Phenylacetaldehyde induced apoptosis in colorectal cancer

Abstract

Disclosed herein are methods to treat and detect colorectal cancer using a specific microbiome signature screening and phenylacetaldehyde dosage in blood serum as detection tools. Also, disclosed herein is a method of treating colorectal cancer using phenylacetaldehyde.

Description

[0001] Docket No.103361-541WO1 PHENYLACETALDEHYDE INDUCED APOPTOSIS IN COLORECTAL CANCER CROSS REFERENCE TO RELATED APPLICATIONS This application claims priority to, and the benefit of, U.S. Provisional Patent Application No. 63 / 594,146, filed October 30, 2023, which is incorporated by reference herein in its entirety. FIELD Disclosed herein are methods for detecting and treating colorectal cancer. BACKGROUND Colorectal cancer (CRC) is the third most common cancer worldwide and third most common cause of cancer-related death in the United States. The prognosis of patients with colorectal is ultimately linked to time of detection. When colorectal cancer is found at an early stage before it has spread, the 5-year relative survival rate is about 90%. For this reason, the American Cancer Society recommends a CRC screening for average risk people at age 45 years, with colonoscopy as the gold standard. Unfortunately, the Centers for Disease Control and Prevention estimates that about 22% of the population in that age range are not screened. The American Cancer Society evaluated that the two main reasons mentioned for not getting a colonoscopy were 1) concern about complexity and cost, including taking time off; 2) fear of a painful / difficult test and the embarrassment to discuss CRC screening with their doctor. Alternatives to colonoscopy would alleviate these concerns. There are limited options available, one being an at-home commercial test named Cologuard® (Exact Science, Madison, WI) based on the detection of certain DNA markers and blood in stool. Although it addresses the two main reasons mentioned above, it still has limitations. Firstly, Cologuard® offers benefits of comfort and convenience, but the Cologuard test is not a replacement for a colonoscopy due to its lower efficiency (92% predictive power). Secondly, this test has a high rate of false negative results (people with cancer receiving a negative result) of about 8% and even higher false positive results (people without cancer receiving a positive result) of about 13%. Finally, there is a long turnover between the moment the patient receives the at-home kit and the time of receiving the results of about 3 weeks. Therefore, there is a need in the art to continually improve CRC screening rates, efficacy, and improve earlier detection and clinical outcomes. Docket No.103361-541WO1 CRC carcinogenesis is complex and of long duration and impacted by a multitude of genetic and environmental factors. Accumulating evidence demonstrates that the host microbiota is a key mediator of colon carcinogenesis, potentially through food components that alter the structure and function of microflora leading to indirect systemic effects or locally acting oncometabolites and tumor-suppressive metabolites. For instance, short-chain fatty acids produced by butyrate-producing bacteria have been found to inhibit inflammation and colon carcinogenesis, while other microbial metabolites, such as genotoxic hydrogen sulfide converted from dietary sulfur by sulfur-metabolizing microorganisms, are hypothesized to enhance the colon carcinogenesis cascade. Phenylalanine (Phe) has been shown to be downregulated in gastrointestinal cancer patients, potentially serving as a useful marker for cancer patients. Interestingly, phenylalanine is converted to phenylacetaldehyde (PAA) by oxidative decarboxylation, a process commonly involving gut microbiota although the many factors impacting production remain poorly defined. PAA is also an important rose flower and tomato volatile aroma, which has potential health- promoting benefits. Recently, researchers have shown that PAA inhibits the maintenance of breast cancer stem cells through the reactive oxygen species (ROS)-dependent Stat3 / IL-6 signal and decreased xenograft growth in vivo. The potential for the human microbiome to impact colon carcinogenesis via a multitude of mechanisms is not fully understood. There is a need to further examine mechanisms in vitro and in vivo to study the ability of PAA to impact colon cancer cell biology and response to therapeutics. Given the limitations described above, alternatives to colonoscopy are required as a response to the shortcomings of traditional diagnostics to enhance sensitivity and specificities. SUMMARY In one aspect, disclosed herein is a method of treating colorectal cancer in a subject, comprising: obtaining a sample from the subject; detecting the presence or absence of gut microbiota; wherein said gut microbiota comprises positively correlated bacteria that produce phenylacetaldehyde (PAA) and negatively correlated bacteria that do not produce PAA, wherein the positively correlated bacteria comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463, and Docket No.103361-541WO1 wherein the negatively correlated bacteria comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670, wherein the subject is predicted to have colorectal cancer if the amount of positively correlated bacteria is lower in the subject than in comparison to a control or if the amount of negatively correlated bacteria is higher in the subject than in comparison to a control; and administering a therapeutically effective dose of PAA to the subject who is predicted to have colorectal cancer. In some embodiments, the gut microbiota is determined by performing 16S rRNA based qPCR or metagenomics sequencing. In some embodiments, the sample is serum, blood or fecal matter. In one aspect, disclosed herein is a method of detecting colorectal cancer in a subject, comprising: obtaining a sample from the subject; performing metagenomics sequencing or qPCR on the sample; and determining positively and negatively correlated bacterial species to PAA production, wherein lower levels of PAA are negatively correlated to at least one bacterial species, wherein the negatively correlated bacterial species comprise Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670, and wherein higher levels of PAA are positively correlated to at least one bacterial species, wherein the positively correlated bacterial species comprise Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463. In one aspect, disclosed herein is a method of determining a gut microbiota signature for cancer detection, comprising: obtain a serum sample from a subject and a control; determining the PAA levels in the serum sample; obtaining a fecal sample from the subject and the control; performing metagenomic sequencing or qPCR on the fecal sample; and Docket No.103361-541WO1 determining bacterial species which are positively and negatively correlated to the PAA levels in the serum sample, wherein positively correlated bacterial species produce PAA and negatively correlated bacterial species do not produce PAA, wherein the subject has cancer if the negatively correlated bacterial species are higher than positively correlated bacterial species in the subject as compared to the control. In some embodiments, the cancer is colorectal cancer. In one aspect, disclosed herein is a method of treating colorectal cancer in a subject comprising: administering a therapeutically effective dose of phenylacetaldehyde (PAA) as an adjunct with a chemotherapy drug to the subject, wherein the chemotherapy drug is 5-fluorouracil. In one aspect, disclosed herein is a method for predicting a treatment response to cancer immunotherapy, comprising: obtaining a sample from a cancer subject; and detecting the presence or absence of gut microbiota, wherein said gut microbiota comprises good responder bacteria that are positively correlated to immunotherapeutic response and poor responder bacteria that are negatively correlated to immunotherapeutic response, wherein the good responder bacteria comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944 or Butyrivibrio txid1458463, and wherein the poor responder bacteria comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743 or Bacillus txid492670, wherein the subject is predicted to positively respond to the cancer immunotherapy treatment if the good responder bacteria are higher in the subject than in comparison to a control, or wherein the subject is predicted to positively respond to the cancer immunotherapy treatment if the poor responder bacteria are lower in the subject than in comparison to a control; and administering a therapeutically effective dose of PAA to the subject that is predicted not to positively respond to the cancer immunotherapy treatment. In some embodiments, the cancer immunotherapy is an anti-PD-1 treatment or an anti- Docket No.103361-541WO1 CTLA-4 treatment. In one aspect, disclosed herein is a kit for detecting colorectal cancer (CRC) in a sample from a subject, comprising: a panel of 10 bacterial species positively correlated with increased PAA levels in the subject, wherein the positively correlated bacterial species comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463; and a panel of 10 bacterial species negatively correlated with decreased PAA levels in the subject, wherein the negatively correlated bacterial species comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670, wherein the subject has CRC if the sample has more negatively correlated bacterial species as compared to positively correlated bacterial species. BRIEF DESCRIPTION OF FIGURES The accompanying figures, which are incorporated in and constitute a part of this specification, illustrate several aspects described below. FIGS. 1A, 1B, 1C, 1D, 1E, 1F, 1G and 1H depict PAA level in serum and its related gut microbiota signature are altered in CRC patients. FIG. 1A shows schematic representation of the clinical study cohort. FIG. 1B shows concentrations of PAA in the serum of non-CRC control patients and CRC patients measured by GC-MS / MS (n=30 per group, ***p<0.001, unpaired Student’s t-test). FIG. 1C shows ROC analysis showing the sensitivity and specificity of PAA level in serum to discriminate control patients from CRC patients. FIG. 1D shows schematic representation of the clinical validation cohort. FIG. 1E shows concentrations of PAA in the serum of non- CRC control patients and CRC patients measured by GC-MS / MS (***p<0.001, unpaired Student’s t-test). FIG. 1F shows ROC analysis showing the sensitivity and specificity of PAA level in serum to discriminate control patients from CRC patients. FIG. 1G shows volcano plot representing the correlation between the relative abundance of bacteria species and serum PAA levels calculated by p-values and Spearman’s correlation coefficient. Each dot represents a species. The red dots represent the top 10 bacteria species positively correlated to PAA Docket No.103361-541WO1 concentration, and the blue dots represent the top 10 bacteria negatively correlated to PAA concentration in CRC patients and non-CRC controls (n=30 per group). FIG. 1H shows microbial co-occurrence networks between the top 10 bacteria positively / negatively correlated to PAA using a cut off- of p<0.05, -0.5>r and r>0.5 (Spearman correlation coefficient). Red edges represent positive correlations, and blue edges indicate negative correlations. Edge thickness represents the correlation strength (r coefficient). Node size represents the relative abundance of bacteria. FIGS. 2A, 2B, 2C, 2D, 2E, 2F and 2G depict PAA inhibits CRC in vitro and in vivo. FIG. 2A shows cell viability of HCT116 and RKO was analyzed by ATP assay after incubation ZLWK^YDULRXV^FRQFHQWUDWLRQV^RI^3$$^^^^^^^^^^^^^^^^^^^^^^^^^^DQG^^^^^^^0^^IRU^^^^KRXUV^^),*^^^%^ shows organoid viability was assessed by ATP assay after incubation with various concentrations RI^3$$^^^^^^^^^^^^^^^^^^DQG^^^^^^0^^IRU^^^^KRXUV^^),*^^^&^VKRZV^UHSUHVHQWDWLYH^SLFWXUH^RI^ HCT116, RKO cell lines, FIG. 2D and two distinct CRC patient-derived oUJDQRLG^OLQHV^DIWHU^^^^ KRXUV^LQFXEDWLRQ^ZLWK^3$$^^^^^^^^DQG^^^^^0^^^^^;^^ZLWK^EULJKW^ILHOG^PLFURVFRS\^^5HG^DUURZV^ show collapsed dead organoids. The results are presented as the mean ± SEM. **p<0.01, ***p<0.001. FIG. 2E shows experimental design: NSG mice underwent subcutaneous flank injection with RKO cell line in two separate groups (control or PAA treated). When tumors reached approximately 200 mm3, mice from the PAA treated group received 20mg / kg of PAA injected intraperitoneally per day during 5 consecutive days over a period of 12 days (arrows). FIG. 2F shows tumor growth was monitored everyday using calipers. Data are represented as mean ± SE (n = 5 for each group); ***p<0.0001 using linear regression statistical test. FIG. 2G shows tumor size in mm3measured 21 days post randomization. Statistical analysis was done using Mann–Whitney test. FIGS. 3A, 3B, 3C and 3D depict PAA induces ER stress and autophagy in CRC cell lines. FIG. 3A shows volcano plot for differentially expressed genes comparing control condition WR^WUHDWPHQW^ZLWK^3$$^^^^^0^IRU^^^^KRXUV^LQ^+&7^^^^DQG^5.2^FHOO^OLQHV^^%OXH^UHSUHVHQWV^ downregulated genes; red represents upregulated genes; gray represents non-significant genes. FIG. 3B shows gene ontology analyses of significant differentially expressed genes. Top panel– Venn diagram representing the significantly enriched GO terms for HCT116 and RKO cell lines. Bottom panel – Enriched GO terms shared by HCT116 and RKO cell lines after 24 hours of 50 ^0^3$$^WUHDWPHQW^^ / RJ^^-fold changes > 1.5; FDR q-value<0.25. Gene ratio corresponds to the percentage of genes enriched in a GO term. FIG. 3C shows immunoblot analysis of ER stress and autophagy markers in HCT116 and RKO cell lines comparing control condition to PAA 10 ^0^RU^^^^^0^IRU^^^^KRXUV^^FIG. 3D shows immunoblot analysis of PI3K pathway, ERK Docket No.103361-541WO1 pathway, cell cycle markers and stress markers in HCT116 and RKO cell lines comparing FRQWURO^FRQGLWLRQ^WR^3$$^^^^^0^RU^^^^^0^IRU^^^^KRXUV^ FIGS. 4A, 4B, 4C, 4D, 4E and 4F depict PAA potentiates 5-FU effect in vitro on CRC cells and organoids and in vivo. FIG. 4A shows cell viability and FIG. 4B shows organoid viability were analyzed by ATP assay after incubation with PAA alone (0, 10, and 50 μM) or in combination with 5-)8^^^^^^0^^IRU^^^^KRXUV^^7KH^UHVXOWV^DUH^SUHVHQWHG^DV^WKH^PHDQ^^^6(0^^ Statistical analysis was done using Mann-Whitney test. *p<0.05, **p<0.01, ***p<0.001. FIG. 4C shows immunofluorescence staining of DAPI (blue), and Ki-^^^^JUHHQ^^LQ^+&7^^^^DQG^5.2^ cells treated with PAA alone or in combination with 5-FU for 24 hours. Histograms represent the TXDQWLILFDWLRQ^RI^SRVLWLYH^FHOOV^IRU^.L^^^DFFRUGLQJ^WR^WUHDWPHQWV. FIG. 4D shows immunohistochemical staining of hematoxylin and eosin, and Ki- ^^^LQ^WZR^GLVWLQFW^RUJDQRLG^ lines treated with PAA alone (10 or 50 μM) or in combination with 5-FU (10 μM) for 24 hours. FIG. 4E shows colony formation assay in HCT116 and RKO cells incubated with PAA alone (10 or 50 μM) or in combination with 5-FU (10 μM) for 144 hours. FIG. 4F shows left panel - Tumor growth of subcutaneous RKO xenograft treated by PAA and 5-FU alone or in combination compared to untreated condition (control). ***p<0.0001 using linear regression statistical test. Right panel-Comparison of tumor size in mm321 days after first day of treatment. Data are represented as mean ± SE (n = 5 for each group). Statistical analysis was done using Mann-Whitney test. *p<0.05, **p<0.01, ***p<0.001. FIGS. 5A, 5B, 5C, and 5D depict PAA induces ROS, DNA damage and cell cycle blockage. FIG. 5A shows Top Panel-Immunofluorescence staining of DAPI (blue), and Ȗ+^$; (green) in HCT116 and RKO cells treated with PAA alone or in combination with 5-FU for 24 hours. Bottom panel-Quantification of percentage of cell population showing more than two Ȗ+^$; foci per nucleus after 24 hours of PAA alone or in combination of 5-FU in HCT116 and RKO cell lines. FIG. 5B shows kinetic of total ROS production in HCT116 and RKO cell lines from 0 to 240 minutes after treatment of PAA 10 μM or 50 μM. Positive control conditions were treated with N-Acetylcysteine 100 μM. Negative control conditions were treated with N- Acetylcysteine 10mM. ***p<0.0001, **p<0.001, *p<0.05 using linear regression statistical test. FIG. 5C shows quantification of total ROS production 4 hours after treatment with PAA 10 μM or 50 μM in HCT116 and RKO cell lines. Data are represented as mean ± SE (n = 5 for each group). Statistical analysis was done using Mann-Whitney test. *p<0.05, **p<0.01, ***p<0.001. FIG. 5D shows cell cycle distribution after PAA and 5-FU treatment for 24 hrs quantified by PI staining and flow cytometry analysis. ^ Docket No.103361-541WO1 FIG. 6 shows schematic representation of underlying mechanism of PAA-induced cell death in CRC. ),*^^^^VKRZV^the chemical structure of Phenylacetaldehyde. FIG. 8 shows transcriptomic analysis of CRC cell lines treated with PAA. FIG. 9A and 9B show dose-dependent inhibition of CRC cell lines and patient-derived organoid treated with 5-)8^IRU^^^^KRXUV^ FIG. 9A shows viability of HCT116 and RKO CRC FHOO^OLQHV^DIWHU^^^^KRXUV^RI^LQFUHDVLQJ^GRVH^RI^^-FU assessed by CellTiter Glow 2.0. Results are normalized to their control conditions. FIG. 9B shows viability of two independent patient- GHULYHG^RUJDQRLG^&5&^OLQHV^DIWHU^^^^KRXUV^RI^LQFUHDVLQJ^GRVH^RI^^-FU assessed by CellTiter Glow 3D. Results are normalized to their control conditions. Statistical analysis was done using Mann-Whitney test. *p <0.05, **p<0.01, ***p<0.001. FIG. 10A and 10B show Combined treatment of PAA and 5-FU induces apoptosis in CRC cell lines. FIG. 10A shows Annexin V / PI VWDLQLQJ^RI^&5&^FHOO^OLQHV^DIWHU^^^^KRXUV^ treatment with PAA (l0μM or 50μM) and 5-FU (l0μM) was analyzed with an Annexin V / PI Apoptosis Detection Kit by flow cytometry. FIG. 10B shows quantification of the percentage of cell death in HCT11^^DQG^5.2^DIWHU^^^^KRXUV of treatment with PAA alone or in combination with 5-FU. FIG. 11 shows Molecular effects of PAA and 5-FU on survival of CRC cell lines. Western blot of proliferation and cell death marker comparing treatment for ^^ hours of PAA and 5-FU alone or in combination in two colorectal cancer cell lines. Actin is shown as a reference protein. FIG. 12 shows the use of a specific microbiome signature detection in patient’s stool (20 bacteria strains) as a predictive marker for immunotherapy resistance. The power value of or absence of the microbiome signature is interrogated to predict the immunotherapeutic response of D^FRKRUW^RI^^^^^^SDWLHQWV^^ZLWK^^PHODQRPD^^WUHDWHG^^ZLWK^^LPPXQRWKHUDS\^^^3'^^^DQG^^&7 / $^^ inhibitors). Taken together, the specific microbiome signature has a 95% prediction power to identify good responders from poor responders. This has potential across multiple cancers. DETAILED DESCRIPTION Disclosed herein are methods for treating and detecting colorectal cancer in a subject using predictive gut microbiota signature and phenylacetaldehyde (PAA) as a therapeutic agent. Those skilled in the relevant art will recognize and appreciate that many changes can be made to the various embodiments of the invention described herein, while still obtaining the beneficial results of the present disclosure. It will also be apparent that some of the desired Docket No.103361-541WO1 benefits of the present disclosure can be obtained by selecting some of the features of the present disclosure without utilizing other features. Accordingly, those who work in art will recognize that many modifications and adaptations to the present disclosure are possible and can even be desirable in certain circumstances and are a part of the present disclosure. Thus, the following description is provided as illustrative of the principles of the present disclosure and not in limitation thereof. Reference will now be made in detail to the embodiments of the invention, examples of which are illustrated in the drawings and the examples. