Autoantibody Production in Cancer—The Humoral Immune Response toward Autologous Antigens in Cancer Patients

Modulator of VRAC Current 1 Is a Potential Target Antigen in Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Multiple sclerosis (MS) is a chronic immune-mediated demyelinating disease of the CNS. Highlighted by the success of B-cell-depleting therapies such as the monoclonal anti-CD20 antibodies rituximab, ocrelizumab, and ofatumumab, B cells have been shown to play a central role in the immunopathology of the disease. Yet, the target antigens of the pathogenic B-cell response in MS remain unclear.

METHODS

We combined polyclonal B-cell stimulation of peripheral blood mononuclear cells with a human proteome-wide protein microarray to identify target antigens of MS by comparing samples from 20 patients with MS with 9 age-matched and sex-matched healthy controls. Results were verified by enzyme-linked immunosorbent assay (ELISA) in 3 independent validation cohorts (N = 47 patients with MS in remission; N = 20 patients with MS during relapse; N = 25 HCs; N = 30 patients with other noninflammatory neurologic diseases; N = 9 patients with other inflammatory neurologic diseases). Experimental autoimmune encephalomyelitis (EAE) was used as an animal model to evaluate the pathogenicity of the antibodies of choice.

RESULTS

Our results corroborate the existing concept of a highly diverse autoimmune response in MS. Yet, a significantly elevated antibody response against the membrane protein modulator of VRAC current 1 (MLC1) was noted in B-cell culture supernatants and serum samples of patients with MS. Furthermore, significantly elevated titers to MLC1 were observed in the CSF of patients with neuroinflammatory diseases other than MS. Neurons and astrocytes were identified as the main cell types expressing MLC1 in the brain of a patient with MS. Injection of anti-MLC1 antibodies into mice with EAE led to strong in vivo binding to cerebral cortical neurons and to the death of 4 of the 7 injected mice.

DISCUSSION

Future studies will have to address the diagnostic and prognostic value of MLC1-specific antibodies in neuroinflammatory disorders such as MS and characterize the functional role of MLC1 expression in neurons and astrocytes.

TRIAL REGISTRATION INFORMATION

The study has been registered in the German Clinical Trials Register (study number DRKS00015528).

MAP1LC3C repression reduces CIITA- and HLA class II expression in non-small cell lung cancer

In the last decade, advancements in understanding the genetic landscape of lung squamous cell carcinoma (LUSC) have significantly impacted therapy development. Immune checkpoint inhibitors (ICI) have shown great promise, improving overall and progression-free survival in approximately 25% of the patients. However, challenges remain, such as the lack of predictive biomarkers, difficulties in patient stratification, and identifying mechanisms that cancers use to become immune-resistant ("immune-cold"). Analysis of TCGA datasets reveals reduced MAP1LC3C expression in cancer. Further analysis indicates that low MAP1LC3C is associated with reduced CIITA and HLA expression and with decreased immune cell infiltration. In tumor cells, silencing MAP1LC3C inhibits CIITA expression and suppresses HLA class II production. These findings suggest that cancer cells are selected for low MAP1LC3C expression to evade efficient immune responses.

IP-to-MS: An Unbiased Workflow for Antigen Profiling

Immunoprecipitation is among the most widely utilized methods in biomedical research, with applications that include the identification of antibody targets and associated proteins. The path to identifying these targets is not straightforward, however, and often requires the use of chemical cross-linking and/or gel electrophoresis to separate targets from an overabundance of immunoglobulin protein. Such experiments are labor intensive and often yield long lists of candidate antibody targets. Here, we describe an unbiased immunoprecipitation-to-mass spectrometry (IP-to-MS) method that relies on a novel protein tag to separate low abundance immunoprecipitated proteins from overwhelmingly abundant immunoglobulins. We demonstrate that the IP-to-MS serotyping workflow is highly reproducible and can be used for the identification of novel, patient-specific antigen targets in multiple disease states. Furthermore, we show that IP-to-MS may outperform conventional methods of antibody detection, including enzyme-linked immunosorbent assay, while also enabling patient stratification beyond what is possible with traditional approaches.

Repertoires and Tumor-Reactivity Analysis of B Cell Immunoglobulins Derived from Cancer Patients

Tumor-infiltrating B cells have emerged in recent years as key markers of patient prognosis and responsiveness to immunotherapy. Recent technical advances, such as single-cell RNA sequencing and B cell receptor immune profiling, revealed diverse subsets and the immunoglobulin landscape of B cells located within human tumors. Secreted antibodies in solid tumors exhibit multiple effector functions, with the potential to significantly impact distinct immune responses, clinical outcomes, and patient survival. Nonetheless, a few studies examine the tumor reactivity and specificity of these immunoglobulins. Here we describe our current methodology for retrieving single B cells from human primary solid tumors for single-cell RNA sequencing followed by computational analysis to identify B cell subpopulations and immunoglobulin receptor repertoires. Furthermore, we provide a technique for evaluating and quantifying the tumor-binding capabilities of expressed antibodies. This approach holds promise for future immunotherapies and enhances our understanding of their potential clinical applications.

Extracellular vesicle autoantibodies

Autoantibodies are immunoglobulin proteins produced by autoreactive B cells responding to self-antigens. Extracellular vesicles (EVs) are membranous structures released by almost all types of cells and extensively distributed in various biological fluids. Studies have indicated that EVs loaded with self-antigens not only play important roles in antigen presentation and autoantibody production but can also form functional immune complexes with autoantibodies (termed EV autoantibodies). While numerous papers have summarized the production and function of pathogenic autoantibodies in diseases, especially autoimmune diseases, reviews on EV autoantibodies are rare. In this review, we outline the existing knowledge about EVs, autoantibodies, and EV antigens, highlighting the formation of EV autoantibodies and their functions in autoimmune diseases and cancers. In conclusion, EV autoantibodies may be involved in the occurrence of disease(s) and also serve as potential non-invasive markers that could help in the diagnosis and/or prognosis of disease. Additional studies designed to define in more detail the molecular characteristics of EV autoantibodies and their contribution to disease are recommended.

Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial

Background and Objectives: Lung nodules detected by chest computed tomography (CT) often require invasive biopsies for definitive diagnosis, leading to unnecessary procedures for benign lesions. A blood-based biomarker test that predicts lung cancer risk in CT-detected nodules could help stratify patients and direct invasive diagnostics toward high-risk individuals. Methods: In this multicenter, single-blinded clinical trial, we evaluated a test measuring plasma levels of p53, anti-p53 autoantibodies, CYFRA 21-1, and anti-CYFRA 21-1 autoantibodies in patients with CT-detected lung nodules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated, and subgroup analyses by gender, age, and smoking status were performed. A total of 1132 patients who had CT-detected lung nodules, including 885 lung cancer cases and 247 benign lesions, were enrolled from two academic hospitals in South Korea. Results: The test demonstrated a sensitivity of 78.4% (95% CI: 75.7-81.1) and specificity of 93.1% (95% CI: 90.0-96.3) in predicting lung cancer in CT-detected nodules. The PPV was 97.6%, and the NPV was 54.6%. Performance was consistent across gender (sensitivity 79.3% in men and 76.8% in women) and age groups, with a specificity of 93.4% in men and 92.7% in women. Stage I lung cancer was detected with a sensitivity of 80.6%. Conclusions: The Lung Cancer test based on 9G technology presented here offers a non-invasive method for stratifying lung cancer risk in patients with CT-detected nodules. Its integration into clinical practice could reduce unnecessary interventions and foster earlier detection.

Functional evaluation of circulating anti-cancer antibodies with a 3D tumor cell growth inhibition assay

Antibodies directed against surface antigens of tumor cells are commonly found in sera of cancer patients and of oncological animal models. Polyclonal antibodies directed against various epitopes of the same antigen may be spontaneously elicited by tumor antigens or may result from the administration of specific vaccines and other immunostimulating treatments. Furthermore, after therapeutic administration of monoclonal antibodies, the antibody will be detectable in the bloodstream for several weeks. Circulating antibodies are easily detected with enzyme-linked immunosorbent assays (ELISA) and other immunometric tests which, however, cannot tell whether the antibodies are functional, i.e. whether they can significantly inhibit (or enhance) tumor growth. One possibility would be to treat conventional (i.e. bi-dimensional, 2D) tumor cell cultures with antibody-containing sera. However, in several instances, it was found that 2D cultures were poorly sensitive, even to powerful monoclonal antibodies like trastuzumab, whereas three-dimensional (3D) cultures may better reveal the tumor-inhibitory activity of circulating antibodies. We describe here a breast cancer 3D soft agar colony growth inhibition assay that was developed to quantify the tumor cell inhibitory activity of antibodies against human HER-2 elicited in mice by specific vaccines. The assay might be readily modified to analyze antibodies against different surface antigens expressed by other tumor types and also for testing of new monoclonal antibodies and nanobodies.

