The Role of Biomarkers in Adrenocortical Carcinoma: A Review of Current Evidence and Future Perspectives

The Role of the Gap Junction Protein Connexin in Adrenal Gland Tumorigenesis

Gap junctions (GJs) are important in the regulation of cell growth, morphology, differentiation and migration. However, recently, more attention has been paid to their role in the pathogenesis of different diseases as well as tumorigenesis, invasion and metastases. The expression pattern and possible role of connexins (Cxs), as major GJ proteins, under both physiological and pathological conditions in the adrenal gland, were evaluated in this review. The databases Web of Science, PubMed and Scopus were searched. Studies were evaluated if they provided data regarding the connexin expression pattern in the adrenal gland, despite current knowledge of this topic not being widely investigated. Connexin expression in the adrenal gland differs according to different parts of the gland and depends on ACTH release. Cx43 is the most studied connexin expressed in the adrenal gland cortex. In addition, Cx26, Cx32 and Cx50 were also investigated in the human adrenal gland. Cx50 as the most widespread connexin, along with Cx26, Cx29, Cx32, Cx36 and Cx43, has been expressed in the adrenal medulla with distinct cellular distribution. Considerable effort has recently been directed toward connexins as therapeutically targeted molecules. At present, there exist several viable strategies in the development of potential connexin-based therapeutics. The differential and hormone-dependent distribution of gap junctions within adrenal glands, the relatively large gap junction within this gland and the increase in the gap junction size and number following hormonal treatment would indicate that gap junctions play a pivotal role in cell functioning in the adrenal gland.

High Filamin a Expression in Adrenocortical Carcinomas Is Associated with a Favourable Tumour Behaviour: A European Multicentric Study

The insulin-like growth factor 2 (IGF2) promotes cell growth by overactivating the IGF system in an autocrine loop in adrenocortical carcinomas (ACCs). The cytoskeleton protein filamin A (FLNA) acts as a repressor of IGF2 mitogenic signalling in ACC cells. The aims of this study were to test FLNA expression by immunohistochemistry in 119 ACCs and 26 adrenocortical adenomas (ACAs) and to evaluate its relationship with clinicopathological features and outcome in ACCs. We found that 71.4% of ACCs did not express FLNA, whereas FLNA absence was a rare event in ACAs (15.4%, p < 0.001 vs. ACCs). In addition, the expression of FLNA was associated with a less aggressive tumour behaviour in ACCs. Indeed, the subgroup of ACCs with high FLNA showed a lower ENSAT stage, Weiss score, and S-GRAS score compared to ACCs with low FLNA expression (p < 0.05). Moreover, patients with high FLNA had a longer overall survival than those with low FLNA (p < 0.05). In conclusion, our data suggest that FLNA may represent a "protective" factor in ACCs, and the integration of FLNA immunohistochemical expression in ACC tissues along with other clinical and molecular markers could be helpful to improve diagnostic accuracy and prognosis prediction in ACCs.

Metastatic Adrenocortical Carcinoma With Chromothripsis: A Case Report and Literature Review

Metastatic adrenocortical carcinoma (ACC) often has a poor outcome, with a five-year survival of less than 25%. We report a rare case of metastatic ACC with a myxoid variant with chromothripsis. We review the histologic variants of ACC, including myxoid type, molecular drivers, and current and investigational therapies for adrenocortical carcinoma. We also discuss the mechanism of chromothripsis, chromothripsis in ACC tumorigenesis, and propose potential therapies targeting chromothripsis.

Construction of a novel clinical nomogram to predict cancer-specific survival in patients with primary malignant adrenal tumors: a large population-based retrospective study

Background

Primary malignant adrenal tumors were rare and had a poor prognosis. This investigation aimed to create a useful clinical prediction nomogram to anticipate cancer-specific survival (CSS) of patients with a primary malignant adrenal tumor.

Method

This study included 1748 patients with malignant adrenal tumor diagnoses subjects from 2000 to 2019. These subjects were allocated randomly into training (70%) and validation (30%) cohorts. Patients with adrenal tumors underwent univariate and multivariate Cox regression analyses to identify the CSS-independent predictive biomarkers. Therefore, a nomogram was created depending on those predictors, and calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to assess the calibration capacity of the nomogram, discriminative power, and clinical efficiency, respectively. Afterward, a risk system for categorizing patients with adrenal tumors was established.

