OTU deubiquitinase, ubiquitin aldehyde binding 2 (OTUB2) modulates the stemness feature, chemoresistance, and epithelial-mesenchymal transition of colon cancer via regulating GINS complex subunit 1 (GINS1) expression.

BACKGROUND: Colon cancer is one of the most prevalent tumors in the digestive tract, and its stemness feature significantly contribute to chemoresistance, promote the epithelial-mesenchymal transition (EMT) process, and ultimately lead to tumor metastasis. Therefore, it is imperative for researchers to elucidate the molecular mechanisms underlying the enhancement of stemness feature, chemoresistance, and EMT in colon cancer. METHODS: Sphere-formation and western blotting assays were conducted to assess the stemness feature. Edu, flow cytometry, and cell viability assays were employed to evaluate the chemoresistance. Immunofluorescence and western blotting assays were utilized to detect EMT. Immunoprecipitation, ubiquitination, agarose gel electrophoresis, chromatin immunoprecipitation followed by quantitative PCR (chip-qPCR), and dual luciferase reporter gene assays were employed for mechanistic investigations. RESULTS: We demonstrated a markedly higher expression level of OTUB2 in colon cancer tissues compared to adjacent tissues. Furthermore, elevated OTUB2 expression was closely associated with poor prognosis and distant tumor metastasis. Functional experiments revealed that knockdown of OTUB2 attenuated stemness feature of colon cancer, enhanced its sensitivity to oxaliplatin, inhibited its EMT process, ultimately reduced the ability of tumor metastasis. Conversely, overexpression of OTUB2 exerted opposite effects. Mechanistically, we identified OTUB2 as a deubiquitinase for SP1 protein which bound specifically to SP1 protein, thereby inhibiting K48 ubiquitination of SP1 protein. The SP1 protein functioned as a transcription factor for the GINS1, exerting its regulatory effect by binding to the 1822-1830 region of the GINS1 promoter and enhancing its transcriptional activity. Ultimately, alterations in GINS1 expression directly regulated stemness feature, chemosensitivity, and EMT progression in colon cancer. CONCLUSION: Collectively, the OTUB2/SP1/GINS1 axis played a pivotal role in driving stemness feature, chemoresistance, and EMT in colon cancer. These results shed new light on understanding chemoresistance and metastasis mechanisms involved in colon cancer.

Disulfidptosis signature predicts immune microenvironment and prognosis of gastric cancer.

BACKGROUND: Disulfidptosis is a newly identified mechanism of cell death triggered by disulfide stress. Thus, gaining a comprehensive understanding of the disulfidptosis signature present in gastric cancer (GC) could greatly enhance the development of personalized treatment strategies for this disease. METHODS: We employed consensus clustering to identify various subtypes of disulfidptosis and examined the distinct tumor microenvironment (TME) associated with each subtype. The Disulfidptosis (Dis) score was used to quantify the subtype of disulfidptosis in each patient. Subsequently, we assessed the predictive value of Dis score in terms of GC prognosis and immune efficacy. Finally, we conducted in vitro experiments to explore the impact of Collagen X (COL10A1) on the progression of GC. RESULTS: Two disulfidptosis-associated molecular subtypes (Discluster A and B) were identified, each with distinct prognosis, tumor microenvironment (TME), immune cell infiltration, and biological pathways. Discluster A, characterized by high expression of disulfidptosis genes, exhibited a high immune score but poor prognosis. Furthermore, the Dis score proved useful in predicting the prognosis and immune response in GC patients. Those in the low Dis score group showed better prognosis and increased sensitivity to immunotherapy. Finally, our experimental findings validated that downregulation of COL10A1 expression attenuates the proliferation and migration capabilities of GC cells while promoting apoptosis. CONCLUSIONS: This study demonstrates that the disulfidptosis signature can assist in risk stratification and personalized treatment for patients with GC. The results offer valuable theoretical support for anti-tumor strategies.

Comparative assessment of the capability of machine learning-based radiomic models for predicting omental metastasis in locally advanced gastric cancer.

