Cancer prevalence among the rural poverty-stricken population in Northeast China

The innovative model based on artificial intelligence algorithms to predict recurrence risk of patients with postoperative breast cancer

Purpose

This study aimed to develop a machine learning model to retrospectively study and predict the recurrence risk of breast cancer patients after surgery by extracting the clinicopathological features of tumors from unstructured clinical electronic health record (EHR) data.

Methods

This retrospective cohort included 1,841 breast cancer patients who underwent surgical treatment. To extract the principal features associated with recurrence risk, the clinical notes and histopathology reports of patients were collected and feature engineering was used. Predictive models were next conducted based on this important information. All algorithms were implemented using Python software. The accuracy of prediction models was further verified in the test cohort. The area under the curve (AUC), precision, recall, and F1 score were adopted to evaluate the performance of each model.

Results

A training cohort with 1,289 patients and a test cohort with 552 patients were recruited. From 2011 to 2019, a total of 1,841 textual reports were included. For the prediction of recurrence risk, both LSTM, XGBoost, and SVM had favorable accuracies of 0.89, 0.86, and 0.78. The AUC values of the micro-average ROC curve corresponding to LSTM, XGBoost, and SVM were 0.98 ± 0.01, 0.97 ± 0.03, and 0.92 ± 0.06. Especially the LSTM model achieved superior execution than other models. The accuracy, F1 score, macro-avg F1 score (0.87), and weighted-avg F1 score (0.89) of the LSTM model produced higher values. All P values were statistically significant. Patients in the high-risk group predicted by our model performed more resistant to DNA damage and microtubule targeting drugs than those in the intermediate-risk group. The predicted low-risk patients were not statistically significant compared with intermediate- or high-risk patients due to the small sample size (188 low-risk patients were predicted via our model, and only two of them were administered chemotherapy alone after surgery). The prognosis of patients predicted by our model was consistent with the actual follow-up records.

Conclusions

The constructed model accurately predicted the recurrence risk of breast cancer patients from EHR data and certainly evaluated the chemoresistance and prognosis of patients. Therefore, our model can help clinicians to formulate the individualized management of breast cancer patients.

Purpurin, a anthraquinone induces ROS-mediated A549 lung cancer cell apoptosis via inhibition of PI3K/AKT and proliferation

OBJECTIVES

In this study, we sought to evaluate purpurin, a natural biomedicine and a potential inhibitor in decreasing the growth rate of lung cancer cells by modulating the role of PI3K/AKT signalling-associated proliferation and apoptosis.

METHODS

A549 cells were treated with purpurin (30 μM) for 24 and 48 h incubation, respectively, and it has been analysed for cytotoxicity, ROS-mediated apoptotic staining. Moreover, purpurin-mediated lipid peroxidation and GSH were measured by biochemical estimation. Furthermore, PI3K/AKT signalling-mediated cell proliferation and apoptotic gene expression done were by western blot.

KEY FINDINGS

In this study, we observed that purpurin could effectively kill A549 cancer cell lines and leads to cell death, thus conforming increased cytotoxicity, production of ROS-mediated enhancement of lipid peroxidation, nuclear fragmentation and apoptosis. Moreover, the GSH content of A549 cell lines was also diminished after treatment with purpurin. This study demonstrates that purpurin inhibits the phosphorylated PI3K/AKT molecules mediated cyclin-D1 and PCNA, thereby inducing apoptosis by observing increased proapoptotic mediators Bax, cleaved PARP, cytochrome-c, caspase-9 and caspase-3; and decreased Bcl-2 expression in the lung cancer cell lines.

CONCLUSION

This result concluded that purpurin eliminates the A549 lung cancer cells by blocking the PI3K/AKT pathway thereby inducing apoptosis.

Effects of cancer treatment on household impoverishment: a multicentre cross-sectional study in China

OBJECTIVES

To determine the incidence and intensity of household impoverishment induced by cancer treatment in China.

