Exploring the role of CD8+ T cells in clear renal cell carcinoma metastasis.

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 75-80% of all patients with renal cell carcinoma. Despite its prevalence, little is known regarding the key components involved in ccRCC metastasis. In this study, scRNA-seq analysis was employed to classify CD8+ T cells into four sub-clusters based on their genetic profiles and immunofluorescence experiments were used to validate two key clusters. Through gene set enrichment analysis, these newly identified sub-clusters were found to exhibit distinct biological characteristics. Notably, TYMP, TOP2A, CHI3L2, CDKN3, CENPM, and RZH2 were highly expressed in these sub-clusters, indicating a correlation with poor prognosis. Among these sub-clusters, CD8+ T cells (MT-ND4) were identified as potentially playing a critical role in mediating ccRCC metastasis. These results contribute to our understanding of CD8+ T cell heterogeneity in ccRCC and shed light on the mechanisms underlying the loss of immune response against cancer.

Amplification of Hippo Signaling Pathway Genes Is Governed and Implicated in the Serous Subtype-Specific Ovarian Carcino-Genesis.

Among women, ovarian cancer ranks as the fifth most common cause of cancer-related deaths. This study examined the impact of Hippo signaling pathway on ovarian carcinogenesis. Therefore, the signatures related to Hippo signaling pathway were derived from the molecular signatures database (MSigDB) and were used for further analysis. The Z score-based pathway activation scoring method was employed to investigate the expression patterns of these signatures in the mRNA expression profiles of ovarian cancer cohorts. Compared to other subtype tumors, the results of this study show that the Hippo signaling pathway signatures are dysregulated prominently in serous subtype-specific ovarian carcinogenesis. A receiver operating characteristic (ROC) curve-based results of the Hippo gene set, yes-associated protein 1 (YAP1), and mammalian sterile 20-like kinases 1 (MST1) genes can predict the serous subtype tumors by higher specificity and sensitivity with significant areas under the curve values also further reconfirmed these signaling dysregulations. Moreover, these gene sets were studied further for mutation analysis in the profile of high-grade serous ovarian adenocarcinoma in the cBioPortal database. The OncoPrint results reveal that these Hippo signaling pathway genes are amplified highly during the grade three and stage third or fourth of serous type ovarian tumors. In addition, the results of the Dependency Map (DepMap) plot also clearly show that these genes are amplified significantly across the ovarian cancer cell lines. Finally, overall survival (OS) curve plot investigations also revealed that these gene expressions show poor survival patterns linked to highly expressed conditions in serous subtypes of ovarian cancer patients with significant p-values (p < 0.05). Thus, the current finding would help to develop the targeted therapies treatment for serous subtype ovarian carcinogenesis.

BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations.

Methods to detect malignant lesions from screening mammograms are usually trained with fully annotated datasets, where images are labelled with the localisation and classification of cancerous lesions. However, real-world screening mammogram datasets commonly have a subset that is fully annotated and another subset that is weakly annotated with just the global classification (i.e., without lesion localisation). Given the large size of such datasets, researchers usually face a dilemma with the weakly annotated subset: to not use it or to fully annotate it. The first option will reduce detection accuracy because it does not use the whole dataset, and the second option is too expensive given that the annotation needs to be done by expert radiologists. In this paper, we propose a middle-ground solution for the dilemma, which is to formulate the training as a weakly- and semi-supervised learning problem that we refer to as malignant breast lesion detection with incomplete annotations. To address this problem, our new method comprises two stages, namely: (1) pre-training a multi-view mammogram classifier with weak supervision from the whole dataset, and (2) extending the trained classifier to become a multi-view detector that is trained with semi-supervised student-teacher learning, where the training set contains fully and weakly-annotated mammograms. We provide extensive detection results on two real-world screening mammogram datasets containing incomplete annotations and show that our proposed approach achieves state-of-the-art results in the detection of malignant breast lesions with incomplete annotations.

DUB3 is a MAGEA3 deubiquitinase and a potential therapeutic target in hepatocellular carcinoma.

