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Scientists from across Oncology and the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences set off on the 15 June on a six-day road-trip.
Impact of Human Epidermal Growth Factor Receptor 2 in Patients With Metastatic Colorectal Cancer Treated With Chemotherapy Plus Bevacizumab or Anti-EGFRs: Exploratory Analysis of Eight Randomized Trials
PURPOSE Human epidermal growth factor receptor 2 (HER2) amplification/overexpression (HER2-pos) is detected in 5% of RAS/BRAF wild-type metastatic colorectal cancers (mCRCs). Its prognostic/predictive role in terms of benefit from anti-EGFR/bevacizumab (bev) is debated. Similarly, the role of activating HER2 mutations (mut) is unclear. METHODS We collected individual data of 1,604 patients with proficient mismatch repair (pMMR)/microsatellite stable (MSS) RAS/BRAF wild-type untreated mCRC with HER2 amplification/expression status available enrolled in eight randomized clinical trials (RCT; TRIBE2, TRIPLETE, VALENTINO, ATEZOTRIBE, PANDA, PANAMA, PARADIGM, and CALGB/SWOG80405). Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were assessed with respect to HER2 amplification/expression and HER2 mutational status and according to biologics (anti-EGFR/bev). RESULTS Patients with HER2-pos were 81 (5%). HER2-pos patients experienced shorter PFS (median PFS [mPFS]: 9.8 v 12.2 months, hazard ratio [HR], 1.31, P = .02) and OS (median OS [mOS]: 28.0 v 34.9 months, HR, 1.37, P = .01), also after adjustment for covariates ( P adj PFS = .02, P adj OS = .048). ORR was similar between HER2-pos and HER2-negative (HER2-neg) tumors (75% v 72%, odds ratio [OR], 1.21, P = .47). We found no interaction between HER2 amplification/expression status and biologics' effect in terms of PFS ( P int = .76), OS ( P int = .76), and ORR ( P int = .64). In left-sided HER2-pos tumors, outcomes were similar with chemotherapy plus bev/anti-EGFRs in terms of PFS (9.8 v 9.3 months, HR, 0.73, P = .29), OS (29.8 v 28.0 months, HR, 1.29, P = .40), and ORR (59% v 79%, OR, 0.39, P = .10). HER2 -mutant tumors (2% of patients with HER2-neg tumors) showed shorter OS than HER2 wild-type ones (mOS: 23.7 v 34.4 months, HR, 1.56, P = .04) with no differential effect of biologics ( P int ORR = .81; P int PFS = .95; P int OS = .92). CONCLUSION To our knowledge, this is the largest analysis of HER2 status in patients with untreated mCRC enrolled in RCT. Waiting for targeted approaches, HER2-pos and mut do not predict benefit from bev/anti-EGFRs and should be regarded as negative prognostic factors in pMMR/MSS RAS/BRAF wild-type mCRC.
Landscape Analysis of CLDN18 Expression and Isoform Distribution in Solid Tumors: Insights From MONSTAR‐SCREEN‐2 Study
ABSTRACTClaudin 18.2 (CLDN18.2), a tight junction protein isoform, is an emerging therapeutic target in oncology. CLDN18 is well‐characterized in gastric cancer, but its pan‐cancer expression profiles and isoform distributions are poorly documented. In the present study, we analyzed CLDN18 expression in patients with solid tumors enrolled in the MONSTAR‐SCREEN‐2 study using immunohistochemistry (IHC, n = 349) and whole‐transcriptome sequencing (WTS, n = 2191). A splice junction analysis algorithm characterized isoform distribution patterns in WTS data and evaluated temporal changes using paired pre‐ and postchemotherapy specimens. IHC detected CLDN18.2 (≥ 40% of tumor cells showing any staining intensity) in 16.3% of patients, with highest prevalence in gastric (54.5%), biliary tract (21.7%), pancreatic (20.7%), and small intestinal (18.2%) cancers. WTS and IHC findings were significantly correlated (p < 0.001). WTS analysis with optimized transcript thresholds (n = 2191) demonstrated the CLDN18‐high population to be 13.8%, with highest proportions in gastric (64.5%), small intestinal (40.0%), pancreatic (37.8%), and biliary tract (20.0%) cancers. Isoform analysis of 364 patients revealed CLDN18.2 predominance (mean 18.2/18.1 proportion 0.945), with CLDN18.1 predominance observed in only 4.9% of patients. Longitudinal analysis of 27 paired gastric cancer samples revealed a significant reduction in CLDN18 expression and a nonsignificant decrease in the CLDN18.2 proportion following chemotherapy. This analysis validates WTS as a complementary approach to IHC for CLDN18 assessment and demonstrates significant CLDN18 expression across multiple cancer types. The predominance of CLDN18.2 supports the expansion of targeted therapeutic approaches beyond gastric cancer and indicates the potential of RNA‐based screening.