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Terminology Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood to one of ordinary skill in the art to which this disclosure belongs. The term “comprising” and variations thereof as used herein is used synonymously with the term “including” and variations thereof and are open, non-limiting terms. Although the terms “comprising” and “including” have been used herein to describe various embodiments, the terms “consisting essentially of” and “consisting of” can be used in place of “comprising” and “including” to provide for more specific embodiments and are also disclosed. As used in this disclosure and in the appended claims, the singular forms “a”, “an”, “the”, include plural referents unless the context clearly dictates otherwise. The following definitions are provided for the full understanding of terms used in this specification. The terms "about" and "approximately" are defined as being “close to” as understood by one of ordinary skill in the art. In one non-limiting embodiment the terms are defined to be within 10%. In another non-limiting embodiment, the terms are defined to be within 5%. In still another non-limiting embodiment, the terms are defined to be within 1%. As used herein, the terms "may," "optionally," and "may optionally" are used interchangeably and are meant to include cases in which the condition occurs as well as cases in which the condition does not occur. Thus, for example, the statement that a formulation "may include an excipient" is meant to include cases in which the formulation includes an excipient as well as cases in which the formulation does not include an excipient. “Composition” refers to any agent that has a beneficial biological effect. Beneficial biological effects include both therapeutic effects, e.g., treatment of a disorder or other undesirable physiological condition, and prophylactic effects, e.g., prevention of a disorder or Docket No.103361-541WO1 other undesirable physiological condition. The terms also encompass pharmaceutically acceptable, pharmacologically active derivatives of beneficial agents specifically mentioned herein, including, but not limited to, a vector, polynucleotide, cells, salts, esters, amides, proagents, active metabolites, isomers, fragments, analogs, and the like. When the term “composition” is used, then, or when a particular composition is specifically identified, it is to be understood that the term includes the composition per se as well as pharmaceutically acceptable, pharmacologically active vector, polynucleotide, salts, esters, amides, proagents, conjugates, active metabolites, isomers, fragments, analogs, etc. The term “comprising”, and variations thereof as used herein is used synonymously with the term “including” and variations thereof and are open, non-limiting terms. Although the terms “comprising” and “including” have been used herein to describe various embodiments, the terms “consisting essentially of” and “consisting of” can be used in place of “comprising” and “including” to provide for more specific embodiments and are also disclosed. An "increase" can refer to any change that results in a greater amount of a symptom, disease, composition, condition, or activity. An increase can be any individual, median, or average increase in a condition, symptom, activity, composition in a statistically significant DPRXQW^^7KXV^^WKH^LQFUHDVH^FDQ^EH^D^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^RU^PRUH^LQFUHDVH^VR^long as the increase is statistically significant. A "decrease" can refer to any change that results in a smaller amount of a symptom, disease, composition, condition, or activity. A substance is also understood to decrease the genetic output of a gene when the genetic output of the gene product with the substance is less relative to the output of the gene product without the substance. Also, for example, a decrease can be a change in the symptoms of a disorder such that the symptoms are less than previously observed. A decrease can be any individual, median, or average decrease in a condition, symptom, activity, composition in a statistically significant amount. Thus, the decrease can be a ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^RU^ 100% decrease so long as the decrease is statistically significant. By “reduce” or other forms of the word, such as “reducing” or “reduction,” is meant lowering of an event or characteristic. It is understood that this is typically in relation to some standard or expected value, in other words it is relative, but that it is not always necessary for the standard or relative value to be referred to. By “prevent” or other forms of the word, such as “preventing” or “prevention,” is meant to stop a particular event or characteristic, to stabilize or delay the development or progression of Docket No.103361-541WO1 a particular event or characteristic, or to minimize the chances that a particular event or characteristic will occur. Prevent does not require comparison to a control as it is typically more absolute than, for example, reduce. As used herein, something could be reduced but not prevented, but something that is reduced could also be prevented. Likewise, something could be prevented but not reduced, but something that is prevented could also be reduced. It is understood that where reduce or prevent are used, unless specifically indicated otherwise, the use of the other word is also expressly disclosed. The term “subject” refers to any individual who is the target of administration or treatment. The subject can be a vertebrate, for example, a mammal. In one aspect, the subject can be human, non-human primate, bovine, equine, porcine, canine, or feline. The subject can also be a guinea pig, rat, hamster, rabbit, mouse, or mole. Thus, the subject can be a human or veterinary patient. The term “patient” refers to a subject under the treatment of a clinician, e.g., physician. The term “treatment” refers to the medical management of a patient with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder. This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder. In addition, this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder. As used herein, the term "polymerase chain reaction" ("PCR") refers to a method for increasing the concentration of a segment of a target sequence in a mixture of genomic DNA without cloning or purification. This process for amplifying the target sequence typically consists of introducing a large excess of two oligonucleotide primers to the DNA mixture containing the desired target sequence, followed by a precise sequence of thermal cycling in the presence of a DNA polymerase. The two primers are complementary to their respective strands of the double stranded target sequence. To effect amplification, the mixture is denatured, and the primers then annealed to their complementary sequences within the target molecule. Following annealing, the primers are extended with a polymerase so as to form a new pair of complementary strands. The steps of denaturation, primer annealing, and polymerase extension can be repeated many times to Docket No.103361-541WO1 obtain a high concentration of an amplified segment of the desired target sequence. Unless otherwise noted, PCR, as used herein, also includes variants of PCR such as allele-specific PCR, asymmetric PCR, hot-start PCR, ligation-mediated PCR, multiplex-PCR, reverse transcription PCR, or any of the other PCR variants known to those skilled in the art. The term “administering” refers to an administration that is oral, topical, intravenous, subcutaneous, transcutaneous, transdermal, intramuscular, intra-joint, parenteral, intra-arteriole, intradermal, intraventricular, intracranial, intraperitoneal, intralesional, intranasal, rectal, vaginal, by inhalation or via an implanted reservoir. The term “parenteral” includes subcutaneous, intravenous, intramuscular, intra-articular, intra-synovial, intrasternal, intrathecal, intrahepatic, intralesional, and intracranial injections or infusion techniques. A "primer" is a short polynucleotide, generally with a free 3'-OH group that binds to a target or "template" potentially present in a sample of interest by hybridizing with the target, and thereafter promoting polymerization of a polynucleotide complementary to the target. A "polymerase chain reaction" ("PCR") is a reaction in which replicate copies are made of a target polynucleotide using a "pair of primers" or a "set of primers" consisting of an "upstream" and a "downstream" primer, and a catalyst of polymerization, such as a DNA polymerase, and typically a thermally stable polymerase enzyme. Methods for PCR are well known in the art, and taught, for example in "PCR: A PRACTICAL APPROACH" (M. MacPherson et al., IRL Press at Oxford University Press (1991)). All processes of producing replicate copies of a polynucleotide, such as PCR or gene cloning, are collectively referred to herein as "replication." A primer can also be used as a probe in hybridization reactions, such as Southern or Northern blot analyses. Sambrook et al., supra. The terms “treat,” “treating,” “treatment,” and grammatical variations thereof as used herein, include partially or completely delaying, alleviating, mitigating, or reducing the intensity of one or more attendant symptoms of a disorder or condition and / or alleviating, mitigating, or impeding one or more causes of a disorder or condition. Treatments according to the disclosure may be applied preventively, prophylactically, palliatively, or remedially. Treatments are administered to a subject prior to onset (e.g., before obvious signs of disease), during early onset (e.g., upon initial signs and symptoms of disease), or after an established development of the disease. Prophylactic administration can occur for several days to years prior to the manifestation of symptoms of an infection. "Pharmaceutically acceptable carrier" (sometimes referred to as a “carrier”) means a carrier or excipient that is useful in preparing a pharmaceutical or therapeutic composition that is Docket No.103361-541WO1 generally safe and non-toxic and includes a carrier that is acceptable for veterinary and / or human pharmaceutical or therapeutic use. The terms "carrier" or "pharmaceutically acceptable carrier" can include, but are not limited to, phosphate buffered saline solution, water, emulsions (such as an oil / water or water / oil emulsion) and / or various types of wetting agents. A “nucleotide” is a compound consisting of a nucleoside, which consists of a nitrogenous base and a 5-carbon sugar, linked to a phosphate group forming the basic structural unit of nucleic acids, such as DNA or RNA. The four types of nucleotides are adenine (A), cytosine (C), guanine (G), and thymine (T), each of which are bound together by a phosphodiester bond to form a nucleic acid molecule. A “nucleic acid” is a chemical compound that serves as the primary information-carrying molecules in cells and makes up the cellular genetic material. Nucleic acids are nucleotides, which are the monomers made of a 5-carbon sugar (usually ribose or deoxyribose), a phosphate group, and a nitrogenous base. A nucleic acid can also be a deoxyribonucleic acid (DNA) or a ribonucleic acid (RNA). The terms “percent identity” and “% identity,” as applied to nucleotide sequences, refer to the percentage of residue matches between at least two nucleotide sequences aligned using a standardized algorithm. Such an algorithm may insert, in a standardized and reproducible way, gaps in the sequences being compared in order to optimize alignment between two sequences, and therefore achieve a more meaningful comparison of the two sequences. Percent identity for a nucleic acid sequence may be determined as understood in the art. (See, e.g., U.S. Pat. No. ^^^^^^^^^^^ZKLFK^LV^LQFRUSRUDWHG^KHUHLQ^E\^UHIHUHQFH^LQ^LWV^HQWLUHW\^^^$^VXLWH^RI^FRPPRQO\^XVHG^ and freely available sequence comparison algorithms is provided by the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST) (Altschul, S. F. et al. (1990) J. Mol. Biol. 215:403410), which is available from several sources, including the NCBI, Bethesda, Md., at its website. The BLAST software suite includes various sequence analysis programs including “blastn,” that is used to align a known nucleotide sequence with other polynucleotide sequences from a variety of databases. Also available is a tool called “BLAST 2 Sequences” that is used for direct pairwise comparison of two nucleotide sequences. “BLAST 2 Sequences” can be accessed and used interactively at the NCBI website. The “BLAST 2 Sequences” tool can be used for both blastn and blastp (discussed above). Percent identity may be measured over the length of an entire defined nucleotide sequence or may be measured over a shorter length, for example, over the length of a fragment taken from a larger, defined sequence, for instance, a fragment of at least 20, at least 30, at least ^^^^DW^OHDVW^^^^^DW^OHDVW^^^^^DW^OHDVW^^^^^^RU^DW^OHDVW^^^^^FRQWLJXRXV^QXFOHRWLGHV^^6XFK^OHQJWKV^DUH^ Docket No.103361-541WO1 exemplary only, and it is understood that any fragment length may be used to describe a length over which percentage identity may be measured. Methods of treating colorectal cancer In one aspect, disclosed herein is a method of treating colorectal cancer in a subject, comprising: obtaining a sample from the subject; detecting the presence or absence of gut microbiota; wherein said gut microbiota comprises positively correlated bacteria that produce phenylacetaldehyde (PAA) and negatively correlated bacteria that do not produce PAA, wherein the subject is predicted to have colorectal cancer if the amount of positively correlated bacteria is lower in the subject than in comparison to a control and if the amount of negatively correlated bacteria is higher in the subject than in comparison to a control; and administering a therapeutically effective dose of PAA to the subject who is predicted to have colorectal cancer. In some aspect, also disclosed herein is a method of treating colorectal cancer in a subject, comprising: obtaining a sample from the subject; detecting the presence or absence of gut microbiota; wherein said gut microbiota comprises positively correlated bacteria that produce phenylacetaldehyde (PAA) or negatively correlated bacteria that do not produce PAA, wherein the subject is predicted to have colorectal cancer if the amount of positively correlated bacteria is lower in the subject than in comparison to a control or if the amount of negatively correlated bacteria is higher in the subject than in comparison to a control; and administering a therapeutically effective dose of PAA to the subject who is predicted to have colorectal cancer. As used herein, the gut microbiota comprises positively correlated bacteria that produce phenylacetaldehyde (PAA) and negatively correlated bacteria that do not produce PAA. In some embodiments, the positively correlated bacteria can comprise at least one of the following: Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio Docket No.103361-541WO1 txid1458463. In some embodiments, the positively