Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

FAT1 as a tumor mutation burden specific gene affects the immunotherapy effect in head and neck squamous cell cancer

BACKGROUND

Response to immunotherapy is the main challenge of head and neck squamous cancer (HNSCC) treatment. Previous studies have indicated that tumor mutational burden (TMB) is associated with prognosis, but it is not always a precise index. Hence, investigating specific genetic mutations and tumor microenvironment (TME) changes in TMB-high patients is essential for precision therapy of HNSCC.

METHODS

A total of 33 HNSCC patients were enrolled in this study. We calculated the TMB score based on next-generation sequencing (NGS) sequencing and grouped these patients based on TMB score. Then, we examined the immune microenvironment of HNSCC using assessments of the bulk transcriptome and the single-cell RNA sequence (scRNA-seq) focusing on the molecular nature of TMB and mutations in HNSCC from our cohort. The association of the mutation pattern and TMB was analyzed in The Cancer Genome Atlas (TCGA) and validated by our cohort.

RESULTS

33 HNSCC patients were divided into three groups (TMB-low, -medium, and -high) based on TMB score. In the result of 520-gene panel sequencing data, we found that FAT1 and LRP1B mutations were highly prevalent in TMB-high patients. FAT1 mutations are associated with resistance to immunotherapy in HNSCC patients. This involves many metabolism-related pathways like RERE, AIRE, HOMER1, etc. In the scRNA-seq data, regulatory T cells (Tregs), monocytes, and DCs were found mainly enriched in TMB-high samples.

CONCLUSION

Our analysis unraveled the FAT1 gene as an assistant predictor when we use TMB as a biomarker of drug resistance in HNSCC. Tregs, monocytes, and dendritic cells (DCs) were found mainly enriched in TMB-high samples.

Tumor-specific T cells in head and neck cancer have rescuable functionality and can be identified through single-cell co-culture

BACKGROUND

Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) remains a treatment-resistance disease with limited response to immunotherapy. While T cells in HNSCC are known to display phenotypic dysfunction, whether they retain rescuable functional capacity and tumor-killing capability remains unclear.

METHODS

To investigate the functionality and tumor-specificity of tumor-infiltrating lymphocytes (TILs) across HNSCCs, malignant cell lines and TILs were derived from 31 HPV-negative HNSCCs at the time of standard surgical resection. T cell functional capacity was evaluated through ex vivo expansion, immunophenotyping, and IsoLight single-cell proteomics. Tumor-specificity was investigated through both bulk and single-cell tumor-TIL co-culture.

RESULTS

TILs could be successfully generated from 24 patients (77%), including both previously untreated and radiation recurrent HNSCCs. We demonstrate that across HNSCCs, TILs express multiple exhaustion markers but maintain a predominantly effector memory phenotype. After ex vivo expansion, TILs retain immunogenic functionality even from radiation-resistant, exhausted, and T cell-depleted disease. We further demonstrate tumor-specificity of T cells across HNSCC patients through patient-matched malignant cell-T cell co-culture. Finally, we use optofluidic technology to establish an autologous single tumor cell-single T cell co-culture platform for HNSCC. Cells derived from three HNSCC patients underwent single-cell co-culture which enabled identification and visualization of individual tumor-killing TILs in real-time in all patients.

CONCLUSIONS

These studies show that cancer-specific T cells exist across HNSCC patients with rescuable immunogenicity and can be identified on a single-cell level. These data lay the foundation for development of patient-specific T cell immunotherapies in HNSCC.

Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes

Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.

Developing and validating the model of tumor-infiltrating immune cell to predict survival in patients receiving radiation therapy for head and neck squamous cell carcinoma

Background

Radiotherapy (RT) is a mainstay of head and neck squamous cell carcinoma (HNSCC) treatment. Due to the influence of RT on tumor cells and immune/stromal cells in microenvironment, some studies suggest that immunologic landscape could shape treatment response. To better predict the survival based on genomic data, we developed a prognostic model using tumor-infiltrating immune cell (TIIC) signature to predict survival in patients undergoing RT for HNSCC.

Methods

Gene expression data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Data from HNSCC patients undergoing RT were extracted for analysis. TIICs prevalence in HNSCC patients was quantified by gene set variation analysis (GSVA) algorithm. TIICs and post-RT survival were analyzed using univariate Cox regression analysis and used to construct and validate a tumor-infiltrating cells score (TICS).

Results

Five of 26 immune cells were significantly associated with HNSCC prognosis in the training cohort (all P<0.05). Kaplan-Meier (KM) survival curves showed that patients in the high TICS group had better survival outcomes (log-rank test, P<0.05). Univariate analyses demonstrated that the TICS had independent prognostic predictive ability for RT outcomes (P<0.05). Patients with high TICS scores showed significantly higher expression of immune-related genes. Functional pathway analyses further showed that the TICS was significantly related to immune-related biological process. Stratified analyses supported integrating TICS and tumor mutation burden (TMB) into individualized treatment planning, as an adjunct to classification by clinical stage and human papillomavirus (HPV) infection.

Conclusions

The TICS model supports a personalized medicine approach to RT for HNSCC. Increased prevalence of TIIC within the tumor microenvironment (TME) confers a better prognosis for patients undergoing treatment for HNSCC.

