Integrative multi-omics analyses identify molecular subtypes of head and neck squamous cell carcinoma with distinct therapeutic vulnerabilities.

Substantial heterogeneity in molecular features, patient prognoses, and therapeutic responses in head and neck squamous cell carcinomas (HNSCC) highlights the urgent need to develop molecular classifications that reliably and accurately reflect tumor behavior and inform personalized therapy. Here, we leveraged the similarity network fusion bioinformatics approach to jointly analyze multi-omics datasets spanning copy number variations, somatic mutations, DNA methylation, and transcriptomic profiling and derived a prognostic classification system for HNSCC. The integrative model consistently identified three subgroups (IMC1-3) with specific genomic features, biological characteristics, and clinical outcomes across multiple independent cohorts. The IMC1 subgroup included proliferative, immune-activated tumors and exhibited a more favorable prognosis. The IMC2 subtype harbored activated EGFR signaling and an inflamed tumor microenvironment with cancer-associated fibroblast/vascular infiltrations. Alternatively, the IMC3 group featured highly aberrant metabolic activities and impaired immune infiltration and recruiting. Pharmacogenomics analyses from in silico predictions and from patient-derived xenograft model data unveiled subtype-specific therapeutic vulnerabilities including sensitivity to cisplatin and immunotherapy in IMC1 and EGFR inhibitors (EGFRi) in IMC2, which was experimentally validated in patient-derived organoid models. Two signatures for prognosis and EGFRi sensitivity were developed via machine learning. Together, this integrative multi-omics clustering for HNSCC improves current understanding of tumor heterogeneity and facilitates patient stratification and therapeutic development tailored to molecular vulnerabilities.

Development of a novel senescence-related gene signature to predict clinical outcomes, immune landscape, and chemotherapeutic sensitivity in oral squamous cell carcinoma.

BACKGROUND: Cellular senescence significantly associates with tumor initiation, progression, and therapeutic response across multiple cancers. Here, we sought to develop a novel senescence-related genes (SRGs)-derived signature for oral squamous cell carcinoma (OSCC) prognostication and therapeutic response prediction. METHODS: OSCC-specific SRG prognostic signature was established with univariate Cox regression, Kaplan-Meier survival, and LASSO-penalized multivariate Cox regression analyses. A SRG nomogram integrating this signature and selected clinicopathological parameters were constructed by multivariate Cox regression. SiRNA-mediated gene knockdown was exploited to validate its function in vitro. The utilities of SRG signature in predicting immune status and chemotherapeutic sensitivities were analyzed. RESULTS: The prognostic performance of SRG signature/nomogram was satisfactory in multiple independent cohorts. CDK1 knockdown induced senescence phenotype in vitro. Moreover, SRG signature scores negatively correlated with tumor-infiltrating immune cells and associated with multiple chemotherapeutic drug sensitivities. CONCLUSIONS: Our results established SRG-derived signature/nomogram as powerful predictors for prognosis and chemotherapeutic response for OSCC.

Univariable and multivariable mendelian randomization study revealed the modifiable risk factors of urolithiasis.

BACKGROUND: Urolithiasis is a common urological disease with increasing incidence worldwide, and preventing its risk poses significant challenges. Here, we used Mendelian randomization (MR) framework to genetically assess the causal nature of multifaceted risk factors on urolithiasis. METHODS: 17 potential risk factors associated with urolithiasis were collected from recently published observational studies, which can be categorized basically into lifestyle factors and circulating biomarkers. The instrumental variables of risk factors were selected from large-scale genome-wide association studies (N ≤ 607,291). Summary-level data on urolithiasis were obtained from UK Biobank (UKB) (3,625 cases and 459,308 noncases) and the FinnGen consortium (5,347 cases and 213,445 noncases). The univariable and multivariable MR analyses were applied to evaluate the causal, independent effect of these potential risk factors upon urolithiasis. Effects from the two consortia were combined by the meta-analysis methods. RESULTS: Higher genetically predicted sex hormone-binding globulin (SHBG, OR, 0.708; 95% CI, 0.555 to 0.903), estradiol (OR, 0.179; 95% CI, 0.042 to 0.751), tea intake (OR, 0.550; 95% CI, 0.345 to 0.878), alcoholic drinks per week (OR, 0.992; 95% CI, 0.987 to 0.997), and some physical activity (e.g., swimming, cycling, keeping fit, and bowling, OR, 0.054; 95% CI, 0.008 to 0.363) were significantly associated with a lower risk of urolithiasis. In the Multivariate Mendelian Randomization (MVMR) analyses, the significant causal associations between estradiol, SHBG, tea intake, and alcoholic drinks per week with urolithiasis were robust even after adjusting for potential confounding variables. However, the previously observed causal association between other exercises and urolithiasis was no longer significant after adjusting for these factors. CONCLUSIONS: The univariable and multivariable MR findings highlight the independent and significant roles of estradiol, SHBG, tea intake, and alcoholic drinks per week in the development of urolithiasis, which might provide a deeper insight into urolithiasis risk factors and supply potential preventative strategies.

