Pancreatic cancer (PC) is one of the most dismal diseases with a five-year survival rate of only 6%. Such poor prognosis is attributed to both a lack of early detection methods and its intrinsic resistance to cytotoxic agents and radiotherapy. Identifying driving events in the initial stage is of great significance for curable pancreatic ductal adenocarcinoma (PDA) detection and effective targeted therapy. Furthermore, Kirsten rat sarcoma viral oncogene (KRAS) plays a critical role in the initiation and maintenance of pancreatic tumors, thus contributing to the conversion of anti-tumor inflammation to pro-tumor inflammation. Both the KRAS mutation and inflammation are concurrent in the initial stage of PDA, and they compose a positive feedback loop to enhance each other’s activity. This positive feedback loop generates a harsh environment, which helps pancreatic cells maintain the stemness phenotype, accelerates cell turnover rate, increases genome instability, and hence elevates the incidence of PDA formation. Full article

In this study we use vibrational optical coherence tomography (VOCT) to study the mechanovibrational peak heights exhibited by benign and cancerous skin lesions. When a tissue is vibrated using audible sound it resonates at frequencies that represent the major components. The resonant frequency is related to the elastic modulus through a calibration equation developed in vitro using isolated tissue components. New cancerous skin lesions were identified based on the presence of a new cellular peak (80 Hz) with increased stiffness, a new blood vessel peak (130 Hz) that appears to be less stiff than normal blood vessels (150 Hz), and a fibrous tissue peak (260 Hz) present in carcinomas. The objective of this study was to differentiate different skin cancers using VOCT. Mechanovibrational spectra were normalized by dividing by the largest peak of the different skin lesions. Differences in peak heights between actinic keratosis, basal cell carcinoma, squamous cell carcinoma, and melanoma were used to noninvasively “fingerprint” the different skin lesions. The results suggest that VOCT can be used to noninvasively differentiate between different skin cancers and to identify early skin cancers possibly as small as 0.1 mm based on the heights of the 50, 80, and 130 Hz peaks Further work is underway to use machine learning in conjunction with quantitative VOCT peak heights derived from mechanovibrational spectra to noninvasively identify different skin cancers. Full article

Pancreatic ductal adenocarcinoma (PDAC) is most often detected at an advanced stage due to a lack of symptoms at the first stage. PDAC is relatively uncommon, and screening of the asymptomatic population is not feasible or cost-effective. Therefore, screening of individuals in high-risk groups is recommended. Diabetes mellitus (DM) is associated with PDAC, and patients with DM are recognized as a high-risk group for PDAC. Here, we review the complex relationship between pancreatic cancer and DM, including the role of diabetes as a risk factor for pancreatic cancer and its role in inducing the destruction of islet β cells and insulin resistance. We also review the current study about discriminating DM with pancreatic cancer from normal DM and the model for early screening of pancreatic cancer in DM. Full article

In recent years, miRNAs have been shown to play an important role in many diseases, most notably cancers. Traditional experiments for cancer diagnostics are time-consuming and expensive, thus more attention is being diverted towards discovering computational methods for predicting miRNA–disease association and using them in cancer diagnostics. miRNA numerical sequence information and genes targeted by miRNA were used for the construction of descriptors for machine-learning models. Next, we generated a table of miRNA descriptors using all of the miRNAs in a specific cancer dataset for disease classification. To show the effectiveness of the system, we constructed miRNA descriptor systems for pancreatic cancer, lung cancer, and breast cancer. With the Random Forest classifier, we obtained classification accuracies of 86.9%, 86.3%, and 85.1% for the above-mentioned cancers, respectively. Next, different disease datasets were tested on each model, including new miRNA sets for each cancer type from other studies. The models were able to classify the corresponding cancer miRNAs with >90% accuracy and other disease and cancer datasets with <60% accuracy. With this information, we constructed a hard-voting scheme using the three cancer classification models that is able to perform cancer diagnostics. The results suggest that our method is effective in miRNA–disease association prediction and performing cancer diagnostics. Full article

DNA methylation is essential for regulating tissue-specific gene expression, genomic imprinting, X chromosome inactivation and retroviral element silencing. The transformation from normal to cancer cells is accompanied by changes in DNA methylation resulting in the activation of oncogenes and inactivation of tumor suppressor genes. This process is regulated by methylation and contributes to the support and development of tumors. Epigenetic modifications account for the development of resistance in cancer cells treated with anticancer drugs. Dysregulated signaling pathways involved in tumor drug resistance include the Wnt canonical and non-canonical pathways and the PI3K/PTEN/AKT/mTOR pathway. This review considers the mechanisms and specific methylated biomarkers that participate in such resistances and how resistance to individual treatments for breast, ovarian, uterine and cervix tumors are introduced. Full article

Regulatory T cells (Tregs) are a vital cell subset that induces immune tolerance in the tumor microenvironment by secreting suppressive cytokines and inhibiting innate immune cells. Transforming growth factor-beta (TGF-β) plays an important role in this process. However, the effect of TGF-β blockade on intratumoral Tregs and its specific biological role remains unclear. Quantitative and functional changes in Tregs were evaluated after TGF-β blockade with gradient doses of monoclonal antibody 1D11 in a murine pancreatic ductal adenocarcinoma model. The number of tumor infiltrating Tregs decreased significantly (high dose, low dose and control, 38.6 ± 8.1, 38.6 ± 1.8, 74.6 ± 4.9 /40× field, p = 0.024) after 1D11 administration, while CD8⁺ T cells in the tumor microenvironment significantly increased in the low dose group but reversed in the high dose group (3.1 ± 1.4, 12.3 ± 2.1, 5.4 ± 0.5 /40× field, p = 0.016). The frequency of CD4⁺, CD8⁺ or Treg cells in the peripheral blood and spleen showed no significant change. The typical cytokines TGF-β and inerleukin-10 secreted by Tregs as well as interferon-γ produced by cytotoxic T cells in tumor tissues did not change compared with the controls. TGF-β blockade with a monoclonal antibody can reduce Tregs in the tumor niche, however, its therapeutic efficacy in PDAC patients remains limited. Further investigation of combination therapies is required. Full article