Squamous Cell Carcinoma Tissues Research Articles

Expression of angiotensin converting enzyme 2 in patients with oral squamous cell carcinoma

BackgroundOral squamous cell carcinoma (OSCC), being a multifactorial cancer, is significantly higher in South Asian countries and only 70 % of the cases are reported only in its advanced stages. As a component of the renin-angiotensin system (RAS), Angiotensin-Converting Enzyme 2 (ACE2) has been reported to restrain the progression of hepatocellular carcinoma (HCC) and non-small cell lung cancer (NSCLC) by inhibiting angiogenesis, nevertheless the role of ACE 2 in Oral Squamous Cell Carcinoma progression remains unexplored. ObjectiveTo quantify and compare tissue expression levels of Angiotensin Converting Enzyme 2 in patients with oral squamous cell carcinoma and healthy individuals. Materials and methodsThe current study was a case-control study, that includes n = 10 Oral Squamous Cell Carcinoma samples and n = 10, non-pathological tissues taken from healthy subjects, as controls. Fresh tissue samples were collected from the primary tumor areas of OSCC patients and healthy tissue samples from patients who had tooth extraction, and both tissues were stored at −80 °C. RNA isolation was performed using the TRIR kit from Invitrogen. cDNA was synthesized from total RNA isolated from tissues using a first-strand synthesis kit. Finally, ACE2 was assayed using an ultrasensitive human-specific ELISA kit. Statistical analysis was done using independent T test. ResultsThe data were expressed as mean ± standard deviation and the statistical analysis was done.OSCC patients showed ACE 2 mean optical density of 0.37 with SD ± 0.045 and healthy individuals showed a mean optical density of 0.45 with SD ± 0.052. The mean ng/L scores of OSCC and healthy individuals were 13.57 with SD ± 1.65 and 16.2 with SD ± 1.9 respectively. Optical density and concentration ng/L scores were compared between OSCC samples, showed a minimum value of 0.137 and a maximum of 2.253. Analyzed results shows that the ACE 2 protein expression in OSCC tumour tissue was lower than that in normal tissue (p = 0.004) ConclusionAngiotensin Converting Enzyme 2 was significantly lower in Oral Squamous Cell Carcinoma tissues when compared with healthy samples. However, further validation in large-scale prospective studies is necessary to explore the role of ACE 2 in prognosis of OSCC.

Combination of high anti-SKI and low anti-TMED5 antibody levels is preferable prognostic factor in esophageal carcinoma.

Given that esophageal cancer is highly malignant, the discovery of novel prognostic markers is eagerly awaited. We performed serological identification of antigens by recombinant cDNA expression cloning (SEREX) and identified SKI proto-oncogene protein and transmembrane p24 trafficking protein 5 (TMED5) as antigens recognized by serum IgG antibodies in patients with esophageal carcinoma. SKI and TMED5 proteins were expressed in Escherichia coli, purified by affinity chromatography, and used as antigens. The serum anti-SKI antibody (s-SKI-Ab) and anti-TMED5 antibody (s-TMED5-Ab) levels were significantly higher in 192 patients with esophageal carcinoma than in 96 healthy donors. The presence of s-SKI-Abs and s-TMED5-Abs in the patients' sera was confirmed by western blotting. Immunohistochemical staining showed that the TMED5 protein was highly expressed in the cytoplasm and nuclear compartments of the esophageal squamous cell carcinoma tissues, whereas the SKI protein was localized predominantly in the nuclei. Regarding the overall survival in 91 patients who underwent radical surgery, the s-SKI-Ab-positive and s-TMED5-Ab-negative statuses were significantly associated with a favorable prognosis. Additionally, the combination of s-SKI-Ab-positive and s-TMED5-Ab-negative cases showed an even clearer difference in overall survival as compared with that of s-SKI-Ab-negative and s-TMED5-Ab-positive cases. The s-SKI-Ab and s-TMED5-Ab biomarkers are useful for diagnosing esophageal carcinoma and distinguishing between favorable and poor prognoses.

Deciphering age-specific molecular features in cervical cancer and constructing an angio-immune prognostic model.

