Metastasis is the leading cause of death in colorectal cancer (CRC) patients, and the liver is the most common site of metastasis. Tumor cell metastasis can be thought of as an invasion-metastasis cascade and metastatic organotropism is thought to be a process that relies on the intrinsic properties of tumor cells and their interactions with molecules and cells in the microenvironment. Many studies have provided new insights into the molecular mechanism and contributing factors involved in CRC liver metastasis for a better understanding of the organ-specific metastasis process. The purpose of this review is to summarize the theories that explain CRC liver metastasis at multiple molecular dimensions (including genetic and non-genetic factors), as well as the main factors that cause CRC liver metastasis. Many findings suggest that metastasis may occur earlier than expected and with specific organ-anchoring property. The emergence of potential metastatic clones, the timing of dissemination, and the distinct routes of metastasis have been explained by genomic studies. The main force of CRC liver metastasis is also thought to be epigenetic alterations and dynamic phenotypic traits. Furthermore, we review key extrinsic factors that influence CRC cell metastasis and liver tropisms, such as pre-niches, tumor stromal cells, adhesion molecules, and immune/inflammatory responses in the tumor microenvironment. In addition, biomarkers associated with early diagnosis, prognosis, and recurrence of liver metastasis from CRC are summarized to enlighten potential clinical practice, including some markers that can be used as therapeutic targets to provide new perspectives for the treatment strategies of CRC liver metastasis. Colorectal cancer (CRC) is the world’s second leading cause of cancer deaths, and liver metastasis from CRC accounts for the majority of fatalities in CRC patients , 2. CRC’Many studies have found that cancer metastasis is a complex selective process influenced by anatomical, biological, and microenvironmental factors . Theorie+HLA-DR−/low MDSCs in CRLM patients were shown to inhibit T-cell proliferation and predict poor prognosis [According to a traditional model of metastatic spread, cancer cells undergo the following general steps known as metastatic cascade, which can be divided into two major phases: 1) dissemination from the primary lesion to distant organs by entering systemic circulation and adapting to a new microenvironment , and (2) colonization followed by expanding growth . The mulrognosis . ANGPTL1rognosis . Under hrognosis . In addirognosis . E-cadherognosis   disseminMetastasis is recognized as an evolutionary process, with the genomes carrying the archeological record of each metastatic cancer cell. Indeed, many genomic studies have been conducted to explain metastatic subclones’ emergence and and investigate the “timing, route, and direction” of metastatic spread . It appeCancer cells are thought to acquire metastatic capacity due to genetic and epigenetic changes. Genetic mutations can potentially disrupt epigenetic patterns, and the interaction between these two mechanisms can promote metastasis. , 39–42.Although numerous genetic alterations have been detected between the primary tumor and metastatic sites in CRC –45, muchSeveral whole-genome sequencing analyses on metastatic tumors have been performed in recent years to gain insight into the critical genetic events involved in CRLM. Several studies have been conducted to investigate single nucleotide variations (SNVs), mutated genes, and chromosome copy numbers of CRLM. An analysis of metastatic solid tumor genomes revealed that consistent genetic changes indicate cancer metastasis remains to be further identified . A pan-cSeveral studies have been conducted to identify frequently mutated genes involved in metastasis. For example, 707 genes have been identified as LM-associated genes, which specifically mutated in the LM regions but not in CRC tumors without liver metastasis, including ADAMTS10, NELL1, and RXFP3, implying their roles in liver metastasis. Furthermore, ADAP1 fusions were discovered in the RNA-seq dataset, indicating that ADAP1 was fused to GET4, SUN1, or NOC4L in an out-of-frame manner in the LM region. Two in-frame fusions of the ADAP1’s ArfGAP domain with proteins from GEMIN4 and TMEM8A have been discovered, which may facilitate metastasis by activating GTPase . A studyThe differences in chromosome copy number between primary and secondary tumors revealed that genetic aberrations in liver metastasis are a dynamic process, such as the presence of a focal amplification of chromosome 7p in primary tumors but not in the LM region. The loss or gain of copy number variations (CNVs) most likely allows clones to be more fit in a new environment . Anand aAccording to phylogenetic analysis of non-synonymous SNVs from the primary tumor and metastatic liver lesions, there were three main clonal evolution patterns from primary to liver metastases: clonal-clonal pattern (C–C) (early events), subclonal-clonal pattern (S–C) (middle-stage events), none-clonal pattern (0-C) (later events). In terms of CNV events, Chr 20q amp, 17p del, 18q del, and 8p del in clonal- clonal evolution were considered as early events, 8q amp in liver metastasis-specific evolution was considered as later events, and 8q amp, 13q amp, and 8p del in subclonal-clonal evolution were considered as middle-stage events. SYNE1 was a mutant gene with S–C clonal evolution characteristics. Its mRNA expression level in normal, CRC primary, and liver metastasis gradually decreased; however, its functional mechanism in CRLM remains unknown . Tumor mNo genetic changes have been identified as consensus metastasis-specific drivers in the process of CRC metastasis. However, epigenetic changes may provide an alternative mechanism to induce tumor cells for metastatic phenotypes . The corDysregulation in DNA methylation is the mainly studied DNA modification in tumor and metastasis . The met6A) is the most prevalent internal modification in messenger (m)RNA in eukaryotes, and recent studies have shown that m6A modification also exists in lncRNAs, Circular RNAs (circRNAs), and pre- Micro RNAs (pre-miRNAs), and plays essential roles for their biogenesis and functions [6A modification accelerates CRC progression and metastasis by promoting glycolysis in cancer cells, inducing immunosuppression in the tumor microenvironment, maintaining tumor cell stemness, and promoting chemoresistance [6A reader, was the most significantly upregulated m6A regulator in CRC cells. YTHDF1 activated RhoA signaling by binding to the m6A site of ARHGEF2 messenger RNA, leading to enhanced translation of ARHGEF2, and the YTHDF1-m6A-ARHGEF2 axis promoted the growth of CRC cell lines in primary organs as well as in lung and liver metastases [RNA N6-methyladenosine -like traits, EMT, and autophagy, among others, are linked to the acquisition of metastatic ability , 74. AccThe dominant view of hierarchical organization is a critical concept for understanding the role of cellular plasticity within cancer stem cells, differentiated cells, and cells in the intermediate state, which reflects cell–cell cooperation between different clones . Many stMany recent studies have looked into the relationships between CSCs and non-CSCs, as well as the role of cellular plasticity in CRC with metastasis. CSCs, as the tumor’s clonogenic core, have specific markers such as leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5). Because selective depletion of colon Lgr5 + CSCs prevented liver metastasis, the experimental evidence has proven that colon cancer-derived liver metastasis depends on a specific subpopulation of Lgr5 + cells. However, once the Lgr5 + cell consumption was stopped, the tumor regenerated rapidly, indicating that the tumor cannot be eliminated by ablating Lgr5 + cells. A study further discovered that colorectal tumors were maintained by proliferative Lgr5 − cells. Lgr5 − cells replenished the Lgr5 + cell pools to promote tumor growth. Furthermore, other experiments revealed a dynamic phenotype of Lgr5 cells that showed that Lgr5 re-expressed after arriving the support microenvironmrnt of the stem cell niche, but the most disseminated and seeding cells are Lgr5 − rather than Lgr5 + . Finally, both Lgr5 − and Lgr5 + cells were observed enriched in liver metastasis, and Lgr5 + cells were required for metastatic tumor growth, indicating that cellular plasticity is a deterministic step in the metastasis process  Fig. 3DD3D.The phenotypic properties of stem cells (such as CD44)  and theiThe tumor microenvironment includes innate and adaptive immune cells, stromal cells, endothelial cells, and cancer-associated fibroblasts. Since crosstalk between tumor cells and immune cells ultimately results in an environment that promotes tumor growth and metastasis, the tumor microenvironment is closely related to tumor formation and metastasis . CRLM isSeed-soil theory and pre-niche theory both support the idea that cancer metastasis is not random but rather organ-specific . Some reThe tumor microenvironment is made up of tumor stroma and tumor cells, and their interaction promotes cancer growth and metastasis . Cancer-The two cores of the tumor microenvironment are immunity and inflammation, but the relationship between the two is unclear. Inflammation promotes tumor development; persistent inflammatory cells and factors can transform the tumor-related inflammatory microenvironment into an immunosuppressive microenvironment, promoting tumor progression and metastasis .Influential microenvironmental factors may act as metastasis initiators in cancer cells, allowing them to spread to distant organs and establish metastasis at a secondary site. The cytoplasmic membrane-bound pattern recognition receptor nucleotide-binding oligomerization domain 1 (NOD1) receptor can recognize microorganisms and mediate inflammation. Under inflammatory stimulation, NOD1 promoted the metastatic phenotype of CRC cells via the p38 MAPK pathway. It enhanced the adhesion and metastasis of CRC cells to the liver sinusoids, as Henry Y. et al. It is demonstrated that NOD1 can be a novel target of inflammation-mediated cancer metastasis . WenjingAs the most common immune cells in the tumor microenvironment, macrophages play a critical regulatory role in the progression of inflammation and tumor metastasis. Circulating monocyte precursors are recruited to tumor sites, infiltrating tumors, termed TAMs. Macrophages have diverse phenotypes and functions, and at least two phenotypes of TAMs are involved in tumor promotion. Classically-activated (M1) macrophages secrete pro-inflammatory factors and pronounced anti-tumor activity, but the alternatively-activated (M2) macrophages can suppress the immune system by forming a barrier around invasive cells and establishing a “microenvironment” in which tumor cells can escape immune surveillance and metastasize. The intrinsic plasticity of TAMs controlled the balance between tumor-suppressing and tumor-promoting activities. . Li et aThe unpredictability of distant metastasis limits treatment options as well. Thus, identifying biomarkers for liver metastasis and treating CRC will benefit the patients . In TablIn recent years, mutated and differentially expressed genes have been identified as potential predictive and prognostic biomarkers for CRLM. The incidence of BRAF mutation in metastatic CRC is less than 10%, but BRAF V600E mutation is thought to be a relevant therapeutic target for metastatic CRC management. Although the data showed that CRC patients with KRAS mutations had a higher risk of liver metastasis, the difference was not statistically significant, and the risk of liver metastasis in patients with BRAF mutations was lower than that in patients with Wt BRAF. As a result, there was no clear link between KRAS and BRAF mutations and liver metastasis in patients with CRC . A multiERCC1 may serve as a predictive biomarker for the effectiveness of chemotherapy. The expression of ERCC1 was primarily examined in the relationship between CRC and liver metastasis. There was no clear evidence of a link between ERCC1 expression and concurrent/metachronous liver metastasis, and no evidence of a link between the primary tumor and liver metastasis was found. A study examines ERCC1 protein in primary colorectal cancer and corresponding liver metastases. Good reproducibility of IHC expression benefited ERCC1 as a predictive biomarker