Abstract

Background

   To investigate the role of the translocase of the outer mitochondrial
   membrane 40 (TOM40) in oral squamous cell carcinoma (OSCC) with the aim
   of identifying new biomarkers or potential therapeutic targets.

Methods

   TOM40 expression level in OSCC was evaluated using datasets downloaded
   from The Cancer Genome Atlas (TCGA), as well as clinical data. The
   correlation between TOM40 expression level and the clinicopathological
   parameters and survival were analyzed in TCGA. The signaling pathways
   associated with TOM40 were identified through gene set enrichment
   analysis. A network of genes co-expressed with TOM40 was constructed
   and functionally annotated by gene ontology (GO) and Kyoto Encyclopedia
   of Genes and Genomes (KEGG) pathway enrichment analyses. The immune
   infiltration pattern in OSCC was analyzed in the TCGA-OSCC cohort using
   the CIBERSORT algorithm. Clinically significant factors of OSCC were
   screened through the expression levels of TOM40 and a clinically
   relevant nomogram was constructed. The TCGA-OSCC cohort was divided
   into the TOM40^high and TOM40^low groups and the correlation between
   TOM40 expression level and the sensitivity to frequently used
   chemotherapeutic drugs was evaluated. CCK-8 and colony formation assays
   were applied to determine the cell growth.

Results

   TOM40 was highly expressed in OSCC tissues and correlated negatively
   with the overall survival (P < 0.05). Patients with high TOM40
   expression level showed worse prognosis. Furthermore, GO and KEGG
   enrichment analyses of the differentially expressed genes related to
   TOM40 showed that these genes are mainly associated with immunity and
   tumorigenesis. Immunological infiltration analysis has found that the
   expression levels of TOM40 are correlated with the proportions of
   several immune cells. Moreover, we found that TOM40 knockdown inhibited
   cell growth in OSCC cell lines.

Conclusions

   Our results uncovered that TOM40 is a reliable prognostic marker and
   therapeutic target in OSCC.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s12885-024-13417-w.

   Keywords: OSCC, TOM40, Prognostic marker, Cell growth, Therapeutic
   target

Background

   Oral squamous cell carcinoma (OSCC) is the most common type of head and
   neck malignancy and occurs in the oral cavity and oropharynx [[38]1].
   OSCC exhibits high prevalence and morbidity, with 476,1125 new cases
   and 225,900 deaths recorded worldwide in 2020 [[39]2]. Cigarette
   smoking, alcohol consumption, betel nut chewing and human
   papillomavirus (HPV) infection are the most common risk factors
   [[40]3]. Despite advances in treatment strategies, the 5-year survival
   rate of OSCC patients is less than 50% [[41]4]. The poor prognosis of
   OSCC can be attributed to the lack of effective biomarkers for early
   diagnosis, local recurrence and distant metastases [[42]5]. Therefore,
   it is crucial to identify novel predictive biomarkers and therapeutic
   targets for OSCC in order to improve survival outcomes.

   The mitochondria play multiple roles during cancer progression, and
   mitochondrial biogenesis and quality control are constantly activated
   in cancer cells [[43]6]. Therefore, anti-cancer therapies targeting the
   mitochondria have been developed in recent years [[44]7]. The
   translocase of the outer mitochondrial membrane (TOM) complex controls
   the entry of most mitochondrial proteins [[45]8, [46]9]. The TOM
   complex consists of two TOM40 proteins linked by two TOM22 receptor
   subunits and a phospholipid that form a channel and the small accessory
   proteins TOM5, TOM6 and TOM7 that surround the channel [[47]9–[48]11].
   TOM40 has a 19-stranded β-barrel structure that forms the channel for
   transporting metabolites, ions, and proteins across the outer
   mitochondrial membrane [[49]12–[50]14]. The aberrant expression of
   TOM40 may contribute to mitochondrial dysfunction and has been
   associated with the pathogenesis and progression of neurological
   disorders, including Alzheimer’s disease and Parkinson’s disease
   [[51]15–[52]17]. Furthermore, TOM40 is overexpressed in ovarian cancer
   and nasopharyngeal carcinoma tissues [[53]18, [54]19]. However, the
   correlation between TOM40 expression and OSCC is still unknown and the
   potential molecular mechanisms remain to be elucidated.