Although melanoma-associated antigen A3 and A6 (MAGEA3/6)-specific tumor vaccines have shown antitumor effects in melanoma and non-small cell lung cancer (NSCLC), many cancers do not respond because MAGEA3 can promote cancer without triggering an immune response. Here, we identified DUB3 as the MAGEA3 deubiquitinase. DUB3 interacts with, deubiquitinates and stabilizes MAGEA3. Depletion of DUB3 in hepatocellular carcinoma (HCC) cells results in MAGEA3 degradation and P53-dependent growth inhibition. Moreover, DUB3 knockout attenuates HCC tumorigenesis in vivo, which can be rescued by restoration of MAGEA3. Intriguingly, pharmacological inhibition of DUB3 by palbociclib promotes degradation of MAGEA3 and inhibits tumor growth in preclinical models implanted with parental HCC cells but not with DUB3 knockout HCC cells. In patients with HCC, DUB3 is highly expressed, and its levels positively correlate with MAGEA3 levels. Taken together, DUB3 is a MAGEA3 deubiquitinase, and abrogating DUB3 enzymatic activity by palbociclib is a promising therapeutic strategy for HCC.

An Interpretable and Accurate Deep-Learning Diagnosis Framework Modeled With Fully and Semi-Supervised Reciprocal Learning.

The deployment of automated deep-learning classifiers in clinical practice has the potential to streamline the diagnosis process and improve the diagnosis accuracy, but the acceptance of those classifiers relies on both their accuracy and interpretability. In general, accurate deep-learning classifiers provide little model interpretability, while interpretable models do not have competitive classification accuracy. In this paper, we introduce a new deep-learning diagnosis framework, called InterNRL, that is designed to be highly accurate and interpretable. InterNRL consists of a student-teacher framework, where the student model is an interpretable prototype-based classifier (ProtoPNet) and the teacher is an accurate global image classifier (GlobalNet). The two classifiers are mutually optimised with a novel reciprocal learning paradigm in which the student ProtoPNet learns from optimal pseudo labels produced by the teacher GlobalNet, while GlobalNet learns from ProtoPNet's classification performance and pseudo labels. This reciprocal learning paradigm enables InterNRL to be flexibly optimised under both fully- and semi-supervised learning scenarios, reaching state-of-the-art classification performance in both scenarios for the tasks of breast cancer and retinal disease diagnosis. Moreover, relying on weakly-labelled training images, InterNRL also achieves superior breast cancer localisation and brain tumour segmentation results than other competing methods.

ASPP2 Is Phosphorylated by CDK1 during Mitosis and Required for Pancreatic Cancer Cell Proliferation.

(1) Background: pancreatic cancer is highly lethal. The role of apoptosis-stimulating protein of p53-2 (ASPP2) in this lethal disease remains unclear. This protein belongs to the ASPP family of p53 interacting proteins. Previous studies in this lab used phosphate-binding tag (Phos-tag) sodium dodecyl sulfate (SDS) polyacrylamide gels and identified a motility upshift of the ASPP family of proteins during mitosis. (2) Purpose: this study expands on previous findings to identify the detailed phosphorylation regulation of ASPP2 during mitosis, as well as the function of ASPP2 in pancreatic cancer. (3) Methods: the Phos-tag technique was used to investigate the phosphorylation mechanism of ASPP2 during mitosis. Phospho-specific antibodies were generated to validate the phosphorylation of ASPP2, and ASPP2-inducible expression cell lines were established to determine the role of ASPP2 in pancreatic cancer. RNA sequencing (RNA-Seq) was used to uncover the downstream targets of ASPP2. (4) Results: results demonstrate that ASPP2 is phosphorylated during mitosis by cyclin-dependent kinase 1 (CDK1) at sites S562 and S704. In vitro and in vivo results show that ASPP2 is required for pancreatic cancer growth. Furthermore, the expressions of yes-associated protein (YAP)-related genes are found to be dramatically altered by ASPP2 depletion. Together, these findings reveal the phosphorylation mechanism of ASPP2 during mitosis. Collectively, results strongly indicate that ASPP2 is a potential target for abating tumor cell growth in pancreatic cancer.

Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images.

Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images. UAD is an important medical image analysis (MIA) method to be applied in disease screening problems because the training sets available for those problems usually contain only normal images. However, the exclusive reliance on normal images may result in the learning of ineffective low-dimensional image representations that are not sensitive enough to detect and segment unseen abnormal lesions of varying size, appearance, and shape. Pre-training UAD methods with self-supervised learning, based on computer vision techniques, can mitigate this challenge, but they are sub-optimal because they do not explore domain knowledge for designing the pretext tasks, and their contrastive learning losses do not try to cluster the normal training images, which may result in a sparse distribution of normal images that is ineffective for anomaly detection. In this paper, we propose a new self-supervised pre-training method for MIA UAD applications, named Pseudo Multi-class Strong Augmentation via Contrastive Learning (PMSACL). PMSACL consists of a novel optimisation method that contrasts a normal image class from multiple pseudo classes of synthesised abnormal images, with each class enforced to form a dense cluster in the feature space. In the experiments, we show that our PMSACL pre-training improves the accuracy of SOTA UAD methods on many MIA benchmarks using colonoscopy, fundus screening and Covid-19 Chest X-ray datasets.

