Use of methylation and fragmentation signals in the detection of early-stage colorectal cancer

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Background: Colorectal cancer (CRC) remains a leading cause of cancer related mortality worldwide. We utilized cell-free DNA (cfDNA) methylation and fragmentation characteristics of selected cancer-related biomarker regions and applied tumor-derived signal deduction and a machine learning algorithm to refine a blood test for the early detection of CRC. Methods: This was a prospective, international (Spain, Ukraine, Germany and USA [part of NCT04792684 study] population), observational cohort study. Plasma samples were collected either prior to a scheduled screening colonoscopy or prior to colonic surgery for primary CRC. 95 cfDNA samples from 48 early stage (I-II), 47 late-stage (III-IV) CRC patients (mean age 65 [48-83], female 45%, distal cancers 51%) and 204 age, gender and country of origin matched colonoscopy-checked controls were analyzed. 79 of the control patients had a negative colonoscopy finding (cNEG), 96 had benign findings of diverticulosis, hemorrhoids and/or hyperplastic polyps (BEN), 29 had non-advanced adenomas (NAA). Samples were analyzed utilizing previously described hybrid-capture based sequencing methodology. Panel of targeted biomarkers was previously identified through tissue- and plasma-based discovery and further narrowed down through cancer-related biological pathways analysis workflow. Individual cfDNA fragments belonging to each biomarker region were scored for cancer-specific signal. Finally, calculated scores were used in prediction model building and testing for establishing panel accuracy for CRC detection. Results: Prediction model utilizing a panel of methylation and fragmentation scores originating from cfDNA biomarkers belonging to relevant cancer development and progression related pathways, such as axonal guidance, ephrin receptor signaling, epithelial-mesenchymal transition and FGF signaling, correctly classified 92% (87/95) of CRC patients. Sensitivity per cancer stage ranged from 91% (21/23) for stage I, 92% (23/25) for stage II, 91% (30/33) for stage III and 93% (13/14) for stage IV. Fragmentation signals contributed most to early-stage cancers (I-II), while methylation signals were more significant for late stage (III-IV) detection. Specificity of the model was 94% (199/204), with 97% (28/29) NAA, 91% (87/96) BEN and 96% (76/79) cNEG patients correctly identified. Lesion location, gender, age and country of origin were not significantly correlated to prediction outcome. Conclusions: Use of methylation and fragmentation characteristics of cancer-related cfDNA regions, combined with a machine-learning algorithm is highly accurate for early-stage (I-II) CRCs (92% sensitivity at 94% specificity). The study is being further expanded on larger cohort for validation of a highly accurate and minimally invasive blood-based CRC screening test.

Abstract P028: Methylation biomarkers for colorectal cancer early detection and survival prognostics impact gene expression and link to cancer-related biological pathways

Background: DNA methylation has been previously shown to have diagnostic and predictive potential for colorectal cancer (CRC). Aim of this study was to evaluate putative methylation markers in the context of early cancer development and diagnostics as well as further investigate the biological significance of these regions. Methods: Biomarker discovery was done by whole genome bisulfite sequencing (WGBS) of 88 CRC, 48 advanced adenoma (AA) and corresponding adjacent normal tissue (NAT) samples. Short-list of significantly hypermethylated regions (DMRs) was correlated to transcriptomics data from 512 CRC patients in The Cancer Genome Atlas (TCGA) cohort. Pathway enrichment for biological pathway analysis of the DMRs was done by using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Survival analysis was performed using Kaplan–Meier method on sub-groups of patients divided by the methylation status of individual markers. Finally, individual marker significance of selected regions was evaluated by analyzing 26 plasma samples from early stage (stage I-IIA) CRC samples and 42 colonoscopy verified controls (CNT) with targeted methylation sequencing assay. Results: 4167 putative marker regions were identified from biomarker discovery with WGBS. Differential signal could be observed both between AA and NAT and CRC and NAT, while several of these regions were differentially methylated also between AA and CRC samples, indicating biological signal change with adenoma progression to cancer. 84 hypermethylated DMRs from several verification studies were further evaluated against transcriptome data from TCGA, where overlap for 69 genes was found. 19 of these genes showed a significant down- regulation (p< 0.05), indicating a link between hypermethylation and gene expression. 2 genes showed significant up-regulation (p< 0.05), which could indicate other epigenic processes to be in place. KEGG pathway analysis revealed that the top pathways involved were axonal guidance, ephrin receptor signaling, epithelial-mesenchymal transition and FGF signaling, which all play significant role in the context of cancer development and progression. Kaplan-Meier analysis showed significant correlation to patients 5- year survival prediction linked to 3 genes: FGF14 (p=0.025, HR = 1.75) DPY19L2P1 (p=0.012, HR = 1.86), PTPRO (p=0.046, HR = 1.63). Targeted sequencing analysis on plasma samples of patients with early stage (I-IIA) colorectal cancer and age and gender matching colonoscopy-verified controls, showed high individual marker accuracy with AUC= 0.78 for FGF14, AUC= 0.81 for DPY19L2P1 and AUC= 0.73 for PTPRO. Conclusions: Methylation markers have distinct signals in early development of CRC, with high individual accuracy for separating early-stage cancers from matching controls. These regions have impact on gene expression and can be linked to relevant biological pathways. Extending early detection potential of the markers to further prognostics and stratification, could lead to better outcomes and improved survival of the patients.

