The determination of the mutation load, a total number of nonsynonymous point mutations, by whole-exome sequencing was shown to be useful in predicting the treatment responses to cancer immunotherapy. However, this technique is expensive and time-consuming, which hampers its application in clinical practice. Therefore, the objective of this study was to construct a mutation load estimation model for lung adenocarcinoma, using a small set of genes, as a predictor of the immunotherapy treatment response. Using the somatic mutation data downloaded from The Cancer Genome Atlas (TCGA) database, a computational framework was developed. The estimation model consisted of only 24 genes, used to estimate the mutation load in the independent validation cohort precisely (R² = 0.7626). Additionally, the estimated mutation load can be used to identify the patients with durable clinical benefits, with 85% sensitivity, 93% specificity, and 89% accuracy, indicating that the model can serve as a predictive biomarker for cancer immunotherapy treatment response. Furthermore, our analyses demonstrated the necessity of the cancer-specific models by the constructed melanoma and colorectal models. Since most genes in the lung adenocarcinoma model are not currently included in the sequencing panels, a customized targeted sequencing panel can be designed with the selected model genes to assess the mutation load, instead of whole-exome sequencing or the currently used panel-based methods. Consequently, the cost and time required for the assessment of mutation load may be considerably decreased, which indicates that the presented model is a more cost-effective approach to cancer immunotherapy response prediction in clinical practice.

Differential diagnosis of intrahepatic cholangiocarcinoma (iCCA) from its histologic mimickers, especially metastatic adenocarcinomas of gastric and pancreatic origin, is a great challenge for pathologists. In this study, through bioinformatics analysis of data from The Cancer Genome Atlas and Gene Expression Omnibus, we identified C-reactive protein (CRP) as a candidate marker to differentiate iCCA from other adenocarcinomas and validated its diagnostic performance by immunohistochemistry in a large cohort of clinical samples including 103 iCCAs, 384 other adenocarcinomas, and 34 liver metastases of various origins. The sensitivity and specificity of CRP expression in the diagnosis of iCCA were 75.7% and 91.1% when using tissue microarrays and 93.3% and 88.2% when using whole tissue sections, respectively. We also compared the diagnostic performance of CRP with N-cadherin, a previously reported marker for iCCA. The sensitivity and specificity of N-cadherin were 54.4% and 92.2% when using tissue microarrays and 80.0% and 88.2% when using whole tissue sections, respectively. The sensitivity of CRP was higher than that of N-cadherin, whereas their specificity was similar. CRP expression was associated with mass-forming gross type (P<0.001), absence of perineural invasion (P=0.002), and N-cadherin expression (P<0.001). CRP expression was also associated with better overall survival (P=0.002) and longer recurrence-free time (P=0.032) after surgery. Our study suggests that CRP is a promising immunohistochemical marker to differentiate iCCA from other adenocarcinomas. Compared with N-cadherin, CRP showed higher sensitivity and similar specificity. CRP expression was associated with better prognosis in iCCA.

The immune system is a key biological system present in vertebrates. Exposure to pathogens elicits various defensive immune mechanisms that protect the host from potential threats and harmful substances derived from pathogens such as parasites, bacteria, and viruses. The complex immune system of humans and many other vertebrates can be divided into two major categories: the innate and the adaptive immune systems. At present, analysis of the complex interactions between the two subsystems that regulate host defense and inflammatory responses remains challenging. Based on time-course microarray data following primary and secondary infection of zebrafish by Candida albicans, we constructed two intracellular protein–protein interaction (PPI) networks for primary and secondary responses of the host. 57 proteins and 341 PPIs were identified for primary infection while 90 proteins and 385 PPIs were identified for secondary infection. There were 20 proteins in common while 37 and 70 proteins specific to primary and secondary infection. By inspecting the hub proteins of each network and comparing significant changes in the number of linkages between the two PPI networks, we identified TGF-β signaling and apoptosis as two of the main functional modules involved in primary and secondary infection. Smad7, a member of the inhibitor SMADs, was identified to be a key protein in TGF-β signaling involved in secondary infection only. Indeed, the Smad7-dependent feedback system is related to the TGF-β signaling pathway and the immune response, suggesting that Smad7 may be an important regulator of innate and adaptive immune responses in zebrafish. Furthermore, we found that apoptosis was differentially involved in the two infection phases; more specifically, whereas apoptosis was promoted in response to primary infection, it was inhibited during secondary infection. Our initial in silico analyses pave the way for further investigation into the interesting roles played by the TGF-β signaling pathway and apoptosis in innate and adaptive immunity in zebrafish. Such insights could lead to therapeutic advances and improved drug design in the continual battle against infectious diseases.

Immunotherapy benefits selected cases of gastric cancer (GC), but the correlation between biomarkers and prognosis is still unclear. Fifty-two patients with GC who underwent immunotherapy were enrolled from June 2016 to December 2020. Their clinical features and biomarkers—microsatellite instability-high (MSI-H), programmed cell death ligand 1 (PD-L1) combined positive score (CPS), and Epstein–Barr encoding region (EBER)—were analyzed. Eight patients had MSI-H, five patients had EBER, 29 patients had CPS ≥ 1, and 20 patients had no biomarker. The overall response rates (ORRs) of the MSI-H, EBER, PD-L1 CPS ≥ 1, and all-negative group were 75%, 60%, 44.8%, and 15%, respectively. Compared with that of the all-negative group, progression-free survival (PFS) was better in the MSI-H (p = 0.018), CPS ≥ 5 (p = 0.012), and CPS ≥ 10 (p = 0.006) groups, but not in the EBER (p = 0.2) and CPS ≥ 1 groups (p = 0.35). Ten patients had combined biomarkers, CPS ≥ 1 with either MSI-H or EBER. The ORRs were 66.7% for CPS ≥ 1 and MSI-H and 75% for CPS ≥ 1 and EBER. PFS was better in patients with combined biomarkers (p = 0.01). MSI-H, EBER, and CPS are useful biomarkers for predicting the efficacy of immunotherapy.