for platinum-based chemotherapy. However, no consistency has been observed when comparing IHC expression in primary tumors and matched liver metastases. It means ERCC1 expression of liver metastases can not be assessed in archived material (primary tumor biopsies), implying the need to use tissue from actual tumor burden to evaluate ERCC1 expression , 112. ThA study published in 2013 used array-based comparative genomic hybridization (aCGH) to examine genetic changes in metastatic site samples from two groups of CRC patients with liver metastases who had survival rates of less than five years and more than five years. Through survival analysis, metastatic tissue samples with whole chromosome 4 loss indicated a higher survival rate in the patients, implying that the absence of chromosome 4 may reduce the risk of recurrence of CRLM .Non-coding RNAs regulate the development and metastasis of CRC and have a significant effect on cancer biology. Moreover, the primary tumors release a variety of exosomes containing various LncRNAs to promote the formation of the anterior liver niche, molecules released by exosomes can be detected by liquid biopsy, and LncRNAs can be used as an effective biomarker to predict early metastasis, especially micrometastases that cannot be detected by pathological methods . Li Sun miRNA is a type of short single-stranded endogenous non-coding RNA that can bind to the 3'-untranslated region (3'-UTR) of mRNA to regulate transcription, resulting in translational inhibition. When miRNA expression in the plasma of CRC patients with and without liver metastases was compared, miR-21, miR-203, and miR-210 were significantly dysregulated in patients with liver metastatic CRC, indicating their roles as early detection biomarkers. Significantly downregulated miR-19a, miR-203, and miR-21 have been shown to have the ability to predict patients at high risk of recurrence .6A methyltransferase. METTL14’s downstream target was lncRNA XIST, according to Xiao Yang et al. Down-regulation of oncogenic lncRNA XIST via METTL14 inhibited CRC cell metastasis and growth; thus, METTL14 may be a promising therapeutic target [LncRNAs, typically > 200 bp in length, are natural prognostic biomarkers. Yiya and GAS5 expression were upregulated at liver metastasis compared with the primary CRC, and CRC patients with high expression of Yiya and GAS5 had a higher risk of liver metastasis. Yiya’s expression was found to be an independent risk factor for liver metastasis in early-stage patients using Cox proportional-risk regression analysis, suggesting that it could be the most potential predictive biomarker for liver metastasis . The mosc target .Hanchen Xu et al. discovered a difference in circRNA expression between tissue samples from CRC patients with and without liver metastasis. It was discovered that circRNA_0001178 and circRNA_0000826 might be potential diagnostic biomarkers for CRLM by constructing a circRNA-miRNA-mRNA network [Some small-scale cohort studies have discovered that various types of circulating molecules can be used as potential biomarkers for prognostic prediction of CRLM. However, their actual clinical applications were still minimal . There wCRC liver spread is difficult to detect very early, with limited treatment options and a poor prognosis, resulting in median survival of about six months for CRLM patients . There wCRC metastasis may occur at the stage of tumorigenesis. In recent years, genomic analysis in the difference between primary tumors and metastatic sites has challenged the notion that CRC metastasis is an early event. In addition to the evidence-based genomic analysis, the “seed-soil” theory and the formation of pre-niches also suggest that metastasis occurs at an early stage and that specific molecules secreted by the primary tumor predispose to the occurrence of CRC in the liver. “Parallel evolution” discovered that the genetic divergence between the primary tumor and the metastatic site is greater than that of the “linear evolution model”, implying that in CRC, some metastatic clones leave the primary site at an early stage and evolve further within the metastases . The cenThe role of molecular genetic changes in metastatic evolution is still largely unknown. Here, we found that epigenetic changes were more likely than genetic changes to be the direct driver of metastasis, and certain gene mutations were associated with specific metastasis patterns. However, studies at the genome level have demonstrated that metastatic CRC is of monoclonal and polyclonal origin and follows both monophyletic and polyphyletic seeding patterns. By identifying critical genes in metastatic evolution, it may be possible to improve the ability to determine whether CRC has metastasized. Recent research on the genome landscape of patients with metastatic CRC has revealed a link between mutant genes and metastasis patterns. S-C evolutionary pattern was associated with KRAS, SYNE1, CACNA1H, PCLO, FBXL2, and DNAH11 . HoweverClinical evidence indicates that reasonable combination strategies are essential in the clinical treatment and efficacy of CRC liver metastases . The tumThis review summarized the main perspectives related to metastasis, especially focusing on the factors influencing organ-specific metastasis. Beginning with general metastasis principles to understand the process of metastasis, we summarize and integrate the hypothesis of the metastatic evolution patterns (including origin of metastatic cloning and the pattern of metastatic seeding), genetic/epigenetic changes related to CRLM, molecular and cellular mechanisms, and biomarkers providing ideas for challenging metastatic CRC. The phenotypic change of CSCs is also one of the essential intrinsic factors for CRLM, which is a prerequisite for metastasis formation. For extrinsic factors of CRLM, cell/molecular interactions between tumor cells and the tumor microenvironment have been shown to mediate metastasis. Among them, CAFs are critical cellular components that induce CRLM, and the establishment of an immunosuppressive microenvironment has been established in the metastatic site. The relationship between inflammation and immune response needs to be further explored. Several central questions remain to be clarified: (1) Whether and what kind of the evidence based on the genome level can predict the potential of CRC to develop liver metastases in the early stage and predict the efficacy of immunotherapy, to provide a reference for clinical treatment strategies? (2) The dynamic evolution of cancer stem cell phenotypes is a prerequisite for CRLM. How can it be an effective therapeutic target or a biomarker for early detection? (3) Since macrophages and CAFs play an essential role in CRLM, whether they affect the organ tropism of metastasis? What is possible to detect CRLM early by detecting cell phenotypes in the tumor microenvironment? And whether can we predict a state of suppressive immune microenvironment for a tumor? Exploration of these issues will provide helpful information for early detection and appropriate treatment strategies for CRLM. Finally, we summarize the current therapeutic targets for CRLM, as well as diagnostic/prognostic biomarkers, and analyze the strengths and limitations of these methods, hoping to provide valuable clues for the diagnosis and treatment of CRLM.


There is substantial variability in prostate cancer (PCa) mortality rates across Caucasian American (CA), African American (AA), Asian, and Hispanic men; however, these estimates are unable to disentangle race or ethnicity from confounding factors. The current study explores survival differences in long‐term PCa outcomes between self‐reported AA and CA men, and examines clinicopathologic features across self‐reported CA, AA, Asian, and Hispanic men.This retrospective cohort study utilized the Center for Prostate Disease Research (CPDR) Multi‐center National Database from 1990 to 2017. Subjects were consented at military treatment facilities nationwide. AA, CA, Asian, or Hispanic men who underwent radical prostatectomy (RP) for localized PCa within the first year of diagnosis were included in the analyses. Time from RP to biochemical recurrence (BCR), BCR to metastasis, and metastasis to overall death were evaluated using Kaplan–Meier unadjusted estimation curves and adjusted Cox proportional hazards regression.p = 0.01); however, no difference was observed between AA and CA men for a time from BCR to metastasis  and time from metastasis to overall death .This study included 7067 men, of whom 5155 (73%) were CA, 1468 (21%) were AA, 237 (3%) were Asian, and 207 (3%) were Hispanic. AA men had a significantly decreased time from RP to BCR compared to CA men (HR = 1.25, 95% CI = 1.06–1.48, In an equal access health care setting, AA men had a shorter survival time from RP to BCR, but comparable survival time from BCR to metastasis and metastasis to overall death. Previous research has demonstrated significant differences in long‐term prostate cancer outcomes in Caucasian American compared to African American men. This study explored whether racial differences in long‐term oncological outcomes exist among men diagnosed with prostate cancer and treated surgically, in equal access health care settings. While African American men had slightly poorer biochemical recurrence‐free survival compared to Caucasian American men, there were no racial differences observed for distant metastasis‐free survival or overall survival, controlling for detailed clinical factors. In a large racially heterogeneous cohort of men within an equal access health care setting, long‐term prostate cancer outcomes were comparable across race. The primary aim of this study was to examine the relationship between CA and AA race and survival time from radical prostatectomy (RP) to BCR, BCR to metastasis, and metastasis to overall survival, controlled for a wide array of clinicopathologic relevant variables. A secondary study aim was to compare clinicopathologic variables across CA, AA, Hispanic, and Asian men.22.1A retrospective cohort study was conducted on patients enrolled in the Center for Prostate Disease Research (CPDR) Multi‐Center National Database in men with biopsy‐confirmed PCa who underwent RP treatment within 12 months of diagnosis between January 1, 1990 and December 31, 2017. Enrollees in the CPDR database are military health care beneficiaries who are eligible for TRICARE‐for‐life health care coverage. Demographic, clinical, treatment, and outcomes data were collected as part of routine patient follow‐up on all CPDR enrollees. Informed consent was obtained at the time of transrectal ultrasound‐guided biopsy (TRUS) for suspicion of PCa, as described previously.2.2Patient characteristics of interest in this study included: Age at diagnosis (years), time from RP to last follow up (years), time from diagnosis to RP (months), self‐reported race or ethnicity , obesity , number of medical comorbidities , PSA (ng/ml) at time of diagnosis, pathologic stage , 2014 ISUP Gleason score , surgical margin status , primary treatment year , post‐BCR PSA doubling time (PSADT) , any secondary treatment, BCR, metastasis, metastasis after BCR, death from any cause, and death from any cause after metastasis.2.3BCR was defined as a PSA value ≥0.2 ng/ml observed at ≥8 weeks post‐operatively, followed by a subsequent confirmatory PSA level ≥0.2 ng/ml or the initiation of salvage therapy.BCR, distant metastasis, and overall death were modeled as time‐dependent study endpoints with three possible results: Achieved endpoint, censored, or achieved end of study with no event. Men with <6 months of follow‐up time were excluded from each model. As an endpoint, distant metastasis must have occurred more than 1 year after PCa diagnosis. For the BCR endpoint, men were censored at treatment date between RP and BCR, date of last known medical visit, or date of death. For the distant metastasis and death endpoint, men were censored at the date of last known medical visit or date of death. Exclusions were also made for men who underwent adjuvant treatments between RP and BCR, between BCR and metastasis, or between metastasis and death, due to the variability and strong correlation of receipt of treatment with PSADT.2.4U test was used to compare categorical and continuous variables, respectively.All statistical analyses were performed using SAS version 9.4 . Frequencies and distributions of patient features were calculated for the study cohort, and stratified by race/ethnicity . The chi‐square test and Mann–Whitney P‐values were computed using two‐sided statistical tests (α = 0.05). PH assumptions were checked using the ASSESS PH statement in SAS, and each variable met the PH assumption.A Kaplan Meier curve analysis was used to produce 5‐, 10‐, and 15‐year probability estimates for survival from RP to BCR, BCR to metastasis, and metastasis to overall death as a function of race and race by obesity, restricted to AA and CA men. Cox proportional hazards (PH) analysis was used to model RP to BCR, BCR to distant metastasis, and distant metastasis to overall death as a time‐dependent outcome, as a function of race (CA versus AA). The Cox PH model from RP to BCR was controlled for age at RP, time from diagnosis to RP, primary treatment year, diagnostic PSA, obesity, pathologic stage, Gleason score, surgical margin status, and the number of major comorbidities. The BCR to metastasis Cox PH model was controlled for age at BCR, time from RP to BCR, obesity, pathologic stage, Gleason score, surgical margin status, and PSADT. The metastasis to overall death model was adjusted for age at metastasis, time from RP to metastasis, obesity, and the number of major comorbidities. Hazards ratios (HR) and 95% confidence intervals (CI) were reported for Cox PH models. 