Cancer incidence is increasingly seen in younger individuals. Molecular distinctions between young and elderly patients at onset are understudied. This study used public databases to explore genomic, transcriptomic, and immune-related features across age groups in cervical cancer. Additionally, it aims to create a prognostic model applicable across diverse age cohorts, enabling precise patient stratification, and personalized therapies. Gene mutations, expression data, and clinicopathological information were obtained from 317 cervical cancer patients. These patients were divided into a young group and an old group based on the median age of onset. The characteristics of differential gene mutation, gene expression, and immune cells analysis were analyzed by R software. Finally, the prognostic model was constructed by univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox regression analyses of angiogenic and immune gene sets. Its validity was further confirmed using an additional 300 cervical squamous cell carcinoma and endocervical adenocarcinoma tissues. Cervical cancer patients at elderly onset age exhibit a significantly higher frequency of NOTCH1 and TP53 driver mutations compared to young patients, along with a notably higher tumor mutational burden. However, there were no significant differences between the 2 groups in terms of genomic instability and age-related mutational signatures. Differential gene expression analysis revealed that the young group significantly upregulated interferon-alpha and gamma responses and exhibited significantly higher activity in multiple metabolic pathways. Immune microenvironment analysis indicated enrichment of dendritic cells and natural killer cells in the young group, while transforming growth factor-β signature was enriched in the elderly group, indicating a higher degree of immune exclusion. A multigene prognostic model based on angiogenesis and T cell immune gene sets showed excellent prognostic performance independent of clinical factors such as age. High-risk groups identified by the model exhibit significant activation of tumor-promoting processes, such as metastasis and angiogenesis. Our study reveals distinct patterns in cancer-driving mechanisms, biological processes, and immune system status between young and elderly patients at onset with cervical cancer. These findings shed light on the age-specific underlying mechanisms of carcinogenesis. Furthermore, an independent molecular prognostic model is constructed to provide valuable references for patient stratification and the development of potential drug targets.

Pleckstrin Homology Domain Leucine-rich Repeat Protein Phosphatase Acts as a Tumor Suppressor in Oral Squamous Cell Carcinoma.

The pleckstrin homology domain leucine-rich repeat protein phosphatase (PHLPP) family has been found to have both tumor-suppressor and oncogenic properties across various types and locations of cancer. Given that PHLPP has not been previously studied in oral squamous cell carcinoma (SCC), we conducted an assessment of the expression of both its isoforms in oral SCC tissues and cell lines and compared these findings to their corresponding normal counterparts. In addition, we assessed the relationship between PHLPP and clinicopathological factors and patient survival. Quantitative real-time polymerase chain reaction was used to detect the mRNA levels of PHLPP1 and PHLPP2 in cancerous and normal cell lines in addition to 124 oral SCC and noncancerous adjacent epithelia (N = 62, each). Correlations between their expression rate and clinicopathological parameters were further evaluated in 57 patients. Data were statistically analyzed with t test and paired t test, analysis of variance, Mann-Whitney U , and Cox Regression tests ( P < 0.05). We found significantly lower levels of both PHLPP isoforms in oral SCC tissues compared with noncancerous epithelia ( P < 0.001, for both). However, in the cell lines, this difference was significant only for PHLPP1 ( P = 0.027). The correlation between the two isoforms was significant only in cancerous tissues ( P < 0.001). None of the clinicopathologic factors showed significant associations with either of the isoforms and there was no correlation with survival. We showed for the first time that PHLPP1 and PHLPP2 act as tumor suppressors in oral SCC at the mRNA level. The regulation of their mRNA appears to be different between normal and cancerous tissues.

Study of head and neck squamous cell carcinoma transcriptome after proton therapy

