Integrated single-cell sequencing and transcriptome sequencing to reveal a 9-gene prognostic signature of immune cells in colorectal cancer

doi:10.19401/j.cnki.1007-3639.2024.06.003

Abstract

Abstract:

Background and purpose: Colorectal carcinoma (CRC) is a common malignant tumor with incidence and mortality rates second only to gastric cancer and esophageal cancer among digestive system malignancies. Increasing evidence suggests that immune cells play a significant role in the occurrence and development of CRC. The aim of this study was to construct a prognostic model related to immune cell-associated genes to predict the prognosis of CRC patients and enable precise management. Methods: Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) data, along with clinical information for colorectal cancer, were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Differential genes of immune cell subtypes were extracted, and genes related to prognosis were screened in TCGA data using Cox regression and LASSO regression, with external validation using GSE39582 and GSE41258. The prognostic model was used to analyze chemotherapy drug sensitivity, assess immunotherapy efficacy, analyze pathways related to risk scores, and perform clinical correlation analysis. Finally, the expression levels of model genes were validated in 10 fresh frozen CRC tissues with post-operative pathological examination and cell lines using real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) and immunohistochemistry. All samples were approved by the Fudan University Shanghai Cancer Center Ethics Committee (No. 050432-4-2108*). Results: We defined 16 cell clusters based on the scRNA-seq dataset (GSE161277) and labeled these clusters as different cell types using the R package celldex. Differential analysis of immune cell subtypes yielded 374 differentially expressed genes. Using univariate Cox and LASSO analyses, we constructed a 9-gene risk prognostic model in CRC. This risk model exhibited reliable prognostic prediction performance and played an important role in predicting anti-tumor drug sensitivity, immunotherapy efficacy, potential molecular mechanisms, and clinical characteristics. Patients with high-risk scores had a lower probability of benefiting from immunotherapy. Conclusion: We constructed a 9-gene risk prognostic model based on the heterogeneity of immune cells in the CRC tumor microenvironment, which predicted the survival and treatment outcomes of CRC patients.

Key words: Colorectal carcinoma, Prognostic model, Cancer immunity and immunotherapy, Drug screening, scRNA-seq

CLC Number:

R735.3+4

TANG Nan, HUANG Huixia, LIU Xiaojian. Integrated single-cell sequencing and transcriptome sequencing to reveal a 9-gene prognostic signature of immune cells in colorectal cancer[J]. China Oncology, 2024, 34(6): 548-560.