   The aim of this study was to assess the biological role of TOM40 in
   OSCC. To this end, we systematically analyzed the expression,
   regulatory network and prognostic relevance of TOM40 in OSCC. The
   correlation between tumor-infiltrating immune cells and TOM40
   expression level was also analyzed. Overall, our findings suggest that
   high expression of TOM40 portends poor prognosis and a dysregulated
   immune landscape in OSCC. Thus, TOM40 warrants further investigation as
   a potential prognostic biomarker and therapeutic target in OSCC.

Methods

Ethics statement

   No ethical approval nor informed consent was required in this study due
   to the public availability of data in the TCGA databases.

Data retrieval

   TOM40 expression levels were analysed in clinical samples from the
   TIMER database ([55]https://cistrome.shinyapps.io/timer/) using
   |log2(fold-change) |> 1 and p < 0.05 as the threshold [[56]20–[57]22].
   RNA-Sequencing expression data and clinical information of OSCC samples
   were downloaded from the TCGA database
   ([58]https://portal.gdc.cancer.gov/). Limma package in R software
   (version 4.3.2) was used to search for Differentially Expressed Genes
   (DEGs) with |fold change| > 1 and p-value < 0.05 as a screening
   threshold. Extracted DEGs were inputted into subsequent bioinformatics
   analysis.

Protein-protein interaction (PPI) network construction

   The PPI network of TOM40 and the co-expressed genes was formulated by
   STRING database ([59]https://stringdb.org/). The network and the hub
   genes were visualized by Cytoscape.

GO and KEGG analyses

   We used “clusterProfiler”, an R package, to analyze the enrichment of
   DEGs by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes
   (KEGG). In addition, we visualized the data to make the results more
   intuitive and understandable.

Construction and verification of predictive nomogram

   We accessed “survival” and “rms” packages of the R package to build a
   nomogram for predicting survival of OSCC patients. And to explore the
   precision of the nomogram, the calibration curves were constructed.

Immune infiltration and chemosensitivity analyses

   We employed the CIBERSORT algorithm to gain the immune score of
   relationship between TOM40 and immune cell infiltration. We further
   used the Spearman method to analyse the relationship between TOM40 and
   immune infiltrating cells.

   We referred to the public pharmacology portal Genomics of Drug
   Sensitivity in Cancer (GDSC) ([60]https://www.cancerrxgene.org/) to
   investigate the role of TOM40 on chemotherapy. IC50 of OSCC
   chemotherapeutic agents were calculated by the R package “pRRophetic”.
   In this way, to reveal the potential role of TOM40 in immune cell
   infiltration as well as chemotherapeutic response.

Cell culture

   HN4 cell line was kindly gift by Professor Juan Du from the Chinese
   University of Hong Kong Shen Zhen. SCC9 cell line was purchased from
   BeNa Culture Collection. HN4 and SCC9 cell lines were cultured in DMEM
   or RPMI 1640 medium supplemented with 9% FBS (Gibco). All cells were
   maintained at 37℃ in a humidified incubator (Thermo Fisher Scientifc)
   with 5% CO[2].

RNA isolation and realtime PCR

   RNA isolation and realtime PCR was performed as previously described
   [[61]18]. Total RNA was isolated from the cultured cells using the
   RNeasy Mini Kit (Qiagen) and reverse transcribed using RT Master Mix
   for qPCR kit (MedChemExpress). Real-time PCR was performed using SYBR
   Green qPCR Master Mix (MedChemExpress) on the ABI7500 FAST Real Time
   PCR system (Applied Biosystems). ACTB was used as the internal control.
   The primer sequences were as follows: TOM40 forward 5′-
   CGAAGTTTGTGAACTGGCAGGTG − 3′; reverse 5′- AAGGCGTGATGCTCTGGAGGTA-3′;
   ACTB forward 5′-CACCATTGGCAATGAGCGGTTC-3′, reverse 5′-AGGTCT
   TTGCGGATGTC CACGT-3′ [[62]23].

siRNA transfection

   siRNA transfection was performed as previously described [[63]18]. The
   TOM40 siRNA sequences were provided by Shanghai GenePharma Co. Ltd.
   Cells were transfected with the respective siRNAs using
   GP-transfect-Mate (GenePharma) according to the manufacturer’s
   protocol. The siRNA sequences targeting TOM40 were as follows:
   siTOM40#1: 5′-GCAAGGAGCUGUUUCCCAUTT-3′, siTOM40#2:
   5′-GGUUGGCAACGGUAACGUUTT-3′.

