The Landscape of Somatic Copy Number Alterations in Head and Neck Squamous Cell Carcinoma

A prognostic model for hepatocellular carcinoma patients based on polyunsaturated fatty acid-related genes

OBJECTIVE

Polyunsaturated fatty acids (PUFAs) have attracted increasing attention for their role in liver cancer development. The objective of this study is to develop a prognosis prediction model for patients with liver cancer based on PUFA-related metabolic gene characteristics.

METHOD

Transcriptome data and clinical data were obtained from public databases, while gene sets related to PUFAs were acquired from the gene set enrichment analysis (GSEA) database. Univariate Cox analysis was conducted on the training set, followed by LASSO logistic regression and multivariate Cox analysis on genes with p < .05. Subsequently, the stepwise Akaike information criterion method was employed to construct the model. The high- and low-risk groups were divided based on the median score, and the model's survival prediction ability, diagnostic efficiency, and risk score distribution of clinical features were validated. The above procedures were also validated in the validation set. Immune infiltration levels were evaluated using four algorithms, and the immunotherapeutic potential of different groups was explored. Significant enrichment pathways among different groups were selected based on the GSEA algorithm, and mutation analyses were conducted. Nomogram prognostic models were constructed by incorporating clinical factors and risk scores using univariate and multivariate Cox regression analysis, validated through calibration curves and clinical decision curves. Additionally, sensitivity analysis of drugs was performed to screen potential targeted drugs.

RESULTS

We constructed a prognostic model comprising eight genes (PLA2G12A, CYP2C8, ABCCI, CD74, CCR7, P2RY4, P2RY6, and YY1). Validation across multiple datasets indicated the model's favorable prognostic prediction ability and diagnostic efficiency, with poorer grading and staging observed in the high-risk group. Variations in mutation status and pathway enrichment were noted among different groups. Incorporating Stage, Grade, T.Stage, and RiskScore into the nomogram prognostic model demonstrated good accuracy and clinical decision benefits. Multiple immune analyses suggested greater benefits from immunotherapy in the low-risk group. We predicted multiple targeted drugs, providing a basis for drug development.

CONCLUSION

Our study's multifactorial prognostic model across multiple datasets demonstrates good applicability, offering a reliable tool for personalized therapy. Immunological and mutation-related analyses provide theoretical foundations for further research. Drug predictions offer important insights for future drug development and treatment strategies. Overall, this study provides comprehensive insights into tumor prognosis assessment and personalized treatment planning.

Inferring chromosomal instability from copy number aberrations as a measure of chromosomal instability across human cancers

BACKGROUND

Cancer is a complex disease that is the second leading cause of death in the United States. Despite research efforts, the ability to manage cancer and select optimal therapeutic responses for each patient remains elusive. Chromosomal instability (CIN) is primarily a product of segregation errors wherein one or many chromosomes, in part or whole, vary in number. CIN is an enabling characteristic of cancer, contributes to tumor-cell heterogeneity, and plays a crucial role in the multistep tumorigenesis process, especially in tumor growth and initiation and in response to treatment.

AIMS

Multiple studies have reported different metrics for analyzing copy number aberrations as surrogates of CIN from DNA copy number variation data. However, these metrics differ in how they are calculated with respect to the type of variation, the magnitude of change, and the inclusion of breakpoints. Here we compared metrics capturing CIN as either numerical aberrations, structural aberrations, or a combination of the two across 33 cancer data sets from The Cancer Genome Atlas (TCGA).

METHODS AND RESULTS

Using CIN inferred by methods in the CINmetrics R package, we evaluated how six copy number CIN surrogates compared across TCGA cohorts by assessing each across tumor types, as well as how they associate with tumor stage, metastasis, and nodal involvement, and with respect to patient sex.

CONCLUSIONS

We found that the tumor type impacts how well any two given CIN metrics correlate. While we also identified overlap between metrics regarding their association with clinical characteristics and patient sex, there was not complete agreement between metrics. We identified several cases where only one CIN metric was significantly associated with a clinical characteristic or patient sex for a given tumor type. Therefore, caution should be used when describing CIN based on a given metric or comparing it to other studies.

