Regulators of genetic risk of breast cancer identified by integrative network analysis

Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations

Elucidating the molecular dependencies behind the cancer-type specificity of driver mutations may reveal new therapeutic opportunities. We hypothesized that developmental programs would impact the transduction of oncogenic signaling activated by a driver mutation and shape its cancer-type specificity. Therefore, we designed a computational analysis framework by combining single-cell gene expression profiles during fetal organ development, latent factor discovery, and information theory-based differential network analysis to systematically identify transcription factors that selectively respond to driver mutations under the influence of organ-specific developmental programs. After applying this approach to VHL mutations, which are highly specific to clear cell renal cell carcinoma (ccRCC), we revealed important regulators downstream of VHL mutations in ccRCC and used their activities to cluster patients with ccRCC into three subtypes. This classification revealed a more significant difference in prognosis than the previous mRNA profile-based method and was validated in an independent cohort. Moreover, we found that EP300, a key epigenetic factor maintaining the regulatory network of the subtype with the worst prognosis, can be targeted by a small inhibitor, suggesting a potential treatment option for a subset of patients with ccRCC. This work demonstrated an intimate relationship between organ development and oncogenesis from the perspective of systems biology, and the method can be generalized to study the influence of other biological processes on cancer driver mutations.

Omics-derived biological modules reflect metabolic brain changes in Alzheimer's disease

INTRODUCTION

Brain glucose hypometabolism, indexed by the fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging, is a metabolic signature of Alzheimer's disease (AD). However, the underlying biological pathways involved in these metabolic changes remain elusive.

METHODS

Here, we integrated [18F]FDG-PET images with blood and hippocampal transcriptomic data from cognitively unimpaired (CU, n = 445) and cognitively impaired (CI, n = 749) individuals using modular dimension reduction techniques and voxel-wise linear regression analysis.

RESULTS

Our results showed that multiple transcriptomic modules are associated with brain [18F]FDG-PET metabolism, with the top hits being a protein serine/threonine kinase activity gene cluster (peak-t(223) = 4.86, P value < 0.001) and zinc-finger-related regulatory units (peak-t(223) = 3.90, P value < 0.001).

DISCUSSION

By integrating transcriptomics with PET imaging data, we identified that serine/threonine kinase activity-associated genes and zinc-finger-related regulatory units are highly associated with brain metabolic changes in AD.

HIGHLIGHTS

We conducted an integrated analysis of system-based transcriptomics and fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) at the voxel level in Alzheimer's disease (AD). The biological process of serine/threonine kinase activity was the most associated with [18F]FDG-PET in the AD brain. Serine/threonine kinase activity alterations are associated with brain vulnerable regions in AD [18F]FDG-PET. Zinc-finger transcription factor targets were associated with AD brain [18F]FDG-PET metabolism.

DCS, a novel classifier system based on disulfidptosis reveals tumor microenvironment heterogeneity and guides frontline therapy for clear cell renal carcinoma

Background

Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown.

Methods

In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified.

Results

We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy.

Conclusion

This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

An in vitro model of acute horizontal basal cell activation reveals gene regulatory networks underlying the nascent activation phase

While horizontal basal cells (HBCs) make minor contributions to olfactory epithelium (OE) regeneration during homeostatic conditions, they possess a potent, latent capacity to activate and subsequently regenerate the OE following severe injury. Activation requires, and is mediated by, the downregulation of the transcription factor (TF) TP63. In this paper, we describe the cellular processes that drive the nascent stages of HBC activation. The compound phorbol 12-myristate 13-acetate (PMA) induces a rapid loss in TP63 protein and rapid enrichment of HOPX and the nuclear translocation of RELA, previously identified as components of HBC activation. Using bulk RNA sequencing (RNA-seq), we find that PMA-treated HBCs pass through various stages of activation identifiable by transcriptional regulatory signatures that mimic stages identified in vivo. These temporal stages are associated with varying degrees of engraftment and differentiation potential in transplantation assays. Together, these data show that our in vitro HBC activation system models physiologically relevant features of in vivo HBC activation and identifies new candidates for mechanistic testing.

Identification of collagen subtypes of gastric cancer for distinguishing patient prognosis and therapeutic response

Background

Gastric cancer is a highly heterogeneous disease, presenting a major obstacle to personalized treatment. Effective markers of the immune checkpoint blockade response are needed for precise patient classification. We, therefore, divided patients with gastric cancer according to collagen gene expression to indicate their prognosis and treatment response.

Methods

We collected data for 1250 patients with gastric cancer from four cohorts. For the TCGA-STAD cohort, we used consensus clustering to stratify patients based on expression levels of 44 collagen genes and compared the prognosis and clinical characteristics between collagen subtypes. We then identified distinct transcriptomic and genetic alteration signatures for the subtypes. We analyzed the associations of collagen subtypes with the responses to chemotherapy, immunotherapy, and targeted therapy. We also established a platform-independent collagen-subtype predictor. We verified the findings in three validation cohorts (GSE84433, GSE62254, and GSE15459) and compared the collagen subtyping method with other molecular subtyping methods.

Results

We identified two subtypes of gastric adenocarcinoma: a high-expression collagen subtype (CS-H) and a low-expression collagen subtype (CS-L). Collagen subtype was an independent prognostic factor, with better overall survival in the CS-L subgroup. The inflammatory response, angiogenesis, and phosphoinositide 3-kinase (PI3K)/Akt pathways were transcriptionally active in the CS-H subtype, while DNA repair activity was significantly greater in the CS-L subtype. PIK3CA was frequently amplified in the CS-H subtype, while PIK3C2A, PIK3C2G, and PIK3R1 were frequently deleted in the CS-L subtype. CS-H subtype tumors were more sensitive to fluorouracil, while CS-L subtype tumors were more sensitive to immune checkpoint blockade. CS-L subtype was predicted to be more sensitive to HER2-targeted drugs, and CS-H subtype was predicted to be more sensitive to vascular endothelial growth factor and PI3K pathway-targeting drugs. Collagen subtyping also has the potential to be combined with existing molecular subtyping methods for better patient classification.

Conclusions

We classified gastric cancers into two subtypes based on collagen gene expression and validated these subtypes in three validation cohorts. The collagen subgroups differed in terms of prognosis, clinical characteristics, transcriptome, and genetic alterations. The subtypes were closely related to patient responses to chemotherapy, immunotherapy, and targeted therapy.

Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses

Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.

Loss of LPAR6 and CAB39L dysregulates the basal-to-luminal urothelial differentiation program, contributing to bladder carcinogenesis

We describe a strategy that combines histologic and molecular mapping that permits interrogation of the chronology of changes associated with cancer development on a whole-organ scale. Using this approach, we present the sequence of alterations around RB1 in the development of bladder cancer. We show that RB1 is not involved in initial expansion of the preneoplastic clone. Instead, we found a set of contiguous genes that we term "forerunner" genes whose silencing is associated with the development of plaque-like field effects initiating carcinogenesis. Specifically, we identified five candidate forerunner genes (ITM2B, LPAR6, MLNR, CAB39L, and ARL11) mapping near RB1. Two of these genes, LPAR6 and CAB39L, are preferentially downregulated in the luminal and basal subtypes of bladder cancer, respectively. Their loss of function dysregulates urothelial differentiation, sensitizing the urothelium to N-butyl-N-(4-hydroxybutyl)nitrosamine-induced cancers, which recapitulate the luminal and basal subtypes of human bladder cancer.

Single cell and bulk RNA sequencing identifies tumor microenvironment subtypes and chemoresistance-related IGF1+ cancer-associated fibroblast in gastric cancer

BACKGROUND

The tumor microenvironment (TME) significantly influences prognosis and drug resistance in various tumors, yet its heterogeneity and the mechanisms affecting therapeutic response remain unclear in gastric cancer (GC).

