Exploring the diversified roles of Anoctamin Family in Pan-Cancer

doi:10.21203/rs.3.rs-3233965/v1

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Research Article

Exploring the diversified roles of Anoctamin Family in Pan-Cancer

https://doi.org/10.21203/rs.3.rs-3233965/v1

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Background

Anoctamin family (Transmembrane Protein 16), has gained growing attention for generating exosome and ectosome to mediate cancer cell communication in the process of phospholipid scrambling. However, former studies only focused on one narrow process in a single cancer. Instead, we designed a multidimensional study to comprehensively investigate the impact of ANO family on eight critical multi-omics cancer features in TCGA pan-cancer cohort.

Methods

TCGA pan-cancer cohorts were downloaded from UCSC xena. Differential analysis, survival analysis, and correlation analysis with tumor mutation burden, immune-phenotyping, stemness, cell proportion of tumor microenvironment, and drug sensitivity were conducted by R software. Alteration landscape was obtained from cBioportal with STRING database showing the protein-protein interaction network. Nanoparticle Tracking Analysis and Western Blot were employed to identify the ANO5 exosome.

Results

Extensive and profound associations were found between ANO family and eight crucial cancer features, including clinical prognosis, metastasis, drug resistance, tumor mutation burden, stemness, and tumor microenvironment. ANO1 possessed a high mutation frequency and is a driver gene in multiple cancers. ANO5 can exist in exosome to mediate cell-cell communication.

Conclusions

ANO family broadly participates in the proliferation, metastasis, and drug resistance in a barrage of cancers by generating extracellular vesicles to mediate cell-cell communication and interacting with TMB, stemness, stromal and immune cell proportions in tumor microenvironment. ANO members can serve as reliable biomarkers for prognosis of cancer, as well as promising targets for trans-cancer treatment.

Anoctamin family

exosome

multi-omics

pan-cancer

tumor microenvironment

The anoctamin (ANO) family, also called transmembrane protein 16 (TMEM16), is a new type of Ca²⁺-activated chloride channel (CaCC) (1, 2). ANO1-10, the major family members, are broadly expressed in epithelial tissues (3), operating as ion channels and phospholipid scramblases (4, 5), which play a key role in cell-cell communication by generating extracellular vesicles (EV: both exosomes and ectosomes) (6).

Recently, there has been a growing amount of evidence connecting the ANO family with tumor formation, progression, and metastasis. ANO1 (DOG1) has been identified as a driver gene in gastrointestinal stromal tumor (GIST) and head and neck squamous cell carcinoma (HNSC) (7–9), interacting with Her-2 (10), PI3K, TGF-beta, and TNF-α (11–16). ANO5 (17, 18), ANO7 (19, 20), and ANO9 (21) were identified as biomarkers for poor survival outcomes in several cancers. ANO6 was reported to promote cell apoptosis (22), ferroptosis (23, 24), and cancer proliferation (25). Most of these former studies, however, only focused on one narrow process of a single cancer with common test validation. Moreover, knowledge about effects of ANO members on multiple cancers’ development is still a void.

Consequently, we first designed a multidimensional study to comprehensively investigate the impact of the ANO family on eight critical multi-omics cancer phenotypes across 33 cancer types, including their prognostic effect, correlation with tumor mutation burden (TMB), immune subtypes, tumor stemness, tumor purity, drug resistance, genetic alteration, and protein-protein interaction (PPI). Among them, TMB reflects the mutation frequency and serves as a critical factor in predicting immunotherapy response (26). Six immune subtypes are discovered to represent different immune status in diverse cancers: wound healing (C1), IFN-γ dominant (C2), inflammatory (C3), lymphocyte depleted (C4), immunologically quiet (C5), TGF-β dominant (C6) (27). Tumor purity (28, 29) indicates the proportion of stromal and immune cells in the tumor microenvironment (TME), which is the key to tumor metastasis and drug resistance (30). Tumor stemness is pivotal for cancer proliferation and self-renewal (31). Genetic alteration and PPI assist in finding the driver gene for targeted therapy. In addition, as most studies have reported, ANO members play a communicative role in the formation and release of exosomes, thereby mediating cell communication (6).