Citation Format: Pol Canal Noguer, Alejandro Requena Bermejo, Francesco Mattia Mancuso, Juan Carlos Higareda, Marina Manrique López, Marko Chersicola, Pablo Pérez Martínez, Pablo Antonio Camino, Primoz Knap, Vivian Erklavec Zajec, Kristi Kruusmaa. Methylation biomarkers for colorectal cancer early detection and survival prognostics impact gene expression and link to cancer-related biological pathways. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P028.

Genetic evolution to tyrosine kinase inhibitory therapy in patients with EGFR-mutated non-small-cell lung cancer

BACKGROUND

Tumour heterogeneity impacts the efficacy of metastatic cancer treatment even if actionable mutations are identified. Clinicians need to understand if assessing one lesion provides reliable information to drive a therapeutic decision in non-small-cell lung cancer (NSCLC) patients.

METHODS

We analysed inter-tumour heterogeneity from five autopsied individuals with NSCLC-harbouring mutations in the epidermal growth factor receptor (EGFR), treated with EGFR tyrosine kinase inhibitors (TKIs). Through a comprehensive next-generation sequencing (NGS) oncopanel, and an EGFR panel for digital droplet PCR (ddPCR), we compared metastases within individuals, longitudinal biopsies from the same lesions and, whenever possible, the primary naive tumour.

RESULTS

Analysis of 22 necropsies from five patients revealed homogeneity in pathogenic mutations and TKI-resistance mechanisms within each patient in four of them. In-depth analysis by whole-exome sequencing from patient 1 confirmed homogeneity in clonal mutations, but heterogeneity in passenger subclonal alterations. Different resistance mechanisms were detected depending on the patient and line of treatment. Three patients treated with a c-MET inhibitor in combination with TKI lost MET amplification upon progression.

CONCLUSION

At a given point and under selective TKI pressure, a single metastasis biopsy in disseminated tumours from EGFR-mutated NSCLC patients could provide a reasonable assessment of actionable alterations useful for therapeutic decisions.

Early evolutionary divergence between papillary and anaplastic thyroid cancers

Background

Papillary thyroid cancer (PTC) is the most common thyroid carcinoma and exhibits an almost uniformly good prognosis, while anaplastic thyroid cancer (ATC) is less frequent and is one of the most aggressive cancers usually resistant to conventional treatment. Current hypothesis posits that ATC derives from PTC through the progressive acquisition of a discrete number of genomic alterations and implies that the mutational landscape of ATC resembles that of PTC. However, the clinical behaviour of ATC and PTC is radically different. We decided to address the disconnection between the clinical behaviour of ATC and PTC and the proposed model of the progressive development of ATC from PTC.

Patients and methods

We carried out exome sequencing of DNA from 14 ATC specimens including three cases of concomitant ATC and PTC as well as their corresponding normal DNA from 14 patients. The sequencing results were validated using droplet digital PCR. We carried out immunohistochemistry and immunofluorescence studies of the concomitant ATC and PTC cases. In addition, we integrated our sequencing results with the existing TCGA data.

Results

Most of the somatic mutations identified in the ATC component differed from the ones in PTC in the cases of concomitant ATC and PTC. The trunks of the phylogenetic trees representing the somatic mutations were short with long branches. In one case of concomitant PTC and ATC specimens, we observed an infiltration of PTC cells within the ATC component. Moreover, we integrated our results with data obtained from TCGA and observed that the most frequent mutations found in ATC presented high cancer cell fraction values and were significantly different from the PTC ones.

Conclusion

ATC diverge from PTC early in tumour development and both tumour types evolve independently. Our work allows the understanding of the relationship between ATC and PTC facilitating the clinical management of these malignancies.

Impact of circulating tumor DNA mutant allele fraction on prognosis in RAS-mutant metastatic colorectal cancer

