High mRNA expression of splice variant SYK short correlates with hepatic disease progression in chemonaive lymph node negative colon cancer patients

Clinically relevant immune subtypes based on alternative splicing landscape of immune-related genes for lung cancer advanced PPPM approach

Background

Alternative splicing (AS) occurs in the process of gene post-transcriptional process, which is very important for the correct synthesis and function of protein. The change of AS pattern may lead to the change of expression level or function of lung cancer-related genes, and then affect the occurrence and development of lung cancers. The specific AS pattern might be used as a biomarker for early warning and prognostic assessment of a cancer in the framework of predictive, preventive, and personalized medicine (PPPM; 3PM). AS events of immune-related genes (IRGs) were closely associated with tumor progression and immunotherapy. We hypothesize that IRG-AS events are significantly different in lung adenocarcinomas (LUADs) vs. controls or in lung squamous cell carcinomas (LUSCs) vs. controls. IRG-AS alteration profiling was identified to construct IRG-differentially expressed AS (IRG-DEAS) signature models. Study on the selective AS events of specific IRGs in lung cancer patients might be of great significance for further exploring the pathogenesis of lung cancer, realizing early detection and effective monitoring of lung cancer, finding new therapeutic targets, overcoming drug resistance, and developing more effective therapeutic strategies, and better used for the prediction, diagnosis, prevention, and personalized medicine of lung cancer.

Methods

The transcriptomic, clinical, and AS data of LUADs and LUSCs were downloaded from TCGA and its SpliceSeq databases. IRG-DEAS events were identified in LUAD and LUSC, followed by their functional characteristics, and overall survival (OS) analyses. OS-related IRG-DEAS prognostic models were constructed for LUAD and LUSC with Lasso regression, which were used to classify LUADs and LUSCs into low- and high-risk score groups. Furthermore, the immune cell distribution, immune-related scores, drug sensitivity, mutation status, and GSEA/GSVA status were analyzed between low- and high-risk score groups. Also, low- and high-immunity clusters and AS factor (SF)-OS-related-AS co-expression network and verification of cell function of CELF6 were analyzed in LUAD and LUSC.

Results

Comprehensive analysis of transcriptomic, clinical, and AS data of LUADs and LUSCs identified IRG-AS events in LUAD (n = 1607) and LUSC (n = 1656), including OS-related IRG-AS events in LUAD (n = 127) and LUSC (n = 105). A total of 66 IRG-DEAS events in LUAD and 89 IRG-DEAS events in LUSC were identified compared to controls. The overlapping analysis between IRG-DEASs and OS-related IRG-AS events revealed 14 OS-related IRG-DEAS events for LUAD and 16 OS-related IRG-DEAS events for LUSC, which were used to identify and optimize a 12-OS-related-IRG-DEAS signature prognostic model for LUAD and an 11-OS-related-IRG-DEAS signature prognostic model for LUSC. These two prognostic models effectively divided LUAD or LUSC samples into low- and high-risk score groups that were closely associated with OS, clinical characteristics, and tumor immune microenvironment, with significant gene sets and pathways enriched in the two groups. Moreover, weighted gene co-expression network (WGCNA) and nonnegative matrix factorization method (NMF) analyses identified four OS-relevant subtypes of LUAD and six OS-relevant subtypes of LUSC, and ssGSEA identified five immunity-relevant subtypes of LUAD and five immunity-relevant subtypes of LUSC. Interestingly, splicing factors-OS-related-AS network revealed hub molecule CELF6 was significantly related to the malignant phenotype in lung cancer cells.

Conclusions

This study established two reliable IRG-DEAS signature prognostic models and constructed interesting splicing factor-splicing event networks in LUAD and LUSC, which can be used to construct clinically relevant immune subtypes, patient stratification, prognostic prediction, and personalized medical services in the PPPM practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00366-4.