Life quality improvement of patients with non-small cell lung cancer undergoing targeted therapy: A case study of continuous care

To investigate the improvement effect of targeted therapy on non-small cell carcinoma patients life quality after the continuous nursing intervention. 104 non-small cell lung cancer patients in our hospital from July 2017 to November 2019 were allocated evenly and randomly into the control group (C) and the study group (S). By using clinical baseline data, quality of life questionnaire core 30 for cancer patients, evaluation of patient compliance behavior, the MOS item short-form health survey (SF-36), self rating depression scale (SDS), self rating anxiety scale (SAS), Overall Survival (OS) progression-free survival and adverse reaction symptoms were evaluated for the life quality of patients. There was comparability between the 2 sets of basic data. There was no significant difference in quality of life questionnaire core 30, SF-36, SAS, or SDS scores before treatment. After 3 months, there was a significant difference in the scores of various scales before treatment. At the same time, there was significant statistical significance before and after treatment in Group S. Their compliance rates were 84.62% and 98.08%. Adverse reactions incidence in Group S was lower. Taking a 2-year follow-up period as an example, significant statistical differences existed in OS and progression-free survival rates between adenocarcinoma and squamous carcinoma. SDS and SAS had high consistency in scoring with QLQ-30 and SF-36 scales. Targeted treatment for non-small cell carcinoma patients significantly improves their life quality and reduces the incidence of adverse reactions after continuous nursing intervention.

Cancer stem cells of head and neck squamous cell carcinoma; distance towards clinical application; a systematic review of literature

Head and neck squamous cell carcinoma (HNSCC) is the major pathological type of head and neck cancer (HNC). The disease ranks sixth among the most common malignancies worldwide, with an increasing incidence rate yearly. Despite the development of therapy, the prognosis of HNSCC remains unsatisfactory, which may be attributed to the resistance to traditional radio-chemotherapy, relapse, and metastasis. To improve the diagnosis and treatment, the targeted therapy for HNSCC may be successful as that for some other tumors. Nanocarriers are the most effective system to deliver the anti-cancerous agent at the site of interest using passive or active targeting approaches. The system enhances the drug concentration in HCN target cells, increases retention, and reduces toxicity to normal cells. Among the different techniques in nanotechnology, quantum dots (QDs) possess multiple fluorescent colors emissions under single-source excitation and size-tunable light emission. Dendrimers are the most attractive nanocarriers, which possess the desired properties of drug retention, release, unaffecting by the immune system, blood circulation time enhancing, and cells or organs specific targeting properties. In this review, we have discussed the up-to-date knowledge of the Cancer Stem Cells of Head and Neck Squamous Cell Carcinoma. Although a lot of data is available, still much more efforts remain to be made to improve the treatment of HNSCC.

Effective TME-related signature to predict prognosis of patients with head and neck squamous cell carcinoma

Introduction: The tumor microenvironment (TME) is crucial for the development of head and neck squamous cell carcinoma (HNSCC). However, the correlation of the characteristics of the TME and the prognosis of patients with HNSCC remains less known. Methods: In this study, we calculated the immune and stromal cell scores using the "estimate" R package. Kaplan-Meier survival and CIBERSORT algorithm analyses were applied in this study. Results: We identified seven new markers: FCGR3B, IGHV3-64, AC023449.2, IGKV1D-8, FCGR2A, WDFY4, and HBQ1. Subsequently, a risk model was constructed and all HNSCC samples were grouped into low- and high-risk groups. The results of both the Kaplan-Meier survival and receiver operating characteristic curve (ROC) analyses showed that the prognosis indicated by the model was accurate (0.758, 0.756, and 0.666 for 1-, 3- and 5-year survival rates). In addition, we applied the CIBERSORT algorithm to reveal the significant differences in the infiltration levels of immune cells between the two risk groups. Discussion: Our study elucidated the roles of the TME and identified new prognostic biomarkers for patients with HNSCC.

Clinical plasma cells-related genes to aid therapy in colon cancer

The tumor immune microenvironment (TIME) of colon cancer (CC) has been associated with extensive immune cell infiltration (IMI). Increasing evidence demonstrated that plasma cells (PC) have an extremely important role in advance of antitumor immunity. Nonetheless, there is a lack of comprehensive analyses of PC infiltration in clinical prognosis and immunotherapy in CC. This study systematically addressed the gene expression model and clinical information of CC patients. Clinical samples were obtained from the TCGA (The Cancer Genome Atlas) databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), GSVA, and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were employed to research the potential mechanism and pathways. Immunophenoscore (IPS) was obtained to evaluate the immunotherapeutic significance of risk score. Half maximal inhibitory concentration (IC50) of chemotherapeutic medicine was predicted by employing the pRRophetic algorithm. A total of 513 CC samples (including 472 tumor samples and 41 normal samples) were collected from the TCGA-GDC database. Significant black modules and 313 candidate genes were considered PC-related genes by accessing WGCNA. Five pivotal genes were established through multiple analyses, which revealed excellent prognostic. The underlying correlation between risk score with tumor mutation burden (TMB) was further explored. In addition, the risk score was obviously correlated with various tumor immune microenvironment (TIME). Also, risk CC samples showed various signaling pathways activity and different pivotal sensitivities to administering chemotherapy. Finally, the biological roles of the CD177 gene were uncovered in CC.