Innovative molecular subtypes of multiple signaling pathways in colon cancer and validation of FMOD as a prognostic-related marker

PURPOSE

Colon cancer is highly heterogeneous in terms of the immune and stromal microenvironment, genomic integrity, and oncogenic properties; therefore, molecular subtypes of the four characteristic dimensions are expected to provide novel clues for immunotherapy of colon cancer.

METHODS

According to the enrichment of four dimensions, we performed consensus cluster analysis and identified three robust molecular subtypes for colon cancer, namely immune enriched, immune deficiency, and stroma enriched. We characterized and validated the immune infiltration, gene mutations, copy number variants, methylation, protein expression, and clinical features in different datasets. Finally, we developed an 8-gene risk prognostic model and proposed the innovative RiskScore. In addition, a nomogram model was constructed combining clinical characteristics and RiskScore to validate its excellent clinical predictive power.

RESULTS

Combining clinical patient tissue samples and histochemical microarray data, we found that high FMOD expression in tumor epithelial cells was associated with poorer patient prognosis, but FMOD expression in the mesenchyme was not associated with prognosis. In pan-cancer, RiskScore, a prognostic model constructed based on characteristic pathway scores, was a poor prognostic factor for malignancy and was negatively associated with immunotherapy response.

CONCLUSION

The identification of molecular subtypes could provide innovative ideas for immunotherapy of colon cancer.

Circulating Tumor DNA in Head and Neck Squamous Cell Carcinoma

Tumors shed cell-free DNA (cfDNA) into the plasma. “Liquid biopsies” are a diagnostic test to analyze cfDNA in order to detect minimal residual cancer, profile the genomic tumor landscape, and monitor cancers non-invasively over time. This technique may be useful in patients with head and neck squamous cell carcinoma (HNSCC) due to genetic tumor heterogeneity and limitations in imaging sensitivity. However, there are technical challenges that need to be overcome for the widespread use of liquid biopsy in the clinical management of these patients. In this review, we discuss our current understanding of HNSCC genetics and the role of cfDNA genomic analyses as an emerging precision diagnostic tool.

Single cell analysis in head and neck cancer reveals potential immune evasion mechanisms during early metastasis

Profiling tumors at single-cell resolution provides an opportunity to understand complexities underpinning lymph-node metastases in head and neck squamous-cell carcinoma. Single-cell RNAseq (scRNAseq) analysis of cancer-cell trajectories identifies a subpopulation of pre-metastatic cells, driven by actionable pathways including AXL and AURK. Blocking these two proteins blunts tumor invasion in patient-derived cultures. Furthermore, scRNAseq analyses of tumor-infiltrating CD8 + T-lymphocytes show two distinct trajectories to T-cell dysfunction, corroborated by their clonal architecture based on single-cell T-cell receptor sequencing. By determining key modulators of these trajectories, followed by validation using external datasets and functional experiments, we uncover a role for SOX4 in mediating T-cell exhaustion. Finally, interactome analyses between pre-metastatic tumor cells and CD8 + T-lymphocytes uncover a putative role for the Midkine pathway in immune-modulation and this is confirmed by scRNAseq of tumors from humanized mice. Aside from specific findings, this study demonstrates the importance of tumor heterogeneity analyses in identifying key vulnerabilities during early metastasis.

Isolation and characterization of head and neck cancer-derived peritumoral and cancer-associated fibroblasts

Introduction

Head and neck squamous cell carcinomas (HNSCC) are characterized by strong cellular and molecular heterogeneity and treatment resistance entailing poor survival. Besides cell-intrinsic properties, carcinoma cells receive important cues from non-malignant cells within the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are a major component of the TME that impact on the molecular make-up of malignant cells and have a decisive function in tumor progression. However, the potential functionality of fibroblasts within tumor-adjacent, macroscopically normal tissue remains poorly explored.

Methods

Here, we isolated primary peritumoral fibroblasts (PtFs) from macroscopically normal tissue in vicinity of primary human papillomavirus-negative and -positive oropharyngeal HNSCC and compared their phenotype and functionality with matched CAFs (n = 5 pairs) and with human oral fibroblasts (hOFs).