Western blotting

   Western blotting was performed as previously described [[64]18]. Total
   protein was extracted from the cultured cells using RIPA lysis buffer
   (Beyotime Biotech). Equal amounts of protein per sample (20 µg) were
   separated by SDS-PAGE, and then transferred to a PVDF membrane
   (Millipore). After blocking with 5% BSA in TBST for 1 h at room
   temperature, the blots were incubated overnight with primary antibodies
   at 4℃ with constant shaking. Following incubation with HRP-conjugated
   secondary antibodies (Cell Signaling) at room temperature for 2 h, the
   positive bands were developed using the Pierce™ ECL Western Blotting
   Substrate (Thermo Scientifc).

Cell viability assay

   Cell viability assay was performed as previously described [[65]18].
   The transfected cells were seeded in 96 well plates and cultured for
   varying durations. At predetermined time points, 10µL Cell Counting
   Kit-8 reagent (MedChemExpress) was added to each well and the cells
   were incubated for 2 h at 37℃. Absorbance was measured at 450 nm on a
   multi-mode plate reader (Molecular Devices).

Colony forming assay

   Colony forming assay was performed as previously described [[66]18].
   The cells were seeded in 6 well plates at the density of 500 cells per
   well. After 2 weeks of culturing, the ensuing colonies were fixed with
   4% paraformaldehyde and stained with crystal violet. Colonies with more
   than 50 cells were counted.

Statistical analysis

   R software version 4.1.3 was used for statistical analysis of the
   datasets. p-values and FDR (false discovery rate) q-values below 0.05
   were regarded as statistically significant. Statistical analysis of the
   functional assays was performed using GraphPad Prism software version
   5.0. Data were expressed as mean ± standard error of the mean (SEM) of
   at least three independent experiments. Student’s t-test was used to
   compare two groups and multiple groups were compared using one-way
   ANOVA. Cell viability was examined by two-way ANOVA. P value < 0.05 was
   considered statistically significant.

Results

TOM40 is upregulated in OSCC

   As shown in Fig. [67]1A, TOM40 mRNA expression levels were
   significantly higher in HNSCC, BLCA, BRCA, CESC, ESCA, KICH, KIRC,
   KIRP, LIHC, LUAD, LUSC, PRAD, READ, STAD and UCEC samples in TCGA
   datasets. In contrast, TOM40 was downregulated in PCPG. Furthermore,
   TOM40 was significantly upregulated in the OSCC tissues compared to
   that in the normal tissues (Fig. [68]1B). Likewise, TOM40 was
   overexpressed in the clinical OSCC specimens compared to paired
   adjacent normal tissues (Fig. [69]1C). Furthermore, patients with high
   TOM40 expression level had a shorter overall survival (OS) and
   progression free survival (PFS) compared to those with low TOM40
   expression level (Fig. [70]1D and E). As shown in Fig. [71]2E, the area
   under the curve (AUC) of TOM40 for predicting the prognosis of OSCC
   patients was 0.848. Taken together, TOM40 is aberrantly upregulated in
   OSCC tissues and portends poor prognosis.

Fig. 1.

   [72]Fig. 1
   [73]Open in a new tab

   TOM40 is upregulated in OSCC and correlates with poor prognosis. (A)
   Pan-cancer TOM40 mRNA expression level in TIMER 2.0 database. (*:
   P value < 0.05; **: P value < 0.01; ***: P value < 0.001). TCGA = the
   cancer genome atlas. (B) Expression of TOM40 gene in tumor and normal
   tissues in TCGA database. (C) TOM40 expression level in OSCC and paired
   non-tumor tissues. (D) OS curves of OSCC patients demarcated by TOM40
   expression level in the TCGA database. (E) ROC curve for the prognostic
   value of TOM40

Fig. 2.

