Comprehensive Integrative Analysis Research Articles

Alternative splicing and intron retention: Their profiles and roles in cutaneous fibrosis of systemic sclerosis

BackgroundAlternative splicing (AS) and intron retention (IR) implicated in multiple pathophysiological processes, have rarely been reported in systemic sclerosis (SSc). MethodsWe integrated bulk RNA-seq and 4D label-free mass spectrometry to perform a multi-omics analysis of AS and IR in SSc skin tissue and fibroblasts. RMATS and iREAD were used to identify AS and IR, which were validated by real-time PCR. Spearman correlation and the LASSO method were employed to assess correlations among clinical features, introns, splicing factors (regulators of AS) and proteins. FindingsAS profiles showed distinct alterations in SSc skin tissue, with the most pronounced changes occurring in IR. AS and IR were associated with total modified Rodnan skin score (mRSS) and local skin score. Upon TGF-β stimulation, fibroblasts exhibited significant alterations in IR profiles, affecting genes related to fibroblast proliferation and collagen fibril organization. A comprehensive integrated analysis of introns, exons, and proteome profiles revealed that IR exerted a negative impact on protein expression, with certain changes being under intronic control. RT-PCR confirmed the presence of intron and exon-derived sequences of CTTN, OGA, MED16 and PHYKPL. Additionally, notable changes were observed in the regulatory network of splicing factors in SSc skin tissues. These factors are also involved in fibrosis pathways and correlated with clinical features. ConclusionTotally, abnormal AS, IR profiles and splicing factors were identified in SSc, altered IRs and splicing factors participated in fibrosis-related pathways. IR exerted a negative impact on protein expression in TGF-β-stimulated fibroblasts. Clarification of the IR mechanisms will provide new insights into the pathophysiology of SSc.

Proteo-metabolomics and patient tumor slice experiments point to amino acid centrality for rewired mitochondria in fibrolamellar carcinoma

Fibrolamellar carcinoma (FLC) is a rare, lethal, early-onset liver cancer with a critical need for new therapeutics. The primary driver in FLC is the fusion oncoprotein, DNAJ-PKAc, which remains challenging to target therapeutically. It is critical, therefore, to expand understanding of the FLC molecular landscape to identify druggable pathways/targets. Here, we perform the most comprehensive integrative proteo-metabolomic analysis of FLC. We also conduct nutrient manipulation, respirometry analyses, as well as key loss-of-function assays in FLC tumor tissue slices from patients. We propose a model of cellular energetics in FLC pointing to proline anabolism being mediated by ornithine aminotransferase hyperactivity and ornithine transcarbamylase hypoactivity with serine and glutamine catabolism fueling the process. We highlight FLC's potential dependency on voltage-dependent anion channel (VDAC), a mitochondrial gatekeeper for anions including pyruvate. The metabolic rewiring in FLC that we propose in our model, with an emphasis on mitochondria, can be exploited for therapeutic vulnerabilities.

Hypoxia Stimulates PYGB Enzymatic Activity to Promote Glycogen Metabolism and Cholangiocarcinoma Progression.

Cholangiocarcinoma (CCA) displays enhanced glycolysis, pivotal for fulfilling the heightened energy demands intrinsic to its malignant progression. Recent research has indicated that endogenous glycogen rather than exogenous glucose acts as the major carbon source for glycolysis, highlighting the need to better understand the regulation of glycogen homeostasis in CCA. Here, through comprehensive integrative analysis, we identified that glycogen phosphorylase brain form (PYGB), the main enzyme involved in glycogen homeostasis, was markedly upregulated in CCA tissues, serving as an independent prognostic indicator for human CCA patients. Moreover, elevated PYGB expression potentiated cholangiocarcinogenesis and augmented CCA cell proliferation in both organoid and xenograft models. Hypoxia stimulated PYGB activity in a phosphoglycerate kinase 1 (PGK1)-dependent manner, leading to glycogenolysis and the subsequent release of glucose-6-phosphate (G6P) and thereby facilitating aerobic glycolysis. Notably, a virtual screening pinpointed the beta-blocker carvedilol as a potent pharmacological inhibitor of PYGB that could attenuate CCA progression. Collectively, these findings position PYGB as a promising prognostic biomarker and therapeutic target for CCA.

