Identification of prognostic risk model based on plasma cell markers in hepatocellular carcinoma through single-cell sequencing analysis.

Hepatocellular carcinoma (HCC) represents a substantial global health burden. Tumorinfiltrating B lymphocytes (TIL-Bs) contribute to tumor progression and significantly impact the efficacy of tumor therapy. However, the characteristics of TIL-Bs in HCC and their effect on HCC therapy remain elusive. Single-cell RNA sequencing (scRNAseq) was applied to investigate the heterogeneity, cellular differentiation and cell-cell communication of TIL-Bs in HCC. Further, the Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC) and liver cancer institutes (LCI) cohorts were applied to construct and validate the plasma cell marker-based prognostic risk model. The relationship between the prognostic risk model and the responsiveness of immunotherapy and chemotherapy in patients with HCC were estimated by OncoPredict and tumor immune dysfunction and exclusion (TIDE) algorithm. Finally, we established nomogram and calibration curves to evaluate the precision of the risk score in predicating survival probability. Our data identified five subtypes of TIL-Bs in HCC, each exhibiting varying levels of infiltration in tumor tissues. The interactions between TIL-Bs and other cell types contributed to shaping distinct tumor microenvironments (TME). Moreover, we found that TIL-Bs subtypes had disparate prognostic values in HCC patients. The prognostic risk model demonstrated exceptional predictive accuracy for overall survival and exhibited varying sensitivities to immunotherapy and chemotherapy among patients with HCC. Our data demonstrated that the risk score stood as an independent prognostic predictor and the nomogram results further affirmed its strong prognostic capability. This study reveals the heterogeneity of TIL-Bs and provides a prognostic risk model based on plasma cell markers in HCC, which could prove valuable in predicting prognosis and guiding the choice of suitable therapies for patients with HCC.

Targeting Tumor Heterogeneity by Breaking a Stem Cell and Epithelial Niche Interaction Loop.

Tumor heterogeneity, the presence of multiple distinct subpopulations of cancer cells between patients or among the same tumors, poses a major challenge to current targeted therapies. The way these different subpopulations interact among themselves and the stromal niche environment, and how such interactions affect cancer stem cell behavior has remained largely unknown. Here, it is shown that an FGF-BMP7-INHBA signaling positive feedback loop integrates interactions among different cell populations, including mammary gland stem cells, luminal epithelial and stromal fibroblast niche components not only in organ regeneration but also, with certain modifications, in cancer progression. The reciprocal dependence of basal stem cells and luminal epithelium is based on basal-derived BMP7 and luminal-derived INHBA, which promote their respective expansion, and is regulated by stromal-epithelial FGF signaling. Targeting this interaction loop, for example, by reducing the function of one or more of its components, inhibits organ regeneration and breast cancer progression. The results have profound implications for overcoming drug resistance because of tumor heterogeneity in future targeted therapies.

Global analysis of T-cell groups reveals immunological features and common antigen targets of digestive tract tumors.

BACKGROUND: T cells are key players in the tumor immune microenvironment (TIME), as they can recognize and eliminate cancer cells that express neoantigens derived from somatic mutations. However, the diversity and specificity of T-cell receptors (TCRs) that recognize neoantigens are largely unknown, due to the high variability of TCR sequences among individuals. METHODS: To address this challenge, we applied GLIPH2, a novel algorithm that groups TCRs based on their predicted antigen specificity and HLA restriction, to cluster the TCR repertoire of 1,702 patients with digestive tract cancer. The patients were divided into five groups based on whether they carried tumor-infiltrating or clonal-expanded TCRs and calculated their TCR diversity. The prognosis, tumor subtype, gene mutation, gene expression, and immune microenvironment of these groups were compared. Viral specificity inference and immunotherapy relevance analysis performed for the TCR groups. RESULTS: This approach reduced the complexity of TCR sequences to 249 clonally expanded and 150 tumor-infiltrating TCR groups, which revealed distinct patterns of TRBV usage, HLA association, and TCR diversity. In gastric adenocarcinoma (STAD), patients with tumor-infiltrating TCRs (Patients-TI) had significantly worse prognosis than other patients (Patients-nonTI). Patients-TI had richer CD8+ T cells in the immune microenvironment, and their gene expression features were positively correlated with immunotherapy response. We also found that tumor-infiltrating TCR groups were associated with four distinct tumor subtypes, 26 common gene mutations, and 39 gene expression signatures. We discovered that tumor-infiltrating TCRs had cross-reactivity with viral antigens, indicating a possible link between viral infections and tumor immunity. CONCLUSION: By applying GLIPH2 to TCR sequences from digestive tract tumors, we uncovered novel insights into the tumor immune landscape and identified potential candidates for shared TCRs and neoantigens.

