Identification of anti-SF3B1 autoantibody as a diagnostic marker in patients with hepatocellular carcinoma

Point-of-care testing for early-stage liver cancer diagnosis and personalized medicine: Biomarkers, current technologies and perspectives

Liver cancer is a highly prevalent and lethal form of cancer worldwide. In the absence of early diagnosis, treatment options for this disease are severely restricted. Recent advancements in genomics and bioinformatics have facilitated the discovery of a multitude of novel biomarkers that accurately depict an individual's disease diagnosis, progression, and treatment response. Leveraging these breakthroughs, personalized medicine employs an individual's biomarker profile to enable early detection of liver cancer and inform decisions regarding treatment selection, dosage determination, and prognosis assessment. The current lack of readily applicable, timely, and economically viable tools for biomarker analysis has hindered the incorporation of personalized medicine into regular clinical procedures. Over the past decade, significant advancements have been achieved in the field of molecular point-of-care testing (POCT) and amplification techniques, leading to substantial improvements in the diagnosis of liver cancer and the implementation of precision medicine. Instrument-free PCR technology or plasma PCR technology can shorten the complex procedure of in vitro detection of nucleic acid-based biomarkers. Also, compared to traditional ELISA, various nanomaterials modified with monoclonal antibodies to target proteins for recognition, capture, and detection have improved the efficiency of protein-based biomarker detection. These advances have reduced the time and cost of clinical detection of early-stage hepatocellular carcinoma and improved the efficiency of timely diagnosis and survival of suspected patients while reducing unnecessary testing costs and procedures. This review aims to provide a comprehensive overview of the current and emerging biomarkers employed in the early detection of liver cancer, as well as the advancements in point-of-care molecular testing technology and platforms. The primary objective is to assess their potential in facilitating the implementation of personalized medicine. This review ultimately revealed that the diagnosis of early-stage hepatocellular carcinoma not only requires sensitive biomarkers, but its various modifications and changes during the progression of cirrhosis to early-stage hepatocellular carcinoma will be a greater focus of our attention in the future. The rapid development of POCT has facilitated the opportunity to readily detect liver cancer in the general population in the future, and the integration of multi-pathway multiplexing and intelligent algorithms has improved the sensitivity and accuracy of early liver cancer biomarker detection. It is expected that the integration of point-of-care technology will be instrumental in the widespread adoption of personalized medicine in the foreseeable future.

hccTAAb Atlas: An Integrated Knowledge Database for Tumor-Associated Autoantibodies in Hepatocellular Carcinoma

Tumor-associated autoantibodies (TAAbs) have demonstrated potential as biomarkers for cancer detection. However, the understanding of their role in hepatocellular carcinoma (HCC) remains limited. In this study, we aimed to systematically collect and standardize information about these TAAbs and establish a comprehensive database as a platform for in-depth research. A total of 170 TAAbs were identified from published papers retrieved from PubMed, Web of Science, and Embase. Following normative reannotation, these TAAbs were referred to as 162 official symbols. The hccTAAb (tumor-associated autoantibodies in hepatocellular carcinoma) atlas was developed using the R Shiny framework and incorporating literature-based and multiomics data sets. This comprehensive online resource provides key information such as sensitivity, specificity, and additional details such as official symbols, official full names, UniProt, NCBI, HPA, neXtProt, and aliases through hyperlinks. Additionally, hccTAAb offers six analytical modules for visualizing expression profiles, survival analysis, immune infiltration, similarity analysis, DNA methylation, and DNA mutation analysis. Overall, the hccTAAb Atlas provides valuable insights into the mechanisms underlying TAAb and has the potential to enhance the diagnosis and treatment of HCC using autoantibodies. The hccTAAb Atlas is freely accessible at https://nscc.v.zzu.edu.cn/hccTAAb/.

Decoding the role of aberrant RNA alternative splicing in hepatocellular carcinoma: a comprehensive review

During eukaryotic gene expression, alternative splicing of messenger RNA precursors is critical in increasing protein diversity and regulatory complexity. Multiple transcript isoforms could be produced by alternative splicing from a single gene; they could eventually be translated into protein isoforms with deleted, added, or altered domains or produce transcripts containing premature termination codons that could be targeted by nonsense-mediated mRNA decay. Alternative splicing can generate proteins with similar, different, or even opposite functions. Increasingly strong evidence indicates that abnormal RNA splicing is a prevalent and crucial occurrence in cellular differentiation, tissue advancement, and the development and progression of cancer. Aberrant alternative splicing could affect cancer cell activities such as growth, apoptosis, invasiveness, drug resistance, angiogenesis, and metabolism. This systematic review provides a comprehensive overview of the impact of abnormal RNA alternative splicing on the development and progression of hepatocellular carcinoma.

Serum BRD2 autoantibody in hepatocellular carcinoma and its detection using mimotope peptide‑conjugated BSA

Tumor‑associated (TA) autoantibodies are considered to be promising biomarkers for the early detection of cancer, prior to the development of clinical symptoms. In the present study, a novel TA autoantibody was detected, which may prove to be useful as a diagnostic marker of human HCC using an HBx‑transgenic (HBx‑tg) hepatocellular carcinoma (HCC) mouse model. Its target antigen was identified as the bromodomain‑containing protein 2 (BRD2), a transcriptional regulator that plays a pivotal role in the transcriptional control of diverse genes. BRD2 was upregulated in HCC tissues of the H‑ras12V‑tg mouse and human subjects, as demonstrated using western blotting or immunohistochemical analysis, with the BRD2 autoantibody. In addition, the truncated BRD2 reactive to the BRD2 autoantibody was detected in tumor cell‑derived exosomes, which possibly activated TA immune responses and the generation of autoantibodies. For the detection of the serum BRD2 autoantibody, epitope mimicries of autoantigenic BRD2 were screened from a random cyclic peptide CX₇C library with the BRD2 autoantibody. A mimotope with the sequence of CTSVFLPHC, which was cyclized by one pair of cysteine residues, exhibited high affinity to the BRD2 autoantibody and competitively inhibited the binding of the autoantibody to the cellular BRD2 antigen. The use of this cyclic peptide as a capture antigen in human serum enzyme‑linked immunosorbent assay allowed the distinction of patients with HCC from healthy subjects with 64.41% sensitivity and 82.42% specificity (area under the ROC curve, 0.7761), which is superior to serum alpha‑fetoprotein (AFP; 35.83% sensitivity; 100% specificity; area under the ROC curve, 0.5337) for the diagnosis of HCC. In addition, the detection of the BRD2 autoantibody combined with other autoantibody biomarkers or AFP has increased the accuracy of HCC diagnosis, suggesting that the combinational detection of cancer biomarkers, including the BRD2 autoantibody, is a promising assay for HCC diagnosis.

