PAK5

The genetic heterogeneity of non-small cell lung cancer (NSCLC) may impact clinical response and outcomes to targeted therapies. In second-line osimertinib treatment for NSCLC, real-world data on genetic biomarkers for treatment efficacy and prognosis remain incomplete. This real-world study involved 68 NSCLC patients receiving first-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). All of these patients developed resistance, and 49 of them subsequently underwent second-line osimertinib treatment. A 639-gene DNA panel was employed to assess the impact of molecular alterations on treatment efficacy, clinical outcomes and resistance. The findings showed that the median progression-free survival (PFS) for second-line osimertinib therapy was 13.3 months. Genes alterations such as P21 (RAC1) activated kinase 5 (PAK5), RNA binding motif protein 10 (RBM10), and EPH receptor A3 (EPHA3) mutations were associated with significantly shorter PFS in osimertinib therapy. At multivariate analysis, they were all independent risk predictors of shorter PFS. Additionally, the median overall survival (OS) for osimertinib was 26.2 months. Glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A), hepatocyte growth factor (HGF), and RBM10 mutations were significantly associated with poorer OS in osimertinib treatment. The multivariate analysis demonstrated that only RBM10 mutation emerged as an independent risk predictor of shorter OS. In vitro experiments showed that RBM10 mutations could promote the proliferation and migration ability of NSCLC cells and reduced cell apoptosis. The resistance mechanisms to osimertinib were heterogeneous. Histone cluster 1 H2B family member D (HIST1H2BD) acted as a novel resistance mechanism to osimertinib. Previously unreported HIST1H2BD mutations (p.K25Q and p.E36D) were detected in the NSCLC tissues. In vitro experiments confirmed that HIST1H2BD mutations led to resistance to osimertinib. In summary, we demonstrate that genetic biomarkers, such as PAK5, RBM10, and EPHA3, are independent predictors of PFS in second-line osimertinib treatment, with RBM10 emerging as an independent predictor of OS. Additionally, HIST1H2BD represents a novel resistance mutation to osimertinib. All of these findings offer valuable insights for making personalized treatment strategies for NSCLC patients.

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients' survival under immunotherapy, and could provide valuable assistance for clinical practice.

This study aimed to identify genomic regions, pathways, and putative candidate genes associated with resistance to gastrointestinal nematode in Santa Ines sheep. The phenotypic information comprised 5529 records from 1703 naturally infected animals. After genomic data quality control, 37,511 SNPs from 589 animals were available. The weighted single-step approach for genome-wide association study was performed to estimate the SNP effects and variances accounted by 10-SNP sliding windows. Confirming the polygenic nature of the studied traits, 20, 22, 21, and 19 genomic windows that explained more than 0.5% of the additive genetic variance were identified for fecal egg counts (FEC), Famacha© (FAM), packed cell volume (PCV), and total plasma protein (TPP), respectively. A total of 81, 122, 106, and 101 protein-coding genes were found in windows associated with FEC, FAM, PCV, and TPP, respectively. Several protein-coding genes related to the immune system and inflammatory response functions were identified within those genomic regions, such as ADCY9, ADRB2, BRAF, CADM1, CCL20, CD70, CREBBP, FNBP1, HTR4, IL16, IL22, IL26, MAPK8, NDFIP1, NLRC3, PAK5, PLCB1, PLCB4, ROCK1, TEK, TNFRSF12A, and VAV1. Functional enrichment analysis by DAVID tool also revealed many significant (P < 0.05) pathways and Gene Ontology terms that could be related to resistance to gastrointestinal nematode in Santa Ines sheep, such as chemokine signaling pathway (oas04062), cAMP signaling pathway (oas04024), cGMP-PKG signaling pathway (Oas04022), platelet activation (Oas04611), Rap1 signaling pathway (oas04015), and oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen (GO:0016705). These results contribute to improving the knowledge of the genetic architecture of resistance to gastrointestinal nematode in Santa Ines sheep.