Single-Cell Molecular Profiling of Head and Neck Squamous Cell Carcinoma Reveals Five Dysregulated Signaling Pathways Associated With Circulating Tumor Cells.

OBJECTIVES: To determine the dysregulated signaling pathways of head and neck squamous cell carcinoma associated with circulating tumor cells (CTCs) via single-cell molecular characterization. INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) has a significant global burden and is a disease with poor survival. Despite trials exploring new treatment modalities to improve disease control rates, the 5 year survival rate remains low at only 60%. Most cancer malignancies are reported to progress to a fatal phase due to the metastatic activity derived from treatment-resistant cancer cells, regarded as one of the most significant obstacles to develope effective cancer treatment options. However, the molecular profiles of cancer cells have not been thoroughly studied. METHODS: Here, we examined in-situ HNSCC tumors and pairwisely followed up with the downstream circulating tumor cells (CTCs)-based on the surrogate biomarkers to detect metastasis that is established in other cancers - not yet being fully adopted in HNSCC treatment algorithms. RESULTS: Specifically, we revealed metastatic HNSCC patients have complex CTCs that could be defined through gene expression and mutational gene profiling derived from completed single-cell RNASeq (scRNASeq) that served to confirm molecular pathways inherent in these CTCs. To enhance the reliability of our findings, we cross-validated those molecular profiles with results from previously published studies. CONCLUSION: Thus, we identified 5 dysregulated signaling pathways in CTCs to derive HNSCC biomarker panels for screening HNSCC in situ tumors.

ObjectivesInvestigating the dysregulated signaling pathways of head and neck squamous cell carcinoma (HNSCC) linked with circulating tumor cells (CTCs) using single-cell molecular characterization.IntroductionHNSCC poses a significant global health burden with poor survival rates despite advancements in treatment. Metastatic activity from treatment-resistant cancer cells remains a major challenge in developing effective treatments. However, the molecular profiles of cancer cells, particularly CTCs, are not well-understood.MethodsWe analyzed in-situ HNSCC tumors and corresponding CTCs using surrogate biomarkers to detect metastasis, a technique not widely used in HNSCC treatment protocols.ResultsOur study revealed complex CTCs in metastatic HNSCC patients characterized by gene expression and mutational gene profiling via single-cell RNASeq (scRNASeq). These profiles confirmed molecular pathways inherent in CTCs, further validated by previous research.ConclusionThrough our research, we identified five dysregulated signaling pathways in CTCs, suggesting potential biomarker panels for HNSCC screening in situ tumors.

DeepDecon accurately estimates cancer cell fractions in bulk RNA-seq data.

Understanding the cellular composition of a disease-related tissue is important in disease diagnosis, prognosis, and downstream treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technique have allowed the measurement of gene expression profiles for individual cells. However, scRNA-seq is still too expensive to be used for large-scale population studies, and bulk RNA-seq is still widely used in such situations. An essential challenge is to deconvolve cellular composition for bulk RNA-seq data based on scRNA-seq data. Here, we present DeepDecon, a deep neural network model that leverages single-cell gene expression information to accurately predict the fraction of cancer cells in bulk tissues. It provides a refining strategy in which the cancer cell fraction is iteratively estimated by a set of trained models. When applied to simulated and real cancer data, DeepDecon exhibits superior performance compared to existing decomposition methods in terms of accuracy.

RNA-Sequencing Combined With Genome-Wide Allele-Specific Expression Patterning Identifies ZNF44 Variants as a Potential New Driver Gene for Pediatric Neuroblastoma.

INTRODUCTION: Neuroblastoma (NB) is one of the children's most common solid tumors, accounting for approximately 8% of pediatric malignancies and 15% of childhood cancer deaths. Somatic mutations in several genes, such as ALK, have been associated with NB progression and can facilitate the discovery of novel therapeutic strategies. However, the differential expression of mutated and wild-type alleles on the transcriptome level is poorly studied. METHODS: This study analyzed 219 whole-exome sequencing datasets with somatic mutations detected by MuTect from paired normal and tumor samples. RESULTS: We prioritized mutations in 8 candidate genes (RIMS4, RUSC2, ALK, MYCN, PTPN11, ALOX12B, ZNF44, and CNGB1) as potential driver mutations. We further confirmed the presence of allele-specific expression of the somatic mutations in NB with integrated analysis of 127 RNA-seq samples (of which 85 also had DNA-seq data available), including MYCN, ALK, and PTPN11. The allele-specific expression of mutations suggests that the same somatic mutation may have different effects on the clinical outcomes of tumors. CONCLUSION: Our study suggests 2 novel variants of ZNF44 as a novel candidate driver gene for NB.

