Intestinal flora promotes the pathogenesis of colorectal cancer (CRC) through microorganisms and their metabolites. This study aimed to investigate the composition of intestinal flora in different stages of CRC progression and the effect of fecal microbiota transplantation (FMT) on CRC mice. The fecal microbiome from healthy volunteers (HC), colorectal adenoma (CRA), inflammatory bowel disease (IBD), and CRC patients were analyzed by 16s rRNA gene sequencing. In an azoxymethane (AOM)/dextran-sulfate-sodium (DSS)-induced CRC mouse, the effect of FMT from HC, CRA, CRC, and IBD patients on CRC mice was assessed by histological analysis. Expression of inflammation- EMT-associated proteins and Wnt/β-catenin pathway were assessed using qRT-PCR and western blot. The ratio of the fecal microorganisms and metabolomics alteration after FMT were also assessed. Prevotella, Faecalibacterium, Phascolarctobacterium, Veillonella, Alistipes, Fusobacterium, Oscillibacter, Blautia, and Ruminococcus abundance was different among HC, IBD, CRC, and CRA patients. HC-FMT alleviated disease progression and inflammatory response in CRC mice, inhibited splenic T help (Th)1 and Th17 cell numbers, and suppressed the EMT and Wnt/β-catenin pathways in tumor tissues of CRC mice. IBD-FMT, CRA-FMT, and CRC-FMT played deleterious roles; the CRC-FMT mice exhibited the most malignant phenotype. Compared with the non-FMT CRC mice, Muribaculaceae abundance was lower after FMT, especially lowest in the IBD-FMT group; while Lactobacillus abundance was higher after FMT and especially high in HC-FMT. Akkermansia and Ileibacterium abundance increased after FMT-HC compared to other groups. Metabolite correlation analysis revealed that Muribaculaceae abundance was significantly correlated with metabolites such as Betaine, LysoPC, and Soyasaponin III. Lactobacillus abundance was positively correlated with Taurocholic acid 3-sulfate, and Ileibacterium abundance was positively correlated with Linoleoyl ethanolamide. The different intestinal microbiota communities of HC, IBD, CRA, and CRC patients may be attributed to the different modulation effects of FMT on CRC mice. CRC-FMT promoted, while HC-FMT inhibited the progress of CRC. Increased linoleoyl ethanolamide levels and abundance of Muribaculaceae, Akkermansia, and Ileibacterium and reduced Fusobacterium might participate in inhibiting CRC initiation and development. This study demonstrated that FMT intervention could restore the intestinal microbiota and metabolomics of CRC mice, suggesting FMT as a potential strategy for CRC therapy.

Background: Nivolumab plus chemotherapy (NC) was recently approved as the first-line intervention for human epidermal growth factor receptor 2-negative advanced gastric/gastroesophageal junction cancer (GC/GEJC). Moreover, in the latest KEYNOTE-859 (NCT03675737), pembrolizumab plus chemotherapy (PC) was demonstrated to produce remarkable patient survival outcomes. Objectives: The clinicians and patients need to assess NC and PC preference for cancer drugs. Design: The cost-effective analysis. Methods: In an economic assessment of the United States, United Kingdom, and Chinese healthcare systems using a Markov model simulated patients with GC/GEJC, two treatment decision branches with three health states and a tracked time horizon of 15 years were developed. The overall cost and efficacy outcomes of first-line strategies PC and NC were evaluated at willingness-to-pay (WTP) thresholds of different national, including life-years (LYs), quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and incremental net-health benefit (INHB). Sensitivity and subgroup analyses were considered. Results: Given a WTP threshold of $150,000, $60,161, and $37,653 per QALY in the United States, United Kingdom, and China, respectively, both PC and NC achieved QALYs of 1.67 and 1.65 (2.51 and 2.48 LYs), 1.65 and 1.63 (2.48 and 2.45 LYs), and 1.60 and 1.58 (2.40 and 2.37 LYs), with total costs of $242,444 and $232,617, $148,367 and $127,737, and $16,693 and $24,016, respectively. Based on our sensitivity analysis, the programmed death-1 inhibitors cost produced the largest impact on the outcome. In addition, the cost-effectiveness probabilities of PC were 38.3%, 4.1%, and 100% in the three aforementioned countries, respectively. Conclusion: In the case of the Chinese payers’ perspective, PC appeared more dominant as first-line therapy for advanced GC/GEJC patients, whereas NC was preferred in the United States and United Kingdom.

