Download PDF
Perspective  |  Open Access  |  23 Mar 2025

Microbiome as a predictive biomarker in locally advanced rectal cancer

Views: 40 |  Downloads: 26 |  Cited:  0
Microbiome Res Rep. 2025;4:18.
10.20517/mrr.2024.85 |  © The Author(s) 2025.
Author Information
Article Notes
Cite This Article

Abstract

The incidence of locally advanced rectal cancer (LARC) among young people is rising alarmingly. In recent years, new protocols have been introduced for the management of LARC, some of which are associated with the risk of significant toxicity. Despite these advancements, robust predictive biomarkers for LARC have yet to be established. The microbiome has emerged as a potential biomarker due to its interaction with tumor multiomics. This article provides a critical overview of the current evidence on the microbiome and LARC, including its relationship with the immune system and epigenomics, and also highlights both the current limitations and future perspectives in the field.

Keywords

Microbiome, locally advanced rectal cancer, epigenomics, exposome, Fusobacterium nucleatum

Colorectal cancer (CRC) is one of the three most prevalent cancers worldwide and a leading cause of cancer-related deaths[1]. From a pathogenesis perspective, Fearon and Vogelstein proposed a model in which multiple genomic aberrations accumulate progressively, leading to the malignant transformation from healthy mucosa to invasive carcinoma[2]. However, in recent years, growing evidence has highlighted the significance of the exposome in CRC development and outcomes[3]. Diet is among the most studied factors.

An anti-inflammatory diet, for instance, promotes the production of short-chain fatty acids that help maintain gut barrier integrity[4]. This dietary pattern has been associated with better outcomes in patients with stage III CRC featuring high-risk characteristics[5]. In contrast, a Western diet has been linked to a higher incidence of CRC, particularly in individuals with the presence of Fusobacterium nucleatum (Fn)[6] and pks+ Escherichia coli[7]. However, it is essential to consider the significant interindividual variability in CRC risk and evolution once diagnosed[8]. Beyond diet, other factors - such as physical activity[9], air pollution[10], microplastic intake[11], and disruptions in circadian rhythms[12] - are emerging as important contributors to CRC development. Given this complexity, molecular pathology epidemiology offers a framework to better understand the interactions between the external exposome and internal factors (including the microbiome). This framework also integrates multi-omics data (such as genomics, transcriptomics, immune contexture, and metabolomics) to provide a comprehensive view of CRC in individual patients[13]. In the near future, this approach should be incorporated into multimodal management strategies for CRC.

Rectal cancer accounts for approximately one-third of CRC cases, and it is one of the main tumor sites in patients under 50 years of age[1,14]. These patients belong to the entity early-onset CRC (EOCRC), and its incidence has been increasing globally[1,14]. Since 23% of rectal cancer cases are diagnosed in young people[15], EOCRC represents a significant health concern from medical, social, emotional, and occupational perspectives. It also poses a major challenge for the scientific community, as the underlying causes of EOCRC remain poorly understood[15]. It has been hypothesized that individuals born after 1960 may be part of a potential cohort effect, with increased exposure to various risk factors, such as “Western” dietary patterns, rising childhood and adolescent obesity, reduced physical activity, antibiotic use, and increased artificial feeding[14]. However, further research is required to validate these hypotheses. In addition to the EOCRC issue, rectal cancer - particularly locally advanced rectal cancer (LARC) - faces another challenge related to its therapeutic approach. In recent years, the classical preoperative protocols for LARC, which combine neoadjuvant radiotherapy (RT) with chemotherapy (CT) using fluoropyrimidines, have given way to total neoadjuvant treatment (TNT) regimens. The goal of TNT is to improve the rate of complete clinical responses (cCR)[16]. TNT regimens typically include CT-RT, followed by or preceded by polychemotherapy (mainly oxaliplatin and fluoropyrimidines), before standard surgery with total mesorectal excision[16]. However, these regimens may cause disabling adverse events, such as severe neurotoxicity, affecting up to 25% of patients[17]. Among patients who achieve a cCR - estimated at 16%-30%[18] - some may be eligible for Watch and Wait protocols at specialized centers, potentially avoiding surgical morbidity, including fecal and urinary incontinence, and sexual dysfunction[16]. However, the long-term prognostic impact for patients who experience tumor regrowth remains unclear[19].

