IgM and IgA augmented autoantibody signatures improve early-stage detection of colorectal cancer prior to nodal and distant spread

Prediction of resistance to bevacizumab plus FOLFOX in metastatic colorectal cancer-Results of the prospective multicenter PERMAD trial

BACKGROUND

Anti-vascular endothelial growth factor (VEGF) monoclonal antibodies (mAbs) are widely used for tumor treatment, including metastatic colorectal cancer (mCRC). So far, there are no biomarkers that reliably predict resistance to anti-VEGF mAbs like bevacizumab. A biomarker-guided strategy for early and accurate assessment of resistance could avoid the use of non-effective treatment and improve patient outcomes. We hypothesized that repeated analysis of multiple cytokines and angiogenic growth factors (CAFs) before and during treatment using machine learning could provide an accurate and earlier, i.e., 100 days before conventional radiologic staging, prediction of resistance to first-line mCRC treatment with FOLFOX plus bevacizumab.

PATIENTS AND METHODS

15 German and Austrian centers prospectively recruited 50 mCRC patients receiving FOLFOX plus bevacizumab as first-line treatment. Plasma samples were collected every two weeks until radiologic progression (RECIST 1.1) as determined by CT scans performed every 2 months. 102 pre-selected CAFs were centrally analyzed using a cytokine multiplex assay (Luminex, Myriad RBM).

RESULTS

Using random forests, we developed a predictive machine learning model that discriminated between the situations of "no progress within 100 days before radiological progress" and "progress within 100 days before radiological progress". We could further identify a combination of ten out of the 102 CAF markers, which fulfilled this task with 78.2% accuracy, 71.8% sensitivity, and 82.5% specificity.

CONCLUSIONS

We identified a CAF marker combination that indicates treatment resistance to FOLFOX plus bevacizumab in patients with mCRC within 100 days prior to radiologic progress.

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.

Autoantibody repertoire profiling in tissue and blood identifies colorectal cancer-specific biomarkers

Autoantibodies (AAbs) in the blood of colorectal cancer (CRC) patients have been evaluated for tumor detection. However, it remains uncertain whether these AAbs are specific to tumor-associated antigens. In this study, we explored the IgG and IgM autoantibody repertoires in both the in situ tissue microenvironment and peripheral blood as potential tumor-specific biomarkers. We applied high-density protein arrays to profile AAbs in the tumor-infiltrating lymphocyte supernatants and corresponding serum from four patients with CRC, as well as in the serum of three noncancer controls. Our findings revealed that there were more reactive IgM AAbs than IgG in both the cell supernatant and corresponding serum, with a difference of approximately 3-5 times. Immunoglobulin G was predominant in the serum, while IgM was more abundant in the cell supernatant. We identified a range of AAbs present in both the supernatant and the corresponding serum, numbering between 432 and 780, with an average of 53.3% shared. Only 4.7% (n = 23) and 0.2% (n = 2) of reactive antigens for IgG and IgM AAbs, respectively, were specific to CRC. Ultimately, we compiled a list of 19 IgG AAb targets as potential tumor-specific AAb candidates. Autoantibodies against one of the top candidates, p15INK4b-related sequence/regulation of nuclear pre-mRNA domain-containing protein 1A (RPRD1A), were significantly elevated in 53 CRC patients compared to 119 controls (p < 0.0001). The project revealed that tissue-derived IgG AAbs, rather than IgM, are the primary source of tumor-specific AAbs in peripheral blood. It also identified potential tumor-specific AAbs that could be applied for noninvasive screening of CRC.

