Elsevier

Journal of Proteomics

Volume 247, 15 September 2021, 104320
Journal of Proteomics

Integrated tissue proteome and metabolome reveal key elements and regulatory pathways in cutaneous squamous cell carcinoma

https://doi.org/10.1016/j.jprot.2021.104320Get rights and content

Highlights

  • We performed integrated tissue proteomic and metabolomic analyses for CSCC.

  • Significantly distinct proteomic and metabolomic profiles were identified.

  • DNA damage responses, apoptosis, and autophagy were associated with CSCC development.

  • Protein digestion & absorption and platelet activation were also related to CSCC.

  • A four-metabolite panel was well developed to distinguish CSCC tissues.

Abstract

Cutaneous squamous cell carcinoma (CSCC) is a widespread malignancy but has a very low long-term survival rate for patients at the metastatic stage. Therefore, it is urgent to identify prognostic biomarkers for CSCC and improve our understanding of disease progression. Here we took advantage of a data-independent acquisition (DIA)-based nano liquid chromatography equipped with an orbitrap mass spectrometry (nLC-MS/MS) and ultraperformance LC coupled to a time-of-flight tandem MS (UPLC-TOF-MS/MS) technique to analyze cancer and corresponding noncancerous tissues from 20 CSCC patients for integrated proteomic and metabolomic analyses. Overall, 6241 tissue proteins were detected, while 136 proteins were significantly expressed in CSCC tissues. Further functional analysis revealed that various biological processes were highly enriched and participated in the pathogenesis of CSCC, especially DNA damage responses. Moreover, 641 named metabolites in total were identified, among which 181 were significantly changed in CSCC tissues. A total of 101 pathways were significantly enriched including apoptosis, autophagy, PI3K-Akt and mTOR signaling pathways. Interestingly, two pathways, protein digestion & absorption and platelet activation were both enriched in proteomic and metabolomic studies involving 5 proteins and 11 metabolites. Accordingly, a four-metabolite panel consisting of arachidonate, glutamine, glutamic acid, and proline (all area under the curve (AUC) values more than 0.9) was developed with a high accuracy (0.971) to distinguish the 20 detected cancer tissues from their noncancerous tissues. Collectively, our work highlighted the key elements and regulatory pathways involved in the pathogenesis of CSCC. More importantly, the present study not only provided potential biomarkers for the early diagnosis of CSCC, but also expanded our knowledge of the physiopathology of the disease.

Significance

CSCC is the second most common human cancer but has few treatment options and few sensitive biomarkers for diagnosis. Here we comprehensively revealed its molecular characteristics by performing integrated tissue proteomic and metabolomic analyses. Significantly distinct profiles and certain enriched pathways including DNA damage responses were identified as associated with CSCC. Moreover, protein digestion & absorption and platelet activation were both enriched in the proteome and metabolome. These identified molecular changes probably play significant roles in CSCC development. Finally, we developed a four-metabolite panel to distinguish CSCC with high accuracy. Overall, our data not only provided potential diagnostic biomarkers, but also extended knowledge on the pathogenesis of CSCC.

Introduction

Cutaneous squamous cell carcinoma (CSCC) is one of the most common cancers, representing approximately 20% of all skin tumors [1]. This keratinocyte-derived cancer is the fastest-growing cancer and usually develops on sun-exposed skin and proceeds as a progressively invasive malignancy [2]. It mostly starts from precancerous lesions and progresses into invasive CSCC with metastatic potential. Although early-stage CSCC can be successfully treated with surgery, metastatic CSCC has a very low long-term survival rate (10–20%) due to the lack of an effective therapeutic strategy [3]. Thus, there is an urgent need to identify prognostic biomarkers for early-stage CSCC and uncover the underlying mechanisms to identify new therapeutic targets for patients at the middle and advanced stages, as well as patients with metastatic CSCC.