RNA splicing: a dual-edged sword for hepatocellular carcinoma

RNA splicing is the fundamental process that brings diversity at the transcriptome and proteome levels. The spliceosome complex regulates minor and major processes of RNA splicing. Aberrant regulation is often associated with different diseases, including diabetes, stroke, hypertension, and cancer. In the majority of cancers, dysregulated alternative RNA splicing (ARS) events directly affect tumor progression, invasiveness, and often lead to poor survival of the patients. Alike the rest of the gastrointestinal malignancies, in hepatocellular carcinoma (HCC), which alone contributes to ~ 75% of the liver cancers, a large number of ARS events have been observed, including intron retention, exon skipping, presence of alternative 3'-splice site (3'SS), and alternative 5'-splice site (5'SS). These events are reported in spliceosome and non-spliceosome complexes genes. Molecules such as MCL1, Bcl-X, and BCL2 in different isoforms can behave as anti-apoptotic or pro-apoptotic, making the spliceosome complex a dual-edged sword. The anti-apoptotic isoforms of such molecules bring in resistance to chemotherapy or cornerstone drugs. However, in contrast, multiple malignant tumors, including HCC that target the pro-apoptotic favoring isoforms/variants favor apoptotic induction and make chemotherapy effective. Herein, we discuss different splicing events, aberrations, and antisense oligonucleotides (ASOs) in modulating RNA splicing in HCC tumorigenesis with a possible therapeutic outcome.

An Autoantigen Atlas From Human Lung HFL1 Cells Offers Clues to Neurological and Diverse Autoimmune Manifestations of COVID-19

COVID-19 is accompanied by a myriad of both transient and long-lasting autoimmune responses. Dermatan sulfate (DS), a glycosaminoglycan crucial for wound healing, has unique affinity for autoantigens (autoAgs) from apoptotic cells. DS-autoAg complexes are capable of stimulating autoreactive B cells and autoantibody production. We used DS-affinity proteomics to define the autoantigen-ome of lung fibroblasts and bioinformatics analyses to study the relationship between autoantigenic proteins and COVID-induced alterations. Using DS-affinity, we identified an autoantigen-ome of 408 proteins from human HFL1 cells, at least 231 of which are known autoAgs. Comparing with available COVID data, 352 proteins of the autoantigen-ome have thus far been found to be altered at protein or RNA levels in SARS-CoV-2 infection, 210 of which are known autoAgs. The COVID-altered proteins are significantly associated with RNA metabolism, translation, vesicles and vesicle transport, cell death, supramolecular fibrils, cytoskeleton, extracellular matrix, and interleukin signaling. They offer clues to neurological problems, fibrosis, smooth muscle dysfunction, and thrombosis. In particular, 150 altered proteins are related to the nervous system, including axon, myelin sheath, neuron projection, neuronal cell body, and olfactory bulb. An association with the melanosome is also identified. The findings from our study illustrate a connection between COVID infection and autoimmunity. The vast number of COVID-altered proteins with high intrinsic propensity to become autoAgs offers an explanation for the diverse autoimmune complications in COVID patients. The variety of autoAgs related to mRNA metabolism, translation, and vesicles suggests a need for long-term monitoring of autoimmunity in COVID. The COVID autoantigen atlas we are establishing provides a detailed molecular map for further investigation of autoimmune sequelae of the pandemic, such as "long COVID" syndrome.

Summary Sentence

An autoantigen-ome by dermatan sulfate affinity from human lung HFL1 cells may explain neurological and autoimmune manifestations of COVID-19.

Impact of Alternative Splicing Variants on Liver Cancer Biology

Simple Summary

Among the top ten deadly solid tumors are the two most frequent liver cancers, hepatocellular carcinoma, and intrahepatic cholangiocarcinoma, whose development and malignancy are favored by multifactorial conditions, which include aberrant maturation of pre-mRNA due to abnormalities in either the machinery involved in the splicing, i.e., the spliceosome and associated factors, or the nucleotide sequences of essential sites for the exon recognition process. As a consequence of cancer-associated aberrant splicing in hepatocytes- and cholangiocytes-derived cancer cells, abnormal proteins are synthesized. They contribute to the dysregulated proliferation and eventually transformation of these cells to phenotypes with enhanced invasiveness, migration, and multidrug resistance, which contributes to the poor prognosis that characterizes these liver cancers.

Abstract

The two most frequent primary cancers affecting the liver, whose incidence is growing worldwide, are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), which are among the five most lethal solid tumors with meager 5-year survival rates. The common difficulty in most cases to reach an early diagnosis, the aggressive invasiveness of both tumors, and the lack of favorable response to pharmacotherapy, either classical chemotherapy or modern targeted therapy, account for the poor outcome of these patients. Alternative splicing (AS) during pre-mRNA maturation results in changes that might affect proteins involved in different aspects of cancer biology, such as cell cycle dysregulation, cytoskeleton disorganization, migration, and adhesion, which favors carcinogenesis, tumor promotion, and progression, allowing cancer cells to escape from pharmacological treatments. Reasons accounting for cancer-associated aberrant splicing include mutations that create or disrupt splicing sites or splicing enhancers or silencers, abnormal expression of splicing factors, and impaired signaling pathways affecting the activity of the splicing machinery. Here we have reviewed the available information regarding the impact of AS on liver carcinogenesis and the development of malignant characteristics of HCC and iCCA, whose understanding is required to develop novel therapeutical approaches aimed at manipulating the phenotype of cancer cells.

