Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma

Zhao, Xin; Li, Han; Lyu, Shaocheng; Zhai, Jialei; Ji, Zhiwei; Zhang, Zhigang; Zhang, Xinxue; Liu, Zhe; Wang, Huaguang; Xu, Jianjun; Fan, Hua; Kou, Jiantao; Li, Lixin; Lang, Ren; He, Qiang

doi:10.7150/ijbs.58886

Cited by 30 publications

(26 citation statements)

References 81 publications

(91 reference statements)

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“…GSE165399 ( 8 ) cohort contained scRNA-seq data of one normal sample (GSM5032773) and two tumor samples (GSM5032771 and GSM5032772). Seurat R package was employed to preprocess single-cell data ( 9 ).…”

Section: Methodsmentioning

confidence: 99%

Discovering a Four-Gene Prognostic Model Based on Single-Cell Data and Gene Expression Data of Pancreatic Adenocarcinoma

Huang

Zhou

et al. 2022

Front. Endocrinol.

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BackgroundPancreatic cancer has a 5-year overall survival lower than 8%. Pancreatic adenocarcinoma (PAAD) is the most common type. This study attempted to explore novel molecular subtypes and a prognostic model through analyzing tumor microenvironment (TME).Materials and MethodsSingle-cell RNA sequencing (scRNA-seq) data and expression profiles from public databases were downloaded. Three PAAD samples with single-cell data and 566 samples with gene expression data were included. Seurat was used to identify cell subsets. SVA merged and removed batch effects from multichip datasets. CIBERSORT was used to evaluate the components of different cells in transcriptome, ConsensusClusterPlus was used to identify molecular subtypes, and gene set enrichment analysis was used for functional enrichment analysis. LASSO Cox was performed to construct dimensionality reduction and prognosis model.ResultsMemory B cells (MBCs) were identified to be significantly with PAAD prognosis. Two immune subtypes (IS1 and IS2) with distinct overall survival were constructed. Forty-one DEGs were identified between IS1 and IS2. Four prognostic genes (ANLN, ARNTL2, SERPINB5, and DKK1) were screened to develop a prognostic model. The model was effective in classifying samples into high-risk and low-risk groups with distinct prognosis. Three subgroups of MBCs were identified, where MBC_0 and MBC_1 were differentially distributed between IS1 and IS2, high-risk and low-risk groups.ConclusionsMBCs were closely involved in PAAD progression, especially MBC_0 and MBC_1 subgroups. The four-gene prognostic model was predictive of overall survival and could guide immunotherapy for patients with PAAD.

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Section: Methodsmentioning

confidence: 99%

Discovering a Four-Gene Prognostic Model Based on Single-Cell Data and Gene Expression Data of Pancreatic Adenocarcinoma

Huang

Zhou

et al. 2022

Front. Endocrinol.

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“…Many studies (15,31) have shown that ASCP is always more aggressive and malignant histologically than ACP, but previous studies on ASCP (10,14,16) have confirmed that there is no difference in OS between ASCP and ACP in the whole population, which is different from the conclusions reported in the literature (8,12,25). In order to arrive at a reliable conclusion and minimize the influence of various biases, we used PSM to balance the baseline characteristics.…”

Section: Discussionmentioning

confidence: 99%

Survival Analysis and Prediction Model of ASCP Based on SEER Database

Lin²,

Yang³

et al. 2022

Front. Oncol.