Clinicomolecular Profile and Efficacy of Human Epidermal Growth Factor Receptor 2 (HER2)-Targeted Therapy for HER2 -Amplified Advanced Biliary Tract Cancer
PURPOSE This study aimed to investigate the clinicomolecular profiles and the efficacy of human epidermal growth factor receptor 2 (HER2)-targeted therapy in HER2 -amplified biliary tract cancer (BTC). METHODS This study was an international collaboration that used combined data from the prospective SCRUM-Japan GOZILA and MONSTAR-SCREEN in Japan and retrospective reviews in the United States; patients with advanced BTC who had received systemic therapy were included. The clinicomolecular profiles were evaluated in an exploratory cohort, whereas the efficacy of HER2-targeted therapy was assessed in a biomarker-selected cohort. RESULTS Of the 439 patients in the exploratory cohort, 43 (10%) had HER2 amplification. The frequencies of coalterations were higher in patients with HER2 amplification versus patients without HER2 amplification including HER2 mutations (26% v 5%, P < .001), TP53 mutations (84% v 61%, P = .003), and BRAF amplification (9% v 2%, P = .030). There were no KRAS mutations identified in patients with HER2- amplified BTC. No significant difference in overall survival (OS) was observed between patients with and without HER2 amplification (median, 17.7 v 16.9 months; hazard ratio [HR], 0.95 [95% CI, 0.65 to 1.40]). Of the 60 patients with HER2 -amplified BTC in the biomarker-selected cohort (43 from Japan and 17 from the United States), the OS was significantly longer in 29 patients who received HER2-targeted therapy than in those who did not receive HER2-targeted therapy (median, 24.3 v 12.1 months; HR, 0.39 [95% CI, 0.23 to 0.82]). Multivariate analysis identified HER2-targeted therapy as an independent prognostic factor for OS (HR, 0.29 [95% CI, 0.14 to 0.58]; P < .001). CONCLUSION HER2 amplification was found in 10% of advanced BTC and was not identified as an independent prognostic factor for OS. Patients with HER2 -amplified BTC derive significant benefit from HER2-targeted therapy.
Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study
PURPOSE The utility of capturing heterogeneity by circulating tumor DNA (ctDNA) genotyping combined with tissue analysis or applying it in a sequential manner remains uncertain. METHODS We assessed the clinical value of ctDNA genotyping using data from 2,187 patients with advanced solid tumors enrolled in SCRUM-Japan MONSTAR-SCREEN-1, a nationwide cancer genome screening project, which examined ctDNA from longitudinally collected blood samples and tumor tissue samples (UMIN 000036749). RESULTS Among 667 patients with both baseline ctDNA and tissue genotyping results, 51 (7.6%) had actionable biomarkers identified exclusively through ctDNA genotyping. The most frequent targets of genotype-matched therapy guided by solely ctDNA were immune checkpoint, estrogen receptor, and poly(ADP-ribose) polymerase (PARP). Comparison of objective response rates (ORRs) and progression-free survival (PFS) between patients treated based on tissue versus ctDNA alone showed no significant difference, with ORRs of 34.0% versus 23.1% ( P = .54) and a median PFS of 11.5 versus 13.8 months (hazard ratio [HR], 1.4 [95% CI, 0.72 to 2.80]), respectively. Among 924 patients undergoing sequential ctDNA genotyping, the detection of actionable biomarkers increased from 63.2% to 72.5% following subsequent ctDNA. Targets for genotype-matched therapy guided by subsequent ctDNA alone commonly included PARP, immune checkpoint, and BRAF. The ORR was 23.2% and 26.7% ( P = .75), and the median PFS was 5.2 and. 3.7 months (HR, 1.5 [95% CI, 0.79 to 2.80]) for genotype-matched therapy based on initial versus subsequent ctDNA alone, respectively. CONCLUSION Combining ctDNA with tissue analysis, followed by sequential ctDNA assessments, effectively enhances the identification of actionable biomarkers. This strategy facilitates clinically beneficial, genetically informed therapies, underscoring its significant value in precision oncology.