Small Municipalities in the Amazon under the Risk of Future Climate Change

The focus of this work is on small municipalities (population below 50 thousand inhabitants) that cover around 87% of the territory of the Brazilian Legal Amazon (BLA). Based on a comprehensive integrated analysis approach using the three components hazard (climate extremes from CMIP6 future scenarios), exposure (directly affected population), and vulnerability (subdimensions of susceptibility and coping/adaptive capacity by using multidimensional indicators), the latter two using current datasets provided by the official Census IBGE 2022, we document a quantitative assessment of the risk R of natural disasters in the BLA region. We evidenced a worrying and imminent intensification of the curve of R in most Amazonian municipalities over the next two 25-year periods. The overall results of the highest proportions of R (total municipalities affected) pointed out the Amazonas, Roraima, Pará, and Maranhão as the main states, presenting projected categories of R high in the near future (2015 to 2039) and very high in the far future (2040 to 2064). The detailed assessment of the susceptibility and coping/adaptive capacity allowed us to elucidate the principal indicators that aggravate the degree of vulnerability: economy, the precariousness of urban infrastructure, medical services, communication, and urban mobility, whose combined factors, unfortunately, reveal a widespread poverty profile along the small Amazonian municipalities. Our scientific findings can assist decision makers in targeted strategies planning and public policies to minimize and mitigate ongoing and future climate change.

Potential diagnostic and drug target markers in glioblastoma

Glioblastoma multiforme (GBM) IDH-wildtype is the most prevalent brain malignancy in adults. However, molecular mechanisms, which leads to GBM have not been completely elucidated. Granulocyte colony-stimulating factor (GCSF), Granulocyte colony-stimulating factor receptor GCSFR, and Signal transducers and activators of transcription 3 (STAT3) have been involved in the occurrence and development of various cancers, but their role in GBM is little known. Herein, we have investigated the gene and protein expression of GCSF, GCSFR, and STAT3 in 21 tissue biopsy samples and also in tumor associated normal tissue (TANT) samples derived from glioblastoma patients, which revealed significantly differential expression of these genes. To validate our findings, we performed a comprehensive integrated analysis of transcriptomic and proteomic profiling of respective genes by retrieving GBM RNA-sequence data from Genome Atlas Databases. GO and KEGG analysis revealed enrichment in disease-related pathways, such as JAK/STAT pathway activation, which were associated with GBM progression. We further performed computational docking analysis of potential drug candidate Nisin against GCSF, and the results were validated in vitro through cytotoxic activity assay using a human glioblastoma cell line SF-767 in a dose-dependent manner. Our comprehensive analysis reveals that GCSF augments glioma progression, and its blockade with anticancer bacteriocin peptide Nisin can potentially inhibit the growth and metastasis of GBM.

Abstract 6414: Molecular differentiation between complete and incomplete responders to neoadjuvant therapy in rectal cancer

Abstract Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment for locally advanced rectal cancer, but only 20-40% of patients completely respond to this treatment. This study aims to identify the molecular features associated with a response to nCRT. We generated and collected genomic and transcriptomic data from 712 cancers prior to treatment from our own data and from publicly available data. A comprehensive integrated analysis was performed. We found that patients with a complete response have decreased risk of both local recurrence and future metastasis. We identified multiple molecular differences between complete and incomplete responders. Complete responders have a higher tumor mutation burden and more significant co-occurring mutations than the incomplete responders. In addition, mutations in DNA repair genes were enriched in complete responders and they also had lower expression of these genes indicating that defective DNA repair is associated with complete response to nCRT. Using logistic regression, we identified three significant predictors of complete response: tumor size, mutations within specific network genes, and the existence of three or more specific co-occurrent mutations. In incompletely responder tumors, abnormal cell-cell interaction and increased cancer associated fibroblasts were associated with recurrence. Additionally, gene expression analysis identified a subset of immune hot tumors with worse outcomes and upregulation of immune checkpoint proteins. Our study directly informs the clinical management of rectal cancer by elucidating the molecular differences between tumors with complete and incomplete responses to neoadjuvant chemoradiotherapy (nCRT), as well as the features of tumors prone to recurrence. We have pinpointed critical molecular markers and clinical indicators—such as tumor size, specific gene mutations, and particular mutation patterns—that are significant predictors of treatment response. These findings offer valuable biomarkers for personalizing treatment strategies. Additionally, the observed mutation enrichment in DNA repair genes among complete responders suggests new avenues for therapeutic innovation. By highlighting the distinct molecular and immune profiles of non-responder tumors at higher recurrence risk, our research supports the advancement of precision oncology approaches, enhancing prognosis and treatment customization in rectal cancer care, ultimately striving to bridge the gap between scientific discovery and clinical application. Citation Format: Fengyuan Huang, M. Chandler McLeod, Regina Kay Irwin, Mary Smithson, Zongliang Yue, Min Gao, Karin M. Hardiman, Zechen Chong. Molecular differentiation between complete and incomplete responders to neoadjuvant therapy in rectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6414.

