Pre-treatment CT-based radiomics nomogram for predicting microsatellite instability status in colorectal cancer.

OBJECTIVES: Stratification of microsatellite instability (MSI) status in patients with colorectal cancer (CRC) improves clinical decision-making for cancer treatment. The present study aimed to develop a radiomics nomogram to predict the pre-treatment MSI status in patients with CRC. METHODS: A total of 762 patients with CRC confirmed by surgical pathology and MSI status determined with polymerase chain reaction (PCR) method were retrospectively recruited between January 2013 and May 2019. Radiomics features were extracted from routine pre-treatment abdominal pelvic computed tomography (CT) scans acquired as part of the patients' clinical care. A radiomics nomogram was constructed using multivariate logistic regression. The performance of the nomogram was evaluated using discrimination, calibration, and decision curves. RESULTS: The radiomics nomogram incorporating radiomics signatures, tumor location, patient age, high-density lipoprotein expression, and platelet counts showed good discrimination between patients with non-MSI-H and MSI-H, with an area under the curve (AUC) of 0.74 [95% CI, 0.68-0.80] in the training cohort and 0.77 [95% CI, 0.68-0.85] in the validation cohort. Favorable clinical application was observed using decision curve analysis. The addition of pathological characteristics to the nomogram failed to show incremental prognostic value. CONCLUSIONS: We developed a radiomics nomogram incorporating radiomics signatures and clinical indicators, which could potentially be used to facilitate the individualized prediction of MSI status in patients with CRC. KEY POINTS: • There is an unmet need to non-invasively determine MSI status prior to treatment. However, the traditional radiological evaluation of CT is limited for evaluating MSI status. • Our non-invasive CT imaging-based radiomics method could efficiently distinguish patients with high MSI disease from those with low MSI disease. • Our radiomics approach demonstrated promising diagnostic efficiency for MSI status, similar to the commonly used IHC method.

CT imaging findings of renal epithelioid lipid-poor angiomyolipoma.

OBJECTIVES: To identify specific imaging and clinicopathological features of a rare potentially malignant epithelioid variant of renal lipid-poor angiomyolipoma (E-lpAML). METHODS: A total of 20 patients with E-lpAML and 43 patients with other lpAML were retrospectively included. Multiphase computed tomography (CT) imaging features and clinicopathological findings were recorded. Independent predictors for E-lpAML were identified using multivariate logistic regression and were used to construct a diagnostic score for differentiation of E-lpAML from other lpAML. RESULTS: The E-lpAML group consisted of 6 men and 14 women (age median ± SD: 39.45 ± 15.70, range: 16.0-68.0 years). E-lpAML tended to appear as hyperdense mass lesions located at the renal sinus (n = 8, 40%) or at the renal cortex (n = 12, 60%), with a "fast-in and slow-out" enhancement pattern (n = 20, 100%), cystic degeneration (n = 18, 90%), "eyeball" sign (n = 11, 55%), and tumor neo-vasculature (n = 15, 75%) on CT. Multivariate logistic regression analysis showed that the independent predictors for diagnosing E-lpAML were cystic degeneration on CT imaging and CT value of the tumor in corticomedullary phase of enhancement. A predictive model was built with the two predictors, achieving an area under the curve (AUC) of 93.5% (95% confidence interval (95%CI): 84.3-98.2%) with a sensitivity of 95.0% (95%CI: 75.1-99.9%) and a specificity of 83.72% (95%CI: 69.3-93.2%). CONCLUSION: We identified specific CT imaging features and predictors that could contribute to the correct diagnosis of E-lpAML. Our findings should be helpful for clinical management of E-lpAML which could potentially be malignant and may require nephron-sparing surgery while other lpAML tumors which are benign require no intervention. KEY POINTS: • It is important to differentiate renal epithelioid lipid-poor angiomyolipoma (E-lpAML) from other lpAML because of differences in clinical management. • E-lpAML tumors tend to be large hyperdense tumors in the renal sinus with cystic degeneration and "fast-in and slow-out" pattern of enhancement. • Our CT imaging-based predictive model was robust in its performance for predicting E-lpAML from other lpAML tumors.

Trace the profile and function of circular RNAs in Sertoli cell only syndrome.

