Background Chondrosarcoma (CS) most commonly involves the pelvis. This study aimed to analyze differences in clinical characteristics and prognostic factors between primary and secondary conventional pelvic CS, and provide reference for clinical diagnosis and treatment. Methods Eighty patients (54 primary cases and 26 secondary cases) with pelvic CS were included in this retrospective study. The tumor site, Enneking stage, soft tissue mass, margin, initial tumor grade, incidence of local recurrence and distant metastasis were evaluated. Kaplan-Meier method was used to calculate the overall survival rate. X-2 test and log-rank test were used for univariate analysis, and Cox test was used in multivariate analysis. Results The average age of patients with secondary CS was significantly younger than that of patients with primary CS (P < 0.001). The soft tissue mass of patients with secondary CS was significantly larger than that of patients with primary CS (P = 0.002). There was a significant difference in initial tumor pathologic grade between the two groups (P = 0.002). No statistically significant difference was observed in the local recurrence rate between the two groups. The median recurrence time of patients with primary CS after the first treatment was significantly shorter than that of patients with secondary CS (P < 0.001). The overall survival rate of patients with secondary CS was much higher than that of patients with primary CS (P = 0.003). Cox regression analysis showed that the initial tumor grade was an independent factor in the overall survival rate of patients with CS. Conclusion There were significant differences in age, soft tissue mass, initial tumor grade, and overall survival rate between the two groups. The overall survival rate of pelvic CS was related to the initial tumor grade of CS.
Zoledronic acid (ZA) is one of the most important and effective class of anti-resorptive drug available among bisphosphonate (BP), which could effectively reduce the risk of skeletal-related events, and lead to a treatment paradigm for patients with skeletal involvement from advanced cancers. However, the exact molecular mechanisms of its anticancer effects have only recently been identified. In this review, we elaborate the detail mechanisms of ZA through inhibiting osteoclasts and cancer cells, which include the inhibition of differentiation of osteoclasts via suppressing receptor activator of nuclear factor kappa B ligand (RANKL)/receptor activator of nuclear factor kappa B (RANK) pathway, non-canonical Wnt/Ca2+/calmodulin dependent protein kinase II (CaMKII) pathway, and preventing of macrophage differentiation into osteoclasts, in addition, induction of apoptosis of osteoclasts through inhibiting farnesyl pyrophosphate synthase (FPPS)-mediated mevalonate pathway, and activation of reactive oxygen species (ROS)-induced pathway. Furthermore, ZA also inhibits cancer cells proliferation, viability, motility, invasion and angiogenesis; induces cancer cell apoptosis; reverts chemoresistance and stimulates immune response; and acts in synergy with other anti-cancer drugs. In addition, some new ways for delivering ZA against cancer is introduced. We hope this review will provide more information in support of future studies of ZA in the treatment of cancers and bone cancer metastasis.
BackgroundThe aim of this study was to develop and validate a visual nomogram for predicting the risk of bone metastasis (BM) in newly diagnosed thyroid carcinoma (TC) patients.MethodsThe demographics and clinicopathologic variables of TC patients from 2010 to 2015 in the Surveillance, Epidemiology and End Results (SEER) database were retrospectively reviewed. Chi-squared (chi 2) test and logistic regression analysis were performed to identify independent risk factors. Based on that, a predictive nomogram was developed and validated for predicting the risk of BM in TC patients. The C-index was used to compute the predictive performance of the nomogram. Calibration curves and decision curve analysis (DCA) were furthermore used to evaluate the clinical value of the nomogram.ResultsAccording to the inclusion and exclusion criteria, the data of 14,772 patients were used to analyze in our study. After statistical analysis, TC patients with older age, higher T stage, higher N stage, poorly differentiated, follicular thyroid carcinoma (FTC) and black people had a higher risk of BM. We further developed a nomogram with a C-index of 0.925 (95%CI,0.895-0.948) in the training set and 0.842 (95%CI,0.777-0.907) in the validation set. The calibration curves and decision curve analysis (DCA) also demonstrated the reliability and accuracy of the clinical prediction model.ConclusionsThe present study developed a visual nomogram to accurately identify TC patients with high risk of BM, which might help to further provide more individualized clinical decision guidelines.
