PESSA: A web tool for pathway enrichment score-based survival analysis in cancer.

The activation levels of biologically significant gene sets are emerging tumor molecular markers and play an irreplaceable role in the tumor research field; however, web-based tools for prognostic analyses using it as a tumor molecular marker remain scarce. We developed a web-based tool PESSA for survival analysis using gene set activation levels. All data analyses were implemented via R. Activation levels of The Molecular Signatures Database (MSigDB) gene sets were assessed using the single sample gene set enrichment analysis (ssGSEA) method based on data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The European Genome-phenome Archive (EGA) and supplementary tables of articles. PESSA was used to perform median and optimal cut-off dichotomous grouping of ssGSEA scores for each dataset, relying on the survival and survminer packages for survival analysis and visualisation. PESSA is an open-access web tool for visualizing the results of tumor prognostic analyses using gene set activation levels. A total of 238 datasets from the GEO, TCGA, EGA, and supplementary tables of articles; covering 51 cancer types and 13 survival outcome types; and 13,434 tumor-related gene sets are obtained from MSigDB for pre-grouping. Users can obtain the results, including Kaplan-Meier analyses based on the median and optimal cut-off values and accompanying visualization plots and the Cox regression analyses of dichotomous and continuous variables, by selecting the gene set markers of interest. PESSA (https://smuonco.shinyapps.io/PESSA/ OR http://robinl-lab.com/PESSA) is a large-scale web-based tumor survival analysis tool covering a large amount of data that creatively uses predefined gene set activation levels as molecular markers of tumors.

CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity.

Drug therapy is vital in cancer treatment. Accurate analysis of drug sensitivity for specific cancers can guide healthcare professionals in prescribing drugs, leading to improved patient survival and quality of life. However, there is a lack of web-based tools that offer comprehensive visualization and analysis of pancancer drug sensitivity. We gathered cancer drug sensitivity data from publicly available databases (GEO, TCGA and GDSC) and developed a web tool called Comprehensive Pancancer Analysis of Drug Sensitivity (CPADS) using Shiny. CPADS currently includes transcriptomic data from over 29 000 samples, encompassing 44 types of cancer, 288 drugs and more than 9000 gene perturbations. It allows easy execution of various analyses related to cancer drug sensitivity. With its large sample size and diverse drug range, CPADS offers a range of analysis methods, such as differential gene expression, gene correlation, pathway analysis, drug analysis and gene perturbation analysis. Additionally, it provides several visualization approaches. CPADS significantly aids physicians and researchers in exploring primary and secondary drug resistance at both gene and pathway levels. The integration of drug resistance and gene perturbation data also presents novel perspectives for identifying pivotal genes influencing drug resistance. Access CPADS at https://smuonco.shinyapps.io/CPADS/ or https://robinl-lab.com/CPADS.

Proteomics appending a complementary dimension to precision oncotherapy.

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application.

Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.

Development and validation of a radiosensitivity model to evaluate radiotherapy benefits in pan-cancer.

Radiotherapy, one of the most fundamental cancer treatments, is confronted with the dilemma of treatment failure due to radioresistance. To predict the radiosensitivity and improve tumor treatment efficiency in pan-cancer, we developed a model called Radiation Intrinsic Sensitivity Evaluation (RISE). The RISE model was built using cell line-based mRNA sequencing data from five tumor types with varying radiation sensitivity. Through four cell-derived datasets, two public tissue-derived cohorts, and one local cohort of 42 nasopharyngeal carcinoma patients, we demonstrated that RISE could effectively predict the level of radiation sensitivity (area under the ROC curve [AUC] from 0.666 to 1 across different datasets). After the verification by the colony formation assay and flow cytometric analysis of apoptosis, our four well-established radioresistant cell models successfully proved higher RISE values in radioresistant cells by RT-qPCR experiments. We also explored the prognostic value of RISE in five independent TCGA cohorts consisting of 1137 patients who received radiation therapy and found that RISE was an independent adverse prognostic factor (pooled multivariate Cox regression hazard ratio [HR]: 1.84, 95% CI 1.39-2.42; p < 0.01). RISE showed a promising ability to evaluate the radiotherapy benefit while predicting the prognosis of cancer patients, enabling clinicians to make individualized radiotherapy strategies in the future and improve the success rate of radiotherapy.