Objectives: In radiomics, high-throughput algorithms extract objective quantitative features from medical images. In this study, we evaluated CT-based radiomics features, clinical features, in-depth learning features, and a combination of features for predicting a good pathological response (GPR) in non-small cell lung cancer (NSCLC) patients receiving immunotherapy-based neoadjuvant therapy (NAT).Materials and methods: We reviewed 62 patients with NSCLC who received surgery after immunotherapy-based NAT and collected clinicopathological data and CT images before and after immunotherapy-based NAT. A series of image preprocessing was carried out on CT scanning images: tumor segmentation, conventional radiomics feature extraction, deep learning feature extraction, and normalization. Spearman correlation coefficient, principal component analysis (PCA), and least absolute shrinkage and selection operator (LASSO) were used to screen features. The pretreatment traditional radiomics combined with clinical characteristics (before_rad_cil) model and pretreatment deep learning characteristics (before_dl) model were constructed according to the data collected before treatment. The data collected after NAT created the after_rad_cil model and after_dl model. The entire model was jointly constructed by all clinical features, conventional radiomics features, and deep learning features before and after neoadjuvant treatment. Finally, according to the data obtained before and after treatment, the before_nomogram and after_nomogram were constructed.Results: In the before_rad_cil model, four traditional radiomics features (“original_shape_flatness,” “wavelet hhl_firer_skewness,” “wavelet hlh_firer_skewness,” and “wavelet lll_glcm_correlation”) and two clinical features (“gender” and “N stage”) were screened out to predict a GPR. The average prediction accuracy (ACC) after modeling with k-nearest neighbor (KNN) was 0.707. In the after_rad_cil model, nine features predictive of GPR were obtained after feature screening, among which seven were traditional radiomics features: “exponential_firer_skewness,” “exponential_glrlm_runentropy,” “log- sigma-5-0-mm-3d_firer_kurtosis,” “logarithm_skewness,” “original_shape_elongation,” “original_shape_brilliance,” and “wavelet llh_glcm_clustershade”; two were clinical features: “after_CRP” and “after lymphocyte percentage.” The ACC after modeling with support vector machine (SVM) was 0.682. The before_dl model and after_dl model were modeled by SVM, and the ACC was 0.629 and 0.603, respectively. After feature screening, the entire model was constructed by multilayer perceptron (MLP), and the ACC of the GPR was the highest, 0.805. The calibration curve showed that the predictions of the GPR by the before_nomogram and after_nomogram were in consensus with the actual GPR.Conclusion: CT-based radiomics has a good predictive ability for a GPR in NSCLC patients receiving immunotherapy-based NAT. Among the radiomics features combined with the clinicopathological information model, deep learning feature model, and the entire model, the entire model had the highest prediction accuracy.

Platinum-based drugs, the most widely used chemotherapeutic drugs in clinical oncology, have long faced the problem of drug resistance, which is urgently in need of resolution. Identifying biomarkers of drug resistance may help reduce platinum resistance and improve therapeutic efficacy. This study aims to identify potential biomarkers associated with the development of cisplatin resistance in non-small cell lung cancer (NSCLC) and explore mechanisms to overcome chemoresistance. NSCLC cisplatin resistance cell lines were constructed, and transcriptome sequencing was performed. Results were validated using Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Molecular docking, proteomics sequencing, and in vitro and in vivo experiments were conducted to evaluate the role of Heme Oxygenase 1 (HO-1) in cisplatin resistance. NSCLC cisplatin resistance cell lines, GEO and TCGA data identified HMOX1, downstream of Nrf2, as a key drug resistance gene induced by cisplatin. Activation of the Nrf2/HO-1 pathway was found to induce ferroptosis resistance, a critical mechanism of cisplatin resistance. Candidate compounds SB 202190 and Nordihydroguaiaretic acid (NDGA) effectively reactivated ferroptosis by inhibiting HO-1, thereby increasing cisplatin sensitivity. The Nrf2/HO-1 pathway is a significant contributor to cisplatin resistance in NSCLC. Targeting HO-1 with SB 202190 and NDGA presents a promising strategy to overcome resistance and improve chemotherapy outcomes.