Data mining on identifying diagnosis and prognosis biomarkers in head and neck squamous carcinoma

Head and neck squamous carcinoma (HNSC) induces high cancer-related death worldwide. The biomarker screening on diagnosis and prognosis is of great importance. This research is aimed to explore the specific diagnostic and prognostic biomarkers for HNSC through bioinformatics analysis. The mutation and dysregulation data were acquired from UCSC Xena and TCGA databases. The top ten genes with mutation frequency in HNSC were TP53 (66%), TTN (35%), FAT1 (21%), CDKN2A (20%), MUC16 (17%), CSMD3 (16%), PIK3CA (16%), NOTCH1 (16%), SYNE1 (15%), LRP1B (14%). A total of 1,060 DEGs were identified, with 396 up-regulated and 665 downregulated in HNSC patients. Patients with lower expression of ACTN2 (P = 0.039, HR = 1.3), MYH1 (P = 0.005, HR = 1.5), MYH2 (P = 0.035, HR = 1.3), MYH7 (P = 0.053, HR = 1.3), and NEB (P = 0.0043, HR = 1.5) exhibit longer overall survival time in HNSC patients. The main DEGs were further analyzed by pan-cancer expression and immune cell infiltration analyses. MYH1, MYH2, and MYH7 were dysregulated in the cancers. Compared with HNSC, their expression levels are lower in the other types of cancers. MYH1, MYH2, and MYH7 were expected to be the specific diagnostic and prognostic molecular biomarkers of HNSC. All five DEGs have a significant positive correlation with CD4+T cells and macrophages.

Genomic landscape and gene expression profiles of feline oral squamous cell carcinoma

Feline oral squamous cell carcinoma (FOSCC) is a cancer of the squamous cell lining in the oral cavity and represents up to 80% of all oral cancers in cats, with a poor prognosis. We have used whole exome sequencing (WES) and RNA sequencing of the tumor to discover somatic mutations and gene expression changes that may be associated with FOSCC occurrence. FOSCC offers a potential comparative model to study human head and neck squamous cell carcinoma (HNSCC) due to its similar spontaneous formation, and morphological and histological features. In this first study using WES to identify somatic mutations in feline cancer, we have identified tumor-associated gene mutations in six cats with FOSCC and found some overlap with identified recurrently mutated genes observed in HNSCC. Four samples each had mutations in TP53, a common mutation in all cancers, but each was unique. Mutations in other cellular growth control genes were also found such as KAT2B and ARID1A. Enrichment analysis of FOSCC gene expression profiles suggests a molecular similarity to human OSCC as well, including alterations in epithelial to mesenchymal transition and IL6/JAK/STAT pathways. In this preliminary study, we present exome and transcriptome results that further our understanding of FOSCC.

Pembrolizumab and cabozantinib in recurrent metastatic head and neck squamous cell carcinoma: a phase 2 trial

Anti-programmed cell death protein 1 (PD-1) therapy is a standard of care in recurrent metastatic head and neck squamous cell carcinoma (RMHNSCC). Vascular endothelial growth factor inhibitors, including tyrosine kinase inhibitors, have immunomodulatory properties and have offered promising results when combined with anti-PD-1 agents. We conducted a phase 2, multicenter, single-arm trial of pembrolizumab and cabozantinib in patients with RMHNSCC who had Response Evaluation Criteria in Solid Tumors v.1.1 measurable disease and no contraindications to either agent. We assessed the primary end points of tolerability and overall response rate to the combination with secondary end points of progression-free survival and overall survival and performed correlative studies with PDL-1 and combined positive score, CD8+ T cell infiltration and tumor mutational burden. A total of 50 patients were screened and 36 were enrolled with 33 evaluable for response. The primary end point was met, with 17 out of 33 patients having a partial response (52%) and 13 (39%) stable disease with an overall clinical benefit rate of 91%. Median and 1-year overall survival were 22.3 months (95% confidence interval (CI) = 11.7-32.9) and 68.4% (95% CI = 45.1%-83.5%), respectively. Median and 1-year progression-free survival were 14.6 months (95% CI = 8.2-19.6) and 54% (95% CI = 31.5%-72%), respectively. Grade 3 or higher treatment-related adverse events included increased aspartate aminotransferase (n = 2, 5.6%). In 16 patients (44.4%), the dose of cabozantinib was reduced to 20 mg daily. The overall response rate correlated positively with baseline CD8+ T cell infiltration. There was no observed correlation between tumor mutational burden and clinical outcome. Pembrolizumab and cabozantinib were well tolerated and showed promising clinical activity in patients with RMHNSCC. Further investigation of similar combinations are needed in RMHNSCC. The trial is registered at ClinicalTrials.gov under registration no. NCT03468218 .

Circadian rhythm-related genes index: A predictor for HNSCC prognosis, immunotherapy efficacy, and chemosensitivity

Background

Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and is highly aggressive and heterogeneous, leading to variable prognosis and immunotherapy outcomes. Circadian rhythm alterations in tumourigenesis are of equal importance to genetic factors and several biologic clock genes are considered to be prognostic biomarkers for various cancers. The aim of this study was to establish reliable markers based on biologic clock genes, thus providing a new perspective for assessing immunotherapy response and prognosis in patients with HNSCC.

Methods

We used 502 HNSCC samples and 44 normal samples from the TCGA-HNSCC dataset as the training set. 97 samples from GSE41613 were used as an external validation set. Prognostic characteristics of circadian rhythm-related genes (CRRGs) were established by Lasso, random forest and stepwise multifactorial Cox. Multivariate analysis revealed that CRRGs characteristics were independent predictors of HNSCC, with patients in the high-risk group having a worse prognosis than those in the low-risk group. The relevance of CRRGs to the immune microenvironment and immunotherapy was assessed by an integrated algorithm.