METHODS

The heterogenous TME were explored with single-cell RNA-sequencing (scRNA-seq) data of 50 primary GC samples. We then identified four GC TME subtypes with nonnegative matrix factorization (NMF) and constructed a pearson nearest-centroid classifier based on subtype-specific upregulated genes. Genomic features and clinical significance of four subtypes were comprehensively evaluated. We reclustered fibroblasts to identify cancer-associated fibroblast (CAF) subtype associated with poor clinical outcomes. RT-qPCR and double immunofluorescence staining were applied to validate the findings. Cellchat analysis elucidated potential molecular mechanisms of the CAF subtype in GC disease progression and chemotherapy resistance.

FINDINGS

The GC TME exhibited high heterogeneity, influencing chemo-sensitivity. Four TME-based subtypes predicting response to immunotherapy and chemotherapy were identified and validated in 1406 GC patients. Among which, ISG1 subtype displayed higher fibroblasts infiltration and heightened oncogenic pathways, and inferior response to chemotherapy with unfavorable prognosis. Microsatellite instability-high (MSI-H) GCs within four TME subtypes showed immunological heterogeneity. We then reported an IGF1-overexpressing CAF was associated with chemo-resistance and GC recurrence. Cell communication analysis revealed IGF1+ CAF may induce drug-resistant phenotypes in tumor cells through IGF1-α6β4 integrin ligand-receptor binding and activation of EMT biological process.

INTERPRETATION

We identified four TME-based subtypes with different clinical outcomes and IGF1+ CAFs contributing to poor clinical outcomes in GC, which might provide guidance for individualized treatment and facilitate the development of novel therapeutic targets.

Germline determinants of aberrant signaling pathways in cancer

Cancer is a complex disease influenced by a heterogeneous landscape of both germline genetic variants and somatic aberrations. While there is growing evidence suggesting an interplay between germline and somatic variants, and a substantial number of somatic aberrations in specific pathways are now recognized as hallmarks in many well-known forms of cancer, the interaction landscape between germline variants and the aberration of those pathways in cancer remains largely unexplored. Utilizing over 8500 human samples across 33 cancer types characterized by TCGA and considering binary traits defined using a large collection of somatic aberration profiles across ten well-known oncogenic signaling pathways, we conducted a series of GWAS and identified genome-wide and suggestive associations involving 276 SNPs. Among these, 94 SNPs revealed cis-eQTL links with cancer-related genes or with genes functionally correlated with the corresponding traits' oncogenic pathways. GWAS summary statistics for all tested traits were then used to construct a set of polygenic scores employing a customized computational strategy. Polygenic scores for 24 traits demonstrated significant performance and were validated using data from PCAWG and CCLE datasets. These scores showed prognostic value for clinical variables and exhibited significant effectiveness in classifying patients into specific cancer subtypes or stratifying patients with cancer-specific aggressive phenotypes. Overall, we demonstrate that germline genetics can describe patients' genetic liability to develop specific cancer molecular and clinical profiles.

TRPS1 modulates chromatin accessibility to regulate estrogen receptor alpha (ER) binding and ER target gene expression in luminal breast cancer cells

Common genetic variants in the repressive GATA-family transcription factor (TF) TRPS1 locus are associated with breast cancer risk, and luminal breast cancer cell lines are particularly sensitive to TRPS1 knockout. We introduced an inducible degron tag into the native TRPS1 locus within a luminal breast cancer cell line to identify the direct targets of TRPS1 and determine how TRPS1 mechanistically regulates gene expression. We acutely deplete over 80 percent of TRPS1 from chromatin within 30 minutes of inducing degradation. We find that TRPS1 regulates transcription of hundreds of genes, including those related to estrogen signaling. TRPS1 directly regulates chromatin structure, which causes estrogen receptor alpha (ER) to redistribute in the genome. ER redistribution leads to both repression and activation of dozens of ER target genes. Downstream from these primary effects, TRPS1 depletion represses cell cycle-related gene sets and reduces cell doubling rate. Finally, we show that high TRPS1 activity, calculated using a gene expression signature defined by primary TRPS1-regulated genes, is associated with worse breast cancer patient prognosis. Taken together, these data suggest a model in which TRPS1 modulates the genomic distribution of ER, both activating and repressing transcription of genes related to cancer cell fitness.

FGFR inhibition augments anti-PD-1 efficacy in murine FGFR3-mutant bladder cancer by abrogating immunosuppression

The combination of targeted therapy with immune checkpoint inhibition (ICI) is an area of intense interest. We studied the interaction of fibroblast growth factor receptor (FGFR) inhibition with ICI in urothelial carcinoma (UC) of the bladder, in which FGFR3 is altered in 50% of cases. Using an FGFR3-driven, Trp53-mutant genetically engineered murine model (UPFL), we demonstrate that UPFL tumors recapitulate the histology and molecular subtype of their FGFR3-altered human counterparts. Additionally, UPFL1 allografts exhibit hyperprogression to ICI associated with an expansion of T regulatory cells (Tregs). Erdafitinib blocked Treg proliferation in vitro, while in vivo ICI-induced Treg expansion was fully abrogated by FGFR inhibition. Combined erdafitinib and ICI resulted in high therapeutic efficacy. In aggregate, our work establishes that, in mice, co-alteration of FGFR3 and Trp53 results in high-grade, non-muscle-invasive UC and presents a previously underappreciated role for FGFR inhibition in blocking ICI-induced Treg expansion.

Biomarker potential of the LEF1/TCF family members in breast cancer: Bioinformatic investigation on expression and clinical significance

The LEF1/TCF transcription factor family is related to the development of diverse tissue types, including the mammary tissue, and dysregulation of its expression and function has been described to favor breast tumorigenesis. However, the clinical and biological relevance of this gene family in breast cancer is still poorly understood. Here, we used bioinformatics approaches aiming to reduce this gap. We investigated its expression patterns in molecular and immune breast cancer subtypes; its correlation with immune cell infiltration, and its prognostic values in predicting outcomes. Also, through regulons construction, we determined the genes whose expression is influenced by these transcription factors, and the pathways in which they are involved. We found that LEF1 and TCF3 are over-expressed in breast tumors regarding non-tumor samples, while TCF4 and TCF7 are down-expressed, with the gene's methylation status being associated with its expression dysregulation. All four transcription factors presented significance at the diagnostic and prognostic levels. LEF1, TCF4, and TCF7 presented a significant correlation with immune cell infiltration, being associated with the immune subtypes of less favorable outcomes. Altogether, this research contributes to a more accurate understanding of the expression and clinical and biomarker significance of the LEF1/TCF transcription factors in breast cancer.

An in vitro model of acute horizontal basal cell activation reveals dynamic gene regulatory networks underlying the acute activation phase

Horizontal basal cells (HBCs) activate only in response to severe olfactory epithelium (OE) injury. This activation is mediated by the loss of the transcription factor TP63. Using the compound phorbol 12-myristate 13-acetate (PMA), we find that we can model the process of acute HBC activation. First, we find that PMA treatment induces a rapid loss in TP63 protein and induces the expression of HOPX and the nuclear translocation of RELA, previously identified to mediate HBC activation. Using bulk RNA sequencing, we find that PMA-treated HBCs pass through various stages of acute activation identifiable by transcriptional regulatory signatures that mimic stages identified in vivo . These temporal stages are associated with varying degrees of engraftment and differentiation potential in transplantation assays. Together, this data shows that our model can model physiologically relevant features of HBC activation and identifies new candidates for mechanistic testing.

