Real-Time Tumor Gene Expression Profiling to Direct Gastric Cancer Chemotherapy: Proof-of-Concept “3G” Trial

Early Increase in Circulating PD-1+CD8+ T Cells Predicts Favorable Survival in Patients with Advanced Gastric Cancer Receiving Chemotherapy

The clinical significance of PD-1 expression in circulating CD8+ T cells in patients with gastric cancer (GC) receiving chemotherapy remains unelucidated. Therefore, we aimed to examine its prognostic significance in blood samples of 68 patients with advanced GC who received platinum-based chemotherapy. The correlation between peripheral blood mononuclear cells, measured using fluorescence-activated cell sorting, was evaluated. Patients were divided into two groups according to the changes in PD-1+CD8+ T-cell frequencies between day 0 and 7. They were categorized as increased or decreased PD-1+CD8+ T-cell groups. The increased PD-1+CD8+ T-cell group showed longer progression-free survival (PFS) and overall survival (OS) than the decreased PD-1+CD8+ T-cell group (PFS: 8.7 months vs. 6.1 months, p = 0.007; OS: 20.7 months vs. 10.8 months, p = 0.003). The mean duration of response was significantly different between the groups (5.7 months vs. 2.5 months, p = 0.041). Multivariate analysis revealed that an increase in PD-1+CD8+ T-cell frequency was an independent prognostic factor. We concluded that the early increase in PD-1+CD8+ T-cell frequency is a potential predictor of favorable prognoses and durable responses in patients with advanced GC receiving chemotherapy.

Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma

BACKGROUND

We aimed to build a novel model with golgi apparatus related genes (GaGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC).

METHODS

We performed a bioinformatic analysis of integrated PTC datasets with the GaGs to identify differentially expressed GaGs (DE-GaGs). Then we generated PFI-related DE-GaGs and established a novel GaGs based signature. After that, we validated the signature on multiple external datasets and PTC cell lines. Further, we conducted uni- and multivariate analyses to identify independent prognostic characters. Finally, we established a signature and clinical parameters-based nomogram for predicting the PFI of PTC.

RESULTS

We identified 260 DE-GaGs related to PFI in PTC. The functional enrichment analysis showed that the DE-MTGs were associated with an essential oncogenic glycoprotein biosynthetic process. Consequently, we established and optimized a novel 11 gene signature that could distinguish patients with poorer prognoses and predicted PFI accurately. The novel signature had a C-index of 0.78, and the relevant nomogram had a C-index of 0.79. Also, it was closely related to the pivotal clinical characters of and anaplastic potential in datasets and PTC cell lines. And the signature was confirmed a significant independent prognostic factor in PTC. Finally, we built a nomogram by including the signature and relevant clinical factors. Validation analysis showed that the nomogram's efficacy was satisfying in predicting PTC's PFI.

CONCLUSION

The GaGs signature and nomogram were closely associated with PTC prognosis and may help clinicians improve the individualized prediction of PFI, especially for high-risk patients after surgery.

Role of IL-6/STAT3 Axis in Resistance to Cisplatin in Gastric Cancers

Gastric cancer, the second most common cause of death worldwide, is characterized by poor prognosis and low responsiveness to chemotherapy. Indeed, multidrug resistance, based mainly on cellular and molecular factors, remains one of the most limiting factors of the current approach to gastric cancer (GC) therapy. We employed a comprehensive gene expression analysis through data mining of publicly available databases to assess the role of the signal transducer and activator of transcription 3 (STAT3) in gastric cancer drug efficiency. It has been proposed that gastric cancer cells are less sensitive to these drugs because they develop resistance to these agents through activating alternative signalling pathways responsible for overcoming pharmacological inhibition. Our study evaluated the hypothesis that activating STAT3 signalling in response to cisplatin reduces the reaction to the drug. Consistent with this hypothesis, inhibition of interleukin 6 (IL-6)/STAT3 in combination therapy with cisplatin prevented both STAT3 activation and more lethality than induction by a single agent. The data suggest that the IL-6/STAT3 axis block associated with cisplatin treatment may represent a strategy to overcome resistance.

Clinical relevance of PD-1 positive CD8 T-cells in gastric cancer

BACKGROUND

We evaluated the relevance of PD-1⁺CD8⁺ T-cells in gastric cancer (GC) including prognostic significance, association with chemotherapy and immunotherapy sensitivity and correlations with the tumor microenvironment (TME).

