Platelet-lymphocyte ratio predicts chemotherapy response and prognosis in patients with gastric cancer undergoing radical resection.

Background: Amounting literatures have reported the significance of systemic inflammatory markers for evaluating tumor prognosis. But few studies have systematically compared their superiority and their impact on adjuvant chemotherapy. Aims: We aimed to investigate the ability of inflammatory markers to predict the efficacy of chemotherapy in GC patients undergoing radical therapy and to identify an effective methodology based on the study's findings that would enable clinicians to differentiate between chemotherapy-responsive populations. Methods: We retrospectively enrolled 730 GC patients who underwent radical gastrectomy. Fibrinogen (FIB), platelet-lymphocyte ratio (PLR), systemic inflammation response index (SIRI), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR) and lymph node ratio (LNR) were grouped according to cutoff values. Their clinical significance for GC prognosis was determined by multivariate COX regression analysis in the 730 GC patients and high/low PLR status subgroups. Cases were divided into four groups according to PLR status and adjuvant chemotherapy status and survival was compared among groups. Results: Multivariate analysis showed that PLR was an independent prognostic factor for overall survival (OS) and disease-free survival (DFS) of GC patients. Adjuvant chemotherapy improved survival more significantly in patients with low PLR than that with high PLR. Among patients receiving adjuvant chemotherapy, low PLR was significantly associated with prolonged survival in TNM stage II, but not in TNM stage III. Conclusion: Preoperative high PLR is an independent risk factor for GC patients undergoing radical gastrectomy and adversely affects the postoperative chemotherapy effect.

Glucose metabolism-based signature predicts prognosis and immunotherapy strategies for colon adenocarcinoma.

BACKGROUND: The global prevalence and metastasis rates of colon adenocarcinoma (COAD) are high, and therapeutic success is limited. Although previous research has primarily explored changes in gene phenotypes, the incidence rate of COAD remains unchanged. Metabolic reprogramming is a crucial aspect of cancer research and therapy. The present study aims to develop cluster and polygenic risk prediction models for COAD based on glucose metabolism pathways to assess the survival status of patients and potentially identify novel immunotherapy strategies and related therapeutic targets. METHODS: COAD-specific data (including clinicopathological information and gene expression profiles) were sourced from The Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus (GEO) datasets (GSE33113 and GSE39582). Gene sets related to glucose metabolism were obtained from the MSigDB database. The Gene Set Variation Analysis (GSVA) method was utilized to calculate pathway scores for glucose metabolism. The hclust function in R, part of the Pheatmap package, was used to establish a clustering system. The mutation characteristics of identified clusters were assessed via MOVICS software, and differentially expressed genes (DEGs) were filtered using limma software. Signature analysis was performed using the least absolute shrinkage and selection operator (LASSO) method. Survival curves, survival receiver operating characteristic (ROC) curves and multivariate Cox regression were analyzed to assess the efficacy and accuracy of the signature for prognostic prediction. The pRRophetic program was employed to predict drug sensitivity, with data sourced from the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: Four COAD subgroups (i.e., C1, C2, C3 and C4) were identified based on glucose metabolism, with the C4 group having higher survival rates. These four clusters were bifurcated into a new Clust2 system (C1 + C2 + C3 and C4). In total, 2175 DEGs were obtained (C1 + C2 + C3 vs. C4), from which 139 prognosis-related genes were identified. ROC curves predicting 1-, 3- and 5-year survival based on a signature containing nine genes showed an area under the curve greater than 0.7. Meanwhile, the study also found this feature to be an important predictor of prognosis in COAD and accordingly assessed the risk score, with higher risk scores being associated with a worse prognosis. The high-risk and low-risk groups responded differently to immunotherapy and chemotherapeutic agents, and there were differences in functional enrichment pathways. CONCLUSIONS: This unique signature based on glucose metabolism may potentially provide a basis for predicting patient prognosis, biological characteristics and more effective immunotherapy strategies for COAD.

Prognostic utility of TME-associated genes in pancreatic cancer.