LncRNA MIR200CHG inhibits EMT in gastric cancer by stabilizing miR-200c from target-directed miRNA degradation

Gastric cancer (GC) is a heterogeneous disease, threatening millions of lives worldwide, yet the functional roles of long non-coding RNAs (lncRNAs) in different GC subtypes remain poorly characterized. Microsatellite stable (MSS)/epithelial-mesenchymal transition (EMT) GC is the most aggressive subtype associated with a poor prognosis. Here, we apply integrated network analysis to uncover lncRNA heterogeneity between GC subtypes, and identify MIR200CHG as a master regulator mediating EMT specifically in MSS/EMT GC. The expression of MIR200CHG is silenced in MSS/EMT GC by promoter hypermethylation, associated with poor prognosis. MIR200CHG reverses the mesenchymal identity of GC cells in vitro and inhibits metastasis in vivo. Mechanistically, MIR200CHG not only facilitates the biogenesis of its intronic miRNAs miR-200c and miR-141, but also protects miR-200c from target-directed miRNA degradation (TDMD) through direct binding to miR-200c. Our studies reveal a landscape of a subtype-specific lncRNA regulatory network, providing clinically relevant biological insights towards MSS/EMT GC.

ELOVL2-AS1 suppresses tamoxifen resistance by sponging miR-1233-3p in breast cancer

Tamoxifen (Tam) has long been a top treatment option for breast cancer patients, but the challenge of eliminating cancer recurrence remains. Here, we identify a signalling pathway involving ELOVL2, ELOVL2-AS1, and miR-1233-3p, which contributes to drug resistance in Tam-resistant (TamR) breast cancer. ELOVL2-AS1, a long noncoding RNA, was significantly upregulated by its antisense gene, ELOVL2, which is known to be downregulated in TamR cells. Additionally, ELOVL2-AS1 underwent the most hypermethylation in MCF-7/TamR cells. Furthermore, patients with breast cancer who developed TamR during chemotherapy had significantly lower expression of ELOVL2-AS1 compared to those who responded to Tam. Ectopic downregulation of ELOVL2-AS1 by siRNA both stimulated cancer cell growth and deteriorated TamR. We also found that ELOVL2-AS1 sponges miR-1233-3p, which has pro-proliferative activity and elevates TamR, leading to the activation of potential target genes, such as MYEF2, NDST1, and PIK3R1. These findings suggest that ELOVL2-AS1, in association with ELOVL2, may contribute to the suppression of drug resistance by sponging miR-1233-3p in breast cancer.

Dual network analysis of transcriptome data for discovery of new therapeutic targets in non-small cell lung cancer

The drug therapy for non-small cell lung cancer (NSCLC) have always been issues of poisonous side effect, acquired drug resistance and narrow applicable population. In this study, we built a novel network analysis method (difference- correlation- enrichment- causality- node), which was based on the difference analysis, Spearman correlation network analysis, biological function analysis and Bayesian causality network analysis to discover new therapeutic target of NSCLC in the sequencing data of BEAS-2B and 7 NSCLC cell lines. Our results showed that, as a proteasome subunit coding gene in the central of cell cycle network, PSMD2 was associated with prognosis and was an independent prognostic factor for NSCLC patients. Knockout of PSMD2 inhibited the proliferation of NSCLC cells by inducing cell cycle arrest, and exhibited marked increase of cell cycle blocking protein p21, p27 and decrease of cell cycle driven protein CDK4, CDK6, CCND1 and CCNE1. IPA and molecular docking suggested bortezomib has stronger affinity to PSMD2 compared with reported targets PSMB1 and PSMB5. In vitro and In vivo experiments demonstrated the inhibitory effect of bortezomib in NSCLC with different driven mutations or with tyrosine kinase inhibitors resistance. Taken together, bortezomib could target PSMD2, PSMB1 and PSMB5 to inhibit the proteasome degradation of cell cycle check points, to block cell proliferation of NSCLC, which was potential optional drug for NSCLC patients.

Silencing of genes by promoter hypermethylation shapes tumor microenvironment and resistance to immunotherapy in clear-cell renal cell carcinomas

The efficacy of immune checkpoint inhibitors varies in clear-cell renal cell carcinoma (ccRCC), with notable primary resistance among patients. Here, we integrate epigenetic (DNA methylation) and transcriptome data to identify a ccRCC subtype characterized by cancer-specific promoter hypermethylation and epigenetic silencing of Polycomb targets. We develop and validate an index of methylation-based epigenetic silencing (iMES) that predicts primary resistance to immune checkpoint inhibition (ICI) in the BIONIKK trial. High iMES is associated with VEGF pathway silencing, endothelial cell depletion, immune activation/suppression, EZH2 activation, BAP1/SETD2 deficiency, and resistance to ICI. Combination therapy with hypomethylating agents or tyrosine kinase inhibitors may benefit patients with high iMES. Intriguingly, tumors with low iMES exhibit increased endothelial cells and improved ICI response, suggesting the importance of angiogenesis in ICI treatment. We also develop a transcriptome-based analogous system for extended applicability of iMES. Our study underscores the interplay between epigenetic alterations and tumor microenvironment in determining immunotherapy response.

An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the commonest cause of chronic liver disease worldwide and represents an unmet precision medicine challenge. We established a retrospective national cohort of 940 histologically defined patients (55.4% men, 44.6% women; median body mass index 31.3; 32% with type 2 diabetes) covering the complete MASLD severity spectrum, and created a secure, searchable, open resource (SteatoSITE). In 668 cases and 39 controls, we generated hepatic bulk RNA sequencing data and performed differential gene expression and pathway analysis, including exploration of gender-specific differences. A web-based gene browser was also developed. We integrated histopathological assessments, transcriptomic data and 5.67 million days of time-stamped longitudinal electronic health record data to define disease-stage-specific gene expression signatures, pathogenic hepatic cell subpopulations and master regulator networks associated with adverse outcomes in MASLD. We constructed a 15-gene transcriptional risk score to predict future hepatic decompensation events (area under the receiver operating characteristic curve 0.86, 0.81 and 0.83 for 1-, 3- and 5-year risk, respectively). Additionally, thyroid hormone receptor beta regulon activity was identified as a critical suppressor of disease progression. SteatoSITE supports rational biomarker and drug development and facilitates precision medicine approaches for patients with MASLD.

A cancer-associated fibroblast subtypes-based signature enables the evaluation of immunotherapy response and prognosis in bladder cancer

Bladder cancer (BLCA) is one of the most prevalent and heterogeneous urinary malignant tumors. Previous researches have reported a significant association between cancer-associated fibroblasts (CAFs) and poor prognosis of tumor patients. However, uncertainty surrounds the role of CAFs in the BLCA tumor microenvironment, necessitating further investigation into the CAFs-related gene signatures in BLCA. In this study, we identified three CAF subtypes in BLCA according to single-cell RNA-seq data and constructed CAFs-related risk score (CRRS) by screening 102,714 signatures. The survival analysis, ROC curves, and nomogram suggested that CRRS was a valuable predictor in 2,042 patients from 9 available public datasets and Xiangya real-world cohort. We further revealed the significant correlation between CRRS and clinicopathological characteristics, genome alterations, and epithelial-mesenchymal transition (EMT). A high CRRS indicated a non-inflamed phenotype and a lower remission rate of immunotherapy in BLCA. In conclusion, the CRRS had the potential to predict the prognosis and immunotherapy response of BLCA patients.

Revealing metastatic castration-resistant prostate cancer master regulator through lncRNAs-centered regulatory network

BACKGROUND

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive form of cancer unresponsive to androgen deprivation therapy (ADT) that spreads quickly to other organs. Despite reduced androgen levels after ADT, mCRPC development and lethality continues to be conducted by the androgen receptor (AR) axis. The maintenance of AR signaling in mCRPC is a result of AR alterations, androgen intratumoral production, and the action of regulatory elements, such as noncoding RNAs (ncRNAs). ncRNAs are key elements in cancer signaling, acting in tumor growth, metabolic reprogramming, and tumor progression. In prostate cancer (PCa), the ncRNAs have been reported to be associated with AR expression, PCa proliferation, and castration resistance. In this study, we aimed to reconstruct the lncRNA-centered regulatory network of mCRPC and identify the lncRNAs which act as master regulators (MRs).