MvlearnR and Shiny App for multiview learning.

The package mvlearnR and accompanying Shiny App is intended for integrating data from multiple sources or views or modalities (e.g. genomics, proteomics, clinical, and demographic data). Most existing software packages for multiview learning are decentralized and offer limited capabilities, making it difficult for users to perform comprehensive integrative analysis. The new package wraps statistical and machine learning methods and graphical tools, providing a convenient and easy data integration workflow. For users with limited programming language, we provide a Shiny Application to facilitate data integration anywhere and on any device. The methods have potential to offer deeper insights into complex disease mechanisms. mvlearnR is available from the following GitHub repository: https://github.com/lasandrall/mvlearnR. The web application is hosted on shinyapps.io and available at: https://multi-viewlearn.shinyapps.io/MultiView_Modeling/.

Strategies of Integrated Analysis of ATAC-seq and RNA-seq Data

The ATAC-seq and RNA-seq have been widely used in the epigenomes analysis of mammals. However, there is a lack of comprehensive integrated analysis of ATAC-seq and RNA-seq data. Here, we explored two effective strategies for analyzing ATAC-seq and RNA-seq data using proliferation and differentiation myoblast cells as model. One strategy is a joint analysis by integrating Hi-C data with ATAC-seq and RNA-seq data. The other strategy is to investigate the association between ATAC-seq and RNA-seq data only based on genome physical distance in the case of no availability of Hi-C data. Hi-C data-based integrated analysis showed a strong correlation between genes and distal enhancers, particularly between genes and promoters, within the topologically associated domains (TADs) and chromatin loops. In the absence of Hi-C data, the integrated analysis based on 500 kb physical distance between genes and associated peaks revealed a strong positive correlation between gene expression and chromatin accessibility. Moreover, the function enrichment analysis indicated that both integrated analysis results could reflect the cellular states. Our proposed two integrated analysis strategies combine ATAC-seq and RNA-seq data, which lay a foundation for subsequent epigenetics studies.

Alterations of small non-coding RNA in the spermatozoa of mice with paternal experimental autoimmune epididymo-orchitis are associated with metabolic dysfunction in offspring.

Infection and inflammation of the genital tract are major potentially treatable factors contributing to male infertility. The profile of small non-coding RNA (sncRNAs) in spermatozoa can be altered by environmental exposures and inflammatory conditions. Experimental autoimmune epididymo-orchitis (EAEO) is a well-established model of autoimmune-induced chronic testicular and epididymal inflammation. This model investigates the effect of chronic inflammation on sperm sncRNA profiles and offspring phenotypes. Regarding the EAEO model, mice were immunized with testis homogenates thrice. Subsequently, flow cytometry and histological analyses were conducted on EAEO mice. Next-generation sequencing was used to profile small RNA of spermatozoa from the caput, corpus, and cauda epididymis. We performed a comprehensive integrative analysis of sperm sncRNAs and chronic epididymitis and identified their molecular signatures. The metabolic functions of the first-generation (F1) offspring were evaluated using a glucose tolerance test (GTT). Body weight and metabolic function were significantly altered in F1 offspring from EAEO sperm donors. The analysis of cauda sperm sncRNA profiles revealed that the proportions of miRNAs and tsRNAs increased and decreased, respectively, after autoimmunization. Three differentially expressed miRNAs and seven differentially expressed tsRNAs were significantly correlated with F1 metabolic dysfunction. The expression patterns of miRNAs and tsRNAs in mice partially overlapped with those observed in the spermatozoa from human patients with chronic epididymitis. We revealed that autoimmune epididymo-orchitis alters sncRNA profiles in mouse spermatozoa. Offspring from mice with autoimmune orchitis develop metabolic disorders. A comprehensive analysis of human and mouse inflammation data revealed an association between alterations in the miRNA and tsRNA profiles of epididymal spermatozoa and offspring phenotypes.

Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma

Although prognostic prediction of nasopharyngeal carcinoma (NPC) remains a pivotal research area, the role of dynamic contrast-enhanced magnetic resonance (DCE-MR) has been less explored. This study aimed to investigate the role of DCR-MR in predicting progression-free survival (PFS) in patients with NPC using magnetic resonance (MR)- and DCE-MR-based radiomic models. A total of 434 patients with two MR scanning sequences were included. The MR- and DCE-MR-based radiomics models were developed based on 289 patients with only MR scanning sequences and 145 patients with four additional pharmacokinetic parameters (volume fraction of extravascular extracellular space (ve), volume fraction of plasma space (vp), volume transfer constant (Ktrans), and reverse reflux rate constant (kep) of DCE-MR. A combined model integrating MR and DCE-MR was constructed. Utilizing methods such as correlation analysis, least absolute shrinkage and selection operator regression, and multivariate Cox proportional hazards regression, we built the radiomics models. Finally, we calculated the net reclassification index and C-index to evaluate and compare the prognostic performance of the radiomics models. Kaplan-Meier survival curve analysis was performed to investigate the model’s ability to stratify risk in patients with NPC. The integration of MR and DCE-MR radiomic features significantly enhanced prognostic prediction performance compared to MR- and DCE-MR-based models, evidenced by a test set C-index of 0.808 vs 0.729 and 0.731, respectively. The combined radiomics model improved net reclassification by 22.9%–52.6% and could significantly stratify the risk levels of patients with NPC (p = 0.036). Furthermore, the MR-based radiomic feature maps achieved similar results to the DCE-MR pharmacokinetic parameters in terms of reflecting the underlying angiogenesis information in NPC. Compared to conventional MR-based radiomics models, the combined radiomics model integrating MR and DCE-MR showed promising results in delivering more accurate prognostic predictions and provided more clinical benefits in quantifying and monitoring phenotypic changes associated with NPC prognosis.

Deciphering the tumor-suppressive role of PSMB9 in melanoma through multi-omics and single-cell transcriptome analyses

Skin cutaneous melanoma (SKCM) poses a significant challenge in skin cancers. Recent immunotherapy breakthroughs have revolutionized melanoma treamtment, yet tumor heterogeneity persists as an obstacle. Epigenetic modifications orchestrated by DNA methylation contributed to tumorigenesis, thus potentially unveiling melanoma prognosis. Here, we identified an interferon-gamma (IFN-g) sensitive subtype, which possesses favorable outcomes, robust infiltration CD8+T cells, and IFN-g score in bulk RNA-seq profile. Subsequently, we established an IFN-g sensitivity signature based on machine learning.We validated that PSMB9 is strongly correlated with immunotherapy response in both methylation and expression cohorts in this 10-probe signature. We assumed that PSMB9 acts as a putative melanoma suppressor, for its activation of CD8+T cell; capacity to modulate IFN-γ secretion; and dynamics altering IFN-g receptors in bulk tissue. We performed single-cell RNA-seq on immunotherapy patients’ tissue to uncover the nuanced role of PSMB9 in activating CD8T + cells, enhancing IFN-g, and influencing malignant cells receptors and transcriptional factors.Overexpress PSMB9 in two SKCM cell lines to mimic the hypomethylated state to approve our conjecture. Strong cell proliferation and migration inhibition were detected on both cells, indicating that PSMB9 is present in tumor cells and that high expression is detrimental to tumor growth and migration.Overall, comprehensive integrated analysis shows that PSMB9 emerges as a vital prognostic marker, acting predictive potential regarding immunotherapy in melanoma. This evidence not only reveals the multifaceted impact of PSMB9 on both malignant and immune cells but also serves as a prospective target for undergoing immunotherapeutic strategies in the future.

Integrative taxonomy reveals unrecognised species diversity in African Corypha larks (Aves: Alaudidae)

Abstract The species complex comprising the rufous-naped lark Corypha africana, Sharpe’s lark Corypha sharpii, the red-winged lark Corypha hypermetra, the Somali long-billed lark Corypha somalica and Ash’s lark Corypha ashi encompasses 31 recognised taxa across sub-Saharan Africa, many of which are extremely poorly known and some not observed for decades. Only 17 taxa have been studied molecularly and none comprehensively for morphology, vocalisations or other behaviours. Here, we undertake comprehensive integrative taxonomic analyses based on plumage and morphometrics (for 97% of the taxa), mitochondrial and nuclear loci (77%), ≤ 1.3 million genome-wide single nucleotide polymorphisms (68%), song (many described for the first time; 52%) and additional behavioural data (45%). All polytypic species as presently circumscribed are paraphyletic, with eight primary clades separated by ≤ 6.3–6.8 Myr, broadly supported by plumage, morphometrics, song and other behaviours. The most recent divergences concern sympatric taxon pairs usually treated as separate species, whereas the divergence of all clades including C. africana subspecies is as old as sister species pairs in other lark genera. We propose the recognition of nine instead of five species, while C. ashi is synonymised with C. somalica rochei as C. s. ashi. The geographical distributions are incompletely known, and although the nine species are generally para-/allopatric, some might be sympatric.

