Transcriptome analysis of Oral Squamous Cell Carcinoma Utilizing Expression Datasets of Middle-aged Indian Males

doi:10.21203/rs.3.rs-4936223/v1

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Transcriptome analysis of Oral Squamous Cell Carcinoma Utilizing Expression Datasets of Middle-aged Indian Males

https://doi.org/10.21203/rs.3.rs-4936223/v1

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Oral squamous cell carcinoma (OSCC) is a major contributor to disease burden and mortality, particularly in rural India. This study aims to identify genes associated with OSCC through differential expression analysis utilizing datasets (BioProject: PRJNA853478) obtained from middle-aged Indian males. Differential expression analysis, transcript assembly, and functional enrichment were performed using standard Tuxedo II suite protocols, along with the StringTie, Ballgown, and KOBAS packages. The comprehensive analysis identified genes like NOTCH1, PTEN, and NCBP2 as significantly associated with OSCC. Furthermore, our findings contrast with existing studies, as we did not observe a significant association of crucial mediators of OSCC such as PROS1 and CTBP1 genes, which may be attributed to ethnic variations and differing sampling strategies. Importantly, we observed a significant enrichment of DNA repair pathways, particularly mismatch repair genes suggesting these pathways as promising prognostic and therapeutic targets for OSCC. Overall, our findings have identified key genes associated with OSCC, and the expression profiling of these genes may serve as valuable prognostic markers for the detection of OSCC, particularly in the context of the Indian population.

Biological sciences/Biological techniques

Biological sciences/Biotechnology

Biological sciences/Cancer

Biological sciences/Cell biology

Biological sciences/Computational biology and bioinformatics

Oral squamous cell carcinoma

next-generation sequencing

RNA-seq

Differential gene expression

expression datasets

Oral cancer is a prominent cancer type accounting for 177,000 mortalities globally in 2020 [1]. India alone bears a significant burden of the disease, with approximately 77,000 new cases and 52,000 deaths annually [2], and advanced cancer stages correlating with a 20% five-year survival rate [3]. Predisposition to oral cancer is significantly affected by higher exposure to chewing tobacco which particularly places the Indian population at greatest risk of early onset and development of the disease [2].

Approximately half of the head and neck tumour incidents involve tumorigenesis in the oral cavity [4] and approximately 90% of neoplasms originate from squamous cells [5, 6], hence such cancers are called oral squamous cell carcinoma (OSCC). Other malignant oral abrasions include erythroplasia, dysplastic leukoplakia, oral submucous fibrosis, and oral epithelium dysplasia (OED) [7, 8]. Oral carcinogenesis is driven by a genetic alteration in epithelial cells causing dysregulation of cell proliferation and differentiation during the dysplasia stage [9](Fig. 1). Moreover, epithelial-mesenchymal transition (EMT) is a triggering event for cancer invasion and aggressive metastasis [10]. The epithelial cells are characterized by polarity and strong cell-to-cell adhesion, which is lost during the activation of EMT[10, 11].

Timely diagnosis and treatment of oral cancer are extremely critical for improving patient outcomes, as early detection is associated with higher survival rates and better quality of life. However, in rural India, achieving prompt diagnosis is challenging due to several factors. First, the incidence of raw tobacco chewingࣧa significant risk factor for OSCC is considerably higher in rural areas compared to urban regions [12–14]. Second, rural areas often lack adequate clinical settings and comprehensive health services, making it difficult for patients to access timely and effective care [15–17]. Furthermore, the economic constraints of rural patients typically hinder their ability to afford specialized treatments, exacerbating delays in diagnosis and intervention [18]. These barriers collectively contribute to poorer prognosis and have been largely associated with advanced stages of oral cancer and increased mortality rates among rural populations [19]. It has been observed that the detection of oral cancer at stage I was associated with a favorable prognosis with an estimated 80% survival rate [20]. In contrast, when the same lesions were diagnosed at stage III, the survival rate significantly dropped to approximately 20% [21]. These observations thus stress upon the urgent need for the identification of new prognostic markers, that are easily accessible and field deployable. Further, such advancements especially hold great importance in rural Indian settings, where they can significantly improve patient outcomes by enabling earlier and more effective interventions. Given the recent developments in rapid next-generation sequencing, especially RNA-seq methods, have paved the way for biomarker stratification-based prognoses that could contribute to an increased likelihood of early intervention and subsequently enhance survival rates, especially in rural clinical settings [15–17].

