Search

Gastric cancer cases are often diagnosed at an advanced stage with poor prognosis. Platinum-based chemotherapy has been internationally accepted as first-line therapy for inoperable or metastatic gastric cancer. To achieve greater benefits, selection of patients eligible for this treatment is critical. Although gene expression profiling has been widely used as a genomic classifier to identify molecular subtypes of gastric cancer and to stratify patients for different chemotherapy regimens, its prediction accuracy can be improved. Adenosine-to-inosine (A-to-I) RNA editing has emerged as a new player contributing to gastric cancer development and progression, offering potential clinical utility for diagnosis and treatment. Using a systematic computational approach followed by both in vitro validations and in silico validations in The Cancer Genome Atlas (TCGA), we conducted a transcriptome-wide RNA editing analysis of a cohort of 104 patients with advanced gastric cancer and identified an RNA editing (GCRE) signature to guide gastric cancer chemotherapy. RNA editing events stood as a prognostic and predictive biomarker in advanced gastric cancer. A GCRE score based on the GCRE signature consisted of 50 editing sites associated with 29 genes, predicting response to chemotherapy with a high accuracy (84%). Of note, patients demonstrating higher editing levels of this panel of sites presented a better overall response. Consistently, gastric cancer cell lines with higher editing levels showed higher chemosensitivity. Applying the GCRE score on TCGA dataset confirmed that responders had significantly higher levels of editing in advanced gastric cancer. Overall, this newly defined GCRE signature reliably stratifies patients with advanced gastric cancer and predicts response from chemotherapy. Significance: This study describes a novel A-to-I RNA editing signature as a prognostic and predictive biomarker in advanced gastric cancer, providing a new tool to improve patient stratification and response to therapy.

Background: DNA methylation signatures describing distinct histological subtypes of oesophageal cancer have been reported. We studied DNA methylation in samples from the MRC OE02 phase III trial, which randomised patients with resectable oesophageal cancer to surgery alone (S) or neoadjuvant chemotherapy followed by surgery (CS).Aim: The aim of the study was to identify epigenetic signatures predictive of chemotherapy benefit in patients with oesophageal adenocarcinoma (OAC) from the OE02 trial and validate the findings in an independent cohort.Methods: DNA methylation was analysed using the Illumina GoldenGate platform on surgically resected OAC specimens from patients in the OE02 trial. Cox proportional hazard analysis was performed to select probes predictive of survival in the CS arm. Non-negative matrix factorisation was used to perform clustering and delineate DNA methylation signatures. The findings were validated in an independent cohort of patients with gastroesophageal adenocarcinoma treated with neoadjuvant chemotherapy.Results: A total of 229 patients with OAC were analysed from the OE02 trial (118 in the CS arm and 111 in the S arm). There was no difference in DNA methylation status between the CS and S arms. A metagene signature was created by dichotomising samples into two clusters. In cluster 1, patients in the CS arm had significant overall survival (OS) benefit (median OS CS: 931 days vs. S: 536 days [HR: 1.54, P = 0.031]). In cluster 2, patients in the CS arm had similar (or worse) OS compared with patients in the S arm (CS: 348 days vs. S: 472 days [HR: 0.70, P = 0.1], and test of interaction was significant (p = 0.005). In the validation cohort (n = 13), there was no difference in DNA methylation status in paired pre- and post-treatment samples. When the epigenetic signature was applied, cluster 1 samples had better OS (median OS, cluster 1: 1174 days vs. cluster 2: 392 days, HR: 3.47, p = 0.059)Conclusions: This is the first and largest study of DNA methylation in patients with OAC uniformly treated in a randomised phase III trial. We identified an epigenetic signature that may serve as a predictive biomarker for chemotherapy benefit in OAC. (C) 2019 Elsevier Ltd. All rights reserved.

A dose of 200 mg 3-weekly of pembrolizumab was approved by the Food and Drug Administration (FDA) as treatment for advanced non-small cell lung cancer (NSCLC) without oncogenic drivers. This is despite evidence showing no difference in efficacy with 2 mg/kg. Our study aimed to assess the efficacy of a lower fixed dose of 100 mg, which is closer to 2 mg/kg weight-based dose in an average-sized Asian patient. All patients receiving pembrolizumab for advanced NSCLC from January 2016 to March 2020 in National University Hospital, Singapore, were included in this retrospective observational study. The effect of pembrolizumab 100 mg (Pem100) vs 200 mg (Pem200) upon survival outcomes, toxicity and cost were examined. One hundred fourteen patients received pembrolizumab. Sixty-five (57%) and 49 (43%) received Pem100 and Pem200, respectively. There was no difference in progression-free survival (PFS) and overall survival (OS) between Pem100 vs Pem200 as a single agent (PFS: 6.8 vs 4.2 months, hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.36-1.46, P = .36; 9 month OS: 58% vs 63%, HR 1.08, 95% CI 0.48-2.41, P = .86) and when combined with chemotherapy (9-month PFS: 60% vs 50%, HR0.84, 95% CI 0.34-2.08, P = .71; 9-month OS: 85% vs 58%, HR 0.27, 95% CI 0.062-1.20, P = .09). No significant difference in response rate or ≥G3 immune-related toxicities between Pem100 and Pem200 was observed. A cost minimisation analysis evaluating the degree of cost savings related to drug costs estimated a within study cost saving of SGD4,290,912 and cost saving per patient of SGD39,942 in the Pem100 group. A 100 mg of pembrolizumab appears to be effective with reduction in cost. A randomised trial should be done to investigate a lower dose of pembrolizumab.