Protocol for PPP1R15A-inhibited mouse model establishment with subcutaneous B16F1 tumor and single-cell analysis.

Here, we present a protocol for exploring the effects of PPP1R15A inhibitor, Sephin1, on antitumor immunity of B16F1 subcutaneous tumor in mice. We describe steps for constructing single-cell transcriptome and TCR libraries, sequencing, and using sequencing data for the integration of expression and TCR data. We then detail procedures for gene differentiation, regulon and cell-cell communication analysis, and validation of single-cell analysis results. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

Intact regulation of G1/S transition renders esophageal squamous cell carcinoma sensitive to PI3Kα inhibitors.

Phosphatidylinositol 3-kinase alpha (PI3Kα) inhibitors are currently evaluated for the therapy of esophageal squamous cell carcinoma (ESCC). It is of great importance to identify potential biomarkers to predict or monitor the efficacy of PI3Kα inhibitors in an aim to improve the clinical responsive rate in ESCC. Here, ESCC PDXs with CCND1 amplification were found to be more sensitive to CYH33, a novel PI3Kα-selective inhibitor currently in clinical trials for the treatment of advanced solid tumors including ESCC. Elevated level of cyclin D1, p21 and Rb was found in CYH33-sensitive ESCC cells compared to those in resistant cells. CYH33 significantly arrested sensitive cells but not resistant cells at G1 phase, which was associated with accumulation of p21 and suppression of Rb phosphorylation by CDK4/6 and CDK2. Hypo-phosphorylation of Rb attenuated the transcriptional activation of SKP2 by E2F1, which in turn hindered SKP2-mediated degradation of p21 and reinforced accumulation of p21. Moreover, CDK4/6 inhibitors sensitized resistant ESCC cells and PDXs to CYH33. These findings provided mechanistic rationale to evaluate PI3Kα inhibitors in ESCC patients harboring amplified CCND1 and the combined regimen with CDK4/6 inhibitors in ESCC with proficient Rb.

Targeting KRAS-mutant stomach/colorectal tumors by disrupting the ERK2-p53 complex.

KRAS is widely mutated in human cancers, resulting in unchecked tumor proliferation and metastasis, which makes identifying KRAS-targeting therapies a priority. Herein, we observe that mutant KRAS specifically promotes the formation of the ERK2-p53 complex in stomach/colorectal tumor cells. Disruption of this complex by applying MEK1/2 and ERK2 inhibitors elicits strong apoptotic responses in a p53-dependent manner, validated by genome-wide knockout screening. Mechanistically, p53 physically associates with phosphorylated ERK2 through a hydrophobic interaction in the presence of mutant KRAS, which suppresses p53 activation by preventing the recruitment of p300/CBP; trametinib disrupts the ERK2-p53 complex by reducing ERK2 phosphorylation, allowing the acetylation of p53 protein by recruiting p300/CBP; acetylated p53 activates PUMA transcription and thereby kills KRAS-mutant tumors. Our study shows an important role for the ERK2-p53 complex and provides a potential therapeutic strategy for treating KRAS-mutant cancer.

Single-cell RNA sequencing reveals the suppressive effect of PPP1R15A inhibitor Sephin1 in antitumor immunity.

Protein phosphatase 1 regulatory subunit 15A (PPP1R15A) is an important factor in the integrated stress response (ISR) in mammals and may play a crucial role in tumorigenesis. In our studies, we found an inhibitor of PPP1R15A, Sephin1, plays a protumorigenic role in mouse tumor models. By analyzing the single-cell transcriptome data of the mouse tumor models, we found that in C57BL/6 mice, Sephin1 treatment could lead to higher levels of ISR activity and lower levels of antitumor immune activities. Specifically, Sephin1 treatment caused reductions in antitumor immune cell types and lower expression levels of cytotoxicity-related genes. In addition, T cell receptor (TCR) repertoire analysis demonstrated that the clonal expansion of tumor-specific T cells was inhibited by Sephin1. A special TCR + macrophage subtype in tumor was identified to be significantly depleted upon Sephin1 treatment, implying its key antitumor role. These results suggest that PPP1R15A has the potential to be an effective target for tumor therapy.