Emerging immunologic approaches as cancer anti-angiogenic therapies

Targeting tumor angiogenesis, the formation of new blood vessels supporting cancer growth and spread, has been an intense focus for therapy development. However, benefits from anti-angiogenic drugs like bevacizumab have been limited by resistance stemming from activation of compensatory pathways. Recent immunotherapy advances have sparked interest in novel immunologic approaches that can induce more durable vascular pruning and overcome limitations of existing angiogenesis inhibitors. This review comprehensively examines these emerging strategies, including modulating tumor-associated macrophages, therapeutic cancer vaccines, engineered nanobodies and T cells, anti-angiogenic cytokines/chemokines, and immunomodulatory drugs like thalidomide analogs. For each approach, the molecular mechanisms, preclinical/clinical data, and potential advantages over conventional drugs are discussed. Innovative therapeutic platforms like nanoparticle delivery systems are explored. Moreover, the importance of combining agents with distinct mechanisms to prevent resistance is evaluated. As tumors hijack angiogenesis for growth, harnessing the immune system's specificity to disrupt this process represents a promising anti-cancer strategy covered by this review.

Identification of autoantibodies as potential non-invasive biomarkers for intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) presents a challenging diagnosis due to its nonspecific early clinical manifestations, often resulting in late-stage detection and high mortality. Diagnosing iCCA is further complicated by its limited accuracy, often necessitating multiple invasive procedures for precise identification. Despite carbohydrate antigen 19-9 (CA19-9) having been investigated and employed for iCCA diagnosis, it demonstrates modest diagnostic performance. Consequently, the identification of novel biomarkers with improved sensitivity and specificity remains an imperative yet formidable task. Autoantibodies, as early indicators of the immune response against cancer, offer a promising avenue for enhancing diagnostic accuracy. Our study aimed to identify non-invasive blood-based autoantibody biomarkers capable of distinguishing iCCA patients from healthy individuals (CTRs). We profiled autoantibodies in 26 serum samples (16 iCCAs and 10 CTRs) using protein microarrays containing 1622 functional proteins. Leveraging machine learning techniques, we identified a signature composed of three autoantibody biomarkers (NDE1, PYCR1, and VIM) in conjunction with CA19-9 for iCCA detection. This combined signature demonstrated superior diagnostic performance with an AUC of 96.9%, outperforming CA19-9 alone (AUC: 83.8%). These results suggest the potential of autoantibody biomarkers to develop a complementary non-invasive diagnostic utility for routine iCCA screening.

Autoantibodies in cancer: a systematic review of their clinical role in the most prevalent cancers

Although blood autoantibodies were initially associated with autoimmune diseases, multiple evidence have been accumulated showing their presence in many types of cancer. This has opened their use in clinics, since cancer autoantibodies might be useful for early detection, prognosis, and monitoring of cancer patients. In this review, we discuss the different techniques available for their discovery and validation. Additionally, we discuss here in detail those autoantibody panels verified in at least two different reports that should be more likely to be specific of each of the four most incident cancers. We also report the recent developed kits for breast and lung cancer detection mostly based on autoantibodies and the identification of novel therapeutic targets because of the screening of the cancer humoral immune response. Finally, we discuss unsolved issues that still need to be addressed for the implementation of cancer autoantibodies in clinical routine for cancer diagnosis, prognosis, and/or monitoring.

Anti-PD-1 Autoantibody Predicts Survival of Patients With Hepatocellular Carcinoma Receiving Atezolizumab/Bevacizumab

Background and Aims

Methods for predicting therapeutic response to immune checkpoint inhibitors in cancer therapy are in high demand. In patients with advanced hepatocellular carcinoma (HCC), atezolizumab (anti-programmed cell death-ligand 1 [PD-L1]) and bevacizumab (anti-vascular endothelial growth factor) combination therapy (Atezo/Bev therapy) is a first-line treatment. However, no reliable biomarkers are currently available to predict its efficacy. Here, we examined serum anti-PD-1 autoantibody levels as candidate biomarkers.

Methods

We prospectively enrolled 63 patients with advanced HCC who received Atezo/Bev therapy. Serum anti-PD-1 autoantibody levels were measured before treatment using an indirect enzyme-linked immunosorbent assay. The correlation between the titers and response to therapy was statistically examined.

Results

Serum anti-PD-1 autoantibody levels were not significantly associated with the treatment response in any patient. However, when examining only patients who received the Atezo/Bev as their first-line therapy, higher anti-PD-1 autoantibody levels were significantly associated with worse overall survival rates. The titer was an independent risk factor for poor prognosis (odds ratio [OR] = 7.8, P = .013), in addition to a higher neutrophil-to-lymphocyte ratio (OR = 7.1, P = .009) and lower albumin levels (OR = 14.2, P = .003).

Conclusion

Serum anti-PD-1 autoantibody levels correlated with the overall survival rate in patients who received Atezo/Bev as first-line therapy. Serum anti-PD-1 autoantibody levels may serve as new biomarkers for predicting the efficacy of immune checkpoint inhibitors in patients with HCC.

Enhanced Lung Cancer Detection Using a Combined Ratio of Antigen-Autoantibody Immune Complexes against CYFRA 21-1 and p53

The early detection of lung cancer (LC) improves patient outcomes, but current methods have limitations. Autoantibodies against tumor-associated antigens have potential as early biomarkers. This study evaluated the 9G testTM Cancer/Lung, measuring circulating complexes of two antigen-autoantibody immune complexes (AIC) against their respective free antigens (CYFRA 21-1 and p53) for LC diagnosis. We analyzed 100 LC patients and 119 healthy controls using the 9G testTM Cancer/Lung, quantifying the levels of AICs (CYFRA 21-1-Anti-CYFRA 21-1 autoantibody immune complex (CIC) and p53-Anti-p53 autoantibody immune complex (PIC)), free antigens (CYFRA 21-1 and p53), and ratios of AICs/antigens (LC index). The levels of the CICs and PICs were significantly elevated in LC compared to the controls (p < 0.0062 and p < 0.0026), while free antigens showed no significant difference. The CIC/CYFRA 21-1 and PIC/p53 ratios were also significantly higher in LC (all, p < 0.0001). The LC index, when combining both ratios, exhibited the best diagnostic performance with an area under the curve (AUC) of 0.945, exceeding individual CICs, PICs, and free antigens (AUCs ≤ 0.887). At a cut-off of 3.60, the LC index achieved 81% sensitivity and 95% specificity for LC diagnosis. It detected early-stage (Stage I-II) LC with 87.5% sensitivity, exceeding its performance in advanced stages (72.7%). The LC index showed no significant differences based on age, gender, smoking status (former, current, or never smoker), or pack years smoked. The LC index demonstrates promising potential for early LC diagnosis, exceeding conventional free antigen markers.

Characterization of latently infected EBV+ antibody-secreting B cells isolated from ovarian tumors and malignant ascites

Introduction

Intra-tumoral B cells mediate a plethora of immune effector mechanisms with key roles in anti-tumor immunity and serve as positive prognostic indicators in a variety of solid tumor types, including epithelial ovarian cancer (EOC). Several aspects of intra-tumoral B cells remain unclear, such as their state of activation, antigenic repertoires, and capacity to mature into plasma cells.

Methods

B lymphocytes were isolated from primary EOC tissue and malignant ascites and were maintained in cell culture medium. The stably maintained cell lines were profiled with flow cytometry and B cell receptor sequencing. Secreted antibodies were tested with a human proteome array comprising more than 21,000 proteins, followed by ELISA for validation. Originating tumor samples were used for spatial profiling with chip cytometry.

Results

Antibody-secreting B lymphocytes were isolated from the ovarian tumor microenvironment (TME) of four different EOC patients. The highly clonal cell populations underwent spontaneous immortalization in vitro, were stably maintained in an antibody-secreting state, and showed presence of Epstein-Barr viral (EBV) proteins. All originating tumors had high frequency of tumor-infiltrating B cells, present as lymphoid aggregates, or tertiary lymphoid structures. The antigens recognized by three of the four cell lines are coil-coil domain containing protein 155 (CCDC155), growth factor receptor-bound protein 2 (GRB2), and pyruvate dehydrogenase phosphatase2 (PDP2), respectively. Anti-CCDC155 circulating IgG antibodies were detected in 9 of 20 (45%) of EOC patients' sera. Tissue analyses with multiparameter chip cytometry shows that the antibodies secreted by these novel human B cell lines engage their cognate antigens on tumor cells.