The Machine-Learning-Mediated Interface of Microbiome and Genetic Risk Stratification in Neuroblastoma Reveals Molecular Pathways Related to Patient Survival.

Currently, most neuroblastoma patients are treated according to the Children's Oncology Group (COG) risk group assignment; however, neuroblastoma's heterogeneity renders only a few predictors for treatment response, resulting in excessive treatment. Here, we sought to couple COG risk classification with tumor intracellular microbiome, which is part of the molecular signature of a tumor. We determine that an intra-tumor microbial gene abundance score, namely M-score, separates the high COG-risk patients into two subpopulations (Mhigh and Mlow) with higher accuracy in risk stratification than the current COG risk assessment, thus sparing a subset of high COG-risk patients from being subjected to traditional high-risk therapies. Mechanistically, the classification power of M-scores implies the effect of CREB over-activation, which may influence the critical genes involved in cellular proliferation, anti-apoptosis, and angiogenesis, affecting tumor cell proliferation survival and metastasis. Thus, intracellular microbiota abundance in neuroblastoma regulates intracellular signals to affect patients' survival.

Molecular Characterization of Differentiated-Resistance MSC Subclones by Single-Cell Transcriptomes.

Background: The mechanism of tumorigenicity potentially evolved in mesenchymal stem cells (MSCs) remains elusive, resulting in inconsistent clinical application efficacy. We hypothesized that subclones in MSCs contribute to their tumorgenicity, and we approached MSC-subclones at the single-cell level. Methods: MSCs were cultured in an osteogenic differentiation medium and harvested on days 12, 19, and 25 for cell differentiation analysis using Alizarin Red and followed with the single-cell transcriptome. Results: Single-cell RNA-seq analysis reveals a discrete cluster of MSCs during osteogenesis, including differentiation-resistant MSCs (DR-MSCs), differentiated osteoblasts (DO), and precursor osteoblasts (PO). The DR-MSCs population resembled cancer initiation cells and were subjected to further analysis of the yes associated protein 1 (YAP1) network. Verteporfin was also used for YAP1 inhibition in cancer cell lines to confirm the role of YAP1 in MSC--involved tumorigenicity. Clinical data from various cancer types were analyzed to reveal relationships among YAP1, OCT4, and CDH6 in MSC--involved tumorigenicity. The expression of cadherin 6 (CDH6), octamer-binding transcription factor 4 (OCT4), and YAP1 expression was significantly upregulated in DR-MSCs compared to PO and DO. YAP1 inhibition by Verteporfin accelerated the differentiation of MSCs and suppressed the expression of YAP1, CDH6, and OCT4. A survey of 56 clinical cohorts revealed a high degree of co-expression among CDH6, YAP1, and OCT4 in various solid tumors. YAP1 inhibition also down-regulated HeLa cell viability and gradually inhibited YAP1 nuclear localization while reducing the transcription of CDH6 and OCT4. Conclusions: We used single-cell sequencing to analyze undifferentiated MSCs and to discover a carcinogenic pathway in single-cell MSCs of differentiated resistance subclones.

Reply to Schramm, L. Comment on "Li et al. BDP1 Variants I1264M and V1347M Significantly Associated with Clinical Outcomes of Pediatric Neuroblastoma Patients Imply a New Prognostic Biomarker: A 121-Patient Cancer Genome Study. Diagnostics 2021, 11, 2364".

We thank Professor Laura Schramm for her comment on the history and clarification of BDP1 nomenclature, her contribution to gene cloning [...].

BDP1 Variants I1264M and V1347M Significantly Associated with Clinical Outcomes of Pediatric Neuroblastoma Patients Imply a New Prognostic Biomarker: A 121-Patient Cancer Genome Study.

BACKGROUND: Neuroblastoma (N.B.) is the most common tumor in children. The gene BDP1 (B Double Prime 1) plays a role in cancers but is less known in N.B. Thus, we conducted this study to investigate the value of BDP1 mutations in N.B. METHODS: A dataset of 121 NB patients from the Cancer Genome Atlas database was used to analyze BDP1 gene mutations by RNA sequencing. Kaplan-Meier estimates were performed for overall survival (O.S.) analysis on BDP1 variants, and Cox's proportional hazards regression model was used for multivariate analysis. RESULTS: In 121 NB patients, we identified two variants of BDP1 associated with N.B., located at chr5:71511131 and chr5:71510884. The prevalence of these BDP1 variants, I1264M and V1347M, was 52.9% (64/121) and 45.5% (55/121), respectively. O.S. analysis showed a significant difference between subgroups with or without BDP1 variants (p < 0.05). Multivariate analysis further revealed that BDP1ariants were independent prognostic variables in N.B. (p < 0.05). CONCLUSION: Our results suggest BDP1 variants are associated with significantly improved clinical outcomes in N.B., thus providing clinicians with a new tool.