correlated bacterium can be Clostridium txid1638787. In some embodiments, the positively correlated bacterium can be Clostridium txid1697791. In some embodiments, the positively correlated bacterium can be Firmicute txid1263021. In some embodiments, the positively correlated bacterium can be Coprobascillus txid100884. In some embodiments, the positively correlated bacterium can be Coprobascillus txid127889. In some embodiments, the positively correlated bacterium can be Coprobascillus txid1182556. In some embodiments, the positively correlated bacterium can be Streptococcus txid99822. In some embodiments, the positively correlated bacterium can be Acidaminococcus txid1203555. In some embodiments, the positively correlated bacterium can be Roseburia txid1262944. In some embodiments, the positively correlated bacterium can be Butyrivibrio txid1458463. In some embodiments, the positively correlated bacteria can comprise at least 1, 2, ^^^^^^^^^^^^^^^^^^^^RU^^^^EDFWHULD^RI^WKH^IROORZLQJ^^Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463. In some embodiments, the panel of positively correlated bacteria can comprise at least 5 bacteria of the following: Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463. In some embodiments, the panel of positively correlated bacteria can comprise at least 10 bacteria of the following: Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463. In some embodiments, the negatively correlated bacteria comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670. In some embodiments, the negatively correlated bacterium can be Alistipes txid1262695. In some embodiments, the negatively correlated bacterium can be Fusobacterium txid1583098. In some embodiments, the negatively correlated bacterium can be Fusobacterium txid712288. In some embodiments, the negatively correlated bacterium can be Fusobacterium txid1032505. In some embodiments, the negatively correlated bacterium can be Leuconostoc txid1403934. In some embodiments, the negatively correlated bacterium can be Paenibacillus txid78058. In some embodiments, the Docket No.103361-541WO1 negatively correlated bacterium can be Alcanivorax txid519051. In some embodiments, the negatively correlated bacterium can be Arthrobacter txid1690248. In some embodiments, the negatively correlated bacterium can be Bacillus txid1127743. In some embodiments, the negatively correlated bacterium can be Bacillus txid492670. In some embodiments, the panel of negatively correlated bacteria can comprise at least 5 bacteria of the following: Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670. In some embodiments, the panel of negatively correlated bacteria can comprise at least 10 bacteria of the following: Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670. In some embodiments, WKH^QHJDWLYHO\^FRUUHODWHG^EDFWHULD^FDQ^FRPSULVH^DW^OHDVW^^^^^^^^^^^^^^^^^^^^^^^^^^^RU^^^^EDFWHULD^RI^WKH^ following: Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670. In some embodiments, the gut microbiota analysis can be determined by performing 16S rRNA qPCR or metagenomics sequencing. In some embodiments, the sample is serum, blood or fecal matter. In one aspect, disclosed herein is a method of treating colorectal cancer in a subject comprising: administering a therapeutically effective dose of phenylacetaldehyde (PAA) as an adjunct with a chemotherapy drug to the subject. It is understood and herein contemplated that the disclosed treatment regimens can used alone or in combination with any anti-cancer therapy known in the art including, but not limited to Abemaciclib, Abiraterone Acetate, Abitrexate (Methotrexate), Abraxane (Paclitaxel Albumin- stabilized Nanoparticle Formulation), ABVD, ABVE, ABVE-PC, AC, AC-T, Adcetris (Brentuximab Vedotin), ADE, Ado-Trastuzumab Emtansine, Adriamycin (Doxorubicin Hydrochloride), Afatinib Dimaleate, Afinitor (Everolimus), Akynzeo (Netupitant and Palonosetron Hydrochloride), Aldara (Imiquimod), Aldesleukin, Alecensa (Alectinib), Alectinib, Alemtuzumab, Alimta (Pemetrexed Disodium), Aliqopa (Copanlisib Hydrochloride), Alkeran for Injection (Melphalan Hydrochloride), Alkeran Tablets (Melphalan), Aloxi (Palonosetron Hydrochloride), Alunbrig (Brigatinib), Ambochlorin (Chlorambucil), Amboclorin Chlorambucil), Amifostine, Aminolevulinic Acid, Anastrozole, Aprepitant, Aredia (Pamidronate Disodium), Arimidex (Anastrozole), Aromasin (Exemestane),Arranon (Nelarabine), Arsenic Docket No.103361-541WO1 Trioxide, Arzerra (Ofatumumab), Asparaginase Erwinia chrysanthemi, Atezolizumab, Avastin (Bevacizumab), Avelumab, Axitinib, Azacitidine, Bavencio (Avelumab), BEACOPP, Becenum (Carmustine), Beleodaq (Belinostat), Belinostat, Bendamustine Hydrochloride, BEP, Besponsa (Inotuzumab Ozogamicin) , Bevacizumab, Bexarotene, Bexxar (Tositumomab and Iodine I 131 Tositumomab), Bicalutamide, BiCNU (Carmustine), Bleomycin, Blinatumomab, Blincyto (Blinatumomab), Bortezomib, Bosulif (Bosutinib), Bosutinib, Brentuximab Vedotin, Brigatinib, BuMel, Busulfan, Busulfex (Busulfan), Cabazitaxel, Cabometyx (Cabozantinib-S-Malate), Cabozantinib-S-Malate, CAF, Campath (Alemtuzumab), Camptosar , (Irinotecan Hydrochloride), Capecitabine, &$32;, Carac (Fluorouracil--Topical), Carboplatin, CARBOPLATIN-7$;2 / , Carfilzomib, Carmubris (Carmustine), Carmustine, Carmustine Implant, Casodex (Bicalutamide), CEM, Ceritinib, Cerubidine (Daunorubicin Hydrochloride), Cervarix (Recombinant HPV Bivalent Vaccine), Cetuximab, CEV, Chlorambucil, CHLORAMBUCIL-PREDNISONE, CHOP, Cisplatin, Cladribine, Clafen (Cyclophosphamide), Clofarabine, Clofarex (Clofarabine), Clolar (Clofarabine), CMF, Cobimetinib, Cometriq (Cabozantinib-S-Malate), Copanlisib Hydrochloride, COPDAC, COPP, COPP-ABV, Cosmegen (Dactinomycin), Cotellic (Cobimetinib), Crizotinib, CVP, Cyclophosphamide, Cyfos (Ifosfamide), Cyramza (Ramucirumab), Cytarabine, Cytarabine Liposome, Cytosar-U (Cytarabine), Cytoxan (Cyclophosphamide), Dabrafenib, Dacarbazine, Dacogen (Decitabine), Dactinomycin, Daratumumab, Darzalex (Daratumumab), Dasatinib, Daunorubicin Hydrochloride, Daunorubicin Hydrochloride and Cytarabine Liposome, Decitabine, Defibrotide Sodium, Defitelio (Defibrotide Sodium), Degarelix, Denileukin Diftitox, Denosumab, DepoCyt (Cytarabine Liposome), Dexamethasone, Dexrazoxane Hydrochloride, Dinutuximab, Docetaxel, Doxil (Doxorubicin Hydrochloride Liposome), Doxorubicin Hydrochloride, Doxorubicin Hydrochloride Liposome, Dox-SL (Doxorubicin Hydrochloride Liposome), DTIC-Dome (Dacarbazine), Durvalumab, Efudex (Fluorouracil--Topical), Elitek (Rasburicase), Ellence (Epirubicin Hydrochloride), Elotuzumab, Eloxatin (Oxaliplatin), Eltrombopag Olamine, Emend (Aprepitant), Empliciti (Elotuzumab), Enasidenib Mesylate, Enzalutamide, Epirubicin Hydrochloride , EPOCH, Erbitux (Cetuximab), Eribulin Mesylate, Erivedge (Vismodegib), Erlotinib Hydrochloride, Erwinaze (Asparaginase Erwinia chrysanthemi) , Ethyol (Amifostine), Etopophos (Etoposide Phosphate), Etoposide, Etoposide Phosphate, Evacet (Doxorubicin Hydrochloride Liposome), Everolimus, Evista , (Raloxifene Hydrochloride), Evomela (Melphalan Hydrochloride), Exemestane, 5-FU (Fluorouracil Injection), 5-FU (Fluorouracil-- Topical), Fareston (Toremifene), Farydak (Panobinostat), Faslodex (Fulvestrant), FEC, Femara (Letrozole), Filgrastim, Fludara (Fludarabine Phosphate), Fludarabine Phosphate, Fluoroplex ^^ Docket No.103361-541WO1 (Fluorouracil--Topical), Fluorouracil Injection, Fluorouracil--Topical, Flutamide, Folex (Methotrexate), Folex PFS (Methotrexate), FOLFIRI, FOLFIRI-BEVACIZUMAB, FOLFIRI- &(78;,0$%, )2 / ),5,12;, )2 / )2;, Folotyn (Pralatrexate), FU-LV, Fulvestrant, Gardasil (Recombinant HPV Quadrivalent Vaccine), Gardasil 9 (Recombinant HPV Nonavalent Vaccine), Gazyva (Obinutuzumab), Gefitinib, Gemcitabine Hydrochloride, GEMCITABINE- CISPLATIN, GEMCITABINE-2;$ / ,3 / $7,1, Gemtuzumab Ozogamicin, Gemzar (Gemcitabine Hydrochloride), Gilotrif (Afatinib Dimaleate), Gleevec (Imatinib Mesylate), Gliadel (Carmustine Implant), Gliadel wafer (Carmustine Implant), Glucarpidase, Goserelin Acetate, Halaven (Eribulin Mesylate), Hemangeol (Propranolol Hydrochloride), Herceptin (Trastuzumab), HPV Bivalent Vaccine, Recombinant, HPV Nonavalent Vaccine, Recombinant, HPV Quadrivalent Vaccine, Recombinant, Hycamtin (Topotecan Hydrochloride), Hydrea (Hydroxyurea), Hydroxyurea, Hyper-CVAD, Ibrance (Palbociclib), Ibritumomab Tiuxetan, Ibrutinib, ICE, Iclusig (Ponatinib Hydrochloride), Idamycin (Idarubicin Hydrochloride), Idarubicin Hydrochloride, Idelalisib, Idhifa (Enasidenib Mesylate), Ifex (Ifosfamide), Ifosfamide, Ifosfamidum (Ifosfamide), IL-2 (Aldesleukin), Imatinib Mesylate, Imbruvica (Ibrutinib), Imfinzi (Durvalumab), Imiquimod, Imlygic (Talimogene Laherparepvec), Inlyta (Axitinib), Inotuzumab Ozogamicin, Interferon Alfa-2b, Recombinant, Interleukin-2 (Aldesleukin), Intron A (Recombinant Interferon Alfa-2b), Iodine I 131 Tositumomab and Tositumomab, Ipilimumab, Iressa (Gefitinib), Irinotecan Hydrochloride, Irinotecan Hydrochloride Liposome, Istodax (Romidepsin), Ixabepilone, Ixazomib Citrate, Ixempra (Ixabepilone), Jakafi (Ruxolitinib Phosphate), JEB, Jevtana (Cabazitaxel), Kadcyla (Ado- Trastuzumab Emtansine), Keoxifene (Raloxifene Hydrochloride), Kepivance (Palifermin), Keytruda (Pembrolizumab), Kisqali (Ribociclib), Kymriah (Tisagenlecleucel), Kyprolis (Carfilzomib), Lanreotide Acetate, Lapatinib Ditosylate, Lartruvo (Olaratumab), Lenalidomide, Lenvatinib Mesylate, Lenvima (Lenvatinib Mesylate), Letrozole, Leucovorin Calcium, Leukeran (Chlorambucil), Leuprolide Acetate, Leustatin (Cladribine), Levulan (Aminolevulinic Acid), Linfolizin (Chlorambucil), LipoDox (Doxorubicin Hydrochloride Liposome), Lomustine, Lonsurf (Trifluridine and Tipiracil Hydrochloride), Lupron (Leuprolide Acetate), Lupron Depot (Leuprolide Acetate), Lupron Depot-Ped (Leuprolide Acetate), Lynparza (Olaparib), Marqibo (Vincristine Sulfate Liposome), Matulane (Procarbazine Hydrochloride), Mechlorethamine Hydrochloride, Megestrol Acetate, Mekinist (Trametinib), Melphalan, Melphalan Hydrochloride, Mercaptopurine, Mesna, Mesnex (Mesna), Methazolastone (Temozolomide), Methotrexate, Methotrexate LPF (Methotrexate), Methylnaltrexone Bromide, Mexate (Methotrexate), Mexate- AQ (Methotrexate), Midostaurin, Mitomycin C, Mitoxantrone Hydrochloride, Mitozytrex Docket No.103361-541WO1 (Mitomycin C), MOPP, Mozobil (Plerixafor), Mustargen (Mechlorethamine Hydrochloride) , Mutamycin (Mitomycin C), Myleran (Busulfan), Mylosar (Azacitidine), Mylotarg (Gemtuzumab Ozogamicin), Nanoparticle Paclitaxel (Paclitaxel Albumin-stabilized Nanoparticle Formulation), Navelbine (Vinorelbine Tartrate), Necitumumab, Nelarabine, Neosar (Cyclophosphamide), Neratinib Maleate, Nerlynx (Neratinib Maleate), Netupitant and Palonosetron Hydrochloride, Neulasta (Pegfilgrastim), Neupogen (Filgrastim), Nexavar (Sorafenib Tosylate), Nilandron (Nilutamide), Nilotinib, Nilutamide, Ninlaro (Ixazomib Citrate), Niraparib Tosylate Monohydrate, Nivolumab, Nolvadex (Tamoxifen Citrate), Nplate (Romiplostim), Obinutuzumab, Odomzo (Sonidegib), OEPA, Ofatumumab, OFF, Olaparib, Olaratumab, Omacetaxine Mepesuccinate, Oncaspar (Pegaspargase), Ondansetron Hydrochloride, Onivyde (Irinotecan Hydrochloride Liposome), Ontak (Denileukin Diftitox), Opdivo (Nivolumab), OPPA, Osimertinib, Oxaliplatin, Paclitaxel, Paclitaxel Albumin-stabilized Nanoparticle Formulation, PAD, Palbociclib, Palifermin, Palonosetron Hydrochloride, Palonosetron Hydrochloride and Netupitant, Pamidronate Disodium, Panitumumab, Panobinostat, Paraplat (Carboplatin), Paraplatin (Carboplatin), Pazopanib Hydrochloride, PCV, PEB, Pegaspargase, Pegfilgrastim, Peginterferon Alfa-2b, PEG-Intron (Peginterferon Alfa-2b), Pembrolizumab, Pemetrexed Disodium, Perjeta (Pertuzumab), Pertuzumab, Platinol (Cisplatin), Platinol-AQ (Cisplatin), Plerixafor, Pomalidomide, Pomalyst (Pomalidomide), Ponatinib Hydrochloride, Portrazza (Necitumumab), Pralatrexate, Prednisone, Procarbazine Hydrochloride , Proleukin (Aldesleukin), Prolia (Denosumab), Promacta (Eltrombopag Olamine), Propranolol Hydrochloride, Provenge (Sipuleucel-T), Purinethol (Mercaptopurine), Purixan (Mercaptopurine), Radium 223 Dichloride, Raloxifene Hydrochloride, Ramucirumab, Rasburicase, R-CHOP, R-CVP, Recombinant Human Papillomavirus (HPV) Bivalent Vaccine, Recombinant Human Papillomavirus (HPV) Nonavalent Vaccine, Recombinant Human Papillomavirus (HPV) Quadrivalent Vaccine, Recombinant Interferon Alfa-2b, Regorafenib, Relistor (Methylnaltrexone Bromide), R-EPOCH, Revlimid (Lenalidomide), Rheumatrex (Methotrexate), Ribociclib, R-ICE, Rituxan (Rituximab), Rituxan Hycela (Rituximab and Hyaluronidase Human), Rituximab, Rituximab and , Hyaluronidase Human, ,Rolapitant Hydrochloride, Romidepsin, Romiplostim, Rubidomycin (Daunorubicin Hydrochloride), Rubraca (Rucaparib Camsylate), Rucaparib Camsylate, Ruxolitinib Phosphate, Rydapt (Midostaurin), Sclerosol Intrapleural Aerosol (Talc), Siltuximab, Sipuleucel-T, Somatuline Depot (Lanreotide Acetate), Sonidegib, Sorafenib Tosylate, Sprycel (Dasatinib), STANFORD V, Sterile Talc Powder (Talc), Steritalc (Talc), Stivarga (Regorafenib), Sunitinib Malate, Sutent (Sunitinib Malate), Sylatron (Peginterferon Alfa-2b), Sylvant (Siltuximab), Synribo (Omacetaxine Mepesuccinate), Tabloid (Thioguanine), TAC, Tafinlar Docket No.103361-541WO1 (Dabrafenib), Tagrisso (Osimertinib), Talc, Talimogene Laherparepvec, Tamoxifen Citrate, Tarabine PFS (Cytarabine), Tarceva (Erlotinib Hydrochloride), Targretin (Bexarotene), Tasigna (Nilotinib), Taxol (Paclitaxel), Taxotere (Docetaxel), Tecentriq , (Atezolizumab), Temodar (Temozolomide), Temozolomide, Temsirolimus, Thalidomide, Thalomid (Thalidomide), Thioguanine, Thiotepa, Tisagenlecleucel, Tolak (Fluorouracil--Topical), Topotecan Hydrochloride, Toremifene, Torisel (Temsirolimus), Tositumomab and Iodine I 131 Tositumomab, Totect (Dexrazoxane Hydrochloride), TPF, Trabectedin, Trametinib, Trastuzumab, Treanda (Bendamustine Hydrochloride), Trifluridine and Tipiracil Hydrochloride, Trisenox (Arsenic Trioxide), Tykerb (Lapatinib Ditosylate), Unituxin (Dinutuximab), Uridine Triacetate, VAC, Vandetanib, VAMP, Varubi (Rolapitant Hydrochloride), Vectibix (Panitumumab), VeIP, Velban (Vinblastine Sulfate), Velcade (Bortezomib), Velsar (Vinblastine Sulfate), Vemurafenib, Venclexta (Venetoclax), Venetoclax, Verzenio (Abemaciclib), Viadur (Leuprolide Acetate), Vidaza (Azacitidine), Vinblastine Sulfate, Vincasar PFS (Vincristine Sulfate), Vincristine Sulfate, Vincristine Sulfate Liposome, Vinorelbine Tartrate, VIP, Vismodegib, Vistogard (Uridine Triacetate), Voraxaze (Glucarpidase), Vorinostat, Votrient (Pazopanib Hydrochloride), Vyxeos (Daunorubicin Hydrochloride and Cytarabine Liposome), Wellcovorin (Leucovorin Calcium), ;DONRUL^^&UL]RWLQLE^, ;HORGD^^&DSHFLWDELQH^, ;( / ,5,, ;( / 2;, ;JHYD^^'HQRVXPDE^, ;RILJR^^5DGLXP^^^^^'LFKORULGH^, ;WDQGL^^(Q]DOXWDPLGH^, Yervoy (Ipilimumab), Yondelis (Trabectedin), Zaltrap (Ziv-Aflibercept), Zarxio (Filgrastim), Zejula (Niraparib Tosylate Monohydrate), Zelboraf (Vemurafenib), Zevalin (Ibritumomab Tiuxetan), Zinecard (Dexrazoxane Hydrochloride), Ziv-Aflibercept, Zofran (Ondansetron Hydrochloride), Zoladex (Goserelin Acetate), Zoledronic Acid, Zolinza (Vorinostat), Zometa (Zoledronic Acid), Zydelig (Idelalisib), Zykadia (Ceritinib), and / or Zytiga (Abiraterone Acetate). The treatment methods can include or further include checkpoint inhibitors including, but are not limited to antibodies that block PD-1 (such as, for example, Nivolumab (BMS- ^^^^^^^RU^0';^^^^^^^pembrolizumab, CT-011, MK-^^^^^^^3'-L1 (such as, for example, atezolizumab, avelumab, durvalumab, 0';-1105 (BMS-936559), MPDL3280A, or 06%^^^^^^^&^^^3'- / ^^^VXFK^DV^^IRU^H[DPSOH^^U+,J0^^%^^^^&7 / $-4 (such as, for example, ,SLOLPXPDE^^0';-010), Tremelimumab (CP-^^^^^^^^^^^,'2^^%^-H3 (such as, for example, 0*$^^^^^0*'^^^^^RPEXUWDPDE^^^%^-+^^^%^-H3, T cell immunoreceptor with Ig and ITIM domains (TIGIT)(such as, for example BMS-^^^^^^^^203-313M32, MK-^^^^^^$%-154, ASP- ^^^^^^07,*^^^^$^^RU^3965,32^^^&'^^^^%- and T-lymphocyte attenuator (BTLA), V-domain Ig suppressor of T cell activation (VISTA)(such as, for example, JNJ-61610588, CA-^^^^^^7,0^^ (such as, for example, TSR-^^^^^0%*^^^^^6\P^^^^^,1&$*1^^^^^^ / <^^^^^^^^^^%06-986258, Docket No.103361-541WO1 SHR-^^^^^^52^^^^^^^^^^ / $*-3 (such as, for example, BMS-986016, LAG525, MK-4280, 5(*1^^^^^^765-^^^^^%,^^^^^^^^6\P^^^^^)6^^^^^0*'^^^^^DQG^,PPXWHS^^^In some embodiments, the chemotherapy drug is 5-fluorouracil. In one aspect, disclosed herein is a method of treating colorectal cancer in a subject comprising: administering a therapeutically effective dose of phenylacetaldehyde (PAA) to the subject. Methods of detecting cancer In one aspect, disclosed herein is a method of detecting colorectal cancer in a subject, comprising: obtaining a sample from the subject; performing metagenomics sequencing or qPCR on the sample; and determining positively and negatively correlated bacterial species to PAA production, wherein lower levels of PAA are negatively correlated to bacterial species, wherein higher levels of PAA are positively correlated to bacterial species. In some embodiments, the subject is predicted to have colorectal cancer if the amount of positively correlated bacteria is lower in the subject than in comparison to a control or if the amount of negatively correlated bacteria is higher in the subject than in comparison to a control. As used herein “control” refers to a healthy individual, without any diagnosed colorectal cancer. In some embodiments, the gut microbiota analysis can be determined by performing 16S