The major risk factors for the development and progression of CSCC include ultraviolet (UV) radiation exposure, advanced age, and fair complexion [4]. Immunosuppression, autoimmune diseases, and chronic lymphocytic leukemia are additional well-established risk factors for CSCC. Recently, advanced high-throughput omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, have dramatically extended our understanding of complex diseases including CSCC. For example, three genome-wide association studies (GWAS) have identified 14 single-nucleotide polymorphisms (SNPs) associated with cutaneous SCC that are involved in skin pigmentation, cell-mediated immunity, cellular proliferation, and anti-apoptotic pathways [5]. Moreover, Mahapatra et al. (2020) recently employed RNA-seq to perform a comprehensive analysis of coding and noncoding transcriptomic differences between nine CSCCs and seven healthy skin samples [1]. A total of 5352 protein-coding genes, 55 circular RNAs, and 908 lncRNAs were determined to be differentially altered in CSCC. Further analysis revealed that pathways such as the cell cycle, epidermal differentiation, inflammation, and apoptosis were significantly enriched, which provided new insights into the molecular pathogenesis of CSCC.

Proteomics allows simultaneous detection of thousands of proteins in biological samples, which holds great potential for determining biomarkers and functional networks in large-scale clinical studies on various types of cancer [6]. Turhani et al. (2006) collected oral squamous cell carcinoma (OSCC) and control samples for proteomic analysis by using 2-DE and MALDI-TOF-MS [6]. The results showed that twenty proteins were differentially altered in OSCC, which may be potential diagnostic markers with clinical significance. By using a proteomic-based approach with formalin-fixed paraffin-embedded (FFPE) CSCCs, two significantly changed proteins, ANXA5 and DDOST, were found to be significantly associated with poorer clinical outcomes in CSCC [7]. In addition, Azimi et al. (2020) employed a DIA based SWATH-MS on FFPE samples to discriminate actinic keratosis (AK), Bowen's disease, and CSCC [8]. In total, 3574 proteins across the 93 samples were detected, and 19, 5, and 6 proteins were determined to be exclusive to AK, Bowen's disease and CSCC lesions, respectively. More importantly, 118, 230, and 17 proteins offered potential biomarkers for predicting various levels of tumor differentiation including well differentiated, moderately differentiated and poorly differentiated CSCC lesions, respectively.

In addition, another high-throughput and powerful analysis technology, metabolomics, also shows great potential for identifying the biomarkers and functional pathways of various diseases including cancers [[9], [10], [11]]. For example, Cheng et al. (2020) employed an integrative strategy combining the transcriptome and metabolome to elucidate the underlying mechanism of esophageal squamous cell carcinoma (ESCC) [12]. Five metabolites associated with the tyrosine pathway including tyrosine and phenylalanine, were determined to be diagnostic biomarkers for ESCC and metastatic ESCC patients. A biological model incorporating both metabolic and transcriptional dysregulation was also constructed to illustrate the pathogenesis of ESCC, as well as its metastasis. Likewise, Zhou et al. (2017) integrated “omics”, including microRNAome, proteomics and metabolomics, to reveal the potential molecular mechanisms of arsenic-induced malignant cell transformation [13]. By using UPLC-TOF MS/MS, 68 metabolites, including glutathione, phenylalanine, tyrosine and citric acid, were determined to be significantly changed in arsenic-induced transformed cells and were associated with glutathione metabolism, met cycle, citrate cycle, phenylalanine and tyrosine metabolism. Together with microRNAome and proteomics data, the results expanded our understanding of arsenic-induced cell malignant transformation and provided early potential biomarkers for CSCC induced by arsenic.

In this study taking advantage of two powerful technologies, we employed the UPLC-TOF-MS/MS and nLC-MS/MS for integrated metabolomic and DIA-based proteomic analyses of cancer tissues and corresponding noncancerous tissues from 20 patients with CSCC. We aimed to identify key regulatory molecules (proteins and/or metabolites) and functional networks, which may provide potential CSCC biomarkers for diagnostic purposes and extend our understanding of the pathogenesis of the disease.