Protein array processing software for automated semiquantitative analysis of serum antibody repertoires

Effective immunotherapies activate natural antitumor immune responses in patients undergoing treatment. The ability to monitor immune activation in response to immunotherapy is critical in measuring treatment efficacy over time and across patient cohorts. Protein arrays are systematically arranged, large collections of annotated proteins on planar surfaces, which can be used for the characterization of disease-specific and treatment-induced antibody repertoires in individuals undergoing immunotherapy. However, the absence of appropriate image analysis and data processing software presents a substantial hurdle, limiting the uptake of this approach in immunotherapy research. We developed a first, automated semiquantitative open-source software package for the analysis of widely used protein macroarrays. The software allows accurate single array and inter-array comparative studies through the tackling of intra-array inconsistencies arising from experimental disparities. The innovative and automated image analysis process includes adaptive positioning, background identification and subtraction, removal of null signals, robust statistical analysis, and protein pair validation. The normalized values allow a convenient semiquantitative data analysis of different samples or timepoints. Enabling accurate characterization of sample series to identify disease-specific immune profiles or their relative changes in response to treatment may serve as a diagnostic or predictive tool of disease.

Tumor organoid model of colorectal cancer (Review)

The establishment of self-organizing 'mini-gut' organoid models has brought about a significant breakthrough in biomedical research. Patient-derived tumor organoids have emerged as valuable tools for preclinical studies, offering the retention of genetic and phenotypic characteristics of the original tumor. These organoids have applications in various research areas, including in vitro modelling, drug discovery and personalized medicine. The present review provided an overview of intestinal organoids, focusing on their unique characteristics and current understanding. The progress made in colorectal cancer (CRC) organoid models was then delved into, discussing their role in drug development and personalized medicine. For instance, it has been indicated that patient-derived tumor organoids are able to predict response to irinotecan-based neoadjuvant chemoradiotherapy. Furthermore, the limitations and challenges associated with current CRC organoid models were addressed, along with proposed strategies for enhancing their utility in future basic and translational research.

Combined with prognostic nutritional index and IgM for predicting the clinical outcomes of gastric cancer patients who received surgery

Objective

Although the survival rate of patients who undergo surgery for gastric cancer has greatly improved, still many patients have a poor prognosis. This retrospective study aimed to investigate the predictive ability of the PNI-IgM score, a combined prognostic nutritional index (PNI), and immunoglobulin M (IgM), on the prognosis of patients undergoing surgery for gastric cancer.

Methods

340 patients with gastric cancer who underwent surgery from January 2016 to December 2017 were selected. The PNI-IgM score ranged from 1 to 3: score of 1, low PNI (< 48.45) and low IgM (< 0.87); score of 2, low PNI and high IgM, or high PNI and low IgM; score of 3, high PNI and high IgM. We compared the differences in disease-free survival (DFS) and overall survival (OS) among the three groups, while univariate and multivariate analyses calculated prognostic factors for DFS and OS. In addition, the nomograms were constructed based on the results of multivariate analysis to estimate the 1-, 3- and 5-year survival probability.

Results

There were 67 cases in the PNI-IgM score 1 group, 160 cases in the PNI-IgM score 2 group, and 113 cases in the PNI-IgM score 3 group. The median survival times of DFS in the PNI-IgM score group 1, the PNI-IgM score group 2, and the PNI-IgM score group 3 were 62.20 months, not reached, and not reached, and 67.57 months vs. not reached vs. not reached in three groups for OS. Patients in the PNI-IgM score group 1 had a lower DFS than the PNI-IgM score group 2 (HR = 0.648, 95% CI: 0.418-1.006, P = 0.053) and the PNI-IgM score group 3 (HR = 0.337, 95% CI: 0.194-0.585, P < 0.001). In stratified analysis, PNI-IgM score 1 had a worse prognosis in the age < 60 years group and CA724 < 2.11 U/m group.

Conclusion

PNI-IgM score is a novel combination of nutritional and immunological markers that can be used as a sensitive biological marker for patients with gastric cancer who undergo surgery. The lower the PNI-IgM score, the worse the prognosis.

