Alternative splicing in colon, bladder, and prostate cancer identified by exon array analysis

Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation

Advances in computer science in combination with the next-generation sequencing have introduced a new era in biology, enabling advanced state-of-the-art analysis of complex biological data. Bioinformatics is evolving as a union field between computer Science and biology, enabling the representation, storage, management, analysis and exploration of many types of data with a plethora of machine learning algorithms and computing tools. In this study, we used machine learning algorithms to detect differentially expressed genes between different types of cancer and showing the existence overlap to final results from RNA-sequencing analysis. The datasets were obtained from the National Center for Biotechnology Information resource. Specifically, dataset GSE68086 which corresponds to PMID:200,068,086. This dataset consists of 171 blood platelet samples collected from patients with six different tumors and healthy individuals. All steps for RNA-sequencing analysis (preprocessing, read alignment, transcriptome reconstruction, expression quantification and differential expression analysis) were followed. Machine Learning- based Random Forest and Gradient Boosting algorithms were applied to predict significant genes. The Rstudio statistical tool was used for the analysis.

Transcriptomic analysis reveals regulation of adipogenesis via long non-coding RNA, alternative splicing, and alternative polyadenylation

Obesity is characterized by dysregulated adipogenesis that leads to increased number and/or size of adipocytes. Understanding the molecular mechanisms governing adipogenesis is therefore key to designing therapeutic interventions against obesity. In our study, we analyzed 3'-end sequencing data that we generated from human preadipocytes and adipocytes, as well as previously published RNA-seq datasets, to elucidate mechanisms of regulation via long non-coding RNA (lncRNA), alternative splicing (AS) and alternative polyadenylation (APA). We discovered lncRNAs that have not been previously characterized but may be key regulators of white adipogenesis. We also detected 100 AS events and, using motif enrichment analysis, identified RNA binding proteins (RBPs) that could mediate exon skipping-the most prevalent AS event. In addition, we show that usage of alternative poly(A) sites in introns or 3'-UTRs of key adipogenesis genes leads to isoform diversity, which can have significant biological consequences on differentiation efficiency. We also identified RBPs that may modulate APA and defined how 3'-UTR APA can regulate gene expression through gain or loss of specific microRNA binding sites. Taken together, our bioinformatics-based analysis reveals potential therapeutic avenues for obesity through manipulation of lncRNA levels and the profile of mRNA isoforms via alternative splicing and polyadenylation.

CALD1 facilitates epithelial-mesenchymal transition progression in gastric cancer cells by modulating the PI3K-Akt pathway

BACKGROUND

CALD1 has been discovered to be abnormally expressed in a variety of malignant tumors, including gastric cancer (GC), and is associated with tumor progression and immune infiltration; however, the roles and mechanisms of CALD1 in epithelial-mesenchymal transition (EMT) in GC are unknown.

AIM

To investigate the role and mechanism of CALD1 in GC progression, invasion, and migration.

METHODS

In this study, the relationship between CALD1 and GC, as well as the possible network regulatory mechanisms of CALD1, was investigated by bioinformatics and validated by experiments. CALD1-siRNA was synthesized and used to transfect GC cells. Cell activity was measured using the CCK-8 method, cell migration and invasive ability were measured using wound healing assay and Transwell assay, and the expression levels of relevant genes and proteins in each group of cells were measured using qRT-PCR and Western blot. A GC cell xenograft model was established to verify the results of in vitro experiments.

RESULTS

Bioinformatics results showed that CALD1 was highly expressed in GC tissues, and CALD1 was significantly higher in EMT-type GC tissues than in tissues of other types of GC. The prognosis of patients with high expression of CALD1 was worse than that of patients with low expression, and a prognostic model was constructed and evaluated. The experimental results were consistent with the results of the bioinformatics analysis. The expression level of CALD1 in GC cell lines was all higher than that in gastric epithelial cell line GES-1, with the strongest expression found in AGS and MKN45 cells. Cell activity was significantly reduced after CALD1-siRNA transfection of AGS and MKN45 cells. The ability of AGS and MKN45 cells to migrate and invade was reduced after CALD1-siRNA transfection, and the related mRNA and protein expression was altered. According to bioinformatics findings in GC samples, the CALD1 gene was significantly associated with the expression of members of the PI3K-AKT-mTOR signaling pathway as well as the EMT signaling pathway, and was closely related to the PI3K-Akt signaling pathway. Experimental validation revealed that upregulation of CALD1 increased the expression of PI3K, p-AKT, and p-mTOR, members of the PI3K-Akt pathway,while decreasing the expression of PTEN; PI3K-Akt inhibitor treatment decreased the expression of PI3K, p-AKT, and p-mTOR in cells overexpressing CALD1 (still higher than that in the normal group), but increased the expression of PTEN (still lower than that in the normal group). CCK-8 results revealed that the effect of CALD1 on tumor cell activity was decreased by the addition of the inhibitor. Scratch and Transwell experiments showed that the effect of CALD1 on tumor cell migration and invasion was weakened by the addition of the PI3K-Akt inhibitor. The mRNA and protein levels of EMT-related genes in AGS and MKN45 cells were greatly altered by the overexpression of CALD1, whereas the effect of overexpression of CALD1 was significantly weakened by the addition of the PI3K-Akt inhibitor. Animal experiments showed that tumour growth was slow after inhibition of CALD1, and the expression of some PI3K-Akt and EMT pathway proteins was altered.

CONCLUSION

Increased expression of CALD1 is a key factor in the progression, invasion, and metastasis of GC, which may be associated with regulating the PI3K-Akt pathway to promote EMT.

Comprehensive analysis of alternative splicing across multiple transcriptomic cohorts reveals prognostic signatures in prostate cancer

BACKGROUND

Alternative splicing (AS) plays a crucial role in transcriptomic diversity and is a hallmark of cancer that profoundly influences the development and progression of prostate cancer (PCa), a prevalent and potentially life-limiting cancer among men. Accumulating evidence has highlighted the association between AS dysregulation and the onset and progression of PCa. However, a comprehensive and integrative analysis of AS profiles at the event level, utilising data from multiple high-throughput cohorts and evaluating the prognosis of PCa progression, remains lacking and calls for thorough exploration.

RESULTS

We identified a differentially expressed retained intron event in ZWINT across three distinct cohorts, encompassing an original array-based dataset profiled by us previously and two RNA sequencing (RNA-seq) datasets. Subsequent in-depth analyses of these RNA-seq datasets revealed  141 altered events, of which 21 demonstrated a significant association with patients' biochemical recurrence-free survival (BCRFS). We formulated an AS event-based prognostic signature, capturing six pivotal events in genes CYP4F12, NFATC4, PIGO, CYP3A5, ALS2CL, and FXYD3. This signature effectively differentiated  high-risk patients diagnosed with PCa, who experienced shorter BCRFS, from their low-risk counterparts. Notably, the signature's predictive power surpassed traditional clinicopathological markers in forecasting 5-year BCRFS, demonstrating robust performance in both internal and external validation sets. Lastly, we constructed a novel nomogram that integrates patients' Gleason scores with pathological tumour stages, demonstrating improved prognostication of BCRFS.

CONCLUSIONS

Prediction of clinical progression remains elusive in PCa. This research uncovers novel splicing events associated with BCRFS, augmenting existing prognostic tools, thus potentially refining clinical decision-making.

Alternative splicing in bladder cancer: potential strategies for cancer diagnosis, prognosis, and treatment

Bladder cancer is the most common malignancy of the urinary tract worldwide. The therapeutic options to tackle this disease comprise surgery, intravesical or systemic chemotherapy, and immunotherapy. Unfortunately, a wide number of patients ultimately become resistant to these treatments and develop aggressive metastatic disease, presenting a poor prognosis. Therefore, the identification of novel therapeutic approaches to tackle this devastating pathology is urgently needed. However, a significant limitation is that the progression and drug response of bladder cancer is strongly associated with its intrinsic molecular heterogeneity. In this sense, RNA splicing is recently gaining importance as a critical hallmark of cancer since can have a significant clinical value. In fact, a profound dysregulation of the splicing process has been reported in bladder cancer, especially in the expression of certain key splicing variants and circular RNAs with a potential clinical value as diagnostic/prognostic biomarkers or therapeutic targets in this pathology. Indeed, some authors have already evidenced a profound antitumor effect by targeting some splicing factors (e.g., PTBP1), mRNA splicing variants (e.g., PKM2, HYAL4-v1), and circular RNAs (e.g., circITCH, circMYLK), which illustrates new possibilities to significantly improve the management of this pathology. This review represents the first detailed overview of the splicing process and its alterations in bladder cancer, and highlights opportunities for the development of novel diagnostic/prognostic biomarkers and their clinical potential for the treatment of this devastating cancer type. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA in Disease and Development > RNA in Disease.

