Direct monofluoroalkenylation of C-H bonds are straightforward approaches for accessing multisubstituted monofluoroalkenes. However, general methods for the monofluoroalkenylation of C(sp3)-H bonds remain challenges. Here we report the development of a...

The synthesis of valuable alkyl-substituted heteroarenes from abundant and inexpensive feedstocks under mild conditions is attractive and highly desirable in pharmaceutical and natural product synthesis. Minisci-type cross dehydrogenative coupling between heteroarenes and C­(sp3)–H bonds offers direct access to these important scaffolds in a step-economic manner. Herein, assisted by stop-flow microtubing reactors, an operationally simple protocol for the visible light-induced hydrogen-evolution cross coupling of heteroarenes with unactivated C­(sp3)–H bonds was developed in a metal- and external oxidant-free manner. A wide range of alkylated heteroarenes was generated with common feedstock chemicals, including ethane. Mechanistic studies indicated that photoredox-induced hydrogen atom transfer processes followed by dehydrogenative rearomatization delivered the desired coupling products. The merits of this strategy were further demonstrated by the late-stage functionalization of various complex bioactive molecules.

An electron donor−acceptor complex-initiated αcyanation of tertiary amines has been described. The reaction protocol provides a novel method to synthesize various α-amino nitriles under mild conditions. The reaction can proceed smoothly without the presence of photocatalysts and transition metal catalysts, and either oxidants are unnecessary or O 2 is the only oxidant. The practicality of this method is showcased not only by the late-stage functionalization of natural alkaloid derivatives and pharmaceutical intermediate, but also by the applicability of a stop−flow microtubing reactor.

Background: Molecular classification of lung adenocarcinoma (LUAD) based on transcriptomic features has been widely studied. The complementarity of data obtained from multilayer molecular biology could help the LUAD classification via combining multi-omics information. Methods:We successfully divided samples from the The Cancer Genome Atlas (TCGA) (n=437) into four subtypes (CS1, CS2, CS3 and CS4) by 10 comprehensive multi-omics clustering methods in the "movics" R package. Meanwhile, external validation sets from different sequencing technologies proved the robustness of the grouping model. The relationship between subtypes, prognosis, molecular features, tumor microenvironment and response to first-line therapy was further analyzed. Next we used univariate Cox regression analysis and Lasso regression analysis to explore the application of biomarkers in clinical prognosis and constructed a prognostic model.Results: CS1 showed the worst overall survival (OS) among all four clusters, possibly related to its poor immune infiltration, higher tumor mutation and worse chromosomal stability. Patients in different subtypes differed significantly in cancer stem cell characteristics, activation of cancer-related pathways, sensitivity to chemotherapy and immunotherapy. The prognostic model showed good predictive performance. The 1-, 2-and 3-year areas under the curve of risk score were 0.779, 0.742 and 0.678, respectively. Seven genes (DKK1, TSPAN7, ID1, DLGAP5, HHIPL2, CD40 and SEMA3C) used to build the model may be potential therapeutic targets for LUAD.Conclusions: Four LUAD subtypes with different molecular characteristics and clinical implications were identified successfully through bioinformatic analysis. Our results may contribute to precision medicine and inform the development of rational clinical strategies for targeted and immune therapies.

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