Result

The univariate and multivariate Cox analysis demonstrated the CSS-independent predictive factors, including age, tumor stage, size, histological type, and surgery. As a result, a nomogram was developed using these variables. For the 3-, 5-, and 10-year CSS of this nomogram, the values of the area under the curve (AUC) of the ROC curves were 0.829, 0.827, and 0.822, respectively. Furthermore, the AUC values of the nomogram were higher than those of the individual independent prognostic components of CSS, indicating that the nomogram had stronger prognostic prediction reliability. A novel risk stratification method was created to further improve patient stratification and give clinical professionals a better reference for clinical decision-making.

Conclusion

Through the developed nomogram and risk stratification method, the CSS of patients with malignant adrenal tumors could be predicted more precisely, assisting physicians to differentiate patients better and creating personalized treatment strategies to optimize patient benefits.

The Enhanced Expression of ZWILCH Predicts Poor Survival of Adrenocortical Carcinoma Patients

Zwilch kinetochore protein (ZWILCH) plays a key role in proper cell proliferation. The upregulation of the ZWILCH gene was observed in many types of cancers, but the association of ZWILCH with adrenocortical carcinoma (ACC) was not investigated so far. The main aim of the presented study was to verify if the enhanced level of the ZWILCH gene can be used as a diagnostic marker for ACC development and progression, as well as a predictor of survival time for ACC patients. The performed analyses included investigation of the ZWILCH expression profile in tumors with publicly available TCGA (The Cancer Genome Atlas) datasets and transcriptomic data from the Gene Expression Omnibus (GEO) database, as well as, in human biological samples of normal adrenal, adrenocortical carcinoma and in commercially available tissue microarrays. The findings demonstrate statistically significant higher ZWILCH gene expression in ACC tissue in comparison with normal adrenal glands. Furthermore, there is a strong correlation between ZWILCH upregulation and tumor mitotic rate and the probability of patient survival. The enhanced ZWILCH level is also connected with the activation of genes involved in cell proliferation and the inhibition of genes related to the immune system. This work contributes to a better understanding of the role of ZWILCH as an ACC biomarker and diagnostic tool.

Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Background: The only curative option for patients with locally or locally advanced adrenocortical carcinoma is primary tumor curative sexual resection (ACC). However, overall survival remains low, with most deaths occurring within the first 2 years following surgery. The 5-year survival rate after surgery is less than 30%. As a result, more accurate prognosis-related predictive biomarkers must be investigated urgently to detect patients' disease status after surgery. Methods: Data from FerrDb were obtained to identify ferroptosis-related genes, and ACC gene expression profiles were collected from the GEO database to find differentially expressed ACC ferroptosis-related genes using differential expression analysis. The DEFGs were subjected to Gene Ontology gene enrichment analysis and KEGG signaling pathway enrichment analysis. PPI network building and predictive analysis were used to filter core genes. The expression of critical genes in ACC pathological stage and pan-cancer was then investigated. In recent years, immune-related factors, DNA repair genes, and methyltransferase genes have been employed in diagnosing and prognosis of different malignancies. Cancer cells are mutated due to DNA repair genes, and highly expressed DNA repair genes promote cancer. Dysregulation of methyltransferase genes and Immune-related factors, which are shown to be significantly expressed in numerous malignancies, also plays a crucial role in cancer. As a result, we investigated the relationship of AURKA with immunological checkpoints, DNA repair genes, and methyltransferases in pan-cancer. Result: The DEGs found in the GEO database were crossed with ferroptosis-related genes, yielding 42 differentially expressed ferroptosis-related genes. Six of these 42 genes, particularly AURKA, are linked to the prognosis of ACC. AURKA expression was significantly correlated with poor prognosis in patients with multiple cancers, and there was a significant positive correlation with Th2 cells. Furthermore, AURKA expression was positively associated with tumor immune infiltration in Lung adenocarcinoma (LUAD), Liver hepatocellular carcinoma (LIHC), Sarcoma (SARC), Esophageal carcinoma (ESCA), and Stomach adenocarcinoma (STAD), but negatively correlated with the immune score, matrix score, and calculated score in these tumors. Further investigation into the relationship between AURKA expression and immune examination gene expression revealed that AURKA could control the tumor-resistant pattern in most tumors by regulating the expression level of specific immune examination genes. Conclusion: AURKA may be an independent prognostic marker for predicting ACC patient prognosis. AURKA may play an essential role in the tumor microenvironment and tumor immunity, according to a pan-cancer analysis, and it has the potential to be a predictive biomarker for multiple cancers.