Immunohistochemical Expression Analysis of Caldesmon Isoforms in Colorectal Carcinoma Reveals Interesting Correlations with Tumor Characteristics

Colorectal cancer is a notorious disease, with almost half of the patients succumbing to the disease. The prevalence and incidence rates of colorectal cancer are increasing in many parts of the world, highlighting the need to discover new biomarkers for diagnosis and therapy. Caldesmon (CaD), an actin-binding protein that plays a significant role in controlling cell motility, has emerged as a promising biomarker. The CALD1 gene encodes CaD as multiple transcripts that mainly encode two protein isoforms: High-molecular-weight (h-CaD), expressed in smooth muscle, and low-molecular-weight (l-CaD), expressed in nonsmooth muscle cells. Most studies have suggested an oncogenic role of CaD in colorectal cancer, but the exact subcellular localization of the two CaD isoforms in tumor cells and stroma have not been clarified yet. Here, we analyzed tissue samples from 262 colorectal cancer patients by immunohistochemistry analysis using specific antibodies for l-CaD and h-CaD. The results showed elevated cytoplasmic expression levels of l-Cad in 187/262 (71.4%) cases. l-Cad was expressed at low levels in the normal colon mucosa and was also consistently expressed in the cancer-associated stroma of all cases, suggesting that it could play a role in modulating the tumor microenvironment. l-CaD expression in cancer cells was associated with preinvasive stages of cancer. Survival analysis indicated that patients with high l-CaD expression in tumor cells could respond poorly to selective chemotherapeutic 5FU, but not combination chemotherapy. h-CaD was expressed in colonic and vascular smooth muscle cells as expected and to a lesser extent in the tumor-associated stroma, but it was not expressed in the cancer cells or normal colon mucosal epithelial cells. Collectively, these data clarify how the expression patterns of CaD isoforms in colorectal cancer can have applications in the management of colorectal cancer patients.

Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis

There is a pertinent need to develop prognostic biomarkers for practicing predictive, preventive and personalized medicine (PPPM) in colorectal cancer metastasis. The analysis of isoform expression data governed by alternative splicing provides a high-resolution picture of mRNAs in a defined condition. This information would not be available by studying gene expression changes alone. Hence, we utilized our prior data from an exon microarray and found ADAM12 and MUC4 to be strong biomarker candidates based on their alternative splicing scores and pattern. In this study, we characterized their isoform expression in a cell line model of metastatic colorectal cancer (SW480 & SW620). These two genes were found to be good prognostic indicators in two cohorts from The Cancer Genome Atlas database. We studied their exon structure using sequence information in the NCBI and ENSEMBL genome databases to amplify and validate six isoforms each for the ADAM12 and MUC4 genes. The differential expression of these isoforms was observed between normal, primary and metastatic colorectal cancer cell lines. RNA-Seq analysis further proved the differential expression of the gene isoforms. The isoforms of MUC4 and ADAM12 were found to change expression levels in response to 5-Fluorouracil (5-FU) treatment in a dose-, time- and cell line-dependent manner. Furthermore, we successfully detected the protein isoforms of ADAM12 and MUC4 in cell lysates, reflecting the differential expression at the protein level. The change in the mRNA and protein expression of MUC4 and ADAM12 in primary and metastatic cells and in response to 5-FU qualifies them to be studied as potential biomarkers. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their potential use as prognostic and/or predictive biomarkers in the PPPM approach towards cancer.

Emerging role of caldesmon in cancer: A potential biomarker for colorectal cancer and other cancers

Colorectal cancer (CRC) is a devastating disease, mainly because of metastasis. As a result, there is a need to better understand the molecular basis of invasion and metastasis and to identify new biomarkers and therapeutic targets to aid in managing these tumors. The actin cytoskeleton and actin-binding proteins are known to play an important role in the process of cancer metastasis because they control and execute essential steps in cell motility and contractility as well as cell division. Caldesmon (CaD) is an actin-binding protein encoded by the CALD1 gene as multiple transcripts that mainly encode two protein isoforms: High-molecular-weight CaD, expressed in smooth muscle, and low-molecular weight CaD (l-CaD), expressed in nonsmooth muscle cells. According to our comprehensive review of the literature, CaD, particularly l-CaD, plays a key role in the development, metastasis, and resistance to chemoradiotherapy in colorectal, breast, and urinary bladder cancers and gliomas, among other malignancies. CaD is involved in many aspects of the carcinogenic hallmarks, including epithelial mesenchymal transition via transforming growth factor-beta signaling, angiogenesis, resistance to hormonal therapy, and immune evasion. Recent data show that CaD is expressed in tumor cells as well as in stromal cells, such as cancer-associated fibroblasts, where it modulates the tumor microenvironment to favor the tumor. Interestingly, CaD undergoes selective tumor-specific splicing, and the resulting isoforms are generally not expressed in normal tissues, making these transcripts ideal targets for drug design. In this review, we will analyze these features of CaD with a focus on CRC and show how the currently available data qualify CaD as a potential candidate for targeted therapy in addition to its role in the diagnosis and prognosis of cancer.

Quantitative immunopeptidomics reveals a tumor stroma-specific target for T cell therapy

T cell receptor (TCR)-based immunotherapy has emerged as a promising therapeutic approach for the treatment of patients with solid cancers. Identifying peptide-human leukocyte antigen (pHLA) complexes highly presented on tumors and rarely expressed on healthy tissue in combination with high-affinity TCRs that when introduced into T cells can redirect T cells to eliminate tumor but not healthy tissue is a key requirement for safe and efficacious TCR-based therapies. To discover promising shared tumor antigens that could be targeted via TCR-based adoptive T cell therapy, we employed population-scale immunopeptidomics using quantitative mass spectrometry across ~1500 tumor and normal tissue samples. We identified an HLA-A*02:01-restricted pan-cancer epitope within the collagen type VI α-3 (COL6A3) gene that is highly presented on tumor stroma across multiple solid cancers due to a tumor-specific alternative splicing event that rarely occurs outside the tumor microenvironment. T cells expressing natural COL6A3-specific TCRs demonstrated only modest activity against cells presenting high copy numbers of COL6A3 pHLAs. One of these TCRs was affinity-enhanced, enabling transduced T cells to specifically eliminate tumors in vivo that expressed similar copy numbers of pHLAs as primary tumor specimens. The enhanced TCR variants exhibited a favorable safety profile with no detectable off-target reactivity, paving the way to initiate clinical trials using COL6A3-specific TCRs to target an array of solid tumors.

Alternative splicing patterns reveal prognostic indicator in muscle-invasive bladder cancer

Background

Bladder cancer is one of the most lethal malignancy in urological system, and 20–25% of bladder cancer patients are muscle invasive with unfavorable prognosis. However, the role of alternative splicing (AS) in muscle-invasive bladder cancer (MIBC) remains to be elucidated.

Methods

Percent spliced in (PSI) data obtained from the Cancer Genome Atlas (TCGA) SpliceSeq database (n = 394) were utilized to evaluate the AS events in MIBC. Prognosis-associated AS events were screened out by univariate Cox regression. LASSO Cox regression was used to identify reliable prognostic patterns in a training set and further validated in a test set. Splicing regulatory networks were constructed by correlations between PSI of AS events and RNA expression of splicing factors.

Results

As a result, a total of 2589 prognosis-related AS events in MIBC were identified. Pathways of spliceosomal complex (FDR = 0.017), DNA-directed RNA polymerase II, core complex (FDR = 0.032), and base excision repair (FDR = 0.038) were observed to be significantly enriched. Additionally, we noticed that most of the prognosis-related AS events were favorable factors. According to the LASSO and multivariate Cox regression analyses, 15-AS-based signature was established with the area under curve (AUC) of 0.709, 0.823, and 0.857 at 1-, 3-, and 5- years, respectively. The MIBC patients were further divided into high- and low-risk groups based on median risk sores. Interestingly, we observed that the prevalence of FGFR3 with mutations and focal amplification was significantly higher in low-risk group. Functional and immune infiltration analysis suggested potential signaling pathways and distinct immune states between these two groups. Moreover, splicing correlation network displayed a regulatory mode of prognostic splicing factors (SF) in MIBC patients.

Conclusions

This study not only provided novel insights into deciphering the possible mechanism of tumorgenesis and pathogenesis but also help refine risk stratification systems and potential treatment of decision-making for MIBC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02685-0.

DJExpress: An Integrated Application for Differential Splicing Analysis and Visualization

RNA-seq analysis of alternative pre-mRNA splicing has facilitated an unprecedented understanding of transcriptome complexity in health and disease. However, despite the availability of countless bioinformatic pipelines for transcriptome-wide splicing analysis, the use of these tools is often limited to expert bioinformaticians. The need for high computational power, combined with computational outputs that are complicated to visualize and interpret present obstacles to the broader research community. Here we introduce DJExpress, an R package for differential expression analysis of transcriptomic features and expression-trait associations. To determine gene-level differential junction usage as well as associations between junction expression and molecular/clinical features, DJExpress uses raw splice junction counts as input data. Importantly, DJExpress runs on an average laptop computer and provides a set of interactive and intuitive visualization formats. In contrast to most existing pipelines, DJExpress can handle both annotated and de novo identified splice junctions, thereby allowing the quantification of novel splice events. Moreover, DJExpress offers a web-compatible graphical interface allowing the analysis of user-provided data as well as the visualization of splice events within our custom database of differential junction expression in cancer (DJEC DB). DJEC DB includes not only healthy and tumor tissue junction expression data from TCGA and GTEx repositories but also cancer cell line data from the DepMap project. The integration of DepMap functional genomics data sets allows association of junction expression with molecular features such as gene dependencies and drug response profiles. This facilitates identification of cancer cell models for specific splicing alterations that can then be used for functional characterization in the lab. Thus, DJExpress represents a powerful and user-friendly tool for exploration of alternative splicing alterations in RNA-seq data, including multi-level data integration of alternative splicing signatures in healthy tissue, tumors and cancer cell lines.

