Lack of predictive tools for conventional and targeted cancer therapy: Barriers to biomarker development and clinical translation

Exploring the impact of intra-tumoural heterogeneity on liquid biopsy cell-free DNA methylation and copy number in head and neck squamous cell carcinoma

Liquid biopsy profiling is gaining increasing promise towards biomarker-led identification and disease stratification of tumours, particularly for tumours displaying significant intra-tumoural heterogeneity (ITH). For head and neck squamous cell carcinoma (HNSCC), which display high levels of genetic ITH, identification of epigenetic modifications and methylation signatures has shown multiple uses in stratification of HNSCC for prognosis, treatment, and HPV status. In this study, we investigated the potential of liquid biopsy methylomics and genomic copy number to profile HNSCC. We conducted multi-region sampling of tumour core, tumour margin and normal adjacent mucosa, as well as plasma cell-free DNA (cfDNA) across 9 HNSCC patients. Collectively, our work highlights the prevalence of methylomic ITH in HNSCC, and demonstrates the potential of cfDNA methylation as a tool for ITH assessment and serial sampling.

Prognostic determinants in cancer survival: a multidimensional evaluation of clinical and genetic factors across 10 cancer types in the participants of Genomics England's 100,000 Genomes Project

BACKGROUND

Cancer is a complex disease, caused and impacted by a combination of genetic, demographic, clinical, environmental and lifestyle factors. Analysis of cancer characteristics, risk factors, treatment options and the heterogeneity across cancer types has been the focus of medical research for years. The aim of this study is to describe and summarise genetic, clinicopathological, behavioural and demographic characteristics and their differences across ten common cancer types and evaluate their impact on overall survival outcomes.

METHODS

This study included data from 9977 patients with bladder, breast, colorectal, endometrial, glioma, leukaemia, lung, ovarian, prostate, and renal cancers. Genetic data collected through the 100,000 Genomes Project was linked with clinical and demographic data provided by the National Cancer Registration and Analysis Service (NCRAS), Hospital Episode Statistics (HES) and Office for National Statistics (ONS). Descriptive and Kaplan Meier survival analyses were performed to visualise similarities and differences across cancer types. Cox proportional hazards regression models were applied to identify statistically significant prognostic factor associations with overall survival.

RESULTS

161 clinical and 124 genetic factors were evaluated for prognostic association with overall survival. Of these, 116 unique factors were found to have significant prognostic effect for overall survival across ten cancer types when adjusted for age, sex and stage. The findings confirmed prognostic associations with overall survival identified in previous studies in factors such as multimorbidity, tumour mutational burden, and mutations in genes BRAF, CDH1, NF1, NRAS, PIK3CA, PTEN, TP53. The results also identified new prognostic associations with overall survival in factors such as mental health conditions, female health-related conditions, previous hospital encounters and mutations in genes FANCE, FBXW7, GATA3, MSH6, PTPN11, RB1, RNF43.

CONCLUSION

This study provides a comprehensive view of clinicopathological and genetic prognostic factors across different cancer types and draws attention to less commonly known factors which might help produce more precise prognosis and survival estimates. The results from this study contribute to the understanding of cancer disease and could be used by researchers to develop complex prognostic models, which in turn could help predict cancer prognosis more accurately and improve patient outcomes.

Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction

Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.

Clinical Use of Molecular Biomarkers in Canine and Feline Oncology: Current and Future

Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues or body fluids using various techniques. This review discusses how these genomic alterations can be determined and the findings used in clinical settings as diagnostic, prognostic, predictive, and screening biomarkers. We showcase the somatic and germline genomic alterations currently available to date for testing dogs and cats in a clinical setting, discussing their utility in each biomarker class. We also look at some emerging molecular biomarkers that are promising for clinical use. Finally, we discuss the hurdles that need to be overcome in going 'bench to bedside', i.e., the translation from discovery of genomic alterations to adoption by veterinary clinicians. As we understand more of the genomics underlying canine and feline tumours, molecular biomarkers will undoubtedly become a mainstay in delivering precision veterinary care to dogs and cats with cancer.

