The cancer-testis gene,MEIOB,sensitizes triple-negative breast cancer to PARP1 inhibitors by inducing homologous recombination deficiency

Objective:The newly defined cancer-testis(CT)gene,MEIOB,was previously found to play key roles in DNA double-strand break(DSB)repair.In this study,we aimed to investigate the effects and mechanisms of MEIOB in the carcinogenesis of triple-negative breast cancers(TNBCs).Methods:The Cancer Genome Atlas database was used to quantify the expression of MEIOB.Cox regression analysis was used to evaluate the association between MEIOB expression and the prognosis of human TNBC.The effects of MEIOB on cell proliferation and migration in TNBCs were also assessed in vitro.Patient-derived xenograft(PDX)models were used to assess the sensitivity of breast cancers with active MEIOB to PARP1 inhibitors.Results:We confirmed MEIOB as a CT gene whose expression was restricted to the testes and breast tumors,especially TNBCs.Its activation was significantly associated with poor survival in breast cancer patients[overall,hazard ratio(HR)=1.90(1.16–2.06);TNBCs:HR=7.05(1.16–41.80)].In addition,we found that MEIOB was oncogenic and significantly promoted the proliferation of TNBC cells.Further analysis showed that MEIOB participated in DSB repair in TNBCs.However,in contrast to its function in meiosis,it mediated homologous recombination deficiency(HRD)through the activation of poly ADP-ribose polymerase(PARP)1 by interacting with YBX1.Furthermore,activated MEIOB was shown to confer sensitivity to PARP inhibitors,which was confirmed in PDX models.Conclusions:MEIOB played an oncogenic role in TNBC through its involvement in HRD.In addition,dysregulation of MEIOB sensitized TNBC cells to PARP inhibitors,so MEIOB may be a therapeutic target of PARP1 inhibitors in TNBC.

Euclidean Distance Transform on the Sea Based on Cellular Automata Modeling

To explore the problem of distance transformations while obstacles existing,this paper presents an obstacle-avoiding Euclidean distance transform method based on cellular automata.This research took the South China Sea and its adjacent sea areas as an example,imported the data of land-sea distribution and target points,took the length of the shortest obstacle-avoiding path from current cell to the target cells as the state of a cellular,designed the state transform rule of each cellular that considering a distance operator,then simulated the propagation of obstacle-avoiding distance,and got the result raster of obstacle-avoiding distance transform.After analyzing the effect and precision of obstacle avoiding,we reached the following conclusions:first,the presented method can visually and dynamically show the process of obstacle-avoiding distance transform,and automatically calculate the shortest distance bypass the land;second,the method has auto-update mechanism and each cellular can rectify distance value according to its neighbor cellular during the simulation process;at last,it provides an approximate solution for exact obstacle-avoiding Euclidean distance transform and the proportional error is less than 1.96%.The proposed method can apply to the fields of shipping routes design,maritime search and rescue,etc.

Promotion effect of FOXCUT as a microRNA sponge for miR-24-3p on progression in triple-negative breast cancer through the p38 MAPK signaling pathway

Background:Triple-negative breast cancer(TNBC)is a type of highly invasive breast cancer with a poor prognosis.According to new research,long noncoding RNAs(lncRNAs)play a significant role in the progression of cancer.Although the role of lncRNAs in breast cancer has been well reported,few studies have focused on TNBC.This study aimed to explore the biological function and clinical significance of forkhead box C1 promoter upstream transcript(FOXCUT)in triple-negative breast cancer.Methods:Based on a bioinformatic analysis of the cancer genome atlas(TCGA)database,we detected that the lncRNA FOXCUT was overexpressed in TNBC tissues,which was further validated in an external cohort of tissues from the General Surgery Department of the First Affiliated Hospital of Nanjing Medical University.The functions of FOXCUT in proliferation,migration,and invasion were detected in vitro or in vivo.Luciferase assays and RNA immunoprecipitation(RIP)were performed to reveal that FOXCUT acted as a competitive endogenous RNA(ceRNA)for the microRNA miR-24-3p and consequently inhibited the degradation of p38.Results:lncRNA FOXCUT was markedly highly expressed in breast cancer,which was associated with poor prognosis in some cases.Knockdown of FOXCUT significantly inhibited cancer growth and metastasis in vitro or in vivo.Mechanistically,FOXCUT competitively bounded to miR-24-3p to prevent the degradation of p38,which might act as an oncogene in breast cancer.Conclusion:Collectively,this research revealed a novel FOXCUT/miR-24-3p/p38 axis that affected breast cancer progression and suggested that the lncRNA FOXCUT could be a diagnostic marker and therapeutic target for breast cancer.

A Heuristic Radiomics Feature Selection Method Based on Frequency Iteration and Multi-Supervised Training Mode

Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for diagnosis.It has received great attention due to its huge application prospects in recent years.We can know that the number of features selected by the existing radiomics feature selectionmethods is basically about ten.In this paper,a heuristic feature selection method based on frequency iteration and multiple supervised training mode is proposed.Based on the combination between features,it decomposes all features layer by layer to select the optimal features for each layer,then fuses the optimal features to form a local optimal group layer by layer and iterates to the global optimal combination finally.Compared with the currentmethod with the best prediction performance in the three data sets,thismethod proposed in this paper can reduce the number of features fromabout ten to about three without losing classification accuracy and even significantly improving classification accuracy.The proposed method has better interpretability and generalization ability,which gives it great potential in the feature selection of radiomics.

The multi-omics basis of potato heterosis

Heterosis is a fundamental biological phenomenon characterized by the superior performance of hybrids over their parents.Although tremendous progress has been reported in seed crops,the molecular mechanisms underlying heterosis in clonally propagated crops are largely unknown.Potato(Solanum tuberosum L.)is the most important tuber crop and an ongoing revolution is transforming potato from a clonally propagated tetraploid crop into a seed-propagated diploidhybrid potato.In our previous study,we developed the first generation of highly homozygous inbred lines of potato and hybrids with strong heterosis.Here,we integrated transcriptome,metabolome,and DNA methylation data to explore the genetic and molecular basis of potato heterosis at three developmental stages.We found that the initial establishment of heterosis in diploid potato was mainly due to dominant complementation.Flower color,male fertility,and starch and sucrose metabolism showed obvious gene dominant complementation in hybrids,and hybrids devoted more energy to primary metabolism for rapid growth.In addition,we identified~2700 allele-specific expression genes at each stage,which likely function in potato heterosis and might be regulated by CHH allele-specific methylation level.Our multi-omics analysis provides insight into heterosis in potato and facilitates the exploitation of heterosis in potato breeding.