Most patients with pancreatic cancer are already in the locally advanced or metastatic stage at initial diagnosis. While systemic chemotherapy provides clinical benefits for those with mid-to-late-stage pancreatic cancer, its efficacy is often limited by patient tolerance. In response to the dual clinical demands of robust antitumor activity and high targeting specificity, antibody-drug conjugate (ADC) has emerged as a promising solution. By conjugating highly selective monoclonal antibodies with potent cytotoxic small-molecule drugs, ADC achieves precise tumor-targeting while minimizing damage to healthy tissues, which thereby improves treatment tolerance. However, due to the complex pathological features of pancreatic cancer, no ADC has yet been approved for clinical use for this disease. A comprehensive evaluation of factors including ADC-specific targets, payload selection, antibody-drug linkage strategies, drug delivery mechanisms, tissue distribution variability, and tumor heterogeneity will be crucial to advancing the clinical translation of ADC for pancreatic cancer treatment.

The effective local management of oligometastatic non-small cell lung cancer (NSCLC) has the potential to prolong patients' survival. The role of radiotherapy as a local treatment modality in patients with oligometastatic NSCLC, whether as first-line therapy or consolidation therapy, remains uncertain. Several studies have demonstrated that stereotactic ablative radiotherapy can offer clinical benefits for patients with oligometastatic NSCLC without increasing adverse reactions. Furthermore, the exploration of the potential synergistic effects of combining radiotherapy and immunotherapy on extending progression-free survival and overall survival in patients with oligometastatic NSCLC is also a topic worthy of attention.

Small bowel capsule endoscopy and double-balloon enteroscopy have become new methods for clinical diagnosis of radiation enteritis (RE) , especially for abnormal intestinal tissue. Targeted biopsy or interventional therapy is expected to achieve precision treatment of RE. The screening of molecular markers in biological samples has also become a new direction for RE diagnosis. Fecal microbiota transplantation has become one of the promising treatments for RE. In addition, mechanism studies based on traditional Chinese medicine, targeted cell death, and omics analysis provide rich strategies for the diagnosis and treatment of RE.

Objective:To investigate the feasibility of individualized primary clinical target volume (CTV) delineation in intensity-modulated radiotherapy for nasopharyngeal carcinoma (NPC).Methods:Clinical data of 87 consecutive patients newly diagnosed with lateralized NPC in Jiangsu Cancer Hospital between October 2016 and February 2018 were retrospectively analyzed. Lateralized NPC is defined as tumor invasion not exceeding the contralateral wall. According to the tumor spread, the primary CTV was optimized as follows: CTV2 only covered the medial part of the contralateral pterygopalatine fossa, whereas the contralateral foramen oval was not included; on the level of parapharyngeal space, the contralateral side of CTV only covered the posterior lateral lymph nodes, whereas the contralateral internal jugular vein was not regularly covered. Failure patterns and 5-year survival [local control rate (LCR), progression-free survival (PFS) and overall survival (OS)] were evaluated by Kaplan-Meier method. Paired t-test and rank-sum test were used to analyze the dose variation in the optimized region and adverse reactions. Results:The median follow-up time was 59.5 months. The 5-year LCR, PFS, and OS were 98.9%, 86.5% and 92.1%, respectively. There was no local recurrence in the optimized area of CTV. Dosimetric comparison results showed that the doses of parotid gland, temporal lobe, cochlea and middle ear on the contralateral side were reduced by 13.45%, 9.14%, 38.83%, and 29.36%, respectively. Four cases (4.6%) developed grade 3 hearing loss, all on the ipsilateral side. The optimized scheme significantly alleviated the hearing loss on the contralateral side compared to that on the ipsilateral side ( P<0.001). Other grade 3 late adverse reactions included cranial nerve injury, subcutaneous fibrosis in the neck and visual impairment, with 1 case each. Conclusion:Individualized primary CTV for lateralized NPC is feasible and safe, with obvious dosimetric advantages and reduced adverse reaction rate, which is worthy of clinical promotion.