Novel insights into the progression and prognosis of the calpain family members in hepatocellular carcinoma: a comprehensive integrated analysis.

Objectives: The goal of our bioinformatics study was to comprehensively analyze the association between the whole calpain family members and the progression and prognosis of hepatocellular carcinoma (HCC). Methods: The data were collected from The Cancer Genome Atlas (TCGA). The landscape of the gene expression, copy number variation (CNV), mutation, and DNA methylation of calpain members were analyzed. Clustering analysis was performed to stratify the calpain-related groups. The least absolute shrinkage and selection operator (LASSO)-based Cox model was used to select hub survival genes. Results: We found 14 out of 16 calpain members expressed differently between tumor and normal tissues of HCC. The clustering analyses revealed high- and low-risk calpain groups which had prognostic difference. We found the high-risk calpain group had higher B cell infiltration and higher expression of immune checkpoint genes HAVCR2, PDCD1, and TIGHT. The CMap analysis found that the histone deacetylase (HDAC) inhibitor trichostatin A and the PI3K-AKT-mTOR pathway inhibitors LY-294002 and wortmannin might have a therapeutic effect on the high-risk calpain group. The DEGs between calpain groups were identified. Subsequent univariate Cox analysis of each DEG and LASSO-based Cox model obtained a calpain-related prognostic signature. The risk score model of this signature showed good ability to predict the overall survival of HCC patients in TCGA datasets and external validation datasets from the Gene Expression Omnibus database and the International Cancer Genome Consortium database. Conclusion: We found that calpain family members were associated with the progression, prognosis, and drug response of HCC. Our results require further studies to confirm.

MicrobiomeAnalyst 2.0: comprehensive statistical, functional and integrative analysis of microbiome data.

Microbiome studies have become routine in biomedical, agriculturaland environmental sciences with diverse aims, including diversity profiling, functional characterization, and translational applications. The resulting complex, often multi-omics datasets demand powerful, yet user-friendly bioinformatics tools to reveal key patterns, importantbiomarkers, and potentialactivities. Here we introduce MicrobiomeAnalyst 2.0 to support comprehensive statistics, visualization, functional interpretation, and integrative analysis of data outputs commonly generated from microbiome studies. Compared to the previous version, MicrobiomeAnalyst 2.0 features three new modules: (i) a Raw Data Processing module for amplicon data processing and taxonomy annotation that connects directly with the Marker Data Profiling module for downstream statistical analysis; (ii) a Microbiome Metabolomics Profiling module to help dissect associations between community compositions and metabolic activities through joint analysis of paired microbiome and metabolomics datasets; and (iii) a Statistical Meta-Analysis module to help identify consistent signatures by integrating datasets across multiple studies. Other important improvements include added support for multi-factor differential analysis andinteractive visualizations for popular graphical outputs,updated methods for functional prediction and correlation analysis, and expanded taxon set libraries based on the latest literature. These new features are demonstrated using a multi-omics dataset from a recent type 1 diabetes study. MicrobiomeAnalyst 2.0 is freely available at microbiomeanalyst.ca.

Abstract 6077: Comprehensive multi-omic characterization of genetic changes associated with sinonasal squamous cell carcinoma progression

