The Cancer Omics Atlas: an integrative resource for cancer omics annotations

MicroRNA Expression Profiling-Potential Molecular Discrimination of Papillary Thyroid Carcinoma Subtypes

Recent research has revealed the importance of miRNAs in the diagnosis and clinical evolution of papillary thyroid cancer (PTC). We aim to identify a specific miRNA profile that could differentiate between specific subtypes of PTC.

METHODS

In this cross-sectional study, total RNA was extracted from paraffin-embedded tissues of 43 patients, 17 with an infiltrative follicular variant of PTC (iFVPTC) and 26 with a conventional variant of PTC (cPTC). Nine miRNAs were evaluated using qRT-PCR technology and specific miRNA assays.

RESULTS

We found specific patterns for cPTC and iFVPTC, such as miRNA altered in both types of tumours (miR-146b-5p, miR-181a-5p, miR-221-3p, miR-21-5p and miR-222-3p) and two miRNAs significantly expressed only in cPTC (miR-20b-5p, miR-21-5p). The iFVPTC group presented strong and moderate correlations between miRNA expression and clinical data. miR-221-3p, miR-195-5p, miR-181-5p, miR-146b-5p and miR-222 were correlated with age, tumour size (TS) or lymph node metastases (N), while only miR-20b-5p, miR-195-5p and miR-181-5p were correlated with TS, N and age in the cPTC group.

CONCLUSIONS

The present study allowed the identification of a signature of two miRNAs to confirm miRNA differences between the two histological subtypes of TC. Our results provide advances in the molecular diagnosis of TC and could help to improve the diagnostic performance of already existing molecular classifiers.

The genes significantly associated with an improved prognosis and long-term survival of glioblastoma

BACKGROUND AND PURPOSE

Glioblastoma multiforme (GBM) is the most devastating brain tumor with less than 5% of patients surviving 5 years following diagnosis. Many studies have focused on the genetics of GBM with the aim of improving the prognosis of GBM patients. We investigated specific genes whose expressions are significantly related to both the length of the overall survival and the progression-free survival in patients with GBM.

METHODS

We obtained data for 12,042 gene mRNA expressions in 525 GBM tissues from the Cancer Genome Atlas (TCGA) database. Among those genes, we identified independent genes significantly associated with the prognosis of GBM. Receiver operating characteristic (ROC) curve analysis was performed to determine the genes significant for predicting the long-term survival of patients with GBM. Bioinformatics analysis was also performed for the significant genes.

RESULTS

We identified 33 independent genes whose expressions were significantly associated with the prognosis of 525 patients with GBM. Among them, the expressions of five genes were independently associated with an improved prognosis of GBM, and the expressions of 28 genes were independently related to a poorer prognosis of GBM. The expressions of the ADAM22, ATP5C1, RAC3, SHANK1, AEBP1, C1RL, CHL1, CHST2, EFEMP2, and PGCP genes were either positively or negatively related to the long-term survival of GBM patients.

CONCLUSIONS

Using a large-scale and open database, we found genes significantly associated with both the prognosis and long-term survival of patients with GBM. We believe that our findings may contribute to improving the understanding of the mechanisms underlying GBM.

Identifying tumor immunity-associated molecular features in liver hepatocellular carcinoma by multi-omics analysis

Background: Although current immunotherapies have achieved some successes for hepatocellular carcinoma (HCC) patients, their benefits are limited for most HCC patients. Therefore, the identification of biomarkers for promoting immunotherapeutic responses in HCC is urgently needed.

Methods: Using the TCGA HCC cohort, we investigated correlations of various molecular features with antitumor immune signatures (CD8⁺ T cell infiltration and cytolytic activity) and an immunosuppressive signature (PD-L1 expression) in HCC. These molecular features included mRNAs, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), proteins, and pathways.

