Autoantibody profiling identifies predictive biomarkers of response to anti-PD1 therapy in cancer patients

High-Throughput Antigen Microarray Identifies Longitudinal Prognostic Autoantibody for Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Antibody Profiling of Pan-Cancer Viral Proteome Reveals Biomarkers for Nasopharyngeal Carcinoma Diagnosis and Prognosis

Diagnosing, predicting disease outcome, and identifying effective treatment targets for virus-related cancers are lacking. Protein biomarkers have the potential to bridge the gap between prevention and treatment for these types of cancers. While it has been shown that certain antibodies against EBV proteins could be used to detect nasopharyngeal carcinoma (NPC), antibodies targeting are solely a tiny part of the about 80 proteins expressed by the EBV genome. Furthermore, it remains unclear what role other viruses play in NPC since many diseases are the result of multiple viral infections. For the first time, this study measured both IgA and IgG antibody responses against 646 viral proteins from 23 viruses in patients with NPC and control subjects using nucleic acid programmable protein arrays. Candidate seromarkers were then validated by ELISA using 1665 serum samples from three clinical cohorts. We demonstrated that the levels of five candidate seromarkers (EBV-BLLF3-IgA, EBV-BLRF2-IgA, EBV-BLRF2-IgG, EBV-BDLF1-IgA, EBV-BDLF1-IgG) in NPC patients were significantly elevated than controls. Additional examination revealed that NPC could be successfully diagnosed by combining the clinical biomarker EBNA1-IgA with the five anti-EBV antibodies. The sensitivity of the six-antibody signature at 95% specificity to diagnose NPC was comparable to the current clinically-approved biomarker combination, VCA-IgA, and EBNA1-IgA. However, the recombinant antigens of the five antibodies are easier to produce and standardize compared to the native viral VCA proteins. This suggests the potential replacement of the traditional VCA-IgA assay with the 5-antibodies combination to screen and diagnose NPC. Additionally, we investigated the prognostic significance of these seromarkers titers in NPC. We showed that NPC patients with elevated BLLF3-IgA and BDLF1-IgA titers in their serum exhibited significantly poorer disease-free survival, suggesting the potential of these two seromarkers as prognostic indicators of NPC. These findings will help develop serological tests to detect and treat NPC in the future.

Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10-12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.

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.

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.

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 development of a tumor-associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor-based treatment in patients with advanced non-small-cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have become one important therapeutic strategy for advanced non-small-cell lung cancer (NSCLC). It remains imperative to identify reliable and convenient biomarkers to predict both the efficacy and toxicity of immunotherapy, and tumor-associated autoantibodies (TAAbs) are recognized as one of the promising candidates for this.

PATIENTS AND METHODS

This study enrolled 97 advanced NSCLC patients with ICI-based immunotherapy treatment, who were divided into a training cohort (n = 48) and a validation cohort (n = 49), and measured for the serum level of 35 TAAbs. According to the statistical association between the serum positivity and clinical outcome of each TAAb in the training cohort, a TAAb panel was developed to predict the progression-free survival (PFS), and further examined in the validation cohort and in different subgroups. Similarly, another TAAb panel was derived to predict the occurrence of immune-related adverse events (irAEs).

RESULTS

In the training cohort, a 7-TAAb panel composed of p53, CAGE, MAGEA4, GAGE7, UTP14A, IMP2, and PSMC1 TAAbs was derived to predict PFS (median PFS [mPFS] 9.9 vs. 4.3 months, p = 0.043). The statistical association between the panel positivity and longer PFS was confirmed in the validation cohort (mPFS 11.1 vs. 4.8 months, p = 0.015) and in different subgroups of patients. Moreover, another 4-TAAb panel of BRCA2, MAGEA4, ZNF768, and PARP TAAbs was developed to predict the occurrence of irAEs, showing higher risk in panel-positive patients (71.43% vs. 28.91%, p = 0.0046).