Studies increasingly show the involvement of circular RNAs (circRNAs) in several diseases. This study aims to explore the circRNA expression pattern in the testicular tissues of patients with Sertoli only cell syndrome (SCOS) and their potential functions. High throughput circRNA microarray analysis indicated that 399 circRNAs were upregulated and 1195 were down-regulated (fold change >2, P < 0.05) in SCOS relative to obstructive azoospermia (OA). The hsa_circRNA_101222, hsa_circRNA_001387, hsa_circRNA_001153, hsa_circRNA_101373 and hsa_circRNA_103864 were validated by qRT-PCR. Furthermore, the hosting genes of the differentially expressed circRNAs (DEcircRNAs) were enriched in biological processes related to cell cycle and intercellular communication. Also, the overlapping genes between the hosting genes of SCOS-related DEcircRNAs and those highly expressed in Sertoli cells of non-obstructive azoospermia (NOA) were enriched in immune cell development and cell communication. Taken together, aberrantly expressed circRNAs likely mediate SCOS development by regulating the function of Sertoli cells and the spermatogenic microenvironment.

Effect of lamin-A expression on migration and nuclear stability of ovarian cancer cells.

OBJECTIVE: Nuclear lamina plays important roles in nuclear shape and mechanical stability. Many studies demonstrated that defects of lamin-A were associated with several diseases, but little research was found on its potential roles in ovarian cancer. METHODS: GEPIA and GEO database were used to analyze lamin-A in ovarian tissues, followed by assessing lamin-A and prognosis of ovarian cancer patients with Kaplan-Meier plotter. Then, transient transfected HO-8910 cells with shRNA to knockdown lamin-A. Knockdown efficiency was determined by western blot, qRT-PCR and immunofluorescence. Meanwhile, lamin-A was overexpressed in HO-8910 PM cells. Then, 2D migration, 3D migration through 3 µm and 8 µm pores were carried out, followed by immunofluorescence and TEM observation. RESULTS: Lamin-A tended to be lower in ovarian cancer, and higher expression of lamin-A was associated with better survival. After lamin-A knockdown, 2D and 3D migration (3 µm, 8 µm) abilities of HO-8910 cells were significantly increased (p < 0.001), while overexpression of lamin-A in HO-8910PM impeded migration. Meanwhile, when HO-8910 cells migrated through 3 µm pores, nuclei became strikingly elongated, and down-regulation of lamin-A promoted nuclear plasticity, making the circularity of nucleus increased. Besides, further knockdown group had the highest proportion of γ-H2AX, with micronuclei forming. Furthermore, western blot showed that the expression of BRCA1, Ku80 and Rad50 decreased significantly after further knockdown, suggesting impairment of DNA damage repair. CONCLUSIONS: Lamin-A was down-regulated in ovarian cancer, and higher lamin-A was associated with better prognosis. Nuclei with high lamin-A were severely deformed through constricted pores. Moderate lamin-A enhanced nuclear plasticity, so as to strengthen migration ability. When lamin-A was further knockdown, ovarian cancer cells that migrated through restricted pores decreased, with DNA damage, genomic instability and impairment of DNA damage repair.

Gliosarcoma: a clinical and radiological analysis of 48 cases.

