncRNA profiles can be used to predict cancer tissue of origin with high generalizability and accuracy. Citation Format: Jeffrey Wang, Helen Li, Lisa Fish, Kimberly H. Chau, Patrick Arensdorf, Hani Goodarzi, Babak Alipanahi. Discovery and validation of orphan noncoding RNA profiles across multiple cancers in TCGA and two independent cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3353.

Characterizing a cancer spliceosome Cells undergo many genomic changes as they progress toward metastatic cancer. One aspect of this change is to RNA expression and splicing isoforms, but how these differences affect tumor progression is not well characterized. Fish et al. developed a computational framework called pyTEISER that identifies structural cis-regulatory elements that control diverse types of RNA regulation. Applying pyTEISER to models of breast cancer metastasis, they discovered an RNA short-stem-loop element that forms a “structural splicing enhancer” that acts in cis to regulate alternative splicing of RNA transcripts. One of these interactions encompasses the RNA-binding protein SNRPA1 and results in alternative exon inclusion that affects metastatic capacity in xenograft models. Thus, RNA element binding may play a role in splicing regulation and is potentially an important component of the cis-splicing code. Science , this issue p. eabc7531

Eukaryotic transfer RNAs can become selectively fragmented upon various stresses, generating tRNA‐derived small RNA fragments. Such fragmentation has been reported to impact a small fraction of the tRNA pool and thus presumed to not directly impact translation. We report that oxidative stress can rapidly generate tyrosine‐tRNA(GUA) fragments in human cells—causing significant depletion of the precursor tRNA. Tyrosine‐tRNA(GUA) depletion impaired translation of growth and metabolic genes enriched in cognate tyrosine codons. Depletion of tyrosine tRNA(GUA) or its translationally regulated targets USP3 and SCD repressed proliferation—revealing a dedicated tRNA‐regulated growth‐suppressive pathway for oxidative stress response. Tyrosine fragments are generated in a DIS3L2 exoribonuclease‐dependent manner and inhibit hnRNPA1‐mediated transcript destabilization. Moreover, tyrosine fragmentation is conserved in C. elegans. Thus, tRNA fragmentation can coordinately generate trans‐acting small RNAs and functionally deplete a tRNA. Our findings reveal the existence of an underlying adaptive codon‐based regulatory response inherent to the genetic code.

A 35-year-old gentleman presented with epigastric pain and bilious emesis. He also endorsed urinary frequency, non-bloody diarrhea and diffuse bone pain. On physical examination he had epigastric tenderness and multiple hyperpigmented skin lesions. An abdominal computed tomography (CT) scan revealed multiple diverticula with peri-colonic fat stranding in the descending and sigmoid colon, concerning for diverticulitis. He was started on a course of metronidazole and ciprofloxacin. A 3.1 cm mass was incidentally noted in the uncinate process of the pancreas. Bilateral adrenal nodules were also appreciated. An endoscopic ultrasound (EUS) guided trans-gastric fine needle aspiration biopsy was performed, revealing a well differentiated pancreatic neuroendocrine tumor (pNET - pT3N1Mx, intermediate risk). Chromogranin A was elevated to 108 ng/ml (reference range Three years later, he presented with severe abdominal pain and a new pancreatic mass was noted on CT. Chromogranin A was elevated to 227 ng/mL. EUS revealed a 0.35 cm mass in the bed of the pancreatic head, encasing the superior mesenteric artery. Pathology was positive for recurrence of the neuroendocrine tumor. He was hypercalcemic to 11.4 mg/dL and parathyroid hormone was elevated to 319 pg/mL. CT neck revealed a 0.1 cm nodule concerning for parathyroid adenoma. He underwent a subtotal parathyroidectomy. Genetic testing confirmed Multiple Endocrine Neoplasia Type 1 (MEN1) with a heterozygous mutation of the menin1 gene. MEN1 is a rare genetic syndrome with affected individuals at increased risk of developing pancreatic, pituitary, parathyroid gland and cutaneous tumors. With a kaleidoscope of presentations, clinicians must maintain a high index of suspicion for MEN1, particularly for cases with nonfunctioning pNETs which present insidiously and are the foremost cause of mortality in MEN1 patients.1 Further clarity is needed on MEN1 associated pNET prognostic risk stratification, surveillance and targeted immunochemotherapy.2 Timely and algorithmic screening for MEN 1 syndrome in patients with pancreatic incidentalomas is essential to improving patient outcomes. 1. Kamilaris CDC, Stratakis CA. Multiple Endocrine Neoplasia Type 1 (MEN1): An Update and the Significance of Early Genetic and Clinical Diagnosis. Front Endocrinol. 2019;10:339. doi:10.3389/fendo.2019.00339 2. Yates CJ, Newey PJ, Thakker RV. Challenges and controversies in management of pancreatic neuroendocrine tumours in patients with MEN1. Lancet Diabetes Endocrinol. 2015;3(11):895-905. doi:10.1016/S2213-8587(15)00043-1