CONCLUSIONS

Collectively, our study developed and validated two TAAb panels as valuable prognostic biomarkers for immunotherapy.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Development of a protein microarray for profiling circulating autoantibodies in human diseases

PURPOSE

To develop a robust microarray platform to detect thousands of serological autoantibodies (AAbs) simultaneously in different diseases.

EXPERIMENTAL DESIGN

An AAbMap microarray was prepared by printing a total of 4032 purified His-tagged human proteins and peptide probes on a chemically-modified slide. The sensitivity, dynamic range, and the inter- and intra-array reproducibility of the AAb microarray were then systematically tested and optimized. Finally, the large-scale profiling of AAbs in the serum of patients with different human diseases using the AAbMap microarray was demonstrated.

RESULTS

The dynamic range of antibody (Ab) detection was 2 to 3 orders of magnitude with the lowest limit of detection (LOD) of 68 pg/mL. The intra-array (r) correlation of duplicate spots was 1.00, whereas the inter-array correlations between different arrays and batches were 0.99 and 0.97 to 0.98, respectively. Notably, 132, 266, 171, and 84 AAbs were detected in pooled serum from healthy controls (HCs) or patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), or lung cancer (LC), respectively. These AAbs included antibodies that target well-known disease biomarkers, such as anti-cyclic citrullinated peptide, anti-ribonucleoprotein, and anti-nucleosome.

CONCLUSIONS AND CLINICAL RELEVANCE

We developed a microarray platform to measure thousands of serological AAbs simultaneously with high sensitivity and reproducibility. The array can help study autoimmunity and complement genomics, proteomics, and metabolomics data for systematic investigations of human diseases.

Comparative Combinatorial Implications and Theranostics of Immunotherapy in the Impediment of Alveolar Soft Part Sarcoma

BACKGROUND

Immune checkpoint inhibitors (ICIs), specifically programmed cell death receptor- 1/ligand 1 (PD-1/L1) inhibitors, have shown potential pharmacological efficacy in several cancers. Nonetheless, data pertinent to their therapeutic efficacy in alveolar soft-part sarcoma (ASPS) are limited.

OBJECTIVE

The retrospective aspects of ICIs (anti-PD1/PD-L1 blockers) to target ASPS are comparatively analyzed for clinical outcomes with other targeted immunotherapy modalities.

METHODS

We have conducted a systematic review without statistical analysis or comprehensive meta-analysis by collecting the articles published between 1952 and Sep 10th, 2020, by searching the following words: alveolar soft part sarcoma and immunotherapy including immune checkpoint, immune checkpoint inhibitors, and PD-1, PD-L1. We performed a pooled analysis of case reports, conferences, clinical trials, and other research reports pertinent to the efficacy of a PD-1 or PD-L1 antagonist in patients diagnosed with metastatic ASPS.

RESULTS

The effective studies include 10 case reports, 2 conference reports, 5 clinical trials, and 2 additional research reports. A total of 110 patients were reported to be enrolled in the pooled analysis; among them, 87 (78.38%) received a PD-1/PD-L1 antagonist. For patients who received anti-PD-1/PD-L1as monotherapy, their clinical response rates (CRR) were 63.22% whereas those who received targeted therapy and immunotherapy had a CRR of 78.95% (15/19). In the patients treated with double immunotherapy, their CRR was 100% (4/4). Tumor mutational burden and mismatch repair status have significant implications for predicting the ASPS prognosis.

CONCLUSION

Alveolar soft-part sarcoma patients with distant metastases can exhibit better clinical outcomes with immunotherapy, particularly toripalimab, atezolizumab, and axitinib combinatorial regimen with pembrolizumab. In addition, this review describes the therapeutic implications to guide personalized medicine depending on the expression patterns of PD-1/PD-L1 during the immunotherapy with ASPS.

Autoantibodies - enemies, and/or potential allies?