rRNA qPCR or metagenomics sequencing. In some embodiments, the sample is serum, blood or fecal matter. In one aspect, disclosed herein is a method of determining colorectal cancer (CRC) in a subject comprising: obtaining a sample from the subject; measuring PAA concentration in the serum; and determining the subject is predicted to have CRC if the amount of PAA is lower in the subject as compared to control. As used herein, the PAA concentration is measured using GC- MS / MS-based targeted metabolomics, wherein the GC-MS / MS-based targeted metabolomics provides precise and quantitative analysis of small, volatile metabolites for deep insights into metabolic pathways and their perturbations under different conditions. Methods of determining gut microbiota signature In one aspect, disclosed herein is a method of determining a gut microbiota signature for Docket No.103361-541WO1 cancer detection, comprising: obtain a serum sample from a subject and a control; determining the PAA levels in the serum sample; obtaining a fecal sample from the subject and the control; performing metagenomic sequencing or qPCR on the fecal sample; and determining bacterial species which are positively and negatively correlated to the PAA levels in the serum sample. In some embodiments, the positively correlated bacterial species produce PAA. In some embodiments, the negatively correlated bacterial species do not produce PAA. In some embodiments, the subject has cancer if the negatively correlated bacterial species are higher than positively correlated bacterial species in the subject as compared to the control. The disclosed compositions can be used to treat any disease where uncontrolled cellular proliferation occurs such as cancers. A representative but non-limiting list of cancers that the disclosed compositions can be used to treat is the following: lymphomas such as B cell lymphoma and T cell lymphoma; mycosis fungoides; Hodgkin’s Disease; myeloid leukemia (including, but not limited to acute myeloid leukemia (AML) and / or chronic myeloid leukemia (CML)); bladder cancer; brain cancer; nervous system cancer; head and neck cancer; squamous cell carcinoma of head and neck; renal cancer; lung cancers such as small cell lung cancer, non- small cell lung carcinoma (NSCLC), lung squamous cell carcinoma (LUSC), and Lung Adenocarcinomas (LUAD); neuroblastoma / glioblastoma; ovarian cancer; pancreatic cancer; prostate cancer; skin cancer; hepatic cancer; melanoma; squamous cell carcinomas of the mouth, throat, larynx, and lung; cervical cancer; cervical carcinoma; breast cancer including, but not limited to triple negative breast cancer; genitourinary cancer; pulmonary cancer; esophageal carcinoma; head and neck carcinoma; large bowel cancer; hematopoietic cancers; testicular cancer; and colon and rectal cancers. In some embodiments, the cancer is colorectal cancer. In some embodiments, the specific microbiome signature has at least 90%, 91%, 92%, 93%, 94%, 95%, or 96% prediction power to identify subjects with cancer and determine correlation to serum PAA levels. In some embodiments, the specific microbiome signature has at least 94% prediction power to identify subjects with cancer and determine correlation to serum PAA levels. In some embodiments, the specific microbiome signature has at least 95% prediction power to identify subjects with cancer and determine correlation to serum PAA levels. Method for predicting cancer immunotherapy response In one aspect, disclosed herein is a method for predicting a treatment response to cancer immunotherapy, comprising: Docket No.103361-541WO1 obtaining a sample from a cancer subject; and detecting the presence or absence of gut microbiota; and administering a therapeutically effective dose of PAA to the subject that is predicted not to positively respond to the cancer immunotherapy treatment. In some embodiments, said gut microbiota comprises good responder bacteria that are positively correlated to immunotherapeutic response. In some embodiments, said gut microbiota comprises poor responder bacteria that are negatively correlated to immunotherapeutic response. In some embodiments, the good responder bacteria comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944 or Butyrivibrio txid1458463. In some embodiments, the good responder bacteria FDQ^FRPSULVH^DW^OHDVW^^^^^^^^^^^^^^^^^^^^^^^^^^^RU^^^^ bacteria of the following: Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944 or Butyrivibrio txid1458463. In some embodiments, the good responder bacteria can comprise at least 5 bacteria of the following: Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944 or Butyrivibrio txid1458463. In some embodiments, the good responder bacteria can comprise at least 10 bacteria of the following: Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944 or Butyrivibrio txid1458463. In some embodiments, the poor responder bacteria comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743 or Bacillus txid492670. In some embodiments, the good responder bacteria FDQ^FRPSULVH^DW^OHDVW^^^^^^^^^^^^^^^^^^^^^^^^^^^RU^^^^EDFWHULD^RI^WKH^ following: Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743 or Bacillus txid492670. In some embodiments, the good responder bacteria can comprise at least 5 bacteria of the following: Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium Docket No.103361-541WO1 txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743 or Bacillus txid492670. In some embodiments, the good responder bacteria can comprise at least 10 bacteria of the following: Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743 or Bacillus txid492670. In some embodiments, the subject is predicted to positively respond to the cancer immunotherapy treatment if the good responder bacteria are higher in the subject than in comparison to a control. In some embodiments, the subject is predicted to positively respond to the cancer immunotherapy treatment if the poor responder bacteria are lower in the subject than in comparison to a control. In some embodiments, the cancer immunotherapy is an anti-PD-1 treatment. In some embodiments, the cancer immunotherapy is an anti-CTLA-4 treatment. In some embodiments, the specific microbiome signature has at least 90%, 91%, 92%, 93%, 94%, 95%, or 96% prediction power to identify good responders from poor responders. In some embodiments, the specific microbiome signature has at least 94% prediction power to identify good responders from poor responders. In some embodiments, the specific microbiome signature has at least 95% prediction power to identify good responders from poor responders. Kits for detecting colorectal cancer In one aspect, disclosed herein is a kit for detecting colorectal cancer (CRC) in a sample from a subject, comprising: a panel of 10 bacterial species positively correlated with increased PAA levels in the subject, wherein the positively correlated bacterial species comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463; and a panel of 10 bacterial species negatively correlated with decreased PAA levels in the subject, wherein the negatively correlated bacterial species comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium Docket No.103361-541WO1 txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670, wherein the subject has CRC if the sample has more negatively correlated bacterial species as compared to positively correlated bacterial species. It will be apparent to those skilled in the art that various modifications and variations can be made in the present disclosure without departing from the scope or spirit of the invention. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the methods disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims. EXAMPLES The following examples are set forth below to illustrate the compositions, devices, methods, and results according to the disclosed subject matter. These examples are not intended to be inclusive of all aspects of the subject matter disclosed herein, but rather to illustrate representative methods and results. These examples are not intended to exclude equivalents and variations of the present invention which are apparent to one skilled in the art. Example 1: Phenylacetaldehyde (PAA) and its related gut microbiota are decreased in colorectal cancer (CRC) patients To investigate the clinical significance of phenylacetaldehyde (PAA) and its associated gut microbiota in colorectal cancer (CRC), GC-MS / MS-based targeted metabolomics and metagenomic sequencing was performed on the serum / stool samples from a test cohort composed of 30 pre-treatments CRC patients and 30 age- and gender-matched healthy controls (FIG. 1A, Table 1). Compared to control subjects, serum PAA concentration was significantly decreased by 41% in CRC patients (median: 1039μg / L for control, 613 μg / L for CRC. p<0.001) (FIG. 1B). Using receiver operating characteristic (ROC) analysis, PAA serum levels had an area under ROC curve value of 88% (95% CT: 80%-^^^^^S^^^^^^^^^GHPRQVWUDWLQJ^WKH^DELOLW\^RI^ serum PAA concentration to distinguish healthy from CRC patients (FIG. 1C). These results ZHUH^WHVWHG^IRU^YDOLGDWLRQ^LQ^DQ^LQGHSHQGHQW^FRKRUW^FRPSRVHG^RI^^^^&5&^SDWLHQWV^WUHDWHG^^DQG^^ 53 healthy controls from The Wexner Medical Center and James Comprehensive Cancer Center in Columbus, Ohio. (FIG. 1D, Table 2). Using GC-MS / MS on serum samples, the PAA concentration was significantly decreased in CRC patients (median: 848.5μg / L for control, ^^^^J^ / ^IRU^&5&^SDWLHQWV^^3 ^^^^^^^^FIG. 1E). The median levels for CRC patients in both the Docket No.103361-541WO1 test and validation populations were similar. ROC analysis on the validation set revealed that the serum PAA level for identifying CRC patients had an AUC of 0.66, demonstrating a good predictive value (FIG. 1F). The difference in serum levels was noted across all CRC stages, including stage T tumors. Together, these data prove the potential of measuring PAA serum levels as a potential biomarker to distinguish healthy people from patients with CRC. To explore the spectrum of bacteria species from the gut microbiome potentially responsible for PAA secretion, fecal metagenomic sequencing was performed on the test cohort. Comparing CRC to the control group, 1105 species showed a significant difference in abundance (p<0.05). To better estimate which species are associated with PAA release, Spearman's correlation coefficient and associated p-value between the relative abundance of 1105 species and PAA levels were calculated (Table 3). As depicted in the volcano plot, the species Clostridium sp.UNK.MGS6, Firmicutes bacterium CAG4l, Coprobacillus cateniformis, and Roseburia sp.CAG303 showed a significant positive correlation to serum PAA level. Conversely, the species Alistipes sp.CAG435, Fusobacterium hwasookii, Bacillus sp.5B6, and Bacillus velezensis showed a significant negative correlation with serum PAA (FIG. 1G). To further assess the potential microbial interactions between PAA-related microbes, microbial co- occurrence networks were constructed using R software (FIG. 1H). Using a cut-off of p<0.05, - 0.5> r, and r> 0.5, 49 correlations (edges) were displayed between the top 10 bacteria positively or negatively correlated to PAA which demonstrated a strong interdependency and competition between these species. Notably, the top 10 positively correlated bacteria were exclusively abundant in the control group, while all top 10 negatively correlated bacteria were both exclusively and significantly abundant in CRC. The main influencers (largest nodes) are generally composed of known healthy-enriched bacteria, such as Firmicutes bacterium CAG4l or Coprobacillus sp.D6, while CRC-enriched Fusobacterium and Bacillus species displayed more complex microbial co-occurrence association. Taken together, these data demonstrated that a decrease in PAA in serum correlates with a change of the microbiome signature in CRC patients. Example 2: PAA treatment decreases viability of CRC cells and organoids in vitro Observing the decrease of PAA in CRC patients led to the investigation of its potential anticancer properties. Therefore, HCT116 and RKO CRC cell lines were exposed to increasing doses of PAA (0, 0.1, 1, 10, 50, 100, and 1000 μM) in vitro IRU^^^K^DQG^WKHQ^FHOO^YLDELOLW\ was measured^^$IWHU^^^^KRXUV^RI^WUHDWPHQW^^3$$^LQKLELWHG^&5&^FHOO^YLDELOLW\^LQ^D^GRVH-dependent manner (with IC50 of ~^^^^0^DQG^~25 μM for HCT116 cells and RKO cells, respectively) (FIG. 2A). To confirm these results with a more complex in vitro model, two distinct patient-derived Docket No.103361-541WO1 CRC organoid lines were generated^^$IWHU^^^^KRXUV^RI^LQFXEDWLRQ^^WKH^YLDELOLW\^RI^ERWK^RUJDQRLG^ lines decreased with increasing concentrations of PAA (with IC50 of ~25 μM and ~^^^^0^^ respectively) (FIG. 2B). Using bright field microscopy, an alteration of cell morphology of both CRC cell lines and patient- derived CRC organoids was noticed DIWHU^^^^KRXUV^RI^3$$^WUHDWPHQW^ at 10 μM and 50 μM compared to control (Red arrows in FIGS. 2C and 2D). To further study the relationship between PAA and CRC growth, a CRC mouse xenograft model was established using RKO cell lines. The RKO cells (1 x 106) were injected s.c. into the flanks of NSG mice. The tumors were allowed to grow to a size of approximately 200mm3and then randomized into two groups (control and PAA treated). The mice in the PAA-treated group received intraperitoneally 20mg / kg injections per day for 5 consecutive days over a period of 12 days (FIG. 2E). Tumor size was measured daily using calipers. The PAA-treated group exhibited a significantly slower growth kinetic compared with the control condition (linear regression; p<0.0001) (FIG. 2F). Measured 21 days after randomization, the tumors of the group treated with PAA showed a significant decrease in size (p=0.031) (FIG. 2G). These data demonstrated that treatment with PAA decreases tumor growth in vivo. Collectively, the results highlight that PAA inhibited the viability of CRC in vitro and in vivo. Example 3: PAA inhibits CRC progression by inducing endoplasmic reticulum (ER) stress, autophagy, and by inhibiting survival signaling pathways To identify genes or pathways involved in the anticancer properties of PAA, RNA-seq analysis was performed on HCT116 and RKO cell lines after 24 hours of 50 μM treatment with PAA. On gene expression analysis, using a cutoff of at least a 2-fold difference and a p<0.0001, ^^^^^DQG^^^^^^JHQHV^ZHUH^GLIIHUHQWLDOO\^H[SUHVVHG^JHQHV^^'(*^^LQ^WKH^3$$^WUHDWHG^JURXS^ comparHG^WR^FRQWURO^IRU^+&7^^^^DQG^5.2^^UHVSHFWLYHO\^^*6(^^^^^^^^^FIG. 3A, FIG. 8). These lists of DEG were then submitted to a Gene Ontology analysis. For HCT116, 110 GO terms have been found to be enriched in the PAA 50 μM treated group while RKO had 59 enriched GO terms. The enriched GO terms shared by the two CRC cell lines were focused to better understand the specific effect of PAA treatment. Using this modifier, it was identified that 19 similar GO terms significantly were shared between HCT116 and RKO after treatment with PAA (qvalue < 0.25). As shown in FIG. 3B, most GO terms are related to ER stress (ERS) and autophagy. To test these findings more directly, HCT116 and RKO were treated with either 10μM or 50μM of PAA for 24 hours and tested for ERS and autophagy markers. Using Western blot, strong induction of markers of ER stress, like BiP, p-eiF2, and p-JNK were noticed in both cell ^^ Docket No.103361-541WO1 lines after 50 μM treatment (FIG. 3C). An increase in markers of autophagy was also observed, such as an increase of LC3B flux, Beclin, ATG12, and a decrease of P62 in both cell lines after 50μM treatment. Surprisingly, no significant effect on ERS and autophagy have been found after only 10 μM PAA treatment in HCT116 and RKO cell lines (FIG. 3C). Several studies on CRC have confirmed that ERS and unfolding protein response are part of the survival strategy for cells. Nonetheless, if the adaptive response fails to restore the protein- folding function of the ER, or if severe and sustained ERS occurs, the persistence of the UPR signal results in apoptosis. Because it was highlighted that increasing ERS is linked to a decrease in viability, the inhibition of survival and proliferation pathways were evaluated using Western Blot. For both cell lines, while treatment of 24 hours with 10 μM does not impact protein expression, an important decrease in expression of members of PI3K and ERK pathway was observed after treatment with 50 μM of PAA. Next, to determine whether the inhibition of PI3K and ERK pathways could have an impact on cell cycle proteins, CRC lines were exposed to the indicated concentration of PAA (FIG. 3D). The results revealed that 50μM of PAA treatment reduced the expression of Cyclin D1 and concomitantly increased the expression of P53, P21 / Cip1, and p-Chk2. These results are in accordance with a P53-dependent G1 blockage of the cell cycle as observed by flow cytometry (FIG. 5D). Interestingly, a genotoxic stress marker characterized by the induction of Ȗ+^$; was observed after 50 μM of PAA treatment as well as a decrease of full-length caspase 3, a marker of cell death initiation was also noticed. In summary, a high concentration treatment with PAA induced persistent ER stress leading to autophagy in CRC cell lines. The prolonged autophagy and inhibition of PI3K and ERK pathways induced a P53-dependent G1 blockage of the cell cycle. Example 4: PAA potentiates the anti-tumor effect of 5-FU on CRC In colorectal cancer (CRC), 5-fluorouracil (5-FU) treatment has a limited overall response rate, unavoidable drug resistance, and