New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

EMLI-ICC: an ensemble machine learning-based integration algorithm for metastasis prediction and risk stratification in intrahepatic cholangiocarcinoma.

Robust strategies to identify patients at high risk for tumor metastasis, such as those frequently observed in intrahepatic cholangiocarcinoma (ICC), remain limited. While gene/protein expression profiling holds great potential as an approach to cancer diagnosis and prognosis, previously developed protocols using multiple diagnostic signatures for expression-based metastasis prediction have not been widely applied successfully because batch effects and different data types greatly decreased the predictive performance of gene/protein expression profile-based signatures in interlaboratory and data type dependent validation. To address this problem and assist in more precise diagnosis, we performed a genome-wide integrative proteome and transcriptome analysis and developed an ensemble machine learning-based integration algorithm for metastasis prediction (EMLI-Metastasis) and risk stratification (EMLI-Prognosis) in ICC. Based on massive proteome (216) and transcriptome (244) data sets, 132 feature (biomarker) genes were selected and used to train the EMLI-Metastasis algorithm. To accurately detect the metastasis of ICC patients, we developed a weighted ensemble machine learning method based on k-Top Scoring Pairs (k-TSP) method. This approach generates a metastasis classifier for each bootstrap aggregating training data set. Ten binary expression rank-based classifiers were generated for detection of metastasis separately. To further improve the accuracy of the method, the 10 binary metastasis classifiers were combined by weighted voting based on the score from the prediction results of each classifier. The prediction accuracy of the EMLI-Metastasis algorithm achieved 97.1% and 85.0% in proteome and transcriptome datasets, respectively. Among the 132 feature genes, 21 gene-pair signatures were developed to establish a metastasis-related prognosis risk-stratification model in ICC (EMLI-Prognosis). Based on EMLI-Prognosis algorithm, patients in the high-risk group had significantly dismal overall survival relative to the low-risk group in the clinical cohort (P-value < 0.05). Taken together, the EMLI-ICC algorithm provides a powerful and robust means for accurate metastasis prediction and risk stratification across proteome and transcriptome data types that is superior to currently used clinicopathological features in patients with ICC. Our developed algorithm could have profound implications not just in improved clinical care in cancer metastasis risk prediction, but also more broadly in machine-learning-based multi-cohort diagnosis method development. To make the EMLI-ICC algorithm easily accessible for clinical application, we established a web-based server for metastasis risk prediction (http://ibi.zju.edu.cn/EMLI/).

Validation of Roussouly classification in predicting the occurrence of adjacent segment disease after short-level lumbar fusion surgery.

BACKGROUND: Recent studies demonstrated that restoring sagittal alignment to the original Roussouly type can remarkably reduce complication rates after adult spinal deformity surgery. However, there is still no data proving the benefit of maintaining ideal Roussouly shape in the lumbar degenerative diseases and its association with the development of adjacent segment disease (ASD). Thus, this study was performed to validate the usefulness of Roussouly classification to predict the occurrence of ASD after lumbar fusion surgery. MATERIALS AND METHODS: This study retrospectively reviewed 234 consecutive patients with lumbar degenerative diseases who underwent 1- or 2-level fusion surgery. Demographic and radiographic data were compared between ASD and non-ASD groups. The patients were classified by both "theoretical" [based on pelvic incidence (PI)] and "current" (based on sacral slope) Roussouly types. The patients were defined as "matched" if their "current" shapes matched the "theoretical" types and otherwise as "mismatched". The logistic regression analysis was performed to identify the factors associated with ASD. Finally, clinical data and spinopelvic parameters of "theoretical" and "current" types were compared. RESULTS: With a mean follow-up duration of 70.6 months, evidence of ASD was found in the 68 cases. Postoperatively, ASD group had more "current" shapes classified as type 1 or 2 and fewer as type 3 than the non-ASD group (p < 0.001), but the distribution of "theoretical" types was similar between groups. Moreover, 80.9% (55/68) of patients with ASD were mismatched, while 48.2% (80/166) of patients without ASD were mismatched (p < 0.001). A multivariate analysis identified age [odds ratio (OR) = 1.058)], 2-level fusion (OR = 2.9830), postoperative distal lordosis (DL, OR = 0.949) and mismatched Roussouly type (OR = 4.629) as independent risk factors of ASD. Among the four "theoretical" types, type 2 had the lowest lumbar lordosis, DL, and segmental lordosis. When considering the "current" types, current type 2 was associated with higher rates of 2-level fusion, worse DL, and greater pelvic tilt compared with other current types. CONCLUSIONS: DL loss and mismatched Roussouly type were significant risk factors of ASD. To decrease the incidence of ASD, an appropriate value of DL should be achieved to restore sagittal alignment back to the ideal Roussouly type. LEVEL OF EVIDENCE: Level 4.