In this view, the present study aims to identify genetic signatures associated with oral cancer. To achieve this, we utilized an expression dataset (BioProject: PRJNA853478) and conducted differential expression analysis comparing oral cancer tumor tissue and healthy tissue obtained from the Indian male population.

Transformation of the normal oral squamous epithelium into OSCC through a series of stages influenced by mutagenic agents (e.g., tobacco) and epigenetic alterations (e.g., DNA methylation, histone modifications, oncoviral infections). The progression includes initial epithelial hyperplasia, followed by dysplasia characterized by dysregulation of key genes such as TP53, NOTCH1, STAT3, RB1, and cell cycle regulators (CDKs, cyclins). These molecular disruptions promote cancer cell invasion and the acquisition of epithelial-to-mesenchymal transition (EMT) traits, driven by signaling pathways including TGF-beta, Wnt, and EGFR. The invasive cancer cells stimulate angiogenesis via VEGF, leading to metastasis, which is further associated with the presence of tumor-associated macrophages and tumor-infiltrating lymphocytes. (Inset) Cell morphology from the tissue biopsy shows progression of oral epithelium undergoing hyperplasia to dysplasia and ultimately progressing to carcinoma in situ (advanced stage of precancerous lesions).

2.1 Data collection and analysis

The expression datasets were derived from the Sequence Read Archive (SRA) database (Project ID: PRJNA853478, by Gujarat Biotechnology Research Centre, Gujrat, India)(Table 1). (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA853478). The study included bulk RNA-Seq reads of 3 tumor samples and 5 healthy individuals from Indian males, ages ranging from 37 to 48 years. The NCBI-SRA database was used to retrieve the accession IDs, which were then downloaded to the DDBJ Read Archive (DRA) database. The tissue samples were assigned SRR Accession IDs represented as SRR198944XX (where XX ϵ [47, 54]). (For detailed sample characteristics, please refer to Supplementary Table S1).

The retrieved .sra files were split using the SRAToolkit (https://hpc.nih.gov/apps/sratoolkit.html). The human reference genome (.fasta)and gene annotation (.gtf) version GRCh38 were downloaded from ENSEMBL (https://asia.ensembl.org/Homo_sapiens/Info/Index). All the raw RNAseq reads were validated for a quality check using the FastQC program (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and low-quality reads were trimmed, and adapters were removed using the TrimGalore program (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) (Supplementary Figure S1 & Supplementary Table S2). The trimmed reads were aligned to the human reference genome using HISAT2.0 (https://daehwankimlab.github.io/hisat2/) [22]. The output SAM file was converted into an indexed BAM file using Samtools (https://www.htslib.org/). Further, the indexing and coordinate sorting of the BAM file were carried out to retrieve the overlapping genomic regions. The entire sequencing analysis using the tuxedo protocol was executed on a 64-bit computer system using Ubuntu 22.04.2 version with 16GB RAM.

2.2 Transcript assembly and differential gene expression

The processed coordinate-sorted BAM file obtained from the previous step was used for transcript assembly using StringTie ((https://ccb.jhu.edu/software/stringtie/)) [23]. The individual .gtf files were merged by using –the merge StringTie function. Differential gene expression analysis was performed using the Ballgown package (https://www.bioconductor.org/packages/release/bioc/html/ballgown.html) with the - stringtie-eB command. The detailed workflow is provided in Fig. 2.