OBJECTIVES: To retrospectively review the radiological and clinicopathological features of gliosarcoma (GSM) and differentiate it from glioblastoma multiforme (GBM). METHODS: The clinicopathological data and imaging findings (including VASARI analysis) of 48 surgically and pathologically confirmed GSM patients (group 1) were reviewed in detail, and were compared with that of other glioblastoma (GBM) cases in our hospital (group 2). RESULTS: There were 28 men and 20 women GSM patients with a median age of 52.5 years (range, 24-80 years) in this study. Haemorrhage (n = 21), a salt-and-pepper sign on T2-weighted images (n = 36), unevenly thickened wall (n = 36) even appearing as a paliform pattern (n = 32), an intra-tumoural large feeding artery (n = 32) and an eccentric cystic portion (ECP) (n = 19) were more commonly observed in the GSM group than in GBM patients. Based on our experience, GSM can be divided into four subtypes according to magnetic resonance imaging (MRI) features. When compared to GBM (group 2), there were more patients designated with type III lesions (having very unevenly thickened walls) and IV (solid) lesions among the GSM cases (group 1). On univariate prognostic analysis, adjuvant therapy (radiotherapy, chemotherapy, and radiochemotherapy) and existence of an eccentric cyst region were prognostic factors. However, Cox's regression model showed only adjuvant therapy as a prognostic factor for GSM. CONCLUSIONS: When compared to GBM, certain imaging features are more likely to occur in GSM, which may help raise the possibility of this disease. All GSM patients are recommended to receive adjuvant therapy to achieve a better prognosis with radiotherapy, chemotherapy or radiochemotherapy all as options. KEY POINTS: • Diagnosis of gliosarcoma can be suggested preoperatively by imaging. • Gliosarcoma can be divided into four subtypes based on MRI. • Paliform pattern and ECP tend to present in gliosarcoma more than GBM. • The cystic subtype of gliosarcoma may predict a more dismal prognosis. • All gliosarcoma patients should receive adjuvant therapy to achieve better prognosis.

[Molecular markers derived from ovarian cancer and its correlation with the types of oviductal epithelial lesions].

OBJECTIVE: To explore the role of P53, pairing box gene 8 antibody (PAX8), and calcium omentum protein (Calretinin) in the origin of epithelial ovarian cancer.
 Methods: A total of 63 tissue samples of ovarian tumor and fallopian tubes were collected. Immunohistochemistry methods were used to analyze the expression of P53, PAX8, and Calretinin. The relationship between these protein levels and the classification of ovarian tumors was evaluated.
 Results: In epithelial ovarian cancer, the P53 or PAX8 was correlated with the occurrence of high-grade carcinoma, while the calretinin was correlated with the occurrence of low-grade carcinoma (P<0.05). The combination of PAX8 with Calretinin was correlated with the grade of ovarian tumor (P<0.05). The combination of P53 with Calretinin was correlated with the grade of tumor (P<0.05). The combination of P53 with PAX8 was correlated with the grade of tumor (P<0.05). The expression of P53 in fallopian tubes was correlated with the malignant degree of epithelial ovarian cancer (P<0.05). The degree of fallopian tube lesions in patients with ovarian cancer was correlated with epithelial ovarian cancer. The malignant lesions of tubal epithelium was correlated with high-grade carcinoma, while the normal or atypical hyperplasia of tubal epithelium was correlated with low-grade carcinoma (P<0.05).
 Conclusion: P53 and Calretinin combined with PAX8 show a synergistic effect on the differentiation of epithelial ovarian cancer grade. The morphology of HE and the expression of TP53 in the fallopian tube epithelium play an auxiliary role in the diagnosis of epithelial ovarian cancer.

The role of miR-205 in the VEGF-mediated promotion of human ovarian cancer cell invasion.

OBJECTIVE: Our objective was to investigate a miRNA pathway that acts downstream of VEGF-induced invasion of ovarian cancer cells. METHOD: We used two paired high and low metastatic serous ovarian cancer cells to demonstrate the role of miR-205 in VEGF-induced invasion of ovarian cancer cells and to investigate the gene targets of miR-205. RESULTS: Our previous comparative proteomics studies showed that VEGF decreased the expression of Ezrin and Lamin A/C, and this result was validated in the present study using qPCR and Western blotting. Then we found that VEGF enhanced the invasiveness of and inhibited apoptosis in ovarian cancer cells as assessed by transwell invasion assays and Annexin V-FITC immunostaining, respectively. VEGFR was also expressed in ovarian cancer cells, as assessed by immunocytochemical staining. Furthermore, using the dual-luciferase report assay system, we demonstrated that miR-205 targeted Ezrin and Lamin A/C. MiR-205 was up-regulated in ovarian cancer cells exposed to VEGF, as determined by miRNA microarray analysis and verified by qPCR. MiR-205 promoted the invasion and proliferation of ovarian cancer cells. CONCLUSION: Our data reveal a new potential pathway in which VEGF promotes the invasion of ovarian cancer cells, partially via the down-regulation of Ezrin and Lamin A/C caused by increased expression of miR-205.

Ensemble Machine Learning Model Incorporating Radiomics and Body Composition for Predicting Intraoperative HDI in PPGL.