BackgroundHeterogeneity of metastatic renal cell carcinoma (RCC) constraints accurate prognosis prediction of the tumor. We therefore aimed at developing a novel nomogram for accurate prediction of overall survival (OS) of patients with metastatic RCC.MethodsWe extracted 2010 to 2016 data for metastatic RCC patients in the Surveillance, Epidemiology, and End Results (SEER) database, and randomly stratified them equally into training and validation sets. Prognostic factors for OS were analyzed using Cox regression models, and thereafter integrated into a 1, 3 and 5-year OS predictive nomogram. The nomogram was validated using the training and validation sets. The performance of this model was evaluated by the Harrell's concordance index (C-index), calibration curve, integrated discrimination improvement (IDI), category-free net reclassification improvement (NRI), index of prediction accuracy (IPA), and decision curve analysis (DCA).ResultsOverall, 2315 metastatic RCC patients in the SEER database who fulfilled our inclusion criteria were utilized in constructing a nomogram for predicting OS of newly diagnosed metastatic RCC patients. The nomogram incorporated eight clinical factors: Fuhrman grade, lymph node status, sarcomatoid feature, cancer-directed surgery and bone, brain, liver, and lung metastases, all significantly associated with OS. The model was superior to the American Joint Committee on Cancer (AJCC) staging system (7th edition) both in training (C-indices, 0.701 vs. 0.612, P<0.001) and validation sets (C-indices, 0.676 vs. 0.600, P<0.001). The calibration plots of the nomogram corresponded well between predicted and observed values. NRI, IDI, and IPA further validated the superior predictive capability of the nomogram relative to the AJCC staging system. The DCA plots revealed reliable clinical application of our model in prognosis prediction of metastatic RCC patients.ConclusionsWe developed and validated an accurate nomogram for individual OS prediction of metastatic RCC patients. This nomogram can be applied in design of clinical trials, patient counseling, and rationalizing therapeutic modalities.
BackgroundExtensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.MethodsIn this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.ResultsOur analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4.ConclusionWe conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.
BackgroundImmunomodulatory activities of human mesenchymal stromal /stem cells (hMSCs) has been widely recognized as the most critical function of hMSCs for exerting its therapeutic effects. However, the detailed mechanisms responsible for regulating the immunomodulation of hMSCs still remain largely unknown. Previous studies revealed that the Notch1 protein exerted a pro-immunomodulatory function probably through interacting with the protein(s) subjective to proteasome-mediated protein degradation. The DLC-1 protein represents a well characterized tumor suppressor subjective to proteasome-mediated degradation. However, the detailed signaling pathway of Notch1 and the involvement of DLC-1 in regulating the immunomodulation of hMSCs have not been studied before.MethodsThe transfection with cDNA or siRNA into hMSCs assisted by co-culture of hMSCs with peripheral blood mononuclear cells and small molecule inhibitors of signaling proteins, followed by immunoprecipitation, Western blotting, RT-PCR, and flowcytometry, were employed to characterize the Notch1 signaling, to identify DLC-1 as a candidate proteasome-targeted protein, and to characterize DLC-1 signaling pathway and its interaction with the Notch1 signaling, in the regulation of immunomodulation of hMSCs, specifically, the inhibition of pro-inflammatory CD4(+)-Th1 lymphocytes, and the release of immunomodulatory molecule IDO1.Statistical analysisOne-way ANOVA was utilized as a statistical tool to analyze the data presented as means SEM of at least three separate experiments.ResultsThe present study revealed that the Notch1-Hey1 axis, but not the Notch1-Hes1 axis, was likely responsible for mediating the pro-immunomodulatory function of the Notch1 signaling. The DLC-1 protein was found subjective to proteasome-mediated protein degradation mediated by the DDB1 and FBXW5 E3 ligases and served as an inhibitor of the immunomodulation of hMSCs through inhibiting Rock1, but not Rock2, downstream the DLC-1 signaling. The Notch1 signaling in the Notch1-Hey1 pathway and the DLC-1 signaling in the DLC-1-Rock1-FBXW5 pathway exhibited a mutual exclusion interaction in the regulation of immunomodulation of hMSCs.Conclusions The present study uncovers a novel function of DLC-1 tumor suppressor in regulating the immunomodulation of hMSCs. It also proposes a novel mutual exclusion mechanism between the DLC-1 signaling and the Notch1 signaling that is possibly responsible for fine-tuning the immunomodulation of hMSCs with different clinical implications in hMSCs therapy.