DESIGN

Average income and daily consumption per capita of the households and out-of-pocket payments for cancer care were estimated. Household impoverishment was determined by comparing per capita daily consumption against the Chinese poverty line (CPL, US$1.2) and the World Bank poverty line (WBPL, US$1.9) for 2015. Both pre-treatment and post-treatment consumptions were calculated assuming that the households would divert daily consumption money to pay for cancer treatment.

PARTICIPANTS

Cancer patients diagnosed initially from 1 January 2015 to 31 December 2016 who had received cancer treatment subsequently. Those with multiple cancer diagnoses were excluded.

DATA SOURCES

A household questionnaire survey was conducted on 2534 cancer patients selected from nine hospitals in seven provinces through two-stage cluster/convenience sampling.

FINDINGS

5.89% (CPL) to 12.94% (WBPL) households were impoverished after paying for cancer treatment. The adjusted OR (AOR) of post-treatment impoverishment was higher for older patients (AOR=2.666-4.187 for ≥50 years vs <50 years, p<0.001), those resided in central region (AOR=2.619 vs eastern, p<0.01) and those with lower income (AOR=0.024-0.187 in higher income households vs the lowest 20%, p<0.001). The patients without coverage from social health insurance had higher OR (AOR=1.880, p=0.040) of experiencing post-treatment household impoverishment than those enrolled with the insurance for urban employees. Cancer treatment is associated with an increase of 5.79% (CPL) and 12.45% (WBPL) in incidence of household impoverishment. The median annual consumption gap per capita underneath the poverty line accumulated by the impoverished households reached US$128 (CPL) or US$212 (WBPL). US$31 170 395 (CPL) or US$115 238 459 (WBPL) were needed to avoid household impoverishment induced by cancer treatment in China.

CONCLUSIONS

The financial burden of cancer treatment imposes a significant risk of household impoverishment despite wide coverage of social health insurance in China.

Nedaplatin reduces multidrug resistance of non-small cell lung cancer by downregulating the expression of long non-coding RNA MVIH

Cisplatin-based chemotherapy is the standard treatment for non-small cell lung cancer (NSCLC). However, drug resistance emergences after treatment. Long non-coding RNA microvascular invasion in hepatic cancer (MVIH) plays an important role in drug resistance in a variety of cancers. This study investigates the role of nedaplatin on multidrug resistance in NSCLC and its relationship with MVIH. Lung cancer A549 and H1650 cells were treated with cisplatin to obtain multidrug-resistant A549/DDP and H1650/ DDP cells. A549/DDP and H1650/ DDP cells were treated with nedaplatin, MVIH siRNA and siRNA NC. It was found that both MVIH siRNA and nedaplatin significantly reduce the mRNA expression of MVIH in A549/DDP and H1650/ DDP cells. MTT assay showed that the proliferation of MDR cells was significantly higher than that of other cells. Nedaplatin and MVIH siRNA significantly inhibit the proliferation of A549 and H1650 cells. The results of colony formation assay were consistence with MTT results. Nedaplatin and MVIH siRNA significantly reduced colony formation in MDR cells. Flow cytometry showed that NDP and MVIH siRNA significantly decrease the proportion of cells in G0/G1 and increase the proportion of cells in S phase compared with untreated and MDR cells. The apoptotic rate of MDR cells was significantly lower than that of other cells, while the apoptosis rate of cells in NDP and MVIH siRNA group was significantly higher than that of the other three groups of cells. Wound healing assay and Transwell chamber experiments confirmed that both NDP and MVIH siRNA significantly reduced the migration and invasion abilities of MDR cells. The expression of E-cadherin in MDR cells was significantly lower than that in untreated cells, and the expression of N-cad, α-SMA and Vimentin significantly increased in the MDR cells. NPD and MVIH siRNA reverse the EMT process. In conclusion, LncRNA MVIH is upregulated in drug resistant NSCLC cells. Nedaplatin can reduce the expression of MVIH and reverse EMT process, thus reversing the drug resistance of cisplatin in non-small cell lung cancer cells.