Development of a novel prognostic signature derived from essential genes in head and neck squamous cell carcinoma.

BACKGROUND: Substantial heterogeneity in head and neck squamous cell carcinoma (HNSCC) compromise accurate patient stratification and personalized treatment planning. Current molecular classification is largely based on genes with highly variable expression without considering their functional roles. Here, we sought to identify HNSCC essential genes for patient stratification and prognostication. METHODS: Essential genes for HNSCC were screened from genome-wide CRISPR knockout datasets. Candidates were further identified through univariate Cox regression. The least absolute shrinkage and selection operator was utilized to develop the prognostic signature. Candidate essential genes were exploited to classify patients into subgroups by consensus clustering. Survival outcomes, genomic alterations, signaling activities, and therapeutic vulnerabilities were compared between patient subgroups. RESULTS: Sixty-eight genes were identified as candidates and utilized to develop an 8-gene prognostic signature. Patients were segregated into two clusters with distinct survival rates across multiple cohorts based on upregulated essential genes. Cluster 2 exhibited higher TP53, CDKN2A, and NOTCH1 mutations, higher stromal activities, worse prognosis as well as and sensitivities to cell cycle inhibitors. Cluster 1 was characterized by a better prognosis and susceptibility to PI3K/AKT and MAPK inhibitors. CONCLUSION: Our study developed a novel and robust prognostic signature and classification derived from essential genes for HNSCC, which sheds new light on HNSCC precision oncology.

Development of a novel prognostic signature derived from enhancer RNA-regulated genes in head neck squamous cell carcinoma.

BACKGROUND: Enhancer RNAs (eRNAs) are increasingly recognized as prognostic biomarkers-across human cancers. Here, we sought to develop a novel eRNA-regulated genes (ERGs)-derived prognostic signature for head neck squamous cell carcinoma (HNSCC). METHODS: Candidate ERGs were identified via co-expression between individual survival-related eRNAs and their putative targets by Spearman's correlation analyses. The ERG signature was developed by univariate Cox regression, Kaplan-Meier survival analysis and maximum AUC in 1000 iterations of LASSO-penalized multivariate Cox regression. An ERG nomogram incorporating ERG signature and selected clinicopathological parameters were constructed by multivariate Cox regression. Biological roles of eRNA of interest were further explored in vitro. RESULTS: The ERG signature successfully stratified patients into subgroups with distinct survival in multiple cohorts. An ERG nomogram was developed with satisfactory performance in prognostication. Inhibition of ENSR00000165816 significantly reduced transcript level of SLC2A9 and impaired cell proliferation and invasion. CONCLUSION: Our results establish ERG signature and nomogram as powerful prognostic predictors for HNSCC.

Development of a novel signature derived from single cell RNA-sequencing for preoperative prediction of lymph node metastasis in head and neck squamous cell carcinoma.

BACKGROUND: Lymph node metastasis (LNM) is considered as an adverse prognostic indicator for cancer patients. Preoperative knowledge of LNM is valuable for pretreatment decision making. Here, we sought to develop and validate an LNM signature for preoperative prediction of LNM in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: By studying single cell RNA-sequencing data (scRNA-seq), differentially expressed mRNA were selected and analyzed through univariate logistic regression and least absolute shrinkage and selection operator (LASSO) to identify an LNM signature. Multivariate logistic regression was utilized to establish an LNM nomogram incorporating LNM signature and T-classification. RESULTS: The LNM signature was significantly associated with lymph node status and prognosis. The LNM signature and LNM nomogram displayed a robust predictive effect. CONCLUSION: Our study reveals that LNM signature is a powerful biomarker for preoperative prediction of LNM in patients with HNSCC, which may be effective to realize individualized outcome prediction.