Broad dysregulation of gene expression control is a hallmark of cancer progression. Identifying the underlying master regulators that drive pathological gene expression is a key challenge in precision oncology. Here, we have developed a network analytical framework, named PRADA, that identifies oncogenic RNA-binding proteins through the systematic detection of coordinated changes in their target regulons. Application of this approach to data collected from clinical samples, patient-derived xenografts, and cell line models of colon cancer metastasis revealed the RNA-binding protein RBMS1 as a suppressor of colon cancer progression. We observed that silencing RBMS1 results in increased metastatic capacity in xenograft mouse models, and that restoring its expression blunts metastatic liver colonization. We have found that RBMS1 functions as a post-transcriptional regulator of RNA stability by directly binding and stabilizing ~80 target mRNAs. Measurements in more than 180 clinical samples as well as survival analyses in publicly available datasets, have shown that RBMS1 silencing and the subsequent downregulation of its targets are strongly associated with disease progression and poor survival in colon cancer patients. Together, our findings establish a role for RBMS1 as a previously unknown regulator of RNA stability and as a suppressor of colon cancer metastasis with clinical utility for risk stratification of patients.SignificanceBy applying a new analytical approach to transcriptomic data from clinical samples and models of colon cancer progression, we have uncovered RBMS1 as a suppressor of metastasis and as a post-transcriptional regulator of RNA stability. Notably, RBMS1 silencing and downregulation of its targets are negatively associated with patient survival.

Background: Liquid biopsies have emerged as effective diagnostic tools in disease monitoring and minimal residual disease detection. Circulating tumor DNA (ctDNA) was recently shown to be a predictor of poor response and recurrence in breast cancer. However, ctDNA shedding from breast tumors can rapidly decrease during treatment, resulting in reduced sensitivity in measuring early changes in tumor response or residual cancer burden (RCB) after neoadjuvant chemotherapy (NAC). We recently reported the discovery of orphan non-coding RNAs (oncRNAs), a class of small RNAs that are not present in healthy cells, but emerge from cancer cells. Similar to ctDNA, tumor-released oncRNAs can be used to detect the presence of an underlying tumor; however, since they are actively released by cancer cells, their abundance in the cell-free compartment is substantially higher than ctDNA. Therefore, we hypothesized that monitoring circulating oncRNAs in blood permits a more sensitive approach to measuring treatment response (i.e., pathologic complete response, or pCR) and estimating RCB. Patients and Methods: Cell-free RNA (cfRNA) was extracted from ~1 ml sera of 72 breast cancer patients treated in the neoadjuvant I-SPY 2 TRIAL with NAC alone or combined with MK-2206 (AKT inhibitor) treatment. For each patient, treatment-naïve samples (T0) were compared with samples from post-treatment and prior to surgery (T3) time-point. RNA samples were subjected to small RNA sequencing (SMARTer), and the presence and abundance of cell-free oncRNA species were then determined by identifying and counting the reads that map to oncRNA loci across samples. Notably, oncRNAs species were pre-annotated from the Cancer Genome Atlas (TCGA), and our approach does not require bespoke personalized assays. We used a machine-learning model to compare abundance of cfRNA species before and after treatment (i.e., T3-T0) to predict pCR and RCB. For this, we split our cohort into a training and a testing set (48 and 24) and trained a model to simultaneously learn the presence of residual disease (pCR vs. no pCR) and its extent (RCB). We then measured the performance of our model on the held-out test data and the entire dataset. To confirm the robustness of our model, we also employed a leave-one-out strategy, whereby pCR and RCBIndex of each patient was predicted using a model that was trained on the other patients in the cohort. Finally, to assess the ability of our oncRNA-based model to risk-stratify patients who fail to achieve pCR (without having been explicitly trained on relapse data), we used the model’s oncRNA score to predict patients at the highest risk of distant recurrence (n=8 out of 36) and performed a multivariate Cox analysis, controlling for HR/Her2 status (median follow-up time was 4.8 years). Results: The model’s accuracy for predicting pCR—based on changes in circulating oncRNA species between T3 and T0—was 85% for the training data and 79% for the held-out test data (positive predictive value of 75% and negative predictive value of 83%) with combined accuracy of 83%; precision 86% and recall 83%; Pearson R=0.5 for RCB. A leave-one-out strategy showed similar performance (area under ROC of 0.77 versus 0.81 in train-test split). Finally, among the patients who failed to achieve pCR, we observed a significantly higher risk of distant recurrence in those with the highest scores (DRFS: hazard-ratio = 8.4, ANOVA P Citation Format: Hani Goodarzi, Albertas Navickas, Jefferey Wang, Kristle Garcia, Mark J Magbanua, Lisa Fish, Lamorna Brown Swigart, Gillian Hirst, Denise Wolf, Christina Yau, Jo Chien, Carol Simmons, Amy Delson, Laura Esserman, Laura van 't Veer. Tumor-released circulating orphan non-coding RNAs reflect treatment response and survival in breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD9-04.

