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 is limited because of their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in locally recurrent nasopharyngeal carcinoma. METHODS: This multicenter, retrospective study included 921 patients with locally recurrent nasopharyngeal carcinoma. A machine learning signature and nomogram based on pretreatment magnetic resonance imaging features were developed for predicting overall survival in a training cohort and validated in 2 independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance 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 analysis. RESULTS: The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving concordance 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 statistically improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with statistically distinct overall survival rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-sequencing analysis revealed differences in interferon response and lymphocyte infiltration between risk groups. CONCLUSIONS: A magnetic resonance imaging-based radiomic signature predicted overall survival 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 locally recurrent nasopharyngeal carcinoma patients.

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.

Dissecting the heterogeneity of the microenvironment in primary and recurrent nasopharyngeal carcinomas using single-cell RNA sequencing.

Nasopharyngeal carcinoma (NPC) has a 10-15% recurrence rate, while no long term or durable treatment options are currently available. Single-cell profiling in recurrent NPC (rNPC) may aid in designing effective anticancer therapies, including immunotherapies. For the first time, we profiled the transcriptomes of ∼60,000 cells from four primary NPC and two rNPC cases to provide deeper insights into the dynamic changes in rNPC within radiation fields. Heterogeneity of both immune cells (T, natural killer, B, and myeloid cells) and tumor cells was characterized. Recurrent samples showed increased infiltration of regulatory T cells in a highly immunosuppressive state and CD8+ T cells in a highly cytotoxic and dysfunctional state. Enrichment of M2-polarized macrophages and LAMP3+ dendritic cells conferred enhanced immune suppression to rNPC. Furthermore, malignant cells showed enhanced immune-related features, such as antigen presentation. Elevated regulatory T cell levels were associated with a worse prognosis, with certain receptor-ligand communication pairs identified in rNPC. Even with relatively limited samples, our study provides important clues to complement the exploitation of rNPC immune environment and will help advance targeted immunotherapy of rNPC.

Synthesis and characterization of homochiral polymeric S-malato molybdate(VI): toward the potentially stereospecific formation and absolute configuration of iron-molybdenum cofactor in nitrogenase.

Reaction of sodium or potassium molybdate and excess malic acid in a wide range of pH values (pH 4.0-7.0) resulted in the isolation of two cis-dioxo-bis(malato)-Mo(VI) complexes, viz. Na(3)[MoO(2)H(S-mal)(2)] and K(3)[MoO(2)H(S-mal)(2)].H(2)O (H(3)mal=malic acid). The sodium complex is also characterized by an X-ray structure analysis, showing that the mononuclear Mo units are linked together via very strong symmetric CO(2)...H... O(2)C-hydrogen bond [2.432(5) A], forming a polymeric chain. The molybdenum atoms are quasi-octahedrally coordinated by two cis-oxo groups and two bidentate malate ligands via its alkoxy and alpha-carboxyl groups, while the beta-carboxylic and carboxylate groups remain uncomplexed, as the coordination of vicinal carboxylate and alkoxide of homocitrate in FeMo cofactor of nitrogenase. The absolute configuration of the metal center in this S-malato complex is assigned as Lambda and the homochirality within the chain is established as a homochiral form ...Lambda(S)-Lambda(S)-Lambda(S)-Lambda(S)... . It is proposed that the chiral configuration of the metal center in wild-type FeMo-co biosynthesis might be induced by the early coordination of the chiral R-homocitric acid, while a mixture of raceme might be obtained in the biosynthesis of NifV(-) FeMo-cofactor. The absolute configuration of wild-type FeMo-cofactor is assigned as Delta(R).