Proteomic analysis and translational perspective of hepatocellular carcinoma: Identification of diagnostic protein biomarkers by an onco-proteogenomics approach

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

Elevated expression of ISY1, APOA-1, SYNE1, MTG1, and MMP10 at HCC initiation: HCC specific protein network involving interactions of key regulators of lipid metabolism, EGFR signaling, MAPK, and splicing pathways

Identification of molecular regulators of hepatocellular carcinoma (HCC) initiation and progression is not well understood. We chemically induced HCC in male Wistar rats by administration of diethyl nitrosamine (DEN) and 2-acetylaminofluorene (2-AFF). Using 2D-electrophoresis and MALDI-TOF-MS/MS analyses, we characterized differentially expressed proteins in liver tissues at early stage of HCC progression. Using RT-PCR analysis, we quantified the mRNA expression of the characterized proteins and validated the transcript expression with tumor tissues of clinically confirmed HCC patients. Using bioinformatic tools, we analyzed a network among the introduced proteins that identified their interacting partners and analyzed the molecular mechanisms associated with signaling pathways during HCC progression. We characterized a protein, namely, pre-mRNA splicing factor 1 homolog (ISY1), which is upregulated at both transcriptome and proteome levels at HCC initiation, progression, and tumor stages. We analyzed the interacting partners of ISY1, namely, APOA-1, SYNE1, MMP10, and MTG1. Real-time PCR analysis confirmed elevated expression of APOA-1 mRNA at HCC initiation, progression, and tumor stages in animals undergoing tumorigenesis. The mRNA expression of the interacting partners was validated with tumor tissues of clinically confirmed liver cancer patients; the analysis revealed significant elevation in expression of transcripts. The transcriptome and proteome analyses complement each other and dysregulation in mRNA and protein expression of these regulators may play critical role in HCC initiation and progression.

Circulating Biomarkers for the Early Diagnosis and Management of Hepatocellular Carcinoma with Potential Application in Resource-Limited Settings

Hepatocellular carcinoma (HCC) is among the world's third most lethal cancers. In resource-limited settings (RLS), up to 70% of HCCs are diagnosed with limited curative treatments at an advanced symptomatic stage. Even when HCC is detected early and resection surgery is offered, the post-operative recurrence rate after resection exceeds 70% in five years, of which about 50% occur within two years of surgery. There are no specific biomarkers addressing the surveillance of HCC recurrence due to the limited sensitivity of the available methods. The primary goal in the early diagnosis and management of HCC is to cure disease and improve survival, respectively. Circulating biomarkers can be used as screening, diagnostic, prognostic, and predictive biomarkers to achieve the primary goal of HCC. In this review, we highlighted key circulating blood- or urine-based HCC biomarkers and considered their potential applications in resource-limited settings, where the unmet medical needs of HCC are disproportionately highly significant.

Recent progress in molecular mechanisms of postoperative recurrence and metastasis of hepatocellular carcinoma

Hepatectomy is currently considered the most effective option for treating patients with early and intermediate hepatocellular carcinoma (HCC). Unfortunately, the postoperative prognosis of patients with HCC remains unsatisfactory, predominantly because of high postoperative metastasis and recurrence rates. Therefore, research on the molecular mechanisms of postoperative HCC metastasis and recurrence will help develop effective intervention measures to prevent or delay HCC metastasis and recurrence and to improve the long-term survival of HCC patients. Herein, we review the latest research progress on the molecular mechanisms underlying postoperative HCC metastasis and recurrence to lay a foundation for improving the understanding of HCC metastasis and recurrence and for developing more precise prevention and intervention strategies.