METHODS

We used publicly available RNA-sequencing to infer the regulatory network of lncRNAs in mCRPC. Five gene signatures were employed to conduct the master regulator analysis. Inferred MRs were then subjected to functional enrichment and symbolic regression modeling. The latter approach was applied to identify the lncRNAs with greater predictive capacity and potential as a biomarker in mCRPC.

RESULTS

We identified 31 lncRNAs involved in cellular proliferation, tumor metabolism, and invasion-metastasis cascade. SNHG18 and HELLPAR were the highlights of our results. SNHG18 was downregulated in mCRPC and enriched to metastasis signatures. It accurately distinguished both mCRPC and primary CRPC from normal tissue and was associated with epithelial-mesenchymal transition (EMT) and cell-matrix adhesion pathways. HELLPAR consistently distinguished mCRPC from primary CRPC and normal tissue using only its expression.

CONCLUSION

Our results contribute to understanding the regulatory behavior of lncRNAs in mCRPC and indicate SNHG18 and HELLPAR as master regulators and potential new diagnostic targets in this tumor.

Driver gene combinations dictate cutaneous squamous cell carcinoma disease continuum progression

The molecular basis of disease progression from UV-induced precancerous actinic keratosis (AK) to malignant invasive cutaneous squamous cell carcinoma (cSCC) and potentially lethal metastatic disease remains unclear. DNA sequencing studies have revealed a massive mutational burden but have yet to illuminate mechanisms of disease progression. Here we perform RNAseq transcriptomic profiling of 110 patient samples representing normal sun-exposed skin, AK, primary and metastatic cSCC and reveal a disease continuum from a differentiated to a progenitor-like state. This is accompanied by the orchestrated suppression of master regulators of epidermal differentiation, dynamic modulation of the epidermal differentiation complex, remodelling of the immune landscape and an increase in the preponderance of tumour specific keratinocytes. Comparative systems analysis of human cSCC coupled with the generation of genetically engineered murine models reveal that combinatorial sequential inactivation of the tumour suppressor genes Tgfbr2, Trp53, and Notch1 coupled with activation of Ras signalling progressively drives cSCC progression along a differentiated to progenitor axis. Taken together we provide a comprehensive map of the cSCC disease continuum and reveal potentially actionable events that promote and accompany disease progression.

TRPS1 modulates chromatin accessibility to regulate estrogen receptor (ER) binding and ER target gene expression in luminal breast cancer cells

Breast cancer is the most frequently diagnosed cancer in women. The most common subtype is luminal breast cancer, which is typically driven by the estrogen receptor α (ER), a transcription factor (TF) that activates many genes required for proliferation. Multiple effective therapies target this pathway, but individuals often develop resistance. Thus, there is a need to identify additional targets that regulate ER activity and contribute to breast tumor progression. TRPS1 is a repressive GATA-family TF that is overexpressed in breast tumors. Common genetic variants in the TRPS1 locus are associated with breast cancer risk, and luminal breast cancer cell lines are particularly sensitive to TRPS1 knockout. However, we do not know how TRPS1 regulates target genes to mediate these breast cancer patient and cellular outcomes. We introduced an inducible degron tag into the native TRPS1 locus within a luminal breast cancer cell line to identify the direct targets of TRPS1 and determine how TRPS1 mechanistically regulates gene expression. We acutely deplete over eighty percent of TRPS1 from chromatin within 30 minutes of inducing degradation. We find that TRPS1 regulates transcription of hundreds of genes, including those related to estrogen signaling. TRPS1 directly regulates chromatin structure, which causes ER to redistribute in the genome. ER redistribution leads to both repression and activation of dozens of ER target genes. Downstream from these primary effects, TRPS1 depletion represses cell cycle-related gene sets and reduces cell doubling rate. Finally, we show that high TRPS1 activity, calculated using a gene expression signature defined by primary TRPS1-regulated genes, is associated with worse breast cancer patient prognosis. Taken together, these data suggest a model in which TRPS1 modulates the activity of other TFs, both activating and repressing transcription of genes related to cancer cell fitness.

Differential expression of Dusp1 and immediate early response genes in the hippocampus of rats, subjected to forced swim test

The forced swim test (FST) is widely used to screen for potential antidepressant drugs and treatments. Despite this, the nature of stillness during FST and whether it resembles "depressive-like behavior" are widely debated issues. Furthermore, despite being widely used as a behavioral assay, the effects of the FST on the brain transcriptome are rarely investigated. Therefore, in this study we have investigated changes in the transcriptome of the rat hippocampus 20 min and 24 h after FST exposure. RNA-Seq is performed on the hippocampus tissues of rats 20 min and 24 h after an FST. Differentially expressed genes (DEGs) were identified using limma and used to construct gene interaction networks. Fourteen differentially expressed genes (DEGs) were identified only in the 20-m group. No DEGs were identified 24 h after the FST. These genes were used for Gene Ontology term enrichment and gene-network construction. Based on the constructed gene-interaction networks, we identified a group of DEGs (Dusp1, Fos, Klf2, Ccn1, and Zfp36) that appeared significant based on multiple methods of downstream analysis. Dusp1 appears especially important, as its role in the pathogenesis of depression has been demonstrated both in various animal models of depression and in patients with depressive disorders.

Molecular signature of neutrophil extracellular trap mediating disease module in idiopathic inflammatory myopathy

The rarity and heterogeneity of idiopathic inflammatory myopathy (IIM) pose challenges for researching IIM in affected individuals. We analyzed integrated transcriptomic datasets obtained using muscle tissues from patients with five distinct IIM subtypes to investigate the shared and distinctive cellular and molecular characteristics. A transcriptomic dataset of muscle tissues from normal controls (n = 105) and patients with dermatomyositis (n = 89), polymyositis (n = 33), inclusion body myositis (n = 121), immune-mediated necrotizing myositis (n = 75), and anti-synthetase syndrome (n = 18) was used for differential gene-expression analysis, functional-enrichment analysis, gene set-enrichment analysis, disease-module identification, and kernel-based diffusion scoring. Damage-associated molecular pattern-associated pathways and neutrophil-mediated immunity were significantly enriched across different IIM subtypes, although their activities varied. Interferons-signaling pathways were differentially activated across all five IIM subtypes. In particular, neutrophil extracellular trap (NET) formation was significantly activated and correlated with Fcγ R-mediated signaling pathways. NET formation-associated genes were key for establishing disease modules, and FCGRs, C1QA, and SERPINE1 markedly perturbed the disease modules. Integrated transcriptomic analysis of muscle tissues identified NETs as key components of neutrophil-mediated immunity involved in the pathogenesis of IIM subtypes and, thus, has therapeutically targetable value.

Expression-based subtypes define pathologic response to neoadjuvant immune-checkpoint inhibitors in muscle-invasive bladder cancer

Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced-stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment tumors from the PURE01 neoadjuvant pembrolizumab immunotherapy trial, using a consolidative approach that combined transcriptional and genetic profiling with digital spatial profiling. We identify five distinctive genetic and transcriptomic programs and validate these in an independent neoadjuvant CPI trial to identify the features of response or resistance to CPI. By modeling the regulatory network, we identify the histone demethylase KDM5B as a repressor of tumor immune signaling pathways in one resistant subtype (S1, Luminal-excluded) and demonstrate that inhibition of KDM5B enhances immunogenicity in FGFR3-mutated BCa cells. Our study identifies signatures associated with response to CPI that can be used to molecularly stratify patients and suggests therapeutic alternatives for subtypes with poor response to neoadjuvant immunotherapy.

