Enhanced Clinical Utility of Molecular Budding Signature as a Recurrence Risk Determinant in Stage II and III Colon Cancer Patients.

BACKGROUND: A molecular budding signature (MBS), which consists of seven tumor budding-related genes, was recently presented as a prominent prognostic indicator in colon cancer (CC) using microarray data acquired from frozen specimens. This study aimed to confirm the predictive power of MBS for recurrence risk based on formalin-fixed, paraffin-embedded (FFPE) materials. METHODS: This research utilized the same microarray data from a prior multicenter study using FFPE whole tissue sections, which retrospectively reviewed 232 stage II CC patients without adjuvant chemotherapy and 302 stage III CC patients with adjuvant chemotherapy. All patients underwent upfront curative surgery without neoadjuvant therapy between 2009 and 2012. An MBS score was calculated using the mean of log2 [each signal] of seven genes (MSLN, SLC4A11, WNT11, SCEL, RUNX2, MGAT3, and FOXC1) as described before. RESULTS: The MBS-low group exhibited a better relapse-free survival (RFS) than the MBS-high group in stage II (P = 0.0077) and in stage III CC patients (P = 0.0003). Multivariate analyses revealed that the MBS score was an independent prognostic factor in both stage II (P = 0.0257) and stage III patients (P = 0.0022). Especially among T4, N2, or both (high-risk) stage III patients, the MBS-low group demonstrated markedly better RFS compared with the MBS-high group (P = 0.0013). CONCLUSIONS: This study confirmed the predictive power of the MBS for recurrence risk by employing FFPE materials in stage II/III CC patients.

Evaluation of 95-Gene Classifier of Formalin-fixed Paraffin-embedded Tissues in ER-positive, HER2-negative, and Node-negative Breast Cancer.

BACKGROUND/AIM: A subset of patients with estrogen receptor (ER)-positive, HER2-negative, and node-negative breast cancer experience recurrences. Predicting patients who will have recurrences within 5 years of surgery is essential so that patients can be selected to receive adjuvant chemotherapy. The 95-gene classifier (95-GC) has been validated as a method to differentiate patients into high and low-risk groups for early recurrence. PATIENTS AND METHODS: In this study, we performed 95-GC analysis on 56 formalin-fixed paraffin-embedded (FFPE) tissue samples from patients who underwent surgery for ER-positive, HER2-negative, and node-negative breast cancer and did not receive adjuvant chemotherapy. We associated the obtained high- and low-risk groups with clinicopathological characteristics and recurrence-free survival (RFS). RESULTS: We classified 12 out of 56 patients into the high-risk recurrence group. We found significantly higher KI67 scores in patients in the high-risk group. Other clinicopathological characteristics were not associated with the 95-GC risk groups. Patients in the 95-GC low-risk group had a significantly better prognosis than those in the high-risk group (p=0.0387). The 5-year RFS rate was 97.6% in the low-risk group and 74.1% in the high-risk group, while the 10-year RFS rates were 90.1% and 74.1%, respectively. CONCLUSION: The 95-GC score can accurately predict RFS within 5 years of surgery for ER-positive, HER2-negative, and node-negative breast cancer using FFPE tissue samples. These prediction models could help assign patients to the most effective treatment regimen.

Multicenter retrospective study on the use of Curebest™ 95GC Breast for estrogen receptor-positive and node-negative early breast cancer.

BACKGROUND: The benefits of postoperative chemotherapy in patients with estrogen receptor (ER)-positive breast cancer remain unclear. The use of tumor grade, Ki-67, or ER expression failed to provide an accurate prognosis of the risk of relapse after surgery in patients. This study aimed to evaluate whether a multigene assay Curebest™ 95GC Breast (95GC) can identify the risk of recurrence and provide more insights into the requirements for chemotherapy in patients. METHODS: This single-arm retrospective multicenter joint study included patients with ER-positive, node-negative breast cancer who were treated at five facilities in Japan and had received endocrine therapy alone as adjuvant therapy. The primary lesion specimens obtained during surgery were analyzed using the 95GC breast cancer multigene assay. Based on the 95GC results, patients were classified into low-risk (95GC-L) and high-risk (95GC-H) groups. RESULTS: The 10-year relapse-free survival rates were 88.4 and 59.6% for the 95GC-L and 95GC-H groups, respectively. Histologic grade, Ki-67, and PAM50 exhibited a significant relationship with the 95GC results. The segregation into 95GC-L and 95GC-H groups within established clinical factors can identify subgroups of patients using histologic grade or PAM50 classification with good prognosis without receiving chemotherapy. CONCLUSIONS: Based on the results of our retrospective study, 95GC could be used to evaluate the long-term prognosis of ER-positive, node-negative breast cancer. Even though further prospective validation is necessary, the inclusion of 95GC in clinical practice could help to select optimal treatments for breast cancer patients and identify those who do not benefit from the addition of chemotherapy, thus avoiding unnecessary treatment.