CONTEXT: Intraoperative hemodynamic instability (HDI) can lead to cardiovascular and cerebrovascular complications during surgery for pheochromocytoma/paraganglioma (PPGL). OBJECTIVES: We aimed to assess the risk of intraoperative HDI in patients with PPGL to improve surgical outcome. METHODS: A total of 199 consecutive patients with PPGL confirmed by surgical pathology were retrospectively included in this study. This cohort was separated into 2 groups according to intraoperative systolic blood pressure, the HDI group (n = 101) and the hemodynamic stability (HDS) group (n = 98). It was also divided into 2 subcohorts for predictive modeling: the training cohort (n = 140) and the validation cohort (n = 59). Prediction models were developed with both the ensemble machine learning method (EL model) and the multivariate logistic regression model using body composition parameters on computed tomography, tumor radiomics, and clinical data. The efficiency of the models was evaluated with discrimination, calibration, and decision curves. RESULTS: The EL model showed good discrimination between the HDI group and HDS group, with an area under the curve of (AUC) of 96.2% (95% CI, 93.5%-99.0%) in the training cohort, and an AUC of 93.7% (95% CI, 88.0%-99.4%) in the validation cohort. The AUC values from the EL model were significantly higher than the logistic regression model, which had an AUC of 74.4% (95% CI, 66.1%-82.6%) in the training cohort and an AUC of 74.2% (95% CI, 61.1%-87.3%) in the validation cohort. Favorable calibration performance and clinical applicability of the EL model were observed. CONCLUSION: The EL model combining preoperative computed tomography-based body composition, tumor radiomics, and clinical data could potentially help predict intraoperative HDI in patients with PPGL.

CT radiomics identifying non-responders to neoadjuvant chemoradiotherapy among patients with locally advanced rectal cancer.

BACKGROUND AND PURPOSE: Early detection of non-response to neoadjuvant chemoradiotherapy (nCRT) for locally advanced colorectal cancer (LARC) remains challenging. We aimed to assess whether pretreatment radiotherapy planning computed tomography (CT) radiomics could distinguish the patients with no response or no downstaging after nCRT from those with response and downstaging after nCRT. MATERIALS AND METHODS: Patients with LARC who were treated with nCRT were retrospectively enrolled between March 2009 and March 2019. Traditional radiological characteristics were analyzed by visual inspection and radiomic features were analyzed through computational methods from the pretreatment radiotherapy planning CT images. Differentiation models were constructed using radiomic methods and clinicopathological characteristics for predicting non-response to nCRT. Model performance was assessed for classification efficiency, calibration, discrimination, and clinical application. RESULTS: This study enrolled a total of 215 patients, including 151 patients in the training cohort (50 non-responders and 101 responders) and 64 patients in the validation cohort (21 non-responders and 43 responders). For predicting non-response, the model constructed with an ensemble machine learning method had higher performance with area under the curve (AUC) values of 0.92 and 0.89 as compared to the model constructed with the logistic regression method (AUC: 0.72 and 0.71 for the training and validation cohorts, respectively). Both decision curve and calibration curve analyses confirmed that the ensemble machine learning model had higher prediction performance. CONCLUSION: Pretreatment CT radiomics achieved satisfying performance in predicting non-response to nCRT and could be helpful to assist in treatment planning for patients with LARC.

CT-based assessment of sarcopenia for differentiating wild-type from mutant-type gastrointestinal stromal tumor.