Altered B cell immunoglobulin signature exhibits potential diagnostic values in human colorectal cancer

Antibody-secreting B cells have long been considered the central element of gut homeostasis; however, tumor-associated B cells in human colorectal cancer (CRC) have not been well characterized. Here, we show that the clonotype, phenotype, and immunoglobulin subclasses of tumor-infiltrating B cells have changed compared to adjacent normal tissue B cells. Remarkably, the tumor-associated B cell immunoglobulin signature alteration can also be detected in the plasma of patients with CRC, suggesting that a distinct B cell response was also evoked in CRC. We compared the altered plasma immunoglobulin signature with the existing method of CRC diagnosis. Our diagnostic model exhibits improved sensitivity compared to the traditional biomarkers, CEA and CA19-9. These findings disclose the altered B cell immunoglobulin signature in human CRC and highlight the potential of using the plasma immunoglobulin signature as a non-invasive method for the assessment of CRC.

Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers

Combining adaptive and innate immunity induction modes, the repertoire of immunoglobulin M (IgM) can reflect changes in the internal environment including malignancies. Previously, it was shown that a mimotope library reflecting the public IgM repertoire of healthy donors (IgM IgOme) can be mined for efficient probes of tumor biomarker antibody reactivities. To better explore the interpretability of this approach for IgM, solid tumor-related profiles of IgM reactivities to linear epitopes of actual tumor antigens and viral epitopes were studied. The probes were designed as oriented planar microarrays of 4526 peptide sequences (as overlapping 15-mers) derived from 24 tumor-associated antigens and 209 cancer-related B cell epitopes from 30 viral antigens. The IgM reactivity in sera from 21 patients with glioblastoma multiforme, brain metastases of other tumors, and non-tumor-bearing neurosurgery patients was thus probed in a proof-of-principle study. A graph representation of the binding data was developed, which mapped the cross-reactivity of the mixture of IgM (poly)specificities, delineating different antibody footprints in the features of the graph-neighborhoods and cliques. The reactivity graph mapped the major features of the IgM repertoire such as the magnitude of the reactivity (titer) and major cross-reactivities, which correlated with blood group reactivity, non-self recognition, and even idiotypic specificities. A correlation between an aspect of this image of the IgM IgOme, namely, small cliques reflecting rare self-reactivities and the capacity of subsets of the epitopes to separate the diagnostic groups studied was found. In this way, the graph representation helped the feature selection in its filtering step and provided reduced feature sets, which, after recursive feature elimination, produced a classifier containing 51 peptide reactivities separating the three diagnostic groups with an unexpected efficiency. Thus, IgM IgOme approaches to repertoire studies is greatly augmented when self/viral antigens are used and the data are represented as a reactivity graph. This approach is most general, and if it is applicable to tumors in immunologically privileged sites, it can be applied to any solid tumors, for instance, breast or lung cancer.

Chemotherapy-Induced Broadly Reactive Autoantibodies in a Colon Cancer Patient

The link between cancer and autoimmunity is well known. However, the extent to which chemotherapy induces autoimmune responses is still unclear. Here, we quantified IgM responses to various human tissues and patient tumors before and during adjuvant chemotherapy (seven cycles of the FOLFIRI plus cetuximab regimen) with metastasized colorectal cancer. IgM levels against all tissues tested increased shortly after the first cycle and further increased in the second and third cycles. Autoimmune responses then declined during cycles four through seven, but remained above baseline for most tissues. Our results suggest that chemotherapy can induce wide-reactive autoimmune responses. Monitoring self-reactive IgM responses during treatment may help alleviate the side effects associated with autoimmunity.