Results

Expression patterns of CD90, CD73, CD105, smooth muscle actin, Vimentin, and S100A4 were comparable in PtFs, CAFs, and hOFs. Cell proliferation and doubling times of CAFs and PtFs were heterogeneous across patients (n =2 PtF>CAF; n = 1 CAF>PtF; n = 2 CAF=PtF) and reflected inferior growth than hOFs. Furthermore, PtFs displayed an reduced heterogeneity in cell size compared to matched CAFs, which were characterized by the presence of single large cells. Overall, conditioned supernatants from CAFs had more frequently growth-promoting effects on a panel of carcinoma cell lines of the upper aerodigestive tract carcinoma cell lines (Cal27, Cal33, FaDu, and Kyse30), whereas significant differences in migration-inducing effects demonstrated a higher potential of PtFs. Except for Kyse30, CAFs were significantly superior to hOFs in promoting proliferation, while PtFs induced stronger migration than hOFs in all carcinoma lines tested. Analysis of soluble factors demonstrated significantly increased VEGF-A production in CAFs (except in pat.8), and significantly increased PDGF-BB production in PtFs of two patients. Tube formation assays confirmed a significantly enhanced angiogenic potential of conditioned supernatants from CAFs compared to hOFs on human umbilical vascular endothelial cells (HUVECs) in vitro.

Discussion

Hence, matched CAFs and PtFs present in HNSCC patients are heterogeneous in their proliferation-, migration-, and angiogenesis-promoting capacity. Despite this heterogeneity, CAFs induced stronger carcinoma cell proliferation and HUVEC tube formation overall, whereas PtFs promoted migration of tumor cells more strongly.

Identification and validation of an inflammation-related lncRNAs signature for improving outcomes of patients in colorectal cancer

Background: Colorectal cancer is the fourth most deadly cancer worldwide. Although current treatment regimens have prolonged the survival of patients, the prognosis is still unsatisfactory. Inflammation and lncRNAs are closely related to tumor occurrence and development in CRC. Therefore, it is necessary to establish a new prognostic signature based on inflammation-related lncRNAs to improve the prognosis of patients with CRC.

Methods: LASSO-penalized Cox analysis was performed to construct a prognostic signature. Kaplan-Meier curves were used for survival analysis and ROC curves were used to measure the performance of the signature. Functional enrichment analysis was conducted to reveal the biological significance of the signature. The R package “maftool” and GISTIC2.0 algorithm were performed for analysis and visualization of genomic variations. The R package “pRRophetic”, CMap analysis and submap analysis were performed to predict response to chemotherapy and immunotherapy.

Results: An effective and independent prognostic signature, IRLncSig, was constructed based on sixteen inflammation-related lncRNAs. The IRLncSig was proved to be an independent prognostic indicator in CRC and was superior to clinical variables and the other four published signatures. The nomograms were constructed based on inflammation-related lncRNAs and detected by calibration curves. All samples were classified into two groups according to the median value, and we found frequent mutations of the TP53 gene in the high-risk group. We also found some significantly amplificated regions in the high-risk group, 8q24.3, 20q12, 8q22.3, and 20q13.2, which may regulate the inflammatory activity of cancer cells in CRC. Finally, we identified chemotherapeutic agents for high-risk patients and found that these patients were more likely to respond to immunotherapy, especially anti-CTLA4 therapy.

Conclusion: In short, we constructed a new signature based on sixteen inflammation-related lncRNAs to improve the outcomes of patients in CRC. Our findings have proved that the IRLncSig can be used as an effective and independent marker for predicting the survival of patients with CRC.