A Master Autoantigen-ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases

Chronic and debilitating autoimmune sequelae pose a grave concern for the post-COVID-19 pandemic era. Based on our discovery that the glycosaminoglycan dermatan sulfate (DS) displays peculiar affinity to apoptotic cells and autoantigens (autoAgs) and that DS-autoAg complexes cooperatively stimulate autoreactive B1 cell responses, we compiled a database of 751 candidate autoAgs from six human cell types. At least 657 of these have been found to be affected by SARS-CoV-2 infection based on currently available multi-omic COVID data, and at least 400 are confirmed targets of autoantibodies in a wide array of autoimmune diseases and cancer. The autoantigen-ome is significantly associated with various processes in viral infections, such as translation, protein processing, and vesicle transport. Interestingly, the coding genes of autoAgs predominantly contain multiple exons with many possible alternative splicing variants, short transcripts, and short UTR lengths. These observations and the finding that numerous autoAgs involved in RNA-splicing showed altered expression in viral infections suggest that viruses exploit alternative splicing to reprogram host cell machinery to ensure viral replication and survival. While each cell type gives rise to a unique pool of autoAgs, 39 common autoAgs associated with cell stress and apoptosis were identified from all six cell types, with several being known markers of systemic autoimmune diseases. In particular, the common autoAg UBA1 that catalyzes the first step in ubiquitination is encoded by an X-chromosome escape gene. Given its essential function in apoptotic cell clearance and that X-inactivation escape tends to increase with aging, UBA1 dysfunction can therefore predispose aging women to autoimmune disorders. In summary, we propose a model of how viral infections lead to extensive molecular alterations and host cell death, autoimmune responses facilitated by autoAg-DS complexes, and ultimately autoimmune diseases. Overall, this master autoantigen-ome provides a molecular guide for investigating the myriad of autoimmune sequalae to COVID-19 and clues to the rare but reported adverse effects of the currently available COVID vaccines.

Immunodiagnostic Biomarkers for Hepatocellular Carcinoma (HCC): The First Step in Detection and Treatment

Hepatocellular carcinoma (HCC) exerts huge effects on the health burden of the world because of its high mortality and poor prognosis. HCC is often clinically detected late in patients. If HCC could be detected and treated earlier, the survival rate of patients will be greatly improved. Therefore, identifying specific biomarkers is urgent and important for HCC. The liver is also recognized as an immune organ. The occurrence of HCC is related to exacerbation of immune tolerance and/or immunosurveillance escape. The host immune system plays an important role in the recognition and targeting of tumor cells in cancer immunotherapy, as can be seen from the clinical success of immune checkpoint inhibitors and chimeric antigen receptor (CAR) T cells. Thus, there is a pressing medical need to discover immunodiagnostic biomarkers specific to HCC for understanding the pathological mechanisms of HCC, especially for immunotherapy targets. We have reviewed the existing literature to summarize the immunodiagnostic markers of HCC, including autoantibodies against tumor-associated antigens (TAAs) and exosomes, to provide new insights into HCC and early detection of this deadly cancer.

HCC and Tumor Biomarkers: Does One Size Fits All?

Hepatocellular carcinoma (HCC) is a highly malignant disease and early diagnosis rates remain to be unsatisfactory. Owing to this limitation, advances in treatment options including liver transplantation (LT) are limited to improve survival. Recent HCC guidelines no longer recommend alpha-fetoprotein (AFP) as a surveillance and diagnostic tool for HCC. Hence, utilization of novel biomarkers has become imperative to improve disease management strategies. Noninvasive, serum-based biomarkers are potential options to aid early diagnosis as well as prompting treatment. However, further studies are required to find out the accuracy and potential of these approaches and introduce into clinical practice.

SF3B1 mutation in pancreatic cancer contributes to aerobic glycolysis and tumor growth through a PP2A-c-Myc axis

Hot spot gene mutations in splicing factor 3b subunit 1 (SF3B1) are observed in many types of cancer and create abundant aberrant mRNA splicing, which is profoundly implicated in tumorigenesis. Here, we identified that the SF3B1 K700E (SF3B1^K700E) mutation is strongly associated with tumor growth in pancreatic ductal adenocarcinoma (PDAC). Knockdown of SF3B1 significantly retarded cell proliferation and tumor growth in a cell line (Panc05.04) with the SF3B1^K700E mutation. However, SF3B1 knockdown had no notable effect on cell proliferation in two cell lines (BxPC3 and AsPC1) carrying wild‐type SF3B1. Ectopic expression of SF3B1^K700E but not SF3B1^WT in SF3B1‐knockout Panc05.04 cells largely restored the inhibitory role induced by SF3B1 knockdown. Introduction of the SF3B1^K700E mutation in BxPC3 and AsPC1 cells also boosted cell proliferation. Gene set enrichment analysis demonstrated a close correlation between SF3B1 mutation and aerobic glycolysis. Functional analyses showed that the SF3B1^K700E mutation promoted tumor glycolysis, as evidenced by glucose consumption, lactate release, and extracellular acidification rate. Mechanistically, the SF3B1 mutation promoted the aberrant splicing of PPP2R5A and led to the activation of the glycolytic regulator c‐Myc via post‐translational regulation. Pharmacological activation of PP2A with FTY‐720 markedly compromised the growth advantage induced by the SF3B1^K700E mutation in vitro and in vivo. Taken together, our data suggest a novel function for SF3B1 mutation in the Warburg effect, and this finding may offer a potential therapeutic strategy against PDAC with the SF3B1^K700E mutation.