Aim. To evaluate changes in the transcriptome of head and neck squamous cell carcinoma (HNSCC) tissue cells in patients after proton therapy.Materials and methods. Biopsy material obtained from 3 HNSCC patients before and after proton therapy at a total dose of 10 isoGy was homogenized, purified, and concentrated. Then total RNA was isolated with further purification and concentration with the RNA Clean &amp; Concentrator kit (Zymo Research). Library quantitation was assessed using the Qubit 2.0 instrument (Invitrogen, Life Technologies). After isolation of 1 μg total RNA for sequencing, libraries were prepared on the Illumina platform using the TruSeq RNA Sample Prep Kit v2 with a 10-cycle enrichment step according to the manufacturer’s recommendations. The quality of RNA and the resulting libraries was checked using the Agilent 2100 Bioanalyzer system (Agilent Tec. Inc., USA). The RIN parameter for RNA was at least 7. The library concentration was assessed by real-time PCR on the CFX96 Touch Real-Time PCR Detection System (Bio-Rad, USA). Final libraries were pooled in equimolar ratios before sequencing on the Illumina HiSeq 2500 platform using 50 base-pair paired-end reads. The Q20 parameter for all samples was &gt; 97%, and the number of reads averaged 60.2 million per sample. Raw reads were processed using the RTA 1.17.21.3 and Casava 1.8.2 (Illumina). The enrichment analysis was performed using the PANTHER 17.0 software.Results. The transcriptome analysis of HNSCC after proton radiation therapy (5 x 2 isoGy) at a total dose of 10 isoGy revealed 1,414 significantly differentially expressed genes. The 10 most and least expressed genes and their associated signaling pathways were identified. A number of signaling pathways associated with the underexpressed genes were detected in HNSCC after proton therapy, such as: STAT5; PD-1 signaling pathway; marked MET-mediated activation of PTK2 signaling pathway, PDGF signaling; CD22-mediated regulation of BCR; and FCERI-mediated MAPK activation. In addition to the above signaling pathways, activation of collagen degradation, FCGR3A-mediated phagocytosis, and FCGR3A-mediated interleukin (IL)-10 synthesis are of interest. In the enrichment analysis among highly expressed genes, keratinization and biological oxidation processes were activated in HNSCC tissues after proton therapy.Conclusion. Proton therapy in HNSCC leads to overexpression of genes involved in the regulation of keratinization and biological oxidation processes as well as to underexpression of genes associated with suppression of signaling pathways: STAT5, PD-1, MET-mediated activation of PTK2 signaling pathway, PDGF signaling; CD22-mediated regulation of BCR; FCERI-mediated MAPK activation, collagen degradation, FCGR3A-mediated phagocytosis activation, and FCGR3A-mediated IL-10 synthesis. All signaling pathways of underexpressed genes function in HNSCC cells if there is no negative influence on the tumor from outside (irradiation or delivery of antitumor drugs). The predominance of suppressed signaling pathways over activated ones most likely indicates a decrease in the functional potential of cells after proton therapy. The dose-dependence of PT effects necessitates further study of changes in cellular and molecular-genetic signatures of HNSCC after proton irradiation with different doses.

The metabolic reprogramming of γ-aminobutyrate in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy. The oncometabolites have been studied in OSCC, but the mechanism of metabolic reprogramming remains unclear. To identify the potential metabolic markers to distinguish malignant oral squamous cell carcinoma (OSCC) tissue from adjacent healthy tissue and study the mechanism of metabolic reprogramming in OSCC. We compared the metabolites between cancerous and paracancerous tissues of OSCC patients by 1HNMR analysis. We established OSCC derived cell lines and analyzed their difference of RNA expression by RNA sequencing. We investigated the metabolism of γ-aminobutyrate in OSCC derived cells by real time PCR and western blotting. Our data revealed that much more γ-aminobutyrate was produced in cancerous tissues of OSCC patients. The investigation based on OSCC derived cells showed that the increase of γ-aminobutyrate was promoted by the synthesis of glutamate beyond the mitochondria. In OSCC cancerous tissue derived cells, the glutamate was catalyzed to glutamine by glutamine synthetase (GLUL), and then the generated glutamine was metabolized to glutamate by glutaminase (GLS). Finally, the glutamate produced by glutamate-glutamine-glutamate cycle was converted to γ-aminobutyrate by glutamate decarboxylase 2 (GAD2). Our study is not only benefit for understanding the pathological mechanisms of OSCC, but also has application prospects for the diagnosis of OSCC.

The Role of Infiltrated T Lymphocyte in Oral Squamous Cell Carcinoma: Insights into Clinicopathological Characteristics and Prognosis.

To compare and analyze the presence of CD4+ and CD8 + lymphocyte infiltrates in Oral squamous cell carcinoma (OSCC) tissue versus adjacent tissue and their clinical significance. We enrolled a total of 152 patients diagnosed with OSCC, all of whom had confirmed diagnoses through pathological reports. Clinical and demographics data were extracted from medical records. Tissue microarrays were constructed and immunohistochemical staining for CD4 and CD8 was performed. The average number of infiltrating CD4+ T cells in OSCC tumor tissue was 1026.22±1163.36 cells/mm2, which did not significantly differ from the count in adjacent tissue, which was 1163.36±1013.23 cells/mm2. However, the number of CD8+ T cell infiltration in tumor tissue was significantly higher than in adjacent tissue (655.25±705.70 vs 504.56±659.26 cells/mm2, p = 0.026). We observed that, among patients who consumed alcohol, the CD4+ T cell infiltration in tumor tissue being significantly lower than that in adjacent tissue (P=0.036). Moreover, the CD8+ T cell infiltration in cancer tissue was significantly higher than in adjacent tissue for T1-2 patients (p=0.005). Patients with higher CD8+ T cell in tumor tissue exhibited significantly improved overall survival (p = 0.043). Multivariate analyses revealed that alcohol consumption had a significant impact on the number of CD4+T lymphocytes in tumor tissue (OR = 0.403, P = 0.033) while T stage was the independent factor affecting CD8+ T lymphocyte infiltration in tumor tissue (OR = 0.459, P = 0.031). OSCC patients with a higher number of CD8+ T lymphocyte infiltration in tumor tissue exhibited an improved prognosis.