Abstract Approximately 50-80% of sinonasal tract cancers are sinonasal squamous cell carcinoma (SNSCC), a rare malignancy which occur in the nasal cavity and maxillary sinus. These lesions possess a propensity for local invasion into adjacent structures including the skull base, brain, and orbit. Owing to relatively mild symptoms during early stages, which resemble benign sinonasal disease, most patients are already in clinically advanced stages when diagnosed. Therefore, despite improvements in endoscopic surgical approaches, radiotherapy and imaging techniques, the 5-year overall survival for advanced SNSCC patients remains poor (~40%). Inverted sinonasal papilloma (IP) is a locally aggressive, benign epithelial neoplasm arising in the paranasal sinuses which has a high recurrence rate and transforms to SNSCC in 10%-25% of cases. As some IP evolve to malignant neoplasms, it has been presumed that they represent an intermediate step in SNSCC progression. However, the current tools for detecting altered epithelial cells, such as clinical examination and histological characteristics, have limited prognostic value for predicting which IP will progress to malignancy, and the link between IP and invasive disease remains unclear. Activating mutations in EGFR and PIK3CA genes as well as loss-of-function mutations in TP53 have been reported in a few very small cohorts of IP and SNSCC lesions, suggesting their role in IP pathogenesis and progression to invasive malignancy. Other observed alterations potentially associated with malignant transition include KRAS mutations, loss of heterozygosity (LOH) at the 9p21 locus (containing p16INK4a), mismatch repair genes deficiency, amplification of FGFR1 and SOX2 genes, as well as NFκB, COX2 and HOXA9 overexpression. While these studies provide a snapshot of molecular changes in SNSCC, genetic alterations critical to the development of SNSCC are poorly understood, and the exact mechanism underlying malignant transformation remains unknown. In this study we have used PandaOmic, a multi-omic data analysis and visualization algorithm, to perform a first comprehensive integrative analysis of WES, mitochondrial sequencing and transcriptomic data obtained from 11 IP lesions, matched invasive SNSCC tumors and histologically normal paranasal sinus epithelium collected from the same patients. Our analysis reveals heterogeneous mutational patterns, gene expression changes and signaling pathways features associated with SNSCC pathogenesis, and provides crucial insights that may aid in the development of novel means of prevention, diagnosis, and treatment of this rare, aggressive and poorly characterized malignancy. Citation Format: Alka Singh, Nikita Babushkin, Michael Korzinkin, Viktoria Sarkisova, Vasudha Mishra, Ari Rosenberg, Mark Lingen, Justin Bishop, Alex Zhavoronkov, Nyall London, Nishant Agrawal, Xuanyao Liu, Evgeny Izumchenko. Comprehensive multi-omic characterization of genetic changes associated with sinonasal squamous cell carcinoma progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6077.

Comprehensive analysis of carotenoids constituents in purple-coloured leaves and carotenoid-derived aroma differences after processing into green, black, and white tea

Carotenoids differentiate among tea cultivars and play role in contributing aroma flavor and colour appearance in tea products. In this study, 3 carotenes and 16 xanthophylls were accurately quantified of 0.79–1.56 × 103 μg g−1 in 15 tea cultivars possessing leaves of different colours. Lutein and β-carotene accounted for >80% of total carotenoids. Single carotenoid accumulation patterns and their correlations with chlorophylls and primary metabolites (amino acids, alkaloids, and saccharides) were elucidated. Tea processing (withering, ‘kill-green,’ fermentation, and drying processes) decreased tea carotenoids by >65%, promoting volatile apocarotenoid production. In total, 25 crucial carotenoid-derived aroma compounds were detected in green, white, and black teas prepared from purple shoots. Additionally, α/β-ionone and their derivates, and dihydroactinidiolide accounted for >50% of total volatiles and therefore explained the fruity aroma in purple tea products. A comprehensive integrative analysis of sensory attributes and volatile and carotenoid precursor dynamics clearly revealed patterns of tea carotenoid accumulation and degradation contribution to tea aroma.

Tumor Microenvironment Determinants of Immunotherapy Response Identified By Integrated Host & Viral Analysis of Post-Transplant Lymphoproliferative Disorders