Objective:To analyze the efficacy, safety and prognostic factors of immune checkpoint inhibitors in the treatment of recurrent and metastatic cervical cancer.Methods:A total of 87 patients with recurrent and metastatic cervical cancer admitted to the First Affiliated Hospital of Soochow University from January 2018 to June 2022 were retrospectively analyzed. They were divided into non immunotherapy group ( n=32) and immunotherapy group ( n=55) according to whether immune checkpoint inhibition was applied after recurrence and metastasis. The disease control rate (DCR), progression free survival (PFS), overall survival 1 (OS1, date of pathology diagnosis to the end of follow-up or time of death), overall survival 2 (OS2, time of first immunotherapy/non-immunotherapy to the end of follow-up or time of death), safety and prognostic factors of the two groups were analyzed and compared. Results:In 87 patients with recurrent and metastatic cervical cancer, the DCR of the non immunotherapy group and immunotherapy group were 53.1% (17/32) and 72.7% (40/55) respectively ( χ2=3.44, P=0.064). The median OS1 of the non immunotherapy group was 51.0 months, while the immunotherapy group did not reach the median OS1, with a statistically significant difference ( χ2=7.50, P=0.006). The median OS2 of the non immunotherapy group was 28.0 months, while the immunotherapy group did not reach the median OS2, with a statistically significant difference ( χ2=7.07, P=0.008). The median PFS of the non immunotherapy group and immunotherapy group were 18.0 months and 23.0 months respectively, with no significant difference ( χ2=0.01, P=0.915). In the immunotherapy group, 70.9% (39/55) of patients received immune checkpoint inhibitors as first-line treatment and 29.1% (16/55) received as second-line and above treatment. Both groups of patients did not achieve median OS2, with median PFS of 23.0 and 17.0 months respectively, and there were no statistically significant differences ( χ2=0.94, P=0.333; χ2=2.00, P=0.158) ; 38.2% (21/55) of patients received immune checkpoint inhibitor combined with local radiotherapy, 61.8% (34/55) patients did not receive radiotherapy. And neither group of patients achieved median OS2, with median PFS of 19.0 and 25.0 months respectively, with no statistically significant differences ( χ2=0.62, P=0.432; χ2=0.01, P=0.906). The incidences of grade 1-2 hematuria and hypothyroidism in the non immunotherapy group and immunotherapy group were 53.1% (17/32) vs. 27.3% (15/55, χ2=5.82, P=0.016), 3.1% (1/32) vs. 21.8% (12/55, χ2=4.19, P=0.041) respectively. The incidence of myelosuppression in the non immunotherapy group [grade 1-2: 59.4% (19/32), grade 3-4: 34.4% (11/32) ] was significantly different from that in the immunotherapy group [grade 1-2: 80.0% (44/55), grade 3-4: 3.6% (2/55) ; Z=3.50, P<0.001]. There were no statistically significant differences between creatinine increase, glutamic-oxaloacetic transaminase and glutamic-pyruvic transaminase increase, lymphocyte decrease, hypoproteinemia, proteinuria, rash, fatigue (all P>0.05). Univariate regression analysis showed that the use of immune checkpoint inhibitor was an independent protective factor affecting the prognosis of patients ( HR=0.31, 95% CI: 0.12-0.77, P=0.012) . Conclusion:Whether used as first-line or second-line or above treatment, the use of immune checkpoint inhibitors in patients with recurrent and metastatic cervical cancer prolongs their OS1, OS2, and has good safety. The application of immune checkpoint inhibitors is an independent protective factor affecting the prognosis of patients.

Brain metastases are one of the most common distant metastases in patients with non-small cell lung cancer (NSCLC), and the prognosis will be extremely poor. The effect of chemotherapy and operation is limited. As a standard treatment, radiotherapy is widely used in clinical practice. Radiotherapy alone includes whole brain radiotherapy, stereotactic radiotherapy and whole brain radiotherapy combined with stereotactic radiotherapy. With the continuous development of radiotherapy and the progress of gene sequencing, radiotherapy has been combined with targeted drugs, anti-angiogenic drugs and immunodrugs in the treatment of NSCLC brain metastasis, which can improve the survival of patients with NSCLC brain metastasis.

Cisplatin-based systemic chemotherapy combined with external beam radiation followed by intracavitary brachytherapy (ICBT) has become the standard treatment modality for locally advanced cervical cancer. Benefiting from the improvement in the imaging accuracy of medical imaging equipment and the development of image fusion technology, ICBT has developed into image-guided brachytherapy (IGBT) rather than the mode relying only on single image guidance. Factors such as the selection of a suitable image acquisition technology and the optimization of the multimodal imaging fusion strategy to reduce the dose deviation of IGBT are the key to the success of cervical cancer treatment. Radiotherapy practice is also plagued by these factors. Deep learning-based artificial intelligence technology has emerged in constructing intelligent radiotherapy platforms and solutions and has become an important means of solving the key problems in the multi-modal fusion IGBT for cervical cancer. Moreover, this technology is also a new way to improve the overall diagnosis and treatment level of cervical cancer, reduce the workload of physicians, and popularize the radiotherapy experience in grassroots organizations.