An autoantigen profile of human A549 lung cells reveals viral and host etiologic molecular attributes of autoimmunity in COVID-19

We aim to establish a comprehensive COVID-19 autoantigen atlas in order to understand autoimmune diseases caused by SARS-CoV-2 infection. Based on the unique affinity between dermatan sulfate and autoantigens, we identified 348 proteins from human lung A549 cells, of which 198 are known targets of autoantibodies. Comparison with current COVID data identified 291 proteins that are altered at protein or transcript level in SARS-CoV-2 infection, with 191 being known autoantigens. These known and putative autoantigens are significantly associated with viral replication and trafficking processes, including gene expression, ribonucleoprotein biogenesis, mRNA metabolism, translation, vesicle and vesicle-mediated transport, and apoptosis. They are also associated with cytoskeleton, platelet degranulation, IL-12 signaling, and smooth muscle contraction. Host proteins that interact with and that are perturbed by viral proteins are a major source of autoantigens. Orf3 induces the largest number of protein alterations, Orf9 affects the mitochondrial ribosome, and they and E, M, N, and Nsp proteins affect protein localization to membrane, immune responses, and apoptosis. Phosphorylation and ubiquitination alterations by viral infection define major molecular changes in autoantigen origination. This study provides a large list of autoantigens as well as new targets for future investigation, e.g., UBA1, UCHL1, USP7, CDK11A, PRKDC, PLD3, PSAT1, RAB1A, SLC2A1, platelet activating factor acetylhydrolase, and mitochondrial ribosomal proteins. This study illustrates how viral infection can modify host cellular proteins extensively, yield diverse autoantigens, and trigger a myriad of autoimmune sequelae. Our work provides a rich resource for studies into “long COVID” and related autoimmune sequelae.

Abdominal ultrasound and alpha-foetoprotein for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease

BACKGROUND

Hepatocellular carcinoma (HCC) occurs mostly in people with chronic liver disease and ranks sixth in terms of global instances of cancer, and fourth in terms of cancer deaths for men. Despite that abdominal ultrasound (US) is used as an initial test to exclude the presence of focal liver lesions and serum alpha-foetoprotein (AFP) measurement may raise suspicion of HCC occurrence, further testing to confirm diagnosis as well as staging of HCC is required. Current guidelines recommend surveillance programme using US, with or without AFP, to detect HCC in high-risk populations despite the lack of clear benefits on overall survival. Assessing the diagnostic accuracy of US and AFP may clarify whether the absence of benefit in surveillance programmes could be related to under-diagnosis. Therefore, assessment of the accuracy of these two tests for diagnosing HCC in people with chronic liver disease, not included in surveillance programmes, is needed.

OBJECTIVES

Primary: the diagnostic accuracy of US and AFP, alone or in combination, for the diagnosis of HCC of any size and at any stage in adults with chronic liver disease, either in a surveillance programme or in a clinical setting. Secondary: to assess the diagnostic accuracy of abdominal US and AFP, alone or in combination, for the diagnosis of resectable HCC; to compare the diagnostic accuracy of the individual tests versus the combination of both tests; to investigate sources of heterogeneity in the results.

SEARCH METHODS

We searched the Cochrane Hepato-Biliary Group Controlled Trials Register, the Cochrane Hepato-Biliary Group Diagnostic-Test-Accuracy Studies Register, Cochrane Library, MEDLINE, Embase, LILACS, Science Citation Index Expanded, until 5 June 2020. We applied no language or document-type restrictions.

SELECTION CRITERIA

Studies assessing the diagnostic accuracy of US and AFP, independently or in combination, for the diagnosis of HCC in adults with chronic liver disease, with cross-sectional and case-control designs, using one of the acceptable reference standards, such as pathology of the explanted liver, histology of resected or biopsied focal liver lesion, or typical characteristics on computed tomography, or magnetic resonance imaging, all with a six-months follow-up.

DATA COLLECTION AND ANALYSIS

We independently screened studies, extracted data, and assessed the risk of bias and applicability concerns, using the QUADAS-2 checklist. We presented the results of sensitivity and specificity, using paired forest-plots, and tabulated the results. We used a hierarchical meta-analysis model where appropriate. We presented uncertainty of the accuracy estimates using 95% confidence intervals (CIs). We double-checked all data extractions and analyses.

MAIN RESULTS

We included 373 studies. The index-test was AFP (326 studies, 144,570 participants); US (39 studies, 18,792 participants); and a combination of AFP and US (eight studies, 5454 participants). We judged at high-risk of bias all but one study. Most studies used different reference standards, often inappropriate to exclude the presence of the target condition, and the time-interval between the index test and the reference standard was rarely defined. Most studies with AFP had a case-control design. We also had major concerns for the applicability due to the characteristics of the participants. As the primary studies with AFP used different cut-offs, we performed a meta-analysis using the hierarchical-summary-receiver-operating-characteristic model, then we carried out two meta-analyses including only studies reporting the most used cut-offs: around 20 ng/mL or 200 ng/mL. AFP cut-off 20 ng/mL: for HCC (147 studies) sensitivity 60% (95% CI 58% to 62%), specificity 84% (95% CI 82% to 86%); for resectable HCC (six studies) sensitivity 65% (95% CI 62% to 68%), specificity 80% (95% CI 59% to 91%). AFP cut-off 200 ng/mL: for HCC (56 studies) sensitivity 36% (95% CI 31% to 41%), specificity 99% (95% CI 98% to 99%); for resectable HCC (two studies) one with sensitivity 4% (95% CI 0% to 19%), specificity 100% (95% CI 96% to 100%), and one with sensitivity 8% (95% CI 3% to 18%), specificity 100% (95% CI 97% to 100%). US: for HCC (39 studies) sensitivity 72% (95% CI 63% to 79%), specificity 94% (95% CI 91% to 96%); for resectable HCC (seven studies) sensitivity 53% (95% CI 38% to 67%), specificity 96% (95% CI 94% to 97%). Combination of AFP (cut-off of 20 ng/mL) and US: for HCC (six studies) sensitivity 96% (95% CI 88% to 98%), specificity 85% (95% CI 73% to 93%); for resectable HCC (two studies) one with sensitivity 89% (95% CI 73% to 97%), specificity of 83% (95% CI 76% to 88%), and one with sensitivity 79% (95% CI 54% to 94%), specificity 87% (95% CI 79% to 94%). The observed heterogeneity in the results remains mostly unexplained, and only in part referable to different cut-offs or settings (surveillance programme compared to clinical series). The sensitivity analyses, excluding studies published as abstracts, or with case-control design, showed no variation in the results. We compared the accuracy obtained from studies with AFP (cut-off around 20 ng/mL) and US: a direct comparison in 11 studies (6674 participants) showed a higher sensitivity of US (81%, 95% CI 66% to 90%) versus AFP (64%, 95% CI 56% to 71%) with similar specificity: US 92% (95% CI 83% to 97%) versus AFP 89% (95% CI 79% to 94%). A direct comparison of six studies (5044 participants) showed a higher sensitivity (96%, 95% CI 88% to 98%) of the combination of AFP and US versus US (76%, 95% CI 56% to 89%) with similar specificity: AFP and US 85% (95% CI 73% to 92%) versus US 93% (95% CI 80% to 98%).