Histopathologic Features of Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is a rare and aggressive malignancy that poses challenging issues regarding the diagnostic workup. Indeed, no presurgical technique or clinical parameters can reliably distinguish between adrenal cortical adenomas, which are more frequent and have a favorable outcome, and ACC, and the final diagnosis largely relies on histopathologic analysis of the surgical specimen. However, even the pathologic assessment of malignancy in an adrenal cortical lesion is not straightforward and requires a combined evaluation of multiple histopathologic features. Starting from the Weiss score, which was developed in 1984, several histopathologic scoring systems have been designed to tackle the difficulties of ACC diagnosis. Dealing with specific histopathologic variants (eg, Liss-Weiss-Bisceglia scoring system for oncocytic ACC) or patient characteristics (eg, Wieneke index in the pediatric setting), these scores remarkably improved the diagnostic workup of ACC and its subtypes. Nevertheless, cases with misleading features or discordant correlations between pathologic findings and clinical behavior still occur. Owing to multicentric collaborative studies integrating morphologic features with ancillary immunohistochemical markers and molecular analysis, ACC has eventually emerged as a multifaceted, heterogenous malignancy, and, while innovative and promising approaches are currently being tested, the future clinical management of patients with ACC will mainly rely on personalized medicine and target-therapy protocols. At the dawn of the new Fifth World Health Organization classification of endocrine tumors, this review will tackle ACC from the pathologist's perspective, thus focusing on the main available diagnostic, prognostic, and predictive tissue-tethered features and biomarkers and providing relevant clinical and molecular correlates.

Exploratory Circular RNA Profiling in Adrenocortical Tumors

Simple Summary

The histological differential diagnosis of adrenocortical adenoma and carcinoma is difficult and requires great expertise. Measures taken towards the distinction of adrenal tumors are of paramount importance. The non-coding circular RNAs (circRNAs) were shown to be expressed in a tissue and tumor specific manner. CircRNAs are investigated as a useful adjunct to the differential diagnosis of benign and malignant tumors of several organs, but they have not been investigated in adrenocortical tumors yet. Here, we have performed circRNA profiling in adrenocortical tumors by next-generation sequencing to detect already known and de novo circRNAs. Out of the five most differentially expressed circRNAs, circPHC3 could be confirmed by TaqMan RT-qPCR to be overexpressed in carcinoma and adenoma vs. healthy tissues in an independent validation cohort.

Abstract

Differentiation of adrenocortical adenoma (ACA) and carcinoma (ACC) is often challenging even in the histological analysis. Circular RNAs (circRNAs) belonging to the group of non-coding RNAs have been implicated as relevant factors in tumorigenesis. Our aim was to explore circRNA expression profiles in adrenocortical tumors by next-generation sequencing followed by RT-qPCR validation. Archived FFPE (formalin-fixed, paraffin embedded) including 8 ACC, 8 ACA and 8 normal adrenal cortices (NAC) were used in the discovery cohort. For de novo and known circRNA expression profiling, a next-generation sequencing platform was used. CIRI2, CircExplorer2, AutoCirc bioinformatics tools were used for the discovery of circRNAs. The top five most differentially circRNAs were measured by RT-qPCR in an independent validation cohort (10 ACC, 8 ACA, 8 NAC). In silico predicted, interacting microRNAs potentially sponged by differentially expressed circRNAs were studied by individual RT-qPCR assays. We focused on overexpressed circRNAs here. Significantly differentially expressed circRNAs have been revealed between the cohorts by NGS. Only circPHC3 could be confirmed to be significantly overexpressed in ACC, ACA vs. NAC samples by RT-qPCR. We could not observe microRNA expression changes fully corresponding to our sponging hypothesis. To the best of our knowledge, our study is the first to investigate circRNAs in adrenocortical tumors. Further studies are warranted to explore their biological and diagnostic relevance.

