The mutation profiles of cell-free DNA in patients with oesophageal squamous cell carcinoma who were responsive and non-responsive to neoadjuvant chemotherapy

Multi-omics approaches for biomarker discovery in predicting the response of esophageal cancer to neoadjuvant therapy: A multidimensional perspective

Neoadjuvant chemoradiotherapy (NCRT) followed by surgery has been established as the standard treatment strategy for operable locally advanced esophageal cancer (EC). However, achieving pathologic complete response (pCR) or near pCR to NCRT is significantly associated with a considerable improvement in survival outcomes, while pCR patients may help organ preservation for patients by active surveillance to avoid planned surgery. Thus, there is an urgent need for improved biomarkers to predict EC chemoradiation response in research and clinical settings. Advances in multiple high-throughput technologies such as next-generation sequencing have facilitated the discovery of novel predictive biomarkers, specifically based on multi-omics data, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra. The application of multi-omics data has shown the benefits in improving the understanding of underlying mechanisms of NCRT sensitivity/resistance in EC. Particularly, the prominent development of artificial intelligence (AI) has introduced a new direction in cancer research. The integration of multi-omics data has significantly advanced our knowledge of the disease and enabled the identification of valuable biomarkers for predicting treatment response from diverse dimension levels, especially with rapid advances in biotechnological and AI methodologies. Herein, we summarize the current status of research on the use of multi-omics technologies in predicting NCRT response for EC patients. Current limitations, challenges, and future perspectives of these multi-omics platforms will be addressed to assist in experimental designs and clinical use for further integrated analysis.

An update of clinical value of circulating tumor DNA in esophageal cancer: a systematic review and meta-analysis

BACKGROUND

Esophageal cancer (EC) is a deadly disease with limited therapeutic options. Although circulating tumor DNA (ctDNA) could be a promising tool in this regard, the availiable evidence is limited. We performed a systematic review and meta-analysis to summarize the clinical applicability of the next-generation sequencing (NGS) and droplet digital polymerase chain reaction (ddPCR) technology on the ctDNA detection of the EC and listed the current challenges.

METHODS

We systematically searched MEDLINE (via PubMed), Embase (via OVID), ISI Web of Science database and Cochrane Library from January, 2000 to April, 2023. Progression-free survival (PFS) and overall survival (OS) were set as primary outcome endpoints. Pathologic response was evaluated by tumor regression grade (TRG), according to the eighth edition of the American Joint Committee on Cancer (AJCC). Major pathologic regression (MPR) was defined as TRG 1 and 2. The MPR was set as secondary endpoint. Hazard rate (HR) and associated 95% CI were used as the effect indicators the association between ctDNA and prognosis of EC. MPR rates were also calculated. Fixed-effect model (Inverse Variance) or random-effect model (Mantel-Haenszel method) was performed depending on the statistically heterogeneity.

RESULTS

Twenty-two studies, containing 1144 patients with EC, were included in this meta-analysis. The results showed that OS (HR = 3.87; 95% CI, 2.86-5.23) and PFS (HR = 4.28; 95% CI, 3.34-5.48) were shorter in ctDNA-positive patients. In the neoadjuvant therapy, the sensitivity analysis showed the clarified HR of ctDNA-positive was 1.13(95% CI, 1.01-1.28). We also found that TP53, NOTCH1, CCND1 and CNKN2A are the most frequent mutation genes.

CONCLUSIONS

Positive ctDNA is associated with poor prognosis, which demonstrated clinical value of ctDNA. Longitudinal ctDNA monitoring showed potential prognostic value in the neoadjuvant therapy. In an era of precision medicine, ctDNA could be a promising tool to individualize treatment planning and to improve outcomes in EC.

PROSPERO REGISTRATION NUMBER

CRD42023412465.

Exploiting the Molecular Basis of Oesophageal Cancer for Targeted Therapies and Biomarkers for Drug Response: Guiding Clinical Decision-Making

Worldwide, oesophageal cancer is the sixth leading cause of deaths related to cancer and represents a major health concern. Sub-Saharan Africa is one of the regions of the world with the highest incidence and mortality rates for oesophageal cancer and most of the cases of oesophageal cancer in this region are oesophageal squamous cell carcinoma (OSCC). The development and progression of OSCC is characterized by genomic changes which can be utilized as diagnostic or prognostic markers. These include changes in the expression of various genes involved in signaling pathways that regulate pathways that regulate processes that are related to the hallmarks of cancer, changes in the tumor mutational burden, changes in alternate splicing and changes in the expression of non-coding RNAs such as miRNA. These genomic changes give rise to characteristic profiles of altered proteins, transcriptomes, spliceosomes and genomes which can be used in clinical applications to monitor specific disease related parameters. Some of these profiles are characteristic of more aggressive forms of cancer or are indicative of treatment resistance or tumors that will be difficult to treat or require more specialized specific treatments. In Sub-Saharan region of Africa there is a high incidence of viral infections such as HPV and HIV, which are both risk factors for OSCC. The genomic changes that occur due to these infections can serve as diagnostic markers for OSCC related to viral infection. Clinically this is an important distinction as it influences treatment as well as disease progression and treatment monitoring practices. This underlines the importance of the characterization of the molecular landscape of OSCC in order to provide the best treatment, care, diagnosis and screening options for the management of OSCC.