Results: We found that the mutations of several oncogenes and tumor suppressor genes significantly correlated with reduced antitumor immune signatures, including TTN, CTNNB1, RB1, ZFHX4, and TP53. It indicates that these genes’ mutations may inhibit antitumor immune responses in HCC. Four proteins (Syk, Lck, STAT5, and Caspase-7) had significant positive expression correlations with CD8⁺ T cell enrichment, cytolytic activity, and PD-L1 expression in HCC. It suggests that these proteins’ expression could be useful biomarkers for the response to immune checkpoint inhibitors Similiarly, we identified other types of biomarkers potentially useful for predicting the response to ICIs, including miRNAs (hsa-miR-511-5p, 150-3p, 342-3p, 181a-3p, 625-5p, 4772-3p, 155-3p, 142-5p, 142-3p, 155-5p, 625-3p, 1976, 7702), many lncRNAs, and pathways (apoptosis, cytokine-cytokine receptor interaction, Jak-STAT signaling, MAPK signaling, PI3K-AKT signaling, HIF-1 signaling, ECM receptor interaction, focal adhesion, and estrogen signaling). Further, tumor mutation burden showed no significant correlation with antitumor immunity, while tumor aneuploidy levels showed a significant negative correlation with antitumor immunity.

Conclusion: The molecular features significantly associated with HCC immunity could be predictive biomarkers for immunotherapeutic responses in HCC patients. They could also be potential intervention targets for boosting antitumor immunity and immunotherapeutic responses in HCC.

Differential Expression of Zinc-Dependent HDAC Subtypes and their Involvement in Unique Pathways Associated with Carcinogenesis

OBJECTIVE

The present study aims to identify the effect of ZnHDACs expression on the survival of the patients. Further, reveal the unique and common genes associated with each ZnHDACs and their associated pathways.

METHODS

The patient data was obtained from the Cancer Genome Atlas Program (TCGA) database and was analyzed using cBioportal and Gene Expression Profiling Interactive Analysis 2(GEPIA2) online tools. Protein-protein interactions and functional interactomic analysis were done using STRING, DAVID, and KEGG pathway databases.

RESULTS

HDAC1, 2, 8, 11 were over-expressed and, HDAC4, 5, 6, 7, and 10 were down-regulated in all the cancer types, but there are few exceptional expression patterns such as HDAC7 and HDAC10 overexpression in HNSC, HDAC3 down-regulation in LUAD, and PRAD. The unique genes interacting with each ZnHDACs provided a better understanding of ZnHDAC's putative role in carcinogenesis. The present study reported that JARID2, stem cell regulation gene uniquely interacts with HDAC1, BPTF-CHRAC-BAZIA axis, enzymes for chromatin modeling selectively interacting with only HDAC2, HDAC3 in H2A acetylation via DMAP1 and YEATS4. HDAC6 associated unique genes regulate protein stability, HDAC7 in subnuclear localization and splicing, HDAC8 in telomere maintenance, HDAC9 in chromosomal rearrangements, and HDAC11 in maintaining histone core and folding.

CONCLUSION

The unique genes and pathways associated with a particular ZnHDACs could provide a wide window for interrogating these genes for obtaining putative drug targets.

Analysis of cancer omics data: a selective review of statistical techniques

Cancer is an omics disease. The development in high-throughput profiling has fundamentally changed cancer research and clinical practice. Compared with clinical, demographic and environmental data, the analysis of omics data-which has higher dimensionality, weaker signals and more complex distributional properties-is much more challenging. Developments in the literature are often 'scattered', with individual studies focused on one or a few closely related methods. The goal of this review is to assist cancer researchers with limited statistical expertise in establishing the 'overall framework' of cancer omics data analysis. To facilitate understanding, we mainly focus on intuition, concepts and key steps, and refer readers to the original publications for mathematical details. This review broadly covers unsupervised and supervised analysis, as well as individual-gene-based, gene-set-based and gene-network-based analysis. We also briefly discuss 'special topics' including interaction analysis, multi-datasets analysis and multi-omics analysis.