A benchmark study of deep learning-based multi-omics data fusion methods for cancer

BACKGROUND

A fused method using a combination of multi-omics data enables a comprehensive study of complex biological processes and highlights the interrelationship of relevant biomolecules and their functions. Driven by high-throughput sequencing technologies, several promising deep learning methods have been proposed for fusing multi-omics data generated from a large number of samples.

RESULTS

In this study, 16 representative deep learning methods are comprehensively evaluated on simulated, single-cell, and cancer multi-omics datasets. For each of the datasets, two tasks are designed: classification and clustering. The classification performance is evaluated by using three benchmarking metrics including accuracy, F1 macro, and F1 weighted. Meanwhile, the clustering performance is evaluated by using four benchmarking metrics including the Jaccard index (JI), C-index, silhouette score, and Davies Bouldin score. For the cancer multi-omics datasets, the methods' strength in capturing the association of multi-omics dimensionality reduction results with survival and clinical annotations is further evaluated. The benchmarking results indicate that moGAT achieves the best classification performance. Meanwhile, efmmdVAE, efVAE, and lfmmdVAE show the most promising performance across all complementary contexts in clustering tasks.

CONCLUSIONS

Our benchmarking results not only provide a reference for biomedical researchers to choose appropriate deep learning-based multi-omics data fusion methods, but also suggest the future directions for the development of more effective multi-omics data fusion methods. The deep learning frameworks are available at https://github.com/zhenglinyi/DL-mo .

MicroRNAs and Long Non-Coding RNAs in Adrenocortical Carcinoma

Non-coding RNAs (ncRNAs) are a type of genetic material that do not encode proteins but regulate the gene expression at an epigenetic level, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). The role played by ncRNAs in many physiological and pathological processes has gained attention during the last few decades, as they might be useful in the diagnosis, treatment and management of several human disorders, including endocrine and oncological diseases. Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine cancer, still characterized by high mortality and morbidity due to both endocrine and oncological complications. Despite the rarity of this disease, recently, the role of ncRNA has been quite extensively evaluated in ACC. In order to better explore the role of the ncRNA in human ACC, this review summarizes the current knowledge on ncRNA dysregulation in ACC and its potential role in the diagnosis, treatment, and management of this tumor.

Spindle and Kinetochore-Associated Complex is Associated With Poor Prognosis in Adrenocortical Carcinoma

INTRODUCTION

The spindle and kinetochore-associated (SKA) complex, composed of three subunits (SKA1, SKA2, and SKA3), stabilizes spindle microtubule attachment to the kinetochore (KT) in the middle stage of mitosis. High expression of this complex is associated with poor prognosis for several tumors. However, the potential role of SKA complex overexpression in rare malignant diseases, such as adrenocortical carcinoma (ACC), has not been well investigated.

MATERIALS AND METHODS

In this study, we used several databases to explore the relationship between SKA subunit expression and prognosis in ACC patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) databases were used to analyze enriched pathways in ACC.

RESULTS

The results suggest that each of the three SKA subunits are overexpressed in ACC and that high expression is correlated with poor patient prognosis. Overexpression of the SKA complex is associated with the expression of organelle fission, nuclear division, and chromosome segregation pathways. Furthermore, differential expression of hub genes for proteins that interact physically or functionally with the SKA complex (CCNB2, UBE2C, BUB1B, TPX2, CCNA2, CDCA8, CCNB1, MELK, TOP2A, and KIF2C) revealed additional potential biomarkers for ACC.

CONCLUSIONS

Our findings provide additional understanding of the mechanisms of ACC and suggest an approach for biomarker discovery using publicly available resources.

[Multifactorial assessment of prognostic features of adrenocortical cancer]

OBJECTIVE

To determine the predictors of the aggressive course of adrenocortical cancer (ACC). ACC is a rare malignant neoplasm of the adrenal cortex with a variable prognosis. At present, predicting the course of the disease and clinical outcome in patients presents significant difficulties, since many aspects of the treatment of ACC have not been studied or require clarification. In particular, the prognostic value of markers that are used in clinical practice has not been fully determined.