Figures/Tables 8

Fig. 1

Tab. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

References 51

[1]	DEKKER E, TANIS P J, VLEUGELS J L A, et al. Colorectal cancer[J]. Lancet, 2019, 394(10207): 1467-1480. doi: S0140-6736(19)32319-0 pmid: 31631858
[2]	EDWARDS B K, NOONE A M, MARIOTTO A B, et al. Annual Report to the Nation on the status of cancer, 1975-2010, featuring prevalence of comorbidity and impact on survival among persons with lung, colorectal, breast, or prostate cancer[J]. Cancer, 2014, 120(9): 1290-1314. doi: 10.1002/cncr.28509 pmid: 24343171
[3]	PATEL S G, KARLITZ J J, YEN T, et al. The rising tide of early-onset colorectal cancer: a comprehensive review of epidemiology, clinical features, biology, risk factors, prevention, and early detection[J]. Lancet Gastroenterol Hepatol, 2022, 7(3): 262-274.
[4]	HAN L, WANG S Y, WEI C, et al. Tumour microenvironment: a non-negligible driver for epithelial-mesenchymal transition in colorectal cancer[J]. Expert Rev Mol Med, 2021, 23: e16. doi: 10.1017/erm.2021.13 pmid: 34758892
[5]	LUO X J, ZHAO Q, LIU J, et al. Novel genetic and epigenetic biomarkers of prognostic and predictive significance in stage Ⅱ/Ⅲ colorectal cancer[J]. Mol Ther, 2021, 29(2): 587-596.
[6]	CHEN B, SCURRAH C R, MCKINLEY E T, et al. Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps[J]. Cell, 2021, 184(26): 6262-6280.e26. doi: 10.1016/j.cell.2021.11.031 pmid: 34910928
[7]	GUO W, ZHANG C Y, WANG X, et al. Resolving the difference between left-sided and right-sided colorectal cancer by single-cell sequencing[J]. JCI Insight, 2022, 7(1): e152616.
[8]	NORKIN M, ORDÓÑEZ-MORÁN P, HUELSKEN J. High-content, targeted RNA-seq screening in organoids for drug discovery in colorectal cancer[J]. Cell Rep, 2021, 35(3): 109026.
[9]	SIEGEL R L, MILLER K D, WAGLE N S, et al. Cancer statistics, 2023[J]. CA Cancer J Clin, 2023, 73(1): 17-48.
[10]	JIN M Z, JIN W L. The updated landscape of tumor microenvironment and drug repurposing[J]. Sig Transduct Target Ther, 2020, 5: 166.
[11]	PITT J M, MARABELLE A, EGGERMONT A, et al. Targeting the tumor microenvironment: removing obstruction to anticancer immune responses and immunotherapy[J]. Ann Oncol, 2016, 27(8): 1482-1492. doi: 10.1093/annonc/mdw168 pmid: 27069014
[12]	JACKSTADT R, VAN HOOFF S R, LEACH J D, et al. Epithelial NOTCH signaling rewires the tumor microenvironment of colorectal cancer to drive poor-prognosis subtypes and metastasis[J]. Cancer Cell, 2019, 36(3): 319-336.e7. doi: S1535-6108(19)30371-X pmid: 31526760
[13]	TIAN S B, CHU Y N, HU J, et al. Tumour-associated neutrophils secrete AGR2 to promote colorectal cancer metastasis via its receptor CD98hc-xCT[J]. Gut, 2022, 71(12): 2489-2501.
[14]	YIN Y, LIU B X, CAO Y L, et al. Colorectal cancer-derived small extracellular vesicles promote tumor immune evasion by upregulating PD-L1 expression in tumor-associated macrophages (adv. sci. 9/2022)[J]. Adv Sci, 2022, 9(9).
[15]	DEL VECCHIO F, MASTROIACO V, MARCO A D, et al. Next-generation sequencing: recent applications to the analysis of colorectal cancer[J]. J Transl Med, 2017, 15(1): 246.
[16]	LIANG L L, YU J, LI J, et al. Integration of scRNA-seq and bulk RNA-seq to analyse the heterogeneity of ovarian cancer immune cells and establish a molecular risk model[J]. Front Oncol, 2021, 11: 711020.
[17]	QU X D, ZHAO X Y, LIN K X, et al. M2-like tumor-associated macrophage-related biomarkers to construct a novel prognostic signature, reveal the immune landscape, and screen drugs in hepatocellular carcinoma[J]. Front Immunol, 2022, 13: 994019.
[18]	LU J, CHEN Y F, ZHANG X Q, et al. A novel prognostic model based on single-cell RNA sequencing data for hepatocellular carcinoma[J]. Cancer Cell Int, 2022, 22(1): 38.
[19]	ZHENG X B, SONG J N, YU C E, et al. Single-cell transcriptomic profiling unravels the adenoma-initiation role of protein tyrosine kinases during colorectal tumorigenesis[J]. Signal Transduct Target Ther, 2022, 7(1): 60.
[20]	VIJAYAN Y, LANKADASARI M B, HARIKUMAR K B. Acid ceramidase: a novel therapeutic target in cancer[J]. Curr Top Med Chem, 2019, 19(17): 1512-1520. doi: 10.2174/1568026619666190227222930 pmid: 30827244
[21]	LUCKI N C, SEWER M B. Genistein stimulates MCF-7 breast cancer cell growth by inducing acid ceramidase (ASAH1) gene expression[J]. J Biol Chem, 2011, 286(22): 19399-19409. doi: 10.1074/jbc.M110.195826 pmid: 21493710
[22]	LI Y H, LIU H T, XU J, et al. The value of detection of S100A8 and ASAH1 in predicting the chemotherapy response for breast cancer patients[J]. Hum Pathol, 2018, 74: 156-163.
[23]	REALINI N, SOLORZANO C, PAGLIUCA C, et al. Discovery of highly potent acid ceramidase inhibitors with in vitro tumor chemosensitizing activity[J]. Sci Rep, 2013, 3: 1035. doi: 10.1038/srep01035 pmid: 23301156
[24]	MACHALA M, PROCHÁZKOVÁ J, HOFMANOVÁ J, et al. Colon cancer and perturbations of the sphingolipid metabolism[J]. Int J Mol Sci, 2019, 20(23): 6051.