As the first multidimensional study to elucidate the effect of ANO family on eight crucial multi-omics features in TCGA pan-cancer cohort, we believe that it will be helpful to deepen our cognition of ANO family in the cancer field and guide clinical practice of diagnosis and treatment.

Data acquisition

The Ethics Committee of Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine approved this study. The pan-cancer dataset in The Cancer Genome Atlas (TCGA) which consists of 33 kinds of cancer and adjacent tissue samples, was downloaded from UCSC Xena (http://xena.ucsc.edu/) on June 24, 2020. Next, gene expression values for ANO1, ANO10, ANO2, ANO3, ANO4, ANO5, ANO6, ANO7, ANO7L1, ANO8, ANO9, ANOS1, and ANOS2P were merged with phonotype information for further analysis.

Differential analysis for the ANO family between tumor and adjacent tissues

A boxplot was used to demonstrate the medium expression value of the ANO family in 33 kinds of tumor tissue. Differentially expressed genes between each specific tumor and adjacent tissue were selected with the Wilcox test. Tumors with fewer than three normal samples were excluded. Next, a heatmap was portrayed to present the expression differences ranked by log2 fold change (FC) value.

Survival analysis and clinical correlation of ANO family in pan-cancer

Survival analysis was implemented for each ANO gene with the median FPKM value as the cut-off to divide patients into high-expressed and low-expressed groups. Kaplan-Meier curves were plotted to demonstrate a statistically significant survival outcome for each ANO gene. Subsequently, Cox proportional hazard regression was applied to access the effect size of each ANO gene on overall survival (OS) in 33 cancer types. Moreover, the Kruskal-Wallis test was employed to present the correlation between the expression of ANO members and TNM stage.

Correlation between the ANO family and TMB in pan-cancer

TMB is a key factor in predicting the immune therapy response and prognosis of patients with most types of cancer (32). Lawrence et al. performed a comprehensive investigation of TMB in 27 cancer types by calculating non-synonymous mutations per mega base (33). By applying the same process, we comprehensively surveyed the TMB levels in 33 cancer types with a Pearson correlation coefficient describing their correlation with the expression of ANO members.

Correlation between tumor immune subtype and ANO family in pan-cancer

Thorsson V, et al. identified 6 immune subtypes in the TCGA program which play key roles in the field of immunotherapy and other cancer treatment practice: wound healing (C1), IFN-γ dominant (C2), inflammatory (C3), lymphocyte depleted (C4), immunologically quiet (C5), TGF-β dominant (C6) (27). To access the correlation between ANO genes and the immune subtypes of each tumor type, the Kruskal-Wallis test was utilized to access the differences in ANO gene expression among six immune subtypes.

Correlation analysis between the ANO family and TME, tumor stemness scores in pan-cancer

It has been known to us that the tumor micro-environment (TME) plays an important role in cancer progression and drug resistance (28). ESTIMATE is an algorithm to evaluate tumor TME by calculating stromal, immune, and ESTIMATE scores to reflect the proportion of stromal and immune cells (34). We performed this algorithm and Spearman correlation analysis to identify correlations between ESTIMATE scores in pan-cancer and the ANO family. In addition, correlation analysis was also employed between the ANO family and stemness indices, which contain both DNA methylation-based stemness score (DNAss) and mRNA expression-based stemness score (RNAss), proposed by Malta TM et al., to access tumor stemness features by using the one-class logistic regression (OCLR) algorithm (35).

Drug sensitivity analysis in pan-cancer

CellMiner, a web-based tool compiled by the U.S. National Cancer Institute, provides data on RNA-seq profiles and drug activity in the NCI-60 cell line sets (36). To be more specific, RNA-seq values of 22,379 genes and drug responses of 20,503 compounds are available in their database (https://discover.nci.nih.gov/cellminer/) (37). To explore the correlation between ANO gene expression levels and drug sensitivity, the Pearson correlation analysis was conducted between ANO gene expression value (log2 (FPKM + 1)) and the Drug Activity Z score originated from CellMiner.