MATERIAL AND METHODS

Histological and immunohistochemical studies of the surgical material of adrenal neoplasms were performed. The study included 73 patients with a histologically confirmed diagnosis of ACC: 51 (69.9%) women and 22 (30.1%) men aged 17 to 82 years. Cox regression model was used for survival analysis. Statistically significant factors (p<0.05) according to the results of independent regression analysis were included in the Kaplan-Meier analysis followed by pairwise comparison using the log-rank test.

RESULTS

An increased risk of recurrence is associated with the presence of pathological mitoses and excessive secretion of aldosterone, death - with stage IV according to the classification of the European Network for the Study of Adrenal Tumors (ENSAT), relapse and death - the value of mitotic activity more than 20, the Ki-67 index more than 12, the classic variant. Mitotic activity and hormonal activity were independent predictors of recurrence-free survival, mitotic activity and ENSAT stage were independent predictors of overall survival.

CONCLUSIONS

In the present work, potential predictors of the course of ACC are identified, which are available for use in routine practice. Based on the totality of clinical, morphological, immunohistochemical data used in the diagnosis of ACC, a conception of the patient's survival can be obtained.

The Diagnostic, Prognostic and Therapeutic Role of miRNAs in Adrenocortical Carcinoma: A Systematic Review

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with a dismal prognosis and a high rate of recurrence and mortality. Therapeutic options are limited. In some cases, the distinction of ACCs from benign adrenal neoplasms with the existing widely available pathological and histopathological tools is difficult. Thus, new biomarkers have been tested. We conducted a review of the recent literature on the advances of the diagnostic, prognostic and therapeutic role of miRNAs on ACC patients. More than 10 miRNAs validated by multiple studies were found to present a diagnostic and prognostic role for ACC patients, from which miR-483-5p and miR-195 were the most frequently met biomarkers. In particular, upregulation of miR-483-5p and downregulation of miR-195 were the most commonly validated molecular alterations. Unfortunately, data on the therapeutic role of miRNA are still scarce and limited mainly at the experimental level. Thus, the role of miRNA regulation in ACC remains an area of active research.

Simultaneous determination of mitotane, its metabolite, and five steroid hormones in urine samples by capillary electrophoresis using β-CD2 SDS1 complexes as hydrophobic compounds solubilizers

Mitotane is a cytotoxic drug used in the treatment of inoperable adrenocortical carcinoma, it inhibits steroidogenesis as well, and therefore monitoring the level of steroid hormones in patients treated with mitotane is a crucial point of therapy. Hence, we have developed a simple, fast, and efficient electrophoretic method combined with reverse polarity sweeping as online preconcentration technique and dispersive liquid-liquid microextraction for the simultaneous determination of mitotane, its main metabolite DDA, and five steroid hormones (progesterone, testosterone, epitestosterone, cortisol, and corticosterone) in urine samples. In addition, a new sample matrix consisting of β-CD₂ SDS₁ complexes for a high hydrophobic compounds solubilization was developed. Approach based on the application of β-cyclodextrin and SDS complex of a ratio 2:1 allowed for hydrodynamic injection into the capillary of a solution containing both mitotane and other analytes. The detection limits of the analytes for the reverse polarity sweeping-dispersive liquid-liquid microextraction method were found to be in the range of 1.5-3 ng/mL, which were approximately 1000 times lower than in the conventional hydrodynamic injection (5 s, 0.5 psi) without any preconcentration procedure. All analytes were completely resolved in less than 13 min by uncoated silica capillary with an inner diameter of 75 μm (ID) × 60 cm. Electrophoretic separation was performed in reverse polarity with a voltage of -25 kV with a background electrolyte (BGE) consisting of 100 mM SDS, 25% ACN, 25 mM phosphate buffer (pH 2.5), and 7 mM β-cyclodextrin.

Clinical management and outcomes associated with etoposide, doxorubicin, and cisplatin plus mitotane treatment in metastatic adrenocortical carcinoma: a single institute experience

BACKGROUND

Adrenocortical carcinoma (ACC) is a rare and aggressive disease that is often diagnosed at an advanced stage. There is no standard treatment for metastatic ACC; EDP-M (etoposide, doxorubicin, and cisplatin plus mitotane) is one treatment option. A randomized controlled trial (FIRM-ACT) evaluating the efficacy of EDP-M showed progression-free survival (PFS) was 5.0 months, overall survival (OS) was 14.8 months, the response rate was 19%, and adrenal insufficiency occurred in 3.4% of patients. However, the efficacy and safety of this regimen in Asia are not fully reported.