Evidence for AJUBA-catenin-CDH4-linked differentiation resistance of mesenchymal stem cells implies tumorigenesis and progression of head and neck squamous cell carcinoma: a single-cell transcriptome approach.

An increasing number of reports indicate that mesenchymal stem cells (MSCs) play an essential role in promoting tumorigenesis and progression of head and neck squamous cell carcinoma (HNSCC). However, the molecular mechanisms underlying this process remain unclear. Using the MSC model system, this study analyzes the molecular pathway by which differentiation resistant MSCs promote HNSCC. MSCs were cultured in osteogenic differentiation media and harvested on days 12 and 19. Cells were stained for cell differentiation analysis using Alizarin Red. The osteogenesis-resistant MSCs (OR-MSCs) and MSC-differentiation-derived osteoblasts (D-OSTBs) were identified and subjected to the single-cell transcriptome analysis. Gene-specific analyses of these two sub-populations were performed for the patterns of differential expression. A total of 1 780 differentially expressed genes were determined to distinguish OR-MSCs significantly from D-OSTB. Notably, AJUBA, ß-catenin, and CDH4 expression levels were upregulated considerably within the OR-MSCs compared to D-OSTBs. To confirm their clinical relevance, a survey of a clinical cohort revealed a high correlation among the expression levels of AJUBA, ß-catenin and CDH4. The results shed new light that OR-MSCs participate in the development of HNSCC via a pathway mediated by AJUBA, ß-catenin, CDH4, and CTNNB1, thereby implying that MSC-based therapy is a promising therapeutic approach in the management of HNSCC.

LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing.

BACKGROUND: Long-read RNA-Seq techniques can generate reads that encompass a large proportion or the entire mRNA/cDNA molecules, so they are expected to address inherited limitations of short-read RNA-Seq techniques that typically generate < 150 bp reads. However, there is a general lack of software tools for gene fusion detection from long-read RNA-seq data, which takes into account the high basecalling error rates and the presence of alignment errors. RESULTS: In this study, we developed a fast computational tool, LongGF, to efficiently detect candidate gene fusions from long-read RNA-seq data, including cDNA sequencing data and direct mRNA sequencing data. We evaluated LongGF on tens of simulated long-read RNA-seq datasets, and demonstrated its superior performance in gene fusion detection. We also tested LongGF on a Nanopore direct mRNA sequencing dataset and a PacBio sequencing dataset generated on a mixture of 10 cancer cell lines, and found that LongGF achieved better performance to detect known gene fusions over existing computational tools. Furthermore, we tested LongGF on a Nanopore cDNA sequencing dataset on acute myeloid leukemia, and pinpointed the exact location of a translocation (previously known in cytogenetic resolution) in base resolution, which was further validated by Sanger sequencing. CONCLUSIONS: In summary, LongGF will greatly facilitate the discovery of candidate gene fusion events from long-read RNA-Seq data, especially in cancer samples. LongGF is implemented in C++ and is available at https://github.com/WGLab/LongGF .

Genomic Analysis of Oral Lichen Planus and Related Oral Microbiome Pathogens.

Oral lichen planus (OLP) is a common chronic inflammatory disease affecting the oral mucosa. The pathogenesis of OLP is incompletely understood but is thought to be related to the immune system. As the oral cavity is a major reservoir and transmission gateway for bacteria, viruses, and fungi, the microbial composition of the oral cavity could play a role in the pathogenesis of OLP. However, limited by analytic technology and knowledge of the microbial community in the oral cavity, it is not yet clear which pathogens are associated with OLP. Next generation sequencing (NGS) is a powerful tool to identify pathogens for many infectious diseases. In this study, we compared the host cell gene expression profiles and the microbial profiles between OLP patients and matched healthy individuals. We identified the activation of the hepatocyte nuclear factor alpha (HNF4A) network in OLP patients and potential pathogens, including Corynebacterium matruchotii, Fusobacterium periodonticum, Streptococcus intermedius, Streptococcus oralis, and Prevotella denticola. Prevotella denticola is capable of activating the HNF4A gene network. Our findings shed light on the previously elusive association of OLP with various diseases like hepatitis, and indicate that OLP is a T-helper type 17 (Th17) mediated mucosal inflammatory process. The identified molecular pathways and microbes could be used to inform future investigations into OLP pathogenesis and to develop novel therapeutics for OLP treatment.

