Intratumor Bacterial Presence and Serum Amyloid A in Colorectal Cancer


 Background & Aims:The initiation, development, and progression of many cancers, including colorectal cancer (CRC), are associated with environmental factors. A significant link exists between specific bacterial infections and cancer incidence, with a strong association between chronic infection, chronic inflammation and colorectal carcinogenesis. Recently, we reported significantly increased levels of lipopolysaccharide in CRC patient blood, compared to that of healthy individuals. By analysing CRC tumors, this study aims to contribute to the identification of (novel) markers/factors associated with CRC tumorigenesis.Methods: Colorectal tumor samples from newly diagnosed (histologically confirmed) CRC patients (n = 24) and morphologically normal colon biopsies (n = 10) were collected and analysed in a cross-sectional study. Immunohistochemistry protocols and statistical signal analysis were used to detect specific bacteria and proteins of interest in human colorectal tissue. Furthermore, the presence of structural protein changes in CRC tumor tissues, compared to control tissues, was investigated using the fluorescent amyloidselective Amytracker™ 630 marker and confocal microscopy.Results: We show an intratumor bacterial presence in CRC patients, with high levels of Escherichia coli strongly associated with CRC. High levels of intratumor serum amyloid A are also strongly associated with CRC. Furthermore, Helicobacter pylori is elevated, but to a smaller degree, and only when we account for data imbalance. We also report a significantly enhanced amyloid-specific fluorescence signal in CRC tumors, compared to control tissues.Conclusions: The role that infections play in a variety of cancers, including CRC, is increasingly recognized, and we provide evidence of a bacterial presence in CRC tumors. The analysis of CRC tumors, in addition to CRC blood, offers unique opportunities to investigate factors that may fuel colorectal carcinogenesis, and to ultimately identify novel markers that are associated with CRC.