Discussion

These studies demonstrate that within the tumor-infiltrating lymphocyte population in EOC resides a low frequency population of antibody-secreting B cells that have been naturally exposed to EBV. Once stably maintained, these novel cell lines offer unique opportunities for future studies on intratumor B cell biology and new target antigen recognition, and for studies on EBV latency and/or viral reactivation in the TME of non-EBV related solid tumors such as the EOC.

Autoantibody-positivity before and seroconversion during treatment with anti-PD-1 is associated with immune-related adverse events in patients with melanoma

INTRODUCTION

Treatment with the immune checkpoint inhibitor anti-programmed cell death protein-1 (PD-1) often causes immune-related adverse events (irAEs). Since irAEs resemble autoimmune diseases, autoantibodies might play a role and could potentially be used to identify patients at risk. Therefore, we investigated the association between autoantibody-positivity and toxicity as well as clinical response in patients with melanoma treated with anti-PD-1.

MATERIALS AND METHODS

This two-center, retrospective study included 143 patients with melanoma treated with anti-PD-1. Toxicities grade ≥2 and recurrences/responses were captured until 6 months after treatment initiation. Autoantibody measurements were performed at baseline and 3 months after treatment initiation, including IgM-rheumatoid factor (RF), antinuclear antibodies (ANA), extractable nuclear antigen, anti-cyclic citrullinated peptide antibodies (anti-CCP2) and anti-thyroid antibodies.

RESULTS

169 irAEs were experienced by 86/143 patients (137 grades 1-2, 32 grades 3-4), the most common being thyroiditis (n=25), dermatitis (n=24), and sicca problems (n=19). Patients with autoantibodies at baseline experienced more irAEs (p=0.001), predominantly associated with anti-thyroid antibodies and thyroid dysfunction. No association was observed between any irAE and anti-CCP2, RF or ANA. In women, baseline and on-treatment anti-thyroid antibody-positivity as well as seroconversion during treatment was associated with thyroid dysfunction. In men, this association was only observed on-treatment. The presence of autoantibodies was not associated with melanoma recurrence (p=0.776) or response (p=0.597).

CONCLUSION

The presence of autoantibodies prior to anti-PD-1 therapy is associated with irAEs in patients with melanoma. Both baseline positivity and seroconversion of anti-thyroid antibodies were strongly associated with thyroid dysfunction. This association was stronger in women, with all women who were baseline positive developing thyroid dysfunction.

Autoantibodies against Endophilin A2 as a novel biomarker are beneficial to early diagnosis of breast cancer

BACKGROUND

Due to the lack of early symptoms, breast cancer is frequently overlooked, leading to distant metastases and multi-organ lesions that directly threaten patients' lives. We have identified a novel tumor marker, antibodies to endophilin A2 (EA2), to improve early diagnosis of breast cancer.

METHODS

Antibody levels of EA2 were analyzed in sera of patients with cancers of different origins and stages by indirect enzyme-linked immunosorbent assay (ELISA). Diagnostic accuracy and reference range were determined by the area under the receiver operating curve and distribution curve. The levels of EA2 antigen in sera were determined by sandwich ELISA.

RESULTS

The levels of antibodies against EA2 were higher in sera of patients with breast cancer (P < 0.0001), liver cancer (P = 0.0005), gastric cancer (P = 0.0026), and colon cancer (P = 0.0349) than those in healthy controls, but not in patients with rectal cancer (P = 0.1151), leukemia (P = 0.7508), or lung cancer (P = 0.2247). The highest diagnostic value was for breast cancer, particularly in early cases (AUC = 0.8014) and those with distant metastases (AUC = 0.7885). The titers of EA2 antibodies in sera were correlated with levels of EA2 antigen in breast cancer patients.

CONCLUSION

Antibodies to EA2 are novel blood biomarkers for early diagnosis of breast cancer that warrants further study in larger-scale cohort studies.

Anti-BIRC5 autoantibody serves as a valuable biomarker for diagnosing AFP-negative hepatocellular carcinoma

Background

Autoantibodies targeting tumor-associated antigens (TAAbs) have emerged as promising biomarkers for early cancer detection. This research aimed to assess the diagnostic capacity of anti-BIRC5 autoantibody in detecting AFP-negative hepatocellular carcinoma (ANHCC).

Methods

This research was carried out in three stages (discovery phase, validation phase, and evaluation phase) and included a total of 744 participants. Firstly, the anti-BIRC5 autoantibody was discovered using protein microarray, exhibiting a higher positive rate in ANHCC samples (ANHCCs) compared to normal control samples (NCs). Secondly, the anti-BIRC5 autoantibody was validated through enzyme-linked immunosorbent assay (ELISA) in 85 ANHCCs and 85 NCs from two clinical centers (Zhengzhou and Nanchang). Lastly, the diagnostic usefulness of the anti-BIRC5 autoantibody for hepatocellular carcinoma (HCC) was evaluated by ELISA in a cohort consisting of an additional 149 AFP-positive hepatocellular carcinoma samples (APHCCs), 95 ANHCCs and 244 NCs. The association of elevated autoantibody to high expression of BIRC5 in HCC was further explored by the database from prognosis, immune infiltration, DNA methylation, and gene mutation level.

Results

In the validation phase, the area under the ROC curve (AUC) of anti-BIRC5 autoantibody to distinguish ANHCCs from NCs in Zhengzhou and Nanchang centers was 0.733 and 0.745, respectively. In the evaluation phase, the AUCs of anti-BIRC5 autoantibody for identifying ANHCCs and HCCs from NCs were 0.738 and 0.726, respectively. Furthermore, when combined with AFP, the AUC for identifying HCCs from NCs increased to 0.914 with a sensitivity of 77.5% and specificity of 91.8%. High expression of BIRC5 gene is not only correlated with poor prognosis of HCCs, but also significantly associated with infiltration of immune cells, DNA methylation, and gene mutation.

Conclusion

The findings suggest that the anti-BIRC5 autoantibody could serve as a potential biomarker for ANHCC, in addition to its supplementary role alongside AFP in the diagnosis of HCC. Next, we can carry out specific verification and explore the function of anti-BIRC5 autoantibody in the occurrence and development of HCC.

Serum anti-CFL1, anti-EZR, and anti-CYPA autoantibody as diagnostic markers in ovarian cancer

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer.

Clinical Significance of Uncommon, Non-Clinical, and Novel Autoantibodies

Autoantibodies are a common mark of autoimmune reaction and their identification in the patients' serum, cerebrospinal fluid, or tissues is generally believed to represent diagnostic or prognostic biomarkers of autoimmune diseases or autoinflammatory conditions. Traditionally, autoantibody testing is an important part of the clinical examination of suspected patients, and in the absence of reliable T cell tests, characterization of autoantibody responses might be suitable in finding causes of specific autoimmune responses, their strength, and sometimes commencement of autoimmune disease. Autoantibodies are also useful for prognostic stratification in clinically diverse groups of patients if checked repeatedly. Antibody discoveries are continuing, with important consequences for verifying autoimmune mechanisms, diagnostic feasibility, and clinical management. Adding newly identified autoantibody-autoantigen pairs to common clinical laboratory panels should help upgrade and harmonize the identification of systemic autoimmune rheumatic disorders and other autoimmune conditions. Herein, we aim to summarize our current knowledge of uncommon and novel autoantibodies in the context of discussing their validation, diagnostic practicability, and clinical relevance. The regular updates within the field are important and well justified.

Identification of novel prognostic autoantibodies in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone via a high-throughput antigen microarray

BACKGROUND

R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first-line treatment for diffuse large B-cell lymphoma (DLBCL). However, 20%-40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand.

METHODS

Baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCLs. In the discovery phase (n = 20), a high-density antigen microarray (∼21,000 proteins) was used to expound AAb profiles. In the verification phase (n = 181), with a DLBCL-focused microarray, comparative results based on event-free survival at 24 months (EFS24) and lasso Cox regression models of progression-free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. They were further validated by enzyme-linked immunosorbent assay in validation phase 1 (n = 135) and a dynamic cohort (n = 12). In validation phase 2, a two-AAb-based risk score was established. They were further validated in an immunohistochemistry cohort (n = 55) and four independent Gene Expression Omnibus datasets (n = 1598).

