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Abstract Background This study aimed to predict metastasis risk and identify prognostic factors of gastrointestinal signet ring cell carcinoma (SRCC) using data from the SEER database, the largest cancer dataset in North America. Methods Data were obtained from the SEER database, covering 17 cancer registries from 2004 to 2020. Demographic and clinical data included sex, age, race, tumor location, size, pathological grade, stage, overall survival time, and treatment modalities. Statistical analyses were conducted using SPSS and R software. Propensity Score Matching (PSM) ensured comparable baseline characteristics between gastric cancer (GC) and colorectal cancer (CRC) groups. LASSO regression analysis identified predictors of metastasis, leading to the construction of predictive models using the lrm function in R. Nomograms were visualized with the “rms” package and assessed via ROC curves, calibration curves, and decision curve analysis (DCA). Cox regression analyses identified prognostic indicators for overall survival (OS), and Kaplan–Meier curves compared OS between high-risk and low-risk groups. Results From 2004 to 2020, 7680 SRCC patients were identified, including 4980 GC and 2700 CRC patients. CRC patients were older and had larger tumors, higher staging, and worse differentiation. Nomograms demonstrated good discriminative ability, with AUCs of 0.704 and 0.694 for GC, and 0.694 and 0.701 for CRC in training and validation cohorts, respectively. The DCA curve indicates that this predictive model has a high gain in predicting metastasis and OS. Conclusions The nomograms effectively predicted metastasis risk and OS in metastatic SRCC patients, offering clinical utility in stratifying patients and guiding treatment decisions, thereby enhancing personalized treatment approaches.

Abstract An increasing number of studies indicate that long noncoding RNAs (lncRNAs) play important roles in tumour proliferation, migration and other vital processes and are expected to become novel biomarkers for early cancer screening. The expression of the lncRNA NBR2 (adjacent breast cancer suppressor BRCA1) has been found to decrease in several cancer types. However, it is still unknown whether the lncRNA NBR2 is involved in breast cancer and autophagy. According to the Kaplan–Meier plotter survival curve analysis, the survival rate of the group with high lncRNA-NBR2 expression was higher than that of the group with low lncRNA-NBR2 expression. The suppression of cancer cell proliferation, invasion and migration by the lncRNA NBR2 has been demonstrated, suggesting that this lncRNA is involved in the development and progression of cancer. Our subsequent study revealed that the lncRNA NBR2 inhibited autophagy in breast cancer cells, and that starvation conditions enhanced this inhibitory effect. Moreover, this lncRNA changed the proliferation ability of breast cancer cells by affecting protective autophagy. The aim of this study was to investigate the link between starvation and lncRNAs by evaluating changes in autophagy-related proteins, cell proliferation and other biological processes. Together, these studies provide strategies for the early screening of breast cancer and suggest that starvation therapy can be used as a new approach for the treatment of cancer.