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Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to detect genome-wide interactions between a protein of interest and DNA in vivo. Loci showing strong enrichment over adjacent background regions are typically considered to be sites of binding. Insufficient attention has been given to systematic artifacts inherent to the ChIP-seq procedure that might generate a misleading picture of protein binding to certain loci. We show here that unrelated transcription factors appear to consistently bind to the gene bodies of highly transcribed genes in yeast. Strikingly, several types of negative control experiments, including a protein that is not expected to bind chromatin, also showed similar patterns of strong binding within gene bodies. These false positive signals were evident across sequencing platforms and immunoprecipitation protocols, as well as in previously published datasets from other labs. We show that these false positive signals derive from high rates of transcription, and are inherent to the ChIP procedure, although they are exacerbated by sequencing library construction procedures. This expression bias is strong enough that a known transcriptional repressor like Tup1 can erroneously appear to be an activator. Another type of background bias stems from the inherent nucleosomal structure of chromatin, and can potentially make it seem like certain factors bind nucleosomes even when they don't. Our analysis suggests that a mock ChIP sample offers a better normalization control for the expression bias, whereas the ChIP input is more appropriate for the nucleosomal periodicity bias. While these controls alleviate the effect of the biases to some extent, they are unable to eliminate it completely. Caution is therefore warranted regarding the interpretation of data that seemingly show the association of various transcription and chromatin factors with highly transcribed genes in yeast.

Elucidating how antigen exposure and selection shape the human antibody repertoire is fundamental to our understanding of B-cell immunity. We sequenced the paired heavy- and light-chain variable regions (VH and VL, respectively) from large populations of single B cells combined with computational modeling of antibody structures to evaluate sequence and structural features of human antibody repertoires at unprecedented depth. Analysis of a dataset comprising 55,000 antibody clusters from CD19⁺CD20⁺CD27⁻ IgM-naive B cells, >120,000 antibody clusters from CD19⁺CD20⁺CD27⁺ antigen–experienced B cells, and >2,000 RosettaAntibody-predicted structural models across three healthy donors led to a number of key findings: (i) VH and VL gene sequences pair in a combinatorial fashion without detectable pairing restrictions at the population level; (ii) certain VH:VL gene pairs were significantly enriched or depleted in the antigen-experienced repertoire relative to the naive repertoire; (iii) antigen selection increased antibody paratope net charge and solvent-accessible surface area; and (iv) public heavy-chain third complementarity-determining region (CDR-H3) antibodies in the antigen-experienced repertoire showed signs of convergent paired light-chain genetic signatures, including shared light-chain third complementarity-determining region (CDR-L3) amino acid sequences and/or Vκ,λ–Jκ,λ genes. The data reported here address several longstanding questions regarding antibody repertoire selection and development and provide a benchmark for future repertoire-scale analyses of antibody responses to vaccination and disease.

The prostate gland mainly contains basal and luminal cells constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here we describe a genome-wide transcriptome analysis of human benign prostatic basal and luminal epithelial populations using deep RNA sequencing. Through molecular and biological characterizations, we show that the differential gene-expression profiles account for their distinct functional properties. Strikingly, basal cells preferentially express gene categories associated with stem cells, neurogenesis and ribosomal RNA (rRNA) biogenesis. Consistent with this profile, basal cells functionally exhibit intrinsic stem-like and neurogenic properties with enhanced rRNA transcription activity. Of clinical relevance, the basal cell gene-expression profile is enriched in advanced, anaplastic, castration-resistant and metastatic prostate cancers. Therefore, we link the cell-type-specific gene signatures to aggressive subtypes of prostate cancer and identify gene signatures associated with adverse clinical features. Gene-expression profiles can be used to predict the prognosis of cancer patients. Here, the authors describe gene expression profiles of human prostate epithelial lineages and show that basal cells have intrinsic stem and neurogenic properties, and molecularly resemble aggressive prostate cancer.