[25]	VIJAYAN Y, JAMES S, VISWANATHAN A, et al. Targeting acid ceramidase enhances antitumor immune response in colorectal cancer[J]. J Adv Res, 2023: S 2090-S1232(23)00403-4.
[26]	LI M L, ZHAO X, YONG H M, et al. Transketolase promotes colorectal cancer metastasis through regulating AKT phosphorylation[J]. Cell Death Dis, 2022, 13(2): 99.
[27]	YANG H, WU X L, WU K H, et al. MicroRNA-497 regulates cisplatin chemosensitivity of cervical cancer by targeting transketolase[J]. Am J Cancer Res, 2016, 6(11): 2690-2699. pmid: 27904781
[28]	SHUKLA S K, PUROHIT V, MEHLA K, et al. MUC1 and HIF-1alpha signaling crosstalk induces anabolic glucose metabolism to impart gemcitabine resistance to pancreatic cancer[J]. Cancer Cell, 2017, 32(3): 392.
[29]	DASGUPTA S, RAJAPAKSHE K, ZHU B K, et al. Metabolic enzyme PFKFB4 activates transcriptional coactivator SRC-3 to drive breast cancer[J]. Nature, 2018, 556(7700): 249-254.
[30]	WANG H L, CHEN Y, WANG Y Q, et al. Sirtuin5 protects colorectal cancer from DNA damage by keeping nucleotide availability[J]. Nat Commun, 2022, 13(1): 6121.
[31]	UTO T, FUKAYA T, MITOMA S, et al. Clec4A4 acts as a negative immune checkpoint regulator to suppress antitumor immunity[J]. Cancer Immunol Res, 2023, 11(9): 1266-1279.
[32]	LIU B, CHENG L, GAO H H, et al. The biology of VSIG4: implications for the treatment of immune-mediated inflammatory diseases and cancer[J]. Cancer Lett, 2023, 553: 215996.
[33]	CHOW A, SCHAD S, GREEN M D, et al. Tim-4⁺ cavity-resident macrophages impair anti-tumor CD8⁺ T cell immunity[J]. Cancer Cell, 2021, 39(7): 973-988.e9.
[34]	WU S, PEI Q, NI W, et al. HSPA1A protects cells from thermal stress by impeding ESCRT-0-mediated autophagic flux in epidermal thermoresistance[J]. J Investig Dermatol, 2021, 141(1): 48-58.e3.
[35]	WANG X, WANG Y T, FANG Z Y, et al. Targeting HSPA1A in ARID2-deficient lung adenocarcinoma[J]. Natl Sci Rev, 2021, 8(10): nwab014.
[36]	JIANG Y, XU Y J, ZHENG C, et al. Acetyltransferase from Akkermansia muciniphilablunts colorectal tumourigenesis by reprogramming tumour microenvironment[J]. Gut, 2023, 72(7): 1308-1318.
[37]	GUCCINI I, REVANDKAR A, D’AMBROSIO M, et al. Senescence reprogramming by TIMP1 deficiency promotes prostate cancer metastasis[J]. Cancer Cell, 2021, 39(1): 68-82.e9. doi: 10.1016/j.ccell.2020.10.012 pmid: 33186519
[38]	TIAN Z F, OU G S, SU M X, et al. TIMP1 derived from pancreatic cancer cells stimulates Schwann cells and promotes the occurrence of perineural invasion[J]. Cancer Lett, 2022, 546: 215863.
[39]	SCHOEPS B, ECKFELD C, PROKOPCHUK O, et al. TIMP1 triggers neutrophil extracellular trap formation in pancreatic cancer[J]. Cancer Res, 2021, 81(13): 3568-3579.
[40]	MA B B, UEDA H, OKAMOTO K, et al. TIMP1 promotes cell proliferation and invasion capability of right-sided colon cancers via the FAK/Akt signaling pathway[J]. Cancer Sci, 2022, 113(12): 4244-4257.
[41]	HECKMANN B L, ZHANG X D, XIE X T, et al. The G₀/G₁ switch gene 2 (G0S2): regulating metabolism and beyond[J]. Biochim Biophys Acta, 2013, 1831(2): 276-281.
[42]	NIELSEN T S, MØLLER N. Adipose triglyceride lipase and G0/G1 switch gene 2: approaching proof of concept[J]. Diabetes, 2014, 63(3): 847-849. doi: 10.2337/db13-1838 pmid: 24556865
[43]	KIOKA H, KATO H, FUJIKAWA M, et al. Evaluation of intramitochondrial ATP levels identifies G₀/G₁ switch gene 2 as a positive regulator of oxidative phosphorylation[J]. Proc Natl Acad Sci U S A, 2014, 111(1): 273-278.
[44]	CHANG X F, MONITTO C L, DEMOKAN S, et al. Identification of hypermethylated genes associated with cisplatin resistance in human cancers[J]. Cancer Res, 2010, 70(7): 2870-2879. doi: 10.1158/0008-5472.CAN-09-3427 pmid: 20215521
[45]	BARREAU O, ASSIÉ G, WILMOT-ROUSSEL H, et al. Identification of a CpG island methylator phenotype in adrenocortical carcinomas[J]. J Clin Endocrinol Metab, 2013, 98(1): E174-E184.
[46]	KUSAKABE M, KUTOMI T, WATANABE K, et al. Identification of G0S2 as a gene frequently methylated in squamous lung cancer by combination of in silico and experimental approaches[J]. Int J Cancer, 2010, 126(8): 1895-1902. doi: 10.1002/ijc.24947 pmid: 19816938
[47]	ASHRAF Y, MANSOURI H, LAURENT-MATHA V, et al. Immunotherapy of triple-negative breast cancer with cathepsin D-targeting antibodies[J]. J Immunother Cancer, 2019, 7(1): 29.
[48]	LIU C M, SHEN H T, LIN Y A, et al. Antiproliferative and antimetastatic effects of praeruptorin C on human non-small cell lung cancer through inactivating ERK/CTSD signalling pathways[J]. Molecules, 2020, 25(7): 1625.
[49]	XU J S, DAI S Q, YUAN Y, et al. A prognostic model for colon cancer patients based on eight signature autophagy genes[J]. Front Cell Dev Biol, 2020, 8: 602174.
[50]	XIE L Q, ZHAO C, CAI S J, et al. Novel proteomic strategy reveal combined alpha1 antitrypsin and cathepsin D as biomarkers for colorectal cancer early screening[J]. J Proteome Res, 2010, 9(9): 4701-4709.
[51]	WANG K, FU S Y, DONG L X, et al. Periplocin suppresses the growth of colorectal cancer cells by triggering LGALS3 (galectin 3)-mediated lysophagy[J]. Autophagy, 2023, 19(12): 3132-3150.