RESULTS

Four AAbs (CREB1, N4BP1, UBAP2, and DEAF1) were identified that showed associations with EFS24 status (p < .05) and superior PFS and OS (p < .05). A novel risk score model based on CREB1 and N4BP1 AAbs was developed to predict PFS with areas under the curve of 0.72, 0.71, 0.76, and 0.82 at 1, 3, 5, and 7 years, respectively, in DLBCL treated with R-CHOP independent of the International Prognostic Index (IPI) and provided significant additional recurrence risk discrimination (p < .05) for the IPI. CREB1 and N4BP1 proteins and messenger RNAs were also associated with better PFS and OS (p < .05).

CONCLUSIONS

This study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the IPI in DLBCL.

Immune-Related Adverse Events Due to Cancer Immunotherapy: Immune Mechanisms and Clinical Manifestations

The landscape of cancer treatment has undergone a significant transformation with the introduction of Immune Checkpoint Inhibitors (ICIs). Patients undergoing these treatments often report prolonged clinical and radiological responses, albeit with a potential risk of developing immune-related adverse events (irAEs). Here, we reviewed and discussed the mechanisms of action of ICIs and their pivotal role in regulating the immune system to enhance the anti-tumor immune response. We scrutinized the intricate pathogenic mechanisms responsible for irAEs, arising from the evasion of self-tolerance checkpoints due to drug-induced immune modulation. We also summarized the main clinical manifestations due to irAEs categorized by organ types, detailing their incidence and associated risk factors. The occurrence of irAEs is more frequent when ICIs are combined; with neurological, cardiovascular, hematological, and rheumatic irAEs more commonly linked to PD1/PD-L1 inhibitors and cutaneous and gastrointestinal irAEs more prevalent with CTLA4 inhibitors. Due to the often-nonspecific signs and symptoms, the diagnosis of irAEs (especially for those rare ones) can be challenging. The differential with primary autoimmune disorders becomes sometimes intricate, given the clinical and pathophysiological similarities. In conclusion, considering the escalating use of ICIs, this area of research necessitates additional clinical studies and practical insights, especially the development of biomarkers for predicting immune toxicities. In addition, there is a need for heightened education for both clinicians and patients to enhance understanding and awareness.

Harnessing the potential of long non-coding RNAs in breast cancer: from etiology to treatment resistance and clinical applications

Breast cancer (BC) is the most common malignancy among women and a leading cause of cancer-related deaths of females worldwide. It is a complex and molecularly heterogeneous disease, with various subtypes that require different treatment strategies. Despite advances in high-resolution single-cell and multinomial technologies, distant metastasis and therapeutic resistance remain major challenges for BC treatment. Long non-coding RNAs (lncRNAs) are non-coding RNAs with more than 200 nucleotides in length. They act as competing endogenous RNAs (ceRNAs) to regulate post-transcriptional gene stability and modulate protein-protein, protein-DNA, and protein-RNA interactions to regulate various biological processes. Emerging evidence suggests that lncRNAs play essential roles in human cancers, including BC. In this review, we focus on the roles and mechanisms of lncRNAs in BC progression, metastasis, and treatment resistance, and discuss their potential value as therapeutic targets. Specifically, we summarize how lncRNAs are involved in the initiation and progression of BC, as well as their roles in metastasis and the development of therapeutic resistance. We also recapitulate the potential of lncRNAs as diagnostic biomarkers and discuss their potential use in personalized medicine. Finally, we provide lncRNA-based strategies to promote the prognosis of breast cancer patients in clinical settings, including the development of novel lncRNA-targeted therapies.

B cell clonality in cancer

Carcinogenesis in the process of long-term co-evolution of tumor cells and immune environment essentially becomes possible due to incorrect decisions made, remembered, and reproduced by the immune system at the level of clonal populations of antigen-specific T- and B-lymphocytes. Tumor-immunity interaction determines the nature of such errors and, consequently, delineates the possible ways of successful immunotherapeutic intervention. It is generally recognized that tumor-infiltrating B cells (TIL-B) can play both pro-tumor and anti-tumor roles. However, the exact mechanisms that determine the contribution of clonal B cell lineages with different specificities and functions remain largely unclear. This is due to the variability of cancer types, the molecular heterogeneity of tumor cells, and, to a large extent, the individual pattern of each immune response. Further progress requires detailed investigation of the functional properties and phenotypes of clonally heterogeneous B cells in relation to their antigenic specificities, which determine the functionality of both effector B lymphocytes and immunoglobulins produced in the tumor environment. Based on a real understanding of the role of clonal antigen-specific populations of B lymphocytes in the tumor microenvironment, we need to learn how to develop new methods of targeted immunotherapy, as well as adapt existing treatment options to the specific needs of different patients and patient subgroups. In this review, we will cover B cells functional diversity and their multifaceted roles in the tumor environment.

Autoantibodies, antigen-autoantibody complexes and antigens complement CA125 for early detection of ovarian cancer

BACKGROUND

Multiple antigens, autoantibodies (AAb), and antigen-autoantibody (Ag-AAb) complexes were compared for their ability to complement CA125 for early detection of ovarian cancer.

METHODS

Twenty six biomarkers were measured in a single panel of sera from women with early stage (I-II) ovarian cancers (n = 64), late stage (III-IV) ovarian cancers (186), benign pelvic masses (200) and from healthy controls (502), and then split randomly (50:50) into a training set to identify the most promising classifier and a validation set to compare its performance to CA125 alone.

RESULTS

Eight biomarkers detected ≥ 8% of early stage cases at 98% specificity. A four-biomarker panel including CA125, HE4, HE4 Ag-AAb and osteopontin detected 75% of early stage cancers in the validation set from among healthy controls compared to 62% with CA125 alone (p = 0.003) at 98% specificity. The same panel increased sensitivity for distinguishing early-stage ovarian cancers from benign pelvic masses by 25% (p = 0.0004) at 95% specificity. From 21 autoantibody candidates, 3 AAb (anti-p53, anti-CTAG1 and annt-Il-8) detected 22% of early stage ovarian cancers, potentially lengthening lead time prior to diagnosis.

CONCLUSION

A four biomarker panel achieved greater sensitivity at the same specificity for early detection of ovarian cancer than CA125 alone.

Immune-related adverse events in non-small cell lung cancer: Occurrence, mechanisms and therapeutic strategies

The emergence of immune checkpoint inhibitors (ICIs) has heralded a transformative era in the therapeutic landscape of non-small cell lung cancer (NSCLC). While ICIs have demonstrated clinical efficacy in a portion of patients with NSCLC, these treatments concurrently precipitate a spectrum of immune-related adverse events (irAEs), encompassing mild to severe manifestations, collectively posing a risk of significant organ damage. Consequently, there exists an imperative to augment our comprehension of the pathophysiological underpinnings of irAEs and to formulate more efficacious preventive and ameliorative strategies. In this comprehensive review, we delineate the clinical presentation of organ-specific irAEs in patients with NSCLC and provide an in-depth analysis of recent advancements in understanding the mechanisms driving ICI-induced toxicity. Furthermore, we discuss potential strategies and targets for ameliorating these irAEs. Ultimately, this review aims to furnish valuable insights to guide further research endeavours in the context of irAEs in NSCLC patients.

Liquid biopsy in T-cell lymphoma: biomarker detection techniques and clinical application

T-cell lymphoma is a highly invasive tumor with significant heterogeneity. Invasive tissue biopsy is the gold standard for acquiring molecular data and categorizing lymphoma patients into genetic subtypes. However, surgical intervention is unfeasible for patients who are critically ill, have unresectable tumors, or demonstrate low compliance, making tissue biopsies inaccessible to these patients. A critical need for a minimally invasive approach in T-cell lymphoma is evident, particularly in the areas of early diagnosis, prognostic monitoring, treatment response, and drug resistance. Therefore, the clinical application of liquid biopsy techniques has gained significant attention in T-cell lymphoma. Moreover, liquid biopsy requires fewer samples, exhibits good reproducibility, and enables real-time monitoring at molecular levels, thereby facilitating personalized health care. In this review, we provide a comprehensive overview of the current liquid biopsy biomarkers used for T-cell lymphoma, focusing on circulating cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), Epstein-Barr virus (EBV) DNA, antibodies, and cytokines. Additionally, we discuss their clinical application, detection methodologies, ongoing clinical trials, and the challenges faced in the field of liquid biopsy.

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/.