N6-methyladenosine-modified circSLCO1B3 promotes intrahepatic cholangiocarcinoma progression via regulating HOXC8 and PD-L1.

BACKGROUND: Refractoriness to surgical resection and chemotherapy makes intrahepatic cholangiocarcinoma (ICC) a fatal cancer of the digestive system with high mortality and poor prognosis. Important function invests circRNAs with tremendous potential in biomarkers and therapeutic targets. Nevertheless, it is still unknown how circRNAs contribute to the evolution of ICC. METHODS: CircRNAs in paired ICC and adjacent tissues were screened by circRNAs sequencing. To explore the impact of circRNAs on ICC development, experiments involving gain and loss of function were conducted. Various experimental techniques, including quantitative real-time PCR (qPCR), western blotting, RNA immunoprecipitation (RIP), luciferase reporter assays, RNA pull-down, chromatin immunoprecipitation (ChIP), ubiquitination assays and so on were employed to identify the molecular regulatory role of circRNAs. RESULTS: Herein, we reported a new circRNA, which originates from exon 9 to exon 15 of the SLCO1B3 gene (named circSLCO1B3), orchestrated ICC progression by promoting tumor proliferation, metastasis and immune evasion. We found that the circSLCO1B3 gene was highly overexpressed in ICC tissues and related to lymphatic metastasis, tumor sizes, and tumor differentiation. Mechanically, circSLCO1B3 not only promoted ICC proliferation and metastasis via miR-502-5p/HOXC8/SMAD3 axis, but also eradicated anti-tumor immunity via suppressing ubiquitin-proteasome-dependent degradation of PD-L1 by E3 ubiquitin ligase SPOP. We further found that methyltransferase like 3 (METTL3) mediated the m6A methylation of circSLCO1B3 and stabilizes its expression. Our findings indicate that circSLCO1B3 is a potential prognostic marker and therapeutic target in ICC patients. CONCLUSIONS: Taken together, m6A-modified circSLCO1B3 was correlated with poor prognosis in ICC and promoted ICC progression not only by enhancing proliferation and metastasis via potentiating HOXC8 expression, but also by inducing immune evasion via antagonizing PD-L1 degradation. These results suggest that circSLCO1B3 is a potential prognostic marker and therapeutic target for ICC.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma.

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity.

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Potential anti-tumor effects of regulatory T cells in the tumor microenvironment: a review.

Regulatory T cells (Tregs) expressing the transcription factor FoxP3 are essential for maintaining immunological balance and are a significant component of the immunosuppressive tumor microenvironment (TME). Single-cell RNA sequencing (ScRNA-seq) technology has shown that Tregs exhibit significant plasticity and functional diversity in various tumors within the TME. This results in Tregs playing a dual role in the TME, which is not always centered around supporting tumor progression as typically believed. Abundant data confirms the anti-tumor activities of Tregs and their correlation with enhanced patient prognosis in specific types of malignancies. In this review, we summarize the potential anti-tumor actions of Tregs, including suppressing tumor-promoting inflammatory responses and boosting anti-tumor immunity. In addition, this study outlines the spatial and temporal variations in Tregs function to emphasize that their predictive significance in malignancies may change. It is essential to comprehend the functional diversity and potential anti-tumor effects of Tregs to improve tumor therapy strategies.

Crosstalk of cell death pathways unveils an autophagy-related gene AOC3 as a critical prognostic marker in colorectal cancer.

The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Specifically, we identified a subtype (CDN4) endowed with high autophagy activity and the worst prognosis. Furthermore, AOC3 was identified as a potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and significant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC.

Role of body mass index and weight change in the risk of cancer: A systematic review and meta-analysis of 66 cohort studies.

