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Additional File 8: Table S3. Analysis of SETD8 mutations and predicting the functional effects by silico analysis.

Additional File 1: Figure S1. TMB for SETD8 WT and SETD8 Mutant specimens in the WES cohort.

Additional File 5: Figure S5. UNC0379 sensitizes cervical cancer cells to cisplatin treatment in vitro.

Additional File 2: Figure S2. 53BP1 recruitment decreased after SETD8 knockdown in SiHa and CaSki with cisplatin treatment.

Additional File 3: Figure S3.SETD8 mutation can affect the methyltransferase activity on H4K20 and SETD8 correlated with H4K20me1/2 and γ-H2AX levels before and after cisplatin chemotherapy.

Additional File 4: Figure S4. UNC0379 increased apoptosis inducted by cisplatin and impaired NHEJ repair efficiency in vivo and in vitro.

Additional File 6: Table S1. Patient characteristics of NACT Cohort.

Simultaneous sources acquisition, also referred to as “blended acquisition”, involves recording two or more shots simultaneously. It allows for denser spatial sampling and can greatly speed up the field data acquisition. Thus, it has potential advantage to improve seismic data quality and reduce acquisition cost. In order to achieve the goal of blended acquisition, a deblending procedure is necessary. It attenuates the interference and thus improves the resolution of the pre-stack time migration image. In this paper, we propose an efficient deblending method, which applies frequency-varying median and mean filters to cross-spread azimuth-offset gathers (XSPR-AO). The method can be used with variable window sizes according to the characteristics of the interference. The effectiveness of the method is validated by a field data example.

Neoadjuvant chemotherapy (NACT) remains an attractive alternative for controlling locally advanced cervical cancer. However, approximately 15–34% of women do not respond to induction therapy. To develop a risk stratification tool, 56 patients with stage IB‐IIB cervical cancer are included in 2 research centers from the discovery cohort. Patient‐specific somatic mutations led to NACT non‐responsiveness are identified by whole‐exome sequencing. Next, CRISPR/Cas9‐based library screenings are performed based on these genes to confirm their biological contribution to drug resistance. A 15‐gene classifier is developed by generalized linear regression analysis combined with the logistic regression model. In an independent validation cohort of 102 patients, the classifier showed good predictive ability with an area under the curve of 0.80 (95% confidence interval (CI), 0.69–0.91). Furthermore, the 15‐gene classifier is significantly associated with patient responsiveness to NACT in both univariate (odds ratio, 10.8; 95% CI, 3.55–32.86; p = 2.8 × 10−5) and multivariate analysis (odds ratio, 17.34; 95% CI, 4.04–74.40; p = 1.23 × 10−4) in the validation set. In conclusion, the 15‐gene classifier can accurately predict the clinical response to NACT before treatment, representing a promising approach for guiding the selection of appropriate treatment strategies for locally advanced cervical cancer., In a multicenter study of 158 patients with stage IB‐IIB cervical cancer, a 15‐core‐gene classifier is developed by integrated analysis of whole‐exome sequencing and CRISPR library screening. By predicting cervical cancer patients who would benefit from neoadjuvant chemotherapy, the classifier has the potential to guide the proper selection of treatment modalities, implicating a significant advance toward individualizing therapy.