LncRNA-HOTAIRM1 promotes aerobic glycolysis and proliferation in osteosarcoma via the miR-664b-3p/Rheb/mTOR pathway.

Osteosarcoma (OS), which is a common and aggressive primary bone malignancy, occurs mainly in children and adolescent. Long noncoding RNAs (lncRNAs) are reported to play a pivotal role in various cancers. Here, we found that the lncRNA HOTAIRM1 is upregulated in OS cells and tissues. A set of functional experiments suggested that HOTAIRM1 knockdown attenuated the proliferation and stimulated the apoptosis of OS cells. A subsequent mechanistic study revealed that HOTAIRM1 functions as a competing endogenous RNA to elevate ras homologue enriched in brain (Rheb) expression by sponging miR-664b-3p. Immediately afterward, upregulated Rheb facilitates proliferation and suppresses apoptosis by promoting the mTOR pathway-mediated Warburg effect in OS. In summary, our findings demonstrated that HOTAIRM1 promotes the proliferation and suppresses the apoptosis of OS cells by enhancing the Warburg effect via the miR-664b-3p/Rheb/mTOR axis. Understanding the underlying mechanisms and targeting the HOTAIRM1/miR-664b-3p/Rheb/mTOR axis are essential for OS clinical treatment.

MicroRNA-324-3p inhibits osteosarcoma progression by suppressing PGAM1-mediated aerobic glycolysis.

Osteosarcoma (OS) is the most common primary malignant neoplasm of the bone. Recent studies have indicated that the inhibitory effects of microRNA (miR)-324-3p could affect the development of numerous cancers. However, its biological roles and underlying mechanisms in OS progression remain unexplored. In this study, miR-324-3p expression was markedly reduced in OS cell lines and tissues. Functionally, miR-324-3p overexpression suppressed OS progression and was involved in the Warburg effect. Mechanistically, miR-324-3p negatively regulated phosphoglycerate mutase 1 (PGAM1) expression by targeting its 3'-UTR. Moreover, high expression of PGAM1 promoted OS progression and aerobic glycolysis, which were associated with inferior overall survival in patients with OS. Notably, the tumor suppressor functions of miR-324-3p were partially recovered by PGAM1 overexpression. In summary, the miR-324-3p/PGAM1 axis plays an important role in regulating OS progression by controlling the Warburg effect. Our results provide mechanistic insights into the function of miR-324-3p in glucose metabolism and subsequently on the progression of OS. Targeting the miR-324-3p/PGAM1 axis could be a promising molecular strategy for the treatment of OS.

TOD-CUP: a gene expression rank-based majority vote algorithm for tissue origin diagnosis of cancers of unknown primary.

Gene expression profiling holds great potential as a new approach to histological diagnosis and precision medicine of cancers of unknown primary (CUP). Batch effects and different data types greatly decrease the predictive performance of biomarker-based algorithms, and few methods have been widely applied to identify tissue origin of CUP up to now. To address this problem and assist in more precise diagnosis, we have developed a gene expression rank-based majority vote algorithm for tissue origin diagnosis of CUP (TOD-CUP) of most common cancer types. Based on massive tissue-specific RNA-seq data sets (10 553) found in The Cancer Genome Atlas (TCGA), 538 feature genes (biomarkers) were selected based on their gene expression ranks and used to predict tissue types. The top scoring pairs (TSPs) classifier of the tumor type was optimized by the TCGA training samples. To test the prediction accuracy of our TOD-CUP algorithm, we analyzed (1) two microarray data sets (1029 Agilent and 2277 Affymetrix/Illumina chips) and found 91% and 94% prediction accuracy, respectively, (2) RNA-seq data from five cancer types derived from 141 public metastatic cancer tumor samples and achieved 94% accuracy and (3) a total of 25 clinical cancer samples (including 14 metastatic cancer samples) were able to classify 24/25 samples correctly (96.0% accuracy). Taken together, the TOD-CUP algorithm provides a powerful and robust means to accurately identify the tissue origin of 24 cancer types across different data platforms. To make the TOD-CUP algorithm easily accessible for clinical application, we established a Web-based server for tumor tissue origin diagnosis (http://ibi. zju.edu.cn/todcup/).

