A novel telomere-related gene prognostic signature for survival and drug treatment efficiency prediction in lung adenocarcinoma.

OBJECTIVE: Telomere-related genes (TRGs) play a critical role in various types of tumors. However, there is a lack of comprehensive exploration of their relevance in lung cancer. This research aimed to verify the relationship between TRGs gene expression and the prognosis of patients with lung adenocarcinoma (LUAD), as well as the prediction of drug treatment efficiency. METHODS: A total of 2093 TRGs were acquired from TelNet. The clinical information including age, tumor stage, follow up and outcome (death/survival) and TRGs expression profile of LUAD were obtained from the patients in The Cancer Genome Atlas (TCGA) database and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. The two databases were used to construct and verify a prognostic model based on the expression of hubTRGs. The tumor mutation burden, immune infiltration and subtypes, as well as IC50 prediction of multiple targeted drugs were also evaluated in TRGs-divided risk groups. RESULTS: A total of 335 TRGs were significantly differentially expressed in LUAD as compared with normal control. Among them, 9 TRGs (ABCC2, ABCC8, ALDH2, FOXP3, GNMT, JSRP1, MACF1, PLCD3, SULT4A1) were finally identified as hubGenes and used to construct a TRG risk score. The TRG risk score showed favorable performance in constructing a prognostic nomogram in predicting survival of LUAD, and the ROC curves at 1, 3 and 5 years were plotted and the AUROC values were 0.743, 0.754 and 0.735, respectively. Higher TRGs risk score correlated with worse immune subtypes and higher tumor mutation burden in LUAD tissues. In addition, the patients in TRG high risk group harbored a lower TIDE score which indicated potentially better response to immunotherapy. CONCLUSION: This study proposed a broad molecular signature of telomere-related genes that can be used in further functional and therapeutic investigations, and also represents an integrated modality for characterizing critical molecules when exploring novel targets for lung cancer immunotherapy.

Decreased Expression of a Novel lncRNA FAM181A-AS1 is Associated with Poor Prognosis and Immune Infiltration in Lung Adenocarcinoma.

Background: There is no clear information regarding the role of FAM181A antisense RNA 1 (FAM181A-AS1) in lung adenocarcinoma (LUAD). We explored the relationship between FAM181A-AS1 and LUAD using bioinformatics analysis and experimental validation in this study. Methods: Statistics and databases were used to evaluate the relationship between clinical features in LUAD patients and FAM181A-AS1 expression, prognostic factors, regulation network, and immune infiltration of FAM181A-AS1 in function. LUAD cell lines were tested for FAM181A-AS1 expression using qRT-PCR. Results: FAM181A-AS1 showed significantly low expression in LUAD patients. Low FAM181A-AS1 expression predicted a poorer overall survival (OS) (HR: 0.66; 95% CI: 0.49-0.88; P=0.005) and disease specific survival (DSS) (HR: 0.64; 95% CI: 0.44-0.92; P=0.017) of LUAD patients. There was also an independent correlation between low FAM181A-AS1 expression (HR: 0.547; 95% CI: 0.350-0.857; P=0.008) and OS in LUAD patients. The FAM181A-AS1 high-expression phenotype was differentially enriched for M phase, cellular senescence, cell cycle checkpoints, chromatin modifying enzymes, ESR-mediated signaling, DNA repair, G2/M checkpoints, HCMV infection, and DNA double-strand break repair. A correlation was found between the expression of FAM181A-AS1 and immune infiltrating cells. A significant decrease in FAM181A-AS1 expression was observed in LUAD cell lines compared to Beas-2B. Conclusion: There was a significant association between low FAM181A-AS1 expression in LUAD patients and poor survival and immune infiltration. The FAM181A-AS1 gene may provide a useful biomarker for LUAD prognosis and immunotherapy response.

An MR-based radiomics model for differentiation between hepatocellular carcinoma and focal nodular hyperplasia in non-cirrhotic liver.

PURPOSE: We aimed to develop and validate a radiomics model for differentiating hepatocellular carcinoma (HCC) from focal nodular hyperplasia (FNH) in non-cirrhotic livers using Gd-DTPA contrast-enhanced magnetic resonance imaging (MRI). METHODS: We retrospectively enrolled 149 HCC and 75 FNH patients treated between May 2015 and May 2019 at our center. Patients were randomly allocated to a training (n=156) and validation set (n=68). In total, 2260 radiomics features were extracted from the arterial phase and portal venous phase of Gd-DTPA contrast-enhanced MRI. Using Max-Relevance and Min-Redundancy, random forest, least absolute shrinkage, and selection operator algorithm for dimensionality reduction, multivariable logistic regression was used to build the radiomics model. A clinical model and combined model were also established. The diagnostic performance of the models was compared. RESULTS: Eight radiomics features were chosen for the radiomics model, and four clinical factors (age, sex, HbsAg, and enhancement pattern) were chosen for the clinical model. A combined model was built using the factors from the previous models. The classification accuracy of the combined model differentiated HCC from FNH in both the training and validation sets (0.956 and 0.941, respectively). The area under the receiver operating characteristic curve of the combined model was significantly better than that of the clinical model for both the training (0.984 vs. 0.937, p=0.002) and validation (0.972 vs. 0.903, p=0.032) sets. CONCLUSIONS: The combined model provided a non-invasive quantitative method for differentiating HCC from FNH in non-cirrhotic liver with high accuracy. Our model may assist clinicians in the clinical decision-making process.

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis.

