Prevalence of ctDNA in early screen-detected breast cancers using highly sensitive and specific dual molecular barcoded personalised mutation assays

Circulating tumor DNA: current implementation issues and future challenges for clinical utility

Over the past decades, liquid biopsy, especially circulating tumor DNA (ctDNA), has received tremendous attention as a noninvasive detection approach for clinical applications, including early diagnosis of cancer and relapse, real-time therapeutic efficacy monitoring, potential target selection and investigation of drug resistance mechanisms. In recent years, the application of next-generation sequencing technology combined with AI technology has significantly improved the accuracy and sensitivity of liquid biopsy, enhancing its potential in solid tumors. However, the increasing integration of such promising tests to improve therapy decision making by oncologists still has complexities and challenges. Here, we propose a conceptual framework of ctDNA technologies and clinical utilities based on bibliometrics and highlight current challenges and future directions, especially in clinical applications such as early detection, minimal residual disease detection, targeted therapy, and immunotherapy. We also discuss the necessities of developing a dynamic field of translational cancer research and rigorous clinical studies that may support therapeutic strategy decision making in the near future.

Development of a Novel NGS Methodology for Ultrasensitive Circulating Tumor DNA Detection as a Tool for Early-Stage Breast Cancer Diagnosis

Breast cancer (BC) is the most prevalent cancer in women. While usually detected when localized, invasive procedures are still required for diagnosis. Herein, we developed a novel ultrasensitive pipeline to detect circulating tumor DNA (ctDNA) in a series of 75 plasma samples from localized BC patients prior to any medical intervention. We first performed a tumor-informed analysis to correlate the mutations found in tumor tissue and plasma. Disregarding the tumor data next, we developed an approach to detect tumor mutations in plasma. We observed a mutation concordance between the tumor and plasma of 29.50% with a sensitivity down to 0.03% in mutant variant allele frequency (VAF). We detected mutations in 33.78% of the samples, identifying eight patients with plasma-only mutations. Altogether, we determined a specificity of 86.36% and a positive predictive value of 88.46% for BC detection. We demonstrated an association between higher ctDNA median VAF and higher tumor grade, multiple plasma mutations with a likelihood of relapse and more frequent TP53 plasma mutations in hormone receptor-negative tumors. Overall, we have developed a unique ultra-sensitive sequencing workflow with a technology not previously employed in early BC, paving the way for its application in BC screening.

Prognostic role of multiple abnormal genes in non-small-cell lung cancer

BACKGROUND

Non-small-cell lung cancer (NSCLC) has the highest morbidity and mortality rates among all malignant tumor types. Although therapies targeting the mutated genes such as KRAS have been used in the clinic for many years, the prognosis remains poor. Therefore, it is necessary to further study the aberrant expression or mutation of non-target genes affecting the survival and prognosis.

AIM

To explore the impact of simultaneous abnormalities of multiple genes on the prognosis and survival of patients.

METHODS

We used R packages to analyze gene expression data and clinical data downloaded from The Cancer Genome Atlas (TCGA) database. We also collected samples from 85 NSCLC patients from the First People’s Hospital of Jingzhou City and retrospectively followed the patients. Multivariate Cox regression analysis and survival analysis were performed.

RESULTS

Analysis of gene expression data from TCGA revealed that the overexpression of the following single genes affected overall survival: TP53 (P = 0.79), PTEN (P = 0.94), RB1 (P = 0.49), CTNNB1 (P = 0.24), STK11 (P = 0.32), and PIK3CA (P = 0.013). However, the probability of multiple genes (TP53, PTEN, RB1, and STK11) affecting survival was 0.025. Retrospective analysis of clinical data revealed that sex (hazard ratio [HR] = 1.29; [95%CI: 0.64-2.62]), age (HR = 1.05; [95%CI: 1.02-1.07]), smoking status (HR = 2.26; [95%CI: 1.16-4.39]), tumor histology (HR = 0.58; [95%CI: 0.30-1.11]), cancer stage (HR = 16.63; [95%CI: 4.8-57.63]), epidermal growth factor receptor (EGFR) mutation (HR = 1.82; [95%CI: 1.05-3.16]), abundance (HR = 4.95; [95%CI: 0.78-31.36]), and treatment with tyrosine kinase inhibitors (TKIs) (HR = 0.58; [95%CI: 0.43-0.78]) affected patient survival. Co-occurring mutations of TP53, PTEN, RB1, and STK11 did not significantly affect the overall survival of patients receiving chemotherapy (P = 0.96) but significantly affected the overall survival of patients receiving TKIs (P = 0.045).

CONCLUSION

Co-occurring mutation or overexpression of different genes has different effects on the overall survival and prognosis of NSCLC patients. Combined with TKI treatment, the co-occurring mutation of some genes may have a synergistic effect on the survival and prognosis of NSCLC patients.