Autoantibodies are well known as potentially highly harmful antibodies which attack the host via binding to self-antigens, thus causing severe associated diseases and symptoms (e.g. autoimmune diseases). However, detection of autoantibodies to a range of disease-associated antigens has enabled their successful usage as important tools in disease diagnosis, prognosis and treatment. There are several advantages of using such autoantibodies. These include the capacity to measure their presence very early in disease development, their stability, which is often much better than their related antigen, and the capacity to use an array of such autoantibodies for enhanced diagnostics and to better predict prognosis. They may also possess capacity for utilization in therapy, in vivo. In this review both the positive and negative aspects of autoantibodies are critically assessed, including their role in autoimmune diseases, cancers and the global pandemic caused by COVID-19. Important issues related to their detection are also highlighted.

Plasma autoantibodies IgG and IgM to PD1/PDL1 as potential biomarkers and risk factors of lung cancer

Antibodies targeting programmed cell death-1 (PD1) and its ligand (PDL1) have transformed current cancer therapy while little is known about the expression of anti-PD1/PDL1 autoantibodies between lung cancer (LC) patients and normal controls (NC). The expression level of anti-PD1/PDL1 IgG and IgM was detected in plasma of 325 LC and 324 NC by indirect enzyme-linked immune sorbent assay (ELISA). Western blot and indirect immunofluorescence (IIF) were used to verify the ELISA results. The association analysis was used to evaluate the odds ratio (OR) of LC. The expression of anti-PD1/PDL1 IgG in LC samples was significantly higher than NC (P < 0.001 and P < 0.05, respectively). The positive rate of anti-PD1/PDL1 IgG in LC was significantly higher than NC and significant difference was also shown in LC samples of different clinical characteristics, such as clinical stage, nodules diameter, lymph node metastasis and distant metastasis (P < 0.001). Moreover, PD1/PDL1 expression in tissues showed no significant relation with that in plasma (P > 0.05). Anti-PD1/PDL1 IgG were the risk factors related to LC (OR (95% CI): 22.433 (5.426-92.745) and 5.051 (1.316-19.386)), while anti-PD1/PDL1 IgM were the risk factors for LC with ≤ 60 years (OR (95% CI): 6.122 (1.365-27.455) and 7.664 (1.715-34.251)) and anti-PD1 IgM was also the risk factor for male LC cases(OR (95% CI): 6.948 (1.076-44.868)). Plasma anti-PD1/PDL1 IgG and IgM might serve as potential biomarkers and risk predictors for LC.

[Clinical Value of Autoantibody Prognostic Markers in Tumor Immune Checkpoint Inhibitor Therapy]

Serum autoantibody markers have the advantages of easy specimen acquisition, simple detection technology and dynamic real-time monitoring. With the wide application of immune checkpoint inhibitors in the treatment of malignant tumors, autoantibody markers in predicting tumor immune checkpoint inhibitors efficacy and forecasting irAEs (immune related adverse events) show good prediction of potential. This review mainly focused on the progress of autoantibody markers in the prediction of therapeutic effect and the monitoring of irAE in tumor immunotherapy.
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'Know thyself' - host factors influencing cancer response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have revolutionised oncology and are now standard-of-care for the treatment of a wide variety of solid neoplasms. However, tumour responses remain unpredictable, experienced by only a minority of ICI recipients across malignancy types. Therefore, there is an urgent need for better predictive biomarkers to identify a priori the patients most likely to benefit from these therapies. Despite considerable efforts, only three such biomarkers are FDA-approved for clinical use, and all rely on the availability of tumour tissue for immunohistochemical staining or genomic assays. There is emerging evidence that host factors - for example, genetic, metabolic, and immune factors, as well as the composition of one's gut microbiota - influence the response of a patient's cancer to ICIs. Tantalisingly, some of these factors are modifiable, paving the way for co-therapies that may enhance the therapeutic index of these treatments. Herein, we review key host factors that are of potential biomarker value for response to ICI therapy, with a particular focus on the proposed mechanisms for these influences. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Melanoma-specific antigen-associated antitumor antibody reactivity as an immune-related biomarker for targeted immunotherapies

Background:

Immunotherapies, including cancer vaccines and immune checkpoint inhibitors have transformed the management of many cancers. However, a large number of patients show resistance to these immunotherapies and current research has provided limited findings for predicting response to precision immunotherapy treatments.