Unraveling the complex interplay between anti-tumor immune response and autoimmunity mediated by B cells and autoantibodies in the era of anti-checkpoint monoclonal antibody therapies

The intricate relationship between anti-tumor immunity and autoimmunity is a complex yet crucial aspect of cancer biology. Tumor microenvironment often exhibits autoimmune features, a phenomenon that involves natural autoimmunity and the induction of humoral responses against self-antigens during tumorigenesis. This induction is facilitated by the orchestration of anti-tumor immunity, particularly within organized structures like tertiary lymphoid structures (TLS). Paradoxically, a significant number of cancer patients do not manifest autoimmune features during the course of their illness, with rare instances of paraneoplastic syndromes. This discrepancy can be attributed to various immune-mediated locks, including regulatory or suppressive immune cells, anergic autoreactive lymphocytes, or induction of effector cells exhaustion due to chronic stimulation. Overcoming these locks holds the risk to induce autoimmune mechanisms during cancer progression, a phenomenon notably observed with anti-immune checkpoint therapies, in contrast to more conventional treatments like chemotherapy or radiotherapy. Therefore, the challenge arises in managing immune-related adverse events (irAEs) induced by immune checkpoint inhibitors treatment, as decoupling them from the anti-tumor activity poses a significant clinical dilemma. This review summarizes recent advances in understanding the link between B-cell driven anti-tumor responses and autoimmune reactions in cancer patients, and discusses the clinical implications of this relationship.

Association of elevated autoantibody to high expression of GNAS in hepatocellular carcinoma

Purpose

This study was based on hepatocellular carcinoma (HCC) patients of early-stage to explore the diagnostic capability and possible production causes of anti-GNAS autoantibody.

Methods

We evaluated the frequency of anti-GNAS autoantibody in sera from patients with early-stage HCC by enzyme-linked immunosorbent assay (ELISA) and the expression of GNAS protein in early-stage HCC tissues by immunohistochemistry. Western blotting (WB) and real-time polymerase chain reaction (RT-PCR) were utilized to examine the expressions of GNAS protein and mRNA in cell lines. GEO and International Cancer Genome Consortium (ICGC) databases were inquired to explore mRNA expression and mutation of GNAS in HCC tissues.

Results

The positive rates of anti-GNAS autoantibody in HCC patients at clinical stage I (78.1 %) and clinical stage II (57.1 %) were all significantly higher than that in healthy control (20 %). There was also a significant difference in GNAS protein expression between HCC and its adjacent normal liver tissues. The results from WB and RT-PCR showed a significant difference at the mRNA level but no statistical difference at the protein level between HCC and normal liver cell lines. The difference in mRNA level between HCC and adjacent normal liver tissues was verified to be significant. Furthermore, the ICGC database demonstrated a 10.6 % mutation frequency for GNAS in HCC patients.

Conclusion

The coordination of elevated anti-GNAS autoantibody, high expression of GNAS in the mRNA and protein levels in HCC, and high frequency of GNAS mutation indicates that anti-GNAS autoantibody may be used as an early indicator of HCC.

Different Genetic Signatures of Small-Cell Lung Cancer Characterize Anti-GABAB R and Anti-Hu Paraneoplastic Neurological Syndromes

OBJECTIVE

Small-cell lung cancer (SCLC) is the malignancy most frequently associated with paraneoplastic neurological syndromes (PNS) and can trigger different antibody responses against intracellular (Hu) or neuronal surface (GABAB R) antigens. Our aim was to clarify whether the genomic and transcriptomic features of SCLC are different in patients with anti-GABAB R or anti-Hu PNS compared with SCLC without PNS.

METHODS

A total of 76 SCLC tumor samples were collected: 34 anti-Hu, 14 anti-GABAB R, and 28 SCLC without PNS. The study consisted of 4 steps: (1) pathological confirmation; (2) next generation sequencing using a panel of 98 genes, including those encoding the autoantibodies targets ELAVL1-4, GABBR1-2, and KCTD16; (3) genome-wide copy number variation (CNV); and (4) whole-transcriptome RNA sequencing.

RESULTS

CNV analysis revealed that patients with anti-GABAB R PNS commonly have a gain in chromosome 5q, which contains KCTD16, whereas anti-Hu and control patients often harbor a loss. No significantly different number of mutations regarding any onconeural genes was observed. Conversely, the transcriptomic profile of SCLC was different, and the differentially expressed genes allowed effective clustering of the samples into 3 groups, reflecting the antibody-based classification, with an overexpression of KCTD16 specific to anti-GABAB R PNS. Pathway analysis revealed that tumors of patients with anti-GABAB R encephalitis were enriched in B-cell signatures, as opposed to those of patients with anti-Hu, in which T-cell- and interferon-γ-related signatures were overexpressed.

INTERPRETATION

SCLC genetic and transcriptomic features differentiate anti-GABAB R, anti-Hu, and non-PNS tumors. The role of KCTD16 appears to be pivotal in the tumor immune tolerance breakdown of anti-GABAB R PNS. ANN NEUROL 2023;94:1102-1115.

mRNA-based Vaccines Targeting the T-cell Epitope-rich Domain of Epstein Barr Virus Latent Proteins Elicit Robust Anti-Tumor Immunity in Mice

Epstein-Barr virus (EBV) is associated with various malignancies and infects >90% of the global population. EBV latent proteins are expressed in numerous EBV-associated cancers and contribute to carcinogenesis, making them critical therapeutic targets for these cancers. Thus, this study aims to develop mRNA-based therapeutic vaccines that express the T-cell-epitope-rich domain of truncated latent proteins of EBV, including truncatedlatent membrane protein 2A (Trunc-LMP2A), truncated EBV nuclear antigen 1 (Trunc-EBNA1), and Trunc-EBNA3A. The vaccines effectively activate both cellular and humoral immunity in mice and show promising results in suppressing tumor progression and improving survival time in tumor-bearing mice. Furthermore, it is observed that the truncated forms of the antigens, Trunc-LMP2A, Trunc-EBNA1, and Trunc-EBNA3A, are more effective than full-length antigens in activating antigen-specific immune responses. In summary, the findings demonstrate the effectiveness of mRNA-based therapeutic vaccines targeting the T-cell-epitope-rich domain of EBV latent proteins and providing new treatment options for EBV-associated cancers.

Autoimmune PaneLs as PrEdictors of Toxicity in Patients TReated with Immune Checkpoint InhibiTors (ALERT)

BACKGROUND

Immune-checkpoint inhibitors (ICI) can lead to immune-related adverse events (irAEs) in a significant proportion of patients. The mechanisms underlying irAEs development are mostly unknown and might involve multiple immune effectors, such as T cells, B cells and autoantibodies (AutoAb).

METHODS

We used custom autoantigen (AutoAg) microarrays to profile AutoAb related to irAEs in patients receiving ICI. Plasma was collected before and after ICI from cancer patients participating in two clinical trials (NCT03686202, NCT02644369). A one-time collection was obtained from healthy controls for comparison. Custom arrays with 162 autoAg were used to detect IgG and IgM reactivities. Differences of median fluorescent intensity (MFI) were analyzed with Wilcoxon sign rank test and Kruskal-Wallis test. MFI 500 was used as threshold to define autoAb reactivity.

RESULTS

A total of 114 patients and 14 healthy controls were included in this study. irAEs of grade (G) ≥ 2 occurred in 37/114 patients (32%). We observed a greater number of IgG and IgM reactivities in pre-ICI collections from patients versus healthy controls (62 vs 32 p < 0.001). Patients experiencing irAEs G ≥ 2 demonstrated pre-ICI IgG reactivity to a greater number of AutoAg than patients who did not develop irAEs (39 vs 33 p = 0.040). We observed post-treatment increase of IgM reactivities in subjects experiencing irAEs G ≥ 2 (29 vs 35, p = 0.021) and a decrease of IgG levels after steroids (38 vs 28, p = 0.009).

CONCLUSIONS

Overall, these results support the potential role of autoAb in irAEs etiology and evolution. A prospective study is ongoing to validate our findings (NCT04107311).

Redefining serological diagnostics with immunoaffinity proteomics

Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.

Paraneoplastic autoimmune Laminin-332 syndrome (PALS): Anti-Laminin-332 mucous membrane pemphigoid as a prototype

IMPORTANCE

Laminin-332 is an important component of the basement membrane. Recently, autoantibodies to Laminin-332 have been described in several autoimmune diseases. Many of these autoimmune diseases have a high incidence of malignancy. The importance of Laminin-332 autoantibodies and its relationship to malignancy is highlighted by using Laminin-332 Pemphigoid (LM-332Pg) as a prototype.

OBJECTIVE

To identify several autoimmune diseases that have autoantibodies to Laminin-332 present, and to determine the prevalence of malignancy in them. Using Laminin-332 Pemphigoid (LM-332Pg) as a prototype, to compare clinical profiles of LM-332Pg patients with and without cancer. By identifying the temporal detection of cancer, can the influence of autoantibodies to Laminin-332 on prognosis be determined.