Genetic variants in splicing factor genes and susceptibility to bladder cancer

BACKGROUND

Genome-wide association studies have demonstrated that genetic variants are closely related to tumorigenesis and progression of cancer. However, the correlation between genetic variants in splicing factor genes and bladder cancer susceptibility remains unclear.

METHOD

A case-control study with 580 cases of bladder cancer and 1,101 controls was conducted to explore the association of single-nucleotide polymorphisms (SNPs) in splicing factors with bladder cancer susceptibility by logistic regression models, and multiple testing errors were justified by the false discovery rate (FDR) method. Next, we used the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) datasets to further analyze the differential expression of candidate genes.

RESULTS

We found that rs978416 G>A in RBFOX3 contributed to a reduced risk of bladder cancer [adjusted odds ratio (OR) = 0.72, 95% confidence internal (CI) = 0.62-0.84, P = 3.54 × 10^-5], especially in individuals who never smoked (P = 7.83 × 10^-5). Stratified analysis showed that the protective effect of rs978416 was more significant in the subgroup of low grade and non-muscle invasive bladder cancer. Furthermore, the RBFOX3 mRNA expression was decreased in bladder tumor tissues. However, the relatively high expression of RBFOX3 was related to a higher bladder cancer stage.

CONCLUSIONS

Our findings indicated that SNP rs978416 G>A in RBFOX3 may be related to bladder cancer predisposition in Chinese population and might serve as a novel biomarker for bladder cancer risk.

Immunotherapeutic Significance of a Prognostic Alternative Splicing Signature in Bladder Cancer

Objectives: Bladder cancer is the fourth most common malignancy in men in the United States. Aberrant alternative splicing (AS) events are involved in the carcinogenesis, but the association between AS and bladder cancer remains unclear. This study aimed to construct an AS-based prognostic signature and elucidate the role of the tumor immune microenvironment (TIME) and the response to immunotherapy and chemotherapy in bladder cancer. Methods: Univariate Cox regression analysis was performed to detect prognosis-related AS events. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to build prognostic signatures. Kaplan-Meier survival analysis, multivariate Cox regression analysis, and receiver operating characteristic (ROC) curves were conducted to validate the prognostic signatures. Then, the Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and tumor immune estimation resource (TIMER) databases were searched and the single-sample gene set enrichment analysis (ssGSEA) algorithm and CIBERSORT method were performed to uncover the context of TIME in bladder cancer. The Tumor Immune Dysfunction and Exclusion (TIDE) web tool and pRRophetic algorithm were used to predict the response to immunotherapy and chemotherapy. Finally, we constructed a correlation network between splicing factors (SFs) and survival-related AS events. Results: A total of 4684 AS events were significantly associated with overall survival in patients with bladder cancer. Eight prognostic signatures of bladder cancer were established, and a clinical survival prediction model was built. In addition, the consolidated prognostic signature was closely related to immune infiltration and the response to immunotherapy and chemotherapy. Furthermore, the correlation identified EIF3A, DDX21, SDE2, TNPO1, and RNF40 as hub SFs, and function analysis found ubiquitin-mediated proteolysis is correlated most significantly with survival-associated AS events. Conclusion: Our findings highlight the prognostic value of AS for patients with bladder cancer and reveal pivotal players of AS events in the context of TIME and the response to immunotherapy and chemotherapy, which may be important for patient management and treatment.

Targeting Tumor-Stromal Interactions in Pancreatic Cancer: Impact of Collagens and Mechanical Traits

Pancreatic ductal adenocarcinoma (PDAC) has one of the worst outcomes among cancers with a 5-years survival rate of below 10%. This is a result of late diagnosis and the lack of effective treatments. The tumor is characterized by a highly fibrotic stroma containing distinct cellular components, embedded within an extracellular matrix (ECM). This ECM-abundant tumor microenvironment (TME) in PDAC plays a pivotal role in tumor progression and resistance to treatment. Cancer-associated fibroblasts (CAFs), being a dominant cell type of the stroma, are in fact functionally heterogeneous populations of cells within the TME. Certain subtypes of CAFs are the main producer of the ECM components of the stroma, with the most abundant one being the collagen family of proteins. Collagens are large macromolecules that upon deposition into the ECM form supramolecular fibrillar structures which provide a mechanical framework to the TME. They not only bring structure to the tissue by being the main structural proteins but also contain binding domains that interact with surface receptors on the cancer cells. These interactions can induce various responses in the cancer cells and activate signaling pathways leading to epithelial-to-mesenchymal transition (EMT) and ultimately metastasis. In addition, collagens are one of the main contributors to building up mechanical forces in the tumor. These forces influence the signaling pathways that are involved in cell motility and tumor progression and affect tumor microstructure and tissue stiffness by exerting solid stress and interstitial fluid pressure on the cells. Taken together, the TME is subjected to various types of mechanical forces and interactions that affect tumor progression, metastasis, and drug response. In this review article, we aim to summarize and contextualize the recent knowledge of components of the PDAC stroma, especially the role of different collagens and mechanical traits on tumor progression. We furthermore discuss different experimental models available for studying tumor-stromal interactions and finally discuss potential therapeutic targets within the stroma.

An ensemble machine learning model based on multiple filtering and supervised attribute clustering algorithm for classifying cancer samples

BACKGROUND

Machine learning is one kind of machine intelligence technique that learns from data and detects inherent patterns from large, complex datasets. Due to this capability, machine learning techniques are widely used in medical applications, especially where large-scale genomic and proteomic data are used. Cancer classification based on bio-molecular profiling data is a very important topic for medical applications since it improves the diagnostic accuracy of cancer and enables a successful culmination of cancer treatments. Hence, machine learning techniques are widely used in cancer detection and prognosis.

METHODS

In this article, a new ensemble machine learning classification model named Multiple Filtering and Supervised Attribute Clustering algorithm based Ensemble Classification model (MFSAC-EC) is proposed which can handle class imbalance problem and high dimensionality of microarray datasets. This model first generates a number of bootstrapped datasets from the original training data where the oversampling procedure is applied to handle the class imbalance problem. The proposed MFSAC method is then applied to each of these bootstrapped datasets to generate sub-datasets, each of which contains a subset of the most relevant/informative attributes of the original dataset. The MFSAC method is a feature selection technique combining multiple filters with a new supervised attribute clustering algorithm. Then for every sub-dataset, a base classifier is constructed separately, and finally, the predictive accuracy of these base classifiers is combined using the majority voting technique forming the MFSAC-based ensemble classifier. Also, a number of most informative attributes are selected as important features based on their frequency of occurrence in these sub-datasets.

RESULTS

To assess the performance of the proposed MFSAC-EC model, it is applied on different high-dimensional microarray gene expression datasets for cancer sample classification. The proposed model is compared with well-known existing models to establish its effectiveness with respect to other models. From the experimental results, it has been found that the generalization performance/testing accuracy of the proposed classifier is significantly better compared to other well-known existing models. Apart from that, it has been also found that the proposed model can identify many important attributes/biomarker genes.

CALD1 promotes the expression of PD-L1 in bladder cancer via the JAK/STAT signaling pathway

BACKGROUND

Bladder cancer (BC) is a common malignant neoplasm with a high rate of recurrence and progression, despite optimal treatment. There is a pressing need to identify new effective biomarkers for the targeted treatment of BC.

METHODS

The key gene CALD1 was screened via weighed gene co-expression network analysis (WGCNA) from encoding protein genes of BC. Clinical and prognostic significance was explored in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cell Counting Kit-8 (CCK-8), flow cytometry, transwell chamber experiment and nude mouse xenograft assay were performed to test cell growth, apoptosis, migration, invasion and tumorigenesis capacities. Immune correlation was analyzed in The Tumor Immune Estimation Resource (TIMER) database. Relevant signaling pathways were explored using gene set enrichment analysis (GSEA).

RESULTS

Increased expression of CALD1 was significantly correlated with histological grade, clinical stage, T stage, and lymphatic metastasis. Kaplan-Meier survival curves showed that high CALD1 expression was associated with poor overall survival (OS) and disease-free survival (DFS) in TCGA database, and with poor OS in the four GEO databases. CALD1 promotes growth, migration, invasion, and cell cycle of tumor cell, and inhibits tumor cell apoptosis in vitro and in vivo. CADL1 expression was positively correlated with increased CD274 levels (r=0.357, P=9.71e-14). JAK/STAT signaling pathway was significantly enriched in the high CALD1 expression group. CALD1-mediated PD-L1 overexpression (OE) was via the activation of the JAK/STAT signaling pathway; this effect was blocked by the specific JAK inhibitor Ruxolitinib.

CONCLUSIONS

CALD1 is a potential molecular marker associated with prognosis. It promotes the malignant progression of BC and upregulates the PD-L1 expression via the JAK/STAT signaling pathway.

