Gastric cancer (GC) is one of the most common malignancies globally, the occurrence of which undergoes a multistage chronic evolutionary process. It is a great public health issue to deeply understand the mechanisms of GC development and factors affecting the evolution of gastric lesions. Helicobacter pylori infection has been identified as one of the main factors for gastric carcinogenesis and microbial dysbiosis. With the advances in molecular biology techniques, other gastric microbes besides H. pylori have been observed to play an essential role in the development of GC. Previous animal model studies suggested that specific and critical microbes in the stomach can accelerate the malignant transformation of gastric mucosa and the progression of gastric lesions to GC. Recently, the composition of human gastric microbiota has been investigated from stages of precancerous lesions to GC, including characteristics of gastric microbiota diversity, lesion‐associated differential microbes, predicted microbiota‐related functions, microbiota interactions, and microbial mechanisms in gastric carcinogenesis. In this review, we provide an overview of the gastric microbiota, summarize current studies exploring the roles of microbiota in gastric carcinogenesis, and illustrate the significance and prospects of integrative multiomics analysis combined with the microbiome in gastric carcinogenesis.
During the process of carcinogenesis and tumor progression, various molecular alternations occur in different omics levels. In recent years, multiomics approaches including genomics, epigenetics, transcriptomics, proteomics, metabolomics, single-cell omics, and spatial omics have been applied in mapping diverse omics profiles of cancers. The development of high-throughput technologies such as sequencing and mass spectrometry has revealed different omics levels of tumor cells or tissues separately. While focusing on a single omics level results in a lack of accuracy, joining multiple omics approaches together undoubtedly benefits accurate molecular subtyping and precision medicine for cancer patients. With the deepening of tumor research in recent years, taking pathological classification as the only criterion of diagnosis and predicting prognosis and treatment response is found to be not accurate enough. Therefore, identifying precise molecular subtypes by exploring the molecular alternations during tumor occurrence and development is of vital importance. The review provides an overview of the advanced technologies and recent progress in multiomics applied in cancer molecular subtyping and detailedly explains the application of multiomics in identifying cancer driver genes and metastasis-related genes, exploring tumor microenvironment, and selecting liquid biopsy biomarkers and potential therapeutic targets.
As a major kind of cell surface adhesion molecules with signal transduction function, integrins play a major role in tumorigenesis and tumor progression. The role of integrins in tumor cells and the tumor microenvironment has been extensively revealed. Among the integrin family, integrin αvβ3 is the most studied integrin in the past 20 years. Plenty of preclinical and clinical studies have been conducted, which showed clinical benefits of targeting integrin αvβ3 in tumor imaging and treatment. Currently, the focus of interest is gradually shifting from integrin αvβ3 toward other integrin subtypes. Integrin α6 is expressed in many malignant tumors, such as colorectal cancer, head and neck squamous cell carcinoma, breast cancer, pancreatic cancer, and liver cancer, and its expression is correlated with poor survival of the patients. Recent studies have shown that tumor molecular imaging agents and therapeutic drugs targeting integrin α6 have excellent safety and efficacy in preclinical mouse models, encouraging clinical translation of this promising target. In this review, we briefly overview the physiological and pathological function of integrin α6 and highlight the recent advances in integrin α6-targeted imaging and therapeutics in tumors.
Pancreatic cancer is one of the deadliest malignancies, with limited effectiveness of standard therapies, resulting in little improvement in the 5-year survival rate over the past few decades. However, advanced radiotherapy techniques and emerging treatment modalities, such as immunotherapy and targeted therapy, are showing tremendous potential as effective treatment options for pancreatic cancer patients who were previously considered incurable. This review summarizes the current advances and challenges in pancreatic cancer treatment strategies and proposes further optimization directions, aiming to provide insights into the cure of incurable pancreatic cancer.
Background: The aims of this study were to evaluate the prognostic ability of the neoadjuvant rectal (NAR) score and to develop and validate a nomogram based on the NAR for patients with locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT).
Methods: In total, 307 patients, including 230 patients from the primary cohort and 77 from the external cohort, were enrolled across the two centers. The associations of the NAR score with the tumor response, tumor control, and clinicopathological parameters were analyzed. Survival analysis was performed in the primary and external cohorts using Kaplan‒Meier curves. Univariate and multivariate analyses were performed to evaluate the prognostic factors. The NAR‐based nomogram was developed in the primary cohort and validated in the external cohort using the concordance index (C‐index), calibration plots, and decision curve analyses (DCAs).
Results: Kaplan‒Meier survival analysis revealed that the disease‐free survival (DFS) and overall survival (OS) of the NAR > 16 group were significantly lower than those of the NAR ≤ 16 group (p < 0.001). Multivariate Cox regression analysis identified the NAR score as an independent prognostic factor for both DFS (hazard ratio [HR] = 2.484, 95% confidence interval [CI]: 1.159−5.323, p = 0.019) and OS (HR = 4.633, 95% CI: 1.076−19.941, p = 0.04). Calibration plots and DCAs showed that NAR‐based nomograms for DFS and OS were consistent and useful in clinical practice. Moreover, the C‐indexes of the NAR‐based nomograms were better than those of the other variables in both the primary and external cohorts.
Conclusion: Our study validates the prognostic role of the NAR score for DFS and OS. The NAR‐based nomogram for OS could accurately predict the outcome of LARC patients by stratifying the risk score accordingly.
Objective: To clarify the clinical characteristics and pathogenic analysis after lower respiratory tract infection in patients with advanced lung cancer under different treatments.
Methods: A retrospective analysis was adopted to collect 94 cases of patients with advanced lung cancer combined with lower respiratory tract infection from January 1, 2018 to December 1, 2020. Seventy-four cases were male and 20 cases were female. According to the different treatments, the patients were divided into 43 cases in the chemotherapy group and 51 cases in the chemoradiotherapy group. The pathogenic and serological indexes were compared between the two groups to provide ideas for the application of antibiotics.
Results: In the comparison of general clinical data, the chemotherapy group had a shorter hospital stay than the chemoradiotherapy group and a higher body mass index level than the chemoradiotherapy group (p < 0.05). In the comparison of serological indicators, procalcitonin, high-sensitive C-reactive protein, erythrocyte sedimentation rate, and neutrophil percentage were lower in the chemotherapy group, and the lymphocyte was higher than that in the chemoradiotherapy group (p < 0.05). There was no difference in hemoglobin, albumin, creatinine, and alanine transaminase between the two groups (p > 0.05). In the comparison of pathogenicity, the chemotherapy group was more likely to have combined viral infections, while the chemoradiotherapy group was more likely to have Gram-negative bacterial infections (p < 0.05). There was no difference between the two groups in terms of fungal infections (p > 0.05). Besides, the chemoradiotherapy group was more likely to have combined infections (p > 0.05).
Conclusion: Patients with advanced lung cancer treated with chemoradiotherapy have a relatively poor prognosis after developing lower respiratory tract infections and are more likely to have mixed infections. Antibiotics need to be applied as early as possible. The common pathogens should be covered. Antiviral and antifungal drugs can be added as appropriate, and drug sensitivity tests should be completed as early as possible.