A Transcriptomic Signature for Risk-Stratification and Recurrence Prediction in Intrahepatic Cholangiocarcinoma

Upregulation of POC1A in lung adenocarcinoma promotes tumour progression and predicts poor prognosis

Lung adenocarcinoma (LUAD) is characterized by a high incidence rate and mortality. Recently, POC1 centriolar protein A (POC1A) has emerged as a potential biomarker for various cancers, contributing to cancer onset and development. However, the association between POC1A and LUAD remains unexplored. We extracted The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data sets to analyse the differential expression of POC1A and its relationship with clinical stage. Additionally, we performed diagnostic receiver operator characteristic (ROC) curve analysis and Kaplan-Meier (KM) survival analysis to assess the diagnostic and prognostic value of POC1A in LUAD. Furthermore, we investigated the correlation between POC1A expression and immune infiltration, tumour mutation burden (TMB), immune checkpoint expression and drug sensitivity. Finally, we verified POC1A expression using real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Cell experiments were conducted to validate the effect of POC1A expression on the proliferation, migration and invasion of lung cancer cells. POC1A exhibited overexpression in most tumour tissues, and its overexpression in LUAD was significantly correlated with late-stage presentation and poor prognosis. The high POC1A expression group showed lower levels of immune infiltration but higher levels of immune checkpoint expression and TMB. Moreover, the high POC1A expression group demonstrated sensitivity to multiple drugs. In vitro experiments confirmed that POC1A knockdown led to decreased proliferation, migration, and invasion of lung cancer cells. Our findings suggest that POC1A may contribute to tumour development by modulating the cell cycle and immune cell infiltration. It also represents a potential therapeutic target and marker for the diagnosis and prognosis of LUAD.

SerpinB3/4 Expression Is Associated with Poor Prognosis in Patients with Cholangiocarcinoma

Cholangiocarcinoma (CCA), the second most common primary liver tumor, is associated with a dismal outcome, and useful prognostic markers are not currently available in clinical practice. SerpinB3, a serine protease inhibitor, was recently found to play a relevant role in malignant transformation in different cancers. The aim of the present study was to determine the expression of SerpinB3/4 in tissue and serum samples of patients with CCA in relation to clinical outcomes. SerpinB3/4 was assessed in the tissue microarrays (TMAs) of 123 surgically resected CCAs. ELISA assays were carried out in 188 patients with CCA to detect the free and IgM-linked forms of SerpinB3/4. Overall survival was analyzed in relation to SerpinB3/4 expression, and Cox models were used to identify the variables associated with survival. High levels of SerpinB3/4 (TMA score 2+/3+) were detected in 15 tumors (12.2%), characterized by a more advanced TNM stage (III/IV: 64.3% vs. 31.3%; p = 0.031) and lower overall patient survival, independently of CCA subclass (intrahepatic CCA: median 1.1 (0.8-Not Estimable, NE) vs. 2.4 (1.8-3.4) years; p = 0.0007; extrahepatic CCA: median 0.8 (0.2-NE) vs. 2.2 (1.5-5.4) years; p = 0.011). Vascular invasion (p = 0.027) and SerpinB3/4 scores (p = 0.0016) were independently associated with mortality in multivariate analysis. Patients who had detectable free or IgM-linked SerpinB3/4 in their serum showed poorer survival (1 vs. 2.4 years, p = 0.015, for free SerpinB3/4, and 1 vs. 2.6 years, p = 0.0026, for SerpinB3/4-IgM). In conclusion, high levels of SerpinB3/4 in tissue and serum in CCA are associated with poor outcomes after surgery, regardless of tumor subclass.

Predicting very early recurrence in intrahepatic cholangiocarcinoma after curative hepatectomy using machine learning radiomics based on CECT: A multi-institutional study

BACKGROUND

Even after curative resection, the prognosis for patients with intrahepatic cholangiocarcinoma (iCCA) remains disappointing due to the extremely high incidence of postoperative recurrence.