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC. Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy. Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model. Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

Comprehensive nomogram models for predicting checkpoint inhibitor pneumonitis.

Checkpoint inhibitor pneumonitis (CIP) is a common type of immune-related adverse events (irAEs) with poor clinical prognosis. Currently, there is a lack of effective biomarkers and predictive models to predict the occurrence of CIP. This study retrospectively enrolled 547 patients who received immunotherapy. The patients were divided into CIP cohorts of any grade, or grade ≥2 or ≥3. Multivariate logistic regression analysis was used to determine the independent risk factors, based on which we established Nomogram A and B for respectively predicting any grade or grade ≥2 CIP. For Nomogram A to predict any grade CIP, the C indexes in the training and validation cohorts were 0.827 (95% CI=0.772-0.881) and 0.860 (95% CI=0.741-0.918), respectively. Similarly, for Nomogram B to predict grade 2 or higher CIP, the C indexes of the training and validation cohorts were 0.873 (95% CI=0.826-0.921) and 0.904 (95% CI=0.804-0.973), respectively. In conclusion, the predictive power of nomograms A and B has proven satisfactory following internal and external verification. They are promising clinical tools that are convenient, visual, and personalized for assessing the risks of developing CIP.

A prognostic nomogram for predicting recurrence-free survival of stage I-III colon cancer based on immune-infiltrating Treg-related genes.

PURPOSE: A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I-III colon cancer. METHODS: A Treg-related prognostic classifier was built through a variety of bioinformatic methods, whose performance was assessed by KM survival curves, time-dependent receiver operating characteristic (tROC), and Harrell's concordance index (C-index). A prognostic nomogram was generated using this classifier and other traditional clinical parameters. Moreover, the predictive values of this classifier for immunotherapy and chemotherapy therapeutic efficacy were tested using multiple immunotherapy sets and R package "pRRophetic". RESULTS: A nine Treg-related classifier categorized CC patients into high- and low-risk groups with distinct RFS in the multiple datasets (all p < 0.05). The AUC values of 5-year RFS were 0.712, 0.588, 0.669, and 0.662 in the training, 1st, 2nd, and entire validation sets, respectively. Furthermore, this classifier was identified as an independent predictor of RFS. Finally, a nomogram combining this classifier and three clinical variables was generated, the analysis of tROC, C-index, calibration curves, and the comparative analysis with other signatures confirmed its predictive performance. Moreover, KM analysis exhibited an obvious discrepancy in the subgroups, especially in different TNM stages and with adjuvant chemotherapy. We detected the difference between the two risk subsets of immune cell sub-population and the response to immunotherapy and chemotherapy. CONCLUSIONS: We built a robust Treg-related classifier and generated a prognostic nomogram that predicts recurrence-free survival in stage I-III colon cancer that can identify high-risk patients for more personalized and effective therapy.

ncRNAs-mediated overexpression of STIL predict unfavorable prognosis and correlated with the efficacy of immunotherapy of hepatocellular carcinoma.

BACKGROUND: STIL centriolar assembly protein (STIL) is a cytoplasmic protein implicated in cellular growth and proliferation as well as chromosomal stability, which abnormal condition affected tumor immunity and tumor progression. However, the role of STIL in the biological mechanism of hepatocellular carcinoma (HCC) remains unclear. METHODS: Comprehensive bioinformatic approaches, in vitro functional assays, and validation were conducted to elucidate the oncogenic value of STIL in HCC. RESULTS: In the present study, we found that STIL may serve as an independent prognostic indicator and a potential oncogene in HCC. Gene set enrichment analysis (GSEA), and Gene set variation analysis (GSVA) showed that upregulated expression of STIL was positively associated with pathways enriched in the cell cycle and DNA damage response. Subsequently, we identified several non-coding RNAs (ncRNAs) accounting for the upregulation of STIL expression using a combination of in silico bioinformatics approaches (including expression analysis, correlation analysis, and survival analysis). Finally, CCNT2-AS1/SNHG1-has-miR-204-5p-STIL axis was screened out as the most potential upstream ncRNA-related pathway of STIL in HCC. Moreover, STIL expression is highly associated with the infiltration of immune cells, the expression of immune checkpoints, as well as the survival benefit of immunotherapy/chemotherapy. CONCLUSIONS: Our study discloses that ncRNAs-mediated overexpression of STIL independently predicted poor prognosis and correlated with the efficacy of PD-1-targeted immunotherapy in HCC.