Methods:

Here, we applied the next generation phage display mimotope variation analysis (MVA) to profile antibody response and dissect the role of humoral immunity in targeted cancer therapies, namely anti-tumor dendritic cell vaccine (MelCancerVac^®) and immunotherapy with anti-PD-1 monoclonal antibodies (pembrolizumab).

Results:

Analysis of the antibody immune response led to the characterization of epitopes that were linked to melanoma-associated and cancer-testis antigens (CTA) whose antibody response was induced upon MelCancerVac® treatments of lung cancer. Several of these epitopes aligned to antigens with strong immune response in patients with unresectable metastatic melanoma receiving anti-PD-1 therapy.

Conclusions:

This study provides insights into the differences and similarities in tumor-specific immunogenicity related to targeted immune treatments. The antibody epitopes as biomarkers reflect melanoma-associated features of immune response, and also provide insights into the molecular pathways contributing to the pathogenesis of cancer. Concluding, antibody epitope response can be useful in predicting anti-cancer immunity elicited by immunotherapy.

Immunotherapy treatments, which utilize the patient’s own immune system to fight cancer, have become a standard treatment of cancer. However, for many patients’ immunotherapy does not work. During the immune response the body produces proteins called antibodies. This study characterized the antibodies produced following treatment with two different types of immunotherapies that treat skin cancer, to gain insights into how the immune system responds in different individuals. Our results demonstrate that multiple proteins that are present in patients with skin cancer are specifically targeted by the immune system during skin cancer specific immunotherapy. Our results should help further anti-cancer drug development.

Rähni et al profile antibody response in patients with varied response to cancer immunotherapies. They identify antibody epitope responses that predict anti-cancer immunity elicited by immunotherapy.

Comparison of Laboratory Methods for the Clinical Follow Up of Checkpoint Blockade Therapies in Leukemia: Current Status and Challenges Ahead

The development of immune checkpoint inhibitors, the monoclonal antibodies that modulate the interaction between immune checkpoint molecules or their ligands on the immune cells or tumor tissue has revolutionized cancer treatment. While there are various studies proving their efficacy in hematological malignancies, there is also a body of accumulating evidence indicating that immune checkpoint inhibitors’ clinical benefits are limited in such diseases. In addition, due to their regulatory nature that balances the immune responses, blockade of immune checkpoints may lead to toxic side effects and autoimmune responses, and even primary or acquired resistance mechanisms may restrict their success. Thus, the need for laboratory biomarkers to identify and monitor patient populations who are more likely respond to this type of therapy and the management of side effects seem critical. However, guidelines regarding the use of immune checkpoint inhibitors in hematological cancers and during follow-up are limited while there is no consensus on the laboratory parameters to be investigated for safety and efficacy of the treatment. This review aims to provide an insight into recent information on predictive and prognostic value of biomarkers and laboratory tests for the clinical follow up of hematological malignancies, with an emphasis on leukemia.

High-throughput and multi-phases identification of autoantibodies in diagnosing early-stage breast cancer and subtypes

