SPINKs in Tumors: Potential Therapeutic Targets

Liao, Chengcheng; Wang, Qian; An, Jiaxing; Zhang, Minglin; Chen, Jie; Li, Xiaolan; Xiao, Linlin; Wang, Jiajia; Qian, Long; Liu, Jianguo; Guan, Xiaoyan

doi:10.3389/fonc.2022.833741

Cited by 14 publications

(12 citation statements)

References 218 publications

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“…SPINK1 is an oncogenic protein that is overexpressed in various tumors, including HCC [ 6 , 7 ]. Previous investigations into SPINK1 have primarily focused on bulk tumors [ 16 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

“…Serine peptidase inhibitor Kazal type 1 (SPINK1) is a secretory protein that plays important roles in various physiological processes, including pancreatic functions, sperm maturation, and skin barrier homeostasis [ 6 ]. Notably, SPINK1 also assumes critical functions in cancer pathogenesis, and has been identified as dysregulated in many tumor types, including HCC [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

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SPINK1 Overexpression Correlates with Hepatocellular Carcinoma Treatment Resistance Revealed by Single Cell RNA-Sequencing and Spatial Transcriptomics

Yang,

Guo,

et al. 2024

Biomolecules

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Low efficacy of treatments and chemoresistance are challenges in addressing refractory hepatocellular carcinoma (HCC). SPINK1, an oncogenic protein, is frequently overexpressed in many HCC cases. However, the impact of SPINK1 on HCC treatment resistance remains poorly understood. Here, we elucidate the functions of SPINK1 on HCC therapy resistance. Analysis of SPINK1 protein level reveals a correlation between elevated SPINK1 expression and unfavorable prognosis. Furthermore, intercellular variations in SPINK1 expression levels are observed. Subsequent examination of single cell RNA-sequencing data from two HCC cohorts further suggest that SPINK1-high cells exhibit heightened activity in drug metabolic pathways compared to SPINK1-low HCC cells. High SPINK1 expression is associated with reduced sensitivities to both chemotherapy drugs and targeted therapies. Moreover, spatial transcriptomics data indicate that elevated SPINK1 expression correlates with non-responsive phenotype during treatment with targeted therapy and immune checkpoint inhibitors. This is attributed to increased levels of drug metabolic regulators, especially CES2 and CYP3A5, in SPINK1-high cells. Experimental evidence further demonstrates that SPINK1 overexpression induces the expression of CES2 and CYP3A5, consequently promoting chemoresistance to sorafenib and oxaliplatin. In summary, our study unveils the predictive role of SPINK1 on HCC treatment resistance, identifying it as a potential therapeutic target for refractory HCC.

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“…SPINK1 is an oncogenic protein that is overexpressed in various tumors, including HCC [ 6 , 7 ]. Previous investigations into SPINK1 have primarily focused on bulk tumors [ 16 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

SPINK1 Overexpression Correlates with Hepatocellular Carcinoma Treatment Resistance Revealed by Single Cell RNA-Sequencing and Spatial Transcriptomics

Yang,

Guo,

et al. 2024

Biomolecules

View full text Add to dashboard Cite

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“…SPINK5 has also been suggested as a therapeutic target for cancer 43 . Other novel candidates, CSTB, PDCD6, and PDGFRB, had limited research regarding IBD.…”

Section: Discussionmentioning

confidence: 99%

Multiomics-based causal inference identifies novel therapeutic targets for inflammatory bowel disease in East Asians

Kim,

Lee,

Kim

et al. 2023

Preprint

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Multiomics-based efforts to identify therapeutic targets for IBD have been limited to European populations. Prior reports on heterogeneity between East Asians and Europeans in clinical manifestations of IBD and genetic architectures of IBD-related variants warrant a separate investigation in East Asians. Using the East Asian genome and proteome data, we applied two multiomics-based causal inference methods, proteome-wide Mendelian randomization and causal proteome-wide association study. For IBD, Crohn’s disease (CD), and ulcerative colitis (UC), we found 30 potential drug targets with proteomic evidence. IL18R1, IL1RL1, KIR3DL1, and MEP1B had consistent associations with across IBD, CD, and UC. Fifteen targets were CD-specific, while eight were UC-specific. Among the candidate targets, thirteen and eight had supportive MR evidence in the plasma transcriptome data and the multi-tissue transcriptome data of European ancestry, respectively. IL18R1, IL6R, IL16, TNFRSF14 or their direct interactors were currently targeted by drugs being developed to treat IBD. IL1RL1 and PDGFRB had existing drugs that may be repurposed for IBD. Crucially, we identified six previously unreported target genes, opening new avenues for therapeutic interventions in IBD that warrant immediate validation in upcoming experiments and clinical trials.

