As the most aggressive tumor, the outcome of pancreatic cancer (PACA) has not improved observably over the last decade. Anatomy-based TNM staging does not exactly identify treatment-sensitive patients, and an ideal biomarker is urgently needed for precision medicine. Based on expression files of 1280 patients from 10 multicenter cohorts, we screened 32 consensus prognostic genes. Ten machine-learning algorithms were transformed into 76 combinations, of which we selected the optimal algorithm to construct an artificial intelligence-derived prognostic signature (AIDPS) according to the average C-index in the nine testing cohorts. The results of the training cohort, nine testing cohorts, Meta-Cohort, and three external validation cohorts (290 patients) consistently indicated that AIDPS could accurately predict the prognosis of PACA. After incorporating several vital clinicopathological features and 86 published signatures, AIDPS exhibited robust and dramatically superior predictive capability. Moreover, in other prevalent digestive system tumors, the nine-gene AIDPS could still accurately stratify the prognosis. Of note, our AIDPS had important clinical implications for PACA, and patients with low AIDPS owned a dismal prognosis, higher genomic alterations, and denser immune cell infiltrates as well as were more sensitive to immunotherapy. Meanwhile, the high AIDPS group possessed observably prolonged survival, and panobinostat may be a potential agent for patients with high AIDPS. Overall, our study provides an attractive tool to further guide the clinical management and individualized treatment of PACA.

Colorectal cancer (CRC) remains a leading cause of cancer‐related deaths worldwide. Although treatment strategies for solid tumours have been revolutionized by immunotherapy, only a small subset of CRC patients benefit. Using two‐independent cohorts, we found the common frequently mutated genes TTN and OBSCN had the significant correlation with higher tumour mutation burden (TMB) and favourable overall survival. TTN and OBSCN also displayed significant commutation phenomenon. Therefore, based on the status of TTN and OBSCN, we stratified patients into ‘Double‐WT’ phenotype, ‘Single‐Hit’ phenotype and ‘Double‐Hit’ phenotype. Importantly, the ‘Double‐Hit’ phenotype had favourable prognosis, low malignant events propensity, and highest TMB, immune cells infiltration abundance, POLE mutation rate, microsatellite instability ratio, as well as immune checkpoints expression compared with the other two phenotypes. These results indicated that the ‘Double‐Hit’ phenotype suggested ‘immune‐hot’ tumours and potentially better immunotherapeutic efficacy. Bioinformatic algorithm assessment of immunotherapy responses also confirmed this conclusion, and the ‘Double‐Hit’ phenotype was found to be a better predictor of immunotherapy than PD‐L1, PD‐1, CTLA‐4, TMB and microsatellite status. This study revealed CRC patients with TTN/OBSCN ‘Double‐Hit’ was significantly associated favourable prognosis, ‘immune‐hot’ subtype and potentially better immunotherapeutic efficacy.

Background: Chronic kidney disease (CKD) is closely associated with cardiovascular disease. We aimed to examine the association of Life's Essential 8 (LE8), the recently updated measurement of cardiovascular health, with the prevalence of CKD among US adults. Methods and Results: This population‐based cross‐sectional study used data from the National Health and Nutrition Examination Survey from 2007 to 2018 and included adults aged ≥20 years. Multivariable logistic and restricted cubic spline models were used to assess the associations between LE8 and CKD. Among 24 960 participants, 4437 were determined to have CKD (weighted percentage, 14.11%). After the adjustment of potential confounders, higher LE8 scores were associated with reduced odds of CKD (odds ratio for each 10‐point increase, 0.79 [95% CI, 0.76–0.83]), and a nonlinear dose–response relationship was observed. Similar patterns were also identified in the associations of health behavior and health factor scores with CKD. Meanwhile, higher scores for blood glucose (odds ratio, for each 10‐point increase, 0.88 [95% CI, 0.87–0.90]) and blood pressure (odds ratio, for each 10‐point increase, 0.92 [95% CI, 0.91–0.94]) in the LE8 component are significantly associated with a lower prevalence of CKD. The inversed association of LE8 score and CKD was significantly stronger among middle‐aged, male, and coupled participants. Conclusions: LE8 was negatively associated with the prevalence of CKD in a nonlinear fashion. Promoting adherence to optimal cardiovascular health levels may be beneficial to reduce the burden of CKD.