Abstract 6217: Differential genome-wide gene regulatory networks for lung cancer

Abstract Background: Lung cancer remains the leading cause of cancer death worldwide due to the fact that most cases are diagnosed at distant stages, and treatment is less effective. During the past two decades, much effort has been devoted to understanding tumor biology and developing targeted therapeutics, which have significantly improved patient survival. With the increasingly available multi-omics data from healthy controls and lung cancer patients, we constructed gene regulatory networks for the two main subtypes of non-small-cell lung cancer (NSCLC), the most common type of lung cancer. In addition, differential networks were constructed by integrative analysis of data from lung cancer tissue and tissues from healthy lungs. Methods: Transcriptomics and genomic data were obtained from the patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissue available in The Cancer Genome Atlas (TCGA) project, and both types of omics data of normal lung tissue were downloaded from The Genotype-Tissue Expression (GTEx) consortium. The networks for each subtype and the differential networks were constructed by utilizing our newly developed machine learning tools, two-stage penalized least square (2SPLS) approach, and analysis of variance of directed networks (NetANOVA), respectively. Results: For the top three identified subnetworks of LUAD, we identified some well-known genes associated with lung cancer, such as EGFR, IRF1, KRAS, ERBB2, PIK3CA, MYC, at bootstrap frequency &amp;gt;90%. Based on the top three subnetworks with a bootstrap frequency of 100%, results from the Ingenuity Pathway Analysis (IPA) indicated several significant pathways, primary immunodeficiency signaling and communication between innate and adaptive immune cells. GO enrichment analysis showed statistically significant biological processes, including immune response, extracellular matrix organization, and significant KEGG pathways such as Hematopoietic cell lineage. The differential networks between LUAD, LUSC, and healthy lungs showed the same regulations across all three groups, such as the regulation between EEF2 and RACK1, the perturbations between LUAD and healthy (two-way regulations between HIGD2A and ARL10), and LUSC and healthy (GRB14 regulates EIF3E) respectively. In addition, we identified the differences between LUAD and LUSC, such as bi-directional regulations between CLTB and ARL10. Conclusion: Although all groups share most regulations, we identified differential gene regulations between healthy lung tissue and lung cancer tissue and between LUAD and LUSC of NSCLC. Using multi-omics data generated from lung tissues, coupled with advanced machine learning methods, the causal relationships between genome-wide genes from the analysis will help us understand the molecular mechanism of lung cancer and facilitate the development of personalized treatment strategies. Citation Format: Min Zhang, Zhongli Jiang, Dabao Zhang. Differential genome-wide gene regulatory networks for lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6217.

Abstract 3644: Uncover spatial signatures of tumor microenvironment and oncogenic pathways using 6,000-plex single-cell spatial molecular imaging on FFPE skin squamous cell carcinoma

Abstract Background: Tumor progression and therapeutic response are regulated by the tumor microenvironment. Understanding the spatial association and architecture of molecular characteristics and composition of tumor immune microenvironment at single-cell and subcellular resolution encourages improvements in clinical prognosis and immunotherapy benefits. Single-cell Spatial profiling technologies permit the study of transcriptional activity at the spatial, single-cell level and provide abundant, high-resolution information required for the identification of clinical-related features in immuno-oncology. Methods: We performed an ultra-high-plex RNA assay to detect 6,000 targets simultaneously in situ on FFPE human skin squamous cell carcinoma using the CosMx™ Spatial Molecular Imager (SMI). For the selection of regions of interest, four protein markers and DAPI were co-detected on the same tissue slide. Tertiary analysis algorithms were developed for cell typing, co-localization of genes and ligands, cell-cell interaction, and pathway analysis. Results: Thousands of transcripts were simultaneously detected with high sensitivity and specificity on the FFPE skin squamous cell carcinoma tissue section at single-cell subcellular resolution. We investigated the tumor microenvironment including cell types, their spatial distribution and proportion of diversified immune cells in the tumor compartment. The cell typing results revealed many cancerous subpopulations, which resolved spatially from cells that lacked any defining marker genes. We also assessed distances between immune cells and their nearest functional-related neighbors. Moreover, we revealed the ligands co-localization, as well as spatial patterns of direct cell-cell interactions and signaling pathways. We found that some genes have elevated expression in macrophages which are near cancer compared to those are far from cancer cells, empowering the molecular investigation of novel signaling between immune and cancer cells in tumor immune microenvironment. Conclusions: Single-cell spatial measurements of 6,000 RNA and four proteins on the same tissue section, along with a large viewing area on archival FFPE tissue, provide a novel tool to reveal the spatial signature of tumor microenvironment and oncogenic pathways, facilitating the next level of cancer and therapeutic research. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Michael Patrick, Shanshan He, Saskia Ilcisin, David Kroeppler, Patrick Danaher, Jason Reeves, Mark Gregory, Haiyan Zhai, Michael Rhodes, Joseph Beechem. Uncover spatial signatures of tumor microenvironment and oncogenic pathways using 6,000-plex single-cell spatial molecular imaging on FFPE skin squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3644.