Introduction
Patients diagnosed with advanced stages of colorectal cancer (CRC) have a poor prognosis (low 5-year survival rates) 1,2 , with increased incidence and mortality of CRC among young adults being prevalent 3 .
CRC is a heterogeneous disease with various contributing factors involved in the carcinogenic process, including exogenous factors (environmental insults) and endogenous factors (genetic susceptibility) 4 (see Fig. 1). The immune system, intestinal microbiota, environmental and lifestyle risk factors, as well as genetic factors are all involved in the pathogenesis of CRC 5 . The vast majority of CRC cases are sporadic and non-inherited 6-8 , which necessitates further investigation regarding environmental risk factors, including microbial exposures. Importantly, emphasis has again recently been placed on the human tumor microbiome across several cancer types 9 .
The intestinal micro ora provides protection against pathogens and has homeostatic immune and metabolic functions 10 . A breakdown of the physiological balance in the gut ora composition can lead to changes in the local immune system, causing pathology 11 . The involvement of disruptive changes in the gut microbiota balance (gut dysbiosis) in the pathogenesis of several chronic in ammatory pathologies, including cancers such as CRC, is currently a main research focus 2,12−14 . Importantly, a signi cant interaction exists between the intestinal microbiota and CRC pathogenesis, with the immune system playing a central role in this cross-talk 14 .
When the ratio of protective to pro-in ammatory and pro-tumorigenic micro ora becomes deregulated, it can lead to intestinal in ammation via persistent immune dysregulation 10,11 . Chronic in ammatory responses result in a cascade of events, where secreted in ammatory mediators can in uence neoplastic development, cell proliferation, metastasis, and angiogenesis, thereby creating a unique pro-neoplastic or tumor-supporting microenvironment 15,16 . Chronic in ammation thus increases the risk for the development of CRC 17,18 , forming a major part of CRC tumorigenesis [19][20][21] . However, a bidirectional relationship exists between the gut microbiota and the immune system: gut dysbiosis affects host immunity, but mucosal immunity can also in turn modulate the microbiota 14 .
Chronic in ammation in the tumor microenvironment triggers and promotes tumor growth and invasion, angiogenesis, and metastasis 22,23 . Immune cells are actively involved in the in ammatory process, where immune cell in ltrates produce pro-tumorigenic in ammatory cytokines and chemokines 10,24 .
Cytokines and chemokines may act as tumor growth/survival factors by promoting angiogenesis and by suppressing immune-mediated tumor elimination 10 . Immune cells in the tumor microenvironment, together with their secreted growth factors and various signaling molecules, therefore play important roles in promoting the proliferation and survival of tumor cells, and in driving tumor progression 25,26 . In CRC, the activation of speci c transcription factors, the production of in ammatory cytokines and chemokines, and leukocyte in ltration are all factors contributing to the pathology of chronic in ammation 27 .
Cancer cells synthesize and release factors that can fuel the neoplastic process, by recruiting more in ammatory cells and stimulating the in ammatory cascade 25 . Importantly, during tumor progression, bacteria and microbial products can invade the local tumor environment as a result of damage to the epithelial barrier. These barrier defects result in tumor-induced in ammation, stimulated by the invasion of bacteria 29 . A bacterial presence in tumors can therefore promote and accelerate the progression of CRC 29 . This paper will investigate the presence of bacteria (the Gram-negative bacteria Helicobacter pylori (H. pylori) and Escherichia coli (E. coli)) and the bacterial in ammagen lipopolysaccharide (LPS) in the local tumor environment of CRC patients, compared to healthy colorectal tissue biopsies. It is well-known that H. pylori can colonize the gastro duodenal mucosa of humans 30 . An association exists between H. pylori infection and gastric adenocarcinoma, with H. pylori infection also being a risk factor for mucosaassociated lymphoid tissue (MALT) lymphoma 30 . Interestingly, there is also likely an association between H. pylori infection and CRC risk, but causality remains uncertain 31 . This therefore served as the rationale for the detection of H. pylori in CRC tumor tissue samples.
Furthermore, the presence of another in ammatory marker, serum amyloid A (SAA), which is associated with the presence of bacterial products such as LPS, will also be investigated in CRC tumors, compared to control tissues. Importantly, elevated levels of the acute-phase (multifunctional) protein SAA serve as a sensitive marker for acute and chronic in ammatory diseases and have been implicated in colorectal carcinogenesis 25 . In addition, structural changes in proteins associated with CRC tumor cells and/or their microenvironment, using a uorescent amyloidselective marker, will be investigated. When normally soluble proteins undergo a (amyloidogenic) pathological con gurational change and become misfolded, aggregate, and form brils, they become insoluble (resistant to normal proteolytic digestion) 25,32,33 . The extracellular deposition of such amyloid β-pleated sheet brils is associated with several chronic (ongoing) in ammatory disease states 32 .
The impact of environmental factors on CRC initiation, development, and progression, represents a growing research eld 7,8 . The aim of this paper is to demonstrate, by analysing CRC tumors, that an intratumor bacterial presence, together with the presence of in ammatory markers/mediators (speci cally SAA) and structural protein changes, are involved in CRC tumor pathogenesis.

Ethical statement
Ethical clearance for the collection of stored normal colorectal tissue biopsies from healthy individuals (serving as control tissues), as well as tumor tissues from patients with newly diagnosed colorectal adenocarcinoma was obtained from the Health Research Ethics Committee (HREC) of Stellenbosch University (ethics reference: 6585). All study participants signed an informed consent form prior to participation in the study and sample collection. This study, including sample collection and sample processing, was conducted according to the guidelines set by the Declaration of Helsinki.
Sample collection and study population Table 1 shows the sample demographics of healthy and CRC populations. Formalin-xed, para nembedded (FFPE) morphologically normal colon biopsies from 10 healthy individuals and FFPE colorectal tumor resections (n=18) and biopsies (n=6) from 24 patients with newly diagnosed (histologically con rmed) colorectal adenocarcinoma were collected from the National Health Laboratory Service at Tygerberg Hospital, Cape Town, South Africa. The stage of all recruited patients was assessed, with stage 1 (n=1), stage 2 (n=10), stage 3 (n=8), and stage 4 (n=5) CRC patients included. The American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) 8th edition staging system was used to assess the stage of patients who had tumor resections, while CT scans were used to assess the stage of patients who had biopsies taken. None of the CRC patients had any cancer treatment at the time of sample collection (no neoadjuvant chemotherapy or radiotherapy). Genetic predisposition did not form part of the exclusion criteria.