One of the key challenges in LARC is the identification of predictive biomarkers for response and toxicity to neoadjuvant treatments. Currently, the pathological complete response and its correlation with improved survival[20], as well as the MSI-H/dMMR phenotype in less than 10% of patients and the associated benefit from immunotherapy[21], are the most relevant clinical examples. Recently, the microbiome has emerged as a potential biomarker for LARC.

Two meta-analyses published in 2019 found that the fecal microbiome in CRC patients is richer compared to non-CRC individuals, with a higher abundance of oral species, but with no differences in diversity. Functional analysis revealed an association between putrefaction, fermentation, and gluconeogenesis pathways with CRC[22,23]. Additionally, several species, such as Parvimonas spp., Fn, and Peptostreptococcus stomatis, were overrepresented in CRC samples compared to controls[22,23]. In LARC, multiple studies have described differences in microbiome patterns between pre- and post-neoadjuvant treatment in tumor or fecal samples, and these changes are preliminarily correlated with treatment benefits [Table 1].

Table 1

Examples of studies that have preliminarily identified associations between the presence of specific bacterial species and the outcomes of LARC patients undergoing neoadjuvant therapy

AuthorsnSampleTechniqueNegative associationPositive association
Teng et al.[54]353Fecal16S rRNABacteroides vulgatus
White et al.[57]107Tumor and adjacent normal tissueMetagenomic analysisFn, Bacteroides dorei, Ruminococcus bromii
Yi et al.[58]84Fecal16S rRNACoriobacteriaceae, FusobacteriumRoseburia, Dorea, Anaerostipes
Huang et al.[53]73Tumor tissueMetagenomic analysisStreptococcus equinus, Schaalia odontolytica, Clostridium hylemonae, Blautia producta, Pseudomonas azotoformans
Takenaka et al.[59]44Tumor tissue16S rRNAParaprevotella, EnhydrobacterHungatella, Flavonifractor, Methanosphaera

Among the various species, Fn, an anaerobic Gram-negative bacillus, is one of the most studied. A seminal study involving 143 LARC patients found that the persistence of Fn in surgical specimens, determined by RNA in situ hybridization (RNA-ISH) after CT/RT neoadjuvant treatment, was associated with a higher risk of local or distant recurrence [hazard ratio (HR) = 7.5, 95%CI: 3.0-19; P < 0.001][24]. Interestingly, the presence of Fn in diagnostic samples did not show the same correlation, nor did it correlate with the degree of response to neoadjuvant treatment. However, a statistically significant increase in the density of CD8+ cells was observed in patients who had no Fn in either pre- or post-neoadjuvant samples, or in those with Fn present only in pre-treatment samples, compared to patients with Fn present in both samples. These results suggest that Fn may be associated with reduced activation of the cytotoxic immune response, in line with preclinical data showing that Fn uses its virulence proteins to bind negative regulators of the immune cell cycle, such as TIGIT[25] and CEACAM1[26], leading to poor CD4+/CD8+ T-cell infiltration[27]. Contrary to what might be expected based on these properties, Fn has been preliminarily proposed as a favorable biomarker for immunotherapy benefit in MSS CRC. Preclinical data suggest that Fn may enhance the cytotoxic effect of CD8+ T cells through the generation of butyric acid, which mediates epigenomic events that lead to reduced PD-1 expression[28].

Despite promising results that are still pending validation in further studies, several caveats should be considered. Firstly, the prevalence of Fn in LARC is not well established. According to one of the largest series, which included more than 1,000 patients, the proportion of rectal cancers with high levels of Fn - detected by polymerase chain reaction (PCR) - is 2.5%[29]. However, this proportion likely reflects substantial inter- and intraindividual variability due to exposome-related factors such as geographic region and diet.