Despite major advances in the treatment of metastatic colorectal cancer (mCRC), the survival rate remains very poor. This study aims at exploring the prognostic value of RAS-mutant allele fraction (MAF) in plasma in mCRC. Forty-seven plasma samples from 37 RAS-mutated patients with nonresectable metastases were tested for RAS in circulating tumor DNA using BEAMing before first- and/or second-line treatment. RAS MAF was correlated with several clinical parameters (number of metastatic sites, hepatic volume, carcinoembryonic antigen, CA19-9 levels, primary site location, and treatment line) and clinical outcome [progression-free survival (PFS) and overall survival (OS)]. An independent cohort of 32 patients from the CAPRI-GOIM trial was assessed for clinical outcome based on plasma baseline MAF. RAS MAF analysis at baseline revealed a significant correlation with longer OS [Hazard ratios (HR) = 3.514; P = 0.00066]. Patients with lower MAF also showed a tendency to longer PFS, although not statistically significant. Multivariate analysis showed RAS MAFs as an independent prognostic factor in both OS (HR = 2.73; P = 0.006) and first-line PFS (HR = 3.74; P = 0.049). Tumor response to treatment in patients with higher MAF was progression disease (P = 0.007). Patients with low MAFs at baseline in the CAPRI-GOIM group also showed better OS [HR = 3.84; 95% confidence intervals (CI) 1.5-9.6; P = 0.004] and better PFS (HR = 2.5; 95% CI: 1.07-5.62; P = 0.033). This minimally invasive test may help in adding an independent factor to better estimate outcomes before initiating treatment. Further prospective studies using MAF as a stratification factor could further validate its utility in clinical practice.

Proteotoxicity in cardiac amyloidosis: amyloidogenic light chains affect the levels of intracellular proteins in human heart cells

AL amyloidosis is characterized by widespread deposition of immunoglobulin light chains (LCs) as amyloid fibrils. Cardiac involvement is frequent and leads to life-threatening cardiomyopathy. Besides the tissue alteration caused by fibrils, clinical and experimental evidence indicates that cardiac damage is also caused by proteotoxicity of prefibrillar amyloidogenic species. As in other amyloidoses, the damage mechanisms at cellular level are complex and largely undefined. We have characterized the molecular changes in primary human cardiac fibroblasts (hCFs) exposed in vitro to soluble amyloidogenic cardiotoxic LCs from AL cardiomyopathy patients. To evaluate proteome alterations caused by a representative cardiotropic LC, we combined gel-based with label-free shotgun analysis and performed bioinformatics and data validation studies. To assess the generalizability of our results we explored the effects of multiple LCs on hCF viability and on levels of a subset of cellular proteins. Our results indicate that exposure of hCFs to cardiotropic LCs translates into proteome remodeling, associated with apoptosis activation and oxidative stress. The proteome alterations affect proteins involved in cytoskeletal organization, protein synthesis and quality control, mitochondrial activity and metabolism, signal transduction and molecular trafficking. These results support and expand the concept that soluble amyloidogenic cardiotropic LCs exert toxic effects on cardiac cells.

Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME

Gene expression technology has become a routine application in many laboratories and has provided large amounts of gene expression signatures that have been identified in a variety of cancer types. Interpretation of gene expression signatures would profit from the availability of a procedure capable of assigning differentially regulated genes or entire gene signatures to defined cancer signaling pathways. Here we describe a graph-based approach that identifies cancer signaling pathways from published gene expression signatures. Published gene expression signatures are collected in a database (PubLiME: Published Lists of Microarray Experiments) enabled for cross-platform gene annotation. Significant co-occurrence modules composed of up to 10 genes in different gene expression signatures are identified. Significantly co-occurring genes are linked by an edge in an undirected graph. Edge-betweenness and k-clique clustering combined with graph modularity as a quality measure are used to identify communities in the resulting graph. The identified communities consist of cell cycle, apoptosis, phosphorylation cascade, extra cellular matrix, interferon and immune response regulators as well as communities of unknown function. The genes constituting different communities are characterized by common genomic features and strongly enriched cis-regulatory modules in their upstream regulatory regions that are consistent with pathway assignment of those genes.

Codependency in nursing students: recognition and modification of behavioral characteristics

Recent literature estimates that there are approximately 2 1/2 million nurses; of these a significant number may exhibit signs of codependency, a behavior pattern that impedes an individual's ability to relate to others on mature level. Codependency develops in dysfunctional family systems and manifests itself in compulsive behaviors that make life painful and work emotionally difficult. Often, constructive communication is difficult as codependent persons tend to feel low self-esteem and low self-worth. Nursing students may exhibit characteristic codependency traits among fellow students in the classroom, in the clinical setting, and in interactions with faculty. Nurse educators, through their own self-awareness, introspection, and knowledge of the behaviors and characteristics of codependency, can facilitate more effective communication with all nursing students to promote healthier interactions and relationships. Techniques to modify one's method of interacting with others have clear potential for improving professional as well as personal relationships.

A collaborative effort for sex education in rural school settings

Many students report that sex and sexuality education is, at best, inappropriate and, at worst, nonexistent. Alarming statistics for teen pregnancy and a high incidence of sexually transmitted diseases support the need for education and intervention targeted at a young audience. The traditional approach, to incorporate sex education into health education classes taught by schoolteachers, can be difficult to accomplish in rural school settings where adequate financial resources and community involvement are lacking. Through a partnership funded by the W. K. Kellogg Foundation, a collaborative approach was used in two rural Southeastern communities to deliver a program of sex education to students in fourth through sixth grades. The program united the efforts of community leaders, the school administration, parents, and students and faculty of a university school of nursing.