Pan-Cancer Analysis Reveals That E1A Binding Protein p300 Mutations Increase Genome Instability and Antitumor Immunity

E1A binding protein p300 (EP300) is mutated in diverse cancers. Nevertheless, a systematic investigation into the associations of EP300 mutations with genome instability and antitumor immunity in pan-cancer remains lacking. Using the datasets from The Cancer Genome Atlas, we analyzed the correlations between EP300 mutations and genome instability and antitumor immune response in 11 cancer types. Compared to EP300-wild-type cancers, EP300-mutated cancers had significantly higher tumor mutation burden (TMB) in 10 cancer types. EP300-mutated cancers harbored a much higher fraction of microsatellite instable cancers in the colon and gastric cancers. EP300 was co-mutated with genes involved in DNA damage repair pathways in multiple cancers. Furthermore, compared to EP300-wild-type cancers, EP300-mutated cancers had significantly higher immune cytolytic activity scores and ratios of immune-stimulatory over immune-inhibitory signatures in diverse cancers. Also, EP300-mutated cancers showed significantly higher programmed death-ligand 1 (PD-L1) expression levels than EP300-wild-type cancers. The increased TMB, antitumor immune activity, and PD-L1 expression indicated a favorable response to immune checkpoint inhibitors (ICIs) in EP300-mutated cancers, as evident in three cancer cohorts treated with ICIs. Thus, the EP300 mutation could be a predictive biomarker for the response to immunotherapy.

KALRN mutations promote antitumor immunity and immunotherapy response in cancer

Background

kalirin RhoGEF kinase (KALRN) is mutated in a wide range of cancers. Nevertheless, the association between KALRN mutations and the pathogenesis of cancer remains unexplored. Identification of biomarkers for cancer immunotherapy response is crucial because immunotherapies only show beneficial effects in a subset of patients with cancer.

Methods

We explored the correlation between KALRN mutations and antitumor immunity in 10 cancer cohorts from The Cancer Genome Atlas program by the bioinformatics approach. Moreover, we verified the findings from the bioinformatics analysis with in vitro and in vivo experiments. We explored the correlation between KALRN mutations and immunotherapy response in five cancer cohorts receiving immune checkpoint blockade therapy.

Results

Antitumor immune signatures were more enriched in KALRN-mutated than KALRN-wildtype cancers. Moreover, KALRN mutations displayed significant correlations with increased tumor mutation burden and the microsatellite instability or DNA damage repair deficiency genomic properties, which may explain the high antitumor immunity in KALRN-mutated cancers. Also, programmed cell death 1 ligand (PD-L1) expression was markedly upregulated in KALRN-mutated versus KALRN-wildtype cancers. The increased antitumor immune signatures and PD-L1 expression in KALRN-mutated cancers may favor the response to immune checkpoint blockade therapy in this cancer subtype, as evidenced in five cancer cohorts receiving antiprogrammed cell death protein 1 (PD-1)/PD-L1/cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) immunotherapy. Furthermore, the significant association between KALRN mutations and increased antitumor immunity was associated with the fact that KALRN mutations compromised the function of KALRN in targeting Rho GTPases for the regulation of DNA damage repair pathways. In vitro and in vivo experiments validated the association of KALRN deficiency with antitumor immunity and the response to immune checkpoint inhibitors.

Conclusions

The KALRN mutation is a useful biomarker for predicting the response to immunotherapy in patients with cancer.

Functional succinate dehydrogenase deficiency is a common adverse feature of clear cell renal cancer

This study demonstrates that underexpression of succinate dehydrogenase (SDH) subunits resulting in accumulation of oncogenic succinate is a common, adverse, epigenetic modulating feature in clear cell renal cell carcinoma (ccRCC), during pathogenesis and progression. The study sheds light on the mechanisms of down-regulation of SDH subunits in ccRCC and deciphers the consequent oncogenic effects. It shows that functional SDH deficiency is a common feature of ccRCC (∼80% of all kidney cancers), and not just limited to the 0.05 to 0.5% of kidney cancers with germline SDH mutations.