Japan society of clinical oncology position paper on appropriate clinical use of molecular residual disease (MRD) testing
Abstract Although the 5-year relative survival rates for resectable solid tumors have improved over the past few years, the risk of postoperative recurrence necessitates effective monitoring strategies. Recent advancements in molecular residual disease (MRD) testing based on circulating tumor DNA (ctDNA) analysis have shown considerable promise in the context of predicting recurrence; however, significant barriers to widespread clinical implementation remain—mainly, low awareness among healthcare professionals, high costs, and lack of standardized assays and comprehensive evidence. This position paper, led by the Japan Society of Clinical Oncology, aims to establish a common framework for the appropriate clinical use of MRD testing in a tumor type-agnostic manner. It synthesizes currently available evidence, reviews region-specific clinical trends, addresses critical clinical questions related to MRD testing, and offers recommendations to guide healthcare professionals, biotechnology and pharmaceutical companies, and regulatory authorities. These recommendations were developed based on a voting process involving 15 expert members, ensuring a consensus-driven approach. These findings underscore the importance of collaborative efforts among various stakeholders in enhancing the clinical utility of MRD testing. This project aimed to foster consensus and provide clear guidelines to support the advancement of precision medicine in oncology and improve patient outcomes in the context of perioperative care.
Circulating Tumor DNA Assessment to Predict Risk of Recurrence after Surgery in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma
Objective: To investigate the association between perioperative ctDNA status and prognosis in patients with esophageal squamous cell carcinoma (ESCC). Background: Circulating tumor DNA (ctDNA) has emerged as a promising biomarker for assessing molecular residual disease (MRD) in various malignancies. However, there are limited studies evaluating the utility of ctDNA for predicting recurrence risk in patients with ESCC. Methods: We prospectively enrolled patients with locally advanced ESCC who were scheduled to receive neoadjuvant chemotherapy (NAC) followed by surgery. This report retrospectively analyzed ctDNA with a personalized, tumor-informed 16-plex mPCR-NGS assay at multiple time points: pre-NAC, post-NAC but before surgery, postoperatively, and longitudinally during follow-up. Results: A total of 28 patients who underwent curative surgery, and had successful whole-exome sequencing analysis of tumor tissue samples were included in this report. At the pre-NAC time point, ctDNA was detected in 50% of patients with stage I and 100% of those with stages II, III, and IV. Post-NAC but before surgery, ctDNA was detected in 33.3% of patients. The recurrence rate was 77.8% in ctDNA-positive patients compared to 27.8% in ctDNA-negative patients, with significantly worse recurrence-free survival (RFS) for ctDNA-positive patients vs. ctDNA-negative patients (HR: 4.56, P=0.01). In patients analyzed during the MRD window (2-16 weeks post-surgery), the recurrence rate was 100% in ctDNA-positive patients compared to 30.4% in ctDNA-negative patients, with significantly worse RFS (HR: 30.99, P<0.0001). Similarly, during surveillance (>16 weeks post-surgery), detectable ctDNA was significantly associated with poor RFS (HR: 27.34, P=0.003). Conclusion: This study suggests that ctDNA-based MRD assessment may be valuable for evaluating patients with ESCC, particularly in post-NAC and postsurgical settings.