Most cancer mutation profiling studies are laboratory-based and lack direct clinical application. For clinical use, it is necessary to focus on key genes and integrate them with relevant clinical variables. We aimed to evaluate the prognostic value of the dosage of the KRAS G12 mutation, a key pancreatic ductal adenocarcinoma (PDAC) variant and to investigate the biological mechanism of the prognosis associated with the dosage of the KRAS G12 mutation. In this retrospective cohort study, we analyzed 193 surgically treated patients with PDAC between 2009 and 2016. RNA, whole-exome, and KRAS -targeted sequencing data were used to estimate the dosage of the KRAS G12 mutant. Our prognostic scoring system included the mutation dosage from targeted sequencing ( > 0.195, 1 point), maximal tumor diameter at preoperative imaging ( > 20 mm, 1 point), and carbohydrate antigen 19-9 levels ( > 150 U/mL, 1 point). The KRAS mutation dosage exhibited comparable performance with clinical variables for survival prediction. High KRAS mutation dosages activated the cell cycle, leading to high mutation rates and poor prognosis. According to prognostic scoring systems that integrate mutation dosage with clinical factors, patients with 0 points had superior median overall survival of 97.0 months and 1-year, 3-year, and 5-year overall survival rates of 95.8%, 70.8%, and 66.4%, respectively. In contrast, patients with 3 points had worse median overall survival of only 16.0 months and 1-year, 3-year, and 5-year overall survival rates of 65.2%, 8.7%, and 8.7%, respectively. The incorporation of the KRAS G12 mutation dosage variable into prognostic scoring systems can improve clinical variable-based survival prediction, highlighting the feasibility of an integrated scoring system with clinical significance. KRAS mutant dosage enhances prediction of prognosis in pancreatic cancer Pancreatic ductal adenocarcinoma (PDAC) is a severe health issue with low survival rates. This study is aimed to improve PDAC treatment by examining the KRAS gene mutation, which is common in these tumors. The study involved 193 patients who had surgery for PDAC. Researchers used different sequencing methods to measure the KRAS mutation levels and compared these with clinical data. They found that higher KRAS mutation levels were linked to faster tumor growth and earlier recurrence after surgery. By combining KRAS mutation data with clinical factors like tumor size and a blood marker, they developed a scoring system to predict patient outcomes. This system could help doctors tailor treatments more effectively. The study suggests that using KRAS mutation levels can improve predictions about PDAC progression and guide personalized treatment plans in the future. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Telomeres are part of a highly refined system for maintaining the stability of linear chromosomes. Most telomeres rely on simple repetitive sequences and telomerase enzymes to protect chromosomal ends; however, in some species or telomerase-defective situations, an alternative lengthening of telomeres (ALT) mechanism is used. ALT mainly utilises recombination-based replication mechanisms and the constituents of ALT-based telomeres vary depending on models. Here we show that mouse telomeres can exploit non-telomeric, unique sequences in addition to telomeric repeats. We establish that a specific subtelomeric element, the mouse template for ALT (mTALT), is used for repairing telomeric DNA damage as well as for composing portions of telomeres in ALT-dependent mouse embryonic stem cells. Epigenomic and proteomic analyses before and after ALT activation reveal a high level of non-coding mTALT transcripts despite the heterochromatic nature of mTALT-based telomeres. After ALT activation, the increased HMGN1, a non-histone chromosomal protein, contributes to the maintenance of telomere stability by regulating telomeric transcription. These findings provide a molecular basis to study the evolution of new structures in telomeres. Telomeres can be maintained by a telomerase-independent mechanism called an alternative lengthening of telomeres (ALT). Here the authors use mouse Terc (telomerase RNA) knockout embryonic cells and provide longitudinal analysis of ALT telomeres maintained with non-telomeric sequences.

Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapidly screen and identify highly immunogenic epitopes that trigger CTL responses. We used a combined application of this method involving immune-specific signature analysis and HLA-associated peptidomics using samples from six patients with triple-negative breast cancer (TNBC) in order to select immunogenic HLA epitopes for in vitro testing. Additionally, we applied high-throughput imaging at the single-cell level in order to confirm the immunoreactivity of the selected peptides. The results indicated that this method enabled identification of promising CTL peptides capable of inducing antitumor immunity. This platform combining high-resolution computational analysis, HLA-peptidomics, and high-throughput immunogenicity testing allowed rapid and robust identification of highly immunogenic epitopes and represents a powerful technique for cancer-vaccine development.

Background Pancreatic cancer is anatomically divided into pancreatic head and body/tail cancers, and some studies have reported differences in prognosis. However, whether this discrepancy is induced from the difference of tumor biology is hotly debated. Therefore, we aimed to evaluate the differences in clinical outcomes and tumor biology depending on the tumor location. Methods In this retrospective cohort study, we identified 800 patients with pancreatic ductal adenocarcinoma who had undergone upfront curative-intent surgery. Cox regression analysis was performed to explore the prognostic impact of the tumor location. Among them, 153 patients with sufficient tumor tissue and blood samples who provided informed consent for next-generation sequencing were selected as the cohort for genomic analysis. Results Out of the 800 patients, 500 (62.5%) had pancreatic head cancer, and 300 (37.5%) had body/tail cancer. Tumor location in the body/tail of the pancreas was not identified as a significant predictor of survival outcomes compared to that in the head in multivariate analysis (hazard ratio, 0.94; 95% confidence interval, 0.77–1.14; P  = 0.511). Additionally, in the genomic analyses of 153 patients, there were no significant differences in mutational landscapes, distribution of subtypes based on transcriptomic profiling, and estimated infiltration levels of various immune cells between pancreatic head and body/tail cancers. Conclusions We could not find differences in prognosis and tumor biology depending on tumor location in pancreatic ductal adenocarcinoma. Discrepancies in prognosis may represent a combination of lead time, selection bias, and clinical differences, including the surgical burden between tumor sites.