METHODS

Discovery cohort: GC samples were evaluated for AE1/3, CD8, PD-1, Ki-67 and Granzyme-B expression with fluorescence-based multiplex immunohistochemistry (mIHC). Validation cohorts: we analyzed bulk RNAseq GC datasets from TCGA, the "3G" chemotherapy trial and an immunotherapy phase 2 trial. The cox proportional hazards model was used to identify factors that influenced overall survival (OS). To study the TME, we analyzed single-cell RNAseq performed on GCs.

RESULTS

In the discovery cohort of 350 GCs, increased PD-1 expression of CD8 T-cells was prognostic for OS (HR 0.822, p = 0.042). PD-1 expression in CD8 T-cells highly correlated with cytolytic [Granzyme-B⁺] (r = 0.714, p < 0.001) and proliferative [Ki-67⁺] (r = 0.798, p < 0.001) activity. Analysis of bulk RNAseq datasets showed tumors with high PD-1 and CD8A expression levels had improved OS when treated with immunotherapy (HR 0.117, p = 0.036) and chemotherapy (HR 0.475, p = 0.017). Analysis of an scRNAseq dataset of 152,423 cells from 40 GCs revealed that T-cell and NK-cell proportions were higher (24% vs 18% and 19% vs 15%, p < 0.0001), while macrophage proportions were lower (7% vs 11%, p < 0.0001) in CD8PD-1_high compared to CD8PD-1_low tumors.

CONCLUSION

This is one of the largest GC cohorts of mIHC combined with analysis of multiple datasets providing orthogonal validation of the clinical relevance of PD-1⁺CD8⁺ T-cells being associated with improved OS. CD8PD-1_high tumors have distinct features of an immunologically active, T-cell inflamed TME.

Regulatory enhancer profiling of mesenchymal-type gastric cancer reveals subtype-specific epigenomic landscapes and targetable vulnerabilities

OBJECTIVE

Gastric cancer (GC) comprises multiple molecular subtypes. Recent studies have highlighted mesenchymal-subtype GC (Mes-GC) as a clinically aggressive subtype with few treatment options. Combining multiple studies, we derived and applied a consensus Mes-GC classifier to define the Mes-GC enhancer landscape revealing disease vulnerabilities.

DESIGN

Transcriptomic profiles of ~1000 primary GCs and cell lines were analysed to derive a consensus Mes-GC classifier. Clinical and genomic associations were performed across >1200 patients with GC. Genome-wide epigenomic profiles (H3K27ac, H3K4me1 and assay for transposase-accessible chromatin with sequencing (ATAC-seq)) of 49 primary GCs and GC cell lines were generated to identify Mes-GC-specific enhancer landscapes. Upstream regulators and downstream targets of Mes-GC enhancers were interrogated using chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA sequencing, CRISPR/Cas9 editing, functional assays and pharmacological inhibition.

RESULTS

We identified and validated a 993-gene cancer-cell intrinsic Mes-GC classifier applicable to retrospective cohorts or prospective single samples. Multicohort analysis of Mes-GCs confirmed associations with poor patient survival, therapy resistance and few targetable genomic alterations. Analysis of enhancer profiles revealed a distinctive Mes-GC epigenomic landscape, with TEAD1 as a master regulator of Mes-GC enhancers and Mes-GCs exhibiting preferential sensitivity to TEAD1 pharmacological inhibition. Analysis of Mes-GC super-enhancers also highlighted NUAK1 kinase as a downstream target, with synergistic effects observed between NUAK1 inhibition and cisplatin treatment.

CONCLUSION

Our results establish a consensus Mes-GC classifier applicable to multiple transcriptomic scenarios. Mes-GCs exhibit a distinct epigenomic landscape, and TEAD1 inhibition and combinatorial NUAK1 inhibition/cisplatin may represent potential targetable options.

Chromatin Rewiring by Mismatch Repair Protein MSH2 Alters Cell Adhesion Pathways and Sensitivity to BET Inhibition in Gastric Cancer