A 95-gene signature stratifies recurrence risk of invasive disease in ER-positive, HER2-negative, node-negative breast cancer with intermediate 21-gene signature recurrence scores.

PURPOSE: A subset of patients with intermediate 21-gene signature assay recurrence score may benefit from adjuvant chemoendocrine therapy, but a predictive strategy is needed to identify such patients. The 95-gene signature assay was tested to stratify patients with intermediate RS into high (95GC-H) and low (95GC-L) groups that were associated with invasive recurrence risk. METHODS: Patients with ER-positive, HER2-negative, node-negative breast cancer and RS 11-25 who underwent definitive surgery and adjuvant endocrine therapy without any cytotoxic agents were included. RNA was extracted from archived formalin-fixed, paraffin-embedded samples, and 95-gene signature was calculated. RESULTS: 206 patients had RS of 11-25 (95GC-L, N = 163; 95GC-H, N = 43). In Cox proportional hazards model, 95GC-H was significantly associated with shorter time to recurrence than was 95GC-L (HR 5.94; 95%CI 1.81-19.53; P = 0.005). The correlation between 95-gene signature and 21-gene signature assay scores was not strong (correlation coefficient r = 0.27), which might suggest that 95-gene signature reflects biological characteristics differing from what 21-gene signature shows. CONCLUSIONS: The 95-gene signature stratifies patients with ER-positive, HER2-negative, node-negative invasive breast cancer and intermediate RS of 11-25 into high and low groups that are associated with recurrence risk of invasive disease. Further retrospective analysis in the prospectively accrued TAILORx population is warranted to confirm that 95-gene signature can identify patients who would benefit from adjuvant chemoendocrine therapy.

SAG-QC: quality control of single amplified genome information by subtracting non-target sequences based on sequence compositions.

BACKGROUND: Whole genome amplification techniques have enabled the analysis of unexplored genomic information by sequencing of single-amplified genomes (SAGs). Whole genome amplification of single bacteria is currently challenging because contamination often occurs in experimental processes. Thus, to increase the confidence in the analyses of sequenced SAGs, bioinformatics approaches that identify and exclude non-target sequences from SAGs are required. Since currently reported approaches utilize sequence information in public databases, they have limitations when new strains are the targets of interest. Here, we developed a software SAG-QC that identify and exclude non-target sequences independent of database. RESULTS: In our method, "no template control" sequences acquired during WGA were used. We calculated the probability that a sequence was derived from contaminants by comparing k-mer compositions with the no template control sequences. Based on the results of tests using simulated SAG datasets, the accuracy of our method for predicting non-target sequences was higher than that of currently reported techniques. Subsequently, we applied our tool to actual SAG datasets and evaluated the accuracy of the predictions. CONCLUSIONS: Our method works independently of public sequence information for distinguishing SAGs from non-target sequences. This method will be effective when employed against SAG sequences of unexplored strains and we anticipate that it will contribute to the correct interpretation of SAGs.

Monodisperse Picoliter Droplets for Low-Bias and Contamination-Free Reactions in Single-Cell Whole Genome Amplification.

Whole genome amplification (WGA) is essential for obtaining genome sequences from single bacterial cells because the quantity of template DNA contained in a single cell is very low. Multiple displacement amplification (MDA), using Phi29 DNA polymerase and random primers, is the most widely used method for single-cell WGA. However, single-cell MDA usually results in uneven genome coverage because of amplification bias, background amplification of contaminating DNA, and formation of chimeras by linking of non-contiguous chromosomal regions. Here, we present a novel MDA method, termed droplet MDA, that minimizes amplification bias and amplification of contaminants by using picoliter-sized droplets for compartmentalized WGA reactions. Extracted DNA fragments from a lysed cell in MDA mixture are divided into 105 droplets (67 pL) within minutes via flow through simple microfluidic channels. Compartmentalized genome fragments can be individually amplified in these droplets without the risk of encounter with reagent-borne or environmental contaminants. Following quality assessment of WGA products from single Escherichia coli cells, we showed that droplet MDA minimized unexpected amplification and improved the percentage of genome recovery from 59% to 89%. Our results demonstrate that microfluidic-generated droplets show potential as an efficient tool for effective amplification of low-input DNA for single-cell genomics and greatly reduce the cost and labor investment required for determination of nearly complete genome sequences of uncultured bacteria from environmental samples.