AUTHORS' CONCLUSIONS

In the clinical pathway for the diagnosis of HCC in adults, AFP and US, singularly or in combination, have the role of triage-tests. We found that using AFP, with 20 ng/mL as a cut-off, about 40% of HCC occurrences would be missed, and with US alone, more than a quarter. The combination of the two tests showed the highest sensitivity and less than 5% of HCC occurrences would be missed with about 15% of false-positive results. The uncertainty resulting from the poor study quality and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.

An Autoantigen-ome from HS-Sultan B-Lymphoblasts Offers a Molecular Map for Investigating Autoimmune Sequelae of COVID-19

To understand how COVID-19 may induce autoimmune diseases, we have been compiling an atlas of COVID-autoantigens (autoAgs). Using dermatan sulfate (DS) affinity enrichment of autoantigenic proteins extracted from HS-Sultan lymphoblasts, we identified 362 DS-affinity proteins, of which at least 201 (56%) are confirmed autoAgs. Comparison with available multi-omic COVID data shows that 315 (87%) of the 362 proteins are affected in SARS-CoV-2 infection via altered expression, interaction with viral components, or modification by phosphorylation or ubiquitination, at least 186 (59%) of which are known autoAgs. These proteins are associated with gene expression, mRNA processing, mRNA splicing, translation, protein folding, vesicles, and chromosome organization. Numerous nuclear autoAgs were identified, including both classical ANAs and ENAs of systemic autoimmune diseases and unique autoAgs involved in the DNA replication fork, mitotic cell cycle, or telomerase maintenance. We also identified many uncommon autoAgs involved in nucleic acid and peptide biosynthesis and nucleocytoplasmic transport, such as aminoacyl-tRNA synthetases. In addition, this study found autoAgs that potentially interact with multiple SARS-CoV-2 Nsp and Orf components, including CCT/TriC chaperonin, insulin degrading enzyme, platelet-activating factor acetylhydrolase, and the ezrin-moesin-radixin family. Furthermore, B-cell-specific IgM-associated ER complex (including MBZ1, BiP, heat shock proteins, and protein disulfide-isomerases) is enriched by DS-affinity and up-regulated in B-cells of COVID-19 patients, and a similar IgH-associated ER complex was also identified in autoreactive pre-B1 cells in our previous study, which suggests a role of autoreactive B1 cells in COVID-19 that merits further investigation. In summary, this study demonstrates that virally infected cells are characterized by alterations of proteins with propensity to become autoAgs, thereby providing a possible explanation for infection-induced autoimmunity. The COVID autoantigen-ome provides a valuable molecular resource and map for investigation of COVID-related autoimmune sequelae and considerations for vaccine design.

An Autoantigen Profile of Human A549 Lung Cells Reveals Viral and Host Etiologic Molecular Attributes of Autoimmunity in COVID-19

We aim to establish a comprehensive COVID-19 autoantigen atlas in order to understand autoimmune diseases caused by SARS-CoV-2 infection. Based on the unique affinity between dermatan sulfate and autoantigens, we identified 348 proteins from human lung A549 cells, of which 198 are known targets of autoantibodies. Comparison with current COVID data identified 291 proteins that are altered at protein or transcript level in SARS-CoV-2 infection, with 191 being known autoantigens. These known and putative autoantigens are significantly associated with viral replication and trafficking processes, including gene expression, ribonucleoprotein biogenesis, mRNA metabolism, translation, vesicle and vesicle-mediated transport, and apoptosis. They are also associated with cytoskeleton, platelet degranulation, IL-12 signaling, and smooth muscle contraction. Host proteins that interact with and that are perturbed by viral proteins are a major source of autoantigens. Orf3 induces the largest number of protein alterations, Orf9 affects the mitochondrial ribosome, and they and E, M, N, and Nsp proteins affect protein localization to membrane, immune responses, and apoptosis. Phosphorylation and ubiquitination alterations by viral infection define major molecular changes in autoantigen origination. This study provides a large list of autoantigens as well as new targets for future investigation, e.g., UBA1, UCHL1, USP7, CDK11A, PRKDC, PLD3, PSAT1, RAB1A, SLC2A1, platelet activating factor acetylhydrolase, and mitochondrial ribosomal proteins. This study illustrates how viral infection can modify host cellular proteins extensively, yield diverse autoantigens, and trigger a myriad of autoimmune sequelae.

An Autoantigen Atlas from Human Lung HFL1 Cells Offers Clues to Neurological and Diverse Autoimmune Manifestations of COVID-19

COVID-19 is accompanied by a myriad of both transient and long-lasting autoimmune responses. Dermatan sulfate (DS), a glycosaminoglycan crucial for wound healing, has unique affinity for autoantigens (autoAgs) from apoptotic cells. DS-autoAg complexes are capable of stimulating autoreactive B cells and autoantibody production. Using DS affinity, we identified an autoantigenome of 408 proteins from human fetal lung fibroblast HFL11 cells, at least 231 of which are known autoAgs. Comparing with available COVID data, 352 proteins of the autoantigenome have thus far been found to be altered at protein or RNA levels in SARS-Cov-2 infection, 210 of which are known autoAgs. The COVID-altered proteins are significantly associated with RNA metabolism, translation, vesicles and vesicle transport, cell death, supramolecular fibrils, cytoskeleton, extracellular matrix, and interleukin signaling. They offer clues to neurological problems, fibrosis, smooth muscle dysfunction, and thrombosis. In particular, 150 altered proteins are related to the nervous system, including axon, myelin sheath, neuron projection, neuronal cell body, and olfactory bulb. An association with the melanosome is also identified. The findings from our study illustrate a strong connection between viral infection and autoimmunity. The vast number of COVID-altered proteins with propensity to become autoAgs offers an explanation for the diverse autoimmune complications in COVID patients. The variety of autoAgs related to mRNA metabolism, translation, and vesicles raises concerns about potential adverse effects of mRNA vaccines. The COVID autoantigen atlas we are establishing provides a detailed molecular map for further investigation of autoimmune sequelae of the pandemic.