A novel long noncoding RNA SP100-AS1 induces radioresistance of colorectal cancer via sponging miR-622 and stabilizing ATG3.

Although radiotherapy is an essential modality in the treatment of colorectal cancer (CRC), the incidence of radioresistance remains high clinically. Long noncoding RNAs (lncRNAs) reportedly play critical roles in CRC radioresistance by regulating genes or proteins at the transcriptional or post-translational levels. This study aimed to identify novel lncRNAs involved in radioresistance. We found that SP100-AS1 (lncRNA targeting antisense sequence of SP100 gene) was upregulated in radioresistant CRC patient tissues using RNA-seq analysis. Importantly, knockdown of SP100-AS1 significantly reduced radioresistance, cell proliferation, and tumor formation in vitro and in vivo. Mechanistically, mass spectrometry and bioinformatics analyses were used to identify the interacting proteins and microRNAs of SP100-AS1, respectively. Moreover, SP100-AS1 was found to interact with and stabilize ATG3 protein through the ubiquitination-dependent proteasome pathway. In addition, it could serve as a sponge for miR-622, which targeted ATG3 mRNA and affected autophagic activity. Thus, lncRNA SP100-AS1 could act as a radioresistance factor in CRC patients via RNA sponging and protein stabilizing mechanisms. In conclusion, the present study indicates that SP100-AS1/miR-622/ATG3 axis contributes to radioresistance and autophagic activity in CRC patients, suggesting it has huge prospects as a therapeutic target for improving CRC response to radiation therapy.

Genome-wide gain-of-function screening identifies EZH2 mediating resistance to PI3Kα inhibitors in oesophageal squamous cell carcinoma.

Phosphoinositide-3 kinase alpha (PI3Kα) has been confirmed to be a potential therapeutic target for esophageal squamous cell carcinoma (ESCC), while the potency of PI3Kα inhibitors is often attenuated by concurrent oncogenic signalling pathways. We performed genome-wide gain-of-function screening with a CRISPR-SAM library and identified enhancer of zeste homolog 2 (EZH2) rendering ESCC cells resistant to the PI3Kα inhibitor CYH33. Enhanced expression of EZH2 frequently occurs in ESCC and is related to poor prognosis. Overexpression of full-length EZH2 but not methyltransferase-deficient EZH2 conferred resistance to CYH33, while downregulating EZH2 expression restored sensitivity. EZH2 expression was negatively related to the activity of CYH33 against the proliferation of ESCC cell lines and patient-derived cells. Transcriptomic analysis revealed that EZH2 abrogated CYH33-mediated cell cycle regulation. EZH2 epigenetically suppressed the transcription of CDKN1A, promoting RB phosphorylation and cell cycle progression. Concurrently targeting EZH2 significantly potentiated CYH33 to inhibit the growth of ESCC cells and patient-derived xenografts accompanied by enhanced cell cycle arrest. Taken together, our study demonstrated that an EZH2-p21-RB axis remodeled cell cycle regulation and rendered resistance to PI3Kα inhibitors in ESCC. Simultaneously targeting PI3Kα and EZH2 may provide an effective strategy for ESCC therapy with high expression of EZH2.

CST6 protein and peptides inhibit breast cancer bone metastasis by suppressing CTSB activity and osteoclastogenesis.

Background: Bone metastasis is a frequent symptom of breast cancer and current targeted therapy has limited efficacy. Osteoclasts play critical roles to drive osteolysis and metastatic outgrowth of tumor cells in bone. Previously we identified CST6 as a secretory protein significantly downregulated in bone-metastatic breast cancer cells. Functional analysis showed that CST6 suppresses breast-to-bone metastasis in animal models. However, the functional mechanism and therapeutic potential of CST6 in bone metastasis is unknown. Methods: Using in vitro osteoclastogenesis and in vivo metastasis assays, we studied the effect and mechanism of extracellular CST6 protein in suppressing osteoclastic niches and bone metastasis of breast cancer. A number of peptides containing the functional domain of CST6 were screened to inhibit bone metastasis. The efficacy, stability and toxicity of CST6 recombinant protein and peptides were evaluated in preclinical metastasis models. Results: We show here that CST6 inhibits osteolytic bone metastasis by inhibiting osteoclastogenesis. Cancer cell-derived CST6 enters osteoclasts by endocytosis and suppresses the cysteine protease CTSB, leading to up-regulation of the CTSB hydrolytic substrate SPHK1. SPHK1 suppresses osteoclast maturation by inhibiting the RANKL-induced p38 activation. Importantly, recombinant CST6 protein effectively suppresses bone metastasis in vitro and in vivo. We further identified several peptides mimicking the function of CST6 to suppress cancer cell-induced osteoclastogenesis and bone metastasis. Pre-clinical analyses of CTS6 recombinant protein and peptides demonstrated their potentials in treatment of breast cancer bone metastasis. Conclusion: These findings reveal the CST6-CTSB-SPHK1 signaling axis in osteoclast differentiation and provide a promising approach to treat bone diseases with CST6-based peptides.