Autoantibodies (AAbs) targeted tumor‐associated antigens (TAAs) have the potential for early detection of breast cancer. Here, 574 early‐stage breast cancer (ES‐BC) patients containing 4 subtypes (Luminal A, Luminal B, HER2+, TN), 126 benign breast disease (BBD) patients, and 199 normal healthy controls (NHC) were separated into three‐phases to discover, verify, and validate AAbs. In discovery phase using high‐throughput protein microarray, 37 AAbs with sensitivity of 31.25%‐86.25% and specificity over 73% in ES‐BC, and 40 AAbs with different positive rates between subtypes were identified as candidates. In verification phase, 18 AAbs were significantly increased compared with the Control (BBD and NHC) in focused array. Ten out of 18 AAbs exhibited a significant difference between subtypes (P < .05). In ELISA validation phase, 5 novel AAbs (anti‐KJ901215, ‐FAM49B, ‐HYI, ‐GARS, ‐CRLF3) exhibited significantly higher levels in ES‐BC compared with BBD/NHC (P < .05). The sensitivities of individual AAb and a 5‐AAbs panel were 20.41%‐28.57% and 38.78%, whereas the specificities were over 90% and 85.94%. Simultaneously, 4 AAbs except anti‐GARS differed significantly between TN and non‐TN subtype (P < .05). We constructed 3 random forest classifier models based on AAbs to discriminant ES‐BC from Control or BBD, and to discern TN subtype, which yielded an area under the curve of 0.870, 0.860, and 0.875, respectively. Biological interaction analysis revealed 4 TAAs, except for KJ901215, that were associated with well known proteins of BC. This study discovered and stepwise validated 5 novel AAbs with the potential to diagnose ES‐BC and discern TN subtype, indicating easy‐to‐detect and minimally invasive diagnostic value of serum AAbs ahead of biopsy for future application.

Anti-PD1/PDL1 IgG subclass distribution in ten cancer types and anti-PD1 IgG4 as biomarker for the long time survival in NSCLC with anti-PD1 therapy

BACKGROUND

Antibodies targeting programmed cell death-1(PD1) and its ligand (PDL1) have revolutionized cancer therapy. However, little is known about the preexisted anti-PD1/PDL1 autoantibodies (AAbs) distribution in multiple cancer types, nor is their potential biomarker role for anti-PD1 therapy.

METHOD

Plasma anti-PD1/PDL1 AAb IgG and subclasses (IgG1-4) were detected by enzyme-linked immune sorbent assay (ELISA) in 190 cancer patients, covering 10 cancer types (lung, breast, esophageal, colorectal, liver, prostatic, cervical, ovarian, gastric cancers and lymphoma), the comprehensive correlation of AAbs with multiple clinical parameters was analyzed. We further tested these AAbs in 76 non-small cell lung cancer (NSCLC) samples receiving anti-PD1 therapy, the association of AAbs level with survival was analyzed and validated in an independent cohort (n = 32).

RESULTS

Anti-PD1/PDL1 AAb IgG were globally detected in 10 types of cancer patients. IgG1 and IgG2 were the major subtypes for anti-PD1/PDL1 AAbs. Correlation analysis revealed a distinct landscape between various cancer types. The random forest model indicated that IgG4 subtype was mostly associated with cancer. In discovery cohort of 76 NSCLC patients, high anti-PD1 IgG4 was associated with a reduced overall survival (OS, p = 0.019), not progression-free survival (PFS, p = 0.088). The negative association of anti-PD1 IgG4 with OS was validated in 32 NSCLC patients (p = 0.032).

CONCLUSION

This study reports for the first time the distribution of preexisted anti-PD1/PDL1 AAb IgG and subclasses across 10 cancer types. Moreover, the anti-PD1 AAb IgG4 subclass was identified to associate with OS, which may serve as a potential biomarker for anti-PD1 therapeutic survival benefit in NSCLC patients.

