Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression

Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory – reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression.

The role of the microbiome and transcriptome in the development and progression of CIN

The article presents a systematic review of the results of modern clinical studies devoted to the problem of the microbiome and transcriptome in women with cervical intraepithelial neoplasia (CIN). Moderate to severe CIN (CIN II – III) can precede the development of cervical cancer (CC) by several years or even decades. Cervical cancer (CC) is an important global health problem. There is a year-on-year increase in the prevalence of CC. Currently, there are many known risk factors that contribute to the development of CIN and cervical cancer. However, the vaginal and cervical microbiome play an important role in the development and progression of CIN and CC, according to some authors. Thus, the timely detection and treatment of cervical intraepithelial lesion-associated genital infections is now especially important. From these point of view, bacterial vaginosis (BV) is considered an acute problem in gynecological practice, which affects the incidence of precancerous conditions of the cervix. The results of the studies have shown the importance of detailed analysis of the vaginal microbial community, which was performed by the method of next generation sequencing (NGS). These studies were conducted using the NGS method based on the analysis of bacterial 16S rRNA genes, which has a high diagnostic accuracy and allows to determine the verity of the microbial landscape. The study of the transcriptome in women with CIN showed a change in many microRNA molecules, which can become markers of the CIN and cervical cancer upon further study. The introduction of the NGS method into the laboratory diagnostics complex will improve the diagnosis and timely prevent the progression of CIN to cervical cancer.The study of the microbiome of the vaginal biotope and cervical canal will allow to identify the groups of patients at high risk for the progression of precancerous lesions of the cervix and cervical cancer. Transcriptome studies have shown changes in many microRNA molecules (SALL4, FOXO1, HBD-1, HBD-2, HBD-3, LL37, psoriasin and IL-8, etc.) in women with CIN and cervical cancer.

Spatial heterogeneity of the immune compartment within the lungs of critical COVID-19 patients

Cross AR, Sansom S, Roberts I, Cerundolo L, Melero I, De Andrea C, Landecho MF, Klenerman P,Hester J, Issa F Acute respiratory distress syndrome (ARDS) is a defining feature of severe infection with theSARS-CoV-2 virus. Approaches to understand the immune response during COVID-19 are largelyconfined to characterisation of circulating leukocytes, however this approach excludes the mostrelevant cells that are active at the site of infection and injury. The aim of this study was to characterise the immune landscape across the lungs of COVID-19patients. Lung samples from three critical COVID-19 patients were assessed for histopathology,viral load, and distribution using qPCR, in situ hybridisation and immunohistochemistry.Leukocyte distribution was then assessed, and the transcript profile of selected areas examinedagainst the >1800 genes in the Cancer Transcriptome Atlas panel on the NanoString GeoMxDigital Spatial Profiling platform. Lung samples exhibited a spectrum of typical COVID-19 pathology with diffuse alveolar damageconsistent with hyaline membrane and type II pneumocyte hyperplasia, interstitialinflammation, organising pneumonia and thrombi. All tissues tested positive for SARS-CoV-2RNA using qPCR, whilst spatially resolved techniques revealed only few and sparsely distributedcells carrying the viral nucleocapsid protein. Multiplexed immunofluorescence for lymphocytes(CD3+) and macrophages (CD68+) was used to select areas of immune enrichment for spatialtranscriptomic profiling. These targeted analyses highlighted functional pathways involved inthe interferon gamma response, TCR activation and antigen presentation. Comparison acrossimmune-enriched areas identified a heterogeneity in lung infiltrates with spatial separation ofchemokine and complement production. Our data identify pathological immune pathways thatare amenable to therapeutic intervention in critical disease.

LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

Background Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. Results As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. Conclusions LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA.

High SPINK4 Expression Predicts Poor Outcomes among Rectal Cancer Patients Receiving CCRT

Background: Patients with rectal cancer can prospectively be favored for neoadjuvant concurrent chemoradiotherapy (CCRT) to downstage before a radical proctectomy, but the risk stratification and clinical outcomes remain disappointing. Methods: From a published rectal cancer transcriptome dataset (GSE35452), we highlighted extracellular matrix (ECM)-linked genes and identified the serine protease inhibitor Kazal-type 4 (SPINK4) gene as the most relevant among the top 10 differentially expressed genes associated with CCRT resistance. We accumulated the cases of 172 rectal cancer patients who received neoadjuvant CCRT followed by surgery and collected tumor specimens for the evaluation of the expression of SPINK4 using immunohistochemistry. Results: The results revealed that high SPINK4 immunoexpression was significantly related to advanced pre-CCRT and post-CCRT tumor status (both p < 0.001), post-CCRT lymph node metastasis (p = 0.001), more vascular and perineurial invasion (p = 0.015 and p = 0.023), and a lower degree of tumor regression (p = 0.001). In univariate analyses, high SPINK4 immunoexpression was remarkably correlated with worse disease-specific survival (DSS) (p < 0.0001), local recurrence-free survival (LRFS) (p = 0.0017), and metastasis-free survival (MeFS) (p < 0.0001). Furthermore, in multivariate analyses, high SPINK4 immunoexpression remained independently prognostic of inferior DSS and MeFS (p = 0.004 and p = 0.002). Conclusion: These results imply that high SPINK4 expression is associated with advanced clinicopathological features and a poor therapeutic response among rectal cancer patients undergoing CCRT, thus validating the prospective prognostic value of SPINK4 for those patients.

lncRNA GAU1 Induces GALNT8 Overexpression and Potentiates Colorectal Cancer Progression

lncRNA is a key epigenetic regulator in biological processes. In the human cancer transcriptome library MiTranscriptome, we identified GAU1 as the top upregulated lncRNA in colorectal cancer (CRC) by sample set enrichment analysis (overexpression ranking percentile = 99.75 %, P < 10 − 50 ), which is coexpressed with the potential oncogene GALNT8 (Spearman rho = 0.67 , P = 2.44 × 10 − 23 , TCGA dataset n = 184 ). Experimental data revealed that GAU1 regulates the expression of GALNT8. The overexpression of either GAU1 or GALNT8 significantly promotes the cell cycle and proliferation of CRC cell lines and correlates with poor prognosis in patients with CRC ( P = 3.04 × 10 − 2 ), while silencing of GAU1 or GALNT8 suppressed the cancer cell proliferation and induced the CRC cell line resistance to oxaliplatin in vitro treatment. Our results suggested that the previously less studied GAU1 and GALNT8 may play as CRC prognosis markers and potential targets for chemotherapy treatment.

