Systematic screening reveals synergistic interactions that overcome MAPK inhibitor resistance in cancer cells

Objective:Effective adjuvant therapeutic strategies are urgently needed to overcome MAPK inhibitor(MAPKi)resistance,which is one of the most common forms of resistance that has emerged in many types of cancers.Here,we aimed to systematically identify the genetic interactions underlying MAPKi resistance,and to further investigate the mechanisms that produce the genetic interactions that generate synergistic MAPKi resistance.Methods:We conducted a comprehensive pair-wise sgRNA-based high-throughput screening assay to identify synergistic interactions that sensitized cancer cells to MAPKi,and validated 3 genetic combinations through competitive growth,cell viability,and spheroid formation assays.We next conducted Kaplan-Meier survival analysis based on The Cancer Genome Atlas database and conducted immunohistochemistry to determine the clinical relevance of these synergistic combinations.We also investigated the MAPKi resistance mechanisms of these validated synergistic combinations by using co-immunoprecipitation,Western blot,qRTPCR,and immunofluorescence assays.Results:We constructed a systematic interaction network of MAPKi resistance and identified 3 novel synergistic combinations that effectively targeted MAPKi resistance(ITGB3+IGF1R,ITGB3+JNK,and HDGF+LGR5).We next analyzed their clinical relevance and the mechanisms by which they sensitized cancer cells to MAPKi exposure.Specifically,we discovered a novel protein complex,HDGF-LGR5,that adaptively responded to MAPKi to enhance cancer cell stemness,which was up-or downregulated by the inhibitors of ITGB3+JNK or ITGB3+IGF1R.Conclusions:Pair-wise sgRNA library screening provided systematic insights into elucidating MAPKi resistance in cancer cells.ITGB3-+IGF1R-targeting drugs(cilengitide+linsitinib)could be used as an effective therapy for suppressing the adaptive formation of the HDGF-LGR5 protein complex,which enhanced cancer stemness during MAPKi stress.

Surrogate model-assisted interactive genetic algorithms with individual’s fuzzy and stochastic fitness

We propose a surrogate model-assisted algorithm by using a directed fuzzy graph to extract a user’s cognition on evaluated individuals in order to alleviate user fatigue in interactive genetic algorithms with an individual’s fuzzy and stochastic fitness. We firstly present an approach to construct a directed fuzzy graph of an evolutionary population according to individuals’ dominance relations, cut-set levels and interval dominance probabilities, and then calculate an individual’s crisp fitness based on the out-degree and in-degree of the fuzzy graph. The approach to obtain training data is achieved using the fuzzy entropy of the evolutionary system to guarantee the credibilities of the samples which are used to train the surrogate model. We adopt a support vector regression machine as the surrogate model and train it using the sampled individuals and their crisp fitness. Then the surrogate model is optimized using the traditional genetic algorithm for some generations, and some good individuals are submitted to the user for the subsequent evolutions so as to guide and accelerate the evolution. Finally, we quantitatively analyze the performance of the presented algorithm in alleviating user fatigue and increasing more opportunities to find the satisfactory individuals, and also apply our algorithm to a fashion evolutionary design system to demonstrate its efficiency.

Improved particle filtering techniques based on generalized interactive genetic algorithm

This paper improves the resampling step of particle filtering（PF） based on a broad interactive genetic algorithm to resolve particle degeneration and particle shortage.For target tracking in image processing,this paper uses the information coming from the particles of the previous fame image and new observation data to self-adaptively determine the selecting range of particles in current fame image.The improved selecting operator with jam gene is used to ensure the diversity of particles in mathematics,and the absolute arithmetical crossing operator whose feasible solution space being close about crossing operation,and non-uniform mutation operator is used to capture all kinds of mutation in this paper.The result of simulating experiment shows that the algorithm of this paper has better iterative estimating capability than extended Kalman filtering（EKF）,PF,regularized partide filtering（RPF）,and genetic algorithm（GA）-PF.