METHODS

A total of 280 iCCA patients following curative hepatectomy from three independent institutions were recruited to establish the retrospective multicenter cohort study. The very early recurrence (VER) of iCCA was defined as the appearance of recurrence within 6 months. The 3D tumor region of interest (ROI) derived from contrast-enhanced CT (CECT) was used for radiomics analysis. The independent clinical predictors for VER were histological stage, AJCC stage, and CA199 levels. We implemented K-means clustering algorithm to investigate novel radiomics-based subtypes of iCCA. Six types of machine learning (ML) algorithms were performed for VER prediction, including logistic, random forest (RF), neural network, bayes, support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost). Additionally, six clinical ML (CML) models and six radiomics-clinical ML (RCML) models were developed to predict VER. Predictive performance was internally validated by 10-fold cross-validation in the training cohort, and further evaluated in the external validation cohort.

RESULTS

Approximately 30 % of patients with iCCA experienced VER with extremely discouraging outcome (Hazard ratio (HR) = 5.77, 95 % Confidence Interval (CI) = 3.73-8.93, P < 0.001). Two distinct iCCA subtypes based on radiomics features were identified, and subtype 2 harbored a higher proportion of VER (47.62 % Vs 25.53 %) and significant shorter survival time than subtype 1. The average AUC values of the CML and RCML models were 0.744 ± 0.018, and 0.900 ± 0.014 in the training cohort, and 0.769 ± 0.065 and 0.929 ± 0.027 in the external validation cohort, respectively.

CONCLUSION

Two radiomics-based iCCA subtypes were identified, and six RCML models were developed to predict VER of iCCA, which can be used as valid tools to guide individualized management in clinical practice.

New molecular mechanisms in cholangiocarcinoma: signals triggering interleukin-6 production in tumor cells and KRAS co-opted epigenetic mediators driving metabolic reprogramming

Background

Cholangiocarcinoma (CCA) is still a deadly tumour. Histological and molecular aspects of thioacetamide (TAA)-induced intrahepatic CCA (iCCA) in rats mimic those of human iCCA. Carcinogenic changes and therapeutic vulnerabilities in CCA may be captured by molecular investigations in bile, where we performed bile proteomic and metabolomic analyses that help discovery yet unknown pathways relevant to human iCCA.

Methods

Cholangiocarcinogenesis was induced in rats (TAA) and mice (Jnk^Δhepa + CCl₄ + DEN model). We performed proteomic and metabolomic analyses in bile from control and CCA-bearing rats. Differential expression was validated in rat and human CCAs. Mechanisms were addressed in human CCA cells, including Huh28-KRAS^G12D cells. Cell signaling, growth, gene regulation and [U-¹³C]-D-glucose-serine fluxomics analyses were performed. In vivo studies were performed in the clinically-relevant iCCA mouse model.

Results

Pathways related to inflammation, oxidative stress and glucose metabolism were identified by proteomic analysis. Oxidative stress and high amounts of the oncogenesis-supporting amino acids serine and glycine were discovered by metabolomic studies. Most relevant hits were confirmed in rat and human CCAs (TCGA). Activation of interleukin-6 (IL6) and epidermal growth factor receptor (EGFR) pathways, and key genes in cancer-related glucose metabolic reprogramming, were validated in TAA-CCAs. In TAA-CCAs, G9a, an epigenetic pro-tumorigenic writer, was also increased. We show that EGFR signaling and mutant KRAS^G12D can both activate IL6 production in CCA cells. Furthermore, phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in serine-glycine pathway, was upregulated in human iCCA correlating with G9a expression. In a G9a activity-dependent manner, KRAS^G12D promoted PHGDH expression, glucose flow towards serine synthesis, and increased CCA cell viability. KRAS^G12D CAA cells were more sensitive to PHGDH and G9a inhibition than controls. In mouse iCCA, G9a pharmacological targeting reduced PHGDH expression.

Conclusions

In CCA, we identified new pro-tumorigenic mechanisms: Activation of EGFR signaling or KRAS mutation drives IL6 expression in tumour cells; Glucose metabolism reprogramming in iCCA includes activation of the serine-glycine pathway; Mutant KRAS drives PHGDH expression in a G9a-dependent manner; PHGDH and G9a emerge as therapeutic targets in iCCA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02386-2.