Background Estimating the risk of lymph node metastasis (LNM) is crucial for determining subsequent treatments following curative resection of early colorectal cancer (ECC). This multicenter study analyzed the risk factors of LNM and the effectiveness of postoperative chemotherapy in patients with ECC. Methods We retrospectively analyzed the data of 473 patients with ECC who underwent general surgery in five hospitals between January 2007 and October 2018. The correlations between LNM and sex, age, tumor size, tumor location, endoscopic morphology, pathology, depth of invasion and tumor budding (TB) were directly estimated based on postoperative pathological analysis. We also observed the overall survival (OS) and recurrence in ECC patients with and without LNM after matching according to baseline measures. Results In total, 473 ECC patients were observed, 288 patients were enrolled, and 17 patients had LNM (5.90%). The univariate analysis revealed that tumor size, pathology, and lymphovascular invasion were associated with LNM in ECC (P = 0.026, 0.000, and 0.000, respectively), and the multivariate logistic regression confirmed that tumor size, pathology, and lymphovascular invasion were risk factors for LNM (P = 0.021, 0.023, and 0.001, respectively). There were no significant differences in OS and recurrence between the ECC patients with and without LNM after matching based on baseline measures (P = 0.158 and 0.346, respectively), and no significant difference was observed between chemotherapy and no chemotherapy in ECC patients without LNM after surgery (P = 0.729 and 0.052). Conclusion Tumor size, pathology, and lymphovascular invasion are risk factors for predicting LNM in ECC patients. Adjuvant chemotherapy could improve OS and recurrence in patients with LNM but not always in ECC patients without LNM.
BackgroundThe nuclear transport system has been proposed to be indispensable for cell proliferation and invasion in cancers. Prognostic biomarkers and molecular targets in nuclear transport systems have been developed. However, no systematic analysis of genes related to nuclear transport in gliomas has been performed. An integrated prognostic classification involving mutation and nuclear transport gene signatures has not yet been explored.MethodsIn the present study, we analyzed gliomas from a training cohort (TCGA dataset, n=660) and validation cohort (CGGA dataset, n=668) to develop a prognostic nuclear transport gene signature and generate an integrated classification system. Gene set enrichment analysis (GSEA) showed that glioblastoma (GBM) was mainly enriched in nuclear transport progress compared to lower-grade glioma (LGG). Then, we developed a nuclear transport risk score (NTRS) for gliomas with a training cohort. NTRS was significantly correlated with clinical and genetic characteristics, including grade, age, histology, IDH status and 1p/19q codeletion, in the training and validation cohorts.ResultsSurvival analysis revealed that patients with a higher NTRS exhibited shorter overall survival. NTRS showed better prognostic value compared to classical molecular markers, including IDH status and 1p/19q codeletion. Furthermore, univariate and multivariate analyses indicated that NTRS was an independent prognostic factor for gliomas. Enrichment map and Gene Ontology analysis demonstrated that signaling pathways related to the cell cycle were enriched in the NTRSHigh group. Subgroup survival analysis revealed that NTRS could differentiate the outcomes of low- and high-risk patients with wild-type IDH or mutant IDH and 1p/19q non-codeletion.ConclusionsNTRS is associated with poor outcomes and could be an independent prognostic marker in diffuse gliomas. Prognostic classification combined with IDH mutation, 1p/19q codeletion and NTRS could better predict the survival of glioma patients.
BackgroundThe clinicopathological classification of breast cancer is proposed according to therapeutic purposes. It is simplified and can be conducted easily in clinical practice, and this subtyping undoubtedly contributes to the treatment selection of breast cancer. This study aims to investigate the feasibility of using a Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI for predicting the clinicopathological subtypes of breast cancer.MethodsPatients who underwent breast magnetic resonance imaging were confirmed by retrieving data from our institutional picture archiving and communication system (PACS) between March 2013 and September 2017. Five clinicopathological subtypes were determined based on the status of ER, PR, HER2 and Ki-67 from the immunohistochemical test. The radiomic features of diffusion-weighted imaging were derived from the volume of interest (VOI) of each tumour. Fisher discriminant analysis was performed for clinicopathological subtyping by using a backward selection method. To evaluate the diagnostic performance of the radiomic features, ROC analyses were performed to differentiate between immunohistochemical biomarker-positive and -negative groups.ResultsA total of 84 radiomic features of four statistical methods were included after preprocessing. The overall accuracy for predicting the clinicopathological subtypes was 96.4% by Fisher discriminant analysis, and the weighted accuracy was 96.6%. For predicting diverse clinicopathological subtypes, the prediction accuracies ranged from 92 to 100%. According to the cross-validation, the overall accuracy of the model was 82.1%, and the accuracies of the model for predicting the luminal A, luminal BHER2-, luminal BHER2+, HER2 positive and triple negative subtypes were 79, 77, 88, 92 and 73%, respectively. According to the ROC analysis, the radiomic features had excellent performance in differentiating between different statuses of ER, PR, HER2 and Ki-67.ConclusionsThe Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI is a reliable method for the prediction of clinicopathological breast cancer subtypes.