2.3 Functional enrichment and pathway analysis

The genes showing significant differential expression (differentially expressed genes -DEGs) across the classes in the given category were identified (p < 0.001), and their prognostic significance of the DEGs, were evaluated against the clinical pathology database of the Human Protein Atlas (https://www.proteinatlas.org/) [24]. The list of genes that were not reported till date for OSCC were shortlisted based on their expression as a function of FPKM values. Gene Ontology (GO) and functional enrichment analyses were performed using KOBAS 3.0 annotation and enrichment modules (http://bioinfo.org/kobas) [25] to elucidate signalling pathways and molecular functions predominant in oral cancer samples.

The raw FASTQ files were obtained by the SRA toolkit and the quality check was performed with FASTQC. TrimGalore was used for trimming the raw RNA-seq files. The alignment to the human genome reference was done by HISAT2 and SAM files were obtained. The SAM files are converted into BAM files by using Sam tools. Followed by BAM file indexing and sorting, the StringTie suite was used for transcript assembly and merging transcripts. Differential expression analysis was performed with a ballgown package followed by functional enrichment analysis.

Oral cancers constitute a significant public health challenge in India, bearing nearly one-third of the global burden and ranking second in the world for the highest number of cases [26, 27], with Oral Squamous Cell Carcinoma alone accounting for 84–97% of these cases [28]. This high prevalence is largely attributed to widespread habits like tobacco use in various forms such as gutka, zarda, among others[29]. Compounding to this issue is the delayed diagnosis, with 60–80% of cases detected in advanced stages, which in turn increases the disease burden [30]. Early detection thus becomes necessary in improving outcomes and reducing mortality associated with oral cancer, especially in the context of rural India. In view of this, this present study aims to identify molecular markers that hold prognostic significance for oral cancer, utilizing expression datasets. Dataset information with phenotype data with sample ID, gender, and phenotype is shown in Table 1 and the related reads counts as a function of FPKM values for each sample of the dataset are shown in Fig. 3. In this discussion, we will draw similarities and comparisons of the differential expressed genes from our study in reference to the published literature. This analysis will in fact facilitate a strong equivocal emphasis on genes that are associated with oral cancer that may indeed assist in providing cues of genetic markers of oral cancer with prognostic relevance.

Table 1

Phenotype data showcasing sample ID, gender, and population (The highlighted ones are the tumor samples)
Sample ids	Sex	Population
SRR19894447	Male	Normal
SRR19894448	Male	Normal
SRR19894449	Male	Tumor
SRR19894450	Male	Normal
SRR19894451	Male	Tumor
SRR19894452	Male	Normal
SRR19894453	Male	Tumor
SRR19894454	Male	Normal

3.1 Differential expression and association of genes with OSCC

In the present study, upon differential expression analysis comparing datasets of OSCC samples with health controls, we observed that genes like NOTCH1, NCBP2, TP53, PTEN, AURKB, and RB1 were significantly associated with oral cancers. The relative expression of these genes in normal and tumor samples is shown in Fig. 4.

In assertion to our findings, various studies have highlighted dysfunction in the Notch signalling pathway contributing to cancerous lesion development. For instance, recent research by Wu et al. (2021) emphasized that NOTCH1 expression correlates with oral squamous cell carcinoma (OSCC) progression, while the presence of mutated NOTCH1 aids in prognostic stratification when combined with clinicopathologic parameters [31]. NOTCH1 has been reported in various studies to exhibit both oncogenic and antiproliferative effects, with predominant findings suggesting its oncogenic nature particularly by upregulation in oral cancers [32, 33]. Despite these insights, therapeutic strategies targetingNotch1 mutations in oral and head and neck tumours face challenges for the limited efficacy. For example, γ-secretase inhibitors, CB-103, and antibodies targeting DLL-4, NOTCH1, and NOTCH2/3 have been explored but have shown limited success in clinical applications [34].