3p < 0.001), have a longer time from RP to last follow‐up , have PCa treatment in earlier years (p < 0.001), and have a longer post‐BCR PSADT (p = 0.11). AA men were less likely to have major comorbidity . Hispanic men were more likely to have a lower diagnostic PSA level . Asian men were less likely to be obese , and more likely to have a shorter time from diagnosis to RP , be diagnosed with the lowest pathologic prostate tumor stage and grade  and to receive another treatment after RP  , 1468 21%), 237 (3%), and 207 (3%) self‐reported as CA, AA, Asian, and Hispanic, respectively Figure . Median 1%, 237 (p = 0.005) .  men who had BCR in the overall cohort: 821 (20%) CA men and 256 (23%) AA men (Table ) Figure . Additio. Figure .p = 0.154)   men who had distant PCa metastasis following BCR in the overall cohort: 71 (80%) CA men and 16 (18%) AA men. The Kaplan–Meier analysis demonstrated that there was no difference in survival from BCR to metastasis among CA men compared to AA men (log‐rank ) Figure . There w) Figure .p = 0.035)   men who died following their metastatic PCa in the overall cohort: 82 (84%) CA men and 14 (14%) AA men (Table ) Figure . When ev) Figure .Survival time from RP to BCR was shorter for AA men compared to CA men , controlled for a wide array of demographic, clinical, and pathological relevant variables was examined as the primary study aim. Comparison of clinicopathologic variables across CA, AA Hispanic, and Asian race or ethnicity was assessed as a secondary study aim. Both analyses were conducted in a large retrospective cohort of racially diverse PCa patients treated with RP and enrolled in an equal access military health care system over a 28‐year period. This setting reduces the disparity in health care access, treatment, and education, which may influence PCa progression and provides a deeper analysis adjusted for potential confounders. This study supports that there is a positive association between AA race and BCR‐free survival when compared to CA race, but no difference between CA and AA race and survival time between BCR and metastasis, and metastasis and overall death. Furthermore, this analysis revealed that Asian and Hispanic American men have similar or better clinical and pathologic PCa features when compared to CA men. To our knowledge, this is the first study to look at long‐term PCa outcomes on a continuum: From RP to BCR, BCR to metastasis, and metastasis to overall survival, one of the largest RP cohorts comparing long‐term PCa outcomes for CA and AA men, and one of the largest known post‐RP cohorts of Asian and Hispanic American men.p = 0.18). However, despite a shorter BCR‐free survival time for AA men with a near equal proportion of men receiving treatment after BCR, there was no difference in survival time between BCR and metastasis and metastasis and overall death when comparing AA men to CA men. These data are confirmed by a recent analysis on patients who received HT after BCR in an equal access system, showing that race was not a predictor of DM or other adverse outcomes. Additionally, a recent analysis with the entire Department of Defense database revealed no difference in overall survival between AA and CA men diagnosed with PCa.Similar to other studies that have examined race and BCR‐free survival, our analysis also revealed a moderate significant decrease in BCR‐free survival time when comparing AA men to CA men, adjusted for confounding variables. When BCR occurs, the treatment team often recommends either androgen‐deprivation (HT) and/or salvage external beam radiation treatment (EBRT) usually happens. In our cohort, there was no significant difference between race and receipt of treatment after BCR  and do not necessarily reflect the views, opinions or policies of Uniformed Services University of the Health Sciences (USUHS), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., the Department of Defense (DoD), the Departments of the Army, Navy, or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government.Among men undergoing radical prostatectomy in an equal access health care setting, we identified and described a cohort of African American, Caucasian, Asian, and Hispanic men. While African American men had an increased risk of biochemical recurrence compared to Caucasian American men after controlling for prostate cancer prognostic factors, African American men experienced a similar risk of metastasis and overall death compared to Caucasian American men.Figure S1Click here for additional data file.


Tetrahymena thermophila ribozyme. The best design delivers a 93-fold dynamic range of splicing with RENDR controlling fluorescent protein production in response to an RNA input. We further resolve a thermodynamic model to guide RENDR design, show how input signals can be transduced into diverse outputs, demonstrate portability across different bacteria, and use RENDR to detect antibiotic-resistant bacteria. This work shows how transcriptional signals can be monitored in situ and converted into different types of biochemical information using RNA synthetic biology.Individual RNA remains a challenging signal to synthetically transduce into different types of cellular information. Here, we describe Ribozyme-ENabled Detection of RNA (RENDR), a plug-and-play strategy that uses cellular transcripts to template the assembly of split ribozymes, triggering splicing reactions that generate orthogonal protein outputs. To identify split ribozymes that require templating for splicing, we use laboratory evolution to evaluate the activities of different split variants of the  RNA provides a unique readout of a cell’s identity, physiologic status, and phenotype. Here the authors deliver an RNA sensing system that can use the information contained within cellular RNA to selectively control the activity of genetic programs. RNA thus provides a unique readout of a cell’s identity, physiologic status, and phenotype. The development of genetically-encoded technologies that are able to monitor and transduce individual RNA signals into orthogonal genetic outputs would advance cellular programming such that engineered components can be dynamically coupled with cell state to implement engineered functions3. Such technologies could, for example, realize genetic programs that are only active in response to species- and cell-specific signatures, link cell states to biochemical processes, and form the foundation for disease-state-sensing therapeutics. Likewise, transducing RNA signals into biomolecular reporters would allow for monitoring of RNA inside living cells to uncover quantitative temporal and spatial patterns of gene expression, and allow us to elucidate a deeper understanding of regulatory networks and the processes they control. Compared to monitoring proteins, RNA detection is an attractive option as it can be implemented using easily-designed Watson-Crick base pair interactions, operates on fast timescales4, expands the breadth of detection to include non-coding RNA5, and can theoretically access both geno- and phenotypic information of host cells. Thus, there is a strong motivation to create plug-and-play RNA detection platforms able to transduce intracellular RNA signatures into diverse, orthogonal biomolecular outputs for cell monitoring and genetic programming applications.Cells respond to environmental and intracellular signals by modulating the levels of a wide variety of biomolecules that ultimately determine cell physiology and phenotype. Regulatory mechanisms that operate at the transcriptional level represent a major control point in the process of converting instructions contained in the genome into proteins7. These systems are based on a protein output that is split into two inactive fragments, where interacting protein domains are translationally fused to each fragment. Upon interaction of the fused protein domains, the two fragments of the split-protein output are co-localized and the function of the protein is restored. As a result of the versatility of this approach, a wide range of protein outputs, from enzymes to transcription factors, have been engineered as split proteins14. Similarly, a variety of protein interaction domains have been used to sense and respond to specific chemical and cellular interactions, yielding an abundance of tools to detect protein-protein interactions15, sense small molecules16, and implement synthetic gene networks14.In protein engineering, technologies that use protein-protein interactions to control the functionality of an orthogonal protein output have been achieved using topological engineering of split proteins18. While the potential of using split-RNA reporters and split ribozymes for RNA sensing applications has been previously recognized21, these technologies typically suffer from limitations that include low dynamic range , a lack of quantitative design rules to guide the design of new detection interactions, and a lack of modularity for different classes of biomolecular outputs. To address these drawbacks, we have engineered a high-performing, plug-and-play RNA-sensing platform, which we call Ribozyme-ENabled Detection of RNA (RENDR). With RENDR, a cellular RNA input activates a splicing reaction that, in turn, produces an mRNA encoding any chosen orthogonal protein output. To achieve this regime, a splicing ribozyme is synthetically split into two non-functional fragments that are each appended with RNA guide sequences that are designed to interact with the RNA input. The split ribozyme is then inserted within the desired gene output. When present, the RNA input co-localizes the two transcribed ribozyme fragments, forming a functional ribozyme complex, and the ribozyme splices together the mRNA of the protein output. To create the RENDR platform, we first characterized nearly all potential split sites across the splicing ribozyme from Tetrahymena thermophila by applying for the first time a high-throughput laboratory evolution approach from protein engineering to engineer split RNA. Using this strategy, we profiled functional split sites across the ribozyme structure and identified split designs that allowed for high dynamic range of detection of up to 93-fold. We then investigated the design rules for RNA detection by systematically modifying the interactions between the RNA input and RENDR. By characterizing these variants, we derived a simple thermodynamic model that can guide the design of RENDR variants to transduce new RNA signals. To allow for the facile exchange of different genes encoding protein outputs, we explored a modular design strategy that we then harnessed to create RENDR variants that transduce RNA input signals into fluorescent, colorimetric, gaseous, and regulatory outputs. We then demonstrated that RENDR is functionally portable across different bacteria without the need for any genetic modifications. Finally, as a proof of principle application, we demonstrated that RENDR can be used to couple the production of pigment-producing enzymes to the presence of antibiotic resistance genes (ARG), creating a low-cost and facile approach to detecting antibiotic-resistant microbes.When it comes to