Tumor microbiome contributes to an aggressive phenotype in the basal-like subtype of pancreatic cancer.

Despite the uniform mortality in pancreatic adenocarcinoma (PDAC), clinical disease heterogeneity exists with limited genomic differences. A highly aggressive tumor subtype termed 'basal-like' was identified to show worse outcomes and higher inflammatory responses. Here, we focus on the microbial effect in PDAC progression and present a comprehensive analysis of the tumor microbiome in different PDAC subtypes with resectable tumors using metagenomic sequencing. We found distinctive microbial communities in basal-like tumors and identified an increasing abundance of Acinetobacter, Pseudomonas and Sphingopyxis to be highly associated with carcinogenesis. Functional characterization of microbial genes suggested the potential to induce pathogen-related inflammation. Host-microbiota interplay analysis provided new insights into the tumorigenic role of specific microbiome compositions and demonstrated the influence of host genetics in shaping the tumor microbiome. Taken together, these findings indicated that the tumor microbiome is closely related to PDAC oncogenesis and the induction of inflammation. Additionally, our data revealed the microbial basis of PDAC heterogeneity and proved the predictive value of the microbiome, which will contribute to the intervention and treatment of disease.

PI3Kα inhibitor CYH33 triggers antitumor immunity in murine breast cancer by activating CD8+T cells and promoting fatty acid metabolism.

BACKGROUND: The phosphatidylinositol 3-kinase (PI3K) is frequently hyperactivated in cancer and plays important roles in both malignant and immune cells. The effect of PI3Kα inhibitors on the tumor microenvironment (TME) remains largely unknown. Here, we investigated the modulation of the TME by a clinical PI3Kα-specific inhibitor CYH33. METHODS: The activity of CYH33 against a panel of murine tumors in the immune-competent context or athymic mice was detected. Single-cell RNA sequencing and multi-parameter flow cytometry were performed to determine the immune profiling of TME. The effect of CYH33 on immune cells was conducted with primary murine cells. RESULTS: CYH33 exhibited more potent antitumor activity in immune-competent context. CYH33 enhanced the infiltration and activation of CD8+T and CD4+T cells, while attenuating M2-like macrophages and regulatory CD4+T cells. Increase in memory T cells was confirmed by the induction of long-term immune memory on CYH33 treatment. Mechanistically, CYH33 relieved the suppressed expansion of CD8+T cells via preferential polarization of the macrophages to the M1 phenotype. CYH33 promoted fatty acid (FA) metabolism in the TME, while FA enhanced the activity of CD8+T cells in vitro. The combination of CYH33 with the FA synthase (FASN) inhibitor C75 synergistically inhibited tumor growth with enhanced host immunity. CONCLUSIONS: CYH33 induces immune activation and synergizes with FASN inhibitor to further promote the antitumor immunity, which gains novel insights into how PI3K inhibitors exert their activity by modulating TME and provides a rationale for the concurrent targeting of PI3K and FASN in breast cancer treatment.

Identification of Key Genes With Differential Correlations in Lung Adenocarcinoma.

BACKGROUND: With the advent of large-scale molecular profiling, an increasing number of oncogenic drivers contributing to precise medicine and reshaping classification of lung adenocarcinoma (LUAD) have been identified. However, only a minority of patients archived improved outcome under current standard therapies because of the dynamic mutational spectrum, which required expanding susceptible gene libraries. Accumulating evidence has witnessed that understanding gene regulatory networks as well as their changing processes was helpful in identifying core genes which acted as master regulators during carcinogenesis. The present study aimed at identifying key genes with differential correlations between normal and tumor status. METHODS: Weighted gene co-expression network analysis (WGCNA) was employed to build a gene interaction network using the expression profile of LUAD from The Cancer Genome Atlas (TCGA). R package DiffCorr was implemented for the identification of differential correlations between tumor and adjacent normal tissues. STRING and Cytoscape were used for the construction and visualization of biological networks. RESULTS: A total of 176 modules were detected in the network, among which yellow and medium orchid modules showed the most significant associations with LUAD. Then genes in these two modules were further chosen to evaluate their differential correlations. Finally, dozens of novel genes with opposite correlations including ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 were identified. Further biological and survival analyses highlighted their potential values in the diagnosis and treatment of LUAD. Moreover, real-time qPCR confirmed the expression patterns of ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 in LUAD tissues and cell lines. CONCLUSION: Our study provided new insights into the gene regulatory mechanisms during transition from normal to tumor, pioneering a network-based algorithm in the application of tumor etiology.