A robust CD8+ T cell-related classifier for predicting the prognosis and efficacy of immunotherapy in stage III lung adenocarcinoma.

Patients with stage III lung adenocarcinoma (LUAD) have significant survival heterogeneity, meanwhile, CD8+ T cell has a remarkable function in immunotherapy. Therefore, developing novel biomarkers based on CD8+ T cell can help evaluate the prognosis and guide the strategy of immunotherapy for patients with stage III LUAD. Thus, we abstracted twelve datasets from multiple online databases and grouped the stage III LUAD patients into training and validation sets. We then used WGCNA and CIBERSORT, while univariate Cox analysis, LASSO analysis, and multivariate Cox analysis were performed. Subsequently, a novel CD8+ T cell-related classifier including HDFRP3, ARIH1, SMAD2, and UPB1 was developed, which could divide stage III LUAD patients into high- and low-risk groups with distinct survival probability in multiple cohorts (all P < 0.05). Moreover, a robust nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its powerful predictive capacity. Besides, we detected the difference in immune cell subpopulations and evaluated the potential benefits of immunotherapy between the two risk subsets. Finally, we verified the correlation between the gene expression and CD8+ T cells included in the model by immunohistochemistry and validated the validity of the model in a real-world cohort. Overall, we constructed a robust CD8+ T cell-related risk model originally which could predict the survival rates in stage III LUAD. What's more, this model suggested that patients in the high-risk group could benefit from immunotherapy, which has significant implications for accurately predicting the effect of immunotherapy and evaluating the prognosis for patients with stage III LUAD.

Predicting checkpoint inhibitors pneumonitis in non-small cell lung cancer using a dynamic online hypertension nomogram.

OBJECTIVES: Checkpoint inhibitors pneumonitis (CIP) is one of the most lethal adverse events in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Currently, there is no recognized and effective predictive model to predict CIP in NSCLC. MATERIALS AND METHODS: This study retrospectively analyzed 460 NSCLC patients who were first treated with ICIs. Patients were divided into three cohorts based on the occurrence of CIP: any grade CIP cohort, grade ≥ 2 CIP cohort and grade ≥ 3 CIP cohort. RESULTS: A dynamic hypertension nomogram was constructed with elements including hypertension, interstitial lung disease (ILD), emphysema at baseline, and higher baseline platelet/lymphocyte ratio (PLR). The C indices of the training cohort and the internal and external validation cohort in any grade CIP cohort were 0.872, 0.833 and 0.840, respectively. The constructed hypertension nomogram was applied to grade ≥ 2 cohort and grade ≥ 3 cohort, and their C indices were 0.844 and 0.866, respectively. Compared with the non-hypertension nomogram, the hypertension nomogram presented better predictive power. CONCLUSIONS: After validated by internal and external validation cohorts, the dynamic online hypertension has the potential to become a convenient, intuitive, and personalized clinical tool for assessing the risk of CIP in NSCLC patients.

ASF1B is a Promising Prognostic Biomarker and Correlates With Immunotherapy Efficacy in Hepatocellular Carcinoma.