The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospective collection of 478 pathologically confirmed LAGC patients was undertaken, encompassing both clinical features and arterial phase computed tomography images. Radiomic features were extracted using 3D Slicer software. Clinical and radiomic features were further filtered through lasso regression. Selected clinical and radiomic features were used to construct omental metastasis predictive models using support vector machine (SVM), decision tree (DT), random forest (RF), K-nearest neighbors (KNN), and logistic regression (LR). The models' performance metrics included accuracy, area under the curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In the training cohort, the RF predictive model surpassed LR, SVM, DT, and KNN in terms of accuracy, AUC, sensitivity, specificity, PPV, and NPV. Compared to the other four predictive models, the RF model significantly improved PPV. In the test cohort, all five machine learning predictive models exhibited lower PPVs. The DT model demonstrated the most significant variation in performance metrics relative to the other models, with a sensitivity of 0.231 and specificity of 0.990. The LR-based predictive model had the lowest PPV at 0.210, compared to the other four models. In the external validation cohort, the performance metrics of the predictive models were generally consistent with those in the test cohort. The LR-based model for predicting omental metastasis exhibited a lower PPV. Among the machine learning algorithms, the RF predictive model demonstrated higher accuracy and improved PPV relative to LR, SVM, KNN, and DT models.

SULF1 regulates malignant progression of colorectal cancer by modulating ARSH via FAK/PI3K/AKT/mTOR signaling.

BACKGROUND: Colorectal cancer (CRC) has the third highest incidence and second mortality rate of malignant tumors globally, highlighting the urgency to explore the mechanisms underlying CRC progression for refined treatment of this patient population. METHODS: R Studio was used for data sorting and analysis. Cell apoptosis and cell cycle detection were performed by flow cytometry. Quantitative real-time PCR (qRT-PCR) was used to explore mRNA expression levels. Western blotting was used to explore protein expression levels. CCK8, EdU, and colony formation assays were performed to explore the proliferation capacity of CRC cells. Transwell invasion and migration assays, along with the wound healing assay, were used to explore the invasive and migratory abilities of CRC cells. Subcutaneous Xenograft Assay was utilized to evaluate the tumorigenic capacity of CRC cells in vivo. RESULTS: SULF1 was highly expressed in CRC samples and cell lines. The knockdown of SULF1 inhibited the proliferation, invasion, and migration of CRC and increased the rate of cell apoptosis. Meanwhile, we demonstrated that SULF1 could negatively regulate ARSH through the FAK/PI3K/AKT/mTOR pathway. CONCLUSION: We demonstrated that SULF1 could promote CRC progression by regulating ARSH. The SULF1/ARSH/FAK/PI3K/AKT/mTOR signaling pathway represents a promising target for the treatment of this patient population. Colorectal cancer (CRC) has the third highest incidence and second mortality rate of malignant tumors globally. Sulfatase 1 (SULF1) belongs to the sulfatase family, The function of SULF1 in CRC remains elusive. Our study demonstrated that the knockdown of SULF1 could inhibit the proliferation, invasion, and migration of CRC. Meanwhile, our findings indicated that SULF1 could interact with Arylsulfatase Family Member H (ARSH) to regulate the proliferation, invasion, and migration of CRC via the FAK/PI3K/AKT/mTOR signaling pathway. Taken together, our findings suggest that SULF1 might be a new therapeutic target in CRC.

Chemokine­ and chemokine receptor-based subtypes predict prognosis, immunotherapy and chemotherapy response in colorectal cancer patients.