Functional connectomic profile correlates with effective anterior thalamic stimulation for refractory epilepsy.

BACKGROUND: Deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) is an effective treatment for refractory epilepsy; however, seizure outcome varies among individuals. Identifying a reliable noninvasive biomarker to predict good responders would be helpful. OBJECTIVES: To test whether the functional connectivity between the ANT-DBS sites and the seizure foci correlates with effective seizure control in refractory epilepsy. METHODS: We performed a proof-of-concept pilot study of patients with focal refractory epilepsy receiving ANT-DBS. Using normative human connectome data derived from 1000 healthy participants, we investigated whether intrinsic functional connectivity between the seizure foci and the DBS site was associated with seizure outcome. We repeated this analysis controlling for the extent of seizure foci, distance between the seizure foci and DBS site, and using functional connectivity of the ANT instead of the DBS site to test the contribution of variance in DBS sites. RESULTS: Eighteen patients with two or more seizure foci were included. Greater functional connectivity between the seizure foci and the DBS site correlated with more favorable outcome. The degree of functional connectivity accounted for significant variance in clinical outcomes (DBS site: |r| = 0.773, p < 0.001 vs ANT-atlas: |r| = 0.715, p = 0.001), which remained significant when controlling for the extent of the seizure foci (|r| = 0.773, p < 0.001) and the distance between the seizure foci and DBS site (|r| = 0.777, p < 0.001). Significant correlations were independent of variance in the DBS sites (|r| = 0.148, p = 0.57). CONCLUSION: These findings suggest that functional connectomic profile is a potential reliable non-invasive biomarker to predict ANT-DBS outcomes. Accordingly, the identification of ANT responders could decrease the surgical risk for patients who may not benefit and optimize the cost-effective allocation of health care resources.

A Review on Multiple I-III-VI Quantum Dots: Preparation and Enhanced Luminescence Properties.

I-III-VI type QDs have unique optoelectronic properties such as low toxicity, tunable bandgaps, large Stokes shifts and a long photoluminescence lifetime, and their emission range can be continuously tuned in the visible to near-infrared light region by changing their chemical composition. Moreover, they can avoid the use of heavy metal elements such as Cd, Hg and Pb and highly toxic anions, i.e., Se, Te, P and As. These advantages make them promising candidates to replace traditional binary QDs in applications such as light-emitting diodes, solar cells, photodetectors, bioimaging fields, etc. Compared with binary QDs, multiple QDs contain many different types of metal ions. Therefore, the problem of different reaction rates between the metal ions arises, causing more defects inside the crystal and poor fluorescence properties of QDs, which can be effectively improved by doping metal ions (Zn2+, Mn2+ and Cu+) or surface coating. In this review, the luminous mechanism of I-III-VI type QDs based on their structure and composition is introduced. Meanwhile, we focus on the various synthesis methods and improvement strategies like metal ion doping and surface coating from recent years. The primary applications in the field of optoelectronics are also summarized. Finally, a perspective on the challenges and future perspectives of I-III-VI type QDs is proposed as well.

ZHX2 deficiency enriches hybrid MET cells through regulating E-cadherin expression.

Growing evidence indicates that the epithelial to mesenchymal (E/M) hybrid state plays a key role in tumorigenesis. Importantly, a hybrid mesenchymal to epithelial transition (MET) state in which individual cells express both epithelial and mesenchymal markers was recently identified in vivo, further strengthening the bonds between the hybrid EMT state and cancer progression. However, the role and the molecular mechanisms by which the hybrid MET state is maintained in triple-negative breast cancer cells (TNBC) remain elusive. Here, we find that loss of ZHX2 expression results in the hybrid MET phenotype in mesenchymal TNBC cells. Mechanistically, through directly binding to the CDH1 promoter, depletion of ZHX2 specifically reactivates expression of CDH1 encoding E-cadherin, an epithelial marker that is crucial for maintaining epithelial phenotype. Functionally, loss of ZHX2 expression enriches the hybrid MET cells and inhibits the migration and dissemination of TNBC cells or organoids, which could be reversed by restoration of E-cadherin. Moreover, depletion of ZHX2 suppresses lung metastasis in preclinical models of TNBC. In patients with TNBC, ZHX2 expression was amplified and negatively correlated with the expression of E-cadherin. These findings suggest that loss of ZHX2 promotes the hybrid MET state to impair TNBC progression.