Objective:To investigate the prognostic factors of oligometastatic (OM) non-small cell lung cancer (NSCLC) patients and the safety and effectiveness of early radiotherapy intervention.Methods:A retrospective analysis was conducted, including 159 OM NSCLC cases (metastatic sites≤5, metastasis organs≤3) admitted to Department of Radiation Oncology in First Affiliated Hospital of Soochow University from January 2015 to December 2018. Among 159 cases, there were 107 males and 52 females, with the median age of 63 years. 137 cases were administrated via early radiotherapy intervention, and 22 cases via delayed radiotherapy intervention. The receiver operating characteristic curve (ROC) was used to determine the progression-free survival time (PFS)/overall survival time (OS) to ascertain the best cut-off value for local control and prognosis. Survival analysis was calculated by Kaplan-Meier curves, and Log rank test was used for comparison of these curves. Cox proportional hazards regression model was used for multivariate survival analysis.Results:The median follow-up time of 159 cases was 28.2 months. During the follow-up period, there were 16 cases with complete remission (10.1%), 53 cases with partial remission (33.3%), 27 cases with stable disease (17.0%), and 63 cases with progressed disease(39.6%). The local control rates at 3, 6 and 12 months were 83.9%, 59.7% and 41.0%, respectively. The median progression-free survival (PFS) of 159 patients was 8.0 months, the median survival time (OS) was 35.0 months, and 1, 2, and 3-year survival rates were 77.3%, 63.0% and 45.1%, respectively. Adverse reactions related to radiotherapy were relatively mild, mostly grade 1 and 2. PFS/OS= 0.3 is the best cut-off value for determining the patient′s local control and prognosis. The result of univariate analysis showed that gender, number of OM organs, T staging, radiotherapy intervention mode, tumor target volume absorbed dose (DT-GTVnx), PFS/OS were significantly related to median PFS ( χ2=4.175, 16.508, 4.408, 10.300, 6.842, 38.175, P<0.05); gender, pathological type, number of OM organs, initial diagnosis stage, T stage, N stage, lobectomy, radiotherapy intervention mode, tumor target volume (V-GTVnx), tumor load, local control status were significantly related to median OS ( χ2=6.672, 8.330, 21.299, 5.398, 6.874, 6.893, 5.611, 115.206, 4.017, 5.110, 21.299, P< 0.05). The result of multivariate analysis showed that delayed radiotherapy intervention ( HR=3.728, 95% CI 2.099-6.622, P<0.001) was an independent risk factor for PFS in patients with OM NSCLC, and PFS/OS>0.3 ( HR=0.123, 95% CI 0.062-0.246, P<0.001) was an independent protective factor for PFS in patients with OM NSCLC; male ( HR=1.665, 95% CI 1.024-3.043, P=0.033), high tumor burden ( HR=2.113, 95% CI 1.088-4.107, P=0.027), delayed radiotherapy interventions ( HR=15.076, 95% CI 7.925-28.680, P<0.001) were independent risk factors for OS in patients with OM NSCLC. Conclusions:OS of patients with OM NSCLC is significantly prolonged in female, low tumor burden and early radiotherapy intervention. Early radiotherapy intervention significantly improved the prognosis, and radiotherapy-related adverse reactions could be tolerated. These might suggest that local radiotherapy is safe and effective in the treatment of OM NSCLC patients.

Objective To effectively use the clinical data generated in daily operation and to realize information networking based on the existing resources of radiotherapy department. To improve quality management efficiency in radiotherapy process. Methods The radiotherapy process and required documents were analyzed. The reporting tool Microsoft Report Builder, which is based on SQL database, was applied to design the patient documents by extracting and analyzing a large number of data generated by Aria, the existing network of our radiotherapy department. PDCA Tools was used to analyze the weak links in the process. Reports with quantitative indices have been designed according to corresponding countermeasures, so as to improve quality control level of the process. Results More than one thousand patients were treated in our department since 2020. All patient documents of radiotherapy can be archived and inquired online after registration only once. 13 daily statistical reports, 5 quarters and 3 annual reports were scheduled according to practical demands. The waiting time before radiotherapy was shortened from 16.2 days to 14.8 days after operating the reporting system 3 months later. The staff could master the treatment progress of patients easily and patients who interrupted the treatment were found in time. Conclusion The reporting tools can realize patient information extraction and networked management effectively in radiotherapy process. Staff efficiency of personnel work and communication was improved. The resource allocation was optimized according to the report data in real time, improving the efficiency and quality of radiotherapy. This method is generally applicable and practical to radiotherapy department.

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.