BackgroundWe previously reported that low-dose, short-course sunitinib prior to neoadjuvant doxorubicin-cyclophosphamide (AC) normalised tumour vasculature and improved perfusion, but resulted in neutropenia and delayed subsequent cycles in breast cancer patients. This study combined sunitinib with docetaxel, which has an earlier neutrophil nadir than AC.MethodsPatients with advanced solid cancers were randomized 1:1 to 3-weekly docetaxel 75 mg/m2, with or without sunitinib 12.5 mg daily for 7 days prior to docetaxel, stratified by primary tumour site. Primary endpoints were objective-response (ORR:CR + PR) and clinical-benefit rate (CBR:CR + PR + SD); secondary endpoints were toxicity and progression-free-survival (PFS).ResultsWe enrolled 68 patients from 2 study sites; 33 received docetaxel-sunitinib and 35 docetaxel alone, with 33 breast, 25 lung and 10 patients with other cancers.There was no difference in ORR (30.3% vs 28.6%,p = 0.432, odds-ratio [OR] 1.10, 95% CI 0.38–3.18); CBR was lower in the docetaxel-sunitinib arm (48.5% vs 71.4%,p = 0.027 OR 0.37, 95% CI 0.14–1.01). Median PFS was shorter in the docetaxel-sunitinib arm (2.9 vs 4.9 months, hazard-ratio [HR] 2.00, 95% CI 1.15–3.48,p = 0.014) overall, as well as in breast (4.2 vs 5.6 months,p = 0.048) and other cancers (2.0 vs 5.3 months,p = 0.009), but not in lung cancers (2.9 vs 4.1 months,p = 0.597). Median OS was similar in both arms overall (9.9 vs 10.5 months, HR 0.92, 95% CI 0.51–1.67,p = 0.789), and in the breast (18.9 vs 25.8 months,p = 0.354), lung (7.0 vs 6.7 months,p = 0.970) and other cancers (4.5 vs 8.8 months,p = 0.449) subgroups.Grade 3/4 haematological toxicities were lower with docetaxel-sunitinib (18.2% vs 34.3%,p = 0.132), attributed to greater discretionary use of prophylactic G-CSF (90.9% vs 63.0%,p = 0.024). Grade 3/4 non-haematological toxicities were similar (12.1% vs 14.3%,p = 0.792).ConclusionsThe addition of sunitinib to docetaxel was well-tolerated but did not improve outcomes. The possible negative impact in metastatic breast cancer patients is contrary to results of adding sunitinib to neoadjuvant AC. These negative results suggest that the intermittent administration of sunitinib in the current dose and schedule with docetaxel in advanced solid tumours, particularly breast cancers, is not beneficial.Trial registrationThe study was registered (NCT01803503) prospectively on clinicaltrials.gov on 4th March 2013.

Lessons LearnedTKM-080301 showed a favorable toxicity profile at the studied dose. TKM-080301 targeting PLK1 through small interfering RNA mechanism did not demonstrate improved overall survival in patients with advanced hepatocellular carcinoma compared with historical control. Preliminary antitumor activity as shown in this early-phase study does not support further evaluation as a single agent.BackgroundPolo-like kinase 1 (PLK1) is overexpressed in hepatocellular carcinoma (HCC). Knockdown of PLK1 expression by PLK1 small interfering RNA (siRNA) in an HCC cell line showed reduced expression in RNA-induced silencing complex and a reduction in cell proliferation.MethodsA 3 + 3 dose escalation plus expansion cohort at the maximum tolerated dose (MTD) was implemented. Patients with HCC, Eastern Cooperative Oncology Group (ECOG) performance status ≤2, and Child-Pugh score A received TKM-080301 as an intravenous infusion once every week for 3 consecutive weeks, repeated every 28 days.ResultsThe study enrolled 43 patients. The starting dose of TKM-080301 was 0.3 mg/kg, and MTD was declared at 0.75 mg/kg. Following the development of grade 4 thrombocytopenia in two subjects on the expansion cohort, the MTD was redefined at 0.6 mg/kg. Four patients did not have any evaluable postbaseline scan. Of the other 39 subjects who had received at least 0.3 mg/kg, 18 subjects (46.2%) had stable disease (SD) by independent RECIST 1.1 criteria. By Choi criteria, eight subjects (23.1%) had a partial response (PR). For 37 assessable subjects, with 2 subjects censored, median progression-free survival (PFS) was 2.04 months. Median survival for the whole study population was 7.5 months.ConclusionTKM-080301 was generally well tolerated. In this early-phase study, antitumor effect for TKM 080301 was limited. Further evaluation as a single agent in large randomized trials is not warranted.