Improving grain appearance of erect-panicle japonica rice cultivars by introgression of the null gs9 allele

The panicle architecture and grain size of rice affect not only grain yield but also grain quality,especially grain appearance.The erect-panicle(EP)trait controlled by the qpe9-1/dep1 allele has been widely used in high-yielding japonica rice breeding,but usually accompanied with moderate appearance of milled rice.The null gs9 allele shows a good potential for improving grain shape and appearance.However,GS9 and qPE9-1/DEP1 loci are tightly linked,and their interaction is unclear,which obviously restricts their utilization in modern rice breeding.In the present study,comparative analyses of protein and mRNA levels revealed that GS9 and qPE9-1 function independently.Three nearisogenic lines(NILs)carrying various allelic combinations of these two loci,NIL(gs9/qpe9-1),NIL(GS9/qPE9-1)and NIL(gs9/qPE9-1),in the EP japonica cultivar 2661(GS9/qpe9-1)background were developed for genetic interaction analysis.GS9 and qPE9-1 had additive effects on determining grain size,and the null gs9 allele could decrease grain chalkiness and improve grain appearance without affecting plant and panicle architecture in EP japonica cultivars.Additionally,introgression lines(ILs)developed in another released EP japonica cultivar Wuyujing 27(WYJ27)background showed the same additive effect and the feasibility of utilizing the gs9 allele to improve grain appearance quality in high-yielding EP cultivars.This study provides an effective strategy for rice breeders to improve rice grain appearance in EP japonica and related cultivars.

OsMADS16 Genetically Interacts with OsMADS3 and OsMADS58 in Specifying Floral Patterning ~in Rice

Rice （Oryza sativa） has unique floral patterns that contribute to grain yield. However, the molecular mechanism underlying the specification of floral organ identities in rice, particularly the interaction among floral homeotic genes, remains poorly understood. Here, we show that the floral homeotic gene OsMADS16 （also called SUPERWOMAN1, SPWl, a B-class gene） acts together with the rice C-class genes OsMADS3 and OsMADS58 in specifying floral organ patterning. OsMADS16 and the two C-class genes have an overlapping expression pattern in the third whorl founder cells. Compared with the single mutants, both spwl-1 osmads3-4 and spwl-1 osmads58 double mutants exhibit additional whorls of glume-like organs within the flower, particularly an extra whorl of six glume-like structures formed at the position of the wild-type stamens. These ectopic glume-like structures were shown to have palea identity through cellular observation and in situ hybridization analysis using marker genes. Our results suggest that B- and C-class genes play a key role in suppressing indeterminate growth within the floral meristem, particularly whorl-3 primordia. We also hypothesize that, in contrast to previous assumptions, the specialized spikelet organ in rice, the palea, is the counterpart of the sepal in eudicots, and the lemma is homologous to the bract.

GLABROUS INFLORESCENCE STEMS regulates trichome branching by genetically interacting with SIM in Arabidopsis

Arabidopsis trichomes are large branched single cells that protrude from the epidermis. The first mor- phological indication of trichome development is an increase in nuclear content resulting from an initial cycle of endoreduplication. Our previous study has shown that the C2H2 zinc finger protein GLABROUS INFLORESCENCE STEMS (GIS) is required for trichome initiation in the inflorescence organ and for trichome branching in response to gibberellic acid signaling, although GIS gene does not play a direct role in regulating trichome cell division. Here, we describe a novel role of GIS, controlling trichome cell division indirectly by interacting genetically with a key endoreduplication regulator SIAMESE (SIM). Our molecular and genetic studies have shown that GIS might indireclty control cell division and trichome branching by acting downstream of SIM. A loss of function mutation of SIM signficantly reduced the expression of GIS. Futhermore, the overexpression of GIS rescued the trichome cluster cell phenotypes of sim mutant. The gain or loss of function of GIS had no significant effect on the expression of SIM. These results suggest that GIS may play an indirect role in regulating trichome cell division by genetically interacting with SIM.