Co-expression analysis and PPI network

Previous research has shown that genes usually bind together to function in a specific way, rather than working alone. Hence, we employed co-expression analyses between ANO members to explore the potential co-expressed partners, and a PPI network of the ANO family was constructed employing the STRING database (https://string-db.org/).

Genetic alteration of the ANO family in pan-cancer

As intense correlations were identified between the ANO family and clinical features above, we explored the general alteration of the ANO family in pan-cancer to seek for potential driver genes and treatment targets by using cBioportal (http://www.cbioportal.org). An oncoprint illustrated the breadth and frequency of its mutation spectrum across 33 cancer types.

Landscape of alteration in PI3K and TGF-beta pathways in pan-cancer

Former studies pointed that ANO family harbours intense dependency on PI3K and TGF-beta pathways to fulfill their function (13, 38). So, a landscape of PI3K and TGF-beta pathway alteration in pan-cancer was painted, using Genomic Alteration Matrices and curated pathway templates offered by Francisco et al., in their study of oncogenic signaling pathways in PanCancerAltas (39).

Detection of ANO exosome and differential analysis between tumor and normal samples

ANO members are conducive to the release of extracellular vesicles (both exosomes and ectosomes) in the process of phospholipid scrambling to mediate cell communication (6). To confirm whether ANO members can work as exosomes themselves to mediate downstream signaling transduction, we detected the existence of ANO5 exosomes in the culture medium of a series of colorectal cancer cell lines including sw620, sw480, lovo, caco2, DLD1, sw1116, RKO, colo320DM, HT29, HCT116, and colo205, along with normal human intestine cell line HIEC by Nanoparticle Tracking Analysis and Western Blot. In addition, commonly used markers of exosomes including Alix, CD63, CD81, HSP70, and TSG101 were also adopted. All the experiments were performed in triplicates. Expression of ANO family exosomes was also obtained from the exoRbase (http://www.exorbase.org/) to explore their differential expression between tumor and normal samples.

Statistics and software

Data processing and normalization were conducted by R 3.6.1 and several packages for R were adopted for corresponding analysis, including “ggpubr” for differential analysis and “impute” (http://www.bioconductor.org/packages/release/bioc/html/impute.html) to process the raw data from different databases including cellMiner. The significance level for all statistical tests was assigned as two-sided P < 0.05.

Differential expression of ANO family in 33 cancer types

The TCGA cohort of the 33 cancers and their abbreviations were demonstrated in Table 1. All the analysis processes were summarized in Fig. 1a. Median gene expression levels of ANO family in pan-cancer tumor tissues were shown in Fig. 1b, in which ANO1, ANO6, and ANO10 possessed relatively high expression values. When compared with adjacent tissues, most types of tumor showed a significant difference in gene expression levels of ANO family: either up- or down-regulated in tumor tissues (Fig. 1c). For instance, ANO1 was highly expressed in tumor tissues of BLCA (p < 0.01, log2FC = 0.94), COAD (p < 0.001, log2FC = 0.61) and HNSC (p < 0.001, log2FC = 1.79). Such expression differences were also widely seen in other ANO genes across many cancer types (Fig. 1d-o). What is worth noting is that ANO1, ANO6 were significantly higher expressed in COAD (ANO1, log2FC = 0.61; ANO6, log2FC = 0.75) but lower expressed in LUAD (ANO1, log2FC = -0.32; ANO6, log2FC = -0.84), indicating the ANO family's functional diversity in various cancers.