We aimed to identify a prostate cancer DNA hypermethylation microarray signature (denoted as PHYMA) that differentiates prostate cancer from benign prostate hyperplasia (BPH), high from low-grade and lethal from non-lethal cancers. This is a non-randomized retrospective study in 111 local Asian men (87 prostate cancers and 24 BPH) treated from 1995 to 2009 in our institution. Archival prostate epithelia were laser-capture microdissected and genomic DNA extracted and bisulfite-converted. Samples were profiled using Illumina GoldenGate Methylation microarray, with raw data processed by GenomeStudio. A classification model was generated using support vector machine, consisting of a 55-probe DNA methylation signature of 46 genes. The model was independently validated on an internal testing dataset which yielded cancer detection sensitivity and specificity of 95.3% and 100% respectively, with overall accuracy of 96.4%. Second validation on another independent western cohort yielded 89.8% sensitivity and 66.7% specificity, with overall accuracy of 88.7%. A PHYMA score was developed for each sample based on the state of methylation in the PHYMA signature. Increasing PHYMA score was significantly associated with higher Gleason score and Gleason primary grade. Men with higher PHYMA scores have poorer survival on univariate (p = 0.0038, HR = 3.89) and multivariate analyses when controlled for (i) clinical stage (p = 0.055, HR = 2.57), and (ii) clinical stage and Gleason score (p = 0.043, HR = 2.61). We further performed bisulfite genomic sequencing on 2 relatively unknown genes to demonstrate robustness of the assay results. PHYMA is thus a signature with high sensitivity and specificity for discriminating tumors from BPH, and has a potential role in early detection and in predicting survival.

Recent advances have provided unprecedented opportunities to identify prognostic and predictive markers of efficacy of cancer therapy. Genetic markers can be used to exclude patients who will not benefit from therapy, exclude patients at high risk of severe toxicity, and adjust dosing. Genomic approaches for marker discovery now include genome-wide association studies and tumor DNA sequencing. The challenge is now to select markers for which there is enough evidence to transition them to the clinic. The hurdles include the inherent low frequency of many of these markers, the lengthy validation process through trials, as well as legislative and economic hurdles. Attempts to answer questions about certain markers more quickly have led to an increased popularity of trials with enrichment design, especially in the light of the dramatic phase I results seen in recent months. Personalized medicine in oncology is a step closer to reality.

Background & Aims Gastric cancer (GC) is a heterogeneous disease comprising multiple subtypes that have distinct biological properties and effects in patients. We sought to identify new, intrinsic subtypes of GC by gene expression analysis of a large panel of GC cell lines. We tested if these subtypes might be associated with differences in patient survival times and responses to various standard-of-care cytotoxic drugs. Methods We analyzed gene expression profiles for 37 GC cell lines to identify intrinsic GC subtypes. These subtypes were validated in primary tumors from 521 patients in 4 independent cohorts, where the subtypes were determined by either expression profiling or subtype-specific immunohistochemical markers (LGALS4, CDH17). In vitro sensitivity to 3 chemotherapy drugs (5-fluorouracil, cisplatin, oxaliplatin) was also assessed. Results Unsupervised cell line analysis identified 2 major intrinsic genomic subtypes (G-INT and G-DIF) that had distinct patterns of gene expression. The intrinsic subtypes, but not subtypes based on Lauren's histopathologic classification, were prognostic of survival, based on univariate and multivariate analysis in multiple patient cohorts. The G-INT cell lines were significantly more sensitive to 5-fluorouracil and oxaliplatin, but more resistant to cisplatin, than the G-DIF cell lines. In patients, intrinsic subtypes were associated with survival time following adjuvant, 5-fluorouracil–based therapy. Conclusions Intrinsic subtypes of GC, based on distinct patterns of expression, are associated with patient survival and response to chemotherapy. Classification of GC based on intrinsic subtypes might be used to determine prognosis and customize therapy.

Background Non-small cell lung cancer (NSCLC) is a major cause of cancer-related death worldwide due to poor patient prognosis and clinical outcome. Here, we studied the genetic variations underlying NSCLC pathogenesis based on their association to patient outcome after gemcitabine therapy. Results Bioinformatics analysis was used to investigate possible effects of POLA2 G583R (POLA2+1747 GG/GA, dbSNP ID: rs487989) in terms of protein function. Using biostatistics, POLA2+1747 GG/GA (rs487989, POLA2 G583R) was identified as strongly associated with mortality rate and survival time among NSCLC patients. It was also shown that POLA2+1747 GG/GA is functionally significant for protein localization via green fluorescent protein (GFP)-tagging and confocal laser scanning microscopy analysis. The single nucleotide polymorphism (SNP) causes DNA polymerase alpha subunit B to localize in the cytoplasm instead of the nucleus. This inhibits DNA replication in cancer cells and confers a protective effect in individuals with this SNP. Conclusions The results suggest that POLA2+1747 GG/GA may be used as a prognostic biomarker of patient outcome in NSCLC pathogenesis.