POC1A, prognostic biomarker of immunosuppressive microenvironment in cancer

POC1 centriolar protein A (POC1A) effect in pan-cancer remains uncertain. The POC1A expression in normal and tumor tissues underwent analysis in this study utilizing data from the Genotype-Tissue Expression (GTEx) project and the Cancer Genome Atlas (TCGA) database. POC1A prognostic value and clinicopathological features were assessed utilizing the TCGA cohort. The relationship between immunological cell infiltration and POC1A of TCGA samples downloaded from TIMER2 and ImmuCellAI databases were observed. The relation between POC1A and immunological checkpoints genes, microsatellite instability (MSI) as well as tumor mutation burden (TMB) was also evaluated. Additionally, gene set enrichment analysis (GSEA) was utilized for exploring POC1A potential molecular mechanism in pan-cancer. In almost all 33 tumors, POCA1 showed a high expression. In most cases, high POC1A expression was linked significantly with a poor prognosis. Additionally, Tumor immune infiltration and tumors microenvironment were correlated with the expression of POC1A. In addition, TMB and MSI, as well as immune checkpoint genes in pan-cancer, were related to POC1A expression. In GSEA analysis, POC1A is implicated in cell cycle and immune-related pathways. These results might elucidate the crucial roles of POC1A in pan-cancer as a prognostic biomarker and immunotherapy target.

Genome-wide CRISPR screen identified Rad18 as a determinant of doxorubicin sensitivity in osteosarcoma

Background

Osteosarcoma (OS) is a malignant bone tumor mostly occurring in children and adolescents, while chemotherapy resistance often develops and the mechanisms involved remain challenging to be fully investigated.

Methods

Genome-wide CRISPR screening combined with transcriptomic sequencing were used to identify the critical genes of doxorubicin resistance. Analysis of clinical samples and datasets, and in vitro and in vivo experiments (including CCK-8, apoptosis, western blot, qRT-PCR and mouse models) were applied to confirm the function of these genes. The bioinformatics and IP-MS assays were utilized to further verify the downstream pathway. RGD peptide-directed and exosome-delivered siRNA were developed for the novel therapy strategy.

Results

We identified that E3 ubiquitin-protein ligase Rad18 (Rad18) contributed to doxorubicin-resistance in OS. Further exploration revealed that Rad18 interact with meiotic recombination 11 (MRE11) to promote the formation of the MRE11-RAD50-NBS1 (MRN) complex, facilitating the activation of the homologous recombination (HR) pathway, which ultimately mediated DNA damage tolerance and leaded to a poor prognosis and chemotherapy response in patients with OS. Rad18-knockout effectively restored the chemotherapy response in vitro and in vivo. Also, RGD-exosome loading chemically modified siRad18 combined with doxorubicin, where exosome and chemical modification guaranteed the stability of siRad18 and the RGD peptide provided prominent targetability, had significantly improved antitumor activity of doxorubicin.

Conclusions

Collectively, our study identifies Rad18 as a driver of OS doxorubicin resistance that promotes the HR pathway and indicates that targeting Rad18 is an effective approach to overcome chemotherapy resistance in OS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02344-y.

A transcriptomic signature that predicts cancer recurrence after hepatectomy in patients with colorectal liver metastases

BACKGROUND

Cancer recurrence is an important predictor of survival outcomes in patients with colorectal cancer-associated liver metastasis (CRLM), who undergo radical hepatectomy. Therefore, identification of patients with the greatest risk of recurrence is critical for developing a precision oncology strategy that might include frequent surveillance (in low-risk patients) or a more aggressive treatment approach (in high-risk patients). We performed genome-wide expression profiling, to identify and develop a transcriptomic signature for predicting recurrence in patients with CRLM.

METHODS

We analysed a total of 383 patients with CRLM, including 63 patients from a publicly available data set (the NCBI's Gene Expression Omnibus with accession number GSE81423). and 320 patients from whom surgical specimens were collected for independent training (n = 169) and validation (n = 151) of identified biomarkers. Using Cox's proportional hazard regression analysis, we evaluated the clinical significance of the identified gene signature by comparing its performance with several key clinical factors.