Non-invasive prediction for KIT/PDGFRA status in GIST is a challenging problem. This study aims to evaluate whether CT based sarcopenia could differentiate KIT/PDGFRA wild-type gastrointestinal stromal tumor (wt-GIST) from the mutant-type GIST (mu-GIST), and to evaluate genetic features of GIST. A total of 174 patients with GIST (wt-GIST = 52) were retrospectively identified between January 2011 to October 2019. A sarcopenia nomogram was constructed by multivariate logistic regression. The performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve. Genomic data was obtained from our own specimens and also from the open databases cBioPortal. Data was analyzed by R version 3.6.1 and clusterProfiler ( http://cbioportal.org/msk-impact ). There were significantly higher incidence (75.0% vs. 48.4%) and more severe sarcopenia in patients with wt-GIST than in patients with mu-GIST. Multivariate logistic regression analysis showed that sarcopenia score (fitted based on age, gender and skeletal muscle index), and muscle fat index were independent predictors for higher risk of wt-GIST (P < 0.05 for both the training and validation cohorts). Our sarcopenia nomogram achieved a promising efficiency with an AUC of 0.879 for the training cohort, and 0.9099 for the validation cohort with a satisfying consistency in the calibration curve. Favorable clinical usefulness was observed using decision curve analysis. The additional gene sequencing analysis based on both our data and the external data demonstrated aberrant signal pathways being closely associated with sarcopenia in the wt-GIST. Our study supported the use of CT-based assessment of sarcopenia in differentiating the wt-GIST from the mu-GIST preoperatively.

CX3CL1-induced CD16+ monocytes extravasation in myeloperoxidase-ANCA-associated vasculitis correlates with renal damage.

Background: Monocytes are involved in the pathogenesis of ANCA-associated vasculitis (AAV). Monocyte/macrophages are the dominant infiltrating cells in the glomeruli of patients with myeloperoxidase-AAV (MPO-AAV). However, how human monocyte subsets extravasate to the kidney in MPO-AAV with renal damage is unclear. Methods: 30 MPO-AAV patients with renal damage and 22 healthy controls were enrolled in this study. Monocyte subsets and monocyte-related chemokines in the blood and kidneys of MPO-AAV patients were detected. The chemoattractant activity of the CX3CL1-CX3CR1 axis on CD16+ monocytes was observed. The effect of MPO-ANCA on the migration of CD16+ monocytes to human glomerular endothelial cells (HGECs) was detected by flow cytometry and transwell migration assay. Results: Compared with controls, CD16+ monocytes were significantly decreased in the blood and increased in the glomeruli of MPO-AAV patients with renal damage. The level of CX3CL1, but not CCL2, was significantly increased in the plasma of MPO-AAV patients. CX3CL1 co-localized with glomerular endothelial cells in MPO-AAV patients with renal damage. Moreover, we initially found that MPO-ANCA promotes an increase of the chemokine CX3CL1 on HGECs, imposing recruitment on CD16+ monocytes. Finally, the percentage of CD16+ monocytes in the blood was found to be positively correlated with estimated glomerular filtration rate (eGFR) and negatively correlated with urinary protein creatinine ratio in MPO-AAV patients with renal damage. Furthermore, the urinary protein creatinine ratio was positively correlated with the infiltrating of CD14+ and CD16+ cells in the kidneys. Conclusion: Enhanced extravasation of CD16+ monocytes to the kidney via the CX3CL1-CX3CR1 axis may be involved in renal damage in MPO-AAV.

THEM6: A Novel Molecular Biomarker Predicts Tumor Microenvironment, Molecular Subtype, and Prognosis in Bladder Cancer.

Background: Thioesterase superfamily member 6 (THEM6) has been implicated in the development and progression of various cancers. However, prior research emphasized on its regulatory role merely, we aim to investigate the effect of THEM6 gene on the immunological role and its relationship with molecular subtype in bladder cancer (BLCA). Methods: Through pan-cancer analysis, we explored the THEM6 expression pattern and immunological role using The Cancer Genome Atlas (TCGA) database. In addition, we performed a correlation of THEM6 and its immunological functions, including immunomodulators, immune checkpoints, cancer immunity cycles, T cell inflamed score, and tumor-infiltrating immune cells in the BLCA tumor microenvironment (TME) based on TCGA and BLCA microarray cohort from Xiangya Hospital. We also assessed the accuracy of THEM6 in predicting the molecular subtype and its response to different interventions in BLCA. Finally, we computed and validated a prediction model established by THEM6-related different expressed immune-related genes that might help in BLCA prognosis. Results: THEM6 led to immunosuppression in BLCA TME. Furthermore, there was a downregulation in the immunological functions. Besides, THEM6 could effectively distinguish BLCA molecular subtypes, and THEM6 low expression implied basal subtype that was more effective to several interventions, such as immune checkpoint blockade (ICB) therapies, neoadjuvant chemotherapy, and radiotherapy. While THEM6 high expression indicated luminal subtype, hyperprogression and better response to targeted therapies, such as blocking THEM6 and several immune-inhibited oncogenic pathways. Conclusions: THEM6 may be with potential immune-modulating properties and may become a potential new immunotherapy target for BLCA. THEM6 could accurately predict the molecular subtype of BLCA, which was helpful for guiding the treatment. Simultaneously, the prediction model may exhibit an excellent predictive value in patients with BLCA.

