A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection

A review on cell-free RNA profiling: Insights into metabolic diseases and predictive value for bariatric surgery outcomes

BACKGROUND

The advent of liquid biopsies presents a novel, minimally invasive methodology for the detection of disease biomarkers, offering a significant advantage over traditional biopsy techniques. Particularly, the analysis of cell-free RNA (cfRNA) has garnered interest due to its dynamic expression profiles and the capability to study various RNA species, including messenger RNA (mRNA) and long non-coding RNA (lncRNA). These attributes position cfRNA as a versatile biomarker with broad potential applications in clinical research and diagnostics.

SCOPE OF REVIEW

This review delves into the utility of cfRNA biomarkers as prognostic tools for obesity-related comorbidities, such as diabetes, dyslipidemia, and non-alcoholic fatty liver disease.

MAJOR CONCLUSIONS

We evaluate the efficacy of cfRNA in forecasting metabolic outcomes associated with obesity and in identifying patients likely to experience favorable clinical outcomes following bariatric surgery. Additionally, this review synthesizes evidence from studies examining circulating cfRNA across different physiological and pathological states, with a focus on its role in diabetes, including disease progression monitoring and treatment efficacy assessment. Through this exploration, we underscore the emerging relevance of cfRNA signatures in the context of obesity and its comorbidities, setting the stage for future investigative efforts in this rapidly advancing domain.

Tumour-specific activation of a tumour-blood transport improves the diagnostic accuracy of blood tumour markers in mice

BACKGROUND

The accuracy of blood-based early tumour recognition is compromised by signal production at non-tumoral sites, low amount of signal produced by small tumours, and variable tumour production. Here we examined whether tumour-specific enhancement of vascular permeability by the particular tumour homing peptide, iRGD, which carries dual function of binding to integrin receptors overexpressed in the tumour vasculature and is known to promote extravasation via neuropilin-1 receptor upon site-specific cleavage, might be useful to improve blood-based tumour detection by inducing a yet unrecognised vice versa tumour-to-blood transport.

METHODS

To detect an iRGD-induced tumour-to-blood transport, we examined the effect of intravenously injected iRGD on blood levels of α-fetoprotein (AFP) and autotaxin in several mouse models of hepatocellular carcinoma (HCC) or in mice with chronic liver injury without HCC, and on prostate-specific antigen (PSA) levels in mice with prostate cancer.

FINDINGS

Intravenously injected iRGD rapidly and robustly elevated the blood levels of AFP in several mouse models of HCC, but not in mice with chronic liver injury. The effect was primarily seen in mice with small tumours and normal basal blood AFP levels, was attenuated by an anti-neuropilin-1 antibody, and depended on the concentration gradient between tumour and blood. iRGD treatment was also able to increase blood levels of autotaxin in HCC mice, and of PSA in mice with prostate cancer.

INTERPRETATION

We conclude that iRGD induces a tumour-to-blood transport in a tumour-specific fashion that has potential of improving diagnosis of early stage cancer.

FUNDING

Deutsche Krebshilfe, DKTK, LOEWE-Frankfurt Cancer Institute.

Pathformer: a biological pathway informed transformer for disease diagnosis and prognosis using multi-omics data

MOTIVATION

Multi-omics data provide a comprehensive view of gene regulation at multiple levels, which is helpful in achieving accurate diagnosis of complex diseases like cancer. However, conventional integration methods rarely utilize prior biological knowledge and lack interpretability.

RESULTS

To integrate various multi-omics data of tissue and liquid biopsies for disease diagnosis and prognosis, we developed a biological pathway informed Transformer, Pathformer. It embeds multi-omics input with a compacted multi-modal vector and a pathway-based sparse neural network. Pathformer also leverages criss-cross attention mechanism to capture the crosstalk between different pathways and modalities. We first benchmarked Pathformer with 18 comparable methods on multiple cancer datasets, where Pathformer outperformed all the other methods, with an average improvement of 6.3%-14.7% in F1 score for cancer survival prediction, 5.1%-12% for cancer stage prediction, and 8.1%-13.6% for cancer drug response prediction. Subsequently, for cancer prognosis prediction based on tissue multi-omics data, we used a case study to demonstrate the biological interpretability of Pathformer by identifying key pathways and their biological crosstalk. Then, for cancer early diagnosis based on liquid biopsy data, we used plasma and platelet datasets to demonstrate Pathformer's potential of clinical applications in cancer screening. Moreover, we revealed deregulation of interesting pathways (e.g. scavenger receptor pathway) and their crosstalk in cancer patients' blood, providing potential candidate targets for cancer microenvironment study.

AVAILABILITY AND IMPLEMENTATION

Pathformer is implemented and freely available at https://github.com/lulab/Pathformer.

Battle of the biopsies: Role of tissue and liquid biopsy in hepatocellular carcinoma

The diagnosis and management of hepatocellular carcinoma (HCC) have improved significantly in recent years. With the introduction of immunotherapy-based combination therapy, there has been a notable expansion in treatment options for patients with unresectable HCC. Simultaneously, innovative molecular tests for early detection and management of HCC are emerging. This progress prompts a key question: as liquid biopsy techniques rise in prominence, will they replace traditional tissue biopsies, or will both techniques remain relevant? Given the ongoing challenges of early HCC detection, including issues with ultrasound sensitivity, accessibility, and patient adherence to surveillance, the evolution of diagnostic techniques is more relevant than ever. Furthermore, the accurate stratification of HCC is limited by the absence of reliable biomarkers which can predict response to therapies. While the advantages of molecular diagnostics are evident, their potential has not yet been fully harnessed, largely because tissue biopsies are not routinely performed for HCC. Liquid biopsies, analysing components such as circulating tumour cells, DNA, and extracellular vesicles, provide a promising alternative, though they are still associated with challenges related to sensitivity, cost, and accessibility. The early results from multi-analyte liquid biopsy panels are promising and suggest they could play a transformative role in HCC detection and management; however, comprehensive clinical validation is still ongoing. In this review, we explore the challenges and potential of both tissue and liquid biopsy, highlighting that these diagnostic methods, while distinct in their approaches, are set to jointly reshape the future of HCC management.