Biochemical characterization of spleen tyrosine kinase (SYK) isoforms in platelets

Alternate splicing is among the regulatory mechanisms imparting functional diversity in proteins. Studying protein isoforms generated through alternative splicing is therefore critical for understanding protein functions in many biological systems. Spleen tyrosine kinase (Syk) plays an essential role in ITAM/hemITAM signaling in many cell types, including platelets. However, the spectrum of Syk isoforms expressed in platelets has not been characterized. Syk has been shown to have a full-length long isoform SykL and a shorter SykS lacking 23 amino acid residues within its interdomain B. Furthermore, putative isoforms lacking another 23 amino acid-long sequence or a combination of the two deletions have been postulated to exist. In this report, we demonstrate that mouse platelets express full-length SykL and the previously described shorter isoform SykS, but lack other shorter isoforms, whereas human platelets express predominantly SykL. These results both indicate a possible role of alternative Syk splicing in the regulation of receptor signaling in mouse platelets and a difference between signaling regulation in mouse and human platelets.

Targeting the splicing isoforms of spleen tyrosine kinase affects the viability of colorectal cancer cells

Spleen tyrosine kinase (Syk) expression have been both positively and negatively associated with tumorigenesis. Our goal was to evaluate the contribution of Syk and its two splice variants, full length Syk (L) and short isoform Syk (S), in the tumor biology of colorectal cancer cells (CRC). The analysis of Syk expression in primary human colorectal tumors, as well as the analysis of TCGA database, revealed a high Syk mRNA expression score in colorectal cancer tumors, suggesting a tumor promotor role of Syk in CRC. Our analysis showed that Syk (L) isoform is highly expressed in the majority of the tumor tissues and that it remains expressed in tumors in which global Syk expression is downregulated, suggesting the dependence of tumors to Syk (L) isoform. We also identified a small cluster of tumor tissues, which express a high proportion of Syk (S) isoform. This specific cluster is associated with overexpressed genes related to translation and mitochondria, and down regulated genes implicated in the progression of mitosis. For our functional studies, we used short hairpin RNA tools to target the expression of Syk in CRC cells bearing the activating K-Ras (G13D) mutation. Our results showed that while global Syk knock down increases cell proliferation and cell motility, Syk (L) expression silencing affects the viability and induces the apoptosis of the cells, confirming the dependence of cells on Syk (L) isoform for their survival. Finally, we report the promising potential of compound C-13, an original non-enzymatic inhibitor of Syk isolated in our group. In vitro studies showed that C-13 exerts cytotoxic effects on Syk-positive CRC cells by inhibiting their proliferation and their motility, and by inducing their apoptosis, while Syk-negative cell lines viability was not affected. Moreover, the oral and intraperitoneal administration of C-13 reduced the tumor growth of CRC DLD-1 cells xenografts in Nude mice in vivo.

Early Cost-effectiveness Analysis of Risk-Based Selection Strategies for Adjuvant Treatment in Stage II Colon Cancer: The Potential Value of Prognostic Molecular Markers

BACKGROUND

To explore the potential value of consensus molecular subtypes (CMS) in stage II colon cancer treatment selection, we carried out an early cost-effectiveness assessment of a CMS-based strategy for adjuvant chemotherapy.

METHODS

We used a Markov cohort model to evaluate three selection strategies: (i) the Dutch guideline strategy (MSS+pT4), (ii) the mutation-based strategy (MSS plus a BRAF and/or KRAS mutation or MSS plus pT4), and (iii) the CMS-based strategy (CMS4 or pT4). Outcomes were number of colon cancer deaths per 1,000 patients, total discounted costs per patient (pp), and quality-adjusted life-years (QALY) pp. The analyses were conducted from a Dutch societal perspective. The robustness of model predictions was assessed in sensitivity analyses. To evaluate the value of future research, we performed a value of information (VOI) analysis.

RESULTS

The Dutch guideline strategy resulted in 8.10 QALYs pp and total costs of €23,660 pp. The CMS-based and mutation-based strategies were more effective and more costly, with 8.12 and 8.13 QALYs pp and €24,643 and €24,542 pp, respectively. Assuming a threshold of €50,000/QALY, the mutation-based strategy was considered as the optimal strategy in an incremental analysis. However, the VOI analysis showed substantial decision uncertainty driven by the molecular markers (expected value of partial perfect information: €18M).