Results

6-CRRGs were considered to be strongly associated with HNSCC prognosis and a good predictor of HNSCC. The riskscore established by the 6-CRRG was found to be an independent prognostic factor for HNSCC in multifactorial analysis, with patients in the low-risk group having a higher overall survival (OS) than the high-risk group. Nomogram prediction maps constructed from clinical characteristics and riskscore had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and immune checkpoint expression and were more likely to benefit from immunotherapy.

Conclusion

6-CRRGs play a key predictive role for the prognosis of HNSCC patients and can guide physicians in selecting potential responders to prioritise immunotherapy, which could facilitate further research in precision immuno-oncology.

Improving head and neck cancer therapies by immunomodulation of the tumour microenvironment

Targeted immunotherapy has improved patient survival in head and neck squamous cell carcinoma (HNSCC), but less than 20% of patients produce a durable response to these treatments. Thus, new immunotherapies that consider all key players of the complex HNSCC tumour microenvironment (TME) are necessary to further enhance tumour-specific T cell responses in patients. HNSCC is an ideal tumour type in which to evaluate immune and non-immune cell differences because of two distinct TME aetiologies (human papillomavirus (HPV)-positive and HPV-negative disease), multiple anatomic sites for tumour growth, and clear distinctions between patients with locally advanced disease and those with recurrent and/or metastatic disease. Recent technological and scientific advancements have provided a more complete picture of all cellular constituents within this complex TME and have evaluated the interplay of both immune and non-immune cells within HNSCC. Here, we include a comprehensive analysis of the complete ecosystem of the HNSCC TME, performed utilizing data-rich resources such as The Cancer Genome Atlas, and cutting-edge techniques, such as single-cell RNA sequencing, high-dimensional flow cytometry and spatial multispectral imaging, to generate improved treatment strategies for this diverse disease.

Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer

As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including SERPINE1, FEN1, PDGFRB, SNCG, TCF3, and APOC3. The TCGA-STAD cohort was utilized as a training set while the GSE84437 and GSE13861 cohorts were analyzed for validation. Immune cell infiltration and immunotherapy efficacy were investigated in the PRJEB25780 cohort. Data from the genomics of drug sensitivity in cancer (GDSC) database revealed pharmacological response. The GSE13861 and GSE54129 cohorts, single-cell dataset GSE134520, and The Human Protein Atlas (THPA) database were utilized for localization of the key senescence-related genes. Association of a higher risk-score with worse overall survival (OS) was identified in the training cohort (TCGA-STAD, P<0.001; HR = 2.03, 95% CI, 1.45-2.84) and the validation cohorts (GSE84437, P = 0.005; HR = 1.48, 95% CI, 1.16-1.95; GSE13861, P = 0.03; HR = 2.23, 95% CI, 1.07-4.62). The risk-score was positively correlated with densities of tumor-infiltrating immunosuppressive cells (P < 0.05) and was lower in patients who responded to pembrolizumab monotherapy (P = 0.03). Besides, patients with a high risk-score had higher sensitivities to the inhibitors against the PI3K-mTOR and angiogenesis (P < 0.05). Expression analysis verified the promoting roles of FEN1, PDGFRB, SERPINE1, and TCF3, and the suppressing roles of APOC3 and SNCG in GC, respectively. Immunohistochemistry staining and single-cell analysis revealed their location and potential origins. Taken together, the senescence gene-based model may potentially change the management of GC by enabling risk stratification and predicting response to systemic therapy.

Establishment and validation of a ferroptosis-related prognostic signature for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with high heterogeneity. The prognosis of HCC is quite poor and the prognostic prediction also has challenges. Ferroptosis is recently recognized as a kind of iron-dependent cell death, which is involved in tumor progression. However, further study is needed to validate the influence of drivers of ferroptosis (DOFs) on the prognosis of HCC.

Methods

The FerrDb database and the Cancer Genome Atlas (TCGA) database were applied to retrieve DOFs and information of HCC patients respectively. HCC patients were randomly divided into training and testing cohorts with a 7:3 ratio. Univariate Cox regression, LASSO and multivariate Cox regression analyses were carried out to identify the optimal prognosis model and calculate the risk score. Then, univariate and multivariate Cox regression analyses were performed to assess the independence of the signature. At last, gene functional, tumor mutation and immune-related analyses were conducted to explore the underlying mechanism. Internal and external databases were used to confirm the results. Finally, the tumor tissue and normal tissue from HCC patients were applied to validate the gene expression in the model.

Results

Five genes were identified to develop as a prognostic signature in the training cohort relying on the comprehensive analysis. Univariate and multivariate Cox regression analyses confirmed that the risk score was able to be an independent factor for the prognosis of HCC patients. Low-risk patients showed better overall survival than high-risk patients. Receiver operating characteristic (ROC) curve analysis confirmed the signature's predictive capacity. Furthermore, internal and external cohorts were consistent with our results. There was a higher proportion of nTreg cell, Th1 cell, macrophage, exhausted cell and CD8⁺T cell in the high-risk group. The Tumor Immune Dysfunction and Exclusion (TIDE) score suggested that high-risk patients could respond better to immunotherapy. Besides, the experimental results showed that some genes were differentially expressed between tumor and normal tissues.

Conclusion

In summary, the five ferroptosis gene signature showed potential in prognosis of patients with HCC and could also be regarded as a value biomarker for immunotherapy response in these patients.