Reduced succinate dehydrogenase (SDH) activity resulting in adverse succinate accumulation was previously considered relevant only in 0.05 to 0.5% of kidney cancers associated with germline SDH mutations. Here, we sought to examine a broader role for SDH loss in kidney cancer pathogenesis/progression. We report that underexpression of SDH subunits resulting in accumulation of oncogenic succinate is a common feature in clear cell renal cell carcinoma (ccRCC) (∼80% of all kidney cancers), with a marked adverse impact on survival in ccRCC patients (n = 516). We show that SDH down-regulation is a critical brake in the TCA cycle during ccRCC pathogenesis and progression. In exploring mechanisms of SDH down-regulation in ccRCC, we report that Von Hippel-Lindau loss-induced hypoxia-inducible factor–dependent up-regulation of miR-210 causes direct inhibition of the SDHD transcript. Moreover, shallow deletion of SDHB occurs in ∼20% of ccRCC. We then demonstrate that SDH loss-induced succinate accumulation contributes to adverse loss of 5-hydroxymethylcytosine, gain of 5-methylcytosine, and enhanced invasiveness in ccRCC via inhibition of ten-eleven translocation (TET)-2 activity. Intriguingly, binding affinity between the catalytic domain of recombinant TET-2 and succinate was found to be very low, suggesting that the mechanism of succinate-induced attenuation of TET-2 activity is likely via product inhibition rather than competitive inhibition. Finally, exogenous ascorbic acid, a TET-activating demethylating agent, led to reversal of the above oncogenic effects of succinate in ccRCC cells. Collectively, our study demonstrates that functional SDH deficiency is a common adverse feature of ccRCC and not just limited to the kidney cancers associated with germline SDH mutations.

Epithelial-Mesenchymal Transition Gene Signature Related to Prognostic in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) remains an important cause of cancer-related mortality worldwide. Epithelial–mesenchymal transition (EMT) is a key mechanism, promoting not only the invasive or metastatic phenotype but also resistance to therapy. Using bioinformatics approaches, we studied the alteration on EMT related genes and its implication on COAD prognostic based on public datasets. For the EMT mechanisms, two overexpressed genes were identified (NOX4 and IGF2BP3), as well as five downregulated genes (BMP5, DACT3, EEF1A2, GCNT2 and SFRP1) that were related to prognosis in COAD. A qRT-PCR validation step was conducted in a COAD patient cohort comprising of 29 tumor tissues and 29 normal adjacent tissues, endorsing the expression level for BMP5, as well as for two of the miRNAs targeting key EMT related genes, revealing upregulation of miR-27a-5p and miR-146a-5p. The EMT signature can be used to develop a panel of biomarkers for recurrence prediction in COAD patients, which may contribute to the improvement of risk stratification for the patients.

Mutant CDKN2A regulates P16/p14 expression by alternative splicing in renal cell carcinoma metastasis

OBJECTIVE

Metastatic renal cell carcinoma (mRCC) is the important factor for patient mortality, meanwhile gene mutation constantly changes cancer prognosis in tumor process. Exploring the driver mutation in mRCC process become more and more important.

MATERIALS AND METHODS

We obtained the 15 paired primary and metastatic mRCC samples and analyzed specific mutation genes in the metastatic foci (SMGs) by next generation sequencing. Moreover, we explored the Correlated networks, Pathway and Gene Ontology (GO) enrichment results, prediction analysis of AS sites and prognosis of survival.