Targeting a cytokine checkpoint enhances the fitness of armored cord blood CAR-NK cells.

Immune checkpoint therapy has resulted in remarkable improvements in the outcome for certain cancers. To broaden the clinical impact of checkpoint targeting, we devised a strategy that couples targeting of the cytokine-inducible Src homology 2-containing (CIS) protein, a key negative regulator of interleukin 15 (IL-15) signaling, with fourth-generation "armored" chimeric antigen receptor (CAR) engineering of cord blood-derived natural killer (NK) cells. This combined strategy boosted NK cell effector function through enhancing the Akt/mTORC1 axis and c-MYC signaling, resulting in increased aerobic glycolysis. When tested in a lymphoma mouse model, this combined approach improved NK cell antitumor activity more than either alteration alone, eradicating lymphoma xenografts without signs of any measurable toxicity. We conclude that targeting a cytokine checkpoint further enhances the antitumor activity of IL-15-secreting armored CAR-NK cells by promoting their metabolic fitness and antitumor activity. This combined approach represents a promising milestone in the development of the next generation of NK cells for cancer immunotherapy.

Construction of humanized CYP1A2 rats using CRISPR/Cas9 to promote drug metabolism and pharmacokinetic research.

Cytochrome P450 family 1 subfamily A member 2 (CYP1A2), performs an indispensable role in metabolism of both exogenous and endogenous substances. What is more, CYP1A2 functions in human diseases by regulating homeostasis of cholesterol. Despite the emergence of gene-editing animal models, genetically humanized animals that overcome species differences for further exploring the role of CYP1A2 in drug metabolism and human diseases have not yet been constructed. In this study, we inserted human CYP1A2 cDNA into the rat Cyp1a2 gene by using CRISPR/Cas9 technology. Results showed that human CYP1A2 was successfully expressed in humanized rat liver and there were no statistically significant differences of physiological symptoms compared with wild-type (WT) rats. In vitro incubation results indicated the different inhibition of furafylline on CYP1A2 activity in human liver microsomes, humanized CYP1A2 (hCYP1A2) rat liver microsomes, and WT rat liver microsomes, with IC50 values of 7.1 µM, 36.5 µM, and 285.8 µM, respectively. Meanwhile, pharmacokinetic characteristics of clozapine were conducted, and the results suggested that in hCYP1A2 rats, clozapine tended to be metabolized into norclozapine. Both the in vitro and in vivo results demonstrated the different metabolic functions of CYP1A2 in humanized and WT rats. We successfully constructed a novel humanized CYP1A2 rat model using the CRISPR/Cas9 system, providing a powerful tool for better predicting CYP1A2-mediated drug metabolism and pharmacokinetics. Significance Statement Human CYP1A2 takes active part both in the biotransformation of exogenous substances and endogenous substances. Meanwhile, it plays a regulatory role in human diseases, including hypercholesterolemia, hypertension as well as various malignant tumors. This study successfully constructed humanized CYP1A2 rat model by CRISPR/Cas9 technology, providing a powerful model for promoting drug development and safety evaluation, as well as further exploring the role of CYP1A2 in human diseases.

scDetect: a rank-based ensemble learning algorithm for cell type identification of single-cell RNA sequencing in cancer.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has enabled the characterization of different cell types in many tissues and tumor samples. Cell type identification is essential for single-cell RNA profiling, currently transforming the life sciences. Often, this is achieved by searching for combinations of genes that have previously been implicated as being cell-type specific, an approach that is not quantitative and does not explicitly take advantage of other scRNA-seq studies. Batch effects and different data platforms greatly decrease the predictive performance in inter-laboratory and different data type validation. RESULTS: Here, we present a new ensemble learning method named as 'scDetect' that combines gene expression rank-based analysis and a majority vote ensemble machine-learning probability-based prediction method capable of highly accurate classification of cells based on scRNA-seq data by different sequencing platforms. Because of tumor heterogeneity, in order to accurately predict tumor cells in the single-cell RNA-seq data, we have also incorporated cell copy number variation consensus clustering and epithelial score in the classification. We applied scDetect to scRNA-seq data from pancreatic tissue, mononuclear cells and tumor biopsies cells and show that scDetect classified individual cells with high accuracy and better than other publicly available tools. AVAILABILITY AND IMPLEMENTATION: scDetect is an open source software. Source code and test data is freely available from Github (https://github.com/IVDgenomicslab/scDetect/) and Zenodo (https://zenodo.org/record/4764132#.YKCOlrH5AYN). The examples and tutorial page is at https://ivdgenomicslab.github.io/scDetect-Introduction/. And scDetect will be available from Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

LINC01123 enhances osteosarcoma cell growth by activating the Hedgehog pathway via the miR-516b-5p/Gli1 axis.

