Longitudinal dynamics of circulating tumor DNA for treatment monitoring in patients with breast cancer recurrence.

The prevalence and dynamics of circulating tumor DNA (ctDNA) in patients with breast cancer recurrence or de novo metastatic cancer were examined in a retrospective analysis of a prospective observational cohort. Twenty-three recurrent/metastatic breast cancer cases (8 locoregional, 15 distant metastasis) were enrolled, and sequential plasma samples were obtained. Anchor mutations were selected from the target sequencing of each patient's primary and/or metastatic tumor. An in-house developed assay (UHS assay) was employed for a tumor-informed ctDNA assay during treatment and follow-up. A median of three (range 1-5) anchor mutations per case were applied for ctDNA detection. ctDNA was detected in 14 (63.6%, 14/22) cases at the time of enrollment and 18 (78.5%, 18/23) cases during follow-up. More anchor mutations and higher tumor burden were significantly related to higher ctDNA positive rates (p-value 0.036, 0.043, respectively). The mean enriched variant allele frequency (eVAF) at each time point was significantly higher for stable or progressive disease responses (ANOVA test p-value < 0.001). Eight patients showed an increase in their ctDNA eVAF prior to clinical progression with a mean lead time of 6.2 months (range 1.5-11 months). ctDNA dynamics measured using personalized assay reflected the clinical course of breast cancer recurrence.

ASO Author Reflections: The Timeless Debate Between Ivor-Lewis or McKeown Esophagectomy.

Ivor-Lewis (IL) operation, esophagectomy and intrathoracic esophagogastrostomy and McKeown (MK) operation, esophagectomy, and cervical esophagogastrostomy are the most common procedures for esophageal cancer. The authors reported that the oncological outcomes and completeness of upper mediastinal dissection among esophageal squamous cell carcinoma patients undergoing the IL or MK operations were not different in previous paper. Whether the IL procedure can show equivalent oncologic outcomes as compared to the MK procedure in cases of upper esophageal cancer needs to be further studied in the future. In addition, a comparison of the functional outcomes and quality of life between patients who had undergone the IL and MK operations needs to be explored.

Revolutionizing Non-Small Cell Lung Cancer Diagnosis: Ultra-High-Sensitive ctDNA Analysis for Detecting Hotspot Mutations with Long-term Stored Plasma.

PURPOSE: Circulating cell-free DNA (cfDNA) has great potential in clinical oncology. The prognostic and predictive values of cfDNA in non-small cell lung cancer (NSCLC) have been reported, with epidermal growth factor receptor (EGFR), KRAS, and BRAF mutations in tumor-derived cfDNAs acting as biomarkers during the early stages of tumor progression and recurrence. However, extremely low tumor-derived DNA rates hinder cfDNA application. We developed an ultra-high-sensitivity lung version 1 (ULV1) panel targeting BRAF, KRAS, and EGFR hotspot mutations using small amounts of cfDNA, allowing for semi-quantitative analysis with excellent limit-of-detection (0.05%). MATERIALS AND METHODS: Mutation analysis was performed on cfDNAs extracted from the plasma of 104 patients with NSCLC by using the ULV1 panel and targeted next-generation sequencing (CT-ULTRA), followed by comparison analysis of mutation patterns previously screened using matched tumor tissue DNA. RESULTS: The ULV1 panel demonstrated robust selective amplification of mutant alleles, enabling the detection of mutations with a high degree of analytical sensitivity (limit-of-detection, 0.025%-0.1%) and specificity (87.9%-100%). Applying ULV1 to NSCLC cfDNA revealed 51.1% (23/45) samples with EGFR mutations, increasing with tumor stage: 8.33% (stage I) to 78.26% (stage IV). Semi-quantitative analysis proved effective for low-mutation-fraction clinical samples. Comparative analysis with PANAMutyper EGFR exhibited substantial concordance (κ=0.84). CONCLUSION: Good detection sensitivity (~80%) was observed despite the limited volume (1 mL) and long-term storage (12-50 months) of plasma used and is expected to increase with high cfDNA inputs. Thus, the ULV1 panel is a fast and cost-effective method for early diagnosis, treatment selection, and clinical follow-up of patients with NSCLC.

Establishing Patient-Derived Cancer Cell Cultures and Xenografts in Biliary Tract Cancer.

PURPOSE: Biliary tract cancers (BTCs) are rare and show a dismal prognosis with limited treatment options. To improve our understanding of these heterogeneous tumors and develop effective therapeutic agents, suitable preclinical models reflecting diverse tumor characteristics are needed. We established and characterized new patient-derived cancer cell cultures and patient-derived xenograft (PDX) models using malignant ascites from five patients with BTC. MATERIALS AND METHODS: Five patient-derived cancer cell cultures and three PDX models derived from malignant ascites of five patients with BTC, AMCBTC-01, -02, -03, -04, and -05, were established. To characterize the models histogenetically and confirm whether characteristics of the primary tumor were maintained, targeted sequencing and histopathological comparison between primary tissue and xenograft tumors were performed. RESULTS: From malignant ascites of five BTC patients, five patient-derived cancer cell cultures (100% success rate), and three PDXs (60% success rate) were established. The morphological characteristics of three primary xenograft tumors were compared with those of matched primary tumors, and they displayed a similar morphology. The mutated genes in samples (models, primary tumor tissue, or both) from more than one patient were TP53 (n=2), KRAS (n=2), and STK11 (n=2). Overall, the pattern of commonly mutated genes in BTC cell cultures was different from that in commercially available BTC cell lines. CONCLUSION: We successfully established the patient-derived cancer cell cultures and xenograft models derived from malignant ascites in BTC patients. These models accompanied by different genetic characteristics from commercially available models will help better understand BTC biology.