RESULTS

We identify EPCAM, TMEM127, EZH2, EXT1, CDKN2A, PRF1, AIP, CDK4, PRKARIA as SMGs and find that CDKN2A mutation sites affect the prognosis of mRCC by altering splicing elements. Based on the differential analysis for SMGs in KIRC, we found that EPCAM, PRF1 and EZH2 were differential expression in both primary tumors with metastasis compared to primary tumors without metastasis or metastatic tissues. By the AS prediction analysis, we suggest that CDKN2A mutation sites play an important role for RCC metastasis by affecting the p16/p14 expression.

CONCLUSIONS

The SMGs could provide new molecular cues associated with tumor metastasis and have potential clinical implications for cancer prognosis and treatment. Definitive conclusions await further validation and follow up.

Cancer-Associated Stemness and Epithelial-to-Mesenchymal Transition Signatures Related to Breast Invasive Carcinoma Prognostic

Simple Summary

Breast cancer is one of the most common oncological diseases in women, as its incidence is rapidly growing. In this study, we have investigated the mechanism of epithelial-to-mesenchymal transition (EMT) and cancer stem cells (CSCs), demonstrating presence of an interconnectedness between them. This interconnectedness plays important roles in patient prognostic, as well as in diagnostic and therapeutic targets. It is identified that there is a common signature between CSCs and EMT, and this is represented by ALDH1A1, SFRP1, miR-139, miR-21, and miR-200c. This finding will provide a better understanding of this mechanism, and will facilitate the development of novel treatment options.

Abstract

Breast cancer is one of the most common oncological diseases in women, as its incidence is rapidly growing, rendering it unpredictable and causing more harm than ever before on an annual basis. Alterations of coding and noncoding genes are related to tumorigenesis and breast cancer progression. In this study, several key genes associated with epithelial-to-mesenchymal transition (EMT) and cancer stem cell (CSC) features were identified. EMT and CSCs are two key mechanisms responsible for self-renewal, differentiation, and self-protection, thus contributing to drug resistance. Therefore, understanding of the relationship between these processes may identify a therapeutic vulnerability that can be further exploited in clinical practice, and evaluate its correlation with overall survival rate. To determine expression levels of altered coding and noncoding genes, The Cancer Omics Atlas (TCOA) are used, and these data are overlapped with a list of CSCs and EMT-specific genes downloaded from NCBI. As a result, it is observed that CSCs are reciprocally related to EMT, thus identifying common signatures that allow for predicting the overall survival for breast cancer genes (BRCA). In fact, common CSCs and EMT signatures, represented by ALDH1A1, SFRP1, miR-139, miR-21, and miR-200c, are deemed useful as prognostic biomarkers for BRCA. Therefore, by mapping changes in gene expression across CSCs and EMT, suggesting a cross-talk between these two processes, we have been able to identify either the most common or specific genes or miRNA markers associated with overall survival rate. Thus, a better understanding of these mechanisms will lead to more effective treatment options.

DriverDBv3: a multi-omics database for cancer driver gene research

An integrative multi-omics database is needed urgently, because focusing only on analysis of one-dimensional data falls far short of providing an understanding of cancer. Previously, we presented DriverDB, a cancer driver gene database that applies published bioinformatics algorithms to identify driver genes/mutations. The updated DriverDBv3 database (http://ngs.ym.edu.tw/driverdb) is designed to interpret cancer omics’ sophisticated information with concise data visualization. To offer diverse insights into molecular dysregulation/dysfunction events, we incorporated computational tools to define CNV and methylation drivers. Further, four new features, CNV, Methylation, Survival, and miRNA, allow users to explore the relations from two perspectives in the ‘Cancer’ and ‘Gene’ sections. The ‘Survival’ panel offers not only significant survival genes, but gene pairs synergistic effects determine. A fresh function, ‘Survival Analysis’ in ‘Customized-analysis,’ allows users to investigate the co-occurring events in user-defined gene(s) by mutation status or by expression in a specific patient group. Moreover, we redesigned the web interface and provided interactive figures to interpret cancer omics’ sophisticated information, and also constructed a Summary panel in the ‘Cancer’ and ‘Gene’ sections to visualize the features on multi-omics levels concisely. DriverDBv3 seeks to improve the study of integrative cancer omics data by identifying driver genes and contributes to cancer biology.