A novel Signature Constructed using Ferroptosis-Related lncRNA Pairs May Predict the Prognosis of Bladder Cancer Patients

Background:Bladder cancer is one of the most common malignant tumors of the urinary system, and its incidence has been increasing in recent years. Ferroptosis is a recently discovered type of cell death, and some studies have suggested that it is closely associated with tumors. It can promote tumor apoptosis and also promote tumor development. Moreover, it has been reported that a correlation exists between long non-coding RNAs (lncRNAs) pairs and tumors. Herein, we developed an lncRNA pair signature associated with ferroptosis to predict the prognosis of bladder cancer. Methods: We combined the bladder cancer transcriptome data from the Cancer Genome Atlas (TCGA) database to identify ferroptosis-related lncRNA (FRlncRNA) pairs. Using univariate and multivariate Cox analyses and LASSO regression analysis, we identified a FRlncRNA pair signature. We subsequently assessed the predictive prognostic value of this signature and validated the results. Results: The signature included 18 lncRNA pairs and was highly accurate for clinical prediction in patients with bladder cancer. Univariate and multivariate Cox analyses and stratified analysis indicated that the model was an independent prognostic factor. Additionally, we detected a positive correlation between this signature and the tumor immune microenvironment. Conclusion: The FRlncRNA pair signature has good prognostic and clinical predictive value in patients with bladder cancer.

Analysis of Gastric Cancer Transcriptome Allows the Identification of Histotype Specific Molecular Signatures With Prognostic Potential

Gastric cancer is the fifth most common malignancy but the third leading cause of cancer-associated mortality worldwide. Therapy for gastric cancer remain largely suboptimal making the identification of novel therapeutic targets an urgent medical need. In the present study we have carried out a high-throughput sequencing of transcriptome expression in patients with gastric cancers. Twenty-four patients, among a series of 53, who underwent an attempt of curative surgery for gastric cancers in a single center, were enrolled. Patients were sub-grouped according to their histopathology into diffuse and intestinal types, and the transcriptome of the two subgroups assessed by RNAseq analysis and compared to the normal gastric mucosa. The results of this investigation demonstrated that the two histopathology phenotypes express two different patterns of gene expression. A total of 2,064 transcripts were differentially expressed between neoplastic and non-neoplastic tissues: 772 were specific for the intestinal type and 407 for the diffuse type. Only 885 transcripts were simultaneously differentially expressed by both tumors. The per pathway analysis demonstrated an enrichment of extracellular matrix and immune dysfunction in the intestinal type including CXCR2, CXCR1, FPR2, CARD14, EFNA2, AQ9, TRIP13, KLK11 and GHRL. At the univariate analysis reduced levels AQP9 was found to be a negative predictor of 4 years survival. In the diffuse type low levels CXCR2 and high levels of CARD14 mRNA were negative predictors of 4 years survival. In summary, we have identified a group of genes differentially regulated in the intestinal and diffuse histotypes of gastric cancers with AQP9, CARD14 and CXCR2 impacting on patients’ prognosis, although CXCR2 is the only factor independently impacting overall survival.

A Machine Learning Analysis of TCGA Expression Data to Finding Signatures for “Normal-Like” IDH-WT Diffuse Gliomas with a Longer Survival

Classification of primary CNS tumours is currently achieved by complementing histologic analysis with molecular information, in accordance with the WHO guidelines, and aims at providing accurate prognosis and optimal patient management. cIMPACT-NOW update 3 now recommends grading diffuse IDH-wild type astrocytomas as grade IV glioblastomas if they bear one or more of the following molecular alterations: EGFR amplification, TERT promoter mutation, and whole-chromosome 7 gain combined with chromosome 10 loss. In this reanalysis of the Cancer Genome Atlas (TCGA) glioma expression datasets, we identified 14 IDH-wt infiltrating astrocytic gliomas displaying a “normal-like (NL)” transcriptomic profile associated with a longer survival rate. Some of these tumours would be considered as GBM-equivalents with the current diagnostic algorithm. A k-nearest neighbors model was used to identify 3-gene signatures able to identify NL IDH-WT gliomas. Genes such as C5AR1 (complement receptor) SLC32A1 (vesicular gamma-aminobutyric acid transporter), and SMIM10L2A (long non-coding RNA) were overrepresented in these signatures which were validated further using the Chinese Glioma Genome and Ivy Glioblastoma Atlases. They showed high discriminative power and correlation with survival. This finding could lead to the validation of an immunohistochemical or PCR test which would facilitate classification of IDH-WT astrocytomas with unclear histological grading. Furthermore, associated signaling pathways might represent novel treatment targets for aggressive tumours.LEARNING OBJECTIVESThis presentation will enable the learner to: 1.Reconsider recent updates in the WHO classification of infiltrating gliomas.2.Discuss advanced bioinformatics profiling of the brain cancer transcriptome.