Levels and Distributions of 210Pb and 210Po in Selected Seafood Samples in China and Assessment of Related Dose to Population.

In this study, the activity concentrations levels of 210Pb and 210Po in the edible portions of eight seafood samples collected from the Fujian coast of China were determined. The activity concentrations ranged from 0.74 ± 0.08 to 12.6 ± 1.0 Bq/kg for 210Po and from the minimum detectable limit (MDL, 0.80 Bq/kg) to 11. 7 ± 1.1 Bq/kg for 210Pb. The 210Po activity concentration in all the fish organs ranged from 0.68 to 204 Bq/kg (w.w.), and the 210Po activity was mainly concentrated in the stomach, spleen, heart, liver, gonad, and intestine samples. The 210Pb activity concentration in all the fish organs ranged from the MDL to 15.2 Bq/kg (w.w.), and the 210Pb activity was concentrated in the head, fish scale, and gill samples. The annual effective ingestion doses ranged from 82.8 to 255 µSv/a for all age groups, and the lifetime risk of cancers were estimated. Both the effective ingestion doses and cancer risk to humans were within the acceptable ranges.

Simultaneous determination of 210Pb and 210Po in seafood samples using liquid scintillation counting.

The measurement of 210Pb and 210Po in seafood samples has attracted tremendous interest because of their radiotoxicity. In this study, a fast and cost-efficient method for the simultaneous determination of 210Pb and 210Po in seafood samples by ultralow-level liquid scintillation counting after separation on a Sr•spec column was developed. The recoveries of 210Pb and 210Po were ~70% and ~85%, respectively. The minimum detectable activity of the proposed method for 210Pb and 210Po was 3.85 Bq/kg and 1.50 Bq/kg, respectively, which is suitable for the determination of 210Pb and 210Po in seafood samples. The radiochemical procedure was validated by measuring 210Pb and 210Po activity concentrations in IAEA-certified reference materials and successfully applied to shrimp and clam samples.

Adaptive resistance to PI3Kα-selective inhibitor CYH33 is mediated by genomic and transcriptomic alterations in ESCC cells.

Phosphoinositide-3 kinase alpha-specific inhibitors (PI3Kαi) displayed promising potential for the treatment of esophageal squamous cell carcinoma (ESCC) with frequent activation in PI3K signaling. However, acquired resistance is likely to develop and limit the efficacy of PI3Kαi like other targeted therapies. To identify genomic adaptation to PI3Kαi, we applied whole-genome sequencing and detected gene mutation and amplification in four lines of ESCC cells established with adapted resistance to a novel PI3Kαi CYH33. Particularly, HRASG12S mutation was found in KYSE180C cells. Overexpression of HRASG12S in ESCC parental cells rendered resistance to CYH33. By contrast, down-regulation of HRASG12S restored the sensitivity of KYSE180C1 cells to CYH33, and combination of CYH33 and MEK162 displayed synergistic effect against KYSE180C1 cells and xenografts. Furthermore, elevated mTORC1, mitogen-activated protein kinase (MAPK), and c-Myc signaling pathways were found in resistant cells by RNA sequencing and combination of CYH33 and RAD001, MEK162, or OTX015 overcame the resistance to CYH33, which was accompanied with enhanced inhibition on S6, extracellular signal-regulated kinase 1 (ERK), or c-Myc, respectively. Overall, we characterized the adaptations to PI3Kαi in ESCC cells and identified combinatorial regimens that may circumvent resistance.

Brca2 deficiency drives gastrointestinal tumor formation and is selectively inhibited by mitomycin C.