BACKGROUND: The clinical significance and comprehensive characteristics of chemokines and chemokine receptors in colorectal cancer (CRC) have not been previously reported. Our study aims to investigate the expression profiles of chemokines and chemokine receptors, as well as establish subtypes in CRC. METHODS: 1009 CRC samples were enrolled in our study. Consensus unsupervised clustering analysis was conducted to establish subtypes, and a risk score model was developed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. 36 pairs of tissue specimens of CRC patients and two CRC cell lines were used to validate the subtypes and risk score in vitro. Quantitative real-time PCR and western blotting were employed to validate mRNA and protein expression levels, respectively. Flow cytometry was utilized for analyzing cell apoptosis, while cell viability assay and EdU assay were conducted to assess cell proliferation ability. RESULTS: The Cluster B group shares similarities with the low-risk group in terms of exhibiting a higher level of immune cell infiltration and belonging to hot tumor. Patients CRC in the Cluster B group demonstrate a more favorable prognosis and exhibit better response to immunotherapy and chemotherapy. On the other hand, the Cluster A group resembles the high-risk group as it displays lower levels of immune cell infiltration, indicating a cold tumor phenotype. CRC patients in the Cluster A group have poorer prognoses and show less therapeutic efficacy towards immunotherapy and chemotherapy. Furthermore, we utilized a total of 36 pairs of tissue samples obtained from patients with CRC, along with two CRC cell lines for validation in vitro. This comprehensive approach further enhances the scientific validity and reliability of the identified subtypes and risk score in their ability to predict prognosis, response to immunotherapy, and response to chemotherapy among CRC patients. CONCLUSION: We first established robust prognostic subtypes based on chemokines and chemokine receptors, which could potentially serve as a novel biomarker for guiding individualized treatment in patients with CRC undergoing immunotherapy and chemotherapy.

PANoptosis subtypes predict prognosis and immune efficacy in gastric cancer.

PANoptosis is a form of inflammatory programmed cell death that is regulated by the PANoptosome. This PANoptosis possesses key characteristics of pyroptosis, apoptosis, and necroptosis, yet cannot be fully explained by any of these cell death modes. The unique nature of this cell death mechanism has garnered significant interest. However, the specific role of PANoptosis-associated features in gastric cancer (GC) is still uncertain. Patients were categorized into different PAN subtypes based on the expression of genes related to the PANoptosome. We conducted a systematic analysis to investigate the variations in prognosis and tumor microenvironment (TME) among these subtypes. Furthermore, we developed a risk score, called PANoptosis-related risk score (PANS), which is constructed from genes associated with the PANoptosis. We comprehensively analyzed the correlation between PANS and GC prognosis, TME, immunotherapy efficacy and chemotherapeutic drug sensitivity. Additionally, we performed in vitro experiments to validate the impact of Keratin 7 (KRT7) on GC. We identified two PAN subtypes (PANcluster A and B). PANoptosome genes were highly expressed in PANcluster A. PANcluster A has the characteristics of favorable prognosis, abundant infiltration of anti-tumor lymphocytes, and sensitivity to immunotherapy, thus it was categorized as an immune-inflammatory type. Meanwhile, our constructed PANS can effectively predict the prognosis and immune efficacy of GC. Patients with low PANS have a good prognosis, and have the characteristics of high tumor mutation load (TMB), high microsatellite instability (MSI), low tumor purity and sensitivity to immunotherapy. In addition, PANS can also identify suitable populations for different chemotherapy drugs. Finally, we confirmed that KRT7 is highly expressed in GC. Knocking down the expression of KRT7 significantly weakens the proliferation and migration abilities of GC cells. The models based on PANoptosis signature help to identify the TME features of GC and can effectively predict the prognosis and immune efficacy of GC. Furthermore, the experimental verification results of KRT7 provide theoretical support for anti-tumor treatment.

Chemokine- and chemokine receptor-based signature predicts immunotherapy response in female colorectal adenocarcinoma patients.