Background: Metabolic reprogramming is a hallmark of breast cancer progression. However, the underlying regulatory pathways that initiate and maintain this process remain largely unexplored. Recently, we have identified a novel antisense RNA that helps protect breast cancer cells against oxidative stress by reprogramming their metabolic redox state. Using cell line and patient-derived xenograft models, as well as direct measurements in clinical samples, we have demonstrated the unique regulatory functions of this antisense RNA in increasing the metastatic capacity of breast cancer cells. Results: Non-coding RNAs have emerged as major drivers of metastatic progression. We have recently demonstrated that specific classes of non-coding RNAs, such as tRNAs (Goodarzi et al, Cell, 2016) and tRNA fragments (Goodarzi et al, Cell, 2015), play major roles in breast cancer metastasis as post-transcriptional regulators of gene expression. However, these types of regulatory RNAs constitute only a fraction of the non-coding RNAs that are aberrantly expressed in highly metastatic cells. For example, antisense RNAs are a large but often ignored class of RNAs with poorly understood cellular functions. We recently developed a new computational algorithm to systematically annotate antisense RNAs and identify those that are associated with metastatic progression based on data from cell line and patient-derived xenograft models, as well as matched primary and metastatic tumors from triple-negative breast cancer patients. We identified a previously unknown antisense RNA, which is transcribed from a locus in the 3’ UTR of the gene NQO1 (and is hence named NQO1-AS). Both NQO1-AS and NQO1 are significantly upregulated in highly metastatic breast cancer cells, and we have shown that the NQO1 sense mRNA is stabilized by the expression of NQO1-AS. Our results indicate that NQO1-AS forms a stable duplex with the 3’ UTR of NQO1 and induces the expression of a longer and more stable isoform of NQO1 mRNA. Metabolomic measurements in NQO1 knockdown and control cells revealed that increased NQO1 activity enables cancer cells to better tolerate the oxidative stress experienced during metastasis. We demonstrated this by performing lung metastasis assays in xenograft models. To confirm the clinical relevance of these findings, we performed comprehensive clinical association studies, and also used quantitative PCR and immunohistochemistry to measure NQO1 levels across all disease stages. We observed a highly significant association between higher NQO1 and NQO1-AS expression and metastatic relapse. Methods: We developed a method named iRAs to annotate and quantify antisense RNAs. We used global run-on assays (GRO-seq) and RNA sequencing in poorly and highly metastatic breast cancer cells to identify NQO1-AS as a novel pro-metastatic antisense RNA. We used both Gapmers and CRISPR-i to knock down NQO1-AS and to measure its impact on NQO1 mRNA stability and expression. We used CRISPRi to silence NQO1 in both MDA-231 and HCC-1806 breast cancer lines, and measured the metabolic consequences of NQO1 knockdown by measuring NADPH flux as well as performing general metabolomic profiling. We also used in vivo lung colonization assays (n=5 mice in each arm) to measure the metastatic capacity of NQO1 knockdown cells. Log-rank test (univariate) and Cox Proportional Hazard Models (multivariate) were used to perform survival analyses in METABRIC and the kmplot aggregate dataset. Mann-Whitney or ANOVA was used to compare expression of NQO1 and NQO1-AS across samples stratified based on sub-type and tumor grade/stage in public datasets as well as our own measurements in clinical samples (n=96; 5 healthy, 23 stage I, 30 stage II, 29 stage III, and 9 stage IV). IHC was performed on tissue microarrays from CHTN (Breast Progression), and blinded scoring was used to assess NQO1 levels. Citation Format: Hani Goodarzi, Bruce Culbertson, Kristle Garcia, Lisa Fish. A sense-antisense RNA interaction drives metabolic reprogramming in metastatic breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS19-01.