Background: This study was designed to evaluate the effects of body mass index (BMI) and weight change on the risk of developing cancer overall and cancer at different sites. Methods: We searched PubMed and other databases up to July 2023 using the keywords related to 'risk', 'cancer', 'weight', 'overweight', and 'obesity'. We identified eligible studies, and the inclusion criteria encompassed cohort studies in English that focused on cancer diagnosis and included BMI or weight change as an exposure factor. Multiple authors performed data extraction and quality assessment, and statistical analyses were carried out using RevMan and R software. We used random- or fixed-effects models to calculate the pooled relative risk (RR) or hazard ratio along with 95% confidence intervals (CIs). We used the Newcastle-Ottawa Scale to assess study quality. Results: Analysis included 66 cohort studies. Compared to underweight or normal weight, overweight or obesity was associated with an increased risk of endometrial cancer, kidney cancer, and liver cancer but a decreased risk of prostate cancer and lung cancer. Being underweight was associated with an increased risk of gastric cancer and lung cancer but not that of postmenopausal breast cancer or female reproductive cancer. In addition, weight loss of more than five kg was protective against overall cancer risk. Conclusions: Overweight and obesity increase the risk of most cancers, and weight loss of >5 kg reduces overall cancer risk. These findings provide insights for cancer prevention and help to elucidate the mechanisms underlying cancer development. Registration: Reviewregistry1786.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma.

BACKGROUND: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). METHODS: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). RESULTS: This study identified TIME-related lncRNAs from integrated analysis of single­cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. CONCLUSIONS: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Omics-based molecular classifications empowering in precision oncology.

BACKGROUND: In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine. CONCLUSION: This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

MPDZ is associated with immune infiltration and regulates migration and invasion by switching YAP1 phosphorylation in colorectal cancer.

BACKGROUND: Multiple PDZ Domain Crumbs Cell Polarity Complex Component (MPDZ) is involved in a few human cancers. However, the features and potential mechanisms of MPDZ in progression of colorectal cancer (CRC) remains unknown. METHODS: The prognostic role of MPDZ in CRC was determined by Kaplan-Meier and univariate regression analysis. Enrichment analysis was performed to characterize crucial pathways of MPDZ. Immune infiltration and immunotherapeutic outcome were further evaluated. CCK8, EDU, transwell, and wound healing assay were used to assess the influence of MPDZ on pernicious performance of CRC cells. CD8+ T cells and CRC cells were co-cultured to explore the effect of MPDZ on the tumor microenvironment. qRT-PCR, western blot, immunoprecipitation (IP), and methylated RNA immunoprecipitation (me-RIP) were implemented in seeking for the potential mechanisms of MPDZ in CRC. RESULTS: CRC patients with elevated MPDZ expression suffered from significantly worse prognosis. Enrichment analysis revealed that MPDZ involved in pathways related to metastasis and cell cycle in CRC. In addition, MPDZ expression were related to several immunoinhibitors and had the ability to predict immunotherapy response. Finally, in vitro assays demonstrated that MPDZ knockdown inhibited migration, invasion and immune evasion of CRC cells. Mechanistically, MPDZ knockdown enhanced YAP1 phosphorylation by increased LATS1 expression. Moreover, m6A-MPDZ mRNA may be recognized and degraded by m6A recognition protein YTHDF2. CONCLUSIONS: MPDZ was critical for CRC development and could be a promising candidate for the treatment of CRC patients.

A TGF-ß signaling-related lncRNA signature for prediction of glioma prognosis, immune microenvironment, and immunotherapy response.

AIMS: The dysregulation of TGF-ß signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF-ß signaling in glioma is currently unclear. METHODS: Data on glioma's RNA-seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. "ELMER v.2" was used to reconstruct TF-methylation-gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA. RESULTS: In glioma, a TGF-ß signaling-related 15-lncRNA signature was constructed, including AC010173.1, HOXA-AS2, AC074286.1, AL592424.1, DRAIC, HOXC13-AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC-AS1, AGAP2-AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP-1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2-AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF-κB and ERK 1/2 in the TGF-ß signaling pathway. CONCLUSIONS: A prognostic lncRNA signature of TGF-ß signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2-AS1 plays an important role in glioma progression.

Oxidative stress is involved in immunosuppression and macrophage regulation in glioblastoma.