OBJECTIVE: To compare survival outcomes between cervical adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using a propensity score matching (PSM) analysis based on the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Patients diagnosed with cervical cancer between 1998 and 2016 were identified from the SEER database. The Kaplan-Meier method and Cox regression analysis were used to analyze survival. A subgroup analysis of overall survival (OS) between patients with ADC and SCC was performed after the 1:1 PSM analysis. RESULTS: Of the 33,148 patients, 24,591 (79.19%) had SCC and 8,557 (25.81%) had ADC. In the unmatched cohort, after adjustment in multivariate analysis, patients with ADC had a worse prognosis than patients with SCC (hazard ratio [HR]=1.12; 95% confidence interval [CI]=1.07-1.18; p<0.001). In the propensity matched cohort, Kaplan-Meier analysis and subgroup analysis showed that ADC was associated with a worse prognosis than SCC (p=0.001). An analysis stratified by SEER stage revealed a worse prognosis for patients with ADC patients presenting with a regional disease than patients with SCC (HR=1.24; 95% CI=1.14-1.36 p<0.001), but no statistically significant differences were observed between the localized disease (HR=0.97; 95% CI=0.86-1.10; p=0.664) and distant disease (HR=1.09; 95% CI=0.97-1.22; p=0.162) subgroups. CONCLUSION: The significant differences in survival outcomes between patients with cervical ADC and SCC were only observed in the regional disease subgroup, but not in the localized disease and distant disease subgroups.

Histological subtype remains a prognostic factor for survival in nasopharyngeal carcinoma patients.

OBJECTIVES: There is currently no consensus on the prognostic significance of the histological subtype of nasopharyngeal carcinoma (NPC). The aim of the current study was to evaluate the impact of histological subtype on survival in NPC patients based on the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Patients with NPC were identified within the SEER database (2004-2015). The effects of histological subtype on cause-specific survival (CSS) in NPC patients were evaluated using univariate and multivariate Cox regression analyses. Subgroup analysis according to histological subtype in NPC patients was carried out by 1:1 propensity score matching (PSM). RESULTS: A total of 4085 NPC patients were selected from the SEER database, including 1929 with keratinizing squamous cell carcinoma (KSCC), 2203 with nonkeratinizing carcinoma (NKC), and 53 with basaloid squamous cell carcinoma (BSCC). The 3-year and 5-year CSS rates were 61.76% and 55.07% for KSCC patients, 79.57% and 72.09% for NKC patients, and 77.55% and 74.03% for BSCC patients, respectively. Multivariate analysis identified sex, age, marital status, race, T stage, N stage, M stage, radiotherapy, chemotherapy, and histological subtype as significant prognostic factors for CSS in NPC patients. KSCC was found to be associated with worse CSS than NKC on Kaplan-Meier analysis and subgroup analysis after 1:1 PSM. CONCLUSIONS: Histological subtype determines the long-term survival outcomes of patients with NPC. Moreover, the NKC subtype has the best prognosis, while the KSCC subtype has the worst prognosis. LEVEL OF EVIDENCE: NA Laryngoscope, 130:E83-E88, 2020.

Nomogram for predicting the overall survival of patients with inflammatory breast cancer: A SEER-based study.

OBJECTIVES: Inflammatory breast cancer (IBC) is a rare malignancy that is a unique biologic subtype of breast cancer. A nomogram to predict the overall survival (OS) of IBC patients is lacking. The aim of the study was to construct and validate a nomogram to predict the OS of IBC patients based on the Surveillance, Epidemiology, and End Results (SEER) Program. METHODS: Patients diagnosed with IBC between 2010 and 2016 were selected from the SEER database. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram was constructed to predict the 1-, 3- and 5-year OS of these patients. The nomogram was internally and externally validated by Harrell's C-indexes and calibration plots. RESULTS: Patients were randomly divided into a training set (n = 2464) and a validation set (n = 1052). The training set was used to establish a nomogram. Multivariate analysis identified that race, age at diagnosis, breast cancer subtype, grade, N stage, M stage, radiation, chemotherapy, and surgery were significant prognostic factors for the OS. The internally and externally validated Harrell's C-indexes were 0.763 and 0.786, respectively. The calibration plots for predictions of the 1-, 3-, and 5-year OS were in excellent agreement. CONCLUSIONS: A nomogram was constructed to predict the OS for IBC patients based on the SEER database and to provide accurate and individualised survival predictions.

A simplified T classification based on the 8th edition of the UICC/AJCC staging system for nasopharyngeal carcinoma.

Objective: This study aimed to establish a simplified T classification based on the 8th edition of the Union for International Cancer Control/American Joint Committee on Cancer (UICC/AJCC) staging system for nasopharyngeal carcinoma (NPC). Methods: In total, 325 patients with NPC were included in this study. All patients underwent magnetic resonance imaging, and the staging criteria were recorded. These patients were subjected to staging with the 8th edition of the UICC/AJCC staging system for NPC. Results:  Involvement of the oropharynx, nasal cavity, adjacent soft tissue (medial pterygoid, lateral pterygoid, and prevertebral muscles), cervical vertebra, orbit, and hypopharynx were always accompanied by other equivalently or more advanced T-stage classifications. All cases with involvement of the paranasal sinuses showed skull base erosion. The majority of cases with involvement of the pterygoid structure showed skull base erosion. Conclusion: According to the simplification principle, the following new T classification based on the 8th edition of the UICC/AJCC staging system was established: T1, tumor confined to nasopharynx, or beyond the nasopharynx without parapharyngeal involvement; T2, tumor with extension to the parapharyngeal space; T3, tumor with infiltration to bony structures at the skull base; T4, tumor with intracranial extension, involvement of the cranial nerves or parotid gland, and/or extensive soft tissue infiltration beyond the lateral surface of the lateral pterygoid muscle. Validation with a large series of patients is needed.