RNA, programming synthetic RNA to interact with a given RNA signature through Watson-Crick base pairing is relatively straightforward, but transducing this interaction into a biomolecular output in a controlled and orthogonal manner remains challenging. Most RNA sensors have leveraged strand displacement mechanisms that use an RNA input to displace an inhibitory RNA structure, to allow for activation of an outputEscherichia coli (E. coli). To do this, a splicing ribozyme from Tetrahymena thermophila was inserted within the coding sequence (CDS) of a super folder green fluorescent protein (sfGFP) gene such that translation of the full-length protein is disrupted in the absence of splicing. Upon transcription and splicing, the ribozyme removes itself from the flanking exons and ligates together the exons to form a functional sfGFP mRNA, which is then translated to produce a fluorescent protein output  the ribozyme must be inserted immediately downstream of a uracil, which is required for splicing, and (2) the ribozyme should be inserted at a position within sfGFP such that translation of the first exon does not produce a fluorescent signal. Based on these criteria, we constructed a series of plasmids using several ribozyme insertion sites and measured the fluorescence produced by each in E. coli , we applied a high-throughput, transposon-mediated approach to create a near-complete library of split-ribozyme variants6. While this method has widely been used to optimize split proteins, it has not yet been utilized to engineer split RNA. In brief, this method uses a Mu transposase to incorporate a synthetic transposon into every position within the ribozyme sequence. Subsequent cloning steps replace the synthetic transposon with complementary RNA interaction sequences, which we call RNA guides, to create split ribozymes  to identify variants with high on and low off states in the absence and presence of the RNA inhibitor, respectively  are characterized by a conserved core region composed of the helical domains P4–P6 and P3–P728. In general, we observed these conserved regions to have a lower tolerance for split sites, with the exception of the P6 paired region. Taken together, these results suggest that the splicing ribozyme has a tolerance for split sites in specific regions across its sequence, particularly at sites that are surface accessible with low sequence conservation. Additionally, these results demonstrate the value of applying high-throughput protein engineering methodologies to RNA engineering applications.Next, to create a RENDR platform with a high dynamic range of detection, we turned our attention to identifying the optimal ribozyme split sites. An ideal ribozyme split site would destabilize complex formation between the two ribozyme fragments in the absence of RNA input, leading to off states with low signal output. In the presence of the RNA input, this site would have a high level of functional complementation, leading to on states with high signal output. While a few viable split sites within the splicing ribozyme have been identifiedmes Fig. . This RNmes Fig. . We perfely Fig. . To provely Fig. , 9. Overtes Fig. . As has 20. Fluorescence characterization revealed that five of these RENDR designs were functional, leading to higher fluorescence levels in the presence of the RNA input , catechol 2,3-dioxygenase (CatDe), and tetracycline resistance protein (TetA). To allow for the facile redesign of RENDR, a modular cloning strategy was created that allowed for the convenient exchange of different RNA guides /optical density at 600 nm (OD)) is linearly related to the difference in free energy between the IS and the ED. For this analysis, we only considered folding and interactions of the two RNA guides attached to each ribozyme fragment and the RNA input:R2 = 0.882)    Fig. . To valiFMO) gene from Methylophaga aminisulfidivorans st. MP33, which catalyzes the conversion of tryptophan-derived indole into indoxyl, which in turn spontaneously forms indigo. Characterization of this design (RENDR-FMO) in E. coli revealed tight control of indigo production in the absence of the RNA input, and strong induction of indigo synthesis in the presence of the RNA input  from S-adenosyl methionine (AdoMet) and bromide, and has been used as a reporter system for measuring gene expression in complex and non-transparent matrices like soils34. Characterization by GC/MS revealed RENDR-MHT could effectively control the production of CH3Br  assay, which uses a catalytically dead Cas9 (dCas9) protein to transcriptionally repress a genomically-encoded sfGFP gene, placing production of the dCas9 under the control of RENDR (RENDR-dCas9). This assay demonstrated strong repression in the presence of the RNA input, suggesting that dCas9 production can be regulated by an RNA signal using RENDR —a widely used component for gene expression control and genetic circuit design38. Measuring T7 RNAP production from a modular RENDR design using a T7 promoter-sfGFP reporter, we initially noticed a high leak in the off state and significant toxicity . To resolve this, we opted for a split T7 RNAP design13 containing an R632S mutation previously shown to reduce toxicity39. These modifications allowed us to successfully couple RENDR to control the production of T7 RNAP  gene and used the indigo-producing gene, FMO, as an output  and in response output a pigment-producing enzyme that would allow for simple colorimetric detection by eye. Leveraging the plug-and-play nature of RENDR, we exchanged the RNA sensing components to detect a kanamycin resistance , which we posit could limit the specificity of detection. Our RENDR platform addresses these limitations by allowing for the control of theoretically any protein output and yields a high dynamic range of sensing of longer RNA sequences. RENDR could also be used in conjunction with RNA-responsive sgRNAs to exert an additional layer of control. For example, a multiple RNA input AND gate can be generated by pairing current RNA-regulated sgRNA technologies with RENDR-activated Cas proteins. This implementation, and other combinations of RNA tools, could be impactful in adding regulatory specificity to these systems and reducing Cas-derived burden on cells.RENDR delivers a high-performing, plug-and-play RNA detection platform that complements current technologies for transducing RNA signals for cellular programming applications. For example, RNA-responsive CRISPR-Cas single guide RNAs (sgRNAs) have been engineered to form self-inhibiting structures that can be released by a strand displacement reaction with a target RNA18. Like RENDR, toehold switches can control a diversity of protein outputs and offer a high dynamic range of sensing in a variety of contexts. However, toehold switch designs require the addition of amino acids to the start of the CDS, which could interfere with protein structure-function and consequently limit the modularity of these systems. RENDR is not bound by this requirement and may be better suited to regulate a wide variety of protein outputs, Additionally, unlike translation-based RNA-sensor technologies, RENDR is not limited to protein outputs and can in principle be coupled to outputs mediated by nucleic acids . Finally, toehold switches have only been functionally demonstrated in E. coli. As we have shown, RENDR is functionally portable across different Gram-negative bacteria without any genetic modification, and we anticipate that it could be easily ported into other classes of microbes and eventually mammalian cells. This is an important advantage of RENDR, which we believe will facilitate efforts to expand synthetic biology into non-model chassis and consortia. While powerful, we recognize further work is required to achieve the full potential of RENDR. Using RENDR to detect low-abundant endogenous transcripts will require more detailed investigations of the sensitivity and potentially require optimization of the system. Taken together, RENDR expands and complements the RNA synthetic biology toolbox for the transduction of native RNA for cellular programming.The toehold switch, another RNA-sensing device, allows access to the RBS, and consequently translation, of an mRNA sequence in response to an RNA target through a programmable strand displacement reaction43. Here we highlight the potential of engineering large catalytic RNA for synthetic biology applications using laboratory evolution. Specifically, we demonstrate how theoretical and experimental approaches from protein engineering can be easily leveraged to rapidly engineer structurally complex RNA for new capabilities. For example, while in vitro transposon mutagenesis coupled with high-throughput screening has been widely applied to create split, fused, and circularly permutated proteins6, our work represents the first attempt to systematically apply this method for engineering synthetic RNA functions. While we have demonstrated the power of applying these approaches toward creating RNA-sensing split splicing ribozymes, we expect that this is just the beginning. Circular permutation of RNA, for example, would offer distinct topological modifications, which in protein engineering have been used to yield proteins that are optimized for fusion44, have synthetic sensing capabilities45, or offer enhanced and expanded functional characteristics compared to wild-type topologies47. Similarly, topological engineering could be applied to other natural and synthetic ribozymes offering different chemistries or catalytic properties48. Thus, in the coming years, we envision topological engineering of large catalytic RNA to be used to further expand the structure-function landscape of RNA tools.Within the field of RNA synthetic biology, topological engineering of large RNA represents a currently untapped route to diversify and optimize this biomolecule. To date, most synthetic RNA technologies have focused on the rational and computational design of small, non-coding RNA regulators such as small RNA, riboswitches, small self-cleaving ribozymes, and CRISPR RNA49. While this can be achieved by labeling endogenous genes with fluorescent markers , RENDR provides an alternative approach to achieve this that circumvents the need for time-consuming and arduous genome engineering. Compared to other RNA-templated detection reactions, such as fluorescence in situ hybridization (FISH) that depend upon the use of fixed cells, RENDR can be deployed in living cells and allows for dynamic measurements. Beyond direct RNA monitoring, we anticipate RENDR will see broad utility for implementing genetic programs in response to cell phenotype, physiology, and identity. For example, in bacteria, coupling genetic programs to species-specific RNA signatures using RENDR would provide a route to create genetic programs that only function in the desired target host, a goal that is difficult to achieve using traditional regulatory elements  that often function across related species. Similarly, by coupling genetic programs to specific RNA signatures, we anticipate it will be possible to use RENDR to implement burden- and growth-driven feedback within genetic programs. Such feedback control systems are of critical importance to achieve robustness in engineered functions under fluctuating demands for resources and differing environmental conditions50, and to optimize metabolic processes51. Finally, we anticipate that RENDR could be an impactful tool for mammalian synthetic biology to, for example, create therapeutic genetic programs that sense and respond to biomarkers of disease52. Taken together, we predict that the broad utility of RENDR will advance both basic science and application-driven research in the coming years.Dynamic monitoring of RNA in living cells is a valuable sensing modality. Understanding temporal patterns of transcription is critical to uncovering a deeper understanding of gene regulatory networks and the processes they controlAll plasmids used in this study are listed in Supplementary Table E. coli, V. natriegens, and S. oneidensis strains according to Supplementary Table E. coli, plasmids were transformed into chemically competent Escherichia coli str. K-12 substr. MG1655 (E. coli MG1655) or TG1 cells, plated on LB-agar plates containing the appropriate antibiotics (LB-agar-Ab) according to Supplementary Table V. natriegens, plasmids were electroporated into electrocompetent cells made from V. natriegens cells mixed in electroporation buffer  and