Molecular and genetic markers in hepatocellular carcinoma: In silico analysis to clinical validation (current limitations and future promises)

Hepatocellular carcinoma (HCC) is the second cause of cancer-related mortality. The diagnosis of HCC depends mainly on α-fetoprotein, which is limited in its diagnostic and screening capabilities. There is an urgent need for a biomarker that detects early HCC to give the patients a chance for curative treatment. New targets of therapy could enhance survival and create future alternative curative methods. In silico analysis provides both; discovery of biomarkers, and understanding of the molecular pathways, to pave the way for treatment development. This review discusses the role of in silico analysis in the discovery of biomarkers, molecular pathways, and the role the author has contributed to this area of research. It also discusses future aspirations and current limitations. A literature review was conducted on the topic using various databases (PubMed, Science Direct, and Wiley Online Library), searching in various reviews, and editorials on the topic, with overviewing the author’s own published and unpublished work. This review discussed the steps of the validation process from in silico analysis to in vivo validation, to incorporation into clinical practice guidelines. In addition, reviewing the recent lines of research of bioinformatic studies related to HCC. In conclusion, the genetic, molecular and epigenetic markers discoveries are hot areas for HCC research. Bioinformatics will enhance our ability to accomplish this understanding in the near future. We face certain limitations that we need to overcome.

Peptidomics and proteogenomics: background, challenges and future needs

INTRODUCTION

With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development.

AREAS COVERED

Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date.

EXPERT OPINION

This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

De novo sequencing of proteins by mass spectrometry

INTRODUCTION

Proteins are crucial for every cellular activity and unraveling their sequence and structure is a crucial step to fully understand their biology. Early methods of protein sequencing were mainly based on the use of enzymatic or chemical degradation of peptide chains. With the completion of the human genome project and with the expansion of the information available for each protein, various databases containing this sequence information were formed.

AREAS COVERED

De novo protein sequencing, shotgun proteomics and other mass-spectrometric techniques, along with the various software are currently available for proteogenomic analysis. Emphasis is placed on the methods for de novo sequencing, together with potential and shortcomings using databases for interpretation of protein sequence data.

EXPERT OPINION

As mass-spectrometry sequencing performance is improving with better software and hardware optimizations, combined with user-friendly interfaces, de-novo protein sequencing becomes imperative in shotgun proteomic studies. Issues regarding unknown or mutated peptide sequences, as well as, unexpected post-translational modifications (PTMs) and their identification through false discovery rate searches using the target/decoy strategy need to be addressed. Ideally, it should become integrated in standard proteomic workflows as an add-on to conventional database search engines, which then would be able to provide improved identification.

Identification of a protein signature for predicting overall survival of hepatocellular carcinoma: a study based on data mining

BACKGROUND

Hepatocellular carcinoma (HCC), is the fifth most common cancer in the world and the second most common cause of cancer-related deaths. Over 500,000 new HCC cases are diagnosed each year. Combining advanced genomic analysis with proteomic characterization not only has great potential in the discovery of useful biomarkers but also drives the development of new diagnostic methods.

METHODS

This study obtained proteomic data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and validated in The Cancer Proteome Atlas (TCPA) and TCGA dataset to identify HCC biomarkers and the dysfunctional of proteogenomics.

RESULTS

The CPTAC database contained data for 159 patients diagnosed with Hepatitis-B related HCC and 422 differentially expressed proteins (112 upregulated and 310 downregulated proteins). Restricting our analysis to the intersection in survival-related proteins between CPTAC and TCPA database revealed four coverage survival-related proteins including PCNA, MSH6, CDK1, and ASNS.

CONCLUSION

This study established a novel protein signature for HCC prognosis prediction using data retrieved from online databases. However, the signatures need to be verified using independent cohorts and functional experiments.

Early changes in the urine proteome in a rat liver tumour model

BACKGROUND

Urine, as a potential biomarker source among body fluids, can accumulate many early changes in the body due to the lack of mechanisms to maintain a homeostatic state. This study aims to detect early changes in the urinary proteome in a rat liver tumour model.