In consensus with the present study, NCBP2 is significantly linked to the pathogenesis of Head and neck squamous cell carcinoma (HNSCC) with studies indicating its upregulation in more than 30% of patients [35]. Experimental depletion of NCBP2 has demonstrated reductions in OSCC cell proliferation and migration highlighting it as a viable therapeutic target in OSCC[36]. Studies have suggested thatNCBP2 closely interacts with abnormal N7-methylguanosine (m7G), a marker linked to tumour initiation which influences the expression of CCL4/CCL5, which is pivotal in impacting the efficacy of immunotherapy in HNSCC [37]. Such regulatory roles suggest that targeting NCBP2 could potentially induce a transformative shift in oral tumours from a "cold" to a "hot" state, thereby enhancing therapeutic outcomes.

PTEN genetic aberrations in oral squamous cell carcinoma (OSCC) have been variably reported[38, 39]. While Shin et al. 2022 identified PTEN gene mutations in a subset of OSCC cases, highlighting its relevance in tumor development [40], recent findings among Indian populations however documented only intronic deletions in PTEN and found no mutations in the coding region with no pathological outcomes[41]. Nevertheless, immunohistochemical analyses have consistently shown downregulation of PTEN protein expression in cancerous tissues, for example, loss of PTEN protein expression was found to be prevalent in OSCC ranging from 29–96.3% across various studies underscoring its role as a potential biomarker for OSCC [42−46].

Similar to our analysis, Aurora kinases, particularly AURKA and AURKB, have been shown to play critical roles in the progression of OSCC, specifically, AURKA, has been identified to be significantly up regulated in OSCC cell lines and patient tumor samples, correlating with decreased overall survival rates [47]. Moreover, TP53, a critical tumor suppressor gene that is associated with the present study, has been previously demonstrated to directly bind and inhibit AURKA, influencing OSCC development and progression [48, 49]. Although Aurora kinase inhibitors such as ENMD2076, AZD1152, and AMG900 have shown potential in preclinical studies for inducing growth arrest and apoptosis in OSCC their clinical success remains varied, requiring further treatment approaches to improve outcomes in OSCC patients [50–53].

3.2 Obtaining the biologically significant genes associated with OSCC

The differentially expressed genes were filtered resulting in 56 biologically significant genes. The transcripts were compared on the Human Protein Atlas database to obtain information regarding their implications in cancer. Further, those genes were shortlisted that were not reported in oral cancer (Supplementary Table S3). The expression of the shortlisted genes across the samples is represented by a heatmap (Fig. 5). We found 9 genes viz., PROS1, CTBP1, CDK16, NFIC, PNN, NT5C3A, NYNRIN, ERCC5, and GAS5 that were downregulated in the oral cancer samples, while the other 47 genes are upregulated (Fig. 5). The heatmap representation of FPKM values of genes across all the samples is shown in Fig. 6.The Volcano plot representation of up regulated and down regulated genes is depicted in Fig. 7.

The bar represents the expression level of a specific gene. The expression levels are represented in terms of FPKM values. The x-axis represents the genomic position. The genes are as follows: 1) MSTRG:22024-PROS1, 2) MSTRG:23131-CTBP1, 3) MSTRG:32218-CDK16, 4) MSTRG:15379-NFIC, 5) MSTRG.9105: PNN, 6) MSTRG:28110-NT5C3A, 7) MSTRG:8946-NYNRIN, 8) MSTRG:8649-ERCC5, 9) MSTRG:2426: GAS5. The red color represents a high expression, and the yellow color represents a low expression.

Downregulated genes, indicated in red, exhibit a log2 fold change of less than 0 and a p-value less than 0.001, signifying high statistical significance. Conversely, upregulated genes, shown in blue, display a log2 fold change greater than 0 and a p-value less than 0. 001. The x-axis denotes log2fc and the y-axis denotes -log10 (p-value). The red dots represent downregulated genes with log2fc < 0 and p-value < 0.001. The blue dots represent upregulated genes with log2fc > 0 and p-value < 0.001.

