Use of artificial intelligence for the prediction of lymph node metastases in early-stage colorectal cancer: systematic review.

BACKGROUND: Risk evaluation of lymph node metastasis for early-stage (T1 and T2) colorectal cancers is critical for determining therapeutic strategies. Traditional methods of lymph node metastasis prediction have limited accuracy. This systematic review aimed to review the potential of artificial intelligence in predicting lymph node metastasis in early-stage colorectal cancers. METHODS: A comprehensive search was performed of papers that evaluated the potential of artificial intelligence in predicting lymph node metastasis in early-stage colorectal cancers. Studies were appraised using the Joanna Briggs Institute tools. The primary outcome was summarizing artificial intelligence models and their accuracy. Secondary outcomes included influential variables and strategies to address challenges. RESULTS: Of 3190 screened manuscripts, 11 were included, involving 8648 patients from 1996 to 2023. Due to diverse artificial intelligence models and varied metrics, no data synthesis was performed. Models included random forest algorithms, support vector machine, deep learning, artificial neural network, convolutional neural network and least absolute shrinkage and selection operator regression. Artificial intelligence models' area under the curve values ranged from 0.74 to 0.9993 (slide level) and 0.9476 to 0.9956 (single-node level), outperforming traditional clinical guidelines. CONCLUSION: Artificial intelligence models show promise in predicting lymph node metastasis in early-stage colorectal cancers, potentially refining clinical decisions and improving outcomes. PROSPERO REGISTRATION NUMBER: CRD42023409094.

Novel and Annotated Long Noncoding RNAs Associated with Ischemia in the Human Heart.

BACKGROUND: Long noncoding RNAs (lncRNAs) have been implicated in the pathogenesis of cardiovascular diseases. We aimed to identify novel lncRNAs associated with the early response to ischemia in the heart. METHODS AND RESULTS: RNA sequencing data gathered from 81 paired left ventricle samples from patients undergoing cardiopulmonary bypass was collected before and after a period of ischemia. Novel lncRNAs were validated with Oxford Nanopore Technologies long-read sequencing. Gene modules associated with an early ischemic response were identified and the subcellular location of selected lncRNAs was determined with RNAscope. A total of 2446 mRNAs, 270 annotated lncRNAs and one novel lncRNA differed in response to ischemia (adjusted p < 0.001, absolute fold change >1.2). The novel lncRNA belonged to a gene module of highly correlated genes that also included 39 annotated lncRNAs. This module associated with ischemia (Pearson correlation coefficient = -0.69, p = 1 × 10-23) and activation of cell death pathways (p < 6 × 10-9). A further nine novel cardiac lncRNAs were identified, of which, one overlapped five cis-eQTL eSNPs for the gene RWD Domain-Containing Sumoylation Enhancer (RWDD3) and was itself correlated with RWDD3 expression (Pearson correlation coefficient -0.2, p = 0.002). CONCLUSION: We have identified 10 novel lncRNAs, one of which was associated with myocardial ischemia and may have potential as a novel therapeutic target or early marker for myocardial dysfunction.

RNAscope compatibility with image analysis platforms for the quantification of tissue-based colorectal cancer biomarkers in archival formalin-fixed paraffin-embedded tissue.

RNAscope®, has emerged as an important in-situ hybridisation method to validate mRNA expression within single cells whilst preserving tissue morphology in histological samples. The aim of this research was to compare the utility of various open-source and commercial image analysis methods, to quantify mRNA transcripts identified by RNAscope within formalin fixed paraffin embedded (FFPE) histological samples and cell monolayer preparations. Examination of MLH1 expression from 10 histological FFPE colorectal cancer specimens using four image analysis tools (Colour Deconvolution, SpotStudio, WEKA and the LEICA RNA-ISH algorithm) showed the WEKA tool as having the greatest level of agreement with manual quantification. Comparing image analysis methods to qRT-PCR for quantifying MLH1, GFI1 and TNFRSF11A expression within two colorectal cell lines results suggest that these image analysis methods perform at a similar level to qRT-PCR. Furthermore, we describe the strengths and limitations for each image analysis method when used in combination with RNAscope assays. Our study concludes that there are several freely available and commercial image analysis tools that enable reliable RNA in situ expression analysis, however operators need to consider factors, such as expected expression levels of target genes, software usability and functionality.

Increased gene expression variability in BRCA1-associated and basal-like breast tumours.