As essential regulators of gene expression, miRNAs are engaged in the initiation and progression of colorectal cancer (CRC), including antitumour immune response. In this study, we proposed an integrated algorithm, ImmuMiRNA, for identifying miRNA modulators of immune‐associated pathways. Based on these immune‐associated miRNAs, we applied the LASSO algorithm to develop a reliable and individualized signature for evaluating overall survival (OS) and inflammatory landscape of CRC patients. An external public data set and qRT‐PCR data from 40 samples were further utilized to validate this signature. As a result, an immune‐associated miRNA prognostic signature (IAMIPS) consisting of three miRNAs (miR‐194‐3P, miR‐216a‐5p and miR‐3677‐3p) was established and validated. Patients in the high‐risk group possessed worse OS. After stratification for clinical factors, the signature remained a powerful independent predictor for OS. IAMIPS displayed much better accuracy than the traditional clinical stage in assessing the prognosis of CRC. Further analysis revealed that patients in the high‐risk group were characterized by inflammatory response, abundance immune cell infiltration, and higher immune checkpoint profiles and tumour mutation burden (TMB). In conclusion, the IAMIPS is highly predictive of OS in patients with CRC, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.

Hypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also revealed the specific biological and clinical characteristics via bioinformatic methods. The principal component analysis algorithm was employed to develop a hypoxia-associated risk score (HARS). We identified the two hypoxia subtypes: low hypoxia pattern (C1) and high hypoxia pattern (C2). C1 was less sensitive to immunotherapy compared to C2, consistent with the lack of immune cells and immune checkpoints (ICPs) in C1, whereas C2 was the opposite. C2 displayed worse prognosis and higher sensitivity to obatoclax relative to C1, while C1 was more sensitive to sorafenib. The two subtypes also demonstrated subtype-specific genomic variations including mutation, copy number alteration, and methylation. Moreover, we developed and validated a risk signature: HARS, which had excellent performance for predicting prognosis and immunotherapy. We revealed two hypoxia subtypes with distinct biological and clinical characteristics in HCC, which enhanced the understanding of hypoxia pattern. The risk signature was a promising biomarker for predicting prognosis and immunotherapy.

CUGBP Elav‐like family member 2(CELF2) plays crucial roles in the development and activation of T cell. However, the impacts of CELF2 on tumour‐infiltrating immune cells (TIICs) and clinical outcomes of tumours remain unclear. In this study, we found that elevated CELF2 expression was markedly correlated with prolonged survival in multiple tumours, particularly in breast and lung cancers. Notably, CELF2 only impacted the prognosis of triple‐negative breast cancer (TNBC) with lymph node metastasis. Further investigation showed CELF2 expression was positively correlated with the infiltration abundance of dendritic cells (DCs), CD8+ T cells and neutrophils in breast invasive carcinoma (BRCA) and DCs in lung squamous cell carcinoma (LUSC). CELF2 also had strong correlations with markers of diverse TIICs such as T cells, tumour‐associated macrophages and DCs in BRCA and LUSC. Importantly, CELF2 was significantly associated with plenty of immune checkpoint molecules (ICMs) and outperformed five prevalent biomarkers including PD‐1, PD‐L1, CTLA‐4, CD8 and tumour mutation burden in predicting immunotherapeutic responses. Immunohistochemistry also revealed lower protein levels of CELF2 in TNBC and LUSC compared to normal tissues, and patients with high expression showed significantly prolonged prognosis. In conclusion, we demonstrated that increased CELF2 expression was closely related to better prognosis and superior TIIC infiltration and ICM expression, particularly in BRCA and LUSC. CELF2 also performed well in evaluating the immunotherapeutic efficacy, suggesting CELF2 might be a promising biomarker.