Simultaneous metabolite MALDI-MSI, whole exome and transcriptome analysis from formalin-fixed paraffin-embedded tissue sections

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) allows spatial analysis of proteins, metabolites, or small molecules from tissue sections. Here, we present the simultaneous generation and analysis of MALDI-MSI, whole-exome sequencing (WES), and RNA-sequencing data from the same formalin-fixed paraffin-embedded (FFPE) tissue sections. Genomic DNA and total RNA were extracted from (i) untreated, (ii) hematoxylin-eosin (HE) stained, and (iii) MALDI-MSI-analyzed FFPE tissue sections from three head and neck squamous cell carcinomas. MALDI-MSI data were generated by a time-of-flight analyzer prior to preprocessing and visualization. WES data were generated using a low-input protocol followed by detection of single-nucleotide variants (SNVs), tumor mutational burden, and mutational signatures. The transcriptome was determined using 3'-RNA sequencing and was examined for similarities and differences between processing stages. All data met the commonly accepted quality criteria. Besides SNVs commonly identified between differently processed tissues, FFPE-typical artifactual variants were detected. Tumor mutational burden was in the same range for tissues from the same patient and mutational signatures were highly overlapping. Transcriptome profiles showed high levels of correlation. Our data demonstrate that simultaneous molecular profiling of MALDI-MSI-processed FFPE tissue sections at the transcriptome and exome levels is feasible and reliable.

The role of T-cells in head and neck squamous cell carcinoma: From immunity to immunotherapy

Head and neck squamous cell carcinoma (HNSCC) encompass a group of complex entities of tumours affecting the aerodigestive upper tract. The main risk factors are strongly related to tobacco and alcohol consumption, but also HPV infection is often associated. Surgery, radiotherapy and/or chemotherapy are the standard treatments, though the 5-year overall survival is less than 50%. The advances in genomics, molecular medicine, immunology, and nanotechnology have shed a light on tumour biology which helps clinical researchers to obtain more efficacious and less toxic therapies. Head and neck tumours possess different immune escape mechanisms including diminishing the immune response through modulating immune checkpoints, in addition to the recruitment and differentiation of suppressive immune cells. The insights into the HNSCC biology and its strong interaction with the tumour microenvironment highlights the role of immunomodulating agents. Recently, the knowledge of the immunological features of these tumours has paved the way for the discovery of effective biomarkers that allow a better selection of patients with odds of improving overall survival through immunotherapy. Specially biomarkers regarding immune checkpoint inhibitors antibodies, such as anti-PD-1/PD-L1 and anti-CTLA-4 in combination with standard therapy or as monotherapy. New immunotherapies to treat head and neck cancer carcinomas, such as CAR T cells and nanoparticles have been the center of attention and in this review, we discuss the necessity of finding targets for the T cell in the cancer cells to generate CAR T cells, but also the relevance of evaluating specificity and safety of those therapies.

A Four-Gene Signature Associated with Radioresistance in Head and Neck Squamous Cell Carcinoma Identified by Text Mining and Data Analysis

Purpose

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer globally, and radiotherapy plays a crucial part in its treatment. This study was designed to identify potential genes related to radiation resistance in HNSCC.

Method

We first used text mining to obtain common genes related to radiotherapy resistance and HNSCC in published articles. Functional enrichment analyses were conducted to identify the significantly enriched pathways and genes. Protein and protein interactions were performed, and the most significant gene modules were determined; then, genes in the gene modules were validated at transcriptional levels and overall survival. Gene set variation analysis (GSVA) score was calculated, and the association between GSVA score and survival/pathway was estimated. Immune cell infiltration, methylation, and genetic alteration analysis of these genes was conducted in HNSCC patients. Finally, potential sensitive anticancer drugs related to target genes were obtained.

Result

We identified 583 common genes through text mining. After further validation, a four-gene signature (EPHB2, SPP1, SERPINE1, and VEGFC) was constructed. The patients with higher GSVA scores have a worse prognosis than those with lower GSVA scores. Differences in methylation of these four genes in HNSCC tumor tissue and normal tissue were compared, with higher methylation levels of EBPH2 and SPP1 in normal tissue and higher methylation levels of SERPINE1 in the tumor. Immune cell infiltration revealed that the increased expression of these genes was closely related to the infiltration level of CD4+ T cell, neutrophil, macrophage, and dendritic cell. Thirty drugs, including 22 positively and eight negatively correlated drugs that most correlated with related genes, were available for treating HNSCC.

Conclusion

In this study, we identified four potential genes as well as corresponding drugs that might be related to radioresistance in HNSCC patients. These candidate genes may provide a promising avenue to further elevate radiotherapy efficacy.

Patient-derived head and neck tumor slice cultures: a versatile tool to study oncolytic virus action

Head and neck cancer etiology and architecture is quite diverse and complex, impeding the prediction whether a patient could respond to a particular cancer immunotherapy or combination treatment. A concomitantly arising caveat is obviously the translation from pre-clinical, cell based in vitro systems as well as syngeneic murine tumor models towards the heterogeneous architecture of the human tumor ecosystems. To bridge this gap, we have established and employed a patient-derived HNSCC (head and neck squamous cell carcinoma) slice culturing system to assess immunomodulatory effects as well as permissivity and oncolytic virus (OV) action. The heterogeneous contexture of the human tumor ecosystem including tumor cells, cancer-associated fibroblasts and immune cells was preserved in our HNSCC slice culturing approach. Importantly, the immune cell compartment remained to be functional and cytotoxic T-cells could be activated by immunostimulatory antibodies. In addition, we uncovered that a high proportion of the patient-derived HNSCC slice cultures were susceptible to the OV VSV-GP. More specifically, VSV-GP infects a broad spectrum of tumor-associated lineages including epithelial and stromal cells and can induce apoptosis. In sum, this human tumor ex vivo platform might complement pre-clinical studies to eventually propel cancer immune-related drug discovery and ease the translation to the clinics.