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre- and one-week post-operative sera and urines from 560 participants across three hospitals, with machine learning and WGCNA. Aberrations in ‘alanine, aspartate and glutamate metabolism’ proved to be prevalent throughout the ESCC evolution, consistently identified by NMR and MS, and reflected in 16 serum and 10 urine metabolic signatures in both discovery and validation sets. NMR-based simplified panels of any five serum or urine metabolites outperform clinical serological tumor markers (AUC = 0.984 and 0.930, respectively), and are effective in distinguishing early-stage ESCC in test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively, NMR-based biofluid screening can reveal characteristic metabolic events of ESCC and be feasible for early detection (ChiCTR2300073613).

Bioengineered Hydrogels Recapitulate Fibroblast Heterogeneity in Cancer.

Recently mapped transcriptomic landscapes reveal the extent of heterogeneity in cancer-associated fibroblasts (CAFs) beyond previously established single-gene markers. Functional analyses of individual CAF subsets within the tumor microenvironment are critical to develop more accurate CAF-targeting therapeutic strategies. However, there is a lack of robust preclinical models that reflect this heterogeneity in vitro. In this study, single-cell RNA sequencing datasets acquired from head and neck squamous cell carcinoma tissues to predict microenvironmental and cellular features governing individual CAF subsets are leveraged. Some of these features are then incorporated into a tunable hyaluronan-based hydrogel system to culture patient-derived CAFs. Control over hydrogel degradability and integrin adhesiveness enabled derivation of the predominant myofibroblastic and inflammatory CAF subsets, as shown through changes in cell morphology and transcriptomic profiles. Last, using these hydrogel-cultured CAFs, microtubule dynamics are identified, but not actomyosin contractility, as a key mediator of CAF plasticity. The recapitulation of CAF heterogeneity in vitro using defined hydrogels presents unique opportunities for advancing the understanding of CAF biology and evaluation of CAF-targeting therapeutics.

CeRNA Network and WGCNA Analyses of Differentially Expressed Genes in Cervical Cancer Tissues for Association with Survival of Patients.

The study aims to search and identify differentially expressed genes (DEGs) in cervical cancer tissues as novel biomarkers to predict cervical cancer prognosis. The Cancer Genome Atlas (TCGA) data on gene expression profiles in cervical cancer were downloaded and analyzed using R software to identify DEGs in cervical cancer tissues. miRNAs targeted by differentially expressed long non-coding RNAs (DElncRNAs) and mRNAs targeted by microRNAs (miRNAs) were identified using the online miRcode, miRTarBase, TargetScan, and miRDB tools. The ceRNA network and lncRNA expression modules in cervical cancer tissues were constructed using weighted gene co-expression network analysis (WGCNA) and analyzed bioinformatically. The Kaplan-Meier analysis was performed to confirm these DEGs as prognostic markers. Immunohistochemical (IHC) analysis was used to verify expression of the hub genes in 10 paired cervical cancer and normal tissues. A total of 1914 DEmRNAs, 210 DElncRNAs, and 67 DEmiRNAs were identified in cervical cancer samples. There were 39 lncRNAs, 19 miRNAs, and 87 mRNAs involved in the ceRNA network and 25 DElncRNAs, three DEmiRNAs, and four mRNAs involved in the ceRNA sub-network. CACNA1C-AS1 was associated with the yellow and blue modules in the ceRNA sub-network, and LIFR-AS1 was associated with the blue module. The DEmRNAs were involved in cancer-related pathways, and three hub genes (i.e., E2F1, CCNB1, and CCNE1) were highly expressed in cervical squamous cell carcinoma and adenocarcinoma tissues and associated with the prognosis of patients. The ceRNA network and WGCNA analyses are useful to identify novel DEGs that can serve as prognostic markers in cervical cancer. The DEGs will be validated in future studies.