Unraveling the role of peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) expression in colon carcinogenesis

The peroxisome proliferator-activated-β/δ (PPARβ/δ) was identified in 1994, but not until 1999 was PPARβ/δ suggested to be involved in carcinogenesis. Initially, it was hypothesized that expression of PPARβ/δ was increased during colon cancer progression, which led to increased transcription of yet-to-be confirmed target genes that promote cell proliferation and tumorigenesis. It was also hypothesized at this time that lipid-metabolizing enzymes generated lipid metabolites that served as ligands for PPARβ/δ. These hypothetical mechanisms were attractive because they potentially explained how non-steroidal anti-inflammatory drugs inhibited tumorigenesis by potentially limiting the concentration of endogenous PPARβ/δ ligands that could activate this receptor that was increased in cancer cells. However, during the last 20 years, considerable research was undertaken describing expression of PPARβ/δ in normal and cancer cells that has led to a significant impact on the mechanisms by which PPARβ/δ functions in carcinogenesis. Whereas results from earlier studies led to much uncertainty about the role of PPARβ/δ in cancer, more recent analyses of large databases have revealed a more consistent understanding. The focus of this review is on the fundamental level of PPARβ/δ expression in normal tissues and cancerous tissue as described by studies during the past two decades and what has been delineated during this timeframe about how PPARβ/δ expression influences carcinogenesis, with an emphasis on colon cancer.

Susan G. Komen Big Data for Breast Cancer Initiative: How Patient Advocacy Organizations Can Facilitate Using Big Data to Improve Patient Outcomes

Integrating different types of data, including electronic health records, imaging data, administrative and claims databases, large data repositories, the Internet of Things, genomics, and other omics data, is both a challenge and an opportunity that must be tackled head on. We explore some of the challenges and opportunities in optimizing data integration to accelerate breast cancer discovery and improve patient outcomes. Susan G. Komen convened three meetings (2015, 2017, and 2018) with various stakeholders to discuss challenges, opportunities, and next steps to enhance the use of big data in the field of breast cancer. Meeting participants agreed that big data approaches can enhance the identification of better therapies, improve outcomes, reduce disparities, and optimize precision medicine. One challenge is that databases must be shared, linked with each other, standardized, and interoperable. Patients want to be active participants in research and their own care, and to control how their data are used. Many patients have privacy concerns and do not understand how sharing their data can help to effectively drive discovery. Public education is essential, and breast cancer researchers who are skilled in using and analyzing big data are needed. Patient advocacy groups can play multiple roles to help maximize and leverage big data to better serve patients. Komen is committed to educating patients on big data issues, encouraging data sharing by all stakeholders, assisting in training the next generation of data science breast cancer researchers, and funding research projects that will use real-life data in real time to revolutionize the way breast cancer is understood and treated.

Identification of Transcriptional Signatures of Colon Tumor Stroma by a Meta-Analysis

Background

The tumor stroma plays pivotal roles in influencing tumor growth, invasion, and metastasis. Transcriptional signatures of colon tumor stroma (CTS) are significantly associated with prognosis of colon cancer. Thus, identification of the CTS transcriptional features could be useful for colon cancer diagnosis and therapy.

Methods

By a meta-analysis of three CTS gene expression profiles datasets, we identified differentially expressed genes (DEGs) between CTS and colon normal stroma. Furthermore, we identified the pathways, upstream regulators, and protein-protein interaction (PPI) network that were significantly associated with the DEGs. Moreover, we analyzed the enrichment levels of immune signatures in CTS. Finally, we identified CTS-associated gene signatures whose expression was significantly associated with prognosis in colon cancer.