The lncRNA LINC01123 has been reported to act as an oncogene in many human cancers. Nevertheless, the function and underlying mechanism of LINC01123 in osteosarcoma (OS) remain unclear. This study aimed to explore the roles and mechanisms of LINC01123 in OS progression. In this study, the expression of LINC01123 was significantly upregulated in OS cell lines than in a human osteoblast cell line. Furthermore, in vitro and in vivo experiments confirmed that knockdown of LINC01123 suppressed cell progression. Mechanistically, LINC01123 acted as a competing endogenous RNA by sponging miR-516b-5p, thus, increasing Gli1 expression by directly targeting its 3'UTR. Taken together, LINC01123 enhances OS proliferation and metastasis via the miR-516b-5p/Gli1 axis. Therefore, LINC01123 may be a potential therapeutic target for OS treatment.

Chemically Prelithiated Hard-Carbon Anode for High Power and High Capacity Li-Ion Batteries.

Hard carbons (HC) have potential high capacities and power capability, prospectively serving as an alternative anode material for Li-ion batteries (LIB). However, their low initial coulombic efficiency (ICE) and the resulting poor cyclability hinder their practical applications. Herein, a facile and effective approach is developed to prelithiate hard carbons by a spontaneous chemical reaction with lithium naphthalenide (Li-Naph). Due to the mild reactivity and strong lithiation ability of Li-Naph, HC anode can be prelithiated rapidly in a few minutes and controllably to a desirable level by tuning the reaction time. The as-formed prelithiated hard carbon (pHC) has a thinner, denser, and more robust solid electrolyte interface layer consisting of uniformly distributed LiF, thus demonstrating a very high ICE, high power, and stable cyclability. When paired with the current commercial LiCoO2 and LiFePO4 cathodes, the assembled pHC/LiCoO2 and pHC/LiFePO4 full cells exhibit a high ICE of >95.0% and a nearly 100% utilization of electrode-active materials, confirming a practical application of pHC for a new generation of high capacity and high power LIBs.

Senescence and Defense Pathways Contribute to Heterosis.

Hybrids are used extensively in agriculture due to their superior performance in seed yield and plant growth, yet the molecular mechanisms underpinning hybrid performance are not well understood. Recent evidence has suggested that a decrease in basal defense response gene expression regulated by reduced levels of salicylic acid (SA) may be important for vigor in certain hybrid combinations. Decreasing levels of SA in the Arabidopsis (Arabidopsis thaliana) accession C24 through the introduction of the SA catabolic enzyme salicylate1 hydroxylase (NahG) increases plant size, phenocopying the large-sized C24/Landsberg erecta (Ler) F1 hybrids. C24♀ × Ler♂ F1 hybrids and C24 NahG lines shared differentially expressed genes and pathways associated with plant defense and leaf senescence including decreased expression of SA biosynthetic genes and SA response genes. The expression of TL1 BINDING TRANSCRIPTION FACTOR1, a key regulator in resource allocation between growth and defense, was decreased in both the F1 hybrid and the C24 NahG lines, which may promote growth. Both C24 NahG lines and the F1 hybrids showed decreased expression of the key senescence-associated transcription factors WRKY53, NAC-CONTAINING PROTEIN29, and ORESARA1 with a delayed onset of senescence compared to C24 plants. The delay in senescence resulted in an extension of the photosynthetic period in the leaves of F1 hybrids compared to the parental lines, potentially allowing each leaf to contribute more resources toward growth.

Tissue-resident memory CD8+ T cells in cancer immunology and immunotherapy.

Memory T cells can be generated and remain long-term in different tissues following infection or immunization. Tissue-resident memory T (TRM) cells are a unique group of memory T cells that form and persist mainly in peripheral non-lymphoid organs. Unlike effector or central memory T (TEM or TCM) cells, TRM cells do not circulate to the blood but can provide a rapid and robust local response to re-infection. Recently, a large body of clinical studies has shown that CD103+ CD8+ TRM-like cells also exist intratumorally and strongly correlate with favorable prognosis in cancer patients. Cancer vaccine-induced CD103+ CD8+ TRM cells have been reported to suppress tumor growth in mouse models. This suggests that CD8+ TRM-like cells play a crucial role in cancer immunosurveillance and immunotherapy. In this review, we focus on the features and cytotoxic mechanisms of CD8+ TRM-like cells in multiple solid tumors and discuss their potential implications for cancer immunotherapy. We believe a better understanding of the generation, function, and longevity of CD8+ TRM-like cells in the tumor microenvironment will provide new insights for cancer immunotherapies.