BackgroundColon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD.MethodsThe gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis.ResultsAmong 1647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P<0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group.ConclusionWe successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.
BackgroundA secondary malignancy is the most serious complication in lung cancer (LC) survivors. This study aimed to evaluate the clinicopathological features, predictable risk factors and survival of patients with LC who developed therapy-related acute myeloid leukaemia (t-AML).MethodsPatients from the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with t-AML after LC between 1975 and 2015 were included. Standardized incidence ratios (SIRs) were used to perform multiple primary analyses. The risk of t-AML development among LC patients was assessed using a logistic regression model. Kaplan-Meier analysis was used to construct overall survival (OS) curves. Cox regression was used to assess the influence of various prognostic factors.ResultsA total of 104 patients with t-AML after LC-targeting chemotherapy were included. The median latency period to the development of t-AML was 35.5months. The calculated SIR of t-AML was 4.00. Chemoradiotherapy, small cell lung cancer (SCLC), or localized/regional-stage LC was a risk factor for the development of t-AML. The median OS was only 1month, and those younger than 65years were predicted to have a better OS time.Conclusionst-AML is a rare but serious late complication in LC patients and is associated with a poor prognosis. It is necessary to carry out long-term follow-up and screen for t-AML in LC patients, especially among those undergoing both radiotherapy and chemotherapy, with SCLC or with localized/regional-stage LC.
BackgroundThis study is designed to investigate the clinical value of systemic chemotherapy combined with bronchoscopic interventional cryotherapy in the treatment of lung cancer.MethodsA total of 412 lung cancer patients admitted to Cangzhou People's Hospital from March 2018 to March 2020 were collected and divided into test group and control group based on their treatment schedules. The test group received systemic chemotherapy combined with bronchoscopic interventional cryotherapy, while the control group received systemic chemotherapy alone. Tumor objective response rate (ORR), disease control rate (DCR), serum tumor marker levels, serum matrix metalloproteinase (MMP) content, T cell subset level, survival time and adverse reactions of the two groups were observed.ResultsThe ORR and DCR of the test group were better than those of the control group, while those of the non-small cell lung cancer (NSCLC) patients in the test group were better than patients with small-cell lung cancer (SCLC) (P< 0.05). There was no significant difference in serum tumor marker levels, MMP content and T cell subset level between the two groups before treatment. After treatment, the serum tumor marker levels along with serum MMP-2, MMP-9 and CD8(+) levels in the test group decreased more remarkably, while CD4(+) and CD4(+)/CD8(+) levels increased more significantly than those in the control group (P< 0.05). The serum MMP-2 and MMP-9 of NSCLC patients in the test group decreased more remarkably than those of SCLC patients, while there was no significant difference in CD8(+), CD4(+) and CD4(+)/CD8(+). The progression-free survival and overall survival of the test group were obviously longer than those of the control group. The same trend was observed in NSCLC patients compared with SCLC patients in the test group (P< 0.05).ConclusionsSystemic chemotherapy combined with bronchoscopic interventional cryotherapy for lung cancer has good clinical efficacy and safety, and can be widely used in clinical practice.
