The Clinical Implication of Conversion Surgery in Patients with Stage IV Gastric Cancer Who Received Systemic Chemotherapy.

With the advances in chemotherapy and immunotherapy, a small subset of patients may be eligible for conversion surgery after achieving tumor regression with chemotherapy. This is a retrospective cohort study of 118 patients with stage IV gastric cancer who received palliative chemotherapy and conversion surgery with a negative resection margin at Samsung Medical Center. Baseline features included comorbidities, body mass index (BMI), carcinoembryonic antigen (CEA) level, primary tumor size, biopsy histology, distant metastatic sites, and molecular markers-HER2, MSI/MMR, PD-L1, and EBV. Post-chemotherapy features included BMI, CEA level, chemotherapy regimen, objective response to chemotherapy, and number of preoperative chemotherapy cycles. Post-operational features included tumor size, histologic differentiation and Lauren's classification, pathologic tumor and nodal stages, invasion of lymphatics/vessels/nerves, peritoneal cytology, and the receipt of postoperative chemotherapy. Of 118 patients, 60 patients received total gastrectomy and 58 patients received subtotal gastrectomy. In all, 21 patients achieved a pathologic complete response, and 97 patients achieved downstaging to yp stage I, II, or III. Before conversion surgery, patients received first-line capecitabine/oxaliplatin (62%), HER2 inhibitors combined with chemotherapy (18%), immune checkpoint inhibitors (15%), and inhibitors of MET or VEGFR2 (5%). In the multivariable analysis, BMI at the time of diagnosis, either HER2 positive, high MSI, or deficient MMR, and the use of targeted agents were significant prognostic factors. Conversion surgery could be considered in patients with stage IV gastric cancer regardless of the initial disease burden. BMI and molecular markers are important prognostic factors that can be used to select candidates.

Impact of programmed death-ligand 1 (PD-L1) positivity on clinical and molecular features of patients with metastatic gastric cancer.

BACKGROUND: Programmed death-ligand 1 (PD-L1) is an important screening biomarker to select patients with gastric cancer (GC) for optimized treatment, including immune checkpoint inhibitors (ICI). METHODS: In this single-institution retrospective cohort study, patients with metastatic GC with available PD-L1 results between October 2019 and September 2021 were identified by reviewing their electronic medical records. Genomic data were obtained from the Samsung Medical Center Clinical Sequencing Platform. RESULTS: Among the 399 patients, 276 (69%) had a PD-L1 combined positive score (CPS) ≥1, 155 (39%) had a CPS between 1 and 5, and 121 (30%) had a CPS ≥5. Of the 121 patients with CPS ≥5, 28 (23%) had a known etiology for "inflamed tumor," with Epstein-Barr virus (EBV) positivity (N = 11) or high tumor mutational burden (TMB) (N = 17), which included microsatellite instability (MSI) (N = 9). PD-L1 CPS ≥5 was observed in 11/11 (100%) patients with EBV positivity, 9/12 (75%) patients with MSI, and 17/33 (52%) patients with high TMB. For the 108 patients who received ICI therapy, CPS ≥5 was the only predictor significantly associated with survival in multivariable analyses, including TMB, MSI, or EBV. Objective response rate (ORR) was 49% in patients with CPS ≥5, 30% in patients with 1 ≤ CPS <5, and 19% in patients with CPS <1. Among the 31 responders to ICI therapy, 27 (87%) had a CPS of ≥1. Mutations in TET2, IRS2, DOT1L, PTPRT, and LRP1B were associated with a higher ORR (63%-100%), whereas MDC1 mutations were associated with a low ORR (22%). CONCLUSIONS: PD-L1 expression is an independent and sensitive biomarker for ICI therapy. Considering its significant association with several gene alterations, including PIK3CA mutations and MET amplification, combining ICI therapy with other targeted agents may be a promising therapeutic strategy for GC.

Clinical molecular subtyping reveals intrinsic mesenchymal reprogramming in gastric cancer cells.

The mesenchymal cancer phenotype is known to be clinically related to treatment resistance and a poor prognosis. We identified gene signature-based molecular subtypes of gastric cancer (GC, n = 547) based on transcriptome data and validated their prognostic and predictive utility in multiple external cohorts. We subsequently examined their associations with tumor microenvironment (TME) features by employing cellular deconvolution methods and sequencing isolated GC populations. We further performed spatial transcriptomics analysis and immunohistochemistry, demonstrating the presence of GC cells in a partial epithelial-mesenchymal transition state. We performed network and pharmacogenomic database analyses to identify TGF-ß signaling as a driver pathway and, thus, a therapeutic target. We further validated its expression in tumor cells in preclinical models and a single-cell dataset. Finally, we demonstrated that inhibition of TGF-ß signaling negated mesenchymal/stem-like behavior and therapy resistance in GC cell lines and mouse xenograft models. In summary, we show that the mesenchymal GC phenotype could be driven by epithelial cancer cell-intrinsic TGF-ß signaling and propose therapeutic strategies based on targeting the tumor-intrinsic mesenchymal reprogramming of medically intractable GC.

Machine Learning-Based Mortality Prediction Model for Critically Ill Cancer Patients Admitted to the Intensive Care Unit (CanICU).

