Pancreatic cancer is the most lethal type of malignancy and is characterized by high invasiveness without severe symptoms. It is difficult to detect PC at an early stage because of the low diagnostic accuracy of existing routine methods, such as abdominal ultrasound, CT, MRI, and endoscopic ultrasound (EUS). Therefore, it is of value to develop new diagnostic techniques for early detection with high accuracy. In this review, we aim to highlight research progress on novel biomarkers, artificial intelligence, and nanomaterial applications on the diagnostic accuracy of pancreatic cancer.

Colorectal cancer(CRC) is the third most frequent malignant tumor. The gut microbiome acts as a vital component of CRC etiology. Fusobacterium nucleatum(Fn) is a key member of colorectal cancer-associated bacteria. But we lack a systematic and in-depth understanding on its role in CRC evolution. In this article, We reviewed the abundance changes and distribution of Fn in CRC occurrence and development, potential effect of Fn in the initiation of CRC, the source of intratumoral Fn and the cause of its tropism to CRC. In addition, We described the mechanism by which Fn promotes the malignant biological behavior of CRC, affects CRC response to therapy, and shapes the tumor immune microenvironment in great detail. Based on the relationship between Fn and CRC, we proposed strategies for CRC prevention and treatment, and discussed the feasibility and limitations of specific cases, to gain insights into further basic and clinical research in the future.

Colorectal cancer (CRC) is the third most common malignant cancer worldwide with the second highest mortality. Gut microbiota can educate the tumor microenvironment (TME), consequently influencing the efficacy of immune checkpoint inhibitors (ICIs). Fusobacterium nucleatum is one of the most crucial bacteria contributing to colorectal tumorigenesis, but the molecular mechanisms between F. nucleatum and TME or ICIs are poorly investigated. In the present study, we firstly analyzed differentially expressed genes and the biological functions between F. nucleatum-infected and uninfected CRC cell lines, with the findings that CCL22 mRNA expression was markedly upregulated after F. nucleatum infection. Moreover, the survival analysis showed that CCL22 was significantly associated with the overall survival of CRC patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis suggested that CCL22 was related to immune-related terms. Furthermore, the ESTIMATE analysis indicated that the high-CCL22-expression subgroup had a higher immune/stromal/estimate score and lower tumor purity. The CIBERSORT analysis indicated that the high-CCL22-expression group had more immune-suppressive cells and less antitumor immune cells. In addition, immune checkpoint genes and cytotoxic genes were positively correlated with CCL22 expression. The immunophenoscore analysis suggested that CCL22 was associated with the IPS-CTLA4 and PD1/PD-L1/PD-L2 score. Interestingly, CCL22 expression in the KRAS and APC mutation groups was markedly reduced compared to that of the wild groups. In summary, our study provided evidence that CCL22 might play a crucial role in F. nucleatum-related colorectal tumorigenesis and correlate with TME and ICIs, which deserves further study.

Despite immune checkpoint blockade (ICB) therapy contributed to significant advances in cancer therapy, only a small percentage of patients with colorectal cancer (CRC) respond to it. Identification of these patients will facilitate ICB application in CRC. In this study, we integrated multiple CRC cohorts (2,078 samples) to construct tumor microenvironment (TME) subtypes using TME indices calculated by CIBERSORT and ESTIMATE algorithms. Furthermore, a surrogate quantitative indicator, a tumor microenvironment immune gene (TMEIG) score system, was established using the key immune genes between TME clusters 1 and 2. The subsequent analysis demonstrated that TME subtypes and the TMEIG score system correlated with clinical outcomes of patients in multiple CRC cohorts and exhibited distinct immune statuses. Furthermore, Tumor Immune Dysfunction and Exclusion (TIDE) analysis indicated that patients with low TMEIG scores were more likely to benefit from ICB therapy. A study on two ICB cohorts (GSE78220 and IMvigor210) also validated that patients with low TMEIG scores exhibited higher ICB response rates and better prognoses after ICB treatment. The biomarker evaluation module on the TIDE website revealed that the TMEIG score was a robust predictive biomarker. Moreover, differential expression analysis, immunohistochemistry, qPCR experiments, and gene set prioritization module on the TIDE website demonstrated that the five genes that constitute the TMEIG score system (SERPINE1, FABP4, SCG2, CALB2, and HOXC6) were closely associated with tumorigenesis, immune cells, and ICB response indices. Finally, TMEIG scores could accurately predict the prognosis and ICB response of patients with CRC. SERPINE1, FABP4, SCG2, CALB2, and HOXC6 might be potential targets related to ICB treatment. Furthermore, our study provided new insights into precision ICB therapy in CRC.

Background: KRAS mutation, one of the most important biological processes in colorectal cancer, leads to poor prognosis in patients. Although studies on KRAS have concentrated for a long time, there are currently no ideal drugs against KRAS mutations.Methods: Different expression analysis and weighted gene coexpression network analysis was conducted to select candidate genes. Log-rank tests and Cox regression picked out the prognostic genes to build a KRAS-related gene prognostic score (KRGPS). A nomogram based on KRGPS was built to predict survival of clinical patients. Comprehensive analysis showed the prognosis, immune microenvironment and response to immune therapy and chemotherapy in KRGPS subgroups.Results: We collected a KRGPS from the set of two genes GJB6 and NTNG1, with low-KRGSP patients having better progression-free survival (PFS). Low KRGPS is correlated with high infiltration of activated NK cells, plasma cells and activated memory CD4 T cells and that these cells benefit more from immune checkpoint inhibitor therapy. However, high KRGPS is associated with high infiltration of activated mast cells, pathways of immune dysregulation and a high ratio of TP53 and KRAS mutations. KRGPS subgroups are also sensitive to chemotherapy differently. A nomogram, established based on the KRGPS and pathological stage, predict 3- and 5-years PFS well.Conclusions: The KRAS-associated score acts as a promising signature to distinguish prognosis, molecular and immune characteristics, and benefits from immune and chemical therapy. These KRAS-associated genes could be promising targets for drug design.