CONCLUSIONS

On the basis of current evidence, our analyses suggest that the mutation-based selection strategy would be the best use of resources. However, the extensive decision uncertainty for the molecular markers does not allow selection of an optimal strategy at present.

IMPACT

Future research is needed to eliminate decision uncertainty driven by molecular markers.

Circular RNA in Chemonaive Lymph Node Negative Colon Cancer Patients

Circular RNAs (circRNAs) appear important in tumor progression of colon cancer (CC). We identified an extensive catalog of circRNAs in 181 chemonaive stage I/II colon tumors, who underwent curative surgery between 2007 and 2014. We identified circRNAs from RNAseq data, investigated common biology related to circRNA expression, and studied the association between circRNAs and relapse status, tumor stage, consensus molecular subtypes (CMS), tumor localization and microsatellite instability (MSI). We identified 2606 unique circRNAs. 277 circRNAs (derived from 260 genes) were repeatedly occurring in at least 20 patients of which 153 showed a poor or even negative (R < 0.3) correlation with the expression level of their linear gene. The circular junctions for circSATB2, circFGD6, circKMT2C and circPLEKHM3 were validated by Sanger sequencing. Multiple correspondence analysis showed that circRNAs were often co-expressed and that high diversity in circRNAs was associated with favorable disease-free survival (DFS), which was confirmed by Cox regression analysis (Hazard Ratio (HR) 0.60, 95% CI 0.38-0.97, p = 0.036). Considering individual circRNAs, absence of circMGA was significantly associated with relapse, whereas circSATB2, circNAB1, and circCEP192 were associated with both MSI and CMS. This study represents a showcase of the potential clinical utility of circRNAs for prognostic stratification in patients with stage I-II colon cancer and demonstrated that high diversity in circRNAs is associated with favorable DFS.

Model-based effectiveness and cost-effectiveness of risk-based selection strategies for adjuvant chemotherapy in Dutch stage II colon cancer patients

BACKGROUND

We aimed to evaluate the cost-effectiveness of risk-based strategies to improve the selection of surgically treated stage II colon cancer (CC) patients for adjuvant chemotherapy.

METHODS

Using the 'Personalized Adjuvant TreaTment in EaRly stage coloN cancer' (PATTERN) model, we evaluated five selection strategies: (1) no chemotherapy, (2) Dutch guideline recommendations assuming observed adherence, (3) Dutch guideline recommendations assuming perfect adherence, (4) biomarker mutation OR pT4 stage strategy in which patients with MSS status combined with a pT4 stage or a mutation in BRAF and/or KRAS receive chemotherapy assuming perfect adherence and (5) biomarker mutation AND pT4 stage strategy in which patients with MSS status combined with a pT4 stage tumor and a BRAF and/or KRAS mutation receive chemotherapy assuming perfect adherence. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Analyses were conducted from a societal perspective. The robustness of model predictions was assessed in sensitivity analyses.

RESULTS

The reference strategy, that is, no adjuvant chemotherapy, resulted in 139 CC deaths in a cohort of 1000 patients, 8.077 QALYs pp and total costs of €22,032 pp. Strategies 2-5 were more effective (range 8.094-8.217 QALYs pp and range 118-136 CC deaths per 1000 patients) and more costly (range €22,404-€25,102 pp). Given a threshold of €50,000/QALY, the optimal use of resources would be to treat patients with either the full adherence strategy and biomarker mutation OR pT4 stage strategy.

CONCLUSION

Selection of stage II CC patients for chemotherapy can be improved by either including biomarker status in the selection strategy or by improving adherence to the Dutch guideline recommendations.

Model-based evaluation of the cost effectiveness of 3 versus 6 months' adjuvant chemotherapy in high-risk stage II colon cancer patients

BACKGROUND

Our aim was to evaluate the cost effectiveness of 3 months' adjuvant chemotherapy versus 6 months in high-risk (T4 stage + microsatellite stable) stage II colon cancer (CC) patients.

