China is one of the countries with the highest incidence of gastric cancer. There are differences in epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selection between gastric cancer patients from the Eastern and Western countries. Non‐Chinese guidelines cannot specifically reflect the diagnosis and treatment characteristics for the Chinese gastric cancer patients. The Chinese Society of Clinical Oncology (CSCO) arranged for a panel of senior experts specializing in all sub‐specialties of gastric cancer to compile, discuss, and revise the guidelines on the diagnosis and treatment of gastric cancer based on the findings of evidence‐based medicine in China and abroad. By referring to the opinions of industry experts, taking into account of regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted experts’ consensus judgement on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes. This guideline uses tables and is complemented by explanatory and descriptive notes covering the diagnosis, comprehensive treatment, and follow‐up visits for gastric cancer.

Mechanisms of resistance to anti-EGFR therapy in colorectal cancer

Tumor-associated macrophages have emerged as crucial factors for metastases. Microglia are indispensable components of the brain microenvironment and play vital roles in brain metastasis (BM). However, the underlying mechanism of how activated microglia promote brain metastasis of non-small cell lung cancer (NSCLC) remains elusive. Here, we purified cell lines with brain-metastatic tropism and employed a co-culture system to reveal their communication with microglia. By single-cell RNA-sequencing and transcriptome difference analysis, we identified IL6 as the key regulator in brain-metastatic cells (A549-F3) to induce anti-inflammatory microglia via JAK2/STAT3 signaling, which in turn promoted the colonization process in metastatic A549-F3 cells. In our clinical samples, patients with higher levels of IL6 in serum showed higher propensity for brain metastasis. Additionally, the TCGA (The Cancer Genome Atlas) data revealed that NSCLC patients with a lower level of IL6 had a longer overall survival time compared to those with a higher level of IL6. Overall, our data indicate that the targeting of IL6/JAK2/STAT3 signaling in activated microglia may be a promising new approach for inhibiting brain metastasis in NSCLC patients.

Introduction: Since the outbreak of coronavirus disease 2019 (COVID-19), more than 3000 (including clinical diagnosis) healthcare workers (HCWs) have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China. This study is aimed to investigate the risk perception and immediate psychological state of HCWs in the early stage of the COVID-19 epidemic. Methods: This study utilized a cross-sectional survey designed on a convenient sample of 4357 HCWs in China. Its data were collected using anonymous structured questionnaires distributed through social software. 6 questions were set to evaluate the participants’ risk perception of COVID-19, and a General Health Questionnaire was used to identify the participants’ immediate psychological status. Descriptive statistics were used for data analysis. Risk perception and psychological status were compared by demographic characteristics and COVID-19 exposure experiences. Result: A total of 4,600 questionnaires were distributed, and 4,357 qualified ones (94.7%) were collected. The main concerns of HCWs are: infection of colleagues (72.5%), infection of family members (63.9%), protective measures (52.3%) and medical violence (48.5%). And 39.1% of the HCWs had psychological distress, especially working in Wuhan, participating in frontline treatments, having been isolated and having family members or colleagues infected. Conclusions: The finding indicating that, faced with the COVID-19 epidemic, HCWs, especially in Wuhan, were worried about the risks of infection and protective measures, resulting in psychological distress, so further actions should be taken.

Purpose: In search of reliable biologic markers to predict the risk of normal tissue damage by radio(chemo)therapy before treatment, we investigated the association between single nucleotide polymorphisms (SNPs) in the transforming growth factor 1 (TGFβ1) gene and risk of radiation pneumonitis (RP) in patients with non–small-cell lung cancer (NSCLC). Patients and Methods: Using 164 available genomic DNA samples from patients with NSCLC treated with definitive radio(chemo)therapy, we genotyped three SNPs of the TGFβ1 gene (rs1800469:C-509T, rs1800471:G915C, and rs1982073:T869C) by polymerase chain reaction restriction fragment length polymorphism method. We used Kaplan-Meier cumulative probability to assess the risk of grade ≥ 3 RP and Cox proportional hazards analyses to evaluate the effect of TGFβ1 genotypes on such risk. Results: There were 90 men and 74 women in the study, with median age of 63 years. Radiation doses ranging from 60 to 70 Gy (median = 63 Gy) in 30 to 58 fractions were given to 158 patients (96.3%) and platinum-based chemotherapy to 147 (89.6%). Grade ≥ 2 and grade ≥ 3 RP were observed in 74 (45.1%) and 36 patients (22.0%), respectively. Multivariate analysis found CT/CC genotypes of TGFβ1 rs1982073:T869C to be associated with a statistically significantly lower risk of RP grades ≥ 2 (hazard ratio [HR] = 0.489; 95% CI, 0.227 to 0.861; P = .013) and grades ≥ 3 (HR = 0.390; 95% CI, 0.197 to .774; P = 0.007), respectively, compared with the TT genotype, after adjustment for Karnofsky performance status, smoking status, pulmonary function, and dosimetric parameters. Conclusion: Our results showed that CT/CC genotypes of TGFβ1 rs1982073:T869C gene were associated with lower risk of RP in patients with NSCLC treated with definitive radio(chemo)therapy and thus may serve as a reliable predictor of RP.

Artificial intelligence (AI) has been widely used in various medical fields, such as image diagnosis, pathological classification, selection of treatment schemes, and prognosis analysis. Especially in the image-aided diagnosis of tumors, the cooperation of human-computer interactions has become mature. However, the ethics of the application of AI as an emerging technology in clinical decision-making have not been fully supported, so the clinical decision support system (CDSS) based on AI technology has not fully realized human-computer interactions in clinical practice as the image-aided diagnosis system. The CDSS was currently used and promoted worldwide including Watson for Oncology, Chinese society of clinical oncology-artificial intelligence (CSCO AI) and so on. This paper summarized the applications and clarified the principle of AI in CDSS, analyzed the difficulties of AI in oncology decisions, and provided a reference scheme for the application of AI in oncology decisions in the future.