BackgroundHypopharyngeal squamous cell carcinoma (HSCC) is a rare type of head and neck cancer with poor prognosis. However, till now, there is still no model predicting the survival outcomes for HSCC patients. We aim to develop a novel nomogram predicting the long-term cancer-specific survival (CSS) for patients with HSCC and establish a prognostic classification system.MethodsData of 2021 eligible HSCC patients were retrieved from the Surveillance, Epidemiology and End Results database between 2010 and 2015. We randomly split the whole cases (ratio: 7:3) into the training and the validation cohort. Cox regression as well as the Least absolute shrinkage and selection operator (LASSO) COX were used to select significant predictors of CSS. Based on the beta-value of these predictors, a novel nomogram was built. The concordance index (C-index), the calibration curve and the decision curve analysis (DCA) were utilized for the model validation and evaluation using the validation cohort.ResultsIn total, cancer-specific death occurred in 974/2021 (48.2%) patients. LASSO COX indicated that age, race, T stage, N stage, M stage, surgery, radiotherapy and chemotherapy are significant prognosticators of CSS. A prognostic model based on these factors was constructed and visually presented as nomogram. The C-index of the model was 0.764, indicating great predictive accuracy. Additionally, DCA and calibration curves also demonstrated that the nomogram had good clinical effect and satisfactory consistency between the predictive CSS and actual observation. Furthermore, we developed a prognostic classification system that divides HSCC patients into three groups with different prognosis. The median CSS for HSCC patients in the favorable, intermediate and poor prognosis group was not reached, 39.0-Mo and 10.0-Mo, respectively (p<0.001).ConclusionsIn this study, we constructed the first nomogram as well as a relevant prognostic classification system that predicts CSS for HSCC patients. We believe these tools would be helpful for clinical practice in patients' consultation and risk group stratification.
BackgroundFollow-up after curative surgery is increasingly recognized as an important component of breast cancer care. Although current guideline regulates the follow-ups, there are no relevant studies on the adherence to it in China. This study investigated the post-surgery follow-up and explored its association with patients, tumor and treatment characteristics.MethodsA total of 711 patients underwent surgical treatment in Shanxi Bethune Hospital from March 2012 to May 2018 were included in this study. Baseline sociodemographic, tumor, and treatment characteristics were obtained from the hospital electronic medical records. The post-surgery follow-up was reviewed and assessed from the patient's follow-up examination record. Factors associated with the first three-year follow up was evaluated using logistic regression analysis.ResultsThe annual follow-up rate after surgery decreased gradually from 67.1% at the 1st year, 60.2% at the 3rd year to 51.9% at the 4th year, and 43.5% at the 5th year. Loss of follow-up during the first 3 years after surgery was significantly associated with older age (>65years), lower medical insurance coverage, axillary lymph node dissection, and less intensity of systemic treatment.ConclusionA significant downtrend of annual follow-up rate for breast cancer survivors was confirmed in this study. Loss of follow-up within the first 3years after surgery was associated with both patient's characteristics and treatment. These results will provide evidence to help clinicians to develop tailored patient management after curative surgery.
BackgroundIdentifying the mutation status of KRAS is important for optimizing treatment in patients with colorectal cancer (CRC). The aim of this study was to investigate the predictive value of haematological parameters and serum tumour markers (STMs) for KRAS gene mutations.MethodsThe clinical data of patients with colorectal cancer from January 2014 to December 2018 were retrospectively collected, and the associations between KRAS mutations and other indicators were analysed. Receiver operating characteristic (ROC) curve analysis was performed to quantify the predictive value of these factors. Univariate and multivariate logistic regression models were applied to identify predictors of KRAS mutations by calculating the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs).ResultsKRAS mutations were identified in 276 patients (35.2%). ROC analysis revealed that age, CA12-5, AFP, SCC, CA72-4, CA15-3, FERR, CYFRA21-1, MCHC, and tumor location could not predict KRAS mutations (P=0.154, 0.177, 0.277, 0.350, 0.864, 0.941, 0.066, 0.279, 0.293, and 0.053 respectively), although CEA, CA19-9, NSE and haematological parameter values showed significant predictive value (P=0.001, <0.001, 0.043 and P=0.003, <0.001, 0.001, 0.031, 0.030, 0.016, 0.015, 0.019, and 0.006, respectively) but without large areas under the curve. Multivariate logistic regression analysis showed that CA19-9 was significantly associated with KRAS mutations and was the only independent predictor of KRAS positivity (P=0.016).ConclusionsHaematological parameters and STMs were related to KRAS mutation status, and CA19-9 was an independent predictive factor for KRAS gene mutations. The combination of these clinical factors can improve the ability to identify KRAS mutations in CRC patients.