Background: Anti-silencing function 1B (ASF1B), a histone H3-H4 chaperone, is crucial for S-phase progression and cell proliferation. Recent studies have shown that ASF1B may be used as a new proliferation marker for cancer prognosis. However, the prognostic value and effect of ASF1B on tumor cells and the immune microenvironment in hepatocellular carcinoma (HCC) remain unclear. Methods: We analyzed the expression of ASF1B and its prognostic value using The Cancer Genome Atlas (TCGA) database (as a training set) and other databases, and we validated the findings by immunohistochemistry in our clinical database, containing 141 HCC patients (as a validation set). Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to probe the tumor-associated biological processes of ASF1B in HCC. The interrelationships between ASF1B expression and tumor immunological characteristics were analyzed by multiple databases. The Imvigor210 cohort was retrieved to assess the ability of ASF1B to predict immunotherapy efficacy. Results: ASF1B was highly expressed in tumor tissue compared to paracancerous tissue. High ASF1B expression was associated with worse overall survival (OS) and progression-free survival (PFS) in the training set (p = 0.005, p < 0.001) and validation set (p < 0.001, p < 0.001). Multivariate analysis revealed that ASF1B was an independent prognostic factor associated with OS and PFS. GSEA and GSVA suggested that ASF1B was involved in tumor-associated biological processes, including the cell cycle, DNA replication, base excision repair, mismatch repair, RNA degradation, ubiquitin-mediated proteolysis, and nucleotide excision repair. Further analysis revealed that the levels of ASF1B were positively correlated with the immune cells infiltration of B cells, CD8+ T cells, CD4+ T cells, neutrophils, and dendritic cells. However, ASF1B was positively correlated with Treg cell infiltration and inhibitory immune checkpoints in exhausted T cells. Patients who received anti-PD-L1 immunotherapy with high ASF1B expression had a higher objective response. Conclusion: The ASF1B level is an independent prognostic factor and may serve as a potential immunotherapeutic target.

Characteristics of the immunogenicity and tumor immune microenvironment in HER2-amplified lung adenocarcinoma.

Objective: Besides breast and gastric cancer, HER2 amplification/mutation are also found in lung adenocarcinoma (LUAD). However, the correlation between HER2 variations and the phenotype of immunogenicity and tumor immune microenvironment (TIME) in LUAD compared with breast and gastric cancer has yet to be fully elucidated. Methods: We integrated public databases (discovery set) and internal data (validated set) of 288 patients representing three distinct HER2-altered tumors. Genomic data were used to identify somatic mutations, copy number variations, and calculate tumor mutational burden (TMB) and microsatellite instability score. RNA sequencing was conducted to estimate immune gene signatures and contents of tumor-infiltrating immune cell populations. Finally, IHC was used to determine PD-L1 expression and the tumoral-infiltration of immune cells in 50 HER2-variant tumor specimens with no prior therapeutic regimens. Results: Compared with HER2-amplified breast and gastric cancers, patients with HER2-amplified LUAD showed higher immunogenicity, mainly manifested in immune checkpoints expression and tissue/blood TMB. Additionally, HER2-amplified LUAD exhibited an inflamed TIME with remarkably increased genes encoding HLAs, T-cell activity and immune cell-type, and accompanied with tumor-infiltrating lymphocytes. In LUAD, patients with HER2 amplification possessed higher tissue TMB than HER2 mutation, whereas no difference was observed in PD-L1 expression. HER2 amplification (primary) was associated with significantly higher PD-L1 expression and TMB than acquired HER2 amplification after resistance to EGFR-TKIs. Conclusion: Patients with HER2-amplified LUAD have better immunogenicity and/or an inflamed TIME among HER2-aberrant tumors. Our study may provide clues for establishing the benefits and uses of ICIs for patients with this disease.

A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma.

Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses' survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG.

MUC4 isoforms expression profiling and prognosis value in Chinese melanoma patients.