Objective: We discuss the implementation and outcomes of a diabetic ketoacidosis (DKA) critical care pathway (CCP) at a 462-bed teaching hospital. Methods: A multi-disciplinary team implemented a DKA CCP that was translated into 3 computerized physician order entry (CPOE) order sets corresponding to the phases of DKA care. Historical and postintervention data were obtained via automated queries of the electronic medical record (EMR) and further analyzed by manual chart review. Results: Average length of stay decreased from 104.3 to 72.9 hours (P = .0003) after implementation of a DKA CCP. Conclusion: Outcome data supports the use of a DKA CCP at our institution. Abbreviations: DKA = diabetic ketoacidosis CCP = critical care pathway EMR = electronic medical record CPOE = computerized physician order entry ICD-9 = International Classification of Diseases, ninth revision LoS = length of stay SQL = standard query language

To compare the effectiveness of 2 insulin protocols to treat glucocorticoid-induced hyperglycemia in the nonintensive care hospital setting.A randomized, open-label, parallel-arm study was conducted comparing standard recommended care of complete insulin orders (CIO) (i.e., 3-part insulin regimen of long-acting basal [background], rapid-acting bolus [mealtime], and rapid-acting correction factor) to an experimental group following a regimen of Neutral Protamine Hagedorn (NPH) plus CIO (NPH-CIO). The primary outcome was mean blood glucose (BG), and the secondary outcome was percent of BG in target range of 70 to 180 mg/dL. Hypoglycemia was also evaluated.Sixty-one patients completed 2 to 5 consecutive inpatient days (31 CIO; 30 NPH-CIO). Baseline mean BG results were 237.2 ± 50.2 and 221.9 ± 35.8 mg/dL (P = .30) in the CIO and NPH-CIO groups, respectively. No significant difference in overall mean BG between the 2 groups was detected; however, a significant difference arose on day 3: mean BG 181.8 ± 32.6 mg/dL (CIO) versus 157.2 ± 6.1 mg/dL (NPH-CIO) (P = .03). Moreover, the total daily doses (TDDs) of insulin did not differ: 34.8 ± 43.0 units (CIO) versus 35.8 ± 25.0 units (NPH-CIO) (P = .13). Percent of BG in target was 54.6% (CIO) and 62% (NPH-CIO) (P = .24). Incidence of severe hypoglycemia (50 mg/dL) was the same in both groups (0.1%).NPH added to 3-part insulin regimen (CIO) may be an effective way to a combat glucocorticoid-induced hyperglycemia, though further research is needed in a larger population.

Background: Breast cancer progression accompanies broad reprogramming of the alternative splicing landscape with functional implications for tumor growth and metastasis. However, the underlying regulatory pathways that are hijacked by cancer cells to drive pathological splicing programs remain largely unknown. Here, we have described a novel regulatory pathway, mediated by the splicing factor SNRPA1, that promotes breast cancer progression. Results: We used high-coverage RNA sequencing to compare alternative splicing patterns in highly metastatic breast cancer cells (MDA-LM2) to their less metastatic parental line (MDA-231). We identified a novel structural splicing enhancer (SSE) element that is enriched among the exons up-regulated in highly metastatic cells and showed that it is bound by the RNA-binding protein SNRPA1, which in turn acts as a splicing factor. We used loss-of-function and gain-of-function both in vitro and in vivo xenograft mouse models to establish SNRPA1 as a promoter of breast cancer cell invasion (~2-fold change in two independent cell lines, P=0.002) and metastasis (~5-10 fold change in lung colonization in two independent cell lines, P Methods: We used a framework called ‘mixture of isoforms’ (MISO) to quantify changes in alternative splicing. We then applied iTEISER, a computational tool we have developed, to find cis-regulatory elements that drive alternative splicing patterns. We used bait RNA to co-precipitate and mass-spectrometry to identify the RNA-binding proteins that interact with SSEs. Lentiviral delivery of shRNAs (two independent hairpins) or transgenes to modulate SNRPA1 expression and RNA-seq was used to measure their regulatory consequences on splicing. For the resulting lines (both MDA-231 and HCC-1806 backgrounds), in vitro cancer cell invasion and in vivo lung colonization assays were also performed (n=5 mice in each arm). Log-rank test (univariate) and Cox Proportional Hazard Models (multivariate) were used to perform survival analyses in METABRIC and the kmplot aggregate dataset. Mann-Whitney or ANOVA was used to compare expression of SNRPA1 across samples stratified based on sub-type and tumor grade/stage in public datasets as well as our own measurements in clinical samples (n=96; 5 healthy, 23 stage I, 30 stage II, 29 stage III, and 9 stage IV). Conclusion: In sum, we have discovered a previously unknown regulatory pathway of RNA splicing that acts as a promoter of metastasis in breast, which may inform new therapeutic targets among the SNRPA1 regulon for adjuvant therapy. Citation Format: Hani Goodarzi, Lisa Fish, Bruce Culbertson. A pro-metastatic alternative splicing program that drives breast cancer progression [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD8-07.