Mutations in the DNA mismatch repair gene MSH2 are causative of microsatellite instability (MSI) in multiple cancers. Here, we discovered that besides its well-established role in DNA repair, MSH2 exerts a novel epigenomic function in gastric cancer. Unbiased CRISPR-based mass spectrometry combined with genome-wide CRISPR functional screening revealed that in early-stage gastric cancer MSH2 genomic binding is not randomly distributed but rather is associated specifically with tumor-associated super-enhancers controlling the expression of cell adhesion genes. At these loci, MSH2 genomic binding was required for chromatin rewiring, de novo enhancer-promoter interactions, maintenance of histone acetylation levels, and regulation of cell adhesion pathway expression. The chromatin function of MSH2 was independent of its DNA repair catalytic activity but required MSH6, another DNA repair gene, and recruitment to gene loci by the SWI/SNF chromatin remodeler SMARCA4/BRG1. Loss of MSH2 in advanced gastric cancers was accompanied by deficient cell adhesion pathway expression, epithelial-mesenchymal transition, and enhanced tumorigenesis in vitro and in vivo. However, MSH2-deficient gastric cancers also displayed addiction to BAZ1B, a bromodomain-containing family member, and consequent synthetic lethality to bromodomain and extraterminal motif (BET) inhibition. Our results reveal a role for MSH2 in gastric cancer epigenomic regulation and identify BET inhibition as a potential therapy in MSH2-deficient gastric malignancies.

SIGNIFICANCE

DNA repair protein MSH2 binds and regulates cell adhesion genes by enabling enhancer-promoter interactions, and loss of MSH2 causes deficient cell adhesion and bromodomain and extraterminal motif inhibitor synthetic lethality in gastric cancer.

Epigenetic promoter alterations in GI tumour immune-editing and resistance to immune checkpoint inhibition

OBJECTIVES

Epigenomic alterations in cancer interact with the immune microenvironment to dictate tumour evolution and therapeutic response. We aimed to study the regulation of the tumour immune microenvironment through epigenetic alternate promoter use in gastric cancer and to expand our findings to other gastrointestinal tumours.

DESIGN

Alternate promoter burden (APB) was quantified using a novel bioinformatic algorithm (proActiv) to infer promoter activity from short-read RNA sequencing and samples categorised into APB_high, APB_int and APB_low. Single-cell RNA sequencing was performed to analyse the intratumour immune microenvironment. A humanised mouse cancer in vivo model was used to explore dynamic temporal interactions between tumour kinetics, alternate promoter usage and the human immune system. Multiple cohorts of gastrointestinal tumours treated with immunotherapy were assessed for correlation between APB and treatment outcomes.

RESULTS

APB_high gastric cancer tumours expressed decreased levels of T-cell cytolytic activity and exhibited signatures of immune depletion. Single-cell RNAsequencing analysis confirmed distinct immunological populations and lower T-cell proportions in APB_high tumours. Functional in vivo studies using 'humanised mice' harbouring an active human immune system revealed distinct temporal relationships between APB and tumour growth, with APB_high tumours having almost no human T-cell infiltration. Analysis of immunotherapy-treated patients with GI cancer confirmed resistance of APB_high tumours to immune checkpoint inhibition. APB_high gastric cancer exhibited significantly poorer progression-free survival compared with APB_low (median 55 days vs 121 days, HR 0.40, 95% CI 0.18 to 0.93, p=0.032).

CONCLUSION

These findings demonstrate an association between alternate promoter use and the tumour microenvironment, leading to immune evasion and immunotherapy resistance.

Machine-learning model derived gene signature predictive of paclitaxel survival benefit in gastric cancer: results from the randomised phase III SAMIT trial

OBJECTIVE

To date, there are no predictive biomarkers to guide selection of patients with gastric cancer (GC) who benefit from paclitaxel. Stomach cancer Adjuvant Multi-Institutional group Trial (SAMIT) was a 2×2 factorial randomised phase III study in which patients with GC were randomised to Pac-S-1 (paclitaxel +S-1), Pac-UFT (paclitaxel +UFT), S-1 alone or UFT alone after curative surgery.

DESIGN

The primary objective of this study was to identify a gene signature that predicts survival benefit from paclitaxel chemotherapy in GC patients. SAMIT GC samples were profiled using a customised 476 gene NanoString panel. A random forest machine-learning model was applied on the NanoString profiles to develop a gene signature. An independent cohort of metastatic patients with GC treated with paclitaxel and ramucirumab (Pac-Ram) served as an external validation cohort.

RESULTS

From the SAMIT trial 499 samples were analysed in this study. From the Pac-S-1 training cohort, the random forest model generated a 19-gene signature assigning patients to two groups: Pac-Sensitive and Pac-Resistant. In the Pac-UFT validation cohort, Pac-Sensitive patients exhibited a significant improvement in disease free survival (DFS): 3-year DFS 66% vs 40% (HR 0.44, p=0.0029). There was no survival difference between Pac-Sensitive and Pac-Resistant in the UFT or S-1 alone arms, test of interaction p<0.001. In the external Pac-Ram validation cohort, the signature predicted benefit for Pac-Sensitive (median PFS 147 days vs 112 days, HR 0.48, p=0.022).