The clinical significance and comprehensive characteristics of chemokines and chemokine receptors in female patients with advanced colorectal adenocarcinoma have not ever been reported. Our study explored the expression profiles of chemokines and chemokine receptors and constructed a chemokine- and chemokine receptor-based signature in female patients with advanced colorectal adenocarcinoma. Four independent cohorts containing 1335 patients were enrolled in our study. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were performed to construct the signature. CIBERSORT was used to evaluate the landscape of immune cell infiltration. Thirty-two pairs of tissue specimens of female advanced colorectal cancer (CRC) patients and two CRC cell lines were used to validate the signature in vitro. Quantitative real-time PCR and western blotting were performed to validate the mRNA and protein expression levels of signature genes. EdU and colony formation assays were performed to examine proliferative ability. Transwell and wound healing assays were used to evaluate cell invasion and migration capacity. During the signature construction and validation process, we found that the signature was more applicable to female patients with advanced colorectal adenocarcinoma. Hence, the subsequent study mainly focused on the particular subgroup. Enrichment analyses revealed that the signature was closely related to immunity. The landscape of immune cell infiltration presented that the signature was significantly associated with T cells CD8 and neutrophils. Gene set enrichment analysis (GSEA) confirmed that the high-risk group was chiefly enriched in the tumor-promoting related pathways and biological processes, whereas the low-risk group was mainly enriched in anti-tumor immune response pathways and biological processes. The signature was closely correlated with CTLA4, PDL1, PDL2, TMB, MSI, and TIDE, indicating that our signature could serve as a robust biomarker for immunotherapy and chemotherapy response. ROC curves verified that our signature had more robust prognostic power than all immune checkpoints and immunotherapy-related biomarkers. Finally, we used 32 pairs of tissue specimens and 2 CRC cell lines to validate our signature in vitro. We first provided a robust prognostic chemokine- and chemokine receptor-based signature, which could serve as a novel biomarker for immunotherapy and chemotherapy response to guide individualized treatment for female patients with advanced colorectal adenocarcinoma.

Surgical approach for complete resection of giant retroperitoneal liposarcoma with diaphragmatic hernia via ninth rib thoracotomy.

Background: Resection of a giant retroperitoneal liposarcoma is difficult and technically demanding, especially for large retroperitoneal tumors accompanied by a diaphragmatic hernia. Technically, the open abdominal approach can be time-consuming and difficult to perform, with possible intraoperative complications and other factors bringing psychological and physical difficulties to the patient. This study reports a safe and feasible approach for the complete resection of a large retroperitoneal tumor complicated by a diaphragmatic hernia. Methods: A 58-year-old male patient with persistent upper abdominal pain and distension was treated at a local hospital on 4 July 2022. Computed tomography showed a mixed-density mass on the right retroperitoneum, and liposarcoma was considered. On 6 July 2022, the patient was transferred to our hospital for further treatment. Computed tomography showed a mass with low-density fatty shadow in the right adrenal region. The boundary with the right adrenal gland was unclear. The mass was 102 mm × 74 mm, and the right lobe of the liver was compressed. Insufficiency of the right middle lobe of the liver was seen due to a right diaphragmatic hernia and left mediastinal deviation. We considered the traditional approach for tumor resection via laparotomy, but we opted to perform a comprehensive evaluation first. The tumor was close to the back of the right kidney and liver, causing the diaphragm to rise because of its proximity to these organs. Exposing the tumor through laparotomy would be difficult, making it challenging to remove. The patient had a diaphragmatic hernia and moderate pulmonary dysfunction; therefore, we decided to enter the abdomen through a thoracotomy of the ninth rib. Results: Using our technique, the tumor was easily visualized and completely removed in approximately 30 min. The intraoperative blood loss was 100 ml, and no postoperative bleeding, pneumothorax, intestinal fistula, infection, or other complications occurred. Conclusion: The transthoracic approach may be a safer and more feasible resection method than the traditional open approach for patients with giant retroperitoneal liposarcoma with a diaphragmatic hernia.

Development and validation of a CT radiomics and clinical feature model to predict omental metastases for locally advanced gastric cancer.