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Section: Introductionmentioning

confidence: 99%

“…These results imply that SPINK1, released by cells experiencing low oxygen levels, acts in a paracrine manner to shield surrounding cancer cells with sufficient oxygen levels from radiation, highlighting its role in radioresistance. [37] [38] FOXM1 (Fork head Box Protein M1) is a crucial transcription factor linked to cellular proliferation, selfrenewal, and tumorigenesis. Its widespread expression during the cell cycle links it to cancer, where its overexpression is commonly observed, signifying an unfavorable outlook for individuals with cancer.…”

Section: Introductionmentioning

confidence: 99%

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

Parichehreh,

Kiaei,

Boush

et al. 2024

Preprint

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BackgroundMalignant neoplasm of the pancreas (MNP), a highly lethal illness with bleak outlook and few therapeutic avenues, entails numerous cellular transformations. These include irregular proliferation of ductal cells, activation of stellate cells, initiation of epithelial-to-mesenchymal transition, and changes in cell shape, movement, and attachment. Discovering potent drug cocktails capable of addressing the genetic and protein factors underlying pancreatic cancer’s development is formidable due to the disease’s intricate and varied nature.MethodIn this study, we introduce a fresh model utilizing Graph Attention Networks (GATs) to pinpoint potential drug pairings with synergistic effects for MNP, following the RAIN protocol. This protocol comprises three primary stages: Initially, employing Graph Neural Network (GNN) to suggest drug combinations for disease management by acquiring embedding vectors of drugs and proteins from a diverse knowledge graph encompassing various biomedical data types, such as drug-protein interactions, gene expression, and drug-target interactions. Subsequently, leveraging natural language processing to gather pertinent articles from clinical trials incorporating the previously recommended drugs. Finally, conducting network meta-analysis to assess the relative effectiveness of these drug combinations.ResultWe implemented our approach on a network dataset featuring drugs and genes as nodes, connected by edges representing their respective p-values. Our GAT model identified Gemcitabine, Pancrelipase Amylase, and Octreotide as the optimal drug combination for targeting the human genes/proteins associated with this cancer. Subsequent scrutiny of clinical trials and literature confirmed the validity of our findings. Additionally, network meta-analysis confirmed the efficacy of these medications concerning the pertinent genes.ConclusionBy employing GAT within the RAIN protocol, our approach represents a novel and efficient method for recommending prominent drug combinations to target proteins/genes associated with pancreatic cancer. This technique has the potential to aid healthcare professionals and researchers in identifying optimal treatments for patients while also unveiling underlying disease mechanisms.HighlightsGraph Attention Networks (GATs) used to recommend drug combinations for pancreatic cancerRAIN protocol applied to extract relevant information from clinical trials and literatureGemcitabine, Pancrelipase Amylase, and Octreotide identified as optimal drug combinationNetwork meta-analysis confirmed the effectiveness of the drug combination on gene targetsNovel and efficient method for drug discovery and disease mechanism elucidationAbstract Figure

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SPINKs in Tumors: Potential Therapeutic Targets

Cited by 14 publications

References 218 publications

SPINK1 Overexpression Correlates with Hepatocellular Carcinoma Treatment Resistance Revealed by Single Cell RNA-Sequencing and Spatial Transcriptomics

SPINK1 Overexpression Correlates with Hepatocellular Carcinoma Treatment Resistance Revealed by Single Cell RNA-Sequencing and Spatial Transcriptomics

Multiomics-based causal inference identifies novel therapeutic targets for inflammatory bowel disease in East Asians

Graph Attention Networks for Drug Combination Discovery: Targeting Pancreatic Cancer Genes with RAIN Protocol

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