pulsed at 0.9 kV using a MicroPulser Electroporator (Bio-rad). Electroporated cells were recovered at 37 °C for 1 h, plated onto LB3-agar (25 g/L LB broth (Fisher), 20 g/L NaCl (Fisher), 15 g/L Agar (Fisher)) with antibiotics according to Supplementary Table g for 1 min and resuspending in with the same volume of PBS. Bulk fluorescence measurements were performed on 50 µL of washed culture diluted in 50 µL of PBS. For experiments using S. oneidensis, plasmids were electroporated into electrocompetent cells made from S. oneidensis cells washed 3 times with 10% glycerol and pulsed at 1.2 kV using the same electroporator as above. Electroporated cells were recovered at 30 °C for 2 h, plated onto LB-agar-Ab plates according to Supplementary Table Fluorescence measurements were performed in various transformed E. coli, V. natriegens, or S. oneidensis transformed with combinations of empty control plasmids pJEC101, pJEC102, or pJEC103, referred to here as blank cells. Blank cells do not express reporter genes, only antibiotic resistance genes, and were used to determine autofluorescence levels. OD and FL values for each colony were first corrected for by subtracting the mean value of the media blank from the respective value of the experimental conditions. The ratio of the corrected FL to the corrected OD (FL/OD) was then calculated for each well.Each 96-well block included at least two sets of controls; a media blank and https://taborlab.github.io/FlowCal/]. Gated biological replicates were combined into a single dataset and resulting data was plotted using the Matplotlib (v3.6.2) package [https://matplotlib.org/].FCS files containing flow cytometry data collected on the Sony Biotechnology SH800 Cell Sorter were analyzed using a custom Python script. In brief, FCS files were imported and cells were gated using a high-low gate on forward scatter vs side scatter plots using the FlowCal (v1.3.0) package  - [FL/OD (+AHL)])/sqrt(2), and variants were split into tertiles based on their distance. Tertiles for each replicate were compared across duplicates and variants in the top two tertiles in both replicates were considered functional. Functionally-validated variants were pooled from glycerol stocks into 45 mL LB-Ab cultures and grown overnight at 37 °C at 250 rpm. Plasmid DNA of the pooled culture was isolated using a Midiprep Kit (Qiagen) and PCR was used to generate amplicons containing the 5’ fragment of the split-ribozyme. After column purification, the PCR product was sent for NGS   version 4.0.0.2755. Briefly, 1.5 mL of each cell culture was centrifuged for 10 min at 13,000 × g. Pellets were resuspended in 100 µL water, 1 mL of DMSO was added, and samples were vortexed. To quantify the yield, 100 µL of extracted indigo was added to a 96-well plate and the OD at 620 nm was measured for all samples. An optimized growth protocol was used for characterization in the experiment performed in Fig. 4, 0.1 mM CaCl2) with appropriate antibiotics was used, cultures were grown for 48 h instead of 24 h, and indigo was extracted from 5 mL of culture.Plasmids were transformed as described for fluorescence measurements. Colonies  were used to inoculate 300 µL of LB-Ab in a 96 deep-well plate overnight at 37 °C at 1000 rpm. For each overnight culture, 100 µL was transferred to a 5 mL LB-Ab culture containing 5 mM tryptophan and grown to saturation at 37 °C at 250 rpm for 24 h. Indigo was extracted from cultures using dimethyl sulfoxide (DMSO)g for 1 min followed by resuspension in 1 mL M63 medium 2SO4, 68 g KH2PO4, 0.00025 g FeSO4.7H2O, 30 mL 6 M KOH to pH = 7, water up to 1 L], and water up to 250 mL). Washed cells were diluted to OD 600 = 0.05 with M63 medium in a final volume of 1 mL in 2 mL Phenomenex glass vials and subsequently crimped every 2.5 min to account for the time it takes the Gas Chromatography/Mass Spectrometry (GC/MS) instrument to process each sample. Crimped glass vials were grown at 37 °C at 250 rpm for 6 h. A GC/MS containing an Agilent 8890 gas chromatograph fit with an Agilent 7693A autosampler and a 5977B mass spectrometer was used to measure samples. The Agilent MassHunter Workstation Quantitative Analysis software (v10.0) was used to quantify resulting methyl-bromide and carbon dioxide (CO2) production. To account for cell density, the methyl-bromide production was normalized to CO2 concentration for each sample.Plasmids were transformed as described for fluorescence measurements. Colonies  were used to inoculate 50 mL tubes with 5 mL LB-Ab and grown overnight at 37 °C at 250 rpm. Cells were washed and normalized to a fixed OD before being transferred to GC-MS vials. Briefly, 1 mL of each overnight culture washed three times by centrifugation at 13,000 × p-values of less than 0.05 for experimental sample measurements compared to blank cell measurements were considered significantly different.The sample average and standard deviation (s.d.) were calculated from the replicates of each sample in all experiments. Significance in all experiments was assessed using a homoscedastic two-sample t-Test with an alpha of 0.05. In all cases, resulting E. coli strain MG1655. Plasmids were transformed and colonies were used to inoculate 5 mL of LB-Ab and incubated at 37 °C at 250 rpm overnight. Following incubation, 100 µL of each overnight culture was used to inoculate 5 mL of pre-warmed LB-Ab and grown for 6 h. After growth, 500 µL of each culture was centrifuged at 13,000 × g for 1 min and the supernatant removed. Pellets were resuspended in 750 µL of Trizol reagent (Thermo Fisher Scientific) and incubated at room temperature for 5 min, then 150 µL of chloroform was added, mixed by vortexing for 15 s, and incubated at room temperature for 3 min. After incubation, samples were centrifuged for 15 min at 12,000 × g at 4 °C and the top aqueous layer isolated and 1 µL of RNA-grade glycogen  and 375 µL of isopropanol were added. The solution was then incubated at room temperature for 10 min and centrifuged at 4 °C at 13,000 × g for 15 min. After centrifugation, the isopropanol was carefully removed, pellets were washed in 600 µL of chilled 70% ethanol, and samples were centrifuged at 4 °C at 13,000 × g for 2 min. Following removal of the ethanol, the pellets were centrifuged again at 4 °C at 13,000 × g for 2 min to ensure the complete removal of the ethanol. Pellets were air dried for 5 min and resuspended in 18 µL of RNase-free water.RNA extractions and quantitative PCR measurements were performed in biological triplicate using g at 4 °C for 10 min. After centrifugation, 190 µL of the top aqueous layer was removed and added to 190 µL of chloroform. Samples were vortexed for 10 s, incubated for 3 min at room temperature, and centrifuged at 13,000 × g at 4 °C for 10 min. After centrifugation, 170 µL of the top aqueous layer was removed and added to 170 µL of chloroform. Samples were vortexed for 10 s, incubated for 3 min at room temperature, and centrifuged at 13,000 × g at 4 °C for 10 min. After centrifugation, 120 µL of the top aqueous layer was removed and mixed with 1 µL of RNA-grade glycogen, 360 µL of chilled 100% ethanol, and 12 µL of 3 M sodium acetate. Samples were mixed by pipetting and incubated at −80 °C for at least 1 h. After incubation, the samples were centrifuged for 30 min at 13,000 × g at 4 °C. After removing the supernatant, the resulting RNA pellets were washed with 600 µL of chilled 70% ethanol and centrifuged at 4 °C at 13,000 × g for 10 min. After centrifugation, the ethanol was removed, and the pellets were centrifuged at 4 °C at 13,000 × g for 2 min. Ethanol wash was repeated a second time to ensure the complete removal of any remaining ethanol. Pellets were air dried for 5 min and resuspended in 12 µL of RNase-free water.The concentration of all samples was measured with a Qubit fluorometer (Thermo Fisher Scientific). For each sample, 1.5 µg of total RNA  was digested by Turbo DNase (Thermo Fisher Scientific) according to the manufacturer’s instructions. After digestion, 150 µL of RNase-free water and 200 µL of phenol-chloroform were added to each tube. The samples were then mixed by vortexing for 10 s, incubated at room temperature for 3 min, and centrifuged at 13,000 × sfGFP standard was analyzed in parallel. The standard curve was used to determine the relative abundance of sfGFP cDNA in all tested samples and to infer the efficiency of the qPCR primer set (85%). Results were analyzed using CFX Manager Software (v3.1) (Biorad). Briefly, the standard curve was used to determine the starting quantity (SQ) of the sfGFP cDNA in each reaction. The SQ values of technical replicates for each sample were then averaged to give a single value for each biological replicate. The mean and s.d of biological replicates were then calculated for each sample type.The concentration of all samples was measured with a Qubit fluorometer. To anneal primers for cDNA synthesis reactions, 75 ng of total RNA, 0.5 µL of 2 µM reverse transcription primer, 1 µL of 10 mM dNTPs (New England BioLabs), and RNase-free water (up to 6.5 µl) were combined. This mixture was then incubated at 65 °C for 5 min and cooled on ice for 5 min. For reverse transcription, 0.25 µL of Superscript III reverse transcriptase (Thermo Fisher Scientific), 1 μL of 100 mM Dithiothreitol (DTT), 1× first-strand buffer (Thermo Fisher Scientific), 0.5 µL RNaseOUT (Thermo Fisher Scientific), and RNase-free water up to 3.5 µL were then added to the annealed primer reaction, and the total mixture was incubated at 55 °C for 1 h, 75 °C for 15 min, and then stored at −20 °C. The resulting cDNA samples were subsequently analyzed via qPCR on a CFX Connect Real-Time PCR system (Bio-Rad). Each biological sample for each condition was analyzed in three technical replicates in a 96-well microplate covered with an optically clear seal. Total RNA samples were also analyzed as non-reverse transcription controls (NRT) to confirm that no DNA could be detected under the conditions used. Additionally, a non-template control was run to confirm that no non-specific amplification was present. For each technical replicate, a reaction was prepared by mixing 5 µL of Maxima SYBR green qPCR master mix (Thermo Fisher Scientific), 2 µL of cDNA and 0.5 µL of 2 µM forward and reverse sfGFP qPCR primers, and RNase-free water up to 10 µL. For the reaction, the following program was used: 50 °C for 2 min, 95 °C for 10 min, followed by 30 cycles of 95 °C for 15 s and 60 °C for 1 min. Melting curve analysis was run after all measurements to ensure that only a single product was amplified. For quantification, a standard curve covering four ten-fold serial dilutions of an Further information on research design is available in the Supplementary InformationReporting Summary