Genome-wide selection footprints and deleterious variations in young Asian allotetraploid rapeseed.

Brassica napus (AACC, 2n = 38) is an important oilseed crop grown worldwide. However, little is known about the population evolution of this species, the genomic difference between its major genetic groups, such as European and Asian rapeseed, and the impacts of historical large-scale introgression events on this young tetraploid. In this study, we reported the de novo assembly of the genome sequences of an Asian rapeseed (B. napus), Ningyou 7, and its four progenitors and compared these genomes with other available genomic data from diverse European and Asian cultivars. Our results showed that Asian rapeseed originally derived from European rapeseed but subsequently significantly diverged, with rapid genome differentiation after hybridization and intensive local selective breeding. The first historical introgression of B. rapa dramatically broadened the allelic pool but decreased the deleterious variations of Asian rapeseed. The second historical introgression of the double-low traits of European rapeseed (canola) has reshaped Asian rapeseed into two groups (double-low and double-high), accompanied by an increase in genetic load in the double-low group. This study demonstrates distinctive genomic footprints and deleterious SNP (single nucleotide polymorphism) variants for local adaptation by recent intra- and interspecies introgression events and provides novel insights for understanding the rapid genome evolution of a young allopolyploid crop.

Overexpression of miR-182 inhibits ossification of ligamentum flavum cells by targeting NAMPT.

Ossification of the ligamentum flavum (OLF) is a debilitating disease resulting from the development of ectopic bone formation, which leads to the compression of the spinal cord. Nicotinamide phosphoribosyltransferase (NAMPT) was found to be upregulated and microRNA-182 (miR-182) was downregulated in OLF tissue. We investigated the effects of NAMPT and miR-182 expression in OLF cells and the influence on proteins associated with osteogenic differentiation. MiR-182 overexpression inhibited NAMPT, RUNX2, OCN and OPN mRNA and protein expression in OLF cells. Alkaline phosphatase (ALP) assay and Alizarin red staining confirmed reduced levels of osteogenic differentiation and mineralized nodule formation. Knockdown of NAMPT and the NAMPT inhibitor FK866 also inhibits RUNX2, OCN and OPN mRNA expression and protein levels, whereas overexpression of NAMPT promotes the expression of RUNX2, OCN and OPN and the generation of bone nodules. Dual-luciferase reporter assays revealed that miR-182 directly targets NAMPT and downregulates its expression. Transfection of OLF cells with miR-182 downregulated NAMPT and suppressed the regulation of RUNX2, OCN, and OPN by NAMPT overexpression. Overall, these data demonstrate that miR-182 suppresses OLF by downregulating NAMPT.

Integrated mRNA and miRNA profile expression in livers of Jinhua and Landrace pigs.

Objective: To explore the molecular mechanisms of fat metabolism and deposition in pigs, an experiment was conducted to identify hepatic mRNAs and miRNAs expression and determine the potential interaction of them in two phenotypically extreme pig breeds. Methods: mRNA and miRNA profiling of liver from 70-day Jinhua (JH) and Landrace (LD) pigs were performed using RNA sequencing. Blood samples were taken to detect results of serum biochemistry. Bioinformatics analysis were applied to construct differentially expressed miRNA-mRNA network. Results: Serum total triiodothyronine (TT3) and total thyroxine (TT4) were significantly lower in Jinhua pigs, but the content of serum total cholesterol (TCH) and low-density lipoprotein cholesterol (LDLC) were strikingly higher. A total of 467 differentially expressed genes (DEGs) and 35 differentially expressed miRNAs (DE miRNAs) were identified between JH and LD groups. Gene ontology analysis suggested that DEGs were involved in oxidation-reduction, lipid biosynthetic and lipid metabolism process. Interaction network of DEGs and DE miRNAs were constructed, according to target prediction results. Conclusion: We generated transcriptome and miRNAome profiles of liver from Jinhua and Landrace pig breeds which represent distinguishing phenotypes of growth and metabolism. The potential miRNA-mRNA interaction networks may provide a comprehensive understanding in the mechanism of lipid metabolism. These results serve as a basis for further investigation on biological functions of miRNAs in the porcine liver.

