Novel function of THEMIS2 in the enhancement of cancer stemness and chemoresistance by releasing PTP1B from MET

Triple negative breast cancer (TNBC) possesses poor prognosis mainly due to lack of effective endocrine or targeted therapies, aggressive nature and high rate of chemoresistance. Cancer stem cells (CSCs) are considered to play critical roles in cancer recurrence and chemoresistance. THEMIS2 was identified as the sole common elevated gene in three triple negative breast cancer (TNBC) and two ovarian CSC lines. We discovered an intrinsic signaling scaffold function of THEMIS2, which acts as a novel regulator of cancer stemness in promoting multiple cancer stemness properties including sphere formation, stemness markers expression, chemoresistance and tumorigenicity with low numbers of cancer cells implantation. For the first time, we demonstrated that THEMIS2 specifically enhanced MET activating phosphorylation by suppressing the association of protein-tyrosine phosphatases 1B (PTP1B) with p-MET and MET, which accounted mainly for THEMIS2-mediated effect on cancer stemness and chemoresistance. Increased THEMIS2 expression was associated with poor survival in TNBC patients and in patients from our breast cancer cohort. We found that non-cytotoxic dosages of cryptotanshinone (CPT) could potently inhibit cancer stemness, chemoresistance and tumorigenicity by suppressing expression of THEMIS2. Notably, stable overexpression of THEMIS2 is associated with enhanced sensitivity toward Capmatinib and CPT treatment. Expression levels of THEMIS2 and p-MET protein were positively correlated in the 465 breast cancer specimens. Our study revealed the novel oncogenic role of THEMIS2 and its underlying mechanism via suppressing PTP1B association with MET and thus leading to its activation. Our findings suggest that THEMIS2 could be a biomarker for MET targeted therapy and also provide a potential clinical application using low dosages of CPT for treatment of THEMIS2 positive TNBC.

Identification of a Cancer Stemness Driven Prognostic Model and Therapeutic Drug Targets by Machine Learning in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies. Cancer stem cells (CSCs), characterized by self-renewal and drug-resistance, play an important role in the development and progression of diverse cancers, but the underlying association of HCC and CSCs is not fully researched.Methods: Transcriptome and clinical data of 903 patients in four independent HCC cohorts were obtained from TCGA, ICGC, and GEO databases. We evaluated the stemlike index for each patient to reflect the cancer stemness by using one-class logistic regression (OCLR) algorithm. GISTIC 2.0, Maftools and GSVA were used to reveal the association between the stemness index and genomic variation and biological processes in HCC. The differential expression analysis, univariate Cox analysis and LASSO analysis were used to identify the prognostic stemness signatures. The HCC stemness-related risk score (HCSRS) was constructed to quantify stemness levels of individual tumors. Based on HCSRS, the nomogram was established for HCC prognosis in a quantitative approach. Additionally, single sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to evaluate the immune infiltration levels in HCC, and drug response analysis was adopted to identify potential agents with drug sensitivity in high-HCSRS score patients.Results: The stemness index in HCC tissues was significantly higher than that in normal tissues, and there was a significant positive correlation with pathological grade. Patients with high stemness index showed higher somatic mutation frequency, tumor mutation load, and copy number variation frequency, and were significantly enriched in tumor-related signaling pathways. Meanwhile, the 7-gene based HCSRS model that was trained and validated in 4 independent cohorts exhibited high predictive significance for overall survival (OS). Further analysis revealed that patients with high HCSRS possessed higher immunosuppression status, characterized by significantly decreased infiltration of anti-tumor immune cells (CD8 T cells, cytotoxic T cells, DC cells, NK cells, etc.) and exhausted CYT responses. At last, a total of twelve agents were identified to have potential therapeutic effects in high-HCSRS patients.Conclusion: In current study, we systematically analyzed the potential relationship of HCC stemness with genomic variation, tumor microenvironment and biological processes, provided a theoretical basis for individualized treatment of HCC patients.

miR-137 Inhibition of the Invasion, Metastasis, and Epithelial-Mesenchymal Transition of Nasopharyngeal Cancer by Regulating KDM1A