EVIDENCE REVIEW

A literature search was conducted to identify autoimmune and inflammatory diseases in which autoantibodies to Laminin-332 were present. Subsequently, the rate of malignancy in these autoimmune diseases was determined. A search for publications on LM-332Pg patients to determine cancer rates and clinical outcomes to examine if a relationship can be proposed, was performed.

FINDINGS

Autoantibodies to Laminin-332 were detected in recent studies of systemic lupus erythematosus (SLE), psoriasis, bronchiolitis obliterans (BO), graft-vs-host disease (GVH), bullous pemphigoid (BP), lichen planus (LP), epidermolysis bullosa acquisita (EBA), and membranous glomerulonephropathy (MGN). A high incidence of cancer rate was reported in these autoimmune diseases including primary Sjögren's syndrome (pSS), systemic sclerosis (SS), dermatomyositis (DM), multiple sclerosis (MS), immune thrombocytopenia purpura (ITP), and rheumatoid arthritis (RA). Data analysis demonstrated that LM-332Pg patients had a higher risk of developing ovarian, uterine, lung, gastric cancers and leukemia. The incidence for breast cancer was lower, when compared with global cancer rates. Patients diagnosed with cancer after the presence of LM-332Pg had higher rates of mortality and lower rates of remission, compared to those diagnosed with cancer prior to the discovery/diagnosis of LM-332Pg. When studied, levels of Laminin-332 autoantibodies correlated with the presence or absence of malignancy.

CONCLUSIONS AND RELEVANCE

Preliminary analysis suggests that autoantibodies to Laminin-332 are present in multiple autoimmune diseases, which also have a high incidence of malignancy. Detailed analysis of available data highlights that patients who developed LM-332Pg after cancer was diagnosed, had a more favorable prognosis, compared to patients who developed cancer when LM-332Pg was previously present. Preliminary data would suggest that autoantibodies to Laminin-332 could serve as an important biomarker in certain patients, for correlation with possible incidence of malignancy.

Hydrophobicity and molecular mass-based separation method for autoantibody discovery from mammalian total cellular proteins

Serum autoantibody profiles are unique to individuals and reflect the level and history of autoimmunity and tumor immunity. The identification of autoantibody biomarkers is critical for the development of immune monitoring systems for immune-related disorders. Here, we present a practical method for large-scale autoantibody discovery using total cellular proteins from cultured mammalian cells. We found that nucleic acid-free and fully denatured water-soluble total cellular proteins from mammalian cells were superior, allowing precise separation by reversed-phase HPLC after preparing a large set of homogeneous total cellular proteins. After separating the proteins based on hydrophobicity, the fractionated samples were subjected to molecular mass analysis using conventional SDS-PAGE. The resulting two-dimensional gel electrophoresis was successfully employed for immune blotting and LC-MS/MS analysis. All procedures, including TRIzol-based total cellular protein extraction, solubilization of denatured proteins, reversed-phase HPLC separation, and SDS-PAGE, were highly reproducible and easily scalable. We propose this novel two-dimensional gel electrophoresis system as an alternative proteomics-based methodology suitable for large-scale autoantibody discovery.

Serum autoantibody profiling of oral squamous cell carcinoma patients reveals NUBP2 as a potential diagnostic marker

Introduction

Oral Squamous Cell Carcinoma (OSCC), a common malignancy of the head and neck region, is frequently diagnosed at advanced stages, necessitating the development of efficient diagnostic methods. Profiling autoantibodies generated against tumor-associated antigens have lately demonstrated a promising role in diagnosis, predicting disease course, and response to therapeutics and relapse.

Methods

In the current study, we, for the first time, aimed to identify and evaluate the diagnostic value of autoantibodies in serum samples of patients with OSCC using autoantibody profiling by an immunome protein array. The utility of anti-NUBP2 antibody and tissue positivity in OSCC was further evaluated.

Results and discussion

We identified a total of 53 autoantibodies with significant differential levels between OSCC and control groups, including 25 that were increased in OSCC and 28 that were decreased. These included autoantibodies against Thymidine kinase 1 (TK1), nucleotide-binding protein 2 (NUBP2), and protein pyrroline-5-carboxylate reductase 1 (PYCR1), among others. Immunohistochemical validation indicated positive staining of NUBP2 in a large majority of cases (72%). Further, analysis of OSCC data available in TCGA revealed higher NUBP2 expression correlated with better disease-free patient survival. In conclusion, the differential serum autoantibodies identified in the current study, including those for NUBP2, could be used as potential biomarkers for early diagnosis or as screening biomarkers for OSCC pending investigation in a larger cohort.

The Usefulness of the Ratio of Antigen-Autoantibody Immune Complexes to Their Free Antigens in the Diagnosis of Non-Small Cell Lung Cancer

Autoantibodies against specific lung cancer-associated antigens have been suggested for the performance of lung cancer diagnosis. This study aimed to evaluate the diagnostic performance of the antigen-autoantibody immune complex (AIC) against its free antigens for CYFRA21-1, ProGRP, neutrophil gelatinase-associated lipocalin (NGAL), and neuron-specific enolase (NSE) in non-small cell lung cancer (NSCLC). In total, 85 patients with NSCLC and 120 healthy controls (HCs) were examined using a 9-guanine DNA chip method. The ratios of AICs to their antigens and the combinations of ratios consisting of two to four markers were calculated. The levels of AICs for CYFRA21-1, ProGRP, NGAL, and NSE were higher than those for their free antigens in all participants. The levels of each free antigens distinguished patients with NSCLC from the HCs. The ratios of the AIC to its antigen and seven combinations of two to four ratios were significantly higher in patients with NSCLC than in the HCs. Excellent diagnostic performance was observed for all combination ratios (C4-1), with 85.9% sensitivity and 86.7% specificity at a 3.51 cut-off. Higher sensitivity was observed in the early stages (0-I) and adenocarcinoma than in stages II-IV and other pathological types. Combining all ratios of AICs and their antigens for all four markers was useful when diagnosing NSCLC.

The presence of autoantibodies is associated with improved overall survival in lung cancer patients

Objective

Autoantibodies have been reported to be associated with cancers. As a biomarker, autoantibodies have been widely used in the early screening of lung cancer. However, the correlation between autoantibodies and the prognosis of lung cancer patients is poorly understood, especially in the Asian population. This retrospective study investigated the association between the presence of autoantibodies and outcomes in patients with lung cancer.

Methods

A total of 264 patients diagnosed with lung cancer were tested for autoantibodies in Henan Provincial People's Hospital from January 2017 to June 2022. The general clinical data of these patients were collected, and after screening out those who met the exclusion criteria, 151 patients were finally included in the study. The Cox proportional hazards model was used to analyze the effect of autoantibodies on the outcomes of patients with lung cancer. The Kaplan-Meier curve was used to analyze the relationship between autoantibodies and the overall survival of patients with lung cancer.

Results

Compared to lung cancer patients without autoantibodies, those with autoantibodies had an associated reduced risk of death (HRs: 0.45, 95% CIs 0.27~0.77), independent of gender, age, smoking history, pathological type, and pathological stage of lung cancer. Additionally, the association was found to be more significant by subgroup analysis in male patients, younger patients, and patients with small cell lung cancer. Furthermore, lung cancer patients with autoantibodies had significantly longer survival time than those without autoantibodies.

Conclusion

The presence of autoantibodies is an independent indicator of good prognosis in patients with lung cancer, providing a new biomarker for prognostic evaluation in patients with lung cancer.

Identification and evaluation of novel serum autoantibody biomarkers for early diagnosis of gastric cancer and precancerous lesion

PURPOSE

Early diagnosis is crucial for optimal prognosis of gastric cancer (GC). Hereby, we aimed to identify novel serum autoantibody-based biomarkers for precancerous lesion (PL) and early GC.

METHODS

We performed serological proteome analysis (SERPA) combined with nanoliter-liquid chromatography combined with quadrupole time of flight tandem mass spectrometry (Nano-LC-Q-TOF-MS/MS) to screen for GC-associated autoantibodies. The identified autoantibodies were analyzed for potential detection value for PL and GC by enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic (ROC) curves analysis was conducted to evaluate the accuracy of the biomarkers.