RESULTS

We identified a six-gene panel that robustly categorised patients with recurrence in the discovery (area under the curve (AUC) = 0.90). We showed that the panel was a significant predictor of recurrence in the clinical training (AUC = 0.83) and validation cohorts (AUC = 0.81). By combining our panel with key clinical factors, we established a risk-stratification model that emerged as an independent predictor of recurrence (AUC = 0.85; univariate: hazard ratio (HR) = 4.34, 95% confidence interval (CI) = 2.71-6.93, P < 0.001; multivariate: HR = 3.40, 95% CI = 1.76-6.56, P < 0.001). The stratification model revealed recurrence prediction in 89% of high-risk group and non-recurrence in 62% of low-risk group.

CONCLUSIONS

We established a novel transcriptomic signature that robustly predicts recurrence, which has significant implications for the management of patients with CRLM.

Current Advances in Basic and Translational Research of Cholangiocarcinoma

Simple Summary

Cholangiocarcinoma (CCA) is highly malignant biliary tract cancer, which is characterized by limited treatment options and poor prognosis. Basic science studies to seek therapies for CCA are also limited due to lack of gold-standard experimental models and heterogeneity of CCA resulting in various genetic alterations and origins of tumor cells. Recent studies have developed new experimental models and techniques that may facilitate CCA studies leading to the development of novel treatments. This review summarizes the update in current basic studies of CCA.

Abstract

Cholangiocarcinoma (CCA) is a type of biliary tract cancer emerging from the biliary tree. CCA is the second most common primary liver cancer after hepatocellular carcinoma and is highly aggressive resulting in poor prognosis and patient survival. Treatment options for CCA patients are limited since early diagnosis is challenging, and the efficacy of chemotherapy or radiotherapy is also limited because CCA is a heterogeneous malignancy. Basic research is important for CCA to establish novel diagnostic testing and more effective therapies. Previous studies have introduced new techniques and methodologies for animal models, in vitro models, and biomarkers. Recent experimental strategies include patient-derived xenograft, syngeneic mouse models, and CCA organoids to mimic heterogeneous CCA characteristics of each patient or three-dimensional cellular architecture in vitro. Recent studies have identified various novel CCA biomarkers, especially non-coding RNAs that were associated with poor prognosis or metastases in CCA patients. This review summarizes current advances and limitations in basic and translational studies of CCA.

Identification of Mutator-Derived Alternative Splicing Signatures of Genomic Instability for Improving the Clinical Outcome of Cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is an aggressive carcinoma with increasing incidence and poor outcomes worldwide. Genomic instability and alternative splicing (AS) events are hallmarks of carcinoma development and progression. The relationship between genomic instability, AS events, and tumor immune microenvironment remain unclear.

METHODS

The splicing profiles of patients with cholangiocarcinoma were obtained from The Cancer Genome Atlas (TCGA) spliceSeq database. The transcriptomics, simple nucleotide variation (SNP) and clinical data of patients with cholangiocarcinoma were obtained from TCGA database. Patients were divided into genomic unstable (GU-like) and genomic stable (GS-like) groups according to their somatic mutations. Survival-related differential AS events were identified through integrated analysis of splicing profiling and clinical data. Kyoto Encyclopedia of Genes and Genomes enrichment analysis was used to identify AS events occurring in genes enriched in cancer pathways. Pearson correlation was applied to analyze the splicing factors regulating AS events. CIBERSORT was used identify differentially infiltrating immune cells.

RESULTS

A prognostic signature was constructed with six AS events. Using this signature, the hazard ratio of risk score for overall survival is 2.362. For TCGA patients with cholangiocarcinoma, the area under the receiver operating characteristic curve is 0.981. CDK11A is a negative regulator of survival associated AS events. Additionally, the CD8+ T cell proportion and PD-L1 expression are upregulated in patients with cholangiocarcinoma and high splicing signatures.

CONCLUSION

We provide a prognostic signature for cholangiocarcinoma overall survival. The CDK11A splicing factor and SLC46A1-39899-ES and IARS-86836-ES AS events may be potential targets for cholangiocarcinoma therapy. Patients with high AS risk score may be more sensitive to anti-PD-L1/PD1 immunotherapy.