Table 1

TCGA cohort of the 33 cancers and their abbreviations.
Cancer full name	Abbreviation	Cancer full name	Abbreviation
Adrenocortical carcinoma	ACC	Lung adenocarcinoma	LUAD
Bladder Urothelial Carcinoma	BLCA	Lung squamous cell carcinoma	LUSC
Breast invasive carcinoma	BRCA	Mesothelioma	MESO
Cervical squamous cell carcinoma and endocervical adenocarcinoma	CESC	Ovarian serous cystadenocarcinoma	OV
Cholangiocarcinoma	CHOL	Pancreatic adenocarcinoma	PAAD
Colon adenocarcinoma	COAD	Pheochromocytoma and Paraganglioma	PCPG
Lymphoid Neoplasm Diffuse Large B-cell Lymphoma	DLBC	Prostate adenocarcinoma	PRAD
Esophageal carcinoma	ESCA	Rectum adenocarcinoma	READ
Glioblastoma multiforme	GBM	Sarcoma	SARC
Head and Neck squamous cell carcinoma	HNSC	Skin Cutaneous Melanoma	SKCM
Kidney Chromophobe	KICH	Stomach adenocarcinoma	STAD
Kidney renal clear cell carcinoma	KIRC	Testicular Germ Cell Tumors	TGCT
Kidney renal papillary cell carcinoma	KIRP	Thyroid carcinoma	THCA
Acute Myeloid Leukemia	LAML	Thymoma	THYM
Brain Lower Grade Glioma	LGG	Uterine Corpus Endometrial Carcinoma	UCEC
Liver hepatocellular carcinoma	LIHC	Uterine Carcinosarcoma	UCS
Uveal Melanoma	UVM

Survival analysis and clinical correlation analysis of ANO family in pan-cancer

Patients in 33 types of tumor cohorts were then divided into high- and low-expressed group according to the median expression value of each ANO gene. Subsequent survival analyses obtained significant differences across many cancer types. Specifically, low ANO1 expression levels indicated a better prognosis of UVM (Fig. 2a, p = 0.017) and HNSC (Fig. 2b, p = 0.014) patients. Additionally, high expression levels of ANOS1 were correlated with a longer overall survival of LAML patients (Fig. 2c, p = 0.019). In addition, elevated ANO3 expression also suggested a more favorable survival outcome of KIRC patients (Fig. 2d, p < 0.001). Moreover, down-regulation of ANO4 was linked with a better prognosis of UVM patients (Fig. 2e, p < 0.001). Besides, elevated ANO5 and ANO6 expression were associated with worse survival outcomes of LUSC (Fig. 2f, p < 0.001) and LGG (Fig. 2g, p < 0.001) patients, respectively. What’s more, up-regulation of ANO7L1 (Fig. 2h, p = 0.007) and ANO8 (Fig. 2i, p < 0.001) both indicated a longer overall survival of UVM patients.

Further Cox regression analysis confirmed this variance in a forest plot (Fig. 3a). Typically, ANO5 acted as a risk factor in THCA (HR = 2.93), LIHC (HR = 1.45) and UVM (HR = 2.07) but served as a protective factor in KIRP (HR = 0.40), PAAD (HR = 0.58), MESO (HR = 0.47), etc..

Subsequent clinical analysis in STAD cohort revealed that expression of ANO1 (p = 0.043) and ANOS1 were higher expressed, while ANO7L1 possessed a lower expression in advanced pathological stage (Fig. 3b). This suggested that ANO1, ANOS1 might serve as risk factor of STAD progression and metastasis. As for COAD, ANO7 and ANO7L1 were also relatively low expressed in stage IV (Fig. 3c), consistent with the results in STAD, underlying a negative regulation network between ANO7, ANO7L1 and progression and metastasis of COAD.

Correlation between ANO family and TMB in pan-cancer

TMB in 33 cancer types was presented in the form of log10 (TMB + 1). Cancers were ordered by the value of median somatic mutation frequency (Fig. 4a) where a relatively high TMB was seen in SKCM, LUSC, LUAD, BLCA and COAD. High TMB in LUSC and SKCM can be attributed to the exposure of tobacco and UV light which are known factors to genetic mutation. But high TMB in LUAD, BLCA and COAD, seems to be their inherent essence at beginning.

Subsequent correlation analysis demonstrated an extensive negative correlations between ANO family and TMB in 33 cancer types (Fig. 4b). THYM, however, showed a widely positive associations with ANO1 (Pearson coefficient = 0.34), ANO10 (Pearson coefficient = 0.53), ANO2 (Pearson coefficient = 0.38), etc, underlying its mutational heterogeneity from other cancers.