   [74]Fig. 2
   [75]Open in a new tab

   Construction of Cox regression model. (A) The heatmap of risk score
   level and clinical characteristics. (B and C) Univariate cox regression
   and multivariate cox regression according to risk score and clinical
   characteristics. (D) The calibration curve of the nomogram. € The
   development of a nomogram based on the clinical characteristics in the
   TCGA training cohort. N stands for N classification in TNM system, and
   T stands for T classification in TNM system

Establishment and validation of a predictive nomogram

   The TOM40^high and TOM40^low groups were divided by the median
   expression level of TOM40 (Fig. [76]2A). Univariate Cox regression
   analyses were used to test whether the TOM40 gene signatures were
   independent prognostic factors of other features, such as age, gender
   and grade (Fig. [77]2B). To predict the survival of OSCC patients from
   a clinical perspective, TOM40 and clinical factors were used to
   construct a nomogram that could estimate the probability of 1-, 3-, and
   5-year OS. TOM40, age, gender, grade, stage and TMN status were
   included as variables to predict prognosis (Fig. [78]2C). The 45° line
   represents the best prediction model and the resulting calibration plot
   indicates that the nomogram performed well (Fig. [79]2D).

Functional analyses of TOM40-related genes

   The OSCC patients were divided into the TOM40^high and TOM40^low groups
   based on the median expression level. We identified 134 differentially
   expressed genes (DEGs) between the two groups and found 11 genes that
   were most significantly correlated with TOM40 (Fig. [80]3A). To further
   explore the potential biological function of TOM40 in OSCC, we
   constructed a PPI network of the 134 DEGs and the most significantly 11
   genes associated with TOM40 on the basis of the topological overlap by
   string and cytoscape (Fig. 3B and C, Supplementary Figure [81]S1).
   Moreover, GO analysis showed that the genes were enriched in skin
   development, epidermis development, myofibril, contractile fiber,
   sarcomere, actin binding, etc. (Fig. [82]3D). KEGG pathway analysis
   further established the association between TOM40 and cardiac muscle
   contraction, dilated cardiomyopathy, hypertrophic cardiomyopathy,
   adrenergic signaling in cardiomyocytes, etc. (Fig. [83]3E). Based on
   these results, we surmised that TOM40 regulates epidermal development
   and plays an important role during tumorigenesis.

Fig. 3.

   [84]Fig. 3
   [85]Open in a new tab

   Network ofTOM40 and KEGG and GO biological function enrichment analyses
   ofTOM40-related genes. (A) The TOM40 gene co-expression network. Red
   and green represent genes with positive and negative correlation to
   TOM40 respectively. (B) PPI network of TOM40-related DEGs. Red and
   green represent the positively and negatively correlated genes
   respectively. The size of the graph is proportional to the correlation
   of TOM40. (C) The heatmap shows the DEGs associated with TOM40 in the
   TCGA-OSCC cohort. (D) KEGG signaling pathway enrichment analysis. (E)
   GO biological function enrichment analysis (when P-value < 0.05,
   q-value < 0.05, the results were statistically significant)

TOM40 expression is correlated to immune infiltration in OSCC

   The association between TOM40 expression level and the infiltration of
   22 immune cell types in OSCC cases was analyzed using the CIBERSORT
   algorithm. As shown in Fig. [86]4A, naïve B cells, naïve CD4 T cells,
   regulatory T cells (Tregs), and resting mast cells correlated
   negatively with TOM40 expression level. Therefore, we further evaluated
   the immune landscape in the TOM40^high and TOM40^low groups in 344 OSCC
   sample from TCGA. As shown in Fig. [87]4B, TOM40 overexpression was
   associated with an increased abundance of M2 macrophages, M1
   macrophages, and memory activated CD4 T cells, whereas low expression
   of TOM40 correlated to higher infiltration of naïve B cells,
   neutrophils, resting mast cells, resting dendritic cells and Tregs.

Fig. 4.