"I just wanted more": Hereditary cancer syndromes patients' perspectives on the utility of circulating tumour DNA testing for cancer screening

Hereditary cancer syndromes (HCS) predispose individuals to a higher risk of developing multiple cancers. However, current screening strategies have limited ability to screen for all cancer risks. Circulating tumour DNA (ctDNA) detects DNA fragments shed by tumour cells in the bloodstream and can potentially detect cancers early. This study aimed to explore patients' perspectives on ctDNA's utility to help inform its clinical adoption and implementation. We conducted a qualitative interpretive description study using semi-structured phone interviews. Participants were purposively sampled adult HCS patients recruited from a Canadian HCS research consortium. Thirty HCS patients were interviewed (n = 19 women, age range 20s-70s, n = 25 were white). Participants were highly concerned about developing cancers, particularly those without reliable screening options for early detection. They "just wanted more" than their current screening strategies. Participants were enthusiastic about ctDNA's potential to be comprehensive (detect multiple cancers), predictive (detect cancers early) and tailored (lead to personalized clinical management). Participants also acknowledged ctDNA's potential limitations, including false positives/negatives risks and experiencing additional anxiety. However, they saw ctDNA's potential benefits outweighing its limitations. In conclusion, participants' belief in ctDNA's potential to improve their care overshadowed its limitations, indicating patients' support for using ctDNA in HCS care.

RNA nanostructures for targeted drug delivery and imaging

The RNA molecule plays a pivotal role in many biological processes by relaying genetic information, regulating gene expression, and serving as molecular machines and catalyzers. This inherent versatility of RNA has fueled significant advancements in the field of RNA nanotechnology, driving the engineering of complex nanoscale architectures toward biomedical applications, including targeted drug delivery and bioimaging. RNA polymers, serving as building blocks, offer programmability and predictability of Watson-Crick base pairing, as well as non-canonical base pairing, for the construction of nanostructures with high precision and stoichiometry. Leveraging the ease of chemical modifications to protect the RNA from degradation, researchers have developed highly functional and biocompatible RNA architectures and integrated them into preclinical studies for the delivery of payloads and imaging agents. This review offers an educational introduction to the use of RNA as a biopolymer in the design of multifunctional nanostructures applied to targeted delivery in vivo, summarizing physical and biological barriers along with strategies to overcome them. Furthermore, we highlight the most recent progress in the development of both small and larger RNA nanostructures, with a particular focus on imaging reagents and targeted cancer therapeutics in pre-clinical models and provide insights into the prospects of this rapidly evolving field.

Molecular Biomarkers in Cancer

Molecular cancer biomarkers are any measurable molecular indicator of risk of cancer, occurrence of cancer, or patient outcome. They may include germline or somatic genetic variants, epigenetic signatures, transcriptional changes, and proteomic signatures. These indicators are based on biomolecules, such as nucleic acids and proteins, that can be detected in samples obtained from tissues through tumor biopsy or, more easily and non-invasively, from blood (or serum or plasma), saliva, buccal swabs, stool, urine, etc. Detection technologies have advanced tremendously over the last decades, including techniques such as next-generation sequencing, nanotechnology, or methods to study circulating tumor DNA/RNA or exosomes. Clinical applications of biomarkers are extensive. They can be used as tools for cancer risk assessment, screening and early detection of cancer, accurate diagnosis, patient prognosis, prediction of response to therapy, and cancer surveillance and monitoring response. Therefore, they can help to optimize making decisions in clinical practice. Moreover, precision oncology is needed for newly developed targeted therapies, as they are functional only in patients with specific cancer genetic mutations, and biomarkers are the tools used for the identification of these subsets of patients. Improvement in the field of cancer biomarkers is, however, needed to overcome the scientific challenge of developing new biomarkers with greater sensitivity, specificity, and positive predictive value.

Prognostic Evaluation of Metastasis-Related Lymphocyte/Monocyte Ratio in Stage Ⅰ-Ⅲ Breast Cancer Receiving Chemotherapy

Purpose

This study aims to clarify the prognostic significance of metastasis-related indicators in peripheral blood in stage I-III breast cancer (BC).

Methods

The clinicopathological data of 938 breast cancer patients and 509 benign breast disease patients were retrospectively analyzed, and fasting blood samples were collected before treatment. Univariate and multivariate regression analyses were used to evaluate factors related to metastasis risk and prognosis. The Kaplan-Meier method was used to generate survival curves, and the log-rank test was used to measure differences in survival between groups.

Results

Use the cut-off value (3.433) of LMR, the logistic regression analysis revealed that high carbohydrate antigen 153 (CA153), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), killer T cell level, and low lymphocyte to monocyte ratio (LMR) level were significantly associated with BC distant metastasis. In contrast, LMR>=3.433 (HR: 0.409, 95%CI: 0.193–0.867, P = 0.020), Th/Tc ratio >=1.946 (HR: 0.378, 95% CI: 0.158–0.904, P =0.029) is regarded as a protective factor in the multivariate cox analyses. LMR is an independent prognostic factor for DFS in HER2-negative BC patients.

Conclusion

Peripheral blood parameters play an important role in predicting distant metastasis and prognosis of BC patients. As a potential marker, LMR can predict the metastasis and prognosis of patients with stage I-III BC.