Background: Post-transplant lymphoproliferative disorder (PTLD) is a major cause of morbidity in transplantation; however, some PTLD subtypes are curable using anti-CD20 immunotherapy alone or with reduction of immunosuppression (R-ISR). We hypothesized that a comprehensive integrated analysis of the tumor immune microenvironment (TME), virome, genome, transcriptome, and cell-free DNA (cfDNA) could offer biologically and clinically relevant insights into the immunobiology of PTLD. Methods: We identified 75 patients with PTLD after solid organ (n=69) or hematopoietic stem cell (n=6) transplantation. 32 cases occurred <2 years post-transplant (TTD<2, 43%) and 69% were EBV+ by clinical Epstein-Barr-encoded small RNA (EBER) ISH (Table 1). Tumor and cfDNA hybrid capture was performed as previously described, utilizing panels for 322 B-cell lymphoma genes (Kurtz JCO 2018), 180 viral species (Garofalo Blood 2019), and TCR-loci for repertoire profiling (Shukla Blood 2020). Tumor RNAseq was quantified with Salmon & analyzed by DESeq2, fgsea, CIBERSORTx, and Ecotyper. Results: Tumor microenvironment Compared to EBV-negative DLBCL-PTLD, EBV+ cases showed significantly higher expression of IFN-associated (MX1, IFI44, IFIT3) and antiviral response genes including CD30/TNFRSF8 and APOBEC3A. TME immune cell subset deconvolution revealed no difference in B-cell populations, but EBV+ cases were enriched in CD4+ memory activated T-cells, M1 macrophages, activated DCs, and eosinophils. Considering lymphoma TME ecotypes (Steen Cancer Cell 2021), the immunoreactive LE4 ecotype identified EBV+ non-GCB cases with median TTD 93 days, while the immune-poor LE8 aligned with EBV- GCB with median TTD 3686 days. TCR repertoires revealed DLBCL-PTLD tumors to have lower T-cell diversity as compared to DLBCL-NOS (p=0.007, Chao1 index), driven by dominant T-cell clones in EBV+ cases. Virome enrichment by targeted capture confirmed elevated EBV DNA in EBER+ cases, allowing stratification of clinical EBV status by sequencing. While total viral burden and anellovirus level (a marker of immunosuppression) were higher at TTD<2, CMV and HHV6 were similar for later diagnoses. Mutations & mechanisms Compared to DLBCL-NOS, DLBCL-PTLD had significantly fewer variants in the NFkB pathway genes MYD88 and PIM1 and several immune regulatory genes (TNFRSF14, B2M, and CD58). In contrast, TP53, CARD11, and TNFAIP3 were similar. Notably, 12 tumors had no detected oncogenic single-nucleotide variants: these cases were all TTD<2 & EBV+. Overall, more coding variants were seen in EBV- PTLD and TTD>2 (p<0.001 for both comparisons) (Fig 1). We compared mutational signatures within targeted genes to evaluate mechanisms driving these differences. Compared to EBV+ DLBCL-PTLD, EBV- cases were enriched in SBS84, an AID/SHM signature seen in DLBCL-NOS (p<0.001), and had higher AICDA mRNA expression (padj=0.003). Conversely, EBV+ DLBCL-PTLD was enriched in DNA mismatch repair signatures SBS6/21 (p=0.01); and SBS17 (p<0.001), a cryptic mechanism also reported in EBV+ Burkitt lymphomas (Grande Blood 2019). mRNA from EBV+ cases showed corresponding downregulation in the DNA MMR pathway (padj=0.004). Likewise, MSI quantification with mSINGS (Hause Nat Med 2016) showed more altered loci in EBV+ tumors (p=0.013), together suggesting EBV-induced inhibition of MMR as a mutational mechanism. Clinical response We compared DLBCL-PTLD patients with complete response to R-ISR to those requiring chemotherapy. Patients with response had shorter TTD but no difference in coding mutation burden. However, the TME of patients requiring chemotherapy contained more M0/non-activated macrophages and regulatory T-cells; similarly, all patients with the immune-depleted TME ecotype LE8 received chemotherapy. While no difference was seen in NFkB pathway genes, patients requiring chemotherapy showed higher expression of MYC & E2F targets. Conclusions: Through multimodal characterization of the TME and virome in the largest sequencing cohort to date, we identify distinct immunogenomic features reflecting divergent PTLD biology. These include evidence of MMR defects in EBV+ PTLD and TME depletion & MYC pathway enrichment in patients failed by R-ISR, suggesting potential markers of clinical risk. Additional analyses including non-DLBCL cases, viral, and cfDNA data are in progress to further clarify these pathogenetic mechanisms. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Identifying Biomarkers of Cisplatin Sensitivity in Non-Small Cell Lung Cancer via Comprehensive Integrative Analysis

