Assessment of residual cancer burden and survival in neoadjuvant chemotherapy of inoperable stage III breast cancer: A ten-year follow-up analysis in Vietnam.

BACKGROUND: Prognostic scores such as Residual Cancer Burden (RCB), Clinical Pathological Score (CPS), and Neo-Bioscore have been introduced to categorize breast cancer patients into different prognostic risk groups after neoadjuvant chemotherapy (NAC). PURPOSE: To evaluate the prognostic value of the residual cancer burden index in a large group of Vietnamese breast cancer patients treated with neoadjuvant chemotherapy in real-world settings. METHODS: 126 patients diagnosed with stage III breast cancer received neoadjuvant chemotherapy according to the AP regimes. After operation of BC, pathologic complete response (pCR) and Residual cancer burden (RCB) were evaluated. All breast cancer patients' survival were analyzed by using Kaplan-Meier and Log-Rank models. RESULTS: The average overall survival (OS) time was 75 months, with 90 (71.4%) recurrence and 82 (65%) mortality. The Kaplan Meier curve between OS and DFS with subgroups RCB indicate that the groups with higher RCB had a lower probability of survival, with statistical significance. Adjusted Cox regression model for age, menstruation, side of breast, clinical respose and overall stage illustrate that patients in RCB group 3 had a 2.7 times higher risk of mortality (95% CI: 1.28-5.67) compared to RCB group 0, p = 0.01. Patients with higher RCB levels had a higher risk of mortality. CONCLUSION: Stage IIIC, RCB score and RCB group are the independent prognostic factors for predicting survival time of breast cancer patients receiving neoadjuvant treatment.

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Fragment length profiles of cancer mutations enhance detection of circulating tumor DNA in patients with early-stage hepatocellular carcinoma.

BACKGROUND: Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. METHODS: Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. RESULTS: Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. CONCLUSIONS: Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Circulating DNA methylation profile improves the accuracy of serum biomarkers for the detection of nonmetastatic hepatocellular carcinoma.

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, µTASWako®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

The early detection of liver cancer in high-risk populations can help people with the disease have a higher chance of survival and better quality of life. However, this is still a healthcare challenge. Current commercial blood tests measuring protein signatures in the blood have low accuracy due to increased levels of these proteins being detected in both liver cancer patients and patients with chronic liver diseases. In this study, we identified a set of signatures in DNA released by cancer cells into the bloodstream and used them as biomarkers to distinguish liver cancer patients from high-risk patients. We also demonstrated that adding those signatures to a commercial blood test currently used in clinics could improve the accuracy in detecting liver cancer patients.

Pathogenic Variant Profile of Hereditary Cancer Syndromes in a Vietnamese Cohort.

BACKGROUND: Hereditary cancer syndromes (HCS) are responsible for 5-10% of cancer cases. Genetic testing to identify pathogenic variants associated with cancer predisposition has not been routinely available in Vietnam. Consequently, the prevalence and genetic landscape of HCS remain unknown. METHODS: 1165 Vietnamese individuals enrolled in genetic testing at our laboratory in 2020. We performed analysis of germline mutations in 17 high- and moderate- penetrance genes associated with HCS by next generation sequencing. RESULTS: A total of 41 pathogenic variants in 11 genes were detected in 3.2% individuals. The carrier frequency was 4.2% in people with family or personal history of cancer and 2.6% in those without history. The percentage of mutation carriers for hereditary colorectal cancer syndromes was 1.3% and for hereditary breast and ovarian cancer syndrome was 1.6%. BRCA1 and BRCA2 mutations were the most prevalent with the positive rate of 1.3% in the general cohort and 5.1% in breast or ovarian cancer patients. Most of BRCA1 mutations located at the BRCA C-terminus domains and the top recurrent mutation was NM_007294.3:c.5251C>T (p.Arg1751Ter). One novel variant NM_000038.6(APC):c.6665C>A (p.Pro2222His) was found in a breast cancer patient with a strong family history of cancer. A case study of hereditary cancer syndrome was illustrated to highlight the importance of genetic testing. CONCLUSION: This is the first largest analysis of carrier frequency and mutation spectrum of HCS in Vietnam. The findings demonstrate the clinical significance of multigene panel testing to identify carriers and their at-risk relatives for better cancer surveillance and management strategies.

Application of St Gallen Categories in Predicting Survival for Patients With Breast Cancer in Vietnam.

Breast cancer is a heterogeneous disease with different tumor subtypes. Identifying risk categories will help make better treatment decisions. Hence, this study aimed to predict the survival outcomes of invasive breast cancer in Vietnam, using St Gallen 2007 classification. This study was conducted on 501 patients with breast cancer who had surgical operations, but had not received neoadjuvant chemotherapy, from 2011 to 2013. The clinicopathological characteristics were recorded. Immunohistochemistry staining was performed on ER, PR, HER2/neu, and Ki67 markers. For HER2/neu(2+), fluorescence in situ hybridization was used as the test. All patients with breast cancer were stratified according to 2007 St Gallen categories. Kaplan-Meier and log-rank models were used to analyze survival rates. There were 3.8% cases classified as low risk (LR), 72.1% as intermediate risk (IR1: 60.1% and IR2: 12.0%), and 24.1% as high risk (HR1: 11.8% and HR2: 12.3%). Patients who were LR had the best prognosis, with a 5-year overall survival (OS) rate of 100%. Intermediate-risk patients were at 92.3%. High-risk patients had the worst prognosis, with a 5-year OS proportion of 69.3% (P < .05). For disease-free survival (DFS), risk categories were categorized as LR: 100%, IR: 90.3%, and HR: 69.3% (P < .05). Three main risk categories of breast cancer had a distinct OS and DFS. These findings suggest that the 2007 St Gallen risk category could be used to stratify patients with breast cancer into different risk groups in Vietnam.