Transcriptomic analysis of castration, chemo-resistant and metastatic prostate cancer elucidates complex genetic crosstalk leading to disease progression

Prostate adenocarcinoma, with its rising numbers and high fatality rate, is a daunting healthcare challenge to clinicians and researchers alike. The mainstay of our meta-analysis was to decipher differentially expressed genes (DEGs), their corresponding transcription factors (TFs), miRNAs (microRNA) and interacting pathways underlying the progression of prostate cancer (PCa). We have chosen multiple datasets from primary, castration-resistant, chemo-resistant and metastatic prostate cancer stages for investigation. From our tissue-specific and disease-specific co-expression networks, fifteen hub genes such as ACTB, ACTN1, CDH1, CDKN1A, DDX21, ELF3, FLNA, FLNC, IKZF1, ILK, KRT13, KRT18, KRT19, SVIL and TRIM29 were identified and validated by molecular complex detection analysis as well as survival analysis. In our attempt to highlight hub gene-associated mutations and drug interactions, FLNC was found to be most commonly mutated and CDKN1A gene was found to have highest druggability. Moreover, from DAVID and gene set enrichment analysis, the focal adhesion and oestrogen signalling pathways were found enriched which indicates the involvement of hub genes in tumour invasiveness and metastasis. Finally by Enrichr tool and miRNet, we identified transcriptional factors SNAI2, TP63, CEBPB and KLF11 and microRNAs, namely hsa-mir-1-3p, hsa-mir-145-5p, hsa-mir-124-3p and hsa-mir-218-5p significantly controlling the hub gene expressions. In a nutshell, our report will help to gain a deeper insight into complex molecular intricacies and thereby unveil the probable biomarkers and therapeutic targets involved with PCa progression.

Transcript-Level Dysregulation of BCL2 Family Genes in Acute Myeloblastic Leukemia

The expression of apoptosis-related BCL2 family genes, fine-tuned in normal cells, is dysregulated in many neoplasms. In acute myeloid leukemia (AML), this problem has not been studied comprehensively. To address this issue, RNA-seq data were used to analyze the expression of 26 BCL2 family members in 27 AML FAB M1 and M2 patients, divided into subgroups differently responding to chemotherapy. A correlation analysis, analysis of variance, and Kaplan-Meier analysis were applied to associate the expression of particular genes with other gene expression, clinical features, and the presence of mutations detected by exome sequencing. The expression of BCL2 family genes was dysregulated in AML, as compared to healthy controls. An upregulation of anti-apoptotic and downregulation of pro-apoptotic genes was observed, though only a decrease in BMF, BNIP1, and HRK was statistically significant. In a group of patients resistant to chemotherapy, overexpression of BCL2L1 was manifested. In agreement with the literature data, our results reveal that BCL2L1 is one of the key players in apoptosis regulation in different types of tumors. An exome sequencing data analysis indicates that BCL2 family genes are not mutated in AML, but their expression is correlated with the mutational status of other genes, including those recurrently mutated in AML and splicing-related. High levels of some BCL2 family members, in particular BIK and BCL2L13, were associated with poor outcome.

Exploring microRNA target genes and identifying hub genes in bladder cancer based on bioinformatic analysis

BACKGROUND

Bladder cancer (BC) is the second most frequent malignancy of the urinary system. The aim of this study was to identify key microRNAs (miRNAs) and hub genes associated with BC as well as analyse their targeted relationships.

METHODS

According to the microRNA dataset GSE112264 and gene microarray dataset GSE52519, differentially expressed microRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using the R limma software package. The FunRich software database was used to predict the miRNA-targeted genes. The overlapping common genes (OCGs) between miRNA-targeted genes and DEGs were screened to construct the PPI network. Then, gene ontology (GO) analysis was performed through the "cluster Profiler" and "org.Hs.eg.db" R packages. The differential expression analysis and hierarchical clustering of these hub genes were analysed through the GEPIA and UCSC Cancer Genomics Browser databases, respectively. KEGG pathway enrichment analyses of hub genes were performed through gene set enrichment analysis (GSEA).

RESULTS

A total of 12 DEMs and 10 hub genes were identified. Differential expression analysis of the hub genes using the GEPIA database was consistent with the results for the UCSC Cancer Genomics Browser database. The results indicated that these hub genes were oncogenes, but VCL, TPM2, and TPM1 were tumour suppressor genes. The GSEA also showed that hub genes were most enriched in those pathways that were closely associated with tumour proliferation and apoptosis.

CONCLUSIONS

In this study, we built a miRNA-mRNA regulatory targeted network, which explores an understanding of the pathogenesis of cancer development and provides key evidence for novel targeted treatments for BC.

The Function and Prognostic Value of RNA-Binding Proteins in Colorectal Adenocarcinoma Were Analyzed Based on Bioinformatics of Smart Medical Big Data

Colon cancer is the third most frequent cancer in the world and is mainly adenocarcinoma in terms of pathological type. It has been confirmed that the dysregulation of RNA-binding proteins (RBPs) significantly participates in the occurrence and development of numerous malignant tumors. Therefore, we analyzed the RBPs associated with colon adenocarcinoma (COAD) to assess their possible biological effects and prognostic value. A total of 398 COAD tissue datasets and 39 normal tissue datasets were retrieved from the TCGA data resource and screened out the RBPs, which are differentially expressed between tumor tissues and nontumor tissues. Then, bioinformatics analyses based on smart medical big data were conducted on these RBPs. Overall, 181 differentially expressed RBPs were uncovered, consisting of 121 upregulated RBPs and 60 downregulated RBPs. Finally, we selected 7 prognostic-related RBPs with research prospects and constructed a prognostic model according to the median risk score. There were remarkable differences in OS between the high-risk and low-risk groups. In addition, the performance of the prognostic model was evaluated and verified with other COAD patient data in the TCGA database. The results showed that the area under the ROC curve (AUC) for the train group was 0.744 and the one for the test group was 0.661, confirming that the model assesses patients' prognosis to some extent. And based on 7 hub RBPs, we constructed a nomogram as a reference for evaluating the survival rate of COAD patients.

The cancer-associated fibroblasts related gene CALD1 is a prognostic biomarker and correlated with immune infiltration in bladder cancer

BACKGROUND

Stromal components of the tumor microenvironment contribute to bladder cancer progression, and Cancer-Associated Fibroblasts (CAFs) were reported to play an important role. Accumulating pieces of evidence indicate that CAFs participate in the crosstalk with tumor cells and have a complex interaction network with immune components. Further studies on the role of CAFs in the bladder cancer microenvironment and searching for possible specific markers are important for a deeper understanding of CAFs in bladder cancer progression and immunomodulation.

METHODS

In the present study, we examined the abundance of CAFs in the TCGA and GEO datasets using the MCP-COUNTER algorithm. Additionally, the expression of genes related to CAFs was analyzed through the Weighted Gene Co-expression Network Analysis (WGCNA). The CIBERSORT and ESTIMATE algorithms were used to discuss the correlation of the key CAFs-related gene and the tumor microenvironment components. Immunohistochemistry analysis in clinical samples was used to validate the results of bioinformatics analysis.

RESULTS

The results showed that CAFs were closely associated with the progression and prognosis of bladder cancer. WGCNA also revealed that CALD1 was a key CAFs-related gene in bladder cancer. Moreover, further in-depth analysis showed that CALD1 significantly affected the progression and prognosis of bladder cancer. The CIBERSORT and ESTIMATE algorithms demonstrated significant correlations between CALD1 and the tumor microenvironment components, including CAFs, macrophages, T cells, and multiple immune checkpoint related genes. Finally, immunohistochemistry results validated the strong association of CALD1 with CAFs and macrophages.

CONCLUSIONS

In the present study, we confirmed the cancer-promoting roles of CAFs in bladder cancer. Being a key gene associated with CAFs, CALD1 may promote bladder cancer progression by remodeling the tumor microenvironment. The bioinformatics methods, including the CIBERSORT, MCP-COUNTER and ESTIMATE algorithms, may provide important value for studying the tumor microenvironment.

An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer

The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.

Systematic analysis of the function and prognostic value of RNA binding proteins in Colon Adenocarcinoma

Background: Abnormal expression of RNA-binding proteins (RBPs) is closely related to tumorigenesis, progression, and prognosis. This study performed systematic bioinformatic analysis of RBPs abnormally expressed in colon adenocarcinoma (COAD) using the Cancer Genome Atlas (TCGA) database to screen prognostic markers and potential therapeutic targets. Methods: First, the gene expression data from COAD samples were used to screen out differentially expressed RBPs for functional enrichment analysis and to visualize interaction relationships. Second, RBPs that were significantly related to prognosis were screened through univariate and multivariate Cox regression analysis to construct a prognostic model. The prediction performance of the prognostic model was evaluated by survival analysis and receiver operating characteristic (ROC) curve analysis. It addition, it was verified in the test cohort. The Human Protein Atlas (HPA) online database was used to verify the expression levels of RBPs in the prognostic model. Results: The study identified 181 differentially expressed RBPs and analyzed their interaction and functional enrichment, which were mainly related to non-coding RNA processing, ribosome biogenesis, RNA metabolic processes, RNA phosphodiester bond hydrolysis, and alternative mRNA splicing. Five RBPs related to prognosis were used to construct a prognostic model, and its predictive ability was verified by the test cohort. ROC curve analysis showed that the prognostic model had good sensitivity and specificity. Independent prognostic analysis showed that risk scores could be used as independent prognostic factors for COAD. Conclusion: This study constructed a reliable prognostic model by analyzing COAD differentially expressed RBPs, facilitating the screening of COAD prognostic markers and therapeutic targets.