Molecular Alterations of Circulating Cell-Free DNA in the Pathological Progression of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most malignant cancers. Early diagnosis of HCC is important to reduce the mortality rate. The aim of this study is to explore the plasma cell-free DNA (cfDNA) mutation profile in the pathological progression of HCC and to investigate the significance of plasma cfDNA mutations in the early diagnosis of HCC.

Methods

Thirty-seven patients with chronic hepatitis B (CHB), eight with liver cirrhosis (LC), and eleven with HCC were enrolled in this cohort. Plasma cfDNA and white blood cell DNA were isolated, and plasma cfDNA mutation profiles were detected using a targeted gene panel.

Results

The sequencing results of plasma cfDNA showed that HCC-related gene mutations were present in patients with CHB and LC. The mutation burden of HCC-related genes increased from CHB and LC to HCC. In patients with HCC, the average mutation burden of NRAS (10.1%), TP53 (7.4%), PTEN (4.2%), and APOB (2.6%) was the highest. The average mutation burden of PTEN, APOB, FRAS1, KDM6A, DDR2, TTK, NRAS, TP53, PTPRB, MPL, FCRL1, HN1, and SFN gradually increased from CHB and LC to HCC. The mutation burden of 18 HCC-related genes had an area under the receiver operating characteristics of 0.92 for the diagnosis of HCC.

Conclusions

The mutation burden of HCC-related genes increased from CHB and LC to HCC. An optimal combination of cfDNA mutations in the gene panel for diagnosing HCC in patients with CHB and LC was selected. Our study indicates that somatic mutations in plasma cfDNA may serve as potential biomarkers for early HCC diagnosis.

Biomarkers for the prediction of esophageal cancer neoadjuvant chemoradiotherapy response: A systemic review

Neoadjuvant chemoradiotherapy followed by surgery has been established as the standard treatment for locally advanced esophageal cancer. For patients with complete regression after neoadjuvant chemotherapy, active surveillance rather than planned surgery has been proposed as an organ preservation strategy. Reliable biomarkers to predict chemoradiation response is needed. We first summarized the previous reports of biomarkers with the potential to predict the treatment response of esophageal cancer neoadjuvant chemoradiotherapy. These traditional biomarkers are classified into three groups: genetic biomarkers, RNA biomarkers, and protein biomarkers. We then summarized some special types of biomarkers, including metabolites biomarkers, immune and tumor microenvironment biomarkers, and microbiome biomarkers.

Plasma Circulating Tumor DNA Sequencing Predicts Minimal Residual Disease in Resectable Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is lethal as tumors are rarely detected at an early stage and have a high recurrence rate. There are no particularly useful biomarkers for the prognostic prediction of ESCC. Circulating tumor DNA (ctDNA) is becoming an important biomarker for non-invasive diagnosis and monitoring tumor prognosis. Here, we aimed to analyze variations in plasma cell-free DNA (cfDNA) amount to search for minimal residual disease (MRD). Plasma and white blood cells (WBCs) of 60 patients were collected before tumor resection and a week after surgery. Tumor specimens were also collected as formalin-fixed paraffin-embedded (FFPE) samples. All samples were extracted to analyze the genetic alterations of 61 genes using capture-based next-generation sequencing (NGS). Tumor variants were detected in 38 patients with ESCC, and the two driver genes with the highest mutation frequency were TP53 and PIK3CA. Of the pre-surgical plasma cfDNA samples, 73.7% of identified variants matched the tissue. In patients who did not receive adjuvant therapy after surgery, postoperative cfDNA-positive patients had shorter overall survival (hazard ratios (HR), 25.8; 95% CI, 2.7–242.6; P = 0.004) and were more likely to relapse than postoperative cfDNA-negative patients (HR, 184.6; 95% CI, 3.6–9576.9; P = 0.01). Detection of ctDNA after surgical tumor excision is associated with tumor relapse and disease-specific survival, and can be used as a prognostic biomarker for MRD detection in ESCC.