high-dosage side effects. To investigate whether PAA treatment could potentiate the effect of 5-FU in vitro, first HCT116 and RKO cells were treated with PAA alone (0, 10, and 50 μM) or in combination with 5-FU (10 μM, minimum effective dosage, FIG. 9A and 9B) and then a cell viability assay was performed. For both CRC FHOO^OLQHV^^^^^KRXUV^RI^FRPELQHG^WUHDWPHQW^VLJQLILFDQWO\^GHFUHDVHG^WKH^FHOO^YLDELOLW\^FRPSDUHG^WR^ PAA (50 μM) or 5-FU (10 μM) alone (FIG. 4A). These results were further supported by an Annexin V / PI experiment to quantify cell death after single-agent or combined treatment. For both cell lines, combined treatment with PAA 50 μM and 5-FU induced more cell death than PAA alone or 5-FU alone (FIG. 10A and 10B). Also, cells treated with combined treatment Docket No.103361-541WO1 showed a decrease in total PARP and full-length caspase 3 proteins, both of which are markers of induced apoptosis (FIG. 11). In two distinct patient-derived CRC organoid lines treated with PAA (50 μM) and / or 5-FU (10 μM), similar results were observed (FIG. 4B). Furthermore, immunostaining for Ki-^^^ZDV^SHUIRUPHG^WR^IXUWKHU^LQYHVWLJDWH^WKH^SUROLIHUDWLYH^SRWHQWLDO^RI^FHOOV^ and organoids after PAA and / or 5-FU treatment. As shown in FIG. 4C, the combined treatment in both CRC cell lines significantly decreased Ki-^^^VWDLQLQJ^ZKHQ^FRPSDUHG^ZLWK^WKH^^^^^0^ PAA or 5-FU alone. Similar results were observed in both CRC organoid lines (FIG. 4D). Interestingly, it was noticed that the size of organoids was also strongly affected with combined treatment yielding small organoids. The impact of PAA treatment on cell clonogenicity of CRC cell lines with or without 5- FU was further tested. For both cell lines, 10μM PAA treatment did not affect clonogenicity. However, treatment with 50 μM PAA significantly decreased the clonogenicity capacities in HCT116 and RKO. The combined treatment of PAA and 5-FU showed a significant decrease in the number of colonies compared to PAA or 5-FU alone (FIG. 4E). Taken together, these results confirmed the combined treatment of PAA and 5-FU effect on suppressing viability and colony formation of CRC cells and organoids. Lastly, it was evaluated if the in vitro observations were reproducible in an in vivo model. A CRC mouse xenograft model was established using the RKO cell line. After injection of 1 x 106cells subcutaneously, tumors were allowed to grow to a size of approximately 200mm3before mice were randomized into four groups (control, PAA 20mg / kg, 5-FU 10mg / kg, and combined treatment of PAA+5-FU). Tumor size was measured daily using calipers. As described in FIG. 2F, PAA treated group exhibited a significantly slower growth kinetic compared with the control condition (linear regression; p<0.0001) (FIG.4F). The same effect was observed in the group treated with 5-FU. Interestingly, a significant difference between single agent PAA and single agent 5-FU was not observed. However, the combined treatment group exhibited significantly slower growth compared to the control, PAA alone, and 5-FU alone groups (p<0.0001). Measured 21 days after randomization, the tumor size of the group treated with PAA showed a significant decrease by 33.0% compared to control (p=0.031) (FIG. 2G). The group treated with 5-FU alone showed a significant decrease in tumor size compared to the control group by 34.3% (p=0.031). Finally, the study group which received combined treatment yielded D^VLJQLILFDQW^GHFUHDVH^LQ^WXPRU^VL]H^RI^^^^^^^FRPSDUHG^WR^WKH^FRQWURO^FRQGLWLRQ^^S ^^^^^^^^^FIG. 4F). Importantly, the tumors in the combined treatment group were also significantly smaller than the single agent PAA or single agent 5-FU groups. Together, these data demonstrate that treatment with PAA can potentiate the effect of 5-FU on colorectal cancer in vitro and in vivo. Docket No.103361-541WO1 Example 5: PAA induces ROS, DNA damage and cell cycle blockage Among its mechanisms of action, 5-FU is known to induce DNA double strand breaks (dDSB) leading to replication stress and blockage of cell cycle progression in the S phase and ultimately to cell death. In line with the previous results, dDSB and cell cycle progression responses were assessed to treatment with PAA alone, 5-FU alone, or combination treatment in HCT116 and RKO cell lines. Using immunofluorescence staining of Ȗ+^$;^^WKH^LQGXFWLRQ^RI^ dDSB was analyzed 24hrs after treatment. As shown in FIG. 5A, an increase of dDSB was observed in both cell lines after treatment with 5- FU. Exposure to PAA at increasing concentrations also induced a dose-GHSHQGHQW^SKRVSKRU\ODWLRQ^RI^+^$;^^D^NQRZQ^HIIHFW^RI^ aldehyde derivatives. Interestingly, the frequency of Ȗ+^$;-positive cells was significantly higher in the combined treatment than in PAA alone or 5-FU alone (FIG. 5A-Bottom panel). ROS are a common inducer of dDSB, therefore, it was tested if PAA could induce oxidative stress to enhance the cytotoxicity of 5-FU in CRC cells. Total ROS detection was examined in kinetics up to 4 hours after treatment of 10μM or 50μM of PAA. After PAA treatment, a rapid dose-dependent increase in ROS generation was observed compared to control conditions in both cell lines (FIG. 5B). Compared to control conditions, after 4 hours with 10 μM DQG^^^^^0^FXOWXUH^^526^LQFUHDVHG^E\^^^^^DQG^^^^^^UHVSHFWLYHO\^LQ^+&7^^^^^DQG^LQFUHDVHG^ ^^^^DQG^^^^^^UHVSHFWLYHO\^^LQ^WKH^5.2^FHOO^OLQH^^FIG. 5C). Adding the free radical scavenger N- acetylcysteine, abolished the PAA-induced effects, supporting mediation via ROS. (FIG. 5C). Together, these results show that PAA- induced oxidative stress generates dDSB which potentiates the 5-FU cytotoxic effect in CRC. In addition, a cell cycle distribution analysis was performed using flow cytometry to elucidate how the combination of PAA and 5-FU affected cell proliferation. Compared to control, CRC cells treated with PAA alone harbored a dose dependent G1 arrest (FIG. 5D). This is in accordance with the degradation of Cyclin D1 observed by Western blot (FIG. 11). On the other hand, treatment with 5-FU alone induced an increased proportion of blockage at the S phase (FIG. 5D), which is consistent with previous reports and in accordance with the accumulation of Cyclin El protein expression observed by Western blot compared to control condition (FIG. 11). In the combination of PAA and 5-FU, the proportion of cells in the G1 phase gradually increased and the proportion of cells in the S phase decreased compared to 5-FU alone (FIG. 5D). In summary, treatment with PAA induced generation of ROS altering the DNA integrity by creating dDSB. The PAA-induced DNA damage resulted in a G1 arrest of the cell cycle. Docket No.103361-541WO1 While 5-FU treatment also generated dDSB leading to a blockage in the S phase, the combined treatment created a greater amount of dDSB than either drug alone. Interestingly, the two molecules showed capacities to induce cell cycle blockage at a different phase which potentially explains the stronger effect on induction cell death and decrease of proliferation while combined. Discussion This study demonstrates that the phenylalanine metabolite, PAA, is a potential diagnostic biomarker and therapeutic agent for CRC. By using targeted GC-MS / MS and metagenomic analysis in clinical samples, it was found that serum PAA levels and its correlated bacteria were decreased in CRC patients compared to healthy patients. Based on this finding, further experimentation discovered that PAA inhibits CRC development and potentiates the 5-FU anti- cancer effect. Investigation into the mechanism revealed that PAA induced ROS which ultimately generated DNA damages and in parallel initiated ER stress-induced autophagy leading to down-regulation of PI3K / AKT / mTOR and ERK signaling pathway, cell cycle blockage, and ultimately cell death (FIG. 6). Decreased human serum PAA levels in CRC patients compared to healthy controls is a novel discovery. There is clearly a clinical need to develop new biomarkers that might portend the development of CRC before it would otherwise be detected. The findings suggest that declining serum PAA levels could serve as such a marker. The presented data supports the rationale for larger scale patient evaluations and validation. Several mechanisms might be responsible for the source of PAA in humans. First, the metabolism of Phe by the liver, which maintains the stability of circulating Phe concentrations as this amino acid is essential and not synthesized by the host. Notably, due to constant exposure of the liver to bacterial components transported through the portal vein, altered microbial metabolites of Phe have long been observed in liver diseases and gut microbial dysbiosis. Next, as an essential aromatic amino acid from food, Phe is actively catabolized by gut microbiota. For example, betaproteobacterium could anaerobically degrade Phe to PAA by transamination and decarboxylation. Furthermore, the production of the natural flavor compound PAA in the food industry is mostly biosynthesized by microorganisms, such as Escherichia coli and yeast. Thus, it was hypothesized that microbial metabolism is an important source of human circulating PAA Previous studies have proven that the altered gut microbiota of CRC results in the accumulation or loss of microbiota-derived metabolites that promote tumor progression. However, there has not been an investigation of tumor-associated bacteria related to PAA synthesis. To address this issue, based on Spearman's correlation coefficient, the level of PAA in serum with bacteria abundances was correlated using metagenomics analysis. It was determined that the bacterial Docket No.103361-541WO1 species that positively correlated with PAA serum level were Clostridium sp.UNK.MGS6, Firmicutes bacterium CAG41, Coprobacillus cateniformis, and Roseburia sp.CAG303 and were significantly elevated in healthy control. However, it was found that the abundance of species negatively correlated to the level of PAA in serum, Alistipes sp.CAG435, Fusobacterium hwasookii, Bacillus sp.5B6, and Bacillus velezensis were significantly increased in CRC. Consistently, Clostridium and Firmicutes are predominant genera in the human intestine involving maintenance of intestinal homeostasis and barrier function. Several gut symbiont Clostridium spp. have been found to generate aromatic amino acid metabolites, which supports the maintenance of PAA levels in healthy people. Moreover, Roseburia spp. are short-chain fatty acids-producing anaerobic bacteria belonging to the Clostridium cluster, and their immunity maintenance, colonic motility, and anti-inflammatory properties have been characterized. Therefore, the decreased abundance of PAA-correlated healthy bacteria, such as Clostridium spp., Firmicutes spp., and Roseburia spp. in CRC may influence the decline of PAA. In contrast, PAA level was found to be negatively correlated to the relative abundance of Fusobacterium spp., a typical CRC-specific bacteria that promotes tumor progression and is capable of being a prognostic biomarker for CRC patients. Interestingly, a previous study showed that phenyl lactic acid, an end product of PAA metabolism, was among the major metabolites of Fusobacterium spp., which supports the finding of a potential negative association between PAA level and Fusobacterium. Taken together, these findings explain the difference in PAA level, but also provides important clinical implications for future microbial-based PAA diagnosis and treatment in CRC. Overexpression of the PI3K / Akt / mTOR signaling pathway, involved in the regulation of cellular proliferation and survival, has been reported in various cancers, especially in CRC. In addition, activation of the ERK pathway plays an important part in CRC progression. Theresults support that PAA is a critical regulator of CRC cell proliferation and survival based on PI3K / Akt / mTOR and ERK pathway. However, the function of PAA related to potentiation of 5- FU is unknown. 5-FU, is a first-line adjuvant chemotherapy in CRC and acts by targeting S- phase cells. The results show that single agent 5-FU enhanced CRC cell death and S phase blockage. It was also found that PAA added to 5-FU induced more cell death and G1 phase blockage through a DNA damage mechanism. So, the combination of both could be a potential multi-target tool against cancer. Several studies have shown that aldehyde groups, including acetaldehyde and benzaldehyde, can result in an increase in ROS generation, damaging proteins and lipid functions. Along with the induction of ROS, the aldehyde-induced damaged proteins and lipids Docket No.103361-541WO1 can trigger the endoplasmic reticulum stress (ERS) pathway. ERS activates an intracellular signal transduction pathway, called unfolded protein response (UPR). The UPR is tailored essentially to reestablish ER homeostasis through adaptive mechanisms involving the stimulation of autophagy. While the activation of the ER stress pathway in cancer cells confers resistance to stressful environments, it is also known that chronic ER stress induction can be detrimental. Indeed, many biomolecules are able to generate apoptosis in cancer by inducing ERS-induced autophagy. Indeed, ERS- induced ROS via PAA is demonstrated in the study. In conclusion, the findings provide novel evidence that decreased levels of the bacteria metabolite PAA serve as a CRC biomarker, and its associated bacteria may contribute to CRC development. Decrease in PAA, which has pro-tumor effects via PI3K / AKT / mTOR and ERK / MARK pathways may allow unchecked pathways to trigger dysplastic and malignant changes. Furthermore, increasing PAA levels in the local tumor environment could enhance the therapeutic effectiveness of 5-FU. Materials and Methods Patients and specimen collection. For the test cohort, blood draw and feces samples were collected from 30 CRC patients at the time of diagnosis before surgery or chemotherapy treatment, and from 30 age- and gender-matched healthy controls in Shanghai Tenth People's Hospital affiliated with Tongji University from ^^^^ to 2018 (Patient demographics are provided in Table 1). Serum was collected by centrifuging the blood draw 500g 15min at 4°C and submitted to a target metabolite analysis described below. Genomic DNA was extracted from stool samples to run metagenomic sequencing in order to analyze the bacterial abundance. )RU^WKH^YDOLGDWLRQ^FRKRUW^^VHUXP^VDPSOHV^IURP^^^^&5&^SDWLHQWV^DW^WKH^WLPH^RI^GLDJQRVLV^ before surgery or chemotherapy treatment, and from 53 age- and gender-matched healthy controls were collected from the Biospecimen Service Shared Resource / Total Cancer Care / Biorepository at The Ohio State University Comprehensive Cancer Center, Columbus (Table 2). For the generation of CRC organoids, tumor samples from CRC patients were obtained within an IRB-approved biobank with written informed consent. Metabolite extraction. From serum samples, 100μL of each was taken and placed in a 2mL Eppendorf tube then deproteinized by adding 400μL of ice-cold methanol. The samples were vortexed at maximum speed for 30s and incubated at -20°C for 2 hours. Then, they were centrifuged at 12000g for 15 min at 4°C. 100μL supernatant was transferred into a GC injection vial and proceeded by GC-MS / MS. Targeted GC-MS / MS. Phenylacetaldehyde was isolated using chromatography on a Docket No.103361-541WO1 Thermo Scientific TSQ8000 EVO GC-MS / MS column using Thermo Scientific InoVax (Agilent +3^,112:$;^^^Pî^^^^PPî^^^^^P^^^&ROXPQ^WHPSHUDWXUH^^7KH^LQLWLDO^WHPSHUDWXUH^ZDV^ maintained at 50°C for 1 min. 20°C / min, rise to 250°C, hold for 4 min; Flow rate: 1ml / min. Inlet temperature: 250°C; Split ratio: 10:1; Mass spectrometry transfer temperature 250°C; MS Source :200°C; Scan :50-500; Reaction gas: helium. Metagenomic sequencing. The bacterial DNA was extracted from frozen fecal samples using QIAamp Fast DNA Stool Mini Kit (Qiagen, Hilden, Germany). The DNA concentration was measured by NanoDrop (Thermofisher, MA, USA) and Qubit®2.0 (Invitrogen, CA, USA). TruSeq DNA HT Sample Prep Kit (Illumina, CA, USA) was used for library construction. The quality of all libraries was estimated by Agilent Bioanalyzer 2100 (Agilent Technologies, CA, USA). The libraries constructed from all samples were pooled and sequenced on the +LVHT^;-ten platform (Illumina). Raw paired-end reads were screened using the following criteria: (l) reads containing ambiguous bases were deleted; (2) reads with low-quality bases (Q < 20) were trimmed; (3) reads with less than 60% of high-quality bases (Phred score 2: 20) were removed. Then, clean reads were aligned against all known bacterial genomes from the National Center for Biotechnology Information GenBank with SOAPaligner (version 2.21). The aligned reads were classified as different taxonomic ranks to count classification and relative abundance. Cell culture. Two CRC cell lines (HCT116, and RKO) were purchased from the American Type Culture Collection. The cell lines were verified by short tandem repeat analysis and cultured in modified DMEM containing 10% FBS, and 1% penicillin-VWUHSWRP\FLQ^DW^^^^&^^ Cell lines were verified by Short Tandem Repeat analysis using 10 markers. All experiments were realized with cell lines and organoids ranging from passage 1 to passage 20. Organoid generation and maintenance. Quickly after harvesting, the tissues were processed as previously reported. The organoid media was changed every two days. All experiments were carried out with organoids ranging from passage 1 to passage 20. Murine model. To investigate the effect of PAA (FIG. ^) on CRC in vivo, a total of 1 x 106viable RKO cells were resuspended in 200 μL of PBS and injected s.c. in the flank of 6- week-old female NSG mice obtained from Ohio State University according to an IACUC- approved protocol. Once the tumor volume reached a size of 200 mm3, mice were randomized into 4 groups of five mice receiving different treatments (Control condition, PAA 20mg / kg, 5- FU 10mg / kg, PAA+5-FU). Mice were injected intraperitoneally with corresponding treatment for two rounds of five consecutive days with two days in between (FIG. 2E). Tumor volumes were recorded daily using calipers. Mice were euthanized on day 21. Docket No.103361-541WO1 Chemicals and treatment. PAA was purchased from MP Biomedicals (ref# 156145, CA, USA). 