Targeted and immuno-based therapies in sarcoma: mechanisms and advances in clinical trials

Sarcomas represent a distinct group of rare malignant tumors with high heterogeneity. Limited options with clinical efficacy for the metastatic or local advanced sarcoma existed despite standard therapy. Recently, targeted therapy according to the molecular and genetic phenotype of individual sarcoma is a promising option. Among these drugs, anti-angiogenesis therapy achieved favorable efficacy in sarcomas. Inhibitors targeting cyclin-dependent kinase 4/6, poly-ADP-ribose polymerase, insulin-like growth factor-1 receptor, mTOR, NTRK, metabolisms, and epigenetic drugs are under clinical evaluation for sarcomas bearing the corresponding signals. Immunotherapy represents a promising and favorable method in advanced solid tumors. However, most sarcomas are immune "cold" tumors, with only alveolar soft part sarcoma and undifferentiated pleomorphic sarcoma respond to immune checkpoint inhibitors. Cellular therapies with TCR-engineered T cells, chimeric antigen receptor T cells, tumor infiltrating lymphocytes, and nature killer cells transfer show therapeutic potential. Identifying tumor-specific antigens and exploring immune modulation factors arguing the efficacy of these immunotherapies are the current challenges. This review focuses on the mechanisms, advances, and potential strategies of targeted and immune-based therapies in sarcomas.

Lithographic Processes for the Scalable Fabrication of Micro- and Nanostructures for Biochips and Biosensors

Since the early 2000s, extensive research has been performed to address numerous challenges in biochip and biosensor fabrication in order to use them for various biomedical applications. These biochips and biosensor devices either integrate biological elements (e.g., DNA, proteins or cells) in the fabrication processes or experience post fabrication of biofunctionalization for different downstream applications, including sensing, diagnostics, drug screening, and therapy. Scalable lithographic techniques that are well established in the semiconductor industry are now being harnessed for large-scale production of such devices, with additional development to meet the demand of precise deposition of various biological elements on device substrates with retained biological activities and precisely specified topography. In this review, the lithographic methods that are capable of large-scale and mass fabrication of biochips and biosensors will be discussed. In particular, those allowing patterning of large areas from 10 cm² to m², maintaining cost effectiveness, high throughput (>100 cm² h^-1), high resolution (from micrometer down to nanometer scale), accuracy, and reproducibility. This review will compare various fabrication technologies and comment on their resolution limit and throughput, and how they can be related to the device performance, including sensitivity, detection limit, reproducibility, and robustness.

Detection of Posttranslational Modification Autoantibodies Using Peptide Microarray

Autoantibodies are humoral antibodies against self-proteins and play vital roles in maintaining the homeostasis. Autoantibodies can also target posttranslational modifications (PTMs) of proteins and the identification of new PTM autoantibodies is important to identify biomarkers for the early diagnosis of cancer and autoimmune diseases. In this chapter, we describe a method to detect PTM autoantibodies using citrullinated peptide microarray as an example. This method can be used to screen serum autoantibodies for different human diseases.

Peripheral Blood Autoantibodies Against to Tumor-Associated Antigen Predict Clinical Outcome to Immune Checkpoint Inhibitor-Based Treatment in Advanced Non-Small Cell Lung Cancer

Background

Peripheral blood biomarkers to immunotherapy have attracted more and more attentions owing to noninvasive nature. This study was designed to identify a panel of tumor associated autoantibodies (TAAbs) in plasma to predict the clinical outcome of ICIs-based treatment in advanced NSCLC patients and correlation between TAAbs and checkpoint inhibitor pneumonitis (CIP) would also be investigated.

Materials and Methods

Baseline plasma was collected from patients with advanced NSCLC before receiving ICIs-based treatment. ELISA was used to detect concentration of autoantibodies. Clinical efficacy was evaluated according to RECIST v1.1.

Results

We have identified a panel of five-TAAbs to predict responses of ICIs-based treatment in a discovery cohort (n = 37), and confirmed its predictive value in a validation cohort (n = 129). In the validation cohort, the positivity of this 5-TAAbs panel was significantly associated with better response (ORR: 44.4% vs. 13.6%, P < 0.001) and longer PFS (7.6 vs. 3.3m, P < 0.001). This significant association was remained in subgroup of patients treated with combination therapy (ORR: 43.8% vs. 13.7%, P = 0.004,PFS: 6.7 vs. 3.7m, P = 0 .017). Furthermore, this 5-TAAs panel worked better in patients who received subsequent-line treatment (ORR: 42.4% vs. 7.7%, P = 0.001, PFS: 6.2 vs. 3.0m, P = 0.004) than those received first-line treatment (ORR: 46.7% vs. 35.7%, P = 0.345, PFS: NR vs. 10.48m, P = 0.146). In addition, the CIP incidence in patients with 5-TAAbs positive was significantly higher comparing to negative patients (20.4% vs. 5.9%, P = 0.015).