Correlation between ANO family and immune subtypes

We then explored the expression differences of ANO family in six tumor immune subtypes, including wound healing (C1), IFN-γ dominant (C2), inflammatory (C3), lymphocyte depleted (C4), immunologically quiet (C5), and TGF-beta dominant (C6). The expression value of subtype C5 were identified to have significant distinction with other subtypes. ANO1, ANO2, ANO6, ANO7, ANO7L1, and ANO9 were relatively high expressed in subtype C5 while ANO3, ANO4, ANO5, ANO8, ANOS1, and ANOS2P were significantly low expressed, indicating a possible regulation relationship between tumor immune micro-environment and ANO family function (Figure S1a).

For LIHC, without immune subtype C5, which only existed in LGG, significant expression differences of ANO1, ANO10, ANO2, ANO4, ANO6, ANO7, ANO7L1, ANO8, ANO9, and ANOS1 existed among the five subtypes (Figure S1b). In terms of LUAD, ANO1, ANO7 and ANO8 were quite low expressed in subtype C4 while ANO2, ANO4, ANO5, ANO8, ANO9 and ANOS1 were rather high expressed in subtype C3 (Figure S1c). For SARC, significant differences of ANO1, ANO2, ANO6, ANO7L1, ANO9, and ANOS1 expression were also discovered among the five subtypes (Figure S1d). Taken together, these results revealed a underlying correlation between ANO family and six tumor immune subtypes.

Role of ANO family in tumor microenvironment and tumor stemness

ANO members showed broad positive correlations with stromal, immune, and ESTIMATE scores and extensive negative correlations with tumor purity of 33 cancer types (Fig. 5a-d). Notably, ANO9 and ANOS1 were negatively associated with tumor purity of most cancer types, which indicated that cancers with high expression of ANO9, ANOS1 tended to have more stromal and immune cells while less tumor cells in TME. In addition, DLBC showed broad negative correlations while SARC revealed wide positive correlations with the expression of ANO family. Taken together, the function diversity of ANO family was characterized in TME of diverse cancers.

In correlation analysis with tumor stemness, there was a large part of negative correlations between DNAss and ANO family (Fig. 5e). Taking OV for example, there were negative correlations for ANO4 (Spearman coefficient = 0.42), ANO8 (Spearman coefficient = -0.75), ANO9 (Spearman coefficient = -0.5) and positive correlations for ANOS2P (Spearman coefficient = 0.41). In terms of RNAss, these negative correlations were even more obvious and extensive, indicating a potential negative regulation network between ANO family and tumor stemness (Fig. 5f).

Specifically, for LIHC, significant associations were recognized between ANO4 and ANOS1 expression levels and RNAss, DNAss, stromal scores, immune scores, and ESTIMATE scores (Figure S2a). As for COAD, intense associations were also observed between ANO members (ANO2, ANO3, ANO4, ANO9 and ANOS1) and tumor stemness scores and tumor purity (Figure S2b), which are consistent with the results of LIHC (Figure S2c). Consequently, ANO4 and ANOS1 were suggested to play key roles in the regulation of tumor stemness and TME.

ANO family and Drug sensitivity

Ranked by the absolute value of Pearson coefficients, drugs with sensitivity significantly correlated with ANO family expression were demonstrated (Figure S3). Notably, ANO2, ANO5, ANO8, etc., were revealed to be negatively correlated with Drug Activity Z score in drugs of Eriblin mesilate, Acrichine, Vinorelbine, etc., indicating that high expression of these ANO genes might increase drugs’ resistance against tumors. However, ANO3, ANO4, ANO7 and ANO9 were shown to have strong positive correlations with the sensitivity of Buthionine, sulphox, Vemurafenib, ABT-199, Carboplatin and Palbociclib, suggesting that elevated expression of ANO genes could augment the sensitivity of anti-tumor drugs.