5-FU was purchased from Tokyo Chemical Industry (ref# FO151, Tokyo, Japan). Cells and organoids were exposed to PAA alone or in combination with 5-)8^IRU^^^^RU^^^^KRXUV^ according to the experiments. Regular medium with 0.1% DMSO was used as vehicle control. ATP viability assay. ATP viability assay was performed with CellTiter-Glo® 2.0 Assay for cell lines, and CellTiter-Glo® 3D Cell Viability Assay for organoid lines, according to the manufacturer's protocol (Promega, WI, USA). Cells or organoids were lysed with CellTiter- Glo® Reagent (100 μL) for 30 min. A luminescence signal was detected by BioTek microplate reader (Cytation 5, VT, USA). Colony formation. Cells were seeded in T25 flasks at a density of 15 x 104for RKO or 25 x 104for HCT116. After the treatment with PAA alone or in combination with 5-FU for 144 hours, the colonies were fixed with absolute ethanol and stained with crystal violet. The experiments were done in triplicate. Annexin V / propidium iodide (PI) apoptosis assay. Cells were cultured in 6-well plates with PAA alone or in combination with 5-)8^IRU^^^^KRXUV^^7KH^FHOOV^ZHUH^VWDLQHG^ZLWK^),7&- Annexin V solution and PI solution before being examined using flow cytometry. Positive cell death was counted by adding up cells being Annexin V+ / PI+, Annexin V+ / PI-, and Annexin V- / PI+. Cell cycle distribution analysis. Cells were cultured in 6-well plates with PAA alone or in combination with 5-FU for 24hrs. Cells were then fixed with ice-FROG^^^^^HWKDQRO^DQG^VWRUHG^ at -20°C overnight. Cells were treated with RNase A and subsequently stained with Propidium Iodine solution. The cell cycle was analyzed using an LSRII flow cytometer (BD Biosciences, CA, USA). The total amount of cell death was calculated by adding Annexin V+ / PI-, Annexin V- / PI+, and Annexin V+ / PI+ population. RNA sequencing (RNA-Seq). RNA was extracted using RNeasy Plus Mini Kit (Qiagen, #^^^^^^^DQG^TXDQWLILHG using NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA). The RNA integrity was assessed by Bioanalyzer 2100 (Agilent, CA, USA) and confirmed by electrophoresis with denaturing agarose gel. Poly (A) RNA is purified from 1μg total RNA using Dynabeads Oligo (dT)25-61005 (Thermo Fisher, CA, USA) using two rounds of purification. Cleaved RNA fragments were copied into double-stranded cDNA using (sequentially) reverse transcriptase, random primers, DNA polymerase, and RNase H. Following ligation of the sequencing adapter, the cDNA products were purified. The average insert size for the final cDNA library was 300±50 bp. Finally, the 2x150 bp paired-end sequencing (PE150) was performed on an Illumina Novaseq™ 6000 (LC-BioTechnology CO., Ltd., Hangzhou, China) Docket No.103361-541WO1 following the vendor's recommended protocol. After removing the low-quality bases and undetermined bases, HISAT2 software was used to map reads to the genome. After the final transcriptome was generated, StringTie and ballgown were used to estimate the expression levels of all transcripts and perform expression levels for mRNAs by calculating FPKM. The differentially expressed mRNAs were selected with fold change >2 or fold change <0.5 and p- value <0.05 by R package edgeR or DESeq2. Immunohistochemistry assay. Organoids were fixed with PFA 4% and included in an agarose plug (1.5%). The agarose plugs were paraffin-embedded and sectioned in 5 μm slices before being stained as described previously. Ki-^^^DQWLERG\^^&HOO^6LJQDOLQJ^7HFKQRORJ\^>&67@^^ ref# 9129S) and H&E staining reagent were used for organoid THC. Images were collected on ECHO laboratories RVL-100-G microscope. Immunofluorescence assay. HCT116 and RKO were grown on glass coverslips and treated with PAA alone or in combination with 5-FU for 24 hours. Cells were then fixed with 4% SDUDIRUPDOGHK\GH^DQG^SHUPHDELOL]HG^ZLWK^D^VROXWLRQ^FRQWDLQLQJ^^^P0^+(3(6^>S+^^^^@^^^^P0^ NaCl, 3mM MgCl2, 300mM Sucrose, and 0.5% Triton. Cells were blocked for 15 min with 3% ERYLQH^VHUXP^DOEXPLQ^DQG^^^^PLON^IROORZHG^E\^LQFXEDWLRQ^ZLWK^.L^^^DQWLERG\^^&67^^UHI^ 9129S, 1:800) or Ȗ+^$; DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^IRU^RQH^KRXU^DW^URRP^WHPSHUDWXUH^^ accordingly. Cells were washed and incubated with secondary antibody (Sigma-Aldrich, ref# A0545, 1:1000 dilution) and mounted with Vectashiled DAPI. Images were collected on a Leica Microsystems confocal microscope (DM16000). Western blot. Western blot assay was performed as described previously. The primary antibody was used in the present study including Phospho-$.7^DQWLERG\^>&HOO^6LJQDOLQJ^ 7HFKQRORJ\^^&67^^^UHI^^^^^^6^^^^^^^^@^^$.7^DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^^^3KRVSKR- S^^^DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^^^3^^^DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^P725^ antibody (CST, ref# 2983S, 1:1000), Phospho-(5.^DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^^^(5.^ DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^^^(7)^(^DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^^^^3KRVSKR- &KN^^^^&67^^^UHI^^^^^^^7^^^^^^^^^^^^^S^^^^DQWLERG\^^^6DQWD^^&UX]^%LRWHFKQRORJ\^^UHI^^VF-126, ^^^^^^^^^S^^^DQWLERG\^^&67^^UHI^^^^^^7^^^^^^^^^^^Ȗ+^$; DQWLERG\^^&67^^UHI^^^^^^6^^^^^^^^^^ Caspase-3 antibody (CST, ref# 9662S, 1:1000), PARP antibody (CST, ref# 9532T, 1:1000), Cyclin D1 (CST, ref# 55506T, 1:1000), Cyclin E1 antibody (CST, ref# 4129T, 1:1000), Beclin DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^ / &^%7^77^DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^^$7*^^^^ DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^%L3^*53^^^DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^SKRVSKRU- eiF2a antibody (CST, ref# 3398, 1:1000), eiF2a antibody (CST, ref# 5324, 1:1000), phosphor- -1.^DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^-1.^DQWLERG\^^&67^^UHI^^^^^^^^^^^^^^^^^3^^^DQWLERG\^ Docket No.103361-541WO1 (CST, ref# 88588, 1:1000), P-actin antibody (Santa Cruz Biotechnology, ref# sc-^^^^^^^^^^^^^^^^ $IWHU^LQFXEDWLRQ^ZLWK^WKH^VHFRQGDU\^DQWLERGLHV^^&67^^UHI^^^^^^^^^^^^^^^GLOXWLRQ^^&67^^UHI^^ ^^^^^^^^^^^^^GLOXWLRQ^^^WKH^DQWLJHQ-antibody complex on the membrane was detected with 6XSHU6LJQDO^:HVW^'XUD^([WHQGHG^'XUDWLRQ^6XEVWUDWH^^7KHUPR^6FLHQWLILF^^UHI^^^^^^^^^0$^^ USA). Total ROS quantification. 1x105of RKO or HCT116 cells were seeded into 12-well SODWHV^^&HOOV^ZHUH^LQFXEDWHG^RYHUQLJKW^LQ^'0(0^DW^^^^&^LQ^DQ^DWPRVSKHUH^RI^^^^&2^^^7KH^QH[W^ day, cells were treated with 100μM H2O2 for positive control, 10mM of N-Acetylcysteine for negative control, 10 or 50 μM of PAA in combination of not with N-Acetylcysteine. Total ROS and superoxide levels in live, unfixed cells were measured by a total ROS / superoxide kit per manufacturer's instructions (Invitrogen ref# 88-5930) and analyzed using Cytation 5 (Agilent ref# CYT5FV) luminescence plate reader in kinetic from 15min to 4 hours at 488nM excitation and 520nM emission wavelength. Statistical Analysis. Data were presented as the mean ± standard error of the mean (SEM). All the statistical analysis was done using GraphPad Prism 9 software (GraphPad Inc, CA, USA) or R software (version 4.0.3). An analysis of tumor growth comparing different groups was done using linear regression. Qualitative variables were compared using a chi-square test or Fisher's exact test, while quantitative variables were compared using the unpaired or paired two-tailed Student t-test or Mann-Whitney U test, accordingly. Statistical comparison of multiple groups was analyzed by one-way ANOVA followed by Tukey's or Games-Howell post- hoc comparison test. A p-value of < 0.05 indicated statistical significance (*p<0.05, **p <0.01, ***p <0.001). ^^ Docket No.103361-541WO1 References x Adamsen, B. L., Kravik, K. L. & De Angelis, P. M. DNA damage signaling in response to 5-fluorouracil in three colorectal cancer cell lines with different mismatch repair and TP53 status. Int J Oncol ^^^^^^^-682 (2011). x Alnuqaydan, A. M., Rah, B., Almutary, A. G. & Chauhan, S. S. Synergistic antitumor effect of 5-fluorouracil and withaferin-A induces endoplasmic reticulum stress- mediated autophagy and apoptosis in colorectal cancer cells. Am J Cancer Res ^^^^^^^-815 (2020). x Antiabong, J. F., Ball, A. S. & Brown, M. H. The effects of iron limitation and cell density on prokaryotic metabolism and gene expression: Excerpts from Fusobacterium QHFURSKRUXP^VWUDLQ^^^^^^VKHHS^LVRODWH^^^Gene 563, 94-102 (2015). x Blondy, S. et al. 5-Fluorouracil resistance mechanisms in colorectal cancer: From classical pathways to promising processes. Cancer Sci 111, 3142-3154 (2020). x Bultman, S. J. Interplay between diet, gut microbiota, epigenetic events, and colorectal cancer. Mol Nutr Food Res ^^^^^^^^^^^ x Chen, K.-Y., Chen, Y.-J., Cheng, C.-J., Jhan, K.-Y. & Wang, L.-C. Benzaldehyde Attenuates the Fifth Stage Larval Excretory-Secretory Product of Angiostrongylus cantonensis- Induced Injury in Mouse Astrocytes via Regulation of Endoplasmic Reticulum Stress and Oxidative Stress. Biomolecules ^^^^^^^^^^^^^^^ x Choi, H. S., Kim, S.-L., Kim, J.-H., Ko, Y.-C. & Lee, D.-S. Plant Volatile, Phenylacetaldehyde Targets Breast Cancer Stem Cell by Induction of ROS and Regulation of Stat3 Signal. Antioxidants (Basel) 9, E1119 (2020). x Chok, K. C., Koh, R. Y., Ng, M. G., Ng, P. Y. & Chye, S. M. Melatonin Induces Autophagy via Reactive Oxygen Species-Mediated Endoplasmic Reticulum Stress Pathway in Colorectal Cancer Cells. Molecules 26, 5038 (2021). x Coker, O. O. et al. Altered gut metabolites and microbiota interactions are implicated in colorectal carcinogenesis and can be non-invasive diagnostic biomarkers. Microbiome 10, 35 (2022). x Cui, J. et al. Acetaldehyde Induces Neurotoxicity In Vitro via Oxidative Stress- and Ca2+ Imbalance-Mediated Endoplasmic Reticulum Stress. Oxid Med Cell Longev ^^^^^^^^^^^^^^ (2019). x De Angelis, P. M., Svendsrud, D. H., Kravik, K. L. & Stokke, T. Cellular response to 5- fluorouracil (5-FU) in 5-FU-resistant colon cancer cell lines during treatment and recovery. Molecular Cancer 5, 20 (2006). Docket No.103361-541WO1 x Dodd, D. et al. A gut bacterial pathway metabolizes aromatic amino acids into nine circulating metabolites. Nature 551, 648-^^^^^^^^^^^ x Duncan, S. H. et al. Proposal of Roseburia faecis sp. nov., Roseburia hominis sp. nov. and Roseburia inulinivorans sp. nov., based on isolates from human faeces. Int J Syst Evol Microbiol ^^^^^^^^-2441 (2006). x Etschmann, M. M. W. & Schrader, J. An aqueous-organic two-phase bioprocess for efficient production of the natural aroma chemicals 2-phenylethanol and 2- phenylethylacetate with yeast. Appl Microbiol Biotechnol ^^^^^^^-443 (2006). x Fang, J. Y. & Richardson, B. C. The MAPK signalling pathways and colorectal cancer. Lancet Oncol 6, 322-^^^^^^^^^^^ x Ferrandon, S. et al. CoA Synthase (COASY) Mediates Radiation Resistance via PI3K Signaling in Rectal Cancer. Cancer Res 80, 334-346 (2020). x Goirand, F. et al. How can we best monitor 5-FU administration to maximize benefit to risk ratio? Expert Opin Drug Metab Toxicol 14, 1303-1313 (2018). x *XR^^'^^^=KDQJ^^ / ^^^3DQ^^+^^^^ / L^^;^^0HWDEROLF^HQJLQHHULQJ^RI^(VFKHULFKLD^FROL^IRU^ production of 2-Phenylethylacetate from L-phenylalanine. Microbiologyopen ^^^^^^^^^^ x Heidelberger, C. et al. Fluorinated pyrimidines, a new class of tumour-inhibitory compounds. Nature ^^^^^^^^-^^^^^^^^^^^ x Jain, N. & Walker, W. A. Diet and host-microbial crosstalk in postnatal intestinal immune homeostasis. Nat Rev Gastroenterol Hepatol 12, 14-25 (2015). x Kaminaga, Y. et al. Plant phenylacetaldehyde synthase is a bifunctional homotetrameric enzyme that catalyzes phenylalanine decarboxylation and oxidation. J Biol Chem ^^^^^^^^^^- 23366 (2006). x Keku, T. O., McCoy, A. N. & Azcarate-Peril, A. M. Fusobacterium spp. and colorectal cancer: cause or consequence? Trends Microbiol 21, 506-508 (2013). x Kim, S. Y. et al. Coptisine induces autophagic cell death through down-regulation of PI3K / Akt / mTOR signaling pathway and up-regulation of ROS-mediated mitochondrial dysfunction in hepatocellular carcinoma Hep3B cells. Arch Biochem Biophys ^^^^^^^^^^^^ (2021). x Li, C. et al. Dehydrodiisoeugenol inhibits colorectal cancer growth by endoplasmic reticulum stress-induced autophagic pathways. J Exp Clin Cancer Res 40, 125 (2021). x / LX^^<^^^+RX^^<^^^:DQJ^^*^^^=KHQJ^^;^^^^+DR^^+^^*XW^0LFURELDO^0HWDEROLWHV^RI^$URPDWLF^ Amino Acids as Signals in Host-Microbe Interplay. Trends Endocrinol Metab 31, 818-834 Docket No.103361-541WO1 (2020). x Longley, D. B., Harkin, D. P. & Johnston, P. G. 5-fluorouracil: mechanisms of action and clinical strategies. Nat Rev Cancer 3, 330-338 (2003). x Louis, P., Hold, G. L. & Flint, H. J. The gut microbiota, bacterial metabolites and colorectal cancer. Nat Rev Microbiol 12, 661-^^^^^^^^^^^ x Manzoni, M., Molinari, F., Tirelli, A. & Aragozzini, F. Phenylacetaldehyde by acetic acid bacteria oxidation of 2-phenylethanol. Biotechnol Lett 15, 341-346 (1993). x Marcobal, A., de las Rivas, B. & Mufioz, R. First genetic characterization of a bacterial beta-phenylethylamine biosynthetic enzyme in Enterococcus faecium RM58. FEMS Microbiol Lett 258, 144-149 (2006). x Marietta, C., Thompson, L. H., Lamerdin, J. E. & Brooks, P. J. Acetaldehyde Stimulates )$1&'^^0RQRXELTXLWLQDWLRQ^^+^$;^3KRVSKRU\ODWLRQ^^DQG^%5&$^^3KRVSKRU\ODWLRQ^LQ^+XPDQ^ Cells in Vitro: Implications for Alcohol-Related Carcinogenesis. Mutat Res ^^^^^^^-83 (2009). x Matsuzaki, K., Kumatoriya, K., Tando, M., Kometani, T. & Shinohara, M. Polyphenols from persimmon fruit attenuate acetaldehyde-induced DNA double- strand breaks by scavenging acetaldehyde. Sci Rep 12, 10300 (2022). x Miyoshi, H. & Stappenbeck, T. S. In vitro expansion and genetic modification of gastrointestinal stem cells in spheroid culture. Nat Protoc ^^^^^^^-2482 (2013). x Mohseni, A. H., Taghinezhad-6^^6^^^^)X^^;^^*XW^PLFURELRWD-derived metabolites and colorectal cancer: New insights and updates. Microb Pathog 149, 104569 (2020). x Mota-Gutierrez, J., Barbosa-Pereira, L., Ferrocino, I. & Cocolin, L. Traceability of Functional Volatile Compounds Generated on Inoculated Cocoa Fermentation and Its Potential Health Benefits. Nutrients 11, E884 (2019). x Narayanankutty, A. PI3K / Akt / mTOR Pathway as a Therapeutic Target for Colorectal Cancer: A Review of Preclinical and Clinical Evidence. Curr Drug Targets ^^^^^^^^-1226 (2019). x Nguyen, L. H. et al. Association Between Sulfur-Metabolizing Bacterial Communities in Stool and Risk of Distal Colorectal Cancer in Men. Gastroenterology 158, 1313-1325 (2020). x Panoutsopoulos, G. I., Kouretas, D., Gounaris, E. G. & Beedham, C. Enzymatic oxidation of 2-phenylethylamine to phenylacetic acid and 2-phenylethanol with special reference to the metabolism of its intermediate phenylacetaldehyde. Basic Clin Pharmacol Toxicol ^^^^^^^-^^^^ (2004). x Sarvestani, S. K. et al. Induced organoids derived from patients with ulcerative colitis Docket No.103361-541WO1 recapitulate colitic reactivity. Nat Commun 12, 262 (2021). x Schmitt, G., Arndt, F., Kahnt, J. & Heider, J. Adaptations to a Loss-of-Function Mutation in the Betaproteobacterium Aromatoleum aromaticum: Recruitment of Alternative Enzymes for Anaerobic Phenylalanine Degradation. J Bacteriol 199, e00383-^^^^^^^^^^ x Seidenberg, M., Martinez, R. J., Guthrie, R., Minnemeyer, H. & Tieckelmann, H. Phenylalanine metabolism: the production of phenylacetaldehyde by a Proteus species. Arch Biochem Biophys ^^^^^^^-^^^^^^^^^^^ x Seo, B. et al. Roseburia spp. Abundance Associates with Alcohol Consumption in Humans and Its Administration Ameliorates Alcoholic Fatty Liver in Mice. Cell Host Microbe ^^^^^^-40.e6 (2020). x Shah, M. A. & Schwartz, G. K. Cell cycle-mediated drug resistance: an emerging concept in cancer therapy. 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Sci Rep 9, 1505 (2019). x :DQJ^^;^^et al. Psoralen inhibits malignant proliferation and induces apoptosis through WULJJHULQJ^HQGRSODVPLF^UHWLFXOXP^VWUHVV^LQ^KXPDQ^600&^^^^^KHSDWRPD^FHOOV^^Biol Res 52, 34 (2019). x Wiggins, T., Kumar, S., Markar, S. R., Antonowicz, S. & Hanna, G. B. Tyrosine, phenylalanine, and tryptophan in gastroesophageal malignancy: a systematic review. Cancer Epidemiol Biomarkers Prev 24, 32-38 (2015). x Yan, T., Zhao, Y., Jiang, Z. & Chen, J. Acetaldehyde Induces Cytotoxicity via Triggering Docket No.103361-541WO1 Mitochondrial Dysfunction and Overactive Mitophagy. Mol Neurobiol 59, 3933-3946 (2022). x Yu, T. et al. Fusobacterium nucleatum Promotes Chemoresistance to Colorectal Cancer by Modulating Autophagy. Cell ^^^^^^^^-^^^^H^^^^^^^^^^ x Zagato, E. et al. Endogenous murine microbiota member Faecalibaculum rodentium and its human homologue protect from intestinal tumour growth. Nat Microbiol 5, 511-524 (2020). x Zhang, S. et al. Assessment of genotoxicity of four volatile pollutants from cigarette VPRNH^EDVHG^RQ^WKH^LQ^YLWUR^\+^$;^DVVD\^XVLQJ^KLJK^FRQWHQW^VFUHHQLQJ^^Environmental Toxicology and Pharmacology 55, 30-^^^^^^^^^^