Mucin 4 (MUC4), a type I membrane-bound mucin, blocks apoptosis, promotes invasion, proliferation and migration and causes chemo-resistance in epithelial cancers. However, the expression profiling and clinical implications of MUC4 alternative splicing during cancer pathogenesis, including melanoma, remain obscure. We examined the mRNA expression profiling of MUC4 isoforms in gastrointestinal cancer cell lines, melanoma cell lines, human epidermal melanocyte cells, as well as 138 cases of human melanoma tissues by RT-qPCR. Then we analyzed the relationship of mRNA expression of MUC4 isoforms to clinicopathological characteristics and survival of patients. The dynamic mRNA expression profiling of MUC4 isoforms was found in melanoma. We identified MUC4 isoform f was highly expressed in melanoma cell lines but negative in gastrointestinal cancer cell lines. Clinical analysis based on 138 cases of human melanomas showed that MUC4 isoform d was related with melanoma subtypes (p = 0.028) and TNM stage (p = 0.036). MUC4 isoform e was related with tumor thickness (p = 0.004) and T stage (p = 0.036). The Kaplan-Meier assay showed that the median overall survival (OS) for patients with MUC4 isoform f high expression was significantly shorter than that of patients with low expression (p = 0.024). And the median PFS of the patients with high expression of MUC4 isoform d or e was significantly shorter than that of with low expression (p = 0.012 and 0.035, respectively). Multivariate analysis indicated that high level of MUC4 isoform f was an independent prognostic factor for OS, and MUC4 isoform d was an independent prognostic factor for PFS of patients treated with chemotherapy. In conclusion, our results indicate that the dynamic MUC4 isoforms expressed in melanoma, and MUC4 isoform d and f might be served as a novel prognostic indicator of melanoma patients.

Correction to: Frequent genetic aberrations in the cell cycle related genes in mucosal melanoma indicate the potential for targeted therapy.

Following publication of the original article [1], the authors reported errors in Figures 2, 3 and Figure 3 'continued'.

Frequent genetic aberrations in the cell cycle related genes in mucosal melanoma indicate the potential for targeted therapy.

BACKGROUND: Melanoma is one of the most aggressive cancers with extremely poor prognosis, and the median survival time for stage IV patients is approximately 6 to 8 months. Unlike cutaneous melanoma, mucosal melanoma is a rare melanoma subtype among Caucasian patients but its incidence remains as high as 22.6% among Chinese patients. Screening specific genetic variations is the guideline to select targeted drugs for the treatment of advanced melanoma, whereas the genetic variation spectrum and potential therapeutic targets for mucosal melanoma are largely unclear. It is urgent to identify promising genetic variants for mucosal melanoma so as to develop effective targeted therapies for this disease. METHODS: Tumor samples from 213 Chinese mucosal melanoma patients were involved in this study. P16INK4a/Cyclin D1/CDK4 copy number was examined using the QuantiGene Plex DNA assay and the correlation between abnormal copy number and clinicopathological parameters was analyzed. Patient-derived xenograft models (PDX) were performed to detect the effects of CDK4/6 inhibitors on the proliferation of mucosal melanoma cells with altered copy number of CDK4 pathway (CDK4, Cyclin D1 and P16INK4a). The molecular mechanisms of CDK4/6 inhibitors on the proliferation of mucosal melanoma were analyzed by RNAseq. RESULTS: Among the 213 samples, the amplification rate of CDK4 and CCND1 was 47.0% and 27.7%, respectively, and the deletion rate of P16INK4a was 57.7%. Patients with more than one genetic abnormality were up to 81.7%. CDK4 pathway gene copy number variation was not associated with the prognosis of patients with mucosal melanoma (P > 0.05). Drug sensitivity tests showed that AT7519, a broad-spectrum CDK inhibitor, and PD0332991, a specific CDK4/6 inhibitor, exhibited higher inhibitory effect on CDK4 signaling pathway abnormal mucosal melanoma cells-derived PDX tumors growth than CDK4 signaling pathway normal ones. RNA-seq analysis showed that CDK4 inhibitors may affect tumor proliferation through multiple signaling pathways. CONCLUSIONS: Abnormal copy number of cell cycle related genes is frequently found in mucosal melanoma. CDK4/6 inhibitors significantly suppress the PDX tumor growth with abnormal CDK4 pathway. CDK4 signaling variations predict the effectiveness of CDK4 inhibitors in mucosal melanoma.

Clinical analysis of bone metastasis of gastric cancer: incidence, clinicopathological features and survival.