Severely polarized extracellular acidity around tumour cells.

Extracellular pH impacts many molecular, cellular and physiological processes, and hence is tightly regulated. Yet, in tumours, dysregulated cancer cell metabolism and poor vascular perfusion cause the tumour microenvironment to become acidic. Here by leveraging fluorescent pH nanoprobes with a transistor-like activation profile at a pH of 5.3, we show that, in cancer cells, hydronium ions are excreted into a small extracellular region. Such severely polarized acidity (pH <5.3) is primarily caused by the directional co-export of protons and lactate, as we show for a diverse panel of cancer cell types via the genetic knockout or inhibition of monocarboxylate transporters, and also via nanoprobe activation in multiple tumour models in mice. We also observed that such spot acidification in ex vivo stained snap-frozen human squamous cell carcinoma tissue correlated with the expression of monocarboxylate transporters and with the exclusion of cytotoxic T cells. Severely spatially polarized tumour acidity could be leveraged for cancer diagnosis and therapy.

Elucidating Hedgehog pathway's role in HNSCC progression: insights from a 6-gene signature

With the emergence of targeted inhibition strategies for Hedgehog signaling in cancer, multiple Hedgehog signaling pathway-related biomarkers have become the focus of research. SsGSEA algorithm was employed to analyze the Hedgehog pathway scores of samples in TCGA-HNSC dataset and divide them into two groups. Weighted co-expression network analysis was performed to identify modules strongly associated with the Hedgehog pathway. Differentially up-regulated genes in tumor samples in comparison to the normal ones were screened by Limma, in which genes belonging to modules strongly related to Hedgehog pathway were further filtered by LASSO reduction and multivariate Cox regression analysis to develop a model. ESTIMATE and CIBERSORT were served to characterize the tumor microenvironment (TME). TIDE assessed immunotherapy response. Hedgehog pathway activity was significantly higher in head and neck squamous cell carcinoma (HNSCC) tissues than in normal tissues and was correlated with HNSCC survival, glycan, cofactors and vitamins, drug metabolism, and matrix scores. Six genes (SLC2A3, EFNB2, OAF, COX4I2, MT2A and TXNRD1) were captured to form a Hedgehog associated 6-gene signature, and the resulting risk score was an independent indicator of HNSCC prognosis. It was significantly positively correlated with stromal score, metabolism, angiogenesis and inflammatory response. Patients in low-risk group with a low TIDE score had higher immunotherapy sensitivity relative to those in high-risk group. This study revealed novel findings of the Hedgehog pathway in HNSCC progression and opened up a Hedgehog pathology-related signature to help identify risk factors contributing to HNSCC progression and help predict immunotherapy outcomes.

Prognostic significance of RKIP, TGM2, and CMTM4 expression in oral squamous cell carcinoma.

The expression of RKIP, TGM2, and CMTM4 in oral squamous cell carcinoma (OSCC) and normal oral tissues was detected and their correlations were analyzed. The relationships between RKIP, TGM2, and CMTM4 and the clinicopathological parameters and prognosis of patients were analyzed. Seventy cancerous and adjacent normal tissue samples were selected, recorded in the pathology department, and embedded in paraffin. Protein expression was detected by immunohistochemistry. Statistical software (SPSS 25.0, IBM Corporation) was used for the statistical analysis. The chi-squared (χ2) test was used to analyze the expression of RKIP, TGM2, and CMTM4 proteins and their clinicopathological features. Differences in RKIP, TGM2, and CMTM4 protein levels between OSCC and normal tissues were compared using a χ2 test. Survival analysis was performed using the Kaplan-Meier method, and differences between survival curves were determined using the log-rank test. The effects of RKIP, TGM2, and CMTM4 expression on patient prognosis were analyzed using a multivariate Cox proportional hazards regression model. P < .05 was considered statistically significant. The expression level of RKIP correlated with age and clinical stage (P < .05). TGM2 was associated with clinical stage and lymph node metastasis (P < .05). The expression of CMTM4 increased with a decrease in cancer differentiation. Kaplan-Meier survival analysis suggested that the positive expression of TGM2 and CMTM4 may predict poor prognosis in patients with OSCC. The multivariate Cox proportional hazards regression model suggested that TGM2 could be an independent prognostic factor for patients with OSCC. Combined expression of TGM2 and CMTM4 can be used as an indicator to evaluate the risk of metastasis and prognosis of OSCC.