Characterization of tumor immune microenvironment and cancer therapy for head and neck squamous cell carcinoma through identification of a genomic instability-related lncRNA prognostic signature

Head and neck squamous cell carcinoma (HNSCC) represents one of the most prevalent and malignant tumors of epithelial origins with unfavorable outcomes. Increasing evidence has shown that dysregulated long non-coding RNAs (lncRNAs) correlate with tumorigenesis and genomic instability (GI), while the roles of GI-related lncRNAs in the tumor immune microenvironment (TIME) and predicting cancer therapy are still yet to be clarified. In this study, transcriptome and somatic mutation profiles with clinical parameters were obtained from the TCGA database. Patients were classified into GI-like and genomic stable (GS)-like groups according to the top 25% and bottom 25% cumulative counts of somatic mutations. Differentially expressed lncRNAs (DElncRNAs) between GI- and GS-like groups were identified as GI-related lncRNAs. These lncRNA-related coding genes were enriched in cancer-related KEGG pathways. Patients totaling 499 with clinical information were randomly divided into the training and validation sets. A total of 18 DElncRNAs screened by univariate Cox regression analysis were associated with overall survival (OS) in the training set. A GI-related lncRNA signature that comprised 10 DElncRNAs was generated through least absolute shrinkage and selection operator (Lasso)-Cox regression analysis. Patients in the high-risk group have significantly decreased OS vs. patients in the low-risk group, which was verified in internal validation and entire HNSCC sets. Integrated HNSCC sets from GEO confirmed the notable survival stratification of the signature. The time-dependent receiver operating characteristic curve demonstrated that the signature was reliable. In addition, the signature retained a strong performance of OS prediction for patients with various clinicopathological features. Cell composition analysis showed high anti-tumor immunity in the low-risk group which was evidenced by increased infiltrating CD8+ T cells and natural killer cells and reduced cancer-associated fibroblasts, which was convinced by immune signatures analysis via ssGSEA algorithm. T helper/IFNγ signaling, co-stimulatory, and co-inhibitory signatures showed increased expression in the low-risk group. Low-risk patients were predicted to be beneficial to immunotherapy, which was confirmed by patients with progressive disease who had high risk scores vs. complete remission patients. Furthermore, the drugs that might be sensitive to HNSCC were identified. In summary, the novel prognostic GILncRNA signature provided a promising approach for characterizing the TIME and predicting therapeutic strategies for HNSCC patients.

Integrated Multi-Omics Signature Predicts Survival in Head and Neck Cancer

Head and Neck Cancer (HNC) is characterized by phenotypic, biological, and clinical heterogeneity. Despite treatment modalities, approximately half of all patients will die of the disease. Several molecular biomarkers have been investigated, but until now, without clinical translation. Here, we identified an integrative nine-gene multi-omics signature correlated with HNC patients’ survival independently of relapses or metastasis development. This prognosis multi-omic signature comprises genes mapped in the chromosomes 1q, 3p, 8q, 17q, 19p, and 19q and encompasses alterations at copy number, gene expression, and methylation. Copy number alterations in LMCD1-A1S and GRM7, the methylation status of CEACAM19, KRT17, and ST18, and the expression profile of RPL29, UBA7, FCGR2C, and RPSAP58 can predict the HNC patients’ survival. The difference higher than two years observed in the survival of HNC patients that harbor this nine-gene multi-omics signature can represent a significant step forward to improve patients’ management and guide new therapeutic targets development.

Genetic analysis of single disseminated tumor cells in the lymph nodes and bone marrow of patients with head and neck squamous cell carcinoma

Considering the limited information on the biology and molecular characteristics of disseminated tumor cells (DTCs) in head and neck squamous cell carcinoma (HNSCC), we examined the genomic alterations in DTCs from HNSCCs and their potential clinical relevance. To analyze both the lymphatic and hematogenous routes of tumor cell dissemination, we investigated samples from lymph nodes (LNs) and bone marrow (BM) of 49 patients using immunofluorescence double staining for epithelial cells expressing cytokeratin 18 (KRT18) and/or epithelial cell adhesion molecules (EpCAM, CD326). The identified marker‐positive cells were isolated by micromanipulation followed by single‐cell whole‐genome amplification and metaphase‐based comparative genomic hybridization (mCGH) to determine genome‐wide copy number alterations. The findings were correlated with clinical parameters and follow‐up data. We detected chromosomal aberrations in KRT18‐ and EpCAM‐positive cells from both compartments; BM‐derived cells showed a significantly higher percentage of aberrant genome (PAG) per cell than cells detected in LNs. No significant association was found between DTC data and clinical follow‐up. Genomic profiling of BM‐DTCs revealed genomic alterations typical for HNSCC, suggesting hematogenous dissemination of subclones around the time of surgery. In contrast, DTC data in LNs revealed that several marker‐positive cells were not of malignant origin, indicating the presence of epithelial glandular inclusions in parts of the processed neck LN samples. Therefore, DTC detection of LNs in the neck based only on epithelial markers is not advisable and requires detection of chromosomal instability (CIN), gene mutations, or additional markers, which have yet to be identified. Nevertheless, our investigation paves the way for larger studies to focus on HNSCC BM‐DTCs with high‐resolution methods to gain deeper insights into the biology of hematogenous metastasis in this cancer.