   [88]Fig. 4
   [89]Open in a new tab

   TOM40 is associated with the immune landscape of OSCC. (A) The
   differences in immune cell expression between TOM40^high and TOM40^low
   expression (B) The association between TOM40 and immune cells in the
   TCGA-OSCC cohort. P < 0.05, **P < 0.01, ***P < 0.001. (C) Heatmap
   showing the correlation between 16 immune checkpoint molecules and
   TOM40. The numbers in each box indicate the correlation coefficient
   between two cells. Red represents positive correlation and blue
   represents negative correlation. The darker the color, the more
   significant the correlation. (D) Violin plot revealing the distinction
   between low and high express TOM40 in TMB. (E) Estimate the score of
   the expression profile in the low and high express TOM40. *P < 0.05

Relationship between TOM40 and therapeutic responses

   Due to the significant impact of immune checkpoint molecules on the
   response to immunotherapy, we analyzed the correlation between TOM40
   expression level and multiple immune checkpoint genes. TNFRSF18, CD276,
   LAG3, TNFRSF25, LGALS9, VTCN1, CD40 and CD70 were positively correlated
   with TOM40, while CD27, TNFSF14, CD48, BTLA, CD40LG, CD28, CD244 and
   CD200R1 showed negative correlation (Fig. [90]4C). The tumor purity was
   then estimated by calculating the relative proportions of stromal and
   immune cell populations using the ESTIMATE algorithm (Fig. [91]4D). The
   clinical outcomes of cancer immunotherapy also depend on the gene
   expression patterns and mutations in the tumor cells. There was a
   positive correlation between TOM40 expression level and tumor mutation
   burden (TMB) (P < 0.001) in the OSCC samples (Fig. [92]4E). Lastly, the
   relationship between TOM40 expression level and the IC[50] values of
   nine FDA-approved chemotherapy drugs and immunological agents were
   analyzed. As shown in Fig. [93]5A to I, low expression of TOM40
   correlated with higher sensitivity to 5-fluorouracil, etoposide,
   methotrexate, cisplatin, doxorubicin, mitomycin, zibotentan, epothilone
   and gemcitabine.

Fig. 5.

   [94]Fig. 5
   [95]Open in a new tab

   TOM40 expression can predict the chemotherapy response in OSCC. The
   sensitivity of TOM40 ^high and TOM40^low samples to (A) 5-fluorouracil,
   (B) etoposide, (C) methotrexate, (D) cisplatin, (E) doxorubicin, (F)
   mitomycin, (G) zibotentan, (H) epothilone, and (I) gemcitabine are
   indicated

TOM40 promotes proliferation of OSCC cells in vitro

   To further evaluate the role of TOM40 in the progression of OSCC, we
   knocked down TOM40 in the HN4 and SCC9 cells using two siRNA constructs
   (siTOM40#1 and siTOM40#2). Both siRNAs achieved significant suppression
   of TOM40 protein and mRNA in the OSCC cell lines (Fig. [96]6A and B).
   Furthermore, TOM40 silencing markedly decreased the viability of the
   HN4 and SCC9 cells (Fig. [97]6C and D). The OSCC cells with TOM40
   knockdown also formed significantly fewer colonies in vitro, indicating
   a reduction in their proliferative capacity (Fig. [98]6E and F). Taken
   together, TOM40 knockdown inhibited the growth of OSCC cells in vitro,
   indicating that it is essential for the proliferation of the tumor
   cells.

Fig. 6.

   [99]Fig. 6
   [100]Open in a new tab

   TOM40 knockdown inhibited the proliferation of OSCC cells in vitro. (A)
   and (B) TOM40 protein and mRNA expression in HN4 and SCC9 cells
   transfected with siControl, siTOM40#1 or siTOM40#2. (C) and (D)
   Viability of HN4 and SCC9 cells transfected with siControl, siTOM40#1
   or siTOM40#2. (E) and (F) Representative images and number of colonies
   formed by HN4 and SCC9 cells transfected with siControl, siTOM40#1 or
   siTOM40#2. (G) Signaling connections involved in the TOM40 regulated
   OSCC development. The data represent the mean ± SEM of at least three
   independent experiments. * p < 0.05, versus siControl

