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Store-operated Ca2+ entry (SOCE) is an essential pathway for Ca2+ signaling, and regulates various vital cellular functions. It is triggered by the endoplasmic reticulum Ca2+ sensor stromal interaction molecule 1 (STIM1). Illustration of STIM1 spatiotemporal structure at the nanometer scale during SOCE activation provides structural and functional insights into the fundamental Ca2+ homeostasis. In this study, we used direct stochastic optical reconstruction microscopy (dSTORM) to revisit the dynamic process of the interaction between STIM1, end-binding protein (EB), and microtubules to the ER-plasma membrane. Using dSTORM, we found that“powder-like”STIM1 aggregates into “trabecular-like” architectures toward the cell periphery during SOCE, and that an intact microtubule network and EB1 are essential for STIM1 trafficking. After thapsigargin treatment, STIM1 can interact with EB1 regardless of undergoing aggregation. We generated STIM1 variants adapted from a real-world database and introduced them into SiHa cells to clarify the impact of STIM1 mutations on cancer cell behavior. The p.D76G and p.D84Y variants locating on the Ca2+ binding domain of STIM1 result in inhibition of focal adhesion turnover, Ca2+ influx during SOCE and subsequent cell migration. Inversely, the p.R643C variant on the microtubule interacting domain of STIM1 leads to dissimilar consequence and aggravates cell migration. These findings imply that STIM1 mutational patterns have an impact on cancer metastasis, and therefore could be either a prognostic marker or a novel therapeutic target to inhibit the malignant behavior of STIM1-mediated cancer cells. Altogether, we generated novel insight into the role of STIM1 during SOCE activation, and uncovered the impact of real-world STIM1 variants on cancer cells.

The analysis of cell-free DNA (cfDNA) is rapidly emerging as a powerful approach to guide the clinical care of cancer patients. Several comprehensive cfDNA assays designed to detect mutations across several genes are now available. Here, we analyzed the use of a cfDNA panel in colorectal cancer (CRC) patients. Twenty-eight CRC patients with relapse or metastatic disease and 31 patients with no evidence of disease (NED) were enrolled. Genomic alterations in cfDNA were analyzed by the Oncomine™ Pan-Cancer Cell-Free Assay that detects hotspot mutations, small indels, copy number changes, and gene fusions across 52 genes. In the NED group, genomic alterations in cfDNA were detected in 12/31 patients (38.7%). The detection of alterations was more common in patients who were ≥60 years old, and the most common genomic alteration was a TP53 mutation. Fifty percent of the TP53 mutations were frequently or very frequently found in human cancers. Among 28 patients with relapse or metastatic disease, 22 (78.6%) had genomic alterations in cfDNA. The alterations were detected most frequently in TP53 (n = 10), followed by KRAS (n = 9). Actionable targets for CRC, including ERBB2 amplification and BRAF mutations, could be identified by this cfDNA assay. Compared with mutational profiling routinely analyzed using tumor samples, several additional targets with currently available therapies, including IDH1, IDH2, and PDGFRA mutations, were discovered. The cfDNA assay could identify potentially actionable targets for CRC. Identifying how to filter out cancer-like genomic alterations not derived from tumors remains a challenge.

Many studies failed to demonstrate benefit from the addition of targeted agents to current standard adjuvant FOLFOX chemotherapy in stage III colorectal cancer (CRC) patients. Intratumor heterogeneity may foster the resistant subclones and leads to cancer recurrence. Here, we built a cancer evolution model and applied machine learning analysis to identify potential therapeutic targets. Among 78 CRC cases, whole-genome (WGS) and deep targeted sequencing data generated from paired blood and primary tumor were used for phylogenetic tree reconstruction. Genetic alterations in the PI3K/AKT, and RTK oncogenic signaling pathways were commonly detected in founding clones. The dominant subclones frequently exhibited dysregulations in the TP53, FBXW7/NOTCH1 tumor suppression, and DNA repair pathways. Fourteen genetic mutations were simultaneously selected by random forest and LASSO methods. The logistic regression model had better accuracy (79%), precision (70%), and recall (65%) and area under the curve (AUC) (82%) for cancer recurrence prediction. Three genes, including MYO18A in the founding clone, FBXW7, and ATM in the dominant subclone, affected the prognosis were selected simultaneously by different feature sets. The in vitro studies, HCT-116 cells transfected with MYO18A siRNA demonstrated a significant reduction in cell migration activity by 20–40%. These results indicate that MYO18A plays a crucial role in the migration of human CRC cells. The cancer evolution model revealed the critical mutations in the founding and dominant subclones. They can be used to predict clinical outcomes and the development of novel therapeutic targets for stage III CRC.

This study aimed to determine the real-world, long-term prognostic impacts, and adverse effects (AEs) of bevacizumab (BEV) in Asian patients with ovarian/tubal/peritoneal cancers. We retrospectively reviewed the medical records of consecutive patients with ovarian/tubal/peritoneal cancer on front-line chemotherapy with or without BEV (Cohort 1) and those who relapsed following chemotherapy and/or BEV (Cohort 2) between 2011 and 2018 in a tertiary medical centre. Patient characteristics, BEV dosages, clinical outcomes, and AEs were analyzed. Hazard ratios for disease progression and death were analyzed using a cox proportional regression model. Benefits of BEV used throughout triweekly, in terms of improved progression-free survival (PFS) and overall survival (OS), were observed at a dosage of 7.5–15 mg/kg among advanced-stage Cohort 1 patients. A progression-free interval of