Results

We identified numerous significantly upregulated genes (such as CTHRC1, NFE2L3, SULF1, SOX9, ENC1, and CCND1) and significantly downregulated genes (such as MYOT, ASPA, KIAA2022, ARHGEF37, BCL-2, and PPARGC1A) in CTS versus colon normal stroma. Furthermore, we identified significantly upregulated pathways in CTS that were mainly involved in cellular development, immune regulation, and metabolism, as well as significantly downregulated pathways in CTS that were mostly metabolism-related. Moreover, we identified upstream TFs (such as SUZ12, NFE2L2, RUNX1, STAT3, and SOX2), kinases (such as MAPK14, CSNK2A1, CDK1, CDK2, and CDK4), and master metabolic transcriptional regulators (MMTRs) (such as HNF1A, NFKB1, ZBTB7A, GATA2, and GATA5) regulating the DEGs. We found that CD8+ T cells were more enriched in CTS than in colon normal stroma. Interestingly, we found that many of the DEGs and their regulators were prognostic markers for colon cancer, including CEBPB, PPARGC1, STAT3, MTOR, BCL2, JAK2, and CDK1.

Conclusions

The identification of CTS-specific transcriptional signatures may provide insights into the tumor microenvironment that mediates the development of colon cancer and has potential clinical implications for colon cancer diagnosis and treatment.

Identification of genomic features associated with immunotherapy response in gastrointestinal cancers

Gastrointestinal (GI) cancers prevail and account for an extremely high number of cancer deaths worldwide. The traditional treatment strategies, including surgery, chemotherapy, radiotherapy, and targeted therapy, have a limited therapeutic effect for advanced GI cancers. Recently, immunotherapy has shown promise in treating various refractory malignancies, including the GI cancers with mismatch repair deficiency (dMMR) or microsatellite instability (MSI). Thus, immunotherapy could be a promising treatment approach for GI cancers. Unfortunately, only a small proportion of GI cancer patients currently respond to immunotherapy. Therefore, it is important to discover predictive biomarkers for stratifying GI cancer patients response to immunotherapy. Certain genomic features, such as dMMR/MSI, tumor mutation burden (TMB), and tumor aneuploidy have been associated with tumor immunity and im-munotherapy response and may serve as predictive biomarkers for cancer immunotherapy. In this review, we examined the correlations between tumor immunity and three genomic features: dMMR/MSI, TMB, and tumor aneuploidy. We also explored their correlations using The Cancer Genome Atlas data and confirmed that the dMMR/MSI status, high TMB, and low tumor aneuploidy are associated with elevated tumor immunity in GI cancers. To improve the immunotherapeutic potential in GI cancers, more genetic or genomic features associated with tumor immune response need to be identified. Furthermore, it is worth exploring the combination of different immunotherapeutic methods and the combination of immunotherapy with other therapeutic approaches for cancer therapy.

CMTCN: a web tool for investigating cancer-specific microRNA and transcription factor co-regulatory networks

Transcription factors (TFs) and microRNAs (miRNAs) are well-characterized trans-acting essential players in gene expression regulation. Growing evidence indicates that TFs and miRNAs can work cooperatively, and their dysregulation has been associated with many diseases including cancer. A unified picture of regulatory interactions of these regulators and their joint target genes would shed light on cancer studies. Although online resources developed to support probing of TF-gene and miRNA-gene interactions are available, online applications for miRNA-TF co-regulatory analysis, especially with a focus on cancers, are lacking. In light of this, we developed a web tool, namely CMTCN (freely available at http://www.cbportal.org/CMTCN), which constructs miRNA-TF co-regulatory networks and conducts comprehensive analyses within the context of particular cancer types. With its user-friendly provision of topological and functional analyses, CMTCN promises to be a reliable and indispensable web tool for biomedical studies.

Correction to: The Cancer Omics Atlas: an integrative resource for cancer omics annotations

Following publication of the original article [1], the authors reported an error in Fig. 1A.