Analysis of transcriptional and epigenetic changes in hybrid vigor of allopolyploid Brassica napus uncovers key roles for small RNAs.

Heterosis is a fundamental biological phenomenon characterized by the superior performance of a hybrid compared with its parents. The underlying molecular basis for heterosis, particularly for allopolyploids, remains elusive. In this study we analyzed the transcriptomes of Brassica napus parental lines and their F1 hybrids at three stages of early flower development. Phenotypically, the F1 hybrids show remarkable heterosis in silique number and grain yield. Transcriptome analysis revealed that various phytohormone (auxin and salicylic acid) response genes are significantly altered in the F1 hybrids relative to the parental lines. We also found evidence for decreased expression divergence of the homoeologous gene pairs in the allopolyploid F1 hybrids and suggest that high-parental expression-level dominance plays an important role in heterosis. Small RNA and methylation studies aimed at examining the epigenetic effect of the changes in gene expression level in the F1 hybrids showed that the majority of the small interfering RNA (siRNA) clusters had a higher expression level in the F1 hybrids than in the parents, and that there was an increase in genome-wide DNA methylation in the F1 hybrid. Transposable elements associated with siRNA clusters had a higher level of methylation and a lower expression level in the F1 hybrid, implying that the non-additively expressed siRNA clusters resulted in lower activity of the transposable elements through DNA methylation in the hybrid. Our data provide insights into the role that changes in gene expression pattern and epigenetic mechanisms contribute to heterosis during early flower development in allopolyploid B. napus.

A naive Bayes algorithm for tissue origin diagnosis (TOD-Bayes) of synchronous multifocal tumors in the hepatobiliary and pancreatic system.

Synchronous multifocal tumors are common in the hepatobiliary and pancreatic system but because of similarities in their histological features, oncologists have difficulty in identifying their precise tissue clonal origin through routine histopathological methods. To address this problem and assist in more precise diagnosis, we developed a computational approach for tissue origin diagnosis based on naive Bayes algorithm (TOD-Bayes) using ubiquitous RNA-Seq data. Massive tissue-specific RNA-Seq data sets were first obtained from The Cancer Genome Atlas (TCGA) and ∼1,000 feature genes were used to train and validate the TOD-Bayes algorithm. The accuracy of the model was >95% based on tenfold cross validation by the data from TCGA. A total of 18 clinical cancer samples (including six negative controls) with definitive tissue origin were subsequently used for external validation and 17 of the 18 samples were classified correctly in our study (94.4%). Furthermore, we included as cases studies seven tumor samples, taken from two individuals who suffered from synchronous multifocal tumors across tissues, where the efforts to make a definitive primary cancer diagnosis by traditional diagnostic methods had failed. Using our TOD-Bayes analysis, the two clinical test cases were successfully diagnosed as pancreatic cancer (PC) and cholangiocarcinoma (CC), respectively, in agreement with their clinical outcomes. Based on our findings, we believe that the TOD-Bayes algorithm is a powerful novel methodology to accurately identify the tissue origin of synchronous multifocal tumors of unknown primary cancers using RNA-Seq data and an important step toward more precision-based medicine in cancer diagnosis and treatment.

The miR-15b-5p/PDK4 axis regulates osteosarcoma proliferation through modulation of the Warburg effect.

Blocking aerobic glycolysis has been proposed as an attractive therapeutic strategy for impairing the proliferation of cancer cells. However, the underlying mechanisms are poorly understood. Here, we show that miR-15b-5p was downregulated in osteosarcoma (OS) and that lower expression of miR-15b-5p promoted proliferation and contributed to the Warburg effect in OS cells. Mechanistically, miR-15b-5p acted as a tumor suppressor in OS by directly targeting pyruvate dehydrogenase kinase-4 and inhibiting its expression. These results reveal a previously unknown function of miR-15b-5p in OS, which is associated with metabolic alterations that promote cancer progression. miR-15b-5p may play an essential role in the molecular therapy of patients with OS.

Correction: Engineering highly sensitive whole-cell mercury biosensors based on positive feedback loops from quorum-sensing systems.

Correction for 'Engineering highly sensitive whole-cell mercury biosensors based on positive feedback loops from quorum-sensing systems' by Sheng Cai, et al., Analyst, 2018, DOI: 10.1039/c7an00587c.