Pre-Treatment Computed Tomography Radiomics for Predicting the Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Retrospective Study.

Background and Purpose: Computerized tomography (CT) scans are commonly performed to assist in diagnosis and treatment of locally advanced rectal cancer (LARC). This study assessed the usefulness of pretreatment CT-based radiomics for predicting pathological complete response (pCR) of LARC to neoadjuvant chemoradiotherapy (nCRT). Materials and Methods: Patients with LARC who underwent nCRT followed by total mesorectal excision surgery from July 2010 to December 2018 were enrolled in this retrospective study. A total of 340 radiomic features were extracted from pretreatment contrast-enhanced CT images. The most relevant features to pCR were selected using the least absolute shrinkage and selection operator (LASSO) method and a radiomic signature was generated. Predictive models were built with radiomic features and clinico-pathological variables. Model performance was assessed with decision curve analysis and was validated in an independent cohort. Results: The pCR was achieved in 44 of the 216 consecutive patients (20.4%) in this study. The model with the best performance used both radiomics and clinical variables including radiomic signatures, distance to anal verge, lymphocyte-to-monocyte ratio, and carcinoembryonic antigen. This combined model discriminated between patients with and without pCR with an area under the curve of 0.926 and 0.872 in the training and the validation cohorts, respectively. The combined model also showed better performance than models built with radiomic or clinical variables alone. Conclusion: Our combined predictive model was robust in differentiating patients with and without response to nCRT.

Neoadjuvant immunotherapy, chemotherapy, and combination therapy in muscle-invasive bladder cancer: A multi-center real-world retrospective study.

To parallelly compare the efficacy of neoadjuvant immunotherapy (tislelizumab), neoadjuvant chemotherapy (gemcitabine and cisplatin), and neoadjuvant combination therapy (tislelizumab + GC) in patients with muscle-invasive bladder cancer (MIBC) and explore the efficacy predictors, we perform a multi-center, real-world cohort study that enrolls 253 patients treated with neoadjuvant treatments (combination therapy: 98, chemotherapy: 107, and immunotherapy: 48) from 15 tertiary hospitals. We demonstrate that neoadjuvant combination therapy achieves the highest complete response rate and pathological downstaging rate compared with neoadjuvant immunotherapy or chemotherapy. We develop and validate an efficacy prediction model consisting of pretreatment clinical characteristics, which can pinpoint candidates to receive neoadjuvant combination therapy. We also preliminarily reveal that patients who achieve pathological complete response after neoadjuvant treatments plus maximal transurethral resection of the bladder tumor may be safe to receive bladder preservation therapy. Overall, this study highlights the benefit of neoadjuvant combination therapy based on tislelizumab for MIBC.

Lamin-A interacting protein Hsp90 is required for DNA damage repair and chemoresistance of ovarian cancer cells.

Ovarian cancer is the most malignant gynecologic cancer. Previous studies found that lamin-A was associated with DNA damage repair proteins but the underlying mechanism remains unclear. We speculate that this may be related to its interacting proteins, such as Hsp90. The aim of this study is to investigate the effects of Hsp90 on DNA damage repair and chemoresistance of ovarian cancer cells. In our research, co-immunoprecipitation (co-IP) and mass spectrometry (MS) were used to identify proteins interacting with lamin-A and the interaction domain. Next, the relationship between lamin-A and Hsp90 was explored by Western blotting (WB) and immunofluorescence staining. Then, effect of Hsp90 inhibition on DNA damage repair was assessed through detecting Rad50 and Ku80 by WB. Furthermore, to test the roles of 17-AAG on cell chemosensitivity, CCK-8 and colony formation assay were carried out. Meanwhile, IC50 of cells were calculated, followed by immunofluorescence to detect DNA damage. At last, the mouse xenograft model was used in determining the capacity of 17-AAG and DDP to suppress tumor growth and metastatic potential. The results showed that lamin-A could interact with Hsp90 via the domain of lamin-A1-430. Besides, the distribution of Hsp90 could be affected by lamin-A. After lamin-A knockdown, Hsp90 decreased in the cytoplasm and increased in the nucleus, suggesting that the interaction between lamin-A and Hsp90 may be related to the nucleocytoplasmic transport of Hsp90. Moreover, inhibition of Hsp90 led to an obvious decrease in the expression of DSBs (DNA double-strand break) repair proteins, as well as cell proliferation ability upon DDP treatment and IC50 of DDP, causing more serious DNA damage. In addition, the combination of 17-AAG and DDP restrained the growth of ovarian cancer efficiently in vivo and prolonged the survival time of tumor-bearing mice.