Alterations of RNA splicing patterns in esophagus squamous cell carcinoma

Alternative splicing (AS) is an important biological process for regulating the expression of various isoforms from a single gene and thus to promote proteome diversity. In this study, RNA-seq data from 15 pairs of matched esophageal squamous cell carcinoma (ESCC) and normal tissue samples as well as two cell lines were analyzed. AS events with significant differences were identified between ESCC and matched normal tissues, which were re-annotated to find protein coding genes or non-coding RNAs. A total of 45,439 AS events were found. Of these, 6019 (13.25%) significant differentially AS events were identified. Exon skipping (SE) events occupied the largest proportion of abnormal splicing events. Fifteen differential splicing events with the same trends of ΔΨ values in ESCC tissues, as well in the two cell lines were found. Four pathways and 20 biological processes related to pro-metastasis cell junction and migration were significantly enriched for the differentially spliced genes. The upregulated splicing factor SF3B4, which regulates 92 gene splicing events, could be a potential prognostic factor of ESCC. Differentially spliced genes, including HNRNPC, VCL, ZNF207, KIAA1217, TPM1 and CALD1 are shown with a sashimi plot. These results suggest that cell junction- and migration-related biological processes are influenced by AS abnormalities, and aberrant splicing events can be affected by splicing factor expression changes. The involved splicing factor SF3B4 was found to be a survival-related gene in ESCC and is presumed to regulate AS in multiple cancers. In summary, we identified significant differentially expressed AS events which may be related to the development of ESCC.

Construction and prognostic analysis of miRNA-mRNA regulatory network in liver metastasis from colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common cancers in the world, and liver metastasis is the leading cause of colorectal cancer-related deaths. However, the mechanism of liver metastasis in CRC has not been clearly elucidated.

Methods

Three datasets from the Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEGs), which were subjected to functional enrichment analysis and protein-protein interaction analysis. Subsequently, mRNA-miRNA network was constructed, and the associated DEGs and DEMs were performed for prognostic analysis. Finally, we did infiltration analysis of growth arrest specific 1 (GAS1)-associated immune cells.

Results

We obtained 325 DEGs and 9 differentially expressed miRNAs (DEMs) between primary CRC and liver metastases. Enrichment analysis and protein-protein interactions (PPI) further revealed the involvement of DEGs in the formation of the inflammatory microenvironment and epithelial-mesenchymal transition (EMT) during the liver metastases process in CRC. Survival analysis demonstrated that low-expressed GAS1 as well as low-expressed hsa-miR-33b-5p was a favorable prognostic indicator of overall survival. Further exploration of GAS1 revealed that its expression was interrelated with the infiltration of immune cells in tumor tissues.

Conclusions

In summary, DEGs, DEMs, and their interactions found in liver metastasis of CRC may provide a basis for further understanding of the mechanism of CRC metastasis.

Profiles of alternative splicing landscape in breast cancer and their clinical significance: an integrative analysis based on large-sequencing data

Background

Alternative splicing (AS) is closely correlated with the initiation and progression of carcinoma. The systematic analysis of its biological and clinical significance in breast cancer (BRCA) is, however, lacking.

Methods

Clinical data and RNA-seq were obtained from the TCGA dataset and differentially expressed AS (DEAS) events between tumor and paired normal BRCA tissues were identified. Enrichment analysis was then used to reveal the potential biological functions of DEAS events. We performed protein-protein interaction (PPI) analysis of DEAS events by using STRING and the correlation network between splicing factors (SFs) and AS events was constructed. The LASSO Cox model, Kaplan-Meier and log-rank tests were used to construct and evaluate DEAS-related risk signature, and the association between DEAS events and clinicopathological features were then analyzed.

Results

After strict filtering, 35,367 AS events and 973 DEAS events were detected. DEAS corresponding genes were significantly enriched in pivotal pathways including cell adhesion, cytoskeleton organization, and extracellular matrix organization. A total of 103 DEAS events were correlated with disease free survival. The DEAS-related risk signature stratified BRCA patients into two groups and the area under curve (AUC) was 0.754. Moreover, patients in the high-risk group had enriched basel-like subtype, advanced clinical stages, proliferation, and metastasis potency.

Conclusions

Collectively, the profile of DEAS landscape in BRCA revealed the potential biological function and prognostic value of DEAS events.

A Roadmap Toward the Definition of Actionable Tumor-Specific Antigens

The search for tumor-specific antigens (TSAs) has considerably accelerated during the past decade due to the improvement of proteogenomic detection methods. This provides new opportunities for the development of novel antitumoral immunotherapies to mount an efficient T cell response against one or multiple types of tumors. While the identification of mutated antigens originating from coding exons has provided relatively few TSA candidates, the possibility of enlarging the repertoire of targetable TSAs by looking at antigens arising from non-canonical open reading frames opens up interesting avenues for cancer immunotherapy. In this review, we outline the potential sources of TSAs and the mechanisms responsible for their expression strictly in cancer cells. In line with the heterogeneity of cancer, we propose that discrete families of TSAs may be enriched in specific cancer types.

Integrated analysis of RNA-binding proteins in human colorectal cancer

Background

Although RNA-binding proteins play an essential role in a variety of different tumours, there are still limited efforts made to systematically analyse the role of RNA-binding proteins (RBPs) in the survival of colorectal cancer (CRC) patients.

Methods

Analysis of CRC transcriptome data collected from the TCGA database was conducted, and RBPs were extracted from CRC. R software was applied to analyse the differentially expressed genes (DEGs) of RBPs. To identify related pathways and perform functional annotation of RBP DEGs, Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out using the database for annotation, visualization and integrated discovery. Protein-protein interactions (PPIs) of these DEGs were analysed based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized by Cytoscape software. Based on the Cox regression analysis of the prognostic value of RBPs (from the PPI network) with survival time, the RBPs related to survival were identified, and a prognostic model was constructed. To verify the model, the data stored in the TCGA database were designated as the training set, while the chip data obtained from the GEO database were treated as the test set. Then, both survival analysis and ROC curve verification were conducted. Finally, the risk curves and nomograms of the two groups were generated to predict the survival period.

Results

Among RBP DEGs, 314 genes were upregulated while 155 were downregulated, of which twelve RBPs (NOP14, MRPS23, MAK16, TDRD6, POP1, TDRD5, TDRD7, PPARGC1A, LIN28B, CELF4, LRRFIP2, MSI2) with prognostic value were obtained.

Conclusions

The twelve identified genes may be promising predictors of CRC and play an essential role in the pathogenesis of CRC. However, further investigation of the underlying mechanism is needed.

COL6A3 promotes cellular malignancy of osteosarcoma by activating the PI3K/AKT pathway

OBJECTIVE In this study, we aimed to investigate the role of COL6A3 on cell motility and the PI3K/AKT signaling pathway in osteosarcoma. METHODS The relative expression of COL6A3 was achieved from a GEO dataset in osteosarcoma tissue. siRNA technology was applied to decrease the COL6A3 expression in cells, and cell counting kit-8 (CCK-8) assay and colony formation analysis were used to examine the cell proliferation potential. Knockdown COL6A3 made the proliferation and colony formation abilities worse than the COL6A3 without interference. Likewise, in contrast to the si-con group, cell invasion and migration were inhibited in the si-COL6A3 group. Moreover, the western blot results suggested that the PI3K/AKT signaling pathway was manipulated by measuring the protein expression of the PI3K/AKT pathway-related markers, due to the COL6A3 inhibition. CONCLUSION COL6A3 plays a crucial role in modulating various aspects of the progression of osteosarcoma, which would provide a potentially effective treatment for osteosarcoma.

The Biological Role of the Collagen Alpha-3 (VI) Chain and Its Cleaved C5 Domain Fragment Endotrophin in Cancer

The collagen alpha-3 (VI) chain encoded by the gene COL6A3 is one of the 3 subunits of collagen VI which is a microfibrillar component of the extracellular matrix and is essential for the stable assembly process of collagen VI. The collagen alpha-3 (VI) chain and the cleaved C5 domain fragment, called endotrophin, are highly expressed in a variety of cancers and play a crucial role in cancer progression. The biological functions of endotrophin in tumors can be driven by adipocytes. Studies have demonstrated that endotrophin can directly affect the malignancy of cancer cells through TGF-β-dependent mechanisms, inducing epithelial–mesenchymal transition and fibrosis of the tumor microenvironment. In addition, endotrophin can also recruit macrophages and endothelial cells through chemotaxis to regulate the tumor microenvironment and ultimately promote tumor inflammation and angiogenesis. Furthermore, COL6A3 and endotrophin serve as novel diagnostic and prognostic biomarkers in cancer and contribute to clinical therapeutic applications in the future. In summary, in this review, we discuss the importance of the collagen alpha-3 (VI) chain and endotrophin in cancer progression, the future clinical applications of endotrophin and the remaining challenges in this field.

Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

BACKGROUND

Alternative splicing (AS) is an important mechanism of regulating eukaryotic gene expression. Understanding the most common AS events in colorectal cancer (CRC) will help developing diagnostic, prognostic or therapeutic tools in CRC.

METHODS

Publicly available RNA-seq data of 28 pairs of CRC and normal tissues and 18 pairs of metastatic and normal tissues were used to identify AS events using PSI and DEXSeq methods.

RESULT

The highly significant splicing events were used to search a database of The Cancer Genome Atlas (TCGA). We identified AS events in 9 genes in CRC (more inclusion of CLK1-E4, COL6A3-E6, CD44v8-10, alternative first exon regulation of ARHGEF9, CHEK1, HKDC1 and HNF4A) or metastasis (decrease of SERPINA1-E1a, CALD-E5b, E6). Except for CHEK1, all other 8 splicing events were confirmed by TCGA data with 382 CRC tumors and 51 normal controls. The combination of three splicing events was used to build a logistic regression model that can predict sample type (CRC or normal) with near perfect performance (AUC = 1). Two splicing events (COL6A3 and HKDC1) were found to be significantly associated with patient overall survival. The AS features of the 9 genes are highly consistent with previous reports and/or relevant to cancer biology.

CONCLUSIONS

The significant association of higher expression of the COL6A3 E5-E6 junction and HKDC1 E1-E2 with better overall survival was firstly reported. This study might be of significant value in the future biomarker, prognosis marker and therapeutics development of CRC.

Right and left-sided colon cancers - specificity of molecular mechanisms in tumorigenesis and progression

Background

Given the differences in embryonic origin, vascular and nervous supplies, microbiotic burden, and main physiological functions of left and right colons, tumor location is increasingly suggested to dictate tumor behavior affecting pathology, progression and prognosis. Right-sided colon cancers arise in the cecum, ascending colon, hepatic flexure and/or transverse colon, while left-sided colon cancers arise in the splenic flexure, descending, and/or sigmoid colon. In contrast to prior reports, we attempt to delineate programs of tumorigenesis independently for each side.

Methods

Four hundred and eleven samples were extracted from The Cancer Genome Atlas-COAD cohort, based on a conservative sample inclusion criterion. Each side was independently analyzed with respect to their respective normal tissue, at the level of transcription, post-transcription, miRNA control and methylation in both a stage specific and stage-agnostic manner.

Results

Our results indicate a suppression of enzymes involved in various stages of carcinogen breakdown including CYP2C8, CYP4F12, GSTA1, and UGT1A within right colon tumors. This implies its reduced capacity to detoxify carcinogens, contributing to a genotoxic tumor environment, and subsequently a more aggressive phenotype. Additionally, we highlight a crucial nexus between calcium homeostasis (sensing, mobilization and absorption) and immune/GPCR signaling within left-sided tumors, possibly contributing to its reduced proliferative and metastatic potential. Interestingly, two genes SLC6A4 and HOXB13 show opposing regulatory trends within right and left tumors. Post-transcriptional regulation mediated by both RNA-binding proteins (e.g. NKRF (in left) and MSI2 (in right)) and miRNAs (e.g. miR-29a (in left); miR-155, miR181-d, miR-576 and miR23a (in right)) appear to exhibit side-specificity in control of their target transcripts and is pronounced in right colon tumors. Additionally, methylation results depict location-specific differences, with increased hypomethylation in open seas within left tumors, and increased hypermethylation of CpG islands within right tumors.

Conclusions

Differences in molecular mechanisms captured here highlight distinctions in tumorigenesis and progression between left and right colon tumors, which will serve as the basis for future studies, influencing the efficacies of existing and future diagnostic, prognostic and therapeutic interventions.

Expression Changes Confirm Genomic Variants Predicted to Result in Allele-Specific, Alternative mRNA Splicing

Splice isoform structure and abundance can be affected by either noncoding or masquerading coding variants that alter the structure or abundance of transcripts. When these variants are common in the population, these nonconstitutive transcripts are sufficiently frequent so as to resemble naturally occurring, alternative mRNA splicing. Prediction of the effects of such variants has been shown to be accurate using information theory-based methods. Single nucleotide polymorphisms (SNPs) predicted to significantly alter natural and/or cryptic splice site strength were shown to affect gene expression. Splicing changes for known SNP genotypes were confirmed in HapMap lymphoblastoid cell lines with gene expression microarrays and custom designed q-RT-PCR or TaqMan assays. The majority of these SNPs (15 of 22) as well as an independent set of 24 variants were then subjected to RNAseq analysis using the ValidSpliceMut web beacon (http://validsplicemut.cytognomix.com), which is based on data from the Cancer Genome Atlas and International Cancer Genome Consortium. SNPs from different genes analyzed with gene expression microarray and q-RT-PCR exhibited significant changes in affected splice site use. Thirteen SNPs directly affected exon inclusion and 10 altered cryptic site use. Homozygous SNP genotypes resulting in stronger splice sites exhibited higher levels of processed mRNA than alleles associated with weaker sites. Four SNPs exhibited variable expression among individuals with the same genotypes, masking statistically significant expression differences between alleles. Genome-wide information theory and expression analyses (RNAseq) in tumor exomes and genomes confirmed splicing effects for 7 of the HapMap SNP and 14 SNPs identified from tumor genomes. q-RT-PCR resolved rare splice isoforms with read abundance too low for statistical significance in ValidSpliceMut. Nevertheless, the web-beacon provides evidence of unanticipated splicing outcomes, for example, intron retention due to compromised recognition of constitutive splice sites. Thus, ValidSpliceMut and q-RT-PCR represent complementary resources for identification of allele-specific, alternative splicing.

A functional network of gastric-cancer-associated splicing events controlled by dysregulated splicing factors

Comprehensive understanding of aberrant splicing in gastric cancer is lacking. We RNA-sequenced 19 gastric tumor–normal pairs and identified 118 high-confidence tumor-associated (TA) alternative splicing events (ASEs) based on high-coverage sequencing and stringent filtering, and also identified 8 differentially expressed splicing factors (SFs). The TA ASEs occurred in genes primarily involved in cytoskeletal organization. We constructed a correlative network between TA ASE splicing ratios and SF expression, replicated it in independent gastric cancer data from The Cancer Genome Atlas and experimentally validated it by knockdown of the nodal SFs (PTBP1, ESRP2 and MBNL1). Each SF knockdown drove splicing alterations in several corresponding TA ASEs and led to alterations in cellular migration consistent with the role of TA ASEs in cytoskeletal organization. We have therefore established a robust network of dysregulated splicing associated with tumor invasion in gastric cancer. Our work is a resource for identifying oncogenic splice forms, SFs and splicing-generated tumor antigens as biomarkers and therapeutic targets.

Pathway-guided analysis identifies Myc-dependent alternative pre-mRNA splicing in aggressive prostate cancers

We sought to define the landscape of alternative pre-mRNA splicing in prostate cancers and the relationship of exon choice to known cancer driver alterations. To do so, we compiled a metadataset composed of 876 RNA-sequencing (RNA-Seq) samples from five publicly available sources representing a range of prostate phenotypes from normal tissue to drug-resistant metastases. We subjected these samples to exon-level analysis with rMATS-turbo, purpose-built software designed for large-scale analyses of splicing, and identified 13,149 high-confidence cassette exon events with variable incorporation across samples. We then developed a computational framework, pathway enrichment-guided activity study of alternative splicing (PEGASAS), to correlate transcriptional signatures of 50 different cancer driver pathways with these alternative splicing events. We discovered that Myc signaling was correlated with incorporation of a set of 1,039 cassette exons enriched in genes encoding RNA binding proteins. Using a human prostate epithelial transformation assay, we confirmed the Myc regulation of 147 of these exons, many of which introduced frameshifts or encoded premature stop codons. Our results connect changes in alternative pre-mRNA splicing to oncogenic alterations common in prostate and many other cancers. We also establish a role for Myc in regulating RNA splicing by controlling the incorporation of nonsense-mediated decay-determinant exons in genes encoding RNA binding proteins.

Identification of Key Biomarkers in Bladder Cancer: Evidence from a Bioinformatics Analysis

Bladder cancer (BCa) is one of the most common malignancies and has a relatively poor outcome worldwide. However, the molecular mechanisms and processes of BCa development and progression remain poorly understood. Therefore, the present study aimed to identify candidate genes in the carcinogenesis and progression of BCa. Five GEO datasets and TCGA-BLCA datasets were analyzed by statistical software R, FUNRICH, Cytoscape, and online instruments to identify differentially expressed genes (DEGs), to construct protein‒protein interaction networks (PPIs) and perform functional enrichment analysis and survival analyses. In total, we found 418 DEGs. We found 14 hub genes, and gene ontology (GO) analysis revealed DEG enrichment in networks and pathways related to cell cycle and proliferation, but also in cell movement, receptor signaling, and viral carcinogenesis. Compared with noncancerous tissues, TPM1, CRYAB, and CASQ2 were significantly downregulated in BCa, and the other hub genes were significant upregulated. Furthermore, MAD2L1 and CASQ2 potentially play a pivotal role in lymph nodal metastasis. CRYAB and CASQ2 were both significantly correlated with overall survival (OS) and disease-free survival (DFS). The present study highlights an up to now unrecognized possible role of CASQ2 in cancer (BCa). Furthermore, CRYAB has never been described in BCa, but our study suggests that it may also be a candidate biomarker in BCa.