PurposeTo identify features on preoperative MR imaging with diffusion-weighted imaging (DWI) for predicting next-generation sequencing (NGS)-based tumor cellularity and patient outcome after surgical resection of pancreatic ductal adenocarcinoma (PDAC).MethodsThis retrospective study included 105 patients with surgically resected PDAC who underwent preoperative MR imaging with DWI. Tumor cellularity was measured using molecular techniques and bioinformatics methods. Clinico-pathologic findings including tumor T stage for predicting disease-free survival (DFS) and overall survival (OS) were identified using Cox proportional hazards model. Important MR imaging findings including apparent diffusion coefficient (ADC) value of PDAC and modified ADC value (the ratio of the ADC value of PDAC to the ADC value of the spleen) for predicting higher tumor cellularity (≥ 30%) and poor prognosis were also identified.ResultsThe median DFS and OS were 12.0 months [95% confidence interval (CI), 8.0–17.0] and 22.0 months (95% CI, 18.0–29.0), respectively. Higher T stage (T3/4) [hazard ratio (HR), 7.720, (95% CI 1.072, 55.612); p = 0.048] and higher tumor cellularity [HR, 1.599 (95% CI, 1.003–2.548); p = 0.048] were significantly associated with worse DFS. Among MR imaging features, the modified ADC value was significantly associated with tumor cellularity [odds ratio, 0.068 (95% CI, 0.012–0.372); p = 0.002], and PDAC with lower modified ADC value [≤ 1.40 (cutoff value)] showed significantly shorter median DFS than PDAC with higher modified ADC value [8 months (95% CI, 4–12) vs. 16 months (95% CI, 10–29); HR, 1.713 (95% CI, 1.073–2.735), log-rank p = 0.024].ConclusionHigher NGS-based tumor cellularity may be a negative prognostic factor in pancreatic cancer after resection, and modified ADC value derived from DWI could be helpful in predicting tumor cellularity and patient surgical outcome with regard to recurrence.Graphic abstract

Background Lysosomes are closely linked to autophagic activity, which plays a vital role in pancreatic ductal adenocarcinoma (PDAC) biology. The survival of PDAC patients is still poor, and the identification of novel genetic factors for prognosis and treatment is highly required to prevent PDAC-related deaths. This study investigated the germline variants related to lysosomal dysfunction in patients with PDAC and to analyze whether they contribute to the development of PDAC. Methods The germline putative pathogenic variants (PPV) in genes involved in lysosomal storage disease (LSD) was compared between patients with PDAC (n = 418) and healthy controls (n = 845) using targeted panel and whole-exome sequencing. Furthermore, pancreatic organoids from wild-type and Kras G12D mice were used to evaluate the effect of lysosomal dysfunction on PDAC development. RNA sequencing (RNA-seq) analysis was performed with established PDAC patient-derived organoids (PDOs) according to the PPV status. Results The PPV in LSD-related genes was higher in patients with PDAC than in healthy controls (8.13 vs. 4.26%, Log 2 OR = 1.65, P = 3.08 × 10 –3 ). The PPV carriers of LSD-related genes with PDAC were significantly younger than the non-carriers (mean age 61.5 vs. 65.3 years, P = 0.031). We further studied a variant of the lysosomal enzyme, galactosylceramidase (GALC), which was the most frequently detected LSD variant in our cohort. Autophagolysosomal activity was hampered when GALC was downregulated, which was accompanied by paradoxically elevated autophagic flux. Furthermore, the number of proliferating Ki-67 + cells increased significantly in pancreatic organoids derived from G alc knockout Kras G12D mice. Moreover, GALC PPV carriers tended to show drug resistance in both PDAC cell line and PDAC PDO, and RNA-seq analysis revealed that various metabolism and gene repair pathways were upregulated in PDAC PDOs harboring a GALC variant. Conclusions Genetically defined lysosomal dysfunction is frequently observed in patients with young-onset PDAC. This might contribute to PDAC development by altering metabolism and impairing autophagolysosomal activity, which could be potentially implicated in therapeutic applications for PDAC.

High expression of the forkhead box P1 (FOXP1) transcription factor distinguishes the aggressive activated B cell (ABC) diffuse large B-cell lymphoma (DLBCL) subtype from the better prognosis germinal center B-cell (GCB)-DLBCL subtype and is highly correlated with poor outcomes. A genetic or functional role for FOXP1 in lymphomagenesis, however, remains unknown. Here, we report that sustained FOXP1 expression is vital for ABC-DLBCL cell-line survival. Genome-wide analyses revealed direct and indirect FOXP1 transcriptional enforcement of ABC-DLBCL hallmarks, including the classical NF-κB and MYD88 (myeloid differentiation primary response gene 88) pathways. FOXP1 promoted gene expression underlying transition of the GCB cell to the plasmablast—the transient B-cell stage targeted in ABC-DLBCL transformation—by antagonizing pathways distinctive of GCB-DLBCL, including that of the GCB “master regulator,” BCL6 (B-cell lymphoma 6). Cell-line derived FOXP1 target genes that were highly correlated with FOXP1 expression in primary DLBCL accurately segregated the corresponding clinical subtypes of a large cohort of primary DLBCL isolates and identified conserved pathways associated with ABC-DLBCL pathology.