Purpose Head and neck cancers (HNC) radiotherapy (RT) is associated with inevitable injury to parotid glands and subsequent xerostomia. We investigated the utility of standardized uptake values (SUV) derived from routinely performed 18-fluorodeoxygluocose positron-emission tomography (18FDG-PET) to develop metabolic imaging biomarkers (MIBs) of RT-related parotid injury. Methods Data for oropharyngeal cancer (OPC) patients treated with RT at our institution between 2005-2015 with available planning computed tomography (CT), dose grid, pre- & first post-RT 18FDG-PET-CT scans, and physician-reported xerostomia assessment at 3-6 months post-RT (Xero 3-6ms) per CTCAE, was retrieved, following an IRB approval. A CT-CT deformable image co-registration followed by voxel-by-voxel resampling of pre & post-RT 18FDG activity and dose grid were performed. Ipsilateral (Ipsi) and contralateral (contra) parotid glands were sub-segmented based on the received dose in 5 Gy increments, i.e. 0-5 Gy, 5-10 Gy sub-volumes, etc. Median and dose-weighted SUV were extracted from whole parotid volumes and sub-volumes on pre- & post-RT PET scans, using in-house code that runs on MATLAB. Wilcoxon signed-rank and Kruskal-Wallis tests were used to test differences pre- and post-RT. Results 432 parotid glands, belonging to 108 OPC patients treated with RT, were sub-segmented & analyzed. Xero 3-6ms was reported as: non-severe (78.7%) and severe (21.3%). SUV- median values were significantly reduced post-RT, irrespective of laterality (p=0.02). A similar pattern was observed in parotid sub-volumes, especially ipsi parotid gland sub-volumes receiving doses 10-50 Gy (p<0.05). A Kruskal-Wallis test showed a significantly higher mean planned RT dose in the contra parotid in the patients with more severe Xero 3-6mo (p= 0.03). Multiple logistic regression showed a combined clinical-dosimetric-metabolic imaging model could predict the severity of Xero 3-6mo; AUC=0.78 (95%CI:0.66-0.85;p<0.0001) Conclusion We sought to quantify pre- and post-RT 18FDG-PET metrics of parotid glands in patients with OPC. Temporal dynamics of PET-derived metrics can potentially serve as MIBs of RT-related xerostomia in concert with clinical and dosimetric variables. Keywords: Xerostomia; FDG-PET; radiotherapy; imaging biomarkers; predictive model; head and neck cancer

Colorectal cancer (CRC) has emerged as a major public health concern due to its high incidence and mortality worldwide and a series of transcription factors have been proven by a number of studies to play crucial roles in the development of CRC. In this study, integrative bioinformatics analyses were performed to analyze differentially expressed transcription factors in CRC. FOXS1 was shown to be considerably up-regulated in CRC and linked to patients’ survival according to online data. Furthermore, the expression level of FOXS1 showed to be increased within clinical CRC tissues and cell lines. Concerning cellular functions, FOXS1 knockdown significantly suppressed colony formation and cell invasion of CRC cells; regarding epithelial-mesenchymal transition (EMT) markers, FOXS1 knockdown dramatically elevated E-cadherin proteins but reduced N-cadherin, vimentin, and β-catenin proteins than normal control and sh-NC groups. Conversely, FOXS1 facilitated CRC cell aggressiveness. In the subcutaneous xenograft tumor model, FOXS1 knockdown inhibited, whereas FOXS1 overexpression facilitated tumor growth and EMT. In conclusion, FOXS1 is significantly up-regulated in CRC. Functionally, FOXS1 knockdown repressed the capacity of cancer cells to proliferate and invade in vitro and inhibited tumor growth in the subcutaneous xenograft tumor model in vivo. FOXS1 exerts the oncogenic role in CRC through facilitating the EMT process in CRC.