Regulated transgene expression is an integral component of gene therapies, cell therapies and biomanufacturing. However, transcription factor-based regulation, upon which most applications are based, suffers from complications such as epigenetic silencing that limit expression longevity and reliability. Constitutive transgene transcription paired with post-transcriptional gene regulation could combat silencing, but few such RNA- or protein-level platforms exist. Here we develop an RNA-regulation platform we call “PERSIST" which consists of nine CRISPR-specific endoRNases as RNA-level activators and repressors as well as modular OFF- and ON-switch regulatory motifs. We show that PERSIST-regulated transgenes exhibit strong OFF and ON responses, resist silencing for at least two months, and can be readily layered to construct cascades, logic functions, switches and other sophisticated circuit topologies. The orthogonal, modular and composable nature of this platform as well as the ease in constructing robust and predictable gene circuits promises myriad applications in gene and cell therapies. Gene circuits must resist epigenetic silencing for reliable therapeutic applications. Here the authors develop an RNA-level regulation platform using CRISPR endoRNases that is modular, scalable, and more stable than traditional transcriptional versions. However, hurdles such as epigenetic silencing challenge the therapeutic and biomanufacturing potential of these strategies. Epigenetic silencing is the prevention of gene expression that is typically regulated by DNA methylation and chromatin remodeling 8. Epigenetic silencing of transgenes has been observed in many therapeutically-relevant cell types including stem cells9, neurons10, and CHO cells11, and inhibits the engineered functions of these cells over time. While the location of genomic integration has been shown to be one factor that effects silencing17, other emerging factors such as features of promoter sequences22 and preferences for a transcriptionally active state26 make transcription factor-based gene regulation unsuitable in many contexts.Transcription factor-based gene regulation in mammalian systems remains a cornerstone of both basic biological research and the field of synthetic biology. Transcription factor-promoter pairs such as the Tet-On or Tet-Off systems28, and may also find use in modern therapeutic modalities such as mRNA gene therapies. Other options are the new protein-based protein-regulation platforms that use orthogonal proteases31 to control protein degradation. The field would benefit from the development of protein-based RNA-regulation platforms with similar properties that enable control of protein production, e.g., for regulation of secreted proteins. Some protein-based RNA-level regulators exist, mainly using translational repressors34 and RNA-cleaving Cas proteins41, but there is still a great need for demonstrated scalability and composability. Also, all of these examples canonically act as only repressor-like “OFF” switches; several RNA-based activator-like “ON” switches have been developed44, but none of these are composable for circuit engineering. The field currently lacks an RNA-acting activation/repression toolkit that is scalable, robust, modular, and composable to use in place of transcription factors.Recently developed post-transcriptional platforms comprising activator- and repressor-like regulators may be able to address this silencing problem. Such platforms would allow the use of constitutive promoters routinely employed in gene therapy, which tend to resist silencingHere we develop a post-transcriptional regulation platform that exploits RNA cleavage to control transcript degradation. We term this platform “Programmable Endonucleolytic Scission-Induced Stability Tuning” (PERSIST). We use CRISPR-specific endoribonucleases (endoRNases) as effectors for RNA cleavage-based regulation and adapt a set of nine that are orthogonal in their cleavage to serve as RNA-level “activators” and “repressors”. We create RNA-level ON-switch and OFF-switch motifs that can be engineered into the untranslated regions (UTRs) of transcripts and can be modified with a cognate endRNase RNA target sequence to be activated or repressed by specific endoRNases. The endoRNases exhibit up to 300-fold dynamic range as repressors and up to 100-fold dynamic range as activators in the PERSIST platform. When benchmarked against Tet-On, this regulatory modality is less vulnerable to silencing compared to transcriptional regulation because it can make use of vetted constitutive promoters routinely used in gene and cell therapies.We demonstrate that our endoRNase platform exhibits modularity and composability by creating multi-level cascades, all 16 two-input Boolean logic functions, and a positive feedback motif. A useful feature of this platform is that these endoRNase regulators can function as both activators and repressors simultaneously, which allows for compact engineering of previously complex motifs such as a feed-forward loop and RNA-level bistable switch. The performance and simplicity of the PERSIST platform, combined with its resistance to silencing, will enable the facile construction of genetic circuits with extended functional lifetimes for applications in biomanufacturing, gene therapies, and engineered cell therapies.45 or endoribonucleases47, can reduce transgene expression  of the degradation motif, “wt1”, within the 3′ UTR , repeats of these RNA degradation motifs represent a flexible way to fine-tune mRNA half-life.First, we sought to identify a mechanism that leads to rapid mRNA degradation. A natural short 8bp RNA motif has been recently identified that binds heterogeneous nuclear ribonucleoproteins, which in turn recruit deadenylase complexes, resulting in mRNA degradation in a variety of cell types56 has been used in several synthetic biology studies to stabilize engineered transcripts57. When we inserted the MALAT1 triplex upstream of 30 repeats of the wt1 degradation motif, the expression of the EYFP reporter remained low  structure from the MALAT1 long-noncoding RNA47 and here we show that it can be repurposed to activate expression when its cleavage site is placed within the PERSIST-ON motif  to activate the expression of the TRE promoter. We engineered both the Tet-On and PERSIST switches to drive the expression of the fluorescent protein mKO2 and compared it to a control construct encoding constitutive mKO2 expression from a hEF1a promoter  has been used as a translational repressor in mammalian synthetic biology previously61. Importantly, these endonucleases cleave short, specific (often hairpin-structured) sequences called direct repeats, and orthologs of these endonucleases are thought to cleave their respective direct repeats orthogonally62. We hypothesized that these Cas6 and Cas13 families could provide a large number of parts that orthogonally cleave mRNAs when their cognate cleavage domain is engineered into the transcript. We evaluated nine total endonucleases, four from the Cas6 family: Csy4, Cse3 (TthCas6e)63, CasE (EcoCas6e)64 and Cas6 (PfuCas6-1)65 and five from the Cas13 family: LwaCas13a36, PspCas13b39, PguCas13b39, RanCas13b39, and RfxCas13d40. Since Csy4 and all of the Cas13 family endonucleases have previously been used in mammalian cells, only Cse3, CasE, and Cas6 required mammalian codon optimization; we made several other modifications to the Cas13 family endonucleases to improve performance and ensure compatibility with other endonucleases  renders it cleavable only by Cse3 and not CasE. As seen in Fig. We first evaluated the orthogonality of the Cas proteins by testing each Cas protein with every pairwise combination of Cas-responsive PERSIST-OFF and -ON reporters  motif provides redundant regulation, where regulation of a downstream gene via multiple pathways often yields a greater dynamic range. We hypothesized that a cFFL could increase the dynamic range of the PERSIST-ON response to an endoRNAse input. In our cFFL, CasE acts as the input and Csy4 as an intermediate node, where both act on the output  from the level of the regulated substrate (mRNA) we have been able to simplify the design and composition of post-transcriptional regulatory motifs, which may allow these platforms to be used in more complex circuits. Together, both protease-based platforms and our PERSIST platform represent important steps in the synergistic development of post-transcriptional regulation capabilities for use in a wide variety of applications. Importantly, all post-transcriptional platforms enable the use of vetted strong constitutive promoters that resist epigenetic silencing. We show that the PERSIST platform can resist epigenetic silencing for at least 2 months, which can provide important benefits for durable long-term conditional gene expression in cell-based therapies and biomanufacturing.Here we present a composable, scalable, and programmable RNA activation/repression platform that can be used in place of transcription factors. While other post-transcriptional platforms exist , to our knowledge, PERSIST is the first RNA-regulation platform that has demonstrated both composable activator- and repressor-like regulators. Protease-based regulation platforms74 or multiple parts75. Therefore, it may be possible to extend the PERSIST platform for the detection of single-input and multi-input endogenous RNA cleavers such as disease-relevant endoRNases, ribozymes, and miRNAs.Activation of an endoRNase by another endoRNase shown here was enabled by our development of an RNA-level ON switch, which has been a challenge in the field due to the fact that translation is typically “on” by default. While a primary focus of the work described here is endoRNase-based activation, we also explore whether our PERSIST-ON-switch can be directly activated by two other types of RNA cleavers: ribozymes  parts as published previouslyl-Glutamine (Corning), and 1% MEM Non-Essential Amino Acids (Gibco). CHO-K1 cells (ATCC) were maintained in Ham’s F-12K (Kaighn’s) medium supplemented with 10% FBS (Corning), 1% Penicillin–Streptomycin-l-Glutamine (Corning), and 1% MEM Non-Essential Amino Acids (Gibco). Doxycycline Hyclate  was diluted in water at 10 mg/μL, stored at −20 ∘C, and used at a final concentration of 4 μM for experiments. Trichostatin A  was diluted in DMSO, stored at −20 ∘C, and used at a final concentration of 100 nM for experiments.HEK293FT (Invitrogen) cells were maintained in Dulbecco’s modified Eagle medium  supplemented with 10% FBS (Corning), 1% Penicillin–Streptomycin-HEK293FT cell transfections were performed using Lipofectamine 3000 (invitrogen) with a 1.1:1.1:1 Lipofectamine 3000:P3000:DNA ratio in 24-well or 96-well format. Complexes were prepared in Opti-MEM (Gibco). 150,000–200,000 cells or 30,000–50,000 cells were plated on the day of transfection into 24-well or 96-well plates, respectively, in culture media without antibiotics and analyzed by flow cytometry after 48 hours. CHO-K1 cell transfections were performed using Lipofectamine LTX (invitrogen) with a 4:1:1 LTX:Plus Reagent:DNA ratio in 24-well or 96-well format. Complexes were prepared in Opti-MEM (Gibco). Cells were plated on the day of transfection and analyzed by flow cytometry after 48 hours.59. For payload integration, cells were transfected with engineered construct and BxBI expressing plasmid in 12-well plate format. After 3 days, media was supplemented with 8 μg/mL puromycin (invivogen) and 10 μg/mL blasticidin (invivogen). Cells were maintained under selection for 2 weeks with fresh media containing antibiotics refreshed every 2 days. After 2 weeks, cell lines were evaluated for response and underwent single-cell sorting.Constructs were integrated into CHO-K1 cells that had been previously engineered with a landing pad in their putative Rosa26 locusCell fluorescence was analyzed with LSR Fortessa flow cytometer, equipped with 405, 488, 561, and 637 nm lasers (BD Biosciences). The following laser and filter combinations were used to evaluate the fluorescent proteins used in transient transfection experiments in this study: tagBFP, 405 nm laser, 450/50 filter; EYFP, 488 nm laser and 515/20 nm filter; mKO2, 561 nm laser, 582/42 filter; iRFP, 640 nm laser, 780/60 filter. See Supplementary Fig. nlinfit function  and output  expression levels using the Further information on research design is available in the Supplementary InformationReporting SummaryPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1


This quality improvement project was a collaboration between an adult, inpatient female psychiatric intensive care unit (PICU) in South London and the Sexual and Reproductive Health Rights, Inclusion and Empowerment (SHRINE) programme. SHRINE is a London-based programme delivering SRH care to any individual with serious mental illness, substance misuse and/or learning disability.The primary aim of this quality improvement project was to assess patients’ sexual and reproductive (SRH) needs, and the acceptability of providing SRH assessments in a female PICU setting. Secondary aims were to explore the barriers to access and the feasibility of providing SRH assessments and SHRINE interventions in the PICU.A bi-monthly SRH in-reach clinic and a nurse led SRH referral pathway were implemented on the PICU over a seven-month period. Within a quality improvement framework, a staff training needs assessment was performed, training delivered, a protocol developed, staff attitudes explored, and patient and carer engagement sought.30% of women were identified as having unmet SRH needs and proceeded to a specialist appointment, representing a 2.5-fold increase in unmet need detection. 42% of women were assessed, representing a 3.5-fold increase in uptake. 21% of women initiated SRH interventions of which 14% had all their SRH needs met.Results identified SRH needs for PICU admissions are greater than realised. Staff highlighted the acceptability and importance of SRH care, if interventions are appropriately timed and the patient’s individual risk profile considered. Providing a nurse-led referral pathway for an SRH in-reach clinic is acceptable, feasible and beneficial for PICU patients.No significant relationships.