""We employed radiomics and clinical features to develop and validate a preoperative prediction model to estimate the omental metastases status of locally advanced gastric cancer (LAGC). A total of 460 patients (training cohort, n = 250; test cohort, n = 106; validation cohort, n = 104) with LAGC who were confirmed T3/T4 stage by postoperative pathology were continuously collected retrospectively, including clinical data and preoperative arterial phase computed tomography images (APCT). Dedicated radiomics prototype software was used to segment the lesions and extract features from the preoperative APCT images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the extracted radiomics features, and a radiomics score model was constructed. Finally, a prediction model of omental metastases status and a nomogram were constructed combining the radiomics scores and selected clinical features. An area under the curve (AUC) of the receiver operating characteristic curve (ROC) was used to validate the capability of the prediction model and nomogram in the training cohort. Calibration curves and decision curve analysis (DCA) were used to evaluate the prediction model and nomogram. The prediction model was internally validated by the test cohort. In addition, 104 patients from another hospital's clinical and imaging data were gathered for external validation. In the training cohort, the combined prediction (CP) model (AUC 0.871, 95% CI 0.798-0.945) of the radiomics scores combined with the clinical features, compared with clinical features prediction (CFP) model (AUC 0.795, 95% CI 0.710-0.879) and radiomics scores prediction (RSP) model (AUC 0.805, 95% CI 0.730-0.879), had the better predictive ability. The Hosmer-Lemeshow test of the CP model showed that the prediction model did not deviate from the perfect fitting (p = 0.893). In the DCA, the clinical net benefit of the CP model was higher than that of the CFP model and RSP model. In the test and validation cohorts, the AUC values of the CP model were 0.836 (95% CI 0.726-0.945) and 0.779 (95% CI 0.634-0.923), respectively. The preoperative APCT-based clinical-radiomics nomogram showed good performance in predicting omental metastases status in LAGC, which may contribute to clinical decision-making.

Schwann cells as a target cell for the treatment of cancer pain.

Tumor erosion and metastasis can invade surrounding tissues, damage nerves, and sensitize the peripheral primary receptors, inducing pain, which can potentially worsen the suffering of patients with cancer. Reception and transmission of sensory signal receptors, abnormal activation of primary sensory neurons, and activation of glial cells are involved in cancer pain. Therefore, exploring promising therapeutic methods to suppress cancer pain is of great significance. Various studies have found that the use of functionally active cells is a potentially effective way to relieve pain. Schwann cells (SCs) act as small, biologically active pumps that secrete pain-relieving neuroactive substances. Moreover, SCs can regulate the progression of tumor cells, including proliferation and metastasis, through neuro-tumor crosstalk, which emphasizes the critical role of SCs in cancer and cancer pain. The mechanisms by which SCs repair injured nerves and exert analgesia include neuroprotection, neurotrophy, nerve regeneration, neuromodulation, immunomodulation, and enhancement of the nerve-injury microenvironment. These factors may ultimately restore the damaged or stimulated nerves and contribute to pain relief. Strategies for pain treatment using cell transplantation mainly focus on analgesia and nerve repair. Although these cells are in the initial stages of nerve repair and pain, they open new avenues for the treatment of cancer pain. Therefore, this paper discusses, for the first time, the possible mechanism of SCs and cancer pain, and new strategies and potential problems in cancer pain treatment.

ATP ion channel P2X purinergic receptors in inflammation response.

Different studies have confirmed that P2X purinergic receptors play a key role in inflammation. Activation of P2X purinergic receptors can release inflammatory cytokines and participate in the progression of inflammatory diseases. In an inflammatory microenvironment, cells can release a large amount of ATP to activate P2X receptors, open non-selective cation channels, activate multiple intracellular signaling, release multiple inflammatory cytokines, amplify inflammatory response. While P2X4 and P2X7 receptors play an important role in the process of inflammation. P2X4 receptor can mediate the activation of microglia involved in neuroinflammation, and P2X7 receptor can mediate different inflammatory cells to mediate the progression of tissue-wide inflammation. At present, the role of P2X receptors in inflammatory response has been widely recognized and affirmed. Therefore, in this paper, we discussed the role of P2X receptors-mediated inflammation. Moreover, we also described the effects of some antagonists (such as A-438079, 5-BDBD, A-804598, A-839977, and A-740003) on inflammation relief by antagonizing the activities of P2X receptors.