RESULTS

We identified seven candidates, such as mRNA export factor (RAE1), Nucleophosmin 1 (NPM1), phosphoglycerate kinase 1 (PGK1), and ADP-ribosylation factor 4 (ARF4). Antibodies against all seven proteins were present at higher levels in sera from 242 patients (51 PL, 78 early GC, 113 advanced GC) compared with sera from 122 healthy individuals. RAE1-specific autoantibody discriminated best between patients at different GC stages, with area under the curve (AUC) values of 0.710, 0.745, and 0.804 for PL, early GC, and advanced GC, respectively. Two predictive models composed of gender, RAE1, PGK1, NPM1, and ARF4 autoantibodies (Model 2 for PL) and of age, gender, RAE1, PGK1, and NPM1 autoantibodies (Model 3 for early GC) had improved diagnostic efficiencies, with AUCs of 0.803 and 0.857, sensitivities of 66.7% and 75.6%, and specificities of 78.7% and 87.7%, respectively.

CONCLUSION

The identified serum tumor-associated autoantibodies (TAAbs) may have good potential for early detection of GC and PL.

Systemic immune parameters after prior radiation therapy in patients receiving immune checkpoint inhibitors

INTRODUCTION

Preclinical studies have demonstrated the ability of radiation therapy (RT) to augment immune response and tumor control by immune checkpoint inhibitors (ICI). However, numerous clinical trials combining RT and ICI have yielded relatively disappointing results. To improve understanding of optimal use of these therapies, we assessed systemic immune effects of prior RT in patients receiving ICI.

METHODS AND MATERIALS

Pre- and post-ICI blood samples were collected from patients enrolled in a prospective immunotherapy biospecimen protocol. Mutiplex panels of 40 cytokines and 120 autoantibodies (Ab) were analyzed. We identified differences in these parameters according to receipt, timing, and type of prior RT. We calculated P values using the Pearson product-moment correlation coefficient and false discovery rate (FDR) using the Benjamini-Hochberg Procedure.

RESULTS

Among 277 total patients, 69 (25%) received RT in the 6 months prior to ICI initiation. Among RT-treated patients, 23 (33%) received stereotactic RT, and 33 (48%) received curative intent RT. There was no significant difference in demographics or type of immunotherapy between patients according to prior RT exposure. Baseline complement C8 Ab and MIP-1d/CCL15 were significantly higher among patients with prior RT. For MIP-1d/CCL15, only prior stereotactic RT was associated with significant differences.

CONCLUSIONS

Prior RT is associated with few changes in systemic immune parameters in patients receiving ICI. The underlying mechanisms and optimal approach to harnessing the potential synergy of RT and ICI require further prospective clinical investigation.

Human Autoantigen Atlas: Searching for the Hallmarks of Autoantigens

Understanding autoimmunity to endogenous proteins is crucial in diagnosing and treating autoimmune diseases. In this work, we developed a user-friendly AAgAtlas portal (http://biokb.ncpsb.org.cn/aagatlas_portal/index.php#), which can be used to search for 8045 non-redundant autoantigens (AAgs) and 47 post-translationally modified AAgs against 1073 human diseases that are prioritized by a credential score developed by multisource evidence. Using AAgAtlas, the immunogenic properties of human AAgs was systematically elucidated according to their genetic, biophysical, cytological, expression profile, and evolutionary characteristics. The results indicated that human AAgs are evolutionally conserved in protein sequence and enriched in three hydrophilic and polar amino acid residues (K, D, and E) that are located at the protein surface. AAgs are enriched in proteins that are involved in nucleic acid binding, transferase, and the cytoskeleton. Genome, transcriptome, and proteome analyses further indicated that AAb production is associated with gene variance and abnormal protein expression related to the pathological activities of different tumors. Collectively, our data outlines the hallmarks of human AAgs that facilitate the understanding of humoral autoimmunity and the identification of biomarkers of human diseases.

Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma

Beyond tertiary lymphoid structures, a significant number of immune-rich areas without germinal center-like structures are observed in non-small cell lung cancer. Here, we integrated transcriptomic data and digital pathology images to study the prognostic implications, spatial locations, and constitution of immune rich areas (immune hotspots) in a cohort of 935 patients with lung cancer from The Cancer Genome Atlas. A high intratumoral immune hotspot score, which measures the proportion of immune hotspots interfacing with tumor islands, was correlated with poor overall survival in lung squamous cell carcinoma but not in lung adenocarcinoma. Lung squamous cell carcinomas with high intratumoral immune hotspot scores were characterized by consistent upregulation of B-cell signatures. Spatial statistical analyses conducted on serial multiplex IHC slides further revealed that only 4.87% of peritumoral immune hotspots and 0.26% of intratumoral immune hotspots were tertiary lymphoid structures. Significantly lower densities of CD20+CXCR5+ and CD79b+ B cells and less diverse immune cell interactions were found in intratumoral immune hotspots compared with peritumoral immune hotspots. Furthermore, there was a negative correlation between the percentages of CD8+ T cells and T regulatory cells in intratumoral but not in peritumoral immune hotspots, with tertiary lymphoid structures excluded. These findings suggest that the intratumoral immune hotspots reflect an immunosuppressive niche compared with peritumoral immune hotspots, independent of the distribution of tertiary lymphoid structures. A balance toward increased intratumoral immune hotspots is indicative of a compromised antitumor immune response and poor outcome in lung squamous cell carcinoma.

SIGNIFICANCE

Intratumoral immune hotspots beyond tertiary lymphoid structures reflect an immunosuppressive microenvironment, different from peritumoral immune hotspots, warranting further study in the context of immunotherapies.

CD19 (+) B Cell Combined with Prognostic Nutritional Index Predicts the Clinical Outcomes of Patients with Gastric Cancer Who Underwent Surgery

(1) Background: The aim of this study was to explore the predictive ability of lymphocyte subsets for the prognosis of gastric cancer patients who underwent surgery and the prognostic value of CD19 (+) B cell combined with the Prognostic Nutritional Index (PNI). (2) Methods: This study involved 291 patients with gastric cancer who underwent surgery at our institution between January 2016 and December 2017. All patients had complete clinical data and peripheral lymphocyte subsets. Differences in clinical and pathological characteristics were examined using the Chi-square test or independent sample t-tests. The difference in survival was evaluated using Kaplan-Meier survival curves and the Log-rank test. Cox's regression analysis was performed to identify independent prognostic indicators, and nomograms were used to predict survival probabilities. (3) Results: Patients were categorized into three groups based on their CD19 (+) B cell and PNI levels, with 56 cases in group one, 190 cases in group two, and 45 cases in group three. Patients in group one had a shorter progression-free survival (PFS) (HR = 0.444, p < 0.001) and overall survival (OS) (HR = 0.435, p < 0.001). CD19 (+) B cell-PNI had the highest area under the curve (AUC) compared with other indicators, and it was also identified as an independent prognostic factor. Moreover, CD3 (+) T cell, CD3 (+) CD8 (+) T cell, and CD3 (+) CD16 (+) CD56 (+) NK T cell were all negatively correlated with the prognosis, while CD19 (+) B cell was positively associated with the prognosis. The C-index and 95% confidence interval (CI) of nomograms for PFS and OS were 0.772 (0.752-0.833) and 0.773 (0.752-0.835), respectively. (4) Conclusions: Lymphocyte subsets including CD3 (+) T cell, CD3 (+) CD8 (+) T cell, CD3 (+) CD16 (+) CD56 (+) NK T cell, and CD19 (+) B cell were related to the clinical outcomes of patients with gastric cancer who underwent surgery. Additionally, PNI combined with CD19 (+) B cell had higher prognostic value and could be used to identify patients with a high risk of metastasis and recurrence after surgery.

p53 and p63 Proteoforms Derived from Alternative Splicing Possess Differential Seroreactivity in Colorectal Cancer with Distinct Diagnostic Ability from the Canonical Proteins

Colorectal cancer (CRC) is the third most common cancer and the second most frequent cause of cancer-related death worldwide. The detection in plasma samples of autoantibodies against specific tumor-associated antigens has been demonstrated to be useful for the early diagnosis of CRC by liquid biopsy. However, new studies related to the humoral immune response in cancer are needed to enable blood-based diagnosis of the disease. Here, our aim was to characterize the humoral immune response associated with the different p53 and p63 proteoforms derived from alternative splicing and previously described as aberrantly expressed in CRC. Thus, here we investigated the diagnostic ability of the twelve p53 proteoforms and the eight p63 proteoforms described to date, and their specific N-terminal and C-terminal end peptides, by means of luminescence HaloTag beads immunoassays. Full-length proteoforms or specific peptides were cloned as HaloTag fusion proteins and their seroreactivity analyzed using plasma from CRC patients at stages I-IV (n = 31), individuals with premalignant lesions (n = 31), and healthy individuals (n = 48). p53γ, Δ40p53β, Δ40p53γ, Δ133p53γ, Δ160p53γ, TAp63α, TAp63δ, ΔNp63α, and ΔNp63δ, together with the specific C-terminal end α and δ p63 peptides, were found to be more seroreactive against plasma from CRC patients and/or individuals with premalignant lesions than from healthy individuals. In addition, ROC (receiver operating characteristic) curves revealed a high diagnostic ability of those p53 and p63 proteoforms to detect CRC and premalignant individuals (AUC higher than 85%). Finally, electrochemical biosensing platforms were employed in POC-like devices to investigate their usefulness for CRC detection using selected p53 and p63 proteoforms. Our results demonstrate not only the potential of these biosensors for the simultaneous analysis of proteoforms’ seroreactivity, but also their convenience and versatility for the clinical detection of CRC by liquid biopsy. In conclusion, we here show that p53 and p63 proteoforms possess differential seroreactivity in CRC patients in comparison to controls, distinctive from canonical proteins, which should improve the diagnostic panels for obtaining a blood-based biomarker signature for CRC detection.