Here we performed a systematic search to identify breast-cancer-specific small noncoding RNAs, which we have collectively termed orphan noncoding RNAs (oncRNAs). We subsequently discovered that one of these oncRNAs, which originates from the 3' end of TERC, acts as a regulator of gene expression and is a robust promoter of breast cancer metastasis. This oncRNA, which we have named T3p, exerts its prometastatic effects by acting as an inhibitor of RISC complex activity and increasing the expression of the prometastatic genes NUPR1 and PANX2. Furthermore, we have shown that oncRNAs are present in cancer-cell-derived extracellular vesicles, raising the possibility that these circulating oncRNAs may also have a role in non-cell autonomous disease pathogenesis. Additionally, these circulating oncRNAs present a novel avenue for cancer fingerprinting using liquid biopsies.

SUMMARYEukaryotic transfer RNAs can become selectively fragmented upon various stresses, generating tRNA-derived small RNA fragments. Such fragmentation has been reported to impact a small fraction of the tRNA pool and thus presumed to not directly impact translation. We report that oxidative stress can rapidly generate tyrosine tRNAGUA fragments in human cells—causing significant depletion of the precursor tRNA. Tyrosine tRNAGUA depletion impaired translation of growth and metabolic genes enriched in cognate tyrosine codons. Depletion of tyrosine tRNAGUA or its translationally regulated targets USP3 and SCD repressed proliferation—revealing a dedicated tRNA-regulated growth suppressive pathway for oxidative stress response. Tyrosine fragments are generated in a DIS3L2 exoribonuclease-dependent manner and inhibit hnRNPA1-mediated transcript destabilization. Moreover, tyrosine fragmentation is conserved in C. elegans. Thus, tRNA fragmentation can coordinately generate trans-acting small-RNAs and functionally deplete a tRNA. Our findings reveal the existence of an underlying adaptive codon-based regulatory response inherent to the genetic code.

SUMMARYPost-transcriptional regulation of RNA stability is a key step in gene expression control. We describe a regulatory program, mediated by the double-stranded RNA binding protein TARBP2, that controls RNA stability in the nucleus. TARBP2 binding to pre-mRNAs results in increased intron retention, subsequently leading to targeted degradation of TARBP2-bound transcripts. This is mediated by TARBP2 recruitment of the m6A RNA methylation machinery to its target transcripts, where deposition of m6A marks influences the recruitment of splicing regulators, inhibiting efficient splicing. Interactions between TARBP2 and the nucleoprotein TPR then promote degradation of these TARBP2-bound transcripts by the nuclear exosome. Additionally, analysis of clinical gene expression datasets revealed a functional role for this TARBP2 pathway in lung cancer. Using xenograft mouse models, we find that TARBP2 impacts tumor growth in the lung, and that this function is dependent on TARBP2-mediated destabilization of ABCA3 and FOXN3. Finally, we establish the transcription factor ZNF143 as an upstream regulator of TARBP2 expression.RESEARCH HIGHLIGHTSThe RNA-binding protein TARBP2 controls the stability of its target transcripts in the nucleusNuclear TARBP2 recruits the methyltransferase complex to deposit m6A marks on its target transcriptsTARBP2 and m6A-mediated interactions with splicing and nuclear RNA surveillance complexes result in target transcript intron retention and decay.Increased TARBP2 expression is associated with lung cancer and promotes lung cancer growthin vivo.The transcription factor ZNF143 drives oncogenic TARBP2 upregulation in lung cancer.