Improved Luminous Efficiency of AgInS2 Quantum Dots and Zeolitic Imidazolate Framework-70 Composite for White Light Emitting Diode Applications.

The application of multiple quantum dots (QDs) in the field of white light emitting diodes (WLEDs) is still an important challenge due to their low luminous efficiency and quenching phenomenon. In this paper, we prepared AgInS2 QDs/zeolitic imidazolate framework-70 (AIS/ZIF-70) composite by a microwave hydrothermal method. Owing to the high porosity and stability of ZIF-70, it could effectively prevent quenching issues due to the aggregation of QDs. Since the ZIF-70 and QDs were chemically bonded, the formation of the ZnS layer could effectively passivate the surface defect and thus the quantum yield reached 21.49 % in aqueous solution. The luminous efficiency (LE) of the assembled AIS/ZIF-based WLED was reinforced by 6.8 times with a molar ratio of AgIn/Zn=18, i. e. at 5.26 % molar fraction of ZIF-70. Moreover, the color rendering index (CRI) and correlated color temperature (CCT) of AIS/ZIF-based WLED were 84.3 and 3631 K, respectively, indicating its potential application in solid-state lighting.

Multi-trait genomic selection improves the prediction accuracy of end-use quality traits in hard winter wheat.

Improvement of end-use quality remains one of the most important goals in hard winter wheat (HWW) breeding. Nevertheless, the evaluation of end-use quality traits is confined to later development generations owing to resource-intensive phenotyping. Genomic selection (GS) has shown promise in facilitating selection for end-use quality; however, lower prediction accuracy (PA) for complex traits remains a challenge in GS implementation. Multi-trait genomic prediction (MTGP) models can improve PA for complex traits by incorporating information on correlated secondary traits, but these models remain to be optimized in HWW. A set of advanced breeding lines from 2015 to 2021 were genotyped with 8725 single-nucleotide polymorphisms and was used to evaluate MTGP to predict various end-use quality traits that are otherwise difficult to phenotype in earlier generations. The MTGP model outperformed the ST model with up to a twofold increase in PA. For instance, PA was improved from 0.38 to 0.75 for bake absorption and from 0.32 to 0.52 for loaf volume. Further, we compared MTGP models by including different combinations of easy-to-score traits as covariates to predict end-use quality traits. Incorporation of simple traits, such as flour protein (FLRPRO) and sedimentation weight value (FLRSDS), substantially improved the PA of MT models. Thus, the rapid low-cost measurement of traits like FLRPRO and FLRSDS can facilitate the use of GP to predict mixograph and baking traits in earlier generations and provide breeders an opportunity for selection on end-use quality traits by culling inferior lines to increase selection accuracy and genetic gains.

ADMANI: Annotated Digital Mammograms and Associated Non-Image Datasets.

Supplemental material is available for this article. Keywords: Mammography, Screening, Convolutional Neural Network (CNN) Published under a CC BY 4.0 license. See also the commentary by Cadrin-Chênevert in this issue.

Composite dietary antioxidant index negatively correlates with osteoporosis among middle-aged and older US populations.

OBJECTIVE: To assess whether the composite dietary antioxidant index (CDAI) is associated with osteoporosis (OP) in middle-aged and older US populations. METHODS: We conducted a cross-sectional survey and identified individuals aged 40-85 years (n=11,664) from secondary datasets from the 2007-2010, 2013-2014, and 2017-2018 National Health and Nutrition Examination Survey (NHANES). Dual-energy X-ray absorptiometry was used to measure bone mineral density (BMD), and OP was defined as a BMD T-score ≤-2.5 at the femoral neck or lumbar spine. The CDAI score was calculated based on dietary data from the first NHANES 24-hour dietary recall. Multivariate logistic regression models were used to evaluate the association between CDAI and OP. RESULTS: Among the 11,664 participants, the average age was 60.3 (11.8), 5,898 (50.6%) were female, and 925 (7.9%) had OP. The median CDAI was -2.0 (interquartile range, -6.9 to 4.2). After adjusting for age, sex, race, family income, body mass index, physical activity, calorie intake, estimated glomerular filtration rate, smoking and drinking status, hypertension, and diabetes, the CDAI was associated with OP (odds ratio (OR), 0.98; 95% CI: 0.96-0.99). Participants in the highest CDAI quantile were at low risk of osteoporosis (OR, 0.61; 95% CI: 0.44-0.85) versus those in the lowest quantile. Moreover, this association was stable in the subgroup and sensitivity analyses. CONCLUSION: Dietary antioxidant ability assessed by using the CDAI was inversely associated with OP among US adults aged 40-85 years.