Comprehensive characterization of epidemiological and 3D radiographic features of non-third molar impacted teeth in a Chinese dental population.

OBJECTIVE: This retrospective study aimed to comprehensively delineate the epidemiological and 3-dimensional radiographic characteristics of non-third molar (non-M3) impacted teeth in a Chinese dental population. MATERIAL AND METHODS: Patients with impacted teeth except for the third molar (ITEM3) were retrospectively screened via cone-beam CT images from 75,021 patients treated at our institution from June 2012 to December 2018. Demographic and clinical data of patients with ITEM3 were retrieved from medical records. CBCT coupled with 3-dimensional reconstruction was employed to characterize the radiographic features of ITEM3. Associations between these epidemiological, clinical, and radiographic features were further statistically analyzed. RESULTS: Among 1975 eligible patients, 2467 ITEM3s were identified with a prevalence of 2.63% (1975/75,021). Females slightly outnumbered males with a ratio of 1.12:1. The majority of ITEM3 was single (1577, 79.85%) in the maxilla. The maxillary canine teeth were the most frequently impacted (52.45%), followed by maxillary incisors. The mesioangular position was the most common orientation (43.8%), followed by vertical and buccal-lingual orientations. The most frequently associated lesion was external root resorption of the adjacent tooth, which was significantly correlated with the morphology and position of the impacted tooth. CONCLUSION: Most ITEM3 was single, mesioangular, found at maxillary canines, sometimes associated with diverse complications. Our data advance the current understanding of ITEM3 and offer insights into the management of this dental abnormality. CLINICAL RELEVANCE: These findings are useful for clinicians to comprehensively understand the prevalence, radiographic features, and complications of non-M3 impacted teeth.

Expression of an Antiviral Gene GmRUN1 from Soybean Is Regulated via Intron-Mediated Enhancement (IME).

Most of R (resistance) genes encode the protein containing NBS-LRR (nucleotide binding site and leucine-rich repeat) domains. Here, N. benthamiana plants were used for transient expression assays at 3-4 weeks of age. We identified a TNL (TIR-NBS-LRR) encoding gene GmRUN1 that was resistant to both soybean mosaic virus (SMV) and tobacco mosaic virus (TMV). Truncation analysis indicated the importance of all three canonical domains for GmRUN1-mediated antiviral activity. Promoter-GUS analysis showed that GmRUN1 expression is inducible by both salicylic acid (SA) and a transcription factor GmDREB3 via the cis-elements as-1 and ERE (ethylene response element), which are present in its promoter region. Interestingly, GmRUN1 gDNA (genomic DNA) shows higher viral resistance than its cDNA (complementary DNA), indicating the existence of intron-mediated enhancement (IME) for GmRUN1 regulation. We provided evidence that intron2 of GmRUN1 increased the mRNA level of native gene GmRUN1, a soybean antiviral gene SRC7 and also a reporter gene Luciferase, indicating the general transcriptional enhancement of intron2 in different genes. In summary, we identified an antiviral TNL type soybean gene GmRUN1, expression of which was regulated at different layers. The investigation of GmRUN1 gene regulatory network would help to explore the mechanism underlying soybean-SMV interactions.

Melatonin Enhances Seed Germination and Seedling Growth of Medicago sativa Under Salinity via a Putative Melatonin Receptor MsPMTR1.

Alfalfa (Medicago sativa L.) is an important forage crop, and salt stress is a major limiting factor in its yield. Melatonin (MT) is a multi-regulatory molecule in plants. We showed that basal MT content was positively correlated with the salt tolerance degree of different alfalfa varieties. MT and its precursor 5-HT fully recovered seed germination while partially ameliorated seedling growth of salt-stressed alfalfa. The 5-HT showed some divergent effects from MT with regards to growth amelioration under salinity. Salt stress caused stunted plant growth in soil culture, while MT ameliorated it by elevating plant height, fresh weight, branching number, and chlorophyll content. Silencing of a putative MT receptor, MsPMTR1, which was shown to be membrane-localized, abolished the ameliorative effects of MT on salt-stressed alfalfa seedling growth, while overexpression of MsPMTR1 improved plant growth under salt stress. The RNA sequencing analysis showed that nine pathway genes were specifically induced by MT treatment compared with salt stress. These MT-responsive differentially expressed genes include basal metabolic pathway genes, such as "ribosome, elongation factor," "sugar and lipid metabolism," and "photosynthesis" and stress-related genes encoding "membrane integrity" related proteins, heat shock protein, peroxidase/oxidoreductase, and protease. Several abiotic stress response-related genes, such as DRE, ARF, HD-ZF, MYB, and REM were repressed by NaCl treatment while induced by MT treatment. In summary, we demonstrated the importance of MsPMTR1 in MT-mediated salt tolerance in alfalfa, and we also analyzed the regulatory mechanism of MT during alfalfa seed germination under salt stress.