PURPOSE: Inherited variants in the cancer susceptibility genes, BRCA1 and BRCA2 account for up to 5% of breast cancers. Multiple gene expression studies have analysed gene expression patterns that maybe associated with BRCA12 pathogenic variant status; however, results from these studies lack consensus. These studies have focused on the differences in population means to identified genes associated with BRCA1/2-carriers with little consideration for gene expression variability, which is also under genetic control and is a feature of cellular function. METHODS: We measured differential gene expression variability in three of the largest familial breast cancer datasets and a 2116 breast cancer meta-cohort. Additionally, we used RNA in situ hybridisation to confirm expression variability of EN1 in an independent cohort of more than 500 breast tumours. RESULTS: BRCA1-associated breast tumours exhibited a 22.8% (95% CI 22.3-23.2) increase in transcriptome-wide gene expression variability compared to BRCAx tumours. Additionally, 40 genes were associated with BRCA1-related breast cancers that had ChIP-seq data suggestive of enriched EZH2 binding. Of these, two genes (EN1 and IGF2BP3) were significantly variable in both BRCA1-associated and basal-like breast tumours. RNA in situ analysis of EN1 supported a significant (p = 6.3 × 10-04) increase in expression variability in BRCA1-associated breast tumours. CONCLUSION: Our novel results describe a state of increased gene expression variability in BRCA1-related and basal-like breast tumours. Furthermore, genes with increased variability may be driven by changes in DNA occupancy of epigenetic effectors. The variation in gene expression is replicable and led to the identification of novel associations between genes and disease phenotypes.

Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA in situ hybridisation.

Genome-wide expression studies using microarrays and RNAseq have increased our understanding of colorectal cancer development. Translating potential gene biomarkers from these studies for clinical utility has typically relied on PCR-based technology and immunohistochemistry. Results from these techniques are limited by tumour sample heterogeneity and the lack of correlation between mRNA transcript abundance and corresponding protein levels. The aim of this research was to investigate the clinical utility of the RNA in situ hybridisation technique, RNAscope®, for measuring intra-tumoural gene expression of potential prognostic markers in a colorectal cancer cohort. Two candidate gene markers (GFI1 and TNFRSF11A) assessed in this study were identified from a previous study led by the The Cancer Genome Atlas (TCGA) Network, and analysis was performed on 112 consecutively collected, archival FFPE colorectal cancer tumour samples. Consistent with the TCGA Network study, we found reduced GFI1 expression was associated with high-grade and left-sided tumours, and reduced TNFRSF11A expression was associated with metastasis and high nodal involvement. RNAscope® combined with image analysis also enabled quantification of GFI1 and TNFRSF11A mRNA expression levels at the single cell level, allowing cell-type determination. These data showed that reduced mRNA transcript abundance measured in patients with poorer prognosis occurred in carcinoma cells, and not lymphocytes, stromal cells or normal epithelial cells. To our knowledge, this is the first study to assess the intra-tumoural expression patterns of GFI1 and TNFRSF11A and to validate their microarray expression profiles using RNAscope. We also demonstrate the utility of RNAscope® technology to show that expression differences are derived from carcinoma cells rather than from cells located in the tumour microenvironment.

Quantifying BRCA1 and BRCA2 mRNA Isoform Expression Levels in Single Cells.

BRCA1 and BRCA2 spliceogenic variants are often associated with an elevated risk of breast and ovarian cancers. Analyses of BRCA1 and BRCA2 splicing patterns have traditionally used technologies that sample a population of cells but do not account for the variation that may be present between individual cells. This novel proof of concept study utilises RNA in situ hybridisation to measure the absolute expression of BRCA1 and BRCA2 mRNA splicing events in single lymphoblastoid cells containing known spliceogenic variants (BRCA1c.671-2 A>G or BRCA2c.7988 A>T). We observed a large proportion of cells (>42%) in each sample that did not express mRNA for the targeted gene. Increased levels (average mRNA molecules per cell) of BRCA2 ∆17_18 were observed in the cells containing the known spliceogenic variant BRCA2c.7988 A>T, but cells containing BRCA1c.671-2 A>G were not found to express significantly increased levels of BRCA1 ∆11, as had been shown previously. Instead, we show for each variant carrier sample that a higher proportion of cells expressed the targeted splicing event compared to control cells. These results indicate that BRCA1/2 mRNA is expressed stochastically, suggesting that previously reported results using RT-PCR may have been influenced by the number of cells with BRCA1/2 mRNA expression and may not represent an elevation of constitutive mRNA expression. Detection of mRNA expression in single cells allows for a more comprehensive understanding of how spliceogenic variants influence the expression of mRNA isoforms. However, further research is required to assess the utility of this technology to measure the expression of predicted spliceogenic BRCA1 and BRCA2 variants in a diagnostic setting.