METHODS

The tumour model was established with the Walker-256 carcinosarcoma cell line (W256). Urinary proteins at days 3, 5, 7 and 11 were profiled by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Compared with controls, differential proteins were selected. Associations of differential proteins with cancer were retrieved.

RESULTS

At days 3, 5, 7 and 11, five, fifteen, eleven and twelve differential proteins were identified, respectively. Some of the differential proteins were reported to be associated with liver cancer. This differential urinary protein pattern was different from the patterns in W256 subcutaneous, lung metastasis and intracerebral tumour models.

CONCLUSIONS

This study demonstrates that (1) early changes in urinary proteins can be found in the rat liver tumour model; (2) urinary proteins can be used to differentiate the same tumour cells grown in different organs.

HKR3 regulates cell cycle through the inhibition of hTERT in hepatocellular carcinoma cell lines

Hepatocellular carcinoma is a malignant disease with improved hepatic regeneration and survival, and is activated by human telomere transferase (hTERT). hTERT is expressed during early fetal development and switched off in most adult tissues, but it becomes reactivated in HCC. The exact mechanism regulating these expression changes remains unknown during HCC progress. We evaluated the relationship between hTERT expression and human kruppel-related 3 (HKR3) and cell cycle-related factors in HCC cell lines. Following transfection for hTERT knockdown and HKR3 overexpression, proteomic and transcriptomic analyses related to hTERT were performed using liquid chromatography/mass spectrometry (LC/MS) and RNA sequencing (RNAseq) in HCC cell lines. The expression levels of hTERT, HKR3, and cell cycle-related factors were measured using western blotting, and tumor growth were evaluated via cell proliferation and cell cycle assays. Transcriptomic and proteomic analyses showed that HKR3, hTERT and cyclin-dependent kinase inhibitor 2A (CDKN2A) were correlated. Up-regulation of HKR3 expression decreased hTERT and cyclin activation and suppressed the G1/S phase of the cell cycle through CDKN2A activation. Our results suggest that HKR3 induced regulation of cell cycle through hTERT inhibition and CDKN2A activation. Our results will facilitate further exploration of the pathways regulating human telomerase activity in HCC cell lines.

Clinical multi-omics strategies for the effective cancer management

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis.

BIOLOGICAL SIGNIFICANCE

In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.

Large hepatocellular carcinoma in a non-cirrhotic liver with peritoneal and omental metastasis in a healthy man: a case report

Background

Liver cancer is the second leading cause of cancer death in men worldwide. Hepatocellular carcinoma usually develops in the setting of cirrhosis or chronic inflammation. Major risk factors for developing hepatocellular carcinoma are chronic hepatitis B or C virus infection, alcoholic cirrhosis, and nonalcoholic fatty liver disease. The most frequent locations for hepatocellular carcinoma to metastasize are the lungs, portal vein, bones, and regional lymph nodes.

Case presentation

A 41-year-old Sri Lankan man presented with progressive abdominal distension and on examination was found to have a palpable irregular mass in the left lobe of his liver with moderate ascites. His ascitic fluid was an exudate without malignant cells. An ultrasound scan and contrast-enhanced computed tomography of his abdomen showed a large contrast-enhancing lesion in the left lobe of his liver without features of cirrhosis. Laparoscopic assessment revealed peritoneal and omental deposits. Histology of the biopsies taken from the liver lesion, omental deposits, and peritoneal deposits supported a diagnosis of hepatocellular carcinoma. His liver biochemistry was normal and hepatitis serology was negative. He is abstinent from alcohol and did not have metabolic syndrome.

Conclusions

It is rare for a young patient to develop hepatocellular carcinoma with a normal liver without chronic hepatitis B or C infection, or any other risk factors. Intraperitoneal metastasis of non-ruptured hepatocellular carcinoma is also very rare. Here we report a rare case of a 41-year-old man with a large hepatocellular carcinoma in a non-cirrhotic liver without chronic hepatitis who presented with peritoneal and omental metastasis.