Ex vivo radiation sensitivity assessment for individual head and neck cancer patients using deep learning-based automated nuclei and DNA damage foci detection

IntroductionTumor biopsy tissue response to ex vivo irradiation is potentially an interesting biomarker for in vivo tumor response, therefore, for treatment personalization. Tumor response ex vivo can be characterized by DNA damage response, expressed by the large-scale presence of DNA damage foci in tumor nuclei. Currently, characterizing tumor nuclei and DNA damage foci is a manual process that takes hours per patient and is subjective to inter-observer variability, which is not feasible in for clinical decision making. Therefore, our goal was to develop a method to automatically segment nuclei and DNA damage foci in tumor tissue samples treated with radiation ex vivo to characterize the DNA damage response, as potential biomarker for in vivo radio-sensitivity. MethodsOral cavity tumor tissue of 21 patients was irradiated ex vivo (5 or 0 Gy), fixated 2 h post-radiation, and used to develop our method for automated nuclei and 53BP1 foci segmentation. The segmentation model used both deep learning and conventional image-analysis techniques. The training (22 %), validation (22 %), and test set (56 %) consisted of thousands of manually segmented nuclei and foci. The segmentations and number of foci per nucleus in the test set were compared to their ground truths. ResultsThe automatic nuclei and foci segmentations were highly accurate (Dice = 0.901 and Dice = 0.749, respectively). An excellent correlation (R2 = 0.802) was observed for the foci per nucleus that outperformed reported inter-observation variation. The analysis took ∼ 8 s per image. ConclusionThis model can replace manual foci analysis for ex vivo irradiation of head-and-neck squamous cell carcinoma tissue, reduces the image-analysis time from hours to minutes, avoids the problem of inter-observer variability, enables assessment of multiple images or conditions, and provides additional information about the foci size. Thereby, it allows for reliable and rapid ex vivo radio-sensitivity assessment, as potential biomarker for response in vivo and treatment personalization.

DDX27 regulates oral squamous cell carcinoma development through targeting CSE1L

The headings aimsDEAD-box helicase 27 (DDX27), a member of the DEAD-Box nucleic acid helicase family, holds an elusive role in oral squamous cell carcinoma (OSCC). This study aims to unravel the regulatory functions of DDX27 in OSCC and explore its downstream targets. Materials and methodsA commercial oral squamous cell carcinoma (OSCC) tissue microarray (TMA) was utilized. We analyzed differentially expressed genes in OSCC through the GEO database. Target gene silencing was achieved using the shRNA-mediated lentivirus method. Coexpedia analysis identified co-expressed genes associated with DDX27. Additionally, a Co-Immunoprecipitation (Co-IP) experiment confirmed the protein interaction between DDX27 and CSE1L. Xenograft tumor models were employed to evaluate DDX27's role in OSCC tumor formation. Key findingsElevated DDX27 expression in OSCC correlated with a higher pathological grade. DDX27 knockdown resulted in decreased cell proliferation, increased apoptosis, inhibited cell migration, and induced G2/M phase cell cycle arrest, as well as impaired tumor outgrowth. Coexpedia analysis identified STAU1, NELFCD, and CSE1L as top co-expressed genes. Lentiviral vectors targeting STAU1, NELFCD, and CSE1L revealed that silencing CSE1L significantly impaired cell growth, indicating it as a downstream target of DDX27. Cell rescue experiments demonstrated that increased DDX27 levels ameliorated cell proliferation, attenuated apoptosis, and CSE1L depletion blocked cell development induced by DDX27 overexpression. SignificancesThis study highlighted DDX27 as a potential therapeutic target for OSCC treatment, shedding light on its crucial role in OSCC development. Targeting DDX27 or its downstream effector, CSE1L, holds promise for innovative OSCC therapies.

Pseudoimmunofluorescent immunohistochemistry image analysis of phosphorylated signaling proteins in human esophageal squamous cell carcinoma tissue.

Immunohistochemistry is primarily employed to visualize the localization of specific molecules in tissue samples. However, there is an increasing need for software-assisted quantitative assessment. In the present study, we performed inverted blue channel-based pseudoimmunofluorescence image analysis using original immunohistochemistry images. In human esophageal squamous cell carcinoma tissues, various humoral factors promote the phosphorylation of signaling proteins, including proteinkinase B (Akt) and/or extracellular signal-regulated kinase 1/2 (ERK1/2), leading to tumor progression. Our method demonstrated applicability in the analysis of localized signaling proteins in histological sections. Relatively high phosphorylated Akt (p-Akt) intensity was observed in the cancer-stroma adjacent (Adj) and noncancerous regions of the superficial layer(SL). Furthermore, localized phosphorylated ERK1/2 (Thr202/Tyr204) was observed in the Adj of the SL and invasive front, distinct from the pattern of p-Akt(Ser473) and p-Akt (Thr308). In conclusion, pseudoimmunofluorescent immunohistochemistry image analysis is useful for the quantitative assessment and objective interpretation of localized signaling proteins in esophageal squamous cell carcinoma. The method can also be applied to analyze various immunohistochemistry images from diverse tissues.