METHODS

We retrospectively analyzed 43 patients diagnosed with metastatic ACC at the National Cancer Center Hospital between 1997 and 2020. We evaluated PFS, OS, and response in 17 patients who received EDP-M as first-line therapy.

RESULTS

The median age at treatment initiation was 45 years (range 18-74). Eight patients (47%) had autonomous hormone production, including six patients with hypercortisolism. The best response of partial response and stable disease was seen in two (12%) and ten (59%) patients, respectively. The median PFS was 6.2 months [95% confidence interval (CI): 4.3-10.0]. The median OS was 15.4 months (95% CI 11.6-not reached). Three patients received only one cycle due to adverse effects associated with hypercortisolism. Grade 3/4 adverse events associated with adrenal insufficiency occurred in three (17%) cases, resulting in EDP-M discontinuation.

CONCLUSIONS

The EDP-M regimen had similar PFS to that observed in FIRM-ACT. Adrenal insufficiency was more frequent in the current study, but this could be managed with supportive endocrinological care such as cortisol replacement.

Mass Spectrometry-Based Proteomic Discovery of Prognostic Biomarkers in Adrenal Cortical Carcinoma

Simple Summary

Adrenal cortical carcinoma (ACC) is an extremely rare disease with a variable prognosis. Current prognostic markers have limitations in identifying patients with a poor prognosis and who require adjuvant therapy. We developed the prognostic biomarker candidates of ACC using mass-spectrometry-based proteomics and machine learning algorithm. We further validated them in The Cancer Genome Atlas data and performed the survival analysis according to the expression levels of each protein. In addition, HNRNPA1, the protein identified as a prognostic marker of ACC based on proteomics, was validated in the immunohistochemistry staining. The prognostic protein biomarkers of ACC found in this study are expected to help determine the appropriate treatment plan for patients.

Abstract

Adrenal cortical carcinoma (ACC) is an extremely rare disease with a variable prognosis. Current prognostic markers have limitations in identifying patients with a poor prognosis. Herein, we aimed to investigate the prognostic protein biomarkers of ACC using mass-spectrometry-based proteomics. We performed the liquid chromatography–tandem mass spectrometry (LC–MS/MS) using formalin-fixed paraffin-embedded (FFPE) tissues of 45 adrenal tumors. Then, we selected 117 differentially expressed proteins (DEPs) among tumors with different stages using the machine learning algorithm. Next, we conducted a survival analysis to assess whether the levels of DEPs were related to survival. Among 117 DEPs, HNRNPA1, C8A, CHMP6, LTBP4, SPR, NCEH1, MRPS23, POLDIP2, and WBSCR16 were significantly correlated with the survival of ACC. In age- and stage-adjusted Cox proportional hazard regression models, only HNRNPA1, LTBP4, MRPS23, POLDIP2, and WBSCR16 expression remained significant. These five proteins were also validated in TCGA data as the prognostic biomarkers. In this study, we found that HNRNPA1, LTBP4, MRPS23, POLDIP2, and WBSCR16 were protein biomarkers for predicting the prognosis of ACC.

Future Directions in Diagnosis, Prognosis and Disease Monitoring of Adrenocortical Carcinoma: Novel Non-Invasive Biomarkers

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with frequent metastatic spread and poor prognosis. The disease can occur at any age with unexpected biological behavior. Recent genome-wide studies of ACC have contributed to our understanding of the disease, but diagnosis of ACC remains a challenge, even for multidisciplinary expert teams. Patients with ACC are frequently diagnosed in advanced stages and have limited therapeutic options. Therefore, for earlier diagnosis and better clinical management of adrenocortical carcinoma, specific, sensitive, and minimal invasive markers are urgently needed. Over several decades, great efforts have been made in discovering novel and reliable diagnostic and prognostic biomarkers including microRNAs, steroid profilings, circulating tumor cells, circulating tumor DNAs and radiomics. In this review, we will summarize these novel noninvasive biomarkers and analyze their values for diagnosis, predicting prognosis, and disease monitoring. Current problems and possible future application of these non-invasive biomarkers will also be discussed.