Identification of diagnostic and prognostic signatures derived from preoperative blood parameters for oral squamous cell carcinoma.

BACKGROUND: We aimed to develop novel diagnostic and prognostic signatures based on preoperative inflammatory, immunological, and nutritional parameters in blood (PIINPBs) by machine learning algorithms for patients with oral squamous cell carcinoma (OSCC). METHODS: A total of 486 OSCC patients and 200 age and gender-matched non-OSCC patients who were diagnosed and treated at our institution for noninfectious, nontumor diseases were retrospectively enrolled and divided into training and validation cohorts. Based on PIINPB, 6 machine learning classifiers including random forest, support vector machine, extreme gradient boosting, naive Bayes, neural network, and logistic regression were used to derive diagnostic models, while least absolute shrinkage and selection operator (LASSO) analyses were employed to construct prognostic signatures. A novel prognostic nomogram integrating a PIINPB-derived prognostic signature and selected clinicopathological parameters was further developed. Performances of these signatures were assessed by receiver operating characteristic (ROC) curves, calibrating curves, and decision tree. RESULTS: Diagnostic models developed by machine learning algorithms from 13 PIINPBs, which included counts of white blood cells (WBC), neutrophils (N), monocytes (M), lymphocytes (L), platelets (P), albumin (ALB), and hemoglobin (Hb), along with albumin-globulin ratio (A/G), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), displayed satisfactory discriminating capabilities in patients with or without OSCC, and among OSCC patients with diverse pathological grades and clinical stages. A prognostic signature based on 6 survival-associated PIINPBs (L, P, PNI, LMR, SII, A/G) served as an independent factor to predict patient survival. Moreover, a novel nomogram integrating prognostic signature and tumor size, pathological grade, cervical node metastasis, and clinical stage significantly enhanced prognostic power [3-year area under the curve (AUC) =0.825; 5-year AUC =0.845]. CONCLUSIONS: Our results generated novel and robust diagnostic and prognostic signatures derived from PIINPBs by machine learning for OSCC. Performance of these signatures suggest the potential for PIINPBs to supplement current regimens and provide better patient stratification and prognostic prediction.

Immune landscape and subtypes in primary resectable oral squamous cell carcinoma: prognostic significance and predictive of therapeutic response.

BACKGROUND: Immune landscape of cancer has been increasingly recognized as a key feature affecting disease progression, prognosis and therapeutic response. Here, we sought to comprehensively characterize the patterns of tumor-infiltrating immune cells (TIIs) in primary oral squamous cell carcinoma (OSCC) and develop immune features-derived models for prognostication and therapeutic prediction. METHODS: A total number of 392 patients with OSCC receiving ablative surgery at three independent centers were retrospectively enrolled and defined as training, testing and validation cohorts. Detailed features of 12 types of TIIs at center of tumor and invasive margin were assessed by immunohistochemistry coupled with digital quantification. TIIs abundance in OSCC was also estimated by bioinformatics approaches using multiple publicly available data sets. Prognostic models based on selected immune features were trained via machine learning approach, validated in independent cohorts and evaluated by time-dependent area under the curves and concordance index (C-index). Immune types of OSCC were further identified by consensus clustering and their associations with genetic, molecular features and patient survival were clarified. RESULTS: Patterns of TIIs infiltration varied among patients and dynamically evolved along with tumor progression. Prognostic models based on selected TIIs were identified as efficient and sensitive biomarkers to stratify patients into subgroups with favorable or inferior survival as well as responders or non-responders to postoperative radiotherapy or immunotherapy. These models outperformed multiple conventional biomarkers and immune-related scores in prognostic prediction. Furthermore, we identified two main immune subtypes of OSCC (immune-hot and immune-cold) which harbored characteristic TIIs infiltrations and genomic and molecular features, and associated with patient survival. CONCLUSIONS: Our results delineated immune landscape and subtypes in OSCC, consolidated their clinical values as robust biomarkers to predict patient survival and therapeutic benefits and reinforced key roles of TIIs and tumor-immune interactions underlying oral tumorigenesis, ultimately facilitating development of tailed immunotherapeutic strategies.