Oral Squamous Cell Carcinoma Cells with Acquired Resistance to Erlotinib Are Sensitive to Anti-Cancer Effect of Quercetin via Pyruvate Kinase M2 (PKM2).

Oral squamous cell carcinoma (OSCC) frequently carries high epidermal growth factor receptor (EGFR) expression. Erlotinib, a small molecule tyrosine kinase inhibitor (TKI), is an effective inhibitor of EGFR activity; however, resistance to this drug can occur, limiting therapeutic outcomes. Therefore, in the current study, we aimed to unveil key intracellular molecules and adjuvant reagents to overcome erlotinib resistance. First, two HSC-3-derived erlotinib-resistant cell lines, ERL-R5 and ERL-R10, were established; both exhibited relatively higher growth rates, glucose utilization, epithelial-mesenchymal transition (EMT), and invasiveness compared with parental cells. Cancer aggressiveness-related proteins, such as N-cadherin, Vimentin, Twist, MMP-2, MMP-9, and MMP-13, and the glycolytic enzymes PKM2 and GLUT1 were upregulated in ERL-R cells. Notably, ERL-R cells were sensitive to quercetin, a naturally-existing flavonol phytochemical with anti-cancer properties against various cancer cells. At a concentration of 5 µM, quercetin effectively arrested cell growth, reduced glucose utilization, and inhibited cellular invasiveness. An ERL-R5-derived xenograft mouse model confirmed the growth-inhibitory efficacy of quercetin. Additionally, knock-down of PKM2 by siRNA mimicked the effect of quercetin and re-sensitized ERL-R cells to erlotinib. Furthermore, adding quercetin blocked the development of erlotinib-mediated resistance by enhancing apoptosis. In conclusion, our data support the application of quercetin in anti-erlotinib-resistant OSCC and indicate that PKM2 is a determinant factor in erlotinib resistance and quercetin sensitivity.

Lifetime exposure to benzophenone-3 at an environmentally relevant concentration leads to female-biased social behavior and cognition deficits in zebrafish.

Benzophenone-3 (BP3) is an organic UV filter widely used in the commercial formulations of various personal care products. It has been detected ubiquitously in the environment and human tissues. Recently, BP3-induced neurotoxicity has been identified as the main health risk to humans and aquatic organisms. However, most research has been focused on embryonic development, and few studies explore chronic lifetime exposure. In the present study, we evaluated the neurotoxicity of lifetime exposure to an environmentally relevant concentration of BP3 in zebrafish. Our findings revealed that continuous BP3 exposure at 10 µg/L (0.04 µM) from 6 h post fertilization (hpf) to adulthood at 5 months led to female-biased social behavioral deficits and learning and memory impairment. These neurobehavioral effects were characterized by decreased prosocial activities in the social preference test and mirror biting assay, and reduced learning and memory in a T-maze test. Furthermore, these effects were accompanied by female-specific decreases in brain weight and brain dopamine concentration, female-biased decrease of neurogenesis in the telencephalon as well as female-specific increases in apoptotic cells and expression levels of genes and proteins related to the apoptosis pathway in the brain. Our results suggest that BP3-induced social behavior and learning/memory deficits are correlated to the cell loss in the telencephalon region of the zebrafish brain.

Activation of ALOX12 by a multi-organelle-orienting photosensitizer drives ACSL4-independent cell ferroptosis.

Ferroptosis is a recently-defined tumor suppression mechanism, but the sensitivity of many tumorigenic cells to ferroptosis is limited by their deficient expression of acyl-CoA synthetase long-chain family member 4 (ACSL4). Here, we report the discovery of a photosensitizer, namely TPCI, which can evoke ACSL4-independent ferroptosis of cancer cells in photodynamic therapy. Through co-localization with 12-lipoxygenase (ALOX12) in multiple subcellular organelles, TPCI activates ALOX12 to generate lipid reactive oxygen species in large quantity and trigger cell ferroptosis. Intriguingly, confining TPCI exclusively in lysosomes switches the cell death from ferroptosis to apoptosis. More strikingly, the ferroptosis mediated by TPCI-induced ALOX12 activation does not require the participation of ACSL4. Therefore, our study identifies TPCI as the first ALOX12 activator to induce ferroptosis independent of ACSL4, which renders a viable therapeutic approach on the basis of distinct ferroptosis of cancer cells, regardless their ACSL4 expressions.