A novel metadherinΔ7 splice variant enhances triple negative breast cancer aggressiveness by modulating mitochondrial function via NFĸB-SIRT3 axis

Metadherin (MTDH) expression inversely correlates with prognosis of several cancers including mammary carcinomas. In this work, we identified a novel splice variant of MTDH with exon7 skipping (MTDHΔ7) and its levels were found significantly high in triple negative breast cancer (TNBC) cells and in patients diagnosed with TNBC. Selective overexpression of MTDHΔ7 in MDA-MB-231 and BT-549 cells enhanced proliferation, invasion, and epithelial-to-mesenchymal (EMT) transition markers in comparison to its wildtype counterpart. In contrast, knockdown of MTDHΔ7 induced antiproliferative/antiinvasive effects. Mechanistically, MTDH-NFĸB-p65 complex activated SIRT3 transcription by binding to its promoter that in turn enhanced MnSOD levels and promoted EMT in TNBC cells. Intriguingly, mitochondrial OCR through Complex-I and -IV, and glycolytic rate (ECAR) were significantly high in MDA-MB-231 cells stably expressing MTDHΔ7. While depletion of SIRT3 inhibited MTDH-Wt/Δ7-induced OCR and ECAR, knockdown of MnSOD inhibited only ECAR. In addition, MTDH-Wt/Δ7-mediated pro-proliferative/-invasive effects were greatly obviated with either siSIRT3 or siMnSOD in these cells. The functional relevance of MTDHΔ7 was further proved under in vivo conditions in an orthotopic mouse model of breast cancer. Mice bearing labeled MDA-MB-231 cells stably expressing MTDHΔ7 showed significantly more tumor growth and metastatic ability to various organs in comparison to MTDH-Wt bearing mice. Taken together, MTDHΔ7 promotes TNBC aggressiveness through enhanced mitochondrial biogenesis/function, which perhaps serves as a biomarker.

Gene Selection for the Discrimination of Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Cancer discrimination is a typical application of gene expression analysis using a microarray technique. However, microarray data suffer from the curse of dimensionality and usual imbalanced class distribution between the majority (tumor samples) and minority (normal samples) classes. Feature gene selection is necessary and important for cancer discrimination.

OBJECTIVES

To select feature genes for the discrimination of CRC.

METHODS

We improve the feature selection algorithm based on differential evolution, DEFSw by using RUSBoost classifier and weight accuracy instead of the common classifier and evaluation measure for selecting feature genes from imbalance data. We firstly extract differently expressed genes (DEGs) from the CRC dataset of the TCGA and then select the feature genes from the DEGs using the improved DEFSw algorithm. Finally, we validate the selected feature gene sets using independent datasets and retrieve the cancer related information for these genes based on text mining through the Coremine Medical online database.

RESULTS

We select out 16 single-gene feature sets for colorectal cancer discrimination and 19 single-gene feature sets only for colon cancer discrimination.

CONCLUSIONS

In summary, we find a series of high potential candidate biomarkers or signatures, which can discriminate either or both of colon cancer and rectal cancer with high sensitivity and specificity.

Improved detection of prostate cancer using a magneto-nanosensor assay for serum circulating autoantibodies

Purpose

To develop a magneto-nanosensor (MNS) based multiplex assay to measure protein and autoantibody biomarkers from human serum for prostate cancer (CaP) diagnosis.

Materials and methods

A 4-panel MNS autoantibody assay and a MNS protein assay were developed and optimized in our labs. Using these assays, serum concentration of six biomarkers including prostate-specific antigen (PSA) protein, free/total PSA ratio, as well as four autoantibodies against Parkinson disease 7 (PARK7), TAR DNA-binding protein 43 (TARDBP), Talin 1 (TLN1), and Caldesmon 1 (CALD1) and were analyzed. Human serum samples from 99 patients (50 with non-cancer and 49 with clinically localized CaP) were evaluated.

Results

The MNS assay showed excellent performance characteristics and no cross-reactivity. All autoantibody assays showed a statistically significant difference between CaP and non-cancer samples except for PARK7. The most significant difference was the combination of the four autoantibodies as a panel in addition to the free/total PSA ratio. This combination had the highest area under the curve (AUC)– 0.916 in ROC analysis.

Conclusions

Our results suggest that this autoantibody panel along with PSA and free PSA have potential to segregate patients without cancer from those with prostate cancer with higher sensitivity and specificity than PSA alone.

2,3,7,8-Tetrachlorodibenzo-p-dioxin modifies alternative splicing in mouse liver

Alternative splicing is a co-transcriptional mechanism that generates protein diversity by including or excluding exons in different combinations, thereby expanding the diversity of protein isoforms of a single gene. Abnormalities in this process can result in deleterious effects to human health, and several xenobiotics are known to interfere with splicing regulation through multiple mechanisms. These changes could lead to human diseases such as cancer, neurological disorders, autoimmune diseases, and developmental disorders. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is an environmental contaminant generated as a byproduct of various industrial activities. Exposure to this dioxin has been linked to a wide range of pathologies through the alteration of multiple cellular processes. However, the effects of TCDD exposure on alternative splicing have not yet been studied. Here, we investigated whether a single po. dose of 5 μg/kg or 500 μg/kg TCDD influence hepatic alternative splicing in adult male C57BL/6Kou mouse. We identified several genes whose alternative splicing of precursor messenger RNAs was modified following TCDD exposure. In particular, we demonstrated that alternative splicing of Cyp1a1, Ahrr, and Actn1 was significantly altered after TCDD treatment. These findings show that the exposure to TCDD has an impact on alternative-splicing, and suggest a new avenue for understanding TCDD-mediated toxicity and pathogenesis.

A bioinformatic analysis identifies circadian expression of splicing factors and time-dependent alternative splicing events in the HD-MY-Z cell line

The circadian clock regulates key cellular processes and its dysregulation is associated to several pathologies including cancer. Although the transcriptional regulation of gene expression by the clock machinery is well described, the role of the clock in the regulation of post-transcriptional processes, including splicing, remains poorly understood. In the present work, we investigated the putative interplay between the circadian clock and splicing in a cancer context. For this, we applied a computational pipeline to identify oscillating genes and alternatively spliced transcripts in time-course high-throughput data sets from normal cells and tissues, and cancer cell lines. We investigated the temporal phenotype of clock-controlled genes and splicing factors, and evaluated their impact in alternative splice patterns in the Hodgkin Lymphoma cell line HD-MY-Z. Our data points to a connection between clock-controlled genes and splicing factors, which correlates with temporal alternative splicing in several genes in the HD-MY-Z cell line. These include the genes DPYD, SS18, VIPR1 and IRF4, involved in metabolism, cell cycle, apoptosis and proliferation. Our results highlight a role for the clock as a temporal regulator of alternative splicing, which may impact malignancy in this cellular model.

Gene Expression Analyses in Non Muscle Invasive Bladder Cancer Reveals a Role for Alternative Splicing and Tp53 Status

Non-muscle invasive bladder cancer (NMIBC) represents a crucial problem for the national health care systems due to its high rates of recurrence and the consequent need of frequent follow-ups. Here, gene expression analyses in patients diagnosed as NMIBC were performed to determine those molecular pathways involved in tumor initiation, finding that both MYC and E2F are up regulated and helps to tumor initiation and progression. Our results also support an important involvement of alternative splicing events, modifying key pathways to favour bladder tumor evolution. Finally, since MDM2 showed differential exon usage, mutations in TP53 and its protein expression have been also studied in the same patients. Our data support that recurrence is epigenetically mediated and favoured by an increase protein expression of TP53, which appears more frequently mutated in advanced stages and grades, being associated to a worse prognosis. Therefore, TP53 mutational status could be used as a potential biomarker in the first stages of NMIBC to predict recurrence and prognosis.

Discovery of plasma messenger RNA as novel biomarker for gastric cancer identified through bioinformatics analysis and clinical validation

Background

Gastric cancer (GC) is the third leading cause of cancer-related death worldwide, partially due to the lack of effective screening strategies. Thus, there is a stringent need for non-invasive biomarkers to improve patient diagnostic efficiency in GC.

Methods

This study initially filtered messenger RNAs (mRNAs) as prospective biomarkers through bioinformatics analysis. Clinical validation was conducted using circulating mRNA in plasma from patients with GC. Relationships between expression levels of target genes and clinicopathological characteristics were calculated. Then, associations of these selected biomarkers with overall survival (OS) were analyzed using the Kaplan-Meier plotter online tool.