Identification of Immune-Related Subtypes and Characterization of Tumor Microenvironment Infiltration in Bladder Cancer

Tumors are closely related to the tumor microenvironment (TME). The complex interaction between tumor cells and the TME plays an indisputable role in tumor development. Tumor cells can affect the TME, promote tumor angiogenesis and induce immune tolerance by releasing cell signaling molecules. Immune cell infiltration (ICI) in the TME can affect the prognosis of patients with bladder cancer. However, the pattern of ICI of the TME in bladder cancer has not yet been elucidated. Herein, we identified three distinct ICI subtypes based on the TME immune infiltration pattern of 584 bladder cancer patients using the ESTIMATE and CIBERSORT algorithms. Then, we identified three gene clusters based on the differentially expressed genes (DEGs) between the three ICI subtypes. In addition, the ICI score was determined using single sample gene set enrichment analysis (ssGSEA). The results suggested that patients in the high ICI score subgroup had a favorable prognosis and higher expression of checkpoint-related and immune activity-related genes. The high ICI score subgroup was also linked to increased tumor mutation burden (TMB) and neoantigen burden. A cohort treated with anti-PD-L1 immunotherapy confirmed the therapeutic advantage and clinical benefit of patients with higher ICI scores. In the end, our study also shows that the ICI score represents an effective prognostic predictor for evaluating the response to immunotherapy. In conclusion, our study deepened the understanding of the TME, and it provides new ideas for improving patients' response to immunotherapy and promoting individualized tumor immunotherapy in the future.

Genomic heterogeneity and copy number variant burden are associated with poor recurrence-free survival and 11q loss in human papillomavirus-positive squamous cell carcinoma of the oropharynx

BACKGROUND

Human papillomavirus-positive (HPV+) squamous cell carcinoma of the oropharynx (OPSCC) is the most prevalent HPV-associated malignancy in the United States. Favorable treatment outcomes have led to increased interest in treatment de-escalation to reduce treatment morbidity as well as the development of prognostic markers to identify appropriately low-risk patients. Intratumoral genomic heterogeneity and copy number alteration burden have been demonstrated to be predictive of poor outcomes in many other cancers; therefore, we sought to determine whether intratumor heterogeneity and genomic instability are associated with poor outcomes in HPV+ OPSCC.

METHODS

Tumor heterogeneity estimates were made based on targeted exome sequencing of 45 patients with HPV+ OPSCC tumors. Analysis of an additional cohort of HPV+ OPSCC tumors lacking matched normal sequencing allowed copy number analysis of 99 patient tumors.

RESULTS

High intratumorally genomic heterogeneity and high numbers of copy number alterations were strongly associated with worse recurrence-free survival. Tumors with higher heterogeneity and frequent copy number alterations were associated with loss of distal 11q, which encodes key genes related to double-strand break repair, including ATM and MRE11A.

CONCLUSIONS

Both intratumor genomic heterogeneity and high-burden copy number alterations are strongly associated with poor recurrence-free survival in patients with HPV+ OPSCC. The drivers of genomic instability and heterogeneity in these tumors remains to be elucidated. However, 11q loss and defective DNA double-strand break repair have been associated with genomic instability in other solid tumors. Copy number alteration burden and intratumoral heterogeneity represent promising avenues for risk stratification of patients with HPV+OPSCC.