MARK2 regulates chemotherapeutic responses through class IIa HDAC-YAP axis in pancreatic cancer.

Despite paclitaxel's wide use in cancer treatment, patient response rate is still low and drug resistance is a major clinical obstacle. Through a Phos-tag-based kinome-wide screen, we identified MARK2 as a critical regulator for paclitaxel chemosensitivity in PDAC. We show that MARK2 is phosphorylated by CDK1 in response to antitubulin chemotherapeutics and in unperturbed mitosis. Phosphorylation is essential for MARK2 in regulating mitotic progression and paclitaxel cytotoxicity in PDAC cells. Mechanistically, our findings also suggest that MARK2 controls paclitaxel chemosensitivity by regulating class IIa HDACs. MARK2 directly phosphorylates HDAC4 specifically during antitubulin treatment. Phosphorylated HDAC4 promotes YAP activation and controls expression of YAP target genes induced by paclitaxel. Importantly, combination of HDAC inhibition and paclitaxel overcomes chemoresistance in organoid culture and preclinical PDAC animal models. The expression levels of MARK2, HDACs, and YAP are upregulated and positively correlated in PDAC patients. Inhibition of MARK2 or class IIa HDACs potentiates paclitaxel cytotoxicity by inducing mitotic abnormalities in PDAC cells. Together, our findings identify the MARK2-HDAC axis as a druggable target for overcoming chemoresistance in PDAC.

Protective Effect of Bifidobacterium lactis JYBR-190 on Intestinal Mucosal Damage in Chicks Infected With Salmonella pullorum.

Pullorum is one of the most serious diseases that endanger the chicken industry. With the advent of the era of anti-antibiotics in feed, the replacement of antibiotics by probiotics has become the focus and hotspot of related research. In this study, hematoxylin-eosin (H&E) staining, immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA) were used to observe the structural changes of intestinal mucosa in chicks infected with Salmonella pullorum, and to analyze TNF-α, IL-10, IFN-γ, proliferating cell nuclear antigen (PCNA), and secreted immunoglobulin A (sIgA) levels. The results showed that the intestinal villus height, villus height to crypt depth ratio (V/C), and muscle layer thickness of duodenum, jejunum and cecum in the JYBR-190 group were significantly higher than those of the infection group and antibiotic group. Furthermore, the levels of PCNA, sIgA and IL-10 in JYBR-190 group were significantly increased, whereas the expression of TNF-α and IFN-γ was significantly decreased. Taken together, Bifidobacterium lactis JYBR-190 has a protective effect on intestinal mucosal damage in chicks infected with Salmonella pullorum.

The phosphatase CTDSPL2 is phosphorylated in mitosis and a target for restraining tumor growth and motility in pancreatic cancer.

Carboxy-terminal domain (CTD) small phosphatase like 2 (CTDSPL2), also known as SCP4 or HSPC129, is a new member of the small CTD phosphatase (SCP) family and its role in cancers remains unclear. Here, we used a Phos-tag technique to screen a series of phosphatases and identified CTDSPL2 as a mitotic regulator. We demonstrated that CTDSPL2 was phosphorylated at T86, S104, and S134 by cyclin-dependent kinase 1 (CDK1) in mitosis. Depletion of CTDSPL2 led to mitotic defects and prolonged mitosis. Resultantly, CTDSPL2 deletion restrained proliferation, migration, and invasion in pancreatic cancer cells. We further confirmed the dominant negative effects of a phosphorylation-deficient mutant form of CTDSPL2, implying the biological significance of CTDSPL2 mitotic phosphorylation. Moreover, RT2 cell cycle array analysis revealed p21 and p27 as downstream regulators of CTDSPL2, and inhibition of p21 and/or p27 partially rescued the phenotype in CTDSPL2-deficient cell lines. Importantly, both CTDSPL2 depletion and phosphorylation-deficient mutant CTDSPL2 hindered tumor growth in xenograft models. Together, our findings for the first time highlight the novel role of CTDSPL2 in regulating cell mitosis, proliferation and motility in pancreatic cancer and point out the implications of CTDSPL2 in regulating two critical cell cycle participants (p21 and p27), providing an alternative molecular target for pancreatic cancer treatment.