PPI network and co-expression analysis

PPI network of ANO family was shown in Figure S4a, where ANO1 and ANO8 lied in the center connecting with ANO2, ANO6, ANO5, ANO9, suggesting that ANO1 and ANO8 might be of central roles in ANO family to regulate the function of other members. Additionally, co-expression analysis among ANO family revealed intense correlations between ANO4 and ANO5, ANO9 and ANO7L1, both with a Pearson coefficient of 0.35 (Figure S4b), suggesting that they are potential co-expressed gene partners.

Genetic alteration of ANO family in pan-cancer

The oncoprint illustrated genetic alteration breadth and frequency of ANO family across 33 cancer types (Figure S4c). ANO1 and ANO2 were on the top roll with a high alteration frequency of 7% and 4%, respectively, mainly missense mutation, amplification, fusion and deep deletion, indicating that they might be potential tumor driver genes to cause carcinogenesis. Nevertheless, ANO7L1 and ANOS2P both had 0% of genetic alteration, revealing that they were probably not the tumor driver genes.

Landscape of alteration in PI3K and TGF-beta signaling pathways in pan-cancer

As ANO family harbours intense dependency on PI3K and TGF-beta pathways to fulfill their function (13, 38), alteration in PI3K and TGF-beta pathways were explored, where the figure design and original data were offered by Francisco, etc. (39). Alterations in the PI3K pathway were seen in multiple cancer types where LUSC, lumA subtype of BRCA, LUAD, etc., took up the top of the list and PI3KCA served as the most frequent gene to alter in different tumors (Fig. 6a). The highest alterations in TGF-beta pathway existed in pancreatic and gastrointestinal cancers. The TGF-beta pathway, not as widely altered as the PI3K pathway, featured the variance of TGFBR2 in form of fusion and multiple alteration (Fig. 6b).

ANO family can act as exosome and exist in peripheral blood

By using Nanoparticle Tracking Analysis, we detected the presence of ANO5 exosomes (Fig. 7a). In addition, ANO5 exosomes were revealed to be high expressed in patients with COAD than normal patients (Fig. 7b). Moreover, ANO5 exosomes were shown to be high expressed in the culture of several colorectal cancer cell lines such as sw620, colo320DM, HT29, and HCT116 (Fig. 7c). This indicated that ANO5 could perform as extracellular exosomes to fulfill its function. What’s more, ANO5 exosomes were characterized to exist in the peripheral blood of COAD patient by various markers (Fig. 7d), suggesting that it could be a potential biomarker of noninvasive testing for measurement and treatment of cancer. As data from exoRBase confirmed the exosomes’ expression of ANO family in different tissues (Fig. 7d), it can be further inferred that ANO members could serve as exosomes to mediate downstream signal transduction. What’s more, the speculative structure model and mechanism diagram of ANO family were illustrated in Figure S5.

ANO family has gained growing attention for its special function of phospholipid scrambling which can generate exosomes and ectosomes to mediate cancer cell communication. But former studies only focused on a narrow process in a single cancer with common test validation. In the current study, we firstly carried out a multidimensional study to elucidate their effects on eight crucial multi-omics cancer features in TCGA pan-cancer cohort.

Our study revealed an intense correlation between ANO family and various cancers development. ANO members can serve as reliable prognostic biomarkers and promising treatment targets for several cancers. ANO5, for instance, was concurrently low expressed in COAD, THCA, and PRAD, and patients in low expressed ANO5 group showed poor survival outcomes. These results are consistent with former studies which reported that low expression of ANO5 was correlated colorectal cancer metastasis, thyroid cancer migration (17, 18, 40), and shorter OS of prostate cancer (41). It can be concluded that ANO5 can regulate cancer proliferation and metastasis in a wide range, serving as a promising target for trans-cancer treatment.