Detection of human papillomavirus in cases of head and neck squamous cell carcinoma by RNA-seq and VirTect.

Next-generation sequencing provides an opportunity to detect viral species from RNA-seq data of human tissues, but existing computational approaches do not perform optimally on clinical samples. We developed a bioinformatic method called VirTect for detecting viruses in neoplastic human tissues using RNA-seq data. Here, we used VirTect to analyze RNA-seq data from 363 head and neck squamous cell carcinoma (HNSCC) patients and identified 22 human papillomavirus (HPV)-induced HNSCCs. These predictions were validated by manual review of pathology reports on histopathologic specimens. VirTect showed better performance in recall and accuracy compared to the two existing prediction methods, VirusFinder and VirusSeq, in identifying viral sequences from RNA-seq data. The majority of HPV carcinogenesis studies thus far have been performed on cervical cancer and generalized to HNSCC. Our results suggest that carcinogenesis of HPV-induced HNSCC and other cases of HNSCC involve different genes, so understanding the underlying molecular mechanisms will have a significant impact on therapeutic approaches and outcomes. In summary, RNA-seq together with VirTect can be an effective solution for the detection of viruses from tumor samples and can facilitate the clinicopathologic characterization of various types of cancers with broad applications for oncology.

Single-cell transcriptomes reveal the mechanism for a breast cancer prognostic gene panel.

The clinical benefits of the MammaPrint® signature for breast cancer is well documented; however, how these genes are related to cell cycle perturbation have not been well determined. Our single-cell transcriptome mapping (algorithm) provides details into the fine perturbation of all individual genes during a cell cycle, providing a view of the cell-cycle-phase specific landscape of any given human genes. Specifically, we identified that 38 out of the 70 (54%) MammaPrint® signature genes are perturbated to a specific phase of the cell cycle. The MammaPrint® signature panel derived its clinical prognosis power from measuring the cell cycle activity of specific breast cancer samples. Such cell cycle phase index of the MammaPrint® signature suggested that measurement of the cell cycle index from tumors could be developed into a prognosis tool for various types of cancer beyond breast cancer, potentially improving therapy through targeting a specific phase of the cell cycle of cancer cells.

Relapse pathway of glioblastoma revealed by single-cell molecular analysis.

Glioblastoma multiforme (GBM) remains an incurable brain tumor. The highly malignant behavior of GBM may, in part, be attributed to its intraclonal genetic and phenotypic diversity (subclonal evolution). Identifying the molecular pathways driving GBM relapse may provide novel, actionable targets for personalized diagnosis, characterization of prognosis and improvement of precision therapy. We screened single-cell transcriptomes, namely RNA-seq data of primary and relapsed GBM tumors from a patient, to define the molecular profile of relapse. Characterization of hundreds of individual tumor cells identified three mutated genes within single cells, involved in the RAS/GEF GTP-dependent signaling pathway. The identified molecular pathway was further verified by meta-analysis of RNA-seq data from more than 3000 patients. This study showed that single-cell molecular analysis overcomes the inherent heterogeneity of bulk tumors with respect to defining tumor subclonal evolution relevant to GBM relapse.

Microfluidic enrichment of plasma cells improves treatment of multiple myeloma.

Cytogenetic alterations form the basis for risk stratification for multiple myeloma (MM) and guide the selection of therapy; however, current pathology assays performed on bone marrow samples can produce false-negatives due to the unpredictable distribution and rarity of MM cells. Here, we report on a microfluidic device used to facilitate CD45 depletion to enhance the detection of cytogenetic alterations in plasma cells (PCs). Bone marrow samples from 48 patients with MM were each divided into two aliquots. One aliquot was subjected to classic flow cytometry and fluorescent in situ hybridization (FISH). The other first went through CD45+ cell depletion, further enriched by microfluidic size selection. The enriched samples were then analyzed using flow cytometry and FISH and compared to those analyzed using the classic method only. Unlike the traditional method, the microfluidic device removed the CD45+ leukocytes and specifically selected PCs from the remaining white blood cells. Therefore, the microfluidic method (MF-CD45-TACs) significantly increased the percentage of CD38+ /CD138+ cells to 37.7 ± 20.4% (P < 0.001) from 10.3 ± 8.5% in bone marrow. After the MF-CD45-TAC enrichment, the detection rate of IgH rearrangement, del(13q14), del(17p), and 1q21 gains, rose to 56.3% (P < 0.001), 37.5% (P < 0.001), 22.9% (P < 0.001), and 41.7% (P = 0.001), respectively; all rates of detection were significantly increased compared to the classically analyzed samples. In this clinical trial, this microfluidic-assisted assay provided a precise detection of cytogenetic alterations in PCs and improved clinical outcomes.

