Acquired Resistance to KRAS (G12C) Inhibition in Cancer

BACKGROUND: Clinical trials of the KRAS inhibitors adagrasib and sotorasib have shown promising activity in cancers harboring KRAS glycine-to-cysteine amino acid substitutions at codon 12 (KRAS(G12C)). The mechanisms of acquired resistance to these therapies are currently unknown. METHODS: Among patients with KRAS(G12C) -mutant cancers treated with adagrasib monotherapy, we performed genomic and histologic analyses that compared pretreatment samples with those obtained after the development of resistance. Cell-based experiments were conducted to study mutations that confer resistance to KRAS(G12C) inhibitors. RESULTS: A total of 38 patients were included in this study: 27 with non-small-cell lung cancer, 10 with colorectal cancer, and 1 with appendiceal cancer. Putative mechanisms of resistance to adagrasib were detected in 17 patients (45% of the cohort), of whom 7 (18% of the cohort) had multiple coincident mechanisms. Acquired KRAS alterations included G12D/R/V/W, G13D, Q61H, R68S, H95D/Q/R, Y96C, and high-level amplification of the KRAS(G12C) allele. Acquired bypass mechanisms of resistance included MET amplification; activating mutations in NRAS, BRAF, MAP2K1, and RET; oncogenic fusions involving ALK, RET, BRAF, RAF1, and FGFR3; and loss-of-function mutations in NF1 and PTEN. In two of nine patients with lung adenocarcinoma for whom paired tissue-biopsy samples were available, histologic transformation to squamous-cell carcinoma was observed without identification of any other resistance mechanisms. Using an in vitro deep mutational scanning screen, we systematically defined the landscape of KRAS mutations that confer resistance to KRAS(G12C) inhibitors. CONCLUSIONS: Diverse genomic and histologic mechanisms impart resistance to covalent KRAS(G12C) inhibitors, and new therapeutic strategies are required to delay and overcome this drug resistance in patients with cancer. (Funded by Mirati Therapeutics and others; ClinicalTrials.gov number, NCT03785249.)

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Sea Anemone-like Nanomachine Based on DNA Strand Displacement Composed of Three Boolean Logic Gates: Diversified Input for Intracellular Multitarget Detection

Efficient and accurate acquisition of cellular biomolecular information is crucial for exploring cell fate, achieving early diagnosis, and the effective treatment of various diseases. However, current DNA biosensors are mostly limited to single-target detection, with few complex logic circuits for comprehensive analysis of three or more targets. Herein, we designed a sea anemone-like DNA nanomachine based on DNA strand displacement composed of three logic gates (YES-AND-YES) and delivered into the cells using gold nano bipyramid carriers. The AND gate activation depends on the trigger chain released by upstream DNA strand displacement reactions, while the output signal relies on the downstream DNAzyme structure. Under the influence of diverse inputs (including enzymes, miRNA, and metal ions), the interconnected logic gates simultaneously perform logical analysis on multiple targets, generating a unique output signal in the YES/NO format. This sensor can successfully distinguish healthy cells from tumor cells and can be further used for the diagnosis of different tumor cells, providing a promising platform for accurate cell-type identification