Secondly, there is no consensus on the best methodology for identifying this bacterium and its associated microbial communities, including sample processing, bioinformatics tools, and workflows. Moreover, the degree of concordance between microbiome patterns in fecal and tumor tissue remains largely unexplored, with existing data showing inconsistencies[30,31]. This issue is particularly relevant for Fn, as its representation in tumor tissue is higher than in fecal samples when 16S rRNA sequencing is used[32].

Thirdly, a comprehensive understanding of the oncogenic properties of Fn is necessary to fully determine whether its presence in LARC is a consequence of Fn itself, which could lead to new therapeutic strategies, or whether it results from tumor evolution that promotes Fn colonization. Preliminary data suggest that Fn exhibits pro-tumoral traits, as it promotes gut tumorigenesis in APCMin/+ mice through the activation of oncogenic pathways and modulation of the tumor microenvironment. Fn binds to Toll-like receptor 4, triggering MAPK pathway activation via miR-21[33] in CRC cell lines. It also activates the Wnt pathway by binding E-cadherin on CRC cells through FadA, one of its virulence proteins[34,35].

Finally, given the complexity of the human microbiome and its interactions with the host’s (epi)genetics, the transcriptional processes, and the immune system, it is currently difficult to propose a single species as a robust biomarker for LARC.

In parallel with LARC, microbiome analysis has also emerged as a potential biomarker for response and toxicity to immune checkpoint inhibitors (ICIs) in oncology. This opens the door to lessons learned from other cancer types that could be applied to LARC. For example, Akkermansia muciniphila has been preliminarily associated with better outcomes with ICIs, especially in non-small cell lung cancer[36]. The modulation of antitumor immune response by the microbiota occurs through various mechanisms: production of immunomodulatory metabolites by bacteria[37,38], bacterial migration from the gut to other organs[39], antigen mimicry[40], and direct modulation of the tumor microenvironment via immune checkpoint expression[41], lymphocyte trafficking molecules[42], or the production of chemokines like CXCL13[43]. Taking into account this network, bioinformatics approaches that consider not only microbial groups but also their interplay with the human host acting as a functional ecosystem, may offer more accurate predictions for immunotherapy outcomes[36]. This approach should be considered for LARC as more information becomes available, especially from mechanistic studies evaluating the immunomodulatory effects of RT and oxaliplatin-based CT.

In addition to immune responses, the analysis of epigenomic events is also highly relevant in LARC, given the rising incidence among young people[2]. Epigenomic analysis, using various approaches in tumor tissue, could provide valuable insights. One such approach involves the determination of methylation markers in specific genes, such as the hypomethylation of transcription factor AP-2 epsilon (TFAP2E)[44] and the hypermethylation of O-6-methylguanine-DNA methyltransferase (MGMT)[45], both of which are associated with a better response to neoadjuvant treatment. Additionally, baseline hypomethylation of long interspersed element-1 (LINE-1), which is linked to genomic instability, has been preliminarily associated with poorer survival and a higher risk of recurrence in LARC[46], as well as with physical inactivity, smoking, high BMI, and pesticide exposure[47]. Other approaches include determining the methylator phenotype (CIMP-H), although results have been inconclusive, or examining genome-wide methylation markers, which may prove more useful. For example, a preliminary study with 53 LARC patients treated with RT and 5FU-based CT showed that treatment could alter methylation patterns in tissue, and that low initial methylation levels were associated with a higher probability of treatment response[48]. Furthermore, the use of CpG island methylation arrays revealed that methylation patterns in regions near transcriptional regulatory zones of genes regulated by enhancer of zeste homolog 2 (EZH2) could discriminate the prognosis of LARC patients treated with neoadjuvant therapy[49].