Host sunflower-induced silencing of parasitism-related genes confers resistance to invading Orobanche cumana.

Orobanche cumana is a holoparasitic plant that attaches to host-plant roots and seriously reduces the yield of sunflower (Helianthus annuus L.). Effective control methods are lacking with only a few known sources of genetic resistance. In this study, a seed-soak agroinoculation (SSA) method was established, and recombinant tobacco rattle virus vectors were constructed to express RNA interference (RNAi) inducers to cause virus-induced gene silencing (VIGS) in sunflower. A host target gene HaTubulin was systemically silenced in both leaf and root tissues by the SSA-VIGS approach. Trans-species silencing of O. cumana genes were confirmed for 10 out of 11 target genes with silencing efficiency of 23.43%-92.67%. Knockdown of target OcQR1, OcCKX5, and OcWRI1 genes reduced the haustoria number, and silencing of OcEXPA6 caused further phenotypic abnormalities such as shorter tubercles and necrosis. Overexpression of OcEXPA6 caused retarded root growth in alfalfa (Medicago sativa). The results demonstrate that these genes play an important role in the processes of O. cumana parasitism. High-throughput small RNA (sRNA) sequencing and bioinformatics analyses unveiled the distinct features of target gene-derived siRNAs in O. cumana such as siRNA transitivity, strand polarity, hotspot region, and 21/22-nt siRNA predominance, the latter of which was confirmed by Northern blot experiments. The possible RNAi mechanism is also discussed by analyzing RNAi machinery genes in O. cumana. Taken together, we established an efficient host-induced gene silencing technology for both functional genetics studies and potential control of O. cumana. The ease and effectiveness of this strategy could potentially be useful for other species provided they are amenable to SSA.

Improvement of host-induced gene silencing efficiency via polycistronic-tRNA-amiR expression for multiple target genes and characterization of RNAi mechanism in Mythimna separata.

Host-induced gene silencing (HIGS) emerged as a new strategy for pest control. However, RNAi efficiency is reported to be low in Lepidoptera, which are composed of many important crop pests. To address this, we generated transgenic plants to develop HIGS effects in a maize pest, Mythimna separata (Lepidoptera, Noctuidae), by targeting chitinase encoding genes. More importantly, we developed an artificial microRNA (amiR) based PTA (polycistronic-tRNA-amiR) system for silencing multiple target genes. Compared with hpRNA (hairpin RNA), transgenic expression of a PTA cassette including an amiR for the gut-specific dsRNA nuclease gene MsREase, resulted in improved knockdown efficiency and caused more pronounced developmental abnormalities in recipient insects. When target gene siRNAs were analysed after HIGS and direct dsRNA/siRNA feeding, common features such as sense polarity and siRNA hotspot regions were observed, however, they differed in siRNA transitivity and major 20-24nt siRNA species. Core RNAi genes were identified in M. separata, and biochemical activities of MsAGO2, MsSID1 and MsDcr2 were confirmed by EMSA (electrophoretic mobility shift assay) and dsRNA cleavage assays, respectively. Taken together, we provide compelling evidence for the existence of the RNAi mechanism in M. separata by analysis of both siRNA signatures and RNAi machinery components, and the PTA system could potentially be useful for future RNAi control of lepidopteran pests.

Ethylene Enhances Seed Germination and Seedling Growth Under Salinity by Reducing Oxidative Stress and Promoting Chlorophyll Content via ETR2 Pathway.