One of the most frequent malignancies in the head and neck is nasopharyngeal carcinoma (NPC). MicroRNAs, a kind of tiny noncoding RNA molecule, have been used as negative regulators in different types of cancer therapy in recent decades by downregulating their targets. Recent research suggests that microRNAs play an important role in cancer’s epithelial-to-mesenchymal transition (EMT), supporting or inhibiting EMT development. The epithelial-to-mesenchymal transition (EMT) is linked to a variety of cancer-related activities, including growth, metastasis, and invasion. Previous research has linked EMT to cancer stem-like characteristics as well as treatment resistance. Moreover, since microRNAs (miRNAs) are important regulators of the EMT phenotype, certain miRNAs have an effect on cancer stemness and treatment resistance. As a result, both fundamental research and clinical therapy benefit from knowing the connection between EMT-associated miRNAs and cancer stemness/drug resistance. As a result, we looked at the different functions that EMT-associated miRNAs (miR-137) play in the stem-like characteristics of malignant cells in this article. Then we looked at how EMT-associated miRNAs interact with nasopharyngeal cancer’s drug-resistant complex signaling pathways. Using qRT-PCR, we evaluated the performance of several micro RNAs with the proposed miR-137 for inhibiting invasion, metastasis, and the EMT process. In conclusion, our findings showed that miR-137 acted as a tumor suppressor gene in controlling NPC EMT and metastasis and that it may be a new therapeutic strategy and prognosis marker for the disease.

The Small-Molecule Wnt Inhibitor ICG-001 Efficiently Inhibits Colorectal Cancer Stemness and Metastasis by Suppressing MEIS1 Expression

Recurrence and metastasis remain major obstacles in colorectal cancer (CRC) treatment. Recent studies suggest that a small subpopulation of cells with a self-renewal ability, called cancer stem-like cells (CSCs), promotes recurrence and metastasis in CRC. Unfortunately, no CSC inhibitor has been demonstrated to be more effective than existing chemotherapeutic drugs, resulting in a significant unmet need for effective CRC therapies. In this study, transcriptomic profiling of metastatic tumors from CRC patients revealed significant upregulation in the Wnt pathway and stemness genes. Thus, we examined the therapeutic effect of the small-molecule Wnt inhibitor ICG-001 on cancer stemness and metastasis. The ICG-001 treatment efficiently attenuated self-renewal activity and metastatic potential. Mechanistically, myeloid ecotropic viral insertion site 1 (MEIS1) was identified as a target gene of ICG-001 that is transcriptionally regulated by Wnt signaling. A series of functional analyses revealed that MEIS1 enhanced the CSC behavior and metastatic potential of the CRC cells. Collectively, our findings suggest that ICG-001 efficiently inhibits CRC stemness and metastasis by suppressing MEIS1 expression. These results provide a basis for the further clinical investigation of ICG-001 as a targeted therapy for CSCs, opening a new avenue for the development of novel Wnt inhibitors for the treatment of CRC metastasis.

Immune Infiltration, Cancer Stemness, and Targeted Therapy in Gastrointestinal Stromal Tumor

ObjectiveTo investigate the characteristics of the tumor immune microenvironment in patients with gastrointestinal stromal tumor (GIST) and identify cancer stem-like properties of GIST to screen potential druggable molecular targets.MethodsThe gene expression data of 60 patients with GIST was retrieved from the Array Express database. CIBERSORT was applied to calculate the level of immune infiltration. ssGSEA and ESTIMATE were used to calculate the cancer stemness index and tissue purity. The Connectivity Map (CMAP) database was implemented to screen targeted drugs based on cancer stem-like properties of GIST.ResultThere was a difference in the level of immune infiltration between the metastasis and non-metastasis GIST groups. The low level of T-cell infiltration was correlated with high tumor purity and tumor stemness index, and the correlation coefficients were -0.87 and -0.61 (p < 0.001), respectively. Furthermore, there was a positive correlation between cancer stemness index and cell purity (p < 0.001). The cancer stemness index in the metastasis group was higher than that in the non-metastasis group (p = 0.0017). After adjusting for tumor purity, there was no significant correlation between T-cell infiltration and cancer stemness index (p = 0.086). Through the pharmacological mechanism of topoisomerase inhibitors, six molecular complexes may be the targets of GIST treatment.ConclusionImmune infiltration in GIST patients is related to cancer stem-like properties, and the correlation relies on tumor purity. Cancer stemness index can be used as a new predictive biomarker of tumor metastasis and targets of drug therapy for GIST patients.

Development and Validation of a Novel M6A-related LncRNA Prognostic Signature Associated with Immune Microenvironment for Ovarian Serous Cystadenocarcinoma

Background: OV is the most lethal gynecological malignancy. M6A and lncRNAs have great influence on OV development and patients' immunotherapy response. Here, we decided to establish a reliable signature in the light of mRLs. Method: The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis in the light of TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model in the light of the mRLs. K-M analysis, PCA, GSEA, and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune features comparison, consensus clustering analysis, and Pan-cancer analysis.Results: A prognostic signature comprising four mRLs: WAC-AS1, LINC00997, DNM3OS, and FOXN3-AS1, was constructed and verified for OV according to TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, people can identify patients more effectively. All the sample were assigned into two clusters, and the clusters had different overall survival, clinical features, and tumor microenvironment. Finally, Pan-cancer analysis further demonstrated the four mRLs significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. Conclusion: This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.