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BackgroundThis study aims to compare the incidence and clinical and survival characteristics of adenosquamous carcinoma of the pancreas (ASCP) and adenomatous carcinoma of the pancreas (ACP), analyze the survival factors of ASCP and construct a prognostic model.MethodPatients diagnosed with pancreatic cancer from 2000 to 2018 are selected from the SEER database. ASCP and ACP are compared in terms of epidemiology, clinical characteristics and prognosis. Cases are matched in a 1:2 ratio, and survival analysis is performed. The Cox proportional hazard model is used to determine covariates related to overall survival (OS), and an ASCP prognosis nomogram is constructed and verified by consistency index (C-index), calibration chart and decision curve analysis (DCA). The accuracy of the model is compared with that of AJCC.Stage and SEER.Stage to obtain the area under the receiver operating characteristic (ROC) curve.Resultsthe age-adjusted incidence of ACP increased significantly over time from 2000 to 2008 and from 2008 to 2018 (P < 0.05). APC was 2.01% (95% CI: 1.95–2.21) and 1.08% (95% CI: 0.93–1.25) respectively. The age-adjusted incidence of ASCP increased with time from 2000 to 2018 (P < 0.05) and APC was 3.64% (95% CI: 3.25–4.01).After propensity score matching (PSM), the OS and cancer-specific survival (CSS) of ACP are better than those of ASCP. The survival time of ASCP is significantly improved by the combined treatment of surgery + chemotherapy + radiotherapy, with a median OS of 31 months. Cox proportional hazard regression analysis shows that age, race, surgery, radiotherapy, chemotherapy and tumor size are independent factors affecting the prognosis. DCA and area under the curve (AUC) value shows that the model has good discrimination ability.ConclusionThe OS prognosis of ASCP is worse than that of ACP, and the nomogram has high accuracy for the prognosis prediction of ASCP.

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“…In fact, our current study is not the first to focus on the single-cell pattern of ASPC. Xin et al reported single-cell sequencing results from one ASPC sample, demonstrating that EGFRassociated ligand-receptor pairs are activated in ductalstromal cell communications (10). However, their study has some questions that need to be explored.…”

Section: Discussionmentioning

confidence: 99%

“…S t u di e s f oc u s i n g o n t h e A S P C t u m or microenvironment using single-cell sequencing analysis are also rare, and there is only one study related to ASPC. Xin et al reported single-cell sequencing results from one ASPC sample, demonstrating that epidermal growth factor receptor (EGFR)-associated ligand-receptor pairs are activated in ductalstromal cell communications (10). However, their study lacked a depiction of the ASPC tumor microenvironment and a comparison between PDAC and ASPC.…”

Section: Introductionmentioning

confidence: 99%

Single-cell sequencing reveals heterogeneity between pancreatic adenosquamous carcinoma and pancreatic ductal adenocarcinoma with prognostic value

Zhang¹,

Wu²,

Pan³

et al. 2022

Front. Immunol.

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Pancreatic adenosquamous carcinoma (ASPC) is a rare subtype of pancreatic cancer with lethal malignancy, and few studies have focused on the heterogeneity of ASPC. Here, we performed a single-cell sequencing procedure on pancreatic tumor tissue from an ASPC patient and a patient with high-grade intraductal papillary mucinous neoplasm (IPMN). Through the combined analysis of single-cell sequencing data from five pancreatic ductal adenocarcinoma (PDAC) patients, one IPMN patient, and one ASPC patient in a public database, we identified 11 main types of cells, including macrophages, B cells, cancer stem cells, ductal cells, fibroblasts, endo/stellate cells, neutrophils, acinar cells, T cells, natural killer (NK) cells, dendritic cells, and mast cells. Then, the different characteristics and differentiation paths of the immune microenvironment among IPMN, ASPC, and PDAC in macrophages, T cells, and cancer-associated fibroblasts (CAFs) were identified through multiple bioinformatics analyses. Two novel special cancer-associated fibroblasts were identified as nCAFs and imCAFs. Then, cancer cells in duct cells were identified using the infercnv software. Two ASPC-specific subgroups of cancer cells with squamous cell features were identified. Finally, the identified specific CAFs and cancer cells were mapped to TCGA-PAAD cohort through the cibersoftx software. All of these identified subgroups were calculated to have a significant prognostic value in pancreatic cancer patients. These findings will promote the clinical application of single-cell sequencing data of pancreatic cancer and deepen our understanding of ASPC.

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Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma

Cited by 30 publications

References 81 publications

Discovering a Four-Gene Prognostic Model Based on Single-Cell Data and Gene Expression Data of Pancreatic Adenocarcinoma

Discovering a Four-Gene Prognostic Model Based on Single-Cell Data and Gene Expression Data of Pancreatic Adenocarcinoma

Survival Analysis and Prediction Model of ASCP Based on SEER Database

Single-cell sequencing reveals heterogeneity between pancreatic adenosquamous carcinoma and pancreatic ductal adenocarcinoma with prognostic value

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