Alfalfa (Medicago sativa L.) is an important forage, and salinity is a major stress factor on its yield. In this study, we show that osmotic stress retards alfalfa seedling growth, while ionic/oxidative stress reduces its seed germination. Ethylene treatment can recover the germination rate of alfalfa seeds under salt stress, while ethylene inhibitor silver thiosulfate exacerbates salt effects. ETH reduces the accumulation of MDA and H2O2 and increases POD activity. ETH and ACC improve the salt tolerance of alfalfa by increasing proline content under salt stress. In contrast, STS inhibits alfalfa seed germination by reducing POD activity. NaCl treatment reduces chlorophyll content in alfalfa leaves, while ETH and ACC can increase the chlorophyll content and promote seedling growth. ETH promotes the growth of alfalfa in saline condition by reducing the expression of MsACO and MsERF8 genes, while increases its germination rate by upregulating MsERF11 gene. Silencing of MsETR2, a putative ethylene receptor gene in alfalfa, abolishes ethylene triggered tolerance to salt stress. In summary, we show that ethylene improves salt tolerance in alfalfa via MsETR2 dependent manner, and we also analyze the regulatory mechanism of ethylene during germination of alfalfa seeds under salt stress.

The role of NAC transcription factor in plant cold response.

The NAC transcription factor (TF) is one of the largest families of TFs in plants and plays an important role in plant growth, development, and response to environmental stress. The structural and functional characteristics of NAC TFs have been uncovered in the past years, including sequence binding features of the DNA-binding domain located in the N-terminus and dynamic interplay between the domain located at the C-terminus and other proteins. Studies on NAC TF are increasing in number; these studies distinctly contribute to our understanding of the regulatory networks of NAC-mediated complex signaling and transcriptional reprogramming. Previous studies have indicated that NAC TFs are key regulators of the plant stress response. However, these studies have been for six years so far and mainly focused on drought and salt stress. There are relatively few reports about NAC TFs in plant cold signal pathway and no related reviews have been published. In this review article, we summarize the structural features of NAC TFs, the target genes, upstream regulators and interaction proteins of stress-responsive NAC TFs, and the roles NAC TFs play in plant cold stress signal pathway.

Predictive value of prognostic nutritional index in patients with oral squamous cell carcinoma.

OBJECTIVES: To determine the prognostic significance of preoperative prognostic nutritional index (PNI) in patients with primary oral squamous cell carcinoma (OSCC) after ablative surgery. MATERIALS AND METHODS: A total of 333 patients from two tertiary referral centers were enrolled as training and validation cohorts. The PNI was calculated as 10× serum albumin (g/dL) + 0.005 × total lymphocyte number (per mm3 ), and its optimal cutoff value for patient stratification was identified by X-tile software. Cox's proportional regression analyses and receiver operating characteristic (ROC) curves were employed to identify prognostic factors and their predictive performance. RESULTS: The optimal cutoff value of PNI was 47.4. Patients with low PNI had significantly shorter overall (OS) and disease-free survival than those with high PNI. Moreover, multivariate regression analyses indicated that PNI was an independent prognostic factor for OS in the training (hazard ratio [HR], 2.267; 95% confidence interval [CI]:1.335-3.849; p = .002) and validation (HR, 2.247; 95% CI: 1.352-3.735; p = .002) cohorts. ROC analyses revealed similar or superior predictive performance of PNI as compared to other prognostic parameters. CONCLUSIONS: Our findings reveal that decreased preoperative PNI significantly associates with worse prognosis for patients with OSCC, which serves as a novel prognostic biomarker for OSCC.

Corrigendum: Ethylene Enhances Seed Germination and Seedling Growth Under Salinity by Reducing Oxidative Stress and Promoting Chlorophyll Content via ETR2 Pathway.

[This corrects the article DOI: 10.3389/fpls.2020.01066.].

Development and validation of a seven-immune-feature-based prognostic score for oral squamous cell carcinoma after curative resection.