CONCLUSION

Using machine-learning techniques on one of the largest GC trials (SAMIT), we identify a gene signature representing the first predictive biomarker for paclitaxel benefit.

TRIAL REGISTRATION NUMBER

UMIN Clinical Trials Registry: C000000082 (SAMIT); ClinicalTrials.gov identifier, 02628951 (South Korean trial).

Single patient classifier as a prognostic biomarker in pT1N1 gastric cancer: Results from two large Korean cohorts

Objective

Benefits of adjuvant treatment in pT1N1 gastric cancer (GC) remain controversial. Additionally, an effective biomarker for early GC is the need of the hour. The prognostic and predictive roles of single patient classifier (SPC) were validated in stage II/III GC. In this study, we aimed to elucidate the role of SPC as a biomarker for pT1N1 GC.

Methods

The present retrospective biomarker study (NCT03485105) enrolled patients treated for pT1N1 GC between 1996 and 2012 from two large hospitals (the Y cohort and S cohort). For SPC, mRNA expression of four classifier genes (GZMB, WARS, SFRP4 and CDX1) were evaluated by real-time reverse transcription-polymerase chain reaction assay. The SPC was revised targeting pT1 stages and the prognosis was stratified as high- and low-risk group by the expression of SFRP4, a representative epithelial-mesenchymal transition marker.

Results

SPC was evaluated in 875 patients (n=391 and 484 in the Y and S cohorts, respectively). Among 864 patients whose SPC result was available, 41 (4.7%) patients experience GC recurrence. According to revised SPC, 254 (29.4%) patients were classified as high risk [123 (31.5%) and 131 (27.1%) in the Y and S cohorts, respectively]. The high risk was related to frequent recurrence in both Y and S cohort (log-rank P=0.023, P<0.001, respectively), while there was no difference byGZMB and WARS expression. Multivariable analyses of the overall-cohort confirmed the high risk of revised SPC as a significant prognostic factor [hazard ratio (HR): 4.402 (2.293−8.449), P<0.001] of GC. A significant difference was not detected by SPC in the prognosis of patients in the presence and absence of adjuvant treatment (log-rank P=0.670).

Conclusions

The present study revealed the revised SPC as a prognostic biomarker of pT1N1 GC and suggested the use of the revised SPC for early-stage GC as like stage II/III.

Real-World Therapeutic Outcomes of S-1 Adjuvant Chemotherapy for pStage II/III Gastric Cancer in the Elderly

BACKGROUND

The predictive factors for discontinuation of S-1 administration and prognostic factors in elderly patients with pStage II/III gastric cancer receiving S-1 adjuvant chemotherapy remain unclear.

METHODS

Between January 2004 and December 2016, 80 elderly gastric cancer patients (≥70 years) undergoing curative D2 gastrectomy were enrolled in this study. Predictive factors for completion of S-1 administration over 1 year, adverse events due to S-1 administration, and prognostic factors for overall survival (OS) and relapse-free survival (RFS) were evaluated.

RESULTS

Twenty-eight patients (35%) completed 8 courses of S-1. The median relative dose intensity was 82.1% (IQR 31.1-100%). The incidence rates of hematological and nonhematological adverse events were acceptable. Distal gastrectomy was an independent predictive factor for completion of S-1 administration (odds ratio [OR] 0.364; 95% confidence interval [CI] 0.141-0.939; p = 0.037). Higher postoperative neutrophil count/lymphocyte count (N/L) ratio and more advanced stage adversely influenced OS. Multivariate analysis revealed that a higher postoperative N/L ratio and more advanced stage adversely affected RFS.

CONCLUSION

To complete adjuvant S-1 administration to elderly patients with pStage II/III gastric cancer, total gastrectomy should be avoided if possible. A new regimen for elderly gastric cancer patients with higher postoperative N/L ratios and more advanced stage should be established.

"3G" Trial: An RNA Editing Signature to Guide Gastric Cancer Chemotherapy

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.

A Multi-cohort Study of the Prognostic Significance of Microsatellite Instability or Mismatch Repair Status after Recurrence of Resectable Gastric Cancer

PURPOSE

High microsatellite instability (MSI) is related to good prognosis in gastric cancer. We aimed to identify the prognostic factors of patients with recurrent gastric cancer and investigate the role of MSI as a prognostic and predictive biomarker of survival after tumor recurrence.