Genetic and epigenetic reprogramming caused by disease states in other tissues is always systemically reflected in peripheral blood leukocytes (PBLs). Accurate transcriptional readouts of Messenger RNA (mRNA) and Long non-coding RNA (lncRNA) in peripheral blood leukocytes are fundamental for disease-related study, diagnosis and treatment. However, little is known about the impact of preanalytical variables on RNA quality and downstream messenger RNA and Long non-coding RNA readouts. In this study, we explored the impact of RNA extraction kits and timing of blood placement on peripheral blood leukocyte-derived RNA quality. A novel enhanced evaluation system including RNA yields, purity, RNA integrity number (RIN) values and β-actin copies was employed to more sensitively identify RNA quality differences. The expression levels of informative mRNAs and Long non-coding RNAs in patients with chronic obstructive pulmonary disease (COPD) or triple-negative breast cancer (TNBC) were measured by Quantitative reverse transcription polymerase chain reaction (qRT–PCR) to investigate the impact of RNA quality on transcriptional readouts. Our results showed that the quality of RNA extracted by different kits varies greatly, and commercial kits should be evaluated and managed before batch RNA extraction. In addition, the quality of extracted RNA was highly correlated with the timing of blood placement, and the copy number of β-actin was significantly decreased after leaving blood at RT over 12 h. More importantly, compromised RNA leads to skewed transcriptional readouts of informative mRNAs and Long non-coding RNAs in patients with chronic obstructive pulmonary disease or triple-negative breast cancer. These findings have significant implications for peripheral blood leukocyte-derived RNA quality management and suggest that quality control is necessary prior to the analysis of patient messenger RNA and Long non-coding RNA expression. Peripheral blood leukocytes (PBLs) often act as proxies for disease states since they can systemically reflect genetic and epigenetic reprogramming in other tissues . RNA, whRNA yields, purity and RNA integrity number (RIN) are routinely used as standard indicators to estimate RNA quality . RecentlQuantitative reverse transcription polymerase chain reaction (qRT–PCR) is the most commonly used technique for detecting mRNA and lncRNA expression and verifying the candidates of RNA-seq . Some reVarious methods have been developed to purify PBL-derived RNA, and the red blood cell (RBC) lysis method has been primarily recommended for biobanks for further research . In receOur results showed that the yields of RNA extracted by TRIzol were slightly higher than those of RNA purified by kit 1 and kit 2, while the mean yields of RNA extracted by kit 3 were half as low as those of RNA purified by TRIzol, kit 1 and kit 2 ; Table 1DdPCR was performed to detect the variance of β-actin copies to more accurately evaluate the inconsistencies of RNA in each group. In ddPCR, the reaction is divided into at least 10,000 partitions, and 40 cycles of classical PCR are carried out in each of these impervious nanocompartments. Those partitions with the amplified product are designated positive, and those with no amplified product are designated negative. Quantification was then achieved using Poisson statistics by counting fluorescence-positive and total droplet numbers  Figure . As the Although the fresher the better is the golden rule when dealing with clinical samples, in most cases, blood collection and further RNA extraction are always conducted at different times and in different spaces, so it is necessary to find a balance between the storage conditions and RNA quality. Whereas previous studies have demonstrated that the storage temperature and duration are critical to RNA quality, the conclusion needs more verification due to the limited samples and evaluation system .To explore the impact of the timing of blood placement at RT on the quality of PBL-derived RNA, sixty tubes of blood were placed on the lab bench at RT for 0, 30, 60, and 90 min before RNA extraction with kit 1 . Our res+ T lymphocytes, neutrophils, and macrophages are the main types of immune cells of the local inflammatory milieu (etc.) and lncRNAs  in peripheral blood mononuclear cells (PBMCs) from COPD patients versus smokers  were heavily reliant on RNA integrity . AdditioIn this study, we first assessed the effects of extraction kits and timing of blood placement on PBL-derived RNA quality. A novel enhanced evaluation system including RNA yields, purity, RIN values and β-actin copies was employed to identify RNA differences. We found that the quality of RNA extracted by kit 1 and kit 2 was comparable to that of RNA purified by TRIzol, and kit 1 had a better performance than kit 2 in RIN values and β-actin copies. However, RNA extracted by kit 3 was subjected to severe degradation due to the lack of RNase inactivator, suggesting that kit evaluation and management should be performed before RNA extraction in batches. In addition, placement of blood at RT over 12 h significantly compromised the copy number of β-actin, indicating that the timing of blood placement at RT should be within 12 h to obtain desirable RNA. More importantly, the relative transcriptional readouts of the informative mRNAs and lncRNAs in patients with TNBC or COPD were heavily dependent on the quality of extracted RNA, and improper preanalytical handling may lead to skewed results. Our findings thus exhibited significant implications for PBL-derived RNA quality assessment and downstream qRT–PCR analysis.In brief, 5 ml blood in each sample was centrifuged at 1,500 g for 10 min at 4°C. After centrifugation, three different fractions are distinguishable: The upper layer is plasma; the intermediate layer is buffy coat, which concentrates leukocytes; and the bottom layer contains concentrated erythrocytes. The buffy coat was then harvested, and RBC lysis buffer was added to lyse the remaining erythrocytes. After centrifugation, total WBCs were harvested from the pellets. The following procedure was carried out according to the manufacturer’s instructions for the evaluated RNA extraction kits .A COPD patient was eligible for this study if he met the following criteria: smoking history (≥20 pack years); postbronchodilator FEV1 ≥ 25% of the predicted value and postbronchodilator FEV1/forced vital capacity (FVC) ≤ 0.70; and no history of asthma, atopy  or any other active lung disease.A TNBC patient was eligible for this study if she met the following criteria: grade 2 or 3 infiltrating ductal carcinoma with negative expression of ER, PR and HER2 proteins or accompanied by medullary features, infiltrating micropapillary carcinoma, or occasional vascularized thrombus.versus negative droplets were read by a QX200™ Droplet Reader, and the absolute quantification of β-actin was calculated using QuantaSoft software (Bio-Rad). Primer sequences for ddPCR are listed in The yields and purity of extracted RNA were assessed by using a denovix spectrophotometer. The absorption at UV 260 nm was used to assess the RNA yields, and the ratio of 260 nm and 280 nm was used to evaluate RNA purity. An Agilent 4150 Bioanalyzer and the RNA 6000 Nano LabChip kit were employed to calculate the RNA Integrity Number (RIN). The RIN index ranges from 1 to 10, with 1 indicating the greatest degradation and 10 being the most intact RNA . The copThe relative transcriptional readouts of the informative mRNAs and LncRNAs in patients with COPD or TNBC were measured by qRT–PCR. Quantitative PCR was performed with SYBR Green Real-Time PCR Master Mix  in the Real-Time PCR System . The cycling profile was as follows: initial denaturation at 95°C for 5°min, followed by 40 cycles with 20 s at 95°C, 20 s at 60°C and 30 s at 72°C. The expression level of β-actin was used as an internal control. Primer sequences for qRT–PCR are listed in t-test and analysis of variance. Multiple comparison correction was conducted by Tamhane’s T2 (or T2’) and LSD(L) test for normally distributed data with unequal or equal variances, respectively. P < .05 was considered to indicate a statistically significant difference.Statistical analysis was performed using SPSS version 21 (IBM Corp.). All statistical graphs were constructed using Prism 8.0 . All the results are presented as the mean ± standard deviation (SD). The comparison between groups was drawn through


The purpose of this study was to validate undersampled single-photon emission computed tomography (SPECT) imaging using a combination of compressed sensing (CS) iterative reconstruction (CS-IR) and offset acquisition.Three types of numerical phantoms were used to evaluate image quality and quantification derived from CS with offset acquisition. SPECT images were reconstructed using filtered back-projection (FBP), maximum likelihood-expectation maximization (ML-EM), CS-IR, and CS-IR with offset acquisition. The efficacy of CS-IR with offset acquisition was examined in terms of spatial resolution, aspect ratio (ASR), activity concentration linearity, contrast, percent coefficient of variation (%CV), and specific binding ratio (SBR).The full widths at half maximum remained unchanged as the number of projections decreased in CS-IR with offset acquisition. Changes in ASRs and linearities of count density were observed for ML-EM and CS-IR from undersampled projections. The %CV obtained by CS-IR with offset acquisition was substantially lower than that obtained by ML-EM and CS-IR. There were no significant differences between the %CVs obtained from 60 projections by CS-IR with offset acquisition and from 120 projections by FBP. Although the SBRs for CS-IR with offset acquisition tended to be slightly lower than for FBP, the SBRs for CS-IR with offset acquisition did not change with the number of projections.CS-IR with offset acquisition can provide good image quality and quantification compared with a commonly used SPECT reconstruction method, especially from undersampled projection data. Our proposed method could shorten overall SPECT acquisition times, which would benefit patients and enable quantification with dynamic SPECT acquisitions.  