However, despite a recent study revealed that ANO5 can enhance the activity of JAK/STAT3 pathway to promote tumor proliferation (17), no study described how low expression of ANO5 promoted these cancers’ development. Interestingly, contrast to the low level of ANO5 mRNA, ANO5 exosomes were found to be quite high expressed in the culture of CRC cell lines and blood samples in our study. Given these results above, we speculate that ANO5 could mainly exist in the form of extracellular exosomes to fulfill its function: activating signaling pathway like JAK/STAT3 to promote cancer proliferation. Moreover, as other paralogs in ANO family presented the similar structure and function of secreting EVs (exosomes and ectosomes) (5), it is reasonable to believe that these ANO members can also exist in exosomes or ectosomes to mediate cell communication.

Our study also uncovered strong correlations between ANO5 and TMB, stemness, tumor purity and drug insensitivity of Alvocidib. Taking PAAD for example, ANO5 expression was found to be negatively correlated with its TMB and DNAss but positively correlated with its tumor purity. Because ANO5 was seen low expressed in PAAD tumor tissue, that means PAAD have higher mutation burden to motivate proliferation, higher stemness to maintain self-renewal and higher proportion of stromal and immune cells in TME to mediate migration. This is supported by the result of previous studies that stem cells in PAAD could promote its drug resistance (42) and TME in PAAD was able to facilitate its metastasis (43). Consequently, we proposed that ANO5 was a fundamental element in maintaining stemness and regulating TME evolution in cancers.

Another pivotal member in ANO family that needs elucidating is ANO1, one of the well-known driver genes in GIST and HNSC (44, 45). Consistently, ANO1 was found to be high expressed in HNSC in our study and patients in the high expression group possessed a worse survival outcome. Moreover, high expression of ANO1 has been reported to promote the proliferation of lung (46), gastric and ovarian(13, 38) cancer by activating EFGR/MAPK, TGF-beta and PI3K/Akt pathways, respectively. These studies, coupled with the high mutation frequency of ANO1, suggested that ANO1 extensively act as a tumor driver gene in many types of cancer. So, anti-tumor drugs targeting ANO1 seems to have potential applications in trans-cancer treatment.

ANO1, similar to ANO5, also possessed tight correlation with TMB, cancer stemness, tumor purity. In cancer of UVM, ANO1 showed a strong negative correlation with its purity but positively correlated with its DNAss. As ANO1 was high expressed in UVM, UVM had a high tumor stemness and high proportion of immune and stromal cells in TME to promote its development. This is in line with a previous study showing that tumor associated macrophage in TME was reported to promote the metastasis of UVM (47).

ANO6 is another famous ANO member for its special ability to induce cell apoptosis (22) and ferroptosis (23, 24). Consistently, high expression of ANO6 in KIRC was a protective factor in our study. But ANO6 can also act as a risk factor in variety of cancers such as LGG. A former study also claimed that ANO6 was high expressed in glioma and could promote its invasion by stimulating ERK signaling pathway (25). This dual character declared a complex regulating function of ANO6 in cancers. It might be attributed to the downstream alternative RNA splicing where a possible variant of ANO6 with reverse function was generated to facilitate cancer development.

Because ANO6 possessed a quite strong negative correlation with tumor purity of LGG, we assume that the low tumor purity of LGG is more critical to LGG’s development than the cell death effect of ANO6. That is to say: high proportion of stromal and immune cells in TME play a key role in the progression of LGG, which is consistent to a previous study(48). Simultaneously, ANO6 had a strong negative correlation with RNAss of LGG, coupled with the high expression of ANO6, this suggested LGG have a relatively low stemness, which is corresponded to its low degree of malignancy.

Other ANO members, likewise, also demonstrated broad connection with plenty of cancers (19, 49). When integrating these results together, it can be concluded that ANO family broadly participate in the proliferation, metastasis and drug resistance in a barrage of cancers. And that is realized by generating exosomes and ectosomes to mediate downstream signaling transduction; interacting with TMB, tumor stemness, stromal and immune cells in TME. ANO members can serve as reliable biomarkers for prognosis, as well as chemotherapy response, and promising targets for trans-cancer treatment, especially for tumor with a strong stemness and complex TME.