Tissue preparation
An automated tissue processer (Tissue-Tek® VIP™ Vacuum In ltration Processor) was used for tissue processing, which runs for a total time of ± 12 hours according to the protocol in Supplementary Table  S1. Following sectioning of blocks (using the Leica RM 2125 rotary microtome (SMM instruments, Germany)), tissue sections were transferred to a water bath and placed onto standard microscope slides for haematoxylin and eosin (H&E) staining, or positively charged microscope slides for immunohistochemistry and for confocal analysis. Prior to staining, slides were incubated at approximately 60˚C for about one hour for the removal of wax. Ultimately, following staining of the sections, a glass coverslip was mounted onto the tissue using distyrene, a plasticizer, and xylene (DPX) mounting media and left to dry for 48 hours (Dako uorescence mounting medium was used for confocal analysis).

Haematoxylin and eosin (H&E) staining
To study the morphology and structure of healthy colorectal tissues and CRC tumor tissues, the H&E stain was used to stain tissue sections. Slides were placed into a plastic staining rack, which was placed into the Leica Auto Stainer XL (SMM instruments, Germany). The autostainer follows a pre-programmed procedure, including steps for the depara nisation, rehydration, and clearing of the tissue (see Supplementary Table S2). Zeiss Axioskop 2 Microscope (Carl Zeiss, Germany) was used to view the slides and examine staining, with Zen Lite software (v2.3, Germany) used to capture the images.

Immunohistochemistry
All immunohistochemical staining procedures were performed on the BOND-MAX automated system (Leica, Wetzlar, Germany), using the Bond Polymer Re ne Detection System (Leica Bond TM ) (Cat no.