Splicing factor SF3B1 is overexpressed and implicated in the aggressiveness and survival of hepatocellular carcinoma

Splicing alterations represent an actionable cancer hallmark. Splicing factor 3B subunit 1 (SF3B1) is a crucial splicing factor that can be targeted pharmacologically (e.g. pladienolide-B). Here, we show that SF3B1 is overexpressed (RNA/protein) in hepatocellular carcinoma (HCC) in two retrospective (n = 154 and n = 172 samples) and in five in silico cohorts (n > 900 samples, including TCGA) and that its expression is associated with tumor aggressiveness, oncogenic splicing variants expression (KLF6-SV1, BCL-XL) and decreased overall survival. In vitro, SF3B1 silencing reduced cell viability, proliferation and migration and its pharmacological blockade with pladienolide-B inhibited proliferation, migration, and formation of tumorspheres and colonies in liver cancer cell lines (HepG2, Hep3B, SNU-387), whereas its effects on normal-like hepatocyte-derived THLE-2 proliferation were negligible. Pladienolide-B also reduced the in vivo growth and the expression of tumor-markers in Hep3B-induced xenograft tumors. Moreover, SF3B1 silencing and/or blockade markedly modulated the activation of key signaling pathways (PDK1, GSK3b, ERK, JNK, AMPK) and the expression of cancer-associated genes (CDK4, CD24) and oncogenic SVs (KLF6-SV1). Therefore, the genetic and/or pharmacological inhibition of SF3B1 may represent a promising novel therapeutic strategy worth to be explored through randomized controlled trials.

Discovery and Validation of Serum Autoantibodies Against Tumor-Associated Antigens as Biomarkers in Gastric Adenocarcinoma Based on the Focused Protein Arrays

INTRODUCTION:

Previous studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC).

METHODS:

Protein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group.

RESULTS:

A panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti–serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888–0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852–0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852–0.919) in the training cohort and 0.884 (95% CI: 0.842–0.925) in the validation cohort.

DISCUSSION:

Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC.

Cyclic Peptide Mimotopes for the Detection of Serum Anti-ATIC Autoantibody Biomarker in Hepato-Cellular Carcinoma

Tumor-associated (TA) autoantibodies have been identified at the early tumor stage before developing clinical symptoms, which holds hope for early cancer diagnosis. We identified a TA autoantibody from HBx-transgenic (HBx-tg) hepatocellular carcinoma (HCC) model mouse, characterized its target antigen, and examined its relationship to human HCC. The mimotopes corresponding to the antigenic epitope of TA autoantibody were screened from a random cyclic peptide library and used for the detection of serum TA autoantibody. The target antigen of the TA autoantibody was identified as an oncogenic bi-functional purine biosynthesis protein, ATIC. It was upregulated in liver cancer tissues of HBx-tg mouse as well as human HCC tissues. Over-expressed ATIC was also secreted extracellularly via the cancer-derived exosomes, which might cause auto-immune responses. The cyclic peptide mimotope with a high affinity to anti-ATIC autoantibody, CLPSWFHRC, distinguishes between serum samples from HCC patients and healthy subjects with 70.83% sensitivity, 90.68% specificity (AUC = 0.87). However, the recombinant human ATIC protein showed a low affinity to anti-ATIC autoantibody, which may be incompatible as a capture antigen for serum TA autoantibody. This study indicates that anti-ATIC autoantibody can be a potential HCC-associated serum biomarker and suggests that autoantibody biomarker's efficiency can be improved by using antigenic mimicry to native antigens present in vivo.

A proteomic repertoire of autoantigens identified from the classic autoantibody clinical test substrate HEp-2 cells

BACKGROUND

Autoantibodies are a hallmark of autoimmune diseases. Autoantibody screening by indirect immunofluorescence staining of HEp-2 cells with patient sera is a current standard in clinical practice. Differential diagnosis of autoimmune disorders is based on commonly recognizable nuclear and cytoplasmic staining patterns. In this study, we attempted to identify as many autoantigens as possible from HEp-2 cells using a unique proteomic DS-affinity enrichment strategy.

METHODS

HEp-2 cells were cultured and lysed. Total proteins were extracted from cell lysate and fractionated with DS-Sepharose resins. Proteins were eluted with salt gradients, and fractions with low to high affinity were collected and sequenced by mass spectrometry. Literature text mining was conducted to verify the autoantigenicity of each protein. Protein interaction network and pathway analyses were performed on all identified proteins.

RESULTS

This study identified 107 proteins from fractions with low to high DS-affinity. Of these, 78 are verified autoantigens with previous reports as targets of autoantibodies, whereas 29 might be potential autoantigens yet to be verified. Among the 107 proteins, 82 can be located to nucleus and 15 to the mitotic cell cycle, which may correspond to the dominance of nuclear and mitotic staining patterns in HEp-2 test. There are 55 vesicle-associated proteins and 12 ribonucleoprotein granule proteins, which may contribute to the diverse speckled patterns in HEp-2 stains. There are also 32 proteins related to the cytoskeleton. Protein network analysis indicates that these proteins have significantly more interactions among themselves than would be expected of a random set, with the top 3 networks being mRNA metabolic process regulation, apoptosis, and DNA conformation change.

CONCLUSIONS

This study provides a proteomic repertoire of confirmed and potential autoantigens for future studies, and the findings are consistent with a mechanism for autoantigenicity: how self-molecules may form molecular complexes with DS to elicit autoimmunity. Our data contribute to the molecular etiology of autoimmunity and may deepen our understanding of autoimmune diseases.