Findings from the current study stand in sheer contrast to the study of Al Kafri et al., (2019)which highlighted PROS1 as a crucial mediator in OSCC. In fact, PROS1 through Tyro3-Erk signaling activation has been demonstrated to significantly promote OSCC progression[54]. This observed difference may be due to ethnic differences and genetic makeup, or even the type of tumour environment, which however requires further functional analysis.

Yet another contrasting finding of the present study to the existing literature is the downregulation of CtBP1 gene. CtBP1 overexpression has been implicated as a "hallmark of cancer," exerting its malignant behavior through transcriptional regulation. Further, subsequent studies have confirmed CtBP1 overexpression in various cancers, such as prostate [55], melanomas [56], colon [57], ovarian [58], and breast cancer [59]. Interestingly, the phenomenon of downregulation of CtBP1in OSCC as observed in the present study is supported by the finding of Poser et al, (2003) that showed significant proportion of melanomas exhibited low mRNA levels of CtBP1[60]. The functional role of CtBP1 has always been debatable in inducing carcinogenesis. For example, Takayama et al. (2013) found that CtBP1 suppresses tumors in AR-positive prostate cancer cells [61], whereas Wang et al. (2012) in the same cells reported CtBP1overexpression in promoting aberrant cell proliferation [62].

In the present findings, we observed downregulation of the Growth arrest-specific 5 (GAS5) gene which was well anticipated. Indeed, GAS5 encoding long non-coding RNA [63]has been shown to have tumour suppressor effects by inducing apoptosis and suppressing tumor angiogenesis across various malignancies including gastric cancer cells and adenocarcinomas [64–67]. Although the full impact of GAS5 expression on OSCC clinical outcomes remains unclear, further functional studies could establish GAS5 as a potential pro-apoptotic prognostic marker for monitoring OSCC progression. Further, in our analysis, NYNRIN gene was found downregulated. Although cellular implications of NYNRIN remain underexplored, yet recent studies have highlighted its constitutional cancer-predisposing mutations, particularly in Wilms tumor cases with biallelic truncating mutations [68] and in melanoma metastasis [69]. Despite its implications in cancer predisposition, the specific functions of NYNRIN in OSCC remain poorly understood. Given the important role of NYNRIN in RNA processing events [70], investigating its role through microRNA–mRNA regulation could provide further insights into OSCC pathogenesis.

In the present study, an important repair gene ERCC5 recruited in nucleotide excision repair (NER), was found to be downregulated. Our functional analysis revealed significant enrichment of repair pathways, particularly NER, likely due to the downregulation of ERCC5. Genetic studies have increasingly associated single-nucleotide polymorphisms in ERCC5 with varying susceptibilities to cancers. As per, The AACR Project GENIE Consortium, 2017, these alterations have been identified in 2.11% of all cancers, prominently in colon adenocarcinoma, lung adenocarcinoma, and endometrioid adenocarcinoma [71]. Recent studies have indicated a significant association between the ERCC5 rs751402 polymorphism and oral cancer risk [72]. Next, in the present study, we found downregulation of transcription factor - NFIC (Nuclear factor I-C) in oral cancer samples, which indeed stands in quite a contrast to the findings of Lee et al., 2009 which have shown that loss of NFIC induces apoptosis in aberrant odontoblasts by suppresses odontogenic cell proliferation and contributing to shortened root formation [73]. While genomic analyses and studies in animal models have underscored the role of NFICgenein carcinogenesis [74], its functional importance remains underexplored in the context of oral cancers.

3.3 Functional enrichment and pathway analysis

Upon functional enrichment analysis, we found that DNA repair pathways (Mismatch repair, nucleotide excision repair, homologous recombination, and Fanconi anemia pathway), cell signaling pathways (EGFR pathway, Notch signaling pathway, and HIF-1 pathway) and metabolic pathways (steroid biosynthesis, nicotinate, and nicotinamide metabolism) to be enriched in patient samples. The enriched pathways and networks associated with oral cancer are depicted in Fig. 8.