The therapeutic potential of immunotherapy in the treatment of breast cancer: Rational strategies and recent progress

The second leading cause of cancer death in women worldwide is breast cancer (BC), and despite significant advances in BC therapies, a significant proportion of patients develop metastasis and disease recurrence. Currently used treatments, like radiotherapy, chemotherapy, and hormone replacement therapy, result in poor responses and high recurrence rates. Alternative therapies are therefore needed for this type of cancer. Cancer patients may benefit from immunotherapy, a novel treatment strategy in cancer treatment. Even though immunotherapy has been successful in many cases, some patients do not respond to the treatment or those who do respond relapse or progress. The purpose of this review is to discuss several different immunotherapy approaches approved for the treatment of BC, as well as different strategies for immunotherapy for the treatment of BC.

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.

Metabolic dialogs between B cells and the tumor microenvironment: Implications for anticancer immunity

Immunometabolism, a branch of biology describing the link between immunity and metabolism, is an emerging topic in cancer immunology. It is currently well accepted that B cells and tertiary lymph structures formed by them are associated with favorable outcomes when patients undergo cancer immunotherapy. Understanding the determinants of B-cell fate and function in cancer patients is necessary for improving cancer immunotherapy. Accumulating evidence points to the tumor microenvironment being a critical metabolic hurdle to an efficient antitumor B-cell response. At the same time, several B-cell-derived metabolites have recently been reported to inhibit anticancer immunity. In this literature review, key B-cell immunometabolism studies and the metabolic life of B cells were summarized. Then, we discussed the intrinsic metabolic pathways of B cells themselves and how the tumor microenvironment and B cells in tumors metabolically influence each other. Finally, we pointed out key questions to provide some inspiration for further study of the role of B-cell immunometabolism in the antitumor immune response.

Cancer Is Associated with the Emergence of Placenta-Reactive Autoantibodies

Placenta-specific antigens are minimally expressed or unexpressed in normal adult tissues, while they are widely expressed in cancer. In the course of carcinogenesis, a vast array of autoantibodies (AAbs) is produced. Here, we used a quantitative approach to determine the reactivity of AAbs in the sera of patients with breast (BrC: N = 100, 100% female, median age: 51 years), gastric (GC: N = 30, 46.6% female, median age: 57 years), bladder (BC: N = 29, 34.4% female, median age: 57 years), and colorectal (CRC: N = 34, 41.1% female, median age: 51 years) cancers against first-trimester (FTP) and full-term placental proteome (TP) in comparison with age- and sex-matched non-cancer individuals. Human-on-human immunohistochemistry was used to determine reactive target cells in FTP. The effect of pregnancy on the emergence of placenta-reactive autoantibodies was tested using sera from pregnant women at different trimesters of pregnancy. Except for BC, patients with BrC (p < 0.0284), GC (p < 0.0002), and CRC (p < 0.0007) had significantly higher levels of placenta-reactive AAbs. BrC (p < 0.0001) and BC (p < 0.0409) in the early stages triggered higher autoantibody reactivity against FTP. The reactivities of BrC sera with FTP did not show an association with ER, PR, or HER2 expression. Pregnancy in the third trimester was associated with the induction of TP- and not FTP-reactive autoantibodies (=0.018). The reactivity of BrC sera with placental proteins was found to be independent of gravidity or abortion. BrC sera showed a very strong and specific pattern of reactivity with scattered cells beneath the syncytiotrophoblast layer. Our results reinforce the concept of the coevolution of placentation and cancer and shed light on the future clinical application of the placental proteome for the non-invasive early detection and treatment of cancer.

The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer

Lung cancer is a disease that in recent years has become one of the greatest threats to modern society. Every year there are more and more new cases and the percentage of deaths caused by this type of cancer increases. Despite many studies, scientists are still looking for answers regarding the mechanisms of lung cancer development and progression, with particular emphasis on the role of the immune system. The aim of this literature review was to present the importance of disorders of the immune system and the accompanying changes at the level of cell signaling in the pathogenesis of lung cancer. The collected results showed that in the process of immunopathogenesis of almost all subtypes of lung cancer, changes in the tumor microenvironment, deregulation of immune checkpoints and abnormalities in cell signaling pathways are involved, which contribute to the multistage and multifaceted carcinogenesis of this type of cancer. We, therefore, suggest that in future studies, researchers should focus on a detailed analysis of tumor microenvironmental immune checkpoints, and to validate their validity, perform genetic polymorphism analyses in a wide range of patients and healthy individuals to determine the genetic susceptibility to lung cancer development. In addition, further research related to the analysis of the tumor microenvironment; immune system disorders, with a particular emphasis on immunological checkpoints and genetic differences may contribute to the development of new personalized therapies that improve the prognosis of patients.

Checkpoint inhibitor immune-related adverse events: A focused review on autoantibodies and B cells as biomarkers, advancements and future possibilities

The use of immune checkpoint inhibitors (ICIs) has evolved rapidly with unprecedented treatment benefits being obtained for cancer patients, including improved patient survival. However, over half of the patients experience immune related adverse events (irAEs) or toxicities, which can be fatal, affect the quality of life of patients and potentially cause treatment interruption or cessation. Complications from these toxicities can also cause long term irreversible organ damage and other chronic health conditions. Toxicities can occur in various organ systems, with common observations in the skin, rheumatologic, gastrointestinal, hepatic, endocrine system and the lungs. These are not only challenging to manage but also difficult to detect during the early stages of treatment. Currently, no biomarker exists to predict which patients are likely to develop toxicities from ICI therapy and efforts to identify robust biomarkers are ongoing. B cells and antibodies against autologous antigens (autoantibodies) have shown promise and are emerging as markers to predict the development of irAEs in cancer patients. In this review, we discuss the interplay between ICIs and toxicities in cancer patients, insights into the underlying mechanisms of irAEs, and the involvement of the humoral immune response, particularly by B cells and autoantibodies in irAE development. We also provide an appraisal of the progress, key empirical results and advances in B cell and autoantibody research as biomarkers for predicting irAEs. We conclude the review by outlining the challenges and steps required for their potential clinical application in the future.

Posttranslational modifications induce autoantibodies with risk prediction capability in patients with small cell lung cancer

Small cell lung cancer (SCLC) elicits the generation of autoantibodies that result in unique paraneoplastic neurological syndromes. The mechanistic basis for the formation of such autoantibodies is largely unknown but is key to understanding their etiology. We developed a high-dimensional technique that enables detection of autoantibodies in complex with native antigens directly from patient plasma. Here, we used our platform to screen 1009 human plasma samples for 3600 autoantibody-antigen complexes, finding that plasma from patients with SCLC harbors, on average, fourfold higher disease-specific autoantibody signals compared with plasma from patients with other cancers. Across three independent SCLC cohorts, we identified a set of common but previously unknown autoantibodies that are produced in response to both intracellular and extracellular tumor antigens. We further characterized several disease-specific posttranslational modifications within extracellular proteins targeted by these autoantibodies, including citrullination, isoaspartylation, and cancer-specific glycosylation. Because most patients with SCLC have metastatic disease at diagnosis, we queried whether these autoantibodies could be used for SCLC early detection. We created a risk prediction model using five autoantibodies with an average area under the curve of 0.84 for the three cohorts that improved to 0.96 by incorporating cigarette smoke consumption in pack years. Together, our findings provide an innovative approach to identify circulating autoantibodies in SCLC with mechanistic insight into disease-specific immunogenicity and clinical utility.