Moreover, a link between epigenomics and the microbiome has been preliminarily described. A study in murine models showed that crypt cells in germ-containing models exhibited hypomethylation of elements regulating inflammatory processes compared to germ-free models. This was attributed to increased expression of ten-eleven-translocation 3 (TET3), an enzyme involved in DNA demethylation[50]. Similarly, it has been suggested that certain metabolites produced by gut bacteria, such as folate (produced by Bifidobacterium and Lactobacillus) and short-chain fatty acids like butyrate (mostly produced by Firmicutes), can influence DNA methylation[51,52]. Additionally, the presence of butyrate-producing bacteria in tissue has been associated with resistance to CT/RT[53], as has nucleotide biosynthesis mediated by Bacteroides vulgatus[54].

Finally, beyond its neoplastic effects, the microbiome has been preliminarily linked to surgical complications in LARC, such as low anterior resection syndrome[55], and even with depressive symptoms and sleep disturbances[56], suggesting the relevance of the gut-brain axis.

In conclusion, the microbiome holds promise as a biomarker in LARC. However, further collaborative efforts are needed to clarify its role in tumor carcinogenesis and standardize the methodology of analysis. Validation studies in patients should also consider the evolving exposome and other “omics” fields, such as epigenomics, to provide a comprehensive understanding of this disease, which notably affects young people.

DECLARATIONS

Authors’ contributions

Designed the outline of the manuscript and provided a clinical perspective: Mulet Margalef N, Manzano Mozo JL

Contributed to the redaction of the part related to microbiome and exposome: Obón-Santacana M, Borgognone A

Contributed to the redaction of the part related to epigenomics: Martín Abad B

Contributed to the redaction of the part related to immunity: Martínez-Balibrea E

All the authors have read and approved the manuscript.

Availability of data and materials

Not applicable.

Financial support and sponsorship

None.

Conflicts of interest

Mulet Margalef N has an advisory role for Amgen and has received travel grant support from Merck and MSD. Manzano Mozo JL has an advisory role for Merck Serono, Servier, Takeda, Pierre-Fabre, Novartis, and Bristol Myers Squibb. The other authors declared that there are no conflicts of interest.

Ethical approval and consent to participate

Not applicable.

Consent for publication.

Not applicable.

Copyright

© The Author(s) 2025.

REFERENCES

1. Morgan E, Arnold M, Gini A, et al. Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut. 2023;72:338-44.

2. Fearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell. 1990;61:759-67.

3. Botteri E, Peveri G, Berstad P, et al. Lifestyle changes in middle age and risk of cancer: evidence from the European Prospective Investigation into Cancer and Nutrition. Eur J Epidemiol. 2024;39:147-59.

4. Seethaler B, Nguyen NK, Basrai M, et al. Short-chain fatty acids are key mediators of the favorable effects of the Mediterranean diet on intestinal barrier integrity: data from the randomized controlled LIBRE trial. Am J Clin Nutr. 2022;116:928-42.

5. Cheng E, Ou FS, Ma C, et al. Diet- and lifestyle-based prediction models to estimate cancer recurrence and death in patients with stage III colon cancer (CALGB 89803/Alliance). J Clin Oncol. 2022;40:740-51.

6. Mehta RS, Nishihara R, Cao Y, et al. Association of dietary patterns with risk of colorectal cancer subtypes classified by Fusobacterium nucleatum in tumor tissue. JAMA Oncol. 2017;3:921-7.

7. Wang K, Lo CH, Mehta RS, et al. An empirical dietary pattern associated with the gut microbial features in relation to colorectal cancer risk. Gastroenterology. 2024;167:1371-83.e4.

8. Papier K, Bradbury KE, Balkwill A, et al. Diet-wide analyses for risk of colorectal cancer: prospective study of 12,251 incident cases among 542,778 women in the UK. Nat Commun. 2025;16:375.

9. Papadimitriou N, Kazmi N, Tsilidis KK, et al. Identifying metabolomic mediators of the physical activity and colorectal cancer relationship. Cancer Epidemiol Biomarkers Prev. 2025.

10. Jiang F, Zhao J, Sun J, et al. Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study. EBioMedicine. 2024;103:105126.

