Molecular profiling and prognostic analysis in Chinese cholangiocarcinoma: an observational, retrospective single-center study.

Cholangiocarcinoma (CCA) is a primary malignancy which is often diagnosed when it is advanced and inoperable due to the lack of effective biomarkers and poor sensitivity of clinical diagnosis. Molecular profiling may provide information for improved clinical management, particularly targeted therapy. The study aimed to improve the understanding of molecular characteristics and its association with prognosis in Chinese CCA. We enrolled 41 Chinese patients with CCA, including 6 intrahepatic CCA (iCCA), 14 perihilar CCA (pCCA), and 21 distal CCA (dCCA) cases, all patients underwent radical operations and tumor samples underwent next-generation sequencing (NGS) by Foundation One Dx, which analyzed 324 genes. The patients' genetic characteristics, clinical management, and prognosis were analyzed. The most mutated genes were TP53 (68%, 28/41), CDKN2A (37%, 15/41), and SMAD4 (29%, 12/41). The genetic mutations in dCCA, pCCA, and iCCA were significantly different. For example, NOTCH3 mutations were not found in dCCA. The gene mutations of AXL were specifically associated with lymph node metastasis in patients with CCA, whereas gene mutations of SMAD4 were specifically associated with lymphovascular invasion. Furthermore, mutations in APC, DAXX, FANCA, LTK, MAP2K4, and NOTCH1 were associated with a poor prognosis (P < 0.05). This study provides an overview of genetic alterations in Chinese patients with CCA, which will provide novel potential biomarkers for the diagnosis of CCA and may guide targeted therapeutic strategies for Chinese patients with CCA.

The Prognosis Performance of a Neutrophil- and Lymphocyte-Associated Gene Mutation Score in a Head and Neck Cancer Cohort.

The treatment of head and neck squamous cell carcinomas (HNSCCs) is multimodal, and chemoradiotherapy (CRT) is a critical component. However, the availability of predictive or prognostic markers in patients with HNSCC is limited. Inflammation is a well-documented factor in cancer, and several parameters have been studied, with the neutrophil-to-lymphocyte ratio (NLR) being the most promising. The NLR is the most extensively researched clinical biomarker in various solid tumors, including HNSCC. In our study, we collected clinical and next-generation sequencing (NGS) data with targeted sequencing information from 107 patients with HNSCC who underwent CRT. The difference in the NLR between the good response group and the poor response group was significant, with more patients having a high NLR in the poor response group. We also examined the genetic alterations linked to the NLR and found a total of 41 associated genes across eight common pathways searched from the KEGG database. The overall mutation rate was low, and there was no significant mutation difference between the low- and high-NLR groups. Using a multivariate binomial generalized linear model, we identified three candidate genes (MAP2K2, MAP2K4, and ABL1) that showed significant results and were used to create a gene mutation score (GMS). Using the NLR-GMS category, we noticed that the high-NLR-GMS group had significantly shorter relapse-free survival compared to the intermediate- or low-NLR-GMS groups.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC.

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

Comprehensive analysis of genomic mutation signature and tumor mutation burden for prognosis of intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy of the biliary tract. Analysis of somatic mutational profiling can reveal new prognostic markers and actionable treatment targets. In this study, we explored the utility of genomic mutation signature and tumor mutation burden (TMB) in predicting prognosis in iCCA patients. METHODS: Whole-exome sequencing and corresponding clinical data were collected from the ICGC portal and cBioPortal database to detect the prognostic mutated genes and determine TMB values. To identify the hub prognostic mutant signature, we used Cox regression and Lasso feature selection. Mutation-related signature (MRS) was constructed using multivariate Cox regression. The predictive performances of MRS and TMB were assessed using Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis using gene set enrichment analysis (GSEA) for mutated genes. Based on the MRS, TMB, and the TNM stage, a nomogram was constructed to visualize prognosis in iCCA patients. RESULTS: The mutation landscape illustrated distributions of mutation frequencies and types in iCCA, and generated a list of most frequently mutated genes (such as Tp53, KRAS, ARID1A, and IDH1). Thirty-two mutated genes associated with overall survival (OS) were identified in iCCA patients. We obtained a six-gene signature using the Lasso and Cox method. AUCs for the MRS in the prediction of 1-, 3-, and 5-year OS were 0.759, 0.732, and 0.728, respectively. Kaplan-Meier analysis showed a significant difference in prognosis for patients with iCCA having a high and low MRS score (P < 0.001). GSEA was used to show that several signaling pathways, including MAPK, PI3K-AKT, and proteoglycan, were involved in cancer. Conversely, survival analysis indicated that TMB was significantly associated with prognosis. GSEA indicated that samples with high MRS or TMB also showed an upregulated expression of pathways involved in tumor signaling and the immune response. Finally, the predictive nomogram (that included MRS, TMB, and the TNM stage) demonstrated satisfactory performance in predicting survival in patients with iCCA. CONCLUSIONS: Mutation-related signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for determining outcomes in patients with iCCA.