Single-Cell Digital Lysates Generated by Phase-Switch Microfluidic Device Reveal Transcriptome Perturbation of Cell Cycle.

With conventional gene expression profiling, information concerning cellular heterogeneity is often lost in the physical mixing and averaging of millions of cells. Single-cell transcriptome analysis has the potential to address these issues. However, there is a need to determine how many cells are needed to draw meaningful conclusions in each single-cell study. Here, we introduce the concept of "digital lysate" for assessing cellular heterogeneity with a phase-switch microfluidic platform and apply it to construct a molecular map of transcriptome perturbation during the cell cycle. Using a phase-switch droplet microfluidic platform and next-generation sequencing, we obtained transcriptomes of single cells by random sampling. Digital lysates were generated by permutating and averaging multiple single-cell transcriptomes. In our studied cell populations, digital lysates converged to physical lysates ( r = 0.93), and the sample-to-sample repeatability was comparable to that of conventional analysis of a physical lysate ( r = 0.98). After determining the number of cells needed, single-cell transcriptomes were used to organize cells into a map by molecular similarity, and the map was validated by cell cycle-specific markers ( p = 0.003). Cell cycle regulatory genes were inferred using this molecular map and verified with siRNA assays. The study described here provides an effective approach, the generation and analysis of digital lysates, to investigate cellular heterogeneity.

Gene Manipulation with Micro RNAs at Single-Human Cancer Cell.

Micro RNAs (miRNAs) are small RNAs processed from longer precursor RNA transcripts that can fold back on themselves to form Watson-Crick paired hairpin structures. Once processed from the longer molecule, the small RNA is much too short to code for proteins but can play other very important roles, like gene regulation. The phenomenon of RNA interference was initially observed by Napoli and Jorgensen in transgenic petunia flowers, where gene suppression was observed after introducing a transgene of chalcone synthase (CHS) belonging to the flavonoid biosynthesis pathway. miRNAs were first discovered for their roles in development but it has quickly become evident that they have causal roles in cancer as well. miRNA can also be used to manipulate genes for the investigation of carcinogenesis. Single-cell transcriptome profiling studies in our laboratory suggest that carcinogenesis often is the result of the malfunction of multiple members of a molecular pathway. Here, we describe a protocol to manipulate multiple cancer-related genes in a single human cell to investigate how multiple genes interact during carcinogenesis.

CCR5 Governs DNA Damage Repair and Breast Cancer Stem Cell Expansion.

The functional significance of the chemokine receptor CCR5 in human breast cancer epithelial cells is poorly understood. Here, we report that CCR5 expression in human breast cancer correlates with poor outcome. CCR5+ breast cancer epithelial cells formed mammospheres and initiated tumors with >60-fold greater efficiency in mice. Reintroduction of CCR5 expression into CCR5-negative breast cancer cells promoted tumor metastases and induced DNA repair gene expression and activity. CCR5 antagonists Maraviroc and Vicriviroc dramatically enhanced cell killing mediated by DNA-damaging chemotherapeutic agents. Single-cell analysis revealed CCR5 governs PI3K/Akt, ribosomal biogenesis, and cell survival signaling. As CCR5 augments DNA repair and is reexpressed selectively on cancerous, but not normal breast epithelial cells, CCR5 inhibitors may enhance the tumor-specific activities of DNA damage response-based treatments, allowing a dose reduction of standard chemotherapy and radiation.Significance: This study offers a preclinical rationale to reposition CCR5 inhibitors to improve the treatment of breast cancer, based on their ability to enhance the tumor-specific activities of DNA-damaging chemotherapies administered in that disease. Cancer Res; 78(7); 1657-71. ©2018 AACR.

Single-cell genomic analysis of head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) incidence or rates have increased dramatically recently with little improvement in patient outcomes. There is an unmet need in HNSCC to develop reliable molecular markers capable of evaluating patient risks and advising treatments. This review focuses on recent developments in single-cell molecular analysis of cancer, and its applications for HNSCC diagnosis and treatments. For proof of concept, we examined gene expression levels of 62 patients with HNSCC, and correlate the gene expression profiles to single-cell gene expression profiles obtained from a pilot single-cell study of CCR5-positive breast carcinoma cells. The single-cell molecular analyses complemented the lysate data and reveals heterogeneity of oncogenesis pathways with the cancer cell population. Our single-cell molecular analysis indicated that molecular heterogeneity exists in HNSCC and should be addressed in treatment strategy of HNSCC. Single-cell molecular technology can have significant impact on diagnosis, therapeutic decision making, and prognosis of HNSCC.