DS9800
). An automated immunohistochemical staining protocol was used, including a standard dewax (using Bond Dewax Solution (Leica Bond TM ) (Cat no. AR9222)) and rehydrate program, as well as pretreatment for antigen retrieval. Refer to Table 2 for the automated staining protocol. Tissues were either incubated in Bond Epitope Retrieval (ER) Solution 2 (Leica Bond TM ) (Cat no. AR9640) or Bond ER Solution 1 (Leica Bond TM ) (Cat no. AR9961), prior to incubation with the primary antibody. Following a wash step (standard wash protocol with Bond Wash Solution (Leica Bond TM ) (Cat no. AR9590)), endogenous peroxidases in tissue sections were blocked. After incubation with the primary antibody, the chromogen diaminobenzidine (DAB) was used to visualize positive antibody-antigen reactions, and counterstained with haematoxylin to observe tissue morphology. Following completion of automated staining, the samples were dehydrated (refer to Supplementary Table S3). Zeiss Axio Observer 7 inverted Microscope (Carl Zeiss, Germany) with Axiocam 305 colour camera, using the bright eld modality and 5x objective, was used to view the slides and examine staining.
Immunohistochemical protocols were developed and optimized to detect the proteins of interest in the tissue samples. The following antibodies were used: anti-H. pylori antibody, anti-E. coli antibody, anti-E. coli LPS antibody, and anti-SAA antibody. The optimal dilution factor of each antibody (step 9 in Table 2) (all antibodies were diluted in Bond Primary Antibody Diluent (Leica Bond TM ) (Cat no. AR9352)) and the optimal ER buffer in each case (step 3 in Table 2) were optimized. Positive (tissue) controls for H. pylori, E. coli, LPS, and SAA were used to con rm that each antibody binds to its speci c immunogen. Negative antibody controls were also included. Negative and positive control images are shown in Supplementary   Fig. S1-S4. Zeiss Axioskop 2 Microscope (Carl Zeiss, Germany) was used to view these control slides and examine staining, with Zen Lite software (v2.3, Germany) used to capture the images.
To detect H. pylori in tissue sections, Anti-Helicobacter pylori antibody [EPR10353] (rabbit monoclonal IgG, ab172611, Abcam) was used (diluted 1:250). ER1 buffer was used for heat-induced epitope retrieval (HIER). H. pylori human gastritis tissue (from a stomach biopsy), as recommended by the antibody datasheet, was used as a positive tissue control. For detection of E. coli, E. coli serotype 0157 Monoclonal Antibody (I88H) (mouse monoclonal IgG, MA1-7303, Invitrogen) was used (diluted 1:100), using ER2 buffer. For a positive control, healthy platelet poor plasma (PPP) was exposed to a colony of E. coli cells (E. coli ATCC 13706). The Cytospin® 3 Cell Preparation System was used to deposit a monolayer of cells in a de ned area onto a microscope slide, using centrifugal force. A volume of 150 μL of the exposed PPP sample was added to the sample chamber, and centrifuged at a speed of 2000 rpm for 3 minutes. To detect bacterial LPS in tissue sections, Anti-E. coli LPS antibody [2D7/1] (mouse monoclonal IgG, ab35654, Abcam) was used (diluted 1:100), using ER2 buffer. Rat intestinal tissue, as recommended by the antibody datasheet, was used as a positive tissue control. To detect SAA in tissues, immuno-puri ed rabbit anti-human SAA antibody (kindly provided by Prof. Frederick C. de Beer and Dr. Marcielle de Beer from the University of Kentucky), with a concentration of 4.1 mg mL -1 , was used (diluted 1:1500), using ER1 buffer. Human tonsil tissue was used as a positive tissue control. To simplify automated imaging of the tissue randomly positioned on the different slides, a block was drawn around each tissue section to fully encompass the outer boundaries of the speci c section. The coordinates of the four corners of this box shaped perimeter were then used to set up a tile scan in the Zen Pro software (v2.5, Germany). The software automatically calculated the number of images to acquire to scan the complete section. Importantly, tiles containing artefacts were excluded from analysis, as well as tiles containing no tissue in the eld of view. About 97 tile images were analysed per CRC tumor tissue sample, and ± 11 tile images per healthy colorectal tissue sample. The stitching function of the analyses section of the Zen software, which allows for the correct alignment of the tiles to view a complete section, was applied. However, only the individual tiles were used for statistical analyses. The intensity and exposure time settings were 8.3% and 0.08 seconds, respectively.

Statistical analysis
The immunohistochemistry signal was analysed in the following straightforward manner. 1D colour histograms for each of the four antibody signals were formed based on manually identi ed regions across multiple images. These histograms are shown in Figure 7A. These (normalized) histograms were then applied across each image to determine a total signal strength. A logistic statistical model (using glm in R 4.0.2) was then applied to determine the strength of association (and con dence intervals) between the signal strength and disease status. As the dynamic range of the signal is very large, a log transform was performed to the signal strength. Odds Ratios are reported on the log scale after z-score standardisation to allow meaningful comparison between stains. Lastly, as the datasets were imbalanced, with more disease images than control images, we performed an additional analysis with inverse frequency weighting of the logistic loss. Results are consistent between these weighted and unweighted models with the exception of H. pylori, where we make more conservative claims. The unweighted model does not account for the imbalance regarding the number of control tissue and CRC tumor tissue samples, and also not for the imbalance in the number of images per sample, while the weighted model accounts for these data imbalances (making it unbiased).
Data of the confocal analysis were tested for normality using the Shapiro-Wilk normality test, and analysed using the Mann-Whitney non-parametric test in GraphPad Prism 7.04 (the image plot of the confocal data was prepared in GraphPad Prism 7.04). Statistical signi cance was accepted at p<0.05.