Results

Based on a comprehensive analysis of transcriptional expression profiles across 5 microarrays, top 3 over- and underexpressed mRNAs in GC were generated. Compared with normal controls, expression levels of collagen type VI alpha 3 chain (COL6A3), serpin family H member 1 (SERPINH1) and pleckstrin homology and RhoGEF domain containing G1 (PLEKHG1) were significantly upregulated in GC plasmas. Receiver-operating characteristic (ROC) curves on the diagnostic efficacy of plasma COL6A3, SERPINH1 and PLEKHG1 mRNAs in GC showed that the area under the ROC (AUC) was 0.720, 0.698 and 0.833, respectively. Combined, these three biomarkers showed an elevated AUC of 0.907. Interestingly, the higher COL6A3 level was significantly correlated with lymph node metastasis and poor prognosis in GC patients. High level of SERPINH1 mRNA expression was correlated with advanced age, poor differentiation, lower OS, and PLEKHG1 was also associated with poor OS in GC patients.

Conclusion

Our results suggested that circulating COL6A3, SERPINH1 and PLEKHG1 mRNAs could be putative noninvasive biomarkers for GC diagnosis and prognosis.

Alternative splicing events during adipogenesis from hMSCs

Adipogenesis, the developmental process of progenitor-cell differentiating into adipocytes, leads to fat metabolic disorders. Alternative splicing (AS), a ubiquitous regulatory mechanism of gene expression, allows the generation of more than one unique messenger RNA (mRNA) species from a single gene. Till now, alternative splicing events during adipogenesis from human mesenchymal stem cells (hMSCs) are not yet fully elucidated. We performed RNA-Seq coupled with bioinformatics analysis to identify the differentially expressed AS genes and events during adipogenesis from hMSCs. A global survey separately identified 1262, 1181, 1167, and 1227 ASE involved in the most common types of AS including cassette exon, alt3, and alt5, especially with cassette exon the most prevalent, at 7, 14, 21, and 28 days during adipogenesis. Interestingly, 122 differentially expressed ASE referred to 118 genes, and the three genes including ACTN1 (alt3 and cassette), LRP1 (alt3 and alt5), and LTBP4 (cassette, cassette_multi, and unknown), appeared in multiple AS types of ASE during adipogenesis. Except for all the identified ASE of LRP1 occurred in the extracellular topological domain, alt3 (84) in transmembrane domain significantly differentially expressed was the potential key event during adipogenesis. Overall, we have, for the first time, conducted the global transcriptional profiling during adipogenesis of hMSCs to identify differentially expressed ASE and ASE-related genes. This finding would provide extensive ASE as the regulator of adipogenesis and the potential targets for future molecular research into adipogenesis-related metabolic disorders.

Vinculin promotes gastric cancer proliferation and migration and predicts poor prognosis in patients with gastric cancer

Vinculin is a highly conserved protein involved in cell proliferation, migration, and adhesion. However, the effects of vinculin on gastric cancer (GC) remain unclear. Therefore, we aimed to explore the functional role of vinculin in GC, as well as its underlying mechanism. Expression of vinculin in patients with GC was analyzed by real-time polymerase chain reaction, Western blot analysis, and immunohistochemistry. Overall survival was evaluated by the Kaplan-Meier method with the log-rank test. The relationship between vinculin and clinicopathological characteristics of patients with GC was further identified. In addition, we assessed the expression of vinculin in GC cell lines. Besides, vinculin was suppressed or overexpressed by transfection with small interfering (si-vinculin) or pcDNA-vinculin and then cell viability, cell apoptosis, and/or migration was respectively examined by the 3-(4, 5-dimethylthiazole-2-yl)-2, 5-biphenyl tetrazolium bromide assay, flow cytometer, and scratch assay, respectively. Moreover, the cell cycle- and apoptosis-related proteins were detected by Western blot analysis. The expression of vinculin was significantly increased in the GC tissues and cells compared with the nontumor tissues or cells. Vinculin protein positive staining was mainly located in the cell membrane and cytoplasm. Moreover, vinculin was significantly associated with Tumor Node Metastasis (TNM) and poor differentiation. Patients with high vinculin levels had significantly worse overall survival than those with low levels. Suppression of vinculin significantly decreased cell viability and migration and promoted cell apoptosis. However, overexpression of vinculin statistically increased cell viability but had no effects on cell apoptosis. Vinculin promotes GC proliferation and migration and predicts poor prognosis in patients with GC.

Temporal Splicing Switches in Elements of the TNF-Pathway Identified by Computational Analysis of Transcriptome Data for Human Cell Lines

Alternative splicing plays an important role in numerous cellular processes and aberrant splice decisions are associated with cancer. Although some studies point to a regulation of alternative splicing and its effector mechanisms in a time-dependent manner, the extent and consequences of such a regulation remains poorly understood. In the present work, we investigated the time-dependent production of isoforms in two Hodgkin lymphoma cell lines of different progression stages (HD-MY-Z, stage IIIb and L-1236, stage IV) compared to a B lymphoblastoid cell line (LCL-HO) with a focus on tumour necrosis factor (TNF) pathway-related elements. For this, we used newly generated time-course RNA-sequencing data from the mentioned cell lines and applied a computational pipeline to identify genes with isoform-switching behaviour in time. We analysed the temporal profiles of the identified events and evaluated in detail the potential functional implications of alterations in isoform expression for the selected top-switching genes. Our data indicate that elements within the TNF pathway undergo a time-dependent variation in isoform production with a putative impact on cell migration, proliferation and apoptosis. These include the genes TRAF1, TNFRSF12A and NFKB2. Our results point to a role of temporal alternative splicing in isoform production, which may alter the outcome of the TNF pathway and impact on tumorigenesis.

Tropomyosins: Potential Biomarkers for Urothelial Bladder Cancer

Despite the incidence and prevalence of urothelial bladder cancer (UBC), few advances in treatment and diagnosis have been made in recent years. In this review, we discuss potential biomarker candidates: the tropomyosin family of genes, encoded by four loci in the human genome. The expression of these genes is tissue-specific. Tropomyosins are responsible for diverse cellular roles, most notably based upon their interplay with actin to maintain cellular processes, integrity and structure. Tropomyosins exhibit a large variety of splice forms, and altered isoform expression levels have been associated with cancer, including UBC. Notably, tropomyosin isoforms are detectable in urine, offering the potential for non-invasive diagnosis and risk-stratification. This review collates the basic knowledge on tropomyosin and its isoforms, and discusses their relationships with cancer-related phenomena, most specifically in UBC.

CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis

BACKGROUND

Bladder cancer (BC) is one of the most common malignant neoplasms in the genitourinary tract. We employed the GSE13507 data set from the Gene Expression Omnibus (GEO) database in order to identify key genes related to tumorigenesis, progression, and prognosis in BC patients.

METHODS

The data set used in this study included 10 normal bladder mucosae tissue samples and 165 primary BC tissue samples. Differentially expressed genes (DEGs) in the 2 types of samples were identified by GEO2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the online website DAVID. The online website STRING was used to construct a protein-protein interaction network. Moreover, the plugins in MCODE and cytoHubba in Cytoscape were employed to find the hub genes and modules in these DEGs.

RESULTS

We identified 154 DEGs comprising 135 downregulated genes and 19 upregulated genes. The GO enrichment results were mainly related to the contractile fiber part, extracellular region part, actin cytoskeleton, and extracellular region. The KEGG pathway enrichment results mainly comprised type I diabetes mellitus, asthma, systemic lupus erythematosus, and allograft rejection. A module was identified from the protein-protein interaction network. In total, 15 hub genes were selected and 3 of them comprising CALD1, CNN1, and TAGLN were associated with both overall survival and disease-free survival.

CONCLUSION

CALD1, CNN1, and TAGLN may be potential biomarkers for diagnosis as well as therapeutic targets in BC patients.

Colorectal cancer vaccines: Tumor-associated antigens vs neoantigens

Therapeutic options for the treatment of colorectal cancer (CRC) are diverse but still not always satisfying. Recent success of immune checkpoint inhibition treatment for the subgroup of CRC patients suffering from hyper-mutated tumors suggests a permanent role of immune therapy in the clinical management of CRC. Substantial improvement in treatment outcome could be achieved by development of efficient patient-individual CRC vaccination strategies. This mini-review summarizes the current knowledge on the two general classes of targets: tumor-associated antigens (TAAs) and tumor-specific antigens. TAAs like carcinoembryonic antigen and melanoma associated antigen are present in and shared by a subgroup of patients and a variety of clinical studies examined the efficacy of different TAA-derived peptide vaccines. Combinations of several TAAs as the next step and the development of personalized TAA-based peptide vaccines are discussed. Improvements of peptide-based vaccines achievable by adjuvants and immune-stimulatory chemotherapeutics are highlighted. Finally, we sum up clinical studies using tumor-specific antigens - in CRC almost exclusively neoantigens - which revealed promising results; particularly no severe adverse events were reported so far. Critical progress for clinical outcomes can be expected by individualizing neoantigen-based peptide vaccines and combining them with immune-stimulatory chemotherapeutics and immune checkpoint inhibitors. In light of these data and latest developments, truly personalized neoantigen-based peptide vaccines can be expected to fulfill modern precision medicine's requirements and will manifest as treatment pillar for routine clinical management of CRC.