Chemotherapy-Induced, Broadly Reactive Autoantibodies in a Colon Cancer Patient

The link between cancer and autoimmunity is well-established. For example, increased levels of autoantibodies are frequently found in cancer patients, and autoimmune diseases are linked to an increased risk for certain neoplasms. However, the extent to which chemotherapy induces autoimmune reactions remains largely elusive. Here, we quantified immunoglobulin M (IgM) responses to various human tissues and the patient's tumor before and during adjuvanted chemotherapy (seven cycles of the FOLFIRI regimen (folinic acid/fluorouracil/irinotecan) plus cetuximab) of a patient with metastasized colon cancer. IgM levels against all investigated tissues increased shortly after the first cycle and were further boosted by cycles two and three. Autoimmune responses then decreased during cycles four to seven but remained above baseline levels for most tissues. Our findings suggest that chemotherapy can induce broadly reactive autoimmune responses. Monitoring self-reactive IgM responses during treatment may help alleviate autoimmunity-related adverse events.

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.

Isotypic analysis of anti-p53 serum autoantibodies and p53 protein tissue phenotypes in colorectal cancer

The presence of IgA- and IgM-specific autoantibody (AAb) isotypes and their relationship to p53 tissue expression patterns are not well understood. This study aims to investigate the clinical utility of the anti-p53 AAb isotypes and tissue positivity in colorectal cancer (CRC). We analysed anti-p53 IgG, IgM, and IgA AAbs in sera of 99 CRC patients and 99 non-cancer control subjects. Corresponding tissue expression of the p53 protein was evaluated by immunohistochemistry (IHC). Anti-p53 AAbs of the IgG isotype were present in the sera of 21 out of 99 patients (21%), while IgM AAbs were observed in 9 (9%) and IgA in 2 (2%) CRC patients. Anti-p53 AAbs of all three isotypes were generally associated with IHC staining indicative of mutated TP53. Seropositive anti-p53 IgM cases in the absence of anti-p53 IgG were linked to wild-type p53. Anti-p53 IgA in the absence of IgG AAbs was detected in two non-cancer controls indicating a potential p53 epitope mimicry. Although seropositivity was not associated with patient survival (P = 0.650), mutant-pattern p53 tissue expression was associated with reduced 5-year overall survival (P = 0.032), however, it was not an independent prognostic marker (Multivariate Cox regression, P = 0.193). In conclusion, immunoglobulin isotyping revealed that anti-p53 IgM and IgA AAbs were predominantly concurrent with anti-p53 serum IgG and the mutant-pattern p53 tissue phenotype. IgM and IgA seropositive cases in absence of anti-p53 IgG were linked to wild-type p53 tissue phenotype indicating early anti-p53 immune responses preceding isotype class-switch (IgM) or p53 antigen mimicry (IgA).

Application Progress of Organoids in Colorectal Cancer

Currently, colorectal cancer is still the third leading cause of cancer-related mortality, and the incidence is rising. It is a long time since the researchers used cancer cell lines and animals as the study subject. However, these models possess various limitations to reflect the cancer progression in the human body. Organoids have more clinical significance than cell lines, and they also bridge the gap between animal models and humans. Patient-derived organoids are three-dimensional cultures that simulate the tumor characteristics in vivo and recapitulate tumor cell heterogeneity. Therefore, the emergence of colorectal cancer organoids provides an unprecedented opportunity for colorectal cancer research. It retains the molecular and cellular composition of the original tumor and has a high degree of homology and complexity with patient tissues. Patient-derived colorectal cancer organoids, as personalized tumor organoids, can more accurately simulate colorectal cancer patients’ occurrence, development, metastasis, and predict drug response in colorectal cancer patients. Colorectal cancer organoids show great potential for application, especially preclinical drug screening and prediction of patient response to selected treatment options. Here, we reviewed the application of colorectal cancer organoids in disease model construction, basic biological research, organoid biobank construction, drug screening and personalized medicine, drug development, drug toxicity and safety, and regenerative medicine. In addition, we also displayed the current limitations and challenges of organoids and discussed the future development direction of organoids in combination with other technologies. Finally, we summarized and analyzed the current clinical trial research of organoids, especially the clinical trials of colorectal cancer organoids. We hoped to lay a solid foundation for organoids used in colorectal cancer research.