[Clinicopathological features and prognostic factors of patients with lung metastasis of stage â a~â ¢b cervical cancer].

Objective: To investigate the clinicopathological features and prognostic factors of lung metastasis in patients with cervical cancer after treatment. Methods: The clinicopathological data of 191 patients with lung metastasis of stage Ⅰa-Ⅲb cervical cancer (FIGO 2009 stage) treated in Sichuan Cancer Hospital from January 2007 to December 2020 were analyzed retrospectively. Kaplan Meier method and Log rank test were used for survival analysis, and Cox regression model was used for prognostic factors analysis. Results: Among 191 patients with lung metastasis of cervical cancer, pulmonary metastasis was found in 134 patients (70.2%) during follow-up examination, and 57 patients (29.8%) had clinical symptoms (cough, chest pain, shortness of breath, hemoptysis, and fever). The time from the initial treatment of cervical cancer to the discovery of lung metastasis was 1-144 months in the whole group, with a median time of 19 months. Univariate analysis of the prognosis of lung metastasis after treatment of cervical cancer showed that the diameter of cervical tumor, lymph node metastasis, positive surgical margin, disease-free interval after treatment of cervical cancer, whether it is accompanied by other metastasis, the number, location and maximum diameter of lung metastasis, and the treatment method after lung metastasis are related to the prognosis of patients with lung metastasis of cervical cancer. Multivariate analysis showed that the number of lung metastases and other site metastases in addition to lung metastases were independent factors affecting the prognosis of patients with lung metastases of cervical cancer (P<0.05). Conclusions: For patients with cervical cancer, attention should be paid to chest CT examination during follow-up to guard against the possibility of lung metastasis after treatment. Besides lung metastasis, other site metastasis and the number of lung metastasis are independent factors affecting the prognosis of patients with lung metastasis of cervical cancer. For patients with lung metastasis after treatment of cervical cancer, surgical treatment is an effective treatment. It is necessary to strictly grasp the surgical indications, and some patients can achieve long-term survival. For patients with lung metastasis of cervical cancer who are not suitable for resection of lung metastasis, the remedial treatment of chemotherapy with or without radiotherapy is still a recommended choice.

[Analysis of factors related to the prognostic benefit of neoadjuvant chemotherapy followed by interval debulking surgery in patients with advanced ovarian cancer].

Objective: To explore the prognostic factors of patients with advanced epithelial ovarian cancer (EOC) who received neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS). Methods: The clinical and pathological data of patients with stage Ⅲc-Ⅳ EOC underwent surgical treatment in Sichuan Cancer Center from January 1st, 2014 to December 31th, 2018 were retrospectively analyzed, and the prognosis was followed up. Results: (1) A total of 216 EOC patients were included in the study, whose age was (52.1±8.7) years old, the median follow-up time was 44.6 months (17.2-80.1 months), the median progression free survival (PFS) was 11.1 months (8.5-13.8 months), and the median overall survival (OS) was 40.0 months (32.7-47.3 months). (2) Among 216 patients with advanced EOC, there were 75 cases in the primary debulking surgery (PDS) group and 141 cases in the NACT+IDS group. Compared with the PDS group, the serum CA125 level before treatment (median: 859.4 vs 1 371.0 kU/L), proportion of stage Ⅳ patients [5.3% (4/75) vs 23.4% (33/144)] and no visible residual disease (R0) cytoreduction rate in the NACT+IDS group were significantly higher [(41.3% (31/75) vs 61.7% (87/144); all P<0.05]. The median PFS in the NACT+IDS group was significantly shorter than that of the PDS group (9.1 vs 15.2 months; χ2=7.014, P=0.008), but there was no significant difference in the median OS between the two groups (42.6 vs 38.0 months; χ2=1.325, P=0.250). (3) Univariate analysis showed that body mass index (BMI), preoperative serum CA125 level, surgical-pathological stage, NACT effect, postoperative residual tumor size, time to initiation of postoperative chemotherapy and chemotherapy regimen were significantly correlated with PFS in the NACT+IDS group (all P<0.05); preoperative serum CA125 level, surgical-pathological stage, NACT effect, postoperative residual tumor size, postoperative chemotherapy regimen were significantly related with OS in the NACT+IDS group (all P<0.05). Multivariate analysis showed that BMI, postoperative residual tumor size, time to initiation of postoperative chemotherapy were independent factors of PFS in the NACT+IDS group (all P<0.05); preoperative serum CA125 level, surgical-pathological stage, postoperative residual tumor size were independent factors of OS in the NACT+IDS group (all P<0.05). The results showed that the PFS of patients with normal preoperative serum CA125 level and (or) chemotherapy ≤7 days after IDS was longer, while no significant difference comparable with those in the PDS group (P>0.05), and OS was also showing an prolonged trend, but the difference was also not statistically significant (P>0.05). Conclusions: Normal CA125 before IDS and time received chemotherapy no longer than 7 days after IDS are two related factors of prognosis benefit in advance EOC patients treated with NACT+IDS. Therefore, timely adjustment of the dose and regimen of NACT to reduce CA125 level to normal range in about three cycles before IDS, and strengthen IDS perioperative management to promote postoperative recovery and perform chemotherapy as soon as possible might help to improve the prognosis of patients.

Prediction of RNA-binding proteins by voting systems.

It is important to identify which proteins can interact with RNA for the purpose of protein annotation, since interactions between RNA and proteins influence the structure of the ribosome and play important roles in gene expression. This paper tries to identify proteins that can interact with RNA using voting systems. Firstly through Weka, 34 learning algorithms are chosen for investigation. Then simple majority voting system (SMVS) is used for the prediction of RNA-binding proteins, achieving average ACC (overall prediction accuracy) value of 79.72% and MCC (Matthew's correlation coefficient) value of 59.77% for the independent testing dataset. Then mRMR (minimum redundancy maximum relevance) strategy is used, which is transferred into algorithm selection. In addition, the MCC value of each classifier is assigned to be the weight of the classifier's vote. As a result, best average MCC values are attained when 22 algorithms are selected and integrated through weighted votes, which are 64.70% for the independent testing dataset, and ACC value is 82.04% at this moment.