Projection data, which are obtained by rotating the gamma camera, are required from 64 to 128 views based on the sampling theorem (T (99mTc . Therefo Compressed sensing (CS) is a signal processing technique that was initially proposed for sparse signal recovery, and CS iterative reconstruction (CS-IR) can be performed from fewer data than typical images 123I-ioflupane SPECT from undersampled projection data. CS-IR reduced the projection number and total acquisition time by approximately two-thirds without decreasing the image quality and quantification. However, CS-IR was not appropriate for very small projection numbers because, while it can mitigate the effects of streak artifacts and projection numbers, the reconstructed images exhibit a specific patchy pattern behavior. Therefore, further reductions in the projection number and the total acquisition time require the introduction of different characteristics to the CS-IR algorithm., 7. In C Takahashi et al. developed wide-angle offset acquisition to reduce the projection number and the total acquisition time . Offset  In this study, we achieved a shorter acquisition time from undersampled SPECT imaging data using a combination of our CS-IR method and offset acquisition. We evaluated the quality and quantification of the SPECT imaging data obtained from undersampled projection data by CS-IR with offset acquisition (CS-IR with offset) using digital mathematical and striatal numerical phantoms.Phantom design Three types of numerical phantoms were used to evaluate image quality and quantification . SpatialSimulation conditions Simulating Medical Imaging Nuclear Detectors (SIMIND) Monte Carlo program version 6.2 was used to generate the projection data , 12. TheImage reconstruction Image reconstruction from onset acquisition (current SPECT acquisition) was performed by maximum likelihood-expectation maximization (ML-EM) and CS-IR , 13. In p is the projection data and  Where Data analysis The spatial resolutions were calculated as the full width at half maximum (FWHM) of the 2D (x- and y-axis) linear profiles in the transaxial images. The FWHMs obtained for the two axes were averaged. The image distortion was assessed by the aspect ratio (ASR) asFWHMradial and FWHMtangential are the FWHM values in the radial and tangential directions, respectively. The linearity of the count density was examined by comparing the reconstructed SPECT counts and simulated values. Six circular regions of interest (ROIs) with areas of 80 mm2 were placed on the multi-cylinder parts and the mean SPECT counts were measured. We also investigated the properties of CS-IR with offset using the percent coefficient of variation (%CV) and specific binding ratio (SBR). Where 2) were set on the 3D- Rectangle ROIs  was significantly lower than that obtained by ML-EM and CS-IR (p<0.05). The %CVs obtained from 120 projections were 7.2%±3.6% by FBP, 8.0%±3.6% by ML-EM, 6.9%±4.2% by CS-IR, and 6.1%±4.6% by CS-IR with offset. The %CVs obtained from 60 projections were 8.8%±4.1% by ML-EM, 7.7%±4.5% by CS-IR, and 7.0%±3.6% by CS-IR with offset. CS-IR with offset reduced the image noise level by 3.2%–26% compared with CS-IR. There was no significant difference between the %CV obtained from 60 projections by CS-IR with offset and that obtained from 120 projections by FBP.IR, and CS-IR with offset than by FBP. However, SBRs showed minimal change for CS-IR with offset for different number of projections as some difference was observed. SPECT images of the 3D-SDB phantom are shown in streak artifacts and TV-specific patchy patterns appeared in the undersampled CS recon-structed images (8–30 projections), these artifacts were mitigated by CS-IR with offset images. In particular, a sharp outline of the striatum and cerebral parenchyma was only maintained by CS-IR with offset from 8–15 projections. In image acquisition, the total acquisition time depends on the number of projections and the shoot acquisition time per projection. Because the total acquisition time affects the image quality and quantification, it is balanced by the need to acquire sufficient counts. One way to shorten acquisition times is to reduce the number of projections in a 360° acquisition.  Although this approach is simple, reducing the number of projections can decrease the image quality and increase the number and prominence of streak artifacts. Therefore, we assessed the effect of a combination of CS iterative reconstruction and offset acquisition from undersampled projection data. Our results indicated that CS-IR with offset improved the image quality without decreasing the quantification compared with FBP and CS-IR. In addition, it is possible that CS-IR with offset enables a greater reduction in the number of projections because a sharp outline of the striatal phantom is obtained from 8–15 projections. In previous studies, offset acquisition has enabled a reduction in the number of projections while maintaining the image quality for brain and myocardial SPECT , 14. In  To assess the spatial resolution and linearity of count density, we used the FWHM, ASR, and relative count density of the reconstructed images. Although the FWHMs and ASRs obtained by the ML-EM and CS-IR methods changed as the number of projections decreased, the FWHM and ASR obtained by CS-IR with offset remained constant. Furthermore, a significant correlation was observed between the reconstructed SPECT counts and simulated values by all reconstruction methods. However, the linearity of the count density for small projection numbers (8–15 projections) was only retained by CS-IR with offset. The optimal number of projections for SPECT images is defined by the sampling theorem .  In addition, we demonstrated that a larger number of projections is not essential for iterative reconstruction techniques, including CS iterative reconstruction . The com %CVs increased as the number of projections decreased. However, CS-IR with offset decreased the image noise level compared with ML-EM and CS-IR. In addition, the %CV values obtained by CS-IR with offset from 60 projections were significantly lower than those obtained by FBP from 120 projections. In this study, a reduction in the number of projections implied a decrease in the total acquisition time and counts because the acquisition time per projection was kept stable. Our results indicate that offset acquisition is a good approach for undersampled SPECT imaging by CS iterative reconstruction, considering our previous findings. However, the effect of CS reconstruction was restricted in comparison with our previous study. The reason for this result is the β value setting. L1 regularization by TV strongly depends on the hyper-parameter β values. Although image uniformity is improved, a specific patchy pattern is visible in reconstructed images when the β values are higher. Therefore, we used β=0.001 (lower than in the previous study) because offset acquisition was expected to improve the image quality. Nevertheless, the combination of CS reconstruction with offset acquisition enabled a reduction in image noise with both regular and smaller projection numbers. β values are key to controlling the effect of the CS algorithm . Further work is required to optimize the CS parameters for different SPECT imaging approaches. Although the SBRs obtained by CS-IR with offset were slightly lower than those obtained by FBP, our results showed that the values were similar. These results are also consistent with those obtained from smaller numbers of projections. Based on the results of linearity and image uniformity, offset acquisition seems to show a clear advantage for CS-based SPECT reconstruction regardless of the number of projections. However, the SBR values obtained by CS with offset acquisition were under-estimated. We did not perform resolution recovery because our aim was simply to evaluate the effect of CS-IR with offset. Further work is required to include the resolution recovery technique in CS with offset acquisition. In SPECT image reconstruction, it is clear that theoretically unrealistic reconstruction conditions from a small number of projections decrease the reconstructed image quality, especially by FBP. However, the striatum and brain detail was clearly visible by ML-EM and CS reconstruction under theoretically unrealistic reconstruction conditions. In particular, CS-IR with offset provided better reconstructed images compared with ML-EM and CS-IR from only 8 projections. This result raises the possibility of rapid dynamic SPECT acquisition using a commercially available dual-head SPECT camera. Our CS-IR with offset method can shorten overall SPECT acquisition times by drastically reducing the number of projections. Although validation of the proposed algorithm is necessary before its use with a variety of SPECT imaging techniques, the combination of CS reconstruction and offset acquisition will potentially be useful for studying dynamic perfusion or parametric imaging with SPECT. In this study, because we developed a challenging novel approach for rapid SPECT acquisition, offset acquisition is not implemented on current SPECT system. Although the image processing is needed to be implemented, it is possible that offset acquisition using continuous-mode acquisition with the small step angle. Our study has several main limitations. First, we performed only digital phantom research and our results might hold best when the acquisition count is sufficient. Image acquisition and reconstruction should be evaluated for several uptake patterns. Therefore, it is necessary to evaluate the effect of CS-IR with offset in clinical examinations using commercially available devices. Second, neither scatter nor attenuation was investigated in our simulation because the aim was simply to evaluate the effect of CS-IR with offset from undersampled projection data. Third, our simulation conditions were performed only one of the commercially available SPECT/CT device with collimator, and the Butterworth filter setting was fixed. Finally, resolution recovery improves the spatial resolution of SPECT images; thus, future studies should examine CS reconstruction including resolution recovery.  We evaluated CS reconstruction combined with offset sampling acquisition from undersampled projections. Our algorithm provides good image quality and quantification from undersampled sparse-view SPECT projection data. A combination of CS reconstruction and offset sampling shortened the overall SPECT acquisition times, which would help to reduce motion artifacts and improve patient comfort in clinical SPECT imaging. This article does not contain any studies with human participants or animals. The authors have no conflicts of interest to declare.