BRCA2 is crucial for repairing DNA double-strand breaks with high fidelity, and loss of BRCA2 increases the risks of developing breast and ovarian cancers. Herein, we show that BRCA2 is inactively mutated in 10% of gastric and 7% of colorectal adenocarcinomas, and that this inactivation is significantly correlated with microsatellite instability. Villin-driven Brca2 depletion promotes mouse gastrointestinal tumor formation when genome instability is increased. Whole-genome screening data showed that these BRCA2 monoallelic and biallelic mutant tumors were selectively inhibited by mitomycin C. Mechanistically, mitomycin C provoked double-strand breaks in cancer cells that often recruit wild-type BRCA2 for repair; the failure to repair double-strand breaks caused cell-cycle arrest at the S phase and p53-mediated cell apoptosis of BRCA2 monoallelic and biallelic mutant tumor cells. Our study unveils the role of BRCA2 loss in the development of gastrointestinal tumors and provides a potential therapeutic strategy to eliminate BRCA2 monoallelic and biallelic mutant tumors through mitomycin C.

Natural Selection on Exonic SNPs Shapes Allelic Expression Imbalance (AEI) Adaptability in Lung Cancer Progression.

Tumors are driven by a sequence of genetic and epigenetic alterations. Previous studies have mostly focused on the roles of somatic mutations in tumorigenesis, but how germline variants act is largely unknown. In this study, we hypothesized that allelic expression imbalance (AEI) participated in the process of germline variants on tumorigenesis. We screened single-nucleotide polymorphisms (SNPs) as representative germline variants. By using 127 patients' RNA sequencing data from paired lung cancer and adjacent normal tissues from public databases, we analyzed the effects of the functional consequence of SNPs, function and conservativeness on genes with AEI. We found that natural selection can affect AEI. Functional adaptability of genes with a high frequency of AEI and a correlation of the incidence of AEI with conservativeness were observed in both adjacent tissues and tumor tissues. Moreover, we observed a higher incidence of AEI in genes with non-synonymous SNPs than in those with synonymous SNPs. However, we also found that AEI was affected by allele expression noise, especially in tumor tissues, which led to an increased proportion of AEI, weakened the effect of natural selection and eliminated the influence of the functional consequence of SNPs on AEI. We unveiled a previously unknown adaptive regulatory mechanism in which the effect of natural selection on SNPs can be reflected in allelic expression, which provides insight into a better understanding of cancer evolution.

Identifying circulating miRNA biomarkers for early diagnosis and monitoring of lung cancer.

Liquid biopsy refers to the sampling, screening, and detecting potential biomarkers in unique liquid samples for clinical use. Lung cancer is one of the most highly frequent cancer subtypes, which is hard to be early diagnosed and monitored by radiological and histopathological evaluation that are the most general and accurate methods. Circulating miRNA is a potential clinical examination index for tumor detection and monitoring tumorigenesis progression using liquid biopsy. However, recognizing and validating the unique clinical values of each candidate circulating miRNA is expensive and time consuming. In this study, we presented a novel computational approach for identifying significant circulating miRNAs that may be applied to early screening, diagnosis, and constant monitoring of lung cancer progression. This approach incorporated several machine learning algorithms and was applied on the expression profiles of circulating miRNAs on lung cancer patients and control samples. In brief, a powerful feature selection method, minimum redundancy maximum relevance, was adopted to evaluate the importance of all features, resulting in a feature list. Then, incremental feature selection incorporating random forest followed to extract key circulating miRNAs. At the same time, an efficient classifier with MCC 0.740 was built. Top five circulating miRNAs, including miR-92a, miR-140-5p, miR-331-3p, miR-223, miR-374a, were analyzed and confirmed that they participated in the pathogenesis of lung cancer, indicating their significant prognosis power in lung cancer.

Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.

Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature white blood cells from the bone marrow. Therapy resistance resulting from the persistence of leukemia stem cells (LSCs) are found in numerous patients. Comparative transcriptome studies have been previously conducted to analyze differentially expressed genes between LSC+ and LSC- cells. However, these studies mainly focused on a limited number of genes with the most obvious expression differences between the two cell types. We developed a computational approach incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS), incremental feature selection (IFS), support vector machine (SVM), Repeated Incremental Pruning to Produce Error Reduction (RIPPER), to identify gene expression features specific to LSCs. One thousand 0ne hudred fifty-nine features (genes) were first identified, which can be used to build the optimal SVM classifier for distinguishing LSC+ and LSC- cells. Among these 1159 genes, the top 17 genes were identified as LSC-specific biomarkers. In addition, six classification rules were produced by RIPPER algorithm. The subsequent literature review on these features/genes and the classification rules and functional enrichment analyses of the 1159 features/genes confirmed the relevance of extracted genes and rules to the characteristics of LSCs.