Background. BRAF exon 15 p.V600E (BRAF V600E) mutation has been established as an important molecular marker for papillary thyroid carcinoma diagnosis by ultrasound-guided fine-needle aspiration biopsy (FNAB). Sanger sequencing is the gold standard for detecting BRAF V600E mutations but fails to identify low-frequency mutations. However, droplet digital PCR (ddPCR) is a popular new method for detecting low-frequency mutations. Here, we compare the efficiency of droplet digital PCR (ddPCR) and Sanger sequencing for detection of the BRAF V600E mutation in thyroid fine-needle aspiration (FNA) samples. Methods. Thyroid fine-needle aspiration samples from 278 patients with 310 thyroid nodules were collected. Sanger sequencing and ddPCR were conducted to detect the BRAF V600E mutation. Results. The BRAF V600E mutation was found in 94 nodules (30.32) by ddPCR and 40 nodules (12.90) by Sanger sequencing in 310 FNA samples. A total of 119 nodules were confirmed PTC by postsurgical pathology. Among which the BRAF mutation was found in 80 (67.23) nodules by ddPCR and 31 (26.05) by Sanger sequencing. All nodules carrying the mutation detected by Sanger sequencing (SS+) were verified by ddPCR (ddPCR+). Also, all nodules with no mutation detected by ddPCR were interpreted as wild-type by Sanger sequencing (SS). In addition. Almost all SS+/ddPCR+nodules (95.00; 38/40) and SS/ddPCR+nodules (100.00; 54/54) displayed a BRAF mutation rate of >5 and <15, respectively, indicating easy misdetection by Sanger sequencing when the mutation rate is between 5 and 15. Conclusion. ddPCR has higher sensitivity than Sanger sequencing and we propose ddPCR as a supplement to Sanger sequencing in molecular testing of BRAF using FNAB samples.

Major histocompatibility complex (MHC) could serve as a potential biomarker for tumor immunotherapy, however, it is not yet known whether MHC could distinguish potential beneficiaries. Single‐cell RNA sequencing datasets derived from patients with immunotherapy were collected to elucidate the association between MHC and immunotherapy response. A novel MHCsig was developed and validated using large‐scale pan‐cancer data, including The Cancer Genome Atlas and immunotherapy cohorts. The therapeutic value of MHCsig was further explored using 17 CRISPR/Cas9 datasets. MHC-related genes were associated with drug resistance and MHCsig was significantly and positively associated with immunotherapy response and total mutational burden. Remarkably, MHCsig significantly enriched 6% top‐ranked genes, which were potential therapeutic targets. Moreover, we generated Hub-MHCsig, which was associated with survival and disease-special survival of pan-cancer, especially low-grade glioma. This result was also confirmed in cell lines and in our own clinical cohort. Later low-grade glioma-related Hub-MHCsig was established and the regulatory network was constructed. We provided conclusive clinical evidence regarding the association between MHCsig and immunotherapy response. We developed MHCsig, which could effectively predict the benefits of immunotherapy for multiple tumors. Further exploration of MHCsig revealed some potential therapeutic targets and regulatory networks.