Wei Liu

Transcription factors (TFs) as key regulators play crucial roles in biological processes. The identification of TF-target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression. The accumulated data of chromatin immunoprecipitation sequencing (ChIP-seq) provide great opportunities to discover the TF-target regulations across different conditions. In this study, we constructed a database named hTFtarget, which integrated huge human TF target resources (7190 ChIP-seq samples of 659 TFs and high-confidence binding sites of 699 TFs) and epigenetic modification information to predict accurate TF-target regulations. hTFtarget offers the following functions for users to explore TF-target regulations: (1) browse or search general targets of a query TF across datasets; (2) browse TF-target regulations for a query TF in a specific dataset or tissue; (3) search potential TFs for a given target gene or non-coding RNA; (4) investigate co-association between TFs in cell lines; (5) explore potential co-regulations for given target genes or TFs; (6) predict candidate TF binding sites on given DNA sequences; (7) visualize ChIP-seq peaks for different TFs and conditions in a genome browser. hTFtarget provides a comprehensive, reliable and user-friendly resource for exploring human TF-target regulations, which will be very useful for a wide range of users in the TF and gene expression regulation community. hTFtarget is available at http://bioinfo.life.hust.edu.cn/hTFtarget.

Cancer stem cells (CSCs) are a heterogeneous group of tumor cells that play a significant role in tumorigenesis, therapeutic resistance, and recurrence in liver hepatocellular carcinoma (LIHC). This study combines clinical data sets from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) with bulk RNA sequencing data. This study also features the GSE156625 single-cell RNA sequencing (scRNA) data set from the GEO to explore the prognostic significance of CSC biomarkers (BCSCs) in LIHC. In this research, we introduce a developed prognostic risk model that relies on nine specific BCSCs, including ADM, CCL5, CD274, DLGAP5, HOXD9, IGF1, S100A9, SOCS2, and TNFRSF11B. It was found that high-risk patients experience shorter overall survival rates when compared to low-risk patients. Additionally, the study characterized the composition of immune cells within the tumor microenvironment (TME) and revealed significant variations in gene-expression levels and mutation rates between different risk groups. The model suggests that liver cancer progression might be driven by immune evasion independent of PD-L1 and highlights the potential of the low-risk BCSC group being sensitive to various treatments. Our findings offer a promising foundation for personalized LIHC therapy and highlight the need for further experimental validation of the roles of these CSCs in disease progression.

PURPOSE: The MD Anderson Oropharynx Cancer (MDA-OPC) cohort is a unique single-institution, prospective longitudinal cancer cohort. The cohort aims to enhance the therapeutic index of OPC management by supporting data needs for independent investigators to conduct rigorous observational studies examining exposures and factors associated with acute and late toxicities, cancer progression, recurrence, new malignancies and quality of life in OPC survivors. PARTICIPANTS: A total of 1811 patients with OPC with a minimum follow-up of 6 months have been consented to our prospective registry between 18 March 2015 and 29 December 2023. Clinical and treatment (Tx) data are available on all patients, including previously untreated patients (1443, 80%). Most previously untreated patients (97%) consented to longitudinal patient-reported outcomes and functional assessments for critical time points including pre-Tx, during-Tx and post-Tx at 3-6 months, 12 months, 18-24 months and annually up to 5 years. FINDINGS TO DATE: The median age for the MDA-OPC cohort is 66 years (range, 25-96) with the majority being male (89%), white (92%) and with human papillomavirus (HPV)/p16-associated OPC (88%) primarily located in the tongue base or tonsil (90%). For previously untreated patients, 79% were diagnosed with stage I/II disease, and nearly half underwent curative intent chemoradiation. Overall survival was significantly higher for HPV/p16-associated OPC at 1 year (98% vs 93%) and 5 years (83% vs 54%; p<0.0001) compared with HPV-negative disease. Longitudinal PRO and clinician-graded toxicity outcomes (eg, osteoradionecrosis, neuropathy, dysphagia) are summarised. FUTURE PLANS: Future work includes expansion of the MDA-OPC cohort and survivorship surveillance to 10 years under the recently funded OPC-SURVIVOR research programme (P01CA285249), which aims to identify non-invasive, clinic-ready biomarkers and examine novel phenotypes and mechanistically matched mitigation strategies for latent OPC sequelae. Additionally, we aim to expand our advanced data infrastructure by integrating large data streams from parallel clinical trials and imaging registries. TRIAL REGISTRATION NUMBERS: NCT01893307, NCT03145077.

Background: Cancer stem cells (CSCs) are key drivers of tumorigenesis and metastasis. However, the precise roles of CSC-associated genes in these processes remain unclear. Methods: This study integrates cancer stem cell biomarkers and clinical data from The Cancer Genome Atlas (TCGA) specific to bladder cancer (BLCA). By combining differentially expressed genes (DEGs) from TCGA-BLCA samples with CSC-related biomarkers, we conducted comprehensive functional analyses and developed an 8-gene prognostic signature through Cox regression, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression. This model was validated with GEO datasets (GSE13507 and GSE32894), and the single-cell RNA seq dataset GSE222315 was subsequently analyzed to characterize the signature genes and elucidate their interactions. And a nomogram was created to stratify TCGA-BLCA patients into risk categories. The ‘oncoPredict’ algorithm based on the GDSC2 dataset assessed drug sensitivity in BLCA. Result: From the TCGA cohort, 665 CSC-related genes were identified, with 120 showing significant differential expression. The 8-gene signature (ALDH1A1, CBX7, CSPG4, DCN, FASN, INHBB, MYC, NCAM1) demonstrated strong predictive power for overall survival in both TCGA and GEO cohorts, as confirmed by Kaplan–Meier and ROC analyses. The nomogram, integrating age, tumor stage and risk scores, demonstrated high predictive accuracy. Additionally, the oncoPredict algorithm indicated varying drug sensitivities across patient groups. Based on retrospective data, we identified a novel CSC-related prognostic signature for BLCA. This finding suggests that targeting these genes could offer promising therapeutic strategies.