[0002] Docket No.103361-541WO1 TABLES Table 1 depicts clinical characteristics of study cohort. Characteristics Control, (N=30) CRC, (N=30) P values Age (mean ± SEM) 63.0 ± 0.9 63.2 ± 1.3 0.9182 Gender 0.4118 Female12 8Male 18 22 Tumor location - Right - 3 Left - 12 Rectum - 15 Tumor size (cm) - <5 - 24 #5 - 6 Differentiation - Well-moderate - 29 Poor - 1 T stage - T1 - T2 - 6 T3 - T4 - 24 N stage - N0 - 18 N1 - N2 - 12 M stage - M0 - 28 M1 - 2 Docket No.103361-541WO1 Table 2 depicts clinical characteristics of validation cohort. Characteristics Control, (N=S3) CRC, (N=7S) P values Age (mean ± SEM) 60.0 ± 1.44 ^^^^^^^^^^ 0.6852 Gender 0.6136 Female28 43Male 25 32 Tumor location - Right - 22 Left - 15 Transverse 6 Rectum - 32 Tumor size (cm) - <5 - 24 #5 - 6 Differentiation - Well-moderate - 29 Poor - 1 Unknown - 45 T stage - T1 - T2 - 21 T3 - T4 - 54 N stage - N0 - ^^ N1 - N2 - 38 M stage - M0 - 55 M1 - 20 Docket No.103361-541WO1 Table 3 depicts Spearman's correlation coefficient and associated p-value between the relative abundance of species and PAA.