Nervous system-related gene regulatory networks and functional evolution of ETS proteins across species

The ETS domain transcription factor family is one of the major transcription factor superfamilies that play regulatory roles in development, cell growth, and cancer progression. Although different functions of ETS member proteins in the nervous system have been demonstrated in various studies, their role in neuronal cell differentiation and the evolutionary conservation of its target genes have not yet been extensively studied. In this study, we focused on the regulatory role of ETS transcription factors in neuronal differentiation and their functional evolution by comparative transcriptomics. In order to investigate the regulatory role of ETS transcription factors in neuronal differentiation across species, transcriptional profiles of ETS members and their target genes were investigated by comparing differentially expressed genes and gene regulatory networks, which were analyzed using human, gorilla, mouse, fruit fly and worm transcriptomics datasets. Bioinformatics approaches to examine the evolutionary conservation of ETS transcription factors during neuronal differentiation have shown that ETS member proteins regulate genes associated with neuronal differentiation, nervous system development, axon, and synaptic regulation in different organisms. This study is a comparative transcriptomic study of ETS transcription factors in terms of neuronal differentiation using a gene regulatory network inference algorithm. Overall, a comparison of gene regulation networks revealed that ETS members are indeed evolutionarily conserved in the regulation of neuronal differentiation. Nonetheless, ETS, PEA3, and ELF subfamilies were found to be relatively more active transcription factors in the transcriptional regulation of neuronal differentiation.

Progression-associated molecular changes in basal/squamous and sarcomatoid bladder carcinogenesis

The aggressive basal/squamous (Ba/Sq) bladder cancer (BLCA) subtype is often diagnosed at the muscle-invasive stage and can progress to the sarcomatoid variant. Identification of molecular changes occurring during progression from non-muscle-invasive BLCA (NMIBC) to Ba/Sq muscle-invasive BLCA (MIBC) is thus challenging in human disease. We used the N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) mouse model of Ba/Sq MIBC to study longitudinally the molecular changes leading to the Ba/Sq phenotype and to the sarcomatoid variant using IHC and microdissection followed by RNA-seq at all stages of progression. A shift to the Ba/Sq phenotype started in early progression stages. Pathway analysis of gene clusters with coordinated expression changes revealed Shh signaling loss and a shift from fatty acid metabolism to glycolysis. An upregulated cluster, appearing early in carcinogenesis, showed relevance to human disease, identifying NMIBC patients at risk of progression. Similar to the human counterpart, sarcomatoid BBN tumors displayed a Ba/Sq phenotype and epithelial-mesenchymal transition (EMT) features. An EGFR/FGFR1 signaling switch occurred with sarcomatoid dedifferentiation and correlated with EMT. BLCA cell lines with high EMT were the most sensitive to FGFR1 knockout and resistant to EGFR knockout. Taken together, these findings provide insights into the underlying biology of Ba/Sq BLCA progression and sarcomatoid dedifferentiation with potential clinical implications. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

CRISPR/Cas9 screen uncovers functional translation of cryptic lncRNA-encoded open reading frames in human cancer

Emerging evidence suggests that cryptic translation within long noncoding RNAs (lncRNAs) may produce novel proteins with important developmental/physiological functions. However, the role of this cryptic translation in complex diseases (e.g., cancer) remains elusive. Here, we applied an integrative strategy combining ribosome profiling and CRISPR/Cas9 screening with large-scale analysis of molecular/clinical data for breast cancer (BC) and identified estrogen receptor α-positive (ER+) BC dependency on the cryptic ORFs encoded by lncRNA genes that were upregulated in luminal tumors. We confirmed the in vivo tumor-promoting function of an unannotated protein, GATA3-interacting cryptic protein (GT3-INCP) encoded by LINC00992, the expression of which was associated with poor prognosis in luminal tumors. GTE-INCP was upregulated by estrogen/ER and regulated estrogen-dependent cell growth. Mechanistically, GT3-INCP interacted with GATA3, a master transcription factor key to mammary gland development/BC cell proliferation, and coregulated a gene expression program that involved many BC susceptibility/risk genes and impacted estrogen response/cell proliferation. GT3-INCP/GATA3 bound to common cis regulatory elements and upregulated the expression of the tumor-promoting and estrogen-regulated BC susceptibility/risk genes MYB and PDZK1. Our study indicates that cryptic lncRNA-encoded proteins can be an important integrated component of the master transcriptional regulatory network driving aberrant transcription in cancer, and suggests that the "hidden" lncRNA-encoded proteome might be a new space for therapeutic target discovery.

Steroidogenic Factor 1, a Goldilocks Transcription Factor from Adrenocortical Organogenesis to Malignancy

Steroidogenic factor-1 (SF-1, also termed Ad4BP; NR5A1 in the official nomenclature) is a nuclear receptor transcription factor that plays a crucial role in the regulation of adrenal and gonadal development, function and maintenance. In addition to its classical role in regulating the expression of P450 steroid hydroxylases and other steroidogenic genes, involvement in other key processes such as cell survival/proliferation and cytoskeleton dynamics have also been highlighted for SF-1. SF-1 has a restricted pattern of expression, being expressed along the hypothalamic-pituitary axis and in steroidogenic organs since the time of their establishment. Reduced SF-1 expression affects proper gonadal and adrenal organogenesis and function. On the other hand, SF-1 overexpression is found in adrenocortical carcinoma and represents a prognostic marker for patients' survival. This review is focused on the current knowledge about SF-1 and the crucial importance of its dosage for adrenal gland development and function, from its involvement in adrenal cortex formation to tumorigenesis. Overall, data converge towards SF-1 being a key player in the complex network of transcriptional regulation within the adrenal gland in a dosage-dependent manner.

Transcriptional Profile of Human Pancreatic Acinar Ductal Metaplasia

BACKGROUND AND AIMS

Aberrant acinar to ductal metaplasia (ADM), one of the earliest events involved in exocrine pancreatic cancer development, is typically studied using pancreata from genetically engineered mouse models.

METHODS

We used primary, human pancreatic acinar cells from organ donors to evaluate the transcriptional and pathway profiles during the course of ADM.

RESULTS

Following 6 days of three-dimensional culture on Matrigel, acinar cells underwent morphological and molecular changes indicative of ADM. mRNA from 14 donors' paired cells (day 0, acinar phenotype and day 6, ductal phenotype) was subjected to whole transcriptome sequencing. Acinar cell specific genes were significantly downregulated in the samples from the day 6 cultures while ductal cell-specific genes were upregulated. Several regulons of ADM were identified including transcription factors with reduced activity (PTF1A, RBPJL, and BHLHA15) and those ductal and progenitor transcription factors with increased activity (HNF1B, SOX11, and SOX4). Cells with the ductal phenotype contained higher expression of genes increased in pancreatic cancer while cells with an acinar phenotype had lower expression of cancer-associated genes.

CONCLUSION

Our findings support the relevancy of human in vitro models to study pancreas cancer pathogenesis and exocrine cell plasticity.

The NFIB/CARM1 partnership is a driver in preclinical models of small cell lung cancer

The coactivator associated arginine methyltransferase (CARM1) promotes transcription, as its name implies. It does so by modifying histones and chromatin bound proteins. We identified nuclear factor I B (NFIB) as a CARM1 substrate and show that this transcription factor utilizes CARM1 as a coactivator. Biochemical studies reveal that tripartite motif 29 (TRIM29) is an effector molecule for methylated NFIB. Importantly, NFIB harbors both oncogenic and metastatic activities, and is often overexpressed in small cell lung cancer (SCLC). Here, we explore the possibility that CARM1 methylation of NFIB is important for its transforming activity. Using a SCLC mouse model, we show that both CARM1 and the CARM1 methylation site on NFIB are critical for the rapid onset of SCLC. Furthermore, CARM1 and methylated NFIB are responsible for maintaining similar open chromatin states in tumors. Together, these findings suggest that CARM1 might be a therapeutic target for SCLC.

Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers

Transcriptome-wide association studies (TWAS) have successfully discovered many putative disease susceptibility genes. However, TWAS may suffer from inaccuracy of gene expression predictions due to inclusion of non-regulatory variants. By integrating prior knowledge of susceptible transcription factor occupied elements, we develop sTF-TWAS and demonstrate that it outperforms existing TWAS approaches in both simulation and real data analyses. Under the sTF-TWAS framework, we build genetic models to predict alternative splicing and gene expression in normal breast, prostate and lung tissues from the Genotype-Tissue Expression project and apply these models to data from large genome-wide association studies (GWAS) conducted among European-ancestry populations. At Bonferroni-corrected P < 0.05, we identify 354 putative susceptibility genes for these cancers, including 189 previously unreported in GWAS loci and 45 in loci unreported by GWAS. These findings provide additional insight into the genetic susceptibility of human cancers. Additionally, we show the generalizability of the sTF-TWAS on non-cancer diseases.

The Potential of NORAD-PUMILIO-RALGAPB Regulatory Axis as a Biomarker in Breast Cancer

Introduction: Long non-coding RNAs (LncRNA) represent a heterogeneous family of RNAs that have emerged as regulators of various biological processes through their association with proteins in ribonucleoproteins complexes. The dynamic of these interactions can affect cell metabolism, including cancer development. Annually, breast cancer causes thousands of deaths worldwide, and searching for new biomarkers is pivotal for better diagnosis and treatment. Methods: Based on in silico prediction analysis, we focus on LncRNAs that have binding sites for PUMILIO, an RBP family involved in post-transcriptional regulation and associated with cancer progression. We compared the expression levels of these LncRNAs in breast cancer and non-tumor samples from the TCGA database. We analyzed the impact of overall and disease-free survival associated with the expression of the LncRNAs and co-expressed genes and targets of PUMILIO proteins. Results: Our results found NORAD as the most relevant LncRNA with a PUMILIO binding site in breast cancer, differently expressed between Luminal A and Basal subtypes. Additionally, NORAD was co-expressed in a Basal-like subtype (0.55) with the RALGAPB gene, a target gene of PUMILIO related to chromosome stability during cell division. Conclusion: These data suggest that this molecular axis may provide insights for developing novel therapeutic strategies for breast cancer.

FOXA1 repression drives lineage plasticity and immune heterogeneity in bladder cancers with squamous differentiation

Cancers arising from the bladder urothelium often exhibit lineage plasticity with regions of urothelial carcinoma adjacent to or admixed with regions of divergent histomorphology, most commonly squamous differentiation. To define the biologic basis for and clinical significance of this morphologic heterogeneity, here we perform integrated genomic analyses of mixed histology bladder cancers with separable regions of urothelial and squamous differentiation. We find that squamous differentiation is a marker of intratumoral genomic and immunologic heterogeneity in patients with bladder cancer and a biomarker of intrinsic immunotherapy resistance. Phylogenetic analysis confirms that in all cases the urothelial and squamous regions are derived from a common shared precursor. Despite the presence of marked genomic heterogeneity between co-existent urothelial and squamous differentiated regions, no recurrent genomic alteration exclusive to the urothelial or squamous morphologies is identified. Rather, lineage plasticity in bladder cancers with squamous differentiation is associated with loss of expression of FOXA1, GATA3, and PPARG, transcription factors critical for maintenance of urothelial cell identity. Of clinical significance, lineage plasticity and PD-L1 expression is coordinately dysregulated via FOXA1, with patients exhibiting morphologic heterogeneity pre-treatment significantly less likely to respond to immune checkpoint inhibitors.

CRISPRi screens in human iPSC-derived astrocytes elucidate regulators of distinct inflammatory reactive states

Astrocytes become reactive in response to insults to the central nervous system by adopting context-specific cellular signatures and outputs, but a systematic understanding of the underlying molecular mechanisms is lacking. In this study, we developed CRISPR interference screening in human induced pluripotent stem cell-derived astrocytes coupled to single-cell transcriptomics to systematically interrogate cytokine-induced inflammatory astrocyte reactivity. We found that autocrine-paracrine IL-6 and interferon signaling downstream of canonical NF-κB activation drove two distinct inflammatory reactive signatures, one promoted by STAT3 and the other inhibited by STAT3. These signatures overlapped with those observed in other experimental contexts, including mouse models, and their markers were upregulated in human brains in Alzheimer's disease and hypoxic-ischemic encephalopathy. Furthermore, we validated that markers of these signatures were regulated by STAT3 in vivo using a mouse model of neuroinflammation. These results and the platform that we established have the potential to guide the development of therapeutics to selectively modulate different aspects of inflammatory astrocyte reactivity.

Comprehensive Characterization of the Regulatory Landscape of Adrenocortical Carcinoma: Novel Transcription Factors and Targets Associated with Prognosis

We reconstructed a transcriptional regulatory network for adrenocortical carcinoma (ACC) using transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)-ACC cohort. We investigated the association of transcriptional regulatory units (regulons) with overall survival, molecular phenotypes, and immune signatures. We annotated the ACC regulons with cancer hallmarks and assessed single sample regulon activities in the European Network for the Study of Adrenal Tumors (ENSAT) cohort. We found 369 regulons associated with overall survival and subdivided them into four clusters: RC1 and RC2, associated with good prognosis, and RC3 and RC4, associated with worse outcomes. The RC1 and RC3 regulons were highly correlated with the 'Steroid Phenotype,' while the RC2 and RC4 regulons were highly correlated with a molecular proliferation signature. We selected two regulons, NR5A1 (steroidogenic factor 1, SF-1) and CENPA (Centromeric Protein A), that were consistently associated with overall survival for further downstream analyses. The CENPA regulon was the primary regulator of MKI-67 (a marker of proliferation KI-67), while the NR5A1 regulon is a well-described transcription factor (TF) in ACC tumorigenesis. We also found that the ZBTB4 (Zinc finger and BTB domain-containing protein 4) regulon, which is negatively associated with CENPA in our transcriptional regulatory network, is also a druggable anti-tumorigenic TF. We anticipate that the ACC regulons may be used as a reference for further investigations concerning the complex molecular interactions in ACC tumors.

Network analysis to identify symptoms clusters and temporal interconnections in oncology patients

Oncology patients experience numerous co-occurring symptoms during their treatment. The identification of sentinel/core symptoms is a vital prerequisite for therapeutic interventions. In this study, using Network Analysis, we investigated the inter-relationships among 38 common symptoms over time (i.e., a total of six time points over two cycles of chemotherapy) in 987 oncology patients with four different types of cancer (i.e., breast, gastrointestinal, gynaecological, and lung). In addition, we evaluated the associations between and among symptoms and symptoms clusters and examined the strength of these interactions over time. Eight unique symptom clusters were identified within the networks. Findings from this research suggest that changes occur in the relationships and interconnections between and among co-occurring symptoms and symptoms clusters that depend on the time point in the chemotherapy cycle and the type of cancer. The evaluation of the centrality measures provides new insights into the relative importance of individual symptoms within various networks that can be considered as potential targets for symptom management interventions.

A transcriptional network of cell cycle dysregulation in noninvasive papillary urothelial carcinoma

Human cancers display a restricted set of expression profiles, despite diverse mutational drivers. This has led to the hypothesis that select sets of transcription factors act on similar target genes as an integrated network, buffering a tumor's transcriptional state. Noninvasive papillary urothelial carcinoma (NIPUC) with higher cell cycle activity has higher risk of recurrence and progression. In this paper, we describe a transcriptional network of cell cycle dysregulation in NIPUC, which was delineated using the ARACNe algorithm applied to expression data from a new cohort (n = 81, RNA sequencing), and two previously published cohorts. The transcriptional network comprised 121 transcription factors, including the pluripotency factors SOX2 and SALL4, the sex hormone binding receptors ESR1 and PGR, and multiple homeobox factors. Of these 121 transcription factors, 65 and 56 were more active in tumors with greater and less cell cycle activity, respectively. When clustered by activity of these transcription factors, tumors divided into High Cell Cycle versus Low Cell Cycle groups. Tumors in the High Cell Cycle group demonstrated greater mutational burden and copy number instability. A putative mutational driver of cell cycle dysregulation, such as homozygous loss of CDKN2A, was found in only 50% of High Cell Cycle NIPUC, suggesting a prominent role of transcription factor activity in driving cell cycle dysregulation. Activity of the 121 transcription factors strongly associated with expression of EZH2 and other members of the PRC2 complex, suggesting regulation by this complex influences expression of the transcription factors in this network. Activity of transcription factors in this network also associated with signatures of pluripotency and epithelial-to-mesenchymal transition (EMT), suggesting they play a role in driving evolution to invasive carcinoma. Consistent with this, these transcription factors differed in activity between NIPUC and invasive urothelial carcinoma.

Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data

Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as ‘signaling hubs’. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called ‘SURFACER’. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.

Immune depletion of the methylated phenotype of colon cancer is closely related to resistance to immune checkpoint inhibitors

Background

Molecular typing based on single omics data has its limitations and requires effective integration of multiple omics data for tumor typing of colorectal cancer (CRC).

Methods

Transcriptome expression, DNA methylation, somatic mutation, clinicopathological information, and copy number variation were retrieved from TCGA, UCSC Xena, cBioPortal, FireBrowse, or GEO. After pre-processing and calculating the clustering prediction index (CPI) with gap statistics, integrative clustering analysis was conducted via MOVICS. The tumor microenvironment (TME) was deconvolved using several algorithms such as GSVA, MCPcounter, ESTIMATE, and PCA. The metabolism-relevant pathways were extracted through ssGSEA. Differential analysis was based on limma and enrichment analysis was carried out by Enrichr. DNA methylation and transcriptome expression were integrated via ELMER. Finally, nearest template or hemotherapeutic sensitivity prediction was conducted using NTP or pRRophetic.

Results

Three molecular subtypes (CS1, CS2, and CS3) were recognized by integrating transcriptome, DNA methylation, and driver mutations. CRC patients in CS3 had the most favorable prognosis. A total of 90 differentially mutated genes among the three CSs were obtained, and CS3 displayed the highest tumor mutation burden (TMB), while significant instability across the entire chromosome was observed in the CS2 group. A total of 30 upregulated mRNAs served as classifiers were identified and the similar diversity in clinical outcomes of CS3 was validated in four external datasets. The heterogeneity in the TME and metabolism-related pathways were also observed in the three CSs. Furthermore, we found CS2 tended to loss methylations while CS3 tended to gain methylations. Univariate and multivariate Cox regression revealed that the subtypes were independent prognostic factors. For the drug sensitivity analysis, we found patients in CS2 were more sensitive to ABT.263, NSC.87877, BIRB.0796, and PAC.1. By Integrating with the DNA mutation and RNA expression in CS3, we identified that SOX9, a specific marker of CS3, was higher in the tumor than tumor adjacent by IHC in the in-house cohort and public cohort.

Conclusion

The molecular subtypes based on integrated multi-omics uncovered new insights into the prognosis, mechanisms, and clinical therapeutic targets for CRC.

Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia

KMT2A-rearranged infant acute lymphoblastic leukemia (ALL) represents the most refractory type of childhood leukemia. To uncover the molecular heterogeneity of this disease, we perform RNA sequencing, methylation array analysis, whole exome and targeted deep sequencing on 84 infants with KMT2A-rearranged leukemia. Our multi-omics clustering followed by single-sample and single-cell inference of hematopoietic differentiation establishes five robust integrative clusters (ICs) with different master transcription factors, fusion partners and corresponding stages of B-lymphopoietic and early hemato-endothelial development: IRX-type differentiated (IC1), IRX-type undifferentiated (IC2), HOXA-type MLLT1 (IC3), HOXA-type MLLT3 (IC4), and HOXA-type AFF1 (IC5). Importantly, our deep mutational analysis reveals that the number of RAS pathway mutations predicts prognosis and that the most refractory subgroup of IC2 possesses 100% frequency and the heaviest burden of RAS pathway mutations. Our findings highlight the previously under-appreciated intra- and inter-patient heterogeneity of KMT2A-rearranged infant ALL and provide a rationale for the future development of genomics-guided risk stratification and individualized therapy.

Multi-omics data integration and modeling unravels new mechanisms for pancreatic cancer and improves prognostic prediction

Pancreatic ductal adenocarcinoma (PDAC), has recently been found to be a heterogeneous disease, although the extension of its diversity remains to be fully understood. Here, we harmonize transcriptomic profiles derived from both PDAC epithelial and microenvironment cells to develop a Master Regulators (MR)-Gradient model that allows important inferences on transcriptional networks, epigenomic states, and metabolomics pathways that underlies this disease heterogeneity. This gradient model was generated by applying a blind source separation based on independent components analysis and robust principal component analyses (RPCA), following regulatory network inference. The result of these analyses reveals that PDAC prognosis strongly associates with the tumor epithelial cell phenotype and the immunological component. These studies were complemented by integration of methylome and metabolome datasets generated from patient-derived xenograft (PDX), together experimental measurements of metabolites, immunofluorescence microscopy, and western blot. At the metabolic level, PDAC favorable phenotype showed a positive correlation with enzymes implicated in complex lipid biosynthesis. In contrast, the unfavorable phenotype displayed an augmented OXPHOS independent metabolism centered on the Warburg effect and glutaminolysis. Epigenetically, we find that a global hypermethylation profile associates with the worst prognosis. Lastly, we report that, two antagonistic histone code writers, SUV39H1/SUV39H2 (H3K9Me3) and KAT2B (H3K9Ac) were identified key deregulated pathways in PDAC. Our analysis suggests that the PDAC phenotype, as it relates to prognosis, is determined by a complex interaction of transcriptomic, epigenomic, and metabolic features. Furthermore, we demonstrated that PDAC prognosis could be modulated through epigenetics.

Transcription factor network analysis identifies REST/NRSF as an intrinsic regulator of CNS regeneration in mice

The inability of neurons to regenerate long axons within the CNS is a major impediment to improving outcome after spinal cord injury, stroke, and other CNS insults. Recent advances have uncovered an intrinsic program that involves coordinate regulation by multiple transcription factors that can be manipulated to enhance growth in the peripheral nervous system. Here, we use a systems genomics approach to characterize regulatory relationships of regeneration-associated transcription factors, identifying RE1-Silencing Transcription Factor (REST; Neuron-Restrictive Silencer Factor, NRSF) as a predicted upstream suppressor of a pro-regenerative gene program associated with axon regeneration in the CNS. We validate our predictions using multiple paradigms, showing that mature mice bearing cell type-specific deletions of REST or expressing dominant-negative mutant REST show improved regeneration of the corticospinal tract and optic nerve after spinal cord injury and optic nerve crush, which is accompanied by upregulation of regeneration-associated genes in cortical motor neurons and retinal ganglion cells, respectively. These analyses identify a role for REST as an upstream suppressor of the intrinsic regenerative program in the CNS and demonstrate the utility of a systems biology approach involving integrative genomics and bio-informatics to prioritize hypotheses relevant to CNS repair.

The origin of bladder cancer from mucosal field effects

Whole-organ mapping was used to study molecular changes in the evolution of bladder cancer from field effects. We identified more than 100 dysregulated pathways, involving immunity, differentiation, and transformation, as initiators of carcinogenesis. Dysregulation of interleukins signified the involvement of inflammation in the incipient phases of the process. An aberrant methylation/expression of multiple HOX genes signified dysregulation of the differentiation program. We identified three types of mutations based on their geographic distribution. The most common were mutations restricted to individual mucosal samples that targeted uroprogenitor cells. Two types of mutations were associated with clonal expansion and involved large areas of mucosa. The α mutations occurred at low frequencies while the β mutations increased in frequency with disease progression. Modeling revealed that bladder carcinogenesis spans 10-15 years and can be divided into dormant and progressive phases. The progressive phase lasted 1-2 years and was driven by β mutations.