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer

The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.

A signature of immune-related gene pairs (IRGPs) for risk stratification and prognosis of oral cancer patients

Background

With low response to present immunotherapy, it is imperative to identify new immune-related biomarkers for more effective immunotherapies for oral cancer.

Methods

RNA profiles for 390 oral cancer patients and 32 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database and differentially expressed genes (DEGs) were analyzed. Immune genesets from ImmPort repository were overlapped with DEGs. After implementing univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, key immune-related gene pairs (IRGPs) among the overlapped DEGs for predicting the survival risk were obtained. Then, the cutoff of risk score was calculated by the receiver operating characteristic (ROC) curve to stratify oral cancer patients into high and low-risk groups. Multivariate Cox analysis was used to analyze independent prognostic indicators for oral cancer. Besides, infiltration of immune cells, functional annotation, and mutation analysis of IRGPs were conducted. Biological functions correlated with IRGPs were enriched by Gene Set Enrichment Analysis (GSEA) method.

Results

We identified 698 differentially expressed genes (DEGs) in response to oral cancer. 17 IRGPs among the DEGs were identified and integrated into a risk score model. Patients in the high-risk group have a significantly worse prognosis than those in the low-risk group in both training (P<0.001) and test (P=0.019) cohorts. Meanwhile, the IRGP model was identified as an independent prognostic factor for oral cancer. Different infiltration patterns of immune cells were found between the high- and low-risk groups that more types of T and B cells were enriched in the low-risk group. More immune-related signaling pathways were highly enriched in the low-risk group and Tenascin C (TNC) was the most frequently mutated gene. We have developed a novel 17-IRGPs signature for risk stratification and prognostic prediction of oral cancer.

Conclusion

Our study provides a foundation for improved immunotherapy and prognosis and is beneficial to the individualized management of oral cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02630-1.

A Novel Quantification System Combining iTRAQ Technology and Multi-Omics Assessment to Predict Prognosis and Immunotherapy Efficacy in Colon Cancer

Background: Colon cancer is one of the most common cancer types, although it has certain unique genetic features. This study aimed to develop a unique score for assessing prognosis and immunotherapy efficacy using integrated multi-omics analysis.

Methods: Isobaric tagging for relative and absolute quantification (iTRAQ) based proteomic analysis was used to screen differentially expressed proteins (DEP) between tumor and normal samples. DEP mRNA obtained from TCGA were clustered into different categories to show landscape-related prognosis and function. Following that, DEG was extracted from DEP mRNA, and the DEP-related score (DEPRS) was constructed to investigate the difference in immunotherapy prognosis and sensitivity. Finally, WCGNA, random forest, and artificial neural networks were used to screen for key genes. The prognostic value and protein level of these genes were validated.

Results: A total of 243 DEPs were identified through iTRAQ analysis, and the corresponding DEP mRNA was clustered into three. Following a series of tests, 1,577 DEGs were identified from overlapped DEP mRNA clusters and were classified into three gene clusters. The two types of clusters described above shared comparable characteristics in terms of prognosis and function. Then, it was established that a high DEPRS indicated a poor prognosis and DEPRS had significant associations with TMB, MSI status, and immunotherapeutic response. Finally, the key genes HART3 and FBLN2 were identified and were found to be implicated in immunotherapy and prognosis.

Conclusion: The development of a DEPRS based on multi-omics analysis will aid in improving our understanding of colon cancer and guiding a more effective immunotherapy strategy. DEPRS and key genes are used as biomarkers in the clinical evaluation of patients.

Ethanol promoting the upregulation of C-X-C Motif Chemokine Ligand 1（CXCL1） and C-X-C Motif Chemokine Ligand 6（CXCL6） in models of early alcoholic liver disease

Alcoholic liver disease (ALD) denotes a series of liver diseases caused by ethanol. Recently, immune-related genes (IRGs) play increasingly crucial role in diseases. However, it’s unclear the role of IRGs in ALD. Bioinformatic analysis was used to discern the core immune-related differential genes (IRDGs) in the present study. Subsequently, Cell Counting Kit-8 say, oil red O staining, and triglyceride detection were employed to explore optimal experimental conditions of establishing hepatocellular models of early ALD. Ultimately, real-time reverse transcription-PCR and immunohistochemistry/immunocytochemistry methods were adopted to verify the expressions of mRNA and proteins of core IRDGs, respectively. C-X-C Motif Chemokine Ligand 1 (Cxcl1) and Cxcl6 were regarded as core IRDGs via integrated bioinformatics analysis. Besides, Lieber Decarli Ethanol feeding and 200 mM and 300 mM ethanol stimulating L02 cells for 36 h can both successfully hepatocellular model. In ethanol groups, the levels of CXCL1 and CXCL6 mRNA were significantly upregulated than pair-fed groups (P < 0.0001). Also, immunohistochemistry revealed that positive particles of CXCL1 and CXCL6 in mice model of early ALD were obviously more than control groups (P < 0.0001). Besides, in L02 hepatocytes stimulated by ethanol, CXCL1 and CXCL6 mRNA were over-expressed, compared with normal L02 cells (P < 0.0001). Meanwhile, immunocytochemistry indicated that CXCL1 and CXCL6 proteins in hepatocellular model of early ALD were higher than normal L02 hepatocytes stimulus (P < 0.0001). Ethanol promoted the upregulation of Cxcl1 and Cxcl6 mRNA and proteins in models of early ALD, denoting their potentiality of acting as biomarkers of ALD.

Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

Objectives

Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients.

Methods and Results

Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis.

Conclusions

We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.

Precise Identification of Recurrent Somatic Mutations in Oral Cancer Through Whole-Exome Sequencing Using Multiple Mutation Calling Pipelines

Understanding the genomic alterations in oral carcinogenesis remains crucial for the appropriate diagnosis and treatment of oral squamous cell carcinoma (OSCC). To unveil the mutational spectrum, in this study, we conducted whole-exome sequencing (WES), using six mutation calling pipelines and multiple filtering criteria applied to 50 paired OSCC samples. The tumor mutation burden extracted from the data set of somatic variations was significantly associated with age, tumor staging, and survival. Several genes (MUC16, MUC19, KMT2D, TTN, HERC2) with a high frequency of false positive mutations were identified. Moreover, known (TP53, FAT1, EPHA2, NOTCH1, CASP8, and PIK3CA) and novel (HYDIN, ALPK3, ASXL1, USP9X, SKOR2, CPLANE1, STARD9, and NSD2) genes have been found to be significantly and frequently mutated in OSCC. Further analysis of gene alteration status with clinical parameters revealed that canonical pathways, including clathrin-mediated endocytotic signaling, NFκB signaling, PEDF signaling, and calcium signaling were associated with OSCC prognosis. Defining a catalog of targetable genomic alterations showed that 58% of the tumors carried at least one aberrant event that may potentially be targeted by approved therapeutic agents. We found molecular OSCC subgroups which were correlated with etiology and prognosis while defining the landscape of major altered events in the coding regions of OSCC genomes. These findings provide information that will be helpful in the design of clinical trials on targeted therapies and in the stratification of patients with OSCC according to therapeutic efficacy.

Combination of Tumor Mutational Burden and Specific Gene Mutations Stratifies Outcome to Immunotherapy Across Recurrent and Metastatic Head and Neck Squamous Cell Carcinoma

Purpose: To investigate the prognostic significance of tumor mutational burden (TMB) combined with specific prognosis-related gene mutations in immunotherapy for recurrent and metastatic head and neck squamous cell carcinoma (r/m HNSCC).

Methods: One hundred thirty-two r/m HNSCC patients from the Morris and Allen cohorts had undergone immunotherapy. We constructed the immunotherapy-related gene prognostic index TP-PR combining TMB and PIK3CA, TP53, or ROS1 mutation. And we analyzed the differences in overall survival (OS) and immune cell infiltration between samples in different groups. The association of each signature’s single-sample gene set enrichment analysis scores with TP-PR was tested using Spearman’s correlation test.

Results: The median OS of the patients with high TMB (TMB ≥10 mut/Mb) who received immunotherapy for r/m HNSCC was 2.5 times as long as that of the patients with low TMB (25 vs. 10 months). More importantly, the high TP-PR (TP-PR >0) group had better median OS (25 vs. 8 months) than the low TP-PR (TP-PR ≤0) group. CD8⁺ T cells and activated memory CD4⁺ T cells in the tissues of the patients with high TP-PR were higher than those in the patients with low TP-PR. Results showed that TP-PR stratification had a higher area under the curve (AUC) value (0.77, 95% CI 0.86–0.68) compared with TMB stratification (0.56, 95% CI 0.68–0.44). The differential gene expression in the high and low TP-PR groups mainly influenced metabolism-related signaling pathways.

Conclusion: TP-PR was an effective predictor of immunotherapy outcome for r/m HNSCC, which might be better than TMB alone. Patients with high TP-PR had a better survival benefit than had the patients with low TP-PR.

Characterization of the Immune Cell Infiltration Landscape of Thyroid Cancer for Improved Immunotherapy

Within the endocrine system, thyroid cancer (THCA) is the most typical malignant tumor. Tumor-infiltrating immune cells play vital roles in tumor progression, recurrence, metastasis as well as response to immunotherapy. However, THCA’s immune infiltrative landscape is still not clarified. Therefore, we utilized two statistical algorithms to investigate the immune cell infiltration (ICI) landscape of 505 THCA samples and defined three ICI immune subtypes. The ICI scores were calculated using principal-component analysis. Increased tumor mutation burden (TMB) and immune-related signaling pathways were associated to a high ICI score. The high ICI score group indicated a relatively longer overall survival (OS) than the low ICI score group. Most immune checkpoint-related and immune activation-related genes were considerably upregulated in the ICI high group, which indicates stronger immunogenicity and a greater likelihood of benefiting from immunotherapy. In two cohort studies of patients receiving immunotherapy, high-ICI-score group showed notable therapeutic effects and clinical advantages compared to those with lower ICI scores. These results demonstrate that ICI score acts as an effective prognostic indicator and predictor of response to immunotherapy.

