The m6A reader HNRNPC promotes glioma progression by enhancing the stability of IRAK1 mRNA through the MAPK pathway.

Glioma is the most common and aggressive type of primary malignant brain tumor. The N6-methyladenosine (m6A) modification widely exists in eukaryotic cells and plays an important role in the occurrence and development of human tumors. However, the function and mechanism of heterogeneous nuclear ribonucleoprotein C (HNRNPC), an RNA-binding protein and m6A reader in gliomas remains to be comprehensively and extensively explored. Herein, we found that HNRNPC mRNA and protein overexpression were associated with a poor prognosis for patients with gliomas, based on the data from TCGA, the CGGA, and the TMAs. Biologically, HNRNPC knockdown markedly repressed malignant phenotypes of glioma in vitro and in vivo, whereas ectopic HNRNPC expression had the opposite effect. Integrative RNA sequencing and MeRIP sequencing analyses identified interleukin-1 receptor-associated kinase 1 (IRAK1) as a downstream target of HNRNPC. The glioma public datasets and tissue microarrays (TMAs) data indicated that IRAK1 overexpression was associated with poor prognosis, and IRAK1 knockdown significantly repressed malignant biological behavior in vitro. Mechanistically, HNRNPC maintains the mRNA stability of IRAK1 in an m6A-dependent manner, resulting in activation of the mitogen-activated protein kinase (MAPK) signaling pathway, which was necessary for the malignant behavior of glioma. Our findings demonstrate the HNRNPC-IRAK1-MAPK axis as a crucial carcinogenic factor for glioma and the novel underlying mechanism of IRAK1 upregulation, which provides a rationale for therapeutically targeting epitranscriptomic modulators in glioma.

Anatomic prognostic factors and their potential roles in refining M1 classification for de novo metastatic nasopharyngeal carcinoma.

BACKGROUND AND PURPOSE: To identify anatomic prognostic factors and their potential roles in refining M1 classification for de novo metastatic nasopharyngeal carcinoma (M1-NPC). MATERIALS AND METHODS: All M1-NPC treated with chemotherapy and/or radiotherapy between 2010 and 2019 from two centers (training and validation cohort) were included. The prognostic value of metastatic disease extent and involved organs for overall survival (OS) were assessed by several multivariable analyses (MVA) models. A new M1 classification was proposed and validated in a separate cohort who received immuno-chemotherapy. RESULTS: A total of 197 M1-NPC in the training and 307 in the validation cohorts were included for M1 subdivision study with median follow-up of 46 and 57 months. MVA model with "≤2 organs/≤5 lesions" as the definition of oligometastasis had the highest C-index (0.623) versus others (0.606-0.621). Patients with oligometastasis had better OS versus polymetastasis (hazard ratio [HR] 0.47/0.63) while liver metastases carried worse OS (HR 1.57/1.45) in MVA in the training/validation cohorts, respectively. We proposed to divide M1-NPC into M1a (oligometastasis without liver metastases) and M1b (liver metastases or polymetastasis) with 3-year OS of 66.5%/31.7% and 64.9%/35.0% in the training/validation cohorts, respectively. M1a subset had a better median progress-free survival (not reach vs. 17 months, p < 0.001) in the immuno-chemotherapy cohort (n = 163). CONCLUSION: Oligometastasis (≤2 organs/≤5 lesions) and liver metastasis are prognostic for M1-NPC. Subdivision of M1-NPC into M1a (oligometastasis without liver metastasis) and M1b (liver metastasis or polymetastasis) depicts the prognosis well in M1-NPC patients who received immuno-chemotherapy.

A Novel Prognostic Model Predicts Outcomes in Non-Metastatic Nasopharyngeal Carcinoma Based on Inflammation, Nutrition, and Coagulation Signature.

Purpose: This study aimed to assess the prognostic and predictive value of a circulating hematological signature (CHS) and to develop a CHS-based nomogram for predicting prognosis and guiding individualized chemotherapy in non-metastatic nasopharyngeal carcinoma (NPC) patients. Patients and Methods: NPC patients were recruited between January 2014 and December 2017 at the Jiangxi Cancer Hospital. The CHS was constructed based on a series of hematological indicators. The nomogram was developed by CHS and clinical factors. Results: A total of 779 patients were included. Three biomarkers were selected by least absolute shrinkage and selection operator regression, including prognostic nutritional index, albumin-to-fibrinogen ratio, and prealbumin-to-fibrinogen ratio, were used to construct the CHS. The patients in the low-CHS group had better 5-year DMFS and OS than those in the high-CHS group in the training (DMFS: 85.0% vs 56.6%, p<0.001; OS: 90.3% vs 65.4%, p<0.001) and validation cohorts (DMFS: 92.3% vs 43.6%, p<0.001; OS: 92.1% vs 65.5%, p<0.001). The nomogram_CHS showed better performance than clinical stage in predicting distant metastasis (concordance index: 0.728 vs 0.646). In the low-TRS (total risk scores) group, the patients received RT alone, CCRT and IC plus CCRT had similar 5-year DMFS and OS (p>0.05). In the middle-TRS group, the patients received RT alone had worse 5-year DMFS (58.7% vs 80.8% vs 90.8%, p=0.002) and OS (75.0% vs 94.1% vs 95.0%, p=0.001) than those received CCRT or IC plus CCRT. In the high-TRS group, the patients received RT alone and CCRT had worse 5-year DMFS (18.6% vs 31.3% vs 81.5%, p<0.001) and OS (26.9% vs 53.2% vs 88.8%, p<0.001) than those received IC plus CCRT. Conclusion: The developed nomogram_CHS had satisfactory prognostic accuracy in NPC patients and may individualize risk estimation to facilitate the identification of suitable IC candidates.

MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma.

Chemotherapy remains controversial for stage II nasopharyngeal carcinoma because of its considerable prognostic heterogeneity. We aimed to develop an MRI-based deep learning model for predicting distant metastasis and assessing chemotherapy efficacy in stage II nasopharyngeal carcinoma. This multicenter retrospective study enrolled 1072 patients from three Chinese centers for training (Center 1, n = 575) and external validation (Centers 2 and 3, n = 497). The deep learning model significantly predicted the risk of distant metastases for stage II nasopharyngeal carcinoma and was validated in the external validation cohort. In addition, the deep learning model outperformed the clinical and radiomics models in terms of predictive performance. Furthermore, the deep learning model facilitates the identification of high-risk patients who could benefit from chemotherapy, providing useful additional information for individualized treatment decisions.

The role of radiologic extranodal extension in predicting prognosis and chemotherapy benefit for T1-2 N1 nasopharyngeal carcinoma: A multicenter retrospective study.

BACKGROUND AND PURPOSE: This multicenter retrospective study aimed to investigated the prognostic value of unequivocal radiologic extranodal extension (rENE) and the efficacy of chemotherapy for stage T1-2 N1 nasopharyngeal carcinoma (NPC) in the IMRT era. MATERIALS AND METHODS: We included 1,082 patients treated in 2005-2017 from three centers. rENE was recorded as G1 (coalescent nodal mass comprising ≥ 2 inseparable nodes) or G2 (invading beyond perinodal fat to frankly infiltrate adjacent structures). Multivariable analysis (MVA) evaluated the prognostic value of rENE. The value of chemotherapy was assessed in rENE-positive (rENE + ) and rENE-negative (rENE - ) subset separately. RESULTS: Centers 1, 2, and 3 had 139/515 (27.0 %), 100/365 (27.4 %), and 43/202 (21.3 %) cN + patients with rENE, respectively. Compared to rENE-, rENE + patients had a worse distant metastasis-free survival (DMFS) and overall survival (OS) (all p < 0.001). MVA confirmed the prognostic of both G1-rENE and G2-rENE for distant metastasis [G1: hazard ratio (HR): 2.933, G2: HR: 6.942, all p < 0.001] and death (G1: HR: 1.587, p = 0.040; G2: HR: 6.162, p < 0.001). There was no significant difference for DMFS and OS between chemo-radiotherapy and radiotherapy alone in rENE + and rENE - groups (all p > 0.1). However, rENE + patients with a cumulative cisplatin/nedaplatin dose (CCND) of > 160 mg/m2 had an improved DMFS (p = 0.033) but no OS (p = 0.197). CONCLUSION: Unequivocal rENE is prognostic in patients with T1-2 N1 NPC. Addition of chemotherapy to radiotherapy did not affect DMFS and OS in rENE - patients. Chemotherapy with a CCND of > 160 mg/m2 improved DMFS in rENE + patients.

Systemic immune-inflammation index as a prognostic marker in patients with newly diagnosed metastatic nasopharyngeal carcinoma: a propensity score-matched study.

BACKGROUND: Systemic immune-inflammation index (SII) is significantly associated with poor survival in variety of cancers. However, SII has not yet been investigated in patients with newly diagnosed metastatic nasopharyngeal carcinoma (mNPC). Thus, our aim is to explore the role of SII in metastatic Nasopharyngeal Carcinoma. METHODS: Two hundred and forty-three patients with newly diagnosed mNPC were retrospectively enrolled. The Kaplan-Meier analysis and Cox regression analysis was performed to evaluate the prognostic value of SII in overall survival (OS) and progression-free survival (PFS). Heterogeneity of factors was balanced by using propensity score-matched (PSM) analysis (1:1 for high SII versus low SII). RESULTS: Kaplan-Meier analysis showed that patients with high SII were associated with poor median OS (18.0 vs. 36.0 m, P<0.001) and PFS (10.0 vs. 22.0 m, P<0.001) in mNPC. The Cox regression analysis suggested that high SII was a prognostic factor for OS (HR 1.75, 95% CI: 1.22-2.52, P=0.001) and PFS (HR 1.69, 95% CI: 1.22-2.35, P=0.002). PSM analysis still confirmed that SII was an independent marker for OS (HR 1.86, 95% CI: 1.22-2.83, P=0.004) and PFS (HR 1.84, 95% CI: 1.23-2.77, P=0.003). CONCLUSIONS: SII is an independent prognostic biomarker for poor OS and PFS in patients with newly diagnosed mNPC and might be a promising tool for guiding treatment strategy decisions.