Role of germline variants in the metastasis of breast carcinomas

Most cancer-related deaths in breast cancer patients are associated with metastasis, a multistep, intricate process that requires the cooperation of tumour cells, tumour microenvironment and metastasis target tissues. It is accepted that metastasis does not depend on the tumour characteristics but the host’s genetic makeup. However, there has been limited success in determining the germline genetic variants that influence metastasis development, mainly because of the limitations of traditional genome-wide association studies to detect the relevant genetic polymorphisms underlying complex phenotypes. In this work, we leveraged the extreme discordant phenotypes approach and the epistasis networks to analyse the genotypes of 97 breast cancer patients. We found that the host’s genetic makeup facilitates metastases by the dysregulation of gene expression that can promote the dispersion of metastatic seeds and help establish the metastatic niche—providing a congenial soil for the metastatic seeds.

Development of a miRNA-based classifier for detection of colorectal cancer molecular subtypes

Previously, colorectal cancer (CRC) has been classified into four distinct molecular subtypes based on transcriptome data. These consensus molecular subtypes (CMSs) have implications for our understanding of tumor heterogeneity and the prognosis of patients. So far, this classification has been based on the use of messenger RNAs (mRNAs), although microRNAs (miRNAs) have also been shown to play a role in tumor heterogeneity and biological differences between CMSs. In contrast to mRNAs, miRNAs have a smaller size and increased stability, facilitating their detection. Therefore, we built a miRNA-based CMS classifier by converting the existing mRNA-based CMS classification using machine learning (training dataset of n = 271). The performance of this miRNA-assigned CMS classifier (CMS-miRaCl) was evaluated in several datasets, achieving an overall accuracy of ~ 0.72 (0.6329-0.7987) in the largest dataset (n = 158). To gain insight into the biological relevance of CMS-miRaCl, we evaluated the most important features in the classifier. We found that miRNAs previously reported to be relevant in microsatellite-instable CRCs or Wnt signaling were important features for CMS-miRaCl. Following further studies to validate its robustness, this miRNA-based alternative might simplify the implementation of CMS classification in clinical workflows.

Combined exome and transcriptome sequencing of non-muscle-invasive bladder cancer: associations between genomic changes, expression subtypes, and clinical outcomes

BACKGROUND

Three-quarters of bladder cancer patients present with early-stage disease (non-muscle-invasive bladder cancer, NMIBC, UICC TNM stages Ta, T1 and Tis); however, most next-generation sequencing studies to date have concentrated on later-stage disease (muscle-invasive BC, stages T2+). We used exome and transcriptome sequencing to comprehensively characterise NMIBCs of all grades and stages to identify prognostic genes and pathways that could facilitate treatment decisions. Tumour grading is based upon microscopy and cellular appearances (grade 1 BCs are less aggressive, and grade 3 BCs are most aggressive), and we chose to also focus on the most clinically complex NMIBC subgroup, those patients with grade 3 pathological stage T1 (G3 pT1) disease.

METHODS

Whole-exome and RNA sequencing were performed in total on 96 primary NMIBCs including 22 G1 pTa, 14 G3 pTa and 53 G3 pT1s, with both exome and RNA sequencing data generated from 75 of these individual samples. Associations between genomic alterations, expression profiles and progression-free survival (PFS) were investigated.

RESULTS

NMIBCs clustered into 3 expression subtypes with different somatic alteration characteristics. Amplifications of ARNT and ERBB2 were significant indicators of worse PFS across all NMIBCs. High APOBEC mutagenesis and high tumour mutation burden were both potential indicators of better PFS in G3pT1 NMIBCs. The expression of individual genes was not prognostic in BCG-treated G3pT1 NMIBCs; however, downregulated interferon-alpha and gamma response pathways were significantly associated with worse PFS (adjusted p-value < 0.005).

CONCLUSIONS

Multi-omic data may facilitate better prognostication and selection of therapeutic interventions in patients with G3pT1 NMIBC. These findings demonstrate the potential for improving the management of high-risk NMIBC patients and warrant further prospective validation.

High-Throughput Profiling of Colorectal Cancer Liver Metastases Reveals Intra- and Inter-Patient Heterogeneity in the EGFR and WNT Pathways Associated with Clinical Outcome

Simple Summary

Tumor heterogeneity can greatly influence therapy outcome and patient survival. In this study, we aimed at unraveling inter- and intra-patient heterogeneity of colorectal cancer liver metastases (CRLM). To this end, we comprehensively characterized CRLM using state-of-the-art high-throughput technologies combined with bioinformatics analyses. We found a high degree of inter- and intra-patient heterogeneity among the metastases, in particular in genes of the WNT and EGFR pathways. Through analyzing the master regulators and effectors associated with the regulation of these genes, we identified a specific gene signature that was highly expressed in a large cohort of colorectal cancer patients and associated with clinical outcome.

Abstract

Seventy percent of patients with colorectal cancer develop liver metastases (CRLM), which are a decisive factor in cancer progression. Therapy outcome is largely influenced by tumor heterogeneity, but the intra- and inter-patient heterogeneity of CRLM has been poorly studied. In particular, the contribution of the WNT and EGFR pathways, which are both frequently deregulated in colorectal cancer, has not yet been addressed in this context. To this end, we comprehensively characterized normal liver tissue and eight CRLM from two patients by standardized histopathological, molecular, and proteomic subtyping. Suitable fresh-frozen tissue samples were profiled by transcriptome sequencing (RNA-Seq) and proteomic profiling with reverse phase protein arrays (RPPA) combined with bioinformatic analyses to assess tumor heterogeneity and identify WNT- and EGFR-related master regulators and metastatic effectors. A standardized data analysis pipeline for integrating RNA-Seq with clinical, proteomic, and genetic data was established. Dimensionality reduction of the transcriptome data revealed a distinct signature for CRLM differing from normal liver tissue and indicated a high degree of tumor heterogeneity. WNT and EGFR signaling were highly active in CRLM and the genes of both pathways were heterogeneously expressed between the two patients as well as between the synchronous metastases of a single patient. An analysis of the master regulators and metastatic effectors implicated in the regulation of these genes revealed a set of four genes (SFN, IGF2BP1, STAT1, PIK3CG) that were differentially expressed in CRLM and were associated with clinical outcome in a large cohort of colorectal cancer patients as well as CRLM samples. In conclusion, high-throughput profiling enabled us to define a CRLM-specific signature and revealed the genes of the WNT and EGFR pathways associated with inter- and intra-patient heterogeneity, which were validated as prognostic biomarkers in CRC primary tumors as well as liver metastases.

Identification and Validation of N6-Methyladenosine-Related Biomarkers for Bladder Cancer: Implications for Immunotherapy

N6-methyladenosine (m⁶A) has emerged as one of the most important modifications of RNA. Based on the expression of 23 different modes of m⁶A regulatory factors, we identified three different m⁶A modification patterns in bladder cancer. The effects of the three different modes of m⁶A modification on clinicopathological characteristics, immune cell infiltration levels and expression levels of immune checkpoint genes were comprehensively analyzed. In addition, the effects of different modes of m⁶A modification on the therapeutic efficacy of anti-PD-L1 immunotherapy (atezolizumab) are also discussed. Our results confirm that m⁶A methylation plays an important role in immune cell recruitment in the tumor microenvironment of bladder cancer, which influences the efficacy of anti-PD-L1 therapy for bladder cancer. We further confirmed the important role of FTO protein in the biological function of bladder cancer cells by performing in vitro experiments. FTO functions as an oncogene in bladder cancer cells, and upon FTO knockdown, the level of m⁶A enzyme activity in bladder cancer cells was significantly increased, apoptosis was increased, and cell proliferation and cell invasion were reduced. In addition, our study also confirmed that K216H and K216E are probably important targets for regulating FTO. We provide new insights into the regulatory pathways of the immune microenvironment and the methylation function of m⁶A in bladder cancer, which will help in designing novel diagnostic methods, prognostic tools, and therapeutic targets.