Aim: We evaluated the incidence, clinicopathological features, prognostic factors and survival of gastric cancer (GC) with bone metastasis in a single large cancer center in China. Patients & methods: Patients with bone metastasis of GC were retrospectively analyzed. Overall survival was estimated using the Kaplan-Meier method. Clinicopathological factors, which were associated with prognostic factors for survival, were evaluated. Results: The incidence of bone metastasis was 11.3% for metastatic GC patients. Median overall survival time was 6.5 months. Multivariate analysis revealed two independent poor prognostic factors: Eastern Cooperative Oncology Group ≥2 (p = 0.023) and lack of palliative chemotherapy (p = 0.018). Conclusion: The incidence of bone metastasis from metastatic GC was underestimated. The prognosis of GC with bone metastasis was poor.

miR-let-7b and miR-let-7c suppress tumourigenesis of human mucosal melanoma and enhance the sensitivity to chemotherapy.

BACKGROUND: Mucosal melanoma with poor prognosis is a common histopathologic subtype of melanoma among Chinese and other Asian peoples. Regulated microRNAs (miRNAs) have been reported as oncogenes or tumour suppressors in melanoma. However, the roles of specific miRNAs in mucosal melanoma remain largely unknown. Here, we aimed to assess the biological functions, molecular mechanisms and clinical potential of miR-let-7b and miR-let-7c in mucosal melanoma. METHODS: The expression of miR-let-7b and miR-let-7c in mucosal melanoma was determined by quantitative polymerase chain reaction (qPCR). Cutoff scores for miR-let-7b and miR-let-7c expressions were calculated through receiver operating characteristic (ROC) curve analysis in 106 mucosal melanoma patients according to recurrence. Correlations of miR-let-7b and miR-let-7c expression with clinicopathological characteristics, disease-free survival (DFS) and clinical benefits after treatment were then statistically analysed. The biological functions and molecular mechanisms of miR-let-7b and miR-let-7c were studied in vitro and in vivo. RESULTS: The expression of miR-let-7b and miR-let-7c was decreased in 94 cases (88.7%) and 89 cases (84.0%) of 106 mucosal melanoma patients compared with mucosal nevi. A correlation was observed between the expression of miR-let-7b, miR-let-7c and DFS after surgery. In addition, overexpression of miR-let-7b or miR-let-7c inhibited mucosal melanoma cell growth, migration, invasion and metastasis and induced cell apoptosis and cell cycle arrest in vitro and in vivo. Mechanistically, miR-let-7b and miR-let-7c directly targeted metadherin (MTDH) and calumenin (CALU) and suppressed phospho-ERK in mucosal melanoma cells. MTDH and CALU reversed the partial function of miR-let-7b and miR-let-7c in vitro. Furthermore, progression-free survival (PFS) of mucosal melanoma patients upon temozolomide-based and paclitaxel-based chemotherapy was related to miR-let-7b and miR-let-7c expression. Overexpression of miR-let-7b or miR-let-7c in patient-derived xenograft (PDX) models and certain mucosal melanoma cells had better growth inhibition after temozolomide and paclitaxel treatment. MTDH reversed the sensitivity of miR-let-7b and miR-let-7c to paclitaxel in vitro. CONCLUSIONS: Our results suggested that miR-let-7b and miR-let-7c inhibited the recurrence of mucosal melanoma through inhibiting cell growth, migration, invasion and metastasis, inducing cell apoptosis and cell cycle arrest by targeting MTDH and CALU. In addition, miR-let-7b and miR-let-7c increased sensitivity to chemotherapeutic agents by targeting MTDH.

Potential Mutations in Uveal Melanoma Identified Using Targeted Next-Generation Sequencing.