Oxidative stress dually affected cancer progression, while its effect on glioblastomas remained unclear. Herein, we clustered the multicenter glioblastoma cohorts based on the oxidative-stress-responsive genes (OSS) expression. We found that cluster 2 with high OSS levels suffered a worse prognosis. Functional analyses and immune-related analyses results exhibited that M2-like pro-tumoral macrophages and neutrophils were enriched in cluster 2, while Natural killer cells' infiltration was decreased. The increased M2-like pro-tumoral macrophages in cluster 2 was confirmed by immunofluorescence. An integrated single-cell analysis validated the malignant features of cluster 2 neoplastic cells and discovered their crosstalk with M2-like pro-tumoral macrophages. Moreover, we observed that SOD3 knockdown might decrease the M2-like pro-tumoral transformation of macrophage in vitro and in vivo. Comprehensively, we revealed oxidative stress' prognostic and immunosuppressive potential in glioblastoma and discovered SOD3's potential role in regulating macrophage M2-like pro-tumoral transformation.

Correlation between second and first primary cancer: systematic review and meta-analysis of 9 million cancer patients.

BACKGROUND: Many survivors of a first primary cancer (FPCs) are at risk of developing a second primary cancer (SPC), with effects on patient prognosis. Primary cancers have different frequencies of specific SPC development and the development of SPCs may be closely related to the FPC. The aim of this study was to explore possible correlations between SPCs and FPCs. METHODS: Relevant literature on SPCs was retrospectively searched and screened from four databases, namely, PubMed, EMBASE, Web of Science, and PMC. Data on the number of patients with SPC in 28 different organ sites were also collected from The Surveillance, Epidemiology, and End Results (SEER) 8 Registry and NHANES database. RESULTS: A total of 9 617 643 patients with an FPC and 677 430 patients with an SPC were included in the meta-analysis. Patients with a first primary gynaecological cancer and thyroid cancer frequently developed a second primary breast cancer and colorectal cancer. Moreover, those with a first primary head and neck cancer, anal cancer and oesophageal cancer developed a second primary lung cancer more frequently. A second primary lung cancer and prostate cancer was also common among patients with first primary bladder cancer and penile cancer. Patients with second primary bladder cancer accounted for 56% of first primary ureteral cancer patients with SPCs. CONCLUSIONS: This study recommends close clinical follow-up, monitoring and appropriate interventions in patients with relevant FPCs for better screening and early diagnosis of SPCs.

The regulatory role and clinical application prospects of circRNA in the occurrence and development of CNS tumors.

BACKGROUND: Central nervous system (CNS) tumors originate from the spinal cord or brain. The study showed that even with aggressive treatment, malignant CNS tumors have high mortality rates. However, CNS tumor risk factors and molecular mechanisms have not been verified. Due to the reasons mentioned above, diagnosis and treatment of CNS tumors in clinical practice are currently fraught with difficulties. Circular RNAs (circRNAs), single-stranded ncRNAs with covalently closed continuous structures, are essential to CNS tumor development. Growing evidence has proved the numeral critical biological functions of circRNAs for disease progression: sponging to miRNAs, regulating gene transcription and splicing, interacting with proteins, encoding proteins/peptides, and expressing in exosomes. AIMS: This review aims to summarize current progress regarding the molecular mechanism of circRNA in CNS tumors and to explore the possibilities of clinical application based on circRNA in CNS tumors. METHODS: We have summarized studies of circRNA in CNS tumors in Pubmed. RESULTS: This review summarized their connection with CNS tumors and their functions, biogenesis, and biological properties. Furthermore, we introduced current advances in clinical RNA-related technologies. Then we discussed the diagnostic and therapeutic potential (especially for immunotherapy, chemotherapy, and radiotherapy) of circRNA in CNS tumors in the context of the recent advanced research and application of RNA in clinics. CONCLUSIONS: CircRNA are increasingly proven to participate in decveloping CNS tumors. An in-depth study of the causal mechanisms of circRNAs in CNS tomor progression will ultimately advance their implementation in the clinic and developing new strategies for preventing and treating CNS tumors.