Claims

Docket No.103361-541WO1 CLAIMS What is claimed is:

1. A method of treating colorectal cancer in a subject, comprising: obtaining a sample from the subject; detecting the presence or absence of gut microbiota; wherein said gut microbiota comprises positively correlated bacteria that produce phenylacetaldehyde (PAA) and negatively correlated bacteria that do not produce PAA, wherein the positively correlated bacteria comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463, or wherein the negatively correlated bacteria comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670, wherein the subject is predicted to have colorectal cancer if the amount of positively correlated bacteria is lower in the subject than in comparison to a control or if the amount of negatively correlated bacteria is higher in the subject than in comparison to a control; and administering a therapeutically effective dose of PAA to the subject who is predicted to have colorectal cancer.

2. The method of claim 1, wherein the gut microbiota is determined by performing 16S rRNA based qPCR or metagenomics sequencing.

3. The method of claim 1 or 2, wherein the sample is serum, blood or fecal matter.

4. A method of detecting colorectal cancer in a subject, comprising: obtaining a sample from the subject; performing metagenomics sequencing or qPCR on the sample; andDocket No.103361-541WO1 determining positively and negatively correlated bacterial species to phenylacetaldehyde (PAA) production, wherein lower levels of PAA are negatively correlated to at least one bacterial species, wherein the negatively correlated bacterial species comprise Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670, wherein higher levels of PAA are positively correlated to at least one bacterial species, wherein the positively correlated bacterial species comprise Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463.

5. The method of claim 4, wherein the sample comprises fecal matter from the subject.

6. A method of determining a gut microbiota signature for cancer detection, comprising: obtain a serum sample from a subject and a control; determining phenylacetaldehyde (PAA) levels in the serum sample; obtaining a fecal sample from the subject and the control; performing metagenomic sequencing or qPCR on the fecal sample; and determining bacterial species which are positively and negatively correlated to the PAA levels in the serum sample, wherein positively correlated bacterial species produce PAA and negatively correlated bacterial species do not produce PAA, wherein the subject has cancer if the negatively correlated bacterial species are higher than positively correlated bacterial species in the subject as compared to the control. ^^ The method of claim 6, wherein the cancer is colorectal cancer.

8. The method of claim 6 RU^^, wherein lower levels of PAA are negatively correlated to at least one bacterial species, wherein the negatively correlated bacterial species comprise Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, ^^Docket No.103361-541WO1 Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670.

9. The method of claim 6 RU^^, wherein higher levels of PAA are positively correlated to at least one bacterial species, wherein the positively correlated bacterial species comprise Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463.

10. A method of treating colorectal cancer in a subject comprising: administering a therapeutically effective dose of phenylacetaldehyde (PAA) as an adjunct with a chemotherapy drug to the subject, wherein the chemotherapy drug is 5- fluorouracil.

11. A method for predicting a treatment response to cancer immunotherapy, comprising: obtaining a sample from a cancer subject; and detecting the presence or absence of gut microbiota, wherein said gut microbiota comprises good responder bacteria that are positively correlated to immunotherapeutic response and poor responder bacteria that are negatively correlated to immunotherapeutic response, wherein the good responder bacteria comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944 or Butyrivibrio txid1458463, wherein the poor responder bacteria comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743 or Bacillus txid492670, wherein the subject is predicted to positively respond to the cancer immunotherapy treatment if the good responder bacteria are higher in the subject than in comparison to a control, or wherein the subject is predicted to positively respond to the cancerDocket No.103361-541WO1 immunotherapy treatment if the poor responder bacteria are lower in the subject than in comparison to a control; and administering a therapeutically effective dose of phenylacetaldehyde (PAA) to the subject that is predicted not to positively respond to the cancer immunotherapy treatment.

12. The method of claim 11, wherein the cancer immunotherapy is an anti-PD-1 treatment.

13. The method of claim 11, wherein the cancer immunotherapy is an anti-CTLA-4 treatment.

14. A kit for detecting colorectal cancer in a sample from a subject, comprising: a panel of 10 bacterial species positively correlated with increased phenylacetaldehyde (PAA) levels in the subject, wherein the positively correlated bacterial species comprise at least one of Clostridium txid1638787, Clostridium txid1697791, Firmicute txid1263021, Coprobascillus txid100884, Coprobascillus txid127889, Coprobascillus txid1182556, Streptococcus txid99822, Acidaminococcus txid1203555, Roseburia txid1262944, or Butyrivibrio txid1458463; and a panel of 10 bacterial species negatively correlated with decreased PAA levels in the subject, wherein the negatively correlated bacterial species comprise at least one of Alistipes txid1262695, Fusobacterium txid1583098, Fusobacterium txid712288, Fusobacterium txid1032505, Leuconostoc txid1403934, Paenibacillus txid78058, Alcanivorax txid519051, Arthrobacter txid1690248, Bacillus txid1127743, or Bacillus txid492670.

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