Autoantibody signature in hepatocellular carcinoma using seromics

Background

Alpha-fetoprotein (AFP) is a widely used biomarker for hepatocellular carcinoma (HCC) early detection. However, low sensitivity and false negativity of AFP raise the requirement of more effective early diagnostic approaches for HCC.

Methods

We employed a three-phase strategy to identify serum autoantibody (AAb) signature for HCC early diagnosis using protein array-based approach. A total of 1253 serum samples from HCC, liver cirrhosis, and healthy controls were prospectively collected from three liver cancer centers in China. The Human Proteome Microarray, comprising 21,154 unique proteins, was first applied to identify AAb candidates in discovery phase (n = 100) and to further fabricate HCC-focused arrays. Then, an artificial neural network (ANN) model was used to discover AAbs for HCC detection in a test phase (n = 576) and a validation phase (n = 577), respectively.

Results

Using HCC-focused array, we identified and validated a novel 7-AAb panel containing CIAPIN1, EGFR, MAS1, SLC44A3, ASAH1, UBL7, and ZNF428 for effective HCC detection. The ANN model of this panel showed improvement of sensitivity (61.6–77.7%) compared to AFP (cutoff 400 ng/mL, 28.4–30.7%). Notably, it was able to detect AFP-negative HCC with AUC values of 0.841–0.948. For early-stage HCC (BCLC 0/A) detection, it outperformed AFP (cutoff 400 ng/mL) with approximately 10% increase in AUC.

Conclusions

The 7-AAb panel provides potentially clinical value for non-invasive early detection of HCC, and brings new clues on understanding the immune response against hepatocarcinogenesis.

The significance of m6A RNA methylation regulators in predicting the prognosis and clinical course of HBV-related hepatocellular carcinoma

Background

Hepatocarcinogenesis is reportedly correlated with abnormal m6A modifications; however, it is unknown whether m6A RNA methylation regulators facilitate the occurrence of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Thus, we constructed an m6A-related model that may enhance HBV-related HCC prognosis.

Methods

Gene signatures of HNRNPA2B1 and RBM15 were generated by univariate and Lasso Cox regression analyses using the gene set and clinical information from The Cancer Genome Atlas (TCGA) database. High-risk and low-risk groups were confirmed based on the gene signature model. Furthermore, we validated the predictive roles of the two genes for overall survival (OS) in the GSE14520 dataset. The relative expression of 22 paired mRNAs was measured using quantitative real-time polymerase chain reaction (qRT-PCR) analysis to determine whether the two genes had a predictive role in our Guilin cohort.

Results

The differences in OS between the high-risk and low-risk groups were statistically significant in the TCGA (p = 0.003) and GSE14520 (p = 0.045) datasets, but not in the Guilin cohort, owing to differences in clinical information among the three cohorts (mainly the TNM stage and survival state). Stratified analysis of TNM stages showed that the two-gene signature acted as a prognostic indicator of HBV-related HCC patients in the early TNM stage; both TCGA and GSE14520 cohorts showed statistical significance. Moreover, multivariate Cox regression analysis indicated that the two-gene signature was an independent factor for predicting prognosis (HR = 1.087, 95% CI: 1.007–1.172). Correlation analysis between the gene signature and clinical features revealed that the risk stratification was significantly correlated with grade and survival state. Finally, Gene Set Enrichment Analysis (GSEA) revealed that the KEGG pathways associated with the cell cycle, DNA replication, the spliceosome, repair, and metabolism-related processes were all significantly enriched in the high-risk group. Among the enriched genes, the expression levels of the replication protein RPA1 and the pre-mRNA splicing factor SF3B1 were significantly upregulated in the high-risk group. These results might help in elucidating the underlying molecular mechanisms of HBV-related HCC.

Conclusions

Our data may provide new predictive signatures and potential therapeutic targets to identify and treat HBV-related HCC patients in the early disease stage.

Early Diagnosis of Hepatocellular Carcinoma Using Machine Learning Method

Hepatocellular carcinoma (HCC) is a serious cancer which ranked the fourth in cancer-related death worldwide. Hence, more accurate diagnostic models are urgently needed to aid the early HCC diagnosis under clinical scenarios and thus improve HCC treatment and survival. Several conventional methods have been used for discriminating HCC from cirrhosis tissues in patients without HCC (CwoHCC). However, the recognition successful rates are still far from satisfactory. In this study, we applied a computational approach that based on machine learning method to a set of microarray data generated from 1091 HCC samples and 242 CwoHCC samples. The within-sample relative expression orderings (REOs) method was used to extract numerical descriptors from gene expression profiles datasets. After removing the unrelated features by using maximum redundancy minimum relevance (mRMR) with incremental feature selection, we achieved “11-gene-pair” which could produce outstanding results. We further investigated the discriminate capability of the “11-gene-pair” for HCC recognition on several independent datasets. The wonderful results were obtained, demonstrating that the selected gene pairs can be signature for HCC. The proposed computational model can discriminate HCC and adjacent non-cancerous tissues from CwoHCC even for minimum biopsy specimens and inaccurately sampled specimens, which can be practical and effective for aiding the early HCC diagnosis at individual level.

Knockdown of SF3B1 inhibits cell proliferation, invasion and migration triggering apoptosis in breast cancer via aberrant splicing

BACKGROUND

Splicing factor 3b subunit 1 (SF3B1) was frequently reported to be significantly mutated in breast cancer. However, the status of SF3B1 expression, its function and molecular consequence in breast cancer remained unreported.

METHODS

Immunohistochemistry was used to assess SF3B1expression in 110 breast cancer samples. SF3B1 knock‑down in ZR-75-30 and MDA-MB-231 cells was performed by shRNA transfection. The expression of SF3B1 in cells was detected by quantitative real‑time PCR and western blot. Cell proliferation ability was determined by MTT and colony formation assay. Migration and invasion were determined by transwell assay. Flow cytometry was performed to investigate cell cycle and apoptosis. RNA-sequencing was performed to examine differentially expressed genes and affected alternative splicing events.

