Radiomic signatures associated with tumor immune heterogeneity predict survival in locally recurrent nasopharyngeal carcinoma

BACKGROUND

The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma (lrNPC) is limited due to their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in lrNPC.

METHODS

This multicenter, retrospective study included 921 patients with lrNPC. A machine learning signature and nomogram based on pretreatment MRI features were developed for predicting overall survival (OS) in a training cohort and validated in two independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index (C-index) and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA sequencing (RNA-seq) analysis.

RESULTS

The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving C-indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables significantly improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with significantly distinct OS rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-seq analysis revealed differences in interferon response and lymphocyte infiltration between risk groups.

CONCLUSIONS

An MRI-based radiomic signature predicted OS more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for lrNPC patients.

Construction and application of nasopharyngeal carcinoma-specific big data platform based on electronic health records

OBJECTIVE

To establish a nasopharyngeal carcinoma-specific big data platform based on electronic health records (EHRs) to provide data support for real-world study of nasopharyngeal carcinoma.

METHODS

A multidisciplinary expert team was established for this project. Based on industry standards and practical feasibility, the team designed the nasopharyngeal carcinoma data element standards including 14 modules and 640 fields. Data from patients diagnosed with nasopharyngeal carcinoma who visited Southern Hospital after 1999 were extracted from 15 EHRs systems and were cleaned, structured, and standardized using information technologies such as machine learning and natural language processing. In addition, a series of measures such as quality control and data encryption were taken to ensure data quality and patient privacy. At the platform application level, 10 functional modules were designed according to the needs of nasopharyngeal carcinoma research.

RESULTS

As of 1 October 2022, the Big Data platform has included 11,617patients, of whom 8228 (70.83 %) were male and 3389 (29.17 %) were female, with a median age of 48 years (interquartile range, 40 years). The data in the platform were validated to have a high level of completeness and accuracy, especially for key variables such as social demographics, laboratory tests and vital signs. Currently, six projects involving risk factors, early diagnosis, treatment efficacy and prevention of treatment-related toxic reactions have been conducted on the platform.

CONCLUSIONS

We have established a high-quality NPC-specific big data platform by integrating heterogeneous data from multiple sources in the EHR. The platform provides an effective tool and strong data support for real-world studies of nasopharyngeal carcinoma, which helps to improve research efficiency, reduce costs, and improve the quality of research results. We expect to promote multicenter nasopharyngeal carcinoma data sharing in the future to facilitate the generation of high-quality real-world evidence in nasopharyngeal carcinoma. This article may provide some reference value for other comprehensive hospitals to establish a big data platform for nasopharyngeal carcinoma.

Radiomic signatures reveal multiscale intratumor heterogeneity associated with tissue tolerance and survival in re-irradiated nasopharyngeal carcinoma: a multicenter study

BACKGROUND

Post-radiation nasopharyngeal necrosis (PRNN) is a severe adverse event following re-radiotherapy for patients with locally recurrent nasopharyngeal carcinoma (LRNPC) and associated with decreased survival. Biological heterogeneity in recurrent tumors contributes to the different risks of PRNN. Radiomics can be used to mine high-throughput non-invasive image features to predict clinical outcomes and capture underlying biological functions. We aimed to develop a radiogenomic signature for the pre-treatment prediction of PRNN to guide re-radiotherapy in patients with LRNPC.

METHODS

This multicenter study included 761 re-irradiated patients with LRNPC at four centers in NPC endemic area and divided them into training, internal validation, and external validation cohorts. We built a machine learning (random forest) radiomic signature based on the pre-treatment multiparametric magnetic resonance images for predicting PRNN following re-radiotherapy. We comprehensively assessed the performance of the radiomic signature. Transcriptomic sequencing and gene set enrichment analyses were conducted to identify the associated biological processes.

RESULTS

The radiomic signature showed discrimination of 1-year PRNN in the training, internal validation, and external validation cohorts (area under the curve (AUC) 0.713-0.756). Stratified by a cutoff score of 0.735, patients with high-risk signature had higher incidences of PRNN than patients with low-risk signature (1-year PRNN rates 42.2-62.5% vs. 16.3-18.8%, P < 0.001). The signature significantly outperformed the clinical model (P < 0.05) and was generalizable across different centers, imaging parameters, and patient subgroups. The radiomic signature had prognostic value concerning its correlation with PRNN-related deaths (hazard ratio (HR) 3.07-6.75, P < 0.001) and all causes of deaths (HR 1.53-2.30, P < 0.01). Radiogenomics analyses revealed associations between the radiomic signature and signaling pathways involved in tissue fibrosis and vascularity.

CONCLUSIONS

We present a radiomic signature for the individualized risk assessment of PRNN following re-radiotherapy, which may serve as a noninvasive radio-biomarker of radiation injury-associated processes and a useful clinical tool to personalize treatment recommendations for patients with LANPC.

[Fibroblast growth factor receptor 1 propagates estrogen and fluid shear stress driven proliferation and differentiation response in MC3T3-E1 cells]

Fluid shear stress (FSS) and estrogen exposure positively regulate bone metabolism. Fibroblast growth factor receptor 1 (FGFR1) plays a vital role in FSS-induced osteogenesis. An in vitro experiment with MC3T3-E1 cells combined with microarray analysis aided us in identification of the genes differentially expressed in response to FSS and highlighted the role of FGFR1 in this process. Both estrogen exposure and FSS increase methyl thiazol tetrazolium (MTT) values and alkaline phosphatase (ALP) activity, as well as the levels of Runt-related transcription factor 2 (Runx2) and osteocalcin (OCN). The effects of estrogen exposure and FSS were cumulative. Treatment with PD166866 inhibitor of the FGFR1 reduced the MTT values, increased ALP activity, and increased the levels of Runx2 and OCN. To investigate the regulation of FGFR1 signaling in stressed cells, a number of key components of the mitogen-activated protein kinase (MAPK) cascade were quantitatively examined. Neither estrogen nor FSS change the protein expression of extracellular signal-regulated kinase (ERK), Jun amino-terminal kinases (JNK) or p38, but positively influence their phosphorylation levels. Treatment with the FGFR1 inhibitor induced an increase in ERK phosphorylation levels only. In summary, estrogen exposure and FSS have a synergistic effect in osteogenesis. FGFR1 promotes osteoblast proliferation and inhibits the differentiation of osteoblasts. In MC3T3-E1 cells, FGFR1 signaling responds to independent and combined effects of estrogen and FSS. MAPK cascades participate in osteogenesis, but only the ERK signaling pathway responds to FGFR1.

Molecular gas in the halo fuels the growth of a massive cluster galaxy at high redshift

The largest galaxies in the universe reside in galaxy clusters. Using sensitive observations of carbon monoxide, we show that the Spiderweb galaxy-a massive galaxy in a distant protocluster-is forming from a large reservoir of molecular gas. Most of this molecular gas lies between the protocluster galaxies and has low velocity dispersion, indicating that it is part of an enriched intergalactic medium. This may constitute the reservoir of gas that fuels the widespread star formation seen in earlier ultraviolet observations of the Spiderweb galaxy. Our results support the notion that giant galaxies in clusters formed from extended regions of recycled gas at high redshift.