Materials and Methods

This retrospective cohort study enrolled patients treated for stage II/III gastric cancer who developed tumor recurrence and in whom the MSI status or mismatch repair (MMR) status of the tumor was known. MSI status and the expression of MMR proteins were evaluated using polymerase chain reaction and immunohistochemical analysis, respectively.

RESULTS

Of the 790 patients included, 64 (8.1%) had high MSI status or MMR deficiency. The tumor-node-metastasis stage, type of recurrence, Lauren classification, chemotherapy after recurrence, and interval to recurrence were independently associated with survival after tumor recurrence. The MSI/MMR status and receiving adjuvant chemotherapy were not associated with survival after recurrence. In a subgroup analysis of patients with high MSI or MMR-deficient gastric cancer, those who did not receive adjuvant chemotherapy had better treatment response to chemotherapy after recurrence than those who received adjuvant chemotherapy.

CONCLUSION

Patients with high MSI/MMR-deficient gastric cancer should be spared from adjuvant chemotherapy after surgery, but aggressive chemotherapy after recurrence should be considered. Higher tumor-node-metastasis stage, Lauren classification, interval to recurrence, and type of recurrence are associated with survival after tumor recurrence and should thus be considered when establishing a treatment plan and designing clinical trials targeting recurrent gastric cancer.

Enabling Technologies for Personalized and Precision Medicine

Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care.

Management of early-stage gastro-esophageal cancers: expert perspectives from the Australasian Gastrointestinal Trials Group (AGITG) with invited international faculty

Introduction: A multimodal approach in operable early-stage oesophago-gastric (OG) cancer has evolved in the last decade, leading to improvement in overall outcomes.Areas covered: A review of the published literature and conference abstracts was undertaken on the topic of optimal adjunctive chemotherapy or chemoradiotherapy in early-stage OG cancers. This review article focuses on the current evidence pertaining to neoadjuvant and perioperative strategies in curable OG cancers including the evolving landscape of immunotherapy and targeted drugs in this setting.Expert commentary: Adjunctive therapies in the form of preoperative chemo-radiotherapy (CRT) or chemotherapy and perioperative chemotherapy over surgery alone improve outcomes in patients with operable OG cancer. Although there are variations in practice around the world, a multi-disciplinary approach to patient care is of paramount importance. Immunotherapy and on treatment functional imaging are two examples of emerging strategies to improve the outcome for early-stage patients. A better understanding of the molecular biology of this disease may help overcome the problem of tumor heterogeneity and enable more rationally designed and targeted therapeutic interventions in the future.

Dissection of gastric cancer heterogeneity for precision oncology

Gastric cancer (GC) remains the fifth most prevalent cancer worldwide and the third leading cause of global cancer mortality. Comprehensive ‐omic studies have unveiled a heterogeneous GC landscape, with considerable molecular diversity both between and within tumors. Given the complex nature of GC, a long‐sought goal includes effective identification of distinct patient subsets with prognostic and/or predictive outcomes to enable tailoring of specific treatments (“precision oncology”). In this review, we highlight various approaches to molecular classification in GC, covering recent genomic, transcriptomic, proteomic and epigenomic features. We pay special attention to the translational significance of classifier systems and examine potential confounding factors which deserve further investigation. In particular, we discuss recent advancements in our knowledge of intra‐subtype, intra‐patient and intra‐tumor heterogeneity, and the pivotal role of the tumor stromal microenvironment.

What's New in Gastric Cancer: The Therapeutic Implications of Molecular Classifications and Future Perspectives

Despite some remarkable innovations and the advent of novel molecular classifications the prognosis of patients with advanced gastric cancer (GC) remains overall poor and current clinical application of new advances is disappointing. During the last years only Trastuzumab and Ramucirumab have been approved and currently used as standard of care targeted therapies, but the systemic management of advanced disease did not radically change in contrast with the high number of molecular drivers identified. The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) classifications paved the way, also for GC, to that more contemporary therapeutic approach called "precision medicine" even if tumor heterogeneity and a complex genetic landscape still represent a strong barrier. The identification of specific cancer subgroups is also making possible a better selection of patients that are most likely to respond to immunotherapy. This review aims to critically overview the available molecular classifications summarizing the main druggable molecular drivers and their possible therapeutic implications also taking advantage of new technologies and acquisitions.