Conclusion

Our 5-TAAbs panel is a potential predictive biomarker for responses and toxicities to ICIs-based treatment in patients with advanced NSCLC.

Relationship between circulating tumor-associated autoantibodies and clinical outcomes in advanced-stage NSCLC patients receiving PD-1/-L1 directed immune checkpoint inhibition

BACKGROUND

Durable tumor regressions are observed in a subset of advanced-stage non-small cell lung cancer (NSCLC) patients receiving PD-1/-L1 targeted immune checkpoint inhibitors (or 'immunotherapy') alone or in combination with chemotherapy. However, the majority of advanced NSCLC patients receiving these agents do not experience long-term disease control. Existing methods to identify patients most likely to gain clinical benefit from PD-1/-L1 immunotherapy have limitations, creating a need for improved methods to guide treatment selection, particularly for those likely to benefit from single-agent immunotherapy. Here, we describe the development of a series of novel assays for tumor-associated autoantibodies as part of an exploratory study intended to determine if these biomarkers have potential prognostic value in this setting.

METHOD

A selection of recombinant tumor autoantigens previously characterized for their diagnostic utility were developed and preliminarily evaluated by this study. These include: Fumarate Dehydrogenase (FH), Hydroxysteroid 17-Beta Dehydrogenase 10 (HSD17B10), Inosine Monophosphate Dehydrogenase 2 (IMPDH2), New York Esophageal Squamous Cell Carcinoma-1 (NY ESO-1), Phosphoglycerate Mutase 1 (PGAM1), and Vimentin. Custom Luminex immunobead assays were developed for these targets to quantitatively assess autoantibody levels in individual patient sera. Assays were erected as indirect immunoassays on MagPlex® Microspheres using standard carbodiimide/NHS-based chemistries, utilizing a biotin-conjugated secondary (i.e. anti-human IgG) antibody and R-phycoerythrin-conjugated streptavidin reporter system. Standard curves were created for quantitative purposes using commercially-available anti-antigen antibodies and permitted analytical performance characteristics to be calculated. These assays were used to preliminarily evaluate a series of pretreatment serum samples from stage IV NSCLC patients receiving anti PD-1/-L1 therapy after failure of at least one prior line of therapy (n = 40) and their classification efficiency calculated based on 12 months overall survival (OS) threshold.

RESULTS

Six assays were developed that each showed dynamic ranges of four orders of magnitude and provided more than 90% classification accuracy based on the observed clinical outcome data. Inter- and intra-assay precision was assessed within these standards and overall %CVs of ≤7% and ≤ 10%, respectively, were calculated. Generally, the baseline level of autoantibodies were significantly (p < 0.05) lower in the ≥12 months survival group relative to the <12 months survival groups. Serum titers of FH, HSD170B, NY-ESO-1, and vimentin were significantly correlated with ≥12 month survival (p-value 0.0038, 0.0061, 0.0073, and 0.022, respectively). IMPDH2 and PGAM1 were found to have marginal significance (p-value 0.08 and 0.076, respectively).

CONCLUSION

This study demonstrates an efficient and promising means for assessing circulating autoantibody titers that could be useful in selecting advanced NSCLC patients for PD-1/-L1 directed immunotherapy. Further exploration and validation of this paradigm is warranted to further refine current treatment selection methods for this therapeutic strategy.

Protein array-based companion diagnostics in precision medicine

INTRODUCTION

The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities.

AREA COVERED

This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests.

EXPERT OPINION

Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.