RESULTS

SF3B1 is overexpressed in breast cancer tissues compared with normal tissues. Overexpression of SF3B1 is associated with lymph node metastasis. SF3B1 knockdown in MDA-MB-231 and ZR-75-30 breast cancer cells significantly induced the suppression of proliferation, migration, invasion and also enhancement of apoptosis. RNA-sequencing data revealed that 860 genes were significantly up-regulated and 776 genes were significantly down-regulated upon SF3B1 knockdown. Differentially expressed genes enriched in the signaling pathways including Ras signaling pathway; cytokine receptor interaction; tight junction; MAPK signaling pathway, Glycine, serine and threonine metabolism. Alternative splicing analysis revealed that exon skipping (SKIP) and cassette exons (MSKIP) were the most common molecular effect upon SF3B1 knockdown.

CONCLUSIONS

Our study suggests that SF3B1 may be an important molecular target for breast cancer treatment and provides a new clue for clinical treatment of breast cancer.

Serum anti-EIF3A autoantibody as a potential diagnostic marker for hepatocellular carcinoma

Tumor-associated autoantibodies are promising diagnostic biomarkers for early detection of tumors. We have screened a novel tumor-associated autoantibody in hepatocellular carcinoma (HCC) model mice. Its target antigen was identified as eukaryotic translation initiation factor 3 subunit A (EIF3A) by proteomic analysis, and the elevated expression of EIF3A in HCC tissues of tumor model mice as well as human patients was shown. Also, its existence in tumor-derived exosomes was revealed, which seem to be the cause of tumor-associated autoantibody production. To use serum anti-EIF3A autoantibody as biomarker, ELISA detecting anti-EIF3A autoantibody in human serum was performed using autoantibody-specific epitope. For the sensitive detection of serum autoantibodies its specific conformational epitopes were screened from the random cyclic peptide library, and a streptavidin antigen displaying anti-EIF3A autoantibody-specific epitope, XC90p2(-CPVRSGFPC-), was used as capture antigen. It distinguished patients with HCC (n = 102) from healthy controls (n = 0285) with a sensitivity of 79.4% and specificity of 83.5% (AUC = 0.87). Also, by simultaneously detecting with other HCC biomarkers, including alpha-fetoprotein, HCC diagnostic sensitivity improved from 79.4% to 85%. Collectively, we suggest that serum anti-EIF3A autoantibody is a useful biomarker for the diagnosis of HCC and the combinational detection of related biomarkers can enhance the accuracy of the cancer diagnosis.

A comprehensive autoantigen-ome of autoimmune liver diseases identified from dermatan sulfate affinity enrichment of liver tissue proteins

BACKGROUND

Autoimmune diseases result from aberrant immune attacks by the body itself. It is mysterious how autoantigens, a large cohort of seemingly unconnected molecules expressed in different parts of the body, can induce similar autoimmune responses. We have previously found that dermatan sulfate (DS) can form complexes with molecules of apoptotic cells and stimulate autoreactive CD5+ B cells to produce autoantibodies. Hence, autoantigenic molecules share a unique biochemical property in their affinity to DS. This study sought to further test this uniform principle of autoantigenicity.

RESULTS

Proteomes were extracted from freshly collected mouse livers. They were loaded onto columns packed with DS-Sepharose resins. Proteins were eluted with step gradients of increasing salt strength. Proteins that bound to DS with weak, moderate, or strong affinity were eluted with 0.4, 0.6, and 1.0 M NaCl, respectively. After desalting, trypsin digestion, and gel electrophoresis, proteins were sequenced by mass spectrometry. To validate whether these proteins have been previously identified as autoantigens, an extensive literature search was conducted using the protein name or its alternative names as keywords. Of the 41 proteins identified from the strong DS-affinity fraction, 33 (80%) were verified autoantigens. Of the 46 proteins with moderate DS-affinity, 27 (59%) were verified autoantigens. Of the 125 proteins with weak DS-affinity, 44 (35%) were known autoantigens. Strikingly, these autoantigens fell into the classical autoantibody categories of autoimmune liver diseases: ANA (anti-nuclear autoantibodies), SMA (anti-smooth muscle autoantibodies), AMA (anti-mitochondrial autoantibodies), and LKM (liver-kidney microsomal autoantigens).

CONCLUSIONS

This study of DS-affinity enrichment of liver proteins establishes a comprehensive autoantigen-ome for autoimmune liver diseases, yielding 104 verified and 108 potential autoantigens. The liver autoantigen-ome sheds light on the molecular origins of autoimmune liver diseases and further supports the notion of a unifying biochemical principle of autoantigenicity.

A repertoire of 124 potential autoantigens for autoimmune kidney diseases identified by dermatan sulfate affinity enrichment of kidney tissue proteins

Autoantigens are the molecular targets in autoimmune diseases. They are a cohort of seemingly unrelated self-molecules present in different parts of the body, yet they can trigger a similar chain of autoimmune responses such as autoantibody production. We previously reported that dermatan sulfate (DS) can bind self-molecules of dying cells to stimulate autoreactive CD5+ B cells to produce autoantibodies. The formation of autoantigen-DS complexes converts the normally non-antigenic self-molecules to none-self antigens, and thus DS-affinity represents a common underlying biochemical property for autoantigens. This study sought to apply this property to identify potential autoantigens in the kidney. Total proteins were extracted from mouse kidney tissues and loaded onto DS-Sepharose resins. Proteins without affinity were washed off the resins, whereas those with increasing DS-affinity were eluted with step gradients of increasing salt strength. Fractions with strong and moderate DS-affinity were sequenced by mass spectrometry and yielded 25 and 99 proteins, respectively. An extensive literature search was conducted to validate whether these had been previously reported as autoantigens. Of the 124 proteins, 79 were reported autoantigens, and 19 out of 25 of the strong-DS-binding ones were well-known autoantigens. Moreover, these proteins largely fell into the two most common autoantibody categories in autoimmune kidney diseases, including 40 ANA (anti-nuclear autoantibodies) and 25 GBM (glomerular basement membrane) autoantigens. In summary, this study compiles a large repertoire of potential autoantigens for autoimmune kidney diseases. This autoantigen-ome sheds light on the molecular etiology of autoimmunity and further supports our hypothesis DS-autoantigen complexes as a unifying principle of autoantigenicity.