Discussion

   OSCC is a type of head and neck cancer, and ranks sixteenth globally in
   terms of incidence [[101]5]. Although the quality of life of OSCC
   patients has improved significantly due to advances in surgery,
   radiotherapy, chemotherapy and combination therapies, the 5-year
   survival rate remains low. Smoking and betel nut chewing are the main
   risk factors for OSCC. Furthermore, genetic susceptibility, the tumor
   microenvironment (TME), abnormal gene expression and immune
   infiltration have also been linked to tumorigenesis [[102]2, [103]24].
   Immunotherapy and immune factor-specific targeted therapy are
   increasingly being explored as treatment strategies against OSCC
   [[104]20], given that the immune landscape and TICs can affect disease
   progression and are correlated with the prognosis and treatment
   response [[105]21]. Therefore, understanding the relationship between
   immune cell infiltration and tumor development is critical to identify
   novel diagnostic markers and therapeutic targets. Whole-genome
   transcriptomics studies have shown that immune-related genes can
   predict the survival outcomes of cancer patients or responsiveness to
   certain immunotherapies [[106]25]. However, the molecular mechanism
   underlying OSCC pathogenesis has not yet been elucidated so far.

   The mitochondria are key determinants of cancer cell energy metabolism
   [[107]26]. TOM40 is a subunit of the TOM complex and functions as a
   channel for importing proteins into the mitochondria and maintaining
   mitochondrial homeostasis [[108]27]. In addition, TOM40 is closely
   associated with mitochondrial function and activity in cancer cells.
   One study showed that TOM40 enhanced ovarian cancer cell growth by
   modulating mitochondrial function, intracellular ATP production and ROS
   levels [[109]19]. In our previous study, TOM40 was associated with poor
   overall survival and disease specific survival in nasopharyngeal
   carcinoma. Knockdown of TOM40 promoted ROS production and decreased
   mitochondrial membrane potential. Moreover, AKT/mTOR and p53/21
   signaling were downstream of TOM40 [[110]18]. However, it is unclear
   whether TOM40 plays a role in regulating progression of OSCC.

   We found that TOM40 was upregulated in the OSCC tissues compared to the
   normal tissues in TCGA. In addition, TOM40 expression level correlated
   significantly with the T stage, age, and the clinical stage of OSCC.
   Moreover, its overexpression portended worse prognosis, progressive
   free survival and overall survival rate. In line with the above
   findings, TOM40 silencing caused a significant reduction in the
   proliferative capacity of OSCC cells by cell viability and colony
   forming assay. Therefore, to better guide clinical practice, we
   constructed a prognostic nomogram based on TOM40 expression level and
   related clinical factors.

   The TME plays an important role in tumor development and progression.
   The infiltrating immune cells create an inflammatory environment and
   aid in the immune escape of tumor cells [[111]28]. Therefore, immune
   checkpoint inhibitors (ICIs) have become an integral part of various
   cancer treatment strategies and are increasingly being promoted as the
   first-line treatment for advanced unresectable cancer [[112]29,
   [113]30]. We found that TOM40 is related to the microenvironment and
   immune landscape of OSCC. Furthermore, we evaluated the relationship
   between TOM40 expression level and the sensitivity to FDA-approved
   drugs and found that high expression level of TOM40 enhanced the
   chemoresistance of OSCC.

   Nevertheless, our study has some limitations that ought to be
   addressed. First, our findings are based on publicly available datasets
   and a limited number of clinical specimens. Second, bioinformatics is
   only a prediction tool, and a certain technical threshold is required
   to ensure the accuracy of results. Third, the subgroup analysis of
   TOM40-expressing OSCC according to race, smoking, drinking and HPV
   history was not performed, which will be the focus of our next study.
   Finally, the molecular mechanisms underlying the regulatory role of
   TOM40 in the pathogenesis of OSCC also need to be elucidated.

Conclusions

   In summary, this study indicated that high TOM40 expression level is
   strongly correlated with poor prognosis in OSCC by bioinformatics.
   TOM40 is also related to immune infiltration and drug sensitivity.
   Moreover, we demonstrated TOM40 is overexpressed in OSCC tissues and
   TOM40 knockdown inhibits tumor proliferation in vitro study. Thus,
   TOM40 is a potential prognostic biomarker and therapeutic target for
   OSCC. Further studies are needed to determine the impact of TOM40 on
   the immune landscape of OSCC and elucidate the role of the co-expressed
   genes.

Electronic supplementary material

   Below is the link to the electronic supplementary material.
   [114]12885_2024_13417_MOESM1_ESM.tif^ (2.5MB, tif)

   Supplementary Material 1: Figure S1: PPI network of the most
   significantly 11 genes associated with TOM40
   [115]Supplementary Material 2^ (626.3KB, tif)

Acknowledgements