Immune infiltrates have been increasingly recognized as robust prognostic factors for human cancer. Here, we developed and validated a seven-immune-feature-based prognostic score (7IFBPS) for patients with oral squamous cell carcinoma (OSCC) after curative resection. Fourteen immune features regarding detailed locations and densities of seven types of tumor-infiltrating immune cells (TIIs) were characterized in clinical samples from 269 eligible patients in three independent cohorts by immunohistochemistry coupled with digital quantitation. Optimal cutoff values for individual immune features were yielded using X-tile software. The 7IFBPS was constructed by Kaplan-Meier and Cox regression model in training cohort and verified in testing, validation and combined cohorts. Concordance index (C-index), receiver operating characteristics and calibration curves were employed to define the performance of 7IFBPS in prognostic prediction. High CD3 IM (invasive margin), CD3 CT (center of tumor), CD8 CT, CD45RO IM, CD45RO CT, FOXP3 IM and FOXP3 CT significantly associated with improved survival. The 7IFBPS score was calculated using the formula: 1.041 × CD3 IM + 1.24 × CD3 CT + 1.701 × CD8 CT + 1.127 × CD45RO IM + 1.348 × CD45RO CT + 1.089 × FOXP3 IM + 1.483 FOXP3 CT. High 7IFBPS significantly associated with improved survival in all cohorts and served as an independent prognostic predictor. The C-index of 7IFBPS for predicting survival was 0.668 (95% CI, 0.609-0.726). Calibration curves for survival probability showed good agreement between prediction by 7IFBPS and actual observation. Collectively, our findings established the 7IFBPS as a novel powerful prognostic classifier for resectable OSCC. It holds potentials to be incorporated into current prognostic regime to better patient stratification.

Therapeutically targeting head and neck squamous cell carcinoma through synergistic inhibition of LSD1 and JMJD3 by TCP and GSK-J1.

BACKGROUND: The histone demethylase LSD1 is a key mediator driving tumorigenesis, which holds potential as a promising therapeutic target. However, treatment with LSD1 inhibitors alone failed to result in complete cancer regression. METHODS: The synergistic effects of TCP (a LSD1 inhibitor) and GSK-J1 (a JMJD3 inhibitor) against HNSCC were determined in vitro and in preclinical animal models. Genes modulated by chemical agents or siRNAs in HNSCC cells were identified by RNA-seq and further functionally interrogated by bioinformatics approach. Integrative siRNA-mediated gene knockdown, rescue experiment and ChIP-qPCR assays were utilised to characterise the mediators underlying the therapeutic effects conferred by TCP and GSK-J1. RESULTS: Treatment with TCP and GSK-J1 impaired cell proliferation, induced apoptosis and senescence in vitro, which were largely recapitulated by simultaneous LSD1 and JMJD3 knockdown. Combinational treatment inhibited tumour growth and progression in vivo. Differentially expressed genes modulated by TCP and GSK-J1 were significantly enriched in cell proliferation, apoptosis and cancer-related pathways. SPP1 was identified as the mediator of synergy underlying the pro-apoptosis effects conferred by TCP and GSK-J1. Co-upregulation of LSD1 and JMJD3 associated with worse prognosis in patients with HNSCC. CONCLUSIONS: Our findings revealed a novel therapeutic strategy of simultaneous LSD1 and JMJD3 inhibition against HNSCC.

Identification of a prognostic alternative splicing signature in oral squamous cell carcinoma.

Alternative splicing (AS) is critically associated with tumorigenesis and patient's prognosis. Here, we systematically analyzed survival-associated AS signatures in oral squamous cell carcinoma (OSCC) and evaluated their prognostic predictive values. Survival-related AS events were identified by univariate and multivariate Cox regression analyses using OSCC data from the TCGA head neck squamous cell carcinoma data set. The Percent Spliced In calculated by SpliceSeq from 0 to 1 was used to quantify seven types of AS events. A predictive model based on AS events was constructed by least absolute shrinkage and selection operator Cox regression assay and further validated using a training-testing cohort design. Patient survival was estimated using the Kaplan-Meier method and compared with Log-rank test. The receiver operating characteristics curve area under the curves was used to evaluate the predictive abilities of these predictive models. Furthermore, gene-gene interaction networks and the splicing factors (SFs)-AS regulatory network was generated by Cytoscape. A total of 825 survival-related AS events within 719 genes were identified in OSCC samples. The integrative predictive model was better at predicting outcomes of patients as compared to those models built with the individual AS event. The predictive model based on three AS-related genes also effectively predicted patients' survival. Moreover, seven survival-related SFs were detected in OSCC including RBM4, HNRNPD, and HNRNPC, which have been linked to tumorigenesis. The SF-AS network revealed a significant correlation between survival-related AS genes and these SFs. Our findings revealed a systemic portrait of survival-associated AS events and the splicing network in OSCC, suggesting that AS events might serve as novel prognostic biomarkers and therapeutic targets for OSCC.