As the current study acquired cohorts from public database TCGA, the conclusion may not be applicable when extended to other patients. What’s more, given the inherent disadvantages of bioinformatics analysis, extra experimental verification was still required to further confirm these conclusions. However, despite these imperfections, the study are still the first to clarify the role of ANO family in a multi-omics dimension with preliminary test. Moreover, to deepen our knowledge about ANO family in pan-cancer field, further validation by laboratory experiments focusing on the concrete regulating network will be preformed as some previous studies did (50, 51).

Extensive and profound associations were found between ANO members and eight crucial cancer features. ANO family broadly participate in the proliferation, metastasis and drug resistance in a barrage of cancers by generating EVs to mediate cell-cell communication; interacting with TMB, tumor stemness, stromal and immune cells in TME. ANO members can serve as reliable biomarkers for prognosis, as well as therapy response, and promising targets for trans-cancer treatment, especially for tumor with a strong stemness and complex TME. Moreover, ANO members can exist in exosomes themselves to mediate downstream signaling transduction.

Ethics approval and consent to participate

Because the open accessibility of TCGA project, additional ethical permission was not acquired.

Consent for publication

Not applicable.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the TCGA program (https://portal.gdc.cancer.gov).

Competing interests

The authors declare that they have no competing interests.

Funding

This work was sponsored by the National Natural Science Foundation of China (No. 81974391, 82072806, 82173265); Leading health talents of Shanghai Municipal Health Commission (2022LJ002); Shanghai Rising-Star Program (23QC1401400); the Natural Science Foundation of Shanghai (23ZR1441300); Shanghai Municipal Commission of Health and Family Planning (20204Y0042); Hospital Funded Clinical Research, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (21XHDB06). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author Contributions

Conception/design: Yifan Liu, Bingnan Lu, Man Li, Tianyue Yang, Xu Song, Xiuwu Pan, Wang Zhou, Xingang Cui

Provision of study material: Yifan Liu, Bingnan Lu, Man Li, Mingyu Qu, Xu Song, Xiuwu Pan, Wang Zhou, Xingang Cui

Collection and/or assembly of data: Yifan Liu, Bingnan Lu, Man Li, Yuntao Yao, Xu Song, Xiuwu Pan, Wang Zhou, Xingang Cui

Manuscript writing: Yifan Liu, Bingnan Lu, Man Li, Tianyue Yang, Mingyu Qu, Yuntao Yao, Xu Song, Xiuwu Pan, Wang Zhou, Xingang Cui

Final approval of manuscript: Yifan Liu, Bingnan Lu, Man Li, Tianyue Yang, Mingyu Qu, Yuntao Yao, Xu Song, Xiuwu Pan, Wang Zhou, Xingang Cui

Acknowledgments

We thank the The Cancer Genome Atlas (TCGA) team for using their data.

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No competing interests reported.

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Exploring the diversified roles of Anoctamin Family in Pan-Cancer

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Abstract

Background

Methods

Results

Conclusions

Figures

Introduction

Materials and Methods

Data acquisition

Differential analysis for the ANO family between tumor and adjacent tissues

Survival analysis and clinical correlation of ANO family in pan-cancer

Correlation between the ANO family and TMB in pan-cancer

Correlation between tumor immune subtype and ANO family in pan-cancer

Correlation analysis between the ANO family and TME, tumor stemness scores in pan-cancer

Drug sensitivity analysis in pan-cancer

Co-expression analysis and PPI network

Genetic alteration of the ANO family in pan-cancer

Landscape of alteration in PI3K and TGF-beta pathways in pan-cancer

Detection of ANO exosome and differential analysis between tumor and normal samples

Statistics and software

Results

Differential expression of ANO family in 33 cancer types

Survival analysis and clinical correlation analysis of ANO family in pan-cancer

Correlation between ANO family and TMB in pan-cancer

Correlation between ANO family and immune subtypes

Role of ANO family in tumor microenvironment and tumor stemness

ANO family and Drug sensitivity

PPI network and co-expression analysis

Genetic alteration of ANO family in pan-cancer

Landscape of alteration in PI3K and TGF-beta signaling pathways in pan-cancer

ANO family can act as exosome and exist in peripheral blood

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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