11. Bruno A, Dovizio M, Milillo C, et al. Orally ingested micro- and nano-plastics: a hidden driver of inflammatory bowel disease and colorectal cancer. Cancers. 2024;16:3079.

12. Stein MJ, Baurecht H, Bohmann P, et al. Diurnal timing of physical activity and risk of colorectal cancer in the UK Biobank. BMC Med. 2024;22:399.

13. Ogino S. Abstract IA019: molecular pathological epidemiology of tumor microbiota and immunity can give etiologic insights. Cancer Res. 2022;82:IA019.

14. Akimoto N, Ugai T, Zhong R, et al. Rising incidence of early-onset colorectal cancer - a call to action. Nat Rev Clin Oncol. 2021;18:230-43.

15. Spaander MCW, Zauber AG, Syngal S, et al. Young-onset colorectal cancer. Nat Rev Dis Primers. 2023;9:21.

16. Capdevila J, Gómez MA, Guillot M, et al. SEOM-GEMCAD-TTD clinical guidelines for localized rectal cancer (2021). Clin Transl Oncol. 2022;24:646-57.

17. Cheng F, Zhang R, Sun C, et al. Oxaliplatin-induced peripheral neurotoxicity in colorectal cancer patients: mechanisms, pharmacokinetics and strategies. Front Pharmacol. 2023;14:1231401.

18. van der Valk MJM, Hilling DE, Bastiaannet E, et al; IWWD Consortium. Long-term outcomes of clinical complete responders after neoadjuvant treatment for rectal cancer in the International Watch & Wait Database (IWWD): an international multicentre registry study. Lancet. 2018;391:2537-45.

19. Zwart WH, Hotca A, Hospers GAP, Goodman KA, Garcia-Aguilar J. The multimodal management of locally advanced rectal cancer: making sense of the new data. Am Soc Clin Oncol Educ Book. 2022;42:1-14.

20. Fokas E, Ströbel P, Fietkau R, et al; German Rectal Cancer Study Group. Tumor regression grading after preoperative chemoradiotherapy as a prognostic factor and individual-level surrogate for disease-free survival in rectal cancer. J Natl Cancer Inst. 2017;109:djx095.

21. Cercek A, Roxburgh CSD, Strombom P, et al. Adoption of total neoadjuvant therapy for locally advanced rectal cancer. JAMA Oncol. 2018;4:e180071.

22. Thomas AM, Manghi P, Asnicar F, et al. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat Med. 2019;25:667-78.

23. Wirbel J, Pyl PT, Kartal E, et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med. 2019;25:679-89.

24. Serna G, Ruiz-Pace F, Hernando J, et al. Fusobacterium nucleatum persistence and risk of recurrence after preoperative treatment in locally advanced rectal cancer. Ann Oncol. 2020;31:1366-75.

25. Gur C, Ibrahim Y, Isaacson B, et al. Binding of the Fap2 protein of Fusobacterium nucleatum to human inhibitory receptor TIGIT protects tumors from immune cell attack. Immunity. 2015;42:344-55.

26. Gur C, Maalouf N, Shhadeh A, et al. Fusobacterium nucleatum supresses anti-tumor immunity by activating CEACAM1. Oncoimmunology. 2019;8:e1581531.

27. Chen T, Li Q, Zhang X, et al. TOX expression decreases with progression of colorectal cancers and is associated with CD4 T-cell density and Fusobacterium nucleatum infection. Hum Pathol. 2018;79:93-101.

28. Wang X, Fang Y, Liang W, et al. Fusobacterium nucleatum facilitates anti-PD-1 therapy in microsatellite stable colorectal cancer. Cancer Cell. 2024;42:1729-46.e8.

29. Mima K, Nishihara R, Qian ZR, et al. Fusobacterium nucleatum in colorectal carcinoma tissue and patient prognosis. Gut. 2016;65:1973-80.

30. Vicente-Valor J, Tesolato S, Paz-Cabezas M, et al. Fecal microbiota strongly correlates with tissue microbiota composition in colorectal cancer but not in non-small cell lung cancer. Int J Mol Sci. 2025;26:717.