Rows represent the enrichment ratio, and the ratio is obtained as input gene number/background gene number. The color codes assigned are based on the enrichment ratio. The functional annotations are grouped if they share the same module number and are represented with the same color. In the circular network, the nodes correspond to an enriched term and the edges represent the connections between two enriched terms with the gene-overlapped ratio surpassing a respective cut-off (default < 0.5). The circular layout of the network is based on the gravitational attraction between the two modes. The bar plot color is correlated with the color in the circular network, defining modules and interactions. Different modules are represented by different colors that denote nodes belonging to specific topological communities within a structured network.

In assertion to our findings, studies have demonstrated the critical role of mismatch repair (MMR) deficiency in areca nutrelated oral squamous cell carcinomas (OSCCs), as a predictor of prognosis in this specific subset of oral cancers [75]. Notably, the presence of MMR in OSCC correlated with an elevated incidence of metachronous malignancies and advanced primary tumors [76]. Supporting our findings concerning DNA repair through homologous recombination (HR) pathways, Ho et al., 2022, demonstrated that deficiencies in HR components are linked to malignant transformations in oral epithelial dysplasia [77]. Additionally, other repair mechanisms, including nucleotide excision repair and base excision repair pathways enriched in our analysis, have previously been associated with the transition from oral leukoplakia to OSCC [78]. The prominence of repair pathways is well demonstrated by the studies of Joshi et al., 2021, which showed strong associations of repair proteins such as XRCC4 and DNA ligase IV in NHEJ as predictive biomarkers for oral squamous cell carcinoma [79].

In our further analysis, similar to the findings from the current study, Comparative genomic hybridization studies by Sparano et al. (2006) revealed frequent alterations in Fanconi anemia genes (BRCA1, BRCA2, FANCD2, and FANCG) in OSCC[80]. These genes are pivotal in maintaining genomic stability through homologous recombination (HR) and are highly involved in the repair of DNA double-strand breaks. The present findings in addition are corroborated by studies of Prime et al., which highlighted the critical role of HR and Fanconi anaemia genes in OSCC development[81]. Moreover, Fanconi anemia pathways, linked to HNSCC through FANC–BRCA methylation, were found to influence survival outcomes in patients exposed to tobacco and alcohol [82].

Apart from repair pathways, we found a significant association of cell signaling pathways to be enriched in oral carcinoma like EGFR-related pathways. EGFR, a highly polymorphic and mutation-prone gene, has been significantly implicated in the pathogenesis of HNSCC affecting over 90% of cases [83–84]. Targeting EGFR has therefore become pivotal in therapeutic strategies for HNSCC, with monoclonal antibodies like Cetuximab zalutumumab, panitumumab, and nimotuzumab showing efficacy in clinical settings [85–87]. Further, we found the Notch signalling pathway, and HIF-1 pathways to be highly enriched in patient samples. In fact, functional assays have demonstrated the pivotal role of HIF-1α in promoting stemness, resistance mechanisms, and epithelial-mesenchymal transition (EMT) in CD44 + cells of HNSCC [88]. Specifically, HIF-1α has been shown to activate NOTCH1 signaling pathways within the CD44 + stem-like cell population of HNSCC, thereby contributing to the acquisition of chemoresistance traits. These critical findings have paved the way for developing therapeutic strategies aimed at targeting HIF-1α and NOTCH1 signalling using approaches such as RNA interference and through the development of specific inhibitors like Evofosfamide (Evo), which have demonstrated efficacy in reversing chemoresistance both in vitro and In vivo [89].