Using a functional model of breast cancer heterogeneity, we previously showed that clonal sub-populations proficient at generating circulating tumour cells were not all equally capable of forming metastases at secondary sites1. A combination of differential expression and focused in vitro and in vivo RNA interference screens revealed candidate drivers of metastasis that discriminated metastatic clones. Among these, asparagine synthetase expression in a patient’s primary tumour was most strongly correlated with later metastatic relapse. Here we show that asparagine bioavailability strongly influences metastatic potential. Limiting asparagine by knockdown of asparagine synthetase, treatment with L-asparaginase, or dietary asparagine restriction reduces metastasis without affecting growth of the primary tumour, whereas increased dietary asparagine or enforced asparagine synthetase expression promotes metastatic progression. Altering asparagine availability in vitro strongly influences invasive potential, which is correlated with an effect on proteins that promote the epithelial-to-mesenchymal transition. This provides at least one potential mechanism for how the bioavailability of a single amino acid could regulate metastatic progression.

Upon exposure to stress, tRNAs are enzymatically cleaved, yielding distinct classes of tRNA-derived fragments (tRFs), yielding distinct classes of tRFs. We identify a novel class of tRFs derived from tRNA(Glu), tRNA(Asp), tRNA(Gly), and tRNA(Tyr) that, upon induction, suppress the stability of multiple oncogenic transcripts in breast cancer cells by displacing their 3' untranslated regions (UTRs) from the RNA-binding protein YBX1. This mode of post-transcriptional silencing is sequence specific, as these fragments all share a common motif that matches the YBX1 recognition sequence. Loss-of-function and gain-of-function studies, using anti-sense locked-nucleic acids (LNAs) and synthetic RNA mimetics, respectively, revealed that these fragments suppress growth under serum-starvation, cancer cell invasion, and metastasis by breast cancer cells. Highly metastatic cells evade this tumor-suppressive pathway by attenuating the induction of these tRFs. Our findings reveal a tumor-suppressive role for specific tRNA-derived fragments and describe a molecular mechanism for their action. This transcript displacement-based mechanism may generalize to other tRNA, ribosomal-RNA, and sno-RNA fragments.

Aberrant regulation of RNA stability has an important role in many disease states. Deregulated post-transcriptional modulation, such as that governed by microRNAs targeting linear sequence elements in messenger RNAs, has been implicated in the progression of many cancer types. A defining feature of RNA is its ability to fold into structures. However, the roles of structural mRNA elements in cancer progression remain unexplored. Here we performed an unbiased search for post-transcriptional modulators of mRNA stability in breast cancer by conducting whole-genome transcript stability measurements in poorly and highly metastatic isogenic human breast cancer lines. Using a computational framework that searches RNA sequence and structure space, we discovered a family of GC-rich structural cis-regulatory RNA elements, termed sRSEs for structural RNA stability elements, which are significantly overrepresented in transcripts displaying reduced stability in highly metastatic cells. By integrating computational and biochemical approaches, we identified TARBP2, a double-stranded RNA-binding protein implicated in microRNA processing, as the trans factor that binds the sRSE family and similar structural elements--collectively termed TARBP2-binding structural elements (TBSEs)--in transcripts. TARBP2 is overexpressed in metastatic cells and metastatic human breast tumours and destabilizes transcripts containing TBSEs. Endogenous TARBP2 promotes metastatic cell invasion and colonization by destabilizing amyloid precursor protein (APP) and ZNF395 transcripts, two genes previously associated with Alzheimer's and Huntington's disease, respectively. We reveal these genes to be novel metastasis suppressor genes in breast cancer. The cleavage product of APP, extracellular amyloid-α peptide, directly suppresses invasion while ZNF395 transcriptionally represses a pro-metastatic gene expression program. The expression levels of TARBP2, APP and ZNF395 in human breast carcinomas support their experimentally uncovered roles in metastasis. Our findings establish a non-canonical and direct role for TARBP2 in mammalian gene expression regulation and reveal that regulated RNA destabilization through protein-mediated binding of mRNA structural elements can govern cancer progression.