Mutational profiling of low-grade gliomas identifies prognosis and immunotherapy-related biomarkers and tumour immune microenvironment characteristics

Low-grade glioma (LGG) is a heterogeneous tumour with the median survival rate less than 10 years. Therefore, it is urgent to develop efficient immunotherapy strategies of LGG. In this study, we analysed mutation profiles based on the data of 510 LGG patients from the Cancer Genome Atlas (TCGA) database and investigated the prognostic value of mutated genes and evaluate their immune infiltration. Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to indicate the characteristics of gliomas that respond to immune checkpoint blockade (ICB) therapy. Univariate and multivariate cox regression analysis was performed to identify indicators to construct the nomogram model. 485 (95.47%) of 508 LGG samples showed gene mutation, and 9 mutated genes were significantly related to overall survival (OS), among which 6 mutated genes were significantly correlated with OS between mutation and wildtypes. Immune infiltration and immune score analyses revealed that these six mutated genes were significantly associated with tumour immune microenvironment in LGG. The response of LGG with different characteristics to ICB was evaluated by TIDE algorithm. Finally, CIC gene was screened through both univariate and multivariate Cox regression analyses, and the nomogram model was established to determine the potential prognostic value of CIC in LGG. Our study provides comprehensive analysis of mutated genes in LGG, supporting modulation of mutated genes in the management of LGG.

Promising New Tools for Targeting p53 Mutant Cancers: Humoral and Cell-Based Immunotherapies

Transcription factor and oncosuppressor protein p53 is considered as one of the most promising molecular targets that remains a high-hanging fruit in cancer therapy. TP53 gene encoding the p53 protein is known to be the most frequently mutated gene in human cancers. The loss of transcriptional functions caused by mutations in p53 protein leads to deactivation of intrinsic tumor suppressive responses associated with wild-type (WT) p53 and acquisition of new pro-oncogenic properties such as enhanced cell proliferation, metastasis and chemoresistance. Hotspot mutations of p53 are often immunogenic and elicit intratumoral T cell responses to mutant p53 neoantigens, thus suggesting this protein as an attractive candidate for targeted anti-cancer immunotherapies. In this review we discuss the possible use of p53 antigens as molecular targets in immunotherapy, including the application of T cell receptor mimic (TCRm) monoclonal antibodies (mAbs) as a novel powerful approach.

Uncovering the Subtype-Specific Molecular Characteristics of Breast Cancer by Multiomics Analysis of Prognosis-Associated Genes, Driver Genes, Signaling Pathways, and Immune Activity

Breast cancer is a heterogeneous malignant disease with different prognoses and has been divided into four molecular subtypes. It is believed that molecular events occurring in breast stem/progenitor cells contribute to the carcinogenesis and development of different breast cancer subtypes. However, these subtype-specific molecular characteristics are largely unknown. In this study, we employed 1217 breast cancer samples from The Cancer Genome Atlas (TCGA) database for a multiomics analysis of the molecular characteristics of different breast cancer subtypes based on PAM50 algorithms. We detected the expression changes of subtype-specific genes and revealed that the expression of particular subtype-specific genes significantly affected prognosis. We also investigated the mutations and copy number variations (CNVs) of breast cancer driver genes and the representative genes of ten signaling pathways in different subtypes and revealed several subtype-specifically altered genes. Moreover, we detected the infiltration of various immune cells in different subtypes of breast cancer and showed that the infiltration levels of major immune cell types are different among these subtypes. Additionally, we investigated the factors affecting the immune infiltration level and the immune cytolytic activity in different breast cancer subtypes, namely, the mutation burden, genome instability and cancer-associated fibroblast (CAF) infiltration. This study may shed light on the molecular events contributing to carcinogenesis and development and provide potential markers and targets for the clinical diagnosis and treatment of different breast cancer subtypes.

A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer

Prostate cancer (PCa) is the second most common malignancy in men, but its exact pathogenetic mechanisms remain unclear. This study explores the effect of enhancer RNAs (eRNAs) in PCa. Firstly, we screened eRNAs and eRNA -driven genes from The Cancer Genome Atlas (TCGA) database, which are related to the disease-free survival (DFS) of PCa patients;. screening methods included bootstrapping, Kaplan-Meier (KM) survival analysis, and Pearson correlation analysis. Then, a risk score model was established using multivariate Cox analysis, and the results were validated in three independent cohorts. Finally, we explored the function of eRNA-driven genes through enrichment analysis and analyzed drug sensitivity on datasets from the Genomics of Drug Sensitivity in Cancer database. We constructed and validated a robust prognostic gene signature involving three eRNA-driven genes namely MAPK15, ZNF467, and MC1R. Moreover, we evaluated the function of eRNA-driven genes associated with tumor microenvironment (TME) and tumor mutational burden (TMB), and identified remarkable differences in drug sensitivity between high- and low-risk groups. This study identified a prognostic gene signature, which provides new insights into the role of eRNAs and eRNA-driven genes while assisting clinicians to determine the prognosis and appropriate treatment options for patients with PCa.

Single-Cell TCR and Transcriptome Analysis: An Indispensable Tool for Studying T-Cell Biology and Cancer Immunotherapy

T cells have been known to be the driving force for immune response and cancer immunotherapy. Recent advances on single-cell sequencing techniques have empowered scientists to discover new biology at the single-cell level. Here, we review the single-cell techniques used for T-cell studies, including T-cell receptor (TCR) and transcriptome analysis. In addition, we summarize the approaches used for the identification of T-cell neoantigens, an important aspect for T-cell mediated cancer immunotherapy. More importantly, we discuss the applications of single-cell techniques for T-cell studies, including T-cell development and differentiation, as well as the role of T cells in autoimmunity, infectious disease and cancer immunotherapy. Taken together, this powerful tool not only can validate previous observation by conventional approaches, but also can pave the way for new discovery, such as previous unidentified T-cell subpopulations that potentially responsible for clinical outcomes in patients with autoimmunity or cancer.