Results
Patho-morphology of colorectal cancer (CRC) tumor tissues

The presence of an intratumor bacterial component and in ammatory marker
Representative tile images of (A) healthy colorectal tissue biopsies and (B) CRC tumor tissues stained with anti-H. pylori antibody (Fig. 3), anti-E. coli antibody (Fig. 4), anti-E. coli LPS antibody (Fig. 5), and anti-SAA antibody (Fig. 6) are shown. Also refer to Supplementary Fig. S9-S12 for tile images that are stitched together of (A) healthy colorectal tissue biopsies and (B) CRC tumor tissues, stained with anti-H. pylori antibody, anti-E. coli antibody, anti-E. coli LPS antibody, and anti-SAA antibody, respectively.
Refer to Fig. 7A for 1D colour histograms of manually extracted positive signal for each of the four antibodies. The areas identi ed as positive signal for the anti-E. coli LPS antibody and anti-SAA antibody deliver normally distributed histograms with clear peaks for all channels. However, the H. pylori signal and E. coli signal are less normally distributed than the signal of the anti-E. coli LPS and anti-SAA antibodies. Figure 7B shows box and whisker plots that compare the log signal present in healthy colorectal tissues and CRC tumor tissues, stained with anti-H. pylori antibody, anti-E. coli antibody, anti-E.
coli LPS antibody, and anti-SAA antibody, respectively. Table 3 indicates the Odds Ratios and con dence intervals (for the unweighted and weighted models) of the log signal for each antibody. It can be seen that both the E. coli and SAA signals are signi cantly elevated in CRC tumor tissues, compared to healthy colorectal tissues (this nding is consistent in both unweighted and weighted models). It is important to note that, when the data is weighted, high levels of both E. coli and SAA have an even stronger association with CRC. The ndings for H. pylori, on the other hand, are not consistent across the unweighted and weighted models and the effect size is smaller. When looking at the unweighted result, there is no signi cant difference in the H. pylori signal between healthy colorectal tissues and CRC tumor tissues. However, when the data is weighted (when the data imbalance is accounted for), the H. pylori signal becomes signi cantly elevated in the disease population. High levels of H. pylori are therefore also associated with CRC, but to a smaller degree than E. coli and SAA. This is in line with the general understanding that H. pylori is predominantly present in the antrum of the stomach and the proximal duodenum. Lastly, there is no signi cant difference in the bacterial LPS signal between healthy colorectal tissues and CRC tumor tissues.  Figure 8B compares the distribution of the MFIs in a scatterplot, indicating that CRC tumor tissues contain signi cantly greater amyloid-speci c signal, compared to healthy colorectal tissues.
Additionally, in order to visualize the structure of the tissue sections in combination with the amyloidspeci c uorescence signal, two healthy colorectal tissue samples and two CRC tumor tissue samples were stained with Hoechst uorescent dye and the amyloid-selective Amytracker™ 630 marker. In this way, the nuclei of the tissues were stained, and could be visualized together with the amyloid-speci c signal present in the tissue sections (refer to Supplementary Fig. S14 for confocal micrographs and corresponding transmitted light images).