3523 Background: CRC progression accompanies dysregulations in pathways of gene expression control. Regulatory pathways that govern RNA decay have emerged as key mechanisms coopted by cancer cells. Here, we have described a novel regulatory program that acts as a suppressor of metastasis in CRC. Methods: We have developed a computational approach called PRADA that identifies master regulators of aberrant mRNA stability. By applying this tool to a compendium of gene expression data collected from patient samples and colon cancer cell lines, we have identified a novel regulatory program involved in CRC metastasis. We have used xenograft models and genomic technologies to functionally dissect this pathway. We have also performed multivariate analysis in public datasets, as well as qPCR-based measurements in tumor samples to establish its clinical relevance. Results: PRADA identified the RNA-binding protein RBMS1 as a key factor in CRC metastasis. RBMS1, which is silenced in highly metastatic cells, binds and stabilizes a large regulon of mRNAs. Silencing RBMS1 in established lines resulted in increased liver colonization in xenograft models and its over-expression reduced metastasis. We also identified the set of genes that are directly bound and regulated by RBMS1 and function downstream. Loss of RBMS1 and its regulon provide a signature predictive of RFS in localized CRC (n = 574, HR = 0.48, p = 0.038) even when controlled for known prognostic factors in a multivariate analysis (Table). We also observed a 4-fold reduction (P

Post-transcriptional deregulation is a defining feature of metastatic cancer. While many microRNAs have been implicated as regulators of metastatic progression, less is known about the roles and mechanisms of RNA-binding proteins in this process. We identified muscleblind-like 1 (MBNL1), a gene implicated in myotonic dystrophy, as a robust suppressor of multiorgan breast cancer metastasis. MBNL1 binds the 3′ untranslated regions (UTRs) of DBNL (drebrin-like protein) and TACC1 (transforming acidic coiled-coil containing protein 1)—two genes that we implicate as metastasis suppressors. By enhancing the stability of these genes’ transcripts, MBNL1 suppresses cell invasiveness. Consistent with these findings, elevated MBNL1 expression in human breast tumors is associated with reduced metastatic relapse likelihood. Our findings delineate a post-transcriptional network that governs breast cancer metastasis through RNA-binding protein-mediated transcript stabilization.

Decoding post-transcriptional regulatory programs in RNA is a critical step towards the larger goal of developing predictive dynamical models of cellular behaviour. Despite recent efforts, the vast landscape of RNA regulatory elements remains largely uncharacterized. A long-standing obstacle is the contribution of local RNA secondary structure to the definition of interaction partners in a variety of regulatory contexts, including--but not limited to--transcript stability, alternative splicing and localization. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (for example, human cardiac troponin T) or affects other aspects of RNA biology. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence. Here we present a computational framework based on context-free grammars and mutual information that systematically explores the immense space of small structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behaviour. By applying this framework to genome-wide human mRNA stability data, we reveal eight highly significant elements with substantial structural information, for the strongest of which we show a major role in global mRNA regulation. Through biochemistry, mass spectrometry and in vivo binding studies, we identified human HNRPA2B1 (heterogeneous nuclear ribonucleoprotein A2/B1, also known as HNRNPA2B1) as the key regulator that binds this element and stabilizes a large number of its target genes. We created a global post-transcriptional regulatory map based on the identity of the discovered linear and structural cis-regulatory elements, their regulatory interactions and their target pathways. This approach could also be used to reveal the structural elements that modulate other aspects of RNA behaviour.

The abundance of mRNA is mainly determined by the rates of RNA transcription and decay. Here, we present a method for unbiased estimation of differential mRNA decay rate from RNA-sequencing data by modeling the kinetics of mRNA metabolism. We show that in all primary human tissues tested, and particularly in the central nervous system, many pathways are regulated at the mRNA stability level. We present a parsimonious regulatory model consisting of two RNA-binding proteins and four microRNAs that modulate the mRNA stability landscape of the brain, which suggests a new link between RBFOX proteins and Alzheimer's disease. We show that downregulation of RBFOX1 leads to destabilization of mRNAs encoding for synaptic transmission proteins, which may contribute to the loss of synaptic function in Alzheimer's disease. RBFOX1 downregulation is more likely to occur in older and female individuals, consistent with the association of Alzheimer's disease with age and gender."mRNA abundance is determined by the rates of transcription and decay. Here, the authors propose a method for estimating the rate of differential mRNA decay from RNA-seq data and model mRNA stability in the brain, suggesting a link between mRNA stability and Alzheimer's disease."