31. Valciukiene J, Strupas K, Poskus T. Tissue vs. fecal-derived bacterial dysbiosis in precancerous colorectal lesions: a systematic review. Cancers. 2023;15:1602.

32. Tesolato S, Ortega-Hernández A, Gómez-Garre D, et al. Gut microbiota profiles in feces and paired tumor and non-tumor tissues from colorectal cancer patients. Relationship to the body mass index. PLoS One. 2023;18:e0292551.

33. Yang Y, Weng W, Peng J, et al. Fusobacterium nucleatum increases proliferation of colorectal cancer cells and tumor development in mice by activating Toll-like receptor 4 signaling to nuclear factor-κB, and up-regulating expression of microRNA-21. Gastroenterology. 2017;152:851-66.e24.

34. Rubinstein MR, Wang X, Liu W, Hao Y, Cai G, Han YW. Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin/β-catenin signaling via its FadA adhesin. Cell Host Microbe. 2013;14:195-206.

35. Rubinstein MR, Baik JE, Lagana SM, et al. Fusobacterium nucleatum promotes colorectal cancer by inducing Wnt/β-catenin modulator Annexin A1. EMBO Rep. 2019;20:e47638.

36. Derosa L, Iebba V, Silva CAC, et al. Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome. Cell. 2024;187:3373-89.e16.

37. Sivan A, Corrales L, Hubert N, et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science. 2015;350:1084-9.

38. Bender MJ, McPherson AC, Phelps CM, et al. Dietary tryptophan metabolite released by intratumoral Lactobacillus reuteri facilitates immune checkpoint inhibitor treatment. Cell. 2023;186:1846-62.e26.

39. Daillère R, Vétizou M, Waldschmitt N, et al. Enterococcus hirae and Barnesiella intestinihominis facilitate cyclophosphamide-induced therapeutic immunomodulatory effects. Immunity. 2016;45:931-43.

40. Szallasi Z, Prosz A, Sztupinszki Z, Moldvay J. Are tumor-associated carbohydrates the missing link between the gut microbiome and response to immune checkpoint inhibitor treatment in cancer? Oncoimmunology. 2024;13:2324493.

41. Park JS, Gazzaniga FS, Wu M, et al. Targeting PD-L2-RGMb overcomes microbiome-related immunotherapy resistance. Nature. 2023;617:377-85.

42. Fidelle M, Rauber C, Alves Costa Silva C, et al. A microbiota-modulated checkpoint directs immunosuppressive intestinal T cells into cancers. Science. 2023;380:eabo2296.

43. Cremonesi E, Governa V, Garzon JFG, et al. Gut microbiota modulate T cell trafficking into human colorectal cancer. Gut. 2018;67:1984-94.

44. Ebert MP, Tänzer M, Balluff B, et al. TFAP2E-DKK4 and chemoresistance in colorectal cancer. N Engl J Med. 2012;366:44-53.

45. Jensen GL, Pourfarrokh N, Volz M, et al. Improved pathologic response to chemoradiation in MGMT methylated locally advanced rectal cancer. Clin Transl Radiat Oncol. 2023;42:100667.

46. Mima K, Nowak JA, Qian ZR, et al. Tumor LINE-1 methylation level and colorectal cancer location in relation to patient survival. Oncotarget. 2016;7:55098-109.

47. Del Re B, Giorgi G. Long INterspersed element-1 mobility as a sensor of environmental stresses. Environ Mol Mutagen. 2020;61:465-93.

48. Tsang JS, Vencken S, Sharaf O, et al. Global DNA methylation is altered by neoadjuvant chemoradiotherapy in rectal cancer and may predict response to treatment - a pilot study. Eur J Surg Oncol. 2014;40:1459-66.

49. Meng X, Huang Z, Wang R, et al. The prognostic role of EZH2 expression in rectal cancer patients treated with neoadjuvant chemoradiotherapy. Radiat Oncol. 2014;9:188.