Discussion
We have previously analysed CRC patient blood and reported that circulating levels of LPS are signi cantly elevated in the CRC population, compared to controls 37 . The aim of this study was to analyse the local tumor environment of these patients (to describe CRC tumor physiology), to identify factors that are involved in CRC tumor pathogenesis. Refer to Fig. 9 for an overview of the ndings of CRC patient blood sample and tumor tissue analyses.
The tumor physiology of CRC patients was analysed by rst investigating the patho-morphology of CRC tumor tissues. A clear difference was observed in the structure and appearance of cells when comparing normal colorectal tissues to CRC tumor tissues, by using the H&E stain. This is as a result of aberrations in cell proliferation and differentiation in cancer patients 38 . Within the lumen of malignant glands, mucin and (granular) necrotic material were frequently observed. CRC is often associated with dirty necrosis within glandular lumina 39 . There was also an overproduction of mucin in some tumors, with excess mucin in ltrating the stroma. Importantly, mucin is involved in the metastatic process of CRC 40 . The tumor stroma is also an important role player in tissue invasion and in driving tumor progression 41,42 . It has been suggested that a reduction of the epithelial cells/stroma (E/S) ratio may serve as indication of tumor progression (a poor prognosis) in CRC patients 42 . The desmoplastic stromal reaction observed in CRC tumors is associated with a poor prognosis in these patients 43,44 . Furthermore, the host antitumor immune response affects tumor progression and recurrence 45  The presence of bacteria in CRC tumor tissues (focusing on the Gram-negative bacteria H. pylori and E. coli), compared to healthy colorectal tissues, was also investigated in this paper. Importantly, there is a signi cant link between speci c bacterial infections and cancer incidence 47,48 31,56,57 . The hypothesis that by-products of H. pylori infection may increase the risk of CRC, is supported by ndings showing that increased serum levels of gastrin (hypergastrinemia) are positively associated with an increased risk of CRC [57][58][59] . Hypergastrinemia may be involved in CRC pathogenesis by inducing increased cell proliferation in the colonic mucosa 60 . It is therefore possible that H. pylori infection itself is not the only factor implicated in an increased CRC risk, which highlights the complex (and less established) relationship between H. pylori and CRC 57 . The results of this paper showed that, when accounting for the imbalance in the data, high levels of H. pylori are associated with CRC, but have a small effect size.
Mucosa-adherent E. coli, a commensal bacteria forming part of the human gut microbiota, is strongly associated with CRC 61-65 . A signi cantly modi ed intestinal microbiota composition is evident in CRC patients, compared to controls, with an increased diversity of Gram-negative bacteria subgroups being present 71 . LPS is a very potent in ammagen and an essential component of the outer membrane of Gram-negative bacteria 72 .
This bacterial antigen induces innate immunity and can cause intestinal in ammation when recognized by toll-like receptor 4 10 , with this signaling pathway being actively involved in the metastatic cascade 73 .  25,77 . SAA also contains binding sites for components of the ECM, laminin and heparin/heparan sulfate 25,74 . The role of SAA as an ECM adhesion protein contributes to its proposed role in tumorigenesis 25,74 .
We therefore showed that there is an intratumor bacterial presence and (upregulated) expression of SAA

Conclusions
When the physiological balance of the gut microbial composition becomes compromised, it may result in a pro-in ammatory environment, contributing to the development of CRC 84 . This supports the view that the onset of many cancers, including CRC, is associated with environmental or external factors 6 . We have recently analysed the systemic environment of CRC patients, where circulating LPS and other circulating biomarkers, indicative of systemic in ammation and abnormal clot formation, were investigated. A main nding was that elevated circulating LPS levels are predictive of an increased chance of CRC 37 . Here, we demonstrated that there is an intratumor bacterial presence in CRC patients, showing that high levels of E. coli are strongly associated with CRC, and that H. pylori is also signi cantly elevated in CRC tumor tissues, compared to healthy colorectal tissues. Importantly, we also showed that the presence of high levels of intratumor SAA is strongly associated with CRC.
The development of novel, non-invasive, sensitive, and speci c early detection methods (such as tumor biomarkers), together with early diagnosis and effective treatment strategies, are pivotal to minimize and manage the vast number of individuals affected by CRC 19 . To study the local tumor environment of CRC patients, in combination with analysing their systemic environment, offers unique opportunities for the identi cation of novel markers that are associated with CRC. We conclude that the heterogeneity of CRC necessitates the employment of holistic approaches when investigating colorectal carcinogenesis, to improve our overall understanding of the disease.

Declarations Data Availability
The datasets analysed for this study can be found on Google Drive: https://drive.google.com/drive/folders/1sOcsKTQabwx-HcvpkG6gt7eKMysl-w-V?usp=sharing.

Figure 1
Different aspects that in uence colorectal cancer (CRC) pathogenesis, highlighting the involvement of exogenous (environmental) factors.