An important metabolic pathway that was enriched for the OSCC in the present study was the steroid biosynthesis pathway. Reports on the involvement of steroids in OSCC are notably scarce in the literature. However, Marocchio et al. (2013) recently indicated abundant expression of estrogen beta receptors (ERβ) in oral squamous cancer cells [90]. Additionally, recent bioinformatics investigations have shown modules for steroid synthesis pathways were significantly enriched in OSCC [91]. The direct involvement of steroid synthesis pathways in OSCC pathogenesis is still being pursued however it is most likely that the consumption of tobacco enhances ROS via oxidative stress pathways which may induce tumorigenic properties in squamous epithelial cells [92, 93].

In conclusion, this study identifies key genes significantly associated with OSCC, notably, genes such as NOTCH1 and PTEN which we anticipate may serve as substantial prognostic indicators in OSCC detection and progression. Further, in sheer contrast with previous studies, there was a lack of association of critical mediators of OSCC like PROS1 and CTBP1 with patient samples the discrepancies which may be due to ethnic variations and differences in sample collection strategies. Additionally, we observed a significant enrichment of genes involved in DNA repair pathways, especially mismatch repair genes, which could serve as promising therapeutic targets specifically in OSCC. Overall, our findings have identified key genes associated with OSCC, and the expression profiling of these genes may serve as valuable prognostic markers for the detection of OSCC, particularly in the context of the Indian population.

AUTHOR CONTRIBUTION

A.N.: Conceptualized the idea, Principal investigator and chief project administrator.

N.B.: Performed NGS RNA seq analysis, prepared the manuscript draft.

S.B.: Co-investigated the project and prepared the manuscript.

S.K., D.B., R.D.S., A. K.: Visualized the data and performed statistical analysis.

R.C., I.C., A.K., K.S.: Validated and curated the data and additional programmer of the project.

S.K.S: Involved in Investigation, Project administration, Supervision, Writing – review & editing of the MS.

CONFLICTS OF INTEREST/COMPETING INTERESTS:

The authors declare that they have no conflicts of interest.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE:

Not applicable.

HUMAN AND ANIMAL RIGHTS:

No animals or humans were used in the studies that were the basis of this research.

ACKNOWLEDGMENTS:

AK, KS, and SKS thankfully acknowledge the MHRD-RUSA Phase 2.0 under [grant sanctioned wide letter no. F.24-51/ 2014-U, Policy (TN Multi-Gen), Department of Education, Government of India, dated 09.10.2018]; Tamil Nadu State Council for Higher Education (TANSCHE) under [grant sanctioned wide letter no. AU: S.O. (P&D): TANSCHE Projects: 117/2021, dated 31.03.2021, File No. RGP/2019-20/ALU/HECP-0048 dated 27.04.2021]; Department of Biotechnology, Ministry of Science and Technology, New Delhi, under Grant/Award [No. BT/PR40154/BTIS/137/ 34/2021, dated 07.03.2022]; DST-PURSE 2nd Phase Program [Order No. SR/PURSE Phase 2/38 (G dated 21.02.2017)& DST-FIST (SR/FST/LSI—667/2016)]; DBT-NNP Project, New Delhi, under Grant/Award [No. BT/PR40156/BTIS/54/2023 dated 06.02.2023] for providing financial assistance, infrastructure facilities in the lab.

FUNDING

We do not receive any funding for this study.

AVAILABILITY OF DATA AND MATERIALS

All data and materials generated are included in this published article and are available from corresponding author upon reasonable request.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

Not applicable.

CONSENT FOR PUBLICATION

Not applicable.

COMPETING INTERESTS

The authors declare no competing interests.

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No competing interests reported.

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Transcriptome analysis of Oral Squamous Cell Carcinoma Utilizing Expression Datasets of Middle-aged Indian Males

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Abstract

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Introduction

Materials and Methods

2.1 Data collection and analysis

2.2 Transcript assembly and differential gene expression

2.3 Functional enrichment and pathway analysis

Results and discussion

3.1 Differential expression and association of genes with OSCC

3.2 Obtaining the biologically significant genes associated with OSCC

3.3 Functional enrichment and pathway analysis

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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