Section snippets

Sample collection

Twenty patients with CSCC were enrolled in the present study and their basic information are provided in Table S1. The subjects recruited here had normal kidney and liver function, and did not take any drugs before sampling to avoid affecting metabolism. Twenty pairs of primary CSCC and their matched noncancerous tissue samples (>2 cm away from the edge of the tumor) from twenty patients were obtained, immediately frozen in liquid nitrogen, transferred into Eppendorf tubes and finally stored at

Proteomics changes in CSCC patients

To comprehensively reveal the proteome characterization of CSCC, we first employed DIA-MS/MS for six pooled samples from CSCC patients' tissues and their noncancerous tissues as the controls. A total of 6241 proteins across those pooled samples in the DIA-MS/MS analysis were detected and quantified (Table S2). Further online PANTHER analysis showed that 2404 proteins were annotated and classified (Fig. 1A), nearly half of which functioned as metabolite interconversion enzymes (22.59%), protein

Discussion

CSCC is the second most common human cancer, highlighting the importance of understanding its pathogenesis due to the lack of sensitive biomarkers for early diagnosis and few treatment options for patients with metastatic CSCC [18]. Therefore, we took advantage of integrated proteomic and metabolomic analyses to comprehensively reveal the molecular characterizations of CSCC by performing DIA-based quantitative proteomics analysis and UPLC-TOF-MS/MS-based metabolomic analysis. It should be

Conclusion

In summary, our study comprehensively revealed the molecular characteristics associated with CSCC by performing DIA-based quantitative proteomics analysis and UPLC-TOF-MS/MS-based metabolomic analysis. Significantly distinct proteomic and metabolomic profiles were identified and certain enriched pathways including DNA damage responses, apoptosis, and autophagy, and several cancer-associated signaling pathways were determined to be involved in the disease. More importantly, two pathways, protein

Declarstion of Competing Interest

The authors declared no conflict of interest.

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (No. 81960865), Department of Science and Technology of Jiangxi Province (Grant No. 20181BBG78041 and 20202BABL206106), and National Cancer Center Climbing Fund (No. NCC201814B045); in part by grants from Health and Family Planning Commission of Jiangxi Province (Grant No. 20203577, 20203693 and 20203192).

References (36)

  • L.D. Nardo et al.

    Molecular genetics of cutaneous squamous cell carcinoma: perspective for treatment strategies

    J. Eur. Acad. Dermatol. Venereol.

    (2019)
  • K.Y. Sarin et al.

    Genome-wide meta-analysis identifies eight new susceptibility loci for cutaneous squamous cell carcinoma

    Nat. Commun.

    (2020)
  • D. Turhani et al.

    Identification of differentially expressed, tumor-associated proteins in oral squamous cell carcinoma by proteomic analysis

    Electrophoresis

    (2006)
  • A. Shapanis et al.

    Identification of proteins associated with development of metastasis from cutaneous squamous cell carcinomas (cSCCs) via proteomic analysis of primary cSCCs

    Br. J. Dermatol.

    (2020)
  • A. Azimi et al.

    Data independent acquisition proteomic analysis can discriminate between actinic keratosis, Bowen’s disease, and cutaneous squamous cell carcinoma

    J. Invest. Dermatol.

    (2020)
  • Z. Zheng et al.

    Peiminine inhibits colorectal cancer cell proliferation by inducing apoptosis and autophagy and modulating key metabolic pathways

    Oncotarget

    (2017)
  • J. Cheng et al.

    Integrating transcriptome and metabolome variability to reveal pathogenesis of esophageal squamous cell carcinoma

    Biochim. Biophys. Acta Mol. basis Dis.

    (1867)
  • Y. Zhou et al.

    Integration of microRNAome, proteomics and metabolomics to analyze arsenic-induced malignant cell transformation

    Oncotarget

    (2017)
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