Reclassification of Kidney Clear Cell Carcinoma Based on Immune Cell Gene-Related DNA CpG Pairs

Background: A new method was developed based on the relative ranking of gene expression level, overcoming the flaw of the batch effect, and having reliable results in various studies. In the current study, we defined the two methylation sites as a pair. The methylation level in a specific sample was subject to pairwise comparison to calculate a score for each CpGs-pair. The score was defined as a CpGs-pair score. If the first immune-related CpG value was higher than the second one in a specific CpGs-pair, the output score of this immune-related CpGs-pair was 1; otherwise, the output score was 0. This study aimed to construct a new classification of Kidney Clear Cell Carcinoma (KIRC) based on DNA CpGs (methylation sites) pairs. Methods: In this study, the biomarkers of 28 kinds of immune infiltration cells and corresponding methylation sites were acquired. The methylation data were compared between KIRC and normal tissue samples, and differentially methylated sites (DMSs) were obtained. Then, DNA CpGs-pairs were obtained according to the pairs of DMSs. In total, 441 DNA CpGs-pairs were utilized to construct a classification using unsupervised clustering analysis. We also analyzed the potential mechanism and therapy of different subtypes, and validated them in a testing set. Results: The classification of KIRC contained three subgroups. The clinicopathological features were different across three subgroups. The distribution of immune cells, immune checkpoints and immune-related mechanisms were significantly different across the three clusters. The mutation and copy number variation (CNV) were also different. The clinicopathological features and potential mechanism in the testing dataset were consistent with those in the training set. Conclusions: Our findings provide a new accurate and stable classification for developing personalized treatments for the new specific subtypes.

A Methylation-Based Reclassification of Bladder Cancer Based on Immune Cell Genes

Simple Summary

Bladder cancer (BC) development is highly related to immune cell infiltration. In this study, we aimed to construct a new classification of bladder cancer molecular subtypes based on immune-cell-associated CpG(Methylation) sites. The classification was accurate and stable. BC patients were successfully divided into three subtypes based on the immune-cell-associated CpG sites. The clinicopathologic features, distribution of immune cells, level of expression of checkpoints, stromal score, immune score, ESTIMATEScore, tumor purity, APC co_inhibition, APC co_stimulation, HLA, MHC class_I, Type I IFN_respons, Type II IFN response, and DNA stemness score (DNAss) presented significant differences among the three subgroups. The specific genomic alteration was also different across subgroups. High-level immune infiltration showed a correlation with high-level methylation. A lower RNA stemness score (RNAss) was associated with higher immune infiltration. Cluster 2 demonstrated a better response to chemotherapy. The anti-cancer targeted drug therapy results are different among the three subgroups.

Abstract

Background: Bladder cancer is highly related to immune cell infiltration. This study aimed to develop a new classification of BC molecular subtypes based on immune-cell-associated CpG sites. Methods: The genes of 28 types of immune cells were obtained from previous studies. Then, methylation sites corresponding to immune-cell-associated genes were acquired. Differentially methylated sites (DMSs) were identified between normal samples and bladder cancer samples. Unsupervised clustering analysis of differentially methylated sites was performed to divide the sites into several subtypes. Then, the potential mechanism of different subtypes was explored. Results: Bladder cancer patients were divided into three groups. The cluster 3 subtype had the best prognosis. Cluster 1 had the poorest prognosis. The distribution of immune cells, level of expression of checkpoints, stromal score, immune score, ESTIMATEScore, tumor purity, APC co_inhibition, APC co_stimulation, HLA, MHC class_I, Type I IFN Response, Type II IFN Response, and DNAss presented significant differences among the three subgroups. The distribution of genomic alterations was also different. Conclusions: The proposed classification was accurate and stable. BC patients could be divided into three subtypes based on the immune-cell-associated CpG sites. Specific biological signaling pathways, immune mechanisms, and genomic alterations were varied among the three subgroups. High-level immune infiltration was correlated with high-level methylation. The lower RNAss was associated with higher immune infiltration. The study of the intratumoral immune microenvironment may provide a new perspective for BC therapy.