50. Zouggar A, Haebe JR, Benoit YD. Intestinal microbiota influences DNA methylome and susceptibility to colorectal cancer. Genes. 2020;11:808.

51. Ansari I, Raddatz G, Gutekunst J, et al. The microbiota programs DNA methylation to control intestinal homeostasis and inflammation. Nat Microbiol. 2020;5:610-9.

52. Kopp M, Dürr K, Steigleder M, Clavel T, Rychlik M. Development of stable isotope dilution assays for the quantitation of intra- and extracellular folate patterns of Bifidobacterium adolescentis. J Chromatogr A. 2016;1469:48-59.

53. Huang X, Chen C, Xie W, et al. Metagenomic analysis of intratumoral microbiome linking to response to neoadjuvant chemoradiotherapy in rectal cancer. Int J Radiat Oncol Biol Phys. 2023;117:1255-69.

54. Teng H, Wang Y, Sui X, et al. Gut microbiota-mediated nucleotide synthesis attenuates the response to neoadjuvant chemoradiotherapy in rectal cancer. Cancer Cell. 2023;41:124-38.e6.

55. Kim MJ, Park S, Park JW, et al. Gut microbiome associated with low anterior resection syndrome after rectal cancer surgery. Sci Rep. 2023;13:8578.

56. González-Mercado VJ, Sarkar A, Penedo FJ, et al. Gut microbiota perturbation is associated with acute sleep disturbance among rectal cancer patients. J Sleep Res. 2020;29:e12915.

57. White MG, Damania A, Alshenaifi J, et al. Young-onset rectal cancer: unique tumoral microbiome and correlation with response to neoadjuvant therapy. Ann Surg. 2023;278:538-48.

58. Yi Y, Shen L, Shi W, et al. Gut microbiome components predict response to neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer: a prospective, longitudinal study. Clin Cancer Res. 2021;27:1329-40.

59. Takenaka IKTM, Bartelli TF, Defelicibus A, et al. Exome and tissue-associated microbiota as predictive markers of response to neoadjuvant treatment in locally advanced rectal cancer. Front Oncol. 2022;12:809441.

Cite This Article

Perspective
Open Access
Microbiome as a predictive biomarker in locally advanced rectal cancer
Núria Mulet Margalef, ... Mireia Obón-Santacana

How to Cite

Mulet, Margalef, N.; Martín Abad, B.; Martínez-Balibrea, E.; Manzano Mozo, J. L.; Borgognone, A.; Obón-Santacana, M. Microbiome as a predictive biomarker in locally advanced rectal cancer. Microbiome. Res. Rep. 2025, 4, 18. http://dx.doi.org/10.20517/mrr.2024.85

Download Citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click on download.

Export Citation File:

Type of Import

Tips on Downloading Citation

This feature enables you to download the bibliographic information (also called citation data, header data, or metadata) for the articles on our site.

Citation Manager File Format

Use the radio buttons to choose how to format the bibliographic data you're harvesting. Several citation manager formats are available, including EndNote and BibTex.

Type of Import

If you have citation management software installed on your computer your Web browser should be able to import metadata directly into your reference database.

Direct Import: When the Direct Import option is selected (the default state), a dialogue box will give you the option to Save or Open the downloaded citation data. Choosing Open will either launch your citation manager or give you a choice of applications with which to use the metadata. The Save option saves the file locally for later use.

Indirect Import: When the Indirect Import option is selected, the metadata is displayed and may be copied and pasted as needed.

About This Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Data & Comments

Data

Views
40
Downloads
26
Citations
0
Comments
0
1

Comments

Comments must be written in English. Spam, offensive content, impersonation, and private information will not be permitted. If any comment is reported and identified as inappropriate content by OAE staff, the comment will be removed without notice. If you have any queries or need any help, please contact us at [email protected].

0
Download PDF
Share This Article
Scan the QR code for reading!
See Updates
Contents
Figures
Related
Microbiome Research Reports
ISSN 2771-5965 (Online)

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/