BACKGROUND: Although cancer patients are increasingly admitted to the intensive care unit (ICU) for cancer- or treatment-related complications, improved mortality prediction remains a big challenge. This study describes a new ML-based mortality prediction model for critically ill cancer patients admitted to ICU. PATIENTS AND METHODS: We developed CanICU, a machine learning-based 28-day mortality prediction model for adult cancer patients admitted to ICU from Medical Information Mart for Intensive Care (MIMIC) database in the USA (n = 766), Yonsei Cancer Center (YCC, n = 3571), and Samsung Medical Center in Korea (SMC, n = 2563) from 2 January 2008 to 31 December 2017. The accuracy of CanICU was measured using sensitivity, specificity, and area under the receiver operating curve (AUROC). RESULTS: A total of 6900 patients were included, with a 28-day mortality of 10.2%/12.7%/36.6% and a 1-year mortality of 30.0%/36.6%/58.5% in the YCC, SMC, and MIMIC-III cohort. Nine clinical and laboratory factors were used to construct the classifier using a random forest machine-learning algorithm. CanICU had 96% sensitivity/73% specificity with the area under the receiver operating characteristic (AUROC) of 0.94 for 28-day, showing better performance than current prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE) or Sequential Organ Failure Assessment (SOFA) score. Application of CanICU in two external data sets across the countries yielded 79-89% sensitivity, 58-59% specificity, and 0.75-0.78 AUROC for 28-day mortality. The CanICU score was also correlated with one-year mortality with 88-93% specificity. CONCLUSION: CanICU offers improved performance for predicting mortality in critically ill cancer patients admitted to ICU. A user-friendly online implementation is available and should be valuable for better mortality risk stratification to allocate ICU care for cancer patients.

FoxM1-dependent and fatty acid oxidation-mediated ROS modulation is a cell-intrinsic drug resistance mechanism in cancer stem-like cells.

Increased oxidative phosphorylation (OXPHOS) and reactive oxygen species (ROS) levels are inherently linked. ROS are essential signaling molecules, with detrimental effects when produced in excess during chemotherapy, leading to cell death. Cancer stem-like cells (CSCs) are a subpopulation of tumor cells resistant to chemotherapy, highly invasive and metastagenic, driving malignant cancer behavior. In this study, we demonstrated that CSCs exhibit increased OXPHOS but paradoxically low ROS levels. Considering the detrimental effects of large amounts of ROS, CSCs have developed potential mechanisms for quenching excess ROS to maintain redox homeostasis. We aimed to investigate the distinct metabolic features and mechanisms of ROS regulation in gastric CSCs and explore potential therapeutic strategies targeting CSCs. Human gastric cancer cell lines, AGS and MKN1, were subjected to liquid chromatography/mass spectrometry-based metabolomic and microarray analyses. Mitochondrial properties such as mitochondrial mass, membrane potential, and ROS were assessed by flow cytometric analysis. CSCs with increased OXPHOS levels maintained low ROS levels by coupling FoxM1-dependent Prx3 expression and fatty acid oxidation-mediated NADPH regeneration. Thus, interventions targeting ROS homeostasis in CSCs may be a useful strategy for targeting this drug-resistant tumor cell subpopulation.

Inflammasomes and autoimmune and rheumatic diseases: A comprehensive review.

Inflammasomes are a multi-protein platform forming a part of the innate immune system. Inflammasomes are at standby status and can be activated when needed. Inflammasome activation is an important mechanism for the production of active interleukin (IL)-1ß and IL-18, which have important roles to instruct adaptive immunity. Active forms of inflammasomes trigger a series of inflammatory cascades and lead to the differentiation and polarization of naïve T cells and secretion of various cytokines, which can induce various kinds of autoimmune and rheumatic diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), gout, Sjögren's syndrome, Behçet's disease, anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis and IgA vasculitis (former Henoch-Schönlein purpura ). In this review, we summarize studies published on inflammasomes and review their roles in various autoimmune diseases. Understanding of the role of inflammasomes may facilitate the diagnosis of autoimmune diseases and the development of tailored therapies in the future.

Mitochondria-centric bioenergetic characteristics in cancer stem-like cells.

Metabolic and genotoxic stresses that arise during tumor progression and anti-cancer treatment, respectively, can impose a selective pressure to promote cancer evolution in the tumor microenvironment. This process ultimately selects for the most "fit" clones, which generally have a cancer stem cell like phenotype with features of drug resistance, epithelial-mesenchymal transition, invasiveness, and high metastatic potential. From a bioenergetics perspective, these cancer stem-like cells (CSCs) exhibit mitochondria-centric energy metabolism and are capable of opportunistically utilizing available nutrients such as fatty acids to generate ATP and other metabolic substances, providing a selective advantage for their survival in an impermissible environment and metabolic context. Thus, diverse therapeutic strategies are needed to efficiently tackle these CSCs and eliminate their advantage. Here, we review the metabolic and bioenergetic characteristics and vulnerabilities specific to CSCs, which can provide an unprecedented opportunity to curb CSC-driven cancer mortality rates. We particularly focus on the potential of a CSC bioenergetics-targeted strategy as a versatile therapeutic component of treatment modalities applicable to most cancer types. A cancer bioenergetics-targeted strategy can expand the inventory of combinatorial regimens in the current anti-cancer armamentarium.