Supplementary Figure S1 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>Comprehensive overview of the scRNA-seq dataset and analysis from pretreatment to post-RT in esophageal cancer patients.</p>
Supplementary Figure S3 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>Marker gene expression by lymphocytes.</p>
Supplementary Figure S4 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>KEGG pathway visualization of virus- and HLA-associated immune reactions.</p>
Supplementary Figure S8 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>Prediction of the ICI effect and optimal regimen using mathematical model analysis.</p>
Supplementary Figure S7 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>Identification of radiation-induced immune suppression signals through spatial transcriptomics.</p>
Supplementary Figure S5 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>Induction of CD8+ T cells induces IFNG pathway activation during RT.</p>
Supplementary Figure S6 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>Activation of TGFB during and after RT suppresses lymphocytes.</p>
Supplementary Figure S2 from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<p>The procedures of the calculation the treatment scores.</p>
Data from Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
<div>Abstract<p>Radiotherapy (RT) combined with immune checkpoint inhibitor (ICI) therapy has attracted substantial attention due to its potential to improve outcomes for patients with several types of cancer. However, the optimal administration timepoints and drug combinations remain unclear because the mechanisms underlying RT-induced changes in immune checkpoint molecule expression and interaction with their ligand(s) remain unclear. In this study, we demonstrated the dynamics of lymphocyte-mediated molecular interactions in tissue samples from patients with esophageal cancer throughout RT schedules. Single-cell RNA sequencing and spatial transcriptomic analyses were performed to investigate the dynamics of these interactions. The biological signal in lymphocytes transitioned from innate to adaptive immune reaction, with increases in ligand–receptor interactions, such as <i>PD-1</i>–<i>PD-L1</i>, <i>CTLA4</i>–<i>CD80</i>/<i>86</i>, and <i>TIGIT</i>–<i>PVR</i> interactions. A mathematical model was constructed to predict the efficacy of five types of ICIs when administered at four different timepoints. The model suggested that concurrent anti–PD-1/PD-L1 therapy or concurrent/adjuvant anti-CTLA4/TIGIT therapy would exert a maximal effect with RT. This study provides rationale for clinical trials of RT combined with defined ICI therapy, and these findings will support future studies to search for more effective targets and timing of therapy administration.</p></div>
Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration
Abstract Radiotherapy (RT) combined with immune checkpoint inhibitor (ICI) therapy has attracted substantial attention due to its potential to improve outcomes for patients with several types of cancer. However, the optimal administration timepoints and drug combinations remain unclear because the mechanisms underlying RT-induced changes in immune checkpoint molecule expression and interaction with their ligand(s) remain unclear. In this study, we demonstrated the dynamics of lymphocyte-mediated molecular interactions in tissue samples from patients with esophageal cancer throughout RT schedules. Single-cell RNA sequencing and spatial transcriptomic analyses were performed to investigate the dynamics of these interactions. The biological signal in lymphocytes transitioned from innate to adaptive immune reaction, with increases in ligand–receptor interactions, such as PD-1–PD-L1, CTLA4–CD80/86, and TIGIT–PVR interactions. A mathematical model was constructed to predict the efficacy of five types of ICIs when administered at four different timepoints. The model suggested that concurrent anti–PD-1/PD-L1 therapy or concurrent/adjuvant anti-CTLA4/TIGIT therapy would exert a maximal effect with RT. This study provides rationale for clinical trials of RT combined with defined ICI therapy, and these findings will support future studies to search for more effective targets and timing of therapy administration.
Artificial Intelligence–Powered Human Epidermal Growth Factor Receptor 2 and Tumor Microenvironment Analysis in Human Epidermal Growth Factor Receptor 2–Amplified Metastatic Colorectal Cancer: Exploratory Analysis of Phase II TRIUMPH Trial
PURPOSE Human epidermal growth factor receptor 2 (HER2)–targeted therapies have shown promise in treating HER2 -amplified metastatic colorectal cancer (mCRC). Identifying optimal biomarkers for treatment decisions remains challenging. This study explores the potential of artificial intelligence (AI) in predicting treatment responses to trastuzumab plus pertuzumab (TP) in patients with HER2 -amplified mCRC from the phase II TRIUMPH trial. MATERIALS AND METHODS AI-powered HER2 quantification continuous score (QCS) and tumor microenvironment (TME) analysis were applied to the prescreening cohort (n = 143) and the TRIUMPH cohort (n = 30). AI analyzers determined the proportions of tumor cells (TCs) with HER2 staining intensity and the densities of various cells in TME, examining their associations with clinical outcomes of TP. RESULTS The AI-powered HER2 QCS for HER2 immunohistochemistry (IHC) achieved an accuracy of 86.7% against pathologist evaluations, with a 100% accuracy for HER2 IHC 3+ patients. Patients with ≥50% of TCs showing HER2 3+ staining intensity (AI-H3-high) exhibited significantly prolonged progression-free survival (PFS; median PFS, 4.4 v 1.4 months; hazard ratio [HR], 0.12 [95% CI, 0.04 to 0.38]) and overall survival (OS; median OS, 16.5 v 4.1 months; HR, 0.13 [95% CI, 0.05 to 0.38]) compared with the AI-H3-low (<50% group). Stratification among patients with AI-H3-high included TME-high (all lymphocyte, fibroblast, and macrophage densities in the cancer stroma above the median) and TME-low (anything below the median), showing a median PFS of 1.3 and 5.6 months for TME-high and TME-low respectively, with an HR of 0.04 (95% CI, 0.01 to 0.19) for AI-H3-high with TME-low compared with AI-H3-low. CONCLUSION AI-powered HER2 QCS and TME analysis demonstrated potential in enhancing treatment response predictions in patients with HER2 -amplified mCRC undergoing TP therapy.