OBJECTIVE To review the evidence about the impact of hypoglycemia on patients with diabetes that has become available since the past reviews of this subject by the American Diabetes Association and The Endocrine Society and to provide guidance about how this new information should be incorporated into clinical practice. PARTICIPANTS Five members of the American Diabetes Association and five members of The Endocrine Society with expertise in different aspects of hypoglycemia were invited by the Chair, who is a member of both, to participate in a planning conference call and a 2-day meeting that was also attended by staff from both organizations. Subsequent communications took place via e-mail and phone calls. The writing group consisted of those invitees who participated in the writing of the manuscript. The workgroup meeting was supported by educational grants to the American Diabetes Association from Lilly USA, LLC and Novo Nordisk and sponsorship to the American Diabetes Association from Sanofi. The sponsors had no input into the development of or content of the report. EVIDENCE The writing group considered data from recent clinical trials and other studies to update the prior workgroup report. Unpublished data were not used. Expert opinion was used to develop some conclusions. CONSENSUS PROCESS Consensus was achieved by group discussion during conference calls and face-to-face meetings, as well as by iterative revisions of the written document. The document was reviewed and approved by the American Diabetes Association’s Professional Practice Committee in October 2012 and approved by the Executive Committee of the Board of Directors in November 2012 and was reviewed and approved by The Endocrine Society’s Clinical Affairs Core Committee in October 2012 and by Council in November 2012. CONCLUSIONS The workgroup reconfirmed the previous definitions of hypoglycemia in diabetes, reviewed the implications of hypoglycemia on both short- and long-term outcomes, considered the implications of hypoglycemia on treatment outcomes, presented strategies to prevent hypoglycemia, and identified knowledge gaps that should be addressed by future research. In addition, tools for patients to report hypoglycemia at each visit and for clinicians to document counseling are provided.

Targets of the tandem Gcn4 acidic activation domains in transcription preinitiation complexes were identified by site-specific cross-linking. The individual Gcn4 activation domains cross-link to three common targets, Gal11/Med15, Taf12, and Tra1, which are subunits of four conserved coactivator complexes, Mediator, SAGA, TFIID, and NuA4. The Gcn4 N-terminal activation domain also cross-links to the Mediator subunit Sin4/Med16. The contribution of the two Gcn4 activation domains to transcription was gene specific and varied from synergistic to less than additive. Gcn4-dependent genes had a requirement for Gal11 ranging from 10-fold dependence to complete Gal11 independence, while the Gcn4-Taf12 interaction did not significantly contribute to the expression of any gene studied. Complementary methods identified three conserved Gal11 activator-binding domains that bind each Gcn4 activation domain with micromolar affinity. These Gal11 activator-binding domains contribute additively to transcription activation and Mediator recruitment at Gcn4- and Gal11-dependent genes. Although we found that the conserved Gal11 KIX domain contributes to Gal11 function, we found no evidence of specific Gcn4-KIX interaction and conclude that the Gal11 KIX domain does not function by specific interaction with Gcn4. Our combined results show gene-specific coactivator requirements, a surprising redundancy in activator-target interactions, and an activator-coactivator interaction mediated by multiple low-affinity protein-protein interactions.

Objective: To assess the availability and clinical value of blood glucose (BG) testing at the time of admission to the intensive care unit (ICU) after such testing was implemented as routine care in the ICU. Methods: We studied ICU admission BG testing rates and the prevalence of hyperglycemia. In this effort, we assessed the frequency of baseline BG testing in 330 consecutive patients during a period of 3 months and then implemented routine BG monitoring in 1,147 consecutive ICU patients during a 7-month period. Results: Of the total study population, 25% had previously diagnosed diabetes (PDD). At baseline, 70% had BG measured within 4 hours before or after ICU admission (99% of patients with and 60% of patients without PDD). After implementation of routine BG monitoring, there was a significant increase in testing (70% before versus 87% after, P

Newly synthesized histones are acetylated prior to their deposition into nucleosomes. Following nucleosome formation and positioning, they are rapidly deacetylated, an event that coincides with further maturation of the chromatin fiber. The histone deacetylases (HDACs) used for histone deposition and de novo chromatin formation are poorly understood. In the ciliate Tetrahymena thermophila , transcription-related deacetylation in the macronucleus is physically separated from deposition-related deacetylation in the micronucleus. This feature was utilized to identify an HDAC named Thd2, a class II HDAC that acts on newly synthesized histones to remove deposition-related acetyl moieties. The THD2 transcript is alternatively spliced, and the major form contains a putative inositol polyphosphate kinase (IPK) domain similar to Ipk2, an enzyme that promotes chromatin remodeling by SWI/SNF remodeling complexes. Cells lacking Thd2, which retain deposition-related acetyl moieties on new histones, exhibit chromatin and cytological phenotypes indicative of a role for Thd2 in chromatin maturation, including the proteolytic processing of histone H3.