METHODS

Using the validated PATTERN Markov cohort model, which simulates the disease progression of stage II CC patients from diagnosis to death, we first evaluated a reference strategy in which high-risk patients were treated with chemotherapy for 6 months. In the second strategy, treatment duration was shortened to 3 months. Both strategies were evaluated for CAPOX (capecitabine plus oxaliplatin) and FOLFOX (fluorouracil, leucovorin and oxaliplatin). Based on trial data, we assumed that shortened treatment duration compared with a 6-month regimen was equally effective for CAPOX and less effective for FOLFOX. Adverse events were highest in the 6-month strategy. Analyses were conducted from a societal perspective using a lifelong time horizon. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Incremental net monetary benefit (iNMB) was calculated using a willingness-to-pay value of €50,000/QALY.

RESULTS

For CAPOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €41,257 pp. The 3-month strategy resulted in an equal number of CC deaths, but higher QALYs (6.80 pp) and lower costs (€37,645 pp), leading to a iNMB of €8454 per person for 3 months versus 6 months. For FOLFOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €47,135 pp. The 3-month strategy resulted in more CC deaths (393), lower QALYs (6.19 pp) and lower costs (€44,389 pp). An iNMB of -€23,189 was found for 3 months versus 6 months.

CONCLUSION

Our findings indicate that 3 months' adjuvant chemotherapy should be considered as standard of care in high-risk stage II CC patients for CAPOX, but not for FOLFOX.

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

AIM

To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy.

METHODS

A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy.

RESULTS

Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively.

CONCLUSION

This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.

Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis

Prognostic biomarkers are of great significance to predict the outcome of patients with cancer, to guide the clinical treatments, to elucidate tumorigenesis mechanisms, and offer the opportunity of identifying therapeutic targets. To screen and develop prognostic biomarkers, high throughput profiling methods including gene microarray and next-generation sequencing have been widely applied and shown great success. However, due to the lack of independent validation, only very few prognostic biomarkers have been applied for clinical practice. In order to cross-validate the reliability of potential prognostic biomarkers, some groups have collected the omics datasets (i.e., epigenetics/transcriptome/proteome) with relative follow-up data (such as OS/DSS/PFS) of clinical samples from different cohorts, and developed the easy-to-use online bioinformatics tools and web servers to assist the biomarker screening and validation. These tools and web servers provide great convenience for the development of prognostic biomarkers, for the study of molecular mechanisms of tumorigenesis and progression, and even for the discovery of important therapeutic targets. Aim to help researchers to get a quick learning and understand the function of these tools, the current review delves into the introduction of the usage, characteristics and algorithms of tools, and web servers, such as LOGpc, KM plotter, GEPIA, TCPA, OncoLnc, PrognoScan, MethSurv, SurvExpress, UALCAN, etc., and further help researchers to select more suitable tools for their own research. In addition, all the tools introduced in this review can be reached at http://bioinfo.henu.edu.cn/WebServiceList.html.

GENT2: an updated gene expression database for normal and tumor tissues

BACKGROUND

Gene Expression database of Normal and Tumor tissues 2 (GENT2) is an updated version of GENT, which has provided a user-friendly search platform for gene expression patterns across different normal and tumor tissues compiled from public gene expression data sets.

RESULTS

We refactored GENT2 with recent technologies such as Apache Lucene indexing for fast search and Google Web Toolkit (GWT) framework for a user-friendly web interface. Now, GENT2 contains more than 68,000 samples and has several new useful functions. First, GENT2 now provides gene expression across 72 different tissues compared to 57 in GENT. Second, with increasing importance of tumor subtypes, GENT2 provides an option to study the differential expression and its prognostic significance based on tumor subtypes. Third, whenever available, GENT2 provides prognostic information of a gene of interest. Fourth, GENT2 provides a meta-analysis of survival information to provide users more reliable prognostic value of a gene of interest.

CONCLUSIONS

In conclusion, with these significant improvements, GENT2 will continue to be a useful tool to a wide range of researchers. GENT2 is freely available at http://gent2.appex.kr .