Primer	Sequence (5‘-3’)
CD36-1-F	GGCTGTGACCGGAACTGTG
CD36-1-R	AGGTCTCCAACTGGCATTAGAA
CTSD-F	ATTCAGGGCGAGTACATGATCC
CTSD-R	CGACACCTTGAGCGTGTAG
G0S2-F	TCGGCCTGATGGAGACTGT
G0S2-R	TTCTGGAGAGCCTGTCGCT
TIMP1-F	AGAGTGTCTGCGGATACTTCC
TIMP1-R	CCAACAGTGTAGGTCTTGGTG
HSPA1A-F	AGCTGGAGCAGGTGTGTAAC
HSPA1A-R	TACCTCCTCAATGGTGGGGC
VSIG4-1-F	GGGGCACCTAACAGTGGAC
VSIG4-1-R	GTCTGAGCCACGTTGTACCAG
CLEC4A-F	GACTGTGCTAGAATGGAGGCT
CLEC4A-R	GTCGCTGACCTTCTGGATCTG
TKT-1-F	TCATCGAGTGCTACATTGCTG
TKT-1-R	GCCATGCGAATCTGGTCAAAG
ASAH1-1-F	AGATGTCATGTGGATAGGGTTCC
ASAH1-1-R	GGGGCCAATATCTTGGTCTTG
β-actin-F	TTGTTACAGGAAGTCCCTTGCC
β-actin-R	ATGCTATCACCTCCCCTGTGTG