Resveratrol is an inhibitory polyphenol of epithelial-mesenchymal transition induced by Fusobacterium nucleatum

ObjectiveResveratrol is a natural phytoalexin that has anti-inflammatory properties, reverses doxorubicin resistance, and inhibits epithelial-mesenchymal transition (EMT) in many types of cancer cells. Fusobacterium nucleatum is reportedly enriched in oral squamous cell carcinoma (OSCC) tissues compared to adjacent normal tissues, sparking interest in the relationship between F. nucleatum and OSCC. Recently, F. nucleatum was shown to be associated with EMT in OSCC. In the present study, we aimed to investigate the effects of the natural plant compound resveratrol on F. nucleatum-induced EMT in OSCC. DesignF. nucleatum was co-cultured with OSCC cells, with a multiplicity of infection (MOI) of 300:1. Resveratrol was used at a concentration of 10 μM. Cell Counting Kit-8 and wound healing assays were performed to examine the viability and migratory ability of OSCC cells. Subsequently, real-time RT-PCR was performed to investigate the gene expression of EMT-related markers. Western blotting and immunofluorescence analyses were used to further analyze the expression of the epithelial marker E-cadherin and the EMT transcription factor SNAI1. ResultsCo-cultivation with F. nucleatum did not significantly enhance cell viability. The co-cultured cells displayed similarities to the positive control of EMT, exhibiting enhanced migration and expression changes in EMT-related markers. SNAI1 was significantly upregulated, whereas E-cadherin, was significantly downregulated. Notably, resveratrol inhibited F. nucleatum-induced cell migration, decreasing the expression of SNAI1. ConclusionsResveratrol inhibited F. nucleatum-induced EMT by downregulating SNAI1, which may provide a target for OSCC treatment.

A positive feedback between PDIA3P1 and OCT4 promotes the cancer stem cell properties of esophageal squamous cell carcinoma

BackgroundIncreasing evidence has indicated that long non-coding RNAs (lncRNAs) have been proven to regulate esophageal cancer progression. The lncRNA protein disulfide isomerase family A member 3 pseudogene 1 (PDIA3P1) has been shown to promote cancer stem cell properties; however, its mechanism of action remains unclear. In this study, we investigated the regulation of esophageal cancer stem cell properties by the interaction of PDIA3P1 with proteins.MethodsThe GEPIA2 and Gene Expression Omnibus databases were used to analyze gene expression. PDIA3P1 expression in human esophageal squamous cell carcinoma (ESCC) tissues and cell lines was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Loss-of-function experiments were performed to determine the effects of PDIA3P1 on ESCC cell proliferation, migration, and invasion. The sphere formation assay, number of side population cells, and CD271 + /CD44 + cells were detected by flow cytometry to identify the cancer stem cell properties. RNA immunoprecipitation (RIP), RNA pull-down, co-immunoprecipitation (co-IP), dual luciferase reporter, and cleavage under targets and tagmentation (CUT&Tag) assays were performed to elucidate the underlying molecular mechanisms.ResultsPDIA3P1 expression was upregulated in ESCC cell lines and tissues. Functionally, higher PDIA3P1 expression promoted cell proliferation, invasion, and metastasis and inhibited apoptosis in esophageal cancer. Importantly, PDIA3P1 promoted cancer stem cell properties in ESCC. Mechanistically, PDIA3P1 interacted with and stabilized octamer-binding transcription factor 4 (OCT4) by eliminating its ubiquitination by the ubiquitinating enzyme WW domain-containing protein 2 (WWP2). Moreover, as a transcription factor, OCT4 bound to the PDIA3P1 promoter and promoted its transcription.ConclusionsOur research revealed a novel mechanism by which a positive feedback loop exists between PDIA3P1 and OCT4. It also demonstrated that the PDIA3P1-WWP2-OCT4 loop is beneficial for promoting the cancer stem cell properties of ESCC. Owing to this regulatory relationship, the PDIA3P1-WWP2-OCT4-positive feedback loop might be used in the diagnosis and prognosis, as well as in the development of novel therapeutics for esophageal cancer.