Background/objective: Uveal melanoma (UM) is the most common intraocular malignancy and has a high tendency to metastasize to the liver. Although primary tumours can be successfully treated, there is currently no effective treatment for metastatic UM. To gain insight into the genetics of UM, we performed the targeted next-generation sequencing (NGS) of UM samples from a non-Caucasian population. Methods: This study included tumour samples and blood samples from 107 UM patients at Peking University Cancer Hospital & Institute. Clinical data were collected. DNA was extracted from formalin-fixed, paraffin-embedded (FFPE) specimens. Using the HaloPlex Target Enrichment System (Agilent Technologies), NGS was performed to investigate mutations in a 35-gene panel composed of cancer-related genes. Results: Recurrent coding mutations were found in the known UM drivers GNAQ and GNA11. FOXO1, PIK3R1 and HIF1A were also found to harbour somatic mutations in more than 20% of patients, a result that may indicate previously undescribed associations between these genes and UM pathogenesis. Patients with HIF1A and FOXO1 mutations exhibited worse overall survival (OS). In multivariate analysis, FOXO1 mutation was an independent prognostic factor for OS (P<0.05) that was associated with an increase in the risk ratio by a factor of 1.35. Notably, we found that HIF1A and FOXO1 mutations were associated with metastatic transformation of UM (P<0.05 and P<0.001, respectively). Conclusion: Our findings from analyses of targeted NGS data shed new light on the molecular genetics of UM and facilitate the exploration of mutations associated with metastatic potential.

Prognostic role of NRAS isoforms in Chinese melanoma patients.

Neuroblastoma rat-sarcoma viral oncogene homolog (NRAS) isoforms are expressed in melanoma tumor tissues, which have been described in Caucasian melanoma. However, the status and the clinical significance of NRAS isoforms in the Asian population have not been investigated on a large scale. We examined the expression levels of NRAS isoforms of 140 melanoma samples using quantitative real-time PCR. Furthermore, the relationship of mRNA expression of NRAS isoforms to clinicopathological characteristics and survival of patients was analyzed. Statistical analysis showed that NRAS isoform 2 expression was correlated with melanoma subtypes (P=0.007), and NRAS isoform 4 expression was correlated with tumor thickness (P=0.031) and clinical stage (P=0.006). The median overall survival for patients with high expression of NRAS isoform 3 was significantly shorter than that for patients with low expression of NRAS isoform 3 (P=0.007). In addition, high expression of NRAS isoform 5 was associated with a worse prognosis (P=0.049 and 0.002 for overall survival and disease-free survival, respectively). Multivariate Cox regression analysis showed that high expression levels of NRAS isoform 3 and isoform 5 were independent poor prognostic factors for patients. Our results indicated that the mRNA expressions of NRAS isoform 3 and isoform 5 may be novel indicators of the prognosis of Chinese melanoma patients.

Establishment and characterization of melanoma patient-derived xenograft models for preclinical evaluation of novel therapeutics.

Patient-derived xenograft (PDX) models mostly retain the histological and genetic features of their donor tumors, which have been used for investigating various types of cancer. However, PDX models for melanoma, especially acral melanoma, are reported occasionally. We aimed to establish a large panel of melanoma PDX models representing the predominant Asian melanomas. Ninety-three fresh melanoma samples were implanted subcutaneously into nonobese diabetic/severe combined immunodeficiency mice. The histological and genetic characteristics were analyzed in both patient tumors and PDX models using immunohistochemistry, PCR amplification, and Sanger sequencing. Furthermore, the sensitivities of PDX models harboring distinct mutation profiles to binimetinib (a MEK inhibitor), vemubrafenib (a BRAF inhibitor), and imatinib (a KIT inhibitor) were also evaluated. Twenty-five PDX models were established successfully [25/93 (26.9%)] and passaged to maintain tumors in vivo. Clinical stage and origin of tumor sample were correlated with successful establishment rates (P=0.008 and <0.001, respectively). The histological (expression of NRAS, P16, and RB) and genetic (mutation status of NRAS, BRAF, and KIT) characteristics were stably maintained from patient tumors to PDX models. Targeted drugs could inhibit the tumor growth of PDX models harboring the corresponding target gene mutations. These PDX models constitute a pharmacological platform, enabling personalized development of therapeutic strategies for Asian melanomas.