N6-Methyladenosine in Cancer Immunotherapy: An Undervalued Therapeutic Target.

N6-methylation of adenosine (m6A), a post-transcriptional regulatory mechanism, is the most abundant nucleotide modification in almost all types of RNAs. The biological function of m6A in regulating the expression of oncogenes or tumor suppressor genes has been widely investigated in various cancers. However, recent studies have addressed a new role of m6A modification in the anti-tumor immune response. By modulating the fate of targeted RNA, m6A affects tumor-associated immune cell activation and infiltration in the tumor microenvironment (TME). In addition, m6A-targeting is found to affect the efficacy of classical immunotherapy, which makes m6A a potential target for immunotherapy. Although m6A modification together with its regulators may play the exact opposite role in different tumor types, targeting m6A regulators has been shown to have wide implications in several cancers. In this review, we discussed the link between m6A modification and tumor with an emphasis on the importance of m6A in anti-tumor immune response and immunotherapy.

CT-Based Sarcopenic Nomogram for Predicting Progressive Disease in Advanced Non-Small-Cell Lung Cancer.

BACKGROUND: It is prudent to identify the risk for progressive disease (PD) in patients with non-small-cell lung cancer (NSCLC) who undergo platinum-based chemotherapy. The present study aimed to develop a CT imaging-based sarcopenic nomogram for predicting the risk of PD prior to chemotherapy treatment. METHODS: We retrospectively enrolled patients with NSCLC who underwent platinum-based chemotherapy. Imaging-based body composition parameters such as skeletal muscle index (SMI) for assessment of sarcopenia were obtained from pre-chemotherapy chest CT images at the level of the eleventh thoracic vertebral body (T11). Sarcopenic nomogram was constructed using multivariate logistic regression and performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve. RESULTS: Sixty (14.7%) of the 408 patients in the study cohort developed PD during chemotherapy. The prediction nomogram for developing PD achieved a moderate efficiency with an area under the curve (AUC) of 0.75 (95% CI: 0.69-0.80) for the training cohort, and 0.76 (95%CI: 0.68-0.84) for the validation cohort, as well as a good performance of consistence (bootstrap for training cohort: 0.75 ± 0.02; validation cohort: 0.74 ± 0.06). Favorable clinical application was observed in the decision curve analysis. CONCLUSION: Our CT-based sarcopenic nomogram showed the potential for an individualized prediction of progression for patients with NSCLC receiving platinum-based chemotherapy.

Preoperative Magnetic Resonance Imaging Radiomics for Predicting Early Recurrence of Glioblastoma.

PURPOSE: Early recurrence of glioblastoma after standard treatment makes patient care challenging. This study aimed to assess preoperative magnetic resonance imaging (MRI) radiomics for predicting early recurrence of glioblastoma. PATIENTS AND METHODS: A total of 122 patients (training cohort: n = 86; validation cohort: n = 36) with pathologically confirmed glioblastoma were included in this retrospective study. Preoperative brain MRI images were analyzed for both radiomics and the Visually Accessible Rembrandt Image (VASARI) features of glioblastoma. Models incorporating MRI radiomics, the VASARI parameters, and clinical variables were developed and presented in a nomogram. Performance was assessed based on calibration, discrimination, and clinical usefulness. RESULTS: The nomogram consisting of the radiomic signatures, the VASARI parameters, and blood urea nitrogen (BUN) values showed good discrimination between the patients with early recurrence and those with later recurrence, with an area under the curve of 0.85 (95% CI, 0.77-0.94) in the training cohort and 0.84 [95% CI, 0.71-0.97] in the validation cohort. Decision curve analysis demonstrated favorable clinical application of the nomogram. CONCLUSION: This study showed the potential usefulness of preoperative brain MRI radiomics in predicting the early recurrence of glioblastoma, which should be helpful in personalized management of glioblastoma.

Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

Rationale: Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. Methods: We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteristics in the BLCA tumor microenvironment (TME), including immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T cell inflamed score. We also analyzed the role of Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA. Our results were validated in several public cohorts as well as our BLCA tumor microarray cohort, the Xiangya cohort. We developed an immune risk score (IRS), validated it, and tested its ability to predict the prognosis and response to cancer immunotherapy. Results: We found that Siglec15 was specifically overexpressed in the TME of various cancers. We hypothesize that Siglec15 designs a non-inflamed TME in BLCA based on the evidence that Siglec15 negatively correlated with immunomodulators, TIICs, cancer immunity cycles, immune checkpoints, and T cell inflamed score. Bladder cancer with high Siglec15 expression was not sensitive to cancer immunotherapy, but exhibited a higher incidence of hyperprogression. High Siglec15 levels indicated a luminal subtype of BLCA characterized by lower immune infiltration, lower response to cancer immunotherapy and neoadjuvant chemotherapy, but higher response to anti-angiogenic therapy and targeted therapies such as blocking Siglec15, ß-catenin, PPAR-γ, and FGFR3 pathways. Notably, a combination of anti-Siglec15 and cancer immunotherapy may be a more effective strategy than monotherapy. IRS can accurately predict the prognosis and response to cancer immunotherapy. Conclusions: Anti-Siglec15 immunotherapy might be suitable for BLCA treatment as Siglec15 correlates with a non-inflamed TME in BLCA. Siglec15 could also predict the molecular subtype and the response to several treatment options.

Integrated analysis of gene expression and DNA methylation profiles in ovarian cancer.

BACKGROUND: Ovarian cancer is an epithelial malignancy that intrigues people for its poor outcome and lack of efficient treatment, while methylation is an important mechanism that have been recognized in many malignancies. In this study, we attempt to assess abnormally methylated gene markers and pathways in ovarian cancer by integrating three microarray datasets. METHODS: Three datasets including expression (GSE26712 and GSE66957) and methylation (GSE81224) datasets were accessed. GEO2R platform was used to detect abnormally methylated-differentially expressed genes. Protein-protein interaction (PPI) networks were built and analysed for hypermethylated and hypermethylated differentially expressed genes using Cytoscape software and Mcode app. GEPIA and cBioPortal platforms were used to validate the expression of the hub genes and the correlation between their mRNA expressions and methylation levels. Kaplan Meier-plotter platform were used to assess the prognostic significance of the hub genes. RESULTS: Six hundred eighty-one hypomethylated-upregulated genes were detected and involved in Rap1 signaling pathway, biosynthesis of amino acids, endocrine resistance, apoptosis, pathways in cancer. The hub genes were TNF, UBC, SRC, ESR1, CDK1, PECAM1, CXCR4, MUC1, IKBKG. Additionally, 337 hypermethylated-downregulated genes were detected and involved in pathways in cancer, focal adhesion, sphingolipid signaling pathway, EGFR tyrosine kinase inhibitor resistance, cellular senescence. The hub genes were BDNF, CDC42, CD44, PPP2R5C, PTEN, UBB, BMP2, FOXO1, KLHL2. TNF, ESR1, MUC1, CD44, PPP2R5C, PTEN, UBB and FOXO1 showed significant negative correlation between their mRNA expressions and methylation levels. TNF, ESR1 and FOXO1 showed prognostic significance. CONCLUSIONS: Two novel gene networks were found for ovarian cancer. TNF, ESR1, MUC1 and FOXO1 are our candidate genes that might take part in ovarian cancer progression in an epigenetic approach, TNF, ESR1 and FOXO1 may serve as potential markers for ovarian cancer prognosis evaluation.