Background: Only 30-40% of non-small cell lung cancer (NSCLC) patients are clinically sensitive to cisplatin-based chemotherapy. Thus, it is necessary to identify biomarkers for personalized cisplatin chemotherapy in NSCLC. However, data heterogeneity and low-value density make it challenging to detect reliable cisplatin efficacy biomarkers using traditional analysis methods. Objective: This paper aims to find reliable cisplatin efficacy biomarkers for NSCLC patients using comprehensive integrative analysis. Method: We searched online resources and collected six NSCLC transcriptomics data sets with responses to cisplatin. The six data sets are divided into two groups: the learning group for biomarker identification and the test group for independent validation. We performed comprehensive integrative analysis under two kinds of frameworks, i.e., one-level and two-level, with three integrative models. Pathway analysis was performed to estimate the biological significance of the resulting biomarkers. For independent validation, logrank statistic was employed to test how significant the difference of Kaplan- Meier (KM) curves between two patient groups is, and the Cox proportional-hazards model was used to test how the expression of a gene is associated with patients’ survival time. Especially, a permutation test was performed to verify the predictive power of a biomarker panel on cisplatin efficacy. For comparison, we also analyzed each learning data set individually, in which three popular differential expression models, Limma, SAM, and RankSum, were used. Results: A total of 318 genes were identified as a core panel of cisplatin efficacy markers for NSCLC patients, exhibiting consistent differential expression between cisplatin-sensitive and –resistant groups across studies. A total of 129 of 344 KEGG pathways were found to be enriched in the core panel, reflecting a picture of the molecular mechanism of cisplatin resistance in NSCLC. By mapping onto the KEGG pathway tree, we found that a KEGG pathway-level I module, genetic information processing, is most active in the core panel with the highest activity ratio in response to cisplatin in NSCLC as expected. Related pathways include mismatch repair, nucleotide excision repair, aminoacyl-tRNA biosynthesis, and basal transcription factors, most of which respond to DNA double-strand damage in patients. Evaluation on two independent data sets demonstrated the predictive power of the core marker panel for cisplatin sensitivity in NSCLC. Also, some single markers, e.g., MST1R, were observed to be remarkably predictive of cisplatin resistance in NSCLC. Conclusion: Integrative analysis is more powerful in detecting biomarkers for cisplatin efficacy by overcoming data heterogeneity and low-value density in data sets, and the identified core panel (318 genes) can help develop personalized medicine of cisplatin chemotherapy for NSCLC patients.

3D chromatin remodelling in the germ line modulates genome evolutionary plasticity

Chromosome folding has profound impacts on gene regulation, whose evolutionary consequences are far from being understood. Here we explore the relationship between 3D chromatin remodelling in mouse germ cells and evolutionary changes in genome structure. Using a comprehensive integrative computational analysis, we (i) reconstruct seven ancestral rodent genomes analysing whole-genome sequences of 14 species representatives of the major phylogroups, (ii) detect lineage-specific chromosome rearrangements and (iii) identify the dynamics of the structural and epigenetic properties of evolutionary breakpoint regions (EBRs) throughout mouse spermatogenesis. Our results show that EBRs are devoid of programmed meiotic DNA double-strand breaks (DSBs) and meiotic cohesins in primary spermatocytes, but are associated in post-meiotic cells with sites of DNA damage and functional long-range interaction regions that recapitulate ancestral chromosomal configurations. Overall, we propose a model that integrates evolutionary genome reshuffling with DNA damage response mechanisms and the dynamic spatial genome organisation of germ cells.

Integrated small RNA profiling and degradome analysis of Anthurium andraeanum cultivars with different-colored spathes

MicroRNAs (miRNAs) are known to play vital roles in coloration of leaves, flowers, and fruits in plants. However, their functions in spathe coloration are poorly known. Anthurium andraeanum is a popular ornamental plant with various spathe colors. In this study, small RNA and degradome libraries from three A. andraeanum cultivars with different-colored spathes were constructed and sequenced. Illumina sequencing resulted in 94 conserved miRNAs, and 34 novel miRNAs in total were then identified based on precursor sequences and hairpin structures. Differential expression analysis showed that 52, 51, and 49 miRNAs were differentially expressed in comparisons of orange- versus white-colored spathe, purple- versus white-colored spathe, and purple- versus orange-colored spathe, respectively. The expression patterns of miRNAs and their corresponding targets involved in spathe coloration were further analyzed, and displayed that miR156b and miR529 were highly abundant in the spathes with higher anthocyanin content. These two miRNAs co-targeted a gene encoding SPL17, which may function as a negative regulator in anthocyanin accumulation. In addition, miR408 was also abundantly expressed in purple- and orange-colored spathes, and its typical targets were also identified. This comprehensive integrated analysis provides insight into the miRNA-mediated genetic regulation in spathe coloration of A. andraeanum.